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Discrimination of human and non-human sources of pollution in gulf of mexico waters by microbial source tracking methods...

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Title:
Discrimination of human and non-human sources of pollution in gulf of mexico waters by microbial source tracking methods and the investigation of the influence of environmental factors on _escherichia coli_ survival
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Book
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English
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Korajkic, Asja
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University of South Florida
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Tampa, Fla
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Subjects / Keywords:
Water Quality
Fecal Indicator Bacteria
Remediation
Sediment
Protozoa
Dissertations, Academic -- Biology-Integrative -- Masters -- USF   ( lcsh )
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non-fiction   ( marcgt )

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Abstract:
ABSTRACT: Water quality worldwide is assessed by enumeration of fecal indicator bacteria (FIB) (fecal coliforms, Escherichia coli, and enterococci) intended to act as surrogates for human enteric pathogens. In environmental waters, this predictive relationship is confounded by many possible sources of FIB with varying implications for human health. Many physico-chemical and biological factors influence the fate of enteric pathogens and FIB in aquatic habitats, but are poorly understood, thus limiting our understanding of the usefulness of FIB as fecal pollution indicators. These studies explored the field application of a "toolbox" approach to microbial source tracking (MST) intended to discriminate between human and non-human fecal pollution: a) in a Florida estuary used for shellfishing and recreational activities and b) at public beaches before and after remediation of wastewater infrastructure. Lastly, the effects of environmental factors (sediments, protozoa, sunlight) on survival of culturable E. coli were investigated in freshwater and seawater mesocosms simulating environmental conditions. Detection of a human- associated MST marker (the esp gene of Enterococcus faecium) at sites with suspected sewage contamination indicated that human fecal pollution is impacting water quality in Wakulla County, while Lagrangian drifters designed to follow current and tidal movement suggested that local hydrology plays an important role in bacterial transport and deposition pathways. Elevated FIB concentrations and frequent detection of human-associated MST markers (esp and human polyomaviruses) identified human sewage pollution at a public beach, facilitating remediation efforts (sewage main repair, removal of portable/abandoned restrooms), followed by significant decreases in FIB concentrations and MST marker detection. These studies show that comprehensive microbial water quality assessment can reliably identify contamination sources, thereby improving pollution mitigation and restoring recreational water quality. Protozoan predation, freshwater vs. seawater habitat and sediment vs. water column location affected the concentration of culturable E. coli in outdoor mesocosms. Sediments offered a refuge from predation where freshwater vs. seawater habitat was amore important determinant of survival. These findings provide important insight into the ecology of E. coli and their natural predators in aquatic habitats and underscore the inherent effect different habitats play in their survival.
Thesis:
Dissertation (PHD)--University of South Florida, 2010.
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Includes bibliographical references.
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by Asja Korajkic.
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Title from PDF of title page.
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Document formatted into pages; contains X pages.

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ABSTRACT: Water quality worldwide is assessed by enumeration of fecal indicator bacteria (FIB) (fecal coliforms, Escherichia coli, and enterococci) intended to act as surrogates for human enteric pathogens. In environmental waters, this predictive relationship is confounded by many possible sources of FIB with varying implications for human health. Many physico-chemical and biological factors influence the fate of enteric pathogens and FIB in aquatic habitats, but are poorly understood, thus limiting our understanding of the usefulness of FIB as fecal pollution indicators. These studies explored the field application of a "toolbox" approach to microbial source tracking (MST) intended to discriminate between human and non-human fecal pollution: a) in a Florida estuary used for shellfishing and recreational activities and b) at public beaches before and after remediation of wastewater infrastructure. Lastly, the effects of environmental factors (sediments, protozoa, sunlight) on survival of culturable E. coli were investigated in freshwater and seawater mesocosms simulating environmental conditions. Detection of a human- associated MST marker (the esp gene of Enterococcus faecium) at sites with suspected sewage contamination indicated that human fecal pollution is impacting water quality in Wakulla County, while Lagrangian drifters designed to follow current and tidal movement suggested that local hydrology plays an important role in bacterial transport and deposition pathways. Elevated FIB concentrations and frequent detection of human-associated MST markers (esp and human polyomaviruses) identified human sewage pollution at a public beach, facilitating remediation efforts (sewage main repair, removal of portable/abandoned restrooms), followed by significant decreases in FIB concentrations and MST marker detection. These studies show that comprehensive microbial water quality assessment can reliably identify contamination sources, thereby improving pollution mitigation and restoring recreational water quality. Protozoan predation, freshwater vs. seawater habitat and sediment vs. water column location affected the concentration of culturable E. coli in outdoor mesocosms. Sediments offered a refuge from predation where freshwater vs. seawater habitat was amore important determinant of survival. These findings provide important insight into the ecology of E. coli and their natural predators in aquatic habitats and underscore the inherent effect different habitats play in their survival.
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PAGE 1

Di scriminat io n of Human and Non Human Sources of Pollution in Gulf o f Mexico Waters by Microbial Source Tracking Methods and the Invest igat io n of the Influence of Envi ronmental Factors on Escherichia coli Survival by Asja Korajkic A d isse rtati on submitted in partial fulfillment of th e requirements for the degree of Doctor of Philosophy Departm ent of Integrative Bio lo gy College o f Arts and Sciences Universit y of South Florida Maj or Prof essor: Val erie J. Harwood, Ph. D. Cynthia Battie Ph.D Daniel V. Lim, Ph.D. John T. Lisle, Ph. D. Kathleen M. Scott, Ph.D. Date of approval : July 8, 2010 Keywords: Water Qualit y, Fecal In dicator B acteri a, R emediation, S ediment, P rotozoa Copy ri ght 2010, Asja Korajkic

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DEDICATION To my mo m wi th out y our uncondi ti onal lo ve and support, none of this would ever be possible. This dedicat io n is a sm all token of appreciat io n fo r every thing y ou di d, and cont inue to do. You will forever have my love and gratitude.

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ACKNOWLEDGEMENTS I would like to express a sincere thanks to Dr Valerie J. Harwood, my mentor and advisor for all o f t he guidance and invaluable advice she provided over the years. Thank yo u for believing in me and mo ld ing me into a scient ist I am today. I would also like to th ank my co m mittee members, Dr Cynthia Battie, Dr Daniel V. Lim, Dr John T. Lisle and Dr Kathleen M. Scott for the time, support and helpful suggesti ons they provi ded during the course of my graduate studies. Furthermore, I would like to acknowledge Dr Jonathan W ynn, for accepting to serve as a chair person in my dissertation defense. Speci al thanks is also due to my co workers, former and current members of the Harwood l ab (Mi ri am Bro wnell, Katrina Gordon, Stephaney Leskinen, Bina Nayak, Chr istopher Staley and Za chery Stal ey) for their friendship, support and help with so me parts of my research. Last, but not the least, I would lik e to acknowl edge my stepfather, Rafael Morales, fo r his unwavering support and my fur r y fr iends (Boss, Teo, Lou Lou and Bucky) for thei r uncondit io nal lo ve that provided much needed relief during so me o f th e challenging times.

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i TABLE OF CONTENTS LIST OF TABLES ................................ ................................ ................................ ......... iii LIST OF FIGURES ................................ ................................ ................................ ........ v ABSTRACT ................................ ................................ ................................ ................ vi i i CHAPTER ONE – BACKGROUND AND OVERVIEW OF RESEARCH .................... 1 Introduction ................................ ................................ ................................ ......... 1 Moni to ring ambient water qualit y ................................ ............................ 1 Development of current regulatory standards ................................ ........... 6 Envi ronmental fa ctors that affect FIB survival in water bodies ............... 10 Factors limit ing FIB survival in the environm ent ................................ ... 16 Im portance of microorganisms in the food web ................................ ...... 2 2 Microbi al Sourc e Tracking (MST) ................................ ......................... 23 Resear ch Goal s and Chapter Objectives ................................ ............................. 3 1 Si gnificance of research ................................ ................................ ..................... 3 4 References ................................ ................................ ................................ ......... 3 6 CHAPTER TWO: APPLICATION OF MICROBIAL SOURCE TRACKING METHODS IN A GULF OF MEXICO FIELD SETTING ................................ ..... 6 4 Abstract ................................ ................................ ................................ ............. 6 5 Introduction ................................ ................................ ................................ ....... 6 5 Materi als and M ethods ................................ ................................ ...................... 6 8 Sam ple co llect io n ................................ ................................ ................... 6 8 Enumeration of indicator organisms ................................ ....................... 6 9 Drifter experiment ................................ ................................ .................. 70 Library independent MST ................................ ................................ ...... 7 0 Sensit ivit y a nd specificit y of the esp assay ................................ ............. 7 1 Data analysis ................................ ................................ .......................... 72 Results ................................ ................................ ................................ .............. 7 3 In dicator organi sm concentrati ons ................................ .......................... 7 3 L ibrary independent MST ................................ ................................ ...... 7 4 Sensit ivit y a nd specificit y of the esp assay ................................ ............. 75 Drifters ................................ ................................ ................................ .. 7 5 Di scussi on ................................ ................................ ................................ ......... 8 4 References ................................ ................................ ................................ ......... 8 8

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ii CHAPTER THREE: INVESTIGATION OF HUM AN SEWAGE POLLUTION AND PATHOGEN ANALYSI S AT FLORIDA GULF CO AST BEACHES ........... 9 4 Abstract ................................ ................................ ................................ ............. 9 5 Introductio n ................................ ................................ ................................ ....... 9 5 Materi als and Methods ................................ ................................ ...................... 9 8 Sam pling strategy ................................ ................................ .................. 9 8 FIB concentrations ................................ ................................ ................. 9 9 Pathogen analysis ................................ ................................ ................... 99 Microbi al source tracking ................................ ................................ ..... 10 1 Data analysis ................................ ................................ ........................ 102 Results ................................ ................................ ................................ ............ 10 3 Fecal in dicator bacteria concentrations ................................ ................. 10 3 Microbi al source tracking ................................ ................................ ..... 10 5 Pathogen analysis ................................ ................................ ................. 10 6 Remedi ati on of wastewater infrastructur e ................................ ............ 10 6 Di scussi on ................................ ................................ ................................ ....... 11 3 References ................................ ................................ ................................ ....... 11 6 PROTOZOAN PREDATION IS A DOMINANT DETERM INANT OF ESCHERICHIA COLI PERS ISTENCE IN ENVIRONME NTAL WATERS .......... 12 2 Abstract ................................ ................................ ................................ ........... 12 2 Introduction ................................ ................................ ................................ ..... 12 3 Materi als and Methods ................................ ................................ .................... 126 Sam pling si tes and sample treatment ................................ .................... 126 Mesocosm prepara ti on ................................ ................................ ......... 12 7 E. coli st rains ................................ ................................ ....................... 128 E. coli enumerat io n ................................ ................................ .............. 12 9 Data analyses ................................ ................................ ....................... 130 Results ................................ ................................ ................................ ............ 13 1 Different ia l survival o f E. coli ................................ .............................. 13 1 Survival o f mixed E. coli population wit hout protozoa ......................... 132 Freshwater meso cosm s wi th and wi th out pro tozoa ............................... 133 Seawater mesocosms wit h and wi th out protozoa ................................ .. 134 Effect of protozoa ................................ ................................ ................ 135 Di scussi on ................................ ................................ ................................ ....... 149 References ................................ ................................ ................................ ....... 154 APPENDICES ................................ ................................ ................................ ............ 162 Appendix A: Wakulla Count y: FIB concentrations and MST marker distribut io ns by site ................................ ................................ ..................... 163 Appendix B: Hillsborou gh County FIB concentratio ns, MST marker distribut io n and pathogen detection by site ................................ ................. 169 Appendix C: E. coli concentrations in water (log 10 CFU/100 ml) and sediments (log 10 CFU/10 0 g) of freshwater and seawater me socosm s by strain ................................ ................................ ................................ ...... 179 ABOUT THE AUTHOR ................................ ................................ ..................... End page

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iii LIST OF TABLES Table 1. Post hoc one way analyses of variance (ANOVA) and Tukey’s results fo r F I B co ncentrations in the water column and sediments by site fo llo wing significant MANOVA ( p < 0.001) ................................ ................... 7 7 Table 2. Com parison of F I B concentrati ons between the water column and sediments by si te (two tail, paired t test) ................................ .......................... 7 8 Table 3. Si te by si te com parison of mean FIB concentrations in the water column fo r Phase I vs. Phase II sam p les (two tail, unpaired t test) .............................. 10 8 Table 4. Si te by si te com parison of mean FIB concentrations in the sediments for Phase I vs. Phase II samp les (two tail, unpaired t test) ................................ ... 10 9 Table 5. Com parison of MST markers and pathogen ( esp HPy V, and total culturable enteroviruses) frequency distribut io n in t he water column and sediments between Phase I pre remediat io n and Phase II post remediat io n rem ediat io n samples ................................ ........................... 1 1 0 Table 6. Experimental design: mesocosm characterist ic s, treatm ents, sam pling schedule and data analyses ................................ ................................ ............. 138 Table 7. Protozoa Absent: C om parison of E. coli lo g 10 red ucti on in freshwater and seawater mesocosms without protozoa ................................ ... 139 Table 8. Protozoa Present vs. Absent: C om parison of E. coli lo g 10 reducti on in freshwater an d seawater meso cosm s wi th and without protozoa ................. 140 Table 9. Fresh Water vs. Salt Water: Co mpar ison of E. coli lo g 10 reducti on values in mesocosms with and wit hout protozoa between freshwater and seawater mesocosms ................................ ................................ ............... 141 Table 10. Com parison of the ef fects of protozoa presence and freshwater vs. seawater habitats on E. coli lo g 10 reduction values in the water column (l og 10 CFU/100 ml) and sediments (log 10 CFU/100 g, wet weight) ............... 142

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iv Table 11. Com parison of the effects of protozoa presence an d matrix characterist ic s on E. coli lo g 10 reduction values in freshwater and seawater mesocosms ................................ ................................ .................... 143

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v LIST OF FIGURES Figure 1. Mean F I B concentrati ons (l og 10 transformed) in the water column sam ples by site (CFU/100 ml) ................................ ................................ ........ 7 9 Figure 2 Mean FIB concentrati ons (l og 10 transformed) in sediment samples by site (CFU/100 g wet weight) ................................ ................................ ..... 80 Figure 3. F I B co ncentrations (log 10 transformed) in oyster tissue (columns; CFU/g) vs. F I B concentrations in the overlying water column (lines; CFU/100 ml) ................................ ................................ ........................ 8 1 Figure 4. Frequency of detecti on of th e human associ ated esp gene in the water col umn and sediments at each site ................................ ................................ .. 8 2 Figure 5 Drifter tracks fro m Ju ne 6, 2007 overlaid with water collect io n points fo r esp assay ................................ ................................ ................................ ... 8 3 Figure 6A. Mean FIB concentrations (log 10 CFU/100 ml) in the water column sam ples by s it e ................................ ................................ .......................... 11 1 Figure 6B. Mean FIB concentrations (CFU/100 g of wet weight) in sediment sam ples by site ................................ ................................ ........................... 11 2 Figure 7. Protozoa Absent: Mean E. coli co ncentrations in the water co lu mn (l og 10 CFU/100 ml) and sediments (log 10 CFU/ 100 g, wet weight) over time in freshwater and seawater mesocosms ................................ ................. 144 Figure 8. Protozoa Present vs. Absent: Mean E. coli concentrations in the water col umn (l og 10 CFU/100 ml) and sediments (l og 10 CFU/ 100 g, wet weight) over time in freshwate r mesocosm s .............. 145 Figure 9. Protozoa Present vs. Absent: Mean E. coli concentrations in the water col umn (l og 10 CFU/100 ml) and sediments (l og 10 CFU/ 100 g, wet weight) over time in seawater me socosm s ................ 146

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vi Figure 10. Comparison o f t he effects of protozoa presence/absence and freshwater vs seawater habitat on E. coli lo g 10 reduction in (A) th e water column (log 10 CFU/100 ml) and (B) sediments (l og 10 CFU/100 g wet weight) of fr e shwater and seawater mesocosms ........ 147 Figure 11. Comparison o f t he effects of protozoa presence and matrix characterist ics on E. coli lo g 10 reduction in freshwater (A) and seawater (B) mesocosms ................................ ................................ ............. 148 Figure A1. Mean of indicator organism concentr at ions (l og 10 transform ed ) and esp marker detection in the water column sam ples of MS site by sampling date (CFU/100 ml) ................................ ... 163 Figure A2. Mean of indicator organism concentrations (log 10 transform ed) and esp marker detection in sediment sample s of MS site by sampling date (CFU/100 g wet wei ght) ................................ ................................ ............ 164 Figure A3. Mean of indicator organism concentrations (log 10 transform ed) and esp marker detection in the water column samples of BR sit e by sam pling date (CFU/100 ml) ................................ ................................ ...... 165 Figure A4. Mean of indicator organism concentrations (log 10 transform ed) and esp marker detection in sediment samples of BR site by sampling date (CFU/100 g wet weight) ................................ ................................ ............. 166 Figure A5. Mean of indicator organism concentrations (log 10 transform ed) and esp marker detection in the water column samples o f 319 sit e by sam pling date (CFU/100 ml) ................................ ................................ ...... 167 Figure A6. Mean of indicator organism concentrations (log 10 transform ed) and esp marker detection in sediment samples of 319 si te by sam pling date (CFU/100 g wet weight) ................................ ................................ ..... 168 Figure B1. Mean of indicator organism concentrations (log 10 transform ed), MST marker and pathogen detection in the water column samples of BH site by sampling date (CFU/100 ml) ................................ .................... 169 Figure B2. Mean of indicator organism concentrations (log 10 transform ed) and MST marker detection in sediment samples o f BH site by sampling date (CFU/100 g wet weight) ................................ ................................ ..... 170 Figure B3. Mean of indicator organism concentrations (log 10 transf orm ed), MST m arker and pathogen detection in the water column samples o f BTD 1 sit e by sampling date (CFU/100 ml) ................................ ........................... 171

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vii Figure B4. Mean of indicator organism concentrations (log 10 transform ed) and MST marker detection in sediment sampl es o f BTD 1 site by sam pling date (CFU/100 g wet weight) ................................ ...................... 172 Figure B5. Mean of indicator organism concentrations (log 10 transform ed), MST marker and pathogens detection in the water column samples of BTD 2 sit e by sampling date (CFU/ 100 ml) ................................ ............... 173 Figure B6. Mean of indicator organism concentrations (log 10 transform ed) and MST marker detection in sediment samples o f BTD 2 site by sam pling date (CFU/100 g wet weight) ................................ ...................... 174 Figure B7. Mean of indicator organism concentrations (l og 10 transform ed), MST marker and pathogen detection in the water column samples of BTD 3 sit e by sampling date (CFU/100 ml) ................................ ............... 175 Figure B8. Mean of indicator organism concentrations (log 10 transform ed) and MST marker detection in s ediment sam ples o f BTD 3 site by sam pling date (CFU/100 g wet weight) ................................ ...................... 176 Figure B9. Mean of indicator organism concentrations (log 10 transform ed) MST marker and pathogen detection in the water column samples o f BTD 4 sit e by sampling date (CFU/100 ml) ................................ ........................... 177 Figure B10. Mean of indicator organism concentrations (log 10 transform ed) and MST marker detection in sediment samples of BTD 4 si te by sam pling date (CFU/100 g wet weight) ................................ .................... 178 Figure C1: Mean concentrations (log 1 0 transformed) for HS strain .............................. 179 Figure C2: Mean concentrations (log 10 transformed) for SMS 35 strain ...................... 180 Figure C3. Mean concentrations (log 10 transform ed) f or WW6 strain .......................... 181 Figure C4: Mean concentrations (log 10 tr ansformed) for ATCC 8739 strain ................ 183 Figure C5: Mean concentrations (log 10 transformed) for MG 1655 strain .................... 183

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viii Di scriminat io n of Human and Non Human Sources of Pollution in Gulf o f Mexico Waters by Microbial Source Tracking Methods and the Invest igat io n of the Influence of Envi ronment al Factors on Escherichia coli Survival Asja Korajkic ABSTRACT W ater quali ty worl dwide is assessed by enumeration of fecal indicator bacteria (FIB) (fecal co lifo rm s, Escherichia coli and enterococci) intended to act as surrogates for human enteric path ogens. In environmental waters, t his predict ive relationship is confounded by many possible sources of FIB wi th varying implicat io ns fo r human health Many physico chemical and bio lo gical factors influence the fate of enteric pathogens and FIB in aquat ic h abi tats, but are poorly understood, thus limit ing our understanding of the usefulness of FIB as fecal po llution indicators. These studies explored the field application o f a “t oolbox” approach to microbial source tracking (MST) int ended to di scriminate be tween human and non human fecal pollut io n: a) in a Florida estuary used for shellfishi ng and recreational act ivit ies and b) at public beaches before and after remediat io n of wastewater infrastructure. Lastly, the effects of environmental factors (sediments protozoa, sunlight) on survival o f culturable E. coli were invest igated in freshwater and seawater mesocosms simulating environmental condit io ns.

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ix Detection of a human associ ated MST marker (the esp gene of Enterococcus faecium ) at sit es with suspected sewage contamination indicated that human fecal pollut io n is impact ing water qualit y in Wakulla Count y, while Lagrangian drifters designed to follow current and tidal mo vement suggested that local hydro lo gy pl ay s a n important rol e in bacterial tra nsport an d deposit io n pathway s. Elevated FIB concentrations and frequent detection of human associated MST markers ( esp and human polyo maviruses) ident ified human sewage po llut io n at a public beach, facilitat ing remediation efforts (sewage main repair, removal o f portabl e/abandoned restrooms), fo llo wed by significant decreases in FIB concentrations and MST marker detection. These studies show that comprehensive microbial water qualit y assessment can reliably ident ify contaminatio n sources th ereby improving pollut i on mit igat io n and restoring recreat io nal water qualit y. Protozoan predation, freshwater vs. seawater habit at and sediment vs. water col umn lo cati on affected the concentration of cul turable E. coli in outdoor m esocosm s. S ediments offered a refuge fro m pre dati on where freshwater vs seawater habitat was a mo re important determinant of survival. These findings provide important insight into th e ecology of E. coli and their natural predators in aquatic habitats and underscore the inherent effect different habi tats pl ay in their survival.

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1 CHAPTER ONE – BACKGROUND AND OVERVIEW OF RESEARCH Introduction Moni toring ambient water qualit y Hum an fecal po llut io n of environmental waters used for recreational purposes, shellfish harvest ing, or as a source of d ri nking water supply can pose a serious threat to public healt h. While risks from animal fecal po llutio n are not insignificant, as evidenced by incidences o f zoonoti c diseases (Craun, 2004; Graczyk et al. 1998; Leclerc et al. 2002; Pacha et al. 1988) the high degree of host associat io n of viral pathogens increases th e risk of illness fo llo wing exposure to waters contaminated with human s ewage (Haile et al. 1999; Wade et al. 2003) Testi ng environmental waters directly for the presence of all waterborne pathogens is currently unfeasible due to: a) broad phylogenet ic d iversit y (enco mpassing bacterial, viral and protozoan grou ps), b) overwhelming number of organi sms fro m each group, and c) the lack of appropriate, sensit ive and cost/time effect ive methodology (Field & Samadpour, 2007) Instead, fecal indicator bacteria ( FIB ) are used globally as surrogates for waterborne pathogens, and t heir concentrations are int ended to act as a gauge of microbial contaminat ion of recreati onal waters According to the early and ant iquated definit io n of FIB paradigm, indicator organisms shoul d have similar survival t ime and transport charac teristics in t he environment co mpared to th at of pathogens, and their only source would be human fecal po llut io n (Bonde, 1977) The fai lure of FIB to adhere to these characteristics can lead to “false negat ives” where FIB

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2 are absent but pathogens are present, and “false posit ives” where FIB are present but pathogens are absent. The former case scenario is a threat to public healt h, as it ma y allow human exposure to pathogens, while the latter causes econo mic hardships in coastal communit ies through potentially unnecessary beach and shellfish harvest ing area cl osures. A proposal for the revis io n o f th e FIB paradigm, reflecting amo ng other t hings th e fact that som e recreational waterborne infect io ns are not gastrointestinal and that many waterborne pathogens are actually zoonotic agents, was published recent ly (Boehm et al. 2009) Bri efly, it was suggested that improved FIB standard needs to: a) account fo r th e addit io nal source ty pes (urban run of f a nd animal feces) as opposed to only one (m unici pal wastewater) addressed in t he early versio n and b) take into considerat io n a mo re detailed categorizat io n of watersheds (temperate fresh, temperate marine, tropical fresh and tropical marine) in contrast to relatively narrow divisio n int o f reshwater and marine waters (Boehm et al. 2009) Proposed revisions to the FIB p aradigm also sti pulate th e necessit y fo r epi demi ol ogical studi es in the above ment io ned types of watersheds and during exposure to urban run off and anima l feces (Boehm et al. 2009) Coliform bacteria (comprised o f facultat ively anaerobic, gram negat ive, non spore fo rm ing, rod shaped, lactose fer ment ing organisms) have a long history o f e m pl oyment as indices of drinking water qualit y (Leclerc et al. 2001) Members o f t he total coliform group furthermore produce gas fro m lactose fermentation at 35C and include Escherichia Klebsiella Enterobacter and Citrobacter spp. (Am erican Pu blic Health Associ at io n, 1999; Orskov, 1981) Today total co liform analyses are predominant ly u sed fo r the assessment of drinking water qualit y a nd the integrit y o f dr inking water di stribut io n systems (Ameri can Public Healt h Associat io n, 1999)

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3 Current ly u sed FIB fo r recreational water qualit y assessment include the fecal coliform group, Escherichia coli and enterococci ( Enterococcus species) (American Public Healt h Associat io n, 1999; United States Environmental Protection Agency, 2002a; United States Environmental Protecti on Agency 2002b) Fecal coliforms are a thermo tol erant subgroup of the coliforms, growing well at 44.5 C (Amer ic an Public Healt h Associ at io n, 1999; Orskov, 1981) Fecal co liforms include most Escherichia coli strains and certain strains of Klebsiella spp., al th ough the latter (along with so me Citrobacter and Enterobacter spp.) have been associated with discharges fro m paper, pulp and textile mills (Gauthi er et al. 2000; Dufour & Cabelli, 1976; Caplenas et al. 1981) The abilit y of E. coli to hy drolyze 4 methylumbelliferyl D glucuronide (MUG) to yield a fluorogenic product is an important phenotypic trait used to different iat e it from Klebsiella spp. and other thermotolerant coliforms (Fen g & Hartman, 1982; Hajna & Perry 1943) Enterococci are G ram posi ti ve cocci arranged in pairs or chains that are catalase negat ive, strict ly fer me nt ativ e organisms capable of growth over wi de pH (4.5 10) and tem perature (10C 45C) ranges and elevated sal t concentrati ons (10% NaCl). Enterococci were formerly classified as Lancefield group D streptococci based on the serol ogy of cell wall ant igens, until genet ic analysis merited placing these organisms into a separate genus (Schleifer, 1984) Abilit y t o g row in 6.5% NaCl and hydro lysis o f esculin in the presence of bile are two important characterist ic s that are used to di st inguish Enterococcus spp. from Streptococc us spp. (Fack la m et al. 1974) As inadequacies of currently recognized FIB fo r predict ing th e presence of human enteri c pathogens have been recognized ( see further discussed below) al ternat ive

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4 indicators were proposed, including anaerobic, endospore fo rming Clostri dium perfringens and bacteriophages (Bisson & Cabelli, 1980; Gantze r et al. 1998; Payment & Franco, 1993; Fujioka & Shizumura, 1985) Resistance to environmental stress, prol onged survival t ime in th e environment compared to FIB and pathogens, and broad host di stributi on indicate that C. perf r ingens is at best a conserv at ive indicator of past sewage or recent con taminati on events (Davies et al. 1995; Desmarais et al. 2002; Horm an et al. 2004; Medema et al. 1997; Sorensen et al. 1989) Bacteriophages (i ncluding F specific RNA coliphage and Bacteroides fragilis HSP40 phage) have been shown to be better predictors of enteric virus survival in the environment than FIB (Chung & Sobsey, 1993; Havelaar & Pothogeboom, 1988; Sinton et al. 2002; Tartera et al. 1988) due to their structural similarit ies (e.g. comparable size, shape and geno mic configuration) (Havelaar & Pothogeboom, 1988) and host specificit y (Dutka et al. 1987; Leclerc et al. 2000; Tartera & Jofre, 1987; Tartera et al. 1989) Ho wever, limited di str ibut io n in sewage and co mp lex methodology have restricted widespread applicat io n of bacteri ophages as indices of human fecal po llut ion (Griffit h et al. 2003; Leclerc et al 2000; Scott et al. 2002; Noble et al. 2003a) Enteroviruses and Salmonella spp. are two commo n enteric pathogens, ident ified as a cause of numerous waterborne gastroent e ri ti s cases (Angul o et al. 1997; Centers for Di s ease Control and Prevent io n, 2004; Centers for Disease Control and Prevent io n, 2008; O'Reilly et al. 2007; Clark, 1996; Schuster et al. 2005; Amvrosieva et al. 2006) Both have been iso lat ed fro m t he water column o f ambient fresh and marine waters (Catal ao Di onisi o et al. 2000; Fuhrman et al. 2005; Gersberg et al. 2006; Gregory et al. 2006; Schets et al. 2008; Touron et al. 2007) and Salmonella spp. are frequent ly recovered

PAGE 17

5 fro m sediments (Crai g et al. 2003; Obiri Danso & J ones, 1999; Pommepuy et al. 1992; Fish & Pettibone, 1995) Studi es assessing the abilit y o f FIB to predi ct pathogen presence (i ncluding Salmonella spp. and enteroviruses) fo und a striking lack of predict ive rel at io nship (Crai g et al. 20 03; Obiri Danso & Jones, 1999; Pommepuy et al. 1992; Fish & Pettibone, 1995; Horman et al. 2004; Leclerc et al. 2001; McFeters et al. 1974; Fremaux et al. 2009; Lipp et al. 2001; Dorner et al. 2007; Goyal et al. 1979) While E. coli ma y no t b e a n ideal FIB, it is important to recognize the important rol e it serve s as a model organism, broadening our knowledge and understanding of genet ic s and evo lut io n in prokaryotes. It is not just an indicator of fecal po llut io n. Throughout the y ears, E. coli w as used to d emo nstrate horizontal gene trans fer by conj ugat io n (Lederberg, 1946a; Lederberg, 1946 b) in studies of phage genet ic s (Nom ura & Benzer, 1961; Benzer & Champe, 1961) and in the experiments on the gene topography which were instrumental in the understanding that genes are linear structures (Benzer, 1961) The pi oneering work of Richard Lenski on evo lut io n t hat invo lved tracking phenoty pic and genoty pic changes in 12 populat io ns of E. coli since 1988 (and is still ongoing) is importan t in understanding adaptation of organisms to a variet y o f environmental condit io ns (Ostrowski et al. 2008; Philippe et al. 2009; Bennett & Lenski, 2007; Sleight et al. 2008; Blount et al. 2008) Com parison o f 16S rRNA gene sequences showed that E. coli is 95.4 – 97.4 % and 99.6 – 99.9 % ident ic al to Salmonella and Shigella spp., respectively (F ukushima et al. 2002) Sequence analysis fro m ot her genes led to the proposal that Shigella spp. represent an E. coli lineage that diverged fairly recent ly due to the high degree of rel atedness between them (Pupo et al. 2000; Wang et al. 2001) These findings suggest

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6 th at the utilit y o f E. co li as a model organism can be extended to studies of Enterobacteriacaeae pathogen eco lo gy in aquat ic habitats parti cularly if a variet y o f E. coli strains are used to avoid over generalizat io n from one lineage o f t his rather diverse species Development of current regulatory standards The first documented record that ident ifies contaminated drinking water supply as a source for waterborne pathogens dates back to mid 19 th century London, when John Snow established that th e cho lera epidemic was spread by dr inking water polluted by human sewage (Snow, 1855) Shortly thereafter, Von Fritsch linked Klebsiella spp. to human sewage (Wo lf, 1972) and Theodor Escherich described his discovery o f Bacillus coli (now known as Escherichia coli ) in fecal microbial flora of infants (Escherich, 1855) Around the same time, the first treatment processes that attempted to impro ve d ri nking water safet y beg an, all prior treatments focused on improving palatabilit y o nly (Anonymous, 1910; Frankland, 1896; Santo Domingo, 2008) In 1914, U.S. Public Heal th Service (USPHS) recommended total co lifo rm s as the first standard for drinking water qualit y a nd safe ty which started the era of using co lifo rm bacteria as indicators of human fecal po llut io n (Leclerc et al. 2001) In subsequent decades, the recurrent iso lat io n of co lifo rm s (including E. coli ) and enterococci fro m var iety of sources (Harri s, 1932; Ostrolenk & Hunte r, 1946; Ostrolenk et al. 1947; Perry & Bayliss, 1936) and th ei r broad host distribut io n led to a discussio n of th e usefulness of these FIB as indicators of human fecal po llution (Elli ot, 1961; Perry & Bayliss, 1936; Wo lf, 1972) Different ratios of fecal co li fo rm s com pared to fecal streptococci (FC/FS ratio) iso lat ed from feces of humans and animals led to the proposal of using the FC/FS ratio as

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7 a tool to distinguish different sources of fecal po llution (Gel dreich & Kenner, 1969; Li tsky et al. 1955; Litsky et al. 1953; Varga & Anderson, 1968) Ratios of 4 .0 or hi gher were though t to be indicat ive of human fecal po llut io n, while ratios of 0.7 or lower si gnified that the pollut io n source was of animal origin (Geldreich, 1976) Num erical values were refined later to include mixed sources of po llut io n, represented by FC/FS rati os between 0.7 and 4 .0 (Geldreich, 1976) Additional research discredited FC/FS rati os as it was shown that the proposed ratios are not consis tent in human and animal feces (Pourcher et al. 1991; Devriese et al. 19 94; Howell et al. 1995) and th at different ia l survival o f FIB co mp licates its interpretation (Doran & Linn, 1979; Mara & Oragui 1981; McFeters et al. 1974; Anderson et al. 1997) None of the recommen dati ons descri bed thus far are part of th e federally mandated regulatory framework. The legislat ive acts in t he United States that recognized th e need for monitoring and improving water quality started with the passage of the Clean Water Act (CWA) by Congress in 1972. T he intentio n of the CWA was to regulate pollutant discharges to surface waters, with the broader scope of attempt ing to restore the nat io n’s waterway s to thei r designated use (e.g. fishing, primary body contact recreati onal use). In 1974, the Safe Drinking Water Act (SDWA) was passed wit h t he int ent to protect public healt h by regulating the natio n’s drinking water supply. Subsequent amendments to the CWA and SDWA (most notably in 1986 and 2000) recogni zed the importance of protecting the source waters used fo r drinking water supply (e.g. rivers, lakes, reservo ir s). In 1986, the United States Environmental Protection Agency (US EPA) published Ambient Water Qualit y Cr it eri a for Bacteria, which recommended testing for E. coli and

PAGE 20

8 enterococci, in freshwater an d estuarine/marine recreational waters, respectively (Uni ted States Environmental Protection Agency, 1986) Per this document, current fed erally regul ated limits for FIB in ambient waters are based on the acceptable r isk of eight gastrointestinal illnesses per 1000 swimmers fo llo wing exposure (United States Envi ronmental Protecti on Agency, 1986) In freshwater, regulatory limits expressed as geom etri c means (applicable only to sce narios where at least five samples are collected fro m a specified site per month) are 126 and 33 colony forming units (CFUs) per 100 ml of sample for E. coli and enterococci, respect ively (United States Environmental P rotecti on Agency, 1986) In cases where fewer samples are co llected, a one time sample maximum limit applies (235 575 CFU/100 ml for E. coli and 61 151 CFU/100 ml for enterococci) where th e limit is determined by the levels o f beach usage (United States Envi ronmental Protecti on Agency, 1986) In marine waters, only enterococci are recommended wit h t he acceptable geometric mean of 35 CFU/100 ml and one time sample maximum range of 104 501 CFU/100 ml (Uni ted States Environmental Protecti on Agency, 1986) Wade et al. provided a systematic review and meta analysis of published epidemio lo gical wi th th e aim o f quantifying the associat io n between FIB concentrations and GI illness, as we ll as the po tential for GI illness when FIB are bel ow regul atory limit s (Wade et al. 2003) Thei r findings support the use of current E. coli and enterococci guidelines for freshwater and marin e waters, respectively. The State of Fl ori da also monitors fecal co lifo rm concentrati ons in fresh and marine waters wi th limits set not to exce ed 400 CFU/100 ml in 10.0% of samples co llected fro m t he same si te, or a geometri c mean limit of 200 CFU/100 ml (Fl ori da Administrative Code, 1998) The National Shellfish Sanitat io n Program (NSSP) s pecifies acceptable levels of fecal

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9 coliforms in ambient waters used for shellfish harvesting as 14 and 43 CFU/100 ml, for geom etri c mean and one time sample maximum, respect ively (Nat io nal Shellfish Sanitat io n Program, 2003) Addit io na l r egulat io ns issued by US EPA (in 1985 and 1992) supplemented the CWA by adding Total Maximum Daily Load (TMDL) requirements. Essent ia lly, TMDL provi si on s requi re each state to develop a loading estimate for each monitored pollutant fo r every watershed that is failing to meet water qualit y st andards for its designated us e. The Beaches Environmental Assessment and Coastal Healt h (BEACH) Act of 2000 further am ended the Clean Water Act by establishing a nat io nal standard for monitoring and reporting FIB concentrations (pertaining to states with coastal recreat io nal waters an d Great Lakes region) and mandat ing state coordinated monitoring programs. Due to the nature of current testing methods that measure culturable FIB concentrations there is at least a one day del ay between co llect ing a sample and reporting th e results. In turn, thi s delays the posting o f warning s at si tes wi th fa iling water qualit y which would alert the public that water qualit y a nd safet y is compro mised. This di sconnect resulted in a lawsuit against US EPA brought by the Natural Resources Defense Council ( NRDC), the Nati onal Associat io n of Clean Water Agencies (NACWA), and the Los Angeles County Flood Control District. According to the terms of th e settlement reached between the US EPA and the plaint iffs in 2008, US EPA is responsible for conducting epidemi ol ogical studies in coastal recreational waters fo llo wed by development of new, more rapid methodology (based on those studies) and prom ul gating a revised rule by 2012 (NRDC v. Johnson, 2008) The new criteria would

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10 act to repl ace the e xist ing recommendat io ns from 1986 Ambient Water Qualit y Cr it eria fo r Bacteri a docum ent. E nvironmental factors th at affect FIB survival in water bodies The validit y o f use of FIB as surrogates for human enteric pathogens has been under debate for the bett er part of th e 20 th century and is st ill ongo ing (see “ Moni toring ambient water qualit y ” above) and was recent ly summarized in several publicat io ns (Ashbo lt 2001; Craig et al. 2003; Field & Samadpour, 2007; Lecl erc et al. 2001; Savichtcheva & Okabe, 2006) A ma jo r argum ent is th at th e current regulatory standards do not adequately protect human healt h due mainly to th e differences in survival and transp ort characteristics between FIB and pathogens, particularl y protozoa and viruses. For example, recorded waterborne outbreaks of gastroenterit is caused by Cryptosporidium spp. fo llo wing ingest io n of potable water that complied with regulatory gui delines (Casem ore, 1990; Meinha rdt et al. 1996; Goldstein et al. 1996; Mackenzie et al. 1994) emp hasize the inadequacy of FIB to consistent ly predict the presence of protozoan pathogens. A s imilar lack of correlation between FIB and enteric viruses was observed for the finished prod uct of drinking water treatment plants (Payment et al. 1985) final effluents of wastewater treatment pl ants (Ty rrell et al. 1995) and reclaimed water (Harwood et al. 2005) underlining th e deficiencies of FIB as surrogates for viral pathogens. Furtherm ore, t he beneficial role o f sediments and aquat ic vegetation as a refuge and a potential reservo ir as well as the differen ti al survival abilit y o f so me FIB subt yp es can affect their survival in the aquatic environments potentially contribut ing to di sconnect with the enteric pathogens

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11 Extended survival of FIB in t he environment due to attachment to particles was recogni zed decades ago (Allen et al. 1953; Bonde, 1967; Gerba & McLeod, 1976; Ri ttenberg et al. 1958; Savage, 1905; Van Donsel & Geldreich, 1971) Sediments and soils have been im plicated as a reservoir for FIB in a variet y o f c limates, including tem perate (By appanahalli et al. 2003a; Byappanahalli et al. 2006; Fazi et al. 2008; Ishii et al. 2007; Ishii et al. 2006a; Kinzelman et al. 2004; LaLiberte & Grimes, 1982; Obiri Danso & Jones, 1999; Tunnicliff & B ri ckler, 1984; Whit man et al. 2003) subtropical (Anderson et al. 2005; Buckley et al. 1998; Desmarais et al. 2002; Hartz et al. 2008; Sol o Gabriele et al. 2000) tropi cal (Byappanahalli & Fujioka, 20 04; Byappanahalli & Fujioka, 1998) and even Antarctica (Edwards et al., 2009). The trend for elevated FIB concentrations in sediments has been shown for different freshwater environments including streams (Buckley et al. 1998; Byappanahalli et al. 2003a; By appanahalli & Fujioka, 2004; Byappanahalli & Fujioka, 1998) rivers (Fazi et al. 2008; Obiri Danso & Jones, 1999; Savage, 1905; Tunnicliff & Brickler, 1984) and lakes (Byappanahalli et al. 2006; Doyle et al. 1992; Ishii et al. 2007; Ishii e t al. 2006a; Kinzelman et al. 2004; LaLiberte & Grimes, 1982; Pote et al. 2009) Retention o f FIB in sediments was also documented for estuarine, tidally influenced system s (Allen et al. 1953; Catalao Dionisio et al. 2000; Craig et al. 2004; Desmarais et al. 2002; Shiari s et al. 1987; Solo Gabriele et al. 2000) as well as marine beaches (Bonde, 1967; Bonilla et al. 2007; Davies et al. 1995; Ferguson et al. 2005; Gerba & McLeod, 1976; Lee et al. 2006; Rittenberg et al. 1958) In aquatic environments, organisms can exist either as free flo at ing pl anktoni c cells, or attached to particles. While the degree of the attachment is dependent on surface

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12 properties of organisms and particles, attachment has been observed for E. coli in a variet y o f e nvironments (Weiss, 1951; Pommepuy et al. 1992; Auer & Niehaus, 1993; Garci a Ar misen & Servais, 2009) A p osi tive correlat io n ( by linear regression) between th e settling rate of particle associated E coli and suspended matter concentration was noted i n instances where suspended matter content of th e water was below 50 mg/L ; conversely waters wi th higher suspended matter concentration (> 50 mg/L) fo llo wed a mo re constant sedimentation pattern (Garcia Ar misen & Servais, 2009) Attachment of FIB to parti c les and subsequent sedimentation play an important role, because it allows sediments to act as a reservoir fro m which FIB ca n be re suspended, ul ti mately result ing in increased FIB concentrations in the overlying water column. Resuspensio n of FIB fro m se diments into the water column in the shallow, int erst it ia l sur f zone has been studied, because this region is the most susceptible to shear fo rces, ti dal influences, and disturbances due to anthropogenic act ivit y. T idal patterns and wave act io n were found to be tw o f actors governing resuspensio n of E. coli and enterococci fro m marine beach sediments into the overlaying water column (Boehm & Weisber g, 2005; Bonilla et al. 2007; Desmarais et al. 2002) A similar situat io n was noted for freshwater lakes, where resuspension o f E. coli from sediments into the water col umn via wave act io n was the main factor impacting beach water qualit y at Lake Michi g an and Lake Superior (Kinzelman et al. 2004; Ishii et al. 2007) Estuarine and coastal waterway s fo llo w the same general trend, where high E. coli co ncentrations were observed in the river bank so ils, from which they were shown to be resuspended and washed into the water column during high tide and after storm events (Sol o Gabriele e t al. 2000)

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13 Studi es conducted i n me socosms that enumerated FIB from both freshwater and estuarine/saltwater environments re corded extended survival o f FIB over time in sediments co mpared to the water column (Anderson et al. 2005; Craig et al. 2004; Davies et al. 1995; Desmarais et al. 2002; Pote et al. 2009; Gerba & McLeod, 1976) . Cul turable FIB in sediments persisted fo r m ore than fo ur weeks in experiments incubated under artific ial condit io ns in laboratory studies (Crai g et al. 2004; Davies et al. 1995; Desmarais et al. 2002; Gerba & McLeod, 1976; Pote et al. 2009) as well as in mesocosms exposed to ambient condit io ns (Anderson et al. 2005) FIB concentrations in sediments tend to be 1 3 orders of magnitude higher than in the water column (Bonilla et al. 2007; Hood & Ness, 1982 ; Shiaris et al. 1987; Kinzelman et al. 2004; Solo Gabriele et al. 2000) and generally exhibit slower decay rates than organisms in the overlaying water column (Garcia Ar misen & Servais, 2009; Anderson et al. 2005) Despite the fact that consistently higher FIB concentrations are routinely r ecovered fro m sediments, monitoring sediments is not a part of the regulatory framework in any country and guidelines for FIB concentrations in sediments do not exist. The importance of sediments as reservo ir s fo r FIB and pathogens was illustrated in a rec ent epidemio lo gical study th at investigated the risk of illness fo llo wing exposure to sand at beaches across the U S (Heaney et al. 2009) A significant posit ive associat io n was found between exposure to sand and incidence of gastroenteritis and diarrhea; the same relat io nship was not observed for non gastrointestinal illnesses (Heaney et al. 2009; Bonilla et al. 2007) Hi gh FIB concentrations were also associated with the green macro alga Cladophora in freshwater areas where abundance of the se algal species leads to

PAGE 26

14 accumulat io n on the shorelines, which presents a beach management problem (By appanahalli et al. 2009; By appanahalli et al. 2003b; Byappanahalli et al. 2007; Heuvel et al. 2010; Ishii et al. 2006b; Whit man et al. 2003) Laboratory studies showed th at al gal leachate was capable of supporting in vitro mu lt ip licati on of E. coli (By appanahalli et al. 2003b) and that both E. coli and enterococci can survive on dried al gal mats for up to 6 months (Byappanahalli et al. 2003b; Whit ma n et al. 2003) In a freshwater habitat E. coli concentrations in water underlying the mat were significant ly higher compared to the surrounding water, and a significant p osi tive correl at io n was fo und between E. coli co ncentrations attached to Cladophora and in underlying water (Heuvel 2010). These results suggest that algae ca n act as sources fro m w hich FIB can enter surrounding waters, potentially having a negative impact on recreati onal water qualit y. Phylogenet ic relat io nships of E. coli and Salmonella spp. iso lat es fro m Cladophora were assessed by fluorophore enh anced rep PCR (HFERP) fingerprint ing (By appanahalli et al. 2009; By appanahalli et al. 2007) Genetic dist inctness of algal iso lat es as co mpared to other sources suggests that certain sub popul at io ns may be adapted to survival in these mats and as such can present a recurring source of FIB and pathogens to nearby beaches (Byappanahalli et al. 2009; Byappanahalli et al. 2007) Isol at io n of other bacte ri al pathogens fro m t he same mats, including Shiga toxin producing E. coli (STEC), Shigella spp., and Campylobacter in 25% 100% of samples analyzed confirms the abilit y o f Cladophora to harbor pathogenic organisms and dem onstrates that at least some aspec ts of th e FIB and pathogen behavior in the environment are similar (Ishii et al. 2006b)

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15 A me socosm study investigat ing changes in population structure of E. coli (determined by ribotyping) from varying sources (dog feces, sewage, and contaminated soil) over time in fresh and salt water found that some strains exhibited different ia l survival, as e videnced by prevalence of so me subtypes and disappearance of others in the later stages of the study (Anderson et al. 2005) A similar scenario was noted in soils, where a strain dependent response to soil co mpositio n (l oam or sandy so il supplemented wi th swine manure slurry) was observed. An increase in abundance o f so me E. coli strains (and decrease o f others) illustrated differential survival (strain dependent survival abilit y ) (Topp, 2003) According t o th e FIB paradigm, the human gastrointestinal (GI) tract i s a primary habitat for these organisms, while all other env ironments in which they are eventually deposi ted woul d be secondary habitats. Significantly lower strain diversit y in E. coli septic tank populat io ns (secondary habitat), compared to their primary habitat (human feces) was observed in a study invest igat ing th e genet ic structure of E. coli populat io ns fro m t wo different habitats (Gordon et al. 2002) Furthermore, iso lat es fro m secondary habitat grew better at lower temperatures compared to the human iso lat es, while the opposite was true for fecal iso lat es (Gordon et al. 2002) These results indicate that some E. coli st rains are better equipped than others for survival in secondary habitats (Gordon et al. 2002) Phenoty pic an d genoty pic distinctness of E. coli st rains responsible for fecal coliform blooms in two Australian lakes was observed, where all bloo m st rains shared a group 1 capsule type and the capsule encoding cps lo cus was genet ically dist inct from E. coli strains i so lat ed fro m vertebrates (Power et al. 2005) The physio lo gical and genet ic di st inctness of bloo m st rains indicates the potential for developing and/or acquiring trai ts

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16 th at have an adaptive advantage for E. coli in secondary habi tats, in thi s case a iding their survival and persistence in aquatic environments (Power et al. 2005) The abilit y o f so me FIB strains to survive in secondary habitats better than other s trains underlines the complex relat io nships that these organisms have with each oth er and wit h t heir environment. When c om bined with the wide distribut i on and lack of host specificit y, different ia l survival even further confounds th e al ready imperfect FIB paradi gm Factors limit ing FIB survival in the environment Several parameters ar e responsible for the decline of FIB concentrations in the environment, and can be broadly divided into biotic and abiotic factors. Physico chemical characterist ic s including salinit y, pH, di ssolved oxygen, temperature, turbidit y and sunlight irradiat io n a re am ong abi oti c factors that can have detrimental effect on FIB survival. Sunlight inact ivat io n has received a good deal of attention as an effective germicidal factor, since the concept was first proposed well over a century ago (Downes, 1877) After absorption of ultravio let (UV) light by nucleic acids was discovered (Gates, 1929) considerable research e ffo rts during the 1950’s were devoted to elucidation o f t he mechanisms of UV disinfect io n and inact ivat io n of microorganisms (Brandt & Gi ese, 1956; Dulbecc o, 1950; Kelner, 1950) UV light causes damage either di rect ly by inducing pyrimidine dimer format io n by UV B wavelengths (280 315 nm) (Jagger et al. 1967; Phillips et al. 1967) or indir ectly through creation of highly react ive oxygen species in a process termed photo oxi dat io n (Gong et al. 1988; Webb & Brown, 1979; Webb & Lorenz, 1970) UV disinfect io n was reported to be somewhat more effect i ve against viruses and protozoa than bacteria, mainly owing to the fact that repair

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17 mechanisms of two former groups are not as efficient (Knudson, 1985; Linden et al. 2001; Linden et al. 2002; Oguma et al. 2001; Rauth, 1965; Shin et al. 2001) In ambient waters, inact iv at io n of FIB th rough the germicidal effects of sunlight has been recorded numerous times (Ga meson & Saxon, 1967; Davies Co lley et al. 1994; Fujioka et al. 1981; Fujioka & Narikawa, 1982; Fujioka & Yoneyama, 2002; Sinton et al. 1994; Sinton et al. 1999; Solic, 1992) Sunlight inactivation o f FIB in aerated system s, such as waste stabilizat io n ponds (WSPs), was shown to increase as DO concentrations increased (Curti s et al. 1992; Davies Co lley et al. 1999; Davies Co lley et al. 2003; Craggs et al. 2004; Sinton et al. 2002; Davies Co lley et a l. 1997) The proposed mechanism for the observed synergist ic action between DO concentrations and sunlight inact ivat io n is mo st likely due to endogenous chemicals th at act as sensit izers when they absorb light ( e.g. porphyrin derivat ives flavins mena quino ne ) ( Curti s et al., 1992 Davis Coller et al., 1999, Davis Co lley et al., 1997 ). R eacti on s between exci ted sensit izer mo lecules and oxy gen leads to fo rm at io n of react ive oxygen species (singlet oxy gen, superoxide, hydrogen peroxide and hydroxyl radica ls) resul ti ng in photo oxi dat ive damage to the organism (Curtis et al., 1992, Davis Colle y et al., 1999 Davis Colley et al., 1997) Studi es co mpar ing sunlight ina ct ivat io n in fresh versus salt waters (Davies & Evison, 1991; Fujioka et al. 1981; Fujioka & Narikawa, 1 982; Fujioka & Yoneyama, 2002; Sinton et al. 1999; Sinton et al. 2002) in general found inact ivat io n to be si gnificant ly mo re pronounced in waters with higher salinit y irrespect ive of the organism tested. Measurements of UV absorbance in freshwater vers us marine waters showed the greater absorbance in the former, and it was attributed to higher concentrations of

PAGE 30

18 chemicals such as humic acids (Davies & Eviso n, 1991; Curtis et al. 1992) It i s int erest ing to note that an inverse relat io nship between fec al co lifo rm s (including E. coli ) and salinit y w as observed even in the absence of sunlight (Solic, 1992; Evison, 1988) al th ough th e mag nit ude of decline was not as high. In marine waters, sunlight inact ivat io n was reported to be considerably higher for fecal co lifo rm s than for enterococci (Davies Co lley et al. 1994; Sinton et al. 1994; Solic, 1992) While increased tem perature and pH have an inverse relat io nship wit h FIB survival when measured alone, exposure to sunlight was found to exacerbate this effect, result i ng in more rapid declin e of FIB (Curti s et al. 1992; Solic, 1992; Rijal & Fujioka, 2001) Water turbi di ty and depth are two factors that inversely affect sunlight inact ivat io n of microbes. Both factors are posit ively correlated with absorbance, which is th e difference between the amount of light energy (measured at a specific wavelength) th at enters a sample and the amount that passes through it (United States Environmental Protecti on Agency, 2006) Once absorbed, UV light loses its germicidal properties, thus non specific absorption (by substances other than the intended target) hinders the eff iciency of UV light disinfection. In environmental waters as well as mesocosm studies, th e depth (Davies Colle y et al. 2003; Davies Co lley et al. 2005; Fujioka et al. 1981) and turbidit y (Davies Co lley et al. 2005; Fujioka & Narikawa, 1982; Christensen & Linden, 2003) of th e irradiated water are inversely proportional to the effect iveness of sunlight disinfect io n. Interestingly the majorit y o f experiments examining the germicidal effect of UV irradi at io n fro m su nlight did not include sediments in the ex perimental desi gn (Curtis et al. 1992; Davies & Evison, 1991; Davies et al. 2009; Davies Co lley et al. 1994;

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19 Davies Co lley et al. 1999; Fujioka et al. 1981; Fujioka & Narikawa, 1982; Fujioka & Yoney ama, 2002; Si nt on et al. 1994; Sinton et al. 1999; Sinton et al. 2002; Craggs et al. 2004) The attachment of FIB to parti culate matter and the role of sediments as a refuge and potential reservo ir of FIB have been well established. While it is exceedingly difficu lt to mimic all of the environmental condit io ns in any experimental design, inclusio n of sediments provides more realist ic data on UV inact ivat io n of FIB in aquat ic habitats. While sunlight inactivat io n of FI B is a natural, highly cost effect ive process, i ts efficacy is great ly dependent on numerous environmental factors including chemical com posi ti on of the water (e.g. DO, turbidit y, humic acids) as well as site dependent characterist ic s (e.g. depth and canopy cover). Furthermore, incident sunlight irradia ti on is highly variable not only on the temporal scale, but on seasonal and geographic scales as well. Sunlight inact ivat io n is therefore variable and particularly site specific, and as such it does not play an equally important role in FIB inactivat io n in different sy stems. Grazing by bacterivorous protozoa, bacteriophage infect io n fo llo wed by virus mediated lysis, and predation by so me bacteria are among the biot ic effects that exert control over abundance of prokaryotic organisms in the environment. Pr edation by bacteri a has been well described for Vibrio spp., most notably Vibrio parahaemolyticus where infection by predatory Bdellovibrio spp. has been shown to play a role in popul at io n dynamics of these species (Sutton & Besant, 1994; Mitchell, 1971) Bac teri ophage infect io n affects a much wider range of bacteri a, including current ly u sed FIB Vi ral infect io n has been suggested as a mechanism responsible for the removal of up

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20 to 50% of autochthonous bacteria fro m aquatic habitats (Fuhrman & Noble, 1995; Proctor & Fuhrman, 1990; Thingstad, 2000) The removal o f bacteria in aquat ic environments due to the grazing activit y o f bacterivorous protozoa, which includes flagellated and ciliated organisms, has been extensively docum ented (Barcina et al. 1991b; Davies et al. 1995 ; Enzinger & Cooper, 1976; Gonzalez et al. 1992; Hartke et al. 2002; Iriberri et al. 1994a; Iriberri et al. 1994b; McCambridge & McMeekin, 1980a; McCambridge & McMeekin, 1980b; Menon et al. 1996; Menon et al. 2003; Mitchell, 1971; Rhodes & Kator, 199 0; Roper & Marshall, 1978; Servais et al. 2007; Sherr et al. 1988) Some accounts show protozoan grazing to be responsible for up to 90% of overall mortalit y of autochthonous organisms and allochthonous FIB from freshwater and marine environments alike (Menon et al. 2003; Anderson, 1986) Mesocosm and environmental chamber based experiments documented di sappearance of E. coli in mar ine (Sherr et al. 1988; Gonzalez et al. 1990a; Gonzalez et al. 1990b; Davies et al. 1995) estuarine (McCambridge & McMeekin, 1980b; Anderson et al. 1983; Enzinger & Cooper, 1976) and freshwater environments (Simek, 1996; Si mek, 2000; An et al. 2002; Menon et al. 1996; Gonzalez et al. 1990a; Surbeck et al. 2010; Davies et al. 1995) in t he presence of protozoan predators. Only two of these studi es included sediments in the experimental design; in general clearance of E. coli was si gnificant ly higher in the water column, suggest ing that sediments offer a refuge fro m predatory protozoa (An et al. 2002; Davies et al. 1995) The abundance of heterotrophic nanoflagellates (HNFs) in lakes, river and surface marine waters has been est imated at between 10 2 10 4 cells per ml (Boenigk & Arndt,

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21 2002) While small HNFs contribute ~30% of total plankton bio mass, they are extrem ely important bacterial grazers, capable o f consuming 75 80% of bacteria (Si mek et al. 1997) In coastal marine waters, Paraphysomonas imperforata com pri sed up to 98% of pl ankton (Lim et al. 1999) while Spumella spp. were dominant bacterivores in freshwater lakes ( Cleven & Weisse, 2001) Larger HNFs (e.g. Kathablepharis spp.) contributed significant ly mo re to total bio ma ss, but were insignificant as bacterial grazers (Cl even & Weisse, 2001) Sm all ciliated proti sts (e.g. Cyclidium Uronema and Halsteria genera) are al so consi dered to be important bacterial grazers, especially in highly productive environments (e.g. ponds and th roughout surface marine waters) (Nakano et al. 1998; Simek, 2000; Sherr & Sherr, 1987) For example, in eutrophic freshwater lake s th e digest io n rates of individual cells of Halster ia spp. were shown to be between 1580 and 3220 bacterial cells per one hour (Simek, 2000) ,. Prey characteristics such as cell wall morphology and size i nfluence the magnitude and efficiency of protozoan grazing (Gonzal ez et al. 1990b; Beardsley et al. 2003; Matz et al. 2002; Simek et al. 1994; Verit y, 1991) Red uced grazing rates on Gram posi tive organi sms ( Staphylococcus aureus, S. epidermidis and Ent. faecalis ) com pared to E. coli (Iriberri et al. 1994b; Iriberri et al. 1994a; Gonzalez et al. 1990a; Nilsson, 1987) w ere observed. Protozoa also preferent ia lly graze on larger cells (Menon et al. 1996; Menon et al. 2003; Fenchel, 1986; Gonzalez et al. 1990b; Iriberri et al. 1994a; Iriberri et al. 1994b; Simek et al. 1994; Anderson, 1986) and their affi nit y fo r E. coli is two times higher than for smaller, autochthonous microorganisms (Menon et al. 1996; Menon et al. 2003) Characteristics of predators such as physio lo gical state (Jurgens, 1995) life cycle stage (Fenchel, 1986; Boenigk, 2002) and size (e.g. larger

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22 protozoa show slower ingest io n rates) (Sherr et al. 1988) were shown to play a role in bacterivorous behavior. Predati on rates are dependent on temperature, as digestion rates increased exponent ia lly between 12C and 22C, for both flagellates and ciliates (She rr et al. 1988) A direct correlat io n between rates of predatio n and temperature was found in a variet y o f e nvironments, with mo re vigorous grazing and an increase in protozoan concentrations at higher temperatures (An et al. 2002; Anderson et al. 1983; Barcina et al. 1991a; McCambridge & McMeekin, 1980a; Sherr et al. 1988) Studies comparing t he effects of sunlight inact ivat io n and protozoan grazing on E. coli survival rates found th at combined exposure to both resulted in significant ly greater E. coli mo rtalit y t han ei th er factor alone (McCambridge & McMeekin, 1981; Rhodes & Kator, 1990) Im portance of microorganisms in the food web Early studies of marine eco lo gy di d not attribute a significant role to microorganisms in aquat ic fo od webs (Shelford, 1913; Lindeman, 1942; Paine, 1966; Summerhayes & Elton, 1923) ; th ose early opinio ns gradually changed as our knowledge and understanding of the importance of microorganisms in these systems evo lved (Azam & Ammerman, 1984; Pomero y, 1974) The key role of microbes in ocean productivit y was not suggested until the mid 70’s (Pom eroy 1974) Shortly af ter, th e term “microbial lo op” was coined to describe a pathway of disso lved organic carbon (DOC) cycling in aquati c environments that is dependent on microorganisms (A zam & Ammerman, 1984) Predatory protozoa and their bacterial prey are both essent ia l parts of microbial loop. A source of d ebate today is the mechanism of prokaryotic bio mass control in the aquati c environments. Some authors argue for a “bottom up” approach where prokaryotic

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23 abundance is controlled by nutrient availabilit y, while others propose a “top down” approach where prot oz oan grazing is the limit ing factor (Pace & Cole, 1994; Gaso l et al. 2002; Gaso l, 1994; Thingstad, 2000; Surbeck et al. 2010; Pernthaler, 2005) Field observat io ns and modeling studies in both freshwater and marine environments, suggested that “top down” con trol is mo re applicable in o ligotrophic systems, while com pet it io n fo r nutri ents or “bottom up” control is more important in eutrophic systems (Strom 2000; Pace & Co le, 1994; Thingstad, 2000; Gaso l, 1994; Gaso l et al. 2002) A recent California study showed that when DOC and phosphorus concentrations are below 7 and 0.07 m g/L, respect ively, E. coli and enterococci reduct io n rates are exponent ia l (Surbeck et al. 2010) ; above these thresh ol d concentrati ons, organi sms eit her grow exponent ia lly or display a steady state pattern, oscillat ing around some mean value (Surbeck et al. 2010) The enterococci data fro m the steady state pattern fit the Lotka Vol terra predator prey oscillat io n mo del where bacteri al growth is controlled by protozoa consumption (Surbeck et al. 2010) It is evident that the relat io nship between microbial communit ies and their environment in aquatic ecosystems is complex and dynamic. Generalizat io ns about the rol e t hat any one factor pl ays on influencing bacteri al survival must be made cautiously, since the interplay of various biotic and abiot ic factors is likely do be dependent on site specific characterist ic s. Microbi al S ource T racking (MST) Acco rding to the US EPA’s Nat io nal Summary o f I mpaired Waters, 39 998 water bodi es nat io nwide are listed as being impaired today, and “pathogens”(assessed as FIB ) are the most frequent cause of impairment (15.2%) (United States Environmental Protecti on Agency, 2008) The National Resources Defense Council reported the highest

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24 level of beach closures and advisories in 2008 since they starte d tracking recreational water qualit y 19 years ago (N at io nal Resource Defense Council, 2009) It is evident fro m th ese reports that ambient water qualit y in t he U S today suffers fro m microbial impairments and more importantly that sources of these microbes are not well characterized. H um an sewage poses a rel at ively high human healt h r isk compared to other ty pes of fecal contaminat io n (Wade et al. 2003) therefore identificat io n of pollut io n sources is important. Point sources of pollut io n (e.g. WWTP effluents, sewage spills) are recognized contributors to the problem, but contribut io n from non point sources (e.g. agricultural runo ff, stormwater runoff) is frequently underest imated and is considerably more challenging to manage and remediate. For example, in the beach water qualit y r eport issued by NRDC for year 2009, approximately 36% of beach closures were due to non point source contaminat io n (stormwater, surface runo ff), considerably more th an point sources (e.g. sewage spills 8%) (National Resource Defense Council, 2009) The effect of stormw ater run off and rainfall events on microbial water qualit y in receiving waters has been the subject of a great deal of recent research (Ahn et al. 2005; Brownell et al. 2007; Coulliette et al. 2009; Coulliette & Noble, 2008; Noble et al. 2004; Noble et al. 2003b; Shehane et al. 2005; Reeves et al. 2004) El evated FIB levels in coastal waters of southern California and Florida, as well as shellfish harvest ing areas in a North Carolina estuary have been shown to be influenced by stormwater run off fo llo wing periods of heavy rainfall events (Coulliette et al. 2009; Coulliette & Noble, 2008) While the impact of human sewage contaminat io n on public healt h r isks has been well documented (Cabelli et al. 1979; Cabelli et al. 1982; Fleisher et al. 1996; Fleisher et al. 1998; S ilva, 2010) th e effect of stormwater pollut io n on the risk of infection to

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25 recreati onal water users is difficult to estimate due in part to dispersal characteristics of storm water runoff and hydro lo gy of th e receiving waters (Ahn et al. 2005) Nonetheless, bacteri al, viral and protozoan pathogens have been detected in stormwater run off (Ahn et al. 2005; Selvakumar & Borst, 2006; Rajal et al. 2007; Arnone & Walling, 2006; Ahmed et al. 2008a) The impact of stormwater runo ff and rainfall events on water qualit y in receiving waters is exemplified by the pre em pt ive beach closures that som e states, including Florida, practice. P re empt ive clo sures due to heavy rainfall accounted fo r 22 % of beach closures in 2008, while 73% of all beaches mo nit ored nati onwide were cl osed in response to the observed exceedance of FIB regulatory standards (Nati onal Resource Defense Council, 2009) The abi lit y t o trace microorganisms fro m t heir ending point (e.g. water bodies or fo od polluted by fecal contaminat io n) to their point of origin would provide better understanding of the contamination source(s) and enable more precise and t imely rem ediat io n. Micr obial source tracking (MST) is a collect io n of methodologies that have been developed wit h t he aim o f d istinguishing contaminat io n ori ginat ing from various fecal sources in the contaminated watersheds. For the most part, MST methods target nonpathogenic or ganisms rather than pathogens, due to their prevalence in host popul at io ns (Harwood, 2007) Since MST methods evo lved largely in response to legislat ive act io ns, such as TMDLs and the BEACH act, the use of recognized FIB as targets in MST would be of value to water qualit y managers charged wit h ident ifying fecal pollut io n sources in watersheds; however, many MST methods target alternat ive organ is ms due to the lack of host specificit y o f fecal co lifo rm s, E. coli and enterococci.

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26 Depe nding on the techniques used, MST methods can be broadly divided into library dependent and library independent. Library dependent methods are generally culture base d and requi re ty ping of iso lat es (usually E. coli or en terococci ) fro m fec al sources. The patterns (or fingerprints) generated by FIB typing fro m known fecal sources are compared to those from ambient (water body ) samples. Based on the ty pe of fingerprint generated library dependent methods can be described as phenotypic (e.g. antibiot ic resistance analysis, carbon source utilizat io n profiles) (Wiggins et al. 1999; Hagedorn et al. 2003; Harwood et al. 2003) or genoty pic (e.g. BOX PCR riboty ping, pul se d field gel el ectrophoresis, randomly am plified polymorphic DNA am plified fragment length polymorphism ) (Parveen et al. 1999; Carson et al. 2003; Dombek et al. 2000; Aslam et al. 2003; Hahm et al. 2003; McLellan et al. 2001) While earlier MST studi es generally reported accurate cl assificat io n of bacteria i so lat ed from known fecal sources into correct library categories it was later determined that high correct classificat ion rates were likely a result of small library size, and not an accurate reflect io n of method performance (Harwood, 2007; Stoeckel & Harwood, 2007) Other limitations of library dependent m ethods were underlined as well (such as lack of applicabilit y a cross geographical and temporal scales, and th e presence of indist inguishable patterns in different source ca tegori es) (Griffit h et al. 2003; Harwood et al. 2003; Myoda et al. 2003; Field & Samadpour, 2007) and since th en, mainstream methodology has focused on library independent assays that target a host associated microorganism, most frequent ly via PCR. Alt hough so me library independent met hods target microorganisms associated wi th animal hosts (including gul l, avian, bovine, porcine and canine) (Kildare et al.

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27 2007; Lu et al. 2007; Shanks et al. 2008; Ufnar et al. 2007; Weid haas et al. 2010; Lamendella et al. 2008) ma ny have fo cused on ident ifying human associated targets (Ufnar et al. 2006; Bernhard & Field, 2000b; McQuai g et al. 2006; Scott et al. 2005; Shanks et al. 2007; Layton et al. 2006) Mo st of the library independent MST methods do not require a culture step, extending the range of MST targets to include anaerobic organi sms that are not readily culturab le (e.g. Cytophaga Flavobacter Bacteroides group) but are present in the fecal matter at considerably higher concentrations than FIB (Matsuki et al. 2 002) Wi th respect to the genet ic t arget of the assays, most focus on the small subunit rRNA due to th e presence of highly specific regio ns th at allow host species specific phylot ypes to be targeted (Bernhard & Field, 2000b; Layton et al. 2006; Matsuki et al. 2002; Lu et al. 2008) O th er gene targets were al so explo red including surface attachment proteins (Hamilton et al. 2006; Scott et al. 2005) methanogen specific genes ( nifH ) (Ufnar et al. 2007; Ufnar et al. 2006) as well as genes with unknown funct io ns th at were ident ified th rough a metageno mic approach (Lu et al. 2007) Two human associated MST markers utilized in studies described below (Chapters two and three) target th e enterococc al surface protein ( e sp ) of Ent. faecium (Scott et al. 2005) and a region of th e conserved t ant igen of human polyo maviruses (HPy Vs) (Bofill Mas et al. 2000) These particular markers were ident ified th rough clinical studi es investigat ing potential virulence mechanisms of Ent. faecium (Willems et al. 2001; Rice et al. 2003) a nd di seases o f th e urinary tract as well as mult ifocal leukoencephalopathy a comm on co mp licat io n in immuno com promised individuals (Arthur et al. 1989; Arthur & Shah, 1989) Th e fact that organi sms carrying these genes

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28 are excreted in human feces (Pourcher et al. 1991; Vanchiere et al. 2005a) and urine (Arthur et al. 1989; Vanchiere et al. 2005b) in th e case of HPyVs facilitated their use in M ST studi es. Both markers were used in the past to reliably detect human sewage (Griffit h et al. 2009; Harwood et al. 2009; McQuaig et al. 2006; Ahmed et al. 2008b; Ahmed et al. 2009; Betancourt & Fujioka, 2009; McQuaig et al. 2009) As is the case wit h all MS T m arker s, esp and HPyVs have certain advantages and di sadvantages A ma jo r benefit of the esp marker is the fact that it is carried by an Enterococcus sp p Ent. faecium is a representative of this regulatory approved FIB group th erefore its use in MST s implifies data interpretation in t he context of current regul atory guidelines One of the drawbacks of this method is the necessit y fo r a cultu re dependent enrichment step (Scott et al. 2005) th at prol ongs the time necessary to perform th e assay. A variant of th e esp gene is present in both Ent faecium and E nt faecalis ; however, the lat ter i s not a proposed human MST marker, as it is present in feces of several animal s pecies (Hammerum & Jensen, 2002; Shankar et al. 1999) Thi s fact has led to some confusio n in t he recent literature (Whit man et al. 2007; Byappanahalli et al. 2008) as detection of th e esp marker fro m Ent. faecalis was int erpreted to imply lack of specificit y in t he Ent. faecium esp gene. A h uman specific MST marker targeting HPyVs had no cross reactivit y w it h waste fro m other species (Harwood et al. 2009; McQuaig et al. 2006) The advantage of th e high level of host specificit y o f HPyVs over other human associ ated assays is that its presence is a very reliable marker of human sewage pollut io n (McQuaig et al. 2009; Harwood et al. 2009) One of th e disadvantages of this method is the lack of correlat io n wi th th e concentrations o f FIB (McQuaig et al. 2006)

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29 Recent development of MST markers and so me studies of recreational water qualit y have utilized the quant it ative PCR approach (Field & Samadpour, 2007; Stoeckel & Harwood, 2007; Vogel et al. 2007; Santo Domingo & Sadowsky, 2007; Shanks et al. 2010) which bypass es agarose gel electrophoresis and provi des a quant it ative, rather than presence/absence signal like end point (convent io nal ) PCR While quantitative PCR is not a novel method (Heid et al. 1996; Gibson e t al. 1996; Wittwer et al. 1997; Morrison et al. 1998) i ts use in water qualit y studi es was not widespread until recent ly. The main advantage s of quant it ative over convent io nal PCR is that th e fo rm er allows detection of am plicon accumulat io n as the re acti on progresses (e.g. in “real time”) and it enumerates an actual number of gene copies present in the sample There are two general detecti on strategies for quantitative PCR; a) th e Sybr Green m ethod measures th e change in fluorescen ce as the intercalat i ng dye binds non specifically to increasing numbers of DNA mo lecules (Wi ttwer et al. 1997; Morrison et al. 1998) and b) a probe such as TaqMan specifically binds to DNA sequences as the second strand is being synthesized. A fluor ophore attached to the probe is cleaved by DNA po lymerase act ivit y a nd fluoresces when it is dissociated fro m a quencher mo lecule (Gibson et al. 1996) The progression o f MST methodology, advantages and disadvantages of various methods have been extensively reviewed (Fiel d & Samadpour, 2007; Harwood, 2007; Santo Domingo & Sadowsky, 2007; Savichtcheva & Okabe, 2006; Scott et al. 2002; Si mpson et al. 2002; Stoeckel & Harwood, 2007; Yan & Sadowsky, 2007; Meays et al. 2004) Studies that tested th e performance of MST markers in th e field, found that detection limit s of assays targeting markers from th e same host species are variable and can differ by more than one order of magnitude (Harwood et al. 2009; Shanks et al.

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30 2010; Lu et al. 2007) Furthermore, distribution o f MST markers in target populat io ns is not uniform as evidenc ed by th e detecti on of chicken associ ated m arkers in other avian species (Lu et al. 2007) and a wide range of distribut io n of cow associ ated marker s across different bovine populations (Shanks et al. 2010) A t oolbox approach to MST using mult ip le markers in conjunct io n with FIB select pathogens and sanitary surveys of th e region was shown to reliably identify po llut io n sourc e(s) in the environment (Noble et al. 2006; Vogel et al. 2007; Savichtcheva et al. 2007; Noble et al. 2003a; Lee et al. 2008; Harwood et al. 2009) One of the largely unexplored aspects of MST pertains to the fate of various markers in the ambient waters. Several recent studies conducted in mesocosms assessed environmental factors affecting the persis tence of different Bacteroidales markers (Bae & Wuertz, 2009; Bell et al. 2009; Okabe & Shimazu, 2007; Walters & Field, 2009; Walters et al. 2009) In freshwater mesocosms protozoan grazing was recognized as a major fo rce b ehind the rapid decline of Bacteroidales markers (Bell et al. 2009; Dick et al. 2010; Okabe & Shimazu, 2007) Similar results were observed for saltwater mesocosms, where marker persistence increased with increased salinit y a nd decreased temp erature, presum ably because act ivit y o f protozoa is reduced under those condit io ns (Okabe & Shimazu, 2007) The effect of temperature alone on the persistence of Bacteroidales markers showed variable results, where so me researchers reported inverse relat io nship s (Bell et al. 2009; Okabe & Shimazu, 2007) while others did not find temperature to be a si gnificant factor (Di ck et al. 2010) Somewhat contradictory results were reported for th e influence of sunlight in saltwater where one study found th at it si gnificant ly decreased persistence of human Bacteroidales as com pared to th e con trol s incubated in

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31 th e dark (Walters et al. 2009) while another study reported no effect (Bae & Wuertz, 2009) In freshwater mesocosms, sunlight did not significantly affect persistence of two human Bacteroidales markers (Walters & Field, 2009; Dick et al. 2010) The observed variabilit y o f MST marker response to different biotic and abiot ic environme nt al param eters underlines the complexit y of eco lo gi cal interactions and emphasizes the need fo r a better understanding of factors affect ing marker persistence in different watersheds. Remediation o f impaired waters and facilitating return to their desig nated usage is th e ult imate goal of MST. At the same time, application of MST methods before and after rem edial efforts would be an appropriate test of their performance in a true field setting. While successful identificat io n of the source(s) has been ach ieved, remediat io n can be probl emat ic as it can often be costly and it requires continued commit ment and close collaboration between the scientific co mmunit y a nd many local/state agencies. Nonetheless, a few studi es published to date ut iliz ing MST techniqu es showed success of rem edial act io ns in improving water qualit y and reducing beach closures (Dickerson et al. 2007; Kinzelman, 2009; Hagedorn et al. 1999) The body of lit erature published to date shows that, while each MST method has its advantages and disadvantages, com prehensive, well planned microbial water qualit y st udies can identify contaminat io n sources reliably, leading to implementation of tangible act io ns to improve environmental water q ualit y a nd safet y. Research Goals and Chapter Objectives The main goals of my research were two fo ld ; (1) demonstrating the applicat io n of MST tools to discriminate between human and non human pollut io n source(s) in

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32 ambient waters and (2) determinat io n of th e effect of select ed environmental parameters on survival o f E. coli in freshwater and seawater habitats. My research work that focused on determinat io n of po llut io n sources com prised fi rst two chapters of my dissertati on. The first study (published in t he Journal of Applied Microbi ol ogy ) investigated pollut io n source(s) affecting recreational and shellfishing water qualit y in t he Wakulla Count y FL This area has a history of beach and shellfishing bed closures due to high FIB concentrations A c omb inat io n of cul ture dependent FIB enumerat io n by standard methods and MST testing id entified areas that were affected by human fecal po llut io n, while a hydrol ogical study of th e region determined the effect of flow patterns of FIB loading in the area. Th e second study (submitted for publication in the Journal of Applied Microbi ol ogy ) fo cused on comparing water qualit y at two Florida beaches in Hillsborough C ounty by FIB measurements and MST methods for detection of human pollut io n sources. In addit io n, th ese measurements were compared before and after rem ediat io n at one of the beaches that underwent remediat io n of the wastewater infrastructure. Evaluat io n of the effects of certain environmental parameters (freshwater vs sal twater habitat, presence of prot oz oa and sediment, exposure to sunlight, and variat io n in individual strains) on survival o f E. coli was the focus of the remainder of the research. More specifically, I met hodi cally examined the effects of individual variables, as well as combinat io n s of several variables on E. coli survival in mesocosm s th at simulated ambient condi ti ons.

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33 In a broader context, I hope to provide valuable information about using toolbox approach to microbial source tracking, as well as insight into the ecol ogy and fate of E. coli a globally used FIB, in the aquatic habitats. The description of the studies (including materials and methods utilized, results and discussio n of the original research) comprising my doctoral dissertation is outlined in Chapters Two through Four. In Chapter Two, I emp lo yed enumeration o f FIB MST techniques and a hydrological study of the region to identify po llut io n sources and FIB lo ading at coastal beaches of Wakulla Count y, Fl ori da. Specifically, my object ives were to: 1) Determine concentrations of FIB in t he water column, sediments and oy ster ti ssues at selected sampling sites 2) Em pl oy a human associated MST marker (enterococcal surface protein o f Enterococcus faecium esp ) at the same sites to determine whether observed FIB concentrations are re sul t of human versus non human fecal pollut io n 3) Examine flow patterns of Ochlo ckonee River through Langragian drifters to determine the role of local hydro lo gy and topography on bacterial transport and loading In Chapter Three, I examined FIB concentrations in the water column and sediments, presence of human associated MST markers, and selected human pathogens at tw o public beaches in Hillsborough County, before and after remedial act io ns were undertaken to improve beach water qualit y. The main object ives o f t he study were: 1) Assessment of recreational water qualit y a nd FIB sources before remediat io n

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34 2) Evaluat io n of the success of the remedial actions through FIB enumeration and human associ ated MST techniques ( esp and human polyo maviruses) 3) Determinat io n of pres ence/absence of human pathogens ( Salmonella spp. and enterovi ruses) The focus of Chapter Four was to determine the effect of certain environmental param eters on the survival o f E. coli in mesocosms that simulated environmental condi ti ons. The main goals in cluded: 1) Determining the effect of sediment presence on E. coli survival in freshwater and seawater habitats in t he mesocosms with and without protozoa 2) Evaluat ing effects of freshwater vs. seawater habit ats on E. coli survival 3) Determining the effect of pro tozoan predators on decline of E. coli in freshwater and estuarine habitats 4) Evaluat ing the combined effect of sediments, protozoan predators direct sunlight exposure and characteristics of freshwater vs. se a water habitat on E. coli survival Significance of research Through the research goals and object ives outlines above, I aim to advance our knowl edge about the field applicat io n of microbial source tracking methodology and to improve our understanding o f ecological relat io nships of fecal indicator bacter ia in t he environment. The intended applied benefit is to provide informat io n about the advantages of th e tool box approach ( simul taneous applicat io n of several different techniques) to pollut io n source tracking and detailed characterizatio ns of individual watersheds, in order to improve rehabilitat io n of recreational water qualit y i mpairments.

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35 Through my research I showed that a combination of FIB enumeration, MST methods, and regional hydro lo gi cal study can reliably inform regulatory agencies of FIB sourc es, improving risk assessment and pollut io n mit igat io n in impaired waters. As one of the first studies that emplo yed MST to conclusively ident ify po llut io n sources and report on the successful effects of remediat io n act io ns, I showed that a com prehensive m ic robial water qualit y st udy can ident ify contaminat io n sources through th e use of MST markers and th at clo se collaboration with local/and state agencies can resul t in tangible act io ns to improve recreational water qualit y and safet y. My invest igat io n of t he envi ronmental parameters governing E. coli survival in freshwater and seawater mesocosm s id entified protozoan predators as an important contributor to the decline of E. coli co ncentrations in t he water column, while freshwater vs. saltwater habitat was mo re important determina n t of persistence in sediments. I hope th at this research has provided an important insight into the intricate ecological rel at io nships o f ind icator bacteria and their secondary habitats.

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63 Webb, R.B. & Brown, M.S. (1979) Action Spect ra for Oxygen Dependent and Independent Inactivation of Escherichia coli Wp2s from 254 Nm to 460 Nm. Photochemistry and Photobiology 29 (2), 407 409. Webb, R.B. & Lorenz, J.R. (1970) Oxygen Dependence and Repair of Lethal Effects of near Ultravio let and Vis ible Light. Photochemistry and Photobiology 12 (4), 283 289. Weidhaas, J.L., Macbeth, T.W., Olsen, R.L., Sadowsky, M.J., Norat, D. & Harwood, V.J. (2010) Identificat io n of a Brevibacterium marker gene specific to poultry litter and development of a quant it a tive PCR assay. J Appl Microbiol 109 (1), 334 347. Weiss, C.M. (1951) Adsorption of E. coli on River and Estuarine Silts. Sewage and Industrial Wastes 23 (2), 227 237. Whitman, R.L., Przybyla Kelly, K., Shively, D.A. & Byappanahalli, M.N. (2007) Incidence of th e enterococcal surface protein (esp) gene in human and animal fecal sources. Environmental Science & Technology 41 (17), 6090 6095. Whitman, R.L., Shively, D.A., Pawlik, H., Nevers, M.B. & Byappanahalli, M.N. (2003) Occurrence of Escherichia coli and ent erococci in Cladophora ( Chlorophyta ) in nearshore water and beach sand of Lake Michigan. Appl Environ Microbiol 69 (8), 4714 4719. Wiggins, B.A., Andrews, R.W., Conway, R.A., Corr, C.L., Dobratz, E.J., Dougherty, D.P., Eppard, J.R., Knupp, S.R., Limjoco, M. C., Mettenburg, J.M., Rinehardt, J.M., Sonsino, J., Torrijos, R.L. & Zimmerman, M.E. (1999) Use of ant ibiot ic resistance analysis to ident ify nonpo int sources of fecal pollut io n. Appl Environ Microbiol 65 (8), 3483 3486. Willems, R.J.L., Homan, W., Top, J., van Santen Verheuvel, M., Tribe, D., Manzioros, X., Gaillard, C., Vandenbroucke Gr auls, C., Mascini, E.M., van Kr egten, E., van Embden, J.D.A. & Bonten, M.J.M. (2001) Variant esp gene as a marker of a dist inct genet ic lineage of vancomycin resistant Enter ococcus faecium spreading in hospitals. Lancet 357 (9259), 853 855. Wittwer, C.T., Herrmann, M.G., Moss, A.A. & Rasmussen, R.P. (1997) Continuous fluorescence monitoring of rapid cycle DNA amplificat io n. Biotechniques 22 (1), 130 &. Wolf, H.W. (1972) The Col iform Count as a Measure of Water Qualit y. In Water Pollution Microbiology pp. 333 345. Edited by R. Mitchell. New York: Wiley Intersci ence. Yan, T. & Sadowsky, M.J. (2007) Determining sources of fecal bacteria in waterways. Environmental Monitoring and Assessment 129 (1 3), 97 106.

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64 CHAPTER TWO: APPLICATION OF MICROBIAL SOURCE TRACKING METHODS IN A GULF OF MEXICO FIELD SETTING Asja Korajkic, Bri an D. Badgl ey Mi ri am J. Brownell, and Valerie J. Harwood* Departm ent of Bi ol ogy Universit y of South Flor ida 4202 East Fowler Avenue, SCA 110 Tam pa, FL 33620 *Author to whom correspondence should be addressed vharwood@mail.cas.usf.edu Running Tit le: Performance of source tracking methods (Publishe d in Journal o f Applied Microbio lo gy 2009, 107(5), 1518 1527)

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65 Abstract Microbi al water qualit y a nd possible human sources of fecal po llution were assessed in a Florida estuary that serves shellfishing and recreational act ivit ies. Fecal i ndicator organi sm s ( F I B ), including fecal coliforms, Escherichia coli and enterococci were quantified fro m mar ine and river waters, sediments, and oysters. Florida recreati onal water standards were infrequent ly exceeded ( 6% 1 0% of samples ); however, shellfishing standards were more frequently exceeded (28 %). FIB co ncentrations in oy sters and overlaying waters were significant ly c orrelated, but oy ster and sediment F I B concentrations were uncorrelated. The human associ ated e sp gene of Ent. faecium was detected in marine and fresh waters at si tes wi th suspected human sewage contaminat io n. Lagrangian drifters, used to determine the pathways of bacterial transport and deposit io n, suggested that sediment deposition fro m t he Ochlo ckonee River contributes to frequent detection of e sp at a Gulf o f Mexico beach. These data indicate that human fecal pollut io n is impact ing water qualit y in Wakulla Count y a nd that local topography and hydro lo gy pl ay a rol e in bacterial transport and deposit io n. A co mbinat io n of F I B enumerat io n, MST metho ds, and regional hydrological study can reliably inform regul atory agencies of F I B sources, improving risk assessment and pollution mit ig ati on in impaired waters. Introduction Fecal contaminat io n of surface waters used for recreation, shellfish harvest ing, or as a drinking water source can pose a serious threat to human health. Due to the cost constraints and impracticabilit y of testing directly for all enteric pathogens, bacterial F I B have been used for over a century as a surrogate for the assessment of e nvironmental

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66 water qualit y a nd safet y. Epi demi ol ogical studi es conducted over the past 30 y ears have supported the correlat io n between levels of certain indicator organisms and the risk o f gastroenterit is in recreat io nal water users (Cabelli et al. 1979; Cabelli et al. 1982; Fleisher, 1985; Fleisher et al. 1993) ; howe ver, various factors can confound this rel at io nship, including ubiquitousness and extended survival o f certain F I B in t he environment (Anderson et al. 2005; Byappanahalli et al. 2006; Da vies et al. 1995) Current ly, water column samples are collected to assess the qualit y o f recreational and shellfishing waters (United States Environmental Protection Agency, 1986; Florida Ad ministrative Code (FAC: 62 603), 1998) Sediments are generally not sampled, and no regul atory standards e xist for sediment F I B concentrati ons; however, prolonged survival of E. coli and enterococci in sediments and aquatic vegetation has been documented (Anderson et al. 2005; Whit man et al. 2003; Topp, 2003; Solo Gabriele et al. 2000) Furtherm ore, the potenti al for contaminat io n of the overlaying water column by re suspension o f sediment particles indicates the need for better assessment of contribut ing contaminat io n sources (Kinzelman et al. 2004; LaLiberte & Grimes, 1982) V arious sediments have been implicated as a reservo ir fo r F I B especially in tropical and subtropi cal systems, where concentrations could be artificially elevated due to the effects of th e climate and/or sediment characterist ics (Desmarais et al. 2002; Solo Gabriele et al. 2000; Brownell et al. 2007) Recent studies have indicated that certain E. coli strains are capable of long term survival and even growth in secondary habitats (e.g. environmental wat ers and soil) (Anderson et al. 2005; Power et al. 2005; Byappanahalli et al. 2006) Certain members of th e enterococci may also display different ia l survival, as suggested by the recurrent

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67 iso lat io n of a particular Ent. faecalis st rain fro m mar ine waters in California (Ferguson et al. 2005) In addit io n to thei r probl emat ic survival patterns in the environment, E. coli and Enterococcus spp. are normal inhabitants of the gastrointestinal tract of most warm blooded and so me cold blooded animals, and t herefore provide no informat io n about the source of fecal contaminat io n (Harwood et al. 1999) While animal fecal contamination cannot be considered an insignificant human health threat as evidenced by zoonotic waterborne disease outbreaks, the host specificit y of the viruses carried in human fecal materi al in crease the probabilit y o f illness fo llo wing exposure. Because of the threat that contaminat io n of environmental waters with human sewage poses, and the possibilit y o f eliminat ing such contaminat io n when the source is known th e abilit y t o discriminat e betw een human vs. non human contaminat io n source is important. Microbi al source tracking methods have been developed with the aim o f di st inguishing contaminat io n ori ginat ing from various fecal sources. Library independent microbial source tracking (MST) meth ods are a subset of fecal source tracking that generally focus on detection of a microbial target gene by PCR. The target should be specific to, or highly associated with, waste fro m particular host species (Hamilton et al. 2006; Scott et al. 2005; Bernhard & Field, 2000b; United States Environmental Protecti on Age ncy, 2005; McQuaig et al. 2006; Layton et al. 2006; Stoeckel & Harwood, 2007) A variet y o f library independent methods (Scott et al. 2005; Bernhard & Field, 2000b; McDonald et al. 2006; McQuaig et al. 2006; United States Envi ronmental Protecti on Agency, 2005) have been emplo yed with increasing frequency over the last decade to determine so urces of fecal indicator bacteria and other source sp ecific tracers of contaminat io n

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68 The fat e of fecal indicator bacteria in environmental waters is often affected by transport through the watershed due to river flows, tidal currents, or wind and wave dr iven advect io n. Examination o f sur face curren ts of th e water ci rculati on patterns has improved the abilit y t o determine the sources and healt h r isks associated with areas of high F I B concentrati ons and to develop predict ive models describing their fate (Gol dscheider et al. 2007; Grant, 2005; Boehm et al. 2005; Liu, 2006) One important tool to track surface transport, particularly in shallow coastal waters, is the use of La g rangian drifters. Drifters have been used successfully to determine surface currents and mixing (Castelao, 2008; MacFadyen, 2005) as well as transport of chemical contaminants and passive bio lo gical particle s such as larvae and bacteria (Gol d schei der et al. 2007; Fiechter, 2008; Hitchcock, 2008) The primary object ive of this study was to investigate the occurrence and source(s) of microbial indicators of fecal po llut io n in public beach recreat io nal waters and sands and other selected sites in Wakulla Count y whose waters are extensively used fo r both recreation and shellfishing The abilit y t o ident ify po llut io n source s quickly and efficient ly would allow for mo re rapid efficient remed iat io n of impacted waters and mo re precise risk assessme nt (United States Environmental Protection Agency, 2005) Materials and Methods Sam ple co llect io n Three sites in the Ochlock o nee River estuary which discharges int o th e Gulf o f Mexico in th e Fl ori da panhandle were samp led approximately every two weeks during tw o six month sampling peri ods ( January 25 through June 14, 2005 and January 8 th rough April 24, 2007) for a total of 18 sampling events Two estuarine sites, Mash’s

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69 Sands Beach (MS), and a boat ramp al ong a ti dal c reek (BR), were in close proximit y a nd had average salinit ies of 22.0 ‰, and17. 8 ‰ respectively One freshwater site was represented by the Ochl ockonee River at the Route 319 Bridge (319) wit h average salinit y of 0.6 ‰. Grab samples of water (1 L) and th e top layer of sediment (~25 g and ~3 cm depth) were collected in sterile containers, stored in a cooler on ice, and processed wi thin 8 h of collect io n. Water samples were collected at a depth of approximately 0.2 m. Depending on the depth of the sampling si te, sediment was collected either by hand or wi th a sampling pol e. During the first six mo nt h study period, oysters (minimum o f t hree per sampling event) were sampled from the support columns of the boat ramp at a depth where they were covered with water at lo w and high tide. Oysters were stored as above, and were processed within the same t ime frame. Enumeration of indicator organisms Water and sediment samples were processed by membrane filtrat io n (0.45 m m pore si ze, 47 mm diameter) fo r enumerat io n of fecal co lifo rm s, E. coli and enterococci. Sediment samples were first diluted 1:10 with sterile buffered water (0.0425 g L 1 KH 2 PO 4 and 0.4055 g L 1 MgCl 2 ; pH 7.2) and sonicated (Anderson et al. 2005) to rel ease bacteria attached to particles. F ecal coliforms were enumerated on mF C agar af ter 24 h incubat io n at 44.5 C (Am eri can Public Healt h Associat io n, 1999) ; enterococci were enumerated on mEI agar at 41C after 24 h incubat io n (United States Envi ronmental Protecti on Agency, 2002a) ; E coli was enumerated on mTEC media at 35 o C for 2 h, followed by 22 h incubation at 44.5 o C (United Sta tes Environmental Protecti on Agency, 2002b) Col onies on pl ates were counted and concentrations were reported as CFU/100 ml or CFU/100 g (wet wei ght) for water and sediment samples,

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70 respectively Oyster tissue was diluted 1:10 with sterile buffered water and homogenized. Hom ogenates (1 ml) were spread on 150 mm agar plates containing mFC agar for fecal coliforms or mE for enterococci, and incubated at 44.5C and 41C, respect ively. Fecal coliform co lo nies originat ing fro m mFC plates were further ident ifie d as E. coli by incubat io n in EC MUG broth (4 met hylumbelliferyl D gl ucuronide). At least 50% of MUG posi tive iso lates were subjected to confirmatio n of the E. coli ident ificat io n by the API 20E biochemical test system ( Bi oMeri eux Hazel wood, MO). Esculin hydro lysi s by maroon/brown colonies on mE agar (presum ptive enterococci) was confirmed by incubat io n in enterococcosel broth ( Becton Dickinson Franklin Lakes, NJ) for 24 h at 37 C. Bacterial counts were reported as CFU/g of ti ssue. Drifter experiment The last two sampling events conducted on May 9, 2007 and June 5, 2007 were coordinated with a concurrent hydrological study being conducted in Ochlockonee Bay. That study empl oy ed th e use of Lagrangian drifters to track surface currents and ci rculat io n within and nea r the mouth of the bay The drifters were designed wit h a lo w profile to minimize wind drag and allow transport into shallow waters. Drifters were rel eased at various points within the Ochlockonee River Bay and recovered after a period of approximately 6 0 75 min. The drifters logged GPS data regularly at five minute int ervals so that thei r path coul d be accurately plotted. W ater samples were collected at th e poi nt s of drifter rel ease and recovery for analysis of th e presence o f esp marker. Library inde pendent MST Minor modificat io ns o f a previously published procedure were used to detect the esp gene of Ent. faecium (Scott et al. 2005) Sediment and water at sites MS and 319

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71 were sampled on 18 dates for esp analysis, while BR site was sampled on 17 dates. Three hundred ml of water and 25 ml of sediment suspension (see above for preparation) were concentrated by me mbrane fi lt rat io n and incubated on mEI media at 41C for 48 h. Fil ters were transferred to 5.0 ml dextrose broth (Difco Laboratories, Detroit MI) in sterile, 15 ml conical screw cap tubes vortexed vigorously and incubated for 3 h at 41C wi th shak ing. Two ml o f az ide dextrose broth were transferred to a sterile centrifuge tube and centrifuged at 7,500 g for 10 min. DNA extraction was performed using the QIAamp DNA Stool Mini Kit according to manufacturer’s instructions ( Qiagen, Inc Val encia, CA). The primers and PCR condit io ns were previously published (Scott et al. 2005) PCR products (expected size 680 bp) were visualized by agar ose el ectrophoresi s (1.5% agarose gel). The positive control for the esp PCR assay, E nt faecium C68, was am plified by PCR for each sample event. Furthermore, it was shown that each of the PCR reacti ons were not inhibited in an environmental water and sedi ment by seeding aliquots of water and sediment samples wit h t he posit ive control Ent faecium C68 (approximately 100 cells) and subjecting the mixture to PCR. Results for water samples are presented as frequency of posi ti ve results, or the number of sample s testing posi ti ve for the esp gene divided by the total number of samples analyzed Sensit ivit y a nd specificit y of the esp assay Fecal samples from seagulls (n=39) and dogs (n=20) were sampled by collecting fecal material freshly deposited on the ground wit h sterile cotton swabs, which were stored in tubes containing 250 m l st erile buffered water All fecal samples were streaked on mEI agar and were incubated and transferred to azide dextrose broth as described above (Library independent MST). The remaind er of th e esp protocol (DNA extraction,

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72 PCR reactions and gel electrophoresis) was also performed as described above. S ewage samples (n=3) were collected int o sterile bottles fr om mu nicipal sewage influent fro m Wakulla Count y wastewater treatment plant, as well as Falkenburg Road (Hillsborough County Fl ori da) and Ol dsmar (Pinellas Count y, Flori da) wastewater treatment plants. All fecal and sewage samples were placed on ice and processed within 8 h. Seri al dilut io ns o f sewage in buffered water were prepared and samples were processed by membrane filtrat io n and incubated on mEI agar, as described earlier. The remainder of the protocol (DNA extraction, PCR reactions, and gel electrophoresis) was performed as described above. Data analysis All F I B concentrati o ns were log 10 transformed before data analysis. The mean F I B concentrations in both the water column and sediments by site were compared by MANOVA fo llo wed by one way ANOVA and Tukey’s posthoc test (SPSS version 16.0, Chicago Illino is). The relationship be tween F I B concentrati ons iso lat ed fro m t he water col umn and sediment of the same site (two tailed paired t test) was assessed using the GraphPad InStat software (Version 3.00, San Diego, California). The relat io nship between rainfall and FIB concentrati ons in t he water column and sediments, as well as rel at io nship between F I B iso lat ed from the oyster tissues and water column was assessed using linear (Pearson) correlat io n (two tailed P test) using the same so ft ware. Binary lo gist ic regressio n mo dels were us ed to assess the rela ti onship of bacterial indicator organi sms wi th th e presence of human associated marker (SPSS software ) The rel at io nships were considered significant in cases where the P value for model chi square was <0.05 and the confidence interval did not include one (1).

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73 Results Indicator organi sm concentrati ons The m aj ori ty of water samples met Florida regulatory limits for recreational water s, as 94% and 90% of sam ples were below th e limit s fo r fecal co lifo rm s (400 CFU/100 ml) and enterococci ( 104 CFU/100 ml) respect ively Regulatory limits for shelfishing waters (43 CFU/100 ml fecal co lifo rm s) were m et by 72% of water samples collected (none of which were co llected in locat io ns permitted for commercial shellfishing). Regulatory limits for feca l co liforms in recreat io nal waters were exceeded once at freshwater site 319 and twice at the estuarine site BR (Fig. 1). Enterococci limits were exceeded once at 319, once at MS (Gulf o f M exico) and three times at BR (Fig. 1). Shellfishing standards for f ecal co lifo rm s were exceeded twice at MS, seven t imes at BR and six times at 319 (Fig. 1). Fecal co liform concentrations in the water column were si gnificant ly higher at the freshwater site (319) compared to the marine beach site (MS) ( P <0.05) (Fig. 1, Tab le 1 ). No other significant differences in indicator organism concentrations by site were observed. A significant posit ive correlation was detected fo r cum ulat ive rainfall 24 hours pri or to sam pling and fecal co lifo rm concentrati ons in the water column at all sites (Pearson correlat io n: r = 0.287, P <0.05). A similar relat io nship was observed for E. coli concentrations in the water column and cumulat ive rainfall 24 hours prior to sampling (Pearson correlat io n: r= 0.303, P <0.05 ). Enterococci concentrations in t he sediments of site BR (estuarine) were si gnificant ly higher than those at site 319 ( P <0.001) (Table 1, Fig. 2). Sediments at the BR site harbored significant ly higher concentrations o f bo th E. coli and enterococci

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74 com pared to the MS site ( P <0.05 ) (Ta ble 1, Fig. 2). The comparison o f mea n F I B concentrations in the water column and sediments revealed that sediments harbored si gnificant ly (approximately one log) higher concentrations of all three organisms (Table 2). Concentrations of all three F I B in t he water column samples were highly correl ated wi th each other (Pearson correlat io n coefficient: r value 0.73 0.88 P <0.0001 ), wi th similar correl at io n values for sediments (Pearson correlation coefficient: r value 0.66 0.85 P <0.0001 ). Oy ster ti ssues wer e sampled at the BR site between March 8 and June 14, 2005. A significant correlat io n ( Pearson correlation coefficient: r value 0.76 0.83, P< 0.05 ) was found between concentrations of all three F I B in o yst er tissues com pared to samples fro m o verlying water s (Fi g. 3). In contrast, there was no correlat io n between F I B le vels in o yst er tissue vs. sediments (data not shown). (Addit io nal data included in Appendix A) Library independent MST A library independent MST assay targeting the human associ ated esp gene of Ent. faecium was performed on all water and sediment samples. The frequency of detection of th e marker ranged from 0.29 (BR) to 0.44 (MS and 319) in the water column and from 0.05 (BR and 319) to 0.17 (MS) in sediments (Fi gure 4). Binary logist ic regres si on mo dels were used to assess the relat io nship of bacterial indicator organisms with the presence of the esp marker. A weak but significant correlat io n was found between fecal coliforms (Nagelkerke R 2 = 0.09; odds ratio 2.37; c 2 0.03 ) and esp gene detection in the water column. A similar relat io nshi p was observed between E. coli co ncentration and esp gene detection in the water column (Nagelkerke R 2 = 0.11; odds ratio 2.54, c 2 0.0 2)

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75 Furtherm ore, a weak negative correlat io n was detected between fecal coliforms and esp gene detection in sediments (Nagelkerke R 2 = 0.19; odds ratio 0.21, c 2 0.0 2) (Addit io nal data included in Appendix A) Sensit ivit y a nd specificit y of the esp assay In order to assess the specificit y o f t he esp mar ker, the assay was performed on fecal material fro m t wo non ta rget groups of organisms, seagulls (n=39) and dogs (n=20). The cho ic e of animals was governed by: 1) similarit y o f t he gastrointestinal bacterial fl ora of dogs and humans, and 2) potential impac ts of th e resi dent seagull popul at io n observed at the Mashes Sands Beach and other sites in the Wakulla Count y. While a large percentage from both groups contained detectable levels o f culturable enterococci in their feces (54% and 100% for seagulls and do gs, respectively), the cross reactivit y o f t he esp marker was fairly low (14.3% or n=3 for seagulls; 5% or n=1 for dogs). Serial dilutions of primary influent from three municipal wastewater treatment plants were tested in order to assess the sensit ivit y o f t he assay. The three wastewater treatment plants (WWTP) sampled were: Falkenburg Road WWTP (Hillsborough County, FL), Oldsmar WWTP (Pinellas Count y) and Wakulla WWTP (Wakulla County, FL). The detection limit of the assay was 10 l of sewage per 300 ml water (a 30,000 fo ld dilut io n). The corresponding ranges o f IO counts iso lat ed fro m 10 l of raw sewage from three WWTP were as fo llo ws: 1) fecal co liforms 145 535 CFU; 2) E. coli 148 487 CFU; 3) enterococci 77 372 CFU. Drifters Nineteen drifters were released and tracked (three fro m May and 16 from June). Sam pling in May was conducted in the Ochlockonee River. Five water samples were

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76 collected concurrent ly fo r esp analysis, one at the commo n release point for the drifters, and t he remainder along the drifter paths. The sample co llected at the drifter release point tested posit ive for the esp marker, and two of the remaining samples (50%) also tested posi ti ve for the esp marker. During the June sampling, drifters were released in two groups (ei ght drifters each) in the mouth of the Ochlockonee Bay. Sixteen water samples were collected (two where the drifter groups were released and 14 where the drifters were recovered ) One of the samples co llected at the drifter release points was posi ti ve for the esp marker (50%). Seven samples (50%) obtained at the drifter collect io n points tested posi ti ve for the marker. In general, drifters were tidally driven, fo llo wing the depth contours of Ochlockonee Bay Upon exit ing th e bay, the path went over the sand shoals at the south end of Mashes Sands Beach and in a general eastward direction Only drifter paths from June sampling are shown, since they were more relevant to the study area (Fi g. 5).

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77 Table 1. Pos t ho c one way analyses of variance (AN OVA) and Tukey’s results for F I B concentrations in the water column and sediments by site fo llo wing significant MANOVA ( p < 0.001). Only co mpar isons where a significant difference was dem onstrated are shown. Means and standard deviations are presented as lo g 10 CFU per 100 ml water or 100 g sediment. Site abbreviat io ns: MS Mashes Sands Beach; BR Boat Ram p; 319 Bri dge over Ochlockonee River. Organism Matrix Com parison Mean and SD P value Enterococci Sediment MS vs BR 1.98 + / 0.63 vs 2.78 + / 0.58 <0.05 Enterococci Sediment BR vs 319 2.78 + / 0.58 vs 1.36 + / 1.01 <0.001 Fecal coliforms Water MS vs 319 1.05 + / 0.41 vs 1.55 + / 0.57 <0.05 E. coli Sediment MS vs BR 1.63 + / 0.86 vs 2.47 + / 0.91 <0.05

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78 Table 2. Com parison of F I B concentrations betwee n t he water column and sediments by si te (two tail, paired t test). Only co mpar isons where a significant differen ce was dem onstrated are shown. Means and standard deviations are presented as log 10 CFU per 100 ml water or 100 g sediment. Site abbreviat io ns : MS Mashes Sands Beach; BR Boat Ram p; 319 Bri dge over Ochlockonee River. Si te Organism Two tailed P value Water mean (log 10 ) Sediment mean (l og 10 ) Fecal coliforms <0.0001 1.03 + / 0.41 1.85 + / 0.61 E. coli 0.0001 1.03 + / 0.43 1.82 + / 0.59 MS E nt erococci 0.0004 0.98 + / 0.50 1.96 + / 0.62 Fecal coliforms 0.0078 1.47 + / 0.76 2.46 + / 0.90 E. coli 0.0073 1.42 + / 0.81 2.47 + / 0.94 BR Enterococci <0.0001 1.33 + / 0.63 2.79 + / 0.57 319 E. coli 0.0112 1.26 + / 0.80 2.00 + / 0.86

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79 0 0.5 1 1.5 2 2.5 3 3.5 4 MS (n=17) BR (n=16) 319 (n= 17) Sites log 10 CFU/100 ml Figure 1. Mean F I B concentrati ons (l og 10 transformed) in the water column samples by si te (CFU/100 ml) Error bars represent standard deviat io ns. Site abbreviat io ns (x axis): MS Mashes Sands Beach, BR Boat ramp, 319 Bridge over Ochlockonee River n= number of samples analyzed. F I B concentrati ons (y axis) are represented as lo g 10 transformed CFU/100 ml. Fecal co liforms concentrations are represented by striped bars ( ); E. coli concentrations are represented by dotted bars ( ); enterococci concentrations are represented by bars wit h diagonal lines ( ). Verti cal lines with crosses ( x ) represent fecal co lifo rm s regulatory guidelines for recreational waters (400 CFU / 100 ml) ; vertical lines wit h filled squares ( ) represent enterococci regulatory gui delines for enterococci (104 CFU/ 100 ml) ; vert ical lines wit h filled ci rcles ( •) represent s hellfishing regulat io ns for fecal co lifo rm s (43 CFU / 100 ml fo r a grab sample)

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80 0 0. 5 1 1. 5 2 2. 5 3 3. 5 4 MS (n=16) BR (n= 16) 319 (n= 17) Sites log 10 CFU/100 g Figure 2. Me an FIB concentrati ons (l og 10 transformed) in sediment sam ples by site (CFU/100 g wet weight). Error bars represent standard deviations. Site abbreviat io ns ( x axis): MS Mashes Sands Beach, BR Boat ramp, 319 Bridge over Ochlockonee River n= number of samples analyzed. IO concentrations (y axis) are represented as log 10 transformed CFU/g wet weight). Fecal co lifo rm s concentrati ons are represented by stri ped bars ( ); E. coli co ncentrations are represented by dotted bars ( ); enterococci concentratio ns are represented by bars wit h diagonal lines ( ).

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81 -0.50 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 030805 032205 040505 042605 050305 051705 061405 Sampling D at es log 10 CFU/g log 10 CFU/100ml Figure 3. F I B concentrations (log 10 transformed) in oyster tissue (columns; CFU/g) vs. F I B concentrations in the overlying water column (lines; CFU/100 ml). Dates of oyster sampling are on the x axis Error bars represent standard deviations. F I B concentrations in o ysters (y axis) are shown as log 10 transformed CFU/g o yst er tissue. F I B concentrations (z axis) are shown as log 10 transformed CFU/100 ml. The vert ical line wi th crosses ( x ) represents feca l co lifo rm concentrati on in the water column; vert ical line wi th filled squares ( ) represents E. coli co ncentrations in the water column; vertical line wi th em pt y c ircles ( ) represents enterococci concentrations in the water column. Bars wi th di agonal cr ossing lines ( ) represent fecal co liform concentrations in the oyster ti ssue; checkered bars ( ) represent E. coli co ncentrations in the o yst er tissues; bars with hori zontal lines ( ) represent enterococci concentratio ns in the o yst er tissue.

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82 0 0. 1 0. 2 0. 3 0. 4 0. 5 0. 6 0. 7 0. 8 0. 9 1 MS BR 319 Sites Figure 4. Frequency of detecti on of th e human associ ated esp gene in the water column and sediments at each site. Site abbreviat io ns (x axis): MS Mashes Sands Beach, BR Boat ram p, 319 Bridge over Ochlockonee River. Frequency detection (0 to 1) of esp marker is r epresented on y axis. Frequency distribution was calculated as a number of posi ti ve esp marker samples over a total number of samples at a particular site on which th e esp assay was performed. Gray column ( ) represents frequency detection of esp marker in th e water column; black co lu mn ( ) wi th white dots represents frequency o f esp marker detection in sediments.

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83 Figure 5. Drifter tracks fro m Ju ne 6, 2007 overlaid with water collect io n points for esp assay. The second group of drifters that were deployed in the Ochlockonee Bay on June 6, 2007. Deplo yment and collect io n sites are marke d wi th green and blue filled dots, respectively Drifter traj ectori es are represented by white lines. Dots indicate 5 minute int erpolated posi ti on. The red dots wi th black border are the locations where water samples were collected for the esp assay.

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84 Discussion Despite the accumulat ing evidence that F I B are not ideal indicators of human fecal pollut io n and pathogen presence, they are still recognized as federal an d state standards for the evaluat io n of the microbial aspects of environmental water qualit y a nd safet y (Fl ori da Administrative Co de (FAC: 62 603), 1998; National Shellfish Sanitat io n Program 2003; United States Environmental Protection Agency, 1986) Coastal waters of Wakulla Count y ha ve experienced sporadi c exceedances o f recreati onal and shellfishing water qualit y standards for F I B th at are not explained by releases from po int sources such as sewage infrastructure. These exceedances have attracted public and regul atory attenti on, and threaten the designated uses of this estuary. Previous studies have determined that stormwater ru noff ma y i mpact the qualit y of receiving environmental waters, due to the deposit io n of relatively high concentrations of IOs retained in the stormwater conveyance systems (Brownell et al. 2007; Marino, 1991; Shehane et al. 2005) The significant correlation between rainfall 24 hours prior to sampling and F I B concentrati ons in the water column suggests that water qualit y in t he watershed is adversely affected by stormwater. F I B concentrations in sediments were signi ficant ly higher (greater than 1 log) th an in the water column Previ ous MST studi es did not seek to determine the contribution o f sediments to elevated F I B concentrations in environmental waters (Wiggins, 1996; Wiggins et al. 1999; Wh it lo ck et al. 2002; Parveen et al. 1999; Harwood et al. 2000; Hamilton et al. 2006; Hagedorn et al. 2003; Graves et al. 2007) rather, th ey fo cused on human and animal waste pollut io n sources Recent studi es however, have acknowledged th e importanc e of s ediments and/or stormwater as

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85 reservo ir s fo r F I B (Brownell et al. 2007; Choi et al. 2003; Moore et al. 2006; Bonilla et al. 2007; Anderson et al. 2005; Ferguson et al. 2005) The relat io nship between F I B concentrations in water and sediments vs. F I B concentrations in oyster tissue was determined in oysters that were native to the sampling si te (not rel ocated), in estuarine waters that did not meet the fecal coliform guidelines for shellfishing waters se t by th e Nati onal Sh ellfish Sanitat io n Program (Na ti onal Sh ellfish Sanitat io n Program, 2003) The in situ correlat io n between the F I B le vels in the o yst er ti ssue and F I B le vels in the water column describes a dynamic relat io nship wit h fluctuati ons of bacterial levels over time. Conversely, sediment F I B c oncentrations were not correlated with F I B concentrati ons in o yst er tissue, reflect ing the oyster’s filt er feeding lifest yle. Other studies that explored the relat io nship of microbial concentrations in water vs. oysters emplo yed relocated or depurated anim als, and found that the oysters tended to accumulate microorganisms fro m t he surrounding water (Daskin et al. 2008; Shieh et al. 2003; Burkhardt & Calci, 2000) According to recent estimates, approximately 13% of the nat io n’s surface waters do not meet regulatory criteria for recreational waters in t erms of fecal indicator bacteria (United States Environmental Protection Agency, 2005) Point sources of pollut io n (e.g. WWTP effluents, sewage spills) are recognized contributors to the problem, but contribution fro m non point sources (e.g. agricultural runo ff, stormwater runoff) is frequently underest imated and is considerably more challenging to manage and rem ediate. Microbial source tracking tools have been developed within the last decade for th e purpose of determ ining pollut io n sources and dist inguishing between human and non human fecal po llut io n (Ahmed et al. 2008c; Ahmed et al. 2008e; Ahmed et al. 2008d;

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86 Bernhard & Field, 2000a; Dickerson et al. 2007; Graves et al. 2 007; Griffit h et al. 2003; Layton et al. 2006; McQuaig et al. 2006; Scott et al. 2005; Stoeckel & Harwood, 2007; United States Environmental Protection Agency, 2005) Even though regulatory standards for fecal co liforms and enterococci were infrequen tly exceeded, human associ ated MST m arkers were detected regularly in the area of study. Possible sources of human sewage contaminat io n, result ing in the detection of human associ ated m arker were identified in t his study Both MS and BR sites have bathroom s in close proximit y t o the water that were serviced by sept ic t anks and converted to a sewer system in late 2004 Due to the structural damage o f t he restroom at si te MS sustained during the storm surge in the hurricane season of 2005, it was replaced by the portabl e restrooms placed relat ively clo se to the waters edge (~10 15 meters). In a previous study conducted in the Tampa Bay area (Harwood, unpublished data) it was established that the cleaning practices of portable restrooms can result in increased concentrations of indicator organisms and human associ ated m arkers in nearby water bodi es into which the water has drained. On the banks o f Ochlockonee River near sampling site 319, several live aboard boats are docked and it is suspected that waste ori gi nating fro m t he boats might not be disposed off p roperly, thus contributing to the detection of increased levels o f F I B and MST markers in the area. The data collected during this study strongly indicate that human fecal po llut io n affects water qualit y in Ochlockonee Bay While Lagrangian drifters have been used to track surface transport of bacteria and larvae, including F I B (Bonilla et al. 2007; Goldscheider et al. 2007; Hitchcock, 2008) to the best of our knowledge they have not been used before in the conjunct io n

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87 wi th mo le cular MST methods. The drifter experiment conduc ted i n our study indicates th at during high t ide outfl ow f rom Ochl ockonee Bay flo ws onto Mashes Sands beach, which may result in deposits of bacteri a fro m upstream sources It was noted th at th e ending points for drifters (MS) displayed an elevated freque ncy of esp marker detection com pared to the nearby BR si te, which was sheltered fro m t he path of current flow This correl at io n supports the hypothesis that deposit io n fro m t he outflow of the Ochlockonee River is a significant source of F I B and human asso ciated MST markers that are detected at Mashes Sands beach. Current ly, MST methods are not officially accepted by any of the regulatory agencies as tools for mo nit oring environmental water qualit y and safet y However, thei r utilizat io n in development and implementation of total maximum daily load (TMDL) programs is a step toward the transit io n from a purely research role to one of active applicat io n (United States Environmental Protection Agency, 2005) Data collected in th e study indicate that human fecal po llut io n is impacting recreational water qualit y in Ochlockonee Bay Furtherm ore, storm water runoff and local topography and hydro lo gical condit io ns exist ing in Ochlo cknee Bay appear to be important contributors to the transport pathways of contaminants Thi s work indicates that the combinat io n of F I B enumerat io n, MST methods, and hydrological survey o f t he region can provide valuable informat io n about F I B sources, aiding in the remediation o f impaired waters.

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88 Reference s Ahmed, W., Stewart, J., Gardner, T. & Powell, D. (2008a) A real time polymerase chain react io n assay for quant it ative detection of the human specific enterococci surface protein marker in sewage and environmental waters. Environ Micro biol Ahmed, W., Stewart, J., Powell, D. & Gardner, T. (2008b) Evaluat io n of Bacteroides markers for the detection of human faecal po llut io n. Lett Appl Microbiol 46 (2), 237 242. Ahmed, W., Stewart, J., Powell, D. & Gardner, T. (2008c) Evaluat io n of the hos t specificit y and prevalence of enterococci surface protein (esp) marker in sewage and its applicat io n fo r sourcing human fecal po llut ion. J Environ Qual 37 (4), 1583 1588. American Public Health Association (1999) Standard Methods for the Examinat io n of Wa ter and Wastewater, Standard Method 9222D. Anderson, K.L., Whitlock, J.E. & Harwood, V.J. (2005) Persistence and different ia l survival of fecal indicator bacteria in subtropical waters and sediments. Appl Environ Microbiol 71 (6), 3041 3048. Bernhard, A.E. & Field, K.G. (2000a) Identificatio n of nonpoint sources of fecal pollut io n in coastal waters by using host specific 16S ribosomal DNA genet ic markers fro m fecal anaerobes. Appl Environ Microbiol 66 (4), 1587 1594. Bernhard, A.E. & Field, K.G. (2000b) A PCR assay t o di scriminate human and ruminant feces on the basis of host differences in Bacteroides Prevotella genes encoding 16S rRNA. Appl Environ Microbiol 66 (10), 4571 4574. Boehm, A.B., Keymer, D.P. & Shellenbarger, G.G. (2005) An analyt ical model o f ente rococci inact ivat io n, grazing, and transport in the surf zone of a marine beach. Water Res 39 (15), 3565 3678. Bonilla, T.D., Nowosielski, K., Cuvelier, M., Hartz, A., Green, M., Esiobu, N., McCorquodale, D.S., Fleisher, J.M. & Rogerson, A. (2007) Prevalenc e and di stribut io n of fecal indicator organisms in South Florida beach sand and preliminary assessment of healt h effects associated with beach sand exposure. Mar Pollut Bull 54 (9), 1472 1482. Brownell, M.J., Harwood, V.J., Kurz, R.C., McQuaig, S.M., Lukasi k, J. & Scott, T.M. (2007) Confirmat io n of putative stormwater impact on water qualit y at a Fl ori da beach by microbial source tracking methods and structure of indicator organi sm populations. Water Res 41 (16), 3747 3757.

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89 Burkhardt, W., 3rd & Calci, K.R. (2 000) Select ive accumulat io n may account for shellfish associ ated viral illness. Appl Environ Microbiol 66 (4), 1375 8. Byappanahalli, M.N., Whitman, R.L., Shively, D.A., Sadowsky, M.J. & Ishii, S. (2006) Population structure, persistence, and seasonalit y o f autochthonous Escherichia coli in t emperate, coastal forest soil from a Great Lakes watershed. Environ Microbiol 8 (3), 504 513. Cabelli, V.J., Dufour, A.P., Levin, M.A., McCabe, L.J. & Haberman, P.W. (1979) Relationship of microbial indicators to healt h e ffects at marine bathing beaches. Am J Public Health 69 (7), 690 696. Cabelli, V.J., Dufour, A.P., McCabe, L.J. & Levin, M.A. (1982) Swimming associated gastroenterit is and water qualit y. Am J Epidemiol 115 (4), 606 616. Castelao, R., Schofield, O., Glenn, S ., Chant, R., Kohut, J. (2008) Cross shelf transport of freshwater on the New Jersey shelf. J. Geophys. Res. Oceans 113 (C07017), 1 12. Choi, S., Chu, W., Brown, J., Becker, S.J., Harwood, V.J. & Jiang, S.C. (2003) Applicat io n of enterococci antibiot ic resi stance patterns for contamination source ident ificat io n at Huntington Beach, California. Mar Pollut Bull 46 (6), 748 755. Daskin, J.H., Calci, K.R., Burkhardt, W., 3rd & Carmichael, R.H. (2008) Use of N stable isotope and microbial analyses to define wastew at er influence in Mobile Bay AL. Mar Pollut Bull 56 (5), 860 868. Davies, C.M., Long, J.A., Donald, M. & Ashbolt, N.J. (1995) Survival o f fecal microorganisms in marine and freshwater sediments. Appl Environ Microbiol 61 (5), 1888 1896. Desmarais, T.R., Sol o Gabriele, H.M. & Palmer, C.J. (2002) Influence of so il o n fecal indicator organisms in a tidally influenced subtropical environment. Appl Environ Microbiol 68 (3), 1165 1672. Dickerson, J.W., Jr., Hagedorn, C. & Hassall, A. (2007) Detection and remediat io n of human ori gin poll ut io n at two public beaches in Virginia using mult ip le source tracking methods. Water Res 41 (16), 3758 3770. Ferguson, D.M., Moore, D.F., Getrich, M.A. & Zhowandai, M.H. (2005) Enumeration and speciation of enterococci found in marine and intertidal sediments and coastal water i n southern California. J Appl Microbiol 99 (3), 598 608. Fiechter, J., Haus, B.K., Melo, N., Mooers, C.N.K. (2008) Physical processes impact ing passive particle dispersal in the Upper Florida Keys. Continental Sh elf Research 28 (10 11), 1261 1272.

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90 Fleisher, J.M. (1985) Im plicat io ns of coliform variabilit y in t he assessment of the sani tary quali ty of recreati onal waters. J Hyg (Lond) 94 (2), 193 200. Fleisher, J.M., Jones, F., Kay, D., Stanwell Smith, R., Wyer, M. & Morano, R. (1993) Water and non water related risk factors for gastroenterit is amo ng bathers exposed to sewage contaminated marine waters. Int J Epidemiol 22 (4), 698 708. Florida Administrative Code (FAC: 62 603) (1998) Surface Water Qualit y S tandards. Gol dscheider, N., Haller, L., Pote, J., Wildi, W. & Zopfi, J. (2007) Characterizing water ci rculati on and contaminant transport in Lake Geneva using bacteriophage tracer experiments and limno lo gical methods. Environ Sci Technol 41 (15), 5252 5258. Grant, S.B., Kim, J.H., Jones, B.H., Jenkins, S.A., Wasyl, J., Cudaback, C. (2005) Surf zone entrainment, along shore transport, and human healt h implicat io ns o f pollut io n from tidal outlets. J. Geophys. Res. Oceans 110 (C10025), 1 20. Graves, A.K., Hagedorn, C., Brook s, A., Hagedorn, R.L. & Martin, E. (2007) Microbi al source tracking in a rural watershed dominated by cattle. Water Res 41 (16), 3729 3739. Griffith, J.F., Weisberg, S.B. & McGee, C.D. (2003) Evaluat io n of microbial source tracking methods using mixed fecal sources in aqueous test samples. J Water Health 1 (4), 141 151. Hagedorn, C., Crozier, J.B., Mentz, K.A., Booth, A.M., Graves, A.K., Nelson, N.J. & Reneau, R.B., Jr. (2003) Carbon source utilizat io n profiles as a method to ident ify sources of faecal po llut io n in water. J Appl Microbiol 94 (5), 792 799. Hamilton, M.J., Yan, T. & Sadowsky, M.J. (2006) Development of goose and duck specific DNA markers to determine sources of Escherichia coli in waterways. Appl Environ Microbiol 72 (6), 4012 4019. Harwood, V.J. Butler, J., Parrish, D. & Wagner, V. (1999) Isolat io n of fecal co liform bacteri a fro m t he diamo ndback terrapin ( Malaclemys terrapin centrata ). Appl Environ Microbiol 65 (2), 865 867. Harwood, V.J., Whitlock, J. & Withington, V. (2000) Classificat io n of an ti biotic resistance patterns of indicator bacteria by discriminant analysis: use in predict ing th e source of fecal contaminat io n in subtropical waters. Appl Environ Microbiol 66 (9), 3698 3704. Hitchcock, G.L., Arnold, W.S., Frischer, M., Kelble, C., Cowen, R.K. (2008) Short term di spersal of an intent io nally released patch of larval Mercenaria spp. in the Indian River Lagoon, Florida, USA. Bulletin of Marine Science 82 (1), 41 57.

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91 Kinzelman, J., McLellan, S.L., Daniels, A.D., Cashin, S., Singh, A., Gradus, S & Bagley, R. (2004) Non point source pollut io n: determinat io n of replicat io n versus persistence of Escherichia coli in surface water and sediments with correlat io n of levels to readily measurable environmental parameters. J Water Health 2 (2), 103 114. La Liberte, P. & Grimes, D.J. (1982) Survival of Escherichia coli in lake bottom sediment. Appl Environ Microbiol 43 (3), 623 628. Layton, A., McKay, L., Williams, D., Garrett, V., Gentry, R. & Sayler, G. (2006) Development of Bacteroides 16S rRNA gene TaqMan based real ti me PCR assays for estimat io n of total, human, and bovine fecal po llut io n in water. Appl Environ Microbiol 72 (6), 4214 4224. Liu, L., Phanikumar, M.S., Molloy, S.L., Whitman, R.L., Shively, D.A., Nevers, M.B., Schwab, D.J., Rose, J.B. (2006) Mo deling the transport and inact ivat io n of E. coli and enterococci in the near shore region of Lake Michigan. Environmental Science and Technology 40 (16), 5022 5028. MacFadyen, A., Hickey, B.M., Foreman, M.G. (2005) Transport of surface waters fro m t he Juan de Fuca eddy regio n t o the Washington coast. Continental Shelf Research 25 (16), 2008 2021. Marino, R.P., Gannon, J.J. (1991) Survival o f fe cal co lifo rm s and fecal streptococci in storm drain sediment. Water Res 25 (9), 1089 1098. McDonald, J.L., Hartel, P.G ., Gentit, L.C., Belcher, C.N., Gates, K.W., Rodgers, K., Fisher, J.A., Smith, K.A. & Payne, K.A. (2006) Ident ifying sources of fecal contaminat io n inexpensively wit h t argeted sampling and bacterial source tracking. J Environ Qual 35 (3), 889 897. McQuaig, S.M., Scott, T.M., Harwood, V.J., Farrah, S.R. & Lukasik, J.O. (2006) Detection of Human Derived Fecal Po llution in Environmental Waters by Use of a PCR Based Human Polyo mavirus Assay. Appl Environ Microbiol 72 (12), 7567 7574. Moore, D.F., Zhowandai, M.H., Ferguson, D.M., McGee, C., Mott, J.B. & Stewart, J.C. (2006) Comparison of 16S rRNA sequencing with convent io nal and commercial phenoty pic techniques for ident ificat io n of enterococci fro m t he marine environment. J Appl Microbiol 100 (6), 1272 1281. Nation al Shellfish Sanitation Program (2003) Gui de for the Control of Mo lluscan Shellfish.

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92 Parveen, S., Portier, K.M., Robinson, K., Edmiston, L. & Tamplin, M.L. (1999) Di scriminant analysis o f r iboty pe profiles of Escherichia coli fo r different iat ing human and nonhuman sources of fecal po llut io n. Appl Environ Microbiol 65 (7), 3142 3147. Power, M.L., Littlefield Wyer, J., Gordon, D.M., Veal, D.A. & Slade, M.B. (2005) Phenoty pic and genoty pic characteri zat io n of encapsulated Escherichia coli iso lat ed from blooms in t wo Australian lakes. Environ Microbiol 7 (5), 631 640. Scott, T.M., Jenkins, T.M., Lukasik, J. & Rose, J.B. (2005) Potential use o f a host associ ated m ol ecular marker in Enterococcus faecium as an index o f hu man fecal pollut io n. Environ Sci Technol 39 (1 ), 283 287. Shehane, S.D., Harwood, V.J., Whitlock, J.E. & Rose, J.B. (2005) The influence of rainfall on the incidence o f microbial faecal indicators and the dominant sources of faecal po llution in a Florida river. J Appl Microbiol 98 (5), 1127 1136. Shieh Y.C., Baric, R.S., Woods, J.W. & Calci, K.R. (2003) Molecular surveillance of enterovi rus and norwalk like virus in o yst ers rel ocated to a m unicipal sewage impacted gulf estuary. Appl Environ Microbiol 69 (12), 7130 7136. Solo Gabriele, H.M., Wolfert, M.A ., Desmarais, T.R. & Palmer, C.J. (2000) Sources of Escherichia coli in a coastal subtropical environment. Appl Environ Microbiol 66 (1), 230 237. Stoeckel, D.M. & Harwood, V.J. (2007) Performance, design, and analysis in microbial source tracking studies. Appl Environ Microbiol 73 (8), 2405 2415. Topp, E., Welsh, M., Tien, Y.C., Dang, A., Lazarovits, G., Conn, K., Zhu, H. (2003) Strain dependent vari abili ty in growth and survival of Escherichia coli in agri cul tural so il. FEMS Microbiology Letters 44 (3), 303 308. United States Environmental Protection Agency (1986) Ambient water qualit y criteria fo r bacteri a, EPA440/5 84 002. Washington, D.C. United States Environmental Protection Agency (2002a) Method 1600: enterococci in water by me mbrane filtration using m embrane enterococcus indoxyl B D gl ucosi de agar (m EI), EPA 821 R 02 022. Washington, D.C. United States Environmental Protection Agency (2002b) Method 1603: Escherichia coli ( E. coli ) in water by membrane filtrat io n using modified membrane th erm otolerant Escherichia coli agar (modified mTEC), EPA 821 R 02 023. Washington, D.C. United States Environmental Protection Agency (2005) Microbial Source Tracking Gui de Docum ent, EPA/600 R 05 064. Cincinnat i, OH.

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93 Whitlock, J.E., Jones, D.T. & Harwood, V.J. (2002) Identification o f t he sources of fecal co lifo rm s in an urban watershed using ant ibiotic resistance analysis. Water Res 36 (17), 4273 4282. Whitman, R.L., Shively, D.A., Pawlik, H., Nevers, M.B. & Byappanahalli, M.N. (2003) Occurrence of Escherichia coli and enterococci in Cladophora ( Chlorophyta ) in nearshore water and beach sand of Lake Michigan. Appl Environ Microbiol 69 (8), 4714 4719. Wiggins, B.A. (1996) Discriminant analysis of antibiot ic resistance patterns in fecal streptococci a m ethod to different i ate human and animal sources of fecal pollut io n in natural waters. Appl Environ Microbiol 62 (11), 3997 4002. Wiggins, B.A., Andrews, R.W., Conway, R.A., Corr, C.L., Dobratz, E.J., Dougherty, D.P., Eppard, J.R., Knupp, S.R., Limjoco, M.C., Mettenburg, J.M., Rinehardt, J.M., Sonsino, J., Torrijos, R.L. & Zimmerman, M.E. (1999) Use of ant ibiot ic resistance analysis to ident ify nonpo int sources of fecal pollut io n. Appl Environ Microbiol 65 (8), 3483 3486.

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94 CHAPTER THREE: INVESTIGATION OF HUM AN SEWAGE POLLU TION AND PATHOGEN ANALYSIS AT FLORIDA GULF COAST BEACHES Asja Korajkic, Miriam J. Brownell, and Valerie J. Harwood* Departm ent of Integrative Bio lo gy Universit y of South Florida 4202 East Fowler Avenue, SCA 110 Tam pa, FL 33620 *Author to whom correspon dence should be addressed vharwood@ usf.edu Tel ephone: 813 974 1524 Fax: 813 974 3263 Running Tit le: Microbial source tracking at Gulf of Mexico beaches (Manuscript JAM 2010 0931 submitted for peer re view in the Journal o f Applied Microbi ol ogy )

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95 Abstract Water qualit y at two Fl ori da beaches was co mpared using fecal indicator bacteria (FIB) measurements and microbial source tracking (MST) methods for detecting human source pollut io n. These values were a lso compared before and after remediat io n of wastewater infrastructure at one beach. Fecal co liforms, Escherichia coli and enterococci were enumerated in estuarine water and sediment samples. PCR assays for the human associ ated esp gene o f Enterococcus fa ecium and human polyo maviruses (HPy Vs) were used to detect human sewage. Culturable Salmonella and enteric viruses were also analyzed. MST ident ified human sewage contamination at one beach, leading to repair of a sewer main and relocat io n of portable rest room s. Exceedances of Florida recreational water regul atory standards were significantly reduced after remediat io n (by 52% for fecal coliforms and 39% for enterococci), and the frequency of detection of MST markers decreased. Coxsackie virus B4 and HPyVs w ere co detected following a major sewage spill, but Salmonella was not detected during the study. These data indicate that infrastructure remediat io n significant ly reduced pollut io n from human sewage at the impacted beach. A co mprehensive microbial water q ualit y st udy th at can ident ify contaminat io n sources through the use of MST markers and close collaboration with lo cal/and state agencies can result in tangible act io ns to improve recreational water qualit y a nd safety. I ntroduction A significant portion of water bodi es in the United States fail to meet regulatory cri teria for their designated use due to elevated concentrations of fecal indicator bacteria (FIB) (United States Environmental Protection Agency, 2000; Natural Resources Defense

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96 Council, 2008) Elevated levels of fecal microorganisms in recreational water bodies can have detrimental effects on public healt h and can cause econo mic hardships for the coastal communit ies (i .e. beach closures). According to the Natural Resourc es Defense Council (NRDC), beach closings and advisories reached the fourth highest level in 2008 since NRDC started tracking beach water qualit y 19 years ago (National Resource Defense Council, 2009) Fl ori da ranked ninth amo ng the fift y states in beach water qualit y, as only 3% of samples exceeded regulat ory guidelines for FIB (National Resource Defense Cou ncil, 2009) In Florida, more beach closures in 2008 were attributed to stormwater runoff (35%) than to sewage spills (6%) (National Resource Defense Council, 2009) The impact of sewage contaminat io n on recreational water qualit y and associated public healt h r isks has been well documented (Cabelli et al. 1979; Cabelli et al. 1982; Fleisher et al. 1996; Fleisher et al. 1998; Silva, 2010) however, the contribut io n of stormwater runoff to pathogens and healt h r isk in recreat io nal waters is much less clear (Kinzelman et al. 2004; Noble et al. 2003b; Ahn et al. 2005) Due to the known health risks fro m human sewage contaminat io n, and the abilit y t o repair or upgrade inadequate wastewater infrastructure, detection of a human component of fecal contaminat io n ( if it exists) is useful for m any aspects of water qualit y ma nagement, including beach monitoring and total ma ximum daily lo ad (TMDL) implementation plans (Brownell et al. 2007; Di ckerson et al. 2007; Field & Samadpour, 2007; Kinzelman, 2009; Noble et al. 2006; Nobl e et al. 2003b; Vogel et al. 2007) Enumeration of FIB in a water body provi des no informat io n about the source(s) of contaminat io n (Harwood et al 2000; Stoeckel and Harwood 2007; USEPA 2005). The

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97 rapi dly growing field of microbial source tracking (MST) can help determine the dominant con tributors to fecal po llut io n in enviro nmental waters (Stoeckel & Harwood, 2007; United States Environmental Protecti on Agency, 2005) Recent studies of recreati onal water qualit y ha ve frequent ly ut ilized library indepe ndent MST methods that target host associated microorganism s (Field & Samadpour, 2007; Stoeckel & Harwood, 2007; Vogel et al. 2007; Santo Domingo & Sadowsky, 2007) While most MST methods target nonpathogenic mi croorganisms, due in part to th ei r greater prevalence in host populations compared to pathogens (Harwood, 2007) it is important to remember th at FIB and most MST targets represent surrogates for pathogens. An alternat ive to measuring surrogates for pathogens is to test for specific pathogens, although one must choose from a myriad of potential targets, as it is com pletely unfeasible to test fo r all possible waterborne pathogens. Salmonella spp. and enterovi ruses have been ident ified as et io lo gi cal agents in a number of recorded waterborne gastroenterit is outbreaks worldwide (Angulo et al. 1997; Clark, 1996; O'Re illy et al. 2007; Schuster et al. 2005; Centers for Disease Control and Prevent io n, 2004; Centers for Disease Control and Prevent io n, 2008; Amvrosieva et al. 2006) Both pathogens have been iso lat ed from recreational surface waters with wide ranging sa linit ies (Catalao Dionisio et al. 2000; Fuhrman et al. 2005; Gersberg et al. 2006; Gregory et al. 2006; Savichtchev a et al. 2007; Schets et al. 2008; Touron et al. 2007) even in instances where FIB concentrations would have met US EPA guidelines (Denis Mize et al. 2004) and were therefore ch osen as targets for this study Our primary object ives were to investigate the possi bilit y o f a human source of FIB at recreational beaches in th e Tampa Bay estuary using MST tools and to assess the

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98 success of pollut io n reducti on fo llo wing infrastructure improvements at one beach. Results fro m P hase I (before remediat io n) showed that waters sampled at Bahia Beach (BH) rarely exceeded any o f t he regulatory FIB limits and no human sources of pollution were identified. Water samples collected at Ben T. Davis Beach (BTD) frequent ly did exceed regulatory FIB limits, and human sources of sewage po llution were ident ified and rem ediated through collaboration wit h lo cal and state agencies. This effort was fo llo wed by continued sampling to assess the success o f remed ia l act io ns during Phase II. The resul ts of thi s study are applicable to many efforts, incl uding TMDL assessment for impaired waters and monitoring/regulat io n of beach use. Materials and M ethods Sam pling strategy Four sites at Ben T. Davis Beach (BTD, si tes 1 4) in Tampa, FL and four sites at Bahia Beach (BH, sites 1 4) in Ruskin, FL were chosen for sampling fo llo wing a contaminant source survey in which potential contributors to contamination were ident ified. The GPS coordinates for the sam pling si tes pr esented as lat it ude/l ongi tude are: BH (N 27 43 ’ 743 ” / W 082 28 ’ 591 ” ), BTD 1 (N 27 58 ’ 146 ”/ W 082 34 ’ 502 ” ), BTD 2 (N 27 58’ 111 ”/ W 082 34’ 455 ” ), BTD 3 (N 27 58’ 063 ”/ W 082 34 ’ 394 ” ) and BTD 4 (N 27 58 ’ 044 ”/ W 082 34’ 252 ” ). These sites were sampled at approximately monthly int ervals fro m May 2006 to July 2007 (Phase I before remediat io n) for a total of nine sampling events. Sites at both beaches were several hundred yards apart. Due to a) the lack of exceedances of regulatory criteria for FIB, b) ove rall trend of low FIB concentrations in both water column and sediments, c) similarit y o f FIB concentrations at all sites, and d) rare detection of human MST markers, sampling of three sites at BH was

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99 di scontinued during Phase II. All four BTD sites and on ly one site at Bahia Beach were sampled further at approximately mo nt hly intervals (September 2007 to June 2008) during Phase II (after remediation) for seven sampling events. Grab samples o f sur face water (3 L) and sediments (~2 3 cm depth, and ~ 50 g we ig ht ) were collected during high tide in sterile containers for FIB enumerat io n, esp HPy Vs, and Salmonella spp. analysis. Samples were stored on ice and processed within 4 hours of sampling. One hundred liters of water at each site was filt ered for entero virus enumerat io n except on the fo llo wing dates and sites because of elevated turbidit y: 1) 09/05/07, 60.00 L filtered at BTD 2, 74.00 L filtered on BTD 1, 55.97 L filtered at BTD 4, and 2) 06/10/08 56.78 L filtered at BTD 4. FIB concentrations Water and s ediment sam ples were processed by standard membrane filtrat io n ( 0.45 m m pore si ze, 47 mm diameter ) techniques for enumerat io n of fecal co liforms (American Public Healt h Association, 1999) E. coli (United States Environmental Protecti on Agency, 2002b) and enterococci (United States Environmental Protection Agency, 2002a) Sediment samples were diluted 1:10 in sterile buffered water and sonicated to release organisms attached to particles according to a previously described protocol (Anderson et al. 2005; Ko rajkic et al. 2009) Colonies on plates were counted and reported as CFU per 100 ml of water or 100 g of sediment (wet weight), respectively. Pathogen analysis Cul ture based detection of Salmonella spp. in the water and sediments was carried out only during Phase II. One liter of environmental water and 50 ml of sediment suspension (prepared as described earlier) were processed by a standard membrane

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100 filtrat io n t echnique on nitrocellulo se membrane filt ers (0.45 m m pore size, 47 mm di ameter). Filters w ere pl aced in 100 ml o f bu ffered peptone water (enrichment media) and incubated for at least 16 h at 37 C (Hill et al. 2002) Next, filters and buffered peptone water were blended at high speed for 1 min, fo llo wed by inoculat io n of the 10 ml of blended suspensio n int o 10 ml of double strength Rappaport Vassiliadis ( RV 10 ) broth, followed by incubat io n fo r 20 h at 43C (American Public Healt h Associat io n, 1999; Vassiliadis, 1983) Following incubation, 100 m l o f t he enrichment was spread pl ated on Salmo nella Shi gella agar and XLT 4 agar, two select ive differential media for th e detection of Salmonella spp. (Am erican Public Health Associat io n, 1999) The putative Salmonella spp. col onies (defined as co lo rless co lo nies wit h black centers on Salmo nella Shigella agar, and yellow red col onies with black centers on XLT 4) were iso lat ed on Salmo nella Shigella agar and XLT 4 agar as pure cultures for further processing and confirmat io n (API 20E system and PCR). Characteristic is ol ated colonies were ident ified bio chemically through the API 20E system (Bio mer ieux, France) and by PCR targeting the invA gene (Rahn et al 1992) The results of the API 20E system were interpreted the next day through the use of Ap iWeb TM according to manufacturer’s instructions. For whole cell PCR confirmat io n of Salmonella spp. a single co lo ny was transferred to a 2 ml tube containing 1 ml o f st erile nanopure water and vortexed vigorously. The suspensio n was heated in boiling water for 10 min, fo llo wed by a 5 min incubation on ice, (Moganedi et al. 2007) and it served as th e tem plate for the PCR reaction. The PCR reagent mixture contained: 25l of Jum pStart TM DNA polymerase (Sigma Aldrich, St. Louis, MO), 15 l nanopure H 2 O, 2.5 l (10 mm concentration) o f each primer, and 5 l of template DNA. PCR condit io ns

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101 were previously published (Moganedi et al. 2007) Products of t he PCR reaction were visualized by agarose electrophoresis and staining with ethidium bromide. The expected PCR product size was ~284 bp. Cul turable enteroviruses were measured only during Phase II according to previously established protocols (American Public Healt h Associat io n, 1999; United States Environmental Protection Agency, 2001) Bri efly, water was collected in clean pl asti c buckets and pH was adjusted to 3.5 wit h 1M HCl f ol lo wed by filtrat io n t hrough a negat ively charged filter (length 10 inches, pore siz e 0.45 m) (Pall Corporation, Timo nium, MD). Filters were stored in cl ear pl ast ic bags overnight at 4C. The next day processing of the viral filters was performed in the Tampa Regio nal Laboratory o f t he Fl ori da Depart me nt of Heal th Bri efly, viral particl es were eluted with 950 ml of sterile beef extract (pH 9.5) and allowed to flocculate (United States Environmental Protection Agency, 2001) Sam ples were further concentrated by centrifugation and purified by filt eri ng through 0.80 m and 0.22 m filters (Ameri can Public Healt h Associat io n, 1999; United States Environmental Protection Agency, 2001) All samples were inoculated into Buffalo Green Monkey (BGM) kidney cell lines and incubated and passaged according to published pr otocol s (Am erican Public Health Associat io n, 1999; United States Environmental Protection Agency, 2001) During the six week incubation peri od, sam ples were regul arly examined microscopically for cytopathic effects (CPE) th at woul d indicate presence of enteroviruses Microbi al source tracking Sediments and water at BTD and BH were sampled 16 times each for the duration of th e project (both phases). The Ent. faecium esp methodol ogy (cul ture fo llo wed by

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102 PCR) was performed as previously described (Koraj kic et al. 2009; Scott et al. 2005) on all water and sediment samples. The human polyo mavirus (HPy Vs) PCR assay targeting th e conserved t antigen was performed only on water samples according to published protocol (McQuaig et al. 2006) fo r the first 9 sampling events (Phase I). In order to increase sensit ivit y, a mo dified assay using a different primer set was used in Phase II of th e project (post remediat io n) (Harwood et al. 2009) A positive control for t he PCR assays, BK Virus (VR 837) and Enterococcus faecium (C68) were seeded into water samples fro m each site to test for inhibit io n. Results for MST assays are presented as frequency of posi ti ve results, or the number of samples testing posit ive for the t arget divided by the total number of samples analyzed. Data analysis Pri or to data analysis, all FIB concentrations were log 10 transformed to achieve a norm al distribut io n of the data. Statist ical relationships were considered significant at the al pha lev el  0.05. One way repeated m easures analysis o f var ia nce (ANOVA) fo llo wed by Tukey’s posthoc test (GraphPad InStat software, version 3.00, San Diego, CA) were used to compare the mean FIB concentrations by site, as well as average log 10 reduction in FIB con centrati ons between the two phases. The same so ft ware was used to assess the rel at io nship of FIB concentrations iso lat ed from the water column and sediment from the same site between Phase I and Phase II (two tailed unpaired t test). GraphPad was also use d for linear (Pearson) correlat io n to determine if a statistically significant relat io nship existed between cumulat ive rainfall 1, 3 and 7 days prior to sampling and FIB concentrations iso lat ed from the water column and sediments. The relationship between FIB exceedances/non exceedances, as well as presence/absence of MST markers

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103 com pared by study phase was assessed by the Fisher exact test (two si ded) (GraphPad). The relat io nship between FIB from the water column and sediments and presence/absence of MST markers and pathogens was assessed through binary logist ic regression models (PASW so ft ware versio n 17, SPSS Chicago, IL). Relat io nships where th e P value for model chi square was <0.05 and the confidence interval did not include one were considered to be si gnificant. Results Fecal indicator bacteria concentrations During Phase I, water samples co llected at the more impacted beach, BTD, exceeded Florida regulatory standards for fecal co liforms (400 CFU/ 100 ml) and enterococci (104 CFU/ 100 ml) in 58.3% an d 50.0 % of samples co llected (Figure 6 A) respectively At the less impacted beach, BH, regulatory standards for both fecal coliforms and enterococci were exceeded in 13.9% of water samples co llected. No si gnificant difference in mean FIB concentrations a mo ng the four sites was detected in th e water column ( P value range 0.32 0.43) or sediments ( P value range 0.08 0.43) at BH (data not shown). Thus, sampling efforts at this beach during Phase II were reduced to one site that had the highest proportion o f FIB exceedances (2 out of 9 total samples collected for both fecal co lifo rm s and enterococci). Levels o f FIB recovered from sediments of both beaches were relat ively close to concentrations found in the water col umn (Figures 6 A and 6 B). There was an over all significant reduction in the frequency o f exceedances of fecal co lifo rm ( P < 0.0001) and enterococci ( P = 0.0011) regulatory standards at Ben T. Davis Beach, between the two study periods (before and after remediat io n) (Figure 6 A,

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104 Table 3 ). Only 7.1% an d 10.7% of samples collected during Phase II were out of com pliance wit h fecal co lifo rm and enterococci standards, respect ively. A statist ically si gnificant reduction of FIB concentrations was observed fo llo wing remediat io n in t he water column o f mo st BTD si tes, wi th th e exception of BTD 4 (Tabl e 3 ). Note that P values for fecal co lifo rm and E. coli at BTD 4 are very close to significant. The average lo g 10 reducti on between Phase I and Phase II FIB concentrations in the water column was si gnificant ly higher fo r fecal co liforms and E. coli com pared to enterococci (Table 3 ). Sediment FIB concentrations decreased significantly fro m P hase I to Phase II a t si tes BTD 1 and BTD 4 (Table 4 ) and in general closely resembled trends observed for the water column (Figur es 6 A and 6 B). No significant difference in average log 10 reduction was noted for FIB concentrations in sediments (Table 4 ). The tendency of generally low FIB concentrations (in water and sediments) persisted during Phase II at the BH site that was sampled continually (Figures 6 A and 6 B), where all o f t he samples collected were wi thin enterococci regul atory gui delines and only 13.0% exceeded the fecal co liform standard. The relat io nship between cumulat ive rainfall preceding the sample events (by 1, 3 and 7 days) and FIB concentrations (data fro m bo th study phases included) was assessed. A significant, posit ive correlat io n was detected between cumulat ive rainfall 7 days prior to sam pling and fecal co lifo rm concentrati ons at BTD 1 ( P = 0.0239, r = 0.5606) and BTD 3 ( P = 0.0390, r = 0. 5198). A similar relat io nship was noted for E. coli concentrations at BTD 1, 1 day ( P = 0.0398, r = 0.5352) and 7 days prior ( P = 0.0295, r = 0.5437); however, enterococci concentrations were not correlated with rainfall. FIB dat a fro m a ll BTD sites were pool ed and co mpared to rainfall, and significant posit ive

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105 rel at io nships were found fo r fecal co liforms and E. coli wit h cumulat ive rainfall 1 day and 7 days prior to the sampling event; however, enterococci concentrations remaine d uncorrel ated wi th antecedent rainfall. No si gnificant correlat io n was found at BH for any of th e param eters tested. (Addit io nal data included in Appendix B) Microbi al source tracking Two PCR methods were emplo yed for MST: one targeting the esp gene o f Ent. faecium, which was performed on all water and sediment samples, and one targeting HPy Vs, which was performed only on water column samples. Both markers were detected frequently at BTD sites before remediat io n ( frequency o f detection for esp at each si te ranged fro m 0.33 0.56, and fro m 0.00 0.33 for HPyVs). The highest frequency of detection occurred at BTD 1 (Table 5 ). At BH, only the esp marker was detected once in t he water column (Table 5 ). Fo llo wing rem ediat io n efforts, a general trend in reduction of MST marker detection was noted at BTD sites, where the frequency of detection decreased to 0.00 0.33 and 0.00 0.29, for esp and HPyVs, respect ively (Table 5 ). The highest decline in MST markers was observed at BTD 1, where the esp marker was detected s ig nificant ly less frequent ly in t he water column ( P = 0.03). The same significant relat io nshi p was observed for the esp marker when data were combined for sites that were affected the mo st by remediat io n efforts (BTD 1 and BTD 4, P = 0.04). All MST marker detection continued to be sporadic and rare at BH (Table 5 ). The relat io nship between FIB and MST markers was assessed using binary lo gist ic regressio n mo dels. A relatively weak, but significant posit ive correlation was

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106 fo und between fecal co lifo rm concen trati ons in the water column and presence of the esp marker (Nagelkerke R 2 = 0.11; odds ratio 1.87, c 2 0.01). A similar relat io nship that was not quite statistically significant was observed for E. coli co ncentrations and detection of esp in t he water column (Nagelkerke R 2 = 0.13; odds ratio 2.60, c 2 0.07). No relat io nship was detected between concentrat io ns of FIB and presence/absence of the HPyVs marker. (Addit io nal data included in Appendix B) Pathogen analysis Testing for culturable Salmonella spp. was performed on all water and sediment samples, while a culturable enterovirus assay was performed onl y o n water samples. Assays for both pathogens were performed only in Phase II. No Salmonella spp. colonies were detected for the duration of the study. An enterovirus, ident ified as a Coxsackie B4, was detected at BTD 1 once, during the last sampling event (Table 5 ). It i s noteworthy th at HPyVs were co detected with enterovirus at the same site during the same sampling event, which occurred fo llo wing a major sewage spill less than a mile away (Table 5 ). (Addit io nal data included in Appendix B) Remediation of wastewater infrastructure Collaborative efforts of the local agencies charged with protection of human and environmental health (Environmental Protection Commission o f H illsborough County, Hillsborough County Departm ent of Heal th and Cit y o f T am pa Stor mwater Department) acted jo int ly t o help ident ify, repair and remediate the human sources of sewage pollut io n ident ified during Phase I. Actions taken to correct the problems at BTD included: 1) repai ri ng/replacing sections of the fault y sewer main (BTD 3, BTD 4), 2) removing the

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107 dam aged, abandoned restrooms (which were scheduled to be replaced) (BTD 1) ,and 3) mo ving the portable restrooms to the north side of the parking lot and away fro m t he bay water (BTD 1).

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108 Table 3. Si te by si te com parison of mean FIB concentrations in the water column for Phase I vs. Phase II samples (two tail, unpaired t test). P values for statist ically si gnificant com parisons are in bo ld. Means and standard deviations are presented as log 10 CFU/100 ml water. Si te Organism P val ue Pre rem ediat io n Pos t rem ediat io n Log 10 reducti on Fecal coliforms 0.0031 3.08 + / 1.25 1.28 + / 0.49 1.80 E. coli 0.0046 2.73 + / 1.26 1.04 + / 0.44 1.69 BTD a 1 Enterococci 0.0011 2.32 + / 0.58 1.21 + / 0.48 1.11 Fecal coliforms 0.0035 3.13 + / 0.63 1.94 + / 0.72 1.19 E. coli 0.0047 2.95 + / 0.80 1.62 + / 0.77 1.33 BTD 2 Enterococci 0.1444 2.22 + / 0.49 1.78 + / 0.67 0.44 Fecal coliforms 0.0028 2.51 + / 0.76 1.41 + / 0.25 1.10 E. coli 0.0020 2.25 + / 0.77 1.03 + / 0.38 1.22 BTD 3 Enterococ ci 0.0422 1.79 + / 0.58 1.07 + / 0.70 0.72 Fecal coliforms 0.0930 2.59 + / 1.17 1.71 + / 0.62 0.88 E. coli 0.0795 2.27 + / 1.09 1.38 + / 0.70 0.89 BTD 4 Enterococci 0.2861 1.78 + / 0.97 1.34 + / 0.48 0.44 a Ben T. Davis Beach

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109 Table 4. Si te by si te c om parison of mean FIB concentrations in the sediments for Phase I vs. Phase II samples (two tail, unpaired t test). P values for statist ically significant com parisons are in bo ld. Means and standard deviations are presented as log 10 CFU/100 g of sediment ( wet weight) Si te Organism P value Pre rem ediat io n Pos t rem ediat io n Log 10 reducti on Fecal co lifo rm s 0.0239 3.23 + / 1.23 1.78 + / 0.98 1.45 E. coli 0.0023 2.73 + / 1.05 0.92 + / 0.84 1.81 BTD a 1 Enterococci 0.0050 3.04 + / 0.56 2.14 + / 0.50 0.90 Fecal co lifo rm s 0.1206 2.84 + / 0.71 2.15 + / 0.98 0.69 E. coli 0.0841 2.48 + / 1.00 1.49 + / 1.11 0.99 BTD 2 Enterococci 0.6154 2.58 + / 0.58 2.35 + / 1.15 0.23 Fecal co lifo rm s 0.2772 2.28 + / 1.16 1.67 + / 0.96 0.61 E. coli 0.0807 2.19 + / 1.11 1.31 + / 0.62 0.88 BTD 3 Enterococci 0.1164 2.49 + / 0.38 2.10 + / 0.56 0.39 Fecal co lifo rm s 0.2112 3.26 + / 1.10 2.64 + / 0.63 0.62 E. coli 0.0320 2.82 + / 0.91 1.71 + / 0.94 1.11 BTD 4 Enterococci 0.0191 3.25 + / 0.38 2.17 + / 1.51 1.08 a Ben T. Davis Beach

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110 Table 5. Com parison of MST markers and pathogen ( esp HPy V, and total cul turable enterovi ruses) frequency distribut io n in t he water column and sediments between Phase I pre remediat io n and Phase II post remediat io n remediat io n samples. Salmonella w as not detected. Pre remediat io n Pos t rem ediat io n Si te esp Water HPy V Water esp Sediment esp Water HPy V Water TCE a Water esp Sediment BH 0.11 0.00 0.00 0.00 0.14 0.00 0.14 BTD 1 0.56 0.33 0.44 0.00 0.14 0.14 0.14 BTD 2 0.44 0.00 0.22 0.43 0.00 0. 00 0.14 BTD 3 0.33 0.11 0.22 0.14 0.29 0.00 0.14 BTD 4 0.33 0.22 0.11 0.14 0.29 0.00 0.14 a Total culturable enteroviruses (TCE) performed only in Phase II

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111 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 BH BTD-1 BTD-2 BTD-3 BTD-4 Sites log 10 CFU/100 ml Figure 6 A Mean FIB concentrations ( lo g 10 CFU/100 ml) in th e water co lu mn samples by site. E rror bars represent standard deviat io ns. Means represent 9 samples collected before remediat io n, and 7 after. Site abbreviat io ns (x axis): BH Bahia Beach, BTD Ben T. Davi s Beach (sites 1 4). FIB concentrations before remediat io n are represented by: fecal co lifo rm s ( ); E. coli ( ); enterococci ( ). Symbols represent FIB concentrations af ter the remediation: fecal coliforms ( ); E. coli ( ); enterococci ( ).

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112 -0.5 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 BH BTD-1 BTD-2 BTD-3 BTD-4 Site s log 10 CFU/100g Figure 6 B Mean FIB concentrations (CFU/100 g of wet weight) in sediment sam ples by si te Erro r bars represent standard deviat io ns. Means represent 9 samples co llected before rem ediat io n, and 7 after. Site abbreviat io ns (x axis): BH Bahia Beach, BTD Ben T. Davis Beach (sites 1 4). FIB concentrations before remediat io n are represented by: fecal co liforms ( ); E. coli ( ); enterococci ( ). Symbo ls represent FIB concentrations a ft er th e remediat io n: fecal coliforms ( ); E. coli ( ); enterococci ( ).

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113 Discussion Microbi al source tracking methods have been emplo yed with increasing frequency over the l ast decade to di scriminate between human and non human pollut io n sources (Ahmed et al. 2008b; Bernhard & Field, 2000a; Graves et al. 2007; Harwood et al. 2009; Korajkic et al. 2009; McQuaig et al. 2006; Noble et al. 2006) Source ide nt ificat io n, however, must be fo llo wed up by implementation of corrective act io ns if improvements in water qualit y are to be achieved. Data from Phase I indicated that human fecal po llution affected water qualit y at BTD beach, as evidenced by frequent exc eedances of FIB regulatory standards and recurrent detection of human associated MST markers. Greater frequency o f MST marker detection at sites BTD 1, BTD 3 and BTD 4, along with a contaminant source survey ident ified several contributors to the poor wate r qualit y. Corrective actions (described in th e Remediat io n sect io n of the Result s) addressed these sources and resulted in a si gnificant decrease in regulatory standard exceedances and detection of MST markers during Phase II. Even though remedial act io ns were successful for improving water qualit y, sporadi c sewage leaks st ill plague the BTD area due to aging sewer infrastructure. In May 2008 (during Phase II), a large sewage spill (~250,000 gallo ns) occurred in result ing in the co detection of enterovirus (Coxsackie B4) and HPyVs at BTD 1 during the last sampling event. An earlier study determined that FIB reservo ir s in the sediments of stormwater system s can have a negative impact on receiving waters during rain events (Brownell et al. 2007) Several oth er studi es also documented detrimental effects of stormwater and rainfall run of f on water qualit y in receiving waters (Marino, 1991; Shehane et al. 2005;

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114 Ahn et al. 2005; Noble et al. 2003b) Com parison between FIB concentrations in the water column and cumulat ive rainfall prior to sample event detected significant posit ive rel at io nships, indicating that storm water runoff is impact ing water qualit y at Ben T. Davis Beach (sites 1 and 3). It is interesting that the rainfall FIB relat io nship was not consistent am ong all FIB t ypes, i. e. fecal co lifo rm and E. coli co ncentrations were correl ated while enterococci wer e not Thi s finding highlights the influence of th e physio lo gy and eco lo gy o f FIB on their relat io nship with environmental parameters. No impact of rainfall on water qualit y at th e control si te, Bahia beach, was observed. Unlike BTD, which has a major stor mwater outfall, ditch systems and a stormwater swale structure that channel runo ff t oward the beach, BH has fewer such structures and is also surrounded by less impervious surface s (e.g. parking lots ) Interestingly FIB concentrations quant ified in sedime nt s in our study were quite similar to FIB concentrations in the water column. This finding contrasts with those of previous stu di es, which generally found FIB in sediments to be 1 3 orders of magnitude higher compared to the overlaying water column (K oraj kic et al. 2009; Wapnick, 2007; Kinzelman et al. 2004; Solo Gabriele et al. 2000; Brownell et al. 2007; Badgley et al. 2010) This difference underlines the effects of regio nal hydro lo gy and topography characterist ic s on FIB ecology in aquatic environments and it reinforces the fact that broad generalizations about these environments are unwise. This study is among the first to emplo y MST methods to conclusively identify a pollut io n source and also report on the successful effects of remediation act io ns. Other such case studies include (Kinzelman, 2009; Dickerson et al. 2007; Hagedorn et al. 1999) In all cases, pollut io n source(s) were ident ified and ranged fro m cattle (Hagedorn

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115 et al. 1999) to fault y sewer infrastructure (Di ckerson et al. 2007) to FIB loading fro m stor mwater ou tl ets and re suspensio ns of FIB from beach sediments (Kinzelman, 2009) Corrective act io ns undertaken (restricting cattle access, sewage infrastructure repairs, redesign o f a ma jo r storm water outl et, and improved beach grooming strategies) were successful as evidenced by improvement in microb ial water qualit y a nd reduced beach cl osures (Di ckerson et al. 2007; Kinzelman, 2009; Hagedorn et al. 1999) The successful outcomes of our study and the above ment io ned case studies emphasize the importance of co llaborative efforts where scient ific tools are utilized to assess recreati onal water qualit y a nd ident ify po llution sources, and local governments are invo lved in the remediat io n attem pts to restore the watershed to their original intended use. It has been established th rough previous studies that FIB alo ne are not adequate predi ctors of pathogen presence (Anderson et al. 2005; Craig et al. 2003; Field & Sam adpour, 2007; Harwood et al. 2005) The data collected during this study strongly indicate that human fecal po llut io n was affect ing water quali ty at all si tes at Ben T. Davis beach, while Bahia B each acted as a negat ive control site. This work signifies that th e combinat io n of an effect ive contaminant source survey, FIB enumerat io n, MST techniques, and pathogen analysis can provide valuable insig ht int o th e pollut io n sources affect ing water qualit y, and that collaboration with local agencies can result in a timely rem ediat io n of impacted watersheds.

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116 References Ahmed, W., Stewart, J., Gardner, T. & Powell, D. (2008) A real ti m e polymerase chain react io n assay for quant it ative detection of the human specific enterococci surface protein marker in sewage and environmental waters. Environ Microbiol 10 (12), 3255 3264. Ahn, J.H., Grant, S.B., Surbeck, C.Q., DiGiacomo, P.M., Nezlin, N .P. & Jiang, S. (2005) Coastal water qualit y i mpact of stormwater runoff fro m an urban watershed in southern California. Environ Sci Technol 39 (16), 5940 5953. American Public Health Association (1999) Standard Methods for the Examinat io n of Water and Wast ewater, Standard Method 9222D. Amvrosieva, T.V., Paklonskaya, N.V., Biazruchka, A.A., Kazinetz, O.N., Bohush, Z.F. & Fisenko, E.G. (2006) Enteroviral infect io n outbreak in the republic o f Belarus: Principal characteristics and phylogenet ic analysis o f et io lo gi cal agents. Central European Journal of Public Health 14 (2), 67 73. Anderson, K.L., Whitlock, J.E. & Harwood, V.J. (2005) Persistence and different ia l survival of fecal indicator bacteria in subtropical waters and sediments. Appl Environ Microbiol 71 (6 ), 3041 3048. Angulo, F.J., Tippen, S., Sharp, D.J., Payne, B.J., Collier, C., Hill, J.E., Barrett, T.J., Clark, R.M., Geldreich, E.E., Donnell, H.D. & Swerdlow, D.L. (1997) A communit y w aterborne outbreak of salmo nello sis and the effect iveness of a bo il w ater order. American Journal of Public Health 87 (4), 580 584. Badgley, B.D., Thomas, F.I.M. & Harwood, V.J. (2010) The effects of submerged aquati c vegetation on the persistence of environmental populations of Enterococcus spp. Environmental Microbiology 1 2 (5), 1271 1281. Bernhard, A.E. & Field, K.G. (2000) Identificat ion of nonpo int sources of fecal pollut io n in coastal waters by using host specific 16S ribosomal DNA genet ic markers fro m fecal anaerobes. Appl Environ Microbiol 66 (4), 1587 1594. Brownell, M .J., Harwood, V.J., Kurz, R.C., McQuaig, S.M., Lukasik, J. & Scott, T.M. (2007) Confirmat io n of putative stormwater impact on water qualit y at a Fl ori da beach by microbial source tracking methods and structure of indicator organi sm populations. Water Res 4 1 (16), 3747 3757. Cabelli, V.J., Dufour, A.P., Levin, M.A., McCabe, L.J. & Haberman, P.W. (1979) Relationship of microbial indicators to healt h effects at marine bathing beaches. Am J Public Health 69 (7), 690 696.

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117 Cabelli, V.J., Dufour, A.P., McCabe, L.J. & Levin, M.A. (1982) Swimming associated gastroenterit is and water qualit y. Am J Epidemiol 115 (4), 606 616. Catalao Dionisio, L.P., Joao, M., Ferreiro, V.S., Fidalgo, M.L., Garcia Rosado, M.E. & Borrego, J.J. (2000) Occurrence of Salmonella spp in estuarin e and coastal waters of Portugal. Antonie Van Leeuw enhoek 78 (1), 99 106. Centers for Disease Control and Prevention (2004) Surveillance for waterborne di sease outbreaks associated with recreational water. Atlanta, GA. Centers for Disease Control and Preve ntion (2008) Surveillance for Waterborne Di sease and Outbreaks Associated with Recreational Water Use and Other Aquat ic Facilit y Associ ated Heal th Events --United States, 2005 -2006. At la nt a, GA. Clark, R.M., Geldreich, E.E., Fox, K.R., Rice, E.W., John son, C.H., Goodrich, J.A., Barnick, J.A., Abdesaken, F., Hill, J.E., Angulo, F.J. (1996) A waterborne Salmonella typhimurium outbreak in Gideon, Missouri: results from a field investigat io n. Int. J. Environ. Health Res. 6 (3), 187 193. Craig, D.L., Fallowfi eld, H.J. & Cromar, N.J. (2003) Effect iveness o f guideline faecal indicator organism values in est imat io n of exposure risk at recreational coastal si tes. Water Sci Technol 47 (3), 191 198. Denis Mize, K., Fout, G.S., Dahling, D.R. & Francy, D.S. (2004) Dete cti on of human enteri c viruses in stream water with RT PCR and cell culture. J Water Health 2 (1), 37 47. Dickerson, J.W., Jr., Hagedorn, C. & Hassall, A. (2007) Detection and remediat io n of human ori gin poll ut io n at two public beaches in Virginia using mul ti ple source tracking methods. Water Res 41 (16), 3758 3770. Field, K.G. & Samadpour, M. (2007) Fecal source tracking, the indicator paradigm, and managing water qualit y. Water Res 41 (16), 3517 3538. Fleisher, J.M., Kay, D., Salmon, R.L., Jones, F., Wyer, M .D. & Godfree, A.F. (1996) Marine waters contaminated with domestic sewage: nonenteric illnesses associ ated wi th bather exposure in the United Kingdom. Am J Public Health 86 (9), 1228 1234. Fleisher, J.M., Kay, D., Wyer, M.D. & Godfree, A.F. (1998) Estimate s of the severit y of illnesses associated with bathing in marine recreational waters contaminated wi th dom esti c sewage. Int J Epidemiol 27 (4), 722 726.

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118 Fuhrman, J.A., Liang, X. & Noble, R.T. (2005) Rapid detection of enteroviruses in small vo lu mes of natur al waters by real ti me quantitat ive reverse transcriptase PCR. Appl Environ Microbiol 71 (8), 4523 4530. Gersberg, R.M., Rose, M.A., Robles Sikisaka, R. & Dhar, A.K. (2006) Quant it ati ve detection of hepat it is a virus and enteroviruses near the United States Mexico border and correlat io n wit h le vels o f fecal indicator bacteria. Appl Environ Microbiol 72 (12), 7438 7444. Graves, A.K., Hagedorn, C., Brooks, A., Hagedorn, R.L. & Martin, E. (2007) Microbi al source tracking in a rural watershed dominated by cattle. Water Res 41 (16), 3729 3739. Gregory, J.B., Litaker, R.W. & Noble, R.T. (2006) Rapid one step quantitative reverse transcri ptase PCR assay wit h competit ive internal posit ive control for detection of enterovi ruses in environmental samples. Appl Environ Mic robiol 72 (6), 3960 3967. Hagedorn, C., Robinson, S.L., Filtz, J.R., Grubbs, S.M., Angier, T.A. & Reneau, R.B., Jr. (1999) Determining sources of fecal po llution in a rural Virginia watershed with antibiot ic resistance patterns in fecal streptococci. Appl E nviron Microbiol 65 (12), 5522 5531. Harwood, V.J. (2007) Assumpt io ns and Limitat io ns Associated with Microbial Source Tracking Methods. In Microbial Source Tracking pp. 33 64. Edited by J.W. Santo Domingo, Sadowsky M.J. Washington, D.C.: ASM Press. Harwo od, V.J., Brownell, M., Wang, S., Lepo, J., Ellender, R.D., Ajidahun, A., Hellein, K.N., Kennedy, E., Ye, X. & Flood, C. (2009) Validat io n and field testing of library independent microbial source tracking methods in the Gulf of Mexico. Water Res 43 (19), 4 812 4819. Harwood, V.J., Levine, A.D., Scott, T.M., Chivukula, V., Lukasik, J., Farrah, S.R. & Rose, J.B. (2005) Validit y of the indicator organism paradigm for pathogen reducti on in reclaimed water and public healt h protection. Appl Environ Microbiol 71 (6 ), 3163 3170. Hill, V.R., Kantardjieff, A., Sobsey, M.D. & Westerman, P.W. (2002) Reduction of enteri c microbes in flushed swine wastewater treated by a bio lo gical aerated filt er and UV irradiat io n. Water Environ Res 74 (1), 91 99. Kinzelman, J., McLellan, S.L., Daniels, A.D., Cashin, S., Singh, A., Gradus, S. & Bagley, R. (2004) Non point source pollut io n: determinat io n of replicat io n versus persistence of Escherichia coli in surface water and sediments with correlat io n of levels to readily measurable envir onmental param eters. J Water Health 2 (2), 103 114.

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119 Kinzelman, J., McLellan, S. J. (2009) Success of science based best management practi ces in reducing swimming bans a case study fro m Racine, Wisconsin, USA. Aquatic Ecosystem Health & Management 12 (2), 1 87 196. Korajkic, A., Badgley, B.D., Brownell, M.J. & Harwood, V.J. (2009) Application o f microbial source tracking methods in a Gulf o f Mexico field setting. J Appl Microbiol 107 (5), 1518 1527. Marino, R.P., Gannon, J.J. (1991) Survival o f fe cal co lifo rm s and fecal streptococci in storm drain sediment. Water Res 25 (9), 1089 1098. McQuaig, S.M., Scott, T.M., Harwood, V.J., Farrah, S.R. & Lukasik, J.O. (2006) Detection of Human Derived Fecal Po llution in Environmental Waters by Use of a PCR Based Human Polyo mavirus Assay. Appl Environ Microbiol 72 (12), 7567 7574. Moganedi, K.L.M., Goyvaerts, E.M.A., Venter, S.N. & Sibara, M.M. (2007) Optimisat io n of the PCR invA primers for the detection of Salmonella in drinking and surface waters fo llo wing a pre cul tivati on step. Water Sa 33 (2), 195 202. National Resource Defense Council (2009) Testi ng the Waters: A Guide to Water Qualit y at Vacation Beaches. Natural Resources Defense Council (2008) Testing the Waters: A guide to Water Qualit y at Vacation Beaches. Noble, R.T ., Griffith, J.F., Blackwood, A.D., Fuhrman, J.A., Gregory, J.B., Hernandez, X., Liang, X., Bera, A.A. & Schiff, K. (2006) Mult it iered approach using quant it ative PCR to track sources of fecal pollut io n affect ing Santa Monica Bay California. Appl Environ Microbiol 72 (2), 1604 1612. Noble, R.T., Weisberg, S.B., Leecaster, M.K., McGee, C.D., Dorsey, J.H., Vainik, P. & Orozco Borbon, V. (2003) Storm effects on regional beach water qualit y al ong the southern California shoreline. J Water Health 1 (1), 23 31. O' Reilly, C.E., Bowen, A.B., Perez, N.E., Sarisky, J.P., Shepherd, C.A., Miller, M.D., Hubbard, B.C., Herring, M., Buchanan, S.D., Fitzgerald, C.C., Hill, V., Arrowood, M.J., Xiao, L.X., Hoekstra, R.M., Mintz, E.D. & Lynch, M.F. (2007) A waterborne outbreak of gastroenterit is w ith mult iple etio lo gi es am ong resort island visitors and residents: Ohio, 2004. Clinical Infectious Diseases 44 (4), 506 512. Rahn, K., De Grandis, S.A., Clarke, R.C., McEwen, S.A., Galan, J.E., Ginocchio, C., Curtiss, R., 3rd & Gyles, C .L. (1992) Amplification of an invA gene sequence o f Salmonella typhimurium by po lymerase chain reaction as a specific method of detection of Salmonella Mol Cell Probes 6 (4), 271 279.

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120 Santo Domingo, J.W. & Sadowsky, M.J. (2007) Microbial Source Tracking. Washington, DC: American Societ y fo r Mi crobi ol ogy Savichtcheva, O., Okayama, N. & Okabe, S. (2007) Relat io nships between Bacteroides 16S rRNA genet ic markers and presence of bacterial enteric pathogens and convent io nal fecal indicators. Water Res 41 (16), 3615 3628. Schets, F.M., van Wijnen, J.H., Schijven, J.F., Schoon, H. & de Roda Husman, A.M. (2008) Monitoring of waterborne pathogens in surface waters in Amsterdam, the Netherl ands, and the potential health risk associated with exposure to Cryptosporidiu m and Giardia in t hese waters. Appl Environ Microbiol 74 (7), 2069 2078. Schuster, C.J., Ellis, A.G., Robertson, W.J., Charron, D.E., Aramini, J.J., Marshall, B.J. & Medeiros, D.T. (2005) Infect io us di sease outbreaks related to drinking water i n Canada, 197 4 2001. Canadian Journal of Public Health Revue Canadienne De Sante Publique 96 (4), 254 258. Scott, T.M., Jenkins, T.M., Lukasik, J. & Rose, J.B. (2005) Potential use o f a host associ ated m ol ecular marker in Enterococcus faecium as an index o f hu man fecal pollut io n. Environ Sci Technol 39 (1), 283 287. Shehane, S.D., Harwood, V.J., Whitlock, J.E. & Rose, J.B. (2005) The influence of rainfall on the incidence o f microbial faecal indicators and the dominant sources of faecal po llution in a Florida river. J App l Microbiol 98 (5), 1127 1136. Silva, A.M., Vieira, H., Martins, N., Granja, A.T.S., Vale, M.J., Vale, F.F. (2010) Vi ral and bacterial contamination in recreat io nal waters: a case study in Lisbon bay area. Journal of Applied Microbiology 108 (3), 1023 1031. Solo Gabriele, H.M., Wolfert, M.A., Desmarais, T.R. & Palmer, C.J. (2000) Sources of Escherichia coli in a coastal subtropical environment. Appl Environ Microbiol 66 (1), 230 237. Stoeckel, D.M. & Harwood, V.J. (2007) Performance, design, and analysis in mi crobial source tracking studies. Appl Environ Microbiol 73 (8), 2405 2415. Touron, A., Berthe, T., Gargala, G., Fournier, M., Ratajczak, M., Servais, P. & Petit, F. (2007) Assessment of faecal contaminat io n and the relationship between pathogens and faecal bacteri al indicators in an estuarine environment (Seine, France). Mar Pollut Bull 54 (9), 1441 1450. United States Environmental Protection Agency (2000) Atlas of America’s polluted waters. Office of Water (4503F), EPA 840 B00 002. Washington, D.C.

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121 United States Environmental Protection Agency (2001) USEPA Manual o f Methods fo r Vi rol ogy EPA/600/4 84/013 (N15). Washington, D.C. United States Environmental Protection Agency (2002a) Method 1600: enterococci in water by me mbrane filtration using membrane ente rococcus indoxyl B D gl ucosi de agar (m EI), EPA 821 R 02 022. Washington, D.C. United States Environmental Protection Agency (2002b) Method 1603: Escherichia coli ( E. coli ) in water by membrane filtrat io n using modified membrane th erm otolerant Escherichia coli agar (modified mTEC), EPA 821 R 02 023. Washington, D.C. United States Environmental Protection Agency (2005) Microbial Source Tracking Gui de Docum ent, EPA/600 R 05 064. Cincinnat i, OH. Vassiliadis, P. (1983) The Rappaport Vassiliadis (RV) enrichmen t m edium fo r the iso lat io n of Salmonella : an overview. J Appl Bacteriol 54 (1), 69 76. Vogel, J.R., Stoeckel, D.M., Lamendella, R., Zelt, R.B., Santo Domingo, J.W., Walker, S.R. & Oerther, D.B. (2007) Identifying fecal sources in a selected catchment reach using mult iple source tracking tools. J Environ Qual 36 (3), 718 729. Wapnick, C.M., Korajkic, A., Harwood, V.J. (2007) Applicat io n of Microbial Source Tracking (MST) Methods in Assessment of the Sources of Fecal Po llut io n in Tributari es In Biennial Confere nce on Stormw ater Research and Watershed Management Orl ando, FL.

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122 PROTOZOAN PREDATION IS A DOMINANT DETERM INANT OF ESCHERICHIA COLI PERSISTENCE IN ENVIR ONMENTAL WATERS Abstract Escherichia coli are fecal indicator bacteria (FIB) used to ass ess recreati onal water qualit y wo rl dwide. Several factors were shown in other studies to affect their survival in aquati c habitats, but the magnitude of each factor’s contribut io n is uncertain. The goal o f thi s work was to systematically co mpare the influe nce o f selected parameters ( exposure to sunlight, freshwater vs. seawater, the presence of protozoa and sediments) on the survival of E. coli st rains of known origin in outdoor mesocosms. Incubation periods ranged fro m 9 15 days, and samples for enumerati on of culturable E. coli were collected approximately every oth er day. In mesocosms lacking protozoa, extended survival was noted i n t he sediments vs. the water column as well increased persistence in freshwater com pared to seawater habitats I nclusio n of indigenous pond protozoa in freshwater mesocosms caused a much more rapid decline in E. coli populations vs. mesocosms wi th out protozoa particularly in the water column. N ative protozoa also affect ed the decline of E. coli co ncentrations in seawater meso cosm s where no culturable organisms were detected in the water column after 5 days. Significant ly h igher E. coli densit ies were maintained in sediments co mpared to the water column, particularly in seawater, underscoring their importance as a refuge and p ote nt ia l r eservo ir of th ese organisms. The

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123 rel at ive magnitude o f t he protozoan predation in the water column of freshwater mesocosms was dependent on the matrix characterist ic s si gnifying that fa ctors affect ing FIB survival in the water column and sedimen ts are di ssimilar. Freshwater vs. saltwater habitat exerted more pressure on the survival o f cult urable organisms in the sediments, em phasizing the intrinsic effects of different habitats on FIB survival. Introduction Di rect quantificat io n of disease cau sing bacteria and viruses is time consuming and expensive, and it is virtually impossible to test for all possible pathogens in a water body Instead, microbio lo gical quali ty of recreat io nal waters in Florida and across the US is assessed by enumerat io n o f culturable fecal indicator bacteria (FIB) including fecal coliforms, Escherichia coli and enterococci (Fl ori da Administrative Code, 1998; United States Environmental Protection Agency, 1986; United States Environmental Protection Agency, 2002b; United States Environmental Protection Agency, 2002a) Norm ally a commensal, non patho genic organism, E. coli is shed in feces of humans and many other warm and col d blooded animals alo ng wit h enteric pathogens (Harwood et al. 1999; Harris, 1932; Geldreich, 1978; Varga & Anderson, 1968; Pourcher et al. 1991) A high degree of genet ic similarit y t o important enteric pathogens belo nging to the genera Salmonella and Shigella (Fukushima et al. 2002; Pupo et al. 2000; Wang et al. 2001) makes it a particularly useful model organism. Ideally FIB should provide a warning that fecal contaminat io n of waters by human derived sewage has recent ly o ccurred, and their presence should correlate with the presence of huma n pathogens in the water. However, s tudi es invest igating the validit y of FIB paradigm found extended survival exhibited by E. coli in environmental waters and

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124 sediments to be one of the factors confounding the usefulness and interpretation of the current w at er qualit y guidelines (Anderson et al. 2005; Byappanahalli & Fujioka, 1998; Desmarais et al. 2002; Davies et al. 1995; Obiri Danso & Jones, 1999; Solo Gabriele et al. 2000; Goyal et al. 1977; Fish & Pettib one, 1995; Sherer, 1992; Rhodes & Kator, 1988) In particular, sediments have been implicated as a refuge and a potential reservoir fo r FIB in a variet y o f c limates and environments (Byappanahalli et al. 2003; Fazi et al. 2008; Ishii et al. 2007; Kin zelman et al. 2004; LaLiberte & Grimes, 1982; Obiri Danso & Jones, 1999; Tunnicliff & Brickler, 1984; Whit man et al. 2003; Anderson et al. 2005; Buckley et al. 1998) While extended persistence and ev en potenti al replicat io n of FIB in t he environment are well documented, there is no clear consensus on the relat ive magnitude of th e detrimental factor(s) responsible for their ultimate decline. Several abiot ic factors, chief among them sunlight irradiat io n, have been suggested as a possible mechanism res ponsible for the decline of E. coli co ncentrations in ambient waters. The germicidal properties of UV radiat io n in sunlight were recognized early on (Gameson & Saxon, 1 967; Downes, 1877) and later studies documented rapid declines of E. coli and other organi sms in oxygen rich, shallow, marine waters in the absence of sediments (Davies Colley et al. 1994; Fujioka et al. 1981; Sinton et al. 1994; Sinton et al. 1999) Inact ivat io n rates were slower in freshwater (e.g. organisms survived for longer periods of time ) com pared to m arine waters (Fujioka & Narikawa, 1982; Davies & Evison, 1991; Si nt on et al. 2007; Sinton et al. 2002) Protozoan predation is one of the most important biot ic factors influencing E. coli survival in the en vironment ; th e r el at ive importance of bacterivorous protozoa grazing is

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125 th e highest in productive waters (e.g. ponds and surface marine waters) (Beardsley et al. 2003; Sherr et al. 1988; Nakano et al. 1998) Protozoan predation was found to be responsible for up to 90% removal of E. coli in th e laboratory mesocosm studies in fresh and marine waters alike (Anderson, 1986; Menon et al. 1996; Menon et al. 2003) Recorded bacterial mortalit y r ates in the presence of protozoa were relat ively high, reaching 34 x 10 3 per hour (Menon et al., 2003). It was even suggested th at the inverse rel at io nship between temperature and FIB survival observed in the environment is due to protozoa, since these organisms have higher abu ndance and better feeding efficiency at warm er tem peratures (An et al. 2002; Anderson et al. 1983; McCambridge & McMeekin, 1980; Sherr et al. 1988; Barcina et al. 1991; C le ven, 2004b; Cleven, 2004a; Fernandez Leborans & Fernandez Fernandez, 2002) While th e synergist ic action o f su nlight inact ivat io n and protozoan predation were shown to be more effect ive at E. coli inact ivat io n t han eit her factor alone (McCambridge & McMeekin, 1981; Rhodes & Kator, 1990) persistence of FIB in t he environment is influenced by a co mp lex array of bio lo gi cal and physico chemical parameters (Rhodes & Kator, 1988) Environmental condit io ns are hard to simulate, and direct c om parisons and int erpretati on of the results is further confounded by a variet y o f e xperimental designs (McFeters & Terzieva, 1991) The object ive of thi s study was to methodically compare the influence of selected param eters (sunlight, freshwater vs. seawater, presence of protozoa and sediments, and variat io n in individual strains) on the survival o f culturable E. coli in outd oor m esocosm s, mimicking environmenta l co ndit io ns as closely as possible. To the best of our knowl edge, our study is a unique effort to systematically quantify the effect of singular,

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12 6 as well as co mbinat io n of these environmental parameters on variances in E. coli concentrations incubated und er ambient condit io ns in warm subtropical climates. Our resul ts indicate that in warm, subtropical climates, the presence o f protozoa is among the dominant determinants of E. coli persistence in freshwater and estuarine aquat ic habitats. Materials and Me thods Sam pling si tes and sample treatment Water and sediment samples used to construct mesocosms were collected at the fo llo wing locat io ns: Ben T. Davis Beach (for all seawater mesocosms), Hillsborough River and a pond at Universit y of South Florida (Tamp a, FL) grounds for freshwater mesocosms (Table 6). Salinit y measurements at these sites were as fo llo ws: 24 ppt (Ben T. Davi s), 0.22 ppt (Hillsborough River) and 0.26 ppt (pond). Water and sediment samples fro m each site were collected in shallow waters (~ 20 30 cm depth) from swash zone of the beach, and river/pond banks. Approximately 20 liters of water and 15 kg of sediments fro m each location were collected into sterile containers and large debris (e.g. leaves, branches) was manually remo ved. Water and sediment samples for non protozoa containing mesocosms were filter sterilized (0.45 m m and 0.22 m m pore size) and heat dri ed, respectively to remove indigenous organisms. Removal efficiency was tested by filt ering 100 ml o f water and 50 ml o f sediment suspensio n on mTEC media and by spread pl at ing 100 l of each on TSA (trypt ic so y agar). Only water and sediments in which no culturable organisms were detected were used. For the protozoa co nt aining mesocosms, water and sediment samples were collected from the pond and Ben T. Davis Beach one day prior to inoculat io n, and were held at 4 C ov ernight. At the time of

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127 inoculat io n, untreated water and sediments contained negligible (0 10 CFU/ 100 ml or g wet weight) concentrations o f ind igenous E. coli Mesocosm preparati on Three mesocosm experiments were conducted in July 2009 and March and Apr il 2010. Each of the three mesocosms series contained both water and sediment (Table 6) and were exposed to sunlight. The July 2009 series consisted of 30 individual mesocosms divided into two treatments: 15 for freshwater (Hillsborough River) and 15 for s eawater (Ben T. Davis beach) (Table 6). For each treatment, five different E. coli st rains were inoculated individually into triplicate mesocosms, none of which contained protozoa. Mesocosm s were incubated for 15 days, and samples were collected immediatel y a ft er inoculat io n (T0), daily for 3 days (T1 T3), and every other day unt il t he end of the experiment (Table 6). The cumulat ive average of mean daily ambient temperatures during 15 day s incubat io n was 27.8 + / 1.2 C. Mesocosm seri es conducted in Mar ch and April 2010 consisted of ten mesocosms each, divided into two treatments (protozoa versus no protozoa) with five replicates (Tabl e 6). Water and sediments were collected at USF pond (March experiment) and Ben T. Davi s Beach (April experiment). Both s ets of mesocosms were inoculated with a mixture of five different E. coli st rains. Mesocosms were incubated for 9 days total, and samples were collected at T0 and T1, and every other day thereafter (Table 6). The cum ulat ive averages o f mea n daily ambient tem peratures duri ng 9 days incubat io n were 16.75 + / 4.20 C and 22.49 + / 1.21 C during the March and April experiments, respectively

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128 For all o f t he experiments, mesocosms were constructed in 1.5 liter borosilicate gl ass beakers, and filled wit h appr oximately 3 3.5 cm of sediment (by depth) and one liter of water. All beakers were covered with translucent ziplock bags to prevent cross contaminat io n by rodents, insects and rainfall. Beakers were placed i n large plastic bins filled with mu nicipal tap wa te r ( ~ 3 cm below the rim o f t he beakers ) to m oderate tem perature fluctuations, and were incubated outdoors in t he Botani cal Gardens at Universit y of South Florida Tampa campus. E. coli st rains All mesocosms contained the fo llo wing E. coli st rains: MG1655 ATCC 8739, SMS 35, HS and WW6 (iso lat ed from fina l e ffluents of Marshall Street wastewater treatm ent pl ant in Clearwater, FL). Strain select io n was governed by the diverse backgrounds o f ind ividual organisms. E. coli MG1655 and ATCC 8739 are both K 12 de scendents commo nly used as control strains for a variety o f assays (Blattner et al. 1997) Strain HS is co mmensal inhabitant of human gastrointestinal tract (Levine et al. 1978) while SMS 35 was iso lat ed fro m so il contaminated w it h heavy metals (Fricke et al. 2008) Both of these strains were kindly provided by Dr Jacques Ravel o f t he Inst it ute fo r Geno me Sciences. All strains were streaked for iso lat io n on TSA and incubated overnight at 37 C The next d ay, one colony fro m each TSA plate was aseptically transferred into 5 ml o f T SB (try pti c so y broth) and incubated overnight at 37 C Fo llo wing incubat io n, 1 ml of TSB suspensio n was centrifuged at 14 000 rpm for 3 min, fo llo wed by two successive washing s teps in 1 x PBS (8 g/L NaCl, 0.2 g/L KCl, 1.44 g/L Na 2 HPO 4 0.24 KH 2 PO 4 pH 7.4) and final resuspensio n in 1 ml of 1 x PBS. One

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129 milliliter of bacterial suspensio n was inoculated in water column and sediments of each mesocosms, stirred and allowed to settle pri or to T0 sam ple co llect io n. E. coli enumerat io n Decimal dilution series of samples were prepared in sterile buffered water (0.0425 g/ L KH 2 PO 4 and 0.4055 g/ L MgCl 2 ; pH 7.2) and processed by standard membrane filtrat io n met hods (0.45 m m pore size, 47 mm diameter) (United States Environmental Protecti on Agency, 2002b) Escherichia coli fro m w ater and sediment samples was enumerated on mTEC media at 35 o C for 2 h, follo wed by 22 h incubation at 44.5 o C (United States Environmental Protection Agen cy, 2002b) Sediment samples were first diluted 1:10 with sterile buffered water and shaken by hand for 2 min. to disassociate bacteri a fro m sediment particles, fo llo wed by membrane filtration o f t he supernatant. Several dilut io ns prepared in the sterile buffered water were processed for each sampling point. Colonies were counted on plates, and concentrations were adjusted for the dilut io n factor, and reported as log 10 CFU/100 ml or log 10 CFU/100 grams (wet weight) for water and sediment samples, respectiv ely. Data analyse s All E. coli concentrations were log 10 transformed and norm alized to 100 ml or 100 g (wet weight) for water column and sediments, respectively bef ore data analysis. Decrease of culturable organism concentrations over time is presented as lo g 10 reduction, cal culated by subtracting init ial concentration from the final (in case of overall reducti on), or concentrati on recovered fro m t he earlier time point minus concentration recovered fro m so me specified time point later in the experiment. In som e cases, cul turable organisms were not detected after a certain time po int therefore log 10

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130 reducti on was calculated by subtracting init ia l concentration fro m t he last time po int when culturable organisms were detected. For the statist ical analyses des cribed below for March and April experiments, log 10 reducti ons were calculated for the fift h day o f incubat io n (T5). The reason for this is the lack of detection of culturable organisms at T7 and T9 in the water column of both freshwater and seawater mesoc osm s containing protozoa. In addit io n, for July mesocosms, analysis (one way ANOVA) w as conducted fo r reducti on value calculated at both T5 and T15, since culturable E. coli were recovered fro m so me replicates of all treatments for the duratio n of the expe riment. One way analyses of variance (ANOVA) wit h Tukey Kramer post hoc tests for si gnificance (GraphPad InStat software v ersi on 3.00 fo r Windows San Diego, C A ) were used to assess the relationships between E. coli lo g 10 reducti on in: a) different matric es (water, sediment), and b) different mesocosm treatments (freshwater/seawater, protozoa present/absent) (Table 6). The effects of different independent variables, as well as int eract io n of vari ables on E. coli lo g 10 reduction cal culated at T5 were evalu ated using tw o way ANOVA (GraphPad Prism so ft ware version 5.00 for Windows, San Diego, CA) (Tabl e 6). Analyses were organized in a 2 x 2 block design, with protozoa presence/absence variables presented in co lu mns, and water/sediment or freshwater/seawater variables in rows. The contribution of each row variable to the observed differences in co lu mn means was assessed by Bonferroni post hoc tests with 95% confidence intervals. Analyses were conducted by co mpar ing log 10 reduction values in: a) water column of freshwater/seawater mesocosms with and without protozoa, b) sediments of the same treatments, c) between water column and sediments of freshwater mesocosms with and without protozoa, and d) same comparisons in seawater mesocosms.

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131 Results Different ia l su rvival of E. coli The aim of the init ial mesocosm series conducted in July 2009 was to assess different ia l survival o f 5 E. coli st rains (different responses of the various strains in terms of survival in the mesocosms) by enumerat io n of culturable concen trati ons in two matri ces (water and sediments) and under different environmental condit io ns ( freshwater and seawater) during a 15 day incubat io n period (Table 6). Indigenous organisms fro m water and sediment used to construct mesocosms were removed, and me socosms were incubated outdoors, exposed to ambient temperatures and direct sunlight UV irradiation. While different ia l survival was observed amo ng the strains tested (data presented in Appendix C; Figures C1 C5), i t was also noted that under all condit io n s cul turable concentrations remained much higher than expected, with no appreciable decline until the fift h day o f incubation. Addit io nal experiments (data not shown) were conducted com paring the persistence of starved cells (incubated in 1 x PBS for 72 ho urs prior to inoculat io n) to non starved (preparation utilized for mesocosms described above) over time under the same condit io ns. The lack of differences in E. coli co ncentrations over time between the two treatments indicated that physio lo gi cal state was not responsible for th e extended survival. Furthermore, supplementary experiments (data not shown) explored potential blockage of sunlight irradiat io n by t ranslucent zip lo ck bag by com paring E. coli persistence in covered versus uncovered mesocosms over time. No si gnificant difference in bacterial survival between the two experiments ruled out blockage o f su nlight irradiat io n as a contribut ing factor. These observat io ns led to further investigat io ns focusing on the effects of protozoan predation on cultur able E. coli

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132 concentrations in environmental waters and sediments because all indigenous microbiota were removed from the experiments described above, and survival t imes for E. coli in th ese mesocosms was much longer than expected. For this reason, data fr om th e July 2009 mesocosm series is presented as an average of data from all strains, and survival is addressed fro m t he standpoint of matrix (water versus sediment) and treatment condit io ns (freshwater versus seawater). Survival o f mixed E. coli populati on wi th out protozoa During the first three days of the experiment, there was no appreciable decline o f cul turable E. coli concentrations under any o f t he condit io ns tested (Figure 7 ). The averages of log 10 transform ed cul turable concentrati ons for T0 throu gh T3 were as fo llo ws: water column (freshwater: 8.31 + / 0.18; seawater 7.90 + / 0.24) and sediments (freshwater: 7.98 + / 0.10; seawater 7.51 + / 0.18). In the water column of both freshwater and seawater mesocosms, the largest decline occurred fro m T 5 t o T7, measuring 3.03 + / 0.11 and 3.26 + / 0.23 log 10 reductions, respect ively (see Materials and Methods; Data Analyses). For the remainder of the experiment, the decrease in culturable concentrations in t he water column cont inued, with the overall log 10 reducti on of 7.56 + / 0.33 and 7.79 + / 0.20, for freshwater and seawater, respectively (Figure 7 ). In the freshwater sediments, th e decline of culturable organisms was not as abrupt, but fo llo wed a more gradual pattern, with the largest log 10 reduction (1 .65 + / 0.24) occurring between T11 and T13, and an overall reduction o f 3.49 + / 0.32 log 10 (Fi gure 7 ). In the seawater sediments, the decline was more pronounced and daily log 10 reduction values ranged from 0.43 – 1.20, wi th th e overall reduct io n of 4.70 + / 0.70 (Figure 7 ).

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133 Log 10 reductions calculated at T5 and T15 in the water column o f freshwater and seawater mesocosms, as well as between water column and sediments of the same mesocosm ty pe were com pared by one way ANOVA (Tables 7A and 7B). The result s dem onstrated that E. coli survival in sediments is significantly greater when co mpared to th e water column in seawater mesocosms ( P < 0.001) (Table 7A). In freshwater mesocosms, this trend is less apparent at T5 ( P > 0.05), compared to T15 ( P < 0.001) (T able 7A). Greater persistence of E. coli was measured in freshwater compared to seawater ( P value range < 0.05 – < 0.001), for both water column and sediments (Table 7B). In both matrices, values of log 10 reduction for the water column and sediments betwe en freshwater and seawater mesocosms were less different at T15 compared to T5 (Tabl e 7B). The overall log 10 reducti on fo llo wed the same general pattern: seawater water col umn (7.80 + / 0.20) > freshwater water column (7.56 + / 0.33) > seawater sediments ( 4.70 + / 0.70) > freshwater sediments (3.50 + / 0.32). Freshwater mesocosms with and wit hout protozoa The effect of protozoan predators on persistence of culturable E. coli concentrations in freshwater (water and sediments) was invest igated during a Mar ch 2010 study (Table 6). Both experimental treatments contained the same E. coli ino cul um, consist ing of a mixture of all 5 strains A large overall decrease ( 4.90 + / 0.14 lo g 10 reducti on) of culturable E. coli concentrations in the water column was obse rved in protozoa co nt aining mesocosms after a 5 day incubat io n peri od (Fi gure 8 ) and was fo llo wed by a leveling of f o f E. coli co ncentrations during the last two days (T7, T9) (Fi gure 8 ). A similar decline was not observed for the matching mesocosms lackin g protozoa, where E. coli co ncentrations rem ained relat ively unchanged during the first

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134 th ree day s (7.15 + / 0.11 log 10 CFU/100 ml) fo llo wed by a sl ow er decline of less than one order of magnitude per day (T5 T9) and th e lo g 10 reduction was 0.47 + / 0.22 a t T5 (Fi gure 8 ). A comparison of E. coli lo g 10 reduction in the water column o f mesocosms wi th and wi th out protozoa showed that those with protozoa experienced significant ly mo re rapi d declines ( P < 0.001) concentrations of culturable bacteria ( Table 8 ). P opul at io n dynamics were different in the sediments of protozoa co nt aining mesocosms, where a considerably smaller decrease (log 10 reduction of 1.57 + / 0.21) was observed co mpared to the water column af ter 5 days (Figure 8 ). However, in the mesocosms lacki ng protozoa, concentrations remained largely unchanged (7.21 + / 0.07 lo g10 CFU/100 g) for the duration of the experiment (Figure 8 ). The observed difference in decrease o f culturable E. coli concentrations between protozoa co nt aining and protozoa deficien t m esocosm s over time was statistically significant ( P < 0.001) (Table 8 ). Furthermore, th e decline o f E. coli co ncentrations in t he water col umn o f bo th mesocosms with and without protozoa were significant ly lo wer com pared to the sediment concentrations ( P = 0.001) (Figure 8 ). Seawater mesocosms wit h and wit hout protozoa A mesocosm experiment conducted during April 2010 utilized essent ia lly the same experimental design wit h respect to the E. coli inoculum and presence/absence of protozoan predators as t he March 2010 experiments (Table 6). The only difference between the two was in the source of water and sediments (freshwater vs. seawater). Cul turable E. coli co ncentrations in the water column o f mesocosms with protozoa fo llo wed a precipitous decline o f 2 4 orders of magnitude per day during the fi rst three day s (T0 T3), and no culturable organisms were detected during the last two

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135 sampling po int s (T7 and T9) (Figure 9 ). In the mesocosms lacking protozoa, culturable E. coli population exhibited a grad ual init ial decline of less than one order of magnitude (T0 T3), fo llo wed by a more pronounced decrease in concentrations between T3 and T5 (Fi gure 9 ). C om parisons of lo g 10 reduction of culturable E. coli at T5 in me socosms with and wit hout protozoa, revea led significant ly greater populat io n declines when protozoa were present ( P = 0.001) (Tabl e 8). Concentrati ons of cul turable E. coli in t he sediments of protozoa co nt aining mesocosms exhibited approximately one order of magnitude decline per day, result in g in an overall decrease of 3.24 + / 0.31 log 10 at T5 (Fi gure 9 ). Conversely, in the mesocosms lacking protozoa, E. coli populations declined slight ly mo re than one order of magnitude over 5 days (1.75 + / 0.20 log 10 reduction at T5) (Figure 9 ). Differenc es in the log 10 reducti ons of E. coli between the two treatments were statist ically significant ( P < 0.001) (Tabl e 8). Com parison of log 10 reductions of E. coli populat io ns between matrices (water and sediment) at T5 was extremely significant ( P < 0.001) f or both protozoa co nt aining and protozoa deficient mesocosms (Figure 9 ). The decrease in log 10 reducti ons matched by matrix type (water or sediment) and presence/absence of protozoa were compared between freshwater and seawater incubat io n condit io ns In g eneral, log 10 reductions in freshwater were significantly less th an in seawater ( P < 0.001 ) ( Table 9 ). Effect of protozoa The magnitude of the effect of protozoan predation on E. coli persistence in t he water column and sediments of freshwater and seawat er mesocosms, as well as th e contribution o f t he water salinit y and matrix to the difference in lo g 10 reduction at T5 was

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136 assessed by two way analysis o f variance. Log 10 reductions in th e water col umn of fresh and seawater me socosms were compared between m esocosms wi th and wi th out protozoa. Protozoan presence was extremely significant ( P < 0.0001) and responsible for 46.6 % of th e total variance in both types of mesocosms (Table 10, Figure 10 A). Seawater vs. freshwater also significantly affected log 10 redu cti ons ( P < 0.0001), although it contributed slight ly less to total variance (43.8 %) (Table 10, Figure 10 A). The differences between populati on declines over time in the presence and in the absence of protozoa in the water column o f both freshwater and se awater mesocosm s were s ta tist ically significant ( P < 0.001) (Table 10, Figure 10 ). Interaction of the two variables accounted for the smallest percent variat io n (9.25 %), but it did significant ly affect the outcom e ( P < 0.0001) (Table 10). The same co mpar i son was used to assess differences in log 10 reduction of E. coli iso lat ed from sediments of freshwater and seawater mesocosms, with and wit hout protozoa. Overall, interact io n of the two variables (protozoa presence/absence and salinit y) di d not contribute si gnificant ly t o the variance between data sets ( P = 0.2951) (Tabl e 10, Figure 10 B), but protozoa presence alone did have a significant effect ( P < 0.0001) that accounted for 43.4 % of total variation (Table 10, Figure 10 B). Seawater habitat alone had an e ven greater effect ( P < 0.0001) on differences in reduction of E. coli concentrations, contribut ing 53.9 % to total variat ion (Table 10, Figure 10 B). The differences between protozoa presence/absence treatments on reduction in E. coli popul at io ns were sign ificant in both freshwater and seawater sediments ( P < 0.001) (Tabl e 10).

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137 The effect of matrix (water column and sediments) on differences in reduct io n of E. coli between protozoa co nt aining and protozoa deficient mesocosms was co mpared separately fo r the freshwater and seawater series using the same analyt ical tool (Table 11, Figure s 1 1 A and 1 1 B). In freshwater, interaction of variables (water versus sediment, protozoa presence/absence) was significant ( P < 0.0001), accounting for 12.3% of overall varianc e. Each variable alone also significant ly a ffected the decrease in populations ( P < 0.0001) contribut ing 61.7% (protozoa presence/absence) and 25.4% (water col umn/sediment) to the total variance (Table 10, Figure 1 1 A). Overall, protozoa presence was an ext rem ely important contributor to decline of culturable populat io ns in both, water column and sediments ( P < 0.001), (Figure 1 1 A). In the seawater mesocosms, the interaction of variables (water versus sediment, protozoa presence/absence) did not significant ly affect log 10 reduction of E. coli ( P = 0.2462) (Tabl e 11, Figure 1 1 B). However, protozoa presence did account for 20% of variabilit y ( P < 0.0001) and this effect was significant in both water column and sediments ( P < 0.001) (Table 11). Characteristics of th e matrix (water column, sediments) had the greatest contribut io n to variance (78.9% at P < 0.0001) (Table 11, Figure 1 1 B).

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138 Table 6. Experimental design: mesocosm characterist ics, treatments, sampling schedule and data analyses Seri es Treatment Matr ix and inoculum Replicates per treatm ent Length of incubat io n (day s) Total samples collected Data analyses Freshwater (no protozoa) July 2009 Seawater (no pr otozoa) Water and sediment; five E. coli strains in individual mesocosms 3 a 15 10 One way ANOVA Protozoa March 2010 (freshwater) No protozoa Protozoa April 2010 (seawater) No protozoa Water and sediment; five E. coli strains combined in mesocosms 5 9 6 One and two way ANOVA a Three replicates for each str ain

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139 Table 7. Protozoa Absent: C om parison of E. coli lo g 10 reducti on in freshwater and seawater mesocosms without protozoa. Water column (log 10 CFU/100 ml) and sediment (l og 10 CFU/10 0 g, wet weight) reduction values calculated at T5 and T15 for three indiv idual replicates and co mpared by one way ANOVA wit h Tukey Kramer post tests A Water vs sediment Water lo g 10 re ducti on + / SD Sediment lo g 10 reducti on + / SD P value T5 T15 T5 T15 T5 T15 F a 0.32 + / 0.24 7.56 + / 0.33 0.11 + / 0.01 3.50 + / 0.32 >0.05 < 0.001 S b 2.91 + / 0.19 7.90 + / 0.20 1.23 + / 0.05 4.70 + / 0.70 <0.001 < 0.001 a Freshwater b Seawater B. Freshwater vs seawater Freshwater lo g 10 reducti on + / SD Seawater lo g 10 reducti on + / SD P value T5 T15 T5 T15 T5 T15 W a 0.32 + / 0.24 7.56 + / 0.33 2.91 + / 0.19 7.90 + / 0.20 < 0.001 < 0.05 S b 0.11 + / 0.01 3.50 + / 0.32 1.23 + / 0.05 4.70 + / 0.70 < 0.001 < 0.05 a Water b Sediment

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140 Table 8 Protozoa Present vs. Absent: C om parison of E. coli lo g 10 reduction in freshwater and seawater mesocosms with and without protozoa. Water column (log 10 CFU/100 ml) and sediments (log 10 CFU/100 g, wet weight) reduction values calculated at T5 for five indi vidual replicates and co mpared by one way ANOVA wit h Tukey Kramer post tests Matrix No protozoa lo g 10 reducti on + / SD Protozoa lo g 10 reducti on + / SD P value Water column 0.47 + / 0.22 4.90 + / 0.14 < 0.001 Freshwater Sediments 0.12 + / 0.11 1.5 7 + / 0.21 < 0.001 Water column 4.81 + / 0.10 6.51 + / 0.14 < 0.001 Seawater Sediments 1.75 + / 0.18 3.24 + / 0.31 < 0.001 a negative value indicates increase in concentrations

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141 Table 9. Fresh Water vs. Salt Water: Co mpar ison of E. coli lo g 10 reduction in mesocosms with and without protozoa between freshwater and seawater mesocosms. Water column (log 10 CFU/100 ml) and sediments (log 10 CFU/10 0 g, wet weight) reducti on values calculated at T5 for five individual replicates and compared by one way ANOVA wi th Tukey Kramer post tests Treatment Matrix Freshwater lo g 10 reducti on + / SD Seawater lo g 10 r educti on + / SD P value Water 4.90 + / 0.14 6.51 + / 0.14 < 0.001 Protozoa Sediment 1.57 + / 0.21 3.24 + / 0.31 < 0.001 Water 0.47 + / 0.22 4. 81 + / 0.10 < 0.001 No protozoa Sediment 0.12 + / 0.11 1.75 + / 0.18 < 0.001 a negative value indicates increase in concentrations

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142 Table 10. Com parison of the effects of protozoa presence and freshwater vs. seawater habitats on E. coli lo g 10 reduction values in t he water column (log 10 CFU/100 ml) and sediments (log 10 CFU/100 g, wet weight). Log 10 reduction values calculated at T5 for five individual replicates and co mpared by two way ANOVA wit h Bonferroni post tests Source of variat io n % of total variation P value Pos t tests Interacti on 9.25 < 0.0001 Fresh vs salt 43.8 < 0.0001 Water column P a vs NP b 46.6 < 0.0001 P a vs NP b Freshwater P < 0.001 Seawater P < 0.001 Interacti on 0.18 0.2951 Fr esh vs salt 53.9 < 0.0001 Sediments P a vs NP b 43.4 < 0.0001 P a vs NP b Freshwater P < 0.001 Seawater P < 0.001 a Protozoa present b Protozoa absent

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143 Table 11. Com parison of the effects of protozoa presence and matrix characterist ics on E. coli lo g 10 reducti on values in freshwater and seawater mesocosms. Water c ol umn (l og 10 CFU/100 ml) and sediments (log 10 CFU/100 g, wet weight) reduction values were cal culated at T5 for five individual replicates and compared by two way ANOVA with Bonferroni post tests. Source of variat io n % of total variation P value Pos t tes ts Interacti on 12.3 < 0.0001 Water vs sediment 25.4 < 0.0001 Freshwater P a vs NP b 61.7 < 0.0001 P a vs NP b Water P < 0.001 Sediment P > 0.001 Interacti on 0.09 0.2462 Water vs sediment 78.9 < 0. 0001 Seawater P a vs NP b 20.0 < 0.0001 P a vs NP b Water P < 0.001 Sediment P < 0.001 a Protozoa present b Protozoa absent

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144 0 1 2 3 4 5 6 7 8 9 10 T0 T1 T2 T3 T5 T7 T9 T11 T1 3 T1 5 Time log 10 CFU/ 100 ml(g) Figure 7 Protozoa Absent : Mean E. coli co ncentrations in the water column (log 10 CFU/100 ml) and sediments (log 10 CFU/ 100 g, wet weight) over time in freshwater and seawater mes ocosms Averaged data fro m 5 separate mesocosm treatments (run in true tri plicates), each containing a different E. coli st rain. Columns represent sediment values, while lines represent water column values: ( ) and ( ) represent freshwater; ( ) and ( ) represent seawater values.

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145 0 1 2 3 4 5 6 7 8 T0 T1 T3 T5 T7 T9 Time Log 10 CFU/100 ml (g) Figure 8 Protozoa Present vs. Absent : Mean E. coli concentrations in the water column (l og 10 CFU/100 ml) and sediments (log 10 CFU/ 100 g, wet weight) over time in fresh water mesocosms. Averaged data from five individual replicate mesocosms. Columns represent sediment values, while lines represent water column values: ( ) and ( ) protozoa present; ( ) and ( ) protozoa absent.

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146 0 1 2 3 4 5 6 7 8 T0 T1 T3 T5 T7 T9 Time log 10 CFU/ 100 ml(g) Figure 9 Protozoa Present vs. Absent : Mean E. coli concentrations in the water column (l og 10 CFU/100 ml) and sediments (log 10 CFU/ 100 g, wet weight) over time in seawater mesocosms. Averaged data from five individual replicate mesocosms. Columns represent sediment values, while lines represent water column values: ( ) and ( ) protozoa present; ( ) and ( ) protozoa absent.

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147 A B P NP P NP 0 2 4 6 8 Fresh wa ter S ea wa ter log 10 CFU/100 ml P NP P NP -1 0 1 2 3 4 Fresh wa ter S ea wa ter log 10 CFU/100 g Figure 10 Co mp ari son of th e effects of protozoa presence /absence and freshwater vs seawater habit at on E. coli lo g 10 reducti on in (A) th e water column ( lo g 10 CFU/100 ml) and (B) sediments (log 10 CFU/100 g wet weight) of freshwater and seawater mesocosms Log 10 reduction values calculated at T5 for five individual replicates. Protozoa present (P, ), protozoa absent ( NP, ). Different letters above columns denotes statist ically significant difference of E. coli co ncentrations in the water col umn (A) and sediments (B) between freshwater and seawater mesocosms and between the water column and sediments of freshwater/ sea water m esocosm s a b c a d e f g

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148 A B P NP P NP -2 0 2 4 6 Wat er S ed im en t log 10 CFU/100 ml (g) P NP P NP 0 2 4 6 8 Wat er S ed im en t log 10 CFU/100 ml (g) Figure 1 1 Co mp ari son o f t he effects of protozoa presence and ma tri x characterist ic s on E. coli lo g 10 reduction in fr eshwater (A) and seawater (B) mesocosms. Water column (log 10 CFU/100 ml) and sediment (log 10 CFU/100 g, wet weight) reduction values calculated at T5 for five individual replicates. Protozoa present (P, ), protozoa absent (NP, ). Different letters above col umns denotes statist ically significant difference of E. coli co ncentrations in the water column (A) and sediments (B) between freshwater and seawater mesocosms and between the freshwater and seawater mesocosms in the water col umn/sediments a b c d e a f g

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149 Discussion Quant ificat io n of FIB is used throughout the world to assess th e microbio lo gical safet y o f dr inking water, recreational waters and shellfishing waters. The U.S. Envi ronmental Pro tecti on Agency recommends the use of E. coli as an indicator organi sm for the assessment of recreational water qualit y o f a mbient freshwater bodie s (United States Environmental Protection Agency, 1986; United States Environmental Protecti on Agency, 2002b) While many quest io ns have been raised about the validit y o f FIB paradigm, the effects of environmental factors on survival is the most relevant to issues discussed here. The init ial experiment in this study (July mesocosms) co mpared the persistence of E. coli in t he water column and sediments of freshwater and seawater mesocosms (in the absence of protozoa) incubated outdoors and thus exposed to direct sunlight. Surpri singly, in contrast to the previous studies that described a rapid decline o f FI B due to germicidal effects of sunlight (Davies Colle y et al. 1994; Davies Colle y et al. 1997; Fujioka et al. 1981; Fujioka & Narikawa, 1982; Sinton et al. 2007; Sinton et al. 1999; Si nt on et al. 2002) we observed a very slow chang e in E. coli co ncentrations in freshwater and seawater, and in both water column and sediments. It is important to note th at the main difference between our study condi ti ons and the above ment io ned works is inclusio n of sediments in the experimental design The importance of sediments in protecting E. coli from harmful influences exerted by biot ic and abiotic environmental param eters i s well documented (Davies et al. 1995; Craig et al. 2004; Gerba & McLeod, 1976; Allen et al. 1953; Bonde, 1967; Shiaris et al. 1987; Beversdorf et al. 2007) and,

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150 coupl ed wi th th e lack of protozoa, is likely the reason we observed such a slow decay rate in t he init ia l e xperiments. Regardless of protozoan presence, comparisons of reduction in E. coli populat io ns between freshwater and seawater environments showed significant ly greater persistence in freshwater systems in both water column and sediments. This observa ti on is consistent wi th previous findings of a negative relat io nship between salinit y and E. coli survival (Anderson et al. 1979; Carlucci & Pramer, 1960; Gauthier et al. 1993; Lessard & Si eburth, 1983; Rozen & Belkin, 2001; Evison, 1988; Anderson et al. 2005) In the absence of protozoa, extended survival o f E. coli w as observed in both freshwater and seawater sediments, com pared to the water column This pattern is consistent with previ ous studi es indicat ing sediments as a refuge and potential reservo ir of fecal indicator bacteria (Anderson et al. 2005; Buckley et al. 1998; By appanahalli et al. 2003; Craig et al. 2004; Davies et al. 1995; Frie s et al. 2008; Gerba & McLeod, 1976; Hood & Ness, 1982; Ishii et al. 2007; Kinzelman et al. 2004; Pote et al. 2009) It is noteworthy that this trend was even more significant in mesocosms incubated for lo nger period of time (15 days), than during the fir st 9 day s, which may be due to the time required for the bacteria to become stressed under the outdoor mesocosm condit io ns in t he absence of protozoan predation. The same general trend of extended persistence in th e sediments compared to the water colu mn was observed in the presence of protozoa in both freshwater and saltwater mesocosms, indicat ing that bacterial attachment to sediment particles may o ffer protection from predatory protozoa. Interestingly, in the seawater mesocosms, the presence of sedim ents had m ore effect on the persistence of cul turable E. coli concentrations compared to the presence of protozoa, once again

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151 underlining the important role of sediments as a refuge. Maintenance of elevated FIB concentrations in sediments is of pract ical i mportance and has public health implications, as previous studies indicated potential for resuspension that can result in the increased concentrations in the water column (Kinzelman et al. 2004; Boehm & Weisberg, 2005; LaLiberte & Grimes, 1982; Ferguson et al. 2005; Craig et al. 2004; Fries et al. 2008; An et al. 2002) The simultaneous assessment of the effects of protozoan predation and seawater habitat on E. coli persistence in the water column indicated that protozoan grazing is the mo re important determinant of E. coli persi stence compared to sewater vs. fresh water habitats. Protozoan bacterivory is a recognized contributor to the decline of bacterial popul at io ns in aquatic environments (Beardsley et al. 2003; Menon et al. 2003; Rhodes & Kator, 1990; Iriberri et al. 1994; Gonzalez et al. 1992; Surbeck et al. 2010) ; however, the relative magnitude of impact of protozoan presence on E. coli survival in freshwater and seawater systems was not previously described. Understanding FIB ecol ogy in aquatic habitats is important, since current regulatory guidelines for the assessment of the recreational water qualit y are based solely on the water samples (American Public Healt h Association, 1999; Florida Administrative Code, 1998; United States Environmental Protection Agency, 2002b; United States Environmental Protection Agency, 2002a) Interestingly the same co mpar ison of the effects of protozoa vs. water type carri ed out in the sediments indicated that freshwater vs seawater habitat had a greater effect on E. coli persistence than prot ozoa presence. Previous works documented rel at ively low rates of protozoan grazing in sedime nt s com pared to the water column

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152 (Fi rst & Hollibaugh, 2008; Wieltschnig et al. 2008; Konigs & Cleven, 2007; Wieltschnig et al. 2003; Gucker & Fischer, 2 003; Hamels et al. 2001; Starink et al. 1996; Epstein & Shiaris, 1992) but detrimental effects of marine environments on bacterial survival in the sediments were rarely addressed. To the best of our knowledge, only one other study perform ed di rect com p arisons of FIB survival in freshwater vs saltwater sediments and showed extended persistence in the former (Anderson et al. 2005) However, the descript io n of the extent of impact of seawater habitat of E. c oli persi stence in the sediments in the presence of indigenous microbiota is novel. This finding implies that factors governing FIB persistence in different matrices (e.g. water column and sediments) are dissimilar and that wide generalizat io ns wi th th e re spect to the effect of environmental parameters on E. coli survival across habitats are unwise. The data collected in this study strongly indicate that protozoan predation i s one of th e main factors responsible for th e decline of culturable E. coli co nce nt rations in the water column ; however the magnitude of the protozoan predation is dependent on habitat characterist ic s (f reshwater vs seawater). Furthermore, results of this study indicate that differences between freshwater and seawater habit at are more important determinant of decline of culturable E. coli in t he sediments, and that protozoan predation in the freshwater habitats is matrix dependent (water column vs sediments) Alt hough utilit y o f E. coli extends beyo nd the water qualit y issues, as it is a recogni zed prokary oti c mo del organism, the principles governing its survival in the environment are less than clear. Better u nderstand ing of th e ecology of FIB in t he aquatic habitats is needed in order to improve predicti ons regarding their behavior in t he

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153 environment and d evelop better indicator systems for the assessment of the recreational water qualit y.

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154 References Allen, L.A., Grindley, J. & Brooks, E. (1953) Some Chemical and Bacterial Characteristics of Bottom Deposits fro m L akes and Estuaries. Journal of Hygiene 51 (2), 185 194. American Public Health Association (1999) Standard Methods for the Examinat io n of Water and Wastewater, Standard Method 9222D. An, Y.J., Kampbell, D.H. & Breidenbach, G.P. (2002) Escherichia coli and t otal coliforms in water and sediments at lake marinas. Environmental Pollution 120 (3), 771 778. Anderson, A., Larsson, U., Hagstrom, A. (1986) Si ze select ive grazing by a microflagellate on pelagic bacteria. Mar Ecol Prog Ser 33 51 57. Anderson, I.C., Rho des, M. & Kator, H. (1979) Sublethal Stress in Escherichia coli Funct io n of Salinit y. Applied and Environmental Microbiology 38 (6), 1147 1152. Anderson, I.C., Rhodes, M.W. & Kator, H.I. (1983) Seasonal Variat io n in Survival o f Escherichia coli Exposed In si tu in Membrane Diffusio n Chambers Containing Fil tered and Nonfiltered Estuarine Water. Applied and Environmental Microbiology 45 (6), 1877 1883. Anderson, K.L., Whitlock, J.E. & Harwood, V.J. (2005) Persistence and different ia l survival of fecal indicato r bacteria in subtropical waters and sediments. Appl Environ Microbiol 71 (6), 3041 3048. Barcina, I., Ayo, B., Muela, A., Egea, L. & Iriberri, J. (1991) Predation Rates of Flagellate and Ciliated Protozoa on Bacterioplankton in a River. Fems Microbiology E cology 85 (2), 141 149. Beardsley, C., Pernthaler, J., Wosniok, W. & Amann, R. (2003) Are readily culturable bacteri a in coastal North Sea waters suppressed by select ive grazing mortalit y? Applied and Environmental Microbiology 69 (5), 2624 2630. Beversdorf, L.J., Bornstein Forst, S.M. & McLellan, S.L. (2007) The potential for beach sand to serve as a reservoir for Escherichia coli and the physical influences on cell die of f. Journal of Applied Microbiology 102 (5), 1372 1381. Blattner, F.R., Plunkett, G., Blo ch, C.A., Perna, N.T., Burland, V., Riley, M., ColladoVides, J., Glasner, J.D., Rode, C.K., Mayhew, G.F., Gregor, J., Davis, N.W., Kirkpatrick, H.A., Goeden, M.A., Rose, D.J., Mau, B. & Shao, Y. (1997) The complete geno me sequence of Escherichia coli K 12. Science 277 (5331), 1453 1469.

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161 Whitman, R.L., Shively, D.A., Pawlik, H., Nevers, M.B. & Byappanahalli, M.N. (2003) Occurrence of Escherichia coli and entero co cci in Cladophora ( Chlorophyta ) in nearshore water and beach sand of Lake Michigan. Appl Environ Microbiol 69 (8), 4714 4719. Wieltschnig, C., Fischer, U.R., Kirschner, A.K.T. & Velimirov, B. (2003) Benthic bacteri al producti on and protozoan predation in a sil ty fr eshwater environment. Microbial Ecology 46 (1), 62 72. Wieltschnig, C., Fischer, U.R., Velimirov, B. & Kirschner, A.K.T. (2008) Effects of deposi t feeding macrofauna on benthic bacteria, viruses, and protozoa in a silt y freshwater sediment. Microb ial Ecology 56 (1), 1 12.

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162 APPENDICES

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Appendix A 163 Appendix A: Wakulla Count y FIB concentrations and MST marker distribut io ns by site 0 0. 5 1 1. 5 2 2. 5 3 1/25/2 00 5 2/15/20 05 3/ 8/200 5 3/ 22/ 20 05 4/5/200 5 4/ 26/20 07 5/ 3/200 5 5/17/20 05 6/ 14/ 20 05 1/8/20 07 1/ 24/20 07 2/ 7/200 7 2/21/2 00 7 3/13/20 07 3/ 26/ 20 07 4/ 10/20 07 4/ 24/20 07 Da te log 10 CFU/100 ml Figure A1. Mean of indicator organism concentratio ns ( lo g 10 transform ed ) and esp marker detection in the water co lu mn samples of MS site by sampling date (CFU/100 ml) Error bars represent standard deviat io ns. Fecal coliforms concentrations ( ); E. coli ( ); enterococci ( ). Verti cal lines represent regulatory guidelines for fecal co lifo rm s ( x ) (400 CFU / 100 ml) ; en terococci ( ) (104 CFU/ 100 ml) ; and fecal co lifo rm s shellfishing guidelines (•) (43 CFU / 100 ml ). Bl ue ci rcles represent esp marker detection.

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Appendix A (Continued) 164 0 0. 5 1 1. 5 2 2. 5 3 3. 5 1/25/2 00 5 2/15/20 05 3/ 8/200 5 3/ 22/ 20 05 4/5/200 5 4/ 26/20 07 5/ 3/200 5 5/17/20 05 6/ 14/ 20 05 1/8/20 07 1/ 24/20 07 2/ 7/200 7 2/21/2 00 7 3/13/20 07 3/ 26/ 20 07 4/ 10/20 07 4/ 24/20 07 Da te log 10 CFU/100 g F igure A 2. Mean of indicator organism concentratio ns ( lo g 10 transform ed) and esp marker detection in sed iment samples of MS site by sampling date (CFU/100 g wet wei ght). Error bars represent standard deviat io ns. Fecal co lifo rm s ( ); E. coli ( ); enterococci ( ). Blue circles represent esp marker detection.

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Appendix A (Continued) 165 -0.5 0 0.5 1 1.5 2 2.5 3 3.5 1/25/2 00 5 3/ 8/200 5 3/22/20 05 4/ 5/200 5 4/26/20 07 5/ 3/200 5 5/17/20 05 6/14/20 05 1/ 8/200 7 1/ 24/20 07 2/ 7/200 7 2/21/20 07 3/ 13/20 07 3/26/20 07 4/ 10/20 07 4/ 24/20 07 Da te log 10 CFU/100 ml Figure A3. Mean of indicator organism conc entrati on s (l og 10 transform ed) and esp marker detection in the water column samples of BR site by sampling date (CFU/100 ml). Error bars represent standard deviat io ns. Fecal coliforms ( ); E. coli ( ); enterococci ( ).Verti cal lines represent regulatory g ui delines for fecal coliforms ( x ) (400 CFU / 100 ml) ; enterococci ( ) (104 CFU/ 100 ml) ; and fecal co liforms shellfishing gui delines (•) (43 CFU / 100 ml ). Blue ci rcles represent esp marker detection.

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Appendix A (Continued) 166 0 1 2 3 4 5 6 7 1/25/2 00 5 3/ 8/200 5 3/22/20 05 4/ 5/200 5 4/26/20 07 5/ 3/200 5 5/17/20 05 6/14/20 05 1/ 8/200 7 1/ 24/20 07 2/ 7/200 7 2/21/20 07 3/ 13/20 07 3/26/20 07 4/ 10/20 07 4/ 24/20 07 Da te log 10 CFU/100 g Figure A4. Mean of indicator organism concentratio ns (l og 10 transform ed) and esp marker detection in sediment samples of BR site by sampling date (CFU/100 g wet wei ght). Error bars represent standard deviat io ns. Fecal co lifo rm s concentrati ons ( ); E. coli ( ); enterococci ( ).Bl ue ci rcles represent esp m arker detection.

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Appendix A (Continued) 167 0 0. 5 1 1. 5 2 2. 5 3 1/25/2 00 5 2/15/20 05 3/ 8/200 5 3/ 22/ 20 05 4/5/200 5 4/ 26/20 07 5/ 3/200 5 5/17/20 05 6/ 14/ 20 05 1/8/20 07 1/ 24/20 07 2/ 7/200 7 2/21/2 00 7 3/13/20 07 3/ 26/ 20 07 4/ 10/20 07 4/ 24/20 07 Da te log 10 CFU/100 ml Figure A 5. Mean of indicator organism concentratio ns ( lo g 10 transform ed) and esp marker detection in the water column samples of 319 site by sampling date (CFU/100 ml). Error bars represent standard deviat io ns. Fecal coliforms con centrati ons ( ); E. coli ( ); enterococci ( ).Verti cal lines represent regulatory guidelines for fecal co lifo rm s ( x ) (400 CFU / 100 ml) ; enterococci ( ) (104 CFU/ 100 ml) ; and fecal co liforms shellfishing gui delines (•) (43 CFU / 100 ml ). Blue ci rcles represe nt esp marker detection.

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Appendix A (Continued) 168 0 0. 5 1 1. 5 2 2. 5 3 3. 5 4 1/25/2 00 5 2/15/20 05 3/ 8/200 5 3/ 22/ 20 05 4/5/200 5 4/ 26/20 07 5/ 3/200 5 5/17/20 05 6/ 14/ 20 05 1/8/20 07 1/ 24/20 07 2/ 7/200 7 2/21/2 00 7 3/13/20 07 3/ 26/ 20 07 4/ 10/20 07 4/ 24/20 07 Da te log 10 CFU/100 g Figure A 6. Mean of indicator organism concentratio ns ( lo g 10 transform ed) and esp marker detection in sediment samples of 319 site by sampling date (CFU/100 g wet wei ght). Error bars represent standard deviat io ns. Fecal co lifo rm s concentrati ons ( ); E. coli ( ); enterococci ( ). Bl ue ci rcles represent esp marker detection.

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Appendix B 169 Appendix B: Hillsborough County FIB concentr atio ns, MST marker di stribut io n and pathogen detection by site -0. 5 0 0. 5 1 1. 5 2 2. 5 3 3. 5 8/8/200 6 8/29/20 06 9/12/20 06 9/26/20 06 10 /31 /2 006 12 /19 /2 006 1/23/20 07 2/6/200 7 3/6/200 7 9/5/200 7 9/25/20 07 10 /29 /2 007 4/22/ 20 08 5/6/200 8 5/20/20 08 6/10/20 08 Da te log 10 CFU/100 ml Figure B1. Mean of indicator organi sm concentratio ns ( lo g 10 transform ed), MST m arker and pathogen detection in the water column samples of BH site by sampling date (CFU/100 ml). Error bars represent standard deviatio ns. Fecal co liforms concentrations ( ); E. coli ( ); enterococci ( ).Verti cal lines represent regulatory guidelines for fecal coliforms ( x ) (400 CFU / 100 ml) ; enterococci ( ) (104 CFU/ 100 ml) ; and fecal co liforms shellfishing guidelines (•) (43 CFU / 100 ml ). Bl ue ci rcles represent esp marker detection, and orange circles represent HPyV marker detection

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Appendix B (Continued) 170 0 0. 5 1 1. 5 2 2. 5 3 3. 5 8/8/20 06 8/ 29/ 20 06 9/ 12/ 20 06 9/ 26/ 20 06 10 /31 /2 006 12 /19 /2 006 1/23/20 07 2/ 6/200 7 3/ 6/200 7 9/ 5/200 7 9/25/2 00 7 10 /29 /2 007 4/22/2 00 8 5/ 6/200 8 5/20/20 08 6/10/20 08 Da te log 10 CFU/100 g Figure B2. Mean of indicator organism concentratio ns ( lo g 10 transform ed) and MST marker detection in sediment samples of BH site by sampling date (CFU/100 g wet wei ght). Error bars represent standard deviat io ns. Fecal co lifo rm s concentrati ons ( ); E. coli ( ); enterococci ( ).Bl ue ci rcles represent esp marker detection.

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Appendix B (Continued) 171 0 1 2 3 4 5 6 5/9/20 06 6/ 27/ 20 06 7/ 18/ 20 06 9/5/200 6 10 /17 /2 006 11 /7 /2 00 6 1/16/20 07 3/20/20 07 7/23/20 07 9/ 5/200 7 9/25/2 00 7 10 /29 /2 007 4/22/2 00 8 5/ 6/200 8 5/20/20 08 6/10/20 08 Da te log 10 CFU/100 ml Figure B3. Mean of indicator organism concentratio ns ( lo g 10 transform ed), MST m arker and pathogen detection in the water column samples of BTD 1 si te by sampling date (CFU/100 ml). Error bars represent standard deviatio ns. Fecal co liforms concentrations ( ); E. coli ( ); enterococci ( ).Verti cal lines represent regulatory gui delines for fecal coliforms ( x ) (400 CFU / 100 ml) ; enterococci ( ) (104 CFU/ 100 ml) ; and fecal co liforms shellfishing guidelines (•) (43 CFU / 100 ml ). Bl ue c ir cles represent esp marker detection, orange circles represent HPyV marker detection, and red circles represent enterovi rus detecti on.

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Appendix B (Continued) 172 0 1 2 3 4 5 6 5/9/20 06 6/ 27/ 20 06 7/ 18/ 20 06 9/5/200 6 10 /17 /2 006 11 /7 /2 00 6 1/16/20 07 3/20/20 07 7/23/20 07 9/ 5/200 7 9/25/2 00 7 10 /29 /2 007 4/22/2 00 8 5/ 6/200 8 5/20/20 08 6/10/20 08 Da te log 10 CFU/100 g Figure B4. Mean of indicator organism concentratio ns ( lo g 10 transform ed) and MST marker detection in sediment sam ples of BTD 1 si te by sampling date (CFU/100 g wet wei ght). Error bars represent standard deviat io ns. Fecal co lifo rm s concentrati ons ( ); E. coli ( ); enterococci ( ).Bl ue ci rcles represent esp marker detection.

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Appendix B (Continued) 173 0 0. 5 1 1. 5 2 2. 5 3 3. 5 4 4. 5 5/9/20 06 6/ 27/ 20 06 7/ 18/ 20 06 9/5/200 6 10 /17 /2 006 11 /7 /2 00 6 1/16/20 07 3/20/20 07 7/23/20 07 9/ 5/200 7 9/25/2 00 7 10 /29 /2 007 4/22/2 00 8 5/ 6/200 8 5/20/20 08 6/10/20 08 Da te log 10 CFU/100 ml Figure B5. Mean of indicator orga nism concentratio ns ( lo g 10 transform ed), MST m arker and pathogens detection in the water column samples of BTD 2 si te by sampling date (CFU/100 ml). Error bars represent standard deviatio ns. Fecal co liforms concentrations ( ); E. coli ( ); enterococci ( ). Vertical lines represent regulatory guidelines for fecal coliforms ( x ) (400 CFU / 100 ml) ; enterococci ( ) (104 CFU/ 100 ml) ; and fecal co liforms shellfishing guidelines (•) (43 CFU / 100 ml ). Bl ue ci rcles represent esp marker detection.

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Appendix B (Continued) 174 0 0. 5 1 1. 5 2 2. 5 3 3. 5 4 4. 5 5/9/20 06 6/ 27/ 20 06 7/ 18/ 20 06 9/5/200 6 10 /17 /2 006 11 /7 /2 00 6 1/16/20 07 3/20/20 07 7/23/20 07 9/ 5/200 7 9/25/2 00 7 10 /29 /2 007 4/22/2 00 8 5/ 6/200 8 5/20/20 08 6/10/20 08 Da te log 10 CFU/100 g Figure B6. Mean of indicator organism concentratio ns ( lo g 10 transform ed) and MST marker detection in s ediment sam ples of BTD 2 si te by sampling date (CFU/100 g wet wei ght). Error bars represent standard deviat io ns. Fecal co lifo rm s concentrati ons ( ); E. coli ( ); enterococci ( ). Bl ue ci rcles represent esp marker detection.

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Appendix B (Continued) 175 0 0. 5 1 1. 5 2 2. 5 3 3. 5 4 4. 5 5/9/20 06 6/ 27/ 20 06 7/ 18/ 20 06 9/5/200 6 10 /17 /2 006 11 /7 /2 00 6 1/16/20 07 3/20/20 07 7/23/20 07 9/ 5/200 7 9/25/2 00 7 10 /29 /2 007 4/22/2 00 8 5/ 6/200 8 5/20/20 08 6/10/20 08 Da te log 10 CFU/100 ml Figure B 7. Mean of indic ator organi sm concentratio ns ( lo g 10 transform ed), MST m arker and pathogen detection in the water column samples of BTD 3 si te by sampling date (CFU/100 ml). Error bars represent standard deviatio ns. Fecal co liforms concentrations ( ); E. coli ( ); enter oc occi ( ).Verti cal lines represent regulatory gui delines for fecal coliforms ( x ) (400 CFU / 100 ml) ; enterococci ( ) (104 CFU/ 100 ml) ; and fecal co liforms shellfishing guidelines (•) (43 CFU / 100 ml ). Bl ue ci rcles represent esp marker detection and orange ci rcles represent HPy V marker detection.

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Appendix B (Continued) 176 0 1 2 3 4 5 6 5/9/20 06 6/ 27/ 20 06 7/ 18/ 20 06 9/5/200 6 10 /17 /2 006 11 /7 /2 00 6 1/16/20 07 3/20/20 07 7/23/20 07 9/ 5/200 7 9/25/2 00 7 10 /29 /2 007 4/22/2 00 8 5/ 6/200 8 5/20/20 08 6/10/20 08 Da te log 10 CFU/100 g Figure B8. Mean of indicator organism concentratio ns ( lo g 10 transform ed) and MST marker detection in sediment samples of BTD 3 si te by sampling date (CFU/100 g wet wei ght). Error bars represent standard de viat io ns. Fecal co lifo rm s concentrati ons ( ); E. coli ( ); enterococci ( ).Bl ue ci rcles represent esp marker detection.

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Appendix B (Continued) 177 0 0. 5 1 1. 5 2 2. 5 3 3. 5 4 4. 5 5 5/9/20 06 6/ 27/ 20 06 7/ 18/ 20 06 9/5/200 6 10 /17 /2 006 11 /7 /2 00 6 1/16/20 07 3/20/20 07 7/23/20 07 9/ 5/200 7 9/25/2 00 7 10 /29 /2 007 4/22/2 00 8 5/ 6/200 8 5/20/20 08 6/10/20 08 Da te log 10 CFU/100 ml Figure B9. Mean of indicator organism concentratio ns ( lo g 10 transform ed) MST marker and pathogen detection in the water column s amples of BTD 4 si te by sampling date (CFU/100 ml). Error bars represent standard deviatio ns. Fecal co liforms concentrations ( ); E. coli ( ); enterococci ( ).Verti cal lines represent regulatory gui delines for fecal coliforms ( x ) (400 CFU / 100 ml) ; enter o co cci ( ) (104 CFU/ 100 ml) ; and fecal co liforms shellfishing guidelines (•) (43 CFU / 100 ml ). Bl ue ci rcles represent esp marker detection and orange circles represent HPyV marker detection.

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Appendix B (Continued) 178 0 1 2 3 4 5 6 5/9/20 06 6/ 27/ 20 06 7/ 18/ 20 06 9/5/200 6 10 /17 /2 006 11 /7 /2 00 6 1/16/20 07 3/20/20 07 7/23/20 07 9/ 5/200 7 9/25/2 00 7 10 /29 /2 007 4/22/2 00 8 5/ 6/200 8 5/20/20 08 6/10/20 08 Da te log 10 CFU/100 g Figure B10. Mean of indicator organism concentrations (lo g 10 transform ed) and MST marker detection in sediment samples of BTD 4 si te by sampling date (CFU/100 g wet wei ght). Error bars represent standard deviat io ns. Fecal co lifo rm s concentrati ons are represented by striped bars ( ); E. coli concentrations are represented by dotted bars ( ); enterococci concentrations are represented by bars with diagonal lines ( ). Blue circles represent esp marker detection.

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Appendix C 179 Appendix C: E. coli concentrations in water (log 10 CFU/100 ml) and sediments (log 10 C FU/100 g) of freshwater and sea water m esocosms by strain 0 1 2 3 4 5 6 7 8 9 10 T0 T1 T2 T3 T5 T7 T9 T11 T1 3 T1 5 Time log 10 CFU/100 ml/g Figure C1: Mean concentrations (log 10 transform ed) f or HS strain. Error bars represent standard deviations fo r three replicates Freshwater concentrations: water col umn ( ), sediment ( ). Seawater concentra ti ons: water col umn ( ), sediment ( ).

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Appendix C (Continued) 180 0 1 2 3 4 5 6 7 8 9 10 T0 T1 T2 T3 T5 T7 T9 T11 T1 3 T1 5 Time log 10 CFU/100ml/g Figure C2: Mean concentrations (log 10 transform ed) f or SMS 35 strain. Error bars represent standard deviations fo r three replicates Freshwater concentrations: water col umn ( ), sediment ( ). Seawater con centr ati ons: water col umn ( ), sediment ( ).

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Appendix C (Continued) 181 0 1 2 3 4 5 6 7 8 9 10 T0 T1 T2 T3 T5 T7 T9 T11 T1 3 T1 5 Time log 10 CFU/100ml/g Figure C3. Mean concentrations (log 10 transformed) for WW6 strain. Error bars represent standard deviations fo r three replicates Freshwater concentrations: water col umn ( ), sediment ( ). Seawater co ncentrat io ns: water column ( ), sediment ( ).

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Appendix C (Continued) 182 0 1 2 3 4 5 6 7 8 9 10 T0 T1 T2 T3 T5 T7 T9 T11 T1 3 T1 5 Time log 10 CFU/100ml/g Figure C4: Mean concentrations (log 10 transform ed) f or ATCC 8739 strain. Error bars represent standard deviations fo r three replicates Freshwater concentrations: water col umn ( ), sediment ( ). Seawater co ncent rati ons: water col umn ( ), sediment ( ).

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Appendix C (Continued) 183 0 1 2 3 4 5 6 7 8 9 10 T0 T1 T2 T3 T5 T7 T9 T11 T1 3 T1 5 Time log 10 CFU/100ml/g Figure C5: Mean concentrations (log 10 transform ed) f or MG 1655 strain. Error bars represent standard deviations fo r three replicates Freshwater concentrations: w ater col umn ( ) sediment ( ). Seawat er concen trati ons: water col umn ( ), sediment ( ).

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ABOUT THE AUTHOR A sja Korajkic was born in t he former Yugoslavia and she mo ved to the USA in 1998. In the fall semester of 2004, she received her Bachelor of Science degree with the concentration i n Microbio lo gy fro m t he Univerist y of South Florida (USF) Immediately af ter receiving her B.S. degree, she was accepted in the graduate program in t he Bio lo gy Departm ent at USF, in the water qualit y/environmental microbio lo gy laboratory of Dr Val erie J. H arwood During the course of her graduate studies, she was emplo yed as a research assistant, and later project manager, on numerous research studies investigating water qualit y and field applicat io n of microbial source tracking techniques. She was also em p lo yed by the Bi ol ogy Departm ent at USF as a teaching assistant for a variet y o f laboratories, including General Microbio lo gy Determinat ive Bacteriology and Microbial Physio lo gy and Genetics. She presented her research work at several nat io nal and regi onal meetings of the American Societ y fo r Microbiology as well as Biennial Storm water Associ at io n me eting. S he is a published author in the peer reviewed journals, and her research was also published in the conference proceedings paper. Asja is also a rec ip ie nt of th e fo llo wing awards : Tharp Summer Fellowship (USF 2010) Fl ori da Storm water Associ at io n Scho larship (FSA 2008) 107 th g eneral meet ing of the ASM and Southeastern branch of the ASM (2005, 2008) travel grant s fo r an outstanding abstract (ASM 2007) an d The Fourth Annual Graduate Research Symposium (USF 2005) grant for an outstanding presentation