Vibrio parahaemolyticus : Incidence, Growth and Survival in Chesapeake Bay Oysters

1. Vibrio parahaemolyticus:Incidence, Growth and Survival in Chesapeake Bay Oysters Salina Parveen, Ph.D. Food Science and Technology Program Department of Agriculture, Food and Resource Sciences University of Maryland Eastern Shore Princess Anne, Maryland

2. Introduction • Vibrio parahaemolyticus (Vp) is a Gram-negative halophillic rod • Grow on or in ordinary media containing 1-8% NaCl • Highly motile in liquid media with polar flagellum • Grow well from 25 to 44°C (Oliver and Kaper 2001)

3. Introduction • Optimum temperature for growth is 37°C • Can not proliferate below 10°C • Occurs naturally in marine, coastal and estuarine environments • Isolated from seawaters, sediments and seafoods (Oliver and Kaper 2001)

4. Introduction • A significant cause of bacterial seafood-borne illness • U.S. CDC estimates ~7,880 Vibrio illnesses/year • ~2,800 are estimated to be associated with Vp and raw oyster consumption • Common symptom-gastroenteritis with occasional bloody diarrhea • Primary septicemia- individuals with underlying chronic illness (US FDA 2005)

5. Introduction • Pathogenic and non-pathogenic strains • Pathogenic strains of Vp produce a thermostable direct hemolysin (TDH) and thermostable related hemolysin (TRH) • 95% of clinical strains produce TDH and TDH was also detected in 47% of oysters • A number of significant Vp illness outbreaks have been reported in the U.S. • Recently, two cases of Vp infections have been reported from Chesapeake Bay oysters (CDC 1999; Blackstone et al. 2003; Food safety network 2006; Anon. 2008)

6. Introduction • Several investigators reported the incidence of Vp in the Gulf and Pacific coasts • Seasonal cycle of Vp in sediment and water in the U.S. was first reported by Kaneko and Colwell • Reported that densities of total and pathogenic Vp in shellfish at harvest were directly related to harvest water temperature • No information is available about the incidence of total and pathogenic Vpin Chesapeake Bay oysters (Kaneko and Colwell, 1973, 1975; Kaysner et al. 1990; DePaola et al. 2003)

7. Introduction • Recently, Food and Drug Administration (FDA) has published risk assessments for Vp in raw oysters • Identified data gaps that increase the uncertainty of risk assessments • Lack of predictive models for the growth and survival of total and pathogenic Vp in oysters (Miles et al. 1997; US FDA 2005)

8. Introduction • Risk assessments have had to make very board extrapolations from bacteriological broth-studies • Effects of temperature and time on the growth and survival of Vp in post-harvest oysters • A single harvest region, limited seasons and to one specific storage temperature • Harvest region, season and the harvest water conditions influence subsequent Vpgrowth andsurvival during storage (Gooch et al. 2002)

9. Objectives • To determine the incidence of total and pathogenic Vp in oysters and waters in the Chesapeake Bay • To examine the correlation of Vp levels in oysters and waters with environmental parameters • To develop predictive models for the growth and survival of total and pathogenic Vp in oysters as a function of temperature

10. Objectives • To validate the models with model-independent data, considering season of harvest, geographical harvest area, harvest water salinity and temperature well as Asian oysters • To compare the growth and survival of total and pathogenic Vp in American and Asian oysters

11. Methodology Collection of Samples • Oysters (American oyster, Crassostrea virginica) were collected from the Chesapeake Bay, MD and Gulf Coast, AL • Asian Oysters (C. ariakensis) were collected from the Chesapeake Bay, VA • Water temperature, salinity, pH and conductivity were measured, with a model 85 dissolved oxygen conductivity meter (Cook et al. 2002)

12. Mobile Bay Mississippi Sound Methodology Sampling Sites Cedar Point Chesapeake Bay Sampling Sites Gulf of Mexico

13. Methodology • Chlorophyll content was measured by using YSI chlorophyll sensor • Fecal coliforms by standard methods • Water samples were collected in sterile 1-liter wide mouth containers After harvest, the oysters were shipped to the laboratory • All microbiological analyses were initiated within 24 hours of sample collection (Cook et al. 2002)

14. Methodology • Incidence Study • Two separate set of samples of 12 oysters each were analyzed • Growth and Survival Study • Oysters were stored at 5, 10, 15, 20, 25 and 30°C • At selected time intervals, two separate set of samples of 6 oysters each were analyzed

15. Methodology • Preparation of Samples • 12 or 6 oysters (scrubbed, shucked) • Added phosphate buffered saline (PBS) and blended for 90s • Serial 10-fold dilutions were prepared in PBS (DePaola and Kaysner 2004)

16. Methodology Bacteriological Analysis-A Direct Plating-Colony Hybridization Original homogenate and 10-fold serial dilutions spread plated on T1N3 Incubated 16-18 hr at 35C colony lifts Hybridization (tlh & tdh), colorimetric detection and enumeration Colonies of Vp (DePaola and Kaysner 2004)

17. Multiplex Real Time PCR (q-PCR) Three tubes Most Probable Number (MPN) Method Enrich oyster homogenate in APW (Alkaline peptone water) Boil for 10 min. Analyze by q-PCR (tdh and trh genes) (Nordstrom et al. 2007)

18. Methodology Primary and Secondary Model Development • log10 values and mean and standard deviation were plotted with Excel spread sheet software • The dynamic model described by Baranyi and Roberts (1994) was used to fit curves to the experimental data and to estimate values for the primary parameters-using DMFit curve-fitting software • lag phase duration (LPD [h]) • growth/inactivation rate (GR [log CFU/h]) • Maximum population density (MPD [log CFU/g])

19. Methodology • Secondary model was produced using Table Curve 2D (SPSS Inc., Chicago, IL) with built-in and customized equations • The Ratkowsky square root model was used to model GR • Model performance was measured by bias (Bf) and accuracy (Af) factors • Statistical analysis-Regression analysis (Baranyi et al. 1999)

20. Results and Discussion Incidence of total Vp in oysters at three sites in Chesapeake Bay BC:Broad Creek; Chester River:CR; Eastern River (ER) (Parveen et al. 2008)

21. Detection of Vp in oyster and water samples by Direct-plating and real-time PCR (q-PCR)(June to October)

22. Results and Discussion 30°C 5°C 15°C The inactivation/growth profile of total Vp in shell stock oysters at 5, 15 and 30°C with primary curve fitting (Chesapeake Bay, 2005)

23. Results and Discussion Storage GR LPD MPD Temperature (log CFU/h) (h) (CFU/g) (°C) 2005 2006 2005 2006 2005 2006 5 10 15 20 25 30 -0.002 -0.001 0.054 0.107 0.280 0.264 -0.001 -0.002 0.022 0.058 0.177 0.175 ND ND ND ND 10.66 4.07 ND ND ND ND ND ND CNBD CNBD 4.55 5.05 6.03 5.40 CNBD CNBD 4.40 6.50 6.69 5.52 Primary growth/inactivation parameters for the temperature ranged from 5-30°C. GR- Growth/inactivation rate; LPD- Lag phase duration; MPD-Maximum population density; ND-Not detected; CNBD-Could not be determined

24. Results and Discussion Predicted and observed growth rate (GR) of total Vp in shell stock oysters CB-Chesapeake Bay

25. Results and Discussion Model Performance-Bias (Bf) and Accuracy (Af) Factors Bf=exp Where m is number of observations, p is predicted, o is observed and μ is growth rate Af=exp Bf=1.00 Af=1.03

26. Results and Discussion Predicted and observed growth rate (GR) of total Vp in shell stock oysters CB-Chesapeake Bay; GC-Gulf Coast

27. Results and Discussion Validation of Models Oysters Bf Af 1.04 1.05 1.06 1.05 CB-American oysters CB-Asian oysters GC-American oysters Combined 1.02 1.02 1.03 1.02

28. Results and Discussion P>0.05 Effects of harvest temperature and salinity on growth rate

29. Results and Discussion P> 0.05 P>0.05 P> 0.05Effects of harvest regions/seasons on growth rate

30. Results and Discussion Comparison of growth and survival of total and pathogenic Vp in American oysters

31. Results and Discussion Comparison of growth and survival of total and pathogenic Vp in Asian oysters

32. Results and Discussion Comparison of growth and survival of total and pathogenic Vp in American and Asian oysters

33. Conclusions • Total Vp was detected in 79% of the samples using direct plating-colony hybridization method at densities ranging from 1.5x101 to 6.0x102 cfu/g • Levels of total Vp at all sites followed a seasonal trend with higher levels in the warmer months • Real time PCR was able to detect significant number of pathogenic Vp in water samples

34. Conclusions • Total Vp was slowly inactivated at 5°C and 10°C • Maximum GR was observed at 25°C • MPD displayed a peak form at 25°C • No significant LPD was observed • The bias (Bf) and accuracy (Af) factors were 1.00 and 1.03, respectively

35. Conclusions • The Bf and Af factors for the growth rates determined in Gulf Coast oysters during the summer, fall and spring were 1.02 and 1.04; 1.02 and 1.04 and 1.03 and 1.07, respectively • The Bf and Af factors for the growth rates in Asian oysters were 1.02 and 1.05, respectively • These results suggest that the model developed for the growth and survival of total Vp in Chesapeake Bay oysters are valid for, and predictive of, growth occurring in oysters harvested from Gulf Coast over multiple seasons as well as in Asian oysters • Harvest region/season, temperature and salinity had no effects on GR

36. Conclusions • GR of pathogenic Vp were higher than those observed for totalVp in American and Asian oysters at 10,15, 20, 25, & 30°C • These results also indicate that total and pathogenic Vp multiplied more rapidly in American oysters than Asian oysters • The results of this study will assist risk managers and the seafood industry in designing more effective food safety systems • Further confirmation and mechanism of pathogenic Vp GR require additional study as this may substantially affect risk predictions and impact of controls

37. Current Studies • Development of predictive models for the growth and survival of pathogenic Vp in oysters • Development of predictive models for the growth and survival of V. vulnificus (Vv) in oysters • Investigation of the effects of storage condition on sensory and textural characteristics of oysters

38. Future Studies • Secondary models will be incorporated into spreadsheet format and into the USDA Pathogen Modeling Program (PMP; www.arserrc.gov/mfs/pathogen.htm) • Raw data sets will be archived in ComBase (http://wyndmoor.arserrc.gov/combase/), an international database of predictive microbiology information

39. Acknowledgements FDAMDEVIMS Angelo DePaola Kathy Brohawn S. Allen John Bowers Bill Beatty Jessica Jones John McKay Jeff Krantz and others Univ. of Tasmania, Australia Mark Tamplin The Maryland Watermen’s Association,Inc. UMES Ligia DaSilva Chanelle White Apsara Hettiarachchi Meshack Mudoh Jurgen Schwarz Tom Rippen Geoff Rutto United States Department of Agriculture National Research Initiative grant # 2006-35201-16644

40. Thank you!

41. QUESTIONS ???