Presentation is loading. Please wait.

Presentation is loading. Please wait.

How well do indicator bacteria estimate Salmonella in freshwater streams? Timothy M. Smith, Zsofia Jakab, Sarah F. Lucento, David W. Buckalew Department.

Similar presentations


Presentation on theme: "How well do indicator bacteria estimate Salmonella in freshwater streams? Timothy M. Smith, Zsofia Jakab, Sarah F. Lucento, David W. Buckalew Department."— Presentation transcript:

1 How well do indicator bacteria estimate Salmonella in freshwater streams? Timothy M. Smith, Zsofia Jakab, Sarah F. Lucento, David W. Buckalew Department of Biological and Environmental Sciences Longwood University Farmville, VA 23909 Introduction Use of ‘total coliform’ and ‘fecal coliform/thermotolerant coliform’ bacteria as environmental risk indicators for the presence of fecal-associated pathogens has been used since the early 20 th Century (Eijkman, 1904; Leiter, 1929). The most recent USEPA guideline (2012) for water monitoring recommends the use of these indicator bacteria since “it is difficult, time-consuming, and expensive to test for specific pathogens”. While some studies suggest the relationship between coliforms and pathogen is somewhat clear and positive for protozoan pathogens ( Hogan et al., 2012 ), for human viruses (McQuaig et al., 2012 ), and for bacterial pathogens (Efstratiou et al., 1998) others show a weak to no correlation (DePaola et al., 2010; Schriewer et al., 2010). The questions we have addressed include: How effective are indicator bacteria such as total coliforms and/or E. coli in predicting the counts of potential pathogens, specifically Salmonella species, in freshwater streams in south-central Virginia? We chose Salmonella as it is considered the cause of the largest number of enteric infections worldwide. Methods Bacterial Isolation and Enumeration Water samples were collected from three locations: Appomattox River (APP2), Sayler’s Creek (SAY5), and Green Creek (GRE16). All samples were processed for Salmonella and for Total Coliform (TC) and E. coli (EC). Salmonella enrichment and analysis: Membrane filtration Results Table 1 provides both pooled and composite averages for each of the three sampling sites. Figures 1, 2, and 3 illustrate the proportion of each bacterial group per sample date at each of the three sampling sites – APP2 (Fig 1; n=29), Say5 (Fig. 2; n=31), and GRE16 (Fig. 3; n=30). Total Coliform and E. coli enumeration: Colilert defined substrates medium + + + + + - - Membrane labeled (+) for Salmonella spp. and (-) for others Statistical Analyses and Data presentation For each Salmonella enumeration, the average colony counts of two 1 mL field duplicate samples was taken and multiplied by 100 to represent the number of suspect Salmonella spp. present per 100 mL standard volume. All enumerations of TC and EC were also recorded with respect to 100 mL volumes for all samples tested. Bacterial count data was recorded and illustrated by the use of stacked column graphs (see Fig.’s 1, 2, and 3 below). Since all Salmonella – indicator comparisons (e.g., Sal vs TC and Sal vs EC) at each sample site were significantly different by Student t-test comparisons(p<0.05), a Pearson r correlation combined with a linear regression analysis was performed to determine the degree of correlation between counts of Salmonella spp. and indicator bacteria across the 18 months of the study. Courtesy of Oxoid™ website An example of (+) agglutination from this experiment Discussion Although not all of our data show positive correlations between fecal indicator bacteria and Sal species, the majority of our samples revealed a positive correlation between numbers of EC and numbers of Sal in the watershed of the upper Appomattox River. EC concentrations are generally 1 order of magnitude less than Salmonella concentrations, but as E.coli increases, so does Salmonella. The relationship between any one group of free-living bacteria and any other within the external environment cannot be perfectly linear as there exist a constellation of functional parameters relating to differential survivorship. The ecology and environmental survival characteristics of bacterial, viral, and parasitic enteropathogens vary suggesting that no single indicator organism or group can consistently predict the presence of all enteric pathogens. Fecal indicator bacteria (Coliforms, Fecal Coliforms, E.coli, and Enterococci) have been used to assess biological quality of environmental and potable water since the early 20 th Century and they have adequately withstood the test of time. Microbial monitoring using only fecal indicator bacteria may not be sufficient for each particular pathogen, but they may have a high degree of predictive value if relationships are examined with respect to specific pathogen and environment. Bacterial counts from both the Appomattox River and Green Creek sites reveal significant (p<0.05) and linear relationships between bacterial indicator and Salmonella. The relationship between EC and Sal counts for APP2 and GRE16 produced R 2 values of 0.458 and 0.338, respectively (Fig’s 4 and 5) and Pearson correlation coefficients of 0.722 and 0.471, respectively (Table 2). These relationships were not observed between the Sayler’s Creek bacterial counts (see Fig 6 and Table 2). LONGWOOD UNIVERSITY Department of Biological and Environmental Sciences Indicator Bacteria used for assessing water quality: Escherichia coli (EC), Klebsiella spp., Enterobacter spp., and Citrobacter spp. Common human pathogens transferred via water: Bacterial pathogens: Salmonella* Campylobacter Listeria Protozoan pathogens: Giardia Entamoeba Cryptosporidium Viral pathogens: Coxsackievirus Hepatitis A Rotavirus Norovirus Picornaviridae Reoviridae Caliciviridae Why test for indicators of water quality? Filter membrane with Salmonella growth MPN for total coliforms counting chromogenic ONPG + MPN for E. coli counting fluorescent MUG + Salmonella (Sal)Coliforms (TC)E.coli (EC) Pooled data (n=90)3878.7 ± 36751202.5 ± 1686.2349.8 ± 486.6 APP 2 site (n=29)2836.2 ± 1696.4803.7 ± 1139136.2 ± 96.8 GRE 16 site (n=30)4850 ± 50941551.8 ± 1873599.5 ± 754.7 SAY 5 site (n=31)3882.3 ± 32091237.7 ± 1885.2307.9 ± 186.6 Table 1. Overview of data set: Pooled and site-by-site means ± std. dev. Figure 1. Proportional view of TC vs EC vs Sal counts per sample from the Appomattox River sampling site; 29 total samples Figure 2. Proportional view of TC vs EC vs Sal counts per sample from the Sayler’s Creek sampling site; 31 total samples LONGWOOD UNIVERSITY Department of Biological and Environmental Sciences Figure 3. Proportional view of TC vs EC vs Sal counts per sample from the Green Creek sampling site; 30 total samples Pearson r coeff. Appomattox RiverWarm months Cold months Composite Sal vs Coliform-0.0100.075 0.279 Sal vs EC0.692 0.7000.722 Green Creek Sal vs Coliform0.185 0.7400.423 Sal vs EC0.414 0.5680.471 Sayler's Creek Sal vs Coliform-0.061-0.292 0.169 Sal vs EC0.132 0.2560.131 Courtesy of Oxoid™ website Graphics courtesy of www.Wikipedia.org Figure 4. Comparison of numbers of E.coli and Salmonella from the same water samples obtained from APP2 collection site. Figure 5. Comparison of numbers of E.coli and Salmonella from the same water samples obtained from GRE16 collection site. Figure 6. Comparison of numbers of E.coli and Salmonella from the same water samples obtained from SAY5 collection site. Table 2. Pearson correlations comparing Salmonella counts with both Coliform and E.coli counts in warm weather, cold weather, and composite samples. Literature cited DePaola, A. et al. 2010. Bacterial and viral pathogens in live oysters: 2007 United States Market survey. AEM. 76: 2754-2768. Eijkman, E. 1904. Die Garungsprobe be 46 als Hilfsmittel bei der Trinkwasseruntersuchung. Zentralbl. Bakteriol. Parasitenkd. Infectionskr. Hyg. Abt. 1 Orig. 37: 742-752. Hogan, J.N. et al. 2012. Longitudinal Poisson regression to evaluate the epidemiology of Cryptosporidium, Giardia, and fecal indicator bacteria in coastal California wetlands. AEM. 78: 3606-3613. Leiter, W.L. 1929. The Eijkman fermentation test as an aid in the detection of fecal organisms in water. Amer. J. Hyg. 9: 705-734. McQuaig, S. et al. 2012. Association of fecal indicator bacteria with human viruses and microbial source tracking markers at coastal beaches impacted by non-point source pollution. AEM. 78: 6423-6432. Schriewer, A. 2010. Presence of Bacteroidales as a predictor of pathogens in surface waters of the central California Coast. AEM. 76: 5802- 5814. USEPA 2012. Water monitoring and assessment 5.11 Fecal Bacteria. See: http://water.epa.gov/type/rsl/monitoring/vms511.cfmhttp://water.epa.gov/type/rsl/monitoring/vms511.cfm


Download ppt "How well do indicator bacteria estimate Salmonella in freshwater streams? Timothy M. Smith, Zsofia Jakab, Sarah F. Lucento, David W. Buckalew Department."

Similar presentations


Ads by Google