Development of a novel cross-streaking method for isolation, confirmation, and enumeration of Salmonella from irrigation ponds

Luo, Zhiyao; Gu, Ganyu; Giurcanu, Mihai; Adams, Paige; Vellidis, George; Bruggen, A.H.C. van; Wright, Anita C.

doi:10.1016/j.mimet.2014.03.012

Cited by 15 publications

(19 citation statements)

References 26 publications

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“…We used a most-probable-number (MPN) enumeration protocol for Salmonella developed by Luo et al (2014). Briefly, three replicates of three sample volumes (500 ml, 100 ml, and 10 ml) were analysed for each composite, resulting in a total of nine replicates analysed per composite.…”

Section: Methodsmentioning

confidence: 99%

Impact of storm runoff onSalmonellaandEscherichia coliprevalence in irrigation ponds of fresh produce farms in southern Georgia

et al. 2018

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Aims: To examine Salmonella and Escherichia coli in storm runoff and irrigation ponds used by fresh produce growers, and compare Salmonella serovars with those found in cases of human salmonellosis. Methods and Results: We collected water before and after rain events at two irrigation ponds on farms in southern Georgia, USA, and collected storm runoff/storm flow within the contributing watershed of each pond. Salmonella and E. coli concentrations were higher in ponds after rain events by an average of 0.46 (P < 0.01) and 0.61 (P < 0.05) log10 most probable number (MPN) 100 ml−1, respectively. Salmonella concentrations in storm runoff from fields and forests were not significantly higher than in ponds before rain events, but concentrations in storm flow from streams and ditches were higher by an average of 1.22 log10 MPN 100 ml−1 (P < 0.001). Eighteen Salmonella serovars were identified from 155 serotyped isolates, and eight serovars were shared between storm runoff/storm flow and ponds. Seven of the serovars, including five of the shared serovars, were present in cases of human illness in the study region in the same year. However, several serovars most commonly associated with human illness in the study region (e.g. Javiana, Enteritidis, and Montevideo) were not found in any water samples. Conclusions: Salmonella and E. coli concentrations in irrigation ponds were higher, on average, after rain events, but concentrations of Salmonella were low, and the ponds met FDA water quality standards based on E. coli. Some similarities and notable differences were found between Salmonella serovars in water samples and in cases of human illness. Significance and Impact of Study: This study directly examined storm runoff/storm flow into irrigation ponds and quantified increases in Salmonella and E. coli following rain events, with potential implications for irrigation pond management as well as human health.

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Section: Methodsmentioning

confidence: 99%

Impact of storm runoff onSalmonellaandEscherichia coliprevalence in irrigation ponds of fresh produce farms in southern Georgia

et al. 2018

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“…The prevalence of Salmonella was evaluated as the percentage of positive samples from triplicate aliquots of all sample types, i.e., surface and subsurface water (500 ml) and perimeter and benthic sediments (100 g). Salmonella was enumerated by a 3-tube ϫ 3-dilution most probable number (MPN) method as previously described (25). Briefly, triplicate enrichment cultures of lactose broth (2ϫ; Fisher Scientific, Inc.) were inoculated with an equal volume (500, 100, or 10 ml) or weight (100, 10, or 1 g) of water or wet sediment, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…Thus, the best predictor for Salmonella is likely to be an assay for detection of Salmonella itself. Improvements in PCR (57)(58)(59) and non-PCR methods, such as the application of multiple agars (25), may offer alternatives to fecal indicators for future agricultural water quality analysis. The virulence potential of Salmonella isolates associated with agricultural water remains to be determined, but the antibiotic resistance patterns and genetic relatedness of pond isolates to serovars commonly associated with disease support the need for continued monitoring and surveillance.…”

Section: Figmentioning

confidence: 99%

Distribution and Characterization of Salmonella enterica Isolates from Irrigation Ponds in the Southeastern United States

Luo

Ginn

et al. 2015

Appl Environ Microbiol

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f Irrigation water has been implicated as a likely source of produce contamination by Salmonella enterica. Therefore, the distribution of S. enterica was surveyed monthly in irrigation ponds (n ‫؍‬ 10) located within a prime agricultural region in southern Georgia and northern Florida. All ponds and 28.2% of all samples (n ‫؍‬ 635) were positive for Salmonella, with an overall geometric mean concentration (0.26 most probable number [MPN]/liter) that was relatively low compared to prior reports for rivers in this region. Salmonella peaks were seasonal; the levels correlated with increased temperature and rainfall (P < 0.05). The numbers and occurrence were significantly higher in water (0.32 MPN/liter and 37% of samples) than in sediment (0.22 MPN/ liter and 17% of samples) but did not vary with depth. Representative isolates (n ‫؍‬ 185) from different ponds, sample types, and seasons were examined for resistance to 15 different antibiotics; most strains were resistant to streptomycin (98.9%), while 20% were multidrug resistant (MDR) for 2 to 6 antibiotics. DiversiLab repetitive extragenic palindromic-element sequence-based PCR (rep-PCR) revealed genetic diversity and showed 43 genotypes among 191 isolates, as defined by >95% similarity. The genotypes did not partition by pond, season, or sample type. Genetic similarity to known serotypes indicated Hadar, Montevideo, and Newport as the most prevalent. All ponds achieved the current safety standards for generic Escherichia coli in agricultural water, and regression modeling showed that the E. coli level was a significant predictor for the probability of Salmonella occurrence. However, persistent populations of Salmonella were widely distributed in irrigation ponds, and the associated risks for produce contamination and subsequent human exposure are unknown, supporting continued surveillance of this pathogen in agricultural settings.

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“…), and UFL‐1352 was isolated from an irrigation pond in Georgia in a prior study (Luo et al . ). CM sensitivity of additional isolates was also examined for strains listed in Table and obtained from both environmental (Luo et al .…”

Section: Methodsmentioning

confidence: 97%

“…CM sensitivity of additional isolates was also examined for strains listed in Table and obtained from both environmental (Luo et al . ) and clinical sources (Dr. Carina Blackmore, Florida Department of Health). Strains were stored at −80°C in Luria Broth (LB, 1% yeast extract, 1% tryptone, Fisher BioReagents, pH 7·4), prepared and autoclaved with 50% glycerol.…”

Section: Methodsmentioning

confidence: 99%

Application of chitosan microparticles for mitigation of Salmonella in agricultural water

Fan

Ginn

et al. 2017

J Appl Microbiol

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Development of a novel cross-streaking method for isolation, confirmation, and enumeration of Salmonella from irrigation ponds

Cited by 15 publications

References 26 publications

Impact of storm runoff onSalmonellaandEscherichia coliprevalence in irrigation ponds of fresh produce farms in southern Georgia

Impact of storm runoff onSalmonellaandEscherichia coliprevalence in irrigation ponds of fresh produce farms in southern Georgia

Distribution and Characterization of Salmonella enterica Isolates from Irrigation Ponds in the Southeastern United States

Application of chitosan microparticles for mitigation of Salmonella in agricultural water

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