Multiple antibiotic resistance indexing of Escherichia coli to identify high-risk sources of fecal contamination of foods

Escherichia coli isolates taken from environments considered to have low and high enteric disease potential for humans were screened against 12 antibiotics to determine the prevalence of multiple antibiotic resistance among the isolates of these environments. It was determined that multiple-antibiotic-resistant E. coli organisms exist in large numbers within the major reservoirs of enteric diseases for humans while existing in comparatively low numbers elsewhere. These differences provide a method for distinguishing high-risk contamination of foods by indexing the frequency with which multiple-antibiotic-resistant E. coli organisms occur among isolates taken from a sample.     

Multiple antibiotic resistance indexing of Escherichia coli to identify high-risk sources of fecal contamination of foods.

Escherichia coli isolates taken from environments considered to have low and high enteric disease potential for humans were screened against 12 antibiotics to determine the prevalence of multiple antibiotic resistance among the isolates of these environments. It was determined that multiple-antibiotic-resistant E. coli organisms exist in large numbers within the major reservoirs of enteric diseases for humans while existing in comparatively low numbers elsewhere. These differences provide a method for distinguishing high-risk contamination of foods by indexing the frequency with which multiple-antibiotic-resistant E. coli organisms occur among isolates taken from a sample.     

Considerations when using discriminant function analysis of antimicrobial resistance profiles to identify sources of fecal contamination of surface water in Michigan

The goals of this study were to (i) identify issues that affect the ability of discriminant function analysis (DA) of antimicrobial resistance profiles to differentiate sources of fecal contamination, (ii) test the accuracy of DA from a known-source library of fecal Escherichia coli isolates with isolates from environmental samples, and (iii) apply this DA to classify E. coli from surface water. A repeated cross-sectional study was used to collect fecal and environmental samples from Michigan livestock, wild geese, and surface water for bacterial isolation, identification, and antimicrobial susceptibility testing using disk diffusion for 12 agents chosen for their importance in treating E. coli infections or for their use as animal feed additives. Nonparametric DA was used to classify E. coli by source species individually and by groups according to antimicrobial exposure. A modified backwards model-building approach was applied to create the best decision rules for isolate differentiation with the smallest number of antimicrobial agents. Decision rules were generated from fecal isolates and applied to environmental isolates to determine the effectiveness of DA for identifying sources of contamination. Principal component analysis was applied to describe differences in resistance patterns between species groups. The average rate of correct classification by DA was improved by reducing the numbers of species classifications and antimicrobial agents. DA was able to correctly classify environmental isolates when fewer than four classifications were used. Water sample isolates were classified by livestock type. An evaluation of the performance of DA must take into consideration relative contributions of random chance and the true discriminatory power of the decision rules.     

Host species-specific metabolic fingerprint database for enterococci and Escherichia coli and its application to identify sources of fecal contamination in surface waters

A metabolic fingerprint database of enterococci and Escherichia coli from 10 host groups of animals was developed to trace the sources of fecal contamination in surface waters. In all, 526 biochemical phenotypes (BPTs) of enterococci and 530 E. coli BPTs were obtained from 4,057 enterococci and 3,728 E. coli isolates tested. Of these, 231 Enterococcus BPTs and 257 E. coli BPTs were found in multiple host groups. The remaining 295 Enterococcus BPTs and 273 E. coli BPTs were unique to individual host groups. The database was used to trace the sources of fecal contamination in a local creek. The mean diversities (Di) of enterococci (Di = 0.76 +/- 0.05) and E. coli (Di = 0.88 +/- 0.04) were high (maximum 1) in water samples, indicating diverse sources of fecal contamination. Overall, 71% of BPTs of enterococci and 67% of E. coli BPTs from water samples were identified as human and animal sources. Altogether, 248 Enterococcus BPTs and 282 E. coli BPTs were found in water samples. Among enterococci, 26 (10%) BPTs were identical to those of humans and 152 BPTs (61%) were identical to those of animals (animal BPTs). Among E. coli isolates, 36 (13%) BPTs were identical to those of humans and 151 (54%) BPTs were identical to those of animals. Of the animal BPTs, 101 (66%) Enterococcus BPTs and 93 (62%) E. coli BPTs were also unique to individual animal groups. On the basis of these unique Enterococcus BPTs, chickens contributed 14% of contamination, followed by humans (10%), dogs (7%), and horses (6%). For E. coli, humans contributed 13% of contamination, followed by ducks (9%), cattle (7%), and chickens (6%). The developed metabolic fingerprint database was able to distinguish between human and animal sources as well as among animal species in the studied catchment.     

Multiple antibiotic resistance indexing of coliforms to identify high risk contamination sites in aquatic environment

Bacteriological analysis of the water samples collected from upstream, midstream and downstream points along the bank of the river revealed high populations of Escherichia coli, Citrobacter freundii, Citrobacter diversus, Enterobacter aerogens and Klebsiella species. All these isolates were screened against eight antibiotics to determine the prevalence of multiple antibiotic resistance among isolates at different sites of the river. The study revealed that multiple antibiotic resistance was prominently seen in coliforms at downstream sites (Average multiple antibiotic resistance index, MAR Index = 0.43) while it was low in coliforms at upstream sites (MAR Index = 0.15). These differences in MAR indices provide a method for distinguishing high risk contamination sites in aquatic environment.     

Evaluation of two library-independent microbial source tracking methods to identify sources of fecal contamination in French estuaries

In order to identify the origin of the fecal contamination observed in French estuaries, two library-independent microbial source tracking (MST) methods were selected: (i) Bacteroidales host-specific 16S rRNA gene markers and (ii) F-specific RNA bacteriophage genotyping. The specificity of the Bacteroidales markers was evaluated on human and animal (bovine, pig, sheep, and bird) feces. Two human-specific markers (HF183 and HF134), one ruminant-specific marker (CF193'), and one pig-specific marker (PF163) showed a high level of specificity (>90%). However, the data suggest that the proposed ruminant-specific CF128 marker would be better described as an animal marker, as it was observed in all bovine and sheep feces and 96% of pig feces. F RNA bacteriophages were detected in only 21% of individual fecal samples tested, in 60% of pig slurries, but in all sewage samples. Most detected F RNA bacteriophages were from genotypes II and III in sewage samples and from genotypes I and IV in bovine, pig, and bird feces and from pig slurries. Both MST methods were applied to 28 water samples collected from three watersheds at different times. Classification of water samples as subject to human, animal, or mixed fecal contamination was more frequent when using Bacteroidales markers (82.1% of water samples) than by bacteriophage genotyping (50%). The ability to classify a water sample increased with increasing Escherichia coli or enterococcus concentration. For the samples that could be classified by bacteriophage genotyping, 78% agreed with the classification obtained from Bacteroidales markers.     

Antibiotic resistance of fecal indicator bacteria from fishponds and nearby water sources in the Ayeyarwady Delta region of Myanmar

Limnology - Antibiotics are widely used for disease prevention in animal husbandry, including on chicken, cow and pig farms. Manure from farm animals can be used as fish food, especially in...     

Antibiotic resistance in Salmonella enterica serovar Typhimurium exposed to microcin-producing Escherichia coli

Microcin 24 is an antimicrobial peptide secreted by uropathogenic Escherichia coli. Secretion of microcin 24 provides an antibacterial defense mechanism for E. coli. In a plasmid-based system using transformed Salmonella enterica, we found that resistance to microcin 24 could be seen in concert with a multiple-antibiotic resistance phenotype. This multidrug-resistant phenotype appeared when Salmonella was exposed to an E. coli strain expressing microcin 24. Therefore, it appears that multidrug-resistant Salmonella can arise as a result of an insult from other pathogenic bacteria.     

Occurrence of antibiotic resistance in Escherichia coli from surface waters and fecal pollution sources near Hamilton, Ontario

Antibiotic resistance was examined in 462 Escherichia coli isolates from surface waters and fecal pollution sources around Hamilton, Ontario. Escherichia coli were resistant to the highest concentrations of each of the 14 antibiotics studied, although the prevalence of high resistance was mostly low. Two of 12 E. coli isolates from sewage in a CSO tank had multiple resistance to ampicillin, ciprofloxacin, gentamicin, and tetracycline above their clinical breakpoints. Antibiotic resistance was less prevalent in E. coli from bird feces than from municipal wastewater sources. A discriminant function calculated from antibiotic resistance data provided an average rate of correct classification of 68% for discriminating E. coli from bird and wastewater fecal pollution sources. The preliminary microbial source tracking results suggest that, at times, bird feces might be a more prominent contributor of E. coli to Bayfront Park beach waters than municipal wastewater sources.     

Antibiotic resistance among different species of fecal coliforms isolated from water samples.

The distribution of resistance to ampicillin, chloramphenicol, sulfonamides, tetracycline, and streptomycin among fecal coliforms in sewage, surface waters, and sea water was investigated. The incidence of resistant strains among isolates varied significantly among the water samples, without obvious connection with the water source or the level of pollution. The average frequency of multiple resistance was not always high in the same samples in which the overall resistance was high. The species composition varied considerably in different water samples. A significant correlation was observed between the relative frequency of Klebsiella species and the incidence of ampicillin resistance in water samples. The importance of species composition of fecal coliforms, affected by their source and by the aquatic environment, on the resistance pattern is noted.     

Rapid enzymatic detection of Escherichia coli contamination in polluted river water

AIMS: The relationship between the rate of beta-D-glucuronidase hydrolysis (GLUase-HR) and the E. coli concentration in rivers differing in the extent of faecal pollution was investigated. It was hypothesized that the rate of GLUase-HR is a better surrogate parameter for E. coli concentrations than estimated numbers of faecal coliforms (FC). METHODS AND RESULTS: The GLUase-HR of the water sample filter residues was determined as the rate of cleavage of 4-methylumbelliferyl-beta-D-glucuronide. FC and E. coli concentrations were enumerated using mFC and Chromocult Coliform agar, respectively. Regression analysis revealed that a 90% variation of the variable log GLUase-HR was directly related to the variable log E. coli concentrations. The observed relationship between the log of the FC count and the log of the GLUase activity could be explained by the hydrolysis activity of the E. coli population, as E. coli is a part of the FC group. CONCLUSION: The data suggest that the log of the GLUase-HR can be used as a surrogate parameter for the log of the E. coli concentrations. SIGNIFICANCE AND IMPACT OF THE STUDY: GLUase-HR determination may provide a rapid alternative technique to estimate E. coli concentrations in freshwaters.     

Use of 16S-23S rRNA intergenic spacer region PCR and repetitive extragenic palindromic PCR analyses of Escherichia coli isolates to identify nonpoint fecal sources

Despite efforts to minimize fecal input into waterways, this kind of pollution continues to be a problem due to an inability to reliably identify nonpoint sources. Our objective was to find candidate source-specific Escherichia coli fingerprints as potential genotypic markers for raw sewage, horses, dogs, gulls, and cows. We evaluated 16S-23S rRNA intergenic spacer region (ISR)-PCR and repetitive extragenic palindromic (rep)-PCR analyses of E. coli isolates as tools to identify nonpoint fecal sources. The BOXA1R primer was used for rep-PCR analysis. A total of 267 E. coli isolates from different fecal sources were typed with both techniques. E. coli was found to be highly diverse. Only two candidate source-specific E. coli fingerprints, one for cow and one for raw sewage, were identified out of 87 ISR fingerprints. Similarly, there was only one candidate source-specific E. coli fingerprint for horse out of 59 BOX fingerprints. Jackknife analysis resulted in an average rate of correct classification (ARCC) of 83% for BOX-PCR analysis and 67% for ISR-PCR analysis for the five source categories of this study. When nonhuman sources were pooled so that each isolate was classified as animal or human derived (raw sewage), ARCCs of 82% for BOX-PCR analysis and 72% for ISR-PCR analysis were obtained. Critical factors affecting the utility of these methods, namely sample size and fingerprint stability, were also assessed. Chao1 estimation showed that generally 32 isolates per fecal source individual were sufficient to characterize the richness of the E. coli population of that source. The results of a fingerprint stability experiment indicated that BOX and ISR fingerprints were stable in natural waters at 4, 12, and 28 degrees C for 150 days. In conclusion, 16S-23S rRNA ISR-PCR and rep-PCR analyses of E. coli isolates have the potential to identify nonpoint fecal sources. A fairly small number of isolates was needed to find candidate source-specific E. coli fingerprints that were stable under the simulated environmental conditions.     

Antibiotic resistance genes in water environment

The use of antibiotics may accelerate the development of antibiotic resistance genes (ARGs) and bacteria which shade health risks to humans and animals. The emerging of ARGs in the water environment is becoming an increasing worldwide concern. Hundreds of various ARGs encoding resistance to a broad range of antibiotics have been found in microorganisms distributed not only in hospital wastewaters and animal production wastewaters, but also in sewage, wastewater treatment plants, surface water, groundwater, and even in drinking water. This review summarizes recently published information on the types, distributions, and horizontal transfer of ARGs in various aquatic environments, as well as the molecular methods used to detect environmental ARGs, including specific and multiplex PCR (polymerase chain reaction), real-time PCR, DNA sequencing, and hybridization based techniques.     

Genetic characterization of Escherichia coli populations from host sources of fecal pollution by using DNA fingerprinting

Escherichia coli isolates were obtained from common host sources of fecal pollution and characterized by using repetitive extragenic palindromic (REP) PCR fingerprinting. The genetic relationship of strains within each host group was assessed as was the relationship of strains among different host groups. Multiple isolates from a single host animal (gull, human, or dog) were found to be identical; however, in some of the animals, additional strains occurred at a lower frequency. REP PCR fingerprint patterns of isolates from sewage (n = 180), gulls (n = 133), and dairy cattle (n = 121) were diverse; within a host group, pairwise comparison similarity indices ranged from 98% to as low as 15%. A composite dendrogram of E. coli fingerprint patterns did not cluster the isolates into distinct host groups but rather produced numerous subclusters (approximately >80% similarity scores calculated with the cosine coefficient) that were nearly exclusive for a host group. Approximately 65% of the isolates analyzed were arranged into host-specific groups. Comparable results were obtained by using enterobacterial repetitive intergenic consensus PCR and pulsed-field gel electrophoresis (PFGE), where PFGE gave a higher differentiation of closely related strains than both PCR techniques. These results demonstrate that environmental studies with genetic comparisons to detect sources of E. coli contamination will require extensive isolation of strains to encompass E. coli strain diversity found in host sources of contamination. These findings will assist in the development of approaches to determine sources of fecal pollution, an effort important for protecting water resources and public health.     

Antibiotic resistance and population structure in Escherichia coli from free-ranging African yellow baboons.

Two collections of Escherichia coli from human hosts and one from free-ranging African yellow baboons were examined for the ability to utilize various sugars (biotype) and for resistance to antibiotics. The frequency of antibiotic resistance in the E. coli flora of baboons that feed regularly in village garbage dumps was found to be no greater than that in baboons not associated with human habitation. The frequency of antibiotic resistance in E. coli isolated from baboons is similar to that in E. coli isolated from humans before the widespread use of antibiotics but significantly lower than that in recent isolates from humans. The biotype data indicate that the amount and distribution of genetic variation in the E. coli among free-ranging baboon troops are similar to those in isolates from humans. However, E. coli isolates from baboons are able to utilize a greater variety of sugars as their sole carbon source, possibly because of a greater variety of sugars in the baboon diet.     

Identifying host sources of fecal pollution: diversity of Escherichia coli in confined dairy and swine production systems

Repetitive extragenic palindromic PCR fingerprinting of Escherichia coli is one microbial source tracking approach for identifying the host source origin of fecal pollution in aquatic systems. The construction of robust known-source libraries is expensive and requires an informed sampling strategy. In many types of farming systems, waste is stored for several months before being released into the environment. In this study we analyzed, by means of repetitive extragenic palindromic PCR using the enterobacterial repetitive intergenic consensus primers and comparative analysis using the Bionumerics software, collections of E. coli obtained from a dairy farm and from a swine farm, both of which stored their waste as a slurry in holding tanks. In all fecal samples, obtained from either barns or holding tanks, the diversity of the E. coli populations was underrepresented by collections of 500 isolates. In both the dairy and the swine farms, the diversity of the E. coli community was greater in the manure holding tank than in the barn, when they were sampled on the same date. In both farms, a comparison of stored manure samples collected several months apart suggested that the community composition changed substantially in terms of the detected number, absolute identity, and relative abundance of genotypes. Comparison of E. coli populations obtained from 10 different locations in either holding tank suggested that spatial variability in the E. coli community should be accounted for when sampling. Overall, the diversity in E. coli populations in manure slurry storage facilities is significant and likely is problematic with respect to library construction for microbial source tracking applications.