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.     

Antibiotic resistance indexing of Escherichia coli to identify sources of fecal contamination in water

A total of 202 Escherichia coli isolated from urban and rural water were tested with 11 antibiotics to assess the prevalence of antibiotic resistance from each source. Urban waters harbored higher percentages of resistant E. coli strains than rural waters. Antibiotic-resistant E. coli may offer an index of water quality related to source.     

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.     

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.     

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.     

Multiple antibiotic resistance patterns of Escherichia coli isolates from swine farms.

Antibiotic resistance of Escherichia coli from sows and pigs was determined to compare patterns between pigs of various ages and degrees of antibiotic use. Resistance patterns differed between farm types and pigs of differing ages, indicating that pig age and degree of antibiotic use affect resistance of fecal E. coli.     

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.     

Adaptation to the fitness costs of antibiotic resistance in Escherichia coli.

Policies aimed at alleviating the growing problem of drug-resistant pathogens by restricting antimicrobial usage implicitly assume that resistance reduces the Darwinian fitness of pathogens in the absence of drugs. While fitness costs have been demonstrated for bacteria and viruses resistant to some chemotherapeutic agents, these costs are anticipated to decline during subsequent evolution. This has recently been observed in pathogens as diverse as HIV and Escherichia coli. Here we present evidence that these gentic adaptations to the costs of resistance can virtually preclude resistant lineages from reverting to sensitivity. We show that second site mutations which compensate for the substantial (14 and 18% per generation) fitness costs of streptomycin resistant (rpsL) mutations in E. coli create a genetic background in which streptomycin sensitive, rpsL+ alleles have a 4-30% per generation selective disadvantage relative to adapted, resistant strains. We also present evidence that similar compensatory mutations have been fixed in long-term streptomycin-resistant laboratory strains of E. coli and may account for the persistence of rpsL streptomycin resistance in populations maintained for more than 10,000 generations in the absence of the antibiotic. We discuss the public health implications of these and other experimental results that question whether the more prudent use of antimicrobial chemotherapy will lead to declines in the incidence of drug-resistant pathogenic microbes.     

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.     

The use of ribotyping and antibiotic resistance patterns for identification of host sources of Escherichia coli strains

AIMS: To compare antibiotic resistance and ribotyping patterns ability to identify triplicate isolates sent from a group of 40 Escherichia coli taken from seven host sources. METHODS AND RESULTS: Of the 120 isolates, 22 isolates were resistant to ampicillin, streptomycin, tetracycline and trimethoprim and 98 isolates were susceptible. Antibiotic patterns identified 33 of the triplicates and three of the six groups had isolates from multiple hosts. Ribotyping divided the isolates into 27 ribotype groups with all triplicates grouped into the same ribotype group with one host per group. CONCLUSIONS: Antibiotic susceptibility pattern placed 98 of the isolates in a single group with 50% of the antibiotic susceptibility pattern groups containing multiple host species. Ribotyping groups were host specific with each host having one to seven ribotype groups. SIGNIFICANCE AND IMPACT OF THE STUDY: Antibiotic susceptibility pattern groups have been used for environmental source identification and faecal pollution tracking, however these groups do not always distinguish between host species. Stability of the markers is a potential concern and this system can only be used if antibiotic resistance levels are high in the isolates studied. All isolates have a ribotype group which was stable and like other molecular methods has advantages over antibiotic susceptibility pattern groups which uses a phenotypic method.     

新生儿大肠埃希菌败血症耐药性分析

目的 探讨新生儿败血症的大肠埃希菌耐药情况,为早期诊断和合理治疗提供依据.方法 对2002年8月至2011年8月确诊的64例大肠埃希菌败血症新生儿的药敏结果进行回顾性分析,并对早、晚发型新生儿败血症的大肠埃希菌分离株耐药率进行比较.结果 64株大肠埃希菌分离株中,产ESBLs 29株,检出率为45.31％.其中晚发型败血症ESBLs检出率明显高于早发型(56.41％ vs 28.00％,P＜0.05).早、晚发型新生儿败血症的大肠埃希菌分离株均对亚胺培南、美罗培南、哌拉西林/他唑巴坦、头孢哌酮/舒巴坦耐药率较低,均小于26.00％;早、晚发型新生儿败血症的大肠埃希菌分离株对多种抗生素的耐药率不同,差异具有统计学意义(均P＜0.05).结论 新生儿早发型与晚发型败血症的大肠埃希菌分离株对药物的耐药率有差异,建议临床在抗感染治疗时,应根据药敏结果,合理使用抗菌药物.     

Association of antibiotic resistance in agricultural Escherichia coli isolates with attachment to quartz

Surface water can be contaminated by bacteria from various sources, including manure from agricultural facilities. Attachment of these bacteria to soil and organic particles contributes to their transport through the environment, though the mechanism of attachment is unknown. As bacterial attachment to human tissues is known to be correlated with antibiotic resistance, we have investigated here the relationship between bacterial attachment to environmental particles and antibiotic resistance in agricultural isolates. We evaluated 203 Escherichia coli isolates collected from swine facilities for attachment to quartz, resistance to 13 antibiotics, and the presence of genes encoding 13 attachment factors. The genes encoding type I, EcpA, P pili, and Ag43 were detected, though none was significantly related to attachment. Quartz attachment was positively and significantly (P < 0.0038) related to combined resistance to amoxicillin/streptomycin/tetracycline/sulfamethazine/tylosin/chlortetracycline and negatively and significantly (P < 0.0038) related to combined resistance to nalidixic acid/kanamycin/neomycin. These results provide clear evidence for a link between antibiotic resistance and attachment to quartz in agricultural isolates. We propose that this may be due to encoding by the responsible genes on a mobile genetic element. Further exploration of the relationship between antibiotic resistance and attachment to environmental particles will improve the understanding and modeling of environmental transport processes, with the goal of preventing human exposure to antibiotic-resistant or virulent microorganisms.     

Stability in Escherichia coli of an antibiotic resistance plasmid from Bacteroides fragilis.

A Bacteroides fragilis strain resistant to penicillin G, tetracycline, and clindamycin was screened for the presence of plasmid deoxyribonucleic acid (DNA). Agarose gel electrophoresis of ethanol-precipitated DNA from cleared lysates of this strain revealed two plasmid DNA bands. The molecular weights of the plasmids were estimated by their relative mobility in agarose gel and compared with standard plasmids with known molecular weights. The molecular weights were 3.40 +/- 0.20 x 10(6) and 1.95 +/- 0.05 x 10(6) for plasmids pBY1 and pBY2, respectively. Plasmid DNA purified by cesium chloride-ethidium bromide gradient centrifugation was used to transform a restriction- and modification-negative strain of Escherichia coli. Penicillin G- and tetracycline-resistant transformants were screened for the presence of plasmid DNA. A plasmid band corresponding to a molecular weight of 1.95 x 10(6) was present in all transformants tested. Curing experiments demonstrated that the plasmid, referred to as pBY22 when present in transformants, was responsible for penicillin G and tetracycline resistance. Plasmid pBY22 was mobilized and transferred to other E. coli strains by plasmid R1drd-19. Stability of pBY22 was examined in different E. coli strains and was shown to be stably maintained in both restriction-negative and restriction-positive strains. Unexpectedly, pBY2 and pBY22 were resistant to digestion by 12 different restriction endonucleases.     

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.     

Effect of feeding live yeast products to calves with failure of passive transfer on performance and patterns of antibiotic resistance in fecal Escherichia coli

Fifty-two newborn Holstein calves with serum IgG concentrations less than 0.73 g.dL(-1) were randomly assigned to one of four treatments: no added live yeast (control), 0.5 g of live yeast added to the grain for 84 d (SC; Saccharomyces cerevisiae), 0.5 g of live yeast added to the milk for 42 d (SB; S. cerevisiae, spp. boulardii), and 0.5 g of live yeast added to the grain for 84 d and to the milk for 42 d (SCSB). Calves were offered 440 g of milk replacer DM for the first 42 d and grain for ad libitum intake throughout the study. Plasma was analyzed weekly for concentrations of glucose and beta-hydroxybutyrate. Escherichia coli isolated from fecal samples collected every 2 weeks were used for determination of antibiotic resistance patterns. Calves receiving SC consumed more grain DM, had increased weight gain prior to weaning, and increased plasma glucose concentrations compared to controls. Days with diarrhea were reduced by feeding live yeast to calves. Antibiotic resistance in fecal E. coli was associated with the age of calves with highest levels of resistance observed in the 3 d calves. While calves receiving SCSB had higher levels of antibiotic resistance than controls, this effect was not associated with any of the other treatments. Improvements in performance of calves with failure of passive transfer were observed when live yeast was added only to the grain.     

Lytic phages obscure the cost of antibiotic resistance in Escherichia coli

The long-term persistence of antibiotic-resistant bacteria depends on their fitness relative to other genotypes in the absence of drugs. Outside the laboratory, viruses that parasitize bacteria (phages) are ubiquitous, but costs of antibiotic resistance are typically studied in phage-free experimental conditions. We used a mathematical model and experiments with Escherichia coli to show that lytic phages strongly affect the incidence of antibiotic resistance in drug-free conditions. Under phage parasitism, the likelihood that antibiotic-resistant genetic backgrounds spread depends on their initial frequency, mutation rate and intrinsic growth rate relative to drug-susceptible genotypes, because these parameters determine relative rates of phage-resistance evolution on different genetic backgrounds. Moreover, the average cost of antibiotic resistance in terms of intrinsic growth in the antibiotic-free experimental environment was small relative to the benefits of an increased mutation rate in the presence of phages. This is consistent with our theoretical work indicating that, under phage selection, typical costs of antibiotic resistance can be outweighed by realistic increases in mutability if drug resistance and hypermutability are genetically linked, as is frequently observed in clinical isolates. This suggests the long-term distribution of antibiotic resistance depends on the relative rates at which different lineages adapt to other types of selection, which in the case of phage parasitism is probably extremely common, as well as costs of resistance inferred by classical in vitro methods.     

Multiple antibiotic resistance in Rhizobium japonicum.

A total of 48 strains of the soil bacterium Rhizobium japonicum were screened for their response to several widely used antibiotics. Over 60% of the strains were resistant to chloramphenicol, polymyxin B, and erythromycin, and 47% or more of the strains were resistant to neomycin and penicillin G, when tested by disk assay procedures. The most common grouping of resistances in strains was simultaneous resistance to tetracycline, penicillin G, neomycin, chloramphenicol, and streptomycin (25% of all strains tested). The occurrence of multiple drug resistance in a soil bacterium that is not a vertebrate pathogen suggests that chemotherapeutic use of antibiotics is not required for the development of multiple drug resistance.