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APPLIED AND ENVIRONMENTAL MICROBIOLOGY, Oct. 2007, p. 5982–5989 0099-2240/07/$08.00ϩ0 doi:10.1128/AEM.00709-07Copyright 2007, American Society for Microbiology. All Rights Reserved.
Influence of Antibiotic Selection on Genetic Composition of Escherichia coli Populations from Conventional and Seth T. Walk,1 Janice M. Mladonicky,1 Jaclyn A. Middleton,1 Anthony J. Heidt,1 Julie R. Cunningham,1 Paul Bartlett,2 Kenji Sato,3 and Thomas S. Whittam1* Microbial Evolution Laboratory, National Food Safety and Toxicology Center, Michigan State University, East Lansing, Michigan 488241; Department of Large Animal Clinical Sciences, National Food Safety and Toxicology Center, Michigan State University, East Lansing, Michigan 488242; and Department of Veterinary Sciences, University of Wyoming, Laramie, Wyoming 820703 Received 28 March 2007/Accepted 30 July 2007 The widespread agricultural use of antimicrobials has long been considered a crucial influence on the
prevalence of resistant genes and bacterial strains. It has been suggested that antibiotic applications in
agricultural settings are a driving force for the development of antimicrobial resistance, and epidemiologic
evidence supports the view that there is a direct link between resistant human pathogens, retail produce, farm
animals, and farm environments. Despite such concerns, little is understood about the population processes
underlying the emergence and spread of antibiotic resistance and the reversibility of resistance when antibiotic
selective pressure is removed. In this study, hierarchical log-linear modeling was used to assess the association
between farm type (conventional versus organic), age of cattle (calf versus cow), bacterial phenotype (resistant
versus susceptible), and the genetic composition of Escherichia coli populations (E. coli Reference Collection
[ECOR] phylogroup A, B1, B2, or D) among 678 susceptible and resistant strains from a previously published
study of 60 matched dairy farms (30 conventional and 30 organic) in Wisconsin. The analysis provides evidence
for clonal resistance (ampicillin resistance) and genetic hitchhiking (tetracycline resistance [Tetr]), estimated
the rate of compositional change from conventional farming to organic farming (mean, 8 years; range, 3 to 15
years), and discovered a significant association between low multidrug resistance, organic farms, and strains
of the numerically dominant phylogroup B1. These data suggest that organic farming practices not only change
the frequency of resistant strains but also impact the overall population genetic composition of the resident E.
coli flora. In addition, the results support the hypothesis that the current prevalence of Tetr loci on dairy farms
has little to do with the use of this antibiotic.
Escherichia coli is an indicator species for a variety of an- tion, it is hypothesized that deleterious effects on fitness are thropogenic effects on microbial populations, such as the compensated by changes elsewhere in the genome (21, 24, 25, emergence and spread of antibiotic resistance in agriculture (1, 32, 33, 37). The occurrence of such compensatory fitness mu- 5–10, 14, 20, 30, 35, 36, 38, 39). Although most strains are tations makes it difficult to determine whether the abundance commensal bacteria and nonpathogenic to humans and ani- and distribution of resistant strains are results of direct selec- mals, there are well-recognized pathogenic strains that can tion on the original mutation that caused resistance, selection cause a variety of human and zoonotic diseases, and some on compensatory changes, or other ecological factors that limit commensal populations are known to carry high levels of an- population diversity (environmental selection, bottlenecks, ge- tibiotic resistance (4, 28, 29). Such resistant populations pose a netic drift, etc.). There is sound evidence that antibiotic use public and veterinary health risk because of the potential trans- increases the abundance of resistant phenotypes (34), but it is fer of genetic resistance determinants to pathogens. In addi- not clear if the cessation of antibiotic use will decrease abun- tion, certain virulence factors may be mobilized on genetic dance after compensatory changes have occurred (2, 22). In elements and transferred to normally commensal but antibiotic- addition, resistance loci may be genetically linked to loci under resistant strains via horizontal exchange (31, 42, 43).
strong selection and be carried at a high frequency in the During antibiotic selection in the laboratory, resistance-con- ferring mutations often have measurable deleterious effects Antibiotic use in dairy cattle provides an ideal opportunity to (i.e., a resistance cost) due to a reduction in the function of assess the role of natural selection in bacterial populations for genes in which resistance mutations arise. In order to maintain several reasons. The source of the antibiotic selective pressure a competitive advantage over other members of the popula- is known, and the dosage is often recorded. The commongenetic determinants for certain resistant phenotypes havebeen characterized, and high-throughput assays are available * Corresponding author. Mailing address: Microbial Evolution Lab- oratory, 165 Food Safety and Toxicology Building, Michigan State for their identification. Hypotheses generated under labora- University, East Lansing, MI 48824. Phone: (517) 432-3100, ext. 178.
tory conditions can be tested in vivo by comparing bacteria Fax: (517) 432-2310. E-mail: [email protected].
from farms that regularly use antibiotics (conventional) and † Supplemental material for this article may be found at http://aem bacteria from farms that rarely use antibiotics (organic) (34).
ᰔ Published ahead of print on 17 August 2007.
Finally, a number of studies have previously characterized re- GENETIC COMPOSITION OF E. COLI POPULATIONS ON FARMS sistance dynamics on both farm types and have identified vari- A separate PCR was run with primers targeting the TspE4.C2 anonymous DNA ables that significantly influence the abundance of resistant locus using published conditions (12).
Resistance loci and class 1 integron PCR. Ampr and Tetr strains were
phenotypes (1, 5, 7, 14, 30, 34–36).
screened for the presence of six previously identified resistance loci. A multiplex The purpose of the present study was to assess the influence PCR was used to detect the presence of blaTEM, blaSHV, and blaOXA-1 in Ampr of antibiotic selection on the genetic composition of E. coli strains by the method of Colom et al. (13). Fragments of the tetA, tetB, and tetC populations from conventional and organic dairy farms. First, genes were targeted in Tetr strains using the primers and conditions published byBoerlin et al. (9). Three primer sets were used to determine the presence of class we used a PCR-based assay (12) to quantify the abundance and 1 integrons in the resistant strains. Primer sets targeting the class 1 integrase distribution of four phylogenetic groups in populations cul- locus, intI1, the conserved region cassette regions A and B, and the quaternary tured during a longitudinal sampling of cattle from matched ammonium compound resistance gene qacE⌬1 are given along with the reaction conventional and organic dairy farms in Wisconsin (34). We conditions in reference 23. Integron presence was defined as amplification of all then assessed the pattern of statistical dependence for farm Statistical analyses. Strains were categorized for analysis as follows: F for farm
type (conventional versus organic), age of cattle (cows versus type (conventional versus organic), A for age of cattle (calf versus cow), D for calves), bacterial phenotype (resistant versus susceptible), and resistant phenotype (resistant versus susceptible) or drug susceptibility level bacterial genetic composition (E. coli Reference Collection (high or medium versus low), and E for ECOR group (A, B1, B2, and D). The [ECOR] groups A, B1, B2, and D) using hierarchical log-linear numbers of strains in each category were recorded in the cells of contingencytables. Hierarchical log-linear modeling with nested effects was used to assess dependent associations using the CATMOD procedure and SAS statistical soft-ware (SAS Institute, Cary, NC). Nonsignificant, higher-order interactions wereremoved until the most parsimonious model was found based on the likelihood MATERIALS AND METHODS
ratio chi-square statistic for testing goodness of fit (G2). Nonsignificant G2 valuesindicated that the fit model was not significantly different from the saturated E. coli strain collection. A total of 678 E. coli strains (367 random susceptible
model. Odds ratios were calculated based on parameter estimates from the most and 311 resistant strains) were assembled from a collection of 1,121 strains of a longitudinal sampling of 10 randomly selected cows and calves from a matched We chose to use log-linear modeling because the categorical variables in the set of 30 conventional and 30 organic dairy farms in Wisconsin (34). Briefly, a analysis were observed simultaneously and also because no assumptions or dis- cluster of organic farms was selected, and the geographically closest conventional tinctions needed to be made about whether variables were response or explan- farm was selected for purposes of comparison so as to minimize the effects of atory (40). This methodology is different from other approaches, like the chi- distance (cline effects). All organic farms were certified by a USDA-accredited square test, in that it tests the strength of associations between categorical certification agency as not having treated adult cows with an antibiotic for at least (Poisson distributed) variables and not significance. There are no assumptions 3 years (mean, 8 years; range, 3 to 15 years) prior to this study. More information that the dependent and independent variables be linearly related or that the about these farms is available (34).
relationship between variables be the same along the entire range (homoscedas- In the original study (34), fecal samples were taken from five lactating cows ticity). All variables were assumed to be independent. The expected counts in and five calves (Ͻ6 months of age) at each of two visits (once in March and once each cell of the contingency tables were above the rule-of-thumb cutoff of Ն1 and in September) and conducted with aseptic technique. Laboratory isolation was no more than 20% of cells Ͻ5. In addition, residuals were small (standardized begun within 72 h, and a single E. coli colony was isolated from each fecal sample residuals of Ͻ1.96) and were normally distributed.
so as to exclude any single farm or within-animal bias. All isolates were con- Higher-order (three-way) interactions for multidrug-resistant phenotypes firmed by standard biochemical assays. MICs of 17 antibiotics were determined were visualized in mosaic displays for multiway contingency tables (15), which for each strain as recommended by the CLSI (formerly NCCLS) (26) using a were obtained online at http://euclid.psych.yorku.ca/cgi/mosaics. The original commercially available semiautomatic broth microdilution test (Sensititre; Trek plots were redrawn and shaded with respect to the significant (␣ ϭ 0.05) asso- Diagnostic Systems Inc., Cleveland, OH) and appropriate quality control strains.
These antibiotics included ampicillin, amoxicillin-clavulanic acid, cephalothin,cefoxitin, ceftiofur, ceftriaxone, streptomycin, kanamycin, gentamicin, apramy-cin, amikacin, tetracycline, sulfamethoxazole, trimethoprim-sulfamethoxazole, nalidixic acid, and ciprofloxacin. Ampicillin resistance (Ampr) and tetracyclineresistance (Tetr) phenotypes were confirmed by the presence of overnight growth Overall abundance of E. coli phylogroups. Strains belonging
on LB broth (Lennox; Becton, Dickinson, and Company, Sparks, MD) agar to all four ECOR phylogroups were identified (Fig. 1) among containing antibiotic at the CLSI cutoff concentrations (32 ␮g/ml and 16 ␮g/ml, the 678 E. coli strains from calves and cows on dairy farms. The respectively). More details about the strain collection and isolation procedures relative phylogroup composition of these bacterial populations was used to compare different patterns of antibiotic resistance.
ECOR phylogrouping by multiplex PCR. Strains were grouped into one of
four phylogenetic lineages (A, B1, B2, or D) based on methods adapted from The populations analyzed here represent the natural variation those of Clermont et al. (12). Genomic DNA was isolated from 2 ml of overnight in farm type (conventional versus organic), age of cattle (calf culture in LB broth (Lennox; Becton, Dickinson, and Company, Sparks, MD) versus cow), and resistance phenotype (resistant versus suscep- using the Puregene DNA isolation kit (Gentra Systems Inc., Minneapolis, MN.).
tible). It is clear that phylogroup abundance was not evenly DNA preparations were quantified with a NanoDrop ND-1000 UV-visible spec- distributed among the different types of dairy farms (Fig. 1; see trophotometer (NanoDrop Technologies, Wilmington, DE), diluted to a finalconcentration of 100 ng/␮l, and stored at 4°C. Genomic DNA preparations were Table S1 in the supplemental material). The most abundant tested using primers targeting a 650-bp region of the conserved housekeeping phylogenetic groups were B1 (58.3%) and A (27.4%), whereas gene mdh (see www.shigatox.net/stec/mlst-new/index.html for primer sequences groups D (11.5%) and B2 (2.8%) were rare. B2 strains were and reaction conditions), and AmpliTaq Gold DNA polymerase (Applied Bio- not sampled at each variable level (no resistant B2 genotypes systems). This protocol has produced a positive amplicon in strains representing were found on organic farms), so these data were combined the genotypic diversity of the species as well as E. coli’s most recent commonancestor, Escherichia albertii. Genomic DNA was reisolated if the assay was with group D strain data (B2D) for statistical analyses.
negative. Strains that were negative for duplicate, independent genomic isola- Genetic composition of antibiotic-susceptible and -resistant
tions were considered members of species other than E. coli and excluded from E. coli populations. Our initial goal was to test for dependent
further analysis. Representative ECOR strains were used as template controls associations among three nominal variables (F for farm type, A for a duplex PCR targeting the genes chuA and yjaA. We found that the following for age of cattle, and E for ECOR phylogroup) by analyzing duplex conditions yielded higher PCR specificity with AmpliTaq Gold than thepublished triplex: denaturation at 94°C for 10 min; 35 cycles of 92°C for 1 min, the number of strains in these categories. The tests for asso- 59°C for 1 min, and 72°C for 30 seconds; and a final elongation at 72°C for 5 min.
ciations in the susceptible population (susceptible to 17 anti- FIG. 1. Histogram plots of ECOR phylogroups for susceptible and resistant E. coli populations from conventional (A) and organic (B) farms (strains from calves [black bars] and strains from cows [gray bars]).
microbials) by log-linear modeling of the 376 susceptible revealed a significant association between farm type and strains revealed no significant interactions with ECOR phylo- ECOR phylogrouping (Table 1). Based on parameter esti- grouping (Table 1). In other words, the distribution of phylo- mates, the odds of recovering resistant E. coli of phylogroup A groups in antibiotic-susceptible E. coli sampled from calves were significantly greater on conventional farms than on or- and cows on conventional and organic dairy farms was similar ganic farms (df ϭ 1, ␹2 ϭ 21.1, probability [Pr] Ͼ ␹2 Ͻ 0.0001).
and not significantly different. A significant negative associa- This overabundance of phylogroup A strains was not seen in tion was found between conventional farms and the number of the susceptible or resistant population from organic farms. In susceptible calf strains [i.e., the F(A ϭ calf) interaction in addition, there were no significant farm-phylogroup (i.e., F-E) Table 1[). This result was expected because the abundance of interactions when the susceptible populations from both farms resistant strains was higher in calves on conventional farms and the resistant population from organic farms were analyzed than in calves on organic farms. Despite this discrepancy in together (model not shown). These data suggest that resistance abundance, however, these data indicate that susceptible determinants on conventional farms were linked to the genetic strains of the four phylogroups were circulating at similar fre- backgrounds of phylogroup A and that these strains increased quencies on both farm types in young and adult animals.
in frequency as a result of antibiotic use. Interestingly, animal A similar analysis was applied to the 311 resistant strains and age was not associated with the distribution of phylogroups in TABLE 1. Best-fit models explaining the frequency of antibiotic-susceptible and -resistant E. coli from conventional and organic dairy farmsa ␮ ϩ A ϩ E ϩ F(A ϭ calf) ␮ ϩ A ϩ E ϩ F(E ϭ ECOR group A) a The analysis is based on testing hierarchical log-linear models with nested effects in parentheses. Nominal categorical variables are designated as follows: A for animal age (calf or cow), E for ECOR phylogroup (A, B1, B2, or D), and F for farm type (conventional or organic).
b ␮ designates the overall main effect.
c The likelihood ratio chi-square statistic was used to test for goodness of fit of the final population model (compared to the saturated model).
GENETIC COMPOSITION OF E. COLI POPULATIONS ON FARMS TABLE 2. Log-linear modeling of significant associations between farm type, multidrug resistance, and ECOR phylogrouping Final F-D-E modelb ␮ ϩ F ϩ D ϩ E ϩ F-E ϩ D-E ϩ F-D(E ϭ ECOR F-D(E ϭ ECOR group B1) ␮ ϩ F ϩ D ϩ E ϩ F-E ϩ D-E ϩ D-E(F ϭ organic) ␮ ϩ F ϩ D ϩ E ϩ F-E ϩ D-E ϩ F-E(D ϭ high) ϩ F-E(D ϭ medium) ϩ F-E(D ϭ low) a Model of farm type (F), multidrug resistance (D), and ECOR phylogrouping (E).
b Three separate parameterizations of the F-D-E model are given to show statistical dependence as a function of nested effects. ␮ designates the overall main effect.
c Significant interactions (three-way) with E.
the resistant population, suggesting that similar phylogroups tional farms are associated with medium and highly resistant circulate at similar frequencies in young and adult dairy cattle.
phylogroup A and B1 strains, whereas in contrast, organic Influence of multidrug resistance on genetic composition.
farms with virtually no antibiotic use are associated with low Strains were categorized according to their level of drug sus- and highly resistant phylogroup B1 and D strains.
ceptibility (D) as defined by the number of antimicrobial-re- The association between the age of cattle (A), multidrug sistant phenotypes (low, one or two antimicrobial-resistant resistance (D), and ECOR phylogrouping (E) was also found phenotypes; medium, three or four antimicrobial-resistant to be heterogeneous. The high abundance of resistant calf phenotypes; high, five or more antimicrobial-resistant pheno- strains and limited overall resistance on organic farms resulted types). A log-linear model fit to the data according to farm type in sampling zeros for three of the nine possible categories in (F), multidrug resistance level (D), and ECOR phylogrouping cows (no medium resistant ECOR B2D strains, highly resistant (E) revealed significant heterogeneity in the association be- phylogroup A strains, or highly resistant phylogroup B1 strains tween these variables (Table 2), including the presence of a were sampled). After correction for sampling zeros in the significant three-way (F-D-E) interaction. In other words, the resistant cow categories, the three-way interaction term (A- best-fit model to these data included all three variables. The D-E) was not significant in the model. These data suggest that model was simplified slightly by reparameterizing and nesting the age of the cattle influences the abundance of multidrug- the variables (F-D-E models I, II, and III in Table 2), which resistant strains but does not influence the genetic composition allowed nonsignificant levels to be removed.
To illustrate the complexity of the interactions affecting bac- Tetracycline and ampicillin resistance determinants. Of the
terial multidrug resistance, we summarized the components of 311 resistant strains analyzed, 129 (41.5%) were Ampr, 281 the E. coli populations using mosaic plots of three different (90.4%) were Tetr, and 112 (36.0%) were resistant to both parameterizations of the F-D-E log-linear model (Fig. 2). Odds drugs. Based on PCR screening for three common E. coli ratios were estimated for significant interactions with respect to a fixed (nested) factor. For example, when the effect of (92.2%) Ampr strains carried the bla multidrug resistance was nested, a significant two-way interac- maining 10 (7.8%) strains did not produce an amplicon for any tion between farm type (F) and phylogroup (E) was found and of the targeted loci. Similarly, for three genes known to confer can be seen by comparing the size of the shaded box to the size E. coli tetracycline resistance (tetA, tetB, and tetC), 268 (95.4%) of the nonshaded boxes for a given level of drug susceptibility Tetr strains carried at least one of these loci, while 13 (4.5%) (D). When the low multidrug resistance level is considered did not. The tetB and tetA genes were the most abundant (top row of panel B), it is clear that the shaded box represent- (64.8% and 28.1%), while the tetC gene was rarely sampled ing group B1 strains on organic farms is larger than the one for conventional farms. The opposite is true for phylogroup A or Genetic composition and resistance determinants. We cre-
B2D strains (larger boxes for the conventional farm category); ated four data sets according to the four genetic determinants hence, a significant interaction is represented by the shaded present in the resistant population. Data from the susceptible organic B1 box (df ϭ 2, ␹2 ϭ 6.3, Pr Ͼ ␹2 ϭ 0.044). The odds population analyzed above were added to each to create a of isolating phylogroup A strains with medium multidrug re- two-level factor (G) for log-linear modeling. Factor G catego- sistance were significantly higher on conventional farms (df ϭ rized strains that carried a resistance gene (bla 2, ␹2 ϭ 8.3, Pr Ͼ ␹2 ϭ 0.016), and the odds of isolating highly or tetC) or did not (susceptible). Due to the low occurrence in resistant, phylogroup B2D strains were significantly higher on the sample, data for tetCϩ strains (n ϭ 7) were pooled with organic farms (df ϭ 2, ␹2 ϭ 10.3, Pr Ͼ ␹2 ϭ 0.006). As data for strains that were negative for all three loci (n ϭ 13) mentioned above, there were no resistant phylogroup B2 and called tetC/other. Data for strains that were negative for strains isolated from organic farms, so the shaded B2D box on the three ␤-lactamase loci (n ϭ 10) were omitted. Log-linear organic farms represents group D strains only. Phylogroup- models were fit to each of the four data sets to test for asso- specific interactions were also found when model effects were ciations between F, G, and E (Table 3).
fixed for E (df ϭ 2, ␹2 ϭ 9.6, Pr Ͼ ␹2 ϭ 0.008) and F (df ϭ 4, Interactions between the resistance loci and ECOR phylo- ␹2 ϭ 18.64, Pr Ͼ ␹2 Ͻ 0.001). These data suggest that conven- groups were not dependent on farm type (no F-G-E interac- FIG. 2. Mosaic plots of the dependent associations between farm type (organic [o] and conventional [c]) (F), multidrug resistance (D), and ECOR phylogrouping (E). Shaded boxes mark significant odds ratio estimates (positive odds only). (A) Overall mosaic plot for F-D-E. (B) F-Einteractions at fixed levels of D. (C) F-D interactions at fixed levels of E. (D) D-E interactions at fixed levels of F.
tions). The genetic composition of the susceptible population based on the presence of three loci (intI1, qacE⌬1, and the was not significantly different from those of the tetA, tetB, or conserved cassette region). Of the total 298 Ampr and/or Tetr tetC/other populations (models not shown). The only signifi- strains, 59 (19.8%) carried a class I integron. We created a cant G-E association was found in the bla three-level factor called “integron populations” that was com- (Table 3), where the odds of sampling the bla prised of resistant, integron-positive strains (intϩ); resistant, conventional farms was significantly associated with ECOR integron-negative strains (intϪ); and susceptible, integron neg- phylogroup A (df ϭ 1, ␹2 ϭ 5.0, Pr Ͼ ␹2 ϭ 0.025). These data ative strains (susceptible). Log-linear models were then used to suggest that the genetic composition of resistant E. coli popu- test for significant associations between farm type (F), ECOR lations on dairy farms is dependent on individual resistance phylogrouping (E), and integron populations (I).
There was no significant phylogroup-integron (E-I) interac- Genetic composition and class I integrons. All Ampr and
tion with farm type (no F-E-I interaction). However, the dis- Tetr strains were screened for the presence of class I integrons tribution of ECOR phylogroups was dependent on integron TABLE 3. Log-linear modeling of farm type, resistance gene, and ECOR phylogrouping ␮ ϩ F ϩ G ϩ E ϩ F-E ϩ F-G ␮ ϩ F ϩ G ϩ E ϩ F-E ϩ F-G ␮ ϩ F ϩ E ϩ F-E ϩ F-G ϩ G-E a Model of farm type (F), resistance gene (G), and ECOR phylogrouping (E). Resistant populations were defined by the determinant they carried. Note that G-E was a significant term in the blaTEM population only. ␮ designates the overall main effect.
b Significant G-E (two-way) interaction for the blaTEM population.
GENETIC COMPOSITION OF E. COLI POPULATIONS ON FARMS presence in these populations (df ϭ 4, ␹2 ϭ 12.4, Pr Ͼ ␹2 ϭ ferred. For example, we expected to find a significant differ- 0.015). The intϪ and susceptible populations were composi- ence between the genetic composition of resistant and suscep- tionally the same (B1 Ͼ A Ͼ B2D), but phylogroups in the intϩ tible populations if a resistant clone swept to high frequency population were evenly sampled. This analysis suggests that the during drug use on conventional farms (clonal expansion). We intϩ population had significantly more group A and B2D had the same expectation if clonal interference were operating strains than the other (intϪ and susceptible) populations.
between multiple resistant clones of the same phylogroup. Anadditional possibility was that clonal interference was operat-ing between clones of different phylogroups. The expectation DISCUSSION
here was a more even distribution of phylogroups compared to In this study, we examined the dynamics of antibiotic selec- the susceptible population. The significant association between tion on conventional and organic dairy farms by comparing the conventional farms, antibiotic resistance, and phylogroup A relative frequencies of four phylogenetic groups (genetic com- strains supports the expectation that strains of this phylogroup position) of antibiotic-resistant and susceptible E. coli popula- were being selected. This observation does not exclude the tions. It is noteworthy that this definition of genetic composi- possibility that resistant strains of other phylogroups were se- tion does not closely measure the amount and distribution of lected but suggests that selection was stronger for group A genetic diversity at the gene and genotype levels but instead is strains. Further characterization is needed, however, to differ- susceptible to the phylogroup level so that the dynamics are entiate between the spread of one clone or multiple closely indicative of broad changes in population genetic structure. A number of studies use this compositional definition to look for The compositional similarity between susceptible popula- patterns in complex systems with many interacting variables.
tions and resistant populations on organic farms suggests that For example, phylogroup B1 strains were found to be common there is an optimal genetic composition (OGC) for the farms in in a variety of host species (16), but they were not numerically this study. In other words, these data suggest that there is a dominant in healthy swine (11) or some human populations stable relative frequency of ECOR phylogroups in dairy cattle (27). In short, these data allow observational inferences to be in the absence of antibiotic selection. Interestingly, populations made about the ecology of certain phylogenetic groups.
of E. coli from freshwater beaches also appear to have an The genetic composition of E. coli from dairy farms was not OGC, as defined by a stable composition at six separate beach similar (B1 Ͼ A Ͼ D Ͼ B2), suggesting that phylogroup B1 sites (41). Although defining the precise mechanism of resis- strains colonize at a higher abundance and, therefore, have a tance requires further work, the overabundance of phylogroup higher relative fitness in dairy cattle. This result is different A strains on conventional dairy farms was significantly associ- than what is seen in Australian herbivores where group B2 strains dominate, although climate and proximity to human presence of class I integrons in the overall resistant population.
activity can also influence the relative distribution of phyloge- linked to phylogroup A strains during selection on conven- Rate of compositional change in antibiotic-resistant popu-
tional farms and resulted in a departure from OGC. If this lations on conventional farms. A key finding of this study is
interpretation is correct, we predict that a more discriminant that there is an overabundance of resistant phylogroup A genetic characterization of Ampr strains from conventional strains on conventional diary farms compared to phylogroup A farms will reveal less genetic diversity in group A strains than strains on organic farms where antibiotic use has been limited.
in resistant strains of phylogroups B1 and B2D.
Based on two observations, we are confident that this over- Ampicillin and other ␤-lactamase antibiotics are commonly abundance has been a consequence of antibiotic use and not used on dairy farms. In a survey of conventional dairy opera- some other conventional farm management practice. First, sus- tions from July 2001 to June 2002 in Pennsylvania, about half ceptible populations on conventional farms and organic farms of the farms (n ϭ 17), for which records were available (n ϭ are nearly identical in genetic composition and are not statis- 33), reported using ampicillin to treat pneumonia in calves tically different, suggesting that these E. coli populations expe- (36). A wider survey of dairy farms (n ϭ 131; 99 conventional rience similar selective pressures in both agricultural environ- and 32 organic) from Michigan, Minnesota, New York, and ments. Second, the composition of the resistant populations on Wisconsin found no ampicillin use on organic farms compared organic farms was not significantly different from the compo- to 8%, 22%, 26%, 12%, and 4% use on conventional farms for sition of the susceptible populations. These observations also treatment of calf respiratory disease, adult respiratory disease, suggest the possibility that the resistant population on conven- clinical mastitis, metritis, and foot problems, respectively (44).
tional farms will evolve to that of the susceptible populations This difference in the use of ampicillin between conventional on organic farms if antibiotic use was stopped. Given that and organic dairy practices may be responsible for the higher organic farms in this study were certified as having not used frequency of resistant phylogroup A strains we observed.
antibiotics for at least 3 years (mean, 8 years; range, 3 to 15 Evidence for hitchhiking of resistance loci. In contrast to the
years), we estimate that, when antibiotic selective pressure is Ampr population, there was no evidence supporting an under- removed, it takes at least this long for the compositional tran- lying clonal model for the dynamics in the Tetr population.
Populations carrying Tetr determinants (tetA, tetB, and tetC/ Evidence for clonal resistance dynamics. Although these
other) were at OGC on both farm types. This observation is data do not address questions about the acquisition of resis- difficult to explain if antibiotic selection and clonal spread were tance determinants by susceptible strains, the observations may occurring on a single farm type. One explanation is that the adequately describe general dynamics after resistance is con- organic farms received an occasional flux of Tetr strains from conventional farms, and the migration was sufficient to main- reported for such change may be longer than the average life tain the observed similarity. However, this explanation seems unlikely because the occasional flux would likely bring Ampr Effect of multidrug resistance on genetic composition. We
strains from conventional farms as well, which in turn would found a rather complicated interaction between farm type, ameliorate the differences discussed above. If Tetr loci were multidrug resistance, and ECOR phylogrouping (Fig. 2). Sig- linked to other compensatory, beneficial mutations, then the nificant associations depended on the way our log-linear model composition of these populations might appear similar regard- was parameterized. However, all three possible parameteriza- tions resulted in a significant association between low multi- Several lines of evidence support the hypothesis for the role drug resistance, group B1 strains, and organic farms. These of hitchhiking or compensatory mutations in Tetr antibiotic data suggest an inverse relationship between multidrug resis- resistance spread. Bartoloni et al. initially described a resistant tance and fitness for group B1 strains on organic farms. Since E. coli population from humans living in a remote Guarani phylogroup B1 strains were the numerically dominant group Indian community in Bolivia (3). Individuals of the village had overall, this result should be encouraging for those seeking to little contact with outsiders and no veterinary or agricultural reduce the amount of multidrug-resistant strains in dairy cattle antibiotic use, relied on rainwater for survival, and had limited available health care (every 3 months). Nevertheless, tetracy- Two of the parameterizations showed an association with cline resistance was found in 64% (69 of 108) of the individuals high multidrug resistance, group D strains, and organic tested. Pallecchi et al. recently characterized the underlying farms. This result is important because a number of human genetic determinants and ECOR phylogroups for 113 resistantstrains of the original collection (28). The authors found that pathogens, including the strain most associated with human of the 103 Tetr strains analyzed, 52 carried tetA and 51 carried hemorrhagic colitis, O157:H7, belong to this group (accord- tetB. These loci were distributed among all four E. coli phylo- ing to the PCR method used here). However, we are cau- groups (same procedure used in this study) and were found on tious to base generalizations on this analysis because (i) we all five conjugative plasmids identified in this study. The abun- did not design our sampling study to directly address this dance and distribution of Tetr strains in this remote community question and (ii) the abundance of strains used for these support the hypothesis that naturally occurring Tetr deter- comparisons were low. For example, the F-E(D ϭ high) minants circulate in hosts for reasons other than selection by association (Table 2) between highly resistant phylogroup D strains and organic farms becomes nonsignificant if two Support of the hitchhiking hypothesis for Tetr loci is also fewer strains were sampled on organic farms and two addi- consistent with the description of a “calf-adapted” E. coli pop- tional strains were sampled on conventional farms. Simi- ulation that was multiply resistant to streptomycin, sulfadia- larly, we are cautious about the association between highly zine, and tetracycline (20). Almost all strains (49 of 50) ana- multidrug-resistant phylogroup B1 strains and medium mul- lyzed shared a ϳ140-kb chromosomal location and the same tidrug-resistant phylogroup A strains on conventional farms resistance loci (strA, sul2, and tetB) and were genetically because the significance of the association depends on the diverse by pulsed-field gel electrophoresis. Khachatryan and colleagues showed that on average the streptomycin-, sulfadi- Conclusions. The genetic composition for the antibiotic-
azine-, and tetracycline-resistant population outcompeted sus- susceptible E. coli populations on conventional farms, suscep- ceptible strains in vitro and in neonatal calves (18). They also tible E. coli populations on organic farms, and resistant E. coli showed that the resistance loci themselves do not influence this populations on organic farms was the same, suggesting a rel- selective advantage (19). Their main conclusion was that the ative steady-state genetic composition for the farms in this combination of strA, sul2, and tetB in the original resistant study. In contrast, the resistant population on conventional population had hitchhiked with some other fitness-conferring farms had an overabundance of Ampr, group A strains that could be explained by linked loci (bla Effect of age on genetic composition. Sato et al. showed that
during a selective sweep or clonal interference among closely the resistant strains examined here were most prevalent in related strains. Given the amount of time since organic farms calves on conventional farms (34). A similar positive associa- had abandoned conventional practices, the rate of composi- tion has been reported in other studies of preweaned calves tional change was estimated to be between 3 and 15 years and adult cattle (5, 7, 20). These observations suggest thatantibiotic-resistant strains are better at colonizing calves than (mean, 8 years). In contrast to the Ampr population, the Tetr adult cows. One explanation for these observations is that the populations analyzed here showed no clonal dynamics and cost of resistance (fitness cost) becomes too great as the host appeared to achieve a steady-state genetic composition. These gastrointestinal tract matures and competition with other data add support to the hypothesis that the abundance and microbes increases. Regardless of its influence on preva- distribution of Tetr determinants are weakly influenced by lence, the age of cattle had little effect on the distribution of antibiotic use. We found that the age of cattle had little influ- phylogenetic groups in either the susceptible or resistant ence on the genetic composition of the resistant or susceptible populations of this study. These data suggest that resistant populations. Finally, phylogroup B1 strains with low multidrug strains decrease in abundance as the cattle age, while the resistance were significantly associated with organic farms, sug- genetic composition of the population remains stable. Other gesting that these dairy farming practices have a proportion- analyses of human strains showed a significant association ately large, negative effect on the prevalence of multidrug- between host age and genetic composition, but the time GENETIC COMPOSITION OF E. COLI POPULATIONS ON FARMS ACKNOWLEDGMENTS
21. Levin, B. R., and C. T. Bergstrom. 2000. Bacteria are different: observations,
interpretations, speculations, and opinions about the mechanisms of adap- This work was supported in part by MRU matching funds from the tive evolution in prokaryotes. Proc. Natl. Acad. Sci. USA 97:6981–6985.
College of Veterinary Medicine and the Graduate College of Michigan 22. Levy, S. B. 2002. The 2000 Garrod lecture. Factors impacting on the problem
of antibiotic resistance. J. Antimicrob. Chemother. 49:25–30.
23. Lindstedt, B. A., E. Heir, I. Nygard, and G. Kapperud. 2003. Characteriza-
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