Landscape heterogeneity and local adaptation define the spatial genetic structure of Pacific salmon in a pristine environment

Identifying the spatial distribution of genetic variation across the landscape is an essential step in informing species conservation. Comparison of closely related and geographically overlapping species can be particularly useful in cases where landscape may similarly influence genetic structure. Congruent patterns among species highlight the importance that landscape heterogeneity plays in determining genetic structure whereas contrasting patterns emphasize differences in species-specific ecology and life-history or the importance of species-specific adaptation to local environments. We examined the interacting roles of demography and adaptation in determining spatial genetic structure in two closely related and geographically overlapping species in a pristine environment. Using single nucleotide polymorphism (SNP) loci exhibiting both neutral and putative adaptive variation, we evaluated the genetic structure of sockeye salmon in the Copper River, Alaska; these data were compared to existing data for Chinook salmon from the same region. Overall, both species exhibited patterns of isolation by distance; the spatial distribution of populations largely determined the distribution of genetic variation across the landscape. Further, both species exhibited largely congruent patterns of within- and among-population genetic diversity, highlighting the role that landscape heterogeneity and historical processes play in determining spatial genetic structure. Potential adaptive differences among geographically proximate sockeye salmon populations were observed when high F_ST outlier SNPs were evaluated in a landscape genetics context. Results were evaluated in the context of conservation efforts with an emphasis on reproductive isolation, historical processes, and local adaptation.     

Evaluation of denaturing gradient gel electrophoresis to differentiate Escherichia coli populations in secondary environments

The development of methodology to differentiate mixed populations of Escherichia coli in the secondary habitat might improve monitoring of fecal pollution indicators and facilitate the development of strategies to mitigate bacterial pollution. The objective of this study was to determine the ability of denaturing gradient gel electrophoresis (DGGE) to differentiate mixed assemblages of E. coli in the natural environment. After confirming the identity of 184 environmental bacterial isolates as E. coli, each was subjected to polymerase chain reaction (PCR) of the beta-glucuronidase gene (uidA) followed by DGGE fingerprinting. The ability of DGGE to discriminate individual isolates at the strain level was determined by comparing fingerprints to those resulting from a standard, library-dependent fingerprinting method, BOX-PCR. Computerized analysis of fingerprints indicated that DGGE and BOX-PCR identified 15 and 21 unique phylotypes respectively. Rank-abundance plots comparing the numerical distribution of unique E. coli phylotypes detected by both methods revealed no difference in resolution at the population level. In water and sediment samples from two beaches, DGGE effectively distinguished indigenous E. coli populations with an average rate of correct classification (site-based) of 83%. Denaturing gradient gel electrophoresis of uidA genes isolated and PCR-amplified from environmental samples appears to be an effective tool to differentiate unique E. coli populations and should be useful to characterize E. coli dynamics in the secondary environment.     

Effects of population succession on demographic and genetic processes: predictions and tests in the daylily Hemerocallis thunbergii (Liliaceae)

Spatial genetic structure within plant populations is influenced by variation in demographic processes through space and time, including a population's successional status. To determine how demographic structure and fine-scale genetic structure (FSGS) change with stages in a population's successional history, we studied Hemerocallis thunbergii (Liliaceae), a nocturnal flowering and hawkmoth-pollinated herbaceous perennial with rapid population turnover dynamics. We examined nine populations assigned to three successive stages of population succession: expansion, maturation, and senescence. We developed stage-specific expectations for within-population demographic and genetic structure, and then for each population quantified the spatial aggregation of individuals and genotypes using spatial autocorrelation methods (nonaccumulative O-ring and kinship statistics, respectively), and at the landscape level measured inbreeding and genetic structure using Wright's F-statistics. Analyses using the O-ring statistic revealed significant aggregation of individuals at short spatial scales in expanding and senescing populations, in particular, which may reflect restricted seed dispersal around maternal individuals combined with relatively low local population densities at these stages. Significant FSGS was found for three of four expanding, no mature, and only one senescing population, a pattern generally consistent with expectations of successional processes. Although allozyme genetic diversity was high within populations (mean %P = 78.9 and H(E) = 0.281), landscape-level differentiation among sites was also high (F(ST) = 0.166) and all populations exhibited a significant deficit of heterozygotes relative to Hardy-Weinberg expectations (range F = 0.201-0.424, mean F(IS) = 0.321). Within populations, F was not correlated with the degree of FSGS, thus suggesting inbreeding due primarily to selfing as opposed to mating among close relatives in spatially structured populations. Our results demonstrate considerable variation in the spatial distribution of individuals and patterns and magnitude of FSGS in H. thunbergii populations across the landscape. This variation is generally consistent with succession-stage-specific differences in ecological processes operating within these populations.     

Scale-Dependent Effects of a Heterogeneous Landscape on Genetic Differentiation in the Central American Squirrel Monkey (Saimiri oerstedii)

Landscape genetic studies offer a fine-scale understanding of how habitat heterogeneity influences population genetic structure. We examined population genetic structure and conducted a landscape genetic analysis for the endangered Central American Squirrel Monkey (Saimiri oerstedii) that lives in the fragmented, human-modified habitats of the Central Pacific region of Costa Rica. We analyzed non-invasively collected fecal samples from 244 individuals from 14 groups for 16 microsatellite markers. We found two geographically separate genetic clusters in the Central Pacific region with evidence of recent gene flow among them. We also found significant differentiation among groups of S. o. citrinellus using pairwise F(ST) comparisons. These groups are in fragments of secondary forest separated by unsuitable "matrix" habitats such as cattle pasture, commercial African oil palm plantations, and human residential areas. We used an individual-based landscape genetic approach to measure spatial patterns of genetic variance while taking into account landscape heterogeneity. We found that large, commercial oil palm plantations represent moderate barriers to gene flow between populations, but cattle pastures, rivers, and residential areas do not. However, the influence of oil palm plantations on genetic variance was diminished when we restricted analyses to within population pairs, suggesting that their effect is scale-dependent and manifests during longer dispersal events among populations. We show that when landscape genetic methods are applied rigorously and at the right scale, they are sensitive enough to track population processes even in species with long, overlapping generations such as primates. Thus landscape genetic approaches are extremely valuable for the conservation management of a diverse array of endangered species in heterogeneous, human-modified habitats. Our results also stress the importance of explicitly considering the heterogeneity of matrix habitats in landscape genetic studies, instead of assuming that all matrix habitats have a uniform effect on population genetic processes.     

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.     

Statistical analyses: possible reasons for unreliability of source tracking efforts

Analyses for the presence of indicator organisms provide information on the microbiological quality of water. Indicator organisms recommended by the United States Environmental Protection Agency for monitoring the microbiological quality of water include Escherichia coli, a thermotolerant coliform found in the feces of warm-blooded animals. These bacteria can also be isolated from environmental sources such as the recreational and pristine waters of tropical rain forests in the absence of fecal contamination. In the present study, E. coli isolates were compared to E. coli K12 (ATCC 29425) by restriction fragment length polymorphism using pulsed-field gel electrophoresis. Theoretically, genomic DNA patterns generated by PFGE are highly specific for the different isolates of an organism and can be used to identify variability between environmental and fecal isolates. Our results indicate a different band pattern for almost every one of the E. coli isolates analyzed. Cluster analysis did not show any relations between isolates and their source of origin. Only the discriminant function analysis grouped the samples with the source of origin. The discrepancy observed between the cluster analysis and discriminant function analysis relies on their mathematical basis. Our validation analyses indicate the presence of an artifact (i.e., grouping of environmental versus fecal samples as a product of the statistical analyses used and not as a result of separation in terms of source of origin) in the classification results; therefore, the large genetic heterogeneity observed in these E. coli populations makes the grouping of isolates by source rather difficult, if not impossible.     

Presence and growth of naturalized Escherichia coli in temperate soils from Lake Superior watersheds

The presence of Escherichia coli in water is used as an indicator of fecal contamination, but recent reports indicate that soil populations can also be detected in tropical, subtropical, and some temperate environments. In this study, we report that viable E. coli populations were repeatedly isolated from northern temperate soils in three Lake Superior watersheds from October 2003 to October 2004. Seasonal variation in the population density of soilborne E. coli was observed; the greatest cell densities, up to 3 x 10(3) CFU/g soil, were found in the summer to fall (June to October), and the lowest numbers, < or =1 CFU/g soil, occurred during the winter to spring months (February to May). Horizontal, fluorophore-enhanced repetitive extragenic palindromic PCR (HFERP) DNA fingerprint analyses indicated that identical soilborne E. coli genotypes, those with > or =92% similarity values, overwintered in frozen soil and were present over time. Soilborne E. coli strains had HFERP DNA fingerprints that were unique to specific soils and locations, suggesting that these E. coli strains became naturalized, autochthonous members of the soil microbial community. In laboratory studies, naturalized E. coli strains had the ability to grow and replicate to high cell densities, up to 4.2 x 10(5) CFU/g soil, in nonsterile soils when incubated at 30 or 37 degrees C and survived longer than 1 month when soil temperatures were < or =25 degrees C. To our knowledge, this is the first report of the growth of naturalized E. coli in nonsterile, nonamended soils. The presence of significant populations of naturalized populations of E. coli in temperate soils may confound the use of this bacterium as an indicator of fecal contamination.     

A conceptual framework for the spatial analysis of landscape genetic data

Understanding how landscape heterogeneity constrains gene flow and the spread of adaptive genetic variation is important for biological conservation given current global change. However, the integration of population genetics, landscape ecology and spatial statistics remains an interdisciplinary challenge at the levels of concepts and methods. We present a conceptual framework to relate the spatial distribution of genetic variation to the processes of gene flow and adaptation as regulated by spatial heterogeneity of the environment, while explicitly considering the spatial and temporal dynamics of landscapes, organisms and their genes. When selecting the appropriate analytical methods, it is necessary to consider the effects of multiple processes and the nature of population genetic data. Our framework relates key landscape genetics questions to four levels of analysis: (i) node-based methods, which model the spatial distribution of alleles at sampling locations (nodes) from local site characteristics; these methods are suitable for modeling adaptive genetic variation while accounting for the presence of spatial autocorrelation. (ii) Link-based methods, which model the probability of gene flow between two patches (link) and relate neutral molecular marker data to landscape heterogeneity; these methods are suitable for modeling neutral genetic variation but are subject to inferential problems, which may be alleviated by reducing links based on a network model of the population. (iii) Neighborhood-based methods, which model the connectivity of a focal patch with all other patches in its local neighborhood; these methods provide a link to metapopulation theory and landscape connectivity modeling and may allow the integration of node- and link-based information, but applications in landscape genetics are still limited. (iv) Boundary-based methods, which delineate genetically homogeneous populations and infer the location of genetic boundaries; these methods are suitable for testing for barrier effects of landscape features in a hypothesis-testing framework. We conclude that the power to detect the effect of landscape heterogeneity on the spatial distribution of genetic variation can be increased by explicit consideration of underlying assumptions and choice of an appropriate analytical approach depending on the research question.     

Genetic relatedness of Escherichia coli isolates in interstitial water from a Lake Huron (Canada) beach

Research was undertaken to characterize Escherichia coli isolates in interstitial water samples of a sandy beach on the southeastern shore of Lake Huron, Ontario, Canada. A survey of the beach area revealed the highest abundance of E. coli in interstitial water of the foreshore beach sand next to the swash zone. Higher concentrations of E. coli (up to 1.6 x 10(6) CFU/100 ml of water) were observed in the interstitial water from the sampling holes on the beach itself compared to lake water and sediment. Repetitive extragenic palindromic PCR (REP-PCR) was used to characterize the genetic diversity of E. coli isolates from interstitial water samples on the beach. E. coli isolates from the same sampling location frequently exhibited the same REP-PCR pattern or were highly similar to each other. In contrast, E. coli isolates from different sampling locations represented populations distinct from each other. This study has identified a unique ecological niche within the foreshore area of the beach where E. coli may survive and possibly multiply outside of host organisms. The results are of interest as increasing concentrations of E. coli in recreational waters are often considered to be an indication of recent fecal pollution.     

Fine-scale analysis reveals cryptic landscape genetic structure in desert tortoises

Characterizing the effects of landscape features on genetic variation is essential for understanding how landscapes shape patterns of gene flow and spatial genetic structure of populations. Most landscape genetics studies have focused on patterns of gene flow at a regional scale. However, the genetic structure of populations at a local scale may be influenced by a unique suite of landscape variables that have little bearing on connectivity patterns observed at broader spatial scales. We investigated fine-scale spatial patterns of genetic variation and gene flow in relation to features of the landscape in desert tortoise (Gopherus agassizii), using 859 tortoises genotyped at 16 microsatellite loci with associated data on geographic location, sex, elevation, slope, and soil type, and spatial relationship to putative barriers (power lines, roads). We used spatially explicit and non-explicit Bayesian clustering algorithms to partition the sample into discrete clusters, and characterize the relationships between genetic distance and ecological variables to identify factors with the greatest influence on gene flow at a local scale. Desert tortoises exhibit weak genetic structure at a local scale, and we identified two subpopulations across the study area. Although genetic differentiation between the subpopulations was low, our landscape genetic analysis identified both natural (slope) and anthropogenic (roads) landscape variables that have significantly influenced gene flow within this local population. We show that desert tortoise movements at a local scale are influenced by features of the landscape, and that these features are different than those that influence gene flow at larger scales. Our findings are important for desert tortoise conservation and management, particularly in light of recent translocation efforts in the region. More generally, our results indicate that recent landscape changes can affect gene flow at a local scale and that their effects can be detected almost immediately.     

Landscape structure and the genetic effects of a population collapse

Both landscape structure and population size fluctuations influence population genetics. While independent effects of these factors on genetic patterns and processes are well studied, a key challenge is to understand their interaction, as populations are simultaneously exposed to habitat fragmentation and climatic changes that increase variability in population size. In a population network of an alpine butterfly, abundance declined 60–100% in 2003 because of low over-winter survival. Across the network, mean microsatellite genetic diversity did not change. However, patch connectivity and local severity of the collapse interacted to determine allelic richness change within populations, indicating that patch connectivity can mediate genetic response to a demographic collapse. The collapse strongly affected spatial genetic structure, leading to a breakdown of isolation-by-distance and loss of landscape genetic pattern. Our study reveals important interactions between landscape structure and temporal demographic variability on the genetic diversity and genetic differentiation of populations. Projected future changes to both landscape and climate may lead to loss of genetic variability from the studied populations, and selection acting on adaptive variation will likely occur within the context of an increasing influence of genetic drift.     

Do landscape processes predict phylogeographic patterns in the wood frog?

Understanding factors that influence population connectivity and the spatial distribution of genetic variation is a major goal in molecular ecology. Improvements in the availability of high-resolution geographic data have made it increasingly possible to quantify the effects of landscape features on dispersal and genetic structure. However, most studies examining such landscape effects have been conducted at very fine (e.g. landscape genetics) or broad (e.g. phylogeography) spatial scales. Thus, the extent to which processes operating at fine spatial scales are linked to patterns at larger scales remains unclear. Here, we test whether factors impacting wood frog dispersal at fine spatial scales are correlated with genetic structure at regional scales. Using recently developed methods borrowed from electrical circuit theory, we generated landscape resistance matrices among wood frog populations in eastern North America based on slope, a wetness index, land cover and absolute barriers to wood frog dispersal. We then determined whether these matrices are correlated with genetic structure based on six microsatellite markers and whether such correlations outperform a landscape-free model of isolation by resistance. We observed significant genetic structure at regional spatial scales. However, topography and landscape variables associated with the intervening habitat between sites provide little explanation for patterns of genetic structure. Instead, absolute dispersal barriers appear to be the best predictor of regional genetic structure in this species. Our results suggest that landscape variables that influence dispersal, microhabitat selection and population structure at fine spatial scales do not necessarily explain patterns of genetic structure at broader scales.     

Genetic diversity and population structure of Escherichia coli isolated from freshwater beaches

Escherichia coli is an important member of the gastrointestinal tract of humans and warm-blooded animals (primary habitat). In the external environment outside the host (secondary habitat), it is often considered to be only a transient member of the microbiota found in water and soil, although recent evidence suggests that some strains can persist in temperate soils and freshwater beaches. Here we quantified the population genetic structure of E. coli from a longitudinal collection of environmental strains isolated from six freshwater beaches along Lake Huron and the St. Clair River in Michigan. Multilocus enzyme electrophoresis (MLEE) and multilocus sequence typing (MLST) revealed extensive genetic diversity among 185 E. coli isolates with an average of 40 alleles per locus. Despite evidence for extensive recombination generating new alleles and genotypic diversity, several genotypes marked by distinct MLEE and MLST profiles were repeatedly recovered from separate sites at different times. A PCR-based phylogrouping technique showed that the persistent, naturalized E. coli belonged to the B1 group. These results support the hypothesis that persistent genotypes have an adaptive advantage in the secondary habitat outside the host.     

Geographical and Ecological Drivers of Mitonuclear Genetic Divergence in a Mediterranean Grasshopper

The study of the neutral and/or selective processes driving genetic variation in natural populations is central to determine the evolutionary history of species and lineages and understand how they interact with different historical and contemporary components of landscape heterogeneity. Here, we combine nuclear and mitochondrial data to study the processes shaping genetic divergence in the Mediterranean esparto grasshopper (Ramburiella hispanica). Our analyses revealed the presence of three main lineages, two in Europe that split in the Early-Middle Pleistocene and one in North Africa that diverged from the two European ones after the Messinian. Lineage-specific potential distribution models and tests of environmental niche differentiation suggest that the phylogeographic structure of the species was driven by allopatric divergence due to the re-opening of the Gibraltar strait at the end of the Messinian (Europe–Africa split) and population fragmentation in geographically isolated Pleistocene climatic refugia (European split). Although we found no evidence for environment as an important driver of genetic divergence at the onset of lineage formation, our analyses considering the spatial distribution of populations and different aspects of landscape composition suggest that genetic differentiation at mitochondrial loci was largely explained by environmental dissimilarity, whereas resistance-based estimates of geographical distance were the only predictors of genetic differentiation at nuclear markers. Overall, our study shows that although historical factors have largely shaped concordant range-wide patterns of mitonuclear genetic structure in the esparto grasshopper, different contemporary processes (neutral gene flow vs. environmental-based selection) seem to be governing the spatial distribution of genetic variation in the two genomes.     

Linking genetic and ecological differentiation in an ungulate with a circumpolar distribution

Genetic differentiation among populations may arise from the disruption of gene flow due to local adaptation to distinct environments and/or neutral accumulation of mutations and genetic drift resulted from geographical isolation. Quantifying the role of these processes in determining the genetic structure of natural populations remains challenging. Here, we analyze the relative contribution of isolation‐by‐resistance (IBR), isolation‐by‐environment (IBE), genetic drift and historical isolation in allopatry during Pleistocene glacial cycles on shaping patterns of genetic differentiation in caribou/reindeer populations Rangifer tarandus across the entire distribution range of the species. Our study integrates analyses at range‐wide and regional scales to partial out the effects of historical and contemporary isolation mechanisms. At the circumpolar scale, our results indicate that genetic differentiation is predominantly explained by IBR and historical isolation. At a regional scale, we found that IBR, IBE and population size significantly explained the spatial distribution of genetic variation among populations belonging to the Euro‐Beringian lineage within North America. In contrast, genetic differentiation among populations within the North American lineage was predominantly explained by IBR and population size, but not IBE. We also found discrepancies between genetic and ecotype designation across the Holarctic species distribution range. Overall, these results indicate that multiple isolating mechanisms have played roles in shaping the spatial distribution of genetic variation across the distribution range of a large mammal with high potential for gene flow. Considering multiple spatial scales and simultaneously testing a comprehensive suite of potential isolating mechanisms, our study contributes to understand the ecological and evolutionary processes underlying organism–landscape interactions.     

Testing the role of ancient and contemporary landscapes on structuring genetic variation in a specialist grasshopper

Understanding the processes underlying spatial patterns of genetic diversity and structure of natural populations is a central topic in evolutionary biogeography. In this study, we combine data on ancient and contemporary landscape composition to get a comprehensive view of the factors shaping genetic variation across the populations of the scrub‐legume grasshopper (Chorthippus binotatus binotatus) from the biogeographically complex region of southeast Iberia. First, we examined geographical patterns of genetic structure and employed an approximate Bayesian computation (ABC) approach to compare different plausible scenarios of population divergence. Second, we used a landscape genetic framework to test for the effects of (1) Late Miocene paleogeography, (2) Pleistocene climate fluctuations, and (3) contemporary topographic complexity on the spatial patterns of population genetic differentiation. Genetic structure and ABC analyses supported the presence of three genetic clusters and a sequential west‐to‐east splitting model that predated the last glacial maximum (LGM, c. 21 Kya). Landscape genetic analyses revealed that population genetic differentiation was primarily shaped by contemporary topographic complexity, but was not explained by any paleogeographic scenario or resistance distances based on climate suitability in the present or during the LGM. Overall, this study emphasizes the need of integrating information on ancient and contemporary landscape composition to get a comprehensive view of their relative importance to explain spatial patterns of genetic variation in organisms inhabiting regions with complex biogeographical histories.     

Effect of landscape features on genetic structure of the goitered gazelle (<Emphasis Type="Italic">Gazella subgutturosa</Emphasis>) in Central Iran

The populations of goitered gazelle suffered significant decline due to natural and anthropogenic factors over the last century. Investigating the effects of barriers on gene flow among the remaining populations is vital for conservation planning. Here we adopted a landscape genetics approach to evaluate the genetic structure of the goitered gazelle in Central Iran and the effects of landscape features on gene flow using 15 polymorphic microsatellite loci. Spatial autocorrelation, isolation by distance (IBD) and isolation by resistance (IBR) models were used to elucidate the effects of landscape features on the genetic structure. Ecological modeling was used to construct landscape permeability and resistance map using 12 ecogeographical variables. Bayesian algorithms revealed three genetically homogeneous groups and restricted dispersal pattern in the six populations. The IBD and spatial autocorrelation revealed a pattern of decreasing relatedness with increasing distance. The distribution of potential habitats was strongly correlated with bioclimatic factors, vegetation type, and elevation. Resistance distances and graph theory were significantly related with variation in genetic structure, suggesting that gazelles are affected by landscape composition. The IBD showed greater impact on genetic structure than IBR. The Mantel and partial Mantel tests indicated low but non-significant effects of anthropogenic barriers on observed genetic structure. We concluded that a combination of geographic distance, landscape resistance, and anthropogenic factors are affecting the genetic structure and gene flow of populations. Future road construction might impede connectivity and gene exchange of populations. Conservation measures on this vulnerable species should consider some isolated population as separate management units.     

Demographic processes shaping genetic variation

Demographic processes modulate genome-wide levels and patterns of genetic variation via impacting effective population size independently of natural selection. Such processes include the perturbation of population distributions from external events shaping habitat landscape and internal factors shaping the probability of contemporaneous alleles in a population (coalescence). Several patterns have recently emerged: spatial and temporal heterogeneity in population structure have different influences on the persistence of new mutations and genetic variation, multi-locus analyses indicate that gene flow continues to occur during speciation and the incorporation of demographic processes into models of molecular evolution and association genetics approaches has improved statistical power to detect deviations from neutral-equilibrium expectations and decreased false positive rates.     

Clonal populations of thermotolerant Enterobacteriaceae in recreational water and their potential interference with fecal Escherichia coli counts

Bacterial strains were isolated from beach water samples using the original Environmental Protection Agency method for Escherichia coli enumeration and analyzed by pulsed-field gel electrophoresis (PFGE). Identical PFGE patterns were found for numerous isolates from 4 of the 9 days sampled, suggesting environmental replication. 16S rRNA gene sequencing, API 20E biochemical testing, and the absence of beta-glucuronidase activity revealed that these clonal isolates were Klebsiella, Citrobacter, and Enterobacter spp. In contrast, 82% of the nonclonal isolates from water samples were confirmed to be E. coli, and 16% were identified as other fecal coliforms. These nonclonal isolates produced a diverse range of PFGE patterns similar to those of isolates obtained directly from untreated sewage and gull droppings. beta-Glucuronidase activity was critical in distinguishing E. coli from other fecal coliforms, particularly for the clonal isolates. These findings demonstrate that E. coli is a better indicator of fecal pollution than fecal coliforms, which may replicate in the environment and falsely elevate indicator organism levels.     

Origin of contamination and genetic diversity of Escherichia coli in beef cattle

The possible origin of beef contamination and genetic diversity of Escherichia coli populations in beef cattle, on carcasses and ground beef, was examined by using random amplification of polymorphic DNA (RAPD) and PCR-restriction fragment length polymorphism (PCR-RFLP) analysis of the fliC gene. E. coli was recovered from the feces of 10 beef cattle during pasture grazing and feedlot finishing and from hides, carcasses, and ground beef after slaughter. The 1,403 E. coli isolates (855 fecal, 320 hide, 153 carcass, and 75 ground beef) were grouped into 121 genetic subtypes by using the RAPD method. Some of the genetic subtypes in cattle feces were also recovered from hides, prechilled carcasses, chilled carcasses, and ground beef. E. coli genetic subtypes were shared among cattle at all sample times, but a number of transient types were unique to individual animals. The genetic diversity of the E. coli population changed over time within individual animals grazing on pasture and in the feedlot. Isolates from one animal (59 fecal, 30 hide, 19 carcass, and 12 ground beef) were characterized by the PCR-RFLP analysis of the fliC gene and were grouped into eight genotypes. There was good agreement between the results obtained with the RAPD and PCR-RFLP techniques. In conclusion, the E. coli contaminating meat can originate from cattle feces, and the E. coli population in beef cattle was highly diverse. Also, genetic subtypes can be shared among animals or can be unique to an animal, and they are constantly changing.