Nancy C. Stoppe

Escherichia coli phylogenetic group determination and its application in the identification of the major animal source of fecal contamination

BackgroundEscherichia coli strains are commonly found in the gut microflora of warm-blooded animals. These strains can be assigned to one of the four main phylogenetic groups, A, B1, B2 and D, which can be divided into seven subgroups (A0, A1, B1, B22, B23, D1 and D2), according to the combination of the three genetic markers chuA, yjaA and DNA fragment TspE4.C2. Distinct studies have demonstrated that these phylo-groups differ in the presence of virulence factors, ecological niches and life-history. Therefore, the aim of this work was to analyze the distribution of these E. coli phylo-groups in 94 human strains, 13 chicken strains, 50 cow strains, 16 goat strains, 39 pig strains and 29 sheep strains and to verify the potential of this analysis to investigate the source of fecal contamination.ResultsThe results indicated that the distribution of phylogenetic groups, subgroups and genetic markers is non-random in the hosts analyzed. Strains from group B1 were present in all hosts analyzed but were more prevalent in cow, goat and sheep samples. Subgroup B23 was only found in human samples. The diversity and the similarity indexes have indicated a similarity between the E. coli population structure of human and pig samples and among cow, goat and sheep samples. Correspondence analysis using contingence tables of subgroups, groups and genetic markers frequencies allowed the visualization of the differences among animal samples and the identification of the animal source of an external validation set. The classifier tools Binary logistic regression and Partial least square -- discriminant analysis, using the genetic markers profile of the strains, differentiated the herbivorous from the omnivorous strains, with an average error rate of 17%.ConclusionsThis is the first work, as far as we are aware, that identifies the major source of fecal contamination of a pool of strains instead of a unique strain. We concluded that the analysis of the E. coli population structure can be useful as a supplementary bacterial source tracking tool.

Pathogenic parasites and enteroviruses in wastewater: support for a regulation on water reuse.

Brazilian regulations for nonpotable reuse are being established using World Health Organization guidelines, however, they should be developed based on local monitoring studies. This study intended to analyze enteroviruses, protozoa and viable Ascaris sp. eggs in raw (24) and treated (24) effluents from four Wastewater Treatment Plants of São Paulo State, Brazil. The protozoa were detected with the US Environmental Protection Agency (USEPA) Method 1623 in the treated effluents and by centrifugation/Immunomagnetic Separation in the raw influent samples. Viable Ascaris sp. eggs were analyzed according to a modified USEPA method. Enteroviruses were quantified by using human rhabdomyosarcoma cells after adequate concentration procedures. All wastewater influents were positive for Giardia sp. whereas Cryptosporidium sp. was detected in 58.3% of the samples. Giardia sp. and Cryptosporidium sp. were present in 79.2 and 25.0% respectively, of the treated wastewater samples. Viable Ascaris sp. eggs were detected in 50.0 and 12.5% of influent and treated wastewater samples. Enteroviruses were isolated in the 24 raw influent samples and in 46% of the treated samples. Taking into account the densities of Giardia sp. in some treated wastewaters intended to be used as reclaimed water, Quantitative Microbial Risk Assessment studies should be conducted to establish pathogen quantitative criteria for a future Brazilian regulation for water reuse.

Use of Escherichia coli BOX-PCR fingerprints to identify sources of fecal contamination of water bodies in the State of São Paulo, Brazil.

Repetitive element sequence-based polymerase chain reaction (rep-PCR) is one of the commonest methods used to identify sources of fecal contamination of water systems. In this work, BOX-A1R-based repetitive extragenic palindromic-PCR (BOX-PCR) was used to discriminate Escherichia coli strains originating from different animals and water sources, and the suitability of the technique for bacterial source tracking (BST) was evaluated. A total of 214 strains from humans, 150 strains from animals, 55 strains from sewage and 77 strains from water bodies were analyzed by the BOX-PCR technique. When maximum similarity between the fingerprints was used, a correct classification rate of 84% was achieved for strains from human and animal sources. Furthermore, 95% of the strains found in sewage were classified as being from human sources by at least one of the four classification tools used. Classification of the strains found in water bodies in the State of São Paulo was based on the fingerprints obtained for human and animal sources. Most of the sampling sites appeared to be affected by mixed sources of fecal contamination. The use of BOX-PCR for BST could be especially valuable in developing countries, where simplicity and cost are important considerations.

Prevalence of virulence factors in Escherichia coli isolated from healthy animals and water sources in Brazil

The aim of this work was to verify the presence of seven virulence factors (ST, LT, eae, stx(1), stx(2), INV and EAEC) among Escherichia coli strains isolated from healthy humans, bovines, chickens, sheep, pigs and goats, from two sewage treatment plants and from the Tietê River. We have found a high prevalence of eae, stx(1) and stx(2) in ruminants. The EAEC gene was only found in humans and sewage. No strains presented ST, LT or INV. BOX-PCR fingerprints revealed a high diversity among the strains analysed and a non-clonal origin of strains that presented the same virulence factors. Therefore, we concluded that ruminants may constitute an important reservoir of most diarrheagenic E. coli in Brazil, except for EAEC strains. These results emphasize the importance of the identification of the animal source of fecal contamination for the correct water risk assessment.

Clustering of water bodies in unpolluted and polluted environments based on Escherichia coli phylogroup abundance using a simple interaction database

Different types of water bodies, including lakes, streams, and coastal marine waters, are often susceptible to fecal contamination from a range of point and nonpoint sources, and have been evaluated using fecal indicator microorganisms. The most commonly used fecal indicator is Escherichia coli, but traditional cultivation methods do not allow discrimination of the source of pollution. The use of triplex PCR offers an approach that is fast and inexpensive, and here enabled the identification of phylogroups. The phylogenetic distribution of E. coli subgroups isolated from water samples revealed higher frequencies of subgroups A1 and B23 in rivers impacted by human pollution sources, while subgroups D1 and D2 were associated with pristine sites, and subgroup B1 with domesticated animal sources, suggesting their use as a first screening for pollution source identification. A simple classification is also proposed based on phylogenetic subgroup distribution using the w-clique metric, enabling differentiation of polluted and unpolluted sites.

Social Network Analysis Metrics and Their Application in Microbiological Network Studies

In the last decade, several researchers have been using interaction networks resources to investigate of the role of biologic interactions in biodiversity maintenance. The conceptual foundations are the same as in Social Networks (such as Facebook), that have brought a set of metrics to study the network structure and the function of each node in the network. Thus, the aim of this work was to assess the application of Social Network Analysis (SNA) concepts and metrics in microbiological interaction networks, to identify patterns of cohesive subgroups, besides discovering new knowledge regarding the underlying structure of subgroups. We built a bipartite microbiological interaction database containing frequency of phylogenetic subgroups in water bodies and applied the following SNA metrics: dependence distribution, strength, betweenness centrality and clique. The sna package for the R program, Pajek, Dieta and Ucinet programs were the tools used. Among the results, we found that SNA concepts and metrics are extremely useful in microbiological studies to understand the correlation between each node in the network (the generalist and the predominant nodes), as well as to analyze the co-occurrence pattern of microorganisms in the network (cohesive subgroups).

Worldwide Phylogenetic Group Patterns of Escherichia coli from Commensal Human and Wastewater Treatment Plant Isolates

Escherichia coli is an important microorganism in the gastrointestinal tract of warm-blooded animals. Commensal populations of E. coli consist of stable genetic isolates, which means that each individual has only one phylogenetic group (phylogroup). We evaluated the frequency of human commensal E. coli phylogroups from 116 people and observed that the majority of isolates belonged to group A. We also evaluated the frequency of phylogroups in wastewater samples and found a strong positive correlation between the phylogroup distribution in wastewater and human hosts. In order to find out if some factors, such as geographical location, and climate could influence the worldwide phylogroup distribution, we performed a meta-analysis of 39 different studies and 24 countries, including different climates, living areas, and feeding habits. Unexpectedly, our results showed no substructuring patterns of phylogroups; indicating there was no correlation between phylogroup distribution and geographic location, climate, living area, feeding habits, or date of collection.