Dataset Information

Host distributions of uncultivated fecal Bacteroidales bacteria reveal genetic markers for fecal source identification.

ABSTRACT: The purpose of this study was to examine host distribution patterns among fecal bacteria in the order Bacteroidales, with the goal of using endemic sequences as markers for fecal source identification in aquatic environments. We analyzed Bacteroidales 16S rRNA gene sequences from the feces of eight hosts: human, bovine, pig, horse, dog, cat, gull, and elk. Recovered sequences did not match database sequences, indicating high levels of uncultivated diversity. The analysis revealed both endemic and cosmopolitan distributions among the eight hosts. Ruminant, pig, and horse sequences tended to form host- or host group-specific clusters in a phylogenetic tree, while human, dog, cat, and gull sequences clustered together almost exclusively. Many of the human, dog, cat, and gull sequences fell within a large branch containing cultivated species from the genus Bacteroides. Most of the cultivated Bacteroides species had very close matches with multiple hosts and thus may not be useful targets for fecal source identification. A large branch containing cultivated members of the genus Prevotella included cloned sequences that were not closely related to cultivated Prevotella species. Most ruminant sequences formed clusters separate from the branches containing Bacteroides and Prevotella species. Host-specific sequences were identified for pigs and horses and were used to design PCR primers to identify pig and horse sources of fecal pollution in water. The primers successfully amplified fecal DNAs from their target hosts and did not amplify fecal DNAs from other species. Fecal bacteria endemic to the host species may result from evolution in different types of digestive systems.

SUBMITTER: Dick LK

PROVIDER: S-EPMC1151806 | biostudies-literature | 2005 Jun

REPOSITORIES: biostudies-literature

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Host distributions of uncultivated fecal Bacteroidales bacteria reveal genetic markers for fecal source identification.

Dick Linda K LK Bernhard Anne E AE Brodeur Timothy J TJ Santo Domingo Jorge W JW Simpson Joyce M JM Walters Sarah P SP Field Katharine G KG

Applied and environmental microbiology 20050601 6

The purpose of this study was to examine host distribution patterns among fecal bacteria in the order Bacteroidales, with the goal of using endemic sequences as markers for fecal source identification in aquatic environments. We analyzed Bacteroidales 16S rRNA gene sequences from the feces of eight hosts: human, bovine, pig, horse, dog, cat, gull, and elk. Recovered sequences did not match database sequences, indicating high levels of uncultivated diversity. The analysis revealed both endemic an ...[more]

PMID: 15933020

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Project description:BackgroundClostridiales and Bacteroidales are uniquely adapted to the gut environment and have co-evolved with their hosts resulting in convergent microbiome patterns within mammalian species. As a result, members of Clostridiales and Bacteroidales are particularly suitable for identifying sources of fecal contamination in environmental samples. However, a comprehensive evaluation of their predictive power and development of computational approaches is lacking. Given the global public health concern for waterborne disease, accurate identification of fecal pollution sources is essential for effective risk assessment and management. Here, we use random forest algorithm and 16S rRNA gene amplicon sequences assigned to Clostridiales and Bacteroidales to identify common fecal pollution sources. We benchmarked the accuracy, consistency, and sensitivity of our classification approach using fecal, environmental, and artificial in silico generated samples.ResultsClostridiales and Bacteroidales classifiers were composed mainly of sequences that displayed differential distributions (host-preferred) among sewage, cow, deer, pig, cat, and dog sources. Each classifier correctly identified human and individual animal sources in approximately 90% of the fecal and environmental samples tested. Misclassifications resulted mostly from false-positive identification of cat and dog fecal signatures in host animals not used to build the classifiers, suggesting characterization of additional animals would improve accuracy. Random forest predictions were highly reproducible, reflecting the consistency of the bacterial signatures within each of the animal and sewage sources. Using in silico generated samples, we could detect fecal bacterial signatures when the source dataset accounted for as little as ~ 0.5% of the assemblage, with ~ 0.04% of the sequences matching the classifiers. Finally, we developed a proxy to estimate proportions among sources, which allowed us to determine which sources contribute the most to observed fecal pollution.ConclusionRandom forest classification with 16S rRNA gene amplicons offers a rapid, sensitive, and accurate solution for identifying host microbial signatures to detect human and animal fecal contamination in environmental samples.

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Dataset Information

Host distributions of uncultivated fecal Bacteroidales bacteria reveal genetic markers for fecal source identification.

Publications

Host distributions of uncultivated fecal Bacteroidales bacteria reveal genetic markers for fecal source identification.

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