Dataset Information

Microbiological and 16S rRNA analysis of sulphite-reducing clostridia from river sediments in central Italy.

ABSTRACT: BACKGROUND: Microbiological indicators are commonly used in the assessment of public health risks associated with fecal contamination of freshwater ecosystems. Sediments are a reservoir of microorganisms, and can thus provide information on past pollution events, not obtainable through the testing of surface water. Moreover, pathogens present in sediment may represent future threats to human health. Clostridium perfringens, a typical colonizer of sediments, has been suggested as an alternative indicator of fecal pollution. In order to be suitable for such purpose, the microorganism should be widely distributed in contaminated environments. The objective of this study was thus to determine the composition of the anaerobic community in sediment samples of the lower Tiber basin, in central Italy, through a combined approach involving granulometric analysis of sediment samples, as well as a microbiological and molecular (16S rRNA) analysis of strains. RESULTS: Granulometry showed a similar, clayey sediment composition, in most sampling sites. The microbiological method, employing, an adaptation of the standard method, proved to be effective in isolating anaerobic bacteria from the environmental matrix for the purpose of genetic analysis. Eighty-three strains of bacteria were isolated and the partial 16S rRNA gene sequenced. While biochemical analysis detected only C. perfringens strains, phylogenetic analysis indicated the presence of three clusters: C. perfringens, C. bifermentans and B. cereus, comprising eight taxa. C. perfringens, the commonest in almost all sediment sampling sites, was present in all sites, and in both seasons (seasonal sampling was carried out only along the Tiber and Aniene rivers). None of the described genetic profiles showed complete similarity with GenBank sequences. CONCLUSION: The study underlines the value of C. perfringens as an alternative microbial indicator of fecal contamination in river sediments. This is supported by the bacterium's presence in all sampling sites, and in both seasons, coupled with its detectability using commercial diagnostic kits. The study also illustrates the presence of an anaerobic community of considerable biodiversity in the lower Tiber basin, with C. perfringens as its main component. The 16S rRNA analysis, while confirming the phylogenetic relationships among isolated species, also showed haplotype patterns different from those present in the NCBI database.

SUBMITTER: Marcheggiani S

PROVIDER: S-EPMC2569943 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

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Microbiological and 16S rRNA analysis of sulphite-reducing clostridia from river sediments in central Italy.

Marcheggiani Stefania S Iaconelli Marcello M D'angelo Annamaria A Pierdominici Elio E La Rosa Giuseppina G Muscillo Michele M Equestre Michele M Mancini Laura L

BMC microbiology 20081008

<h4>Background</h4>Microbiological indicators are commonly used in the assessment of public health risks associated with fecal contamination of freshwater ecosystems. Sediments are a reservoir of microorganisms, and can thus provide information on past pollution events, not obtainable through the testing of surface water. Moreover, pathogens present in sediment may represent future threats to human health. Clostridium perfringens, a typical colonizer of sediments, has been suggested as an altern ...[more]

PMID: 18842132

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Project description:Rivers are often challenged by fecal contaminations. The barrier effect of sediments against fecal bacteria was investigated through the use of a microbial source tracking (MST) toolbox, and by Next Generation Sequencing (NGS) of V5-V6 16S rRNA gene (rrs) sequences. Non-metric multi-dimensional scaling analysis of V5-V6 16S rRNA gene sequences differentiated bacteriomes according to their compartment of origin i.e., surface water against benthic and hyporheic sediments. Classification of these reads showed the most prevalent operating taxonomic units (OTU) to be allocated to Flavobacterium and Aquabacterium. Relative numbers of Gaiella, Haliangium, and Thermoleophilum OTU matched the observed differentiation of bacteriomes according to river compartments. OTU patterns were found impacted by combined sewer overflows (CSO) through an observed increase in diversity from the sewer to the hyporheic sediments. These changes appeared driven by direct transfers of bacterial contaminants from wastewaters but also by organic inputs favoring previously undetectable bacterial groups among sediments. These NGS datasets appeared more sensitive at tracking community changes than MST markers. The human-specific MST marker HF183 was strictly detected among CSO-impacted surface waters and not river bed sediments. The ruminant-specific DNA marker was more broadly distributed but intense bovine pollution was required to detect transfers from surface water to benthic and hyporheic sediments. Some OTU showed distribution patterns in line with these MST datasets such as those allocated to the Aeromonas, Acinetobacter, and Pseudomonas. Fecal indicators (Escherichia coli and total thermotolerant coliforms) were detected all over the river course but their concentrations were not correlated with MST ones. Overall, MST and NGS datasets suggested a poor colonization of river sediments by bovine and sewer bacterial contaminants. No environmental outbreak of these bacterial contaminants was detected.

Project description:The advent of next generation sequencing has coincided with a growth in interest in using these approaches to better understand the role of the structure and function of the microbial communities in human, animal, and environmental health. Yet, use of next generation sequencing to perform 16S rRNA gene sequence surveys has resulted in considerable controversy surrounding the effects of sequencing errors on downstream analyses. We analyzed 2.7×10(6) reads distributed among 90 identical mock community samples, which were collections of genomic DNA from 21 different species with known 16S rRNA gene sequences; we observed an average error rate of 0.0060. To improve this error rate, we evaluated numerous methods of identifying bad sequence reads, identifying regions within reads of poor quality, and correcting base calls and were able to reduce the overall error rate to 0.0002. Implementation of the PyroNoise algorithm provided the best combination of error rate, sequence length, and number of sequences. Perhaps more problematic than sequencing errors was the presence of chimeras generated during PCR. Because we knew the true sequences within the mock community and the chimeras they could form, we identified 8% of the raw sequence reads as chimeric. After quality filtering the raw sequences and using the Uchime chimera detection program, the overall chimera rate decreased to 1%. The chimeras that could not be detected were largely responsible for the identification of spurious operational taxonomic units (OTUs) and genus-level phylotypes. The number of spurious OTUs and phylotypes increased with sequencing effort indicating that comparison of communities should be made using an equal number of sequences. Finally, we applied our improved quality-filtering pipeline to several benchmarking studies and observed that even with our stringent data curation pipeline, biases in the data generation pipeline and batch effects were observed that could potentially confound the interpretation of microbial community data.

Dataset Information

Microbiological and 16S rRNA analysis of sulphite-reducing clostridia from river sediments in central Italy.

Publications

Microbiological and 16S rRNA analysis of sulphite-reducing clostridia from river sediments in central Italy.

Similar Datasets

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