Dataset Information

Evaluation of 16S rRNA sequencing and reevaluation of a short biochemical scheme for identification of clinically significant Bacteroides species.

ABSTRACT: Sequence analysis of the 16S rRNA gene represents a highly accurate and versatile method for bacterial classification and identification, even when the species in question is notoriously difficult to identify by phenotypic means. In this study, we evaluated the utility of 16S rRNA gene sequencing as a means of identifying clinically important Bacteroides species. We sequenced 231 clinical isolates that had been identified by a short biochemical scheme. Based on the sequence analysis, 192 clinical isolates were assigned to an established species, with the other 39 clinical strains revealing five unique sequences that may represent five novel species. This is in contrast to identification obtained from a short biochemical scheme, by which only 73.5% (172 of 231) of isolates were correctly identified to species level. Based on the solid identification obtained from 16S rRNA gene sequencing, the short biochemical scheme was modified and improved to provide clinical laboratories with an inexpensive and simple alternative for the identification of isolates of clinically significant Bacteroides species.

SUBMITTER: Song Y

PROVIDER: S-EPMC1081359 | biostudies-literature | 2005 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Evaluation of 16S rRNA sequencing and reevaluation of a short biochemical scheme for identification of clinically significant Bacteroides species.

Song Yuli Y Liu Chengxu C Bolanos Mauricio M Lee Julia J McTeague Maureen M Finegold Sydney M SM

Journal of clinical microbiology 20050401 4

Sequence analysis of the 16S rRNA gene represents a highly accurate and versatile method for bacterial classification and identification, even when the species in question is notoriously difficult to identify by phenotypic means. In this study, we evaluated the utility of 16S rRNA gene sequencing as a means of identifying clinically important Bacteroides species. We sequenced 231 clinical isolates that had been identified by a short biochemical scheme. Based on the sequence analysis, 192 clinica ...[more]

PMID: 15814962

Similar Datasets

Project description:Short-amplicon 16S rRNA gene sequencing is currently the method of choice for studies investigating microbiomes. However, comparative studies on differences in procedures are scarce. We sequenced human stool samples and mock communities with increasing complexity using a variety of commonly used protocols. Short amplicons targeting different variable regions (V-regions) or ranges thereof (V1-V2, V1-V3, V3-V4, V4, V4-V5, V6-V8, and V7-V9) were investigated for differences in the composition outcome due to primer choices. Next, the influence of clustering (operational taxonomic units [OTUs], zero-radius OTUs [zOTUs], and amplicon sequence variants [ASVs]), different databases (GreenGenes, the Ribosomal Database Project, Silva, the genomic-based 16S rRNA Database, and The All-Species Living Tree), and bioinformatic settings on taxonomic assignment were also investigated. We present a systematic comparison across all typically used V-regions using well-established primers. While it is known that the primer choice has a significant influence on the resulting microbial composition, we show that microbial profiles generated using different primer pairs need independent validation of performance. Further, comparing data sets across V-regions using different databases might be misleading due to differences in nomenclature (e.g., Enterorhabdus versus Adlercreutzia) and varying precisions in classification down to genus level. Overall, specific but important taxa are not picked up by certain primer pairs (e.g., Bacteroidetes is missed using primers 515F-944R) or due to the database used (e.g., Acetatifactor in GreenGenes and the genomic-based 16S rRNA Database). We found that appropriate truncation of amplicons is essential and different truncated-length combinations should be tested for each study. Finally, specific mock communities of sufficient and adequate complexity are highly recommended.IMPORTANCE In 16S rRNA gene sequencing, certain bacterial genera were found to be underrepresented or even missing in taxonomic profiles when using unsuitable primer combinations, outdated reference databases, or inadequate pipeline settings. Concerning the last, quality thresholds as well as bioinformatic settings (i.e., clustering approach, analysis pipeline, and specific adjustments such as truncation) are responsible for a number of observed differences between studies. Conclusions drawn by comparing one data set to another (e.g., between publications) appear to be problematic and require independent cross-validation using matching V-regions and uniform data processing. Therefore, we highlight the importance of a thought-out study design including sufficiently complex mock standards and appropriate V-region choice for the sample of interest. The use of processing pipelines and parameters must be tested beforehand.

Dataset Information

Evaluation of 16S rRNA sequencing and reevaluation of a short biochemical scheme for identification of clinically significant Bacteroides species.

Publications

Evaluation of 16S rRNA sequencing and reevaluation of a short biochemical scheme for identification of clinically significant Bacteroides species.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets