Dataset Information

Catheter-related Microbacterium bacteremia identified by 16S rRNA gene sequencing.

ABSTRACT: We describe the application of 16S rRNA gene sequencing in defining two cases of catheter-related Microbacterium bacteremia. In the first case, a gram-positive bacillus was isolated from both the blood culture and central catheter tip of a 39-year-old woman with chronic myeloid leukemia. The API Coryne system identified the isolate as 98.9% Aureobacterium or Corynebacterium aquaticum. In the second case, a gram-positive bacillus was recovered from five sets of blood cultures from both central catheter and percutaneous venipuncture of a 5-year-old girl with acute myeloid leukemia. The isolate was identified by the API Coryne system as 99.7% Cellulomonas or Microbacterium species. Further phenotypic tests failed to identify the two isolates. 16S rRNA gene sequencing showed 99.4% similarity between the first isolate and Microbacterium oxydans and 98.7% similarity between the second isolate and Microbacterium trichotecenolyticum, indicating that both isolates were Microbacterium species. Microbacterium infections are rarely reported in the literature. Although the central venous catheter was previously proposed to be a source of bacteremia, the first case in this report represents the first culture-documented case of catheter-related Microbacterium bacteremia.

SUBMITTER: Lau SK

PROVIDER: S-EPMC120609 | biostudies-literature | 2002 Jul

REPOSITORIES: biostudies-literature

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Catheter-related Microbacterium bacteremia identified by 16S rRNA gene sequencing.

Lau Susanna K P SK Woo Patrick C Y PC Woo Gibson K S GK Yuen Kwok-Yung KY

Journal of clinical microbiology 20020701 7

We describe the application of 16S rRNA gene sequencing in defining two cases of catheter-related Microbacterium bacteremia. In the first case, a gram-positive bacillus was isolated from both the blood culture and central catheter tip of a 39-year-old woman with chronic myeloid leukemia. The API Coryne system identified the isolate as 98.9% Aureobacterium or Corynebacterium aquaticum. In the second case, a gram-positive bacillus was recovered from five sets of blood cultures from both central ca ...[more]

PMID: 12089308

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Project description:BackgroundIn the last few years, 16S rRNA gene sequencing (16S rDNA-seq) has seen a surprisingly rapid increase in election rate as a methodology to perform microbial community studies. Despite the considerable popularity of this technique, an exiguous number of specific tools are currently available for proper 16S rDNA-seq count data preprocessing and simulation. Indeed, the great majority of tools have been developed adapting methodologies previously used for bulk RNA-seq data, with poor assessment of their applicability in the metagenomics field. For such tools and the few ones specifically developed for 16S rDNA-seq data, performance assessment is challenging, mainly due to the complex nature of the data and the lack of realistic simulation models. In fact, to the best of our knowledge, no software thought for data simulation are available to directly obtain synthetic 16S rDNA-seq count tables that properly model heavy sparsity and compositionality typical of these data.ResultsIn this paper we present metaSPARSim, a sparse count matrix simulator intended for usage in development of 16S rDNA-seq metagenomic data processing pipelines. metaSPARSim implements a new generative process that models the sequencing process with a Multivariate Hypergeometric distribution in order to realistically simulate 16S rDNA-seq count table, resembling real experimental data compositionality and sparsity. It provides ready-to-use count matrices and comes with the possibility to reproduce different pre-coded scenarios and to estimate simulation parameters from real experimental data. The tool is made available at http://sysbiobig.dei.unipd.it/?q=Software#metaSPARSimand https://gitlab.com/sysbiobig/metasparsim.ConclusionmetaSPARSim is able to generate count matrices resembling real 16S rDNA-seq data. The availability of count data simulators is extremely valuable both for methods developers, for which a ground truth for tools validation is needed, and for users who want to assess state of the art analysis tools for choosing the most accurate one. Thus, we believe that metaSPARSim is a valuable tool for researchers involved in developing, testing and using robust and reliable data analysis methods in the context of 16S rRNA gene sequencing.

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

Catheter-related Microbacterium bacteremia identified by 16S rRNA gene sequencing.

Publications

Catheter-related Microbacterium bacteremia identified by 16S rRNA gene sequencing.

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