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Assessment of metagenomic assembly using simulated next generation sequencing data.

ABSTRACT: Due to the complexity of the protocols and a limited knowledge of the nature of microbial communities, simulating metagenomic sequences plays an important role in testing the performance of existing tools and data analysis methods with metagenomic data. We developed metagenomic read simulators with platform-specific (Sanger, pyrosequencing, Illumina) base-error models, and simulated metagenomes of differing community complexities. We first evaluated the effect of rigorous quality control on Illumina data. Although quality filtering removed a large proportion of the data, it greatly improved the accuracy and contig lengths of resulting assemblies. We then compared the quality-trimmed Illumina assemblies to those from Sanger and pyrosequencing. For the simple community (10 genomes) all sequencing technologies assembled a similar amount and accurately represented the expected functional composition. For the more complex community (100 genomes) Illumina produced the best assemblies and more correctly resembled the expected functional composition. For the most complex community (400 genomes) there was very little assembly of reads from any sequencing technology. However, due to the longer read length the Sanger reads still represented the overall functional composition reasonably well. We further examined the effect of scaffolding of contigs using paired-end Illumina reads. It dramatically increased contig lengths of the simple community and yielded minor improvements to the more complex communities. Although the increase in contig length was accompanied by increased chimericity, it resulted in more complete genes and a better characterization of the functional repertoire. The metagenomic simulators developed for this research are freely available.

SUBMITTER: Mende DR

PROVIDER: S-EPMC3285633 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Assessment of metagenomic assembly using simulated next generation sequencing data.

Mende Daniel R DR Waller Alison S AS Sunagawa Shinichi S Järvelin Aino I AI Chan Michelle M MM Arumugam Manimozhiyan M Raes Jeroen J Bork Peer P

PloS one 20120223 2

Due to the complexity of the protocols and a limited knowledge of the nature of microbial communities, simulating metagenomic sequences plays an important role in testing the performance of existing tools and data analysis methods with metagenomic data. We developed metagenomic read simulators with platform-specific (Sanger, pyrosequencing, Illumina) base-error models, and simulated metagenomes of differing community complexities. We first evaluated the effect of rigorous quality control on Illu ...[more]

PMID: 22384016

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Project description:IntroductionMetagenomic next-generation sequencing (mNGS) assay for detecting infectious agents is now in the stage of being translated into clinical practice. With no approved approaches or guidelines available, laboratories adopt customized mNGS assays to detect clinical samples. However, the accuracy, reliability, and problems of these routinely implemented assays are not clear.ObjectivesTo evaluate the performance of 90 mNGS laboratories under routine testing conditions through analyzing identical samples.MethodsEleven microbial communities were generated using 15 quantitative microbial suspensions. They were used as reference materials to evaluate the false negatives and false positives of participating mNGS protocols, as well as the ability to distinguish genetically similar organisms and to identify true pathogens from other microbes based on fictitious case reports.ResultsHigh interlaboratory variability was found in the identification and the quantitative reads per million reads (RPM) values of each microbe in the samples, especially when testing microbes present at low concentrations (1 × 103 cell/ml or less). 42.2% (38/90) of the laboratories reported unexpected microbes (i.e. false positive problem). Only 56.7% (51/90) to 83.3% (75/90) of the laboratories showed a sufficient ability to obtain clear etiological diagnoses for three simulated cases combined with patient information. The analysis of the performance of mNGS in distinguishing genetically similar organisms in three samples revealed that only 56.6% to 63.0% of the laboratories recovered RPM ratios (RPM S. aureus /RPM S. epidermidis ) within the range of a 2-fold change of the initial input ratios (indicating a relatively low level of bias).ConclusionThe high interlaboratory variability found in both identifying microbes and distinguishing true pathogens emphasizes the urgent need for improving the accuracy and comparability of the results generated across different mNGS laboratories, especially in the detection of low-microbial-biomass samples.

Project description:BackgroundMetagenomic next-generation sequencing (mNGS) technology has been widely used to diagnose various infections. Based on the most common pathogen profiles, targeted mNGS (tNGS) using multiplex PCR has been developed to detect pathogens with predesigned primers in the panel, significantly improving sensitivity and reducing economic burden on patients. However, there are few studies on summarizing pathogen profiles of pulmonary infections in immunocompetent and immunocompromised patients in Jilin Province of China on large scale.MethodsFrom January 2021 to December 2023, bronchoalveolar lavage fluid (BALF) or sputum samples from 546 immunocompetent and immunocompromised patients with suspected community-acquired pneumonia were collected. Pathogen profiles in those patients on whom mNGS was performed were summarized. Additionally, we also evaluated the performance of tNGS in diagnosing pulmonary infections.ResultsCombined with results of mNGS and culture, we found that the most common bacterial pathogens were Pseudomonas aeruginosa, Klebsiella pneumoniae, and Acinetobacter baumannii in both immunocompromised and immunocompetent patients with high detection rates of Staphylococcus aureus and Enterococcus faecium, respectively. For fungal pathogens, Pneumocystis jirovecii was commonly detected in patients, while fungal infections in immunocompetent patients were mainly caused by Candida albicans. Most of viral infections in patients were caused by Human betaherpesvirus 5 and Human gammaherpesvirus 4. It is worth noting that, compared with immunocompetent patients (34.9%, 76/218), more mixed infections were found in immunocompromised patients (37.8%, 14/37). Additionally, taking final comprehensive clinical diagnoses as reference standard, total coincidence rate of BALF tNGS (81.4%, 48/59) was much higher than that of BALF mNGS (40.0%, 112/280).ConclusionsOur findings supplemented and classified the pathogen profiles of pulmonary infections in immunocompetent and immunocompromised patients in Jilin Province of China. Most importantly, our findings can accelerate the development and design of tNGS specifically used for regional pulmonary infections.

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Assessment of metagenomic assembly using simulated next generation sequencing data.

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Assessment of metagenomic assembly using simulated next generation sequencing data.

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