Dataset Information

Assessment of urban microbiome assemblies with the help of targeted in silico gold standards.

ABSTRACT: BACKGROUND:Microbial communities play a crucial role in our environment and may influence human health tremendously. Despite being the place where human interaction is most abundant we still know little about the urban microbiome. This is highlighted by the large amount of unclassified DNA reads found in urban metagenome samples. The only in silico approach that allows us to find unknown species, is the assembly and classification of draft genomes from a metagenomic dataset. In this study we (1) investigate the applicability of an assembly and binning approach for urban metagenome datasets, and (2) develop a new method for the generation of in silico gold standards to better understand the specific challenges of such datasets and provide a guide in the selection of available software. RESULTS:We applied combinations of three assembly (Megahit, SPAdes and MetaSPAdes) and three binning tools (MaxBin, MetaBAT and CONCOCT) to whole genome shotgun datasets from the CAMDA 2017 Challenge. Complex in silico gold standards with a simulated bacterial fraction were generated for representative samples of each surface type and city. Using these gold standards, we found the combination of SPAdes and MetaBAT to be optimal for urban metagenome datasets by providing the best trade-off between the number of high-quality genome draft bins (MIMAG standards) retrieved, the least amount of misassemblies and contamination. The assembled draft genomes included known species like Propionibacterium acnes but also novel species according to respective ANI values. CONCLUSIONS:In our work, we showed that, even for datasets with high diversity and low sequencing depth from urban environments, assembly and binning-based methods can provide high-quality genome drafts. Of vital importance to retrieve high-quality genome drafts is sequence depth but even more so a high proportion of the bacterial sequence fraction too achieve high coverage for bacterial genomes. In contrast to read-based methods relying on database knowledge, genome-centric methods as applied in this study can provide valuable information about unknown species and strains as well as functional contributions of single community members within a sample. Furthermore, we present a method for the generation of sample-specific highly complex in silico gold standards. REVIEWERS:This article was reviewed by Craig Herbold, Serghei Mangul and Yana Bromberg.

SUBMITTER: Gerner SM

PROVIDER: S-EPMC6889603 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Assessment of urban microbiome assemblies with the help of targeted in silico gold standards.

Gerner Samuel M SM Rattei Thomas T Graf Alexandra B AB

Biology direct 20181012 1

<h4>Background</h4>Microbial communities play a crucial role in our environment and may influence human health tremendously. Despite being the place where human interaction is most abundant we still know little about the urban microbiome. This is highlighted by the large amount of unclassified DNA reads found in urban metagenome samples. The only in silico approach that allows us to find unknown species, is the assembly and classification of draft genomes from a metagenomic dataset. In this stud ...[more]

PMID: 30621760

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Project description:BackgroundEffective standardisation of methodologies to analyse the microbiome is essential to the entire microbiome community. Despite the microbiome field being established for over a decade, there are no accredited or certified reference materials available to the wider community. In this study, we describe the development of the first reference reagents produced by the National Institute for Biological Standards and Control (NIBSC) for microbiome analysis by next-generation sequencing. These can act as global working standards and will be evaluated as candidate World Health Organization International Reference Reagents.ResultsWe developed the NIBSC DNA reference reagents Gut-Mix-RR and Gut-HiLo-RR and a four-measure framework for evaluation of bioinformatics tool and pipeline bias. Using these reagents and reporting system, we performed an independent evaluation of a variety of bioinformatics tools by analysing shotgun sequencing and 16S rRNA sequencing data generated from the Gut-Mix-RR and Gut-HiLo-RR. We demonstrate that key measures of microbiome health, such as diversity estimates, are largely inflated by the majority of bioinformatics tools. Across all tested tools, biases were present, with a clear trade-off occurring between sensitivity and the relative abundance of false positives in the final dataset. Using commercially available mock communities, we investigated how the composition of reference reagents may impact benchmarking studies. Reporting measures consistently changed when the same bioinformatics tools were used on different community compositions. This was influenced by both community complexity and taxonomy of species present. Both NIBSC reference reagents, which consisted of gut commensal species, proved to be the most challenging for the majority of bioinformatics tools tested. Going forward, we recommend the field uses site-specific reagents of a high complexity to ensure pipeline benchmarking is fit for purpose.ConclusionsIf a consensus of acceptable levels of error can be agreed on, widespread adoption of these reference reagents will standardise downstream gut microbiome analyses. We propose to do this through a large open-invite collaborative study for multiple laboratories in 2020. Video Abstract.

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Assessment of urban microbiome assemblies with the help of targeted in silico gold standards.

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Assessment of urban microbiome assemblies with the help of targeted in silico gold standards.

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