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Sensitivity of shotgun metagenomics to host DNA: abundance estimates depend on bioinformatic tools and contamination is the main issue.

ABSTRACT: A recent study reported that increasing host DNA abundance and reducing read depth impairs the sensitivity of detection of low-abundance micro-organisms by shotgun metagenomics. The authors used DNA from a synthetic bacterial community with abundances varying across several orders of magnitude and added varying proportions of host DNA. However, the use of a marker-gene-based abundance estimation tool (MetaPhlAn2) requires considerable depth to detect marker genes from low-abundance organisms. Here, we reanalyse the deposited data, and place the study in the broader context of low microbial biomass metagenomics. We opted for a fast and sensitive read binning tool (Kraken 2) with abundance estimates from Bracken. With this approach all organisms are detected even when the sample comprises 99?% host DNA and similarly accurate abundance estimates are provided (mean squared error 0.45 vs. 0.3 in the original study). We show that off-target genera, whether contaminants or misidentified reads, come to represent over 10?% of reads when the sample is 99?% host DNA and exceed counts of many target genera. Therefore, we applied Decontam, a contaminant detection tool, which was able to remove 61?% of off-target species and 79?% of off-target reads. We conclude that read binning tools can remain sensitive to low-abundance organisms even with high host DNA content, but even low levels of contamination pose a significant problem due to low microbial biomass. Analytical mitigations are available, such as Decontam, although steps to reduce contamination are critical.

SUBMITTER: McArdle AJ

PROVIDER: S-EPMC7523627 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Sensitivity of shotgun metagenomics to host DNA: abundance estimates depend on bioinformatic tools and contamination is the main issue.

McArdle Andrew J AJ Kaforou Myrsini M

Access microbiology 20200217 4

A recent study reported that increasing host DNA abundance and reducing read depth impairs the sensitivity of detection of low-abundance micro-organisms by shotgun metagenomics. The authors used DNA from a synthetic bacterial community with abundances varying across several orders of magnitude and added varying proportions of host DNA. However, the use of a marker-gene-based abundance estimation tool (MetaPhlAn2) requires considerable depth to detect marker genes from low-abundance organisms. He ...[more]

PMID: 33005868

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Project description:Although microbial communities are associated with human, environmental, plant, and animal health, there exists no cost-effective method for precisely characterizing species and genes in such communities. While deep whole-metagenome shotgun (WMS) sequencing provides high taxonomic and functional resolution, it is often prohibitively expensive for large-scale studies. The prevailing alternative, 16S rRNA gene amplicon (16S) sequencing, often does not resolve taxonomy past the genus level and provides only moderately accurate predictions of the functional profile; thus, there is currently no widely accepted approach to affordable, high-resolution, taxonomic, and functional microbiome analysis. To address this technology gap, we evaluated the information content of shallow shotgun sequencing with as low as 0.5 million sequences per sample as an alternative to 16S sequencing for large human microbiome studies. We describe a library preparation protocol enabling shallow shotgun sequencing at approximately the same per-sample cost as 16S sequencing. We analyzed multiple real and simulated biological data sets, including two novel human stool samples with ultradeep sequencing of 2.5 billion sequences per sample, and found that shallow shotgun sequencing recovers more-accurate species-level taxonomic and functional profiles of the human microbiome than 16S sequencing. We discuss the inherent limitations of shallow shotgun sequencing and note that 16S sequencing remains a valuable and important method for taxonomic profiling of novel environments. Although deep WMS sequencing remains the gold standard for high-resolution microbiome analysis, we recommend that researchers consider shallow shotgun sequencing as a useful alternative to 16S sequencing for large-scale human microbiome research studies where WMS sequencing may be cost-prohibitive. IMPORTANCE A common refrain in recent microbiome-related academic meetings is that the field needs to move away from broad taxonomic surveys using 16S sequencing and toward more powerful longitudinal studies using shotgun sequencing. However, performing deep shotgun sequencing in large longitudinal studies remains prohibitively expensive for all but the most well-funded research labs and consortia, which leads many researchers to choose 16S sequencing for large studies, followed by deep shotgun sequencing on a subset of targeted samples. Here, we show that shallow- or moderate-depth shotgun sequencing may be used by researchers to obtain species-level taxonomic and functional data at approximately the same cost as amplicon sequencing. While shallow shotgun sequencing is not intended to replace deep shotgun sequencing for strain-level characterization, we recommend that microbiome scientists consider using shallow shotgun sequencing instead of 16S sequencing for large-scale human microbiome studies.

Dataset Information

Sensitivity of shotgun metagenomics to host DNA: abundance estimates depend on bioinformatic tools and contamination is the main issue.

Publications

Sensitivity of shotgun metagenomics to host DNA: abundance estimates depend on bioinformatic tools and contamination is the main issue.

Similar Datasets

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