Dataset Information

Two-Target Quantitative PCR To Predict Library Composition for Shallow Shotgun Sequencing.

ABSTRACT: When determining human microbiota composition, shotgun sequencing is a powerful tool that can generate high-resolution taxonomic and functional information at once. However, the technique is limited by missing information about host-to-microbe ratios observed in different body compartments. This limitation makes it difficult to plan shotgun sequencing assays, especially in the context of high sample multiplexing and limited sequencing output and is of particular importance for studies employing the recently described shallow shotgun sequencing technique. In this study, we evaluated the use of a quantitative PCR (qPCR)-based assay to predict host-to-microbe ratio prior to sequencing. Combining a two-target assay involving the bacterial 16S rRNA gene and the human beta-actin gene, we derived a model to predict human-to-microbe ratios from two sample types, including stool samples and oropharyngeal swabs. We then validated it on two independently collected sample types, including rectal swabs and vaginal secretion samples. This assay enabled accurate prediction in the validation set in a range of sample compositions between 4% and 98% nonhuman reads and observed proportions varied between -18.8% and +19.2% from the expected values. We hope that this easy-to-use assay will help researchers to plan their shotgun sequencing experiments in a more efficient way. IMPORTANCE When determining human microbiota composition, shotgun sequencing is a powerful tool that can generate large amounts of data. However, in sample compositions with low or variable microbial density, shallowing sequencing can negatively affect microbial community metrics. Here, we show that variable sequencing depth decreases measured alpha diversity at differing rates based on community composition. We then derived a model that can determine sample composition prior to sequencing using quantitative PCR (qPCR) data and validated the model using a separate sample set. We have included a tool that uses this model to be available for researchers to use when gauging shallow sequencing viability of samples.

SUBMITTER: Cho MY

PROVIDER: S-EPMC8409737 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Two-Target Quantitative PCR To Predict Library Composition for Shallow Shotgun Sequencing.

Cho Matthew Y MY Oliva Marc M Spreafico Anna A Chen Bo B Wei Xu X Choi Yoojin Y Kaul Rupert R Siu Lillian L LL Coburn Bryan B Schneeberger Pierre H H PHH

mSystems 20210713 4

When determining human microbiota composition, shotgun sequencing is a powerful tool that can generate high-resolution taxonomic and functional information at once. However, the technique is limited by missing information about host-to-microbe ratios observed in different body compartments. This limitation makes it difficult to plan shotgun sequencing assays, especially in the context of high sample multiplexing and limited sequencing output and is of particular importance for studies employing ...[more]

PMID: 34254823

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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.

Project description:DNA barcoding is critical to conservation and biodiversity research, yet public reference databases are incomplete. Existing barcode databases are biased toward cytochrome oxidase subunit I (COI) and frequently lack associated voucher specimens or geospatial metadata, which can hinder reliable species assignments. The emergence of metabarcoding approaches such as environmental DNA (eDNA) has necessitated multiple marker techniques combined with barcode reference databases backed by voucher specimens. Reference barcodes have traditionally been generated by Sanger sequencing, however sequencing multiple markers is costly for large numbers of specimens, requires multiple separate PCR reactions, and limits resulting sequences to targeted regions. High-throughput sequencing techniques such as genome skimming enable assembly of complete mitogenomes, which contain the most commonly used barcoding loci (e.g., COI, 12S, 16S), as well as nuclear ribosomal repeat regions (e.g., ITS1&2, 18S). We evaluated the feasibility of genome skimming to generate barcode references databases for marine fishes by assembling complete mitogenomes and nuclear ribosomal repeats. We tested genome skimming across a taxonomically diverse selection of 12 marine fish species from the collections of the National Museum of Natural History, Smithsonian Institution. We generated two sequencing libraries per species to test the impact of shearing method (enzymatic or mechanical), extraction method (kit-based or automated), and input DNA concentration. We produced complete mitogenomes for all non-chondrichthyans (11/12 species) and assembled nuclear ribosomal repeats (18S-ITS1-5.8S-ITS2-28S) for all taxa. The quality and completeness of mitogenome assemblies was not impacted by shearing method, extraction method or input DNA concentration. Our results reaffirm that genome skimming is an efficient and (at scale) cost-effective method to generate all mitochondrial and common nuclear DNA barcoding loci for multiple species simultaneously, which has great potential to scale for future projects and facilitate completing barcode reference databases for marine fishes.

Dataset Information

Two-Target Quantitative PCR To Predict Library Composition for Shallow Shotgun Sequencing.

Publications

Two-Target Quantitative PCR To Predict Library Composition for Shallow Shotgun Sequencing.

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