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. 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.
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http://dx.doi.org/10.1128/mSystems.00069-18 | DOI Listing |
Commun Med (Lond)
January 2025
Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Canada.
Background: Understanding factors associated with antimicrobial resistance (AMR) distribution across populations is a necessary step in planning mitigation measures. While associations between AMR and socioeconomic-status (SES), including employment and education have been increasingly recognized in low- and middle-income settings, connections are less clear in high-income countries where SES remains an important influence on other health outcomes.
Methods: We explored the relationship between SES and AMR in Calgary, Canada using spatially-resolved wastewater-based surveillance of resistomes detected by metagenomics across eight socio-economically diverse urban neighborhoods.
PLoS One
January 2025
Department of Epidemiology and Biostatistics, University of Western Ontario, London, Ontario, Canada.
The microbiome is increasingly regarded as a key component of human health, and analysis of microbiome data can aid in the development of precision medicine. Due to the high cost of shotgun metagenomic sequencing (SM-seq), microbiome analyses can be done cost-effectively in two phases: Phase 1-sequencing of 16S ribosomal RNA, and Phase 2-SM-seq of an informative subsample. Existing research suggests strategies to select the subsample based on biological diversity and dissimilarity metrics calculated using operational taxonomic units (OTUs).
View Article and Find Full Text PDFSci Adv
January 2025
UCL Genetics Institute, Research Department of Genetics, Evolution and Environment, University College London, London WC1E 6BT, UK.
The North Pontic region, which encompasses present-day Ukraine, was a crossroads of migration, connecting the vast Eurasian Steppe with Central Europe. We generated shotgun-sequenced genomic data for 91 individuals dating from around 7000 BCE to 1800 CE to study migration and mobility history in the region, with a particular focus on historically attested migrating groups during the Iron Age and the medieval period. We infer a high degree of temporal heterogeneity in ancestry, with fluctuating genetic affinities to different present-day Eurasian groups.
View Article and Find Full Text PDFJ Agric Food Chem
January 2025
Department of Food Science and Technology, College of Agriculture and Life Sciences, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, South Korea.
Antimicrobial resistance (AMR) poses a critical global public health challenge. This study investigates the microbiome of var. (kale) to evaluate the role of food production systems, particularly plant-derived foods, in AMR dissemination.
View Article and Find Full Text PDFMicroorganisms
December 2024
Traditional Food Research Group, Korea Food Research Institute, Iseo-myeon, Wanju-gun 55365, Jeollabuk-do, Republic of Korea.
The microbial community of a soy sauce is one of the most important factors in determining the sensory characteristics of that soy sauce. In this study, the microbial communities and sensory characteristics of twenty samples of Korean soy sauce () were investigated using shotgun metagenome sequencing and descriptive sensory analysis, and their correlations were explored by partial least square (PLS) regression analysis. The metagenome analysis identified 1332 species of bacteria, yeasts, molds, and viruses across 278 genera, of which , , and accounted for more than 80% of the total community.
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