MIDAS2: Metagenomic Intra-species Diversity Analysis System

Zhao, Chunyu; Dimitrov, Boris; Goldman, Miriam; Nayfach, Stephen; Pollard, Katherine S.

doi:10.1093/bioinformatics/btac713

Cited by 12 publications

(9 citation statements)

References 9 publications

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“…For example, the site‐by‐sample snp_freq table may be used to compute between‐samples distances (e.g., Manhattan distance). Principal coordinates analysis (PCoA) plots based on these pairwise distances can be used to visualize strain‐level diversity (Zhao et al., 2022a). Alternatively, the snp_freq table can be provided as input to strain deconvolution tools, such as StrainFacts (Smith, Li, Shi, Abate, & Pollard, 2022), which enable strain tracking, transmission, and investigations into strain‐level ecological dynamics.…”

Section: Guidelines For Understanding Resultsmentioning

confidence: 99%

“…The subsequent calling of population SNVs across samples is compute intensive. But this step scales linearly with increasing numbers of CPUs (Zhao et al., 2022a) so we recommend using as many CPUs as feasible.…”

Section: Strategic Planningmentioning

confidence: 99%

“…This protocol describes how to use the Metagenomic Intra‐Species Diversity Analysis System 2 (MIDAS2; Zhao, Dimitrov, Goldman, Nayfach, & Pollard, 2022a) to genotype the species present in microbial communities using shotgun metagenomic data, a bioinformatics procedure known as metagenotyping. Most microbial species harbor immense intraspecific genetic variation, in the form of single nucleotide variants (SNVs), gene copy number variants (CNVs), and other structural variants (Garud & Pollard, 2020; Shoemaker, Chen, & Garud, 2022; Van Rossum, Ferretti, Maistrenko, & Bork, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Genotyping Microbial Communities with MIDAS2: From Metagenomic Reads to Allele Tables

et al. 2022

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The Metagenomic Intra-Species Diversity Analysis System 2 (MIDAS2) is a scalable pipeline that identifies single nucleotide variants and gene copy number variants in metagenomes using comprehensive reference databases built from public microbial genome collections (metagenotyping). MIDAS2 is the first metagenotyping tool with functionality to control metagenomic read mapping filters and to customize the reference database to the microbial community, features that improve the precision and recall of detected variants. In this article we present four basic protocols for the most common use cases of MI-DAS2, along with supporting protocols for installation and use. In addition, we provide in-depth guidance on adjusting command line parameters, editing the reference database, optimizing hardware utilization, and understanding the metagenotyping results. All the steps of metagenotyping, from raw sequencing reads to population genetic analysis, are demonstrated with example data in two downloadable sequencing libraries of single-end metagenomic reads representing a mixture of multiple bacterial species. This set of protocols empowers users to accurately genotype hundreds of species in thousands of samples, providing rich genetic data for studying the evolution and strain-level ecology of microbial communities.

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Section: Guidelines For Understanding Resultsmentioning

confidence: 99%

Section: Strategic Planningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Genotyping Microbial Communities with MIDAS2: From Metagenomic Reads to Allele Tables

et al. 2022

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“…Additionally, MIDAS2 offers a step forward in comparison to the MIDAS tool, by enabling the analysis of growingly extensive reference genome databases. It also provides the capability of creating personalized databases and utilizing paired-end reads to enhance the accuracy of single-nucleotide variants (SNV) analysis ( Zhao et al, 2022 ). Also, MetaPhlAn 4, has been released as a new method that allows integrating information from both metagenome assemblies and microbial isolate genomes for improved and more comprehensive metagenomic taxonomic profiling, enabling more profound and more comprehensive microbiome biomarker detection ( Blanco-Miguez et al, 2023 ).…”

Section: Challenges and Future Perspective Of Novel Metagenomics Appr...mentioning

confidence: 99%

Mammals’ sperm microbiome: current knowledge, challenges, and perspectives on metagenomics of seminal samples

et al. 2023

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Bacterial growth is highly detrimental to sperm quality and functionality. However, during the last few years, using sequencing techniques with a metagenomic approach, it has been possible to deepen the study of bacteria-sperm relationships and describe non-culturable species and synergistic and antagonistic relationships between the different species in mammalian animals. We compile the recent metagenomics studies performed on mammalian semen samples and provide updated evidence to understand the importance of the microbial communities in the results of sperm quality and sperm functionality of males, looking for future perspectives on how these technologies can collaborate in the development of andrological knowledge.

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“…To understand how the microbial community composition changed, strain-resolved metagenomics was applied. For the first time, the variant calling incorporated shotgun metagenomic reads to trace strains by identifying distinctive patterns of alleles across SNVs within a species. , Furthermore, the strain deconvolution strategy extracts strain genotypes from shotgun metagenomic data based on allele frequencies. , This combination unveiled fine-scale evolutionary mechanisms, functional dynamics, and metabolic variations that could contribute to the selection of resistant microorganisms.…”

Section: Introductionmentioning

confidence: 99%

Adaptation of Anaerobic Digestion Microbial Communities to High Ammonium Levels: Insights from Strain-Resolved Metagenomics

Bucci,

Ghiotto,

Zampieri

et al. 2023

Environ. Sci. Technol.

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Ammonia release from proteinaceous feedstocks represents the main inhibitor of the anaerobic digestion (AD) process, which can result in a decreased biomethane yield or even complete failure of the process. The present study focused on the adaptation of mesophilic AD communities to a stepwise increase in the concentration of ammonium chloride in synthetic medium with casein used as the carbon source. An adaptation process occurring over more than 20 months allowed batch reactors to reach up to 20 g of NH 4+ N/L without collapsing in acidification nor ceasing methane production. To decipher the microbial dynamics occurring during the adaptation and determine the genes mostly exposed to selective pressure, a combination of biochemical and metagenomics analyses was performed, reconstructing the strains of key species and tracking them over time. Subsequently, the adaptive metabolic mechanisms were delineated by following the single nucleotide variants (SNVs) characterizing the strains and prioritizing the associated genes according to their function. An in-depth exploration of the archaeon Methanoculleus bourgensis vb3066 and the putative syntrophic acetate-oxidizing bacteria Acetomicrobium sp. ma133 identified positively selected SNVs on genes involved in stress adaptation. The intraspecies diversity with multiple coexisting strains in a temporal succession pattern allows us to detect the presence of an additional level of diversity within the microbial community beyond the species level.

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MIDAS2: Metagenomic Intra-species Diversity Analysis System

Cited by 12 publications

References 9 publications

Genotyping Microbial Communities with MIDAS2: From Metagenomic Reads to Allele Tables

Genotyping Microbial Communities with MIDAS2: From Metagenomic Reads to Allele Tables

Mammals’ sperm microbiome: current knowledge, challenges, and perspectives on metagenomics of seminal samples

Adaptation of Anaerobic Digestion Microbial Communities to High Ammonium Levels: Insights from Strain-Resolved Metagenomics

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