The microbiome has a myriad of important roles in sustaining ecosystem functions and human health. However, achieving mechanistic understanding of any complex microbiome (e.g., the human gut microbiome) is still challenging due to both the extreme cross-species diversity, as a single microbiome harbors thousands of microbial species, and intraspecific diversity, as each species harbors immense genetic variation, including single nucleotide polymorphisms, gene copy number variants, structural variants and mobile genetic elements. Intraspecific diversity can have important functional consequences, such as on pathogenicity and antibiotic resistance, and is useful for investigating the ecological dynamics of microbial species, as well as the evolutionary forces behind them. The ability to quantify microbes broadly and accurately beyond species level, as well as characterize the functional role of individual strains within the complex microbiome, is a prerequisite to the potential application of microbiome genomics in areas such as environmental engineering or the customization of therapeutics with high precision.
Although considerable efforts have been made in the past to culture and sequence microbes, many species have not been grown under laboratory conditions and therefore lack sequenced genomes. Additionally, intraspecific diversity has still been overlooked for the vast majority of microbes. Recent advances in both sequencing technologies and bioinformatics tools have offered a great opportunity to address this challenge. This article collection aims to expand the known strain repertoire of diverse environments through both genomic and metagenomic approaches, making available new genomes, genes and genetic variants of cultured and uncultured microbes. The newly discovered genomic sequences should represent a significant increase over the previously known phylogenetic diversity, generate novel insights into functions, and substantially improve the power of models for predicting microbe-environment associations. Moreover, we aim to enrich the methods or pipelines in order to help overcome the computational barrier for strain-level analysis of microbiomes. The knowledge generated by this collection will be essential for driving future microbiome studies and will open doors to numerous applications in basic research, biotechnology, and medicine.
In this article collection, we welcome a wide variety of genomic and metagenomic studies that examine microbial diversity and functions in microbiomes at subspecies or strain level. We particularly welcome Reviews, Mini Reviews, Original Research, Hypothesis and Theory, and Technology and Code articles on the following (but not limited to) topics:
1) Expanding intraspecific diversity through high-throughput culturomics approaches, or recovery of metagenome-assembled genomes (MAGs) from environmental or host samples.
2) Compiling many genomes, genes or genetic variants from multiple sources to reveal patterns of diversity and functions at a large scale.
3) Filling in missing genetic variation through completing genome assemblies using long-read sequencing or other methods.
4) Investigating the functional consequences of intraspecific diversity, including metabolic activity, pathogenicity, antibiotic resistance, etc.
5) Elucidating the roles of drift, selection, and recombination in driving microbial intraspecific diversity across taxonomic groups and environments.
6) Investigating transmission and dispersal of microbial lineages across space or time by tracking their genetic variants, mobile genetic elements or strains.
7) Identifying potential strain-specific microbial interactions, e.g., phage predation on bacteria.
8) Improving strain-level analysis of microbiome through development of novel statistical methods or bioinformatics tools.
Please note that Systems Microbiology does not consider descriptive studies that are solely based on amplicon (e.g., 16S rRNA) profiles, unless they are accompanied by a clear hypothesis and experimentation, and provide insight into the microbiological system or process being studied.
The microbiome has a myriad of important roles in sustaining ecosystem functions and human health. However, achieving mechanistic understanding of any complex microbiome (e.g., the human gut microbiome) is still challenging due to both the extreme cross-species diversity, as a single microbiome harbors thousands of microbial species, and intraspecific diversity, as each species harbors immense genetic variation, including single nucleotide polymorphisms, gene copy number variants, structural variants and mobile genetic elements. Intraspecific diversity can have important functional consequences, such as on pathogenicity and antibiotic resistance, and is useful for investigating the ecological dynamics of microbial species, as well as the evolutionary forces behind them. The ability to quantify microbes broadly and accurately beyond species level, as well as characterize the functional role of individual strains within the complex microbiome, is a prerequisite to the potential application of microbiome genomics in areas such as environmental engineering or the customization of therapeutics with high precision.
Although considerable efforts have been made in the past to culture and sequence microbes, many species have not been grown under laboratory conditions and therefore lack sequenced genomes. Additionally, intraspecific diversity has still been overlooked for the vast majority of microbes. Recent advances in both sequencing technologies and bioinformatics tools have offered a great opportunity to address this challenge. This article collection aims to expand the known strain repertoire of diverse environments through both genomic and metagenomic approaches, making available new genomes, genes and genetic variants of cultured and uncultured microbes. The newly discovered genomic sequences should represent a significant increase over the previously known phylogenetic diversity, generate novel insights into functions, and substantially improve the power of models for predicting microbe-environment associations. Moreover, we aim to enrich the methods or pipelines in order to help overcome the computational barrier for strain-level analysis of microbiomes. The knowledge generated by this collection will be essential for driving future microbiome studies and will open doors to numerous applications in basic research, biotechnology, and medicine.
In this article collection, we welcome a wide variety of genomic and metagenomic studies that examine microbial diversity and functions in microbiomes at subspecies or strain level. We particularly welcome Reviews, Mini Reviews, Original Research, Hypothesis and Theory, and Technology and Code articles on the following (but not limited to) topics:
1) Expanding intraspecific diversity through high-throughput culturomics approaches, or recovery of metagenome-assembled genomes (MAGs) from environmental or host samples.
2) Compiling many genomes, genes or genetic variants from multiple sources to reveal patterns of diversity and functions at a large scale.
3) Filling in missing genetic variation through completing genome assemblies using long-read sequencing or other methods.
4) Investigating the functional consequences of intraspecific diversity, including metabolic activity, pathogenicity, antibiotic resistance, etc.
5) Elucidating the roles of drift, selection, and recombination in driving microbial intraspecific diversity across taxonomic groups and environments.
6) Investigating transmission and dispersal of microbial lineages across space or time by tracking their genetic variants, mobile genetic elements or strains.
7) Identifying potential strain-specific microbial interactions, e.g., phage predation on bacteria.
8) Improving strain-level analysis of microbiome through development of novel statistical methods or bioinformatics tools.
Please note that Systems Microbiology does not consider descriptive studies that are solely based on amplicon (e.g., 16S rRNA) profiles, unless they are accompanied by a clear hypothesis and experimentation, and provide insight into the microbiological system or process being studied.
