Best Practices in Microbiology

This Consensus Statement presents the standards for technical reporting in environmental and host-associated microbiome studies (STREAMS) guidelines.

We provide guidance on the planning, execution and description of statistical analyses in microbiome studies.

Here the authors outline best practices for the development, implementation and evaluation of synthetic microbial communities (or SynComs) across different systems.

Here the authors discuss the use of synthetic communities, or SynComs, in plant–microbiome research and propose steps to develop community standards that will support future research.

Here the authors make recommendations for the design of clinical trials for prebiotics and probiotics that includes consideration of diet and the gut microbiome.

This Review discusses how organ-on-chip models can applied for infectious disease research.

The extent and diversity of exposures to microbial stimuli have a crucial role in regulating the capacity of a host to mount an immune response to a challenge, such as vaccination, making exposure history an important factor to optimize in rodent models.

A noticeable part of the microbiome literature, especially that working with low-biomass samples, is plagued by reagent contamination. Here we describe visual, statistical, methodical and ecological techniques to facilitate recognition of signals that represent contamination.

In this Consensus Statement, a consortium of microbiome scientists discuss current sequencing data sharing policies and propose the use of a Data Reuse Information (DRI) tag to promote equitable and collaborative data sharing.

As the saying goes, sharing is caring — but when it comes to the data underlying primary research papers published at Nature Microbiology, sharing is also mandatory.

Researchers can be expected to employ a vast range of experimental techniques in pursuit of a scientific question. Making efforts to seek expert advice and develop the competency to generate, store and analyse high-quality data when first using an approach will save time in the long run.

Increasing research on microbial communities has resulted in massive amounts of data being generated and shared, yet data accessibility, accuracy and thoroughness remain problematic and can be a substantial obstacle for scientists looking to explore existing datasets.

An outline of best practices, resources and suggested improvements to ensure that the complexities inherent to microbial big data do not hamper accessibility.

Big data abound in microbiology, but the workflows designed to enable researchers to interpret data can constrain the biological questions that can be asked. Five years after anvi’o was first published, this community-led multi-omics platform is maturing into an open software ecosystem that reduces constraints in ‘omics data analyses.

microbeMASST is a tool to associate known and unknown metabolites to microbial producers leveraging untargeted metabolomics data.

The Nagoya Protocol was drafted to ensure the fair and equitable sharing of benefits arising from the international use of genetic resources, but the lack of unified procedures and unclear definitions relating to microorganisms present considerable hurdles to microbiology research.

A framework centred on relationality among Indigenous peoples, researchers and microorganisms is presented, to guide ethical microbiome research.

This Perspective argues that microbiome ownership needs to be considered in microbiome research involving Indigenous peoples.

Specific actions to develop equitable partnerships in microbiome research are proposed.

Despite evidence of sex-specific pathogenesis, few studies of infectious diseases report or analyse sex or gender, unless it is the primary focus. Using HIV as an example, it is argued here that this leaves potentially informative data unexplored and that integrating sex and gender in analyses may accelerate research in microbial pathogenesis.

In this Consensus Statement, the authors outline strategies for processing, analysing and interpreting low-biomass microbiome samples, and provide recommendations to minimize contaminants.

SeqCode is the result of a community effort to unify nomenclature for uncultured and cultured prokaryotes using genome sequences.

Resolving widespread incomplete and uneven archaeal classifications is achieved by a rank-normalized genome-based taxonomy.

The present outbreak of a coronavirus-associated acute respiratory disease called coronavirus disease 19 (COVID-19) is the third documented spillover of an animal coronavirus to humans in only two decades that has resulted in a major epidemic. The Coronaviridae Study Group (CSG) of the International Committee on Taxonomy of Viruses, which is responsible for developing the classification of viruses and taxon nomenclature of the family Coronaviridae, has assessed the placement of the human pathogen, tentatively named 2019-nCoV, within the Coronaviridae. Based on phylogeny, taxonomy and established practice, the CSG recognizes this virus as forming a sister clade to the prototype human and bat severe acute respiratory syndrome coronaviruses (SARS-CoVs) of the species Severe acute respiratory syndrome-related coronavirus, and designates it as SARS-CoV-2. In order to facilitate communication, the CSG proposes to use the following naming convention for individual isolates: SARS-CoV-2/host/location/isolate/date. While the full spectrum of clinical manifestations associated with SARS-CoV-2 infections in humans remains to be determined, the independent zoonotic transmission of SARS-CoV and SARS-CoV-2 highlights the need for studying viruses at the species level to complement research focused on individual pathogenic viruses of immediate significance. This will improve our understanding of virus–host interactions in an ever-changing environment and enhance our preparedness for future outbreaks.

The authors propose a nomenclature of SARS-CoV-2 lineages to assist research on epidemiology and decision-making during the COVID-19 pandemic. This nomenclature is based on the SARS-CoV-2 phylogeny and designed to provide a real-time bird’s-eye view of the diversity of the hundreds of thousands of genome sequences collected worldwide. The authors develop a set of rules to produce a hierarchical four-level nomenclature of labels that is flexible and dynamic.

In this Consensus Statement, the authors discuss the issue of naming uncultivated prokaryotic microorganisms, which currently do not have a formal nomenclature system due to a lack of type material or cultured representatives, and propose two recommendations including the recognition of DNA sequences as type material.

Here, the International Committee on Taxonomy of Viruses describe a new, expanded virus classification scheme with 15 ranks that closely aligns with the Linnaean taxonomic system and better encompasses viral diversity.

This Perspective discusses fungal taxonomy and provides guidance for the naming of fungal taxa known only from sequences.