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An interpretable Transformer-based model accurately predicts chronological age across body site and identifies key microbial signatures of aging.

The Qiita web platform provides access to large amounts of public microbial multi-omic data and enables easy analysis and meta-analysis of standardized private and public data.

A new discovery strategy, ‘reverse metabolomics’, facilitates high-throughput matching of mass spectrometry spectra in public untargeted metabolomics datasets, and a proof-of-concept experiment identified an association between microbial bile amidates and inflammatory bowel disease.

Genome-wide ancient DNA data from individuals from the Middle Bronze Age to Iron Age documents large-scale movement of people from the European continent between 1300 and 800 bc that was probably responsible for spreading early Celtic languages to Britain.

Inflammatory bowel disease dysbiosis networks were different between humans and dogs, with some species switching from positive to negative between groups. Stool samples were sufficient for dog-classification, whereas mucosal samples are required in humans.

The spatial distribution and parameters that affect soil microorganism communities are largely unknown. In this study, bacterial communities up to 240 metres apart are shown to be similar and are affected by soil pH, plant abundance and snow depth.

Autism spectrum disorder (ASD) is characterized by heterogeneous phenotypes. Disruption of the gut–brain axis (GBA) has been implicated in ASD although with limited reproducibility across studies. In this study, the authors propose a framework to leverage multi-omic datasets and investigate how the GBA influences ASD.

Advances in protein structure prediction have led to a significant influx of protein structure data. Here the authors exploit this data to offer an unbiased overview of complex sequence-structure-function relationships in the protein universe. This work opens up new uses for 3D structure data repositories in meta-omics and other fields of biology.

Ley, Gordon and colleagues have analysed and compared published sequences of bacterial communities from humans with both free-living communities and those that are associated with diverse animals. They conclude that gut-associated microbiotas are profoundly different from other free-living microbiotas, and call for widespread sampling of the human gut microbiota to study how different cultures, lifestyles and technologies are impacting on the biodiversity within these fascinating communities.

A conserved network of bacteria and fungi underpins cadaver decomposition despite selection effects of location, climate and season.

Higher milk intake is associated with lower type 2 diabetes risk in lactase non-persistent individuals, partly through gut microbiome and blood metabolites.

Analysis of human genotypes and 16S microbiome data of 18,473 individuals from 25 cohorts through a genome-wide association study, a phenome-wide association study and Mendelian randomization identifies host genetic and microbial trait associations.

Chronic alcohol use is associated with intestinal bacterial overgrowth and dysbiosis, but the contribution of ethanol is unclear. Here, using mouse models, the authors find that ethanol is not directly metabolized by the gut microbiota, and that induced changes are rather a side effect of elevated acetate levels.

The gut-derived molecule 4-ethylphenol influences complex behaviours in mice through effects on oligodendrocyte function and myelin patterning in the brain.

Cellular contexts such as disease state, organismal life stage and tissue microenvironment, shape intercellular communication, and ultimately affect an organism’s phenotypes. Here, the authors present Tensor-cell2cell, an unsupervised method for deciphering context-driven intercellular communication.

The authors use a machine-learning approach to uncover confounding variables in studies that seek to establish an association between the gut microbiota and human disease.

This work presents a sequencing strategy based on unique molecular identifiers that improves long-read consensus sequence accuracy of targeted amplicons as well as shotgun whole-genome fragments.

Gut microbiome composition has a role in health and disease. Here the authors show that microbiome signatures related to the Enterobacteriaceae family are associated with cause-specific mortality risk in a well phenotyped Finish population over a 15-year follow-up.

SourceTracker finds the proportion and origin of contaminants in a given sample. Its database will prove useful in screening of metagenomic datasets for contaminants.

A systematic evaluation of parameters that affect short amplicons sequenced on Illumina platforms provides guidelines for how to eliminate erroneous reads and improve data interpretation.

The microbiota of cesarean-born infants can be partially restored to that of vaginally born infants immediately after birth.

Large, updatable phylogenetic trees are constructed using a divide-and-conquer strategy.

Beals, Kayser et al. demonstrate that exercise, in conjunction with diet-induced weight loss, causes greater improvement in whole-body insulin sensitivity than matched diet-induced weight loss alone in people with obesity and prediabetes.

Openshaw and colleagues find myeloid inflammation and complement activation signatures in patients with long COVID who were previously hospitalized.

Here, applying an ecological framework to cross-sectional and longitudinal data, the authors identify major branches of the human gut microbiome across the lifespan that connect local ecological states, allowing to better capture associations with health, diet, and lifestyle.

As phase 1 of the Earth Microbiome Project, analysis of 16S ribosomal RNA sequences from more than 27,000 environmental samples delivers a global picture of the basic structure and drivers of microbial distribution.

The increasing amount of sequenced microbial genomes and metagenomes requires platforms for efficient integrated analysis. Here, Asnicar et al. present PhyloPhlAn 3.0, a pipeline allowing large-scale microbial genome characterization and phylogenetic contextualization at multiple levels of resolution.

Taxonomy classification of amplicon sequences is an important step in investigating microbial communities in microbiome analysis. Here, the authors show incorporating environment-specific taxonomic abundance information can lead to improved species-level classification accuracy across common sample types.

Metabolomics data from germ-free and specific-pathogen-free mice reveal effects of the microbiome on host chemistry, identifying conjugations of bile acids that are also enriched in patients with inflammatory bowel disease or cystic fibrosis.

mmvec, a neural-network-based algorithm, uses paired multiomics data (microbial sequence counts and metabolite abundances) to compute the conditional probability of observing a metabolite in the presence of a specific microorganism.

In this study, the microbiota of multiple body sites from 101 marine fish species from Southern California were sampled and analysed. The authors compared diversity measures while also establishing a method to estimate microbial biomass. Body site is shown to be the strongest driver of microbial diversity and patterns of phylosymbiosis are observed across the gill, skin and hindgut.

Serine deficiency can increase small fibre neuropathy in wild-type mice and serine replacement in diabetic mice alleviates diabetic neuropathy, directly linking amino acid metabolism to peripheral nerve disorders.

Standards for sequencing the microbial 'uncultivated majority', namely bacterial and archaeal single-cell genome sequences, and genome sequences from metagenomic datasets, are proposed.

Allaband et al. analyse how timing of sample collection affects the conclusions that can be drawn from microbiome studies, which has implications for study design.

The long-term dynamic behaviour of the gut microbiome in inflammatory bowel disease demonstrates increased deviation from the ‘healthy plane’ when compared to the normal variation observed in healthy individuals.

Biomphalaria glabrata is a fresh water snail that acts as a host for trematode Schistosoma mansoni that causes intestinal infection in human. This work describes the genome and transcriptome analyses from 12 different tissues of B glabrata, and identify genes for snail behavior and evolution.

The gut microbiomes of urban-industrialized societies differ from those of traditional rural societies and hunter-gatherers. Here the authors perform a comparative analysis of available and new gut microbiome data to provide fresh insight into these differences.

Association analysis identifies 65 new breast cancer risk loci, predicts target genes for known risk loci and demonstrates a strong overlap with somatic driver genes in breast tumours.

Genome-wide association analysis of gut microbial taxa in a single homogenous population-based cohort of 5,959 Finnish individuals identifies 567 independent SNP–taxon associations, including strong associations with LCT, ABO and MED13L.

Multi-omics analyses of faecal samples from patients with ulcerative colitis reveal a link between Bacteroides vulgatus protease activity and severity of disease symptoms.

An untargeted mass spectrometry analysis of a biological sample will detect both biological molecules and compounds that are derived from, for example, diet and the environment. This Review examines the design of such experiments, how to process and interpret the vast amount of data that are produced, and how far we are from being able to use mass spectrometry to inventory the world around us.

The rapid increase in the number of proteins in sequence databases and the diversity of their functions challenge computational approaches for automated function prediction. Here, the authors introduce DeepFRI, a Graph Convolutional Network for predicting protein functions by leveraging sequence features extracted from a protein language model and protein structures.

Qemistree uses fragmentation spectra to predict molecular fingerprints and represent their relationships as a tree, enabling comparison of metabolomics data across different experimental conditions and exploration of chemical diversity in mixtures.

Fructose consumption has greatly increased in recent years and has been linked to the development of hepatic steatosis. Here, the authors show that fructose promotes gut-barrier deterioration and subsequent endotoxaemia that in turn induces hepatic lipogenesis by activation TLR signalling in liver macrophages.

Many computational tools for metagenomic profiling have been developed, with different algorithms and features. This analysis shows that, when comparing these tools, the distinction of different types of relative sequence abundance should be taken into consideration.