Matthew R. Olm

The paper compares gut microbiomes of Tsimane and Hadza populations to show that many microbes co-migrated with humans globally, but are now vanishing in industrialized populations.

ZipStrain enables rapid and precise strain-resolved metagenomics by analyzing 2,754 human samples to identify strain-sharing gradients and gene variation.

This study uses MIg-Seq to analyze IgA targeting in infant gut microbiota, finding increased targeting of Bifidobacterium and diet-specific associations with IgA binding.

The paper compares DNA extraction and virome processing methods to show how they affect the characterization of human gut viral communities, finding that MDA significantly biases results.

MiFoDB is a metagenomics workflow that identifies microbes in fermented foods with high taxonomic resolution, enabling strain tracking and functional analysis.

The paper assesses strain-level diversity of Bradyrhizobium across soils in Australia, finding significant geographic and environmental variation in strain composition and inferred traits.

The paper introduces MIG-Seq to analyze IgA binding to gut microbiome strains and finds that microbial genes, especially mucus degradation genes, predict IgA binding levels.

The paper uses transporter gene frequencies to predict metabolite characteristics and identifies siderophore-like BGCs in gut microbiomes.

This study investigates how gestational age affects the functional potential and species richness of the gut microbiome in premature infants using genome-resolved metagenomics.

The paper identifies shifts in microbial transcription patterns in preterm infants prior to NEC onset, suggesting hypoxic conditions in the gut.

The paper analyzes microbial diversity and metabolic potential in cyanotoxin-producing cyanobacterial mats across a river network using metagenomic sequencing.

dRep groups genomes with fast Mash distances, then accurate ANI, de-replicating 1,125 infant gut genomes in 92 CPU hours versus 2,784 for naive gANI.