Hadza Hunter-Gatherer Gut Microbiome, Cross-Sectional

By human microbiome sequencing we can better understand how host evolutionary and ontogenetic history is reflected in the microbial function. However, there has been no information on the gut metagenome configuration in hunter-gatherer populations, posing a gap in our knowledge of gut microbiota (GM)-host mutualism arising from a lifestyle that describes over 90% of human evolutionary history. Here, we present the first metagenomic analysis of GM from Hadza hunter-gatherers of Tanzania, showing a unique enrichment in metabolic pathways that align with the dietary and environmental factors characteristic of their foraging lifestyle. We found that the Hadza GM is adapted for broad spectrum carbohydrate metabolism, reflecting the complex polysaccharides in their diet. Furthermore, the Hadza GM is equipped for branched-chain amino acid degradation and aromatic amino acid biosynthesis. Resistome functionality demonstrates the existence of antibiotic resistance genes in a population with little to no antibiotic exposure, indicating the ubiquitous presence of environmentally derived resistances. Our results demonstrate how the functional specificity of the GM correlates with environment and lifestyle, and how complexity from the exogenous environment is matched by endogenous homeostasis. The Hadza gut metagenome structure allows to appreciate the co-adaptive functional role of the GM in complementing the human physiology, providing a better understanding of the versatility of human life and subsistence.

Classified as human gut / stool shotgun DNA metagenome of adult by deterministic_prior with confidence 0.90. Assay shotgun_dna.

• host external_curation.infant_catalog · “infant triage reason_code age_adult_only”
• body site study.title · “the Hadza hunter-gatherer gut microbiota.”
• body site study.description · “information on the gut metagenome configuration in”
• life stage external_curation.infant_catalog · “infant triage reason_code age_adult_only”

38 runs over 38 samples · mean 2.07 Gbp per run (median 1.31 Gbp, total 78.62 Gbp; 38 runs with a base count) · layout PAIRED 38 · platform ILLUMINA 38 · models Illumina Genome Analyzer IIx (38) · 55% of runs with a Sandpiper profile · first public 2015-06-05

Rampelli S first · Schnorr SL · Consolandi C · Turroni S · Severgnini M · Peano C · Brigidi P · Crittenden AN · Henry AG · Candela M last · Quercia S · Castagnetti A · Nayfach S first · Rodriguez-Mueller B · Garud N · Pollard KS last · Soverini M first · Biagi E · Puente-Sánchez F first · García-García N · Tamames J last · Tisza MJ first · Buck CB last · Auchtung TA first · Stewart CJ · Smith DP · Triplett EW · Agardh D · Hagopian WA · Ziegler AG · Rewers MJ · She JX · Toppari J · Lernmark Å · Akolkar B · Krischer JP · Vehik K · Auchtung JM · Ajami NJ · Petrosino JF last · Tarracchini C first · Fontana F · Mancabelli L · Lugli GA · Alessandri G · Turroni F · Ventura M · Milani C last · Orihara K first · Yahagi K · Saito Y · Watanabe Y · Sasai T · Hara T · Tsukuda N · Oki K · Fujimoto J · Matsuki T last · Ormaasen I first · Rudi K · Diep DB · Snipen L last · van Sinderen D · Sola L first · Candeliere F · Busi E · Raimondi S · Amaretti A · Rossi M last

PRJNA278393.csv.gz (2.1 KB) · parquet (72.1 KB) — all 38 samples, every field with route and confidence · PRJNA278393_determinations.csv.gz (4.5 KB) — 353 evidence rows