Expanding the human gut microbiome atlas of Africa
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Study information
-
Quality control
- Retracted paper
- Contamination issues suspected
- Batch effect issues suspected
- Uncontrolled confounding suspected
- Results are suspect (various reasons)
- Tags applied
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI
Authors
Maghini DG, Oduaran OH, Olubayo LAI, Cook JA, Smyth N, Mathema T, Belger CW, Agongo G, Boua PR, Choma SSR, Gómez-Olivé FX, Kisiangani I, Mashaba GR, Micklesfield L, Mohamed SF, Nonterah EA, Norris S, Sorgho H, Tollman S, Wafawanaka F, Tluway F, Ramsay M, Wirbel J, Bhatt AS, Hazelhurst S
Journal
Nature
Year
2025
Population studies provide insights into the interplay between the gut microbiome and geographical, lifestyle, genetic and environmental factors. However, low- and middle-income countries, in which approximately 84% of the world's population lives1, are not equitably represented in large-scale gut microbiome research2-4. Here we present the AWI-Gen 2 Microbiome Project, a cross-sectional gut microbiome study sampling 1,801 women from Burkina Faso, Ghana, Kenya and South Africa. By engaging with communities that range from rural and horticultural to post-industrial and urban informal settlements, we capture a far greater breadth of the world's population diversity. Using shotgun metagenomic sequencing, we identify taxa with geographic and lifestyle associations, including Treponema and Cryptobacteroides species loss and Bifidobacterium species gain in urban populations. We uncover 1,005 bacterial metagenome-assembled genomes, and we identify antibiotic susceptibility as a factor that might drive Treponema succinifaciens absence in urban populations. Finally, we find an HIV infection signature defined by several taxa not previously associated with HIV, including Dysosmobacter welbionis and Enterocloster sp. This study represents the largest population-representative survey of gut metagenomes of African individuals so far, and paired with extensive clinical biomarkers and demographic data, provides extensive opportunity for microbiome-related discovery.
Experiment 1
Reviewed Marked as Reviewed by Svetlana up on 2025-2-13
Curated date: 2025/02/03
Curator:
Revision editor(s):
Subjects
- Location of subjects
- Kenya
- South Africa
- Host species Species from which microbiome was sampled. Contact us to have more species added.
- Homo sapiens
- Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
- Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces,feces
- Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- HIV-
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- People Living With HIV on Antiretroviral therapy (ART+ PLWH)
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Women living with HIV in Agincourt, South Africa (n = 60), Soweto, South Africa (n = 50) and Nairobi, Kenya (n = 19)
- Group 0 sample size Number of subjects in the control (unexposed) group
- 719
- Group 1 sample size Number of subjects in the case (exposed) group
- 119
Lab analysis
- Sequencing type
- WMS
- 16S variable region One or more hypervariable region(s) of the bacterial 16S gene
- Not specified
Statistical Analysis
- Statistical test
- Mixed-Effects Regression
- Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
- 0.01
- MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
- Yes
- Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment
- antibiotic therapy, geographic area
Alpha Diversity
- Inverse Simpson Modification of Simpsons index D as 1/D to obtain high values in datasets of high diversity and vice versa
- decreased
Signature 1
Source: Figure 4d, Supplementary Data 10
Description: Species-level prokaryotic differential abundance between seronegative and HIV+ participants in Agincourt (South Africa), Soweto (South Africa) and Nairobi (Kenya).
Abundance in Group 1: increased abundance in
Signature 2
Source: Supplementary Data 10
Description: Species-level prokaryotic differential abundance between seronegative and HIV+ participants in Agincourt (South Africa), Soweto (South Africa) and Nairobi (Kenya).
Abundance in Group 1: decreased abundance in
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