Characterization of the gut microbiota of Papua New Guineans using reverse transcription quantitative PCR

Study information

Reviewed Marked as Reviewed by Fatima on 2022/08/9

study design

cross-sectional observational, not case-control

Citation

PMID PubMed identifier for scientific articles.

25658868

DOI Digital object identifier for electronic documents.

10.1371/journal.pone.0117427

URI

https://pubmed.ncbi.nlm.nih.gov/25658868/

Authors

Greenhill AR, Tsuji H, Ogata K, Natsuhara K, Morita A, Soli K, Larkins JA, Tadokoro K, Odani S, Baba J, Naito Y, Tomitsuka E, Nomoto K, Siba PM, Horwood PF, Umezaki M

Journal

PloS one

Year

2015

There has been considerable interest in composition of gut microbiota in recent years, leading to a better understanding of the role the gut microbiota plays in health and disease. Most studies have been limited in their geographical and socioeconomic diversity to high-income settings, and have been conducted using small sample sizes. To date, few analyses have been conducted in low-income settings, where a better understanding of the gut microbiome could lead to the greatest return in terms of health benefits. Here, we have used quantitative real-time polymerase chain reaction targeting dominant and sub-dominant groups of microorganisms associated with human gut microbiome in 115 people living a subsistence lifestyle in rural areas of Papua New Guinea. Quantification of Clostridium coccoides group, C. leptum subgroup, C. perfringens, Bacteroides fragilis group, Bifidobacterium, Atopobium cluster, Prevotella, Enterobacteriaceae, Enterococcus, Staphylococcus, and Lactobacillus spp. was conducted. Principle coordinates analysis (PCoA) revealed two dimensions with Prevotella, clostridia, Atopobium, Enterobacteriaceae, Enterococcus and Staphylococcus grouping in one dimension, while B. fragilis, Bifidobacterium and Lactobacillus grouping in the second dimension. Highland people had higher numbers of most groups of bacteria detected, and this is likely a key factor for the differences revealed by PCoA between highland and lowland study participants. Age and sex were not major determinants in microbial population composition. The study demonstrates a gut microbial composition with some similarities to those observed in other low-income settings where traditional diets are consumed, which have previously been suggested to favor energy extraction from a carbohydrate rich diet.

Experiment 1

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Reviewed Marked as Reviewed by Fatima on 2022/08/9

Curated date: 2022/07/15

Curator: Kaluifeanyi101

Revision editor(s): Kaluifeanyi101, Claregrieve1, Victoria

Subjects

Location of subjects: Papua New Guinea

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: Socioeconomic status class,Socioeconomic status,socioeconomic status,socioeconomic factors

Group 0 name Corresponds to the control (unexposed) group for case-control studies: High SES (low land region)

Group 1 name Corresponds to the case (exposed) group for case-control studies: Low SES (high land region)

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Participants living a subsistence lifestyle in the high-land rural areas of Papua New Guinea

Group 0 sample size Number of subjects in the control (unexposed) group: 29

Group 1 sample size Number of subjects in the case (exposed) group: 86

Lab analysis

Sequencing type: 16S

16S variable region One or more hypervariable region(s) of the bacterial 16S gene: Not specified

Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance: RT-qPCR

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).: relative abundances

Statistical test: Mann-Whitney (Wilcoxon)

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): 0.05

MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?: No

Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment: age, sex

Signature 1

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Reviewed Marked as Reviewed by Fatima on 2022/08/9

Curated date: 2022/07/15

Curator: Kaluifeanyi101

Revision editor(s): Kaluifeanyi101, Claregrieve1

Source: Table 4

Description: Comparison of population numbers of selected microbial groups in the highland and lowland study participants.

Abundance in Group 1: increased abundance in Low SES (high land region)

NCBI	Quality Control	Links
Actinomycetota
Bacteroidota
Enterobacteriaceae
Bacillota
Lactobacillus

Revision editor(s): Kaluifeanyi101, Claregrieve1