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.
Authors
Maya-Lucas O, Murugesan S, Nirmalkar K, Alcaraz LD, Hoyo-Vadillo C, Pizano-Zárate ML, García-Mena J
Journal
Anaerobe
Year
2019
Keywords:
Cholesterol, Gut microbiome, High-throughput sequencing, Mexican children, Obesity, Triglycerides
Obesity is a metabolic disorder and global health issue. In Mexico 34.4% of children between 5 and 11 years-old are overweight or obese. Here we address this issue studying the gut microbiome in a sample of Mexican children affected by obesity. We performed metagenomic shotgun-sequencing of DNA isolated from fecal samples from a cohort of normal weight and obese Mexican children using Illumina platform with HiSeq 2500. We also examined their metabolic factors and fecal short-chain fatty acids concentration. The results show that a remarkable dysbiosis of bacteria, archaea and viruses was not observed in the obese children group compared to the normal weight group; however, the archaeal community exhibited an increase of unclassified Methanobrevibacter spp. in obese children. The bacterial communities of all participants were clustered into three different enterotypes. Most normal weight children have a gut bacterial community dominated by Ruminococcus spp. (Enterotype 3), while most obese children had a community dominated by Prevotella spp. (Enterotype 2). On the other hand, changes in the gut microbiome were correlated with clinical metadata and could be used to stratify individuals based on their phenotype. The species Megamonas spp. were over-represented in obese children, whereas members of the family Oscillospiraceae were depleted in the same individuals and negatively correlated with levels of serum cholesterol. A microbiome comparative metabolic pathway analysis showed that two KEGG pathway modules of glycolysis, Glycolysis I (from Glucose 6-Phosphate), and Glycolysis II (from Fructose 6-Phosphate) were significantly overrepresented in normal weight children. Our results establish specific alterations in the gut microbiome of Mexican children affected of obesity, along with clinical alterations, providing information on the microbiome composition that may be useful for prognosis, diagnosis, and treatment.
Experiment 1
Subjects
- Location of subjects
- Mexico
- Host species Species from which microbiome was sampled (if applicable)
- 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
- Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
- obesity Adiposis,Adiposity,Obese,Obese (finding),obesity,Obesity (disorder),Obesity [Ambiguous],obesity disease,obesity disorder,Obesity NOS,Obesity, unspecified,Overweight and obesity
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- normal
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- obese
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- unrelated children between 9 and 11 years
- Group 0 sample size Number of subjects in the control (unexposed) group
- 10
- Group 1 sample size Number of subjects in the case (exposed) group
- 10
Lab analysis
- Sequencing type
- WMS
- Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
- Illumina
Statistical Analysis
- Statistical test
- LEfSe
- 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
- LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool
- 2
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- unchanged
- Chao1 Abundance-based estimator of species richness
- unchanged
- Simpson Estimator of species richness and species evenness: more weight on species evenness
- unchanged
- Richness Number of species
- unchanged
Signature 1
Needs review
Source: Figure 4A
Description: Significant bacteria, path abundance-coverage, gene families found in the gut microbiome and association with metadata. Figure shows graphs of linear discriminant analysis (LDA) scores for differentially abundant bacterial genera, families or species;
Abundance in Group 1: increased abundance in obese
| NCBI | Quality Control | Links |
|---|---|---|
| Megamonas | ||
| Lachnospiraceae bacterium |
Signature 2
Needs review
Source: Figure 4A
Description: Significant bacteria, path abundance-coverage, gene families found in the gut microbiome and association with metadata. Figure shows graphs of linear discriminant analysis (LDA) scores for differentially abundant bacterial genera, families or species;
Abundance in Group 1: decreased abundance in obese
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