Implications of gut microbiota dysbiosis and metabolic changes in prion disease

Study information

Needs review

study design

case-control

Citation

PMID PubMed identifier for scientific articles.

31837420

DOI Digital object identifier for electronic documents.

https://doi.org/10.1016/j.nbd.2019.104704

URI

Authors

Yang D, Zhao D, Shah SZA, Wu W, Lai M, Zhang X, Li J, Guan Z, Zhao H, Li W, Gao H, Zhou X, Yang L

Journal

Neurobiology of disease

Year

2020

Keywords:

Metabolomics, Microbiome, Multi-omics analysis, Prion infection, Short chain fatty acids

Evidence of the gut microbiota influencing neurodegenerative diseases has been reported for several neural diseases. However, there is little insight regarding the relationship between the gut microbiota and prion disease. Here, using fecal samples of 12 prion-infected mice and 25 healthy controls, we analyzed the structure of the gut microbiota and metabolic changes by 16S rRNA sequencing and LC-MS-based metabolomics respectively as multi-omic analyses. Additionally, SCFAs and common amino acids were detected by GC-MS and UPLC respectively. Enteric changes induced by prion disease affected both structure and abundances of the gut microbiota. The gut microbiota of infected mice displayed greater numbers of Proteobacteria and less Saccharibacteria at the phylum level and more Lactobacillaceae and Helicobacteraceae and less Prevotellaceae and Ruminococcaceae at the family level. A total of 145 fecal metabolites were found to be significantly different in prion infection, and most (114) of these were lipid metabolites. Using KEGG pathway enrichment analysis, we found that 3 phosphatidylcholine (PC) compounds significantly decreased and 4 hydrophobic bile acids significantly increased. Decreases of 8 types of short-chain acids (SCFAs) and increases of Cys and Tyr and decreases of His, Trp, and Arg were observed in prion infection. Correlation analysis indicated that the gut microbiota changes observed in our study may have been the shared outcome of prion disease. These findings suggest that prion disease can cause significant shifts in the gut microbiota. Certain bacterial taxa can then respond to the resulting change to the enteric environment by causing dramatic shifts in metabolite levels. Our data highlight the health impact of the gut microbiota and related metabolites in prion disease.

Experiment 1

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Curated date: 2024/03/15

Curator: Ikehdarlington

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Subjects

Location of subjects: China

Host species Species from which microbiome was sampled. Contact us to have more species added.: Mus musculus

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: Prion disease prion disease,prion disease pathway,prion induced disorder,prion protein disease,spongiform encephalopathy,Prion disease

Group 0 name Corresponds to the control (unexposed) group for case-control studies: Healthy Control

Group 1 name Corresponds to the case (exposed) group for case-control studies: Prion-infected mice

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Prion-infected mice

Group 0 sample size Number of subjects in the control (unexposed) group: 25

Group 1 sample size Number of subjects in the case (exposed) group: 12

Lab analysis

Sequencing type: 16S

16S variable region One or more hypervariable region(s) of the bacterial 16S gene: V3-V4

Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance: Illumina

Statistical Analysis

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

Statistical test: LEfSe; Random Forest Analysis; Welch's T-Test

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

LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool: 3

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness: decreased

Chao1 Abundance-based estimator of species richness: decreased

Simpson Estimator of species richness and species evenness: more weight on species evenness: decreased

Richness Number of species: decreased

Signature 1

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Curated date: 2024/03/18

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Source: Fig. 2B

Description: Cladogram made by LEfSe reflecting differentially abundance of bacterial taxa.

Abundance in Group 1: decreased abundance in Prion-infected mice

NCBI	Quality Control	Links
Alloprevotella
Candidatus Saccharibacteria
Candidatus Saccharimonas
Oscillospiraceae
Prevotellaceae
Rikenellaceae RC9 gut groupRikenellaceae RC9 gut group

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Signature 2

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Source: Fig. 2B

Description: Cladogram made by LEfSe reflecting differentially abundance of bacterial taxa.

Abundance in Group 1: increased abundance in Prion-infected mice

NCBI	Quality Control	Links
Bacilli
Campylobacterales
Epsilonproteobacteria
Helicobacter
Helicobacteraceae
Lactobacillaceae
Lactobacillales
Lactobacillus
Pseudomonadota

Revision editor(s): Ikehdarlington