Exposure to concentrated ambient PM2.5 alters the composition of gut microbiota in a murine model

From BugSigDB
Reviewed Marked as Reviewed by Claregrieve1 on 2022/12/29
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI
Authors
Wang W, Zhou J, Chen M, Huang X, Xie X, Li W, Cao Q, Kan H, Xu Y, Ying Z
Journal
Particle and fibre toxicology
Year
2018
Keywords:
Diabetes, Glucose homeostatic, Gut microbiota, PM2.5
BACKGROUND: Exposure to ambient fine particulate matter (PM2.5) correlates with abnormal glucose homeostasis, but the underlying biological mechanism has not been fully understood. The gut microbiota is an emerging crucial player in the homeostatic regulation of glucose metabolism. Few studies have investigated its role in the PM2.5 exposure-induced abnormalities in glucose homeostasis. METHODS: C57Bl/6J mice were exposed to filtered air (FA) or concentrated ambient PM2.5 (CAP) for 12 months using a versatile aerosol concentration enrichment system (VACES) that was modified for long-term whole-body exposures. Their glucose homeostasis and gut microbiota were examined and analysed by correlation and mediation analysis. RESULTS: Intraperitoneal glucose tolerance test (IPGTT) and insulin tolerance test (ITT) showed that CAP exposure markedly impaired their glucose and insulin tolerance. Faecal microbiota analysis demonstrated that the impairment in glucose homeostasis was coincided with decreased faecal bacterial ACE and Chao-1 estimators (the indexes of community richness), while there was no significant change in all faecal fungal alpha diversity estimators. The Pearson's correlation analyses showed that the bacterial richness estimators were correlated with glucose and insulin tolerance, and the mediation analyses displayed a significant mediation of CAP exposure-induced glucose intolerance by the alteration in the bacterial Chao-1 estimator. LEfSe analyses revealed 24 bacterial and 21 fungal taxa differential between CAP- and FA-exposed animals. Of these, 14 and 20 bacterial taxa were correlated with IPGTT AUC and ITT AUC, respectively, and 5 fungal taxa were correlated with abnormalities in glucose metabolism. CONCLUSIONS: Chronic exposure to PM2.5 causes gut dysbiosis and may subsequently contribute to the development of abnormalities in glucose metabolism.

Experiment 1


Reviewed Marked as Reviewed by Claregrieve1 on 2022/12/29

Curated date: 2021/01/10

Curator: WikiWorks

Revision editor(s): Claregrieve1, WikiWorks, Victoria

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
Air pollution air pollution,Air pollution
Group 0 name Corresponds to the control (unexposed) group for case-control studies
mice exposed to PM 2.5 (CAP)
Group 1 name Corresponds to the case (exposed) group for case-control studies
mice exposed to filtered air (FA)
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
male C57Bl/6 J mice exposed to PM2.5 (CAP)
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
16S
16S variable region One or more hypervariable region(s) of the bacterial 16S gene
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
ANOVA
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)?
Yes

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness
increased
Chao1 Abundance-based estimator of species richness
increased
Simpson Estimator of species richness and species evenness: more weight on species evenness
increased
Richness Number of species
unchanged

Signature 1

Reviewed Marked as Reviewed by Claregrieve1 on 2022/12/29

Curated date: 2021/01/10

Curator: Zyaijah Bailey

Revision editor(s): Claregrieve1, WikiWorks

Source: Figure 4 & text

Description: The differential taxa between FA- and CAP-exposed mice

Abundance in Group 1: increased abundance in mice exposed to filtered air (FA)

NCBI Quality ControlLinks
Marvinbryantia
Mycoplasma
Mycoplasmataceae
Mycoplasmatales
Rikenellaceae
Alistipes finegoldii
Metamycoplasma sualvi
Rikenella microfusus
Lachnospiraceae bacterium DW52

Revision editor(s): Claregrieve1, WikiWorks

Signature 2

Reviewed Marked as Reviewed by Claregrieve1 on 2022/12/29

Curated date: 2021/01/10

Curator: Zyaijah Bailey

Revision editor(s): Claregrieve1, WikiWorks

Source: Figure 4 & text

Description: The differential taxa between FA- and CAP-exposed mice

Abundance in Group 1: decreased abundance in mice exposed to filtered air (FA)

NCBI Quality ControlLinks
Campylobacterales
Campylobacterota
Helicobacter
Helicobacteraceae
Peptostreptococcaceae
Romboutsia
Clostridium sp. 001
Clostridiaceae
Lachnospiraceae bacterium 10-1
Clostridium sp. Culture Jar-56
Papillibacter
Allobaculum
Turicibacter
Helicobacter hepaticus

Revision editor(s): Claregrieve1, WikiWorks