Bacterial Metabolism and Transport Genes Are Associated with the Preference of Drosophila melanogaster for Dietary Yeast DOI

Tanner B. Call,

Emma K. Davis,

Joseph D. Bean

et al.

Applied and Environmental Microbiology, Journal Year: 2022, Volume and Issue: 88(16)

Published: Aug. 1, 2022

Many animal traits are influenced by their associated microorganisms ("microbiota"). To expand our understanding of the relationship between microbial genotype and host phenotype, we report an analysis influence microbiota on dietary preference fruit fly Drosophila melanogaster. First, confirmed through experiments flies reared bacteria-free ("axenic") or in monoassociation with two different strains bacteria that significantly influences across a range ratios yeast:dietary glucose. Then, focusing microbiota-dependent changes for yeast (DPY), performed metagenome-wide association (MGWA) study to define species specificity this trait predict bacterial genes it. In subsequent mutant analysis, disrupting subset MGWA-predicted DPY, including involved thiamine biosynthesis glucose transport. Follow-up tests revealed DPY did not depend modification protein content diet, suggesting mediate effects independent diet more specific than broad Together, these findings provide additional insight into determinants nutrition behavior revealing genetic disruptions D. melanogaster DPY. IMPORTANCE Associated ("microbiota") impact physiology hosts, defining mechanisms underlying interactions is major gap field host-microbe interactions. This expands how can (DPY) model host, show preferences vary identity microbes colonize flies. We then identify candidate contributed some influences. predicted genes, transport biosynthesis, resulted efforts feeding host.

Language: Английский

Antibiotic-induced gut microbiota dysbiosis has a functional impact on purine metabolism DOI Creative Commons
Xin Liu,

Leyong Ke,

Ke Lei

et al.

BMC Microbiology, Journal Year: 2023, Volume and Issue: 23(1)

Published: July 13, 2023

Dysbiosis of the gut microbiota is closely linked to hyperuricemia. However, effect microbiome on uric acid (UA) metabolism remains unclear. This study aimed explore mechanisms through which microbiomes affect UA with hypothesis that modifying intestinal influences development hyperuricemia.We proposed combining an antibiotic strategy protein-protein interaction analysis test this hypothesis. The data demonstrated antibiotics altered composition as increased, and spectrum was connected purine salvage pathway. antibiotic-elevated concentration dependent increase in code for proteins involved metabolism, paralleled by depletion bacteria-coding enzymes required On contrary, abundant decreased We also found antibiotic-increased coincided a higher relative abundance bacteria hyperuricemia mice.An combined prediction bacterial function presents feasible method defining key Our investigations discovered core may be related enriches related-proteins. enrich salvage-proteins probiotic decreasing urate, are more likely killed antibiotics. Therefore, pathway potential target treatment both resistance.

Language: Английский

Citations

13

Covariation Between Microbiome Composition and Host Transcriptome in the Gut of Wild Drosophila melanogaster: A Re‐Analysis DOI Creative Commons

Frances Llanwarne,

A. Dobson

Ecology and Evolution, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 1, 2025

ABSTRACT Gut microbiota are fundamental for healthy animal function, but the evidence that host function can be predicted from taxonomy remains equivocal, and natural populations remain understudied compared to laboratory animals. Paired analyses of covariation in parameters powerful approaches characterise host–microbiome relationships mechanistically, especially wild animals also lab models, enabling insight into ecological basis at molecular cellular levels. The fruitfly Drosophila melanogaster is a preeminent model organism, amenable field investigation by ‘omic analyses. Previous work male D. guts analysed paired measurements (A) bacterial diversity abundance, measured 16S amplicon sequencing; (B) gut transcriptome, no signature was detected. Here, we re‐analyse those data comprehensively. We find orthogonal axes microbial genera, which correspond differential expression genes. differentially expressed gene sets were enriched functions including protein translation, mitochondrial respiration, immunity reproduction. Each set had distinct functional signature, suggesting flies exhibit range variation, microbiome variation. These findings lay foundation better connect ecology genetics leading host‐microbiome model.

Language: Английский

Citations

0

Bacterial Metabolism and Transport Genes Are Associated with the Preference of Drosophila melanogaster for Dietary Yeast DOI

Tanner B. Call,

Emma K. Davis,

Joseph D. Bean

et al.

Applied and Environmental Microbiology, Journal Year: 2022, Volume and Issue: 88(16)

Published: Aug. 1, 2022

Many animal traits are influenced by their associated microorganisms ("microbiota"). To expand our understanding of the relationship between microbial genotype and host phenotype, we report an analysis influence microbiota on dietary preference fruit fly Drosophila melanogaster. First, confirmed through experiments flies reared bacteria-free ("axenic") or in monoassociation with two different strains bacteria that significantly influences across a range ratios yeast:dietary glucose. Then, focusing microbiota-dependent changes for yeast (DPY), performed metagenome-wide association (MGWA) study to define species specificity this trait predict bacterial genes it. In subsequent mutant analysis, disrupting subset MGWA-predicted DPY, including involved thiamine biosynthesis glucose transport. Follow-up tests revealed DPY did not depend modification protein content diet, suggesting mediate effects independent diet more specific than broad Together, these findings provide additional insight into determinants nutrition behavior revealing genetic disruptions D. melanogaster DPY. IMPORTANCE Associated ("microbiota") impact physiology hosts, defining mechanisms underlying interactions is major gap field host-microbe interactions. This expands how can (DPY) model host, show preferences vary identity microbes colonize flies. We then identify candidate contributed some influences. predicted genes, transport biosynthesis, resulted efforts feeding host.

Language: Английский

Citations

3