bioRxivMicrobiologyPreprint
Metabolic flexibility among fiber degraders supports gut microbiome stability across host diets in the American cockroach
Amber N. DePoyiD, Helen E. WalliD, Kara A. TinkeriD, Ian M. BlackiD, Elizabeth A. OtteseniD
Abstract
Scavenging omnivores face challenges in maintaining gut microbiome homeostasis due to a highly variable diet. Work in mammalian models has highlighted the importance of fiber-degrading taxa and their utilization of dietary polysaccharides and host glycans in structuring gut microbiome composition and function. However, less is known about biological mechanisms supporting gut microbiome homeostasis in insects. Here, we present a metatranscriptomic analysis of hindgut microbial transcriptional responses to diverse host diets in the American cockroach (Periplaneta americana), a hindgut-fermenting and omnivorous insect. We analyzed microbial community transcriptomes from hindguts of cockroaches fed high-fiber, high-protein, high-fat, and starvation diets. Microbial taxa predicted to be primary fiber degraders increased transcription of genes associated with utilization of dietary polysaccharides in insects fed a high-fiber diet. In contrast, these taxa responded to starvation and low fiber diets with upregulation of transcripts associated with degradation of host glycans. Analysis of N- and O-glycans in the cockroach midgut confirm the presence of predicted substrates for these pathways. As a result, we hypothesize that peritrophic matrix glycans serve as a critical carbohydrate subsidy supporting insect gut microbial metabolism in the absence of dietary fiber. Observed stability in gut microbiome composition and the transcriptional activity of many secondary fermenters and hydrogenotrophic taxa in the gut suggests that this strategy can be highly successful. Together, this work supports a novel physiological role for the peritrophic matrix of insects and other invertebrates in supporting gut microbiome homeostasis across dietary shifts.
- organism: Drosophila
- assay: metagenomics
- research focus: cell type annotation
- approach: statistical model
- Citations
- 3
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