Microbial GenomicsMicrobiologyPeer-reviewed journal article
Intraspecific microbiome dynamics across the life cycle of the milkweed bug Oncopeltus fasciatus
Will Larner, Nádia Thölke da Silva Grego, Kristen A. PanfilioiD
Abstract
The microbiome is an important part of the complete nutritional and genomic profile of insects. The species-rich insect order Hemiptera (aphids, cicadas, true bugs) is highly diverse for mode of microbiome acquisition, with the conundrum that species in the seed-feeding subfamily Lygaeinae have lost obvious anatomy for housing bacteria, either in bacteriocytes or midgut crypts. Here we characterize the microbiome of the milkweed bug Oncopeltus fasciatus as a tractable lygaeinid, using 16S rRNA sequencing. We assess how bacterial taxa vary between the sexes and across life history stages in a controlled environment, focusing on maternal-to-embryo transmission and distinguishing egg-stage constituents that are superficial or internal (transovarially transmitted). Among a core microbiome of 28 genera, the egg stage shows the greatest diversity, with a particular expansion of the family Comamonadaceae. We also analyze inter-individual variability in nymphs and adults and validate structured, stage-specific detection of seed material. Comparative analysis identifies Rhizobium as a notable microbiome constituent in seed-feeding Hemiptera, which we had previously shown to lack nitrogen metabolism components in the genome. Overall, we provide a nuanced assessment of bacterial abundance dynamics between individuals and across the life cycle and discuss the implications for acquisition and potential relevance as nutritional endosymbionts. This will underpin comparative investigations in seed-feeding bugs and future work in O. fasciatus on tissue-specific and diet-specific microbiome profiles, including in natural populations.
- organism: Drosophila
- assay: metagenomics
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: experimental assay
- Citations
- 1
- FWCI
- 3.83
- Field percentile
- top 15%
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