Insights into the evolution of herbivory from a leaf-mining fly.

Herbivorous insects and their host plants comprise most known species on Earth. Illuminating how herbivory repeatedly evolved in insects from non-herbivorous lineages is critical to understanding how this biodiversity is created and maintained. We characterized the trophic niche of Scaptomyza flava, a representative of a lineage nested within the Drosophila that transitioned to herbivory ~10-15 million years ago. We used natural history studies to determine if S. flava is a true herbivore or a cryptic microbe-feeder, given that the ancestral character state for the family Drosophilidae is likely microbe-feeding. Specifically, we quantified oviposition substrate choice and larval viability across food-types, trophic-related morphological traits, and nitrogen isotope and sterol profiles across putatively herbivorous and non-herbivorous drosophilids. The results of these studies show that S. flava is an obligate herbivore of living plants. Paired with its genetic model host, Arabidopsis thaliana, S. flava is a novel and powerful system for exploring mechanisms underlying the evolution of herbivory, a complex trait that enabled the exceptional diversification of insects.

Using strain-resolved analysis to identify contamination in metagenomics data.

BACKGROUND: Metagenomics analyses can be negatively impacted by DNA contamination. While external sources of contamination such as DNA extraction kits have been widely reported and investigated, contamination originating within the study itself remains underreported. RESULTS: Here, we applied high-resolution strain-resolved analyses to identify contamination in two large-scale clinical metagenomics datasets. By mapping strain sharing to DNA extraction plates, we identified well-to-well contamination in both negative controls and biological samples in one dataset. Such contamination is more likely to occur among samples that are on the same or adjacent columns or rows of the extraction plate than samples that are far apart. Our strain-resolved workflow also reveals the presence of externally derived contamination, primarily in the other dataset. Overall, in both datasets, contamination is more significant in samples with lower biomass. CONCLUSION: Our work demonstrates that genome-resolved strain tracking, with its essentially genome-wide nucleotide-level resolution, can be used to detect contamination in sequencing-based microbiome studies. Our results underscore the value of strain-specific methods to detect contamination and the critical importance of looking for contamination beyond negative and positive controls. Video Abstract.