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Happy to announce that MEDI, our method to quantify dietary intake through metagenomics is out now. 🧬 🧪🧫🦠 www.nature.com/articles/s42... #metagenomics #microbiome #microbiomesky So what is MEDI? A combination of two things:

(1) a linked food database of more than 400 food items that includes nutrition and genomic information with multiple fallback strategies (partial assemblies, higher ranks)

(2) a high specificity identification and quantification pipeline that reliably identifies metagenomic reads coming from food items even when those make up less than 0.001% of the total DNA

One new things we added since the preprint is validation with two controlled feeding studies. In both, MEDI was able to detect the dietary intervention . There was also good agreement with some micro- and macronutrients when creating a standardized portion out of the detected food items.

We were also able to infer the onset of solid food consumption in infants and found good agreement of MEDI with food frequency questionnaires. Last but not least, MEDI could identify dietary patterns associated with metabolic syndrome in a retrospective study.

Right now MEDI works best with high depth sequencing (>30M reads) and only works for human samples (working on including other hosts). However, it does *not* require new assays and can be used for existing metagenomic sequencing data to add dietary information.

This seems really useful - we have two projects where we would be very excited to try this out if you think it could work for non-human animals; one aims to estimate the degree to which different gulls are feeding on human foods (and how that influences health and disease measured in various ways).

2nd we do a lot of wild primate diet analyses (with metabarcoding) to explore trophic links and understand origins of disease outbreaks (e.g.,mpox) - if MEDI is sensitive, would be keen to try it out on our collection of shotgun metagenomes, many of which we have already done other diet analyses on

We are excited about having a way to quantify the microbiome and diet in the same sample in a single go and will use it for a bunch of projects in the future.

Thanks to @gibbological.bsky.social and all the collaborators: Hannah Holscher, @kl-fil.bsky.social l, @geeksthatspeak.bsky.social , and @chmoei.bsky.social . 💻+🥑+🦠=❤️