EID?: wwwnc.cdc.gov/eid

12/12 📰 For more background and wider context, check out the @liverpooluni.bsky.social press release covering this study’s impact on understanding and diagnosing infectious intestinal diseases: news.liverpool.ac.uk/2025/05/20/a...

11/12 🙏 A big thank you to all my amazing collaborators who made this work possible @blancaps.bsky.social @jayhinton.bsky.social @acdarby.bsky.social (PI) and many of the INTEGRATE consortium not on BlueSky.
Thank you to @nihr.bsky.social for funding via the second HPRU-GI @livuni-ives.bsky.social.

10/12 🔍 This dual-omics approach captures both what pathogens are present and what they're doing, offering unmatched resolution for understanding infectious intestinal disease biology.

9/12 📊 RNA/DNA ratios differed significantly between positive and negative cases, helping distinguish true infection from bystander carriage and providing a molecular readout of microbial activity.

8/12 📦 Critically, RNA in stool remained stable enough for pathogen detection without preservatives (and after self-sample and surviving the mail service!), providing evidence for the routine potential of metatranscriptomics in clinical settings (with some work!)

7/12 🧫 For the first time, we captured a comprehensive snapshot of Salmonella gene expression from a human stool sample. These data reveal how bacteria survive and adapt after leaving the gut. Explore via Hinton Lab’s interactive browser: jb.hintonlab.com/index.html?d...

6/12 🦠➡️🧬 Metatranscriptomics also detected Cryptosporidium via its RNA virus, CSpV1, previously reported in diarrhoeic animals (doi.org/10.1186/s135...). Cryptosporidium was undetectable in metagenomic data, suggesting RNA sequencing can sensitively detect it when DNA methods fall short.

5/12 🦠 Metatranscriptomics captured active Adenovirus F infections via broad transcriptome coverage (in a couple of samples, near complete!), despite it being a DNA virus, highlighting its use in profiling ongoing viral activity during diarrhoeal illness.

4/12
🧪 Metatranscriptomics showed superior sensitivity, with strong correlation to conventional diagnostics for 6/15 pathogens and to Luminex for 8/14.
🧬 Metagenomics performed well for some targets but showed lower overall concordance.