We have a fully-funded PhD studentship available to elucidate the host-adaptive traits of the human gut microbiome: bbsrcdtp.lifesci.cam.ac.uk/how-apply (targeted project: TRG-VET-AA26).

Feel free to reach out with a CV and cover letter stating your interest in this project.

Applications to our free course on "Introduction to Experimental Design and Core Statistics" closes this Friday. Part of the @ukgibanetwork.bsky.social, this is a great opportunity to improve your statistical skills and get to meet other network members.

Apply here: forms.office.com/e/sdys5HATUH

Representing the bioinformatics crowd at the #GIBANetworklaunch

Interestingly, we found that co-colonizing microbes are more metabolically diverse and functionally similar to Enterobacteriaceae, further supporting that habitat filtering (i.e., environmental selection) is a key factor shaping gut microbial composition.

We identified 172 gut microbial species positively associated with Enterobacteriaceae (co-colonizers) and 135 negatively-associated (co-excluders). Notably, various species belonging to the Faecalibacterium genus were most strongly associated with protection against Enterobacteriaceae colonization.

Using machine learning models trained on the rest of the gut microbiome, we were able to reliably classify individuals based on the presence or absence of Enterobacteriaceae. This predictive power remained largely consistent across diverse health states and geographic locations.

We set out to investigate in a large-scale dataset of >12,000 individuals whether there were microbiome differences consistently associated with the presence and abundance of Enterobacteriaceae.