Congrats Rodolfo & Nina et al! Nothing is more gratifying than to see your tool be useful for such a cool study like this one. 🛰️
27.02.2025 20:19
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Congrats Rodolfo & Nina et al! Nothing is more gratifying than to see your tool be useful for such a cool study like this one. 🛰️
In summary, if you're looking for a great time, this paper has everything: virology, glycobiology, microbiology, metabolic models, epidemiology….
💬 Huge thanks to all who contributed! Shoutout to those I know are on this app: @bkell1123.bsky.social @smallard.bsky.social @gilbertjacka.bsky.social @chemsybio.bsky.social
This work reflects the collaborative spirit during the pandemic and the community-driven nature of microbiology—one of the reasons I fell in love with the field.
🔥 Then, we engineered the probiotic Escherichia coli Nissle 1917 (EcN) to produce these heparin lyases. The result? It effectively blocked SARS-CoV-2 binding and infection in human cell cultures!
🧬 We pinpointed the exact heparin lyases from B. thetaiotaomicron responsible for blocking SARS-CoV-2 infection in vitro.
🦠 We tested two common gut bacteria: Bacteroides ovatus and Bacteroides thetaiotaomicron. Both could use heparin as their sole carbon source and their culture supernatants blocked SARS-CoV-2 spike binding!
💡This made us wonder: Could these bacteria impact SARS-CoV-2's ability to infect cells? First, using a metabolic task analysis of multiple large microbiome datasets, we found that heparan sulfate modifying bacteria are inversely enriched according to host age, sex, but not diet.
🔬The gut is a replication reservoir for SARS-CoV-2, and people with GI symptoms often face more severe illness. The virus relies on heparan sulfate proteoglycans in the intestine’s protective layer (glycocalyx) to enter cells. Interestingly, gut bacteria can alter heparan sulfate …
🔥 Finally published in mBio @asm.org! An update from the 2020 pre-print: “SARS-CoV-2 infectivity can be modulated through bacterial grooming of the glycocalyx.” 🔗https://journals.asm.org/doi/10.1128/mbio.04015-24 🧵👇
So happy our paper made the list!
Possibly! I will email you both. 😂
There is a Python implementation & QIIME2 plugin in github.com/biocore/geme... which also contains RPCA, CTF, and phylogenetic-RPCA/CTF. There is also an R implementation here github.com/pixushi/temp.... Both have tutorials linked in the README. 🎓
This new method brings the most requested features for tensor factorization. Namely, correctly accounting for time (ordering/scale), handling varying temporal sampling between subjects, and projecting unseen data into an existing ordination (new subjects or time points). 🚀
New tensor factorization paper out today — a fun collaboration with Pixu Shi, Liat Shenhav, Rob Knight, & Anru_Zhang! 🎉 Check it out here: genomebiology.biomedcentral.com/articles/10....