A while ago, I sat down with insightful Noah Legall, Ph. D. when he asked me about phage therapy and we discussed phage specificity. I’m re-posting his article, which summarizes some of our discussion in the context of an important 2024 study for bacteriophage therapy (https://lnkd.in/gfrKQr44). Gaborieau et al. use machine learning to interpret a matrix of 38,000 in vitro phage host range datapoints with paired genomic data for each phage + bacterium. Their machine learning models are highly predictive of which bacteria a phage can infect based on genomic data alone, in agreement with a very similar study by Keith et al., 2024 (https://lnkd.in/gihUPBhm). Big data and ML/AI like in these studies have an important role to play in making phage therapy scalable. Thanks for sharing your summary, Noah! I've signed up for your Substack, The Microbialist, and look forward to reading more from you!
'The Microbialist' No. 3 ?????? I've had the pleasure of learning about phages through the periphery of my previous research experience and conversations I've had in the past (i.e. Nathan Brown has been a big inspiration in learning more). For this month, I wanted to sit down and see what the cutting edge was with using phage and bacteria genomics to predict interactions ?? In this newsletter, we delve into just this topic! Link to the newsletter in the comments ??