New publication: detecting minor populations important for predicting fluoroquinolone resistance Philip Fowler, 5th April 20238th December 2023 When predicting if an infection is resistant or susceptible to a specific antibiotic, it is all too easy to think that the infection is homogeneous and, in fact, many bioinformatic variant callers encourage that point of view. Or, at best, you can subvert the format of, say, a variant call file (VCF) by using the functionality designed to report diploidy for reporting (up to) two mixed populations. (What plant geneticists do I have no idea). Reality is likely messier, especially in a slow-growing persistent infection like tuberculosis and there have been previous studies suggesting that minor populations that are resistant to an antibiotic can come to dominate and should lead to a prediction of resistant. In this free-to-read paper, Dr Alice Brankin shows how allowing just two or more reads that support one of the two most common resistance-conferring mutations to levofloxacin and moxifloxacin, leads to a significant improvement in the sensitivity of genetics-based resistance prediction with no significant drop in specificity. This is important because the fluoroquinolones are present in several different drug regimes used to treat tuberculosis and brings their performance into line with other antibiotics (such as rifampicin and isoniazid) for which we believe we have a similar level of understanding of the mechanisms of resistance. Share this: Click to share on X (Opens in new window) X Click to share on Bluesky (Opens in new window) Bluesky Click to email a link to a friend (Opens in new window) Email Click to share on LinkedIn (Opens in new window) LinkedIn Click to share on Mastodon (Opens in new window) Mastodon Related antimicrobial resistance clinical microbiology tuberculosis
antimicrobial resistance Accelerating Oxford Nanopore basecalling 26th January 20175th August 2018 It looks innocuous sitting on the desk, an Oxford Nanopore MinION, but it can produce… Share this: Click to share on X (Opens in new window) X Click to share on Bluesky (Opens in new window) Bluesky Click to email a link to a friend (Opens in new window) Email Click to share on LinkedIn (Opens in new window) LinkedIn Click to share on Mastodon (Opens in new window) Mastodon Read More
New publication: Predicting antibiotic resistance in complex protein targets using alchemical free energy methods 26th August 202224th October 2022 In this paper, Alice Brankin calculates how different mutations in the DNA gyrase affect the… Share this: Click to share on X (Opens in new window) X Click to share on Bluesky (Opens in new window) Bluesky Click to email a link to a friend (Opens in new window) Email Click to share on LinkedIn (Opens in new window) LinkedIn Click to share on Mastodon (Opens in new window) Mastodon Read More
antimicrobial resistance New preprint: Predicting pyrazinamide resistance by machine learning 29th April 201929th April 2019 Usually, the protein that an antibiotic binds is essential for bacterial survival, which is how… Share this: Click to share on X (Opens in new window) X Click to share on Bluesky (Opens in new window) Bluesky Click to email a link to a friend (Opens in new window) Email Click to share on LinkedIn (Opens in new window) LinkedIn Click to share on Mastodon (Opens in new window) Mastodon Read More