Skip to content
Fowler Lab
Fowler Lab

Predicting antibiotic resistance de novo

  • News
  • Research
    • Overview
    • Manifesto
    • Software
    • Reproducibility
    • Publications
  • Members
  • Teaching
  • Contact
    • PhDs
  • Wiki
Fowler Lab
Fowler Lab

Predicting antibiotic resistance de novo

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

Post navigation

Previous post
Next post

Related Posts

antimicrobial resistance

New preprint: looking at rifampicin-resistant subpopulations in clinical samples

10th April 202510th April 2025

Since clinical samples are usually grown in a MGIT tube for a while before some…

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

AMyGDA now available from GitHub

27th January 202027th January 2020

AMyGDA is a python module that analyses photographs of 96-well plates and, by examining each…

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

Twitter at #ECCMID

27th April 20175th August 2018

A bit over two years ago I was a guest blogger at the US Biophysical…

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

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
To find out more, including how to control cookies, see here: Cookie Policy
    ©2025 Fowler Lab | WordPress Theme by SuperbThemes