We’re looking for a PostDoc to join us in @halllab.bsky.social @unibirmingham.bsky.social.
Full-time, fixed-term to March 2028. Note tight closing date: 11 Jan 2026. CV + cover letter (submit via portal).
Further details 👇
edzz.fa.em3.oraclecloud.com/hcmUI/Candid...
We’re looking for a PostDoc to join us in @halllab.bsky.social @unibirmingham.bsky.social.
Full-time, fixed-term to March 2028. Note tight closing date: 11 Jan 2026. CV + cover letter (submit via portal).
Further details 👇
edzz.fa.em3.oraclecloud.com/hcmUI/Candid...
Authored by Aldert Zomer, Sam Nooij, Cailean Carter, and Alison Mather (@alisonmather.bsky.social).
Supported by the JPIAMR MEGAISurv project: jpiamr.eu/projects/meg...
Thanks to all contributing to strengthening mutation-focused AMR surveillance in metagenomic data.
Authored by Aldert Zomer, Sam Nooij, Cailean Carter, and Alison Mather (@alisonmather.bsky.social).
Supported by the JPIAMR MEGAISurv project: jpiamr.eu/projects/meg...
Thanks to all contributing to strengthening mutation-focused AMR surveillance in metagenomic data.
The code is open-source, with both a web-based interface and the full repository available:
Web tool: klif.uu.nl/metapointfin...
GitHub: github.com/aldertzomer/...
Feedback on extending reference sets and integrating the approach into surveillance pipelines is welcome.
The code is open-source, with both a web-based interface and the full repository available:
Web tool: klif.uu.nl/metapointfin...
GitHub: github.com/aldertzomer/...
Feedback on extending reference sets and integrating the approach into surveillance pipelines is welcome.
We applied the tool to public datasets on fluoroquinolone, β-lactam, and rifamycin resistance, showing how mutation-level profiling resolves discrepancies between phenotypes and gene-only predictions.
We applied the tool to public datasets on fluoroquinolone, β-lactam, and rifamycin resistance, showing how mutation-level profiling resolves discrepancies between phenotypes and gene-only predictions.
In benchmarks using simulated reads (100–5000 bp), MetaPointFinder outperformed existing mutation mappers and showed strong recovery of mutation-positive reads, particularly from long-read metagenomes.
In benchmarks using simulated reads (100–5000 bp), MetaPointFinder outperformed existing mutation mappers and showed strong recovery of mutation-positive reads, particularly from long-read metagenomes.
The outputs enable calculation of both relative abundance of mutation-driven AMR and the proportion of resistant reads among all reads mapping to a locus (WT + R). Metrics can be summarised at read, gene, or antibiotic-class level, extending metagenomic resistome profiling beyond gene presence.
The outputs enable calculation of both relative abundance of mutation-driven AMR and the proportion of resistant reads among all reads mapping to a locus (WT + R). Metrics can be summarised at read, gene, or antibiotic-class level, extending metagenomic resistome profiling beyond gene presence.
MetaPointFinder performs read-level protein and DNA alignment (DIAMOND + KMA) against curated AMRFinder mutation references. A custom scoring engine evaluates each substitution, enabling accurate detection across both long- and short-read datasets.
MetaPointFinder performs read-level protein and DNA alignment (DIAMOND + KMA) against curated AMRFinder mutation references. A custom scoring engine evaluates each substitution, enabling accurate detection across both long- and short-read datasets.
In metagenomic data, most AMR tools detect only acquired genes, while point mutations in gyrA, parC, folA, rpoB, 23S rRNA and others are major drivers of resistance. These variants are rarely quantified because they require precise alignment and position-specific evaluation.
In metagenomic data, most AMR tools detect only acquired genes, while point mutations in gyrA, parC, folA, rpoB, 23S rRNA and others are major drivers of resistance. These variants are rarely quantified because they require precise alignment and position-specific evaluation.
Our preprint on MetaPointFinder is online:
www.biorxiv.org/content/10.6...
Current resistome profiling has a major gap: it misses mutation-driven AMR, even though chromosomal mutations underpin resistance to key antimicrobials. MetaPointFinder addresses this at the read level in metagenomes.
Our preprint on MetaPointFinder is online:
www.biorxiv.org/content/10.6...
Current resistome profiling has a major gap: it misses mutation-driven AMR, even though chromosomal mutations underpin resistance to key antimicrobials. MetaPointFinder addresses this at the read level in metagenomes.
A new approach for detecting mutation-driven antimicrobial resistance directly from metagenomic reads.
Fills a major gap in current resistome profiling by capturing chromosomal AMR mutations that metagenome tools miss.
github.com/aldertzomer/...
🗓️ Apply by 6 January 2025
➡️https://buff.ly/sFpuQWo
@alisonmather.bsky.social
🗓️ Apply by 6 January 2025
➡️https://buff.ly/sFpuQWo
@alisonmather.bsky.social
🗓️ Apply by 6 January 2025
➡️https://buff.ly/sFpuQWo
@alisonmather.bsky.social
🗓️ Apply by 6 January 2025
➡️https://buff.ly/sFpuQWo
@alisonmather.bsky.social
Davos, 14–19 Jun 2026. Community-level mechanisms, AMR & practical interventions (experimental/computational/interventional).
Deadline: 18 Nov 2025 → tinyurl.com/4un5a8a4
#OneHealth #Microbiome #AMR
Davos, 14–19 Jun 2026. Community-level mechanisms, AMR & practical interventions (experimental/computational/interventional).
Deadline: 18 Nov 2025 → tinyurl.com/4un5a8a4
#OneHealth #Microbiome #AMR
🤰 Understanding the relationship between the maternal microbiome and fetal growth restriction with Professor Mark Webber @webberma.bsky.social and Professor Alison Mather @alisonmather.bsky.social
📅Apply by Monday 14 April
➡️ buff.ly/QL3JFtg
🤰 Understanding the relationship between the maternal microbiome and fetal growth restriction with Professor Mark Webber @webberma.bsky.social and Professor Alison Mather @alisonmather.bsky.social
📅Apply by Monday 14 April
➡️ buff.ly/QL3JFtg
#resistome #amr #microbiome #preterm
#resistome #amr #microbiome #preterm
quadram.ac.uk/vacancies/he...
quadram.ac.uk/vacancies/he...
#microsky
www.findaphd.com/phds/project...
#microsky
www.findaphd.com/phds/project...
www.findaphd.com/phds/project...
www.findaphd.com/phds/project...
Host–microbiota interactions in pancreatic cancer: determining whether they exist, and their influence on disease
Please RT. #MicrobiomeSky
Host–microbiota interactions in pancreatic cancer: determining whether they exist, and their influence on disease
Please RT. #MicrobiomeSky