Tom Stanton
@tomstantonmicro.bsky.social
190 followers 190 following 15 posts
Microbiologist. Lead developer of #Kaptive + bonafide #Klebsiella nerd. Post-doc in the Wyres Lab @AlfredMonash_ID.
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Reposted by Tom Stanton
kjolley.bsky.social
BIGSdb v1.51.4 has been released. This adds a new #Kaptive plugin for surface polysaccharide typing of Acinetobacter baumannii and Klebsiella. github.com/kjolley/BIGS... for details. Kaptive is developed by @tomstantonmicro.bsky.social, @kelwyres.bsky.social , @katholt.bsky.social and colleagues.
Output from Kaptive analysis shown in a BIGSdb isolate record. Tabular results are shown followed by a graphical representation of the genes within the locus analysed.
Reposted by Tom Stanton
kelwyres.bsky.social
Our new #klebsiella O type nomenclature, codesigned with Chris Whitfield, is now live in @pathogenwatch.bsky.social!

Need a quick explainer on the new names? Check out my blog post: tinyurl.com/y8yb3rbb (+link to full review article)

#MicroSky @klebnet.bsky.social @tomstantonmicro.bsky.social
Reposted by Tom Stanton
klebnet.bsky.social
We are pleased to launch the KlebNET Genomic Epidemiology Consortium!

We aim to build a public metadata repository; systematic risk framework for global genomic surveillance; and genomic epi reviews for high-impact #Klebsiella clones.

Join us here:
klebnet.org/klebnet-gsp-...

#ABPHM25
KlebNET-GSP
klebnet.org
Reposted by Tom Stanton
olayarendueles.bsky.social
Always a pleasure to organize this with @caityholmes.bsky.social @lauraamike.bsky.social Jay Vornhagen, Wen wen low, & this year joining us @tomstantonmicro.bsky.social & Juan Valencia.
tomstantonmicro.bsky.social
Lastly, we'd like to thank YOU, the Kaptive community, for guiding development, spotting bugs and collaborating with us!

But this is just the beginning, we have lots of exciting things in store for the future of Kaptive to make in silico serotyping even better!

#kaptive #klebsiella #acinetobacter
tomstantonmicro.bsky.social
Kaptive 3 is now integrated within Kaptive-Web (kaptive-web.erc.monash.edu), PathogenWatch (pathogen.watch), the new Kleborate 3 framework (github.com/klebgenomics...) and Bactopia (bactopia.github.io/latest/).

Remember to cite us if you use Kaptive for your results, and watch out for "Untypeable"!
Pathogenwatch
A global platform for genomic surveillance.
pathogen.watch
tomstantonmicro.bsky.social
We know the command-line can be tricky, so we made the CLI much friendlier 🧑‍💻

For the code-savvy, there's also a Python API allowing Kaptive to be used within your own programs 🧱
All the information you need is in the documentation, which we update regularly: kaptive.readthedocs.io/en/latest/
Introducing Kaptive 3 — Kaptive 3.0.0 documentation
kaptive.readthedocs.io
tomstantonmicro.bsky.social
Kaptive 3 is also much (much) faster than Kaptive 2, taking ~1 second per assembly 🏎️💨

This means that if you don't have a fancy HPC, then don't worry! You can still analyse thousands of your own assemblies on your laptop in a reasonable time! 💻
tomstantonmicro.bsky.social
We then subsampled the corresponding short reads at decreasing depths and created sets of increasingly awful draft assemblies with loci broken over contigs and lots of genes missing.

Kaptive 3 was much more sensitive than Kaptive 2, and maintained accuracy even when the assemblies were awful! 💩
tomstantonmicro.bsky.social
So enter Kaptive 3, a complete overhaul of Kaptive with a new algorithm designed to handle fragmented loci.

We also refactored (and simplified) the confidence score to be more sensitive for broken loci and missing genes, allowing more Kaptive data to be used when the assembly may not be complete 💯
tomstantonmicro.bsky.social
Because of how Kaptive 2 chose the best match locus, missing locus sequence resulted in a coverage bias for shorter loci in the database such, and could sometimes lead to inaccurate calls!

Ever seen a stray KL107 in your data that didn't make sense?

Yeah, that's why...
tomstantonmicro.bsky.social
So in a nutshell, we traced Kaptive's issues with the Klebsiella K-locus all the way back to the gDNA, where:

The locus region is partially amplified ->
Low sequencing read coverage ->
region doesn't assemble well ->
Untypeable Kaptive call ->
Unusable data 🙅‍♀️
tomstantonmicro.bsky.social
These genes have a very low GC compared to the rest of the Klebsiella chromosome, so we wondered if this was affecting how this part of the genome gets sequenced.

Turns out, these genes show decreased sequencing coverage when reads are prepped with Nextera XT, but not so much with Nextera Flex 🤯
tomstantonmicro.bsky.social
The major drivers of low confidence were K-loci that were 1) broken over contigs 🚫 and 2) missing genes ➡️➡️, events that were mostly co-occurring

Turns out, the genes missing were usually those important for antigenic diversity, in this case the glycosyltransferases that dictate the CPS 🍬 structure
tomstantonmicro.bsky.social
So you may have noticed your Klebsiella K-locus results from previous versions of Kaptive (v1-2) having lots of untypeable calls ("Low" + "None" confidence) with draft assemblies; we certainly did!

This meant that lots of useful seroepi data was unusable, so we started by finding out exactly why 🤔
tomstantonmicro.bsky.social
Super excited to finally present the preprint to accompany Kaptive 3 which we released last year!

Big thanks to coauthors @kelwyres.bsky.social, @katholt.bsky.social, @genomarit.bsky.social and Iren Löhr.

Here's what we did to improve in silico antigen typing 👇🧵
www.biorxiv.org/content/10.1...
Fast and Accurate in silico Antigen Typing with Kaptive 3
Surface polysaccharides are common antigens in priority pathogens and therefore attractive targets for novel control strategies such as vaccines, monoclonal antibody and phage therapies. Distinct serotypes correspond to diverse polysaccharide structures that are encoded by distinct biosynthesis gene clusters, e.g. the Klebsiella pneumoniae species complex (KpSC) K- and O- loci encode the synthesis machinery for the capsule (K) and outer-lipopolysaccharides (O), respectively. We previously presented Kaptive and Kaptive 2, programs to identify K and O-loci directly from KpSC genome assemblies (later adapted for Acinetobacter baumannii), enabling sero-epidemiological analyses to guide vaccine and phage therapy development. However, for some KpSC genome collections, Kaptive (v≤2) was unable to type a high proportion of K-loci. Here we identify the cause of this issue as assembly fragmentation, and present a new version of Kaptive (v3) to circumvent this problem, reduce processing times and simplify output interpretation. We compared the performance of Kaptive v2 and Kaptive v3 for typing genome assemblies generated from subsampled Illumina read sets (decrements of 10x depth), for which a corresponding high quality completed genome was also available to determine the 'true' loci (n=549 KpSC, n=198 A. baumannii). Both versions of Kaptive showed high rates of agreement to the matched true locus among 'typeable' locus calls (≥96% for ≥20x read depth), but Kaptive v3 was more sensitive, particularly for low depth assemblies (at <40x depth, v3 ranged 0.85-1 vs v2 0.09-0.94) and/or typing KpSC K-loci (e.g. 0.97 vs 0.82 for non-subsampled assemblies). Overall, Kaptive v3 was also associated with a higher rate of optimal outcomes i.e. loci matching those in the reference database were correctly typed and genuine novel loci were reported as untypeable (73-98% for v3 vs 7-77% for v2 for KpSC K-loci). Kaptive v3 was >1 order of magnitude faster than Kaptive v2 making it easy to analyse thousands of assemblies on a desktop computer, facilitating broadly accessible in silico serotyping that is both accurate and sensitive. The Kaptive v3 source code is freely available on GitHub (https://github.com/klebgenomics/Kaptive), and has been implemented in Kaptive Web (https://kaptive-web.erc.monash.edu). ### Competing Interest Statement The authors have declared no competing interest.
www.biorxiv.org
Reposted by Tom Stanton
bacpop.org
The PopPIPE (github.com/bacpop/PopPIPE) analysis pipeline can be used to subcluster data, create visualisations and run transmission analyses.

Preprint now here: www.biorxiv.org/content/10.1...
Including a case study on nosocomial transmission of vancomycin resistant Enterococcus faecium
GitHub - bacpop/PopPIPE: Population analysis PIPEline 🛠🧬
Population analysis PIPEline 🛠🧬. Contribute to bacpop/PopPIPE development by creating an account on GitHub.
github.com
Reposted by Tom Stanton
zeu.dev
zeu @zeu.dev · Dec 2
whimsy driven development ✨
Reposted by Tom Stanton
wvschaik.bsky.social
Great talk by @bugsinyourguts.bsky.social: Raoultella is definitely Klebsiella + identified novel beta-lactamase variants in K. ornithinolytica/terrigena/planticola #Klebsiella2024
tomstantonmicro.bsky.social
Don't forget to join the #KlebClub Slack workspace!
#Klebsiella #KLEBS2024
join.slack.com/t/klebclub/s...
Slack
join.slack.com
Reposted by Tom Stanton
klebclub.bsky.social
Lots of people are missing, let us know if you want to be included by replying!
You can also share to help us gain visibility
#MicroSky

go.bsky.app/EdereoU