Rafal Mostowy

Phold's manuscript is now available @narjournal.bsky.social thanks to @susiegriggo.bsky.social @npbhavya.bsky.social @vijinim.bsky.social @linsalrob.bsky.social @martinsteinegger.bsky.social @milot.bsky.social @eunbelivable.bsky.social & others not on bsky #phagesky academic.oup.com/nar/article/...

Congratulations Zam! Very well deserved 🥳🍾🎉👏

Unlocking data in Klebsiella lysogens to predict capsular type-specificity of phage depolymerases - Nature Communications Here, the authors exploit the genetic information encoded in Klebsiella prophages to model the interplay between bacteria, prophages, and their depolymerases, using a directed acyclic graph-model and a sequence clustering-based model.

Can we exploit past phage infection events (prophages) to decipher the specificity of phage receptor-binding proteins such as depolymerases?🔎 Happy to share our recent work at @natcomms.nature.com 🔽 #microsky #phagesky

www.nature.com/articles/s41...

Delighted to see our paper studying the evolution of plasmids over the last 100 years, now out! Years of work by Adrian Cazares, also Nick Thomson @sangerinstitute.bsky.social - this version much improved over the preprint. Final version should be open access, apols.
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🌟 Exciting news! We’re launching three fully-funded postdoc positions for "New Horizons for Synthetic Phages”

Join us in tackling antimicrobial resistance with cutting-edge synthetic biology + AI bioinformatics. Based at Flinders Uni in vibrant Adelaide.

👇 Read on for details!
#Phage

Capsular specificity in temperate phages of Klebsiella pneumoniae is driven by diverse receptor-binding enzymes Understanding host-range determinants in temperate bacteriophages is critical for elucidating phage-host co-evolution and advancing phage therapies. We analysed 3,900 Klebsiella genomes from diverse e...

This work was equally driven by two PhD students, Aleksandra Otwinowska (experiments) and Janusz Koszucki (bioinformatics). Check out the preprint or DM if you want to learn more.
www.biorxiv.org/content/10.1...

Why does this matter?
✔️ Advances our understanding of host-range evolution
✔️ Highlights the importance of capsule modification, not just degradation, in phage infection
✔️ Challenges how we type capsules and assess phage specificity
✔️ Has direct implications for phage therapy and vaccine design
🚨🧬💉

This underscores the complexity of predicting enzyme specificity — even similar proteins may target different capsules.

Yet, the study reveals an enormous functional and structural diversity encoded in temperate phages.

But predictions are just the start.

Together with the group of Zuzanna Drulis-Kawa, we experimentally tested 50 candidate enzymes from prophages on a panel of 119 capsule types.

Only 14 were active — and not always on the predicted target.
🧪🧫

We discovered a widespread class of SGNH hydrolase–containing RBPs — enzymes structurally related to deacetylases.

They likely modify capsules (e.g. by removing acetyl groups) instead of degrading them — a very different phage infection strategy!

We found 16 capsule types (K-loci) with strong genetic predictors, mostly receptor-binding proteins (RBPs).
Some were classical depolymerases… but many were not.

This is one of the first large-scale GWAS efforts focused on phage–host interactions — and shows how prophages carry hidden information about viral host range.

🔥 Here’s what we found!

But...

temperate phages (those that integrate into the bacterial genome) are less understood.

We analysed 3,900 Klebsiella genomes and identified over 8,100 prophages, then applied GWAS to link phage genes to capsule types.

Phages use surface-binding proteins to recognise their bacterial hosts.

In Klebsiella, this often means targeting the capsule — a sugary layer that varies across strains. Some phages bring depolymerases, enzymes that slice through these polysaccharides to enable infection.

What determines who a phage can infect?

We tackled this question for temperate phages of Klebsiella — a bacterial pathogen — using a genome-wide association study (GWAS) and a massive protein testing effort.

👇 A thread!

I'm looking for a postdoc in computational evolutionary phage genomics, with the goal to better understand how protein innovation arises in viruses, at @jagiellonskiuni.bsky.social in Krakow (Poland).

Drop me a line if it sounds cool!

Deadline: 20.06.

Link here:
mcb.uj.edu.pl/documents/15...

We're looking for a PhD student to join us at Vilnius University in Lithuania. We work on RNA virus evolution computationally but we'd like to generate more mosquito RNA virus sequence data. Official ad: www.gmc.vu.lt/en/doctoral-.... Please share & continue reading if interested.

Exploration of the genetic landscape of bacterial dsDNA viruses reveals an ANI gap amid extensive mosaicism | mSystems We introduce a novel computational pipeline called MANIAC, designed to accurately assess average nucleotide identity (ANI) and alignment fraction (AF) between diverse viral genomes, scalable to data s...

Appending the link to the paper again!
journals.asm.org/doi/10.1128/...

PS: MANIAC is offered in three modes: Fragment Mode (inspired by bacterial approaches), CDS (using best-bidirectional hits) and Protein (like CDS but with protein sequences. The latter two also offers the calculation of wGRR proposed by @epcrocha.bsky.social, so is great for prophages.

GitHub - bioinf-mcb/MANIAC: Computation of average nucleotide identity with the use of MMseqs2 Computation of average nucleotide identity with the use of MMseqs2 - bioinf-mcb/MANIAC

Finally, we prioritised usability. While no tool is perfect, Maniac is designed to be easy to install & run. If you work on viral comparative genomics or metagenomics, give it a try! 🛠️ Open-source & available here:
github.com/bioinf-mcb/M...

With MANIAC we also obtained some insights into ANI-based taxonomic assignments of dsDNA phages: we found that while it works well for lytic phages, it struggles with temperate phages—likely due to their extensive recombination & mosaicism, as seen in λ-like phages.

To me, this bears resemblance to a recombination threshold hypothesis in bacteria, where above this threshold recombination maintains species cohesiveness (high AF), and below it enhances diversification and evolution (low AF). But it's a hypothesis at this stage. (Figure from PMID 19197054)

Using MANIAC, we noticed that ANI distribution in dsDNA phages shows a distinct gap around 80%. Above this, genomes align well; below it, AF drops. This pattern holds even in large, metagenome-derived datasets like PhageScope, though there we see many more recent recombinants (high ANI and low AF).

MANIAC isn’t just accurate—it’s fast. Its "Fast" setting, which is still reliably accurate for ANI~70%, can process RefSeq on a laptop within minutes and can handle metagenomic datasets on HPCs.

We benchmarked MANIAC's accuracy against both BLAST-based & simulated datasets, showing it estimates ANI reliably over a wider range of sequence divergence than existing tools like CheckV, FastANI or MUMmer, which are better suited for the ANI>80% range.

Most ANI tools handle closely related genomes well (>80% ANI). But for viruses, we often care about ANI around 70%—a range where alignment can be tricky due to genome diversity & rearrangements. MANIAC tackles this using a fragment-based approach inspired by bacterial genome comparisons.

🚀 Follow-up on my recent MANIAC tweet: our new MMseqs2-blased tool is optimised for ANI and alignment fraction (AF) calculation in viral genomes. Unlike many other tools, it excels at ANI ~70%, an important range for viral taxonomy & evolution.

Here’s why that matters ➡️ a thread! 🧵

It was a pleasure working with you and Wanangwa on this project and I'm happy to see it published. Congratulations all!

And now with the working link!
journals.asm.org/doi/10.1128/...

Exploration of the genetic landscape of bacterial dsDNA viruses reveals an ANI gap amid extensive mosaicism | mSystems We introduce a novel computational pipeline called MANIAC, designed to accurately assess average nucleotide identity (ANI) and alignment fraction (AF) between diverse viral genomes, scalable to data s...

You’re right, something went wrong. Here’s the link
journals.asm.org/doi/10.1128/...