Hey hey phage phans,
It’s time again for our most well-loved post format — Phage Picks!
Jess and I run across papers that are so cool, we absolutely have to bookmark them. Those become our Phage Picks!
These are a small fraction of Picks from June/July… the phage field has absolutely been on fire recently, and we regularly find way more papers than we’re able to post (or read).
If YOU have a favorite phage paper (or article) we haven’t posted — email them to me and I’ll have a GUEST PICK every month. Just tell us what the paper is about, and why you’re excited about it. Who wants to be first??
Oh, Phage Picks by the numbers have done way better than any of our other Capsid formats — but we haven’t heard about the format much. Let me ([email protected]) know what you love (or hate) about it!
~ Jan
How AI Revolutionized Protein Science, but Didn’t End It
What is it about?
This article is about how AlphaFold came into the field of protein science, and how it’s changed computational biology.
Why I’m excited about it:
Though AI has only somewhat crept into the phage field, this article is a good indicator of what’s coming down the pike. The reason I’m picking more and more ML, AI, and data-centric phage articles is because I think biology will lean more and more towards the computational side of things. (And that’s because I’m biased and come from the computational side!)
On another note — we read a fair bit of posts and articles about and around technology x biology that are not explicitly phage related. I’ve been reluctant to share them on Capsid & Tail in order to keep C&T phage-focused… but I think some cross-pollination might be interesting for the field!
Let me know if more articles like this one are helpful!
~ Jan
Article: https://www.quantamagazine.org/how-ai-revolutionized-protein-science-but-didnt-end-it-20240626/
Also, we read a fair bit of posts and articles about and around technology x biology that are not explicitly phage related. I’ve been reluctant to share them on Capsid & Tail in order to keep C&T phage-focused… but I think some cross-pollination might actually be interesting for the field.
Protocol for phage matching, treatment, and monitoring for compassionate bacteriophage use in non-resolving infections
What is it about?
This is an in-depth protocol describing how the Israeli Phage Therapy Center (IPTC) does phage therapy. This is a ‘STAR Protocol’ that’s associated with a paper from the same group, which showed how one phage, PASA16, was used across multiple patients around the world. (This is actually one of the phages we borrowed and used in Australia, and the one that saved 7-year-old Dhanvi’s leg in 2019!).
Why I’m excited about it:
Most may be more excited about the clinical case series paper, but I’m particularly into this methods paper they published alongside it. For some reason, comparing how phage therapy centers do things around the world has become my new nerd hobby…
I just think it’s so great to see a phage therapy center put together their roadmap, especially when it involves not just the phage science, but the whole process from communicating with clinicians, selecting patients, to picking phages and purifying them, to monitoring the phage therapy during treatment and tracking patient data. It’s a huge undertaking, but it illustrates how much the challenges of phage therapy go beyond the science (while still being inextricably linked to it at almost every step!).
I also especially love how this paper lays out the timing for their steps (e.g. 22 days for phage banking!), and how detailed the methods are.
Ultimately I think the more centers communicate their process, the easier it will be for new centers to get up and running. As I’ve written about before, it was because of protocols like these (shout out to my good friend Phage on Tap, as well as another memorable paper from the IPTC group called Clinical Phage Microbiology, plus countless more, that it was even possible for us to set up our phage therapy system in Australia given the time, resource, and manpower (womanpower?) constraints we had.
As for the details, I still need to go through this lovely protocol paper with a fine toothed comb and compare to how we did things at Phage Australia! I may put together a summary table and make that its own post one day…
~ Jessica
Paper: https://www.sciencedirect.com/science/article/pii/S266616672400114X
Onallah, H., Yerushalmy, O., Braunstein, R., Alkalay-Oren, S., Rimon, A., Gelman, D., Coppenhagen-Glazer, S., Hazan, R., & Nir-Paz, R. (2024). Protocol for phage matching, treatment, and monitoring for compassionate bacteriophage use in non-resolving infections. In STAR Protocols (Vol. 5, Issue 2, p. 102949). Elsevier BV. https://doi.org/10.1016/j.xpro.2024.102949
Micro-plaque assays: A high-throughput method to detect, isolate, and characterize bacteriophages
What is it about?
In this paper, the authors developed a high-throughput assay to detect / isolate / characterize phages, by creating “micro colonies” using a Singer Rotor HDA. If you’re new to the Rotor, it’s basically high-precision, tiny stabby needle. The Singer creates overlays at a 1536-per plate density! That’s a pretty high throughput!
Each colony is just 2mm in size, but apparently that’s large enough to even observe individual plaques with morphologies. The team then used this tool to create a phind assay to test 1536 independent host-phage pairings — all while generating a massive phage library.
Why I’m excited about it:
We’ve come across few teams that have access to these massive (and fun!) machines, and the Hynes lab has done some really exciting stuff with the Singer (we visited them in-person a few years ago).
When you have access to something this high-throughput, it really changes perspective on what you can get done, and what can be done. Of course, I’m excited to get my hands on one of these to do some really-high-throughput data collection experiments for building more phage/host prediction models!
~ Jan
Paper: https://www.biorxiv.org/content/10.1101/2024.06.20.599855v1
Gayatri Nair, Alejandra Chavez-Carbajal, Rachelle Di Tullio, Shawn French, Dhanyasri Maddiboina, Hanjeong Harvey, Sara Dizzell, Eric D. Brown, Zeinab Hosseini-Doust, Michael G. Surette, Lori L. Burrows, Alexander P. Hynes
bioRxiv 2024.06.20.599855; doi: https://doi.org/10.1101/2024.06.20.599855
Going viral: The role of mobile genetic elements in bacterial immunity
What is it about?
The authors looked at mobile genetic elements and their role in bacterial immunity — and looked at their effect on bacterial defense systems.
Why I’m excited about it:
Phages, plasmids, satellites, whatever… are all “mobile genetic elements” seem to all have the ability carry some kind of defense system. And these encode the bacterial defense systems against MGEs. Basically, MGEs are the sword and the shield.
As someone coming from data engineering, I think it’s powerful to classify phages as part of a wider set of genetic elements that can be moved in and out of (and wielded by) bacteria, or other elements. I’m thinking of it like LEGO blocks. These blocks can be assembled for a specific use — offense, defense, and who knows what.
Since I’m interested in phage/host predictions and building systems that help us detect “weird bacterial offense and defense systems” — I think from a data and genomic perspective, we should be thinking about phages as part of a wider arsenal of mobile genetic elements we can wield for therapy, and for prediction.
And I’m starting to think that instead of “phage x HOST prediction” data engineers and bioinformaticians should think of “bacteria x mobile genetic element co-evolution prediction.”
~ Jan
Unfortunately this article is closed source, please email the authors for access: [email protected] [email protected]
Paper: https://www.cell.com/cell-host-microbe/abstract/S1931-3128(24)00189-6
Beamud, B., Benz, F., & Bikard, D. (2024). Going viral: The role of mobile genetic elements in bacterial immunity. In Cell Host & Microbe (Vol. 32, Issue 6, pp. 804–819). Elsevier BV. https://doi.org/10.1016/j.chom.2024.05.017
A phage tail–like bacteriocin suppresses competitors in metapopulations of pathogenic bacteria
What is it about?
The authors found a conserved mobile genetic element across a bunch of plant bacteria… a prophage? A tailocin?… that the host bacteria was wielding as a weapon against other bacteria!
Basically it’s a tailocin that target outer membranes against very specific strains — so it’s a “weapon” used in competition and coevolution between bacterial populations.
The authors note that these tailocins can be engineered to have new specificities — and to be strain-specific antibiotics. And — because these tailocin-as-stabby-sword-mechanics seems to have been around for ~200 years — it opens up more questions around evolution and resistance.
Why I’m excited about it:
Maybe it’s possible to create highly-specific tailocin cocktails, as targeted antimicrobials?
The paper was looking at plant bacteria — if these tailocin dynamics have been around for hundreds of years, could we use them to help control plant pathogens for agriculture?
A few groups have worked on bacteriocin / tailocin treatments before, and I think I’ve read that they’re kind of hard to produce and not always stable. I’m curious though, if we’re able to “print” these tailocins fairly easily, and use them as a way to train / co-evolve bacteria in a deterministic way, similar to how we use Appelman’s? (Eventually, can we predict how tailocins affect bacterial evolution)
~ Jan
Unfortunately this article is closed source, please email the authors for access: [email protected] (H.A.B.); [email protected]
Tweet: https://twitter.com/hernanaburbano/status/1801388936000061918
Paper: https://www.science.org/doi/10.1126/science.ado0713
Backman, T., Latorre, S. M., Symeonidi, E., Muszyński, A., Bleak, E., Eads, L., Martinez-Koury, P. I., Som, S., Hawks, A., Gloss, A. D., Belnap, D. M., Manuel, A. M., Deutschbauer, A. M., Bergelson, J., Azadi, P., Burbano, H. A., & Karasov, T. L. (2024). A phage tail–like bacteriocin suppresses competitors in metapopulations of pathogenic bacteria. In Science (Vol. 384, Issue 6701). American Association for the Advancement of Science (AAAS). https://doi.org/10.1126/science.ado0713
