Patrick Pausch (UC Berkeley) and colleagues have published a new paper in Science on a new ‘minimal functional’ CRISPR-Cas system comprised of a single 70-kDa protein, CasΦ, that they discovered in phages. This system is active in human and plant cells, has expanded target recognition capacity, and is half the molecular weight of Cas9 and Cas12a, making it extra advantageous for genome editing.
Kaitlyn Kortright (Yale School of Medicine) and colleagues published a new paper in PNAS showing their use of INSeq screening to rapidly identify candidate phage receptors. They successfully identified receptors for 4 well-characterized phages and for 5/6 newly-isolated phages. Their approach is based on screening transposon mutant libraries under phage pressure to find bacterial genes required for phage infection.
High-throughput screenPhage receptorsResearch paper
Oluwafolajimi Adesanya and colleagues, who make up a new team of phage researchers from the University of Ibadan in Nigeria, just published their first review paper on phage therapy. The review also includes a unique perspective on phage therapy possibilities and limitations in Africa.
The Polz lab at the University of Vienna is hiring a postdoc to study phage-host interactions.
The Birmingham Institute of Forest Research (University of Birmingham) is hiring a research fellow to study how new strains of pathogens emerge and evolve using Pseudomonas syringae as a model pathogen. The project involves phage work.
Anyone can post a message to the phage community — and it could be anything from collaboration requests, post-doc searches, sequencing help — just ask!
July 24, 2020
PHAVES 4: How Pranav Johri made it easier to access phage therapy in India
Our next PHAVES event will take place Aug. 4 at 11:00 AM EST / 8:30 PM IST. We’ll be interviewing Pranav Johri, founder of Vitalis Phage Therapy, about his impressive progress improving access to phage therapy in India. Pranav is also the creator and host of the All About Phage Therapy virtual series.
Phage.ai, the interactive platform created by Piotr Tynecki (SLAVIC AI) and Proteon Pharmaceuticals, has released a new update! You can use phage.ai to access 10K phage sequences with extended characteristics (lifecycle, taxonomy, hosts, topology, strandedness, etc), make predictions about your own phages (eg. predict lifestyle), and more!
July 24, 2020
PhageOption 2020 Postponed
The PhageOption 2020 meeting scheduled to take place in Cartagena, Colombia, in November has been postponed to 2022.
From phage-disinfectant combos to phage AI: a recap of July’s PHAVES
Elyse Stachler began her talk by explaining the scope of the problem of hospital-acquired infections. She focused on Pseudomonas aeruginosa and the surface-associated biofilms it often creates, especially on plastics and other surfaces found in clinical settings (like catheters, trachial tubes, etc). She noted that due to the COVID crisis, hospital-acquired bacterial infections are becoming even more common and dangerous.
Elyse set out to pursue the question of how the microbiome of the built environment might be controlled, with a focus on phages. Her unique background as an engineer, and current affiliation at Switzerland’s national water research agency, Eawag, have undoubtedly put her in a great position to delve into these questions.
Elyse’s main questions were whether phages could be effectively combined with disinfectants (like bleach), which are already used to decontaminate hospital surfaces, whether the combination helped, and whether the order mattered. She surmised that if bleach could inactivate phages, this could have the added benefit of letting phages do their work, while also having them be conveniently inactivated after they’d finished (thus limiting the release of active phages into the environment).
She studied two phages, one model phage and one freshly isolated from wastewater, and looked at how they were able to affect P. aeruginosa biofilms in combination with sodium hypochlorite (bleach) in vitro, and she varied the order of application. She found that the two were slightly synergistic, and that biofilms were most effectively reduced if phages were added first. She hypothesized that this might be because the sodium hypochlorite negatively impacted the host bacteria, making the phage infection process less efficient due to sickly hosts. She went on to show that her phages could be partly inactivated by chlorine, suggesting that this too could be an explanation for why phages worked better when added before the disinfectant instead of after.
In the future, Elyse wants to study multispecies biofilms and look at more realistic biofilm conditions. She also made a note that phages do not all react the same way to disinfectants, so many more phage-disinfectant combinations should be examined in the future.
Piotr Tynecki started his talk by introducing the recent paper by Jean-Paul Pirnay that laid out an imagined future for phage therapy by 2035, where AI might one day predict phage-host interactions and help power intelligent phage design to treat any infection. Piotr, a PhD student studying machine learning who stumbled into the world of phage, feels that we’re already moving quickly toward this future. However, he emphasized that its success depends on a strong foundation of data that is shared by the phage community in a standardized, structured way.
Piotr first talked about what AI actually is, how it’s not new (e.g. Neflix, Spotify, etc. already rely on AI). He said it’s not even new to the phage world, because many bioinformatics tools already exist that let phage researchers make predictions based on AI. He walked through the basics about how AI works, and we learned about which parts of AI actually involve the input of human domain experts.
Piotr then described a platform that he co-created with Proteon Pharmaceuticals, and how it can already be used to predict phage lifestyle. He talked about how the algorithm initially worked great for lytic and temperate phages, until he heard from the community that it was failing for phages with lifestyles outside these two canonical types. When his team later updated the tool to account for chronic lifestyles, this vastly improved predictions. He impressed upon us that phage researcher feedback was clearly key to developing algorithms that work.
The second part of Piotr’s talk covered how his team’s platform makes phage taxonomy predictions. He said a recent switch from nucleotide to amino acid-based predictions was incredibly useful, and since there are so many more amino acid sequences matched to phage taxa (37 million!) compared to phage sequences with known lifestyles (low thousands), predicting phage taxonomy has been much more accurate than predicting lifestyle. However, predictions are not so reliable at the level of the genus yet (often there is only one phage genome per genus, as opposed to at least 20 examples of each at the family level). Again, the importance of researchers contributing phage data to central platforms that aggregate and structure it was emphasized.
The third section of Piotr’s talk covered phage.ai, the platform he and his company, SLAVIC AI, co-created with Proteon Pharmaceuticals, and how it can be used today. They built the free, open source platform based on 10,000 publicly available phage genomes. For instance, a user can input a phage genome and get a prediction of its lifestyle, or get a prediction on how different their phage is from all other phages.
Piotr concluded by saying that “the future of phage AI will be unsupervised”, meaning that with enough reliable, aggregated data, we’ll be able to make predictions about phage features without relying on expert-defined rules. He shared what he’s particularly excited about: eventually developing algorithms that can predict what kind of genetic engineering would make a phage more stable, more efficient at infecting, or otherwise “boost” its activity. First step: getting our data in order!
If you’d be interested in participating in a series of practical data science webinars dedicated to phage research, please join Phage Directory’s Slack, and let us know in the #phage-ai channel!
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