21 June 2023

 

There’ve been a ton of cool papers since the last time I shared anything here! Here are a few that I have on my to-skim list and some of you may find interesting:

 

Pathogen evolution:

Estimating the fitness cost and benefit of antimicrobial resistance from pathogen genomic data, a research paper with an R package. I have a vested interest in having someone else figure these phylodynamic problems out for me, so I’m happy to see it. https://royalsocietypublishing.org/doi/10.1098/rsif.2023.0074

 

Developing Phage Therapy That Overcomes the Evolution of Bacterial Resistance. I heard a keynote from Paul Turner about this at the EEID conference last month, it was like seeing my undergrad project dreams come true, very cool stuff. https://www.annualreviews.org/doi/10.1146/annurev-virology-012423-110530

 

Cancer and immunology

A friend (other than Davy, haha) recently gave me a good pitch to stop hating on cancer, so I’m trying! It’s an important problem of course, but even if I’d want to focus on infectious disease, there are a lot of valuable lessons and research synergies to take advantage of. cough and money cough sorry

 

Optimal cancer evasion in a dynamic immune microenvironment generates diverse post-escape tumor antigenicity profiles, a research paper. This is a cool synergy for our immunology-adjacent friends. The authors model different evolutionary strategies of antigenic escape. The optimal strategy actually ends up creating immunologically “hot” and “cold” tumors. I wonder if a similar dynamic could help explain why with certain pathogens (e.g. SARS-CoV-2) you see some chronic infections and some rapidly cleared ones. https://elifesciences.org/articles/82786

 

Deterministic evolution and stringent selection during preneoplasia, a research paper. The inspiration for this paper was the Lenski LTEE, but for cancer. These folks inactivated p53 in barcoded, lineage-traced gastric cell tissue cultures and then let’er rip for two years. They found that early evolutionary dynamics were kind of reproducible, like Lenski did. https://www.nature.com/articles/s41586-023-06102-8

 

General systems biology:

The computational capabilities of many-to-many protein interaction networks, a review. Not dealing with evolution directly, but implies cool, fundamental insights about how evolutionary complexity evolves. https://www.sciencedirect.com/science/article/pii/S240547122300145X?dgcid=author