27 Aug 2023

 Not a lot of papers since I’m traveling—but also science twitter is dying?! I need to find new ways of spotting cool papers. Apologies for the heavy infection biology focus on these :/

Transmission bottleneck size estimation from de novo viral genetic variation. I saw this work presented at a conference in May, the Koelle lab is fantastic at this stuff. The authors develop a new, more careful approach to estimating how many viral particles are responsible for establishing a successful new infection (the transmission bottleneck size). The approach uses a branching process model of within-host viral growth to generate probability distributions used to infer maximum-likelihood estimates for bottleneck size and mutation rate per infection cycle given within-host growth metrics fit to empirical data from pathogen genomic sequencing. They confirm the bottlenecks for SARS-CoV-2 and influenza virus A are both close to 1.

https://www.biorxiv.org/content/10.1101/2023.08.14.553219v1

 

Simulations of sequence evolution: how (un)realistic they really are and why. Relevant to anyone simulating evolution or using simulated data to train ML. The authors use a variety of established models of molecular sequence evolution to generate synthetic phylogenies DNA and protein sequences. They then use supervised machine learning methods to distinguish these synthetic sequences from real-world, empirical sequences without a problem. The main issue seems to be distribution of mutations throughout the sequence: real sequences have much more prominent mutational hotspots than simulated data.

https://www.biorxiv.org/content/10.1101/2023.07.11.548509v1

On that last note, check out this thread of all the ways that mutations are not random 😐 https://twitter.com/Grey_Monroe/status/1686204258574557185

 

SARS-CoV-2 shedding and evolution in immunocompromised hosts during the Omicron period: a multicenter prospective analysis. Most of what we know of viral evolution in chronic infections comes from case studies with small sample sizes. This paper has sequencing data for 104 SARS-CoV-2 infections in immunocompromised patients, 5 of which shed virus for >8 weeks. Very few instances of convergent evolution, which is mostly associated to antibody (including mAb) escape in Spike RBD. Intrahost genetic variation had not been observed in global genomic surveillance. Some possible adaptation to antiviral compounds. HIV/AIDS is most important factor in lengthy chronic infection!

https://www.medrxiv.org/content/10.1101/2023.08.22.23294416v1

 

Non-antibiotic pharmaceuticals exhibit toxicity against Escherichia coli at environmentally relevant concentrations with no evolution of cross-resistance to antibiotics. The type of clever study where you wonder how someone hadn’t looked into this earlier. The authors tested bacterial inhibition of growth to common non-antibiotic pharmaceuticals like acetaminophen and ibuprofen at environmentally-relevant concentrations, given they’re pretty much everywhere. Well, turns out they slow E. coli growth, but don’t actually select for genetic adaptations nor induce cross resistance with actual antibiotics.

https://www.biorxiv.org/content/10.1101/2023.08.21.554069v2

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