The #Evoluncheons paper list is back from vacation this week. Not a lot of papers the past couple weeks since I’m traveling—but also science twitter is dying?! I need to find new ways of spotting cool papers, how are you all doing it?

#evolution

Anyway, good stuff. We have:
1/8

The Koelle Lab revisits bottlenecks! Bottleneck size and mutation rate are inferred from a within-host branching process model fit to empirical sequences. They confirm the bottlenecks for SARS-CoV-2 and influenza A are both close to 1. Seen at EEID 2023!

2/8
https://www.biorxiv.org/content/10.1101/2023.08.14.553219v1

Synthetic DNA+protein sequences created by molecular evolution models are easily distinguished from real-world sequences using supervised ML. Main reason: real sequences have stronger mutation hotspots than simulated data? Seen on post by @GullumLuvl

3/8
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 in real life 😐

4/8
https://twitter.com/Grey_Monroe/status/1686204258574557185

Most knowledge of viral evolution in chronic infections comes from studies with small sample sizes. This paper from Lauring Lab has genomes for 104 SARS-CoV-2 infections in immunocompromised patients, 5 which shed virus for >8 weeks. A lot to unpack:

5/8
https://www.medrxiv.org/content/10.1101/2023.08.22.23294416v1

SARS-CoV-2 shedding and evolution in immunocompromised hosts during the Omicron period: a multicenter prospective analysis

Background: Prolonged SARS-CoV-2 infections in immunocompromised hosts may predict or source the emergence of highly mutated variants. The types of immunosuppression placing patients at highest risk for prolonged infection and associated intrahost viral evolution remain unclear. Methods: Adults aged >18 years were enrolled at 5 hospitals and followed from 4/11/2022-2/1/2023. Eligible patients were SARS-CoV-2 positive in the previous 14 days and had a moderate or severely immunocompromising condition or treatment. Nasal specimens were tested by rRT-PCR every 2-4 weeks until negative in consecutive specimens. Positive specimens underwent viral culture and whole genome sequencing. A Cox proportional hazards model was used to assess factors associated with duration of infection. Results: We enrolled 150 patients with: B cell malignancy or anti-B cell therapy (n=18), solid organ or hematopoietic stem cell transplant (SOT/HSCT) (n=59), AIDS (n=5), non-B cell malignancy (n=23), and autoimmune/autoinflammatory conditions (n=45). Thirty-eight (25%) were rRT-PCR positive and 12 (8%) were culture-positive ≥21 days after initial SARS-CoV-2 detection or illness onset. Patients with B cell dysfunction had longer duration of rRT-PCR positivity compared to those with autoimmune/autoinflammatory conditions (aHR 0.32, 95% CI 0.15-0.64). Consensus (>50% frequency) spike mutations were identified in 5 individuals who were rRT-PCR positive >56 days; 61% were in the receptor-binding domain (RBD). Mutations shared by multiple individuals were rare (<5%) in global circulation. ### Competing Interest Statement All authors have completed ICMJE disclosure forms (www.icmje.org/coi_disclosure.pdf). James Chappell reports receiving grants from NIH and DoD, outside the submitted work. Carlos Grijalva reports grants from NIH, CDC, AHRQ, FDA, Campbell Alliance/Syneos Health, consulting fees and participating on a DSMB for Merck, outside the submitted work. Anne Frosch reports a K08 award from NIH, and participating on the Hennepin Health Research Institute Board of Directors, outside the submitted work. Natasha Halasa reports grants from Sanofi, Quidel, and Merck, outside the submitted work. Adam Lauring reports receiving grants from CDC, NIAID, Burroughs Wellcome Fund, Flu Lab, and consulting fees from Roche, outside the submitted work. Emily Martin reports receiving a grant from Merck, outside the submitted work. ### Funding Statement Primary funding for this study was provided by the US Centers for Disease Control and Prevention (CDC) (award 75D30121F00002). Scientists from the US CDC participated in all aspects of this study, including its design, analysis, interpretation of data, writing the report, and the decision to submit the article for publication. ZR was supported by NIH T32HL007749. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This program was determined to be public health surveillance with waiver of participant informed consent by CDC and institutional review boards at all participating institutions and was conducted in accordance with applicable CDC policy and federal law. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present work are contained in the manuscript. Raw sequencing reads are available on the NCBI short read archive under BioProject PRJNA896930 and consensus sequences are available on GISAID.

medRxiv

Not much convergent evolution, which is mostly associated to antibody (including mAb) escape in Spike RBD. Intrahost variation had not been observed in global genomic surveillance. Possible adaptation to antiviral compounds. AIDS biggest factor in lengthy chronic infection!

6/8

Turns out common non-antibiotic pharmaceuticals (e.g. acetaminophen, ibuprofen) slow E. coli growth at environmentally relevant concentrations, but don’t select for adaptations nor induce cross resistance with actual antibiotics.

7/8
https://www.biorxiv.org/content/10.1101/2023.08.21.554069v2

aight folks see ya next week for #evoluncheons in full force; here's a free pic of the balkan countryside, en la buena parceritos

8/8