auspice
For anyone not familiar with early SARS-CoV-2 phylogenetics, here is an accompany interactive Nextstrain narrative that makes it possible to examine the underlying data and different possible roots: nextstrain.org/groups/jbloo...
11.06.2025 12:09 β π 3 π 0 π¬ 2 π 0
auspice
If you aren't familiar with early SARS-CoV-2 phylogenetic trees, I also made an interactive Nextstrain narrative you can use to look at different representations of the underlying data: nextstrain.org/groups/jbloo...
11.06.2025 12:07 β π 2 π 0 π¬ 0 π 0
Deep mutational scanning of H3 influenza HA
A collection of data, figures, and analysis for exploring pleiotropic constraints on antigenic evolution.
All the data are available for visualization and download at dms-vep.org/Flu_H3_Massa...
Thanks to @timyu.bsky.social for leading study, and also @ckikawa.bsky.social, @bdadonaite.bsky.social, Andrea Loes, & Jane Englund.
27.05.2025 16:27 β π 6 π 2 π¬ 0 π 0
Overall, these results show how pleiotropic effects of mutations constrain HA evolution. Epistasis can alleviate these constraints w respect to cell entry in receptor binding pocket, but we find no evidence that mutations that strongly destabilize HA ever fix in H3N2 evolution.
27.05.2025 16:26 β π 5 π 1 π¬ 1 π 0
To examine implications for antigenic evolution, we measured how all HA mutations affected serum antibody neutralization.
Mutations at key trimer interface sites that cause substantial antibody escape but destabilize HA have never fixed.
27.05.2025 16:26 β π 1 π 1 π¬ 1 π 0
We found extensive entrenchment w respect to cell entry in receptor binding pocket (see below), consistent w prior work by @wchnicholas.bsky.social @rpdevrieslab.bsky.social
www.nature.com/articles/s41...
www.biorxiv.org/content/10.1...
But there was minimal entrenchment w respect to HA stability
27.05.2025 16:25 β π 3 π 1 π¬ 1 π 0
We then looked for evidence of epistasis by examining whether mutations had become entrenched. A mutation is entrenched if reverting it to the ancestral amino acid is deleterious in recent HAs, as schematized below.
27.05.2025 16:24 β π 1 π 1 π¬ 1 π 0
As can be seen below, constraint due to mutational impacts on cell entry are widely distributed across HA including receptor-binding pocket and fusion peptide. But mutational constraint due to HA stability is concentrated at trimer and HA1-HA2 interface.
27.05.2025 16:23 β π 2 π 1 π¬ 1 π 0
Deep mutational scanning of H3 influenza HA
A collection of data, figures, and analysis for exploring pleiotropic constraints on antigenic evolution.
We used pseudovirus deep mutational scanning to characterize all mutations to a recent H3N2 HA. This approach uses virions that can only undergo one round of cell entry & so are not pathogens capable of causing disease.
All measurements available here: dms-vep.org/Flu_H3_Massa...
27.05.2025 16:23 β π 2 π 1 π¬ 1 π 0
Deep mutational scanning of rabies glycoprotein defines mutational constraint and antibody-escape mutations
Rabies virus causes nearly 60,000 human deaths annually. Antibodies that target the rabies glycoprotein (G) are being developed as post-exposure prophβ¦
Final version of our pseudovirus deep mutational scanning of rabies glycoprotein now published in
@cp-cellhostmicrobe.bsky.social: sciencedirect.com/science/arti...
Main addition to preprint summarized above is additional validations of prefusion stabilization candidate mutations in Fig S4 and S5.
20.05.2025 16:37 β π 9 π 2 π¬ 0 π 0
GitHub - jbloomlab/flu_seqneut_H3N2_2023-2024: sequencing-based neutralization assay on H3N2 HA variants from 2023-2024
sequencing-based neutralization assay on H3N2 HA variants from 2023-2024 - jbloomlab/flu_seqneut_H3N2_2023-2024
All data described above are at github.com/jbloomlab/fl...
Thanks to @ckikawa.bsky.social & Andrea Loes for leading study, w important contributions from @huddlej.bsky.social , M Figgins, P Steinberg, T Griffiths, E Troisi, Heidi Peck, Ian Barr, Jan Englund, @scottehensley.bsky.social, T Bedford
12.03.2025 23:57 β π 7 π 0 π¬ 0 π 0
We hope that high-throughput measurements of neutralization of many recent influenza strains by many human sera, which are feasible to make w these new methods, can help w efforts to forecast influenza evolution for vaccine strain selection.
12.03.2025 23:55 β π 9 π 0 π¬ 1 π 0
The actual growth rates of viral strains were highly correlated w fraction of sera w low titers to strains, as shown below.
But there was no correlation if we just pooled all the sera and measured titers: per-serum measurements are needed to capture population heterogeneity.
12.03.2025 23:54 β π 5 π 1 π¬ 1 π 0
Can these measurements of antibody immunity across human population help us understand influenza evolution?
To address that question, we worked w T Bedford, @huddlej.bsky.social, M Figgins, P Steinberg to estimate growth rates of different H3N2 strains in 2023 using multinomial logistic regression.
12.03.2025 23:54 β π 6 π 0 π¬ 1 π 0
Below are titers of a large set of sera against all the strains.
The plot shows the extensive heterogeneity of population antibody immunity: titers against different strains vary widely across individuals.
12.03.2025 23:50 β π 4 π 0 π¬ 1 π 0
Different sera were better or worse at neutralizing different viral strains.
Below plot shows a 14-year old child neutralized most strains but had lower titers to strains mutated at site 145; a 24-year old neutralized those strains well but had lower titers to other strains.
12.03.2025 23:50 β π 4 π 0 π¬ 1 π 0
We used this assay to measure neutralizing titers of a large set of >100 children and adult sera against a panel of viruses representing the H3N2 influenza diversity circulating in humans in 2023.
12.03.2025 23:49 β π 4 π 0 π¬ 1 π 0
We recently developed high-throughput sequencing-based assay to measure how serum antibodies neutralize different influenza strains.
With assay, we can measure 1,872 neutralization curves per 96-well plate, compared to traditional assays that yield 8 or 12 curves per plate.
12.03.2025 23:49 β π 4 π 0 π¬ 1 π 0
As background, human seasonal influenza evolves to erode immunity. Vaccine updated regularly to keep pace w evolution, but forecasting which viral strains will dominate next season is hard.
One limitation is we donβt fully understand human immune landscape that drives evolution.
12.03.2025 23:49 β π 4 π 0 π¬ 1 π 0
New assays described here use single-cycle pseudoviruses, so enable study of F mutations w/o generating actual mutant viruses.
Thanks to @csimonich.bsky.social & Teagan McMahon, Xiaohui Ju, Tim Yu, Natalie Brunette, Terry Stevens-Ayers, Michael Boeckh, @kinglabipd.bsky.social, Alex Greninger
12.03.2025 22:40 β π 14 π 0 π¬ 1 π 0
Overall, RSV F antigenic evolution slower than for influenza hemagglutinin or SARS2 spike.
However, natural mutations can escape antibodies & modestly affect sera.
As antibodies become widely used, important to monitor for antigenic changes.
Assay we describe here will help enable that monitoring
12.03.2025 22:36 β π 11 π 1 π¬ 1 π 0
Interestingly, we found that the rare sporadic RSV strains with nirsevimab escape mutations also have reduced neutralization by human sera. Therefore, escape mutations selected by antibodies could have a moderate impact on polyclonal antibody immunity, and so merit monitoring.
12.03.2025 22:35 β π 4 π 0 π¬ 1 π 0
However, RSV F evolution has escaped some monoclonal antibodies, and we validated that rare sporadic strains have mutations that escape the currently recommended nirsevimab antibody.
12.03.2025 22:35 β π 4 π 0 π¬ 1 π 0
Head of Virology at Charite - UniversitΓ€tsmedizin Berlin
Postdoc in computational genomics studying RNA viruses at Cambridge. She/Her https://orcid.org/0000-0002-8400-6922
Assistant Professor @ulaval.ca; Tier 2 Canada Research Chair in Structural Systems Biology; Focused on virus-host interactions using structural biology
Paleontologist. Developmental Biologist. Anatomist. Polar wanderer. Telling people that they are fish since 2008.
Evolutionary and Mathematical Biology, sequence structure and function, genomes evolve, statistical theory and knowledge, empirical-theoretical interface, communication of evolutionary genetics, collaboratives, the mind-body problem, humanism
PhD student, UW/Fred Hutch MCB Joint Program
Evolutionary biologist; Lewis-Sigler Scholar @ Princeton. Formerly @ Harvard.
Doing science @UCSF in the Coyote-Maestas and Manglik Labs. Former Jackrel Lab @WUSTL www.matthewkhoward.com
Postdoc at UPenn thinking about mutations, cells, and evolution.
https://mrvollger.github.io
Ziheng Yang's Lab at UCL (CLOE) | Computational Molecular Evolution
Website: http://abacus.gene.ucl.ac.uk/
BPP GitHub: https://github.com/bpp/
PAML GitHub: https://github.com/abacus-gene/paml
PAML discussion group: https://groups.google.com/g/pamlsoftware
Bioinformatics and biosecurity
Staff scientist @ Fred Hutch.
PhD student - Machine Learning for Conservation.
Dias&Frazer Lab @crg.eu with Mafalda DΓas and @jonnyfrazer.bsky.social
Probabilistic machine learning to address questions in evolution and health #EvolutionaryMedicine. PI at the Centre for Genomic Regulation, co-leading a group with Mafalda Dias. Previously Harvard.
PhD candidate - Machine Learning and Genomics @CRG.eu with @jonnyfrazer.bsky.social and @MafaldaFigDias
Discover the Languages of Biology
Build computational models to (help) solve biology? Join us! https://www.deboramarkslab.com
DM or mail me!
Virologist & Professor, Pitt Dept. of Microbiology & Molecular Genetics and former Director of @Pitt-PMI.bsky.social
Seattle native living in Pittsburgh.
Website: http://ambrose-lab.com
Professor | Director, UQ Centre for RNA in Neuroscience | Queensland Brain Institute | Noncoding RNA and memory; RNA and DNA modification in the brain.