Biology subjects

Rich, D.

Publications and source records attributed to Rich, D..

4 recordsLinked to original sources

bioRxiv2026

Entrenchment of germline amino-acid differences in antibody affinity maturation

Entrenchment -- epistasis that locks in amino acid differences between homologous proteins, so each disfavors substitutions toward the others state -- has been demonstrated along individual protein lineages over deep evolutionary time. Antibodies offer a unique system for studying entrenchment: multiple homologous germline V gene paralogs provide diverse starting points, and the rapid somatic evolution of affinity maturation generates dense phylogenies from which selection on germline-encoded residues can be inferred. Using DASM, a deep-learning model that separates selection from mutation in antibody repertoire data, we test for entrenchment across immunoglobulin heavy chain variable (IGHV) genes. We detect entrenchment at two levels of germline divergence, driven by different sources of epistasis. Within V gene families (up to [~]20% amino acid divergence), entrenched sites cluster at the borders of the complementarity-determining regions (CDRs, the antigen-binding loops) and show high germline diversity. These sites contact antigen, light chain, and the heavy chain CDR3 loop, all of which are encoded independently of the IGHV germline. This pattern is consistent with epistasis from genetically uncoupled partners. Between V gene families, at deeper levels of divergence (25-40%), entrenchment additionally includes positions in the framework scaffold distant from binding interfaces, suggesting a larger contribution from intra-heavy-chain structural constraints. Observed mutation frequencies in human repertoires corroborate these predictions where data are sufficient. Together, these results demonstrate that the rapid somatic evolution of antibodies can serve as a lens for revealing epistatic constraints acting on germline-encoded residues, including constraints imposed by genetically uncoupled partners assembled during B cell development.

evolutionary biology↗

bioRxiv2025

larch: mapping the parsimony-optimal landscape of trees for directed exploration

Phylogenetic inference algorithms for large data sets typically return a single tree. However, there are often many optimal trees, especially when sequence data is closely related. We develop a compact representation of large collections of maximally parsimonious histories--trees with mutations mapped onto tree edges. Our C++ implementation, larch, leverages this representation for a highly parallel search algorithm. The storage component uses our history DAG structure to compactly represent large families of optimal trees. The search algorithm integrates this storage with matOptimize for rapid tree optimization; the DAG structure allows us to accept thousands of conflicting tree rearrangements in parallel. The integration enables a new type of tree search: one that systematically maps out the collection of good trees, enabling moves that are directed away from the current set of optimal trees to cross valleys and increase the diversity of the set of optimal trees. It is able to identify more parsimonious trees than are found by other methods. We find diverse optimality landscapes for viral datasets, including many distinct plateaux. We also find that our implementation produces similar results whether using a variety of single starting trees or an ensemble of starting trees, indicating effective global optimization.

evolutionary biology↗

bioRxiv2025

Separating selection from mutation in antibody language models

Antibodies are encoded by nucleotide sequences that are generated by V(D)J recombination and evolve according to mutation and selection processes. Existing antibody language models, however, focus exclusively on antibodies as strings of amino acids and are fitted using standard language modeling objectives such as masked or autoregressive prediction. In this paper, we first show that fitting models using this objective implicitly incorporates nucleotide-level mutation processes as part of the protein language model, which degrades performance when predicting effects of mutations on functional properties of antibodies. To address this limitation, we devise a new framework: a Deep Amino acid Selection Model (DASM) that learns the selection effects of amino-acid mutations while explicitly factoring out the nucleotide-level mutation process. By fitting selection as a separate term from the mutation process, the DASM exclusively quantifies functional effects: effects that change some aspect of the function of the antibody. This factorization leads to substantially improved performance on standard functional benchmarks. Moreover, our model is an order of magnitude smaller and multiple orders of magnitude faster to evaluate than existing approaches, as well as being readily interpretable.

evolutionary biology↗

bioRxiv2019

A Sex-Specific Switch in Platelet Receptor Signaling Following Myocardial Infarction

BACKGROUNDA Sex-specific, personalized approach to anti-platelet therapy may be important in patients with myocardial infarction (MI).\n\nOBJECTIVESOur goal was to determine whether platelets activate differently in healthy men and women compared to following MI.\n\nMETHODSBlood was obtained from healthy subjects or patients presenting acutely with ST-segment Elevation Myocardial Infarction (STEMI) and non-ST Segment Elevation Myocardial Infarction (NSTEMI). Platelet function through surface receptor activation was examined in healthy subjects, in patients with MI, and in age- and strain-matched mice before and after MI. Multivariate regression analyses revealed clinical variables associated with platelet receptor sensitivity at the time of MI.\n\nRESULTSPlatelets from healthy women are dose-dependently more active compared to men, particularly through the platelet thromboxane signaling pathway (7.8-fold increase in women vs. 3.0-fold in men, P=0.02). At the time of MI, platelet activation through surface protease-activated receptor 1 (PAR1) was less in women than men (3.5-fold vs. 8.5-fold, respectively, P=0.0001). Multivariate regression analyses revealed male sex (P=0.04) and NSTEMI (P=0.003) as independent predictors of enhanced platelet PAR1 signaling at the time of MI. Similar to humans, healthy female mice showed preferential thrombin-mediated platelet activation compared to male mice (8.7-fold vs. 4.8-fold, respectively; P<0.001). In the immediate post-MI environment, male mice showed preferential thrombin-mediated platelet activation compared to female mice (12.4-fold vs. 5.5-fold, respectively; P<0.001).\n\nCONCLUSIONSThese results outline a previously unrecognized sex-dependent platelet phenotype where inhibition of thrombin signaling in the peri-MI environment--particularly in males--may be an important consideration.\n\nCONDENSED ABSTRACTPreclinical studies evaluating anti-platelet drugs are generally conducted in platelets isolated from healthy individuals. Growing evidence suggests changes in platelet signaling properties in certain disease conditions compared to healthy platelets may alter the response to anti-platelet medications. This investigation revealed that platelets from men and women who are healthy and following MI signal differently, particularly through thromboxane and PAR1 receptors. This effect was especially noted in patients with NSTEMI compared to STEMI. These observations raise the possibility of considering a sex-specific anti-platelet regimen for males and females in atheroembolic vascular diseases such as NSTEMI.

molecular biology↗