Biology subjects

Rajagopalan, R.

Publications and source records attributed to Rajagopalan, R..

3 recordsLinked to original sources

bioRxiv2026

Protein solubility depends on centrifugation: Aiki-Sol, a per-regime predictor for E. coli

MotivationSequence-based predictors of recombinant protein solubility in Escherichia coli have plateaued (NESG independent-test AUC 0.760 [->]~ 0.80 over eight years of protein-language-model variants). The plateau hides a latent confound: the centrifugation regime used to separate the soluble from the insoluble fraction is a hidden variable collapsed into a single binary "soluble" label. The proteins biochemistry does not change between regimes; what changes is which fraction of the lysate is recovered as soluble. Existing predictors treat the regime as label noise rather than a feature, and sequence overlap between training and test partitions masks the resulting failure mode. ResultsWe release the Aiki-Sol Dataset, a tiered E. coli solubility corpus: a ~ 85K stringency-annotated benchmark, an Apache-licensed ~ 147K extension adding binary-only-labelled proteins, and a ~ 229K research-tier pool incorporating non-commercially-licensed sources. On the ~ 85K benchmark, scored on sequence-cluster-disjoint partitions, the strongest published binary comparator falls below chance on the 32,000 x g stratum (AUC 0.491 {+/-} 0.020); a fine-tuned ESM-2 650M backbone with five protocol-matched out-puts lifts pooled AUC by +0.108 (paired-bootstrap CI lower bound +0.090). The gain is curation, not architecture: structure-aware predictors given ESMFold structures do not outperform the sequence-only frame, and capacity scaled to 3B parameters does not exceed the conditioned 650M backbone. The released model, Aiki-Sol, jointly supervises five per-stringency outputs alongside a marginal output for stringency-unknown proteins; on five external cohorts it lifts cohort-mean AUC from 0.69-0.70 to 0.825, with a [≥] +0.10-0.16 lift on the three cohorts at measurably-zero training-pool overlap. Availability and implementationAiki-Sol model weights (Apache 2.0), the 147K-row license-clean training pool of the deployment checkpoint (CC BY 4.0), the cluster-disjoint per-stringency 5-fold partition assignments, per-cohort prediction CSVs, and source code for training, inference, and figure reproduction are available at https://github.com/aikium-public/aiki-sol and archived at Zenodo 10.5281/zenodo.20151817. The research-tier 229K checkpoint is released under CC-BY-NC-ND 4.0 (inheriting the most-restrictive upstream-source tier); its training CSV and the 84,809-protein stringency-annotated bench-mark of [§]2.1 mix non-commercial-tier upstream sources and are not redistributed verbatim. Upstream sources are documented in Data availability and SI [§]S1. The deployment artefact is distributed as a Python package (pip install aikisol) with a predict(seq) entry point. Contactvenkatesh@aikium.com. Supplementary informationSupplementary text, figures, and tables are available at Bioinformatics online.

bioinformatics↗

bioRxiv2025

Functional Category-Specific Intolerance Reflects Genic Function and Clinical Relevance

A key problem in genetics is associating variants with disease phenotypes. In aid of this, much progress has been made in quantifying the functional impact of individual variants on the gene product it codes for. However, the intolerance of the sequence in which those variants are found to functional variation is also a key determinant of whether a deleterious variant is pathogenic or not. Previous approaches to estimating genic intolerance have combined functional variant types, i.e., missense, loss-of-function, etc., or restricted analyses to only one type, i.e., pLI, missense-Z etc. Here we take a different approach and jointly model patterns of intolerance across multiple functional variant types. We refer to this approach as CATMINT. We show that CATMINT is competitive with previous gene level intolerance metrics in predicting disease relevant genes, with CATMINT ranking among the top performing scores across differing types of genes. However, perhaps more exciting is that CATMINT enables variant category specific intolerance estimation, revealing distinct functional profiles across genes/gene families. Analysis of ClinVar data shows that CATMINT intolerance patterns in disease genes recapitulate patterns of pathogenic variants within those genes, supporting the utility of category-specific intolerance in clinical variant interpretation. Further, we use the statistical framework utilized by CATMINT to conduct power analyses, allowing us to classify genes according to the power those genes have to detect intolerance. This allows us, for example, to identify genes that are underpowered and undetected, but may nevertheless be highly intolerant. Together, these results define a framework for understanding how selective pressures shape gene-specific sensitivity to different classes of mutation, improving the resolution of variant interpretation and gene prioritization in clinical and functional genomics.

evolutionary biology↗

bioRxiv2019

Protein Quality Control is a Risk Factor and Therapeutic Target in Toxin-Induced Biliary Atresia

BACKGROUND and AIMS Extra-hepatic biliary atresia (BA) is a pediatric liver disease with no approved medical therapy. Recent studies using human samples and experimental modeling suggest that glutathione redox metabolism and heterogeneity play a role in disease pathogenesis. We sought to dissect the mechanistic basis of liver redox variation and explore how other stress responses affect cholangiocyte injury in BA.METHODS We performed quantitative in situ hepatic glutathione redox mapping in zebrafish larvae carrying targeted mutations in glutathione metabolism genes and correlated these findings with sensitivity to the plant-derived BA-linked toxin biliatresone. We also determined whether genetic disruption of HSP90 protein quality control pathway genes implicated in human BA altered biliatresone toxicity in zebrafish and human cholangiocytes. An in vivo screen of a known drug library was performed to identify novel modifiers of cholangiocyte injury in the zebrafish experimental BA model with subsequent validation.RESULTS Glutathione metabolism gene mutations caused regionally distinct changes in the redox potential of cholangiocytes that differentially sensitized them to biliatresone. Disruption of human BA-implicated HSP90 pathway genes sensitized zebrafish and human cholangiocytes to biliatresone-induced injury independent of glutathione. Phosphodiesterase-5 inhibitors (PDE5i) and other cGMP signaling activators worked synergistically with the glutathione precursor N- acetylcysteine (NAC) in preventing biliatresone-induced injury in zebrafish and human cholangiocytes. PDE5i enhanced proteasomal degradation and required intact HSP90 chaperone.CONCLUSION Regional variation in glutathione metabolism underlies sensitivity to the biliary toxin biliatresone, and mirrors recently reported BA risk stratification linked to glutathione metabolism gene expression. Human BA can be causatively linked to genetic modulation of protein quality control. Combined treatment with NAC and cGMP signaling enhancers warrants further investigation as therapy for BA.Background and Context Biliary atresia (BA) is an obstructive fibrosing cholangiopathy that is the leading indication for liver transplantation in the pediatric population. There are no known treatments to prevent progressive liver injury after surgical restoration of bile flow.New Findings The authors identify factors that affect susceptibility of cholangiocytes to oxidative injury using a toxin-induced BA model. This information is used to validate genetic risk factors for human BA and identified PDE5i as a potential treatment for biliary atresia, either on its own or in combination with the anti-oxidant N-acetyl-cysteine.Limitations The work done in animal and cell culture models needs further study in human tissue-derived models and a larger cohort of BA patients.Impact The findings from this study provide a rationale for identifying new genetic risk factors that predispose to BA and for an interventional study to prevent progressive liver injury in this enigmatic disease.Short Summary This study uses zebrafish and human cell culture models to identify novel injury mechanisms, genetic risk factors and new therapies for the pediatric liver disease biliary atresia.Competing Interest StatementThe authors have declared no competing interest.Abbreviations17-AAG7-N-allylamino-17-demethoxygeldanamycin;BAbiliary atresia;bilbiliatresone;8-Br-cGMP8-Bromoguanosine 3’,5’-cyclic monophosphate;EHCextrahepatic cholangiocytes;Gclglutamate cysteine ligase;GGAgeranylgeranyl acetate;gsrglutathione reductase;GSHreduced glutathione;GSSGoxidized glutathione;IHCintrahepatic cholangiocytes;NACN-acetylcysteine;PDE5iPhosphodiesterase-5 inhibitors;PQCprotein quality control;WTwild-typeView Full Text

pathology↗