Biology subjects

Raychowdhury, R.

Publications and source records attributed to Raychowdhury, R..

4 recordsLinked to original sources

bioRxiv2025

A population-scale atlas of blood and tissue in lupus nephritis

One Sentence SummaryA single-cell atlas of paired blood and tissue samples from Lupus Nephritis patients and healthy controls identified stromal and immune populations within renal tissue, including the scar-associated macrophage populations, which correlate with and may drive renal disease activity. Lupus nephritis (LN), a severe manifestation of Systemic Lupus Erythematosus (SLE), is a heterogeneous disease driven by diverse immune and tissue cell types. We obtained 538K single-cell and 140K single-nuclear profiles from kidney biopsies of 155 LN patients and 30 pre-implantation transplant biopsy controls, along with 325K single-cell blood profiles overlapping many of these patients. We identified key tissue cell types and cell states, and immune cell states; we were able to determine cell states that were tissue specific, and those that were present in the blood. We observed that LN pathological features are significantly associated with cell states using differential gene expression and Covarying Neighborhood Analysis (CNA). These analyses revealed broad changes in cell states associated with irreversible chronic tissue damage. After controlling for the effects of ongoing tissue damage, we observed that expansion of key glomerular and Scar Associated Macrophages (SAMs) populations tracked with increasing inflammatory disease activity. SAMs appear to drive LN fibrosis and, in active disease, infiltrate the glomeruli more than other myeloid cells. These observations strongly support that therapeutic targeting of myeloid populations may offer an as-of-yet unproven strategy to prevent renal inflammation and ongoing kidney damage in LN.

molecular biology↗

bioRxiv2023

DSMBind: SE(3) denoising score matching for unsupervised binding energy prediction and nanobody design

Modeling the binding between proteins and other molecules is pivotal to drug discovery. Geometric deep learning is a promising paradigm for protein-ligand/protein-protein binding energy prediction, but its accuracy is limited by the size of training data as high-throughput binding assays are expensive. Herein, we propose an unsupervised binding energy prediction framework, named DSMBind, which does not need experimental binding data for training. DSMBind is an energy-based model that estimates the likelihood of a protein complex via SE(3) denoising score matching (DSM). This objective, applied at both backbone and side-chain levels, builds on a novel equivariant rotation prediction network derived from Eulers Rotation Equations. We find that the learned log-likelihood of protein complexes is highly correlated with experimental binding energy across multiple benchmarks, even matching the performance of supervised models trained on experimental data. We further demonstrate DSMBinds zero-shot binder design capability through a PD-L1 nanobody design task, where we randomize all three complementarity-determining regions (CDRs) and select the best CDR sequences based on DSMBind score. We experimentally tested the designed nanobodies with ELISA binding assay and successfully discovered a novel PD-L1 binder. In summary, DSMBind offers a versatile framework for binding energy prediction and binder design. Our code is publicly available at github.com/wengong-jin/DSMBind.

bioinformatics↗

bioRxiv2023

Systematically characterizing the roles of E3-ligase family members in inflammatory responses with massively parallel Perturb-seq

E3 ligases regulate key processes, but many of their roles remain unknown. Using Perturb-seq, we interrogated the function of 1,130 E3 ligases, partners and substrates in the inflammatory response in primary dendritic cells (DCs). Dozens impacted the balance of DC1, DC2, migratory DC and macrophage states and a gradient of DC maturation. Family members grouped into co-functional modules that were enriched for physical interactions and impacted specific programs through substrate transcription factors. E3s and their adaptors co-regulated the same processes, but partnered with different substrate recognition adaptors to impact distinct aspects of the DC life cycle. Genetic interactions were more prevalent within than between modules, and a deep learning model, com{beta}VAE, predicts the outcome of new combinations by leveraging modularity. The E3 regulatory network was associated with heritable variation and aberrant gene expression in immune cells in human inflammatory diseases. Our study provides a general approach to dissect gene function.

genomics↗

bioRxiv2017

Genetic analysis of isoform usage in the human anti-viral response reveals influenza-specific regulation of ERAP2 transcripts under balancing selection

While the impact of common genetic variants on gene expression response to cellular stimuli has been analyzed in depth, less is known about how stimulation modulates the genetic control of isoform usage. Analyzing RNA-seq profiles of monocyte-derived dendritic cells from 243 individuals, we uncovered thousands of unannotated isoforms synthesized in response to viral infection and stimulation with type I interferon. We identified more than a thousand single nucleotide polymorphisms associated with isoform usage (isoQTLs), > 40% of which are independent of expression QTLs for the same gene. Compared to eQTLs, isoQTLs are enriched for splice sites and untranslated regions, and depleted of sequences upstream of annotated transcription start sites. Both eQTLs and isoQTLs in stimulated cells explain a significant proportion of the disease heritability attributed to common genetic variants. At the IRF7 locus, we found alternative promoter usage in response to influenza as a possible mechanism by which DNA variants previously associated with immune-related disorders mediate disease risk. At the ERAP2 locus, we shed light on the function of the major haplotype that has been maintained under long-term balancing selection. At baseline and following type 1 interferon stimulation, the major haplotype is associated with absence of ERAP2 expression while the minor haplotype, known to increase Crohns disease risk, is associated with high ERAP2 expression. Surprisingly, in response to influenza infection, the major haplotype results in the expression of two uncharacterized, alternatively transcribed, spliced and translated short isoforms. Thus, genetic variants at a single locus could modulate independent gene regulatory processes in the innate immune response, and in the case of ERAP2, may confer a historical fitness advantage in response to virus.

genomics↗