Biology subjects

D'Costa, S.

Publications and source records attributed to D'Costa, S..

11 recordsLinked to original sources

bioRxiv2026

Mapping the response of primary human chondrocytes to an osteoarthritis-relevant stimulus by single-cell RNA sequencing

Objective: To determine how fibronectin fragment (Fn-f), a matrikine that induces an osteoarthritis (OA)-like phenotype, reshapes chondrocyte states and transcriptional programs at single-cell resolution. Design: Primary human ankle chondrocytes from two cadaveric donors without OA were treated with PBS or purified recombinant Fn-f for 18 hours and profiled by single-cell RNA sequencing. Transcriptional states were characterized by marker genes and functional enrichment, compared with classifications used for OA chondrocytes, and evaluated for Fn-f-dependent changes in abundance and transcriptional programs. Results: Five transcriptionally distinct populations were identified with features that matched previous classifications of effector, inflammatory, pre-hypertrophic/fibrochondrocyte, reparative, and homeostatic chondrocytes. Fn-f markedly redistributed cells among these states, enriching inflammatory chondrocytes while reducing effector and reparative populations. Within transcriptional states, Fn-f differentially altered matrix/cartilage, inflammatory, and stress/immediate-early programs. These responses did not uniformly correspond to assigned subtype identities, demonstrating that transcriptional programs can be dynamically deployed across chondrocyte states. Conclusions: Controlled perturbations of healthy chondrocytes complement observational OA atlases by resolving stimulus-dependent changes in chondrocyte state abundance and transcriptional programs. Discordance between subtype annotations and dynamic functional programs further highlights the need for harmonized definitions of chondrocytes across phenotypic states.

genetics↗

bioRxiv2026

Human hip osteoarthritis-associated Chadl variant induces intervertebral disc degeneration in mice

Chondroadherin-like (CHADL), a small leucine-rich proteoglycan, plays a role in ECM assembly and chondrocyte differentiation. CHADL has been implicated in osteoarthritis (OA) due to the discovery of a rare frameshift variant (rs532464664) that confers one of the highest genetic risks for hip OA reported to date. In this study, we characterized the skeletal phenotypes of two mouse models of Chadl loss-of-function, a global null and an 8bp insertion that mimics the human frameshift variant. Surprisingly, while there was a slight increase in knee OA at 12 months, there were no genotype-based differences in knee or hip OA in aged mice. Interestingly, histological assessment revealed phenotypic changes in the intervertebral discs of mutant mice, along with increased disc height index, suggesting altered motion-segment biomechanics. Polarized imaging showed dysregulated collagen turnover in the annulus fibrosus (AF), evidenced by changes in the proportions of thin and intermediate fibers. There was decreased abundance of the nucleus pulposus (NP) marker CA3 and decreased staining for ECM proteins in the AF of mutants. CHADL loss affected vertebral trabecular architecture, cortical thickness, and mineral density. This study highlights an unrecognized role of CHADL in fine-tuning ECM homeostasis and health of the intervertebral disc and vertebral bone.

cell biology↗

bioRxiv2026

CRISPR-mediated engineering of bovine satellite cells for Alpha-Gal Syndrome-compatible cultivated meat

Alpha-gal Syndrome (AGS) is a potentially life-threatening allergy caused by an IgE-mediated immune response to galactose--1,3-galactose (alpha-gal), a carbohydrate epitope present in most mammalian meats. Currently, strict avoidance of mammalian meat remains the primary management strategy for affected individuals, and alpha-gal-free beef is not commercially available. Here, we leverage cultivated meat as a biotechnology plat-form to address this unmet clinical need by engineering alpha-gal-free bovine muscle cells. Using CRISPR/Cas9 genome editing, we disrupted GGTA1, the gene encoding 1,3-galactosyltransferase, in immortalized bovine satellite cells (iBSCs). High-efficiency editing produced clonal GGTA1 knockout iBSCs harboring a homozygous frameshift mutation. Flow cytometry and immunofluorescence confirmed loss of the alpha-gal epitope, while bulk RNA-seq indicated minimal disruption of global gene expression and preserved myogenic differentiation capacity. Importantly, lysates from GGTA1 knockout iBSCs elicited substantially reduced basophil activation in assays using plasma from a patient with AGS, indicating reduced basophil activation consistent with reduced allergenic potential. Together, these findings establish a proof of concept for engineering AGS-compatible cultivated meat and demonstrate the potential of cultivated meat technologies to address human health challenges. HIGHLIGHTS{circ} CRISPR/Cas9-mediated disruption of GGTA1 eliminated alpha-gal from bovine satellite cells {circ}GGTA1 knockout cells retained myogenic identity and differentiation capacity {circ}GGTA1 knockout reduced basophil activation in an alpha-gal syndrome immune assay {circ}Genome-edited bovine cells provide a proof of concept for AGS-compatible cultivated meat

bioengineering↗

bioRxiv2025

Topological Analysis of the Human Lymph Node Reticular Network Predicts Outcome in Breast Cancer

Axillary lymph nodes (ALN) initiate local immune responses in breast cancer (BC) but how and when ALN become dysfunctional, facilitating metastasis, is unclear. We use unbiased computational approaches to quantify features of ALN stromal architecture. We identify PDGFR{beta} as a robust, immunomarker for human fibroblastic reticular cells (FRC) and use it to quantify how FRC network topology changes during BC progression and after treatment. ALN (n = 331) from 179 BC patients and 23 benign reactive controls were assessed for FRC network metrics, including lacunarity and branchpoints, alongside de-identified clinico-pathological data. We find in node-negative, triple-negative BC, neoadjuvant treatment induced denser FRC networks which correlated with improved survival. Conversely, denser FRC networks in node-positive patients correlated with worsened survival, regardless of BC subtype or treatment. Further, increased FRC alignment within metastases improved survival. We show that FRC network topology predicts prognosis in BC, providing a new avenue for mechanistic, translational research.

pathology↗

bioRxiv2024

Response splicing QTLs in primary human chondrocytes identifies putative osteoarthritis risk genes

Osteoarthritis affects millions worldwide, yet effective treatments remain elusive due to poorly understood molecular mechanisms. While genome-wide association studies (GWAS) have identified over 100 OA-associated loci, identifying the genes impacted at each locus remains challenging. Several studies have mapped expression quantitative trait loci (eQTL) in chondrocytes and colocalized them with OA GWAS variants to identify putative OA risk genes; however, the degree to which genetic variants influence OA risk via alternative splicing has not been explored. We investigated the role of alternative splicing in OA pathogenesis using RNA-seq data from 101 human chondrocyte samples treated with PBS (control) or fibronectin fragment (FN-f), an OA trigger. We identified 590 differentially spliced genes between conditions, with FN-f inducing splicing events similar to those in primary OA tissue. We used CRISPR/Cas9 to mimic an SNRNP70 splicing event observed in OA and FN-f-treated chondrocytes and found that it induced an OA-like expression pattern. Integration with genotyping data revealed 7,188 splicing quantitative trait loci (sQTL) affecting 3,056 genes. While many sQTLs were shared, we identified 738 and 343 condition-specific sQTLs for control and FN-f, respectively. We identified 15 RNA binding proteins whose binding sites were enriched at sQTL splice junctions and found that expression of those RNA binding proteins correlated with exon inclusion. Colocalization with OA GWAS identified 6 putative risk genes, including a novel candidate, PBRM1. Our study highlights the significant impact of alternative splicing in OA and provides potential therapeutic targets for future research.

genetics↗

bioRxiv2024

Response eQTLs, chromatin accessibility, and 3D chromatin structure in chondrocytes provide mechanistic insight into osteoarthritis risk

Osteoarthritis (OA) poses a significant healthcare burden with limited treatment options. While genome-wide association studies (GWAS) have identified over 100 OA-associated loci, translating these findings into therapeutic targets remains challenging. Integrating expression quantitative trait loci (eQTL), 3D chromatin structure, and other genomic approaches with OA GWAS data offers a promising approach to elucidate disease mechanisms; however, comprehensive eQTL maps in OA-relevant tissues and conditions remain scarce. We mapped gene expression, chromatin accessibility, and 3D chromatin structure in primary human articular chondrocytes in both resting and OA-mimicking conditions. We identified thousands of differentially expressed genes, including those associated with differences in sex and age. RNA-seq in chondrocytes from 101 donors across two conditions uncovered 3782 unique eGenes, including 420 that exhibited strong and significant condition-specific effects. Colocalization with OA GWAS signals revealed 13 putative OA risk genes, 10 of which have not been previously identified. Chromatin accessibility and 3D chromatin structure provided insights into the mechanisms and conditional specificity of these variants. Our findings shed light on OA pathogenesis and highlight potential targets for therapeutic development. Highlights{circ} Comprehensive analysis of sex- and age-related global gene expression in human chondrocytes revealed differences that correlate with osteoarthritis {circ}First response eQTLs in chondrocytes treated with an OA-related stimulus {circ}Deeply sequenced Hi-C in resting and activated chondrocytes helps connect OA risk variants to their putative causal genes {circ}Colocalization analysis reveals 13 (including 10 novel) putative OA risk genes

genetics↗

bioRxiv2024

Biophysics-based protein language models for protein engineering

Protein language models trained on evolutionary data have emerged as powerful tools for predictive problems involving protein sequence, structure, and function. However, these models overlook decades of research into biophysical factors governing protein function. We propose Mutational Effect Transfer Learning (METL), a protein language model framework that unites advanced machine learning and biophysical modeling. Using the METL framework, we pretrain transformer-based neural networks on biophysical simulation data to capture fundamental relationships between protein sequence, structure, and energetics. We finetune METL on experimental sequence-function data to harness these biophysical signals and apply them when predicting protein properties like thermostability, catalytic activity, and fluorescence. METL excels in challenging protein engineering tasks like generalizing from small training sets and position extrapolation, although existing methods that train on evolutionary signals remain powerful for many types of experimental assays. We demonstrate METLs ability to design functional green fluorescent protein variants when trained on only 64 examples, showcasing the potential of biophysics-based protein language models for protein engineering.

bioinformatics↗

bioRxiv2023

A survey of Rare Disease awareness among healthcare professionals and researchers in India

Rare diseases (RDs) are diseases that occur infrequently and affect a small fraction of the population. Although these diseases individually affect small number of people, together they affect 400 million people globally at any given time. In India, where resources are scarce, healthcare infrastructure and policy framework are focused on mitigating diseases that affect many people. Further, the level of RD awareness among healthcare professionals, researchers, and general public is considerably low. As a result, many cases of RDs remain unreported, undiagnosed, and untreated. To frame policies regarding RDs, it is crucial to understand the current level of RD awareness among healthcare professional and researchers, as they are key stakeholders in diagnosis, treatment, policy making, and drug development. We conducted an exploratory survey to understand the current level of RD awareness among healthcare professionals and researchers based on identification of an RD, time for diagnosis, treatment options, and relationship with family history and geographic location. We noted that our respondents have considerably low level of RD awareness. They correctly identified the importance of family history but failed to realize the association with geographic location. After presenting the survey findings, we have made recommendation to improve RD awareness in India. Our findings will be helpful to design awareness campaigns and frame relevant policies.

scientific communication and education↗

bioRxiv2022

Inferring protein fitness landscapes from laboratory evolution experiments

Directed laboratory evolution applies iterative rounds of mutation and selection to explore the protein fitness landscape and provides rich information regarding the underlying relationships between protein sequence, structure, and function. Laboratory evolution data consist of protein sequences sampled from evolving populations over multiple generations and this data type does not fit into established supervised and unsupervised machine learning approaches. We develop a statistical learning framework that models the evolutionary process and can infer the protein fitness landscape from multiple snapshots along an evolutionary trajectory. We apply our modeling approach to dihydrofolate reductase (DHFR) laboratory evolution data and the resulting landscape parameters capture important aspects of DHFR structure and function. We use the resulting model to understand the structure of the fitness landscape and find numerous examples of epistasis but an overall global peak that is evolutionarily accessible from most starting sequences. Finally, we use the model to perform an in silico extrapolation of the DHFR laboratory evolution trajectory and computationally design proteins from future evolutionary rounds.

bioinformatics↗

bioRxiv2022

3D Chromatin Structure in Chondrocytes Identifies Putative Osteoarthritis Risk Genes

Genome-wide association studies (GWAS) have identified over 100 loci associated with osteoarthrtis (OA) risk, but the majority of OA risk variants are non-coding, making it difficult to identify the impacted genes for further study and therapeutic development. To address this need, we used a multi-omic approach and genome editing to identify and functionally characterize potential OA risk genes. Computational analysis of GWAS and ChIP-seq data revealed that chondrocyte regulatory loci are enriched for OA risk variants. We constructed a chondrocyte specific regulatory network by mapping 3D chromatin structure and active enhancers in human chondrocytes. We then intersected these data with our previously collected RNA-seq dataset of chondrocytes responding to fibronectin fragment (FN-f), a known OA trigger. Integration of the three genomic datasets with recently reported OA GWAS variants revealed a refined set of putative causal OA variants and their potential target genes. One of the novel putative target genes identified was SOCS2, which was connected to a putative causal variant by a 170 Kb loop and is differentially regulated in response to FN-f. CRISPR-Cas9-mediated deletion of SOCS2 in primary human chondrocytes from three independent donors led to heightened expression of inflammatory markers after FN-f treatment. These data suggest that SOCS2 plays a role in resolving inflammation in response to cartilage matrix damage and provides a possible mechanistic explanation for its influence on OA risk. In total, we identified 56 unique putative OA risk genes for further research and potential therapeutic development.

genomics↗

bioRxiv2019

Engineered cartilage from human chondrocytes with homozygous knockout of cell cycle inhibitor p21

Risk factors for the development of osteoarthritis (OA) include genetic background and focal cartilage injury. The search for disease-modifying OA therapies would benefit from a more comprehensive knowledge of the genetic variants that contribute to chondrocyte dysfunction and the barriers to cartilage regeneration. One goal of this study was to establish a system for producing engineered cartilage tissue from genetically-defined primary human chondrocytes through genome editing and single-cell expansion. This process was utilized to investigate the functional effect of bi-allelic knockout of the cell cycle inhibitor p21. The use of ribonucleoprotein (RNP) CRISPR/Cas9 complexes targeting two sites in the coding region of p21 resulted in a high frequency (16%) of colonies with homozygous p21 knockout. Chondrogenic pellet cultures from expanded chondrocytes with complete loss of p21 produced more glycosaminoglycans (GAG) and maintained a higher cell number. Single-cell derived colonies retained the potential for robust matrix production after expansion, allowing for analysis of colony variability from the same population of targeted cells. The effect of enhanced cartilage matrix production in p21 knockout chondrocytes persisted when matrix production from individual colonies was analyzed. Chondrocytes had lower levels of p21 protein with further expansion, and the difference in GAG production with p21 knockout was strongest at early passages. These results support previous findings that implicate p21 as a barrier to cartilage matrix production and regenerative capacity. Further, this work establishes the use of genome-edited human chondrocytes as a promising approach for engineered tissue models containing user-defined gene knockouts and other genetic variants for investigation of OA pathogenesis.

bioengineering↗