Biology subjects

Ravichandran, P.

Publications and source records attributed to Ravichandran, P..

5 recordsLinked to original sources

bioRxiv2025

Spatiomolecular mapping reveals anatomical organization of heterogeneous cell types in the human nucleus accumbens

The nucleus accumbens (NAc) is a key component of the mesolimbic dopamine system that critically regulates many behaviors related to reward and motivation. The NAc is implicated in several neuropsychiatric disorders, including major depressive disorder, schizophrenia, and substance use disorders. Rodent studies have identified spatial organization of heterogeneous medium spiny neuron (MSN) subtypes across the NAc core and shell, but the extent to which this cellular diversity and spatial organization is conserved in the human brain remains unclear. Here, we generated a spatiomolecular atlas of NAc cell types and spatial domains by integrating spatial transcriptomics and single-nucleus RNA sequencing data from postmortem NAc tissue from 10 neurotypical adult donors. We identified 20 transcriptionally unique cell populations and 8 spatial domains, including specialized D1 islands composed of distinct dopamine receptor 1 (DRD1) MSN subtypes, which were enriched for OPRM1. In contrast to a discrete core vs. shell division, we observed continuous spatial gradients of gene expression across MSN domains, suggesting a more complex organization of DRD1 and DRD2 MSNs. Cross-species comparisons demonstrated conservation of MSN subtypes and spatial features between human, rodent, and nonhuman primate NAc. Genetic enrichment analysis with stratified linkage disequilibrium score regression revealed specific spatial domains associated with risk for psychiatric and addiction-related traits. To investigate this further, we spatially mapped ligand-receptor interactions involving neuropsychiatric risk genes. Finally, we leveraged existing rodent NAc data to identify drug-responsive transcriptional programs and predict their spatial distribution in the human NAc. Collectively, we provide a spatiomolecular framework for understanding the human NAc and its relevance to neuropsychiatric disease.

neuroscience↗

bioRxiv2024

Integrating gene expression and imaging data across Visium capture areas with visiumStitched

BackgroundVisium is a widely-used spatially-resolved transcriptomics assay available from 10x Genomics. Standard Visium capture areas (6.5mm by 6.5mm) limit the survey of larger tissue structures, but combining overlapping images and associated gene expression data allow for more complex study designs. Current software can handle nested or partial image overlaps, but is designed for merging up to two capture areas, and cannot account for some technical scenarios related to capture area alignment. ResultsWe generated Visium data from a postmortem human tissue sample such that two capture areas were partially overlapping and a third one was adjacent. We developed the R/Bioconductor package visiumStitched, which facilitates stitching the images together with Fiji (ImageJ), and constructing SpatialExperiment R objects with the stitched images and gene expression data. visiumStitched constructs an artificial hexagonal array grid which allows seamless downstream analyses such as spatially-aware clustering without discarding data from overlapping spots. Data stitched with visiumStitched can then be interactively visualized with spatialLIBD. ConclusionsvisiumStitched provides a simple, but flexible framework to handle various multi-capture area study design scenarios. Specifically, it resolves a data processing step without disrupting analysis workflows and without discarding data from overlapping spots. visiumStiched relies on affine transformations by Fiji, which have limitations and are less accurate when aligning against an atlas or other situations. visiumStiched provides an easy-to-use solution which expands possibilities for designing multi-capture area study designs.

genomics↗

bioRxiv2024

Aggregation of recount3 RNA-seq data improves the inference of consensus and tissue-specific gene co-expression networks.

BackgroundGene co-expression networks (GCNs) describe relationships among expressed genes key to maintaining cellular identity and homeostasis. However, the small sample size of typical RNA-seq experiments which is several orders of magnitude fewer than the number of genes is too low to infer GCNs reliably. recount3, a publicly available dataset comprised of 316,443 uniformly processed human RNA-seq samples, provides an opportunity to improve power for accurate network reconstruction and obtain biological insight from the resulting networks. ResultsWe compared alternate aggregation strategies to identify an optimal workflow for GCN inference by data aggregation and inferred three consensus networks: a universal network, a non-cancer network, and a cancer network in addition to 27 tissue context-specific networks. Central network genes from our consensus networks were enriched for evolutionarily constrained genes and ubiquitous biological pathways, whereas central context-specific network genes included tissue-specific transcription factors and factorization based on the hubs led to clustering of related tissue contexts. We discovered that annotations corresponding to context-specific networks inferred from aggregated data were enriched for trait heritability beyond known functional genomic annotations and were significantly more enriched when we aggregated over a larger number of samples. ConclusionThis study outlines best practices for network GCN inference and evaluation by data aggregation. We recommend estimating and regressing confounders in each data set before aggregation and prioritizing large sample size studies for GCN reconstruction. Increased statistical power in inferring context-specific networks enabled the derivation of variant annotations that were enriched for concordant trait heritability independent of functional genomic annotations that are context-agnostic. While we observed strictly increasing held-out log-likelihood with data aggregation, we noted diminishing marginal improvements. Future directions aimed at alternate methods for estimating confounders and integrating orthogonal information from modalities such as Hi-C and ChIP-seq can further improve GCN inference.

genomics↗

bioRxiv2023

Integrated single cell and unsupervised spatial transcriptomic analysis defines molecular anatomy of the human dorsolateral prefrontal cortex

The molecular organization of the human neocortex has been historically studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally-defined spatial domains that move beyond classic cytoarchitecture. Here we used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex (DLPFC). Integration with paired single nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we map the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains. Finally, we provide resources for the scientific community to explore these integrated spatial and single cell datasets at research.libd.org/spatialDLPFC/. SummaryGeneration of a molecular neuroanatomical map of the human prefrontal cortex reveals novel spatial domains and cell-cell interactions relevant for psychiatric disease.

neuroscience↗

bioRxiv2021

Dual avatars of E. coli grxB encoded Glutaredoxin 2 perform ascorbate recycling and ion channel activities

Glutaredoxins (Grxs) are single-domain redox enzymes of the thioredoxin superfamily, and primarily function as glutathione (GSH) dependent disulphide reductases. Whereas, the E. coli Glutaredoxin 2 (EcGrx2) encoded by grxB has two conserved GST-fold domains, it still lacks a classical Grx-like functions. In this study, we show for the first time, that EcGrx2 exists in both soluble and membrane integrated forms. The soluble form associates with a previously unidentified GSH dependent dehydroascrobate (DHA) reductase, and the membrane integrated form possesses ion channel activities. Using enzyme kinetic data and structural data we unequivocally demonstrate that EcGrx2 recycles ascorbate (AsA) from DHA. This ability to recycle AsA is inhibited by Zinc (Zn2+). We also show that both wildtype and the E. coli grxB deletion mutant can be rescued from H2O2-induced oxidative stress using ascorbate as an antioxidant, which otherwise is only known as a carbon source in bacteria. Moreover, the grxB- mutant is susceptible to intracellular killing by ROS producing macrophages. We further discovered that EcGrx2 integrates into the native E. coli membrane and show that the purified soluble protein readily inserts into artificial lipid bilayer membrane and conducts ions in vitro. Our data demonstrates a highly conserved functional similarity among EcGrx2-orthologs and highlights that the utilization and subsequent recycling of ascorbate as an antioxidant by grxB harbouring gram-negative bacteria, including human pathogens, may provide a survival advantage under hostile oxidative environments.

biochemistry↗