Biology subjects

Venkataraman, A.

Publications and source records attributed to Venkataraman, A..

18 recordsLinked to original sources

bioRxiv2026

A Neuroendocrine Circuit That Suppresses Excretion and Pelvic Pain During Activity

Mate-seeking during peak sexual receptivity is tightly coupled with exploratory movement, a process made more efficient by transient suppression of excretion. Here, we define a functional hypothalamic-hindbrain circuit in mice that promotes locomotion while eliminating urination and defecation for hours. Chemogenetic stimulation of excitatory estrogen-melanocortin-responsive MC4R+ neurons in the ventrolateral ventromedial hypothalamus (VMHvl) effectively silences bladder and colonic visceral reflexes, even at noxious distension pressures, underscoring the potency of this anti-excretion circuit. Pelvic sensations and excretion are restored only after ablating inhibitory GABAergic neurons in the Barringtons nucleus/locus coeruleus (BAR/LC) hindbrain region or after antagonizing endogenous endorphin signaling. Our study illustrates how a hormone-responsive brain node prioritizes movement over excretion and blunts pelvic discomfort, thereby optimizing an essential voluntary behavior for evolutionary fitness.

physiology↗

bioRxiv2026

Morphomechanically-Informed Spatial Curvature Sequencing in Prostate Cancer

Morphological changes in prostate glands, assessed by Gleason grading, remain the gold standard for diagnosing prostate cancer, yet molecular biomarkers associated with gland shape are not well understood. Here, we introduce CurvSeq, a mechanomorphology-informed framework for spatial sequencing data, and CurvSee, its complementary version for proteomic and imaging datasets. These methods integrate gland boundary curvature, pocket architecture, microenvironmental composition, and molecular profiles to study morphomechanical relationships in prostate adenocarcinoma. Using five independent spatial transcriptomic and multiplexed imaging datasets, we segmented individual prostate glands, extracted gland contours, quantified local curvature and pocket-like concavities, and projected these features onto spatially resolved gene and protein measurements. In Xenium data, CurvSeq distinguished benign and GG1 glands, identifying cancer-associated genes such as PCA3 and AMACR in GG1 glands and basal, basement membrane, and mechanotransduction-associated programs in benign glands. In Visium data, a diffusion-based morphomechanical score ordered benign glands by area, circularity, pocket number, smooth muscle abundance, immune-cell proximity, and remodeling-associated genes including MMP7. In GG4 glands, CurvSeq identified neuroendocrine-like boundary regions associated with MMP7 expression, COL1A1-rich adjacent stroma, and immune-cell accumulation. Finally, CurvSee extended this framework to multiplexed protein imaging, where combined morphology and protein-expression features distinguished Gleason-associated gland states. Together, CurvSeq and CurvSee provide a quantitative framework for linking gland architecture, local microenvironment, and molecular state, showing that prostate gland morphology can be integrated with spatial omics to identify morphomechanical niches associated with cancer progression.

systems biology↗

bioRxiv2025

A Cellular Basis for Heightened Gut Sensitivity in Females

Visceral pain disorders, such as irritable bowel syndrome, exhibit a marked female prevalence. Enhanced signaling between enterochromaffin (EC) cells in the gut epithelium and mucosal sensory nerve fibers likely contributes to this sex bias. Here, we identify a novel estrogen-responsive paracrine pathway in which two enteroendocrine cell types, PYY-expressing L-cells and serotonergic EC cells, communicate to increase gut sensitivity in females. We demonstrate that ER estrogen signaling upregulates the bacterial metabolite SCFA receptor Olfr78 on colonic L-cells, increasing PYY release and their sensitivity to acetate. Elevated PYY acts on neighboring EC cells via NPY1R, thereby enhancing serotonin release and gut pain. We propose that hormonal fluctuations, in conjunction with internal (stress) or environmental (diet) factors, amplify this local estrogen-responsive colonic circuit, resulting in maladaptive gut sensitivity.

physiology↗

bioRxiv2024

Super Resolved Single-Cell Spatial Metabolomics from Multimodal Mass Spectrometry Imaging guided by Imaging Mass Cytometry

Mass spectrometry imaging (MSI) is a powerful technique for spatially resolved analysis of metabolites and other biomolecules within biological tissues. However, the inherent low spatial resolution of MSI often limits its ability to provide detailed cellular-level information. To address this limitation, we propose a guided super-resolution (GSR) approach that leverages high-resolution Imaging Mass Cytometry (IMC) images to enhance the spatial resolution of low-resolution MSI data. By using these detailed IMC images as guides, we improve the resolution of MSI images, creating high-resolution metabolite maps. This enhancement facilitates more precise analysis of cellular structures and tissue architectures, providing deeper insights into super-resolved spatial metabolomics at the single-cell level.

systems biology↗

bioRxiv2024

Strain concentration drives the anatomical distribution of injury in acute and chronic traumatic brain injury

Brain tissue injury caused by mild traumatic brain injury (mTBI) disproportionately concentrates in the midbrain, cerebellum, mesial temporal lobe, and the interface between cortex and white matter at sulcal depths 1-12. The bio-mechanical principles that explain why physical impacts to different parts of the skull translate to common foci of injury concentrated in specific brain structures are unknown. A general and longstanding idea, which has not to date been directly tested in humans, is that different brain regions are differentially susceptible to strain loading11,13-15. We use Magnetic Resonance Elastography (MRE) in healthy participants to develop whole-brain bio-mechanical vulnerability maps that independently define which regions of the brain exhibit disproportionate strain concentration. We then validate those vulnerability maps in a prospective cohort of mTBI patients, using diffusion MRI data collected at three cross-sectional timepoints after injury: acute, sub-acute, chronic. We show that regions that exhibit high strain, measured with MRE, are also the sites of greatest injury, as measured with diffusion MR in mTBI patients. This was the case in acute, subacute, and chronic subgroups of the mTBI cohort. Follow-on analyses decomposed the biomechanical cause of increased strain by showing it is caused jointly by disproportionately higher levels of energy arriving to high-strain structures, as well as the inability of high strain structures to effectively disperse that energy. These findings establish a causal mechanism that explains the anatomy of injury in mTBI based on in vivo rheological properties of the human brain.

neuroscience↗

bioRxiv2023

The impact of multiband and in-plane acceleration on white matter microstructure analysis

Accelerated imaging has been broadly adopted in diffusion MRI studies, yet little is known about its impacts. Acceleration can achieve higher spatial and q-space resolution in shorter time, reduce motion artifacts, and reduce patient burden. However, it leads to noise amplification, and its impacts in clinical cohorts are poorly understood. This study examined the impact of multiband (also called simultaneous multislice, or SMS) and in-plane acceleration (IPA, also called phase acceleration) in diffusion imaging in forty older adults differing in cognitive status. We evaluated a total of 400 scans from five acquisitions: no acceleration (S1P1); SMS=3 with no in-plane acceleration (S3P1); SMS=3 with IPA=2 (S3P2); S6P1; and S6P2. The number of diffusion directions and b-values was kept constant such that acquisition times varied from 21:28 to 3:56. We found that diffusion metrics were highly sensitive to acceleration factor, with a trend towards higher fractional anisotropy (FA) and lower orientation dispersion (OD) with acceleration. The differences between accelerated and unaccelerated acquisitions could be partly explained by the noise amplification (g-factor) and reduced motion. Intraclass correlations (ICCs) of FA and OD in white matter were excellent in both S1P1 and S3P1 (median >0.8), good but lower in S3P2 and S6P1 (medians around 0.70), and poor to fair in S6P2 (medians 0.46 and 0.57). In-plane acceleration decreased ICC, including areas of high susceptibility distortion. In a comparison of mild cognitive impairment versus healthy controls, acceleration tended to reduce group differences, particularly in the fornix, with greater costs in OD than FA. Our results provide guidance regarding the costs of acceleration (possible biases and reduced effect sizes) while also characterizing the benefits (reduced motion, good reliability at higher multiband with no in-plane).

bioengineering↗

bioRxiv2023

BEATRICE: Bayesian Fine-mapping from Summary Datausing Deep Variational Inference

We introduce a novel framework BEATRICE to identify putative causal variants from GWAS statistics. Identifying causal variants is challenging due to their sparsity and high correlation in the nearby regions. To account for these challenges, we rely on a hierarchical Bayesian model that imposes a binary concrete prior on the set of causal variants. We derive a variational algorithm for this fine-mapping problem by minimizing the KL divergence between an approximate density and the posterior probability distribution of the causal configurations. Correspondingly, we use a deep neural network as an inference machine to estimate the parameters of our proposal distribution. Our stochastic optimization procedure allows us to simultaneously sample from the space of causal configurations. We use these samples to compute the posterior inclusion probabilities and determine credible sets for each causal variant. We conduct a detailed simulation study to quantify the performance of our framework against two state-of-the-art baseline methods across different numbers of causal variants and different noise paradigms, as defined by the relative genetic contributions of causal and non-causal variants. We demonstrate that BEATRICE achieves uniformly better coverage with comparable power and set sizes, and that the performance gain increases with the number of causal variants. We also show the efficacy BEATRICE in finding causal variants from the GWAS study of Alzheimers disease. In comparison to the baselines, only BEATRICE can successfully find the APOE{epsilon} 2 allele, a commonly associated variant of Alzheimers. Thus, we show that BEATRICE is a valuable tool to identify causal variants from eQTL and GWAS summary statistics across complex diseases and traits.

genetics↗

bioRxiv2021

A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Neuroimaging Phenotypes of Disease

AO_SCPLOWBSTRACTC_SCPLOWWe propose a novel end-to-end framework for whole-brain and whole-genome imaging-genetics. Our genetics network uses hierarchical graph convolution and pooling operations to embed subject-level data onto a low-dimensional latent space. The hierarchical network implicitly tracks the convergence of genetic risk across well-established biological pathways, while an attention mechanism automatically identifies the salient edges of this network at the subject level. In parallel, our imaging network projects multimodal data onto a set of latent embeddings. For interpretability, we implement a Bayesian feature selection strategy to extract the discriminative imaging biomarkers; these feature weights are optimized alongside the other model parameters. We couple the imaging and genetic embeddings with a predictor network, to ensure that the learned representations are linked to phenotype. We evaluate our framework on a schizophrenia dataset that includes two functional MRI paradigms and gene scores derived from Single Nucleotide Polymorphism data. Using repeated 10-fold cross-validation, we show that our imaging-genetics fusion achieves the better classification performance than state-of-the-art baselines. In an exploratory analysis, we further show that the biomarkers identified by our model are reproducible and closely associated with deficits in schizophrenia.

bioinformatics↗

bioRxiv2020

COUNTEN an AI-driven tool for rapid, and objective structural analyses of the Enteric Nervous System

Healthy gastrointestinal functions require a healthy Enteric Nervous System (ENS). ENS health is often defined by the presence of normal ENS structure. However, we currently lack a comprehensive understanding of normal ENS structure as current methodologies of manual enumeration of neurons within tissue and ganglia can only parse limited tissue regions; and are prone to error, subjective bias, and peer-to-peer discordance. Thus, there is a need to craft objective methods and robust tools to capture and quantify enteric neurons over a large area of tissue and within multiple ganglia. Here, we report on the development of an AI-driven tool COUNTEN which parses HuC/D-immunolabeled adult murine myenteric ileal plexus tissues to enumerate and classify enteric neurons into ganglia in a rapid, robust, and objective manner. COUNTEN matches trained humans in identifying, enumerating and clustering myenteric neurons into ganglia but takes a fraction of the time, thus allowing for accurate and rapid analyses of a large tissue region. Using COUNTEN, we parsed thousands of myenteric neurons and clustered them in hundreds of myenteric ganglia to compute metrics that help define the normal structure of the adult murine ileal myenteric plexus. We have made COUNTEN freely and openly available to all researchers, to facilitate reproducible, robust, and objective measures of ENS structure across mouse models, experiments, and institutions.

neuroscience↗

bioRxiv2020

Differences in functional connectivity distribution after transcranial direct-current stimulation: a connectivity density point of view

In this manuscript we consider the problem of relating functional connectivity measurements viewed as statistical distributions to outcomes. We demonstrate the utility of using the distribution of connectivity on a study of resting state functional magnetic resonance imaging association with an intervention. Specifically, we consider 47 primary progressive aphasia (PPA) patients with various levels of language abilities. These patients were randomly assigned to two treatment arms, tDCS (transcranial direct-current stimulation and language therapy) vs sham (language therapy only), in a clinical trial. We propose a novel approach to analyze the effect of direct stimulation on functional connectivity. We estimate the density of correlations among the regions of interest (ROIs) and study the difference in the density post-intervention between treatment arms. We discover that it is the tail of the density, rather than the mean or lower order moments of the distribution, that demonstrates a significant impact in the classification. This approach has several benefits. Among them, it drastically reduces the number of multiple comparisons compared to edge-wise analysis. In addition, it allows for the investigation of the impact of functional connectivity on the outcomes where the connectivity is not geometrically localized.

neuroscience↗

bioRxiv2020

Detection of SARS-CoV-2 RNA by multiplex RT-qPCR

The current RT-qPCR assay recommended for SARS-CoV-2 testing in the United States requires analysis of three genomic targets per sample: two viral and one host. To simplify testing and reduce the volume of required reagents, we developed a multiplex RT-qPCR assay to detect SARS-CoV-2 in a single reaction. We used existing N1, N2, and RP primer and probe sets by the CDC, but substituted fluorophores to allow multiplexing of the assay. The cycle threshold (Ct) values of our multiplex RT-qPCR were comparable to those obtained by the singleplex assay adapted for research purposes. Low copies (>500 copies / reaction) of SARS-CoV-2 RNA were consistently detected by the multiplex RT-qPCR. Our novel multiplex RT-qPCR improves upon current singleplex diagnostics by saving reagents, costs, time and labor.

microbiology↗

bioRxiv2019

Mechanosensory stimulation via Nanchung expressing neurons can induce daytime sleep in Drosophila

The neurogenetic bases of sleep, a phenomenon considered crucial for well-being of organisms has recently been under investigation using the model organism Drosophila melanogaster. Although sleep is a state where sensory threshold for arousal is enhanced, it is known that certain kinds of repetitive sensory stimuli such as rocking, can in fact promote sleep in humans. Here we report that orbital motion aided mechanosensory stimulation promotes sleep in Drosophila, independent of the circadian clock, but controlled by the homeostatic system. Mechanosensory receptor nanchung (Nan) expressing neurons in the chordotonal organs mediate this sleep induction - flies where these neurons are either silenced or ablated display significantly reduced sleep induction upon mechanosensory stimulation. Transient activation of the Nan-expressing neurons also enhances sleep levels confirming the role of these neurons in sleep induction. Thus, we show for the first time that mechanosensory stimulation promotes sleep even in flies D. melanogaster and that it is mediated by proprioceptors.

neuroscience↗

bioRxiv2019

Antibody against envelope protein from human endogenous retrovirus activates neutrophils in systemic lupus erythematosus

Neutrophil activation and the formation of neutrophil extracellular trap (NET) are hallmarks of innate immune activation in systemic lupus erythematosus (SLE) and contribute to the systemic interferon signature. Here we report that the expression of an endogenous retrovirus (ERV) locus ERV-K102, encoding an envelope protein, was significantly elevated in SLE patient blood and was correlated with higher interferon status. Induction of ERV-K102 expression most strongly correlated with reduced transcript levels of epigenetic silencing factors. SLE IgG promoted phagocytosis of ERV-K102 envelope protein by neutrophils through immune complex formation. ERV immune complex phagocytosis resulted in subsequent NET formation consisting of DNA, neutrophil elastase, and citrullinated histone H3. Finally, analysis of anti-ERV-K102 IgG in SLE patients showed that IgG2 likely mediates this effect. Together, we identified an immunostimulatory ERV-K envelope protein elevated in SLE that may be a target of SLE IgG and able to promote neutrophil activation.\n\neTOC summaryUsing ERVmap, the authors determined that the expression of ERV-K102 locus was elevated in SLE patient blood and correlated with the interferon signature. The envelope protein encoded by this locus activates human neutrophils through immune complex formation with SLE IgG.

immunology↗

bioRxiv2018

ASCOT identifies key regulators of neuronal subtype-specific splicing

Public archives of next-generation sequencing data are growing exponentially, but the difficulty of marshaling this data has led to its underutilization by scientists. Here we present ASCOT, a resource that allows researchers to summarize, visualize, and query alternative splicing patterns in public RNA-Seq data. ASCOT enables rapid identification of splice-variants across tens of thousands of bulk and single-cell RNA-Seq datasets in human and mouse. To demonstrate the utility of ASCOT, we first focused on the nervous system and identified many alternative exons used only by a single neuronal subtype. We then leveraged datasets from the ENCODE and GTEx consortiums to study the unique splicing patterns of rod photoreceptors and found that PTBP1 knockdown combined with overexpression of MSI1 and PCBP2 activates rod-specific exons in HepG2 liver cancer cells. Furthermore, we observed that MSI1 targets intronic UAG motifs proximal to the 5 splice site and interacts synergistically with PTBP1 downregulation. Finally, we show that knockdown of MSI1 in the retina abolishes rod-specific splicing. This work demonstrates how large-scale analysis of public RNA-Seq datasets can yield key insights into cell type-specific control of RNA splicing and underscores the importance of considering both annotated and unannotated splicing events. ASCOT splicing and gene expression data tables, software, and interactive browser are available at http://ascot.cs.jhu.edu.

neuroscience↗

bioRxiv2018

Dynamics of human gut microbiota and short-chain fatty acids in response to dietary interventions with three fermentable fibers

Production of short-chain fatty acids (SCFAs), especially butyrate, in the gut microbiome is required for optimal health but is frequently limited by the lack of fermentable fiber in the diet. We attempted to increase butyrate production by supplementing the diets of 174 healthy young adults for two weeks with resistant starch from potatoes (RPS), resistant starch from maize (RMS), inulin from chicory root, or an accessible corn starch control. RPS resulted in the greatest increase in total SCFAs, including butyrate. Although the majority of microbiomes responded to RPS with increases in the relative abundance of bifidobacteria, those that responded with an increase in Ruminococcus bromii or Clostridium chartatabidum were more likely to yield higher butyrate concentrations, especially when their microbiota were replete with populations of the butyrate-producing species Eubacterium rectale. RMS and inulin induced different changes in fecal communities, but they did not generate significant increases in fecal butyrate levels.\n\nIMPORTANCEThese results reveal that not all fermentable fibers are equally capable of stimulating SCFA production, and they highlight the importance of the composition of an individuals microbiota in determining whether or not they respond to a specific dietary supplement. In particular, R. bromii or C. chartatabidum may be required for enhanced butyrate production in response to RS. Bifidobacteria, though proficient at degrading RS and inulin, may not contribute to the butyrogenic effect of those fermentable fibers in the short term.

microbiology↗

bioRxiv2018

Modulation of fear generalization by the zona incerta

Fear expressed towards threat-associated stimuli is an adaptive behavioral response. In contrast, the generalization of fear responses toward non-threatening cues is maladaptive and a debilitating dimension of trauma- and anxiety-related disorders. Expressing fear to appropriate stimuli and suppressing fear generalization requires integration of relevant sensory information and motor output. While thalamic and sub-thalamic brain regions play important roles in sensorimotor integration, very little is known about the contribution of these regions to the phenomenon of fear generalization. In this study, we sought to determine whether fear generalization could be modulated by the zona incerta (ZI), a sub-thalamic brain region that influences sensory discrimination, defensive responses, and retrieval of fear memories. To do so, we combined differential intensity-based auditory fear conditioning protocols in mice with C-FOS immunohistochemistry and DREADD-based manipulation of neuronal activity in the ZI. C-FOS immunohistochemistry revealed an inverse relationship between ZI activation and fear generalization - the ZI was less active in animals that generalized fear. In agreement with this relationship, chemogenetic inhibition of the ZI resulted in fear generalization, while chemogenetic activation of the ZI suppressed fear generalization. Furthermore, targeted stimulation of GABAergic cells in the ZI reduced fear generalization. To conclude, our data suggest that stimulation of the ZI could be used to treat fear generalization in the context of trauma- and anxiety-related disorders.

neuroscience↗

bioRxiv2017

Ldb1 and Rnf12-dependent regulation of Lhx2 controls the relative balance between neurogenesis and gliogenesis in retina.

Precise control of the relative ratio of retinal neurons and glia generated during development is essential for visual function. We show that Lhx2, which encodes a LIM-homeodomain transcription factor essential for specification and differentiation of retinal Muller glia, also plays a critical role in the development of retinal neurons. Overexpression of Lhx2, and its transcriptional coactivator Ldb1, triggers cell cycle exit and inhibits both Notch signaling and retinal gliogenesis. Lhx2/Ldb1 overexpression also induced the formation of wide-field amacrine cells (wfACs). In contrast Rnf12, which encodes a negative regulator of LDB1, is necessary for the initiation of retinal gliogenesis. We also show that LHX2 protein binds upstream of multiple neurogenic bHLH factors including Ascl1 and Neurog2, which are necessary for suppression of gliogenesis and wfAC formation respectively, and activates their expression. Finally, we demonstrate that the relative level of the LHX2-LDB1 complex in the retina decreases in tandem with the onset of gliogenesis. These findings show that control of Lhx2 function by Ldb1 and Rnf12 acts as a molecular mechanism underpinning the coordinated differentiation of neurons and Muller glia in postnatal retina.\n\nSignificance StatementThe molecular mechanisms that control the ratio neurons and glia that are generated by neuronal progenitors remain unclear. Here we show that Lhx2, a transcription factor essential for retinal gliogenesis, also controls development of retinal neurons. The Lhx2 coactivator Ldb1 promotes Lhx2-dependent neurogenesis, while the Lhx2 corepressor Rnf12 is necessary and sufficient for retinal gliogenesis. Furthermore, Lhx2 directly regulates expression of bHLH factors that promote neural development, which are necessary for Lhx2-dependent neurogenesis. Finally, we show that levels of the LHX2-LDB1 complex, which activates transcription, drop as gliogenesis begins. Dynamic regulation of Lhx2 activity by Ldb1 and Rnf12 thus controls the relative levels of retinal neurogenesis and gliogenesis, and may have similar functions elsewhere in the developing nervous system.

neuroscience↗

bioRxiv2017

A toolbox of immunoprecipitation-grade monoclonal antibodies against human transcription factors.

A key component to overcoming the reproducibility crisis in biomedical research is the development of readily available, rigorously validated and renewable protein affinity reagents. As part of the NIH Protein Capture Reagents Program (PCRP), we have generated a collection of 1406 highly validated, immunoprecipitation (IP) and/or immunoblotting (IB) grade, mouse monoclonal antibodies (mAbs) to 736 human transcription factors. We used HuProt human protein microarrays to identify mAbs that recognize their cognate targets with exceptional specificity. Using an integrated production and validation pipeline, we validated these mAbs in multiple experimental applications, and have distributed them to the Developmental Studies Hybridoma Bank (DSHB) and several commercial suppliers. This study allowed us to perform a meta-analysis that identified critical variables that contribute to the generation of high quality mAbs. We find that using full-length antigens for immunization, in combination with HuProt analysis, provides the highest overall success rates. The efficiencies built into this pipeline ensure substantial cost savings compared to current standard practices.

biochemistry↗