Biology subjects

Menon, R.

Publications and source records attributed to Menon, R..

48 records · Page 3Linked to original sources

bioRxiv2020

Septal HDAC1 facilitates long-lasting extinction of social fear in male mice

Social anxiety disorder (SAD) is primarily caused by traumatic social events and is characterized by intense fear and avoidance of socially enriched contexts. Formation of such intense social aversion requires learning of the association between trauma and originally neutral social stimuli. Acetylation of histones in response to learning is critical for long-term memory formation. Class I histone deacetylases (HDACs) have emerged as powerful negative regulators of long-term memory formation. However, the lack of clarity in isoform and spatial specificity in HDAC function exists. Utilizing the social fear conditioning (SFC) as well as cued fear conditioning (CFC) paradigms, we aimed to functionally characterize the role of class I HDACs, especially HDAC1, in the regulation of aversive memories in social versus non-social contexts. Using cFos expression as a marker of cellular activity, we revealed that the lateral septum (LS) was specifically activated post-acquisition in socially fear conditioned (SFC+) mice. We further measured an increase in activity-inducing HDAC1 phosphorylation at serine residues within the septum of SFC+ mice during extinction of social fear. Pharmacological inhibition of HDAC1 within the LS facilitated, while viral overexpression of septal HDAC1 impaired extinction of social fear. Finally, we found that the abovementioned facilitation of extinction memory by HDAC1 inhibition was long-lasting and persists even after 30 days of extinction. Our results show that LS-HDAC1 is a key regulator of long-lasting social fear extinction, which points towards HDAC1 as a potential therapeutic target for SAD.

neuroscience↗

bioRxiv2020

Whole genome sequencing based differentiation between re-infection and relapse in Indian patients with tuberculosis recurrence, with and without HIV co-infection

Differentiation between relapse and reinfection in cases with tuberculosis (TB) recurrence has important implications for public health, especially in patients with human immunodeficiency virus (HIV) co-infection. Forty-one paired M. tuberculosis isolates collected from 20 HIV-positive and 21 HIV-negative patients, who experienced TB recurrence after previous successful treatment, were subjected to whole genome sequencing (WGS) in addition to spoligotyping and mycobacterial interspersed repeat unit (MIRU) typing. Comparison of M. tuberculosis genomes indicated that 95% of TB recurrences in the HIV-negative cohort were due to relapse, while the majority of TB recurrences (75%) in the HIV-positive cohort was due to re-infection (P=0.0001). Drug resistance conferring mutations were documented in four pairs (9%) of isolates associated with relapse. The high contribution of re-infection to TB among HIV patients warrants further study to explore risk factors for TB exposure in the community.

genomics↗

bioRxiv2020

Towards Building a Smart Kidney Atlas: Network-based integration of multimodal transcriptomic, proteomic, metabolomic and imaging data in the Kidney Precision Medicine Project

AO_SCPLOWBSTRACTC_SCPLOWKidney Precision Medicine Project (KPMP) is building a spatially-specified human tissue atlas at the single-cell resolution with molecular details of the kidney in health and disease. Here, we describe the construction of an integrated reference tissue map of cells, pathways and genes using unaffected regions of nephrectomy tissues and undiseased human biopsies from 55 subjects. We use single-cell and -nucleus transcriptomics, subsegmental laser microdissection bulk transcriptomics and proteomics, near-single-cell proteomics, 3-D nondestructive and CODEX imaging, and spatial metabolomics data to hierarchically identify genes, pathways and cells. Integrated data from these different technologies coherently describe cell types/subtypes within different nephron segments and interstitium. These spatial profiles identify cell-level functional organization of the kidney tissue as indicative of their physiological functions and map different cell subtypes to genes, proteins, metabolites and pathways. Comparison of transcellular sodium reabsorption along the nephron to levels of mRNAs encoding the different sodium transporter genes indicate that mRNA levels are largely congruent with physiological activity.This reference atlas provides an initial framework for molecular classification of kidney disease when multiple molecular mechanisms underlie convergent clinical phenotypes.

bioinformatics↗

bioRxiv2019

Regulation of heterotopic ossification through local inflammatory monocytes in a mouse model of aberrant wound healing

Heterotopic ossification (HO) is an aberrant regenerative process with ectopic bone induction in response to musculoskeletal trauma, in which mesenchymal stem cells (MSC) differentiate into osteochondrogenic cells instead of myocytes or tenocytes. Despite frequent cases of hospitalized musculoskeletal trauma, the inflammatory responses and cell population dynamics that regulate subsequent wound healing and tissue regeneration are still unclear. Here we examine, using a mouse model of trauma-induced HO, the local microenvironment of the initial post-injury inflammatory response. Single cell transcriptome analyses identify distinct monocyte/macrophage populations at the injury site, with their dynamic changes over time elucidated using trajectory analyses. Mechanistically, transforming growth factor beta-1 (TGF{beta}1)-producing monocytes/macrophages are associated with HO and aberrant chondrogenic progenitor cell differentiation, while CD47-activating peptides that reduce systemic TGF{beta} levels help ameliorate HO. Our data thus implicate CD47 activation as a novel therapeutic approach for modulating monocyte/macrophage phenotypes, MSC differentiation and HO formation during wound healing.

immunology↗

bioRxiv2019

A Multimodal and Integrated Approach to Interrogate Human Kidney Biopsies with Rigor and Reproducibility: The Kidney Precision Medicine Project

Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate 3-dimensional (3D) molecular atlases of healthy and diseased kidney biopsies using multiple state-of-the-art OMICS and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single cell level or in 3D space is a significant challenge that can be a futile exercise if not well controlled. We describe a "follow the tissue" pipeline for generating a reliable and authentic single cell/region 3D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation and harmonization across different OMICS and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis and sharing. We established benchmarks for quality control, rigor, reproducibility and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multi-OMICS and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.

scientific communication and education↗

bioRxiv2019

Environmental chemical diethylhexyl phthalate alters intestinal microbiota community structure and metabolite profile in mice

Exposure to environmental chemicals during windows of development is a potentially contributing factor in gut microbiota dysbiosis, and linked to chronic diseases and developmental disorders. We used a community-level model of microbiota metabolism to investigate the effects of diethylhexyl phthalate (DEHP), a ubiquitous plasticizer implicated in neurodevelopmental disorders, on the composition and metabolite outputs of gut microbiota in young mice. Administration of DEHP by oral gavage increased the abundance of Lachnoclostridum, while decreasing Akkermansia, Odoribacter, and Clostridium sensu stricto. Addition of DEHP to in vitro cultured cecal microbiota increased the abundance of Alistipes, Paenibacillus, and Lachnoclostridium. Untargeted metabolomics showed that DEHP broadly altered the metabolite profile in the culture. Notably, DEHP enhanced the production of p-cresol, while inhibiting butyrate synthesis. Metabolic model-guided correlation analysis indicated that the likely sources of p-cresol are Clostridium species. Our results suggest that DEHP can directly modify the microbiota to affect production of bacterial metabolites linked with neurodevelopmental disorders.\n\nImportanceSeveral previous studies have pointed to environmental chemical exposure during windows of development as a contributing factor in neurodevelopmental disorders, and correlated these disorders with microbiota dysbiosis, little is known about how the chemicals specifically alter the microbiota to interfere with development. The findings reported in this paper unambiguously establish that a pollutant linked with neurodevelopmental disorders can directly modify the microbiota to promote the production of a potentially toxic metabolite (p-cresol) that has also been correlated with neurodevelopmental disorders. Further, we use a novel modeling strategy to identify the responsible enzymes and bacterial sources of this metabolite. To the best of our knowledge, the present study is the first to characterize the functional consequence of phthalate exposure on a developed microbiota. Our results suggest that specific bacterial pathways could be developed as diagnostic and therapeutic targets against health risks posed by ingestion of environmental chemicals.

microbiology↗

bioRxiv2019

Biological Filtering and Substrate Promiscuity Prediction for Annotating Untargeted Metabolomics

Mass spectrometry coupled with chromatography separation techniques provides a powerful platform for untargeted metabolomics. Determining the chemical identities of detected compounds however remains a major challenge. Here, we present a novel computational workflow, termed Expanded Metabolic Model Annotation (EMMA), that aims to strike a balance between discovering previously uncharacterized metabolites and the computational burden of annotation. EMMA engineers a candidate set, a listing of putative chemical identities to be used during annotation, through an expanded metabolic model (EMM). An EMM includes not only canonical substrates and products of enzymes already cataloged in a database through a reference metabolic model, but also metabolites that can form due to substrate promiscuity. EMMA was applied to untargeted LC-MS data collected from cultures of Chinese hamster ovary (CHO) cells and murine cecal microbiota. EMM metabolites matched, on average, to 23.92% of measured masses, providing a > 7-fold increase in the candidate set size when compared to a reference metabolic model. Many metabolites suggested by EMMA are not catalogued in PubChem. For the CHO cell, we experimentally confirmed the presence of 4-hydroxy-phenyllactate, a metabolite predicted by EMMA that has not been previously identified as part of CHO cell metabolism.

bioengineering↗

bioRxiv2018

Genome-wide association study of diabetic kidney disease highlights biology involved in renal basement membrane collagen

Diabetic kidney disease (DKD) is a heritable but poorly understood complication of diabetes. To identify genetic variants predisposing to DKD, we performed genome-wide association analyses in 19,406 individuals with type 1 diabetes (T1D) using a spectrum of DKD definitions basedon albuminuria and renal function. We identified 16 genome-wide significant loci. The variant with the strongest association (rs55703767) is a common missense mutation in the collagen type IV alpha 3 chain (COL4A3) gene, which encodes a major structural component of the glomerular basement membrane (GBM) implicated in heritable nephropathies. The rs55703767 minor allele (Asp326Tyr) is protective against several definitions of DKD, including albuminuria and end-stage renal disease. Three other loci are in or near genes with known or suggestive involvement in DKD (BMP7) or renal biology (COLEC11 and DDR1). The 16 DKD-associated loci provide novel insights into the pathogenesis of DKD, identifying potential biological targets for prevention and treatment.

genetics↗

bioRxiv2018

Organoid single-cell profiling identifies a transcriptional signature of glomerular disease

Podocyte injury is central to many forms of kidney disease, but transcriptional signatures reflecting podocyte injury and compensation mechanisms are challenging to analyze in vivo. Human kidney organoids derived from pluripotent stem cells (PSCs), a new model for disease and regeneration, present an opportunity to explore the transcriptional plasticity of podocytes. Here, transcriptional profiling of over 12,000 single cells from human PSC-derived kidney organoid cultures was used to identify robust and reproducible cell-lineage gene expression signatures shared with developing human kidneys based on trajectory analysis. Surprisingly, the gene expression signature characteristic of developing glomerular epithelial cells was also observed in glomerular tissue from a kidney disease cohort. This signature correlated with proteinuria and inverse eGFR, and was confirmed in an independent podocytopathy cohort. Three genes in particular were further identified as critical components of the glomerular disease signature. We conclude that cells in human PSC-derived kidney organoids reliably recapitulate the developmental transcriptional program of podocytes and other cell lineages in the human kidney, and that the early transcriptional profile seen in developing podocytes is reactivated in glomerular disease. Our findings demonstrate an innovative approach to identifying novel molecular programs involved in the pathogenesis of glomerulopathies.

systems biology↗

bioRxiv2018

An eQTL landscape of kidney tissue in human nephrotic syndrome

Expression quantitative trait loci (eQTL) studies illuminate the genetics of gene expression and, in disease research, can be particularly illuminating when using the tissues directly impacted by the condition. In nephrology, there is a paucity of eQTLs studies of human kidney. Here, we used whole genome sequencing (WGS) and microdissected glomerular (GLOM) & tubulointerstitial (TI) transcriptomes from 187 patients with nephrotic syndrome (NS) to describe the eQTL landscape in these functionally distinct kidney structures.\n\nUsing MatrixEQTL, we performed cis-eQTL analysis on GLOM (n=136) and TI (n=166). We used the Bayesian \"Deterministic Approximation of Posteriors\" (DAP) to fine-map these signals, eQtlBma to discover GLOM-or TI-specific eQTLs, and single cell RNA-Seq data of control kidney tissue to identify cell-type specificity of significant eQTLs. We integrated eQTL data with an IgA Nephropathy (IGAN) GWAS to perform a transcriptome-wide association study (TWAS).\n\nWe discovered 894 GLOM eQTLs and 1767 TI eQTLs at FDR <0.05. 14% and 19% of GLOM & TI eQTLs, respectively, had > 1 independent signal associated with its expression. 12% and 26% of eQTLs were GLOM-specific and TI-specific, respectively. GLOM eQTLs were most significantly enriched in podocyte transcripts and TI eQTLs in proximal tubules. The IGAN TWAS identified significant GLOM & TI genes, primarily at the HLA region.\n\nIn this study of NS patients, we discovered GLOM & TI eQTLs, identified those that were tissue-specific, deconvoluted them into cell-specific signals, and used them to characterize known GWAS alleles. These data are publicly available for browsing and download at http://nephqtl.org.

genomics↗

bioRxiv2018

Single-cell analysis of progenitor cell dynamics and lineage specification of the human fetal kidney

The mammalian kidney develops through repetitive and reciprocal interactions between the ureteric bud and the metanephric mesenchyme to give rise to the entire collecting system and the nephrons, respectively. Most of our knowledge of the developmental regulators driving this process has been gained from the study of gene expression and functional genetics in mice and other animal models. In order to shed light on human kidney development, we have used singlecell transcriptomics to characterize gene expression in different cell population, and to study individual cell dynamics and lineage trajectories during development. Single cell transcriptome analyses of 3,865 cells identified 17 clusters of specific cell types as defined by their gene expression profile, including markers of ureteric bud tip- and metanephric mesenchyme-specific progenitors, as well as their intermediate and differentiated lineages including the mature collecting ducts, the renal vesicle and comma- and s-shaped bodies, immature and mature podocytes, proximal tubules, loops of Henle and distal tubules. Other lineages identified include mesangium and cortical and medullary interstitium, endothelial and immune cells as well as hematopoietic cells. Novel markers for these cell types were revealed in the analysis as well as components of key signaling pathways driving renal development in animal models. Altogether, we provide a comprehensive and dynamic gene expression array of the human developing kidney at the single-cell level.

developmental biology↗

bioRxiv2017

Interactions between species introduce spurious associations in microbiome studies

Microbiota contribute to many dimensions of host phenotype, including disease. To link specific microbes to specific phenotypes, microbiome-wide association studies compare microbial abundances between two groups of samples. Abundance differences, however, reflect not only direct associations with the phenotype, but also indirect effects due to microbial interactions. We found that microbial interactions could easily generate a large number of spurious associations that provide no mechanistic insight. Using techniques from statistical physics, we developed a method to remove indirect associations and applied it to the largest dataset on pediatric inflammatory bowel disease. Our method corrected the inflation of p-values in standard association tests and showed that only a small subset of associations is directly linked to the disease. Direct associations had a much higher accuracy in separating cases from controls and pointed to immunomodulation, butyrate production, and the brain-gut axis as important factors in the inflammatory bowel disease.

microbiology↗