Biology subjects

Chauhan, S.

Publications and source records attributed to Chauhan, S..

28 records · Page 2Linked to original sources

bioRxiv2023

Whole-brain mapping reveals the divergent impact of ketamine on the dopamine system

Ketamine is a multifunctional drug with clinical applications as an anesthetic, as a pain management medication and as a transformative fast-acting antidepressant. It is also abused as a recreational drug due to its dissociative property. Recent studies in rodents are revealing the neuronal mechanisms that mediate the complex actions of ketamine, however, its long-term impact due to prolonged exposure remains much less understood with profound scientific and clinical implications. Here, we develop and utilize a high-resolution whole-brain phenotyping approach to show that repeated ketamine administration leads to a dosage-dependent decrease of dopamine (DA) neurons in the behavior state-related midbrain regions and, conversely, an increase within the hypothalamus. Congruently, we show divergently altered innervations of prefrontal cortex, striatum, and sensory areas. Further, we present supporting data for the post-transcriptional regulation of ketamine-induced structural plasticity. Overall, through an unbiased whole-brain analysis, we reveal the divergent brain-wide impact of chronic ketamine exposure on the association and sensory pathways.

neuroscience↗

bioRxiv2022

Transgenic Mouse Models Establish a Protective Role of Type 1 IFN Response in SARS-CoV-2 infection-related Immunopathology

Type 1 interferon (IFN-I) response is the first line of host defense against invading viruses. In the absence of definite mouse models, the role of IFN-I in SARS-CoV-2 infections remained to be perplexing. Here, we developed two mouse models, one with constitutively high IFN-I response (hACE2; Irgm1-/-) and the other with dampened IFN-I response (hACE2; Ifnar1-/-) to comprehend the role of IFN-I response during SARS-CoV-2 invasion. We found that hACE2; Irgm1-/- mice were resistant to lethal SARS-CoV-2 infection with substantially reduced cytokine storm and immunopathology. In striking contrast, a severe SARS-CoV-2 infection along with immune cells infiltration, inflammatory response, and enhanced pathology was observed in the lungs of hACE2; Ifnar1-/- mice. Additionally, hACE2; Ifnar1-/- mice were highly susceptible to SARS-CoV-2 neuroinvasion in the brain accompanied by immune cell infiltration, microglia/astrocytes activation, cytokine response, and demyelination of neurons. The hACE2; Irgm1-/- Ifnar1-/- double knockout mice or hACE2; Irgm1-/- mice treated with STING or RIPK2 pharmacological inhibitors displayed loss of the protective phenotypes observed in hACE2; Irgm1-/- mice suggesting that heightened IFN-I response accounts for the observed immunity. Taken together, we explicitly demonstrate that IFN-I protects from lethal SARS-CoV-2 infection, and Irgm1 (IRGM) could be an excellent therapeutic target. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/520843v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@a3aad4org.highwire.dtl.DTLVardef@12452fcorg.highwire.dtl.DTLVardef@1c43dc0org.highwire.dtl.DTLVardef@b2167d_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2022

Focused ultrasound-mediated brain genome editing

Gene editing in the mammalian brain has been challenging because of the restricted transport imposed by the blood-brain barrier (BBB). Current approaches rely on local injection to bypass the BBB. However, such administration is highly invasive and not amenable to treating certain delicate regions of the brain. We demonstrate a safe and effective gene editing technique by using focused ultrasound (FUS) to transiently open the BBB for the transport of intravenously delivered CRISPR/Cas9 machinery to the brain.

bioengineering↗

bioRxiv2022

Ancestral SARS-CoV-2 driven antibody repertoire diversity in an unvaccinated individual correlates with expanded neutralization breadth

Understanding the quality of immune repertoire triggered during natural infection can provide vital clues that form the basis for development of humoral immune response in some individuals capable of broadly neutralizing pan SARS-CoV-2 variants. We assessed the diversity of neutralizing antibody responses developed in an unvaccinated individual infected with ancestral SARS-CoV-2 by examining the ability of the distinct B cell germline-derived monoclonal antibodies (mAbs) in neutralizing known and currently circulating Omicron variants by pseudovirus and authentic virus neutralization assays. The ability of the antibodies developed post vaccination in neutralizing Omicron variants was compared to that obtained at baseline of the same individual and to those obtained from Omicron breakthrough infected individuals by pseudovirus neutralization assay. Broadly SARS-CoV-2 neutralizing mAbs representing unique B cell lineages with non-overlapping epitope specificities isolated from a single donor varied in their ability to neutralize Omicron variants. Plasma antibodies developed post vaccination from this individual demonstrated neutralization of Omicron BA.1, BA.2 and BA.4 with increased magnitude and found to be comparable with those obtained from other vaccinated individuals who were infected with ancestral SARS-CoV-2. Development of B cell repertoire capable of producing antibodies with distinct affinity and specificities for the antigen immediately after infection capable of eliciting broadly neutralizing antibodies offers highest probability in protecting against evolving SARS-CoV-2 variants. ImportanceDevelopment of robust neutralizing antibodies in SARS-CoV-2 convalescent individuals is known, however varies at population level. We isolated monoclonal antibodies from an individual infected with ancestral SARS-CoV-2 in early 2020 that not only varied in their B cell lineage origin but also varied in their capability and potency to neutralize all the known VOC and currently circulating Omicron variants. This indicated establishment of unique lineages that contributed in forming B cell repertoire in this particular individual immediately following infection giving rise to diverse antibody responses that could compensate each other in providing broadly neutralizing polyclonal antibody response. Individuals who were able to produce such potent polyclonal antibody responses after infection have a higher chance of being protected from evolving SARS-CoV-2 variants.

immunology↗

bioRxiv2022

Impact of abiotic conditions on Fungal Diversity and Comparative analysis of Soil quality of two distinct locations

Soil fertility play a prominent role in biological sustenance in turn fungi are significant participants in bridging biotic and abiotic interactions between the components in the environment, and they involve in breakdown of organic/ inorganic materials during bioleaching/ bioconversion leading to bio-availability and thus recycling of nutrients. Local environmental factors (abiotic), such as the chemical and physical properties of the soil, greatly influence the composition of existing fungal communities and determine the diversity of soil fungi. A correlation study of the micro fungi found in ecologically two different regions (Karnataka state, India) of Uttara Kannada and Chitradurga districts. One being part of Indias Western Ghats, a biologically fertile ecosystem and the other being a dry, arid region of Deccan plateau with scanty rain fall. Soil samples were collected from various geographical locations in order to study and evaluate the role that certain soil physicochemical features play in fungi diversity. According to our findings, soil attributes (fertility) are related to the composition, richness, and diversity of fungi in soils and thus soils physico-chemical properties assessed were linked to fungal diversity measurements. This led us to indicate the role of abiotic factors effecting the fungal diversity in soil and their prominent role in soil fertility. Importance of the WorkThis work signifies the role of fungal diversity on soil fertility and the impact of abiotic and physico-chemical soil parameters on the same. Thus the work explores the importance of the each of these components and the wild fungal strains participation in value addition to their functional role in breakdown of organic/ inorganic materials during bioleaching/ bioconversion leading to bio-availability and thus recycling of nutrients. The work also highlights soil pH as one of key indicators to define the diversity of soil fungi and can provide a direct correlation between pH, bioconversion and fungal activity/ diversity. This work is first of a kind from southern India connecting the western ghat bio-diversity hot-spot fertile region with the neighbouring barren Bayaluseemae region of Karnataka State, South India with regards to abiotic factors, fungi and fertility.

ecology↗

bioRxiv2021

Mapping morphological malformation to genetic dysfunction in blood vessel organoids with 22q11.2 Deletion Syndrome

DiGeorge Syndrome, or 22q11.2 deletion syndrome (22q11.2 DS), is a genetic disorder caused by microdeletions in chromosome 22, impairing the function of endothelial cells (EC) and/or mural cells and leading to deficits in blood vessel development such as abnormal aortic arch morphology, tortuous retinal vessels, and tetralogy of Fallot. The mechanism by which dysfunctional endothelial cells and pericytes contribute to the vasculopathy, however, remains unknown. In this study, we used human blood vessel organoids (VOs) generated from iPSC of 22q11.2 DS patients to model the vascular malformations and genetic dysfunctions. We combined high-resolution lightsheet imaging and single-cell transcriptome analysis to link the genetic profile and vascular phenotype at the single-cell level. We developed a comprehensive analytical methodology by integrating deep learning-mediated blood vessel segmentation, network graph construction, and tessellation analysis for automated morphology characterization. We report that 22q11.2DS VOs demonstrate a smaller size with increased angiogenesis/sprouting, suggesting a less stable vascular network. Overall, clinical presentations of smaller vascular diameter, less connected vasculature, and increased branch points were recapitulated in 22q11.2DS VOs. Single-cell transcriptome profiling showed heterogeneity in both 22q11.2DS and control VOs, but the former demonstrated alterations in endothelial characteristics that are organ-specific and suggest a perturbation in the vascular developmental process. Intercellular communication analysis indicated that the vascular dysfunctions in 22q11.2 deletion were due to a lower cell-cell contact and upregulated extracellular matrix organization involving collagen and fibronectin. Voronoi diagram-based tessellation analysis also indicated that the colocalization of endothelial tubes and mural cells was different between control and 22q11.2 VOs, indicating that alterations in EC and mural interactions might contribute to the deficits in vascular network formation. This study illustrates the utility of VO in revealing the pathogenesis of 22q11.2DS vasculopathy.

bioengineering↗

bioRxiv2021

Machine learning of all Mycobacterium Tuberculosis H37Rv RNA-seq data reveals complex interplay between metabolism, stress response, and infection

Mycobacterium tuberculosis is one of the most consequential human bacterial pathogens, posing a serious challenge to 21st century medicine. A key feature of its pathogenicity is its ability to adapt its transcriptional response to environmental stresses through its transcriptional regulatory network (TRN). While many studies have sought to characterize specific portions of the M. tuberculosis TRN, a systems level characterization and analysis of interactions among the controlling transcription factors remains to be achieved. Here, we applied an unsupervised machine learning method to modularize the M. tuberculosis transcriptome and describe the role of transcription factors (TFs) in the TRN. By applying Independent Component Analysis (ICA) to over 650 transcriptomic samples, we obtained 80 independently modulated gene sets known as "iModulons," many of which correspond to known regulons. These iModulons explain 61% of the variance in the organisms transcriptional response. We show that iModulons: 1) reveal the function of previously unknown regulons, 2) describe the transcriptional shifts that occur during environmental changes such as shifting carbon sources, oxidative stress, and virulence events, and 3) identify intrinsic clusters of transcriptional regulons that link several important metabolic systems, including lipid, cholesterol, and sulfur metabolism. This transcriptome-wide analysis of the M. tuberculosis TRN informs future research on effective ways to study and manipulate its transcriptional regulation, and presents a knowledge-enhanced database of all published high-quality RNA-seq data for this organism to date.

systems biology↗

bioRxiv2021

Mining all publicly available expression data to compute dynamic microbial transcriptional regulatory networks

We are firmly in the era of biological big data. Millions of omics datasets are publicly accessible and can be employed to support scientific research or build a holistic view of an organism. Here, we introduce a workflow that converts all public gene expression data for a microbe into a dynamic representation of the organisms transcriptional regulatory network. This five-step process walks researchers through the mining, processing, curation, analysis, and characterization of all available expression data, using Bacillus subtilis as an example. The resulting reconstruction of the B. subtilis regulatory network can be leveraged to predict new regulons and analyze datasets in the context of all published data. The results are hosted at https://imodulondb.org/, and additional analyses can be performed using the PyModulon Python package. As the number of publicly available datasets increases, this pipeline will be applicable to a wide range of microbial pathogens and cell factories.

bioinformatics↗

bioRxiv2019

Autoimmunity Risk Gene IRGM is a Master Negative Regulator of Interferon Response by Controlling the Activation of cGAS STING and RIG-I-MAVS Signaling Pathways

Activation of type 1 interferon response is extensively connected with the antiviral immunity and pathogenesis of autoimmune diseases. Here, we found that IRGM, whose deficiency is linked with the genesis of several autoimmune disorders, is a master negative regulator of the interferon response. Mechanistically, we show that IRGM interacts with nucleic acid sensor proteins, including cGAS and RIG-I, and mediates their autophagic degradation to restrain activation of interferon signaling. Further, IRGM maintains mitophagy flux, and its deficiency results in the accumulation of defunct leaky mitochondria that releases cytosolic DAMPs triggering activation of interferon responses via cGAS-STING and RIG-I-MAVS signaling axis. Due to an enduring type 1 IFN response in IRGM-deficient cells and mice, they were intrinsically resistant to infection of the Japanese Encephalitis virus, Herpes Simplex virus, and Chikungunya virus. Altogether, this study defines the molecular mechanisms by which IRGM maintains interferon homeostasis and protects from autoimmune diseases. Further, it identifies IRGM as a broad therapeutic target for defense against viruses.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC=\"FIGDIR/small/815506v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (48K):\norg.highwire.dtl.DTLVardef@1d4822org.highwire.dtl.DTLVardef@6aebbcorg.highwire.dtl.DTLVardef@19a9b72org.highwire.dtl.DTLVardef@1539195_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2018

Memote: A community-driven effort towards a standardized genome-scale metabolic model test suite

Several studies have shown that neither the formal representation nor the functional requirements of genome-scale metabolic models (GEMs) are precisely defined. Without a consistent standard, comparability, reproducibility, and interoperability of models across groups and software tools cannot be guaranteed.\n\nHere, we present memote (https://github.com/opencobra/memote) an open-source software containing a community-maintained, standardized set of metabolic model tests. The tests cover a range of aspects from annotations to conceptual integrity and can be extended to include experimental datasets for automatic model validation. In addition to testing a model once, memote can be configured to do so automatically, i.e., while building a GEM. A comprehensive report displays the models performance parameters, which supports informed model development and facilitates error detection.\n\nMemote provides a measure for model quality that is consistent across reconstruction platforms and analysis software and simplifies collaboration within the community by establishing workflows for publicly hosted and version controlled models.

systems biology↗