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Biology subjects

Rajasekhar, P.

Publications and source records attributed to Rajasekhar, P..

10 recordsLinked to original sources

Megakaryocytic proteomic signatures define myeloproliferative neoplasms

The classical Philadelphia-negative myeloproliferative neoplasms (MPNs) are clonal stem cell disorders of the bone marrow with significant niche dysregulation driven in part by abnormal megakaryocytes. The three classical MPNs: polycythemia vera (PV), essential thrombocythemia (ET) and primary myelofibrosis (PMF), display established megakaryocytic morphological differences which aid in their diagnostic classification. The paucity of megakaryocytes in the bone marrow aspirate has previously limited a proteomic analysis of megakaryocytes in clinical samples. We aimed to undertake an unbiased proteomic analysis of in situ megakaryocytes from the bone marrow of patients with PV, ET, and PMF. Using a novel, deep visual proteomics strategy, we dissected and analyzed megakaryocytes from 60 MPN patients and 20 controls (patients with limited stage non-Hodgkin lymphoma who had uninvolved bone marrow). We reveal that megakaryocyte proteomics from MPN patients are distinct to those from control patients, and further, that the megakaryocytes from the three MPNs have unique, disease-specific signatures. The disease-specific megakaryocyte proteome highlights novel pathways of disease.

cancer biology↗

SpatialBench: Comparative cross-platform benchmarking of high-resolution spatial transcriptomics using matched mouse lymphoid tissue

Spatial transcriptomics (ST) has rapidly expanded with the introduction of multiple high-resolution platforms, yet cross-platform benchmarking remains limited and largely focused on technical performance. Here we present SpatialBench, a matched multi-platform resource comprising Visium HD, Xenium and MERSCOPE data together with single-cell and single-nucleus references from a malaria-challenged wild-type and B cell-specific Tbx21 knockout mouse spleen model. In this system, loss of T-bet in B cells disrupts germinal center (GC) polarization and antibody maturation, providing a biologically grounded benchmark for technology comparison. We leveraged this system to systematically evaluate ST platform performance using technical and biological readouts. Across platforms, immune organization and Tbx21-associated programs were consistently recovered, indicating robustness of major biological signals. Platforms instead differed in the level of biological resolution accessible. Visium HD enabled transcriptome-scale GC characterization and, together with Xenium, resolved dark and light zone organization, whereas GC zonation was not resolved in MERSCOPE, consistent with differences in transcript detection sensitivity. SpatialBench provides a biologically defined reference dataset for evaluation of ST technologies, method development, computational benchmarking, and studies of GC spatial organization in lymphoid tissue.

bioinformatics↗

The Colonic Mucus Layer is Thinner and is Associated with Goblet Cell Hyperplasia in the db/db Mouse Model of Type 2 Diabetes

Background & AimsDiabetes mellitus has been associated with both intestinal barrier dysfunction and peripheral neuropathy leading to increased risk of infection. The mucus layer forms a physical barrier against pathogens and is a critical component of the intestinal barrier that may be impaired in diabetes. This study aimed to assess how diabetes impacts goblet cells (GCs), mucus layer integrity, and innervation in the colon. MethodsFluorescence microscopy was used to investigate GCs, the mucus layer, and innervation in the colon of db/db mice. Custom open-access image analysis pipelines were developed to quantify GC numbers, location and content, mucus thickness, bacterial colonization, and innervation density in intestinal tissue sections. We also treated mice with the clinically used glucagon-like peptide 1 receptor (GLP-1R) agonist liraglutide to assess its capacity to reverse pathological changes to GCs and the mucus layer in a model of established type 2 diabetes (T2DM). ResultsThe mucus layer was significantly thinner in the colon of db/db mice with established diabetes and bacteria more readily colonized the epithelium and crypts. Intercrypt GC numbers were significantly reduced in db/db mice. However, there were significantly more GCs per crypt, and crypts were elongated in the db/db colon. Innervation was reduced in the mucosa and external muscle of the colon, consistent with diabetic neuropathic changes. Liraglutide treatment increased the size of GCs but had no effect on GC numbers, mucus thickness, or innervation in this model of established T2DM. ConclusionsMucus barrier dysfunction and GC hyperplasia is evident in the db/db colon. Increased microbial penetrability through the mucus layer suggests potential implications for the increased risk of gastrointestinal infection in diabetes.

physiology↗

Formation of the moving junction is the nexus for host cytoskeletal remodelling during Plasmodium falciparum invasion of human erythrocytes

Plasmodium falciparum invasion of human erythrocytes is a complex and tightly coordinated process, involving host cell attachment, moving junction formation and engagement of the parasites actomyosin motor. The temporal precision of these events is mediated by distinct ligand-receptor interactions and the sequential release of the merozoites apical organelles. What remains unclear is how these molecular and biophysical interactions enable Plasmodium to bypass the stable erythrocyte membrane-cytoskeletal complex. Here, several P. falciparum lines expressing different fluorescently tagged apical organelle proteins, were imaged with lattice light sheet microscopy (LLSM) to determine the timing of cytoskeletal disassembly and apical organelle release. Blocking the AMA1-RON2 interaction has no effect on the PfRh5-basigin Ca2+ flux but prevents host cytoskeleton disassembly. In contrast, the inhibition of parasite actin polymerisation had no effect on cytoskeletal clearance but caused a sustained Ca2+ response. We further demonstrate that establishment of the moving junction is temporally linked to clearance of the host cytoskeleton. Collectively, our findings support the existence of an association between the RON complex and components of the host cytoskeleton, which mediates the localised disruption of the erythrocyte-membrane cytoskeletal complex during invasion.

microbiology↗

A necroptotic-to-apoptotic signaling axis underlies inflammatory bowel disease

Inflammatory bowel disease (IBD) is a chronic condition caused by altered cytokine signaling, maladaptive immunity, dysbiosis, and intestinal barrier dysfunction. Patients with IBD receive therapy to correct these imbalances and achieve remission. However, most patients relapse, suggesting that pathological mechanisms persist during remission. Here, we show that excess epithelial cell death is an underlying feature of IBD that arises in patients in remission and on advanced therapy. Mechanistically, nascent inflammation reprograms epithelial cells into a macrophage-like state that promotes RIPK1-independent necroptotic signaling, then triggers iNOS-mediated mitochondrial apoptosis of absorptive epithelial cells and PUMA-mediated intestinal stem cell death. These findings reveal aberrant epithelial cell death signaling as a hallmark of IBD that occurs early in mucosal lesion development and persists despite current therapeutic approaches. One-Sentence SummaryEpithelial cell death is dysregulated in patients with inflammatory bowel disease.

cell biology↗

Spotlight on 10x Visium: a multi-sample protocol comparison of spatial technologies

BackgroundSpatial transcriptomics allows gene expression to be measured within complex tissue contexts. Among the array of spatial capture technologies available is 10x Genomics Visium platform, a popular method which enables transcriptomewide profiling of tissue sections. Visium offers a range of sample handling and library construction methods which introduces a need for benchmarking to compare data quality and assess how well the technology can recover expected tissue features and biological signatures. ResultsHere we present SpatialBench, a unique reference dataset generated from spleen tissue of mice responding to malaria infection spanning several tissue preparation protocols (both fresh frozen and FFPE samples, with and without CytAssist tissue placement). We noted better quality control metrics in reference samples prepared using probe-based capture methods, particularly those processed with CytAssist, validating the improvement in data quality produced with the platform. Our analysis of replicate samples extends to explore spatially variable gene detection, the outcomes of clustering and cell deconvolution using matched single-cell RNA-sequencing data and publicly available reference data to identify cell types and tissue regions expected in the spleen. Multi-sample differential expression analysis recovered known gene signatures related to biological sex or gene knockout. ConclusionsWe framed a comprehensive multi-sample analysis workflow that allowed us to generate consistent results both within and between different subsets of replicate samples, enabling broader comparisons and interpretations to be made at the group-level. Our SpatialBench dataset, analysis, and workflow can serve as a practical guide for Visium users and may prove valuable in other benchmarking studies.

genomics↗

Gut Analysis Toolbox: Automating quantitative analysis of enteric neurons

The enteric nervous system (ENS) plays an important role in coordinating gut function. The ENS consists of an extensive network of neurons and glial cells within the wall of the gastrointestinal tract. Alterations in neuronal distribution, function, and type are strongly associated with enteric neuropathies and gastrointestinal (GI) dysfunction and can serve as biomarkers for disease. However, current methods for assessing neuronal counts and distribution suffer from undersampling. This is partly due to challenges associated with imaging and analyzing large tissue areas, and operator bias due to manual analysis. Here, we present the Gut Analysis Toolbox (GAT), an image analysis tool designed for characterization of enteric neurons and their neurochemical coding using 2D images of GI wholemount preparations. GAT is developed for the Fiji distribution of ImageJ. It has a user-friendly interface and offers rapid and accurate cell segmentation. Custom deep learning (DL) based cell segmentation models were developed using StarDist. GAT also includes a ganglion segmentation model which was developed using deepImageJ. In addition, GAT allows importing of segmentation generated by other software. DL models have been trained using ZeroCostDL4Mic on diverse datasets sourced from different laboratories. This captures the variability associated with differences in animal species, image acquisition parameters, and sample preparation across research groups. We demonstrate the robustness of the cell segmentation DL models by comparing them against the state-of-the-art cell segmentation software, Cellpose. To quantify neuronal distribution GAT applies proximal neighbor-based spatial analysis. We demonstrate how the proximal neighbor analysis can reveal differences in cellular distribution across gut regions using a published dataset. In summary, GAT provides an easy-to-use toolbox to streamline routine image analysis tasks in ENS research. GAT enhances throughput allowing unbiased analysis of larger tissue areas, multiple neuronal markers and numerous samples rapidly.

neuroscience↗

TRPV4 is expressed by enteric glia and muscularis macrophages of the colon but does not play a prominent role in colonic motility

BackgroundMechanosensation is an important trigger of physiological processes in the gastrointestinal tract. Aberrant responses to mechanical input are associated with digestive disorders, including visceral hypersensitivity. Transient Receptor Potential Vanilloid 4 (TRPV4) is a mechanosensory ion channel with proposed roles in visceral afferent signaling, intestinal inflammation, and gut motility. While TRPV4 is a potential therapeutic target for digestive disease, current mechanistic understanding of how TRPV4 may influence gut function is limited by inconsistent reports of TRPV4 expression and distribution. MethodsIn this study we profiled functional expression of TRPV4 using Ca2+ imaging of wholemount preparations of the mouse, monkey, and human intestine in combination with immunofluorescent labeling for established cellular markers. The involvement of TRPV4 in colonic motility was assessed in vitro using videomapping and contraction assays. ResultsThe TRPV4 agonist GSK1016790A evoked Ca2+ signaling in muscularis macrophages, enteric glia, and endothelial cells. TRPV4 specificity was confirmed using TRPV4 KO mouse tissue or antagonist pre-treatment. Calcium responses were not detected in other cell types required for neuromuscular signaling including enteric neurons, interstitial cells of Cajal, PDGFR+ cells, and intestinal smooth muscle. TRPV4 activation led to rapid Ca2+ responses by a subpopulation of glial cells, followed by sustained Ca2+ signaling throughout the enteric glial network. Propagation of these waves was suppressed by inhibition of gap junctions or Ca2+ release from intracellular stores. Coordinated glial signaling in response to GSK1016790A was also disrupted in acute TNBS colitis. The involvement of TRPV4 in the initiation and propagation of colonic motility patterns was examined in vitro. ConclusionsWe reveal a previously unappreciated role for TRPV4 in the initiation of distension-evoked colonic motility. These observations provide new insights into the functional role of TRPV4 activation in the gut, with important implications for how TRPV4 may influence critical processes including inflammatory signaling and motility. SummaryO_LITRPV4 is expressed by equivalent cell types in the rodent and primate (monkey and human) colon. This mechanosensitive ion channel has proposed roles in inflammation, visceral afferent signaling, and colonic motility. C_LIO_LINew analysis methods were developed to examine cellular communication in the enteric glial network. This approach revealed new insights into inflammation-associated changes in glial connectivity. C_LIO_LINew roles for TRPV4 in transduction of distension-evoked responses in the colon and colonic motility were identified. C_LI Key findingsWe have defined the cell types that functionally express TRPV4 in the gut wall. These include enteric glia, endothelia of blood and lymphatic vessels, mMac, and extrinsic afferent nerves. TRPV4- dependent Ca2+ signaling was not detected in enteric neurons, PDGFR cells, interstitial cells of Cajal and smooth muscle cells, which are important drivers of gut motility. These observations align with our experimental evidence for limited involvement of TRPV4 in neuromuscular transmission and propagating colonic motility. New and NoteworthyO_LINovel cellular sites of functional TRPV4 expression in the GI tract were identified and compared across multiple vertebrate species. New analytical approaches to characterize enteric glial communication in a spatiotemporal manner were developed. C_LIO_LIA supporting role for TRPV4 in the initiation of propagating colonic contractions in response to distension was demonstrated. Potential mechanisms that contribute to TRPV4-mediated effects on GI function were identified. C_LIO_LITRPV4-dependent activity in enteric glia is enhanced in inflammation, consistent with current evidence for inflammation-associated sensitization of TRPV4 on visceral afferents and a major role in mechanically evoked nociceptive signaling. C_LIO_LIPair correlation analysis was used to examine spatial connectivity of Ca2+ signaling, enabling demonstration of dysregulated glial communication in acute inflammation. C_LI

physiology↗

An immunohistochemical atlas of necroptotic pathway expression

Necroptosis is a lytic form of regulated cell death reported to contribute to inflammatory diseases of the gut, skin and lung, as well as ischemic-reperfusion injuries of the kidney, heart and brain. However, precise identification of the cells and tissues that undergo necroptotic cell death in vivo has proven challenging in the absence of robust protocols for immunohistochemical detection. Here, we provide automated immunohistochemistry protocols to detect core necroptosis regulators - Caspase-8, RIPK1, RIPK3 and MLKL - in formalin-fixed mouse and human tissues. We observed surprising heterogeneity in protein expression within tissues, whereby short-lived immune barrier cells were replete with necroptotic effectors, whereas long-lived cells lacked RIPK3 or MLKL expression. Local changes in the expression of necroptotic effectors occurred in response to insults such as inflammation, dysbiosis or immune challenge, consistent with necroptosis being dysregulated in disease contexts. These methods will facilitate the precise localisation and evaluation of necroptotic signaling in vivo. HighlightsO_LI13 automated immunohistochemistry protocols for detecting the necroptotic pathway C_LIO_LINecroptotic pathway expression is confined to fast-cycling immune barriers C_LIO_LINecroptotic pathway expression changes at sites of immunoinflammatory challenge C_LIO_LIImmunodetection of necrosomes in IBD patients is a putative new diagnostic tool C_LI

cell biology↗

Interactive design of GPU-accelerated Image Data Flow Graphs and cross-platform deployment using multi-lingual code generation

Modern life science relies heavily on fluorescent microscopy and subsequent quantitative bio-image analysis. The current rise of graphics processing units (GPUs) in the context of image processing enables batch processing large amounts of image data at unprecedented speed. In order to facilitate adoption of this technology in daily practice, we present an expert system based on the GPU-accelerated image processing library CLIJ: The CLIJ-assistant keeps track of which operations formed an image and suggests subsequent operations. It enables new ways of interaction with image data and image processing operations because its underlying GPU-accelerated image data flow graphs (IDFGs) allow changes to parameters of early processing steps and instantaneous visualization of their final results. Operations, their parameters and connections in the IDFG are stored at any point in time enabling the CLIJ-assistant to offer an undo-function for virtually unlimited rewinding parameter changes. Furthermore, to improve reproducibility of image data analysis workflows and interoperability with established image analysis platforms, the CLIJ-assistant can generate code from IDFGs in programming languages such as ImageJ Macro, Java, Jython, JavaScipt, Groovy, Python and C++ for later use in ImageJ, Fiji, Icy, Matlab, QuPath, Jupyter Notebooks and Napari. We demonstrate the CLIJ-assistant for processing image data in multiple scenarios to highlight its general applicability. The CLIJ-assistant is open source and available online: https://clij.github.io/assistant/

bioinformatics↗