Biology subjects

Munir, A.

Publications and source records attributed to Munir, A..

6 recordsLinked to original sources

bioRxiv2026

LAMA2-related muscular dystrophy alters Schwann cell calcium homeostasis and increases peripheral nerve inflammation

LAMA2-related muscular dystrophy (LAMA2-RD) affects skeletal muscle and peripheral nerves, yet the consequences of LAMA2 deficiency on peripheral nerve integrity beyond early postnatal development remain incompletely understood. We investigated sciatic nerve architecture and molecular alterations across postnatal life in hypomorphic Lama2dy2J/dy2J mice. LAMA2 localizes around the abaxonal surface of myelinating Schwann cells in control nerves. LAMA2-deficient nerves exhibited patchy regions lacking myelinated axons from early postnatal stages into adulthood, including expanded Remak bundles along with axons completely lacking normal Schwann cell ensheathment. In adult nerves, myelin infolding and reduced myelin circularity revealed abnormalities in the architecture of myelin that had formed. Bulk sciatic nerve RNA sequencing identified altered calcium-signaling and immune-related transcriptional signatures. Complementary Fura Red measurements in primary nerve-derived Schwann cell cultures demonstrated decreased intracellular calcium in LAMA2-deficient samples, while ATP-evoked responses were preserved. Older LAMA2-deficient nerves also exhibited increased CD45+CD11b+ myeloid-cell infiltration. Together, these observations extend the characterization of LAMA2-associated neuropathy into adulthood and identify calcium homeostasis and neuroimmune responses as candidate processes relevant to persistent peripheral nerve pathology.

neuroscience↗

bioRxiv2026

HANSEN: An Integrated Structural and Functional Proteome Resource for Structure-Guided Drug Discovery in Mycobacterium leprae

Leprosy remains a leading infectious cause of preventable disability, yet its causative agent, Mycobacterium leprae (M. leprae), is structurally under-characterised. Only ten Protein Data Bank (PDB) entries represent seven of its 1,603 protein-coding genes. We present HANSEN, a proteome-wide structural and functional resource for M. leprae. Monomeric and oligomeric models were generated with AlphaFold 3, Boltz-1, Boltz-2 and Chai-1, and annotated with per-residue confidence, predicted aligned error and, for assemblies, interface confidence. Ligand-binding pockets were predicted with AF2BIND, P2Rank and fpocket, template-derived ligands were modelled within oligomeric complexes, residue-level B-cell epitope propensity was estimated with DiscoTope-3.0, and gene essentiality was transferred from Mycobacterium tuberculosis transposon-sequencing labels. These features are integrated in a relational database with interactive visualisation and combined into a calibrated Target Priority Score that ranks all 1,603 proteins into four tiers and recovers established antimycobacterial targets. HANSEN (https://hansen-leprosy.medschl.cam.ac.uk/home) provides a practical basis for target prioritisation and structure-guided drug discovery in leprosy.

bioinformatics↗

bioRxiv2025

Spatialproteomics - an interoperable toolbox for analyzing highly multiplexed fluorescence image data

SummaryHighly multiplexed immunofluorescence imaging is a recent method to characterize tissues at single-cell resolution on the protein level, offering low cost, high scalability, and the ability to analyze paraffin-embedded tissue samples. However, the analysis of these data involves a sequence of steps, including segmentation, image processing, marker quantification, cell type classification, and neighborhood analysis, each of which involves a multitude of method and parameter choices that need to be adapted to the data and analytical objective at hand. Moreover, variations in data quality can be high and unpredictable, which necessitates further flexibility and interactivity. While individual components exist, there is an unmet need for a coherent toolbox that offers end-to-end coverage of the workflow, flexibility, and automation. We present spatialproteomics, a Python package that addresses these challenges. Built on top of xarray and dask, spatialproteomics can process images that are larger than the working memory. It supports synchronization of shared coordinates across data modalities such as images, segmentation masks, and expression matrices, which facilitates easy and safe subsetting and transformation. We demonstrate spatialproteomics on a set of images of reactive lymph nodes or different forms of B cell Non-Hodgkin lymphomas (BNHL) from 132 patients. We showcase an end-to-end analysis from raw images to statistical characterization of cell type composition and spatial distribution across indolent and aggressive lymphomas. Furthermore, we show how spatialproteomics can process gigapixel whole slide images. Altogether, we propose spatialproteomics as an easy-to-install, easy-to-learn, comprehensive toolbox for constructing powerful end-to-end image analysis solutions for highly multiplexed immunofluorescence imaging. Availability and ImplementationThe source code for spatialproteomics is freely available at https://github.com/sagar87/spatialproteomics under the MIT license. Contactwolfgang.huber@embl.org, Peter-Martin.Bruch@med.uni-duesseldorf.de

bioinformatics↗

bioRxiv2023

CRISPRa-induced upregulation of human LAMA1 compensates for LAMA2-deficiency in Merosin-deficient congenital muscular dystrophy

Merosin-deficient congenital muscular dystrophy (MDC1A) is an autosomal recessive disorder caused by mutations in the LAMA2 gene, resulting in a defective form of the extracellular matrix protein laminin-2 (LAMA2). Individuals diagnosed with MDC1A exhibit progressive muscle wasting and declining neuromuscular functions. No treatments for this disorder are currently available. We previously showed that postnatal Lama1 upregulation, achieved through CRISPR activation (CRISPRa), compensates for Lama2 deficiency and prevents neuromuscular pathophysiology in a mouse model of MDC1A. In this study, we assessed the feasibility of upregulating human LAMA1 as a potential therapeutic strategy for individuals with MDC1A, regardless of their mutations. We hypothesized that CRISPRa-mediated upregulation of human LAMA1 would compensate for the lack of LAMA2 and rescue cellular abnormalities in MDC1A fibroblasts. Global transcriptomic and pathway enrichment analyses of fibroblasts collected from individuals carrying pathogenic LAMA2 mutations, compared with healthy controls, indicated higher expression of transcripts encoding proteins that contribute to wound healing, including Transforming Growth Factor-{beta} (TGF-{beta}) and Fibroblast Growth Factor (FGF). These findings were supported by wound-healing assays indicating that MDC1A fibroblasts migrated significantly more rapidly than the controls. Subsequently, we treated the MDC1A fibroblasts with SadCas9-2XVP64 and sgRNAs targeting the LAMA1 promoter. We observed robust LAMA1 expression, which was accompanied by significant decreases in cell migration and expression of FGFR2, TGF-{beta}2, and ACTA2, which are involved in the wound-healing mechanism in MDC1A fibroblasts. Collectively, our data suggest that CRISPRa-mediated LAMA1 upregulation may be a feasible mutation-independent therapeutic approach for MDC1A. This strategy might be adapted to address other neuromuscular diseases and inherited conditions in which strong compensatory mechanisms have been identified.

genetics↗

bioRxiv2020

Gut Dysbiosis with a Pathobiont Shifts the Intestinal Microbiota Profile and Accelerates Lupus Nephritis

The gut microbiota (GM) exerts a strong influence over the host immune system and dysbiosis of this microbial community can affect the clinical phenotype in chronic inflammatory conditions. To explore the role of the GM in lupus nephritis, we colonized NZM2410 mice with Segmented Filamentous Bacteria (SFB). Gut colonization with SFB was associated with worsening glomerulonephritis, glomerular and tubular immune complex deposition and interstitial inflammation compared to NZM2410 mice free of SFB. With SFB colonization mice experienced an increase in small intestinal lamina propria Th17 cells and group 3 innate lymphoid cells (ILC3s). However, although serum IL-17A expression was elevated in these mice, Th17 cells and ILC3s were not detected in the inflammatory infiltrate in the kidney. In contrast, serum and kidney tissue expression of the macrophage chemoattractants MCP-1 and CXCL1 were significantly elevated in SFB colonized mice. Furthermore, kidney infiltrating F4/80+CD206+ M2-like macrophages were significantly increased in these mice. Evidence of increased gut permeability or "leakiness" was detected in SFB colonized mice. Finally, the intestinal microbiome of SFB colonized mice at 15 and 30 weeks of age exhibited dysbiosis when compared to uncolonized mice at the same time points. Both microbial relative abundance as well as biodiversity of colonized mice was found to be altered. Collectively, SFB gut colonization in the NZM2410 mouse exacerbates kidney disease, promotes kidney M2-like macrophage infiltration and overall intestinal microbiota dysbiosis.

immunology↗

bioRxiv2019

Comparative analyses of metabolic pathways in mycobacteria: Insights into the identification and characterisation of new drug targets in M. tuberculosis, M. leprae and M. abscessus

Three related mycobacteria are the cause of widespread infections in man and are the focus of intense research and drug-discovery efforts in the face of growing antimicrobial resistance. Mycobacterium tuberculosis, the causative agent of tuberculosis, is currently one of the top ten causes of death in the world according to WHO; M. abscessus, a group of non-tuberculous mycobacteria causes lung infections and other opportunistic infections in humans; and M. leprae, the causative agent of leprosy, remains endemic in tropical countries. There is an urgent need to design alternatives to conventional treatment strategies, due to the increase in resistance to standard antibacterials. In this study, we present a comparative analysis of chokepoint and essentiality datasets that will provide insight into the development of new treatment regimes. We illustrate the key metabolic pathways shared between these three organisms and identify drug targets with a wide metabolic impact that are common to the three species. We demonstrate that 72% of the chokepoint enzymes are proteins essential to Mycobacterium tuberculosis. We show also that 78% of the drug targets, prioritized based on their presence in multiple paths on the metabolic network, are present in pathways shared by M. tuberculosis, M. leprae and M. abscessus, including biosynthesis of amino acids, carbohydrates, cell structures, fatty acid and lipid biosynthesis. A further 17% is found in the prioritised pathways shared between M. tuberculosis and M. abscessus. We have performed comparative structure modelling of potential drug targets identified using our analysis in order to assess druggability and demonstrate the importance of chokepoint analysis in terms of drug target identification. AUTHOR SUMMARYComputer simulation studies to design new drugs against mycobacteria

bioinformatics↗