Biology subjects

Murugan, V.

Publications and source records attributed to Murugan, V..

5 recordsLinked to original sources

bioRxiv2026

A Workflow for Spatial Transcriptomic Analysis from Intra-operative Human Skeletal Muscle Biopsies

IntroductionSuccessful reinnervation following peripheral nerve injury is highly variable, and the molecular programs underlying human muscle degeneration and recovery remain poorly defined. There is a critical need for high-resolution, spatially resolved gene expression data from human skeletal muscle obtained in clinically relevant settings. This study aimed to establish the feasibility of applying spatial transcriptomics to intra-operatively human muscle biopsies and to generate a framework for identifying gene expression signatures associated with reinnervation outcomes. MethodsTo validate the workflow, we collected biopsies intraoperatively from upper-extremity muscles during standard-of-care orthopaedic surgical procedures 5 months after traumatic brachial plexus injury. The flash-frozen biopsy was processed using the 10x Genomics Visium HD high-resolution platform. Quality metrics confirmed high RNA integrity and robust transcript detection at 8 {micro}m resolution. ResultsGenes involved in neuromuscular junction formation, degeneration, and regeneration were identified at subcellular resolution and showed fiber-type-specific expression patterns. Analyses were performed using complementary approaches in Seurat and Loupe Browser. ConclusionsTogether, these findings demonstrate the feasibility of spatial transcriptomics in human muscle, establish baseline gene-expression signatures, and provide a foundation for future studies aimed at identifying biomarkers associated with successful reinnervation and improved nerve-repair strategies.

physiology↗

bioRxiv2024

Kinetic patterns of single cell gene expression discriminate between the murine cellular responses to live attenuated and inactivated Yellow Fever vaccines

The success of the live attenuated Yellow Fever vaccine (YF17D) that elicits immunity lasting over thirty years has made it a widely used model to understand the generation of durable protection. We compare the early single-cell level transcriptional response in mice to YF17D and an adjuvanted-inactivated, but less effective version (InYF). Within the first week, we identify 70 kinetic patterns in 45 cellular clusters, majority of which discriminate between the two formulations, some in a tissue and sex-specific manner. Intriguingly, differential transcripts fall into two categories, one whose association with YF17D or InYF is maintained even when decoupled from their cell-type of expression and the other where such cell-plus-gene pairing is critical to maintain differential marker status. We demonstrate applications of this resource, by identifying B cells with varied interferon and antigen responsiveness in relation to each vaccine. This high-resolution dataset is amenable to further biomarker discovery and hypothesis generation.

immunology↗

bioRxiv2024

Nanoparticle-Supported, Rapid, Digital Quantification of Neutralizing Antibodies Against SARS-CoV-2 Variants

The measurement of neutralizing immune responses to viral infection is essential, given the heterogeneity of human immunity and the emergence of new virus strains. However, neutralizing antibody (nAb) assays often require high-level biosafety containment, sophisticated instrumentation, and long detection times. Here, as a proof-of-principle, we designed a nanoparticle-supported, rapid, electronic detection (NasRED) assay to assess the neutralizing potency of monoclonal antibodies (mAbs) against SARS-CoV-2. The gold nanoparticles (AuNPs) coated with human angiotensin-converting enzyme 2 (ACE2) protein as nAb potency reporters were mixed with the mAbs to be tested, as well as streptavidin-conjugated multivalent spike (S) protein or their receptor binding domains (RBD). High-affinity and ACE2-competitive nAbs alter the S (or RBD)-to-ACE2 binding level and modulate AuNP cluster formation and precipitation. The amount of free-floating AuNP reporters is quantified by a semiconductor-based readout system that measures the AuNPs optical extinction, producing nAb signals that can differentiate SARS-CoV-2 variants (Wuhan-Hu-1, Gamma, and Omicron). The modular design nature, short assay time (less than 30 minutes), and portable and inexpensive readout system make this NasRED-nAb assay applicable to measuring vaccine potency, immune responses to infection, and the efficacy of antibody-based therapies.

immunology↗

bioRxiv2024

CountASAP: A Lightweight, Easy to Use Python Package for Processing ASAPseq Data

Declining sequencing costs coupled with the increasing availability of easy-to-use kits for the isolation of DNA and RNA transcripts from single cells have driven a rapid proliferation of studies centered around genomic and transcriptomic data. Simultaneously, a wealth of new techniques have been developed that utilize single cell technologies to interrogate a broad range of cell-biological processes. One recently developed technique, transposase-accessible chromatin with sequencing (ATAC) with select antigen profiling by sequencing (ASAPseq), provides a combination of chromatin accessibility assessments with measurements of cell-surface marker expression levels. While software exists for the characterization of these datasets, there currently exists no tool explicitly designed to reformat ASAP surface marker FASTQ data into a count matrix which can then be used for these downstream analyses. To address this, we created CountASAP, an easy-to-use Python package purposefully designed to transform FASTQ files from ASAP experiments into count matrices compatible with commonly-used downstream bioinformatic analysis packages. CountASAP takes advantage of the independence of the relevant data structures to perform fully parallelized matches of each sequenced read to user-supplied input ASAP oligos and unique cell-identifier sequences.

bioinformatics↗

bioRxiv2023

Multiplexed Methylated DNA Immunoprecipitation Sequencing (Mx-MeDIP-Seq) to Study DNA Methylation Using Low Amounts of DNA

DNA methylation is an epigenetic mark that has a crucial role in regulating gene expression. Aberrant DNA methylation results in severe diseases in humans, such as cancer, autoimmune disease, atherosclerosis, and cardiovascular diseases. Whole-genome bisulfite sequencing and methylated DNA immunoprecipitation are available to study DNA methylation changes, but they are typically used on a few samples at a time. Here, we developed a novel method called Multiplexed Methylated DNA Immunoprecipitation Sequencing (Mx-MeDIP-Seq), that can be used to analyze many DNA samples in parallel, requiring only small amounts of input DNA. In this method, 10 different DNA samples were fragmented, purified, barcoded, and pooled prior to immunoprecipitation. In a head-to-head comparison, we observed 99% correlation between MeDIP-Seq performed individually or combined as Mx-MeDIP-Seq. Moreover, multiplexed MeDIP led to more than 95% normalized percent recovery and a 25-fold enrichment ratio by qPCR, like the enrichment of the conventional method. This technique was successfully performed with as little as 25 ng of DNA, equivalent to 3400 to 6200 cells. Up to 10 different samples were processed simultaneously in a single run. Overall, the Mx-MeDIP-Seq method is cost-effective with faster processing to analyze DNA methylome, making this technique more suitable for high-throughput DNA methylome analysis.

genomics↗