Biology subjects

Jayaram, A.

Publications and source records attributed to Jayaram, A..

5 recordsLinked to original sources

bioRxiv2025

Mechanotransduction and Biophysical Regulation of Fibroblast Plasticity Under Prolonged Shear Stress

Complex interactions between mechanical stimuli and biochemical signaling shape the evolving fibrotic milieu. Fibroblasts contribute to this process, transitioning into myofibroblasts on stiffer substrates, and under low shear in 3D environments. The time-dependent effects of prolonged physiological shear stress on fibroblasts however remain poorly understood. We demonstrate that sustained shear stress (1.2 Pa) over 12 hours induces a temporal cascade of signaling and biophysical changes, driving fibroblast trans-differentiation into myofibroblasts. Cells adopt a spindle-shaped morphology under shear, actively remodeling through actin and -SMA to form elongated stress fibers. Myofibroblasts exhibit increased vinculin and zyxin expression in mature adhesions that remain elevated post-shear. Traction stresses progressively increased over the shear duration and persisted for 12 hours after the removal of the stimulus, indicating mechanical memory. Post-shear, deadhesion strengths increased significantly, accompanied by shifts in gene expressions governing extracellular matrix homeostasis. Prolonged shear enhanced MSD, directionality, and migration speed, all crucial for effective tissue repair. Finally, we demonstrate temporal changes in the biochemical gene expressions mediating the shear-induced remodeling of the extracellular matrix, cytoskeleton, and focal adhesions during the myofibroblast transition. These findings provide insights into the mechanobiological factors driving fibroblast-to-myofibroblast transitions which may inform the development of mechano-therapeutic strategies.

bioengineering↗

bioRxiv2023

Alpha-synuclein oligomers displace monomeric alpha-synuclein from lipid membranes

Parkinsons disease (PD) is an increasingly prevalent and currently incurable neurodegenerative disorder linked to the accumulation of -synuclein (S) protein aggregates in the nervous system. While S binding to membranes in its monomeric state is correlated to its physiological role, S oligomerisation and subsequent aberrant interactions with lipid bilayers have emerged as key steps in PD-associated neurotoxicity. However, little is known of the mechanisms that govern the interactions of oligomeric S (OS) with lipid membranes and the factors that modulate such interactions. This is in large part due to experimental challenges underlying studies of OS-membrane interactions due to their dynamic and transient nature. Here, we address this challenge by using a suite of microfluidics-based assays that enable in-solution quantification of OS-membrane interactions. We find that OS bind more strongly to highly curved, rather than flat, lipid membranes. By comparing the membrane-binding properties of OS and monomeric S (MS), we further demonstrate that OS bind to membranes with up to 150-fold higher affinity than their monomeric counterparts. Moreover, OS compete with and displace bound MS from the membrane surface, suggesting that disruption to the functional binding of MS to membranes may provide an additional toxicity mechanism in PD. These findings present a unique binding mechanism of oligomers to model membranes, which can potentially be targeted to inhibit the progression of PD. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=62 SRC="FIGDIR/small/533646v2_ufig1.gif" ALT="Figure 1"> View larger version (10K): org.highwire.dtl.DTLVardef@4ab089org.highwire.dtl.DTLVardef@18c0709org.highwire.dtl.DTLVardef@220077org.highwire.dtl.DTLVardef@4c85b9_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2022

Selenium Silk Nanostructured Films for Antifungal and Antibacterial Treatments

The rapid emergence of drug-resistant bacteria and fungi poses a threat for healthcare worldwide. The development of novel effective small molecule therapeutic strategies in this space has remained challenging. An orthogonal approach, therefore, is to explore biomaterials with physical modes of action which have the potential to generate antimicrobial activity and in some cases even prevent antimicrobial resistance. Here, to this effect, we describe an approach for forming silk-based films that contain embedded selenium nanoparticles. We show that these materials exhibit both antibacterial and antifungal properties while crucially also remaining highly biocompatible and non-cytotoxic towards mammalian cells. By incorporating the nanoparticles into silk films, the protein scaffold acts in a two-fold manner; it protects the mammalian cells from the cytotoxic effects of the bare nanoparticles, while also providing a template for bacterial and fungal eradication. A range of hybrid inorganic/organic films were produced and an optimum concentration was found, which allowed for both high bacterial and fungal death while also exhibiting low mammalian cell cytotoxicity. Such films can thus pave the way for next generation antimicrobial materials for applications such as wound healing and as agents against topical infections, with the added benefit that bacteria and fungi are unlikely to develop antimicrobial resistance to these hybrid materials.

microbiology↗

bioRxiv2022

Treatment-mediated selection of lethal prostate cancer clones defined by copy number architectures

Despite initial responses to hormone treatment, metastatic prostate cancer invariably evolves to a lethal state. To characterize the intra-patient relationships of metastases that evade treatment, we performed genomewide copy number profiling and bespoke approaches targeting the androgen receptor (AR) on 142 metastatic regions from 10 organs harvested post-mortem from nine men who died from prostate cancer. We identified diverse and patient-unique alterations clustering around the AR in metastases from every patient with evidence of independent acquisition of related genomic changes within an individual and, in some patients, the co-existence of AR-neutral clones. Using the genomic boundaries of pan-autosome copy number change, we confirmed a common clone of origin across metastases and diagnostic biopsies; and identified in individual patients, clusters of metastases occupied by dominant clones with diverged autosomal copy number alterations. Autosome-defined clusters were characterized by cluster-specific AR gene architectures that in two index cases were topologically more congruent than by chance (p-values 0.03, 3.07x10-8). Integration with anatomical site suggested patterns of spread and points of genomic divergence. Copy number boundaries identified treatment-selected clones with putatively distinct lethal trajectories. Statement of significanceLethal prostate cancer evolves from a single clone of origin and upon a treatment-mediated selection, progresses to lethal disease via a limited number of related clones harboring patient-unique androgen receptor gene architectures.

cancer biology↗

bioRxiv2018

Identification of single nucleotide variants using position-specific error estimation in deep sequencing data

BackgroundTargeted deep sequencing is a highly effective technology to identify known and novel single nucleotide variants (SNVs) with many applications in translational medicine, disease monitoring and cancer profiling. However, identification of SNVs using deep sequencing data is a challenging computational problem as different sequencing artifacts limit the analytical sensitivity of SNV detection, especially at low variant allele frequencies (VAFs).\n\nMethodsTo address the problem of relatively high noise levels in amplicon-based deep sequencing data (e.g. with the Ion AmpliSeq technology) in the context of SNV calling, we have developed a new bioinformatics tool called AmpliSolve. AmpliSolve uses a set of normal samples to model position-specific, strand-specific and nucleotide-specific background artifacts (noise), and deploys a Poisson model-based statistical framework for SNV detection.\n\nResultsOur tests on both synthetic and real data indicate that AmpliSolve achieves a good trade-off between precision and sensitivity, even at VAF below 5% and as low as 1%. We further validate AmpliSolve by applying it to the detection of SNVs in 96 circulating tumor DNA samples at three clinically relevant genomic positions and compare the results to digital droplet PCR experiments.\n\nConclusionsAmpliSolve is a new tool for in-silico estimation of background noise and for detection of low frequency SNVs in targeted deep sequencing data. Although AmpliSolve has been specifically designed for and tested on amplicon-based libraries sequenced with the Ion Torrent platform it can, in principle, be applied to other sequencing platforms as well. AmpliSolve is freely available at https://github.com/dkleftogi/AmpliSolve.

genomics↗