Biology subjects

Bo, S.

Publications and source records attributed to Bo, S..

6 recordsLinked to original sources

bioRxiv2026

Perm1 Gene Therapy Mitigates PRDM16-Associated Cardiomyopathy

BackgroundPathogenic variants in PR domain containing 16 (PRDM16) cause pediatric and adult cardiomyopathies characterized by ventricular dilation, systolic dysfunction, and impaired metabolic maturation. Cardiac deficiency of PRDM16 alters metabolic gene expression and long-chain fatty acid (FA) metabolites. However, the downstream mediators involved are not well characterized. Furthermore, whether improving mitochondrial FA metabolism can prevent PRDM16-associated cardiomyopathy is currently unknown. MethodsIn vivo and in vitro approaches using patient-induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) and mouse models with Prdm16 deletion/mutation were employed. Transcriptomics and proteomics analyses were conducted, and adeno-associated virus (AAV)-mediated therapy was tested. ResultsHere, we show that a defect in FA metabolism is an early hallmark of PRDM16 cardiac deficiency. We show, for the first time, that PERM1 is a direct downstream target of PRDM16 and is involved in the regulation of FA metabolism through coordinated action with PGC1. Most importantly, neonatal delivery of AAV9-Perm1 in cardiac-specific Prdm16 knockout (Prdm16 cKO) mice markedly improved contractile parameters, reduced left ventricular (LV) dilation, and extended survival. These cardioprotective effects of PERM1 gene therapy occurred independent of restoring FA oxidation. Transcriptional and proteomic analyses of AAV-Perm1-treated Prdm16 cKO mice demonstrated significant improvements in mitochondrial cristae architecture, preservation of sarcomere organization, reduced cardiomyocyte apoptosis, attenuated myocardial fibrosis, and diminished cardiac remodeling. ConclusionsWe identify PERM1 as a direct downstream effector of PRDM16 and uncover a previously unrecognized PRDM16-PGC1-PERM1 axis essential for FA metabolic regulation in the heart. Perm1 gene therapy ameliorated PRDM16-associated cardiomyopathy through post-transcriptional mechanisms involving preservation of mitochondrial and sarcomere integrity. The current study provides preclinical evidence suggesting that Perm1 gene therapy may be a promising therapeutic target to improve the cardiac outcomes of patients affected by pathogenic PRDM16 variants.

physiology↗

bioRxiv2026

A Novel Glycoproteomics Platform for High-Throughput Identification of Disease-Associated Glycoforms

Glycosylation is a critical post-translational modification, and its aberrant forms are potent disease biomarkers; however, the comprehensive, site-specific identification of all glycosites and glycoforms across an entire proteome remains prohibitively slow and computationally demanding. To address this bottleneck and accelerate biomarker discovery, we introduce the Glycoproteomics Data Analysis Software (GDAS), a novel, high-throughput platform designed to provide confident, proteome-scale identification of disease-specific glycoforms. GDAS streamlines the analysis through a core, multi-step workflow: it initially employs an ultrafast open search (e.g., MSFragger-Glyco) on mass spectrometry data to rapidly screen and statistically reduce the vast proteome database to a manageable subset of significantly regulated glycoproteins, conserving computational resources for subsequent, in-depth, targeted N- and O-glycosylation analysis using specialized tools (e.g., GlycReSoft and O-Pair). Furthermore, a unique Final Analysis Module utilizes an advanced statistical and machine learning pipeline (incorporating Bootstrap/Bayesian methods, XGBoost, and Random Forest) to integrate quantitative results and generate a robust, comprehensive glycosylation score. We demonstrate GDASs power to recognize biologically relevant glycosylation changes in targeted proteins by validating it using published Alzheimers disease data. GDAS can be downloaded from https://github.com/yang-lab/GDAS. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=92 SRC="FIGDIR/small/708406v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@189b270org.highwire.dtl.DTLVardef@1221045org.highwire.dtl.DTLVardef@15a3f50org.highwire.dtl.DTLVardef@1f2d43f_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

Transport kinetics across interfaces between coexisting liquid phases

Biomolecular condensates provide compartments that organize biological processes in the cell. Spatial organization of condensates relies on transport across phase boundaries. We investigate the kinetics of molecule transport across interfaces in phase-separated mixtures. Using non-equilibrium thermodynamics we derive the interfacial kinetics, describing the movement of the interface, and of molecular transport across the interface. In the limit of a thin interface, we show that breaking local equilibrium at the interface introduces a local transport resistance. Subsequently, using a continuum approach, we explore two physical scenarios where such a resistance emerges: a mobility minimum and a potential barrier at the interface. These scenarios lead to the same effective transport model in the sharp interface limit, characterized by a single interface resistance parameter. We discuss experimental conditions for which interface resistance could be observed and how these scenarios could be distinguished.

biophysics↗

bioRxiv2022

Protein Optimization Evolving Tool (POET) based on Genetic Programming

Proteins are used by scientists to serve a variety of purposes in clinical practice and laboratory research. To optimize proteins for greater function, a variety of techniques have been developed. For the development of reporter genes used in Magnetic Resonance Imaging (MRI) based on Chemical Exchange Saturation Transfer (CEST), these techniques have encountered a variety of challenges. Here we develop a mechanism of protein optimization using a computational approach known as "genetic programming". We developed an algorithm called Protein Optimization Evolving Tool (POET). Starting from a small library of literature values, use of this tool allowed us to develop proteins which produce four times more MRI contrast than what was previously state-of-the-art. Next, we used POET to evolve peptides that produced CEST-MRI contrast at large chemical shifts where no other known peptides have previously demonstrated contrast. This demonstrated the ability of POET to evolve new functions in proteins. Interestingly, many of the peptides produced using POET were dramatically different with respect to their sequence and chemical environment than existing CEST producing peptides, and challenge prior understandings of how those peptides function. This suggests that unlike existing algorithms for protein engineering that rely on divergent evolution, POET relies on convergent evolution.

synthetic biology↗

bioRxiv2021

Stochastic dynamics of single molecules across phase boundaries

We discuss the stochastic trajectories of single molecules in a phase-separated liquid, when a dense and a dilute phase coexist. Starting from a continuum theory of macroscopic phase separation we derive a stochastic Langevin equation for molecular trajectories that takes into account thermal fluctuations. We find that molecular trajectories can be described as diffusion with drift in an effective potential, which has a steep gradient at phase boundaries. We discuss how the physics of phase coexistence affects the statistics of molecular trajectories and in particular the statistics of displacements of molecules crossing a phase boundary. At thermodynamic equilibrium detailed balance imposes that the distributions of displacements crossing the phase boundary from the dense or from the dilute phase are the same. Our theory can be used to infer key phase separation parameters from the statistics of single-molecule trajectories. For simple Brownian motion, there is no drift in the presence of a concentration gradient. We show that interactions in the fluid give rise to an average drift velocity in concentration gradients. Interestingly, under non-equilibrium conditions, single molecules tend to drift uphill the concentration gradient. Thus, our work bridges between single-molecule dynamics and collective dynamics at macroscopic scales and provides a framework to study single-molecule dynamics in phase-separating systems.

biophysics↗

bioRxiv2021

Quantitative Theory for the Diffusive Dynamics of Liquid Condensates

To unravel the biological functions of membraneless liquid condensates it is crucial to develop a quantitative understanding of the physics underlying their dynamics. Key processes within such condensates are diffusion and material exchange with their environment. Experimentally, diffusive dynamics are typically probed via fluorescent labels. However, to date we lack a physics-based quantitative framework for the dynamics of labeled condensate components. Here, we derive the corresponding theory, building on the physics of phase separation, and quantitatively validate this framework via experiments. We show that using our theory we can precisely determine diffusion coefficients inside liquid condensates via a spatio-temporal analysis of fluorescence recovery after photobleaching (FRAP) experiments. We showcase the accuracy and precision of our approach by considering space- and time-resolved data of protein condensates and two different polyelectrolyte-coacervate systems. Strikingly, our theory can also be used to determine the diffusion coefficient in the dilute phase and the partition coefficient, without relying on fluorescence measurements in the dilute phase. This bypasses recently described quenching artefacts in the dense phase, which can underestimate partition coefficients by orders of magnitude. Our experimentally verified theory opens new avenues for theoretically describing molecule dynamics in condensates, measuring concentrations based on the dynamics of fluorescence intensities and quantifying rates of biochemical reactions in liquid condensates.

biophysics↗