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Chu, B.

Publications and source records attributed to Chu, B..

14 recordsLinked to original sources

Membrane-anchored influenza neuraminidase vaccine drives human-like broadly protective B cell responses

Influenza neuraminidase (NA) is a promising target for universal flu vaccines, yet eliciting potent B-cell responses against its conserved epitopes remains challenging. Here, we developed a membrane-anchored, folding-domain-free NA (mNA) that elicited superior head-specific germinal center B cell and antibody responses compared to soluble tetrameric NA. In non-human primates, mNA immunization induced cross-reactive memory B cell (MBC) responses, expanding clones with the conserved "DR" motif in HCDR3, a hallmark of human broadly reactive NA antibodies. These MBCs conferred cross-inhibitory activity against diverse NA variants and in vivo cross-protection. Cryo-EM analysis revealed that the 554-C2 clone targets the conserved enzymatic pocket via the "DR" motif, while the 554-C1 clone recognizes previously uncharacterized epitopes at the interface between two adjacent N2 monomers, effectively reducing plaque formation by contemporary H3N2 strains. Our findings highlight the immunological advantages of membrane-anchoring, providing a robust strategy for designing next-generation vaccines against influenza and other pathogens.

immunology↗

Engineered subtilisin protease degrades active KRAS in cancer cells, leading to differential cell targeting

Controlling aberrant RAS signaling has been the subject of intensive efforts aimed at developing specific RAS inhibitors, small molecules that promote RAS degradation, and monobodies that inhibit RAS activity. Direct proteolytic degradation of RAS by site-specific proteases has received considerably less attention. A naturally-occurring protease from Vibrio vulnificus toxin cleaves all RAS isoforms at switch I and attenuates RAS signaling in cell models and patient-derived xenografts, thus demonstrating the potential of this approach. We previously designed a RAS-specific protease, called RASProtease (or RASp), that site-specifically cleaves RAS at switch II. Attacking switch II leverages an order to disorder transition that this region undertakes upon conversion to the active form that predominates in cancer. Switch II participates in an allosteric network that controls KRAS oncogenicity, making it a promising target for proteolytic cleavage that modulates RAS signaling. Preferential targeting of active RAS could be particularly useful for studying RAS signaling networks as well as having potential therapeutic value. Here we examined the effects of RASp cleavage on downstream signaling and cell viability in the MIA PaCa-2 cancer cell model, which harbors homozygous KRAS G12C and is KRAS-dependent for growth and survival. We found that cleavage of KRAS G12C coincided with a decrease in MEK-ERK signaling and resulted in extensive MIA PaCa-2 cell death 24 hours after induction of RASp expression. This level of cell death far exceeded that of control HEK 293T cells under the same conditions, underscoring the vulnerability of this cancer cell model to KRAS G12C elimination.

cancer biology↗

Substrate specificity in a designed RAS-targeting protease is coupled to active site and distal motions

Designing proteases with tailored substrate specificity has emerged as a powerful strategy for manipulating protein function in cells. RAS, a key regulator of cell survival and proliferation, is a compelling target for such approaches. Mutations in RAS are involved in about one-third of all human cancers and drive the hyperactive signaling that promotes tumorigenesis, growth, and metastasis in cancers such as pancreatic and lung cancer. This creates a pressing need for strategies capable of modulating mutant RAS with high substrate specificity to avoid unintended cleavage events. As a model for targeted proteolysis, we present the high-resolution crystal structures of RASProtease(II), which provide a detailed view of the enzymes active site and substrate-binding architecture. Kinetic experiments showed that cleavage of the cognate QEEYSAM substrate is approximately 30-fold faster than the non-cognate QEEISAM, demonstrating strong proteolytic selectivity. NMR dynamics studies combined with structural mapping revealed that substrate binding modulates not only the active site, but also distal regions of RASProtease(II), uncovering long-range allosteric networks. Contrary to the conventional view that non-cognate substrates are simply poor fits for the active site, we found that binding of the non-cognate peptide induces a greater amount of conformational dynamics in the protease than in the apo form or cognate complex, resulting in significant destabilization and providing a mechanistic explanation for the reduced catalytic efficiency. These results reveal how distal structural networks help define substrate specificity and provide principles for rationally designing proteases with enhanced specificity for therapeutic applications. Significance StatementDesigner proteases are gaining interest for their potential as therapeutic agents. It is therefore critical to understand the mechanisms that differentiate cognate and non-cognate sequences to minimize deleterious off-target cleavage events. While the conventional view is that non-cognate substrates are simply poor fits for the active site, we demonstrate here that dynamic allostery plays an integral role in distinguishing between cognate and off-target sequences, using a protease designed to target the oncoprotein RAS as our model system. Moreover, because the RASProtease is derived from a prototypical serine protease, subtilisin, it is likely that the overall mechanism employed for selecting cognate over non-cognate substrates presented here will be generalizable, providing principles for designing enhanced specificity in a wide range of proteases.

biochemistry↗

Uncovering Heterogeneous Effects via Localized Feature Selection

Identifying features that interact to trigger disease, while accounting for heterogeneity across diverse populations, is essential for the development of precision and targeted medicine. Despite the availability of vast and complex health-related datasets, most existing works focus on identifying disease-associated features at the population level or within a few subpopulations, often overlooking individual-level heterogeneity within these groups. To address this limitation, we propose a novel framework that utilizes localized test statistics to identify disease-associated features tailored to individual profiles. Our method leverages the recently developed knockoffs methodology to control the noise level of the selection set so that the results are replicable. Moreover, it allows for the discovery of hidden heterogeneous effects within the data, as demonstrated in an application to single-cell RNA sequencing data for Alzheimers disease. By aggregating localized feature selection results, our framework also enables powerful population-level feature selection. Our framework provides a powerful tool for exploratory studies of precision medicine, offering the potential to generate novel hypotheses for confirmatory biological experiments.

bioinformatics↗

It's a wrap: deriving distinct discoveries with FDR control after a GWAS pipeline

The standard analysis pipeline for genome-wide association studies (GWAS) is based on marginal tests of association. These are computationally convenient and portable, but the discoveries resulting from their rejections are not immediately interpretable, and require post-processing as "clumping" and "fine mapping." An interesting alternative is provided by conditional independence hypotheses: their rejections lead to the identification of distinct signals across the genome, accounting for measured confounders, and pointing to separate causal pathways. An obstacle to the wide adoption of this approach has been that it requires access to individual level data. Overcoming this barrier, recent work has shown how summary statistics resulting from the standard marginal GWAS analysis can be used as input of a procedure to test conditional independence hypotheses while controlling the false discovery rate. This secondary analysis requires sampling of synthetic negative controls (knockoffs) from a distribution determined by the linkage disequilibrium patterns in the genome of the population under study. In prior work, we have pre-computed this distribution for European genomes, starting from information derived from the UK Biobank. Thus, researchers working with GWAS in a European population can carry out a knockoff analysis with minimal computational costs, using the distributed routine GhostKnockoffGWAS. Here we introduce and release a new software (solveblock) that extends this capability to a much richer collection of studies. Given a set of genotyped samples, or a reference dataset, our pipeline efficiently estimates the high-dimensional correlation matrices that describe dependencies across the genome, making rather common sparsity assumptions. Taking this sample-specific estimate as input, the software identifies groups of genetic variants that are highly correlated, and uses them to define an appropriate resolution for conditional independence hypotheses. Finally, we compute the distribution for the exchangeable negative controls necessary to test these hypotheses. The output of solveblock can be passed directly to GhostKnockoffGWAS, allowing users to carry out the complete analysis in a two step procedure. Simulations, based on five UK Biobank sub-populations, illustrate the methods FDR control. The analysis of 26 phenotypes of varying polygenicity in British individuals, results in{approx} 19 additional discoveries, compared to standard marginal association testing. Our code, precompiled software, and processed files for these five sub-populations are openly shared.

genetics↗

Transient Formation of Supramolecular Complexes Between Hyaluronan and Oligopeptides at Submicromolar Concentration

Charged polymer interactions govern critical biological and technological processes by altering the structure and dynamics of the surrounding aqueous environment. How-ever, studying these interactions and the resulting environments across a broad concentration range is challenging, as it demands a combination of multiple techniques with varying resolutions and complex data interpretation. In particular, detecting interactions at submicromolar levels remains technically challenging, with most methods lacking the resolution required for molecular-level characterization. Here, we examined the interactions between high-molecular-weight hyaluronan (HA), a biologically and technologically relevant polymer, and a series of model oligopeptides--nonaarginine, nonalysine, and nonaglycine, chosen for their charge and side-chain chemistry. Using angle-resolved second harmonic scattering (AR-SHS), multi-angle dynamic light scattering, nuclear magnetic resonance spectroscopy, and all-atom molecular dynamics simulations, we captured a detailed molecular picture of HA-peptide interactions across a broad concentration range, including submicromolar concentrations. We found selective and multivalent interactions between HA and positively charged peptides, which are consistently stronger with nonaarginine. These interactions trigger significant solvent and solute remodeling, including nanoscale HA-peptide clustering. Our molecular simulations provide essential atomic-level interpretation of the experimental data, elucidating the transient and dynamic nature of the intermolecular interactions and the underlying processes of molecular aggregation and induced water reorientation. The distinct behavior found in arginine-rich peptides highlights their potential in modulating extracellular environments and as peptide-based drug delivery systems. Moreover, our methodological framework, combining sensitive AR-SHS signals with atomistic simulations and traditional structural techniques, offers unprecedented molecular insight into complex polymer-peptide interactions, laying the groundwork for future research on dynamic supramolecular systems in soft materials and unstructured biological environments such as the extracellular matrix.

biophysics↗

Hypoxia-induced histone methylation and NF-κB activation in pancreas cancer fibroblasts promote EMT-supportive growth factor secretion

The pancreatic ductal adenocarcinoma (PDAC) tumor microenvironment contains hypoxic tissue subdomains and cancer-associated fibroblasts (CAFs) of multiple subtypes that play tumor-promoting and -restraining roles. Here, we demonstrate that hypoxia promotes an inflammatory-like CAF phenotype and that hypoxic CAFs selectively promote epithelial-mesenchymal transition (EMT) in PDAC cancer cells through growth factor-mediated cell crosstalk. By analyzing patient tumor single-cell transcriptomics and conducting an inhibitor screen, we identified IGF-2 and HGF as specific EMT-inducing growth factors produced by hypoxic CAFs. We further found that reactive oxygen species-activated NF-{kappa}B cooperates with hypoxia-dependent histone methylation to promote IGF-2 and HGF expression in hypoxic CAFs. In lineage-traced autochthonous PDAC mouse tumors, hypoxic CAFs resided preferentially near hypoxic, mesenchymal cancer cells. However, in subcutaneous tumors engineered with hypoxia fate-mapped CAFs, once-hypoxic re-oxygenated CAFs lacked a spatial correlation with mesenchymal cancer cells. Thus, hypoxia promotes reversible CAF-malignant cell interactions that drive EMT through druggable signaling pathways. One-sentence summaryWe show that hypoxic fibroblasts in pancreas cancer leverage histone methylation and ROS-mediated NF-{kappa}B activation to produce growth factors that drive epithelial-mesenchymal transition in malignant cells, demonstrating how tumor stromal features cooperate to initiate a signaling process for disease progression.

cancer biology↗

In silico identification of putative causal genetic variants

Understanding the causal genetic architecture of complex phenotypes will fuel future research into disease mechanisms and potential therapies. Here, we illustrate the power of a novel framework: it detects, starting from summary statistics, and across the entire genome, sets of variants that carry non-redundant information on the phenotypes and are therefore more likely to be causal in a biological sense. The approach, implemented in open-source software, is also computationally efficient, requiring less than 15 minutes on a single CPU to perform genome-wide analysis. Through extensive genome-wide simulation studies, we show that the method can substantially outperform existing methods in false discovery rate control, statistical power and various fine-mapping criteria. In applications to a meta-analysis of ten large-scale genetic studies of Alzheimers disease (AD), we identified 82 loci associated with AD, including 37 additional loci missed by conventional GWAS pipeline. Massively parallel reporter assays and CRISPR-Cas9 experiments have confirmed the functionality of the putative causal variants our method points to. Finally, we retrospectively analyzed summary statistics from 67 large-scale GWAS for a variety of phenotypes. Results reveal the methods capacity to robustly discover additional loci for polygenic traits and pinpoint potential causal variants underpinning each locus beyond conventional GWAS pipeline, contributing to a deeper understanding of complex genetic architectures in post-GWAS analyses.

genetics↗

Fine-tuning of SUMOylation modulates drought tolerance

SUMOylation is involved in various aspects of plant biology, including drought stress. However, the relationship between SUMOylation and drought stress tolerance is complex; whether SUMOylation has a crosstalk with ubiquitination in response to drought stress remains largely unclear. In this study, we found that both increased and decreased SUMOylation led to increased survival of apple (Malus x domestica) under drought stress: both transgenic MdSUMO2A overexpressing (OE) plants and MdSUMO2 RNAi plants exhibited enhanced drought tolerance. We further confirmed that MdDREB2A is one of the MdSUMO2 targets. Both transgenic MdDREB2A OE and MdDREB2AK192R OE plants (which lacked the key site of SUMOylation by MdSUMO2A) were more drought tolerant than wild-type plants. However, MdDREB2AK192R OE plants had a much higher survival rate than MdDREB2A OE plants. We further showed SUMOylated MdDREB2A was conjugated with ubiquitin by MdRNF4 under drought stress, thereby triggering its protein degradation. In addition, MdRNF4 RNAi plants were more tolerant to drought stress. These results revealed the molecular mechanisms that underlie the relationship of SUMOylation with drought tolerance and provided evidence for the tight control of MdDREB2A accumulation under drought stress mediated by SUMOylation and ubiquitination.

plant biology↗

A Modular Master Regulator Landscape Determines the Impact of Genetic Alterations on the Transcriptional Identity of Cancer Cells

Despite considerable pan-cancer efforts, the link between genomics and transcriptomics in cancer remains relatively weak and mostly based on statistical rather than mechanistic principles. By performing integrative analysis of transcriptomic and mutational profiles on a sample-by-sample basis, via regulatory/signaling networks, we identified a repertoire of 407 Master-Regulator proteins responsible for canalizing the genetics of 20 TCGA cohorts into 112 transcriptionally-distinct tumor subtypes. Further analysis highlighted a highly-recurrent regulatory architecture (oncotecture) with Master-Regulators organized into 24 modular MR-Blocks, regulating highly-specific tumor-hallmark functions and predictive of patient outcome. Critically, >50% of the somatic alterations identified in individual samples were in proteins affecting Master-Regulator activity, thus yielding novel insight into mechanisms linking tumor genetics and transcriptional identity and establishing novel non-oncogene dependencies. Experimental validation of functional mutations upstream of the most conserved MR-Block confirmed their ability to affect MR-protein activity, suggesting that the proposed methodology may effectively complement and extend current pan-cancer knowledge.

bioinformatics↗

A DNA G-quadruplex/i-motif hybrid

DNA can form many structures beyond the canonical Watson-Crick double helix. It is now clear that noncanonical structures are present in genomic DNA and have biological functions. G-rich G-quadruplexes and C-rich i-motifs are the most well-characterized noncanonical DNA motifs that have been detected in vivo with either proscribed or postulated biological roles. Because of their independent sequence requirements, these structures have largely been considered distinct types of quadruplexes. Here, we describe the crystal structure of the DNA oligonucleotide, d(CCAGGCTGCAA), that self-associates to form a quadruplex structure containing two central antiparallel G-tetrads and six i-motif C-C+ base pairs. Solution studies suggest a robust structural motif capable of assembling as a tetramer of individual strands or as a dimer when composed of tandem repeats. This hybrid structure highlights the growing structural diversity of DNA and suggests that biological systems may harbor many functionally important non-duplex structures.

biochemistry↗

Ca2+-activated K+ channels reduce network excitability, improving adaptability and energetics for transmitting and perceiving sensory information

Ca2+-activated K+ channels (BK and SK) are ubiquitous in synaptic circuits, but their role in network adaptation and sensory perception remains largely unknown. Using electrophysiological and behavioral assays and biophysical modelling, we discover how visual information transfer in mutants lacking the BK channel (dSlo-), SK channel (dSK-) or both (dSK-;;dSlo-) is shaped in the Drosophila R1-R6 photoreceptor-LMC circuits (R-LMC-R system) through synaptic feedforward-feedback interactions and reduced R1-R6 Shaker and Shab K+ conductances. This homeostatic compensation is specific for each mutant, leading to distinctive adaptive dynamics. We show how these dynamics inescapably increase the energy cost of information and distort the mutants motion perception, determining the true price and limits of homeostatic compensation in an in vivo genetic animal model. These results reveal why Ca2+-activated K+ channels reduce network excitability (energetics), improving neural adaptability for transmitting and perceiving sensory information.\n\nHighlightsO_LIHomeostatic plasticity in Drosophila dSlo-, dSK- and dSK-;;dSlo- null-mutants retains R1-R6 photoreceptors light information sampling while reducing other K+-conductances\nC_LIO_LIAs mutant R-LMC-R circuits rebalance synaptic loads homeostatically, R1-R6s become more depolarized, with dSK- and dSK-;;dSlo- responding faster and dSlo- slower, whilst LMC outputs oscillate, with dSK- responding faster and dSK-;;dSlo- and dSlo- slower than wild-type\nC_LIO_LIHomeostatic compensation in the mutant circuits impedes adaptation, increases the energy cost of visual information and distorts optomotor behavior\nC_LIO_LIHence, Ca2+-activated K+ channels improve adaptability and energetics for transmitting and perceiving sensory information\nC_LI

neuroscience↗

Hydrodynamics of transient cell-cell contact: The role of membrane permeability and active protrusion length

In many biological settings, two or more cells come into physical contact to form a cell-cell interface. In some cases, the cell-cell contact must be transient, forming on timescales of seconds. One example is offered by the T cell, an immune cell which must attach to the surface of other cells in order to decipher information about disease. The aspect ratio of these interfaces (tens of nanometers thick and tens of micrometers in diameter) puts them into the thin-layer limit, or \"lubrication limit\", of fluid dynamics. A key question is how the receptors and ligands on opposing cells come into contact. What are the relative roles of thermal undulations of the plasma membrane and deterministic forces from active filopodia? We use a computational fluid dynamics algorithm capable of simulating 10-nanometer-scale fluid-structure interactions with thermal fluctuations up to seconds-and microns-scales. We use this to simulate two opposing membranes, variously including thermal fluctuations, active forces, and membrane permeability. In some regimes dominated by thermal fluctuations, proximity is a rare event, which we capture by computing mean first-passage times using a Weighted Ensemble rare-event computational method. Our results demonstrate that the time-to-contact increases for smaller cell-cell distances (where the thin-layer effect is strongest), leading to an optimal initial cell-cell separation for fastest receptor-ligand binding. We reproduce a previous experimental observation that fluctuation spatial scales are largely unaffected, but timescales are dramatically slowed, by the thin-layer effect. We also find that membrane permeability would need to be above physiological levels to abrogate the thin-layer effect.\n\nAuthor summaryThe elastohydrodynamics of water in and around cells is playing an increasingly recognized role in biology. In this work, we investigate the flow of extracellular fluid in between cells during the formation of a cell-cell contact, to determine whether its necessary evacuation as the cells approach is a rate-limiting step before molecules on either cell can interact. To overcome the computational challenges associated with simulating fluid in this mechanically soft, stochastic and high-aspect-ratio environment, we extend a computational framework where the cell plasma membranes are treated as immersed boundaries in the fluid, and combine this with computational methods for simulating stochastic rare events in which an ensemble of simulations are given weights according to their probability. We find that the internal dynamics of the membranes has speeds in approximately microseconds, but that as the cells approach, a new slow timescale of approximately milliseconds is introduced. Thermal undulations nor typical amounts of membrane permeability can overcome the timescale, but active forces, e.g., from the cytoskeleton, can. Our results suggest an explanation for differences in molecular interactions in live cells compared to in vitro reconstitution experiments.

biophysics↗

Detection of live mycobacteria with a solvatochromic trehalose probe for point-of-care tuberculosis diagnosis

AbstractTuberculosis (TB) is the leading cause of death from an infectious bacterial disease. Poor diagnostic tools to detect active disease plague TB control programs and affect patient care. Accurate detection of live Mycobacterium tuberculosis (Mtb), the causative agent of TB, will improve TB diagnosis and patient treatment. We report that live mycobacteria can be specifically detected with a fluorogenic trehalose analog. We designed a 4-N,N-dimethylamino-1,8- naphthalimide-trehalose (DMN-Tre) conjugate that undergoes >700-fold fluorescence increase when transitioned from aqueous to hydrophobic environments. This enhancement occurs upon metabolic conversion of DMN-Tre to trehalose monomycolate and incorporation into the outer membrane. DMN-Tre labeling enabled the rapid, no-wash visualization of mycobacterial and corynebacterial species without nonspecific labeling of Gram-positive or -negative bacteria. DMN-Tre labeling was selective for live mycobacteria and was reduced by treatment with TB drugs. Lastly, DMN-Tre labeled Mtb in TB-positive sputum samples suggesting this operationally simple method may be deployable for TB diagnosis.

microbiology↗