Biology subjects

Chen, W.-C.

Publications and source records attributed to Chen, W.-C..

13 recordsLinked to original sources

bioRxiv2026

Quantitative Donor Histology and Transcriptomics Link Pancreatic Composition and Precancers Across the Adult Lifespan

Background & Aims: Pancreatic intraepithelial neoplasia (PanIN) is the primary precursor to invasive pancreatic ductal adenocarcinoma (PDAC). While PanIN is common in the general population, PDAC is rare. PDAC risk rises with age, diabetes mellitus, and obesity, but whether this increased risk reflects a greater precancer burden is unknown, as previous studies assessed PanIN presence and grade. We aimed to quantify pancreatic composition and PanIN burden across the adult lifespan to identify demographics of donors carrying disproportionate precancer burden. Methods: We applied CODAvision, a deep-learning segmentation pipeline, to 410 high-quality pancreas sections from Genotype-Tissue Expression (GTEx) donors aged 21 to 70 years. We screened twenty-seven donor phenotypes against 14 compositional measures, applying Benjamini-Hochberg correction for multiple testing. We further related tissue composition and donor phenotype to bulk gene expression in 281 donors to understand which demographics are associated with a compositional or transcriptional fingerprint. Results: PanIN was present in 83% of donors. Acinar proportion declined with age, offset by fat and stroma. Median PanIN burden did not change with age, though the fitted 90th percentile rose from 0.21% to 0.72% of exocrine tissue (uncorrected P=.002). The 39 sections (10%) with high-outlier PanIN burden came disproportionately from donors with type 2 diabetes mellitus and hypertension and had greater stromal proportion and higher fibroblast and immune-cell densities. Both cell types were denser in peri-PanIN stroma than in the surrounding pancreatic parenchyma. PanIN abundance was associated with a gastric transcriptional signature including VSIG1, TFF1, and MUC5AC. Conclusions: Most donors carried little PanIN at any age, whereas high burden was concentrated in a minority of donors more likely to have type 2 diabetes mellitus, hypertension, and inflamed, fibrotic stroma. Because PanIN was present in most donors, its presence did not distinguish high-risk groups, whereas quantitative burden did, concentrating on the metabolic phenotypes already under consideration for pancreatic surveillance.

bioinformatics↗

bioRxiv2026

Systematic CRISPRi perturbation of 1,408 autism risk genes maps multilevel transcriptional convergence in human cortical neurons

Genetic heterogeneity in autism spectrum disorder (ASD) complicates the identification of shared molecular pathways amenable to therapeutic intervention. Here, we perform a CRISPRi Perturb-seq screen targeting 1,408 ASD risk genes in human embryonic stem cell-derived immature cortical neurons and profile the resulting transcriptomic effects by single-cell RNA sequencing. We identify 215 ASD risk genes whose repression induces significant global transcriptomic dysregulation. Leveraging this functional atlas, we characterize candidate genes based on transcriptional similarity to established ASD hub genes. We identify gene programs recurrently dysregulated across perturbations, anchored by processes governing microtubule dynamics, neuron differentiation, cell migration, and transmembrane transport. We further identify CHAMP1 as a previously unrecognized regulator of Wnt signaling and define specific ASD risk genes that modulate the rate of cortical neuron differentiation. Analysis of differentially expressed genes reveals both convergent and perturbation-specific downstream transcriptional responses. Together, these findings provide a multilevel map of transcriptomic convergence in ASD and establish a framework for identifying both pathway-level and genotype-specific therapeutic strategies.

neuroscience↗

bioRxiv2026

Electrode Reduction by Vibrio natriegens Depends on Balanced Expression of Multiheme Cytochromes

Multiheme cytochromes c can facilitate electron transfer across the periplasm and outer membrane of Gram-negative bacteria to enable extracellular electron transfer (EET). EET empowers bacteria to maintain redox balance in oxygen-poor environments by donating electrons to solid materials. The resulting electron flux makes EET pathways useful tools for interfacing microorganisms with electronics. Recently, Vibrio natriegens, a marine bacterium notable for its rapid growth and expanding biotechnological applications, was found to perform iron reduction in a multiheme cytochrome c-dependent manner. However, the role of the V. natriegens EET genes in facilitating reduction of electrodes remains unexplored. Through single gene deletion and complementation, we find that each of cymA, pdsA, mtrA, and mtrB are required for production of electrical current by V. natriegens cultures. Curiously, deletion of the outer membrane decaheme cytochrome mtrC diminished but did not abolish electrode reduction. Modulating the induction of expression of mtrA and mtrC revealed that only a narrow range of induction of these decaheme cytochromes allows balanced cytochrome c production and EET. These findings indicate that a multiheme cytochrome-based EET pathway enables V. natriegens to reduce electrodes and that this pathway requires carefully balanced gene expression to function. This characterization of the role of multiheme cytochromes in the electroactivity of an emerging microbial chassis for biotechnology will enable new bioelectronic applications for V. natriegens and new understanding of the metabolic function of EET.

microbiology↗

bioRxiv2025

MULTICLUST - Fast multinomial clustering of multiallelic genotypes to infer genetic population structure

Identifying population structure from multilocus genotype data is key to down-stream genetic analyses, including analysis of genome-wide association (GWAS), genetic genealogy and phylogenetics, in the fields of conservation, forensics, evolution and more. While inference of population structure has been dominated by Bayesian methods, maximum likelihood methods have some benefits in terms of reliability, consistency and efficiency. Here we extend the methods of Tang et al. [53] and Alexander et al. [2] to handle multi-allelic (e.g., SNP, STR, allozyme) and polyploid loci with missing data to infer genetic admixture proportions and subpopulation allele frequencies. Comparative analyses of our method, MULTICLUST, and STRUCTURE [42] on both simulated and empirical data indicate comparable, fast, reproducible, and accurate estimates of population admixture proportions and allele frequencies using MULTICLUST.MULTICLUST is implemented in the C programming language and is publicly accessible via www.github.com/arunsethuraman/multiclust.

evolutionary biology↗

bioRxiv2025

Inference and visualization of complexgenotype-phenotype with gpmap-tools

Understanding how biological sequences give rise to observable traits, that is, how genotype maps to phenotype, is a central goal in biology. Yet our knowledge of genotype-phenotype maps in natural systems is limited due to the high dimensionality of sequence space and the context-dependent effects of mutations. The emergence of Multiplex assays of variant effect (MAVEs), along with large collections of natural sequences, offer new opportunities to empirically characterize these maps at an unprecedented scale. However, tools for statistical and exploratory analysis of these high-dimensional data are still needed. To address this gap, we developed gpmaptools https://github.com/cmarti/gpmap-tools), a python library that integrates a series of models for inference, phenotypic imputation, and error estimation from MAVE data or collections of natural sequences in the presence of genetic interactions of every possible order. gpmap-tools also provides methods for summarizing patterns of epistasis and visualization of genotype-phenotype maps containing up to millions of genotypes. To demonstrate its utility, we used gpmap-tools to infer genotype-phenotype maps containing 262,144 variants of the Shine-Dalgarno sequence from both genomic 5UTR sequences and experimental MAVE data. Visualization of the inferred landscapes consistently revealed high-fitness ridges that link core motifs at different distances from the start codon. In summary, gpmap-tools provides a flexible, interpretable framework for studying complex genotype-phenotype maps, opening new avenues for understanding the architecture of genetic interactions and their evolutionary consequences.

evolutionary biology↗

bioRxiv2025

Benchmarking and optimizing Perturb-seq in differentiating human pluripotent stem cells

Perturb-seq is a powerful approach to systematically assess how genes and enhancers impact the molecular and cellular pathways of development and disease. However, technical challenges have limited its application in stem cell-based systems. Here, we benchmarked Perturb-seq across multiple CRISPRi modalities, on diverse genomic targets, in multiple human pluripotent stem cells, during directed differentiation to multiple lineages, and across multiple sgRNA delivery systems. To ensure cost-effective production of large-scale Perturb-seq datasets as part of the Impact of Genomic Variants on Function (IGVF) consortium, our optimized protocol dynamically assesses experiment quality across the weeks-long procedure. Our analysis of 1,996,260 sequenced cells across benchmarking datasets reveals shared regulatory networks linking disease-associated enhancers and genes with downstream targets during cardiomyocyte differentiation. This study establishes open tools and resources for interrogating genome function during stem cell differentiation.

genomics↗

bioRxiv2025

Multicilia dynamically transduce Shh signaling to regulate choroid plexus functions

Choroid plexus is a major site for cerebrospinal fluid (CSF) production, characterized by a multiciliated epithelial monolayer that regulates CSF production. We demonstrate that defective choroid plexus ciliogenesis or Intraflagellar transport yields neonatal hydrocephalus, at least in part, due to increased water channel Aqp1 and ion transporter Atp1a2 expression. We demonstrate choroid plexus multicilia as sensory cilia, transducing both canonical and non-canonical Shh signaling. Interestingly, it is the non-canonical Shh signaling that represses Aqp1 and Atp1a2 expression by Smo/Gi/cAMP pathway. Choroid plexus multicilia exhibit unique ciliary ultrastructure, carrying features of both primary and motile cilia. Unlike most cilia that elongate during maturation, choroid plexus ciliary length decreases during development, causing a decline of Shh signaling intensity in developing choroid plexus, a derepression of Aqp1 and Atp1a2, and ultimately, an increased CSF production. Hence, developmental dynamics of choroid plexus multicilia dampens the Shh signaling intensity to promote CSF production.

developmental biology↗

bioRxiv2024

Discrete photoentrainment of mammalian central clock is regulated by bi-stable dynamic network in the suprachiasmatic nucleus.

The circadian clock, an evolutionarily conserved mechanism regulating the majority of physiological functions in many organisms, is synchronized with the environmental light-dark cycle through circadian photoentrainment. This process is mediated by light exposure at specific times, leading to a discrete phase shift including phase delays during early subjective night, phase advances during late subjective night, and no shift at midday, known as the dead zone. In mammals, such as mice, the intrinsically photosensitive retinal ganglion cells (ipRGCs) are crucial for conveying light information to the suprachiasmatic nucleus (SCN), the central clock consisting of approximately 20,000 neurons. While the intracellular signaling pathways that modulate clock gene expression post-light exposure are well-studied, the functional neuronal circuits responsible for the three discrete light responses are not well understood. Utilizing in vivo two-photon microscopy with gradient-index (GRIN) endoscopes, we have identified seven distinct light responses from SCN neurons. Our findings indicate that light responses from individual SCN neurons are mostly stochastic from trial to trial. However, at the population level, light response composition remains similar across trials, with only minor variations between circadian times, suggesting a dynamic populational coding for light input. Additionally, only a small subset of SCN neurons shows consistent light responses. Furthermore, by utilizing the targeted recombination in active populations (TRAP) system to label neurons that respond to light during early subjective night, we demonstrate that their activation can induce phase delays at any circadian time, effectively breaking the gate that produce photoentrainment dead zone typically observed at midday. Our results suggest the existence of at least two separate time-dependent functional circuits within the SCN. We propose a dynamic bi-stable network model for circadian photoentrainment in the mammalian central clock, where a shifting clock is driven by a dynamic functional circuit utilizing population coding to integrate information flow similar to proposed cortical computational network, rather than a simplistic, consistent linear circuit.

neuroscience↗

bioRxiv2023

Self-Healable Spider Dragline Silk Materials

Developing materials with structural flexibility that permits self-repair in response to external disturbances remains challenging. Spider silk, which combines an exceptional blend of strength and pliability in nature, serves as an ideal dynamic model for adaptive performance design. In this work, a novel self-healing material is generated using spider silk. Dragline silk from spider Nephila pilipes is demonstrated with extraordinary in situ self-repair property through a constructed thin film format, surpassing that of two other silks from spider Cyrtophora moluccensis and silkworm Bombyx mori. Subsequently, R2, a key spidroin associated with self-healing, is biosynthesized, with validated cohesiveness. R2 is further programmed with tunable healability (permanent and reversible) and conductivity (graphene doping; R2G) for electronics applications. In the first demonstration, film strips from R2 and R2G are woven manually into multidimensional (1D-3D) conductive fabrics for creating repairable logic gate circuits. In the second example, a reversibly-healable R2/R2G strip is fabricated as a re-configurable wearable ring probe to fit fingertips of varying widths while retaining its detecting capabilities. Such prototype displays a unique conformable wearable technology. Last, the remarkable finding of self-healing in spider silk could offer a new material paradigm for developing future adaptive biomaterials with tailored performance and environmental sustainability.

bioengineering↗

bioRxiv2021

Vaccinia virus-based vaccines confer protective immunity against SARS-CoV-2 virus in Syrian hamsters

COVID-19 in humans is caused by Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that belongs to the beta family of coronaviruses. SARS-CoV-2 causes severe respiratory illness in 10-15% of infected individuals and mortality in 2-3%. Vaccines are urgently needed to prevent infection and to contain viral spread. Although several mRNA- and adenovirus-based vaccines are highly effective, their dependence on the "cold chain" transportation makes global vaccination a difficult task. In this context, a stable lyophilized vaccine may present certain advantages. Accordingly, establishing additional vaccine platforms remains vital to tackle SARS- CoV-2 and any future variants that may arise. Vaccinia virus (VACV) has been used to eradicate smallpox disease, and several attenuated viral strains with enhanced safety for human applications have been developed. We have generated two candidate SARS-CoV-2 vaccines based on two vaccinia viral strains, MVA and v-NY, that express full-length SARS-CoV-2 spike protein. Whereas MVA is growth-restricted in mammalian cells, the v-NY strain is replication-competent. We demonstrate that both candidate recombinant vaccines induce high titers of neutralizing antibodies in C57BL/6 mice vaccinated according to prime-boost regimens. Furthermore, our vaccination regimens generated TH1-biased immune responses in mice. Most importantly, prime-boost vaccination of a Syrian hamster infection model with MVA-S and v-NY-S protected the hamsters against SARS-CoV-2 infection, supporting that these two vaccines are promising candidates for future development. Finally, our vaccination regimens generated neutralizing antibodies that partially cross-neutralized SARS-CoV-2 variants of concern.

immunology↗

bioRxiv2020

Non-parametric Bayesian density estimation for biological sequence space with applications to pre-mRNA splicing and the karyotypic diversity of human cancer

Density estimation in sequence space is a fundamental problem in machine learning that is of great importance in computational biology. Due to the discrete nature and large dimensionality of sequence space, how best to estimate such probability distributions from a sample of observed sequences remains unclear. One common strategy for addressing this problem is to estimate the probability distribution using maximum entropy, i.e. calculating point estimates for some set of correlations based on the observed sequences and predicting the probability distribution that is as uniform as possible while still matching these point estimates. Building on recent advances in Bayesian field-theoretic density estimation, we present a generalization of this maximum entropy approach that provides greater expressivity in regions of sequence space where data is plentiful while still maintaining a conservative maximum entropy char-acter in regions of sequence space where data is sparse or absent. In particular, we define a family of priors for probability distributions over sequence space with a single hyper-parameter that controls the expected magnitude of higher-order correlations. This family of priors then results in a corresponding one-dimensional family of maximum a posteriori estimates that interpolate smoothly between the maximum entropy estimate and the observed sample frequencies. To demonstrate the power of this method, we use it to explore the high-dimensional geometry of the distribution of 5' splice sites found in the human genome and to understand the accumulation of chromosomal abnormalities during cancer progression.

bioinformatics↗

bioRxiv2020

Empirical variance component regression for sequence-function relationships

Contemporary high-throughput mutagenesis experiments are providing an increasingly detailed view of the complex patterns of genetic interaction that occur between multiple mutations within a single protein or regulatory element. By simultaneously measuring the effects of thousands of combinations of mutations, these experiments have revealed that the genotype-phenotype relationship typically reflects genetic interactions not only between pairs of sites, but also higher-order interactions among larger numbers of sites. However, modeling and understanding these higher-order interactions remains challenging. Here, we present a method for reconstructing sequence-to-function mappings from partially observed data that can accommodate all orders of genetic interaction. The main idea is to make predictions for unobserved genotypes that match the type and extent of epistasis found in the observed data. This information on the type and extent of epistasis can be extracted by considering how phenotypic correlations change as a function of mutational distance, which is equivalent to estimating the fraction of phenotypic variance due to each order of genetic interaction (additive, pairwise, three-way, etc.). Using these estimated variance components, we then define an empirical Bayes prior that in expectation matches the observed pattern of epistasis, and reconstruct the genotype-phenotype mapping by conducting Gaussian process regression under this prior. To demonstrate the power of this approach, we present an application to the antibody-binding domain GB1 and also provide a detailed exploration of a dataset consisting of high-throughput measurements for the splicing efficiency of human pre-mRNA 5' splice sites, for which we also validate our model predictions via additional low-throughput experiments.

evolutionary biology↗

bioRxiv2019

Regulation of KRAS4A/B splicing in cancer stem cells by the RBM39 splicing complex.

The KRAS oncogene is expressed as major KRAS4B and minor KRAS4A splice isoforms, the distinct functions of which in cancer are unknown. We demonstrate here that KRAS4A is enriched in cancer stem-like cells, and is activated by hypoxia, whereas KRAS4B is more widely expressed and responds to ER stress. Mice completely lacking either isoform are viable but resistant to lung cancer development, as are Kras4A/B double heterozygous mice expressing both isoforms, but in which splice regulation has been uncoupled. Splicing of KRAS4A, but not KRAS4B, in human tumor cells can be inhibited by treatment with the splice inhibitor indisulam, or by CRISPR/Cas inhibition of the RBM39 splicing complex. Our data suggest that control of KRAS4A/B splicing is a targetable vulnerability in KRAS mutant tumors.

cancer biology↗