Biology subjects

Wu, C.-T.

Publications and source records attributed to Wu, C.-T..

At least 19 recordsLinked to original sources

bioRxiv2026

Coordinated immune-epithelial dynamics in the nasal epithelium protect against respiratory virus infection

Epithelial remodeling is a hallmark of host antiviral responses that strengthen barrier defenses against infection. Our current understanding of viral pathophysiology within the nasal epithelium, the initial site of most respiratory viral infections, remains incomplete due to limited understanding of the native tissue architecture and protective epithelial remodeling during immune events. Leveraging coronavirus disease 2019 (COVID-19) as a model, we applied spatial multi-omics on nasal cross-sectional tissues to characterize the immune-epithelial landscape during infection, identifying a coordinated increase in goblet cells and suppressive macrophages associated with elevated IL13 in the immune compartment. Our results further reveal that goblet cell and suppressive macrophage enrichment are spatially linked in proximity to IL13-expressing CD4 T cells, consistent with IL13-driven remodeling in situ. Using a primary human nasal air-liquid interface model, we demonstrate that IL13 alone is sufficient to remodel epithelial composition and morphology, subsequently restricting viral infection by reshaping the apical mucus barrier of the nasal epithelium. Our findings uncover a spatially organized, IL13-driven circuit for immune-epithelial remodeling as a protective barrier against respiratory viral infections.

immunology↗

bioRxiv2025

Short Oxygen Pulses Enhance Creative Problem-Solving

Creativity is central to human innovation, yet it often fluctuates from moment to moment. Identifying simple interventions to reliably boost creativity has broad scientific and societal value. Here, we tested whether short-pulse oxygen inhalation enhances creative problem-solving. Sixty participants performed two established tasks: the Alternative Uses Test (AUT), capturing divergent idea generation, and the Fusion Innovation Test (FIT), assessing both divergent and convergent thinking. Oxygen ([~]40% FiO2) was delivered in 1-minute pulses at 3-4-minute intervals, designed to align with intrinsic brain flexibility rhythms. Responses were scored for novelty, feasibility, and goal attainment using a validated GPT-based method. Linear mixed-effects regression revealed that oxygen significantly enhances both the quality and quantity of creative ideas across tasks. These findings demonstrate that a safe, low-cost physiological intervention can augment creative performance, providing a new link between oxygen metabolism, neural flexibility, and problem-solving. Significance statementHuman progress depends on creativity, yet individuals often struggle to access their full creative potential. We demonstrate that brief cycles of enriched oxygen inhalation enhance creativity across distinct problem-solving tasks. This safe and low-cost protocol increased both originality and productivity, pointing to oxygen metabolism as a previously underappreciated driver of flexible thinking. The work introduces a novel, scalable approach to support creativity at a time when human innovation is essential alongside advances in artificial intelligence.

neuroscience↗

bioRxiv2025

Spatiotemporal Dynamics of fMRI Signal Changes Induced by High Concentration Normobaric Oxygen Inhalation

While it is well known that oxygen supports the brains metabolic demands, it remains unclear how increased oxygen concentration influences intrinsic neural activity over time and across brain regions. Using resting-state functional magnetic resonance imaging (fMRI), we examined the dynamic responses to high-concentration normobaric oxygen across distinct phases of exposure and withdrawal. We revealed three patterns in the BOLD signals: increased activation during inhalation, an undershoot following immediate oxygen withdrawal, and reactivation even without continued oxygen. These responses were most pronounced in the default mode network (DMN), but also exhibited spatiotemporally heterogeneous patterns across the brain, a map we term Brain Oxygen Sensitivity Topography (BOST). Functional connectivity analyses further revealed increased between-network connectivity during inhalation and enhanced within-network connectivity in the DMN during the aftereffect. This spatiotemporal heterogeneity and transient network reorganization suggests that distinct physiological processes are engaged at each phase, enabling us to predict how different oxygen protocols will enhance specific cognitive functions.

neuroscience↗

bioRxiv2025

The Multifaceted Role of EXOC6A in Ciliogenesis

Ciliogenesis is a highly ordered process that requires membrane trafficking, fusion, and maturation. In this study, we investigated EXOC6A, a component of the exocyst complex known for secretory vesicle trafficking and fusion, and found that it interacts with myosin-Va (Myo-Va) during ciliogenesis. EXOC6A colocalizes with Myo-Va at various stages of ciliogenesis, including preciliary vesicles, ciliary vesicles (CVs), and ciliary sheath membrane during ciliogenesis. We found that EXOC6A vesicles are actively recruited, integrated, and exit from the CVs and the ciliary sheath, implying that EXOC6A vesicles may facilitate continuous cilia membrane remodeling during ciliogenesis. Importantly, EXOC6A knockout impairs ciliogenesis, arresting most cells at the CV stage and preventing recruitment of NPHP and MKS module components to the transition zone. Furthermore, EXOC6A vesicles are transported to the mother centriole via a dynein-, microtubule-, and actin-dependent mechanism. Our results suggest that EXOC6A functions in both early and late stages of ciliogenesis and is involved in orchestrating vesicle dynamics, cilia membrane remodeling, and formation.

cell biology↗

bioRxiv2025

Creativity Potential Networks: Brain Markers for Novelty and Feasibility of Upcoming Divergent Thinking Solutions

The brains resting-state activity can serve as an indicator of cognitive flexibility and predict the likelihood of an upcoming Aha experience. This suggests that spontaneous neural dynamics reflect a persons readiness for creative insight and underscore the potential of resting-state measures as biomarkers for anticipating creative breakthroughs. However, solutions accompanied by an Aha experience are not always truly creative, so it may be more valuable to identify biomarkers specifically linked to novelty and usefulness--two key dimensions of creative performance. To achieve this, we recruit 49 participants to complete the Alternative Uses Test, in which unconventional uses for everyday items are generated. We evaluate the responses for both novelty and feasibility using automated GPT-based methods and analyze resting-state EEG prior to the test. We find that creative performance is better predicted by interactions between different brain areas than by the activation of individual regions. Specifically, the degree centrality of theta-band functional connectivity in the right parietal and occipital areas correlates with novelty, while connectivity in the right middle and inferior frontal areas is associated with more feasible answers. These findings highlight distinct resting-state brain networks underlying the "creative potential" for novelty and feasibility, which could be leveraged to monitor and enhance brain flexibility. Significance statementOur study introduces the Creativity Potential Network (CPN), a resting-state brain network that can predict the novelty and feasibility of the upcoming solution in creative problem-solving. We show that the CPN is represented by communication between brain areas, and that the networks for novelty and feasibility are spatially distinct. This work provides a potential method to assess the potential to be creative without relying on behavioral measures and could be combined with neurofeedback to monitor and enhance brain flexibility.

neuroscience↗

bioRxiv2024

Dietary protein restriction diminishes sucrose reward and reduces sucrose-evoked mesolimbic dopamine signaling

ObjectiveA growing literature suggests manipulating dietary protein status decreases sweet consumption in rodents and in humans. Underlying neurocircuit mechanisms have not yet been determined, but previous work points towards hedonic rather than homeostatic pathways. Here we hypothesized that a history of protein restriction reduces sucrose seeking by altering mesolimbic dopamine signaling. MethodsWe tested this hypothesis using established behavioral tests of palatability and motivation, including the palatability contrast and conditioned place preference (CPP) tests. We used modern optical sensors for measuring real-time nucleus accumbens (NAc) dopamine dynamics during sucrose consumption, via fiber photometry, in male C57/Bl6J mice maintained on low-protein high-carbohydrate (LPHC) or control (CON) diet for [~]5 weeks. ResultsA history of protein restriction decreased the consumption of a sucrose dessert in sated mice by [~]50% compared to controls [T-test, p< 0.05]. The dopamine release in NAc during sucrose consumption was reduced, also by [~]50%, in LPHC-fed mice compared to CON [T-test, p< 0.01]. Furthermore, LPHC-feeding blocked the sucrose-conditioned place preference we observed in CON-fed mice [paired T-test, p< 0.05], indicating reduced motivation. This was accompanied by a 33% decrease in neuronal activation of the NAc core, as measured by c-Fos immunolabeling from brains collected directly after the CPP test. ConclusionsDespite ongoing efforts to promote healthier dietary habits, adherence to recommendations aimed at reducing the intake of added sugars and processed sweets remains challenging. This study highlights chronic dietary protein restriction as a nutritional intervention that suppresses the motivation for sucrose intake, via blunted sucrose-evoke dopamine release in NAc.

physiology↗

bioRxiv2024

Filopodial Mechanotransduction is regulated by Angiotensin-Converting Enzyme 2 (ACE2) and by SARS-CoV-2 spike protein

Filopodia are dynamic, actin-rich cellular protrusions, increasingly linked to cellular mechanotransduction. However, how dynamic filopodia translate external mechanical cues remains poorly understood. Recent studies show that the SARS-CoV-2 spike (S) protein binds the ACE2 receptor on airway multicilia and that cilia are required for viral infection(1) and sufficient to induce filopodial extension and viral binding. To test if spike protein is sufficient to induce filopodial expansion, we employed live-cell single-particle tracking with quantum dots targeting ACE2, to reveal a robust filopodia extension and virus binding mechanism requiring the enzymatic activity of ACE2. Using time-lapse imaging, we reveal that spike protein binding to filopodia is associated with intracellular actin remodeling, alterations in bulk cell stiffness, and an elevation in intracellular calcium levels linked to actin-rearrangement, filopodia initiation, and persistence. We propose the activation of ACE2 creates an active signaling and mechanosensory environment within adherent cells and airway epithelial cells that allows the remodeling of actin in filopodia to trap virus and potentially organize viral exit from cells. [164 words] One-Sentence SummarySARS-CoV-2 spike protein activates calcium and actin dynamics to enable filopodial extension and virus binding

cell biology↗

bioRxiv2023

Dissecting Mismatch Negativity: Early and Late Subcomponents for Detecting Deviants in Local and Global Sequence Regularities

Mismatch negativity (MMN) is commonly recognized as a neural signal of prediction error evoked by deviants in the expected pattern of sensory input. Studies show that MMN diminishes when a sequence pattern becomes more predictable over a longer timescale. This implies that MMN is comprised of multiple subcomponents, each responding to different levels of temporal regularities. To probe the hypothesized subcomponents in MMN, we record human electroencephalography during an auditory local-global oddball paradigm where the tone-to-tone transition probability (local regularity) and the overall sequence probability (global regularity) are manipulated to control temporal predictabilities at two hierarchical levels. We find that the size of MMN is correlated with both probabilities and the spatiotemporal structure of MMN can be decomposed into two distinct subcomponents. Both subcomponents appear as negative waveforms which peak early in the central-frontal area and late in a more frontal area, respectively. With a quantitative predictive coding model, we map the early and late subcomponents to the prediction errors that are tied to local and global regularities, respectively. Our study highlights the hierarchical complexity of MMN and offers an experimental and analytical platform for developing a multi-tiered neural marker, applicable in clinical settings.

neuroscience↗

bioRxiv2023

Crossmodal Hierarchical Predictive Coding for Audiovisual Sequences in Human Brain

Predictive-coding theory proposes that the brain actively predicts sensory inputs based on prior knowledge. While this theory has been extensively researched within individual sensory modalities, there is a crucial need for empirical evidence supporting hierarchical predictive processing across different modalities to further generalize the theory. Here, we examine how crossmodal knowledge is represented and learned in the brain by identifying the hierarchical networks underlying crossmodal predictions when information of one sensory modality leads to a prediction in another modality. We record electroencephalogram (EEG) in humans during a crossmodal audiovisual local-global oddball paradigm, in which the predictability of transitions between tones and images are manipulated at two hierarchical levels: stimulus-to-stimulus transition (local level) and multi-stimulus sequence structure (global level). With a model-fitting approach, we decompose the EEG data using three distinct predictive-coding models: one with no audiovisual integration, one with audiovisual integration at the global level, and one with audiovisual integration at both the local and global levels. The best-fitting model demonstrates that audiovisual integration occurs at both levels. This highlights a convergence of auditory and visual information to construct crossmodal predictions, even in the more basic interactions that occur between individual stimuli. Furthermore, we reveal the spatio-spectro-temporal signatures of prediction-error signals across hierarchies and modalities, and show that auditory and visual prediction-error signals are progressively redirected to the central-parietal area of the brain as learning progresses. Our findings unveil a crossmodal predictive coding mechanism, where the unimodal framework is implemented through more distributed brain networks to process hierarchical crossmodal knowledge.

neuroscience↗

bioRxiv2023

The macronutrient content of a meal modulates subsequent 'dessert' intake, via Fibroblast Growth Factor 21 (FGF21)

Pharmacological administration of Fibroblast growth factor 21 (FGF21) alters food choice, including that it decreases the consumption of sucrose and other sweet tastants. Conversely, endogenous secretion of FGF21 by the liver is modulated by diet, such that plasma FGF21 is increased after eating foods that have a low dietary protein: total energy (P: E) ratio. Together, these findings suggest a strategy to promote healthy eating, in which the macronutrient content of a pre-load meal could reduce the later consumption of sweet desserts. Here, we tested the prediction that individuals eating a low P: E pre-load meal, and next offered a highly palatable sweet dessert, would eat less of the sugary snack compared to controls, due to increased FGF21 signaling. In addition to decreasing sweet intake, FGF21 increases the consumption of dietary protein. Thus, we predicted that individuals eating a low protein pre-load meal, and subsequently offered a very high-protein pellet as dessert or snack, would eat more of the high protein pellet compared to controls, and that this depends on FGF21. We tested this in C57Bl/6J, and liver-specific FGF21-null (FGF21{Delta}L) null male and female mice and littermate controls. Contrary to expectation, eating a low protein pre-load did not reduce the later consumption of a sweet solution in either males or females, despite robustly increasing plasma FGF21. Rather, eating the low protein pre-load increased later consumption of a high protein pellet. This was more apparent among males and was abrogated in the FGF21{Delta}L mice. We conclude that physiologic induction of hepatic FGF21 by a low protein pre-load is not sufficient to reduce later consumption of sweet dessert, though it effectively increases the subsequent intake of dietary protein in male mice.

physiology↗

bioRxiv2022

Iterative transcription factor screening enables rapid generation of microglia-like cells from human iPSC

The ability to differentiate stem cells into human cell types is essential to define basic mechanisms and therapeutics, especially for cell types not routinely accessible by biopsies. But while engineered expression of transcription factors (TFs) identified through TF screens has been found to rapidly and efficiently produce some cell types, generation of other cell types that require complex combinations of TFs has been elusive. Here we develop an iterative, pooled single-cell TF screening method that improves the identification of effective TF combinations using the generation of human microglia-like cells as a testbed: Two iterations identified a combination of SPI1, CEBPA, FLI1, MEF2C, CEBPB, and IRF8 as sufficient to differentiate human iPSC into microglia-like cells in 4 days. Characterization of TF-induced microglia demonstrated molecular and functional similarity to primary microglia. We explore the use of single-cell atlas reference datasets to confirm identified TFs and how combining single-cell TF perturbation and gene expression data can enable the construction of causal gene regulatory networks. We describe what will be needed to fashion these methods into a generalized integrated pipeline, further ideas for enhancement, and possible applications.

bioengineering↗

bioRxiv2021

Determining molecular archetype composition and expression from bulk tissues with unsupervised deconvolution

Complex tissues are composite ecological systems whose components interact with each other to create a unique physiological or pathophysiological state distinct from that found in other tissue microenvironments. To explore this ground yet dynamic state, molecular profiling of bulk tissues and mathematical deconvolution can be jointly used to characterize heterogeneity as an aggregate of molecularly distinct tissue or cell subtypes. We first introduce an efficient and fully unsupervised deconvolution method, namely the Convex Analysis of Mixtures - CAM3.0, that may aid biologists to confirm existing or generate novel scientific hypotheses about complex tissues in many biomedical contexts. We then evaluate the CAM3.0 functional pipelines using both simulations and benchmark data. We also report diverse case studies on bulk tissues with unknown number, proportion and expression patterns of the molecular archetypes. Importantly, these preliminary results support the concept that expression patterns of molecular archetypes often reflect the interactive not individual contributions of many known or novel cell types, and unsupervised deconvolution would be more powerful in uncovering novel multicellular or subcellular archetypes.

bioinformatics↗

bioRxiv2021

COT: an efficient Python tool for detecting marker genes among many subtypes

We develop an accurate and efficient method to detect marker genes among many subtypes using subtype-enriched expression profiles. We implement a Cosine based One-sample Test (COT) Python software that is easy to use and applicable to multi-omics data. We demonstrate the performance and utility of COT on gene expression and proteomics data acquired from tissue or cell subtypes. Formulated as a one-sample test with Cosine similarity test statistic in scatter space, the detected de novo marker genes will allow biologists to perform a more comprehensive and unbiased molecular characterization, deconvolution and classification of complex tissue or cell subtypes.

bioinformatics↗

bioRxiv2021

Sample-wise unsupervised deconvolution of complex tissues

MotivationComplex biological tissues are often a heterogeneous mixture of several molecularly distinct cell or tissue subtypes. Both subtype compositions and expressions in individual samples can vary across different biological states or conditions. Computational deconvolution aims to dissect patterns of bulk gene expression data into subtype compositions and subtype-specific expressions. Typically, existing deconvolution methods can only estimate averaged subtype-specific expressions in a population, while detecting differential expressions or co-expression networks in particular subtypes requires unique subtype expression estimates in individual samples. Different from population-level deconvolution, however, individual-level deconvolution is mathematically an underdetermined problem because there are more variables than observations. ResultsWe report a sample-wise Convex Analysis of Mixtures (swCAM) method that can estimate subtype proportions and subtype-specific expressions in individual samples from bulk tissue transcriptomes. We extend our previous CAM framework to include a new term accounting for between-sample variations and formulate swCAM as a nuclear-norm and{ell} 2,1-norm regularized matrix factorization problem. We determine hyperparameter values using a cross-validation scheme with random entry exclusion and obtain a swCAM solution using an efficient alternating direction method of multipliers. The swCAM is implemented in open-source R scripts. Experimental results on realistic simulation data show that swCAM can accurately estimate subtype-specific expressions in individual samples and successfully extract co-expression networks in particular subtypes that are otherwise unobtainable using bulk expression data. Application of swCAM to bulk-tissue data of 320 samples from bipolar disorder patients and controls identified changes in cell proportions, expression and coexpression modules in patient neurons. Mitochondria related genes showed significant changes suggesting an important role of energy dysregulation in bipolar disorder. Availability and implementationThe R Scripts of swCAM is freely available at https://github.com/Lululuella/swCAM. A users guide and a vignette are provided. Contactyuewang@vt.edu Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2020

Ethacridine inhibits SARS-CoV-2 by inactivating viral particles in cellular models

SARS-CoV-2 is the coronavirus that causes the respiratory disease COVID-19, which is now the third-leading cause of death in the United States. The FDA has recently approved remdesivir, an inhibitor of SARS-CoV-2 replication, to treat COVID-19, though recent data from the WHO shows little to no benefit with use of this anti-viral agent. Here we report the discovery of ethacridine, a safe antiseptic use in humans, as a potent drug for use against SARS-CoV-2 (EC50 ~ 0.08 M). Ethacridine was identified via high-throughput screening of an FDA-approved drug library in living cells using a fluorescent assay. Interestingly, the main mode of action of ethacridine is through inactivation of viral particles, preventing their binding to the host cells. Indeed, ethacridine is effective in various cell types, including primary human nasal epithelial cells. Taken together, these data identify a promising, potent, and new use of the old drug possessing a distinct mode of action for inhibiting SARS-CoV-2.

microbiology↗

bioRxiv2020

Discovery of ciliary G protein-coupled receptors regulating pancreatic islet insulin and glucagon secretion

Multiple G protein coupled receptors (GPCRs) are expressed in pancreatic islet cells but the majority have unknown functions. We observe specific GPCRs localized to primary cilia, a prominent signaling organelle, in pancreatic - and {beta}-cells. Loss of cilia disrupts {beta}-cell endocrine function, but the molecular drivers are unknown. Using functional expression, we identified multiple GPCRs localized to cilia in mouse and human islet - and {beta}-cells, including FFAR4, PTGER4, DRD5, ADRB2, KISS1R, and P2RY14. Free fatty acid receptor 4 (FFAR4) and prostaglandin E receptor 4 (PTGER4) agonists stimulate ciliary cAMP signaling and promote glucagon and insulin secretion by - and {beta}-cell lines, and by mouse and human islets. Transport of GPCRs to primary cilia requires TULP3, whose knockdown in primary human and mouse islets depleted ciliary FFAR4 and PTGER4, and impaired regulated glucagon or insulin secretion, without affecting ciliary structure. Our findings provide index evidence that regulated hormone secretion by islet - and {beta}-cells is regulated by ciliary GPCRs providing new targets for diabetes.

physiology↗

bioRxiv2019

Alignment of LC-MS Profiles by Neighbor-wise Compound-specific Graphical Time Warping with Misalignment Detection

MotivationLiquid chromatography - mass spectrometry (LC-MS) is a standard method for proteomics and metabolomics analysis of biological samples. Unfortunately, it suffers from various changes in the retention times (RT) of the same compound in different samples, and these must be subsequently corrected (aligned) during data processing. Classic alignment methods such as in the popular XCMS package often assume a single time-warping function for each sample. Thus, the potentially varying RT drift for compounds with different masses in a sample is neglected in these methods. Moreover, the systematic change in RT drift across run order is often not considered by alignment algorithms. Therefore, these methods cannot completely correct misalignments. For a large-scale experiment involving many samples, the existence of misalignment becomes inevitable and concerning.\n\nResultsHere we describe an integrated reference-free profile alignment method, neighbor-wise compound-specific Graphical Time Warping (ncGTW), that can detect misaligned features and align profiles by leveraging expected RT drift structures and compound-specific warping functions. Specifically, ncGTW uses individualized warping functions for different compounds and assigns constraint edges on warping functions of neighboring samples. Validated with both realistic synthetic data and internal quality control samples, ncGTW applied to two large-scale metabolomics LC-MS datasets identifies many misaligned features and successfully realigns them. These features would otherwise be discarded or uncorrected using existing methods. The ncGTW software tool is developed currently as a plug-in to the XCMS package.\n\nAvailability and ImplementationAn R package of ncGTW is freely available at https://github.com/ChiungTingWu/ncGTW. A detailed users manual and a vignette are provided within the package.\n\nContactyuewang@vt.edu, yug@vt.edu\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2019

Integrated Identification of Disease Specific Pathways Using Multi-omics data

MotivationIdentification of biological pathways plays a central role in understanding both human health and diseases. Although much work has previously been done to explore the biological pathways by using single omics data, little effort has been reported using multi-omics data integration, mainly due to methodological and technological limitations. Compared to single omics data, multi-omics data will help identifying disease specific functional pathways with both higher sensitivity and specificity, thus gaining more comprehensive insights into the molecular architecture of disease processes.\n\nResultsIn this paper, we propose two computational approaches that integrate multi-omics data and identify disease-specific biological pathways with high sensitivity and specificity. Applying our methods to an experimental multi-omics data dataset on muscular dystrophy subtypes, we identified disease-specific pathways of high biological plausibility. The developed methodology will likely have a broad impact on improving the molecular characterization of many common diseases.\n\nContactyuewang@vt.edu\n\nSupplementary informationSupplementary information attached.

bioinformatics↗