Biology subjects

Huang, L.-C.

Publications and source records attributed to Huang, L.-C..

11 recordsLinked to original sources

bioRxiv2026

Dual Traditional Chinese Medicine-Preconditioned Stem Cell Secretomes in Coaxial Electrospun Nanofibers Synergistically Accelerate Diabetic Wound Regeneration

Chronic diabetic wounds resist healing due to impaired angiogenesis, stalled cellular migration, and persistent inflammation, a challenge further compounded by the rapid degradation of therapeutic growth factors in the proteolytic wound bed. To overcome this, Traditional Chinese Medicine (TCM) compounds are employed not as standalone drugs, but as biomolecular stimuli to precondition the secretome of Wharton's Jelly-derived mesenchymal stem cells (WJMSCs). To overcome these critical translational barriers, this study engineers a core-shell coaxial electrospun nanofibrous scaffold (polyvinyl alcohol core/gelatin shell) designed for the stabilizing and sustained dual-delivery of biologics. We introduce a novel synergistic payload with WJMSCs conditioned medium (WJMSCs-CM) uniquely primed by two specific chinese herbal compounds, Astragaloside IV (AS-IV) and Formononetin (FMN). This core-shell architecture provides native-like contact guidance for cells while converting conventional burst release into a sustained, weeks-long elution. In vitro, this functionalized scaffold restores Akt/eNOS signaling, rescues cellular viability, and promotes robust tube formation in high-glucose-stressed fibroblasts and endothelial cells. In vivo, within an STZ-induced diabetic rat model, the application of this WJMSCs-CM-loaded coaxial scaffold actively inhibits early inflammation and comprehensively accelerates healing, driving near-complete wound closure (98.2 by day 21), mature collagen deposition, and hair follicle neogenesis. Ultimately, this bio-instructive platform successfully integrates physical structural cues with sustained biochemical signaling, offering a potent, multifaceted strategy for chronic wound regeneration.

bioengineering↗

bioRxiv2026

In virio secondary RNA structure analysis of influenza A virus

The genome of influenza A viruses (IAV) consists of eight distinct gene segments that need to be packaged into new virions. Although this process is thought to be controlled by specific RNA-RNA interactions between segments, few studies have identified the RNA structure inside virions and performed functional validations on these structures. Using high-throughput probing techniques such as SHAPE-MaP and DMS-MaPseq, we mapped the secondary structure of the A/Puerto Rico/8/1934 (PR8) IAV genome. We discovered 173 putative structural motifs in both packaging and central regions of all segments. Fifteen motifs were selected for functional studies by introducing synonymous mutations to destabilize the predicted structure and assessing viral fitness. Synonymous mutations in three predicted RNA structures within the packaging signals of NP and PB1 attenuated virus replication in vitro. Interestingly, combining structural changes in multiple motifs within the packaging signals enhanced viral attenuation, supporting the idea of synergistic structural contributions to viral fitness. In contrast, structural synonymous mutations in RNA secondary structures outside packaging signals had no impact on virus replication in vitro. Overall, our findings revealed several new RNA secondary structures within the packaging signals of IAV gene segments that play a critical role in the IAV life cycle.

microbiology↗

bioRxiv2022

Dark kinase annotation, mining and visualization using the Protein Kinase Ontology

The Protein Kinase Ontology (ProKinO) is an integrated knowledge graph that conceptualizes the complex relationships connecting protein kinase sequence, structure, function, and disease in a human and machine-readable format. Here we extend the scope of ProKinO as a discovery tool by including new classes and relationships capturing information on kinase ligand binding sites, expression patterns, and functional features, and demonstrate its application in uncovering new knowledge regarding understudied members of the protein kinase family. Specifically, through graph mining and aggregate SPARQL queries, we identify the p21-activated protein kinase 5 (PAK5) as one of the most frequently mutated dark kinase in human cancers with abnormal expression in multiple cancers, including an unappreciated role in acute myeloid leukemia. We identify recurrent oncogenic mutations in the PAK5 activation loop predicted to alter substrate binding and phosphorylation and identify common ligand/drug binding residues in PAK family kinases, highlighting the potential application of ProKinO in drug discovery. The updated ontology browser and a web component, ProtVista, which allows interactive mining of kinase sequence annotations in 3D structures and Alphafold models, provide a valuable resource for the signaling community. The updated ProKinO database is accessible at http://prokino.uga.edu/browser/.

bioinformatics↗

bioRxiv2021

BRCA1 and ELK-1 regulate Neural Progenitor Cell Fate in the Optic Tectum in response toVisual Experience in Xenopus laevis tadpoles

In developing Xenopus tadpoles, the optic tectum begins to receive patterned visual input while visuomotor circuits are still undergoing neurogenesis and circuit assembly. This visual input regulates neural progenitor cell fate decisions such that maintaining tadpoles in the dark increases proliferation, expanding the progenitor pool, while visual stimulation promotes neuronal differentiation. To identify regulators of activity-dependent neural progenitor cell fate, we used RNA-Seq to profile the transcriptomes of proliferating neural progenitor cells and newly-differentiated immature neurons. Out of 1,130 differentially expressed (DE) transcripts, we identified six DE transcription factors which are predicted to regulate the majority of the other DE transcripts. Here we focused on Breast cancer 1 (BRCA1) and the ETS-family transcription factor, ELK-1. BRCA1 is known for its role in cancers, but relatively little is known about its potential role in regulating neural progenitor cell fate. ELK-1 is a multifunctional transcription factor which regulates immediate early gene expression. We investigated the effect of BRCA1 and ELK-1 on activity-regulated neurogenesis in the tadpole visual system using in vivo time-lapse imaging to monitor the fate of turbo-GFP-expressing SOX2+ neural progenitor cells in the optic tectum. Our longitudinal in vivo imaging analysis shows that knockdown of either BRCA1 or ELK-1 altered the fates of neural progenitor cells, and furthermore that the effects of visual experience on neurogenesis depend on BRCA1 expression, while the effects of visual experience on neuronal differentiation depend on ELK-1 expression. These studies provide insight into the potential mechanisms by which neural activity affects neural progenitor cell fate.

neuroscience↗

bioRxiv2021

Protein Kinase C gamma Mutations Drive Spinocerebellar Ataxia Type 14 by Impairing Autoinhibition

Spinocerebellar ataxia type 14 (SCA14) is a neurodegenerative disease caused by germline variants in the diacylglycerol (DG)/Ca2+-regulated protein kinase C gamma (PKC{gamma}), leading to Purkinje cell degeneration and progressive cerebellar dysfunction. The majority of the approximately 50 identified variants cluster to the DG-sensing C1 domains. Here, we use a FRET- based activity reporter to show that ataxia-associated PKC{gamma} mutations enhance basal activity by compromising autoinhibition. Although impaired autoinhibition generally leads to PKC degradation, the C1 domain mutations protect PKC{gamma} from phorbol ester-induced downregulation. Furthermore, it is the degree of disrupted autoinhibition, not changes in the amplitude of agonist- stimulated activity, that correlate with disease severity. This enhanced basal signaling rewires the brain phosphoproteome, as assessed by phosphoproteomic analysis of cerebella from mice expressing a human PKC{gamma} transgene harboring a SCA14 C1 domain mutation, H101Y. Validating that the pathology arises from disrupted autoinhibition, we show that the degree of impaired autoinhibition correlates inversely with age of disease onset in patients: mutations that cause high basal activity are associated with early onset, whereas those that only modestly increase basal activity, including a previously undescribed variant, D115Y, are associated with later onset. Molecular modeling indicates that almost all SCA14 variants that are not in the C1 domains are at interfaces with the C1B domain, and bioinformatics analysis reveals that variants in the C1B domain are under-represented in cancer. Thus, clustering of SCA14 variants to the C1B domain provides a unique mechanism to enhance PKC{gamma} basal activity while protecting the enzyme from downregulation, deregulating the cerebellar phosphoproteome. One Sentence SummarySCA14 driver mutations in PKC{gamma} impair autoinhibition, with defect correlating inversely with age of disease onset.

biochemistry↗

bioRxiv2021

KinOrtho: a method for mapping human kinase orthologs across the tree of life and illuminating understudied kinases

Protein kinases are among the largest druggable family of signaling proteins, involved in various human diseases, including cancers and neurodegenerative disorders. Despite their clinical relevance, nearly 30% of the 545 human protein kinases remain highly understudied. Comparative genomics is a powerful approach for predicting and investigating the functions of understudied kinases. However, an incomplete knowledge of kinase orthologs across fully sequenced kinomes severely limits the application of comparative approaches for illuminating understudied kinases. Here, we propose KinOrtho, a query- and graph-based orthology inference method that combines full-length and domain-based approaches to map one-to-one kinase orthologs across 17 thousand species. Using multiple metrics, we show that KinOrtho performed better than existing methods in identifying kinase orthologs across evolutionarily divergent species and eliminated potential false positives by flagging sequences without a proper kinase domain for further evaluation. We demonstrate the advantage of using domain-based approaches for identifying domain fusion events, highlighting a case between an understudied serine/threonine kinase TAOK1 and a metabolic kinase PIK3C2A with high co-expression in human cells. We also identify evolutionary fission events involving the understudied OBSCN kinase domains, further highlighting the value of domain-based orthology inference approaches. Using KinOrtho-defined orthologs, Gene Ontology annotations, and machine learning, we propose putative biological functions of several understudied kinases, including the role of TP53RK in cell cycle checkpoint(s), the involvement of TSSK3 and TSSK6 in acrosomal vesicle localization, and potential functions for the ULK4 pseudokinase in neuronal development. The well-curated kinome ortholog set can serve as a valuable resource for illuminating understudied kinases, and the KinOrtho framework can be extended to any gene-family of interest.

evolutionary biology↗

bioRxiv2020

The role of matrix metalloproteinase-9 (MMP-9) in neurodevelopmental deficits and experience-dependent structural plasticity in Xenopus laevis tadpoles

Matrix metalloproteinase-9 (MMP-9) is a secreted endopeptidase targeting extracellular matrix proteins, creating permissive environments for neuronal development and plasticity. Developmental dysregulation of MMP-9 is also associated with neurodevelopmental disorders (ND). Here we test the hypothesis that chronically elevated MMP-9 activity during early neurodevelopment is responsible for neural circuit hyperconnectivity observed after early exposure to valproic acid (VPA), a known teratogen associated with autism spectrum disorder in humans. In Xenopus tadpoles, VPA exposure results in excess local synaptic connectivity, disrupted social behavior and increased seizure susceptibility. We found that overexpressing MMP-9 in the brain copies effects of VPA on synaptic connectivity, and blocking MMP-9 activity pharmacologically or genetically reverses effects of VPA on physiology and behavior. We further show that during normal neurodevelopment MMP-9 levels are tightly regulated by neuronal activity and required for structural plasticity. These studies show a critical role for MMP-9 in both normal and abnormal development.

neuroscience↗

bioRxiv2020

Exploring the understudied human kinome for research and therapeutic opportunities

The functions of protein kinases have been widely studied and over 60 kinase inhibitors are FDA-approved drugs. Membership in the human kinome is nonetheless subject to multiple overlapping and inconsistent definitions and is unevenly studied, complicating functional genomics and chemical genetics. We describe objective criteria for refining the definition of the human kinome to comprise an extended set of 710 kinase domains and a more narrowly curated set of 557 protein kinase like (PKL) domains. An online tool (www.kinome.org) makes it possible to sort these sets on multiple structural and functional criteria. Focusing on the least studied one-third of the kinome we find that many proteins are differentially expressed, essential in multiple cell lines, and mutated in the Cancer Genome Atlas. We show that some understudied kinases are high affinity off-targets of clinical-grade compounds and approved drugs and we describe an optimized small molecule library making use of this information for selective kinome perturbation. We conclude that the understudied kinome contains physiologically important proteins, including possible targets for future drug discovery campaigns.

systems biology↗

bioRxiv2019

Deep evolutionary analysis reveals the design principles of fold A glycosyltransferases

Glycosyltransferases (GTs) are prevalent across the tree of life and regulate nearly all aspects of cellular functions by catalyzing synthesis of glycosidic linkages between diverse donor and acceptor substrates. Despite the availability of GT sequences from diverse organisms, the evolutionary basis for their complex and diverse modes of catalytic and regulatory functions remain enigmatic. Here, based on deep mining of over half a million GT-A fold sequences from diverse organisms, we define a minimal core component shared among functionally diverse enzymes. We find that variations in the common core and the emergence of hypervariable loops extending from the core contributed to the evolution of catalytic and functional diversity. We provide a phylogenetic framework relating diverse GT-A fold families for the first time and show that inverting and retaining mechanisms emerged multiple times independently during the course of evolution. We identify conserved modes of donor and acceptor recognition in evolutionarily divergent families and pinpoint the sequence and structural features for functional specialization. Using the evolutionary information encoded in primary sequences, we trained a machine learning classifier to predict donor specificity with nearly 88% accuracy and deployed it for the annotation of understudied GTs in five model organisms. Our studies provide an evolutionary framework for investigating the complex relationships connecting GT-A fold sequence, structure, function and regulation.

bioinformatics↗

bioRxiv2019

Quantitative Structure-Mutation-Activity Relationship Tests (QSMART) Model for Protein Kinase Inhibitor Response Prediction

Predicting drug sensitivity profiles from genotypes is a major challenge in personalized medicine. Machine learning and deep neural network methods have shown promise in addressing this challenge, but the "black-box" nature of these methods precludes a mechanistic understanding of how and which genomic and proteomic features contribute to the observed drug sensitivity profiles. Here we provide a combination of statistical and neural network framework that not only estimates drug IC50 in cancer cell lines with high accuracy (R2 = 0.861 and RMSE = 0.818) but also identifies features contributing to the accuracy, thereby enhancing explainability. Our framework, termed QSMART, uses a multi-component approach that includes (1) collecting drug fingerprints, cancer cell lines multi-omics features, and drug responses, (2) testing the statistical significance of interaction terms, (3) selecting features by Lasso with Bayesian information criterion, and (4) using neural networks to predict drug response. We evaluate the contribution of each of these components and use a case study to explain the biological relevance of several selected features to protein kinase inhibitor response in non-small cell lung cancer cells. Specifically, we illustrate how interaction terms that capture associations between drugs and mutant kinases quantitatively contribute to the response of two EGFR inhibitors (afatinib and lapatinib) in non-small cell lung cancer cells. Although we have tested QSMART on protein kinase inhibitors, it can be extended across the proteome to investigate the complex relationships connecting genotypes and drug sensitivity profiles.

bioinformatics↗

bioRxiv2018

A prospective, observational study on conversion of Clinically Isolated Syndrome to Multiple Sclerosis during 4-year period (MS NEO study) in Taiwan

ImportanceCIS to MS conversion rates vary depending on population cohorts, initial manifestations, and durations of follow-up.\n\nObjectiveTo investigate conversion rate of patients from CIS to MS and the prognostic significance of demographic and clinical variables in Taiwanese population.\n\nDesignNationwide, prospective, multi-centric, observational study from November 2008 to November 2014 with 4 years follow-up.\n\nSettingMulti-centre setting at 5 institutions in Taiwan.\n\nParticipants152 patients having single clinical event potentially suggestive of MS in last 2 years were enrolled as consecutive sample. 33 patients were lost to follow-up and 16 patients did not complete the study.103 patients completed the study.\n\nIntervention(s) (for clinical trials) or Exposure(s) (for observational studies)Natural progression from first episode of CIS to MS or NMO was observed.\n\nMain Outcome(s) and Measure(s)Variables analysed were proportion of patients converting to MS or NMO after first episode of CIS, duration between first episode of neurological event and diagnosis of MS, status of anti-AQP4 IgG and length of longest contiguous spinal cord lesion in MS patients. Association between baseline characteristics and progression to MS from CIS was analyzed using multiple logistic regression. Multivariate time dependent effect of baseline characteristics on progression to MS was plotted.\n\nResults14.5% patients with CIS converted to MS after 1.1 {+/-} 1.0 years with greater predisposition (18.8%) in those having syndromes referable to the cerebral hemispheres. Conversion rate from ON to MS was 9.7%. 90.9% patients had benign disease course. 46.7% patients had abnormal MRIs at baseline, with 0.6{+/-}0.5 contrast enhanced lesions. Below normal BMI and MRI lesion load ([≥] 4 lesions) were identified as risk indicators for the development of MS. Only 4.5% were positive for anti-AQP4 antibody in MS patients and amongst them, 80% were NMO patients as diagnosed by modern criteria.\n\nConclusions and Relevance Below normal BMI and number of demyelinating lesions ([≥]4) are significant predictors of conversion from CIS to MS. A low conversion rate to MS in Taiwanese CIS patients and majority of them having a benign course and minimal disability suggest the roles of geographic, genetic and ethnic factors.\n\nTrial RegistrationNon-trial observational study.

neuroscience↗