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Biology subjects

Huang, C.-H.

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

At least 19 recordsLinked to original sources

A regenerative fibroblast competence field supports multiple cell fates in adult skin regeneration

Adult mammalian wounds typically restore tissue integrity through fibrotic repair rather than regeneration of the original architecture. Here, we compared small non-regenerative and large regenerative skin wounds to investigate how fibroblasts acquire regenerative competence and enter alternative cell-fate programs. Integrated single-cell RNA sequencing identified a transient signaling and extracellular-matrix-remodeling niche enriched in large wounds, together with NCAM1-associated competent fibroblast states. Time-resolved analysis positioned these states within a root-like fibroblast manifold connected to hair dermal-condensate, endothelial, pericyte and glial-associated fate-entry programs. Inferred cell-cell communication networks revealed shared matrix and adhesion signals, superimposed with branch-associated inputs, including VEGF signaling toward NCAM1-positive endothelial-transition cells. Lineage tracing showed that PDGFRA- and NCAM1-expressing lineages contributed to vascular- and nerve/glial-associated regenerative compartments. Functionally, partial NCAM1 perturbation reduced vascular organization while increasing hair follicle neogenesis, whereas stronger inhibition impaired both outcomes. These findings identify NCAM1 as a regulator of regenerative competence and fate specification within a regenerative competence field rather than a marker of a single terminal lineage. We propose that regenerative wounds activate an NCAM1-associated fibroblast competence field whose quantitative modulation biases competent fibroblasts toward alternative outcomes.

cell biology↗

Manipulating Excitation-Inhibition Balance by Temporal Interference Brain Stimulation at Different Frequencies

Temporal interference brain stimulation (TIBS) is a non-invasive neuromodulation approach that can reach deep brain targets by delivering two kilohertz-frequency currents through scalp electrodes, producing a low-frequency amplitude envelope where the fields intersect. Conventional deep brain stimulation suppresses its targets at 130 Hz, and TIBS studies of epilepsy have adopted the same range. However, which neurons TIBS recruits at different frequencies has never been measured. Here, we recorded from genetically defined populations in the mouse hippocampus across envelope frequencies from 10 to 130 Hz, using cell-type-specific fiber photometry, retrograde viral labelling, and immunohistochemistry. A 10 Hz envelope drives both glutamatergic pyramidal neurons and GABAergic interneurons. From 20 Hz onward pyramidal activity falls below baseline while interneuron activity keeps rising, and the two separate maximally at 100 Hz. Retrogradely labelled cortical neurons projecting to CA2 respond weakly and show no frequency dependence, placing the switch inside the local circuit, and c-fos co-staining identifies parvalbumin interneurons as the population recruited at 100 Hz. Overall, this study provides the first in vivo cell-type-resolved evidence for envelope-frequency-dependent neuromodulation and shows that TIBS envelope frequency is a tunable parameter for excitation-inhibition balance. These findings can guide the choice of envelope frequency in the clinical research of TIBS.

neuroscience↗

Accounting for DNA Recovery and Cell Culturability Enhances Quantitative Compatibility of Molecular and Legiolert Assays for Legionella pneumophila

Disagreement between molecular and culture-based assays for Legionella pneumophila detection is widely reported, yet comparisons have largely been based on direct assay-derived concentrations or binary positive/negative outcomes. However, it remains unclear whether molecular-culture disagreement reflects concentration-level incompatibility or unaccounted methodological and physiological differences related to DNA recovery and cell culturability. In this study, we also observed disagreement between molecular and Legiolert assays in source and finished drinking water samples collected from eight full-scale drinking water systems across the United States. Molecular thresholds adjusted for DNA recovery and cell culturability only partially resolved these discrepancies. We therefore developed a probabilistic Monte Carlo framework that incorporates sample-specific DNA recovery and cell culturability to evaluate the quantitative consistency of culturable L. pneumophila concentrations estimated by molecular and Legiolert assays. Quantitatively consistent and inconsistent samples occurred across both binary concordant and discordant classifications, demonstrating that positive/negative agreement poorly reflects concentration-level comparability. Overall, molecular and Legiolert assays showed strong quantitative consistency once sample-specific DNA recovery and cell culturability were considered. A small proportion of persistent inconsistencies at specific sampling sites, coupled with atypical microbial indicators, suggest that sample heterogeneity likely contributed to the remaining discrepancies. These findings demonstrate that integrating DNA recovery and cell culturability enhanced quantitative consistency between molecular and Legiolert assays and supports the use of molecular methods as rapid quantitative tools to complement culture-based L. pneumophila monitoring. SynopsisAccounting for DNA recovery and cell culturability revealed broad quantitative compatibility between molecular and Legiolert assays for Legionella pneumophila in drinking water. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/739452v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1e01cdcorg.highwire.dtl.DTLVardef@86bbc2org.highwire.dtl.DTLVardef@190fc66org.highwire.dtl.DTLVardef@1aa9ec8_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

Legionella and Mycobacterium populations exhibit geographic structuring across and within drinking water systems

Opportunistic pathogens (OPs) within the Legionella and Mycobacterium can persist and sometimes proliferate in drinking water systems and pose a risk to public health. Most prior research has focused on isolated system components of the drinking water treatment and distribution system and has rarely examined spatiotemporal dynamics across the entire source water, treatment process, and distribution system continuum. This study addresses this critical knowledge gap by quantitative profiling of microbial communities with full length 16S rRNA gene sequencing and flow cytometry, and associated water chemistry parameters, including disinfection byproducts (DBPs), across five full-scale utilities. These utilities reflect varying source water types, geographic locations, treatment regimes, and climate zones. Microbial communities, including Legionella and Mycobacterium populations, in distribution system were shaped by source water type and exhibited significant community divergence across utilities. Within the same genus, strain-level analyses revealed highly distinct Legionella and Mycobacterium sequence variants unique to each utility. Interestingly, a substantial proportion of Legionella and Mycobacterium amplicon sequence variants were both utility specific and often specific to locations within the distribution system, indicating strong geographic structuring both across and within drinking water systems. Understanding the mechanistic underpinnings of this geographic structuring is critical to develop robust strategies for managing and monitoring Legionella and Mycobacterium populations in drinking water systems.

microbiology↗

scDock: Streamlining drug discovery targeting cell-cell communication via scRNA-seq analy-sis and molecular docking

SummaryIdentifying drugs that target intercellular communication networks represents a promising therapeutic strategy, yet linking single-cell RNA sequencing (scRNA-seq) analysis to structure-based drug screening remains technically challenging and requires substantial bioinformatics expertise. We present scDock, an integrated and user-friendly pipeline that seamlessly connects scRNA-seq data processing, cell-cell communication inference, and molecular docking-based drug discovery. Through a single configuration file, users can execute the complete workflow, from raw scRNA-seq data to ranked drug candidates, without programming skills. scDock automates the identification of disease-relevant ligand-receptor interactions from scRNA-seq data and perfoms structure-based virtual screening against these communication targets using Protein Data Bank (PDB) or AlphaFold-predicted protein structures. The pipeline generates comprehensive outputs at each stage, enabling users to explore intercellular signaling alterations and discover therapeutic compounds targeting specific cell-cell communications. scDock addresses a critical gap by providing an accessible end-to-end solution for communication-targeted drug discovery from single-cell data. Availability and ImplementationscDock is freely available at https://github.com/Andrewneteye4343/scDock. It is implemented in R, Python, shell scripts, and supports Linux systems, including Ubuntu and Debian.

bioinformatics↗

Novel Tissue Mechanics-Guided Cellular Flows Enable the Evolution of Feather Follicles

Complex tissue architecture is achieved through multiple rounds of morphological transitions. Here, we analyzed cellular flows and tissue mechanics during avian skin development. We showed how novel cellular flows initiate chemo-mechanical circuits that guide epithelial protrusion, folding, invagination, and spatial cell fate specification. In the initial feather bud formation, stiff dermal condensates protrude vertically out of the locally softened epithelial sheet. As the bud elongates, it stretches the epithelial cells at the base, which mechanically activates YAP and causes the epithelial sheet to fold downward and form a stiff cylindrical wall that invaginates into the skin. This stiff epithelial tongue is essential to the compaction and formation of the tightly packed dermal papillae. These topological transformational events are mechanically interconnected, and the completion of the previous circuit initializes the next one. On the contrary, during scale development, its rigid epithelial sheet restricts dermal cell flows, preventing other further topological transformation. We generated a topological transformation model to show how the process enables the novel evolution of feather follicles.

developmental biology↗

Coronavirus NSP14 Drives Internal m7G Modification to Rewire Host Splicing and Promote Viral Replication

SARS-CoV-2, the causative agent of COVID-19, manipulates host gene expression through multiple mechanisms, including disruption of RNA processing. Here, we identify a novel function of the viral nonstructural protein 14 (NSP14) in inducing N7-methylguanosine (m7G) modification in the internal sequences of host mRNA. We demonstrate that NSP14 catalyzes the conversion of guanosine triphosphate (GTP) to m7GTP, which is subsequently incorporated into mRNA by RNA polymerase II, resulting in widespread internal m7G modification. This activity is dependent on NSP14s N7-methyltransferase (N7-MTase) domain and is enhanced by interaction with NSP10. Internal m7G modification by NSP14 predominantly occurs in the nucleus and is conserved across alpha-, beta- and gamma-coronaviruses. Mechanistically, we show that this RNA modification disrupts normal splicing by promoting intron retention and generating novel splice junctions, particularly in genes regulating genome stability, RNA metabolism and nuclear processes. Importantly, inhibition of m7G modification, through pharmacological targeting of NSP14 or RNA polymerase II, impairs SARS-CoV-2 replication, indicating that the virus hijacks host transcriptomic machinery to support infection. Our findings reveal a previously unrecognized epitranscriptomic mechanism by which coronaviruses reprogram host gene expression and suggest that NSP14-induced m7G modification is a potential therapeutic target.

microbiology↗

Airway microbiome-host transcriptome networks link microbial dysbiosis to survival outcomes and therapeutic opportunities in severe COVID-19

The lower respiratory tract microbiome may critically influence outcomes in severe COVID-19, yet remains understudied. We analyzed bronchoalveolar lavage fluid from 86 severe patients requiring mechanical ventilation, stratified into two groups. We identified 213 bacteria with differential abundance, 11 bacteria associated with differentially expressed genes, and 39 of them were associated with patient survival. The more serious group exhibited reduced microbial network complexity, suggesting ecosystem disruption. To explore therapeutic potential, we employed our previously published model and predicted that compounds like palbociclib, XMD-1499, RS-17053, and RS-504393 may shift host gene expression favoring beneficial microbial signatures. These results highlight an important link between microbial dysbiosis and COVID-19 severity, offering promising directions for microbiome-informed therapeutic strategies. Our findings underscore the importance of the lung microbiome in modulating host responses and clinical outcomes, and suggest that modulating microbial-host interactions may serve as a novel adjunctive approach in the treatment of severe COVID-19. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/661228v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@2fc879org.highwire.dtl.DTLVardef@1128d5dorg.highwire.dtl.DTLVardef@fef0eaorg.highwire.dtl.DTLVardef@17aa499_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

Cell barcoding with tandem fluorescent proteins enables high-throughput signaling dynamics analysis

Cell barcodes are essential for a wide array of experimental applications, including lineage tracing, genetic screening, and single-cell analysis. An optimal barcode library would provide high diversity, live-cell compatible identification, and simple readout. In this work, we introduce single chain tandem fluorescent protein (sctFP) barcodes, constructed by linking different fluorescent proteins (FPs) into a single polypeptide chain with varied copy numbers. We found that the fluorescence signal intensity ratio at different wavelengths can reliably differentiate sctFPs generated using cnidarian FPs, but not prokaryotic FPs that require exogenous cofactors. The sctFPs enable the multiplexing of genetically encoded fluorescent biosensors, enhancing current biosensor multiplexing methods through a simplified imaging and analysis pipeline that support high-throughput applications. Their robust spectral profiles are compatible with a broad range of biosensor types. Using sctFPs, we demonstrate simultaneous tracking of various signaling activities with biosensors of different spectral properties. Together, this strategy provides a robust and scalable method for barcoding cells across diverse experimental contexts.

cell biology↗

AI-powered integration of multi-source data for TAA discovery to accelerate ADC and TCE drug development (I): TAA Target Identification and Prioritization

The advancement of T-cell engagers (TCEs) and antibody-drug conjugates (ADCs) has been hindered by fragmented data landscapes. This paper, the first in a series, introduces an AI-driven framework specifically for tumor-associated antigen (TAA) target identification and prioritization, a critical initial step in TCE and ADC development. Our framework integrates diverse datasets-- including multi-omics repositories and information from scientific publications--to systematically enhance the discovery of TAAs. We have developed a graph retrieval-augmented generation (RAG)-enhanced language model that extracts insights from biological and clinical literature, while integrating curated public oncology-related omics databases such as TCGA, GTEx, single-cell atlases, and additional omics datasets. This approach prioritizes TAAs with high tumor selectivity and low on-target/off-tumor risk. By unifying diverse knowledge sources, our method provides a scalable, efficient, and data-agnostic strategy to address attrition challenges in both ADC and TCE drug development pipelines, focusing initially on TAA target identification and prioritization to transform the landscape of cancer therapeutics.

bioinformatics↗

The pseudoknot structure of a viral RNA reveals a conserved mechanism for programmed exoribonuclease resistance

Exoribonuclease-resistant RNAs (xrRNAs) are viral RNA structures that block degradation by cellular 5'-3' exoribonucleases to produce subgenomic viral RNAs during infection. Initially discovered in flaviviruses, xrRNAs have since been identified in wide range of RNA viruses, including those that infect plants. High sequence variability among viral xrRNAs raises questions about the shared molecular features that characterize this functional RNA class. Here, we present the first structure of a plant-virus xrRNA in its active exoribonuclease-resistant conformation. The xrRNA forms a 9 base pair pseudoknot that creates a knot-like topology similar to that of flavivirus xrRNAs, despite lacking sequence similarity. Biophysical assays confirm a compact pseudoknot structure in solution, and functional studies validate its relevance both in vitro and during infection. Our study reveals how viral RNAs achieve a common functional outcome through highly divergent sequences and identifies the knot-like topology as a defining feature of xrRNAs.

biochemistry↗

Epstein-Barr viral product-containing exosome facilitates LIF-associated immunosuppressive polarization of macrophage in nasopharyngeal carcinoma

Epstein-Barr virus (EBV)-associated nasopharyngeal carcinoma (NPC) is characterized by a highly infiltrated, yet immunosuppressive, tumor microenvironment (TME) in which tumor-associated macrophages (TAMs) play a central role in tumor progression. In this study, we identified exosome-mediated delivery of the EBV oncoprotein LMP1, which acts via induction of leukemia inhibitory factor (LIF), as a key mechanism driving immunosuppressive macrophage polarization. Immunohistochemistry revealed that, in addition to tumor cells, LIF is primarily expressed by stromal TAMs and correlates with poor prognosis. We demonstrated that LMP1-containing exosomes are internalized by macrophages, leading to NF-{kappa}B-dependent upregulation of LIF and polarization toward an immunosuppressive M2d-like phenotype. These macrophages exhibit impaired anti-tumor activity and promote tumor proliferation and vascular dissemination in a LIF-dependent manner. Single-cell transcriptomic analyses of exosome-treated NPC biopsies revealed transcriptional reprogramming across tumor, myeloid, and lymphoid compartments impacting epithelial-mesenchymal transition (EMT); extracellular matrix (ECM) remodeling in tumor cells; immunosuppressive signaling (e.g., CD163 anti-inflammatory and VEGF signaling in macrophages); and enrichment of immune checkpoints and pathways, including PD-1, TGF{beta}-SMAD, and NF-{kappa}B-associated pathways in T cells. Exosome treatment increased expansion of CCL18+-TAMs and expression of CTLA4 in regulatory T cells and exhausted T cells. Immunohistochemistry further confirmed a positive correlation between expression of LIF and CTLA4 in NPC tumors and an inverse correlation between LIF and GZMB/CD8A. These findings define an exosome-driven LMP1-LIF axis that orchestrates immune suppression in NPC and suggest potential targets for restoring anti-tumor immunity.

cancer biology↗

Spatial Transcriptomic Profiling Of Advanced Ovarian Clear Cell Carcinoma Reveals Intra-Tumor Heterogeneity In Epithelial-Mesenchymal Gradient

Intratumoral heterogeneity is intrinsically comprised of molecular alterations of tumor cells and extrinsically from interconnections with microenvironments. This study explores the spatial heterogeneity of ovarian clear cell carcinoma (OCCC), a rare cancer with significance to East Asian women. We profile 21 primary-metastatic tumor pairs in a discovery cohort and 16 tumors in two validation cohorts using spatial transcriptomic (ST) platforms. Our integrative analysis revealed an inverse relationship between OXPHOS and inflammation along the EMT gradient. OCCC cells undergoing partial EMT have metabolic shifts and lose LCN2 expression, possibly via concomitant down-regulation of SOX9. Conversely, LCN2 expression correlated with OXPHOS-enriched tumor signature, low EMT, and better outcomes in OCCC. Single-cell ST profiling using CosMx further identifies nine spatially distinct cancer cell populations including the LCN2-high cancer subclone with a high epithelial score. SOX9 induction could partially restore epithelial-ness in LCN2-low cells suggesting that plasticity in OCCC is achieved via transcriptional reprogramming. Our findings provide further insights into epithelial-mesenchymal plasticity and the adaptive interactions between cancer cells and their microenvironments in OCCC.

cancer biology↗

Calibration of FRET-based biosensors using multiplexed biosensor barcoding

Forster resonance energy transfer (FRET) between fluorescent proteins (FPs) is widely used in the design of genetically encoded fluorescent biosensors, which are powerful tools for monitoring the dynamics of biochemical activities in live cells. FRET ratio, defined as the ratio between acceptor and donor signals, is often used as a proxy for the actual FRET efficiency, which must be corrected for signal crosstalk using donor-only and acceptor-only samples. However, the FRET ratio is highly sensitive to imaging conditions, making direct comparisons across different experiments and over time challenging. Inspired by a method for multiplexed biosensor imaging using barcoded cells, we reasoned that calibration standards with fixed FRET efficiency can be introduced into a subset of cells for normalization of biosensor signals. Our theoretical analysis indicated that the FRET ratio of high-FRET species relative to non-FRET species slightly decreases at high excitation intensity, suggesting the need for calibration using both high and low FRET standards. To test these predictions, we created FRET donor-acceptor pairs locked in "FRET-ON" and "FRET-OFF" conformations and introduced them into a subset of barcoded cells. Our results confirmed the theoretical predictions and showed that the calibrated FRET ratio is independent of imaging settings. We also provided a strategy for calculating the FRET efficiency. Together, our study presents a simple strategy for calibrated and highly multiplexed imaging of FRET biosensors, facilitating reliable comparisons across experiments and supporting long-term imaging applications.

biophysics↗

Nuclear phylogenomics of grasses (Poaceae) supports current classification and reveals repeated reticulation

O_LIGrasses (Poaceae) comprise around 11,800 species and are central for human livelihoods and terrestrial ecosystems. Knowing their relationships and evolutionary history is key to comparative research and crop breeding. Advances in genome-scale sequencing allow for increased breadth and depth of phylogenomic analyses, making it possible to infer a new reference species tree of the family. C_LIO_LIWe inferred a comprehensive species tree of grasses by combining new and published sequences for 331 nuclear genes from genome, transcriptome, target enrichment and shotgun data. Our 1,153-tip tree covers 79% of grass genera (including 21 genera sequenced for the first time) and all but two small tribes. We compared it to a 910-tip plastome tree. C_LIO_LIThe nuclear phylogeny matches that of the plastome at most deep branches, with only a few instances of incongruence. Gene tree-species tree reconciliation suggests that reticulation events occurred repeatedly in the history of grasses. C_LIO_LIWe provide a robust framework for the grass tree of life to support research on grass evolution, including modes of reticulation, and genetic diversity for sustainable agriculture. C_LI

plant biology↗

Self-organizing glycolytic waves fuel cell migration and cancer progression

Glycolysis has traditionally been thought to take place in the cytosol but we observed the enrichment of glycolytic enzymes in propagating waves of the cell cortex in human epithelial cells. These waves reflect excitable Ras/PI3K signal transduction and F-actin/actomyosin networks that drive cellular protrusions, suggesting that localized glycolysis at the cortex provides ATP for cell morphological events such as migration, phagocytosis, and cytokinesis. Perturbations that altered cortical waves caused corresponding changes in enzyme localization and ATP production whereas synthetic recruitment of glycolytic enzymes to the cell cortex enhanced cell spreading and motility. Interestingly, the cortical waves and ATP levels were positively correlated with the metastatic potential of cancer cells. The coordinated signal transduction, cytoskeletal, and glycolytic waves in cancer cells may explain their increased motility and their greater reliance on glycolysis, often referred to as the Warburg effect.

biochemistry↗

Targeting Ras signaling excitability in cancer cells through combined inhibition of FAK and PI3K

The Ras/PI3K/ERK signaling network is frequently mutated in various human cancers including cervical cancer and pancreatic cancer. Previous studies showed that the Ras/PI3K/ERK signaling network displays features of excitable systems including propagation of activity waves, all-or-none responses, and refractoriness. Oncogenic mutations lead to enhanced excitability of the network. A positive feedback loop between Ras, PI3K, the cytoskeleton, and FAK was identified as a driver of excitability. In this study, we investigated the effectiveness of targeting signaling excitability by inhibiting both FAK and PI3K in cervical and pancreatic cancer cells. We found that the combination of FAK and PI3K inhibitors synergistically suppressed the growth of select cervical and pancreatic cancer cell lines through increased apoptosis and decreased mitosis. In particular, FAK inhibition caused downregulation of PI3K and ERK signaling in cervical cancer but not pancreatic cancer cells. Interestingly, PI3K inhibitors activated multiple receptor tyrosine kinases (RTKs), including insulin receptor and IGF-1R in cervical cancer cells, as well as EGFR, Her2, Her3, Axl, and EphA2 in pancreatic cancer cells. Our results highlight the potential of combining FAK and PI3K inhibition for treating cervical and pancreatic cancer, although appropriate biomarkers for drug sensitivity are needed, and concurrent targeting of RTKs may be required for resistant cells.

cancer biology↗

High-Contrast PET imaging with -NT160, a Class-IIa Histone Deacetylase (Class-IIa HDAC) Probe for In Vivo Imaging of Epigenetic Machinery in the Central Nervous System

We utilized positron emission tomography (PET) imaging in vivo to map the spatiotemporal biodistribution/expression (protein density) of class-IIa histone deacetylases (class-IIa HDACs) in the brain. Herein, we report an improved radiosynthesis of [18F]-NT160 using 4-hydroxy-TEMPO which led to a significant improvement in radiochemical yield and molar activity. PET imaging with [18F]-NT160, a highly potent class-IIa HDAC inhibitor with sub-nM affinity for HDAC4 and 5 isoforms, led to high-quality and high-contrast images among various brain regions. [18F]-NT160 displayed excellent pharmacokinetic and imaging characteristics: brain uptake is high in gray matter regions, leading to high-quality PET images; tissue kinetics are appropriate for an 18F tracer and specific binding for class-IIa HDACs is demonstrated by self-blockade. Higher uptake with [18F]-NT160 was observed in the hippocampus, thalamus, and cortex while there was relatively lower uptake in the cerebellum and striatum. Overall, our current studies with [18F]-NT160 will likely facilitate the development and clinical translation of class-IIa HDACs of the next generation of PET tracers for imaging and targeted therapy of cancer and the diseases of the central nervous system (CNS).

neuroscience↗