Biology subjects

Fan, W.

Publications and source records attributed to Fan, W..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Graph-based tracing of dynamically functioning gene circuits in cell fate decisions with isoform resolution

Transcription factor (TF) regulatory networks govern complex cellular processes, yet their inference from single-cell transcriptomes is hindered by TFs low abundance, tissue-specific functions, and isoform diversity. We evaluated the utility of transcription factor activity (TFA) to infer TF-TF interactions, demonstrating its superiority over expression-based methods in capturing tissue-specific, high-fidelity regulatory relationships. Using simulated and real-world transcriptomes across human hematopoiesis and early embryonic development, we validated TFAs ability to render regulatory relationships. Through utilizing the concept of propagated regulome, we uncovered TFAs utility in retrospectively resolving dynamic regulatory circuits. To address regulome limitations, we developed an embryonic stem cell-specific Consensus REgulome Database (CRED) with isoform resolution, revealing functional heterogeneity among TF isoforms. Applied to human preimplantation single-cell datasets, CRED outperformed existing regulomes, identifying isoform-specific regulators and tracing regulatory modules despite severe dropouts. Our work unleashes TFA as a robust tool for reconstructing TF networks and highlights the importance of transited, isoform-level, cell-type-specific analysis in unraveling transcriptional regulatory circuits. HighlightsO_LITFA (Transcription Factor Activity) renders regulatory relationships with high fidelity compared to expression. C_LIO_LIUsing transited regulons enables TFA to retrospectively resolve dynamic regulatory interactions in cell fate decisions. C_LIO_LIAn integrated ESC-specific transited regulome database reveals isoform-level heterogeneity. C_LIO_LITFA successfully identifies key TF regulatory modules during human preimplantation from datasets with severe dropout. C_LI

systems biology↗

bioRxiv2025

Vis-OCT Explorer: an open-source software for visible-light optical coherence tomography data processing

Background and objectivesVisible-light optical coherence tomography (vis-OCT) has enabled the visualization of retinal structures and functions beyond the capabilities of conventional OCTs. However, to reconstruct high-quality images, vis-OCT requires special post-processing, including balanced detection. An open-source, standardized vis-OCT data processing software is essential for clinical applications and translation of vis-OCT. MethodsWe developed Vis-OCT Explorer, an open-source, modular Python-based software for processing vis-OCT images. In addition to the standard spectral-domain OCT processing pipeline - including k-space resampling, dispersion compensation, and fast Fourier transformation - Vis-OCT Explorer offers unique dual-spectrometer balanced detection, short-time-Fourier transformation (STFT) based dispersion compensation coefficient optimization, and GPU-accelerated processing. We evaluated the reconstruction performance by quantifying a quality index extracted from individual B-scan images. We also assessed the repeatability of retinal thickness measurements by five operators on images acquired from different testing sites using the intraclass correlation coefficient (ICC) analysis. ResultsBalanced detection and STFT-based dispersion compensation significantly increased the quality index of reconstructed B-scan images. ICC values of the retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) thickness measurements from four testing sites exceeded 0.8 in 87.5% of the macular-centered images. The ICC of RNFL thickness measurements on all optic nerve head-centered images is above 0.8, showing strong repeatability across users. ConclusionsVis-OCT Explorer provides high-quality image processing and enables highly repeatable measurements on vis-OCT human retinal images. It facilitates future multicenter clinical tests to validate vis-OCTs clinical efficacy.

bioengineering↗

bioRxiv2025

A universal law of thermodynamics-kinetics coupling shapes enzyme allocation and glycolytic efficiency across species

Efficient use of limited cellular resources is fundamental to metabolism. Although flux optimization is widely recognized as a central objective of metabolic networks, how flux efficiency influences the allocation of the metabolic proteome remains unclear and lacks direct validation. Here, we derive a simple analytical relationship linking the equilibrium constant and the catalytic-abundance quotient of reactions within a pathway that defines the condition for maximal efficiency. We refer to this principle as the law of thermodynamics-kinetics coupling. By integrating reaction thermodynamics, enzyme kinetics, transcriptomic, and proteomic data, we show that glycolytic enzyme allocation consistently obeys this law across evolutionarily distant species. Moreover, the drive to optimize glycolytic efficiency is strengthened under oncogenic signaling and limited cellular budget for glycolytic enzymes. These findings establish a universal principle governing enzyme allocation in metabolic pathways and reveal key determinants of efficiency optimality in glycolysis. Significance statementCurrent models of metabolic optimality either rely on coarse-grained proteome allocation or constraint-based simulations, largely neglecting the fundamental constraints imposed by enzyme kinetics and thermodynamics on pathway efficiency. Here, we derive and validate a universal law of thermodynamics-kinetics coupling that robustly governs the allocation of glycolytic enzymes across species under optimal efficiency. This study has three major advances: it reveals universal economic principles of metabolism with simple, generalized mathematical form, uncovers determinants underlying the heterogeneity of metabolic efficiency optimization, and provides a practical blueprint for efficiency optimization of engineered pathways.

systems biology↗

bioRxiv2025

BIN1 deficiency leads to DNA damage and neuronal insulin resistance through ATM dysregulation

The major neuronal isoform of the AD risk gene BIN1 is specifically reduced in patients. In the present work, we demonstrate that BIN1 is necessary for intact insulin signaling and its loss leads to cellular-level insulin resistance. Persistently activated mTORC1 feedback inhibits the insulin signaling; meanwhile, ATM-dependent DNA Damage Response decreases the expression of multiple insulin signaling pathway members. Unexpectedly, nuclear ATM activation is accompanied by autophagic degradation of the cytoplasmic ATM, rendering neurons susceptible to oxidative stress, which predisposes oxidative DNA damage, DNA strand breaks, and ATM-dependent DNA Damage Response. Treating BIN1-deficient mice with rapamycin or liraglutide to improve the insulin response, or with the natural antioxidant alpha-lipoic acid to attenuate oxidative stress, both effectively preserved the spatial cognitive ability. Lastly, we reanalyzed a single-cell transcriptomic dataset from human neurons and identified positive correlations between levels of BIN1 and the insulin signaling, as well as neuronal activity. Together, this work revealed an ATM-centered mechanism that globally damages neuronal health in BIN1-deficient pyramidal neurons, which could be a driving force in the AD disease course.

cell biology↗

bioRxiv2025

Integrin-binding matricellular protein fibulin-5 maintains epidermal stem cell heterogeneity during skin aging

The extracellular matrix (ECM) is crucial in building the extracellular environment and translating extracellular information into biochemical signals that sustain organ functions. Fibulin-5 (Fbln5) is a multifunctional ECM protein essential for forming elastic fibers and regulating cellular functions by binding to integrins. While fibulin-5 expression decreases with age in human skin, the functional implications of this decrease, particularly in epidermal stem cell regulation, have remained largely unexplored. Here, we find that the knocking out of Fbln5 in mice results in early impairments of epidermal stem cell properties, similar to the chronological aging of the skin. The Fbln5 deficiency suppresses the expression of integrins and other cell junction proteins, leading to the inactivation of YAP signaling in epidermal stem cells. This reduction in YAP signaling results in the downregulation of the fast-cycling epidermal stem cell marker SLC1A3 in human skin and primary keratinocytes. These results suggest that, in addition to its known function in elastic fiber formation, fibulin-5 also plays a critical role in regulating the balance of epidermal stem cell populations during skin aging and coordinating the crosstalk between the extracellular environment and intracellular signaling.

developmental biology↗

bioRxiv2025

Stress Granule Formation Drives ZBP1-dependent Necroptosis in Non-obstructive Azoospermia and Aging testes

Male infertility and age-related reproductive decline remain major unmet medical challenges, with limited understanding of the underlying mechanisms. Here, we identify a stress granule-driven necroptosis pathway involving ZBP1 and RIPK3 as a central driver of non-obstructive azoospermia (NOA), a severe form of male infertility marked by loss of spermatogenesis. We show that heat stress or environmental insults activate eIF2 kinases, inducing stress granules that recruit ZBP1 and RIPK3 to form a signaling complex. This leads to RIPK3 activation, MLKL phosphorylation, and necroptotic death of spermatogonia and Sertoli cells. Genetic ablation of Zbp1 or Ripk3 protects mice from heat-induced testicular atrophy, highlighting their essential role in testicular cell death. Notably, this same necroptosis pathway is also activated in aged human testes, suggesting a shared mechanism driving both male infertility and age-related testicular degeneration.

molecular biology↗

bioRxiv2025

Synthesizing human-specific spike-in standards for RNA-seq experiments and assessing their technical performance

Using spike-in standards for RNA-seq experiments is critical to evaluate technical bias introduced during sample preparation, sequencing and analysis. Although some external RNA spike-in standards have been developed, species-specific spike-in standard was not reported yet. Here we developed the human-specific spike-in standards with 65 controls. We first extracted human endogenous RNAs with various lengths and GC contents, introduced random mutations approximately every 75 bp in each RNA, and then synthesized these RNAs as spike-in RNAs. After that, four mixtures of these spike-in RNAs covering a 220 dynamic range were obtained. To ensure the accuracy of RNA concentration, two rounds of ddPCR were conducted for each spike-in RNA and the intraclass correlation coefficient between two ddPCRs ranged from 0.9954 to 0.9971 after removing the two spike-in RNAs with the largest concentration difference. Furthermore, we showed that the sequencing error profiles were distinct between platforms and the library preparation procedures were related with the discrepancies in spike-in RNA read percent, transcript abundance, sequence coverage distribution, and differential gene expression. In addition, two regression models of sequence coverage were built based on RNA second structure and GC content, and 86.62%-91.78% of the variation can be explained. Our study demonstrates the technical performance of the human-specific spike-in standards for RNA-seq experiments and illustrates the biases across different libraries, platforms, and laboratories.

bioinformatics↗

bioRxiv2025

The hollow truth: ethylene-triggered ROS, PCD, senescence, and autophagy drive hollow stem formation

Hollow stems have independently evolved multiple times across the plant kingdom, and play crucial roles in plant development and various environmental adaptations. However, the mechanisms underlying stem hollowness remain poorly understood. Water spinach (Ipomoea aquatica) is one of the few hollow-stemmed plants in the Convolvulaceae family, and its hollow stems are essential for thriving in aquatic environments. Using histochemical staining and transcriptome analysis, we identified programmed cell death (PCD) is involved in cavity formation of water spinach shoot tips. Single-cell transcriptome analysis further revealed that ethylene and reactive oxygen species (ROS) drive and regulate this process by activating transcription factors IaNAC074, IaNAC087, IaNAC029, IaNTL9, and IaTGA9, which initiate PCD, senescence, and autophagy, collectively controlling cell death. These findings were validated through treatments with ethylene and ROS reagents in water spinach and transient expression in tobacco. Additionally, transcriptomic data suggest that these mechanisms may also play a role in hollow stem formation in bamboo, highlighting the conservation of PCD regulatory mechanisms in plant development. This work not only fills a major knowledge gap in the adaptive mechanisms of hollow stem formation but also opens new avenues for agricultural and ecological applications, offering strategies to enhance crop tolerance to flooding and accelerate crop growth.

plant biology↗

bioRxiv2025

Expanding single-cell toolbox with a cost-effective full-length total RNA droplet-based sequencing technology

sc-rDSeq is a scalable, full-length total RNA droplet-based technology that captures both polyadenylated and non-polyadenylated RNAs, including histone-RNAs, small and long non-coding RNAs, and enhancer RNAs. It achieves a tenfold increase in UMIs per cell over inDrops while remaining simple and cost-efficient. Applied to lung cancer cells, sc-rDSeq revealed hidden heterogeneity, divergent signaling pathways, and non-polyA RNA variations undetectable with 3 end-based methods. In EGFR inhibitor-treated persister cells, it confirmed drug-induced cell cycle arrest based on histone mRNA expression, identified distinct resistance strategies. It also detected alternative splicing events and enabled single cell genotyping of SNVs linked to drug resistance. While SNVs act as drivers of drug resistance, additional layers of expression-based cellular states must be explored to fully understand and combat persister cells. These findings highlight the potential of sc-rDSeq to advance transcriptomic studies and personalized medicine by providing a comprehensive and scalable approach to cellular RNA analysis.

genetics↗

bioRxiv2025

Leopard Cats Occupied Human Settlements in China for 3,500 years before the Arrival of Domestic cats in 600-900 CE around the Tang Dynasty

The earliest cats in human settlements in China were not domestic cats (Felis catus), but native leopard cats (Prionailurus bengalensis). To trace when and how domestic cats arrived in East Asia, we analyzed 22 feline bones from 14 sites across China spanning 5,000 years. Nuclear and mitochondrial genomes revealed that leopard cats began occupying anthropogenic scenes around 5,400 years ago and last appeared in 150 CE. Following several centuries gap of archeological feline remains, the first known domestic cat (706-883 CE) in China was identified in Shaanxi during the Tang Dynasty. Genomic analysis suggested a white or partially white coat and a link to a contemporaneous domestic cat from Kazakhstan, indicating a likely dispersal route via the Silk Road. The two felids once independently occupied ancient anthropogenic environments in China but followed divergent paths and reached different destinations in human-animal interactions.

evolutionary biology↗

bioRxiv2024

Revealing long-range heterogeneous organization of nucleoproteins with N6-methyladenine footprinting

A major challenge in epigenetics is uncovering the dynamic distribution of nucleosomes and other DNA-binding proteins, which plays a crucial role in regulating cellular functions. Established approaches such as ATAC-seq, ChIP-seq, and CUT&RUN provide valuable insights but are limited by the ensemble nature of their data, masking the cellular and molecular heterogeneity that is often functionally significant. Recently, long-read sequencing technologies, particularly Single Molecule, Real-Time (SMRT/PacBio) sequencing, have introduced transformative capabilities, such as N6-methyladenine (6mA) footprinting. This technique enables the detection of joint binding events and long-range chromatin organization on individual DNA molecules spanning multiple kilobases. Despite the potential of 6mA footprinting, existing analytical tools for 6mA detection in SMRT sequencing data suffer from significant limitations in both performance and applicability, especially with the latest sequencing platform. To address these gaps, we developed a novel 6mA-calling pipeline based on polymerase kinetics analysis. Our approach significantly outperforms current tools in terms of accuracy and computational efficiency, setting a new benchmark for 6mA detection. Utilizing our optimized experimental and computational framework, we extensively mapped nucleosome positioning and transcription factor occupancy at the single-molecule level, revealing critical features of the transcription-associated epigenetic landscape. Additionally, our work established high-resolution, long-range binding events in mitochondrial DNA, revealing simultaneous loading of two sets of replication machinery onto the displacement loop (D-loop). Our study highlights the potential of 6mA footprinting in capturing the coordinate binding of nucleoproteins and unraveling heterogeneous epigenetic states with unprecedented resolution.

bioinformatics↗

bioRxiv2024

Ribosomal RNA transcription governs splicing through ribosomal protein RPL22

Ribosome biosynthesis is a cancer vulnerability executed by targeting RNA polymerase I (Pol I) transcription. We developed advanced, specific Pol I inhibitors to identify drivers of this sensitivity. By integrating multi-omics features and drug sensitivity data from a large cancer cell panel, we discovered that RPL22 frameshift mutation conferred Pol I inhibitor sensitivity in microsatellite instable cancers. Mechanistically, RPL22 directly interacts with 28S rRNA and mRNA splice junctions, functioning as a splicing regulator. RPL22 deficiency, intensified by 28S rRNA sequestration, promoted the splicing of its paralog RPL22L1 and p53 negative regulator MDM4. Chemical and genetic inhibition of rRNA synthesis broadly remodeled mRNA splicing controlling hundreds of targets. Strikingly, RPL22-dependent alternative splicing was reversed by Pol I inhibition revealing a ribotoxic stress-initiated tumor suppressive pathway. We identify a mechanism that robustly connects rRNA synthesis activity to splicing and reveals their coordination by ribosomal protein RPL22.

molecular biology↗

bioRxiv2024

Deep Learning Driven Cell-Type-Specific Embedding for Inference of Single-Cell Co-expression Networks

The inference of gene co-expression module in specific cell types is important for understanding of cell-type-specific biological processes. We have developed DeepCSCN, an unsupervised deep-learning framework, to infer gene co-expression modules from single-cell RNA sequencing (scRNA-seq) data. Utilizing a global-to-local network construction approach, DeepCSCN can infer co-expression at the whole sample level and construct cell-type-specific co-expression networks. Systematic evaluations on eight public scRNA-seq datasets show that DeepCSCN significantly outperforms eight existing methods in co-expression network construction. Furthermore, DeepCSCN effectively identifies cell-type-specific co-expression networks that are more enriched for cell-specific functional pathways compared to current methods. Finally, application of DeepCSCN on public scRNA-seq data revealed 280 cell-specific gene modules across 27 cell types, including epithelial cells, immune cells, and myonuclei, demonstrating its versatility and accuracy in elucidating cell-type-specific gene co-expression regulation. DeepCSCN offers a powerful tool for researchers to dissect the intricate gene co-expression networks within distinct cell types.

bioinformatics↗

bioRxiv2024

Spike inference from mouse spinal cord calcium imaging data

Calcium imaging is a key method to record the spiking activity of identified and genetically targeted neurons. However, the observed calcium signals are only an indirect readout of the underlying electrophysiological events (single spikes or bursts of spikes) and require dedicated algorithms to recover the spike rate. These algorithms for spike inference can be optimized using ground truth data from combined electrical and optical recordings, but it is not clear how such optimized algorithms perform on cell types and brain regions for which ground truth does not exist. Here, we use a state-of-the-art algorithm based on supervised deep learning (CASCADE) and a non-supervised algorithm based on non-negative deconvolution (OASIS) to test spike rate inference in spinal cord neurons. To enable these tests, we recorded specific ground truth from glutamatergic and GABAergic somatosensory neurons in the superficial dorsal horn of spinal cord in mice of both sexes. We find that CASCADE and OASIS algorithms that were designed for cortical excitatory neurons generalize well to both spinal cord cell types. However, CASCADE models re-trained on our ground truth further improved the performance, resulting in a more accurate inference of spiking activity from spinal cord neurons. We openly provide re-trained models that can be applied to spinal cord data of variable noise levels and frame rates. Together, our ground-truth recordings and analyses provide a solid foundation for the interpretation of calcium imaging data from spinal cord dorsal horn and showcase how spike rate inference can generalize between different regions of the nervous system. Significance StatementCalcium imaging is a powerful method for measuring the activity of genetically identified neurons. However, accurate interpretation of calcium transients depends on having a detailed understanding of how neuronal activity correlates with fluorescence. Such calibration recordings have been performed for cerebral cortex but not yet for most other CNS regions and neuron types. Here, we obtained ground truth data in spinal cord by conducting simultaneous calcium and electrophysiology recordings in excitatory and inhibitory neurons. We systematically investigated the transferability of cortical algorithms to spinal neuron subpopulations and generated inference algorithms optimized to excitatory and inhibitory neurons. Our study provides a foundation for the rigorous interpretation of calcium imaging data from spinal cord. Conflict of interest statementThe authors declare no competing financial conflicts of interest.

neuroscience↗

bioRxiv2024

Preventing escape and malfunction of recoded cells due to tRNA base changes

Engineering the genetic code restricts DNA transfer (cellular bioisolation) and enables new chemistries via non-standard amino acid incorporation. These distinct properties make recoded cells state-of-the-art safe technologies. However, evolutionary pressures may endanger the longevity of the recoding. Here, we reveal that recoded Escherichia coli lacking 18,214 serine codons and two tRNASer can express wild-type antibiotic resistance genes and escape up to seven orders of magnitude faster than expected. We show a two-step escape process whereby recoded cells mistranslate antibiotic resistance genes to survive until modified or mutated tRNAs reintroduce serine into unassigned codons. We developed genetic-code-sensitive kill switches that sense serine incorporation and prevent cellular escape while preserving encoding of three distinct non-standard amino acids. This work lays the foundation for the long-term controlled function of cells that incorporate new chemistries, with implications for the design, use, and biosafety of synthetic genomes in clinical and environmental applications where physical containment is insufficient.

synthetic biology↗

bioRxiv2024

PRISM: Multiplexed Profiling of RNA In-Situ through Single-round of Imaging in Three-Dimensional Tissue

Spatial RNA imaging has not been widely adopted because conventional fluorescence microscopy is limited to only a few channels, and the cyclic reactions needed to increase multiplexing in techniques such as sequential fluorescence in-situ hybridization (FISH) require sophisticated instrumentation. Here, we introduce Profiling of RNA In-situ through Single-round iMaging (PRISM), a method that expands coding capacity through color intensity grading. Using a radius vector filtering strategy to ensure the distinguishability of codewords in color space, PRISM achieves up to 64-plex color-barcoded RNA imaging in a single imaging round with conventional microscopes. We validate PRISMs versatility across various tissues by generating a 3D atlas of mouse embryonic development from E12.5 to E14.5, a quasi-3D tumor-normal transition landscape of human hepatocellular carcinoma (HCC), and a 3D cell atlas and subcellular RNA localization landscapes of mouse brain. Additionally, we show the critical role of cancer-associated fibroblasts (CAFs) in mediating immune infiltration and immune response heterogeneity within and between tumor microenvironments.

bioengineering↗

bioRxiv2024

TRIM32 inhibits Venezuelan Equine Encephalitis Virus Infection by targeting a late step in viral entry

Alphaviruses are mosquito borne RNA viruses that are a reemerging public health threat. Alphaviruses have a broad host range, and can cause diverse disease outcomes like arthritis, and encephalitis. The host ubiquitin proteasome system (UPS) plays critical roles in regulating cellular processes to control the infections with various viruses, including alphaviruses. Previous studies suggest alphaviruses hijack UPS for virus infection, but the molecular mechanisms remain poorly characterized. In addition, whether certain E3 ubiquitin ligases or deubiquitinases act as alphavirus restriction factors remains poorly understood. Here, we employed a cDNA expression screen to identify E3 ubiquitin ligase TRIM32 as a novel intrinsic restriction factor against alphavirus infection, including VEEV-TC83, SINV, and ONNV. Ectopic expression of TRIM32 reduces alphavirus infection, whereas depletion of TRIM32 with CRISPR-Cas9 increases infection. We demonstrate that TRIM32 inhibits alphaviruses through a mechanism that is independent of the TRIM32-STING-IFN axis. Combining reverse genetics and biochemical assays, we found that TRIM32 interferes with genome translation after membrane fusion, prior to replication of the incoming viral genome. Furthermore, our data indicate that the monoubiquitination of TRIM32 is important for its antiviral activity. Notably, we also show two TRIM32 pathogenic mutants R394H and D487N, related to Limb-girdle muscular dystrophy (LGMD), have a loss of antiviral activity against VEEV-TC83. Collectively, these results reveal that TRIM32 acts as a novel intrinsic restriction factor suppressing alphavirus infection and provides insights into the interaction between alphaviruses and the host UPS. Author summaryDue to climate change, wildlife habitat loss, and human activities, alphavirus infections are a growing threat to public health. The host UPS has critical role in virus-host interaction, but how the UPS impact alphavirus infection is not completely understood. In this study, we found that the E3 ubiquitin ligase TRIM32 inhibits diverse alphaviruses in multiple cell types. Mechanistically, TRIM32 impairs primary translation of incoming viral genome in a manner that depends on. monoubiquitination of TRIM32. Additionally, disease-associated alleles of TRIM32 have a loss-of-function with respect to viral inhibition. Together, these findings uncover a novel biological function of TRIM32 in regulating alphavirus infection and provide important insights into the interplay between alphaviruses and the host USP.

microbiology↗

bioRxiv2024

Epigenetic delineation of the earliest cardiac lineage segregation by single-cell multi-omics

The mammalian heart is formed from multiple mesoderm-derived cell lineages. However, it remains largely unknown when and how the specification of mesoderm towards cardiac lineages is determined. Here, we systematically depict the transcriptional trajectories toward cardiomyocyte in early mouse embryo, and characterize the epigenetic landscapes underlying the early mesodermal lineage specification by single-cell multi-omics analyses. The analyses also reveal distinct core regulatory networks (CRN) in controlling specification of mesodermal lineages. We further demonstrate the essential role HAND1 and FOXF1 in driving the earliest cardiac progenitors specification. These key transcription factors occupy at distinct enhancers, but function synergistically and hierarchically to regulate the expression of cardiac-specific genes. In addition, HAND1 is required for exiting from the nascent mesoderm program, while FOXF1 is essential for driving cardiac differentiation during juxta-cardiac field (JCF) specification. Our findings establish transcriptional and epigenetic determinants specifying the early cardiac lineage, providing insights for the investigation of congenital heart defects.

molecular biology↗