Biology subjects

Jiang, W.

Publications and source records attributed to Jiang, W..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Rhamnose-mediated modulation of hair follicle growth: insights from chemical genomics

Pursuing compounds capable of stimulating hair follicle growth or regeneration presents a significant challenge in dermatological research. Dermal papilla (DP) cells, which serve as a dynamic niche for hair follicle stem cells, are often used to identify hair growth-promoting agents as a screening model. Here, we integrated human scalp single-cell RNA sequencing data with human DP cells (hDPCs) gene expression profiles to develop a gene panel for assessing hair follicle inductive potential, then applied a high-throughput sequencing-based high-throughput screening (HTS2) method to quantify the gene expressions of hDPCs perturbed by over 2000 small molecules. Notably, rhamnose was identified as a compound that restored the expression of hair-inducing genes in hDPCs. More importantly, the topical application of rhamnose accelerated hair follicle regeneration by promoting hair cycle into the anagen phase. Transcriptome and central carbon metabolism analyses revealed that rhamnose induced glucose metabolism remodeling favoring glycolysis in mice. A similar phenotype was also observed in rhamnose-treated hDPCs, as demonstrated by glycolysis and mitochondrial stress tests. The present study introduces a novel methodology for evaluating hair-inducing agents and provides valuable insights into the cellular and molecular mechanisms underlying the hair growth-promoting effects of rhamnose. These findings highlight the potential for the therapeutic application of rhamnose in the treatment of alopecia.

pharmacology and toxicology↗

bioRxiv2025

RegFormer: A Single-Cell Foundation Model Powered by Gene Regulatory Hierarchies

Single-cell RNA sequencing (scRNA-seq) enables high-resolution profiling of cellular diversity, but current computational models often fail to incorporate regulatory priors, handle data sparsity, or efficiently process long gene sequences. Here, we present RegFormer, a foundation model that integrates gene regulatory networks (GRNs) with Mamba-based state-space modeling, overcoming the scalability and context-length limitations of Transformer architectures. RegFormer encodes each gene through dual embeddings, a value embedding for quantitative expression and a token embedding for regulatory identity, organized within a GRN-guided gene order to capture both expression dynamics and hierarchical regulation. Pretrained on 26 million human single cells spanning 45 tissues and diverse biological contexts, RegFormer achieves superior scalability and biological fidelity. Across comprehensive benchmarks, it consistently outperforms state-of-the-art single-cell foundation models (scGPT, Geneformer, scFoundation, and scBERT), delivering higher clustering accuracy, improved batch integration, and more precise cell type annotation. RegFormer also reconstructs biologically coherent GRNs, accurately models transcriptional responses to genetic perturbations, and enhances drug response prediction across cancer cell lines. By combining regulatory priors with efficient long-sequence Mamba modeling, RegFormer establishes a biologically grounded and scalable framework for single-cell representation learning, enabling deeper mechanistic insight into gene regulation and cellular state transitions.

bioinformatics↗

bioRxiv2025

SCAN-ACT: Adoptive T Cell Therapy Target Discovery Through Single-Cell Transcriptomics

The FDA approval of T cell receptor-engineered T cells (TCR-T) for synovial sarcoma demonstrates the potential for adoptive T cell therapies (ACTs) in solid tumors. However, the paucity of tumor-specific targets without expression in normal tissues remains a major bottleneck, especially in rare cancer subtypes. Here, we present a comprehensive computational pipeline called SCAN-ACT that leverages single cell RNA sequencing and multi-omics data from tumor and normal tissues to nominate and prioritize targets for both chimeric antigen receptor (CAR)- and TCR-T cells. For surface membrane targets, SCAN-ACT proposes target pairs for bispecific Boolean logic-gated CAR T cells. For peptide-MHC targets, SCAN-ACT proposes intracellular peptides bound to a diverse set of human leukocyte antigens. We applied the SCAN-ACT pipeline to soft tissue sarcoma (STS), analyzing 986,749 single cells to identify and prioritize 395 monospecific CAR-T targets, 14,192 bispecific CAR-T targets, and 5,020 peptide-MHC targets for TCR-T cells. Selected targets were validated experimentally by protein expression and for peptide-MHC binding. Proposed targets and target pairs reflected the mesenchymal, neuronal, and hematopoietic ontogeny of STS. This work provides a robust data repository along with a web-based and user-friendly set of analysis tools to accelerate ACT development for solid tumors.

cancer biology↗

bioRxiv2025

ESMAdam: a plug-and-play all-purpose protein ensemble generator

Proteins often adopt multiple ensemble conformations to perform essential functions such as catalysis, transport, and signal transduction. Traditional physics-based methods for generating these conformations, including molecular dynamics and Monte Carlo simulations, are computationally expensive and time-consuming, limiting their practicality for high-throughput applications like screening. Recent advances in machine learning, particularly deep generative models, offer a promising alternative for protein conformation ensemble generation. However, these models are often task-specific or rely on strong assumptions to generalize. Here, we introduce ESMAdam, a versatile and efficient framework for protein conformation ensemble generation. Using the ESMFold protein language model ESMFold and ADAM stochastic optimization in the continuous protein embedding space, ESMAdam addresses a wide range of ensemble generation tasks. In this work, we demonstrate several basic applications of ESMAdam, including conditional ensemble generation and CG-to-all-atom backmapping. In addition, we showcase advanced applications, such as screening alternative binding modes of protein multimers and reconstructing 3D structures from cryo-EM images. Compared to traditional physics-based methods, ESMAdam significantly reduces computational time. Unlike deep-generative-model-based approaches, it requires no retraining and easily adapts to diverse ensemble restraint conditions, making it exceptionally suited for various structure prediction and screening tasks. This plug-and-play framework represents a step toward efficient and flexible protein ensemble generation for applications in structural biology and drug discovery.

biochemistry↗

bioRxiv2025

Super-compensator alleles rescue diverse deleterious substitutions and buffer the effects of mutations

Compensatory mutations can mitigate the fitness costs of deleterious mutations, yet their distribution, structural contexts, and evolutionary roles remain poorly characterized. Here, we systematically analyzed a public deep mutational scanning (DMS) dataset comprising ~400,000 amino acid variants of imidazole glycerol-phosphate dehydratase (IGPD), with substitutions spanning the entire length of the protein. We found that roughly one-tenth of nonfunctional missense variants can regain function through additional substitutions, predominantly at solvent exposed residues with weak local contacts. Notably, we identified a distinct class of super compensatory substitutions that enhance fitness across diverse genetic backgrounds and buffer mutational effects, resulting in genotypes that occupy locally flatter regions of the fitness landscape. Comparative analyses of additional public DMS datasets across diverse proteins and assays revealed that super compensators recur across different natural sequence-function maps, indicating a broadly represented mode of compensatory effects that sustains mutational persistence and contributes to protein evolutionary robustness.

evolutionary biology↗

bioRxiv2025

Epigenetic phase variation in the gut microbiome enhances bacterial adaptation

The human gut microbiome within the gastrointestinal tract continuously adapts to variations in diet, medications, and host physiology. A strategy for bacterial genetic adaptation is epigenetic phase variation (ePV) mediated by bacterial DNA methylation, which can regulate gene expression, enhance clonal heterogeneity, and enable a single bacterial strain to exhibit variable phenotypic states. Genome-wide and site-specific ePVs have been characterized in human pathogens antigenic variation and virulence factor production. However, the role of ePV in facilitating adaptation within the human microbiome remains poorly understood. Here, we comprehensively cataloged genome-wide and site-specific ePV in human infant and adult gut microbiomes. First, using long-read metagenomic sequencing, we detected genome-wide ePV mediated by complex structural variations of DNA methyltransferases, highlighting those associated with antibiotics or fecal microbiota transplantation. Second, we analyzed a collection of public short-read metagenomic sequencing datasets, uncovering a great prevalence of genome-wide ePV in the human gut microbiome. Third, we quantitatively detected site-specific ePVs using single-molecule methylation analysis to identify dynamic variation associated with antibiotic treatment or probiotic engraftment. Finally, we performed an in-depth assessment of an Akkermansia muciniphila isolate from an infant, highlighting that ePVs can regulate gene expression and enhance the bacterial adaptive capacity by employing a bet-hedging strategy to increase tolerance to differing antibiotics. Our findings indicate that epigenetic modifications are a common strategy used by gut bacteria to adapt to the fluctuating environment.

microbiology↗

bioRxiv2025

Ether Rhodamines with Enhanced Hydrophilicity, Fluorogenicity, and Brightness for Super-Resolution Imaging

Rhodamine dyes are widely used fluorophores in super-resolution fluorescence imaging due to their exceptional optical properties and "aggregation-disaggregation" induced fluorogenic activation. However, their excessive lipophilicity often reduces brightness in aqueous environments and causes off-target staining, limiting their effectiveness in high-resolution imaging. To address these challenges, we introduce an ether-decorated N-terminal modification strategy for rhodamine and silicon-rhodamine (Si-rhodamine), replacing conventional N-alkyl groups. The ether chains enhance water solubility, decrease aggregate size, and improve fluorogenicity across a wide concentration range. Their flexible, hydrophilic structure forms a protective shield around the xanthene core, minimizing dye-water interactions and reducing fluorescence quenching. Additionally, the inductive effect of the ether chains decreases the electron-donating strength of the amino groups, suppressing quenching caused by twisted intramolecular charge transfer (TICT). These modifications collectively increase the quantum yields of ER and ESiR in water from 0.35 and 0.19 (for tetraethyl-substituted analogs) to 0.70 and 0.41, respectively. Probes derived from ER and ESiR exhibit outstanding fluorogenicity, enhanced signal-to-noise ratios, and improved resolution in complex aqueous environments, demonstrating superior performance in advanced super-resolution imaging techniques such as structured illumination microscopy (SIM), stimulated emission depletion (STED) microscopy, and single-molecule localization microscopy (SMLM). This work introduces an innovative strategy for fluorophore design, offering significant advancements for super-resolution imaging applications.

biochemistry↗

bioRxiv2024

Kinetic-model-guided engineering of multiple S. cerevisiae strains improves p-coumaric acid production

The use of kinetic models of metabolism in design-build-learn-test cycles is limited despite their potential to guide and accelerate the optimization of cell factories. This is primarily due to difficulties in constructing kinetic models capable of capturing the complexities of the fermentation conditions. Building on recent advances in kinetic-model-based strain design, we present the rational metabolic engineering of an S. cerevisiae strain designed to overproduce p-coumaric acid (p-CA), an aromatic amino acid with valuable nutritional and therapeutic applications. To this end, we built nine kinetic models of an already engineered p-CA-producing strain by integrating different types of omics data and imposing physiological constraints pertinent to the strain. These nine models contained 268 mass balances involved in 303 reactions across four compartments and could reproduce the dynamic characteristics of the strain in batch fermentation simulations. We used constraint-based metabolic control analysis to generate combinatorial designs of 3 enzyme manipulations that could increase p-CA yield on glucose while ensuring that the resulting engineering strains did not deviate far from the reference phenotype. Among 39 unique designs, 10 proved robust across the phenotypic uncertainty of the models and could reliably increase p-CA yield in nonlinear simulations. We implemented these top 10 designs in a batch fermentation setting using a promoter-swapping strategy for down-regulations and plasmids for up-regulations. Eight out of the ten designs produced higher p-CA titers than the reference strain, with 19 - 32% increases at the end of fermentation. All eight designs also maintained at least 90% of the reference strains growth rate, indicating the critical role of the phenotypic constraint. The high experimental success of our in-silico predictions lays the foundation for accelerated design-build-test-learn cycles enabled by large-scale kinetic modeling.

systems biology↗

bioRxiv2024

Stacked Human Arterial Endothelial Cells Generate Atherosclerotic Fatty Streaks and Release Proinflammatory Cytokines

Fatty streaks are the first sign of atherosclerosis. They consist of lipid-containing foam cells, which were believed to be derived from the monocytes in the blood through the leaky endothelium, and from the vascular smooth muscle cells migrating into the intima from the media. Here, we showed that fatty streaks can also be formed by the stacked human arterial endothelial cells (HAECs) cultured in vitro. Via SEM we revealed a novel cell phenotype (coralthelial) that forms a streak/coral-like structure. We observed accumulation of lipids in the coralthelial cell and increased Golgi and coat protein II markers in its nucleus. Additionally, proinflammatory cytokines were upregulated in these cells, likely due to Golgi nuclear translocation and subsequently increased expression of the ribosomal protein RPL23 in the nucleus. We demonstrated, for the first time, that the atherosclerotic fatty streak-like structure can be generated from the stacked HAECs, which also create a proinflammatory microenvironment. Significance StatementOur work presents a novel perspective on atherosclerotic fatty streak formation, a critical early event in atherosclerosis development. We demonstrate, for the first time, that human arterial endothelial cells (HAECs) can transform into a novel phenotype, termed "coralthelial cells". These cells contribute to fatty streak formation, and produce proinflammatory cytokines through the relocation of RPL23 with the Golgi apparatus to the nucleus. This finding provides a new cellular mechanism by which endothelial cells initiate atherosclerosis, independent of traditional monocyte-derived foam cells. By enriching established paradigms, our research not only opens new avenues for therapeutic intervention targeting endothelial cells but also enhances understanding of vascular diseases and provides potential diagnostic and prognostic markers for atherosclerosis.

cell biology↗

bioRxiv2024

Efficacy and Safety of a novel virulent phage against acute pulmonary infection of Acinetobacter baumanniii in mice

Acinetobacter baumannii (A.baumannii) is a notable opportunistic pathogen responsible for severe hospital-acquired infections, with multidrug-resistant strains posing significant treatment challenges. Phage therapy, which employs bacteriophages as natural bacterial antagonists, has gained renewed attention as a promising solution to combat antibiotic-resistant infections. In this study, we isolated and characterized a novel virulent phage, vB_AbaS_qsb1, which specifically lyses A.baumannii. Phylogenetic and genomic analyses indicate that vB_AbaS_qsb1 is the founding member of a previously unreported genus, which we have named as Acinibactriovirus, with Acinibactriovirus lysinus as the type species. vB_AbaS_qsb1 demonstrated robust stability across diverse temperature and pH ranges, a short latent period, and no known virulence or antibiotic resistance genes within its 54,713 bp dsDNA genome. Safety assessments showed that high-dose vB_AbaS_qsb1 induced no adverse effects in mice, with histopathology confirming its safety profile. Therapeutic experiments further indicated that vB_AbaS_qsb1 provided at least 50% protection against A.baumannii-induced pneumonia, significantly reducing bacterial loads and inflammation markers, while maintaining high phage titers in lung tissue.This study introduces vB_AbaS_qsb1 as a promising candidate for phage therapy against A.baumannii, offering both innovative insights and a valuable framework for future isolation, genomic characterization, and efficacy evaluation of phages targeting antibiotic-resistant bacteria. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/617119v3_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@17bf4cdorg.highwire.dtl.DTLVardef@104c49eorg.highwire.dtl.DTLVardef@89e1dorg.highwire.dtl.DTLVardef@1c4b018_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

A near-complete genome assembly of the bearded dragon Pogona vitticeps provides insights into the origin of Pogona sex chromosomes

BackgroundThe agamid dragon lizard Pogona vitticeps is one of the most popular domesticated reptiles to be kept as pets worldwide. The capacity of breeding in captivity also makes it emerging as a model species for a range of scientific research, especially for the studies of sex chromosome origin and sex determination mechanisms. ResultsBy leveraging the CycloneSEQ and DNBSEQ sequencing technologies, we conducted whole genome and long-range sequencing for a captive-bred ZZ male to construct a chromosome-scale reference genome for P. vitticeps. The new reference genome is [~]1.8 Gb in length, with a contig N50 of 202.5 Mb and all contigs anchored onto 16 chromosomes. Genome annotation assisted by long-read RNA sequencing greatly expanded the P. vitticeps lncRNA catalog. With the chromosome-scale genome, we were able to characterize the whole Z sex chromosome for the first time. We found that over 80% of the Z chromosome remains as pseudo-autosomal region (PAR) where recombination is not suppressed. The sexually differentiated region (SDR) is small and occupied mostly by transposons, yet it aggregates genes involved in male development, such as AMH, AMHR2 and BMPR1A. Finally, by tracking the evolutionary origin and developmental expression of the SDR genes, we proposed a model for the origin of P. vitticeps sex chromosomes which considered the Z-linked AMH as the master sex-determining gene. ConclusionsOur study provides novel insights into the sex chromosome origin and sex determination of this model lizard. The near-complete P. vitticeps reference genome will also benefit future study of amniote evolution and may facilitate genome-assisted breeding.

genomics↗

bioRxiv2024

Deep Generative Optimization of mRNA Codon Sequences for Enhanced Protein Production and Therapeutic Efficacy

Messenger RNA (mRNA) therapeutics show immense promise, but their efficacy is limited by suboptimal protein expression. Here, we present RiboDecode, a deep learning framework that generates mRNA codon sequences for enhanced mRNA translation. RiboDecode introduces several advances, including direct learning from large-scale ribosome profiling data and generative exploration of a large sequence space. In silico analysis demonstrates RiboDecode s robust predictive accuracy for unseen genes and cellular environments. In vitro experiments showed substantial improvements in protein expression, significantly outperforming past methods. In addition, RiboDecode enables mRNA design with consideration of cellular context and demonstrates robust performance across different mRNA formats, including m1{Psi}-modified and circular mRNAs, an important feature for mRNA therapeutics. In vivo mouse studies showed that optimized influenza hemagglutinin mRNAs induce ten times stronger neutralizing antibody responses against influenza virus compared to the unoptimized sequence. In an optic nerve crush model, optimized nerve growth factor mRNAs achieve equivalent neuroprotection of retinal ganglion cells at one-fifth the dose of the unoptimized sequence. Collectively, RiboDecode represents a paradigm shift from rule-based to a data-driven, context-aware approach for mRNA therapeutic applications, enabling the development of more potent and dose-efficient treatments.

bioinformatics↗

bioRxiv2024

Mammalian PIEZO channels rectify anionic currents

Under physiological conditions, mammalian PIEZO channels (PIEZO1 and PIEZO2) elicit transient currents mostly carried by monovalent and divalent cations. PIEZO1 is also known to permeate chloride ions, with a Cl- / Na+ permeability ratio of about 0.2. Yet, little is known about how anions permeate PIEZO channels. Here, by separately measuring sodium and chloride currents using non-permanent counter-ions, we show that both PIEZO1 and PIEZO2 rectify chloride currents outwardly, favoring entry of chloride ions at voltages above their reversal potential, whereas little to no rectification was observed for sodium currents. Interestingly, chloride currents elicited by 9K, an anion-selective PIEZO1 mutant harboring multiple positive residues along intracellular pore fenestrations, also rectify but in the inward direction. Molecular dynamics simulation indicate that the inward rectification of chloride currents in 9K correlates with the largely positive electrostatic potential at the intracellular pore entrance, suggesting that rectification can be tuned by pore polarity. These results demonstrate that the pore of mammalian PIEZO channels inherently rectifies chloride currents. Statement of significanceMechanosensitive PIEZO ion channels play many important roles across cells and tissues. Their open pore facilitates the flow of cations down their electrochemical gradients, eliciting sodium-driven membrane depolarization and calcium-dependent signaling under physiological conditions. Yet, these channels also permeate chloride ions. In this study, we show that the two mammalian PIEZO channel homologs preferentially permeate chloride ions into the cells at voltages more positive than the chloride reversal potential. Although PIEZOs permeate cations more effectively than chloride ions, the influx of chloride ions mediated by PIEZOs could participate in certain physiological processes.

biophysics↗

bioRxiv2024

The genetic landscape of antibiotic sensitivity in Staphylococcus aureus

A comprehensive genetic landscape of antibiotic sensitivity in Staphylococcus aureus is lacking. Using ultra-dense CRISPR-interference libraries, we systematically quantified global gene fitness across ten antibiotics and uncovered hundreds of significant antibiotic-gene interactions. Essential genes dominated these interactions, a finding not revealed by transposon-based studies. Processes most vulnerable to transcriptional repression under antibiotic conditions included cell wall synthesis/cell division (CC), DNA replication/DNA recombination (DD), coenzyme A biosynthesis, and riboflavin metabolism. Network and genetic analyses further revealed novel synergistic genetic interactions (GIs) within these processes, including an extensive CC-DD subnetwork. Only a subset of CC-DD synergies was dependent on the cell division inhibitor SosA. Informed by these GIs, we identified multiple drug-drug combinations with potent synergistic activity against multidrug-resistant S. aureus. Our detailed profiling of drug-gene, gene-gene, and drug-drug interactions reveals novel functional relationships among essential genes and defines a vulnerability landscape to guide new drug target discovery and effective combination therapies.

systems biology↗

bioRxiv2024

Simplified and Rapid Workflow Enhances Throughput of De Novo Sequencing of COVID-19 Neutralizing Antibodies

During the current COVID-19 pandemic, precise antibody sequencing is crucial for the rapid development of broad-spectrum or pan-{beta}-coronavirus neutralizing antibodies (NAbs) to prevent new variants of the coronavirus and other highly pathogenic {beta}-coronaviruses. However, mass spectrometry-based de novo sequencing remains challenging due to its high cost, low throughput, and unexpected missing of certain ion information. We developed an innovative approach using solely bottom-up to provide a rapid, robust, and refined solution for the current de novo sequencing challenges. The methodology, referred to as SP-MEGD for Single-Pot and Multi-Enzymatic Gradient Digestion, capitalizes on a five-protease gradient digestion by sampling every two hours for a total of 6 hours in an integrative reactor. The SP-MEGD method could engender numerous missed cleavage events and produce various peptide products of diverse lengths with overlapping stretches of residues, enabling efficient database-free de novo sequencing. Antibody assembly for single or mixed COVID-19-NAbs with publicly available sequences and commercial antibodies with unknown sequences was efficiently deciphered using our previously proposed optimization method, Fusion assembler. Our innovative study represents the first successful simultaneous discrimination and achieving over 99% accurate sequence coverage of a mixture containing three humanized COVID-19-NAbs (S2P6LH, BD5514LH, and BD5840LH). Furthermore, we utilized SP-MEGD and Fusion to sequence commonly used anti-CD8 and anti-CD4, and successfully confirmed their impact on immune cell clearance through in vivo experiments. Overall, our developed workflow demonstrates promise in facilitating the discovery and development of vaccines and antibody therapeutics while providing deeper insights into monoclonal antibodies (mAbs).

bioengineering↗

bioRxiv2024

Comprehensive assembly of monoclonal and mixed antibody sequences

The elucidation of antibody sequence information is crucial for understanding antigen binding and advancing therapeutic and research applications. However, complete de novo assembly of monoclonal antibody sequences remains challenging due to accuracy and robustness limitations. To address this issue, we introduce Fusion, an innovative de novo assembler that integrates overlapping peptides and template information into complete sequences using a beam search strategy. We demonstrate Fusions performance by reconstructing multiple human and murine antibodies with highest accuracy (100% and over 99%, respectively). Biological validation of the recombinantly expressed AFS98 antibody with unknown sequences further supports its effectiveness. Furthermore, current methods are applicable only to traditional monoclonal antibody sequencing assembly, presenting a significant bottleneck in achieving higher throughput. In contrast, Fusion can assemble peptide sequences from mixtures of two or three monoclonal antibodies into complete individual sequences with the same accuracy as traditional sequencing, significantly enhancing throughput. To our knowledge, this is the first study enabling high-throughput sequencing of multiple antibodies using only bottom-up mass spectrometry. The duration, expense, and reagent consumption of mass spectrometry detection are comparable to those required for sequencing a single monoclonal antibody. In summary, Fusions superior performance in handling the complex antibody sequencing represents a significant advancement in antibody research.

bioinformatics↗

bioRxiv2024

Optics-free Spatial Genomics for Mapping Mouse Brain Aging

Spatial transcriptomics has revolutionized our understanding of cellular network dynamics in aging and disease by enabling the mapping of molecular and cellular organization across various anatomical locations. Despite these advances, current methods face significant challenges in throughput and cost, limiting their utility for comprehensive studies. To address these limitations, we introduce IRISeq (Imaging Reconstruction using Indexed Sequencing), a optics-free spatial transcriptomics platform that eliminates the need for predefined capture arrays or extensive imaging, allowing for the rapid and cost-effective processing of multiple tissue sections simultaneously. Its capacity to reconstruct images based solely on sequencing local DNA interactions allows for profiling of tissues without size constraints and across varied resolutions. Applying IRISeq, we examined gene expression and cellular dynamics in thirty brain regions of both adult and aged mice, uncovering region-specific changes in gene expression associated with aging. Further cell type-centric analysis further identified age-related cell subtypes and intricate changes in cell interactions that are distinct to certain spatial niches, emphasizing the unique aspects of aging in different brain regions. The affordability and simplicity of IRISeq position it as a versatile tool for mapping region-specific gene expression and cellular interactions across various biological systems. One Sentence Summary: IRISeq, an innovative optics-free spatial transcriptomics method, uncovers aging-related changes in spatial gene expression and focal cell interactions in brain aging.

genomics↗

bioRxiv2024

PATJ regulates cell stress responses and vascular remodeling post-stroke

PALS1-associated tight junction (PATJ) protein is linked to metabolic disease and stroke in human genetic studies. Despite the recognized role of PATJ in cell polarization, its specific functions in metabolic disease and ischemic stroke recovery remain largely unexplored. Using a mouse model of stroke, we found post-ischemic stroke duration-dependent increase of PATJ abundance in endothelial cells. PATJ knock-out (KO) HEK293 cells generated by CRISPR-Cas9 suggest roles for PATJ in cell proliferation, migration, mitochondrial stress response, and interactions with the Yes-associated protein (YAP)-1 signaling pathway. Notably, PATJ deletion altered YAP1 nuclear translocation. PATJ KO cells demonstrated extensive transcriptional reprograming based on RNA sequencing analysis. Crucially, we identified dysregulation in genes central to vascular development, stress response, and metabolism, including RUNX1, HEY1, NUPR1, and HK2. These insights offer a new understanding of PATJs complex regulatory functions within cellular and vascular physiology and help lay the groundwork for therapeutic strategies targeting endothelial PATJ-mediated pathways for stroke rehabilitation and neurovascular repair.

neuroscience↗