Biology subjects

Luo, S.

Publications and source records attributed to Luo, S..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

CRISPR-based shuttle cloning of 1,397 human genes into UAS vectors

The construction of genome-wide DNA libraries from publicly available resources is essential for leveraging functional genomics to investigate complex biological systems. However, all existing high-throughput cloning methods for transferring DNA fragments between vectors require PCR amplification of the DNA fragments, rendering the construction of genome-wide DNA libraries labor-intensive and time-consuming. By introducing a concept of CRISPRshuttle cassette, we herein present a method named CRISPR-based shuttle cloning (CRISPRshuttle cloning). This method enables the high-throughput transfer of numerous DNA fragments from original plasmids with identical backbones to a different vector background without the need for PCR amplification of the DNA fragments. The procedure comprises two-step test tube reactions followed by bacterial transformation. Using CRISPRshuttle we successfully generated a library of GAL4/UAS-based UAS-ORF plasmids covering 1,397 human genes conserved in Drosophila. This library may serve as a valuable resource for gain-of-function screening in cultured cells and for the creation of a transgenic UAS-ORF library in Drosophila.

molecular biology↗

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↗

bioRxiv2025

Ultraviolet B Induces Cutaneous Lupus Erythematosus by Triggering a Ribotoxic-Stress-Response-Dependent MIF-p38 Feedback Loop in Keratinocytes

Ultraviolet B (UVB) is one of the most common triggers of cutaneous lupus erythematosus (CLE), but the mechanism is still unclear. Here, we discovered that the expression of macrophage migration inhibitory factor (MIF), a multipotent cytokine, was significantly increased in keratinocytes of lupus patients in scRNA-seq data and clinical samples. We further discovered that UVB exposure induced MIF releasing from lupus keratinocytes and contributed to the tissue remodeling and inflammation by regulating the expression of matrix metalloproteinases (MMPs) and pro-inflammatory cytokines in keratinocytes and fibroblasts. Mechanistically, UVB exposure triggered a ribotoxic stress response (RSR) in lupus keratinocytes, which was featured by the increased level of phospho-ZAK. The RSR induced MIF releasing through the activation of p38 and GSDMD cleavage. The released MIF could further promote the activation of p38 through its receptor CD74, forming a positive feedback loop triggered by UVB exposure in lupus keratinocytes. Intradermal injection of a Mif-shRNA AAV significantly improved the skin lesions in lupus mice. To further investigate the potentials of MIF as a therapeutic target, we developed a microneedle patch capable of intradermal administration of a MIF inhibitor, which effectively protected lupus mice from skin lesions induced by UVB exposure. In conclusion, our findings suggest a novel mechanism by which UVB exposure contributes to the development of CLE by triggering a positive feedback loop of MIF-p38 in lupus keratinocytes. Our results also demonstrate the translational potentials of microneedle patch targeting MIF in the treatment of CLE.

immunology↗

bioRxiv2025

Iterative acylation on mature lasso peptides by widespread acetyltransferases for lipolasso production

The biosynthesis of ribosomally synthesized and post-translationally modified peptides (RiPPs) leverages iterative catalysis to enhance structural and biological diversity. Traditionally, iterative enzymes install multiple post-translational modifications (PTMs) on linear peptides, rather than mature RiPPs with intricate three-dimensional structures, which would require complex changes in substrate binding poses. Here, we present a prolific class of GCN5-related N-acetyltransferases (GNATs) that iteratively and consecutively acylate two Lys residues within the loop and ring motifs of lasso peptides, diverging from the typical iterative modification of linear peptides--an unprecedented function for PTM enzymes. Utilizing high-resolution cryo-electron microscopy and enzymatic reconstitution, we mapped the lasso peptide binding pocket of IatT and pinpointed key residues involved in demarcating the two distinct acetylation steps. Structure-based engineering of IatTs acetyl group recognition site expanded the cavity to accommodate longer-chain acyl groups, leading to the creation of lipolasso peptides, a novel class of ribosomal lipopeptide. This engineering strategy can be applied to any RiPP BGC encoding GNAT, facilitating the efficient diversification of rare ribosomal lipopeptides. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC="FIGDIR/small/630886v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1d88af9org.highwire.dtl.DTLVardef@18c1298org.highwire.dtl.DTLVardef@118b9f3org.highwire.dtl.DTLVardef@580a50_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2024

Same-Slide Spatial Multi-Omics Integration Reveals Tumor Virus-Linked Spatial Reorganization of the Tumor Microenvironment

The advent of spatial transcriptomics and spatial proteomics have enabled profound insights into tissue organization to provide systems-level understanding of diseases. Both technologies currently remain largely independent, and emerging same slide spatial multi-omics approaches are generally limited in plex, spatial resolution, and analytical approaches. We introduce IN-situ DEtailed Phenotyping To High-resolution transcriptomics (IN-DEPTH), a streamlined and resource-effective approach compatible with various spatial platforms. This iterative approach first entails single-cell spatial proteomics and rapid analysis to guide subsequent spatial transcriptomics capture on the same slide without loss in RNA signal. To enable multi-modal insights not possible with current approaches, we introduce k-bandlimited Spectral Graph Cross-Correlation (SGCC) for integrative spatial multi-omics analysis. Application of IN-DEPTH and SGCC on lymphoid tissues demonstrated precise single-cell phenotyping and cell-type specific transcriptome capture, and accurately resolved the local and global transcriptome changes associated with the cellular organization of germinal centers. We then implemented IN-DEPTH and SGCC to dissect the tumor microenvironment (TME) of Epstein-Barr Virus (EBV)-positive and EBV-negative diffuse large B-cell lymphoma (DLBCL). Our results identified a key tumor-macrophage-CD4 T-cell immunomodulatory axis differently regulated between EBV-positive and EBV-negative DLBCL, and its central role in coordinating immune dysfunction and suppression. IN-DEPTH enables scalable, resource-efficient, and comprehensive spatial multi-omics dissection of tissues to advance clinically relevant discoveries.

systems biology↗

bioRxiv2024

On metrics for subpopulation detection in single-cell and spatial omics data

Benchmarks are crucial to understanding the strengths and weaknesses of the growing number of tools for single-cell and spatial omics analysis. A key task is to distinguish subpopulations within complex tissues, where evaluation typically relies on external clustering validation metrics. Different metrics often lead to inconsistencies between rankings, highlighting the importance of understanding the behavior and biological implications of each metric. In this work, we provide a framework for systematically understanding and selecting validation metrics for single-cell data analysis, addressing tasks such as creating cell embeddings, constructing graphs, clustering, and spatial domain detection. Our discussion centers on the desirable properties of metrics, focusing on biological relevance and potential biases. Using this framework, we not only analyze existing metrics, but also develop novel ones. Delving into domain detection in spatial omics data, we develop new external metrics tailored to spatially-aware measurements. Additionally, a Bioconductor R package, poem, implements all the metrics discussed. While we focus on single-cell omics, much of the discussion is of broader relevance to other types of high-dimensional data.

bioinformatics↗

bioRxiv2024

PROPERMAB: an integrative framework for in silico prediction of antibody developability using machine learning

Selection of lead therapeutic molecules is often driven predominantly by pharmacological efficacy and safety. Candidate developability, such as biophysical properties that affect the formulation of the molecule into a product, is usually evaluated only toward the end of the drug development pipeline. The ability to evaluate developability properties early in the process of antibody therapeutic development could accelerate the timeline from discovery to clinic and save considerable resources. In silico predictive approaches, such as machine learning models, which map molecules to predictions of developability properties could offer a cost-effective and high-throughput alternative to experiments for antibody developability assessment. We developed a computational framework, PROPERMAB, for large-scale and efficient in silico prediction of developability properties for monoclonal antibodies, using custom molecular features and machine learning modeling. We demonstrate the power of PROPERMAB by using it to develop models to predict antibody hydrophobic interaction chromatography retention time and high-concentration viscosity. We further show that structure-derived features can be rapidly and accurately predicted directly from sequences by pre-training simple models for molecular features, thus providing the ability to scale these approaches to repertoire-scale sequence datasets.

bioinformatics↗

bioRxiv2024

BrainUnit: Integrating Physical Units into High-Performance AI-Driven Scientific Computing

Artificial intelligence (AI) is revolutionizing scientific research across various disciplines. The foundation of scientific research lies in rigorous scientific computing based on standardized physical units. However, current mainstream high-performance numerical computing libraries for AI generally lack native support for physical units, significantly impeding the integration of AI methodologies into scientific research. To fill this gap, we introduce BrainUnit, a unit system designed to seamlessly integrate physical units into AI libraries, with a focus on compatibility with JAX. BrainUnit offers a comprehensive library of over 2000 physical units and more than 300 unit-aware mathematical functions. It is fully compatible with JAX transformations, allowing for automatic differentiation, just-in-time compilation, vectorization, and parallelization while maintaining unit consistency. We demonstrate BrainUnits efficacy through several use cases in brain dynamics modeling, including detailed biophysical neuron simulations, multiscale brain network modeling, neuronal activity fitting, and cognitive task training. Our results show that BrainUnit enhances the accuracy, reliability, and interpretability of scientific computations across scales, from ion channels to whole-brain networks, without impacting performance. By bridging the gap between abstract computational frameworks and physical units, BrainUnit represents a crucial step towards more robust and physically grounded AI-driven scientific computing.

neuroscience↗

bioRxiv2024

Unique Signatures of Highly Constrained Genes Across Publicly Available Genomic Databases

Publicly available genomic databases and genetic constraint scores are crucial in understanding human population variation and the identification of variants that are likely to have a deleterious impact causing human disease. We utilized the one of largest publicly available databases, gnomAD, to determine genes that are highly constrained for only LoF, only missense, and both LoF/missense variants, identified their unique signatures, and explored their causal relationship with human conditions. Those genes were evaluated for unique patterns including their chromosomal location, tissue level expression, gene ontology analysis, and gene family categorization using multiple publicly available databases. Those highly constrained genes associated with human disease, we identified unique patterns of inheritance, protein size, and enrichment in distinct molecular pathways. In addition, we identified a cohort of highly constrained genes that are currently not known to cause human disease, that we suggest will be candidates to pursue as novel disease-associated genes. In summary, these insights not only elucidate biological pathways of highly constrained genes that expand our understanding of critical cellular proteins but also advance research in rare diseases.

genetics↗

bioRxiv2024

Scalable spatial single-cell transcriptomics and translatomics in 3D thick tissue blocks

Characterizing the transcriptional and translational gene expression patterns at the single-cell level within their three-dimensional (3D) tissue context is essential for revealing how genes shape tissue structure and function in health and disease. However, most existing spatial profiling techniques are limited to 5-20 {micro}m thin tissue sections. Here, we developed Deep-STARmap and Deep-RIBOmap, which enable 3D in situ quantification of thousands of gene transcripts and their corresponding translation activities, respectively, within 200-{micro}m thick tissue blocks. This is achieved through scalable probe synthesis, hydrogel embedding with efficient probe anchoring, and robust cDNA crosslinking. We first utilized Deep-STARmap in combination with multicolor fluorescent protein imaging for simultaneous molecular cell typing and 3D neuron morphology tracing in the mouse brain. We also demonstrate that 3D spatial profiling facilitates comprehensive and quantitative analysis of tumor-immune interactions in human skin cancer.

genomics↗

bioRxiv2024

Loss of H3K9 trimethylation leads to premature aging

Aging is the major risk factor for most human diseases and represents a major socio-economical challenge for modern societies. Despite its importance, the process of aging remains poorly understood. Epigenetic dysregulation has been proposed as a key driver of the aging process. Modifications in transcriptional networks and chromatin structure might be central to age-related functional decline. A prevalent feature described during aging is the overall reduction in heterochromatin, specifically marked by the loss of repressive histone modification, Histone 3 lysine 9 trimethylation (H3K9me3). However, the role of H3K9me3 in aging, especially in mammals, remains unclear. Here we show using a novel mouse strain, (TKOc), carrying a triple knockout of three methyltransferases responsible for H3K9me3 deposition, that the inducible loss of H3K9me3 in adulthood results in premature aging. TKOc mice exhibit reduced lifespan, lower body weight, increased frailty index, multi-organ degeneration, transcriptional changes with significant upregulation of transposable elements, and accelerated epigenetic age. Our data strongly supports the concept that the loss of epigenetic information directly drives the aging process. These findings reveal the importance of epigenetic regulation in aging and suggest that interventions targeting epigenetic modifications could potentially slow down or reverse age-related decline. Understanding the molecular mechanisms underlying the process of aging will be crucial for developing novel therapeutic strategies that can delay the onset of age-associated diseases and preserve human health at old age specially in rapidly aging societies.

physiology↗

bioRxiv2024

Deep learning linking mechanistic models to single-cell transcriptomics data reveals transcriptional bursting in response to DNA damage

Cells must adopt flexible regulatory strategies to make decisions regarding their fate, including differentiation, apoptosis, or survival in the face of various external stimuli. One key cellular strategy that enables these functions is stochastic gene expression programs. However, understanding how transcriptional bursting, and consequently, cell fate, responds to DNA damage on a genome-wide scale poses a challenge. In this study, we propose an interpretable and scalable inference framework, DeepTX, that leverages deep learning methods to connect mechanistic models and scRNA-seq data, thereby revealing genome-wide transcriptional burst kinetics. This framework enables rapid and accurate solutions to transcription models and the inference of transcriptional burst kinetics from scRNA-seq data. Applying this framework to several scRNA-seq datasets of DNA-damaging drug treatments, we observed that fluctuations in transcriptional bursting induced by different drugs was associated with distinct fate decisions: IdU treatment was associated with differentiation in mouse embryonic stem cells by increasing the burst size of gene expression, while low- and high-dose 5FU treatments in human colon cancer cells were associated with changes in burst frequency that corresponded to apoptosis- and survival-related fate, respectively. Together, these results show that DeepTX enables genome-wide inference of transcriptional bursting from single-cell transcriptomics data and can generate hypotheses about how bursting dynamics relate to cell fate decisions.

systems biology↗

bioRxiv2024

Non-additivity of the functional properties of individual P450 species and its manifestation in the effects of alcohol consumption on the metabolism of ketamine and amitriptyline

To explore functional interconnections between multiple P450 enzymes and their manifestation in alcohol-induced changes in drug metabolism, we implemented a high-throughput study of correlations between the composition of the P450 pool and the substrate saturation profiles (SSP) of amitriptyline and ketamine in a series of 23 individual human liver microsomes preparations from donors with a known history of alcohol consumption. The SSPs were approximated with linear combinations of three Michaelis-Menten equations with globally optimized KM (substrate affinity) values. This analysis revealed a strong correlation between the rate of ketamine metabolism and alcohol exposure. For both substrates, alcohol consumption caused a significant increase in the role of the low-affinity enzymes. The amplitudes of the kinetic components and the total rate were further analyzed for correlations with the abundance of 11 major P450 enzymes assessed by global proteomics. The maximal rate of metabolism of both substrates correlated with the abundance of CYP3A4, their predicted principal metabolizer. However, except for CYP2D6 and CYP2E1, responsible for the low-affinity metabolism of ketamine and amitriptyline, respectively, none of the other potent metabolizers of the drugs revealed a positive correlation. Instead, in the case of ketamine, we observed negative correlations with the abundances of CYP1A2, CYP2C9, and CYP3A5. For amitriptyline, the data suggest inhibitory effects of CYP1A2 and CYP2A6. Our results demonstrate the importance of functional interactions between multiple P450 species and their decisive role in the effects of alcohol exposure on drug metabolism.

biochemistry↗

bioRxiv2024

Mechanism, and treatment of anti-CV2/CRMP5 autoimmune pain

Paraneoplastic neurological syndromes arise from autoimmune reactions against nervous system antigens due to a maladaptive immune response to a peripheral cancer. Patients with small cell lung carcinoma or malignant thymoma can develop an autoimmune response against the CV2/collapsin response mediator protein 5 (CRMP5) antigen. For reasons that are not understood, approximately 80% of patients experience painful neuropathies. Here, we investigated the mechanisms underlying anti-CV2/CRMP5 autoantibodies (CV2/CRMP5-Abs)-related pain. We found that patient-derived CV2/CRMP5-Abs can bind to their target in rodent dorsal root ganglia (DRG) and superficial laminae of the spinal cord. CV2/CRMP5-Abs induced DRG neuron hyperexcitability and mechanical hypersensitivity in rats that were abolished by preventing binding to their cognate autoantigen CRMP5. The effect of CV2/CRMP5-Abs on sensory neuron hyperexcitability and mechanical hypersensitivity observed in patients was recapitulated in rats using genetic immunization providing an approach to rapidly identify possible therapeutic choices for treating autoantibody-induced pain including the repurposing of a monoclonal anti-CD20 antibody that selectively deplete B-lymphocytes. These data reveal a previously unknown neuronal mechanism of neuropathic pain in patients with paraneoplastic neurological syndromes resulting directly from CV2/CRMP5-Abs-induced nociceptor excitability. CV2/CRMP5-Abs directly sensitize pain responses by increasing sensory neuron excitability and strategies aiming at either blocking or reducing CV2/CRMP5-Abs can treat pain as a comorbidity in patients with paraneoplastic neurological syndromes.

neuroscience↗

bioRxiv2024

Protocatechuic acid induces endogenous oxidative stress in CR-hvKP by regulating the EMP-PPP pathway

BackgroundKlebsiella pneumoniae is an important opportunistic pathogen and zoonotic pathogen. The widespread use of antibiotics has led to the emergence of a large number of multidrug-resistant Klebsiella pneumoniae in clinical animal husbandry, posing a serious threat to global health security. Protocatechuic acid (PCA) is a phenolic acid substance naturally present in many vegetables and fruits. It is a safe and highly developed new type of antibacterial synergist. PurposeThis study explored the antibacterial and synergistic mechanisms of PCA against Carbapenem-resistant hypervirulent Klebsiella pneumoniae. Study designMetabolomic analysis using PCA to investigate the metabolic effects of CR-hvKP and further explore the antibacterial mechanisms resulting from this metabolic regulation. MethodsThe MIC of PCA was measured by microdilution, and its bactericidal effect was observed by DAPI staining. Resistance and hemolysis tests were performed to ensure safety. The synergy of PCA and meropenem was tested by checkerboard assay. The biofilm inhibition was assessed by crystal violet and EPS assays. The membrane morphology, permeability, and potential were examined by SEM, PI, NPN, and DiSC3(5). The metabolic changes were evaluated by AlamarBlue, metabolomics, enzyme activity, ELISA, molecular docking, and qRT-PCR. The oxidative stress and metabolic disorders were verified by NADP(H), ROS, MDA, and ATP assays. ResultsThe results showed that PCA can synergize with antibiotics and inhibit the biofilm and membrane functions of CR-hvKP at low concentrations. Metabolomics revealed that PCA affects the EMP and PPP pathways of CR-hvKP, causing oxidative stress. This involves the binding of PGAM and the downregulation of BPGM, leading to the accumulation of glycerate-3P. This results in the inhibition of G6PDH and the imbalance of NADPH/NADP+, disrupting the energy metabolism and increasing the oxidative stress, which impair the biofilm and membrane functions and enhance the antibiotic efficacy. ConclusionThe results demonstrate that PCA regulates the EMP-linked PPP pathway of CR-hvKP, inhibits biofilm and membrane functions, and synergizes with antibiotics to kill bacteria, providing new insights and candidates for natural antibacterial enhancers. Author SummaryKlebsiella pneumoniae is a common pathogenic bacterium that can infect both humans and animals, causing serious diseases such as pneumonia, meningitis, and sepsis. Due to the overuse of antibiotics, this bacterium has developed resistance to many drugs, posing a significant threat to global health security. Through our research, we have discovered a natural substance called protocatechuic acid (PCA) that can enhance the effectiveness of antibiotics against this bacterium. PCA is found in many vegetables and fruits and is a safe and non-toxic antibacterial adjuvant. Our analysis of the metabolomics of PCA on Klebsiella pneumoniae has revealed its antibacterial and synergistic mechanisms. The study found that PCA can affect the bacteriums sugar metabolism pathway, leading to the generation of endogenous oxidative stress. This disrupts their energy metabolism, damages their cell membranes and biofilms, making them more susceptible to being killed by antibiotics. Through this mechanism, PCA can synergize with common antibiotics such as meropenem, enhancing their bactericidal ability. Our research has demonstrated that PCA is an effective antibacterial adjuvant, providing new candidates and insights for the development of natural antibacterial agents. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/583678v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@2e2963org.highwire.dtl.DTLVardef@9f3c51org.highwire.dtl.DTLVardef@3125a8org.highwire.dtl.DTLVardef@9f39b7_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

Influence of insulin sensitivity on food cue evoked functional brain connectivity in children

ObjectiveInsulin resistance during childhood is a risk factor for developing type 2 diabetes and other health problems later in life. Studies in adults have shown that insulin resistance affects regional and network activity in the brain which are vital for behavior, e.g. ingestion and metabolic control. To date, no study has investigated whether brain responses to food cues in children are associated with peripheral insulin sensitivity. MethodsWe included 53 children (36 girls) between the age of 7-11 years, who underwent an oral Glucose Tolerance Test (oGTT) to estimate peripheral insulin sensitivity (ISI). Brain responses were measured using functional magnetic resonance imaging (fMRI) before and after glucose ingestion. We compared food-cue task-based activity and functional connectivity (FC) between children with low and high ISI, adjusted for age and BMIz. ResultsIndependent of prandial state (i.e., glucose ingestion), children with lower ISI showed higher FC between the anterior insula and caudate and lower FC between the posterior insula and mid temporal cortex than children with higher ISI. Sex differences were found based on prandial state and peripheral insulin sensitivity in the insular FC. No differences were found on whole-brain food-cue reactivity. ConclusionsChildren with low peripheral insulin sensitivity showed differences in food cue evoked response particularly in insula functional connectivity. These differences might influence eating behavior and future risk of developing diabetes.

neuroscience↗

bioRxiv2024

The Origin and Evolution of Orphan Genes: A Case Study in Tea Plant Family

Orphan genes and transcription factor genes (TFs) are pervasive across genomes, play pivotal roles as regulators in a myriad of biological processes. Despite their ubiquity, the evolutionary trajectories and functional divergence of these genes remain largely unexplored. Theaceae family, encompassing the economically and culturally significant tea plant, presents a unique opportunity to study these dynamics. Here, we decoded a nearly complete, chromosome-scale reference genome of Stewartia gemmata spanning 2.95 Gb. This study is enhanced by integrating the genome of S. gemmata, an early-diverging species within Theaceae, crucial for phylogenomic analyses and understanding the functional dynamics of orphan genes in this family. Our analysis confirmed the absence of a recent specific whole-genome duplication (WGD) event, with tandem duplications emerging as the predominant mechanism for gene duplication at ancestral nodes within Theaceae. By conducting an extensive comparative genomics analysis across 13 Theaceae and comparing these with a wide array of eukaryotic and prokaryotic proteins, we identified 37,618 orphan genes and 25,884 TFs in Theaceae. Interestingly, some orphan genes appear to have ancient origins in tea plant ancestors, suggesting relatively early origins with frequent gains and losses, conversely, many others seem more specific and recent. Notably, the orphan genes are characterized by shorter lengths, fewer exons and functional domains than TFs, implying relatively simpler functional roles. These orphan genes demonstrate diverse cellular localization and functions as predicted by GO/KEGG analysis, and are implicated in environmental response and flavor formation in tea plants. This study not only sheds light on the distinct evolutionary histories and functional divergences between orphan genes and TFs in Theaceae, but also contributes to our understanding of the genetic complexity and adaptability of this economically and culturally valuable plant family. Short summary: The nearly complete genome of an early-diverging species Stewartia gemmata and phylogenomic studies provide insights into new gene evolution in Theaceae.

bioinformatics↗

bioRxiv2024

LncRNA-CIR6 Mediates Repair of Infarcted Hearts by Inducing MSCs Differentiation into Cardiogenic Cells through CDK1

PurposeThis study aims to investigate the induction effect of LncRNA-CIR6 on MSCs differentiation into Cardiogenic Cells in vitro and in vivo. MethodsIn addition to pretreatment with the Ro-3306 (CDK1 inhibitor), LncRNA-CIR6 was transfected into BMSCs and hUCMSCs using jetPRIME. LncRNA-CIR6 was transfected into C57BL/6 mice heart by 100 L of AAV9-cTnT-LncRNA-CIR6-ZsGreen i.v. After 3 weeks of transfection followed by AMI surgery, hUCMSCs (5x105/100 L) were injected by i.v 1 week later. Cardiac function was evaluated using VEVO 2100 and electric mapping 9 days after cell injection. IF, Evans blue-TTC, Masson staining, FACS, and WB were used to determine relevant indicators. ResultsLncRNA-CIR6 induced a significant percentage of differentiation in BMSCs (83.00{+/-}0.58)% and hUCMSCs (95.43{+/-}2.13)% into cardiogenic cells, as determined by the expression of cTnT. Compared with MI group, cardiac contraction and conduction function in MI heart treated by LncRNA-CIR6 or combined with MSCs injection groups were significantly increased as well as the area of MI and fibrosis were significantly lower. The transcriptional expression region of LncRNA-CIR6 was in Chr17 from 80209290 to 80209536. The functional region of LncRNA-CIR6 was located at nucleotides 0-50/190-255 in the sequence. CDK1 is a protein found to be related to the proliferation and differentiation of cardiomyocytes is which located in the functional region of LncRNA-CIR6 secondary structure (from 0 to 17). Ro-3306 impeded the differentiation of MSCs into cardiogenic cells, while MSCs transfected with LncRNA-CIR6 showed high expression of CDK1. LncRNA-CIR6 mediates repair of infarcted hearts by inducing MSCs differentiation into cardiogenic cells through CDK1. ConclusionsLncRNA-CIR6 mediates repair of infarcted hearts by inducing MSCs differentiation into cardiogenic cells through CDK1.

molecular biology↗