Biology subjects

Li, E.

Publications and source records attributed to Li, E..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Optimized R2 Retroelement Complexes Enable Precise and Efficient DNA Insertion into Plant Genomes

Precise, targeted insertion of multi-kilobase DNA sequences into plant genomes is critical for studying gene function, ensuring robust transgene expression, and stacking traits in crops, but remains challenging. Existing targeted insertion methods in plants relying on programmable nucleases are inefficient and can generate unwanted mutations. Newer technologies based on prime editors, transposases, and site-specific recombinases extend capabilities but remain constrained with low efficiencies, off-target integration, silencing, or limited DNA payload size. R2 non-long terminal repeat (non-LTR) retrotransposons integrate via target-primed reverse transcription (TPRT) specifically targeting the 25S ribosomal DNA multicopy site and enabling double-strand-break-free installation of gene-sized DNA sequences. We adapted the avian Taeniopygia guttata R2 protein (R2Tg) for targeted DNA insertion into plant genomes through engineering of R2Tg expression cassettes and RNA payloads carrying intron-disrupted mCherry and RUBY retrotransposition reporters with length-optimized rDNA homology arms. These efforts, together with optimized construct delivery formats and incubation temperatures, define R2 editor design rules enabling efficient DNA integration and functional protein expression from the 25S rDNA locus. In Nicotiana benthamiana leaves, Arabidopsis thaliana protoplasts, and Solanum lycopersicum seedlings, the optimized R2Tg editor system achieved targeted insertion with efficiencies up to 24% payloads ranging in size from 2kb to 5kb. This work establishes a compact R2Tg ribonucleoprotein platform for targeted DNA insertion into plant genomes, targeting a multicopy genomic safe harbor site to enable efficient multi-kilobase gene addition

bioengineering↗

bioRxiv2025

A single-cell transcriptomic atlas of the pigtail macaque placenta in late gestation

The placenta is a complex organ with multiple immune and non-immune cell types that promote fetal tolerance and facilitate the transfer of nutrients and oxygen. The nonhuman primate (NHP) is a key experimental model for studying human pregnancy complications, in part due to similarities in placental structure, which makes it essential to understand how single-cell populations compare across the human and NHP maternal-fetal interface. We constructed a single-cell RNA-Seq (scRNA-Seq) atlas of the placenta from the pigtail macaque (Macaca nemestrina) in the third trimester, comprising three different tissues at the maternal-fetal interface: the chorionic villi (placental disc), chorioamniotic membranes, and the maternal decidua. Each tissue was separately dissociated into single cells and processed through the 10X Genomics and Seurat pipeline, followed by aggregation, unsupervised clustering, and cluster annotation. Next, we determined the maternal-fetal origins of cell populations and analyzed single-cell RNA trajectory, Gene Ontology enrichment, and cell-cell communication. Single-cell populations in the pigtail macaque were strikingly similar in their identity and frequency to those found in the human placenta, including cells from trophoblast, stromal cell, immune, and macrophage lineages. An advantage of our approach was the deep sequencing of three tissues at the maternal-fetal interface, which yielded a rich diversity of common and rare single-cell populations. The third-trimester pigtail macaque single-cell atlas enables the identification of cellular subclusters analogous to those in humans and provides a powerful resource for understanding experimental perturbations on the NHP placenta.

genomics↗

bioRxiv2025

Competing Subclones and Fitness Diversity Shape Tumor Evolution Across Cancer Types

Intratumor heterogeneity arises from ongoing somatic evolution complicating cancer diagnosis, prognosis, and treatment. Here we present TEATIME (estimating evolutionary events through single-timepoint sequencing), a novel computational framework that models tumors as mixtures of two competing cell populations: an ancestral clone with baseline fitness and a derived subclone with elevated fitness. Using cross-sectional bulk sequencing data, TEATIME estimates mutation rates, timing of subclone emergence, relative fitness, and number of generations of growth. To quantify intratumor fitness asymmetries, we introduce a novel metric--fitness diversity--which captures the imbalance between competing cell populations and serves as a measure of functional intratumor heterogeneity. Applying TEATIME to 33 tumor types from The Cancer Genome Atlas, we revealed divergent as well as convergent evolutionary patterns. Notably, we found that immune-hot microenvironments constraint subclonal expansion and limit fitness diversity. Moreover, we detected temporal dependencies in mutation acquisition, where early driver mutations in ancestral clones epistatically shape the fitness landscape, predisposing specific subclones to selective advantages. These findings underscore the importance of intratumor competition and tumor-microenvironment interactions in shaping evolutionary trajectories, driving intratumor heterogeneity. Lastly, we demonstrate that TEATIME-derived evolutionary parameters and fitness diversity offer novel prognostic insights across multiple cancer types.

bioinformatics↗

bioRxiv2025

Intravenous BCG immunization drives naive CD4+ T cell to Th1 differentiation via CD4+ T cell epigenetic reprogramming

Intravenous (IV) administration of live Bacille Calmette-Guerin (BCG) boosts potent immunity through coordinated interactions of innate immune response and adaptive immune response for BCG antiviral activity. The underlying mechanisms by which BCG initiates CD4+ T response remain incompletely understood. Here, we show that IV administration of BCG drives naive CD4+ T cell differentiation to Th1 cell through epigenetic reprogramming. Single-cell transcriptomic and epigenomic analyses revealed that IV BCG immunization induced metabolic reprogramming in monocytes and increased the proportion of T cells. The immunization induced chromatin openness for transcription factors regulating naive CD4+ T cells differentiation into Th1 cells. Importantly, we observed increases in Stat1, Irf1 and interferon-stimulated genes such as Igtp in Th1 cells, leading to upregulation of interferon related gene expression for antiviral response by BCG immunization. Activated transcription factors like Irf1 in CD4+ T cells promotes Il12rb1 expression to facilitate IL-12 signaling and drive naive CD4+ T cells differentiation into Th1 cells. We showed that BCG immunization reduced respiratory syncytial virus (RSV) infection. Thus, transcription regulation through epigenetic reprogramming plays a critical role in BCG-induced CD4+ T cell differentiation and to the broad antiviral activity. SignificanceBacille Calmette-Guerin (BCG) vaccination confers nonspecific protection against heterologous pathogens. Recent work demonstrated that coordinated interactions of innate immune and persistent CD4+ T cell response plays a critical role in BCG induced antiviral activity. In our study, we investigated BCG immunization on epigenetic reprogramming of CD4+ T cells and found that BCG immunization elicited antiviral activity by provoking T cell proliferation. We observed chromatin openness favoring naive T cell differentiation to Th1 response. Importantly, we observed STAT1 and interferon regulatory factor-1 (Irf1) activation. These findings provide mechanistic insights into BCG-induced Th1 response through epigenetic reprogramming and highlight the potential of BCG in offering a long-term protection against emerging and reemerging pathogens. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=181 SRC="FIGDIR/small/655674v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@1c3cb94org.highwire.dtl.DTLVardef@16a8e8forg.highwire.dtl.DTLVardef@b58b88org.highwire.dtl.DTLVardef@dbc994_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIIntravenous BCG immunization drives naive CD4+ T cell differentiation to Th1 response; C_LIO_LIBCG alters chromatin accessibility for transcriptional factor expression favoring Th1 response through a Irf1-Il12rb1-IL12 feedback loop; C_LIO_LIThe immunization elicits antiviral activity against RSV infection; C_LI

immunology↗

bioRxiv2025

Inferring non-coding RNA regulatory network from transcriptomic data and curated databases

Non-coding RNAs (ncRNAs) have played an indispensable role in regulating gene expression and cellular processes. However, the complex regulatory circuits between ncRNAs and coding genes remain understudied. Major challenges for inferring ncRNA regulatory network (NRN) on a transcriptome-wide scale include high dimensionality of both ncRNA and coding gene expression data, their context-dependent interaction, and lack of validation. We hereby propose a comprehensive analytical framework, namely Construction and Analysis of non-coding RNA regulatory NETwork (CAR-NET), specifically designed to infer NRN from transcriptomic data and curated databases on experimentally validated ncRNA-gene interactions and disease-related ncRNAs. At its core is a novel computationally efficient Bayesian network structure learning method that leverages the semi-bipartite graph structure of NRN for dimension reduction, edge orientation and global network search. We also developed and applied algorithms to perform differential network, subnetwork and pathway analysis of the inferred network. We showed the strength of CAR-NET in simulations and three case studies, encompassing lncRNA regulation in brain development, miRNA differential regulation in renal cell carcinoma and regulation by different classes of ncRNAs in different cell lines using bulk or single cell RNA-seq data. An R-shiny app (https://github.com/kehongjie/CAR-NET) was developed to implement the method(s) with interactive GUI.

bioinformatics↗

bioRxiv2025

Perturbing RNA localization for functional study in neurons

Spatial RNA organization plays a pivotal role in diverse cellular processes and diseases, but the functional implications of spatial RNA localization remain underexplored. We present CRISPR-mediated transcriptome organization (CRISPR-TO) that harnesses RNA-guided, nuclease-dead dCas13 for programmable control of RNA localization in live cells. CRISPR-TO enables targeted localization of RNAs to diverse subcellular compartments, including p-bodies, stress granules, telomeres, and nuclear stress bodies, across cell types. In primary cortical neurons, we demonstrate that repositioned mRNAs undergo local translation along neurites and at neurite tips and co-transport with ribosomes, with {beta}-actin mRNA localization enhancing the formation of dynamic filopodial protrusions and inhibiting axonal regeneration. Furthermore, CRISPR-TO-enabled parallel screening in primary neurons identifies Stmn2 mRNA localization as a driver of neurite outgrowth. By enabling large-scale perturbation of the spatial transcriptome, CRISPR-TO bridges a critical gap left by current sequencing and imaging technologies, offering a versatile platform for high-throughput functional interrogation of RNA localization in living cells and organisms.

bioengineering↗

bioRxiv2025

Vacuum and sonication treatment enables efficient transient gene expression in various monocot and eudicot plant seedlings

Transient gene expression in intact plants is essential for rapidly addressing biological questions, where the current toolkit can be improved for higher efficiencies and broader plant species range. Here, we introduce VAST (Vacuum and Sonication-Assisted Transient expression): a transient transformation method that substantially enhances gene expression efficiency, reproducibility, and versatility across diverse monocot and eudicot intact seedlings. By systematically optimizing plant growth conditions and incorporating vacuum infiltration and sonication pre-treatments prior to seedling co-culture with Agrobacterium tumefaciens, we significantly improved transient gene expression efficiency while minimizing tissue damage compared to existing methods in Arabidopsis thaliana. We further demonstrated the broad applicability of VAST by successfully transforming key model and crop species, including tomato, Brassica rapa, Medicago sativa, Setaria italica (foxtail millet), switchgrass, and wheat. We also demonstrated a case study using the VAST-mediated transient transformation, where a cross-species analyses of nitrate-responsive gene expression highlighted both the conserved and diverged biological responses between the two model crops, A. thaliana and S. italica. VASTs simplicity, versatility, and efficiency provide a powerful tool for functional genomics, synthetic biology, and biotechnology research, opening new avenues for the rapid exploration of gene function, regulation, and editing in diverse plant systems.

plant biology↗

bioRxiv2025

Bacterial Vaginosis Toxins Impair Sperm Capacitation and Fertilization

Study questionWhat effect do toxins produced by bacterial vaginosis (BV) bacteria have on sperm function? Summary answerBacterial vaginosis toxins dysregulate sperm capacitation and intracellular calcium homeostasis and impair the ability of sperm to fertilize oocytes. What is known alreadyIn bacterial vaginosis, which is linked to infertility, overgrowth of Prevotella and Gardnerella in the vagina is accompanied by elevated concentrations of the toxins lipopolysaccharide (LPS) and vaginolysin (VLY). Study design, size, durationThis was a laboratory study in which human semen samples were collected from consenting healthy donors with normal semen parameters. Mouse sperm samples were obtained from the caudal epididymis. Participants/materials, setting, methodsMotile mouse and human sperm were isolated via swim-up and treated under non-capacitating or capacitating conditions. LPS from Escherichia coli was commercially available. VLY was produced by cloning the Gardnerella VLY protein in the ClearColi expression system. Mouse sperm were pre-incubated in in vitro fertilization medium with LPS or VLY and then co-cultured with ovulated cumulus-oocyte complexes. The effects of LPS and VLY on sperm motility and hyperactivation were assessed with computer-assisted sperm analysis. Effects on viability were assessed by Hoechst staining. Acrosomal exocytosis was assessed in sperm from transgenic Acr-eGFP mice and in human sperm stained with Pisum sativum agglutinin FITC. Intracellular calcium dynamics were assessed by staining sperm with the calcium-sensitive dye Fluo-4 AM and fluorescent imaging several sperm at the single-cell level. The effects of LPS on sperm from CatSper knock-out mice were assessed. Additionally, sperm were treated with a toll-like receptor 4 antagonist and further exposed to LPS. Main results and the role of chanceExposure of mouse sperm to LPS or VLY significantly decreased in vitro fertilization (P < 0.05). Under capacitating conditions, both toxins initially increased mouse and human sperm hyperactivation, then significantly decreased sperm motility (P < 0.05), hyperactivation (P < 0.05), and acrosomal exocytosis (P < 0.01). These changes were accompanied by a rapid and irreversible increase in intracellular calcium concentration. Effects of LPS, but not VLY, were prevented by polymyxin-B, which aggregates LPS. The LPS-induced intracellular calcium increase required external calcium but not the calcium channel CatSper and was inhibited by the Toll-like receptor 4 antagonist. Limitations, reasons for cautionFirst, the commercially available LPS we used was isolated from Escherichia coli, rather than from the BV-associated bacteria Prevotella bivia. Second, we did not quantify the absolute sperm intracellular calcium concentration before or after LPS or VLY treatment. Third, all of our experiments were in vitro. Wider implications of the findingsThese studies suggest that BV-associated toxins contribute to infertility by, in part, impairing sperm capacitation and reducing their fertilizing ability. Study funding/competing interest(s)This work was supported by the National Institutes of Health (grant #R01 HD069631). The authors declare that they have no conflict of interest.

physiology↗

bioRxiv2025

Transcription factors instruct DNA methylation patterns in plant reproductive tissues

DNA methylation is maintained by forming self-reinforcing connections with other repressive chromatin modifications, resulting in stably silenced genes and transposons. However, these mechanisms fail to explain how new methylation patterns are generated. In Arabidopsis, CLASSY3 (CLSY3) targets the RNA-directed DNA methylation (RdDM) machinery to different loci in reproductive tissues, generating distinct epigenomes via unknown mechanism(s). Here, we discovered that several different REPRODUCTIVE MERISTEM (REM) transcription factors are required for methylation at CLSY3 targets specific to male or female reproductive tissues. We designate these factors as REM INSTRUCT METHYLATION (RIMs) and demonstrate that disruption of their DNA binding domains, or the motifs they recognize, blocks RdDM. These findings not only reveal RIMs as the first sex-specific RdDM proteins but also establish a critical role for genetic information in targeting DNA methylation. This novel mode of targeting expands our understanding of how methylation is regulated to include inputs from both genetic and epigenetic information.

plant biology↗

bioRxiv2025

Automatic detection of fluorescently labeled synapses in volumetric in vivo imaging data

Synapses are submicron structures that connect and enable communication between neurons. Many forms of learning are thought to be encoded by synaptic plasticity, wherein the strength of specific synapses is regulated by modulating expression of neurotransmitter receptors. For instance, regulation of AMPA-type glutamate receptors is a central mechanism controlling the formation and recollection of long-term memories. A critical step in understanding how synaptic plasticity drives behavior is thus to directly observe, i.e., image, fluorescently labeled synapses in living tissue. However, due to their small size and incredible density -- with one [~]0.5 {micro}m diameter synapse every cubic micron -- accurately detecting individual synapses and segmenting each from its closely abutting neighbors is challenging. To overcome this, we trained a convolutional neural network to simultaneously detect and separate densely labeled synapses. These tools significantly increased the accuracy and scale of synapse detection, enabling segmentation of hundreds of thousands of individual synapses imaged in living mice.

neuroscience↗

bioRxiv2025

Bayesian data driven modelling of kinetochore dynamics: space-time organisation of the human metaphase plate

Mitosis is a complex self-organising process that achieves high fidelity separation of duplicated chromosomes into two daughter cells through capture and alignment of chromosomes to the spindle mid-plane. Chromosome movements are driven by kinetochores, multi-protein machines that attach chromosomes to microtubules (MTs), both controlling and generating directional forces. Using lattice light sheet microscopy imaging and automated near-complete tracking of kinetochores at fine spatio-temporal resolution, we produce a detailed atlas of kinetochore metaphase-anaphase dynamics in untransformed human cells (RPE1). We determined the support from this dataset for 17 models of metaphase dynamics using Bayesian inference, demonstrating (1) substantial sister asymmetry that transversely organises the metaphase plate (MPP), (2) substantial spatial organisation of KT dynamic properties within the MPP, and (3) mechanical parameter time dependence, K-fiber forces tuning over the last 5 mins of metaphase towards a set point referred to as the anaphase ready state. These spatio-temporal trends are robust to spindle assembly pathways that are error-prone, suggesting the underpinning processes of kinetochore heterogeneity are intrinsic to mitosis and possibly by design.

systems biology↗

bioRxiv2024

DDX41 dissolves G-quadruplexes to maintain erythroid genome integrity and prevent cGAS-mediated cell death

Deleterious germline DDX41 variants constitute the most common inherited predisposition disorder linked to myeloid neoplasms (MNs). The role of DDX41 in hematopoiesis and how its germline and somatic mutations contribute to MNs remain unclear. Here we show that DDX41 is essential for erythropoiesis but dispensable for the development of other hematopoietic lineages. Using stage-specific Cre models for erythropoiesis, we reveal that Ddx41 knockout in early erythropoiesis is embryonically lethal, while knockout in late-stage terminal erythropoiesis allows mice to survive with normal blood counts. DDX41 deficiency induces a significant upregulation of G-quadruplexes (G4), noncanonical DNA structures that tend to accumulate in the early stages of erythroid precursors. We show that DDX41 co-localizes with G4 on the erythroid genome. DDX41 directly binds to and dissolves G4, which is significantly compromised in MN-associated DDX41 mutants. Accumulation of G4 by DDX41 deficiency induces erythroid genome instability, defects in ribosomal biogenesis, and upregulation of p53. However, p53 deficiency does not rescue the embryonic death of Ddx41 hematopoietic-specific knockout mice. In parallel, genome instability also activates the cGas-Sting pathway, which is detrimental to survival since cGas-deficient and hematopoietic-specific Ddx41 knockout mice are viable without detectable hematologic phenotypes, although these mice continue to show erythroid ribosomal defects and upregulation of p53. These findings are further supported by data from a DDX41 mutated MN patient and human iPSC-derived bone marrow organoids. Our study establishes DDX41 as a G4 dissolver, essential for erythroid genome stability and suppressing the cGAS-STING pathway.

cancer biology↗

bioRxiv2024

Apollo: A comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell

Modern sequencing instruments bring unprecedented opportunity to study within-host viral evolution in conjunction with viral transmissions between hosts. However, no computational simulators are available to assist the characterization of within-host dynamics. This limits our ability to interpret epidemiological predictions incorporating within-host evolution and to validate computational inference tools. To fill this need we developed Apollo, a GPU-accelerated, out-of-core tool for within-host simulation of viral evolution and infection dynamics across population, tissue, and cellular levels. Apollo is scalable to hundreds of millions of viral genomes and can handle complex demographic and population genetic models. Apollo can replicate real within-host viral evolution; accurately recapturing observed viral sequences from an HIV cohort derived from initial population-genetic configurations. For practical applications, using Apollo-simulated viral genomes and transmission networks, we validated and uncovered the limitations of a widely used viral transmission inference tool.

bioinformatics↗

bioRxiv2024

A statistical-based method for the construction and analysis of gene network：application to bacteria

Bacteria play a crucial role in environmental conservation, human health, and medicine. Whether in the gut or the soil, bacterial genomes are rich repositories of resources, such as exploring potential drugs and biopesticides. However, our ability to develop new therapies and deepen our understanding of the bacterial world is hindered by the largely unknown functions of bacterial genes. In this study, we proposed a method of gene network construction and analysis based on a Gaussian Graphical Model (GGM) and random sampling strategy to infer direct interactions at the genomic level in bacteria. Using Vibrio cholerae and Staphylococcus aureus as examples, we integrated partial correlation-based gene co-expression data with gene regulatory and essentiality information extracted from public databases to construct more comprehensive gene networks. Networks built upon bacterial different phenotypes, such as biofilm formation, flagellar assembly, and stress response, demonstrate the effectiveness of this method in deciphering unknown gene functions, uncovering new phenotype-associated factors, and identifying their corresponding interactions, thus providing new targets for experimental validation by researchers. Additionally, we extended this method to 14 bacteria, including 13 pathogens, supporting the investigation of gene functions and pathways at the genomic level in these bacteria. More importantly, for other species, this method of gene network construction can be easily implemented, provided that sufficient transcriptome sequencing samples are available.

systems biology↗

bioRxiv2024

Survival of hepatocytes from executioner caspase activation promotes liver regeneration by enhancing JAK/STAT3 activity

Activation of executioner caspases, which is a key step in the apoptotic process, has been reported to promote tissue regeneration by sending pro-proliferation signals to the surrounding cells. However, whether executioner caspase activation (ECA) has cell-autonomous effect on tissue regeneration is not clear. Here, by generating transgenic mice carrying a lineage tracing system for cells that have experienced ECA, we demonstrate that transient ECA occurs in hepatocytes during liver regeneration after partial hepatectomy (PHx) or carbon tetrachloride (CCl4) treatment. Instead of committing apoptotic cell death, the majority of hepatocytes with ECA survive and proliferate to contribute to liver regeneration. Interestingly, inhibition of ECA in livers results in reduced hepatocyte proliferation and impaired regeneration, whereas increasing ECA to a level sufficient to kill hepatocytes also impedes regeneration, suggesting that ECA needs to be precisely controlled during liver regeneration. Mechanistic studies show that ECA promotes hepatocyte proliferation during regeneration through enhancing JAK/STAT3 activity. Our work reveals an essential role of survival of hepatocytes from ECA in liver regeneration.

developmental biology↗

bioRxiv2024

AxoDen: An Algorithm for the Automated Quantification of Axonal Density in defined Brain Regions

The rodent brain contains 70,000,000+ neurons interconnected via complex axonal circuits with varying architectures. Neural pathologies are often associated with anatomical changes in these axonal projections and synaptic connections. Notably, axonal density variations of local and long-range projections increase or decrease as a function of the strengthening or weakening, respectively, of the information flow between brain regions. Traditionally, histological quantification of axonal inputs relied on assessing the mean fluorescence intensity within a rectangle placed in the brain region-of-inter-est. Despite yielding valuable insights, this conventional method is notably susceptible to background fluorescence, post-acquisition adjustments, and inter-researcher variability. Additionally, it fails to account for the non-uniform innervation across brain regions, thus overlooking critical data such as innervation percentages and axonal distribution patterns. In response to these challenges, we introduce AxoDen, an open-source semi-automated platform designed to increase the speed and rigor of axon quantifications for basic neuroscience discovery. AxoDen processes user-defined brain regions-of-interests incorporating dynamic thresholding of grayscales-transformed images to facilitate binarized pixel measure-ments. Thereby AxoDen segregates the image content into signal and non-signal categories, effectively eliminating background interference and enabling the exclusive measurement of fluorescence from axonal projections. AxoDen provides detailed and accurate representations of axonal density and spatial distribution. AxoDens advanced yet user-friendly platform enhances the reliability and efficiency of axonal density analysis and facilitates access to unbiased high-quality data analysis with no technical background or coding experience required. AxoDen is freely available to everyone as a valuable neuroscience tool for dissecting axonal innervation patterns in precisely defined brain regions.

neuroscience↗

bioRxiv2024

An in-depth analysis and exploreation with focus on the biofilm in Staphylococcus aureus

Research into the biolfilm formation in Staphylococcus aureus has benefited greatly from the generation of high-throughput sequencing data to drive molecular analyses. The accumulation of these data, particularly transcriptomic data, offers a unique opportunity to unearth the network and constituent genes involved in the biofilm formation of Staphylococcus aureus through machine learning strategies and co-expression analyses. Herein, we harnessed all available RNA sequencing data related to Staphylococcus aureus biofilm studies and identified influenced functional pathways and corresponding genes in the process of the transition of bacteria from planktonic to biofilm state via employing machine learning and differential expression analyses. By weighted gene co-expression analysis and our previously developed predictor, important functional modules, potential biofilm-associated proteins and subnetwork of biofilm formation pathway were found. By constructing a protein-protein interaction (PPI) network, we discovered several hitherto unreported novel protein interactions within these functional modules. To make these data more straightforward to experimental biologists, an online database named SAdb was developed (http://sadb.biownmcli.info/). IMPORTANCEIn this work, we conducted a comprehensive and in-depth exploration of RNA sequencing data in biofilm research through differential expression analysis, machine learning, WGCNA, and biofilm-associated protein predictive analysis, which has also illuminated novel analytical perspective for other research into bacterial phenotypes. And, to provide researchers with unimpeded access to these data, we developed a database name SAdb for the storage and analysis of Staphylococcus aureus omics data. We believe that this study will captivate the interest of researchers in the field of bacteriology, particularly those studying biofilms, which play a crucial role in bacterial growth, pathogenicity, and drug resistance.

microbiology↗

bioRxiv2024

CTHRC1+ Fibroblasts and SPP1+ Macrophages Synergistically Contribute to Pro-Tumorigenic Tumor Microenvironment in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is an extremely lethal cancer that accounts for over 90% of all pancreatic cancer cases. With a 5-year survival rate of only 13%, PDAC has proven to be extremely desmoplastic and immunosuppressive to most current therapies, including chemotherapy and surgical resection. In recent years, focus has shifted to understanding the tumor microenvironment (TME) around PDAC, enabling a greater understanding of biological pathways and intercellular interactions that can ultimately lead to potential for future drug targets. In this study, we leverage a combination of single-cell and spatial transcriptomics to further identify cellular populations and interactions within the highly heterogeneous TME. We demonstrate that SPP1+APOE+ tumor-associated macrophages (TAM) and CTHRC1+GREM1+ cancer-associated myofibroblasts (myCAF) not only act synergistically to promote an immune-suppressive TME through active extracellular matrix (ECM) deposition and epithelial mesenchymal transition (EMT), but are spatially colocalized and correlated, leading to worse prognosis. Our results highlight the crosstalk between stromal and myeloid cells as a significant area of study for future therapeutic targets to treat cancer.

cancer biology↗