Search bioRxiv⌕ Search

Biology subjects

Pan, H.

Publications and source records attributed to Pan, H..

At least 37 records · Page 2Linked to original sources

Glypican-1 upregulation elicited in response to a cell-impermeable kinase inhibitor and its overexpression enhance HIV-1 infection

Studies of herpes simplex virus (HSV) entry uncovered a previously unappreciated "outside-in" signaling pathway whereby activation of the calcium (Ca2+) responsive enzyme phospholipid scramblase 1 (PLSCR1), which is known to trigger the bidirectional movement of phosphatidylserines (PS) between the inner and outer leaflet of the plasma membrane, also induces the translocation and subsequent extracellular activation of intracellular proteins, including Akt. We hypothesized that HIV-1, which has been shown to elicit scramblase TMEM16F-mediated PS externalization, may trigger a similar "outside-in" signaling cascade involving exofacial kinase activity to promote its entry into CD4+ T cells. To study this process, we utilized a cell impermeable staurosporine analogue, alkyl-CIMSS, which is a broadly active kinase inhibitor that blocks HSV-induced exofacial Akt phosphorylation and HSV infection. Using multiple cell types including TZM-bl, Jurkat T cells, and human peripheral blood mononuclear cells (PBMCs), we show that, in contrast to the effects on HSV, treatment of cells with alkyl-CIMSS enhances HIV-1 infection post-entry that is not dependent on TMEM16F. To identify potential biological processes that are responsive to alkyl-CIMSS, we performed bulk RNA-sequencing and whole cell proteomics and found that alkyl-CIMSS treatment of cells robustly upregulates the cell surface density of the proteoglycan glypican-1 (GPC1). Lentiviral delivery of GPC1 overexpression and shRNA knockdown constructs reveal that the presence and absence of GPC1 independently of alkyl-CIMSS treatment significantly impact HIV-1 infection, with the effect on infection corresponding to GPC1 expression. Further, we demonstrate that the influence of GPC1 on HIV-1 infection is in part mediated by TGF-{beta} signaling. Collectively, these findings implicate a cell surface protein susceptible to alkyl-CIMSS in restricting HIV-1 infection and identify GPC1 as a novel modulator of HIV-1 infection. Author SummaryWe utilized a cell-impermeable pan-kinase tool compound, alkyl-CIMSS, to identify cell surface molecules that might be involved in viral infection. Treatment of CD4+ T cells with alkyl-CIMSS increased the expression of the cell-surface protein glypican-1, which led to an increase in early HIV reverse transcriptase products and promoted viral infection. Conversely, alkyl-CIMSS inhibited herpes simplex virus entry and infection. These findings illustrate that viruses interact with exofacial cell membrane molecules differently to promote or impede infection.

microbiology↗

Single-nucleus transcriptional and chromatin accessibility profiling of mouse hypothalamic LepRb neurons reveals cell type-specific cis-regulatory elements linked to human obesity

Leptin receptor-expressing hypothalamic neurons (LepRHypo) are key regulators of energy balance, yet a comprehensive, cell type-resolved, chromatin accessibility map of these neurons is lacking. We profiled [~]20,000 LepRHypo nuclei using single-nucleus multiome (snRNA-seq/snATAC-seq), identifying 39 transcriptionally and epigenetically distinct clusters, including AgRP (two subtypes), Pomc (two subtypes), Foxb1, Irx5/3 (three subtypes), Nts, PNOC (two subtypes), Kiss1/Pdyn (KNDy, two subtypes), Ghrh, Tcf7l2, and Sf1/Nr5a1 (three subtypes) populations. We also identified three Glp1r-expressing clusters with the highest Lepr enrichment, each marked by distinct molecular signatures. Cluster-specific open chromatin regions (OCRs) delineated putative cis-regulatory elements unique to each LepRHypo subtype. Mouse cell-type specific OCRs conserved in the human genome were identified; a subset were proximal to genes with high Human Genetic Evidence (HuGE) scores for obesity-related traits, overlapped obesity-associated GWAS loci, and/or coincided with eQTLs, including variants with the potential to influence human energy balance. Together, these data provide cell type-specific cis-regulatory atlas of LepRHypo neuronal subtypes, including Glp1r/Lepr-enriched populations, and highlight evolutionarily conserved, subtype-specific regulatory elements, associated candidate genes, and putative functional variants that may modulate LepRHypo subtype function and influence energy homeostasis and obesity susceptibility in humans.

neuroscience↗

Origin and novel transport pathways of bacterial hopanoids

Hopanoids are a class of steroid-like lipids that fortify bacterial membranes. Derivatives of hopanoids known as "geo-hopanes" are abundant in sediments and are signatures of ancient bacteria, yet there are conflicting views on their use as markers of specific taxa or environments. Here we analyze conservation of hopanoid biosynthesis across bacterial genomes using modern taxonomic tools. We find that hopanoids most likely originated in an ancestor of marine alphaproteobacteria, and that tolerance of high osmolarity is the most common feature of hopanoid-producing strains. Additionally, microsynteny with hopanoid-related loci revealed new hopanoid-associated gene families, which we term hpnT and hpnS. Structural predictions and the restriction of these gene families to diderms suggests they participate in hopanoid trafficking, potentially forming a pathway analogous to Mla proteins in E. coli.

microbiology↗

MICRORNAS REGULATED BY PREGNANCY TARGET THE HIV INTERACTOME

Innate immunity predictors of HIV risk are influenced by reproductive hormone levels, pregnancy, and lactation status. However, the molecular mechanisms underlying these associations remain unclear. MicroRNAs (miRNAs), as post-transcriptional regulators, play key roles in immune regulation and host-virus interactions. We hypothesized that physiological adaptations to pregnancy include the modulation of systemic miRNA expression, which in turn regulates host genes involved in HIV interaction, potentially influencing susceptibility during pregnancy. To test this, we leveraged a large longitudinal cohort from Uganda and Zimbabwe and analyzed 174 serum samples from 88 participants in pre-pregnancy (PP), pregnancy (P), and breastfeeding (BF) states using the HTG EdgeSeq platform. Differentially expressed (DE) miRNAs in pregnancy were identified with false discovery rate (FDR) < 0.1 (29 upregulated and 131 downregulated) by intersecting pairwise comparisons (P vs. PP and P vs. BF). Validated gene targets (2,733) were identified via miRWalk and modular enrichment analysis performed using Cytoscape/ClueGO. Enriched pathways (FDR<0.05) included Adaptive Immune Response, Hippo Signaling, Cellular Senescence, HSV-1 Infection, and two cancer-related pathways. Genes from pregnancy-enriched pathways overlapped with the known HIV-host interactome at the range of 37 to 88%. From this overlap, the Maximal Clique Centrally (MCC) score (cytoHubba) identified 47 unique hub genes acting as essential regulatory nodes of protein-protein interaction (PPI) network. These hub genes were further examined by their expression patterns predicted by DE miRNAs, and explored for their interactions with the HIV interactome, revealing connectivity with 18 HIV proteins - highest with Tat and gp120 - and impact on the HIV replication process. HLA-A was the most connected host gene, followed by BCL2L1, EIF2AK2, PTEN, and CYCS. These findings support the hypothesis that pregnancy-driven systemic miRNAs may shape HIV susceptibility by regulating hub genes with central role in viral evasion of host immunity. GRAPHIC ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=138 HEIGHT=200 SRC="FIGDIR/small/665982v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@1cd2007org.highwire.dtl.DTLVardef@1f1b9d3org.highwire.dtl.DTLVardef@dee856org.highwire.dtl.DTLVardef@6796c2_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

CCN1 forms a complex with GPC4 and heparin to fine-tune signaling activities for embryonic cortical neural stem cell maintenance

Radial glial cells (RGCs) are the neural stem cells (NSCs) in the developing brain, capable of self-renewing and generating neurons and glia in order. The developmental behaviors of NSCs are determined by extrinsic factors from the NSC niche, together with intrinsic factors. Here, we show that Cellular Communication Network 1 (CCN1), a secreted matricellular protein, is an autocrine factor derived from RGCs in the embryonic telencephalon. Loss of Ccn1 in RGCs leads to accelerated lineage progression of RGCs, and causes premature cell cycle exit and neuronal differentiation, resulting in a reduction in NSC pool size, and in turn, at the expense of the perinatal gliogenesis. Mechanistically, CCN1 interacts with an RGC-expressed membrane protein GPC4, one of the heparan sulfate proteoglycans (HSPGs), and is required for GPC4 to maintain NSCs through the Sonic Hedgehog (Shh) signaling pathway, depending on the binding of heparin to CCN1. Our work provides a potential mechanism for the dynamic and sophisticated interconnections of niche components that meet the needs of context-dependent maintenance, differentiation, and fate determination of NSCs.

developmental biology↗

A human and mouse subpopulation of senescent β-cells induces pathologic dysfunction through targetable paracrine signaling

Cellular senescence is a stress response mechanism marked by irreversible growth arrest, upregulation of antiapoptotic pathways, loss of cellular function, and remodelling of the cellular secretory profile. In both humans and mice, pancreatic {beta}-cells undergo senescence with age and insulin resistance. Targeted removal of senescent cells in mouse models of diabetes improves glucose homeostasis, demonstrating the role {beta}-cell senescence in diabetes progression. In contrast, {beta}-cell senescence also promotes immune surveillance, promoting {beta}-cell survival and function. Thus, a better understanding of senescent cells phenotypic and functional heterogeneity is needed to develop effective therapeutic strategies. Herein, we show that subpopulations of senescent {beta}-cells in mice and humans, which were identified through the expression of Cdkn1a (encoding p21Cip1) and Cdkn2a (encoding p16Ink4a) by single-cell RNA sequencing (scRNA-seq), flow cytometry, spatial transcriptomics, and spatial proteomics, exhibit distinct transcriptional and functional identities. The predominant senescent {beta}-cell subpopulation expressed Cdkn1a and was characterized by a lack of glucose responsiveness, high basal insulin secretion, and transcription of canonical SASP factors. The SASP of Cdkn1a-expressing {beta}-cells had non-cell autonomous effects on neighbouring cells. A subset of four SASP factors from Cdkn1a+ cells was sufficient to induce secondary senescence and {beta}-cell dysfunction in vitro. JAK inhibitors (JAK1/2 and JAK1/3) counteracted secondary senescence induction and restored {beta}-cell function in high-fat diet-fed mice and human islets from donors with or without type 2 diabetes. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC="FIGDIR/small/648438v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@9b8addorg.highwire.dtl.DTLVardef@1b9c4eborg.highwire.dtl.DTLVardef@12f2964org.highwire.dtl.DTLVardef@1468297_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

Dynamic Pathway of Guanidine-III Riboswitch Folding Revealed by Single-Molecule FRET: Mg2+-Assisted Preorganization and Ligand-Induced Kinetic Trapping

Riboswitches are structured RNA elements that regulate gene expression by sensing and binding small molecules. The guanidine-III riboswitch, a critical bacterial regulator responding to guanidine toxicity, undergoes precise conformational changes that remain poorly characterized at a dynamic, mechanistic level. In this study, we employed single-molecule Forster Resonance Energy Transfer (smFRET) coupled with molecular dynamics (MD) simulations to delineate how the guanidine-III riboswitch transitions among distinct conformational states. We identify three principal states [-] an extended (E-state), a compacted prefolded intermediate (P-state), and a folded pseudoknot structure (F-state) [-] with rapid interconversion in the absence of ligand. Magnesium ions significantly stabilize intermediate states via a cooperative, preorganization mechanism, enhancing ligand binding efficiency. Binding of guanidine drastically suppresses the reverse transitions, kinetically trapping the riboswitch into its active folded state primarily through a conformational selection mechanism, with additional contributions from induced-fit dynamics. This work illuminates the unique dynamic pathway by which the guanidine-III riboswitch integrates ionic and ligand cues, ensuring precise gene regulatory responses in bacteria.

biophysics↗

Bacillus velezensis 9912 enhances rice growth by triggering plant hormone modulation and complex miRNA-mRNA regulatory networks

Bacillus velezensis, a prominent member of plant growth-promoting bacteria, effectively suppresses pathogens and promotes plant growth. Despite its well-recognized efficacy, the intricate molecular mechanisms of its growth-promoting attributes remain largely unexplored. In this study, a commercial biopesticide B. velezensis 9912 significantly enhanced leaf photosynthesis and improved rice root development in the field experiment. And then, a rigorous hydroponic experiment was performed to investigate its underlying mechanism in plant growth promotion. High-throughput sequencing and bioinformatics analysis revealed 2,938 rice genes and 30 miRNAs responsive to strain 9912. Notably, differentially expressed genes encompassed key transcription factors like ERF, WRKY, and AP2. Remarkably, auxin-and ethylene-related genes were up-regulation significantly at day 1 and pectinesterase-related genes were up-regulation considerably at day 3, which revealed an unusual growth mechanism for strain 9912 to promote rice root development. In addition, DNA replication, cell cycle, cell division, and cytoskeleton organization were significantly enriched in GO and KEGG pathways. Biosynthetic pathways of secondary metabolites, such as carotenoid, lipid, diterpenoid, and brassinosteroid were also significantly enriched. An integrated analysis of the transcriptome and miRNAome identified several miRNA-mRNA regulatory networks, including miR166-Os08g14940, miR396-Os07g9320, miR529-Os12g31540, and miR6249-Os05g07880, which are involved in the process of growth promotion. In conclusion, our investigation offers insightful thoughts into the dynamic responses of rice genes and miRNAs to B. velezensis 9912, unveiling plant hormone modulation and potential miRNA-mRNA regulatory networks that are imperative in the growth promotion mechanism.

microbiology↗

D-LMBmapX: Generalized Deep-Learning Pipeline for Automated Whole-brain Neural Circuitry Profiling Across Any Developmental Stages

Understanding whole-brain circuitry development is essential for uncovering the origins of disorders linked to abnormal neural wiring, yet progress has been limited by the lack of tools for accurate, comprehensive analysis. Brain development is highly dynamic and region-specific, with pronounced inter-individual variability during early stages, and no existing method achieves whole-brain profiling at arbitrary stages. The rapidly changing morphology of developing axons further complicates segmentation. Here, we present D-LMBmapX, a deep learning pipeline for automated whole-brain circuitry profiling across postnatal development. D-LMBmapX constructs sample-inferred atlases from flanking anchor stages, enabling accurate registration at any time point. By developing a foundation model for generalised axon and soma segmentation, it supports quantitative mesoscale developmental connectomics, demonstrated through spatial-temporal profiling of catecholaminergic projections. D-LMBmapX also enables robust cross-modality and cross-dimensional registration, including precise alignment of single 2D slices to 3D references, and offers generalizable strategies for 5D analysis of diverse biomedical spatial datasets.

neuroscience↗

Gut Microbiome Signatures Reflect Within-Host Subtype Diversity of Blastocystis in Non-Human Primates

Blastocystis is a prevalent gut eukaryote intricately associated with the gut microbiota. This genetically diverse protozoan exhibits significant intra-host subtype heterogeneity, yet the implications of this diversity for the host gut microbiome remain poorly understood. Here, we investigated the interactions between Blastocystis and gut microbiota in non-human primates at the level of subtypes, using a comprehensive investigation of gut microbiota for Blastocystis carriers of captive Macaca fascicularis (discovery cohort, n = 100) and Macaca mulatta (validation cohort, n = 26). We identified highly prevalent intra-host co-occurrence patterns of Blastocystis SSU rRNA-based subtypes, primarily dominated by Subtype 1(ST1) or ST3. These patterns were associated with compositional and structural variations in the gut microbiome but were not significantly influenced by host covariates such as sex, age, or BMI. Specifically, Ruminococcaceae-enterotype was enriched in the patterns dominated by ST1, whereas Limosilactobacillus-enterotype was predominantly identified in the patterns dominated by ST3. We discovered that the absolute abundance of Blastocystis was a critical determinant in elucidating this association across concurrent patterns. In vivo experiments in a new cohort (n = 11) demonstrated that lactic acid bacteria, enriched in the Limosilactobacillus-enterotype, were sufficient to reduce Blastocystis load. We validated the strong association between gut microbiome composition and Blastocystis load in M. mulatta, confirming that specific microbial features could quantitatively predict Blastocystis status in both species. Our findings establish a direct link between gut microbial variations, intra-host genetic heterogeneity, and absolute abundance in Blastocystis for non-human primates.

microbiology↗

Infectome analysis of bat kidneys from Yunnan province, China, reveals close relatives of Hendra-Nipah viruses and prevalent bacterial and eukaryotic pathogens

Bats are natural reservoirs for a wide range of microorganisms, including many notable zoonotic pathogens. However, the infectome of bat kidneys remains poorly understood. To address this gap, we performed meta-transcriptomic sequencing on kidney tissues from 142 bats, spanning ten species sampled at five locations in Yunnan province, China. This analysis identified 22 viral species, including 20 novel viruses, two of which represented newly discovered henipaviruses closely related to the highly pathogenic Hendra and Nipah viruses. These henipaviruses were found in the kidneys of bats inhabiting an orchard near villages, raising concerns about potential fruit contamination via bat urine and transmission risks to livestock or humans. Additionally, we identified a novel protozoan parasite, tentatively named Klossiella yunnanensis, along with two highly abundant bacterial species, one of which is a newly discovered species--Flavobacterium yunnanensis. These findings broaden our understanding of the bat kidney infectome, underscore critical zoonotic threats, and highlight the need for comprehensive, full-spectrum microbial analyses of previously understudied organs to better assess spillover risks from bat populations.

microbiology↗

DDI-GPT: Explainable Prediction of Drug-Drug Interactions using Large Language Models enhanced with Knowledge Graphs

Identifying potential drug-drug interactions (DDIs) before clinical use is essential for patient safety yet remains a significant challenge in drug development. We presented DDI-GPT, a deep learning framework that predicts DDIs by combining knowledge graphs (KGs) and pre-trained large language models (LLMs), enabling early detection of potential drug interactions. We demonstrated that DDI-GPT outperforms current state-of-the-art methods by capturing contextual dependencies between biomedical entities to infer potential DDIs. Through feature attribution methods, we show that our explainable deep learning (DL) models enhance the quality of explanations on the pathways and interactome networks. Using TwoSIDES as our benchmark dataset, DDI-GPT achieved the best performance of 0.964 in AUROC compared with existing DL methods. We also applied DDI-GPT to perform zero-shot prediction on 9,480 DDI records, encompassing 442 distinct drugs from the FDA Adverse Event Reporting System. DDI-GPT can attain a high accuracy of in 0.84 AUROC, with an improvement of 14% compared to the best previously published method. We explored model interpretations on predicted DDIs involving Brutons tyrosine kinase (BTK) inhibitors and uncovered CYP3A-enriched signals underlying the contaminant use of BTK inhibitors with other drugs leading to toxicity. Altogether, DDI-GPT, implemented as both a web server platform and a software package, identifies DDI events and offers a deep learning tool for drug safety use with expandable features.

bioinformatics↗

PAIRWISE: Deep Learning-based Prediction of Effective Personalized Drug Combinations in Cancer

Combination therapies offer promise for improving cancer treatment efficacy and preventing recurrence. However, identifying optimal drug combinations tailored to specific cancer subtypes and individual patients is extremely challenging due to the vast number of possible combinations and tumor heterogeneity. To address this gap, we take a machine learning approach combining deep learning with transfer learning to incorporate prior scientific knowledge and predict drug synergy based on tumor-specific transcriptome profiles. This approach, called PAIRWISE, explicitly modeled synergistic effects of drug combinations in cancer cell lines or individual tumor samples based on drug chemical structures, drug targets, and transcriptomes of inferred samples. PAIRWISE outperformed competing models with an area under the receiver operating characteristic curve (AUROC) of 0.85 on held-out cancer cell lines. When applied to an independent dataset of combinations with Bruton Tyrosine Kinase inhibitors (BTKi) in Diffuse Large B Cell Lymphoma (DLBCL) cell lines, PAIRWISE accurately predicted synergistic drug combinations with an AUROC of 0.72. To further confirm the robustness of PAIRWISE predictions, we performed an in silico, patient profile-directed screen for other compounds that would synergize with BTKi in DLBCL patients, and confirmed the synergy of the predictions using a panel of eight non-Hodgkin lymphoma cell lines. These findings demonstrate the ability of PAIRWISE to nominate effective personalized drug combinations, accelerating the development of precision oncology.

bioinformatics↗

Bergeyella cardium variant induces unique cytoplasmic vacuolization cell death

Bacterial pathogens have evolved multiple mechanisms to modulate host cell death, evade host immunity, and establish persistent infection. Here, we show that an emerging pathogen Bergeyella cardium variant (BCV) survives serum killing, inducing unique cytoplasmic vacuolization cell death in the majority of cells and apoptosis in a small number of bystanders. The cytoplasmic vacuolization cell death triggered by BCV is characterized by fused lysosome-associated termination and is inhibited by the sodium channel inhibitor amiloride. Endosomal solute carrier family 9 member A9 (SLC9A9) was identified as a critical regulator in the process of BCV-triggered cytoplasmic vacuolization cell death. Moreover, outer membrane vesicles (OMVs) or transfection of barrel-like membrane proteins lipocalin, {beta}-barrel, and PorV dramatically induced cytoplasmic vacuolization. BCV hijacked SLC9A9 by maintaining its high expression, increasing cytoplasmic vacuolization, and enhancing pathogenicity. These findings contribute to the development of novel approaches to modulate cytoplasmic vacuolization cell death and treat infectious diseases. HighlightsO_LIBCV triggers unique cytoplasmic vacuolization cell death. C_LIO_LISLC9A9 is essential for BCV-induced cytoplasmic vacuolization cell death. C_LIO_LIOMVs and the transfection of barrel-like proteins derived from BCV induce cytoplasmic vacuolization cell death. C_LIO_LIBCV increases pathogenicity via cytoplasmic vacuolization cell death. C_LI

cell biology↗

Small mammals in biodiversity hotspot harbor viruses of epidemic potential

Metagenomic sequencing has transformed our understanding of viral diversity in wildlife and its threat to human health. Despite this progress, many studies have lacked systematic and ecologically informed sampling, which has left numerous potentially emergent viruses undiscovered, and the drivers of their ecology and evolution poorly understood. We conducted an extensive analysis of viruses in the lung, spleen, and gut of 1,688 animals from 38 mammalian species across 428 sites in Yunnan, China--a hotspot for zoonotic diseases. We identified 162 mammalian viral species, including 102 novel species and 24 posing potential risks to humans due to their relationships with known pathogens associated with serious diseases and their ability to cross major host species barriers. Our findings offer an in-depth view of virus organotropism, cross-species transmission, host sharing patterns, and the ecological factors influencing viral evolution, all of which are critical for anticipating and mitigating future zoonotic outbreaks.

microbiology↗

CureSCi Metadata Catalog - finding and harmonizing studies for secondary analysis of hydroxyurea use for sickle cell disease

ObjectivesSickle cell disease (SCD) is a rare group of inherited red blood cell disorders that affect hemoglobin, resulting in serious multi-system complications. The limited number of patients available to participate in research studies can inhibit investigating sophisticated relationships. Secondary analysis is a research method that involves using existing data to answer new research questions. Data harmonization enables secondary analysis by combining data across studies, especially helpful for rare disease research where individual studies may be small. The National Heart, Lung, and Blood Institute Cure Sickle Cell Initiative (CureSCi) Metadata Catalog is a web-based tool to identify SCD study datasets for conducting data harmonization and secondary analysis. We present a proof-of-concept secondary analysis to explore factors associated with discontinuation of hydroxyurea, a safe and effective first line SCD therapy, to illustrate the utility of the CureSCi Metadata Catalog to expedite and enable more robust SCD research. MethodsWe performed secondary analysis of SCD studies using a multi-step workflow: develop research questions, identify study datasets, identify variables of interest, harmonize variables, and establish an analysis method. A harmonized dataset consisting of eight predictor variables across five studies was created. Secondary analysis involved a generalized linear model was employed to identify factors that significantly impact hydroxyurea discontinuation. ResultsThe CureSCi Metadata Catalog provided a platform to efficiently find relevant studies and design a harmonization strategy to prepare data for secondary analysis. Multivariate analysis of the harmonized identified that patients who are older, are female, had a history of blood transfusion therapy, had episodes of acute chest syndrome, and had the SC sickle cell genotype are more likely to stop hydroxyurea treatment. ConclusionThis secondary analysis provides a template for how the CureSCi Metadata Catalog expedites dataset discovery of sickle cell studies for identifying relationships between variables or validating existing findings.

bioinformatics↗

Three-dimension transcriptomics maps of whole mouse embryo during organogenesis

Understanding mammalian development heavily relies on classical animal models like the house mouse (Mus musculus). Advanced spatial transcriptomics has enabled biologists to break new ground in studies of molecular dynamics and cellular patterning during embryonic development with spatiotemporal resolution. To construct a comprehensive developmental trajectory, current three-dimensional (3D) spatial transcriptomic profiling leverages mouse embryos from gastrulation (E5.5) to organogenesis (E13.5) in continuity. However, a crucial phase for early organogenesis between E9.5 and E11.5 was deficient. To unveil the mystery of this stage, we present the 3D transcriptomics of mouse embryos at E9.5 and E11.5, with a widely applicable reconstruction workflow that bypasses sophisticated bioinformatic calculations. As our 3D atlas is generated at single-cell resolution, we demonstrate how organogenetic processes can be interpreted at different levels of granularity, from local cellular interactions to whole embryonic regionalization. We release the open-access database MOSTA3D (Mouse Organogenesis Spatiotemporal Transcriptomic Atlas in Three-dimensional) and hope a broader community will contribute to extending this framework from conception to senility in the near future.

developmental biology↗

Collagen modification remodels the sarcoma tumor microenvironment and promotes resistance to immune checkpoint inhibition

Molecular mechanisms underlying immune checkpoint inhibitor (ICI) response heterogeneity in solid tumors, including soft tissue sarcomas (STS), remain poorly understood. Herein, we demonstrate that the collagen-modifying enzyme, procollagen-lysine,2-oxoglutarate 5-dioxygenase 2 (Plod2), which is over-expressed in many tumors relative to normal tissues, promotes immune evasion in undifferentiated pleomorphic sarcoma (UPS), a relatively common and aggressive STS subtype. This finding is consistent with our earlier observation that Plod2 promotes tumor metastasis in UPS, and its enzymatic target, collagen type VI (ColVI), enhances CD8+ T cell dysfunction. We determined that genetic and pharmacologic inhibition of Plod2 with the pan-Plod transcriptional inhibitor minoxidil, reduces UPS growth in an immune competent syngeneic transplant system and enhances the efficacy of anti-Pd1 therapy. These findings suggest that PLOD2 is an actionable cancer target and its modulation could augment immunotherapy responses in patients with UPS, and potentially other sarcomas and carcinomas.

cancer biology↗