Transcriptomic Datasets Research Articles

Potential biomarkers and immune infiltration linking endometriosis with recurrent pregnancy loss based on bioinformatics and machine learning

ObjectiveEndometriosis (EMs) is a chronic inflammatory disease characterized by the presence of endometrial tissue in the non-uterine cavity, resulting in dysmenorrhea, pelvic pain, and infertility. Epidemiologic data have suggested the correlation between EMs and recurrent pregnancy loss (RPL), but the pathological mechanism is unclear. This study aims to investigate the potential biomarkers and immune infiltration in EMs and RPL, providing a basis for early detection and treatment of the two diseases.MethodsTwo RPL and six EMs transcriptomic datasets from the Gene Expression Omnibus (GEO) database were used for differential analysis via limma package, followed by weighted gene co-expression network analysis (WGCNA) for key modules screening. Protein-protein interaction (PPI) network and two machine learning algorithms were applied to identify the common core genes in both diseases. The diagnostic capabilities of the core genes were assessed by receiver operating characteristic (ROC) curves. Moreover, immune cell infiltration was estimated using CIBERSORTx, and the Cancer Genome Atlas (TCGA) database was employed to elucidate the role of key genes in endometrial carcinoma (EC).Results26 common differentially expressed genes (DEGs) were screened in both diseases, three of which were identified as common core genes (MAN2A1, PAPSS1, RIBC2) through the combination of WGCNA, PPI network, and machine learning-based feature selection. The area under the curve (AUC) values generated by the ROC indicates excellent diagnostic powers in both EMs and RPL. The key genes were found to be significantly associated with the infiltration of several immune cells. Interestingly, MAN2A1 and RIBC2 may play a predominant role in the development and prognostic stratification of EC.ConclusionWe identified three key genes linking EMs and RPL, emphasizing the heterogeneity of immune infiltration in the occurrence of both diseases. These findings may provide new mechanistic insights or therapeutic targets for further research of EMs and RPL.

A Transcriptomic Dataset of Liver Tissues from Global and Liver-Specific Bmal1 Knockout Mice

The circadian clock regulates various physiological processes in mammals. The core circadian clock gene Bmal1 is crucial for maintaining the oscillations of the circadian clock system by controlling the rhythmic expression of numerous circadian clock-controlled genes. To explore the transcriptional changes associated with Bmal1 deletion in liver tissues, we collected liver tissues from global and liver-specific Bmal1 knockout mice, along with their respective control groups, at two circadian time points (CT2 and CT14) and used them for transcriptome sequencing analysis. Genotyping, locomotor activity analysis, and comprehensive quality control analyses, including base quality scores, GC content, and mapping rates, confirmed the high quality of sequencing data. Differential expression analysis and RT-qPCR validation confirmed the reliability and validity of the dataset. These data offer a valuable resource for researchers investigating the role of BMAL1 in liver physiology, pathology, and the broader field of circadian biology.

Local Inflammation Precedes Diaphragm Wasting and Fibrotic Remodelling in a Mouse Model of Pancreatic Cancer.

Cancer cachexia represents a debilitating muscle wasting condition that is highly prevalent in gastrointestinal cancers, including pancreatic ductal adenocarcinoma (PDAC). Cachexia is estimated to contribute to ~30% of cancer-related deaths, with deterioration of respiratory muscles suspected to be a key contributor to cachexia-associated morbidity and mortality. In recent studies, we identified fibrotic remodelling of respiratory accessory muscles as a key feature of human PDAC cachexia. To gain insight into mechanisms driving respiratory muscle wasting and fibrotic remodelling in response to PDAC, we conducted temporal histological and transcriptomic analyses on diaphragm muscles harvested from mice-bearing orthotopic murine pancreatic (KPC) tumours at time points reflective of precachexia (D8 and D10), mild-moderate cachexia (D12 and D14) and advanced cachexia (endpoint). During the precachexia phase, diaphragms showed significant leukocyte infiltration (+3-fold to +13-fold; D8-endpoint vs. Sham, p < 0.05) and transcriptomic enrichment of inflammatory processes associated with tissue injury that remained increased through endpoint. Diaphragm inflammation was followed by increases in PDGFR-ɑ+ fibroadipogenic progenitors (+2.5 to +3.8-fold; D10-endpoint vs. Sham, p < 0.05), fibre atrophy (-16% to -24%, D12 to endpoint vs. Sham, p < 0.05), ECM expansion (+1.5 to +1.8-fold; D14-endpoint vs. Sham, p < 0.05), collagen accumulation (+3.8-fold; endpoint vs. Sham, p = 0.0013) and reductions in breathing frequency (-55%, p = 0.0074) and diaphragm excursion (-43%, p = 0.0006). These biological processes were supported by changes in the diaphragm transcriptome. Ingenuity pathway analysis predicted factors involved in inflammatory responses to tissue injury, including TGF-β1, angiotensin and PDGF BB, as top upstream regulators activated in diaphragms prior to and throughout cachexia progression, while PGC-1α and the insulin receptor were among the top upstream regulators predicted to be suppressed. The transcriptomic dataset further revealed progressive disturbances to networks involved in lipid, glucose and oxidative metabolism, activation of the unfolded protein response and neuromuscular junction remodelling associated with denervation. In summary, our data support leukocyte infiltration and expansion of PDGFRα mesenchymal progenitors as early events that precede wasting and fibrotic remodelling of the diaphragm in response to PDAC that may also underlie metabolic disturbances, weakness and respiratory complications.

Progressive natural killer cell dysfunction in advanced-stage clear-cell renal cell carcinoma and association with clinical outcomes.

Natural killer (NK) cells are important contributors to antitumor immunity in clear-cell renal cell carcinoma (ccRCC). However, their phenotype, function, and association with clinical outcomes in ccRCC remain poorly understood. We analyzed single-cell RNA sequencing data from 13 primary tumors, 1 localized tumor extension, and 1 metastasis from ccRCC patients at different clinical stages. For each primary tumor specimen, paired normal kidneys were also analyzed. Differential gene expression analysis was carried out to investigate NK cell phenotypes and to derive a gene expression signature. Gene signatures from NK cell subclusters of interest were used to interrogate bulk transcriptomic datasets and expression with clinical outcomes. Finally, tumor-infiltrating NK cell function (cytokine production and cytotoxicity) was assessed by isolation of live NK cells from ccRCC tissue, co-culture with K562 target cells, and measurement of cytokine production (interferon-γ) and cytotoxicity (CD107a) markers by flow cytometry. Single-cell transcriptomic data were analyzed from 13 patients with ccRCC (tumor/normal kidney), resulting in 21 139 NK cells. Clustering analysis revealed six NK cell subsets. Bright-like NK cells were significantly enriched in advanced ccRCC compared with localized ccRCC and normal kidney, expressed markers of tissue residency (ZNF683/Hobit, ITGA1/CD49a, CD9, ITGAE/CD103), and had decreased expression of cytotoxicity genes (GZMB/Granzyme-B, PRF1/perforin). In independent cohorts (The Cancer Genome Atlas ccRCC cohort, CheckMate 025), a gene expression score representing this dysfunctional NK cell phenotype was enriched in advanced ccRCC and was associated with worse overall survival. Functional interrogation of tumor-infiltrating NK cells from ccRCC confirmed that tumor-resident CD49a+CD9+ NK cells had impaired cytotoxicity compared with CD49a-CD9- NK cells. A dysfunctional, tumor-resident NK cell phenotype was enriched among patients with metastatic disease and associated with worse survival in patients with advanced ccRCC across multiple patient cohorts. Restoration of NK cell function (via cytokine stimulation or NK cell engineering) could provide a novel avenue for therapeutic intervention against ccRCC.

Anticancer and therapeutic efficacy of XPO1 inhibition in pancreatic ductal adenocarcinoma through DNA damage and modulation of miR-193b/KRAS/LAMC2/ERK/AKT signaling cascade.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and grave malignancies with confined and ineffective therapeutic options. XPO1 is a critical regulator of nuclear export and activation of tumor suppressor proteins. The present study evaluated the therapeutic potential and molecular mechanisms of XPO1 inhibition against PDAC. Firstly, we observed significant overexpression of XPO1 transcript in 179 PDAC patients than 171 normal pancreatic tissues in TCGA transcriptomic dataset. Higher XPO1 transcript levels displayed worse overall and disease-free survival. Further, we confirmed significant upregulation of XPO1 in a panel of PDAC cells. Eltanexor treatment resulted in significant inhibition of cell viability, clonogenic growth, migration, and epithelial-mesenchymal transition (EMT), along with the induction of cell cycle arrest. Mechanistically, eltanexor modulated the expression of key proteins including p21, p27, p53, cyclin B1, cyclin D1, c-Myc, N-cadherin, vimentin, E-cadherin associated with the cell viability, growth, cell cycle and EMT. Additionally, the eltanexor treatment resulted in marked increase in expression of γH2AX, and cleaved PARP, cleaved caspase-9 leading to induction of DNA damage and apoptosis of PDAC cells, respectively. Moreover, eltanexor treatment regulated the expression of key non-coding RNAs including miR193b, DINO, MALAT-1, H19, and SOX21-AS1 linked with tumorigenesis. Our results revealed a correlation among miR193b/KRAS/LAMC2, XPO1/KRAS, and LAMC2/KRAS. The findings also revealed that eltanexor treatment rescued the expression of miR193b which acts as a sponge for LAMC2 and KRAS resulting in the suppression of AKT/ERK downstream signaling cascade in PDAC. Interestingly, the combination of eltanexor with gemcitabine showed significant anticancer activity in PDAC cells. Altogether, our findings revealed the crucial role of XPO1 in modulating the expression of oncogenic proteins, ncRNAs, and DNA damage during PDAC progression as well as identified novel therapeutic miR-193b/KRAS/LAMC2/ERK/AKT axis.

Transcriptome datasets of salt-stressed tomato plants treated with zinc oxide nanoparticles.

Salinity diminishes agricultural productivity and quality, resulting in overall economic losses on a worldwide scale. Zinc oxide nanoparticles (ZnO-NPs) have been found to enhance plant physiological and metabolic processes, as well as increase overall resilience to abiotic stressors. A research study was undertaken to assess the effects of foliar application of chemically produced ZnO-NPs on tomato plants, both in the presence and absence of a NaCl stressor. The datasets were obtained through the utilization of the shallow mRNA sequencing technology. Six datasets from the SRA were uploaded to NCBI. The aforementioned datasets encompass the Transcriptome Shotgun Assembly (TSA), the contigs that underwent blasting, mapping, and annotation from the pre-processed datasets, and the count table derived from the quantification of RNA-seq reads. All the aforementioned data is encompassed under the Mendeley database. Moving forward, the utilization of databases will facilitate the examination of modifications in plant biochemical reactions at the level of gene expression.

Scatterbar: an R package for visualizing proportional data across spatially resolved coordinates.

Displaying proportional data across many spatially resolved coordinates is a challenging but important data visualization task, particularly for spatially resolved transcriptomics data. Scatter pie plots are one type of commonly used data visualization for such data but present perceptual challenges that may lead to difficulties in interpretation. Increasing the visual saliency of such data visualizations can help viewers more accurately identify proportional trends and compare proportional differences across spatial locations. We developed scatterbar, an open-source R package that extends ggplot2, to visualize proportional data across many spatially resolved coordinates using scatter stacked bar plots. We apply scatterbar to visualize deconvolved cell-type proportions from a spatial transcriptomics dataset of the adult mouse brain to demonstrate how scatter stacked bar plots can enhance the distinguishability of proportional distributions compared to scatter pie plots. scatterbar is available on CRAN https://cran.r-project.org/package=scatterbar with additional documentation and tutorials at https://jef.works/scatterbar/. Supplementary data are available at Bioinformatics online.

Interneuron loss and microglia activation by transcriptome analyses in the basal ganglia of Tourette disorder.

Tourette disorder is characterized by motor hyperactivity and tics that are believed to originate in basal ganglia. Postmortem immunocytochemical analyses previously revealed decreases in cholinergic, parvalbumin, and somatostatin interneurons (IN) within the caudate/putamen of individuals with TS. We obtained transcriptome and open chromatin datasets by snRNAseq and snATAC-seq, respectively, from caudate/putamen postmortem specimens of 6 adult TS and 6 matched normal control (NC). Differential gene expression and differential chromatin accessibility analyses were performed in identified cell types. The data reproduced the known cellular composition of the human striatum, including a majority of medium spiny neurons (MSN) and small populations of GABAergic and cholinergic IN. IN were decreased by ∼50% in TS brains, with no difference in other cell types. Differential gene expression analysis suggested that mitochondrial oxidative metabolism in MSN and synaptic adhesion and function in IN were both decreased in TS subjects, while there was activation of immune response in microglia. Gene expression changes correlated with changes in activity of cis-regulatory elements, suggesting a relationship of transcriptomic and regulatory abnormalities in MSN, OL and AST of TS brains. This initial analysis of the TS basal ganglia transcriptome at the single cell level confirms the loss and synaptic dysfunction of basal ganglia IN, consistent with in vivo basal ganglia hyperactivity. In parallel, oxidative metabolism was decreased in MSN and correlated with activation of microglia cells, attributable at least in part to dysregulated activity of putative enhancers, implicating altered epigenomic regulation in TS.

Spatial single-cell maps reveal ST6GAL1 promoting ovarian cancer metastasis.

In this study, spatial and single-cell transcriptome techniques were used to investigate the role of beta-galactoside alpha-2,6-sialyltransferase 1 (ST6GAL1) in promoting peritoneal metastasis in ovarian cancer epithelial cells. We collected single-cell transcriptomic (GSE130000) and spatial transcriptomic datasets (GSE211956) from the Gene Expression Omnibus and RNA-sequencing data from The Cancer Genome Atlas. The Robust Cell Type Decomposition (RCTD) approach was implemented to integrate spatial and single-cell transcriptomic data. In addition, pseudo-time trajectory analysis, cell-cell communication networks, transcription factor activity profiling, spatial interaction mapping, and prognostic significance of gene expression were assessed. A significant enrichment of ST6GAL1 was observed in the epithelial cells of ovarian cancer, particularly in peritoneal metastases, which exhibited elevated metabolic activity compared to primary tumors. The levels of ST6GAL1 were significantly high in peritumoral and adjacent non-tumorous tissues, with increased metabolic activity, while the tumor core demonstrated ST6GAL1-negative epithelial cells. Extensive cell-cell communication and transcription factor networks were unraveled, potentially influencing vascular permeability and intracellular signaling. Clinically, high expression of ST6GAL1 in epithelial cells is associated with diminished progression-free survival, indicating its prognostic potential. In conclusion, ST6GAL1 is likely to significantly impact the progression and metastasis of ovarian cancer.

DSCT: A novel deep learning framework for rapid and accurate spatial transcriptomic cell typing

Abstract Unraveling the complex cell-type composition and gene expression patterns at the cellular spatial resolution is crucial for understanding intricate cell functions in the brain. In this study, we developed Deep Neural Network-based Spatial Cell Typing (DSCT), an innovative framework for spatial cell typing within spatial transcriptomic datasets. This approach utilizes a synergistic integration of an enhanced gene selection strategy and a lightweight deep neural network for data training, offering a more rapid and accurate solution for the analysis of spatial transcriptomic data. Based on comprehensive analysis, DSCT achieved exceptional accuracy in cell-type identification across various brain regions, species, and spatial transcriptomic platforms. It also performed well in mapping finer cell types, thereby showcasing its versatility and adaptability across diverse datasets. Strikingly, DSCT exhibited high efficiency and remarkable processing speed, with fewer computational resource demands. As such, this novel approach opens new avenues for exploring the spatial organization of cell types and gene expression patterns, advancing our understanding of biological functions and pathologies within the nervous system.

A quantitative prediction method utilizing whole omics data for biosensing

Omics data provide a plethora of quantifiable information that can potentially be used to identify biomarkers targeting the physiological processes and ecological phenomena of organisms. However, omics data have not been fully utilized because current prediction methods in biomarker construction are susceptible to data multidimensionality and noise. We developed OmicSense, a quantitative prediction method that uses a mixture of Gaussian distributions as the probability distribution, yielding the most likely objective variable predicted for each biomarker. Our benchmark test using a transcriptome dataset revealed that OmicSense achieves accurate and robust prediction against background noise without overfitting. Weighted gene co-expression network analysis revealed that OmicSense preferentially utilized hub nodes of the network, indicating the interpretability of the method. Application of OmicSense to single-cell transcriptome, metabolome, and microbiome datasets confirmed high prediction performance (r > 0.8), suggesting applicability to diverse scientific fields. Given the recent rapidly expanding availability of omics data, the developed prediction tool OmicSense, can accelerate the use of omics data as a “biosensor” based on an assemblage of potential biomarkers.

The Mining for Flowering-Related Genes Based on De Novo Transcriptome Sequencing in the Endangered Plant Phoebe chekiangensis

Phoebe chekiangensis is an indigenous, endangered, and valuable timber and garden tree species in China, which is notable for having a short juvenile phase (early flowering), unique among the Phoebe genus. However, the molecular mechanisms regulating the flowering of P. chekiangensis remain unexplored, primarily due to the lack of transcriptomic or genomic data. In the present study, transcriptome sequencing yielded 53 million RNA reads, resulting in 111,250 unigenes after de novo assembly. Of these, 47,525 unigenes (42.72%) were successfully annotated in the non-redundant (Nr) database. Furthermore, 15,605 unigenes were assigned to Clusters of Orthologous Groups (KOGs), and 36,370 unigenes were classified into Gene Ontology (GO) categories. A total of 16,135 unigenes were mapped to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, involving 298 pathways. Based on the expression levels, Gibberellin signaling pathway-related genes were the most predominant expression levels. Hormonal analysis showed that gibberellin (GA) levels varied across tissues and flowering stages, as GA20 levels in leaves were low during full bloom, while GA1 and GA5 levels peaked in flowers. Furthermore, several key genes involved in gibberellin biosynthesis, including CPS, GID1, GA20ox, GA3ox, and GA2ox, exhibited stage-specific expression patterns. Certain genes were highly expressed during the initial phases of flowering, while others, like GA3ox and GA2ox, reached peak expression at full bloom. These findings provide valuable insights into the molecular mechanisms underlying flowering in P. chekiangensis, laying the foundation for future breeding efforts. This transcriptome dataset will serve as an important public resource for molecular research on this species, facilitating the discovery of functional genes related to its growth, development, and flowering regulation.

P0172 In silico drug repurposing approach for the discovery of therapeutics for intestinal fibrosis in crohn’s disease

Abstract Background Intestinal fibrosis in Crohn’s disease (CD) can lead to stricture formation and other disease-related complications.1,2 Given the lack of anti-fibrotic drugs, current treatment strategies are limited to anti-inflammatory therapies, endoscopic balloon dilation and surgery.1 Our aim was to identify compounds and druggable targets that can reverse the gene expression signature in mucosal fibroblasts associated with intestinal fibrosis. Methods A signature associated with fibrotic CD was derived from three publicly available transcriptomic datasets of fibroblasts isolated from fibrostenotic strictures of CD patients. We conducted a meta-regression analysis across the transcriptomic datasets to identify significant differentially expressed genes (DEGs) associated with fibrostenotic CD. Three drug repurposing platforms (iLINCS, L1000 CDS2 and CLUE io), connected to the NIH LINCS database,3,4 were used to identify compounds that could reverse the fibrotic signature, ranked by their anti-fibrotic potential using the CoDReS (Composite Drug Reranking Scoring) tool. Transcription factors and miRNAs targeting the fibrostenotic signature were identified via the TRRUST and miRWalk databases. A gene interaction network was constructed, incorporating transcription factors (TRRUST TF), miRNAs and DEGs. Drugs targeting key network components were identified using the DGiDb database. Results Via the analysis of combined transcriptomic datasets from fibrostenotic- versus non-stenosis-associated mucosal fibroblasts, fibroblast activation protein (FAP), IL7 receptor and transcription factor AP-2 gamma, emerged as the most significantly upregulated genes in fibrostenotic CD (Figure 1). Out of 6,783 compounds, PI3K/Akt/mTOR inhibitors, Src kinase family inhibitors and histone deacetylase inhibitors were predicted as being most effective in reversing this pathologic gene signature. The gene interaction network revealed 15 hub genes as central components with the most interconnections (Table 1). Among these top 15 key gene regulators, IL6, PPARγ and angiotensin receptor type 1 (AGTR1) were the highest ranked druggable targets, based on the drug-gene interaction analysis. Conclusion Our in silico drug repurposing approach identified several potential anti-fibrotic compounds and druggable targets for the treatment of CD-associated intestinal fibrosis. These findings open novel avenues for the development of anti-fibrotic drugs and provide a foundation for future research on cell and pathway-specific mechanisms driving fibrosis in CD.

The endoplasmic reticulum degradation-enhancing α-mannosidase-like protein 3 attenuates the unfolded protein response and has pro-survival and pro-viral roles in hepatoma cells and hepatocellular carcinoma patients

BackgroundChronic hepatitis B virus (HBV) infection is a major risk for development of hepatocellular carcinoma (HCC), a frequent malignancy with a poor survival rate. HBV infection results in significant endoplasmic reticulum (ER) stress and activation of the unfolded protein response (UPR) signaling, a contributing factor to carcinogenesis. As part of the UPR, the ER-associated degradation (ERAD) pathway is responsible for removing the burden of misfolded secretory proteins, to re-establish cellular homeostasis. Emerging evidence indicates consistent upregulation of ERAD factors, including members of the ER degradation-enhancing alpha-mannosidase-like protein (EDEM) family in infection and various tumor types. However, the significance of this gene expression pattern in HBV-driven pathology is just beginning to be deciphered.MethodsIn this study we quantified the expression of the ERAD factor EDEM3, in a cohort of HCC patients with and without HBV infection, and validated our results by analysis of publically available transcriptomic and microarray data sets. We performed mechanistic studies in HepaRG cells with modulated EDEM3 expression to address UPR, ERAD, autophagy and apoptosis signaling, and their consequences on HBV infection.ResultsOur work revealed significantly elevated EDEM3 expression in HCC tissues irrespective of HBV infection, while the highest levels were observed in tissues from HBV-infected patients. Investigation of published transcriptomic data sets confirmed EDEM3 upregulation in independent HCC patient cohorts, associated with tumor progression, poor survival prognosis and resistance to therapy. EDEM3-overexpressing hepatic cells exhibited attenuated UPR and activated secretory autophagy, which promoted HBV production. Conversely, cell depletion of EDEM3 resulted in significant ER stress inducing pro-apoptotic mechanisms and cell death.ConclusionsWe provide evidence of major implications of the ERAD pathway in HBV infection and HCC development and progression. Our results suggest that ERAD activation in HBV-infected cells is a protective mechanism against prolonged ER stress, potentially contributing to establishment of chronic HBV infection and promoting tumorigenesis. Developing specific inhibitors for ERAD factors may be an attractive approach to improve efficiency of current antiviral and anticancer therapies.

P0096 Impaired fatty acid oxidation is a hallmark of Ulcerative Colitis: evidence from multi-cohort transcriptomics analysis

Abstract Background Ulcerative colitis (UC) is characterized by persistent colonic mucosal inflammation. Despite available treatments, most patients experience only temporary remission. The lack of universally effective treatments results from our incomplete understanding of UC pathophysiology. While many gene expression studies have provided valuable insights into UC mechanisms, the growing availability of transcriptomics datasets offers a unique opportunity for large-scale, cross-validating analyses. Here, we used multiple independent datasets to identify the most consistently dysregulated pathways in UC mucosal biopsies. Methods We performed an integrative analysis of 10 open transcriptomics datasets from human UC and healthy mucosal biopsies (n=710 samples after selection). Each dataset underwent a separate differential expression analysis followed by gene set enrichment. We used 6 different gene set databases to make the analysis as broad as possible (9962 pathways). The results were aggregated across all datasets to identify consistently altered genes and pathways. Since each dataset has a different number of samples and a different sample distribution between the groups, the aggregation was done purely on the ranking level. The complete workflow of the experiment is in Figure 1. Results Mitochondrial fatty acid oxidation emerged as the most significantly dysregulated pathway with a mean rank 4 (median 2.5) across 6 datasets. The analysis revealed a coordinated pattern of metabolic rewiring: systematic downregulation of the entire mitochondrial transport machinery (CPT1A, SLC25A20, CPT2) and the carnitine transporter SLC22A5, accompanied by decreased expression of β-oxidation enzymes (ACADS, ACADM, ACADVL, HADHA, HADHB, HADH, EHHADH) and consistent downregulation of the medium-chain fatty acid activating enzyme ACSF2. In contrast, ACSL4, which specifically activates polyunsaturated fatty acids, showed consistent upregulation. This metabolic disruption was coupled with coordinated changes in membrane remodeling enzymes, with upregulation of LPCAT1 and downregulation of LPCAT3, suggesting systematic alterations in membrane phospholipid composition. Conclusion Our multi-cohort analysis reveals a specific pattern of metabolic disruption in UC that extends beyond pathway inhibition. The coordinated upregulation of the ferroptosis mediator ACSL4 together with systematic changes in membrane remodeling enzymes suggests active metabolic rewiring that could promote ferroptotic cell death through altered membrane phospholipid composition and increased susceptibility to lipid peroxidation. These findings highlight potential new therapeutic targets in UC focused on specific aspects of lipid metabolism and ferroptosis regulation.

P0101 Phenotyping of human UC colonic tissue reveals inflammatory pathway gene expression in PD-1+ conventional and regulatory T cells which overlap with those regulated by rosnilimab in a mouse model of colitis

Abstract Background PD-1 co-inhibitory receptor agonists, such as rosnilimab, are a promising class of therapeutics that leverage immune homeostatic mechanisms to regulate T cell activity for treatment of inflammatory diseases, including ulcerative colitis (UC). In UC lamina propria, multiple T cell subtypes express PD-1, including peripheral helper T cells (Tph) and effector memory T cells, and the reduction of PD-1+ Tph cells is correlated with remission.1 Also, PD-1+ Tregs may comprise a subpopulation of pro-inflammatory Tregs in the UC colon. In a mouse model of colitis (induced by transfer of CD4+CD45Rb+ T cells from human PD-1 transgenic mice), rosnilimab treatment of established disease showed reduced body weight loss, reduced inflammation of the colon, and reduced infiltration of CD4 T cells.2 Methods A secondary analysis of active UC patient-derived colonic tissue characterized PD-1+ T cell subsets via a CD3-sorted single-cell proteomics and transcriptomics dataset.3 Pathway activity was estimated using Progeny.4 Bulk RNA-sequencing, gene expression analysis, and enrichment of human UC significant Reactome5 pathways was performed on colonic tissue from mice treated with rosnilimab in the colitis model. Results In human UC colonic tissue, PD-1+ CD4 conventional T (Tcon) cells and PD-1+ Tregs had increased JAK-STAT, TNF, and NF-κB estimated pathway activity compared to PD-1(-) cells. PD-1+ Tregs had increased expression of genes associated with a pro-inflammatory phenotype, including TNF, TBX21(TBET), and IL12RB2, and decreased expression of IL2RA (CD25). RNA-Seq of mouse colitis identified upregulated genes, compared to naive animals, in pathways that were also involved in human UC (“Signaling by interleukins” (e.g., Il6) and “Chemokine receptors bind chemokines” (e.g., Ccl20)). Expression levels of these genes in rosnilimab treated mice were similar to naive control animals. Additionally, the barrier gene Muc3 and fibrosis-associated Mmp9 were dysregulated in colitis but normal in rosnilimab-treated mice. Conclusion In UC colonic tissue, PD-1+ CD4 Tcon cells demonstrated increased inflammatory gene expression and PD-1+ Tregs exhibited a pro-inflammatory phenotype, suggesting that targeting both PD-1+ CD4 Tcon and PD-1+ Tregs may contribute to the therapeutic efficacy of rosnilimab in UC. These additional analyses support preclinical findings and suggest beneficial modulation of gene expression pathways of human UC, including reduction of pro-inflammatory cytokines and fibrosis, and upregulation of barrier function genes. These data demonstrate that PD-1 is upstream of multiple clinically validated drivers of UC and support the scientific rationale for studying rosnilimab in an ongoing Phase 2 study in UC (NCT06127043).

Mapping cells through time and space with moscot.

Single-cell genomic technologies enable the multimodal profiling of millions of cells across temporal and spatial dimensions. However, experimental limitations hinder the comprehensive measurement of cells under native temporal dynamics and in their native spatial tissue niche. Optimal transport has emerged as a powerful tool to address these constraints and has facilitated the recovery of the original cellular context1-4. Yet, most optimal transport applications are unable to incorporate multimodal information or scale to single-cell atlases. Here we introduce multi-omics single-cell optimal transport (moscot), a scalable framework for optimal transport in single-cell genomics that supports multimodality across all applications. We demonstrate the capability of moscot to efficiently reconstruct developmental trajectories of 1.7 million cells from mouse embryos across 20 time points. To illustrate the capability of moscot in space, we enrich spatial transcriptomic datasets by mapping multimodal information from single-cell profiles in a mouse liver sample and align multiple coronal sections of the mouse brain. We present moscot.spatiotemporal, an approach that leverages gene-expression data across both spatial and temporal dimensions to uncover the spatiotemporal dynamics of mouse embryogenesis. We also resolve endocrine-lineage relationships of delta and epsilon cells in a previously unpublished mouse, time-resolved pancreas development dataset using paired measurements of gene expression and chromatin accessibility. Our findings are confirmed through experimental validation of NEUROD2 as a regulator of epsilon progenitor cells in a model of human induced pluripotent stem cell islet cell differentiation. Moscot is available as open-source software, accompanied by extensive documentation.

Unveiling the signal valve specifically tuning the TGF-β1 suppression of osteogenesis: mediation through a SMAD1-SMAD2 complex

BackgroundTGF-β1 is the most abundant cytokine in bone, in which it serves as a vital factor to interdict adipogenesis and osteogenesis of bone marrow-derived mesenchymal stem cells (BM-MSCs). However, how TGF-β1 concurrently manipulates differentiation into these two distinct lineages remains elusive.MethodsTreatments with ligands or inhibitors followed by biochemical characterization, reporter assay, quantitative PCR and induced differentiation were applied to MSC line or primary BM-MSCs for signaling dissection. In vivo adipogenesis and ex vivo culture of bone explants were used to verify the functions of different SMAD complexes. Ingenuity Pathway Analysis, and analysis of transcriptomic datasets from human BM-MSCs in combination with hierarchical clustering and STRING assay were used to decipher the interplaying co-repressors. Mouse models of chronic and acute bone loss followed by biochemical assays and micro-computed tomography demonstrated the bone effects when functionally blocking the critical co-repressor HDAC1.ResultsDistinct from the TGF-β1 inhibition on adipogenesis through canonical SMAD2/3 signaling, we clarified that TGF-β1 suppresses osteogenesis by inducing the formation of previously unidentified mixed SMADs mainly composed of SMAD1 and SMAD2, in which SMAD2 recruits more TGF-β1-induced co-repressors including HDAC1, TGIF1 and ATF3, whereas SMAD1 allows directing the whole transcriptional suppression complex to the cis-elements of osteogenic genes. Depletion of the cross-activation to the mixed SMADs dismantled specifically the TGF-β1 suppression on osteogenesis without affecting its inhibition on adipogenesis. Such phenomena can be reproduced via knockdown of co-repressors such as Hdac1 or addition of HDAC1 inhibitors in TGF-β1-treated MSCs. In either the chronic or the acute bone loss model, we demonstrated that the TGF-β signaling was augmented in the bone niche during osteolysis, whereas administration of HDAC1 inhibitors significantly improved bone quality.ConclusionThis study identifies a new signal valve through which TGF-β1 can inhibit osteogenesis specifically. Functional interruption of this valve can tilt the seesaw balance of BM-MSC differentiation towards osteogenesis, highlighting the interplaying co-repressors, such as HDAC1, as promising therapeutic targets to combat diverse degenerative orthopedic diseases.

Age-associated microglial transcriptome leads to diminished immunogenicity and dysregulation of MCT4 and P2RY12/P2RY13 related functions

The aging process is marked by a time-dependent deterioration in cellular functions, particularly the immune and neural systems. Understanding the phenotype acquisition of microglia, the sentinel immune cells of the brain, is crucial for understanding the nature of age-related neurological diseases. However, the specific phenotype adopted by microglia during aging remains a subject of debate and is contingent on the chosen experimental model. To address these unresolved questions, we employed a novel and highly controlled approach utilizing long-term cultivated BV-2 microglia, exempted from additional external stimuli. Our findings revealed that aged microglial cells, in comparison to their younger counterparts, acquire a distinct gene expression profile, primarily characterized by alterations in microglial immune response. Indeed, pro-inflammatory stimulated aged and young BV-2 microglia exhibited similar transcriptomic profiles, yet the response intensity to the stimulus was markedly muted in the aged microglia. Functional neurotoxic assays confirmed diminished neuronal death in coculture with aged, activated microglia, underscoring a compromised immune response. Furthermore, a subsequent comparative analysis of aged BV-2 microglia with established transcriptomic microglial datasets from aged mice and humans identified 13 overlapping genes, laying the foundation for identifying core microglial aging signature. Particularly noteworthy were SLC16A3 and P2RY13, which consistently exhibited upregulation and downregulation, respectively, across all datasets. Additionally, four other genes—CAPG, LGALS3BP, NRIP1, and P2RY12—were found to share regulatory patterns in response to both aging and extrinsic activation. An in-depth investigation focused on SLC16A3, encoding the high-affinity lactate transporter MCT4, revealed disruptions in extracellular acidification rate and lactate concentration with age. Microglial purine sensing and motility capacities, regulated by P2RY12/P2RY13, displayed age-related alterations. Remarkably, protein analysis in human brain tissue validated the observed upregulation of MCT4 and downregulation of P2RY12 in aged microglia. In conclusion, our study unveils a distinct phenotype in aged microglia characterized by compromised immune responsiveness. Through the integration of in vitro cultured BV-2 microglia with primary microglia datasets, we identify critical molecular determinants of microglial cellular aging confirmed in human-aged brain tissue. This comprehensive approach offers potential insights for understanding and potentially reprogramming aged microglia, with implications for combating age-related neurological disorders.

Identification of cis-sQTL demonstrates genetic associations and functional implications of inflammatory processes in Nelore cattle muscle tissue.

This study aimed to identify splicing quantitative trait loci (cis-sQTL) in Nelore cattle muscle tissue and explore the involvement of spliced genes (sGenes) in immune system-related biological processes. Genotypic data from 80 intact male Nelore cattle were obtained using SNP-Chip technology, while RNA-Seq analysis was performed to measure gene expression levels, enabling the integration of genomic and transcriptomic datasets. The normalized expression levels of spliced transcripts were associated with single nucleotide polymorphisms (SNPs) through an analysis of variance using an additive linear model with the MatrixEQTL package. A permutation analysis then assessed the significance of the best SNPs for each spliced transcript. Functional enrichment analysis was performed on the sGenes to investigate their roles in the immune system. In total, 3,187 variants were linked to 3,202 spliced transcripts, with 83 sGenes involved in immune system processes. Of these, 31 sGenes were enriched for five transcription factors. Most cis-sQTL effects were found in intronic regions, with 27 sQTL variants associated with disease susceptibility and resistance in cattle. Key sGenes identified, such as GSDMA, NLRP6, CASP6, GZMA, CASP4, CASP1, TREM2, NLRP1, and NAIP, were related to inflammasome formation and pyroptosis. Additionally, genes like PIDD1, OPTN, NFKBIB, STAT1, TNIP3, and TREM2 were involved in regulating the NF-kB pathway. These findings lay the groundwork for breeding disease-resistant cattle and enhance our understanding of genetic mechanisms in immune responses.