SEARCH · Search PubMed

Results for “single cell sequencing”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12Linked to original sources

PubMed2025

Spatial transcriptomics-aided localization for single-cell transcriptomics with STALocator.

Single-cell RNA-sequencing (scRNA-seq) techniques can measure gene expression at single-cell resolution but lack spatial information. Spatial transcriptomics (ST) techniques simultaneously provide gene expression data and spatial information. However, the data quality of the spatial resolution or gene coverage is still much lower than the quality of the single-cell transcriptomics data. To this end, we develop a ST-Aided Locator for single-cell transcriptomics (STALocator) to localize single cells to corresponding ST data. Applications on simulated data showed that STALocator performed better than other localization methods. When applied to the human brain and squamous cell carcinoma data, STALocator could robustly reconstruct the relative spatial organization of critical cell populations. Moreover, STALocator could enhance gene expression patterns for Slide-seqV2 data and predict genome-wide gene expression data for fluorescence in situ hybridization (FISH) and Xenium data, leading to the identification of more spatially variable genes and more biologically relevant Gene Ontology (GO) terms compared with the raw data. A record of this paper's transparent peer review process is included in the supplemental information.

Single-Cell Analysis↗

PubMed2025

ChemPerturb-seq screen identifies a small molecule cocktail enhancing human beta cell survival after subcutaneous transplantation.

Traditional chemical screens have focused on a single assay per screen, making them labor intensive and costly. Here, we combined a chemical screen with single-cell RNA sequencing (scRNA-seq) to perform Chemical Perturb-seq (ChemPerturb-seq), enabling a systematic analysis of the molecular changes of human beta cells upon individual small molecule treatments. Using this platform, we performed an in vivo barcoded screen and discovered a small molecule cocktail, including beta-lipotropin 61-91, insulin growth factor-1, and prostaglandin E2, with which preconditioning human beta cells and primary islets significantly enhanced function and survival when transplanted subcutaneously to female, but not to male, mice. We identified two additional molecules, serotonin and histamine, that promote islet function when transplanted subcutaneously to male mice using ChemPerturb-seq. Such small molecule cocktails could be applied to improve the current FDA-approved islet transplantation procedure. Finally, we developed an artificial intelligence (AI)-powered website, ChemPerturbDB, which provides user-friendly open access analysis of the extensive ChemPerturb-seq dataset.

Humans↗

PubMed1999

In situ sequencing of peptides from biological tissues and single cells using MALDI-PSD/CID analysis.

The ability to directly sequence peptides from biological cells using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with postsource decay (PSD) and collision-induced dissociation (CID) fragment ion mass analysis is explored. Three different sample preparation methods are described for sequencing peptides in tissue samples and in single neurons from the invertebrate model Aplysia californica. To characterize peptides from the atrial gland, MALDI-PSD/CID is applied directly to a tissue blot covered with the matrix alpha-cyano-4-hydroxycinnamic acid (CHCA). The resulting fragment ions combined with database searching confirm the structure of several novel peptides encoded by egg-laying hormone genes. Moreover, MS profiling of a single unidentified neuron detects peptides with molecular weights of myomodulins C and E; this assignment is confirmed using MALDI-PSD with the matrix 2,5-dihydroxybenzoic acid (DHB). DHB does not always provide adequate fragmentation for PSD experiments; therefore, a unique dual-matrix sampling method, employing both DHB and CHCA, is developed to directly sequence a decapeptide from a single cerebral ganglion B cell. Mass accuracy of fragment ions from cellular samples is typical for the instrument employed and is not deleteriously affected by the morphology and complexity of the samples.

Amino Acid Sequence↗

PubMed2025

LKB1 inactivation promotes epigenetic remodeling-induced lineage plasticity and antiandrogen resistance in prostate cancer.

Epigenetic regulation profoundly influences the fate of cancer cells and their capacity to switch between lineages by modulating essential gene expression, thereby shaping tumor heterogeneity and therapy response. In castration-resistant prostate cancer (CRPC), the intricacies behind androgen receptor (AR)-independent lineage plasticity remain unclear, leading to a scarcity of effective clinical treatments. Utilizing single-cell RNA sequencing on both human and mouse prostate cancer samples, combined with whole-genome bisulfite sequencing and multiple genetically engineered mouse models, we investigated the molecular mechanism of AR-independent lineage plasticity and uncovered a potential therapeutic strategy. Single-cell transcriptomic profiling of human prostate cancers, both pre- and post-androgen deprivation therapy, revealed an association between liver kinase B1 (LKB1) pathway inactivation and AR independence. LKB1 inactivation led to AR-independent lineage plasticity and global DNA hypomethylation during prostate cancer progression. Importantly, the pharmacological inhibition of TET enzymes and supplementation with S-adenosyl methionine were found to effectively suppress AR-independent prostate cancer growth. These insights shed light on the mechanism driving AR-independent lineage plasticity and propose a potential therapeutic strategy by targeting DNA hypomethylation in AR-independent CRPC.

Male↗

PubMed2026

Identification and evaluation of glutamine-related gene characteristics based on multi-omics to predict the prognosis of patients with colorectal cancer.

BACKGROUND: Colorectal cancer (CRC), a prevalent malignancy of the gastrointestinal tract, ranks among the leading causes of cancer-related morbidity and mortality. Its clinical course is marked by high fatality and poor prognosis. Elucidating the mechanisms underlying CRC initiation and recurrence is therefore critical for identifying novel therapeutic targets. METHODS: This study incorporated two datasets, TCGA-CRC and GSE17537. A total of 84 glutamine metabolism-related genes (GMRGs) were identified, and differential expression analysis was conducted using the TCGA-CRC dataset. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to determine gene modules most strongly associated with GMRG scores. Single-cell RNA sequencing (scRNA-seq) was utilized to characterize key cellular clusters and to identify differentially expressed genes (DEGs) between high and low glutamine metabolism (GM) groups. Overlapping GMRGs were visualized using the ggVennDiagram package in R. A CRC risk prediction model was developed through Cox proportional hazards and LASSO regression analyses, with performance evaluated by ROC curves. Cell type enrichment across 64 immune and stromal populations was assessed via xCell, and intergroup differences were tested using the Wilcoxon rank-sum test. TIDE scores were used to estimate immunotherapy responsiveness, while oncoPredict facilitated drug sensitivity profiling. PCOLCE2 expression in CRC was validated by RT-qPCR and Western blotting. Its functional role was examined through CCK-8 assays, invasion and migration tests, flow cytometry, and glutamate quantification. RESULTS: ScRNA-seq analysis identified two key cell populations and 437 DEGs associated with GM status. WGCNA pinpointed the MEgreen module as most significantly correlated with GMRG scores, encompassing 1075 genes. Integration of DEGs, module genes, and GM-related DEGs yielded 60 candidate genes for downstream analysis. A GMRG-based prognostic model comprising six genes (SRPX, CXCL1, GPX3, PCOLCE2, CLU, SEMA3E) demonstrated strong predictive performance. Prognostic gene expression correlated with immune and stromal infiltration patterns, as indicated by Spearman correlation analysis. The high-risk group exhibited diminished predicted response to immunotherapy (TIDE scores). Drug sensitivity analysis identified four compounds—Dasatinib-51, WH-4-023-56, TWS-119-366, and LDN-193189-478—with elevated efficacy in high-risk CRC cases. PCOLCE2 expression was significantly reduced in CRC tissues. Functional assays revealed that PCOLCE2 knockdown did not substantially affect cell proliferation but significantly impaired invasion and migration in CRC cells, increased apoptosis, and suppressed both glutamine uptake and glutamate production—highlighting its oncogenic role. CONCLUSION: Six GMRGs—SRPX, CXCL1, GPX3, PCOLCE2, CLU, and SEMA3E—were identified as key components of a robust prognostic model for CRC. These findings offer valuable insights into CRC pathogenesis and potential therapeutic strategies. Notably, this study provides the first evidence implicating PCOLCE2 as a tumor-promoting factor in CRC.

Glutamine↗

PubMed2025

A Multi-omics Exploration Revealing SLIT2 as a Prime Therapeutic Target for Peripheral Facial Paralysis: Integrating Single-Cell Transcriptomics and Plasma Proteome Data.

Peripheral facial paralysis (PFP) is a common neurological disorder characterized by facial-nerve dysfunction. Identifying therapeutic targets and understanding the molecular and cellular mechanisms underlying PFP are crucial for developing effective treatment strategies. This study combined Mendelian randomization (MR) analysis and single-cell RNA sequencing (scRNA-seq) to explore potential therapeutic candidates and their roles in PFP pathophysiology. The MR analysis included 1925 publicly available plasma protein cis-heritability instruments. Instrumental variables were selected for MR analysis to identify plasma proteins associated with PFP, followed by colocalization analysis to evaluate shared genetic variants between the identified proteins and PFP. After the initial identification of plasma proteins associated with Bell's palsy using MR analysis, a rat model of facial-nerve injury was established to further dissect underlying mechanisms at cellular and molecular levels. Using scRNA-seq technology, we delved deeply into cellular Heterogeneity and dynamic changes in gene expression in the facial-nerve nucleus tissues under both injured and control conditions, thereby achieving a systematic study ranging from macroscopic genetic associations to microscopic cellular functions. Finally, expression patterns were preliminarily validated by performing in vitro immunofluorescence analysis on the facial-nerve nucleus samples of SD rats. The MR analysis results identified 30 plasma proteins significantly associated with PFP, with nine target genes showing differential expression in the scRNA-seq data. Colocalization analysis demonstrated that slit guidance Ligand 2 (SLIT2), semaphorin 4D (SEMA4D), EGF containing fibulin extracellular matrix protein 1 (EFEMP1), and sprouty related EVH1 domain containing 2 (SPRED2) shared causal variants with PFP. SLIT2 was highly expressed in the microglia and inhibitory neurons in the experimental group, whereas SEMA4D showed elevated expression across multiple glial cell types in the same group. In contrast, EFEMP1 and SPRED2 showed distinct expression patterns in fibroblasts and oligodendrocytes. The role of SLIT2 has been previously well-documented in many central nervous system diseases. However, for the first time, this study detected SLIT2 alteration after facial-nerve injury. Altered intercellular signaling, particularly enhanced SLIT2-ROBO signaling between neurons and glial cells, was observed in the PFP group. Pseudotime analysis revealed dynamic SLIT2 expression during microglia and inhibitory neuron differentiation, mirroring changes in ROBO1 expression. Immunofluorescence analysis of rat facial-nerve nucleus samples verified that SLIT2 protein levels were significantly increased in the facial-nerve nuclei of injured samples. In conclusion, despite the fact that this study is primarily founded on animal models and despite notable differences existing between animals and humans in terms of the facial motor nucleus, this study successfully identified SLIT2 as potential therapeutic targets for PFP. The SLIT2-ROBO axis stands out as a particularly promising candidate. SLIT2 may play a role in modulating neuroimmune interactions and promoting nerve repair. These findings provide a foundation for future clinical studies and targeted interventions to enhance recovery from PFP. Future research should focus on human sample validation to enhance clinical translation.

Animals↗

PubMed2026

Perturbation of genes linked to common schizophrenia risk variants identifies cilia programs.

Schizophrenia (SCZ) is a common psychiatric disorder characterized by psychosis, emotional withdrawal, and cognitive deficits. Most SCZ risk variants reside in non-coding regions of the genome and are thought to influence disease risk by modulating gene regulation. However, the target genes, biological pathways, and cell types through which these variants exert their effects remain poorly understood. To address this gap, we employed in vivo CRISPR droplet sequencing (CROP-seq) in the postnatal mouse neocortex. We perturbed 12 SCZ risk genes previously linked to functionally validated risk variants, followed by single-cell RNA sequencing. We identified 3,031 differentially expressed genes (DEGs) that recapitulate transcriptional alterations observed in postmortem SCZ brains. Integrative analysis using DEG clustering, factor analysis, and gene regulatory network inference uncovered convergent gene programs with distinct biological functions and cell type specificity. Notably, ciliary transcriptional programs consistently emerged across analytical frameworks. The primary cilium is a neurocircuit modulating signaling organelle in neurons and glia that remains understudied in SCZ. Perturbation of key contributors to the ciliary transcriptional programs led to significant alterations in ciliary structure, suggesting that SCZ genetic risk factors may influence how brain cells sense and transduce extracellular signals through synapse-independent mechanisms. Together, this study provides the first in vivo characterization of the functional consequence of common variant architecture in SCZ and implicates ciliary dysfunction as a convergent downstream mechanism.

Journal Article↗

PubMed2026

Uncovering heterogeneous effects via localized feature selection.

Identifying features that interact to trigger disease, while accounting for heterogeneity across diverse populations, is essential for the development of precision and targeted medicine. Despite the availability of vast and complex health-related datasets, most existing works focus on identifying disease-associated features at the population level or within a few subpopulations, often overlooking individual-level heterogeneity within these groups. To address this limitation, we propose a framework that utilizes localized test statistics to identify disease-associated features tailored to individual profiles. Our method leverages the recently developed knockoffs methodology to control the noise level of the selection set so that the results are replicable. Moreover, it allows for the discovery of hidden heterogeneous effects within the data, as demonstrated in an application to single-cell RNA sequencing data for Alzheimer's disease. By aggregating localized feature selection results, our framework also enables powerful population-level feature selection. Our framework provides a powerful tool for exploratory studies of precision medicine, offering the potential to generate novel hypotheses for confirmatory biological experiments.

Alzheimer Disease↗

PubMed2026

Multiomics approaches reveal direct NF-κB p65 target genes in pancreatic islets during cytokine exposure and in type 1 diabetes.

Autoimmune diseases, including Type 1 diabetes (T1D), are often characterized by overactive inflammatory signaling pathways. The proinflammatory cytokine interleukin-1β (IL-1β) elicits global gene expression changes in islet β-cells which overlap with islets obtained from human donors with T1D. The direct transcriptional link between NF-κB subunit p65 and target genes involved with autoimmune events was investigated. We used a multiomics approach including bulk RNA-sequencing (RNA-Seq), single-cell RNA-sequencing (scRNA-Seq), and chromatin immunoprecipitation coupled to deep sequencing (ChIP-Seq), alongside molecular docking simulations, and transcriptional assays. Through the various experimental modalities, we identified early response genes driven by IL-1β that were differentially expressed in pancreatic islets from human T1D donors and also conserved across mouse, rat, and human tissues. ChIP-Seq revealed genes that are direct genomic targets of the NF-κB p65 transcription factor. Moreover, regions that gained RNA polymerase II binding following cellular exposure to IL-1β were identified, complementing the early response gene profile induced by β-cell exposure to IL-1β. Molecular docking simulations predicted that mutations reducing p65 transcriptional capacity do not alter DNA binding ability. These findings clearly show that IL-1β signaling in pancreatic β-cells directs p65 to specific genomic regions congruent with increased gene expression relevant to T1D in β-cell lines as well as mouse and human islets exposed to cytokines. Islets from human donors with T1D express genes identified as direct p65 targets using unbiased approaches, implicating heightened NF-κB activity as a critical component of autoimmune disease etiology.NEW & NOTEWORTHY Using multiple Seq-based approaches, this study identified genes expressed in human pancreatic tissue from donors with Type 1 diabetes that are regulated acutely by exposure to the cytokine interleukin-1beta. The NF-kB transcription factor p65 (RelA) was determined via ChIP-Seq to be a major control node regulating this immediate early response. These collective datasets are consistent with a paradigm of overactive NF-kB signaling as a critical component of autoimmunity in both rodents and humans.

Humans↗

PubMed2026

Protocol to identify genes required for cardiomyocyte development using Perturb-Seq.

While Perturb-Seq combines CRISPR-based screening with single-cell RNA sequencing (scRNA-seq), large-scale experiments are costly and its application during development is complicated by differentiation heterogeneity. Here, we present a protocol to identify genes required for cardiomyocyte development using Perturb-Seq. We describe steps for sgRNA (single guide RNA) library cloning and infection, cardiomyocyte differentiation, cell hashing, super loading, and scRNA-seq. We then detail procedures for sequencing, mapping, and data analysis. For complete details on the use and execution of this protocol, please refer to Sivakumar et al.1.

CRISPR↗

PubMed2002

Epstein-Barr virus-positive Hodgkin/Reed-Sternberg-like B cell in non-hodgkin lymphoma: nucleotide sequence of the amplified immunoglobulin heavy-chain variable region gene by the single-cell polymerase chain reaction technique.

We examined nucleotide sequences of Epstein-Barr virus (EBV)-positive Hodgkin/Reed-Sternberg (HRS)-like B cells in a case of diffuse large B-cell lymphoma (DLBCL) and a case of adult T-cell lymphoma (ATL) for single-cell polymerase chain reaction of the immunoglobulin heavy-chain gene variable region (VH gene). HRS-like B cells were scattered in the area irrelevant to the lymphoma infiltrates of DLBCL and in the lymphoma area of ATL. HRS-like B cells were positive for CD20 and CD30 but negative for CD15. EBV presented in HRS-like B cells in both cases but not in any lymphoma cells. VH genes of five HRS-like B cells analyzed in DLBCL were polyclonal and showed in-frame sequences with 0% to 2.8% somatic mutation frequency. In an ATL, VH genes of five HRS-like B cells analyzed were polyclonal and somatically mutated. Four cells carried in-frame rearrangements with 3.5% to 17.7% mutation frequency. One of the VH genes has a one-codon deletion. From the fifth cell, an out-of-frame rearrangement with an insertion and a deletion was obtained. Thus, we showed polyclonal EBV-positive HRS-like B cells in both DLBCL and ATL and that whereas EBV-positive, HRS-like B cells in DLBCL exhibited unmutated and mutated VH gene, those in ATL were found to have a somatically mutated VH gene with/without deletions and/or insertions. The HRS-like B cells may appear because of active EBV infection in a patient who is immunosuppressed from the primary lymphoma.

Adult↗

PubMed1990

An ancient, highly conserved family of cysteine-rich protein domains revealed by cloning type I and type II murine macrophage scavenger receptors.

Scavenger receptors have been implicated in the development of atherosclerosis and other macrophage-associated functions. The bovine type I and type II scavenger receptors are multidomain transmembrane proteins that differ only by the presence in the type I receptor of an additional, extracellular cysteine-rich C-terminal domain. The isolation of type I and type II receptor cDNAs from a murine macrophage cell line, P388D1, establishes the presence of mRNAs encoding both receptor types in a single cell. Their sequences are highly similar to the bovine cDNAs. Receptor type-specific cDNA probes map to a common locus on murine chromosomes 8, suggesting that a single gene encodes both mRNAs. The type I-specific scavenger receptor cysteine-rich (SRCR) domain helps define a previously unrecognized family of remarkably well-conserved domains. Highly homologous SRCR domains (one, three, or four per polypeptide chain) are found in diverse secreted and cell-surface proteins from humans (e.g., CD5, complement factor I), mice (Ly-1), and sea urchins (speract receptor).

Amino Acid Sequence↗

PubMed2023

Dandelion uses the single-cell adaptive immune receptor repertoire to explore lymphocyte developmental origins.

Assessment of single-cell gene expression (single-cell RNA sequencing) and adaptive immune receptor (AIR) sequencing (scVDJ-seq) has been invaluable in studying lymphocyte biology. Here we introduce Dandelion, a computational pipeline for scVDJ-seq analysis. It enables the application of standard V(D)J analysis workflows to single-cell datasets, delivering improved V(D)J contig annotation and the identification of nonproductive and partially spliced contigs. We devised a strategy to create an AIR feature space that can be used for both differential V(D)J usage analysis and pseudotime trajectory inference. The application of Dandelion improved the alignment of human thymic development trajectories of double-positive T cells to mature single-positive CD4/CD8 T cells, generating predictions of factors regulating lineage commitment. Dandelion analysis of other cell compartments provided insights into the origins of human B1 cells and ILC/NK cell development, illustrating the power of our approach. Dandelion is available at https://www.github.com/zktuong/dandelion .

Humans↗

PubMed2026

Amaranth: enhanced single-cell transcript assembly via discriminative modelling of UMI reads and internal reads.

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) has transformed transcriptome profiling at cellular resolution, yet accurate reconstruction of full-length transcripts for individual cells remains a central challenge. Emerging scRNA-seq protocols can produce reads that span entire transcripts, enabling isoform-level expression analysis. For example, Smart-seq protocols combine unique molecular identifier (UMI)-linked reads that index and stitch together multiple reads from the same molecule, with internal reads filling coverage gaps. We demonstrate that these read types exhibit markedly different biological and statistical properties in strandness, 5'/3' coverage bias, and genomic locality. Existing assemblers fail to leverage these distinctions, yielding suboptimal assembly. RESULTS: We developed Amaranth, a novel single-cell assembler that discriminatively models UMI and internal reads. Amaranth implements heuristics specifically designed to address the distinct biases of UMI-linked and internal reads, enabling accurate strandness assignment for internal reads, reliable splicing graph refinement, and precise transcript start site determination. We also developed Amaranth-meta, which integrates information across cells to enhance individual cell assemblies. Benchmarked on Smart-seq3 datasets from human HEK293T and mouse fibroblast cells, Amaranth outperformed other state-of-the-art assemblers in assembling individual cells and in meta-assembly. Amaranth advances isoform-level analysis in single-cell transcriptomics, facilitating detailed studies at cellular resolution. AVAILABILITY AND IMPLEMENTATION: Amaranth is implemented in C++ and is freely available at https://github.com/Shao-Group/amaranth under the BSD-3-Clause license. Scripts, documentation, and data for reproducing experiments in this manuscript are available at https://github.com/Shao-Group/amaranth-test.

Single-Cell Gene Expression Analysis↗

PubMed2026

REG3α is a Predictive Biomarker of Complicated Disease from Preclinical through Established Crohn's Disease.

BACKGROUND: Regenerating islet-derived 3-alpha (REG3α) is a serum biomarker in patients with graft-versus-host disease (GVHD) linked to 6-month mortality. REG3α is produced by intestinal Paneth cells, which are implicated in Crohn's disease (CD) pathophysiology. OBJECTIVE: To assess associations between serum REG3α and progressive CD DESIGN: Serum REG3α was measured in two cross-sectional (M: Mount Sinai, L: Leuven) and a pre-diagnostic cohort (P: PREDICTS) with serial samples up to 10 years before CD diagnosis. Tissue REG3α expression was assessed via bulk RNA sequencing from paired ileal and colonic biopsies. Serum REG3α and tissue REG3α were associated with CD progression (hospitalization, surgery, steroid course, or new advanced therapy). Single-cell RNA sequencing data explored associations between REG3α expression, Paneth cell phenotypes, and CD. RESULTS: In 394 patients, high serum REG3α associated with CD progression, independent of C-reactive protein and endoscopic activity (M: HR 1.9 (95%CI 1.3-2.8); L: HR 2.9 (95%CI 1.9-4.6), both p<0.001). The association persisted in patients with mild or inactive CD. In the pre-diagnostic cohort, high serum REG3α predicted the development of CD, particularly complicated (B2/3) and surgical presentations, up to 10 years before diagnosis (P). Analysis of REG3α expression and Paneth cell transcriptomes suggested that CD is associated with loss of regenerative Paneth cell populations and enrichment in REG3α-expressing populations, suggesting a mechanism through which changes in serum REG3α associate with complicated CD. CONCLUSION: Serum REG3α holds potential as a non-invasive, prognostic biomarker in CD, independent of disease activity. High serum REG3α, even years before diagnosis, is linked to a complicated disease course.

Crohn’s Disease↗

PubMed2003

Experimental immunity to the G1 domain of the proteoglycan versican induces spondylitis and sacroiliitis, of a kind seen in human spondylarthropathies.

OBJECTIVE: Experimental immunity to the G1 domain of the cartilage proteoglycan (PG) aggrecan (AG1) leads to the development of spondylitis as well as polyarthritis in BALB/c mice. The PG versican contains a structurally similar G1 domain (VG1). This study was conducted to determine whether immunity to VG1 would elicit similar pathology in these mice. METHODS: Recombinant natively folded VG1 and AG1 were prepared. BALB/c mice received either a series of 5 injections of human VG1 or AG1, or no protein. Polyarthritis was determined clinically, and spondylitis and sacroiliitis histologically. Immunohistochemistry of rat tissues was used to study the localization of versican. Enzyme-linked immunosorbent assays were employed to study humoral immunity to the recombinant proteins as well as to overlapping synthetic peptides covering all these human G1 domains and mouse homologs. Affinity-purified antibodies to human AG1 and VG1 were isolated from sera of hyperimmunized mice. T lymphocyte proliferation assays were performed using recombinant human proteins. T cell lines reactive with specific immunodominant T cell epitopes in human AG1 and VG1 were isolated. Synthetic peptides encoding sequences in these human proteins and in corresponding mouse proteins were used in these analyses. Guanidinium chloride extracts of mouse spines were also used in Western blots to study antibody cross-reactivity. RESULTS: Immunity to recombinant VG1 did not result in clinical polyarthritis. There was, however, clear evidence that VG1, like AG1, could induce spondylitis in the lumbar spine and sacroiliitis. Accumulation of mononuclear cells was observed in spinal ligaments adjacent to the intervertebral disc, in the intervertebral disc, and in the sacroiliac joints, the same sites where versican is localized. In contrast to AG1-immunized mice, in which T cells reactive with human AG1 cross-reacted with mouse AG1, there was no evidence in VG1-immunized mice that T cell immunity to human VG1 was cross-reactive with a mouse synthetic peptide that contained the sequence corresponding to the single immunodominant T cell sequence recognized in human VG1. Antibodies to specific sequences in human VG1 did, however, cross-react with human AG1 and with corresponding peptide sequences in mouse versican and aggrecan and with mouse proteins containing VG1 and AG1, present in mouse spine extracts. Similarly, antibodies to human AG1 cross-reacted with human VG1 and with extracted mouse VG1 and AG1 and synthetic peptides containing mouse sequences that corresponded to the reactive human epitopes in AG1 and VG1. CONCLUSION: These observations suggest that humoral immunity to human VG1 is involved in the induction of experimental spondylitis and sacroiliitis in BALB/c mice. This humoral immunity is cross-reactive with mouse versican and aggrecan but is not associated with polyarthritis, probably because of the lack of cross-reactive T cell immunity and the absence of detectable versican in articular cartilage limbs. Induction of polyarthritis by bovine or human aggrecan requires the involvement of immunity mediated by T lymphocytes that are cross-reactive to a mouse aggrecan epitope. Together these observations suggest that humoral immunity to versican as well as immunity to aggrecan may be of importance in the development of the spinal pathology characteristic of spondylarthropathies.

ADAM Proteins↗

PubMed2026

The pseudouridine epitranscriptomic landscape of advanced prostate cancer therapeutic resistance identifies TIMM17A as a key player.

BACKGROUND: Resistance to androgen receptor signaling inhibitors (ARSIs) remains a major barrier of advanced prostate cancer (PCa) treatment. While RNA epitranscriptomic modifications are increasingly recognized as key regulators of tumor biology, the role of pseudouridine (Ψ) in therapeutic resistance is largely unexplored. METHODS: A darolutamide-resistant PCa cell model was established and subjected to integrated multi-omics profiling using bulk RNA sequencing and photo-crosslinking-assisted Ψ sequencing (PA-Ψ-seq). Differential expression and pseudouridylation analyses were combined to identify Ψ-associated genes. Public datasets validated expression and prognosis. Functional assays including RNA knockdown, cell proliferation, colony formation, and xenograft models were conducted. Single-cell RNA sequencing investigated tumor microenvironment (TME) interactions. RESULTS: We identified extensive transcriptomic and pseudouridylation alterations associated with ARSI resistance, with a significant positive correlation between Ψ modification and mRNA expression. Integrated analysis highlighted a subset of "hyper-up" genes enriched in resistance-related pathways. Thus, TIMM17A was identified as a novel candidate. TIMM17A expression was significantly elevated in PCa and correlated with disease progression and poor prognosis. Experimental validations demonstrated that TIMM17A promoted tumor growth and resistance, while its knockdown restored sensitivity to darolutamide both in vitro and in vivo. Mechanistically, TIMM17A expression may be regulated by PUS1‑mediated pseudouridylation. Single-cell analysis further revealed that TIMM17A is enriched in malignant epithelial cells and associated with enhanced cell-cell communication within the TME. CONCLUSIONS: This study delineates the pseudouridine epitranscriptomic landscape in advanced PCa and identifies TIMM17A as a key mediator of therapeutic resistance. Targeting the Ψ-TIMM17A axis may offer a novel strategy to overcome ARSI resistance.

Advanced prostate cancer↗

PubMed2026

ELISA (Embedding-Linked Interactive Single-cell Agent): an interpretable hybrid generative Artificial Intelligence agent for expression-grounded discovery in single-cell genomics.

Translating single-cell RNA sequencing (scRNA-seq) data into mechanistic biological hypotheses remains a critical bottleneck, as agentic AI systems lack direct access to transcriptomic representations while expression foundation models remain opaque to natural language. Here, we introduce ELISA (Embedding-Linked Interactive Single-cell Agent), an interpretable framework that unifies single-cell generative pretrained transformer expression embeddings with biomedical bidirectional encoder representations from transformers-based semantic retrieval and large-language model (LLM)-mediated interpretation for interactive single-cell discovery. An automatic query classifier routes inputs to gene marker scoring, semantic matching, or reciprocal rank fusion pipelines depending on whether the query is a gene signature, natural language concept, or mixture of both. Integrated analytical modules perform pathway activity scoring across 60+ gene sets, ligand-receptor interaction prediction using 280+ curated pairs, condition-aware comparative analysis, and cell-type proportion estimation, all operating directly on embedded data without access to the original count matrix. Benchmarked across six diverse scRNA-seq datasets spanning inflammatory lung disease, pediatric and adult cancers, organoid models, healthy tissue, and neurodevelopment, ELISA significantly outperforms CellWhisperer, a classical lexical retriever (BM25), and a random baseline in cell type retrieval (combined permutation test, $p < 2\times 10^{-5}$ for each), with particularly large gains on gene-signature queries (Cohen's $d = 5.98$ for mean reciprocal rank). ELISA replicates published biological findings (mean composite score 0.88), and generates candidate hypotheses through grounded LLM reasoning, bridging the gap between transcriptomic data exploration and biological discovery.

Generative Artificial Intelligence↗