GSEApy: a comprehensive package for performing gene set enrichment analysis in Python

Lineage Tracing Reveals Clone-Specific Responses to Doxorubicin in Triple-Negative Breast Cancer

Triple-negative breast cancer, characterized by aggressive growth and high intratumor heterogeneity, presents a significant clinical challenge. Here, we use a lineage-tracing system, ClonMapper, which couples heritable clonal identifying tags with single-cell RNA-sequencing (scRNA-seq), to better elucidate the response to doxorubicin in a model of TNBC. We demonstrate that, while there is a dose-dependent reduction in overall clonal diversity, there is no pre-existing resistance signature among surviving clones. Separately, we found the existence of two transcriptomically distinct clonal subpopulations that remain through the course of treatment. Among clones persisting across multiple samples we identified divergent phenotypes, suggesting a response to treament independent of clonal identity. Finally, a subset of clones harbor novel changes in expression following treatment. The clone and sample specific responses to treatment identified herein highlight the need for better personalized treatment strategies to overcome tumor heterogeneity.

SciLinker: a large-scale text mining framework for mapping associations among biological entities

Introduction

The biomedical literature is the go-to source of information regarding relationships between biological entities, including genes, diseases, cell types, and drugs, but the rapid pace of publication makes an exhaustive manual exploration impossible. In order to efficiently explore an up-to-date repository of millions of abstracts, we constructed an efficient and modular natural language processing pipeline and applied it to the entire PubMed abstract corpora.

Methods

We developed SciLinker using open-source libraries and pre-trained named entity recognition models to identify human genes, diseases, cell types and drugs, normalizing these biological entities to the Unified Medical Language System (UMLS). We implemented a scoring schema to quantify the statistical significance of entity co-occurrences and applied a fine-tuned PubMedBERT model for gene-disease relationship extraction.

Results

We identified and analyzed over 30 million association sentences, including more than 11 million gene-disease co-occurrence sentences, revealing more than 1.25 million unique gene-disease associations. We demonstrate SciLinker's ability to extract specific gene-disease relationships using osteoporosis as a case study. We show how such an analysis benefits target identification as clinically validated targets are enriched in SciLinker-derived disease-associated genes. Moreover, this co-occurrence data can be used to construct disease-specific networks, providing insights into significant relationships among biological entities from scientific literature.

Conclusion

SciLinker represents a novel text mining approach that extracts and quantifies associations between biomedical entities through co-occurrence analysis and relationship extraction from PubMed abstracts. Its modular design enables expansion to additional entities and text corpora, making it a versatile tool for transforming unstructured biomedical data into actionable insights for drug discovery.

Emerging Clostridioides difficile ribotypes have divergent metabolic phenotypes

Clostridioides difficile is a gram-positive spore-forming pathogen that commonly causes diarrheal infections in the developed world. Although C. difficile is a genetically diverse species, certain ribotypes are overrepresented in human infections, and it is unclear if metabolic adaptations are essential for the emergence of these epidemic ribotypes. To identify ribotype-specific metabolic differences, we therefore tested carbon substrate utilization by 88 C. difficile isolates and looked for differences in growth between 22 ribotypes. As expected, C. difficile was capable of growing on a variety of carbon substrates. Further, C. difficile strains clustered by phylogenetic relationship and displayed ribotype-specific and clade-specific metabolic capabilities. Surprisingly, we observed that two emerging lineages, ribotypes 023 and 255, have divergent metabolic phenotypes. In addition, although C. difficile Clade 5 is the most evolutionary distant clade and often detected in animals, it displayed robust growth on simple sugars similar to Clades 1-4. Altogether, our results corroborate the generalist metabolic strategy of C. difficile but also demonstrate lineage-specific metabolic capabilities.IMPORTANCEThe gut pathogen Clostridioides difficile utilizes a wide range of carbon sources. Microbial communities can be rationally designed to combat C. difficile by depleting its preferred nutrients in the gut. However, C. difficile is genetically diverse with hundreds of identified ribotypes, and most of its metabolic studies were performed with lab-adapted strains. To identify ribotype-specific metabolic differences, we profiled carbon metabolism by a myriad of C. difficile clinical isolates. While the metabolic capabilities of these isolates clustered by their genetic lineage, we observed surprising metabolic divergence between two emerging lineages. We also found that genetically newer and older clades grew to a similar level on simple sugars, which contrasts with recent findings that newer clades experienced positive selection on genes involved in simple sugar metabolism. Altogether, our results underscore the importance of considering the metabolic diversity of pathogens in the study of their evolution and the rational design of therapeutic interventions.

Shaping early neural development by timed elevated tissue oxygen tension: Insights from multiomic analysis on human cerebral organoids

Oxygen plays a critical role in early neural development in brains, particularly before establishment of complete vasculature; however, it has seldom been investigated due to technical limitations. This study uses an in vitro human cerebral organoid model with multiomic analysis, integrating advanced microscopies and single-cell RNA sequencing, to monitor tissue oxygen tension during neural development. Results reveal a key period between weeks 4 and 6 with elevated intra-organoid oxygen tension, altered energy homeostasis, and rapid neurogenesis within the organoids. The timed oxygen tension elevation can be suppressed by hypoxia treatment or silencing of neuroglobin gene. This study provides insights into the role of oxygen in early neurogenesis from functional, genotypic, phenotypic, and proteomic aspects. These findings highlight the significance of the timed tissue oxygen tension elevation in neurogenesis and provide insights into the role of neuroglobin in neural development, with potential implications for understanding neurodegenerative diseases and therapeutic strategies.

Unraveling the spatial and signaling dynamics and splicing kinetics of immune infiltration in osteoarthritis synovium

Introduction

Osteoarthritis (OA), a debilitating joint disorder characterized by synovial inflammation and immune myeloid cell infiltration, currently lacks a comprehensive spatial and transcriptional atlas. This study investigates the spatial dynamics, splicing kinetics, and signaling pathways that drive immune infiltration in OA synovium.

Methods

We integrated single-cell RNA sequencing (scRNA-seq) data from 8 OA and 4 healthy synovial samples with spatial transcriptomics using Spatrio. Spatial transition tensor (STT) analysis decoded multistable spatial homeostasis, while splicing kinetics and non-negative matrix factorization (NMF) identified gene modules. CellPhoneDB and pyLIGER mapped ligand-receptor interactions and transcriptional networks.

Results

Re-annotation of scRNA-seq data resolved synovial cells into 27 subclasses. Spatial analysis revealed OA-specific attractors (8 in OA vs. 6 in healthy samples), including immune myeloid (Attractor3) and lymphoid infiltration (Attractor4). Key genes OLR1 (myeloid homeostasis) and CD69 (T-cell activation) exhibited dysregulated splicing kinetics, driving inflammatory pathways. Myeloid-specific transcription factors (SPI1, MAF, NFKB1) and lymphoid-associated BCL11B were identified as regulators. Computational drug prediction nominated ZILEUTON as a potential inhibitor of ALXN5 to mitigate myeloid infiltration.

Discussion

This study delineates the spatial and transcriptional landscape of OA synovium, linking immune cell dynamics to localized inflammation. The identification of OLR1 and CD69 as spatial homeostasis drivers, alongside dysregulated signaling networks, offers novel therapeutic targets. These findings advance strategies to modulate immune infiltration and restore synovial homeostasis in OA.

Integrative analysis of gene expression and chromatin dynamics multi-omics data in mouse models of bleomycin-induced lung fibrosis

BACKGROUND

Pulmonary fibrosis is a relentless and ultimately fatal lung disorder. Despite a wealth of research, the intricate molecular pathways that contribute to the onset of PF, especially the aspects related to epigenetic modifications and chromatin dynamics, continue to be elusive and not fully understood.

METHODS

Utilizing a bleomycin-induced pulmonary fibrosis model, we conducted a comprehensive analysis of the interplay between chromatin structure, chromatin accessibility, gene expression patterns, and cellular heterogeneity. Our chromatin structure analysis included 5 samples (2 control and 3 bleomycin-treated), while accessibility and expression analysis included 6 samples each (3 control and 3 bleomycin-treated).

RESULTS

We found that chromatin architecture, with its alterations in compartmentalization and accessibility, is positively correlated with genome-wide gene expression changes during fibrosis. The importance of immune system inflammation and extracellular matrix reorganization in fibrosis is underscored by these chromatin alterations. Transcription factors such as PU.1, AP-1, and IRF proteins, which are pivotal in immune regulation, are associated with an increased abundance of their motifs in accessible genomic regions and are correlated with highly expressed genes.

CONCLUSIONS

We identified 14 genes that demonstrated consistent changes in their expression, accessibility, and compartmentalization, suggesting their potential as promising targets for the development of treatments for lung fibrosis.

Splenic TNF-α signaling potentiates the innate-to-adaptive transition of antiviral NK cells

Natural killer (NK) cells possess both innate and adaptive features. Here, we investigated NK cell activation across tissues during cytomegalovirus infection, which generates antigen-specific clonal expansion and long-lived memory responses. Longitudinal tracking and single-cell RNA sequencing of NK cells following infection revealed enhanced activation in the spleen, as well as early formation of a CD69lo precursor population that preferentially gave rise to adaptive NK cells. Splenic NK cells demonstrated heightened tumor necrosis factor alpha (TNF-α) signaling and increased expression of the receptor TNFR2, which coincided with elevated TNF-α production by splenic myeloid cells. TNFR2-deficient NK cells exhibited impaired interferon gamma (IFN-γ) production and expansion. TNFR2 signaling engaged two distinct nuclear factor κB (NF-κB) signaling arms-innate effector NK cell responses required canonical NF-κB signaling, whereas non-canonical NF-κB signaling enforced differentiation of CD69lo adaptive NK cell precursors. Thus, NK cell priming in the spleen during viral infection promotes an innate-to-adaptive transition, providing insight into avenues for generating adaptive NK cell immunity across diverse settings.

The polyamine-regulating enzyme SSAT1 impairs tissue regulatory T cell function in chronic cutaneous inflammation

Regulatory T (Treg) cells are a critical immune component guarding against excessive inflammation. Treg cell dysfunction can lead to chronic inflammatory diseases with current therapies aimed at inhibiting effector T cells rather than rescuing Treg cell function. We utilized single-cell RNAsequencing data from patients with chronic inflammation to identify SAT1, the gene encoding spermidine/spermine N1-acetyltransferase (SSAT), as a driver of skin-resident Treg cell dysfunction. CRISPRa-driven SAT1 expression in human skin-derived Treg cells impaired their suppressive function and induced a pro-inflammatory phenotype. During cutaneous type-17 inflammation, keratinocyte 4-1BBL induces SAT1 on Treg cells. In a mouse model of psoriasis, pharmacological inhibition of SSAT rescued Treg cell number and function. Together, these data show that SAT1 expression has severe functional consequences on Treg cells and suggest a therapeutic target to treat chronic inflammatory disease.

A single-cell atlas of circulating immune cells over the first 2 months of age in extremely premature infants

Extremely premature infants (EPIs) who are born before 30 weeks of gestation are susceptible to infection; however, the trajectory of their peripheral immunity is poorly understood. Here, we undertook longitudinal analyses of immune cells from 250 μl of whole blood at 1 week, 1 month, and 2 months from 10 EPIs and compared these with samples from healthy adults and with preterm and full-term cord blood samples. Single-cell suspensions from individual samples were split to perform single-cell RNA sequencing, T and B cell receptor sequencing, and phosphoprotein mass cytometry. The trajectories of circulating T, B, myeloid, and natural killer cells in EPIs over the first 2 months of life were distinct from those of full-term infants. In EPIs, peripheral T cell development rapidly progressed over the first month of life, with an increase in the proportion of naïve CD4+, regulatory, and cycling T cells, accompanied by greater STAT5 (signal transducer and activator of transcription 5) signaling. EPI memory CD4+ T cells showed a T helper 1 (TH1) predominance compared with TH2 skewing of central memory-like T cells in full-term infants, and B cells from 2-month-old EPIs exhibited increased signatures of activation and differentiation. Both B and T cells from 2-month-old EPIs displayed increased interferon signatures compared with cells from full-term infants. In conclusion, we demonstrated the feasibility of longitudinal multiomic analyses in EPIs using minute amounts of blood and developed a resource describing peripheral immune development in EPIs that suggested ongoing activation in early life.

Spatiotemporal Profiling Defines Persistence and Resistance Dynamics during Targeted Treatment of Melanoma

Resistance of BRAF-mutant melanomas to targeted therapy arises from the ability of cells to enter a persister state, evade treatment with relative dormancy, and repopulate the tumor when reactivated. A better understanding of the temporal dynamics and specific pathways leading into and out of the persister state is needed to identify strategies to prevent treatment failure. Using spatial transcriptomics in patient-derived xenograft models, we captured clonal lineage evolution during treatment. The persister state showed increased oxidative phosphorylation, decreased proliferation, and increased invasive capacity, with central-to-peripheral gradients. Phylogenetic tracing identified intrinsic and acquired resistance mechanisms (e.g., dual-specific phosphatases, reticulon-4, and cyclin-dependent kinase 2) and suggested specific temporal windows of potential therapeutic susceptibility. Deep learning-enabled analysis of histopathologic slides revealed morphologic features correlating with specific cell states, demonstrating that juxtaposition of transcriptomics and histologic data enabled identification of phenotypically distinct populations from using imaging data alone. In summary, this study defined state change and lineage selection during melanoma treatment with spatiotemporal resolution, elucidating how choice and timing of therapeutic agents will impact the ability to eradicate resistant clones. Significance: Tracking clonal progression during treatment uncovers conserved, global transcriptional changes and local clone-clone and spatial patterns underlying the emergence of resistance, providing insights into therapy-induced tumor evolution.

Potential molecular mechanisms of Jiedu Tongluo Tiaogan Formula in treating hyperthyroidism based on network pharmacology and in vivo experiments in mice

"Jiedu Tongluo Tiaoying Formula" (JDTLTYF) is a kind of traditional Chinese medicine (TCM) prescription for treating hyperthyroidism, which can effectively improve the condition of patients. The main active ingredients of JDTLTYF were collected from the traditional Chinese medicine systems pharmacology (TCMSP) database, and the target was predicted. Genes related to hyperthyroidism were identified using DisGeNET, GeneCards, and Online Mendelian Inheritance in Man (OMIM) databases. Protein-protein interaction (PPI) network and interaction network of "formula-herb-active ingredient-target genes" was constructed. Mass spectrometry was used to identify the components. The binding of key components to the target was verified by molecular docking and molecular dynamics (MD) simulations. A hyperthyroidism mouse model was established by using levothyroxine sodium tablets, and the hormone and expression levels of inflammatory factors were examined by ELISA and Western blot. The key genes of JDTLTYF in the treatment of hyperthyroidism were TNF and AKT1. The results of mass spectrometry also showed that quercetin was one of the main components. The results of molecular docking and MD simulation showed that the binding-free energy between AKT1 and quercetin was the lowest, and the binding was stable. In vivo experimental results showed that gastric lavage with JDTLTYF could target AKT1 and TNF-α, effectively alleviate the pathological features of hyperthyroidism in mice, and reduce inflammation response. This study elucidated the key small molecule compounds and their action targets of JDTLTYF in the treatment of hyperthyroidism. It provides a direction for the development of new drugs for clinical hyperthyroidism.NEW & NOTEWORTHY Based on the network pharmacology and molecular dynamics (MD) simulation, this study elucidated the key small molecule compounds and their action targets of JDTLTYF Chinese herbal prescription (debark peony root, common selfheal fruit-spike, figwort root, thunberg fritillary bulb, and oyster shell) in the treatment of hyperthyroidism, preliminarily analyzed its molecular mechanism, and provided a reference direction for subsequent cell experiments.

Data Mining and in Silico Analysis of Ethiopian Traditional Medicine: Unveiling the Therapeutic Potential of Rumex abyssinicus Jacq

Multicomponent traditional medicine prescriptions are widely used in Ethiopia for disease treatment. However, inconsistencies across practitioners, cultures, and locations have hindered the development of reliable therapeutic medicines. Systematic analysis of traditional medicine data is crucial for identifying consistent and reliable medicinal materials. In this study, we compiled and analyzed a dataset of 505 prescriptions, encompassing 567 medicinal materials used for treating 106 diseases. Using association rule mining, we identified significant associations between diseases and medicinal materials. Notably, wound healing-the most frequently treated condition-was strongly associated with Rumex abyssinicus Jacq., showing a high support value. This association led to further in silico and network analysis of R. abyssinicus Jacq. compounds, revealing 756 therapeutic targets enriched in various KEGG pathways and biological processes. The Random-Walk with Restart (RWR) algorithm applied to the CODA PPI network identified these targets as linked to diseases such as cancer, inflammation, and metabolic, immune, respiratory, and neurological disorders. Many hub target genes from the PPI network were also directly associated with wound healing, supporting the traditional use of R. abyssinicus Jacq. for treating wounds. In conclusion, this study uncovers significant associations between diseases and medicinal materials in Ethiopian traditional medicine, emphasizing the therapeutic potential of R. abyssinicus Jacq. These findings provide a foundation for further research, including in vitro and in vivo studies, to explore and validate the efficacy of traditional and natural product-derived medicines.

Single-Cell RNA Sequencing Reveals the Tumor Heterogeneity and Immunosuppressive Microenvironment in Urothelial Carcinoma

Urothelial carcinoma (UC) can arise from either the lower urinary tract or the upper tract; they represent different disease entities and require different clinical treatment strategies. A full understanding of the cellular characteristics in UC may guide the development of novel therapies. Here, we performed single-cell transcriptome analysis from four patients with UC of the bladder (UCB), five patients with UC of the ureter (UCU), and four patients with UC of the renal pelvis (UCRP) to develop a comprehensive cell atlas of UC. We found the rare epithelial cell subtype EP9 with epithelial-to-mesenchymal transition (EMT) and cancer stem cell (CSC) features, and specifically expressed SOX6, which was associated with poor prognosis. We also found that ACKR1+ endothelial cells and inflammatory cancer-associated fibroblasts (iCAFs) were more enriched in UCU, which may promote pathogenesis. While ESM1+ endothelial cells may more actively participate in UCB and UCRP tumorigenesis by promoting angiogenesis. Additionally, CD8 + effector T cells were more enriched in UCU and UCRP patients, while Tregs were mainly enriched in UCB tumors. C1QC+ macrophages and LAMP3+ dendritic cells were more enriched in UCB, which is closely related to the formation of the heterogeneous immunosuppressive microenvironment. Furthermore, we found strong interactions between iCAFs, EP9, and Endo_ESM1, and different degrees of activation of the FGF-FGFR3 axis and immune checkpoint pathway were observed in different UC subtypes. Our study elucidated the cellular heterogeneity and the components of the microenvironment in UC arising from the upper and lower urinary tracts and provided novel therapeutic targets.

Investigating subpopulation dynamics in clonal CHO-K1 cells with single-cell RNA sequencing

Chinese Hamster Ovary (CHO) cells produce monoclonal antibodies and other biotherapeutics at industrial scale. Despite their ubiquitous nature in the biopharmaceutical industry, little is known about the behaviors of individual transfected clonal CHO cells. Most CHO cells are assessed on their stability, their ability to produce the protein of interest over time. But CHO cells have primarily been studied in bulk, instead assuming that these bulk samples are homogenous because of presumed genetic clonality across the sample. This does not address cellular heterogeneity in these ostensibly clonal cells. These variable stability phenotypes may reflect heterogeneity within the clonal samples. In this study, we performed single-cell RNA sequencing on two clonal CHO-K1 cell populations with different stability phenotypes over a 90 day culture period. Our data showed that the instability of one of the clone's gene expression was due in part to the emergence of a low-producing subpopulation in the aged samples. This low-producing subpopulation did not exhibit markers of cellular stress which were expressed in the higher-producing populations. Further multiomic investigation should be performed to better characterize this heterogeneity.

Personalized, autologous neoantigen-specific T cell therapy in metastatic melanoma: a phase 1 trial

New treatment approaches are warranted for patients with advanced melanoma refractory to immune checkpoint blockade (ICB) or BRAF-targeted therapy. We designed BNT221, a personalized, neoantigen-specific autologous T cell product derived from peripheral blood, and tested this in a 3 + 3 dose-finding study with two dose levels (DLs) in patients with locally advanced or metastatic melanoma, disease progression after ICB, measurable disease (Response Evaluation Criteria in Solid Tumors version 1.1) and, where appropriate, BRAF-targeted therapy. Primary and secondary objectives were evaluation of safety, highest tolerated dose and anti-tumor activity. We report here the non-pre-specified, final results of the completed monotherapy arm consisting of nine patients: three at DL1 (1 × 108-1 × 109 cells) and six at DL2 (2 × 109-1 × 1010 cells). Drug products (DPs) were generated for all enrolled patients. BNT221 was well tolerated across both DLs, with no dose-limiting toxicities of grade 3 or higher attributed to the T cell product observed. Specifically, no cytokine release, immune effector cell-associated neurotoxicity or macrophage activation syndromes were reported. A dose of 5.0 × 108-1.0 × 1010 cells was identified for further study conduct. Six patients showed stable disease as best overall response, and tumor reductions (≤20%) were reported for four of these patients. In exploratory analyses, multiple mutant-specific CD4+ and CD8+ T cell responses were generated in each DP. These were cytotoxic, polyfunctional and expressed T cell receptors with broad functional avidities. Neoantigen-specific clonotypes were detected after treatment in blood and tumor. Our results provide key insights into this neoantigen-specific adoptive T cell therapy and demonstrate proof of concept for this new therapeutic approach. ClinicalTrials.gov registration: NCT04625205 .

The cellular and molecular cardiac tissue responses in human inflammatory cardiomyopathies after SARS-CoV-2 infection and COVID-19 vaccination

Myocarditis, characterized by inflammatory cell infiltration, can have multiple etiologies, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or, rarely, mRNA-based coronavirus disease 2019 (COVID-19) vaccination. The underlying cellular and molecular mechanisms remain poorly understood. In this study, we performed single-nucleus RNA sequencing on left ventricular endomyocardial biopsies from patients with myocarditis unrelated to COVID-19 (Non-COVID-19), after SARS-CoV-2 infection (Post-COVID-19) and after COVID-19 vaccination (Post-Vaccination). We identified distinct cytokine expression patterns, with interferon-γ playing a key role in Post-COVID-19, and upregulated IL16 and IL18 expression serving as a hallmark of Post-Vaccination myocarditis. Although myeloid responses were similar across all groups, the Post-Vaccination group showed a higher proportion of CD4+ T cells, and the Post-COVID-19 group exhibited an expansion of cytotoxic CD8+ T and natural killer cells. Endothelial cells showed gene expression changes indicative of vascular barrier dysfunction in the Post-COVID-19 group and ongoing angiogenesis across all groups. These findings highlight shared and distinct mechanisms driving myocarditis in patients with and without a history of SARS-CoV-2 infection or vaccination.

Exploring CX3CR1 as a prognostic biomarker and immunotherapeutic target in sarcoma

BACKGROUND

Sarcomas (SARC) are a diverse group of malignant tumors originating from mesenchymal tissues, characterized by poor prognosis under conventional therapies. CX3CR1, a chemokine receptor involved in immune cell migration, has emerged as a key player in SARC. Post-translational modifications (PTMs) such as phosphorylation and ubiquitination critically modulate CX3CR1, influencing cancer progression, immune responses, and treatment resistance.

METHODS

This study investigates CX3CR1 expression, its biological functions, and prognostic value in SARC. Using data from The Cancer Genome Atlas (TCGA), we analyzed CX3CR1 gene expression, methylation patterns, CRISPR screening results, and immune infiltration metrics. Functional experiments included knockout and overexpression models, CCK-8 assays and flow cytometry to assess apoptosis.

RESULTS

CX3CR1 expression was significantly elevated in SARC tissues and positively correlated with overall survival, disease-specific survival, and progression-free intervals. Methylation analysis identified CpG sites associated with CX3CR1 expression, differentiating tumor and adjacent tissues. CRISPR screening highlighted CX3CR1's essential role in tumor growth, while immune infiltration analysis underscored its impact on the tumor microenvironment. PTMs were found to stabilize CX3CR1, enhancing its activity in key signaling pathways. Overexpression of CX3CR1 amplified inflammatory and apoptotic responses, while knockdown showed protective effects in vitro.

CONCLUSIONS

CX3CR1 serves as a promising prognostic biomarker and therapeutic target in sarcoma. Targeting CX3CR1's PTMs could advance personalized treatments and improve outcomes for sarcoma patients.

Discovery of Herbal Remedies and Key Components for Major Depressive Disorder Through Biased Random Walk Analysis on a Multiscale Network

Major depressive disorder (MDD) is a widespread psychiatric condition with substantial socioeconomic impacts, yet single-target pharmacotherapies often yield responses. To address its multifactorial nature, this study employed a multiscale network analysis of herbs, their active components, and MDD-associated protein targets. Using a biased random walk with restart, we calculated interactions between disease-related and herb-derived targets, identifying herbs highly correlated with MDD. Enrichment analysis further revealed key signaling pathways, including oxidative stress, neuroinflammation, and hormone metabolism, underlying these herbs' therapeutic effects. We identified Ephedrae herba, Glehniae radix, Euryales semen, and Campsitis flos as promising candidates, each containing multiple bioactive compounds (such as ephedrine, psoralen, xanthine, and ursolic acid) that modulate critical processes like oxidation-reduction, inflammatory cytokine regulation, and transcriptional control. Network visualization showed how these herbs collectively target both shared and distinct pathways, supporting a synergistic, multi-target therapeutic strategy. This approach underscores the significance of network-based methodologies in addressing complex disorders such as MDD, where focusing on a single target may overlook synergistic interactions. By integrating diverse molecular data, this study provides a systematic framework for identifying novel interventions. Future experimental validation will be crucial to confirm these predictions and facilitate the translation of findings into effective MDD therapies.

Diagnostics and immunological function of CENPN in human tumors: from pan-cancer analysis to validation in breast cancer

Background

Centromere protein N (CENPN), a member of the centromere protein family, contributes to ribonucleic assembly, mitosis progression, and chromosome separation. CENPN manifests a close link with the occurrence and progression of several malignant cancers, but there is no pan-cancer study on CENPN, and we aim to ascertain the connection between CENPN and human cancer prognosis and immunotherapy.

Methods

The CENPN function in multiple malignant tumors was comprehensively investigated with data from The Cancer Genome Atlas (TCGA) and integrated Gene Expression Omnibus (GEO) database. We examined the transcriptional level, prognostic effect, diagnostic value, genetic and epigenetic alteration, methylation level, and immunological importance of CENPN. Furthermore, this work provided further confirmation of the phenotypic regulating function of CENPN in breast cancer (BC) cells.

Results

CENPN exhibited significant upregulation in diverse cancer tissues and had different expression patterns across immunological and molecular subgroups in several cancer types. Elevated expression of CENPN may correlate with a worse prognosis. CENPN effectively differentiates most cancers from healthy tissues. Hypomethylate was shown to be CENPN promoter in most cancers. CENPN was shown to be connected with levels of different immune cell infiltration. Kyoto Encyclopedia of Genes and Genomes (KEGG) and the Gene Set Enrichment Analysis (GSEA) analysis suggested that CENPN may mediate neutrophil extranuclear trap formation, cell cycle, and P53 signaling pathways in cancer. In vitro studies showed that the overexpression of CENPN promotes the proliferation, invasion, and migration of BC cells, while concurrently inhibiting their apoptosis.

Conclusions

CENPN may operate as a novel predictive indicator and molecular target for targeted therapy in pan-cancer. Significantly, CENPN contributed to controlling the BC growth and advancement.

Pig jejunal single-cell RNA landscapes revealing breed-specific immunology differentiation at various domestication stages

Background

Domestication of wild boars into local and intensive pig breeds has driven adaptive genomic changes, resulting in significant phenotypic differences in intestinal immune function. The intestine relies on diverse immune cells, but their evolutionary changes during domestication remain poorly understood at single-cell resolution.

Methods

We performed single-cell RNA sequencing (scRNA-seq) and marker gene analysis on jejunal tissues from wild boars, a Chinese local breed (Jinhua), and an intensive breed (Duroc). Then, we developed an immune cell evaluation system that includes immune scoring, gene identification, and cell communication analysis. Additionally, we mapped domestication-related clustering relationships, highlighting changes in gene expression and immune function.

Results

We generated a single-cell atlas of jejunal tissues, analyzing 26,246 cells and identifying 11 distinct cell lineages, including epithelial and plasma cells, and discovered shared and unique patterns in intestinal nutrition and immunity across breeds. Immune cell evaluation analysis confirmed the conservation and heterogeneity of immune cells, manifested by highly conserved functions of immune cell subgroups, but wild boars possess stronger immune capabilities than domesticated breeds. We also discovered four patterns of domestication-related breed-specific genes related to metabolism, immune surveillance, and cytotoxic functions. Lastly, we identified a unique population of plasma cells with distinctive antibody production in Jinhua pig population.

Conclusions

Our findings provide valuable single-cell insights into the cellular heterogeneity and immune function evolution in the jejunum during pig at various domestication stages. The single-cell atlas also serves as a resource for comparative studies and supports breeding programs aimed at enhancing immune traits in pigs.

Unveiling the cell-type-specific landscape of cellular senescence through single-cell transcriptomics using SenePy

Senescent cells accumulate in most tissues with organismal aging, exposure to stressors, or disease progression. It is challenging to identify senescent cells because cellular senescence signatures and phenotypes vary widely across distinct cell types and tissues. Here we developed an analytical algorithm that defines cell-type-specific and universal signatures of cellular senescence across a wide range of cell types and tissues. We utilize 72 mouse and 64 human weighted single-cell transcriptomic signatures of cellular senescence to create the SenePy scoring platform. SenePy signatures better recapitulate in vivo cellular senescence than signatures derived from in vitro senescence studies. We use SenePy to map the kinetics of senescent cell accumulation in healthy aging as well as multiple disease contexts, including tumorigenesis, inflammation, and myocardial infarction. SenePy characterizes cell-type-specific in vivo cellular senescence and could lead to the identification of genes that serve as mediators of cellular senescence and disease progression.

Cell type transcriptomics reveal shared genetic mechanisms in Alzheimer's and Parkinson's disease

Historically, Alzheimer's disease (AD) and Parkinson's disease (PD) have been investigated as two distinct disorders of the brain. However, a few similarities in neuropathology and clinical symptoms have been documented over the years. Traditional single gene-centric genetic studies, including GWAS and differential gene expression analyses, have struggled to unravel the molecular links between AD and PD. To address this, we tailor a pattern-learning framework to analyze synchronous gene co-expression at sub-cell-type resolution. Utilizing recently published single-nucleus AD (70,634 nuclei) and PD (340,902 nuclei) datasets from postmortem human brains, we systematically extract and juxtapose disease-critical gene modules. Our findings reveal extensive molecular similarities between AD and PD gene cliques. In neurons, disrupted cytoskeletal dynamics and mitochondrial stress highlight convergence in key processes; glial modules share roles in T-cell activation, myelin synthesis, and synapse pruning. This multi-module sub-cell-type approach offers insights into the molecular basis of shared neuropathology in AD and PD.

CITEgeist: Cellular Indexing of Transcriptomes and Epitopes for Guided Exploration of Intrinsic Spatial Trends

Spatial transcriptomics provides insights into tissue architecture by linking gene expression with spatial localization. Current deconvolution methods rely heavily on single-cell RNA sequencing (scRNA-seq) references, which are costly and often unavailable, mainly if the tissue under evaluation is limited, such as in a core biopsy specimen. We present a novel tool, CITEgeist, that deconvolutes spatial transcriptomics data using antibody capture from the same slide as the reference, directly leveraging cell surface protein measurements from the same tissue section. This approach circumvents the limitations of scRNA-seq as a reference, offering a cost-effective and biologically grounded alternative. Our method employs mathematical optimization to estimate cell type proportions and gene expression profiles, incorporating sparsity constraints for robustness and interpretability. Benchmarks against state-of-the-art deconvolution methods show improved accuracy in cell type resolution, particularly in dense tumor microenvironments, while maintaining computational efficiency. This antibody-based tool advances spatial transcriptomics by providing a scalable, accurate, and reference-independent solution for deconvolution in complex tissues. We validate this tool by using a combined approach of simulated data and clinical samples by applying CITEgeist to translational pre-treatment and post-treatment ER+ breast tumors from an ongoing clinical trial, emphasizing the applicability and robustness of CITEgeist.

Targeting ELOVL6 to disrupt c-MYC driven lipid metabolism in pancreatic cancer enhances chemosensitivity

Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer with a 12% survival rate, highlighting the need for novel therapies. c-MYC overexpression, driven by upstream mutations and amplifications, reprograms tumor metabolism and promotes proliferation, migration and metastasis. This study identifies ELOVL6, a fatty acid elongase regulated by c-MYC, as a potential therapeutic target. Using PDAC mouse models and cell lines, we show that c-MYC directly upregulates ELOVL6 during tumor progression. Genetic or chemical inhibition of ELOVL6 reduces proliferation and migration by altering fatty acid composition, affecting membrane rigidity, permeability and pinocytosis. These changes increase Abraxane uptake and show a synergistic effect when combined with ELOVL6 inhibition in vitro. In vivo, ELOVL6 interference significantly suppresses tumor growth and improves Abraxane response, prolonging survival. These findings position ELOVL6 as a promising target for improving PDAC treatment outcomes.

Identification and characterization of cell niches in tissue from spatial omics data at single-cell resolution

Deciphering the features, structure, and functions of the cell niche in tissues remains a major challenge. Here, we present scNiche, a computational framework to identify and characterize cell niches from spatial omics data at single-cell resolution. We benchmark scNiche with both simulated and biological datasets, and demonstrate that scNiche can effectively and robustly identify cell niches while outperforming other existing methods. In spatial proteomics data from human triple-negative breast cancer, scNiche reveals the influence of the microenvironment on cellular phenotypes, and further dissects patient-specific niches with distinct cellular compositions or phenotypic characteristics. By analyzing mouse liver spatial transcriptomics data across normal and early-onset liver failure donors, scNiche uncovers disease-specific liver injury niches, and further delineates the niche remodeling from normal liver to liver failure. Overall, scNiche enables decoding the cellular microenvironment in tissues from single-cell spatial omics data.

Learning and actioning general principles of cancer cell drug sensitivity

High-throughput screening of drug sensitivity of cancer cell lines (CCLs) holds the potential to unlock anti-tumor therapies. In this study, we leverage such datasets to predict drug response using cell line transcriptomics, focusing on models' interpretability and deployment on patients' data. We use large language models (LLMs) to match drug to mechanisms of action (MOA)-related pathways. Genes crucial for prediction are enriched in drug-MOAs, suggesting that our models learn the molecular determinants of response. Furthermore, by using only LLM-curated, MOA-genes, we enhance the predictive accuracy of our models. To enhance translatability, we align RNAseq data from CCLs, used for training, to those from patient samples, used for inference. We validated our approach on TCGA samples, where patients' best scoring drugs match those prescribed for their cancer type. We further predict and experimentally validate effective drugs for the patients of two highly lethal solid tumors, i.e., pancreatic cancer and glioblastoma.

Infusion of young donor plasma components in older patients modifies the immune and inflammatory response to surgical tissue injury: a randomized clinical trial

BACKGROUND

Preclinical evidence suggests that young plasma has beneficial effects on multiple organ systems in aged mice. Whether young plasma exerts beneficial effects in an aging human population remains highly controversial. Despite lacking data, young donor plasma infusions have been promoted for age-related conditions. Given the preclinical evidence that young plasma exerts beneficial effects by attenuating inflammation, this study examined whether administering a young plasma protein fraction to an elderly population would exert anti-inflammatory and immune modulating effects in humans, using surgery as a tissue injury model.

METHODS

This double-blind, placebo-controlled study enrolled and randomized 38 patients undergoing major joint replacement surgery. Patients received four separate infusions of a plasma protein fraction derived from young donors, or placebo one day before surgery, before and after surgery on the day of surgery, and one day after surgery. Blood specimens for proteomic and immunological analyses were collected before each infusion. Based on the high-content assessment of circulating plasma proteins with single-cell analyses of peripheral immune cells, proteomic signatures and cell-type-specific signaling responses that separated the treatment groups were derived with regression models.

RESULTS

Elastic net regression models revealed that administration a young plasma protein fraction significantly altered the proteomic (AUC = 0.796, p = 0.002) and the cellular immune response (AUC 0.904, p < 0.001) to surgical trauma resulting in signaling pathway- and cell type-specific anti-inflammatory immune modulation. Affected proteomic pathways regulating inflammation included JAK-STAT, NF-kappa B, and MAPK (p < 0.001). These findings were confirmed at the cellular level as the MAPK and JAK/STAT signaling responses were diminished and IkB, the negative regulator of NFkB, was elevated in adaptive immune cells.

CONCLUSION

Reported findings provide a first proof of principle in humans that a young plasma protein fraction actively regulates inflammatory and immune responses in an elderly population. They provide a solid rationale for elucidating active principles in young plasma that may be of therapeutic benefits for a range of age-related pathologies.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03981419.

Chronic exposure to glucocorticoids amplifies inhibitory neuron cell fate during human neurodevelopment in organoids

Disruptions in the tightly regulated process of human brain development have been linked to increased risk for brain and mental illnesses. While the genetic contribution to these diseases is well established, important environmental factors have been less studied at molecular and cellular levels. Here, we used single-cell and cell type-specific techniques to investigate the effect of glucocorticoid (GC) exposure, a mediator of antenatal environmental risk, on gene regulation and lineage specification in unguided human neural organoids. We characterized the transcriptional response to chronic GC exposure during neural differentiation and studied the underlying gene regulatory networks by integrating single-cell transcriptomics with chromatin accessibility data. We found lasting cell type-specific changes that included autism risk genes and several transcription factors associated with neurodevelopment. Chronic GC exposure influenced lineage specification primarily by priming the inhibitory neuron lineage through transcription factors like PBX3. We provide evidence for convergence of genetic and environmental risk factors through a common mechanism of altering lineage specification.

Proteomics of stress-induced cardiomyopathy: insights from differential expression, protein interaction networks, and functional pathway enrichment in an isoproterenol-induced TTC mouse model

Backgrounds

Takotsubo cardiomyopathy (TTC), also known as stress-induced cardiomyopathy, is a condition characterized by transient left ventricular dysfunction without coronary artery obstruction.

Methods

We utilized label-free quantitative proteomics to analyze protein expression in a murine model of TTC, induced by a high dose of isoproterenol (ISO) injection.

Results

We found that a single high dose of ISO injection in mice could induce stress-related cardiac dysfunction.The proteomic analysis revealed 81 differentially expressed proteins (DEPs) between the ISO and control groups-39 were upregulated, and 42 were downregulated. Key pathways enriched by Gene Ontology (GO) analysis included collagen fibril organization, cholesterol biosynthesis, and elastic fiber assembly. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment indicated significant changes in unsaturated fatty acid biosynthesis, glutathione metabolism, steroid biosynthesis, and ferroptosis. Key hub proteins identified by the protein-protein interaction (PPI) network included Ntrk2, Fdft1, Serpine1, and Cyp1a1. Gene set enrichment analysis (GSEA) showed upregulation in terpenoid backbone biosynthesis, oxidative phosphorylation, and ferroptosis, with downregulation in pathways such as systemic lupus erythematosus and Rap1 signaling.

Conclusions

This study employed high-throughput liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify key proteins associated with energy metabolism, oxidative stress, inflammation, and cell death in TTC. These findings provide new insights into the molecular mechanisms of stress-induced myocardial injury and may offer potential therapeutic targets for mitigating cardiovascular damage under stress conditions.

Recirculating regulatory T cells mediate thymic regeneration through amphiregulin following damage

Thymic injury associated with disease or cancer treatment reduces T cell production and makes patients more vulnerable to infections and cancers. Here, we examined the role of regulatory T (Treg) cells on thymic regeneration. Treg cell frequencies increased in the thymus in various acute injury models. Depletion of Treg cells impaired thymic regeneration, impacting both the thymocyte compartment and the stromal cell compartment; adoptive transfer of Treg cells enhanced regeneration. Expansion of circulating Treg cells, as opposed to that of tissue resident or recent thymic emigrants, explained this increase, as seen using parabiotic and adoptive transfer models. Single-cell analyses of recirculating Treg cells revealed expression of various regenerative factors, including the cytokine amphiregulin. Deletion of amphiregulin in these Treg cells impaired regeneration in the injured thymus. We identified an analogous population of CD39+ICOS+ Treg cells in the human thymus. Our findings point to potential therapeutic avenues to address aging- and treatment-induced immunosuppression.

Transcriptional impacts of substance use disorder and HIV on human ventral midbrain neurons and microglia

For people with HIV (PWH), substance use disorders (SUDs) are a prominent neurological risk factor, and the impacts of both on dopaminergic pathways are a potential point of deleterious convergence. Here, we profile, at single nucleus resolution, the substantia nigra (SN) transcriptomes of 90 postmortem donors in the context of chronic HIV and opioid/cocaine SUD, including 67 prospectively characterized PWH. We report altered microglial expression for hundreds of pro- and anti-inflammatory regulators attributable to HIV, and separately, to SUD. Stepwise, progressive microglial dysregulation, coupled to altered SN dopaminergic and GABAergic signaling, was associated with SUD/HIV dual diagnosis and further with lack of viral suppression in blood. In virologically suppressed donors, SUD comorbidity was associated with microglial transcriptional changes permissive for HIV infection. We report HIV-related downregulation of monoamine reuptake transporters specifically in dopaminergic neurons regardless of SUD status or viral load, and additional transcriptional signatures consistent with selective vulnerability of SN dopamine neurons.

Transcriptional and Neurochemical Signatures of Cerebral Blood Flow Alterations in Individuals With Schizophrenia or at Clinical High Risk for Psychosis

BACKGROUND

The brain integrates multiple scales of description, from the level of cells and molecules to large-scale networks and behavior. Understanding relationships across these scales may be fundamental to advancing understanding of brain function in health and disease. Recent neuroimaging research has shown that functional brain alterations that are associated with schizophrenia spectrum disorders (SSDs) are already present in young adults at clinical high risk for psychosis (CHR-P), but the cellular and molecular determinants of these alterations remain unclear.

METHODS

Here, we used regional cerebral blood flow (rCBF) data from 425 individuals (122 with an SSD compared with 116 healthy control participants [HCs] and 129 individuals at CHR-P compared with 58 HCs) and applied a novel pipeline to integrate brainwide rCBF case-control maps with publicly available transcriptomic data (17,205 gene maps) and neurotransmitter atlases (19 maps) from 1074 healthy volunteers.

RESULTS

We identified significant correlations between astrocyte, oligodendrocyte, oligodendrocyte precursor cell, and vascular leptomeningeal cell gene modules for both SSD and CHR-P rCBF phenotypes. Additionally, endothelial cell genes were correlated in SSD, and microglia in CHR-P. Receptor distribution significantly predicted case-control rCBF differences, with dominance analysis highlighting dopamine (D1, D2, dopamine transporter), acetylcholine (VAChT, M1), gamma-aminobutyric acid A (GABAA), and glutamate (NMDA) receptors as key predictors for SSD (R2adjusted = 0.58, false discovery rate [FDR]-corrected p < .05) and CHR-P (R2adjusted = 0.6, pFDR < .05) rCBF phenotypes. These associations were primarily localized in subcortical regions and implicate cell types involved in stress response and inflammation, alongside specific neuroreceptor systems, in shared and distinct rCBF phenotypes in psychosis.

CONCLUSIONS

Our findings underscore the value of integrating multiscale data as a promising hypothesis-generating approach toward decoding biological pathways involved in neuroimaging-based psychosis phenotypes, potentially guiding novel interventions.

High-resolution spatially resolved proteomics of complex tissues based on microfluidics and transfer learning

Despite recent advances in imaging- and antibody-based methods, achieving in-depth, high-resolution protein mapping across entire tissues remains a significant challenge in spatial proteomics. Here, we present parallel-flow projection and transfer learning across omics data (PLATO), an integrated framework combining microfluidics with deep learning to enable high-resolution mapping of thousands of proteins in whole tissue sections. We validated the PLATO framework by profiling the spatial proteome of the mouse cerebellum, identifying 2,564 protein groups in a single run. We then applied PLATO to rat villus and human breast cancer samples, achieving a spatial resolution of 25 μm and uncovering proteomic dynamics associated with disease states. This approach revealed spatially distinct tumor subtypes, identified key dysregulated proteins, and provided novel insights into the complexity of the tumor microenvironment. We believe that PLATO represents a transformative platform for exploring spatial proteomic regulation and its interplay with genetic and environmental factors.

A Temporal and Spatial Atlas of Adaptive Immune Responses in the Lymph Node Following Viral Infection

The spatial organization of adaptive immune cells within lymph nodes is critical for understanding immune responses during infection and disease. Here, we introduce AIR-SPACE, an integrative approach that combines high-resolution spatial transcriptomics with paired, high-fidelity long-read sequencing of T and B cell receptors. This method enables the simultaneous analysis of cellular transcriptomes and adaptive immune receptor (AIR) repertoires within their native spatial context. We applied AIR-SPACE to mouse popliteal lymph nodes at five distinct time points after Vaccinia virus footpad infection and constructed a comprehensive map of the developing adaptive immune response. Our analysis revealed heterogeneous activation niches, characterized by Interferon-gamma (IFN-γ) production, during the early stages of infection. At later stages, we delineated sub-anatomical structures within the germinal center (GC) and observed evidence that antibody-producing plasma cells differentiate and exit the GC through the dark zone. Furthermore, by combining clonotype data with spatial lineage tracing, we demonstrate that B cell clones are shared among multiple GCs within the same lymph node, reinforcing the concept of a dynamic, interconnected network of GCs. Overall, our study demonstrates how AIR-SPACE can be used to gain insight into the spatial dynamics of infection responses within lymphoid organs.

UV-induced reorganization of 3D genome mediates DNA damage response

While it is well-established that UV radiation threatens genomic integrity, the precise mechanisms by which cells orchestrate DNA damage response and repair within the context of 3D genome architecture remain unclear. Here, we address this gap by investigating the UV-induced reorganization of the 3D genome and its critical role in mediating damage response. Employing temporal maps of contact matrices and transcriptional profiles, we illustrate the immediate and holistic changes in genome architecture post-irradiation, emphasizing the significance of this reconfiguration for effective DNA repair processes. We demonstrate that UV radiation triggers a comprehensive restructuring of the 3D genome organization at all levels, including loops, topologically associating domains and compartments. Through the analysis of DNA damage and excision repair maps, we uncover a correlation between genome folding, gene regulation, damage formation probability, and repair efficacy. We show that adaptive reorganization of the 3D genome is a key mediator of the damage response, providing new insights into the complex interplay of genomic structure and cellular defense mechanisms against UV-induced damage, thereby advancing our understanding of cellular resilience.

Staphylococcus aureus-specific TIGIT+ Treg are present in the blood of healthy subjects - a hurdle for vaccination?

Staphylococcus aureus poses an enormous burden of morbidity and mortality worldwide. Making an efficacious vaccine has however proven extremely challenging. Due to colonizing interactions, pre-existing S. aureus-specific CD4+ T cells are often found in the human population and yet a detailed characterization of their phenotypes and how they might in turn impact vaccine efficacy are thus far unknown. Using an activation induced marker assay to sort for S. aureus-specific CD4+ T cells in an effector function-independent manner, single cell transcriptomic analysis was conducted. Remarkably, S. aureus-specific CD4+ T cells consisted not only of a broader spectrum of conventional T cells (Tcon) than previously described but also of regulatory T cells (Treg). As compared to polyclonally-activated CD4+ T cells, S. aureus-specific Tcon were enriched for the expression of the Th17-type cytokine genes IL17A, IL22 and IL26, while higher percentages of S. aureus-specific Treg expressed the T Cell Immunoreceptor with Ig and ITIM domains (TIGIT), a pleiotropic immune checkpoint. Notably, the antagonistic anti-TIGIT mAb Tiragolumab increased IL-1β production in response to S. aureus in vitro. Therefore, these results uncover the presence of S. aureus-specific TIGIT+ Treg in the blood of healthy subjects that could blunt responses to vaccination and indicate TIGIT as a potential targetable biomarker to overcome pre-exposure-induced immunosuppression.

Early tolerance and late persistence as alternative drug responses in cancer

Bacteria withstand antibiotic treatment through three alternative mechanisms: resistance, persistence or tolerance. While resistance and persistence have been described, whether drug-induced tolerance exists in cancer cells remains largely unknown. Here, we show that human cancer cells elicit a tolerant response when exposed to commonly used chemotherapy regimens, propelled by the pervasive activation of autophagy, leading to the comprehensive activation of DNA damage repair pathways. After prolonged drug exposure, such tolerant responses morph into persistence, whereby the increased DNA damage repair is entirely reversed. The central regulator of mitophagy PINK1 drives this reduction in DNA repair via the cytoplasmic relocalization of the cell identity master HNF4A, thus hampering HNF4A transcriptional activation of DNA repair genes. We conclude that exposing cancer cells to relevant standard-of-care antitumour therapies induces a pervasive drug-induced tolerant response that might be broadly exploited to increase the impact of first-line, adjuvant treatments and debulking in advanced cancers.

Fatty acid amide hydrolase gene inactivation induces hetero-cellular potentiation of microglial function in the 5xFAD mouse model of Alzheimer's disease

Neuroinflammation has recently emerged as a crucial factor in Alzheimer's disease (AD) etiopathogenesis. Microglial cells play an important function in the inflammatory response; specifically, the emergence of disease-associated microglia (DAM) has offered new insights into the conflicting perspectives on the detrimental or beneficial roles of microglia. We previously showed that modulating the endocannabinoid tone by fatty acid amide hydrolase (FAAH) inactivation renders beneficial effects in an amyloidosis context, paradoxically accompanied by an exacerbated neuroinflammatory response and the enrichment of DAM population. Here, we aim to elucidate the role of microglial cells in FAAH-lacking mice in the 5xFAD mouse model of AD by using RNA-sequencing analysis, molecular determinations, and morphological studies by using in vivo multiphoton microscopy. FAAH-lacking AD mice displayed upregulated inflammatory genes and exhibited a DAM genetic profile. Conversely, genes linked to AD were downregulated. Depleting microglia using PLX5622 revealed that plaque-associated microglia in FAAH-deficient AD mice had a more stable, ramified morphology and increased Aβ uptake, leading to reduced plaque growth compared to control mice. Importantly, FAAH expression was negligible in microglial cells, thus suggesting a role for FAAH in the cellular interplay in the central nervous system. Our findings show that Faah gene inactivation triggers a hetero-cellular enhancement of microglial function that was paradoxically paralleled by an exacerbated inflammatory response. Taken together, the present data highlight FAAH as a potential therapeutic target in AD.

Spatial transcriptomic clocks reveal cell proximity effects in brain ageing

Old age is associated with a decline in cognitive function and an increase in neurodegenerative disease risk1. Brain ageing is complex and is accompanied by many cellular changes2. Furthermore, the influence that aged cells have on neighbouring cells and how this contributes to tissue decline is unknown. More generally, the tools to systematically address this question in ageing tissues have not yet been developed. Here we generate a spatially resolved single-cell transcriptomics brain atlas of 4.2 million cells from 20 distinct ages across the adult lifespan and across two rejuvenating interventions-exercise and partial reprogramming. We build spatial ageing clocks, machine learning models trained on this spatial transcriptomics atlas, to identify spatial and cell-type-specific transcriptomic fingerprints of ageing, rejuvenation and disease, including for rare cell types. Using spatial ageing clocks and deep learning, we find that T cells, which increasingly infiltrate the brain with age, have a marked pro-ageing proximity effect on neighbouring cells. Surprisingly, neural stem cells have a strong pro-rejuvenating proximity effect on neighbouring cells. We also identify potential mediators of the pro-ageing effect of T cells and the pro-rejuvenating effect of neural stem cells on their neighbours. These results suggest that rare cell types can have a potent influence on their neighbours and could be targeted to counter tissue ageing. Spatial ageing clocks represent a useful tool for studying cell-cell interactions in spatial contexts and should allow scalable assessment of the efficacy of interventions for ageing and disease.

Inhibition of IFITM3 in cerebrovascular endothelium alleviates Alzheimer's-related phenotypes

INTRODUCTION

Interferon-induced transmembrane protein 3 (IFITM3) modulates γ-secretase in Alzheimer's Disease (AD). Although IFITM3 knockout reduces amyloid β protein (Aβ) production, its cell-specific effect on AD remains unclear.

METHODS

Single nucleus RNA sequencing (snRNA-seq) was used to assess IFITM3 expression. Adeno-associated virus-BI30 (AAV-BI30) was injected to reduce IFITM3 expression in the cerebrovascular endothelial cells (CVECs). The effects on AD phenotypes in cells and AD mice were examined through behavioral tests, two-photon imaging, flow cytometry, Western blot, immunohistochemistry, and quantitative polymerase chain reaction assay (qPCR).

RESULTS

IFITM3 expression was increased in the CVECs of patients with AD. Overexpression of IFITM3 in primary endothelial cells enhanced Aβ generation through regulating beta-site APP cleaving enzyme 1 (BACE1) and γ-secretase. Aβ further increased IFITM3 expression, creating a vicious cycle. Knockdown of IFITM3 in CVECs decreased Aβ accumulation within cerebrovascular walls, reduced Alzheimer's-related pathology, and improved cognitive performance in AD transgenic mice.

DISCUSSION

Knockdown of IFITM3 in CVECs alleviates AD pathology and cognitive impairment. Targeting cerebrovascular endothelial IFITM3 holds promise for AD treatment.

HIGHLIGHTS

Interferon-induced transmembrane protein 3 (IFITM3) expression was increased in the cerebrovascular endothelial cells (CVECs) of patients with Alzheimer's Disease (AD). Cerebrovascular endothelial IFITM3 regulates amyloid β protein (Aβ) generation through regulating beta-site APP cleaving enzyme 1 (BACE1) and γ-secretase. Knockdown of IFITM3 in CVECs reduces Aβ deposits and improves cognitive impairments in AD transgenic mice. Cerebrovascular endothelial IFITM3 could be a potential target for the treatment of AD.

A Regulatory Circuits Analysis Tool, "miRCuit," Helps Reveal Breast Cancer Pathways: Toward Systems Medicine in Oncology

A systems medicine understanding of the regulatory molecular circuits that underpin breast cancer is essential for early cancer detection and precision/personalized medicine in clinical oncology. Transcription factors (TFs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) control gene expression and cell biology, and by extension, serve as pillars of the regulatory circuits that determine human health and disease. We report here the development of a regulatory circuit analysis program, miRCuit, constructing 10 different types of regulatory elements involving messenger RNA, miRNA, lncRNA, and TFs. Using the miRCuit, we analyzed expression profiling data from 179 invasive ductal breast carcinoma and 51 normal tissue samples from the Gene Expression Omnibus database. We identified eight circuit types along with two special types of circuits, one of which highlighted the significant roles of lncRNA CASC15, miR-130b-3p, and TF KLF5 in breast cancer development and progression. These findings advance our understanding of the regulatory molecules associated with breast cancer. Moreover, miRCuit offers a new avenue for users to construct circuits from regulatory molecules for potential applications to decipher disease pathogenesis.

Integrative mapping of human CD8+ T cells in inflammation and cancer

CD8+ T cells exhibit remarkable phenotypic diversity in inflammation and cancer. However, a comprehensive understanding of their clonal landscape and dynamics remains elusive. Here we introduce scAtlasVAE, a deep-learning-based model for the integration of large-scale single-cell RNA sequencing data and cross-atlas comparisons. scAtlasVAE has enabled us to construct an extensive human CD8+ T cell atlas, comprising 1,151,678 cells from 961 samples across 68 studies and 42 disease conditions, with paired T cell receptor information. Through incorporating information in T cell receptor clonal expansion and sharing, we have successfully established connections between distinct cell subtypes and shed light on their phenotypic and functional transitions. Notably, our approach characterizes three distinct exhausted T cell subtypes and reveals diverse transcriptome and clonal sharing patterns in autoimmune and immune-related adverse event inflammation. Furthermore, scAtlasVAE facilitates the automatic annotation of CD8+ T cell subtypes in query single-cell RNA sequencing datasets, enabling unbiased and scalable analyses. In conclusion, our work presents a comprehensive single-cell reference and computational framework for CD8+ T cell research.

INSTINCT: Multi-sample integration of spatial chromatin accessibility sequencing data via stochastic domain translation

Recent advances in spatial epigenomic techniques have given rise to spatial assay for transposase-accessible chromatin using sequencing (spATAC-seq) data, enabling the characterization of epigenomic heterogeneity and spatial information simultaneously. Integrative analysis of multiple spATAC-seq samples, for which no method has been developed, allows for effective identification and elimination of unwanted non-biological factors within the data, enabling comprehensive exploration of tissue structures and providing a holistic epigenomic landscape, thereby facilitating the discovery of biological implications and the study of regulatory processes. In this article, we present INSTINCT, a method for multi-sample INtegration of Spatial chromaTIN accessibility sequencing data via stochastiC domain Translation. INSTINCT can efficiently handle the high dimensionality of spATAC-seq data and eliminate the complex noise and batch effects of samples through a stochastic domain translation procedure. We demonstrate the superiority and robustness of INSTINCT in integrating spATAC-seq data across multiple simulated scenarios and real datasets. Additionally, we highlight the advantages of INSTINCT in spatial domain identification, visualization, spot-type annotation, and various downstream analyses, including motif enrichment analysis, expression enrichment analysis, and partitioned heritability analysis.

Targeting BRD4 ameliorates experimental emphysema by disrupting super-enhancer in polarized alveolar macrophage

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a progressive chronic lung disease characterized by chronic airway inflammation and emphysema. Macrophage polarization plays an important role in COPD pathogenesis by secreting inflammatory mediators. Bromodomain-containing protein 4 (BRD4), an epigenetic reader that specifically binds to histones, plays a crucial role in inflammatory diseases by regulating macrophage polarization. Herein, we attempted to examine the hypothesis that modulating alveolar macrophage polarization via BRD4 inhibitors might has a potential for COPD treatment.

METHODS

We firstly analyzed BRD4 expression and its correlation with clinical parameters and macrophage polarization markers in sputum transcriptomes from 94 COPD patients and 36 healthy individuals. In vivo, BRD4 inhibitor JQ1 and degrader ARV-825 were intraperitoneally administrated into emphysema mice to assess their effects on lung emphysema and inflammation. In vitro, RNA-seq and CUT&Tag assay of BRD4 and H3K27ac were applied for elucidating how BRD4 regulates macrophage polarization.

RESULTS

We found an increased expression of BRD4 in the induced sputum from patients with COPD and unveiled a strong correlation between BRD4 expression and clinical parameters as well as macrophage polarization. Subsequently, BRD4 inhibitor JQ1 and degrader ARV-825 significantly mitigated emphysema and airway inflammation along with better protection of lung function in mice. BRD4 inhibition also suppressed both M1 and M2 alveolar macrophage polarization. The CUT&Tag assay of BRD4 and H3K27ac, revealed that BRD4 inhibition disrupted the super-enhancers (SEs) of IRF4 (a crucial transcription factor for M2 macrophage), and subsequently affected the expression of matrix metalloproteinase 12 (MMP12) which is vital for emphysema development.

CONCLUSION

This study suggested that downregulation of BRD4 might suppress airway inflammation and emphysema through disrupting the SEs of IRF4 and alveolar macrophages polarization, which might be a potential target of therapeutic intervention in COPD. A diagram of the mechanism by which BRD4 mediated super-enhancer of IRF4 in M2 AMs. Graphic illustration showed targeting BRD4 in M2 polarized AMs lead to the downregulation of MMP12 expression, resulting in the amelioration of experimental emphysema by disrupting the super-enhancer of IRF4.

Interneuron Loss and Microglia Activation by Transcriptome Analyses in the Basal Ganglia of Tourette Disorder

BACKGROUND

Tourette disorder (TS) is characterized by motor hyperactivity and tics that are believed to originate in the basal ganglia. Postmortem immunocytochemical analyses has revealed decreases in cholinergic (CH), as well as parvalbumin and somatostatin GABA (gamma-aminobutyric acid) interneurons (INs) within the caudate/putamen of individuals with TS.

METHODS

We obtained transcriptome and open chromatin datasets by single-nucleus RNA sequencing and single-nucleus ATAC sequencing, respectively, from caudate/putamen postmortem specimens of 6 adults with TS and 6 matched normal control subjects. Differential gene expression and differential chromatin accessibility analyses were performed in identified cell types.

RESULTS

The data reproduced the known cellular composition of the human striatum, including a majority of medium spiny neurons (MSNs) and small populations of GABA-INs and CH-INs. INs were decreased by ∼50% in TS brains, with no difference in other cell types. Differential gene expression analysis suggested that mitochondrial oxidative metabolism in MSNs and synaptic adhesion and function in INs were both decreased in subjects with TS, 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 MSNs, oligodendrocytes, and astrocytes of TS brains.

CONCLUSIONS

This initial analysis of the TS basal ganglia transcriptome at the single-cell level confirms the loss and synaptic dysfunction of basal ganglia INs, consistent with in vivo basal ganglia hyperactivity. In parallel, oxidative metabolism was decreased in MSNs and correlated with activation of microglia cells, which is attributable at least in part to dysregulated activity of putative enhancers, implicating altered epigenomic regulation in TS.

Behavioral and genetic markers of susceptibility to escalate fentanyl intake

Background

The "loss of control" over drug consumption, present in opioid use disorder (OUD) and known as escalation of intake, is well-established in preclinical rodent models. However, little is known about how antecedent behavioral characteristics, such as valuation of hedonic reinforcers prior to drug use, may impact the trajectory of fentanyl intake over time. Moreover, it is unclear if distinct escalation phenotypes may be driven by genetic markers predictive of OUD susceptibility.

Methods

Male and female Sprague-Dawley rats (n=63) were trained in a sucrose reinforcement task using a progressive ratio schedule. Individual differences in responsivity to sucrose were hypothesized to predict escalation of fentanyl intake. Rats underwent daily 1-h acquisition sessions for i.v. fentanyl self-administration (2.5 μg/kg; FR1) for 7 days, followed by 21 6-h escalation sessions, then tissue from prefrontal cortex was collected for RNA sequencing and qPCR. Latent growth curve and group-based trajectory modeling were used, respectively, to evaluate the association between sucrose reinforcement and fentanyl self-administration and to identify whether distinct escalation phenotypes can be linked to gene expression patterns.

Results

Sucrose breakpoints were not predictive of fentanyl acquisition nor change during escalation, but did predict fentanyl intake on the first day of extended access to fentanyl. Permutation analyses did not identify associations between behavior and single gene expression when evaluated overall, or between our ascertained phenotypes. However, weighted genome correlation network analysis (WGCNA) and gene set enrichment analysis (GSEA) determined several gene modules linked to escalated fentanyl intake, including genes coding for voltage-gated potassium channels, calcium channels, and genes involved in excitatory synaptic signaling. Transcription factor analyses identified EZH2 and JARID2 as potential transcriptional regulators associated with escalated fentanyl intake. Genome-wide association study (GWAS) term categories were also generated and positively associated with terms relating to substance use disorders.

Discussion

Escalation of opioid intake is largely distinct from motivation for natural reward, such as sucrose. Further, the gene networks associated with fentanyl escalation suggest that engagement of select molecular pathways distinguish individuals with "addiction prone" behavioral endophenotypes, potentially representing druggable targets for opioid use disorder. Our extended in silico identification of SNPs and transcription factors associated with the "addiction prone" high escalating rats highlights the importance of integrating findings from translational preclinical models. Through a precision medicine approach, our results may aid in the development of patient-centered treatment options for those with OUD.

Genome-scale spatial mapping of the Hodgkin lymphoma microenvironment identifies tumor cell survival factors

A key challenge in cancer research is to identify the secreted factors that contribute to tumor cell survival. Nowhere is this more evident than in Hodgkin lymphoma, where malignant Hodgkin Reed Sternberg (HRS) cells comprise only 1-5% of the tumor mass, the remainder being infiltrating immune cells that presumably are required for the survival of the HRS cells. Until now, there has been no way to characterize the complex Hodgkin lymphoma tumor microenvironment at genome scale. Here, we performed genome-wide transcriptional profiling with spatial and single-cell resolution. We show that the neighborhood surrounding HRS cells forms a distinct niche involving 31 immune and stromal cell types and is enriched in CD4+ T cells, myeloid and follicular dendritic cells, while being depleted of plasma cells. Moreover, we used machine learning to nominate ligand-receptor pairs enriched in the HRS cell niche. Specifically, we identified IL13 as a candidate survival factor. In support of this hypothesis, recombinant IL13 augmented the proliferation of HRS cells in vitro. In addition, genome-wide CRISPR/Cas9 loss-of-function studies across more than 1,000 human cancer cell lines showed that IL4R and IL13RA1, the heterodimeric partners that constitute the IL13 receptor, were uniquely required for the survival of HRS cells. Moreover, monoclonal antibodies targeting either IL4R or IL13R phenocopied the genetic loss of function studies. IL13-targeting antibodies are already FDA-approved for atopic dermatitis, suggesting that clinical trials testing such agents should be explored in patients with Hodgkin lymphoma.

Spatial transcriptome reveals histology-correlated immune signature learnt by deep learning attention mechanism on H&E-stained images for ovarian cancer prognosis

BACKGROUND

The ability to predict the prognosis of patients with ovarian cancer can greatly improve disease management. However, the knowledge on the mechanism of the prediction is limited. We sought to deconvolute the attention feature learnt by a deep learning convolutional neural networks trained with whole-slide images (WSIs) of hematoxylin-and-eosin (H&E)-stained tumor samples using spatial transcriptomic data.

METHODS

In this study, 773 WSIs of H&E-stained tumor sections from 335 patients with treatment naïve high-grade serous ovarian cancer who were included in The Cancer Genome Atlas (TCGA) Pan-Cancer study were used to train, and validate, and to test a ResNet101 CNN model modified with attention mechanism. WSIs from patients in an independent cohort were used to further evaluate the model.

RESULTS

The prognostic value of the predicted H&E-based survival scores from the trained model on patient survival was evaluated. The attention signals learnt by the model were then examined their correlation with immune signatures using spatial transcriptome. After validating the model with the testing datasets, pathway enrichment analysis showed that the H&E-based survival score significantly correlated with certain immune signatures and this was validated spatially using spatial transcriptome data generated from ovarian cancer FFPE samples by correlating the selected signature and attention signal.

CONCLUSIONS

In conclusion, attention mechanism might be useful to identify regions for their specific immune activities. This could guide future pathological study for the useful immunological features that are important in modulating the prognosis of ovarian cancer patients.

snoRNA-facilitated protein secretion revealed by transcriptome-wide snoRNA target identification

Small nucleolar RNAs (snoRNAs) are non-coding RNAs known for guiding RNA modifications, including 2'-O-methylation (Nm) and pseudouridine (Ψ). While snoRNAs may also interact with other RNAs, such as mRNA, the full repertoire of RNAs targeted by snoRNA remains elusive due to the lack of effective technologies that identify snoRNA targets transcriptome wide. Here, we develop a chemical crosslinking-based approach that comprehensively detects cellular RNA targets of snoRNAs, yielding thousands of previously unrecognized snoRNA-mRNA interactions in human cells and mouse brain tissues. Many interactions occur outside of snoRNA-guided RNA modification sites, hinting at non-canonical functions beyond RNA modification. We find that one of these snoRNAs, SNORA73, targets mRNAs that encode secretory proteins and membrane proteins. SNORA73 also interacts with 7SL RNA, part of the signal recognition particle (SRP) required for protein secretion. The mRNA-SNORA73-7SL RNA interactions enhance the association of the SNORA73-target mRNAs with SRP, thereby facilitating the secretion of encoded proteins.

Benchmarking and optimizing Perturb-seq in differentiating human pluripotent stem cells

Perturb-seq is a powerful approach to systematically assess how genes and enhancers impact the molecular and cellular pathways of development and disease. However, technical challenges have limited its application in stem cell-based systems. Here, we benchmarked Perturb-seq across multiple CRISPRi modalities, on diverse genomic targets, in multiple human pluripotent stem cells, during directed differentiation to multiple lineages, and across multiple sgRNA delivery systems. To ensure cost-effective production of large-scale Perturb-seq datasets as part of the Impact of Genomic Variants on Function (IGVF) consortium, our optimized protocol dynamically assesses experiment quality across the weeks-long procedure. Our analysis of 1,996,260 sequenced cells across benchmarking datasets reveals shared regulatory networks linking disease-associated enhancers and genes with downstream targets during cardiomyocyte differentiation. This study establishes open tools and resources for interrogating genome function during stem cell differentiation.