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Biology subjects

Liu, S.

Publications and source records attributed to Liu, S..

At least 73 records · Page 4Linked to original sources

Estrogen-Deficiency Degrades Left Ventricular Diastolic Function and Energy Metabolism in Hypertensive Female Mice

AimsHeart failure (HF) due to diastolic dysfunction (DD) but normal left ventricular (LV) ejection fraction (EF) is termed HF with preserved EF (HFpEF). Given its high prevalence in post-menopausal women, we hypothesized that 17{beta}-estradiol (E2) function is mechanistically linked to DD HF and investigated E2-deficiency in the etiology of DD in a mouse model. MethodsFemale C57BL/6J mice were divided into one group with hypertension induced by N({omega})-nitro-L-arginine methyl ester (L) and cardiac pressure overload induced by angiotensin II (A), collectively inducing DD, and one group with sham treatment. Groups were subdivided to receive an ovariectomy (OVX) to induce estrogen-deficiency and emulate menopause or sham surgery. During the next 21 days, mice were tested for cardiac function, food intake, response to E2 agonists, gene profiling, cardiomyocyte-contractility and elasticity, and cardiac mitochondrial function. ResultsOVX-associated E2-deficiency exacerbated DD in a time-dependent way without affecting EF or stroke volume, emulating a severe DD phenotype. These changes paralleled those for mitochondrial dysfunction, i.e., upregulation of genes associated with stress, energy metabolism, and fibrosis, as well as functional and structural defects in cardiomyocytes. Treatment of OVX + (L + A) with E2 or a G-protein-coupled estrogen receptor agonist normalized diastolic function, whereas estrogen receptor beta agonists did not. The OVX DD mice exhibited moderately impaired mitochondrial function, which delayed cardiomyocyte relaxation but not contraction, altered cardiac substrate utilization, reduced cardiomyocyte elasticity, increased production of reactive oxygen species, and potentiated extracellular fibrosis. ConclusionsOVX-induced E2-deficiency generates metabolic, structural, and functional changes in cardiomyocytes and the adjacent extracellular matrix, exacerbating the effects of L and A on diastolic function. This robust DD model revealed a role for E2 via ER in diastole-regulation in female mice and raised questions about similar mechanisms operative in postmenopausal women. HIGHLIGHTSO_LIOvariectomy (OVX)-induced estrogen-deficiency exacerbated diastolic dysfunction (DD) induced by hypertension and pressure overload with preserved ejection fraction in female C57BL/6J mice. C_LIO_LIIn post-OVX-treated DD mice, heart weight and fibrosis preceded other metrics of cardiac dysfunction. C_LIO_LIOVX-induced estrogen-deficiency increased the expression of genes associated with stress, energy metabolism, and especially fibrosis. C_LIO_LIMetabolic imaging of the heart by positron emission tomography revealed that DD with preserved ejection fraction was associated with mitochondrial dysfunction presenting as increased accretion of cardiac energy substrates, [18F]deoxyglucose and [11C]palmitate, effects that worsened following OVX. C_LIO_LIOVX increased cardiomyocyte stiffness and fibrosis and reduced cardiomyocyte lengthening and compliance in the context of female DD. C_LIO_LIImproved diastolic function following delivery of GPER agonists or estradiol to OVX DD female mice implicates estrogen receptor in the maintenance of normal cardiac function. C_LI

physiology↗

Architecture of a portal complex embedded in the poxvirus core

Gene transcription within the viral core is a unique feature of poxvirus replication. Following entry into the cytoplasm, the poxvirus core dissociates from the lateral bodies and undergoes expansion, functioning as a compartment for early transcription. However, the mechanisms governing molecular exchange between the viral core and the host cytoplasm remain poorly understood. Here, we determine the structures of the portal complex and its pore on the poxvirus core at 7.1 [A] and 4.9 [A] resolution, respectively, using cryo-electron tomography and sub-tomogram averaging. The pore is assembled from three viral proteins, E8, E6, and L3, for which we constructed an atomic model. Structural and channel analyses reveal that the pore satisfies the geometric and electrostatic requirements for the transport of RNA and smaller negatively charged molecules, while excluding double-stranded DNA and cytosolic DNA sensors. Together, our findings establish a structural framework for understanding the assembly and function of the poxvirus portal complex and identify potential targets for antiviral intervention.

biophysics↗

MOFF2: A Transferable Coarse-Grained Protein Force Field for Predictive Condensate Simulations

Coarse-grained protein force fields enable simulations of biomolecular systems at length and time scales that are difficult to access with atomistic models, but achieving transferability across folded, intrinsically disordered, and multidomain proteins remains challenging. A central difficulty is that one-bead-per-residue models must represent chemically specific residue interactions while also absorbing solvent-mediated and many-body effects into a simplified energy function. Here, we present MOFF2, a transferable coarse-grained protein force field that combines residue-pair-specific interactions with a density-dependent many-body potential. MOFF2 is optimized using a two-stage strategy: bottom-up parameter learning from heterogeneous reference ensembles followed by refinement against experimental conformational observables. The resulting model provides balanced performance across ordered proteins, intrinsically disordered proteins, and multidomain proteins, and predicts condensate saturation-concentration trends for A1-LCD variant systems. Analysis of the learned parameters reveals chemically interpretable interaction patterns and density-dependent effects that explain the models improved transferability. These results demonstrate that combining a generalized coarse-grained energy function with data-driven optimization can produce a practical and interpretable force field for protein conformational and condensate simulations.

biophysics↗

Quantifying annotation-stratified pleiotropy and co-polygenicity between complex traits

Understanding shared genetic architecture is essential to interpreting disease comorbidities and trait correlations. We introduce SBayesAPP, a Bayesian model that integrates GWAS summary statistics with functional annotations to jointly estimate annotation-stratified SNP effect-size correlation and pleiotropic variant proportion (co-polygenicity) between traits, dissecting genetic correlation and coheritability enrichment across annotations. Simulations and real data analyses show improved accuracy and interpretability over existing methods. In type 2 diabetes analyses with 15 traits, SBayesAPP reveals clear tissue- and cell-type-specific enrichment and distinguishes mechanisms driven by few large-effect variants versus many modest-effect variants. The analysis of smoking and lung cancer prioritizes lung and immune cells, and identifies cell-type-specific genetic correlations driven by either pleiotropic or lung-cancer-specific variants, consistent with a causal relationship model. For schizophrenia and educational attainment, despite near-zero genome-wide genetic correlation, cell-type-specific correlations range from -0.20 to 0.21, with strong (co)heritability enrichment and high co-polygenicity found in dopaminergic neurons and oligodendrocytes. These results highlight the ability of SBayesAPP to resolve annotation-specific genetic sharing and uncover biological mechanisms across complex traits.

genomics↗

AI-guided analysis of human pancreatic islet sociology reveals distinct cell compositional changes in type 1 diabetes

Human pancreatic islets exhibit greater anatomic and cellular heterogeneity than previously appreciated, raising fundamental questions about how their composition varies with age, sex, region, and islet size and how type 1 diabetes (T1D) alters these relationships. Yet these questions remained largely unresolved due to the bottleneck of manual tissue inspection. Here, we developed an integrated artificial intelligence (AI)-guided imaging, processing, and statistical pipeline enabling unbiased, high-throughput analysis of more than 2 million candidate islets from 106 non-diabetic (ND) and T1D donors. We identified age-, region-, sex-, and islet size-dependent differences in islet distribution and composition between ND and T1D donors. Profound {beta}-cell loss in T1D was accompanied by reciprocal -cell expansion, whereas {delta}-cells and pancreatic polypeptide cells were largely resilient. Cell area and pseudotime analyses uncovered regional and age-dependent trajectories of islet remodeling across T1D progression, along with distinct patterns of cytoarchitectural reorganization of the endocrine pancreas.

pathology↗

Genomic Inbreeding and Selection Signatures analyses in the Doberman Pinscher breed

The Doberman Pinscher population has undergone strong artificial selection for morphology and behavior, which can reduce genomic diversity and increase autozygosity. Here, we characterized the genome structure and identified selection signatures in Doberman Pinschers using complementary within- and between-population approaches. Genotypes from 3,226 Dobermans Dogs (Illumina CanineHD; 216,184 SNPs) provided by the Doberman Diversity Project were analyzed after purpose-specific quality control. Genomic inbreeding was quantified using four allele-frequency-based metrics and the runs of homozygosity (FROH) approach. Selection signatures were detected using intrapopulation (i.e., Runs of Homozygosity--ROH; Integrated Haplotype Score--iHS; and Number of Segregating Sites by Length--nSL) and interpopulation methods (i.e., Fixation Index--FST; Cross-Population Extended Haplotype Homozygosity--XP-EHH; and Cross-Population Number of Segregating Sites by Length--XP-nSL) comparing the Doberman Pinscher breed to Labrador Retriever (n=237). Dobermans showed high overall inbreeding, with a mean FROH of 0.42 (range 0.22-0.68), whereas the allele-frequency-based inbreeding estimators had similar means ([~]0.04). The partitioning of the ROH indicated high contributions from medium-to-long ROHs, consistent with recent inbreeding. The ROH scans identified 39,512 SNPs in ROH islands ([≥]50% frequency across individuals), with notable concentrations on CFA2, CFA3, and CFA31. Haplotype-based scans identified 2,820 candidate iHS SNPs and 2,173 candidate nSL SNPs (|score|>2). A common set of 310 SNPs was shared among ROH, iHS, and nSL, mapping near 279 genes that were mostly enriched for developmental pathways, particularly neurodevelopment and neuron-related cellular components. Between breeds, 349 highly differentiated SNPs were detected by FST, while XP-EHH and XP-nSL highlighted over 1,000 of Doberman-specific haplotype signals. A total of seven SNPs overlapped across FST, XP-EHH, and XP-nSL, which were located mainly on CFA8 ([~]59.48-60.61 Mb) near the KCNK10, SPATA7, PTPN21, NEGR1, and BTG1 genes. These genes are mainly linked to neural development and signaling, but BTG1 has also been associated with cardiomyocyte cell-cycle regulation, and KCNK10 with cardiac excitability and remodeling. Overall, the Doberman Pinscher breed exhibits high genome-wide autozygosity and levels of inbreeding. In addition, our results showed consistent, multi-method evidence of selection at loci associated with neurodevelopmental and regulatory pathways. These findings provide prioritized targets for follow-up studies that integrate phenotypes relevant to breed health and performance.

genomics↗

Single-cell spatial transcriptomics and snRNA-seq decoding the organizational principles of functional modules in the mouse amygdala

The amygdala is a functionally heterogeneous nuclear complex comprising multiple subnuclei that orchestrate diverse behaviors, making it essential for survival and reproduction. However, the precise neural mechanisms underlying these heterogeneous functions remain elusive, primarily due to limited knowledge of the amygdalas cellular heterogeneity, developmental origins, spatial organization, and gene expression profiles. Here, we integrate single-cell-resolution spatial transcriptomics with precise anatomical dissection and single-nucleus RNA sequencing to systematically map the subnuclear enrichment patterns of amygdalar cell types. We further demonstrate that developmental origin determines subnuclear positioning and propose a novel functional modular architecture based on cellular composition and gene expression signatures. Furthermore, we reveal that the central amygdala (CEA) exhibits developmental heterogeneity, with Isl1+ neurons in its medial subdivision (CEAm) predominantly originating from hypothalamic progenitors. Our findings establish a spatially resolved cellular and molecular framework for investigating amygdalar functions at cellular type resolution and understanding amygdala-related neuropsychiatric disorders.

neuroscience↗

Interstitium-mimicking porous alveolar membranes enable physiologic aerosol transport and distinct acute-chronic lung injury responses

Barrier membranes govern transport and mechanochemical coupling in lung-on-chip systems but typically exhibit low open porosity, limited pore interconnectivity, and diffusion distances exceeding native thin septal regions. An interstitium-mimicking, alveolus-shaped poly({varepsilon}-caprolactone) membrane is developed using dual-templated nonsolvent-induced phase separation followed by controlled enzymatic pore enlargement. The resulting architecture achieves [~]40% total porosity with 97% pore interconnectivity and incorporates a locally thinned dome region ([~]2.5 {micro}m). This structure sustains cyclic deformation while increasing oxygen diffusivity fivefold compared with conventional Transwell(R) membranes under both acellular and epithelial-endothelial co-culture conditions. Integrated into an air-liquid interface platform, the membrane enables direct aerosol deposition and quantitative interrogation of cross-barrier mass transfer. Using carbonaceous nanoscale particulate matter as a model inhaled aerosol, controlled exposure induces dose-dependent oxidative, inflammatory, and genotoxic responses. Matched cumulative dose studies reveal distinct biological trajectories: acute high-dose exposure produces rapid cytotoxic stress and barrier disruption, whereas chronic low-dose exposure preserves viability yet promotes sustained DNA repair and genome-maintenance programs. Compartment-resolved analysis and therapeutic intervention further demonstrate the platforms utility for spatial and translational interrogation of lung injury. By restoring physiologically relevant diffusion distance, interconnectivity, and strain responsiveness, the interstitium-mimicking membrane advances lung-on-chip design toward functional replication of alveolar transport dynamics for studying lung injury and barrier dysfunction.

bioengineering↗

Linezolid Acts as a Selective Inhibitor of the JAK2V617F Mutation

The JAK2V617F (JAK2VF) driver mutation is found in 95% of patients with polycythemia vera (PV), a progressive myeloproliferative neoplasm. Current treatments suppress excessive hematopoiesis but lack specificity for targeting JAK2VF cells, are unable to deplete mutant stem/progenitor cells and ultimately result in drug resistance. We discovered that the FDA-approved antibiotic, linezolid (LZD), ameliorates the PV phenotype across multiple model systems. LZD suppressed cell proliferation and STAT5 signaling, altered the cell cycle, and increased apoptosis of JAK2VF-harboring human erythroleukemia cells, but not in wild-type acute leukemia cells. Computational modelling indicated that LZD interacts specifically with mutant JAK2VF but not with wild-type JAK2 protein. We further showed that, in JAK2VF mice that faithfully recapitulate human PV, LZD mitigates disease burden by selectively targeting JAK2VF stem cells thereby normalizing spleen size and blood counts. LZD also inhibited hematopoietic colony formation by patient-derived peripheral blood mononuclear cells, with the more primitive progenitors being preferred targets. Importantly, LZD selectively decreased JAK2VF+ colony numbers, without impacting wild-type JAK2 colonies. In all, the data provide a firm foundation for evaluating LZD-like molecules as an effective therapy for PV and other myeloproliferative neoplasms. Key pointsO_LILinezolid acts as a JAK2V617FIZselective inhibitor in PV mouse models and PV patient samples while sparing wildIZtype hematopoiesis. C_LIO_LILinezolid acts directly on JAK2V617F hematopoietic stem cells. C_LI

cancer biology↗

Evolution of supernumerary chromosomes in wheat blast fungal pathogens

A genome of Pyricularia oryzae (synonym Magnaporthe oryzae), the fungus that causes blast disease on diverse grass species, has seven core chromosomes and may contain supernumerary mini-chromosomes. The P. oryzae Triticum (PoT) pathotype is the phylogenetic lineage responsible for devastating epidemics of wheat blast disease. Genomic analysis of wheat blast field isolates from the initial outbreak in 1985 in Brazil through recent field isolates in South America revealed dynamic presence and structure of mini-chromosomes. Two "earliest" field isolates representing founder lineages for the Triticum pathotype contain similar mini-chromosomes. Another PoT founder isolate from 1986 and 37 out of 39 Triticum field isolates collected between 1986 and 1992 lack mini-chromosomes. Mini-chromosomes present in the founder strains each contain two copies of the PWT7 wheat blast avirulence gene, and PWT7 was lost from subsequent early strains through mini-chromosome loss. Almost all PoT field isolates from 2005 to 2020 have regained mini-chromosomes in which PWT7 sequences have been replaced by other sequences. Telomere-to-telomere assemblies of 11 mini-chromosomes identified two major mini-chromosome types in the South American PoT population, and demonstrated significant within-mini-chromosome sequence alterations as well as recombination with other mini-chromosomes or core chromosome ends. Additionally, our data indicate horizontal mini-chromosome transfer between Pyricularia species, resulting in nearly identical genomic fragments shared between P. oryzae and Pyricularia pennisetigena isolates in the PWT4 avirulence gene region. Our genomic analysis depicts the dynamic mini-chromosome compartment in the diverse South American Triticum field population through time, indicating important roles for mini-chromosomes in pathogen adaptation and pathogenicity.

evolutionary biology↗

Calmodulin controls the tempo of HSV-1 gene-expression cascade to reshape infection heterogeneity

Viral replication exhibits substantial heterogeneity among individual cells. Although temporally ordered gene-expression cascades are thought to contribute to such heterogeneity in DNA viruses, whether and how their tempo is regulated, and how cell-to-cell variability shapes population-level infection outcomes, remain unknown. Here, we developed a high-throughput live-cell imaging platform to track HSV-1 gene-expression dynamics in individual cells and, in combination with single-cell RNA sequencing, identified calmodulin (CaM) as a host regulator of HSV-1 gene-expression tempo. CaM accelerates progression from immediate-early to early and late phases at the single-cell level by advancing their onset. By increasing the fraction of virus-producing cells without altering burst size, CaM reshapes the distribution of infection outcomes, thereby promoting population-level viral replication. Pharmacological inhibition of CaM protects mice from lethal infection, exceeding acyclovir. These findings establish CaM-mediated temporal control as a key determinant of population-level viral output and a regulator of infection heterogeneity.

microbiology↗

DINMC: A Deep Learning Framework for Interpretable Normative Model Construction and Pathological Brain Alteration Detection

Background and ObjectiveNormative modeling is a key tool for understanding brain alterations in neurodegenerative diseases, such as cerebellar-type multiple system atrophy. However, existing methods lack interpretability and fail to capture clinically meaningful pathological changes. This study presents DINMC, a Deep Interpretable Normative Model Construction framework, which combines autoencoder-based learning with statistical hypothesis testing to better capture and interpret disease-specific neu-roanatomical changes. MethodsThe DINMC framework constructs normative models using neuroimaging data from multi-site large healthy cohorts. It utilizes a U-shaped convolutional autoencoder to train these models, which are then applied to reconstruct brain features from both patients and healthy controls within the same study cohort. Pathological confidence values are derived by fusing original and deviation feature spaces, offering a measure of disease-related pathology reflected in each dimension of the features. The framework was validated through statistical analysis and prognostic classification and regression tasks. ResultsThe pathological confidence provides valuable insights into the neuroanatomical regions most affected by the disease, as well as the correlation between changes in these regions and clinical assessment scales. Our optimal model outperform traditional methods in prognostic prediction tasks, with an AUC of 0.972 for classification tasks and an R2 of 0.432 for regression tasks. ConclusionDINMC provides a novel and interpretable framework for neuroimaging analysis. By combining deep learning and statistical hypothesis testing, this framework offers a unique solution to improving both the interpretability and performance of normative models in neuroimaging. The approach is scalable to other neuroimaging datasets, offering a versatile tool for broader biomedical applications.

bioinformatics↗

PRISMA: A tensor-based framework for deconstructing the genetic architecture of complex diseases, with application to diabetic retinopathy

Complex-disease GWAS compress heterogeneous, tissue-dependent genetic effects into global locus-level statistics, masking local regulatory routes through which polygenic risk contributes to disease architecture. Here we introduce PRISMA (Polygenic Risk Integration via Summary-statistics Multi-tissue Array-decomposition), a summary-statistics framework for quantifying tissue-resolved genetic heterogeneity hidden within aggregate GWAS signals. PRISMA integrates GWAS and multi-tissue cis-eQTL data using graph Laplacian-regularized block-wise factorization, preserving local linkage disequilibrium topology during decomposition. Applied to diabetic retinopathy, PRISMA deconvolved aggregated polygenic risk into three tissue-biased genetic axes corresponding to vascular-metabolic, systemic immune-inflammatory, and retina-specific neurodegenerative trajectories. The framework prioritized 549 axis-associated targets, including 403 below the conventional genome-wide significance threshold, and showed higher tissue-regulatory resolution than PCA, NMF, and K-means. A height GWAS negative-control analysis supported trait-dependent regulatory reprioritization within a shared eQTL-mappable framework. Independent single-cell transcriptomic analyses supported axis-specific enrichment across fibrovascular, immune, and retinal compartments. Exploratory vitreous humor proteomic and metabolomic profiling further nominated candidate molecular correlates of downstream convergence. PRISMA reframes complex-disease GWAS from aggregate locus discovery toward quantitative, LD-aware mapping of tissue-resolved genetic trajectories.

genomics↗

Taxon-resolved sources of organic carbon preserved in lake sediments using the sedaDNA GenC pipeline

Organic carbon (OC) burial in lakes is an important component of the global carbon cycle, but the source organisms of preserved OC remain poorly resolved. Here we develop the genC pipeline, which combines sedimentary ancient DNA concentrations, read-based taxonomic assignments, and group-specific priors for DNA and cellular carbon content to derive OCDNA-projected, a semi-quantitative proxy for the magnitude and taxonomic composition of preserved sedimentary OC. We apply genC to six high-latitude lake records spanning the last 30,000 years. OCDNA-projected broadly agrees with independent proxies for total organic carbon and aquatic contribution, supporting its reliability. Our results indicate that environmental conditions, especially warming, rather than preservation alone, are the main drivers of preserved OC variation. Terrestrial sources, mainly woody plants, dominate lake sediment OC. Eukaryotic algae as well as aquatic and terrestrial bacteria become more important during the warmer Holocene. These results establish sedaDNA as a taxonomically resolved tool for reconstructing long-term changes in preserved lake-sediment OC.

paleontology↗

Genos-m: a foundation model for human-associated microbial genomes

Human-associated microbial genomes encode extensive strain-level diversity and niche-specific gene repertoires that are critical to host health. However, these complex sequence features remain difficult to capture using general-purpose DNA foundation models, highlighting the need for dedicated representation learning tailored to the human microbiome. Here, we introduce Genos-m, an open-source foundation model for human-associated microbial genome representation. Genos-m was pretrained on approximately 1.2 trillion nucleotide tokens from a curated microbial genome corpus, including human-associated prokaryotic isolates, high-quality metagenome-assembled genomes (MAGs) and bacteriophages, supplemented with GTDB species-level representative genomes to broaden prokaryotic taxonomic breadth. The model uses a sparsely activated Mixture-of-Experts (MoE) Transformer architecture, with 4.7 billion total parameters, approximately 330 million activated parameters per forward pass and a maximum context length of one million base pairs. We evaluated frozen Genos-m representations across short-sequence and gene-level tasks, biosynthetic gene cluster (BGC)-based regional sequence tasks, whole-genome strain phenotype prediction, and zero-shot transfer on prokaryote-related RNAfitness assays. Across these benchmarks, Genos-m consistently ranked among the leading comparison models, with the best performance in five of eight gene-fitness regression tasks and in BGC type classification. Using sparse autoencoders, we identified sparse features in Genos-m hidden activations that aligned with annotated ORFs, intergenic regions, and tRNA and rRNA loci. In downstream applications, Genos-m-derived genome-informed species representations in-corporated into a human microbiome self-supervised learning model improved colorectal cancer (CRC)-control classification over conventional species-abundance random forest models. Genos-m also generated stable sample-level embeddings from as few as 10,000 metagenomic reads, retaining gut microbial community structure that distinguished geographic origin and aligned with enterotypes defined from full-depth taxonomic profiles. Together, these results support Genos-m as a reusable representation model for microbial genomes and metagenomes, with conclusions bounded by the reported datasets, task definitions and evaluation protocols. Genos-m model weights, inference code, and usage documentation are publicly available on GitHub (https://github.com/BGI-HangzhouAI/Genos-m) and Hugging-Face (https://huggingface.co/BGI-HangzhouAI/Genos-m).

bioinformatics↗

Decoding Immune Reconstitution Failure in People Living with HIV through Single-cell Genomics

Immune non-responders (INRs), a subset of people living with HIV (PLWH), fail to achieve full immune reconstitution and remain at increased risk of morbidity, mortality, and non-AIDS-related illnesses. As the mechanisms underlying this impaired immune recovery remain poorly understood, we performed single-cell multi-omics profiling on peripheral blood mononuclear cells from 43 INRs, 47 immune responders and 53 healthy donors. Our dataset comprises 2,744,009 transcriptomes and 1,226,658 chromatin-accessibility profiles across 58 identified immune cell types. INRs exhibited markedly elevated inflammatory signaling, increased apoptotic activity, and dysregulation of immune-activating ligand-receptor interactions. Additionally, we identified 2,996 interaction cis-eGenes and 5,938 cis-caPeaks, and validated key cell type-specific cis-xQTL effects associated with immune reconstitution failure. Furthermore, we identified 3,551 sc-eQTLs and 872 cell-state interaction eQTLs (ieQTLs) in CD4+ T cells. A genotype-specific upregulation of OAS3 in INRs, likely regulated by STAT1, was identified based on these results. We developed scPRISM (single cell Predictive Reconstitution Immune Status Model), a multi-modal framework that integrates scRNA-seq and scATAC-seq data to perform the dual tasks of differentiating disease states and predicting gene expression from chromatin accessibility, thereby deciphering the cell type-specific cis-regulatory basis of the disease. Our study delineates the transcriptional and epigenomic landscape of immune dysregulation in INRs and provides new genetic insights into HIV-associated immune reconstitution failure. These findings offer a foundation for developing biomarkers and precision therapies to restore immune function in PLWH.

genetics↗

Systematic characterization of the yeast secretome under diverse proteosynthetic stress conditions reveals secretion of functional ER chaperone BiP

The yeast secreted proteome plays critical biological roles and influences product and production parameters in industrial fermentation. Systematic profiling of the response of the yeast secretome to intrinsic and extrinsic factors is therefore essential for understanding these functions and for optimizing manufacturing processes. Here, we characterized the yeast secretome under diverse proteosynthetic stress conditions, including glycosylation deficiency, oxidative, reductive, and thermal stresses. The secretome was predominantly composed of conventionally secreted proteins, while a subset of proteins appeared to be secreted via unconventional pathways. Distinct secretome profiles were observed in response to different stressors, driven by a combination of altered intracellular proteomes, altered canonical secretion, and altered cell lysis and unconventional protein secretion, while reflecting the underlying metabolic state of the cells. Heat stress did not impact protein glycosylation but did cause similar protein misfolding stress to N-glycosylation deficiency. Intriguingly, canonically intracellular chaperone BiP was abundant in the secretome in particular stress conditions where its activity would be beneficial. BiP interacted with probable extracellular client proteins in vitro, consistent with it acting as a functional extracellular chaperone/holdase in conditions such as reductive stress in which client proteins could be misfolded outside the cell.

biochemistry↗

Combined Checkpoint Inhibition Amplifies Post-Infarction Injury via T Cell-Mediated Macrophage Activation

BackgroundThis study aimed to investigate whether combined PD-1/CTLA-4 immune checkpoint inhibition predisposes the heart to a hyperinflammatory state, thereby exacerbating cardiac injury following acute myocardial infarction (MI), a critical unresolved question in cardio-oncology. MethodsMyocardial infarction was induced in Pd1-/-Ctla4+/- mice, a genetic model mimicking combined checkpoint inhibition. Key mechanistic insights were gained through in vivodepletion of CD8+ T cells (using anti-CD8a antibody) and pharmacological inhibition of the JAK-STAT1 pathway (using Tofacitinib). Cardiac function, structural injury, and immune responses were comprehensively assessed via echocardiography, flow cytometry, immunofluorescence, and molecular analyses. ResultsCompared to wild-type controls, Pd1-/-Ctla4+/- mice exhibited significantly increased post-MI mortality, worse cardiac function, and larger infarct size. Mechanistically, the aggravated injury was driven by an amplified infiltration of activated, IFN-{gamma}-producing CD8+ T cells, which activated the JAK-STAT1 pathway in macrophages, polarizing them towards a pro-inflammatory state. Depleting CD8+ T cells or inhibiting the JAK-STAT1 pathway effectively attenuated macrophage-driven inflammation and improved all aspects of post-MI injury. ConclusionsCombined PD-1/CTLA-4 blockade exacerbates post-infarction cardiac injury by promoting CD8+ T cell-mediated activation of macrophages via the JAK-STAT1 axis. This work elucidates MI as a context-dependent immune-related adverse event in ICI therapy and identifies CD8+ T cells and the JAK-STAT1 pathway as promising therapeutic targets for cardioprotection in these patients. RESEARCH PERSPECTIVEO_ST_ABSWhat Is New?C_ST_ABSO_LIThis study identifies acute myocardial infarction (MI) as a potential, context-dependent immune-related adverse event in the setting of combined PD-1/CTLA-4 checkpoint inhibition, shifting the paradigm beyond the classic focus on myocarditis. C_LIO_LIIt elucidates a novel pathogenic axis where combined checkpoint deficiency exacerbates post-MI injury specifically through CD8+ T cell-derived IFN-{gamma}, which activates macrophages via the JAK-STAT1 pathway. C_LI What Question Should Be Addressed Next?O_LIFuture studies should employ anti-PD-1/CTLA-4 monoclonal antibodies in wild-type or humanized mouse models to validate findings and better recapitulate the pharmacokinetics of clinical ICI therapy, strengthening translational relevance. C_LIO_LIThe long-term consequences of this primed inflammatory state on chronic cardiac remodeling, heart failure development, and the potential interplay with atherosclerosis warrant further investigation. C_LI

immunology↗