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Biology subjects

Rong, S.

Publications and source records attributed to Rong, S..

14 recordsLinked to original sources

OPA1 controls mitochondrial dysfunction-driven liver fibrosis in MASLD

Progressive hepatic fibrosis is the principal determinant of morbidity and mortality in metabolic dysfunction-associated steatotic liver disease and steatohepatitis (MASLD/MASH). Mitochondrial dysfunction is a hallmark of MASH, and the release of mitochondrial damage-associated molecular patterns (mito-DAMPs) from injured hepatocytes can promote fibrosis. However, how mitochondrial dynamics and quality control shape the fibrotic response in MASLD/MASH remains unclear. Here, through large-scale genomic analyses of mitochondrial genes governing mitophagy, fusion and fission in human MASLD, with a power-equivalent sample size of approximately 700,000 individuals, we identify a strong association between hepatic fibrosis and the mitochondrial fusion factor dynamin-like GTPase optic atrophy 1 (OPA1). OPA1 transcripts and protein abundance in the liver epithelium were progressively dysregulated with advancing fibrosis. In mice, hepatocyte-specific OPA1 loss alone was sufficient to induce hepatic stellate cell activation and fibrosis in zone 3, promoted the release of mito-DAMPs into the circulation and exacerbated fibrosis in experimental MASH. These findings identify OPA1 as a central regulator of the hepatic fibrotic response and connect defective mitochondrial homeostasis to mito-DAMP release, hepatic stellate cell activation and fibrosis in MASLD.

genetics↗

Lipid mobilization establishes metabolic tolerance and prevents autonomic collapse in infection

Survival during infection depends on both pathogen clearance and the ability to tolerate infection-induced physiological changes. Metabolic adaptations are a central component of this tolerance, but the mechanisms underlying these responses remain incompletely defined. Here, we identify white adipose tissue (WAT) lipolysis as a central regulator of metabolic tolerance to infection. In patients with sepsis, higher circulating non-esterified fatty acid (NEFA) levels were associated with reduced mortality. In mouse models of polymicrobial sepsis, infection induced robust adipose lipolysis and increased circulating NEFAs. Genetic ablation of adipose triglyceride lipase (ATGL) in adipose tissue impaired lipolysis, leading to hypothermia, bradycardia, and increased mortality without altering immune cell populations or pathogen burden, consistent with a defect in tolerance rather than resistance. Mechanistically, lipolysis-derived NEFAs, but not glycerol, were required for protection, as restoring circulating NEFAs rescued autonomic stability and survival in adipose tissue ATGL-deficient mice. Infection-induced lipolysis was redundantly regulated and did not depend on any single upstream signaling pathway. Both pharmacologic activation of lipolysis using a {beta}3-adrenergic agonist and exogenous fatty acid supplementation increased circulating NEFAs, improved survival, and promoted tolerance in mice. Consistent with these findings, analysis of real-world electronic health record data demonstrated that septic patients receiving FDA-approved {beta}3-adrenergic agonists had reduced mortality or hospice discharge in a propensity-matched cohort. Together, these results identify WAT lipolysis and circulating fatty acids as key mediators of tolerance to infection and support a therapeutic strategy based on repurposing clinically available {beta}3-adrenergic agonists to improve outcomes in sepsis. One Sentence SummaryWhite adipose tissue lipolysis promotes metabolic tolerance to infection through circulating fatty acids and is associated with improved survival in sepsis

physiology↗

Identifying non-coding variant effects at scale via machine learning models of cis-regulatory reporter assays

The inability to interpret the functional impact of non-coding variants has been a major impediment in the promise of precision medicine. While high-throughput experimental approaches such as Massively Parallel Reporter Assays (MPRAs) have made major progress in identifying causal variants and their underlying molecular mechanisms, these tools cannot exhaustively measure variant effects genome-wide. Here we present MPAC, an ensemble of machine-learning models trained on MPRA data that provides accurate and scalable prediction of the cis-regulatory impact of non-coding variants. Using MPAC we predict allelic effects for 575M single nucleotide variants (SNVs) across diverse applications, including complex trait genetics, clinical and tumor sequencing, evolutionary analyses, and saturation mutagenesis. We find MPAC predictions match the performance of empirical MPRAs in identifying causal complex trait-associated alleles. We demonstrate the utility of MPAC by applying it to ClinVar, identifying non-coding pathogenic variation with higher accuracy than other sequence-to-function models. We also nominate 1,892 candidate non-coding cancer drivers by predicting the functional effects of somatic SNVs in the COSMIC database. Next, we evaluate population-level genetic variation by predicting effects for all 514M non-coding SNVs in gnomAD, quantifying the relationship between regulatory function and evolutionary constraint. Finally, we generate prospective functional maps using in-silico saturation mutagenesis across 18,658 human promoters, observing widespread selection against variants predicted to disrupt promoter activity. Collectively, this study establishes the value of non-coding functional predictions and provides a comprehensive, publicly available resource for variant interpretation.

genomics↗

One-Size-Fits-Many: Antisense oligonucleotides for rescuing splicing mutations in hotspot exons

Mutations that impact splicing play a significant role in disease etiology but are not fully understood. To characterize the impact of exonic variants on splicing in 71 clinically-actionable disease genes in asymptomatic people, we analyzed 32,112 exonic mutations from ClinVar and Geisinger MyCode using a minigene reporter assay. We identify 1,733 splice-disrupting mutations, of which the most extreme 1-2% of variants are likely to be deleterious. We report that these variants are not distributed evenly across exons but are mostly concentrated in the [~]8% of exons that are most susceptible to splicing mutations (i.e. hotspot exons). We demonstrate that splicing defects in these exons can be reverted by ASOs targeting the splice sites of either their upstream or downstream flanking exons. This finding supports the feasibility of developing single therapeutic ASOs that could revert all splice-altering variants localized to a particular exon.

molecular biology↗

Single-cell dissection of prognostic architecture and immunotherapy response in Helicobacter pylori infection associated gastric cancer

Most of the gastric cancer (GC) worldwide are ascribed to Helicobacter pylori (H. pylori) infections, which have a detrimental effect on the immunotherapys efficacy. Comprehensively dissecting the key cell players and molecular pathways associated with cancer immunotherapies is critical for developing novel therapeutic strategies against H. pylori infection associated GC. We performed a comprehensive single-cell transcriptome analysis of nine GC with current H. pylori infection (HpGC), three GC with previous H. pylori infection (ex-HpGC), six GC without H. pylori infection (non-HpGC), and six healthy controls (HC). We also investigated key cell players and molecular pathways associated with GC immunotherapy outcomes. We revealed the molecular heterogeneity of different cell components in GC including epithelium, immune cells, and cancer-associated fibroblasts (CAFs) at the single-cell level. The malignant epithelium of HpGC exhibited high expression level of inflammatory and epithelial-mesenchymal transition (EMT) signature, HpGC and ex-HpGC were enriched with VEGFA+ angiogenic tumor-associated macrophages (Angio-TAM) and IL11+ inflammatory CAF (iCAF), characterized by high expression levels of NECTIN2 and VEGFA/B. Additionally, we found significant correlations between the abundance of iCAF with Angio-TAM and TIGIT+ suppressive T cells, and iCAF interacted with Angio-TAM through the VEGF and ANGPTL angiogenic pathways. We also developed an immune signature and angiogenic signature and demonstrated that the iCAF abundance and angiogenic signature could predict poor immunotherapy outcomes in GC. We revealed the transcriptome characteristics and heterogeneity of various cellular constituents of HpGC and demonstrated that a synergistic combination of immunotherapy and anti-angiogenic targeted therapy may be an effective therapeutic modality for HpGC.

cancer biology↗

STING-dependent cytosolic DNA sensing pathway drives the progression to leukemia in TET2-mutated HSPCs

Somatic loss-of-function mutations of the dioxygenase Ten-eleven translocation-2 (TET2) occur frequently in individuals with clonal hematopoiesis (CH) and acute myeloid leukemia (AML). These common hematopoietic disorders can be recapitulated in mouse models. However, the underlying mechanisms by which the deficiency in TET2 promotes these disorders remain largely unknown. Here we show that the cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS)-stimulator of interferon genes (STING) pathway is activated to mediate the effect of TET2 deficiency in leukemogenesis in mouse models. DNA damage arising in Tet2-deficient hematopoietic stem/progenitor cells (HSPCs) leads to activation of the cGAS-STING pathway which in turn induces the development of CH and myeloid transformation. Notably, both pharmacological inhibition and genetic deletion of STING suppresses Tet2 mutation-induced aberrant myelopoiesis. In patient-derived xenograft (PDX) models, STING inhibition specifically attenuates the proliferation of leukemia cells from TET2-mutated individuals. These observations suggest that the hematopoietic transformation associated with TET2 mutations is powered through sterile inflammation dependent on the activated cGAS-STING pathway, and that STING may represent a potential target for intervention of relevant hematopoietic malignancies. Key pointsO_LITet2 deficiency leads to DNA damage which in turn activates the cGAS-STING pathway to induce an inflammatory response C_LIO_LIBlocking STING in TET2-mutated hematopoietic stem/progenitor cells suppresses clonal hematopoiesis in mice and leukemogenesis in patient-derived xenograft models C_LI

cancer biology↗

Large scale functional screen identifies genetic variants with splicing effects in modern and archaic humans

Humans co-existed and interbred with other hominins which later became extinct. These archaic hominins are known to us only through fossil records and for two cases, genome sequences. Here we engineer Neanderthal and Denisovan sequences into thousands of artificial genes to reconstruct the pre-mRNA processing patterns of these extinct populations. Of the 5,224 alleles tested in this massively parallel splicing reporter assay (MaPSy), we report 969 exonic splicing mutations (ESMs) that correspond to differences in exon recognition between extant and extinct hominins. Using MaPSy splicing variants, predicted splicing variants, and splicing quantitative trait loci, we show that splice-disrupting variants experienced greater purifying selection in anatomically modern humans than in Neanderthals. Adaptively introgressed variants were enriched for moderate effect splicing variants, consistent with positive selection for alternative spliced alleles following introgression. As particularly compelling examples, we characterized a novel tissue-specific alternative splicing variant at the adaptively introgressed innate immunity gene TLR1, as well as a novel Neanderthal introgressed alternative splicing variant in the gene HSPG2 that encodes perlecan. We further identified potentially pathogenic splicing variants found only in Neanderthals and Denisovans in genes related to sperm maturation and immunity. Finally, we found splicing variants that may contribute to variation among modern humans in total bilirubin, balding, hemoglobin levels, and lung capacity. Our findings provide novel insights into natural selection acting on splicing in human evolution and demonstrate how functional assays can be used to identify candidate causal variants underlying differences in gene regulation and phenotype.

genomics↗

Sequencing uracil in DNA at single-nucleotide resolution

As an aberrant base in DNA, uracil is generated by dUMP misincorporation or cytosine deamination, and involved in multiple physiological and pathological processes. Current methods for whole-genome mapping of uracil all rely on uracil-DNA N-glycosylase (UNG) and are limited in resolution or specificity. Here, we present a UNG-independent Single-Nucleotide resolution Uracil Sequencing (SNU-seq) method utilizing the UdgX protein which specifically excises the uracil and forms a covalent bond with the resulting deoxyribose. SNU-seq was validated on synthetic DNA and applied to mammalian genomes. We found that the uracil content of pemetrexed-treated cells fluctuated along with DNA replication timing. We also accurately detected uracil introduced through cytosine deamination by the cytosine base editor (nCas9-APOBEC) and verified uracil occurrence in "WRC" motif within Activation-Induced Cytidine Deaminase (AID) hotspot regions in CSR-activated UNG -/- B cells.

biochemistry↗

Plasma exosomal miRNA analysis of Alzheimer's disease reveals the dysfunction of a neural network

Exosomal microRNA (miRNA) is an emerging source for biomarkers of Alzheimers disease (AD). Here, we profiled miRNA expression in AD, mild cognitive impairment (MCI), and controls. The assessment and validation of differentially expressed miRNA represented their potential to be novel biomarkers for AD and MCI. We conducted 13 co-expression networks and a miRNA network module linked to neural function emerged as the most significantly associated with AD diagnosis. The conservation analysis revealed the M1 was highly preserved in controls but dysfunction in AD and MCI. The module pattern between MCI and NC was similar, but significantly differed from AD, suggesting that the neural network regulated by miRNA changed during the mild cognitive stage, and the total miRNA expression altered in AD stage. Additionally, 24 out of 26 M1 hub-miRNAs were derived from brain tissue, and 15 had been reported as AD biomarkers. We consequently proposed the other 11 miRNAs could play important roles in AD. Our study highlights that co-expression network analysis can provide a new path for finding novel biomarkers.

bioinformatics↗

SGLT2 inhibition by intraperitoneal dapagliflozin mitigates peritoneal fibrosis and ultrafiltration failure in a mouse model of chronic peritoneal exposure to high-glucose dialysate

Peritoneal dialysis (PD) is limited by glucose-mediated peritoneal membrane (PM) fibrosis, angiogenesis and ultrafiltration failure. Influencing PM integrity by pharmacologically targeting sodium-dependent glucose transporter (SGLT)-mediated glucose uptake has not been studied. In this study wildtype C57Bl/6N mice were treated with high-glucose dialysate via an intraperitoneal catheter, with or without addition of selective SGLT2 inhibitor dapagliflozin. PM structural changes, ultrafiltration capacity and PET status for glucose, urea and creatinine were analyzed. Expression of SGLT and GLUT was analyzed by real-time PCR, immunofluorescence and immunohistochemistry. Peritoneal effluents were analyzed for cellular and cytokine composition. We found that peritoneal SGLT2 was expressed in mesothelial cells and in skeletal muscle. Dapagliflozin significantly reduced effluent TGF-{beta} concentrations, peritoneal thickening and fibrosis as well as microvessel density, resulting in improved ultrafiltration, despite the fact that it did not affect development of high glucose transporter status. In vitro, dapagliflozin reduced monocyte chemoattractant protein-1 release under high glucose conditions in human and murine peritoneal mesothelial cells. Pro-inflammatory cytokine release in macrophages was reduced only when cultured in high glucose conditions with an additional inflammatory stimulus. In summary, dapagliflozin improved structural and functional peritoneal health in the context of high glucose PD.

molecular biology↗

Ecological load and balancing selection in circumboreal barnacles

Acorn barnacle adults experience environmental heterogeneity at various spatial scales of their circumboreal habitat, raising the question of how adaptation to high environmental variability is maintained in the face of strong juvenile dispersal and mortality. Here we show that 4% of genes in the barnacle genome experience balancing selection across the entire range of the species. Many of these genes harbor mutations maintained across 2 million years of evolution between the Pacific and Atlantic oceans. These genes are involved in ion regulation, pain reception, and heat tolerance, functions which are essential in highly variable ecosystems. The data also reveal complex population structure within and between basins, driven by the trans-Arctic interchange and the last glaciation. Divergence between Atlantic and Pacific populations is high, foreshadowing the onset of allopatric speciation, and suggesting that balancing selection is strong enough to maintain functional variation for millions of years in the face of complex demography.

evolutionary biology↗

ARG1 could be expressed by human, but not represent for repair

Arginase 1 (ARG1), typically expressed under stress or stimulation rather than in the healthy condition in humans. However, more and more studies claim ARG1 could be expressed by human and represents healing process. Including THP-1 monocyte shift to M2 macrophages rendered a higher expression of ARG1 than that with bone-graft has an ideal effect on anti-inflammation, resulting in tissue healing. With the higher expression of ARG1 seemingly induced by the constructed material and represented by the anti-inflammatory situation. For these reasons, this study focuses on whether traditional markers of macrophages could be express by human or not during clinical healing process. Through harvesting bone tissue samples during bone healing process and confirm the expression of markers at transcriptome and protein levels. The results showed the expression of ARG1 relatively low by bulk-RNA sequencing, quantitative polymerase chain reaction (qPCR), immunofluorescence (IF) and flow cytometry or could not be detected during process of healing of healthy donor. Taken together, results indicate that the ARG1 is not chosen for a regenerative marker in human bone tissue.

immunology↗

Single-cell-resolution transcriptome map of human, chimpanzee, bonobo, and macaque brains

Identification of gene expression traits unique to the human brain sheds light on the mechanisms of human cognition. Here we searched for gene expression traits separating humans from other primates by analyzing 88,047 cell nuclei and 422 tissue samples representing 33 brain regions of humans, chimpanzees, bonobos, and macaques. We show that gene expression evolves rapidly within cell types, with more than two-thirds of cell type-specific differences not detected using conventional RNA sequencing of tissue samples. Neurons tend to evolve faster in all hominids, but non-neuronal cell types, such as astrocytes and oligodendrocyte progenitors, show more differences on the human lineage, including alterations of spatial distribution across neocortical layers.

evolutionary biology↗

Localization of adaptive variants in human genomes using averaged one-dependence estimation

Statistical methods for identifying adaptive mutations from population-genetic data face several obstacles: assessing the significance of genomic outliers, integrating correlated measures of selection into one analytic framework, and distinguishing adaptive variants from hitchhiking neutral variants. Here, we introduce SWIF(r), a probabilistic method that detects selective sweeps by learning the distributions of multiple selection statistics under different evolutionary scenarios and calculating the posterior probability of a sweep at each genomic site. SWIF(r) is trained using simulations from a user-specified demographic model and explicitly models the joint distributions of selection statistics, thereby increasing its power to both identify regions undergoing sweeps and localize adaptive mutations. Using array and exome data from 45 {ddagger}Khomani San hunter-gatherers of southern Africa, we identify an enrichment of adaptive signals in genes associated with metabolism and obesity. SWIF(r) provides a transparent probabilistic framework for localizing beneficial mutations that is extensible to a variety of evolutionary scenarios.

evolutionary biology↗