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Transcriptomic characterization of the intestine in Stichopus monotuberculatus under gradient temperature stress and HSP gene family-mediated molecular adaptation.

The increasing frequency of extreme temperature events under climate change poses a growing threat to the stability of tropical sea cucumber aquaculture. To characterize the molecular responses of the tropical sea cucumber Stichopus monotuberculatus to acute temperature stress, juveniles were exposed for 96 h to 15 °C, 20 °C, 25 °C, 30 °C, and 35 °C, followed by transcriptomic profiling of the intestine. By transcriptomic analysis, 2258, 634, 1618, and 2980 differentially expressed genes (DEGs) were identified at 15, 20, 30, and 35 °C compared to control, respectively. More DEGs were generally detected at temperatures further from 25 °C, with the 35 °C group showing the largest transcriptional response. Although cold and heat stress both affected metabolism and protein homeostasis, their enrichment profiles differed. At 15 °C, DEGs were mainly enriched in the spliceosome and p53 signaling pathways, highlighting RNA processing and p53 signaling as prominent features of the cold-stress response. At 35 °C, DEGs were mainly enriched in the PI3K-Akt signaling pathway, ubiquitin-mediated proteolysis, and mitophagy, indicating enhanced regulation of cell survival, protein turnover, and mitochondrial quality control. HSP genes also responded differently to cold and heat stress. Most HSP70 and HSP90 family members were downregulated at low temperatures, whereas HSP70 genes and small heat shock proteins were markedly upregulated at high temperatures. Overall, the intestinal transcriptome showed distinct responses to cold and heat stress. These results identify pathways and HSP genes potentially involved in the temperature response of S. monotuberculatus and provide useful information for evaluating temperature tolerance and defining suitable temperatures for its aquaculture.

Heat shock protein

Targeting the bile acid receptor TGR5 with Gentiopicroside to activate Nrf2 antioxidant signaling and mitigate Parkinson's disease in an MPTP mouse model.

INTRODUCTION: Parkinson's disease (PD) is a common neurodegenerative disorder characterized by classical symptoms including bradykinesia, rest tremor and rigidity. Oxidative stress and mitochondrial dysfunction are recognized as pivotal factors in PD progression. Gentiopicroside (GPS), a secoiridoid derived from Gentiana manshurica Kitagawa, exhibits antioxidant and mitophagy induction properties. Nonetheless, the effects and mechanisms by which GPS mitigates neurodegeneration in PD remain to be thoroughly elucidated. OBJECTIVES: The goal of this study was to investigate the neuroprotective effects and mechanisms of GPS in PD models. METHODS: We established the MPTP/MPP+-induced PD models to measure the neuroprotection of GPS. Transcriptomic analysis, oxidative biochemical kits, western blot and cell immunofluorescence were conducted to elucidate the fundamental mechanisms at play. Subsequently, the targeting and activation of the transmembrane G protein-coupled receptor-5 (TGR5) by GPS were measured by molecular docking, cellular thermal shift assay, microscale thermophoresis (MST) and cyclic adenosine monophosphate (cAMP) quantitation. Finally, we verified whether the neuroprotective and antioxidant effects of GPS were dependent on TGR5 by using specific small interfering RNA (siRNA), pharmacological antagonist and knockout mice. RESULTS: GPS significantly attenuated dopaminergic (DAergic) neuron loss and restored motor function in the MPTP-induced PD mouse model. Whole-genome RNA sequencing and subsequent mechanistic investigations revealed that GPS enhanced the expression and facilitated nuclear entry of factor erythroid-related 2-factor 2 (Nrf2), and reduced oxidative stress and mitochondrial dysfunction stimulated by neurotoxin. Additionally, GPS could target TGR5 and prevent its downregulation in PD model. TGR5's silencing or inhibition weakened the neuroprotective effect of GPS and blocked GPS-mediated activation of Nrf2 antioxidant signaling in PD model. Moreover, the therapeutic effect of GPS in mitigating motor deficits and neurodegeneration was also abolished in Tgr5 knockout mice. CONCLUSION: These findings collectively indicated that GPS targeted TGR5 to activate Nrf2 antioxidant signaling and ultimately ameliorated the pathological progression of PD.

Animals

m6A-Mediated epitranscriptomic control of mitochondrial dysfunction in neurodegeneration.

Mitochondrial dysfunction is a common pathology of neurodegenerative diseases, which contributes to neuronal vulnerability via excessive oxidative stress, impaired bioenergetics, and dysregulated apoptosis. Emerging studies highlighted the critical role of epitranscriptomic RNA modifications, particularly N6-methyladenosine (m6A), in mitochondrial gene expression regulation and cellular stress responses. m6A modifications are installed by methyltransferases ("writers," METTL3/METTL14), recognized by reader proteins (YTH domain family proteins, IGF2BPs), and removed by demethylases ("erasers," FTO, ALKBH5), collectively orchestrating mRNA splicing, localization, stability, and translation. Recent evidence demonstrates that m6A modifications modulate both nuclear-encoded and mitochondrially encoded transcripts and regulate key mitochondrial processes, including fission/fusion dynamics, oxidative phosphorylation, mitophagy, and apoptosis. Dysregulation of m6A machinery disrupts mitochondrial homeostasis, exacerbates oxidative stress and neuroinflammation, and promotes neuronal loss. Importantly, pharmacological or genetic modulation of m6A regulators can restore mitochondrial function, inhibit caspase activation, and dampen pro-inflammatory signaling, underscoring their therapeutic potential. This review consolidates current insights into mitochondrial epitranscriptomics, emphasizing how m6A modifications act as central regulators of mitochondrial stress responses and neurodegeneration.

Humans

Firemaster 550 differentially alters gene expression underlying synaptic function in amygdala of prairie voles after gestational or lactational exposure.

Neurodevelopmental disorders often share similar behavioral diagnostic criteria including socioemotional and cognitive deficits. The prairie vole is a uniquely suitable model to study these deficits because they demonstrate strong social affiliation, bi-parental care, and partner attachment. Previously, we have shown that developmental exposure to the flame-retardant mixture Firemaster 550 (FM 550) impairs socioemotional behavior in the prairie vole and alters underlying neuroanatomy and function. However, the mechanisms for impaired pair bonding in males and increased anxiety in females remain unknown, along with the specific critical window(s) of vulnerability. Herein, we exposed prairie vole dams to FM 550 during gestation or lactation, and performed bulk RNA-seq on the amygdala, a hub of socioemotional processing, in their adult offspring. Two mathematically orthogonal methods were utilized for analysis, a linear statistical method and an ensemble machine learning method, incorporating sex as a biological variable. Gene ontology (GO) pathway analysis was performed following both and results compared to identify potential mechanisms of toxicity. GO results indicated consistent expression changes in the Synapse cellular component in all conditions, and implicated glutamatergic signaling specifically. Additionally, gestational exposure (GE) altered genes underlying modulation of synaptic transmission and neural development, while lactational exposure (LE) impacted genes underlying synaptic plasticity, axon guidance, and mitophagy. Machine learning identified disruption of endocrine system development, regulation of biosynthetic processes in GE animals, and suppression of various neuroinflammatory genes across multiple groups. Finally, we performed RNA expression analysis using Nanostring and demonstrated stronger correlation with the differentially expressed genes (DEG) of interest in females than males. Overall, this study demonstrates both the intersecting and distinct impacts of FM 550 exposure on amygdalar gene expression depending on sex and timing of exposure.

Animals

Transfer learning with multiomics integration and deep neural networks reveals drug resistance mechanisms in cancer.

Drug resistance remains one of the primary challenges in effective cancer therapy. In this study, we employed a deep neural network (DNN)-based transfer learning (TL) approach to predict drug response and uncover drug resistance mechanisms. We integrated gene expression, somatic mutation, and copy number aberration (CNA) data with drug response profiles using multi-omics integration (MI). We used the Genomics of Drug Sensitivity in Cancer (GDSC) data for training and incorporated drugs with same pathways into the training models. We then evaluated drug response predictions on independent in-vivo PDX Encyclopedia (PDX) and ex-vivo the Cancer Genome Atlas (TCGA) datasets. In addition, we conducted pathway enrichment analyses to elucidate the mechanisms underlying drug resistance for paclitaxel, 5-fluorouracil (5-FU), gemcitabine, and cetuximab. We also applied Fisher's exact test (FET) to assess potential associations between drug resistance and the presence of mutations or CNAs. Our pan-drug models outperformed other methods based on the area under the precision-recall curve (AUCPR). Our pathway enrichment analyses revealed LDHB-mediated pyruvate metabolism and FYN-mediated focal adhesion might have pivotal roles in paclitaxel resistance, while PINK1-mediated mitophagy might be critical in 5-FU resistance. In addition to transcriptional activation, FET suggested that CNAs in LDHB and PINK1 may also be associated with resistance to paclitaxel and 5-FU, respectively. Furthermore, enrichment results for paclitaxel and cetuximab indicated shared resistance mechanisms between the two drugs. Importantly, our findings are consistent with prior experimental studies, providing literature-based validation of our results. Overall, our DNN-based TL approach achieved strong predictive performance across PDX & TCGA datasets and enrichment analyses provided valuable biological insights into drug resistance mechanisms.

Humans

GiGCN: a network-based framework for uncovering synthetic lethal and viable genetic interactions.

Genetic interactions (GIs) underpin the functional connectivity of genes and pathways, and are important for dissecting genotype-phenotype relationships and identifying therapeutic targets for diseases. However, the scale of the human genome restricts systematic experimental interrogation of GIs. Existing computational tools focus on predicting synthetic lethality (SL) and synthetic viability (SV), the two primary forms of GIs, yet their accuracy and biological interpretability are compromised by inadequate modeling of the molecular mechanisms behind positive and negative interactions, as well as the limitation of negative samples. To overcome these challenges, we developed Genetic Interaction Graph Convolutional Network (GiGCN), a signed network modeling framework for the joint identification of gene pairs with SL and SV. We built a high-confidence signed genetic network by integrating verified GIs, and non-interacting gene pairs, together with gene semantic similarity derived from biological processes. By leveraging disentangled subspace decomposition, this framework separately models distinct functional dimensions within gene networks, enabling robust representation of context-dependent regulatory relationships and accurate discrimination of SL and SV events. Benchmark experiments demonstrate that GiGCN outperforms state-of-the-art approaches (area under receiver operating-characteristic curve: 0.978, and area under precision-recall curve: 0.944). Further analyses reveal biologically meaningful insights, including known and novel SL interactions centered on the oncogene MYC Proto-Oncogene (MYC), as well as SV interactions linked to autophagy and mitophagy pathways. This study provides a robust and interpretable network-based strategy for systematically exploring GIs. The GiGCN framework not only improves the precision of SL and SV prediction, but also offers mechanistic insights into gene functional relationships, thereby supporting the discovery of actionable therapeutic targets for cancer and other human diseases.

Humans

Innovative strategies for mitochondrial dysfunction in myeloproliferative neoplasms a step toward precision medicine.

Myeloproliferative neoplasms (MPNs) are clonal disorders of hematopoietic stem cells characterized by aberrant proliferation of myeloid lineages, driven primarily by mutations in JAK2, CALR, and myeloproliferative leukemia, leading to constitutive activation of the JAK-STAT pathway. Emerging evidence highlights mitochondrial dysfunction as a key factor in MPN pathogenesis, contributing to increased reactive oxygen species production, mitochondrial DNA mutations, and dysregulated mitochondrial dynamics, which collectively promote clonal expansion and apoptosis resistance. Targeting mitochondrial pathways has gained attention as a therapeutic strategy, with approaches including mitochondria-targeted antioxidants, metabolic inhibitors, and modulation of mitophagy and mitochondrial fission/fusion dynamics. However, challenges such as drug delivery specificity, therapeutic resistance, and off-target effects remain significant. Recent advances in precision medicine, incorporating genomic, transcriptomic, and proteomic profiling, offer a more personalized approach to MPN treatment by tailoring interventions to individual mutation patterns. Additionally, novel therapeutic strategies, including gene editing technologies, RNA-based therapies, and nanoparticle-mediated drug delivery systems, hold promise for overcoming current treatment limitations. The integration of artificial intelligence in drug discovery and biomarker identification further enhances the potential for targeted therapies. Future research should focus on refining these strategies, developing reliable biomarkers for patient stratification, and exploring combination therapies that enhance treatment efficacy while minimizing adverse effects. By addressing mitochondrial dysfunction as an underlying driver of MPNs, these emerging approaches have the potential to improve disease management, extend patient survival, and enhance quality of life. Also, this new approach of precision medicine allows patient stratification and ensures that treatments are formed according to the individual disease biology of each patient, which results in overall better outcomes.

combination drug therapy

Parkin Induces Ubiquitination and Large Extracellular Vesicle Release of HMGB1 to Activate Antitumor Immunity.

UNLABELLED: Parkin (PRKN) is a mitochondria-associated E3 ubiquitin ligase that mediates mitophagy and organelle quality control. More recently, PRKN has been implicated in stimulating antitumor immunity and reprogramming the tumor immune microenvironment. In this study, we showed that PRKN ubiquitinates the alarmin molecule, high-mobility group box-1 (HMGB1) on Lys146 (K146) using predominantly K48 linkages. By molecular modeling, the in-between-ring domain of PRKN (Gln326-Leu358) made extensive contacts with the amino-terminus A-box of HMGB1 (Met1-Ser42), forming a mitochondria-associated PRKN-HMGB1 complex that juxtaposes K146 to ubiquitin active site residues Gly76 and Arg74. Instead of proteasomal degradation, PRKN ubiquitination of K146 enabled the loading of HMGB1 but not HMGB1 K146A mutant, onto autophagy- and mitochondria-derived large extracellular vesicles (LEV). In turn, released PRKN-HMGB1-LEV stimulated a potent IFN and cytokine response in recipient cells, expanding CD8+ T-cell subsets with effector (CD69+/KLRG1+), self-renewal (TCF1+/PD-1+), and cytotoxic (KLRG1+/GrzB+) properties. Conditional expression of PRKN induced HMGB1 release, activated intratumoral CD8+ T cells, and suppressed syngeneic tumor growth in vivo in a response that was abolished by HMGB1 silencing. These data identify that PRKN-LEV-regulated release of HMGB1 reprograms antitumor immunity via stimulation of IFN signaling and expansion of specialized CD8+ T-cell subsets. SIGNIFICANCE: Parkin ubiquitinates the alarmin molecule HMGB1 to enable its regulated release in large extracellular vesicles that activate interferon signaling, expand specialized CD8+ T-cell subsets, and promote antitumor immunity.

HMGB1 Protein

Nanopore-based full-length transcriptome sequencing for understanding the underlying molecular mechanisms of rapid and slow progression of diabetes nephropathy.

BACKGROUND: Diabetic nephropathy (DN) has been a major factor in the outbreak of end-stage renal disease for decades. As the underlying mechanisms of DN development remains unclear, there is no ideal methods for the diagnosis and therapy. OBJECTIVE: We aimed to explore the key genes and pathways that affect the rate progression of DN. METHODS: Nanopore-based full-length transcriptome sequencing was performed with serum samples from DN patients with slow progression (DNSP, n = 5) and rapid progression (DNRP, n = 6). RESULTS: Here, transcriptome proclaimed 22,682 novel transcripts and obtained 45,808 simple sequence repeats, 1,815 transcription factors, 5,993 complete open reading frames, and 1,050 novel lncRNA from the novel transcripts. Moreover, a total of 341 differentially expressed transcripts (DETs) and 456 differentially expressed genes (DEGs) between the DNSP and DNRP groups were identified. Functional analyses showed that DETs mainly involved in ferroptosis-related pathways such as oxidative phosphorylation, iron ion binding, and mitophagy. Moreover, Functional analyses revealed that DEGs mainly involved in oxidative phosphorylation, lipid metabolism, ferroptosis, autophagy/mitophagy, apoptosis/necroptosis pathway. CONCLUSION: Collectively, our study provided a full-length transcriptome data source for the future DN research, and facilitate a deeper understanding of the molecular mechanisms underlying the differences in fast and slow progression of DN.

Humans

Programmed cell death and risk of diabetic retinopathy: a Mendelian randomization study.

BACKGROUND: Programmed cell death (PCD) plays an important role in diabetic retinopathy (DR); however, the underlying genetic mechanisms remain unclear. We used Mendelian randomization (MR) to investigate the causal relationships between PCD-related genes and DR. This study aimed to investigate the effects of PCD on the risk of DR by conducting MR analysis. METHODS: Summary statistics from gene expression quantitative trait loci (eQTL) studies (31,684 Europeans) were analyzed. Genetic instrumental variables were selected using cis-eQTL single-nucleotide polymorphisms (SNPs; P&#x2009;<&#x2009;5&#x2009;&#xd7;&#x2009;10-&#x2009;8). Summary data-based MR (SMR) was employed to assess causal associations between PCD-related genes and DR, with three additional MR methods used for sensitivity testing. Bayesian colocalization was used to examine the shared regulatory mechanisms between PCD QTLs and DR risk loci. RESULTS: Sensitivity and colocalization analyses revealed six genes that affected DR: cathepsin H (CTSH), NAD(P)H: quinone oxidoreductase 1 (NQO1), tribbles pseudokinase 3 (TRIB3), and phosphoglycerate mutase 5 (PGAM5), which increased DR risk, and iron-responsive element binding protein 2 (IREB2) and tumor necrosis factor (TNF), which exhibited protective effects. Multivariate MR confirmed significant causal effects for CTSH, IREB2, and PGAM5 (p&#x2009;<&#x2009;0.050). Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis (including 10 STRING-derived genes) revealed that 13 genes were enriched in necroptosis, apoptosis, mitophagy, and TNF signaling pathways in DR. CONCLUSIONS: This MR study supports the causal involvement of PCD in DR and identifies candidate genes (CTSH, IREB2, PGAM5, NQO1, TRIB3, and TNF) for therapeutic targeting or biomarker development in DR prevention or diagnosis.

Humans

Transcriptional and histopathological profiling of skeletal muscle in Bla/J mice at the stage of dysferlinopathy manifestation.

Dysferlinopathy is a rare muscular dystrophy characterized by chronic muscle damage and ineffective regeneration. While late-stage morphological changes, such as fibroadipose replacement, are well described, the early molecular mechanisms driving muscle fiber loss and regenerative failure at the onset of the disease remain largely uncharacterized. To address this gap, we investigated the skeletal muscles of dysferlin-deficient Bla/J mice during the early manifestation stage (3&#x2005;months of age). This exploratory study aimed to identify primary pathomorphogenetic events by correlating the transcriptomic profile of the tissue with its specific histopathological and ultrastructural alterations. We performed a comparative analysis of the m. gastrocnemius in 3-month-old Bla/J mice versus wild-type controls using RNA sequencing, RT-qPCR, histomorphometry and transmission electron microscopy. The results revealed atrophy and muscle fiber necrosis without the expected induction of Fbxo32 and Trim63 ubiquitin ligases, suggesting ubiquitin-proteasome system-independent muscle mass loss. Furthermore, the absence of Casp3, Bak1, and Bad induction, confirmed by the lack of active caspase-3, excluded apoptosis as the primary death mechanism. A differentiation block in satellite cells was confirmed by the lack of Myf5, Myod1, and Myog induction and a trend toward Tead4 suppression, pointing to an early failure of the reparative program. Exploratory RNA sequencing also identified a suppression of Prkn expression accompanied by LC3B-II-positive autophagosome accumulation. Immunohistochemical and immunofluorescent evaluation of the mitochondrial network (TOMM20) revealed abnormal accumulations and dense clumping, indicating impaired organelle clearance. Furthermore, ultrastructural analysis demonstrated internal organelle damage and the presence of myelin-like structures, consistent with a state of stalled mitophagy. Collectively, this exploratory study demonstrates that early muscle atrophy and myofiber necrosis in dysferlinopathy occur independently of canonical ubiquitin-proteasome and apoptotic pathways. Instead, the disease manifestation stage is structurally characterized by stalled mitochondrial clearance and a delayed regenerative response.

Animals

Autophagy in the Regulation of Placental Development: From Trophoblast Differentiation to Metabolic Stress Adaptation.

Successful pregnancy depends on precise placental development, where trophoblast differentiation, syncytialization, invasion, and adaptation to metabolic stress are critical. Autophagy, a lysosome-mediated degradation pathway, has emerged as an important regulator of cellular homeostasis, yet its integrated role in trophoblast fate and functions has not been comprehensively summarised. This review synthesises current evidence on autophagy's functions throughout placentation, from trophoblast differentiation to syncytialization and extravillous trophoblast invasion. We examine how autophagy enables cellular remodelling during differentiation, supports metabolic adaptation under hypoxia and nutrient stress, and maintains mitochondrial quality control through selective mitophagy. Autophagy is essential for syncytiotrophoblast formation via endoplasmic reticulum stress-coordinated activation and p53 downregulation. However, its effects on trophoblast invasion are context-dependent, influenced by oxygen tension, autophagic flux completeness, and differentiation state, which can potentially be shaped by parent-offspring genetic conflicts through genomic imprinting. Both excessive and insufficient autophagy contribute to pregnancy complications, including pre-eclampsia, foetal growth restriction, gestational diabetes mellitus, preterm birth, recurrent spontaneous abortion and obstetric antiphospholipid syndrome through distinct molecular mechanisms. Autophagy functions as a dynamically tuned homeostatic mechanism in placental development. Understanding condition-specific autophagy dysregulation is thereby crucial for improving pregnancy outcomes.

Autophagy

Activation of pro-survival autophagy by a small molecule promoting p62 oligomerization.

Autophagy is a critical mechanism of cellular quality control, orchestrated by selective autophagy receptor (SAR) proteins. Pharmacologically enhancing the cargo-targeting capacity of SARs presents an attractive but underexplored strategy for the precise therapeutic activation of autophagy. Here, we characterize SQ-1, a small-molecule activator of autophagy that engages the prototypical SAR protein p62/sequestosome-1 (SQSTM1). We show that SQ-1 sensitizes p62 to oxidation and promotes its disulfide-mediated oligomerization in response to mitochondrial reactive oxygen species (ROS). This ROS-dependent activation of p62-mediated selective autophagy enhances the clearance of ROS-generating mitochondria and restores cell viability in models of Niemann-Pick type C1 disease, which is marked by impaired autophagic flux. In summary, the unique mode of action of SQ-1 enables self-regulated autophagy activation, offering a potential therapeutic strategy for lysosomal storage disorders and a broader spectrum of age-related diseases characterized by defective autophagy.

Niemann-Pick type C1 disease

Quantitative Proteomic Analysis of APP/PS1 Transgenic Mice.

BACKGROUND: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder affecting the central nervous system (CNS), with its etiology still shrouded in uncertainty. The interplay of extracellular amyloid-&#x3b2; (A&#x3b2;) deposition, intracellular neurofibrillary tangles (NFTs) composed of tau protein, cholinergic neuronal impairment, and other pathogenic factors is implicated in the progression of AD. OBJECTIVE: The current study endeavors to delineate the proteomic landscape alterations in the hippocampus of an AD murine model, utilizing proteomic analysis to identify key physiological and pathological shifts induced by the disease. This endeavor aims to shed light on the underlying pathogenic mechanisms, which could facilitate early diagnosis and pave the way for novel therapeutic interventions for AD. METHODS: To dissect the proteomic perturbations induced by A&#x3b2; and Presenilin-1 (PS1) in the AD pathogenesis, we undertook a label-free quantitative (LFQ) proteomic analysis focusing on the hippocampal proteome of the APP/PS1 transgenic mouse model. Employing a multi-faceted approach that included differential protein functional enrichment, cluster analysis, and protein-protein interaction (PPI) network analysis, we conducted a comprehensive comparative proteomic study between APP/PS1 transgenic mice and their wild-type C57BL/6 counterparts. RESULTS: Mass spectrometry identified a total of 4817 proteins in the samples, with 2762 proteins being quantifiable. Comparative analysis revealed 396 proteins with differential expression between the APP/PS1 and control groups. Notably, 35 proteins exhibited consistent temporal regulation trends in the hippocampus, with concomitant alterations in biological pathways and PPI networks. CONCLUSIONS: This study presents a comparative proteomic profile of transgenic (APP/PS1) and wild-type mice, highlighting the proteomic divergences. Furthermore, it charts the trajectory of proteomic changes in the AD mouse model across the developmental stages from 2 to 12 months, providing insights into the physiological and pathological implications of the disease-associated genetic mutations.

Animals