The Antiviral and Cancer Genomic DNA Deaminase APOBEC3H Is Regulated by an RNA-Mediated Dimerization Mechanism.

Human APOBEC3H and homologous single-stranded DNA cytosine deaminases are unique to mammals. These DNA-editing enzymes function in innate immunity by restricting the replication of viruses and transposons. APOBEC3H also contributes to cancer mutagenesis. Here, we address the fundamental nature of RNA in regulating human APOBEC3H activities. APOBEC3H co-purifies with RNA as an inactive protein, and RNase A treatment enables strong DNA deaminase activity. RNA-binding-defective mutants demonstrate clear separation of function by becoming DNA hypermutators. Biochemical and crystallographic data demonstrate a mechanism in which double-stranded RNA mediates enzyme dimerization. Additionally, APOBEC3H separation-of-function mutants show that RNA binding is required for cytoplasmic localization, packaging into HIV-1 particles, and antiviral activity. Overall, these results support a model in which structured RNA negatively regulates the potentially harmful DNA deamination activity of APOBEC3H while, at the same time, positively regulating its antiviral activity.

Downregulation of the m6A reader YTHDC2 upregulates exosome content in lung adenocarcinoma via inhibiting IFIT and OAS family members.

N6-Methyladenosine (m6A) is the most prevalent mRNA modification. Its biological function primarily relies on its "Reader" protein, such as YTHDC2. Previous studies have shown that YTHDC2 downregulation is a procarcinogenic phenomenon in lung adenocarcinoma (LUAD). However, further investigation is needed to understand the molecular mechanisms of downstream genes and the associated biological phenomena following YTHDC2 downregulation. Here, we found that YTHDC2 knockout upregulated exosome content in LUAD. Following YTHDC2 knockout, the mRNA levels of OAS family members (OASs) and IFIT family members (IFITs) also decreased; and inhibition of OASs and IFITs could promote exosome content. Several m6A modification sites on the NT domain of OASs and the TPR12 domain of IFITs were found to increase the stability of OASs and IFITs in a YTHDC2-dependent manner. OASs and IFITs affected exosome content through target genes including RAB5A, RAB7, and RAB11A, and three arginine (R) amino acids on IFITs were critical for combination IFITs with targeted RAB mRNAs and subsequent degradation. Simultaneously, OASs degraded targeted RABs through RNAseL. Additionally, mutual bindings between OASs and IFITs were critical for their target gene degradation. Collectively, the above findings might provide a theoretical basis for the treatment of LUAD patients with low YTHDC2 expression.

Epigenetic modification of a pectin methylesterase gene activates apoplastic iron reutilization in tomato roots.

Iron (Fe) distribution and reutilization are crucial for maintaining Fe homeostasis in plants. Here, we demonstrate that the tomato (Solanum lycopersicum) Colorless nonripening (Cnr) epimutant exhibits increased Fe retention in cell wall pectin due to an increase in pectin methylesterase (PME) activity. This ultimately leads to Fe deficiency responses even under Fe-sufficient conditions when compared to the wild type (WT). Whole-genome bisulfite sequencing revealed that modifications to cell wall-related genes, especially CG hypermethylation in the intron region of PECTIN METHYLESTERASE53 (SlPME53), are involved in the Cnr response to Fe deficiency. When this intron hypermethylation of SlPME53 was artificially induced in WT, we found that elevated SlPME53 expression was accompanied by increased PME activity and increased pectin-Fe retention. The manipulation of SlPME53, either through overexpression in WT or knockdown in Cnr, influenced levels of pectin methylesterification and accumulation of apoplast Fe in roots. Moreover, CG hypermethylation mediated by METHYLTRANSFERASE1 (SlMET1) increased SlPME53 transcript abundance, resulting in greater PME activity and higher Fe retention in cell wall pectin. Therefore, we conclude that the Cnr mutation epigenetically modulates SlPME53 expression by SlMET1-mediated CG hypermethylation, and thus the capacity of the apoplastic Fe pool, creating opportunities for genetic improvement of crop mineral nutrition.

On the identification of differentially-active transcription factors from ATAC-seq data.

ATAC-seq has emerged as a rich epigenome profiling technique, and is commonly used to identify Transcription Factors (TFs) underlying given phenomena. A number of methods can be used to identify differentially-active TFs through the accessibility of their DNA-binding motif, however little is known on the best approaches for doing so. Here we benchmark several such methods using a combination of curated datasets with various forms of short-term perturbations on known TFs, as well as semi-simulations. We include both methods specifically designed for this type of data as well as some that can be repurposed for it. We also investigate variations to these methods, and identify three particularly promising approaches (a chromVAR-limma workflow with critical adjustments, monaLisa and a combination of GC smooth quantile normalization and multivariate modeling). We further investigate the specific use of nucleosome-free fragments, the combination of top methods, and the impact of technical variation. Finally, we illustrate the use of the top methods on a novel dataset to characterize the impact on DNA accessibility of TRAnscription Factor TArgeting Chimeras (TRAFTAC), which can deplete TFs-in our case NFkB-at the protein level.

Ten simple rules for computational biologists collaborating with wet lab researchers.

Computational biologists are frequently engaged in collaborative data analysis with wet lab researchers. These interdisciplinary projects, as necessary as they are to the scientific endeavor, can be surprisingly challenging due to cultural differences in operations and values. In this Ten Simple Rules guide, we aim to help dry lab researchers identify sources of friction and provide actionable tools to facilitate respectful, open, transparent, and rewarding collaborations.

Identification of pyruvic and maleic acid as potential markers for disease activity and prognosis in chronic urticaria.

BACKGROUND: Population-based studies have highlighted the link between chronic urticaria (CU) and metabolic syndrome, and metabolic alterations have been revealed in CU. However, to our knowledge, a comprehensive metabolomics study on a large cohort of patients with CU has not been reported. OBJECTIVE: We sought to explore the underlying metabolic subtypes and novel metabolite biomarkers for CU diagnosis and therapy. METHODS: Plasma samples from 80 patients with CU and 82 healthy controls were collected for metabolomics quantification and bioinformatics analysis. Another independent cohort consisting of 144 patients with CU was studied to validate the findings. Bone marrow-derived mast cells and mice with IgE-induced passive cutaneous anaphylaxis were used for in vitro and in vivo experiments, respectively. RESULTS: We observed clear metabolome differences between CU patients and healthy controls. Meanwhile, differential metabolites N6-acetyl-l-lysine, l-aspartate, maleic acid, and pyruvic acid were used to construct random forest classifiers and achieved area under receiver operating characteristic curve values greater than 0.85, suggesting their potential as diagnostic biomarkers of CU. More importantly, by exploring the underlying metabolic subtypes of CU, we found that the low abundance of pyruvic acid and maleic acid was significantly related to the activity of CU, poor efficacy of second-generation H1 antihistamines, and short relapse-free time. The results were validated in the independent cohort. Moreover, supplementation with pyruvate or maleate could significantly attenuate IgE-mediated mast cell activation in vitro and in vivo. CONCLUSIONS: Plasma pyruvic acid and maleic acid may be effective biomarkers for predicting disease activity, therapeutic efficacy, and prognosis for patients with CU.

Real-Time Simulation of the Reaction Kinetics of Supported Metal Nanoparticles.

A common issue with supported metal catalysts is the sintering of metal nanoparticles, resulting in catalyst deactivation. In this study, we propose a theoretical framework for realizing a real-time simulation of the reactivity of supported metal nanoparticles during the sintering process, combining density functional theory calculations, microkinetic modeling, Wulff-Kaichew construction, and sintering kinetic simulations. To validate our approach, we demonstrate its feasibility on α-Al2O3(0001)-supported Ag nanoparticles, where the simulated sintering behavior and ethylene epoxidation reaction rate as a function of time show qualitative agreement with experimental observation. Our proposed theoretical approach can be employed to screen out the promising microstructure feature of α-Al2O3 for stable supported Ag NPs, including the surface orientation and promoter species modified on it. The outlined approach of this work may be applied to a range of different thermocatalytic reactions other than ethylene epoxidation and provide guidance for the development of supported metal catalysts with long-term stability.

GCphase: an SNP phasing method using a graph partition and error correction algorithm.

BACKGROUND: The utilization of long reads for single nucleotide polymorphism (SNP) phasing has become popular, providing substantial support for research on human diseases and genetic studies in animals and plants. However, due to the complexity of the linkage relationships between SNP loci and sequencing errors in the reads, the recent methods still cannot yield satisfactory results. RESULTS: In this study, we present a graph-based algorithm, GCphase, which utilizes the minimum cut algorithm to perform phasing. First, based on alignment between long reads and the reference genome, GCphase filters out ambiguous SNP sites and useless read information. Second, GCphase constructs a graph in which a vertex represents alleles of an SNP locus and each edge represents the presence of read support; moreover, GCphase adopts a graph minimum-cut algorithm to phase the SNPs. Next, GCpahse uses two error correction steps to refine the phasing results obtained from the previous step, effectively reducing the error rate. Finally, GCphase obtains the phase block. GCphase was compared to three other methods, WhatsHap, HapCUT2, and LongPhase, on the Nanopore and PacBio long-read datasets. The code is available from https://github.com/baimawjy/GCphase . CONCLUSIONS: Experimental results show that GCphase under different sequencing depths of different data has the least number of switch errors and the highest accuracy compared with other methods.

Association of Anticoagulant Use With Hemorrhage Location and Etiology in Incident Spontaneous Intracerebral Hemorrhage.

BACKGROUND: It is unknown whether hypertensive microangiopathy or cerebral amyloid angiopathy (CAA) predisposes more to anticoagulant-associated intracerebral hemorrhage (AA-ICH). The purpose of our study was to determine whether AA-ICH is associated with lobar location and probable CAA. METHODS: This was a cross-sectional analysis of patients with first-ever spontaneous ICH admitted to a tertiary hospital in Boston, between 2008 and 2023. Univariable and multivariable logistic regression were used to investigate the association between anticoagulation use and both lobar hemorrhage location and probable CAA on magnetic resonance imaging (MRI) by Boston Criteria 2.0 or computed tomography by Simplified Edinburgh Criteria. RESULTS: A total of 1104 patients (mean [SD] age, 73 [12]; 499 females [45.0%]) were included. Of the 1104 patients, 268 (24.3%) had AA-ICH: 148 (55.2%) with vitamin K antagonists and 107 (39.9%) with direct oral anticoagulants. Brain MRI was performed in 695 (63.0%) patients. The proportion of patients with lobar hemorrhage was not different between those with and without AA-ICH (121/268 [45.1%] versus 424/836 [50.7%]; odds ratio [OR], 0.80 [95% CI, 0.61-1.05]; P=0.113). Patients with AA-ICH were less likely to have probable CAA on MRI (17/146 [11.6%] versus 127/549 [23.1%]; OR, 0.44 [95% CI, 0.25-0.75]; P=0.002) and probable CAA on MRI or computed tomography if MRI not performed (27/268 [10.0%] versus 200/836 [23.9%]; OR, 0.36 [95% CI, 0.23-0.55]; P<0.001). Among patients with AA-ICH, there were no differences in the proportion with lobar hemorrhage (63/148 [42.6%] versus 46/107 [43.0%]; OR, 1.02 [95% CI, 0.62-1.68]; P=0.946) or probable CAA on MRI (10/72 [13.9%] versus 7/69 [10.1%]; OR, 0.70 [95% CI, 0.25-1.96]; P=0.495) between vitamin K antagonists and direct oral anticoagulant users. CONCLUSIONS: AA-ICH was not associated with lobar hemorrhage location but was associated with reduced odds of probable CAA. These results suggest that hypertensive microangiopathy may predispose more toward incident AA-ICH than CAA and emphasize the importance of blood pressure control among anticoagulant users. These findings require replication in additional cohorts.

3D genome contributes to MHC-II neoantigen prediction.

Reliable and ultra-fast DNA and RNA sequencing have been achieved with the emergence of high-throughput sequencing technology. When combining the results of DNA and RNA sequencing for tumor cells of cancer patients, neoantigens that potentially stimulate the immune response of either CD4+ or CD8+ T cells can be identified. However, due to the abundance of somatic mutations and the high polymorphic nature of human leukocyte antigen (HLA) it is challenging to accurately predict the neoantigens. Moreover, comparing to HLA-I presented peptides, the HLA-II presented peptides are more variable in length, making the prediction of HLA-II loaded neoantigens even harder. A number of computational approaches have been proposed to address this issue but none of them considers the DNA origin of the neoantigens from the perspective of 3D genome. Here we investigate the DNA origins of the immune-positive and non-negative HLA-II neoantigens in the context of 3D genome and discovered that the chromatin 3D architecture plays an important role in more effective HLA-II neoantigen prediction. We believe that the 3D genome information will help to increase the precision of HLA-II neoantigen discovery and eventually benefit precision and personalized medicine in cancer immunotherapy.

A Chemoenzymatic Method Enables Global Enrichment and Characterization of Protein Arginine Methylation.

Arginine methylation is one of the most important post-translational modifications involved in the regulation of numerous biological processes. To better understand the biological significance of arginine methylation, enrichment methods need to be developed to analyze the methylated proteome at large-scale. Unfortunately, the prevailing enrichment method based on immunoaffinity purification can only enrich a subset of them due to the lack of pan-specific antibodies. Therefore, it is crucial to develop a stable and efficient antibody-free approach for the global analysis of arginine methylation. In this study, we developed a chemoenzymatic method for the simultaneous identification of mono- and dimethylated arginine. Totally, we identified 1006 arginine methylation events in Jurkat T cells, corresponding to 645 dimethylated sites and 361 monomethylated sites. We further applied the developed approach to global identification of the substrate proteins regulated by type I protein arginine methyltransferases (PRMTs) and identified 49 substrate proteins of type I PRMTs, which will facilitate a better understanding of PRMTs-regulated biological processes. Given the robust performance of this method, it would have broad application in methylproteomics analysis.

Micro Reference Electrode with an Ultrathin Ionic Path.

Reference electrode (RE) plays the core role in accurate potential control in electrochemistry. However, nanoresolved electrochemical characterization techniques still suffer from unstable potential control of pseudo-REs, because the commercial RE is too large to be used in the tiny electrochemical cell, and thus only pseudo-RE can be used. Therefore, microsized RE with a stable potential is urgently required to push the nanoresolved electrochemical measurements to a new level of accuracy and precision, but it is quite challenging to reproducibly fabricate such a micro RE until now. Here, we revisited the working mechanism of the metal-junction RE and clearly revealed the role of the ionic path between the metal wire and the borosilicate glass capillary to maintain a stable potential of RE. Based on this understanding, we developed a method to fabricate micro ultrastable-RE, where a reproducible ultrathin ionic path can form by dissolving a sandwiched sacrificial layer between the Pt wire and the capillary for the ion transfer. The potential of this new micro RE was almost the same as that of the commercial Ag/AgCl electrode, while the size is much smaller. Different from commercial REs that must be stored in the inner electrolyte, the new RE could be directly stored in air for more than one year without potential drift. Eventually, we successfully applied the micro RE in the electrochemical tip-enhanced Raman spectroscopy (EC-TERS) measurement to precisely control the potential of the working electrode, which makes it possible to compare the results from different laboratories and techniques to better understand the electrochemical interface at the nanoscale.

Deep learning-guided adjuvant chemotherapy selection for elderly patients with breast cancer.

PURPOSE: The efficacy of adjuvant chemotherapy in elderly breast cancer patients is currently controversial. This study aims to provide personalized adjuvant chemotherapy recommendations using deep learning (DL). METHODS: Six models with various causal inference approaches were trained to make individualized chemotherapy recommendations. Patients who received actual treatment recommended by DL models were compared with those who did not. Inverse probability treatment weighting (IPTW) was used to reduce bias. Linear regression, IPTW-adjusted risk difference (RD), and SurvSHAP(t) were used to interpret the best model. RESULTS: A total of 5352 elderly breast cancer patients were included. The median (interquartile range) follow-up time was 52 (30-80) months. Among all models, the balanced individual treatment effect for survival data (BITES) performed best. Treatment according to following BITES recommendations was associated with survival benefit, with a multivariate hazard ratio (HR) of 0.78 (95% confidence interval (CI): 0.64-0.94), IPTW-adjusted HR of 0.74 (95% CI: 0.59-0.93), RD of 12.40% (95% CI: 8.01-16.90%), IPTW-adjusted RD of 11.50% (95% CI: 7.16-15.80%), difference in restricted mean survival time (dRMST) of 12.44 (95% CI: 8.28-16.60) months, IPTW-adjusted dRMST of 7.81 (95% CI: 2.93-11.93) months, and p value of the IPTW-adjusted Log-rank test of 0.033. By interpreting BITES, the debiased impact of patient characteristics on adjuvant chemotherapy was quantified, which mainly included breast cancer subtype, tumor size, number of positive lymph nodes, TNM stages, histological grades, and surgical type. CONCLUSION: Our results emphasize the potential of DL models in guiding adjuvant chemotherapy decisions for elderly breast cancer patients.

Adverse pregnancy outcomes and multiple cancers risk in both mother and offspring: an umbrella review of systematic reviews with meta-analyses of observational studies.

BACKGROUND: Adverse pregnancy outcomes have reached epidemic proportions in recent years with serious health ramifications, especially for diverse cancers risk. Therefore, we carried out an umbrella review to systematically evaluate the validity and strength of the data and the extent of potential biases of the established association between adverse pregnancy outcomes and cancers risk in both mother and offspring. METHODS: PubMed, Embase, and Web of Science databases were searched from inception until 18 January 2024. Meta-analyses of observational studies investigating the relationship between adverse pregnancy outcomes and multiple cancers risk in both mother and offspring were included. Evidence certainty was assessed using Grading of Recommendations, Assessment, Development, and Evaluation. The protocol for this umbrella review was prospectively registered in PROSPERO (CRD42023470544). RESULTS: The search identified 129 meta-analyses of observational studies and 42 types of cancer. Moderate certainty of evidence, exhibiting statistical significance, has been observed linking per kilogram increase in birth weight to a heightened risk of breast cancer (OR = 1.07, 95% CI = 1.02-1.12), prostate cancer (OR = 1.02, 95% CI = 1.00-1.05), leukemia (OR = 1.18, 95% CI = 1.13-1.23), and acute lymphoblastic leukemia in offspring (OR = 1.18, 95% CI = 1.12-1.23); rubella infection during pregnancy to an increased risk of leukemia in offspring (OR = 2.79, 95% CI = 1.16-6.71); and a linear dose-response association between an increase in the proportion of optimal birth weight and an elevated risk of acute lymphoblastic leukemia in offspring (OR = 1.16, 95% CI = 1.09-1.24), respectively. CONCLUSIONS: Although some adverse pregnancy outcomes have clinically promising associations with risk of several cancers in both mother and offspring, it is essential to conduct additional research to solidify the evidence, evaluate causality, and ascertain clinical utility.

Multifunctional Carbon Dots for Biomedical Applications: Diagnosis, Therapy, and Theranostic.

Designing suitable nanomaterials is an ideal strategy to enable early diagnosis and effective treatment of diseases. Carbon dots (CDs) are luminescent carbonaceous nanoparticles that have attracted considerable attention. Through facile synthesis, they process properties including tunable light emission, low toxicity, and light energy transformation, leading to diverse applications as optically functional materials in biomedical fields. Recently, their potentials have been further explored, such as enzyme-like activity and ability to promote osteogenic differentiation. Through refined synthesizing strategies carbon dots, a rich treasure trove for new discoveries, stand a chance to guide significant development in biomedical applications. In this review, the authors start with a brief introduction to CDs. By presenting mechanisms and examples, the authors focus on how they can be used in diagnosing and treating diseases, including bioimaging failure of tissues and cells, biosensing various pathogenic factors and biomarkers, tissue defect repair, anti-inflammation, antibacterial and antiviral, and novel oncology treatment. The introduction of the application of integrated diagnosis and treatment follows closely behind. Furthermore, the challenges and future directions of CDs are discussed. The authors hope this review will provide critical perspectives to inspire new discoveries on CDs and prompt their advances in biomedical applications.

Molybdenum-Doped Cobalt-Free Cathode Realizing the Electrochemical Stability by Enhanced Covalent Bonding.

The doping strategy effectively enhances the capacity and cycling stability of cobalt-free nickel-rich cathodes. Understanding the intrinsic contributions of dopants is of great importance to optimize the performances of cathodes. This study investigates the correlation between the structure modification and their performances of Mo-doped LiNi0.8Mn0.2O2 (NM82) cathode. The role of doped Mo's valence state has been proved functional in both lattice structural modification and electronic state adjustment. Although the high-valence of Mo at the cathode surface inevitably reduces Ni valence for electronic neutrality and thus causes ion mixing, the original Mo valence will influence its diffusion depth. Structural analyses reveal Mo doping leads to a mixed layer on the surface, where high-valence Mo forms a slender cation mixing layer, enhancing structural stability and Li-ion transport. In addition, it is found that the high-valence dopant of Mo6+ ions partially occupies the unfilled 4d orbitals, which may strengthen the Mo─O bond through increased covalency and therefore reduce the oxygen mobility. This results in an impressive capacity retention (90.0% after 200 cycles) for Mo-NM82 cathodes with a high Mo valence state. These findings underscore the valence effect of doping on layered oxide cathode performance, offering guidance for next-generation cathode development.

Proximity-Dependent Activation of Split DNAzyme Kinase.

Binary (also known as split) nucleic acid enzymes have emerged as novel tools in biosensors. We report a new split strategy to split the DNAzyme kinase into two independent and non-functional fragments, denoted Dk1sub and Dk1enz. In the presence of the specific target, their free ends are brought sufficiently close to interact with each other without the formation of Watson-Crick base pairings between Dk1sub and Dk1enz, thus allowing the DNA phosphorylation reaction. We term this approach proximity-dependent activation of split DNAzyme kinase (ProxSDK). The utility of ProxSDK is demonstrated by engineering a biosensing system that is capable of measuring specific DNA-protein interactions. We envision that the approach described herein will find useful applications in biosensing, imaging, and clinical diagnosis.

StreamSAXS: a Python-based workflow platform for processing streaming SAXS/WAXS data.

StreamSAXS is a Python-based small- and wide-angle X-ray scattering (SAXS/WAXS) data analysis workflow platform with graphical user interface (GUI). It aims to provide an interactive and user-friendly tool for analysis of both batch data files and real-time data streams. Users can easily create customizable workflows through the GUI to meet their specific needs. One characteristic of StreamSAXS is its plug-in framework, which enables developers to extend the built-in workflow tasks. Another feature is the support for both already acquired and real-time data sources, allowing StreamSAXS to function as an offline analysis platform or be integrated into large-scale acquisition systems for end-to-end data management. This paper presents the core design of StreamSAXS and provides user cases demonstrating its utilization for SAXS/WAXS data analysis in offline and online scenarios.

Rab32 facilitates Schwann cell pyroptosis in rats following peripheral nerve injury by elevating ROS levels.

BACKGROUND: Peripheral nerve injury (PNI) is commonly observed in clinical practice, yet the underlying mechanisms remain unclear. This study investigated the correlation between the expression of a Ras-related protein Rab32 and pyroptosis in rats following PNI, and potential mechanisms have been explored by which Rab32 may influence Schwann cells pyroptosis and ultimately peripheral nerve regeneration (PNR) through the regulation of Reactive oxygen species (ROS) levels. METHODS: The authors investigated the induction of Schwann cell pyroptosis and the elevated expression of Rab32 in a rat model of PNI. In vitro experiments revealed an upregulation of Rab32 during Schwann cell pyroptosis. Furthermore, the effect of Rab32 on the level of ROS in mitochondria in pyroptosis model has also been studied. Finally, the effects of knocking down the Rab32 gene on PNR were assessed, morphology, sensory and motor functions of sciatic nerves, electrophysiology and immunohistochemical analysis were conducted to assess the therapeutic efficacy. RESULTS: Silencing Rab32 attenuated PNI-induced Schwann cell pyroptosis and promoted peripheral nerve regeneration. Furthermore, our findings demonstrated that Rab32 induces significant oxidative stress by damaging the mitochondria of Schwann cells in the pyroptosis model in vitro. CONCLUSION: Rab32 exacerbated Schwann cell pyroptosis in PNI model, leading to delayed peripheral nerve regeneration. Rab32 can be a potential target for future therapeutic strategy in the treatment of peripheral nerve injuries.

WTAP-mediated m6A modification of lncRNA Snhg1 improves myocardial ischemia-reperfusion injury via miR-361-5p/OPA1-dependent mitochondrial fusion.

BACKGROUND: Myocardial ischemia-reperfusion injury (MIRI) is caused by reperfusion after ischemic heart disease. LncRNA Snhg1 regulates the progression of various diseases. N6-methyladenosine (m6A) is the frequent RNA modification and plays a critical role in MIRI. However, it is unclear whether lncRNA Snhg1 regulates MIRI progression and whether the lncRNA Snhg1 was modified by m6A methylation. METHODS: Mouse cardiomyocytes HL-1 cells were utilized to construct the hypoxia/reoxygenation (H/R) injury model. HL-1 cell viability was evaluated utilizing CCK-8 method. Cell apoptosis, mitochondrial reactive oxygen species (ROS), and mitochondrial membrane potential (MMP) were quantitated utilizing flow cytometry. RNA immunoprecipitation and dual-luciferase reporter assays were applied to measure the m6A methylation and the interactions between lncRNA Snhg1 and targeted miRNA or target miRNAs and its target gene. The I/R mouse model was constructed with adenovirus expressing lncRNA Snhg1. HE and TUNEL staining were used to evaluate myocardial tissue damage and apoptosis. RESULTS: LncRNA Snhg1 was down-regulated after H/R injury, and overexpressed lncRNA Snhg1 suppressed H/R-stimulated cell apoptosis, mitochondrial ROS level and polarization. Besides, lncRNA Snhg1 could target miR-361-5p, and miR-361-5p targeted OPA1. Overexpressed lncRNA Snhg1 suppressed H/R-stimulated cell apoptosis, mitochondrial ROS level and polarization though the miR-361-5p/OPA1 axis. Furthermore, WTAP induced lncRNA Snhg1 m6A modification in H/R-stimulated HL-1 cells. Moreover, enforced lncRNA Snhg1 repressed I/R-stimulated myocardial tissue damage and apoptosis and regulated the miR-361-5p and OPA1 levels. CONCLUSION: WTAP-mediated m6A modification of lncRNA Snhg1 regulated MIRI progression through modulating myocardial apoptosis, mitochondrial ROS production, and mitochondrial polarization via miR-361-5p/OPA1 axis, providing the evidence for lncRNA as the prospective target for alleviating MIRI progression.