Human SRMAtlas: A Resource of Targeted Assays to Quantify the Complete Human Proteome.

The ability to reliably and reproducibly measure any protein of the human proteome in any tissue or cell type would be transformative for understanding systems-level properties as well as specific pathways in physiology and disease. Here, we describe the generation and verification of a compendium of highly specific assays that enable quantification of 99.7% of the 20,277 annotated human proteins by the widely accessible, sensitive, and robust targeted mass spectrometric method selected reaction monitoring, SRM. This human SRMAtlas provides definitive coordinates that conclusively identify the respective peptide in biological samples. We report data on 166,174 proteotypic peptides providing multiple, independent assays to quantify any human protein and numerous spliced variants, non-synonymous mutations, and post-translational modifications. The data are freely accessible as a resource at http://www.srmatlas.org/, and we demonstrate its utility by examining the network response to inhibition of cholesterol synthesis in liver cells and to docetaxel in prostate cancer lines.

Evolutionary origins and interactomes of human, young microproteins and small peptides translated from short open reading frames.

All species continuously evolve short open reading frames (sORFs) that can be templated for protein synthesis and may provide raw materials for evolutionary adaptation. We analyzed the evolutionary origins of 7,264 recently cataloged human sORFs and found that most were evolutionarily young and had emerged de novo. We additionally identified 221 previously missed sORFs potentially translated into peptides of up to 15 amino acids-all of which are smaller than the smallest human microprotein annotated to date. To investigate the bioactivity of sORF-encoded small peptides and young microproteins, we subjected 266 candidates to a mass-spectrometry-based interactome screen with motif resolution. Based on these interactomes and additional cellular assays, we can associate several candidates with mRNA splicing, translational regulation, and endocytosis. Our work provides insights into the evolutionary origins and interaction potential of young and small proteins, thereby helping to elucidate this underexplored territory of the human proteome.

circRNADisease v2.0: an updated resource for high-quality experimentally supported circRNA-disease associations.

circRNADisease v2.0 is an enhanced and reliable database that offers experimentally verified relationships between circular RNAs (circRNAs) and various diseases. It is accessible at http://cgga.org.cn/circRNADisease/ or http://cgga.org.cn:9091/circRNADisease/. The database currently includes 6998 circRNA-disease entries across multiple species, representing a remarkable 19.77-fold increase compared to the previous version. This expansion consists of a substantial rise in the number of circRNAs (from 330 to 4246), types of diseases (from 48 to 330) and covered species (from human only to 12 species). Furthermore, a new section has been introduced in the database, which collects information on circRNA-associated factors (genes, proteins and microRNAs), molecular mechanisms (molecular pathways), biological functions (proliferation, migration, invasion, etc.), tumor and/or cell line and/or patient-derived xenograft (PDX) details, and prognostic evidence in diseases. In addition, we identified 7 159 865 relationships between mutations and circRNAs among 30 TCGA cancer types. Due to notable enhancements and extensive data expansions, the circRNADisease 2.0 database has become an invaluable asset for both clinical practice and fundamental research. It enables researchers to develop a more comprehensive understanding of how circRNAs impact complex diseases.

Sugar status in preexisting leaves determines systemic stomatal development within newly developing leaves.

Stomata are pores found in the epidermis of stems or leaves that modulate both plant gas exchange and water/nutrient uptake. The development and function of plant stomata are regulated by a diverse range of environmental cues. However, how carbohydrate status in preexisting leaves might determine systemic stomatal formation within newly developing leaves has remained obscure. The glucose (Glc) sensor HEXOKINASE1 (HXK1) has been reported to decrease the stability of an ethylene/Glc signaling transcriptional regulator, EIN3 (ETHYLENE INSENSITIVE3). EIN3 in turn directly represses the expression of SUC2 (sucrose transporter 2), encoding a master transporter of sucrose (Suc). Further, KIN10, a nuclear regulator involved in energy homeostasis, has been reported to repress the transcription factor SPCH (SPEECHLESS), a master regulator of stomatal development. Here, we demonstrate that the Glc status of preexisting leaves determines systemic stomatal development within newly developing leaves by the HXK1-¦EIN3-¦SUC2 module. Further, increasing Glc levels in preexisting leaves results in a HXK1-dependent decrease of EIN3 and increase of SUC2, triggering the perception, amplification and relay of HXK1-dependent Glc signaling and thereby triggering Suc transport from mature to newly developing leaves. The HXK1-¦EIN3-¦SUC2 molecular module thereby drives systemic Suc transport from preexisting leaves to newly developing leaves. Subsequently, increasing Suc levels within newly developing leaves promotes stomatal formation through the established KIN10⟶ SPCH module. Our findings thus show how a carbohydrate signal in preexisting leaves is sensed, amplified and relayed to determine the extent of systemic stomatal development within newly developing leaves.

Detection and editing of the updated Arabidopsis plastid- and mitochondrial-encoded proteomes through PeptideAtlas.

Arabidopsis (Arabidopsis thaliana) ecotype Col-0 has plastid and mitochondrial genomes encoding over 100 proteins. Public databases (e.g. Araport11) have redundancy and discrepancies in gene identifiers for these organelle-encoded proteins. RNA editing results in changes to specific amino acid residues or creation of start and stop codons for many of these proteins, but the impact of RNA editing at the protein level is largely unexplored due to the complexities of detection. Here, we assembled the nonredundant set of identifiers, their correct protein sequences, and 452 predicted nonsynonymous editing sites of which 56 are edited at lower frequency. We then determined accumulation of edited and/or unedited proteoforms by searching ∼259 million raw tandem MS spectra from ProteomeXchange, which is part of PeptideAtlas (www.peptideatlas.org/builds/arabidopsis/). We identified all mitochondrial proteins and all except 3 plastid-encoded proteins (NdhG/Ndh6, PsbM, and Rps16), but no proteins predicted from the 4 ORFs were identified. We suggest that Rps16 and 3 of the ORFs are pseudogenes. Detection frequencies for each edit site and type of edit (e.g. S to L/F) were determined at the protein level, cross-referenced against the metadata (e.g. tissue), and evaluated for technical detection challenges. We detected 167 predicted edit sites at the proteome level. Minor frequency sites were edited at low frequency at the protein level except for cytochrome C biogenesis 382 at residue 124 (Ccb382-124). Major frequency sites (>50% editing of RNA) only accumulated in edited form (>98% to 100% edited) at the protein level, with the exception of Rpl5-22. We conclude that RNA editing for major editing sites is required for stable protein accumulation.

The ProteomeXchange consortium at 10 years: 2023 update.

Mass spectrometry (MS) is by far the most used experimental approach in high-throughput proteomics. The ProteomeXchange (PX) consortium of proteomics resources (http://www.proteomexchange.org) was originally set up to standardize data submission and dissemination of public MS proteomics data. It is now 10 years since the initial data workflow was implemented. In this manuscript, we describe the main developments in PX since the previous update manuscript in Nucleic Acids Research was published in 2020. The six members of the Consortium are PRIDE, PeptideAtlas (including PASSEL), MassIVE, jPOST, iProX and Panorama Public. We report the current data submission statistics, showcasing that the number of datasets submitted to PX resources has continued to increase every year. As of June 2022, more than 34 233 datasets had been submitted to PX resources, and from those, 20 062 (58.6%) just in the last three years. We also report the development of the Universal Spectrum Identifiers and the improvements in capturing the experimental metadata annotations. In parallel, we highlight that data re-use activities of public datasets continue to increase, enabling connections between PX resources and other popular bioinformatics resources, novel research and also new data resources. Finally, we summarise the current state-of-the-art in data management practices for sensitive human (clinical) proteomics data.

The Zea mays PeptideAtlas: A New Maize Community Resource.

This study presents the Maize PeptideAtlas resource (www.peptideatlas.org/builds/maize) to help solve questions about the maize proteome. Publicly available raw tandem mass spectrometry (MS/MS) data for maize collected from ProteomeXchange were reanalyzed through a uniform processing and metadata annotation pipeline. These data are from a wide range of genetic backgrounds and many sample types and experimental conditions. The protein search space included different maize genome annotations for the B73 inbred line from MaizeGDB, UniProtKB, NCBI RefSeq, and for the W22 inbred line. 445 million MS/MS spectra were searched, of which 120 million were matched to 0.37 million distinct peptides. Peptides were matched to 66.2% of proteins in the most recent B73 nuclear genome annotation. Furthermore, most conserved plastid- and mitochondrial-encoded proteins (NCBI RefSeq annotations) were identified. Peptides and proteins identified in the other B73 genome annotations will improve maize genome annotation. We also illustrate the high-confidence detection of unique W22 proteins. N-terminal acetylation, phosphorylation, ubiquitination, and three lysine acylations (K-acetyl, K-malonyl, and K-hydroxyisobutyryl) were identified and can be inspected through a PTM viewer in PeptideAtlas. All matched MS/MS-derived peptide data are linked to spectral, technical, and biological metadata. This new PeptideAtlas is integrated in MaizeGDB with a peptide track in JBrowse.

Phosphorylation in the Plasmodium falciparum Proteome: A Meta-Analysis of Publicly Available Data Sets.

Malaria is a deadly disease caused by Apicomplexan parasites of the Plasmodium genus. Several species of the Plasmodium genus are known to be infectious to humans, of which P. falciparum is the most virulent. Post-translational modifications (PTMs) of proteins coordinate cell signaling and hence regulate many biological processes in P. falciparum homeostasis and host infection, of which the most highly studied is phosphorylation. Phosphosites on proteins can be identified by tandem mass spectrometry (MS) performed on enriched samples (phosphoproteomics), followed by downstream computational analyses. We have performed a large-scale meta-analysis of 11 publicly available phosphoproteomics data sets to build a comprehensive atlas of phosphosites in the P. falciparum proteome, using robust pipelines aimed at strict control of false identifications. We identified a total of 26,609 phosphorylated sites on P. falciparum proteins, split across three categories of data reliability (gold/silver/bronze). We identified significant sequence motifs, likely indicative of different groups of kinases responsible for different groups of phosphosites. Conservation analysis identified clusters of phosphoproteins that are highly conserved and others that are evolving faster within the Plasmodium genus, and implicated in different pathways. We were also able to identify over 180,000 phosphosites within Plasmodium species beyond falciparum, based on orthologue mapping. We also explored the structural context of phosphosites, identifying a strong enrichment for phosphosites on fast-evolving (low conservation) intrinsically disordered regions (IDRs) of proteins. In other species, IDRs have been shown to have an important role in modulating protein-protein interactions, particularly in signaling, and thus warranting further study for their roles in host-pathogen interactions. All data have been made available via UniProtKB, PRIDE, and PeptideAtlas, with visualization interfaces for exploring phosphosites in the context of other data on Plasmodium proteins.

Meta-Analysis of Rice Phosphoproteomics Data to Understand Variation in Cell Signaling Across the Rice Pan-Genome.

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have reanalyzed publicly available mass spectrometry proteomics data sets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,565 phosphosites on serine, threonine, and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety and clustered the data to identify groups of sites with similar patterns across rice family groups. The data has been loaded into UniProt Knowledge-Base─enabling researchers to visualize sites alongside other data on rice proteins, e.g., structural models from AlphaFold2, PeptideAtlas, and the PRIDE database─enabling visualization of source evidence, including scores and supporting mass spectra.

Detection of the Arabidopsis Proteome and Its Post-translational Modifications and the Nature of the Unobserved (Dark) Proteome in PeptideAtlas.

This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource (build 2023-10) providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected post-translational modifications (PTMs), and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18,267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins, and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome: the "dark" proteome. This dark proteome is highly enriched for E3 ligases, transcription factors, and for certain (e.g., CLE, IDA, PSY) but not other (e.g., THIONIN, CAP) signaling peptides families. A machine learning model trained on RNA expression data and protein properties predicts the probability that proteins will be detected. The model aids in discovery of proteins with short half-life (e.g., SIG1,3 and ERF-VII TFs) and for developing strategies to identify the missing proteins. PeptideAtlas is linked to TAIR, tracks in JBrowse, and several other community proteomics resources.

The Circulating Proteome─Technological Developments, Current Challenges, and Future Trends.

Recent improvements in proteomics technologies have fundamentally altered our capacities to characterize human biology. There is an ever-growing interest in using these novel methods for studying the circulating proteome, as blood offers an accessible window into human health. However, every methodological innovation and analytical progress calls for reassessing our existing approaches and routines to ensure that the new data will add value to the greater biomedical research community and avoid previous errors. As representatives of HUPO's Human Plasma Proteome Project (HPPP), we present our 2024 survey of the current progress in our community, including the latest build of the Human Plasma Proteome PeptideAtlas that now comprises 4608 proteins detected in 113 data sets. We then discuss the updates of established proteomics methods, emerging technologies, and investigations of proteoforms, protein networks, extracellualr vesicles, circulating antibodies and microsamples. Finally, we provide a prospective view of using the current and emerging proteomics tools in studies of circulating proteins.

Targeting erythroid progenitor cells for cancer immunotherapy.

Immunotherapy, especially immune checkpoint blockade therapy, represents a major milestone in the history of cancer therapy. However, the current response rate to immunotherapy among cancer patients must be improved; thus, new strategies for sensitizing patients to immunotherapy are urgently needed. Erythroid progenitor cells (EPCs), a population of immature erythroid cells, exert potent immunosuppressive functions. As a newly recognized immunosuppressive population, EPCs have not yet been effectively targeted. In this review, we summarize the immunoregulatory mechanisms of EPCs, especially for CD45+ EPCs. Moreover, in view of the regulatory effects of EPCs on the tumor microenvironment, we propose the concept of EPC-immunity, present existing strategies for targeting EPCs, and discuss the challenges encountered in both basic research and clinical applications. In particular, the impact of existing cancer treatments on EPCs is discussed, laying the foundation for combination therapies. The aim of this review is to provide new avenues for improving the efficacy of cancer immunotherapy by targeting EPCs.

Universal Spectrum Identifier for mass spectra.

Mass spectra provide the ultimate evidence to support the findings of mass spectrometry proteomics studies in publications, and it is therefore crucial to be able to trace the conclusions back to the spectra. The Universal Spectrum Identifier (USI) provides a standardized mechanism for encoding a virtual path to any mass spectrum contained in datasets deposited to public proteomics repositories. USI enables greater transparency of spectral evidence, with more than 1 billion USI identifications from over 3 billion spectra already available through ProteomeXchange repositories.

NKAIN1, as an oncogene, promotes the proliferation and metastasis of breast cancer, affecting its prognosis.

Na, K-ATPase interaction (NKAIN) is a transmembrane protein family, which can interact with Na, K-ATPase ß1 subunit. NKAIN1 plays an important role in alcohol-dependent diseases such as endometrial and prostate cancers. However, the relationship between NKAIN1 and human breast cancer has not been studied. Hence, this study aimed to explore the relationship between NKAIN1 expression and breast cancer. Data used in this study were mainly from the Cancer Genome Atlas, including differential expression analysis, Kaplan-Meier survival analysis, receiver operating characteristic curve analysis, multiple Cox regression analysis, co-expression gene analysis, and gene set enrichment analysis. Analyses were performed using reverse transcription-quantitative polymerase chain reaction, western blot analysis, and immunohistochemistry on 46 collected samples. The knockdown or overexpression of NKAIN1 in vitro in MCF-7 and MDA-MB-231 cell lines altered the proliferation and migration abilities of tumor cells. In vivo experiments further confirmed that NKAIN1 knockdown effectively inhibited the proliferation and migration of cancer cells. Therefore, our study identified NKAIN1 as an oncogene that is highly expressed in breast cancer tissues. The findings highlight the potential of NKAIN1 as a molecular biomarker of breast cancer.

The Arabidopsis PeptideAtlas: Harnessing worldwide proteomics data to create a comprehensive community proteomics resource.

We developed a resource, the Arabidopsis PeptideAtlas (www.peptideatlas.org/builds/arabidopsis/), to solve central questions about the Arabidopsis thaliana proteome, such as the significance of protein splice forms and post-translational modifications (PTMs), or simply to obtain reliable information about specific proteins. PeptideAtlas is based on published mass spectrometry (MS) data collected through ProteomeXchange and reanalyzed through a uniform processing and metadata annotation pipeline. All matched MS-derived peptide data are linked to spectral, technical, and biological metadata. Nearly 40 million out of ∼143 million MS/MS (tandem MS) spectra were matched to the reference genome Araport11, identifying ∼0.5 million unique peptides and 17,858 uniquely identified proteins (only isoform per gene) at the highest confidence level (false discovery rate 0.0004; 2 non-nested peptides ≥9 amino acid each), assigned canonical proteins, and 3,543 lower-confidence proteins. Physicochemical protein properties were evaluated for targeted identification of unobserved proteins. Additional proteins and isoforms currently not in Araport11 were identified that were generated from pseudogenes, alternative start, stops, and/or splice variants, and small Open Reading Frames; these features should be considered when updating the Arabidopsis genome. Phosphorylation can be inspected through a sophisticated PTM viewer. PeptideAtlas is integrated with community resources including TAIR, tracks in JBrowse, PPDB, and UniProtKB. Subsequent PeptideAtlas builds will incorporate millions more MS/MS data.

Broadband lens and graphene/silicon photodiode for wide spectral imaging.

We designed a broadband lens along with a graphene/silicon photodiode for wide spectral imaging ranging from ultraviolet to near-infrared wavelengths. By using five spherical glass lenses, the broadband lens, with the modulation transfer function of 0.38 at 100 lp/mm, corrects aberrations ranging from 340 to 1700 nm. Our design also includes a broadband graphene/silicon Schottky photodiode with the highest responsivity of 0.63 A/W ranging from ultraviolet to near-infrared. By using the proposed broadband lens and the broadband graphene/silicon photodiode, several single-pixel imaging designs in ultraviolet, visible, and near-infrared wavelengths are demonstrated. Experimental results show the advantages of integrating the lens with the photodiode and the potential to realize broadband imaging with a single set of lens and a detector.

miR-20a: a key regulator of orthodontic tooth movement via BMP2 signaling pathway modulation.

AIM: In this study, we aimed to establish a rat tooth movement model to assess miR-20's ability in enhancing the BMP2 signaling pathway and facilitate alveolar bone remodeling. METHOD: 60 male SD rats had nickel titanium spring devices placed between their left upper first molars and incisors, with the right side serving as the control. Forces were applied at varying durations (18h, 24h, 30h, 36h, 42h, 1d, 3d, 5d, 7d, 14d), and their bilateral maxillary molars and surrounding alveolar bones were retrieved for analysis. Fluorescent quantitative PCR was conducted to assess miR-20a, BMP2, Runx2, Bambi and Smad6 gene expression in alveolar bone, and western blot was performed to determine the protein levels of BMP2, Runx2, Bambi, and Smad6 after mechanical loading. RESULT: We successfully established an orthodontic tooth movement model in SD rats and revealed upregulated miR-20a expression and significantly increased BMP2 and Runx2 gene expression and protein synthesis in alveolar bone during molar tooth movement. Although Bambi and Smad6 gene expression did not significantly increase, their protein synthesis was found to decrease significantly. CONCLUSION: MiR-20a was found to be involved in rat tooth movement model alveolar bone remodeling, wherein it promoted remodeling by reducing Bambi and Smad6 protein synthesis through the BMP2 signaling pathway.

Pelvic floor muscle strength and influencing factors based on vaginal manometry among healthy women at different life stages: A multicentre cross-sectional study.

OBJECTIVE: To assess pelvic floor muscle (PFM) strength and influencing factors among healthy women at different life stages. DESIGN: Multicentre cross-sectional study. SETTING: Fourteen hospitals in China. POPULATION: A total of 5040 healthy women allocated to the following groups (with 1680 women per group): premenopausal nulliparous, premenopausal parous and postmenopausal. METHODS: The PFM strength was evaluated by vaginal manometry. Multivariate logistic regression was used to determine the influencing factors for low PFM strength. MAIN OUTCOME MEASURES: Maximum voluntary contraction pressure (MVCP). RESULTS: The median MVCP values were 36, 35 and 35 cmH2O in premenopausal nulliparous (aged 19-51 years), premenopausal parous (aged 22-61 years), and postmenopausal (aged 40-86 years) women, respectively. In the premenopausal nulliparous group, physical work (odds ratio, OR 2.05) was the risk factor for low PFM strength, which may be related to the chronic increased abdominal pressure caused by physical work. In the premenopausal parous group, the number of vaginal deliveries (OR 1.28) and diabetes (OR 2.70) were risk factors for low PFM strength, whereas sexual intercourse (<2 times per week vs. none, OR 0.55; ≥2 times per week vs. none, OR 0.56) and PFM exercise (OR 0.50) may have protective effects. In the postmenopausal group, the number of vaginal deliveries (OR 1.32) and family history of pelvic organ prolapse (POP) (OR 1.83) were risk factors for low PFM strength. CONCLUSIONS: Physical work, vaginal delivery, diabetes and a family history of POP are all risk factors for low PFM strength, whereas PFM exercises and sexual life can have a protective effect. The importance of these factors varies at different stages of a woman's life.

Pipette-tip solid-phase extraction coupled with matrix-assisted laser desorption/ionization mass spectrometry enables rapid and high-throughput analysis of antidepressants in rat serum.

Therapeutic drug monitoring is essential for ensuring the efficacy and safety of medications. This study introduces a streamlined approach that combines pipette-tip solid-phase extraction (PT-SPE) with matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS), facilitating rapid and high-throughput monitoring of drug concentrations. As a demonstration, this method was applied to the extraction and quantification of antidepressants in serum. Utilizing Zip-Tip C18, the method enabled the extraction of antidepressants from complex biological matrices in less than 2 min, with the subsequent MALDI-MS analysis yielding results in just 1 min. Optimal extraction recoveries were achieved using a sampling solution at pH 9.0 and a 10 µL ethanol desorption solution containing 0.1% phosphoric acid. For MALDI analysis, 2,5-dihydroxybenzoic acid was identified as the most effective matrix for producing the highest signal intensity. The quantification strategy exhibited robust linearities (R2 ≥ 0.997) and satisfactory limits of quantification, ranging from 0.05 to 0.5 µg/mL for a suite of antidepressants. The application for monitoring dynamic concentration changes of antidepressants in rat serum emphasized the method's efficacy. This strategy offers the advantages of high throughput, minimal sample usage, environmental sustainability, and simplicity, providing ideas and a reference basis for the subsequent development of methods for therapeutic drug monitoring.

Mettl1 knockdown alleviates cardiac I/R injury in mice by inactivating the Mettl1-CYLD-P53 positive feedback loop.

The N7-methylguanosine (m7G) methyltransferase Mettl1 has been recently implicated in cardiac repair and fibrosis. In this study we investigated the role of Mettl1 in mouse cardiomyocytes injury and the underlying mechanisms. Cardiac ischemia/reperfusion (I/R) I/R model was established in mice by ligation of the left anterior descending coronary artery (LAD) for 45 min followed by reperfusion for 24 h. We showed the mRNA and protein levels of Mettl1 were significantly upregulated in mouse I/R hearts and H2O2-treated neonatal mouse cardiomyocytes (NMCMs). Mettl1 knockdown markedly ameliorated cardiac I/R injury, evidenced by decreased infarct size, apoptosis, and improved cardiac function. Overexpression of Mettl1 triggered cardiomyocytes apoptosis in vivo and in vitro. By performing RNA sequencing combined with m7G methylated RNA sequencing in Mettl1-overexpressing mouse hearts, we revealed that Mettl1 catalyzed m7G modification of the deubiquitinase cylindromatosis (CYLD) mRNA to increase the expression of CYLD, which enhanced the stability of P53 via abrogating its ubiquitination degradation. Vice versa, P53 served as a transcriptional factor to positively regulate Mettl1 expression during I/R injury. Knockdown of CYLD mitigated cardiomyocytes apoptosis induced by Mettl1 overexpression or oxidative stress. From the available drug-targets databases and literature, we identified 4 small molecule inhibitors of m7G modification. Sinefungin, one of the Mettl1 inhibitors exerted profound protection against cardiac I/R injury in vivo and in vitro. Collectively, this study has identified Mettl1 as a key regulator of cardiomyocyte apoptosis, and targeting the Mettl1-CYLD-P53 positive feedback circuit may represent a novel therapeutic avenue for alleviating cardiac I/R injury.