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1.
J Proteome Res ; 22(12): 3676-3682, 2023 12 01.
Artigo em Inglês | MEDLINE | ID: mdl-37917986

RESUMO

Chemical proteomics utilizes small-molecule probes to covalently engage with their interacting proteins. Since chemical probes are tagged to the active or binding sites of functional proteins, chemical proteomics can be used to profile protein targets, reveal precise binding sites/mechanisms, and screen inhibitors competing with probes in a biological context. These capabilities of chemical proteomics have great potential to enable discoveries of both drug targets and lead compounds. However, chemical proteomics is limited by the time-consuming bottleneck of sample preparations, which are processed manually. With the advancement of robotics and artificial intelligence, it is now possible to automate workflows to make chemical proteomics sample preparation a high-throughput process. An automated robotic system represents a major technological opportunity to speed up advances in proteomics, open new frontiers in drug target discovery, and broaden the future of chemical biology.


Assuntos
Inteligência Artificial , Proteômica , Automação , Proteínas/química , Descoberta de Drogas
2.
bioRxiv ; 2024 Jun 02.
Artigo em Inglês | MEDLINE | ID: mdl-38854050

RESUMO

Protein arginylation is an essential posttranslational modification (PTM) catalyzed by arginyl-tRNA-protein transferase 1 (ATE1) in mammalian systems. Arginylation features a post-translational conjugation of an arginyl to a protein, making it extremely challenging to differentiate from translational arginine residues with the same mass in a protein sequence. Here we present a general activity-based arginylation profiling (ABAP) platform for the unbiased discovery of arginylation substrates and their precise modification sites. This method integrates isotopic arginine labeling into an ATE1 assay utilizing biological lysates (ex vivo) rather than live cells, thus eliminating translational bias derived from the ribosomal activity and enabling bona fide arginylation identification using isotopic features. ABAP has been successfully applied to an array of peptide, protein, cell, patient, and animal tissue samples using 20 µg sample input, with 229 unique arginylation sites revealed from human proteomes. Representative sites were validated and followed up for their biological functions. The developed platform is globally applicable to the aforementioned sample types and therefore paves the way for functional studies of this difficult-to-characterize protein modification.

3.
bioRxiv ; 2024 Jun 21.
Artigo em Inglês | MEDLINE | ID: mdl-38948703

RESUMO

Background: Metabolic remodeling is a hallmark of the failing heart. Oncometabolic stress during cancer increases the activity and abundance of the ATP-dependent citrate lyase (ACL, Acly ), which promotes histone acetylation and cardiac adaptation. ACL is critical for the de novo synthesis of lipids, but how these metabolic alterations contribute to cardiac structural and functional changes remains unclear. Methods: We utilized human heart tissue samples from healthy donor hearts and patients with hypertrophic cardiomyopathy. Further, we used CRISPR/Cas9 gene editing to inactivate Acly in cardiomyocytes of MyH6-Cas9 mice. In vivo, positron emission tomography and ex vivo stable isotope tracer labeling were used to quantify metabolic flux changes in response to the loss of ACL. We conducted a multi-omics analysis using RNA-sequencing and mass spectrometry-based metabolomics and proteomics. Experimental data were integrated into computational modeling using the metabolic network CardioNet to identify significantly dysregulated metabolic processes at a systems level. Results: Here, we show that in mice, ACL drives metabolic adaptation in the heart to sustain contractile function, histone acetylation, and lipid modulation. Notably, we show that loss of ACL increases glucose oxidation while maintaining fatty acid oxidation. Ex vivo isotope tracing experiments revealed a reduced efflux of glucose-derived citrate from the mitochondria into the cytosol, confirming that citrate is required for reductive metabolism in the heart. We demonstrate that YAP inactivation facilitates ACL deficiency. Computational flux analysis and integrative multi-omics analysis indicate that loss of ACL induces alternative isocitrate dehydrogenase 1 flux to compensate. Conclusions: This study mechanistically delineates how cardiac metabolism compensates for suppressed citrate metabolism in response to ACL loss and uncovers metabolic vulnerabilities in the heart.

4.
bioRxiv ; 2023 Oct 18.
Artigo em Inglês | MEDLINE | ID: mdl-37905045

RESUMO

Background: Methylation of histone 3 lysine 36 (H3K36me) has emerged as an essential epigenetic component for the faithful regulation of gene expression. Despite its importance in development, disease, and cancer, how the molecular agents collectively shape the H3K36me landscape is unclear. Results: We use a mouse mesenchymal stem cell model to perturb the H3K36me deposition machinery and infer the activities of the five most prominent players: SETD2, NSD1, NSD2, NSD3, and ASH1L. We find that H3K36me2 is the most abundant of the three methylation states and is predominantly deposited at intergenic regions by NSD1, and partly by NSD2. In contrast, H3K36me1/3 are most abundant within exons and are positively correlated with gene expression. We demonstrate that while SETD2 deposits most H3K36me3, it also deposits H3K36me2 within transcribed genes. Additionally, loss of SETD2 results in an increase of exonic H3K36me1, suggesting other H3K36 methyltransferases (K36MTs) prime gene bodies with lower methylation states ahead of transcription. Through a reductive approach, we uncover the distribution patterns of NSD3- and ASH1L-catalyzed H3K36me2. While NSD1/2 establish broad intergenic H3K36me2 domains, NSD3 deposits H3K36me2 peaks on active promoters and enhancers. Meanwhile, the activity of ASH1L is restricted to the regulatory elements of developmentally relevant genes, and our analyses implicate PBX2 as a potential recruitment factor. Conclusions: Within genes, SETD2 deposits both H3K36me2/3, while the other K36MTs are capable of depositing H3K36me1/2 independently of SETD2 activity. For the deposition of H3K36me1/2, we find a hierarchy of K36MT activities where NSD1>NSD2>NSD3>ASH1L. While NSD1 and NSD2 are responsible for most genome-wide propagation of H3K36me2, the activities of NSD3 and ASH1L are confined to active regulatory elements.

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