Cysteine oxidative modification of cellular proteins is crucial for many aspects of cardiac hypertrophy development. However, integrated dissection of multiple types of cysteine oxidative post-translational modifications (O-PTM) of proteomes in cardiac hypertrophy is currently missing. Here we developed a novel discovery platform that encompasses a customized biotin switch-based quantitative proteomics pipeline and an advanced analytic workflow to comprehensively profile the landscape of cysteine O-PTM in an ISO-induced cardiac hypertrophy mouse model. Specifically, we identified a total of 1655 proteins containing 3324 oxidized cysteine sites by at least one of the following three modifications: reversible cysteine O-PTM, cysteine sulfinylation (CysSO2H), and cysteine sulfonylation (CysSO3H). Analyzing the hypertrophy signatures that are reproducibly discovered from this computational workflow unveiled four biological processes with increased cysteine O-PTM. Among them, protein phosphorylation, creatine metabolism, and response to elevated Ca2+ pathways exhibited an elevation of cysteine O-PTM in early stages, whereas glucose metabolism enzymes were increasingly modified in later stages, illustrating a temporal regulatory map in cardiac hypertrophy. Our cysteine O-PTM platform depicts a dynamic and integrated landscape of the cysteine oxidative proteome, through the extracted molecular signatures, and provides critical mechanistic insights in cardiac hypertrophy. Data are available via ProteomeXchange with identifier PXD010336.

Protein stability is a major regulatory principle of protein function and cellular homeostasis. Despite limited understanding on mechanisms, disruption of protein turnover is widely implicated in diverse pathologies from heart failure to neurodegenerations. Information on global protein dynamics therefore has the potential to expand the depth and scope of disease phenotyping and therapeutic strategies. Using an integrated platform of metabolic labeling, high-resolution mass spectrometry and computational analysis, we report here a comprehensive dataset of the in vivo half-life of 3,228 and the expression of 8,064 cardiac proteins, quantified under healthy and hypertrophic conditions across six mouse genetic strains commonly employed in biomedical research. We anticipate these data will aid in understanding key mitochondrial and metabolic pathways in heart diseases, and further serve as a reference for methodology development in dynamics studies in multiple organ systems.

Clinical case reports (CCRs) provide an important means of sharing clinical experiences about atypical disease phenotypes and new therapies. However, published case reports contain largely unstructured and heterogeneous clinical data, posing a challenge to mining relevant information. Current indexing approaches generally concern document-level features and have not been specifically designed for CCRs. To address this disparity, we developed a standardized metadata template and identified text corresponding to medical concepts within 3,100 curated CCRs spanning 15 disease groups and more than 750 reports of rare diseases. We also prepared a subset of metadata on reports on selected mitochondrial diseases and assigned ICD-10 diagnostic codes to each. The resulting resource, Metadata Acquired from Clinical Case Reports (MACCRs), contains text associated with high-level clinical concepts, including demographics, disease presentation, treatments, and outcomes for each report. Our template and MACCR set render CCRs more findable, accessible, interoperable, and reusable (FAIR) while serving as valuable resources for key user groups, including researchers, physician investigators, clinicians, data scientists, and those shaping government policies for clinical trials.

Clinical case reports (CCRs) provide an important means of sharing clinical experiences about atypical disease phenotypes and new therapies. However, published case reports contain largely unstructured and heterogeneous clinical data, posing a challenge to mining relevant information. Current indexing approaches generally concern document-level features and have not been specifically designed for CCRs. To address this disparity, we developed a standardized metadata template and identified text corresponding to medical concepts within 3,100 curated CCRs spanning 15 disease groups and more than 750 reports of rare diseases. We also prepared a subset of metadata on reports on selected mitochondrial diseases and assigned ICD-10 diagnostic codes to each. The resulting resource, Metadata Acquired from Clinical Case Reports (MACCRs), contains text associated with high-level clinical concepts, including demographics, disease presentation, treatments, and outcomes for each report. Our template and MACCR set render CCRs more findable, accessible, interoperable, and reusable (FAIR) while serving as valuable resources for key user groups, including researchers, physician investigators, clinicians, data scientists, and those shaping government policies for clinical trials.