A Multiplexed Quantitative Proteomics Approach to the Human Plasma Protein Signature.

Despite the plasma proteome being able to provide a unique insight into the health and disease status of individuals, holding singular promise as a source of protein biomarkers that could be pivotal in the context of personalized medicine, only around 100 proteins covering a few human conditions have been approved as biomarkers by the US Food and Drug Administration (FDA) so far. Mass spectrometry (MS) currently has enormous potential for high-throughput analysis in clinical research; however, plasma proteomics remains challenging mainly due to the wide dynamic range of plasma protein abundances and the time-consuming procedures required. We applied a new MS-based multiplexed proteomics workflow to quantitate proteins, encompassing 67 FDA-approved biomarkers, in >1300 human plasma samples from a clinical cohort. Our results indicate that this workflow is suitable for large-scale clinical studies, showing good accuracy and reproducibility (coefficient of variation (CV) < 20 for 90% of the proteins). Furthermore, we identified plasma signature proteins (stable in time on an individual basis), stable proteins (exhibiting low biological variability and high temporal stability), and highly variable proteins (with low temporal stability) that can be used for personalized health monitoring and medicine.

iSanXoT: A standalone application for the integrative analysis of mass spectrometry-based quantitative proteomics data.

Many bioinformatics tools are available for the quantitative analysis of proteomics experiments. Most of these tools use a dedicated statistical model to derive absolute quantitative protein values from mass spectrometry (MS) data. Here, we present iSanXoT, a standalone application that processes relative abundances between MS signals and then integrates them sequentially to upper levels using the previously published Generic Integration Algorithm (GIA). iSanXoT offers unique capabilities that complement conventional quantitative software applications, including statistical weighting and independent modeling of error distributions in each integration, aggregation of technical or biological replicates, quantification of posttranslational modifications, and analysis of coordinated protein behavior. iSanXoT is a standalone, user-friendly application that accepts output from popular proteomics pipelines and enables unrestricted creation of quantification workflows and fully customizable reports that can be reused across projects or shared among users. Numerous publications attest the successful application of diverse integrative workflows constructed using the GIA for the analysis of high-throughput quantitative proteomics experiments. iSanXoT has been tested with the main operating systems. Download links for the corresponding distributions are available at https://github.com/CNIC-Proteomics/iSanXoT/releases.

Non-invasive electromechanical assessment during atrial fibrillation identifies underlying atrial myopathy alterations with early prognostic value.

Electromechanical characterization during atrial fibrillation (AF) remains a significant gap in the understanding of AF-related atrial myopathy. This study reports mechanistic insights into the electromechanical remodeling process associated with AF progression and further demonstrates its prognostic value in the clinic. In pigs, sequential electromechanical assessment during AF progression shows a progressive decrease in mechanical activity and early dissociation from its electrical counterpart. Atrial tissue samples from animals with AF reveal an abnormal increase in cardiomyocytes death and alterations in calcium handling proteins. High-throughput quantitative proteomics and immunoblotting analyses at different stages of AF progression identify downregulation of contractile proteins and progressive increase in atrial fibrosis. Moreover, advanced optical mapping techniques, applied to whole heart preparations during AF, demonstrate that AF-related remodeling decreases the frequency threshold for dissociation between transmembrane voltage signals and intracellular calcium transients compared to healthy controls. Single cell simulations of human atrial cardiomyocytes also confirm the experimental results. In patients, non-invasive assessment of the atrial electromechanical relationship further demonstrate that atrial electromechanical dissociation is an early prognostic indicator for acute and long-term rhythm control.

Heteroplasmy of Wild-Type Mitochondrial DNA Variants in Mice Causes Metabolic Heart Disease With Pulmonary Hypertension and Frailty.

BACKGROUND: In most eukaryotic cells, the mitochondrial DNA (mtDNA) is transmitted uniparentally and present in multiple copies derived from the clonal expansion of maternally inherited mtDNA. All copies are therefore near-identical, or homoplasmic. The presence of >1 mtDNA variant in the same cytoplasm can arise naturally or result from new medical technologies aimed at preventing mitochondrial genetic diseases and improving fertility. The latter is called divergent nonpathologic mtDNA heteroplasmy (DNPH). We hypothesized that DNPH is maladaptive and usually prevented by the cell. METHODS: We engineered and characterized DNPH mice throughout their lifespan using transcriptomic, metabolomic, biochemical, physiologic, and phenotyping techniques. We focused on in vivo imaging techniques for noninvasive assessment of cardiac and pulmonary energy metabolism. RESULTS: We show that DNPH impairs mitochondrial function, with profound consequences in critical tissues that cannot resolve heteroplasmy, particularly cardiac and skeletal muscle. Progressive metabolic stress in these tissues leads to severe pathology in adulthood, including pulmonary hypertension and heart failure, skeletal muscle wasting, frailty, and premature death. Symptom severity is strongly modulated by the nuclear context. CONCLUSIONS: Medical interventions that may generate DNPH should address potential incompatibilities between donor and recipient mtDNA.

Transcriptome and proteome mapping in the sheep atria reveal molecular featurets of atrial fibrillation progression.

AIMS: Atrial fibrillation (AF) is a progressive cardiac arrhythmia that increases the risk of hospitalization and adverse cardiovascular events. There is a clear demand for more inclusive and large-scale approaches to understand the molecular drivers responsible for AF, as well as the fundamental mechanisms governing the transition from paroxysmal to persistent and permanent forms. In this study, we aimed to create a molecular map of AF and find the distinct molecular programmes underlying cell type-specific atrial remodelling and AF progression. METHODS AND RESULTS: We used a sheep model of long-standing, tachypacing-induced AF, sampled right and left atrial tissue, and isolated cardiomyocytes (CMs) from control, intermediate (transition), and late time points during AF progression, and performed transcriptomic and proteome profiling. We have merged all these layers of information into a meaningful three-component space in which we explored the genes and proteins detected and their common patterns of expression. Our data-driven analysis points at extracellular matrix remodelling, inflammation, ion channel, myofibril structure, mitochondrial complexes, chromatin remodelling, and genes related to neural function, as well as critical regulators of cell proliferation as hallmarks of AF progression. Most important, we prove that these changes occur at early transitional stages of the disease, but not at later stages, and that the left atrium undergoes significantly more profound changes than the right atrium in its expression programme. The pattern of dynamic changes in gene and protein expression replicate the electrical and structural remodelling demonstrated previously in the sheep and in humans, and uncover novel mechanisms potentially relevant for disease treatment. CONCLUSIONS: Transcriptomic and proteomic analysis of AF progression in a large animal model shows that significant changes occur at early stages, and that among others involve previously undescribed increase in mitochondria, changes to the chromatin of atrial CMs, and genes related to neural function and cell proliferation.

Scaf1 promotes respiratory supercomplexes and metabolic efficiency in zebrafish.

The oxidative phosphorylation (OXPHOS) system is a dynamic system in which the respiratory complexes coexist with super-assembled quaternary structures called supercomplexes (SCs). The physiological role of SCs is still disputed. Here, we used zebrafish to study the relevance of respiratory SCs. We combined immunodetection analysis and deep data-independent proteomics to characterize these structures and found similar SCs to those described in mice, as well as novel SCs including III2  + IV2 , I + IV, and I + III2  + IV2 . To study the physiological role of SCs, we generated two null allele zebrafish lines for supercomplex assembly factor 1 (scaf1). scaf1-/- fish displayed altered OXPHOS activity due to the disrupted interaction of complexes III and IV. scaf1-/- fish were smaller in size and showed abnormal fat deposition and decreased female fertility. These physiological phenotypes were rescued by doubling the food supply, which correlated with improved bioenergetics and alterations in the metabolic gene expression program. These results reveal that SC assembly by Scaf1 modulates OXPHOS efficiency and allows the optimization of metabolic resources.

Comprehensive Quantification of the Modified Proteome Reveals Oxidative Heart Damage in Mitochondrial Heteroplasmy.

Post-translational modifications hugely increase the functional diversity of proteomes. Recent algorithms based on ultratolerant database searching are forging a path to unbiased analysis of peptide modifications by shotgun mass spectrometry. However, these approaches identify only one-half of the modified forms potentially detectable and do not map the modified residue. Moreover, tools for the quantitative analysis of peptide modifications are currently lacking. Here, we present a suite of algorithms that allows comprehensive identification of detectable modifications, pinpoints the modified residues, and enables their quantitative analysis through an integrated statistical model. These developments were used to characterize the impact of mitochondrial heteroplasmy on the proteome and on the modified peptidome in several tissues from 12-week-old mice. Our results reveal that heteroplasmy mainly affects cardiac tissue, inducing oxidative damage to proteins of the oxidative phosphorylation system, and provide a molecular mechanism explaining the structural and functional alterations produced in heart mitochondria.