Redundant role of PAD2 and PAD4 in the development of cardiovascular lesions in a mouse model of Kawasaki Disease vasculitis.

Kawasaki disease (KD) is the leading cause of acquired heart disease in children. While circulating neutrophils are increased and activated during acute KD, it is unclear whether neutrophils and neutrophil extracellular traps (NETs) contribute to the pathogenesis of KD. Peptidylarginine deiminase 4 (PAD4), an enzyme involved in protein citrullination and essential for NETs formation, is implicated in the pathogenesis of various diseases. Here, we used the Lactobacillus casei cell wall extract (LCWE)-induced mouse model of KD vasculitis to determine the contribution of PAD4 in KD vasculitis. We found that the pan-PADs inhibitor, Cl-amidine, significantly reduced LCWE-induced cardiovascular lesions, but neutrophil-specific Padi4 KO mice did not impact development of KD vasculitis. While in vitro treatment of macrophages, which highly express Padi4, with Cl-amidine inhibited IL-1ßsecretion, macrophage-specific Padi4 KO mice did not reduce the lesions. Padi4-/- mice also developed KD vasculitis, AFM30a, a PAD2 inhibitor, significantly reduced KD vasculitis in Padi4-/- mice, indicating a compensatory role of PAD2 in PAD4 deficiency. We also identified several citrullinated proteins in macrophages with constitutively active NLRP3 inflammasome that were inhibited by Cl-amidine treatment, suggesting that protein citrullination participates in NLRP3 inflammasome activation. These data indicate a dispensable role for PAD4-dependent NETs formation, and a redundant role of PAD2 and PAD4 in this murine KD vasculitis. The cardioprotective effects of Cl-amidine to reduce the severity of murine KD vasculitis is not limited to PAD4 inhibition and may include decreased citrullination in the inflammasome pathway.

An Inflection Point in High-Throughput Proteomics with Orbitrap Astral: Analysis of Biofluids, Cells, and Tissues.

This Technical Note presents a comprehensive proteomics workflow for the new combination of Orbitrap and Astral mass analyzers across biofluids, cells, and tissues. Central to our workflow is the integration of Adaptive Focused Acoustics (AFA) technology for cells and tissue lysis to ensure robust and reproducible sample preparation in a high-throughput manner. Furthermore, we automated the detergent-compatible single-pot, solid-phase-enhanced sample Preparation (SP3) method for protein digestion. The synergy of these advanced methodologies facilitates a robust and high-throughput approach for cell and tissue analysis, an important consideration in translational research. This work disseminates our platform workflow, analyzes the effectiveness, demonstrates the reproducibility of the results, and highlights the potential of these technologies in biomarker discovery and disease pathology. For cells and tissues (heart, liver, lung, and intestine) proteomics analysis by data-independent acquisition mode, identifications exceeding 10,000 proteins can be achieved with a 24 min active gradient. In 200 ng injections of HeLa digest across multiple gradients, an average of more than 80% of proteins have a CV less than 20%, and a 45 min run covers ∼90% of the expressed proteome. This complete workflow allows for large swaths of the proteome to be identified and is compatible with diverse sample types.

Myocardial ultrastructure of human heart failure with preserved ejection fraction.

Over half of patients with heart failure have a preserved ejection fraction (>50%, called HFpEF), a syndrome with substantial morbidity/mortality and few effective therapies1. Its dominant comorbidity is now obesity, which worsens disease and prognosis1-3. Myocardial data from patients with morbid obesity and HFpEF show depressed myocyte calcium-stimulated tension4 and disrupted gene expression of mitochondrial and lipid metabolic pathways5,6, abnormalities shared by human HF with a reduced EF but less so in HFpEF without severe obesity. The impact of severe obesity on human HFpEF myocardial ultrastructure remains unexplored. Here we assessed the myocardial ultrastructure in septal biopsies from patients with HFpEF using transmission electron microscopy. We observed sarcomere disruption and sarcolysis, mitochondrial swelling with cristae separation and dissolution and lipid droplet accumulation that was more prominent in the most obese patients with HFpEF and not dependent on comorbid diabetes. Myocardial proteomics revealed associated reduction in fatty acid uptake, processing and oxidation and mitochondrial respiration proteins, particularly in very obese patients with HFpEF.

Blood to Biomarker Quantitation in Under One Hour with Rapid Proteomics using a Hyperthermoacidic Protease.

Multi-step multi-hour tryptic proteolysis has limited the utility of bottom-up proteomics for cases that require immediate quantitative information. The recently available hyperthermoacidic (HTA) protease "Krakatoa" digests samples in a single 5 to 30-minute step at pH 3 and >80 °C; conditions that disrupt most cells and tissues, denature proteins, and block disulfide reformation. The combination of quick single-step sample preparation with high throughput dual trapping column single analytical column (DTSC) liquid chromatography-mass spectrometry (LC-MS) achieves "Rapid Proteomics" in which the time from sample collection to actionable data is less than 1 hour. The presented development and systematic evaluation of this methodology found reproducible quantitation of over 160 proteins from just 1 microliter of whole blood. Furthermore, the preference of the HTA-protease for intact proteins over peptides allows for sensitive targeted quantitation of the Angiotensin I and II bioactive peptides in under half an hour. With these methods we analyzed serum and plasma from 53 individuals and quantified Angiotensin and proteins that were not detected with trypsin. This assessment of Rapid Proteomics suggests that concentration of circulating protein and peptide biomarkers could be measured in almost real-time by LC-MS. TOC Figure: Rapid proteomics enables near real-time monitoring of circulating blood biomarkers. One microliter of blood is collected every 8 minutes, digested for 20 minutes, and then analyzed by targeted mass spectrometry for 8 minutes. This results in a 30-minute delay with datapoints every 8 minutes.

Acoustic ejection mass spectrometry empowers ultra-fast protein biomarker quantification.

The global scientific response to COVID 19 highlighted the urgent need for increased throughput and capacity in bioanalytical laboratories, especially for the precise quantification of proteins that pertain to health and disease. Acoustic ejection mass spectrometry (AEMS) represents a much-needed paradigm shift for ultra-fast biomarker screening. Here, a quantitative AEMS assays is presented, employing peptide immunocapture to enrich (i) 10 acute phase response (APR) protein markers from plasma, and (ii) SARS-CoV-2 NCAP peptides from nasopharyngeal swabs. The APR proteins were quantified in 267 plasma samples, in triplicate in 4.8 h, with %CV from 4.2% to 10.5%. SARS-CoV-2 peptides were quantified in triplicate from 145 viral swabs in 10 min. This assay represents a 15-fold speed improvement over LC-MS, with instrument stability demonstrated across 10,000 peptide measurements. The combination of speed from AEMS and selectivity from peptide immunocapture enables ultra-high throughput, reproducible quantitative biomarker screening in very large cohorts.

ABDS: a bioinformatics tool suite for analyzing biologically diverse samples.

Bioinformatics software tools are essential to identify informative molecular features that define different phenotypic sample groups. Among the most fundamental and interrelated tasks are missing value imputation, signature gene detection, and differential pattern visualization. However, many commonly used analytics tools can be problematic when handling biologically diverse samples if either informative missingness possess high missing rates with mixed missing mechanisms, or multiple sample groups are compared and visualized in parallel. We developed the ABDS tool suite specifically for analyzing biologically diverse samples. Collectively, a mechanism-integrated group-wise pre-imputation scheme is proposed to retain informative missingness associated with signature genes, a cosine-based one-sample test is extended to detect group-silenced signature genes, and a unified heatmap is designed to display multiple sample groups. We describe the methodological principles and demonstrate the effectiveness of three analytics tools under targeted scenarios, supported by comparative evaluations and biomedical showcases. As an open-source R package, ABDS tool suite complements rather than replaces existing tools and will allow biologists to more accurately detect interpretable molecular signals among phenotypically diverse sample groups.

Integrating Clinical Phenotype With Multiomics Analyses of Human Cardiac Tissue Unveils Divergent Metabolic Remodeling in Genotype-Positive and Genotype-Negative Patients With Hypertrophic Cardiomyopathy.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is caused by sarcomere gene mutations (genotype-positive HCM) in ≈50% of patients and occurs in the absence of mutations (genotype-negative HCM) in the other half of patients. We explored how alterations in the metabolomic and lipidomic landscape are involved in cardiac remodeling in both patient groups. METHODS: We performed proteomics, metabolomics, and lipidomics on myectomy samples (genotype-positive N=19; genotype-negative N=22; and genotype unknown N=6) from clinically well-phenotyped patients with HCM and on cardiac tissue samples from sex- and age-matched and body mass index-matched nonfailing donors (N=20). These data sets were integrated to comprehensively map changes in lipid-handling and energy metabolism pathways. By linking metabolomic and lipidomic data to variability in clinical data, we explored patient group-specific associations between cardiac and metabolic remodeling. RESULTS: HCM myectomy samples exhibited (1) increased glucose and glycogen metabolism, (2) downregulation of fatty acid oxidation, and (3) reduced ceramide formation and lipid storage. In genotype-negative patients, septal hypertrophy and diastolic dysfunction correlated with lowering of acylcarnitines, redox metabolites, amino acids, pentose phosphate pathway intermediates, purines, and pyrimidines. In contrast, redox metabolites, amino acids, pentose phosphate pathway intermediates, purines, and pyrimidines were positively associated with septal hypertrophy and diastolic impairment in genotype-positive patients. CONCLUSIONS: We provide novel insights into both general and genotype-specific metabolic changes in HCM. Distinct metabolic alterations underlie cardiac disease progression in genotype-negative and genotype-positive patients with HCM.

Autophagic signaling promotes systems-wide remodeling in skeletal muscle upon oncometabolic stress by D2-HG.

OBJECTIVES: Cachexia is a metabolic disorder and comorbidity with cancer and heart failure. The syndrome impacts more than thirty million people worldwide, accounting for 20% of all cancer deaths. In acute myeloid leukemia, somatic mutations of the metabolic enzyme isocitrate dehydrogenase 1 and 2 cause the production of the oncometabolite D2-hydroxyglutarate (D2-HG). Increased production of D2-HG is associated with heart and skeletal muscle atrophy, but the mechanistic links between metabolic and proteomic remodeling remain poorly understood. Therefore, we assessed how oncometabolic stress by D2-HG activates autophagy and drives skeletal muscle loss. METHODS: We quantified genomic, metabolomic, and proteomic changes in cultured skeletal muscle cells and mouse models of IDH-mutant leukemia using RNA sequencing, mass spectrometry, and computational modeling. RESULTS: D2-HG impairs NADH redox homeostasis in myotubes. Increased NAD+ levels drive activation of nuclear deacetylase Sirt1, which causes deacetylation and activation of LC3, a key regulator of autophagy. Using LC3 mutants, we confirm that deacetylation of LC3 by Sirt1 shifts its distribution from the nucleus into the cytosol, where it can undergo lipidation at pre-autophagic membranes. Sirt1 silencing or p300 overexpression attenuated autophagy activation in myotubes. In vivo, we identified increased muscle atrophy and reduced grip strength in response to D2-HG in male vs. female mice. In male mice, glycolytic intermediates accumulated, and protein expression of oxidative phosphorylation machinery was reduced. In contrast, female animals upregulated the same proteins, attenuating the phenotype in vivo. Network modeling and machine learning algorithms allowed us to identify candidate proteins essential for regulating oncometabolic adaptation in mouse skeletal muscle. CONCLUSIONS: Our multi-omics approach exposes new metabolic vulnerabilities in response to D2-HG in skeletal muscle and provides a conceptual framework for identifying therapeutic targets in cachexia.

The Future of Proteomics is Up in the Air: Can Ion Mobility Replace Liquid Chromatography for High Throughput Proteomics?

The coevolution of liquid chromatography (LC) with mass spectrometry (MS) has shaped contemporary proteomics. LC hyphenated to MS now enables quantification of more than 10,000 proteins in a single injection, a number that likely represents most proteins in specific human cells or tissues. Separations by ion mobility spectrometry (IMS) have recently emerged to complement LC and further improve the depth of proteomics. Given the theoretical advantages in speed and robustness of IMS in comparison to LC, we envision that ongoing improvements to IMS paired with MS may eventually make LC obsolete, especially when combined with targeted or simplified analyses, such as rapid clinical proteomics analysis of defined biomarker panels. In this perspective, we describe the need for faster analysis that might drive this transition, the current state of direct infusion proteomics, and discuss some technical challenges that must be overcome to fully complete the transition to entirely gas phase proteomics.

Targeting low levels of MIF expression as a potential therapeutic strategy for ALS.

Mutations in SOD1 cause amyotrophic lateral sclerosis (ALS), a neurodegenerative disease characterized by motor neuron (MN) loss. We previously discovered that macrophage migration inhibitory factor (MIF), whose levels are extremely low in spinal MNs, inhibits mutant SOD1 misfolding and toxicity. In this study, we show that a single peripheral injection of adeno-associated virus (AAV) delivering MIF into adult SOD1G37R mice significantly improves their motor function, delays disease progression, and extends survival. Moreover, MIF treatment reduces neuroinflammation and misfolded SOD1 accumulation, rescues MNs, and corrects dysregulated pathways as observed by proteomics and transcriptomics. Furthermore, we reveal low MIF levels in human induced pluripotent stem cell-derived MNs from familial ALS patients with different genetic mutations, as well as in post mortem tissues of sporadic ALS patients. Our findings indicate that peripheral MIF administration may provide a potential therapeutic mechanism for modulating misfolded SOD1 in vivo and disease outcome in ALS patients.

Peroxisome proliferator-activated receptor alpha is essential factor in enhanced macrophage immune function induced by angiotensin converting enzyme.

An upregulation of angiotensin-converting enzyme (ACE) expression strengthens the immune activity of myeloid lineage cells as a natural functional regulation mechanism in our immunity. ACE10/10 mice, possessing increased ACE expression in macrophages, exhibit enhanced anti-tumor immunity and anti-bactericidal effects compared to those of wild type (WT) mice, while the detailed molecular mechanism has not been elucidated yet. In this report, we demonstrate that peroxisome proliferator-activated receptor alpha (PPARα) is a key molecule in the functional upregulation of macrophages induced by ACE. The expression of PPARα, a transcription factor regulating fatty acid metabolism-associated gene expressions, was upregulated in ACE-overexpressing macrophages. To pinpoint the role of PPARα in the enhanced immune function of ACE-overexpressing macrophages, we established a line with myeloid lineage-selective PPARα depletion employing the Lysozyme 2 (LysM)-Cre system based on ACE 10/10 mice (named A10-PPARα-Cre). Interestingly, A10-PPARα-Cre mice exhibited larger B16-F10-originated tumors than original ACE 10/10 mice. PPARα depletion impaired cytokine production and antigen-presenting activity in ACE-overexpressing macrophages, resulting in reduced tumor antigen-specific CD8+ T cell activity. Additionally, the anti-bactericidal effect was also impaired in A10-PPARα-Cre mice, resulting in similar bacterial colonization to WT mice in Methicillin-Resistant Staphylococcus aureus (MRSA) infection. PPARα depletion downregulated phagocytic activity and bacteria killing in ACE-overexpressing macrophages. Moreover, THP-1-ACE-derived macrophages, as a human model, expressing upregulated PPARα exhibited enhanced cytotoxicity against B16-F10 cells and MRSA killing. These activities were further enhanced by the PPARα agonist, WY 14643, while abolished by the antagonist, GW6471, in THP-1-ACE cells. Thus, PPARα is an indispensable molecule in ACE-dependent functional upregulation of macrophages in both mice and humans.

An inflection point in high-throughput proteomics with Orbitrap Astral: analysis of biofluids, cells, and tissues.

This technical note presents a comprehensive proteomics workflow for the new combination of Orbitrap and Astral mass analyzers across biofluids, cells, and tissues. Central to our workflow is the integration of Adaptive Focused Acoustics (AFA) technology for cells and tissue lysis, to ensure robust and reproducible sample preparation in a high-throughput manner. Furthermore, we automated the detergent-compatible single-pot, solid-phase-enhanced sample Preparation (SP3) method for protein digestion, a technique that streamlines the process by combining purification and digestion steps, thereby reducing sample loss and improving efficiency. The synergy of these advanced methodologies facilitates a robust and high-throughput approach for cells and tissue analysis, an important consideration in translational research. This work disseminates our platform workflow, analyzes the effectiveness, demonstrates reproducibility of the results, and highlights the potential of these technologies in biomarker discovery and disease pathology. For cells and tissues (heart, liver, lung, and intestine) proteomics analysis by data-independent acquisition mode, identifications exceeding 10,000 proteins can be achieved with a 24-minute active gradient. In 200ng injections of HeLa digest across multiple gradients, an average of more than 80% of proteins have a CV less than 20%, and a 45-minute run covers ~90% of the expressed proteome. In plasma samples including naive, depleted, perchloric acid precipitated, and Seer nanoparticle captured, all with a 24-minute gradient length, we identified 87, 108, 96 and 137 out of 216 FDA approved circulating protein biomarkers, respectively. This complete workflow allows for large swaths of the proteome to be identified and is compatible across diverse sample types.

Fast skeletal myosin binding protein-C expression exacerbates dysfunction in heart failure.

During heart failure, gene and protein expression profiles undergo extensive compensatory and pathological remodeling. We previously observed that fast skeletal myosin binding protein-C (fMyBP-C) is upregulated in diseased mouse hearts. While fMyBP-C shares significant homology with its cardiac paralog, cardiac myosin binding protein-C (cMyBP-C), there are key differences that may affect cardiac function. However, it is unknown if the expression of fMyBP-C expression in the heart is a pathological or compensatory response. We aim to elucidate the cardiac consequence of either increased or knockout of fMyBP-C expression. To determine the sufficiency of fMyBP-C to cause cardiac dysfunction, we generated cardiac-specific fMyBP-C over-expression mice. These mice were further crossed into a cMyBP-C null model to assess the effect of fMyBP-C in the heart in the complete absence of cMyBP-C. Finally, fMyBP-C null mice underwent transverse aortic constriction (TAC) to define the requirement of fMyBP-C during heart failure development. We confirmed the upregulation of fMyBP-C in several models of cardiac disease, including the use of lineage tracing. Low levels of fMyBP-C caused mild cardiac remodeling and sarcomere dysfunction. Exclusive expression of fMyBP-C in a heart failure model further exacerbated cardiac pathology. Following 8 weeks of TAC, fMyBP-C null mice demonstrated greater protection against heart failure development. Mechanistically, this may be due to the differential regulation of the myosin super-relaxed state. These findings suggest that the elevated expression of fMyBP-C in diseased hearts is a pathological response. Targeted therapies to prevent upregulation of fMyBP-C may prove beneficial in the treatment of heart failure. Significance Statement: Recently, the sarcomere - the machinery that controls heart and muscle contraction - has emerged as a central target for development of cardiac therapeutics. However, there remains much to understand about how the sarcomere is modified in response to disease. We recently discovered that a protein normally expressed in skeletal muscle, is present in the heart in certain settings of heart disease. How this skeletal muscle protein affects the function of the heart remained unknown. Using genetically engineered mouse models to modulate expression of this skeletal muscle protein, we determined that expression of this skeletal muscle protein in the heart negatively affects cardiac performance. Importantly, deletion of this protein from the heart could improve heart function suggesting a possible therapeutic avenue.

Mechanical loading reveals an intrinsic cardiomyocyte stiffness contribution to diastolic dysfunction in murine cardiometabolic disease.

Cardiometabolic syndromes including diabetes and obesity are associated with occurrence of heart failure with diastolic dysfunction. There are no specific treatments for diastolic dysfunction and therapies to manage symptoms have limited efficacy. Understanding of the cardiomyocyte origins of diastolic dysfunction is an important priority to identify new therapeutics. The investigative goal was to experimentally define in vitro stiffness (stress/strain) properties of isolated cardiomyocytes derived from rodent hearts exhibiting diastolic dysfunction in vivo in response to dietary induction of cardiometabolic disease. Mice fed a High Fat/Sugar Diet (HFSD vs control) for at least 25 weeks exhibited glucose intolerance, obesity and diastolic dysfunction (echo E/e'). Intact paced cardiomyocytes were functionally investigated in three conditions: non-loaded, loaded and stretched. Mean stiffness of HFSD cardiomyocytes was 70% higher than control. The E/e' doppler ratio for the origin hearts was elevated by 35%. A significant relationship was identified between in vitro cardiomyocyte stiffness and in vivo dysfunction severity. With conversion from non-loaded to loaded condition, the decrement in maximal sarcomere lengthening rate was more accentuated in HFSD cardiomyocytes (vs control). With stretch, the Ca 2+ transient decay time course was prolonged. With transition from 2-4Hz pacing, HFSD cardiomyocyte stiffness was further increased, yet diastolic Ca 2+ rise was 50% less than control. Collectively, these findings demonstrate that a component of cardiac diastolic dysfunction in cardiometabolic disease is derived from intrinsic cardiomyocyte mechanical abnormality. Differential responses to load, stretch and pacing suggest that a previously undescribed alteration in myofilament-Ca 2+ interaction contributes to cardiomyocyte stiffness in cardiometabolic disease. KEY POINTS: Understanding cardiomyocyte stiffness components is an important priority for identifying new therapeutics for diastolic dysfunction, a key feature of cardiometabolic disease. In this study cardiac function was measured in vivo (echocardiography) for mice fed a high-fat/sugar diet (HFSD, ≥25weeks) and performance of intact isolated cardiomyocytes derived from the same hearts was measured during pacing under non-loaded, loaded and stretched conditions in vitro . Using a calibrated cardiomyocyte stretch protocol, stiffness (stress/strain) was elevated in HFSD cardiomyocytes in vitro and correlated with diastolic dysfunction (E/e') in vivo . The HFSD cardiomyocyte Ca 2+ transient decay was prolonged in response to stretch, and stiffness was accentuated in response to pacing increase while the rise in diastolic Ca 2+ was attenuated. These findings suggest that stretch-dependent augmentation of the myofilament-Ca 2+ response during diastole partially underlies elevated cardiomyocyte stiffness and diastolic dysfunction of hearts of animals with cardiometabolic disease.

Interlaboratory Comparison of Antibody-Free LC-MS/MS Measurements of C-peptide and Insulin.

BACKGROUND: The enhanced precision and selectivity of liquid chromatography-tandem mass spectrometry (LC-MS/MS) makes it an attractive alternative to certain clinical immunoassays. Easily transferrable work flows could help facilitate harmonization and ensure high-quality patient care. We aimed to evaluate the interlaboratory comparability of antibody-free multiplexed insulin and C-peptide LC-MS/MS measurements. METHODS: The laboratories that comprise the Targeted Mass Spectrometry Assays for Diabetes and Obesity Research (TaMADOR) consortium verified the performance of a validated peptide-based assay (reproducibility, linearity, and lower limit of the measuring interval [LLMI]). An interlaboratory comparison study was then performed using shared calibrators, de-identified leftover laboratory samples, and reference materials. RESULTS: During verification, the measurements were precise (2.7% to 3.7%CV), linear (4 to 15 ng/mL for C-peptide and 2 to 14 ng/mL for insulin), and sensitive (LLMI of 0.04 to 0.10 ng/mL for C-peptide and 0.03 ng/mL for insulin). Median imprecision across the 3 laboratories was 13.4% (inter-quartile range [IQR] 11.6%) for C-peptide and 22.2% (IQR 20.9%) for insulin using individual measurements, and 10.8% (IQR 8.7%) and 15.3% (IQR 14.9%) for C-peptide and insulin, respectively, when replicate measurements were averaged. Method comparison with the University of Missouri reference method for C-peptide demonstrated a robust linear correlation with a slope of 1.044 and r2 = 0.99. CONCLUSIONS: Our results suggest that combined LC-MS/MS measurements of C-peptide and insulin are robust and adaptable and that standardization with a reference measurement procedure could allow accurate and precise measurements across sites, which could be important to diabetes research and help patient care in the future.

Proteomics of the heart.

Mass spectrometry-based proteomics is a sophisticated identification tool specializing in portraying protein dynamics at a molecular level. Proteomics provides biologists with a snapshot of context-dependent protein and proteoform expression, structural conformations, dynamic turnover, and protein-protein interactions. Cardiac proteomics can offer a broader and deeper understanding of the molecular mechanisms that underscore cardiovascular disease, and it is foundational to the development of future therapeutic interventions. This review encapsulates the evolution, current technologies, and future perspectives of proteomic-based mass spectrometry as it applies to the study of the heart. Key technological advancements have allowed researchers to study proteomes at a single-cell level and employ robot-assisted automation systems for enhanced sample preparation techniques, and the increase in fidelity of the mass spectrometers has allowed for the unambiguous identification of numerous dynamic posttranslational modifications. Animal models of cardiovascular disease, ranging from early animal experiments to current sophisticated models of heart failure with preserved ejection fraction, have provided the tools to study a challenging organ in the laboratory. Further technological development will pave the way for the implementation of proteomics even closer within the clinical setting, allowing not only scientists but also patients to benefit from an understanding of protein interplay as it relates to cardiac disease physiology.

The 2023 Report on the Proteome from the HUPO Human Proteome Project.

Since 2010, the Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify the protein parts list and (2) to make proteomics an integral part of multiomics studies of human health and disease. The HPP relies on international collaboration, data sharing, standardized reanalysis of MS data sets by PeptideAtlas and MassIVE-KB using HPP Guidelines for quality assurance, integration and curation of MS and non-MS protein data by neXtProt, plus extensive use of antibody profiling carried out by the Human Protein Atlas. According to the neXtProt release 2023-04-18, protein expression has now been credibly detected (PE1) for 18,397 of the 19,778 neXtProt predicted proteins coded in the human genome (93%). Of these PE1 proteins, 17,453 were detected with mass spectrometry (MS) in accordance with HPP Guidelines and 944 by a variety of non-MS methods. The number of neXtProt PE2, PE3, and PE4 missing proteins now stands at 1381. Achieving the unambiguous identification of 93% of predicted proteins encoded from across all chromosomes represents remarkable experimental progress on the Human Proteome parts list. Meanwhile, there are several categories of predicted proteins that have proved resistant to detection regardless of protein-based methods used. Additionally there are some PE1-4 proteins that probably should be reclassified to PE5, specifically 21 LINC entries and ∼30 HERV entries; these are being addressed in the present year. Applying proteomics in a wide array of biological and clinical studies ensures integration with other omics platforms as reported by the Biology and Disease-driven HPP teams and the antibody and pathology resource pillars. Current progress has positioned the HPP to transition to its Grand Challenge Project focused on determining the primary function(s) of every protein itself and in networks and pathways within the context of human health and disease.

Influence of FTDP-17 mutants on circular tau RNAs.

At least 53 mutations in the microtubule associated protein tau gene (MAPT) have been identified that cause frontotemporal dementia. 47 of these mutations are localized between exons 7 and 13. They could thus affect the formation of circular RNAs (circRNAs) from the MAPT gene that occurs through backsplicing from exon 12 to either exon 10 or exon 7. We analyzed representative mutants and found that five FTDP-17 mutations increase the formation of 12➔7 circRNA and three different mutations increase the amount of 12➔10 circRNA. CircRNAs are translated after undergoing adenosine to inosine RNA editing, catalyzed by ADAR enzymes. We found that the interferon induced ADAR1-p150 isoform has the strongest effect on circTau RNA translation. ADAR1-p150 activity had a stronger effect on circTau RNA expression and strongly decreased 12➔7 circRNA, but unexpectedly increased 12➔10 circRNA. In both cases, ADAR-activity strongly promoted translation of circTau RNAs. Unexpectedly, we found that the 12➔7 circTau protein interacts with eukaryotic initiation factor 4B (eIF4B), which is reduced by four FTDP-17 mutations located in the second microtubule domain. These are the first studies of the effect of human mutations on circular RNA formation and translation. They show that point mutations influence circRNA expression levels, likely through changes in pre-mRNA structures. The effect of the mutations is surpassed by editing of the circular RNAs, leading to their translation. Thus, circular RNAs and their editing status should be considered when analyzing FTDP-17 mutations.

The Molecular Twin artificial-intelligence platform integrates multi-omic data to predict outcomes for pancreatic adenocarcinoma patients.

Contemporary analyses focused on a limited number of clinical and molecular biomarkers have been unable to accurately predict clinical outcomes in pancreatic ductal adenocarcinoma. Here we describe a precision medicine platform known as the Molecular Twin consisting of advanced machine-learning models and use it to analyze a dataset of 6,363 clinical and multi-omic molecular features from patients with resected pancreatic ductal adenocarcinoma to accurately predict disease survival (DS). We show that a full multi-omic model predicts DS with the highest accuracy and that plasma protein is the top single-omic predictor of DS. A parsimonious model learning only 589 multi-omic features demonstrated similar predictive performance as the full multi-omic model. Our platform enables discovery of parsimonious biomarker panels and performance assessment of outcome prediction models learning from resource-intensive panels. This approach has considerable potential to impact clinical care and democratize precision cancer medicine worldwide.