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.

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.

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.

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.

The ALPHA phase 1 study: pulmonary ArteriaL hypertension treated with CardiosPHere-Derived allogeneic stem cells.

BACKGROUND: Pulmonary Arterial Hypertension (PAH) is a progressive condition with no cure. Even with pharmacologic advances, survival remains poor. Lung pathology on PAH therapies still shows impressive occlusive arteriolar remodelling and plexiform lesions. Cardiosphere-derived cells (CDCs) are heart-derived progenitor cells exhibiting anti-inflammatory and immunomodulatory effects, are anti -fibrotic, anti-oxidative and anti-apoptotic to potentially impact several aspects of PAH pathobiology. In preclinical trials CDCs reduced right ventricular (RV) systolic pressure, RV hypertrophy, pulmonary arteriolar wall thickness and inflammation. METHODS: The ALPHA study was a Phase 1a/b study in which CDCs were infused into patients with Idiopathic (I)PAH, Heritable (H) HPAH, PAH-connective tissue disease (CTD) and PAH-human immunodeficiency virus (HIV). The study was IRB approved and DSMB monitored. Phase 1a, was an open label study (n = 6). Phase 1b was a double-blind placebo-controlled study (n = 20) in which half received 100 million CDCs (the maximum feasible dose from manufacturing perspective) and half placebo (PLAC) infusions. Right heart catheterization (RHC) and cardiac MR imaging (cMR) were performed at baseline and at 4 months post infusion. Patients were followed over a year. FINDINGS: No short-term clinical safety adverse events (AE) were related to the IP, the primary outcome measure. There were no adverse hemodynamic, gas exchange, rhythm or other clinical events following infusion and in the 1st 23 h monitored in hospital. There were no long-term AEs over 12 months noted, including unrelated limited hospitalizations. No immunologic short or long-term AEs were noted. We examined exploratory outcomes across multiple domains to determine encouraging signals to motivate future advanced phase testing. Phase 1a data showed encouraging observations for both 50 and 100 million CDC doses. Several encouraging findings favouring CDCs (n = 16) compared to placebo (n = 10) were noted. On cMR, the RV end diastolic volume (RVEDV) and index (RVEDVI) decreased with CDCs with a rise in the PLAC group. The 6-min walk distance was increased 2 months post infusion in the CDC group compared with PLAC. With PLAC, diffusing capacity (DLCO) decreased at 4 months but was unchanged with CDCs. Serum creatinine decreased with CDCs at 4 months. Encouraging observations favouring CDCs were also noted for RV fractional area change on echo and RV ejection fraction (RVEF) on cMR at 4 months. No differences were observed for mean pulmonary artery pressures or pulmonary vascular resistance. Review of long-term data to 12 months showed continued decline in DLCO for the PLAC cohort at 6 months with no change through 12 months. By contrast, CDC subjects showed an unchanged DLCO over 12-months. For parameters exhibiting early encouraging exploratory findings in CDC subjects, no further improvement was noted in long-term follow up through 12 months. INTERPRETATION: Intravenous CDCs were safe in both the short and long term in PAH subjects and thus may be safe in larger cohorts, in line with our extensive track record of safety in clinical trials for other conditions. Further, CDCs exhibited encouraging exploratory findings across several domains. Repeat dosing (quarterly, over one year) of intravenous CDCs has been reported to yield highly significant sustained disease-modifying bioactivity in subjects with advanced Duchenne muscular dystrophy. Because only single CDC doses were used here, the findings represent a lower limit estimate of CDC's potential in PAH. Upcoming phase 2 studies would logically use a repeat dosing paradigm. FUNDING: California Institute for Regenerative Medicine (CIRM). Project Number: CLIN2-09444.

MicroRNA and Protein Cargos of Human Limbal Epithelial Cell-Derived Exosomes and Their Regulatory Roles in Limbal Stromal Cells of Diabetic and Non-Diabetic Corneas.

Epithelial and stromal/mesenchymal limbal stem cells contribute to corneal homeostasis and cell renewal. Extracellular vesicles (EVs), including exosomes (Exos), can be paracrine mediators of intercellular communication. Previously, we described cargos and regulatory roles of limbal stromal cell (LSC)-derived Exos in non-diabetic (N) and diabetic (DM) limbal epithelial cells (LECs). Presently, we quantify the miRNA and proteome profiles of human LEC-derived Exos and their regulatory roles in N- and DM-LSC. We revealed some miRNA and protein differences in DM vs. N-LEC-derived Exos' cargos, including proteins involved in Exo biogenesis and packaging that may affect Exo production and ultimately cellular crosstalk and corneal function. Treatment by N-Exos, but not by DM-Exos, enhanced wound healing in cultured N-LSCs and increased proliferation rates in N and DM LSCs vs. corresponding untreated (control) cells. N-Exos-treated LSCs reduced the keratocyte markers ALDH3A1 and lumican and increased the MSC markers CD73, CD90, and CD105 vs. control LSCs. These being opposite to the changes quantified in wounded LSCs. Overall, N-LEC Exos have a more pronounced effect on LSC wound healing, proliferation, and stem cell marker expression than DM-LEC Exos. This suggests that regulatory miRNA and protein cargo differences in DM- vs. N-LEC-derived Exos could contribute to the disease state.

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 occur 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 the secondary 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. Highlights: 47/53 known FTDP-17 mutations are located in regions that could influence generation of circular RNAs from the MAPT geneCircular Tau RNAs are translated after adenosine to inosine RNA editing, most effectively caused by ADAR1-p150FTDP-17 mutations influence both circTau RNA and circTau protein expression levelsCircTau protein expression levels do not correlate with circTau RNA expression levelsCircTau proteins bind to eukaryotic initiation factor 4B, which is antagonized by FTDP-17 mutations in exon 10.

Identification of novel biomarkers for the prediction of subclinical coronary artery atherosclerosis in patients with rheumatoid arthritis: an exploratory analysis.

BACKGROUND: Cardiovascular (CV) risk estimation calculators for the general population underperform in patients with rheumatoid arthritis (RA). The purpose of this study was to identify relevant protein biomarkers that could be added to traditional CV risk calculators to improve the capacity of coronary artery calcification (CAC) prediction in individuals with RA. In a second step, we quantify the improvement of this prediction of CAC when these circulating biomarkers are added to standard risk scores. METHODS: A panel of 141 serum and plasma proteins, which represent a broad base of both CV and RA biology, were evaluated and prioritized as candidate biomarkers. Of these, 39 proteins were selected and measured by commercial ELISA or quantitative mass spectroscopy in 561 individuals with RA in whom a measure of CAC and frozen sera were available. The patients were randomly split 50:50 into a training/validation cohort. Discrimination (using area under the receiver operator characteristic curves) and re-classification (through net reclassification improvement and integrated discrimination improvement calculation) analyses were performed first in the training cohort and replicated in the validation cohort, to estimate the increase in prediction accuracy for CAC using the ACA/AHA (American College of Cardiology and the American Heart Association) score with, compared to without, addition of these circulating biomarkers. RESULTS: The model containing ACC/AHA score plus cytokines (osteopontin, cartilage glycoprotein-39, cystatin C, and chemokine (C-C motif) ligand 18) and plus quantitative mass spectroscopy biomarkers (serpin D1, paraoxonase, and clusterin) had a statistically significant positive net reclassifications index and integrated discrimination improvement for the prediction of CAC, using ACC/AHA score without any biomarkers as the reference category. These results were confirmed in the validation cohort. CONCLUSION: In this exploratory analysis, the addition of several circulating CV and RA biomarkers to a standard CV risk calculator yielded significant improvements in discrimination and reclassification for the presence of CAC in individuals with RA.

Protein Coronas on Functionalized Nanoparticles Enable Quantitative and Precise Large-Scale Deep Plasma Proteomics.

Background: The wide dynamic range of circulating proteins coupled with the diversity of proteoforms present in plasma has historically impeded comprehensive and quantitative characterization of the plasma proteome at scale. Automated nanoparticle (NP) protein corona-based proteomics workflows can efficiently compress the dynamic range of protein abundances into a mass spectrometry (MS)-accessible detection range. This enhances the depth and scalability of quantitative MS-based methods, which can elucidate the molecular mechanisms of biological processes, discover new protein biomarkers, and improve comprehensiveness of MS-based diagnostics. Methods: Investigating multi-species spike-in experiments and a cohort, we investigated fold-change accuracy, linearity, precision, and statistical power for the using the Proteograph™ Product Suite, a deep plasma proteomics workflow, in conjunction with multiple MS instruments. Results: We show that NP-based workflows enable accurate identification (false discovery rate of 1%) of more than 6,000 proteins from plasma (Orbitrap Astral) and, compared to a gold standard neat plasma workflow that is limited to the detection of hundreds of plasma proteins, facilitate quantification of more proteins with accurate fold-changes, high linearity, and precision. Furthermore, we demonstrate high statistical power for the discovery of biomarkers in small- and large-scale cohorts. Conclusions: The automated NP workflow enables high-throughput, deep, and quantitative plasma proteomics investigation with sufficient power to discover new biomarker signatures with a peptide level resolution.

Peptidyl arginine deiminase inhibition alleviates angiotensin II-induced fibrosis.

OBJECTIVES: The conversion of protein arginine residues to citrulline by calcium-dependent peptidyl arginine deiminases (PADs) has been implicated in the pathogenesis of several diseases, indicating that PADs are therapeutic targets. A recent study indicated that PAD4 regulates age-related organ fibrosis and dysfunction; however, the specific role of this PAD and its citrullination substrate remains unclear. We investigated whether pharmacological inhibition of PAD activity could affect the progression of fibrosis and restore heart function. METHODS: Cardiac hypertrophy was induced by chronic infusion of angiotensin (Ang) II. After 2 weeks of AngII infusion, a PAD inhibitor (Cl-amidine hydrochloride) or vehicle (saline) was injected every other day for the next 14 days together with the continued administration of AngII for a total of up to 28 days. Cardiac fibrosis and remodeling were evaluated by quantitative heart tissue histology, echocardiography, and mass spectrometry. RESULTS: A reverse AngII-induced effect was observed in PAD inhibitor-treated mice (n=6) compared with AngII vehicle-treated mice, as indicated by a significant reduction in the heart/body ratio (AngII: 6.51±0.8 mg/g vs. Cl-amidine: 5.27±0.6 mg/g), a reduction in fibrosis (AngII: 2.1-fold increased vs. Cl-amidine: 1.8-fold increased), and a reduction in left ventricular posterior wall diastole (LWVPd) (AngII: 1.1±0.04 vs. Cl-amidine: 0.78±0.02 mm). Label-free quantitative proteomics analysis of heart tissue indicated that proteins involved in fibrosis (e.g., periostin), cytoskeleton organization (e.g., transgelin), and remodeling (e.g., myosin light chain, carbonic anhydrase) were normalized by Cl-amidine treatment. CONCLUSION: Our findings demonstrate that pharmacological inhibition of PAD may be an effective strategy to attenuate cardiac fibrosis.

ABDS: tool suite for analyzing biologically diverse samples.

Motivation: Analytics tools are essential to identify informative molecular features about different phenotypic groups. Among the most fundamental tasks are missing value imputation, signature gene detection, and expression pattern visualization. However, most commonly used analytics tools may be problematic for characterizing biologically diverse samples when either signature genes possess uneven missing rates across different groups yet involving complex missing mechanisms, or multiple biological groups are simultaneously compared and visualized. Results: We develop ABDS tool suite tailored specifically to analyzing biologically diverse samples. Mechanism-integrated group-wise imputation is developed to recruit signature genes involving informative missingness, cosine-based one-sample test is extended to detect enumerated signature genes, and unified heatmap is designed to comparably display complex expression patterns. We discuss the methodological principles and demonstrate the conceptual advantages of the three software tools. We also showcase the biomedical applications of these individual tools. Implemented in open-source R scripts, ABDS tool suite complements rather than replaces the existing tools and will allow biologists to more accurately detect interpretable molecular signals among diverse phenotypic samples. Availability and implementation: The R Scripts of ABDS tool suite is freely available at https://github.com/niccolodpdu/ABDS.

A Complete Workflow for High Throughput Human Single Skeletal Muscle Fiber Proteomics.

Skeletal muscle is a major regulatory tissue of whole-body metabolism and is composed of a diverse mixture of cell (fiber) types. Aging and several diseases differentially affect the various fiber types, and therefore, investigating the changes in the proteome in a fiber-type specific manner is essential. Recent breakthroughs in isolated single muscle fiber proteomics have started to reveal heterogeneity among fibers. However, existing procedures are slow and laborious, requiring 2 h of mass spectrometry time per single muscle fiber; 50 fibers would take approximately 4 days to analyze. Thus, to capture the high variability in fibers both within and between individuals requires advancements in high throughput single muscle fiber proteomics. Here we use a single cell proteomics method to enable quantification of single muscle fiber proteomes in 15 min total instrument time. As proof of concept, we present data from 53 isolated skeletal muscle fibers obtained from two healthy individuals analyzed in 13.25 h. Adapting single cell data analysis techniques to integrate the data, we can reliably separate type 1 and 2A fibers. Ninety-four proteins were statistically different between clusters indicating alteration of proteins involved in fatty acid oxidation, oxidative phosphorylation, and muscle structure and contractile function. Our results indicate that this method is significantly faster than prior single fiber methods in both data collection and sample preparation while maintaining sufficient proteome depth. We anticipate this assay will enable future studies of single muscle fibers across hundreds of individuals, which has not been possible previously due to limitations in throughput.

Assessment of a 60-Biomarker Health Surveillance Panel (HSP) on Whole Blood from Remote Sampling Devices by Targeted LC/MRM-MS and Discovery DIA-MS Analysis.

Telehealth, accessing healthcare and wellness remotely, should be a cost-effective and efficient way for individuals to receive care. The convenience of having a reliable remote collection device for blood tests will facilitate access to precision medicine and healthcare. Herein, we tested a 60-biomarker health surveillance panel (HSP), containing 35 FDA/LDT assays and covering at least 14 pathological states, on 8 healthy individuals' ability to collect their own capillary blood from a lancet finger prick and directly compared it to the traditional phlebotomist venous blood and plasma collection methods. All samples were spiked with 114 stable-isotope-labeled (SIL) HSP peptides and quantitatively analyzed by liquid chromatography-multiple reaction monitoring-mass spectrometry (LC/MRM-MS) scheduled method targeting 466 transitions from 114 HSP peptides and by a discovery data-independent acquisition mass spectrometry (DIA-MS) method. The average peak area ratio (PAR) of the HSP quantifier peptide transitions from all 8 volunteers' capillary blood (n = 48), venous blood (n = 48), and matched plasma (n = 24) was <20% coefficients of variation (CV). Heat map analysis of all 8 volunteers demonstrated that each individual had a unique biosignature. Biological replicates from capillary blood and venous blood clustered within each volunteer in k-means clustering analysis. Pearson statistical analysis of the three biofluids indicated that there was >90% similarity. Discovery DIA-MS analysis of the same samples using a plasma spectral library and a pan-human spectral library identified 1121 and 4661 total proteins, respectively. In addition, at least 122 FDA-approved biomarkers were identified. DIA-MS analysis reproducibly quantitated (<30% CV) ∼600-700 proteins in capillary blood, ∼800 proteins in venous blood, and ∼300-400 proteins in plasma, demonstrating that an expansive biomarker panel is possible with current mass spectrometry technology. Both targeted LC/MRM-MS and discovery DIA-MS analysis of whole blood collected on remote sampling devices are viable options for personal proteome biosignature stratification in precision medicine and precision health.