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.

PKG1-modified TSC2 regulates mTORC1 activity to counter adverse cardiac stress.

The mechanistic target of rapamycin complex-1 (mTORC1) coordinates regulation of growth, metabolism, protein synthesis and autophagy1. Its hyperactivation contributes to disease in numerous organs, including the heart1,2, although broad inhibition of mTORC1 risks interference with its homeostatic roles. Tuberin (TSC2) is a GTPase-activating protein and prominent intrinsic regulator of mTORC1 that acts through modulation of RHEB (Ras homologue enriched in brain). TSC2 constitutively inhibits mTORC1; however, this activity is modified by phosphorylation from multiple signalling kinases that in turn inhibits (AMPK and GSK-3ß) or stimulates (AKT, ERK and RSK-1) mTORC1 activity3-9. Each kinase requires engagement of multiple serines, impeding analysis of their role in vivo. Here we show that phosphorylation or gain- or loss-of-function mutations at either of two adjacent serine residues in TSC2 (S1365 and S1366 in mice; S1364 and S1365 in humans) can bidirectionally control mTORC1 activity stimulated by growth factors or haemodynamic stress, and consequently modulate cell growth and autophagy. However, basal mTORC1 activity remains unchanged. In the heart, or in isolated cardiomyocytes or fibroblasts, protein kinase G1 (PKG1) phosphorylates these TSC2 sites. PKG1 is a primary effector of nitric oxide and natriuretic peptide signalling, and protects against heart disease10-13. Suppression of hypertrophy and stimulation of autophagy in cardiomyocytes by PKG1 requires TSC2 phosphorylation. Homozygous knock-in mice that express a phosphorylation-silencing mutation in TSC2 (TSC2(S1365A)) develop worse heart disease and have higher mortality after sustained pressure overload of the heart, owing to mTORC1 hyperactivity that cannot be rescued by PKG1 stimulation. However, cardiac disease is reduced and survival of heterozygote Tsc2S1365A knock-in mice subjected to the same stress is improved by PKG1 activation or expression of a phosphorylation-mimicking mutation (TSC2(S1365E)). Resting mTORC1 activity is not altered in either knock-in model. Therefore, TSC2 phosphorylation is both required and sufficient for PKG1-mediated cardiac protection against pressure overload. The serine residues identified here provide a genetic tool for bidirectional regulation of the amplitude of stress-stimulated mTORC1 activity.

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.

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.

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.

Automated proteomic sample preparation: The key component for high throughput and quantitative mass spectrometry analysis.

Sample preparation for mass spectrometry-based proteomics has many tedious and time-consuming steps that can introduce analytical errors. In particular, the steps around the proteolytic digestion of protein samples are prone to inconsistency. One route for reliable sample processing is the development and optimization of a workflow utilizing an automated liquid handling workstation. Diligent assessment of the sample type, protocol design, reagents, and incubation conditions can significantly improve the speed and consistency of preparation. When combining robust liquid chromatography-mass spectrometry with either discovery or targeted methods, automated sample preparation facilitates increased throughput and reproducible quantitation of biomarker candidates. These improvements in analysis are also essential to process the large patient cohorts necessary to validate a candidate biomarker for potential clinical use. This article reviews the steps in the workflow, optimization strategies, and known applications in clinical, pharmaceutical, and research fields that demonstrate the broad utility for improved automation of sample preparation in the proteomic field.

Sexual Dimorphism in Cardiovascular Biomarkers: Clinical and Research Implications.

Sex-based differences in cardiovascular disease presentation, diagnosis, and response to therapies are well established, but mechanistic understanding and translation to clinical applications are limited. Blood-based biomarkers have become an important tool for interrogating biologic pathways. Understanding sexual dimorphism in the relationship between biomarkers and cardiovascular disease will enhance our insights into cardiovascular disease pathogenesis in women, with potential to translate to improved individualized care for men and women with or at risk for cardiovascular disease. In this review, we examine how biologic sex associates with differential levels of blood-based biomarkers and influences the effect of biomarkers on disease outcomes. We further summarize key differences in blood-based cardiovascular biomarkers along central biologic pathways, including myocardial stretch/injury, inflammation, adipose tissue metabolism, and fibrosis pathways in men versus women. Finally, we present recommendations for leveraging our current knowledge of sex differences in blood-based biomarkers for future research and clinical innovation.

New Views of Old Proteins: Clarifying the Enigmatic Proteome.

All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide a >10 years of projection for technologies to meet the challenges that protein biology presents. With a broad perspective, we discuss grand opportunities to transition the science of proteomics into a more propulsive enterprise. Extrapolating recent trends, we describe a next generation of approaches to define, quantify, and visualize the multiple dimensions of the proteome, thereby transforming our understanding and interactions with human disease in the coming decade.

High-Field Asymmetric Waveform Ion Mobility Spectrometry: Practical Alternative for Cardiac Proteome Sample Processing.

Heart tissue sample preparation for mass spectrometry (MS) analysis that includes prefractionation reduces the cellular protein dynamic range and increases the relative abundance of nonsarcomeric proteins. We previously described "IN-Sequence" (IN-Seq) where heart tissue lysate is sequentially partitioned into three subcellular fractions to increase the proteome coverage more than a single direct tissue analysis by mass spectrometry. Here, we report an adaptation of the high-field asymmetric ion mobility spectrometry (FAIMS) coupled to mass spectrometry, and the establishment of a simple one step sample preparation coupled with gas-phase fractionation. The FAIMS approach substantially reduces manual sample handling, significantly shortens the MS instrument processing time, and produces unique protein identification and quantification approximating the commonly used IN-Seq method in less time.

BIRCH: An Automated Workflow for Evaluation, Correction, and Visualization of Batch Effect in Bottom-Up Mass Spectrometry-Based Proteomics Data.

Recent surges in large-scale mass spectrometry (MS)-based proteomics studies demand a concurrent rise in methods to facilitate reliable and reproducible data analysis. Quantification of proteins in MS analysis can be affected by variations in technical factors such as sample preparation and data acquisition conditions leading to batch effects, which adds to noise in the data set. This may in turn affect the effectiveness of any biological conclusions derived from the data. Here we present Batch-effect Identification, Representation, and Correction of Heterogeneous data (BIRCH), a workflow for analysis and correction of batch effect through an automated, versatile, and easy to use web-based tool with the goal of eliminating technical variation. BIRCH also supports diagnosis of the data to check for the presence of batch effects, feasibility of batch correction, and imputation to deal with missing values in the data set. To illustrate the relevance of the tool, we explore two case studies, including an iPSC-derived cell study and a Covid vaccine study to show different context-specific use cases. Ultimately this tool can be used as an extremely powerful approach for eliminating technical bias while retaining biological bias, toward understanding disease mechanisms and potential therapeutics.

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.

swCAM: estimation of subtype-specific expressions in individual samples with unsupervised sample-wise deconvolution.

MOTIVATION: Complex biological tissues are often a heterogeneous mixture of several molecularly distinct cell subtypes. Both subtype compositions and subtype-specific (STS) expressions can vary across biological conditions. Computational deconvolution aims to dissect patterns of bulk tissue data into subtype compositions and STS expressions. Existing deconvolution methods can only estimate averaged STS expressions in a population, while many downstream analyses such as inferring co-expression networks in particular subtypes require subtype expression estimates in individual samples. However, individual-level deconvolution is a mathematically underdetermined problem because there are more variables than observations. RESULTS: We report a sample-wise Convex Analysis of Mixtures (swCAM) method that can estimate subtype proportions and STS expressions in individual samples from bulk tissue transcriptomes. We extend our previous CAM framework to include a new term accounting for between-sample variations and formulate swCAM as a nuclear-norm and ℓ2,1-norm regularized matrix factorization problem. We determine hyperparameter values using cross-validation with random entry exclusion and obtain a swCAM solution using an efficient alternating direction method of multipliers. Experimental results on realistic simulation data show that swCAM can accurately estimate STS expressions in individual samples and successfully extract co-expression networks in particular subtypes that are otherwise unobtainable using bulk data. In two real-world applications, swCAM analysis of bulk RNASeq data from brain tissue of cases and controls with bipolar disorder or Alzheimer's disease identified significant changes in cell proportion, expression pattern and co-expression module in patient neurons. Comparative evaluation of swCAM versus peer methods is also provided. AVAILABILITY AND IMPLEMENTATION: The R Scripts of swCAM are freely available at https://github.com/Lululuella/swCAM. A user's guide and a vignette are provided. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

S-adenosylmethionine inhibits la ribonucleoprotein domain family member 1 in murine liver and human liver cancer cells.

BACKGROUND AND AIMS: Methionine adenosyltransferase 1A (MAT1A) is responsible for S-adenosylmethionine (SAMe) biosynthesis in the liver. Mice lacking Mat1a have hepatic SAMe depletion and develop NASH and HCC spontaneously. Several kinases are activated in Mat1a knockout (KO) mice livers. However, characterizing the phospho-proteome and determining whether they contribute to liver pathology remain open for study. Our study aimed to provide this knowledge. APPROACH AND RESULTS: We performed phospho-proteomics in Mat1a KO mice livers with and without SAMe treatment to identify SAMe-dependent changes that may contribute to liver pathology. Our studies used Mat1a KO mice at different ages treated with and without SAMe, cell lines, in vitro translation and kinase assays, and human liver specimens. We found that the most striking change was hyperphosphorylation and increased content of La-related protein 1 (LARP1), which, in the unphosphorylated form, negatively regulates translation of 5'-terminal oligopyrimidine (TOP)-containing mRNAs. Consistently, multiple TOP proteins are induced in KO livers. Translation of TOP mRNAs ribosomal protein S3 and ribosomal protein L18 was enhanced by LARP1 overexpression in liver cancer cells. We identified LARP1-T449 as a SAMe-sensitive phospho-site of cyclin-dependent kinase 2 (CDK2). Knocking down CDK2 lowered LARP1 phosphorylation and prevented LARP1-overexpression-mediated increase in translation. LARP1-T449 phosphorylation induced global translation, cell growth, migration, invasion, and expression of oncogenic TOP-ribosomal proteins in HCC cells. LARP1 expression is increased in human NASH and HCC. CONCLUSIONS: Our results reveal a SAMe-sensitive mechanism of LARP1 phosphorylation that may be involved in the progression of NASH to HCC.

Retinal pathological features and proteome signatures of Alzheimer's disease.

Alzheimer's disease (AD) pathologies were discovered in the accessible neurosensory retina. However, their exact nature and topographical distribution, particularly in the early stages of functional impairment, and how they relate to disease progression in the brain remain largely unknown. To better understand the pathological features of AD in the retina, we conducted an extensive histopathological and biochemical investigation of postmortem retina and brain tissues from 86 human donors. Quantitative examination of superior and inferior temporal retinas from mild cognitive impairment (MCI) and AD patients compared to those with normal cognition (NC) revealed significant increases in amyloid ß-protein (Aß42) forms and novel intraneuronal Aß oligomers (AßOi), which were closely associated with exacerbated retinal macrogliosis, microgliosis, and tissue atrophy. These pathologies were unevenly distributed across retinal layers and geometrical areas, with the inner layers and peripheral subregions exhibiting most pronounced accumulations in the MCI and AD versus NC retinas. While microgliosis was increased in the retina of these patients, the proportion of microglial cells engaging in Aß uptake was reduced. Female AD patients exhibited higher levels of retinal microgliosis than males. Notably, retinal Aß42, S100 calcium-binding protein B+ macrogliosis, and atrophy correlated with severity of brain Aß pathology, tauopathy, and atrophy, and most retinal pathologies reflected Braak staging. All retinal biomarkers correlated with the cognitive scores, with retinal Aß42, far-peripheral AßOi and microgliosis displaying the strongest correlations. Proteomic analysis of AD retinas revealed activation of specific inflammatory and neurodegenerative processes and inhibition of oxidative phosphorylation/mitochondrial, and photoreceptor-related pathways. This study identifies and maps retinopathy in MCI and AD patients, demonstrating the quantitative relationship with brain pathology and cognition, and may lead to reliable retinal biomarkers for noninvasive retinal screening and monitoring of AD.

Myofilament Phosphorylation in Stem Cell Treated Diastolic Heart Failure.

RATIONALE: Phosphorylation of sarcomeric proteins has been implicated in heart failure with preserved ejection fraction (HFpEF); such changes may contribute to diastolic dysfunction by altering contractility, cardiac stiffness, Ca2+-sensitivity, and mechanosensing. Treatment with cardiosphere-derived cells (CDCs) restores normal diastolic function, attenuates fibrosis and inflammation, and improves survival in a rat HFpEF model. OBJECTIVE: Phosphorylation changes that underlie HFpEF and those reversed by CDC therapy, with a focus on the sarcomeric subproteome were analyzed. METHODS AND RESULTS: Dahl salt-sensitive rats fed a high-salt diet, with echocardiographically verified diastolic dysfunction, were randomly assigned to either intracoronary CDCs or placebo. Dahl salt-sensitive rats receiving low salt diet served as controls. Protein and phosphorylated Ser, Thr, and Tyr residues from left ventricular tissue were quantified by mass spectrometry. HFpEF hearts exhibited extensive hyperphosphorylation with 98% of the 529 significantly changed phospho-sites increased compared with control. Of those, 39% were located within the sarcomeric subproteome, with a large group of proteins located or associated with the Z-disk. CDC treatment partially reverted the hyperphosphorylation, with 85% of the significantly altered 76 residues hypophosphorylated. Bioinformatic upstream analysis of the differentially phosphorylated protein residues revealed PKC as the dominant putative regulatory kinase. PKC isoform analysis indicated increases in PKC α, ß, and δ concentration, whereas CDC treatment led to a reversion of PKCß. Use of PKC isoform specific inhibition and overexpression of various PKC isoforms strongly suggests that PKCß is the dominant kinase involved in hyperphosphorylation in HFpEF and is altered with CDC treatment. CONCLUSIONS: Increased protein phosphorylation at the Z-disk is associated with diastolic dysfunction, with PKC isoforms driving most quantified phosphorylation changes. Because CDCs reverse the key abnormalities in HFpEF and selectively reverse PKCß upregulation, PKCß merits being classified as a potential therapeutic target in HFpEF, a disease notoriously refractory to medical intervention.

Biological substrate modification suppresses ventricular arrhythmias in a porcine model of chronic ischaemic cardiomyopathy.

AIMS: Cardiomyopathy patients are prone to ventricular arrhythmias (VA) and sudden cardiac death. Current therapies to prevent VA include radiofrequency ablation to destroy slowly conducting pathways of viable myocardium which support re-entry. Here, we tested the reverse concept, namely that boosting local tissue viability in zones of slow conduction might eliminate slow conduction and suppress VA in ischaemic cardiomyopathy. METHODS AND RESULTS: Exosomes are extracellular vesicles laden with bioactive cargo. Exosomes secreted by cardiosphere-derived cells (CDCEXO) reduce scar and improve heart function after intramyocardial delivery. In a VA-prone porcine model of ischaemic cardiomyopathy, we injected CDCEXO or vehicle into zones of delayed conduction defined by electroanatomic mapping. Up to 1-month post-injection, CDCEXO, but not the vehicle, decreased myocardial scar, suppressed slowly conducting electrical pathways, and inhibited VA induction by programmed electrical stimulation. In silico reconstruction of electrical activity based on magnetic resonance images accurately reproduced the suppression of VA inducibility by CDCEXO. Strong anti-fibrotic effects of CDCEXO, evident histologically and by proteomic analysis from pig hearts, were confirmed in a co-culture assay of cardiomyocytes and fibroblasts. CONCLUSION: Biological substrate modification by exosome injection may be worth developing as a non-destructive alternative to conventional ablation for the prevention of recurrent ventricular tachyarrhythmias.

Comparative Proteomic Analysis of HPV(+) Oropharyngeal Squamous Cell Carcinoma Recurrence.

Deintensification therapy for human papillomavirus-related oropharyngeal squamous cell carcinoma (HPV(+) OPSCC) is under active investigation. An adaptive treatment approach based on molecular stratification could identify high-risk patients predisposed to recurrence and better select for appropriate treatment regimens. Collectively, 40 HPV(+) OPSCC FFPE samples (20 disease-free, 20 recurrent) were surveyed using mass spectrometry-based proteomic analysis via data-independent acquisition to obtain fold change and false discovery differences. Ten-year overall survival was 100.0 and 27.7% for HPV(+) disease-free and recurrent cohorts, respectively. Of 1414 quantified proteins, 77 demonstrated significant differential expression. Top enriched functional pathways included those involved in programmed cell death (73 proteins, p = 7.43 × 10-30), apoptosis (73 proteins, p = 5.56 × 10-9), ß-catenin independent WNT signaling (47 proteins, p = 1.45 × 10-15), and Rho GTPase signaling (69 proteins, p = 1.09 × 10-5). PFN1 (p = 1.0 × 10-3), RAD23B (p = 2.9 × 10-4), LDHB (p = 1.0 × 10-3), and HINT1 (p = 3.8 × 10-3) pathways were significantly downregulated in the recurrent cohort. On functional validation via immunohistochemistry (IHC) staining, 46.9% (PFN1), 71.9% (RAD23B), 59.4% (LDHB), and 84.4% (HINT1) of cases were corroborated with mass spectrometry findings. Development of a multilateral molecular signature incorporating these targets may characterize high-risk disease, predict treatment response, and augment current management paradigms in head and neck cancer.

US Severe Acute Respiratory Syndrome Coronavirus 2 Epsilon Variant: Highly Transmissible but With an Adjusted Muted Host T-Cell Response.

BACKGROUND: The multiple mutations comprising the epsilon variant demonstrate the independent convergent evolution of severe acute respiratory syndrome coronavirus (SARS-CoV-2), with its spike protein mutation L452R present in the delta (L452R), kappa (L452R), and lambda (L452Q) variants. METHODS: Coronavirus disease 2019 (COVID-19) variants were detected in 1017 patients using whole-genome sequencing and were assessed for outcome and severity. The mechanistic effects of the epsilon versus non-epsilon variants were investigated using a multiomic approach including cellular response assays and paired cell and host transcriptomic and proteomic profiling. RESULTS: We found that patients carrying the epsilon variant had increased mortality risk but not increased hospitalizations (P < .02). Cells infected with live epsilon compared with non-epsilon virus displayed increased sensitivity to neutralization antibodies in all patients but a slightly protective response in vaccinated individuals (P < .001). That the epsilon SARS-CoV-2 variant is more infectious but less virulent is supported mechanistically in the down-regulation of viral processing pathways seen by multiomic analyses. Importantly, this paired transcriptomics and proteomic profiling of host cellular response to live virus revealed an altered leukocyte response and metabolic messenger RNA processing with the epsilon variant. To ascertain host response to SARS-CoV-2 infection, primary COVID-19-positive nasopharyngeal samples were transcriptomically profiled and revealed a differential innate immune response (P < .001) and an adjusted T-cell response in patients carrying the epsilon variant (P < .002). In fact, patients infected with SARS-CoV-2 and those vaccinated with the BNT162b2 vaccine have comparable CD4+/CD8+ T-cell immune responses to the epsilon variant (P < .05). CONCLUSIONS: While the epsilon variant is more infectious, by altering viral processing, we showed that patients with COVID-19 have adapted their innate immune response to this fitter variant. A protective T-cell response molecular signature is generated by this more transmissible variant in both vaccinated and unvaccinated patients.

Parallelization with Dual-Trap Single-Column Configuration Maximizes Throughput of Proteomic Analysis.

Proteomic analysis on the scale that captures population and biological heterogeneity over hundreds to thousands of samples requires rapid mass spectrometry methods, which maximize instrument utilization (IU) and proteome coverage while maintaining precise and reproducible quantification. To achieve this, a short liquid chromatography gradient paired to rapid mass spectrometry data acquisition can be used to reproducibly quantify a moderate set of analytes. High-throughput profiling at a limited depth is becoming an increasingly utilized strategy for tackling large sample sets but the time spent on loading the sample, flushing the column(s), and re-equilibrating the system reduces the ratio of meaningful data acquired to total operation time and IU. The dual-trap single-column configuration (DTSC) presented here maximizes IU in rapid analysis (15 min per sample) of blood and cell lysates by parallelizing trap column cleaning and sample loading and desalting with the analysis of the previous sample. We achieved 90% IU in low microflow (9.5 µL/min) analysis of blood while reproducibly quantifying 300-400 proteins and over 6000 precursor ions. The same IU was achieved for cell lysates and over 4000 proteins (3000 at CV below 20%) and 40,000 precursor ions were quantified at a rate of 15 min/sample. Thus, DTSC enables high-throughput epidemiological blood-based biomarker cohort studies and cell-based perturbation screening.

Standardized Workflow for Precise Mid- and High-Throughput Proteomics of Blood Biofluids.

BACKGROUND: Accurate discovery assay workflows are critical for identifying authentic circulating protein biomarkers in diverse blood matrices. Maximizing the commonalities in the proteomic workflows between different biofluids simplifies the approach and increases the likelihood for reproducibility. We developed a workflow that can accommodate 3 blood-based proteomes: naive plasma, depleted plasma and dried blood. METHODS: Optimal conditions for sample preparation and data independent acquisition-mass spectrometry analysis were established in plasma then automated for depleted plasma and dried blood. The mass spectrometry workflow was modified to facilitate sensitive high-throughput analysis or deeper profiling with mid-throughput analysis. Analytical performance was evaluated by the linear response of peptides and proteins to a 6- or 7-point dilution curve and the reproducibility of the relative peptide and protein intensity for 5 digestion replicates per day on 3 different days for each biofluid. RESULTS: Using the high-throughput workflow, 74% (plasma), 93% (depleted), and 87% (dried blood) displayed an inter-day CV <30%. The mid-throughput workflow had 67% (plasma), 90% (depleted), and 78% (dried blood) of peptides display an inter-day CV <30%. Lower limits of detection and quantification were determined for peptides and proteins observed in each biofluid and workflow. Based on each protein and peptide's analytical performance, we could describe the observable, reliable, reproducible, and quantifiable proteomes for each biofluid and workflow. CONCLUSION: The standardized workflows established here allows for reproducible and quantifiable detection of proteins covering a broad dynamic range. We envisage that implementation of this standard workflow should simplify discovery approaches and facilitate the translation of candidate markers into clinical use.