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.

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.

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.

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.

A Dual Workflow to Improve the Proteomic Coverage in Plasma Using Data-Independent Acquisition-MS.

Plasma is one of the most important and common matrices for clinical chemistry and proteomic analyses. Data-independent acquisition (DIA) mass spectrometry has enabled the simultaneous quantitative analysis of hundreds of proteins in plasma samples in support population and disease studies. Depletion of the highest abundant proteins is a common tool to increase plasma proteome coverage, but this strategy can result in the nonspecific depletion of protein subsets with which proteins targeted for depletion interact, adversely affecting their analysis. Our work using an antibody-based depletion column revealed significant complementarity not only in the identification of the proteins derived from depleted and undepleted plasma, but importantly also in the extent to which different proteins can be reproducibly quantified in each fraction. We systematically defined four major quantitative parameters of increasing stringency in both the depleted plasma fraction and in undepleted plasma for 757 observed plasma proteins: Linearity cutoff r2 > 0.8; lower limit of quantification (LLOQ); measurement range; limit of detection (LOD). We applied the results of our study to build a web-based tool, PlasmaPilot, that can serve as a protocol decision tree to determine whether the analysis of a specific protein warrants IgY14 mediated depletion.

Lysine and Arginine Protein Post-translational Modifications by Enhanced DIA Libraries: Quantification in Murine Liver Disease.

Proteoforms containing post-translational modifications (PTMs) represent a degree of functional diversity only harnessed through analytically precise simultaneous quantification of multiple PTMs. Here we present a method to accurately differentiate an unmodified peptide from its PTM-containing counterpart through data-independent acquisition-mass spectrometry, leveraging small precursor mass windows to physically separate modified peptidoforms from each other during MS2 acquisition. We utilize a lysine and arginine PTM-enriched peptide assay library and site localization algorithm to simultaneously localize and quantify seven PTMs including mono-, di-, and trimethylation, acetylation, and succinylation in addition to total protein quantification in a single MS run without the need to enrich experimental samples. To evaluate biological relevance, this method was applied to liver lysate from differentially methylated nonalcoholic steatohepatitis (NASH) mouse models. We report that altered methylation and acetylation together with total protein changes drive the novel hypothesis of a regulatory function of PTMs in protein synthesis and mRNA stability in NASH.

Identification of Putative Early Atherosclerosis Biomarkers by Unsupervised Deconvolution of Heterogeneous Vascular Proteomes.

Coronary artery disease remains a leading cause of death in industrialized nations, and early detection of disease is a critical intervention target to effectively treat patients and manage risk. Proteomic analysis of mixed tissue homogenates may obscure subtle protein changes that occur uniquely in underlying tissue subtypes. The unsupervised 'convex analysis of mixtures' (CAM) tool has previously been shown to effectively segregate cellular subtypes from mixed expression data. In this study, we hypothesized that CAM would identify proteomic information specifically informative to early atherosclerosis lesion involvement that could lead to potential markers of early disease detection. We quantified the proteome of 99 paired abdominal aorta (AA) and left anterior descending coronary artery (LAD) specimens (N = 198 specimens total) acquired during autopsy of young adults free of diagnosed cardiac disease. The CAM tool was then used to segregate protein subsets uniquely associated with different underlying tissue types, yielding markers of normal and fibrous plaque (FP) tissues in LAD and AA (N = 62 lesions markers). CAM-derived FP marker expression was validated against pathologist estimated luminal surface involvement of FP, as well as in an orthogonal cohort of "pure" fibrous plaque, fatty streak, and normal vascular specimens. A targeted mass spectrometry (MS) assay quantified 39 of 62 CAM-FP markers in plasma from women with angiographically verified coronary artery disease (CAD, N = 46) or free from apparent CAD (control, N = 40). Elastic net variable selection with logistic regression reduced this list to 10 proteins capable of classifying CAD status in this cohort with <6% misclassification error, and a mean area under the receiver operating characteristic curve of 0.992 (confidence interval 0.968-0.998) after cross validation. The proteomics-CAM workflow identified lesion-specific molecular biomarker candidates by distilling the most representative molecules from heterogeneous tissue types.

Protein S-Nitrosylation Controls Glycogen Synthase Kinase 3ß Function Independent of Its Phosphorylation State.

RATIONALE: GSK-3ß (glycogen synthase kinase 3ß) is a multifunctional and constitutively active kinase known to regulate a myriad of cellular processes. The primary mechanism to regulate its function is through phosphorylation-dependent inhibition at serine-9 residue. Emerging evidence indicates that there may be alternative mechanisms that control GSK-3ß for certain functions. OBJECTIVES: Here, we sought to understand the role of protein S-nitrosylation (SNO) on the function of GSK-3ß. SNO-dependent modulation of the localization of GSK-3ß and its ability to phosphorylate downstream targets was investigated in vitro, and the network of proteins differentially impacted by phospho- or SNO-dependent GSK-3ß regulation and in vivo SNO modification of key signaling kinases during the development of heart failure was also studied. METHODS AND RESULTS: We found that GSK-3ß undergoes site-specific SNO both in vitro, in HEK293 cells, H9C2 myoblasts, and primary neonatal rat ventricular myocytes, as well as in vivo, in hearts from an animal model of heart failure and sudden cardiac death. S-nitrosylation of GSK-3ß significantly inhibits its kinase activity independent of the canonical phospho-inhibition pathway. S-nitrosylation of GSK-3ß promotes its nuclear translocation and access to novel downstream phosphosubstrates which are enriched for a novel amino acid consensus sequence motif. Quantitative phosphoproteomics pathway analysis reveals that nuclear GSK-3ß plays a central role in cell cycle control, RNA splicing, and DNA damage response. CONCLUSIONS: The results indicate that SNO has a differential effect on the location and activity of GSK-3ß in the cytoplasm versus the nucleus. SNO modification of GSK-3ß occurs in vivo and could contribute to the pathobiology of heart failure and sudden cardiac death.

Transient receptor potential channel 6 regulates abnormal cardiac S-nitrosylation in Duchenne muscular dystrophy.

Duchenne muscular dystrophy (DMD) is an X-linked disorder with dystrophin loss that results in skeletal and cardiac muscle weakening and early death. Loss of the dystrophin-sarcoglycan complex delocalizes nitric oxide synthase (NOS) to alter its signaling, and augments mechanosensitive intracellular Ca2+ influx. The latter has been coupled to hyperactivation of the nonselective cation channel, transient receptor potential canonical channel 6 (Trpc6), in isolated myocytes. As Ca2+ also activates NOS, we hypothesized that Trpc6 would help to mediate nitric oxide (NO) dysregulation and that this would be manifest in increased myocardial S-nitrosylation, a posttranslational modification increasingly implicated in neurodegenerative, inflammatory, and muscle disease. Using a recently developed dual-labeling proteomic strategy, we identified 1,276 S-nitrosylated cysteine residues [S-nitrosothiol (SNO)] on 491 proteins in resting hearts from a mouse model of DMD (dmdmdx:utrn+/-). These largely consisted of mitochondrial proteins, metabolic regulators, and sarcomeric proteins, with 80% of them also modified in wild type (WT). S-nitrosylation levels, however, were increased in DMD. Genetic deletion of Trpc6 in this model (dmdmdx:utrn+/-:trpc6-/-) reversed ∼70% of these changes. Trpc6 deletion also ameliorated left ventricular dilation, improved cardiac function, and tended to reduce fibrosis. Furthermore, under catecholamine stimulation, which also increases NO synthesis and intracellular Ca2+ along with cardiac workload, the hypernitrosylated state remained as it did at baseline. However, the impact of Trpc6 deletion on the SNO proteome became less marked. These findings reveal a role for Trpc6-mediated hypernitrosylation in dmdmdx:utrn+/- mice and support accumulating evidence that implicates nitrosative stress in cardiac and muscle disease.

Mining the Proteome Associated with Rheumatic and Autoimmune Diseases.

A steady increase in the incidence of osteoarthritis and other rheumatic diseases has been observed in recent decades, including autoimmune conditions such as rheumatoid arthritis, spondyloarthropathies, systemic lupus erythematosus, systemic sclerosis, and Sjögren's syndrome. Rheumatic and autoimmune diseases (RADs) are characterized by the inflammation of joints, muscles, or other connective tissues. In addition to often experiencing debilitating mobility and pain, RAD patients are also at a higher risk of suffering comorbidities such as cardiovascular or infectious events. Given the socioeconomic impact of RADs, broad research efforts have been dedicated to these diseases worldwide. In the present work, we applied literature mining platforms to identify "popular" proteins closely related to RADs. The platform is based on publicly available literature. The results not only will enable the systematic prioritization of candidates to perform targeted proteomics studies but also may lead to a greater insight into the key pathogenic processes of these disorders.

Mapping Citrullinated Sites in Multiple Organs of Mice Using Hypercitrullinated Library.

Protein citrullination (or deimination), an irreversible post-translational modification, has been implicated in several physiological and pathological processes, including gene expression regulation, apoptosis, rheumatoid arthritis, and Alzheimer's disease. Several research studies have been carried out on citrullination under many conditions. However, until now, challenges in sample preparation and data analysis have made it difficult to confidently identify a citrullinated protein and assign the citrullinated site. To overcome these limitations, we generated a mouse hyper-citrullinated spectral library and set up coordinates to confidently identify and validate citrullinated sites. Using this workflow, we detect a four-fold increase in citrullinated proteome coverage across six mouse organs compared with the current state-of-the art techniques. Our data reveal that the subcellular distribution of citrullinated proteins is tissue-type-dependent and that citrullinated targets are involved in fundamental physiological processes, including the metabolic process. These data represent the first report of a hyper-citrullinated library for the mouse and serve as a central resource for exploring the role of citrullination in this organism.

Proteomic Architecture of Human Coronary and Aortic Atherosclerosis.

BACKGOUND: The inability to detect premature atherosclerosis significantly hinders implementation of personalized therapy to prevent coronary heart disease. A comprehensive understanding of arterial protein networks and how they change in early atherosclerosis could identify new biomarkers for disease detection and improved therapeutic targets. METHODS: Here we describe the human arterial proteome and proteomic features strongly associated with early atherosclerosis based on mass spectrometry analysis of coronary artery and aortic specimens from 100 autopsied young adults (200 arterial specimens). Convex analysis of mixtures, differential dependent network modeling, and bioinformatic analyses defined the composition, network rewiring, and likely regulatory features of the protein networks associated with early atherosclerosis and how they vary across 2 anatomic distributions. RESULTS: The data document significant differences in mitochondrial protein abundance between coronary and aortic samples (coronary>>aortic), and between atherosclerotic and normal tissues (atherosclerotic<

Phospho-Proteomic Analysis of Cardiac Dyssynchrony and Resynchronization Therapy.

Cardiac dyssynchrony arises from conduction abnormalities during heart failure and worsens morbidity and mortality. Cardiac resynchronization therapy (CRT) re-coordinates contraction using bi-ventricular pacing, but the cellular and molecular mechanisms involved remain largely unknown. The aim is to determine how dyssynchronous heart failure (HFdys ) alters the phospho-proteome and how CRT interacts with this unique phospho-proteome by analyzing Ser/Thr and Tyr phosphorylation. Phospho-enriched myocardium from dog models of Control, HFdys , and CRT is analyzed via MS. There were 209 regulated phospho-sites among 1761 identified sites. Compared to Con and CRT, HFdys is hyper-phosphorylated and tyrosine phosphorylation is more likely to be involved in signaling that increased with HFdys and was exacerbated by CRT. For each regulated site, the most-likely targeting-kinase is predicted, and CK2 is highly specific for sites that are "fixed" by CRT, suggesting activation of CK2 signaling occurs in HFdys that is reversed by CRT, which is supported by western blot analysis. These data elucidate signaling networks and kinases that may be involved and deserve further study. Importantly, a possible role for CK2 modulation in CRT has been identified. This may be harnessed in the future therapeutically to compliment CRT, improving its clinical effects.

Identifying High-Priority Proteins Across the Human Diseasome Using Semantic Similarity.

Identifying the genes and proteins associated with a biological process or disease is a central goal of the biomedical research enterprise. However, relatively few systematic approaches are available that provide objective evaluation of the genes or proteins known to be important to a research topic, and hence researchers often rely on subjective evaluation of domain experts and laborious manual literature review. Computational bibliometric analysis, in conjunction with text mining and data curation, attempts to automate this process and return prioritized proteins in any given research topic. We describe here a method to identify and rank protein-topic relationships by calculating the semantic similarity between a protein and a query term in the biomerical literature while adjusting for the impact and immediacy of associated research articles. We term the calculated metric the weighted copublication distance (WCD) and show that it compares well to related approaches in predicting benchmark protein lists in multiple biological processes. We used WCD to extract prioritized "popular proteins" across multiple cell types, subanatomical regions, and standardized vocabularies containing over 20 000 human disease terms. The collection of protein-disease associations across the resulting human "diseasome" supports data analytical workflows to perform reverse protein-to-disease queries and functional annotation of experimental protein lists. We envision that the described improvement to the popular proteins strategy will be useful for annotating protein lists and guiding method development efforts as well as generating new hypotheses on understudied disease proteins using bibliometric information.

Molecular Profile of Priapism Associated with Low Nitric Oxide Bioavailability.

Priapism is a disorder in which prolonged penile erection persists uncontrollably, potentially leading to tissue damage. Priapism commonly afflicts patient populations with severely low nitric oxide (NO) bioavailability. Because NO is a primary mediator of erection, the molecular mechanisms involved in priapism pathophysiology associated with low NO bioavailability are not well-understood. The objective of this study was to identify dysregulated molecular targets and signaling pathways in penile tissue of a mouse model of low NO bioavailability that have potential relevance to priapism. Neuronal plus endothelial NO synthase double knockout mice (NOS1/3-/-) were used as a model of low NO bioavailability. Priapic-like activity was demonstrated in the NOS1/3-/- mice relative to wild-type (WT) mice by the measurement of prolonged erections following cessation of electrical stimulation of the cavernous nerve. Penile tissue was processed and analyzed by reverse-phase liquid chromatography tandem mass spectrometry. As a result, 1279 total proteins were identified and quantified by spectral counting, 46 of which were down-regulated and 110 of which were up-regulated in NOS1/3-/- versus WT (P < 0.05). Ingenuity Pathway Analysis of differentially expressed proteins revealed increased protein kinase A and G-protein coupled receptor signaling in NOS1/3-/- penises, which represent potential mechanisms contributing to priapism for secondary to low NO bioavailability.

Proteomics reveals Rictor as a noncanonical TGF-ß signaling target during aneurysm progression in Marfan mice.

The objective of the present study was to 1) analyze the ascending aortic proteome within a mouse model of Marfan syndrome (MFS; Fbn1C1041G/+) at early and late stages of aneurysm and 2) subsequently test a novel hypothesis formulated on the basis of this unbiased proteomic screen that links changes in integrin composition to transforming growth factor (TGF)-ß-dependent activation of the rapamycin-independent component of mammalian target of rapamycin (Rictor) signaling pathway. Ingenuity Pathway Analysis of over 1,000 proteins quantified from the in vivo MFS mouse aorta by data-independent acquisition mass spectrometry revealed a predicted upstream regulator, Rictor, that was selectively activated in aged MFS mice. We validated this pattern of Rictor activation in vivo by Western blot analysis for phosphorylation on Thr1135 in a separate cohort of mice and showed in vitro that TGF-ß activates Rictor in an integrin-linked kinase-dependent manner in cultured aortic vascular smooth muscle cells. Expression of ß3-integrin was upregulated in the aged MFS aorta relative to young MFS mice and wild-type mice. We showed that ß3-integrin expression and activation modulated TGF-ß-induced Rictor phosphorylation in vitro, and this signaling effect was associated with an altered vascular smooth muscle cell proliferative-migratory and metabolic in vitro phenotype that parallels the in vivo aneurysm phenotype in MFS. These results reveal that Rictor is a novel, context-dependent, noncanonical TGF-ß signaling effector with potential pathogenic implications in aortic aneurysm. NEW & NOTEWORTHY We present the most comprehensive quantitative analysis of the ascending aortic aneurysm proteome in Marfan syndrome to date resulting in novel and potentially wide-reaching findings that expression and signaling by ß3-integrin constitute a modulator of transforming growth factor-ß-induced rapamycin-independent component of mammalian target of rapamycin (Rictor) signaling and physiology in aortic vascular smooth muscle cells.

Dual Labeling Biotin Switch Assay to Reduce Bias Derived From Different Cysteine Subpopulations: A Method to Maximize S-Nitrosylation Detection.

RATIONALE: S-nitrosylation (SNO), an oxidative post-translational modification of cysteine residues, responds to changes in the cardiac redox-environment. Classic biotin-switch assay and its derivatives are the most common methods used for detecting SNO. In this approach, the labile SNO group is selectively replaced with a single stable tag. To date, a variety of thiol-reactive tags have been introduced. However, these methods have not produced a consistent data set, which suggests an incomplete capture by a single tag and potentially the presence of different cysteine subpopulations. OBJECTIVE: To investigate potential labeling bias in the existing methods with a single tag to detect SNO, explore if there are distinct cysteine subpopulations, and then, develop a strategy to maximize the coverage of SNO proteome. METHODS AND RESULTS: We obtained SNO-modified cysteine data sets for wild-type and S-nitrosoglutathione reductase knockout mouse hearts (S-nitrosoglutathione reductase is a negative regulator of S-nitrosoglutathione production) and nitric oxide-induced human embryonic kidney cell using 2 labeling reagents: the cysteine-reactive pyridyldithiol and iodoacetyl based tandem mass tags. Comparison revealed that <30% of the SNO-modified residues were detected by both tags, whereas the remaining SNO sites were only labeled by 1 reagent. Characterization of the 2 distinct subpopulations of SNO residues indicated that pyridyldithiol reagent preferentially labels cysteine residues that are more basic and hydrophobic. On the basis of this observation, we proposed a parallel dual-labeling strategy followed by an optimized proteomics workflow. This enabled the profiling of 493 SNO sites in S-nitrosoglutathione reductase knockout hearts. CONCLUSIONS: Using a protocol comprising 2 tags for dual-labeling maximizes overall detection of SNO by reducing the previously unrecognized labeling bias derived from different cysteine subpopulations.

Identification of a Set of Conserved Eukaryotic Internal Retention Time Standards for Data-independent Acquisition Mass Spectrometry.

Accurate knowledge of retention time (RT) in liquid chromatography-based mass spectrometry data facilitates peptide identification, quantification, and multiplexing in targeted and discovery-based workflows. Retention time prediction is particularly important for peptide analysis in emerging data-independent acquisition (DIA) experiments such as SWATH-MS. The indexed RT approach, iRT, uses synthetic spiked-in peptide standards (SiRT) to set RT to a unit-less scale, allowing for normalization of peptide RT between different samples and chromatographic set-ups. The obligatory use of SiRTs can be costly and complicates comparisons and data integration if standards are not included in every sample. Reliance on SiRTs also prevents the inclusion of archived mass spectrometry data for generation of the peptide assay libraries central to targeted DIA-MS data analysis. We have identified a set of peptide sequences that are conserved across most eukaryotic species, termed Common internal Retention Time standards (CiRT). In a series of tests to support the appropriateness of the CiRT-based method, we show: (1) the CiRT peptides normalized RT in human, yeast, and mouse cell lysate derived peptide assay libraries and enabled merging of archived libraries for expanded DIA-MS quantitative applications; (2) CiRTs predicted RT in SWATH-MS data within a 2-min margin of error for the majority of peptides; and (3) normalization of RT using the CiRT peptides enabled the accurate SWATH-MS-based quantification of 340 synthetic isotopically labeled peptides that were spiked into either human or yeast cell lysate. To automate and facilitate the use of these CiRT peptide lists or other custom user-defined internal RT reference peptides in DIA workflows, an algorithm was designed to automatically select a high-quality subset of datapoints for robust linear alignment of RT for use. Implementations of this algorithm are available for the OpenSWATH and Skyline platforms. Thus, CiRT peptides can be used alone or as a complement to SiRTs for RT normalization across peptide spectral libraries and in quantitative DIA-MS studies.

Effect of peptide assay library size and composition in targeted data-independent acquisition-MS analyses.

The quantification of peptides using targeted analysis of data-independent acquisition MS (DIA-MS) is dependent on the size and characteristics of the assay library. We addressed several important questions on how library composition influences: (1) the number of peptides extracted from DIA-MS datasets, (2) the quality of these peptides and proteins, and (3) the biological conclusions inferred. To answer these questions we constructed five libraries from mouse vascular smooth muscle cell (VSMC) lysate, each unique in depth, input sample complexity, data acquisition mode (DDA-MS or DIA-MS), and precursor fragmentation mode (TOF-CID or Orbitrap HCD) and extracted them against the same eight DIA-MS files of VSMCs treated with vehicle or transforming growth factor ß-1 (TGF-ß1). We found that along with differences in peptide and protein composition, the fragments representing a given peptide differed between the libraries. Collectively these differences impacted both peak group score profile and protein abundance estimates. Surprisingly, there was little overlap in the TGF-ß1 response proteome between libraries. We conclude that additional work is needed to optimize peptide assay library building for DIA-MS applications, particularly in terms of selecting optimal peptides and their respective fragments for protein quantification.

Data-Driven Approach To Determine Popular Proteins for Targeted Proteomics Translation of Six Organ Systems.

Amidst the proteomes of human tissues lie subsets of proteins that are closely involved in conserved pathophysiological processes. Much of biomedical research concerns interrogating disease signature proteins and defining their roles in disease mechanisms. With advances in proteomics technologies, it is now feasible to develop targeted proteomics assays that can accurately quantify protein abundance as well as their post-translational modifications; however, with rapidly accumulating number of studies implicating proteins in diseases, current resources are insufficient to target every protein without judiciously prioritizing the proteins with high significance and impact for assay development. We describe here a data science method to prioritize and expedite assay development on high-impact proteins across research fields by leveraging the biomedical literature record to rank and normalize proteins that are popularly and preferentially published by biomedical researchers. We demonstrate this method by finding priority proteins across six major physiological systems (cardiovascular, cerebral, hepatic, renal, pulmonary, and intestinal). The described method is data-driven and builds upon the collective knowledge of previous publications referenced on PubMed to lend objectivity to target selection. The method and resulting popular protein lists may also be useful for exploring biological processes associated with various physiological systems and research topics, in addition to benefiting ongoing efforts to facilitate the broad translation of proteomics technologies.