Sarah J. Parker

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.

Discordant signaling and autophagy response to fasting in hearts of obese mice: Implications for ischemia tolerance

Autophagy is regulated by nutrient and energy status and plays an adaptive role during nutrient deprivation and ischemic stress. Metabolic syndrome (MetS) is a hypernutritive state characterized by obesity, dyslipidemia, elevated fasting blood glucose levels, and insulin resistance. It has also been associated with impaired autophagic flux and larger-sized infarcts. We hypothesized that diet-induced obesity (DIO) affects nutrient sensing, explaining the observed cardiac impaired autophagy. We subjected male friend virus B NIH (FVBN) mice to a high-fat diet, which resulted in increased weight gain, fat deposition, hyperglycemia, insulin resistance, and larger infarcts after myocardial ischemia-reperfusion. Autophagic flux was impaired after 4 wk on a high-fat diet. To interrogate nutrient-sensing pathways, DIO mice were subjected to overnight fasting, and hearts were processed for biochemical and proteomic analysis. Obese mice failed to upregulate LC3-II or to clear p62/SQSTM1 after fasting, although mRNA for LC3B and p62/SQSTM1 were appropriately upregulated in both groups, demonstrating an intact transcriptional response to fasting. Energy- and nutrient-sensing signal transduction pathways [AMPK and mammalian target of rapamycin (mTOR)] also responded appropriately to fasting, although mTOR was more profoundly suppressed in obese mice. Proteomic quantitative analysis of the hearts under fed and fasted conditions revealed broad changes in protein networks involved in oxidative phosphorylation, autophagy, oxidative stress, protein homeostasis, and contractile machinery. In many instances, the fasting response was quite discordant between lean and DIO mice. Network analysis implicated the peroxisome proliferator-activated receptor and mTOR regulatory nodes. Hearts of obese mice exhibited impaired autophagy, altered proteome, and discordant response to nutrient deprivation.

Multiple and Selective Reaction Monitoring Using Triple Quadrupole Mass Spectrometer: Preclinical Large Cohort Analysis.

Multiple reaction monitoring (MRM), sometimes referred to as selective reaction monitoring (SRM), is a mass spectrometry method that can target selective peptides for the detection and quantitation of a protein. Compared to traditional ELISA, MRM assays have a number of advantages including ease in multiplexing several proteins in the same assay and independence from the necessity for high-quality, expensive, and at times unreliable antibodies. Furthermore, MRM assays can be developed to quantify multiple proteoforms of a single protein allowing the quantification of allelic expression of a particular sequence polymorphism, protein isoform, as well as determining site occupancy of posttranslational modification(s). In this chapter, we describe our workflow for target peptide selection, assay optimization, and acquisition multiplexing. Our workflow is presented using the example of constrained MRM assays developed for the serum protein ApoL1 in its various proteoforms to highlight the specific technical considerations necessary for the difficult task of quantifying peptide targets based on highly specific amino acid sequences by MRM.

Methods for SWATH™: Data Independent Acquisition on TripleTOF Mass Spectrometers

Data independent acquisition (DIA also termed SWATH) is an emerging technology in the field of mass spectrometry based proteomics. Although the concept of DIA has been around for over a decade, the recent advancements, in particular the speed of acquisition, of mass analyzers have pushed the technique into the spotlight and allowed for high-quality DIA data to be routinely acquired by proteomics labs. In this chapter we will discuss the protocols used for DIA acquisition using the Sciex TripleTOF mass spectrometers and data analysis using the Sciex processing software.

The Cohesive Metastasis Phenotype in Human Prostate Cancer

A critical barrier for the successful prevention and treatment of recurrent prostate cancer is detection and eradication of metastatic and therapy-resistant disease. Despite the fall in diagnoses and mortality, the reported incidence of metastatic disease has increased 72% since 2004. Prostate cancer arises in cohesive groups as intraepithelial neoplasia, migrates through muscle and leaves the gland via perineural invasion for hematogenous dissemination. Current technological advances have shown cohesive-clusters of tumor (also known as microemboli) within the circulation. Circulating tumor cell (CTC) profiles are indicative of disseminated prostate cancer, and disseminated tumor cells (DTC) are found in cohesive-clusters, a phenotypic characteristic of both radiation- and drug-resistant tumors. Recent reports in cell biology and informatics, coupled with mass spectrometry, indicate that the integrin adhesome network provides an explanation for the biophysical ability of cohesive-clusters of tumor cells to invade thorough muscle and nerve microenvironments while maintaining adhesion-dependent therapeutic resistance. Targeting cohesive-clusters takes advantage of the known ability of extracellular matrix (ECM) adhesion to promote tumor cell survival and represents an approach that has the potential to avoid the progression to drug- and radiotherapy-resistance. In the following review we will examine the evidence for development and dissemination of cohesive-clusters in metastatic prostate cancer.

Extracellular matrix downregulation in the Drosophila heart preserves contractile function and improves lifespan

Aging is associated with extensive remodeling of the heart, including basement membrane (BM) components that surround cardiomyocytes. Remodeling is thought to impair cardiac mechanotransduction, but the contribution of specific BM components to age-related lateral communication between cardiomyocytes is unclear. Using a genetically tractable, rapidly aging model with sufficient cardiac genetic homology and morphology, e.g. Drosophila melanogaster, we observed differential regulation of BM collagens between laboratory strains, correlating with changes in muscle physiology leading to cardiac dysfunction. Therefore, we sought to understand the extent to which BM proteins modulate contractile function during aging. Cardiac-restricted knockdown of ECM genes Pericardin, Laminin A, and Viking in Drosophila prevented age-associated heart tube restriction and increased contractility, even under viscous load. Most notably, reduction of Laminin A expression correlated with an overall preservation of contractile velocity with age and extension of organismal lifespan. Global heterozygous knockdown confirmed these data, which provides new evidence of a direct link between BM homeostasis, contractility, and maintenance of lifespan.

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 β‐1 (TGF‐β1). 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‐β1 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.

Highly Reproducible Automated Proteomics Sample Preparation Workflow for Quantitative Mass Spectrometry

Sample preparation for protein quantification by mass spectrometry requires multiple processing steps including denaturation, reduction, alkylation, protease digestion, and peptide cleanup. Scaling these procedures for the analysis of numerous complex biological samples can be tedious and time-consuming, as there are many liquid transfer steps and timed reactions where technical variations can be introduced and propagated. We established an automated sample preparation workflow with a total processing time for 96 samples of 5 h, including a 2 h incubation with trypsin. Peptide cleanup is accomplished by online diversion during the LC/MS/MS analysis. In a selected reaction monitoring (SRM) assay targeting 6 plasma biomarkers and spiked β-galactosidase, mean intraday and interday cyclic voltammograms (CVs) for 5 serum and 5 plasma samples over 5 days were <20%. In a highly multiplexed SRM assay targeting more than 70 proteins, 90% of the transitions from 6 plasma samples repeated on 3 separate days had total CVs below 20%. Similar results were obtained when the workflow was transferred to a second site: 93% of peptides had CVs below 20%. An automated trypsin digestion workflow yields uniformly processed samples in less than 5 h. Reproducible quantification of peptides was observed across replicates, days, instruments, and laboratory sites, demonstrating the broad applicability of this approach.

Precision Profiling of the Cardiovascular Post-Translationally Modified Proteome: Where There Is a Will, There Is a Way

There is an exponential increase in biological complexity as initial gene transcripts are spliced, translated into amino acid sequence, and post-translationally modified. Each protein can exist as multiple chemical or sequence-specific proteoforms, and each has the potential to be a critical mediator of a physiological or pathophysiological signaling cascade. Here, we provide an overview of how different proteoforms come about in biological systems and how they are most commonly measured using mass spectrometry-based proteomics and bioinformatics. Our goal is to present this information at a level accessible to every scientist interested in mass spectrometry and its application to proteome profiling. We will specifically discuss recent data linking various protein post-translational modifications to cardiovascular disease and conclude with a discussion for enablement and democratization of proteomics across the cardiovascular and scientific community. The aim is to inform and inspire the readership to explore a larger breadth of proteoform, particularity post-translational modifications, related to their particular areas of expertise in cardiovascular physiology.

Multi-omic profiling of TKI resistant K562 cells suggests metabolic reprogramming to promote cell survival

Resistance to chemotherapy can occur through a wide variety of mechanisms. Typically, resistance tyrosine kinase inhibitors (TKIs) is thought to arise from kinase mutations or signaling pathway reprogramming—however, “off-target” adaptations enabling survival in the presence of TKIs without resistant mutations are poorly understood. Previously, we established cell line resistance models for the three most commonly used TKIs in chronic myeloid leukemia treatment, and found that their resistance to cell death was not attributed entirely to failure of kinase inhibition. In the present study, we performed global, integrated proteomic and transcriptomic profiling of these cell lines to describe the mechanisms of resistance at the protein and gene expression level. We used whole transcriptome RNA sequencing and SWATH-based data-independent acquisition mass spectrometry (DIA-MS). This MS approach does not require isotopic labels and provides quantitative measurements of proteins in a comprehensive, unbiased fashion: a significantly greater proportion of proteins are reliably quantified with this method, in comparison to traditional MS methods. The proteomic and transcriptional data were correlated to generate an integrated understanding of the gene expression and protein alterations associated with TKI resistance. We identified mechanisms of resistance that were unique to each TKI. Additionally, we defined mechanisms of resistance that were common to all TKIs tested. Resistance to all of the TKIs was associated with the oxidative stress responses, hypoxia signatures, and apparent metabolic reprogramming of the cells. Metabolite profiling and glucose-dependence experiments showed that the resistant cells relied on glycolysis (particularly through the pentose phosphate pathway) more heavily than the sensitive cells, which supported the idea that metabolism alterations were associated with resistant cell survival. These experiments are the first to report a global, integrated proteomic and transcriptomic analysis of TKI resistance. These data suggest that targeting metabolic pathways along with TKI treatment may overcome pan-TKI resistance. Key Points Alterations to metabolism are a common feature of target-mutation-independent resistance in CML cells across multiple clinically relevant TKIs. Carbonic anhydrase 1 (CA1) and α-synuclein (SNCA) are novel functional markers of metabolic reprogramming in TKI resistant CML cells.