Rapid empirical discovery of optimal peptides for targeted proteomics

Delineating protein biomarkers for gastric cancers: A catalogue of mass spectrometry-based markers and assessing their suitability for targeted proteomics applications

Gastric cancer (GC) is a global health concern. To facilitate improved management of GCs protein biomarkers have been identified through mass spectrometry-based proteomics platforms. In order to exhibit clinical utility of such data, we congregated over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the mass spectrometry platforms, association of the protein with infectious agents, protein identifiers, sample size and clinical characters of samples used with details on validation. Development of targeted proteomics methods is the cornerstone for pursuing these markers into clinical utility. Therefore, we developed Protein Biomarker Matrix for Gastric Cancer (PBMGC), a simple catalogue of robustness of each protein. This analysis yielded the identification of robust tissue, serum, urine and prognostic protein panels which can be further tested for their clinical utility. We also ascertained proteotypic tryptic peptides of 5631 proteins suitable for developing MRM assays. Extensive characterization of these peptides was carried out to record peptide ions, mass/charge and enhanced specific peptide features. With the vision of catering to proteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). Users can browse and download the data and improve GCPDB by submitting recently published data. SIGNIFICANCE: Mass spectrometry-based proteomics platforms have accumulated substantial data on protein differential regulation in gastric cancer (GC) clinical samples. The utility of such data in clinical applications is limited by search for suitable biomarker panels for assessing GCs. We assembled over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the corresponding details including mass spectrometry platforms, status on the association of the protein with infectious agents, protein identifiers from different databases, sample size and clinical characters of samples used in test and control conditions along with details on their validation. Towards the vision of utilizing these markers in clinical assays, Protein Biomarker Matrix for Gastric Cancer (PBMGC) was developed and clinically relevant multi-protein panels were identified. We also demonstrated identification and characterization of tryptic proteotypic tryptic peptides of 5631 proteins biomarkers of GCs which are suitable for development of multiple reaction monitoring (MRM) assays in a SCIEX QTRAP instrument. With the moto of catering to proteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). The users can browse and download details on different markers and improve GCPDB by submitting recently published data. Such an analysis could lay a cornerstone for building more such resources or conduct such analysis in different clinical conditions to uptake and develop targeted proteomics as the method of choice for clinical applications.

Development of highly multiplex targeted proteomics assays in biofluids using the Stellar mass spectrometer

The development of targeted assays that monitor biomedically relevant proteins is an important step in bridging discovery experiments to large scale clinical studies. Targeted assays are currently unable to scale to hundreds or thousands of targets. We demonstrate the generation of large-scale assays using a novel hybrid nominal mass instrument. The scale of these assays is achievable with the Stellar™ mass spectrometer through the accommodation of shifting retention times by real-time alignment, while being sensitive and fast enough to handle many concurrent targets. Assays were constructed using precursor information from gas-phase fractionated (GPF) data-independent acquisition (DIA). We demonstrate the ability to schedule methods from an orbitrap and linear ion trap acquired GPF DIA library and compare the quantification of a matrix-matched calibration curve from orbitrap DIA and linear ion trap parallel reaction monitoring (PRM). Two applications of these proposed workflows are shown with a cerebrospinal fluid (CSF) neurodegenerative disease protein PRM assay and with a Mag-Net enriched plasma extracellular vesicle (EV) protein survey PRM assay.

Hybrid Quadrupole Mass Filter - Radial Ejection Linear Ion Trap and Intelligent Data Acquisition Enable Highly Multiplex Targeted Proteomics

Targeted mass spectrometry (MS) methods are powerful tools for selective and sensitive analysis of peptides identified by global discovery experiments. Selected reaction monitoring (SRM) is currently the most widely accepted MS method in the clinic, due to its reliability and analytical performance. However, due to limited throughput and the difficulty in setting up and analyzing large scale assays, SRM and parallel reaction monitoring (PRM) are typically used only for very refined assays of on the order of 100 targets or less. Here we introduce a new MS platform with a quadrupole mass filter, collision cell, linear ion trap architecture that has increased acquisition rates compared to the analogous hardware found in the Orbitrap™ Tribrid™ series instruments. The platform can target more analytes than existing SRM and PRM instruments - in the range of 5000 to 8000 peptides per hour. This capability for high multiplexing is enabled by acquisition rates of 70-100 Hz for peptide applications, and the incorporation of real-time chromatogram alignment that adjusts for retention time drift and enables narrow time scheduled acquisition windows. Finally, we describe a Skyline external software tool that implements the building of targeted methods based on data independent acquisition chromatogram libraries or unscheduled analysis of heavy labeled standards. We show that the platform delivers ~10x lower LOQs than traditional SRM analysis for a highly multiplex assay and also demonstrate how analytical figures of merit change while varying method duration with a constant number of analytes, or by keeping a constant time duration while varying the number of analytes.

Data Independent Acquisition to Inform the Development of Targeted Proteomics Assays Using a Triple Quadrupole Mass Spectrometer

Mass spectrometry based targeted proteomics methods provide sensitive and high-throughput analysis of selected proteins. To develop a targeted bottom-up proteomics assay, peptides must be evaluated as proxies for the measurement of a protein or proteoform in a biological matrix. Candidate peptide selection typically relies on predetermined biochemical properties, data from semi-stochastic sampling, or by empirical measurements. These strategies require extensive testing and method refinement due to the difficulties associated with prediction of peptide response in the biological matrix of interest. Gas-phase fractionated (GPF) narrow window data-independent acquisition (DIA) aids in the development of reproducible selected reaction monitoring (SRM) assays by providing matrix-specific information on peptide detectability and quantification by mass spectrometry. To demonstrate the suitability of DIA data for selecting peptide targets, we reimplement a portion of an existing assay to measure 98 Alzheimer's disease proteins in cerebrospinal fluid (CSF). Peptides were selected from GPF-DIA based on signal intensity and reproducibility. The resulting SRM assay exhibits similar quantitative precision to published data, despite the inclusion of different peptides between the assays. This workflow enables development of new assays without additional up-front data acquisition, demonstrated here through generation of a separate assay for an unrelated set of proteins in CSF from the same dataset.

An accelerated and optimized algorithm of selenium-encoded isotopic signature targeted profiling for global selenoproteome analysis

Selenoproteins play crucial roles including protection and recovery from oxidative stress in organisms. Direct profiling of selenoproteins in proteomes is challenging due to their extremely low abundance. We have developed a computational algorithm termed selenium-encoded isotopic signature targeted profiling (SESTAR) to increase the sensitivity of detecting selenoproteins in complex proteomic samples. In this chapter, we briefly described the basic algorithm of SESTAR. We then introduced SESTAR++, an updated version of SESTAR, with accelerated computation speed and lowered false positive rate. We also provided a detailed workflow to apply SESTAR++ to proteomic profiling of selenoproteins, including the instruction of running the software and implementing it in a targeted profiling mode.

Detecting Periprosthetic Joint Infection by Using Mass Spectrometry

BACKGROUND

Novel methods for diagnosing periprosthetic joint infection (PJI) are currently being explored. Mass spectrometry (MS) is an approach that can detect whole-protein changes in synovial fluid and may represent a promising method.

METHODS

Between March 2017 and July 2018, we successively collected synovial fluid samples from patients who were undergoing diagnostic hip or knee aspiration because PJI was suspected. A PJI diagnosis was based on the modified Musculoskeletal Infection Society (MSIS) criteria. Cluster analysis and receiver operating characteristic (ROC) curves were used to evaluate the results, which were quantitatively confirmed with parallel reaction monitoring in another patient group who underwent aspiration between August 2018 and January 2019.

RESULTS

A total of 117 synovial samples, including 51 PJI and 66 non-PJI samples, were analyzed with liquid chromatography-tandem MS (LC-MS/MS). The cluster analysis sensitivity and specificity based on differentially expressed proteins were 0.961 (95% confidence interval [CI], 0.854 to 0.993) and 0.924 (95% CI, 0.825 to 0.972), respectively. Myeloid nuclear differentiation antigen (MNDA) and polymorphonuclear leukocyte serine protease 3 (PRTN3) were the 2 most important markers for detecting PJI. The areas under the curves (AUCs) of MNDA and PRTN3 were 0.969 (95% CI, 0.936 to 1.000) and 0.900 (95% CI, 0.844 to 0.956), respectively. When MNDA and PRTN3 were combined as variables of a predictive model to diagnose PJI, the AUC reached 0.975 (95% CI, 0.943 to 1.000). Our parallel reaction monitoring-based quantitative analysis of another 40 synovial samples confirmed this result.

CONCLUSIONS

MS could be a powerful tool for diagnosing PJI using proteome information or 2 specific markers, MNDA and PRTN3. The parallel reaction monitoring strategy simplified the PJI detection process and provided quantitative results with similar conclusions.

CLINICAL RELEVANCE

The clinical application of MS adds a new powerful tool for the diagnosis of PJI, and the parallel reaction monitoring strategy lays a foundation for the clinical application of MS.

LEVEL OF EVIDENCE

Diagnostic Level II. See Instructions for Authors for a complete description of levels of evidence.

Novel Corneal Protein Biomarker Candidates Reveal Iron Metabolic Disturbance in High Myopia Eyes

Myopia is a major public health concern with increasing global prevalence and is the leading cause of vision loss and complications. The potential role of the cornea, a substantial component of refractive power and the protective fortress of the eye, has been underestimated in the development of myopia. Our study acquired corneal stroma tissues from myopic patients undergoing femtosecond laser-assisted small incision lenticule extraction (SMILE) surgery and investigated the differential expression of circulating proteins between subjects with low and high myopia by means of high-throughput proteomic approaches—the quantitative tandem mass tag (TMT) labeling method and parallel reaction monitoring (PRM) validation. Across all corneal stroma tissue samples, a total of 2,455 proteins were identified qualitatively and quantitatively, 103 of which were differentially expressed between those with low and high myopia. The differentially abundant proteins (DAPs) between the groups of stroma samples mostly demonstrated catalytic activity and molecular function regulator and transporter activity and participated in metabolic processes, biological regulation, response to stimulus, and so forth. Pathway enrichment showed that mineral absorption, ferroptosis, and HIF-1 signaling pathways were activated in the human myopic cornea. Furthermore, TMT analysis and PRM validation revealed that the expression of ferritin light chain (FTL, P02792) and ferritin heavy chain (FTH1, P02794) was negatively associated with myopia development, while the expression of serotransferrin (TF, P02787) was positively related to myopia status. Overall, our results indicated that subjects with low and high myopia could have different proteomic profiles or signatures in the cornea. These findings revealed disturbances in iron metabolism and corneal oxidative stress in the more myopic eyes. Iron metabolic proteins could serve as an essential modulator in the pathogenesis of myopia.

Primary angle closure glaucoma is characterized by altered extracellular matrix homeostasis in the iris

PURPOSE

To characterize the proteome of the iris in primary angle closure glaucoma (PACG).

EXPERIMENTAL DESIGN

In this cross-sectional study, iris samples were obtained from surgical iridectomy of 48 adults with PACG and five normal controls. Peptides from iris were analysed using liquid chromatography-tandem mass spectrometry on an Orbitrap Q Exactive Plus mass spectrometer. Verification of proteins of interest was conducted using selected reaction monitoring on a triple quadrupole mass spectrometer. The main outcome was proteins with a log₂ two-fold difference in expression in iris between PACG and controls.

RESULTS

There were 3,446 non-redundant proteins identified in human iris, of which 416 proteins were upregulated and 251 proteins were downregulated in PACG compared with controls. Thirty-two upregulated proteins were either components of the extracellular matrix (ECM) (fibrillar collagens, EMILIN-2, fibrinogen, fibronectin, matrilin-2), matricellular proteins (thrombospondin-1), proteins involved in cell-matrix interactions (integrins, laminin, histidine-rich glycoprotein, paxillin), or protease inhibitors known to modulate ECM turnover (α-2 macroglobulin, tissue factor pathway inhibitor 2, papilin). Two giant proteins, titin and obscurin, were up- and down-regulated, respectively, in the iris in PACG compared with controls.

CONCLUSIONS AND CLINICAL RELEVANCE

This proteomic study shows that ECM composition and homeostasis are altered in the iris in PACG.

Integration of Data from Liquid-Liquid Phase Separation Databases Highlights Concentration and Dosage Sensitivity of LLPS Drivers

Liquid–liquid phase separation (LLPS) is a molecular process that leads to the formation of membraneless organelles, representing functionally specialized liquid-like cellular condensates formed by proteins and nucleic acids. Integrating the data on LLPS-associated proteins from dedicated databases revealed only modest agreement between them and yielded a high-confidence dataset of 89 human LLPS drivers. Analysis of the supporting evidence for our dataset uncovered a systematic and potentially concerning difference between protein concentrations used in a good fraction of the in vitro LLPS experiments, a key parameter that governs the phase behavior, and the proteomics-derived cellular abundance levels of the corresponding proteins. Closer scrutiny of the underlying experimental data enabled us to offer a sound rationale for this systematic difference, which draws on our current understanding of the cellular organization of the proteome and the LLPS process. In support of this rationale, we find that genes coding for our human LLPS drivers tend to be dosage-sensitive, suggesting that their cellular availability is tightly regulated to preserve their functional role in direct or indirect relation to condensate formation. Our analysis offers guideposts for increasing agreement between in vitro and in vivo studies, probing the roles of proteins in LLPS.

High-Titer De Novo Biosynthesis of the Predominant Human Milk Oligosaccharide 2'-Fucosyllactose from Sucrose in Escherichia coli

Human milk oligosaccharides (HMOs) are unique components of human breast milk. Their large-scale production by fermentation allows infant formulas to be fortified with HMOs, but current fermentation processes require lactose as a starting material, increasing the costs, bioburden, and environmental impact of manufacturing. Here we report the development of an Escherichia coli strain that produces 2'-fucosyllactose (2'-FL), the most abundant HMO, de novo using sucrose as the sole carbon source. Strain engineering required the expression of a novel glucose-accepting galactosyltransferase, overexpression of the de novo UDP-d-galactose and GDP-l-fucose pathways, the engineering of an intracellular pool of free glucose, and overexpression of a suitable α(1,2)-fucosyltransferase. The export of 2'-FL was facilitated using a sugar efflux transporter. The final production strain achieved 2'-FL yields exceeding 60 g/L after fermentation for 84 h. This efficient strategy facilitates the lactose-independent production of HMOs by fermentation, which will improve product quality and reduce the costs of manufacturing.

The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics

Skyline is a freely available, open-source Windows client application for accelerating targeted proteomics experimentation, with an emphasis on the proteomics and mass spectrometry community as users and as contributors. This review covers the informatics encompassed by the Skyline ecosystem, from computationally assisted targeted mass spectrometry method development, to raw acquisition file data processing, and quantitative analysis and results sharing.

Peptide Selection for Accurate Targeted Protein Quantification via a Dimethylation High-Resolution Mass Spectrum Strategy with a Peptide Release Kinetic Model

A crucial step in accurate targeted protein quantification using targeted proteomics is to determine optimal proteotypic peptides representing targeted proteins. In this study, a workflow of peptide selection to determine proteotypic peptides using a dimethylation high-resolution mass spectrum strategy with a peptide release kinetic model was investigated and applied in peptide selection of bovine serum albumin. After specificity, digestibility, recovery, and stability evaluation of tryptic peptides in bovine serum albumin, the optimal proteotypic peptide was selected as LVNELTEFAK. The quantification method using LVNELTEFAK gave a linear range of 1-100 ppm with the coefficient greater than 0.9990, and the detection limit of bovine serum albumin in milk was 0.78 mg/kg. Compared with the proteotypic peptides selected by Skyline, the method showed a better performance in method validation. The workflow exhibited high comprehensiveness and efficiency in peptide selection, facilitating accurate targeted protein quantification in the food matrix, which lack protein standards.

The production of isoprene from cellulose using recombinant Clostridium cellulolyticum strains expressing isoprene synthase

Isoprene is an important bulk chemical which is mostly derived from fossil fuels. It is used primarily for the production of synthetic rubber. Sustainable, biotechnology‐based alternatives for the production of isoprene rely on the fermentation of sugars from food and feed crops, creating an ethical dilemma due to the competition for agricultural land. This issue could be addressed by developing new approaches based on the production of isoprene from abundant renewable waste streams. Here, we describe a proof‐of‐principle approach for the production of isoprene from cellulosic biomass, the most abundant polymer on earth. We engineered the mesophilic prokaryote Clostridium cellulolyticum, which can degrade cellulosic biomass, to utilize the resulting glucose monomers as a feedstock for the production of isoprene. This was achieved by integrating the poplar gene encoding isoprene synthase. The presence of the enzyme was confirmed by targeted proteomics, and the accumulation of isoprene was confirmed by GC‐MS/MS. We have shown for the first time that engineered C. cellulolyticum can be used as a metabolic chassis for the sustainable production of isoprene.

Mass Spectrometry-Based Quantification of Tau in Human Cerebrospinal Fluid Using a Complementary Tryptic Peptide Standard

Here, we report a method for the generation of complementary tryptic (CompTryp) isotope-labeled peptide standards for the relative and absolute quantification of proteins by mass spectrometry (MS). These standards can be digested in parallel with either trypsin (Tryp-C) or trypsin-N (Tryp-N), to generate peptides that significantly overlap in primary sequence having C- and N-terminal arginine and lysine residues, respectively. As a proof of concept, an isotope-labeled CompTryp standard was synthesized for Tau, a well-established biomarker in Alzheimer's disease (AD), which included both N- and C-terminal heavy isotope-labeled (¹⁵N and ¹³C) arginine residues and flanking amino acid sequences to monitor proteolytic digestion. Despite having the exact same mass, the N- and C-terminal heavy Tau peptides are distinguishable by retention time and MS/MS fragmentation profiles. The isotope-labeled Tau CompTryp standard was added to human cerebrospinal fluid (CSF) followed by parallel digestion with Tryp-N and Tryp-C. The native and isotope-labeled peptide pairs were quantified by parallel reaction monitoring (PRM) in a single assay. Notably, both tryptic peptides were effective at quantifying Tau in human CSF, and both showed a significant difference in CSF Tau levels between AD and controls. Treating these CompTryp Tau peptide measurements as independent replicates also improved the coefficient of variation and correlation with Tau immunoassays. More broadly, we propose that CompTryp standards can be generated for any protein of interest, providing an efficient method to improve the robustness and reproducibility for MS analysis of clinical and research samples.

Differential Roles of the Thylakoid Lumenal Deg Protease Homologs in Chloroplast Proteostasis

Deg proteases are involved in protein quality control in prokaryotes. Of the three Arabidopsis (Arabidopsis thaliana) homologs, Deg1, Deg5, and Deg8, located in the thylakoid lumen, Deg1 forms a homohexamer, whereas Deg5 and Deg8 form a heterocomplex. Both Deg1 and Deg5-Deg8 were shown separately to degrade photosynthetic proteins during photoinhibition. To investigate whether Deg1 and Deg5-Deg8 are redundant, a full set of Arabidopsis Deg knockout mutants were generated and their phenotypes were compared. Under all conditions tested, deg1 mutants were affected more than the wild type and deg5 and deg8 mutants. Moreover, overexpression of Deg5-Deg8 could only partially compensate for the loss of Deg1. Comparative proteomics of deg1 mutants revealed moderate up-regulation of thylakoid proteins involved in photoprotection, assembly, repair, and housekeeping and down-regulation of those that form photosynthetic complexes. Quantification of protein levels in the wild type revealed that Deg1 was 2-fold more abundant than Deg5-Deg8. Moreover, recombinant Deg1 displayed higher in vitro proteolytic activity. Affinity enrichment assays revealed that Deg1 was precipitated with very few interacting proteins, whereas Deg5-Deg8 was associated with a number of thylakoid proteins, including D1, OECs, LHCBs, Cyt b ₆ f, and NDH subunits, thus implying that Deg5-Deg8 is capable of binding substrates but is unable to degrade them efficiently. This work suggests that differences in protein abundance and proteolytic activity underlie the differential importance of Deg1 and Deg5-Deg8 protease complexes observed in vivo.

Data-independent acquisition-based SWATH-MS for quantitative proteomics: a tutorial

Many research questions in fields such as personalized medicine, drug screens or systems biology depend on obtaining consistent and quantitatively accurate proteomics data from many samples. SWATH-MS is a specific variant of data-independent acquisition (DIA) methods and is emerging as a technology that combines deep proteome coverage capabilities with quantitative consistency and accuracy. In a SWATH-MS measurement, all ionized peptides of a given sample that fall within a specified mass range are fragmented in a systematic and unbiased fashion using rather large precursor isolation windows. To analyse SWATH-MS data, a strategy based on peptide-centric scoring has been established, which typically requires prior knowledge about the chromatographic and mass spectrometric behaviour of peptides of interest in the form of spectral libraries and peptide query parameters. This tutorial provides guidelines on how to set up and plan a SWATH-MS experiment, how to perform the mass spectrometric measurement and how to analyse SWATH-MS data using peptide-centric scoring. Furthermore, concepts on how to improve SWATH-MS data acquisition, potential trade-offs of parameter settings and alternative data analysis strategies are discussed.

An integrated transcriptomics-guided genome-wide promoter analysis and next-generation proteomics approach to mine factor(s) regulating cellular differentiation

Differential next-generation-omics approaches aid in the visualization of biological processes and pave the way for divulging important events and/or interactions leading to a functional output at cellular or systems level. To this end, we undertook an integrated Nextgen transcriptomics and proteomics approach to divulge differential gene expression of infant and pubertal rat Sertoli cells (Sc).Unlike, pubertal Sc, infant Sc are immature and fail to support spermatogenesis. We found exclusive association of 14 and 19 transcription factor binding sites to infantile and pubertal states of Sc, respectively, using differential transcriptomics-guided genome-wide computational analysis of relevant promoters employing 220 Positional Weight Matrices from the TRANSFAC database. Proteomic SWATH-MS analysis provided extensive quantification of nuclear and cytoplasmic protein fractions revealing 1,670 proteins differentially located between the nucleus and cytoplasm of infant Sc and 890 proteins differentially located within those of pubertal Sc. Based on our multi-omics approach, the transcription factor YY1 was identified as one of the lead candidates regulating differentiation of Sc.YY1 was found to have abundant binding sites on promoters of genes upregulated during puberty. To determine its significance, we generated transgenic rats with Sc specific knockdown of YY1 that led to compromised spermatogenesis.

The promise of targeted proteomics for quantitative network biology

Proteomics is a powerful tool for obtaining information on a large number of proteins with regard to their expression levels, interactions with other molecules, and posttranslational modifications. Whereas nontargeted, discovery proteomics uncovers differences in the proteomic landscape under different conditions, targeted proteomics has been developed to overcome the limitations of this approach with regard to quantitation. In addition to technical advances in instruments and informatics tools, the advent of the synthetic proteome composed of synthetic peptides or recombinant proteins has advanced the adoption of targeted proteomics across a wide range of research fields. Targeted proteomics can now be applied to measurement of the dynamics of any proteins of interest under a variety of conditions as well as to estimation of the absolute abundance or stoichiometry of proteins in a given network. Multiplexed targeted proteomics assays of high reproducibility and accuracy can provide insight at the quantitative level into entire networks that govern biological phenomena or diseases. Such assays will establish a new paradigm for data-driven science.

Cell-free synthesis of stable isotope-labeled internal standards for targeted quantitative proteomics

High-sensitivity mass spectrometry approaches using selected reaction monitoring (SRM) or multiple reaction monitoring (MRM) methods are powerful tools for targeted quantitative proteomics-based investigation of dynamics in specific biological systems. Both high-sensitivity detection of low-abundance proteins and their quantification using this technique employ stable isotope-labeled peptide internal standards. Currently, there are various ways for preparing standards, including chemical peptide synthesis, cellular protein expression, and cell-free protein or peptide synthesis. Cell-free protein synthesis (CFPS) or in vitro translation (IVT) systems in particular provide high-throughput and low-cost preparation methods, and various cell types and reconstituted forms are now commercially available. Herein, we review the use of such systems for precise and reliable protein quantification.

Application of targeted mass spectrometry in bottom-up proteomics for systems biology research

The enormous diversity of proteoforms produces tremendous complexity within cellular proteomes, facilitates intricate networks of molecular interactions, and constitutes a formidable analytical challenge for biomedical researchers. Currently, quantitative whole-proteome profiling often relies on non-targeted liquid chromatography-mass spectrometry (LC-MS), which samples proteoforms broadly, but can suffer from lower accuracy, sensitivity, and reproducibility compared with targeted LC-MS. Recent advances in bottom-up proteomics using targeted LC-MS have enabled previously unachievable identification and quantification of target proteins and posttranslational modifications within complex samples. Consequently, targeted LC-MS is rapidly advancing biomedical research, especially systems biology research in diverse areas that include proteogenomics, interactomics, kinomics, and biological pathway modeling. With the recent development of targeted LC-MS assays for nearly the entire human proteome, targeted LC-MS is positioned to enable quantitative proteomic profiling of unprecedented quality and accessibility to support fundamental and clinical research. Here we review recent applications of bottom-up proteomics using targeted LC-MS for systems biology research. SIGNIFICANCE: Advances in targeted proteomics are rapidly advancing systems biology research. Recent applications include systems-level investigations focused on posttranslational modifications (such as phosphoproteomics), protein conformation, protein-protein interaction, kinomics, proteogenomics, and metabolic and signaling pathways. Notably, absolute quantification of metabolic and signaling pathway proteins has enabled accurate pathway modeling and engineering. Integration of targeted proteomics with other technologies, such as RNA-seq, has facilitated diverse research such as the identification of hundreds of "missing" human proteins (genes and transcripts that appear to encode proteins but direct experimental evidence was lacking).

PECAN: library-free peptide detection for data-independent acquisition tandem mass spectrometry data

Data-independent acquisition (DIA) is an emerging mass spectrometry (MS)-based technique for unbiased and reproducible measurement of protein mixtures. DIA tandem mass spectrometry spectra are often highly multiplexed, containing product ions from multiple cofragmenting precursors. Detecting peptides directly from DIA data is therefore challenging; most DIA data analyses require spectral libraries. Here we present PECAN (http://pecan.maccosslab.org), a library-free, peptide-centric tool that robustly and accurately detects peptides directly from DIA data. PECAN reports evidence of detection based on product ion scoring, which enables detection of low-abundance analytes with poor precursor ion signal. We demonstrate the chromatographic peak picking accuracy and peptide detection capability of PECAN, and we further validate its detection with data-dependent acquisition and targeted analyses. Lastly, we used PECAN to build a plasma proteome library from DIA data and to query known sequence variants.

Development of Selected Reaction Monitoring Methods to Systematically Quantify Kinase Abundance and Phosphorylation Stoichiometry in Human Samples

Protein phosphorylation, one of the most common types of post-translational modifications, is the central regulatory mechanism of cellular signaling networks. In human cells, thousands of proteins are continuously and dynamically phosphorylated and dephosphorylated at specific sites and times in response to external and internal stimuli. Reversible phosphorylation is facilitated by the action of two protein superfamilies: kinases and phosphatases. Kinases play an essential role in almost every relevant physiological process in human cells and their deregulation is linked to pathologies ranging from cancer to autoimmune diseases.Systematic identification of kinases expressed in a particular cell type, quantification of their abundance, and precise determination of their phosphorylation stoichiometry are essential to understand the cellular signaling networks and physiology of a sample. Our protocol outlines the steps to build and use a high-throughput, comprehensive, modular, and robust selected reaction monitoring (SRM) proteomics framework to facilitate quantification of the kinome state in research or clinical human samples.

Systems Biology-Derived Discoveries of Intrinsic Clocks

A systems approach to studying biology uses a variety of mathematical, computational, and engineering tools to holistically understand and model properties of cells, tissues, and organisms. Building from early biochemical, genetic, and physiological studies, systems biology became established through the development of genome-wide methods, high-throughput procedures, modern computational processing power, and bioinformatics. Here, we highlight a variety of systems approaches to the study of biological rhythms that occur with a 24-h period-circadian rhythms. We review how systems methods have helped to elucidate complex behaviors of the circadian clock including temperature compensation, rhythmicity, and robustness. Finally, we explain the contribution of systems biology to the transcription-translation feedback loop and posttranslational oscillator models of circadian rhythms and describe new technologies and "-omics" approaches to understand circadian timekeeping and neurophysiology.

An Optimized Chromatographic Strategy for Multiplexing In Parallel Reaction Monitoring Mass Spectrometry: Insights from Quantitation of Activated Kinases

Reliable quantitation of protein abundances in defined sets of cellular proteins is critical to numerous biological applications. Traditional immunodetection-based methods are limited by the quality and availability of specific antibodies, especially for site-specific post-translational modifications. Targeted proteomic methods, including the recently developed parallel reaction monitoring (PRM) mass spectrometry, have enabled accurate quantitative measurements of up to a few hundred specific target peptides. However, the degree of practical multiplexing in label-free PRM workflows remains a significant limitation for the technique. Here we present a strategy for significantly increasing multiplexing in label-free PRM that takes advantage of the superior separation characteristics and retention time stability of meter-scale monolithic silica-C18 column-based chromatography. We show the utility of the approach in quantifying kinase abundances downstream of previously developed active kinase enrichment methodology based on multidrug inhibitor beads. We examine kinase activation dynamics in response to three different MAP kinase inhibitors in colorectal carcinoma cells and demonstrate reliable quantitation of over 800 target peptides from over 150 kinases in a single label-free PRM run. The kinase activity profiles obtained from these analyses reveal compensatory activation of TGF-β family receptors as a response to MAPK blockade. The gains achieved using this label-free PRM multiplexing strategy will benefit a wide array of biological applications.

A large-scale targeted proteomics assay resource based on an in vitro human proteome

Targeted proteomics approaches are of value for deep and accurate quantification of protein abundance. Extending such methods to quantify large numbers of proteins requires the construction of predefined targeted assays. We developed a targeted proteomics platform-in vitro proteome-assisted multiple reaction monitoring (MRM) for protein absolute quantification (iMPAQT)-by using >18,000 human recombinant proteins, thus enabling protein absolute quantification on a genome-wide scale. Our platform comprises experimentally confirmed MRM assays of mass tag (mTRAQ)-labeled peptides to allow for rapid and straightforward measurement of the absolute abundance of predefined sets of proteins by mass spectrometry. We applied iMPAQT to delineate the quantitative metabolic landscape of normal and transformed human fibroblasts. Oncogenic transformation gave rise to relatively small but global changes in metabolic pathways resulting in aerobic glycolysis (Warburg effect) and increased rates of macromolecule synthesis. iMPAQT should facilitate quantitative biology studies based on protein abundance measurements.

Food allergen detection by mass spectrometry: the role of systems biology

Food allergy prevalence is rising worldwide, motivating the development of assays that can sensitively and reliably detect trace amounts of allergens in manufactured food. Mass spectrometry (MS) is a promising alternative to commonly employed antibody-based assays owing to its ability to quantify multiple proteins in complex matrices with high sensitivity. In this review, we discuss a targeted MS workflow for the quantitation of allergenic protein in food products that employs selected reaction monitoring (SRM). We highlight the aspects of SRM method development unique to allergen quantitation and identify opportunities for simplifying the process. One promising avenue identified through a comprehensive survey of published MS literature is the use of proteotypic peptides, which are peptides whose presence appears robust to variations in food matrix, sample preparation protocol, and MS instrumentation. We conclude that proteotypic peptides exist for a subset of allergenic milk, egg, and peanut proteins. For less studied allergens such as soy, wheat, fish, shellfish, and tree nuts, we offer guidance and tools for peptide selection and specificity verification as part of an interactive web database, the Allergen Peptide Browser (http://www.AllergenPeptideBrowser.org). With ongoing improvements in MS instrumentation, analysis software, and strategies for targeted quantitation, we expect an increasing role of MS as an analytical tool for ensuring regulatory compliance.

Different Alleles of a Gene Encoding Leucoanthocyanidin Reductase (PaLAR3) Influence Resistance against the Fungus Heterobasidion parviporum in Picea abies

Despite the fact that fungal diseases are a growing menace for conifers in modern silviculture, only a very limited number of molecular markers for pathogen resistance have been validated in conifer species. A previous genetic study indicated that the resistance of Norway spruce (Picea abies) to Heterobasidion annosum s.l., a pathogenic basidiomycete species complex, is linked to a quantitative trait loci that associates with differences in fungal growth in sapwood (FGS) that includes a gene, PaLAR3, which encodes a leucoanthocyanidin reductase. In this study, gene sequences showed the presence of two PaLAR3 allelic lineages in P. abies. Higher resistance was associated with the novel allele, which was found in low frequency in the four P. abies populations that we studied. Norway spruce plants carrying at least one copy of the novel allele showed a significant reduction in FGS after inoculation with Heterobasidion parviporum compared to their half-siblings carrying no copies, indicating dominance of this allele. The amount of (+) catechin, the enzymatic product of PaLAR3, was significantly higher in bark of trees homozygous for the novel allele. Although we observed that the in vitro activities of the enzymes encoded by the two alleles were similar, we could show that allele-specific transcript levels were significantly higher for the novel allele, indicating that regulation of gene expression is responsible for the observed effects in resistance, possibly caused by differences in cis-acting elements that we observe in the promoter region of the two alleles.

Mass spectrometry-based absolute quantification reveals rhythmic variation of mouse circadian clock proteins

Absolute values of protein expression levels in cells are crucial information for understanding cellular biological systems. Precise quantification of proteins can be achieved by liquid chromatography (LC)-mass spectrometry (MS) analysis of enzymatic digests of proteins in the presence of isotope-labeled internal standards. Thus, development of a simple and easy way for the preparation of internal standards is advantageous for the analyses of multiple target proteins, which will allow systems-level studies. Here we describe a method, termed MS-based Quantification By isotope-labeled Cell-free products (MS-QBiC), which provides the simple and high-throughput preparation of internal standards by using a reconstituted cell-free protein synthesis system, and thereby facilitates both multiplexed and sensitive quantification of absolute amounts of target proteins. This method was applied to a systems-level dynamic analysis of mammalian circadian clock proteins, which consist of transcription factors and protein kinases that govern central and peripheral circadian clocks in mammals. Sixteen proteins from 20 selected circadian clock proteins were successfully quantified from mouse liver over a 24-h time series, and 14 proteins had circadian variations. Quantified values were applied to detect internal body time using a previously developed molecular timetable method. The analyses showed that single time-point data from wild-type mice can predict the endogenous state of the circadian clock, whereas data from clock mutant mice are not applicable because of the disappearance of circadian variation.

Peptide Biosynthesis with Stable Isotope Labeling from a Cell-free Expression System for Targeted Proteomics with Absolute Quantification

Because of its specificity and sensitivity, targeted proteomics using mass spectrometry for multiple reaction monitoring is a powerful tool to detect and quantify pre-selected peptides from a complex background and facilitates the absolute quantification of peptides using isotope-labeled forms as internal standards. How to generate isotope-labeled peptides remains an urgent challenge for accurately quantitative targeted proteomics on a large scale. Herein, we propose that isotope-labeled peptides fused with a quantitative tag could be synthesized through an expression system in vitro, and the homemade peptides could be enriched by magnetic beads with tag-affinity and globally quantified based on the corresponding multiple reaction monitoring signals provided by the fused tag. An Escherichia coli cell-free protein expression system, protein synthesis using recombinant elements, was adopted for the synthesis of isotope-labeled peptides fused with Strep-tag. Through a series of optimizations, we enabled efficient expression of the labeled peptides such that, after Strep-Tactin affinity enrichment, the peptide yield was acceptable in scale for quantification, and the peptides could be completely digested by trypsin to release the Strep-tag for quantification. Moreover, these recombinant peptides could be employed in the same way as synthetic peptides for multiple reaction monitoring applications and are likely more economical and useful in a laboratory for the scale of targeted proteomics. As an application, we synthesized four isotope-labeled glutathione S-transferase (GST) peptides and added them to mouse sera pre-treated with GST affinity resin as internal standards. A quantitative assay of the synthesized GST peptides confirmed the absolute GST quantification in mouse sera to be measurable and reproducible.

Technical advances in proteomics: new developments in data-independent acquisition

The ultimate aim of proteomics is to fully identify and quantify the entire complement of proteins and post-translational modifications in biological samples of interest. For the last 15 years, liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-dependent acquisition (DDA) mode has been the standard for proteomics when sampling breadth and discovery were the main objectives; multiple reaction monitoring (MRM) LC-MS/MS has been the standard for targeted proteomics when precise quantification, reproducibility, and validation were the main objectives. Recently, improvements in mass spectrometer design and bioinformatics algorithms have resulted in the rediscovery and development of another sampling method: data-independent acquisition (DIA). DIA comprehensively and repeatedly samples every peptide in a protein digest, producing a complex set of mass spectra that is difficult to interpret without external spectral libraries. Currently, DIA approaches the identification breadth of DDA while achieving the reproducible quantification characteristic of MRM or its newest version, parallel reaction monitoring (PRM). In comparative de novo identification and quantification studies in human cell lysates, DIA identified up to 89% of the proteins detected in a comparable DDA experiment while providing reproducible quantification of over 85% of them. DIA analysis aided by spectral libraries derived from prior DIA experiments or auxiliary DDA data produces identification and quantification as reproducible and precise as that achieved by MRM/PRM, except on low‑abundance peptides that are obscured by stronger signals. DIA is still a work in progress toward the goal of sensitive, reproducible, and precise quantification without external spectral libraries. New software tools applied to DIA analysis have to deal with deconvolution of complex spectra as well as proper filtering of false positives and false negatives. However, the future outlook is positive, and various researchers are working on novel bioinformatics techniques to address these issues and increase the reproducibility, fidelity, and identification breadth of DIA.

Metabolic engineering of Clostridium cellulolyticum for the production of n-butanol from crystalline cellulose

BACKGROUND

Sustainable alternatives for the production of fuels and chemicals are needed to reduce our dependency on fossil resources and to avoid the negative impact of their excessive use on the global climate. Lignocellulosic feedstock from agricultural residues, energy crops and municipal solid waste provides an abundant and carbon-neutral alternative, but it is recalcitrant towards microbial degradation and must therefore undergo extensive pretreatment to release the monomeric sugar units used by biofuel-producing microbes. These pretreatment steps can be reduced by using microbes such as Clostridium cellulolyticum that naturally digest lignocellulose, but this limits the range of biofuels that can be produced. We therefore developed a metabolic engineering approach in C. cellulolyticum to expand its natural product spectrum and to fine tune the engineered metabolic pathways.

RESULTS

Here we report the metabolic engineering of C. cellulolyticum to produce n-butanol, a next-generation biofuel and important chemical feedstock, directly from crystalline cellulose. We introduced the CoA-dependent pathway for n-butanol synthesis from C. acetobutylicum and measured the expression of functional enzymes (using targeted proteomics) and the abundance of metabolic intermediates (by LC-MS/MS) to identify potential bottlenecks in the n-butanol biosynthesis pathway. We achieved yields of 40 and 120 mg/L n-butanol from cellobiose and crystalline cellulose, respectively, after cultivating the bacteria for 6 and 20 days.

CONCLUSION

The analysis of enzyme activities and key intracellular metabolites provides a robust framework to determine the metabolic flux through heterologous pathways in C. cellulolyticum, allowing further improvements by fine tuning individual steps to improve the yields of n-butanol.

Metabolic engineering of Clostridium cellulolyticum for the production of n-butanol from crystalline cellulose

Background

Sustainable alternatives for the production of fuels and chemicals are needed to reduce our dependency on fossil resources and to avoid the negative impact of their excessive use on the global climate. Lignocellulosic feedstock from agricultural residues, energy crops and municipal solid waste provides an abundant and carbon-neutral alternative, but it is recalcitrant towards microbial degradation and must therefore undergo extensive pretreatment to release the monomeric sugar units used by biofuel-producing microbes. These pretreatment steps can be reduced by using microbes such as Clostridium cellulolyticum that naturally digest lignocellulose, but this limits the range of biofuels that can be produced. We therefore developed a metabolic engineering approach in C. cellulolyticum to expand its natural product spectrum and to fine tune the engineered metabolic pathways.

Results

Here we report the metabolic engineering of C. cellulolyticum to produce n-butanol, a next-generation biofuel and important chemical feedstock, directly from crystalline cellulose. We introduced the CoA-dependent pathway for n-butanol synthesis from C. acetobutylicum and measured the expression of functional enzymes (using targeted proteomics) and the abundance of metabolic intermediates (by LC-MS/MS) to identify potential bottlenecks in the n-butanol biosynthesis pathway. We achieved yields of 40 and 120 mg/L n-butanol from cellobiose and crystalline cellulose, respectively, after cultivating the bacteria for 6 and 20 days.

Conclusion

The analysis of enzyme activities and key intracellular metabolites provides a robust framework to determine the metabolic flux through heterologous pathways in C. cellulolyticum, allowing further improvements by fine tuning individual steps to improve the yields of n-butanol.

Electronic supplementary material

The online version of this article (doi:10.1186/s12934-015-0406-2) contains supplementary material, which is available to authorized users.

Selecting Optimal Peptides for Targeted Proteomic Experiments in Human Plasma Using In Vitro Synthesized Proteins as Analytical Standards

In targeted proteomics, the development of robust methodologies is dependent upon the selection of a set of optimal peptides for each protein-of-interest. Unfortunately, predicting which peptides and respective product ion transitions provide the greatest signal-to-noise ratio in a particular assay matrix is complicated. Using in vitro synthesized proteins as analytical standards, we report here an empirically driven method for the selection of said peptides in a human plasma assay matrix.

A targeted proteomic strategy for the measurement of oral cancer candidate biomarkers in human saliva

Head and neck cancers, including oral squamous cell carcinoma (OSCC), are the sixth most common malignancy in the world and are characterized by poor prognosis and a low survival rate. Saliva is oral fluid with intimate contact with OSCC. Besides non-invasive, simple, and rapid to collect, saliva is a potential source of biomarkers. In this study, we build an SRM assay that targets fourteen OSCC candidate biomarker proteins, which were evaluated in a set of clinically-derived saliva samples. Using Skyline software package, we demonstrated a statistically significant higher abundance of the C1R, LCN2, SLPI, FAM49B, TAGLN2, CFB, C3, C4B, LRG1, SERPINA1 candidate biomarkers in the saliva of OSCC patients. Furthermore, our study also demonstrated that CFB, C3, C4B, SERPINA1 and LRG1 are associated with the risk of developing OSCC. Overall, this study successfully used targeted proteomics to measure in saliva a panel of biomarker candidates for OSCC.

Rapid biosynthesis of stable isotope-labeled peptides from a reconstituted in vitro translation system for targeted proteomics

Stable isotope-labeled peptides are routinely used as internal standards (a.k.a. reference peptides) for absolute quantitation of proteins in targeted proteomics. These peptides can either be synthesized chemically on solid supports or expressed biologically by concatenating multiple peptides together to a large protein. Neither method, however, has required versatility, convenience, and economy for making a large number of reference peptides. Here, we describe the biosynthesis of stable isotope-labeled peptides from a reconstituted Escherichia coli in vitro translation system. We provide a detailed protocol on how to express these peptides with high purity and how to determine their concentrations with easiness. Our strategy offers a general, fast, and scalable approach for the easy preparation of labeled reference peptides, which will have broad application in both basic research and translational medicine.

Applications of targeted proteomics in systems biology and translational medicine

Biological systems are composed of numerous components of which proteins are of particularly high functional significance. Network models are useful abstractions for studying these components in context. Network representations display molecules as nodes and their interactions as edges. Because they are difficult to directly measure, functional edges are frequently inferred from suitably structured datasets consisting of the accurate and consistent quantification of network nodes under a multitude of perturbed conditions. For the precise quantification of a finite list of proteins across a wide range of samples, targeted proteomics exemplified by selected/multiple reaction monitoring (SRM, MRM) mass spectrometry has proven useful and has been applied to a variety of questions in systems biology and clinical studies. Here, we survey the literature of studies using SRM-MS in systems biology and clinical proteomics. Systems biology studies frequently examine fundamental questions in network biology, whereas clinical studies frequently focus on biomarker discovery and validation in a variety of diseases including cardiovascular disease and cancer. Targeted proteomics promises to advance our understanding of biological networks and the phenotypic significance of specific network states and to advance biomarkers into clinical use.

Using proteomics to probe neurons

Advances in mass spectrometry-based proteomics have allowed researchers to quantify the abundances of the different forms of three closely related proteins in the neurons of mice.

Using Data Independent Acquisition (DIA) to Model High-responding Peptides for Targeted Proteomics Experiments

Targeted mass spectrometry is an essential tool for detecting quantitative changes in low abundant proteins throughout the proteome. Although selected reaction monitoring (SRM) is the preferred method for quantifying peptides in complex samples, the process of designing SRM assays is laborious. Peptides have widely varying signal responses dictated by sequence-specific physiochemical properties; one major challenge is in selecting representative peptides to target as a proxy for protein abundance. Here we present PREGO, a software tool that predicts high-responding peptides for SRM experiments. PREGO predicts peptide responses with an artificial neural network trained using 11 minimally redundant, maximally relevant properties. Crucial to its success, PREGO is trained using fragment ion intensities of equimolar synthetic peptides extracted from data independent acquisition experiments. Because of similarities in instrumentation and the nature of data collection, relative peptide responses from data independent acquisition experiments are a suitable substitute for SRM experiments because they both make quantitative measurements from integrated fragment ion chromatograms. Using an SRM experiment containing 12,973 peptides from 724 synthetic proteins, PREGO exhibits a 40-85% improvement over previously published approaches at selecting high-responding peptides. These results also represent a dramatic improvement over the rules-based peptide selection approaches commonly used in the literature.

Multiplexed peptide analysis using data-independent acquisition and Skyline

Here we describe the use of data-independent acquisition (DIA) on a Q-Exactive mass spectrometer for the detection and quantification of peptides in complex mixtures using the Skyline Targeted Proteomics Environment (freely available online at http://skyline.maccosslab.org). The systematic acquisition of mass spectrometry (MS) or tandem MS (MS/MS) spectra by DIA is in contrast to DDA, in which the acquired MS/MS spectra are only suitable for the identification of a stochastically sampled set of peptides. Similarly to selected reaction monitoring (SRM), peptides can be quantified from DIA data using targeted chromatogram extraction. Unlike SRM, data acquisition is not constrained to a predetermined set of target peptides. In this protocol, a spectral library is generated using data-dependent acquisition (DDA), and chromatograms are extracted from the DIA data for all peptides in the library. As in SRM, quantification using DIA data is based on the area under the curve of extracted MS/MS chromatograms. In addition, a quality control (QC) method suitable for DIA based on targeted MS/MS acquisition is detailed. Not including time spent acquiring data, and time for database searching, the procedure takes ∼1-2 h to complete. Typically, data acquisition requires roughly 1-4 h per sample, and a database search will take 0.5-2 h to complete.

Building high-quality assay libraries for targeted analysis of SWATH MS data

Targeted proteomics by selected/multiple reaction monitoring (S/MRM) or, on a larger scale, by SWATH (sequential window acquisition of all theoretical spectra) MS (mass spectrometry) typically relies on spectral reference libraries for peptide identification. Quality and coverage of these libraries are therefore of crucial importance for the performance of the methods. Here we present a detailed protocol that has been successfully used to build high-quality, extensive reference libraries supporting targeted proteomics by SWATH MS. We describe each step of the process, including data acquisition by discovery proteomics, assertion of peptide-spectrum matches (PSMs), generation of consensus spectra and compilation of MS coordinates that uniquely define each targeted peptide. Crucial steps such as false discovery rate (FDR) control, retention time normalization and handling of post-translationally modified peptides are detailed. Finally, we show how to use the library to extract SWATH data with the open-source software Skyline. The protocol takes 2-3 d to complete, depending on the extent of the library and the computational resources available.

Studying macromolecular complex stoichiometries by peptide-based mass spectrometry

A majority of cellular functions are carried out by macromolecular complexes. A host of biochemical and spectroscopic methods exists to characterize especially protein/protein complexes, however there has been a lack of a universal method to determine protein stoichiometries. Peptide‐based MS, especially as a complementary method to the MS analysis of intact protein complexes, has now been developed to a point where it can be employed to assay protein stoichiometries in a routine manner. While the experimental demands are still significant, peptide‐based MS has been successfully applied to analyze stoichiometries for a variety of protein complexes from very different biological backgrounds. In this review, we discuss the requirements especially for targeted MS acquisition strategies to be used in this context, with a special focus on the interconnected experimental aspects of sample preparation, protein digestion, and peptide stability. In addition, different strategies for the introduction of quantitative peptide standards and their suitability for different scenarios are compared.

Comparative proteomic profiling of pancreatic ductal adenocarcinoma cell lines

Pancreatic cancer is one of the most fatal cancers and is associated with limited diagnostic and therapeutic modalities. Currently, gemcitabine is the only effective drug and represents the preferred first-line treatment for chemotherapy. However, a high level of intrinsic or acquired resistance of pancreatic cancer to gemcitabine can contribute to the failure of gemcitabine treatment. To investigate the underlying molecular mechanisms for gemcitabine resistance in pancreatic cancer, we performed label-free quantification of protein expression in intrinsic gemcitabine-resistant and - sensitive human pancreatic adenocarcinoma cell lines using our improved proteomic strategy, combined with filter-aided sample preparation, single-shot liquid chromatography-mass spectrometry, enhanced spectral counting, and a statistical method based on a power law global error model. We identified 1931 proteins and quantified 787 differentially expressed proteins in the BxPC3, PANC-1, and HPDE cell lines. Bioinformatics analysis identified 15 epithelial to mesenchymal transition (EMT) markers and 13 EMT-related proteins that were closely associated with drug resistance were differentially expressed. Interestingly, 8 of these proteins were involved in glutathione and cysteine/methionine metabolism. These results suggest that proteins related to the EMT and glutathione metabolism play important roles in the development of intrinsic gemcitabine resistance by pancreatic cancer cell lines.

Sample preparation strategies for targeted proteomics via proteotypic peptides in human blood using liquid chromatography tandem mass spectrometry

The simultaneous quantification of protein concentrations via proteotypic peptides in human blood by liquid chromatography coupled to quadrupole MS/MS is an important field of bioanalytical research with a high potential for routine diagnostic applications. This review summarizes currently available sample preparation procedures and trends for absolute protein quantification in blood using LC-MS/MS. It discusses approaches of transferring established qualitative protocols to a quantitative analysis regarding their reliability and reproducibility. Techniques used to enhance method sensitivity such as the depletion of high-abundant proteins or the immunoaffinity enrichment of proteins and peptides are described. Furthermore, workflows for (i) protein denaturation, (ii) disulfide bridge reduction and (iii) thiol alkylation as well as (iv) enzymatic digestion for absolute protein quantification are presented. The main focus is on the tryptic digestion as a bottleneck of protein quantification via proteotypic peptides. Conclusively, requirements for a high-throughput application are discussed.