Translational Proteomics Analysis of Anthracycline-Induced Cardiotoxicity From Cardiac Microtissues to Human Heart Biopsies.

Anthracyclines, including doxorubicin, idarubicin, and epirubicin, are common antitumor drugs as well as well-known cardiotoxic agents. This study analyzed the proteomics alteration in cardiac tissues caused by these 3 anthracyclines analogs. The in vitro human cardiac microtissues were exposed to drugs in 2 weeks; the proteomic data were measured at 7 time points. The heart biopsy data were collected from heart failure patients, in which some patients underwent anthracycline treatment. The anthracyclines-affected proteins were separately identified in the in vitro and in vivo dataset using the WGCNA method. These proteins engage in different cellular pathways including translation, metabolism, mitochondrial function, muscle contraction, and signaling pathways. From proteins detected in 2 datasets, a protein-protein network was established with 4 hub proteins, and 7 weighted proteins from both cardiac microtissue and human biopsies data. These 11 proteins, which involve in mitochondrial functions and the NF-κB signaling pathway, could provide insights into the anthracycline toxic mechanism. Some of them, such as HSPA5, BAG3, and SH3BGRL, are cardiac therapy targets or cardiotoxicity biomarkers. Other proteins, such as ATP5F1B and EEF1D, showed similar responses in both the in vitro and in vivo data. This suggests that the in vitro outcomes could link to clinical phenomena in proteomic analysis.

Proteome and Microbiome Mapping of Human Gingival Tissue in Health and Disease.

Efforts to map gingival tissue proteomes and microbiomes have been hampered by lack of sufficient tissue extraction methods. The pressure cycling technology (PCT) is an emerging platform for reproducible tissue homogenisation and improved sequence retrieval coverage. Therefore, we employed PCT to characterise the proteome and microbiome profiles in healthy and diseased gingival tissue. Healthy and diseased contralateral gingival tissue samples (total n = 10) were collected from five systemically healthy individuals (51.6 ± 4.3 years) with generalised chronic periodontitis. The tissues were then lysed and digested using a Barocycler, proteins were prepared and submitted for mass spectrometric analysis and microbiome DNA for 16S rRNA profiling analysis. Overall, 1,366 human proteins were quantified (false discovery rate 0.22%), of which 69 proteins were differentially expressed (≥2 peptides and p < 0.05, 62 up, 7 down) in periodontally diseased sites, compared to healthy sites. These were primarily extracellular or vesicle-associated proteins, with functions in molecular transport. On the microbiome level, 362 species-level operational taxonomic units were identified. Of those, 14 predominant species accounted for >80% of the total relative abundance, whereas 11 proved to be significantly different between healthy and diseased sites. Among them, Treponema sp. HMT253 and Fusobacterium naviforme and were associated with disease sites and strongly interacted (r > 0.7) with 30 and 6 up-regulated proteins, respectively. Healthy-site associated strains Streptococcus vestibularis, Veillonella dispar, Selenomonas sp. HMT478 and Leptotrichia sp. HMT417 showed strong negative interactions (r < -0.7) with 31, 21, 9, and 18 up-regulated proteins, respectively. In contrast the down-regulated proteins did not show strong interactions with the regulated bacteria. The present study identified the proteomic and intra-tissue microbiome profile of human gingiva by employing a PCT-assisted workflow. This is the first report demonstrating the feasibility to analyse full proteome profiles of gingival tissues in both healthy and disease sites, while deciphering the tissue site-specific microbiome signatures.

Network integration and modelling of dynamic drug responses at multi-omics levels.

Uncovering cellular responses from heterogeneous genomic data is crucial for molecular medicine in particular for drug safety. This can be realized by integrating the molecular activities in networks of interacting proteins. As proof-of-concept we challenge network modeling with time-resolved proteome, transcriptome and methylome measurements in iPSC-derived human 3D cardiac microtissues to elucidate adverse mechanisms of anthracycline cardiotoxicity measured with four different drugs (doxorubicin, epirubicin, idarubicin and daunorubicin). Dynamic molecular analysis at in vivo drug exposure levels reveal a network of 175 disease-associated proteins and identify common modules of anthracycline cardiotoxicity in vitro, related to mitochondrial and sarcomere function as well as remodeling of extracellular matrix. These in vitro-identified modules are transferable and are evaluated with biopsies of cardiomyopathy patients. This to our knowledge most comprehensive study on anthracycline cardiotoxicity demonstrates a reproducible workflow for molecular medicine and serves as a template for detecting adverse drug responses from complex omics data.

Pressure Cycling Technology Assisted Mass Spectrometric Quantification of Gingival Tissue Reveals Proteome Dynamics during the Initiation and Progression of Inflammatory Periodontal Disease.

Understanding the progression of periodontal tissue destruction is at the forefront of periodontal research. The authors aimed to capture the dynamics of gingival tissue proteome during the initiation and progression of experimental (ligature-induced) periodontitis in mice. Pressure cycling technology (PCT), a recently developed platform that uses ultra-high pressure to disrupt tissues, is utilized to achieve efficient and reproducible protein extraction from ultra-small amounts of gingival tissues in combination with liquid chromatography-tandem mass spectrometry (MS). The MS data are processed using Progenesis QI and the regulated proteins are subjected to METACORE, STRING, and WebGestalt for functional enrichment analysis. A total of 1614 proteins with ≥2 peptides are quantified with an estimated protein false discovery rate of 0.06%. Unsupervised clustering analysis shows that the gingival tissue protein abundance is mainly dependent on the periodontitis progression stage. Gene ontology enrichment analysis reveals an overrepresentation in innate immune regulation (e.g., neutrophil-mediated immunity and antimicrobial peptides), signal transduction (e.g., integrin signaling), and homeostasis processes (e.g., platelet activation and aggregation). In conclusion, a PCT-assisted label-free quantitative proteomics workflow that allowed cataloging the deepest gingival tissue proteome on a rapid timescale and provided novel mechanistic insights into host perturbation during periodontitis progression is applied.

Ovine liver proteome: Assessing mechanisms of seasonal weight loss tolerance between Merino and Damara sheep.

The effect of feed restriction on the liver protein profiles of two different breeds of sheep was studied. We compared Merino with the Damara, breeds with respectively low and high tolerance to nutritional stress. Each breed was grouped into two nutritional treatments: restricted (12-14% loss of live weight) and control (maintenance). The trial lasted 42 days. Animals were sacrificed and liver samples subjected to label free shotgun proteomics. The resultant proteins had both their fold change and statistical significance in an unpaired t-test calculated to identify differential protein abundance. The tool WebGestalt was utilized to perform an Overrepresentation Enrichment Analysis (ORA) for gene ontology terms associated with the significant proteins. We further validated shotgun proteomics findings using a selected reaction monitoring (SRM)-based targeted proteomics approach, where similar trends in regulation were obtained for a subset of relevant proteins across an independent cohort of animals. Results confirm that Damara has adapted to nutritional stress by mobilizing stored fatty acids within adipose tissue and converting them to energy more efficiently than Merino. Finally, Merino had an overabundance pattern primarily directed to protein synthesis pathways. Regulated proteins identified may be used as a basis for marker selection towards tolerance to nutritional stress. BIOLOGICAL SIGNIFICANCE: Sheep are one of the most important livestock animals. They remain however poorly understudied and described. Seasonal weight loss (SWL) due to pasture scarcity during the dry season is one of the most limiting conditions to ruminant production in the tropics. To counter SWL, farmers may use supplementation, expensive or difficult to implement. A more suitable long-term solution would be to use breeds that are naturally adapted to nutritional stress. This work contrasts two breeds with different levels of tolerance to SWL, the Damara and the Merino, respectively well and poorly adapted. Comparison is conducted at the level of the hepatic tissue and using label free proteomics. This work identifies a series of pathways in the liver of the Damara via label free proteomics that suggest a unique fatty acid metabolic process within this breed. Proteins that have increased abundance in the Damara in association with fatty acid metabolism may be used as potential markers of tolerance to nutritional stress. This research will pave the way for more viable, long-term solutions for farmers facing annual production problems due to drought in the tropics and the Mediterranean region.

Targeted Proteomics Guided by Label-free Quantitative Proteome Analysis in Saliva Reveal Transition Signatures from Health to Periodontal Disease.

Periodontal diseases are among the most prevalent worldwide, but largely silent, chronic diseases. They affect the tooth-supporting tissues with multiple ramifications on life quality. Their early diagnosis is still challenging, due to lack of appropriate molecular diagnostic methods. Saliva offers a non-invasively collectable reservoir of clinically relevant biomarkers, which, if utilized efficiently, could facilitate early diagnosis and monitoring of ongoing disease. Despite several novel protein markers being recently enlisted by discovery proteomics, their routine diagnostic application is hampered by the lack of validation platforms that allow for rapid, accurate and simultaneous quantification of multiple proteins in large cohorts. Here we carried out a pipeline of two proteomic platforms; firstly, we applied open ended label-free quantitative (LFQ) proteomics for discovery in saliva (n = 67, including individuals with health, gingivitis, and periodontitis), followed by selected-reaction monitoring (SRM)-targeted proteomics for validation in an independent cohort (n = 82). The LFQ platform led to the discovery of 119 proteins with at least 2-fold significant difference between health and disease. The 65 proteins chosen for the subsequent SRM platform included 50 functionally related proteins derived from the significantly enriched processes of the LFQ data, 11 from literature-mining, and four house-keeping ones. Among those, 60 were reproducibly quantifiable proteins (92% success rate), represented by a total of 143 peptides. Machine-learning modeling led to a narrowed-down panel of five proteins of high predictive value for periodontal diseases with maximum area under the receiver operating curve >0.97 (higher in disease: Matrix metalloproteinase-9, Ras-related protein-1, Actin-related protein 2/3 complex subunit 5; lower in disease: Clusterin, Deleted in Malignant Brain Tumors 1). This panel enriches the pool of credible clinical biomarker candidates for diagnostic assay development. Yet, the quantum leap brought into the field of periodontal diagnostics by this study is the application of the biomarker discovery-through-verification pipeline, which can be used for validation in further cohorts.

Subregion-Specific Proteomic Signature in the Hippocampus for Recognition Processes in Adult Mice.

The hippocampal formation is a brain structure essential for higher-order cognitive functions. It has a complex anatomical organization and cellular composition, and hippocampal subregions have different properties and functional roles. In this study, we used SWATH-MS to determine whether the proteomes of hippocampus areas CA1 and CA3 can explain the commonalities or specificities of these subregions in basal conditions and after recognition memory. We show that the proteomes of areas CA1 and CA3 are largely different in basal conditions and that differential changes and dynamics in protein expression are induced in these areas after recognition of an object or object location. While changes are consistent across both recognition paradigms in area CA1, they are not in area CA3, suggesting distinct proteomic responses in areas CA1 and CA3 for memory formation.

Quantitative Profiling of N-linked Glycosylation Machinery in Yeast Saccharomyces cerevisiae.

Asparagine-linked glycosylation is a common posttranslational protein modification regulating the structure, stability and function of many proteins. The N-linked glycosylation machinery involves enzymes responsible for the assembly of the lipid-linked oligosaccharide (LLO), which is then transferred to the asparagine residues on the polypeptides by the enzyme oligosaccharyltransferase (OST). A major goal in the study of protein glycosylation is to establish quantitative methods for the analysis of site-specific extent of glycosylation. We developed a sensitive approach to examine glycosylation site occupancy in Saccharomyces cerevisiae by coupling stable isotope labeling (SILAC) approach to parallel reaction monitoring (PRM) mass spectrometry (MS). We combined the method with genetic tools and validated the approach with the identification of novel glycosylation sites dependent on the Ost3p and Ost6p regulatory subunits of OST. Based on the observations that alternations in LLO substrate structure and OST subunits activity differentially alter the systemic output of OST, we conclude that sequon recognition is a direct property of the catalytic subunit Stt3p, auxiliary subunits such as Ost3p and Ost6p extend the OST substrate range by modulating interfering pathways such as protein folding. In addition, our proteomics approach revealed a novel regulatory network that connects isoprenoid lipid biosynthesis and LLO substrate assembly.

Functional proteomics outlines the complexity of breast cancer molecular subtypes.

Breast cancer is a heterogeneous disease comprising a variety of entities with various genetic backgrounds. Estrogen receptor-positive, human epidermal growth factor receptor 2-negative tumors typically have a favorable outcome; however, some patients eventually relapse, which suggests some heterogeneity within this category. In the present study, we used proteomics and miRNA profiling techniques to characterize a set of 102 either estrogen receptor-positive (ER+)/progesterone receptor-positive (PR+) or triple-negative formalin-fixed, paraffin-embedded breast tumors. Protein expression-based probabilistic graphical models and flux balance analyses revealed that some ER+/PR+ samples had a protein expression profile similar to that of triple-negative samples and had a clinical outcome similar to those with triple-negative disease. This probabilistic graphical model-based classification had prognostic value in patients with luminal A breast cancer. This prognostic information was independent of that provided by standard genomic tests for breast cancer, such as MammaPrint, OncoType Dx and the 8-gene Score.

Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry.

Quantitative proteomics employing mass spectrometry is an indispensable tool in life science research. Targeted proteomics has emerged as a powerful approach for reproducible quantification but is limited in the number of proteins quantified. SWATH-mass spectrometry consists of data-independent acquisition and a targeted data analysis strategy that aims to maintain the favorable quantitative characteristics (accuracy, sensitivity, and selectivity) of targeted proteomics at large scale. While previous SWATH-mass spectrometry studies have shown high intra-lab reproducibility, this has not been evaluated between labs. In this multi-laboratory evaluation study including 11 sites worldwide, we demonstrate that using SWATH-mass spectrometry data acquisition we can consistently detect and reproducibly quantify >4000 proteins from HEK293 cells. Using synthetic peptide dilution series, we show that the sensitivity, dynamic range and reproducibility established with SWATH-mass spectrometry are uniformly achieved. This study demonstrates that the acquisition of reproducible quantitative proteomics data by multiple labs is achievable, and broadly serves to increase confidence in SWATH-mass spectrometry data acquisition as a reproducible method for large-scale protein quantification.SWATH-mass spectrometry consists of a data-independent acquisition and a targeted data analysis strategy that aims to maintain the favorable quantitative characteristics on the scale of thousands of proteins. Here, using data generated by eleven groups worldwide, the authors show that SWATH-MS is capable of generating highly reproducible data across different laboratories.

New Quantitative Mass Spectrometry Approaches Reveal Different ADP-ribosylation Phases Dependent On the Levels of Oxidative Stress.

Oxidative stress is a potent inducer of protein ADP-ribosylation. Although individual oxidative stress-induced ADP-ribosylated proteins have been identified, it is so far not clear to which extent different degrees of stress severity quantitatively and qualitatively alter ADP-ribosylation. Here, we investigated both quantitative and qualitative changes of the hydrogen peroxide (H2O2)-induced ADP-ribosylome using a label-free shotgun quantification and a parallel reaction monitoring (PRM) mass spectrometry approach for a selected number of identified ADP-ribosylated peptides. Although the major part of the basal HeLa ADP-ribosylome remained unchanged upon all tested H2O2 concentrations, some selected peptides change the extent of ADP-ribosylation depending on the degree of the applied oxidative stress. Low oxidative stress (i.e. 4 µm and 16 µm H2O2) caused a reduction in ADP-ribosylation of modified proteins detected under untreated conditions. In contrast, mid to strong oxidative stress (62 µm to 1 mm H2O2) induced a significant increase in ADP-ribosylation of oxidative stress-targeted proteins. The application of the PRM approach to SKOV3 and A2780, ovarian cancer cells displaying different sensitivities to PARP inhibitors, revealed that the basal and the H2O2-induced ADP-ribosylomes of SKOV3 and A2780 differed significantly and that the sensitivity to PARP inhibitors correlated with the level of ARTD1 expression in these cells. Overall, this new PRM-MS approach has proven to be sensitive in monitoring alterations of the ADP-ribosylome and has revealed unexpected alterations in proteins ADP-ribosylation depending on the degree of oxidative stress.

Targeted Proteomics for Multiplexed Verification of Markers of Colorectal Tumorigenesis.

Targeted proteomic methods can accelerate the verification of multiple tumor marker candidates in large series of patient samples. We utilized the targeted approach known as selected/multiple reaction monitoring (S/MRM) to verify potential protein markers of colorectal adenoma identified by our group in previous transcriptomic and quantitative shotgun proteomic studies of a large cohort of precancerous colorectal lesions. We developed SRM assays to reproducibly detect and quantify 25 (62.5%) of the 40 selected proteins in an independent series of precancerous and cancerous tissue samples (19 adenoma/normal mucosa pairs; 17 adenocarcinoma/normal mucosa pairs). Twenty-three proteins were significantly up-regulated (n = 17) or downregulated (n = 6) in adenomas and/or adenocarcinomas, as compared with normal mucosa (linear fold changes ≥ ±1.3, adjusted p value <0.05). Most changes were observed in both tumor types (up-regulation of ANP32A, ANXA3, SORD, LDHA, LCN2, NCL, S100A11, SERPINB5, CDV3, OLFM4, and REG4; downregulation of ARF6 and PGM5), and a five-protein biomarker signature distinguished neoplastic tissue from normal mucosa with a maximum area under the receiver operating curve greater than 0.83. Other changes were specific for adenomas (PPA1 and PPA2 up-regulation; KCTD12 downregulation) or adenocarcinoma (ANP32B, G6PD, RCN1, and SET up-regulation; downregulated AKR1B1, APEX1, and PPA1). Some changes significantly correlated with a few patient- or tumor-related phenotypes. Twenty-two (96%) of the 23 proteins have a potential to be released from the tumors into the bloodstream, and their detectability in plasma has been previously reported. The proteins identified in this study expand the pool of biomarker candidates that can be used to develop a standardized precolonoscopy blood test for the early detection of colorectal tumors.

IDH-mutant glioma specific association of rs55705857 located at 8q24.21 involves MYC deregulation.

The single nucleotide polymorphism rs55705857, located in a non-coding but evolutionarily conserved region at 8q24.21, is strongly associated with IDH-mutant glioma development and was suggested to be a causal variant. However, the molecular mechanism underlying this association has remained unknown. With a case control study in 285 gliomas, 316 healthy controls, 380 systemic cancers, 31 other CNS-tumors, and 120 IDH-mutant cartilaginous tumors, we identified that the association was specific to IDH-mutant gliomas. Odds-ratios were 9.25 (5.17-16.52; 95% CI) for IDH-mutated gliomas and 12.85 (5.94-27.83; 95% CI) for IDH-mutated, 1p/19q co-deleted gliomas. Decreasing strength with increasing anaplasia implied a modulatory effect. No somatic mutations were noted at this locus in 114 blood-tumor pairs, nor was there a copy number difference between risk-allele and only-ancestral allele carriers. CCDC26 RNA-expression was rare and not different between the two groups. There were only minor subtype-specific differences in common glioma driver genes. RNA sequencing and LC-MS/MS comparisons pointed to significantly altered MYC-signaling. Baseline enhancer activity of the conserved region specifically on the MYC promoter and its further positive modulation by the SNP risk-allele was shown in vitro. Our findings implicate MYC deregulation as the underlying cause of the observed association.

Targeted proteomics coming of age - SRM, PRM and DIA performance evaluated from a core facility perspective.

Quantitative mass spectrometry is a rapidly evolving methodology applied in a large number of omics-type research projects. During the past years, new designs of mass spectrometers have been developed and launched as commercial systems while in parallel new data acquisition schemes and data analysis paradigms have been introduced. Core facilities provide access to such technologies, but also actively support the researchers in finding and applying the best-suited analytical approach. In order to implement a solid fundament for this decision making process, core facilities need to constantly compare and benchmark the various approaches. In this article we compare the quantitative accuracy and precision of current state of the art targeted proteomics approaches single reaction monitoring (SRM), parallel reaction monitoring (PRM) and data independent acquisition (DIA) across multiple liquid chromatography mass spectrometry (LC-MS) platforms, using a readily available commercial standard sample. All workflows are able to reproducibly generate accurate quantitative data. However, SRM and PRM workflows show higher accuracy and precision compared to DIA approaches, especially when analyzing low concentrated analytes.

Proteomic profiling of host-biofilm interactions in an oral infection model resembling the periodontal pocket.

Periodontal infections cause inflammatory destruction of the tooth supporting tissues. We recently developed a dynamic, in vitro periodontal organotypic tissue model in a perfusion bioreactor system, in co-culture with an 11-species subgingival biofilm, which may recapitulate early events during the establishment of periodontal infections. This study aimed to characterize the global proteome regulations in this host-biofilm interaction model. Semi-quantitative shotgun proteomics were applied for protein identification and quantification in the co-culture supernatants (human and bacterial) and the biofilm lysates (bacterial). A total of 896 and 3363 proteins were identified as secreted in the supernatant and expressed in the biofilm lysate, respectively. Enriched gene ontology analysis revealed that the regulated secreted human tissue proteins were related to processes of cytoskeletal rearrangement, stress responses, apoptosis, and antigen presentation, all of which are commensurate with deregulated host responses. Most secreted bacterial biofilm proteins derived from their cytoplasmic domain. In the presence of the tissue, the levels of Fusobacterium nucleatum, Actinomyces oris and Campylobacter rectus proteins were significantly regulated. The functions of the up-regulated intracellular (biofilm lysate) proteins were associated with cytokinesis. In conclusion, the proteomic overview of regulated pathways in this host-biofilm interaction model provides insights to the early events of periodontal pathogenesis.

Protein degradation corrects for imbalanced subunit stoichiometry in OST complex assembly.

Protein degradation is essential for cellular homeostasis. We developed a sensitive approach to examining protein degradation rates in Saccharomyces cerevisiae by coupling a SILAC approach to selected reaction monitoring (SRM) mass spectrometry. Combined with genetic tools, this analysis made it possible to study the assembly of the oligosaccharyl transferase complex. The ER-associated degradation machinery compensated for disturbed homeostasis of complex components by degradation of subunits in excess. On a larger scale, protein degradation in the ER was found to be a minor factor in the regulation of protein homeostasis in exponentially growing cells, but ERAD became relevant when the gene dosage was affected, as demonstrated in heterozygous diploid cells. Hence the alleviation of fitness defects due to abnormal gene copy numbers might be an important function of protein degradation.

Quantitative proteomics reveal distinct protein regulations caused by Aggregatibacter actinomycetemcomitans within subgingival biofilms.

Periodontitis is an infectious disease that causes the inflammatory destruction of the tooth-supporting (periodontal) tissues, caused by polymicrobial biofilm communities growing on the tooth surface. Aggressive periodontitis is strongly associated with the presence of Aggregatibacter actinomycetemcomitans in the subgingival biofilms. Nevertheless, whether and how A. actinomycetemcomitans orchestrates molecular changes within the biofilm is unclear. The aim of this work was to decipher the interactions between A. actinomycetemcomitans and other bacterial species in a multi-species biofilm using proteomic analysis. An in vitro 10-species "subgingival" biofilm model, or its derivative that included additionally A. actinomycetemcomitans, were anaerobically cultivated on hydroxyapatite discs for 64 h. When present, A. actinomycetemcomitans formed dense intra-species clumps within the biofilm mass, and did not affect the numbers of the other species in the biofilm. Liquid chromatography-tandem mass spectrometry was used to identify the proteomic content of the biofilm lysate. A total of 3225 and 3352 proteins were identified in the biofilm, in presence or absence of A. actinomycetemcomitans, respectively. Label-free quantitative proteomics revealed that 483 out of the 728 quantified bacterial proteins (excluding those of A. actinomycetemcomitans) were accordingly regulated. Interestingly, all quantified proteins from Prevotella intermedia were up-regulated, and most quantified proteins from Campylobacter rectus, Streptococcus anginosus, and Porphyromonas gingivalis were down-regulated in presence of A. actinomycetemcomitans. Enrichment of Gene Ontology pathway analysis showed that the regulated groups of proteins were responsible primarily for changes in the metabolic rate, the ferric iron-binding, and the 5S RNA binding capacities, on the universal biofilm level. While the presence of A. actinomycetemcomitans did not affect the numeric composition or absolute protein numbers of the other biofilm species, it caused qualitative changes in their overall protein expression profile. These molecular shifts within the biofilm warrant further investigation on their potential impact on its virulence properties, and association with periodontal pathogenesis.

Reproducible and consistent quantification of the Saccharomyces cerevisiae proteome by SWATH-mass spectrometry.

Targeted mass spectrometry by selected reaction monitoring (S/MRM) has proven to be a suitable technique for the consistent and reproducible quantification of proteins across multiple biological samples and a wide dynamic range. This performance profile is an important prerequisite for systems biology and biomedical research. However, the method is limited to the measurements of a few hundred peptides per LC-MS analysis. Recently, we introduced SWATH-MS, a combination of data independent acquisition and targeted data analysis that vastly extends the number of peptides/proteins quantified per sample, while maintaining the favorable performance profile of S/MRM. Here we applied the SWATH-MS technique to quantify changes over time in a large fraction of the proteome expressed in Saccharomyces cerevisiae in response to osmotic stress. We sampled cell cultures in biological triplicates at six time points following the application of osmotic stress and acquired single injection data independent acquisition data sets on a high-resolution 5600 tripleTOF instrument operated in SWATH mode. Proteins were quantified by the targeted extraction and integration of transition signal groups from the SWATH-MS datasets for peptides that are proteotypic for specific yeast proteins. We consistently identified and quantified more than 15,000 peptides and 2500 proteins across the 18 samples. We demonstrate high reproducibility between technical and biological replicates across all time points and protein abundances. In addition, we show that the abundance of hundreds of proteins was significantly regulated upon osmotic shock, and pathway enrichment analysis revealed that the proteins reacting to osmotic shock are mainly involved in the carbohydrate and amino acid metabolism. Overall, this study demonstrates the ability of SWATH-MS to efficiently generate reproducible, consistent, and quantitatively accurate measurements of a large fraction of a proteome across multiple samples.