Ludovic C. Gillet

Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis

Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400–1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics.

OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data.

Hannes L. Rost, 2, ∗ George Rosenberger, 2, ∗ Pedro Navarro, Ludovic Gillet, Sasa M. Miladinovic, 3 Olga T. Schubert, 2 Witold Wolski, Ben C. Collins, Johan Malmstrom, Lars Malmstrom, and Ruedi Aebersold 6, 7, † Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, CH-8093 Zurich, Switzerland Ph.D. Program in Systems Biology, University of Zurich and ETH Zurich, CH-8057 Zurich, Switzerland Biognosys AG, CH-8952 Schlieren, Switzerland SyBIT project of SystemsX.ch, ETH Zurich, CH-8092 Zurich, Switzerland Department of Immunotechnology, Lund University, S-22100 Lund, Sweden Competence Center for Systems Physiology and Metabolic Diseases, CH-8093 Zurich, Switzerland Faculty of Science, University of Zurich, CH-8057 Zurich, Switzerland (Dated: October 19, 2015)

Quantifying protein interaction dynamics by SWATH mass spectrometry: application to the 14-3-3 system

Protein complexes and protein interaction networks are essential mediators of most biological functions. Complexes supporting transient functions such as signal transduction processes are frequently subject to dynamic remodeling. Currently, the majority of studies on the composition of protein complexes are carried out by affinity purification and mass spectrometry (AP-MS) and present a static view of the system. For a better understanding of inherently dynamic biological processes, methods to reliably quantify temporal changes of protein interaction networks are essential. Here we used affinity purification combined with sequential window acquisition of all theoretical spectra (AP-SWATH) mass spectrometry to study the dynamics of the 14-3-3β scaffold protein interactome after stimulation of the insulin-PI3K-AKT pathway. The consistent and reproducible quantification of 1,967 proteins across all stimulation time points provided insights into the 14-3-3β interactome and its dynamic changes following IGF1 stimulation. We therefore establish AP-SWATH as a tool to quantify dynamic changes in protein-complex interaction networks.

Quantitative measurements of N-linked glycoproteins in human plasma by SWATH-MS.

SWATH‐MS is a data‐independent acquisition method that generates, in a single measurement, a complete recording of the fragment ion spectra of all the analytes in a biological sample for which the precursor ions are within a predetermined m/z versus retention time window. To assess the performance and suitability of SWATH‐MS‐based protein quantification for clinical use, we compared SWATH‐MS and SRM‐MS‐based quantification of N‐linked glycoproteins in human plasma, a commonly used sample for biomarker discovery. Using dilution series of isotopically labeled heavy peptides representing biomarker candidates, the LOQ of SWATH‐MS was determined to reach 0.0456 fmol at peptide level by targeted data analysis, which corresponds to a concentration of 5–10 ng protein/mL in plasma, while SRM reached a peptide LOQ of 0.0152 fmol. Moreover, the quantification of endogenous glycoproteins using SWATH‐MS showed a high degree of reproducibility, with the mean CV of 14.90%, correlating well with SRM results (R2 = 0.9784). Overall, SWATH‐MS measurements showed a slightly lower sensitivity and a comparable reproducibility to state‐of‐the‐art SRM measurements for targeted quantification of the N‐glycosites in human blood. However, a significantly larger number of peptides can be quantified per analysis. We suggest that SWATH‐MS analysis combined with N‐glycoproteome enrichment in plasma samples is a promising integrative proteomic approach for biomarker discovery and verification.

Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps

Clinical specimens are each inherently unique, limited and nonrenewable. Small samples such as tissue biopsies are often completely consumed after a limited number of analyses. Here we present a method that enables fast and reproducible conversion of a small amount of tissue (approximating the quantity obtained by a biopsy) into a single, permanent digital file representing the mass spectrometry (MS)-measurable proteome of the sample. The method combines pressure cycling technology (PCT) and sequential window acquisition of all theoretical fragment ion spectra (SWATH)-MS. The resulting proteome maps can be analyzed, re-analyzed, compared and mined in silico to detect and quantify specific proteins across multiple samples. We used this method to process and convert 18 biopsy samples from nine patients with renal cell carcinoma into SWATH-MS fragment ion maps. From these proteome maps we detected and quantified more than 2,000 proteins with a high degree of reproducibility across all samples. The measured proteins clearly distinguished tumorous kidney tissues from healthy tissues and differentiated distinct histomorphological kidney cancer subtypes.

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.

Glycoproteomic Analysis of Prostate Cancer Tissues by SWATH Mass Spectrometry Discovers N-acylethanolamine Acid Amidase and Protein Tyrosine Kinase 7 as Signatures for Tumor Aggressiveness

The identification of biomarkers indicating the level of aggressiveness of prostate cancer (PCa) will address the urgent clinical need to minimize the general overtreatment of patients with non-aggressive PCa, who account for the majority of PCa cases. Here, we isolated formerly N-linked glycopeptides from normal prostate (n = 10) and from non-aggressive (n = 24), aggressive (n = 16), and metastatic (n = 25) PCa tumor tissues and analyzed the samples using SWATH mass spectrometry, an emerging data-independent acquisition method that generates a single file containing fragment ion spectra of all ionized species of a sample. The resulting datasets were searched using a targeted data analysis strategy in which an a priori spectral reference library representing known N-glycosites of the human proteome was used to identify groups of signals in the SWATH mass spectrometry data. On average we identified 1430 N-glycosites from each sample. Out of those, 220 glycoproteins showed significant quantitative changes associated with diverse biological processes involved in PCa aggressiveness and metastasis and indicated functional relationships. Two glycoproteins, N-acylethanolamine acid amidase and protein tyrosine kinase 7, that were significantly associated with aggressive PCa in the initial sample cohort were further validated in an independent set of patient tissues using tissue microarray analysis. The results suggest that N-acylethanolamine acid amidase and protein tyrosine kinase 7 may be used as potential tissue biomarkers to avoid overtreatment of non-aggressive PCa.

Quantitative variability of 342 plasma proteins in a human twin population

The degree and the origins of quantitative variability of most human plasma proteins are largely unknown. Because the twin study design provides a natural opportunity to estimate the relative contribution of heritability and environment to different traits in human population, we applied here the highly accurate and reproducible SWATH mass spectrometry technique to quantify 1,904 peptides defining 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2–7 years, and proportioned the observed total quantitative variability to its root causes, genes, and environmental and longitudinal factors. The data indicate that different proteins show vastly different patterns of abundance variability among humans and that genetic control and longitudinal variation affect protein levels and biological processes to different degrees. The data further strongly suggest that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors. Moreover, we identified 13 cis‐SNPs significantly influencing the level of specific plasma proteins. These results therefore have immediate implications for the effective design of blood‐based biomarker studies.

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.

Absolute Proteome Composition and Dynamics during Dormancy and Resuscitation of Mycobacterium tuberculosis

Mycobacterium tuberculosis remains a health concern due to its ability to enter a non-replicative dormant state linked to drug resistance. Understanding transitions into and out of dormancy will inform therapeutic strategies. We implemented a universally applicable, label-free approach to estimate absolute cellular protein concentrations on a proteome-wide scale based on SWATH mass spectrometry. We applied this approach to examine proteomic reorganization of M. tuberculosis during exponential growth, hypoxia-induced dormancy, and resuscitation. The resulting data set covering >2,000 proteins reveals how protein biomass is distributed among cellular functions during these states. The stress-induced DosR regulon contributes 20% to cellular protein content during dormancy, whereas ribosomal proteins remain largely unchanged at 5%-7%. Absolute protein concentrations furthermore allow protein alterations to be translated into changes in maximal enzymatic reaction velocities, enhancing understanding of metabolic adaptations. Thus, global absolute protein measurements provide a quantitative description of microbial states, which can support the development of therapeutic interventions.