DART-ID increases single-cell proteome coverage.

Analysis by liquid chromatography and tandem mass spectrometry (LC-MS/MS) can identify and quantify thousands of proteins in microgram-level samples, such as those comprised of thousands of cells. This process, however, remains challenging for smaller samples, such as the proteomes of single mammalian cells, because reduced protein levels reduce the number of confidently sequenced peptides. To alleviate this reduction, we developed Data-driven Alignment of Retention Times for IDentification (DART-ID). DART-ID implements principled Bayesian frameworks for global retention time (RT) alignment and for incorporating RT estimates towards improved confidence estimates of peptide-spectrum-matches. When applied to bulk or to single-cell samples, DART-ID increased the number of data points by 30-50% at 1% FDR, and thus decreased missing data. Benchmarks indicate excellent quantification of peptides upgraded by DART-ID and support their utility for quantitative analysis, such as identifying cell types and cell-type specific proteins. The additional datapoints provided by DART-ID boost the statistical power and double the number of proteins identified as differentially abundant in monocytes and T-cells. DART-ID can be applied to diverse experimental designs and is freely available at http://dart-id.slavovlab.net

Proteomic-biostatistic integrated approach for finding the underlying molecular determinants of hypertension in human plasma

Despite advancements in lowering blood pressure, the best approach to lower it remains controversial because of the lack of information on the molecular basis of hypertension. We, therefore, performed plasma proteomics of plasma from patients with hypertension to identify molecular determinants detectable in these subjects but not in controls and vice versa. Plasma samples from hypertensive subjects (cases; n=118) and controls (n=85) from the InGenious HyperCare cohort were used for this study and performed mass spectrometric analysis. Using biostatistical methods, plasma peptides specific for hypertension were identified, and a model was developed using least absolute shrinkage and selection operator logistic regression. The underlying peptides were identified and sequenced off-line using matrix-assisted laser desorption ionization orbitrap mass spectrometry. By comparison of the molecular composition of the plasma samples, 27 molecular determinants were identified differently expressed in cases from controls. Seventy percent of the molecular determinants selected were found to occur less likely in hypertensive patients. In cross-validation, the overall R(2) was 0.434, and the area under the curve was 0.891 with 95% confidence interval 0.8482 to 0.9349, P<0.0001. The mean values of the cross-validated proteomic score of normotensive and hypertensive patients were found to be -2.007±0.3568 and 3.383±0.2643, respectively, P<0.0001. The molecular determinants were successfully identified, and the proteomic model developed shows an excellent discriminatory ability between hypertensives and normotensives. The identified molecular determinants may be the starting point for further studies to clarify the molecular causes of hypertension

Pharmacoproteomic characterisation of human colon and rectal cancer

Most molecular cancer therapies act on protein targets but data on the proteome status of patients and cellular models for proteome-guided pre-clinical drug sensitivity studies are only beginning to emerge. Here, we profiled the proteomes of 65 colorectal cancer (CRC) cell lines to a depth of > 10,000 proteins using mass spectrometry. Integration with proteomes of 90 CRC patients and matched transcriptomics data defined integrated CRC subtypes, highlighting cell lines representative of each tumour subtype. Modelling the responses of 52 CRC cell lines to 577 drugs as a function of proteome profiles enabled predicting drug sensitivity for cell lines and patients. Among many novel associations, MERTK was identified as a predictive marker for resistance towards MEK1/2 inhibitors and immunohistochemistry of 1,074 CRC tumours confirmed MERTK as a prognostic survival marker. We provide the proteomic and pharmacological data as a resource to the community to, for example, facilitate the design of innovative prospective clinical trials. © 2017 The Authors. Published under the terms of the CC BY 4.0 licens

MaxQuant. Live Enables Global Targeting of More Than 25,000 Peptides

Mass spectrometry (MS)-based proteomics is often performed in a shotgun format, in which as many peptide precursors as possible are selected from full or MS1 scans so that their fragment spectra can be recorded in MS2 scans. Although achieving great proteome depths, shotgun proteomics cannot guarantee that each precursor will be fragmented in each run. In contrast, targeted proteomics aims to reproducibly and sensitively record a restricted number of precursor/ fragment combinations in each run, based on prescheduled mass-to-charge and retention time windows. Here we set out to unify these two concepts by a global targeting approach in which an arbitrary number of precursors of interest are detected in real-time, followed by standard fragmentation or advanced peptide-specific analyses. We made use of a fast application programming interface to a quadrupole Orbitrap instrument and real-time recalibration in mass, retention time and intensity dimensions to predict precursor identity. MaxQuant. Live is freely available (www. maxquant. live) and has a graphical user interface to specify many predefined data acquisition strategies. Acquisition speed is as fast as with the vendor software and the power of our approach is demonstrated with the acquisition of breakdown curves for hundreds of precursors of interest. We also uncover precursors that are not even visible in MS1 scans, using elution time prediction based on the auto-adjusted retention time alone. Finally, we successfully recognized and targeted more than 25,000 peptides in single LC-MS runs. Global targeting combines the advantages of two classical approaches in MS-based proteomics, whereas greatly expanding the analytical toolbox. Molecular & Cellular Proteomics 18: 982-994, 2019. DOI: 10.1074/ mcp. TIR118.001131

Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis

Background: Verification of cerebrospinal fluid (CSF) biomarkers for multiple sclerosis and other neurological diseases is a major challenge due to a large number of candidates, limited sample material availability, disease and biological heterogeneity, and the lack of standardized assays. Furthermore, verification studies are often based on a low number of proteins from a single discovery experiment in medium-sized cohorts, where antibodies and surrogate peptides may differ, thus only providing an indication of proteins affected by the disease and not revealing the bigger picture or concluding on the validity of the markers. We here present a standard approach for locating promising biomarker candidates based on existing knowledge, resulting in high-quality assays covering the main biological processes affected by multiple sclerosis for comparable measurements over time. Methods: Biomarker candidates were located in CSF-PR (proteomics.uib.no/csf-pr), and further filtered based on estimated concentration in CSF and biological function. Peptide surrogates for internal standards were selected according to relevant criteria, parallel reaction monitoring (PRM) assays created, and extensive assay quality testing performed, i.e. intra- and inter-day variation, trypsin digestion status over time, and whether the peptides were able to separate multiple sclerosis patients and controls. Results: Assays were developed for 25 proteins, represented by 72 peptides selected according to relevant guidelines and available literature and tested for assay peptide suitability. Stability testing revealed 64 peptides with low intra- and inter-day variations, with 44 also being stably digested after 16 h of trypsin digestion, and 37 furthermore showing a significant difference between multiple sclerosis and controls, thereby confirming literature findings. Calibration curves and the linear area of measurement have, so far, been determined for 17 of these peptides. Conclusions: We present 37 high-quality PRM assays across 21 CSF-proteins found to be affected by multiple sclerosis, along with a recommended workflow for future development of new assays. The assays can directly be used by others, thus enabling better comparison between studies. Finally, the assays can robustly and stably monitor biological processes in multiple sclerosis patients over time, thus potentially aiding in diagnosis and prognosis, and ultimately in treatment decisions.publishedVersio

Protein turnover measurement using selected reaction monitoring-mass spectrometry (SRM-MS)

Protein turnover represents an important mechanism in the functioning of cells, with deregulated synthesis and degradation of proteins implicated in many diseased states. Therefore, proteomics strategies to measure turnover rates with high confidence are of vital importance to understanding many biological processes. In this study, the more widely used approach of non-targeted precursor ion signal intensity (MS1) quantification is compared with selected reaction monitoring (SRM), a data acquisition strategy that records data for specific peptides, to determine if improved quantitative data would be obtained using a targeted quantification approach. Using mouse liver as a model system, turnover measurement of four tricarboxylic acid cycle proteins was performed using both MS1 and SRM quantification strategies. SRM outperformed MS1 in terms of sensitivity and selectivity of measurement, allowing more confident determination of protein turnover rates. SRM data are acquired using cheaper and more widely available tandem quadrupole mass spectrometers, making the approach accessible to a larger number of researchers than MS1 quantification, which is best performed on high mass resolution instruments. SRM acquisition is ideally suited to focused studies where the turnover of tens of proteins is measured, making it applicable in determining the dynamics of proteins complexes and complete metabolic pathways

Molecular responses of mouse macrophages to copper and copper oxide nanoparticles inferred from proteomic analyses

The molecular responses of macrophages to copper-based nanoparticles have been investigated via a combination of proteomic and biochemical approaches, using the RAW264.7 cell line as a model. Both metallic copper and copper oxide nanoparticles have been tested, with copper ion and zirconium oxide nanoparticles used as controls. Proteomic analysis highlighted changes in proteins implicated in oxidative stress responses (superoxide dismutases and peroxiredoxins), glutathione biosynthesis, the actomyosin cytoskeleton, and mitochondrial proteins (especially oxidative phosphorylation complex subunits). Validation studies employing functional analyses showed that the increases in glutathione biosynthesis and in mitochondrial complexes observed in the proteomic screen were critical to cell survival upon stress with copper-based nanoparticles; pharmacological inhibition of these two pathways enhanced cell vulnerability to copper-based nanoparticles, but not to copper ions. Furthermore, functional analyses using primary macrophages derived from bone marrow showed a decrease in reduced glutathione levels, a decrease in the mitochondrial transmembrane potential, and inhibition of phagocytosis and of lipopolysaccharide-induced nitric oxide production. However, only a fraction of these effects could be obtained with copper ions. In conclusion, this study showed that macrophage functions are significantly altered by copper-based nanoparticles. Also highlighted are the cellular pathways modulated by cells for survival and the exemplified cross-toxicities that can occur between copper-based nanoparticles and pharmacological agents

Optimization of differential ion mobility and segmented ion fractionation to improve proteome coverage

La sensibilité et la profondeur de l'analyse protéomique sont limitées par les ions isobares et les interférences qui entravent l'identification des peptides de faible abondance. Lorsque nous analysons des échantillons de grande complexité, une séparation extensive de l'échantillon est souvent nécessaire pour étendre la couverture protéomique. Ces dernières années, la spectrométrie de mobilité ionique à forme d'onde asymétrique à haut champ (FAIMS) a gagné en popularité dans le domaine de la protéomique pour sa capacité à séparer les ions isobares, à améliorer la capacité de pic et la sensibilité de la spectrométrie de masse (MS). Nous rapportons ici l'intégration d'un appareil FAIMS Pro™ à un Q-Exactive HF™ ainsi qu'un spectromètre de masse Orbitrap Exploris 480™. Des expériences protéomiques sur des digestions d'extraits protéiques issues de cellules Hela à l'aide d'un spectromètre de masse avec FAIMS ont amélioré le rapport signal sur bruit (S/N) et réduit les ions interférents, ce qui a entraîné une augmentation du taux d'identification des peptides de plus de 42 %. FAIMS est également combiné avec le fractionnement ionique segmenté (SIFT), qui utilise tour à tour une fenêtre de 100 ~ 300 m/z au lieu de la large plage traditionnelle (700 ~ 800 m/z), augmentant ainsi la profondeur de la couverture protéomique tout en réduisant la proportion de spectres MS/MS chimériques de 50% à 27%. Dans l'analyse quantitative, nous démontrons l'application de FAIMS pour améliorer les mesures quantitatives lorsque le marquage peptidique isobare est utilisé. Par rapport aux expériences LC-MS/MS conventionnelles, la combinaison des expériences FAIMS et SIFT réalisées sur un modèle à deux protéomes a montré une amélioration de 65 % de la précision des mesures quantitatives. Les digestions tryptiques d'extraits protéiques de différentes lignées cellulaires du cancer colorectal ont été utilisées pour l'évaluation de stratégie combinée FAIMS et SIFT sur un spectromètre de masse Orbitrap Exploris 480™ offre un gain d'identification de 70 % par rapport à l'approche conventionnelle et combinée aux données transcriptomiques elle facilite l’identification de variants protéiques.The sensitivity and depth of proteomic analysis in mass spectrometry (MS) is limited by isobaric ions and interferences that hinder the identification of low-abundance peptides. For high complexity samples, extensive separation is often required to expand proteomic coverage. In recent years, high-field asymmetric waveform ion mobility spectrometry (FAIMS) has gained popularity in the field of proteomics for its ability to resolve confounding ions, improve peak capacity, and sensitivity. This thesis presents the integration of a FAIMS Pro™ interface with electrical and gas embedded connections to a Q-Exactive HF™ as well as an Orbitrap Exploris 480™ mass spectrometer. Proteomic experiments on tryptic digests of HeLa cell line using a FAIMS integrated mass spectrometer improved signal-to-noise ratio (S/N) and reduced the occurrence of interfering ions. This enabled a 42% increase in peptide identification rate. Also, FAIMS was combined with segmented ion fractionation (SIFT), which in turn scans with windows of 100~300 m/z width instead of the traditional width (700~800 m/z), further increasing the depth of proteome coverage by a reducing from 50% to 27% in terms of MS/MS chimeric spectra numbers. The application of FAIMS gain improvement on quantitative measurements with TMT labeling method is presented. Compared to conventional LC-MS/MS tests, the combination of FAIMS and SIFT experiments showed a improvement by 65% in quantitative accuracy when performed on a human-yeast two-proteome model. As an application of the method, the tryptic digests from different colorectal cancer cell lines were used for the evaluation. FAIMS-SIFTcombined strategy on an Orbitrap Exploris 480™ mass spectrometer provides a 70% gain in identification compared to the conventional LC-MS/MS approach for the same sample amount and instrument time. This enhanced sensitivity facilitates single amino acid mutations confirmed by RNAseq analyses