Publications by authors named "Lukas Reiter"

44 Publications

Low risk of contrast media induced hypersensitivity reactions in all subtypes of systemic mastocytosis.

Ann Allergy Asthma Immunol 2021 Oct 9. Epub 2021 Oct 9.

Clinic of Clinical Radiology and Nuclear Medicine, University Hospital Mannheim, Heidelberg University, Mannheim, Germany. Electronic address:

Background: Patients with SM are at increased risk of hypersensitivity reactions. Although hymenoptera venoms are the predominant triggers, cases of CMIHR have also been reported and prophylactic premedication is often performed. However, data from larger series are limited and differences between indolent and advanced systemic mastocytosis have not yet been investigated.

Objective: To determine the incidence and severity of CMIHR in all subtypes of SM.

Methods: We analyzed 162 adult patients with SM (ISM, n=65; advSM, n=97). Firstly, the cumulative incidence of CMIHR was retrospectively assessed in the patient's history. Secondly, at our institution, patients underwent 332 CM-enhanced imagings including 80 CT scans with iodine-based contrast agent and 252 MRI with gadoliniumbased contrast agent and tolerance was assessed.

Results: Previous CMIHRs to CT (vomiting, n=1, erythema, n=1, cardiovascular shock, n=1) and MRI (dyspnea, n=1, cardiovascular shock, n=1) had been reported by 4/162 (2.5%) patients (ISM, n=3; advSM, n=1). In contrast, during or after 332 CM-enhanced CT/MRI examinations at our institution, no CMIHRs were reported. Premedication was solely given to 3 patients prior to CT scans, including one with previous CMIHR, who tolerated the imaging well.

Conclusion: We conclude that i) there is a significant discrepancy between perception and prevalence of hypersensitivity reactions to CM in SM, ii) reactions are scarce in ISM and even rarer in advSM, iii) in SM patients without previous history of CM hypersensitivity, prophylactic premedication prior to CM enhanced-CT/MRI is dispensable.
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http://dx.doi.org/10.1016/j.anai.2021.10.004DOI Listing
October 2021

Clinical and histopathological features of myeloid neoplasms with concurrent Janus kinase 2 (JAK2) V617F and KIT proto-oncogene, receptor tyrosine kinase (KIT) D816V mutations.

Br J Haematol 2021 Jul 1;194(2):344-354. Epub 2021 Jun 1.

Haematology and Oncology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.

We report on 45 patients with myeloid neoplasms and concurrent Janus kinase 2 (JAK2) V617F and KIT proto-oncogene, receptor tyrosine kinase (KIT) D816V (JAK2 /KIT ) mutations, which are individually identified in >60% of patients with classical myeloproliferative neoplasms (MPN) and >90% of patients with systemic mastocytosis (SM) respectively. In SM, the concurrent presence of a clonal non-mast cell neoplasm [SM with associated haematological neoplasm (SM-AHN)] usually constitutes a distinct subtype associated with poor survival. All 45 patients presented with a heterogeneous combination of clinical/morphological features typical of the individual disorders (e.g. leuco-/erythro-/thrombocytosis and elevated lactate dehydrogenase for MPN; elevated serum tryptase and alkaline phosphatase for SM). Overlapping features identified in 70% of patients included splenomegaly, cytopenia(s), bone marrow fibrosis and additional somatic mutations. Molecular dissection revealed discordant development of variant allele frequency for both mutations and absence of concurrently positive single-cell derived colonies, indicating disease evolution in two independent clones rather than monoclonal disease in >60% of patients examined. Overall survival of JAK2 /KIT patients without additional somatic high-risk mutations [HRM, e.g. in serine and arginine-rich splicing factor 2 (SRSF2), additional sex combs like-1 (ASXL1) or Runt-related transcription factor 1 (RUNX1)] at 5 years was 77%, indicating that the mutual impact of JAK2 V617F and KIT D816V on prognosis is fundamentally different from the adverse impact of additional HRM in the individual disorders.
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http://dx.doi.org/10.1111/bjh.17567DOI Listing
July 2021

Adverse Prognostic Impact of the D816V Transcriptional Activity in Advanced Systemic Mastocytosis.

Int J Mol Sci 2021 Mar 4;22(5). Epub 2021 Mar 4.

Department of Hematology and Oncology, University Hospital Mannheim, Heidelberg University, 68167 Mannheim, Germany.

In systemic mastocytosis (SM), qualitative and serial quantitative assessment of the D816V mutation is of diagnostic and prognostic relevance. We investigated peripheral blood and bone marrow samples of 161 patients (indolent SM (ISM), = 40; advanced SM, AdvSM, = 121) at referral and during follow-up for the D816V variant allele frequency (VAF) at the DNA-level and the D816V expressed allele burden (EAB) at the RNA-level. A round robin test with four participating laboratories revealed an excellent correlation ( > 0.99, > 0.98) between three different DNA-assays. VAF and EAB strongly correlated in ISM ( 0.91, coefficient of determination, 0.84) but only to a lesser extent in AdvSM ( 0.71; = 0.5). However, as compared to an EAB/VAF ratio ≤2 (cohort A, 77/121 patients, 64%) receiver operating characteristic (ROC) analysis identified an EAB/VAF ratio of >2 (cohort B, 44/121 patients, 36%) as predictive for an advanced phenotype and a significantly inferior median survival (3.3 vs. 11.7 years; = 0.005). In terms of overall survival, Cox-regression analysis was only significant for the EAB/VAF ratio >2 ( = 0.006) but not for VAF or EAB individually. This study demonstrates for the first time that the transcriptional activity of D816V may play an important role in the pathophysiology of SM.
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http://dx.doi.org/10.3390/ijms22052562DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7961551PMC
March 2021

MassIVE.quant: a community resource of quantitative mass spectrometry-based proteomics datasets.

Nat Methods 2020 10 14;17(10):981-984. Epub 2020 Sep 14.

Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA.

MassIVE.quant is a repository infrastructure and data resource for reproducible quantitative mass spectrometry-based proteomics, which is compatible with all mass spectrometry data acquisition types and computational analysis tools. A branch structure enables MassIVE.quant to systematically store raw experimental data, metadata of the experimental design, scripts of the quantitative analysis workflow, intermediate input and output files, as well as alternative reanalyses of the same dataset.
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http://dx.doi.org/10.1038/s41592-020-0955-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7541731PMC
October 2020

A machine learning-based chemoproteomic approach to identify drug targets and binding sites in complex proteomes.

Nat Commun 2020 08 21;11(1):4200. Epub 2020 Aug 21.

Biognosys AG, Wagistrasse 21, 8952, Schlieren, Switzerland.

Chemoproteomics is a key technology to characterize the mode of action of drugs, as it directly identifies the protein targets of bioactive compounds and aids in the development of optimized small-molecule compounds. Current approaches cannot identify the protein targets of a compound and also detect the interaction surfaces between ligands and protein targets without prior labeling or modification. To address this limitation, we here develop LiP-Quant, a drug target deconvolution pipeline based on limited proteolysis coupled with mass spectrometry that works across species, including in human cells. We use machine learning to discern features indicative of drug binding and integrate them into a single score to identify protein targets of small molecules and approximate their binding sites. We demonstrate drug target identification across compound classes, including drugs targeting kinases, phosphatases and membrane proteins. LiP-Quant estimates the half maximal effective concentration of compound binding sites in whole cell lysates, correctly discriminating drug binding to homologous proteins and identifying the so far unknown targets of a fungicide research compound.
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http://dx.doi.org/10.1038/s41467-020-18071-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442650PMC
August 2020

Importance of Adequate Diagnostic Workup for Correct Diagnosis of Advanced Systemic Mastocytosis.

J Allergy Clin Immunol Pract 2020 10 15;8(9):3121-3127.e1. Epub 2020 May 15.

Department of Hematology and Oncology, University Hospital Mannheim, Heidelberg University, Mannheim, Germany. Electronic address:

Background: Little is known about the epidemiology of advanced systemic mastocytosis (advSM).

Objectives: To investigate epidemiologic features and diagnostic pitfalls of advSM in Germany.

Methods: Therefore, 140 patients from a single German reference center of the European Competence Network on Mastocytosis between 2003 and 2018 were analyzed.

Results: The patients' median age was 68 years (range, 26-86 years), and male versus female ratio was 2:1. An elevated serum tryptase, a KIT D816 mutation, and additional somatic mutations, for example, in SRSF2, ASXL1, or RUNX1, were identified in 95%, 91%, and 74% of patients, respectively. Median overall survival was 3.5 years (range, 0.03-14.3 years; male vs female 2.6 vs 4.2 years; P = .02). Two categories of misdiagnoses were identified in 51 of 140 (36%) patients: First, systemic mastocytosis (SM) was overlooked in 28 of 140 (20%) patients primarily diagnosed with various subtypes of myeloid neoplasms. Second, 23 of 140 (16%) patients were diagnosed with supposed progression from indolent SM to advSM; however, combination of an elevated KIT D816V variant allele frequency in peripheral blood (n = 22), monocytosis (n = 9), eosinophilia (n = 6), and/or mutations in SRSF2, ASXL1, or RUNX1 (n = 10) suggest that distinct signs of potential advSM were overlooked in virtually all patients. Based on locally diagnosed patients in an area of 2.5 million inhabitants, but obviously without considering more, yet unrecognized cases, the incidence and prevalence of advSM is at least 0.8 and 5.2, respectively, per 1 million inhabitants.

Conclusions: Adequate analyses of tryptase levels, bone marrow morphology, and genetics in patients with myeloid neoplasms or SM would help to prevent the significant underdiagnosis of advSM.
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http://dx.doi.org/10.1016/j.jaip.2020.05.005DOI Listing
October 2020

Revealing Dynamic Protein Acetylation across Subcellular Compartments.

J Proteome Res 2020 06 27;19(6):2404-2418. Epub 2020 Apr 27.

Biomolecular Chemistry Department, School of Medicine and Public Health, University of Wisconsin-Madison, 53706 Madison, Wisconsin, United States.

Protein acetylation is a widespread post-translational modification implicated in many cellular processes. Recent advances in mass spectrometry have enabled the cataloging of thousands of sites throughout the cell; however, identifying regulatory acetylation marks have proven to be a daunting task. Knowledge of the kinetics and stoichiometry of site-specific acetylation is an important factor to uncover function. Here, an improved method of quantifying acetylation stoichiometry was developed and validated, providing a detailed landscape of dynamic acetylation stoichiometry within cellular compartments. The dynamic nature of site-specific acetylation in response to serum stimulation was revealed. In two distinct human cell lines, growth factor stimulation led to site-specific, temporal acetylation changes, revealing diverse kinetic profiles that clustered into several groups. Overlap of dynamic acetylation sites among two different human cell lines suggested similar regulatory control points across major cellular pathways that include splicing, translation, and protein homeostasis. Rapid increases in acetylation on protein translational machinery suggest a positive regulatory role under progrowth conditions. Finally, higher median stoichiometry was observed in cellular compartments where active acetyltransferases are well described. Data sets can be accessed through ProteomExchange via the MassIVE repository (ProteomExchange: PXD014453; MassIVE: MSV000084029).
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http://dx.doi.org/10.1021/acs.jproteome.0c00088DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7427125PMC
June 2020

Isoform-resolved correlation analysis between mRNA abundance regulation and protein level degradation.

Mol Syst Biol 2020 03;16(3):e9170

Yale Cancer Biology Institute, Yale University, West Haven, CT, USA.

Profiling of biological relationships between different molecular layers dissects regulatory mechanisms that ultimately determine cellular function. To thoroughly assess the role of protein post-translational turnover, we devised a strategy combining pulse stable isotope-labeled amino acids in cells (pSILAC), data-independent acquisition mass spectrometry (DIA-MS), and a novel data analysis framework that resolves protein degradation rate on the level of mRNA alternative splicing isoforms and isoform groups. We demonstrated our approach by the genome-wide correlation analysis between mRNA amounts and protein degradation across different strains of HeLa cells that harbor a high grade of gene dosage variation. The dataset revealed that specific biological processes, cellular organelles, spatial compartments of organelles, and individual protein isoforms of the same genes could have distinctive degradation rate. The protein degradation diversity thus dissects the corresponding buffering or concerting protein turnover control across cancer cell lines. The data further indicate that specific mRNA splicing events such as intron retention significantly impact the protein abundance levels. Our findings support the tight association between transcriptome variability and proteostasis and provide a methodological foundation for studying functional protein degradation.
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http://dx.doi.org/10.15252/msb.20199170DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7073818PMC
March 2020

Rapid and site-specific deep phosphoproteome profiling by data-independent acquisition without the need for spectral libraries.

Nat Commun 2020 02 7;11(1):787. Epub 2020 Feb 7.

Novo Nordisk Foundation Center for Protein Research, Proteomics Program, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3b, 2200, Copenhagen, Denmark.

Quantitative phosphoproteomics has transformed investigations of cell signaling, but it remains challenging to scale the technology for high-throughput analyses. Here we report a rapid and reproducible approach to analyze hundreds of phosphoproteomes using data-independent acquisition (DIA) with an accurate site localization score incorporated into Spectronaut. DIA-based phosphoproteomics achieves an order of magnitude broader dynamic range, higher reproducibility of identification, and improved sensitivity and accuracy of quantification compared to state-of-the-art data-dependent acquisition (DDA)-based phosphoproteomics. Notably, direct DIA without the need of spectral libraries performs close to analyses using project-specific libraries, quantifying > 20,000 phosphopeptides in 15 min single-shot LC-MS analysis per condition. Adaptation of a 3D multiple regression model-based algorithm enables global determination of phosphorylation site stoichiometry in DIA. Scalability of the DIA approach is demonstrated by systematically analyzing the effects of thirty kinase inhibitors in context of epidermal growth factor (EGF) signaling showing that specific protein kinases mediate EGF-dependent phospho-regulation.
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http://dx.doi.org/10.1038/s41467-020-14609-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7005859PMC
February 2020

Combining Precursor and Fragment Information for Improved Detection of Differential Abundance in Data Independent Acquisition.

Mol Cell Proteomics 2020 02 30;19(2):421-430. Epub 2019 Dec 30.

Biognosys, Wagistrasse 21, 8952 Schlieren, Switzerland. Electronic address:

In bottom-up, label-free discovery proteomics, biological samples are acquired in a data-dependent (DDA) or data-independent (DIA) manner, with peptide signals recorded in an intact (MS1) and fragmented (MS2) form. While DDA has only the MS1 space for quantification, DIA contains both MS1 and MS2 at high quantitative quality. DIA profiles of complex biological matrices such as tissues or cells can contain quantitative interferences, and the interferences at the MS1 and the MS2 signals are often independent. When comparing biological conditions, the interferences can compromise the detection of differential peptide or protein abundance and lead to false positive or false negative conclusions.We hypothesized that the combined use of MS1 and MS2 quantitative signals could improve our ability to detect differentially abundant proteins. Therefore, we developed a statistical procedure incorporating both MS1 and MS2 quantitative information of DIA. We benchmarked the performance of the MS1-MS2-combined method to the individual use of MS1 or MS2 in DIA using four previously published controlled mixtures, as well as in two previously unpublished controlled mixtures. In the majority of the comparisons, the combined method outperformed the individual use of MS1 or MS2. This was particularly true for comparisons with low fold changes, few replicates, and situations where MS1 and MS2 were of similar quality. When applied to a previously unpublished investigation of lung cancer, the MS1-MS2-combined method increased the coverage of known activated pathways.Since recent technological developments continue to increase the quality of MS1 signals ( using the BoxCar scan mode for Orbitrap instruments), the combination of the MS1 and MS2 information has a high potential for future statistical analysis of DIA data.
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http://dx.doi.org/10.1074/mcp.RA119.001705DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7000113PMC
February 2020

Classification of mouse B cell types using surfaceome proteotype maps.

Nat Commun 2019 12 16;10(1):5734. Epub 2019 Dec 16.

Biomedical Proteomics Platform, Department of Health Sciences and Technology, ETH Zurich, 8093, Zurich, Switzerland.

System-wide quantification of the cell surface proteotype and identification of extracellular glycosylation sites is challenging when samples are limited. Here, we miniaturize and automate the previously described Cell Surface Capture (CSC) technology, increasing sensitivity, reproducibility and throughput. We use this technology, which we call autoCSC, to create population-specific surfaceome maps of developing mouse B cells and use targeted flow cytometry to uncover developmental cell subpopulations.
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http://dx.doi.org/10.1038/s41467-019-13418-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6915781PMC
December 2019

Systematic Comparison of Strategies for the Enrichment of Lysosomes by Data Independent Acquisition.

J Proteome Res 2020 01 10;19(1):371-381. Epub 2019 Dec 10.

Institute for Biochemistry and Molecular Biology , University of Bonn , 53115 Bonn , Germany.

In mammalian cells, the lysosome is the main organelle for the degradation of macromolecules and the recycling of their building blocks. Correct lysosomal function is essential, and mutations in every known lysosomal hydrolase result in so-called lysosomal storage disorders, a group of rare and often fatal inherited diseases. Furthermore, it is becoming more and more apparent that lysosomes play also decisive roles in other diseases, such as cancer and common neurodegenerative disorders. This leads to an increasing interest in the proteomic analysis of lysosomes for which enrichment is a prerequisite. In this study, we compared the four most common strategies for the enrichment of lysosomes using data-independent acquisition. We performed centrifugation at 20,000 × to generate an organelle-enriched pellet, two-step sucrose density gradient centrifugation, enrichment by superparamagnetic iron oxide nanoparticles (SPIONs), and immunoprecipitation using a 3xHA tagged version of the lysosomal membrane protein TMEM192. Our results show that SPIONs and TMEM192 immunoprecipitation outperform the other approaches with enrichment factors of up to 118-fold for certain proteins relative to whole cell lysates. Furthermore, we achieved an increase in identified lysosomal proteins and a higher reproducibility in protein intensities for label-free quantification in comparison to the other strategies.
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http://dx.doi.org/10.1021/acs.jproteome.9b00580DOI Listing
January 2020

Surpassing 10 000 identified and quantified proteins in a single run by optimizing current LC-MS instrumentation and data analysis strategy.

Mol Omics 2019 10;15(5):348-360

Biognosys AG, Wagistrasse 21, 8952 Schlieren, Switzerland.

Comprehensive proteome quantification is crucial for a better understanding of underlying mechanisms of diseases. Liquid chromatography mass spectrometry (LC-MS) has become the method of choice for comprehensive proteome quantification due to its power and versatility. Even though great advances have been made in recent years, full proteome coverage for complex samples remains challenging due to the high dynamic range of protein expression. Additionally, when studying disease regulatory proteins, biomarkers or potential drug targets are often low abundant, such as for instance kinases and transcription factors. Here, we show that with improvements in chromatography and data analysis the single shot proteome coverage can go beyond 10 000 proteins in human tissue. In a testis cancer study, we quantified 11 200 proteins using data independent acquisition (DIA). This depth was achieved with a false discovery rate of 1% which was experimentally validated using a two species test. We introduce the concept of hybrid libraries which combines the strength of direct searching of DIA data as well as the use of large project-specific or published DDA data sets. Remarkably deep proteome coverage is possible using hybrid libraries without the additional burden of creating a project-specific library. Within the testis cancer set, we found a large proportion of proteins in an altered expression (in total: 3351; 1453 increased in cancer). Many of these proteins could be linked to the hallmarks of cancer. For example, the complement system was downregulated which helps to evade the immune response and chromosomal replication was upregulated indicating a dysregulated cell cycle.
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http://dx.doi.org/10.1039/c9mo00082hDOI Listing
October 2019

Analysis of 1508 Plasma Samples by Capillary-Flow Data-Independent Acquisition Profiles Proteomics of Weight Loss and Maintenance.

Mol Cell Proteomics 2019 06 4;18(6):1242-1254. Epub 2019 Apr 4.

From the ‡Biognosys, 8952 Zurich-Schlieren, Switzerland;

Comprehensive, high throughput analysis of the plasma proteome has the potential to enable holistic analysis of the health state of an individual. Based on our own experience and the evaluation of recent large-scale plasma mass spectrometry (MS) based proteomic studies, we identified two outstanding challenges: slow and delicate nano-flow liquid chromatography (LC) and irreproducibility of identification of data-dependent acquisition (DDA). We determined an optimal solution reducing these limitations with robust capillary-flow data-independent acquisition (DIA) MS. This platform can measure 31 plasma proteomes per day. Using this setup, we acquired a large-scale plasma study of the diet, obesity and genes dietary (DiOGenes) comprising 1508 samples. Proving the robustness, the complete acquisition was achieved on a single analytical column. Totally, 565 proteins (459 identified with two or more peptide sequences) were profiled with 74% data set completeness. On average 408 proteins (5246 peptides) were identified per acquisition (319 proteins in 90% of all acquisitions). The workflow reproducibility was assessed using 34 quality control pools acquired at regular intervals, resulting in 92% data set completeness with CVs for protein measurements of 10.9%.The profiles of 20 apolipoproteins could be profiled revealing distinct changes. The weight loss and weight maintenance resulted in sustained effects on low-grade inflammation, as well as steroid hormone and lipid metabolism, indicating beneficial effects. Comparison to other large-scale plasma weight loss studies demonstrated high robustness and quality of biomarker candidates identified. Tracking of nonenzymatic glycation indicated a delayed, slight reduction of glycation in the weight maintenance phase. Using stable-isotope-references, we could directly and absolutely quantify 60 proteins in the DIA.In conclusion, we present herein the first large-scale plasma DIA study and one of the largest clinical research proteomic studies to date. Application of this fast and robust workflow has great potential to advance biomarker discovery in plasma.
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http://dx.doi.org/10.1074/mcp.RA118.001288DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6553938PMC
June 2019

Comparison of Protein Quantification in a Complex Background by DIA and TMT Workflows with Fixed Instrument Time.

J Proteome Res 2019 03 20;18(3):1340-1351. Epub 2019 Feb 20.

Biognosys AG , Wagistrasse 21 , 8952 Schlieren , Switzerland.

Label-free quantification (LFQ) and isobaric labeling quantification (ILQ) are among the most popular protein quantification workflows in discovery proteomics. Here, we compared the TMT SPS/MS3 10-plex workflow to a label free single shot data-independent acquisition (DIA) workflow on a controlled sample set. The sample set consisted of ten samples derived from 10 biological replicates of mouse cerebelli spiked with the UPS2 protein standard in five different concentrations. For a fair comparison, we matched the instrument time for the two workflows. The LC-MS data were acquired at two facilities to assess interlaboratory reproducibility. Both methods resulted in a high proteome coverage (>5000 proteins) with low missing values on protein level (<2%). The TMT workflow led to 15-20% more identified proteins and a slightly better quantitative precision, whereas the quantitative accuracy was better for the DIA method. The quantitative performance was benchmarked by the number of true positives (UPS2 proteins) within the top 100 candidates. TMT and DIA showed a similar performance. The quantitative performance of the DIA data stayed in a similar range when searching the spectra against a fasta database directly, instead of using a project-specific library. Our experiments also demonstrated that both workflows are readily transferrable between facilities.
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http://dx.doi.org/10.1021/acs.jproteome.8b00898DOI Listing
March 2019

Data-independent Acquisition Improves Quantitative Cross-linking Mass Spectrometry.

Mol Cell Proteomics 2019 04 16;18(4):786-795. Epub 2019 Jan 16.

From the ‡Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany;; §Wellcome Centre for Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, Scotland, United Kingdom;. Electronic address:

Quantitative cross-linking mass spectrometry (QCLMS) reveals structural detail on altered protein states in solution. On its way to becoming a routine technology, QCLMS could benefit from data-independent acquisition (DIA), which generally enables greater reproducibility than data-dependent acquisition (DDA) and increased throughput over targeted methods. Therefore, here we introduce DIA to QCLMS by extending a widely used DIA software, Spectronaut, to also accommodate cross-link data. A mixture of seven proteins cross-linked with bis[sulfosuccinimidyl] suberate (BS) was used to evaluate this workflow. Out of the 414 identified unique residue pairs, 292 (70%) were quantifiable across triplicates with a coefficient of variation (CV) of 10%, with manual correction of peak selection and boundaries for PSMs in the lower quartile of individual CV values. This compares favorably to DDA where we quantified cross-links across triplicates with a CV of 66%, for a single protein. We found DIA-QCLMS to be capable of detecting changing abundances of cross-linked peptides in complex mixtures, despite the ratio compression encountered when increasing sample complexity through the addition of cell lysate as matrix. In conclusion, the DIA software Spectronaut can now be used in cross-linking and DIA is indeed able to improve QCLMS.
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http://dx.doi.org/10.1074/mcp.TIR118.001276DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6442367PMC
April 2019

MSstatsQC 2.0: R/Bioconductor Package for Statistical Quality Control of Mass Spectrometry-Based Proteomics Experiments.

J Proteome Res 2019 02 14;18(2):678-686. Epub 2018 Dec 14.

College of Computer Science , Northeastern University , Boston , Massachusetts 02115 , United States.

MSstatsQC is an R/Bioconductor package for statistical monitoring of longitudinal system suitability and quality control in mass spectrometry-based proteomics. MSstatsQC was initially designed for targeted selected reaction monitoring experiments. This paper presents an extension, MSstatsQC 2.0, that supports experiments with global data-dependent and data-independent acquisition. The extension implements data processing and analyses that are specific to these acquisition types. It relies on state-of-the-art methods of statistical process control to detect deviations from optimal performance of various metrics (such as intensity and retention time of chromatographic peaks) and to summarize the results across multiple metrics and analytes. Additionally, the web-based graphical user interface MSstatsQCgui, implemented as a separate R/Bioconductor package, provides a user-friendly way to visualize and report the results from MSstatsQC 2.0.
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http://dx.doi.org/10.1021/acs.jproteome.8b00732DOI Listing
February 2019

Cost-effective generation of precise label-free quantitative proteomes in high-throughput by microLC and data-independent acquisition.

Sci Rep 2018 03 12;8(1):4346. Epub 2018 Mar 12.

Department of Biochemistry and Cambridge Systems Biology Centre, University of Cambridge, 80 Tennis Court Rd, Cambridge, CB2 1GA, UK.

Quantitative proteomics is key for basic research, but needs improvements to satisfy an increasing demand for large sample series in diagnostics, academia and industry. A switch from nanoflowrate to microflowrate chromatography can improve throughput and reduce costs. However, concerns about undersampling and coverage have so far hampered its broad application. We used a QTOF mass spectrometer of the penultimate generation (TripleTOF5600), converted a nanoLC system into a microflow platform, and adapted a SWATH regime for large sample series by implementing retention time- and batch correction strategies. From 3 µg to 5 µg of unfractionated tryptic digests that are obtained from proteomics-typical amounts of starting material, microLC-SWATH-MS quantifies up to 4000 human or 1750 yeast proteins in an hour or less. In the acquisition of 750 yeast proteomes, retention times varied between 2% and 5%, and quantified the typical peptide with 5-8% signal variation in replicates, and below 20% in samples acquired over a five-months period. Providing precise quantities without being dependent on the latest hardware, our study demonstrates that the combination of microflow chromatography and data-independent acquisition strategies has the potential to overcome current bottlenecks in academia and industry, enabling the cost-effective generation of precise quantitative proteomes in large scale.
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http://dx.doi.org/10.1038/s41598-018-22610-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5847575PMC
March 2018

Plasma Proteomics for Epidemiology: Increasing Throughput With Standard-Flow Rates.

Circ Cardiovasc Genet 2017 Dec;10(6)

From the King's British Heart Foundation Centre, King's College London, United Kingdom (X.Y., F.B., E.H., H.H., M.M.); Agilent Technologies Ltd, Cheadle, United Kingdom (R.T.B., A.S.); Biognosys AG, Schlieren, Switzerland (T.G., S.M., L.R.); Department of Neurology, Medical University of Innsbruck, Austria (R.P., J.W., S.K.); School of Medicine, University of California San Diego (S.T., J.L.W.); and Department of Laboratory Medicine, Bruneck Hospital, Italy (P.S.).

Background: Mass spectrometry is selective and sensitive, permitting routine quantification of multiple plasma proteins. However, commonly used nanoflow liquid chromatography (LC) approaches hamper sample throughput, reproducibility, and robustness. For this reason, most publications using plasma proteomics to date are small in study size.

Methods And Results: Here, we tested a standard-flow LC mass spectrometry (MS) method using multiple reaction monitoring for the application to large epidemiological cohorts. We have reduced the LC-MS run time to almost a third of the nanoflow LC-MS approach. On the basis of a comparison of the quantification of 100 plasma proteins in >1500 LC-MS runs, the SD range of the retention time during continuous operation was substantially lower with the standard-flow LC-MS (<0.05 minutes) compared with the nanoflow LC-MS method (0.26-0.44 minutes). In addition, the standard-flow LC method also offered less variation in protein measurements. However, 5× more sample volume was required to achieve similar sensitivity. Two different commercial multiple reaction monitoring kits and an antibody-based multiplexing kit were used to compare the apolipoprotein measurements in a subset of samples. In general, good agreement was observed between the 2 multiple reaction monitoring kits, but some of the multiple reaction monitoring-based measurements differed from antibody-based assays.

Conclusions: The multiplexing capability of LC-MS combined with a standard-flow method increases throughput and reduces the costs of large-scale protein measurements in epidemiological cohorts, but protein rather than peptide standards will be required for defined absolute proteoform quantification.
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http://dx.doi.org/10.1161/CIRCGENETICS.117.001808DOI Listing
December 2017

Optimization of Experimental Parameters in Data-Independent Mass Spectrometry Significantly Increases Depth and Reproducibility of Results.

Mol Cell Proteomics 2017 Dec 25;16(12):2296-2309. Epub 2017 Oct 25.

From the ‡Biognosys, Wagistrasse 21, 8952 Schlieren, Switzerland.

Comprehensive, reproducible and precise analysis of large sample cohorts is one of the key objectives of quantitative proteomics. Here, we present an implementation of data-independent acquisition using its parallel acquisition nature that surpasses the limitation of serial MS2 acquisition of data-dependent acquisition on a quadrupole ultra-high field Orbitrap mass spectrometer. In deep single shot data-independent acquisition, we identified and quantified 6,383 proteins in human cell lines using 2-or-more peptides/protein and over 7100 proteins when including the 717 proteins that were identified on the basis of a single peptide sequence. 7739 proteins were identified in mouse tissues using 2-or-more peptides/protein and 8121 when including the 382 proteins that were identified based on a single peptide sequence. Missing values for proteins were within 0.3 to 2.1% and median coefficients of variation of 4.7 to 6.2% among technical triplicates. In very complex mixtures, we could quantify 10,780 proteins and 12,192 proteins when including the 1412 proteins that were identified based on a single peptide sequence. Using this optimized DIA, we investigated large-protein networks before and after the critical period for whisker experience-induced synaptic strength in the murine somatosensory cortex 1-barrel field. This work shows that parallel mass spectrometry enables proteome profiling for discovery with high coverage, reproducibility, precision and scalability.
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http://dx.doi.org/10.1074/mcp.RA117.000314DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5724188PMC
December 2017

Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses.

Nat Methods 2017 Sep 21;14(9):921-927. Epub 2017 Aug 21.

Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is the main method for high-throughput identification and quantification of peptides and inferred proteins. Within this field, data-independent acquisition (DIA) combined with peptide-centric scoring, as exemplified by the technique SWATH-MS, has emerged as a scalable method to achieve deep and consistent proteome coverage across large-scale data sets. We demonstrate that statistical concepts developed for discovery proteomics based on spectrum-centric scoring can be adapted to large-scale DIA experiments that have been analyzed with peptide-centric scoring strategies, and we provide guidance on their application. We show that optimal tradeoffs between sensitivity and specificity require careful considerations of the relationship between proteins in the samples and proteins represented in the spectral library. We propose the application of a global analyte constraint to prevent the accumulation of false positives across large-scale data sets. Furthermore, to increase the quality and reproducibility of published proteomic results, well-established confidence criteria should be reported for the detected peptide queries, peptides and inferred proteins.
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http://dx.doi.org/10.1038/nmeth.4398DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5581544PMC
September 2017

WITHDRAWN: Heralds of parallel MS: Data-independent acquisition surpassing sequential identification of data dependent acquisition in proteomics.

Mol Cell Proteomics 2017 Apr 20. Epub 2017 Apr 20.

Biognosys AG, Switzerland;

This article has been withdrawn by the authors. This article did not comply with the editorial guidelines of MCP. Specifically, single peptide based protein identifications of 9-19% were included in the analysis and discussed in the results and conclusions. We wish to withdraw this article and resubmit a clarified, corrected manuscript for review.
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http://dx.doi.org/10.1074/mcp.M116.065730DOI Listing
April 2017

New targeted approaches for the quantification of data-independent acquisition mass spectrometry.

Proteomics 2017 May;17(9)

Somatosensory Signaling and Systems Biology Research Group, Max Planck Institute of Experimental Medicine, Goettingen, Germany.

The use of data-independent acquisition (DIA) approaches for the reproducible and precise quantification of complex protein samples has increased in the last years. The protein information arising from DIA analysis is stored in digital protein maps (DIA maps) that can be interrogated in a targeted way by using ad hoc or publically available peptide spectral libraries generated on the same sample species as for the generation of the DIA maps. The restricted availability of certain difficult-to-obtain human tissues (i.e., brain) together with the caveats of using spectral libraries generated under variable experimental conditions limits the potential of DIA. Therefore, DIA workflows would benefit from high-quality and extended spectral libraries that could be generated without the need of using valuable samples for library production. We describe here two new targeted approaches, using either classical data-dependent acquisition repositories (not specifically built for DIA) or ad hoc mouse spectral libraries, which enable the profiling of human brain DIA data set. The comparison of our results to both the most extended publically available human spectral library and to a state-of-the-art untargeted method supports the use of these new strategies to improve future DIA profiling efforts.
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http://dx.doi.org/10.1002/pmic.201700021DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870755PMC
May 2017

A multicenter study benchmarks software tools for label-free proteome quantification.

Nat Biotechnol 2016 Nov 3;34(11):1130-1136. Epub 2016 Oct 3.

Institute for Immunology, University Medical Center of the Johannes-Gutenberg University Mainz, Mainz, Germany.

Consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH 2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-MS, which uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test data sets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation-window setups. For consistent evaluation, we developed LFQbench, an R package, to calculate metrics of precision and accuracy in label-free quantitative MS and report the identification performance, robustness and specificity of each software tool. Our reference data sets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics.
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http://dx.doi.org/10.1038/nbt.3685DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5120688PMC
November 2016

High-precision iRT prediction in the targeted analysis of data-independent acquisition and its impact on identification and quantitation.

Proteomics 2016 08 28;16(15-16):2246-56. Epub 2016 Jun 28.

Biognosys, Wagistrasse 25, CH-8952 Schlieren, Switzerland.

Targeted analysis of data-independent acquisition (DIA) data is a powerful mass spectrometric approach for comprehensive, reproducible and precise proteome quantitation. It requires a spectral library, which contains for all considered peptide precursor ions empirically determined fragment ion intensities and their predicted retention time (RT). RTs, however, are not comparable on an absolute scale, especially if heterogeneous measurements are combined. Here, we present a method for high-precision prediction of RT, which significantly improves the quality of targeted DIA analysis compared to in silico RT prediction and the state of the art indexed retention time (iRT) normalization approach. We describe a high-precision normalized RT algorithm, which is implemented in the Spectronaut software. We, furthermore, investigate the influence of nine different experimental factors, such as chromatographic mobile and stationary phase, on iRT precision. In summary, we show that using targeted analysis of DIA data with high-precision iRT significantly increases sensitivity and data quality. The iRT values are generally transferable across a wide range of experimental conditions. Best results, however, are achieved if library generation and analytical measurements are performed on the same system.
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http://dx.doi.org/10.1002/pmic.201500488DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5094550PMC
August 2016

Primary resistance of Helicobacter pylori is still low in Southern Austria.

Int J Med Microbiol 2016 Jun 23;306(4):206-11. Epub 2016 Apr 23.

Division of Gastroenterology and Hepatology, Department of Internal Medicine, Medical University of Graz, Austria.

Objectives: We determined primary and secondary resistance rates of H. pylori in different regions of Austria and potential bacterial and host factors associated with resistance.

Methods: In a prospective multicentre study H. pylori was cultivated from biopsies and susceptibility testing was performed according to EUCAST. Resistance to clarithromycin and levofloxacin was determined by sequencing of the resistance-determining regions of 23S rRNA and gyrA genes. cagA, vacA and babA2 genotypes were determined.

Results: A total of 1266 patients were included. 178 isolates were cultured: 128 from patients without prior eradication therapy, 50 from patients after failed eradication. Primary resistance to clarithromycin, levofloxacin and metronidazole were 17.2%, 9.4% and 10.2%, respectively. Secondary resistance to clarithromycin, levofloxacin and metronidazole were 64%, 18% and 44%, respectively. Prior eradication was associated with a higher risk of clarithromycin as well as metronidazole resistance (OR=8.1; 95% CI 3.8-17.1 and OR 5.7; 95% CI 2.5-13, respectively).

Conclusion: Primary resistance to both clarithromycin and levofloxacin was markedly lower in Southern Austria than recently reported.
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http://dx.doi.org/10.1016/j.ijmm.2016.04.003DOI Listing
June 2016

Advancing Urinary Protein Biomarker Discovery by Data-Independent Acquisition on a Quadrupole-Orbitrap Mass Spectrometer.

J Proteome Res 2015 Nov 22;14(11):4752-62. Epub 2015 Oct 22.

Departments of Pathology, Boston Children's Hospital and Harvard Medical School , Boston, Massachusetts 02115, United States.

The promises of data-independent acquisition (DIA) strategies are a comprehensive and reproducible digital qualitative and quantitative record of the proteins present in a sample. We developed a fast and robust DIA method for comprehensive mapping of the urinary proteome that enables large scale urine proteomics studies. Compared to a data-dependent acquisition (DDA) experiments, our DIA assay doubled the number of identified peptides and proteins per sample at half the coefficients of variation observed for DDA data (DIA = ∼8%; DDA = ∼16%). We also tested different spectral libraries and their effects on overall protein and peptide identifications and their reproducibilities, which provided clear evidence that sample type-specific spectral libraries are preferred for reliable data analysis. To show applicability for biomarker discovery experiments, we analyzed a sample set of 87 urine samples from children seen in the emergency department with abdominal pain. The whole set was analyzed with high proteome coverage (∼1300 proteins/sample) in less than 4 days. The data set revealed excellent biomarker candidates for ovarian cyst and urinary tract infection. The improved throughput and quantitative performance of our optimized DIA workflow allow for the efficient simultaneous discovery and verification of biomarker candidates without the requirement for an early bias toward selected proteins.
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http://dx.doi.org/10.1021/acs.jproteome.5b00826DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4993212PMC
November 2015

Quantification of SAHA-Dependent Changes in Histone Modifications Using Data-Independent Acquisition Mass Spectrometry.

J Proteome Res 2015 Aug 13;14(8):3252-62. Epub 2015 Jul 13.

§BiognoSYS AG, Wagistrasse 25, CH-8952 Schlieren, Switzerland.

Histone post-translational modifications (PTMs) are important regulators of chromatin structure and gene expression. Quantitative analysis of histone PTMs by mass spectrometry remains extremely challenging due to the complex and combinatorial nature of histone PTMs. The most commonly used mass spectrometry-based method for high-throughput histone PTM analysis is data-dependent acquisition (DDA). However, stochastic precursor selection and dependence on MS1 ions for quantification impede comprehensive interrogation of histone PTM states using DDA methods. To overcome these limitations, we utilized a data-independent acquisition (DIA) workflow that provides superior run-to-run consistency and postacquisition flexibility in comparison to DDA methods. In addition, we developed a novel DIA-based methodology to quantify isobaric, co-eluting histone peptides that lack unique MS2 transitions. Our method enabled deconvolution and quantification of histone PTMs that are otherwise refractory to quantitation, including the heavily acetylated tail of histone H4. Using this workflow, we investigated the effects of the histone deacetylase inhibitor SAHA (suberoylanilide hydroxamic acid) on the global histone PTM state of human breast cancer MCF7 cells. A total of 62 unique histone PTMs were quantified, revealing novel SAHA-induced changes in acetylation and methylation of histones H3 and H4.
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http://dx.doi.org/10.1021/acs.jproteome.5b00245DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4564294PMC
August 2015

Extending the limits of quantitative proteome profiling with data-independent acquisition and application to acetaminophen-treated three-dimensional liver microtissues.

Mol Cell Proteomics 2015 May 27;14(5):1400-10. Epub 2015 Feb 27.

From the ‡Biognosys, Wagistrasse 25, CH-8952 Schlieren, Switzerland;

The data-independent acquisition (DIA) approach has recently been introduced as a novel mass spectrometric method that promises to combine the high content aspect of shotgun proteomics with the reproducibility and precision of selected reaction monitoring. Here, we evaluate, whether SWATH-MS type DIA effectively translates into a better protein profiling as compared with the established shotgun proteomics. We implemented a novel DIA method on the widely used Orbitrap platform and used retention-time-normalized (iRT) spectral libraries for targeted data extraction using Spectronaut. We call this combination hyper reaction monitoring (HRM). Using a controlled sample set, we show that HRM outperformed shotgun proteomics both in the number of consistently identified peptides across multiple measurements and quantification of differentially abundant proteins. The reproducibility of HRM in peptide detection was above 98%, resulting in quasi complete data sets compared with 49% of shotgun proteomics. Utilizing HRM, we profiled acetaminophen (APAP)(1)-treated three-dimensional human liver microtissues. An early onset of relevant proteome changes was revealed at subtoxic doses of APAP. Further, we detected and quantified for the first time human NAPQI-protein adducts that might be relevant for the toxicity of APAP. The adducts were identified on four mitochondrial oxidative stress related proteins (GATM, PARK7, PRDX6, and VDAC2) and two other proteins (ANXA2 and FTCD). Our findings imply that DIA should be the preferred method for quantitative protein profiling.
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http://dx.doi.org/10.1074/mcp.M114.044305DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4424408PMC
May 2015

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

Mol Cell Proteomics 2015 Mar 5;14(3):739-49. Epub 2015 Jan 5.

From the ‡Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, 8093 Zürich, Switzerland; ‡‡Faculty of Science, University of Zürich, Switzerland;

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.
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http://dx.doi.org/10.1074/mcp.M113.035550DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4349991PMC
March 2015
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