Biomedical applications of ion mobility-enhanced data-independent acquisition-based label-free quantitative proteomics

Mass spectrometry-based proteomics greatly benefited from recent improvements in instrument performance and the development of bioinformatics solutions facilitating the high-throughput quantification of proteins in complex biological samples. In addition to quantification approaches using stable isotope labeling, label-free quantification has emerged as the method of choice for many laboratories. Over the last years, data-independent acquisition approaches have gained increasing popularity. The integration of ion mobility separation into commercial instruments enabled researchers to achieve deep proteome coverage from limiting sample amounts. Additionally, ion mobility provides a new dimension of separation for the quantitative assessment of complex proteomes, facilitating precise label-free quantification even of highly complex samples. The present work provides a thorough overview of the combination of ion mobility and data-independent acquisition-based label-free quantification LC-MS and its applications in biomedical research.

[1]  Ivana V. Yang,et al.  Proteomic analysis of human bronchoalveolar lavage fluid after subsgemental exposure. , 2013, Journal of proteome research.

[2]  D. Cifu,et al.  Post-acute brain injury urinary signature: a new resource for molecular diagnostics. , 2014, Journal of neurotrauma.

[3]  M. Selbach,et al.  Global quantification of mammalian gene expression control , 2011, Nature.

[4]  S. Bahn,et al.  Multidimensional protein fractionation of blood proteins coupled to data-independent nanoLC-MS/MS analysis. , 2010, Journal of proteomics.

[5]  Tao Xu,et al.  Bioinformatics Applications Note Sequence Analysis Xdia: Improving on the Label-free Data-independent Analysis , 2022 .

[6]  Konstantinos Thalassinos,et al.  A comparison of labeling and label-free mass spectrometry-based proteomics approaches. , 2009, Journal of proteome research.

[7]  S. Tenzer,et al.  Oligodendrocytes secrete exosomes containing major myelin and stress‐protective proteins: Trophic support for axons? , 2007, Proteomics. Clinical applications.

[8]  Stefan Tenzer,et al.  Drift time-specific collision energies enable deep-coverage data-independent acquisition proteomics , 2013, Nature Methods.

[9]  Fredrik Levander,et al.  Data processing methods and quality control strategies for label-free LC-MS protein quantification. , 2014, Biochimica et biophysica acta.

[10]  S. Valentine,et al.  Developing liquid chromatography ion mobility mass spectometry techniques , 2005, Expert review of proteomics.

[11]  R. Aebersold,et al.  Mass spectrometry-based proteomics , 2003, Nature.

[12]  B. Devreese,et al.  Protein Markers for Insulin-Producing Beta Cells with Higher Glucose Sensitivity , 2010, PloS one.

[13]  Paul C Guest,et al.  Analysis of the human pituitary proteome by data independent label‐free liquid chromatography tandem mass spectrometry , 2011, Proteomics.

[14]  M. Baek,et al.  Identification of differentially expressed proteins by treatment with PUGNAc in 3T3‐L1 adipocytes through analysis of ATP‐binding proteome , 2013, Proteomics.

[15]  R. Beynon,et al.  Asymmetric Proteome Equalization of the Skeletal Muscle Proteome Using a Combinatorial Hexapeptide Library , 2011, PloS one.

[16]  Matthew E. Welsch,et al.  Regulation of Ferroptotic Cancer Cell Death by GPX4 , 2014, Cell.

[17]  Christopher G. Knight,et al.  Absolute Quantification of the Glycolytic Pathway in Yeast: , 2011, Molecular & Cellular Proteomics.

[18]  Gary D Bader,et al.  A draft map of the human proteome , 2014, Nature.

[19]  Joseph E. Lucas,et al.  A flexible statistical model for alignment of label-free proteomics data – incorporating ion mobility and product ion information , 2013, BMC Bioinformatics.

[20]  J. Reilly,et al.  Extracted Fragment Ion Mobility Distributions: A New Method for Complex Mixture Analysis. , 2012, International journal of mass spectrometry.

[21]  S. Ozanne,et al.  Analysis of the rat hypothalamus proteome by data‐independent label‐free LC‐MS/MS , 2012, Proteomics.

[22]  Mathias Wilhelm,et al.  Ion Mobility Tandem Mass Spectrometry Enhances Performance of Bottom-up Proteomics , 2014, Molecular & Cellular Proteomics.

[23]  Laurent Gatto,et al.  Improving qualitative and quantitative performance for MS(E)-based label-free proteomics. , 2013, Journal of proteome research.

[24]  L. Gatto,et al.  Effects of traveling wave ion mobility separation on data independent acquisition in proteomics studies. , 2013, Journal of proteome research.

[25]  D. Goodlett,et al.  Multiplexed and data-independent tandem mass spectrometry for global proteome profiling. , 2014, Mass spectrometry reviews.

[26]  P. Limbach,et al.  Multiple Enzymatic Digestions and Ion Mobility Separation Improve Quantification of Bacterial Ribosomal Proteins by Data Independent Acquisition Liquid Chromatography−Mass Spectrometry , 2014, Analytical chemistry.

[27]  Chris Hughes,et al.  Using ion mobility data to improve peptide identification: intrinsic amino acid size parameters. , 2011, Journal of proteome research.

[28]  S. Tenzer,et al.  Myelin Proteomics: Molecular Anatomy of an Insulating Sheath , 2009, Molecular Neurobiology.

[29]  G. Mazzucchelli,et al.  Isotope coded protein label quantification of serum proteins--comparison with the label-free LC-MS and validation using the MRM approach. , 2010, Talanta.

[30]  K. Gevaert,et al.  RIBAR and xRIBAR: Methods for reproducible relative MS/MS-based label-free protein quantification. , 2011, Journal of proteome research.

[31]  M. Mann,et al.  Proteomics on an Orbitrap Benchtop Mass Spectrometer Using All-ion Fragmentation , 2010, Molecular & Cellular Proteomics.

[32]  Richard D. Smith,et al.  Toward plasma proteome profiling with ion mobility-mass spectrometry. , 2006, Journal of proteome research.

[33]  Jarrett D. Egertson,et al.  Multiplexed MS/MS for Improved Data Independent Acquisition , 2013, Nature Methods.

[34]  S. Tenzer,et al.  Systematic approaches to central nervous system myelin , 2012, Cellular and Molecular Life Sciences.

[35]  K. Valgepea,et al.  Comparison and applications of label-free absolute proteome quantification methods on Escherichia coli. , 2012, Journal of proteomics.

[36]  Phillip C. Wright,et al.  An insight into iTRAQ: where do we stand now? , 2012, Analytical and Bioanalytical Chemistry.

[37]  F. Gozzo,et al.  Differential seminal plasma proteome according to semen retrieval in men with spinal cord injury. , 2013, Fertility and sterility.

[38]  B. Kuster,et al.  Proteomics: a pragmatic perspective , 2010, Nature Biotechnology.

[39]  M. Gorenstein,et al.  Quantitative proteomic analysis by accurate mass retention time pairs. , 2005, Analytical chemistry.

[40]  Sabine Bahn,et al.  Quantification of proteins using data‐independent analysis (MSE) in simple andcomplex samples: A systematic evaluation , 2011, Proteomics.

[41]  Stefan Tenzer,et al.  Rapid formation of plasma protein corona critically affects nanoparticle pathophysiology. , 2013, Nature nanotechnology.

[42]  M. Mann,et al.  More than 100,000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data-dependent LC-MS/MS. , 2011, Journal of proteome research.

[43]  Melvin A. Park,et al.  High resolution trapped ion mobility spectrometery of peptides. , 2014, Analytical chemistry.

[44]  Wei Zhang,et al.  LFQuant: A label‐free fast quantitative analysis tool for high‐resolution LC‐MS/MS proteomics data , 2012, Proteomics.

[45]  Knut Reinert,et al.  Tools for Label-free Peptide Quantification , 2012, Molecular & Cellular Proteomics.

[46]  M Arthur Moseley,et al.  Longitudinal study of differential protein expression in an Alzheimer's mouse model lacking inducible nitric oxide synthase. , 2013, Journal of proteome research.

[47]  Ronald J Moore,et al.  An LC-IMS-MS platform providing increased dynamic range for high-throughput proteomic studies. , 2010, Journal of proteome research.

[48]  Assumpto Iaconelli,et al.  Secretome of the preimplantation human embryo by bottom-up label-free proteomics , 2011, Analytical and bioanalytical chemistry.

[49]  A. Ottens,et al.  High‐capacity peptide‐centric platform to decode the proteomic response to brain injury , 2012, Electrophoresis.

[50]  Johannes P C Vissers,et al.  Using ion purity scores for enhancing quantitative accuracy and precision in complex proteomics samples , 2012, Analytical and Bioanalytical Chemistry.

[51]  C. Turck,et al.  To label or not to label: Applications of quantitative proteomics in neuroscience research , 2012, Proteomics.

[52]  Ronald J. Moore,et al.  Sources of technical variability in quantitative LC-MS proteomics: human brain tissue sample analysis. , 2013, Journal of proteome research.

[53]  Shanshan Liu,et al.  Exploring skyline for both MSE‐based label‐free proteomics and HRMS quantitation of small molecules , 2014, Proteomics.

[54]  Kai Pong Law,et al.  Recent advances in mass spectrometry: data independent analysis and hyper reaction monitoring , 2013, Expert review of proteomics.

[55]  Shelly C. Lu,et al.  Quantitative proteomic analysis of hepatocyte-secreted extracellular vesicles reveals candidate markers for liver toxicity. , 2014, Journal of proteomics.

[56]  Xudong Yao,et al.  Tandem parallel fragmentation of peptides for mass spectrometry. , 2006, Analytical chemistry.

[57]  S. Tenzer,et al.  A critical role for the cholesterol‐associated proteolipids PLP and M6B in myelination of the central nervous system , 2013, Glia.

[58]  A. Aguzzi,et al.  Quantitative and Integrative Proteome Analysis of Peripheral Nerve Myelin Identifies Novel Myelin Proteins and Candidate Neuropathy Loci , 2011, The Journal of Neuroscience.

[59]  Deborah Moran,et al.  Data-independent acquisition (MSE) with ion mobility provides a systematic method for analysis of a bacteriophage structural proteome. , 2014, Journal of virological methods.

[60]  Richard Willingale,et al.  Qualitative and Quantitative Characterization of Plasma Proteins When Incorporating Traveling Wave Ion Mobility into a Liquid Chromatography–Mass Spectrometry Workflow for Biomarker Discovery: Use of Product Ion Quantitation As an Alternative Data Analysis Tool for Label Free Quantitation , 2014, Analytical chemistry.

[61]  C. Hung,et al.  Label-free protein profiling of adipose-derived human stem cells under hyperosmotic treatment. , 2011, Journal of proteome research.

[62]  M. Gorenstein,et al.  Simultaneous Qualitative and Quantitative Analysis of theEscherichia coli Proteome , 2006, Molecular & Cellular Proteomics.

[63]  Richard D. Smith,et al.  Mass Spectrometry‐Based Proteomics: Existing Capabilities and Future Directions , 2012 .

[64]  Marco Y. Hein,et al.  Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * , 2014, Molecular & Cellular Proteomics.

[65]  D. Goodlett,et al.  Faster, quantitative, and accurate precursor acquisition independent from ion count. , 2011, Analytical chemistry.

[66]  Label-free mass spectrometry proteome quantification of human embryonic kidney cells following 24 hours of sialic acid overproduction , 2013, Proteome Science.

[67]  Ludovic C. Gillet,et al.  Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis* , 2012, Molecular & Cellular Proteomics.

[68]  John D. Venable,et al.  Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra , 2004, Nature Methods.

[69]  D. Goodlett,et al.  Shotgun collision‐induced dissociation of peptides using a time of flight mass analyzer , 2003, Proteomics.

[70]  M. Webster,et al.  Identification of proteomic signatures associated with depression and psychotic depression in post-mortem brains from major depression patients , 2012, Translational Psychiatry.

[71]  S. Tenzer,et al.  Mast Cell–deficient KitW-sh “Sash” Mutant Mice Display Aberrant Myelopoiesis Leading to the Accumulation of Splenocytes That Act as Myeloid-Derived Suppressor Cells , 2013, The Journal of Immunology.

[72]  E. Tremoli,et al.  Proteomic analysis of endothelial cell secretome: a means of studying the pleiotropic effects of Hmg-CoA reductase inhibitors. , 2013, Journal of proteomics.

[73]  Mehdi Mirzaei,et al.  Less label, more free: Approaches in label‐free quantitative mass spectrometry , 2011, Proteomics.

[74]  D. Schieltz,et al.  A historical and proteomic analysis of botulinum neurotoxin type/G , 2011, BMC Microbiology.

[75]  Donald J L Jones,et al.  Assessment of reproducibility in depletion and enrichment workflows for plasma proteomics using label‐free quantitative data‐independent LC‐MS , 2014, Proteomics.

[76]  M. Gorenstein,et al.  The detection, correlation, and comparison of peptide precursor and product ions from data independent LC‐MS with data dependant LC‐MS/MS , 2009, Proteomics.

[77]  Brandon T Ruotolo,et al.  Ion mobility–mass spectrometry for structural proteomics , 2012, Expert review of proteomics.

[78]  Brett Larsen,et al.  Label-free quantitative proteomics trends for protein-protein interactions. , 2013, Journal of proteomics.

[79]  B. Kuster,et al.  Mass-spectrometry-based draft of the human proteome , 2014, Nature.

[80]  J. Yates,et al.  A model for random sampling and estimation of relative protein abundance in shotgun proteomics. , 2004, Analytical chemistry.

[81]  Chad R. Weisbrod,et al.  Accurate peptide fragment mass analysis: multiplexed peptide identification and quantification. , 2012, Journal of proteome research.

[82]  Gerard A. Ateshian,et al.  Growth Factor Priming Differentially Modulates Components of the Extracellular Matrix Proteome in Chondrocytes and Synovium-Derived Stem Cells , 2014, PloS one.

[83]  Samuel I. Miller,et al.  Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. , 2009, Analytical chemistry.

[84]  A. Fagan,et al.  Quantitative Label-Free Proteomics for Discovery of Biomarkers in Cerebrospinal Fluid: Assessment of Technical and Inter-Individual Variation , 2013, Alzheimer's & Dementia.

[85]  S. Tenzer,et al.  Proteome-wide characterization of the RNA-binding protein RALY-interactome using the in vivo-biotinylation-pulldown-quant (iBioPQ) approach. , 2013, Journal of proteome research.

[86]  S. Tenzer,et al.  Proteomic Analyses of Human Cytomegalovirus Strain AD169 Derivatives Reveal Highly Conserved Patterns of Viral and Cellular Proteins in Infected Fibroblasts , 2014, Viruses.

[87]  Laura G. Dubois,et al.  Proteomic analysis of an unculturable bacterial endosymbiont (Blochmannia) reveals high abundance of chaperonins and biosynthetic enzymes. , 2013, Journal of proteome research.

[88]  M. Gorenstein,et al.  Absolute Quantification of Proteins by LCMSE , 2006, Molecular & Cellular Proteomics.

[89]  V. Fromion,et al.  Comprehensive Absolute Quantification of the Cytosolic Proteome of Bacillus subtilis by Data Independent, Parallel Fragmentation in Liquid Chromatography/Mass Spectrometry (LC/MSE)* , 2014, Molecular & Cellular Proteomics.

[90]  Ben C. Collins,et al.  OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data , 2014, Nature Biotechnology.

[91]  Helmut Neumann,et al.  Caspase-8 regulates TNF-alpha induced epithelial necroptosis and terminal ileitis , 2011, Nature.

[92]  David R Goodlett,et al.  Proteomic classification of acute leukemias by alignment-based quantitation of LC-MS/MS data sets. , 2012, Journal of proteome research.

[93]  T. Blake,et al.  Proteomic Analysis and Label-Free Quantification of the Large Clostridium difficile Toxins , 2013, International journal of proteomics.

[94]  S. Baginsky,et al.  Protein identification and quantification by data-independent acquisition and multi-parallel collision-induced dissociation mass spectrometry (MS(E)) in the chloroplast stroma proteome. , 2014, Journal of proteomics.