Data-Independent Acquisition (SWATH) Mass Spectrometry Analysis of Protein Content in Primary Neuronal Cultures

Sequential Window Acquisition of all THeoretical fragment-ion (SWATH) is a recently developed discovery proteomics technique based on Data-Independent Acquisition (DIA) mass spectrometry. In this approach, MS/MS is performed simultaneously on all peptides contained in a predefined wide-open mass window of up to 25 Da. The mass window is sequentially stepped through over the entire mass range, usually between 400 and 1200 Da that covers most peptides. As quantitative MS/MS information is generated for all observable peptides in the sample, the missing data and variability between replicates are substantially reduced when compared to a Data-Dependent Acquisition approach. To identify each peptide from the high complexity of the MS/MS spectra generated from multiple peptides, a comprehensive reference spectral library derived prior from a similar sample by Data-Dependent Acquisition, rather than a conventional genome-wide database, should be used. In this chapter, we describe a general protocol that benefits from the advances of SWATH-MS for the quantification of the primary neuronal culture proteome.

[1]  M. Mann,et al.  MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification , 2008, Nature Biotechnology.

[2]  Alexey I Nesvizhskii,et al.  Untargeted, spectral library‐free analysis of data‐independent acquisition proteomics data generated using Orbitrap mass spectrometers , 2016, Proteomics.

[3]  Jian Wang,et al.  MSPLIT-DIA: sensitive peptide identification for data-independent acquisition , 2015, Nature Methods.

[4]  Oliver M. Bernhardt,et al.  Extending the Limits of Quantitative Proteome Profiling with Data-Independent Acquisition and Application to Acetaminophen-Treated Three-Dimensional Liver Microtissues* , 2015, Molecular & Cellular Proteomics.

[5]  Daniela C Dieterich,et al.  Proteomics of the Synapse – A Quantitative Approach to Neuronal Plasticity* , 2015, Molecular & Cellular Proteomics.

[6]  Michael J MacCoss,et al.  Specter: linear deconvolution for targeted analysis of data-independent acquisition mass spectrometry proteomics , 2018, Nature Methods.

[7]  U. K. Laemmli,et al.  Cleavage of Structural Proteins during the Assembly of the Head of Bacteriophage T4 , 1970, Nature.

[8]  Robert A Edwards,et al.  Visible fluorescent detection of proteins in polyacrylamide gels without staining. , 2004, Analytical biochemistry.

[9]  John Chilton,et al.  Using iRT, a normalized retention time for more targeted measurement of peptides , 2012, Proteomics.

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

[11]  A. Smit,et al.  Dynamics of the mouse brain cortical synaptic proteome during postnatal brain development , 2016, Scientific Reports.

[12]  Yuanyue Li,et al.  Group-DIA: analyzing multiple data-independent acquisition mass spectrometry data files , 2015, Nature Methods.

[13]  Roland Bruderer,et al.  High‐precision iRT prediction in the targeted analysis of data‐independent acquisition and its impact on identification and quantitation , 2016, Proteomics.

[14]  In situ alkylation with acrylamide for identification of cysteinyl residues in proteins during one‐ and two‐dimensional sodium dodecyl sulphate‐polyacrylamide gel electrophoresis , 2002 .

[15]  Alexey I Nesvizhskii,et al.  New targeted approaches for the quantification of data‐independent acquisition mass spectrometry , 2017, Proteomics.

[16]  Ka Wan Li,et al.  Comparative Analyses of Data Independent Acquisition Mass Spectrometric Approaches: DIA, WiSIM‐DIA, and Untargeted DIA , 2018, Proteomics.

[17]  N. Chandra,et al.  A genome-wide structure-based survey of nucleotide binding proteins in M. tuberculosis , 2017, Scientific Reports.

[18]  A. Smit,et al.  Correlation profiling of brain sub-cellular proteomes reveals co-assembly of synaptic proteins and subcellular distribution , 2017, Scientific Reports.

[19]  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.

[20]  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.

[21]  L. Burton,et al.  SWATH‐ID: An instrument method which combines identification and quantification in a single analysis , 2017, Proteomics.