title: Multidimensional Separation Using HILIC and SCX Pre-fractionation for RP LC-MS/MS Platform with Automated Exclusion List-based MS Data Acquisition with Increased Protein Quantification.
abstract: Liquid chromatography-mass spectrometry (LC-MS) based proteomics is one of the most widely used analytical platforms for global protein discovery and quantification. One of the challenges is the difficulty of identifying low abundance biomarker proteins from limited biological samples. Extensive fractionation could expand proteomics dynamic range, however, at the cost of high sample and time consumption. Extensive fractionation would increase the sample need and the labeling cost. Also quantitative proteomics depending on high resolution MS have the limitation of spectral acquisition speed. Those practical problems hinder the in-depth quantitative proteomics analysis such as tandem mass tag (TMT) experiments. We found the joint use of hydrophilic interaction liquid chromatography (HILIC) and strong cation exchange Chromatography (SCX) prefractionation at medium level could improve MS/MS efficiency, increase proteome coverage, shorten analysis time and save valuable samples. In addition, we scripted a program, Exclusion List Convertor (ELC), which automates and streamlines data acquisition workflow using the precursor ion exclusion (PIE) method. PIE reduces redundancy of high abundance MS/MS analyses by running replicates of the sample. The precursor ions detected in the initial run(s) are excluded for MS/MS in the subsequent run. We compared PIE methods with standard data dependent acquisition (DDA) methods running replicates without PIE for their effectiveness in quantifying TMT-tagged peptides and proteins in mouse tears. We quantified a total of 845 proteins and 1401 peptides using the PIE workflow, while the DDA method only resulted in 347 proteins and 731 peptides. This represents a 144% increase of protein identifications as a result of PIE analysis.
authors.affiliation: USC Research Center for Liver Diseases, Keck School of Medicine, University of Southern California, Los Angeles, California, USA; Norris Comprehensive Cancer Center, Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
authors.forename: Yu
authors.initials: Y
authors.lastname: Zhou
authors.affiliation: Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, 1985 Zonal Ave, Los Angeles, California, USA.
authors.forename: Zhen
authors.initials: Z
authors.lastname: Meng
authors.affiliation: Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, 1985 Zonal Ave, Los Angeles, California, USA.
authors.forename: Maria
authors.initials: M
authors.lastname: Edman-Woolcott
authors.affiliation: Department of Ophthalmology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA; Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, 1985 Zonal Ave, Los Angeles, California, USA.
authors.forename: Sarah F
authors.initials: SF
authors.lastname: Hamm-Alvarez
authors.affiliation: USC Research Center for Liver Diseases, Keck School of Medicine, University of Southern California, Los Angeles, California, USA; Norris Comprehensive Cancer Center, Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
authors.forename: Ebrahim
authors.initials: E
authors.lastname: Zandi
keywords: Biomarkers; Exclusion list-based MS data acquisition; HILIC; Proteomics; SCX; TMT quantification