Article

Using Ion Mobility Data to Improve Peptide Identification: Intrinsic Amino Acid Size Parameters

Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States.
Journal of Proteome Research (Impact Factor: 5). 03/2011; 10(5):2318-29. DOI: 10.1021/pr1011312
Source: PubMed

ABSTRACT A new method for enhancing peptide ion identification in proteomics analyses using ion mobility data is presented. Ideally, direct comparisons of experimental drift times (t(D)) with a standard mobility database could be used to rank candidate peptide sequence assignments. Such a database would represent only a fraction of sequences in protein databases and significant difficulties associated with the verification of data for constituent peptide ions would exist. A method that employs intrinsic amino acid size parameters to obtain ion mobility predictions that can be used to rank candidate peptide ion assignments is proposed. Intrinsic amino acid size parameters have been determined for doubly charged peptide ions from an annotated yeast proteome. Predictions of ion mobilities using the intrinsic size parameters are more accurate than those obtained from a polynomial fit to t(D) versus molecular weight data. More than a 2-fold improvement in prediction accuracy has been observed for a group of arginine-terminated peptide ions 12 residues in length. The use of this predictive enhancement as a means to aid peptide ion identification is discussed, and a simple peptide ion scoring scheme is presented.

2 Followers
 · 
142 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: Data-independent acquisition (DIA) implemented in a method called MS(E) can be performed in a massively parallel, time-based schedule rather than by sampling masses sequentially in shotgun proteomics. In MS(E) alternating low and high energy spectra are collected across the full mass range. This approach has been very successful and stimulated the development of variants modeled after the MS(E) protocol, but over narrower mass ranges. The massively parallel MS(E) and other DIA methodologies have enabled effective label-free quantitation methods that have been applied to a wide variety of samples including affinity pulldowns and studies of cells, tissues, and clinical samples. Another complementary technology matches accurate mass and retention times of precursor ions across multiple chromatographic runs. This further enhances the impact of MS(E) in counteracting the stochastic nature of mass spectrometry as applied in proteomics. Otherwise significant amounts of data in typical large-scale protein profiling experiments are missing. A variety of software packages perform this function similar in concept to matching of accurate mass tags. Another enhancement of this method involves a variation of MS(E) coupled with traveling wave ion mobility spectrometry to provide separations of peptides based on cross-sectional area and shape in addition to mass/charge (m/z) ratio. Such a two-dimensional separation in the gas phase considerably increases protein coverage as well as typically a doubling of the number of proteins detected. These developments along with advances in ultrahigh pressure liquid chromatography have resulted in the evolution of a robust and versatile platform for label-free protein profiling.
    Advances in Experimental Medicine and Biology 01/2014; 806:79-91. DOI:10.1007/978-3-319-06068-2_4 · 2.01 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: 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.
    Expert Review of Proteomics 10/2014; 11(6):1-10. DOI:10.1586/14789450.2014.971114 · 3.54 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Ion mobility spectrometry in conjunction with liquid chromatography separations and mass spectrometry offers a range of new possibilities for analyzing complex biological samples. To fully utilize the information obtained from these three measurement dimensions, informatics tools based on the accurate mass and time tag methodology were modified to incorporate ion mobility spectrometry drift times for peptides observed in human serum. In this work a reference human serum database was created for 12,139 peptides and populated with the monoisotopic mass, liquid chromatography normalized elution time, and ion mobility spectrometry drift time(s) for each. We demonstrate that the use of three dimensions for peak matching during the peptide identification process resulted in an increased numbers of identifications and a lower false discovery rate relative to only using the mass and normalized elution time dimensions.
    International Journal of Mass Spectrometry 11/2013; 354-355:312-317. DOI:10.1016/j.ijms.2013.06.028 · 2.23 Impact Factor

Full-text (2 Sources)

Download
47 Downloads
Available from
Jun 1, 2014