An Assessment of Software Solutions for the Analysis of Mass Spectrometry Based Quantitative Proteomics Data

Abstract

Over the past decade, a series of experimental strategies for mass spectrometry based quantitative proteomics and corresponding computational methodology for the processing of the resulting data have been generated. We provide here an overview of the main quantification principles and available software solutions for the analysis of data generated by liquid chromatography coupled to mass spectrometry (LC-MS). Three conceptually different methods to perform quantitative LC-MS experiments have been introduced. In the first, quantification is achieved by spectral counting, in the second via differential stable isotopic labeling, and in the third by using the ion current in label-free LC-MS measurements. We discuss here advantages and challenges of each quantification approach and assess available software solutions with respect to their instrument compatibility and processing functionality. This review therefore serves as a starting point for researchers to choose an appropriate software solution for quantitative proteomic experiments based on their experimental and analytical requirements.

Statistical Model to Analyze Quantitative Proteomics Data Obtained by 18O/16O Labeling and Linear Ion Trap Mass Spectrometry

“…The situation is not better with expression studies obtained using stable isotope labeling approaches. Although a great effort has been devoted to the development of bioinformatics tools for automated analysis of MS data and calculation of peptide ratios for each one of the several isotope labeling strategies currently available (21,22), existing analytical methods for the statistical determination of significant expression changes are scarce (for a review, see Ref. 22).…”

Proteomic analysis of post translational modifications in cyanobacteria

“…The iTRAQ/TMT labeling techniques have been used in cyanobacteria and proved to be efficient and reliable methods for quantitative proteomics [103][104][105][106]. However, this reporter-ion-based quantification is better suited for quantitative analysis of the protein expression profiles rather than for the quantification of PTM levels [107][108][109][110].…”

Neuropeptide alterations in the tree shrew hypothalamus during volatile anesthesia

“…Label-free peptide profiling was performed using SIEVE 1.3 (Service package 2, Thermo Scientific, San Jose, CA). SIEVE is a label-free differential analysis software that aligns and determines features across samples prepared from different conditions [20]. The following parameters were used in the peak alignment and frame generation: m/z min= 300, m/z max = 1500, frame time width = 6.0 min, frame m/z width = 0.02 Da, retention time start= 15 min, retention time stop= 85 min, peak intensity threshold= 10,000.…”