Peptides mass spec analysis

Figure 16.6 The solid phase ICAT reagent provides a thiol-reactive iodoacetyl group to capture cysteine peptides, a spacer containing stable isotopic labels, and a photo-cleavable group that can release the captured peptides for mass spec analysis. The VICAT mass tag is a solution phase labeling agent that also has a photo-cleavable site to release isolated peptides from a (strept)avidin affinity resin. This compound adds a fluorescent group to better detect labeled peptides as they are being isolated from a sample.

Mass spec analysis of the peptide fragments formed by this process yields pairs of MS peaks differing only by the mass change caused by the substitution of deuterium atoms for hydrogen atoms in half of the crosslinks. Thus, searching for MS peaks in the data that differ by the number of deuterium substitutions immediately will identify peptides from the interacting proteins that have been captured by the crosslinking process. 

The use of PIR compounds to study protein interactions is a significant advance over the use of standard homobifunctional crosslinkers. The unique design of the PIR reagent facilitates deconvolution of putative protein interaction complexes through a simplified mass spec analysis. The software can ignore all irrelevant peak data and just focus analysis on the two labeled peptide peaks, which accompany the reporter signal of appropriate mass. This greatly simplifies the bioinformatics of data analysis and provides definitive conformation of protein-protein crosslinks. 

Desai,M.J., Armstrong, D.W. (2004). Analysis of native amino acid and peptide enantiomers by high-performance liquid chromatography/atmospheric pressure chemical ionization mass spectrometry. J. Mass. Spec. 39, 177-187. 

Zabet-Moghaddam, M. et al.. Matrix-assisted laser desorption/ionization mass spectrometry for the characterization of ionic liquids and the analysis of amino acids, peptides and proteins in ionic liquids. /. Mass Spec., 39,1494, 2004. 

Bioinformatics The use of information technology to analyze data obtained from proteomic analysis. An example is the use of databases such as SWISSPROT to identify proteins from sequence information determined by the mass spec-trometric analysis of peptides. See Wang, J.T.L., Data Mining in Bioinformatics, Springer, London, 2005 Lesk, A.M., Introduction to Bioinformatics, Oxford University Press, New York, 2005 Englbrecht, C.C. and Facius, A., Bioinformatics challenges in proteomics. Comb. Chem. High... 

Hanisch, R, et al. (2001). Glycoprotein Identification and Localization of o-glycosilation Sites by Mass Spec-trometric Analysis of Deglycosilated/alkylaminylated Peptide Fragments, Anal. Biochem. 290 47-59. 

The advent of electrospray ionization certainly opened many new application areas for mass spec-trometric analysis. This is based on the ability to provide extreme soft liquid-based ionization. Perhaps the most important application area is the analysis of peptides and proteins. The possibility to perform rapid molecular-weight determination of proteins up to 200 kDa stimulated the commercial availability of MS instrumentation featuring atmospheric-pressure ion sources, equipped with electrospray ionization. Other application areas benefited from these developments. LC-MS has become an important analytical tool in many areas of drug development within the pharmaceutical industry, in the study of natural products in plants, in food and environmental analysis. It is about to enter the clinical application area for therapeutic drug monitoring, systematic toxicological analysis, and monitoring of inherited metabolic diseases. 

Bottom-up proteomics methods still need refinement of protocols, and improvements in the standardization and availability of bioinformatics tools for comprehensive data analysis on a routine basis. Although recent innovations in mass spec-trometric instramentation have aeeelerated the speed and sensitivity of proteome analysis (Hebert et al. 2014), further improvements can be obtained by emphasizing the optimization, simplification, and automation of sample preparation, for example, through single-tube proteomics approaches integrating all steps from cell lysis to peptide fractionation (Hughes et al. 2014 Fan et al. 2014), peptide separation techniques, and bioinformatics tools for fast, automated data interpretation for strain-level identification of cultivable bacteria and comprehensive characterization of each isolated microbial strain in the near future. 

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