Whole-Cell Protein Identification Using the Concept of Unique Peptides

Abstract

A concept of unique peptides (CUP) was proposed and implemented to identify whole-cell proteins from tandem mass spectrometry (MS/MS) ion spectra. A unique peptide is defined as a peptide, irrespective of its length, that exists only in one protein of a proteome of interest, despite the fact that this peptide may appear more than once in the same protein. Integrating CUP, a two-step whole-cell protein identification strategy was developed to further increase the confidence of identified proteins. A dataset containing 40,243 MS/MS ion spectra of Saccharomyces cerevisiae and protein identification tools including Mascot and SEQUEST were used to illustrate the proposed concept and strategy. Without implementing CUP, the proteins identified by SEQUEST are 2.26 fold of those identified by Mascot. When CUP was applied, the proteins bearing unique peptides identified by SEQUEST are 3.89 fold of those identified by Mascot. By cross-comparing two sets of identified proteins, only 89 common proteins derived from CUP were found. The key discrepancy between identified proteins was resulted from the filtering criteria employed by each protein identification tool. According to the origin of peptides classified by CUP and the commonality of proteins recognized by protein identification tools, all identified proteins were cross-compared, resulting in four groups of proteins possessing different levels of assigned confidence.

Velvet domain protein VosA represses the zinc cluster transcription factor SclB regulatory network for Aspergillus nidulans asexual development, oxidative stress response and secondary metabolism

“…Three unique peptides [ 152 ] and three MS/MS counts were demanded for positive protein identification. Furthermore, only proteins identified from at least two out of three biological repetitions were considered further.…”

“… Proteins were identified in at least two out of three biological replicates with a threshold of 3 ≥ MS/MS counts and 3 ≥ unique peptides [ 152 ], and sorted according to functional groups. Proteins identified solely in vegetative samples are highlighted in blue, proteins identified solely in developmental samples are given in green, proteins identified in vegetative and developmental samples are given in orange.…”

The proteomic profiling of calenduloside E targets in HUVEC: design, synthesis and application of biotinylated probe BCEA

“…10,11 A unique peptide can act as a "protein tag" in protein identication. 33 Only proteins identied with at least one unique peptide were considered statistically reliable hits, which resulted in a list of 744 proteins. To shrink the numbers of lower possibility of the potential targets, we then got rid of the protein with the score of zero.…”

Cysteine-Selective Peptide Identification: Selenium-Based Chromophore for Selective S–Se Bond Cleavage with 266 nm Ultraviolet Photodissociation

“…19 Strategies to resolve these issues have employed database filtering prior to the search to incorporate only unique peptides. [20][21][22] This workaround has shown to lower statistical q-values (not to be confused with ion trap Mathieu stability) by reducing the search space, thus increasing peptide confidence. [22][23][24][25] Building selectivity into a proteomic work-flow to allow meaningful database filtering to include only those peptides that contain a more specific type of amino acid composition have shown similar types of improvement.…”

“…[20][21][22] This workaround has shown to lower statistical q-values (not to be confused with ion trap Mathieu stability) by reducing the search space, thus increasing peptide confidence. [22][23][24][25] Building selectivity into a proteomic work-flow to allow meaningful database filtering to include only those peptides that contain a more specific type of amino acid composition have shown similar types of improvement. 25,26 Another rationale for building selectivity into bottom-up workflows is to allow enhanced sampling for peptides of interest.…”