Genome-based peptide fingerprint scanning

Abstract

We have implemented a method that identifies the genomic origins of sample proteins by scanning their peptide-mass fingerprint against the theoretical translation and proteolytic digest of an entire genome. Unlike previously reported techniques, this method requires no predefined ORF or protein annotations. Fixedsize windows along the genome sequence are scored by an equation accounting for the number of matching peptides, the number of missed enzymatic cleavages in each peptide, the number of in-frame stop codons within a window, the adjacency between peptides, and duplicate peptide matches. Statistical significance of matching regions is assessed by comparing their scores to scores from windows matching randomly generated mass data. Tests with samples from Saccharomyces cerevisiae mitochondria and Escherichia coli have demonstrated the ability to produce statistically significant identifications, agreeing with two commonly used programs, PEPTIDENT and MASCOT, in 86% of samples analyzed. This genome fingerprint scanning method has the potential to aid in genome annotation, identify proteins for which annotation is incorrect or missing, and handle cases where sequencing errors have caused framing mistakes in the databases. It might also aid in the identification of proteins in which recoding events such as frameshifting or stop-codon read-through have occurred, elucidating alternative translation mechanisms. The prototype is implemented as a client͞server pair, allowing the distribution, among a set of cluster nodes, of a single or multiple genomes for concurrent analysis.

HybGFS: a hybrid method for genome-fingerprint scanning

“…For example when Giddings et al [12] who used the GFS technique searched experimental peptide masses obtained from Saccharomyces cerevisiae and E. coli against theoretical peptide masses, they were able to identify 17 of the 22 samples tested (77.3%). Taking an alternative approach, Arthur and Wilkins [13] theoretically generated virtual proteins from a genome cleaved into equal-sized fragments, performed translation into all 6 open reading frames (ORFs), and compared the results with experimental data from Mycobacterium tuberculosis .…”

“…Recently, novel protein-identification methods that are independent of predefined protein databases have been reported [12,13]. In genome fingerprint scanning (GFS), the peptide data are mapped directly onto raw genomic sequences by scanning the PMF data against theoretical peptide masses generated computationally from entire genomes [12].…”

“…In genome fingerprint scanning (GFS), the peptide data are mapped directly onto raw genomic sequences by scanning the PMF data against theoretical peptide masses generated computationally from entire genomes [12]. This approach can identify the genomic loci and amino-acid sequences of proteins.…”

Using entropy of drug and protein graphs to predict FDA drug-target network: Theoretic-experimental study of MAO inhibitors and hemoglobin peptides from Fasciola hepatica

“…Once we obtained the data from MALDI-TOF MS analysis of the query band, the most relevant MS signals were introduced into the MASCOT search engine [91,92]. We obtained 20 hits (template proteins) for this protein with MASCOT scores (M s ) higher than 81 (p < 0.05), the threshold value for significant match, see Table 7.…”

Expressed Peptide Tags: An Additional Layer of Data for Genome Annotation

“…17,[21][22][23][24][25][26][27][28] Arthur and Wilkins searched peptide mass fingerprints of 20 2D-gel spots from the extracellular matrix of Mycobacterium tuberculosis against a sixframe translation of the M. tuberculosis genome, mapped the peptides back to the genome, and identified regions with high concentration of peptide hits as coding regions. 22 They also demonstrated this strategy in limited application for a single human chromosome.…”