Mass Spectrometry-Based Proteomics Combined with Bioinformatic Tools for Bacterial Classification

Abstract

Timely classification and identification of bacteria is of vital importance in many areas of public health. We present a mass spectrometry (MS)-based proteomics approach for bacterial classification. In this method, a bacterial proteome database is derived from all potential protein coding open reading frames (ORFs) found in 170 fully sequenced bacterial genomes. Amino acid sequences of tryptic peptides obtained by LC-ESI MS/MS analysis of the digest of bacterial cell extracts are assigned to individual bacterial proteomes in the database. Phylogenetic profiles of these peptides are used to create a matrix of sequence-to-bacterium assignments. These matrixes, viewed as specific assignment bitmaps, are analyzed using statistical tools to reveal the relatedness between a test bacterial sample and the microorganism database. It is shown that, if a sufficient amount of sequence information is obtained from the MS/MS experiments, a bacterial sample can be classified to a strain level by using this proteomics method, leading to its positive identification.

Application of proteomics to ecology and population biology

“…As the field grapples with, and overcomes, these technical issues, application of proteomics to the analysis of protein composition of related taxa should become more common place. For example, application of bioinformatic and molecular evolutionary analysis of MS data using known amino acid substitution patterns can now identify putative homologous proteins from organisms lacking a sequenced genome (Liska and Shevchenko, 2003;Dworzanski et al, 2006).…”

Tandem mass spectrometry for the detection of plant pathogenic fungi and the effects of database composition on protein inferences

“…As was previously described, it is current practice to match an MS/MS spectrum to a peptide sequence and scan the descriptive information linked to the associated protein record to determine the organism of origin for the protein record [6,[13][14][15]. Typically, this information can be used to imply which organisms' proteins are present in a sample.…”

“…Because gels are labor intensive and not suited for quick diagnostic turnaround, we have turned to a more amenable high-throughput protein separation method where we first digest proteins and then separate their peptides by LC before analyzing them by MS/MS (LC-MS/MS [7][8][9][10][11][12]). This high throughput workflow has been used by other groups to identify characteristic peptides from bacterial pathogens [13][14][15]. Unlike the 2-D PAGE method where select proteins are analyzed, LC-MS/MS allows for the screening of a complex number of pathogen, host and background proteins in a sample in a single assay.…”

“…The resulting MS/MS spectra are interpreted with database-search software that compares experimentally acquired spectra to a database of protein sequences [16]. Matches of spectra to peptides from pathogen proteins has been interpreted to imply the presence of the pathogen in a sample [6,[13][14][15].…”

Proteomic characterization and bio-informatic analysis of differentially expressed E. coli Nissle 1917 proteins with response to cocoti wine stress

“…Many studies have reported on the bacterial proteomic changes in response to various stress conditions, but this work is a comprehensive proteomic approach for better understanding of the expressed proteins structure and mechanism in stress conditions of E. coli Nissle 1917 treated with cocoti wine (Soares et al 2013). Proteomics are widely used for characterization and identification of proteins with MS-based techniques (MALDI-TOF/LC-MS) and bio-informatic tools (Krishnamurthy et al 2000;Dworzanski et al 2006). Proteomic studies can focus on looking deeply into the new modifications of proteins; it gives complete information about stress response (Agrawal et al 2005).…”