Dataset Information

E. coli source tracking - A peptide identification-free, genome sequence-independent shotgun proteomics workflow for strain-level bacterial differentiation

ABSTRACT: We report a novel, peptide identification-free shotgun proteomics workflow as a bacterial fingerprinting method. This method uses a similarity-clustering algorithm to segregate the mass spectra that are presumably derived from individual peptide speciess and merge them into discrete units of consensus spectra that comprise the proteomic fingerprints of the bacterial isolates being investigated. The novel method was compared to a traditional peptide identification-based shotgun proteomics workflow and a commonly used PCR-DNA fingerprinting technique for performance benchmarking in differentiating 73 isolates of E. coli by their animal sources (human, cow, dog, and pig). The fingerprints generated using by the novel method were richer in information, more discriminative in separating the E. coli isolates by animal sources, and more accurate in classifying query isolates to the correct animal sources . Our data suggest that, by taking a snapshot of the system-wide expression of bacterial cells and circumventing peptide identification, the novel method generated fingerprints that not only reflected the adaptation of E. coli to different animal hosts more precisely than PCR-DNA fingerprinting but also constituted a fuller representation of the bacterial cells' proteomes than traditional shotgun proteomics.

INSTRUMENT(S): LTQ

ORGANISM(S): Escherichia Coli

SUBMITTER: Wenguang Shao

LAB HEAD: Henry Lam

PROVIDER: PXD001646 | Pride | 2015-10-05

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

Items per page:

1 - 5 of 146

Publications

A peptide identification-free, genome sequence-independent shotgun proteomics workflow for strain-level bacterial differentiation.

Shao Wenguang W Zhang Min M Lam Henry H Lau Stanley C K SC

Scientific reports 20150923

Shotgun proteomics is an emerging tool for bacterial identification and differentiation. However, the identification of the mass spectra of peptides to genome-derived peptide sequences remains a key issue that limits the use of shotgun proteomics to bacteria with genome sequences available. In this proof-of-concept study, we report a novel bacterial fingerprinting method that enjoys the resolving power and accuracy of mass spectrometry without the burden of peptide identification (i.e. genome se ...[more]

PMID: 26395646

Similar Datasets

Project description:The model prokaryote Escherichia coli can exist as a either a commensal or a pathogen in the gut of diverse mammalian hosts. These associations, coupled with its ease of cultivation and genetic variability, have made E. coli a popular indicator organism for tracking the origin of fecal water contamination. Source tracking accuracy is predicated on the assumption that E. coli isolates recovered from contaminated water present a genetic signature characteristic of the host from which they originated. In this study, we compared the accuracy with which E. coli isolated from humans, bear, cattle and deer could be identified by standard fingerprinting methods used for library-based microbial source tracking (repetitive element PCR and pulsed-field gel electrophoresis) in relation to microarray-based analysis of genome content. Our results show that patterns of gene presence or absence were more useful for distinguishing E. coli isolates from different sources than traditional fingerprinting methods, particularly in the case of human strains. Host-associated differences in genome composition included the presence or absence of mobile IS1 elements as well as genes encoding the ferric dicitrate iron transporter (fec), E. coli common pilus (ECP), type 1 fimbriae and the CRISPR associated cas proteins. Many of these differences occurred in regions of the E. coli chromosome previously shown to be M-bM-^@M-^\hot spotsM-bM-^@M-^] for the integration of horizontally-acquired DNA. PCR primers designed to amplify the IS1 and fec loci confirmed array results and demonstrated the ease with which gene presence/absence data can be converted into a diagnostic assay. The data presented here suggest that, despite the high level of genetic diversity observed among isolates by PFGE, human-derived strains may constitute a distinct ecotype distinguished by multiple potential library-independent source tracking markers. Twelve isolates of E. coli ( 3 from bear, 3 from cattle, 3 from deer and 3 from humans) were isolated from feces and/or raw sewage. Genome content for each strain was assessed in duplicate using comparative genome hybridization with E. coli K12 MG1655 as the reference for a total of 24 arrays.

			Action	DRS
	1209.RAW	Raw
	1233.RAW	Raw
	1284.RAW	Raw
	1339.RAW	Raw
	1344.RAW	Raw