Mass spectrometry-based Shiga toxin identification: An optimized approach

J Proteomics. 2018 May 30:180:36-40. doi: 10.1016/j.jprot.2017.06.003. Epub 2017 Jun 8.

Abstract

Toxin expression is a key factor in Shiga toxin (Stx)-producing E. coli, a common pathogen involved in foodborne disease outbreaks. A liquid chromatography-tandem mass spectrometry (LC-MS/MS) based approach has been used in this study to identify commonly reported E. coli toxins, with a focus on Shiga toxins (Stxs). Different sample preparation methods using variable culture conditions and concentrations of mitomycin C (MMC), a common antibiotic/chemotherapy agent capable of stimulating Stx production, were first tested on reference strains EDL933 and 90-2380 by LC-MS/MS detection of tryptic digests of receptor-analogue affinity binding enriched Stx preparations from culture supernatants and lysates. A curated E. coli protein toxin database was also used for faster and more straightforward toxin identification. With eight more genetically confirmed E. coli strains examined to verify the method, this preliminary study indicates that receptor-analogue based affinity enrichment on cell lysate or supernatant is a sensitive and accurate method for Stx identification.

Biological significance: The existence of Stx is very important for identifying Stx-producing E. coli and implementing a clinical treatment regime. This study demonstrates for the first time that using a curated E. coli toxin database, together with receptor-analogue-based affinity enrichment of Stxs after MMC treatment of E. coli, is an easy and appropriate approach for fast and accurate Stx identification through LC-MS/MS.

Keywords: Affinity purification; LC-MS/MS; Mass spectrometry; Shiga toxin identification.

MeSH terms

  • Chromatography, Liquid
  • Databases, Protein*
  • Escherichia coli Proteins / metabolism*
  • Shiga Toxin / metabolism*
  • Shiga-Toxigenic Escherichia coli / metabolism*
  • Tandem Mass Spectrometry

Substances

  • Escherichia coli Proteins
  • Shiga Toxin