Automated SPME–GC–MS monitoring of headspace metabolomic responses of E. coli to biologically active components extracted by the coating

Abstract

Monitoring extracellular metabolites of bacteria is very useful for not only metabolomics research but also for assessment of the effects of various chemicals, including antimicrobial agents and drugs. Herein, we describe the automated headspace solid-phase microextraction (HS-SPME) method coupled with gas chromatography–mass spectrometry (GC–MS) for the qualitative as well as semi-quantitative determination of metabolic responses of Escherichia coli to an antimicrobial agent, cinnamaldehyde. The minimum inhibitory concentration of cinnamaldehyde was calculated to be 2gL−1. We found that cinnamaldehyde was an important factor influencing the metabolic profile and growth process. A higher number of metabolites were observed during the mid-logarithmic growth phase. The metabolite variations (types and concentrations) induced by cinnamaldehyde were dependent on both cell density and the dose of cinnamaldehyde. Simultaneously, 25 different metabolites were separated and detected (e.g., indole, alkane, alcohol, organic acids, esters, etc.) in headspace of complex biological samples due to intermittent addition of high dose of cinnamaldehyde. The study was done using an automated system, thereby minimizing manual workup and indicating the potential of the method for high-throughput analysis. These findings enhanced the understanding of the metabolic responses of E. coli to cinnamaldehyde shock effect and demonstrated the effectiveness of the SPME–GC–MS based metabolomics approach to study such a complex biological system.