Straightforward N-Acyl Homoserine Lactone Discovery and Annotation by LC-MS/MS-based Molecular Networking

N-Acyl-L-homoserine lactones (AHLs) are a large family of signaling molecules in quorum sensing communication. This mechanism is present in a number of bacterial physiological phenomena, including pathogenic phenomena. In this study, we described a simple and accessible way to detect, annotate, and quantify these compounds from bacterial culture media. Analytical standards and ethyl acetate bacterial extracts containing AHLs were analyzed by an ultra-high-performance liquid chromatography system coupled to a mass spectrometer using a nontargeted FullMS data-dependent MS2 method. The results were processed in MZmine2 and then analyzed by a Feature-Based Molecular Networking (FBMN) workflow in the Global Natural Products Social Networking (GNPS) platform for the discovery and annotation of known and unknown AHLs. Our group analyzed 31 AHL standards and included the MS 2 spectra in the spectral library of the GNPS platform. We also provide the 31 standard AHL spectrum list for inclusion in molecular networking analyses. FBMN analysis annotated 30 out of 31 standards correctly. Then, as an example, a set of five bacterial extracts was prepared for AHL annotation. Following the method described in this Article, 5 known and 11 unknown AHLs were properly annotated using the FBMN-based molecular network approach. This study offers the possibility for the automatic annotation of known AHLs and the search for nonreferenced AHLs in bacterial extracts in a somewhat straightforward approach even without acquiring analytical standards. The method also provides relative quantification information.

Automated summary

This study presents a simple and accessible method to detect, annotate, and quantify AHLs in bacterial culture media. The method utilizes an ultra-high-performance liquid chromatography system coupled with a mass spectrometer using a nontargeted FullMS data-dependent MS2 method. Results were processed using MZmine2 and analyzed by the Feature-Based Molecular Networking (FBMN) workflow in the Global Natural Products Social Networking (GNPS) platform. The study demonstrates the automatic annotation of known AHLs and the ability to search for unknown AHLs, even without analytical standards. The method also provides relative quantification information.