Dataset Information

Identification of novel lipid modifications and intermembrane dynamics in Corynebacterium glutamicum using high-resolution mass spectrometry.

ABSTRACT: The complex cell envelopes of Corynebacterineae contribute to the virulence of pathogenic species (such as Mycobacterium tuberculosis and Corynebacterium diphtheriae) and capacity of nonpathogenic species (such as Corynebacterium glutamicum) to grow in diverse niches. The Corynebacterineae cell envelope comprises an asymmetric outer membrane that overlays the arabinogalactan-peptidoglycan complex and the inner cell membrane. Dissection of the lipid composition of the inner and outer membrane fractions is important for understanding the biogenesis of this multilaminate wall structure. Here, we have undertaken the first high-resolution analysis of C. glutamicum inner and outer membrane lipids. We identified 28 lipid (sub)classes (>233 molecular species), including new subclasses of acylated/acetylated trehalose mono/dicorynomycolic acids, using high-resolution LC/MS/MS coupled with mass spectral library searches in MS-DIAL. All lipid subclasses exhibited polarized distributions across the inner and outer membrane fractions generated by differential solvent extraction. Strikingly, deletion of the TmaT protein, which is required for transport of trehalose corynomycolates across the inner membrane, led to the accumulation of triacylglycerols in the inner membrane and to suppressed synthesis of phosphatidylglycerol and alanylated lipids. These analyses indicate unanticipated connectivity in the synthesis and/or transport of different lipid classes in C. glutamicum.

SUBMITTER: Klatt S

PROVIDER: S-EPMC6027913 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundLipids are ubiquitous and serve numerous biological functions; thus lipids have been shown to have great potential as candidates for elucidating biomarkers and pathway perturbations associated with disease. Methods expanding coverage of the lipidome increase the likelihood of biomarker discovery and could lead to more comprehensive understanding of disease etiology.ResultsWe introduce LipidMatch, an R-based tool for lipid identification for liquid chromatography tandem mass spectrometry workflows. LipidMatch currently has over 250,000 lipid species spanning 56 lipid types contained in in silico fragmentation libraries. Unique fragmentation libraries, compared to other open source software, include oxidized lipids, bile acids, sphingosines, and previously uncharacterized adducts, including ammoniated cardiolipins. LipidMatch uses rule-based identification. For each lipid type, the user can select which fragments must be observed for identification. Rule-based identification allows for correct annotation of lipids based on the fragments observed, unlike typical identification based solely on spectral similarity scores, where over-reporting structural details that are not conferred by fragmentation data is common. Another unique feature of LipidMatch is ranking lipid identifications for a given feature by the sum of fragment intensities. For each lipid candidate, the intensities of experimental fragments with exact mass matches to expected in silico fragments are summed. The lipid identifications with the greatest summed intensity using this ranking algorithm were comparable to other lipid identification software annotations, MS-DIAL and Greazy. For example, for features with identifications from all 3 software, 92% of LipidMatch identifications by fatty acyl constituents were corroborated by at least one other software in positive mode and 98% in negative ion mode.ConclusionsLipidMatch allows users to annotate lipids across a wide range of high resolution tandem mass spectrometry experiments, including imaging experiments, direct infusion experiments, and experiments employing liquid chromatography. LipidMatch leverages the most extensive in silico fragmentation libraries of freely available software. When integrated into a larger lipidomics workflow, LipidMatch may increase the probability of finding lipid-based biomarkers and determining etiology of disease by covering a greater portion of the lipidome and using annotation which does not over-report biologically relevant structural details of identified lipid molecules.

Dataset Information

Identification of novel lipid modifications and intermembrane dynamics in Corynebacterium glutamicum using high-resolution mass spectrometry.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets