Rule-Based Ion Prediction with Orthogonal Constraints Reveals Bacterial Phospholipid Remodeling Signatures

Area of Science:

• Microbiology
• Biochemistry
• Analytical Chemistry

Background:

• Phospholipids are crucial for bacterial membrane integrity and antibiotic stress response.
• Accurate annotation of phospholipid molecular species is challenging due to lipidome complexity.

Purpose of the Study:

• To develop a robust bacterial phospholipidomic framework for high-confidence annotation.
• To investigate bacterial membrane remodeling in response to antibiotic stress.

Main Methods:

• Integration of thin-layer chromatography (TLC), gas chromatography-mass spectrometry (GC-MS), and Paternò-Büchi derivatization.
• Utilized liquid chromatography-tandem mass spectrometry (LC-MS/MS) with a rule-based ion prediction library.
• Applied orthogonal structural evidence to reduce annotation ambiguity.

Main Results:

• Observed significant remodeling of membrane phospholipids in *Escherichia coli* during stationary phase and antibiotic exposure.
• Identified increased cardiolipin (CL) and cyclopropane-containing phospholipids under stress.
• Demonstrated framework applicability in *Enterococcus faecium*, noting differences in vancomycin-resistant strains.

Conclusions:

• The developed framework enables scalable and reproducible bacterial phospholipid annotation.
• Provides insights into molecular-species-resolved membrane adaptation.
• Highlights potential for targeting lipid homeostasis pathways as antimicrobial strategies.