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Updated: Jan 3, 2026

Semi-Quantitative Analysis of Peptidoglycan by Liquid Chromatography Mass Spectrometry and Bioinformatics
Published on: October 13, 2020
Peptidoglycomics reveals compositional changes in peptidoglycan between biofilm- and planktonic-derived Pseudomonas
Erin M Anderson1, David Sychantha1, Dyanne Brewer2
1Department of Molecular and Cellular Biology, University of Guelph, Ontario N1G 2W1, Canada.
Abstract:
Peptidoglycan (PG) is a critical component of the bacterial cell wall and is composed of a repeating β-1,4-linked disaccharide of N-acetylglucosamine and N-acetylmuramic acid appended with a highly conserved stem peptide. In Gram-negative bacteria, PG is assembled in the cytoplasm and exported into the periplasm where it undergoes considerable maturation, modification, or degradation depending on the growth phase or presence of environmental stressors. These modifications serve important functions in diverse processes, including PG turnover, cell elongation/division, and antibiotic resistance. Conventional methods for analyzing PG composition are complex and time-consuming. We present here a streamlined MS-based method that combines differential analysis with statistical 1D annotation approaches to quantitatively compare PGs produced in planktonic- and biofilm-cultured Pseudomonas aeruginosa We identified a core assembly of PG that is present in high abundance and that does not significantly differ between the two growth states. We also identified an adaptive PG assembly that is present in smaller amounts and fluctuates considerably between growth states in response to physiological changes. Biofilm-derived adaptive PG exhibited significant changes compared with planktonic-derived PG, including amino acid substitutions of the stem peptide and modifications that indicate changes in the activity of amidases, deacetylases, and lytic transglycosylases. The results of this work also provide first evidence of de-N-acetylated muropeptides from P. aeruginosa The method developed here offers a robust and reproducible workflow for accurately determining PG composition in samples that can be used to assess global PG fluctuations in response to changing growth conditions or external stimuli.
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