Characterization of N-Succinylation of L-Lysylphosphatidylglycerol in <i>Bacillus subtilis</i> Using Tandem Mass Spectrometry
Bibliographic record
Abstract
Phospholipids generally dominate in bacterial lipids. The negatively charged nature of phospholipids renders bacteria susceptible to cationic antibiotic peptides. In comparison with Gram-negative bacteria, Gram-positive bacteria in general have much less zwitterionic phosphatidylethanolamine. However, they are known for producing aminoacylated phosphatidylglycerol (PG), especially positively charged L-lysyl-PG, which is catalyzed by lysyl-PG synthase MprF, which appears to have a broad range of specificity for L-aminoacyl transfer RNAs. In addition, many Gram-positive bacteria also have a dlt-gene-coded D-alanylation pathway for lipoteichoic acids and wall teichoic acids covalently attached to a glycolipid or peptidoglycan. D-Alanylation also masks the dominant negative charge of the phosphate-rich polymers of teichoic acids. Using mass spectrometry, we have recently observed that precursor scans in negative mode for deprotonated amino acid fragments were most sensitive for ester-linked amino acids. Such a scan for precursors generating an m/z 145 lysyl anion revealed lysyl-PG as well as an additional species 100 m/z units greater than lysyl-PG. This unexpected species corresponded precisely to the expected mass of N-succinylated lysyl-PG. Tandem mass spectrometry revealed a precise match to the fragmentation pattern of this putative new species. PG, lysyl-PG, and N-succinyl-lysyl-PG may form a complete loop of charge reversal from -1 to +1 and then back to -1. Analogous charge reversal by N-succinylation of lysine residues in the bacterial as well as eukaryotic proteomes has been recently discovered as a major posttranslational modification. Such modification in bacterial lipids is possibly catalyzed by an enzyme homologous to the enzymes that modify lysine residues in proteins. Graphical Abstract ᅟ.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".