Detection of secreted peptides by using hypothesis-driven multistage mass spectrometry
Bibliographic record
Abstract
A method is presented for the rapid detection and characterization of trace amounts of peptides secreted from microorganisms, including pheromones, virulence factors, and quorum-sensing peptides. The procedure, based on targeted multistage MS, uses a novel matrix-assisted laser desorptionionization-ion trap mass spectrometer to overcome limitations of current MS methods (limited dynamic range, signal suppression effects, and chemical noise) that impair observation of low abundance peptides from complex biological matrixes. Here, secreted peptides that are hypothesized to be present in the supernatant, but that may not be sufficiently abundant to be observed in single-stage mass spectra, are subjected to multistage MS. Highly specific fragmentation signatures enable unambiguous identification of the peptides of interest and differentiation of the signals from the background. As examples, we demonstrate the rapid (<1 min) determination of the mating type of cells in colonies of Saccharomyces cerevisiae and the elucidation of autoinducing peptides (AIPs) from supernatants of pathogenic Staphylococci. We confirm the primary structures of the agrD encoded cyclic AIPs of Staphylococcus aureus for groups I, II, and IV and provide direct evidence that the native group-III AIP is a heptapeptide (INCDFLL). We also show that the homologous peptide from Staphylococcus intermedius is a nonapeptide (RIPTSTGFF) with a lactone ring formed through condensation of the serine side chain with the C terminus of the peptide. This is the first demonstration of cyclization in a staphylococcal AIP that occurs via lactone formation. These examples demonstrate the analytical power of the present procedure for characterizing secreted peptides and its potential utility for identifying microorganisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".