Discrimination of different species from the genus Drosophila by intact protein profiling using matrix-assisted laser desorption ionization mass spectrometry
Bibliographic record
Abstract
BACKGROUND: The use of molecular biology-based methods for species identification and establishing phylogenetic relationships has supplanted traditional methods relying on morphological characteristics. While PCR-based methods are now the commonly accepted gold standards for these types of analysis, relatively high costs, time-consuming assay development or the need for a priori information about species-specific sequences constitute major limitations. In the present study, we explored the possibility to differentiate between 13 different species from the genus Drosophila via a molecular proteomic approach. RESULTS: After establishing a simple protein extraction procedure and performing matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) with intact proteins and peptides, we could show that most of the species investigated reproducibly yielded mass spectra that were adequate for species classification. Furthermore, a dendrogram generated by cluster analysis of total protein patterns agrees reasonably well with established phylogenetic relationships. CONCLUSION: Considering the intra- and interspecies similarities and differences between spectra obtained for specimens of closely related Drosophila species, we estimate that species typing of insects and possibly other multicellular organisms by intact protein profiling (IPP) can be established successfully for species that diverged from a common ancestor about 3 million years ago.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 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".