Proteome‐wide identification of mycobacterial pupylation targets
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mycobacteria use a unique system for covalently modifying proteins based on the conjugation of a small protein, referred to as prokaryotic ubiquitin-like protein (PUP). In this study, we report a proteome-wide analysis of endogenous pupylation targets in the model organism Mycobacterium smegmatis. On affinity capture, a total of 243 candidate pupylation targets were identified by two complementary proteomics approaches. For 41 of these protein targets, direct evidence for a total of 48 lysine-mediated pupylation acceptor sites was obtained by collision-induced dissociation spectra. For the majority of these pupylation targets (38 of 41), orthologous genes are found in the M. tuberculosis genome. Interestingly, approximately half of these proteins are involved in intermediary metabolism and respiration pathways. A considerable fraction of the remaining targets are involved in lipid metabolism, information pathways, and virulence, detoxification and adaptation. Approximately one-third of the genes encoding these targets are located in seven gene clusters, indicating functional linkages of mycobacterial pupylation targets. A comparison of the pupylome under different cell culture conditions indicates that substrate targeting for pupylation is rather dynamic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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 it