Evolution of the regulatory control of vertebrate striated muscle: the roles of troponin I and myosin binding protein-C
Bibliographic record
Abstract
Troponin I (TnI) and myosin binding protein-C (MyBP-C) are key regulatory proteins of contractile function in vertebrate muscle. TnI modulates the Ca(2+) activation signal, while MyBP-C regulates cross-bridge cycling kinetics. In vertebrates, each protein is distributed as tissue-specific paralogs in fast skeletal (fs), slow skeletal (ss), and cardiac (c) muscles. The purpose of this study is to characterize how TnI and MyBP-C have changed during the evolution of vertebrate striated muscle and how tissue-specific paralogs have adapted to different physiological conditions. To accomplish this we have completed phylogenetic analyses using the amino acid sequences of all known TnI and MyBP-C isoforms. This includes 99 TnI sequences (fs, ss, and c) from 51 different species and 62 MyBP-C sequences from 26 species, with representatives from each vertebrate group. Results indicate that the role of protein kinase A (PKA) and protein kinase C (PKC) in regulating contractile function has changed during the evolution of vertebrate striated muscle. This is reflected in an increased number of phosphorylatable sites in cTnI and cMyBP-C in endothermic vertebrates and the loss of two PKC sites in fsTnI in a common ancestor of mammals, birds, and reptiles. In addition, we find that His(132), Val(134), and Asn(141) in human ssTnI, previously identified as enabling contractile function during cellular acidosis, are present in all vertebrate cTnI isoforms except those from monotremes, marsupials, and eutherian mammals. This suggests that the replacement of these residues with alternative residues coincides with the evolution of endothermy in the mammalian lineage.
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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 | 0.000 | 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".