A new class of transcription factors? (Comment on DOI 10.1002/bies.201100089)
Bibliographic record
Abstract
Transcription factors (TFs) are proteins that typically bind DNA and affect transcription in a positive or negative fashion. While several TF families exist based on protein structure, they can be categorized as general or differential. General (or basal) TFs, such as TATA binding protein, are ubiquitously expressed, and required for the expression of a battery of genes regardless of cell type. In contrast, differential TFs are limited spatially and temporally, and dictate cell specific transcription in response to developmental or environmental cues. In this issue, Mills and Taghert suggest a novel category, termed scaling factors, for a group of TFs that are expressed exclusively in mature cells, dictate the expansion of a particular subcellular organelle or resource, control quantitative features of the cell and persist for life. The concept suggests that scaling factors enhance, rather than initiate, existing transcriptional activity, thereby contributing to expansion of specific cell compartments 1. Three TFs are described as scaling factors–MIST1 (and its Drosophila homologue DIMM), which is expressed to high levels in mature serous exocrine cells; PGC1α, a transcriptional co-activator for several TFs, expressed in such diverse cells as adipocytes and skeletal muscle; and TFEB, which is required for lysosome biogenesis. Scaling factors represent an important new conceptualisation of TF function and may explain how cells derived from different embryonic origins show convergence in function and gene expression. However, several questions arise for this model based on previous studies for MIST1/DIMM. Can scaling factors also function as differential TFs? MIST1 is first expressed prior to differentiation of acinar cells in the pancreas 2, and directly regulates expression of the cell cycle regulator, p21 3, which has not been linked to secretion compartment. In addition, the expression of a number of genes, such as Atp2c2, is completely lost in Mist1−/− acinar cells 4. Whether these effects are the result of altered cell function or require MIST1 for initiation still needs to be determined. Do homologues exist for scaling factors in cells with similar functions? The phenotypes observed following loss of function experiments suggest that scaling factors have non-redundant roles that dictate the ability of individual cells to respond to environmental challenges. MIST1 enhances expression of genes involved in cell secretion, but these genes are not unique to MIST1-expressing cells. Gjb1 (encodes the gap junction protein, connexin32) is lost in Mist1−/− pancreatic tissue, but expressed to normal levels in liver hepatocytes 5. Similar exocytosis pathways exist in neurons and endocrine cells, yet neither MIST1, nor a homologue to MIST1, has been identified in these cells. Can loss of a scaling factor affect cell differentiation? Loss of MIST1/DIMM function results in reduced granule formation and regulated secretion, while ablation of PGC1α causes altered cellular metabolism and energy production. While cell determination is not affected, the absence of MIST1 leads to increased accumulation of transitional cells in the gastric epithelium, incomplete maturation of pancreatic acinar cells and enhanced sensitivity to events (e.g. Kras activity) that promote loss of the acinar phenotype 6, 7. MIST1 can also repress myogenic differentiation by targeting the MyoD gene 8. Similarly, PGC1α regulates enterocyte cell fate and protects against tumorigenesis 9. Ultimately, addressing these and other questions will help identify additional scaling factors, and provide a clearer understanding of how scaling factors function and affect multifactorial diseases such as diabetes and cancer.
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.
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 | 0.000 | 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 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".