DISCOVERY AND FUNCTIONAL CHARACTERIZATIONS OF PLAG1 IN HUMAN HEMATOPOEITIC STEM AND PROGENITOR CELLS
Bibliographic record
Abstract
Discovery and functional characterization of self-renewal regulatory factors constitute one of the central themes in the field of human hematopoietic stem and progenitor cell (HSPC) biology both for advancing the fundamental science as well as harnessing the knowledge to expand hematopoietic stem cells (HSCs) for regenerative therapeutics purposes. Musashi-2 (MSI2) is a marker and essential positive regulator of HSCs but knowledge of the transcription factors (TFs) that ensure its appropriate HSC-specific expression is lacking. I believed that uncovering the transcriptional circuitry of MSI2 could also offer opportunities for the discovery of candidate TFs with similar or superior functions in human HSPCs. To that end, initial investigations were set out to identify a conserved minimal promoter region bound by TFs upstream of the translation start site of human MSI2. In silico analysis of the minimal promoter region and series of TF binding-site mutagenesis biochemical assays identified USF2 and PLAG1 as key co-regulators of MSI2 expression and function in the model K562 cell line and cord blood HSPCs. The approach identified PLAG1 as a candidate TF whose function in HSPCs was not previously reported. I have characterized PLAG1 as an important regulator of HSPCs self-renewal using in vitro and xenotransplantation functional genomics coupled with RNA sequencing and downstream pathway analysis. In vitro, overexpression of PLAG1 (PLAG1OE) imparts sustained pro-survival advantage to progenitors and produces significantly more CD34+ cells compared to control culture. PLAG1OE enhances BFU-E and total colony forming unit (CFU) output. Complementary in vitro assays using shRNA-mediated knockdown (PLAG1KD) elucidated impaired CFU output, increased apoptosis and significantly reduced CD34+ cell counts. In vivo transplantation of PLAG1OE CD34+ cells into NSG mice at limiting doses robustly enhances the frequency and absolute number of HSCs by a magnitude of 24.1-fold compared to control. Serial transplantation of bone marrow cells into secondary recipients demonstrated enhanced self-renewal of HSCs compared to control. Mechanistically, transcriptome-wide gene-set enrichment and network analysis revealed that ribosome biogenesis and proteostasis pathways are significantly attenuated. PLAG1OE up-regulates expression of H19 and MEG3 imprinted long non-coding RNA (lncRNA)-derived miR-675 and miR-127 species respectively. In silico overlap analysis with experimentally validated targets of both miR-127 and miR-675 revealed ribosome biogenesis and proteins synthesis pathways components as prime targets. PLAG1 also represses the pan-ribosome biogenesis transcriptional regulator MYC. Down regulation of MYC demonstrates another layer of PLAG1-mediated transcriptional attenuation of protein synthesis. Additionally, we observed dampening of IGF1R/PI3K/AKT/mTOR signaling pathway. Conversely, PLAG1KD down regulated H19 and MEG3 expression and reverses global gene-set enrichment observed by PLAG1OE in reciprocal fashion. Taken together, our study presents PLAG1 as master regulator of ribosome biogenesis and protein synthesis from multiple checkpoints to enhance clonogenicity, survival and long-term self-renewal capacity of HSCs.
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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".