Identification of RIZ1 Targets Involvedin Erythroid Differentiation of K562 Human Erythroleukemia Cells Using Surface-Enhanced Laser Desorption Ionization Time-Of-Flight Mass Spectrometry (SELDI).
Bibliographic record
Abstract
Abstract RIZ1 (PRDM2) is a member of the nuclear protein methyltransferase superfamily involved in chromatin remodeling. RIZ1 functions as a tumor suppressor gene in a number of human cancers and is down regulated in some human acute myeloid leukemias. We previously found RIZ-1 to be silenced in K562 erythroleukemia cells by promoter hypermethylation. Furthermore, expression of RIZ1 in K562 promotes erythroid differentiation and also potentiates TGF-β1 mediated differentiation. To investigate similarities between genes altered by RIZ1 expression and the TGF-β1 pathway, we used SELDI to compare the protein profiles of K562 against K562 + RIZ1 and K562 + TGF-β1. Protein extracts for SELDI profiling were separated into six fractions according to their isoelectric points. Proteins from each fraction were then bound to two different protein chip surfaces (H50-hydrophoboic and CM10-cation exhange) and their mass/charge determined using SELDI. We analyzed four replicates from each sample and classified proteins as differentially expressed if their P-values were below 0.05. In total, we observed 104 differentially expressed proteins (60 upregulated and 44 down regulated) between K562 and K562 + RIZ1 and 176 proteins (96 upregulated and 80 down regulated) between K562 and K562 + TGF-β1. We used 2D-PAGE to identify differentially expressed proteins identified by SELDI analysis and located 48 proteins that were over expressed in K562 + RIZ1 and K562 + TGF-β1 relative to K562. To establish whether these proteins were the same proteins observed using SELDI, we determined if the proteins had the same pI and molecular weight and if the gel-eluted proteins bound to the same protein chip surface with the same mass/charge. 15 of 48 proteins passed the above criteria and we determined their identities using Trypsin-based peptide mapping strategies with molecular weight and pI restrictions. We identified two candidate proteins (14-3-3ε and S100/A13) that are similarly over expressed in K562 + RIZ1 and K562 + TGF-β1. These proteins have been shown to be associated with TGF-β1 signaling. Schistosomal 14-3-3ε interacts with SmRK1, a divergent type I transforming growth factor β1 receptor (TR-I) present on the surface of adult parasites and also binds to and activates human TR-I. S100/A13 belongs to a family of low molecular weight proteins characterized by the presence of two calcium-binding EF-hand motifs that includes S100C/A11, a member recently shown to play a key role in a PKCα mediated pathway essential for the growth inhibition of normal human keratinocytes by TGF-β1. In summary, we demonstrate the potential for using SELDI to identify novel proteins involved in regulating and connecting cellular growth and differentiation pathways.
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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".