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Record W4389221452 · doi:10.1182/blood-2023-184853

TIF1γ Counteracts Ferroptosis to Drive Erythroid Progenitor Differentiation

2023· article· en· W4389221452 on OpenAlexaff
Marlies P. Rossmann, Song Yang, Brian J. Abraham, Ying Wang, Richard A. Young, Siegfried Hekimi, Leonard I. Zon

Bibliographic record

VenueBlood · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiologyCell biologyPyrimidine metabolismChromatin immunoprecipitationZebrafishTranscription factorMolecular biologyBiochemistryGene expressionGeneEnzyme

Abstract

fetched live from OpenAlex

Understanding in-vivo mechanisms of hematopoiesis is critical for developing directed blood differentiation approaches to treat blood disorders such as leukemias. Zebrafish moonshine ( mon) mutant embryos defective for transcriptional intermediary factor 1 gamma ( tif1γ), a conserved transcription elongation and chromatin factor, lack red blood cells due to a block in hematopoietic stem cell differentiation along the erythroid lineage. We recently showed that TIF1γ plays a critical role in mitochondrial metabolism, including maintaining adequate coenzyme Q levels. Through a chemical suppressor screen for the mon mutant, we identified inhibitors of the essential mitochondrial pyrimidine synthesis enzyme dihydroorotate dehydrogenase to promote erythroid differentiation in mon mutants due to its functional link to the electron transport chain. In agreement, our in-vivo metabolomics analyses identified nucleotide metabolism as the most significantly altered processes in mon mutants, with elevated levels of uridine monophosphate and low levels of N-carbamoyl-L-aspartate. Interestingly, imbalances in nucleotide metabolism similar to those in mon mutants have also been reported in the presence of active ferroptosis, a pathway of programmed cell death due to iron-dependent lipid peroxidation. Through transcriptome profiling upon tif1γ loss of function in zebrafish embryos at the onset of hematopoiesis, we uncovered an expression signature indicative of activated ferroptosis. gpx4 and fsp1, inhibitors of ferroptosis acting in parallel pathways, were both downregulated, and chac1 and ptgs2, an enhancer and marker of ferroptosis, respectively, were upregulated. In addition, parallel genome-wide expression and chromatin immunoprecipitation analyses identified anti-ferroptotic genes as direct TIF1γ targets in human cells. In support of these results, we found mon mutants to exhibit increased levels of lipid peroxidation. Functionally, tif1γ loss of function synergizes with loss of gpx4 in blocking erythroid differentiation. These results demonstrate a tight coordination of nucleotide metabolism, mitochondrial respiration, and the regulation of lipid peroxidation as a key function of tif1γ-dependent transcription that drives cell fate decisions in the early erythroid lineage. Our work highlights the importance of the plasticity achieved by transcription regulatory processes such as transcription elongation for metabolic processes during lineage differentiation and could have therapeutic potential for blood diseases.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.259
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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