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Sphingolipids Regulate Myeloid-Erythroid Fate Determination in Human Hematopoiesis

2016· article· en· W2586248620 on OpenAlexaff
Stephanie Z. Xie, Kerstin B. Kaufmann, Olga I. Gan, Sasan Zandi, Naoya Takayama, John E. Dick

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSphingolipid Metabolism and Signaling
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsBiologyCell biologyMyeloidHaematopoiesisGATA1MyelopoiesisSphingolipidProgenitor cellLymphopoiesisPopulationStem cellCell fate determinationTranscription factorImmunologyGeneticsGene

Abstract

fetched live from OpenAlex

Abstract The established model of hematopoiesis posits mature blood lineages are derived through successive stages of progenitors that become increasingly lineage-restricted. Whereas the master transcriptional regulators of myeloid-erythroid fate specification such a in Pu.1, Gata1 and CEBPalpha are well studied, the signaling networks that link extrinsic niche signals to lineage commitment is ill-defined. Sphingosine-1-phosphate (S1P) is a bioactive lipid produced from sphingolipid metabolism that in mice has been implicated in HSC egress, lymphocyte trafficking and lymphocyte lineage determination, mainly through the receptor S1PR1. However, the role of sphingolipid biology in human lineage specification is unknown. Gene expression profiling of 11 highly resolved populations of human stem, progenitor and lineage commited cells was undertaken to gain insight into the transcriptional signatures that define each cell population and the changes that occur during lineage commitment. We previously established that sphingolipid metabolism is transcriptionally distinct between HSC and progenitors (Xie et al In prep). Unbiased clustering of RNA-seq data of 46 sphingolipid genes was sufficient to segregate mature human erythroid, lymphoid, and myeloid cells suggesting that tight regulation of S1P signaling is required for lineage commitment. Myeloid cells have the highest transcriptional expression of S1P receptors among mature lineages whereas erythroid cells have little to no expression predicting that S1P signaling may be important in governing myeloid-erythroid fate. We found that manipulating S1P transport via overexpression of the S1P transporter SPNS2 in cord blood was sufficient to limit erythropoiesis as assayed by single cell in vitro assays and in vivo xenotransplantation. S1P signals through a family of 5 G-protein coupled S1P receptors, with S1PR3 expression being myeloid-specific. S1PR3 protein expression is restricted in the primitive human hematopoietic hierarchy to only a subset of granulocyte-macrophage progenitors. Enforced expression of S1PR3 in HSC, MPP (multipotent progenitors) and CMP (common myeloid progenitors) is sufficient to inhibit erythropoiesis and upregulate myelopoiesis in single cell stromal-based assays suggesting S1PR3 has a unique role in myeloid-erythroid fate specification. Flow cytometry analysis shows S1PR3 protein is highly overexpressed in primary AML relative to normal blood cells, suggesting S1P biology is dysregulated in AML. Collectively, our studies provide the first direct evidence that the S1P pathway governs fate determination along myeloid-erythroid lineage commitment. Future studies will need to be undertaken to determine how this new mechanism of lineage commitment is linked to the transcription factor network. Our studies also suggest that this pathway may play a role in AML biology raising the possibility of a new therapeutic direction for AML. Disclosures No relevant conflicts of interest to declare.

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 score0.003

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 integrity0.0000.000
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 head0.008
GPT teacher head0.239
Teacher spread0.230 · 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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