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Record W2562012807 · doi:10.1182/blood.v126.23.646.646

Tet2 Is a Novel Regulator of Murine Macrophage Differentiation and Polarization

2015· article· en· W2562012807 on OpenAlexaff
Alyssa Cull, Brooke Snetsinger, Michael J. Rauh

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsQueen's University
Fundersnot available
KeywordsHaematopoiesisBiologyMolecular biologyBone marrowEpigeneticsMyeloidGene expressionCancer researchImmunologyStem cellGeneGenetics

Abstract

fetched live from OpenAlex

Abstract Introduction: The epigenetic regulator, TET2, catalyzes the conversion of methylcytosine to 5-hydroxymethylcytosine. Inactivating TET2 mutations are common in myeloid cancers such as chronic myelomonocytic leukemia (CMML). Although TET2 has been characterized in hematopoietic stem and progenitor cells, little is known about its role in disease-relevant monocytes/macrophages (MΦ). Previously, we found increased expression of M2 MΦ-associated arginase 1 (Arg1) in TET2 -mutant CMML and Tet2 -deficient MΦ. Therefore, our goals were to (1) characterize Tet family expression during normal murine MΦ differentiation and polarization, (2) determine the effect of Tet2 -deficiency on broader M1-M2 MΦ spectrum gene signatures. Methods: Hematopoietic-specific Tet2+/- and Tet2-/- knockout mice were generated by breeding floxed Tet2(f/f) with Vav-Cre mice (JAX), in accordance with Queen's University's Animal Care protocols. MΦs obtained by peritoneal lavage (PMΦ) and bone marrow differentiation (BMMΦ) from 9-13 week old Tet2-/- and 20-40 week old Tet2+/- mice were treated with an M1 stimulus (100ng/mL LPS) or an M2 stimulus (10ng/mL Il-4). Comparative gene expression analysis was conducted using a 591 candidate gene Mouse Immunology Gene Expression CodeSet (NanoString). Blood plasma samples collected from Tet2f/f and Tet2-/- mice were sent for cytokine/chemokine array analysis (Eve Technologies). Results: A survey of Tet mRNA expression in wild-type C57BL/6 mouse whole BM showed that Tet1 was most abundantly expressed, with Tet2 and Tet3 having relative abundances of 0.56±0.05 and 0.09±0.01 respectively. In contrast, Tet2 expression peaked, while Tet1 expression diminished during BMMΦ differentiation. Suggesting a functional role, loss of murine Tet2 is associated with skewed myelomonocytic differentiation (i.e. CMML phenotype). In terminally-differentiated MΦ, Tet2 was the most abundantly expressed Tet gene, suggesting MΦ-specific functions. Consistent with this, following a 3-hour LPS stimulation, Tet2 mRNA levels increased 2- to 4-fold, whereas Il-4 failed to induce a similar increase in expression. Overall, our results suggested that Tet2 plays a role in M1 but not M2 macrophage polarization. Based on these findings, we hypothesized that loss of Tet2 would lead to M1 program dysregulation. PMΦs were obtained from Tet2f/f and Tet2-/- mice (n=2/ genotype) and RNA was harvested from untreated and LPS- or Il-4-treated cells. Pools of these RNA samples were then screened using Nanostring. Overall, M1-associated markers such as Stat1, Socs1, Nfkbiz, Il-6, Il-27, Il-12, Il-1 and Ccl2 were markedly increased by 2- to 50-fold in resting Tet2-/- PMΦs compared to matched Tet2f/f samples. These same M1 genes demonstrated a reduced ability to be induced by LPS treatment. We also found that while the expression of most M2 genes was similar in controls versus knockouts, Il-1rn and Arg1 were overexpressed, and Marco was decreased. This suggested that Tet2 -deficient MΦs possess a complex phenotype with a potential homeostatic response to M1 gene dysregulation. We have previously seen variable upregulation of Arg1 in mouse BMMΦs and PMΦs. Approximately 60% of Tet2-deficient mice (+/- and -/-) (n=20) tested for MΦ Arg1 mRNA expression demonstrated 2- to 90-fold increases in Arg1 compared to pooled Tet2f/f controls (n=5). We were interested in investigating the underlying mechanisms contributing to this dramatic increase in expression. Using Nanostring on pooled Tet2-deficient PMΦs with low (n=7) or high (n=8) Arg1 mRNA expression, we were able to identify genes whose expression significantly correlated with Arg1 overexpression: Cxcl3 (p=0.0329), Ppbp (p=0.0015), Cxcl1 (p=0.0104) and Ccl6 (p=0.0185). Of note, Ppbp was the most divergently expressed gene (46-fold difference) in Arg1 low vs Arg1 high macrophages, followed by Arg1 itself (14-fold difference). Suggesting a further environmental influence, blood plasma levels of TNF-alpha, Il-1b, Il-4, Il-10, Il-12 and Il-13 were significantly elevated in mice with high PMΦ Arg1 mRNA expression (n=5) compared to those with low expression (n=10). Conclusions: Tet2 is a novel regulator of murine MΦ, induced during MΦ differentiation and M1-polarization. Tet2 loss leads to complex disruption of the M1-M2 spectrum. We are currently exploring whether human TET2 mutations contribute to the abnormal immune environment of myeloid cancers. 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 score0.002
Threshold uncertainty score0.006

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)0.0020.001

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 head0.012
GPT teacher head0.232
Teacher spread0.220 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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