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Record W4407093653 · doi:10.33540/2833

The Epigenetic and Epitranscriptomic Regulation of Immune Activation

2025· dissertation· en· W4407093653 on OpenAlexaff
Lucas W. Picavet

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsEpigeneticsImmune systemBiologyComputational biologyGeneticsGene

Abstract

fetched live from OpenAlex

Gene expression in immune cells is regulated by intricate mechanisms that contribute to the immune response. Precise control of this expression is crucial for achieving well-timed and finely tuned expression of genes and pathways associated with inflammation. Disruption of this delicate balance can lead to severe complications, such as infections, auto-inflammatory disorders, or autoimmune diseases. This thesis elucidates the role of histone regulation and post-transcriptional regulation via m6A modification in both the adaptive and innate immune systems. Chapter 1 provides a general introduction, setting the stage for the detailed investigations that follow. Chapter 2 delves into the impact of histone regulation on CD4+ T cell activation by inhibiting key co-activators and HAT proteins P300/CBP. The potential of targeted inhibition of P300/CBP through BET inhibition is explored as a therapeutic approach for treating Juvenile Idiopathic Arthritis (JIA). In Chapter 3, the focus shifts to the role of m6A modification in monocyte activation. Following monocyte activation, differential expression of multiple m6A-associated proteins is uncovered, leading to elevated m6A levels. m6A methylation is identified on numerous genes within the TNF signaling via the NFkB pathway, including TNF itself. The m6A reader YTHDC1 binds to m6A-modified TNF, promoting TNF protein expression by facilitating the nuclear export of TNF mRNA. Chapter 4 elaborates on the increased expression of WTAP observed in monocyte activation. An alternative WTAP promoter is identified, which increases expression of a specific WTAP mRNA isoform in monocyte activation under the regulation of NFkB. Chapter 5 returns to JIA, demonstrating expression differences of m6A-associated proteins and increased m6A levels in monocytes derived from the inflamed joint of JIA patients. Decreased expression of the m6A eraser FTO can be induced by environmental cues from the synovial fluid of the inflamed joint. Chapter 6 examines the role of m6A in host immunity against Respiratory Syncytial Virus (RSV) infection. m6A modifications are detected on respiratory viruses, including RSV, which enhances viral replication and immune evasion. On host transcripts, the m6A reader YTHDC1 negatively regulates RSV entry by reducing the expression of the RSV entry receptor CX3CR1. The role of m6A in adaptive immunity and CD4+ T cell activation is discussed in Chapter 7 and Chapter 8, particularly in regulating stability of CD40L and TNF mRNA via m6A reader protein YTHDF2. Chapter 9 provides a general discussion, summarizing the findings of the thesis. Both histone regulation and m6A modification emerge as critical mechanisms for precisely modulating gene expression in different components of the immune system. This chapter explores the intricate interplay between these mechanisms, highlighting factors such as timing, transcript specificity, and reader specificity for m6A modifications. Furthermore, the potential implications of BET inhibition and m6A protein inhibition are underscored as promising therapeutic strategies for addressing autoimmune diseases. Overall, this thesis provides novel insights into how distinct forms of gene regulation orchestrate the immune response. Epigenetic and epitranscriptomic mechanisms, such as histone regulation and m6A modifications, exhibit multifaceted roles in T cell and monocyte activation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.007
GPT teacher head0.225
Teacher spread0.219 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2025
Admission routes1
Has abstractyes

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