Aurora Kinase A Controls Trained Immunity via SAM Metabolism

Study Background and Research Question

Trained immunity describes the phenomenon where innate immune cells, such as macrophages, acquire a memory-like state, enabling them to mount enhanced responses to secondary stimuli. This process is distinct from adaptive immunity and is driven by metabolic and epigenetic reprogramming following exposure to certain pathogens or microbial components, including β-glucan. While the role of chromatin remodeling and metabolic rewiring in trained immunity is well-established, the molecular mechanisms that coordinate these processes remain incompletely understood, particularly the regulation of methyl donor availability and its impact on epigenetic modifications. Aurora kinase A (AurA), a serine/threonine kinase widely studied in the context of mitosis and oncogenesis, is often overexpressed in tumors, but its role in immune cell memory has been unclear. The reference study by Li et al. (eLife 2025;14:RP104138) addresses this gap by investigating whether and how AurA contributes to trained immunity through metabolic and epigenetic mechanisms.

Key Innovation from the Reference Study

The major innovation of Li et al. lies in the identification of AurA as a crucial regulator of trained immunity through its control of endogenous S-adenosylmethionine (SAM) metabolism. The authors demonstrate that inhibition of AurA impairs the establishment of trained immunity in macrophages by disrupting SAM-dependent histone methylation, thereby limiting chromatin accessibility and the expression of inflammatory cytokine genes. Mechanistically, AurA inhibition activates the mTOR-FOXO3-GNMT axis, leading to increased glycine N-methyltransferase (GNMT) expression and subsequent SAM depletion. This study is the first to directly link a mitotic kinase to the metabolic-epigenetic axis underpinning innate immune memory, providing a new perspective on how cell cycle regulators can influence immune cell fate and function (Li et al., 2025).

Methods and Experimental Design Insights

Li et al. employed a combination of pharmacological and genetic approaches to dissect the role of AurA in trained immunity. Key methodological highlights include:

• Pharmacological inhibition: AurA activity was inhibited using small-molecule inhibitors during β-glucan-induced training of mouse macrophages, allowing assessment of trained immunity phenotypes in the presence or absence of AurA signaling.
• Epigenetic profiling: ATAC-seq and RNA-seq were utilized to evaluate changes in chromatin accessibility and gene expression, particularly focusing on inflammatory pathways (JAK-STAT, TNF, NF-κB) following AurA inhibition.
• Metabolomic analysis: Changes in intracellular SAM levels were quantified to establish the metabolic impact of AurA inhibition.
• Protein localization and expression: Nuclear translocation of FOXO3 and GNMT expression were measured to map the signaling cascade downstream of AurA.
• Histone methylation assays: Enrichment of trimethylated histone marks (H3K4me3, H3K36me3) at cytokine gene loci (e.g., Il6, Tnf) was assessed using ChIP-qPCR.
• In vivo tumor models: The functional consequence of AurA inhibition on β-glucan-mediated tumor growth inhibition was tested in mouse models.

Protocol Parameters

• β-glucan training: Macrophages were primed with β-glucan (specific concentrations as in the reference study) for 24 hours, followed by a resting phase and secondary stimulation.
• AurA inhibitor treatment: Small-molecule AurA inhibitors (e.g., MLN8237/Alisertib in similar studies) were applied during priming and/or rest phases to assess effects on trained immunity establishment.
• Chromatin and metabolic analysis: Perform ATAC-seq, RNA-seq, and metabolomics at defined timepoints post-treatment to capture dynamic changes in accessibility and metabolite levels.
• In vivo workflow: Administer β-glucan and AurA inhibitor per established schedules prior to tumor challenge to evaluate combined effects on immune-mediated tumor control.

Core Findings and Why They Matter

The study's core findings are multi-layered and mechanistically robust:

• AurA is required for trained immunity: Inhibition of AurA abrogates β-glucan-induced trained immunity in macrophages, resulting in diminished secondary responses to inflammatory stimuli (Li et al.).
• Epigenetic regulation is SAM-dependent: AurA inhibition reduces intracellular SAM, a key methyl donor, which in turn lowers H3K4me3 and H3K36me3 marks at cytokine gene promoters and exons, limiting their inducible expression.
• mTOR-FOXO3-GNMT axis links AurA to metabolism: Blocking AurA activity promotes nuclear FOXO3 translocation, upregulates GNMT (which consumes SAM), and lowers SAM pools, connecting cell signaling to one-carbon metabolism.
• Anti-tumor immunity is compromised: The tumor growth inhibition typically mediated by β-glucan-trained macrophages is reversed by AurA inhibition, underscoring the immunological and translational relevance of the pathway.

These findings are significant because they extend the concept of trained immunity beyond classical immune signaling and place metabolic and epigenetic regulation at the center of innate immune memory. The identification of SAM as a metabolic checkpoint for chromatin remodeling adds a new layer to our understanding of how innate immunity is established and maintained, with implications for both infectious disease and cancer biology.

Comparison with Existing Internal Articles

Several internal resources have discussed the role of Aurora A kinase and its inhibition in cancer research:

• The article "Aurora Kinase A Regulates Trained Immunity via SAM Metabolism" offers a concise overview of Li et al.'s discovery, emphasizing the link between AurA activity, SAM pools, and chromatin accessibility in trained macrophages. This complements the present review by reinforcing the metabolic-epigenetic axis as a research focus.
• "MLN8237 (Alisertib): Precision Aurora A Kinase Inhibition" and related articles primarily cover the application of MLN8237 (Alisertib) as a selective Aurora A kinase inhibitor in cancer biology, with a focus on apoptosis induction in tumor cells and tumor growth inhibition in animal models. While these works center on oncogenesis and tumor progression, the reference study by Li et al. bridges the gap to immunology by showing how Aurora A kinase modulation can also affect innate immune memory and anti-tumor immunity.
• For workflow and protocol optimization in targeting Aurora A kinase, "MLN8237 (Alisertib): Selective Aurora A Kinase Inhibitor" provides detailed molecular and methodological guidance relevant to both cancer and immune studies.

Together, these resources highlight the versatility of Aurora A kinase inhibitors in both cancer biology and emerging immunometabolic research, with the reference paper supplying novel mechanistic depth to the field.

Limitations and Transferability

While the study by Li et al. is comprehensive in its approach, several limitations should be acknowledged:

• Model system specificity: The experiments are conducted primarily in mouse macrophages and tumor models. Translational relevance to human immune responses and clinical settings requires further validation.
• Pharmacological considerations: The specificity and off-target effects of AurA inhibitors in vivo are not exhaustively characterized within the study. As different inhibitors may vary in selectivity and pharmacokinetics, results should be interpreted with caution when extrapolating to other compounds.
• Focus on β-glucan training: The findings are centered on β-glucan-induced trained immunity; whether similar mechanisms operate for other inducers remains to be determined.

Despite these caveats, the mechanistic insights into the mTOR-FOXO3-GNMT-SAM axis provide a robust framework for further exploration in both fundamental and translational research.

Research Support Resources

For investigators aiming to explore the role of Aurora A kinase in immune cell function, apoptosis induction in tumor cells, or tumor growth inhibition in animal models, MLN8237 (Alisertib) (SKU A4110) is a well-characterized, selective Aurora A kinase inhibitor. According to the product information, MLN8237 is suitable for studies of cell cycle regulation, mitotic processes, and programmed cell death, and is supported by a substantial literature base in cancer biology and emerging immunometabolic workflows. Researchers are encouraged to tailor inhibitor concentrations and protocols to their specific model systems and to consult recent literature to stay abreast of advances in Aurora kinase-targeted research.