Machine learning-assisted design of immunomodulatory lipid nanoparticles for delivery of mRNA to repolarize hyperactivated microglia

Regulating inflammatory microglia presents a promising strategy for treating neurodegenerative and autoimmune disorders, yet effective therapeutic agents delivery to these cells remains a challenge. This study investigates modified lipid nanoparticles (LNP) for mRNA delivery to hyperactivated microglia, particularly those with pro-inflammatory characteristics, utilizing supervised machine learning (ML) classifiers. We developed and screened a library of 216 LNP formulations with varying lipid compositions, N/P ratios, and hyaluronic acid (HA) modifications. The transfection efficiency of eGFP mRNA was assessed in the BV-2 murine microglia cell line under different immunological states, including resting and activated conditions (LPS-activated and IL4/IL13-activated). ML-guided morphometric analysis tracked the phenotypes of various microglia subtypes before and after transfection. Four supervised ML classifiers were investigated to predict transfection efficiency and phenotypic changes based on LNP design parameters. The Multi-Layer Perceptron (MLP) neural network emerged as the best-performing model, achieving weighted F1-scores ≥0.8. While it accurately predicted responses from LPS-activated and resting cells, it struggled with IL4/IL13-activated cells. The MLP model was validated by predicting the performance of four unseen LNP formulations delivering eGFP mRNA to LPS-activated BV2 cells. HA-LNP2 emerged as optimal formulation for delivering target IL10 mRNA, effectively suppressing inflammatory phenotypes, evidenced by shifts in cell morphology, increased IL10 expression, and reduced TNF-α levels. We also evaluated HA-LNP2 on LPS-activated human iPSC-derived microglia, confirming its efficacy in modulating inflammatory responses. This study highlights the potential of tailored LNP design and ML techniques to enhance mRNA therapy for neuroinflammatory disorders by leveraging carrier’s immunogenic properties to modulate microglial responses.

Publication Details

Journal
Figshare
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.28524227
Primary Topic
RNA Interference and Gene Delivery
Type
article
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article

Machine learning-assisted design of immunomodulatory lipid nanoparticles for delivery of mRNA to repolarize hyperactivated microglia

Figshare
RNA Interference and Gene Delivery
article

Machine learning-assisted design of immunomodulatory lipid nanoparticles for delivery of mRNA to repolarize hyperactivated microglia

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Abstract

Regulating inflammatory microglia presents a promising strategy for treating neurodegenerative and autoimmune disorders, yet effective therapeutic agents delivery to these cells remains a challenge. This study investigates modified lipid nanoparticles (LNP) for mRNA delivery to hyperactivated microglia, particularly those with pro-inflammatory characteristics, utilizing supervised machine learning (ML) classifiers. We developed and screened a library of 216 LNP formulations with varying lipid compositions, N/P ratios, and hyaluronic acid (HA) modifications. The transfection efficiency of eGFP mRNA was assessed in the BV-2 murine microglia cell line under different immunological states, including resting and activated conditions (LPS-activated and IL4/IL13-activated). ML-guided morphometric analysis tracked the phenotypes of various microglia subtypes before and after transfection. Four supervised ML classifiers were investigated to predict transfection efficiency and phenotypic changes based on LNP design parameters. The Multi-Layer Perceptron (MLP) neural network emerged as the best-performing model, achieving weighted F1-scores ≥0.8. While it accurately predicted responses from LPS-activated and resting cells, it struggled with IL4/IL13-activated cells. The MLP model was validated by predicting the performance of four unseen LNP formulations delivering eGFP mRNA to LPS-activated BV2 cells. HA-LNP2 emerged as optimal formulation for delivering target IL10 mRNA, effectively suppressing inflammatory phenotypes, evidenced by shifts in cell morphology, increased IL10 expression, and reduced TNF-α levels. We also evaluated HA-LNP2 on LPS-activated human iPSC-derived microglia, confirming its efficacy in modulating inflammatory responses. This study highlights the potential of tailored LNP design and ML techniques to enhance mRNA therapy for neuroinflammatory disorders by leveraging carrier’s immunogenic properties to modulate microglial responses.

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RNA Interference and Gene Delivery
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