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

IF 6.5 2区 医学 Q1 PHARMACOLOGY & PHARMACY
Drug Delivery Pub Date : 2025-12-01 Epub Date: 2025-03-03 DOI:10.1080/10717544.2025.2465909
Mehrnoosh Rafiei, Akbar Shojaei, Ying Chau
{"title":"Machine learning-assisted design of immunomodulatory lipid nanoparticles for delivery of mRNA to repolarize hyperactivated microglia.","authors":"Mehrnoosh Rafiei, Akbar Shojaei, Ying Chau","doi":"10.1080/10717544.2025.2465909","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":11679,"journal":{"name":"Drug Delivery","volume":"32 1","pages":"2465909"},"PeriodicalIF":6.5000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11878168/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Drug Delivery","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/10717544.2025.2465909","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/3 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0

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.

机器学习辅助设计免疫调节脂质纳米颗粒,用于递送mRNA以使过度激活的小胶质细胞再极化。
调节炎性小胶质细胞是治疗神经退行性疾病和自身免疫性疾病的一种很有前途的策略,但有效的治疗药物递送到这些细胞仍然是一个挑战。本研究利用监督机器学习(ML)分类器,研究了修饰脂质纳米颗粒(LNP)将mRNA传递给过度激活的小胶质细胞,特别是那些具有促炎特征的小胶质细胞。我们开发并筛选了216个LNP配方库,这些配方具有不同的脂质组成、氮磷比和透明质酸(HA)修饰。在不同的免疫状态下,包括静息状态和激活状态(lps激活和IL4/ il13激活),我们评估了eGFP mRNA在BV-2小鼠小胶质细胞中的转染效率。ml引导的形态计量学分析跟踪了转染前后各种小胶质细胞亚型的表型。研究了四个监督ML分类器,以预测基于LNP设计参数的转染效率和表型变化。多层感知器(MLP)神经网络成为表现最好的模型,其加权f1得分≥0.8。虽然它准确地预测了lps激活和静息细胞的反应,但它很难预测IL4/ il13激活的细胞。通过预测四种未见的LNP配方向lps激活的BV2细胞递送eGFP mRNA的性能,验证了MLP模型。HA-LNP2是传递目标IL10 mRNA的最佳配方,可以有效抑制炎症表型,这可以通过细胞形态的改变、IL10表达的增加和TNF-α水平的降低来证明。我们还评估了HA-LNP2对lps激活的人类ipsc衍生的小胶质细胞的作用,证实了其调节炎症反应的功效。本研究强调了定制LNP设计和ML技术的潜力,通过利用载体的免疫原性来调节小胶质细胞反应,增强神经炎性疾病的mRNA治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Drug Delivery
Drug Delivery 医学-药学
CiteScore
11.80
自引率
5.00%
发文量
250
审稿时长
3.3 months
期刊介绍: Drug Delivery is an open access journal serving the academic and industrial communities with peer reviewed coverage of basic research, development, and application principles of drug delivery and targeting at molecular, cellular, and higher levels. Topics covered include all delivery systems including oral, pulmonary, nasal, parenteral and transdermal, and modes of entry such as controlled release systems; microcapsules, liposomes, vesicles, and macromolecular conjugates; antibody targeting; protein/peptide delivery; DNA, oligonucleotide and siRNA delivery. Papers on drug dosage forms and their optimization will not be considered unless they directly relate to the original drug delivery issues. Published articles present original research and critical reviews.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信