Esrafili Arezoo, Talitckii Aleksandr, Kupfer Joshua, Thumsi Abhirami, Jaggarapu Madhan Mohan Chandra Sekhar, Dugoni Margaret, Jensen Gregory, Peet Matthew M, Holloway Julianne L, Acharya Abhinav P
Chemical Engineering, School for the Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, Arizona, USA.
Aerospace and Mechanical Engineering, School for the Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, Arizona, USA.
J Biomed Mater Res A. 2025 Jul;113(7):e37962. doi: 10.1002/jbm.a.37962.
Vaccine development requires innovative approaches to improve immune responses while reducing the number of immunizations. In this study, we explore the impact of controlled antigen release on immune activation and regulation using programmable infusion pumps and biodegradable biomaterials in OT-II and wild-type mice to understand the adaptive immune response through controlled antigen delivery in the absence of adjuvant. Ovalbumin (OVA) was delivered via an exponentially decreasing profile, mimicking clearance of infection, and an exponentially increasing profile, mimicking induction of infection. Exponentially decreasing OVA delivery through infusion pumps promoted regulatory T-cell (Treg) activation in secondary lymphoid organs and suppressed pro-inflammatory T-helper type 17 (Th17) responses in blood. An exponentially increasing OVA profile enhanced central memory T-cell (TCM) populations in submandibular blood and humoral immune responses in cardiac blood serum, demonstrating distinct immune modulation based on release kinetics. OVA was also delivered using a biodegradable PLGA-PEG-PLGA (PPP) depot, which provided controlled OVA release in an exponentially decreasing pattern. PPP-OVA treatment significantly reduced the frequency of pro-inflammatory T-helper type 1 (Th1) cells while increasing CD25FOXP3 Treg cells in the spleen. Moreover, to identify T-cell populations that most accurately characterize the divergence in Treg and T-helper response to OVA kinetics, a Sequential Feature Selection (SFS) algorithm with Machine Learning (ML) models was used. ML algorithms identified gMFI of RORγt as a key feature in submandibular blood and the ratio of gMFI of FOXP3 to GATA3 as the marker that was significantly changed by treatments in inguinal lymph nodes (iLN) when infusion pumps were used to deliver OVA. In addition, ML-based SFS identified CD25FOXP3 regulatory T cells as the most important feature, influencing the expression of other cell types in both inguinal lymph nodes (iLN) and spleen when PPP was used to deliver OVA. This finding suggests that the exponentially decreasing profile may generate anti-inflammatory responses. Overall, these findings suggest that controlled antigen delivery enhances immune regulation and memory T cells, providing new insights into immune responses mediated by the release kinetics.
疫苗研发需要创新方法来提高免疫反应,同时减少免疫接种次数。在本研究中,我们使用可编程输液泵和可生物降解生物材料,在OT-II小鼠和野生型小鼠中探索可控抗原释放对免疫激活和调节的影响,以了解在无佐剂情况下通过可控抗原递送产生的适应性免疫反应。卵清蛋白(OVA)通过指数递减曲线递送,模拟感染清除,以及指数递增曲线递送,模拟感染诱导。通过输液泵进行指数递减的OVA递送促进了二级淋巴器官中调节性T细胞(Treg)的激活,并抑制了血液中促炎性辅助性T细胞17(Th17)反应。指数递增的OVA曲线增强了下颌下血液中的中枢记忆T细胞(TCM)群体以及心脏血液血清中的体液免疫反应,表明基于释放动力学存在不同的免疫调节。OVA也使用可生物降解的PLGA-PEG-PLGA(PPP)储库进行递送,其以指数递减模式提供可控的OVA释放。PPP-OVA处理显著降低了促炎性辅助性T细胞1型(Th1)的频率,同时增加了脾脏中CD25FOXP3 Treg细胞。此外,为了确定最准确表征Treg和辅助性T细胞对OVA动力学反应差异的T细胞群体,使用了带有机器学习(ML)模型的序列特征选择(SFS)算法。ML算法确定RORγt的几何平均荧光强度(gMFI)是下颌下血液中的关键特征,当使用输液泵递送OVA时,腹股沟淋巴结(iLN)中FOXP3与GATA3的gMFI比值是受处理显著改变的标志物。此外,基于ML的SFS确定CD25FOXP3调节性T细胞是最重要的特征,当使用PPP递送OVA时,其影响腹股沟淋巴结(iLN)和脾脏中其他细胞类型的表达。这一发现表明指数递减曲线可能产生抗炎反应。总体而言,这些发现表明可控抗原递送增强了免疫调节和记忆T细胞,为释放动力学介导的免疫反应提供了新的见解。