Cyrillus Tan Zhixin, Lux Anja, Biburger Markus, Varghese Prabha, Lees Stephen, Nimmerjahn Falk, Meyer Aaron S
Bioinformatics Interdepartmental Program, University of California, Los Angeles (UCLA).
Department of Genetics, Friedrich-Alexander-University of Erlangen-Nürnberg.
bioRxiv. 2023 Feb 15:2023.02.15.528730. doi: 10.1101/2023.02.15.528730.
Immunoglobulin (Ig)G antibodies coordinate immune effector responses by selectively binding to target antigens and then interacting with various effector cells via the Fcγ receptors. The Fc domain of IgG can promote or inhibit distinct effector responses across several different immune cell types through variation based on subclass and Fc domain glycosylation. Extensive characterization of these interactions has revealed how the inclusion of certain Fc subclasses or glycans results in distinct immune responses. During an immune response, however, IgG is produced with mixtures of Fc domain properties, so antigen-IgG immune complexes are likely to almost always be comprised of a combination of Fc forms. Whether and how this mixed composition influences immune effector responses has not been examined. Here, we measured Fcγ receptor binding to immune complexes of mixed Fc domain composition. We found that the binding properties of the mixed-composition immune complexes fell along a continuum between those of the corresponding pure cases. Binding quantitatively matched a mechanistic binding model, except for several low-affinity interactions mostly involving IgG2. We found that the affinities of these interactions are different than previously reported, and that the binding model could be used to provide refined estimates of these affinities. Finally, we demonstrated that the binding model can predict effector-cell elicited platelet depletion in humanized mice, with the model inferring the relevant effector cell populations. Contrary to the previous view in which IgG2 poorly engages with effector populations, we observe appreciable binding through avidity, but insufficient amounts to observe immune effector responses. Overall, this work demonstrates a quantitative framework for reasoning about effector response regulation arising from IgG of mixed Fc composition.
The binding behavior of mixed Fc immune complexes is a blend of the binding properties for each constituent IgG species.An equilibrium, multivalent binding model can be generalized to incorporate immune complexes of mixed Fc composition.Particularly for low-affinity IgG-Fcγ receptor interactions, immune complexes provide better estimates of affinities.The FcγR binding model predicts effector-elicited cell clearance in humanized mice.
免疫球蛋白（Ig）G抗体通过选择性结合靶抗原，然后经由Fcγ受体与各种效应细胞相互作用，来协调免疫效应反应。IgG的Fc结构域可通过基于亚类和Fc结构域糖基化的变异，在几种不同免疫细胞类型中促进或抑制不同的效应反应。对这些相互作用的广泛表征揭示了某些Fc亚类或聚糖的存在如何导致不同的免疫反应。然而，在免疫反应过程中，产生的IgG具有多种Fc结构域特性，因此抗原-IgG免疫复合物很可能几乎总是由多种Fc形式组合而成。这种混合组成是否以及如何影响免疫效应反应尚未得到研究。在此，我们测量了Fcγ受体与混合Fc结构域组成的免疫复合物的结合情况。我们发现，混合组成免疫复合物的结合特性介于相应纯组分情况之间。除了一些主要涉及IgG2的低亲和力相互作用外，结合在数量上符合一个机械结合模型。我们发现这些相互作用的亲和力与先前报道的不同，并且该结合模型可用于对这些亲和力进行精确估计。最后，我们证明该结合模型可以预测效应细胞在人源化小鼠中引发的血小板消耗情况，该模型还能推断相关的效应细胞群体。与之前认为IgG2与效应细胞群体结合不佳的观点相反，我们观察到通过亲和力有明显的结合，但量不足以观察到免疫效应反应。总体而言，这项工作展示了一个定量框架，用于推断由混合Fc组成的IgG引起的效应反应调节。
混合Fc免疫复合物的结合行为是每种组成IgG种类结合特性的混合。一个平衡的多价结合模型可以推广到包含混合Fc组成的免疫复合物。特别是对于低亲和力的IgG-Fcγ受体相互作用，免疫复合物能提供更好的亲和力估计。FcγR结合模型可预测人源化小鼠中效应细胞引发的细胞清除情况。
