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Machine Learning to Quantify In Situ Humoral Selection in Human Lupus Tubulointerstitial Inflammation
Frontiers in Immunology ( IF 7.3 ) Pub Date : 2020-10-27 , DOI: 10.3389/fimmu.2020.593177
Andrew J Kinloch 1 , Yuta Asano 1 , Azam Mohsin 1 , Carole Henry 1 , Rebecca Abraham 1 , Anthony Chang 2 , Christine Labno 3 , Patrick C Wilson 1 , Marcus R Clark 1
Affiliation  

In human lupus nephritis, tubulointerstitial inflammation (TII) is associated with in situ expansion of B cells expressing anti-vimentin antibodies (AVAs). The mechanism by which AVAs are selected is unclear. Herein, we demonstrate that AVA somatic hypermutation (SHM) and selection increase affinity for vimentin. Indeed, germline reversion of several antibodies demonstrated that higher affinity AVAs can be selected from both low affinity B cell germline clones and even those that are strongly reactive with other autoantigens. While we demonstrated affinity maturation, enzyme-linked immunosorbent assays (ELISAs) suggested that affinity maturation might be a consequence of increasing polyreactivity or even non-specific binding. Therefore, it was unclear if there was also selection for increased specificity. Subsequent multi-color confocal microscopy studies indicated that while TII AVAs often appeared polyreactive by ELISA, they bound selectively to vimentin fibrils in whole cells or inflamed renal tissue. Using a novel machine learning pipeline (CytoSkaler) to quantify the cellular distribution of antibody staining, we demonstrated that TII AVAs were selected for both enhanced binding and specificity in situ. Furthermore, reversion of single predicted amino acids in antibody variable regions indicated that we could use CytoSkaler to capture both negative and positive selection events. More broadly, our data suggest a new approach to assess and define antibody polyreactivity based on quantifying the distribution of binding to native and contextually relevant antigens.



中文翻译:

机器学习量化人类狼疮小管间质炎症的原位体液选择

在人类狼疮性肾炎中,肾小管间质性炎症(TII)与 原位表达抗波形蛋白抗体(AVA)的B细胞扩增。选择AVA的机制尚不清楚。在本文中,我们证明了AVA体细胞超突变(SHM)和选择增加了对波形蛋白的亲和力。确实,几种抗体的种系还原证明,可以从低亲和力B细胞种系克隆中选择高亲和力的AVA,甚至可以与其他自身抗原发生强烈反应的克隆也可以选择。虽然我们证明了亲和力成熟,但酶联免疫吸附测定(ELISA)表明亲和力成熟可能是多反应性甚至非特异性结合增加的结果。因此,尚不清楚是否还有选择来增加特异性。随后的多色共聚焦显微镜研究表明,尽管TII AVA通常通过ELISA表现出多反应性,它们选择性结合至全细胞或发炎的肾组织中的波形蛋白原纤维。使用新颖的机器学习管道(CytoSkaler)量化抗体染色的细胞分布,我们证明了选择TII AVA具有增强的结合力和特异性原位。此外,抗体可变区中单个预测氨基酸的还原表明我们可以使用CytoSkaler捕获阴性和阳性选择事件。更广泛地说,我们的数据提出了一种新的方法,可以基于量化与天然和上下文相关抗原的结合分布来评估和定义抗体多反应性。

更新日期:2020-11-27
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