副镜
表位
抗体
CD3型
分子生物学
T细胞
生物
化学
细胞生物学
免疫学
免疫系统
CD8型
作者
Tatyana Khramova,Liubov Beduleva,Alexandr Sidorov,Alexey Terentiev,Igor Menshikov
标识
DOI:10.1080/08820139.2023.2250818
摘要
ABSTRACTBackground We have earlier discovered a new factor of autoimmunity downregulation, called regulatory rheumatoid factor (regRF). Being anti-idiotypic antibodies, regRF restricts the expansion of CD4+ T lymphocytes to the idiotype of which it is specific, according to the negative feedback principle. It has been shown that only activated CD4+ T lymphocytes are the target of regRF. However, it is still not clear the way regRF distinguishes activated cells from naive ones. RegRF molecules, apart from individual paratopes specific to unique sequences of B- and T-cell receptors, have a shared paratope. We assume that regRF by means of a shared paratope recognizes one of the surface activation molecules of CD4+ T lymphocytes and initiates the cell death. Programmed death-1 (PD-1) has been tested as a potential receptor of the shared regRF paratope and transmitter of the negative regRF signal into activated CD4+ T lymphocytes.Methods The specificity of the shared regRF paratope to PD-1 was determined by ELISA. T cell activation was performed with immobilized anti-CD3ε antibodies. Flow cytometry was used to study the effect of regRF on PD-1+CD4+ lymphocytes.Results We found that regRF binds to PD-1. IgG Fc fragments carrying epitopes specific to the shared paratope of regRF compete with PD-1 for binding to regRF. It follows that regRF recognizes specifically PD-1 by means of a shared paratope. RegRF-containing serum reduced the number of PD-1+CD4+ lymphocytes in proportion to their increase resulting from the action of anti-CD3ε antibodies.Conclusion RegRF uses PD-1 pathway to control activated CD4+ T lymphocytes.KEYWORDS: CD4 T lymphocytescontrol of autoimmunityIgG Fc fragmentsprogrammed death-1regulatory rheumatoid factor AcknowledgmentsWe are grateful to Natalia Makhankova for editorial assistance.Disclosure statementNo potential conflict of interest was reported by the author(s).CRediT authorship contribution statementConceptualization: Liubov Beduleva, Tatyana Khramova; Investigation: Tatyana Khramova, Liubov Beduleva, Alexandr Sidorov, Alexey Terentiev; Writing – Original Draft: Liubov Beduleva, Tatyana Khramova; Writing – Review & Editing: Igor Menshikov. All authors read and approved the final version of the manuscript.Data availability statementData will be made available on request.Additional informationFundingThis work was supported by the Ministry of Science and Higher Education of the Russian Federation [project number 0827-2020-0012].
科研通智能强力驱动
Strongly Powered by AbleSci AI