A Fc engineering approach to define functional humoral correlates of immunity against Ebola virus.
A Fc engineering approach to define functional humoral correlates of immunity against Ebola virus.
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FC工程方法定义了针对埃博拉病毒的免疫力的功能体液相关性。
DOI:
10.1016/j.immuni.2021.03.009
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发表时间:
2021-04-13
期刊:
影响因子:
32.4
通讯作者:
Alter G
中科院分区:
文献类型:
--
作者:
Gunn BM;Lu R;Slein MD;Ilinykh PA;Huang K;Atyeo C;Schendel SL;Kim J;Cain C;Roy V;Suscovich TJ;Takada A;Halfmann PJ;Kawaoka Y;Pauthner MG;Momoh M;Goba A;Kanneh L;Andersen KG;Schieffelin JS;Grant D;Garry RF;Saphire EO;Bukreyev A;Alter G
Protective Ebola virus (EBOV) antibodies have neutralizing activity and induction of Fc-mediated innate immune effector functions. Efforts to enhance Fc-effector functionality often focus on maximizing antibody-dependent cellular cytotoxicity, yet distinct combinations of functions may be critical for antibody-mediated protection. As neutralizing antibodies have been cloned from EBOV disease survivors, we sought to identify survivor Fc-effector profiles to help guide Fc-optimization strategies. Survivors developed a range of functional antibody responses, and we therefore applied a rapid, high-throughput Fc-engineering platform to define the most protective profiles. We generated a library of Fc-variants with identical Fabs from an EBOV neutralizing antibody. Fc-variants with antibody-mediated complement deposition and moderate NK cell activity demonstrated complete protective activity in a stringent in vivo mouse model. Our findings highlight the importance of specific effector functions in antibody-mediated protection and the experimental platform presents a generalizable resource for identifying correlates of immunity to guide therapeutic antibody design. Gunn et al. profile Ebola virus disease survivors and apply a platform for engineering antibody Fc domains to define protective profiles. Fc-variants with complement deposition, yet moderate NK cell activity completely protected infected mice from disease. This experimental platform can be used for identifying correlates of immunity to other pathogens, and to guide therapeutic antibody design.
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影响因子:
32.4
作者:
Gilchuk P;Kuzmina N;Ilinykh PA;Huang K;Gunn BM;Bryan A;Davidson E;Doranz BJ;Turner HL;Fusco ML;Bramble MS;Hoff NA;Binshtein E;Kose N;Flyak AI;Flinko R;Orlandi C;Carnahan R;Parrish EH;Sevy AM;Bombardi RG;Singh PK;Mukadi P;Muyembe-Tamfum JJ;Ohi MD;Saphire EO;Lewis GK;Alter G;Ward AB;Rimoin AW;Bukreyev A;Crowe JE Jr
通讯作者:
Crowe JE Jr
影响因子:
64.5
作者:
Flyak AI;Shen X;Murin CD;Turner HL;David JA;Fusco ML;Lampley R;Kose N;Ilinykh PA;Kuzmina N;Branchizio A;King H;Brown L;Bryan C;Davidson E;Doranz BJ;Slaughter JC;Sapparapu G;Klages C;Ksiazek TG;Saphire EO;Ward AB;Bukreyev A;Crowe JE Jr
通讯作者:
Crowe JE Jr
影响因子:
82.9
作者:
Ackerman ME;Das J;Pittala S;Broge T;Linde C;Suscovich TJ;Brown EP;Bradley T;Natarajan H;Lin S;Sassic JK;O'Keefe S;Mehta N;Goodman D;Sips M;Weiner JA;Tomaras GD;Haynes BF;Lauffenburger DA;Bailey-Kellogg C;Roederer M;Alter G
通讯作者:
Alter G
影响因子:
3.7
作者:
Engler, Carola;Kandzia, Romy;Marillonnet, Sylvestre
通讯作者:
Marillonnet, Sylvestre
DOI:
10.1073/pnas.1609316113
发表时间:
2016-10-18
影响因子:
11.1
作者:
He, Wenqian;Tan, Gene S.;Miller, Matthew S.
通讯作者:
Miller, Matthew S.