Anti-idiotypic antibodies elicit anti-HIV-1-specific B cell responses.
Pia DosenovicAnna-Klara PetterssonAbigail WallEddy S ThientosapolJunli FengConnor WeidleKomal BhullarErvin E KaraHarald HartwegerJoy A PaiMatthew D GrayK Rachael ParksJustin James TaylorMarie PanceraLeonidas StamatatosMichel C NussenzweigAndrew T McGuirePublished in: The Journal of experimental medicine (2019)
Human anti-HIV-1 broadly neutralizing antibodies (bNAbs) protect against infection in animal models. However, bNAbs have not been elicited by vaccination in diverse wild-type animals or humans, in part because B cells expressing the precursors of these antibodies do not recognize most HIV-1 envelopes (Envs). Immunogens have been designed that activate these B cell precursors in vivo, but they also activate competing off-target responses. Here we report on a complementary approach to expand specific B cells using an anti-idiotypic antibody, iv8, that selects for naive human B cells expressing immunoglobulin light chains with 5-amino acid complementarity determining region 3s, a key feature of anti-CD4 binding site (CD4bs)-specific VRC01-class antibodies. In mice, iv8 induced target cells to expand and mature in the context of a polyclonal immune system and produced serologic responses targeting the CD4bs on Env. In summary, the results demonstrate that an anti-idiotypic antibody can specifically recognize and expand rare B cells that express VRC01-class antibodies against HIV-1.
Keyphrases
- antiretroviral therapy
- hiv infected
- hiv positive
- hiv testing
- human immunodeficiency virus
- wild type
- hepatitis c virus
- hiv aids
- endothelial cells
- men who have sex with men
- amino acid
- induced apoptosis
- induced pluripotent stem cells
- south africa
- machine learning
- high glucose
- cell death
- cell proliferation
- pluripotent stem cells
- adipose tissue
- nk cells
- oxidative stress
- skeletal muscle
- cell cycle arrest
- deep learning
- coronavirus disease
- neural network