CD4 T follicular helper cell dynamics during SIV infection
Constantinos Petrovas, Takuya Yamamoto, Michael Y. Gerner, Kristin L. Boswell, Kaska Wloka, Emily C. Smith, David R. Ambrozak, Netanya G. Sandler, Katherina J. Timmer, Xiaoyong Sun, Li Pan, Amanda Poholek, Srinivas S. Rao, Jason M. Brenchley, S. Munir Alam, Georgia D. Tomaras, Mario Roederer, Daniel C. Douek, Robert A. Seder, Ronald N. Germain, Elias K. Haddad, Richard A. Koup
Constantinos Petrovas, Takuya Yamamoto, Michael Y. Gerner, Kristin L. Boswell, Kaska Wloka, Emily C. Smith, David R. Ambrozak, Netanya G. Sandler, Katherina J. Timmer, Xiaoyong Sun, Li Pan, Amanda Poholek, Srinivas S. Rao, Jason M. Brenchley, S. Munir Alam, Georgia D. Tomaras, Mario Roederer, Daniel C. Douek, Robert A. Seder, Ronald N. Germain, Elias K. Haddad, Richard A. Koup
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Research Article

CD4 T follicular helper cell dynamics during SIV infection

Abstract

CD4 T follicular helper (TFH) cells interact with and stimulate the generation of antigen-specific B cells. TFH cell interaction with B cells correlates with production of SIV-specific immunoglobulins. However, the fate of TFH cells and their participation in SIV-induced antibody production is not well understood. We investigated the phenotype, function, location, and molecular signature of TFH cells in rhesus macaques. Similar to their human counterparts, TFH cells in rhesus macaques represented a heterogeneous population with respect to cytokine function. In a highly differentiated subpopulation of TFH cells, characterized by CD150lo expression, production of Th1 cytokines was compromised while IL-4 production was augmented, and cells exhibited decreased survival, cycling, and trafficking capacity. TFH cells exhibited a distinct gene profile that was markedly altered by SIV infection. TFH cells were infected by SIV; yet, in some animals, these cells actually accumulated during chronic SIV infection. Generalized immune activation and increased IL-6 production helped drive TFH differentiation during SIV infection. Accumulation of TFH cells was associated with increased frequency of activated germinal center B cells and SIV-specific antibodies. Therefore, chronic SIV does not disturb the ability of TFH cells to help B cell maturation and production of SIV-specific immunoglobulins.

Authors

Constantinos Petrovas, Takuya Yamamoto, Michael Y. Gerner, Kristin L. Boswell, Kaska Wloka, Emily C. Smith, David R. Ambrozak, Netanya G. Sandler, Katherina J. Timmer, Xiaoyong Sun, Li Pan, Amanda Poholek, Srinivas S. Rao, Jason M. Brenchley, S. Munir Alam, Georgia D. Tomaras, Mario Roederer, Daniel C. Douek, Robert A. Seder, Ronald N. Germain, Elias K. Haddad, Richard A. Koup

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Figure 1

Characterization of TFH cells in RM LNs.

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Characterization of TFH cells in RM LNs. (A) Flow cytometry contour plot...
(A) Flow cytometry contour plots, showing the expression of BCL-6 against either PD-1 or CXCR5 in CD4 T cells from 2 chronic SIV-infected LNs (left panel). Histograms depicting the expression of CCR7 in bulk CM (solid gray), BCL-6hiPD-1hi, and BCL-6hiCXCR5dim/hi CD4 T cells (right panel). The frequency of the gated populations is shown. (B) The gating scheme used for identification of particular CD4 populations in LN preparation is shown. The naive and CM cells were analyzed with respect to ICOS and CD150 expression. The naive population was used as reference for setting the gates. The frequency of the gated populations is shown. (C) Confocal images were collected from LN and SP tissues from SIV-negative (n = 2) RMs. The CD4, CD20, PD-1, and Ki67 markers were simultaneously analyzed, and their relative localization in 1 SIV-negative LN is shown (left panel). The boxed area is shown at higher magnification in the top right and the bottom images (scale bars: 100 μm). The relative distance of CD4 T cells, expressing different amounts of PD-1, from the “center” of the B cell follicle was calculated, and pooled data obtained from 2 SIV-negative SPs are shown (right panel). Each dot represents a cell or a definable part of a CD4 T cell. Bars depict mean ± 95% confidence intervals.