BKV Clearance Time Correlates With Exhaustion State and T-Cell Receptor Repertoire Shape of BKV-Specific T-Cells in Renal Transplant Patients

Abstract

Reactivation of the BK polyomavirus is known to lead to severe complications in kidney transplant patients. The current treatment strategy relies on decreasing the immunosuppression to allow the immune system to clear the virus. Recently, we demonstrated a clear association between the resolution of BKV reactivation and reconstitution of BKV-specific CD4⁺ T-cells. However, which factors determine the duration of viral infection clearance remains so far unclear. Here we apply a combination of in-depth multi-parametric flow cytometry and NGS-based CDR3 beta chain receptor repertoire analysis of BKV-specific T-cells to a cohort of 7 kidney transplant patients during the clinical course of BKV reactivation. This way we followed TCR repertoires at single clone levels and functional activity of BKV-specific T-cells during the resolution of BKV infection. The duration of BKV clearance did not depend on the number of peripheral blood BKV-specific T-cells nor on a few immunodominant BKV-specific T-cell clones. Rather, the T-cell receptor repertoire diversity and exhaustion status of BKV-specific T-cells affected the duration of viral clearance: high clonotype diversity and lack of PD1 and TIM3 exhaustion markers on BKV-specific T-cells was associated with short clearance time. Our data thus demonstrate how the diversity and the exhaustion state of the T-cells can determine the clinical course of BKV infection.

Keywords: BKV; T-cell; TCR repertoire; diversity; exhaustion; immunology.

Figure 1

Recipient and donor HLA type. HLA type of the patients and their kidney donors. Black square indicate presence of the HLA type, white indicate absence.

Figure 2

Difference in BKV viremia clearance time. (A) BKV viremia remission phase for the individual patients in the cohort. The dotted line indicates the best linear fit from the time point before BKV-reactivation to highest BKV load and from the highest BKV load to the first time point with BKV viremia below detection limit. R² indicate the goodness of fit for the time of increasing BKV viremia and for the time with decreasing viremia. (B) Association of time of increasing BKV viremia and the time to clear the virus. (C) Clearance time calculated from the slope of a straight line from the highest BKV value to the first time point with BKV viremia below detection limit.

Figure 3

Clearance time is not explained by magnitude and phenotypic characteristics of BKV-specific T-cells. (A) Gating strategy applied in the current study. (B,C) Pearson correlation of clearance time with BKV-specific CD4⁺ T-cells (B) and BKV-specific CD8⁺ T-cells (C). Each point represents a patient in the study and the dotted line the best linear fit.

Figure 4

Tracking of BKV-specific TCR clonotypes. BKV-specific TCR clonotypes were obtained from IFNγ producing T-cells after stimulation with BKV overlapping peptide pools. TCR clonotypes from whole blood CD4⁺ and CD8⁺ subsets were obtained at different stages of viral clearance. The overlap between the clonotypes of whole blood samples and clonotypes of the IFNγ producing T-cells were identified as BKV-specific T-cells in circulation. The abundance of these circulating BKV-specific T-cells were subsequently compared at distinct stages of viral clearance. Black bars indicate the frequency of clonotypes gained from the earlier to the later time point. Dark gray indicates the frequency of clonotypes found at both time points. Light gray indicates the frequency of clonotypes that has disappeared from the earlier time point to the later. (A) Relative change in BKV-specific clonotypes from the initiation of viral clearance (before) to the resolution of BKV infection (after). (B) Relative change in BKV-specific clonotypes from T-cells obtained during the clearance phase (mid) to the resolution of BKV infection (after). The bars indicate the frequency of clonotypes gained, lost, or sustained as the viral clearance progressed, that is, clonotypes that were present after viral clearance, but not before; clonotypes that were present at the beginning of the clearance phase but not after; and clonotypes present before and after viral clearance.

Figure 5

Repertoire analysis of BKV-specific T-cells. BKV-specific T-cells were isolated and subjected to clonotype analysis. (A) Population diversity by the Shannon index and the inverse Berger-Parker index (B). (C) Comparison of total BKV-specific CD4⁺ T-cells (left panel) and CD8⁺ T-cells (right panel), for patient 2 and the other patients. (D) Pearson correlation of clearance time and cellular exhaustion as marked by PD1 and TIM3 among activated CD4⁺ T-cells, see Supplementary Figures 2–8 for details. Presented is the ratio of stimulated to negative control (DMSO treated). Each point represents a patient in the study and the dotted line the best linear fit.

Figure 6

Summary of hypothesis. Low exhaustion and high TCRβ diversity results in shorter clearance time (black line), while high exhaustion and low TCRβ diversity results in shorter clearance time (gray line).