Can Non-lytic CD8+ T Cells Drive HIV-1 Escape?

The CD8+ T cell effector mechanisms that mediate control of HIV-1 and SIV infections remain poorly understood. Recent work suggests that the mechanism may be primarily non-lytic. This is in apparent conflict with the observation that SIV and HIV-1 variants that escape CD8+ T cell surveillance are frequently selected. Whilst it is clear that a variant that has escaped a lytic response can have a fitness advantage compared to the wild-type, it is less obvious that this holds in the face of non-lytic control where both wild-type and variant infected cells would be affected by soluble factors. In particular, the high motility of T cells in lymphoid tissue would be expected to rapidly destroy local effects making selection of escape variants by non-lytic responses unlikely. The observation of frequent HIV-1 and SIV escape poses a number of questions. Most importantly, is the consistent observation of viral escape proof that HIV-1- and SIV-specific CD8+ T cells lyse infected cells or can this also be the result of non-lytic control? Additionally, the rate at which a variant strain escapes a lytic CD8+ T cell response is related to the strength of the response. Is the same relationship true for a non-lytic response? Finally, the potential anti-viral control mediated by non-lytic mechanisms compared to lytic mechanisms is unknown. These questions cannot be addressed with current experimental techniques nor with the standard mathematical models. Instead we have developed a 3D cellular automaton model of HIV-1 which captures spatial and temporal dynamics. The model reproduces in vivo HIV-1 dynamics at the cellular and population level. Using this model we demonstrate that non-lytic effector mechanisms can select for escape variants but that outgrowth of the variant is slower and less frequent than from a lytic response so that non-lytic responses can potentially offer more durable control.


Radius of Secretion number of cells protected
Supplementary Figure S10. Immune control exerted by a non-lytic response that reduces infectivity. Varying the magnitude of the CD8+ T cell response (row 1), the probability of recognition (row 2) and the radius of secretion (row 3) had little impact on the % of infected cells at set point (column 1) despite a large impact on the number of cells protected (column 2). Only in extreme cases e.g. increasing the probability of recognition 1000-fold (row 2) was there a significant impact on % infected cells (P=3.2x10 -9 , H0: no difference in % infected cells between probability of recognition =0.001 and probability of recognition=1, Wilcoxon Mann Whitney unpaired two-tailed test).

Supplementary Figure S11. Immune control exerted by a non-lytic response that reduces virion production.
Parameter changes which readily boost a lytic CTL response (e.g. increasing the probability of recognition from 0.002 to 0.003) had no significant impact on the protection conferred by a non-lytic response that blocks virion production (protection measured as % of infected cells at set point). However, the non-lytic response that blocks virion production (this figure) was considerably easier to boost than the non-lytic response that reduces infectivity (Supplementary Figure S10). In all cases, increasing the duration of the protective effect so that once protected, cells were protected for the duration of the simulation ("infinite duration"), significantly boosted the nonlytic response. P values, H0: there is no difference in the % of productively infected cells; Magnitude

Equivalence of non-lytic models in chronic infection
It can readily be shown that under a quasi-equilibrium between infected cells and free virus which is assumed to hold during the chronic phase of infection, a non-lytic model where the CD8+ T cells reduce viral production and a non-lytic model where CD8+ T cells reduce infection of new targets produce the same dynamics for the population of productively infected cells.
The dynamics of a non-lytic model where viral infection is decreased can be described by The dynamics of a non-lytic model where viral production is decreased can be described by where β is the infection rate, p is the production rate of free virions, c is the clearance rate of free virions, S is the number of susceptible target cells, T* is the number of productively infected cells, V is the number of free virions, E is the number of virus-specific CD8+T cells, η parameterises the effect of effector CD8+ T cells on the virus and δ I is the death rate of productively infected cells.
The quasi-steady assumption for the non-lytic model where viral infection is decreased results in: while the quasi-steady state assumption for the non-lytic model where viral production is decreased results in: Substituting (3) and (4) into the equations governing the behaviour of productively infected cells (T*), (1) and (2) respectively, both equations can be rewritten: .  Table S1 Initial cell populations. Percentages refer to the number of total grid cells apart from the epitope-specific CD8+ T cell population that is given as a percentage of the splenocytes population.

Influx of infected CD4+ T cells
The CD4+ T cells entering the grid with a probability, p influx , can be uninfected or infected (either with the wild-type or the variant strain). The following equations describe the set of probabilities which define whether the CD4+ T cell that entered the grid will be uninfected, p u , or infected (with the wild-type, p w , or the variant, p v , strain). These probabilities depend on the current population of uninfected, N u , wild-type infected, N w and variant infected, N V , cells present on the grid as well as their respective lifespans, L u , L w and L v . We consider L w =L v .