Thresholds for post-rebound SHIV control after CCR5 gene-edited autologous hematopoietic cell transplantation

  1. E Fabian Cardozo-Ojeda  Is a corresponding author
  2. Elizabeth R Duke
  3. Christopher W Peterson
  4. Daniel B Reeves
  5. Bryan T Mayer
  6. Hans-Peter Kiem
  7. Joshua T Schiffer  Is a corresponding author
  1. Vaccine and Infectious Disease Division, University of Washington, United States
  2. Department of Medicine, University of Washington, United States
  3. Clinical Research Division, Fred Hutchinson Cancer Research Center, United States
  4. Stem Cell and Gene Therapy Program, Fred Hutchinson Cancer Research Center, United States
  5. Department of Pathology, University of Washington, United States
7 figures and 1 additional file

Figures

Study design and mathematical modeling.

(A) Twenty-two pig-tailed macaques were infected with SHIV and suppressed with ART. Next, 17/22 underwent hematopoietic stem and progenitor cell (HSPC) transplantation following myeloablative …

Figure 2 with 1 supplement
Post-transplantation, pre-ATI CD4+ and CD8+ T cell dynamics.

(A) Empirical data for peripheral CD4+ CCR5+ (top row), CD4+CCR5- (middle row), and CD8+ T cell counts (bottom row) for control (blue), wild-type (red), and ΔCCR5 (green) transplantation groups. …

Figure 2—figure supplement 1
CD4+ and CD8+ T cell levels pre-ATI in control group (n = 5) at times relative to post-transplantation in WT and ΔCCR5 transplant groups.

Range of blood (A) CD4+ and (B) CD8+ T cell counts using all data points for the period before ATI in control animals (p-value calculated with a paired t-test for averaged measurements from a time …

Figure 3 with 4 supplements
Mathematical model of T cell reconstitution after hematopoietic stem and progenitor cell (HSPC) transplantation.

(A) Schematics of the model. Each circle represents a cell compartment: T represents the HSPCs from the transplant; P, the progenitor cells in bone marrow (BM) and thymus; S and N, CD4+CCR5+ and CD4+

Figure 3—source code 1

Best model file for T cell reconstitution in Monolix format.

https://cdn.elifesciences.org/articles/57646/elife-57646-fig3-code1-v1.zip
Figure 3—source code 2

R code for plots in Figure 3.

https://cdn.elifesciences.org/articles/57646/elife-57646-fig3-code2-v1.zip
Figure 3—source data 1

Values of the fraction of protected cells in transplant product fp, dose or number of hematopoietic stem and progenitor cell (HSPCs) in transplant product D and time of transplantation tx of each animal for model fitting and projections.

We assumed animal weight of 5 Kg.

https://cdn.elifesciences.org/articles/57646/elife-57646-fig3-data1-v1.docx
Figure 3—source data 2

Competing models for fitting T cell reconstitution with respective AIC values.

Best fit in bold-red (lowest AIC). The AIC values presented for each statistical assumption is the lowest of 10 runs of the SAEM algorithm with different randomly selected initial guesses.

https://cdn.elifesciences.org/articles/57646/elife-57646-fig3-data2-v1.docx
Figure 3—source data 3

Population parameter estimates for the best fits of the model in Equation 2 in the main text (lowest AIC in Figure 3—source data 2) to the T cell reconstitution dynamics.

RSE: relative standard error. Empty fields represent a standard deviation of random effects, σψ, fixed to zero. Values of ψ¯ for Kp,N(t0),S(t0),M(t0), and E(t0) shown here are in log10 cell counts/μL assuming a blood volume of of 3 × 105 μL (calculated assuming blood:weight ratio of 60 mL/kg and body weight of 5 kg). Red values represent an RSE greater than 100% implying that the number of data points may not be enough to estimate the respective parameter.

https://cdn.elifesciences.org/articles/57646/elife-57646-fig3-data3-v1.docx
Figure 3—source data 4

Individual parameter estimates for the best fits of the model in Equation 2 in the main text (lowest AIC in Figure 3—source data 2) to the T cell reconstitution dynamics.

Values obtained for N(t0),S(t0),M(t0), and E(t0) shown here are in log10 cell counts/μL assuming a blood volume of of 3 × 105 μL (calculated assuming blood:weight ratio of 60 mL/kg and body weight of 5 kg). Initial values for the control group where obtained assuming steady state.

https://cdn.elifesciences.org/articles/57646/elife-57646-fig3-data4-v1.docx
Figure 3—source data 5

Population parameter estimates for the best fits used in the R code for Figure 3.

https://cdn.elifesciences.org/articles/57646/elife-57646-fig3-data5-v1.zip
Figure 3—figure supplement 1
Individual fits of the best model to the blood T cell observations pre-ATI in control group from a time relative to post-transplantation in transplant groups.

Empirical data for peripheral T cell subset counts (blue data points) and best fits of the model (black lines) in Equation 2 in the main text to all blood T cell subsets before/after ATI for the …

Figure 3—figure supplement 2
Individual fits of the best model to the blood T cell observations post-transplantation, pre-ATI for the wild-type-transplant group.

Empirical data for peripheral T cell subset counts and plasma viral load (red data points) and best fits of the model (black lines) in Equation 2 in the main text to all blood T cell subsets before …

Figure 3—figure supplement 3
Individual fits of the best model to the blood T cell observations post-transplantation, pre-ATI for the ΔCCR5-transplant group.

Empirical data for peripheral T cell subset counts and plasma viral load (green data points) and best fits of the model (black lines) in Equation 2 in the main text to all blood T cell subsets …

Figure 3—figure supplement 4
Predictions of the best model for the contributors to cell expansion in CD8+ TEM cells in animals from the transplant groups.

Solid line represents the total number of cells that proliferate over time r^e(1Np1+N+S+M+EKe)E. Dashed lines indicate the number of exogenous cells differentiated from Tnaive and TCM (λmM) over time using the maximum …

Figure 4 with 1 supplement
Plasma viral load and CD4+ T cell kinetics after ATI.

(A) Empirical data for viral load (top row) and peripheral T cell counts (middle and bottom rows) for control (blue), wild-type (red) and ΔCCR5 (green) transplantation groups. Each data point shape …

Figure 4—figure supplement 1
Blood CD4+CCR5+ and CD4+CCR5- T cell kinetics post-ATI.

(A) Distribution of the CD4+CCR5+ T-cell nadir post-ATI normalized relative to the CD4+CCR5+ concentration at ATI. (B) Distribution of the CD4+CCR5- T-cell nadir post-ATI normalized relative to the …

Figure 5 with 3 supplements
Mathematical model of virus and T cell dynamics following ATI.

(A) Model: Susceptible cells, S, are infected by the virus, V, at rate β. Ip represents the fraction τ of the infected cells that produce virus, and, Iu, the other fraction that becomes …

Figure 5—source code 1

Best model file for T cell and virus dynamics from acute infection after ATI in Monolix format.

https://cdn.elifesciences.org/articles/57646/elife-57646-fig5-code1-v1.zip
Figure 5—source code 2

R code for plots in Figure 5B.

https://cdn.elifesciences.org/articles/57646/elife-57646-fig5-code2-v1.zip
Figure 5—source code 3

R code for plots and tests in Figure 5C–D.

https://cdn.elifesciences.org/articles/57646/elife-57646-fig5-code3-v1.zip
Figure 5—source data 1

Competing models for fitting T cell and viral dynamics (Equations 2-3 in main text) using the best model in Figure 3—source data 2 and fixing parameter values as in Figure 3—source data 3, with AIC values.

Best fit in bold-red (lowest AIC).

https://cdn.elifesciences.org/articles/57646/elife-57646-fig5-data1-v1.docx
Figure 5—source data 2

Population parameter estimates for the fits of the model with lowest AIC in Figure 5—source data 1 to the T cell and virus dynamics.

RSE: relative standard error. Empty fields represent cases when the standard deviation of random effects, σψ, was fixed to zero. Values of ψ¯ for β,ω4,ω8, and I50 shown here are transformed assuming a blood volume of 3 × 105 μL (calculated assuming blood:weight ratio of 60 mL/kg and body weight of 5 kg). Red values represent an RSE greater than 100% implying that the number of data points may not be enough to estimate the respective parameter.

https://cdn.elifesciences.org/articles/57646/elife-57646-fig5-data2-v1.docx
Figure 5—source data 3

Individual parameter estimates for the fits of the model in Equations 2-3 in main text (lowest AIC in Figure 5—source data 1) to the T cell and virus dynamics.

Values of ψ¯ for β,ω4,ω8, and I50 shown here are transformed assuming a blood volume of 3 × 105 μL (calculated assuming blood:weight ratio of 60 mL/kg and body weight of 5 kg). Shown are individual estimates for animals that continued study after ATI.

https://cdn.elifesciences.org/articles/57646/elife-57646-fig5-data3-v1.docx
Figure 5—source data 4

Individual parameter estimates obtained from Monolix for the best fits used in the R code for Figure 5.

https://cdn.elifesciences.org/articles/57646/elife-57646-fig5-data4-v1.zip
Figure 5—figure supplement 1
Individual fits of the best model to the blood T cell and viral load observations before/after ATI for control group.

Empirical data for peripheral T cell subset counts and plasma viral load (blue data points) and best fits of the model in Equations 2 and 3 to all blood T cell subsets before/after ATI for the …

Figure 5—figure supplement 2
Individual fits of the best model to the blood T cell and viral load observations before/after ATI for the wild-type-transplant group.

Empirical data for peripheral T cell subset counts and plasma viral load (red data points) and best fits of the model in Equations 2 and 3 to all viral load observations and blood T cell subsets …

Figure 5—figure supplement 3
Individual fits of the best model to the blood T cell and viral load observations before/after ATI for the ΔCCR5-transplant group.

Empirical data for peripheral T cell subset counts and plasma viral load (green data points) and best fits of the model in Equations 2 and 3 to all viral load observations and blood T cell subsets …

Figure 6 with 2 supplements
Model predictions of factors governing post-rebound viral control after CCR5 gene-edited hematopoietic stem and progenitor cell (HSPC) transplant.

(A) Predictions for plasma viral loads post-ATI using the optimized mathematical model. Here, Reff=RT(1fpDD+Pr) and is the composite determinant of viral control. Parameter estimates for animal A11219 (Figure …

Figure 6—figure supplement 1
Model predictions for post-rebound viral control after CCR5 gene-edited hematopoietic stem and progenitor cell (HSPC) transplantation based on Reff.

Model predictions of the effective reproductive ratio Reff=RT(1fpDD+Pr)  that lead to post-ATI viral control or not. Reff was computed using varying values of fp: fraction of HSPCs in transplant, D: total amount of …

Figure 6—figure supplement 2
Model predictions of the fraction of protected hematopoietic stem and progenitor cell (HSPCs) in the transplant fp (y-axis) and the fraction of transplanted HSPCs with respect to the total infused plus remaining post-TBI HSPCs D:Pr (x-axis) required for spontaneous viral control.

Blue color represents the parameter space with post-ATI viral control or Reff<1. Yellow-to-red colors represent the parameter space with no control or Reff>1. Data points (green and red shapes) represent …

Model predictions of time to post-ATI viral control given varying times for the start of ATI.

(A-B) Examples of projected (A) viral load and (B) total, modified and unmodified CD4+ CCR5- (solid) and ΔCCR5 CD4+ T cells (dashed) from the model for animal A11219 when fp=0.95, D=108.5 HSPCs and Pr=107 HSPCs, …

Figure 7—source data 1

Results from all simulations varying time to ATI.

https://cdn.elifesciences.org/articles/57646/elife-57646-fig7-data1-v1.zip

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