Predictors of Hepatitis B Cure Using Gene Therapy to Deliver DNA Cleavage Enzymes: A Mathematical Modeling Approach

<div><p>Most chronic viral infections are managed with small molecule therapies that inhibit replication but are not curative because non-replicating viral forms can persist despite decades of suppressive treatment. There are therefore numerous strategies in development to eradicate all non-replicating viruses from the body. We are currently engineering DNA cleavage enzymes that specifically target hepatitis B virus covalently closed circular DNA (HBV cccDNA), the episomal form of the virus that persists despite potent antiviral therapies. DNA cleavage enzymes, including homing endonucleases or meganucleases, zinc-finger nucleases (ZFNs), TAL effector nucleases (TALENs), and CRISPR-associated system 9 (Cas9) proteins, can disrupt specific regions of viral DNA. Because DNA repair is error prone, the virus can be neutralized after repeated cleavage events when a target sequence becomes mutated. DNA cleavage enzymes will be delivered as genes within viral vectors that enter hepatocytes. Here we develop mathematical models that describe the delivery and intracellular activity of DNA cleavage enzymes. Model simulations predict that high vector to target cell ratio, limited removal of delivery vectors by humoral immunity, and avid binding between enzyme and its DNA target will promote the highest level of cccDNA disruption. Development of de novo resistance to cleavage enzymes may occur if DNA cleavage and error prone repair does not render the viral episome replication incompetent: our model predicts that concurrent delivery of multiple enzymes which target different vital cccDNA regions, or sequential delivery of different enzymes, are both potentially useful strategies for avoiding multi-enzyme resistance. The underlying dynamics of cccDNA persistence are unlikely to impact the probability of cure provided that antiviral therapy is given concurrently during eradication trials. We conclude by describing experiments that can be used to validate the model, which will in turn provide vital information for dose selection for potential curative trials in animals and ultimately humans.</p></div

Number of doses prior to viral cure.

<p>Number of doses prior to viral cure.</p

Intracellular HBV DNA cleavage enzyme pharmacodynamics.

<p>(a) An HBV infected cell with three cccDNA molecules (green circles), and delivery of DNA cleavage enzyme containing vectors (red viruses) can transition to several states where none, some, or all of the episomes are eliminated and/or become resistant to the cleavage enzyme. Arrow thickness denotes the relative probability of each event. (b) Cleavage enzymes (red wavy lines) may bind HBV cccDNA molecules cooperatively, whereby binding of one enzyme to its target sequence enhances binding of other enzymes to the same target on separate episomes. (c) Cleavage enzymes (multi-colored wavy lines) that target separate regions within episomes (thick colored lines of corresponding color) may bind HBV cccDNA molecules cooperatively, whereby binding of one enzyme to its target sequence enhances binding of other enzymes to separate sequences on the same episome.</p

High vector delivery, effective enzyme-HBV binding and cooperative binding predict effective cccDNA clearance.

<p>All simulations of HBV eradication show results of ten weekly doses of therapy. A single enzyme is used and <i>de novo</i> resistance is ignored. (a) Each data point represents number of remaining infected cells (y-axis) after a simulation with one of 80 unique parameter sets. x-axis is functional multiplicity of infection (fMOI, separated by vertical black lines and not according to scale). Five different values for enzyme-DNA binding dissociation constant (d = 0.008, 0.04, 0.2, 1 & 5) are represented by blue, green, yellow, orange & red respectively; squares, diamonds, circles and triangles represent different values for the Hill coefficient (h = 0.5, 1, 2, 5). High fMOI, low binding dissociation constant and under conditions of moderate delivery and enzyme-DNA binding, high Hill coefficient (cooperative binding), predict high therapeutic potency. (b) Simulations of 10 weekly doses of a potent regimen (fMOI = 5.0, d = 0.04, h = 2, <i>de novo</i> resistance rate (Ψ) = 0) with decreasing fMOI following each dose due to humoral immunity. (σ: blue, green, orange and red represent decreases in fMOI with each dose of 90%, 50%, 10% and 0% respectively). Removal of vectors following each dose decreases effectiveness of therapy. (c & d) Simulations of 10 weekly doses of a potent regimen (fMOI = 5.0, d = 0.04, h = 2, <i>de novo</i> resistance rate (Ψ) = 0) assuming different burdens of infection (line color represents pre-therapy median number of HBV cccDNA molecules/cell) demonstrate relatively similar potency across highly variable densities of infection whether (c) infected cells or (d) total episomes are tracked as measures of therapeutic outcome.</p

Possible dynamics of HBV cccDNA between vector delivery doses.

<p>(a) Cell death inducing decay of incorporated episome. (b) Episomal degradation. (c) cccDNA expansion despite suppressive antiviral therapy. (d) Hepatocyte replication with equal dispersion of cccDNA molecules between cells. (e) Hepatocyte replication with replication of cccDNA molecules between cells. Only mechanism (c) could increase number of doses needed prior to inactivation while other mechanisms (a, b and d) may allow more rapid cure.</p

Rapid development of <i>de novo</i> resistance to DNA cleavage enzyme therapy.

<p>(a) Potent regimens with high fMOI (m*σ = 5), high enzyme – DNA binding avidity (d = 0.04), and positive binding cooperativity (h = 2) will allow for high levels of simulated resistance and predominance of resistant episomes following only 2 to 3 doses; a higher resistance rate (5% versus 1%) will promote a higher number of infected cells containing enzyme resistant episomes. (b) Infected cells containing enzyme resistant episomes will ultimately achieve equivalent levels assuming equal resistant rates whether a potent (m*σ = 5, d = 0.004 & h = 2) or less potent (m*σ = 1, d = 1 & h = 2) regimen is used. (c) If successive enzymes are dosed that target different regions within HBV cccDNA episomes, then the number of remaining episomes following multiple doses decreases accordingly; susceptible and resistant replication competent genomes are summed; by 60 days, all remaining episomes are resistant to each of the dosed enzymes (not shown in diagram).</p

Packaging of multiple cleavage enzymes that target different HBV regions enhances potency and decreases resistance.

<p>Simulation of HBV eradication employing gene therapy following a single dose. Each data point represents number of remaining infected cells (y-axis) after a simulation with one of 36 unique parameter sets. x-axis is functional multiplicity of infection (fMOI). Enzyme-DNA binding avidity is fixed (d = 0.04). Color represents number of enzymes delivered per vector (orange, green and blue = 1,2 & 3 respectively). Hill coefficient is 1, 2 and 5 (square, diamond and circle). The simulation assumes no pre-existing resistance. (a) Addition of multiple DNA cleavage enzymes within single vectors decreases the number of total remaining infected cells, particularly when vector delivery is high and intracellular binding cooperativity is present. (b) Addition of multiple DNA cleavage enzymes within single vectors decreases the number of total remaining infected cells harboring HBV cccDNA with any <i>de novo</i> resistance mutations, or (c) all possible resistance mutations. (d) Percentage of remaining infected cells containing totally resistant genomes following a single dose increases with high delivery, lower number of cleavage enzymes per vector, and higher binding cooperativity.</p

A single cell may contain episomes with different degrees of resistance to multiple enzymes.

<p>Example of one theoretical cell containing 6, 3, 2 and 1 episomes with 0, 1, 2, and 3 mutations respectively, as well as 3 delivery vectors.</p

Schematic of gene therapy vector delivery.

<p>(a) There is a probability, P_v = [(σ*m)^v * e^−(σ*m)]/v!, of different amounts of vector (red) being delivered to and transduced within each cell containing the target virus (green). (b & c) The percentage of cells with different amounts of transduction will vary according to functional multiplicity of infection (fMOI) which is equal to the ratio of transduced delivery vectors to target hepatocytes multiplied by the proportion of vectors which are transduced, or fMOI = m * σ.</p

Additional file 3: of Viral diversity is an obligate consideration in CRISPR/Cas9 designs for targeting the HIV reservoir

Figure S2. (A) Flowchart showing processing steps for intra-host deep-sequence data. (B) Target site depth based on number of reads overlapping the target site in an alignment for 4 patients with deep-sequence data. Black dots indicate outlier target sites (outside 1.5 × IQR), and target sites are grouped and colored according to which consensus sequence they were identified from (the group- or subtype-level consensus from LANL alignments, or from the patient’s HIV consensus sequence). (EPS 246 kb