Timothy C. Wallstrom

Transmission of Single HIV-1 Genomes and Dynamics of Early Immune Escape Revealed by Ultra-Deep Sequencing

We used ultra-deep sequencing to obtain tens of thousands of HIV-1 sequences from regions targeted by CD8+ T lymphocytes from longitudinal samples from three acutely infected subjects, and modeled viral evolution during the critical first weeks of infection. Previous studies suggested that a single virus established productive infection, but these conclusions were tempered because of limited sampling; now, we have greatly increased our confidence in this observation through modeling the observed earliest sample diversity based on vastly more extensive sampling. Conventional sequencing of HIV-1 from acute/early infection has shown different patterns of escape at different epitopes; we investigated the earliest escapes in exquisite detail. Over 3–6 weeks, ultradeep sequencing revealed that the virus explored an extraordinary array of potential escape routes in the process of evading the earliest CD8 T-lymphocyte responses – using 454 sequencing, we identified over 50 variant forms of each targeted epitope during early immune escape, while only 2–7 variants were detected in the same samples via conventional sequencing. In contrast to the diversity seen within epitopes, non-epitope regions, including the Envelope V3 region, which was sequenced as a control in each subject, displayed very low levels of variation. In early infection, in the regions sequenced, the consensus forms did not have a fitness advantage large enough to trigger reversion to consensus amino acids in the absence of immune pressure. In one subject, a genetic bottleneck was observed, with extensive diversity at the second time point narrowing to two dominant escape forms by the third time point, all within two months of infection. Traces of immune escape were observed in the earliest samples, suggesting that immune pressure is present and effective earlier than previously reported; quantifying the loss rate of the founder virus suggests a direct role for CD8 T-lymphocyte responses in viral containment after peak viremia. Dramatic shifts in the frequencies of epitope variants during the first weeks of infection revealed a complex interplay between viral fitness and immune escape.

Expanded Breadth of the T-Cell Response to Mosaic Human Immunodeficiency Virus Type 1 Envelope DNA Vaccination

ABSTRACT An effective AIDS vaccine must control highly diverse circulating strains of human immunodeficiency virus type 1 (HIV-1). Among HIV-1 gene products, the envelope (Env) protein contains variable as well as conserved regions. In this report, an informatic approach to the design of T-cell vaccines directed to HIV-1 Env M group global sequences was tested. Synthetic Env antigens were designed to express mosaics that maximize the inclusion of common potential T-cell epitope (PTE) 9-mers and minimize the inclusion of rare epitopes likely to elicit strain-specific responses. DNA vaccines were evaluated using intracellular cytokine staining in inbred mice with a standardized panel of highly conserved 15-mer PTE peptides. One-, two-, and three-mosaic sets that increased theoretical epitope coverage were developed. The breadth and magnitude of T-cell immunity stimulated by these vaccines were compared to those for natural strain Envs; additional comparisons were performed on mutant Envs, including gp160 or gp145 with or without V regions and gp41 deletions. Among them, the two- or three-mosaic Env sets elicited the optimal CD4 and CD8 responses. These responses were most evident in CD8 T cells; the three-mosaic set elicited responses to an average of eight peptide pools, compared to two pools for a set of three natural Envs. Synthetic mosaic HIV-1 antigens can therefore induce T-cell responses with expanded breadth and may facilitate the development of effective T-cell-based HIV-1 vaccines.

Effective Flux Boundary Conditions for Upscaling Porous Media Equations

We introduce a new algorithm for setting pressure boundary conditions in subgrid simulations of porous media flow. The algorithm approximates the flux in the boundary cell as the flux through a homogeneous inclusion in a homogeneous background, where the permeability of the inclusion is given by the cell permeability and the permeability of the background is given by the ambient effective permeability. With this approximation, the flux in the boundary cell scales with the cell permeability when that permeability is small, and saturates at a constant value when that permeability is large. The flux conditions provide Neumann boundary conditions for the subgrid pressure. We call these boundary conditions effective flux boundary conditions (EFBCs). We give solutions for the flux through ellipsoidal inclusions in two and three dimensions, assuming symmetric tensor permeabilities whose principal axes align with the axes of the ellipse. We then discuss the considerations involved in applying these equations to scale up problems in geological porous media. The key complications are heterogeneity, fluctuations at all length scales, and boundary conditions at finite scales.

Accurate scale up of two phase flow using renormalization and nonuniform coarsening

This paper describes a new upscaling algorithm, which combines the key aspects of nonuniform coarsening methods and renormalization based multiphase methods. The algorithm is applied to a range of heterogeneous, two dimensional geological descriptions. Extensive simulation results indicate that the new algorithm is able to provide results on highly coarsened grids ((5 x 5)) that are in close agreement with fine grid ((100 x 100)) simulations, at least for the set of problems considered. This very large degree of coarsening is more than an order of magnitude greater than could be achieved with either of the original methods individually, as currently implemented. For the set of problems considered, the algorithm is unbiased and consistent, even at very large levels of scale up.

HIV-2 Genetic Evolution in Patients with Advanced Disease Is Faster than That in Matched HIV-1 Patients

ABSTRACT The objective of this study was to estimate and compare the evolutionary rates of HIV-2 and HIV-1. Two HIV-2 data sets from patients with advanced disease were compared to matched HIV-1 data sets. The estimated mean evolutionary rate of HIV-2 was significantly higher than the estimated rate of HIV-1, both in the gp125 and in the V3 region of the env gene. In addition, the rate of synonymous substitutions in gp125 was significantly higher for HIV-2 than for HIV-1, possibly indicating a shorter generation time or higher mutation rate of HIV-2. Thus, the lower virulence of HIV-2 does not appear to translate into a lower rate of evolution.

Application of a new two-phase upscaling technique to realistic reservoir cross sections

This paper describes further development and testing of the Renormalization and Nonuniform Coarsening (RNC) scale up algorithm, which was recently introduced in Ref. 13. RNC scale up combines nonuniform coarsening with upscaling of the absolute and relative permeabilities to provide coarsened descriptions of two-phase immiscible flow. We diagnose a known bias in the two-phase upscaling algorithm used in RNC. An unbiased alternative is introduced and incorporated into RNC scale up. The modified RNC scale up algorithm is tested on displacements through two dimensional cross sections with permeability and porosity data from conditioned reservoir simulations, and three dimensional linear and quarter-five-spot pattern displacements through computer generated permeability fields. Each reservoir description, measured or synthetic, contains highly heterogeneous and highly layered permeability fields. RNC scale up is used to coarsen these reservoir descriptions by a factor of 300 to 1000. The coarse grid oil cut curves show consistently close agreement with the fine grid curves in overall shape and in breakthrough time. The results are comparable to earlier results in Ref. 13 on displacements through synthetic two dimensional data.

Quantification of margins and uncertainties: A probabilistic framework

Quantification of margins and uncertainties (QMU) was originally introduced as a framework for assessing confidence in nuclear weapons, and has since been extended to more general complex systems. We show that when uncertainties are strictly bounded, QMU is equivalent to a graphical model, provided confidence is identified with reliability one. In the more realistic case that uncertainties have long tails, we find that QMU confidence is not always a good proxy for reliability, as computed from the graphical model. We explore the possibility of defining QMU in terms of the graphical model, rather than through the original procedures. The new formalism, which we call probabilistic QMU, or pQMU, is fully probabilistic and mathematically consistent, and shows how QMU may be interpreted within the framework of system reliability theory.

On the initial-value problem for the Madelung hydrodynamic equations

Abstract We show that the initial-value problem for the Madelung hydrodynamic equations is not well-defined unless it is supplemented by additional conditions at the nodal boundaries. These conditions present a challenge for interpretations of quantum mechanics based on these equations, but may suggest means for stabilizing numerical solutions to these equations.

Smoothing in Maximum Quantum Entropy

The method of Maximum Quantum Entropy (MQE) has been described in a companion paper. Here we give criteria for the smoothness properties of the MQE estimate, as a function of the smoothing operator and the dimension. With point constraints, the MQE estimate will have continuous derivatives of order l in d dimensions if and only if the elliptic smoothing operator is of order 2m, where 2m > l+d. It is thus impossible to constrain individual points unless 2m > d, and the derivative will have discontinuities unless 2m > d + 1.

Maximum Quantum Entropy for Classical Density Functions

Maximum Quantum Entropy (MQE), recently introduced by Richard Silver and also known as Quantum Statistical Inference (QSI), is a method of estimating smooth, non-quantummechanical (“classical”) densities, given information about those densities. It is formally analogous to Maximum Entropy (ME), the difference being that the Shannon entropy is replaced by the quantum entropy. We present a concise description of MQE from a mathematical perspective, not relying on physical analogy. We introduce density matrices and the quantum entropy, compare MQE with ME, discuss the nature of constraints in MQE and show how these constraints influence the density estimate. We conclude with a discussion of the status of MQE as a maximum entropy method.