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Biomedical subjects

Michael W Deem

Publications and source records attributed to Michael W Deem.

14 recordsLinked to original sources
PubMed2006

Physical theory of the competition that allows HIV to escape from the immune system.

Competition within the immune system may degrade immune control of viral infections. We formalize the evolution that occurs in both HIV-1 and the immune system quasispecies. Inclusion of competition in the immune system leads to a novel balance between the immune response and HIV-1, in which the eventual outcome is HIV-1 escape rather than control. The analytical model reproduces the three stages of HIV-1 infection. We propose a vaccine regimen that may be able to reduce competition between T cells, potentially eliminating the third stage of HIV-1.

Biological Evolution↗
PubMed2006

Quantifying influenza vaccine efficacy and antigenic distance.

We introduce a new measure of antigenic distance between influenza A vaccine and circulating strains. The measure correlates well with efficacies of the H3N2 influenza A component of the annual vaccine between 1971 and 2004, as do results of a theory of the immune response to influenza following vaccination. This new measure of antigenic distance is correlated with vaccine efficacy to a greater degree than are current state of the art phylogenetic sequence analyses or ferret antisera inhibition assays. We suggest that this new measure of antigenic distance be used in the design of the annual influenza vaccine and in the interpretation of vaccine efficacy monitoring.

Algorithms↗
PubMed2005

Sculpting the immunological response to dengue fever by polytopic vaccination.

The twin challenges of immunodominance and heterologous immunity have hampered discovery of an effective vaccine against all four dengue viruses. Here, we explore how the T cell competition and selection underlying these asymmetrical properties impede effective T cell vaccine design. The theory we develop predicts dengue vaccine clinical trial data well. From the insights that we gain by this theory, we propose two new ideas for design of epitope-based T cell vaccines against dengue: polytopic injection and subdominant epitope priming.

Dengue↗
PubMed2005

Glassy dynamics in the adaptive immune response prevents autoimmune disease.

The immune system normally protects the human host against death by infection. However, when an immune response is mistakenly directed at self-antigens, autoimmune disease can occur. We describe a model of protein evolution to simulate the dynamics of the adaptive immune response to antigens. Computer simulations of the dynamics of antibody evolution show that different evolutionary mechanisms, namely, gene segment swapping and point mutation, lead to different evolved antibody binding affinities. Although a combination of gene segment swapping and point mutation can yield a greater affinity to a specific antigen than point mutation alone, the antibodies so evolved are highly cross reactive and would cause autoimmune disease, and this is not the chosen dynamics of the immune system. We suggest that in the immune system's search for antibodies, a balance has evolved between binding affinity and specificity.

Animals↗
PubMed2005

Markov chains of infinite order and asymptotic satisfaction of balance: application to the adaptive integration method.

Adaptive Monte Carlo methods can be viewed as implementations of Markov chains with infinite memory. We derive a general condition for the convergence of a Monte Carlo method whose history dependence is contained within the simulated density distribution. In convergent cases, our result implies that the balance condition need only be satisfied asymptotically. As an example, we show that the adaptive integration method converges.

Algorithms↗
PubMed2005

Epitope analysis for influenza vaccine design.

Until now, design of the annual influenza vaccine has relied on phylogenetic or whole-sequence comparisons of the viral coat proteins hemagglutinin and neuraminidase, with vaccine effectiveness assumed to correlate monotonically to the vaccine-influenza sequence difference. We use a theory from statistical mechanics to quantify the non-monotonic immune response that results from antigenic drift in the epitopes of the hemagglutinin and neuraminidase proteins. The results explain the ineffectiveness of the 2003-2004 influenza vaccine in the United States and provide an accurate measure by which to optimize the effectiveness of future annual influenza vaccines.

Drug Design↗
PubMed2004

Evolvability is a selectable trait.

Concomitant with the evolution of biological diversity must have been the evolution of mechanisms that facilitate evolution, because of the essentially infinite complexity of protein sequence space. We describe how evolvability can be an object of Darwinian selection, emphasizing the collective nature of the process. We quantify our theory with computer simulations of protein evolution. These simulations demonstrate that rapid or dramatic environmental change leads to selection for greater evolvability. The selective pressure for large-scale genetic moves such as DNA exchange becomes increasingly strong as the environmental conditions become more uncertain. Our results demonstrate that evolvability is a selectable trait and allow for the explanation of a large body of experimental results.

Computer Simulation↗
PubMed2004

Microarray and EST database estimates of mRNA expression levels differ: the protein length versus expression curve for C. elegans.

BACKGROUND: Various methods for estimating protein expression levels are known. The level of correlation between these methods is only fair, and systematic biases in each of the methods cannot be ruled out. We here investigate systematic biases in the estimation of gene expression rates from microarray data and from abundance within the Expressed Sequence Tag (EST) database. We suggest that length is a significant factor in biases to measured gene expression rates. As a specific example of the importance of the bias of expression rate with length, we address the following evolutionary question: Does the average C. elegans protein length increase or decrease with expression level? Two different answers to this question have been reported in the literature, one method using expression levels estimated by abundance within the EST database and another using microarrays. We have investigated this issue by constructing the full protein length versus expression curve for C. elegans, using both methods for estimating expression levels. RESULTS: The microarray data show a monotonic decrease of length with expression level, whereas the abundance within the EST database data show a non-monotonic behavior. Furthermore, the ratio of the expression level estimated by the EST database to that measured by microarrays is not constant, but rather systematically biased with gene length. CONCLUSIONS: It is suggested that the length bias may lie primarily in the abundance within the EST database method, being not ameliorated by internal standards as it is in the microarray data, and that this bias should be removed before data interpretation. When this is done, both the microarray and the abundance within the EST database give a monotonic decrease of spliced length with expression level, and the correlation between the EST and microarray data becomes larger. We suggest that standard RNA controls be used to normalize for length bias in any method that measures expression.

Animals↗
PubMed2004

Modulation of base-specific mutation and recombination rates enables functional adaptation within the context of the genetic code.

The persistence of life requires populations to adapt at a rate commensurate with the dynamics of their environment. Successful populations that inhabit highly variable environments have evolved mechanisms to increase the likelihood of successful adaptation. We introduce a 64 x 64 matrix to quantify base-specific mutation potential, analyzing four different replicative systems, error-prone PCR, mouse antibodies, a nematode, and Drosophila. Mutational tendencies are correlated with the structural evolution of proteins. In systems under strong selective pressure, mutational biases are shown to favor the adaptive search of space, either by base mutation or by recombination. Such adaptability is discussed within the context of the genetic code at the levels of replication and codon usage.

Adaptation, Biological↗
PubMed2003

Two-dimensional diffusion in the presence of topological disorder.

How topological defects affect the dynamics of particles hopping between lattice sites of a distorted, two-dimensional crystal is addressed. Perturbation theory and numerical simulations show that weak, short-ranged topological disorder leads to a finite reduction of the diffusion coefficient. Renormalization group theory and numerical simulations suggest that longer-ranged disorder, such as that from randomly placed dislocations or random disclinations with no net disclinicity, leads to subdiffusion at long times.

Journal Article↗
PubMed2003

Sequence space localization in the immune system response to vaccination and disease.

We introduce a model of protein evolution to explain limitations in the immune system response to vaccination and disease. The phenomenon of original antigenic sin, wherein vaccination creates memory sequences that can increase susceptibility to future exposures to the same disease, is explained as stemming from localization of the immune system response in antibody sequence space. This localization is a result of the roughness in sequence space of the evolved antibody affinity constant for antigen and is observed for diseases with high year-to-year mutation rates, such as influenza.

Animals↗
PubMed2001

Reaction, Lévy flights, and quenched disorder.

We consider the A+A-->Ø reaction, where the transport of the particles is given by Lévy flights in a quenched random potential. With a common literature model of the disorder, the random potential can only increase the rate of reaction. With a model of the disorder that obeys detailed balance, however, the rate of reaction initially increases and then decreases as a function of the disorder strength. The physical behavior obtained with this second model is in accord with that for reactive turbulent flow, indicating that Lévy flight statistics can model aspects of turbulent fluid transport.

Journal Article↗