Biomedical subjects

Michael A Gilchrist

Publications and source records attributed to Michael A Gilchrist.

8 recordsLinked to original sources

PubMed2006

Identifying fitness and optimal life-history strategies for an asexual filamentous fungus.

Filamentous fungi are ubiquitous and ecologically important organisms with rich and varied life histories, however, there is no consensus on how to identify or measure their fitness. In the first part of this study we adapt a general epidemiological model to identify the appropriate fitness metric for a saprophytic filamentous fungus. We find that fungal fitness is inversely proportional to the equilibrium density of uncolonized fungal resource patches which, in turn, is a function of the expected spore production of a fungus. In the second part of this study we use a simple life history model of the same fungus within a resource patch to show that a bang-bang resource allocation strategy maximizes the expected spore production, a critical fitness component. Unlike bang-bang strategies identified in other life-history studies, we find that the optimal allocation strategy for saprophytes does not entail the use of all of the resources within a patch.

Biological Evolution↗

PubMed2005

Evolution of virulence: interdependence, constraints, and selection using nested models.

Natural selection acts on virus populations at two distinct but interrelated levels: within individual hosts and between them. Studies of the evolution of virulence typically focus on selection acting at the epidemiological or between-host level and demonstrate the importance of trade-offs between disease transmission and virulence rates. Within-host studies reach similar conclusions regarding trade-offs between transmission and virulence at the level of individual cells. Studies which examine selection at both scales assume that between- and within-host selection are necessarily in conflict. We explicitly examine these ideas and assumptions using a model of within-host viral dynamics nested within a model of between-host disease dynamics. Our approach allows us to evaluate the direction of selection at the within- and between-host levels and identify situations leading to conflict and accord between the two levels of selection.

Host-Parasite Interactions↗

PubMed2005

A model of protein translation including codon bias, nonsense errors, and ribosome recycling.

We present and analyse a model of protein translation at the scale of an individual messenger RNA (mRNA) transcript. The model we develop is unique in that it incorporates the phenomena of ribosome recycling and nonsense errors. The model conceptualizes translation as a probabilistic wave of ribosome occupancy traveling down a heterogeneous medium, the mRNA transcript. Our results show that the heterogeneity of the codon translation rates along the mRNA results in short-scale spikes and dips in the wave. Nonsense errors attenuate this wave on a longer scale while ribosome recycling reinforces it. We find that the combination of nonsense errors and codon usage bias can have a large effect on the probability that a ribosome will completely translate a transcript. We also elucidate how these forces interact with ribosome recycling to determine the overall translation rate of an mRNA transcript. We derive a simple cost function for nonsense errors using our model and apply this function to the yeast (Saccharomyces cervisiae) genome. Using this function we are able to detect position dependent selection on codon bias which correlates with gene expression levels as predicted a priori. These results indirectly validate our underlying model assumptions and confirm that nonsense errors can play an important role in shaping codon usage bias.

Animals↗

PubMed2004

Optimizing within-host viral fitness: infected cell lifespan and virion production rate.

We explore how an infected cell's virion production rate can affect the relative fitness of a virus within a host. We perform an invasion analysis, based on an age-structured model of viral dynamics, to derive the within-host relative viral fitness. We find that for chronic infections, in the absence of trade-offs between viral life history stages, natural selection favors viral strains whose virion production rate maximizes viral burst size. We then show how various life history trade-offs such as that between virion production and immune system recognition and clearance of virally infected cells can lead to natural selection favoring production rates lower than the one that maximizes burst size. Our findings suggest that HIV replication rates should vary between cells with different life spans, as has been suggested by recent observation.

Cells↗

PubMed2004

A statistical framework for combining and interpreting proteomic datasets.

MOTIVATION: To identify accurately protein function on a proteome-wide scale requires integrating data within and between high-throughput experiments. High-throughput proteomic datasets often have high rates of errors and thus yield incomplete and contradictory information. In this study, we develop a simple statistical framework using Bayes' law to interpret such data and combine information from different high-throughput experiments. In order to illustrate our approach we apply it to two protein complex purification datasets. RESULTS: Our approach shows how to use high-throughput data to calculate accurately the probability that two proteins are part of the same complex. Importantly, our approach does not need a reference set of verified protein interactions to determine false positive and false negative error rates of protein association. We also demonstrate how to combine information from two separate protein purification datasets into a combined dataset that has greater coverage and accuracy than either dataset alone. In addition, we also provide a technique for estimating the total number of proteins which can be detected using a particular experimental technique. AVAILABILITY: A suite of simple programs to accomplish some of the above tasks is available at www.unm.edu/~compbio/software/DatasetAssess

Algorithms↗

PubMed2003

Optimal viral production.

Viruses reproduce by multiplying within host cells. The reproductive fitness of a virus is proportional to the number of offspring it can produce during the lifetime of the cell it infects. If viral production rates are independent of cell death rate, then one expects natural selection will favor viruses that maximize their production rates. However, if increases in the viral production rate lead to an increase in the cell death rate, then the viral production rate that maximizes fitness may be less than the maximum. Here we pose the question of how fast should a virus replicate in order to maximize the number of progeny virions that it produces. We present a general mathematical framework for studying problems of this type, which may be adapted to many host-parasite systems, and use it to examine the optimal virus production scheduling problem from the perspective of the virus.

Evolution, Molecular↗

PubMed2003

Calibrating a molecular clock from phylogeographic data: moments and likelihood estimators.

We present moments and likelihood methods that estimate a DNA substitution rate from a group of closely related sister species pairs separated at an assumed time, and we test these methods with simulations. The methods also estimate ancestral population size and can test whether there is a significant difference among the ancestral population sizes of the sister species pairs. Estimates presented in the literature often ignore the ancestral coalescent prior to speciation and therefore should be biased upward. The simulations show that both methods yield accurate estimates given sample sizes of five or more species pairs and that better likelihood estimates are obtained if there is no significant difference among ancestral population sizes. The model presented here indicates that the larger than expected variation found in multitaxa datasets can be explained by variation in the ancestral coalescence and the Poisson mutation process. In this context, observed variation can often be accounted for by variation in ancestral population sizes rather than invoking variation in other parameters, such as divergence time or mutation rate. The methods are applied to data from two groups of species pairs (sea urchins and Alpheus snapping shrimp) that are thought to have separated by the rise of Panama three million years ago.

Animals↗

PubMed2002

Modeling host-parasite coevolution: a nested approach based on mechanistic models.

In this study we introduce a mechanistic framework for modeling host-parasite coevolution using a nested modeling approach. The first step in this approach is to construct a mechanistic model of the parasite population dynamics within a host. The second step is to define an epidemiological model which is used to derive the fitness functions for both the host and the parasite. The within-host model is then nested within the epidemiological model by linking the epidemiological parameters such as the transmission rate of the infection or the additional host mortality rate to the dynamics of the within-host model. Nesting the within-host model into an epidemiological model allows us to evaluate the fitness functions for each interactor which in turn allows us to determine the coevolutionary dynamics of the system. This nested approach has the advantage over other approaches in that mechanistic descriptions of the host-parasite biology are used to derive, rather than impose, life-history trade-offs. We illustrate this framework by analysing a simple host-parasite system. In this particular system we find that the coevolutionary equilibrium is always stable and that host survivorship and parasite fitness vary greatly with the cost of the immune response and parasite growth.

Animals↗