New methods for analyzing serological data with applications to influenza surveillance

Two important challenges to the use of serological assays for influenza surveillance include the substantial amount of experimental effort involved, and the inherent noisiness of serological data. Here, informed by the observation that log-transformed serological data (obtained from the hemagglutination-inhibition assay) exist in an effectively one-dimensional space, computational methods are developed for accurately and efficiently recovering unmeasured serological data from a sample of measured data, and systematically minimizing noise found in the measured data. Careful application of these methods would enable the collection of better-quality serological data on a greater number of circulating influenza viruses than is currently possible, and improve the ability to identify potential epidemic/pandemic viruses before they become widespread. Although the focus here is on influenza surveillance, the described methods are more widely applicable

A contact-waiting-time metric and RNA folding rates

Metrics for indirectly predicting the folding rates of RNA sequences are of interest. In this letter, we introduce a simple metric of RNA structural complexity, which accounts for differences in the energetic contributions of RNA base contacts toward RNA structure formation. We apply the metric to RNA sequences whose folding rates were previously determined experimentally. We find that the metric has good correlation (correlation coefficient: -0.95, p << 0.01) with the logarithmically transformed folding rates of those RNA sequences. This suggests that the metric can be useful for predicting RNA folding rates. We use the metric to predict the folding rates of bacterial and eukaryotic group II introns. Future applications of the metric (e.g., to predict structural RNAs) could prove fruitful.Comment: 15 pages, 1 figure, 3 tables, matlab code. Published in FEBS Letters (June '09

An RNA foldability metric; implications for the design of rapidly foldable RNA sequences

Evidence is presented suggesting, for the first time, that the protein foldability metric sigma=(T_theta - T_f)/T_theta, where T_theta and T_f are, respectively, the collapse and folding transition temperatures, could be used also to measure the foldability of RNA sequences. The importance of sigma is discussed in the context of the in silico design of rapidly foldable RNA sequences.Comment: To appear in Biophysical Chemistr

Novel Strategies for Malaria Vaccine Design

The quest for a licensed effective vaccine against malaria remains a global priority. Even though classical vaccine design strategies have been successful for some viral and bacterial pathogens, little success has been achieved for Plasmodium falciparum, which causes the deadliest form of malaria due to its diversity and ability to evade host immune responses. Nevertheless, recent advances in vaccinology through high throughput discovery of immune correlates of protection, lymphocyte repertoire sequencing and structural design of immunogens, provide a comprehensive approach to identifying and designing a highly efficacious vaccine for malaria. In this review, we discuss novel vaccine approaches that can be employed in malaria vaccine design

A complex adaptive systems approach to the kinetic folding of RNA

The kinetic folding of RNA sequences into secondary structures is modeled as a complex adaptive system, the components of which are possible RNA structural rearrangements (SRs) and their associated bases and base pairs. RNA bases and base pairs engage in local stacking interactions that determine the probabilities (or fitnesses) of possible SRs. Meanwhile, selection operates at the level of SRs; an autonomous stochastic process periodically (i.e., from one time step to another) selects a subset of possible SRs for realization based on the fitnesses of the SRs. Using examples based on selected natural and synthetic RNAs, the model is shown to qualitatively reproduce characteristic (nonlinear) RNA folding dynamics such as the attainment by RNAs of alternative stable states. Possible applications of the model to the analysis of properties of fitness landscapes, and of the RNA sequence to structure mapping are discussed.Comment: 23 pages, 4 figures, 2 tables, to be published in BioSystems (Note: updated 2 references

A mechanistic model for long-term immunological outcomes in South African HIV-infected children and adults receiving ART.

Long-term effects of the growing population of HIV-treated people in Southern Africa on individuals and the public health sector at large are not yet understood. This study proposes a novel 'ratio' model that relates CD4+ T-cell counts of HIV-infected individuals to the CD4+ count reference values from healthy populations. We use mixed-effects regression to fit the model to data from 1616 children (median age 4.3 years at ART initiation) and 14,542 adults (median age 36 years at ART initiation). We found that the scaled carrying capacity, maximum CD4+ count relative to an HIV-negative individual of similar age, and baseline scaled CD4+ counts were closer to healthy values in children than in adults. Post-ART initiation, CD4+ growth rate was inversely correlated with baseline CD4+ T-cell counts, and consequently higher in adults than children. Our results highlight the impacts of age on dynamics of the immune system of healthy and HIV-infected individuals

How Can Vaccines Against Influenza and Other Viral Diseases Be Made More Effective?

A large fraction of the world’s most widespread and problematic pathogens, such as the influenza virus, seem to persist in nature by evading host immune responses by inducing immunity to genetically and phenotypically plastic epitopes (aka antigenic variation). The more recent re-emergence of pandemic influenza A/ H1N1 and avian H5N1 viruses has called attention to the urgent need for more effective influenza vaccines. Developing such vaccines will require more than just moving from an egg-based to a tissueculture–based manufacturing process. It will also require a new conceptual understanding of pathogen–host interactions, as well as new approaches and technologies to circumvent immune evasion by pathogens capable of more genetic variation. Here, we discuss these challenges, focusing on some potentially fruitful directions for future research