Judith M. Fonville

The Potential for Respiratory Droplet–Transmissible A/H5N1 Influenza Virus to Evolve in a Mammalian Host

Some natural influenza viruses need only three amino acid substitutions to acquire airborne transmissibility between mammals. Avian A/H5N1 influenza viruses pose a pandemic threat. As few as five amino acid substitutions, or four with reassortment, might be sufficient for mammal-to-mammal transmission through respiratory droplets. From surveillance data, we found that two of these substitutions are common in A/H5N1 viruses, and thus, some viruses might require only three additional substitutions to become transmissible via respiratory droplets between mammals. We used a mathematical model of within-host virus evolution to study factors that could increase and decrease the probability of the remaining substitutions evolving after the virus has infected a mammalian host. These factors, combined with the presence of some of these substitutions in circulating strains, make a virus evolving in nature a potentially serious threat. These results highlight critical areas in which more data are needed for assessing, and potentially averting, this threat.

Antibody landscapes after influenza virus infection or vaccination

We introduce the antibody landscape, a method for the quantitative analysis of antibody-mediated immunity to antigenically variable pathogens, achieved by accounting for antigenic variation among pathogen strains. We generated antibody landscapes to study immune profiles covering 43 years of influenza A/H3N2 virus evolution for 69 individuals monitored for infection over 6 years and for 225 individuals pre- and postvaccination. Upon infection and vaccination, titers increased broadly, including previously encountered viruses far beyond the extent of cross-reactivity observed after a primary infection. We explored implications for vaccination and found that the use of an antigenically advanced virus had the dual benefit of inducing antibodies against both advanced and previous antigenic clusters. These results indicate that preemptive vaccine updates may improve influenza vaccine efficacy in previously exposed individuals. Preemptive vaccine updates may substantially improve influenza vaccine efficacy in previously exposed individuals. [Also see Perspective by Lessler] Hills and valleys of influenza infection Each one of us may encounter several different strains of the ever-changing influenza virus during a lifetime. Scientists can now summarize such histories of infection over a lifetime of exposure. Fonville et al. visualize the interplay between protective responses and the evasive influenza virus by a technique called antibody landscape modeling (see the Perspective by Lessler). Landscapes reveal how exposure to new strains of the virus boost immune responses and indicate possibilities for optimizing future vaccination programs. Science, this issue p. 996; see also p. 919

The evolution of partial least squares models and related chemometric approaches in metabonomics and metabolic phenotyping

Metabonomics is a key element in systems biology, and with current analytical methods, generates vast amounts of quantitative or qualitative metabolic data. Understanding of the global function of the living organism can be achieved by integration of ‘omics’ approaches including metabonomics, genomics, transcriptomics and proteomics, increasing the complexity of the full data sets. Multivariate statistical approaches are well suited to extract the characterizing metabolic information associated with each level of dynamic process. In this review, we discuss techniques that have evolved from principal component analysis and partial least squares (PLS) methods with a focus on improved interpretation and modeling with respect to biomarker recovery and data visualization in the context of metabonomic applications. Visualization is of paramount importance to investigate complex metabolic signatures, the power and potential of which is illustrated with key papers. Recent improvements based on the removal of orthogonal variation are discussed in terms of interpretation enhancement, and are supported by relevant applications. Flexibility of PLS methods in general and of O‐PLS in particular allows implementation of derivative methods such as O2‐PLS, O‐PLS‐variance components, nonlinear methods, and batch modeling to improve analysis of complex data sets, which facilitates extraction of information related to subtle biological processes. These approaches can be used to address issues present in complex multi‐factorial data sets. Thus, we highlight the key advantages and limitations of the different latent variable applications for top‐down systems biology and assess the differences between the methods available. Copyright

Evaluation of Full-Resolution J-Resolved 1H NMR Projections of Biofluids for Metabonomics Information Retrieval and Biomarker Identification

Spectroscopic profiling of biological samples is an integral part of metabolically driven top-down systems biology and can be used for identifying biomarkers of toxicity and disease. However, optimal biomarker information recovery and resonance assignment still pose significant challenges in NMR-based complex mixture analysis. The reduced signal overlap as achieved when projecting two-dimensional (2D) J-resolved (JRES) NMR spectra can be exploited to mitigate this problem and, here, full-resolution (1)H JRES projections have been evaluated as a tool for metabolic screening and biomarker identification. We show that the recoverable information content in JRES projections is intrinsically different from that in the conventional one-dimensional (1D) and Carr-Purcell-Meiboom-Gill (CPMG) spectra, because of the combined result of reduction of the over-representation of highly split multiplet peaks and relaxation editing. Principal component and correlation analyses of full-resolution JRES spectral data demonstrated that peak alignment is necessary. The application of statistical total correlation spectroscopy (STOCSY) to JRES projections improved the identification of previously overlapped small molecule resonances in JRES (1)H NMR spectra, compared to conventional 1D and CPMG spectra. These approaches are demonstrated using a galactosamine-induced hepatotoxicity study in rats and show that JRES projections have a useful and complementary role to standard one-dimensional experiments in complex mixture analysis for improved biomarker identification.

Robust Data Processing and Normalization Strategy for MALDI Mass Spectrometric Imaging

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) provides localized information about the molecular content of a tissue sample. To derive reliable conclusions from MSI data, it is necessary to implement appropriate processing steps in order to compare peak intensities across the different pixels comprising the image. Here, we review commonly used normalization methods, and propose a rational data processing strategy, for robust evaluation and modeling of MSI data. The approach includes newly developed heuristic methods for selecting biologically relevant peaks and pixels to reduce the size of a data set and remove the influence of the applied MALDI matrix. The methods are demonstrated on a MALDI MSI data set of a sagittal section of rat brain (4750 bins, m/z = 50-1000, 111 × 185 pixels) and the proposed preferred normalization method uses the median intensity of selected peaks, which were determined to be independent of the MALDI matrix. This was found to effectively compensate for a range of known limitations associated with the MALDI process and irregularities in MS image sampling routines. This new approach is relevant for processing of all MALDI MSI data sets, and thus likely to have impact in biomarker profiling, preclinical drug distribution studies, and studies addressing underlying molecular mechanisms of tissue pathology.

Dengue viruses cluster antigenically but not as discrete serotypes

The devil in the dengue details Along with their mosquito vectors, dengue viruses are spreading worldwide to infect millions of people. For a few, subsequent infection results in lethal hemorrhagic disease. Katzelnick et al. used antibody-binding data to map structural divergence and antigenic variation among dengue viruses. Comparing results in monkeys and humans, the viruses approximately clustered into the four known groups. However, the four virus groups showed as much antigenic distance within a group as between groups. This finding helps explain why immune responses to dengue are highly variable, and it has complex implications for epidemiology, disease, and vaccine deployment. Science, this issue p. 1338 Dengue viruses show as much divergence within a type as between types. The four genetically divergent dengue virus (DENV) types are traditionally classified as serotypes. Antigenic and genetic differences among the DENV types influence disease outcome, vaccine-induced protection, epidemic magnitude, and viral evolution. We characterized antigenic diversity in the DENV types by antigenic maps constructed from neutralizing antibody titers obtained from African green monkeys and after human vaccination and natural infections. Genetically, geographically, and temporally, diverse DENV isolates clustered loosely by type, but we found that many are as similar antigenically to a virus of a different type as to some viruses of the same type. Primary infection antisera did not neutralize all viruses of the same DENV type any better than other types did up to 2 years after infection and did not show improved neutralization to homologous type isolates. That the canonical DENV types are not antigenically homogeneous has implications for vaccination and research on the dynamics of immunity, disease, and the evolution of DENV.

Direct detection of peptides and small proteins in fingermarks and determination of sex by MALDI mass spectrometry profiling

Matrix Assisted Laser Desorption Ionisation Mass Spectrometry (MALDI MS) can detect and image a variety of endogenous and exogenous compounds from latent fingermarks. This opportunity potentially provides investigators with both an image for suspect identification and chemical information to be used as additional intelligence. The latter becomes particularly important when the fingermark is distorted or smudged or when the suspect is not a previously convicted offender and therefore their fingerprints are not present in the National Fingerprint Database. One of the desirable pieces of intelligence would be the sex of the suspect from the chemical composition of a fingermark. In this study we show that the direct detection of peptides and proteins from fingermarks by MALDI MS Profiling (MALDI MSP), along with the multivariate modeling of the spectra, enables the determination of sex with 85% accuracy. The chemical analysis of the fingermark composition is expected to additionally provide information on traits such as nutritional habits, drug use or hormonal status.

Hyperspectral Visualization of Mass Spectrometry Imaging Data

The acquisition of localized molecular spectra with mass spectrometry imaging (MSI) has a great, but as yet not fully realized, potential for biomedical diagnostics and research. The methodology generates a series of mass spectra from discrete sample locations, which is often analyzed by visually interpreting specifically selected images of individual masses. We developed an intuitive color-coding scheme based on hyperspectral imaging methods to generate a single overview image of this complex data set. The image color-coding is based on spectral characteristics, such that pixels with similar molecular profiles are displayed with similar colors. This visualization strategy was applied to results of principal component analysis, self-organizing maps and t-distributed stochastic neighbor embedding. Our approach for MSI data analysis, combining automated data processing, modeling and display, is user-friendly and allows both the spatial and molecular information to be visualized intuitively and effectively.

The global antigenic diversity of swine influenza A viruses

Swine influenza presents a substantial disease burden for pig populations worldwide and poses a potential pandemic threat to humans. There is considerable diversity in both H1 and H3 influenza viruses circulating in swine due to the frequent introductions of viruses from humans and birds coupled with geographic segregation of global swine populations. Much of this diversity is characterized genetically but the antigenic diversity of these viruses is poorly understood. Critically, the antigenic diversity shapes the risk profile of swine influenza viruses in terms of their epizootic and pandemic potential. Here, using the most comprehensive set of swine influenza virus antigenic data compiled to date, we quantify the antigenic diversity of swine influenza viruses on a multi-continental scale. The substantial antigenic diversity of recently circulating viruses in different parts of the world adds complexity to the risk profiles for the movement of swine and the potential for swine-derived infections in humans. DOI: http://dx.doi.org/10.7554/eLife.12217.001

The confounded effects of age and exposure history in response to influenza vaccination

Numerous studies have explored whether the antibody response to influenza vaccination in elderly adults is as strong as it is in young adults. Results vary, but tend to indicate lower post-vaccination titers (antibody levels) in the elderly, supporting the concept of immunosenescence-the weakening of the immunological response related to age. Because the elderly in such studies typically have been vaccinated against influenza before enrollment, a confounding of effects occurs between age, and previous exposures, as a potential extrinsic reason for immunosenescence. We conducted a four-year study of serial annual immunizations with inactivated trivalent influenza vaccines in 136 young adults (16 to 39 years) and 122 elderly adults (62 to 92 years). Compared to data sets of previously published studies, which were designed to investigate the effect of age, this detailed longitudinal study with multiple vaccinations allowed us to also study the effect of prior vaccination history on the response to a vaccine. In response to the first vaccination, young adults produced higher post-vaccination titers, accounting for pre-vaccination titers, than elderly adults. However, upon subsequent vaccinations the difference in response to vaccination between the young and elderly age groups declined rapidly. Although age is an important factor when modeling the outcome of the first vaccination, this term lost its relevance with successive vaccinations. In fact, when we examined the data with the assumption that the elderly group had received (on average) as few as two vaccinations prior to our study, the difference due to age disappeared. Our analyses therefore show that the initial difference between the two age groups in their response to vaccination may not be uniquely explained by immunosenescence due to ageing of the immune system, but could equally be the result of the different pre-study vaccination and infection histories in the elderly.