Spatial distribution of proteins in the quagga mussel adhesive apparatus

The invasive freshwater mollusc Dreissena bugensis (quagga mussel) sticks to underwater surfaces via a proteinacious ‘anchor’ (byssus), consisting of a series of threads linked to adhesive plaques. This adhesion results in the biofouling of crucial underwater industry infrastructure, yet little is known about the proteins responsible for the adhesion. Here the identification of byssal proteins extracted from freshly secreted byssal material is described. Several new byssal proteins were observed by gel electrophoresis. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry was used to characterize proteins in different regions of the byssus, particularly those localized to the adhesive interface. Byssal plaques and threads contain in common a range of low molecular weight proteins, while several proteins with higher mass were observed only in the plaque. At the adhesive interface, a plaque-specific ~8.1 kDa protein had a relative increase in signal intensity compared to the bulk of the plaque, suggesting it may play a direct role in adhesion.     

Application of Bayesian decomposition for analysing microarray data

MOTIVATION: Microarray and gene chip technology provide high throughput tools for measuring gene expression levels in a variety of circumstances, including cellular response to drug treatment, cellular growth and development, tumorigenesis, among many other processes. In order to interpret the large data sets generated in experiments, data analysis techniques that consider biological knowledge during analysis will be extremely useful. We present here results showing the application of such a tool to expression data from yeast cell cycle experiments. RESULTS: Originally developed for spectroscopic analysis, Bayesian Decomposition (BD) includes two features which make it useful for microarray data analysis: the ability to assign genes to multiple coexpression groups and the ability to encode biological knowledge into the system. Here we demonstrate the ability of the algorithm to provide insight into the yeast cell cycle, including identification of five temporal patterns tied to cell cycle phases as well as the identification of a pattern tied to an approximately 40 min cell cycle oscillator. The genes are simultaneously assigned to the patterns, including partial assignment to multiple patterns when this is required to explain the expression profile. AVAILABILITY: The application is available free to academic users under a material transfer agreement. Go to http://bioinformatics.fccc.edu/ for more details.     

Discovery of microsomal triglyceride transfer protein (MTP) inhibitors with potential for decreased active metabolite load compared to dirlotapide

Analogues related to dirlotapide (1), a gut-selective inhibitor of microsomal triglyceride transfer protein (MTP) were prepared with the goal of further reducing the potential for unwanted liver MTP inhibition and associated side-effects. Compounds were designed to decrease active metabolite load: reducing MTP activity of likely human metabolites and increasing metabolite clearance to reduce exposure. Introduction of 4′-alkyl and 4′-alkoxy substituents afforded compounds exhibiting improved therapeutic index in rats with respect to liver triglyceride accumulation and enzyme elevation. Likely human metabolites of select compounds were prepared and characterized for their potential to inhibit MTP in vivo. Based on preclinical efficacy and safety data and its potential for producing short-lived, weakly active metabolites, compound 13 (PF-02575799) advanced into phase 1 clinical studies.     

Interferon-alpha administration enhances CD8+ T cell activation in HIV infection

Background

Type I interferons play important roles in innate immune defense. In HIV infection, type I interferons may delay disease progression by inhibiting viral replication while at the same time accelerating disease progression by contributing to chronic immune activation.

Methods

To investigate the effects of type I interferons in HIV-infection, we obtained cryopreserved peripheral blood mononuclear cell samples from 10 subjects who participated in AIDS Clinical Trials Group Study 5192, a trial investigating the activity of systemic administration of IFNα for twelve weeks to patients with untreated HIV infection. Using flow cytometry, we examined changes in cell cycle status and expression of activation antigens by circulating T cells and their maturation subsets before, during and after IFNα treatment.

Results

The proportion of CD38+HLA-DR+CD8+ T cells increased from a mean of 11.7% at baseline to 24.1% after twelve weeks of interferon treatment (p = 0.006). These frequencies dropped to an average of 20.1% six weeks after the end of treatment. In contrast to CD8+ T cells, the frequencies of activated CD4+ T cells did not change with administration of type I interferon (mean percentage of CD38+DR+ cells = 2.62% at baseline and 2.17% after 12 weeks of interferon therapy). As plasma HIV levels fell with interferon therapy, this was correlated with a “paradoxical” increase in CD8+ T cell activation (p<0.001).

Conclusion

Administration of type I interferon increased expression of the activation markers CD38 and HLA DR on CD8+ T cells but not on CD4+ T cells of HIV+ persons. These observations suggest that type I interferons may contribute to the high levels of CD8+ T cell activation that occur during HIV infection.     

Extended statistical approaches to modelling spatial pattern in biodiversity in northeast New South Wales. II. Community-level modelling

Regional conservation planning can often make more effective use of sparse biological data by linking these data to remotely mapped environmental variables through statistical modelling. While modelling distributions of individual species is the best known and most widely used approach to such modelling, there are many situations in which more information can be extracted from available data by supplementing, or replacing, species-level modelling with modelling of communities or assemblages. This paper provides an overview of approaches to community-level modelling employed in a series of major land-use planning processes in the northeast New South Wales region of Australia, and evaluates how well communities and assemblages derived using these techniques function as surrogates in regional conservation planning. We also outline three new directions that may enhance the effectiveness of community-level modelling by: (1) more closely integrating modelling with traditional ecological mapping (e.g. vegetation mapping); (2) more tightly linking numerical classification and spatial modelling through application of canonical classification techniques; and (3) enhancing the applicability of modelling to data-poor regions through employment of a new technique for modelling spatial pattern in compositional dissimilarity.     

Novel methods improve prediction of species' distributions from occurrence data

Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.     

Whole‐landscape modelling of compositional turnover in aquatic invertebrates informs conservation gap analysis: An example from south‐western Australia

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