Noise sampling method: an ANOVA approach allowing robust selection of differentially regulated genes measured by DNA microarrays

MOTIVATION: A crucial step in microarray data analysis is the selection of subsets of interesting genes from the initial set of genes. In many cases, especially when comparing a specific condition to a reference, the genes of interest are those which are differentially expressed. Two common methods for gene selection are: (a) selection by fold difference (at least n fold variation) and (b) selection by altered ratio (at least n standard deviations away from the mean ratio). RESULTS: The novel method proposed here is based on ANOVA and uses replicate spots to estimate an empirical distribution of the noise. The measured intensity range is divided in a number of intervals. A noise distribution is constructed for each such interval. Bootstrapping is used to map the desired confidence levels from the noise distribution corresponding to a given interval to the measured log ratios in that interval. If the method is applied on individual arrays having replicate spots, the method can calculate an overall width of the noise distribution which can be used as an indicator of the array quality. We compared this method with the fold change and unusual ratio method. We also discuss the relationship with an ANOVA model proposed by Churchill et al. In silico experiments were performed while controlling the degree of regulation as well as the amount of noise. Such experiments show the performance of the classical methods can be very unsatisfactory. We also compared the results of the 2-fold method with the results of the noise sampling method using pre and post immortalization cell lines derived from the MDAH041 fibroblasts hybridized on Affymetrix GeneChip arrays. The 2-fold method reported 198 genes as upregulated and 493 genes as downregulated. The noise sampling method reported 98 gene upregulated and 240 genes downregulated at the 99.99% confidence level. The methods agreed on 221 genes downregulated and 66 genes upregulated. Fourteen genes from the subset of genes reported by both methods were all confirmed by Q-RT-PCR. Alternative assays on various subsets of genes on which the two methods disagreed suggested that the noise sampling method is likely to provide fewer false positives.     

Predicting HIV drug resistance with neural networks

MOTIVATION: Drug resistance is a very important factor influencing the failure of current HIV therapies. The ability to predict the drug resistance of HIV protease mutants may be useful in developing more effective and longer lasting treatment regimens. METHODS: The HIV resistance is predicted to two current protease inhibitors, Indinavir and Saquinavir. The problem was approached from two perspectives. First, a predictor was constructed based on the structural features of the HIV protease-drug inhibitor complex. A particular structure was represented by its list of contacts between the inhibitor and the protease. Next, a classifier was constructed based on the sequence data of various drug resistant mutants. In both cases, self-organizing maps were first used to extract the important features and cluster the patterns in an unsupervised manner. This was followed by subsequent labelling based on the known patterns in the training set. RESULTS: The prediction performance of the classifiers was measured by cross-validation. The classifier using the structure information correctly classified previously unseen mutants with an accuracy of between 60 and 70%. Several architectures were tested on the more abundant sequence data. The best single classifier provided an accuracy of 68% and a coverage of 69%. Multiple networks were then combined into various majority voting schemes. The best combination yielded an average of 85% coverage and 78% accuracy on previously unseen data. This is more than two times better than the 33% accuracy expected from a random classifier.     

Inhibition of allergic inflammation in the airways using aerosolized antisense to Syk kinase

Activation of the protein tyrosine kinase Syk is an early event that follows cross-linking of Fc gamma R and Fc epsilon R, leading to the release of biologically active molecules in inflammation. We reported previously that aerosolized Syk antisense oligodeoxynucleotides (ASO) depresses Syk expression in inflammatory cells, the release of mediators from alveolar macrophages, and pulmonary inflammation. To study the effect of Syk ASO in allergic inflammation and airway hyperresponsiveness, we used the Brown Norway rat model of OVA-induced allergic asthma. Syk ASO, delivered in a liposome, carrier/lipid complex by aerosol to rats, significantly inhibited the Ag-induced inflammatory cell infiltrate in the bronchoalveolar space, decreasing both neutrophilia and eosinophilia. The number of eosinophils in the lung parenchyma was also diminished. Syk ASO also depressed up-regulation of the expression of beta(2) integrins, alpha(4) integrin, and ICAM-1 in bronchoalveolar lavage leukocytes and reversed the Ag-induced decrease in CD62L expression on neutrophils. Furthermore, the increase in TNF levels in bronchoalveolar lavage following Ag challenge was significantly inhibited. Syk ASO also suppressed Ag-mediated contraction of the trachea in a complementary model. Thus, aerosolized Syk ASO suppresses many of the central components of allergic asthma and inflammation and may provide a new therapeutic approach.     

Algorithmic strategies for the single nucleotide polymorphism haplotype assembly problem

With the consensus human genome sequenced and many other sequencing projects at varying stages of completion, greater attention is being paid to the genetic differences among individuals and the abilities of those differences to predict phenotypes. A significant obstacle to such work is the difficulty and expense of determining haplotypes--sets of variants genetically linked because of their proximity on the genome--for large numbers of individuals for use in association studies. This paper presents some algorithmic considerations in a new approach for haplotype determination: inferring haplotypes from localised polymorphism data gathered from short genome 'fragments.' Formalised models of the biological system under consideration are examined, given a variety of assumptions about the goal of the problem and the character of optimal solutions. Some theoretical results and algorithms for handling haplotype assembly given the different models are then sketched. The primary conclusion is that some important simplified variants of the problem yield tractable problems while more general variants tend to be intractable in the worst case.     

A quantum model for controlled enzymic reactions: II. Controlled biochemical networks

Two control units, the switching and the two factor discriminating net are described. They are derived as a consequence of the enzymic oscillatory behavior induced by substrate “perturbation”. A complex network encompassing long sequences of metabolic reactions is constructed and the organization of cellular metabolic activities in well defined “regimes” and “states” inferred.     

The Biological Connection Markup Language: a SBGN-compliant format for visualization, filtering and analysis of biological pathways

MOTIVATION: Many models and analysis of signaling pathways have been proposed. However, neither of them takes into account that a biological pathway is not a fixed system, but instead it depends on the organism, tissue and cell type as well as on physiological, pathological and experimental conditions. RESULTS: The Biological Connection Markup Language (BCML) is a format to describe, annotate and visualize pathways. BCML is able to store multiple information, permitting a selective view of the pathway as it exists and/or behave in specific organisms, tissues and cells. Furthermore, BCML can be automatically converted into data formats suitable for analysis and into a fully SBGN-compliant graphical representation, making it an important tool that can be used by both computational biologists and 'wet lab' scientists. Availability and implementation: The XML schema and the BCML software suite are freely available under the LGPL for download at http://bcml.dc-atlas.net. They are implemented in Java and supported on MS Windows, Linux and OS X.     

RF hydrazine plasma modification of chitosan for antibacterial activity and nanofiber applications

Chitosan nano powders were modified using RF hydrazine plasma produced at low pressure (26.66 Pa) with 13.56 MHz frequency at a power of 100 W for 30 min. Characterization and investigation of the properties of plasma-modified chitosan (PMCh) and non-modified chitosan (Ch) were carried out using an optical monochromator, FTIR, florescence analysis, TGA, SEM, and X-ray techniques. FTIR spectra of PMCh indicated a band broadening at 3436 cm⁻¹ that confirmed increasing functional groups based on H-bonding. The number of NH₂ groups was determined from fluorescence analysis. TGA analysis shows that the moisture absorption is three times higher in the PMCh structure. Ch and PMCh in PVA solutions were used to produce nanofibers by the electrospinning method; average fiber diameters were 480 and 280 nm for Ch and PMCh, respectively. It was found that the antibacterial effect of PMCh is better than the Ch for Gram-positive strains.     

ABCG9, ABCG11 and ABCG14 ABC transporters are required for vascular development in Arabidopsis

In order to obtain insights into the regulatory pathways controlling phloem development, we characterized three genes encoding membrane proteins from the G sub‐family of ABC transporters (ABCG9, ABCG11 and ABCG14), whose expression in the phloem has been confirmed. Mutations in the genes encoding these dimerizing ‘half transporters’ are semi‐dominant and result in vascular patterning defects in cotyledons and the floral stem. Co‐immunoprecipitation and bimolecular fluorescence complementation experiments demonstrated that these proteins dimerize, either by flexible pairing (ABCG11 and ABCG9) or by forming strict heterodimers (ABCG14). In addition, metabolome analyses and measurement of sterol ester contents in the mutants suggested that ABCG9, ABCG11 and ABCG14 are involved in lipid/sterol homeostasis regulation. Our results show that these three ABCG genes are required for proper vascular development in Arabidopsis thaliana.