Whole-genome expression analysis: challenges beyond clustering.

Measuring the expression of most or all of the genes in a biological system raises major analytic challenges. A wealth of recent reports uses microarray expression data to examine diverse biological phenomena - from basic processes in model organisms to complex aspects of human disease. After an initial flurry of methods for clustering the data on the basis of similarity, the field has recognized some longer-term challenges. Firstly, there are efforts to understand the sources of noise and variation in microarray experiments in order to increase the biological signal. Secondly, there are efforts to combine expression data with other sources of information to improve the range and quality of conclusions that can be drawn. Finally, techniques are now emerging to reconstruct networks of genetic interactions in order to create integrated and systematic models of biological systems.     

Accurate and Fast Multiple-Testing Correction in eQTL Studies

In studies of expression quantitative trait loci (eQTLs), it is of increasing interest to identify eGenes, the genes whose expression levels are associated with variation at a particular genetic variant. Detecting eGenes is important for follow-up analyses and prioritization because genes are the main entities in biological processes. To detect eGenes, one typically focuses on the genetic variant with the minimum p value among all variants in cis with a gene and corrects for multiple testing to obtain a gene-level p value. For performing multiple-testing correction, a permutation test is widely used. Because of growing sample sizes of eQTL studies, however, the permutation test has become a computational bottleneck in eQTL studies. In this paper, we propose an efficient approach for correcting for multiple testing and assess eGene p values by utilizing a multivariate normal distribution. Our approach properly takes into account the linkage-disequilibrium structure among variants, and its time complexity is independent of sample size. By applying our small-sample correction techniques, our method achieves high accuracy in both small and large studies. We have shown that our method consistently produces extremely accurate p values (accuracy > 98%) for three human eQTL datasets with different sample sizes and SNP densities: the Genotype-Tissue Expression pilot dataset, the multi-region brain dataset, and the HapMap 3 dataset.     

Chemical and biological characterisation of a sensor surface for bioprocess monitoring

This paper describes the step-wise fabrication and characterisation of a multi-layer dual polarization interferometry (DPI) based biosensor utilising Protein G (ProG) as the bio-recognition layer for the detection of a fragment antibody (Fab'). The biosensor is capable of monitoring the concentration of Fab' product within the extracellular medium of a fed-batch fermentation after leakage from Escherichia coli (E.coli). The activity, stability and functionality of each sensor layer were analysed in situ using DPI, whilst the chemical identity and homogeneity of the chemical layers were assessed ex situ using X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectrometry (SIMS). Two different biotin linkers were found to produce hugely differing surfaces after the capture of NeutrAvidin? (NA) and biotinylated Protein G (b-ProG). The hydrophilic (PEG)(4)-biotin linker resulted in a surface where the b-ProG layer was deposited and organised above the NA layer producing an active and stable surface, whilst the hydrophobic LC-biotin linker generated a surface where the b-ProG layer was buried within the NA layer leading to variable surfaces and poor binding of the Fab' target. The biosensor has a detection limit of 1.7 μg/ml with a dynamic range covering two orders of magnitude. The sensor can detect the onset of Fab' leakage as early as 2h following product induction, with high signal-to-noise ratios and little interference from extracellular components. Leakage of Fab' followed a biphasic profile, switching to a more rapid rate 20 h after induction, indicating accelerated product loss and the need for cultivation harvest.     

Study of elastic collisions of Myxococcus xanthus in swarms

In very low density situations where a single myxobacterial cell is isolated from direct contact with other cells, the slime capsule interaction with the substrate or slime tracks on the substrate produce a viscous drag that results in a smooth gliding motion. Viscoelastic interactions of myxobacteria cells in a low-density domain close to the edge of a swarm are studied using a combination of a cell-based three-dimensional computational model and cell-tracking experiments. The model takes into account the flexible nature of Myxococcus xanthus as well as the effects of adhesion between cells arising from the interaction of the capsular polysaccharide covering two cells in contact with each other. New image and dynamic cell curvature analysis algorithms are used to track and measure the change in cell shapes that occur as flexible cells undergo significant bending during collisions resulting in direct calibration of the model parameters. Like aspect-ratio and directional reversals, the flexibility of cells and the adhesive cell-cell and cell-substrate interactions of M. xanthus play an important role in smooth gliding and more efficient swarming.     

Decreased expression of both the alpha1- and alpha2-subunits of the Na-K-ATPase reduces maximal alveolar epithelial fluid clearance

Impaired epithelial sodium channel function predisposes to delayed resorption of pulmonary edema and more severe experimental lung injury, whereas even a small fraction of the normal Na-K-ATPase activity is thought to be sufficient to maintain normal ion transport. However, direct proof is lacking. Therefore, we studied baseline and cAMP stimulated alveolar fluid clearance (AFC) in mice with a 50% decrease in lung protein expression of the alpha(1)- and/or alpha(2)-subunit of the Na-K-ATPase. There was no difference in basal and stimulated AFC in alpha(1)(+/-) or alpha(2)(+/-) mice compared with wild-type littermates. Also, the compound heterozygous mice (alpha(1)(+/-)/alpha(2)(+/-)) had normal basal AFC. However, the combined alpha(1)(+/-)/alpha(2)(+/-) mice showed a significant decrease in cAMP-stimulated AFC compared with wild-type littermates (11.1 +/- 1.0 vs. 14.9 +/- 1.8%/30 min, P < 0.001). When exposed to 96 h of >95% hyperoxia, the decrease in stimulated AFC in the alpha(1)(+/-)/alpha(2)(+/-) mice was not associated with more lung edema compared with wild-type littermates (lung wet-to-dry weight ratio 6.6 +/- 0.9 vs. 5.9 +/- 1.1, respectively; P = not significant). Thus a 50% decrease in protein expression of the alpha(1)- or alpha(2)-subunits of the Na-K-ATPase does not impair basal or stimulated AFC. However, a 50% protein reduction in both the alpha(1)- and alpha(2)-subunits of the Na-K-ATPase produces a submaximal stimulated AFC, suggesting a synergistic role for alpha(1)- and alpha(2)-subunits in cAMP-dependent alveolar epithelial fluid clearance.