Impact of microarray technology in nutrition and food research

Microarrays have become standard tools for gene expression profiling as the mRNA levels of a large number of genes can be measured in a single assay. Many technical aspects concerning microarray production and laboratory usage have been addressed in great detail, but it remains still crucial to establish this technology in new research fields such as human nutrition and food-related areas. The correlation between diet and inter-individual variation in gene expression is an important and relatively unexplored issue in human nutrition. Therefore, nutritionists changed their research field dramatically from epidemiology and physiology towards the "omics" sciences. Nutrigenomics as a field of research is based on the complete knowledge of the human genome and refers to the entire spectrum of human genes that determine the interactions of nutrition with the organism. Nutrigenetics is based on the inter-individual, genetically determined differences in metabolism. Nutrigenomics and nutrigenetics carry the hope that individualized diet can improve human health and prevent nutrition-related diseases. In this article we give an overview of current DNA and protein microarray techniques (including fabrication, experimental procedure and data analysis), we describe their applications to nutrition and food research and point out the limitations, problems and pitfalls of microarray experiments.     

A mixed-species microarray for identification of food spoilage bacilli

Failure of food preservation is frequently caused by thermostable spores of members of the Bacillaceae family, which show a wide spectrum of resistance to cleaning and preservation treatments. We constructed and validated a mixed-species genotyping array for 6 Bacillus species, including Bacillus subtilis, Bacillus licheniformis, Bacillus pumilus, Bacillus sporothermodurans, Bacillus cereus and Bacillus coagulans, and 4 Geobacillus species, including Geobacillus stearothermophilus, Geobacillus thermocatenulatus, Geobacillus toebii and Geobacillus sp., in order to track food spoilage isolates from ingredient to product. The discriminating power of the array was evaluated with sets of 42 reference and 20 test strains. Bacterial isolates contain a within-species-conserved core genome comprising 68-88% of the entire genome and a non-conserved accessory genome comprising 7-22%. The majority of the core genome markers do not hybridise between species, thus they allow for efficient discrimination at the species level. The accessory genome array markers provide high-resolution discrimination at the level of individual isolates from a single species. In conclusion, the reported mixed-species microarray contains discriminating markers that allow rapid and cost-effective typing of Bacillus food spoilage bacteria in a wide variety of food products.     

Gene subset selection in kernel-induced feature space

This paper proposes a new filter approach to gene subset selection for kernel-based classifiers. We derive kernel forms of several well-known class separability criteria, and gene subset selection based on the kernelized criteria is applied to microarray cancer classification problems. The performance of our proposed strategy is compared in experiments with those of the conventional filter approach as well as gene ranking methods.     

细胞微图型化技术

对目前细胞微图型化的概念与适用微加工工艺尤其是软刻技术作了探讨，其中包括微压印法、微流体图型化技术与漏印板图型化方法等。进一步，从单种细胞的微图型化与不同细胞的微图型化共培养两个方面，对许多基底材料(包括非生物性的与生物性的)实现细胞微图型化的加工策略(包括基底的几何形貌与化学修饰剪裁等)，以及这些微图型化基底对细胞贴附与铺展的规约和对细胞后续生存生长等功能的影响等方面的研究进展作了回顾与讨论。     

Changes in Gene Expression of E. coli under Conditions of Modeled Reduced Gravity

Relatively few studies have examined bacterial responses to the reduced gravity conditions that are experienced by bacteria grown in space. In this study, whole genome expression of Escherichia coli K12 under clinorotation (which models some of the conditions found under reduced gravity) was analyzed. We hypothesized that phenotypic differences at cellular and population levels under clinorotation (hereafter referred to as modeled reduced gravity) are directly coupled to changes in gene expression. Further, we hypothesized that these responses may be due to indirect effects of these environmental conditions on nutrient accessibility for bacteria. Overall, 430 genes were identified as significantly different between modeled reduced gravity conditions and controls. Up-regulated genes included those involved in the starvation response (csiD, cspD, ygaF, gabDTP, ygiG, fliY, cysK) and redirecting metabolism under starvation (ddpX, acs, actP, gdhA); responses to multiple stresses, such as acid stress (asr, yhiW), osmotic stress (yehZYW), oxidative stress (katE, btuDE); biofilm formation (lldR, lamB, yneA, fadB, ydeY); curli biosynthesis (csgDEF), and lipid biosynthesis (yfbEFG). Our results support the previously proposed hypothesis that under conditions of modeled reduced gravity, zones of nutrient depletion develop around bacteria eliciting responses similar to entrance into stationary phase which is generally characterized by expression of starvation inducible genes and genes associated with multiple stress responses.     

Incremental wrapper-based gene selection from microarray data for cancer classification

Gene expression microarray is a rapidly maturing technology that provides the opportunity to assay the expression levels of thousands or tens of thousands of genes in a single experiment. We present a new heuristic to select relevant gene subsets in order to further use them for the classification task. Our method is based on the statistical significance of adding a gene from a ranked-list to the final subset. The efficiency and effectiveness of our technique is demonstrated through extensive comparisons with other representative heuristics. Our approach shows an excellent performance, not only at identifying relevant genes, but also with respect to the computational cost.     

On denoising and compression of DNA microarray images

We address the problems of noise and huge data sizes in microarray images. First, we propose a mixture model for describing the statistical and structural properties of microarray images. Then, based on the microarray image model, we present methods for denoising and for compressing microarray images. The denoising method is based on a variant of the translation-invariant wavelet transform. The compression method introduces the notion of approximate contexts (rather than traditional exact contexts) in modeling the symbol probabilities in a microarray image. This inexact context modeling approach is important in dealing with the noisy nature of microarray images. Using the proposed denoising and compression methods, we describe a near-lossless compression scheme suitable for microarray images. Results on both denoising and compression are included, which show the performance of the proposed methods. Further experiments using the results of the proposed near-lossless compression scheme in gene clustering using cell-cycle microarray data for S. cerevisiae showed a general improvement in the clustering performance, when compared with using the original data. This provides an indirect validation of the effectiveness of the proposed denoising method.     

Quality control of chip manufacture and chip analysis using epoxy-chips as a model

Biochips are miniaturized, highly ordered analysis systems which offer the unique advantage of highly parallel analysis of thousands of analytes at the same time. Although this technique has been enthusiastically developed and has promised to improve and speed up numerous biological assays, the quality control of chip manufacture, chip analysis and data management has received less attention.

The following article compares three epoxy-containing chip surfaces (ARChip Epoxy, 3D-Link™, and EasySpot) with respect to their autofluorescence, immobilization capacity, background fluorescence and hybridization efficiency. Since data collected from biochip experiments are random snapshots with errors, inherently noisy and incomplete, we tried to evaluate technical factors causing variability and to set up quality control procedures for chip manufacture and chip analysis. Variabilities caused by arraying, glass substrate and polymer coating, fluorescent label and experimental conditions are discussed in details.     

A noise-resistant algorithm for grid finding in microarray image analysis

We present an algorithm for automatic spot localization for microarray images with rectangular spot and block packing. As an input, the algorithm requires only the common array design parameters: number of block rows and columns and number of spot rows and columns within each block. It proved to be robust with respect to different types of contamination and can tolerate a high percentage of the missing spots. The validity of the developed algorithm has been tested and confirmed using a large set of images of various designs from different microarray platforms. Comparison with academic and commercial packages has shown that for uncontaminated images our algorithm performs similarly, whereas for certain problematic images it outperforms the other packages.Patent pending.