Microarray Technology

Introduction

Many technologies have been developed for the study of gene expression but much of them are time-consuming and are limited by the number of genes that one can study at a time. Microarray is a highly parallel hybridization tool. It allows querying a large set of genetic questions at one time.

Microarray technology, or 'DNA chip', takes advantage of the data recently acquired from sequenced genomes and permits scientists to understand how genes are regulated under particular conditions - stress response for example, at a particular time, in a particular cell type of an organism.

Fig. 1: Enlarged picture of an illuminated microarray

Microarrays make use of the hybridization phenomenon existing between complementary single-stranded DNA strands, each sample sequence (target) hybridizes to the complementary strand on the array (probe) allowing to confirm the presence of a particular gene . Multiple DNA probes are spotted on a thin support - such as silicium, glass or polymers - each one being specific for a DNA or RNA target sequence. A typical microarray experiment compares gene expression levels in two different physiological conditions, for instance one can compare the same bacterial strain grown with or without antibiotics. In this case, nucleic acids of both samples are labeled with distinct fluorescent dyes, most popular dyes are Cy-3 (green) and Cy-5 (red).

Red spots on the array correspond to genes found only in sample 2, green ones to genes found only in sample 1, and yellow spots to genes found in both samples.

Fig. 2: Microarray experiment workflow.

Hybridized microarray images produced from microarray experiments are raw data. To obtain information concerning gene expression levels, each spot on these images is analyzed using dedicated image analysis software (for ex. Feature Extraction).

Applications

Microarray technology can be tuned to address a broad variety of research questions, such as:

• genome content analysis and CGH ⁴(Comparative Genomic Hybridization);
• re-sequencing of hybridized genomic DNA^1,2;
• pathogen detection using cognate targets¹;
• pattern recognition analysis (see ZeptoChip Project and ³);
• hierarchical species identification (see Gesnoma Project), or even
• non-cognate pattern analysis (Non-cognate hybridization system (NCHS); patents WO0075377 and US6544777)

In any case, powerful software tools are required; in our case most of them have been developed internally by our bioinformatician team. For instance, an integrated approach permitting to design custom whole-genome oligoarrays appears especially suited for bacterial genomics and transcriptomics (OliCheck Software).

Microarrays combine the potential for simultaneous determination of bacterial identification and speciation, genotype-based susceptibility testing, and various genotyping approaches for epidemiology purpose.

Current limitations principally pertain to poor detection sensitivity. Different technical approaches such as evanescence-waveguide technology (see ZeptoChip Project) or resonance light scattering³ have shown promising results, improving detection sensitivity by 1.5-2 orders of magnitude. Finally, cheaper microarray approaches appear especially promising for routine diagnostic purpose⁴.

Our chips

To date, the Genomic Research Laboratory has developed 4 different Agilent chips mapping several prokaryotic genomes on each chip:

1. S. aureus N315, Mu50, MW2, COL, MSSA476, NCTC8325, MRSA252, USA300 and plasmids (5 versions);
2. E. coli K12, CFT073 and O157H7;
3. Neisseria meningitidis serogroup A and B;
4. Rickettsia conorii str. Malish 7.

Improvement in chip design (increased organism coverage with specific target detection) has been made possible thanks to the development of different 'home-made' software (OliCheck) and algorithms.

	Version 1	Version 5
N315	96%	96%
Mu50	93%	95%
COL	81%	92%
MW2	76%	96%
MSSA476	-	96%
NCTC8325	-	92%
MRSA252	-	94%
USA300	-	96%

Fig. 3: Evolution of S. aureus coverage from the 1^st to the 5^th version of our StaphChip.