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The study of the whole set of mRNA abundance (transcriptome) encoded by the genome of a unicellular organism or a eukaryotic cell at a specific time or under a specific condition, including gene overexpression or knock-out, is called transcriptomics. Transcriptomics allows us to observe to what extent genes are expressed under a particular condition at a time point X and gives us information about how strongly the genes are expressed relative to a reference.
A microarray is a two-dimensional array on a solid substrate (usually a glass slide or silicon thin-film cell) that can be used to assay large quantities of biological material using high-throughput screening, and miniaturized, multiplexed and parallel processing and detection methods. Microarrays come in various types, including DNA-microarrays, protein microarrays, peptide microarrays, tissue microarrays, antibody microarrays, cellular microarrays and others. A DNA microarray is basically an assembly of microscopic DNA spots fixed to a solid surface, usually glass. DNA microarrays are used to measure the expression levels of a gene or a set of genes simultaneously or to genotype multiple regions of a genome2,3. Picomoles (10-12 moles) of a probe are present within each DNA spot that represents a specific DNA sequence, also known as a reporter. The labelled mRNA molecules from the samples are called ‘targets’. Fluorophores are used to measure probe-target hybridization and detection of fluorophore-labelled targets determines the relative abundance of nucleic acid sequences in the target. A microarray experiment can accomplish multiple genetic tests in parallel because an array may contain tens of thousands of probes. The layout of a simple microarray experiment is shown in Figure 1. Recently, it was established in our and other labs that these arrays are reusable, which makes this technique quite cost-effective.
Different RNA isolation and purification techniques have been developed over the years including C-TAB, SDS and GT methods 4–8. Furthermore, several commercial kits are also available. For gene expression high quality RNA is very important. Therefore, the RNA isolation methods are modified to get a maximum quantity of RNA. Similarly, the steps for cDNA preparation and labelling of cDNA are minimized. Normalization of data after scanning is also performed efficiently by using in-house built software packages and tools9.
Streptococcus pneumoniae is a Gram-positive human pathogen that colonizes the nasopharynx and is the cause of multiple infections such as pneumonia, sepsis, otitis media and meningitis10. The bacterium can utilize a wide variety of the nutrients required for growth and survival 11,12. A number of studies have been carried out on the pneumococcal nitrogen metabolism and regulation emphasizing the importance of amino acids and their role in virulence13,14. In this study, the transcriptomic response of S. pneumoniae to changing concentrations of L-serine, an amino acid abundantly present in the human blood plasma, is reported using DNA microarrays. The transcriptomic response of S. pneumoniae grown in a minimum concentration of L-serine (150 µM) was compared to that grown in a maximum concentration (10 mM) of serine. Chemically defined medium (CDM or minimal medium)15 was used for this study to control the concentration of serine. The focus of this study is to make this technique user-friendly and to provide different tools for data normalization and analysis. Therefore, a number of tools were developed for analysis and data interpretation. FIVA (Functional Information Viewer and Analyzer) provides a platform for processing information contained in clusters of genes having similar gene expression patterns and for constructing functional profiles16. PROSECUTOR is another software package that facilitates the identification of putative functions and annotations of genes 17. By making use of clustering methods, DISCLOSE provides a DNA binding site detection algorithm. Cis-regulatory motifs of genes can be projected by using this algorithm 18. Genome2D offers a Windows-based platform for visualization and analysis of transcriptome data by offering different color ranges to characterize the changes in gene expression levels on a genome map19. The PePPER webserver offers, in addition to the all-in-one analysis method, a toolbox for mining for regulons, promoters and transcription factor binding sites 20. Full annotation of intergenic regions in a bacterial genome can be achieved by using this package. Biologists can greatly benefit from PePPER as it offers them a platform for designing experiments so that the hypothesized information can be confirmed in vitro20. These software packages contribute significantly to the microarray analysis as most of them are freely available and make data normalization and analysis very reliable.