Expressed sequence tags (ESTs) are randomly selected clones sequenced from cDNA libraries. Each cDNA library is constructed from total RNA or poly (A) RNA derived from a specific tissue or cell, and thus the library represents genes expressed in the original cellular population.
The exon regions of eukaryotic genes are transcribed as part of the heterogeneous nuclear RNAs (hnRNAs) and are subsequently spliced together to form mRNAs. In vitro, reversal of this process is possible by reverse transcription of the complete set of mRNAs present in any tissue. This yields a library of complementary DNAs (cDNAs) that correspond to the genes expressed in that sample. Sequencing a short segment (<100 bases) at one or both ends of each cDNA produces a “tag” with enough information to identify the expressed gene: these are called expressed sequence tags (ESTs). Comparison of the ESTs from a novel genome or tissue type with those from a genome that is well-characterized allows identification of the function of gene loci expressed in the new organism.
Expressed sequence tags (ESTs) are single-pass reads of approximately 200-800 base pairs (bp) generated from randomly selected cDNA clones. Since they represent the expressed portion of a genomc, ESTs have proven to be extremely useful for purposes of gene identification and verification of gene predictions. They therefore represent a low-cost alternative to full genome sequencing. This is of particular value for eukaryote organisms, which tend to have larger and less gene dense genomes than do prokaryotes.
The use of expressed sequence tags dates back to the early 1980s, when Putney and colleagues sequenced inserts from 178 clones derived from a rabbit muscle cDNA library (1). Several years later, with the advent of high-throughput DNA sequencing technology, they were proposed as a complementary resource to genome sequencing projects (2). Today ESTs are still being exploited for purposes of novel gene discovery, especially for those organisms for which economics of scale preclude complete genome sequencing. The advent of cheaper and faster sequencing technologies has generated an exponential growth in the number of ESTs that have been generated. At the time of writing, 45,660,524 ESTs from 1408 different species had been deposited in the public EST sequence database, dbEST (3). It is interesting to note that the 25 billion by contained in these data exceeds that of the entire set of the non-redundant nucleotide database (22 billion bp). Furthermore, whereas over 500 species are associated with at least 1000 ESTs, only 66 cukaryotes have been fully sequenced to date (4), highlighting the impressive breadth and depth of coverage associated with EST datasets. Importantly, the recent release of “next-generation” sequencing platforms that can generate hundreds of thousands to millions of sequencing reads (of 35-250 bp) promises to again revolutionize the speed and depth of transcriptome data acquisition especially for the majority of neglected organisms.
Microarray Technology
Gene microarray technology rests on the ability to deposit many (tens of thousands) different DNA sequences on a small surface, usually a glass slide (often referred to as a “chip”). The different DNA fragments are arranged in rows and columns such that the identity of each fragment is known through its location on the array. Two types of microarrays are gene expression microarray and tissue microarray (TMA). Techniques like Northern blot and reverse transcriptase-polymerase chain reaction (RT-PCR) allow testing for only a few genes per experiment. But microarray or “global expression profiling” not only looks at orders of magnitude more genes than was possible previously, but also has the advantage that the genes examined are not influenced by preselection of genes.
Molecular Biology research evolves through the development of the technologies used for carrying them out. It is not possible to research on a large number of genes using traditional methods. DNA Microarray is one such technology which enables the researchers to investigate and address issues which were once thought to be non-traceable. One can analyze the expression of many genes in a single reaction quickly and in an efficient manner. DNA Microarray technology has empowered the scientific community to understand the fundamental aspects underlining the growth and development of life as well as to explore the genetic causes of anomalies occurring in the functioning of the human body.
A typical microarray experiment involves the hybridization of an mRNA molecule to the DNA template from which it is originated. Many DNA samples are used to construct an array. The amount of mRNA bound to each site on the array indicates the expression level of the various genes. This number may run in thousands. All the data is collected and a profile is generated for gene expression in the cell.
An array is an orderly arrangement of samples where matching of known and unknown DNA samples is done based on base pairing rules. An array experiment makes use of common assay systems such as microplates or standard blotting membranes. The sample spot sizes are typically less than 200 microns in diameter usually contain thousands of spots.
Thousands of spotted samples known as probes (with known identity) are immobilized on a solid support (a microscope glass slides or silicon chips or nylon membrane). The spots can be DNA, cDNA, or oligonucleotides. These are used to determine complementary binding of the unknown sequences thus allowing parallel analysis for gene expression and gene discovery. An experiment with a single DNA chip can provide information on thousands of genes simultaneously. An orderly arrangement of the probes on the support is important as the location of each spot on the array is used for the identification of a gene.
Types of Microarrays
Depending upon the kind of immobilized sample used construct arrays and the information fetched, the Microarray experiments can be categorized in three ways:
• Microarray Expression Analysis: In this experimental setup, the cDNA derived from the mRNA of known genes is immobilized. The sample has genes from both the normal as well as the diseased tissues. Spots with more intensity are obtained for diseased tissue gene if the gene is over expressed in the diseased condition. This expression pattern is then compared to the expression pattern of a gene responsible for a disease.
• Microarray for Mutation Analysis: For this analysis, the researchers use gDNA. The genes might differ from each other by as less as a single nucleotide base. A single base difference between two sequences is known as Single Nucleotide Polymorphism (SNP) and detecting them is known as SNP detection.
• Comparative Genomic Hybridization: It is used for the identification in the increase or decrease of the important chromosomal fragments harboring genes involved in a disease.
Applications of Microarrays
The range of applications for microarray technology is enormous. However, although in depth details of each one is beyond the scope of this overview, there are two distinctive applications of microarrays that are in wide spread use.
• Gene expression profiling to measure the expression of genes between different cell populations.
• Comparative genomics to analyze genomic alterations such as sequence and single nucleotide polymorphisms.
• Gene Discovery: DNA Microarray technology helps in the identification of new genes, know about their functioning and expression levels under different conditions.
• Disease Diagnosis: DNA Microarray technology helps researchers learn more about different diseases such as heart diseases, mental illness, infectious disease and especially the study of cancer. Until recently, different types of cancer have been classified on the basis of the organs in which the tumors develop. Now, with the evolution of microarray technology, it will be possible for the researchers to further classify the types of cancer on the basis of the patterns of gene activity in the tumor cells. This will tremendously help the pharmaceutical community to develop more effective drugs as the treatment strategies will be targeted directly to the specific type of cancer.
• Drug Discovery: Microarray technology has extensive application in Pharmacogenomics. Pharmacogenomics is the study of correlations between therapeutic responses to drugs and the genetic profiles of the patients. Comparative analysis of the genes from a diseased and a normal cell will help the identification of the biochemical constitution of the proteins synthesized by the diseased genes. The researchers can use this information to synthesize drugs which combat with these proteins and reduce their effect.
• Toxicological Research: Microarray technology provides a robust platform for the research of the impact of toxins on the cells and their passing on to the progeny. Toxicogenomics establishes correlation between responses to toxicants and the changes in the genetic profiles of the cells exposed to such toxicants.
Microarray as a Gene Expression Profiling Tool
The principle aim of using microarray technology as a gene expression profiling tool is to answer some of the fundamental questions in biology such as “when, where, and to what magnitude genes of interest are expressed.’’ Clearly, if a gene is not expressed in a defined time/condition at a defined cell compartment, then it is possible to imagine it can play no role in that subnetwork. This approach is based on the assumption that cellular genes are expressed in response to a particular state and that the expression profile represents the subset of gene transcripts or mRNA expressed in a cell or tissue. In addition to that, expression profiling by microarray analysis provides another approach to measure changes in the multigene patterns of expression to better understand about regulatory mechanisms and broader bioactivity functions of genes.
It is therefore appreciable that the knowledge obtained from microarray gene expression analysis will probably increase our basic understanding of the cause and consequences of diseases (pathogenesis), how drugs and drug candidates work in cells and organisms, and what gene products might have therapeutic uses or may be studied further as an appropriate target for therapeutic intervention.
This ambitious and plausible attempt to understand such molecular interaction is achieved by directly comparing gene expression profiles of host cell to the expression profile of the pathogen. Also an ex vivo measurement of gene expression for host cells before and after they are infected with a microbial pathogen can greatly increase our understanding of such complex molecular interplay. Furthermore by following the pattern of gene expression at different times, it is possible to elucidate which host or pathogen genes are up or downregulated over the course of infection to further identify critical target genes and drug-specific targets in both host and microbial pathogens.
Microarray as a Comparative Genomics Tool
Another important application of microarray technology, which is also finding a widespread use, is gene mutation analysis to analyse genomic alterations such as sequence and single nucleotide polymorphisms. Currently, in the context of microbiology microarray gene mutation analysis is directed to characterisation of genetic differences among microbial isolates, particularly closely related species. For example detecting the presence or absence of DNA sequences/gene(s) between pathogenic and non-pathogenic strains of the same species. Such informative approach would allow us to reveal genes exclusively present in the former that may be required for infectivity, virulence or adaptation to a particular host niche
Similarly, DNA microarray technology can be used to compare between a fully sequenced genome and an unsequenced but related genome of closely related bacteria. Interestingly, such approach can provide us valuable information about the diversity and evolution of pathogens and symbionts. Comparisons of this kind use a microarray containing representations of all the open reading frames (ORFs) of the sequenced, reference strain and labelled DNA from the unsequenced, experimental strain. The resulting hybridised array will then reveal genes common to both strains and genes that are present in the reference strain but absent in the experimental strain. This method, however, may not detect genes present in the experimental strain, but missing in the reference strain, although the use of multi-genome (species array) may detect genes present in the experimental strain. This method may not also detect point mutations, including frame-shift mutations, small deletions and deletions in homologous repetitive elements, rearrangements of the genome that have not resulted in deletion of a gene from the experimental strain. However the use of affymetrix gene chip can identify these mutations.
An elegant and well known example of using microarray as a comparative genomics tool is the comparison made by Behr et al., 1999 between several Mycobacterium bovis vaccine strains e.g. the genome composition of the sequenced M. tuberculosis laboratory strain H37Rv with the closely related pathogenic species, M. bovis, and with several strains of the bacille Calmette-Guerin (BCG) vaccine variant that was produced by serial in vitro passage of M. bovis between 1908 and 1921.
Glass cDNA Microarrays
A Glass DNA microarray was the first type of DNA microarray technology developed. It was pioneered by Patrick Brown and his colleagues at Stanford University and is produced by using a robotic device, which deposits (spots) a nanoliter of DNA (50-150 µm in diameter) onto a coated microscope glass slide surface in serial order with a distance of approximately 200 250 µm from each other, one spot-one gene. These moderate sized glass cDNA microarrays also bear about 10,000 spots or more on an area of 3.6 cm2.
As the name suggests, glass cDNA microarrays use specially manufactured glass slides with desired physico-chemical characteristics e.g. excellent chemical resistance against solvents, good mechanical stability (increased thermal strain point) and low intrinsic fluorescence properties. However, to produce a complete whole genome glass DNA microarray, a series of consecutive steps are followed, ideally each step requiring an appropriate and careful approach. Here, we will not discuss in detail how each step is performed, but briefly outline these steps in the order they are followed.
The first step of manufacturing a glass cDNA microarray is selecting the material to spot onto the microscope glass surface e.g. the genes from public databases/repositories or institutional sources. This is followed by the preparation and purification of DNA sequences representing the gene of interest. In the preparation process, PCR is used to amplify the DNA from library of interest using a universal primer or gene specific primers and the purity of the DNA fragments representing genes of interest are generally checked by sequencing or using on agarose gel to concomitantly obtain an estimate of the DNA concentration. This is an important step because all the DNA fragments should be of similar concentration/ molarity and size, to achieve similar reaction kinetics for all hybridisations. The third step is spotting DNA solution onto chemically modified glass slides usually with poly (L-lysine) or other cross-linking chemical coating materials such as polyethyleneimine polymer p-aminophenyl trimethoxysilane/ diazotization chemistry and dendrimeric structure. It is these substrates that are coated on the surface of the glass slide that determines how the DNA solution will be immobilized on the surface e.g. covalent or non-covalent. However in the course of poly (L-lysine) the negatively charged phosphate groups in the DNA molecule, forms an ionic bond with the positively charged amine-derivatised surface. This spotting step is achieved via a contact printing using precisely controlled robotic pins or other equivalent delivering technology such as inkjet printing.
Fig1. Steps of manufacturing glass cDNA microarrays.
The last step of manufacturing glass DNA microarrays is the post-print processing step involving the drying of the DNA on the slide overnight at room temperature and the use of UV cross-linking to prevent subsequent binding of DNA, and to decrease the background signal upon hybridization of a labeled target.
Advantages of cDNA microarrays
Advantages of Glass cDNA microarrays include their relative affordability with a lower cost. Its accessibility requiring no specific equipment for use such that hybridization does not need specialized equipment, and data capture can be carried out using equipment that is very often already available in the laboratory and flexibility of design as necessitated by the scientific goals of the experiment. In addition to that, Glass cDNA microarrays also have increased detection sensitivity due to longer target sequences (2 kbp).
Disadvantages of cDNA microarrays
Despite their wide spread use, glass cDNA microarray have a few disadvantages such as intensive labor requirement for synthesising, purifying, and storing DNA solutions before microarray fabrication. Further, more printing devices required thus making microarrays more expensive. Also during microarray experiments in the laboratory, sequence homologies between clones representing different closely related members of the same gene family may result in a failure to specifically detect individual genes and instead may hybridise to spot(s) designed to detect transcript from a different gene. This phenomenon is known as cross hybridisation.
