The molecular biology revolution, which exploded during the second half of the twentieth century, paved way for unveiling of genome sequences of several organisms. The dawn of high throughput sequencing has in turn led to a host of technologies that enabled researchers to understand how cells and organisms use the genetic information in accomplishing life processes. While an inventory of sequences in a genome is an important step in understanding functions, the eventual expression of these genomic information storehouses and their regulation give a comprehensive view of the biological landscape.
The central dogma of molecular biology as proposed by the legendary Francis Crick is DNA -> RNA -> Protein. Proteins are the molecular machines enabling life to happen, while RNA is the messenger that facilitates the making of molecular machines from information stored in DNA. Genomic sequencing efforts began with the understanding that a total complement of the proteins present in a cell can be deduced from reading the genetic information stored in a cell's genome. This goal has been largely achieved due to the advancements in many areas of biology and informational sciences.
While the entire genome is present in any given cell, only a subset of genes is expressed (e.g. made into proteins) at any given time or under a given set of conditions. During the early days of understanding gene expression, the presence and levels of 'interesting' gene or a handful of genes was queried. A technique that got popularized as 'northern blotting' was the main work horse for gene expression profiling. With the realization that large gene networks are responsible for the changing landscapes of cells and the increasing availability of technologies to study system-level phenomena, the need to look at all the expressed genes, in a high throughput way, in a given cell under specific conditions became imperative. Several tools have been developed to address this need but one specific technology that revolutionized gene expression analysis is that of microarrays.
Gene microarrays rose as a product of genome sequencing projects, sophistication reached in robotics and advanced computation. The first microarrays were made as platforms in the size of microscope slides, which hosted the signature sequences of a very large set of genes present in a genome. Slowly they evolved into a whole genome platforms, encompassing all genes (known and predicted) that would be expressed under a variety of conditions.
The main principle behind the working of microarrays as a gene expression analysis tool is an extension of the Nucleic Acid Blotting principle - the complementarity of nucleotides present in DNA and RNA (A=T/U; G?C). RNA of a given gene has a complementary sequence to that of the template strand in DNA. This allows the use of short fragments of sequences as baits to all possible genes, and querying which of the genes are being expressed.
Two main methods of microarray fabrication have evolved over the years - spotting of oligonucleotides or gene fragments onto glass slides and in situ synthesis of synthetic oligonucleotides onto solid supports. These methods cater to a wide variety of R&D needs in a wide range of sectors, beyond their first usage in gene expression analysis.
Some of the well-known microarray players in the world are Affymetrix, Agilent, Combimatrix and Nimblegen. MWG arrays, which have been very widely used, are now known as ocichip arrays after ocimum biosolutions. A Hyderabad based biotechnology company has acquired the microarray division from MWG biotech in 2005. Today, ocimum is not only competing in the traditional whole genome array space, but also creating several novel array platforms for researchers across the world to use. Indian researchers are no longer behind in exploiting this technology and as this technology matures, we look forward to see more innovations coming from Indian R&D labs.
The first studies using microarrays tried to find out what genes are expressed in cells under different physiological conditions. The concept was soon extended to understanding the differences in gene expression profiles between normal and diseased tissues. These studies helped the discovery of diagnostic marker genes and potential drug targets. Focused arrays on specific diseases and biological pathways are also being employed to address specific hypotheses. These arrays enable a closer look at the gene expression in diseases like cancer, diabetes and inflammation.
Today microarrays are being used in understanding not just what genes are differentially expressed, but how they could be differentially expressed. The binding of transcription factors to promoter DNA sequences (using ChIP-on-chip assays) is one example where the dynamics of genome function is being understood. As new biological phenomena are being observed, e.g. the role of non-coding RNA (microRNA) in gene regulation, microarray technology is dynamically conforming to the needs of researchers.
In addition to their contribution to a systems-level understanding of biological processes, microarrays have been adapted to facilitate pharmacogenomics. When personalized medicine is at the horizon, understanding the genotype of each patient in the context of a specific drug or treatment regimen is essential. Microarrays facilitate the analysis of individual genotypes, thereby allowing the prediction of drug efficacies and effectiveness in patients. An FDA approved pharmacogenomic microarray tool (AmpliChipTM from Affymetrix and Roche) is a testimony to how this technology is evolving to revolutionize diagnosis, and to make personalized medicine a reality.
On the infectious diseases front, and broadly on species identification, microarrays are showing great promise in the detection of multiple organisms and strains in a given sample. If a patient is suffering from multiple pathogen infection, traditional symptomatic diagnosis might not be able to do justice. This is especially a concern in insect vector borne diseases or water-borne diseases, where multiple pathogens can be easily transmitted to the host. Using microarrays for multiple pathogen detection, a variation of genotypic analysis, would not only help patients but also help epidemiological studies, thereby strengthening public health initiatives throughout the country.
In sum, microarrays are rising to the occasion to cater to all the high throughput needs of researchers interested in transcriptional profiling, genotyping, splice-variant analysis, identification of unknown exons and epigenetic studies. They show great promise to be the right tools that can be employed in resequencing genomes and large-scale sequencing of new organisms. It might not be an unrealistic proposition that a universal microarray is available in the near future, allowing researchers to ask any biological question that they are interested in
(The author is chief executive officer of Ocimum Biosolutions)