Depending on surrounding conditions – e.g. nutrient availability, stress factors or physical parameters - the gene expression of organisms can vary widely. The proxy for gene activity is the messenger RNA (mRNA). The aim of transcriptomics is to capture this information. While transcriptomics deals with the gene expression of single species, metatranscriptomics covers the gene activity profile of the whole community. 


Its applications are manifold: In combination with contextual data, gene expression profiling helps to unravel gene functions. It teaches us, which metabolic pathways are in use under the respective conditions and how the organisms interact with the environment. Hence, it can be applied for environmental monitoring and for the identification of key genes. On the other hand, transcriptomics also play a role in clinical diagnosis and in screening for drug targets or for genes, enzymes and metabolites relevant for biotechnology.



Gene expression analysis techniques were subject to dramatical changes over the last 30 years.

The Northern Blotting technique was developed in the seventies (Alwin et al. 1977) and thus enabled the first gene expression studies. The possibility to analyse gene activity was extended by the creation of RT-PCR around 1990 (Wang et al. 1989).



While both methods are useful if an experiment focuses on few genes microarrays, developed in the early nineties (Schena et al. 1995), were the key to analyse the expression of many genes or even whole genomes in parallel. This high-through-put technology is based on the principle of complementary hybridisation (Figure 1). Gene specific capture oligo-nucleotide probes are immobilized on a solid surface. The template RNA is transcribed to cDNA, labelled with a fluorescence dye and placed on the microarray. In case an mRNA copy of a gene was present in the original sample, its cDNA copy will hybridize to the probe for the respective gene. With high density arrays the expression of ten thousands of genes can be analysed simultaneously.



Figure 1: Sheme of complementary hybridization on a microarray



Recently the so-called Next Generation sequencing (NGS) technologies were developed (Margulies et al. 2005). Being first applied for genomic purposes (Link to MIMAS Genomic page), these methods were soon expanded into the field of transcriptomics and especially the metatranscriptomics. The common basic principle is the sequencing by synthesis of a new DNA strand, which is complementary to the template DNA/cDNA strand. 

In the first step of the procedure, the cDNA or respectively the DNA derived from environmental samples is attached to tiny beads and thus singularised. The cDNA/DNA strand on each bead is amplified. The beads are transferred to a microtiter plate with approximately 1.200.000 wells. The aim is to obtain one bead per well, which is then treated separately, but in parallel with all other beads. Next, sequencing enzymes are added. During the sequencing procedure, the four bases of which DNA consists are added, one at a time. In case the nucleotide is complementary to the template base, it is incorporated and a signal is generated. Subsequently, a complementary strand is generated and the sequence read-out.

The method is illustrated at



Fields of application for Microarrays & NGS

Microarrays are a useful screening tool for a defined search space – for example for the work with pure cultures of already fully sequenced species or for detailed studies of the expression of key genes. However, Microarrays are limited to genes with known sequences.

Pyrosequencing qualifies due to an enormous high through-put (1.200.000 reads in one run) and its capability to cover unknown sequences. Especially in a project like MIMAS, which goal it is to explore the existence and activity of both known and unknown genes in the environment, it is indispensable.

Hence, in MIMAS we will use Microarrays to observe the reaction of model organisms to changes in culture conditions as well as for the validation of the new techniques, but move on to Pyrosequencing mainly for the exploration of environmental samples.




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