- Functional genomics, new tools in malaria research
The word “transcriptome” is gaining increasing popularity since genome sequence data and functional genomic approaches became constitutive elements of modern biology. Transcriptome is the complement of mature messenger RNAs produced in a given cell in a given moment of its life. Although the transcriptome is not rigidly translated in the proteome of that cell, nevertheless it is in most cases largely representative of the cell protein population, and, importantly, it represents a key step in executing the genetic program of differentiation ongoing in that cell.
From the disclosure of the genome sequence of P. falciparum, and, more recently, with the availability of genome data from rodent Plasmodia, transcriptome analysis became a key tool in investigating the biology of the malaria parasite. A recent technology of major importance for these studies is represented by DNA microarrays. DNA sequences specific for all predicted malaria genes, in the form of cDNAs or long oligonucleotides, can be placed in ordered arrays in minute portions of a glass slide, where they can be hybridised by fluorescent cDNAs representing the mRNA complement of the parasite. Our laboratory utilises the type of microarrays shown in Fig. 1, panel A, in which about 7500 long oligonucleotides representative of about 4500 P. falciparum genes are spotted in an area of approximately 2 cm2. This microarray is hybridised with cDNA from the parasite sample under study, usually labelled with the red fluorescent Cyanine-5, and simultaneously with a control or reference cDNA, labelled with the green fluorescent Cyanine-3. The ratio of red versus green fluorescence for each spot of the microarray provides a quantitative measure of the relative expression level of the gene corresponding to that spot. Simple direct comparisons between two parasite stages or treatments, or more complex time course analyses can thus be performed in order to study how the entire repertoire of Plasmodium genes are regulated under the conditions of an experiment.
A few reference studies have been conducted so far with the technology of microarray on human and rodent malaria parasites, and provided relevant cues to understanding Plasmodium biology and development. One of them revealed that in the 48 hours of P. falciparum asexual cycle, the parasite activates sequential waves of gene expression in which almost 80% of its gene complement is positively regulated . Other studies on P. falciparum, P. berghei and P. yoelii confirmed that the different developmental stages of the parasite are accompanied by the expression of large sets of stage-specific transcripts, and indicated that the physiology of each stage is a highly elaborate interaction of constituve and specialised parasite molecules [6, 7].
Our group utilised microarrays specific for P. falciparum with the objective to study a very particular moment of the parasite life cycle: the early phases of parasite transformation in the gametocyte, the Plasmodium sexual cell. The gametocyte is responsible for the transmission of the parasite from the bloodstream of an infected individual to the mosquito, and it therefore represents a key step in the ability of Plasmodium to spread malaria. While gametocytes in course of maturation, after about 5-6 days of differentiation, have been shown to express specific sets of mRNAs in transcriptome and proteome analyses [6, 8, 9], the early gametocytes have been comparatively much less studied, and only two specific molecules Pfs16 and Pfg27- were described in that stage of differentiation. Since early gametocytes cannot be distinguished from small asexual forms, apart from expression of the mentioned early markers, we designed a time course experiment in which parasites producing young gametocytes in the first 40 hours of differentiation were compared with isogenic parasites unable to undergo sexual differentiation. In this experiment RNAs from various time points were hybridised on microarrays, and genes were identified which had an expression profile significantly correlated to the profiles of the genes for the early markers Pfs16 and Pfg27. Further characterisation of this group of genes led so far to identify two novel proteins specifically expressed from early stages of differentiation . This analysis and similar studies conducted in other laboratories [11, 12] were able to significantly increase in few years our knowledge of the specific molecular changes occurring in this underexplored moment of parasite differentiation, and raised new hopes to find effective ways to inhibit specific mechanisms active in early gametocytes with the aim to block parasite transmission.
Transcriptome analysis however provides the opportunity to investigate several other aspects of Plasmodium biology. Understanding parasite response to drug treatment, or identification of key specific molecules required for essential steps of its development are potentially relevant to identification of novel targets for pharmacological and immunological attack. This is a much needed activity given that the fast spread of parasite drug resistance is leaving little hope that current available antimalarial armoury will be adequate to combat the disease in the span of few years. Beside such applicative aspects, transcriptome analysis can also be utilised to enquire fundamental issues of Plasmodium biology, such as how the parasite controls the expression of its genes. The little knowledge available to date on this issue indicates that mechanisms controlling gene expression in Plasmodium recur to molecular components highly specific to the parasite, which strongly suggests that these mechanisms are likely to be attackable without significant interference and damages to homologous molecular components of the human host.
Another example of how the parasite transcriptome can be analysed is presented in Fig. 1. Four independent in-vitro cultures of P. falciparum were synchronised, parasites were sampled and their RNA extracted at two time points, at 30-34 hours and at 40-44 hours after invasion of the red blood cell. The eight cDNA samples thus obtained were all labelled with Cyanine-5, and hybridised on eight microarrays against identical aliquots of a reference cDNA from asynchronous parasites, labelled with Cyanine-3, producing eight gene expression data sets. Between the analytical tools for analysis of microarray expression data, we present here the analysis conducted with the method of Principal Component Analysis (PCA). According to this statistical technique, each of the eight experiments is viewed in a multidimensional space whose coordinates were the expression values of the 1938 genes which gave quality-controlled signals in the eight hybridisations. By applying PCA, relationships between coordinates were captured in order to find a new space in which diversities between experiments (variance) are highlighted. As it is evident from the distribution of points (experiments) in the graphic (Fig. 2, panel B), the analysis clearly distinguishes the transcriptome of parasites sampled at 30-34 hours (triangles) from that of parasite sampled ten hours later (circles). This molecular difference is clearly reflected in the morphological differences exhibited by the parasites in the two time points, i.e. the trophozoite (T) and the schizont (S), respectively (Fig. 1, panel C). In conclusion, this simply designed experiment shows that transcriptome analysis is a sentitive tool to monitor molecular differences associated to parasite development. Moreover, a closer analysis of the transcripts upregulated in one or in the other parasite stage can provide useful information on molecules active at different moment of the parasite asexual cycle. In more complex approaches, genome sequence information can be integrated in the analysis of the trancriptome in order to address questions on the regulatory mechanisms governing gene expression in P. falciparum. Transcriptome data such as those obtained in the experiment presented can for instance be utilised for inspecting genomic sequences upstream of large number of genes showing concomitant upregulation.
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