Gene Expression : From Microarrays to Functional Genomics

The time of the large sequencing projects has enabled unprecedented possibilities of investigating more complex aspects of living organisms. Among the high-throughput technologies based on the genomic sequences, the DNA microarrays are widely used for many purposes, including the measurement of the relative quantity of the messenger RNAs. However, the reliability of microarrays has been strongly doubted as robust analysis of the complex microarray output data has been developed only after the technology had already been spread in the community. An objective of this study consisted of increasing the performance of microarrays, and was measured by the successful validation of the results by independent techniques. To this end, emphasis has been given to the possibility of selecting candidate genes with remarkable biological significance within specific experimental design. Along with literature evidence, the re-annotation of the probes and model-based normalization algorithms were found to be beneficial when analyzing Affymetrix GeneChip data. Typically, the analysis of microarrays aims at selecting genes whose expression is significantly different in different conditions followed by grouping them in functional categories, enabling a biological interpretation of the results. Another approach investigates the global differences in the expression of functionally related groups of genes. Here, this technique has been effective in discovering patterns related to temporal changes during infection of human cells. Another aspect explored in this thesis is related to the possibility of combining independent gene expression data for creating a catalog of genes that are selectively expressed in healthy human tissues. Not all the genes present in human cells are active; some involved in basic activities (named housekeeping genes) are expressed ubiquitously. Other genes (named tissue-selective genes) provide more specific functions and they are expressed preferably in certain cell types or tissues. Defining the tissue-selective genes is also important as these genes can cause disease with phenotype in the tissues where they are expressed. The hypothesis that gene expression could be used as a measure of the relatedness of the tissues has been also proved. Microarray experiments provide long lists of candidate genes that are often difficult to interpret and prioritize. Extending the power of microarray results is possible by inferring the relationships of genes under certain conditions. Gene transcription is constantly regulated by the coordinated binding of proteins, named transcription factors, to specific portions of the its promoter sequence. In this study, the analysis of promoters from groups of candidate genes has been utilized for predicting gene networks and highlighting modules of transcription factors playing a central role in the regulation of their transcription. Specific modules have been found regulating the expression of genes selectively expressed in the hippocampus, an area of the brain having a central role in the Major Depression Disorder. Similarly, gene networks derived from microarray results have elucidated aspects of the development of the mesencephalon, another region of the brain involved in Parkinson Disease.

Plasmids and aromatic degradation in Sphingomonas for bioremediation : Aromatic ring cleavage genes in soil and rhizosphere

Microbial degradation pathways play a key role in the detoxification and the mineralization of polyaromatic hydrocarbons (PAHs), which are widespread pollutants in soil and constituents of petroleum hydrocarbons. In microbiology the aromatic degradation pathways are traditionally studied from single bacterial strains with capacity to degrade certain pollutant. In soil the degradation of aromatics is performed by a diverse community of micro-organisms. The aim of this thesis was to study biodegradation on different levels starting from a versatile aromatic degrader Sphingobium sp. HV3 and its megaplasmid, extending to revelation of diversity of key catabolic enzymes in the environment and finally studying birch rhizoremediation in PAH-polluted soil. To understand biodegradation of aromatics on bacterial species level, the aromatic degradation capacity of Sphingobium sp. HV3 and the role of the plasmid pSKY4, was studied. Toluene, m-xylene, biphenyl, fluorene, phenanthrene were detected as carbon and energy sources of the HV3 strain. Tn5 transposon mutagenesis linked the degradation capacity of toluene, m-xylene, biphenyl and naphthalene to the pSKY4 plasmid and qPCR expression analysis showed that plasmid extradiol dioxygenases genes (bphC and xylE) are inducted by phenanthrene, m-xylene and biphenyl whereas the 2,4-dichlorophenoxyacetic acid herbicide induced the chlorocatechol 1,2-dioxygenase gene (tfdC) from the ortho-pathway. A method to study upper meta-pathway extradiol dioxygenase gene diversity in soil was developed. The extradiol dioxygenases catalyse cleavage of the aromatic ring between a hydroxylated carbon and an adjacent non-hydroxylated carbon (meta-cleavage). A high diversity of extradiol dioxygenases were detected from polluted soils. The detected extradiol dioxygenases showed sequence similarity to known catabolic genes of Alpha-, Beta-, and Gammaproteobacteria. Five groups of extradiol dioxygenases contained sequences with no close homologues in the database, representing novel genes. In rhizoremediation experiment with birch (Betula pendula) treatment specific changes of extradiol dioxygenase communities were shown. PAH pollution changed the bulk soil extradiol dioxygenase community structure and birch rhizosphere contained a more diverse extradiol dioxygenase community than the bulk soil showing a rhizosphere effect. The degradation of pyrene in soil was enhanced with birch seedlings compared to soil without birch. The complete 280,923 kb nucleotide sequence of pSKY4 plasmid was determined. The open reading frames of pSKY4 were divided into putative conjugative transfer, aromatic degradation, replication/maintaining and transposition/integration function-encoding proteins. Aromatic degradation orfs shared high similarity to corresponding genes in pNL1, a plasmid from the deep subsurface strain Novosphingobium aromaticivorans F199. The plasmid backbones were considerably more divergent with lower similarity, which suggests that the aromatic pathway has functioned as a plasmid independent mobile genetic element. The functional diversity of microbial communities in soil is still largely unknown. Several novel clusters of extradiol dioxygenases representing catabolic bacteria, whose function, biodegradation pathways and phylogenetic position is not known were amplified with single primer pair from polluted soils. These extradiol dioxygenase communities were shown to change upon PAH pollution, which indicates that their hosts function in PAH biodegradation in soil. Although the degradation pathways of specific bacterial species are substantially better depicted than pathways in situ, the evolution of degradation pathways for the xenobiotic compounds is largely unknown. The pSKY4 plasmid contains aromatic degradation genes in putative mobile genetic element causing flexibility/instability to the pathway. The localisation of the aromatic biodegradation pathway in mobile genetic elements suggests that gene transfer and rearrangements are a competetive advantage for Sphingomonas bacteria in the environment.

Monitoring Indigenous Tropical Montane Forests in the Taita Hills Using Airborne Digital Camera Imagery

The loss and degradation of forest cover is currently a globally recognised problem. The fragmentation of forests is further affecting the biodiversity and well-being of the ecosystems also in Kenya. This study focuses on two indigenous tropical montane forests in the Taita Hills in southeastern Kenya. The study is a part of the TAITA-project within the Department of Geography in the University of Helsinki. The study forests, Ngangao and Chawia, are studied by remote sensing and GIS methods. The main data includes black and white aerial photography from 1955 and true colour digital camera data from 2004. This data is used to produce aerial mosaics from the study areas. The land cover of these study areas is studied by visual interpretation, pixel-based supervised classification and object-oriented supervised classification. The change of the forest cover is studied with GIS methods using the visual interpretations from 1955 and 2004. Furthermore, the present state of the study forests is assessed with leaf area index and canopy closure parameters retrieved from hemispherical photographs as well as with additional, previously collected forest health monitoring data. The canopy parameters are also compared with textural parameters from digital aerial mosaics. This study concludes that the classification of forest areas by using true colour data is not an easy task although the digital aerial mosaics are proved to be very accurate. The best classifications are still achieved with visual interpretation methods as the accuracies of the pixel-based and object-oriented supervised classification methods are not satisfying. According to the change detection of the land cover in the study areas, the area of indigenous woodland in both forests has decreased in 1955 2004. However in Ngangao, the overall woodland area has grown mainly because of plantations of exotic species. In general, the land cover of both study areas is more fragmented in 2004 than in 1955. Although the forest area has decreased, forests seem to have a more optimistic future than before. This is due to the increasing appreciation of the forest areas.