Transcriptome and glycome profiling of human hematopoietic CD133+ and CD34+ cells

New blood cells are continuously provided by self-renewing multipotent hematopoietic stem cells (HSC). The capacity of HSCs to regenerate the hematopoietic system is utilized in the treatment of patients with hematological malignancies. HSCs can be enriched using an antibody-based recognition of CD34 or CD133 glycoproteins on the cell surface. The CD133+ and CD34+ cells may have partly different roles in hematopoiesis. Furthermore, each cell has a glycome typical for that cell type. Knowledge of HSC glycobiology can be used to design therapeutic cells with improved cell proliferation or homing properties. The present studies characterize the global gene expression profile of human cord blood-derived CD133+ and CD34+ cells, and demonstrate the differences between CD133+ and CD34+ cell populations that may have an impact in transplantation when CD133+ and CD34+ selected cells are used. In addition, these studies unravel the glycome profile of primitive hematopoietic cells and reveal the transcriptional regulation of N-glycan biosynthesis in CD133+ and CD34+ cells. The gene expression profile of CD133+ cells represents 690 differentially expressed transcripts between CD133+ cells and CD133- cells. CD34+ cells have 620 transcripts differentially expressed when compared to CD34- cells. The integrated CD133+/CD34+ cell gene expression profiles proffer novel transcripts to specify HSCs. Furthermore, the differences between the gene expression profiles of CD133+ and CD34+ cells indicate differences in the transcriptional regulation of CD133+ and CD34+ cells. CD133+ cells express a lower number of hematopoietic lineage differentiation marker genes than CD34+ cells. The expression profiles suggest a more primitive nature of CD133+ cells. Moreover, CD133+ cells have characteristic glycome that differ from the glycome of CD133- cells. High mannose-type and biantennary complex-type N-glycans are enriched in CD133+ cells. N-glycosylation-related gene expression pattern of CD133+ cells identify the key genes regulating the CD133+ cell-specific glycosylation including the overexpression of MGAT2 and underexpression of MGAT4. The putative role of MAN1C1 in the increase of unprocessed high mannose-type N-glycans in CD133+ cells is also discussed. These studies provide new information on the characteristics of HSCs. Improved understanding of HSC biology can be used to design therapeutic cells with improved cell proliferation and homing properties. As a result, HSC engineering could further their clinical use.

Transcriptome and proteome analysis of xylose-metabolising Saccharomyces cerevisiae

Increasing concern about global climate warming has accelerated research into renewable energy sources that could replace fossil petroleum-based fuels and materials. Bioethanol production from cellulosic biomass by fermentation with baker s yeast Saccharomyces cerevisiae is one of the most studied areas in this field. The focus has been on metabolic engineering of S. cerevisiae for utilisation of the pentose sugars, in particular D-xylose that is abundant in the hemicellulose fraction of biomass. Introduction of a heterologous xylose-utilisation pathway into S. cerevisiae enables xylose fermentation, but ethanol yield and productivity do not reach the theoretical level. In the present study, transcription, proteome and metabolic flux analyses of recombinant xylose-utilising S. cerevisiae expressing the genes encoding xylose reductase (XR) and xylitol dehydrogenase (XDH) from Pichia stipitis and the endogenous xylulokinase were carried out to characterise the global cellular responses to metabolism of xylose. The aim of these studies was to find novel ways to engineer cells for improved xylose fermentation. The analyses were carried out from cells grown on xylose and glucose both in batch and chemostat cultures. A particularly interesting observation was that several proteins had post-translationally modified forms with different abundance in cells grown on xylose and glucose. Hexokinase 2, glucokinase and both enolase isoenzymes 1 and 2 were phosphorylated differently on the two different carbon sources studied. This suggests that phosphorylation of glycolytic enzymes may be a yet poorly understood means to modulate their activity or function. The results also showed that metabolism of xylose affected the gene expression and abundance of proteins in pathways leading to acetyl-CoA synthesis and altered the metabolic fluxes in these pathways. Additionally, the analyses showed increased expression and abundance of several other genes and proteins involved in cellular redox reactions (e.g. aldo-ketoreductase Gcy1p and 6-phosphogluconate dehydrogenase) in cells grown on xylose. Metabolic flux analysis indicated increased NADPH-generating flux through the oxidative part of the pentose phosphate pathway in cells grown on xylose. The most importantly, results indicated that xylose was not able to repress to the same extent as glucose the genes of the tricarboxylic acid and glyoxylate cycles, gluconeogenesis and some other genes involved in the metabolism of respiratory carbon sources. This suggests that xylose is not recognised as a fully fermentative carbon source by the recombinant S. cerevisiae that may be one of the major reasons for the suboptimal fermentation of xylose. The regulatory network for carbon source recognition and catabolite repression is complex and its functions are only partly known. Consequently, multiple genetic modifications and also random approaches would probably be required if these pathways were to be modified for further improvement of xylose fermentation by recombinant S. cerevisiae strains.

Studies of the Human Transcriptome

Gene expression is one of the most critical factors influencing the phenotype of a cell. As a result of several technological advances, measuring gene expression levels has become one of the most common molecular biological measurements to study the behaviour of cells. The scientific community has produced enormous and constantly increasing collection of gene expression data from various human cells both from healthy and pathological conditions. However, while each of these studies is informative and enlighting in its own context and research setup, diverging methods and terminologies make it very challenging to integrate existing gene expression data to a more comprehensive view of human transcriptome function. On the other hand, bioinformatic science advances only through data integration and synthesis. The aim of this study was to develop biological and mathematical methods to overcome these challenges and to construct an integrated database of human transcriptome as well as to demonstrate its usage. Methods developed in this study can be divided in two distinct parts. First, the biological and medical annotation of the existing gene expression measurements needed to be encoded by systematic vocabularies. There was no single existing biomedical ontology or vocabulary suitable for this purpose. Thus, new annotation terminology was developed as a part of this work. Second part was to develop mathematical methods correcting the noise and systematic differences/errors in the data caused by various array generations. Additionally, there was a need to develop suitable computational methods for sample collection and archiving, unique sample identification, database structures, data retrieval and visualization. Bioinformatic methods were developed to analyze gene expression levels and putative functional associations of human genes by using the integrated gene expression data. Also a method to interpret individual gene expression profiles across all the healthy and pathological tissues of the reference database was developed. As a result of this work 9783 human gene expression samples measured by Affymetrix microarrays were integrated to form a unique human transcriptome resource GeneSapiens. This makes it possible to analyse expression levels of 17330 genes across 175 types of healthy and pathological human tissues. Application of this resource to interpret individual gene expression measurements allowed identification of tissue of origin with 92.0% accuracy among 44 healthy tissue types. Systematic analysis of transcriptional activity levels of 459 kinase genes was performed across 44 healthy and 55 pathological tissue types and a genome wide analysis of kinase gene co-expression networks was done. This analysis revealed biologically and medically interesting data on putative kinase gene functions in health and disease. Finally, we developed a method for alignment of gene expression profiles (AGEP) to perform analysis for individual patient samples to pinpoint gene- and pathway-specific changes in the test sample in relation to the reference transcriptome database. We also showed how large-scale gene expression data resources can be used to quantitatively characterize changes in the transcriptomic program of differentiating stem cells. Taken together, these studies indicate the power of systematic bioinformatic analyses to infer biological and medical insights from existing published datasets as well as to facilitate the interpretation of new molecular profiling data from individual patients.

Studies on Causes of Multiple Sclerosis : From Genes to Transcriptome

Multiple sclerosis (MS) is the most common cause of neurological disability in young adults, affecting more than two million people worldwide. It manifests as a chronic inflammation in the central nervous system (CNS) and causes demyelination and neurodegeneration. Depending on the location of the demyelinated plaques and axonal loss, a variety of symptoms can be observed including deficits in vision, coordination, balance and movement. With a typical age of onset at 20-40 years, the social and economic impacts of MS on lives of the patients and their families are considerable. Unfortunately the current treatments are relatively inefficient and the development of more effective treatments has been impeded by our limited understanding of the causes and pathogenesis of MS. Risk of MS is higher in biological relatives of MS patients than in the general population. Twin and adoption studies have shown that familial clustering of MS is explained by shared genetic factors rather than by shared familial environment. While the involvement of the human leukocyte antigen (HLA) genes was first discovered four decades ago, additional genetic risk factors have only recently been identified through genome-wide association studies (GWAS). Current evidence suggests that MS is a highly polygenic disease with perhaps hundreds of common variants with relatively modest effects contributing to susceptibility. Despite extensive research, the majority of these risk factors still remain to be identified. In this thesis the aim was to identify novel genes and pathways involved in MS. Using genome-wide microarray technology, gene expression levels in peripheral blood mononuclear cells (PBMC) from 12 MS patients and 15 controls were profiled and more than 600 genes with altered expression in MS were identified. Three of five selected findings, DEFA1A3, LILRA4 and TNFRSF25, were successfully replicated in an independent sample. Increased expression of DEFA1A3 in MS is a particularly interesting observation, because its elevated levels have previously been reported also in several other autoimmune diseases. A systematic review of seven microarray studies was then performed leading to identification of 229 genes, in which either decreased or increased expression in MS had been reported in at least two studies. In general there was relatively little overlap across the experiments: 11 of the 229 genes had been reported in three studies and only HSPA1A in four studies. Nevertheless, these 229 genes were associated with several immunological pathways including interleukin pathways related to type 2 and type 17 helper T cells and regulatory T cells. However, whether these pathways are involved in causing MS or related to secondary processes activated after disease onset remains to be investigated. The 229 genes were also compared with loci identified in published MS GWASs. Single nucleotide polymorphisms (SNP) in 17 of the 229 loci had been reported to be associated with MS with P-value less than 0.0001 including variants in CXCR4 and SAPS2, which were the only loci where evidence for correlation between the associated variant and gene expression was found. The CXCR4 variant was further tested for association with MS in a large case-control sample and the previously reported suggestive association was replicated (P-value is 0.0004). Finally, common genetic variants in candidate genes, which had been selected on the basis of showing association with other autoimmune diseases (MYO9B) or showing differential expression in MS in our study (DEFA1A3, LILRA4 and TNFRSF25), were tested for association with MS, but no evidence of association was found. In conclusion, through a systematic review of genome-wide expression studies in MS we have identified several promising candidate genes and pathways for future studies. In addition, we have replicated a previously suggested association of a SNP variant upstream of CXCR4 with MS. Keywords: autoimmune disease, common variant, CXCR4, DEFA1A3, HSPA1A,gene expression, genetic association, GWAS, MS, multiple sclerosis, systematic review

Construction of a global map of human gene expression : the process, tools and analysis

This thesis studies human gene expression space using high throughput gene expression data from DNA microarrays. In molecular biology, high throughput techniques allow numerical measurements of expression of tens of thousands of genes simultaneously. In a single study, this data is traditionally obtained from a limited number of sample types with a small number of replicates. For organism-wide analysis, this data has been largely unavailable and the global structure of human transcriptome has remained unknown. This thesis introduces a human transcriptome map of different biological entities and analysis of its general structure. The map is constructed from gene expression data from the two largest public microarray data repositories, GEO and ArrayExpress. The creation of this map contributed to the development of ArrayExpress by identifying and retrofitting the previously unusable and missing data and by improving the access to its data. It also contributed to creation of several new tools for microarray data manipulation and establishment of data exchange between GEO and ArrayExpress. The data integration for the global map required creation of a new large ontology of human cell types, disease states, organism parts and cell lines. The ontology was used in a new text mining and decision tree based method for automatic conversion of human readable free text microarray data annotations into categorised format. The data comparability and minimisation of the systematic measurement errors that are characteristic to each lab- oratory in this large cross-laboratories integrated dataset, was ensured by computation of a range of microarray data quality metrics and exclusion of incomparable data. The structure of a global map of human gene expression was then explored by principal component analysis and hierarchical clustering using heuristics and help from another purpose built sample ontology. A preface and motivation to the construction and analysis of a global map of human gene expression is given by analysis of two microarray datasets of human malignant melanoma. The analysis of these sets incorporate indirect comparison of statistical methods for finding differentially expressed genes and point to the need to study gene expression on a global level.

Stress responses of Gram-positive bacteria to cationic antimicrobial peptides

As the resistance of bacteria to conventional antibiotics has become an increasing problem, new antimicrobial drugs are urgently needed. One possible source of new antibacterial agents is a group of cationic antimicrobial peptides (CAMPs) produced by practically all living organisms. These peptides are typically small, amphipathic and positively charged and contain well defined a-helical or b-sheet secondary structures. The main antibacterial action mechanism of CAMPs is considered to be disruption of the cell membrane, but other targets of CAMPs also exist. Some bacterial species have evolved defence mechanisms against the harmful effects of CAMPs. One of the most effective defence mechanisms is reduction of the net negative charge of bacterial cell surfaces. Global analysis of gene expression of two Gram-positive bacteria, Bacillus subtilis and Staphylococcus aureus, was used to further study the stress responses induced by different types of CAMPs. B. subtilis cells were treated with sublethal concentrations of a-helical peptide LL-37, b-sheet peptide protegrin 1 or synthetic analogue poly-L-lysine, and the changes in gene expression were studied using DNA macroarrays. In the case of S. aureus, three different a-helical peptides were selected for the transcriptome analyses: temporin L, ovispirin-1 and dermaseptin K4-S4(1-16). Transcriptional changes caused by peptide stress were examined using oligo DNA microarrays. The transcriptome analysis revealed two main cell signalling mechanisms mediating CAMP stress responses in Gram-positive bacteria: extracytoplasmic function (ECF)sigma factors and two-component systems (TCSs). In B. subtilis, ECF sigma factors sigW and sigM as well as TCS LiaRS responded to the cell membrane disruption caused by CAMPs. In S. aureus, CAMPs caused a similar stress response to antibiotics interfering in cell wall synthesis, and TCS VraSR was strongly activated. All of these transcriptional regulators are known to respond to several compounds other than CAMPs interfering with cell envelope integrity, suggesting that they sense cell envelope stress in general. Among the most strongly induced genes were yxdLM (in B. subtilis) and vraDE (in S. aureus) encoding homologous ABC transporters. Transcription of yxdLM and vraDE operons is controlled by TCSs YxdJK and ApsRS, respectively. These TCSs seemed to be responsible for the direct recognition of CAMPs. The yxdLM operon was specifically induced by LL-37, but its role in CAMP resistance remained unclear. VraDE was proven to be a bacitracin transporter. We also showed that the net positive charge of the cell wall affects the signalrecognition of different TCSs responding to cell envelope stress. Inactivation of the Dlt system responsible for the D-alanylation of teichoic acids had a strong and differential effect on the activity of the studied TCSs, depending on their functional role in cells and the stimuli they sense.

Effects of oxygen provision on the physiology of baker's yeast Saccharomyces cerevisiae

The availability of oxygen has a major effect on all organisms. The yeast Saccharomyces cerevisiae is able to adapt its metabolism for growth in different conditions of oxygen provision, and to grow even under complete lack of oxygen. Although the physiology of S. cerevisiae has mainly been studied under fully aerobic and anaerobic conditions, less is known of metabolism under oxygen-limited conditions and of the adaptation to changing conditions of oxygen provision. This study compared the physiology of S. cerevisiae in conditions of five levels of oxygen provision (0, 0.5, 1.0, 2.8 and 20.9% O2 in feed gas) by using measurements on metabolite, transcriptome and proteome levels. On the transcriptional level, the main differences were observed between the three level groups, 0, 0.5 2.8 and 20.9% O2 which led to fully fermentative, respiro-fermentative and fully respiratory modes of metabolism, respectively. However, proteome analysis suggested post-transcriptional regulation at the level of 0.5 O2. The analysis of metabolite and transcript levels of central carbon metabolism also suggested post-transcriptional regulation especially in glycolysis. Further, a global upregulation of genes related to respiratory pathways was observed in the oxygen-limited conditions and the same trend was seen in the proteome analysis and in the activities of enzymes of the TCA cycle. The responses of intracellular metabolites related to central carbon metabolism and transcriptional responses to change in oxygen availability were studied. As a response to sudden oxygen depletion, concentrations of the metabolites of central carbon metabolism responded faster than the corresponding levels of gene expression. In general, the genome-wide transcriptional responses to oxygen depletion were highly similar when two different initial conditions of oxygen provision (20.9 and 1.0% O2) were compared. The genes related to growth and cell proliferation were transiently downregulated whereas the genes related to protein degradation and phosphate uptake were transiently upregulated. In the cultures initially receiving 1.0% O2, a transient upregulation of genes related to fatty acid oxidation, peroxisomal biogenesis, response to oxidative stress and pentose phosphate pathway was observed. Additionally, this work analysed the effect of oxygen on transcription of genes belonging to the hexose transporter gene family. Although the specific glucose uptake rate was highest in fully anaerobic conditions, none of the hxt genes showed highest expression in anaerobic conditions. However, the expression of genes encoding the moderately low affinity transporters decreased with the decreasing oxygen level. Thus it was concluded that there is a relative increase in high affinity transport in anaerobic conditions supporting the high uptake rate.

Comparative and functional genome analysis of fungi for development of the protein production host Trichoderma reesei

Filamentous fungi of the subphylum Pezizomycotina are well known as protein and secondary metabolite producers. Various industries take advantage of these capabilities. However, the molecular biology of yeasts, i.e. Saccharomycotina and especially that of Saccharomyces cerevisiae, the baker's yeast, is much better known. In an effort to explain fungal phenotypes through their genotypes we have compared protein coding gene contents of Pezizomycotina and Saccharomycotina. Only biomass degradation and secondary metabolism related protein families seem to have expanded recently in Pezizomycotina. Of the protein families clearly diverged between Pezizomycotina and Saccharomycotina, those related to mitochondrial functions emerge as the most prominent. However, the primary metabolism as described in S. cerevisiae is largely conserved in all fungi. Apart from the known secondary metabolism, Pezizomycotina have pathways that could link secondary metabolism to primary metabolism and a wealth of undescribed enzymes. Previous studies of individual Pezizomycotina genomes have shown that regardless of the difference in production efficiency and diversity of secreted proteins, the content of the known secretion machinery genes in Pezizomycotina and Saccharomycotina appears very similar. Genome wide analysis of gene products is therefore needed to better understand the efficient secretion of Pezizomycotina. We have developed methods applicable to transcriptome analysis of non-sequenced organisms. TRAC (Transcriptional profiling with the aid of affinity capture) has been previously developed at VTT for fast, focused transcription analysis. We introduce a version of TRAC that allows more powerful signal amplification and multiplexing. We also present computational optimisations of transcriptome analysis of non-sequenced organism and TRAC analysis in general. Trichoderma reesei is one of the most commonly used Pezizomycotina in the protein production industry. In order to understand its secretion system better and find clues for improvement of its industrial performance, we have analysed its transcriptomic response to protein secretion stress conditions. In comparison to S. cerevisiae, the response of T. reesei appears different, but still impacts on the same cellular functions. We also discovered in T. reesei interesting similarities to mammalian protein secretion stress response. Together these findings highlight targets for more detailed studies.

A proteomic view of probiotic Lactobacillus rhamnosus GG

Lactobacillus rhamnosus GG is a probiotic bacterium that is known worldwide. Since its discovery in 1985, the health effects and biology of this health-promoting strain have been researched at an increasing rate. However, knowledge of the molecular biology responsible for these health effects is limited, even though research in this area has continued to grow since the publication of the whole genome sequence of L. rhamnosus GG in 2009. In this thesis, the molecular biology of L. rhamnosus GG was explored by mapping the changes in protein levels in response to diverse stress factors and environmental conditions. The proteomics data were supplemented with transcriptome level mapping of gene expression. The harsh conditions of the gastro-intestinal tract, which involve acidic conditions and detergent-like bile acids, are a notable challenge to the survival of probiotic bacteria. To simulate these conditions, L. rhamnosus GG was exposed to a sudden bile stress, and several stress response mechanisms were revealed, among others various changes in the cell envelope properties. L. rhamnosus GG also responded in various ways to mild acid stress, which probiotic bacteria may face in dairy fermentations and product formulations. The acid stress response of L. rhamnosus GG included changes in central metabolism and specific responses related to the control of intracellular pH. Altogether, L. rhamnosus GG was shown to possess a large repertoire of mechanisms for responding to stress conditions, which is a beneficial character of a probiotic organism. Adaptation to different growth conditions was studied by comparing the proteome level responses of L. rhamnosus GG to divergent growth media and to different phases of growth. Comparing different growth phases revealed that the metabolism of L. rhamnosus GG is modified markedly during shift from the exponential to the stationary phase of growth. These changes were seen both at proteome and transcriptome levels and in various different cellular functions. When the growth of L. rhamnosus GG in a rich laboratory medium and in an industrial whey-based medium was compared, various differences in metabolism and in factors affecting the cell surface properties could be seen. These results led us to recommend that the industrial-type media should be used in laboratory studies of L. rhamnosus GG and other probiotic bacteria to achieve a similar physiological state for the bacteria as that found in industrial products, which would thus yield more relevant information about the bacteria. In addition, an interesting phenomenon of protein phosphorylation was observed in L. rhamnosus GG. Phosphorylation of several proteins of L. rhamnosus GG was detected, and there were hints that the degree of phosphorylation may be dependent on the growth pH.