Array Comparative Genomic Hybridization in Sarcomas

Over the past years, much research on sarcomas based on low-resolution cytogenetic and molecular cytogenetic methods has been published, leading to the identification of genetic abnormalities partially underlying the tumourigenesis. Continued progress in the identification of genetic events such as copy number aberrations relies upon adapting the rapidly evolving high-resolution microarray technology, which will eventually provide novel insights into sarcoma biology, and targets for both diagnostics and drug development. The aim of this Thesis was to characterize DNA copy number changes that are involved in the pathogenesis of soft tissue leiomyosarcoma (LMS), dermatofibrosarcoma protuberans (DFSP), osteosarcoma (OS), malignant fibrous histiocytoma (MFH), and uterine leiomyosarcoma (ULMS) by applying fine resolution array comparative genomic hybridization (aCGH) technology. Both low- and high-grade LMS tumours showed distinct copy number patterns, in addition to sharing two minimal common regions of gains and losses. Small aberrations were detected by aCGH, which were beyond the resolution of chromosomal comparative genomic hybridization (cCGH). DFSP tumours analysed by aCGH showed gains in 17q, 22q, and 21 additional gained regions, but only one region (22q) with copy number loss. Recurrent amplicons identified in OS by aCGH were 12q11-q15, 8q, 6p12-p21, and 17p. Amplicons 12q and 17p were further characterized in detail. The amplicon at 17p was characterized by aCGH in low- and high-grade LMS, OS, and MFH. In all but one case this amplicon, with minimal common regions of gains at 17p11-p12, started with the distal loss of 17p13-pter. OS and high-grade LMS were grouped together as they showed a complex pattern of copy number gains and amplifications at 17p, whereas MFH and low-grade LMS showed a continuous pattern of copy number gains and amplification at 17p. In addition to the commonly gained and lost regions identified in ULMS by aCGH, various biological processes affected by these copy number changes were also indicated by pathway analysis. The three novel findings obtained in this work were: characterization of amplicon 17p in low- and high-grade LMS and MFH, profiles of DNA copy number changes in LMS, and detection of various pathways affected by copy number changes in ULMS. These studies have not been undertaken previously by aCGH technology, thus this Thesis adds new information regarding DNA copy number changes in sarcomas. In conclusion, the aCGH technique used in this Thesis has provided new insights into the genetics of sarcomas by detecting the precise regions affected by copy number changes and some potential candidate target genes within those regions, which had not been uncovered by previously applied low resolution techniques.

Characterization of genomic diversity in extraintestinal pathogenic Escherichia coli (ExPEC) and development of a diagnostic DNA microarray for the differentiation of ExPEC isolates causing urinary tract infections

Extraintestinal pathogenic Escherichia coli (ExPEC) represent a diverse group of strains of E. coli, which infect extraintestinal sites, such as the urinary tract, the bloodstream, the meninges, the peritoneal cavity, and the lungs. Urinary tract infections (UTIs) caused by uropathogenic E. coli (UPEC), the major subgroup of ExPEC, are among the most prevalent microbial diseases world wide and a substantial burden for public health care systems. UTIs are responsible for serious morbidity and mortality in the elderly, in young children, and in immune-compromised and hospitalized patients. ExPEC strains are different, both from genetic and clinical perspectives, from commensal E. coli strains belonging to the normal intestinal flora and from intestinal pathogenic E. coli strains causing diarrhea. ExPEC strains are characterized by a broad range of alternate virulence factors, such as adhesins, toxins, and iron accumulation systems. Unlike diarrheagenic E. coli, whose distinctive virulence determinants evoke characteristic diarrheagenic symptoms and signs, ExPEC strains are exceedingly heterogeneous and are known to possess no specific virulence factors or a set of factors, which are obligatory for the infection of a certain extraintestinal site (e. g. the urinary tract). The ExPEC genomes are highly diverse mosaic structures in permanent flux. These strains have obtained a significant amount of DNA (predictably up to 25% of the genomes) through acquisition of foreign DNA from diverse related or non-related donor species by lateral transfer of mobile genetic elements, including pathogenicity islands (PAIs), plasmids, phages, transposons, and insertion elements. The ability of ExPEC strains to cause disease is mainly derived from this horizontally acquired gene pool; the extragenous DNA facilitates rapid adaptation of the pathogen to changing conditions and hence the extent of the spectrum of sites that can be infected. However, neither the amount of unique DNA in different ExPEC strains (or UPEC strains) nor the mechanisms lying behind the observed genomic mobility are known. Due to this extreme heterogeneity of the UPEC and ExPEC populations in general, the routine surveillance of ExPEC is exceedingly difficult. In this project, we presented a novel virulence gene algorithm (VGA) for the estimation of the extraintestinal virulence potential (VP, pathogenicity risk) of clinically relevant ExPECs and fecal E. coli isolates. The VGA was based on a DNA microarray specific for the ExPEC phenotype (ExPEC pathoarray). This array contained 77 DNA probes homologous with known (e.g. adhesion factors, iron accumulation systems, and toxins) and putative (e.g. genes predictably involved in adhesion, iron uptake, or in metabolic functions) ExPEC virulence determinants. In total, 25 of DNA probes homologous with known virulence factors and 36 of DNA probes representing putative extraintestinal virulence determinants were found at significantly higher frequency in virulent ExPEC isolates than in commensal E. coli strains. We showed that the ExPEC pathoarray and the VGA could be readily used for the differentiation of highly virulent ExPECs both from less virulent ExPEC clones and from commensal E. coli strains as well. Implementing the VGA in a group of unknown ExPECs (n=53) and fecal E. coli isolates (n=37), 83% of strains were correctly identified as extraintestinal virulent or commensal E. coli. Conversely, 15% of clinical ExPECs and 19% of fecal E. coli strains failed to raster into their respective pathogenic and non-pathogenic groups. Clinical data and virulence gene profiles of these strains warranted the estimated VPs; UPEC strains with atypically low risk-ratios were largely isolated from patients with certain medical history, including diabetes mellitus or catheterization, or from elderly patients. In addition, fecal E. coli strains with VPs characteristic for ExPEC were shown to represent the diagnostically important fraction of resident strains of the gut flora with a high potential of causing extraintestinal infections. Interestingly, a large fraction of DNA probes associated with the ExPEC phenotype corresponded to novel DNA sequences without any known function in UTIs and thus represented new genetic markers for the extraintestinal virulence. These DNA probes included unknown DNA sequences originating from the genomic subtractions of four clinical ExPEC isolates as well as from five novel cosmid sequences identified in the UPEC strains HE300 and JS299. The characterized cosmid sequences (pJS332, pJS448, pJS666, pJS700, and pJS706) revealed complex modular DNA structures with known and unknown DNA fragments arranged in a puzzle-like manner and integrated into the common E. coli genomic backbone. Furthermore, cosmid pJS332 of the UPEC strain HE300, which carried a chromosomal virulence gene cluster (iroBCDEN) encoding the salmochelin siderophore system, was shown to be part of a transmissible plasmid of Salmonella enterica. Taken together, the results of this project pointed towards the assumptions that first, (i) homologous recombination, even within coding genes, contributes to the observed mosaicism of ExPEC genomes and secondly, (ii) besides en block transfer of large DNA regions (e.g. chromosomal PAIs) also rearrangements of small DNA modules provide a means of genomic plasticity. The data presented in this project supplemented previous whole genome sequencing projects of E. coli and indicated that each E. coli genome displays a unique assemblage of individual mosaic structures, which enable these strains to successfully colonize and infect different anatomical sites.

Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication

Neuroblastoma has successfully served as a model system for the identification of neuroectoderm-derived oncogenes. However, in spite of various efforts, only a few clinically useful prognostic markers have been found. Here, we present a framework, which integrates DNA, RNA and tissue data to identify and prioritize genetic events that represent clinically relevant new therapeutic targets and prognostic biomarkers for neuroblastoma.

Integration of miRNA and mRNA expression with DNA copy number of Ewing sarcoma cell lines

Ewing sarcoma is an aggressive and poorly differentiated malignancy of bone and soft tissue. It primarily affects children, adolescents, and young adults, with a slight male predominance. It is characterized by a translocation between chromosomes 11 and 22 resulting in the EWSR1-FLI1fusion transcription factor. The aim of this study is to identify putative Ewing sarcoma target genes through an integrative analysis of three microarray data sets. Array comparative genomic hybridization is used to measure changes in DNA copy number, and analyzed to detect common chromosomal aberrations. mRNA and miRNA microarrays are used to measure expression of protein-coding and miRNA genes, and these results integrated with the copy number data. Chromosomal aberrations typically contain also bystanders in addition to the driving tumor suppressor and oncogenes, and integration with expression helps to identify the true targets. Correlation between expression of miRNAs and their predicted target mRNAs is also evaluated to assess the results of post-transcriptional miRNA regulation on mRNA levels. The highest frequencies of copy number gains were identified in chromosome 8, 1q, and X. Losses were most frequent in 9p21.3, which also showed an enrichment of copy number breakpoints relative to the rest of the genome. Copy number losses in 9p21.3 were found have a statistically significant effect on the expression of MTAP, but not on CDKN2A, which is a known tumor-suppressor in the same locus. MTAP was also down-regulated in the Ewing sarcoma cell lines compared to mesenchymal stem cells. Genes exhibiting elevated expression in association with copy number gains and up-regulation compared to the reference samples included DCAF7, ENO2, MTCP1, andSTK40. Differentially expressed miRNAs were detected by comparing Ewing sarcoma cell lines against mesenchymal stem cells. 21 up-regulated and 32 down-regulated miRNAs were identified, includingmiR-145, which has been previously linked to Ewing sarcoma. The EWSR1-FLI1 fusion gene represses miR-145, which in turn targets FLI1 forming a mutually repressive feedback loop. In addition higher expression linked to copy number gains and compared to mesenchymal stem cells, STK40 was also found to be a target of four different miRNAs that were all down-regulated in Ewing sarcoma cell lines compared to the reference samples. SLCO5A1 was identified as the only up-regulated gene within a frequently gained region in chromosome 8. This region was gained in over 90 % of the cell lines, and also with a higher frequency than the neighboring regions. In addition, SLCO5A1 was found to be a target of three miRNAs that were down-regulated compared to the mesenchymal stem cells.

Microarrays in molecular profiling of cancer - focus on head and neck squamous cell carcinoma

Microarrays have a wide range of applications in the biomedical field. From the beginning, arrays have mostly been utilized in cancer research, including classification of tumors into different subgroups and identification of clinical associations. In the microarray format, a collection of small features, such as different oligonucleotides, is attached to a solid support. The advantage of microarray technology is the ability to simultaneously measure changes in the levels of multiple biomolecules. Because many diseases, including cancer, are complex, involving an interplay between various genes and environmental factors, the detection of only a single marker molecule is usually insufficient for determining disease status. Thus, a technique that simultaneously collects information on multiple molecules allows better insights into a complex disease. Since microarrays can be custom-manufactured or obtained from a number of commercial providers, understanding data quality and comparability between different platforms is important to enable the use of the technology to areas beyond basic research. When standardized, integrated array data could ultimately help to offer a complete profile of the disease, illuminating mechanisms and genes behind disorders as well as facilitating disease diagnostics. In the first part of this work, we aimed to elucidate the comparability of gene expression measurements from different oligonucleotide and cDNA microarray platforms. We compared three different gene expression microarrays; one was a commercial oligonucleotide microarray and the others commercial and custom-made cDNA microarrays. The filtered gene expression data from the commercial platforms correlated better across experiments (r=0.78-0.86) than the expression data between the custom-made and either of the two commercial platforms (r=0.62-0.76). Although the results from different platforms correlated reasonably well, combining and comparing the measurements were not straightforward. The clone errors on the custom-made array and annotation and technical differences between the platforms introduced variability in the data. In conclusion, the different gene expression microarray platforms provided results sufficiently concordant for the research setting, but the variability represents a challenge for developing diagnostic applications for the microarrays. In the second part of the work, we performed an integrated high-resolution microarray analysis of gene copy number and expression in 38 laryngeal and oral tongue squamous cell carcinoma cell lines and primary tumors. Our aim was to pinpoint genes for which expression was impacted by changes in copy number. The data revealed that especially amplifications had a clear impact on gene expression. Across the genome, 14-32% of genes in the highly amplified regions (copy number ratio >2.5) had associated overexpression. The impact of decreased copy number on gene underexpression was less clear. Using statistical analysis across the samples, we systematically identified hundreds of genes for which an increased copy number was associated with increased expression. For example, our data implied that FADD and PPFIA1 were frequently overexpressed at the 11q13 amplicon in HNSCC. The 11q13 amplicon, including known oncogenes such as CCND1 and CTTN, is well-characterized in different type of cancers, but the roles of FADD and PPFIA1 remain obscure. Taken together, the integrated microarray analysis revealed a number of known as well as novel target genes in altered regions in HNSCC. The identified genes provide a basis for functional validation and may eventually lead to the identification of novel candidates for targeted therapy in HNSCC.

p53 and DNA damage checkpoint responses in the human prostate

Prostate cancer is the most common noncutaneous malignancy and the second leading cause of cancer mortality in men. In 2004, 5237 new cases were diagnosed and altogether 25 664 men suffered from prostate cancer in Finland (Suomen Syöpärekisteri). Although extensively investigated, we still have a very rudimentary understanding of the molecular mechanisms leading to the frequent transformation of the prostate epithelium. Prostate cancer is characterized by several unique features including the multifocal origin of tumors and extreme resistance to chemotherapy, and new treatment options are therefore urgently needed. The integrity of genomic DNA is constantly challenged by genotoxic insults. Cellular responses to DNA damage involve elegant checkpoint cascades enforcing cell cycle arrest, thus facilitating damage repair, apoptosis or cellular senescence. Cellular DNA damage triggers the activation of tumor suppressor protein p53 and Wee1 kinase which act as executors of the cellular checkpoint responses. These are essential for genomic integrity, and are activated in early stages of tumorigenesis in order to function as barriers against tumor formation. Our work establishes that the primary human prostatic epithelial cells and prostatic epithelium have unexpectedly indulgent checkpoint surveillance. This is evidenced by the absence of inhibitory Tyr15 phosphorylation on Cdk2, lack of p53 response, radioresistant DNA synthesis, lack of G1/S and G2/M phase arrest, and presence of persistent gammaH2AX damage foci. We ascribe the absence of inhibitory Tyr15 phosphorylation to low levels of Wee1A, a tyrosine kinase and negative regulator of cell cycle progression. Ectopic Wee1A kinase restored Cdk2-Tyr15 phosphorylation and efficiently rescued the ionizing radiation-induced checkpoints in the human prostatic epithelial cells. As variability in the DNA damage responses has been shown to underlie susceptibility to cancer, our results imply that a suboptimal checkpoint arrest may greatly increase the accumulation of genetic lesions in the prostate epithelia. We also show that small molecules can restore p53 function in prostatic epithelial cells and may serve as a paradigm for the development of future therapeutic agents for the treatment of prostate cancer We hypothesize that the prostate has evolved to activate the damage surveillance pathways and molecules involved in these pathways only to certain stresses in extreme circumstances. In doing so, this organ inadvertently made itself vulnerable to genotoxic stress, which may have implications in malignant transformation. Recognition of the limited activity of p53 and Wee1 in the prostate could drive mechanism-based discovery of preventative and therapeutic agents.

Molecular Genetic Background of Tumours in Hereditary Leiomyomatosis and Renal Cell Cancer Syndrome

Hereditary Leiomyomatosis and Renal Cell Cancer (HLRCC) is a hereditary tumour predisposition syndrome. Its phenotype includes benign cutaneous and uterine leiomyomas (CLM, ULM) with high penetrance and rarer renal cell cancer (RCC), most commonly of papillary type 2 subtype. Over 130 HLRCC families have been identified world-wide but the RCC phenotype seems to concentrate in families from Finland and North America for unknown reasons. HLRCC is caused by heterozygous germline mutations in the fumarate hydratase (FH) gene. FH encodes the enzyme fumarase from mitochondrial citric acid cycle. Fumarase enzyme activity or type or site of the FH mutation are unassociated with disease phenotype. The strongest evidence for tumourigenesis mechanism in HLRCC supports a hypoxia inducible factor driven process called pseudohypoxia resulting from accumulation of the fumarase substrate fumarate. In this study, to assess the importance of gene- or exon-level deletions or amplifications of FH in patients with HLRCC-associated phenotypes, multiplex ligation-dependent probe amplification (MLPA) method was used. One novel FH mutation, deletion of exon 1, was found in a Swedish male patient with an evident HLRCC phenotype with CLM, RCC, and a family history of ULM and RCC. Six other patients with CLM and 12 patients with only RCC or uterine leiomyosarcoma (ULMS) remained FH mutation-negative. These results suggest that copy number aberrations of FH or its exons are an infrequent cause of HLRCC and that only co-occurrence of benign tumour types justifies FH-mutation screening in RCC or ULMS patients. Determination of the genomic profile of 11 HLRCC-associated RCCs from Finnish patients was performed by array comparative genomic hybridization. The most common copy number aberrations were gains of 2, 7, and 17 and losses of 13q12.3-q21.1, 14, 18, and X. When compared to aberrations of sporadic papillary RCCs, HLRCC-associated RCCs harboured a distinct DNA copy number profile and lacked many of the changes characterizing the sporadic RCCs. The findings suggest a divergent molecular pathway for tumourigenesis of papillary RCCs in HLRCC. In order to find a genetic modifier of RCC risk in HLRCC, genome-wide linkage and identical by descent (IBD) analysis studies were performed in Finnish HLRCC families with microsatellite marker mapping and SNP-array platforms. The linkage analysis identified only one locus of interest, the FH gene locus in 1q43, but no mutations were found in the genes of the region. IBD analysis yielded no convincing haplotypes shared by RCC patients. Although these results do not exclude the existence of a genetic modifier for RCC risk in HLRCC, they emphasize the role of FH mutations in the malignant tumourigenesis of HLRCC. To study the benign tumours in HLRCC, genome-wide DNA copy number and gene expression profiles of sporadic and HLRCC ULMs were defined with modern SNP- and gene-expression array platforms. The gene expression array suggests novel genes involved in FH-deficient ULM tumourigenesis and novel genes with putative roles in propagation of sporadic ULM. Both the gene expression and copy number profiles of HLRCC ULMs differed from those of sporadic ULMs indicating distinct molecular basis of the FH-deficient HLRCC tumours.

Genomic microarrays in chromosomal analysis of leukemia

Chromosomal alterations in leukemia have been shown to have prognostic and predictive significance and are also important minimal residual disease (MRD) markers in the follow-up of leukemia patients. Although specific oncogenes and tumor suppressors have been discovered in some of the chromosomal alterations, the role and target genes of many alterations in leukemia remain unknown. In addition, a number of leukemia patients have a normal karyotype by standard cytogenetics, but have variability in clinical course and are often molecularly heterogeneous. Cytogenetic methods traditionally used in leukemia analysis and diagnostics; G-banding, various fluorescence in situ hybridization (FISH) techniques, and chromosomal comparative genomic hybridization (cCGH), have enormously increased knowledge about the leukemia genome, but have limitations in resolution or in genomic coverage. In the last decade, the development of microarray comparative genomic hybridization (array-CGH, aCGH) for DNA copy number analysis and the SNP microarray (SNP-array) method for simultaneous copy number and loss of heterozygosity (LOH) analysis has enabled investigation of chromosomal and gene alterations genome-wide with high resolution and high throughput. In these studies, genetic alterations were analyzed in acute myeloid leukemia (AML) and chronic lymphocytic leukemia (CLL). The aim was to screen and characterize genomic alterations that could play role in leukemia pathogenesis by using aCGH and SNP-arrays. One of the most important goals was to screen cryptic alterations in karyotypically normal leukemia patients. In addition, chromosomal changes were evaluated to narrow the target regions, to find new markers, and to obtain tumor suppressor and oncogene candidates. The work presented here shows the capability of aCGH to detect submicroscopic copy number alterations in leukemia, with information about breakpoints and genes involved in the alterations, and that genome-wide microarray analyses with aCGH and SNP-array are advantageous methods in the research and diagnosis of leukemia. The most important findings were the cryptic changes detected with aCGH in karyotypically normal AML and CLL, characterization of amplified genes in 11q marker chromosomes, detection of deletion-based mechanisms of MLL-ARHGEF12 fusion gene formation, and detection of LOH without copy number alteration in karyotypically normal AML. These alterations harbor candidate oncogenes and tumor suppressors for further studies.

Genetic alterations in microsatellite-unstable colorectal cancer

Colorectal cancer (CRC) is the third most common cancer in Finland. Of all CRC tumors, 15% display microsatellite-instability (MSI) caused by defective cellular mismatch repair. Cells displaying MSI accumulate a high number of mutations genome-wide, especially in short repeat areas, microsatellites. When targeting genes essential for cell growth or death, MSI can promote tumorigenesis. In non-coding areas, microsatellite mutations are generally considered as passenger events. Since the discovery of MSI and its linkage to cancer, more that 200 genes have been investigated for a role in MSI tumorigenesis. Although various criteria have been suggested for MSI target gene identification, the challenge has been to distinguish driver mutations from passenger mutations. This study aimed to clarify these key issues in the research field of MSI cancer. Prior to this, background mutation rate in MSI cancer has not been studied in a large-scale. We investigated the background mutation rate in MSI CRC by analyzing the spectrum of microsatellite mutations in non-coding areas. First, semenogelin I was studied for a possible role in MSI carcinogenesis. The intronic T9 repeat of semenogelin I was frequently mutated but no evidence for selection during tumorigenesis was obtained. Second, a sequencing approach was utilized to evaluate the general background mutation rate in MSI CRC. Both intronic and intergenic repeats harbored extremely high mutation rates of ≤ 87% and intergenic repeats were more unstable than the intronic repeats. As mutation rates of presumably neutral microsatellites can be high in MSI CRC in the absence of apparent selection pressure, high mutation frequency alone is not sufficient evidence for identification of driver MSI target genes. Next, an unbiased approach was designed to identify the mutatome of MSI CRC. By combining expression array data and a database search we identified novel genes possibly related to MSI CRC carcinogenesis. One of the genes was studied further. In the functional analysis this gene was observed to cause an abnormal cancer-prone cellular phenotype, possibly through altered responses to DNA damage. In our recent study, smooth muscle myosin heavy chain 11 (MYH11) was identified as a novel MSI CRC gene. Additionally, MYH11 has a well established role in acute myeloid leukemia (AML) through an oncogenic fusion protein CBFB-MYH11. We investigated further the role of MYH11 in AML by sequencing. Three novel missense variants of MYH11 were identified. None of the variants were present in the population-based control material. One of the identified variants, V71A, lies in the N-terminal SH3-like domain of MYH11 of unknown function. The other two variants, K1059E and R1792Q are located in the coil-coiled myosin rod essential for the regulation and filament formation of MYH11. The variant K1059E lies in the close proximity of the K1044N that has been functionally assessed in our earlier work of CRC and has been reported to cause total loss of MYH11 protein regulation. As the functional significance of the three novel variants examined in this work remains unknown, future studies should clarify the further role of MYH11 in AML leukaemogenesis and in other malignancies.

DNA-based detection and characterisation of strictly anaerobic beer-spoilage bacteria

Megasphaera cerevisiae, Pectinatus cerevisiiphilus, Pectinatus frisingensis, Selenomonas lacticifex, Zymophilus paucivorans and Zymophilus raffinosivorans are strictly anaerobic Gram-stain-negative bacteria that are able to spoil beer by producing off-flavours and turbidity. They have only been isolated from the beer production chain. The species are phylogenetically affiliated to the Sporomusa sub-branch in the class "Clostridia". Routine cultivation methods for detection of strictly anaerobic bacteria in breweries are time-consuming and do not allow species identification. The main aim of this study was to utilise DNA-based techniques in order to improve detection and identification of the Sporomusa sub-branch beer-spoilage bacteria and to increase understanding of their biodiversity, evolution and natural sources. Practical PCR-based assays were developed for monitoring of M. cerevisiae, Pectinatus species and the group of Sporomusa sub-branch beer spoilers throughout the beer production process. The developed assays reliably differentiated the target bacteria from other brewery-related microbes. The contaminant detection in process samples (10 1,000 cfu/ml) could be accomplished in 2 8 h. Low levels of viable cells in finished beer (≤10 cfu/100 ml) were usually detected after 1 3 d culture enrichment. Time saving compared to cultivation methods was up to 6 d. Based on a polyphasic approach, this study revealed the existence of three new anaerobic spoilage species in the beer production chain, i.e. Megasphaera paucivorans, Megasphaera sueciensis and Pectinatus haikarae. The description of these species enabled establishment of phenotypic and DNA-based methods for their detection and identification. The 16S rRNA gene based phylogenetic analysis of the Sporomusa sub-branch showed that the genus Selenomonas originates from several ancestors and will require reclassification. Moreover, Z. paucivorans and Z. raffinosivorans were found to be in fact members of the genus Propionispira. This relationship implies that they were carried to breweries along with plant material. The brewery-related Megasphaera species formed a distinct sub-group that did not include any sequences from other sources, suggesting that M. cerevisiae, M. paucivorans and M. sueciensis may be uniquely adapted to the brewery ecosystem. M. cerevisiae was also shown to exhibit remarkable resistance against many brewery-related stress conditions. This may partly explain why it is a brewery contaminant. This study showed that DNA-based techniques provide useful tools for obtaining more rapid and specific information about the presence and identity of the strictly anaerobic spoilage bacteria in the beer production chain than is possible using cultivation methods. This should ensure financial benefits to the industry and better product quality to customers. In addition, DNA-based analyses provided new insight into the biodiversity as well as natural sources and relations of the Sporomusa sub-branch bacteria. The data can be exploited for taxonomic classification of these bacteria and for surveillance and control of contaminations.

Stretching single DNA-molecules with temperature-stabilized optical tweezers

This thesis consists of two parts; in the first part we performed a single-molecule force extension measurement with 10kb long DNA-molecules from phage-λ to validate the calibration and single-molecule capability of our optical tweezers instrument. Fitting the worm-like chain interpolation formula to the data revealed that ca. 71% of the DNA tethers featured a contour length within ±15% of the expected value (3.38 µm). Only 25% of the found DNA had a persistence length between 30 and 60 nm. The correct value should be within 40 to 60 nm. In the second part we designed and built a precise temperature controller to remove thermal fluctuations that cause drifting of the optical trap. The controller uses feed-forward and PID (proportional-integral-derivative) feedback to achieve 1.58 mK precision and 0.3 K absolute accuracy. During a 5 min test run it reduced drifting of the trap from 1.4 nm/min in open-loop to 0.6 nm/min in closed-loop.

Methods to improve gene signal: Application to cDNA microarrays

Microarrays are high throughput biological assays that allow the screening of thousands of genes for their expression. The main idea behind microarrays is to compute for each gene a unique signal that is directly proportional to the quantity of mRNA that was hybridized on the chip. A large number of steps and errors associated with each step make the generated expression signal noisy. As a result, microarray data need to be carefully pre-processed before their analysis can be assumed to lead to reliable and biologically relevant conclusions. This thesis focuses on developing methods for improving gene signal and further utilizing this improved signal for higher level analysis. To achieve this, first, approaches for designing microarray experiments using various optimality criteria, considering both biological and technical replicates, are described. A carefully designed experiment leads to signal with low noise, as the effect of unwanted variations is minimized and the precision of the estimates of the parameters of interest are maximized. Second, a system for improving the gene signal by using three scans at varying scanner sensitivities is developed. A novel Bayesian latent intensity model is then applied on these three sets of expression values, corresponding to the three scans, to estimate the suitably calibrated true signal of genes. Third, a novel image segmentation approach that segregates the fluorescent signal from the undesired noise is developed using an additional dye, SYBR green RNA II. This technique helped in identifying signal only with respect to the hybridized DNA, and signal corresponding to dust, scratch, spilling of dye, and other noises, are avoided. Fourth, an integrated statistical model is developed, where signal correction, systematic array effects, dye effects, and differential expression, are modelled jointly as opposed to a sequential application of several methods of analysis. The methods described in here have been tested only for cDNA microarrays, but can also, with some modifications, be applied to other high-throughput technologies. Keywords: High-throughput technology, microarray, cDNA, multiple scans, Bayesian hierarchical models, image analysis, experimental design, MCMC, WinBUGS.