Computational Methods for Locating and Analyzing Conserved Gene Regulatory DNA Elements

This thesis presents methods for locating and analyzing cis-regulatory DNA elements involved with the regulation of gene expression in multicellular organisms. The regulation of gene expression is carried out by the combined effort of several transcription factor proteins collectively binding the DNA on the cis-regulatory elements. Only sparse knowledge of the 'genetic code' of these elements exists today. An automatic tool for discovery of putative cis-regulatory elements could help their experimental analysis, which would result in a more detailed view of the cis-regulatory element structure and function. We have developed a computational model for the evolutionary conservation of cis-regulatory elements. The elements are modeled as evolutionarily conserved clusters of sequence-specific transcription factor binding sites. We give an efficient dynamic programming algorithm that locates the putative cis-regulatory elements and scores them according to the conservation model. A notable proportion of the high-scoring DNA sequences show transcriptional enhancer activity in transgenic mouse embryos. The conservation model includes four parameters whose optimal values are estimated with simulated annealing. With good parameter values the model discriminates well between the DNA sequences with evolutionarily conserved cis-regulatory elements and the DNA sequences that have evolved neutrally. In further inquiry, the set of highest scoring putative cis-regulatory elements were found to be sensitive to small variations in the parameter values. The statistical significance of the putative cis-regulatory elements is estimated with the Two Component Extreme Value Distribution. The p-values grade the conservation of the cis-regulatory elements above the neutral expectation. The parameter values for the distribution are estimated by simulating the neutral DNA evolution. The conservation of the transcription factor binding sites can be used in the upstream analysis of regulatory interactions. This approach may provide mechanistic insight to the transcription level data from, e.g., microarray experiments. Here we give a method to predict shared transcriptional regulators for a set of co-expressed genes. The EEL (Enhancer Element Locator) software implements the method for locating putative cis-regulatory elements. The software facilitates both interactive use and distributed batch processing. We have used it to analyze the non-coding regions around all human genes with respect to the orthologous regions in various other species including mouse. The data from these genome-wide analyzes is stored in a relational database which is used in the publicly available web services for upstream analysis and visualization of the putative cis-regulatory elements in the human genome.

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.

Molecular Mechanisms of Androgen Receptor Interactions

The androgen receptor (AR) mediates the effects of the male sex-steroid hormones (androgens), testosterone and 5?-dihydrotestosterone. Androgens are critical in the development and maintenance of male sexual characteristics. AR is a member of the steroid receptor ligand-inducible transcription factor family. The steroid receptor family is a subgroup of the nuclear receptor superfamily that also includes receptors for the active forms of vitamin A, vitamin D3, and thyroid hormones. Like all nuclear receptors, AR has a conserved modular structure consisting of a non-conserved amino-terminal domain (NTD), containing the intrinsic activation function 1, a highly conserved DNA-binding domain, and a conserved ligand-binding domain (LBD) that harbors the activation function 2. Each of these domains plays an important role in receptor function and signaling, either via intra- and inter-receptor interactions, interactions with specific DNA sequences, termed hormone response elements, or via functional interactions with domain-specific proteins, termed coregulators (coactivators and corepressors). Upon binding androgens, AR acquires a new conformational state, translocates to the nucleus, binds to androgen response elements, homodimerizes and recruits sequence-specific coregulatory factors and the basal transcription machinery. This set of events is required to activate gene transcription (expression). Gene transcription is a strictly modulated process that governs cell growth, cell homeostasis, cell function and cell death. Disruptions of AR transcriptional activity caused by receptor mutations and/or altered coregulator interactions are linked to a wide spectrum of androgen insensitivity syndromes, and to the pathogenesis of prostate cancer (CaP). The treatment of CaP usually involves androgen depletion therapy (ADT). ADT achieves significant clinical responses during the early stages of the disease. However, under the selective pressure of androgen withdrawal, androgen-dependent CaP can progress to an androgen-independent CaP. Androgen-independent CaP is invariably a more aggressive and untreatable form of the disease. Advancing our understanding of the molecular mechanisms behind the switch in androgen-dependency would improve our success of treating CaP and other AR related illnesses. This study evaluates how clinically identified AR mutations affect the receptor s transcriptional activity. We reveal that a potential molecular abnormality in androgen insensitivity syndrome and CaP patients is caused by disruptions of the important intra-receptor NTD/LBD interaction. We demonstrate that the same AR LBD mutations can also disrupt the recruitment of the p160 coactivator protein GRIP1. Our investigations reveal that 30% of patients with advanced, untreated local CaP have somatic mutations that may lead to increases in AR activity. We report that somatic mutations that activate AR may lead to early relapse in ADT. Our results demonstrate that the types of ADT a CaP patient receives may cause a clustering of mutations to a particular region of the receptor. Furthermore, the mutations that arise before and during ADT do not always result in a receptor that is more active, indicating that coregulator interactions play a pivotal role in the progression of androgen-independent CaP. To improve CaP therapy, it is necessary to identify critical coregulators of AR. We screened a HeLa cell cDNA library and identified small carboxyl-terminal domain phosphatase 2 (SCP2). SCP2 is a protein phosphatase that directly interacts with the AR NTD and represses AR activity. We demonstrated that reducing the endogenous cellular levels of SCP2 causes more AR to load on to the prostate specific antigen (PSA) gene promoter and enhancer regions. Additionally, under the same conditions, more RNA polymerase II was recruited to the PSA promoter region and overall there was an increase in androgen-dependent transcription of the PSA gene, revealing that SCP2 could play a role in the pathogenesis of CaP.

Discovering hidden structures in molecular data using a Bayesian partition model approach

Advancements in the analysis techniques have led to a rapid accumulation of biological data in databases. Such data often are in the form of sequences of observations, examples including DNA sequences and amino acid sequences of proteins. The scale and quality of the data give promises of answering various biologically relevant questions in more detail than what has been possible before. For example, one may wish to identify areas in an amino acid sequence, which are important for the function of the corresponding protein, or investigate how characteristics on the level of DNA sequence affect the adaptation of a bacterial species to its environment. Many of the interesting questions are intimately associated with the understanding of the evolutionary relationships among the items under consideration. The aim of this work is to develop novel statistical models and computational techniques to meet with the challenge of deriving meaning from the increasing amounts of data. Our main concern is on modeling the evolutionary relationships based on the observed molecular data. We operate within a Bayesian statistical framework, which allows a probabilistic quantification of the uncertainties related to a particular solution. As the basis of our modeling approach we utilize a partition model, which is used to describe the structure of data by appropriately dividing the data items into clusters of related items. Generalizations and modifications of the partition model are developed and applied to various problems. Large-scale data sets provide also a computational challenge. The models used to describe the data must be realistic enough to capture the essential features of the current modeling task but, at the same time, simple enough to make it possible to carry out the inference in practice. The partition model fulfills these two requirements. The problem-specific features can be taken into account by modifying the prior probability distributions of the model parameters. The computational efficiency stems from the ability to integrate out the parameters of the partition model analytically, which enables the use of efficient stochastic search algorithms.

Genomic approach to organ-specific growth control

Growth is a fundamental aspect of life cycle of all organisms. Body size varies highly in most animal groups, such as mammals. Moreover, growth of a multicellular organism is not uniform enlargement of size, but different body parts and organs grow to their characteristic sizes at different times. Currently very little is known about the molecular mechanisms governing this organ-specific growth. The genome sequencing projects have provided complete genomic DNA sequences of several species over the past decade. The amount of genomic sequence information, including sequence variants within species, is constantly increasing. Based on the universal genetic code, we can make sense of this sequence information as far as it codes proteins. However, less is known about the molecular mechanisms that control expression of genes, and about the variations in gene expression that underlie many pathological states in humans. This is caused in part by lack of information about the second genetic code that consists of the binding specificities of transcription factors and the combinatorial code by which transcription factor binding sites are assembled to form tissue-specific and/or ligand-regulated enhancer elements. This thesis presents a high-throughput assay for identification of transcription factor binding specificities, which were then used to measure the DNA binding profiles of transcription factors involved in growth control. We developed ‘enhancer element locator’, a computational tool, which can be used to predict functional enhancer elements. A genome-wide prediction of human and mouse enhancer elements generated a large database of enhancer elements. This database can be used to identify target genes of signaling pathways, and to predict activated transcription factors based on changes in gene expression. Predictions validated in transgenic mouse embryos revealed the presence of multiple tissue-specific enhancers in mouse c- and N-Myc genes, which has implications to organ specific growth control and tumor type specificity of oncogenes. Furthermore, we were able to locate a variation in a single nucleotide, which carries a susceptibility to colorectal cancer, to an enhancer element and propose a mechanism by which this SNP might be involved in generation of colorectal cancer.

Mu in vitro transposition applications in protein engineering

Transposons, mobile genetic elements that are ubiquitous in all living organisms have been used as tools in molecular biology for decades. They have the ability to move into discrete DNA locations with no apparent homology to the target site. The utility of transposons as molecular tools is based on their ability to integrate into various DNA sequences efficiently, producing extensive mutant clone libraries that can be used in various molecular biology applications. Bacteriophage Mu is one of the most useful transposons due to its well-characterized and simple in vitro transposition reaction. This study establishes the properties of the Mu in vitro transposition system as a versatile multipurpose tool in molecular biology. In addition, this study describes Mu-based applications for engineering proteins by random insertional transposon mutagenesis in order to study structure-function relationships in proteins. We initially characterized the properties of the minimal Mu in vitro transposition system. We showed that the Mu transposition system works efficiently and accurately and produces insertions into a wide spectrum of target sites in different DNA molecules. Then, we developed a pentapeptide insertion mutagenesis strategy for inserting random five amino acid cassettes into proteins. These protein variants can be used especially for screening important sites for protein-protein interactions. Also, the system may produce temperature-sensitive variants of the protein of interest. Furthermore, we developed an efficient screening system for high-resolution mapping of protein-protein interfaces with the pentapeptide insertion mutagenesis. This was accomplished by combining the mutagenesis with subsequent yeast two-hybrid screening and PCR-based genetic footprinting. This combination allows the analysis of the whole mutant library en masse, without the need for producing or isolating separate mutant clones, and the protein-protein interfaces can be determined at amino acid accuracy. The system was validated by analysing the interacting region of JFC1 with Rab8A, and we show that the interaction is mediated via the JFC1 Slp homology domain. In addition, we developed a procedure for the production of nested sets of N- and C-terminal deletion variants of proteins with the Mu system. These variants are useful in many functional studies of proteins, especially in mapping regions involved in protein-protein interactions. This methodology was validated by analysing the region in yeast Mso1 involved in an interaction with Sec1. The results of this study show that the Mu in vitro transposition system is versatile for various applicational purposes and can efficiently be adapted to random protein engineering applications for functional studies of proteins.

Human parvovirus B19: tissue persistence and prevalence of prototypic and new variants

Human parvovirus B19 is a minute ssDNA virus causing a wide variety of diseases, including erythema infectiosum, arthropathy, anemias, and fetal death. After primary infection, genomic DNA of B19 has been shown to persist in solid tissues of not only symptomatic but also of constitutionally healthy, immunocompetent individuals. In this thesis, the viral DNA was shown to persist as an apparently intact molecule of full length, and without persistence-specific mutations. Thus, although the mere presence of B19 DNA in tissue can not be used as a diagnostic criterion, a possible role in the pathogenesis of diseases e.g. through mRNA or protein production can not be excluded. The molecular mechanism, the host-cell type and the possible clinical significance of B19 DNA tissue persistence are yet to be elucidated. In the beginning of this work, the B19 genomic sequence was considered highly conserved. However, new variants were found: V9 was detected in 1998 in France, in serum of a child with aplastic crisis. This variant differed from the prototypic B19 sequences by ~10 %. In 2002 we found, persisting in skin of constitutionally healthy humans, DNA of another novel B19 variant, LaLi. Genetically this variant differed from both the prototypic sequences and the variant V9 also by ~10%. Simultaneously, B19 isolates with DNA sequences similar to LaLi were introduced by two other groups, in the USA and France. Based on phylogeny, a classification scheme based on three genotypes (B19 types 1-3) was proposed. Although the B19 virus is mainly transmitted via the respiratory route, blood and plasma-derived products contaminated with high levels of B19 DNA have also been shown to be infectious. The European Pharmacopoeia stipulates that, in Europe, from the beginning of 2004, plasma pools for manufacture must contain less than 104 IU/ml of B19 DNA. Quantitative PCR screening is therefore a prerequisite for restriction of the B19 DNA load and obtaining of safe plasma products. Due to the DNA sequence variation among the three B19 genotypes, however, B19 PCR methods might fail to detect the new variants. We therefore examined the suitability of the two commercially available quantitative B19 PCR tests, LightCycler-Parvovirus B19 quantification kit (Roche Diagnostics) and RealArt Parvo B19 LC PCR (Artus), for detection, quantification and differentiation of the three B19 types known, including B19 types 2 and 3. The former method was highly sensitive for detection of the B19 prototype but was not suitable for detection of types 2 and 3. The latter method detected and differentiated all three B19 virus types. However, one of the two type-3 strains was detected at a lower sensitivity. Then, we assessed the prevalence of the three B19 virus types among Finnish blood donors, by screening pooled plasma samples derived from >140 000 blood-donor units: none of the pools contained detectable levels of B19 virus types 2 or 3. According to the results of other groups, B19 type 2 was absent also among Danish blood-donors, and extremely rare among symptomatic European patients. B19 type 3 has been encountered endemically in Ghana and (apparently) in Brazil, and sporadical cases have been detected in France and the UK. We next examined the biological characteristics of these virus types. The p6 promoter regions of virus types 1-3 were cloned in front of a reporter gene, the constructs were transfected into different cell lines, and the promoter activities were measured. As a result, we found that the activities of the three p6 promoters, although differing in sequence by >20%, were of equal strength, and most active in B19-permissive cells. Furthermore, the infectivity of the three B19 types was examined in two B19-permissive cell lines. RT-PCR revealed synthesis of spliced B19 mRNAs, and immunofluorescence verified the production of NS1 and VP proteins in the infected cells. These experiments suggested similar host-cell tropism and showed that the three virus types are strains of the same species, i.e. human parvovirus B19. Last but not least, the sera from subjects infected in the past either with B19 type 1 or type 2 (as evidenced by tissue persistence of the respective DNAs), revealed in VP1/2- and VP2-EIAs a 100 % cross-reactivity between virus types 1 and 2. These results, together with similar studies by others, indicate that the three B19 genotypes constitute a single serotype.

Nuclear Import Mechanisms of STAT and NF-kB Transcription Factors

The eukaryotic cell nucleoplasm is separated from the cytoplasm by the nuclear envelope. This compartmentation of eukaryotic cells requires that all nuclear proteins must be transported from the cytoplasm into the nucleus. Transport of macromolecules between the nucleus and the cytoplasm occurs through nuclear pore complexes (NPCs). Proteins to be targeted into the nucleus by the classical nuclear import system contain nuclear localization signals (NLSs), which are recognized by importin alpha, the NLS receptor. Importin alpha binds to importin beta, which docks the importin-cargo complex on the cytoplasmic side of the NPC and mediates the movement of the complex into the nucleus. Presently six human importin alpha isoforms have been identified. Transcription factors are among the most important regulators of gene expression in eukaryotic organisms. Transcription factors bind to specific DNA sequences on target genes and modulate the activity of the target gene. Many transcription factors, including signal transducers and activators of transcription (STAT) and nuclear factor kB (NF-kB), reside in the cytoplasm in an inactive form, and upon activation they are rapidly transported into the nucleus. In the nucleus STATs and NF-kB regulate the activity of genes whose products are critical in controlling numerous cellular and organismal processes, such as inflammatory and immune responses, cell growth, differentiation and survival. The aim of this study was to investigate the nuclear import mechanisms of STAT and NF-kB transcription factors. This work shows that STAT1 homodimers and STAT1/STAT2 heterodimers bind specifically and directly to importin alpha5 molecule via unconventional dimer-specific NLSs. Importin alpha molecules have two regions, which have been shown to directly interact with the amino acids in the NLS of the cargo molecule. The Arm repeats 2-4 comprise the N-terminal NLS binding site and Arm repeats 7-8 the C-terminal NLS binding site. In this work it is shown that the binding site for STAT1 homodimers and STAT1/STAT2 heterodimers is composed of Arm repeats 8 and 9 of importin alpha5 molecule. This work demonstrates that all NF-kB proteins are transported into the nucleus by importin alpha molecules. In addition, NLS was identified in RelB protein. The interactions between NF-kB proteins and importin alpha molecules were found to be directly mediated by the NLSs of NF-kB proteins. Moreover, we found that p50 binds to the N-terminal and p65 to the C-terminal NLS binding site of importin alpha3. The results from this thesis work identify previously uncharacterized mechanisms in nuclear import of STAT and NF-kB. These findings provide new insights into the molecular mechanisms regulating the signalling cascades of these important transcription factors from the cytoplasm into the nucleus to the target genes.

Phylogenetics, taxon delimitation and phylogenetic diversity

Throughout the history of Linnean taxonomy, species have been described with varying degrees of justification. Many descriptions have been based on only a few ambiguous morphological characters. Moreover, species have been considered natural, well-defined units whereas higher taxa have been treated as disparate, non-existent creations. In the present thesis a few such cases were studied in detail. Often the species-level descriptions were based on only a few specimens and the variation previously thought to be interspecific was found to be intraspecific. In some cases morphological characters were sufficient to resolve the evolutionary relationships between the taxa, but generally more resolution was gained by the addition of molecular evidence. However, both morphological and molecular data were found to be deceptive in some cases. The DNA sequences of morphologically similar specimens were found to differ distinctly in some cases, whereas in other closely related species the morphology of specimens with identical DNA sequences differed substantially. This study counsels caution when evolutionary relationships are being studied utilizing only one source of evidence or a very limited number of characters (e.g. barcoding). Moreover, it emphasizes the importance of high quality data as well as the utilization of proper methods when making scientific inferences. Properly conducted analyses produce robust results that can be utilized in numerous interesting ways. The present thesis considered two such extensions of systematics. A novel hypothesis on the origin of bioluminescence in Elateriformia beetles is presented, tying it to the development of the clicking mechanism in the ancestors of these animals. An entirely different type of extension of systematics is the proposed high value of the white sand forests in maintaining the diversity of beetles in the Peruvian Amazon. White sand forests are under growing pressure from human activities that lead to deforestation. They were found to harbor an extremely diverse beetle fauna and many taxa were specialists living only in this unique habitat. In comparison to the predominant clay soil forests, considerably more elateroid beetles belonging to all studied taxonomic levels (species, genus, tribus, and subfamily) were collected in white sand forests. This evolutionary diversity is hypothesized to be due to a combination of factors: (1) the forest structure, which favors the fungus-plant interactions important for the elateroid beetles, (2) the old age of the forest type favoring survival of many evolutionary lineages and (3) the widespread distribution and fragmentation of the forests in the Miocene, favoring speciation.

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.

Microbial identification by detection of ligation probes on DNA microarray

Microbes in natural and artificial environments as well as in the human body are a key part of the functional properties of these complex systems. The presence or absence of certain microbial taxa is a correlate of functional status like risk of disease or course of metabolic processes of a microbial community. As microbes are highly diverse and mostly notcultivable, molecular markers like gene sequences are a potential basis for detection and identification of key types. The goal of this thesis was to study molecular methods for identification of microbial DNA in order to develop a tool for analysis of environmental and clinical DNA samples. Particular emphasis was placed on specificity of detection which is a major challenge when analyzing complex microbial communities. The approach taken in this study was the application and optimization of enzymatic ligation of DNA probes coupled with microarray read-out for high-throughput microbial profiling. The results show that fungal phylotypes and human papillomavirus genotypes could be accurately identified from pools of PCR amplicons generated from purified sample DNA. Approximately 1 ng/μl of sample DNA was needed for representative PCR amplification as measured by comparisons between clone sequencing and microarray. A minimum of 0,25 amol/μl of PCR amplicons was detectable from amongst 5 ng/μl of background DNA, suggesting that the detection limit of the test comprising of ligation reaction followed by microarray read-out was approximately 0,04%. Detection from sample DNA directly was shown to be feasible with probes forming a circular molecule upon ligation followed by PCR amplification of the probe. In this approach, the minimum detectable relative amount of target genome was found to be 1% of all genomes in the sample as estimated from 454 deep sequencing results. Signal-to-noise of contact printed microarrays could be improved by using an internal microarray hybridization control oligonucleotide probe together with a computational algorithm. The algorithm was based on identification of a bias in the microarray data and correction of the bias as shown by simulated and real data. The results further suggest semiquantitative detection to be possible by ligation detection, allowing estimation of target abundance in a sample. However, in practise, comprehensive sequence information of full length rRNA genes is needed to support probe design with complex samples. This study shows that DNA microarray has the potential for an accurate microbial diagnostic platform to take advantage of increasing sequence data and to replace traditional, less efficient methods that still dominate routine testing in laboratories. The data suggests that ligation reaction based microarray assay can be optimized to a degree that allows good signal-tonoise and semiquantitative detection.