Computational Identification of Recessive Mutations in Cancers using High Throughput SNP-arrays

This thesis presents a highly sensitive genome wide search method for recessive mutations. The method is suitable for distantly related samples that are divided into phenotype positives and negatives. High throughput genotype arrays are used to identify and compare homozygous regions between the cohorts. The method is demonstrated by comparing colorectal cancer patients against unaffected references. The objective is to find homozygous regions and alleles that are more common in cancer patients. We have designed and implemented software tools to automate the data analysis from genotypes to lists of candidate genes and to their properties. The programs have been designed in respect to a pipeline architecture that allows their integration to other programs such as biological databases and copy number analysis tools. The integration of the tools is crucial as the genome wide analysis of the cohort differences produces many candidate regions not related to the studied phenotype. CohortComparator is a genotype comparison tool that detects homozygous regions and compares their loci and allele constitutions between two sets of samples. The data is visualised in chromosome specific graphs illustrating the homozygous regions and alleles of each sample. The genomic regions that may harbour recessive mutations are emphasised with different colours and a scoring scheme is given for these regions. The detection of homozygous regions, cohort comparisons and result annotations are all subjected to presumptions many of which have been parameterized in our programs. The effect of these parameters and the suitable scope of the methods have been evaluated. Samples with different resolutions can be balanced with the genotype estimates of their haplotypes and they can be used within the same study.

Computational Methods for Reconstruction and Analysis of Genome-Scale Metabolic Networks

Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the analysis of large metabolic models encompassing the whole metabolism of one or several organisms. We concentrate on three major themes of metabolic modeling: metabolic pathway analysis, metabolic reconstruction and the study of evolution of metabolism. In the first part of this thesis, we study metabolic pathway analysis. We propose a novel modeling framework called gapless modeling to study biochemically viable metabolic networks and pathways. In addition, we investigate the utilization of atom-level information on metabolism to improve the quality of pathway analyses. We describe efficient algorithms for discovering both gapless and atom-level metabolic pathways, and conduct experiments with large-scale metabolic networks. The presented gapless approach offers a compromise in terms of complexity and feasibility between the previous graph-theoretic and stoichiometric approaches to metabolic modeling. Gapless pathway analysis shows that microbial metabolic networks are not as robust to random damage as suggested by previous studies. Furthermore the amino acid biosynthesis pathways of the fungal species Trichoderma reesei discovered from atom-level data are shown to closely correspond to those of Saccharomyces cerevisiae. In the second part, we propose computational methods for metabolic reconstruction in the gapless modeling framework. We study the task of reconstructing a metabolic network that does not suffer from connectivity problems. Such problems often limit the usability of reconstructed models, and typically require a significant amount of manual postprocessing. We formulate gapless metabolic reconstruction as an optimization problem and propose an efficient divide-and-conquer strategy to solve it with real-world instances. We also describe computational techniques for solving problems stemming from ambiguities in metabolite naming. These techniques have been implemented in a web-based sofware ReMatch intended for reconstruction of models for 13C metabolic flux analysis. In the third part, we extend our scope from single to multiple metabolic networks and propose an algorithm for inferring gapless metabolic networks of ancestral species from phylogenetic data. Experimenting with 16 fungal species, we show that the method is able to generate results that are easily interpretable and that provide hypotheses about the evolution of metabolism.

Asteroid identification using statistical orbital inversion methods

An efficient and statistically robust solution for the identification of asteroids among numerous sets of astrometry is presented. In particular, numerical methods have been developed for the short-term identification of asteroids at discovery, and for the long-term identification of scarcely observed asteroids over apparitions, a task which has been lacking a robust method until now. The methods are based on the solid foundation of statistical orbital inversion properly taking into account the observational uncertainties, which allows for the detection of practically all correct identifications. Through the use of dimensionality-reduction techniques and efficient data structures, the exact methods have a loglinear, that is, O(nlog(n)), computational complexity, where n is the number of included observation sets. The methods developed are thus suitable for future large-scale surveys which anticipate a substantial increase in the astrometric data rate. Due to the discontinuous nature of asteroid astrometry, separate sets of astrometry must be linked to a common asteroid from the very first discovery detections onwards. The reason for the discontinuity in the observed positions is the rotation of the observer with the Earth as well as the motion of the asteroid and the observer about the Sun. Therefore, the aim of identification is to find a set of orbital elements that reproduce the observed positions with residuals similar to the inevitable observational uncertainty. Unless the astrometric observation sets are linked, the corresponding asteroid is eventually lost as the uncertainty of the predicted positions grows too large to allow successful follow-up. Whereas the presented identification theory and the numerical comparison algorithm are generally applicable, that is, also in fields other than astronomy (e.g., in the identification of space debris), the numerical methods developed for asteroid identification can immediately be applied to all objects on heliocentric orbits with negligible effects due to non-gravitational forces in the time frame of the analysis. The methods developed have been successfully applied to various identification problems. Simulations have shown that the methods developed are able to find virtually all correct linkages despite challenges such as numerous scarce observation sets, astrometric uncertainty, numerous objects confined to a limited region on the celestial sphere, long linking intervals, and substantial parallaxes. Tens of previously unknown main-belt asteroids have been identified with the short-term method in a preliminary study to locate asteroids among numerous unidentified sets of single-night astrometry of moving objects, and scarce astrometry obtained nearly simultaneously with Earth-based and space-based telescopes has been successfully linked despite a substantial parallax. Using the long-term method, thousands of realistic 3-linkages typically spanning several apparitions have so far been found among designated observation sets each spanning less than 48 hours.

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.

Experimental and computational studies on lipoprotein lipolysis at acidic pH

Atherosclerosis is a disease of the arteries; its characteristic features include chronic inflammation, extra- and intracellular lipid accumulation, extracellular matrix remodeling, and an increase in extracellular matrix volume. The underlying mechanisms in the pathogenesis of advanced atherosclerotic plaques, that involve local acidity of the extracellular fluid, are still incompletely understood. In this thesis project, my co-workers and I studied the different mechanisms by which local extracellular acidity could promote accumulation of the atherogenic apolipoprotein B-100 (apoB-100)-containing plasma lipoprotein particles in the inner layer of the arterial wall, the intima. We found that lipolysis of atherogenic apoB-100-containing plasma lipoprotein particles (LDL, IDL, and sVLDL) by the secretory phospholipase A2 group V (sPLA2-V) enzyme, was increased at acidic pH. Also, the binding of apoB-100-containing plasma lipoprotein particles to human aortic proteoglycans was dramatically enhanced at acidic pH. Additionally, lipolysis by sPLA2-V enzyme further increased this binding. Using proteoglycan-affinity chromatography, we found that sVLDL lipoprotein particles consist of populations, differing in their affinities toward proteoglycans. These populations also contained different amounts of apolipoprotein E (apoE) and apolipoprotein C-III (apoC-III); the amounts of apoC-III and apoE per particle were highest in the population with the lowest affinity toward proteoglycans. Since PLA2-modification of LDL particles has been shown to change their aggregation behavior, we also studied the effect of acidic pH on the monolayer structure covering lipoprotein particles after PLA2-induced hydrolysis. Using molecular dynamics simulations, we found that, in acidity, the monolayer is more tightly packed laterally; moreover, its spontaneous curvature is negative, suggesting that acidity may promote lipoprotein particles fusion. In addition to extracellular lipid accumulation, the apoB-100-containing plasma lipoprotein particles can be taken up by inflammatory cells, namely macrophages. Using radiolabeled lipoprotein particles and cell cultures, we showed that sPLA2-V-modification of LDL, IDL, and sVLDL lipoproteins particles, at neutral or acidic pH, increased their uptake by human monocyte-derived macrophages.

Oral Actinomyces Species in Health and Disease: Identification, Occurence and Importance of Early Colonization

The genus Actinomyces consists of a heterogeneous group of gram-positive, mainly facultatively anaerobic or microaerobic rods showing various degrees of branching. In the oral cavity, streptococci and Actinomyces form a fundamental component of the indigenous microbiota, being among initial colonizers in polymicrobial biofilms. The significance of the genus Actinomyces is based on the capability of species to adhere to surfaces such as on teeth and to co-aggregate with other bacteria. Identification of Actinomyces species has mainly been based on only a few biochemical characteristics, such as pigmentation and catalase production, or on the use of a single commercial kit. The limited identification of oral Actinomyces isolates to species level has hampered knowledge of their role both in health and disease. In recent years, Actinomyces and related organisms have attracted the attention of clinical microbiologists because of a growing awareness of their presence in clinical specimens and their association with disease. This series of studies aimed to amplify the identification methods for Actinomyces species. With the newly developed identification scheme, the age-related occurrence of Actinomyces in healthy mouths of infants and their distribution in failed dental implants was investigated. Adhesion of Actinomyces species to titanium surfaces processed in various ways was studied in vitro. The results of phenotypic identification methods indicated a relatively low applicability of commercially available test kits for reliable identification within the genus Actinomyces. However, in the study of conventional phenotypic methods, it was possible to develop an identification scheme that resulted in accurate differentiation of Actinomyces and closely related species, using various different test methods. Genotypic methods based on 16S rRNA sequence analysis of Actinomyces proved to be a useful method for genus level identification and further clarified the species level identification with phenotypic methods. The results of the study of infants showed that the isolation frequency of salivary Actinomyces species increased according to age: thirty-one percent of the infants at 2 months but 97% at 2 years of age were positive for Actinomyces. A. odontolyticus was the most prominent Actinomyces colonizer during the study period followed in frequency by A. naeslundii and A. viscosus. In the study of explanted dental implants, Actinomyces was the most prevalent bacterial genus, colonizing 94% of the fixtures. Also in the implants A. odontolyticus was revealed as the most common Actinomyces species. It was present in 84% of Actinomyces -positive fixtures followed in frequency by A. naeslundii, A. viscosus and A. israelii. In an in vitro study of titanium surfaces, different Actinomyces species showed variation regarding their adhesion to titanium. Surface roughness as well as albumin coating of titanium had significant effects on adhesion. The use of improved phenotypic and molecular diagnostic methods increased the accuracy of the identification of the Actinomyces to species level. This facilitated an investigation of their occurrence and distribution in oral specimens in both health and disease.

Prevention of type 2 diabetes with lifestyle intervention - emphasis on dietary composition and identification of high-risk individuals

Type 2 diabetes is an increasing, serious, and costly public health problem. The increase in the prevalence of the disease can mainly be attributed to changing lifestyles leading to physical inactivity, overweight, and obesity. These lifestyle-related risk factors offer also a possibility for preventive interventions. Until recently, proper evidence regarding the prevention of type 2 diabetes has been virtually missing. To be cost-effective, intensive interventions to prevent type 2 diabetes should be directed to people at an increased risk of the disease. The aim of this series of studies was to investigate whether type 2 diabetes can be prevented by lifestyle intervention in high-risk individuals, and to develop a practical method to identify individuals who are at high risk of type 2 diabetes and would benefit from such an intervention. To study the effect of lifestyle intervention on diabetes risk, we recruited 522 volunteer, middle-aged (aged 40 - 64 at baseline), overweight (body mass index > 25 kg/m2) men (n = 172) and women (n = 350) with impaired glucose tolerance to the Diabetes Prevention Study (DPS). The participants were randomly allocated either to the intensive lifestyle intervention group or the control group. The control group received general dietary and exercise advice at baseline, and had annual physician's examination. The participants in the intervention group received, in addition, individualised dietary counselling by a nutritionist. They were also offered circuit-type resistance training sessions and were advised to increase overall physical activity. The intervention goals were to reduce body weight (5% or more reduction from baseline weight), limit dietary fat (< 30% of total energy consumed) and saturated fat (< 10% of total energy consumed), and to increase dietary fibre intake (15 g / 1000 kcal or more) and physical activity (≥ 30 minutes/day). Diabetes status was assessed annually by a repeated 75 g oral glucose tolerance testing. First analysis on end-points was completed after a mean follow-up of 3.2 years, and the intervention phase was terminated after a mean duration of 3.9 years. After that, the study participants continued to visit the study clinics for the annual examinations, for a mean of 3 years. The intervention group showed significantly greater improvement in each intervention goal. After 1 and 3 years, mean weight reductions were 4.5 and 3.5 kg in the intervention group and 1.0 kg and 0.9 kg in the control group. Cardiovascular risk factors improved more in the intervention group. After a mean follow-up of 3.2 years, the risk of diabetes was reduced by 58% in the intervention group compared with the control group. The reduction in the incidence of diabetes was directly associated with achieved lifestyle goals. Furthermore, those who consumed moderate-fat, high-fibre diet achieved the largest weight reduction and, even after adjustment for weight reduction, the lowest diabetes risk during the intervention period. After discontinuation of the counselling, the differences in lifestyle variables between the groups still remained favourable for the intervention group. During the post-intervention follow-up period of 3 years, the risk of diabetes was still 36% lower among the former intervention group participants, compared with the former control group participants. To develop a simple screening tool to identify individuals who are at high risk of type 2 diabetes, follow-up data of two population-based cohorts of 35-64 year old men and women was used. The National FINRISK Study 1987 cohort (model development data) included 4435 subjects, with 182 new drug-treated cases of diabetes identified during ten years, and the FINRISK Study 1992 cohort (model validation data) included 4615 subjects, with 67 new cases of drug-treated diabetes during five years, ascertained using the Social Insurance Institution's Drug register. Baseline age, body mass index, waist circumference, history of antihypertensive drug treatment and high blood glucose, physical activity and daily consumption of fruits, berries or vegetables were selected into the risk score as categorical variables. In the 1987 cohort the optimal cut-off point of the risk score identified 78% of those who got diabetes during the follow-up (= sensitivity of the test) and 77% of those who remained free of diabetes (= specificity of the test). In the 1992 cohort the risk score performed equally well. The final Finnish Diabetes Risk Score (FINDRISC) form includes, in addition to the predictors of the model, a question about family history of diabetes and the age category of over 64 years. When applied to the DPS population, the baseline FINDRISC value was associated with diabetes risk among the control group participants only, indicating that the intensive lifestyle intervention given to the intervention group participants abolished the diabetes risk associated with baseline risk factors. In conclusion, the intensive lifestyle intervention produced long-term beneficial changes in diet, physical activity, body weight, and cardiovascular risk factors, and reduced diabetes risk. Furthermore, the effects of the intervention were sustained after the intervention was discontinued. The FINDRISC proved to be a simple, fast, inexpensive, non-invasive, and reliable tool to identify individuals at high risk of type 2 diabetes. The use of FINDRISC to identify high-risk subjects, followed by lifestyle intervention, provides a feasible scheme in preventing type 2 diabetes, which could be implemented in the primary health care system.

Identification of two novel human neuronal ceroid lipofuscinosis genes

The neuronal ceroid lipofuscinoses (NCLs) are a group of mostly autosomal recessively inherited neurodegenerative disorders. The aim of this thesis was to characterize the molecular genetic bases of these, previously genetically undetermined, NCL forms. Congenital NCL is the most aggressive form of NCLs. Previously, a mutation in the cathepsin D (CTSD) gene was shown to cause congenital NCL in sheep. Based on the close resemblance of the phenotypes between congenital NCLs in sheep and human, CTSD was considered as a potential candidate gene in humans as well. When screened for mutations by sequencing, a homozygous nucleotide duplication creating a premature stop codon was identified in CTSD in one family with congenital NCL. While in vitro the overexpressed truncated mutant protein was stable although inactive, the absence of CTSD staining in brain tissue samples of patients indicated degradation of the mutant CTSD in vivo. A lack of CTSD staining was detected also in another, unrelated family with congenital NCL. These results imply that CTSD deficiency underlies congenital NCL. While initially Turkish vLINCL was considered a distinct genetic entity (CLN7), mutations in the CLN8 gene were later reported to account for the disease in a subset of Turkish patients with vLINCL. To further dissect the genetic basis of the disease, all known NCL genes were screened for homozygosity by haplotype analysis of microsatellite markers and/or sequenced in 13 mainly consanguineous, Turkish vLINCL families. Two novel, family-specific homozygous mutations were identified in the CLN6 gene. In the remaining families, all known NCL loci were excluded. To identify novel gene(s) underlying vLINCL, a genomewide single nucleotide polymorphism scan, homozygosity mapping, and positional candidate gene sequencing were performed in ten of these families. On chromosome 4q28.1-q28.2, a novel major facilitator superfamily domain containing 8 (MFSD8) gene with six family-specific homozygous mutations in vLINCL patients was identified. MFSD8 transcript was shown to be ubiquitously expressed with a complex pattern of alternative splicing. Our results suggest that MFSD8 is a novel lysosomal integral membrane protein which, as a member of the major facilitator superfamily, is predicted to function as a transporter. Identification of MFSD8 emphasizes the genetic heterogeneity of Turkish vLINCL. In families where no MFSD8 mutations were detected, additional NCL-causing genes remain to be identified. The identification of CTSD and MFSD8 increases the number of known human NCL-causing genes to eight, and is an important step towards the complete understanding of the genetic spectrum underlying NCLs. In addition, it is a starting point for dissecting the molecular mechanisms behind the associated NCLs and contributes to the challenging task of understanding the molecular pathology underlying the group of NCL disorders.

Identification of the Meckel syndrome gene (MKS1) exposes a novel ciliopathy

Meckel syndrome (MKS, MIM 249000) is an autosomal recessive developmental disorder causing death in utero or shortly after birth. The hallmarks of the disease are cystic kidney dysplasia and fibrotic changes of the liver, occipital encephalocele with or without hydrocephalus and polydactyly. Other anomalies frequently seen in the patients are incomplete development of the male genitalia, club feet and cleft lip or palate. The clinical picture has been well characterized in the literature while the molecular pathology underlying the disease has remained unclear until now. In this study we identified the first MKS gene by utilizing the disease haplotypes in Finnish MKS families linked to the MKS1 locus on chromosome 17q23 (MKS1) locus. Subsequently, the genetic heterogeneity of MKS was established in the Finnish families. Mutations in at least four different genes can cause MKS. These genes have been mapped to the chromosomes 17q23 (MKS1), 11q13 (MKS2), 8q22 (MKS3) and 9q33 (MKS4). Two of these genes have been identified so far: The MKS1 gene (this work) and the MKS3 gene. The identified MKS1 gene was initially a novel human gene which is conserved among species. We found three different MKS mutations, one of them being the Finnish founder mutation. The information available from MKS1 orthologs in other species convinced us that the MKS1 gene is required for normal ciliogenesis. Defects of the cilial system in other human diseases and model organisms actually cause phenotypic features similar to those seen in MKS patients. The MKS3 (TMEM67) gene encodes a transmembrane protein and the gene maps to the syntenic Wpk locus in the rat, which is a model with polycystic kidney disease, agenesis of the corpus callosum and hydrocephalus. The available information from these two genes suggest that MKS1 would encode a structural component of the centriole required for normal ciliary functions, and MKS3 would be a transmembrane component most likely required for normal ciliary sensory signaling. The MKS4 locus was localized to chromosme 9q32-33 in this study by using an inbred Finnish family with two affected and two healthy children. This fourth locus contains TRIM32 gene, which is associated to another well characterized human ciliopathy, Bardet Biedl syndrome (BBS). Future studies should identify the MKS4 gene on chromosome 9q and confirm if there are more than two genes causing MKS Finnish families. The research on critical signaling pathways in organogenesis have shown that both Wnt and Hedgehog pathways are dependent on functional cilia. The MKS gene products will serve as excellent model molecules for more detailed studies of the functional role of cilia in organogenesis in more detail.

Foodborne Yersinia : Identification and Molecular Epidemiology of Isolates from Human Infections

Yersinia enterocolitica and Yersinia pseudotuberculosis are among the major enteropathogenic bacteria causing infections in humans in many industrialized countries. In Finland, Y. pseudotuberculosis has caused 10 outbreaks among humans during 1997-2008. Some of these outbreaks have been very extensive involving over 400 cases; mainly children attending schools and day-care. Y. enterocolitica, on the contrary, has caused mainly a large number of sporadic human infections in Finland. Y. pseudotuberculosis is widespread in nature, causing infections in a variety of domestic and wild animals. Foodborne transmission of human infections has long been suspected, however, attempts to trace the pathogen have been unsuccessful before this study that epidemiologically linked Y. pseudotuberculosis to a specific food item. Furthermore, due to modern food distribution systems, foodborne outbreaks usually involve many geographically separate infection clusters difficult to identify as part of the same outbreak. Among pathogenic Y. enterocolitica, the global predominance of one genetically homogeneous type (bioserotype 4/O:3) is a challenge to the development of genetic typing methods discriminatory enough for epidemiological purposes, for example, for tracing back to the sources of infections. Furthermore, the diagnostics of Y. enterocolitica infections is hampered because clinical laboratories easily misidentify some other members of the Yersinia species (Y. enterocolitica–like species) as Y. enterocolitica. This results in misleading information on the prevalence and clinical significance of various Yersinia isolates. The aim of this study was to develop and optimize molecular typing methods to be used in epidemiological investigations of Y. enterocolitica and Y. pseudotuberculosis, particularly in active surveillance and outbreak investigations of Y. pseudotuberculosis isolates. The aim was also to develop a simplified set of phenotypic tests that could be used in routine diagnostic laboratories for the correct identification of Y. enterocolitica and Y. enterocolitica –like species. A PFGE method designed here for typing of Y. pseudotuberculosis was efficient in linking the geographically dispersed and apparently unrelated Y. pseudotuberculosis infections as parts of the same outbreak. It proved to be useful in active laboratory-based surveillance of Y. pseudotuberculosis outbreaks. Throughout the study period, information about the diversity of genotypes among outbreak and non-outbreak related strains of human origin was obtained. Also, to our knowledge, this was the first study to epidemiologically link a Y. pseudotuberculosis outbreak of human illnesses to a specific food item, iceberg lettuce. A novel epidemiological typing method based on the use of a repeated genomic region (YeO:3RS) as a probe was developed for the detection and differentiation between strains of Y. enterocolitica subspecies palearctica. This method was able to increase the discrimination in a set of 106 previously PFGE typed Finnish Y. enterocolitica bioserotype 4/O:3 strains among which two main PFGE genotypes had prevailed. The developed simplified method was a more reliable tool than the commercially available biochemical test kits for differentiation between Y. enterocolitica and Y. enterocolitica –like species. In Finland, the methods developed for Y. enterocolitica and Y. pseudotuberculosis have been used to improve the identification protocols and in subsequent outbreak investigations.

Modern techniques in detection, identification and quantification of bacteria and peptides from foods

Standards have been placed to regulate the microbial and preservative contents to assure that foods are safe to the consumer. In a case of a food-related disease outbreak, it is crucial to be able to detect and identify quickly and accurately the cause of the disease. In addition, for every day control of food microbial and preservative contents, the detection methods must be easily performed for numerous food samples. In this present study, quicker alternative methods were studied for identification of bacteria by DNA fingerprinting. A flow cytometry method was developed as an alternative to pulsed-field gel electrophoresis, the golden method . DNA fragment sizing by an ultrasensitive flow cytometer was able to discriminate species and strains in a reproducible and comparable manner to pulsed-field gel electrophoresis. This new method was hundreds times faster and 200,000 times more sensitive. Additionally, another DNA fingerprinting identification method was developed based on single-enzyme amplified fragment length polymorphism (SE-AFLP). This method allowed the differentiation of genera, species, and strains of pathogenic bacteria of Bacilli, Staphylococci, Yersinia, and Escherichia coli. These fingerprinting patterns obtained by SE-AFLP were simpler and easier to analyze than those by the traditional amplified fragment length polymorphism by double enzyme digestion. Nisin (E234) is added as a preservative to different types of foods, especially dairy products, around the world. Various detection methods exist for nisin, but they lack in sensitivity, speed or specificity. In this present study, a sensitive nisin-induced green fluorescent protein (GFPuv) bioassay was developed using the Lactococcus lactis two-component signal system NisRK and the nisin-inducible nisA promoter. The bioassay was extremely sensitive with detection limit of 10 pg/ml in culture supernatant. In addition, it was compatible for quantification from various food matrices, such as milk, salad dressings, processed cheese, liquid eggs, and canned tomatoes. Wine has good antimicrobial properties due to its alcohol concentration, low pH, and organic content and therefore often assumed to be microbially safe to consume. Another aim of this thesis was to study the microbiota of wines returned by customers complaining of food-poisoning symptoms. By partial 16S rRNA gene sequence analysis, ribotyping, and boar spermatozoa motility assay, it was identified that one of the wines contained a Bacillus simplex BAC91, which produced a heat-stable substance toxic to the mitochondria of sperm cells. The antibacterial activity of wine was tested on the vegetative cells and spores of B. simplex BAC91, B. cereus type strain ATCC 14579 and cereulide-producing B. cereus F4810/72. Although the vegetative cells and spores of B. simplex BAC91 were sensitive to the antimicrobial effects of wine, the spores of B. cereus strains ATCC 14579 and F4810/72 stayed viable for at least 4 months. According to these results, Bacillus spp., more specifically spores, can be a possible risk to the wine consumer.