Thin-Layer Chromatography with Ultraviolet and Mass Spectrometric Detection: From Preparative-Layer to Miniaturized Ultra-Thin-Layer Technique

The present challenge in drug discovery is to synthesize new compounds efficiently in minimal time. The trend is towards carefully designed and well-characterized compound libraries because fast and effective synthesis methods easily produce thousands of new compounds. The need for rapid and reliable analysis methods is increased at the same time. Quality assessment, including the identification and purity tests, is highly important since false (negative or positive) results, for instance in tests of biological activity or determination of early-ADME parameters in vitro (the pharmacokinetic study of drug absorption, distribution, metabolism, and excretion), must be avoided. This thesis summarizes the principles of classical planar chromatographic separation combined with ultraviolet (UV) and mass spectrometric (MS) detection, and introduces powerful, rapid, easy, low-cost, and alternative tools and techniques for qualitative and quantitative analysis of small drug or drug-like molecules. High performance thin-layer chromatography (HPTLC) was introduced and evaluated for fast semi-quantitative assessment of the purity of synthesis target compounds. HPTLC methods were compared with the liquid chromatography (LC) methods. Electrospray ionization mass spectrometry (ESI MS) and atmospheric pressure matrix-assisted laser desorption/ionization MS (AP MALDI MS) were used to identify and confirm the product zones on the plate. AP MALDI MS was rapid, and easy to carry out directly on the plate without scraping. The PLC method was used to isolate target compounds from crude synthesized products and purify them for bioactivity and preliminary ADME tests. Ultra-thin-layer chromatography (UTLC) with AP MALDI MS and desorption electrospray ionization mass spectrometry (DESI MS) was introduced and studied for the first time. Because of the thinner adsorbent layer, the monolithic UTLC plate provided 10 100 times better sensitivity in MALDI analysis than did HPTLC plates. The limits of detection (LODs) down to low picomole range were demonstrated for UTLC AP MALDI and UTLC DESI MS. In a comparison of AP and vacuum MALDI MS detection for UTLC plates, desorption from the irregular surface of the plates with the combination of an external AP MALDI ion source and an ion trap instrument provided clearly less variation in mass accuracy than the vacuum MALDI time-of-flight (TOF) instrument. The performance of the two-dimensional (2D) UTLC separation with AP MALDI MS method was studied for the first time. The influence of the urine matrix on the separation and the repeatability was evaluated with benzodiazepines as model substances in human urine. The applicability of 2D UTLC AP MALDI MS was demonstrated in the detection of metabolites in an authentic urine sample.

Sensory auditory processing and intuitive sound detection : an investigation of musical experts and nonexperts

The auditory system can detect occasional changes (deviants) in acoustic regularities without the need for subjects to focus their attention on the sound material. Deviant detection is reflected in the elicitation of the mismatch negativity component (MMN) of the event-related potentials. In the studies presented in this thesis, the MMN is used to investigate the auditory abilities for detecting similarities and regularities in sound streams. To investigate the limits of these processes, professional musicians have been tested in some of the studies. The results show that auditory grouping is already more advanced in musicians than in nonmusicians and that the auditory system of musicians can, unlike that of nonmusicians, detect a numerical regularity of always four tones in a series. These results suggest that sensory auditory processing in musicians is not only a fine tuning of universal abilities, but is also qualitatively more advanced than in nonmusicians. In addition, the relationship between the auditory change-detection function and perception is examined. It is shown that, contrary to the generally accepted view, MMN elicitation does not necessarily correlate with perception. The outcome of the auditory change-detection function can be implicit and the implicit knowledge of the sound structure can, after training, be utilized for behaviorally correct intuitive sound detection. These results illustrate the automatic character of the sensory change detection function.

Living on the edge : Population genetics of Finno-Ugric-speaking humans in North Eurasia

The major aim of this thesis was to examine the origins and distribution of uniparental and autosomal genetic variation among the Finno-Ugric-speaking human populations living in Boreal and Arctic regions of North Eurasia. In more detail, I aimed to disentangle the underlying molecular and population genetic factors which have produced the patterns of uniparental and autosomal genetic diversity in these populations. Among Finno-Ugrics the genetic amalgamation and clinal distribution of West and East Eurasian gene pools were observed within uniparental markers. This admixture indicates that North Eurasia was colonized through Central Asia/ South Siberia by human groups already carrying both West and East Eurasian lineages. The complex combination of founder effects, gene flow and genetic drift underlying the genetic diversity of the Finno-Ugric- speaking populations were emphasized by low haplotype diversity within and among uniparental and biparental markers. A high prevalence of lactase persistence allele among the North Eurasian Finno- Ugric agriculturalist populations was also shown indicating a local adaptation to subsistence change with lactose rich diet. Moreover, the haplotype background of lactase persistence allele among the Finno- Ugric-speakers strongly suggested that the lactase persistence T-13910 mutation was introduced independently more than once to the North Eurasian gene pool. A significant difference in genetic diversity, haplotype structure and LD distribution within the cytochrome P450 CYP2C and CYP2D regions revealed the unique gene pool of the Finno-Ugric Saami created mainly by population genetic processes compared to other Europeans and sub-Saharan Mandenka population. From all studied populations the Saami showed also significantly the highest allele frequency of a CYP2C19 gene mutation causing variable drug reactions. The diversity patterns observed within CYP2C and CYP2D regions emphasize the strong effect of demographic history shaping genetic diversity and LD especially among such small and constant size populations as the Finno-Ugric-speaking Saami. Moreover, the increased LD in Saami due to genetic drift and/or admixture was shown to offer an advantage for further attempts to identify alleles associated to common complex pharmacogenetic traits.

Early detection of type 2 diabetes mellitus in Chinese and Indian adult population

Objectives of this study were to determine secular trends of diabetes prevalence in China and develop simple risk assessment algorithms for screening individuals with high-risk for diabetes or with undiagnosed diabetes in Chinese and Indian adults. Two consecutive population based surveys in Chinese and a prospective study in Mauritian Indians were involved in this study. The Chinese surveys were conducted in randomly selected populations aged 20-74 years in 2001-2002 (n=14 592) and 35-74 years in 2006 (n=4416). A two-step screening strategy using fasting capillary plasma glucose (FCG) as first-line screening test followed by standard 2-hour 75g oral glucose tolerance tests (OGTTs) was applied to 12 436 individuals in 2001, while OGTTs were administrated to all participants together with FCG in 2006 and to 2156 subjects in 2002. In Mauritius, two consecutive population based surveys were conducted in Mauritian Indians aged 20-65 years in 1987 and 1992; 3094 Indians (1141 men), who were not diagnosed as diabetes at baseline, were reexamined with OGTTs in 1992 and/or 1998. Diabetes and pre-diabetes was defined following 2006 World Health Organization/ International Diabetes Federation Criteria. Age-standardized, as well as age- and sex-specific, prevalence of diabetes and pre-diabetes in adult Chinese was significantly increased from 12.2% and 15.4% in 2001 to 16.0% and 21.2% in 2006, respectively. A simple Chinese diabetes risk score was developed based on the data of Chinese survey 2001-2002 and validated in the population of survey 2006. The risk scores based on β coefficients derived from the final Logistic regression model ranged from 3 – 32. When the score was applied to the population of survey 2006, the area under operating characteristic curve (AUC) of the score for screening undiagnosed diabetes was 0.67 (95% CI, 0.65-0.70), which was lower than the AUC of FCG (0.76 [0.74-0.79]), but similar to that of HbA1c (0.68 [0.65-0.71]). At a cut-off point of 14, the sensitivity and specificity of the risk score in screening undiagnosed diabetes was 0.84 (0.81-0.88) and 0.40 (0.38-0.41). In Mauritian Indian, body mass index (BMI), waist girth, family history of diabetes (FH), and glucose was confirmed to be independent risk predictors for developing diabetes. Predicted probabilities for developing diabetes derived from a simple Cox regression model fitted with sex, FH, BMI and waist girth ranged from 0.05 to 0.64 in men and 0.03 to 0.49 in women. To predict the onset of diabetes, the AUC of the predicted probabilities was 0.62 (95% CI, 0.56-0.68) in men and 0.64(0.59-0.69) in women. At a cut-off point of 0.12, the sensitivity and specificity was 0.72(0.71-0.74) and 0.47(0.45-0.49) in men; and 0.77(0.75-0.78) and 0.50(0.48-0.52) in women, respectively. In conclusion, there was a rapid increase in prevalence of diabetes in Chinese adults from 2001 to 2006. The simple risk assessment algorithms based on age, obesity and family history of diabetes showed a moderate discrimination of diabetes from non-diabetes, which may be used as first line screening tool for diabetes and pre-diabetes, and for health promotion purpose in Chinese and Indians.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

Quantitative trait loci detection and benefits from marker-assisted selection in dairy cattle

Knowing the chromosomal areas or actual genes affecting the traits under selection would add more information to be used in the selection decisions which would potentially lead to higher genetic response. The first objective of this study was to map quantitative trait loci (QTL) affecting economically important traits in the Finnish Ayrshire population. The second objective was to investigate the effects of using QTL information in marker-assisted selection (MAS) on the genetic response and the linkage disequilibrium between the different parts of the genome. Whole genome scans were carried out on a grand-daughter design with 12 half-sib families and a total of 493 sons. Twelve different traits were studied: milk yield, protein yield, protein content, fat yield, fat content, somatic cell score (SCS), mastitis treatments, other veterinary treatments, days open, fertility treatments, non-return rate, and calf mortality. The average spacing of the typed markers was 20 cM with 2 to 14 markers per chromosome. Associations between markers and traits were analyzed with multiple marker regression. Significance was determined by permutation and genome-wise P-values obtained by Bonferroni correction. The benefits from MAS were investigated by simulation: a conventional progeny testing scheme was compared to a scheme where QTL information was used within families to select among full-sibs in the male path. Two QTL on different chromosomes were modelled. The effects of different starting frequencies of the favourable alleles and different size of the QTL effects were evaluated. A large number of QTL, 48 in total, were detected at 5% or higher chromosome-wise significance. QTL for milk production were found on 8 chromosomes, for SCS on 6, for mastitis treatments on 1, for other veterinary treatments on 5, for days open on 7, for fertility treatments on 7, for calf mortality on 6, and for non-return rate on 2 chromosomes. In the simulation study the total genetic response was faster with MAS than with conventional selection and the advantage of MAS persisted over the studied generations. The rate of response and the difference between the selection schemes reflected clearly the changes in allele frequencies of the favourable QTL. The disequilibrium between the polygenes and QTL was always negative and it was larger with larger QTL size. The disequilibrium between the two QTL was larger with QTL of large effect and it was somewhat larger with MAS for scenarios with starting frequencies below 0.5 for QTL of moderate size and below 0.3 for large QTL. In conclusion, several QTL affecting economically important traits of dairy cattle were detected. Further studies are needed to verify these QTL, check their presence in the present breeding population, look for pleiotropy and fine map the most interesting QTL regions. The results of the simulation studies show that using MAS together with embryo transfer to pre-select young bulls within families is a useful approach to increase the genetic merit of the AI-bulls compared to conventional selection.

Lantibiotic Nisin and Its Detection Methods

The type A lantibiotic nisin produced by several Lactococcus lactis strains, and one Streptococcus uberis strainis a small antimicrobial peptide that inhibits the growth of a wide range of gram-positive bacteria, such as Bacillus, Clostridium, Listeria and Staphylococcus species. It is nontoxic to humans and used as a food preservative (E234) in more than 50 countries including the EU, the USA, and China. National legislations concerning maximum addition levels of nisin in different foods vary greatly. Therefore, there is a demand for non-laborious and sensitive methods to identify and quantify nisin reliably from different food matrices. The horizontal inhibition assay, based on the inhibitory effect of nisin to Micrococcus luteus is the base for most quantification methods developed so far. However, the sensitivity and accuracy of the agar diffusion method is affected by several parameters. Immunological tests have also been described. Taken into account the sensitivity of immunological methods to interfering substances within sample matrices, and possible cross-reactivities with lantibiotics structurally close to nisin, their usefulness for nisin detection from food samples remains limited. The proteins responsible for nisin biosynthesis, and producer self-immunity are encoded by genes arranged into two inducible operons, nisA/Z/QBTCIPRK and nisFEG, which also contain internal, constitutive promoters PnisI and PnisR. The transmembrane histidine kinase NisK and the response regulator NisR form a two-component signal transduction system, in which NisK autophosphorylates after exposure to extra cellular nisin, and subsequently transfers the phosphate to NisR. The phosphorylated NisR then relays the signal downstream by binding to two regulated promoters in the nisin gene cluster, i.e the nisA/Z/Qand the nisF promoters, thus activating transcription of the structural gene nisA/Z/Q and the downstream genes nisBTCIPRK from the nisA/Z/Q promoter, and the genes nisFEG from the nisF promoter. In this work two novel and highly sensitive nisin bioassays were developed. Both of these quantification methods were based on NisRK mediated, nisin induced Green Fluorescent Protein (GFP) fluorescence. The suitabilities of these assays for quantifica¬tion of nisin from food samples were evaluated in several food matrices. These bioassays had nisin sensitivities in the nanogram or picogram levels. In addition, shelf life of nisin in cooked sausages and retainment of the induction activity of nisin in intestinal chyme (intestinal content) was assessed.

Evolution and detection of cyanobacterial hepatotoxin synthetase genes

Mass occurrences (blooms) of cyanobacteria are common in aquatic environments worldwide. These blooms are often toxic, due to the presence of hepatotoxins or neurotoxins. The most common cyanobacterial toxins are hepatotoxins: microcystins and nodularins. In freshwaters, the main producers of microcystins are Microcystis, Anabaena, and Planktothrix. Nodularins are produced by strains of Nodularia spumigena in brackish waters. Toxic and nontoxic strains of cyanobacteria co-occur and cannot be differentiated by conventional microscopy. Molecular biological methods based on microcystin and nodularin synthetase genes enable detection of potentially hepatotoxic cyanobacteria. In the present study, molecular detection methods for hepatotoxin-producing cyanobacteria were developed, based on microcystin synthetase gene E (mcyE) and the orthologous nodularin synthetase gene F (ndaF) sequences. General primers were designed to amplify the mcyE/ndaF gene region from microcystin-producing Anabaena, Microcystis, Planktothrix, and Nostoc, and nodularin-producing Nodularia strains. The sequences were used for phylogenetic analyses to study how cyanobacterial mcy genes have evolved. The results showed that mcy genes and microcystin are very old and were already present in the ancestor of many modern cyanobacterial genera. The results also suggested that the sporadic distribution of biosynthetic genes in modern cyanobacteria is caused by repeated gene losses in the more derived lineages of cyanobacteria and not by horizontal gene transfer. Phylogenetic analysis also proposed that nda genes evolved from mcy genes. The frequency and composition of the microcystin producers in 70 lakes in Finland were studied by conventional polymerase chain reaction (PCR). Potential microcystin producers were detected in 84% of the lakes, using general mcyE primers, and in 91% of the lakes with the three genus-specific mcyE primers. Potential microcystin-producing Microcystis were detected in 70%, Planktothrix in 63%, and Anabaena in 37% of the lakes. The presence and co-occurrence of potential microcystin producers were more frequent in eutrophic lakes, where the total phosphorus concentration was high. The PCR results could also be associated with various environmental factors by correlation and regression analyses. In these analyses, the total nitrogen concentration and pH were both associated with the presence of multiple microcystin-producing genera and partly explained the probability of occurrence of mcyE genes. In general, the results showed that higher nutrient concentrations increased the occurrence of potential microcystin producers and the risk for toxic bloom formation. Genus-specific probe pairs for microcystin-producing Anabaena, Microcystis, Planktothrix, and Nostoc, and nodularin-producing Nodularia were designed to be used in a DNA-chip assay. The DNA-chip can be used to simultaneously detect all these potential microcystin/nodularin producers in environmental water samples. The probe pairs detected the mcyE/ndaF genes specifically and sensitively when tested with cyanobacterial strains. In addition, potential microcystin/nodularin producers were identified in lake and Baltic Sea samples by the DNA-chip almost as sensitively as by quantitative real-time PCR (qPCR), which was used to validate the DNA-chip results. Further improvement of the DNA-chip assay was achieved by optimization of the PCR, the first step in the assay. Analysis of the mcy and nda gene clusters from various hepatotoxin-producing cyanobacteria was rewarding; it revealed that the genes were ancient. In addition, new methods detecting all the main producers of hepatotoxins could be developed. Interestingly, potential microcystin-producing cyanobacterial strains of Microcystis, Planktothrix, and Anabaena, co-occurred especially in eutrophic and hypertrophic lakes. Protecting waters from eutrophication and restoration of lakes may thus decrease the prevalence of toxic cyanobacteria and the frequency of toxic blooms.

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.

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.

Lactic acid bacteria and their antimicrobial peptides : Induction,detection,partial characterization, and potential applications

Bacteriocin-producing lactic acid bacteria and their isolated peptide bacteriocins are of value to control pathogens and spoiling microorganisms in foods and feed. Nisin is the only bacteriocin that is commonly accepted as a food preservative and has a broad spectrum of activity against Gram-positive organisms including spore forming bacteria. In this study nisin induction was studied from two perspectives, induction from inside of the cell and selection of nisin inducible strains with increased nisin induction sensitivity. The results showed that a mutation in the nisin precursor transporter NisT rendered L. lactis incapable of nisin secretion and lead to nisin accumulation inside the cells. Intracellular proteolytic activity could cleave the N-terminal leader peptide of nisin precursor, resulting in active nisin in the cells. Using a nisin sensitive GFP bioassay it could be shown, that the active intracellular nisin could function as an inducer without any detectable release from the cells. The results suggested that nisin can be inserted into the cytoplasmic membrane from inside the cell and activate NisK. This model of two-component regulation may be a general mechanism of how amphiphilic signals activate the histidine kinase sensor and would represent a novel way for a signal transduction pathway to recognize its signal. In addition, nisin induction was studied through the isolation of natural mutants of the GFPuv nisin bioassay strain L. lactis LAC275 using fl uorescence-activated cell sorting (FACS). The isolated mutant strains represent second generation of GFPuv bioassay strains which can allow the detection of nisin at lower levels. The applied aspect of this thesis was focused on the potential of bacteriocins in chicken farming. One aim was to study nisin as a potential growth promoter in chicken feed. Therefore, the lactic acid bacteria of chicken crop and the nisin sensitivity of the isolated strains were tested. It was found that in the crop Lactobacillus reuteri, L. salivarius and L. crispatus were the dominating bacteria and variation in nisin resistance level of these strains was found. This suggested that nisin may be used as growth promoter without wiping out the dominating bacterial species in the crop. As the isolated lactobacilli may serve as bacteria promoting chicken health or reducing zoonoosis and bacteriocin production is one property associated with probiotics, the isolated strains were screened for bacteriocin activity against the pathogen Campylobacter jejuni. The results showed that many of the isolated L. salivarius strains could inhibit the growth of C. jejuni. The bacteriocin of the L. salivarius LAB47 strain, with the strongest activity, was further characterized. Salivaricin 47 is heat-stable and active in pH range 3 to 8, and the molecular mass was estimated to be approximately 3.2 kDa based on tricine SDS-PAGE analysis.

Wind drift of snowfall between the radar volume and ground

This study evaluates how the advection of precipitation, or wind drift, between the radar volume and ground affects radar measurements of precipitation. Normally precipitation is assumed to fall vertically to the ground from the contributing volume, and thus the radar measurement represents the geographical location immediately below. In this study radar measurements are corrected using hydrometeor trajectories calculated from measured and forecasted winds, and the effect of trajectory-correction on the radar measurements is evaluated. Wind drift statistics for Finland are compiled using sounding data from two weather stations spanning two years. For each sounding, the hydrometeor phase at ground level is estimated and drift distance calculated using different originating level heights. This way the drift statistics are constructed as a function of range from radar and elevation angle. On average, wind drift of 1 km was exceeded at approximately 60 km distance, while drift of 10 km was exceeded at 100 km distance. Trajectories were calculated using model winds in order to produce a trajectory-corrected ground field from radar PPI images. It was found that at the upwind side from the radar the effective measuring area was reduced as some trajectories exited the radar volume scan. In the downwind side areas near the edge of the radar measuring area experience improved precipitation detection. The effect of trajectory-correction is most prominent in instant measurements and diminishes when accumulating over longer time periods. Furthermore, measurements of intensive and small scale precipitation patterns benefit most from wind drift correction. The contribution of wind drift on the uncertainty of estimated Ze (S) - relationship was studied by simulating the effect of different error sources to the uncertainty in the relationship coefficients a and b. The overall uncertainty was assumed to consist of systematic errors of both the radar and the gauge, as well as errors by turbulence at the gauge orifice and by wind drift of precipitation. The focus of the analysis is error associated with wind drift, which was determined by describing the spatial structure of the reflectivity field using spatial autocovariance (or variogram). This spatial structure was then used with calculated drift distances to estimate the variance in radar measurement produced by precipitation drift, relative to the other error sources. It was found that error by wind drift was of similar magnitude with error by turbulence at gauge orifice at all ranges from radar, with systematic errors of the instruments being a minor issue. The correction method presented in the study could be used in radar nowcasting products to improve the estimation of visibility and local precipitation intensities. The method however only considers pure snow, and for operational purposes some improvements are desirable, such as melting layer detection, VPR correction and taking solid state hydrometeor type into account, which would improve the estimation of vertical velocities of the hydrometeors.