Cereulide producing B. cereus and amylosin producing B. subtilis and B. mojavensis : characterization of strains and toxigenicities

B. cereus is one of the most frequent occurring bacteria in foods . It produces several heat-labile enterotoxins and one stable non-protein toxin, cereulide (emetic), which may be pre-formed in food. Cereulide is a heat stable peptide whose structure and mechanism of action were in the past decade elucidated. Until this work, the detection of cereulide was done by biological assays. With my mentors, I developed the first quantitative chemical assay for cereulide. The assay is based on liquid chromatography (HPLC) combined with ion trap mass spectrometry and the calibration is done with valinomycin and purified cereulide. To detect and quantitate valinomycin and cereulide, their [NH4+] adducts, m/z 1128.9 and m/z 1171 respectively, were used. This was a breakthrough in the cereulide research and became a very powerful tool of investigation. This tool made it possible to prove for the first time that the toxin produced by B. cereus in heat-treated food caused human illness. Until this thesis work (Paper II), cereulide producing B. cereus strains were believed to represent a homogenous group of clonal strains. The cereulide producing strains investigated in those studies originated mostly from food poisoning incidents. We used strains of many origins and analyzed them using a polyphasic approach. We found that the cereulide producing B. cereus strains are genetically and biologically more diverse than assumed in earlier studies. The strains diverge in the adenylate kinase (adk) gene (two sequence types), in ribopatterns obtained with EcoRI and PvuII (three patterns), tyrosin decomposition, haemolysis and lecithine hydrolysis (two phenotypes). Our study was the first demonstration of diversity within the cereulide producing strains of B. cereus. To manage the risk for cereulide production in food, understanding is needed on factors that may upregulate cereulide production in a given food matrix and the environmental factors affecting it. As a contribution towards this direction, we adjusted the growth environment and measured the cereulide production by strains selected for diversity. The temperature range where cereulide is produced was narrower than that for growth for most of the producer strains. Most cereulide was by most strains produced at room temperature (20 - 23ºC). Exceptions to this were two faecal isolates which produced the same amount of cereulide from 23 ºC up until 39ºC. We also found that at 37º C the choice of growth media for cereulide production differed from that at the room temperature. The food composition and temperature may thus be a key for understanding cereulide production in foods as well as in the gut. We investigated the contents of [K+], [Na+] and amino acids of six growth media. Statistical evaluation indicated a significant positive correlation between the ratio [K+]:[Na+] and the production of cereulide, but only when the concentrations of glycine and [Na+] were constant. Of the amino acids only glycine correlated positively with high cereulide production. Glycine is used worldwide as food additive (E 640), flavor modifier, humectant, acidity regulator, and is permitted in the European Union countries, with no regulatory quantitative limitation, in most types of foods. B. subtilis group members are endospore-forming bacteria ubiquitous in the environment, similar to B. cereus in this respect. Bacillus species other than B. cereus have only sporadically been identified as causative agents of food-borne illnesses. We found (Paper IV) that food-borne isolates of B. subtilis and B. mojavensis produced amylosin. It is possible that amylosin was the agent responsible for the food-borne illness, since no other toxic substance was found in the strains. This is the first report on amylosin production by strains isolated from food. We found that the temperature requirement for amylosin production was higher for the B. subtilis strain F 2564/96, a mesophilic producer, than for B. mojavensis strains eela 2293 and B 31, psychrotolerant producers. We also found that an atmosphere with low oxygen did not prevent the production of amylosin. Ready-to-eat foods packaged in micro-aerophilic atmosphere and/or stored at temperatures above 10 °C, may thus pose a risk when toxigenic strains of B. subtilis or B. mojavensis are present.

Environmental factors affecting the occurrence of periglacial landforms in Finnish Lapland: a numerical approach

Determination of the environmental factors controlling earth surface processes and landform patterns is one of the central themes in physical geography. However, the identification of the main drivers of the geomorphological phenomena is often challenging. Novel spatial analysis and modelling methods could provide new insights into the process-environment relationships. The objective of this research was to map and quantitatively analyse the occurrence of cryogenic phenomena in subarctic Finland. More precisely, utilising a grid-based approach the distribution and abundance of periglacial landforms were modelled to identify important landscape scale environmental factors. The study was performed using a comprehensive empirical data set of periglacial landforms from an area of 600 km2 at a 25-ha resolution. The utilised statistical methods were generalized linear modelling (GLM) and hierarchical partitioning (HP). GLMs were used to produce distribution and abundance models and HP to reveal independently the most likely causal variables. The GLM models were assessed utilising statistical evaluation measures, prediction maps, field observations and the results of HP analyses. A total of 40 different landform types and subtypes were identified. Topographical, soil property and vegetation variables were the primary correlates for the occurrence and cover of active periglacial landforms on the landscape scale. In the model evaluation, most of the GLMs were shown to be robust although the explanation power, prediction ability as well as the selected explanatory variables varied between the models. The great potential of the combination of a spatial grid system, terrain data and novel statistical techniques to map the occurrence of periglacial landforms was demonstrated in this study. GLM proved to be a useful modelling framework for testing the shapes of the response functions and significances of the environmental variables and the HP method helped to make better deductions of the important factors of earth surface processes. Hence, the numerical approach presented in this study can be a useful addition to the current range of techniques available to researchers to map and monitor different geographical phenomena.

Categorical Meteorological Products: Evaluation and Analysis

In meteorology, observations and forecasts of a wide range of phenomena for example, snow, clouds, hail, fog, and tornados can be categorical, that is, they can only have discrete values (e.g., "snow" and "no snow"). Concentrating on satellite-based snow and cloud analyses, this thesis explores methods that have been developed for evaluation of categorical products and analyses. Different algorithms for satellite products generate different results; sometimes the differences are subtle, sometimes all too visible. In addition to differences between algorithms, the satellite products are influenced by physical processes and conditions, such as diurnal and seasonal variation in solar radiation, topography, and land use. The analysis of satellite-based snow cover analyses from NOAA, NASA, and EUMETSAT, and snow analyses for numerical weather prediction models from FMI and ECMWF was complicated by the fact that we did not have the true knowledge of snow extent, and we were forced simply to measure the agreement between different products. The Sammon mapping, a multidimensional scaling method, was then used to visualize the differences between different products. The trustworthiness of the results for cloud analyses [EUMETSAT Meteorological Products Extraction Facility cloud mask (MPEF), together with the Nowcasting Satellite Application Facility (SAFNWC) cloud masks provided by Météo-France (SAFNWC/MSG) and the Swedish Meteorological and Hydrological Institute (SAFNWC/PPS)] compared with ceilometers of the Helsinki Testbed was estimated by constructing confidence intervals (CIs). Bootstrapping, a statistical resampling method, was used to construct CIs, especially in the presence of spatial and temporal correlation. The reference data for validation are constantly in short supply. In general, the needs of a particular project drive the requirements for evaluation, for example, for the accuracy and the timeliness of the particular data and methods. In this vein, we discuss tentatively how data provided by general public, e.g., photos shared on the Internet photo-sharing service Flickr, can be used as a new source for validation. Results show that they are of reasonable quality and their use for case studies can be warmly recommended. Last, the use of cluster analysis on meteorological in-situ measurements was explored. The Autoclass algorithm was used to construct compact representations of synoptic conditions of fog at Finnish airports.