Genetic and environmental influences on human responses to odors

Olfaction, the sense of smell, has many important functions in humans. Human responses to odors show substantial individual variation. Olfactory receptor genes have been identified and other genes may also influence olfaction. However, the proportion of phenotypic variation in odor response due to genetic variation remains largely unknown. Little is also known about which genes modify specific responses to odors. This study aimed to elucidate genetic and environmental influences on human responses to odors. Individuals from Finnish families (n=146) and Australian (n=413), British (n=163), Danish (n=336), and Finnish (n=399) twins rated intensity and pleasantness of a set of 12 (families) or 6 (twins) odors and tried to identify the odors. In addition, the participants rated their own sense of smell and annoyance experienced with different environmental odors. The odor stimuli of a commercial smell test (The Brief Smell Identification Test; banana, chocolate, cinnamon, gasoline, lemon, onion, paint thinner, pineapple, rose, smoke, soap, and turpentine) were presented in the family study. Based on the results of the family study and a literature survey, a new set of odor stimuli (androstenone, chocolate, cinnamon, isovaleric acid, lemon, and turpentine) was designed for the twin studies. In the family sample, heritabilities of the traits were estimated and underlying genomic regions were searched using a genome-wide linkage scan. In the pooled twin sample, variation in the measured traits was decomposed into genetic and environmental components using quantitative genetic modeling. In addition, associations between nongenetic factors (e.g., sex, age, and smoking) and olfactory-related traits were explored. Suggestive evidence for a genetic linkage for pleasantness of cinnamon at a locus on chromosome 4q32.3 emerged from the family sample. High heritability for the pleasantness of cinnamon was found in the family but not the twin study. Heritability of perceived intensity of androstenone odor was determined to be ~30% in the twin sample. A strong genetic correlation between perceived intensity and pleasantness of androstenone, in the absence of any environmental correlation, indicated that only the genetic correlation explained the phenotypic correlation between the traits (r=-0.27) and that the traits were influenced by an overlapping set of genes. Self-rated olfactory function appeared to reflect the odor annoyance experienced rather than actual olfactory acuity or genetic involvement. Results from nongenetic analyses supported the speculated superiority of females' olfactory abilities, the age-related diminishing of olfactory acuity, and the influences of experience-dependent factors on odor responses. This was the first study to estimate heritabilities and perform linkage screens for individual odors. A genetic effect was detected for only a few responses to specific odors, suggesting the predominance of environmental effects in odor perceptions.

A matter of taste : genetic and environmental influences on responses to sweetness

Diet is a major player in the maintenance of health and onset of many diseases of public health importance. The food choice is known to be largely influenced by sensory preferences. However, in many cases it is unclear whether these preferences and dietary behaviors are innate or acquired. The aim of this thesis work was to study the extent to which the individual differences in dietary responses, especially in liking for sweet taste, are influenced by genetic factors. Several traits measuring the responses to sweetness and other dietary variables were applied in four studies: in British (TwinsUK) and Finnish (FinnTwin12 and FinnTwin16) twin studies and in a Finnish migraine family study. All the subjects were adults and they participated in chemosensory measurements (taste and smell tests) and filled in food behavior questionnaires. Further, it was studied, whether the correlations among the variables are mediated by genetic or environmental factors and where in the genome the genes influencing the heritable traits are located. A study of young adult Finnish twins (FinnTwin16, n=4388) revealed that around 40% of the food use is attributable to genetic factors and that the common, childhood environment does not affect the food use even shortly after moving from the parents home. Both the family study (n=146) and the twin studies (British twins, n=663) showed that around half of the variation in the liking for sweetness is inherited. The same result was obtained both by the chemosensory measurements (heritability 41-49%) and the questionnaire variables (heritability 31-54%). By contrast, the intensity perception of sweetness or the responses to saltiness were not influenced by genetic factors. Further, a locus influencing the use-frequency of sweet foods was identified on chromosome 16p. A closer examination of the relationships among the variables based on 663 British twins revealed that several genetic and environmental correlations exist among the different measures of liking for sweetness. However, these correlations were not very strong (range 0.06-0.55) implying that the instruments used measure slightly different aspects of the phenomenon. In addition, the assessment of the associations among responses to fatty foods, dieting behaviors, and body mass index in twin populations (TwinsUK n=1027 and FinnTwin12 n=299) showed that the dieting behaviors (cognitive restraint, uncontrolled eating, and emotional eating) mediate the relationship between obesity and diet. In conclusion, the work increased the understanding of the background variables of human eating behavior. Genetic effects were shown to underlie the variation of many dietary traits, such as liking for sweet taste, use of sweet foods, and dieting behaviors. However, the responses to salty taste were shown to be mainly determined by environmental factors and thus should more easily be modifiable by dietary education, exposure, and learning than sweet taste preferences. Although additional studies are needed to characterize the genetic element located on chromosome 16 that influences the use-frequency of sweet foods, the results underline the importance of inherited factors on human eating behavior.

Responses of soil microbial communities to clonal variation of Norway spruce

In boreal forests, microorganisms have a pivotal role in nutrient and water supply of trees as well as in litter decomposition and nutrient cycling. This reinforces the link between above-ground and below-ground communities in the context of sustainable productivity of forest ecosystems. In northern boreal forests, the diversity of microbes associated with the trees is high compared to the number of distinct tree species. In this thesis, the aim was to study whether conspecific tree individuals harbour different soil microbes and whether the growth of the trees and the community structure of the associated microbes are connected. The study was performed in a clonal field trial of Norway spruce, which was established in a randomized block design in a clear-cut area. Since out-planting in 1994, the spruce clones showed two-fold growth differences. The fast-growing spruce clones were associated with a more diverse community of ectomycorrhizal fungi than the slow-growing spruce clones. These growth performance groups also differed with respect to other aspects of the associated soil microorganisms: the species composition of ectomycorrhizal fungi, in the amount of extraradical fungal mycelium, in the structure of bacterial community associated with the mycelium, and in the structure of microbial community in the organic layer. The communities of fungi colonizing needle litter of the spruce clones in the field did not differ and the loss of litter mass after two-years decomposition was equal. In vitro, needles of the slow-growing spruce clones were colonized by a more diverse community of endophytic fungi that were shown to be significant needle decomposers. This study showed a relationship between the growth of Norway spruce clones and the community structure of the associated soil microbes. Spatial heterogeneity in soil microbial community was connected with intraspecific variation of trees. The latter may therefore influence soil biodiversity in monospecific forests.

Postglacial climate changes and vegetation responses in northern Europe

Postglacial climate changes and vegetation responses were studied using a combination of biological and physical indicators preserved in lake sediments. Low-frequency trends, high-frequency events and rapid shifts in temperature and moisture balance were probed using pollen-based quantitative temperature reconstructions and oxygen-isotopes from authigenic carbonate and aquatic cellulose, respectively. Pollen and plant macrofossils were employed to shed light on the presence and response rates of plant populations in response to climate changes, particularly focusing on common boreal and temperate tree species. Additional geochemical and isotopic tracers facilitated the interpretation of pollen- and oxygen-isotope data. The results show that the common boreal trees were present in the Baltic region (~55°N) during the Lateglacial, which contrasts with the traditional view of species refuge locations in the south-European peninsulas during the glacial/interglacial cycles. The findings of this work are in agreement with recent paleoecological and genetic evidence suggesting that scattered populations of tree species persisted at higher latitudes, and that these taxa were likely limited to boreal trees. Moreover, the results demonstrate that stepwise changes in plant communities took place in concert with major climate fluctuations of the glacial/interglacial transition. Postglacial climate trends in northern Europe were characterized by rise, maxima and fall in temperatures and related changes in moisture balance. Following the deglaciation of the Northern Hemisphere and the early Holocene reorganization of the ice-ocean-atmosphere system, the long-term temperature trends followed gradually decreasing summer insolation. The early Holocene (~11,700-8000 cal yr BP) was overall cool, moist and oceanic, although the earliest Holocene effective humidity may have been low particularly in the eastern part of northern Europe. The gradual warming trend was interrupted by a cold event ~8200 cal yr BP. The maximum temperatures, ~1.5-3.0°C above modern values, were attained ~8000-4000 cal yr BP. This mid-Holocene peak warmth was coupled with low lake levels, low effective humidity and summertime drought. The late Holocene (~4000 cal yr BP-present) was characterized by gradually decreasing temperatures, higher lake levels and higher effective humidity. Moreover, the gradual trends of the late Holocene were probably superimposed by higher-frequency variability. The spatial variability of the Holocene temperature and moisture balance patterns were tentatively attributed to the differing heat capacities of continents and oceans, changes in atmospheric circulation modes and position of sites and subregions with respect to large water bodies and topographic barriers. The combination of physical and biological proxy archives is a pivotal aspect of this work, because non-climatic factors, such as postglacial migration, disturbances and competitive interactions, can influence reshuffling of vegetation and hence, pollen-based climate reconstructions. The oxygen-isotope records and other physical proxies presented in this work manifest that postglacial climate changes were the main driver of the establishment and expansion of temperate and boreal tree populations, and hence, large-scale and long-term vegetation patterns were in dynamic equilibrium with climate. A notable exception to this pattern may be the postglacial invasion of Norway spruce and the related suppression of mid-Holocene temperate forest. This salient step in north-European vegetation history, the development of the modern boreal ecosystem, cannot be unambiguously explained by current evidence of postglacial climate changes. The results of this work highlight that plant populations, including long-lived trees, may be able to respond strikingly rapidly to changes in climate. Moreover, interannual and seasonal variation and extreme events can exert an important influence on vegetation reshuffling. Importantly, the studies imply that the presence of diffuse refuge populations or local stands among the prevailing vegetation may have provided the means for extraordinarily rapid vegetation responses. Hence, if scattered populations are not provided and tree populations are to migrate long distances, their capacity to keep up with predicted rates of future climate change may be lower than previously thought.

Joint Regression and Association Models for Repeated Categorical Responses

The focus of this study is on statistical analysis of categorical responses, where the response values are dependent of each other. The most typical example of this kind of dependence is when repeated responses have been obtained from the same study unit. For example, in Paper I, the response of interest is the pneumococcal nasopharengyal carriage (yes/no) on 329 children. For each child, the carriage is measured nine times during the first 18 months of life, and thus repeated respones on each child cannot be assumed independent of each other. In the case of the above example, the interest typically lies in the carriage prevalence, and whether different risk factors affect the prevalence. Regression analysis is the established method for studying the effects of risk factors. In order to make correct inferences from the regression model, the associations between repeated responses need to be taken into account. The analysis of repeated categorical responses typically focus on regression modelling. However, further insights can also be gained by investigating the structure of the association. The central theme in this study is on the development of joint regression and association models. The analysis of repeated, or otherwise clustered, categorical responses is computationally difficult. Likelihood-based inference is often feasible only when the number of repeated responses for each study unit is small. In Paper IV, an algorithm is presented, which substantially facilitates maximum likelihood fitting, especially when the number of repeated responses increase. In addition, a notable result arising from this work is the freely available software for likelihood-based estimation of clustered categorical responses.

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.

Algorithms for 13C metabolic flux analysis

The metabolism of an organism consists of a network of biochemical reactions that transform small molecules, or metabolites, into others in order to produce energy and building blocks for essential macromolecules. The goal of metabolic flux analysis is to uncover the rates, or the fluxes, of those biochemical reactions. In a steady state, the sum of the fluxes that produce an internal metabolite is equal to the sum of the fluxes that consume the same molecule. Thus the steady state imposes linear balance constraints to the fluxes. In general, the balance constraints imposed by the steady state are not sufficient to uncover all the fluxes of a metabolic network. The fluxes through cycles and alternative pathways between the same source and target metabolites remain unknown. More information about the fluxes can be obtained from isotopic labelling experiments, where a cell population is fed with labelled nutrients, such as glucose that contains 13C atoms. Labels are then transferred by biochemical reactions to other metabolites. The relative abundances of different labelling patterns in internal metabolites depend on the fluxes of pathways producing them. Thus, the relative abundances of different labelling patterns contain information about the fluxes that cannot be uncovered from the balance constraints derived from the steady state. The field of research that estimates the fluxes utilizing the measured constraints to the relative abundances of different labelling patterns induced by 13C labelled nutrients is called 13C metabolic flux analysis. There exist two approaches of 13C metabolic flux analysis. In the optimization approach, a non-linear optimization task, where candidate fluxes are iteratively generated until they fit to the measured abundances of different labelling patterns, is constructed. In the direct approach, linear balance constraints given by the steady state are augmented with linear constraints derived from the abundances of different labelling patterns of metabolites. Thus, mathematically involved non-linear optimization methods that can get stuck to the local optima can be avoided. On the other hand, the direct approach may require more measurement data than the optimization approach to obtain the same flux information. Furthermore, the optimization framework can easily be applied regardless of the labelling measurement technology and with all network topologies. In this thesis we present a formal computational framework for direct 13C metabolic flux analysis. The aim of our study is to construct as many linear constraints to the fluxes from the 13C labelling measurements using only computational methods that avoid non-linear techniques and are independent from the type of measurement data, the labelling of external nutrients and the topology of the metabolic network. The presented framework is the first representative of the direct approach for 13C metabolic flux analysis that is free from restricting assumptions made about these parameters.In our framework, measurement data is first propagated from the measured metabolites to other metabolites. The propagation is facilitated by the flow analysis of metabolite fragments in the network. Then new linear constraints to the fluxes are derived from the propagated data by applying the techniques of linear algebra.Based on the results of the fragment flow analysis, we also present an experiment planning method that selects sets of metabolites whose relative abundances of different labelling patterns are most useful for 13C metabolic flux analysis. Furthermore, we give computational tools to process raw 13C labelling data produced by tandem mass spectrometry to a form suitable for 13C metabolic flux analysis.

Communities of wood-inhabiting fungi : Ecological requirements and responses to forest management and fragmentation

Despite much research on forest biodiversity in Fennoscandia, the exact mechanisms of species declines in dead-wood dependent fungi are still poorly understood. In particular, there is only limited information on why certain fungal species have responded negatively to habitat loss and fragmentation, while others have not. Understanding the mechanisms behind species declines would be essential for the design and development of ecologically effective and scientifically informed conservation measures, and management practices that would promote biodiversity in production forests. In this thesis I study the ecology of polypores and their responses to forest management, with a particular focus on why some species have declined more than others. The data considered in the thesis comprise altogether 98,318 dead-wood objects, with 43,085 observations of 174 fungal species. Out of these, 1,964 observations represent 58 red-listed species. The data were collected from 496 sites, including woodland key habitats, clear-cuts with retention trees, mature managed forests, and natural or natural-like forests in southern Finland and Russian Karelia. I show that the most relevant way of measuring resource availability can differ to a great extent between species seemingly sharing the same resources. It is thus critical to measure the availability of resources in a way that takes into account the ecological requirements of the species. The results show that connectivity at the local, landscape and regional scales is important especially for the highly specialized species, many of which are also red-listed. Habitat loss and fragmentation affect not only species diversity but also the relative abundances of the species and, consequently, species interactions and fungal successional pathways. Changes in species distributions and abundances are likely to affect the food chains in which wood-inhabiting fungi are involved, and thus the functioning of the whole forest ecosystem. The findings of my thesis highlight the importance of protecting well-connected, large and high-quality forest areas to maintain forest biodiversity. Small habitat patches distributed across the landscape are likely to contribute only marginally to protection of red-listed species, especially if habitat quality is not substantially higher than in ordinary managed forest, as is the case with woodland key habitats. Key habitats might supplement the forest protection network if they were delineated larger and if harvesting of individual trees was prohibited in them. Taking the landscape perspective into account in the design and development of conservation measures is critical while striving to halt the decline of forest biodiversity in an ecologically effective manner.

GDP-L-fucose: synthesis and role in inflammation

GDP-L-fucose: synthesis and role in inflammation The migration of leukocytes from intravascular locations to extravascular sites is essential to the immune responses. The initial attachment of leukocytes to the endothelium and the rolling step of the leukocyte extravasation cascade are mediated by selectins, a family of cell adhesion molecules on cell surfaces. Selectins are able to recognize glycoproteins and glycolipids containing the tetrasaccharide sialyl Lewis x (sLex, Neu5Acα2-3Galβ1-4(Fucα1-3)GlcNAc). Several glycosyltransferases are involved in the biosynthesis of sLex, fucosyltransferase VII (Fuc-TVII) being the last enzyme to modify the sLex structure. Fuc-TVII transfers L-fucose from GDP-L-fucose to sialylated N-acetyllactosamine. GDP-L-fucose is synthesized in the cytosol via two different metabolic pathways. The major, constitutively active de novo pathway involves conversion of GDP-α-D-mannose to GDP-β-L-fucose. In the alternative salvage pathway, L-fucokinase synthesizes from free fucose L-fucose-1-phosphate, which is further converted to GDP-L-fucose by GDP-L-fucose pyrophosphorylase. GDP-L-fucose is translocated from the cytosol to Golgi for fucosylation via the GDP-fucose transporter. This thesis involved the study of the synthesis of GDP-L-fucose via the salvage pathway: cloning and expression of murine L-fucokinase and GDP-L-fucose pyrophosphorylase. The gene expression levels of these enzymes were found to be relatively high in various tissues; the mRNA levels were highest in brain, ovary and testis. This study also describes molecular cloning of rat fucosyltransferase VII (FUT7) and its expression as a functional enzyme. Gene expression levels of GDP-L-fucose synthesizing enzymes, GDP-fucose transporter and FUT7 were determined in inflamed tissues as well as cancer cells. Our results revealed a clear upregulation of the enzymes involved in the synthesis of GDP-L-fucose via de novo pathway, GDP-fucose transporter and FUT7 in inflamed tissues and in cancer cells. On the contrary, the GDP-L-fucose salvage pathway was found to be irrelevant in inflammation and in tumorigenesis. Furthermore, our results indicated the transcriptional coregulation of Golgi transporters involved in the synthesis of sulfo sLex, i.e. CMP-sialic acid, GDP-fucose and 3 phosphoadenosine 5 -phosphosulfate transporters, in inflammation.

Recovery responses of acidified Finnish lakes under declining acid deposition

The present work provides a regional-scale assessment of the changes in acidifying deposition in Finland over the past 30 years and the current pattern in the recovery of acid-sensitive lakes from acidification in relation to changes in sulphate deposition. This information is needed for documenting the ecosystem benefits of costly emission reduction policies and further actions in air pollution policy. The development of sulphate deposition in Finland reflects that of European SO2 emissions. Before the 1990s, reductions in sulphur emissions in Europe had been relatively small and sulphate deposition showed no consistent trends. Due to emission reduction measures that were then taken, sulphate deposition started to clearly decline from the late 1980s. The bulk deposition of sulphate has declined 40-60% in most parts of the country during 1990-2003. The decline in sulphate deposition exceeded the decline of base cation deposition, which resulted in a decrease in acidity and acidifying potential of deposition over the 1990s. Nitrogen deposition also decreased since the late 1980s, but less than that of sulphate, and levelling off during the 1990s. Sulphate concentrations in all types of small lakes throughout Finland have declined from the early 1990s. The relative decrease in lake sulphate concentrations (average 40-50%) during 1990-2003 was rather similar to the decline in sulphate deposition, indicating a direct response to the reduction in deposition. There are presently no indications of elevated nitrate concentrations in forested headwater lakes. Base cation concentrations are still declining in many lakes, especially in south Finland, but to a lesser extent than sulphate allowing buffering capacity (alkalinity) to increase, being significant in 60% of the study lakes. Chemical recovery is resulting in biological recovery with populations of acid-sensitive fish species increasing. The recovery has been strongest in lakes in which sulphate has been the major acidifying agent, and recovery has been the strongest and most consistent in lakes in south Finland. The recovery of lakes in central Finland and north Finland is not as widespread and strong as observed in south. Many catchments, particularly in central Finland, have a high proportion of peatlands and therefore high TOC concentrations in lakes, and runoff-induced surges of organic acids have been an important confounding factor suppressing the recovery of pH and alkalinity in these lakes. Chemical recovery is progressing even in the most acidified lakes, but the buffering capacity of many lakes is still low and still sensitive to acidic input. Further reduction in sulphur emissions are needed for the alkalinity to increase in the acidified lakes. Increasing total organic carbon (TOC) concentrations are indicated in small forest lakes in Finland. The trends appear to be related to decreasing sulphate deposition and improved acid-base status of the soil, and the rise in TOC is integral to recovery from acidification. A new challenge is climate change with potential trends in temperature, precipitation and runoff, which are expected to affect future chemical and biological recovery from acidification. The potential impact on the mobilization and leaching of organic acids may become particularly important in Finnish conditions. Long-term environmental monitoring has evidently shown the success of international emission abatement strategies. The importance and value of integrated monitoring approach including physical, chemical and biological variables is clearly indicated, and continuous environmental monitoring is needed as a scientific basis for further actions in air pollution policy.