Saccharomyces cerevisiae é o organismo de escolha para produção de etanol combustível, apresentando-se adaptadas ao ambiente hostil das dornas de fermentação. Adaptações como floculação, formação de espuma e de biofilme são características fenotípicas indesejáveis ao processo brasileiro. Por isso, a pronta identificação destas características faz-se necessária no intuito de minimizar perdas de rendimento e diminuir o custo da produção. Sabe-se que proteínas codificadas pela família de genes FLO estão relacionadas a estes fenótipos, os quais são regulados pela proteína Flo8p, a qual possui papel fundamental na apresentação destas características fenotípicas indesejáveis. Desta forma, o presente trabalho teve como objetivo analisar o fenótipo e o comportamento metabólico, relacionando-os com a regulação via Flo8p. Os resultados obtidos revelam o papel fundamental de Flo8p na regulação positiva destes fenótipos em linhagem isolada do ambiente industrial (FT02). Verificou-se uma forte tendência da participação do gene FLO11 na formação de espuma, via Flo8p. Além disso, através da deleção do FLO8 da linhagem FT02, observou-se a influência positiva de Flo8p na floculação e hidrofobicidade celular, filamentação e poder invasivo. / Saccharomyces cerevisiae is the chosen organism for fuel ethanol production, presenting adapted to the hostile environment of the fermentation vats. Adaptations like flocculation, d foam formation and biofilm are undesirable phenotypes for the Brazilian process. Hence, the early identification of these characteristics is necessary to minimize yield losses and lower the production cost. Proteins codified by FLO gene family are related with these phenotypes, which are positively regulated by Flo8p protein, showing fundamental role in the expression of the undesirable phenotypes. So, the present work aimed to analyze the phenotypes and the metabolic behavior of an industrial strain isolated directly from Brazilian ethanol production process (FT02), relating them with the Flo8p regulation. Our results showed that the Flo8p plays a fundamental role in the regulation of these characteristics in the industrial strain FT02. We also verified a strong tendency of the FLO11 gene participation in the foam formation, by Flo8p. Moreover, by FLO8 deletion in FT02 strain, we could identify the positive influences of the Flo8p in flocculation and cellular hydrophobicity, filamentation and invasive growth.

A família Baculoviridae é um grande grupo de vírus com cerca de 700 espécies de insetos hospedeiros, com dois fenótipos: o ODV (occlusion derived virion), que faz a infecção primária do intestino médio; e o BV (budded virus), responsável pela infecção sistêmica. No Brasil, o nucleopoliedrovírus Anticarsia gemmatalis (AgMNPV) é utilizado como controle biológico da lagarta-da-soja Anticarsia gemmatalis. O genoma do AgMNPV-2D contém 152 ORFs, 26 das quais codificam proteínas estruturais. Entre elas, a glicoproteína GP64 é fundamental para infecção secundária. Este estudo visa identificar proteínas estruturais do AgMNPV-2D por duas abordagens de espectrometria de massas. Também comparar a variabilidade da gp64 de isolados geográficos por sequenciamento por Sanger e de alta cobertura. Assim, identificamos as substituições de gp64 e vimos que ela não suporta a separação geográfica dos isolados. Também identificamos 44 e 33 proteínas em ODV e BV, respectivamente. Seis novas proteínas foram identificadas no ODV e sete delas no BV. Além disso, 11 proteínas celulares foram identificadas no AgMNPV-2D, possivelmente necessárias para infecção. Este achado contribui para o entendimento da morfogênese do AgMNPV e fatores associados à multiplicação viral. / Baculoviridae are arthropod-specific viruses with more than 700 host insects, which produce two phenotypes: the budded virus (BV) and, the occlusion-derived virus (ODV) for intra and across host spread, respectively. Brazil uses the Anticarsia gemmatalis multiple nucleopolyhedrovirus (AgMNPV) as a biological control agent of the velvet bean caterpillar (A. gemmatalis). The genome of the AgMNPV-2D carries 152 ORFs, 26 of which code for structural proteins. Herein, the structural proteins of AgMNPV-2D were analyzed by two mass spectrometry techniques. The additional objective was to compare the gene gp64. of different geographical populations by Sanger and next generation sequencing. This analysis allowed us to observe the substitutions of gp64 and refuted the notion of a geographical isolation of the samples. We also observed a total of 44 proteins of the ODV and 33 of the BV. Six new proteins were found in the ODV and seven in the BV. Furthermore, 11 cellular proteins were also identified, which are possibly assorted during viral morphogenesis. These findings may provide novel insights into AgMNPV biology and its host interaction, leading us to a better understanding about morphogenesis and also the associated factors of the viral multiplication.

Research involved in modeling human lung disease conditions has provided insight into disease development, progression, and treatment. In particular, mouse models of human pulmonary disease are increasingly utilized to characterize lung disease conditions. With advancements in small animal imaging it is now possible to investigate the phenotypic differences expressed in inbred mouse strains in vivo to investigate specific disease conditions that affect the lung. In this thesis our aim was to generate a comprehensive characterization of the normative mouse lung phenotypes in three of the most utilized strains of mice, C57BL/6, A/J, and BALB/c, through imaging techniques. The imaging techniques that we utilized in this research included micro-CT, a custom Large Image Microscope Array (LIMA) system for 3D microscopy, and classical histology. Micro-CT provided a non-destructive technique for acquiring in vivo and fixed lung images. The LIMA 3D microscopy system was utilized for direct correspondence of the gold standard histology images as well as to validate the anatomical structures and measurements that were extracted from the micro-CT images. Finally, complete lung histology slices were utilized for assessment of the peripheral airspace structures that were not resolvable using the micro-CT imaging system. Through our developed imaging acquisition and processing strategies we have been able to successful characterize important phenotypes in the mouse lung that have not previously been known as well as identify strain variations. These findings will provide the scientific community with valuable information to be better equipped and capable of pursuing new avenues of research in investigating pulmonary disease conditions that can be modeled in the mouse.

Genome-wide association studies (GWAS) are a tool of high importance to associate genetic markers, genes and genomic regions with complex phenotypes and diseases, allowing to understand in details this regulation of gene expression as well as the genes, and then develop new techniques of diagnoses and treatment of diseases. Nowadays, the main genetic marker used in GWAS is the SNP (single nucleotide polymorphism), a variation that affects only one base of the DNA, being the most common type of variation between individuals and inside the genome. Even though there are multiple techniques available for GWAS, several complex traits still have unexplained heritability. To contribute to these studies, reference genetic maps are being created, such as the HapMap and 1000 Genomes, which have common genetic variants from world wide population (including European, Asian and African populations). In the last years, two solutions adopted to solve the missing heritability are to use different types of genetic variants and include the rare and population specific markers. Copy number variation (CNV) is a structural variant which use is increasing in GWAS in the last years. This variant is characterized for the deletion or duplication of a region a DNA and its length can be from few bases pair to the whole chromosome, as in Down syndrome. In collaboration of the Heart Institute (InCor-FMUSP), this work uses the dataset from Baependi Heart Study to establish a methodology to characterized the CNVs in the Brazilian population using SNP array data and associate them with height. This project uses the genetic and phenotype data of 1,120 related samples (family structure). For CNV calling, resources from the software PennCNV are used and methodologies of preprocessing, normalization, identification and other analysis are reviewed. The characterization of CNVs include information about location, size, frequency in our population and the patterns of inheritance in trios. The association of CNVs and height is made using linear mixed models and with information of family structure. The obtained results indicate that the Brazilian population has regions with variation in the number of copies that are not in the literature. General characteristics, such as length and frequency in samples, are similar to the information found in the literature. In addition, it was observed that the transmission of CNVs could not follow the Mendelian laws, since the frequency of trios which one parent has a deletion/duplication and the offspring is normal is higher than the frequency of trios with one parent and the offspring has a deletion/duplication. This work also identified a region on chromosome 9 that could be associated to height, being that carries of a duplication in this region can have the expected height dropped by approximately 3cm. / Estudos de associação genética (do inglês, Genome-wide association studies - GWAS) são uma ferramenta fundamental para associar marcadores genéticos, genes e regiões genômicas com doenças e fenótipos complexos, permitindo compreender em mais detalhes essa rede de regulação bem como mapear genes e, com isso, desenvolver técnicas de diagnóstico e tratamento. Atualmente, a principal variante genética utilizada nos estudos de associação é o SNP (do inglês, Single Nucleotide Polymorphism), uma variação que afeta apenas uma base do DNA, sendo o tipo de variação mais comum tanto entre os indivíduos como dentro do genoma. Apesar das diferentes técnicas disponíveis para os estudos de associação, muitas doenças e traços complexos ainda possuem parte de sua herdabilidade inexplicada. Para contribuir com estes estudos, foram criados banco de dados genéticos de referência, como o HapMap e o 1000 Genomes, que possuem representantes das variantes genéticas comuns das populações mundiais (européias, asiáticas e africanas). Nos últimos anos, duas das solucões adotadas para tentar explicar a herdabilidade de doenças e fenótipos complexos correspondem a utilizar diferentes tipos de variantes genéticas e incluir variantes raras e específicas para uma determinada população. O CNV (do inglês, Copy Number Variation) é uma variante estrutural que está ganhando espaço nos estudos de associação nos últimos anos. Essa variante é caracterizada pela deleção ou duplicação de uma região do DNA que pode ser de apenas alguns pares de bases até cromossomos inteiros, como no caso da síndrome de Down. Em parceria com o Instituto do Coração (InCor-FMUSP), este trabalho utiliza os dados do projeto Corações de Baependi para estabelecer uma metodologia para caracterizar os CNVs na população brasileira a partir de dados de SNPs e associá-los com a altura. O projeto inclui dados genéticos e fenótipos de 1,120 indivíduos relacionados (estruturados em famílias). Para a detecção dos CNVs, os recursos do software PennCNV são utilizados e metodologias de processamento, normalização, identificação e análises envolvidas são revisadas. A caracterização dos CNVs obtidos inclui informações de localização, tamanho e frequência na população e padrões de herança genética em trios. A associação dos CNVs com a altura é realizada a partir de modelos lineares mistos e utilizando informações sobre a estrutura de família. Os resultados obtidos indicaram que a população brasileira contém regiões (únicas) com variação no número de cópias que não estão identificadas na literatura. Características gerais dos CNVs, como tamanho e frequência no indivíduo, foram semelhantes ao que é apontado na literatura. Também foi observado que a transmissão de CNV pode não seguir as leis mendelianas, uma vez que a frequência de trios com um dos pais com deleção/duplicação e filho normal era superior à frequência dos trios com filho portador da mesma variação.

L’athérosclérose est une maladie inflammatoire chronique de la paroi vasculaire à évolution lente et silencieuse dont les principaux facteurs de risque sont les dyslipidémies, l’obésité, le diabète et le tabagisme. Les macrophages jouent un rôle crucial dans le développement et la progression de cette maladie. Ils sont issus de la différentiation des monocytes et ils ne constituent pas une population homogène. On peut reconnaître au moins deux sous-populations: les macrophages pro-inflammatoire M1 et les macrophages alternatifs ou M2 qui montrent des propriétés anti-inflammatoires. Les fonctions des macrophages sont régulées par des facteurs de transcription. Mon laboratoire d’accueil a réalisé une analyse transcriptomique sur les facteurs de transcription régulés dans les macrophages alternatifs et parmi les plus induits dans les M2 il y a NOR1 (Neuron-derived Orphan Receptor 1) et TLE1 (Transducin Like Enhancer of Split 1). Pour cette raison nous les avons choisis pour en étudier le rôle dans les macrophages alternatifs humains. Etude de l’expression et rôle de NOR1 dans les macrophages alternatifsNOR1 fait partie de la famille NR4A3 ensemble à deux autres membres, Nurr1 et Nur77 : les trois sont exprimés dans les macrophages au sein de la lésion d’athérosclérose humaine. Cependant l’expression et le rôle de NOR1 dans les macrophages alternatifs n’a pas encore été étudié. En utilisant le model en vitro des macrophages primaires alternatifs humains polarisée en présence de l’IL-4, nous avons démontré que l’expression de NOR1 est induite dans les macrophages M2 chez l’homme, tandis que cette régulation n’est pas vérifiée chez la souris. D’ailleurs l’expression de NOR1 est plus importante dans les zones de la lésion atherosclerotique humaine enrichies par les macrophages CD68+MR+ . En utilisant l’approche de diminution de l’expression de NOR1 par un siRNA spécifique, nous démontrons que l’expression de certaines marqueurs de la polarisation alternative tels que Mannose Receptor (MR), Interleukin-1 receptor antagonist (IL1Ra), CD200 receptor (CD200R), coagulation factor XIII A1 polypeptide (F13A1), interleukin 10 (IL10) and the Peroxisome Proliferator-Activated Receptor (PPARg) sont diminués. De plus, l’expression et l’activité de la matrix metallopeptidase 9 (MMP9) sont induites suite au silencing de NOR1, cette régulation est confirmé par l’approche de surexpression de NOR1 par infection adenovirale. Ces données identifient NOR1 parmi les facteurs de transcription induits dans les macrophages alternatifs humains et permettent de mettre en évidence comme NOR1 soit capable de modifier le phénotype alternatif des macrophages.Etude de l’expression et fonctions potentielles de TLE1 dans les macrophages alternatifsTLE1, appartenant à la grande famille appelée chez la Drosophile avec le nome de Groucho, est connu pour être un répresseur incapable de se fixer directement à l’ADN et que par conséquence agit par interaction avec des autres facteurs de transcription. Aucune donnée n’est disponible quant à l’expression ou aux fonctions de TLE1 dans les macrophages. Nos résultats montrent que TLE1 est parmi les facteurs de transcription les plus exprimés dans les macrophages alternatifs humains. Cette régulation est aussi observée dans les macrophages de souris. Nous avons aussi montré que TLE1 est fortement exprimé dans les zones enrichies en macrophages M2 au sein de la plaque athérosclérotique humaine ainsi que dans les macrophages à phénotype mixte qui infiltrent le tissu adipeux (ATM). Nous avons caractérisé l’expression génique de TLE1 dans les patients obèses avec ou sans diabète et nous montrons que l’expression de TLE1 varie selon le statut métabolique du donneur. / Atherosclerosis is an inflammatory disease in which macrophages play a crucial role. Macrophages are derived from the differentiation of circulating monocytes and they are not an homogenous population. We can distinguish at least two types of macrophages: The pro-inflammatory M1 macrophages and the alternative anti-inflammatory macrophages M2. Functions of macrophages are controlled by transcriptional factors. My laboratory has realised a transcriptomic analysis of transcriptional factors differently regulated among RM and M2 macrophages. Among the most regulated transcriptional factors there is NOR1 (Neuron-derived Orphan Receptor 1) and TLE1 (Transducin Like Enhancer of Split 1). According to these data, we have chose these two transcriptional factors in order to determine their role in human alternative macrophages. The neuron-derived orphan receptor 1 (NOR1) is induced upon human alternative macrophage polarization and stimulates the expression of markers of the M2 phenotypeThe neuron-derived orphan receptor 1 (NOR1), together with Nur77 and Nurr1, is a member of the NR4A orphan nuclear receptor family expressed in human atherosclerotic lesion macrophages. However, the expression and the functions of NOR1 in human alternative macrophages have not been studied yet. Using an in vitro model of IL-4 polarized primary human alternative macrophages we demonstrate that NOR1 expression increased in alternative M2 macrophages in humans but not in mice. Moreover NOR1 expression is also most abundant in CD68+MR+ alternative macrophage-enriched areas of human atherosclerotic plaques in vivo. Silencing NOR1 expression in human alternative macrophages decreases the expression of a panel of M2 markers such as the Mannose Receptor (MR), Interleukin-1 receptor antagonist (IL1Ra), CD200 receptor (CD200R), coagulation factor XIII A1 polypeptide (F13A1), interleukin 10 (IL10) and the Peroxisome Proliferator-Activated Receptor (PPARg). Moreover, expression and enzymatic activity of MMP9 are induced by NOR1 silencing in M2 macrophages, a regulation confirmed in NOR1 gain of function experiments. These data identify NOR1 among the transcription factors induced during alternative differentiation of human macrophages and demonstrate that NOR1 modifies the alternative macrophage phenotype. Study of TLE1 expression and potential functions in human alternative macrophagesTLE1 is a member of the Groucho family and it is mainly described as a transciptional co-repressor. Although lacking in DNA binding activity of their own, this protein is recruited to gene promoters through interaction with other factors. No data are available regarding the expression or role of TLE1 in macrophages. Our results show that TLE1 is among the highest expressed transcriptional factors in human alternative macrophages. This regulation is verified also in murine macrophages. Histological analysis showed that TLE1 expression in human carotid atherosclerotic lesions in vivo co-localizes with the macrophage marker CD68 and the alternative maker MR. Q-PCR analysis of macrophage-enriched areas isolated by LCM showed that the mRNA levels of TLE1 are higher in zones of alternative CD68+MR+ macrophages compared to zones enriched in CD68+MR- macrophages. Moreover we have shown that TLE1 expression is higher in adipose tissue macrophages (ATM) compared to resting macrophages isolated from blood of the same patients. Finally we have characterised the mRNA expression of TLE1 in obese patients affected or not by diabetes and we have shown that TLE1 expression is influenced by the metabolic state of the patients.

In this thesis several important proteins are investigated from a structural perspective. Some of the proteins are disease related while other have important but not completely characterised functions. The techniques used are general as demonstrated by applications on metabolic proteins (CYP21, CYP11B1, IAPP, ADH3), regulatory proteins (p53, GDNF) and a transporter protein (ANTR1). When the protein CYP21 (steroid 21-hydroxylase) is deficient it causes CAH (congenital adrenal hyperplasia). For this protein, there are about 60 known mutations with characterised clinical phenotypes. Using manual structural analysis we managed to explain the severity of all but one of the mutations. By observing the properties of these mutations we could perform good predictions on, at the time, not classified mutations. For the cancer suppressor protein p53, there are over thousand mutations with known activity. To be able to analyse such a large number of mutations we developed an automated method for evaluation of the mutation effect called PREDMUT. In this method we include twelve different prediction parameters including two energy parameters calculated using an energy minimization procedure. The method manages to differentiate severe mutations from non-severe mutations with 77% accuracy on all possible single base substitutions and with 88% on mutations found in breast cancer patients. The automated prediction was further applied to CYP11B1 (steroid 11-beta-hydroxylase), which in a similar way as CYP21 causes CAH when deficient. A generalized method applicable to any kind of globular protein was developed. The method was subsequently evaluated on nine additional proteins for which mutants were known with annotated disease phenotypes. This prediction achieved 84% accuracy on CYP11B1 and 81% accuracy in total on the evaluation proteins while leaving 8% as unclassified. By increasing the number of unclassified mutations the accuracy of the remaining mutations could be increased on the evaluation proteins and substantially increase the classification quality as measured by the Matthews correlation coefficient. Servers with predictions for all possible single based substitutions are provided for p53, CYP21 and CYP11B1. The amyloid formation of IAPP (islet amyloid polypeptide) is strongly connected to diabetes and has been studied using both molecular dynamics and Monte Carlo energy minimization. The effects of mutations on the amount and speed of amyloid formation were investigated using three approaches. Applying a consensus of the three methods on a number of interesting mutations, 94% of the mutations could be correctly classified as amyloid forming or not, evaluated with in vitro measurements. In the brain there are many proteins whose functions and interactions are largely unknown. GDNF (glial cell line-derived neurotrophic factor) and NCAM (neural cell adhesion molecule) are two such neuron connected proteins that are known to interact. The form of interaction was studied using protein--protein docking where a docking interface was found mediated by four oppositely charged residues in respective protein. This interface was subsequently confirmed by mutagenesis experiments. The NCAM dimer interface upon binding to the GDNF dimer was also mapped as well as an additional interacting protein, GFRα1, which was successfully added to the protein complex without any clashes. A large and well studied protein family is the alcohol dehydrogenase family, ADH. A class of this family is ADH3 (alcohol dehydrogenase class III) that has several known substrates and inhibitors. By using virtual screening we tried to characterize new ligands. As some ligands were already known we could incorporate this knowledge when the compound docking simulations were scored and thereby find two new substrates and two new inhibitors which were subsequently successfully tested in vitro. ANTR1 (anion transporter 1) is a membrane bound transporter important in the photosynthesis in plants. To be able to study the amino acid residues involved in inorganic phosphate transportation a homology model of the protein was created. Important residues were then mapped onto the structure using conservation analysis and we were in this way able to propose roles of amino acid residues involved in the transportation of inorganic phosphate. Key residues were subsequently mutated in vitro and a transportation process could be postulated. To conclude, we have used several molecular modelling techniques to find functional clues, interaction sites and new ligands. Furthermore, we have investigated the effect of muations on the function and structure of a multitude of disease related proteins.

Technological advances in the recent decades have enabled cancer researchers to probe the disease at multiple resolutions. This wealth of experimental data combined with computational systems biology methods is now leading to predictive models of cancer progression and response to therapy. We begin by presenting our research group’s multis-cale in silico framework for modeling cancer, whose core is a tissue-scale computational model capable of tracking the progression of tumors from a diffusion-limited avascular phase through angiogenesis, and into invasive lesions with realistic, complex morphologies. We adapt this core model to consider the delivery of systemically-administered anticancer agents and their effect on lesions once they reach their intended nuclear target. We calibrate the model parameters using in vitro data from the literature, and demonstrate through simulation that transport limitations affecting drug and oxygen distributions play a significant role in hampering the efficacy of chemotherapy; a result that has since been validated by in vitro experimentation. While this study demonstrates the capability of our adapted core model to predict distributions (e.g., cell density, pressure, oxygen, nutrient, drug) within lesions and consequent tumor morphology, nevertheless, the underlying factors driving tumor-scale behavior occur at finer scales. What is needed in our multi-scale approach is to parallel reality, where molecular signaling models predict cellular behavior, and ultimately drive what is seen at the tumor level. Models of signaling pathways linked to cell models are already beginning to surface in the literature. We next transition our research to the molecular level, where we employ data mining and bioinformatics methods to infer signaling relationships underlying a subset of breast cancer that might benefit from targeted therapy of Androgen Receptor and associated pathways. Defining the architecture of signaling pathways is a critical first step towards development of pathways models underlying tumor models, while also providing valuable insight for drug discovery. Finally, we develop an agent-based, cell-scale model focused on predicting motility in response to chemical signals in the microenvironment, generally accepted to be a necessary feature of cancer invasion and metastasis. This research demonstrates the use of signaling models to predict emergent cell behavior, such as motility. The research studies presented in this dissertation are critical steps towards developing a predictive, in silico computational model for cancer progression and response to therapy. Our Laboratory for Computational & Predictive Oncology, in collaboration with research groups throughout in the United States and Europe are following a computational systems biology paradigm where model development is fueled by biological knowledge, and model predictions are refining experimental focus. The ultimate objective is a virtual cancer simulator capable of accurately simulating cancer progression and response to therapy on a patient-specific basis. / text

Survival in the face of unpredictable environments is a challenge faced by all organisms. One solution is the evolution of mechanisms that cause stochastic switching between phenotypic states. Despite the wide range of switching strategies found in nature, their evolutionary origins and adaptive significance remain poorly understood. Recently in the Rainey laboratory, a long-term evolution experiment performed with populations of the bacterium Pseudomonas fluorescens SBW25 saw the de novo evolution of a phenotypic switching strategy. This provided an unprecedented opportunity to gain insight into the evolution and maintenance of switching strategies. The derived ‘switcher’ genotype was detected through colony level phenotypic dimorphism. Further microscopic examination revealed the cellular basis of phenotypic switching as the bistable (ON/OFF) expression of a capsule. Transposon mutagenesis demonstrated that the structural basis of the capsule was a colanic acid-like polymer encoded by the Pflu3656-wzb locus. Subsequently, whole genome re-sequencing enabled elucidation of the series of mutational events underlying the evolution of capsule bistability: nine mutations were identified in the switcher. Present in both forms of the switcher, the final mutation – a point mutation in a central metabolic pathway – was shown to be the sole mechanistic cause of capsule switching; it ‘set the stage’ for a series of molecular events directly responsible for bistability. Two models were proposed to explain capsule switching at the molecular level: the genetic amplification-reduction model, and the epigenetic feedback model. Collective results of biochemical and genetic assays proved consistent with the epigenetic model, whereby a decrease in flux through the pyrimidine biosynthetic pathway activates an already-present feedback loop. Subsequent analysis of a second switcher (evolved independently of and in parallel with the first) revealed a radically different genetic route leading to phenotypically and mechanistically similar capsule switching. In addition to providing the first empirical insight into the evolutionary bases of switching strategies, the work presented in this thesis demonstrates the power of natural selection – operating on even the simplest of organisms – to forge adaptive solutions to evolutionary challenges; in a single evolutionary step, selection took advantage of inherent intracellular stochasticity to generate an extraordinarily flexible phenotype.

Diss. (sammanfattning) Uppsala : Sveriges lantbruksuniv., 2004. / Härtill 4 uppsatser.

Diss. (sammanfattning) Uppsala : Sveriges lantbruksuniversitet, 2006. / Härtill 4 uppsatser.