Short communication: Principal components and factor analytic models for test-day milk yield in Brazilian Holstein cattle

A total of 46,089 individual monthly test-day (TD) milk yields (10 test-days), from 7,331 complete first lactations of Holstein cattle were analyzed. A standard multivariate analysis (MV), reduced rank analyses fitting the first 2, 3, and 4 genetic principal components (PC2, PC3, PC4), and analyses that fitted a factor analytic structure considering 2, 3, and 4 factors (FAS2, FAS3, FAS4), were carried out. The models included the random animal genetic effect and fixed effects of the contemporary groups (herd-year-month of test-day), age of cow (linear and quadratic effects), and days in milk (linear effect). The residual covariance matrix was assumed to have full rank. Moreover, 2 random regression models were applied. Variance components were estimated by restricted maximum likelihood method. The heritability estimates ranged from 0.11 to 0.24. The genetic correlation estimates between TD obtained with the PC2 model were higher than those obtained with the MV model, especially on adjacent test-days at the end of lactation close to unity. The results indicate that for the data considered in this study, only 2 principal components are required to summarize the bulk of genetic variation among the 10 traits.

Characterization of a thermostable extracellular tannase produced under submerged fermentation by Aspergillus ochraceus

Background: Tannases are enzymes that may be used in different industrial sectors as, for example, food and pharmaceutical. They are obtained mainly from microorganisms, as filamentous fungi. However, the diversity of fungi stays poorly explored for tannase production. In this article, Aspergillus ochraceus is presented as a new source of tannase with interesting features for biotechnological applications. Results: Extracellular tannase production was induced when the fungus was cultured in Khanna medium with tannic acid as carbon source. The extracellular tannase was purified 9-fold with 2% recovery and a single band corresponding to 85 kDa was observed in SDS-PAGE. The native apparent molecular mass was estimated as 112 kDa. Optima of temperature and pH were 40 degrees C and 5.0, respectively. The enzyme was fully stable from 40 degrees C to 60 degrees C during 1 hr. The activity was enhanced by Mn2+ (33-39%) and NH4+ (15%). The purified tannase hydrolyzed tannic acid and methyl gallate with Km of 0.76 mM and 0.72 mM, respectively, and Vmax of 0.92 U/mg protein and 0.68 U/mg protein, respectively. The analysis of a partial sequence of the tannase encoding gene showed an open read frame of 567 bp and a sequence of 199 amino acids were predicted. TLC analysis revealed the presence of gallic acid as a tannic acid hydrolysis product. Conclusion: The extracellular tannase produced by A. ochraceus showed distinctive characteristics such as monomeric structure and activation by Mn2+, suggesting a new kind of fungal tannases with biotechnological potential. Further, it was the first time that a partial gene sequence for A. ochraceus tannase was described.

Mutation Spectrum in the Large GTPase Dynamin 2, and Genotype-Phenotype Correlation in Autosomal Dominant Centronuclear Myopathy

Centronuclear myopathy (CNM) is a genetically heterogeneous disorder associated with general skeletal muscle weakness, type I fiber predominance and atrophy, and abnormally centralized nuclei. Autosomal dominant CNM is due to mutations in the large GTPase dynamin 2 (DNM2), a mechanochemical enzyme regulating cytoskeleton and membrane trafficking in cells. To date, 40 families with CNM-related DNM2 mutations have been described, and here we report 60 additional families encompassing a broad genotypic and phenotypic spectrum. In total, 18 different mutations are reported in 100 families and our cohort harbors nine known and four new mutations, including the first splice-site mutation. Genotype-phenotype correlation hypotheses are drawn from the published and new data, and allow an efficient screening strategy for molecular diagnosis. In addition to CNM, dissimilar DNM2 mutations are associated with Charcot-Marie-Tooth (CMT) peripheral neuropathy (CMTD1B and CMT2M), suggesting a tissue-specific impact of the mutations. In this study, we discuss the possible clinical overlap of CNM and CMT, and the biological significance of the respective mutations based on the known functions of dynamin 2 and its protein structure. Defects in membrane trafficking due to DNM2 mutations potentially represent a common pathological mechanism in CNM and CMT. Hum Mutat 33: 949-959, 2012. (C) 2012 Wiley Periodicals, Inc.

Intraoral distalizer effects with conventional and skeletal Anchorage: a meta-analysis

Introduction: The aims of this meta-analysis were to quantify and to compare the amounts of distalization and anchorage loss of conventional and skeletal anchorage methods in the correction of Class II malocclusion with intraoral distalizers. Methods: The literature was searched through 5 electronic databases, and inclusion criteria were applied. Articles that presented pretreatment and posttreatment cephalometric values were preferred. Quality assessments of the studies were performed. The averages and standard deviations of molar and premolar effects were extracted from the studies to perform a meta-analysis. Results: After applying the inclusion and exclusion criteria, 40 studies were included in the systematic review. After the quality analysis, 2 articles were classified as high quality, 27 as medium quality, and 11 as low quality. For the meta-analysis, 6 studies were included, and they showed average molar distalization amounts of 3.34 mm with conventional anchorage and 5.10 mm with skeletal anchorage. The meta-analysis of premolar movement showed estimates of combined effects of 2.30 mm (mesialization) in studies with conventional anchorage and 4.01 mm (distalization) in studies with skeletal anchorage. Conclusions: There was scientific evidence that both anchorage systems are effective for distalization; however, with skeletal anchorage, there was no anchorage loss when direct anchorage was used.

Characterization and optimization of ArtinM lectin expression in Escherichia coli

Background ArtinM is a D-mannose-specific lectin from Artocarpus integrifolia seeds that induces neutrophil migration and activation, degranulation of mast cells, acceleration of wound healing, induction of interleukin-12 production by macrophages and dendritic cells, and protective T helper 1 immune response against Leishmania major, Leishmania amazonensis and Paracoccidioides brasiliensis infections. Considering the important biological properties of ArtinM and its therapeutic applicability, this study was designed to produce high-level expression of active recombinant ArtinM (rArtinM) in Escherichia coli system. Results The ArtinM coding region was inserted in pET29a(+) vector and expressed in E. coli BL21(DE3)-Codon Plus-RP. The conditions for overexpression of soluble ArtinM were optimized testing different parameters: temperatures (20, 25, 30 or 37°C) and shaking speeds (130, 200 or 220 rpm) during induction, concentrations of the induction agent IPTG (0.01-4 mM) and periods of induction (1-19 h). BL21-CodonPlus(DE3)-RP cells induced under the optimized conditions (incubation at 20°C, at a shaking speed of 130 rpm, induction with 0.4 mM IPTG for 19 h) resulted in the accumulation of large amounts of soluble rArtinM. The culture provided 22.4 mg/L of rArtinM, which activity was determined by its one-step purification through affinity chromatography on immobilized D-mannose and glycoarray analysis. Gel filtration showed that rArtinM is monomeric, contrasting with the tetrameric form of the plant native protein (jArtinM). The analysis of intact rArtinM by mass spectrometry revealed a 16,099.5 Da molecular mass, and the peptide mass fingerprint and esi-cid-ms/ms of amino acid sequences of peptides from a tryptic digest covered 41% of the total ArtinM amino acid sequence. In addition, circular dichroism and fluorescence spectroscopy of rArtinM indicated that its global fold comprises β-sheet structure. Conclusions Overall, the optimized process to express rArtinM in E. coli provided high amounts of soluble, correctly folded and active recombinant protein, compatible with large scale production of the lectin.

Algoritmos evolutivos e modelo HP para predição de estruturas de proteínas

Predição de estruturas de proteínas (PSP) é um problema computacionalmente complexo. Modelos simplificados da molécula proteica (como o Modelo HP) e o uso de Algoritmos Evolutivos (AEs) estão entre as principais técnicas investigadas para PSP. Entretanto, a avaliação de uma estrutura representada pelo Modelo HP considera apenas o número de contatos hidrofóbicos, não possibilitando distinguir entre estruturas com o mesmo número de contatos hidrofóbicos. Neste trabalho, é apresentada uma nova formulação multiobjetivo para PSP em Modelo HP. Duas métricas são avaliadas: o número de contatos hidrofóbicos e a distância entre os aminoácidos hidrofóbicos, as quais são tratados pelo AE Multiobjetivo em Tabelas (AEMT). O algoritmo mostrou-se rápido e robusto.

Modellazione multibody di veicoli ferroviari: sviluppo ed implementazione di modelli innovativi per l'analisi del contatto ruota - rotaia

The wheel - rail contact analysis plays a fundamental role in the multibody modeling of railway vehicles. A good contact model must provide an accurate description of the global contact phenomena (contact forces and torques, number and position of the contact points) and of the local contact phenomena (position and shape of the contact patch, stresses and displacements). The model has also to assure high numerical efficiency (in order to be implemented directly online within multibody models) and a good compatibility with commercial multibody software (Simpack Rail, Adams Rail). The wheel - rail contact problem has been discussed by several authors and many models can be found in the literature. The contact models can be subdivided into two different categories: the global models and the local (or differential) models. Currently, as regards the global models, the main approaches to the problem are the so - called rigid contact formulation and the semi – elastic contact description. The rigid approach considers the wheel and the rail as rigid bodies. The contact is imposed by means of constraint equations and the contact points are detected during the dynamic simulation by solving the nonlinear algebraic differential equations associated to the constrained multibody system. Indentation between the bodies is not permitted and the normal contact forces are calculated through the Lagrange multipliers. Finally the Hertz’s and the Kalker’s theories allow to evaluate the shape of the contact patch and the tangential forces respectively. Also the semi - elastic approach considers the wheel and the rail as rigid bodies. However in this case no kinematic constraints are imposed and the indentation between the bodies is permitted. The contact points are detected by means of approximated procedures (based on look - up tables and simplifying hypotheses on the problem geometry). The normal contact forces are calculated as a function of the indentation while, as in the rigid approach, the Hertz’s and the Kalker’s theories allow to evaluate the shape of the contact patch and the tangential forces. Both the described multibody approaches are computationally very efficient but their generality and accuracy turn out to be often insufficient because the physical hypotheses behind these theories are too restrictive and, in many circumstances, unverified. In order to obtain a complete description of the contact phenomena, local (or differential) contact models are needed. In other words wheel and rail have to be considered elastic bodies governed by the Navier’s equations and the contact has to be described by suitable analytical contact conditions. The contact between elastic bodies has been widely studied in literature both in the general case and in the rolling case. Many procedures based on variational inequalities, FEM techniques and convex optimization have been developed. This kind of approach assures high generality and accuracy but still needs very large computational costs and memory consumption. Due to the high computational load and memory consumption, referring to the current state of the art, the integration between multibody and differential modeling is almost absent in literature especially in the railway field. However this integration is very important because only the differential modeling allows an accurate analysis of the contact problem (in terms of contact forces and torques, position and shape of the contact patch, stresses and displacements) while the multibody modeling is the standard in the study of the railway dynamics. In this thesis some innovative wheel – rail contact models developed during the Ph. D. activity will be described. Concerning the global models, two new models belonging to the semi – elastic approach will be presented; the models satisfy the following specifics: 1) the models have to be 3D and to consider all the six relative degrees of freedom between wheel and rail 2) the models have to consider generic railway tracks and generic wheel and rail profiles 3) the models have to assure a general and accurate handling of the multiple contact without simplifying hypotheses on the problem geometry; in particular the models have to evaluate the number and the position of the contact points and, for each point, the contact forces and torques 4) the models have to be implementable directly online within the multibody models without look - up tables 5) the models have to assure computation times comparable with those of commercial multibody software (Simpack Rail, Adams Rail) and compatible with RT and HIL applications 6) the models have to be compatible with commercial multibody software (Simpack Rail, Adams Rail). The most innovative aspect of the new global contact models regards the detection of the contact points. In particular both the models aim to reduce the algebraic problem dimension by means of suitable analytical techniques. This kind of reduction allows to obtain an high numerical efficiency that makes possible the online implementation of the new procedure and the achievement of performance comparable with those of commercial multibody software. At the same time the analytical approach assures high accuracy and generality. Concerning the local (or differential) contact models, one new model satisfying the following specifics will be presented: 1) the model has to be 3D and to consider all the six relative degrees of freedom between wheel and rail 2) the model has to consider generic railway tracks and generic wheel and rail profiles 3) the model has to assure a general and accurate handling of the multiple contact without simplifying hypotheses on the problem geometry; in particular the model has to able to calculate both the global contact variables (contact forces and torques) and the local contact variables (position and shape of the contact patch, stresses and displacements) 4) the model has to be implementable directly online within the multibody models 5) the model has to assure high numerical efficiency and a reduced memory consumption in order to achieve a good integration between multibody and differential modeling (the base for the local contact models) 6) the model has to be compatible with commercial multibody software (Simpack Rail, Adams Rail). In this case the most innovative aspects of the new local contact model regard the contact modeling (by means of suitable analytical conditions) and the implementation of the numerical algorithms needed to solve the discrete problem arising from the discretization of the original continuum problem. Moreover, during the development of the local model, the achievement of a good compromise between accuracy and efficiency turned out to be very important to obtain a good integration between multibody and differential modeling. At this point the contact models has been inserted within a 3D multibody model of a railway vehicle to obtain a complete model of the wagon. The railway vehicle chosen as benchmark is the Manchester Wagon the physical and geometrical characteristics of which are easily available in the literature. The model of the whole railway vehicle (multibody model and contact model) has been implemented in the Matlab/Simulink environment. The multibody model has been implemented in SimMechanics, a Matlab toolbox specifically designed for multibody dynamics, while, as regards the contact models, the CS – functions have been used; this particular Matlab architecture allows to efficiently connect the Matlab/Simulink and the C/C++ environment. The 3D multibody model of the same vehicle (this time equipped with a standard contact model based on the semi - elastic approach) has been then implemented also in Simpack Rail, a commercial multibody software for railway vehicles widely tested and validated. Finally numerical simulations of the vehicle dynamics have been carried out on many different railway tracks with the aim of evaluating the performances of the whole model. The comparison between the results obtained by the Matlab/ Simulink model and those obtained by the Simpack Rail model has allowed an accurate and reliable validation of the new contact models. In conclusion to this brief introduction to my Ph. D. thesis, we would like to thank Trenitalia and the Regione Toscana for the support provided during all the Ph. D. activity. Moreover we would also like to thank the INTEC GmbH, the society the develops the software Simpack Rail, with which we are currently working together to develop innovative toolboxes specifically designed for the wheel rail contact analysis.

Machine learning methods for prediction of disulphide bonding states of cysteine residues in proteins

The goal of this thesis work is to develop a computational method based on machine learning techniques for predicting disulfide-bonding states of cysteine residues in proteins, which is a sub-problem of a bigger and yet unsolved problem of protein structure prediction. Improvement in the prediction of disulfide bonding states of cysteine residues will help in putting a constraint in the three dimensional (3D) space of the respective protein structure, and thus will eventually help in the prediction of 3D structure of proteins. Results of this work will have direct implications in site-directed mutational studies of proteins, proteins engineering and the problem of protein folding. We have used a combination of Artificial Neural Network (ANN) and Hidden Markov Model (HMM), the so-called Hidden Neural Network (HNN) as a machine learning technique to develop our prediction method. By using different global and local features of proteins (specifically profiles, parity of cysteine residues, average cysteine conservation, correlated mutation, sub-cellular localization, and signal peptide) as inputs and considering Eukaryotes and Prokaryotes separately we have reached to a remarkable accuracy of 94% on cysteine basis for both Eukaryotic and Prokaryotic datasets, and an accuracy of 90% and 93% on protein basis for Eukaryotic dataset and Prokaryotic dataset respectively. These accuracies are best so far ever reached by any existing prediction methods, and thus our prediction method has outperformed all the previously developed approaches and therefore is more reliable. Most interesting part of this thesis work is the differences in the prediction performances of Eukaryotes and Prokaryotes at the basic level of input coding when ‘profile’ information was given as input to our prediction method. And one of the reasons for this we discover is the difference in the amino acid composition of the local environment of bonded and free cysteine residues in Eukaryotes and Prokaryotes. Eukaryotic bonded cysteine examples have a ‘symmetric-cysteine-rich’ environment, where as Prokaryotic bonded examples lack it.

Molecular architecture of fur binding to iron-induced and - repressed genes in Helicobacter pylori

The ferric uptake regulator protein Fur regulates iron-dependent gene expression in bacteria. In the human pathogen Helicobacter pylori, Fur has been shown to regulate iron-induced and iron-repressed genes. Herein we investigate the molecular mechanisms that control this differential iron-responsive Fur regulation. Hydroxyl radical footprinting showed that Fur has different binding architectures, which characterize distinct operator typologies. On operators recognized with higher affinity by holo-Fur, the protein binds to a continuous AT-rich stretch of about 20 bp, displaying an extended protection pattern. This is indicative of protein wrapping around the DNA helix. DNA binding interference assays with the minor groove binding drug distamycin A, point out that the recognition of the holo-operators occurs through the minor groove of the DNA. By contrast, on the apo-operators, Fur binds primarily to thymine dimers within a newly identified TCATTn10TT consensus element, indicative of Fur binding to one side of the DNA, in the major groove of the double helix. Reconstitution of the TCATTn10TT motif within a holo-operator results in a feature binding swap from an holo-Fur- to an apo-Fur-recognized operator, affecting both affinity and binding architecture of Fur, and conferring apo-Fur repression features in vivo. Size exclusion chromatography indicated that Fur is a dimer in solution. However, in the presence of divalent metal ions the protein is able to multimerize. Accordingly, apo-Fur binds DNA as a dimer in gel shift assays, while in presence of iron, higher order complexes are formed. Stoichiometric Ferguson analysis indicates that these complexes correspond to one or two Fur tetramers, each bound to an operator element. Together these data suggest that the apo- and holo-Fur repression mechanisms apparently rely on two distinctive modes of operator-recognition, involving respectively the readout of a specific nucleotide consensus motif in the major groove for apo-operators, and the recognition of AT-rich stretches in the minor groove for holo-operators, whereas the iron-responsive binding affinity is controlled through metal-dependent shaping of the protein structure in order to match preferentially the major or the minor groove.

Investigating the role of single point mutations in the human proteome: a computational study

In the post genomic era with the massive production of biological data the understanding of factors affecting protein stability is one of the most important and challenging tasks for highlighting the role of mutations in relation to human maladies. The problem is at the basis of what is referred to as molecular medicine with the underlying idea that pathologies can be detailed at a molecular level. To this purpose scientific efforts focus on characterising mutations that hamper protein functions and by these affect biological processes at the basis of cell physiology. New techniques have been developed with the aim of detailing single nucleotide polymorphisms (SNPs) at large in all the human chromosomes and by this information in specific databases are exponentially increasing. Eventually mutations that can be found at the DNA level, when occurring in transcribed regions may then lead to mutated proteins and this can be a serious medical problem, largely affecting the phenotype. Bioinformatics tools are urgently needed to cope with the flood of genomic data stored in database and in order to analyse the role of SNPs at the protein level. In principle several experimental and theoretical observations are suggesting that protein stability in the solvent-protein space is responsible of the correct protein functioning. Then mutations that are found disease related during DNA analysis are often assumed to perturb protein stability as well. However so far no extensive analysis at the proteome level has investigated whether this is the case. Also computationally methods have been developed to infer whether a mutation is disease related and independently whether it affects protein stability. Therefore whether the perturbation of protein stability is related to what it is routinely referred to as a disease is still a big question mark. In this work we have tried for the first time to explore the relation among mutations at the protein level and their relevance to diseases with a large-scale computational study of the data from different databases. To this aim in the first part of the thesis for each mutation type we have derived two probabilistic indices (for 141 out of 150 possible SNPs): the perturbing index (Pp), which indicates the probability that a given mutation effects protein stability considering all the “in vitro” thermodynamic data available and the disease index (Pd), which indicates the probability of a mutation to be disease related, given all the mutations that have been clinically associated so far. We find with a robust statistics that the two indexes correlate with the exception of all the mutations that are somatic cancer related. By this each mutation of the 150 can be coded by two values that allow a direct comparison with data base information. Furthermore we also implement computational methods that starting from the protein structure is suited to predict the effect of a mutation on protein stability and find that overpasses a set of other predictors performing the same task. The predictor is based on support vector machines and takes as input protein tertiary structures. We show that the predicted data well correlate with the data from the databases. All our efforts therefore add to the SNP annotation process and more importantly found the relationship among protein stability perturbation and the human variome leading to the diseasome.

Assessing the functional structure of molecular transporters by EPR spectroscopy

In this thesis, the self-assembled functional structure of a broad range of amphiphilic molecular transporters is studied. By employing paramagnetic probe molecules and ions, continuous-wave and pulse electron paramagnetic resonance spectroscopy reveal information about the local structure of these materials from the perspective of incorporated guest molecules. First, the transport function of human serum albumin for fatty acids is in the focus. As suggested by the crystal structure, the anchor points for the fatty acids are distributed asymmetrically in the protein. In contrast to the crystallographic findings, a remarkably symmetric entry point distribution of the fatty acid binding channels is found, which may facilitate the uptake and release of the guest molecules. Further, the metal binding of 1,2,3-triazole modified star-shaped cholic acid oligomers is studied. These biomimetic molecules are able to include and transport molecules in solvents of different polarity. A pre-arrangement of the triazole groups induces a strong chelate-like binding and close contact between guest molecule and metal ion. In absence of a preordering, each triazole moiety acts as a single entity and the binding affinity for metal ions is strongly decreased. Hydrogels based on N-isopropylacrylamide phase separate from water above a certain temperature. The macroscopic thermal collapse of these hydrogels is utilized as a tool for dynamic nuclear polarization. It is shown that a radical-free hyperpolarized solution can be achieved with a spin-labeled gel as separable matrix. On the nanoscale, these hydrogels form static heterogeneities in both structure and function. Collapsed regions protect the spin probes from a chemical decay while open, water-swollen regions act as catalytic centers. Similarly, thermoresponsive dendronized polymers form structural heterogeneities, which are, however, highly dynamic. At the critical temperature, they trigger the aggregation of the polymer into mesoglobules. The dehydration of these aggregates is a molecularly controlled non-equilibrium process that is facilitated by a hydrophobic dendritic core. Further, a slow heating rate results in a kinetically entrapped non-equilibrium state due to the formation of an impermeable dense polymeric layer at the periphery of the mesoglobule.

Inserimento eterofamigliare supportato di adulti sofferenti di disturbi psichici: Valutazione degli esiti

L’Inserimento Eterofamigliare Supportato di Adulti (IESA) sofferenti di disturbi psichici consiste nell’accogliere persone in cura presso i servizi psichiatrici territoriali, nel proprio domicilio, integrandole nelle proprie relazioni famigliari. Obiettivo è migliorare la qualità di vita dell’utente e favorirne l’integrazione nella comunità. Obiettivo. Valutare gli esiti dello IESA, con un disegno di ricerca longitudinale, considerando: psicopatologia, benessere psicologico, funzionamento sociale e familiare. Metodologia. 40 soggetti: 20 pazienti e 20 ospitanti. La valutazione clinica è stata effettuata all’inizio della convivenza e al follow-up di 1, 3, 6 e 12 mesi. Strumenti utilizzati: BPRS, VGF, PWB, SQ, FAD. Analisi statistica: Modello Lineare Generale (GLM) con l’Analisi della Varianza per prove ripetute e calcolo dell’effect-size. Risultati. 15 pazienti maschi e 5 femmine, 17 italiani. 11 soddisfano i criteri diagnostici (DSM-IV-TR) per schizofrenia e disturbi psicotici, 5 per i disturbi dell’umore e 4 per i disturbi di personalità. Dopo l’inserimento 3 sono stati i ricoveri e 4 le visite psichiatriche urgenti. 8 pazienti modificano/diminuiscono la terapia e 3 la sospendono. Aumenta il benessere psicologico (PWB); diminuiscono i sintomi psicopatologici (BPRS ed SQ) e migliora il funzionamento globale (VFG). Il gruppo dei famigliari composto da 11 uomini e 9 donne, 19 di nazionalità italiana; con età media di 55 anni. 8 sono coniugati, 6 celibi/nubili, 4 divorziati e 2 vedovi. 9 hanno figli, 11 lavorano e 8 sono pensionati. Nei famigliari aumenta il benessere psicologico (PWB), migliora il funzionamento famigliare (FAD) e la valutazione del funzionamento globale (VGF) rimane costante nel tempo. Discussioni e conclusioni. Il progetto IESA sembra migliorare la psicopatologia, con una diminuzione dei comportamenti maladattativi e un aumento delle capacità relazionali dell’ospite favorendone l’integrazione. Inoltre, lo IESA sembra diminuire i costi della cronicità psichiatrica: diminuzione degli accessi al Pronto Soccorso, delle visite psichiatriche urgenti e delle giornate di ricovero.

Unmittelbare, dauerhafte sowie evolutionäre Anpassung an Fremdstoffexpositionen

Eine der Hauptursachen für unerwünschte oder reduzierte Wirkungen von Medikamenten ist die Induktion von Enzymen und Transportern des Medikamentenstoffwechsels. Diese Induktion stellt ursprünglich eine physiologische Reaktion auf die Aufnahme von potentiell schädlichen Fremdstoffen aus der Umwelt dar und sichert so die Gesundheit und Fortpflanzungsfähigkeit von Lebewesen. Beim Menschen sowie anderen Säugetieren werden Fremdstoffe hauptsächlich von den nukleären Rezeptoren PXR und CAR in der Leber und im Dünndarm detektiert. Zu den Medikamenten, welche über PXR und CAR wirken, gehören unter anderem Antikonvulsiva, Statine, antiretrovirale Medikamente, Glucocorticoide sowie Antimykotika. Die durch Fremdstoffe aktivierten Transkriptionsfaktoren PXR und CAR steigern die Menge der Enzyme und Transporter des Fremdstoffmetabolismus. Hierzu zählen vor allem die Cytochrom P450-Enzyme (Cyp-Enzyme) mit breitem Substratspektrum oder der Transporter MDR1, welcher eine Vielzahl von Substraten über Membranen transportiert. Durch die Biotransformation werden die induzierenden, lipophilen Substanzen so modifiziert, dass sie leichter über den Urin oder die Galle ausgeschieden werden können. \r\nDie Dauer der Induktion sollte auf die Zeit der Fremdstoffexposition beschränkt sein, um Störungen des endogenen Stoffwechsels zu vermindern. In dieser Arbeit werden jedoch Hinweise auf dauerhafte und sogar generationsübergreifende Effekte von Medikamenten in Mäusen geliefert. Nachkommen von Müttern, welche bereits vor ihrer Verpaarung einmalig mit TCPOBOP, einem Liganden des murinen CAR, injiziert wurden, hatten eine ungefähr 100-fach gesteigerte Genexpression von Cyp2b10. Auch gab es Expressionsänderungen von Genen, deren Produkte eine Rolle im Lipidstoffwechsel sowie bei Immunkrankheiten spielen. Eine Hochdurchsatz-RNA-Sequenzierung der injizierten Elterngeneration ergab außerdem dauerhafte Expressionsveränderungen anderer Gene des Medikamentenstoffwechsels sowie von Genen mit Verbindung zum Energiemetabolismus. \r\nBerücksichtigt man die enge evolutionäre Verwandtschaft der nukleären Rezeptoren CAR und PXR, sind Langzeitveränderungen auch für PXR möglich und wurden im Verlauf dieser Arbeit ebenfalls untersucht. Eine Hochdurchsatz-Sequenzierung ergab für Mäuse, welche mit dem PXR-Aktivator PCN induziert wurden, dass selbst noch drei Monate nach der Exposition Gene verändert exprimiert waren, welche im Zusammenhang mit Lebernekrosen stehen. Bei Nachkommen von PCN-injizierten Müttern wurden Gene unterschiedlich exprimiert, welche eine Rolle bei der Energiehomöostase sowie im Glukosestoffwechsel spielen. Im Erwachsenenalter sind bei diesen Nachkommen darüber hinaus noch Gene unterschiedlich exprimiert, deren Produkte eine Funktion in der Immunantwort haben. \r\nDa Erwachsene aufgrund ihrer Lebensdauer sowie der absoluten Krankheitshäufigkeit wesentlich öfter Kontakt mit Fremdstoffen haben, war medizinisch von besonderem Interesse, ob anhaltende Genexpressionsänderungen auch bei Erwachsenen zu beobachten sind. So konnte im Rahmen dieser Arbeit gezeigt werden, dass auch einmalig exponierte Adulttiere Gene dauerhaft verändert exprimieren und die Veränderungen im Medikamentenstoffwechsel an die nächste Generation übertrugen. \r\n\r\nBisher sind klinische Studien zur Risikobewertung von Medikamenten (Pharmakovigilanz) nicht generationsübergreifend angelegt. Diese Arbeit gibt Anstöße dafür, dass dies in Zukunft für viel mehr Medikamente notwendig werden könnte. Neben Veränderungen im Medikamentenstoffwechsel ergeben sich Nebenwirkungen von PXR- und CAR-Liganden vor allem aus ihrer Beteiligung an endogenen Stoffwechselwegen. Nach Aktivierung von CAR, welcher viele metabolische Stoffwechselwege steuert, treten beispielsweise Störungen des Energiestoffwechsels auf. Ein tieferes Verständnis der Rezeptoraktivität von CAR samt einer gezielten Modulierung seiner Aktivität würde wichtige Beiträge zum Verständnis der Regulation des Fremdstoffmetabolismus sowie der Entstehung von Nebenwirkungen durch eine Behandlung mit CAR-Liganden leisten. Dauerhafte Veränderungen endogener Stoffwechselwege könnten dann möglicherweise über eine pharmakologische Modulierung der CAR-Aktivität reduziert werden. \r\nZu diesem Zweck wurden im Verlauf dieser Arbeit die CAR-Rezeptoren der Amphibien (Xenopus tropicalis, Xenopus laevis) und Reptilien (Anolis carolinensis) erstmals kloniert, als Proteine exprimiert und charakterisiert. Vergleiche zwischen Tierarten ermöglichen ein besseres Verständnis von humanen Proteinen. Funktionelle Analysen ergaben Ähnlichkeiten des Xenopus laevis-CAR mit dem PXR der Säugetiere: eine niedrige basale Aktivität sowie eine starke Induzierbarkeit durch Liganden. In weiteren funktionellen Analysen wurden die Determinanten der basalen Aktivität des Xenopus laevis-CAR untersucht. Die basale Aktivität war nicht abhängig von der subzellulären Lokalisation, sondern ergab sich aus der Proteinstruktur, welche nur beim CAR der Landvertebraten in einer aktiven Konformation fixiert ist. Ähnlich dem PXR der Säugetiere besitzt CAR der Amphibien eine Aktivierungsdomäne, welche erst durch Ligandenbindung in eine aktive Konformation gebracht wird. Mutationen einzelner Aminosäuren zum jeweils humanen Homolog erhöhten die basale Aktivität des Xenopus laevis-CAR auf die des humanen Rezeptors. Diese Mutanten mit erhöhter basalen Aktivität zeigten eine verstärkte Interaktion mit dem Kofaktor PGC-1a, einem Regulator des Energiestoffwechsels bei Säugetieren. Die hepatischen Zielgene des CAR der Amphibien überlappen zum Teil mit den humanen Zielgenen und spielen ebenfalls eine Rolle im Energiestoffwechsel.

On Ribosome Load, Codon Bias and Protein Abundance

Different codons encoding the same amino acid are not used equally in protein-coding sequences. In bacteria, there is a bias towards codons with high translation rates. This bias is most pronounced in highly expressed proteins, but a recent study of synthetic GFP-coding sequences did not find a correlation between codon usage and GFP expression, suggesting that such correlation in natural sequences is not a simple property of translational mechanisms. Here, we investigate the effect of evolutionary forces on codon usage. The relation between codon bias and protein abundance is quantitatively analyzed based on the hypothesis that codon bias evolved to ensure the efficient usage of ribosomes, a precious commodity for fast growing cells. An explicit fitness landscape is formulated based on bacterial growth laws to relate protein abundance and ribosomal load. The model leads to a quantitative relation between codon bias and protein abundance, which accounts for a substantial part of the observed bias for E. coli. Moreover, by providing an evolutionary link, the ribosome load model resolves the apparent conflict between the observed relation of protein abundance and codon bias in natural sequences and the lack of such dependence in a synthetic gfp library. Finally, we show that the relation between codon usage and protein abundance can be used to predict protein abundance from genomic sequence data alone without adjustable parameters.

On Ribosome Load, Codon Bias and Protein Abundance

Different codons encoding the same amino acid are not used equally in protein-coding sequences. In bacteria, there is a bias towards codons with high translation rates. This bias is most pronounced in highly expressed proteins, but a recent study of synthetic GFP-coding sequences did not find a correlation between codon usage and GFP expression, suggesting that such correlation in natural sequences is not a simple property of translational mechanisms. Here, we investigate the effect of evolutionary forces on codon usage. The relation between codon bias and protein abundance is quantitatively analyzed based on the hypothesis that codon bias evolved to ensure the efficient usage of ribosomes, a precious commodity for fast growing cells. An explicit fitness landscape is formulated based on bacterial growth laws to relate protein abundance and ribosomal load. The model leads to a quantitative relation between codon bias and protein abundance, which accounts for a substantial part of the observed bias for E. coli. Moreover, by providing an evolutionary link, the ribosome load model resolves the apparent conflict between the observed relation of protein abundance and codon bias in natural sequences and the lack of such dependence in a synthetic gfp library. Finally, we show that the relation between codon usage and protein abundance can be used to predict protein abundance from genomic sequence data alone without adjustable parameters.