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.

Computational Methods for Detecting Large-Scale Chromosome Rearrangements in SNP Data

Large-scale chromosome rearrangements such as copy number variants (CNVs) and inversions encompass a considerable proportion of the genetic variation between human individuals. In a number of cases, they have been closely linked with various inheritable diseases. Single-nucleotide polymorphisms (SNPs) are another large part of the genetic variance between individuals. They are also typically abundant and their measuring is straightforward and cheap. This thesis presents computational means of using SNPs to detect the presence of inversions and deletions, a particular variety of CNVs. Technically, the inversion-detection algorithm detects the suppressed recombination rate between inverted and non-inverted haplotype populations whereas the deletion-detection algorithm uses the EM-algorithm to estimate the haplotype frequencies of a window with and without a deletion haplotype. As a contribution to population biology, a coalescent simulator for simulating inversion polymorphisms has been developed. Coalescent simulation is a backward-in-time method of modelling population ancestry. Technically, the simulator also models multiple crossovers by using the Counting model as the chiasma interference model. Finally, this thesis includes an experimental section. The aforementioned methods were tested on synthetic data to evaluate their power and specificity. They were also applied to the HapMap Phase II and Phase III data sets, yielding a number of candidates for previously unknown inversions, deletions and also correctly detecting known such rearrangements.

Computational Methods for Locating and Analyzing Conserved Gene Regulatory DNA Elements

This thesis presents methods for locating and analyzing cis-regulatory DNA elements involved with the regulation of gene expression in multicellular organisms. The regulation of gene expression is carried out by the combined effort of several transcription factor proteins collectively binding the DNA on the cis-regulatory elements. Only sparse knowledge of the 'genetic code' of these elements exists today. An automatic tool for discovery of putative cis-regulatory elements could help their experimental analysis, which would result in a more detailed view of the cis-regulatory element structure and function. We have developed a computational model for the evolutionary conservation of cis-regulatory elements. The elements are modeled as evolutionarily conserved clusters of sequence-specific transcription factor binding sites. We give an efficient dynamic programming algorithm that locates the putative cis-regulatory elements and scores them according to the conservation model. A notable proportion of the high-scoring DNA sequences show transcriptional enhancer activity in transgenic mouse embryos. The conservation model includes four parameters whose optimal values are estimated with simulated annealing. With good parameter values the model discriminates well between the DNA sequences with evolutionarily conserved cis-regulatory elements and the DNA sequences that have evolved neutrally. In further inquiry, the set of highest scoring putative cis-regulatory elements were found to be sensitive to small variations in the parameter values. The statistical significance of the putative cis-regulatory elements is estimated with the Two Component Extreme Value Distribution. The p-values grade the conservation of the cis-regulatory elements above the neutral expectation. The parameter values for the distribution are estimated by simulating the neutral DNA evolution. The conservation of the transcription factor binding sites can be used in the upstream analysis of regulatory interactions. This approach may provide mechanistic insight to the transcription level data from, e.g., microarray experiments. Here we give a method to predict shared transcriptional regulators for a set of co-expressed genes. The EEL (Enhancer Element Locator) software implements the method for locating putative cis-regulatory elements. The software facilitates both interactive use and distributed batch processing. We have used it to analyze the non-coding regions around all human genes with respect to the orthologous regions in various other species including mouse. The data from these genome-wide analyzes is stored in a relational database which is used in the publicly available web services for upstream analysis and visualization of the putative cis-regulatory elements in the human genome.

Computational Methods for Studies of Quantum Dots and Boson Condensates

This thesis presents ab initio studies of two kinds of physical systems, quantum dots and bosons, using two program packages of which the bosonic one has mainly been developed by the author. The implemented models, \emph{i.e.}, configuration interaction (CI) and coupled cluster (CC) take the correlated motion of the particles into account, and provide a hierarchy of computational schemes, on top of which the exact solution, within the limit of the single-particle basis set, is obtained. The theory underlying the models is presented in some detail, in order to provide insight into the approximations made and the circumstances under which they hold. Some of the computational methods are also highlighted. In the final sections the results are summarized. The CI and CC calculations on multiexciton complexes in self-assembled semiconductor quantum dots are presented and compared, along with radiative and non-radiative transition rates. Full CI calculations on quantum rings and double quantum rings are also presented. In the latter case, experimental and theoretical results from the literature are re-examined and an alternative explanation for the reported photoluminescence spectra is found. The boson program is first applied on a fictitious model system consisting of bosonic electrons in a central Coulomb field for which CI at the singles and doubles level is found to account for almost all of the correlation energy. Finally, the boson program is employed to study Bose-Einstein condensates confined in different anisotropic trap potentials. The effects of the anisotropy on the relative correlation energy is examined, as well as the effect of varying the interaction potential.}

A computational study of Compton profiles of water - methanol solutions

The molecular level structure of mixtures of water and alcohols is very complicated and has been under intense research in the recent past. Both experimental and computational methods have been used in the studies. One method for studying the intra- and intermolecular bindings in the mixtures is the use of the so called difference Compton profiles, which are a way to obtain information about changes in the electron wave functions. In the process of Compton scattering a photon scatters inelastically from an electron. The Compton profile that is obtained from the electron wave functions is directly proportional to the probability of photon scattering at a given energy to a given solid angle. In this work we develop a method to compute Compton profiles numerically for mixtures of liquids. In order to obtain the electronic wave functions necessary to calculate the Compton profiles we need some statistical information about atomic coordinates. Acquiring this using ab-initio molecular dynamics is beyond our computational capabilities and therefore we use classical molecular dynamics to model the movement of atoms in the mixture. We discuss the validity of the chosen method in view of the results obtained from the simulations. There are some difficulties in using classical molecular dynamics for the quantum mechanical calculations, but these can possibly be overcome by parameter tuning. According to the calculations clear differences can be seen in the Compton profiles of different mixtures. This prediction needs to be tested in experiments in order to find out whether the approximations made are valid.

Scattering and Refraction as Contrast Mechanisms in X-Ray Imaging

Differentiation of various types of soft tissues is of high importance in medical imaging, because changes in soft tissue structure are often associated with pathologies, such as cancer. However, the densities of different soft tissues may be very similar, making it difficult to distinguish them in absorption images. This is especially true when the consideration of patient dose limits the available signal-to-noise ratio. Refraction is more sensitive than absorption to changes in the density, and small angle x-ray scattering on the other hand contains information about the macromolecular structure of the tissues. Both of these can be used as potential sources of contrast when soft tissues are imaged, but little is known about the visibility of the signals in realistic imaging situations. In this work the visibility of small-angle scattering and refraction in the context of medical imaging has been studied using computational methods. The work focuses on the study of analyzer based imaging, where the information about the sample is recorded in the rocking curve of the analyzer crystal. Computational phantoms based on simple geometrical shapes with differing material properties are used. The objects have realistic dimensions and attenuation properties that could be encountered in real imaging situations. The scattering properties mimic various features of measured small-angle scattering curves. Ray-tracing methods are used to calculate the refraction and attenuation of the beam, and a scattering halo is accumulated, including the effect of multiple scattering. The changes in the shape of the rocking curve are analyzed with different methods, including diffraction enhanced imaging (DEI), extended DEI (E-DEI) and multiple image radiography (MIR). A wide angle DEI, called W-DEI, is introduced and its performance is compared with that of the established methods. The results indicate that the differences in scattered intensities from healthy and malignant breast tissues are distinguishable to some extent with reasonable dose. Especially the fraction of total scattering has large enough differences that it can serve as a useful source of contrast. The peaks related to the macromolecular structure come to angles that are rather large, and have intensities that are only a small fraction of the total scattered intensity. It is found that such peaks seem to have only limited usefulness in medical imaging. It is also found that W-DEI performs rather well when most of the intensity remains in the direct beam, indicating that dark field imaging methods may produce the best results when scattering is weak. Altogether, it is found that the analysis of scattered intensity is a viable option even in medical imaging where the patient dose is the limiting factor.

Methods and tools for mass spectrometric lipidome analysis

The analysis of lipid compositions from biological samples has become increasingly important. Lipids have a role in cardiovascular disease, metabolic syndrome and diabetes. They also participate in cellular processes such as signalling, inflammatory response, aging and apoptosis. Also, the mechanisms of regulation of cell membrane lipid compositions are poorly understood, partially because a lack of good analytical methods. Mass spectrometry has opened up new possibilities for lipid analysis due to its high resolving power, sensitivity and the possibility to do structural identification by fragment analysis. The introduction of Electrospray ionization (ESI) and the advances in instrumentation revolutionized the analysis of lipid compositions. ESI is a soft ionization method, i.e. it avoids unwanted fragmentation the lipids. Mass spectrometric analysis of lipid compositions is complicated by incomplete separation of the signals, the differences in the instrument response of different lipids and the large amount of data generated by the measurements. These factors necessitate the use of computer software for the analysis of the data. The topic of the thesis is the development of methods for mass spectrometric analysis of lipids. The work includes both computational and experimental aspects of lipid analysis. The first article explores the practical aspects of quantitative mass spectrometric analysis of complex lipid samples and describes how the properties of phospholipids and their concentration affect the response of the mass spectrometer. The second article describes a new algorithm for computing the theoretical mass spectrometric peak distribution, given the elemental isotope composition and the molecular formula of a compound. The third article introduces programs aimed specifically for the analysis of complex lipid samples and discusses different computational methods for separating the overlapping mass spectrometric peaks of closely related lipids. The fourth article applies the methods developed by simultaneously measuring the progress curve of enzymatic hydrolysis for a large number of phospholipids, which are used to determine the substrate specificity of various A-type phospholipases. The data provides evidence that the substrate efflux from bilayer is the key determining factor for the rate of hydrolysis.

New computational approaches for inelastic x-ray scattering

Inelastic x-ray scattering spectroscopy is a versatile experimental technique for probing the electronic structure of materials. It provides a wealth of information on the sample's atomic-scale structure, but extracting this information from the experimental data can be challenging because there is no direct relation between the structure and the measured spectrum. Theoretical calculations can bridge this gap by explaining the structural origins of the spectral features. Reliable methods for modeling inelastic x-ray scattering require accurate electronic structure calculations. This work presents the development and implementation of new schemes for modeling the inelastic scattering of x-rays from non-periodic systems. The methods are based on density functional theory and are applicable for a wide variety of molecular materials. Applications are presented in this work for amorphous silicon monoxide and several gas phase systems. Valuable new information on their structure and properties could be extracted with the combination of experimental and computational methods.

Language change as an evolutionary process

In the thesis it is discussed in what ways concepts and methodology developed in evolutionary biology can be applied to the explanation and research of language change. The parallel nature of the mechanisms of biological evolution and language change is explored along with the history of the exchange of ideas between these two disciplines. Against this background computational methods developed in evolutionary biology are taken into consideration in terms of their applicability to the study of historical relationships between languages. Different phylogenetic methods are explained in common terminology, avoiding the technical language of statistics. The thesis is on one hand a synthesis of earlier scientific discussion, and on the other an attempt to map out the problems of earlier approaches in addition to finding new guidelines in the study of language change on their basis. Primarily literature about the connections between evolutionary biology and language change, along with research articles describing applications of phylogenetic methods into language change have been used as source material. The thesis starts out by describing the initial development of the disciplines of evolutionary biology and historical linguistics, a process which right from the beginning can be seen to have involved an exchange of ideas concerning the mechanisms of language change and biological evolution. The historical discussion lays the foundation for the handling of the generalised account of selection developed during the recent few decades. This account is aimed for creating a theoretical framework capable of explaining both biological evolution and cultural change as selection processes acting on self-replicating entities. This thesis focusses on the capacity of the generalised account of selection to describe language change as a process of this kind. In biology, the mechanisms of evolution are seen to form populations of genetically related organisms through time. One of the central questions explored in this thesis is whether selection theory makes it possible to picture languages are forming populations of a similar kind, and what a perspective like this can offer to the understanding of language in general. In historical linguistics, the comparative method and other, complementing methods have been traditionally used to study the development of languages from a common ancestral language. Computational, quantitative methods have not become widely used as part of the central methodology of historical linguistics. After the fading of a limited popularity enjoyed by the lexicostatistical method since the 1950s, only in the recent years have also the computational methods of phylogenetic inference used in evolutionary biology been applied to the study of early language history. In this thesis the possibilities offered by the traditional methodology of historical linguistics and the new phylogenetic methods are compared. The methods are approached through the ways in which they have been applied to the Indo-European languages, which is the most thoroughly investigated language family using both the traditional and the phylogenetic methods. The problems of these applications along with the optimal form of the linguistic data used in these methods are explored in the thesis. The mechanisms of biological evolution are seen in the thesis as parallel in a limited sense to the mechanisms of language change, however sufficiently so that the development of a generalised account of selection is deemed as possibly fruiful for understanding language change. These similarities are also seen to support the validity of using phylogenetic methods in the study of language history, although the use of linguistic data and the models of language change employed by these models are seen to await further development.

Water-ethanol mixtures by molecular dynamics and x-ray Compton scattering

Water-ethanol mixtures are commonly used in industry and house holds. However, quite surprisingly their molecular-level structure is still not completely understood. In particular, there is evidence that the local intermolecular geometries depend significantly on the concentration. The aim of this study was to gain information on the molecular-level structures of water-ethanol mixtures by two computational methods. The methods are classical molecular dynamics (MD), where the movement of molecules can be studied, and x-ray Compton scattering, in which the scattering cross section is sensitive to the electron momentum density. Firstly, the water-ethanol mixtures were studied with MD simulations, with the mixture concentration ranging from 0 to 100%. For the simulations well-established force fields were used for the water and ethanol molecules (TIP4P and OPLS-AA, respectively). Moreover, two models were used for ethanol, rigid and non-rigid. In the rigid model the intramolecular bond lengths are fixed, whereas in the non-rigid model the lengths are determined by harmonic potentials. Secondly, mixtures with three different concentrations employing both ethanol models were studied by calculating the experimentally observable x-ray quantity, the Compton profile. In the MD simulations a slight underestimation in the density was observed as compared to experiment. Furthermore, a positive excess of hydrogen bonding with water molecules and a negative one with ethanol was quantified. Also, the mixture was found more structured when the ethanol concentration was higher. Negligible differences in the results were found between the two ethanol models. In contrast, in the Compton scattering results a notable difference between the ethanol models was observed. For the rigid model the Compton profiles were similar for all the concentrations, but for the non-rigid model they were distinct. This leads to two possibilities of how the mixing occurs. Either the mixing is similar in all concentrations (as suggested by the rigid model) or the mixing changes for different concentrations (as suggested by the non-rigid model). Either way, this study shows that the choice of the force field is essential in the microscopic structure formation in the MD simulations. When the sources of uncertainty in the calculated Compton profiles were analyzed, it was found that more statistics needs to be collected to reduce the statistical uncertainty in the final results. The obtained Compton scattering results can be considered somewhat preliminary, but clearly indicative of the behaviour of the water-ethanol mixtures when the force field is modified. The next step is to collect more statistics and compare the results with experimental data to decide which ethanol model describes the mixture better. This way, valuable information on the microscopic structure of water-ethanol mixtures can be found. In addition, information on the force fields in the MD simulations and on the ability of the MD simulations to reproduce the microscopic structure of binary liquids is obtained.

Titanium Complexes for the Polymerisation of Ethene and Caprolactone

The literature part of the thesis mainly reviews the results of the use of titanium catalysts for ethene and caprolactone polymerisation. The behaviour of titanium catalysts bearing phenoxy-imino ligands has been the focus of more detailed investigations in ethene polymerisation. Reasons for the production of multimodal polyethene for a range of catalysts are also given. The experimental part of the thesis is divided into two sections based on the monomers used in the polymerisations: Part A (ethene) and part B (caprolactone). Part A: Titanium(IV) complexes bearing phenoxy-imino ligands are known to possess high ethene polymerisation activities after MAO activation. Depending on the ligand, the activities of the catalysts in polymerisation can vary between 1 and 44000 kgPE/(mol*cat*h*bar). Depending on the polymerisation temperature and the electronic and steric properties of the catalyst ligands, low to high molar mass values and uni- and multimodal polydispersity values can been observed. In order to discover the reasons for these differences, 22 titanium(IV) complexes containing differently substituted phenoxy-imino derivatives as di- and tetradentate ligands were synthesised with high yields and used as homogeneous catalysts in ethene polymerisations. Computational methods were used to predict the geometry of the synthesised complexes and their configuration after activation. Based on the results obtained, the geometry of the catalyst together with the ligand substituents seem to play a major role in defining the catalytic activity. Novel titanium(IV) complexes bearing malonate ligands were also synthesised. Malonates are considered to be suitable ligand pre-cursors since they can be produced by the simple reaction of any primary or secondary alcohol with malonylchloride, and thus they are easily modifiable. After treatment with MAO these complexes had polymerisation activities between 10 and 50 kgPE/(mol*cat*h*bar) and surprisingly low polydispersity values when compared with similar types of catalysts bearing the O?O chelate ligand. Part B: One of the synthesis routes in the preparation of the above mentioned phenoxy-imino titanium dichloride complexes involved the use of Ti(NMe2)4 with a range of salicylaldimine type compounds. On reaction, these two compounds formed an intermediate product selectively and quantitatively which was active in the ring-opening polymerisation of caprolactone. Several mono-anionic alcoholates were also combined with Ti(NMe2)4 in different molar ratios and used as catalysts. Full conversion of the monomer was achieved within 15 minutes with catalysts having a co-ordination number of 4 while after 22 hours full conversion was achieved with catalysts having a co-ordination number of 6.

Tailoring polyolefin properties by metallocene catalysis

This doctoral thesis deals with the syntheses of olefin homo- and copolymers using different kind of metallocene catalyst. Ethene, propene, 1-hexene, 1-hexadecene, vinylcyclohexane and phenylnorbornene were homo- or copolymerized with the catalysts. The unbridged benzyl substituted zirconium dichloride catalysts (1-4), ansa- bridged acenaphtyl substituted zirconium dichloride catalysts, ( 5, 6), rac- and meso-ethylene-bis(1-indenyl)zirconium dichlorides, (rac- and meso-8), rac-ethylene-bis(1-indenyl)hafnium dichloride, ( 12), bis(9-fluorenyl)hafnium dichloride (14 ) enantiomerically pure (R)- phenylethyl[(9-fluorenyl-1-indenyl)]ZrCl2, (11), 14 and asymmetric dimethylsilyl[(3-benzylindenyl-(2-methylbenzen[e]indenyl)] zirconium dichloride, (13), were prepared in our laboratory. Dimethylsilyl-bis(1-indenyl)zirconium dichloride, (9), isopropylidene(9-fluorenyl-cyclopentadienyl)zirconium dichloride, (10), and were obtained commercially. The solid-state structures of the catalysts rac- and meso-1 were determined by X-ray crystallography. Computational methods were used for the structure optimization of the catalyst rac- and meso-1 in order to compare the theoretical calculations with the experimental results. Polymerization experiments were conducted in a highly purified autoclave system using low pressures (< 5 bar) of gaseous monomers. The experiments were designed to attain the optimal catalytic activity and a uniform copolymer composition. The prepared homo- and copolymers were characterized by the gel permeation chromatography, GPC, differential scanning calorimetry, DSC, nuclear magnetic resonance, NMR, and Fourier transform infrared spectrometry, FTIR . Molar mass (Mw, Mn), molar mass distribution (Mw/Mn), tacticity, comonomer content, melting temperature, glass transition temperature, and end group structures and content were determined. A special attention was paid on the correlation of the polymer properties with the catalyst structures and polymerization conditions. An intramolecular phenyl coordination was found in phenyl substituted benzyl zirconocenes 1-3 explaining the decreased activity of the catalysts. Novel copolymers poly(propene-co-phenylnorbornene) and poly(propene co-vinylcyclohexane), were synthesized and high molar mass poly(ethene-co-1-hexene) and poly(ethene-co-1-hexadecene) copolymers with elastic properties were prepared. Activation of a hafnocene catalyst was studied with UV-Vis spectrometry and activation process for the synthesis of ultra high molar mass poly(1-hexene) was found out.

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.

Maltose and maltotriose transport into ale and lager brewer's yeast strains

Maltose and maltotriose are the two most abundant sugars in brewer s wort, and thus brewer s yeast s ability to utilize them efficiently is of major importance in the brewing process. The increasing tendency to utilize high and very-high-gravity worts containing increased concentrations of maltose and maltotriose renders the need for efficient transport of these sugars even more pronounced. Residual maltose and especially maltotriose are quite often present especially after high and very-high-gravity fermentations. Sugar uptake capacity has been shown to be the rate limiting factor for maltose and maltotriose utilization. The main aim of the present study was to find novel ways to improve maltose and maltotriose utilization during the main fermentation. Maltose and maltotriose uptake characteristics of several ale and lager strains were studied. Genotype determination of the genes needed for maltose and maltotriose utilization was performed. Maltose uptake inhibition studies were performed to reveal the dominant transporter types actually functioning in each of the strains. Temperature-dependence of maltose transport was studied for ale and for lager strains as well as for each of the single sugar transporter proteins Agt1p, Malx1p and Mtt1p. The AGT1 promoter regions of one ale and two lager strains were sequenced by chromosome walking and the promoter elements were searched for using computational methods. The results showed that ale and lager strains predominantly use different maltose and maltotriose transporter types for maltose and maltotriose uptake. Agt1 transporter was found to be the dominant maltose/maltotriose transporter in the ale strains whereas Malx1 and Mtt1- type transporters dominated in the lager strains. All lager strains studied were found to possess a non-functional Agt1 transporter. The ale strains were observed to be more sensitive to temperature decrease in their maltose uptake compared to the lager strains. Single transporters were observed to differ in their sensitivity to temperature decrease and their temperature-dependence was shown to decrease in the order Agt1≥Malx1>Mtt1. The different temperature-dependence between the ale and lager strains was observed to be due to the different dominant maltose/maltotriose transporters ale and lager strains possessed. The AGT1 promoter regions of ale and lager strains were found to differ markedly from the corresponding regions of laboratory strains. The ale strain was found to possess an extra MAL-activator binding site compared to the lager strains. Improved maltose and maltotriose uptake capacity was obtained with a modified lager strain where the AGT1 gene was repaired and put under the control of a strong promoter. Modified strains fermented wort faster and more completely, producing beers containing more ethanol and less residual maltose and maltotriose. Significant savings in the main fermentation time were obtained when modified strains were used. In high-gravity wort fermentations 8 20% and in very-high-gravity wort fermentations even 11 37% time savings were obtained. These are economically significant changes and would cause a marked increase in annual output from the same-size of brewhouse and fermentor facilities.