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.

Asteroid identification using statistical orbital inversion methods

An efficient and statistically robust solution for the identification of asteroids among numerous sets of astrometry is presented. In particular, numerical methods have been developed for the short-term identification of asteroids at discovery, and for the long-term identification of scarcely observed asteroids over apparitions, a task which has been lacking a robust method until now. The methods are based on the solid foundation of statistical orbital inversion properly taking into account the observational uncertainties, which allows for the detection of practically all correct identifications. Through the use of dimensionality-reduction techniques and efficient data structures, the exact methods have a loglinear, that is, O(nlog(n)), computational complexity, where n is the number of included observation sets. The methods developed are thus suitable for future large-scale surveys which anticipate a substantial increase in the astrometric data rate. Due to the discontinuous nature of asteroid astrometry, separate sets of astrometry must be linked to a common asteroid from the very first discovery detections onwards. The reason for the discontinuity in the observed positions is the rotation of the observer with the Earth as well as the motion of the asteroid and the observer about the Sun. Therefore, the aim of identification is to find a set of orbital elements that reproduce the observed positions with residuals similar to the inevitable observational uncertainty. Unless the astrometric observation sets are linked, the corresponding asteroid is eventually lost as the uncertainty of the predicted positions grows too large to allow successful follow-up. Whereas the presented identification theory and the numerical comparison algorithm are generally applicable, that is, also in fields other than astronomy (e.g., in the identification of space debris), the numerical methods developed for asteroid identification can immediately be applied to all objects on heliocentric orbits with negligible effects due to non-gravitational forces in the time frame of the analysis. The methods developed have been successfully applied to various identification problems. Simulations have shown that the methods developed are able to find virtually all correct linkages despite challenges such as numerous scarce observation sets, astrometric uncertainty, numerous objects confined to a limited region on the celestial sphere, long linking intervals, and substantial parallaxes. Tens of previously unknown main-belt asteroids have been identified with the short-term method in a preliminary study to locate asteroids among numerous unidentified sets of single-night astrometry of moving objects, and scarce astrometry obtained nearly simultaneously with Earth-based and space-based telescopes has been successfully linked despite a substantial parallax. Using the long-term method, thousands of realistic 3-linkages typically spanning several apparitions have so far been found among designated observation sets each spanning less than 48 hours.

Novel Mass Spectrometric Analysis Methods for Anabolic Androgenic Steroids in Sports Drug Testing

The feasibility of different modern analytical techniques for the mass spectrometric detection of anabolic androgenic steroids (AAS) in human urine was examined in order to enhance the prevalent analytics and to find reasonable strategies for effective sports drug testing. A comparative study of the sensitivity and specificity between gas chromatography (GC) combined with low (LRMS) and high resolution mass spectrometry (HRMS) in screening of AAS was carried out with four metabolites of methandienone. Measurements were done in selected ion monitoring mode with HRMS using a mass resolution of 5000. With HRMS the detection limits were considerably lower than with LRMS, enabling detection of steroids at low 0.2-0.5 ng/ml levels. However, also with HRMS, the biological background hampered the detection of some steroids. The applicability of liquid-phase microextraction (LPME) was studied with metabolites of fluoxymesterone, 4-chlorodehydromethyltestosterone, stanozolol and danazol. Factors affecting the extraction process were studied and a novel LPME method with in-fiber silylation was developed and validated for GC/MS analysis of the danazol metabolite. The method allowed precise, selective and sensitive analysis of the metabolite and enabled simultaneous filtration, extraction, enrichment and derivatization of the analyte from urine without any other steps in sample preparation. Liquid chromatographic/tandem mass spectrometric (LC/MS/MS) methods utilizing electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI) and atmospheric pressure photoionization (APPI) were developed and applied for detection of oxandrolone and metabolites of stanozolol and 4-chlorodehydromethyltestosterone in urine. All methods exhibited high sensitivity and specificity. ESI showed, however, the best applicability, and a LC/ESI-MS/MS method for routine screening of nine 17-alkyl-substituted AAS was thus developed enabling fast and precise measurement of all analytes with detection limits below 2 ng/ml. The potential of chemometrics to resolve complex GC/MS data was demonstrated with samples prepared for AAS screening. Acquired full scan spectral data (m/z 40-700) were processed by the OSCAR algorithm (Optimization by Stepwise Constraints of Alternating Regression). The deconvolution process was able to dig out from a GC/MS run more than the double number of components as compared with the number of visible chromatographic peaks. Severely overlapping components, as well as components hidden in the chromatographic background could be isolated successfully. All studied techniques proved to be useful analytical tools to improve detection of AAS in urine. Superiority of different procedures is, however, compound-dependent and different techniques complement each other.

Univariate, bivariate, and multivariate methods in corpus-based lexicography : A study of synonymy

In this dissertation, I present an overall methodological framework for studying linguistic alternations, focusing specifically on lexical variation in denoting a single meaning, that is, synonymy. As the practical example, I employ the synonymous set of the four most common Finnish verbs denoting THINK, namely ajatella, miettiä, pohtia and harkita ‘think, reflect, ponder, consider’. As a continuation to previous work, I describe in considerable detail the extension of statistical methods from dichotomous linguistic settings (e.g., Gries 2003; Bresnan et al. 2007) to polytomous ones, that is, concerning more than two possible alternative outcomes. The applied statistical methods are arranged into a succession of stages with increasing complexity, proceeding from univariate via bivariate to multivariate techniques in the end. As the central multivariate method, I argue for the use of polytomous logistic regression and demonstrate its practical implementation to the studied phenomenon, thus extending the work by Bresnan et al. (2007), who applied simple (binary) logistic regression to a dichotomous structural alternation in English. The results of the various statistical analyses confirm that a wide range of contextual features across different categories are indeed associated with the use and selection of the selected think lexemes; however, a substantial part of these features are not exemplified in current Finnish lexicographical descriptions. The multivariate analysis results indicate that the semantic classifications of syntactic argument types are on the average the most distinctive feature category, followed by overall semantic characterizations of the verb chains, and then syntactic argument types alone, with morphological features pertaining to the verb chain and extra-linguistic features relegated to the last position. In terms of overall performance of the multivariate analysis and modeling, the prediction accuracy seems to reach a ceiling at a Recall rate of roughly two-thirds of the sentences in the research corpus. The analysis of these results suggests a limit to what can be explained and determined within the immediate sentential context and applying the conventional descriptive and analytical apparatus based on currently available linguistic theories and models. The results also support Bresnan’s (2007) and others’ (e.g., Bod et al. 2003) probabilistic view of the relationship between linguistic usage and the underlying linguistic system, in which only a minority of linguistic choices are categorical, given the known context – represented as a feature cluster – that can be analytically grasped and identified. Instead, most contexts exhibit degrees of variation as to their outcomes, resulting in proportionate choices over longer stretches of usage in texts or speech.

Exploring the experiences and conceptions of good teaching in higher education : Development of a questionnaire for assessing students' approaches to learning and experiences of the teaching-learning environment

The aim of this dissertation was to adapt a questionnaire for assessing students’ approaches to learning and their experiences of the teaching-learning environment. The aim was to explore the validity of the modified Experiences of Teaching and Learning Questionnaire (ETLQ) by examining how the instruments measure the underlying dimensions of student experiences and their learning. The focus was on the relation between students’ experiences of their teaching-learning environment and their approaches to learning. Moreover, the relation between students’ experiences and students’ and teachers’ conceptions of good teaching was examined. In Study I the focus was on the use of the ETLQ in two different contexts: Finnish and British. The study aimed to explore the similarities and differences between the factor structures that emerged from both data sets. The results showed that the factor structures concerning students’ experiences of their teaching-learning environment and their approaches to learning were highly similar in the two contexts. Study I also examined how students’ experiences of the teaching-learning environment are related to their approaches to learning in the two contexts. The results showed that students’ positive experiences of their teaching-learning environment were positively related to their deep approach to learning and negatively to the surface approach to learning in both the Finnish and British data sets. This result was replicated in Study II, which examined the relation between approaches to learning and experiences of the teaching-learning environment on a group level. Furthermore, Study II aimed to explore students’ approaches to learning and their experiences of the teaching-learning environment in different disciplines. The results showed that the deep approach to learning was more common in the soft sciences than in the hard sciences. In Study III, students’ conceptions of good teaching were explored by using qualitative methods, more precisely, by open-ended questions. The aim was to examine students’ conceptions, disciplinary differences and their relation to students’ approaches to learning. The focus was on three disciplines, which differed in terms of students’ experiences of their teaching-learning environment. The results showed that students’ conceptions of good teaching were in line with the theory of good teaching and there were disciplinary differences in their conceptions. Study IV examined university teachers’ conceptions of good teaching, which corresponded to the learning-focused approach to teaching. Furthermore, another aim in this doctoral dissertation was to compare the students’ and teachers’ conceptions of good teaching, the results of which showed that these conceptions appear to have similarities. The four studies indicated that the ETLQ appears to be a sufficiently robust measurement instrument in different contexts. Moreover, its strength is its ability to be at the same time a valid research instrument and a practical tool for enhancing the quality of students’ learning. In addition, the four studies emphasise that in order to enhance teaching and learning in higher education, various perspectives have to be taken into account. This study sheds light on the interaction between students’ approaches to learning, their conceptions of good teaching, their experiences of the teaching-learning environment, and finally, the disciplinary culture.

Genotyping for genetic association studies: Methods and applications

In this thesis, two separate single nucleotide polymorphism (SNP) genotyping techniques were set up at the Finnish Genome Center, pooled genotyping was evaluated as a screening method for large-scale association studies, and finally, the former approaches were used to identify genetic factors predisposing to two distinct complex diseases by utilizing large epidemiological cohorts and also taking environmental factors into account. The first genotyping platform was based on traditional but improved restriction-fragment-length-polymorphism (RFLP) utilizing 384-microtiter well plates, multiplexing, small reaction volumes (5 µl), and automated genotype calling. We participated in the development of the second genotyping method, based on single nucleotide primer extension (SNuPeTM by Amersham Biosciences), by carrying out the alpha- and beta tests for the chemistry and the allele-calling software. Both techniques proved to be accurate, reliable, and suitable for projects with thousands of samples and tens of markers. Pooled genotyping (genotyping of pooled instead of individual DNA samples) was evaluated with Sequenom s MassArray MALDI-TOF, in addition to SNuPeTM and PCR-RFLP techniques. We used MassArray mainly as a point of comparison, because it is known to be well suited for pooled genotyping. All three methods were shown to be accurate, the standard deviations between measurements being 0.017 for the MassArray, 0.022 for the PCR-RFLP, and 0.026 for the SNuPeTM. The largest source of error in the process of pooled genotyping was shown to be the volumetric error, i.e., the preparation of pools. We also demonstrated that it would have been possible to narrow down the genetic locus underlying congenital chloride diarrhea (CLD), an autosomal recessive disorder, by using the pooling technique instead of genotyping individual samples. Although the approach seems to be well suited for traditional case-control studies, it is difficult to apply if any kind of stratification based on environmental factors is needed. Therefore we chose to continue with individual genotyping in the following association studies. Samples in the two separate large epidemiological cohorts were genotyped with the PCR-RFLP and SNuPeTM techniques. The first of these association studies concerned various pregnancy complications among 100,000 consecutive pregnancies in Finland, of which we genotyped 2292 patients and controls, in addition to a population sample of 644 blood donors, with 7 polymorphisms in the potentially thrombotic genes. In this thesis, the analysis of a sub-study of pregnancy-related venous thromboses was included. We showed that the impact of factor V Leiden polymorphism on pregnancy-related venous thrombosis, but not the other tested polymorphisms, was fairly large (odds ratio 11.6; 95% CI 3.6-33.6), and increased multiplicatively when combined with other risk factors such as obesity or advanced age. Owing to our study design, we were also able to estimate the risks at the population level. The second epidemiological cohort was the Helsinki Birth Cohort of men and women who were born during 1924-1933 in Helsinki. The aim was to identify genetic factors that might modify the well known link between small birth size and adult metabolic diseases, such as type 2 diabetes and impaired glucose tolerance. Among ~500 individuals with detailed birth measurements and current metabolic profile, we found that an insertion/deletion polymorphism of the angiotensin converting enzyme (ACE) gene was associated with the duration of gestation, and weight and length at birth. Interestingly, the ACE insertion allele was also associated with higher indices of insulin secretion (p=0.0004) in adult life, but only among individuals who were born small (those among the lowest third of birth weight). Likewise, low birth weight was associated with higher indices of insulin secretion (p=0.003), but only among carriers of the ACE insertion allele. The association with birth measurements was also found with a common haplotype of the glucocorticoid receptor (GR) gene. Furthermore, the association between short length at birth and adult impaired glucose tolerance was confined to carriers of this haplotype (p=0.007). These associations exemplify the interaction between environmental factors and genotype, which, possibly due to altered gene expression, predisposes to complex metabolic diseases. Indeed, we showed that the common GR gene haplotype associated with reduced mRNA expression in thymus of three individuals (p=0.0002).

Variation in tracheid cross-sectional dimensions and wood viscoelasticity extent and control methods

Printing papers have been the main product of the Finnish paper industry. To improve properties and economy of printing papers, controlling of tracheid cross-sectional dimensions and wood viscoelasticity are examined in this study. Controlling is understood as any procedure which yields raw material classes with distinct properties and small internal variation. Tracheid cross-sectional dimensions, i.e., cell wall thickness and radial and tangential diameters can be controlled with methods such as sorting wood into pulpwood and sawmill chips, sorting of logs according to tree social status and fractionation of fibres. These control methods were analysed in this study with simulations, which were based on measured tracheid cross-sectional dimensions. A SilviScan device was used to measure the data set from five Norway spruce (Picea abies) and five Scots pine (Pinus sylvestris) trunks. The simulation results indicate that the sawmill chips and top pulpwood assortments have quite similar cross-sectional dimensions. Norway spruce and Scots pine are on average also relatively similar in their cross-sectional dimensions. The distributions of these species are somewhat different, but from a practical point of view, the differences are probably of minor importance. The controlling of tracheid cross-sectional dimensions can be done most efficiently with methods that can separate fibres into earlywood and latewood. Sorting of logs or partitioning of logs into juvenile and mature wood were markedly less efficient control methods than fractionation of fibres. Wood viscoelasticity affects energy consumption in mechanical pulping, and is thus an interesting control target when improving energy efficiency of the process. A literature study was made to evaluate the possibility of using viscoelasticity in controlling. The study indicates that there is considerable variation in viscoelastic properties within tree species, but unfortunately, the viscoelastic properties of important raw material lots such as top pulpwood or sawmill chips are not known. Viscoelastic properties of wood depend mainly on lignin, but also on microfibrillar angle, width of cellulose crystals and tracheid cross-sectional dimensions.

From a tree to a stand in Finnish boreal forests: biomass estimation and comparison of methods

There is an increasing need to compare the results obtained with different methods of estimation of tree biomass in order to reduce the uncertainty in the assessment of forest biomass carbon. In this study, tree biomass was investigated in a 30-year-old Scots pine (Pinus sylvestris) (Young-Stand) and a 130-year-old mixed Norway spruce (Picea abies)-Scots pine stand (Mature-Stand) located in southern Finland (61º50' N, 24º22' E). In particular, a comparison of the results of different estimation methods was conducted to assess the reliability and suitability of their applications. For the trees in Mature-Stand, annual stem biomass increment fluctuated following a sigmoid equation, and the fitting curves reached a maximum level (from about 1 kg/yr for understorey spruce to 7 kg/yr for dominant pine) when the trees were 100 years old. Tree biomass was estimated to be about 70 Mg/ha in Young-Stand and about 220 Mg/ha in Mature-Stand. In the region (58.00-62.13 ºN, 14-34 ºE, ≤ 300 m a.s.l.) surrounding the study stands, the tree biomass accumulation in Norway spruce and Scots pine stands followed a sigmoid equation with stand age, with a maximum of 230 Mg/ha at the age of 140 years. In Mature-Stand, lichen biomass on the trees was 1.63 Mg/ha with more than half of the biomass occurring on dead branches, and the standing crop of litter lichen on the ground was about 0.09 Mg/ha. There were substantial differences among the results estimated by different methods in the stands. These results imply that a possible estimation error should be taken into account when calculating tree biomass in a stand with an indirect approach.

Quality Assessment of a Forest Inventory Based on Airborne Laser Scanning

In this study, a quality assessment method based on sampling of primary laser inventory units (microsegments) was analysed. The accuracy of a laser inventory carried out in Kuhmo was analysed as a case study. Field sample plots were measured on the sampled microsegments in the Kuhmo inventory area. Two main questions were considered. Did the ALS based inventory meet the accuracy requirements set for the provider and how should a reliable, cost-efficient and independent quality assessment be undertaken. The agreement between control measurement and ALS based inventory was analysed in four ways: 1) The root mean squared errors (RMSEs) and bias were calculated. 2) Scatter plots with 95% confidence intervals were plotted and the placing of identity lines was checked. 3) Bland-Altman plots were drawn so that the mean difference of attributes between the control method and ALS-method was calculated and plotted against average value of attributes. 4) The tolerance limits were defined and combined with Bland-Altman plots. The RMSE values were compared to a reference study from which the accuracy requirements had been set to the service provider. The accuracy requirements in Kuhmo were achieved, however comparison of RMSE values proved to be difficult. Field control measurements are costly and time-consuming, but they are considered to be robust. However, control measurements might include errors, which are difficult to take into account. Using the Bland-Altman plots none of the compared methods are considered to be completely exact, so this offers a fair way to interpret results of assessment. The tolerance limits to be set on order combined with Bland-Altman plots were suggested to be taken in practise. In addition, bias should be calculated for total area. Some other approaches for quality control were briefly examined. No method was found to fulfil all the required demands of statistical reliability, cost-efficiency, time efficiency, simplicity and speed of implementation. Some benefits and shortcomings of the studied methods were discussed.

Modifications of surface materials and their effects on cleanability as studied by radiochemical methods

Modifications of surface materials and their effects on cleanability have important impacts in many fields of activity. In this study the primary aim was to develop radiochemical methods suitable for evaluating cleanability in material research for different environments. Another aim was to investigate the effects of surface modifications on cleanabilitity and surface properties of plastics, ceramics, concrete materials and also their coatings in conditions simulating their typical environments. Several new 51Cr and 14C labelled soils were developed for testing situations. The new radiochemical methods developed were suitable for examining different surface materials and different soil types, providing quantitative information about the amount of soil on surfaces. They also take into account soil soaked into surfaces. The supporting methods colorimetric determination and ATP bioluminescence provided semi-quantitative results. The results from the radiochemical and supporting methods partly correlated with each other. From a material research point of view numerous new materials were evaluated. These included both laboratory-made model materials and commercial products. Increasing the amount of plasticizer decreased the cleanability of poly(vinyl chloride) (PVC) materials. Microstructured surfaces of plastics improved the cleanability of PVC from particle soils, whereas for oil soil microstructuring reduced the cleanability. In the case of glazed ceramic materials, coatings affected the cleanability. The roughness of surfaces correlated with cleanability from particle soils and the cleanability from oil soil correlated with the contact angles. Organic particle soil was removed more efficiently from TiO2-coated ceramic surfaces after UV-radiation than without UV treatment, whereas no effect was observed on the cleanability of oil soil. Coatings improved the cleanability of concrete flooring materials intended for use in animal houses.