Potato virus A as a heterologous protein expression tool in plants

Viruksien käyttö tuotekehityksen ja tutkimuksen vaatimien proteiinien tuottamiseen, syötävien rokotteiden kehittämiseen ja geeniterapiaan edustavat kasvavia biotekniikan sovellusalueita. Perunan A-virus (PVA) kuuluu potyviruksiin, joiden proteiinit tuotetaan aluksi yhtenä suurena molekyylinä, joka pilkotaan yksittäisiksi proteiineiksi viruksen itsensä tuottamilla entsyymeillä. Siten virusgenomiin lisätty vieras geeni käännetään proteiiniksi virusproteiinien mukana. Lopputuloksena kaikkia proteiineja tuotetaan kasvisoluissa samansuuruinen määrä. Lisäksi, viruksen proteiinikuoren koontimekanismi sallii perintöaineksen merkittävän lisäyksen ilman että viruksen tartutuskyky merkittävästi heikkenee. Koska virus monistuu ja leviää koko kasviin, jo melko pieni määrä kasveja riittää huomattavan proteiinimäärän tuottamiseen esimerkiksi säännösten mukaisessa kasvihuoneessa. Tämän työn tarkoituksena oli muuntaa PVA:n genomia siten, että virus soveltuisi yhden vieraan proteiinin tai useiden erilaisten proteiinien samanaikaiseen tuottamiseen kasveissa. Aluksi kokeiltiin viruksen replikaasia ja kuoriproteiinia koodaavien genomialueiden välistä kohtaa ja ihmisestä peräisi olevaa geeniä, joka tuotti S-COMT-entsyymiä (katekoli-O-metyylitransferaasi). Sen aktiivisuuden rajoittaminen auttaa Parkinsonintaudin hoidossa. Kasvissa tuotettua S-COMT:ia voitaisiin käyttää lääkekehityksessä estolääkkeiden testaukseen. Kahden viikon kuluttua tartutuksesta tupakan lehdissä oli entsymaattisesti aktiivista S-COMT:ia n. 1 % lehden liukoisista proteiineista. PVA:n P1-proteiinia koodaavalta alueelta oli paikannettu kohta, johon ehkä voitaisiin siirtää vieras geeni. Asia varmistettiin siirtämällä tähän kohtaan meduusan geeni, joka tuottaa UV-valossa vihreänä fluoresoivaa proteiinia (GFP). GFP-geeniä kantava PVA levisi kasvissa ja lisääntyi n. 30-50 %:iin viruksen normaalista pitoisuudesta. Koko kasvi fluoresoi vihreänä UV-valossa. Vieras geeni voidaan sijoittaa myös potyviruksen P1- ja HCpro-proteiineja koodaavien alueiden väliin. Samaan PVA-genomiin siirrettiin kolme geeniä, yksi kuhunkin kolmesta kloonauskohdasta: GFP-geeni P1:n sisälle, merivuokon lusiferaasigeeni P1/HCpro-kohtaan ja bakteerin beta-glukuronidaasigeeni (GUS) replikaasi/kuoriproteiini-kohtaan. Virusgenomin ja itse viruksen pituudet kasvoivat 38 %, mutta virus säilytti tartutuskykynsä. Se levisi kasveissa saavuttaen n. 15 % viruksen normaalista pitoisuudesta. Kaikki kolme vierasta proteiinia esiintyivät lehdissä aktiivisina.

The Significance of Wild Plants in the Evolutionary Ecology of Three Major Viruses Infecting Cultivated Sweetpotato in Uganda

The studies presented in this thesis contribute to the understanding of evolutionary ecology of three major viruses threatening cultivated sweetpotato (Ipomoea batatas Lam) in East Africa: Sweet potato feathery mottle virus (SPFMV; genus Potyvirus; Potyviridae), Sweet potato chlorotic stunt virus (SPCSV; genus Crinivirus; Closteroviridae) and Sweet potato mild mottle virus (SPMMV; genus Ipomovirus; Potyviridae). The viruses were serologically detected and the positive results confirmed by RT-PCR and sequencing. SPFMV was detected in 24 wild plant species of family Convolvulacea (genera Ipomoea, Lepistemon and Hewittia), of which 19 species were new natural hosts for SPFMV. SPMMV and SPCSV were detected in wild plants belonging to 21 and 12 species (genera Ipomoea, Lepistemon and Hewittia), respectively, all of which were previously unknown to be natural hosts of these viruses. SPFMV was the most abundant virus being detected in 17% of the plants, while SPMMV and SPCSV were detected in 9.8% and 5.4% of the assessed plants, respectively. Wild plants in Uganda were infected with the East African (EA), common (C), and the ordinary (O) strains, or co-infected with the EA and the C strain of SPFMV. The viruses and virus-like diseases were more frequent in the eastern agro-ecological zone than the western and central zones, which contrasted with known incidences of these viruses in sweetpotato crops, except for northern zone where incidences were lowest in wild plants as in sweetpotato. The NIb/CP junction in SPMMV was determined experimentally which facilitated CP-based phylogenetic and evolutionary analyses of SPMMV. Isolates of all the three viruses from wild plants were genetically similar to those found in cultivated sweetpotatoes in East Africa. There was no evidence of host-driven population genetic structures suggesting frequent transmission of these viruses between their wild and cultivated hosts. The p22 RNA silencing suppressor-encoding sequence was absent in a few SPCSV isolates, but regardless of this, SPCSV isolates incited sweet potato virus disease (SPVD) in sweetpotato plants co-infected with SPFMV, indicating that p22 is redundant for synergism between SCSV and SPFMV. Molecular evolutionary analysis revealed that isolates of strain EA of SPFMV that is largely restricted geographically in East Africa experience frequent recombination in comparison to isolates of strain C that is globally distributed. Moreover, non-homologous recombination events between strains EA and C were rare, despite frequent co-infections of these strains in wild plants, suggesting purifying selection against non-homologous recombinants between these strains or that such recombinants are mostly not infectious. Recombination was detected also in the 5 - and 3 -proximal regions of the SPMMV genome providing the first evidence of recombination in genus Ipomovirus, but no recombination events were detected in the characterized genomic regions of SPCSV. Strong purifying selection was implicated on evolution of majority of amino acids of the proteins encoded by the analyzed genomic regions of SPFMV, SPMMV and SPCSV. However, positive selection was predicted on 17 amino acids distributed over the whole the coat protein (CP) in the globally distributed strain C, as compared to only 4 amino acids in the multifunctional CP N-terminus (CP-NT) of strain EA largely restricted geographically to East Africa. A few amino acid sites in the N-terminus of SPMMV P1, the p7 protein and RNA silencing suppressor proteins p22 and RNase3 of SPCSV were also submitted to positive selection. Positively selected amino acids may constitute ligand-binding domains that determine interactions with plant host and/or insect vector factors. The P1 proteinase of SPMMV (genus Ipomovirus) seems to respond to needs of adaptation, which was not observed with the helper component proteinase (HC-Pro) of SPMMV, although the HC-Pro is responsible for many important molecular interactions in genus Potyvirus. Because the centre of origin of cultivated sweetpotato is in the Americas from where the crop was dispersed to other continents in recent history (except for the Australasia and South Pacific region), it would be expected that identical viruses and their strains occur worldwide, presuming virus dispersal with the host. Apparently, this seems not to be the case with SPMMV, the strain EA of SPFMV and the strain EA of SPCSV that are largely geographically confined in East Africa where they are predominant and occur both in natural and agro-ecosystems. The geographical distribution of plant viruses is constrained more by virus-vector relations than by virus-host interactions, which in accordance of the wide range of natural host species and the geographical confinement to East Africa suggest that these viruses existed in East African wild plants before the introduction of sweetpotato. Subsequently, these studies provide compelling evidence that East Africa constitutes a cradle of SPFMV strain EA, SPCSV strain EA, and SPMMV. Therefore, sweet potato virus disease (SPVD) in East Africa may be one of the examples of damaging virus diseases resulting from exchange of viruses between introduced crops and indigenous wild plant species. Keywords: Convolvulaceae, East Africa, epidemiology, evolution, genetic variability, Ipomoea, recombination, SPCSV, SPFMV, SPMMV, selection pressure, sweetpotato, wild plant species Author s Address: Arthur K. Tugume, Department of Agricultural Sciences, Faculty of Agriculture and Forestry, University of Helsinki, Latokartanonkaari 7, P.O Box 27, FIN-00014, Helsinki, Finland. Email: tugume.arthur@helsinki.fi Author s Present Address: Arthur K. Tugume, Department of Botany, Faculty of Science, Makerere University, P.O. Box 7062, Kampala, Uganda. Email: aktugume@botany.mak.ac.ug, tugumeka@yahoo.com

Aspects and Applications of Pulse Sequence Design for Solution-State Nuclear Magnetic Resonance Spectroscopy

NMR spectroscopy enables the study of biomolecules from peptides and carbohydrates to proteins at atomic resolution. The technique uniquely allows for structure determination of molecules in solution-state. It also gives insights into dynamics and intermolecular interactions important for determining biological function. Detailed molecular information is entangled in the nuclear spin states. The information can be extracted by pulse sequences designed to measure the desired molecular parameters. Advancement of pulse sequence methodology therefore plays a key role in the development of biomolecular NMR spectroscopy. A range of novel pulse sequences for solution-state NMR spectroscopy are presented in this thesis. The pulse sequences are described in relation to the molecular information they provide. The pulse sequence experiments represent several advances in NMR spectroscopy with particular emphasis on applications for proteins. Some of the novel methods are focusing on methyl-containing amino acids which are pivotal for structure determination. Methyl-specific assignment schemes are introduced for increasing the size range of 13C,15N labeled proteins amenable to structure determination without resolving to more elaborate labeling schemes. Furthermore, cost-effective means are presented for monitoring amide and methyl correlations simultaneously. Residual dipolar couplings can be applied for structure refinement as well as for studying dynamics. Accurate methods for measuring residual dipolar couplings in small proteins are devised along with special techniques applicable when proteins require high pH or high temperature solvent conditions. Finally, a new technique is demonstrated to diminish strong-coupling induced artifacts in HMBC, a routine experiment for establishing long-range correlations in unlabeled molecules. The presented experiments facilitate structural studies of biomolecules by NMR spectroscopy.

Problems and Algorithms for Sequence Segmentations

The analysis of sequential data is required in many diverse areas such as telecommunications, stock market analysis, and bioinformatics. A basic problem related to the analysis of sequential data is the sequence segmentation problem. A sequence segmentation is a partition of the sequence into a number of non-overlapping segments that cover all data points, such that each segment is as homogeneous as possible. This problem can be solved optimally using a standard dynamic programming algorithm. In the first part of the thesis, we present a new approximation algorithm for the sequence segmentation problem. This algorithm has smaller running time than the optimal dynamic programming algorithm, while it has bounded approximation ratio. The basic idea is to divide the input sequence into subsequences, solve the problem optimally in each subsequence, and then appropriately combine the solutions to the subproblems into one final solution. In the second part of the thesis, we study alternative segmentation models that are devised to better fit the data. More specifically, we focus on clustered segmentations and segmentations with rearrangements. While in the standard segmentation of a multidimensional sequence all dimensions share the same segment boundaries, in a clustered segmentation the multidimensional sequence is segmented in such a way that dimensions are allowed to form clusters. Each cluster of dimensions is then segmented separately. We formally define the problem of clustered segmentations and we experimentally show that segmenting sequences using this segmentation model, leads to solutions with smaller error for the same model cost. Segmentation with rearrangements is a novel variation to the segmentation problem: in addition to partitioning the sequence we also seek to apply a limited amount of reordering, so that the overall representation error is minimized. We formulate the problem of segmentation with rearrangements and we show that it is an NP-hard problem to solve or even to approximate. We devise effective algorithms for the proposed problem, combining ideas from dynamic programming and outlier detection algorithms in sequences. In the final part of the thesis, we discuss the problem of aggregating results of segmentation algorithms on the same set of data points. In this case, we are interested in producing a partitioning of the data that agrees as much as possible with the input partitions. We show that this problem can be solved optimally in polynomial time using dynamic programming. Furthermore, we show that not all data points are candidates for segment boundaries in the optimal solution.

Mining Sequential Data – in Search of Segmental Structures

Segmentation is a data mining technique yielding simplified representations of sequences of ordered points. A sequence is divided into some number of homogeneous blocks, and all points within a segment are described by a single value. The focus in this thesis is on piecewise-constant segments, where the most likely description for each segment and the most likely segmentation into some number of blocks can be computed efficiently. Representing sequences as segmentations is useful in, e.g., storage and indexing tasks in sequence databases, and segmentation can be used as a tool in learning about the structure of a given sequence. The discussion in this thesis begins with basic questions related to segmentation analysis, such as choosing the number of segments, and evaluating the obtained segmentations. Standard model selection techniques are shown to perform well for the sequence segmentation task. Segmentation evaluation is proposed with respect to a known segmentation structure. Applying segmentation on certain features of a sequence is shown to yield segmentations that are significantly close to the known underlying structure. Two extensions to the basic segmentation framework are introduced: unimodal segmentation and basis segmentation. The former is concerned with segmentations where the segment descriptions first increase and then decrease, and the latter with the interplay between different dimensions and segments in the sequence. These problems are formally defined and algorithms for solving them are provided and analyzed. Practical applications for segmentation techniques include time series and data stream analysis, text analysis, and biological sequence analysis. In this thesis segmentation applications are demonstrated in analyzing genomic sequences.

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.

Characterisation, cloning and production of industrially interesting enzymes: gluconolactone oxidase of Penicillium cyaneo-fulvum and gluconate 5-dehydrogenase of Gluconobacter suboxydans

The work covered in this thesis is focused on the development of technology for bioconversion of glucose into D-erythorbic acid (D-EA) and 5-ketogluconic acid (5-KGA). The task was to show on proof-of-concept level the functionality of the enzymatic conversion or one-step bioconversion of glucose to these acids. The feasibility of both studies to be further developed for production processes was also evaluated. The glucose - D-EA bioconversion study was based on the use of a cloned gene encoding a D-EA forming soluble flavoprotein, D-gluconolactone oxidase (GLO). GLO was purified from Penicillium cyaneo-fulvum and partially sequenced. The peptide sequences obtained were used to isolate a cDNA clone encoding the enzyme. The cloned gene (GenBank accession no. AY576053) is homologous to the other known eukaryotic lactone oxidases and also to some putative prokaryotic lactone oxidases. Analysis of the deduced protein sequence of GLO indicated the presence of a typical secretion signal sequence at the N-terminus of the enzyme. No other targeting/anchoring signals were found, suggesting that GLO is the first known lactone oxidase that is secreted rather than targeted to the membranes of the endoplasmic reticulum or mitochondria. Experimental evidence supports this analysis, as near complete secretion of GLO was observed in two different yeast expression systems. Highest expression levels of GLO were obtained using Pichia pastoris as an expression host. Recombinant GLO was characterised and the suitability of purified GLO for the production of D-EA was studied. Immobilised GLO was found to be rapidly inactivated during D-EA production. The feasibility of in vivo glucose - D-EA conversion using a P. pastoris strain co-expressing the genes of GLO and glucose oxidase (GOD, E.C. 1.1.3.4) of A. niger was demonstrated. The glucose - 5-KGA bioconversion study followed a similar strategy to that used in the D-EA production research. The rationale was based on the use of a cloned gene encoding a membrane-bound pyrroloquinoline quinone (PQQ)-dependent gluconate 5-dehydrogenase (GA 5-DH). GA 5-DH was purified to homogeneity from the only source of this enzyme known in literature, Gluconobacter suboxydans, and partially sequenced. Using the amino acid sequence information, the GA 5-DH gene was cloned from a genomic library of G. suboxydans. The cloned gene was sequenced (GenBank accession no. AJ577472) and found to be an operon of two adjacent genes encoding two subunits of GA 5-DH. It turned out that GA 5-DH is a rather close homologue of a sorbitol dehydrogenase from another G. suboxydans strain. It was also found that GA 5-DH has significant polyol dehydrogenase activity. The G. suboxydans GA 5-DH gene was poorly expressed in E. coli. Under optimised conditions maximum expression levels of GA 5-DH did not exceed the levels found in wild-type G. suboxydans. Attempts to increase expression levels resulted in repression of growth and extensive cell lysis. However, the expression levels were sufficient to demonstrate the possibility of bioconversion of glucose and gluconate into 5-KGA using recombinant strains of E. coli. An uncharacterised homologue of GA 5-DH was identified in Xanthomonas campestris using in silico screening. This enzyme encoded by chromosomal locus NP_636946 was found by a sequencing project of X. campestris and named as a hypothetical glucose dehydrogenase. The gene encoding this uncharacterised enzyme was cloned, expressed in E. coli and found to encode a gluconate/polyol dehydrogenase without glucose dehydrogenase activity. Moreover, the X. campestris GA 5-DH gene was expressed in E. coli at nearly 30 times higher levels than the G. suboxydans GA 5-DH gene. Good expressability of the X. campestris GA-5DH gene makes it a valuable tool not only for 5-KGA production in the tartaric acid (TA) bioprocess, but possibly also for other bioprocesses (e.g. oxidation of sorbitol into L-sorbose). In addition to glucose - 5-KGA bioconversion, a preliminary study of the feasibility of enzymatic conversion of 5-KGA into TA was carried out. Here, the efficacy of the first step of a prospective two-step conversion route including a transketolase and a dehydrogenase was confirmed. It was found that transketolase convert 5-KGA into TA semialdehyde. A candidate for the second step was suggested to be succinic dehydrogenase, but this was not tested. The analysis of the two subprojects indicated that bioconversion of glucose to TA using X. campestris GA 5-DH should be prioritised first and the process development efforts in future should be focused on development of more efficient GA 5-DH production strains by screening a more suitable production host and by protein engineering.

Phylogeography and Adaptive Divergence of Three-spined Stickleback Populations

Genetic studies on phylogeography and adaptive divergence in Northern Hemisphere fish species such as three-spined stickleback (Gasterosteus aculeatus) provide an excellent opportunity to investigate genetic mechanisms underlying population differentiation. According to the theory, the process of population differentiation results from a complex interplay between random and deterministic processes as well historical factors. The main scope in this thesis was to study how historical factors like the Pleistocene ice ages have shaped the patterns molecular diversity in three-spined stickleback populations in Europe and how this information could be utilized in the conservation genetic context. Furthermore, identifying footprints of natural selection at the DNA level might be used in identifying genes involved in evolutionary change. Overall, the results from phylogeographic studies indicate that the three-spined stickleback has colonized the Atlantic basin relatively recently but constitutes three major evolutionary lineages in Europe. In addition, the colonization of freshwater appears to result from multiple and independent invasions by the marine conspecifics. Molecular data together with morphology suggest that the most divergent freshwater populations are located in the Balkan Peninsula and these populations deserve a special conservation genetic status without warranting further taxonomical classification. In order to investigate the adaptive divergence in Fennoscandian three-spined stickleback populations several approaches were used. First, sequence variability in the Eda-gene, coding for the number of lateral plates, was concordant with the previously observed global pattern. Full plated allele is in high frequencies among marine populations whereas low plated allele dominates in the freshwater populations. Second, a microsatellite based genome scan identified both indications of balancing and directional selection in the three-spined stickleback genome, i.e. loci with unusually similar or unusually different allele frequencies over populations. The directionally selected loci were mainly associated with the adaptation to freshwater. A follow up study conducting a more detailed analysis in a chromosome region containing a putatively selected gene locus identified a fairly large genomic region affected by natural selection. However, this region contained several gene predictions, all of which might be the actual target of natural selection. All in all, the phylogeographic and adaptive divergence studies indicate that most of the genetic divergence has occurred in the freshwater populations whereas the marine populations have remained relatively uniform.

Gene Expression : From Microarrays to Functional Genomics

The time of the large sequencing projects has enabled unprecedented possibilities of investigating more complex aspects of living organisms. Among the high-throughput technologies based on the genomic sequences, the DNA microarrays are widely used for many purposes, including the measurement of the relative quantity of the messenger RNAs. However, the reliability of microarrays has been strongly doubted as robust analysis of the complex microarray output data has been developed only after the technology had already been spread in the community. An objective of this study consisted of increasing the performance of microarrays, and was measured by the successful validation of the results by independent techniques. To this end, emphasis has been given to the possibility of selecting candidate genes with remarkable biological significance within specific experimental design. Along with literature evidence, the re-annotation of the probes and model-based normalization algorithms were found to be beneficial when analyzing Affymetrix GeneChip data. Typically, the analysis of microarrays aims at selecting genes whose expression is significantly different in different conditions followed by grouping them in functional categories, enabling a biological interpretation of the results. Another approach investigates the global differences in the expression of functionally related groups of genes. Here, this technique has been effective in discovering patterns related to temporal changes during infection of human cells. Another aspect explored in this thesis is related to the possibility of combining independent gene expression data for creating a catalog of genes that are selectively expressed in healthy human tissues. Not all the genes present in human cells are active; some involved in basic activities (named housekeeping genes) are expressed ubiquitously. Other genes (named tissue-selective genes) provide more specific functions and they are expressed preferably in certain cell types or tissues. Defining the tissue-selective genes is also important as these genes can cause disease with phenotype in the tissues where they are expressed. The hypothesis that gene expression could be used as a measure of the relatedness of the tissues has been also proved. Microarray experiments provide long lists of candidate genes that are often difficult to interpret and prioritize. Extending the power of microarray results is possible by inferring the relationships of genes under certain conditions. Gene transcription is constantly regulated by the coordinated binding of proteins, named transcription factors, to specific portions of the its promoter sequence. In this study, the analysis of promoters from groups of candidate genes has been utilized for predicting gene networks and highlighting modules of transcription factors playing a central role in the regulation of their transcription. Specific modules have been found regulating the expression of genes selectively expressed in the hippocampus, an area of the brain having a central role in the Major Depression Disorder. Similarly, gene networks derived from microarray results have elucidated aspects of the development of the mesencephalon, another region of the brain involved in Parkinson Disease.