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Microarray-based single nucleotide polymorphism (SNP) genotyping enables simultaneous and rapid detection of a large number of markers and is thus an attractive method for forensic individual acid identification. This assay relies on a one-color detection system and minisequencing in solution before hybridization to universal tag arrays. The minisequencing reaction is based on incorporation of a fluorescent dideoxynucleotide to a primer containing a tag-sequence flanking the position to be interrogated. This one-color system detects C and T polymorphisms in separate reactions on multiple polymerase chain reaction targets with the fluorophore TAMRA coupled to the respective dideoxynucleotide. After incorporation, tagged primer sequences are hybridized through their complementary sequence on the array, and positive signals are detected by a confocal laser-scanner.

In this study a description is given of the sequence and analysis of 52 kb from the 1.1 Mb genome of Rickettsia prowazekii, a member of the alpha-Proteobacteria. An investigation was made of nucleotide frequencies and amino acid composition patterns of 41 coding sequences, distributed in 10 genomic contigs, of which 32 were found to have putative homologues in the public databases. Overall, the coding content of the individual contigs ranged from 59 to 97%, with a mean of 81%. The genes putatively identified included genes involved in the biosynthesis of nucleotides, macromolecules and cell wall structures as well as citric acid cycle component genes. In addition, a putative identification was made of a member of the regulatory response family of two-component signal transduction systems as well as a gene encoding haemolysin. For one gene, the homologue of metK, an internal stop codon was discovered within a region that is otherwise highly conserved. Comparisons with the genomic structures of Escherichia coli, Haemophilus influenzae and Bacillus subtilis have revealed several atypical gene organization patterns in the R. prowazekii genome. For example, R. prowazekii was found to have a unique arrangement of genes upstream of dnaA in a region that is highly conserved among other microbial genomes and thought to represent the origin of replication of a primordial replicon. The results presented in this paper support the hypothesis that the R. prowazekii genome is a highly derived genome and provide examples of gene order structures that are unique for the Rickettsia.

We describe here the complete genome sequence (1,111,523 base pairs) of the obligate intracellular parasite Rickettsia prowazekii, the causative agent of epidemic typhus. This genome contains 834 protein-coding genes. The functional profiles of these genes show similarities to those of mitochondrial genes: no genes required for anaerobic glycolysis are found in either R. prowazekii or mitochondrial genomes, but a complete set of genes encoding components of the tricarboxylic acid cycle and the respiratory-chain complex is found in R. prowazekii. In effect, ATP production in Rickettsia is the same as that in mitochondria. Many genes involved in the biosynthesis and regulation of biosynthesis of amino acids and nucleosides in free-living bacteria are absent from R. prowazekii and mitochondria. Such genes seem to have been replaced by homologues in the nuclear (host) genome. The R. prowazekii genome contains the highest proportion of non-coding DNA (24%) detected so far in a microbial genome. Such non-coding sequences may be degraded remnants of 'neutralized' genes that await elimination from the genome. Phylogenetic analyses indicate that R. prowazekii is more closely related to mitochondria than is any other microbe studied so far.

Many mutations in rpsL cause resistance to, or dependence on, streptomycin and are restrictive (hyperaccurate) in translation. Dependence on streptomycin and hyperaccuracy can each be reversed phenotypically by mutations in either rpsD or rpsE. Such compensatory mutations have been shown to have a ram phenotype (ribosomal ambiguity), increasing the level of translational errors. We have shown recently that restrictive rpsL alleles are also associated with a loss of virulence in Salmonella typhimurium. To test whether ram mutants could reverse this loss of virulence, we have isolated a set of rpsD alleles in Salmonella typhimurium. We found that the rpsD alleles restore the virulence of strains carrying restrictive rpsL alleles to a level close to that of the wild type. Unexpectedly, three out of seven mutant rpsD alleles tested have phenotypes typical of restrictive alleles of rpsL, being resistant to streptomycin and restrictive (hyperaccurate) in translation. These phenotypes have not been previously associated with the ribosomal protein S4. Furthermore, all seven rpsD alleles (four ram and three restrictive) can phenotypically reverse the hyperaccuracy associated with restrictive alleles of rpsL. This is the first demonstration that such compensations do not require that the compensating rpsD allele has a ribosomal ambiguity (ram) phenotype.

It has been suggested from in vivo and cryoelectron micrographic studies that the large ribosomal subunit protein L11 and its N-terminal domain play an important role in peptide release by, in particular, the class I release factor RF1. In this work, we have studied in vitro the role of L11 in translation termination with ribosomes from a wild type strain (WT-L11), an L11 knocked-out strain (ΔL11), and an L11 N terminus truncated strain (Cter-L11). Our data show 4-6-fold reductions in termination efficiency (k_cat/K_m) of RF1, but not of RF2, on ΔL11 and Cter-L11 ribosomes compared with wild type. There is, at the same time, no effect of these L11 alterations on the maximal rate of ester bond cleavage by either RF1 or RF2. The rates of dissociation of RF2 but not of RF1 from the ribosome after peptide release are somewhat reduced by the L11 changes irrespective of the presence of RF3, and they cause a 2-fold decrease in the missense error. Our results suggest that the L11 modifications increase nonsense suppression at UAG codons because of the reduced termination efficiency of RF1 and that they decrease nonsense suppression at UGA codons because of a decreased missense error level.

The cellulase mixture of Hypocrea jecorina (formerly Trichoderma reesei) contains a variety of exo- and endoglucanases that belong to different structural families. As such, these enzymes form an interesting model system to study the enzyme-ligand interactions in glycoside hydrolases. The nucleophilic carboxylate of retaining -glycosidases is believed to form a hydrogen bond with the 2-hydroxyl group of their substrate. Consequently, replacing this hydroxyl group with an amino group should result in a stronger electrostatic interaction and thus an increased affinity for the ligand. In this study, several modified cellobiosides were synthesized and evaluated as cellulase inhibitors. The introduction of an amino group was found to have an unpredictable effect on the inhibitory power of the ligands. However, the enzymes display a very high affinity for the corresponding 2-azido compounds, precursors in the synthetic route. The new ligand m-iodobenzyl 2-deoxy-2-azido--cellobioside even is the strongest inhibitor of cellobiohydrolase I known to date (KI= 1 M).

Forensic DNA analysis is routinely performed using polymorphic short tandem repeat (STR) markers. However, for degraded or minute DNA samples, analysis of autosomal single nucleotide polymorphisms (SNPs) in short fragments might be more successful. Furthermore, sequencing of mitochondrial DNA (mtDNA) is often performed on highly degraded or scarce samples due to the high copy number of mtDNA in each cell. Due to the increasing number of complete mtDNA genome sequences available, the limited discrimination power of an mtDNA analysis, may be increased by analysis of coding region polymorphisms in addition to the non-coding variation. Since sequence analysis of the coding region would require more material than generally present in forensic samples, an alternative SNP analysis approach is required. We have developed a one-colour microarray-based SNP detection system for limited forensic materials. The method is based on minisequencing in solution prior to hybridisation to universal tag-arrays. In a first outline of a forensic chip, a combination of 12 nuclear and 21 mitochondrial SNP markers are analysed simultaneously. The mitochondrial markers on the chip are polymorphisms within the hypervariable region as well as in the coding region. Even though the number of markers in the current system is limited, it can easily be extended to yield a greater power of discrimination. When fully developed, microarray analysis provides a promising system for efficient sensitive SNP analysis of forensic samples in the future.

The mitochondrial hypervariable regions I and II have proven to be a useful target for analysis of forensic materials, in which the amount of DNA is limited or highly degraded. Conventional mitochondrial DNA (mtDNA) sequencing can be time-consuming and expensive, limitations that can be minimized using a faster and less expensive typing assay. We have evaluated the exclusion capacity of the linear array mtDNA HVI/HVII region-sequence typing assay (Roche Applied Science) in 16 forensic cases comprising 90 samples. Using the HVI/HVII mtDNA linear array, 56% of the samples were excluded and thus less than half of the samples require further sequencing due to a match or inconclusive results. Of all the samples that were excluded by sequence analysis, 79% could be excluded using the HVI/HVII linear array alone. Using the HVI/HVII mtDNA linear array assay, we demonstrate the potential to decrease sequencing efforts substantially and thereby reduce the cost and the turn-around time in casework analysis.

We have studied the expression of 4.5 S RNA and Fv Il RNA, the catalytic subunit of Escherchia coli RNase P, under various growth conditions. Both RNA species increase in abundance as a function of growth rate. There are roughly 450 molecules of 4.5 S RNA and 80 molecules of M1 RNA per cell at 0.4 doubling per hour, and this is increased to 5300 and 1060 molecules per cell, respectively, at 2.7 doublings per hour. Deletion of both relA and spoT, the two genes that are responsible for synthesis of ppGpp, does not affect the rate of synthesis of either RNA species. However, deletion of fis renders the expression of 4.5 S RNA independent of growth rate, but has little effect on the expression of M1 RNA. These data suggest that the expression of both 4.5 S RNA and M1 RNA genes are growth-rate regulated, but not through the same mechanism. The growth-rate dependent accumulation of 4.5 S RNA depends on FIS-mediated trans-activation, whereas that of M1 RNA is not governed by ppGpp or by FIS.

Molecular biology emerged through unification of genetics and nucleic acid chemistry that took place with the discovery of the double helix (Watson and Crick 1953). Accordingly, molecular biology could be defined as the sum of all techniques used to perform genetic experiments by manipulating DNA. One consequence of the development of these techniques is large-scale sequencing of genomes from an ever increasing number of organisms. However, it became clear from this development that genetic information per se is not enough to grasp the most interesting functional and evolutionary aspects of cells and multi-cellular organisms. In fact, understanding how genotype leads to phenotype depends on concepts and techniques from areas that so far have been largely alien to molecular biological research, like physics, mathematics, and engineering. From the bits and pieces from these and other scientific fields new tools must be generated to make possible an understanding of the dynamic, adapting, and developing living systems that somehow take shape from the instructions given by their genomes. The growing total of these tools and their integration in experimental and theoretical approaches to understand complex biological processes in ways previously out of reach could be a way to define systems biology, in analogy with the above definition of molecular biology.

Implementation and analysis of mathematical models can serve as a powerful tool in understanding how intracellular processes in bacteria affect the bacterial phenotype. In this thesis I have implemented and analysed models of a number of different parts of the bacterium E. coli in order to understand these types of connections. I have also developed new tools for analysis of stochastic reaction-diffusion models.

Resistance mutations in the E. coli ribosomes make the bacteria less susceptible to treatment with the antibiotic drug erythromycin compared to bacteria carrying wildtype ribosomes. The effect is dependent on efficient drug efflux pumps. In the absence of pumps for erythromycin, there is no difference in growth between wildtype and drug target resistant bacteria. I present a model explaining this unexpected phenotype, and also give the conditions for its occurrence.

Stochastic fluctuations in gene expression in bacteria, such as E. coli, result in stochastic fluctuations in biosynthesis pathways. I have characterised the effect of stochastic fluctuations in the parallel biosynthesis pathways of amino acids. I show how the average protein synthesis rate decreases with an increasing number of fluctuating amino acid production pathways. I further show how the cell can remedy this problem by using sensitive feedback control of transcription, and by optimising its expression levels of amino acid biosynthetic enzymes.

The pole-to-pole oscillations of the Min-proteins in E. coli are required for accurate mid-cell division. The phenotype of the Min-oscillations is altered in three different mutants: filamentous cells, round cells and cells with changed membrane lipid composition. I have shown that the wildtype and mutant phenotypes can be explained using a stochastic reaction-diffusion model.

In E. coli, the transcription elongation rate on the ribosmal RNA operon increases with increasing transcription initiation rate. In addition, the polymerase density varies along the ribosomal RNA operons. I present a DNA sequence dependent model that explains the transcription elongation rate speed-up, and also the density variation along the ribosomal operons. Both phenomena are explained by the RNA polymerase backtracking on the DNA.