Detection and molecular epidemiology of tick-borne encephalitis virus infections

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Genomic alterations in Myeloproliferative Neoplasms and Myelodysplastic Syndromes

Myeloproliferative neoplasms (MPN) and myelodysplastic syndromes (MDS) are a heterogeneous group of clonal hematopoietic disorders whose etiology and molecular pathogenesis are poorly understood. During the past decade, enormous developments in microarray technology and bioinformatics methods have made it possible to mine novel molecular alterations in a large number of malignancies, including MPN and MDS, which has facilitated the detection of new prognostic, predictive and therapeutic biomarkers for disease stratification. By applying novel microarray techniques, we profiled copy number alterations and microRNA (miRNA) expression changes in bone marrow aspirate and blood samples. In addition, we set up and validated an miRNA expression test for bone marrow core biopsies in order to utilize the large archive material available in many laboratories. We also tested JAK2 mutation status and compare it with the in vitro growth pattern of hematologic progenitors cells. In the study focusing on 100 MPN cases, we detected a Janus kinase 2 (JAK2) mutation in 71 cases. We observed spontaneous erythroid colony growth in all mutation-positive cases in addition to nine mutation negative cases. Interestingly, seven JAK2V167F negative ET cases showed spontaneous megakaryocyte colony formation, one case of which also harbored a myeloproliferative leukemia virus oncogene (MPL) mutation. We studied copy number alterations in 35 MPN and 37 MDS cases by using oligonucleotide-based array comparative hybridization (array CGH). Only one essential thrombocythemia (ET) case presented copy number alterations in chromosomes 1q and 13q. In contrast, MDS cases were characterized by numerous novel cryptic chromosomal aberrations with the most common copy number losses at 5q21.3q33.1 and 7q22.1q33, while the most common copy number gain was trisomy 8. As for the study of the bone marrow core biopsy samples, we showed that even though these samples were embedded in paraffin and underwent decalcification, they were reliable sources of miRNA and suitable for array expression analysis. Further, when studying the miRNA expression profiles of the 19 MDS cases, we found that, compared to controls, two miRNAs (one human Epstein-Barr virus (miR-BART13) miRNA and one human (has-miR-671-5p) miRNA) were downregulated, whereas two other miRNAs (hsa-miR-720 and hsa-miR-21) were upregulated. However, we could find no correlation between copy number alterations and microRNA expression when integrating these two data. This thesis brings to light new information about genomic changes implicated in the development of MPN and MDS, and also underlines the power of applying genome-wide array screening techniques in neoplasias. Rapid advances in molecular techniques and the integration of different genomic data will enable the discovery of the biological contexts of many complex disorders, including myeloid neoplasias.

Change detection and controlling forest information using multi-temporal Landsat TM imagery.

A method was developed for relative radiometric calibration of single multitemporal Landsat TM image, several multitemporal images covering each others, and several multitemporal images covering different geographic locations. The radiometricly calibrated difference images were used for detecting rapid changes on forest stands. The nonparametric Kernel method was applied for change detection. The accuracy of the change detection was estimated by inspecting the image analysis results in field. The change classification was applied for controlling the quality of the continuously updated forest stand information. The aim was to ensure that all the manmade changes and any forest damages were correctly updated including the attribute and stand delineation information. The image analysis results were compared with the registered treatments and the stand information base. The stands with discrepancies between these two information sources were recommended to be field inspected.

Microbial identification by detection of ligation probes on DNA microarray

Microbes in natural and artificial environments as well as in the human body are a key part of the functional properties of these complex systems. The presence or absence of certain microbial taxa is a correlate of functional status like risk of disease or course of metabolic processes of a microbial community. As microbes are highly diverse and mostly notcultivable, molecular markers like gene sequences are a potential basis for detection and identification of key types. The goal of this thesis was to study molecular methods for identification of microbial DNA in order to develop a tool for analysis of environmental and clinical DNA samples. Particular emphasis was placed on specificity of detection which is a major challenge when analyzing complex microbial communities. The approach taken in this study was the application and optimization of enzymatic ligation of DNA probes coupled with microarray read-out for high-throughput microbial profiling. The results show that fungal phylotypes and human papillomavirus genotypes could be accurately identified from pools of PCR amplicons generated from purified sample DNA. Approximately 1 ng/μl of sample DNA was needed for representative PCR amplification as measured by comparisons between clone sequencing and microarray. A minimum of 0,25 amol/μl of PCR amplicons was detectable from amongst 5 ng/μl of background DNA, suggesting that the detection limit of the test comprising of ligation reaction followed by microarray read-out was approximately 0,04%. Detection from sample DNA directly was shown to be feasible with probes forming a circular molecule upon ligation followed by PCR amplification of the probe. In this approach, the minimum detectable relative amount of target genome was found to be 1% of all genomes in the sample as estimated from 454 deep sequencing results. Signal-to-noise of contact printed microarrays could be improved by using an internal microarray hybridization control oligonucleotide probe together with a computational algorithm. The algorithm was based on identification of a bias in the microarray data and correction of the bias as shown by simulated and real data. The results further suggest semiquantitative detection to be possible by ligation detection, allowing estimation of target abundance in a sample. However, in practise, comprehensive sequence information of full length rRNA genes is needed to support probe design with complex samples. This study shows that DNA microarray has the potential for an accurate microbial diagnostic platform to take advantage of increasing sequence data and to replace traditional, less efficient methods that still dominate routine testing in laboratories. The data suggests that ligation reaction based microarray assay can be optimized to a degree that allows good signal-tonoise and semiquantitative detection.