Biofuels have been proposed to be a suitable replacement to the already depleting fossil fuels. The complex structures of plant biomasses present a challenge the production of biofuels due to recalcitrance. The complex cellulose structure and hydrogen bonding between repeat units of cellulose is believed to be a major contributor to the recalcitrance of cellulose. Fungal organisms come equipped with various oxidative enzymes involved in degradation of plant biomass. The exact mechanism of cellulose degradation remains elusive. The GH61 is a group of proteins which are PMOs. GH61 sequences where previously described as endoglucanases due to weak endoglucanase activity. These enzymes were later found not possess any enzyme activity of their own however they could enhance the activity of other cellulose degrading enzymes. As a result reclassification of these enzymes as AA9 has been implemented. AA9 proteins have been reported to share structural homology with the bacterial AA10 group of enzymes. Based on cleavage products that are produced when AA9 proteins interact with cellulose, AA9 proteins have been grouped into three types. To date the exact mechanism and the sequence and structural basis for differentiating between the various AA9 types remains unknown. Using various bionformatic techniques sequence and structural elements were identified for distinguishing between the AA9 types. A large dataset of sequences was obtained from the Pfam database from UNIPROT entries. Due to high divergence of AA9 sequences, a smaller dataset with the more divergent sequences removed was created. The inclusion of the reference sequences to the data set was done to observe which sequences belong to a certain type. Phylogenetic analysis was able to group AA9 proteins into three distinct groups. MSA and motif analysis revealed that the N-Terminus of these proteins is mostly responsible for type specificity. Structural analysis of AA9 PDB structures and homology models allowed the effect of physicochemical properties to be gauged structurally. The presence of 310 helices and aromatic residues the surface of AA9 sequences is an observation which still warrants further investigation.

Philosophiae Doctor - PhD / End stage renal disease (ESRD), a more severe form of kidney disease, is considered to be a complex trait that may involve multiple processes which work together on a background of a significant genetic susceptibility. Black Africans have been shown to bear an unequal burden of this disease compared to white Europeans, Americans and Caucasians. Despite this, most of the genetic and epidemiological advances made in understanding the aetiology of kidney diseases have been done in other populations outside of sub-Saharan Africa (SSA). Very little research has been undertaken to investigate key genetic factors that drive ESRD in Africans compared to patients from rest of world populations. Therefore, the primary aim of this Bioinformatics thesis was twofold: firstly, to develop and apply a whole exome sequencing (WES) analysis pipeline and use it to understand a genetic mechanism underlying ESRD in a South African population of mixed ancestry. As I hypothesized that the pipeline would enable the discovery of highly penetrate rare variants with large effect size, which are expected to explain an important fraction of the genetic aetiology and pathogenesis of ESRD in these African patients. Secondly, the aim was to develop and set up a multicenter clinical database that would capture a plethora of clinical data for patients with Lupus, one of the risk factors of ESRD. From WES of six family members (five cases and one control); a total of 23 196 SNVs, 1445 insertions and 1340 deletions, overlapped amongst all affected family members. The variants were consistent with an autosomal dominant inheritance pattern inferred in this family. Of these, only 1550 SNVs, 67 insertions and 112 deletions were present in all affected family members but absent in the unaffected family member. Following detailed evaluation of evidence for variant implication and pathogenicity, only 3 very rare heterozygous missense variants in 3 genes COL4A1 [p.R476W], ICAM1 [p.P352L], COL16A1 [p.T116M] were considered potentially disease causing. Computational relatedness analysis revealed approximate amount of DNA shared by family members and confirmed reported relatedness. Genotyping for the Y chromosome was additionally performed to assist in sample identity. The clinical database has been designed and is being piloted at Groote Schuur medical Hospital at the University of Cape Town. Currently, about 290 patients have already been entered in the registry. The resources and methodologies developed in this thesis have the potential to contribute not only to the understanding of ESRD and its risk factors, but to the successful application of WES in clinical practice. Importantly, it contributes significant information on the genetics of ESRD based on an African family and will also improve scientific infrastructure on the African continent. Clinical databasing will go a long way to enable clinicians to collect and store standardised clinical data for their patients.

The thesis deals with bioinformatics analysis, the aim of which was to find a suitable producer of PHA for new generation industrial biotechnologies from the collection of found thermophilic bacteria. Part of experiments was the finding of several thermophilic bacteria based on the similarity of the protein sequence of the phaC gene of the bacterium Cupriavidus necator. The next part of thesis was a literature search of the abilities of these thermophilic bacteria focused on culture conditions and the spectrum of usable substrates. Subsequently, five bacteria were selected for use in NGBI based on the information obtained. Freely available databases were used during the experimental work, and evolutionary analysis were performed in MEGA X and Operon-mapper. Rubrobacter xylanophilus with collection number DSM 9941 was selected from the collection of bacterial strains as the most promising PHA producer for NGIB. The high culture temperature of up to 70 ° C and a large amount of utilized carbohydrate substrates were considered decisive. An interesting result of the analysis was to find the gene sequences of two classes of PHA synthase – I. and III. class, as for a single bacterial strain from the entire collection. Additional genes linked to PHA metabolism were found in genome analysis.

In the food industry, it is very important to take care of the quality, safety and organoleptic properties of the products supplied. For this reason, food must be checked. However, not all information can be found using conventional techniques such as immunoassays, chromatographic techniques, etc. DNA-based techniques can be used for these cases where traditional procedures are insufficient. Among them, the best known technique is PCR. The aim of the thesis was to isolate DNA from vegetable samples (broccoli, beetroot, carrot and pepper). DNA was isolated using the magnetic particle method and the traditional CTAB method. Both methods were able to isolate the DNA from the vegetable samples in quality and at a concentration suitable for PCR, where the 35S rDNA gene region was amplified (more precisely about 700 bp of the 18S-ITS1-5,8S region). After amplification, the PCR products were subjected to restriction reactions and the results compared to bioinformatic analysis. These steps have succeeded in finding suitable enzymes for diferentiation of PCR products from the tested vegetable species.

Local DNA structures are alternative DNA conformations which can be formed aside from typical B-DNA conformation. These structures often play pivotal roles in regulation of basic biological processes, such as DNA replication, transcription or binding of specific ligands. This biological significance makes alternative DNA secondary structures a potential drug target. In this diploma thesis, local structures in genomes of viruses from Flaviviridae and Retroviridae families are analysed using bioinformatics tools. Furthermore, these structures are visualised using atomic force microscopy.

Cancer the second most common causes of death in the Czech Republic. Carriers of mutations in genes predisposing to hereditary cancers represent a small but clinically significant group of high risk individuals. Today, dozens of predisposing genes for hereditary tumor syndromes are known and targeted next generation sequencing (NGS) has become a standard approach for their analysis. NGS allows rapid acceleration diagnostics of causal mutation in high-risk individuals. To identify mutations in genes predisposing to hereditary cancers, we designed a panel NGS analysis including subsequent bioinformatics analysis allowing a reliable identification of single nucleotide variants, insertions/deletions, and large intragenic rearrangements. The bioinformatics procedures described in this thesis were used for panel NGS validation, but also for identification of alterations associating with so far undescribed hereditary tumor types. Bioinformatics analyzes have become the basis for the unified processing of large datasets from the CZECANCA consortium and enable the construction of a population-specific database of genotypes that serve to improve clinical diagnostics of cancer predisposition in Czech patients. The versatility of NGS also allows its use for RNA (cDNA-based) analyzes of splicing variants in the...

Rare diseases represent a heterogeneous group of more than ~7000 different diseases, affecting 3,5-5,9% of the global population. Most rare diseases are genetic, but causal genes are known only in some of them. Many patients with rare diseases remain without a diagnosis, which is crucial for genetic counseling, prevention, and treatment. With the development of new methods of genome analysis, decreasing cost of sequencing, and increasing knowledge of the human genome, a new concept for identifying disease-causing genes was established. It is based on comparing the patient's genetic variability with the genetic variability of the general population. This dissertation describes next-generation sequencing technologies (NGS), bioinformatic analysis of acquired data and their applications in the elucidation of molecular underpinnings of rare genetic diseases. These procedures have led to the identification and characterization of causal genes and gene mutations in autosomal dominant tubulointerstitial kidney disease (SEC61A1, MUC1), autosomal dominant neuronal ceroid lipofuscinosis (CLN6, DNAJC5), neurodegenerative disease of unknown etiology (VPS15), Acadian variant of Fanconi syndrome (NDUFAF6) and spinal muscular atrophy (SMN1). The application of novel genome analysis techniques increased the...

The field of cancer genomics is currently being enhanced by the power of Epigenome-wide association studies (EWAS). Over the last couple of years comprehensive sequence data sets have been generated, allowing analysis of genome-wide activity in cohorts of different individuals to be increasingly available. Finding associations between epigenetic variation and phenotype is one of the biggest challenges in biomedical research. Laboratories lacking dedicated resources and programming experience require bioinformatics expertise which can be prohibitively costly and time-consuming. To address this, we have developed a collection of freely available Galaxy tools (Poterlowicz, 2018a), combining analytical methods into a range of convenient analysis pipelines with graphical user-friendly interface.The tool suite includes methods for data preprocessing, quality assessment and differentially methylated region and position discovery. The aim of this project was to make EWAS analysis flexible and accessible to everyone and compatible with routine clinical and biological use. This is exemplified by my work undertaken by integrating DNA methylation profiles of melanoma patients (at baseline and mitogen-activated protein kinase inhibitor MAPKi treatment) to identify novel epigenetic switches responsible for tumour resistance to therapy (Hugo et al., 2015). Configuration files are publicly published on our GitHub repository (Poterlowicz, 2018b) with scripts and dependency settings also available to download and install via Galaxy test toolshed (Poterlowicz, 2018a). Results and experiences using this framework demonstrate the potential for Galaxy to be a bioinformatics solution for multi-omics cancer biomarker discovery tool.

Background: A hallmark of Notch signaling is its variable role in tumor biology, ranging from tumor-suppressive to oncogenic effects. Until now, the mechanisms and functions of Notch pathways in bladder cancer (BCa) are still unclear. Methods: We used publicly available data from the GTEx and TCGA-BLCA databases to explore the role of the canonical Notch pathways in BCa on the basis of the RNA expression levels of Notch receptors, ligands, and downstream genes. For statistical analyses of cancer and non-cancerous samples, we used R software packages and public databases/webservers. Results: We found differential expression between control and BCa samples for all Notch receptors (NOTCH1, 2, 3, 4), the delta-like Notch ligands (DLL1, 3, 4), and the typical downstream gene hairy and enhancer of split 1 (HES1). NOTCH2/3 and DLL4 can significantly differentiate non-cancerous samples from cancers and were broadly altered in subgroups. High expression levels of NOTCH2/3 receptors correlated with worse overall survival (OS) and shorter disease-free survival (DFS). However, at long-term (>8 years) follow-up, NOTCH2 expression was associated with a better OS and DFS. Furthermore, the cases with the high levels of DLL4 were associated with worse OS but improved DFS. Pathway network analysis revealed that NOTCH2/3 in particular correlated with cell cycle, epithelial–mesenchymal transition (EMT), numbers of lymphocyte subtypes, and modulation of the immune system. Conclusions: NOTCH2/3 and DLL4 are potential drivers of Notch signaling in BCa, indicating that Notch and associated pathways play an essential role in the progression and prognosis of BCa through directly modulating immune cells or through interaction with cell cycle and EMT.

Bladder cancer (BCa) is one of the most common malignancies and has a relatively poor outcome worldwide. However, the molecular mechanisms and processes of BCa development and progression remain poorly understood. Therefore, the present study aimed to identify candidate genes in the carcinogenesis and progression of BCa. Five GEO datasets and TCGA-BLCA datasets were analyzed by statistical software R, FUNRICH, Cytoscape, and online instruments to identify differentially expressed genes (DEGs), to construct protein‒protein interaction networks (PPIs) and perform functional enrichment analysis and survival analyses. In total, we found 418 DEGs. We found 14 hub genes, and gene ontology (GO) analysis revealed DEG enrichment in networks and pathways related to cell cycle and proliferation, but also in cell movement, receptor signaling, and viral carcinogenesis. Compared with noncancerous tissues, TPM1, CRYAB, and CASQ2 were significantly downregulated in BCa, and the other hub genes were significant upregulated. Furthermore, MAD2L1 and CASQ2 potentially play a pivotal role in lymph nodal metastasis. CRYAB and CASQ2 were both significantly correlated with overall survival (OS) and disease-free survival (DFS). The present study highlights an up to now unrecognized possible role of CASQ2 in cancer (BCa). Furthermore, CRYAB has never been described in BCa, but our study suggests that it may also be a candidate biomarker in BCa.