The use of existing medications for diseases they were not originally developed for is called drug repositioning. A popular drug repositioning method to find new drugs against specific cancer types... Show moreThe use of existing medications for diseases they were not originally developed for is called drug repositioning. A popular drug repositioning method to find new drugs against specific cancer types is to search for drugs which are expected to bring back the gene expression activity of cancer cells to that of healthy cells (‘normalization’). One of the main research goals of this thesis was to investigate of this method could also be used on the gene expression profiles of individual tumors, enabling personalization of drug repositioning candidates for each patient. We initially had some success with this approach but this eventually lead to a systematic validation of the underlying principle using almost 10,000 tumor samples across 18 different tumor types. Unfortunately, the predictive power of the method was found to be much lower than previously reported and the part that remained could be nullified by correcting the gene expression profiles of the drugs for the downstream effects of reduced cell division. These results indicate that the current use of the method does not result in drug repositioning candidates specific for a tumor type but is only able to select generally cell-toxic drugs. Show less
Metagenomics enables the detection of all the genetic material of organisms present in a sample, making it a pathogen-agnostic approach for detecting common and rare or novel pathogens that are not... Show moreMetagenomics enables the detection of all the genetic material of organisms present in a sample, making it a pathogen-agnostic approach for detecting common and rare or novel pathogens that are not included in conventional testing. Beforehand, a clinician does not need to have a hypothesis of what pathogen is expected, unlike traditional polymerase chain reaction (PCR) testing.This thesis is focusing on diagnostic yield, clinical findings, and enhancing technical opportunities in viral metagenomics. The identification, typing, and quantification of viruses by means of viral metagenomics as a diagnostic tool are evaluated. Technical aspects are appraised for improved sensitivity and specificity of the wet and dry (bioinformatic) lab components of viral metagenomics. The use of a metagenomic protocol for virus discovery directly in a patient sample is assessed, and the best methods and approaches for performing genetic analysis of the SARS-CoV-2 virus are investigated.Viral metagenomic testing results in the identification of more viruses, therefore it is a valuable addition to current diagnostic test protocols. Additionally, it is a useful test for virus discovery and monitoring during infectious disease outbreaks caused by novel viruses. Show less
Varunjikar, M.S.; Bohn, T.; Sanden, M.; Belghit, I.; Pineda-Pampliega, J.; Palmblad, M.; ... ; Rasinger, J.D. 2023
The present study compared genetically modified (GM) crops with crops from different farming practices using high-resolution tandem mass spectrometry (HR-MS) and proteomics bioinformatics tools. In... Show moreThe present study compared genetically modified (GM) crops with crops from different farming practices using high-resolution tandem mass spectrometry (HR-MS) and proteomics bioinformatics tools. In a previously pub-lished study, a number of significant differences regarding nutritional and elemental composition between a selection of GM, non-GM conventionally farmed, and organic soybeans have been found. In the present study, the proteome-level equivalence of the same samples was assessed using HR-MS. Direct comparison of tandem mass spectra and bottom-up proteomics bioinformatics indicated that proteomes of all samples investigated were very similar overall, with only a few distinct protein expression clusters obtained for GM and organic samples. Standard bottom-up proteome analyses identified 1025 soy proteins; of these 39 were found to be differentially expressed (p < 0.01) between GM, non-GM conventionally farmed, and organically farmed soybeans. Subsequent bioinformatics analyses of these proteins highlighted several potentially affected biochemical pathways that could contribute to the compositional differences reported earlier. In addition, protein markers separating conventionally, and organically farmed soybean seeds were found and peptide markers for the detection of GM soy in food and feed samples are described. Taken together, the data presented here shows that HR-MS based proteomics approaches can be used for the detection of transgenic events in food and feed grade soy, the dif-ferentiation of organically and conventionally farmed plants, and provide mechanistic explanations of effects observed on the phenotypic level of GM plants. HR-MS and proteomic bioinformatics thus should be considered key tools when developing molecular panel approaches for detection and safety assessments of novel crop va-rieties destined for use in feed and food. Show less
Transcriptome signature reversion (TSR) has been extensively proposed and used to discover new indications for existing drugs (i.e. drug repositioning, drug repurposing) for various cancer types.... Show moreTranscriptome signature reversion (TSR) has been extensively proposed and used to discover new indications for existing drugs (i.e. drug repositioning, drug repurposing) for various cancer types. TSR relies on the assumption that a drug that can revert gene expression changes induced by a disease back to original, i.e. healthy, levels is likely to be therapeutically active in treating the disease. Here, we aimed to validate the concept of TSR using the PRISM repurposing data set, which is-as of writing-the largest pharmacogenomic data set. The predictive utility of the TSR approach as it has currently been used appears to be much lower than previously reported and is completely nullified after the drug gene expression signatures are adjusted for the general anti-proliferative downstream effects of drug-induced decreased cell viability. Therefore, TSR mainly relies on generic anti-proliferative drug effects rather than on targeting cancer pathways specifically upregulated in tumor types. Show less
Velden, J. van der; Asselbergs, F.W.; Bakkers, J.; Batkai, S.; Bertrand, L.; Bezzina, C.R.; ... ; Thum, T. 2022
Cardiovascular diseases represent a major cause of morbidity and mortality, necessitating research to improve diagnostics, and to discover and test novel preventive and curative therapies. All of... Show moreCardiovascular diseases represent a major cause of morbidity and mortality, necessitating research to improve diagnostics, and to discover and test novel preventive and curative therapies. All of which warrant experimental models that recapitulate human disease. The translation of basic science results to clinical practice is a challenging task. In particular for complex conditions such as cardiovascular diseases, which often result from multiple risk factors and co-morbidities. This difficulty might lead some individuals to question the value of animal research, citing the translational 'valley of death', which largely reflects the fact that studies in rodents are difficult to translate to humans. This is also influenced by the fact that new, human-derived in vitro models can recapitulate aspects of disease processes. However, it would be a mistake to think that animal models cannot provide a vital step in the translational pathway as they do provide important pathophysiological insights into disease mechanisms particularly on a organ and systemic level. While stem cell-derived human models have the potential to become key in testing toxicity and effectiveness of new drugs, we need to be realistic, and carefully validate all new human-like disease models. In this position paper, we highlight recent advances in trying to reduce the number of animals for cardiovascular research ranging from stem cell-derived models to in situ modelling of heart properties, bioinformatic models based on large datasets, and improved current animal models, which show clinically relevant characteristics observed in patients with a cardiovascular disease. We aim to provide a guide to help researchers in their experimental design to translate bench findings to clinical routine taking the replacement, reduction and refinement (3R) as a guiding concept. Show less
Purpose The aim of this observational radiographic and proteomic study is to explore the influence of both Modic change (MC) and endplate avulsion (EPA) on the inflammation profile of herniated... Show morePurpose The aim of this observational radiographic and proteomic study is to explore the influence of both Modic change (MC) and endplate avulsion (EPA) on the inflammation profile of herniated discs using a proteomic and bioinformatics approach. Methods Fifteen nucleus pulposus (NP) harvested from surgery underwent LC-MS/MC analysis, the proteome was subsequently scanned for inflammatory pathways using a bioinformatics approach. All proteins that were identified in inflammatory pathways and Gene Ontology and present in > 7 samples were integrated in a multiple regression analysis with MC and EPA as predictors. Significant proteins were imputed in an interaction and pathway analysis. Results Compared to annulus fibrosus tear (AFT), six proteins were significantly altered in EPA: catalase, Fibrinogen beta chain, protein disulfide-isomerase, pigment epithelium-derived factor, osteoprotegerin and lower expression of antithrombin-III, all of which corresponded to an upregulation of pathways involved in coagulation and detoxification of reactive oxygen species (ROS). Moreover, the presence of MC resulted in a significant alteration of nine proteins compared to patients without MC. Patients with MC showed a significantly higher expression of clusterin and lumican, and lower expression of catalase, complement factor B, Fibrinogen beta chain, protein disulfide-isomerase, periostin, Alpha-1-antitrypsin and pigment epithelium-derived factor. Together these altered protein expressions resulted in a downregulation of pathways involved in detoxification of ROS, complement system and immune system. Results were verified by Immunohistochemistry with CD68 cell counts. Conclusion Both EPA and MC status significantly influence disc inflammation. The beneficial inflammatory signature of EPA illustrates that endplate pathology does not necessarily have to worsen the outcome, but the pathological inflammatory state is dependent on the presence of MC. Show less
Immunotherapy approach to cancer is only benefiting to a minority of patients. In this study, we approach cancer solutions by studying the microenvironment and its immunological signature... Show moreImmunotherapy approach to cancer is only benefiting to a minority of patients. In this study, we approach cancer solutions by studying the microenvironment and its immunological signature throughout the body by focusing on the systemic immunity with new technology like mass cytometry. By highlighting specific immunological patterns in cancer, we were able to associate responsive immune cells and positive outcome, therefore paving the way to improve immunotherapy in cancer. Show less
Metagenomic next-generation sequencing (mNGS) is an untargeted technique for determination of microbial DNA/RNA sequences in a variety of sample types from patients with infectious syndromes. mNGS... Show moreMetagenomic next-generation sequencing (mNGS) is an untargeted technique for determination of microbial DNA/RNA sequences in a variety of sample types from patients with infectious syndromes. mNGS is still in its early stages of broader translation into clinical applications. To further support the development, implementation, optimization and standardization of mNGS procedures for virus diagnostics, the European Society for Clinical Virology (ESCV) Network on Next-Generation Sequencing (ENNGS) has been established. The aim of ENNGS is to bring together professionals involved in mNGS for viral diagnostics to share methodologies and experiences, and to develop application guidelines. Following the ENNGS publication Recommendations for the introduction of mNGS in clinical virology, part I: wet lab procedure in this journal, the current manuscript aims to provide practical recommendations for the bioinformatic analysis of mNGS data and reporting of results to clinicians. Show less
The use of data derived from genomics and transcriptomic to further develop our understanding of Polycystic Kidney Diseases and identify novel drugs for its treatment.
Neurodegenerative diseases are hallmarked by protein inclusions and cell loss in disease-related brain regions, but the molecular mechanisms that lead to the pathological and symptomatic hallmarks... Show moreNeurodegenerative diseases are hallmarked by protein inclusions and cell loss in disease-related brain regions, but the molecular mechanisms that lead to the pathological and symptomatic hallmarks of neurodegeneration are still not fully understood. In this thesis, we make use of bioinformatics approaches to analyze a high-resolution spatial gene expression atlas of the healthy human brain generated by the Allen Institute of Brain Science. Spatial transcriptomics allows examining the molecular and functional organization of the human brain and can be combined with neuroimaging data to identify brain regions and anatomical structures that are vulnerable to cell loss in neurodegenerative diseases. By combining both data modalities, we examined healthy molecular functions in brain regions associated with disease vulnerability based on neuroimaging features, namely gray matter loss within brain networks in individuals with Parkinson’s disease, Huntington’s disease, and individuals at risk of schizophrenia. With this thesis, we have shown that by applying data-driven computational methods we can explore the whole genome and find gene expression patterns informative of regional brain vulnerability in neurodegenerative diseases. Our methods can similarly be applied to unravel the molecular mechanisms in other neurodegenerative diseases, and potentially even reveal shared mechanisms between neurological disorders. Show less
The order Nidovirales, including families Coronaviridae and Arteriviridae, is a monophyletic group of highly divergent (+)ssRNA viruses that infect vertebrate and invertebrate hosts; they share... Show moreThe order Nidovirales, including families Coronaviridae and Arteriviridae, is a monophyletic group of highly divergent (+)ssRNA viruses that infect vertebrate and invertebrate hosts; they share conserved genome organization and replication mechanisms. The genome sequence is the only information available about many newly discovered nidoviruses whose number is fast increasing driven by technology advancements. This development makes comparative genomics, an approach that already has been used extensively in nidovirology, increasingly important. In this thesis, diverse methods of comparative genomics were used to address scientific questions about composition and evolution of the nidovirus genome and proteome, and their connection to the biology of nidoviruses. Three studies were conducted in collaboration with experimental researchers, and ranged from the analysis of the highly divergent polyprotein N-terminus in arteriviruses, to identification of the fifth universally conserved domain of nidoviruses, and to characterization of a nidovirus with the largest known RNA genome. The latter study prompted the development of a bioinformatics tool facilitating functional annotation of large multidomain polyproteins. The thesis illustrates how a notion of nidovirus-specific conservation has been steadily refined as a result of recent discoveries. Show less
In dit proefschrift worden de moleculaire mechanismen behandeld die onderliggend zijn aan artrose. Specifiek wordt genoomwijd onderzocht welke genen anders tot expressie komen in aangedaan... Show moreIn dit proefschrift worden de moleculaire mechanismen behandeld die onderliggend zijn aan artrose. Specifiek wordt genoomwijd onderzocht welke genen anders tot expressie komen in aangedaan vergeleken met gezond kraakbeen van artrose patienten. Dit in de context van epigenetische regulatie van gen expressie, specifiek door DNA methylatie in het licht van de lokale genetische context in de vorm van puntmutaties. Show less
In this thesis we will explore the use of fuzzy systems theory for applications in bioinformatics. The theory of fuzzy systems is concerned with formulating decision problems in data sets that... Show moreIn this thesis we will explore the use of fuzzy systems theory for applications in bioinformatics. The theory of fuzzy systems is concerned with formulating decision problems in data sets that are ill-defined. It supports the transfer from a subjective human classification to a numerical scale. In this manner it affords the testing of hypothesis and separation of the classes in the data. We first formulate problems in terms of a fuzzy system and then develop and test algorithms in terms of their performance with data from the domain of the life-sciences. From the results and the performance, we will learn about the usefulness of fuzzy systems for the field, as well as the applicability to the kind of problems and practicality for the computation itself. Show less
This dissertation describes the development of glyco-bioinformatics tools that facilitate the high-throughput data processing of glycomics and glycoproteomics experiments, specifically for both... Show moreThis dissertation describes the development of glyco-bioinformatics tools that facilitate the high-throughput data processing of glycomics and glycoproteomics experiments, specifically for both MALDI-TOF-MS (Chapter 2) and LC-ESI-MS (Chapter 3). The developed methods also provide various quality control parameters that assist the researcher in curating both the measured spectra and quantified analytes, thereby providing high-quality data in a high-throughput manner.The tools that were developed within this thesis have been used to identify the influence of glycosylation on trypsin efficacy of Immunoglobulin G (Chapter 3) and two biological cohorts. Specifically, to investigate the serum N-glycosylation during and after pregnancy (Chapter 5) and to identify the differences in the N-glycosylation between maternal and fetal serum and IgG (Chapter 6). Show less
This thesis demonstrates the application of bioinformatics to investigate the mechanisms that are implicated in Huntington’s Disease (HD). HD is an inherited neurodegenerative disorder and although... Show moreThis thesis demonstrates the application of bioinformatics to investigate the mechanisms that are implicated in Huntington’s Disease (HD). HD is an inherited neurodegenerative disorder and although the cause of the disease is known since 1993 we are still lacking a cure or treatment that can effectively treat the symptoms of HD. In order to tackle such a complicated case study, we followed a multidisciplinary approach to exploit the expertise and knowledge of people with diverse scientific background (chapter 2). This blend of disciplines facilitates constant collaboration between bioinformaticians, wet lab technicians, biologists, computer engineers and data scientists. A collaborative eScience model is proposed as a way to combine state-of-the-art computation analysis and laboratory work (chapter 3). At the same time, we explored methods to preserve the results, materials and methods involved in the experiment to increase the reproducibility and reusability of our research (chapter 4). In chapter 5 we identified disease signatures in blood that are functionally similar to signatures in brain. These are proposed as candidate biomarkers to be used as a monitoring tool for the state of the disease in brain, but also as a means to determine whether a treatment is successful or not. Show less
In this thesis I focus on the application of bioinformatics to analyze RNA. The type of experimental data of interest is sequencing data generated with various Next Generation Sequencing technique:... Show moreIn this thesis I focus on the application of bioinformatics to analyze RNA. The type of experimental data of interest is sequencing data generated with various Next Generation Sequencing technique: nuclear RNA, cytoplasmic RNA, captured polyadenylated RNA fragments, etc. I highlight the necessity in developing new tools (e.g., to analyze nuclear RNA) and give a showcase example of implementing such tool and showing its usability on a real biological experiment. The thesis also covers existing tools to perform various types of RNA analysis and shows how these tools can be twigged and expanded to answer certain biological questions (e.g., studying changes in RNA specific to human aging). I also show how current bioinformatic approaches can be used in a particularly complex study such as investigating cancer (in this thesis, breast cancer) pathogenesis. Show less
Advances in technology have turned modern biology into a data-intensive enterprise. The advent of high-output technologies like Microarrays and Next-generation sequencing technologies has resulted... Show moreAdvances in technology have turned modern biology into a data-intensive enterprise. The advent of high-output technologies like Microarrays and Next-generation sequencing technologies has resulted in researchers grappling not just with huge volumes but also multiple types of data. While generation and storage of high-quality data are an important research focus, it is increasingly recognized that translating data into actionable information and insight is a critical research challenge. To infer reliable conclusions from the data, it is often necessary to integrate large amounts of heterogeneous data with different formats and semantics. Given the breadth and volume of data involved, this goal is best achieved through automated methods and tools for data integration and workflow management. This thesis presents automated strategies that combine bioinformatics and statistical methods to identify novel biomarkers in high-throughput OMICs datasets pertaining to the metabolic syndrome and to gain mechanistic insight into the underlying biological processes. An underlying theme in this thesis is data-driven approaches that generate plausible hypothesis which is followed by experimental verification. Show less
