Combinatorial biological complexity: a study of amino acid side chains and alternative splicing

Both, laymen and experts have always been intrigued by nature’s vast complexity and variety. Often, these phenomena arise from combination of parts, as for example, cell types of the human body, or the diverse proteins of a cell. In this thesis I investigate three instances of combinatorial complexity: combinations of aliphatic amino acid side chains, alternative mRNA splicing in fungi, and mutually exclusively spliced exons in human and mouse. In the first part the number of aliphatic amino acid side chains is studied. Structural combinations yield a vast theoretical number, yet we find that only a fraction of them is realized in nature. Reasons especially with respect to restrictions by the genetic code are discussed. Moreover, strategies for the need for increased diversity are examined. In the second part, the extent of alternative splicing (AS) in fungi is investigated. A genome-wide, comparative multi-species study is conducted. I find that AS is common in fungi, but with lower frequency compared to plants and animals. AS is more common in more complex fungi, and is over-represented in pathogens. It is hypothesized that AS contributes to multi-cellular complexity in fungi. In the third part, mutually exclusive exons (MXEs) of mouse and human are detected and characterized. Rather unexpected patterns arose: the majority of MXEs originate from non-adjacent exons and frequently appear in clusters. Known regulatory mechanisms of MXE splicing are unsuitable for these MXEs, and thus, new mechanisms have to be sought. Summarizing it is hypothesized that complexity from combinations constitutes a universal principle in biology. However, there seems to be a need to restrict the combinatorial potential. This is highlighted by the interdependence of MXEs and the low number of realized amino acids in the genetic code. Combinatorial complexity and its restriction are discussed with respect to other biological systems to further substantiate the hypotheses

Environment‐induced epigenetic reprogramming in genomic regulatory elements in smoking mothers and their children

Contains fulltext : 156948.pdf (publisher's version ) (Open Access

Lactate dehydrogenases promote glioblastoma growth and invasion via a metabolic symbiosis

Lactate is a central metabolite in brain physiology but also contributes to tumor development. Glioblastoma (GB) is the most common and malignant primary brain tumor in adults, recognized by angiogenic and invasive growth, in addition to its altered metabolism. We show herein that lactate fuels GB anaplerosis by replenishing the tricarboxylic acid (TCA) cycle in absence of glucose. Lactate dehydrogenases (LDHA and LDHB), which we found spatially expressed in GB tissues, catalyze the interconversion of pyruvate and lactate. However, ablation of both LDH isoforms, but not only one, led to a reduction in tumor growth and an increase in mouse survival. Comparative transcriptomics and metabolomics revealed metabolic rewiring involving high oxidative phosphorylation (OXPHOS) in the LDHA/B KO group which sensitized tumors to cranial irradiation, thus improving mouse survival. When mice were treated with the antiepileptic drug stiripentol, which targets LDH activity, tumor growth decreased. Our findings unveil the complex metabolic network in which both LDHA and LDHB are integrated and show that the combined inhibition of LDHA and LDHB strongly sensitizes GB to therapy.publishedVersio

Examination of Apoptosis Signaling in Pancreatic Cancer by Computational Signal Transduction Analysis

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) remains an important cause of cancer death. Changes in apoptosis signaling in pancreatic cancer result in chemotherapy resistance and aggressive growth and metastasizing. The aim of this study was to characterize the apoptosis pathway in pancreatic cancer computationally by evaluation of experimental data from high-throughput technologies and public data bases. Therefore, gene expression analysis of microdissected pancreatic tumor tissue was implemented in a model of the apoptosis pathway obtained by computational protein interaction prediction. METHODOLOGY/PRINCIPAL FINDINGS: Apoptosis pathway related genes were assembled from electronic databases. To assess expression of these genes we constructed a virtual subarray from a whole genome analysis from microdissected native tumor tissue. To obtain a model of the apoptosis pathway, interactions of members of the apoptosis pathway were analysed using public databases and computational prediction of protein interactions. Gene expression data were implemented in the apoptosis pathway model. 19 genes were found differentially expressed and 12 genes had an already known pathophysiological role in PDAC, such as Survivin/BIRC5, BNIP3 and TNF-R1. Furthermore we validated differential expression of IL1R2 and Livin/BIRC7 by RT-PCR and immunohistochemistry. Implementation of the gene expression data in the apoptosis pathway map suggested two higher level defects of the pathway at the level of cell death receptors and within the intrinsic signaling cascade consistent with references on apoptosis in PDAC. Protein interaction prediction further showed possible new interactions between the single pathway members, which demonstrate the complexity of the apoptosis pathway. CONCLUSIONS/SIGNIFICANCE: Our data shows that by computational evaluation of public accessible data an acceptable virtual image of the apoptosis pathway might be given. By this approach we could identify two higher level defects of the apoptosis pathway in PDAC. We could further for the first time identify IL1R2 as possible candidate gene in PDAC

Data set for the publication

<p>Data set for the publication</p><p>Identification and validation of novel snoRNA-based biomarkers for clear cell renal cell carcinoma from urine-derived extracellular vesicles</p><p> </p&gt

Patient-specific identification of genome-wide DNA-methylation differences between intracranial and extracranial melanoma metastases

Abstract Melanomas frequently metastasize to distant organs and especially intracranial metastases still represent a major clinical challenge. Epigenetic reprogramming of intracranial metastases is thought to be involved in therapy failure, but so far only little is known about patient-specific DNA-methylation differences between intra- and extracranial melanoma metastases. Hierarchical clustering of the methylomes of 24 patient-matched intra- and extracranial melanoma metastases pairs revealed that intra- and extracranial metastases of individual patients were more similar to each other than to metastases in the same tissue from other patients. Therefore, a personalized analysis of each metastases pair was done by a Hidden Markov Model to classify methylation levels of individual CpGs as decreased, unchanged or increased in the intra- compared to the extracranial metastasis. The predicted DNA-methylation alterations were highly patient-specific differing in the number and methylation states of altered CpGs. Nevertheless, four important general observations were made: (i) intracranial metastases of most patients mainly showed a reduction of DNA-methylation, (ii) cytokine signaling was most frequently affected by differential methylation in individual metastases pairs, but also MAPK, PI3K/Akt and ECM signaling were often altered, (iii) frequently affected genes were mainly involved in signaling, growth, adhesion or apoptosis, and (iv) an enrichment of functional terms related to channel and transporter activities supports previous findings for a brain-like phenotype. In addition, the derived set of 17 signaling pathway genes that distinguished intra- from extracranial metastases in more than 50% of patients included well-known oncogenes (e.g. PRKCA, DUSP6, BMP4) and several other genes known from neuronal disorders (e.g. EIF4B, SGK1, CACNG8). Moreover, associations of gene body methylation alterations with corresponding gene expression changes revealed that especially the three signaling pathway genes JAK3, MECOM, and TNXB differ strongly in their expression between patient-matched intra- and extracranial metastases. Our analysis contributes to an in-depth characterization of DNA-methylation differences between patient-matched intra- and extracranial melanoma metastases and may provide a basis for future experimental studies to identify targets for new therapeutic approaches

Different Effects of RNAi-Mediated Downregulation or Chemical Inhibition of NAMPT in an Isogenic IDH Mutant and Wild-Type Glioma Cell Model

The IDH1R132H mutation in glioma results in the neoenzymatic function of IDH1, leading to the production of the oncometabolite 2-hydroxyglutarate (2-HG), alterations in energy metabolism and changes in the cellular redox household. Although shifts in the redox ratio NADPH/NADP+ were described, the consequences for the NAD+ synthesis pathways and potential therapeutic interventions were largely unexplored. Here, we describe the effects of heterozygous IDH1R132H on the redox system in a CRISPR/Cas edited glioblastoma model and compare them with IDH1 wild-type (IDH1wt) cells. Besides an increase in 2-HG and decrease in NADPH, we observed an increase in NAD+ in IDH1R132H glioblastoma cells. RT-qPCR analysis revealed the upregulation of the expression of the NAD+ synthesis enzyme nicotinamide phosphoribosyltransferase (NAMPT). Knockdown of NAMPT resulted in significantly reduced viability in IDH1R132H glioblastoma cells. Given this dependence of IDH1R132H cells on NAMPT expression, we explored the effects of the NAMPT inhibitors FK866, GMX1778 and GNE-617. Surprisingly, these agents were equally cytotoxic to IDH1R132H and IDH1wt cells. Altogether, our results indicate that targeting the NAD+ synthesis pathway is a promising therapeutic strategy in IDH mutant gliomas; however, the agent should be carefully considered since three small-molecule inhibitors of NAMPT tested in this study were not suitable for this purpose

Gene Expression Profiling of Microdissected Pancreatic Ductal Carcinomas Using High-Density DNA Microarrays,

Pancreatic ductal adenocarcinoma (PDAC) remains an important cause of malignancy-related death and is the eighth most common cancer with the lowest overall 5-year relative survival rate. To identify new molecular markers and candidates for new therapeutic regimens, we investigated the gene expression profile of microdissected cells from 11 normal pancreatic ducts, 14 samples of PDAC, and 4 well-characterized pancreatic cancer cell lines using the Affymetrix U133 GeneChip set. RNA was extracted from microdissected samples and cell lines, amplified, and labeled using a repetitive in vitro transcription protocol. Differentially expressed genes were identified using the significance analysis of microarrays program. We found 616 differentially expressed genes. Within these, 140 were also identified in PDAC by others, such as Galectin-1, Galectin-3, and MT-SP2. We validated the differential expression of several genes (e.g., CENPF, MCM2, MCM7, RAMP, IRAK1, and PTTG1) in PDAC by immunohistochemistry and reverse transcription polymerase chain reaction. We present a whole genome expression study of microdissected tissues from PDAC, from microdissected normal ductal pancreatic cells and pancreatic cancer cell lines using highdensity microarrays. Within the panel of genes, we identified novel differentially expressed genes, which have not been associated with the pathogenesis of PDAC before