| 1. |
- Gawel, Danuta R., 1988-
(författare)
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Identification of genes and regulators that are shared across T cell associated diseases
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Genome-wide association studies (GWASs) of hundreds of diseases and millions of patients have led to the identification of genes that are associated with more than one disease. The aims of this PhD thesis were to a) identify a group of genes important in multiple diseases (shared disease genes), b) identify shared up-stream disease regulators, and c) determine how the same genes can be involved in the pathogenesis of different diseases. These aims have been tested on CD4+ T cells because they express the T helper cell differentiation pathway, which was the most enriched pathway in analyses of all disease associated genes identified with GWASs.Combining information about known gene-gene interactions from the protein-protein interaction (PPI) network with gene expression changes in multiple T cell associated diseases led to the identification of a group of highly interconnected genes that were miss-expressed in many of those diseases – hereafter called ‘shared disease genes’. Those genes were further enriched for inflammatory, metabolic and proliferative pathways, genetic variants identified by all GWASs, as well as mutations in cancer studies and known diagnostic and therapeutic targets. Taken together, these findings supported the relevance of the shared disease genes.Identification of the shared upstream disease regulators was addressed in the second project of this PhD thesis. The underlying hypothesis assumed that the determination of the shared upstream disease regulators is possible through a network model showing in which order genes activate each other. For that reason a transcription factor–gene regulatory network (TF-GRN) was created. The TF-GRN was based on the time-series gene expression profiling of the T helper cell type 1 (Th1), and T helper cell type 2 (Th2) differentiation from Native T-cells. Transcription factors (TFs) whose expression changed early during polarization and had many downstream predicted targets (hubs) that were enriched for disease associated single nucleotide polymorphisms (SNPs) were prioritised as the putative early disease regulators. These analyses identified three transcription factors: GATA3, MAF and MYB. Their predicted targets were validated by ChIP-Seq and siRNA mediated knockdown in primary human T-cells. CD4+ T cells isolated from seasonal allergic rhinitis (SAR) and multiple sclerosis (MS) patients in their non-symptomatic stages were analysed in order to demonstrate predictive potential of those three TFs. We found that those three TFs were differentially expressed in symptom-free stages of the two diseases, while their TF-GRN{predicted targets were differentially expressed during symptomatic disease stages. Moreover, using RNA-Seq data we identified a disease associated SNP that correlated with differential splicing of GATA3.A limitation of the above study is that it concentrated on TFs as main regulators in cells, excluding other potential regulators such as microRNAs. To this end, a microRNA{gene regulatory network (mGRN) of human CD4+ T cell differentiation was constructed. Within this network, we defined regulatory clusters (groups of microRNAs that are regulating groups of mRNAs). One regulatory cluster was differentially expressed in all of the tested diseases, and was highly enriched for GWAS SNPs. Although the microRNA processing machinery was dynamically upregulated during early T-cell activation, the majority of microRNA modules showed specialisation in later time-points.In summary this PhD thesis shows the relevance of shared genes and up-stream disease regulators. Putative mechanisms of why shared genes can be involved in pathogenesis of different diseases have also been demonstrated: a) differential gene expression in different diseases; b) alternative transcription factor splicing variants may affect different downstream gene target group; and c) SNPs might cause alternative splicing.
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| 2. |
- Lentini, Antonio, 1990-
(författare)
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Dynamic regulation of DNA methylation in human T-cell biology
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- T helper cells play a central role in orchestrating immune responses in humans. Upon encountering a foreign antigen, T helper cells are activated followed by a differentiation process where the cells are specialised to help combating the infection. Dysregulation of T helper cell activation, differentiation and function has been implicated in numerous diseases, including autoimmunity and cancer. Whereas gene-regulatory networks help drive T-cell differentiation, acquisition of stable cell states require heritable epigenetic signals, such as DNA methylation. Indeed, the establishment of DNA methylation patterns is a key part of appropriate T-cell differentiation but how this is regulated over time remains unknown. Methylation can be directly attached to cytosine residues in DNA to form 5-methylcytosine (5mC) but the removal of DNA methylation requires multiple enzymatic reactions, commonly initiated by the conversion into 5-hydroxymethylcytosine (5hmC), thus creating a highly complex regulatory system. This thesis aimed to investigate how DNA methylation is dynamically regulated during T-cell differentiation.To this end, we employed large-scale profiling techniques combining gene expression as well as genome-wide 5mC and 5hmC measurements to construct a time-series model of epigenetic regulation of differentiation. This revealed that early T-cell activation was accompanied by extensive genome-wide deposition of 5hmC which resulted in demethylation upon proliferation. Early DNA methylation remodelling through 5hmC was not only indicative of demethylation events during T-cell differentiation but also marked changes persisting longterm in memory T-cell subsets. These results suggest that priming of epigenetic landscapes in T-cells is initiated during early activation events, preceding any establishment of a stable lineage, which are then maintained throughout the cells lifespan. The regions undergoing remodelling were also highly enriched for genetic variants in autoimmune diseases which we show to be functional through disruption of protein binding. These variants could potentially disrupt gene-regulatory networks and the establishment of epigenetic priming, highlighting the complex interplay between genetic and epigenetic layers. In the course of this work, we discovered that a commonly used technique to study genome-wide DNA modifications, DNA immunoprecipitation (DIP)-seq, had a false discovery rate between 50-99% depending on the modification and cell type being assayed. This represented inherent technical errors related to the use of antibodies resulting in off-target binding of repetitive sequences lacking any DNA modifications. These sequences are common in mammalian genomes making robust detection of rare DNA modifications very difficult due to the high background signals. However, offtarget binding could easily be controlled for using a non-specific antibody control which greatly improved data quality and biological insight of the data. Although future studies are advised to use alternative methods where available, error correction is an acceptable alternative which will help fuel new discoveries through the removal of extensive background signals.Taken together, this thesis shows how integrative use of high-resolution epigenomic data can be used to study complex biological systems over time as well as how these techniques can be systematically characterised to identify and correct errors resulting in improved detection.
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| 3. |
- Das, Jyotirmoy, et al.
(författare)
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Identification of DNA methylation patterns predisposing for an efficient response to BCG vaccination in healthy BCG-naive subjects
- 2019
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Ingår i: Epigenetics. - : TAYLOR & FRANCIS INC. - 1559-2294 .- 1559-2308. ; 14:6, s. 589-601
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Tidskriftsartikel (refereegranskat)abstract
- The protection against tuberculosis induced by the Bacille Calmette Guerin (BCG) vaccine is unpredictable. In our previous study, altered DNA methylation pattern in peripheral blood mononuclear cells (PBMCs) in response to BCG was observed in a subgroup of individuals, whose macrophages killed mycobacteria effectively (responders). These macrophages also showed production of Interleukin-1 beta (IL-1 beta) in response to mycobacterial stimuli before vaccination. Here, we hypothesized that the propensity to respond to the BCG vaccine is reflected in the DNA methylome. We mapped the differentially methylated genes (DMGs) in PBMCs isolated from responders/non-responders at the time point before vaccination aiming to identify possible predictors of BCG responsiveness. We identified 43 DMGs and subsequent bioinformatic analyses showed that these were enriched for actin-modulating pathways, predicting differences in phagocytosis. This could be validated by experiments showing that phagocytosis of mycobacteria, which is an event preceding mycobacteria-induced IL-1 beta production, was strongly correlated with the DMG pattern.
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| 4. |
- Magnusson, Rasmus, 1992-, et al.
(författare)
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Cross-talks via mTORC2 can explain enhanced activation in response to insulin in diabetic patients
- 2017
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Ingår i: Bioscience Reports. - : PORTLAND PRESS LTD. - 0144-8463 .- 1573-4935. ; 37
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Tidskriftsartikel (refereegranskat)abstract
- The molecular mechanisms of insulin resistance in Type 2 diabetes have been extensively studied in primary human adipocytes, and mathematical modelling has clarified the central role of attenuation of mammalian target of rapamycin (mTOR) complex 1 (mTORC1) activity in the diabetic state. Attenuation of mTORC1 in diabetes quells insulin-signalling network-wide, except for the mTOR in complex 2 (mTORC2)-catalysed phosphorylation of protein kinase B (PKB) at Ser(473) (PKB-S473P), which is increased. This unique increase could potentially be explained by feedback and interbranch cross-talk signals. To examine if such mechanisms operate in adipocytes, we herein analysed data from an unbiased phosphoproteomic screen in 3T3-L1 adipocytes. Using a mathematical modelling approach, we showed that a negative signal from mTORC1-p70 S6 kinase (S6K) to rictor-mTORC2 in combination with a positive signal from PKB to SIN1-mTORC2 are compatible with the experimental data. This combined cross-branch signalling predicted an increased PKB-S473P in response to attenuation of mTORC1 - a distinguishing feature of the insulin resistant state in human adipocytes. This aspect of insulin signalling was then verified for our comprehensive model of insulin signalling in human adipocytes. Introduction of the cross-branch signals was compatible with all data for insulin signalling in human adipocytes, and the resulting model can explain all data network-wide, including the increased PKB-S473P in the diabetic state. Our approach was to first identify potential mechanisms in data from a phosphoproteomic screen in a cell line, and then verify such mechanisms in primary human cells, which demonstrates how an unbiased approach can support a direct knowledge-based study.
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