409 research outputs found
Rule-Based Cell Systems Model of Aging using Feedback Loop Motifs Mediated by Stress Responses
Investigating the complex systems dynamics of the aging process requires integration of a broad range of cellular processes describing damage and functional decline co-existing with adaptive and protective regulatory mechanisms. We evolve an integrated generic cell network to represent the connectivity of key cellular mechanisms structured into positive and negative feedback loop motifs centrally important for aging. The conceptual network is casted into a fuzzy-logic, hybrid-intelligent framework based on interaction rules assembled from a priori knowledge. Based upon a classical homeostatic representation of cellular energy metabolism, we first demonstrate how positive-feedback loops accelerate damage and decline consistent with a vicious cycle. This model is iteratively extended towards an adaptive response model by incorporating protective negative-feedback loop circuits. Time-lapse simulations of the adaptive response model uncover how transcriptional and translational changes, mediated by stress sensors NF-ÎşB and mTOR, counteract accumulating damage and dysfunction by modulating mitochondrial respiration, metabolic fluxes, biosynthesis, and autophagy, crucial for cellular survival. The model allows consideration of lifespan optimization scenarios with respect to fitness criteria using a sensitivity analysis. Our work establishes a novel extendable and scalable computational approach capable to connect tractable molecular mechanisms with cellular network dynamics underlying the emerging aging phenotype
Rule-Based Cell Systems Model of Aging using Feedback Loop Motifs Mediated by Stress Responses
Investigating the complex systems dynamics of the aging process requires integration of a broad range of cellular processes describing damage and functional decline co-existing with adaptive and protective regulatory mechanisms. We evolve an integrated generic cell network to represent the connectivity of key cellular mechanisms structured into positive and negative feedback loop motifs centrally important for aging. The conceptual network is casted into a fuzzy-logic, hybridintelligent framework based on interaction rules assembled from a priori knowledge. Based upon a classical homeostatic representation of cellular energy metabolism, we first demonstrate how positive-feedback loops accelerate damage and decline consistent with a vicious cycle. This model is iteratively extended towards an adaptive response model by incorporating protective negative-feedback loop circuits. Time-lapse simulations of the adaptive response model uncover how transcriptional and translational changes, mediated by stress sensors NF-kB and mTOR, counteract accumulating damage and dysfunction by modulating mitochondrial respiration, metabolic fluxes, biosynthesis, and autophagy, crucial for cellular survival. The model allows consideration of lifespan optimization scenarios with respect to fitness criteria using a sensitivity analysis. Our work establishes a novel extendable and scalable computational approach capable to connect tractable molecular mechanisms with cellular network dynamics underlying the emerging aging phenotype
Recommended from our members
In silico identification of novel genetic factors associated with longevity in Drosophila
To determine genetic factors causing variation in survival into old age, several genome-wide association studies (GWAS) have been carried out on panels of long-lived individuals. The findings from a number of these GWAS studies were somewhat inconclusive, owing to the small sample sizes investigated. It is for this reason that model organisms such as Drosophila melanogaster have become increasingly important in identifying genetic factors underlying longevity.
In this study we hypothesised that co-location of novel genes/genomic regions with genes, known to be associated with longevity, that share biological function with co-located genes, make them good candidates for novel genomic regions, linked to longevity. We further hypothesised that single nucleotide polymorphisms (SNPs) residing within these co-located regions may influence longevity either individually (when a SNP in one of these genes causes a particular phenotype) or collectively (when one or several SNPs in these regions occur in the same individual thus causing the phenotype). Summary statistics of datasets of SNPs generated by two GWAS (Burke et al., 2013; Ivanov et al., 2015) which include position of each SNP and a corresponding statistic (D or P- value) showing the strength of association with longevity were used in this study to guide the initial choice of genes/loci strongly associated with longevity.
First, a network approach was applied to predict novel genes/genomic regions/SNPs, playing a role in longevity, which integrated three-dimensional (3D) chromosome conformation data (Hi-C) and two GWAS datasets. Networks were created using genes/genomic regions, known to associate with longevity, as original nodes with additional nodes (regions) later added to these networks if they strongly interacted (i.e. came into close proximity as measured by the Hi-C data) with the original nodes. Various network measures were calculated, in order to identify important previously unknown regions. These previously unknown regions were further explored and longevity associated genes were found including Rim and Tpi with a 'long-lived' phenotype, and some newly found regions were observed to be common between both GWAS datasets. A human ortholog search of genes found in this analysis resulted in matches to human genes with functions related to lifespan. Subnetworks of these GWAS-based networks were sought for enrichment in GO terms and several genes with no previous association with longevity but enriched in longevity-related terms were identified.
Second, SNPs residing in non-coding regions, e.g. within transcription factor binding sites (TFBSs) recognised by transcription factors (TF) and borders between Topologically Associated Domains (TADs) were analysed. Each TF typically recognises a collection of often dissimilar DNA motifs. Here we hypothesised that TFs may recognise a certain structure, e.g. non-B DNA structures, rather than sequence motifs. Structures such as slipped, cruciform, triplexes and tetraplexes, formed on direct, inverted and mirrored repeats and G-quartets were considered and SNPs residing within these structures were analysed. For the study of SNPs in TAD borders we hypothesised that SNPs residing in these border regions may cause a severe disruption to the way in which regulation usually occurs within these TADs. We found that a significant proportion (~2%) of non-coding SNPs, reported in the DGRP GWAS dataset, resided in TAD border regions on the Drosophila genome, when compared to a match control dataset (
Mitochondria interaction networks show altered topological patterns in Parkinson's disease.
Mitochondrial dysfunction is linked to pathogenesis of Parkinson's disease (PD). However, individual mitochondria-based analyses do not show a uniform feature in PD patients. Since mitochondria interact with each other, we hypothesize that PD-related features might exist in topological patterns of mitochondria interaction networks (MINs). Here we show that MINs formed nonclassical scale-free supernetworks in colonic ganglia both from healthy controls and PD patients; however, altered network topological patterns were observed in PD patients. These patterns were highly correlated with PD clinical scores and a machine-learning approach based on the MIN features alone accurately distinguished between patients and controls with an area-under-curve value of 0.989. The MINs of midbrain dopaminergic neurons (mDANs) derived from several genetic PD patients also displayed specific changes. CRISPR/CAS9-based genome correction of alpha-synuclein point mutations reversed the changes in MINs of mDANs. Our organelle-interaction network analysis opens another critical dimension for a deeper characterization of various complex diseases with mitochondrial dysregulation
In silico Investigation of Chromatin Organisation in Splicing, Ageing, and Histone Mark Propagation along DNA-Loops
A long-standing aim in biology is to elucidate how the genome is tightly compacted inside the eukaryotic nucleus while still retaining its capacity to orchestrate the correct functionality of the cell. While years of research have revealed that this three-dimensional structuring of DNA plays a major role in the transcriptional regulation, most of the existing studies have focused on long-range chromatin interactions, which are mainly established by the CCCTC-binding factor (CTCF), rarely centring at the gene level. Furthermore, our current knowledge on the interplay between structure and function remains largely descriptive with little mechanistic insight. In this dissertation I present three distinct computational studies which integrate multiple levels of molecular phenotype data in an attempt to gain further insights into the influence of chromatin organisation in (i) splicing regulation, (ii) in how distal genetic variants convey their signal, (iii) and an overall view of the misregulation of chromatin compaction in ageing stem cells.
Firstly, I describe a novel splicing mechanism whereby CTCF-mediated DNA- loops that are formed within genes facilitate exon inclusion. My results provide substantial evidence that intragenic loops regulate exon usage and that CTCF binding can be affected either by genetic variation across individuals or by the epigenomic landscape in different cell lines. Those exons being CTCF-regulated frequently overlap annotated protein domains and are enriched for being involved in cellular stress-response and signalling pathways. In summary, this study provides strong evidence for alternative exon usage being regulated by chromatin structure, and thus increases our understanding of functional consequences underlying variation in chromatin architecture.
In a second study, I show initial efforts to unravel the mechanisms that allow a genetic variant (distal-QTL) to confer its effect at distant regions through long-range interactions. By measuring allele-specific biases of various molecular phenotypes occurring along chromatin interactions, I propose two models that intend to explain the propagation of this signal. In the “touch-and-act model” functionality is transmitted through the physical contact of both anchors, independent of the region inside the loop, while in the “spreading model” the function is propagated along the entire loop resulting in a coordinated activation or repression of the whole local neighbourhood. There is evidence for both models occurring at varying proportions, which are partially explained by transcription factor co-enrichments.
Finally, I present a study on how chromatin accessibility impacts the transcriptome and the proteome in mesenchymal stem cells (MSC) from human donors of multiple ages. I also observed a profound misregulation of chromatin organisation occurring with age, possibly due to a decrease in chromatin-related proteins such as histones, CTCF, CENPB, and lamins, which ultimately affect heterochromatin at centromeres and telomeres contributing to genomic instability. By subtle but significant changes in the transcription factor landscape of young and old MSCs, I observe a bias in the differentiation potential. Additionally, I show a loss of bivalent modifications at enhancer and promoter regions that correlate with DNA methylation changes and that could possibly contribute to a decrease in stemness with age.
In summary, I describe a novel splicing mechanism mediated by chromatin intragenic interactions, propose models of how distal-QTLs propagate histone marks, and advance the understanding of chromatin accessibility changes occurring with age in stem cells
A module based approach for identifying driver genes and expanding pathways from integrated biological networks
Each gene or protein has its own function which, when combined with others, allows the group to perform more complex behaviors, e.g. carry out a particular cellular task (functional module) or affect a particular disease phenotype (disease module). One of the major challenges in systems biology is to reveal the roles of genes or proteins in functional modules or disease modules.
In the first part of the dissertation, I present a data-driven method, Correlation Set Analysis (CSA), for comprehensively detecting active regulators in disease populations by integrating co-expression analysis and specific types of literature-derived causal relationships. Instead of investigating the co-expression level between regulators and their targets, I focus on coherence of regulatees of a regulator, e.g. downstream targets of a transcription factor. Using simulated datasets I show that my method can reach high true positive rate and true negative rate (>80%) even the regulatory relationships is weak (only 20% of regulatees are co-expressed). Using three separate real biological datasets I was able to recover well-known and as- yet undescribed, active regulators for each disease population.
In the second part of the dissertation, I develop and apply a new computational algorithm for detecting modules of functionally related genes that are likely to drive malignant transformation. The algorithm takes as input the identity and locations of a small number of known oncogenes (a seed set) on a human genome functional linkage network (FLN). It then searches for a boundary surrounding a gene set encompassing the seed, such that the magnitude of the difference in linkage weights between interior-interior gene pairs, and interior-exterior gene pairs is maximized. Starting with small seed sets for breast and ovarian cancer, I successfully identify known and novel drivers in both cancer types.
In the third part of the dissertation, I propose a module based approach for expanding manually curated functional modules. I use the KEGG pathway database as an example and the results show that my approach can successfully suggest both validated pathway members (genes that are assigned to a particular pathway by other manually curated pathway databases) and novel candidate pathway genes
Uncovering Molecular Properties of Neural Crest Cells
The neural crest is a transient population of cells that arises at the border between the neural and non-neural ectoderm. These cells are induced, undergo an epithelial-to-mesenchymal transition, and then migrate along stereotypical pathways to form a wide array of derivatives. While these cells have long been studied, much about these cells and their interactions is still not understood. In order to better define these cells, we performed a screen for genes involved in neural crest cell development based on an in vitro culture system that produces neural crest cells. This highly successful screen resulted in a large number of candidates to examine, and we performed in situ hybridization to define the mRNA expression of 112 these genes. Moreover, we performed QPCR on several transcription factors that resulted from this screen to determine the level at which they were upregulated in our in vitro culture system. We also present loss-of-function analyses of two different genes that were discovered in our screen for neural crest effectors. These genes, Adh5 and Ccar1, are both functionally relevant in neural crest cells and the loss of either one through morpholino knockdown significantly decreases the mRNA of Sox10 on the injected side. Furthermore, we also show that Adh5 morpholino knockdown also results in a reduction of Snail2 and FoxD3 mRNA. Taken as a whole, this body of work represents the discovery of many new genes involved neural crest cell development, and the demonstration that at least two of these genes are functionally important for neural crest cells
Identification and analysis of a novel nuclear role of Fibroblast Growth Factor 10 (FGF10)
Fibroblast growth factor 10 (FGF10) is a paracrine molecule, serving crucial mesenchymal-to-epithelial signalling roles during development and postnatally. FGF10 binds specifically to FGF-receptor 2 IIIb (FGFR2-IIIb) and their interaction results in signal transduction pathways, which promote epithelial proliferation, motility and survival. Human heterozygous mutations in the Fgf10 gene result in LADD (lacrimo-auriculo-dento-digital) and ALSG (aplasia of lacrimal and salivary glands) syndromes, which to date have been solely attributed to perturbed FGF10 paracrine function. However, the molecular dynamics undelaying LADD-causing G138E FGF10 mutation, which falls outside its receptor interaction interface, has remained enigmatic. Moreover, Fgf10 is expressed within mouse hypothalamus, which is not accompanied by expression of its cognate receptor, signifying FGF10 may have additional intracrine function. In this study, FGF10 was investigated in a context of nuclear translocation and putative endogenous function within mesenchymal and hypothalamic cells. Through interrogation of FGF10’s sequence and subcellular distribution, the protein was found to possess two putative nuclear localization sequences, termed NLS1 and NLS2, which were shown implicated in nuclear translocation of FGF10. Furthermore, the protein was found localising to the cell nucleolus. Subsequent examination of the LADD-causing G138E, through site-directed mutagenesis, revealed its curious positioning within NLS1 and its role in abrogation of both, nuclear and secretory function of the FGF10. Additionally, specific combinatorial mutations within NLS2 abolished the protein’s nuclear translocation, yet did not diminish the protein’s progression through the secretory pathway, showing importance of this motif in the nuclear transport of FGF10. Interestingly, endogenous FGF10 was shown to disrupt differentiation of mesenchymal chondrogenitors, whereas externally applied protein caused the opposite effect, promoting cell differentiation, suggesting contrary function of paracrine and nuclear FGF10. Moreover, novel culture of hypothalamic Fgf10 expressing tanycytes derived from transgenic mice was generated and characterised, showing that intracrine FGF10 may be potentially implicated in control of cell cycle of neural stem cells
Development and Application of Software to Understand 3D Chromatin Structure and Gene Regulation
Nearly all cells contain the same 2 meters of DNA that must be systematically organized into their nucleus for timely access to genes in response to stimuli. Proteins and biomolecular condensates make this possible by dynamically shaping chromatin into 3D structures that connect regulators to their genes. Chromatin loops are structures that are partly responsible for forming these connections and can result in disease when disrupted or aberrantly formed. In this work, I describe three studies centered on using 3D chromatin structure to understand gene regulation. Using multi-omic data from a macrophage activation time course, we show that regulation temporally precedes gene expression and that chromatin loops play a key role in connecting enhancers to their target genes. In the next study, we investigated the role of biomolecular condensates in loop formation by mapping 3D chromatin structure in cell lines before and after disruption of NUP98-HOXA9 condensate formation. Differential analysis revealed evidence of CTCF-independent loop formation sensitive to condensate disruption. In the last study, we used 3D chromatin structure and multi-omic data in chondrocytes to link variant-gene pairs associated with Osteoarthritis (OA). Computational analysis suggests that a specific variant may disrupt transcription factor binding and misregulate inflammatory pathways in OA. To carry out these analyses I built computational pipelines and two R/Bioconductor packages to support the processing and analysis of genomic data. The nullranges package contains functions for performing covariate-matched subsampling to generate null-hypothesis genomic data and mitigate the effects of confounding. The mariner package is designed for working with large chromatin contact data. It extends existing Bioconductor tools to allow fast and efficient extraction and manipulation of chromatin interactions for better understanding 3D chromatin structure and its impact on gene regulation.Doctor of Philosoph
- …