2,891 research outputs found
Quantification of T-cell dynamics in health and disease : Mathematical modeling of experimental data
No full textAn essential branch of the adaptive immune system is formed by T cells which are produced in the thymus. The absence of T cells can be detrimental to the host as is the case in acquired immuno-deficiency syndrome (AIDS). The goal of this thesis is to gain insights into the dynamics of different T-cell subsets in healthy as well as disturbed situations. This information is important not only in understanding how the immune system is regulated normally, but also in guiding therapeutic strategies when the immune system gets disturbed. By combining mathematical modeling with experimental data, this thesis demonstrates how the two can complement each other in quantifying the kinetics of T cells , and in resolving some of the discrepancies in previous kinetic estimates and in the mechanisms of T-cell maintenance in mice and men. In young adult mice, we estimate that naive CD4 and CD8 T cells have expected life spans of 48 and 91 days, while CD4 and CD8 memory T cells have expected life spans of 12 and 17 days, respectively. Our analyses show that throughout life, naive T cell production in mice almost exclusively occurs in the thymus, which implies that in the event of lymphopenia in mice, thymic output is central to successful immune reconstitution. In contrast, studies based on T-cell receptor excision circles (TRECs) have suggested that in humans T-cell proliferation plays a key role in naive T-cell maintenance during adult life. Our results therefore highlight an important qualitative difference in T-cell dynamics between mice and humans. Extrapolation of experimental results from mice to humans should hence be done with caution. Recent work using deuterium labeling from our group indicated that in human adults naive T cells are kinetically homogeneous and very long-lived. This is in contrast to the current consensus that recent thymic emigrants (RTEs) form a separate short-lived sub-population of naive T cells. In several studies described in this thesis, we find no evidence that RTEs in either mice or men form a kinetically separate sub-population of naive T cells. The typical decline in CD4+ T-cell numbers that is observed during HIV infection is accompanied by a shift in the kinetics of both naive and memory CD4 and CD8 T cells to faster turnover rates compared to healthy controls. Our analyses show that in HIV-infected individuals, naive CD4 and CD8 T cells have a 3.3-12 fold shorter expected lifespan, and CD4 and CD8 memory T cells a 2.8-3.1 fold shorter expected lifespan compared to healthy controls. The increased T-cell loss rates in HIV infection are accompanied by higher per capita production rates of both naive and memory T cells. In naive T cells , this increased turnover can explain our observation that longitudinal TREC dynamics after infection are biphasic. In this case, HIV triggers a massive recruitment of naive T cells into the effector/memory compartment where they are quickly lost. We also predict shortening of naive T cell telomeres after HIV infection contrary to previous findings that telomeres are normal in HIV patients. This discrepancy can be attributed to the effect of individual variations when extrapolating cross-sectional data to longitudinal dynamics. We show that changes in thymic output, and T-cell death and proliferation rates tend to affect average TREC contents and telomere lengths similarly. Especially when naive T-cell life spans are affected, as is the case in HIV infection, the observed TREC dilution can only be explained by increased proliferation rates. Reduced thymic output could however add to the observed decline of naive T cells. Indeed, our mouse model of HIV-independent chronic immune activation shows that chronic immune activation is sufficient to cause severe naive T cell depletion, while decreased thymic output aggravates the naive T-cell loss. This suggests that therapeutic strategies for HIV infection that are aimed at boosting thymic function may fail to reconstitute the CD4 T cell pool if immune activation is not simultaneously kept under control
Exploring Evolution and Biology of Oomycetes: Integrative and Comparative Genomics
No full textDiseases that destroy livestock and crops have had catastrophic effects on human civilization, causing starvation and economical losses and continue to be a constant threat to global food production. Pathogenic species occur throughout the tree of life including many bacteria, eukaryotic microorganisms and metazoans. The fascinating taxonomic class of oomycetes unites several important pathogenic eukaryotes of plants and animals. We have witnessed considerable advances characterizing the (molecular) biology of these species, in particular their interactions with the hosts, in the last decades. Nevertheless, our current knowledge still lags behind the possibilities provided by large-scale (gen)omics data which is nowadays easily accessible. Comparative genomics and integrative bioinformatics provide an important framework to accompany and complement classical experimental work to advance our knowledge of these species. This thesis describes four complementary comparative genomic studies focusing on different aspects of cellular function and evolution of pathogenic oomycetes. The analyses presented in this thesis highlight the merit of integrative and comparative genomics as a pivotal tool to explore the biology and evolution of oomycetes. They provide (testable) hypotheses on the evolution, biology and the function of as yet uncharacterized gene products in oomycetes, thereby significantly advancing our knowledge on this intriguing group of organisms
Quantifying the dynamics of viruses and the cellular immune response of the host
No full textInfections can be caused by viruses, which attack certain cells within an infected host. However, the immune system of the host has evolved remarkable defense mechanisms that counter against an infection. In particular, so-called cytotoxic T lymphocytes can recognize and eliminate infected cells. This thesis makes use of mathematical models and computer simulations to describe the dynamics of a virus population and the cellular immune response within an infected host. Such research is of critical importance to better understand the nature of viral infections. In the beginning, questions on the HIV replication rate are addressed. It is investigated how rapid infected cells produce new virus particles and how rapid they die. It has been known that after HIV-infected patients start with antiretroviral drug treatment, the concentration of virus in the blood decreases rapidly. This observation has led to the conclusion that HIV-infected cells are short lived and that they die one to two days after they have been infected. Based on a new analysis, the thesis shows that HIV-infected cells might even live shorter than previously anticipated. Further, several models that describe the dynamics of viruses in presence of a cellular immune response are presented. They are used to investigate the ability of the immune response to suppress the replication of the virus. In the case of the chronic infection with HIV, it is shown how the virus can mutate and avoid recognition and elimination by the immune response. This process is attributed to the failing of HIV-infected patients to control the infection and it is shown how rapid the virus can escape the immune response. Finally, the thesis deals with viral infections in different host species, such as mice, macaques and humans. Therefore, it is discussed as to whether the findings on the influence of the immune response on the viral replication can be generalized. Although some differences in the results can be attributed to the body weight of the host species, additional research is needed to shed more light on the question whether the nature of viral infections is affected by the size of their host
Small homologous blocks in phytophthora genomes do not oint to an ancient whole-genome duplication
No full textGenomes of the plant-pathogenic genus Phytophthora are characterized by small duplicated blocks consisting of two consecutive genes (2HOM blocks) as well as by an elevated abundance of similarly aged gene duplicates. Both properties, in particular the presences of 2HOM blocks, have been attributed to a whole-genome duplication (WGD) at the last common ancestor of Phytophthora. However large intra-species synteny - compelling evidence for a WGD - has not been detected. Here we revisited the WGD hypothesis by deducing the age of 2HOM blocks. Two independent timing methods reveal that the majority of 2HOM blocks arose after divergence of the Phytophthora lineages. In addition, a large proportion of the 2HOM block copies co-localize on the same scaffold. Therefore, the presence of 2HOM blocks does not support a WGD at the last common ancestor of Phytophthora. Thus, genome evolution of Phytophthora is likely driven by alternative mechanisms, such as bursts of transposon activity
Mechanisms of Ventricular Fibrillation : The role of mechano-electrical feedback and tissue heterogeneity
No full textThe heart is a muscular organ that pumps blood throughout the body. The human heart contracts approximately once per second, adding up to more than 2.5 billion contractions over 80 years. Failure in cardiac contraction leads to sudden cardiac death, which is one of the most common causes of death in the industrialized world. In most cases this is caused by ventricular fibrillation (VF). During VF turbulent excitation patterns occur, causing uncoordinated contraction of the ventricles. If VF is not halted by means of defibrillation, blood circulation will cease, causing cardiac death within minutes. One important tool to study the mechanisms underlying cardiac physiology, is mathematical modeling. Over the last decades mathematical models ranging from single cell dynamics to complex three-dimensional whole organ models have been used to study cardiac arrhythmias. The focus of this thesis is to gain more insight in the underlying mechanisms of VF using electrophysiological and mechanical models of the human heart. We are especially interested in mechano-electrical feedback and in the role of tissue heterogeneity in the onset of cardiac arrhythmias. In the first part of this thesis we investigated the basic effects of mechano-electrical feedback in two-dimensional systems using simple low dimensional models to describe cardiac excitable behavior. In the second part of this thesis we used anatomically based models of the human ventricles to study the mechanisms and dynamics of VF and investigated the effects of tissue heterogeneity and mechano-electrical feedback. The most important conclusions regarding mechano-electrical feedback is that local tissue deformations can lead to automatic pacemaker activity via the stretch-activated channels, and that local stretch of fibers can cause an otherwise stable spiral wave to break up. The most important conclusions regarding tissue heterogeneity is that action potential duration restitution heterogeneity is not only important for the initiation of wavebreaks and re-entry, but also affects the dynamics of ventricular fibrillation. Furthermore, different initial conditions can lead to different mechanisms of ventricular fibrillation: either mother rotor or multiple wavelet ventricular fibrillation. These results indicate that mechano-electrical feedback and tissue heterogeneity may play an important role in the initiation and dynamics of ventricular fibrillation. Hence, reducing electrophysiological heterogeneity may be a fruitful target for therapeutic intervention
The interplay between genome and network evolution in eukaryotes
No full textWe assume that the functional relations that a protein engages in, influences it’s evolutionary dynamics. An extreme case is a functional module in which all components are strongly dependent on each other, for example a protein complex or metabolic pathway. If a protein’s function is only relevant on the level of the module, selection will act on module level as well. This leads to distinct phylogenetic patterns: either the module is completely present or completely absent. In other words, the functional module is also an evolutionary module. Surprisingly, we find that most functional modules do not behave like evolutionary modules. In order to remove any biases resulting from erroneous module definitions, we filter our functional modules using high-throughput protein interaction data as well as by cross-comparing different module datasets. We observe only a minor increase in evolutionary modularity. Without strong module-level selection, how is the modular structure of the cellular organization maintained? To answer this question, we represent the molecular machinery as a network of interacting proteins and infer how this network may have evolved. We use an existing model in which networks grow through gene duplication followed by subfunctionalization, to simulate network evolution. Networks that are produced by this model, have a modular structure that is similar to that of real protein interaction networks. We increase the biological relevance of this model by incorporating gene loss. We find that in this extended model, modularity is more easily established and maintained. Importantly, we find that if duplication of existing interactions is the only source of new connections, networks tend to break up. This strongly suggests that gain of completely novel interactions is pivotal in network evolution. In addition to comparing purely topological characteristics of model networks with those of real large-scale protein interaction networks, we study how proteins of different ages are connected in different networks. Previous studies report that protein tend to interact with priteins of a similar age and we demonstrate that this can be partially explained by the process of gene duplcation followed by subfunctionalization. In conclusion, we find that the organization of proteins in specific modules is not conserved in evolution: functional modules do not necessarily behave as evolutionary modules. Moreover, we find that functional modules can spontaneously arise from basic, local evolutionary processes, such as gene duplication
A license to kill: The evolution of NK cell receptors
No full textNatural killer (NK) cells innate immune cells that play a crucial role against viral infections and tumors. To be tolerant against healthy tissue and simultaneously attack infected cells, the activity of NK cells must be tightly regulated. Unlike B and T cells, NK cell do not undergo DNA rearrangements to generate a diverse repertoire of cell surface receptors. Instead, NK cells use a sophisticated array of germline-encoded activating and inhibiting receptors. The best characterized mechanism of NK cell activation is “missing self” detection, i.e. the recognition of virally infected or transformed cells that reduce their MHC expression to evade cytotoxic T cells. To monitor the expression of MHC-I on target cells, NK cells have monomorphic inhibitory receptors which interact with conserved MHC molecules. However, there are other NK cell receptors (NKRs) encoded by gene families showing a remarkable genetic diversity. Thus, NKR haplotypes contain several genes encoding for receptors with activating and inhibiting signaling, and that vary in gene content and allelic polymorphism. But if missing-self detection can be achieved by a monomorphic NKR system why have these polygenic and polymorphic receptors evolved? In this thesis, we use computational evolutionary modelling, data analysis, and mathematical modelling to answer the question of why NK cell receptors have evolved to become specific, polygenic, and polymorphic. We propose that NKRs might have possibly diversified due to the selection pressure imposed by the successful immunoevasive mechanisms evolved by several pathogens. We focus on different hypotheses related to viral evasion mechanisms, i.e. we study the effects of viral evolution of MHC-decoys, and selective MHC down-regulation on the evolution of NK cell receptors. Additionally, we study whether NKRs should diversify to be able to detect peptides of viral origin presented on MHC molecules. We find that NK cell receptors evolve to become specific to distinguish self from non-self and that the required specificity selects for the evolution of polygenicity and polymorphism. The degree of the evolved genetic diversity varies depending on the viral strategy used to escape the NK cell response. While our studies suggest that selective MHC downregulation and peptide sensitivity can drive the evolution of polygenic haplotypes encoding NK cell receptors, the highest genetic diversity evolves in host populations infected with viruses that readily evolve MHC-like decoys. The results in this thesis shed light on the evolutionary processes of NK cell receptors, providing plausible explanations for this fascinating complex system
A detailed comparison of peptides presented by different HLA class I loci: an in silico approach
No full textHuman Leukocyte Antigen (HLA) class I is a group of genes located on human chromosome 6 which play a crucial role in initiating potentially protective immune responses, by presenting pathogen-derived peptides to CD8+ T cells and thus targeting infected cells for elimination. Compare to other HLA class I loci, HLA-B molecules show some specific characteristics: 1) HLA-B alleles have been associated with opposing disease outcomes, namely susceptibility to, or protection from, parasitic and viral infection. 2) HLA-B elicits more dominant T cell responses with higher frequencies or superior magnitude. In order to discover potential mechanisms which may explain why HLA-B restricted T cell responses tend to be immunodominant, the focus of my PHD project has been on an extensive comparison of HLA-A and HLA-B antigen presentation by analysing their ligands. Besides the experimental verified epitopes downloaded, filtered and analyzed from several public databases, I also selected and applied in silico predictions based on different research questions for main steps of antigen presentation pathway : MHC binding (SMM, NetMHC, NetMHCpan), TAP binding probability (SMM) and proteasome cleavage (SMM or NetChop), as a compensatory of potential bias made by experimental data. Since the differences in CD8+ T cell responses mediated via HLA-A and HLA-B molecules might already begin at the antigen presentation level, in chapter 2 we have analyzed the epitope diversity and epitope binding affinity of this two major HLA class I loci. Opposite to our expectation, the amount of epitopes presented by HLA-A molecules is more than that of their HLA-B counterparts with higher binding affinities. Alternatively, targeting more constrained regions of a pathogen genome might be favourable for the outcome of an infection. Thus in chapter 3 we compared CTL epitopes restricted by HLA-A and HLA-B molecules and found that HLA-B molecules prefer to present more epitopes from certain conserved proteins. Moreover the residues targeted by HLA-B alleles in HIV-proteome were significantly more conserved than the ones targeted by HLA-A alleles. In order to explore if similar mechanism occurs in other infectious disease, in chapter 4 a similar analysis was applied on HCV proteome. As a result, we found that HLA molecules associated with HCV clearance preferentially present epitopes from the conserved proteins, like NS5B and Core. In addition, we found that less promiscuous peptide presentation might contribute to viral control during HIV-1 infection (chapter 5). To test whether the HLA promiscuity across loci has an effect on the frequencies of HLA class I haplotypes, we estimated the ligand repertoires for all HLA class I haplotypes (HLA-A-B) by in silico prediction and found that the most common HLA-A-B haplotypes are enriched in HLA-A and HLA–B pairs with distinct peptide binding motifs (chapter 6). In summary, this research implies that factors other than antigen presentation might be more essential for the protective and immunodominant nature of HLA-B-restricted T cell responses. It will also give mre support information for identifying interesting epitopes which could be good candidates for vaccine design
Biomarkers in cancer immunotherapy
Get PDFAntibodies against T cell checkpoint molecules have started to revolutionize cancer treatment. Nevertheless, less than half of all patients respond to these immunotherapies. Recent work supports the potential value of biomarkers that predict therapy outcome and inspires the development of assay systems that interrogate other aspects of the cancer-immunity cycle
Multilevel Evolution and the Emergence of Function
No full textIn this thesis we have researched how novel functions arise through Darwinian Evolution. Evolution has been generating novel traits, forms and functions since its inception, about four billion years ago. Cellular life did not exist at such an early evolutionary stage and instead, according to the RNA world hypothesis, RNAs functioned both as information storage medium (the role of DNA today) and as chemical reaction catalyst (the role of proteins). Because such RNAs catalysed each other's replication (i.e. replication is an altruistic trait), parasites that were replicated but did not spend any time replicating others should have been selected. Was the survival of replicators threatened by this? How could stronger replicators evolve if selection favoured parasites? In Chapter 2 we show that stronger parasites aid indirectly the evolution of stonger replicators thanks to a feedback process driven by the spatial self-organsation of the two species. The problem of the evolution of altruistic and cooperative traits is not limited to the RNA world, but extends to present day organisms as well. One example is the production of shared but costly, useful substances - so called public good - by many microorganisms. Selfish individuals that do not produce public good can thrive by exploiting cooperative individuals, but the system collapses if nobody produces public good. Should public good production be counter-selected when costs are larger because selection for selfishness intensifies? In Chapter 3 we show that selfish individuals evolve at higher costs and organise in space with cooperators. Spatial self-organisation feeds back on the evolution of public good production of cooperators, that become more cooperative, and selfish individuals, that become more selfish. In Chapter 4 we endow interacting RNA-like replicators with genotype and phenotype, respectively nucleotide sequence and secondary structure, and we study the evolutionary consequences of a complex genotype to phenotype map (RNA folding) at high mutation rates. We find that a functional ecosystem emerges, in which novel functions are associated to sequences that cannot be replicated. Such ecosystem enhances the survival of a single (master) sequence. In turn, this sequence contains the entire information to generate the functional ecosystem, and this information is decoded via the mutational process. The stabilising effect of mutations was experimentally observed in yeast's rRNA gene cluster, where mutations ensuing from transcription-replication conflicts are exploited to increase rRNA gene copy number depending on resource availability. In Chapter 5 we model yeast's rRNA mutational dynamics and find that larger rates of mutations are beneficial for long term genome integrity when they are biased towards gene duplications and deletions, even though their short term effect is near-neutral, as is the the case for yeast's rRNA. In conclusion, the results presented in this thesis highlight the merit of a multilevel approach for understanding evolution and its endless inventivity
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