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Untersuchung von gene-drive-Strategien als neue Interventionsstrategien zur Eindämmung der Malaria
(2008)
In der vorliegenden Arbeit haben wir unter Nutzung bioinformatischer Methoden eine innovative Strategie zur Eindämmung der Malaria entwickelt. Die genetische Modifikationsstrategie beinhaltet sowohl Manipulationen aufseiten des gefährlichsten Erregers, Plasmodium falciparum, als auch des Hauptvektors, Anopheles gambiae. In den Genomen beider Spezies wurden eine Reihe neuer konkreter targets identifiziert. Auch bereits beschriebene targets und Ansätze wurden in die Strategie einbezogen bzw. weiter ausgestaltet. Bezüglich der Vektormoskitos wird die Verbreitung eines gegenüber Plasmodien resistenten Genotyps angestrebt. Es werden einerseits effiziente natürliche und künstliche Resistenzgene diskutiert und andererseits eine bekannte Strategie zur Fixierung natürlicher Resistenzallele in natürlichen Populationen verbessert. Auf der Seite der Plasmodien erweiterten wir einen bereits von A. Burt (2003) beschriebenen Eradikationsansatz um weitere targets. Aus ethischen und evolutionsbiologischen Erwägungen bevorzugen wir jedoch eine alternative Strategie, welche die Etablierung von in ihrer Virulenz gemilderten Parasiten zum Ziel hat. Der attenuierte Genotyp wird unter anderem durch komplexe Pathway-Remodellierungen beschrieben (Löwe, Sauerborn, Schirmer, Dandekar, A refined genome engineering strategy against parasites and vectors, Manuskript beim Journal „Genome Biology“ eingereicht). Da sich Mutanten in der Natur gegen Wildtyp-Organismen kaum durchsetzen können, werden zwei drive-Systeme beschrieben, welche für die Implementierung der genetischen Manipulationsstrategie entwickelt wurden. Beide Konstrukte wurden zur Patentierung angemeldet (Patentanmeldung U30010 DPMA bzw. Aktenzeichen 102006029354.1). Zusätzlich zur deutschen wurde für eines der beiden Konstrukte eine PCT-Anmeldung eingereicht, welche in Zukunft einen internationalen Patentschutz ermöglichen soll. Es werden Kalkulationen vorgelegt, welche die Verbreitungstendenzen der Konstrukte in natürlichen Populationen vorhersagen. Die Beschreibung der entwickelten Konstrukte beschränkt sich nicht auf das primäre Anwendungsgebiet der Arbeit (Malaria), sondern beinhaltet auch andere Anwendungsgebiete, vor allem im Bereich der Medizin und Molekularbiologie.
Amphibians evolved in the Devonian period about 400 Mya and represent a transition step in tetrapod evolution. Among amphibians, high-throughput sequencing data are very limited for Caudata, due to their largest genome sizes among terrestrial vertebrates. In this paper we present the transcriptome from the fire bellied newt Cynops orientalis. Data here presented display a high level of completeness, comparable to the fully sequenced genomes available from other amphibians. Moreover, this work focused on genes involved in gametogenesis and sexual development. Surprisingly, the gsdf gene was identified for the first time in a tetrapod species, so far known only from bony fish and basal sarcopterygians. Our analysis failed to isolate fgf24 and foxl3, supporting the possible loss of both genes in the common ancestor of Rhipidistians. In Cynops, the expression analysis of genes described to be sex-related in vertebrates singled out an expected functional role for some genes, while others displayed an unforeseen behavior, confirming the high variability of the sex-related pathway in vertebrates.
In the various groups of social bees, different systems of communication about food sources occur. These communication systems are different solutions to a common problem of social insects: efficiently allocating the necessary number of workers first to the task of foraging and second to the most profitable food sources. The solution chosen by each species depends on the particular ecological circumstances as well as the evolutionary history of that species. For example, the outstanding difference between the bumble bee and the honey bee system is that honey bees can communicate the location of profitable food sources to nestmates, which bumble bees cannot. To identify possible selection pressures that could explain this difference, I have quantified the benefits of communicating location in honey bees. I show that these strongly depend on the habitat, and that communicating location might not benefit bees in temperate habitats. This could be due to the differing spatial distributions of resources in different habitats, in particular between temperate and tropical regions. These distributions may be the reason why the mostly temperate-living bumble bees have never evolved a communication system that allows them to transfer information on location of food sources, whereas most tropical social bees (all honey bees and many stingless bees) are able to recruit nestmates to specific points in their foraging range. Nevertheless, I show that in bumble bees the allocation of workers to foraging is also regulated by communication. Successful foragers distribute in the nest a pheromone which alerts other bees to the presence of food. This pheromone stems from a tergite gland, the function of which had not been identified previously. Usage of a pheromone in the nest to alert other individuals to forage has not been described in other social insects, and might constitute a new mode of communicating about food sources. The signal might be modulated depending on the quality of the food source. Bees in the nest sample the nectar that has been brought into the nest. Their decision whether to go out and forage depends not only on the pheromone signal, but also on the quality of the nectar they have sampled. In this way, foraging activity of a bumble bee colony is adjusted to foraging conditions, which means most bees are allocated to foraging only if high-quality food sources are available. In addition, foraging activity is adjusted to the amount of food already stored. In a colony with full honeypots, no new bees are allocated to foraging. These results help us understand how the allocation of workers to the task of food collection is regulated according to external and internal nest conditions in bumble bees.
Sturgeon immunity is relevant for basic evolutionary and applied research, including caviar‐ and meat‐producing aquaculture, protection of wild sturgeons and their re‐introduction through conservation aquaculture. Starting from a comprehensive overview of immune organs, we discuss pathways of innate and adaptive immune systems in a vertebrate phylogenetic and genomic context. The thymus as a key organ of adaptive immunity in sturgeons requires future molecular studies. Likewise, data on immune functions of sturgeon‐specific pericardial and meningeal tissues are largely missing. Integrating immunological and endocrine functions, the sturgeon head kidney resembles that of teleosts. Recently identified pattern recognition receptors in sturgeon require research on downstream regulation. We review first acipenseriform data on Toll‐like receptors (TLRs), type I transmembrane glycoproteins expressed in membranes and endosomes, initiating inflammation and host defence by molecular pattern‐induced activation. Retinoic acid‐inducible gene‐I‐like (RIG‐like) receptors of sturgeons present RNA and key sensors of virus infections in most cell types. Sturgeons and teleosts share major components of the adaptive immune system, including B cells, immunoglobulins, major histocompatibility complex and the adaptive cellular response by T cells. The ontogeny of the sturgeon innate and onset of adaptive immune genes in different organs remain understudied. In a genomics perspective, our new data on 100 key immune genes exemplify a multitude of evolutionary trajectories after the sturgeon‐specific genome duplication, where some single‐copy genes contrast with many duplications, allowing tissue specialization, sub‐functionalization or both. Our preliminary conclusion should be tested by future evolutionary bioinformatics, involving all >1000 immunity genes. This knowledge update about the acipenseriform immune system identifies several important research gaps and presents a basis for future applications.
The human genome has been sequenced since 2001. Most proteins have been characterized now and with everyday more bioinformatical predictions are experimentally verified. A project is underway to sequence thousand humans. But still, little is known about the evolution of the human proteome itself. Domains and their combinations are analysed in detail but not all of the human domain architectures at once. Like no one before, we have large datasets of high quality human protein-protein-protein interactions and complexes available which allow us to characterize the human proteome with unmatched accuracy. Advanced clustering algorithms and computing power enable us to gain new information about protein interactions without touching a pipette. In this work, the human proteome is analysed at three different levels. First, the origin of the different types of proteins was analysed based on their domain architectures. The second part focuses on the protein-protein interactions. Finally, in the third part, proteins are clustered based on their interactions and non-interactions. Most proteins are built of domains and their function is the sum of their domain functions. Proteins that share the same domain architecture, the linear order of domains are homologues and should have originated from one common ancestral protein. This ancestor was calculated for roughly 750 000 proteins from 1313 species. The relations between the species are based on the NCBI Taxonomy and additional molecular data. The resulting data set of 5817 domains and 32868 domain architectures was used to estimate the origin of these proteins based on their architectures. It could be observed, that new domain architectures are only in a small fraction composed of domains arisen at the same taxon. It was also found that domain architectures increase in length and complexity in the course of evolution and that different organisms like worm, and human share nearly the same amount of proteins but differ in their number of distinct domain architectures. The second part of this thesis focuses on protein-protein interactions. This chapter addresses the question how new evolved proteins form connections within the existing network. The network built of protein-protein interactions was shown to be scale free. Scale free networks, like the internet, consist of few hubs with many connections and many nodes with few connections. They are thought to arise by two mechanisms. First, newly emerged proteins interact with proteins of the network. Second, according to the theory of preferential attachment, new proteins have a higher chance to interact with already interaction rich proteins. The Human Protein Reference Database provides an on in-vivo interaction data based network for human. With the data obtained from chapter one, proteins were marked with their taxon of origin based on their domain architectures. The interaction ratio of proteins of the same taxa compared to all interactions was calculated and higher values than the random model showed for nearly every taxa. On the other hand, there was no enrichment of proteins originated at the taxon of cellular organisms for the node degree found. The node degree is the number of links for this node. According to the theorie of preferential attachment the oldest nodes should have the most interactions and newly arisen proteins should be preferably attached to them not together. Both could not be shown in this analysis, preferential attachment could therefore not be the only explanation for the forming of the human protein interaction network. Finally in part three, proteins and all their interactions in the network are analysed. Protein networks can be divided into smaller highly interacting parts carrying out specific functions. This can be done with high statistical significance but still, it does not reflect the biological significance. Proteins were clustered based on their interactions and non-interactions with other proteins. A version with eleven clusters showed high gene ontology based ratings and clusters related to specific cell parts. One cluster consists of proteins having very few interactions together but many to proteins of two other clusters. This first cluster is significantly enriched with transport proteins and the two others are enriched with extracellular and cytoplasm/membrane located proteins. The algorithm seems therefore well suited to reflect the biological importance behind functional modules. Although we are still far from understanding the origin of species, this work has significantly contributed to a better understanding of evolution at the protein level and has, in particular, shown the relation of protein domains and protein architectures and their preferences for binding partners within interaction networks.
The Glycosylphosphatidylinositol Anchor: A Linchpin for Cell Surface Versatility of Trypanosomatids
(2021)
The use of glycosylphosphatidylinositol (GPI) to anchor proteins to the cell surface is widespread among eukaryotes. The GPI-anchor is covalently attached to the C-terminus of a protein and mediates the protein’s attachment to the outer leaflet of the lipid bilayer. GPI-anchored proteins have a wide range of functions, including acting as receptors, transporters, and adhesion molecules. In unicellular eukaryotic parasites, abundantly expressed GPI-anchored proteins are major virulence factors, which support infection and survival within distinct host environments. While, for example, the variant surface glycoprotein (VSG) is the major component of the cell surface of the bloodstream form of African trypanosomes, procyclin is the most abundant protein of the procyclic form which is found in the invertebrate host, the tsetse fly vector. Trypanosoma cruzi, on the other hand, expresses a variety of GPI-anchored molecules on their cell surface, such as mucins, that interact with their hosts. The latter is also true for Leishmania, which use GPI anchors to display, amongst others, lipophosphoglycans on their surface. Clearly, GPI-anchoring is a common feature in trypanosomatids and the fact that it has been maintained throughout eukaryote evolution indicates its adaptive value. Here, we explore and discuss GPI anchors as universal evolutionary building blocks that support the great variety of surface molecules of trypanosomatids.
This thesis extends the classical theoretical work of Macevicz and Oster (1976, expanded by Oster and Wilson, 1978) on adaptive life history strategies in social insects. It focuses on the evolution of dynamic behavioural patterns (reproduction and activity) as a consequence of optimal allocation of energy and time resources. Mathematical modelling is based on detailed empirical observations in the model species Lasioglossum malachurum (Halictidae; Hymenoptera). The main topics are field observations, optimisation models for eusocial life histories, temporal variation in life history decisions, and annual colony cycles of eusocial insects.
The degree of spatial variation relative to temporal variation influences evolution of dispersal
(2020)
In the face of ongoing global climate and land use change, organisms have multiple possibilities to cope with the modification of their environment. The two main possibilities are to either adapt locally or disperse to a more suitable habitat. The evolution of both local adaptation and dispersal interacts and can be influenced by the spatial and temporal variation (of e.g. temperature or precipitation). In an individual based model (IBM), we explore evolution of phenotypes in landscapes with varying degree of spatial relative to global temporal variation in order to examine its influence on the evolution of dispersal, niche optimum and niche width. The relationship between temporal and spatial variation did neither influence the evolution of local adaptation in the niche optimum nor of niche widths. Dispersal probability is highly influenced by the spatio‐temporal relationship: with increasing spatial variation, dispersal probability decreases. Additionally, the shape of the distribution of the trait values over patch attributes switches from hump‐ to U‐shaped. At low spatial variance more individuals emigrate from average habitats, at high spatial variance more from extreme habitats. The comparatively high dispersal probability in extreme patches of landscapes with a high spatial variation can be explained by evolutionary succession of two kinds of adaptive response. Early in the simulations, extreme patches in landscapes with a high spatial variability act as sink habitats, where population persistence depends on highly dispersive individuals with a wide niche. With ongoing evolution, local adaptation of the remaining individuals takes over, but simultaneously a possible bet‐hedging strategy promotes higher dispersal probabilities in those habitats. Here, in generations that experience extreme shifts from the temporal mean of the patch attribute, the expected fitness becomes higher for dispersing individuals than for philopatric individuals. This means that under certain circumstances, both local adaptation and high dispersal probability can be selected for for coping with the projected environmental changes in the future.
New experimental methods have drastically accelerated the pace and quantity at which biological data is generated. High-throughput DNA sequencing is one of the pivotal new technologies. It offers a number of novel applications in various fields of biology, including ecology, evolution, and genomics. However, together with those opportunities many new challenges arise. Specialized algorithms and software are required to cope with the amount of data, often requiring substantial training in bioinformatic methods. Another way to make those data accessible to non-bioinformaticians is the development of programs with intuitive user interfaces.
In my thesis I developed analyses and programs to tackle current problems with high-throughput data in biology. In the field of ecology this covers the establishment of the bioinformatic workflow for pollen DNA meta-barcoding. Furthermore, I developed an application that facilitates the analysis of ecological communities in the context of their traits. Information from multiple public databases have been aggregated and can now be mapped automatically to existing community tables for interactive inspection. In evolution the new data are used to reconstruct phylogenetic trees from multiple genes. I developed the tool bcgTree to automate this process for bacteria. Many plant genomes have been sequenced in current years. Sequencing reads of those projects also contain data from the chloroplasts. The tool chloroExtractor supports the targeted extraction and analysis of the chloroplast genome. To compare the structure of multiple genomes specialized software is required for calculation and visualization of the relationships. I developed AliTV to address this. In contrast to existing programs for this task it allows interactive adjustments of produced graphics. Thus, facilitating the discovery of biologically relevant information. Another application I developed helps to analyze transcriptomes even if no reference genome is present. This is achieved by aggregating the different pieces of information, like functional annotation and expression level, for each transcript in a web platform. Scientists can then search, filter, subset, and visualize the transcriptome.
Together the methods and tools expedite insights into biological systems that were not possible before.
In a nice assay published in Nature in 1993 the physicist Richard God III started from a human observer and made a number of witty conclusions about our future prospects giving estimates for the existence of the Berlin Wall, the human race and all the rest of the universe. In the same spirit, we derive implications for "the meaning of life, the universe and all the rest" from few principles. Adams´ absurd answer "42" tells the lesson "garbage in / garbage out" - or suggests that the question is non calculable. We show that experience of "meaning" and to decide fundamental questions which can not be decided by formal systems imply central properties of life: Ever higher levels of internal representation of the world and an escalating tendency to become more complex. An observer, "collecting observations" and three measures for complexity are examined. A theory on living systems is derived focussing on their internal representation of information. Living systems are more complex than Kolmogorov complexity ("life is NOT simple") and overcome decision limits (Gödel theorem) for formal systems as illustrated for cell cycle. Only a world with very fine tuned environments allows life. Such a world is itself rather complex and hence excessive large in its space of different states – a living observer has thus a high probability to reside in a complex and fine tuned universe.