Species interactions and diversity: A unified framework using Hill numbers

Biodiversity describes the variety of organisms on planet earth. Ecologists have long hoped for a synthesis between analyses of biodiversity and analyses of biotic interactions among species, such as predation, competition and mutualism. However, it is often unclear how to connect details of these interactions with complex modern analyses of biodiversity. To resolve this gap, we propose a unification of models of biotic interactions and measurements of diversity. We show that analyses of biodiversity obscure details about biotic interactions. For example, identical changes in biodiversity can arise from predation, competition or mutualism. Our approach indicates that traditional models of community assembly miss key facets of diversity change. Instead, we suggest that analyses of diversity change should focus on partitions, which measure mechanisms that directly shape changes in diversity, notably species level selection and immigration, rather than traditional analyses of biotic interactions

Mathematical modeling, simulation and analysis of metabolic oscillations in Bacillus subtilis biofilms

Metabolic oscillations in biofilms of Bacillus subtilis have been reported as periodic halting of growth in the expansion of the colony growing in a microfluidics chamber by Liu et al (2015). This thesis is aimed at understanding these oscillations through minimal dynamic model involving three ordinary differential equations (ODEs). The model is first applied in its basic form in order to describe the oscillations. Next, various modifications of the model are discussed in detail and the results of each modification are viewed in light of the underlying biology. The four modifications investigate the mechanism of oscillations with respect to spatial effects, reversible reactions and more robust reaction kinetics. Finally, we apply the minimal model in a broader perspective in order to understand population dynamics in a typical community of a social organism. We consider three interacting subpopulations of a species that have their own distinct phenotypes. None of the subpopulations have an absolute advantage over the other two. This gives rise to cyclic dynamics like the rock paper scissors game which is analysed using evolutionary game theory. We also present an asymmetrical two-player two- strategy game describing the same system, where the phenotype of each subpopulation is considered as a strategy. This investigation tests the ideal strategies for three different levels of antibiotic stress. We observe bet-hedging in the form of production of resistant cells which are a costly choice in the absence of the antibiotic stress. Although the population dynamics study is described with a broad range of applicability, we also discuss its applications in the B. subtilis biofilm

Species interactions and diversity: A unified framework using Hill numbers

Biodiversity describes the variety of organisms on planet earth. Ecologists have long hoped for a synthesis between analyses of biodiversity and analyses of biotic interactions among species, such as predation, competition, and mutualism. However, it is often unclear how to connect details of these interactions with complex modern analyses of biodiversity. To resolve this gap, we propose a unification of models of biotic interactions and measurements of diversity. We show that analyses of biodiversity obscure details about biotic interactions. For example, identical changes in biodiversity can arise from predation, competition or mutualism. Our approach indicates that traditional models of community assembly miss key facets of diversity change. Instead, we suggest that analyses of diversity change should focus on partitions, which measure mechanisms that directly shape changes in diversity, notably species level selection and immigration, rather than traditional analyses of biotic interactions

Mechanisms of delivery and mode of action of type VI secretion system effectors

In order to manipulate their environment, bacteria evolved a diverse set of secretion systems. Three of these were found to be able to inject their substrates directly into target cells, the type VI secretion system (T6SS) being the most recently discovered of these. The T6SS shares structural and functional homology with other contractile nanomachines such as the contractile phages. It is capable of delivering its substrates into both pro- and eukaryotes in a contact dependent manner and has become a major player in the field of microbial interactions. Recently, medium and high resolution structural data of T6SS subcomplexes and in situ structures provided detailed mechanistic insights into its functioning, further supported by live cell fluorescence microscopy of the assembly dynamics. Nonetheless, the role of some of the conserved core components is not yet fully understood even less so for the associated components. Moreover, despite its implication in numerous processes, the effector repertoire remains poorly characterized. In this thesis, both the effector repertoire and the functional contribution of selected T6SS components were characterized in Acinetobacter baylyi ADP1. We developed a new scarless chromosomal mutagenesis method for A. baylyi ADP1 and fluorescently labeled structural components of the T6SS using this method. Furthermore, we constructed in frame deletions of selected T6SS components and evaluated their role by observing the T6SS dynamics, secretion capacity, target cell lysis and the ability to inhibit a competitor. The results of the fluorescence microscopy in combination with the sensitive lysis assay show that certain components, previously thought to be required for T6SS assembly, are in fact dispensable. Furthermore, we observed that most mutations which diminished the T6SS activity reduced the number of active T6SS structures but did not affect the sheath dynamics. This indicates, that these components are involved in a step preceding the contractile tail formation. Despite ongoing concerted efforts, we were so far unable to fluorescently label secreted components. We identified and characterized five cargo effectors and their corresponding immunity proteins. One of the effectors was disrupted by an insertion element and could be restored. All five effectors exhibited antibacterial activity and did not cross-react with non-cognate immunity proteins. The morphological changes of prey cells targeted by the effectors were observed by fluorescence microscopy of competition mixtures and allowed us to confirm the predicted peptidoglycan amidase activity of Tae1 and the phospholipase activity of Tle1. Although the bioinformatic predictions together with the observed morphological changes and the lysis phenotype of prey cells targeted by the remaining effectors hinted at the subcellular location of their respective targets, the targets themselves remain to be identified. Furthermore, we constructed an effector deficient strain which retained wild-type T6SS activity and elicited the retaliatory attack of Pseudomonas aeruginosa, but failed to inhibit or lyse prey cells. Transcriptome data further indicated, that the damage inflicted by the effector deficient strain does not induce a stress response in the prey. Recently the T6SS was shown to be involved in the horizontal gene transfer of naturally competent Vibrio cholerae. Since A. baylyi ADP1 is known to be naturally competent, we tested whether its T6SS also contributes to horizontal gene transfer. Not only could we demonstrate that the T6SS facilitates the acquisition of DNA from prey cells, but also that lytic effectors are superior to non-lytic effectors suggesting that a lytic effector set may increase the ability to acquire DNA from a diverse range of bacteria. These findings provide further evidence that the T6SS mediated horizontal gene transfer may be a general characteristic of naturally competent bacteria bearing a T6SS. To better understand the role of the T6SS in shaping polymicrobial communities, we employed individual based modelling of interbacterial competition mixtures, the results of which we confirmed by performing the corresponding bacterial competition. We found that the contact dependent antagonistic interactions led to a segregation of the competitors minimizing their contact surface. Once segregated, the prey cells were able to survive or even outgrow the attack of a predator so long as the growth within the domain equaled or outweighed the killing on the surface of the domain. We further demonstrated that this critical domain size, beyond which the prey would survive, depends on the growth rate ratio of the competitors and the attack rate. Recently, others showed that this segregation of the competitors promotes the evolution of public goods

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Task Allocation in Foraging Robot Swarms:The Role of Information Sharing

Autonomous task allocation is a desirable feature of robot swarms that collect and deliver items in scenarios where congestion, caused by accumulated items or robots, can temporarily interfere with swarm behaviour. In such settings, self-regulation of workforce can prevent unnecessary energy consumption. We explore two types of self-regulation: non-social, where robots become idle upon experiencing congestion, and social, where robots broadcast information about congestion to their team mates in order to socially inhibit foraging. We show that while both types of self-regulation can lead to improved energy efficiency and increase the amount of resource collected, the speed with which information about congestion flows through a swarm affects the scalability of these algorithms