Predicting the Distribution of Spiral Waves from Cell Properties in a Developmental-Path Model of Dictyostelium Pattern Formation

The slime mold Dictyostelium discoideum is one of the model systems of biological pattern formation. One of the most successful answers to the challenge of establishing a spiral wave pattern in a colony of homogeneously distributed D. discoideum cells has been the suggestion of a developmental path the cells follow (Lauzeral and coworkers). This is a well-defined change in properties each cell undergoes on a longer time scale than the typical dynamics of the cell. Here we show that this concept leads to an inhomogeneous and systematic spatial distribution of spiral waves, which can be predicted from the distribution of cells on the developmental path. We propose specific experiments for checking whether such systematics are also found in data and thus, indirectly, provide evidence of a developmental path

Computational aspects of cellular intelligence and their role in artificial intelligence.

The work presented in this thesis is concerned with an exploration of the computational aspects of the primitive intelligence associated with single-celled organisms. The main aim is to explore this Cellular Intelligence and its role within Artificial Intelligence. The findings of an extensive literature search into the biological characteristics, properties and mechanisms associated with Cellular Intelligence, its underlying machinery - Cell Signalling Networks and the existing computational methods used to capture it are reported. The results of this search are then used to fashion the development of a versatile new connectionist representation, termed the Artificial Reaction Network (ARN). The ARN belongs to the branch of Artificial Life known as Artificial Chemistry and has properties in common with both Artificial Intelligence and Systems Biology techniques, including: Artificial Neural Networks, Artificial Biochemical Networks, Gene Regulatory Networks, Random Boolean Networks, Petri Nets, and S-Systems. The thesis outlines the following original work: The ARN is used to model the chemotaxis pathway of Escherichia coli and is shown to capture emergent characteristics associated with this organism and Cellular Intelligence more generally. The computational properties of the ARN and its applications in robotic control are explored by combining functional motifs found in biochemical network to create temporal changing waveforms which control the gaits of limbed robots. This system is then extended into a complete control system by combining pattern recognition with limb control in a single ARN. The results show that the ARN can offer increased flexibility over existing methods. Multiple distributed cell-like ARN based agents termed Cytobots are created. These are first used to simulate aggregating cells based on the slime mould Dictyostelium discoideum. The Cytobots are shown to capture emergent behaviour arising from multiple stigmergic interactions. Applications of Cytobots within swarm robotics are investigated by applying them to benchmark search problems and to the task of cleaning up a simulated oil spill. The results are compared to those of established optimization algorithms using similar cell inspired strategies, and to other robotic agent strategies. Consideration is given to the advantages and disadvantages of the technique and suggestions are made for future work in the area. The report concludes that the Artificial Reaction Network is a versatile and powerful technique which has application in both simulation of chemical systems, and in robotic control, where it can offer a higher degree of flexibility and computational efficiency than benchmark alternatives. Furthermore, it provides a tool which may possibly throw further light on the origins and limitations of the primitive intelligence associated with cells

Control of pattern formation in excitable systems

Pattern formation embodies the beauty and complexity of nature. Some patterns like traveling and rotating waves are dynamic, while others such as dots and stripes are static. Both dynamic and static patterns have been observed in a variety of physiological and biological processes such as rotating action potential waves in the brain during sleep, traveling calcium waves in the cardiac muscle, static patterns on the skins of animals, and self-regulated patterns in the animal embryo. Excitable systems represent a class of ultrasensitive systems that are capable of generating different kinds of patterns depending on the interplay between activator and inhibitor dynamics. Through manipulation of different excitable parameters, a diverse array of traveling wave and standing wave patterns can be obtained. In this thesis, I use pattern formation theory to control the excitable systems involved in cell migration and neuroscience to alter the observed phenotype, in an attempt to affect the underlying biological process. Cell migration is critical in many processes such as cancer metastasis and wound healing. Cells move by extending periodic protrusions of their cortex, and recent years have shown that the cellular cortex is an excitable medium where waves of biochemical species organize the cellular protrusion. Altering the protrusive phenotype can drastically alter cell migration — that can potentially affect critical physiological processes. In the first part of this thesis, I use excitable wave theory to model and predict wave pattern changes in amoeboid cells. Using theories of pattern formation, key nodes of the underlying excitable network governing cell migration are altered — to drastically change the cellular migratory phenotype, moving from amoeboid cells to oscillatory cells and from cells that extend long finger-like protrusions to cells that sustain stable rings on the cortex, potentially uncovering a novel method of pattern formation. Excitable systems originated in neuroscience, where different patterns of activity reflect different brain states. Sleep is associated with slow waves, while repeated high-frequency waves are associated with epileptic seizures. These patterns arise from the interplay between the cerebral cortex and the thalamus, which form a closed-loop architecture. In the second part of this thesis, I use a three-layer two-dimensional thalamocortical model, to explore the different parameters that may influence different spatio-temporal dynamics on the cortex. This study reveals that inter- and intra-cortical connectivity, excitation-inhibition balance and synaptic strengths can influence the wave activity patterns, to recreate different dynamic patterns observed in different brain states

Articles indexats publicats per investigadors del Campus de Terrassa: 2013

Aquest informe recull els 228 treballs publicats per 177 investigadors/es del Campus de Terrassa en revistes indexades al Journal Citation Report durant el 2013Preprin

Holocene palaeohydrology from testate amoebae analysis: developing a model for British peatlands

Merged with duplicate record 10026.1/841 on 27.03.2017 by CS (TIS)Testate amoebae (Protozoa: Rhizopoda) are particularly abundant in peatlands. Previous studies have used testate amoebae in palaeoenvironmental studies, but have used qualitative data only, so that results are expressed only in terms of 'wet', 'dry' or 'moist'. This study uses testate amoebae to derive quantitative reconstructions of mire surface wetness for part of the Holocene and is split into two parts. The first part of this study modelled the responses of individual testate amoebae species to environmental variables on ombrotrophic mires, since the peatland-climate link makes these habitats the one of the most useful in palaeoclimate reconstructions. 163 samples of modern testate amoebae faunas were obtained from 9 ombrotrophic mires across Britain. Environmental variables (mean annual water table, moisture content, dissolved organic carbon, pH, Ca^*, Mg^*, SO^^', CI", conductivity and host plant species) were measured. A hydrological monitoring programme on an ombrotrophic mire on Dartmoor provided a detailed record of hydrology and selected water chemistry over a year and identified the season most representative of mean annual environmental conditions. Weighted averaging regression applied to the faunas provided absolute moisture content and mean annual water table optima for 38 common testate amoebae species. In the second part of the study weighted averaging calibration was used to derive transfer functions from the modern species' optima. From these, mean annual water table and substrate moisture content were reconstructed for the top 100 cm of a selected fossil peat core from Bolton Fell Moss, Cumbria. These reconstructions were compared with those derived from plant macrofossil and peat humification analyses. Testate amoebae provided a further insight into the decline of Sphagnum imbricatum, clarified noisy areas of the existing palaeohydrological record and suggested that hydrological changes at Bolton Fell Moss were likely to have been gradual, rather than the sudden event implied by the plant macrofossil record. This study demonstrates the future potential of testate amoebae as palaeohydrological indicators. Expansion of the modem data set in terms of species composition and geographical extent, further applications of testate amoebae into multi-proxy palaeohydrological reconstructions and taxonomic refinements are suggested to improve the technique further

Articles indexats publicats per investigadors del Campus de Terrassa: 2012

Aquest infrome recull els 221 treballs publicats per 216 investigadors/es del Campus de Terrassa en revistes indexades al Journal Citation Report durant el 2012Preprin

Advancing cell signaling interrogation using theoretical and experimental approaches in eukaryotic model systems

Understanding how cells use intracellular signaling to detect environmental changes and alter behaviors is essential for understanding a wide range of biological processes. The current gap of understanding resides in time-changing signals in individual cells (signaling dynamics) and cell-cell communication in multicellular contexts. Here, we used theoretical and experimental approaches to study cell signaling in two eukaryotic model systems, with a specific focus on processes that involve signaling dynamics and cell-cell communication. First, we focus on the starvation-induced population-level signaling oscillations in the social amoebae, Dictyostelium discoideum. By constructing a unifying theoretical framework, we were able to directly compare existing models and experimental data. From this systematic investigation, we identified that the key features in single-cell signaling networks that coordinate population-level oscillations are adaptive spiking and fold-change detection. We then applied experimental approaches to interrogate how temporal changes in a signaling molecule modulate cell behaviors ("signal decoding") and how environmental cues modulate the dynamics of a signaling molecule ("environment encoding") in mammalian fibroblast cells. First, we explored the impact of transient, direct activation of the cAMP pathway on cell migration using an optogenetic tool. We found that cell migration is inhibited by repetitive transient activation of the cAMP pathway, and the inhibitory effect depends on the extent of activation. By characterizing a series of single-cell behaviors, we found that transient activation of the cAMP pathway induces reversible cell contractile force relaxation and actin cytoskeleton reorganization, both of which can potentially mediate migration inhibition. Further, we confirmed that the induced actin cytoskeleton reorganization is mediated by calcium signaling. Next, we investigated cytosolic calcium dynamics in the presence of a common culture media supplement, serum. We found serum induces trains of calcium spikes and further identified a major serum component mediating this response as lysophosphatidic acid (LPA). Although features of calcium spiking display a great amount of variability among cells, the faction of spiking cells and spiking frequency generally encode the concentration of environmental LPA. Through a series of pharmaceutical inhibitor experiments, we identified major sources of calcium ions as well as other pathways that shape calcium spiking. This body of work demonstrates the different utilities of theoretical modeling and experiments in understanding cell signaling which provides an advanced understanding of biological processes that involve signaling dynamics or cell-cell communication

An analysis of selected secretion systems of Pseudomonas species

Direct secretion systems which deliver molecules from one cell to another have huge significance in shaping bacterial communities or in determining the outcome of bacterial associations with eukaryotic organisms. This work examines the roles of the Type III Secretion System (T3SS) and the Type VI Secretion System (T6SS) systems of Pseudomonas, a widespread genus including clinical pathogens and biocontrol strains. Bioinformatic analysis of T6SS phylogeny and associated gene content within Pseudomonas identified several T6SS phylogenetic groups, and linked T6SS components VgrG and Hcp encoded outside of T6SS gene loci with their cognate T6SS phylogenetic groups. Remarkably, such “orphan” vgrG and hcp genes were found to occur in diverse, horizontally transferred, operons often containing putative T6SS accessory components and effectors. The prevalence of a widespread superfamily of T6SS lipase effectors (Tle) was assessed in metagenomes from various environments. The abundance of the Tle superfamily and individual families varied between niches, suggesting there is niche specific selection and specialisation of Tle. Experimental work also discovered that P. fluorescens F113 uses the SPI-1 T3SS to avoid amoeboid grazing in mixed populations. This finding may represent a significant aspect of F113 rhizocompetence, and the rhizocompetence of other Rhizobacteria

A complex systems approach to education in Switzerland

The insights gained from the study of complex systems in biological, social, and engineered systems enables us not only to observe and understand, but also to actively design systems which will be capable of successfully coping with complex and dynamically changing situations. The methods and mindset required for this approach have been applied to educational systems with their diverse levels of scale and complexity. Based on the general case made by Yaneer Bar-Yam, this paper applies the complex systems approach to the educational system in Switzerland. It confirms that the complex systems approach is valid. Indeed, many recommendations made for the general case have already been implemented in the Swiss education system. To address existing problems and difficulties, further steps are recommended. This paper contributes to the further establishment complex systems approach by shedding light on an area which concerns us all, which is a frequent topic of discussion and dispute among politicians and the public, where billions of dollars have been spent without achieving the desired results, and where it is difficult to directly derive consequences from actions taken. The analysis of the education system's different levels, their complexity and scale will clarify how such a dynamic system should be approached, and how it can be guided towards the desired performance