Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution Observatory: Toward Prediction of Coupled Hydrological, Biogeochemical, and Ecological Change

Understanding the process interactions and feedbacks among water, porous geological media, microbes, and vascular plants is crucial for improving predictions of the response of Earth’s critical zone to future climatic conditions. However, the integrated coevolution of landscapes under change is notoriously difficult to investigate. Laboratory studies are limited in spatial and temporal scale, while field studies lack observational density and control. To bridge the gap between controlled laboratory and uncontrollable field studies, the University of Arizona built a macrocosm experiment of unprecedented scale: the Landscape Evolution Observatory (LEO). LEO comprises three replicated, heavily instrumented, hillslope-scale model landscapes within the environmentally controlled Biosphere 2 facility. The model landscapes were designed to initially be simple and purely abiotic, enabling scientists to observe each step in the landscapes’ evolution as they undergo physical, chemical, and biological changes over many years. This chapter describes the model systems and associated research facilities and illustrates how LEO allows for tracking of multiscale matter and energy fluxes at a level of detail impossible in field experiments. Initial sensor, sampler, and soil coring data are already providing insights into the tight linkages between water flow, weathering, and microbial community development. These interacting processes are anticipated to drive the model systems to increasingly complex states and will be impacted by the introduction of vascular plants and changes in climatic regimes over the years to come. By intensively monitoring the evolutionary trajectory, integrating data with mathematical models, and fostering community-wide collaborations, we envision that emergent landscape structures and functions can be linked, and significant progress can be made toward predicting the coupled hydro-biogeochemical and ecological responses to global change

Capture of fixation by rotational flow; a deterministic hypothesis regarding scaling and stochasticity in fixational eye movements.

Visual scan paths exhibit complex, stochastic dynamics. Even during visual fixation, the eye is in constant motion. Fixational drift and tremor are thought to reflect fluctuations in the persistent neural activity of neural integrators in the oculomotor brainstem, which integrate sequences of transient saccadic velocity signals into a short term memory of eye position. Despite intensive research and much progress, the precise mechanisms by which oculomotor posture is maintained remain elusive. Drift exhibits a stochastic statistical profile which has been modeled using random walk formalisms. Tremor is widely dismissed as noise. Here we focus on the dynamical profile of fixational tremor, and argue that tremor may be a signal which usefully reflects the workings of oculomotor postural control. We identify signatures reminiscent of a certain flavor of transient neurodynamics; toric traveling waves which rotate around a central phase singularity. Spiral waves play an organizational role in dynamical systems at many scales throughout nature, though their potential functional role in brain activity remains a matter of educated speculation. Spiral waves have a repertoire of functionally interesting dynamical properties, including persistence, which suggest that they could in theory contribute to persistent neural activity in the oculomotor postural control system. Whilst speculative, the singularity hypothesis of oculomotor postural control implies testable predictions, and could provide the beginnings of an integrated dynamical framework for eye movements across scales

Unraveling the Thousand Word Picture: An Introduction to Super-Resolution Data Analysis

Super-resolution microscopy provides direct insight into fundamental biological processes occurring at length scales smaller than light’s diffraction limit. The analysis of data at such scales has brought statistical and machine learning methods into the mainstream. Here we provide a survey of data analysis methods starting from an overview of basic statistical techniques underlying the analysis of super-resolution and, more broadly, imaging data. We subsequently break down the analysis of super-resolution data into four problems: the localization problem, the counting problem, the linking problem, and what we’ve termed the interpretation problem

The model of local axon homeostasis - Explaining the role and regulation of microtubule bundles in axon maintenance and pathology

Axons are the slender, cable-like, up to meter-long projections of neurons that electrically wire our brains and bodies. In spite of their challenging morphology, they usually need to be maintained for an organism's lifetime. This makes them key lesion sites in pathological processes of ageing, injury and neurodegeneration. The morphology and physiology of axons crucially depends on the parallel bundles of microtubules (MTs), running all along to serve as their structural backbones and highways for life-sustaining cargo transport and organelle dynamics. Understanding how these bundles are formed and then maintained will provide important explanations for axon biology and pathology. Currently, much is known about MTs and the proteins that bind and regulate them, but very little about how these factors functionally integrate to regulate axon biology. As an attempt to bridge between molecular mechanisms and their cellular relevance, we explain here the model of local axon homeostasis, based on our own experiments in Drosophila and published data primarily from vertebrates/mammals as well as C. elegans. The model proposes that (1) the physical forces imposed by motor protein-driven transport and dynamics in the confined axonal space, are a life-sustaining necessity, but pose a strong bias for MT bundles to become disorganised. (2) To counterbalance this risk, MT-binding and -regulating proteins of different classes work together to maintain and protect MT bundles as necessary transport highways. Loss of balance between these two fundamental processes can explain the development of axonopathies, in particular those linking to MT-regulating proteins, motors and transport defects. With this perspective in mind, we hope that more researchers incorporate MTs into their work, thus enhancing our chances of deciphering the complex regulatory networks that underpin axon biology and pathology

Optical near-field dynamics of active 2D semiconductors

When structures with a strong confinement of the electromagnetic fields are considered, the near-field dynamics becomes integral to the description of a semiconductor. Not only it provides feedback from the environment, as is the case in a laser system, but it further mediates the interaction between different, otherwise independent, positions. In such a context, a full-field spatio-temporal description is essential to faithfully describe the dynamics of either an extended semiconductor system or a set of spatially separated emitters. This thesis highlights the importance of combining a complex (many-body and band-resolved) model of semiconductor carrier dynamics with a full-field description of the electromagnetic fields by presenting some applications. With the recent rise in popularity of atomically thin materials, semiconductors can be embedded in increasingly smaller optical environments, whose properties can only be studied by self-consistently combining carrier and field dynamics. The ability to calculate the linear and non-linear response of a system under arbitrary excitation conditions is shown. This is performed without any prior knowledge of the electromagnetic environment and can thus be extended to complex geometries. By embedding active materials in a tailored environment, the complex interaction of the two can be exploited to engineer the optical response of the system by using a self-consistent modelling technique. The complex dynamical interaction between field and gain in a semiconductor laser is another example of a system in which a self-consistent model is required. Here, a set of one-dimensional simulations is reported showing how the output of a semiconductor laser is highly sensitive to perturbation arising from sub-wavelength dynamics of the gain medium. By introducing a random patterning of the laser cavity, a novel approach to the suppression of dynamical instabilities in a laser output is demonstrated. This scheme, based on complex wave interference, is introduced by spatially perturbing the optical environment.Open Acces

Single atom imaging with time-resolved electron microscopy

Developments in scanning transmission electron microscopy (STEM) have opened up new possibilities for time-resolved imaging at the atomic scale. However, rapid imaging of single atom dynamics brings with it a new set of challenges, particularly regarding noise and the interaction between the electron beam and the specimen. This thesis develops a set of analytical tools for capturing atomic motion and analyzing the dynamic behaviour of materials at the atomic scale. Machine learning is increasingly playing an important role in the analysis of electron microscopy data. In this light, new unsupervised learning tools are developed here for noise removal under low-dose imaging conditions and for identifying the motion of surface atoms. The scope for real-time processing and analysis is also explored, which is of rising importance as electron microscopy datasets grow in size and complexity. These advances in image processing and analysis are combined with computational modelling to uncover new chemical and physical insights into the motion of atoms adsorbed onto surfaces. Of particular interest are systems for heterogeneous catalysis, where the catalytic activity can depend intimately on the atomic environment. The study of Cu atoms on a graphene oxide support reveals that the atoms undergo anomalous diffusion as a result of spatial and energetic disorder present in the substrate. The investigation is extended to examine the structure and stability of small Cu clusters on graphene oxide, with atomistic modelling used to understand the significant role played by the substrate. Finally, the analytical methods are used to study the surface reconstruction of silicon alongside the electron beam-induced motion of adatoms on the surface. Taken together, these studies demonstrate the materials insights that can be obtained with time-resolved STEM imaging, and highlight the importance of combining state-ofthe- art imaging with computational analysis and atomistic modelling to quantitatively characterize the behaviour of materials with atomic resolution.The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007–2013)/ERC grant agreement 291522–3DIMAGE, as well as from the European Union Seventh Framework Programme under Grant Agreement 312483-ESTEEM2 (Integrated Infrastructure Initiative -I3)

Membrane protein nanoclustering as a functional unit of immune cells : from nanoscopy to single molecule dynamics

State-of-the-art biophysical techniques featuring high temporal and spatial resolution have allowed for the first time the direct visualization of individual transmembrane proteins on the cell membrane. These techniques have revealed that a large amount of molecular components of the cell membrane do not organize in a random manner but they rather grouped together forming so-called clusters at the nanoscale. Moreover, the lateral behavior of these clusters shows a great dependence on the compartmentalization of the cell membrane by, e.g., the actin cytoskeleton at multiple temporal and spatial scales. Since these lateral and temporal organizations have been shown to be crucial for the regulation of the biological activity by these transmembrane proteins, the understanding of the spatiotemporal behavior of membrane receptors, and of proteins in general, is a necessary step towards understanding the biology of the cell. Protein nanoclustering and membrane compartmentalization have been shown to play a crucial role on leukocytes, particularly on the surface of antigen presenting cells. Hence, the direct visualization of membrane proteins on the cell membrane of antigen presenting proteins represents a crucial step in understanding how an immune response can be controlled by leukocytes at the molecular level. In Chapter 1, the immune system, the membrane receptor DC-SIGN and the antigen presenting protein CD1d are briefly introduced. Moreover, recent advances in superresolution microscopy and single particle tracking techniques which allow the study of membrane proteins at the nanoscale are discussed. Finally, an updated review of protein nanoclustering on the cell membrane shows examples of the importance of protein nanoclustering in regulating biological function in the immune system. Chapter 2 presents the quantitative methodology for analyzing STED nanoscopy images and multi-color single particle tracking data used throughout this thesis. Chapter 2 also describes the single-molecule fluorescence sensitive microscopes implemented in this thesis for multi-color single particle tracking experiments and the corresponding data analysis. At the end of Chapter 2, cartography maps combining high temporal with micron-scale spatial information on the basis of single-molecule detection are presented. The following chapters in this thesis describe the major results obtained on two important receptors of the immune system. In Chapter 3, we address the role of the neck region of DC-SIGN in fine-tuning the nanoclustering degree of DC-SIGN on the cell membrane. Moreover, Chapter 3 also links the nanoclustering capability of DC-SIGN with its virus binding capability. The meso-scale organization of DC-SIGN and its dependence on a glycan-based connectivity is addressed on Chapter 4. This glycosylation network enhances the interaction between DC-SIGN and clathrin beyond stochastic random encountering. In Chapter 5, we showed that DC-SIGN shows subdiffusive behavior and weak ergodicity breaking (wEB) that cannot be described using the continuous time random walk (CTRW) model. Instead, our data are more consistent with a model in which the plasma membrane is composed of "patches" that change in space in time. In Chapter 6, we demonstrate that the antigen presenting protein CD1d organizes in nanoclusters on the cell membrane of antigen presenting cells whose size and density are tightly controlled by the actin cytoskeleton. Moreover, we also showed that this cytoskeletal control of the CD1d nanoclustering predominantly occurs on the pool of CD1d that has undergone lysosomal recycling, including under inflammatory conditions. Finally, in Chapter 7 we summarize the main results of this thesis and highlight future experiments that will expand the knowledge obtained so far regarding the role of plasma membrane organization and biological regulation.Gracias a su alta resolución temporal y espacial, las técnicas biofísicas de última generación han permitido la observación directa de proteínas de transmembrana de forma individual en la membrana celular. Estas técnicas han mostrado que la organización de una gran parte de las proteínas de transmembrana no es aleatoria sino que éstas están agrupadas en la membrana celular formando nano-agregados, o "clusters". En el caso concreto del sistema inmune, se ha demostrado que el agrupamiento de proteínas y los compartimentos de la membrana celular juegan un papel determinante en las células presentadoras de antígenos a la hora de controlar la iniciación de una respuesta inmune. Por tanto, la visualización directa de proteínas de membrana en células presentadoras de antígenos a la escala nanométrica representa un paso crucial en el entendimiento del sistema inmune y en un futuro desarrollo de terapias basadas en el sistema inmune humano. En el primer capítulo de esta tesis, se presentará al lector una breve introducción del sistema inmune y una descripción general de las dos proteínas que se han estudiado extensivamente en esta tesis: el receptor reconocedor de patógenos DC-SIGN y la proteína presentadora de antígenos glicolipídicos CD1d. Se discutirán además los últimos avances en técnicas de microscopía de fluorescencia con alta resolución temporal y espacial que permiten el estudio de proteínas a la escala nanométrica. Finalmente, el primer capítulo concluye con una revisión de los últimos avances en la caracterización de la organización lateral de proteínas de membrana mostrando cómo dicha organización determina la función biológica de estas proteínas. En el capítulo 2, se presentan los distintos tipos de metodología utilizados en esta tesis para cuantificar imágenes de microscopía de super-resolución STED así como para analizar datos provenientes del seguimiento de partículas individuales usando varios colores. Al final del capítulo 2 se presenta una nueva metodología desarrollada en esta tesis que permite el estudio lateral de proteínas de membrana con una alta resolución temporal y una escala espacial de orden de micras y a la que hemos denominado mapas cartográficos. Los siguientes capítulos de esta tesis se enfocan en el estudio de dos importantes proteínas involucradas en el sistema inmune. En el capítulo 3 se describe como la parte central de la estructura del receptor captador de patógenos DC-SIGN determina su grado de nano-agrupamiento sobre la membrana celular. A su vez, este agrupamiento tiene una incidencia clave en la capacidad de DC-SIGN en unirse a partículas virales. La organización de DC-SIGN a la escala mesoscópica y la dependencia de dicha organización de una conectividad en la membrana celular basada en la glicosilación de proteínas es descrita en el capítulo 4. En el capítulo 5 descubrimos que DC-SIGN tiene un comportamiento que no solo es sub-difusivo en la membrana celular sino que también conlleva a la ruptura de ergodicidad por parte de este receptor. Esta rotura de ergodicidad no puede ser descrita por el modelo "continous time random walk" (CTRW) sino por un modelo nuevo donde la difusión de la partícula cambia constantemente en el espacio y en el tiempo. En el capítulo 6 de esta tesis describimos como la molécula CD1d forma nano-agrupamientos en la membrana celular cuyo tamaño y densidad son controlados por el citoesqueleto de actina. Además, observamos que dicho control mayoritariamente sucede cuando CD1d ha sido reciclado a través de compartimentos lisosomales, incluyendo procesos inflamatorios. Finalmente, en el capítulo 7 se discuten las conclusiones generales de esta tesis y se sugieren experimentos a futuro de manera de incrementar, en base a los resultados obtenidos en esta tesis, nuestro conocimiento de la membrana celular y el papel que la organización espacial y temporal juega en el control del sistema inmune