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At least 343 records · Page 19

Biocene 2018 - Welcome to the Period of New Life

Biocene is the period of new life. When our descendants look back at this period in time, they will see evidence, in the geologic and electronic record, of anthropic climate change, growing population, and scarcity of resources. But they will also see the rebirth of human ingenuity as we overcame the challenges that faced us through nature-inspired exploration. The Periodic Table of Life (PeTaL) is a proposed tool and open source framework that uses artificial intelligence to aid in the systematic inquiry of biology for its application to human systems. This presentation defines the PeTaL concept and workflow. Biomimicry, biophysics, biomimetics, bionics and numerous other terms refer to the use of biology and biological principles to inform practices in other disciplines. For the most part, the domain of inquiry in these fields have been confined to extant biological models with the proponents of biomimicry often citing the evolutionary success of extant organisms relative to extinct ones. The primary objective of this paper is to expand the domain of inquiry for human processes that seek to model those that are, were or could be found in nature with examples that relate to the field of aerospace and to spur development of tools that can work together to accelerate the use of artificial intelligence in problem solving. Specifically specialized fields such as paleomimesis, anthropomimesis and physioteleology are proposed in conjunction with artificial evolution. Blockchain technology may be vital in allowing open source design tools such as PeTaL to democratize design and yet protect intellectual property. The overarching philosophy outlined here can be thought of as physiomimetics, a holistic and systematic way of learning from natural history. The backbone of PeTaL integrates an unstructured database with an ontological model consisting of function, morphology, environment, state of matter and ecosystem. Tools include text classification, thesaurus, data visualization, and analysis. Applications of PeTaL include guiding human space exploration, understanding human and geological history, and discovering new or extinct life.

Biocene↗

Shorebird Migration Patterns in Response to Climate Change: A Modeling Approach

The availability of satellite remote sensing observations at multiple spatial and temporal scales, coupled with advances in climate modeling and information technologies offer new opportunities for the application of mechanistic models to predict how continental scale bird migration patterns may change in response to environmental change. In earlier studies, we explored the phenotypic plasticity of a migratory population of Pectoral sandpipers by simulating the movement patterns of an ensemble of 10,000 individual birds in response to changes in stopover locations as an indicator of the impacts of wetland loss and inter-annual variability on the fitness of migratory shorebirds. We used an individual based, biophysical migration model, driven by remotely sensed land surface data, climate data, and biological field data. Mean stop-over durations and stop-over frequency with latitude predicted from our model for nominal cases were consistent with results reported in the literature and available field data. In this study, we take advantage of new computing capabilities enabled by recent GP-GPU computing paradigms and commodity hardware (general purchase computing on graphics processing units). Several aspects of our individual based (agent modeling) approach lend themselves well to GP-GPU computing. We have been able to allocate compute-intensive tasks to the graphics processing units, and now simulate ensembles of 400,000 birds at varying spatial resolutions along the central North American flyway. We are incorporating additional, species specific, mechanistic processes to better reflect the processes underlying bird phenotypic plasticity responses to different climate change scenarios in the central U.S.

Smith, James A.↗

VEGETATION COVER ANALYSIS OF HAZARDOUS WASTE SITES IN UTAH AND ARIZONA USING HYPERSPECTRAL REMOTE SENSING

Remote sensing technology can provide a cost-effective tool for monitoring hazardous waste sites. This study investigated the usability of HyMap airborne hyperspectral remote sensing data (126 bands at 2.3 x 2.3 m spatial resolution) to characterize the vegetation at U.S. Department of Energy uranium processing sites near Monticello, Utah and Monument Valley, Arizona. Grass and shrub species were mixed on an engineered disposal cell cover at the Monticello site while shrub species were dominant in the phytoremediation plantings at the Monument Valley site. The specific objectives of this study were to: (1) estimate leaf-area-index (LAI) of the vegetation using three different methods (i.e., vegetation indices, red-edge positioning (REP), and machine learning regression trees), and (2) map the vegetation cover using machine learning decision trees based on either the scaled reflectance data or mixture tuned matched filtering (MTMF)-derived metrics and vegetation indices. Regression trees resulted in the best calibration performance of LAI estimation (R{sup 2} > 0.80). The use of REPs failed to accurately predict LAI (R{sup 2} < 0.2). The use of the MTMF-derived metrics (matched filter scores and infeasibility) and a range of vegetation indices in decision trees improved the vegetation mapping when compared to the decision tree classification using just the scaled reflectance. Results suggest that hyperspectral imagery are useful for characterizing biophysical characteristics (LAI) and vegetation cover on capped hazardous waste sites. However, it is believed that the vegetation mapping would benefit from the use of 1 higher spatial resolution hyperspectral data due to the small size of many of the vegetation patches (< 1m) found on the sites.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Architecture of the chromatin remodeler RSC and insights into its nucleosome engagement

Eukaryotic DNA is packaged into nucleosome arrays, which are repositioned by chromatin remodeling complexes to control DNA accessibility. The Saccharomyces cerevisiae RSC (Remodeling the Structure of Chromatin) complex, a member of the SWI/SNF chromatin remodeler family, plays critical roles in genome maintenance, transcription, and DNA repair. Here, we report cryo-electron microscopy (cryo-EM) and crosslinking mass spectrometry (CLMS) studies of yeast RSC complex and show that RSC is composed of a rigid tripartite core and two flexible lobes. The core structure is scaffolded by an asymmetric Rsc8 dimer and built with the evolutionarily conserved subunits Sfh1, Rsc6, Rsc9 and Sth1. The flexible ATPase lobe, composed of helicase subunit Sth1, Arp7, Arp9 and Rtt102, is anchored to this core by the N-terminus of Sth1. Our cryo-EM analysis of RSC bound to a nucleosome core particle shows that in addition to the expected nucleosome-Sth1 interactions, RSC engages histones and nucleosomal DNA through one arm of the core structure, composed of the Rsc8 SWIRM domains, Sfh1 and Npl6. Our findings provide structural insights into the conserved assembly process for all members of the SWI/SNF family of remodelers, and illustrate how RSC selects, engages, and remodels nucleosomes.

59 BASIC BIOLOGICAL SCIENCES↗

Membrane insertion for the detection of lipopolysaccharides: Exploring the dynamics of amphiphile-in-lipid assays

Shiga toxin-producing Escherichia coli is an important cause of foodborne illness, with cases attributable to beef, fresh produce and other sources. Many serotypes of the pathogen cause disease, and differentiating one serotype from another requires specific identification of the O antigen located on the lipopolysaccharide (LPS) molecule. The amphiphilic structure of LPS poses a challenge when using classical detection methods, which do not take into account its lipoglycan biochemistry. Typically, detection of LPS requires heat or chemical treatment of samples and relies on bioactivity assays for the conserved lipid A portion of the molecule. Our goal was to develop assays to facilitate the direct and discriminative detection of the entire LPS molecule and its O antigen in complex matrices using minimal sample processing. To perform serogroup identification of LPS, we used a method called membrane insertion on a waveguide biosensor, and tested three serogroups of LPS. The membrane insertion technique allows for the hydrophobic association of LPS with a lipid bilayer, where the exposed O antigen can be targeted for specific detection. Samples of beef lysate were spiked with LPS to perform O antigen specific detection of LPS from E. coli O157. To validate assay performance, we evaluated the biophysical interactions of LPS with lipid bilayers both in- and outside of a flow cell using fluorescence microscopy and fluorescently doped lipids. Our results indicate that membrane insertion allows for the qualitative and reliable identification of amphiphilic LPS in complex samples like beef homogenates. In addition, we also demonstrated that LPS-induced hole formation does not occur under the conditions of the membrane insertion assays. Together, these findings describe for the first time the serogroup-specific detection of amphiphilic LPS in complex samples using a membrane insertion assay, and highlight the importance of LPS molecular conformations in detection architectures.

59 BASIC BIOLOGICAL SCIENCES↗

Crystal structures reveal catalytic and regulatory mechanisms of the dual-specificity ubiquitin/FAT10 E1 enzyme Uba6

The E1 enzyme Uba6 initiates signal transduction by activating ubiquitin and the ubiquitin-like protein FAT10 in a two-step process involving sequential catalysis of adenylation and thioester bond formation. To gain mechanistic insights into these processes, we determined the crystal structure of a human Uba6/ubiquitin complex. Two distinct architectures of the complex are observed: one in which Uba6 adopts an open conformation with the active site configured for catalysis of adenylation, and a second drastically different closed conformation in which the adenylation active site is disassembled and reconfigured for catalysis of thioester bond formation. Surprisingly, an inositol hexakisphosphate (InsP6) molecule binds to a previously unidentified allosteric site on Uba6. Our structural, biochemical, and biophysical data indicate that InsP6 allosterically inhibits Uba6 activity by altering interconversion of the open and closed conformations of Uba6 while also enhancing its stability. In addition to revealing the molecular mechanisms of catalysis by Uba6 and allosteric regulation of its activities, our structures provide a framework for developing Uba6-specific inhibitors and raise the possibility of allosteric regulation of other E1s by naturally occurring cellular metabolites.

59 BASIC BIOLOGICAL SCIENCES↗

The Urban Fabric of the City as Its Affects Thermal Energy Responses Derived from Remote Sensing Data

The physical geography of the city affects numerous aspects of its interlinked biophysical, social, and land-atmosphere characteristics - those attributes that come together to form the total urban environment. One approach to studying the multitude of interactions that occur as a result of urbanization is to view the city from a systems ecology perspective, where energy and material cycle into and out of the urban milieu. Thus, the urban ecosystem is synergistic in linking land, air, water, and living organisms in a vast network of interrelated physical, human, and biological process. Given the number and the shear complexity of the exchanges and, ultimately, their effects, that occur within the urban environment, we are focusing our research on looking at how the morphology or urban fabric of the city, drives thermal energy exchanges across the urban landscape. The study of thermal energy attributes for different cities provides insight into how thermal fluxes and characteristics are partitioned across the city landscape in response to each city's morphology. We are using thermal infrared remote sensing data obtained at a high spatial resolution from aircraft, along with satellite data, to identify and quantify thermal energy characteristics for 4 U.S. cities: Atlanta, GA, Baton Rouge, LA, Salt Lake City, UT, and Sacramento, CA. Analysis of how thermal energy is spatially distributed across the urban landscapes for these cities provides a unique perspective for understanding how the differing morphology of cities forces land-atmosphere exchanges, such as the urban heat island effect, as well as related meteorological and air quality interactions. Keyword: urban ecosystems, remote sensing, urban heat island

Quattrochi, Dale A.↗

Overview of the Graphical User Interface for the GERMcode (GCR Event-Based Risk Model)

The descriptions of biophysical events from heavy ions are of interest in radiobiology, cancer therapy, and space exploration. The biophysical description of the passage of heavy ions in tissue and shielding materials is best described by a stochastic approach that includes both ion track structure and nuclear interactions. A new computer model called the GCR Event-based Risk Model (GERM) code was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL). The GERMcode calculates basic physical and biophysical quantities of high-energy protons and heavy ions that have been studied at NSRL for the purpose of simulating space radiobiological effects. For mono-energetic beams, the code evaluates the linear-energy transfer (LET), range (R), and absorption in tissue equivalent material for a given Charge (Z), Mass Number (A) and kinetic energy (E) of an ion. In addition, a set of biophysical properties are evaluated such as the Poisson distribution of ion or delta-ray hits for a specified cellular area, cell survival curves, and mutation and tumor probabilities. The GERMcode also calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle. The contributions from primary ion and nuclear secondaries are evaluated. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections, and has been used by the GERMcode for application to thick target experiments. The GERMcode provides scientists participating in NSRL experiments with the data needed for the interpretation of their experiments, including the ability to model the beam line, the shielding of samples and sample holders, and the estimates of basic physical and biological outputs of the designed experiments. We present an overview of the GERMcode GUI, as well as providing training applications.

Kim, Myung-Hee Y.↗

Structural and Biochemical Characterization of Human PR70 in Isolation and in Complex with the Scaffolding Subunit of Protein Phosphatase 2A

Protein Phosphatase 2A (PP2A) is a major Ser/Thr phosphatase involved in the regulation of various cellular processes. PP2A assembles into diverse trimeric holoenzymes, which consist of a scaffolding (A) subunit, a catalytic (C) subunit and various regulatory (B) subunits. Here we report a 2.0 A crystal structure of the free B’’/PR70 subunit and a SAXS model of an A/PR70 complex. The crystal structure of B’’/PR70 reveals a two domain elongated structure with two Ca 2+ binding EF-hands. Furthermore, we have characterized the interaction of both binding partner and their calcium dependency using biophysical techniques. Ca 2+ biophysical studies with Circular Dichroism showed that the two EF-hands display different affinities to Ca2+. In the absence of the catalytic C-subunit, the scaffolding A-subunit remains highly mobile and flexible even in the presence of the B’’/PR70 subunit as judged by SAXS. Isothermal Titration Calorimetry studies and SAXS data support that PR70 and the A-subunit have high affinity to each other. This study provides additional knowledge about the structural basis for the function of B’’ containing holoenzymes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Real-time intermembrane force measurements and imaging of lipid domain morphology during hemifusion

Membrane fusion is the core process in membrane trafficking and is essential for cellular transport of proteins and other biomacromolecules. During protein-mediated membrane fusion, membrane proteins are often excluded from the membrane–membrane contact, indicating that local structural transformations in lipid domains play a major role. However, the rearrangements of lipid domains during fusion have not been thoroughly examined. Here using a newly developed Fluorescence Surface Forces Apparatus (FL-SFA), migration of liquid-disordered clusters and depletion of liquid-ordered domains at the membrane–membrane contact are imaged in real time during hemifusion of model lipid membranes, together with simultaneous force–distance and lipid membrane thickness measurements. The load and contact time-dependent hemifusion results show that the domain rearrangements decrease the energy barrier to fusion, illustrating the significance of dynamic domain transformations in membrane fusion processes. Importantly, the FL-SFA can unambiguously correlate interaction forces and in situ imaging in many dynamic interfacial systems.

36 MATERIALS SCIENCE↗

Overview of the Graphical User Interface for the GERM Code (GCR Event-Based Risk Model

The descriptions of biophysical events from heavy ions are of interest in radiobiology, cancer therapy, and space exploration. The biophysical description of the passage of heavy ions in tissue and shielding materials is best described by a stochastic approach that includes both ion track structure and nuclear interactions. A new computer model called the GCR Event-based Risk Model (GERM) code was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL). The GERM code calculates basic physical and biophysical quantities of high-energy protons and heavy ions that have been studied at NSRL for the purpose of simulating space radiobiological effects. For mono-energetic beams, the code evaluates the linear-energy transfer (LET), range (R), and absorption in tissue equivalent material for a given Charge (Z), Mass Number (A) and kinetic energy (E) of an ion. In addition, a set of biophysical properties are evaluated such as the Poisson distribution of ion or delta-ray hits for a specified cellular area, cell survival curves, and mutation and tumor probabilities. The GERM code also calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle. The contributions from primary ion and nuclear secondaries are evaluated. The GERM code accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections, and has been used by the GERM code for application to thick target experiments. The GERM code provides scientists participating in NSRL experiments with the data needed for the interpretation of their experiments, including the ability to model the beam line, the shielding of samples and sample holders, and the estimates of basic physical and biological outputs of the designed experiments. We present an overview of the GERM code GUI, as well as providing training applications.

Kim, Myung-Hee↗

Automated AI-driven Molecular Design for Therapeutic Discovery

In recent years, artificial intelligence and machine learning (AI/ML) approaches have revolutionized the process of designing new therapeutics, enabling scientists to rapidly respond to emerging threats from various pathogens. A prime example is the SARS-CoV-2 main protease, a key target for the development of antiviral inhibitors. In this study, we employed a novel, integrated approach that combines AI-driven iterative design of inhibitor candidates, screening based on physio-chemical properties and toxicity, physics-based computational modeling of protein-inhibitor interactions, and AI-assisted analysis of Native MS biophysical assay and characterization of designed candidates. Our deep learning 3D-scaffold model, which uses an input scaffold as a starting point, generated tens of thousands of compounds while preserving the key scaffold. To optimize these candidates, we calculated a comprehensive set of 136 descriptors, including both 2D and 3D molecular features, for compounds targeting the SARS-CoV-2 Main protease (Mpro) and a neurodegenerative disease-associated protein, cyclophilin (Cyp). The generated compounds were initially filtered based on their properties and then ranked according to their predicted binding affinity using our automated modeling and ML methods. Experimental validation of the Mpro candidates showing inhibitory activity demonstrates that our workflow can expedite the therapeutic discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On The Development of Biophysical Models for Space Radiation Risk Assessment

Experimental techniques in molecular biology are being applied to study biological risks from space radiation. The use of molecular assays presents a challenge to biophysical models which in the past have relied on descriptions of energy deposition and phenomenological treatments of repair. We describe a biochemical kinetics model of cell cycle control and DNA damage response proteins in order to model cellular responses to radiation exposures. Using models of cyclin-cdk, pRB, E2F's, p53, and GI inhibitors we show that simulations of cell cycle populations and GI arrest can be described by our biochemical approach. We consider radiation damaged DNA as a substrate for signal transduction processes and consider a dose and dose-rate reduction effectiveness factor (DDREF) for protein expression.

Cucinotta, F. A.↗

Flavin-Induced Oligomerization in Escherichia coli Adaptive Response Protein AidB

The process known as 'adaptive response' allows Escherichia coli to respond to small doses of DNA-methylating agents by upregulating the expression of four proteins. While the role of three of these proteins in mitigating DNA damage is well understood, the function of AidB is less clear. Although AidB is a flavoprotein, no catalytic role has been established for the bound cofactor. Here we investigate the possibility that flavin plays a structural role in the assembly of the AidB tetramer. We report the generation and biophysical characterization of deflavinated AidB and of an AidB mutant that has greatly reduced affinity for flavin adenine dinucleotide (FAD). Using fluorescence quenching and analytical ultracentrifugation, we find that apo AidB has a high affinity for FAD, as indicated by an apparent dissociation constant of 402.1 {+-} 35.1 nM, and that binding of substoichiometric amounts of FAD triggers a transition in the AidB oligomeric state. In particular, deflavinated AidB is dimeric, whereas the addition of FAD yields a tetramer. We further investigate the dimerization and tetramerization interfaces of AidB by determining a 2.8 {angstrom} resolution crystal structure in space group P3{sub 2} that contains three intact tetramers in the asymmetric unit. Taken together, our findings provide strong evidence that FAD plays a structural role in the formation of tetrameric AidB.

59 BASIC BIOLOGICAL SCIENCES↗

Stream Classification Tool User Manual: For Use in Applications in Hydropower-Related Evironmental Mitigation

Stream classifications are an inventory of different types of streams. Classifications help us explore similarities and differences among different types of streams, make inferences regarding stream ecosystem behavior, and communicate the complexities of ecosystems. We developed a nested, layered, and spatially contiguous stream classification to characterize the biophysical settings of stream reaches within the Eastern United States (~ 900,000 reaches). The classification is composed of five natural characteristics (hydrology, temperature, size, confinement, and substrate) along with several disturbance regime layers, and each was selected because of their relevance to hydropower mitigation. We developed the classification at the stream reach level using the National Hydrography Dataset Plus Version 1 (1:100k scale). The stream classification is useful to environmental mitigation for hydropower dams in multiple ways. First, it creates efficiency in the regulatory process by creating an objective and data-rich means to address meaningful mitigation actions. Secondly, the SCT addresses data gaps as it quickly provides an inventory of hydrology, temperature, morphology, and ecological communities for the immediate project area, but also surrounding streams. This includes identifying potential reference streams as those that are proximate to the hydropower facility and fall within the same class. These streams can potentially be used to identify ideal environmental conditions or identify desired ecological communities. In doing so, the stream provides some context for how streams may function, respond to dam regulation, and an overview of specific mitigation needs. Herein, we describe the methodology in developing each stream classification layer and provide a tutorial to guide applications of the classification (and associated data) in regulatory settings, such as hydropower (re)licensing.

13 HYDRO ENERGY↗

The Electron-Conformational Model of Ryanodine Receptors of the Heart Cell

The main ideas of an electron-conformational (EC) model of ligand-activated ryanodine channels (RyR) that reduces many degrees of freedom of this gigantic nanoscopic molecular complex to two so-called electron and conformational degrees of freedom are presented. In the toy model, the conformational potential or energy profile of the RyR channel represents two branches that describe the dependence of energy on the conformational coordinate (reaction coordinate) in the initial and ligand-activated states, respectively. A model extension that takes into account both the tetrameric structure of the RyR channel and additional (orthogonal) rotational conformational mode has been considered. The EC model has been demonstrated to give a biophysical basis to the traditional phenomenological model of Markov chains. To demonstrate the possibilities of the EC model, we refer to examples of model description of the dynamics of isolated RyR channels and clusters of RyR channels in release units of the heart cell.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Secondary PDZ domain-binding site on class B plexins enhances the affinity for PDZ–RhoGEF

PDZ domains are abundant protein interaction modules and typically recognize a short motif at the C terminus of their ligands, with a few residues in the motif endowing the binding specificity. The sequence-based rules, however, cannot fully account for the specificity between the vast number of PDZ domains and ligands in the cell. Plexins are transmembrane receptors that regulate processes such as axon guidance and angiogenesis. Two related guanine nucleotide exchange factors (GEFs), PDZ–RhoGEF and leukemia-associated RhoGEF (LARG), use their PDZ domains to bind class B plexins and play critical roles in signaling. Here, we present the crystal structure of the full-length cytoplasmic region of PlexinB2 in complex with the PDZ domain of PDZ–RhoGEF. The structure reveals that, in addition to the canonical C-terminal motif/PDZ interaction, the 3D domain of PlexinB2 forms a secondary interface with the PDZ domain. Our biophysical and cell-based assays show that the secondary interface contributes to the specific interaction between plexin and PDZ–RhoGEF and to signaling by plexin in the cell. As a result, formation of secondary interfaces may be a general mechanism for increasing affinity and specificity of modular domain-mediated interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Ferrous iron formation following the co-aggregation of ferric iron and the Alzheimer's disease peptide β-amyloid (1–42)

For decades, a link between increased levels of iron and areas of Alzheimer’s disease (AD) pathology has been recognized, including AD lesions comprised of the peptide b-amyloid (Ab). Despite many observations of this association, the relationship between Ab and iron is poorly understood. Using X-ray microspectroscopy, X-ray absorption spectroscopy, electron microscopy and spectrophotometric iron(II) quantification techniques, we examine the interaction between Ab(1–42) and synthetic iron(III), reminiscent of ferric iron stores in the brain. We report Ab to be capable of accumulating iron(III) within amyloid aggregates, with this process resulting in Ab-mediated reduction of iron(III) to a redox-active iron(II) phase. Additionally, we show that the presence of aluminium increases the reductive capacity of Ab, enabling the redox cycling of the iron. These results demonstrate the ability of Ab to accumulate iron, offering an explanation for previously observed local increases in iron concentration associated with AD lesions. Furthermore, the ability of iron to form redox-active iron phases from ferric precursors provides an origin both for the redox-active iron previously witnessed in AD tissue, and the increased levels of oxidative stress characteristic of AD. These interactions between Ab and iron deliver valuable insights into the process of AD progression, which may ultimately provide targets for disease therapies.

redox↗