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Williams, Timothy J.

Publications and source records attributed to Williams, Timothy J..

14 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Remarkably coherent population structure for a dominant Antarctic Chlorobium species

Background: In Antarctica, summer sunlight enables phototrophic microorganisms to drive primary production, thereby “feeding” ecosystems to enable their persistence through the long, dark winter months. In Ace Lake, a stratified marine-derived system in the Vestfold Hills of East Antarctica, a Chlorobium species of green sulphur bacteria (GSB) is the dominant phototroph, although its seasonal abundance changes more than 100-fold. Here, we analysed 413 Gb of Antarctic metagenome data including 59 Chlorobium metagenome-assembled genomes (MAGs) from Ace Lake and nearby stratified marine basins to determine how genome variation and population structure across a 7-year period impacted ecosystem function. Results: A single species, Candidatus Chlorobium antarcticum (most similar to Chlorobium phaeovibrioides DSM265) prevails in all three aquatic systems and harbours very little genomic variation (≥ 99% average nucleotide identity). A notable feature of variation that did exist related to the genomic capacity to biosynthesize cobalamin. The abundance of phylotypes with this capacity changed seasonally ~ 2-fold, consistent with the population balancing the value of a bolstered photosynthetic capacity in summer against an energetic cost in winter. The very high GSB concentration (> 10 8 cells ml –1 in Ace Lake) and seasonal cycle of cell lysis likely make Ca. Chlorobium antarcticum a major provider of cobalamin to the food web. Analysis of Ca. Chlorobium antarcticum viruses revealed the species to be infected by generalist (rather than specialist) viruses with a broad host range (e.g., infecting Gammaproteobacteria) that were present in diverse Antarctic lakes. The marked seasonal decrease in Ca. Chlorobium antarcticum abundance may restrict specialist viruses from establishing effective lifecycles, whereas generalist viruses may augment their proliferation using other hosts. Conclusion: The factors shaping Antarctic microbial communities are gradually being defined. In addition to the cold, the annual variation in sunlight hours dictates which phototrophic species can grow and the extent to which they contribute to ecosystem processes. The Chlorobium population studied was inferred to provide cobalamin, in addition to carbon, nitrogen, hydrogen, and sulphur cycling, as critical ecosystem services. The specific Antarctic environmental factors and major ecosystem benefits afforded by this GSB likely explain why such a coherent population structure has developed in this Chlorobium species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Genome Analysis of a Verrucomicrobial Endosymbiont With a Tiny Genome Discovered in an Antarctic Lake

Organic Lake in Antarctica is a marine-derived, cold (–13°C), stratified (oxic-anoxic), hypersaline (>200 gl –1 ) system with unusual chemistry (very high levels of dimethylsulfide) that supports the growth of phylogenetically and metabolically diverse microorganisms. Symbionts are not well characterized in Antarctica. However, unicellular eukaryotes are often present in Antarctic lakes and theoretically could harbor endosymbionts. Here, we describe Candidatus Organicella extenuata, a member of the Verrucomicrobia with a highly reduced genome, recovered as a metagenome-assembled genome with genetic code 4 (UGA-to-Trp recoding) from Organic Lake. It is closely related to Candidatus Pinguicocccus supinus (163,218 bp, 205 genes), a newly described cytoplasmic endosymbiont of the freshwater ciliate Euplotes vanleeuwenhoeki (Serra et al., 2020). At 158,228 bp (encoding 194 genes), the genome of Ca. Organicella extenuata is among the smallest known bacterial genomes and similar to the genome of Ca. Pinguicoccus supinus (163,218 bp, 205 genes). Ca. Organicella extenuata retains a capacity for replication, transcription, translation, and protein-folding while lacking any capacity for the biosynthesis of amino acids or vitamins. Notably, the endosymbiont retains a capacity for fatty acid synthesis (type II) and iron–sulfur (Fe-S) cluster assembly. Metagenomic analysis of 150 new metagenomes from Organic Lake and more than 70 other Antarctic aquatic locations revealed a strong correlation in abundance between Ca. Organicella extenuata and a novel ciliate of the genus Euplotes. Like Ca. Pinguicoccus supinus, we infer that Ca. Organicella extenuata is an endosymbiont of Euplotes and hypothesize that both Ca. Organicella extenuata and Ca. Pinguicocccus supinus provide fatty acids and Fe-S clusters to their Euplotes host as the foundation of a mutualistic symbiosis. The discovery of Ca. Organicella extenuata as possessing genetic code 4 illustrates that in addition to identifying endosymbionts by sequencing known symbiotic communities and searching metagenome data using reference endosymbiont genomes, the potential exists to identify novel endosymbionts by searching for unusual coding parameters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Enabling real-time multi-messenger astrophysics discoveries with deep learning

Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that probe the Universe using different cosmic messengers: electromagnetic waves, cosmic rays, gravitational waves and neutrinos. In this Expert Recommendation, we review the key challenges of real-time observations of gravitational wave sources and their electromagnetic and astroparticle counterparts, and make a number of recommendations to maximize their potential for scientific discovery. These recommendations refer to the design of scalable and computationally efficient machine learning algorithms; the cyber-infrastructure to numerically simulate astrophysical sources, and to process and interpret multi-messenger astrophysics data; the management of gravitational wave detections to trigger real-time alerts for electromagnetic and astroparticle follow-ups; a vision to harness future developments of machine learning and cyber-infrastructure resources to cope with the big-data requirements; and finally, the need to build a community of experts to realize the goals of multi-messenger astrophysics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Unexpected host dependency of Antarctic Nanohaloarchaeota

In hypersaline environments, Nanohaloarchaeota (Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, Nanohaloarchaeota [DPANN] superphylum) are thought to be free-living microorganisms. We report cultivation of 2 strains of Antarctic Nanohaloarchaeota and show that they require the haloarchaeon Halorubrum lacusprofundi for growth. By performing growth using enrichments and fluorescence-activated cell sorting, we demonstrated successful cultivation of Candidatus Nanohaloarchaeum antarcticus, purification of Ca. Nha. antarcticus away from other species, and growth and verification of Ca. Nha. antarcticus with Hrr. lacusprofundi ; these findings are analogous to those required for fulfilling Koch’s postulates. We use fluorescent in situ hybridization and transmission electron microscopy to assess cell structures and interactions; metagenomics to characterize enrichment taxa, generate metagenome assembled genomes, and interrogate Antarctic communities; and proteomics to assess metabolic pathways and speculate about the roles of certain proteins. Metagenome analysis indicates the presence of a single species, which is endemic to Antarctic hypersaline systems that support the growth of haloarchaea. The presence of unusually large proteins predicted to function in attachment and invasion of hosts plus the absence of key biosynthetic pathways (e.g., lipids) in metagenome assembled genomes of globally distributed Nanohaloarchaeota indicate that all members of the lineage have evolved as symbionts. Our work expands the range of archaeal symbiotic lifestyles and provides a genetically tractable model system for advancing understanding of the factors controlling microbial symbiotic relationships.

Science & Technology - Other Topics↗
DOE OSTI2018

Early Science on Theta

At the Argonne Leadership Computing Facility, the process for standing up a new system is paired with The Early Science Program. This competitive program prepares a select group of applications science teams to use the new machine very readily by providing them staff support and early access to preproduction system hardware and software. As a result, this column describes three Theta Early Science projects: two science applications and one code development effort.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Large-Scale Simulation of Brain Tissue, Blue Brain Project, EPFL

The initial version of this project described in the awarded proposal aimed at largely focusing on the evaluation of Intel KNL hardware and the development of new scientific use cases such as then eurorobotics and whole brain modeling. However, during the course of the project EPFL has been awarded a high impact INCITE project focused on the development of models to support brain plasticity which is considered as the key toward understanding memory. Considering this very prestigious opportunity a large part of our developments has been refocused on the development of methods to support the plasticity use case which is described in Annex 1 along with the awarded INCITE proposal.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Extreme Scale Unstructured Adaptive CFD: From Multiphase Flow to Aerodynamic Flow Control

Understanding the flow of fluid, either liquid or gas, through and around solid bodies has challenged man since the dawn of scientific inquiry. Many of the great minds of science and math have progressively built up a hierarchy of fluid models. This report is concerned with the computational modeling of turbulent flow around aerodynamic bodies such as planes and wind turbines. In this case, viscous effects near the solid bodies create very thin boundary layers that yield highly anisotropic (gradients normal to the surface may be 10^6 times larger than gradients along the surface) solutions to the governing non-linear partial differential equations (PDE); the Navier-Stokes equations. Furthermore, turbulent flows develop extremely broad ranges of length and time scales.This disparity motivates the use of discretization methods capable of employing adaptivity and implicit time integration. The combination of these features (non-linear, anisotropy, adaptivity, andimplicit) dramatically raise the complexity of the discretization, posing large challenges to efficient scalable parallel implementation. However, through careful design, the more complex algorithms can provide great reductions in computational cost relative to simpler methods (e.g., Cartesian grids with explicit time integration) that are easier to mate efficiently to hardware. In this report, we not only describe our approach but we also address the fact that while complex algorithms may never be as efficient flop-for-flop as simple methods, in the important measure of science-per-core-hour, they can still win big by making complex features like adaptivity and implicit methods as efficient and scalable as possible.

42 ENGINEERING↗
DOE OSTI2017

Free Energy Landscapes of Membrane Transport Proteins

Molecular dynamics (MD) is now a widespread tool for investigating biochemical and biomolecular systems, its prevalence, in no small part, being due to significant advances in computational hardware over the last few decades. Even non-experts can now routinely use MD for protein and nucleic acid structure refinement, studying conformational switching events, and investigating solvation effects due to ligand/drug binding. Nonetheless, the vast majority of simulations being done today utilize only rudimentary algorithmic approaches – so-called “brute force” MD – which only permit access to a small fraction of what the approach has to offer. This is largely because the core algorithm is simple, while advanced techniques can require everything from more sophisticated models and data structures to complicated on-the-fly analysis. A core goal of this early science project is to bring one such advanced MD approach into the broader arena of high-performance computing.In particular, the powerful method of constant-pH MD has long been a relegated to experienced users and specialized model systems. In this work we develop and implement a constant-pH MD algorithm in the NAMD simulation engine making it suitable for deployment on large-scale, next-generation supercomputers as well as ambitious, cutting-edge biological applications. We report,for the first time, constant-pH simulations of a membrane transport protein and use the results to analyze its free energy landscape for ion-selectivity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Quantum Monte Carlo Calculations in Nuclear Theory

To a remarkable extent, atomic nuclei can be described as collections of point-like particles whose dynamics are dictated by a nonrelativistic Hamiltonian involving two- and three-nucleon potentials.Ab initio approaches are aimed at solving the many-body Schr$ \overline{o} $dinger equation associated with the nuclear Hamiltonian, which is a highly non-trivial problem because of the nonperturbative nature and the strong spin-isospin dependence of the nuclear forces. Within this framework it is possible to disentangle the theoretical uncertainty coming from modeling the nuclear potential and currents from that due to the approximations that are usually inherent in many-body techniques.Our many-body method of choice is quantum Monte Carlo (QMC), in particular Green’s function Monte Carlo (GFMC), which allows solving the nuclear Schrodinger equation with the required 1%accuracy level for both the ground- and the low-lying excited states of A ≤ 12 (A is the number of nucleons) nuclei. Since 2000 we have been achieving excellent agreement with experiment for nuclei with increasing number of nucleons by using the Argonne V18 two-nucleon interaction and the Illinois three-nucleon interactions (AV18+IL7). During this period many other groups have been developing chiral effective field theory (χEFT) potentials; these are generally nonlocal and notsuitable for QMC methods. We and collaborators have recently developed a local χEFT potential including the Δ-isobar degrees of freedom which can be used with QMC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Electronic Structure-Based Discovery of Hybrid Photovoltaic Materials on Next-Generation HPC Platforms

Organic and hybrid organic-inorganic materials other significant opportunities for applications in photovoltaics (PV) and other semiconductor applications. The versatility of organic synthesis affords broad flexibility in terms of fine-tuning the properties of the molecular components. For purely organic materials, the interfaces to inorganic electrodes are a key component that determines the efficiency of eventual devices. In organic-inorganic hybrid materials, atomic-scale inorganic components are integrated with the organic functionality to form tightly integrated, crystalline semiconductor materials with potentially entirely new electronic and carrier transport characteristics. In either organic-inorganic interfaces or hybrid materials, the key properties are governed by the details of the atomic structure, which is virtually impossible to foresee based on empirical criteria. Predictive simulations of the structure and electronic properties of such materials or interfaces would thus greatly enhance our ability to identify the most promising organic-inorganic combinations faster, reducing the need for time consuming experimental synthesis attempts while navigating a complex materials space.

14 SOLAR ENERGY↗
DOE OSTI2017

First-Principles Simulations of Functional Materials for Energy Conversion

Computational modeling has become a very effective approach in predicting properties of materials, and in designing functional materials with targeted structural, thermal, or optical properties. Many electronic structure methods have been developed, including density functional theory. Among them, DFT has been widely used in physics and materials science because it is computationally cheaper than other methods but still gives desired accuracy. It also provides a good starting point for higher levels of theory, such as many-body perturbation theory and quantum Monte Carlo. In parallel to these electronic structure method developments, a dramatic increase in computing capabilities over the last decade has enabled large-scale electronic structure calculations to address leading-edge materials science problems. In particular, with Theta at the Argonne Leadership Computing Facility (ALCF), our early science project investigated large-scale nanostructured materials for energy conversion and storage using two open-source electronic structure codes Qbox (http://qboxcode.org) and WEST (http://west-code.org). Qbox is an ab-initio molecular dynamics code based on plane wave DFT, and WEST is a post-DFT code for excited state calculations within many-body perturbation theory.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Delivering Science on Day One

While benchmarking software is useful for testing the performance limits and stability of Argonne National Laboratory’s new Theta supercomputer, there is no substitute for running real applications to explore the system’s potential. The Argonne Leadership Computing Facility’s Theta Early Science Program, modeled after its highly successful code migration program for the Mira supercomputer, has one primary aim: to deliver science on day one. Here is a closer look at the type of science problems that will be getting early access to Theta, a next-generation machine being rolled out this year.

Williams, Timothy J.↗