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The work is reported in the determination of acceptable deployment sequences, simulation of EFM antenna deployment, and contingency analysis for the IMP-J S/C. The spacecraft, mission profile and deployment sequences are described along with the simulation of EFM deployment and deployment failure.
Background: HIV outbreaks in the Former Soviet Union (FSU) countries were characterized by repeated transmission of the HIV variant AFSU, which is now classified as a distinct subtype A sub-subtype called A6. The current study used phylogenetic/phylodynamic and signature mutation analyses to determine likely evolutionary relationship between subtype A6 and other subtype A sub-subtypes. Methods: For this study, an initial Maximum Likelihood phylogenetic analysis was performed using a total of 553 full-length, publicly available, reverse transcriptase sequences, from A1, A2, A3, A4, A5, and A6 sub-subtypes of subtype A. For phylogenetic clustering and signature mutation analysis, a total of 5961 and 3959 pol and env sequences, respectively, were used. Results: Phylogenetic and signature mutation analysis showed that HIV-1 sub-subtype A6 likely originated from sub-subtype A1 of African origin. A6 and A1 pol and env genes shared several signature mutations that indicate genetic similarity between the two subtypes. For A6, tMRCA dated to 1975, 15 years later than that of A1. Conclusion: The current study provides insights into the evolution and diversification of A6 in the backdrop of FSU countries and indicates that A6 in FSU countries evolved from A1 of African origin and is getting bridged outside the FSU region.
Microbial dynamics drive the biotic machinery of early soil evolution. However, integrated knowledge of microbial community establishment, functional associations, and community assembly processes in incipient soil is lacking. This study presents a novel approach of combining microbial phylogenetic profiling, functional predictions, and community assembly processes to analyze drivers of microbial community establishment in an emerging soil system. Rigorous sub-meter sampling of a basalt-soil lysimeter after two years of irrigation revealed the contrasting depth-dependent distribution patterns of soil parameters and community diversity. Phylogenetic analysis of 16S rRNA gene indicated the presence of diverse bacterial and archaeal phyla, with high relative abundance of Actinobacteria on the surface and a consistently high abundance of Proteobacteria at all depths. Predicted functional gene analysis suggested dominant autotrophy signatures, evidence of an incomplete nitrogen cycle, and predicted enzymes of iron (III) to iron (II) conversion followed by intracellular uptake, transport, and regulation. Null modeling revealed microbial community assembly predominantly governed by variable selection. The relative influence of the variable selection decreased with depth, indicating unique and relatively harsh environmental conditions near the surface and more benign conditions with depth. Additionally, high levels of dispersal influenced community composition near the center of the domain, suggesting that spatial processes interact with deterministic selection imposed by the environment. Characterizing the complexity in incipient soils can advance research insights about microbial community diversity and assembly in other incipient systems (e.g., transformation of marginal soils, or soils recovering from disturbances such as fire, erosion, intensive agricultural practices, or contamination).
Abstract Algae are a diverse, polyphyletic group of photosynthetic eukaryotes spanning nearly all eukaryotic lineages of life and collectively responsible for ∼50% of photosynthesis on Earth. Sequenced algal genomes, critical to understanding their complex biology, are growing in number and require efficient tools for analysis. PhycoCosm (https://phycocosm.jgi.doe.gov) is an algal multi-omics portal, developed by the US Department of Energy Joint Genome Institute to support analysis and distribution of algal genome sequences and other ‘omics’ data. PhycoCosm provides integration of genome sequence and annotation for >100 algal genomes with available multi-omics data and interactive web-based tools to enable algal research in bioenergy and the environment, encouraging community engagement and data exchange, and fostering new sequencing projects that will further these research goals.
The revolution in next-generation DNA sequencing technologies is leading to explosive data growth in genomics, posing a significant challenge to the computing infrastructure and software algorithms for genomics analysis. Various big data technologies have been explored to scale up/out current bioinformatics solutions to mine the big genomics data. In this review, we survey some of these exciting developments in the applications of parallel distributed computing and special hardware to genomics. We comment on the pros and cons of each strategy in the context of ease of development, robustness, scalability, and efficiency. Although this review is written for an audience from the genomics and bioinformatics fields, it may also be informative for the audience of computer science with interests in genomics applications.
The changes caused by heat treatment of gibbsite powder at 300–1473 K were studied using the X-ray diffraction (XRD), X-ray photoemission (XPS) spectra and {sup 27}Al magic angle spinning nuclear magnetic resonance spectroscopy ({sup 27}Al MAS NMR). XRD analysis indicates that the transformation sequence involves the formation of κ-Al{sub 2}O{sub 3} as an intermediate phase between χ- and α-Al{sub 2}O{sub 3}. The crystallite size of χ-Al{sub 2}O{sub 3} is as small as 10 nm. XPS analysis indicates that the ratio of aluminium atoms to oxygen atoms in χ-Al{sub 2}O{sub 3} and κ-Al{sub 2}O{sub 3} increases, whereas the expected ratio is observed in α-Al{sub 2}O{sub 3}. The percentage of AlO{sub 4} units in the transition aluminas follows the same behaviour as the ratio of Al/O. - Graphical abstract: The percentage of AlO{sub 4} units in transition aluminas follows the same behaviour as the ratio of Al/O. - Highlights: • Calcination products of gibbsite studied by XRD, XPS and solid-state NMR. • The crystallite size of χ-Al{sub 2}O{sub 3} is as small as 10 nm. • The Al/O atomic ratio determined by XPS is larger than 2/3 in χ-Al{sub 2}O{sub 3} and κ-Al{sub 2}O{sub 3}. • The percentage of AlO{sub 4} in the aluminas follows the same behaviour as the Al/O atomic ratio.
Aircraft loss of control (LOC) is a leading cause of fatal accidents across all transport airplane and operational classes, and can result from a wide spectrum of hazards, often occurring in combination. Technologies developed for LOC prevention and recovery must therefore be effective under a wide variety of conditions and uncertainties, including multiple hazards, and their validation must provide a means of assessing system effectiveness and coverage of these hazards. This requires the definition of a comprehensive set of LOC test scenarios based on accident and incident data as well as future risks. This paper defines a comprehensive set of accidents and incidents over a recent 15 year period, and presents preliminary analysis results to identify worst-case combinations of causal and contributing factors (i.e., accident precursors) and how they sequence in time. Such analyses can provide insight in developing effective solutions for LOC, and form the basis for developing test scenarios that can be used in evaluating them. Preliminary findings based on the results of this paper indicate that system failures or malfunctions, crew actions or inactions, vehicle impairment conditions, and vehicle upsets contributed the most to accidents and fatalities, followed by inclement weather or atmospheric disturbances and poor visibility. Follow-on research will include finalizing the analysis through a team consensus process, defining future risks, and developing a comprehensive set of test scenarios with correlation to the accidents, incidents, and future risks. Since enhanced engineering simulations are required for batch and piloted evaluations under realistic LOC precursor conditions, these test scenarios can also serve as a high-level requirement for defining the engineering simulation enhancements needed for generating them.
Sclerostin, the SOST gene product, is a negative regulator of bone formation and a positive regulator of bone resorption. Here, in this study, treatment of human primary osteoblasts, including cells differentiated to an osteocyte-like stage, with 1α,25-dihydroxyvitaminD 3 (1,25D) resulted in the dose-dependent increased expression of SOST mRNA. A similar effect was observed in human trabecular bone samples cultured ex vivo, and in osteocyte-like cultures of differentiated SAOS2 cells. Treatment of SAOS2 cells with 1,25D resulted in the production and secretion of sclerostin protein. In silico analysis of the human SOST gene revealed a single putative DR3-type vitamin D response element (VDRE) at position -6216 bp upstream of the transcription start site (TSS). This sequence was confirmed to have strong VDRE activity by luciferase reporter assays and electrophoretic mobility shift analysis (EMSA). Sequence substitution in the VDR/RXR half-sites abolished VDRE reporter activity and binding of nuclear proteins. A 6.3 kb fragment of the human proximal SOST promoter demonstrated responsiveness to 1,25D. The addition of the evolutionary conserved region 5 (ECR5), a known bone specific enhancer region, ahead of the 6.3 kb fragment increased basal promoter activity but did not increase 1,25D responsiveness. Site-specific mutagenesis abolished the responsiveness of the 6.3 kb promoter to 1,25D. We conclude that 1,25D is a direct regulator of human SOST gene and sclerostin protein expression, extending the pathways of control of sclerostin expression. At least some of this responsiveness is mediated by the identified classical VDRE however the nature of the transcriptional regulation by 1,25D warrants further investigation.
The mid-lift-to-drag ratio (mid-L/D) lifting body is a fully autonomous spacecraft under design at NASA for enabling a rapid return of scientific payloads from the International Space Station (ISS). For contingency planning and risk assessment for the Earth-return trajectory, an entry demise analysis was performed to examine three potential failure scenarios: (1) nominal entry interface conditions with loss of control, (2) controlled entry at maximum flight path angle, and (3) controlled entry at minimum flight path angle. The objectives of the analysis were to predict the spacecraft breakup sequence and timeline, determine debris survival, and calculate the debris dispersion footprint. Sensitivity analysis was also performed to determine the effect of the initial pitch rate on the spacecraft stability and breakup during the entry. This report describes the mid-L/D lifting body and presents the results of the entry demise and sensitivity analyses.
The emergence of catalytic RNA is believed to have been a key event during the origin of life. Understanding how catalytic activity is distributed across random sequences is fundamental to estimating the probability that catalytic sequences would emerge. Here, we analyze the in vitro evolution of triphosphorylating ribozymes and translate their fitnesses into absolute estimates of catalytic activity for hundreds of ribozyme families. The analysis efficiently identified highly active ribozymes and estimated catalytic activity with good accuracy. The evolutionary dynamics follow Fisher’s Fundamental Theorem of Natural Selection and a corollary, permitting retrospective inference of the distribution of fitness and activity in the random sequence pool for the first time. The frequency distribution of rate constants appears to be log-normal, with a surprisingly steep dropoff at higher activity, consistent with a mechanism for the emergence of activity as the product of many independent contributions.
We adapt the relative polarity method from Shelly et al. (2016) to compute focal mechanisms for microearthquakes associated with the 2014 hydroshearing stimulation at the Newberry volcano geothermal site. We focus the analysis on events relocated by Aguiar and Myers (2018), who report that six event clusters predominantly comprise the 2014 sequence. Data quality allows focal mechanism analysis for four of the six event clusters. We use Hardebeck and Shearer (2002, 2003; hereafter HASH) to compute focal mechanisms based on first–motion polarities and S/P amplitude ratios. We manually determine P– and S–wave polarities for a well–recorded reference event in each cluster, then use waveform cross correlation to determine whether recordings of other events in the cluster are the same or reversed polarity at each network station. Here, most waveform polarities are consistent with the affiliated reference event, indicating similar focal mechanisms within each cluster. The deeper clusters are east–west–striking normal faults, whereas the shallower clusters, close to the top of the open–hole section of the borehole, are strike slip with east–west motion. Regional studies and prestimulation borehole breakouts find the maximum stress direction is vertical and maximum horizontal stress is approximately north–south. Fault geometry and focal mechanisms of microseismicity during the stimulation suggest that increased pressure from fluid injection predominantly caused changes in horizontal stress, consistent with predictions from numerical studies of stress change caused by fluid injection. At shallow depths, where previous studies suggest the difference between vertical and horizontal stress is lowest, injection appears to have rotated the direction of maximum stress from vertical to horizontal, resulting in strike–slip motion. At greater depth, vertical stress continued to be the dominant direction during the stimulation, but fault orientation indicates either reactivation of pre–existing fractures or rotation of the direction of maximum horizontal stress from approximately north–south to east–west.
The Ebola outbreak of 2013–15 infected more than 28,000 people and claimed more lives than all previous filovirus outbreaks combined. Governmental agencies, clinical teams, and the world scientific community pulled together in a multifaceted response ranging from prevention and disease control, to evaluating vaccines and therapeutics in human trials. We report that as this epidemic is finally coming to a close, refocusing on long-term prevention strategies becomes paramount. Given the very real threat of future filovirus outbreaks, and the inherent uncertainty of the next outbreak virus and geographic location, it is prudent to consider the extent and implications of known natural diversity in advancing vaccines and therapeutic approaches. To facilitate such consideration, we have updated and enhanced the content of the filovirus portion of Los Alamos Hemorrhagic Fever Viruses Database. We have integrated and performed baseline analysis of all family Filoviridae sequences deposited into GenBank, with associated immune response data, and metadata, and we have added new computational tools with web-interfaces to assist users with analysis. Here, we (i) describe the main features of updated database, (ii) provide integrated views and some basic analyses summarizing evolutionary patterns as they relate to geo-temporal data captured in the database and (iii) highlight the most conserved regions in the proteome that may be useful for a T cell vaccine strategy.
A methodology is described for generating first-order plant equations of motion for aeroelastic and aeroservoelastic applications. The description begins with the process of generating data files representing specialized mode-shapes, such as rigid-body and control surface modes, using both PATRAN and NASTRAN analysis. NASTRAN executes the 146 solution sequence using numerous Direct Matrix Abstraction Program (DMAP) calls to import the mode-shape files and to perform the aeroelastic response analysis. The aeroelastic response analysis calculates and extracts structural frequencies, generalized masses, frequency-dependent generalized aerodynamic force (GAF) coefficients, sensor deflections and load coefficients data as text-formatted data files. The data files are then re-sequenced and re-formatted using a custom written FORTRAN program. The text-formatted data files are stored and coefficients for s-plane equations are fitted to the frequency-dependent GAF coefficients using two Interactions of Structures, Aerodynamics and Controls (ISAC) programs. With tabular files from stored data created by ISAC, MATLAB generates the first-order aeroservoelastic plant equations of motion. These equations include control-surface actuator, turbulence, sensor and load modeling. Altitude varying root-locus plot and PSD plot results for a model of the F-18 aircraft are presented to demonstrate the capability.
The phylogenetic affiliations of anaerobic gut fungi (Neocallimastigomycota) are typically evaluated using single-gene markers. However, this approach often fails to resolve relationships between closely related lineages. To address this issue and identify alternative markers, we created a curated database comprising the complete ribosomal operon sequences of 156 isolates, representing 20 of the 22 recognized genera and two new genus-level clades. Using long-read sequencing, we obtained ~9 kbp operon sequences and developed a robust analysis pipeline. Incorporating both coding genes and non-coding regions (excluding IGS1) improved phylogenetic resolution. This phylogenetic approach successfully resolved the Cyllamyces and Caecomyces clades (hard-to-distinguish genetically), as well as seven analysed Piromyces species. We also scanned the operon for markers that are suitable for short-read sequencing platforms, with the aim of enhancing biodiversity and phylogenetic studies. Notably, the ETS1 genetic region also enabled the distinction between these lineages, indicating its phylogenetic value within the ribosomal operon. The resulting database is a valuable resource for expanding and strengthening phylogenetic frameworks.
On the basis of small subunit rRNA sequence analyses five major subgroups within the flavobacteria-bacteroides phylum have been defined. These are tentatively designated the cytophaga subgroup (comprising largely Cytophaga species), the flavobacter subgroup (comprising the true flavobacteria and the polyphyletic genus Weeksella), the bacteroides subgroup (comprising the bacteroides and certain cytophaga-like bacteria), the sphingobacter subgroup (which contains the known sphingolipid-producing members of the phylum), and the saprospira subgroup (comprising particular species of Flexibacter, Flavobacterium, Haliscomenobacter, and, of course, the genus Saprospira). These groupings are given not only by evolutionary distance analysis, but can be defined and distinguished on the basis of a simple small subunit rRNA signatures.
Metagenomic sequencing has produced significant amounts of data in recent years. For example, as of summer 2013, MGRAST has been used to annotate over 110,000 data sets totaling over 43 Terabases. With metagenomic sequencing finding even wider adoption in the scientific community, the existing web-based analysis tools and infrastructure in MG-RAST provide limited capability for data retrieval and analysis, such as comparative analysis between multiple data sets. Moreover, although the system provides many analysis tools, it is not comprehensive. By opening MG-RAST up via a web services API (application programmers interface) we have greatly expanded access to MG-RAST data, as well as provided a mechanism for the use of third-party analysis tools with MG-RAST data. This RESTful API makes all data and data objects created by the MG-RAST pipeline accessible as JSON objects. As part of the DOE Systems Biology Knowledgebase project (KBase, http:// kbase.us) we have implemented a web services API for MG-RAST. This API complements the existing MG-RAST web interface and constitutes the basis of KBase’s microbial community capabilities. In addition, the API exposes a comprehensive collection of data to programmers. This API, which uses a RESTful (Representational State Transfer) implementation, is compatible with most programming environments and should be easy to use for end users and third parties. It provides comprehensive access to sequence data, quality control results, annotations, and many other data types. Where feasible, we have used standards to expose data and metadata. Code examples are provided in a number of languages both to show the versatility of the API and to provide a starting point for users. We present an API that exposes the data in MG-RAST for consumption by our users, greatly enhancing the utility of the MG-RAST service.
Rhodopsins are broadly distributed. In this work, we analyzed 23 metagenomes corresponding to marine sediment samples from four regions that share cold climate conditions (Norway; Sweden; Argentina and Antarctica). In order to investigate the genes evolution of viral rhodopsins, an initial set of 6224 bacterial rhodopsin sequences according to COG5524 were retrieved from the 23 metagenomes. After selection by the presence of transmembrane domains and alignment, 123 viral (51) and non-viral (72) sequences (>50 amino acids) were finally included in further analysis. Viral rhodopsin genes were homologs of Phaeocystis globosa virus and Organic lake Phycodnavirus. Non-viral microbial rhodopsin genes were ascribed to Bacteroidetes, Planctomycetes, Firmicutes, Actinobacteria, Cyanobacteria, Proteobacteria, Deinococcus-Thermus and Cryptophyta and Fungi. A rescreening using Blastp, using as queries the viral sequences previously described, retrieved 30 sequences (>100 amino acids). Phylogeographic analysis revealed a geographical clustering of the sequences affiliated to the viral group. This clustering was not observed for the microbial non-viral sequences. The phylogenetic reconstruction allowed us to propose the existence of a putative ancestor of viral rhodopsin genes related to Actinobacteria and Chloroflexi. This is the first report about the existence of a phylogeographic association of the viral rhodopsin sequences from marine sediments.
Here, we report rice consumption is now recognized as an important pathway of human exposure to the neurotoxin methylmercury (MeHg), particularly in countries where rice is a staple food. Although the discovery of a two-gene cluster hgcAB has linked Hg methylation to several phylogenetically diverse groups of anaerobic microorganisms converting inorganic mercury (Hg) to MeHg, the prevalence and diversity of Hg methylators in microbial communities of rice paddy soils remain unclear. We characterized the abundance and distribution of hgcAB genes using third-generation PacBio long-read sequencing and Illumina short-read metagenomic sequencing, in combination with quantitative PCR analyses in several mine-impacted paddy soils from southwest China. Both Illumina and PacBio sequencing analyses revealed that Hg methylating communities were dominated by iron-reducing bacteria (i.e., Geobacter ) and methanogens, with a relatively low abundance of hgcA + sulfate-reducing bacteria in the soil. A positive correlation was observed between the MeHg content in soil and the relative abundance of Geobacter carrying the hgcA gene. Phylogenetic analysis also uncovered some hgcAB sequences closely related to three novel Hg methylators, Geobacter anodireducens , Desulfuromonas sp. DDH964, and Desulfovibrio sp. J2, among which G. anodireducens was validated for its ability to methylate Hg. Lastly, these findings shed new light on microbial community composition and major clades likely driving Hg methylation in rice paddy soils.