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At least 217 records · Page 12

Automated methods for scalable, parallelized enzymatic biopolymer synthesis and modification using microfluidic devices

Methods for the automated template-free synthesis of user-defined sequence controlled biopolymers using microfluidic devices are described. The methods facilitate simultaneous synthesis of up to thousands of uniquely addressed biopolymers from the controlled movement and combination of regents as fluid droplets using microfluidic and EWOD-based systems. In some forms, biopolymers including nucleic acids, peptides, carbohydrates, and lipids are synthesized from step-wise assembly of building blocks based on a user-defined sequence of droplet movements. In some forms, the methods synthesize uniquely addressed nucleic acids of up to 1,000 nucleotides in length. Methods for adding, removing and changing barcodes on biopolymers are also provided. Biopolymers synthesized according to the methods, and libraries and databases thereof are also described. Modified biopolymers, including chemically modified nucleotides and biopolymers conjugated to other molecules are described.

Banal, James↗

A Viable New Strategy for the Discovery of Peptide Proteolytic Cleavage Products in Plant-Microbe Interactions

Small peptides that are proteolytic cleavage products (PCPs) of less than 100 amino acids are emerging as key signaling molecules that mediate cell-to-cell communication and biological processes that occur between and within plants, fungi, and bacteria. Yet, the discovery and characterization of these molecules is largely overlooked. Today, selective enrichment and subsequent characterization by mass spectrometry–based sequencing offers the greatest potential for their comprehensive characterization, however qualitative and quantitative performance metrics are rarely captured. Herein, we addressed this need by benchmarking the performance of an enrichment strategy, optimized specifically for small PCPs, using state-of-the-art de novo–assisted peptide sequencing. As a case study, we implemented this approach to identify PCPs from different root and foliar tissues of the hybrid poplar Populus × canescens 717-1B4 in interaction with the ectomycorrhizal basidiomycete Laccaria bicolor . In total, we identified 1,660 and 2,870 Populus and L. bicolor unique PCPs, respectively. Qualitative results supported the identification of well-known PCPs, like the mature form of the photosystem II complex 5-kDa protein (approximately 3 kDa). A total of 157 PCPs were determined to be significantly more abundant in root tips with established ectomycorrhiza when compared with root tips without established ectomycorrhiza and extramatrical mycelium of L. bicolor . These PCPs mapped to 64 Populus proteins and 69 L. bicolor proteins in our database, with several of them previously implicated in biologically relevant associations between plant and fungus.

59 BASIC BIOLOGICAL SCIENCES↗

A Hybrid AI/ML and Computational Mechanics Based Approach for Time-Series State and Fatigue Life Estimation of Nuclear Reactor Components

Environmental fatigue modeling is a complex problem due to multiple failure modes and their intermixing. The failure modes are function of various underlying causes in addition to the corrosive effect of reactor coolant environment. Some of the major causes are time-dependence of material associated with cyclic loading, load sequence effect associated with random/variable amplitude loading, effect of strain amplitude and rates, effect of varying temperature (along both temporal and spatial directions) and the effect of mean strain and stress. The nonlinear intermixing of failure modes associated with above mentioned causing parameters makes the environmental fatigue modeling is a challenging task. Because of this challenge, fatigue is traditionally being modeled based on experimental data. However, test based empirical approach often requires hundreds of fatigue tests to model the above-mentioned intermixing failure causes even for a single material system. The problem is further exaggerated for reactor component made from multi-material systems such as made from both carbon and stainless-steel base metals and their similar and dissimilar metal welds. With the difficulty of conducting hundreds of fatigue tests to capture the above-mentioned intermixing failure causes, fatigue modeling approaches often depends on empirical models based on limited available test data such as available through ASME code and NUREG 6909. However, these limited test-data-based models may not be enough to accurately predict the life of reactor components. Accurate prediction of life of reactor component would become a necessity, particularly when the license of the reactors to be extended for long-term-operation (LTO) that is for well beyond its original design life of 40 years. The requirement of extending the license of reactor under LTO requires hundreds of fatigue tests to be conducted to understand the mechanism associated with the above-mentioned interdependent failure causes. However, conducting large number of fatigue tests is not a feasibility due to the cost involved. To address this issues Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program trying to develop a hybrid predictive modeling approach. This is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics based modeling tools. The hybrid approach not-only can improve the accuracy of the existing stress analysis and fatigue modeling approach but also can reduce the over-dependency on test-based approach. Towards this goal following are some of the major contributions based on ANL’s FY-20 environmental fatigue modeling activities: 1) A cyclic plasticity material model database for 82/182 dissimilar metal weld, which can be readily shared with US nuclear industry and regulatory agency on request. 2) A well validated analytical modeling methodology to perform cycle-by-cycle stress prediction under both constant amplitude fatigue loading and variable amplitude fatigue loading (with load-sequence effect). 3) An AI/ML/DL based methodology to predict unmeasurable cyclic strain based on other available sensor signals. This type of approach can be used for estimating strain in real reactor components from other sensor readings. 4) An AI/ML based approach to improve the US capability on environmental fatigue testing. This is by improving ANL’s existing environmental fatigue testing capacity to conduct ASME required strain-controlled tests (by controlling strain amplitudes and its rate), while not measuring the strain (due to the difficulty of placing an extensometer in a narrow autoclave in a PWR-water-test system). 5) A simulation and experiment based probabilistic modeling methodology for time-series fatigue state and life estimation of reactor metal such as dissimilar metal weld.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Separable shape tensors for aerodynamic design

Airfoil shape design is a classical problem in engineering and manufacturing. In this work, we combine principled physics-based considerations for the shape design problem with modern computational techniques using a data-driven approach. Modern and traditional analyses of two-dimensional (2D) and three-dimensional (3D) aerodynamic shapes reveal a flow-based sensitivity to specific deformations that can be represented generally by affine transformations (rotation, scaling, shearing, and translation). We present a novel representation of shapes that decouples affine-style deformations over a submanifold and a product submanifold principally of the Grassmannian. As an analytic generative model, the separable representation, informed by a database of physically relevant airfoils, offers: (i) a rich set of novel 2D airfoil deformations not previously captured in the data, (ii) an improved low-dimensional parameter domain for inferential statistics informing design/manufacturing, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal 2D shapes.

42 ENGINEERING↗

Geophysical methods reveal the soil architecture and subsurface stratigraphic heterogeneities across land-lake interfaces along Lake Erie

Abstract Purpose The land-lake interface is a unique zone where terrestrial and aquatic ecosystems meet, forming part of the Earth’s most geochemically and biologically active zones. The unique characteristics of this interface are yet to be properly understood due to the inherently high spatiotemporal variability of subsurface properties, which are difficult to capture with the traditional soil sampling methods. Geophysical methods offer non-invasive techniques to capture variabilities in soil properties at a high resolution across various spatiotemporal scales. Methods We combined electromagnetic induction (EMI), electrical resistivity tomography (ERT), and ground penetrating radar (GPR) with data from soil cores and in situ sensors to investigate hydrostratigraphic heterogeneities across land-lake interfaces along the western basin of Lake Erie. Results EMI revealed high spatial heterogeneities in ECa distribution across the land-lake interfaces, with higher values in the wetland and transition zones compared to the upland zone. Soil ECa maps matched soil maps from a public database with the hydric soil units delineated as high conductivity zones (ECa > 40 mS/m). ERT and GPR showed vertical variation in soil properties with clear stratigraphic boundaries, and correlation of ERT profiles with lithologs from piezometers revealed the stratigraphic units of silt–clay and till sequence down to 3.5 m depth which are consistent with the surficial geology of the study area. Conclusions These results validate the use of multiple geophysical methods for extrapolating soil properties and mapping stratigraphic structures at land-lake interfaces, thereby providing the missing information required to improve the earth system model (ESM) of coastal interfaces.

54 ENVIRONMENTAL SCIENCES↗

P finder: genomic and metagenomic annotation of RNase P RNA gene (rnpB)

Abstract Background The rnpB gene encodes for an essential catalytic RNA (RNase P). Like other essential RNAs, RNase P’s sequence is highly variable. However, unlike other essential RNAs (i.e. tRNA, 16 S, 6 S,...) its structure is also variable with at least 5 distinct structure types observed in prokaryotes. This structural variability makes it labor intensive and challenging to create and maintain covariance models for the detection of RNase P RNA in genomic and metagenomic sequences. The lack of a facile and rapid annotation algorithm has led to the rnpB gene being the most grossly under annotated essential gene in completed prokaryotic genomes with only a 24% annotation rate. Here we describe the coupling of the largest RNase P RNA database with the local alignment scoring algorithm to create the most sensitive and rapid prokaryote rnpB gene identification and annotation algorithm to date. Results Of the 2772 completed microbial genomes downloaded from GenBank only 665 genomes had an annotated rnpB gene. We applied P Finder to these genomes and were able to identify 2733 or nearly 99% of the 2772 microbial genomes examined. From these results four new rnpB genes that encode the minimal T-type P RNase P RNAs were identified computationally for the first time. In addition, only the second C-type RNase P RNA was identified in Sphaerobacter thermophilus . Of special note, no RNase P RNAs were detected in several obligate endosymbionts of sap sucking insects suggesting a novel evolutionary adaptation. Conclusions The coupling of the largest RNase P RNA database and associated structure class identification with the P Finder algorithm is both sensitive and rapid, yielding high quality results to aid researchers annotating either genomic or metagenomic data. It is the only algorithm to date that can identify challenging RNAse P classes such as C-type and the minimal T-type RNase P RNAs. P Finder is written in C# and has a user-friendly GUI that can run on multiple 64-bit windows platforms (Windows Vista/7/8/10). P Finder is free available for download at https://github.com/JChristopherEllis/P-Finder as well as a small sample RNase P RNA file for testing.

59 BASIC BIOLOGICAL SCIENCES↗

Exposing new taxonomic variation with inflammation — a murine model-specific genome database for gut microbiome researchers

The murine CBA/J mouse model widely supports immunology and enteric pathogen research. This model has illuminated Salmonella interactions with the gut microbiome since pathogen proliferation does not require disruptive pretreatment of the native microbiota, nor does it become systemic, thereby representing an analog to gastroenteritis disease progression in humans. Despite the value to broad research communities, microbiota in CBA/J mice are not represented in current murine microbiome genome catalogs. Here we present the first microbial and viral genomic catalog of the CBA/J murine gut microbiome. Using fecal microbial communities from untreated and Salmonella-infected, highly inflamed mice, we performed genomic reconstruction to determine the impacts on gut microbiome membership and functional potential. From high depth whole community sequencing (~ 42.4 Gbps/sample), we reconstructed 2281 bacterial and 4516 viral draft genomes. Salmonella challenge significantly altered gut membership in CBA/J mice, revealing 30 genera and 98 species that were conditionally rare and unsampled in non-inflamed mice. Additionally, inflamed communities were depleted in microbial genes that modulate host anti-inflammatory pathways and enriched in genes for respiratory energy generation. Our findings suggest decreases in butyrate concentrations during Salmonella infection corresponded to reductions in the relative abundance in members of the Alistipes. Strain-level comparison of CBA/J microbial genomes to prominent murine gut microbiome databases identified newly sampled lineages in this resource, while comparisons to human gut microbiomes extended the host relevance of dominant CBA/J inflammation-resistant strains. This CBA/J microbiome database provides the first genomic sampling of relevant, uncultivated microorganisms within the gut from this widely used laboratory model. Using this resource, we curated a functional, strain-resolved view on how Salmonella remodels intact murine gut communities, advancing pathobiome understanding beyond inferences from prior amplicon-based approaches. Salmonella-induced inflammation suppressed Alistipes and other dominant members, while rarer commensals like Lactobacillus and Enterococcus endure. The rare and novel species sampled across this inflammation gradient advance the utility of this microbiome resource to benefit the broad research needs of the CBA/J scientific community, and those using murine models for understanding the impact of inflammation on the gut microbiome more generally.

59 BASIC BIOLOGICAL SCIENCES↗

Genome-wide identification and functional prediction of silicon (Si) transporters in poplar (Populus trichocarpa)

Abstract Silicon (Si) enhances plant tolerance to various biotic and abiotic stressors such as salinity, drought, and heat. In addition, Si can be biomineralized within plants to form organic carbon-containing phytoliths that can have ecosystem-level consequences by contributing to long-term carbon sequestration. Si is taken up and transported in plants via different transporter proteins such as influx transporters (e.g., Lsi1, Lsi6) and efflux transporters (e.g., Lsi2). Additionally, the imported Si can be deposited in plant leaves via silicification process using the Siliplant 1 (e.g., Slp1) protein. Functional homologs of these proteins have been reported in different food crops. Here, we performed a genome-wide analysis to identify different Si transporters and Slp1 homologs in the bioenergy crop poplar ( Populus trichocarpa Torr. and A. Gray ex W. Hook). We identified one channel-type Si influx transporter (PtLsi1; Potri.017G083300), one Si efflux transporter (PtLsi2; Potri.012G144000) and two proteins like Slp1 (PtSlp1a; Potri.004G168600 and PtSlp1b; Potri.009G129900 ) in the P. trichocarpa genome. We found a unique sequence (KPKPPVFKPPPVPI) in PtSlp1a which is repeated six times. Repeated presence of this sequence in PtSlp1a indicates that this protein might be important for silicification processes in P. trichocarpa. The mutation profiles of different Si transporters in a P. trichocarpa genome-wide association study population identified significant and impactful mutations in Potri.004G168600 and Potri.009G129900 . Using a publically accessible database ( http://bar.utoronto.ca/eplant_poplar/ ), digital expression analysis of the putative Si transporters in P. trichocarpa found low to moderate expression in the anticipated tissues, such as roots and leaves. Subcellular localization analysis found that PtLsi1/PtLsi2 are localized in the plasma membrane, whereas PtSlp1a/PtSlp1b are found in the extracellular spaces. Protein–Protein interaction analysis of PtLsi1/PtLsi2 identified Delta-1-pyrroline-5-carboxylate synthase (P5CS) as one of the main interacting partners of PtLsi2, which plays a key role in proline biosynthesis. Proline is a well-known participant in biotic and abiotic stress tolerance in plants. These findings will reinforce future efforts to modify Si accumulation for enhancing plant stress tolerance and carbon sequestration in poplar.

59 BASIC BIOLOGICAL SCIENCES↗

IMG/VR v4: an expanded database of uncultivated virus genomes within a framework of extensive functional, taxonomic, and ecological metadata

Viruses are widely recognized as critical members of all microbiomes. Metagenomics enables large-scale exploration of the global virosphere, progressively revealing the extensive genomic diversity of viruses on Earth and highlighting the myriad of ways by which viruses impact biological processes. IMG/VR provides access to the largest collection of viral sequences obtained from (meta)genomes, along with functional annotation and rich metadata. A web interface enables users to efficiently browse and search viruses based on genome features and/or sequence similarity. Here, for this work, we present the fourth version of IMG/VR, composed of >15 million virus genomes and genome fragments, a ≈6-fold increase in size compared to the previous version. These clustered into 8.7 million viral operational taxonomic units, including 231 408 with at least one high-quality representative. Viral sequences in IMG/VR are now systematically identified from genomes, metagenomes, and metatranscriptomes using a new detection approach (geNomad), and IMG standard annotation are complemented with genome quality estimation using CheckV, taxonomic classification reflecting the latest taxonomic standards, and microbial host taxonomy prediction. IMG/VR v4 is available at https://img.jgi.doe.gov/vr, and the underlying data are available to download at https://genome.jgi.doe.gov/portal/IMG_VR.

59 BASIC BIOLOGICAL SCIENCES↗

Genome‐wide association study of multiple yield traits in a diversity panel of polyploid sugarcane ( Saccharum spp.)

Abstract Sugarcane ( Saccharum spp.) is an important economic crop, contributing up to 80% of sugar and approximately 60% of biofuel globally. To meet the increased demand for sugar and biofuel supplies, it is critical to breed sugarcane cultivars with robust performance in yield traits. Therefore, dissection of causal DNA sequence variants is of great importance, as it provides genetic resources and fundamental information for crop improvement. In this study, we analyzed nine yield traits in a sugarcane diversity panel consisting of 308 accessions primarily selected from the World Collection of Sugarcane and Related Grasses. By genotyping the diversity panel via target enrichment sequencing, we identified a large number of sequence variants. Genome‐wide association studies between the markers and traits were conducted, taking dosages and gene actions into consideration. In total, 217 nonredundant markers and 225 candidate genes were identified to be significantly associated with the yield traits, which can serve as a comprehensive genetic resource database for future gene identification, characterization, and selection for sugarcane improvement. We further investigated runs of homozygosity (ROH) in the sugarcane diversity panel. We characterized 282 ROHs and found that the occurrence of ROHs in the genome were nonrandom and probably under selection. The ROHs were associated with total weight and dry weight, and high ROHs resulted in a decrease in the two traits. This study suggests that genomic inbreeding has led to negative impacts on sugarcane yield.

Yang, Xiping↗

Metagenomic Insights Into the Microbial Iron Cycle of Subseafloor Habitats

Microbial iron cycling influences the flux of major nutrients in the environment (e.g., through the adsorptive capacity of iron oxides) and includes biotically induced iron oxidation and reduction processes. The ecological extent of microbial iron cycling is not well understood, even with increased sequencing efforts, in part due to limitations in gene annotation pipelines and limitations in experimental studies linking phenotype to genotype. This is particularly true for the marine subseafloor, which remains undersampled, but represents the largest contiguous habitat on Earth. To address this limitation, we used FeGenie, a database and bioinformatics tool that identifies microbial iron cycling genes and enables the development of testable hypotheses on the biogeochemical cycling of iron. Herein, we survey the microbial iron cycle in diverse subseafloor habitats, including sediment-buried crustal aquifers, as well as surficial and deep sediments. We inferred the genetic potential for iron redox cycling in 32 of the 46 metagenomes included in our analysis, demonstrating the prevalence of these activities across underexplored subseafloor ecosystems. We show that while some processes (e.g., iron uptake and storage, siderophore transport potential, and iron gene regulation) are near-universal, others (e.g., iron reduction/oxidation, siderophore synthesis, and magnetosome formation) are dependent on local redox and nutrient status. Additionally, we detected niche-specific differences in strategies used for dissimilatory iron reduction, suggesting that geochemical constraints likely play an important role in dictating the dominant mechanisms for iron cycling. Overall, our survey advances the known distribution, magnitude, and potential ecological impact of microbe-mediated iron cycling and utilization in sub-benthic ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

NASA GeneLab RNA-seq consensus pipeline: Standardized processing of short-read RNA-seq data

With the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility, and reusability of pipeline data; to provide a template for data processing of future spaceflight-relevant datasets; and to encourage cross-analysis of data from other databases with the data available in GeneLab.

59 BASIC BIOLOGICAL SCIENCES↗

Standardized multi-omics of Earth’s microbiomes reveals microbial and metabolite diversity

Despite advances in sequencing, lack of standardization makes comparisons across studies challenging and hampers insights into the structure and function of microbial communities across multiple habitats on a planetary scale. Here we present a multi-omics analysis of a diverse set of 880 microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry). We used standardized protocols and analytical methods to characterize microbial communities, focusing on relationships and co-occurrences of microbially related metabolites and microbial taxa across environments, thus allowing us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of an evolving community resource. We demonstrate the utility of this database by testing the hypothesis that every microbe and metabolite is everywhere but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment, whereas the relative abundances of microbially related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner. We additionally show the power of certain chemistry, in particular terpenoids, in distinguishing Earth’s environments (for example, terrestrial plant surfaces and soils, freshwater and marine animal stool), as well as that of certain microbes including Conexibacter woesei (terrestrial soils), Haloquadratum walsbyi (marine deposits) and Pantoea dispersa (terrestrial plant detritus). This Resource provides insight into the taxa and metabolites within microbial communities from diverse habitats across Earth, informing both microbial and chemical ecology, and provides a foundation and methods for multi-omics microbiome studies of hosts and the environment.

59 BASIC BIOLOGICAL SCIENCES↗

COMPILE: a GWAS computational pipeline for gene discovery in complex genomes

Abstract Background Genome-Wide Association Studies (GWAS) are used to identify genes and alleles that contribute to quantitative traits in large and genetically diverse populations. However, traits with complex genetic architectures create an enormous computational load for discovery of candidate genes with acceptable statistical certainty. We developed a streamlined computational pipeline for GWAS (COMPILE) to accelerate identification and annotation of candidate maize genes associated with a quantitative trait, and then matches maize genes to their closest rice and Arabidopsis homologs by sequence similarity. Results COMPILE executed GWAS using a Mixed Linear Model that incorporated, without compression, recent advancements in population structure control, then linked significant Quantitative Trait Loci (QTL) to candidate genes and RNA regulatory elements contained in any genome. COMPILE was validated using published data to identify QTL associated with the traits of α-tocopherol biosynthesis and flowering time, and identified published candidate genes as well as additional genes and non-coding RNAs. We then applied COMPILE to 274 genotypes of the maize Goodman Association Panel to identify candidate loci contributing to resistance of maize stems to penetration by larvae of the European Corn Borer ( Ostrinia nubilalis ). Candidate genes included those that encode a gene of unknown function, WRKY and MYB-like transcriptional factors, receptor-kinase signaling, riboflavin synthesis, nucleotide-sugar interconversion, and prolyl hydroxylation. Expression of the gene of unknown function has been associated with pathogen stress in maize and in rice homologs closest in sequence identity. Conclusions The relative speed of data analysis using COMPILE allowed comparison of population size and compression. Limitations in population size and diversity are major constraints for a trait and are not overcome by increasing marker density. COMPILE is customizable and is readily adaptable for application to species with robust genomic and proteome databases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Preprocessing of Galaxies in the Early Stages of Cluster Formation in Abell 1882 at z = 0.139

A rare opportunity to distinguish between internal and environmental effects on galaxy evolution is afforded by "SuperGroups," systems that are rich and massive, but include several comparably rich substructures, surrounded by filaments. We present here a multiwavelength photometric and spectroscopic study of the galaxy population in the SuperGroup Abell 1882 (A1882) at z = 0.139, combining new data from the MMT and Hectospec with archival results from the Galaxy And Mass Assembly survey, the Sloan Digital Sky Survey, the Nasa/IPAC Extragalactic Database, the Gemini Multi-Object Spectrograph, and the Galaxy Evolution Explorer. These provide spectroscopic classifications for 526 member galaxies, across wide ranges of local density and velocity dispersion. We identify three prominent filaments along which galaxies seem to be entering the SuperGroup (mostly in E–W directions). A1882 has a well-populated red sequence, containing most galaxies with stellar mass >10 10.5 M Sun , and a pronounced color–density relation even within its substructures. Thus, galaxy evolution responds to the external environment as strongly in these unrelaxed systems as we find in rich and relaxed clusters. From these data, local density remains the primary factor, with a secondary role for distance from the inferred center of the entire structure's potential well. The effects on star formation, as traced by optical and near-UV colors, depend on galaxy mass. We see changes in lower-mass galaxies (M < 10 10.5 M Sun ) at four times the virial radius of major substructures, while the more massive near-UV Green Valley galaxies show low levels of star formation within two virial radii. The suppression of star formation ("quenching") occurs in the infall regions of these structures even before the galaxies enter the denser group environment.

79 ASTRONOMY AND ASTROPHYSICS↗

DIVA/DeviceEditor (DIVA) v6.0.0

The DIVA software interfaces a process in which researchers design their DNA with a web-based graphical user interface (DeviceEditor), submit their designs to a central queue, and a few weeks later receive their sequence-verified clonal constructs. Each researcher independently designs the DNA to be constructed with a web-based BioCAD tool, and presses a button to submit their designs to a central queue. Researchers have web-based access to their DNA design queues, and can track the progress of their submitted designs as they progress from "evaluation", to "waiting for reagents", to "in progress", to "complete". Researchers access their completed constructs through the central DNA repository. Along the way, all DNA construction success/failure rates are captured in a central database. Once a design has been submitted to the queue, a small number of dedicated staff evaluate the design for feasibility and provide feedback to the responsible researcher if the design is either unreasonable (e.g., encompasses a combinatorial library of a billion constructs) or small design changes could significantly facilitate the downstream implementation process. The dedicated staff then use DNA assembly design automation software to optimize the DNA construction process for the design, leveraging existing parts from the DNA repository where possible and ordering synthetic DNA where necessary. Once all requisite process inputs are available, the design progresses from "waiting for reagents" to "in progress" in the design queue. Human-readable and machine-parseable DNA construction protocols output by the DNA assembly design automation software are then executed by the dedicated staff exploiting lab automation devices wherever possible. Since the all employed DNA construction methods are sequence-agnostic, standardized (utilize the same enzymatic master mixes and reaction conditions), completely independent DNA construction tasks can be aggregated into the same multi-well plates and pursued in parallel. The resulting sets of cloned constructs can then be screened by high-throughput next-gen sequencing platforms for sequence correctness. A combination of long read-length (e.g., PacBio) and paired-end read platforms (e.g., Illumina) would be exploited depending the particular task at hand (e.g., PacBio might be sufficient to screen a set of pooled constructs with significant gene divergence). Post sequence verification, designs for which at least one correct clone was identified will progress to a "complete" status, while designs for which no correct clones were identified will progress to a "failure" status. Depending on the failure mode (e.g., no transformants), and how many prior attempts/variations of assembly protocol have been already made for a given design, subsequent attempts may be made or the design can progress to a "permanent failure" state. All success and failure rate information will be captured during the process, including at which stage a given clonal construction procedure failed (e.g., no PCR product) and what the exact failure was (e.g. assembly piece 2 missing). This success/failure rate data can be leveraged to refine the DNA assembly design process.

Plahar, Hector↗

White Dwarf Binaries across the H-R Diagram

We created the APOGEE-GALEX-Gaia catalog to study white dwarf (WD) binaries. This database aims to create a minimally biased sample of WD binary systems identified from a combination of GALEX, Gaia, and APOGEE data to increase the number of WD binaries with orbital parameters and chemical compositions. We identify 3414 sources as WD binary candidates, with nondegenerate companions of spectral types between F and M, including main-sequence stars, main-sequence binaries, subgiants, sub-subgiants, red giants, and red clump stars. Among our findings are (a) a total of 1806 systems having inferred WD radii R < 25 R ⊕ , which constitute a more reliable group of WD binary candidates within the main sample; (b) a difference in the metallicity distribution function between WD binary candidates and the control sample of most luminous giants (M H < -3.0); (c) the existence of a population of sub-subgiants with WD companions; (d) evidence for shorter periods in binaries that contain WDs compared to those that do not, as shown by the cumulative distributions of APOGEE radial velocity shifts; (e) evidence for systemic orbital evolution in a sample of 252 WD binaries with orbital periods, based on differences in the period distribution between systems with red clump, main-sequence binary, and sub-subgiant companions and systems with main-sequence or red giant companions; and (f) evidence for chemical enrichment during common envelope (CE) evolution, shown by lower metallicities in wide WD binary candidates (P > 100 days) compared to post-CE (P < 100 days) WD binary candidates.

79 ASTRONOMY AND ASTROPHYSICS↗

Interactive tools for functional annotation of bacterial genomes

Automated annotations of protein functions are error-prone because of our lack of knowledge of protein functions. For example, it is often impossible to predict the correct substrate for an enzyme or a transporter. Furthermore, much of the knowledge that we do have about the functions of proteins is missing from the underlying databases. We discuss how to use interactive tools to quickly find different kinds of information relevant to a protein’s function. Many of these tools are available via PaperBLAST (http://papers.genomics.lbl.gov). Combining these tools often allows us to infer a protein’s function. Ideally, accurate annotations would allow us to predict a bacterium’s capabilities from its genome sequence, but in practice, this remains challenging. We describe interactive tools that infer potential capabilities from a genome sequence or that search a genome to find proteins that might perform a specific function of interest.

59 BASIC BIOLOGICAL SCIENCES↗