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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Divide and Conquer (DC) BLAST: fast and easy BLAST execution within HPC environments

Bioinformatics is currently faced with very large-scale data sets that lead to computational jobs, especially sequence similarity searches, that can take absurdly long times to run. For example, the National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool (BLAST and BLAST+) suite, which is by far the most widely used tool for rapid similarity searching among nucleic acid or amino acid sequences, is highly central processing unit (CPU) intensive. While the BLAST suite of programs perform searches very rapidly, they have the potential to be accelerated. In recent years, distributed computing environments have become more widely accessible and used due to the increasing availability of high-performance computing (HPC) systems. Therefore, simple solutions for data parallelization are needed to expedite BLAST and other sequence analysis tools. However, existing software for parallel sequence similarity searches often requires extensive computational experience and skill on the part of the user. In order to accelerate BLAST and other sequence analysis tools, Divide and Conquer BLAST (DCBLAST) was developed to perform NCBI BLAST searches within a cluster, grid, or HPC environment by using a query sequence distribution approach. Scaling from one (1) to 256 CPU cores resulted in significant improvements in processing speed. Thus, DCBLAST dramatically accelerates the execution of BLAST searches using a simple, accessible, robust, and parallel approach. DCBLAST works across multiple nodes automatically and it overcomes the speed limitation of single-node BLAST programs. DCBLAST can be used on any HPC system, can take advantage of hundreds of nodes, and has no output limitations. Thus, this freely available tool simplifies distributed computation pipelines to facilitate the rapid discovery of sequence similarities between very large data sets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Benchmarking viromics: an in silico evaluation of metagenome-enabled estimates of viral community composition and diversity

Background: Viral metagenomics (viromics) is increasingly used to obtain uncultivated viral genomes, evaluate community diversity, and assess ecological hypotheses. While viromic experimental methods are relatively mature and widely accepted by the research community, robust bioinformatics standards remain to be established. Here we used in silico mock viral communities to evaluate the viromic sequence-to-ecological-inference pipeline, including (i) read pre-processing and metagenome assembly, (ii) thresholds applied to estimate viral relative abundances based on read mapping to assembled contigs, and (iii) normalization methods applied to the matrix of viral relative abundances for alpha and beta diversity estimates. Results: Tools specifically designed for metagenomes, specifically metaSPAdes, MEGAHIT, and IDBA-UD, were the most effective at assembling viromes. Read pre-processing, such as partitioning, had virtually no impact on assembly output, but may be useful when hardware is limited. Viral populations with 2–5 × coverage typically assembled well, whereas lesser coverage led to fragmented assembly. Strain heterogeneity within populations hampered assembly, especially when strains were closely related (average nucleotide identity, or ANI ≥97%) and when the most abundant strain represented <50% of the population. Viral community composition assessments based on read recruitment were generally accurate when the following thresholds for detection were applied: (i) ≥10 kb contig lengths to define populations, (ii) coverage defined from reads mapping at ≥90% identity, and (iii) ≥75% of contig length with ≥1 × coverage. Finally, although data are limited to the most abundant viruses in a community, alpha and beta diversity patterns were robustly estimated (±10%) when comparing samples of similar sequencing depth, but more divergent (up to 80%) when sequencing depth was uneven across the dataset. In the latter cases, the use of normalization methods specifically developed for metagenomes provided the best estimates. Conclusions: These simulations provide benchmarks for selecting analysis cut-offs and establish that an optimized sample-to-ecological-inference viromics pipeline is robust for making ecological inferences from natural viral communities. Continued development to better accessing RNA, rare, and/or diverse viral populations and improved reference viral genome availability will alleviate many of viromics remaining limitations.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Helmet-Mounted Display Technology for Eva Training in NASA's Neutral Buoyancy Lab

Currently, during extravehicular activity (EVA) on the International Space Station (ISS), astronauts are in constant communication with mission control; however, this paradigm will significantly change during future NASA exploration missions due to limited and time-delayed communications. As exploration missions will thereby require an increase in crew autonomy, it is hypothesized that heads-up display (HUD) technology can supplement communications with mission control. Before introducing novel display technology to EVA operations, it must first be demonstrated and evaluated in an EVA training environment. The UC Davis Center for Spaceflight Research, in collaboration with NASA Johnson Space Center’s Human Physiology, Performance, Protection, and Operations (H-3PO) Lab has developed a low-cost and rapid development helmet-mounted display (HMD) for EVA training at NASA’s Neutral Buoyancy Lab (NBL). The first two phases of HMD testing (Phase I and II) at the NBL focused on technology and capability development and demonstration. Crew member feedback was obtained that evaluated aspects of HMD including its user satisfaction, visibility, readability, and usefulness. Overall, feedback indicated HMD was readable, un-obtrusive, and the available display modes had potential to be useful and enhance EVA training. HMD display modes currently available include: real-time biofeedback (metabolic rate), phase elapsed time (PET), ability to set timers, task procedural aids (e.g. Pistol Grip Tool settings) and custom messages. The goal for Phase III, which is currently underway, is to evaluate the effects that access to bioinformatics through HMD has on astronaut training and performance at the NBL. For this phase of testing, crewmembers will be asked to perform a go/no-go task while wearing HMD throughout the NBL run to characterize crew member state of situational awareness with respect to HMD. This information could be used to inform how best to display relatively important or supplemental, but not critical, data in the future.

Heads up display↗
DOE OSTI2014

BBMap: A Fast, Accurate, Splice-Aware Aligner

Alignment of reads is one of the primary computational tasks in bioinformatics. Of paramount importance to resequencing, alignment is also crucial to other areas - quality control, scaffolding, string-graph assembly, homology detection, assembly evaluation, error-correction, expression quantification, and even as a tool to evaluate other tools. An optimal aligner would greatly improve virtually any sequencing process, but optimal alignment is prohibitively expensive for gigabases of data. Here, we will present BBMap [1], a fast splice-aware aligner for short and long reads. We will demonstrate that BBMap has superior speed, sensitivity, and specificity to alternative high-throughput aligners bowtie2 [2], bwa [3], smalt, [4] GSNAP [5], and BLASR [6].

09 BIOMASS FUELS↗
DOE OSTI2014

ISMB Conference Funding to Support Attendance of Early Researchers and Students

ISMB Conference Funding for Students and Young Scientists Historical Description The Intelligent Systems for Molecular Biology (ISMB) conference has provided a general forum for disseminating the latest developments in bioinformatics on an annual basis for the past 22 years. ISMB is a multidisciplinary conference that brings together scientists from computer science, molecular biology, mathematics and statistics. The goal of the ISMB meeting is to bring together biologists and computational scientists in a focus on actual biological problems, i.e., not simply theoretical calculations. The combined focus on “intelligent systems” and actual biological data makes ISMB a unique and highly important meeting. 21 years of experience in holding the conference has resulted in a consistently well-organized, well attended, and highly respected annual conference. "Intelligent systems" include any software which goes beyond straightforward, closed-form algorithms or standard database technologies, and encompasses those that view data in a symbolic fashion, learn from examples, consolidate multiple levels of abstraction, or synthesize results to be cognitively tractable to a human, including the development and application of advanced computational methods for biological problems. Relevant computational techniques include, but are not limited to: machine learning, pattern recognition, knowledge representation, databases, combinatorics, stochastic modeling, string and graph algorithms, linguistic methods, robotics, constraint satisfaction, and parallel computation. Biological areas of interest include molecular structure, genomics, molecular sequence analysis, evolution and phylogenetics, molecular interactions, metabolic pathways, regulatory networks, developmental control, and molecular biology generally. Emphasis is placed on the validation of methods using real data sets, on practical applications in the biological sciences, and on development of novel computational techniques. The ISMB conferences are distinguished from many other conferences in computational biology or artificial intelligence by an insistence that the researchers work with real molecular biology data, not theoretical or toy examples; and from many other biological conferences by providing a forum for technical advances as they occur, which otherwise may be shunned until a firm experimental result is published. The resulting intellectual richness and cross-disciplinary diversity provides an important opportunity for both students and senior researchers. ISMB has become the premier conference series in this field with refereed, published proceedings, establishing an infrastructure to promote the growing body of research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Purification and Characterization of Protein Nanotubes Assembled from a Single Bacterial Microcompartment Shell Subunit

Bacterial microcompartments (BMCs) are apparently icosahedral proteinaceous organelles that are bioinformatically identified in an increasing number of bacterial species. BMCs are delimited by a protein shell composed predominantly of hexameric (BMC-H) subunits that tile into the facets of the BMC shell. Here we report a new biomaterial composed of the single BMC-H protein encoded in the BMC locus of Mycobacterium smegmatis; the function of this type of BMC is unknown. When expressed in Escherichia coli, this BMC-H protein, RmmH, self-assembles into nanotubes, densely packed in the cytoplasmic space. These are the first BMC nanotubes to be purified from cells intact and characterized. Here, we also show formation of the nanotubes initiated from free RmmH hexamers in vitro. Based on the dimensions of the nanotubes and modeling of the RmmH hexamer, we propose two possible structural models. BMC nanotubes offer a new spatial architecture both in vivo and in vitro, composed of a single protein that may be genetically or chemically modified and for use as tubular scaffolding.

36 MATERIALS SCIENCE↗
DOE OSTI2022

RNAseq-based transcriptome assembly of Clostridium acetobutylicum for functional genome annotation and discovery

Accurate genome annotations are essential in modern biology and biotechnology, yet they are still largely based on genome sequencing and comparative analyses. We show that the Clostridium acetobutylicum genome annotation can be markedly improved by integrating bioinformatic predictions with RNA sequencing (RNAseq) data. Samples were acquired under butanol, butyrate, and unstressed treatments across various growth conditions. Analysis of an initial assembly revealed errors due to background signals and limitations of assembly algorithms. Hurdles for RNAseq transcriptome mapping include optimizing library complexity and sequencing depth, yet most studies report low sequencing depth and ignore the effect of ribosomal RNA abundance. An integrative analysis was developed to combine motif predictions, single-nucleotide resolution sequencing depth, and library complexity to resolve difficulties in assembly curation. This minimized false positive error and determined gene boundaries, in some cases, to the exact base-pair of prior studies. This will be the first strand-specific transcriptome assembly in a Clostridium organism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Macrocyclic β‐Sheets Stabilized by Hydrogen Bond Surrogates

Abstract Mimics of protein secondary and tertiary structure offer rationally‐designed inhibitors of biomolecular interactions. β‐Sheet mimics have a storied history in bioorganic chemistry and are typically designed with synthetic or natural turn segments. We hypothesized that replacement of terminal inter‐β‐strand hydrogen bonds with hydrogen bond surrogates (HBS) may lead to conformationally‐defined macrocyclic β‐sheets without the requirement for natural or synthetic β‐turns, thereby providing a minimal mimic of a protein β‐sheet. To access turn‐less antiparallel β‐sheet mimics, we developed a facile solid phase synthesis protocol. We surveyed a dataset of protein β‐sheets for naturally observed interstrand side chain interactions. This bioinformatics survey highlighted an over‐abundance of aromatic–aromatic, cation‐π and ionic interactions in β‐sheets. In correspondence with natural β‐sheets, we find that minimal HBS mimics show robust β‐sheet formation when specific amino acid residue pairings are incorporated. In isolated β‐sheets, aromatic interactions endow superior conformational stability over ionic or cation‐π interactions. Circular dichroism and NMR spectroscopies, along with high‐resolution X‐ray crystallography, support our design principles.

Chemistry↗
DOE OSTI2022

An idea to explore: How an interdisciplinary undergraduate course exploring a global health challenge in molecular detail enabled science communication and collaboration in diverse audiences

Abstract Communication and collaboration are key science competencies that support sharing of scientific knowledge with experts and non‐experts alike. On the one hand, they facilitate interdisciplinary conversations between students, educators, and researchers, while on the other they improve public awareness, enable informed choices, and impact policy decisions. Herein, we describe an interdisciplinary undergraduate course focused on using data from various bioinformatics data resources to explore the molecular underpinnings of diabetes mellitus (Types 1 and 2) and introducing students to science communication. Building on course materials and original student‐generated artifacts, a series of collaborative activities engaged students, educators, researchers, healthcare professionals and community members in exploring, learning about, and discussing the molecular bases of diabetes. These collaborations generated novel educational materials and approaches to learning and presenting complex ideas about major global health challenges in formats accessible to diverse audiences.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Using MbtH-Like Proteins to Alter the Substrate Profile of a Nonribosomal Peptide Adenylation Enzyme

MbtH-like proteins (MLPs) are required for soluble expression and/or optimal activity of some adenylation (A) domains of nonribosomal peptide synthetases (NRPSs). Since A domains can interact with noncognate MLP partners, we investigated how the function of an A domain, TioK, involved in the biosynthesis of the bisintercalator thiocoraline, is altered by noncognate MLPs. Measuring TioK activity with 12 different MLPs from a variety of bacterial species using a radiometric assay suggested that the A domain substrate promiscuity could be altered by foreign MLPs. Kinetic studies and bioinformatics analysis indicated that MLPs’ functions are not as simple as previously thought.

antibiotics, synthethic biology, non-ribosomal pep↗
DOE OSTI2023

Structures and Mechanisms of a Novel Bacterial Transport System for Fatty Acids

Abstract Bacterial acquisition of metabolites is largely facilitated by transporters with unique substrate scopes. The tripartite ATP‐independent periplasmic (TRAP) transporters comprise a large family of bacterial proteins that facilitate the uptake of a variety of small molecules. It has been reported that some TRAP systems encode a fourth protein, the T component. The T‐component, or TatT, is predicted to be a periplasmic‐facing lipoprotein that enables the uptake of metabolites from the outer membrane. However, no substrates were revealed for any TatT and their functional role(s) remained enigmatic. We recently identified a homolog in Methylococcus capsulatus that binds to sterols, and herein, we report two additional homologs that demonstrate a preference for long‐chain fatty acids. Our bioinformatics, quantitative analyses of protein‐ligand interactions, and high‐resolution crystal structures suggest that TatTs might facilitate the trafficking of hydrophobic or lipophilic substrates and represent a new class of bacterial lipid and fatty acid transporters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Using KBase to Assemble and Annotate Prokaryotic Genomes

The DOE Systems Biology Knowledgebase is an open–access bioinformatics software and data platform for analyzing plants, microbes, and their communities. KBase enables scientists to create, execute, collaborate on, and share reproducible analyses of their biological data in the context of public data and private collaborator data. For microbiologists researching prokaryotes, KBase offers analysis tools for performing quality control and assessment of Next–Generation Sequencing reads, de novo assembly, genome annotation, and tools for analyzing structural and functional features of genomes. As a result, this unit demonstrates an example workflow for taking a comparative and iterative approach to assembly and annotation of prokaryotic genomes using KBase that can be used by microbiologists seeking to perform isolate analysis in a rapid and reproducible fashion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Isolation and Whole-Genome Sequencing of Environmental Campylobacter

As a leading cause of bacterial-derived gastroenteritis worldwide, Campylobacter has a significant impact on human health. In the developed world, most campylobacteriosis cases are attributed to the consumption of undercooked, contaminated poultry; however, it has been shown that Campylobacter can be transmitted to humans through contaminated water and other types of food, including beef and milk. As such, high-resolution microbial source-tracking is essential for health department officials to determine the source(s) of Campylobacter outbreaks. For these reasons, this paper provides the techniques needed for isolation of Campylobacter from agricultural and environmental sources, as well as human clinical specimens. Additionally, we describe a simple method for preparing high-quality genomic DNA that can be used for whole-genome sequencing and downstream bioinformatics analyses of Campylobacter genotypes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Screening for High Conductivity/Low Viscosity Ionic Liquids Using Product Descriptors

We seek to optimize Ionic liquids (ILs) for application to redox flow batteries. As part of this effort, we have developed a computational method for suggesting ILs with high conductivity and low viscosity. Since ILs consist of cation-anion pairs, we consider a method for treating ILs as pairs using product descriptors for QSPRs, a concept borrowed from the prediction of protein-protein interactions in bioinformatics. We demonstrate the method by predicting electrical conductivity, viscosity, and melting point on a dataset taken from the ILThermo database on June 18th, 2014. The dataset consists of 4,329 measurements taken from 165 ILs made up of 72 cations and 34 anions. In conclusion, we benchmark our QSPRs on the known values in the dataset then extend our predictions to screen all 2,448 possible cation-anion pairs in the dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Identification and preliminary characterization of conserved uncharacterized proteins from Chlamydomonas reinhardtii , Arabidopsis thaliana , and Setaria viridis

Abstract The rapid accumulation of sequenced plant genomes in the past decade has outpaced the still difficult problem of genome‐wide protein‐coding gene annotation. A substantial fraction of protein‐coding genes in all plant genomes are poorly annotated or unannotated and remain functionally uncharacterized. We identified unannotated proteins in three model organisms representing distinct branches of the green lineage (Viridiplantae): Arabidopsis thaliana (eudicot), Setaria viridis (monocot), and Chlamydomonas reinhardtii (Chlorophyte alga). Using similarity searching, we identified a subset of unannotated proteins that were conserved between these species and defined them as Deep Green proteins. Bioinformatic, genomic, and structural predictions were performed to begin classifying Deep Green genes and proteins. Compared to whole proteomes for each species, the Deep Green set was enriched for proteins with predicted chloroplast targeting signals predictive of photosynthetic or plastid functions, a result that was consistent with enrichment for daylight phase diurnal expression patterning. Structural predictions using AlphaFold and comparisons to known structures showed that a significant proportion of Deep Green proteins may possess novel folds. Though only available for three organisms, the Deep Green genes and proteins provide a starting resource of high‐value targets for further investigation of potentially new protein structures and functions conserved across the green lineage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Microbial community proteomics for characterizing the range of metabolic functions and activities of human gut microbiota

We found that the human gastrointestinal (GI) tract is a complex, dynamic ecosystem that consists of a carefully tuned balance of human host and microbiota membership. The microbiome component is not insignificant, but rather provides important functions that are absolutely critical to many aspects of human health, including nutrient transformation and absorption, drug metabolism, pathogen defense, and immune system development. Microbial community proteomics (sometimes referred to as metaproteomics) provides a powerful approach to measure the range and details of human gut microbiota functions and metabolic activities, revealing information about microbiome development and stability especially with regard to human health vs. disease states. In most cases, both microbial and human proteins are extracted from fecal samples and then measured by the high performance MS-based proteomics technology. We review the field of human gut microbiome community proteomics, with a focus on the experimental and informatics considerations involved in characterizing systems that range from low complexity defined model gut microbiota in gnotobiotic mice, to the simple gut microbiota in the GI tract of newborn infants, and finally to the complex gut microbiota in adults. Moreover, the current state-of-the-art in experimental and bioinformatics capabilities for community proteomics enable a detailed measurement of the gut microbiota, yielding valuable insights into the broad functional profiles of even complex microbiota. Future developments are likely to expand into improved analysis throughput and coverage depth, as well as post-translational modification characterizations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Challenges and Opportunities in State‐of‐the‐Art Proteomics Analysis for Biomarker Development From Plasma Extracellular Vesicles

Extracellular vesicles (EVs) are membrane-bound particles secreted by cells, playing crucial roles in intercellular communication. The composition of EVs can undergo changes in response to stress and disease conditions, making them excellent biomarker candidates. However, extracting protein information from EVs can be challenging due to their low abundance in complex biofluids and copurification with contaminant proteins and particles. Techniques to enrich EVs have their strengths and limitations, without one being able to purify EVs to complete homogeneity. This can lead to compromised recovery rates and increased complexity, making data interpretation difficult. In this viewpoint article, we explore the concept that better characterization of EV composition, followed by quantification of EV proteins in complex samples, might be a more viable route for biomarker development. Mass spectrometers can provide reproducible deep coverage of the EV proteome, despite sample impurities. This paradigm shift presents opportunities to integrate advanced bioinformatics tools to refine the EV proteome landscape, identify novel biomarkers, and streamline validation processes in biomarker development. By focusing on leveraging technology rather than achieving absolute purity, this approach can transform current practices and open opportunities for robust biomarker discovery. Herein, we highlight not only such opportunities but also challenges to implement this concept.

Dakup, Panshak P. [Pacific Northwest National Labo↗