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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Marine Microeukaryote Metatranscriptomics: Sample Processing and Bioinformatic Workflow Recommendations for Ecological Applications

Microeukaryotes (protists) serve fundamental roles in the marine environment as contributors to biogeochemical nutrient cycling and ecosystem function. Their activities can be inferred through metatranscriptomic investigations, which provide a detailed view into cellular processes, chemical-biological interactions in the environment, and ecological relationships among taxonomic groups. Established workflows have been individually put forth describing biomass collection at sea, laboratory RNA extraction protocols, and bioinformatic processing and computational approaches. Here, we present a compilation of current practices and lessons learned in carrying out metatranscriptomics of marine pelagic protistan communities, highlighting effective strategies and tools used by practitioners over the past decade. We anticipate that these guidelines will serve as a roadmap for new marine scientists beginning in the realms of molecular biology and/or bioinformatics, and will equip readers with foundational principles needed to delve into protistan metatranscriptomics.

Cohen, Natalie R.↗
DOE OSTI2021

Bioinformatics Investigations of Universal Stress Proteins from Mercury-Methylating Desulfovibrionaceae

The presence of methylmercury in aquatic environments and marine food sources is of global concern. The chemical reaction for the addition of a methyl group to inorganic mercury occurs in diverse bacterial taxonomic groups including the Gram-negative, sulfate-reducing Desulfovibrionaceae family that inhabit extreme aquatic environments. The availability of whole-genome sequence datasets for members of the Desulfovibrionaceae presents opportunities to understand the microbial mechanisms that contribute to methylmercury production in extreme aquatic environments. We have applied bioinformatics resources and developed visual analytics resources to categorize a collection of 719 putative universal stress protein (USP) sequences predicted from 93 genomes of Desulfovibrionaceae. We have focused our bioinformatics investigations on protein sequence analytics by developing interactive visualizations to categorize Desulfovibrionaceae universal stress proteins by protein domain composition and functionally important amino acids. We identified 651 Desulfovibrionaceae universal stress protein sequences, of which 488 sequences had only one USP domain and 163 had two USP domains. The 488 single USP domain sequences were further categorized into 340 sequences with ATP-binding motif and 148 sequences without ATP-binding motif. The 163 double USP domain sequences were categorized into (1) both USP domains with ATP-binding motif (3 sequences); (2) both USP domains without ATP-binding motif (138 sequences); and (3) one USP domain with ATP-binding motif (21 sequences). We developed visual analytics resources to facilitate the investigation of these categories of datasets in the presence or absence of the mercury-methylating gene pair (hgcAB). Future research could utilize these functional categories to investigate the participation of universal stress proteins in the bacterial cellular uptake of inorganic mercury and methylmercury production, especially in anaerobic aquatic environments.

Isokpehi, Raphael D. (ORCID:0000000268770840)↗
DOE OSTI2022

Benchmark datasets for SARS-CoV-2 surveillance bioinformatics

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), has spread globally and is being surveilled with an international genome sequencing effort. Surveillance consists of sample acquisition, library preparation, and whole genome sequencing. This has necessitated a classification scheme detailing Variants of Concern (VOC) and Variants of Interest (VOI), and the rapid expansion of bioinformatics tools for sequence analysis. These bioinformatic tools are means for major actionable results: maintaining quality assurance and checks, defining population structure, performing genomic epidemiology, and inferring lineage to allow reliable and actionable identification and classification. Additionally, the pandemic has required public health laboratories to reach high throughput proficiency in sequencing library preparation and downstream data analysis rapidly. However, both processes can be limited by a lack of a standardized sequence dataset. We identified six SARS-CoV-2 sequence datasets from recent publications, public databases and internal resources. In addition, we created a method to mine public databases to identify representative genomes for these datasets. Using this novel method, we identified several genomes as either VOI/VOC representatives or non-VOI/VOC representatives. To describe each dataset, we utilized a previously published datasets format, which describes accession information and whole dataset information. Additionally, a script from the same publication has been enhanced to download and verify all data from this study.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2006

Bioinformatics for Exploration

For the purpose of this paper, bioinformatics is defined as the application of computer technology to the management of biological information. It can be thought of as the science of developing computer databases and algorithms to facilitate and expedite biological research. This is a crosscutting capability that supports nearly all human health areas ranging from computational modeling, to pharmacodynamics research projects, to decision support systems within autonomous medical care. Bioinformatics serves to increase the efficiency and effectiveness of the life sciences research program. It provides data, information, and knowledge capture which further supports management of the bioastronautics research roadmap - identifying gaps that still remain and enabling the determination of which risks have been addressed.

Johnson, Kathy A.↗
NASA NTRS2006

A Bioinformatics Facility for NASA

Building on an existing prototype, we have fielded a facility with bioinformatics technologies that will help NASA meet its unique requirements for biological research. This facility consists of a cluster of computers capable of performing computationally intensive tasks, software tools, databases and knowledge management systems. Novel computational technologies for analyzing and integrating new biological data and already existing knowledge have been developed. With continued development and support, the facility will fulfill strategic NASA s bioinformatics needs in astrobiology and space exploration. . As a demonstration of these capabilities, we will present a detailed analysis of how spaceflight factors impact gene expression in the liver and kidney for mice flown aboard shuttle flight STS-108. We have found that many genes involved in signal transduction, cell cycle, and development respond to changes in microgravity, but that most metabolic pathways appear unchanged.

Schweighofer, Karl↗
DOE OSTI2017

Enabling the democratization of the genomics revolution with a fully integrated web-based bioinformatics platform, Version 1.5 and 1.x.

EDGE bioinformatics was developed to help biologists process Next Generation Sequencing data (in the form of raw FASTQ files), even if they have little to no bioinformatics expertise. EDGE is a highly integrated and interactive web-based platform that is capable of running many of the standard analyses that biologists require for viral, bacterial/archaeal, and metagenomic samples. EDGE provides the following analytical workflows: quality trimming and host removal, assembly and annotation, comparisons against known references, taxonomy classification of reads and contigs, whole genome SNP-based phylogenetic analysis, and PCR analysis. EDGE provides an intuitive web-based interface for user input, allows users to visualize and interact with selected results (e.g. JBrowse genome browser), and generates a final detailed PDF report. Results in the form of tables, text files, graphic files, and PDFs can be downloaded. A user management system allows tracking of an individual’s EDGE runs, along with the ability to share, post publicly, delete, or archive their results.

Chain, Patrick↗
DOE OSTI2019

EDGE Bioinformatics

This report gives an overview of Empowering the Development of Genomics Expertise (EDGE) Bioinformatics software.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2006

Robust Bioinformatics Recognition with VLSI Biochip Microsystem

A microsystem architecture for real-time, on-site, robust bioinformatic patterns recognition and analysis has been proposed. This system is compatible with on-chip DNA analysis means such as polymerase chain reaction (PCR)amplification. A corresponding novel artificial neural network (ANN) learning algorithm using new sigmoid-logarithmic transfer function based on error backpropagation (EBP) algorithm is invented. Our results show the trained new ANN can recognize low fluorescence patterns better than the conventional sigmoidal ANN does. A differential logarithmic imaging chip is designed for calculating logarithm of relative intensities of fluorescence signals. The single-rail logarithmic circuit and a prototype ANN chip are designed, fabricated and characterized.

bioinformatics↗
DOE OSTI2015

Bioinformatic analysis of neurotropic HIV envelope sequences identifies polymorphisms in the gp120 bridging sheet that increase macrophage-tropism through enhanced interactions with CCR5

Macrophages express low levels of the CD4 receptor compared to T-cells. Macrophage-tropic HIV strains replicating in brain of untreated patients with HIV-associated dementia (HAD) express Envs that are adapted to overcome this restriction through mechanisms that are poorly understood. Here, bioinformatic analysis of env sequence datasets together with functional studies identified polymorphisms in the β3 strand of the HIV gp120 bridging sheet that increase M-tropism. D197, which results in loss of an N-glycan located near the HIV Env trimer apex, was detected in brain in some HAD patients, while position 200 was estimated to be under positive selection. D197 and T/V200 increased fusion and infection of cells expressing low CD4 by enhancing gp120 binding to CCR5. These results identify polymorphisms in the HIV gp120 bridging sheet that overcome the restriction to macrophage infection imposed by low CD4 through enhanced gp120–CCR5 interactions, thereby promoting infection of brain and other macrophage-rich tissues. - Highlights: • We analyze HIV Env sequences and identify amino acids in beta 3 of the gp120 bridging sheet that enhance macrophage tropism. • These amino acids at positions 197 and 200 are present in brain of some patients with HIV-associated dementia. • D197 results in loss of a glycan near the HIV Env trimer apex, which may increase exposure of V3. • These variants may promote infection of macrophages in the brain by enhancing gp120–CCR5 interactions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

The CopC Family: Structural and Bioinformatic Insights into a Diverse Group of Periplasmic Copper Binding Proteins

The CopC proteins are periplasmic copper binding proteins believed to play a role in bacterial copper homeostasis. Previous studies have focused on CopCs that are part of seven-protein Cop or Pco systems involved in copper resistance. These canonical CopCs contain distinct Cu(I) and Cu(II) binding sites. Mounting evidence suggests that CopCs are more widely distributed, often present only with the CopD inner membrane protein, frequently as a fusion protein, and that the CopC and CopD proteins together function in the uptake of copper to the cytoplasm. In the methanotroph Methylosinus trichosporium OB3b, genes encoding a CopCD pair are located adjacent to the particulate methane monooxygenase (pMMO) operon. The CopC from this organism (Mst-CopC) was expressed, purified, and structurally characterized. The 1.46 Å resolution crystal structure of Mst-CopC reveals a single Cu(II) binding site with coordination somewhat different from that in canonical CopCs, and the absence of a Cu(I) binding site. Furthermore, extensive bioinformatic analyses indicate that the majority of CopCs in fact contain only a Cu(II) site, with just 10% of sequences corresponding to the canonical two-site CopC. Accordingly, a new classification scheme for CopCs was developed, and detailed analyses of the sequences and their genomic neighborhoods reveal new proteins potentially involved in copper homeostasis, providing a framework for expanded models of CopCD function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Bioinformatic Discovery of a Cambialistic Monooxygenase

Dinuclear monooxygenases mediate challenging C–H bond oxidation reactions throughout nature. Many of these enzymes are presumed to exclusively utilize diiron cofactors. Herein we report the bioinformatic discovery of an orphan dinuclear monooxygenase that preferentially utilizes a heterobimetallic manganese–iron (Mn/Fe) cofactor to mediate an O 2 -dependent C–H bond hydroxylation reaction. Unlike the structurally similar Mn/Fe-dependent monooxygenase AibH2, the diiron form of this enzyme (SfbO) exhibits a nascent enzymatic activity. This behavior raises the possibility that many other dinuclear monooxygenases may be endowed with the capacity to harness cofactors with a variable metal content.

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

Bioinformatics of cyanophycin metabolism genes and characterization of promiscuous isoaspartyl dipeptidases that catalyze the final step of cyanophycin degradation

Cyanophycin is a bacterial biopolymer used for storage of fixed nitrogen. It is composed of a backbone of L-aspartate residues with L-arginines attached to each of their side chains. Cyanophycin is produced by cyanophycin synthetase 1 (CphA1) using Arg, Asp and ATP, and is degraded in two steps. First, cyanophycinase breaks down the backbone peptide bonds, releasing β-Asp-Arg dipeptides. Then, these dipeptides are broken down into free Asp and Arg by enzymes with isoaspartyl dipeptidase activity. Two bacterial enzymes are known to possess promiscuous isoaspartyl dipeptidase activity: isoaspartyl dipeptidase (IadA) and isoaspartyl aminopeptidase (IaaA). We performed a bioinformatic analysis to investigate whether genes for cyanophycin metabolism enzymes cluster together or are spread around the microbial genomes. Many genomes showed incomplete contingents of known cyanophycin metabolizing genes, with different patterns in various bacterial clades. Cyanophycin synthetase and cyanophycinase are usually clustered together when recognizable genes for each are found within a genome. Cyanophycinase and isoaspartyl dipeptidase genes typically cluster within genomes lacking cphA1. About one-third of genomes with genes for CphA1, cyanophycinase and IaaA show these genes clustered together, while the proportion is around one-sixth for CphA1, cyanophycinase and IadA. We used X-ray crystallography and biochemical studies to characterize an IadA and an IaaA from two such clusters, in Leucothrix mucor and Roseivivax halodurans, respectively. The enzymes retained their promiscuous nature, showing that being associated with cyanophycin-related genes did not make them specific for β-Asp-Arg dipeptides derived from cyanophycin degradation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Bioinformatics-aided identification, characterization and applications of mushroom linalool synthases

Enzymes empower chemical industries and are the keystone for metabolic engineering. For example, linalool synthases are indispensable for the biosynthesis of linalool, an important fragrance used in 60–80% cosmetic and personal care products. However, plant linalool synthases have low activities while expressed in microbes. Aided by bioinformatics analysis, four linalool/nerolidol synthases (LNSs) from various Agaricomycetes were accurately predicted and validated experimentally. Furthermore, we discovered a linalool synthase (Ap.LS) with exceptionally high levels of selectivity and activity from Agrocybe pediades, ideal for linalool bioproduction. It effectively converted glucose into enantiopure (R)-linalool in Escherichia coli, 44-fold and 287-fold more efficient than its bacterial and plant counterparts, respectively. Phylogenetic analysis indicated the divergent evolution paths for plant, bacterial and fungal linalool synthases. More critically, structural comparison provided catalytic insights into Ap.LS superior specificity and activity, and mutational experiments validated the key residues responsible for the specificity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

PYK-SubstitutionOME: an integrated database containing allosteric coupling, ligand affinity and mutational, structural, pathological, bioinformatic and computational information about pyruvate kinase isozymes

Interpreting changes in patient genomes, understanding how viruses evolve and engineering novel protein function all depend on accurately predicting the functional outcomes that arise from amino acid substitutions. To that end, the development of first-generation prediction algorithms was guided by historic experimental datasets. However, these datasets were heavily biased toward substitutions at positions that have not changed much throughout evolution (i.e. conserved). Although newer datasets include substitutions at positions that span a range of evolutionary conservation scores, these data are largely derived from assays that agglomerate multiple aspects of function. To facilitate predictions from the foundational chemical properties of proteins, large substitution databases with biochemical characterizations of function are needed. We report here a database derived from mutational, biochemical, bioinformatic, structural, pathological and computational studies of a highly studied protein family—pyruvate kinase (PYK). A centerpiece of this database is the biochemical characterization—including quantitative evaluation of allosteric regulation—of the changes that accompany substitutions at positions that sample the full conservation range observed in the PYK family. We have used these data to facilitate critical advances in the foundational studies of allosteric regulation and protein evolution and as rigorous benchmarks for testing protein predictions. We trust that the collected dataset will be useful for the broader scientific community in the further development of prediction algorithms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

β-Carboxysome bioinformatics: identification and evolution of new bacterial microcompartment protein gene classes and core locus constraints

Carboxysomes are bacterial microcompartments (BMCs) that enhance CO 2 fixation in all cyanobacteria. Structurally, carboxysome shell proteins are classified according to the type of oligomer formed: hexameric (BMC-H), trimeric (BMC-T) and pentameric (BMC-P) proteins. To understand the forces driving the evolution of the carboxysome shell, we conducted a bioinformatic study of genes encoding β-carboxysome shell proteins, taking advantage of the recent large increase in sequenced cyanobacterial genomes. In addition to the four well-established BMC-H (CcmK1-4) classes, our analysis reveals two new CcmK classes, which we name CcmK5 and CcmK6. CcmK5 is phylogenetically closest to CcmK3 and CcmK4, and the ccmK5 gene is found only in genomes lacking ccmK3 and ccmk4 genes. ccmK6 is found predominantly in heterocyst-forming cyanobacteria. The gene encoding the BMC-T homolog CcmO is associated with the main carboxysome locus (MCL) in only 60% of all species. We find five evolutionary origins of separation of ccmO from the MCL. Transcriptome analysis demonstrates that satellite ccmO genes, in contrast to MCL-associated ccmO genes, are never co-regulated with other MCL genes. The dispersal of carboxysome shell genes across the genome allows for distinct regulation of their expression, perhaps in response to changes in environmental conditions

regulation↗
DOE OSTI2013

PATRIC, the bacterial bioinformatics database and analysis resource

The Pathosystems Resource Integration Center (PATRIC) is the all-bacterial Bioinformatics Resource Center (BRC) (http://www.patricbrc.org). A joint effort by two of the original National Institute of Allergy and Infectious Diseases-funded BRCs, PATRIC provides researchers with an online resource that stores and integrates a variety of data types [e.g. genomics, transcriptomics, protein– protein interactions (PPIs), three-dimensional protein structures and sequence typing data] and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes in PATRIC, currently more than 10 000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. All the data and integrated analysis and visualization tools are freely available. This manuscript describes updates to the PATRIC since its initial report in the 2007 NAR Database Issue.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center

Here, the Pathosystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center. Recent changes to PATRIC include a redesign of the web interface and some new services that provide users with a platform that takes them from raw reads to an integrated analysis experience. The redesigned interface allows researchers direct access to tools and data, and the emphasis has changed to user-created genome-groups, with detailed summaries and views of the data that researchers have selected. Perhaps the biggest change has been the enhanced capability for researchers to analyze their private data and compare it to the available public data. Researchers can assemble their raw sequence reads and annotate the contigs using RASTtk. PATRIC also provides services for RNA-Seq, variation, model reconstruction and differential expression analysis, all delivered through an updated private workspace. Private data can be compared by `virtual integration' to any of PATRIC's public data. The number of genomes available for comparison in PATRIC has expanded to over 80 000, with a special emphasis on genomes with antimicrobial resistance data. PATRIC uses this data to improve both subsystem annotation and k-mer classification, and tags new genomes as having signatures that indicate susceptibility or resistance to specific antibiotics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Bioinformatics and 3D Structural Analysis of the Coronavirus Main Protease Active Site Diversity

Coronaviruses (Coronaviridae) such as SARS‐CoV‐2 (severe acute respiratory syndrome coronavirus) and MERS‐CoV (Middle East respiratory syndrome coronavirus) have been the source of recent outbreaks and global health concerns. While vaccines have been essential for controlling the SARS‐CoV‐2 (COVID‐19) pandemic, it is uncertain whether they will be effective against future coronavirus strains. Therefore, identification or design of a broad‐spectrum drug that targets highly conserved regions of the main protease of multiple coronavirus strains is essential in the long term. As part of a virtual summer research experience with the RCSB PDB, bioinformatics tools were employed to predict and construct 3D models of the coronavirus main protease (MPro) using SARS‐CoV‐2 as the template, with a focus on mutational trends and active sites. This study focused on the active sites of MPro, a cysteine protease essential for viral assembly and replication. Sequence alignments and structure modeling of MPro structures has identified conserved regions across multiple coronavirus strains. Inhibition of MPro halts coronavirus replication, making it an ideal drug target, and studies of MPro may foster and accelerate the discovery of high affinity broad‐spectrum drugs.

Wu Wu, Amy↗