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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Assembly-Driven Community Genomics of a Hypersaline Microbial Ecosystem

Microbial populations inhabiting a natural hypersaline lake ecosystem in Lake Tyrrell, Victoria, Australia, have been characterized using deep metagenomic sampling, iterative de novo assembly, and multidimensional phylogenetic binning. Composite genomes representing habitat-specific microbial populations were reconstructed for eleven different archaea and one bacterium, comprising between 0.6 and 14.1% of the planktonic community. Eight of the eleven archaeal genomes were from microbial species without previously cultured representatives. These new genomes provide habitat-specific reference sequences enabling detailed, lineage-specific compartmentalization of predicted functional capabilities and cellular properties associated with both dominant and less abundant community members, including organisms previously known only by their 16S rRNA sequences. Together, these data provide a comprehensive, culture-independent genomic blueprint for ecosystem-wide analysis of protein functions, population structure, and lifestyles of co-existing, co-evolving microbial groups within the same natural habitat. The ‘‘assembly-driven’’ community genomic approach demonstrated in this study advances our ability to push beyond single gene investigations, and promotes genome-scale reconstructions as a tangible goal in the quest to define the metabolic, ecological, and evolutionary dynamics that underpin environmental microbial diversity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

New In Situ Imaging and Measurement Technologies for Biological Systems (Brochure)

The U.S. Department of Energy’s (DOE) Office of Biological and Environmental Research (BER) supports fundamental research to advance a predictive understanding of complex biological and environmental systems relevant to DOE’s missions in energy and the environment. Starting with the genetic potential encoded by organisms’ genomes, BER scientists seek to define the principles guiding translation of the genetic code into functional proteins and the metabolic and regulatory networks underlying plant and microbial systems. Concurrent with this research is a need for enabling technologies to place understanding of gene expression, regulation, and function into the spatiotemporal context of whole-cell environments. Imaging and measurement technologies that can resolve multiple key metabolic processes over time within or among cells will act as a crucial bridge toward linking molecular-scale information to whole-cell, systems-level understanding. This brochure outlines the pilot projects at the DOE national laboratories and the investigators leading these efforts. This initial description of BER’s new effort serves as an informational resource for the evolving imaging and measurement technology program.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Identifying RNA contacts from SHAPE-MaP by partial correlation analysis

In a recent paper Siegfried et al. published a new sequence-based structural RNA assay that utilizes mutational profiling to detect base pairing (MaP). Output from MaP provides information about both pairing (via reactivities) and contact (via correlations). Reactivities can be coupled to partition function folding models for structural inference, while correlations can reveal pairs of sites that may be in structural proximity. The possibility for inference of 3D contacts via MaP suggests a novel approach to structural prediction for RNA analogous to covariance structural prediction for proteins. We explore this approach and show that partial correlation analysis outperforms na\"ive correlation analysis. Our results should be applicable to a wide range of high-throughput sequencing based RNA structural assays that are under development.

Tambe, Akshay↗
DOE OSTI2024

Rational Design of Novel Biomimetic Sequence-Defined Polymers for Mineralization Applications

Silica biomineralization is a naturally occurring process, wherein organisms use proteins and other biological structures to direct the formation of complex, hierarchical nanostructures. Discovery and characterization of such proteins and their underlying mechanisms spurred significant efforts to identify routes for biomimetic mineralization that reproduce the exquisite shapes and size selectivities found in nature. A common strategy has been the use of short peptide sequences with chemistry mimicking those found in natural systems, such as the use of the silaffin-derived R5 peptide. While progress has been made using this approach, there are many limitations that have prevented breakthroughs in biomimicry. To advance our ability to use charged macromolecules for silica formation, we propose to use sequence-defined synthetic polymers known as peptoids, or N-substituted polyglycines, which present significant capability for the precise tuning of sequence and structure beyond what can often be achieved with peptides alone. This study presents a computationally predicted design of these polymers that leads to the controlled formation of silica nanomaterials. We investigate surface adsorption and the mineralization process through analysis of binding mechanisms and energetics of the R5 system. Next, we synthesized two R5-inspired peptoids and validated our prediction in the design of mineralization polymers through characterization using surface plasmon resonance and electron microscopy. Here, this computationally guided study holds great promise for designing new sequences with unprecedented control of the placement of chemical functional groups, thus allowing for further unraveling of silicification mechanisms and the eventual design of sequence-defined synthetic polymers leading to the predictive synthesis of nanostructured functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

LncRNA HAND2-AS1 sponging miR-1275 suppresses colorectal cancer progression by upregulating KLF14

Long noncoding RNAs (lncRNAs) represent a novel type of noncoding RNAs of over 200 nucleotides, characterized by no or limited protein-coding potential. Although the function of lncRNAs attracts increasing attention recently, the relationship between lncRNA and colorectal cancer (CRC) remains further investigation. In our study, we found that lncRNA HAND2-AS1 was markedly downregulated in CRC tissues. And its expression level was negatively correlated with metastasis and advanced stage in CRC patients. Furthermore, we showed that HAND2-AS1 low expression predicted poor prognosis. Functionally, we found that overexpression of HAND2-AS1 obviously attenuated the proliferation and invasion of CRC cells. Ectopic expression of HAND2-AS1 also inhibited tumor propagation in vivo. In mechanism, HAND2-AS1 served as a sponge of miR-1275 which targeted KLF14. Through facilitating KLF14 expression, HAND2-AS1 suppressed CRC progression. In conclusion, our study demonstrated that HAND2-AS1 exerts a suppressive role in CRC by sponging miR-1275 and modulating KLF14 expression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters

Abstract With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Short-wavelength-sensitive 2 (Sws2) visual photopigment models combined with atomistic molecular simulations to predict spectral peaks of absorbance

For many species, vision is one of the most important sensory modalities for mediating essential tasks that include navigation, predation and foraging, predator avoidance, and numerous social behaviors. The vertebrate visual process begins when photons of the light interact with rod and cone photoreceptors that are present in the neural retina. Vertebrate visual photopigments are housed within these photoreceptor cells and are sensitive to a wide range of wavelengths that peak within the light spectrum, the latter of which is a function of the type of chromophore used and how it interacts with specific amino acid residues found within the opsin protein sequence. Minor differences in the amino acid sequences of the opsins are known to lead to large differences in the spectral peak of absorbance (i.e. the λ max value). In our prior studies, we developed a new approach that combined homology modeling and molecular dynamics simulations to gather structural information associated with chromophore conformation, then used it to generate statistical models for the accurate prediction of λ max values for photopigments derived from Rh1 and Rh2 amino acid sequences. In the present study, we test our novel approach to predict the λ max of phylogenetically distant Sws2 cone opsins. To build a model that can predict the λ max using our approach presented in our prior studies, we selected a spectrally-diverse set of 11 teleost Sws2 photopigments for which both amino acid sequence information and experimentally measured λ max values are known. The final first-order regression model, consisting of three terms associated with chromophore conformation, was sufficient to predict the λ max of Sws2 photopigments with high accuracy. This study further highlights the breadth of our approach in reliably predicting λ max values of Sws2 cone photopigments, evolutionary-more distant from template bovine RH1, and provided mechanistic insights into the role of known spectral tuning sites.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Genome Sizes and the Benford Distribution

Background: Data on the number of Open Reading Frames (ORFs) coded by genomes from the 3 domains of Life show the presence of some notable general features. These include essential differences between the Prokaryotes and Eukaryotes, with the number of ORFs growing linearly with total genome size for the former, but only logarithmically for the latter. Results: Simply by assuming that the (protein) coding and non-coding fractions of the genome must have different dynamics and that the non-coding fraction must be particularly versatile and therefore be controlled by a variety of (unspecified) probability distribution functions (pdf’s), we are able to predict that the number of ORFs for Eukaryotes follows a Benford distribution and must therefore have a specific logarithmic form. Using the data for the 1000+ genomes available to us in early 2010, we find that the Benford distribution provides excellent fits to the data over several orders of magnitude. Conclusions: In its linear regime the Benford distribution produces excellent fits to the Prokaryote data, while the full nonlinear form of the distribution similarly provides an excellent fit to the Eukaryote data. Furthermore, in their region of overlap the salient features are statistically congruent. This allows us to interpret the difference between Prokaryotes and Eukaryotes as the manifestation of the increased demand in the biological functions required for the larger Eukaryotes, to estimate some minimal genome sizes, and to predict a maximal Prokaryote genome size on the order of 8–12 megabase pairs. These results naturally allow a mathematical interpretation in terms of maximal entropy and, therefore, most efficient information transmission.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

De Novo Design of Molecular Recognition for Sequence Defined Polymers

The proposed research aims at developing a computational framework that allows the de novo design of sequence defined polymers for molecular recognition. This framework will include the prediction of the 1) accessible backbone conformational space in solution environments for small to medium polymer length and 2) how side chains of different size and functionality can be used to design convergent or divergent receptor configurations. A structural database inspired by the protein database will be build that can be used to construct larger scaffolds based on smaller sequences

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1986

RNA catalysis and the origins of life

The role of RNA catalysis in the origins of life is considered in connection with the discovery of riboszymes, which are RNA molecules that catalyze sequence-specific hydrolysis and transesterification reactions of RNA substrates. Due to this discovery, theories positing protein-free replication as preceding the appearance of the genetic code are more plausible. The scope of RNA catalysis in biology and chemistry is discussed, and it is noted that the development of methods to select (or predict) RNA sequences with preassigned catalytic functions would be a major contribution to the study of life's origins.

Orgel, Leslie E.↗
DOE OSTI2015

New Biomaging Technologies for Plant and Microbial Systems

The U.S. Department of Energy’s (DOE) Office of Biological and Environmental Research (BER) supports fundamental research to advance a predictive understanding of complex biological and environmental systems relevant to DOE’s missions in energy and the environment. Starting with the information encoded in organisms’ genomes, BER-funded scientists seek to define the principles guiding translation of the genetic code into functional proteins and the metabolic and regulatory networks underlying plant and microbial systems. Concurrent with this research is a need for enabling technologies to place understanding of gene expression, regulation, and function into the spatiotemporal context of whole-cell environments. Imaging and measurement technologies that can resolve multiple key metabolic processes over time within and among cells will act as a crucial bridge toward linking molecular-scale information to whole-cell, systems-level understanding. This brochure describes the current portfolio of projects and serves as an informational resource for BER’s new and evolving Bioimaging Technology program.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Structure and Function of the N-Terminal Domain of the Vesicular Stomatitis Virus RNA Polymerase

Viruses have various mechanisms to duplicate their genomes and produce virus-specific mRNAs. Negative-strand RNA viruses encode their own polymerases to perform each of these processes. For the nonsegmented negative-strand RNA viruses, the polymerase is comprised of the large polymerase subunit (L) and the phosphoprotein (P). L proteins from members of the Rhabdoviridae, Paramyxoviridae, and Filoviridae share sequence and predicted secondary structure homology. Here, we present the structure of the N-terminal domain (conserved region I) of the L protein from a rhabdovirus, vesicular stomatitis virus, at 1.8-Å resolution. The strictly and strongly conserved residues in this domain cluster in a single area of the protein. Serial mutation of these residues shows that many of the amino acids are essential for viral transcription but not for mRNA capping. Three-dimensional alignments show that this domain shares structural homology with polymerases from other viral families, including segmented negative-strand RNA and double-stranded RNA (dsRNA) viruses. Negative-strand RNA viruses include a diverse set of viral families that infect animals and plants, causing serious illness and economic impact. Furthermore, the members of this group of viruses share a set of functionally conserved proteins that are essential to their replication cycle. Among this set of proteins is the viral polymerase, which performs a unique set of reactions to produce genome- and subgenome-length RNA transcripts. In this article, we study the polymerase of vesicular stomatitis virus, a member of the rhabdoviruses, which has served in the past as a model to study negative-strand RNA virus replication. We have identified a site in the N-terminal domain of the polymerase that is essential to viral transcription and that shares sequence homology with members of the paramyxoviruses and the filoviruses. Newly identified sites such as that described here could prove to be useful targets in the design of new therapeutics against negative-strand RNA viruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

METABOLIC: high-throughput profiling of microbial genomes for functional traits, metabolism, biogeochemistry, and community-scale functional networks

Background Advances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent; however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and microbial contributions to biogeochemical cycling. Results We present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry studies using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the microbiome, potential microbial metabolic handoffs and metabolite exchange, reconstruction of functional networks, and determination of microbial contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, community-scale microbial functional networks using a newly defined metric “MW-score” (metabolic weight score), and metabolic Sankey diagrams. METABOLIC takes ~ 3 h with 40 CPU threads to process ~ 100 genomes and corresponding metagenomic reads within which the most compute-demanding part of hmmsearch takes ~ 45 min, while it takes ~ 5 h to complete hmmsearch for ~ 3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut. Conclusion METABOLIC enables the consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available under GPLv3 at https://github.com/AnantharamanLab/METABOLIC.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

The mechanism and function of circular RNAs in human diseases

Circular RNAs (circRNAs) are a recently discovered form of RNA. Initially, circRNAs were believed to result from errors during the process of gene transcription. However, after further investigation, scientists suggested that circRNAs are of great biological significance. CircRNAs show stability, conservation, abundance, and tissue and stage specificity. They can also function as miRNA sponges, regulate gene expression, and interact with proteins to affect cell behavior. Emerging evidence has also demonstrated that circRNAs participate or show abnormal expression in diseases, including central nervous system diseases, cardiovascular diseases and cancers, indicating their marked potential in the prediction and prognosis of diseases and clinical treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Characterization of Plasma Protein Alterations in Pregnant and Postpartum Individuals Living With HIV to Support Physiologically-Based Pharmacokinetic Model Development

Alterations in plasma protein concentrations in pregnant and postpartum individuals can influence antiretroviral (ARV) pharmacokinetics. Physiologically-based pharmacokinetic (PBPK) models can serve to inform drug dosing decisions in understudied populations. However, development of such models requires quantitative physiological information (e.g., changes in plasma protein concentration) from the population of interest. Objective: To quantitatively describe the time-course of albumin and α1-acid glycoprotein (AAG) concentrations in pregnant and postpartum women living with HIV. Serum and plasma protein concentrations procured from the International Maternal Pediatric Adolescent AIDS Clinical Trial Protocol 1026s (P1026s) were analyzed using a generalized additive modeling approach. Separate non-parametric smoothing splines were fit to albumin and AAG concentrations as functions of gestational age or postpartum duration. The analysis included 871 and 757 serum albumin concentrations collected from 380 pregnant (~20 to 42 wks gestation) and 354 postpartum (0 to 46 wks postpartum) women, respectively. Thirty-six and 32 plasma AAG concentrations from 31 pregnant (~24 to 38 wks gestation) and 30 postpartum women (~2–13 wks postpartum), respectively, were available for analysis. Estimated mean albumin concentrations remained stable from 20 wks gestation to term (33.4 to 34.3 g/L); whereas, concentrations rapidly increased postpartum until stabilizing at ~42.3 g/L 15 wk after delivery. Estimated AAG concentrations slightly decreased from 24 wks gestation to term (53.6 and 44.9 mg/dL) while postpartum levels were elevated at two wks after delivery (126.1 mg/dL) and subsequently declined thereafter. Computational functions were developed to quantitatively communicate study results in a form that can be readily utilized for PBPK model development. By characterizing the trajectory of plasma protein concentrations in pregnant and postpartum women living with HIV, our analysis can increase confidence in PBPK model predictions for HIV antiretrovirals and better inform drug dosing decisions in this understudied population.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MicroRNA-106a-5p facilitates human glioblastoma cell proliferation and invasion by targeting adenomatosis polyposis coli protein

The invasive behavior of glioblastoma multiforme (GBM) cells is an important reason for its poor prognosis. Tumor cells acquire an ability to digest the extracellular matrix and infiltrate the adjacent normal tissue during invasion. Restraining GBM invasion by changing effector molecules can significantly improve the patient's prognosis. MiRNAs are involved in multiple biological functions via suppressing target genes. In this study, we found that miR-106a-5p expression was high in GBM tissues and cells. The data showed an inverse correlation in GBM tissues between the levels of miR-106a-5p and adenomatosis polyposis coli (APC) mRNAs.Additionally, ectopic expression of miR-106a-5pfacilitated the invasion of GBM cells whereas inhibition of miR-106a-5p expression weakened the invasive ability. Numerous transcription factors are downstream effectors of the Wnt/β-catenin pathway. Target prediction databases and luciferase data showed that APC is a new direct target of miR-106a-5p. Importantly, westernblot assays demonstrated that miR-106a-5p can reduce APC protein level and enhance target proteins of Wnt/β-catenin pathway. Thus, we hypothesize that miR-106a-5p directly targets APC, resulting in the activation of Wnt/β-catenin pathway. Our results suggest that miR-106a-5p is involved in the invasive behavior of GBM cells and by targeting APC and activating Wnt/β-catenin pathway, it provides a theoretical basis for developing potential clinical strategies. - Highlights: • miR-106a-5p is upregulated in human glioblastoma. • Upregulation of miR-106a-5p promotes glioma cell proliferation and invasion. • miR-106a-5p inactivates the Wnt/β-catenin pathway by directly targeting APC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Structural basis for membrane targeting by the MVB12-associated [beta]-prism domain of the human ESCRT-I MVB12 subunit

MVB12-associated {beta}-prism (MABP) domains are predicted to occur in a diverse set of membrane-associated bacterial and eukaryotic proteins, but their existence, structure, and biochemical properties have not been characterized experimentally. Here, we find that the MABP domains of the MVB12A and B subunits of ESCRT-I are functional modules that bind in vitro to liposomes containing acidic lipids depending on negative charge density. The MABP domain is capable of autonomously localizing to subcellular puncta and to the plasma membrane. The 1.3-{angstrom} atomic resolution crystal structure of the MVB12B MABP domain reveals a {beta}-prism fold, a hydrophobic membrane-anchoring loop, and an electropositive phosphoinositide-binding patch. The basic patch is open, which explains how it senses negative charge density but lacks stereoselectivity. These observations show how ESCRT-I could act as a coincidence detector for acidic phospholipids and protein ligands, enabling it to function both in protein transport at endosomes and in cytokinesis and viral budding at the plasma membrane.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

PHANOTATE: a novel approach to gene identification in phage genomes

Motivation: Currently there are no tools specifically designed for annotating genes in phages. Several tools are available that have been adapted to run on phage genomes, but due to their underlying design, they are unable to capture the full complexity of phage genomes. Phages have adapted their genomes to be extremely compact, having adjacent genes that overlap and genes completely inside of other longer genes. This non-delineated genome structure makes it difficult for gene prediction using the currently available gene annotators. Here we present PHANOTATE, a novel method for gene calling specifically designed for phage genomes. Although the compact nature of genes in phages is a problem for current gene annotators, we exploit this property by treating a phage genome as a network of paths: where open reading frames are favorable, and overlaps and gaps are less favorable, but still possible. We represent this network of connections as a weighted graph, and use dynamic programing to find the optimal path. Results: We compare PHANOTATE to other gene callers by annotating a set of 2133 complete phage genomes from GenBank, using PHANOTATE and the three most popular gene callers. We found that the four programs agree on 82% of the total predicted genes, with PHANOTATE predicting more genes than the other three. We searched for these extra genes in both GenBank’s non-redundant protein database and all of the metagenomes in the sequence read archive, and found that they are present at levels that suggest that these are functional protein-coding genes. Availability and implementation: https://github.com/deprekate/PHANOTATE. Supplementary information: Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗