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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Targeted inhibition of MASTL kinase activity induces apoptosis in breast cancer

Microtubule-associated serine/threonine kinase-like (MASTL) (or Greatwall kinase (GWL)) is an important cell cycle regulating kinase that regulates the G2-M transition. Uncontrolled MASTL activity is implicated in breast cancer progression. To date, very few inhibitors have been reported against this protein. Here, structure-based computational modeling indicates that the natural product flavopiridol (FLV) binds strongly to MASTL and these results are validated using molecular dynamics simulation studies. Further, an in vitro kinase assay reveals an EC 50 (effective concentration) value of FLV to be 82.1 nM and a better IC 50 compared to the positive reference compound, staurosporine. FLV is found to inhibit MASTL kinase activity, arresting the cell growth in the G1 phase and inducing apoptosis in breast cancer cells. Consistent with these results differential gene expression obtained using RNA sequencing studies, and validated by RT PCR and immunoblot analysis, indicate that MASTL inhibition induces cell cycle arrest and apoptotic-related genes. Furthermore, metastasis- and inflammation- related genes are downregulated. Thus, the deregulation of MASTL signaling pathways on targeted inhibition of its kinase activity is revealed. This study lays a strong foundation for investigating FLV as a lead compound in breast cancer therapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Comparison of pectin-degrading fungal communities in temperate forests using glycosyl hydrolase family 28 pectinase primers targeting Ascomycete fungi

Here, fungi have developed a wide assortment of enzymes to break down pectin, a prevalent polymer in plant cell walls that is important in plant defense and structure. One enzyme family used to degrade pectin is the glycosyl hydrolase family 28 (GH28). In this studywe developed primers for the amplification of GH28 coding genes from a database of 293 GH28 sequences from40 fungal genomes. The primerswere used to successfully amplify GH28 pectinases from all Ascomycota cultures tested, but only three out of seven Basidiomycota cultures. In addition, we further tested the primers in PCRs on metagenomic DNA extracted from senesced tree leaves from different forest ecosystems, followed by cloning and sequencing. Taxonomic specificity for Ascomycota GH28 genes was tested by comparing GH28 composition in leaves to internal transcribed spacer (ITS) amplicon composition using pyrosequencing. All sequences obtained from GH28 primers were classified as Ascomycota; in contrast, ITS sequences indicated that fungal communitieswere up to 39% Basidiomycetes. Analysis of leaf samples indicated that both forest stand and ecosystemtype were important in structuring fungal communities. However, site played the prominent role in explaining GH28 composition, whereas ecosystem type was more important for ITS composition, indicating possible genetic drift between populations of fungi. Overall, these primers will have utility in understanding relationships between fungal community composition and ecosystem processes, as well as detection of potentially pathogenic Ascomycetes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Automated theoretical chemical kinetics: Predicting the kinetics for the initial stages of pyrolysis

Large scale implementation of high level computational theoretical chemical kinetics offers the prospect for dramatically improving the fidelity of combustion chemical modeling. To facilitate such efforts, we have developed a suite of codes, collectively referred to as AutoMech, that allow for the automatic prediction of the kinetics for large sets of reactions via ab initio transition-state-theory based master-equation calculations. The primary input is simply the mechanism, a dictionary relating chemically identifiable species descriptors (e.g., SMILES or InChIs) to species labels in the mechanism, and a specification of the electronic structure and transition state theory models to be implemented. Here we illustrate the current utility of AutoMech through a study of the initial stages of pyrolysis for 3 sets of fuels: sequences of alkanes, alcohols, and aldehydes. For simplicity, the analysis focuses on abstractions from the fuel by H, CH 3 , and OH, and the decomposition of the resulting radicals. Altogether, there are a total of 166 input channels in these sets (more than 363 forward reactions when expanded to the full set of elementary reactions). The code successfully produces high quality rate estimates (with apparent uncertainties less than a factor of two in limited comparisons with experiment) for > 95% of these. For the radical decomposition reactions, the analysis includes predictions for the pressure dependence of the kinetics. This wide-ranging exploration illustrates (i) the effect of different levels of prediction on the expected accuracy, (ii) the branching between abstractions at different sites for different abstractors, (iii) the dependence of the rates on the chemical structure, and (iv) the variation in radical stabilities across chemical families. These results, as well as the demonstrated feasibility of the methodology, should find further utility in the development of accurate rate expressions for arbitrary fuels. (c) 2020 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Elliott, Sarah N.↗
DOE OSTI2023

Comparing Top-Down Proteoform Identification: Deconvolution, PrSM Overlap, and PTM Detection

Generating top-down tandem mass spectra (MS/MS) for complex mixtures of proteoforms has become possible through improvements in fractionation, on-line separation, dissociation, and mass analysis. The algorithms to match tandem mass spectra to sequences have undergone a parallel evolution, with both spectral alignment and peak matching being paired with diverse methods for scoring proteoform-spectral matches (PrSMs). This study assesses state-of-the-art algorithms for top-down identification through three distinct challenges. The first is identifying a large yield of PrSMs while controlling false discovery rate (FDR) in identifying thousands of proteoforms from complex cell lysates via four software workflows: ProSight Proteome Discoverer, TopPIC, Informed Proteomics, and pTop. The second is the deconvolution of data from both Thermo Orbitrap-class and Bruker maXis Q-TOF instruments to produce consistent precursor charge and mass determinations while generating fragment mass lists to optimize identification. The third attempts to detect diverse post-translational modifications (PTMs) in proteoforms from cow milk and human ovarian tissue. The data demonstrate that existing software suites produce admirable sensitivity, in some cases identifying a third of collected tandem mass spectra with FDR controlled below 2%; the overlap in these PrSMs, however, illustrates real value in searching data with multiple search engines. Differences among identification workflows seem to result from each search algorithm incorporating its own deconvolution algorithm. By transmitting deconvolution data from multiple deconvolution routes (Thermo Xtract, Bruker Auto MSn, Mascot Distiller, TopFD, and FLASHDeconv) to the downstream TopPIC search algorithm, we were able to detect common causes of deconvolution disagreement. The detection of PTMs was very inconsistent among search algorithms, with some workflows suggesting as little as 1% of PrSMs from cow’s milk were singly-phosphorylated while other workflows found that 18% of PrSMs were singly-phosphorylated. Taken together, these results make a strong argument for top-down researchers to adopt a standard practice of analyzing each MS/MS experiment with at least two different search engines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Crystal Structures of Trypanosoma cruzi UDP-Galactopyranose Mutase Implicate Flexibility of the Histidine Loop in Enzyme Activation

Chagas disease is a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi. Here we report crystal structures of the galactofuranose biosynthetic enzyme UDP-galactopyranose mutase (UGM) from T. cruzi, which are the first structures of this enzyme from a protozoan parasite. UGM is an attractive target for drug design because galactofuranose is absent in humans but is an essential component of key glycoproteins and glycolipids in trypanosomatids. Analysis of the enzyme-UDP noncovalent interactions and sequence alignments suggests that substrate recognition is exquisitely conserved among eukaryotic UGMs and distinct from that of bacterial UGMs. This observation has implications for inhibitor design. Activation of the enzyme via reduction of the FAD induces profound conformational changes, including a 2.3 {angstrom} movement of the histidine loop (Gly60-Gly61-His62), rotation and protonation of the imidazole of His62, and cooperative movement of residues located on the si face of the FAD. Interestingly, these changes are substantially different from those described for Aspergillus fumigatus UGM, which is 45% identical to T. cruzi UGM. The importance of Gly61 and His62 for enzymatic activity was studied with the site-directed mutant enzymes G61A, G61P, and H62A. These mutations lower the catalytic efficiency by factors of 10-50, primarily by decreasing k{sub cat}. Considered together, the structural, kinetic, and sequence data suggest that the middle Gly of the histidine loop imparts flexibility that is essential for activation of eukaryotic UGMs. Our results provide new information about UGM biochemistry and suggest a unified strategy for designing inhibitors of UGMs from the eukaryotic pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Chromatin structure predicts survival in glioma patients

The pathological changes in epigenetics and gene regulation that accompany the progression of low-grade to high-grade gliomas are under-studied. The authors use a large set of paired atac-seq and RNA-seq data from surgically resected glioma specimens to infer gene regulatory relationships in glioma. Thirty-eight glioma patient samples underwent atac-seq sequencing and 16 samples underwent additional RNA-seq analysis. Using an atac-seq/RNA-seq correlation matrix, atac-seq peaks were paired with genes based on high correlation values (|r 2 | > 0.6). Samples clustered by IDH1 status but not by grade. Surprisingly there was a trend for IDH1 mutant samples to have more peaks. The majority of peaks are positively correlated with survival and positively correlated with gene expression. Constructing a model of the top six atac-seq peaks created a highly accurate survival prediction model (r 2 = 0.68). Four of these peaks were still significant after controlling for age, grade, pathology, IDH1 status and gender. Grade II, III, and IV (primary) samples have similar transcription factors and gene modules. However, grade IV (recurrent) samples have strikingly few peaks. Patient-derived glioma cultures showed decreased peak counts following radiation indicating that this may be radiation-induced. This study supports the notion that IDH1 mutant and IDH1 wildtype gliomas have different epigenetic landscapes and that accessible chromatin sites mapped by atac-seq peaks tend to be positively correlated with expression. The data in this study leads to a new model of treatment response wherein glioma cells respond to radiation therapy by closing open regions of DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Community RNA-Seq: multi-kingdom responses to living versus decaying roots in soil

Abstract Roots are a primary source of organic carbon input in most soils. The consumption of living and detrital root inputs involves multi-trophic processes and multiple kingdoms of microbial life, but typical microbial ecology studies focus on only one or two major lineages. We used Illumina shotgun RNA sequencing to conduct PCR-independent SSU rRNA community analysis (“community RNA-Seq”) and simultaneously assess the bacteria, archaea, fungi, and microfauna surrounding both living and decomposing roots of the annual grass, Avena fatua. Plants were grown in 13CO2-labeled microcosms amended with 15N-root litter to identify the preferences of rhizosphere organisms for root exudates (13C) versus decaying root biomass (15N) using NanoSIMS microarray imaging (Chip-SIP). When litter was available, rhizosphere and bulk soil had significantly more Amoebozoa, which are potentially important yet often overlooked top-down drivers of detritusphere community dynamics and nutrient cycling. Bulk soil containing litter was depleted in Actinobacteria but had significantly more Bacteroidetes and Proteobacteria. While Actinobacteria were abundant in the rhizosphere, Chip-SIP showed Actinobacteria preferentially incorporated litter relative to root exudates, indicating this group’s more prominent role in detritus elemental cycling in the rhizosphere. Our results emphasize that decomposition is a multi-trophic process involving complex interactions, and our methodology can be used to track the trajectory of carbon through multi-kingdom soil food webs.

Nuccio, Erin E. (ORCID:000000030189183X)↗
DOE OSTI2020

Effect of Accurate Modeling of Converter Interfaced Generation (CIG) on a Practical Bulk Power System

With increased penetration of converter interfaced generation (CIG) in power systems, it becomes imperative to adequately model them in both steady-state and dynamic simulations. There are several modeling approaches and simulation platforms for CIG. In addition, it is noted that suitability of modeling approaches and models is also dependent on the system conditions. However, their suitability has yet to be systematically analyzed, and this becomes a challenge in the industry without a systemic method. To tackle these challenges, in this paper, we first develop a methodology for identifying the maximum penetration of aggregated rooftop sources that can be represented as negative loads in both the steady state and dynamic analysis. Then we verify the suitability of positive-sequence performance-based model and detailed electromagnetic transient (EMT) model for utility-scale PV plants under different fault conditions. Based on the results, we perform dynamic simulations on a large practical system with both positive-sequence transient stability(TS) and EMT-TS hybrid simulation. Our study shows that positive-sequence performance based PV plant model is more suitable for study cases with faults relatively far away from the point of connection, and that positive-sequence models and TS simulation approach can produce comparable results with reference to EMT-TS hybrid simulation for normally-cleared single-line-to-ground faults, but the inadequacy of positive-sequence based model and simulation approach becomes obvious for prolonged-tripping of unbalanced faults in proximity of the PV plants.

Huang, Qiuhua↗
DOE OSTI2016

Improving the sensitivity of J coupling measurements in solids with application to disordered materials

It has been shown previously that for magic angle spinning (MAS) solid state NMR the refocused INADEQUATE spin-echo (REINE) experiment can usefully quantify scalar (J) couplings in disordered solids. This paper focuses on the two z filter components in the original REINE pulse sequence, and investigates by means of a product operator analysis and fits to density matrix simulations the effects that their removal has on the sensitivity of the experiment and on the accuracy of the extracted J couplings. The first z filter proves unnecessary in all the cases investigated here and removing it increases the sensitivity of the experiment by a factor ∼1.1–2.0. Furthermore, for systems with broad isotropic chemical shift distributions (namely whose full widths at half maximum are greater than 30 times the mean J coupling strength), the second z filter can also be removed, thus allowing whole-echo acquisition and providing an additional √2 gain in sensitivity. Considering both random and systematic errors in the values obtained, J couplings determined by fitting the intensity modulations of REINE experiments carry an uncertainty of 0.2–1.0 Hz (∼1−10 %).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Using Corticosteroids to Reshape the Gut Microbiome: Implications for Inflammatory Bowel Diseases

Introduction—Commensal gut microbiota play an important role in regulating metabolic and inflammatory conditions. Reshaping intestinal microbiota through pharmacologic means may be a viable treatment option. Here we sought to delineate the functional characteristics of glucocorticoid-mediated alterations on gut microbiota and their subsequent repercussions on host mucin regulation and colonic inflammation. Methods—Adult male C57Bl/6 mice, germ-free (GF), Muc2-heterozygote (±), or Muc2-knockout (-/-) were injected with dexamethasone, a synthetic glucocorticoid, for four weeks. Fecal samples were collected for gut microbiota analysis via 16S rRNA T-RFLP and amplicon sequencing. Intestinal mucosa was collected for mucin gene expression studies. GF mice were conventionalized with gut microbes from treated- and non-treated groups to determine their functional capacities in recipient hosts. Results—Exposure to DEX in WT mice led to substantial shifts in gut microbiota over a four-week period. Furthermore, a significant down-regulation of colonic Muc2 gene expression was observed after treatment. Muc2-knockout mice harbored a pro-inflammatory environment of gut microbes, characterized by the increase or decrease in prevalence of specific microbiota populations such as Clostridiales and Lactobacillaceae, respectively. This colitogenic phenotype was transmissible to IL10-knockout (IL10-KO) mice, a genetically susceptible model of colonic inflammatory disorders. Microbiota from donors pre-treated with DEX, however, ameliorated symptoms of inflammation. We conclude that commensal gut bacteria may be a key mediator of the anti-inflammatory effects observed in the large intestine after GC exposure. These findings underscore the notion that intestinal microbes comprise a “microbial organ” essential for host physiology that can be targeted by therapeutic approaches to restore intestinal homeostasis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Benchmark study of the two-dimensional Hubbard model with auxiliary-field quantum Monte Carlo method

Ground-state properties of the Hubbard model on a two-dimensional square lattice are studied by the auxiliary-field quantum Monte Carlo method. Accurate results for energy, double occupancy, effective hopping, magnetization, and momentum distribution are calculated for interaction strengths of U/t from 2 to 8, for a range of densities including half-filling and n = 0.3,0.5,0.6, 0.75, and 0.875. At half-filling, the results are numerically exact. Away from half-filling, the constrained path Monte Carlo method is employed to control the sign problem. Our results are obtained with several advances in the computational algorithm, which are described in this paper in detail. We discuss the advantages of generalized Hartree-Fock trial wave functions and its connection to pairing wave functions, as well as the interplay with different forms of Hubbard-Stratonovich decompositions. We study the use of different twist angle sets when applying the twist averaged boundary conditions. We propose the use of quasirandom sequences, which improves the convergence to the thermodynamic limit over pseudorandom and other sequences. With it and a careful finite size scaling analysis, we are able to obtain accurate values of ground-state properties in the thermodynamic limit. Detailed results for finite-sized systems up to 16 × 16 are also provided for benchmark purposes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Microbial potential for carbon and nutrient cycling in a geogenic supercritical carbon dioxide reservoir: Microbial life in the deep carbonated biosphere

Microorganisms catalyze carbon cycling and biogeochemical reactions in the deep subsurface and thus may be expected to influence the fate of injected super-critical (sc) CO 2 following geological carbon sequestration (GCS). We hypothesized that natural subsurface scCO 2 reservoirs, which serve as analogs for the long-term fate of sequestered scCO 2 harbor a ‘deep carbonated biosphere’ with carbon cycling potential. We sampled subsurface fluids from scCO 2 - water separators at a natural scCO 2 reservoir at McElmo Dome, Colorado for analysis of 16S rRNA gene diversity and metagenome content. Sequence annotations indicated dominance of Sulfurospirillum, Rhizobium, Desulfovibrio and four members of the Clostridiales family. Genomes extracted from metagenomes using homology and compositional approaches revealed diverse mechanisms for growth and nutrient cycling, including pathways for CO 2 and N 2 fixation, anaerobic respiration, sulfur oxidation, fermentation and potential for metabolic syntrophy. Differences in biogeochemical potential between two production well communities were consistent with differences in fluid chemical profiles, suggesting a potential link between microbial activity and geochemistry. In conclusion, the existence of a microbial ecosystem associated with the McElmo Dome scCO 2 reservoir indicates that potential impacts of the deep biosphere on CO 2 fate and transport should be taken into consideration as a component of GCS planning and modelling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Quantitative Analysis of Color Differences within High Contrast, Low Power Reversible Electrophoretic Displays

Here, quantitative color analysis is performed on videos of high contrast, low power reversible electrophoretic deposition (EPD)-based displays operated under different applied voltages. This analysis is coded in an open-source software, relies on a color differentiation metric, ΔE * 00 , derived from digital video, and provides an intuitive relationship between the operating conditions of the devices and their performance. Time-dependent ΔE * 00 color analysis reveals color relaxation behavior, recoverability for different voltage sequences, and operating conditions that can lead to optimal performance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Morphological and molecular characterization of Paratylenchus beltsvillensis n. sp. (Tylenchida: Paratylenchidae) from the rhizosphere of pine tree ( Pinus virginiana Mill) in Maryland, USA

The pin nematode, Paratylechus beltsvillensis sp. collected from rhizosphere soil of a Virginia pine tree (Pinus virginiana Mill) growing in Little Paint Branch Park, Beltsville, Prince George’s County, Maryland, USA, is described and illustrated along with light and scanning electron photomicrographs. Females, males, and juveniles of this new species were recovered from soil samples using the sugar centrifugal flotation and Baermann funnel extraction methods. Morphologically, females are short, body length ranging from 245 to 267 μm, stylet from 70 to 75 μm long with anchor shaped knobs, vulva located at 70–73% and small vulval flap, spermatheca large, and ovoid filled with sperms. Lateral field with three incisures, of which the outer two are prominent. Tail slender, having a rounded tail terminus. Males without stylet and have a degenerated pharynx, spicules = 17–20 µm and gubernaculum = 5.0–5.5 µm. Both morphological observations and molecular analysis of ITS and partial 28S ribosomal RNA gene sequences indicated that the specimens collected from the soil at Beltsville Park from rhizosphere soil samples from Virginia pine represents a new pin nematode species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Nuclear Power Plant Cyber Security Discrete Dynamic Event Tree Analysis (LDRD 17-0958) FY17 Report

Instrumentation and control of nuclear power is transforming from analog to modern digital assets. These control systems perform key safety and security functions. This transformation is occurring in new plant designs as well as in the existing fleet of plants as the operation of those plants is extended to 60 years. This transformation introduces new and unknown issues involving both digital asset induced safety issues and security issues. Traditional nuclear power risk assessment tools and cyber security assessment methods have not been modified or developed to address the unique nature of cyber failure modes and of cyber security threat vulnerabilities. iii This Lab-Directed Research and Development project has developed a dynamic cyber-risk in- formed tool to facilitate the analysis of unique cyber failure modes and the time sequencing of cyber faults, both malicious and non-malicious, and impose those cyber exploits and cyber faults onto a nuclear power plant accident sequence simulator code to assess how cyber exploits and cyber faults could interact with a plants digital instrumentation and control (DI&C) system and defeat or circumvent a plants cyber security controls. This was achieved by coupling an existing Sandia National Laboratories nuclear accident dynamic simulator code with a cyber emulytics code to demonstrate real-time simulation of cyber exploits and their impact on automatic DI&C responses. Studying such potential time-sequenced cyber-attacks and their risks (i.e., the associated impact and the associated degree of difficulty to achieve the attack vector) on accident management establishes a technical risk informed framework for developing effective cyber security controls for nuclear power.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

From microbial diversity to functional potential using dimensionality reduction

The high dimensionality of microbial diversity data from ‘omics observations can be reduced using Machine Learning, with many recent studies showcasing ML utility for exploratory ecological feature finding and process prediction. Here, we compare the Self Organizing Map (SOM) dimensionality reduction method to the well-documented sample-based Principal Coordinate Analysis (PCoA) and taxa-based Weighted Gene Correlation Network Analysis (WGCNA) using near daily 16S rRNA gene amplicon sequencing data from the 2019 to 2020 MOSAiC International Arctic Drift Expedition. We then map k-means clustering outputs from each method to available metagenomes, extracting functionally distinct seasonal microbial ecotypes in the surface Arctic Ocean. Our results indicate the SOM method better represented expected seasonal transitions and identified a greater number of metabolically distinct functional groups than the more traditional PCoA ordination. Ultimately, we identified four community ecotypes with distinct taxonomic and functional cut-offs driven by seasonality, water mass, and substrate turnover, highlighting the importance of succession in functional diversity for the central Arctic Ocean. These results reinforce ML dimensionality reduction as a meaningful translator in the mining of historical amplicon datasets to address modern mechanistic questions and potentially provide ’omics informed ecotype diversity to leverage in mechanistic biogeochemical models.

Arctic Ocean↗
DOE OSTI2020

Threat Reduction Research Networks: Fostering Sustainable Collaborations Through Trainings for Genomics for Biosurveillance

Scientific research communities can be represented as heterogeneous or multidimensional networks encompassing multiple types of entities and relationships. These networks might include researchers, institutions, meetings, and publications, connected by relationships like authorship, employment, and attendance. We describe a method for efficiently and flexibly capturing, storing, and extracting information from multidimensional scientific networks using a graph database. The database structure is based on an ontology that captures allowable types of entities and relationships. This allows us to construct a variety of projections of the underlying multidimensional graph through database queries to answer specific research questions. We demonstrate this process through a study of the U.S. Biological Threat Reduction Program (BTRP), which seeks to develop Threat Reduction Networks to build and strengthen a sustainable international community of biosecurity, biosafety, and biosurveillance experts to address shared biological threat reduction challenges. Networks like these create connectional intelligence among researchers and institutions around the world, and are central to the concept of cooperative threat reduction. Our analysis focuses on a series of seven BTRP genome sequencing training workshops, showing how they created a growing network of participants and countries over time, which is also reflected in coauthorship relationships among attendees. By capturing concept and relationship hierarchies, our ontology-based approach allows us to pose general or specific questions about networks within the same framework. This approach can be applied to other research communities or multidimensional social networks to capture, analyze, and visualize different types of interactions and how they change over time.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Tackling Structures of Long Noncoding RNAs

RNAs are important catalytic machines and regulators at every level of gene expression. A new class of RNAs has emerged called long non-coding RNAs, providing new insights into evolution, development and disease. Long non-coding RNAs (lncRNAs) predominantly found in higher eukaryotes, have been implicated in the regulation of transcription factors, chromatin-remodeling, hormone receptors and many other processes. The structural versatility of RNA allows it to perform various functions, ranging from precise protein recognition to catalysis and metabolite sensing. While major housekeeping RNA molecules have long been the focus of structural studies, lncRNAs remain the least characterized class, both structurally and functionally. Here, we review common methodologies used to tackle RNA structure, emphasizing their potential application to lncRNAs. When considering the complexity of lncRNAs and lack of knowledge of their structure, chemical probing appears to be an indispensable tool, with few restrictions in terms of size, quantity and heterogeneity of the RNA molecule. Probing is not constrained to in vitro analysis and can be adapted to high-throughput sequencing platforms. Significant efforts have been applied to develop new in vivo chemical probing reagents, new library construction protocols for sequencing platforms and improved RNA prediction software based on the experimental evidence.

SHAPE↗