Chemical Mapping Data Research Articles

Major Mineral Fraction and Physical Properties of Carbonated Peridotite (Listvenite) From ICDP Oman Drilling Project Hole BT1B Inferred From X‐Ray CT Core Images

AbstractWe quantified mineral proportions in listvenite (completely carbonated peridotite) in Hole BT1B drilled across the basal thrust of the Samail ophiolite by the International Continental Scientific Drilling Project Oman Drilling Project using 3D X‐ray Computed Tomography (XCT). We analyzed >250,000 XCT images from a continuous ∼200 m listvenite core. Histograms of the intensity of X‐ray attenuation of each XCT core‐slice image were fitted assuming that the listvenites are composed of magnesite, quartz, and dolomite. The XCT mineral peaks were confirmed by comparison with chemical mapping data obtained using an X‐ray fluorescence (XRF) core scanner. Listvenite matrix is composed almost entirely of magnesite and quartz, consistent with discrete XRD and XRF data. Veins are composed mostly of dolomite. The mean abundance of dolomite in listvenite from BT1B is 11 vol.%, whereas that in core sections within 15 m of the basal thrust is >50 vol.%, suggesting the basal thrust acted as a source of Ca‐ and CO2‐rich fluids. The SiO2:MgO:CaO molar ratio in the entire core from BT1B is 42:52:6, similar to that of onboard XRF data for discrete samples (41:54:5), whereas average Oman peridotites have ratios of (39:60:1), indicating Ca addition perhaps during carbonation. P‐ and S‐wave velocities and density of listvenite are close to those of peridotite and are higher than those of serpentinites. These results suggest that limited material transfer during carbonation and hydration of the Samail ophiolite, except for Ca, CO2, and H2O. Listvenites formed in the mantle wedge above subduction zones may be an overlooked reservoir for carbon in the Earth's interior.

Effect of synthesis conditions on the properties of graphene doped with nitrogen atoms

Graphene doped with nitrogen atoms (N-graphene) was prepared by the template method. Magnesium oxide was subjected to carbonization in the 40% NH3–1% C2H2–C2H4 mixture at 650–750 °C. Then, the MgO core of the prepared N–С/MgO composite was dissolved by treatment in hydrochloric acid. The effects of temperature and synthesis time on the properties of the obtained N-graphene were studied by electron microscopy, Raman spectroscopy, XPS and XRD. The aggregates consisted of N-graphene particles with globular shape reflecting the template method used for their synthesis. The size of the carbon globules was about 30–50 nm. According to the chemical mapping data, C, O and N atoms were uniformly distributed in N-graphene within the analysis area. An increase of the synthesis temperature from 650 to 750 °C led to the decrease of the sample defectiveness, nitrogen atom concentration and surface area of N-graphene.

De novo 3D models of SARS-CoV-2 RNA elements from consensus experimental secondary structures.

The rapid spread of COVID-19 is motivating development of antivirals targeting conserved SARS-CoV-2 molecular machinery. The SARS-CoV-2 genome includes conserved RNA elements that offer potential small-molecule drug targets, but most of their 3D structures have not been experimentally characterized. Here, we provide a compilation of chemical mapping data from our and other labs, secondary structure models, and 3D model ensembles based on Rosetta's FARFAR2 algorithm for SARS-CoV-2 RNA regions including the individual stems SL1-8 in the extended 5′ UTR; the reverse complement of the 5′ UTR SL1-4; the frameshift stimulating element (FSE); and the extended pseudoknot, hypervariable region, and s2m of the 3′ UTR. For eleven of these elements (the stems in SL1–8, reverse complement of SL1–4, FSE, s2m and 3′ UTR pseudoknot), modeling convergence supports the accuracy of predicted low energy states; subsequent cryo-EM characterization of the FSE confirms modeling accuracy. To aid efforts to discover small molecule RNA binders guided by computational models, we provide a second set of similarly prepared models for RNA riboswitches that bind small molecules. Both datasets (‘FARFAR2-SARS-CoV-2’, https://github.com/DasLab/FARFAR2-SARS-CoV-2; and ‘FARFAR2-Apo-Riboswitch’, at https://github.com/DasLab/FARFAR2-Apo-Riboswitch’) include up to 400 models for each RNA element, which may facilitate drug discovery approaches targeting dynamic ensembles of RNA molecules.

Evidence of an Unusual Poly(A) RNA Signature Detected by High-Throughput Chemical Mapping.

Homopolymeric adenosine RNA plays numerous roles in both cells and noncellular genetic material. We report herein an unusual poly(A) signature in chemical mapping data generated by the Eterna Massive Open Laboratory. Poly(A) sequences of length seven or more show unexpected results in the selective 2'-hydroxyl acylation read out by primer extension (SHAPE) and dimethyl sulfate (DMS) chemical probing. This unusual signature first appears in poly(A) sequences of length seven and grows to its maximum strength at length ∼10. In a long poly(A) sequence, the substitution of a single A by any other nucleotide disrupts the signature, but only for the 6 or so nucleotides on the 5' side of the substitution.

Secondary structure of the segment 5 genomic RNA of influenza A virus and its application for designing antisense oligonucleotides

Influenza virus causes seasonal epidemics and dangerous pandemic outbreaks. It is a single stranded (−)RNA virus with a segmented genome. Eight segments of genomic viral RNA (vRNA) form the virion, which are then transcribed and replicated in host cells. The secondary structure of vRNA is an important regulator of virus biology and can be a target for finding new therapeutics. In this paper, the secondary structure of segment 5 vRNA is determined based on chemical mapping data, free energy minimization and structure-sequence conservation analysis for type A influenza. The revealed secondary structure has circular folding with a previously reported panhandle motif and distinct novel domains. Conservations of base pairs is 87% on average with many structural motifs that are highly conserved. Isoenergetic microarray mapping was used to additionally validate secondary structure and to discover regions that easy bind short oligonucleotides. Antisense oligonucleotides, which were designed based on modeled secondary structure and microarray mapping, inhibit influenza A virus proliferation in MDCK cells. The most potent oligonucleotides lowered virus titer by ~90%. These results define universal for type A structured regions that could be important for virus function, as well as new targets for antisense therapeutics.

Influenza virus segment 5 (+)RNA - secondary structure and new targets for antiviral strategies

Influenza A virus is a threat for humans due to seasonal epidemics and occasional pandemics. This virus can generate new strains that are dangerous through nucleotide/amino acid changes or through segmental recombination of the viral RNA genome. It is important to gain wider knowledge about influenza virus RNA to create new strategies for drugs that will inhibit its spread. Here, we present the experimentally determined secondary structure of the influenza segment 5 (+)RNA. Two RNAs were studied: the full-length segment 5 (+)RNA and a shorter construct containing only the coding region. Chemical mapping data combined with thermodynamic energy minimization were used in secondary structure prediction. Sequence/structure analysis showed that the determined secondary structure of segment 5 (+)RNA is mostly conserved between influenza virus type A strains. Microarray mapping and RNase H cleavage identified accessible sites for oligonucleotides in the revealed secondary structure of segment 5 (+)RNA. Antisense oligonucleotides were designed based on the secondary structure model and tested against influenza virus in cell culture. Inhibition of influenza virus proliferation was noticed, identifying good targets for antisense strategies. Effective target sites fall within two domains, which are conserved in sequence/structure indicating their importance to the virus.

Updates to the RNA mapping database (RMDB), version 2

Chemical mapping is a broadly utilized technique for probing the structure and function of RNAs. The volume of chemical mapping data continues to grow as more researchers routinely employ this information and as experimental methods increase in throughput and information content. To create a central location for these data, we established an RNA mapping database (RMDB) 5 years ago. The RMDB, which is available at http://rmdb.stanford.edu, now contains chemical mapping data for over 800 entries, involving 134 000 natural and engineered RNAs, in vitro and in cellulo. The entries include large data sets from multidimensional techniques that focus on RNA tertiary structure and co-transcriptional folding, resulting in over 15 million residues probed. The database interface has been redesigned and now offers interactive graphical browsing of structural, thermodynamic and kinetic data at single-nucleotide resolution. The front-end interface now uses the force-directed RNA applet for secondary structure visualization and other JavaScript-based views of bar graphs and annotations. A new interface also streamlines the process for depositing new chemical mapping data to the RMDB.

Mapping Long Non-Coding RNA Structures with Fragmentation and Next-Generation Sequencing

Recent years have seen an explosion in our appreciation of the myriad roles that RNA plays in the cell, including the discovery of new classes of regulatory RNAs such as long non-coding RNAs (lncRNAs). The three-dimensional folded structure of many coding and non-coding RNAs plays a key role in determining their function and fate in the cell. Obtaining high quality structural information on large numbers of RNAs is therefore essential, but traditional methods such as crystallography and NMR have been limited due to RNA's rugged folding landscape, charged backbone, and the large size of many RNAs of interest. Chemical mapping, in which folded RNAs are reacted with structure-sensitive chemical probes, provides nucleotide-level resolution mapping of base pairing and backbone flexibility, and can be applied both in vitro and in living cells. Chemical mapping data can be combined with thermodynamics-based structure models to predict RNAs’ folded structure, but the confidence of these predictions decreases rapidly with increasing RNA size. Measuring the structure of both the full length RNA and multiple shorter fragments in vitro has been proposed as a route to obtaining high-confidence structures, but applying this approach to longer RNAs requires high-throughput techniques for readout. Next-generation sequencing (NGS) is well suited to this task, as the large number of reads allows simultaneous analysis of multiple sequences and fragments with multiple chemical agents and the sequencing readout avoids length-dependent inaccuracies associated with gel and capillary electrophoresis. I will present results from applying rational fragmentation with NGS readout to map the structure of the 2.4 kb trans-acting lncRNA HOTAIR and discuss implications for folding pathways of large RNAs and possibilities for in vivo measurement.

A Locally Convoluted Cluster Model for Nucleosome Positioning Signals in Chemical Maps

The nucleosome is the fundamental packing unit of DNA in eukaryotic cells, and its positioning plays a critical role in regulation of gene expression and chromosome functions. Using a recently developed chemical mapping method, nucleosomes can be potentially mapped with an unprecedented single-base-pair resolution. Existence of overlapping nucleosomes due to cell mixture or cell dynamics, however, causes convolution of nucleosome positioning signals. In this article, we introduce a locally convoluted cluster model and a maximum likelihood deconvolution approach, and illustrate the effectiveness of this approach in quantification of the nucleosome positional signal in the chemical mapping data. Supplementary materials for this article are available online.

Interfacial morphology development and solute trapping behavior during rapid solidification of an Al–Li–Cu alloy

An aluminum–lithium–copper alloy was rapidly solidified via the electrospark deposition process. High-resolution scanning electron microscopy (HR-SEM), time-of-flight secondary-ion-mass-spectroscopy (TOF-SIMS) and atom probe tomography (APT) were employed to investigate the distribution of solute within the deposited materials. The TOF-SIMS data revealed evidence that solute trapping of lithium occurred during solidification, while SEM and APT revealed the presence of fine copper-rich cells within the microstructure (∼30–60nm in width). This morphology correlated directly with the microstructural morphology predicted by the Kurz–Giovanola–Trivedi (KGT) model for microstructural development during rapid solidification. The KGT model, which can be used to describe the planar–cellular transition within a microstructure, then predicted a solidification front velocity of ∼1ms−1 being realized during electrospark deposition solidification. This SFV corroborated the chemical mapping data, and therefore supported the solute trapping hypothesis, as the continuous growth model for solute trapping as developed by Aziz and Kaplan (Acta Metallurgica 1988; 36:2335) predicts significant trapping of lithium at a SFV of 1ms−1. Finally APT revealed the presence of Al3Li phase upon the copper-rich cell walls. It was then determined that the Al3Li was not formed during solidification, as predicted by a time-dependent nucleation model for phase prediction during rapid solidification, and therefore is the result of a subsequent aging process.

Usefulness of functional and structural solution data for the modeling of tRNA-like structures

Structures of large RNAs are not easily solved by X-ray crystallography or by NMR spectroscopy. This paper reviews the alternate methodology based on enzymatic and chemical mapping data collected on RNAs combined with graphical modeling for the construction of three-dimensional models. The different steps that lead to the establishment of the models are critically discussed. It is shown how the correctness of an RNA model can be strengthened by establishing correlations between the structure and the functionality of the molecule and its variants. Finally, the predictive potential of a model is discussed. The approach is illustrated by results obtained on plant viral tRNA-like structures, and particularly on that of brome mosaic virus (BMV) RNA.

Analysis of the virulence modulating region of potato spindle tuber viroid (PSTVd) by site-directed mutagenesis

A series of nucleotide substitutions (G,s → C; C4, → A; C 315 → U; U31, → C) were introduced into the virulence modulating region of the intermediate strain of potato spindle tuber viroid (PSTVd) in order to examine their effect upon viroid infectivity and pathogenicity with the presence of all four mutations resulting in the sequence of a previously reported severe strain of PSTVd. Eight of the resulting mutant cDNAs were characterized for infectivity and symptom induction in tomato, and the secondary structure of their corresponding RNAs was examined. The combined results of infectivity, computer analysis, and chemical mapping data imply that a previously proposed correlation between thermodynamic stability and PSTVd pathogenicity does not hold true in all cases and suggest that conformation and/or sequence-specific interactions with host factors playa role in symptom development.

Distribution of intermetallic compounds in high pressure gas atomized aluminium-chromium alloy powders: N.J.E. Adkins and P. Tsakiropoulos, (Univ of Surrey, Guildford, UK, Int J Rapid Solidification, Vol 6, 1991, 101–114

An aluminum–lithium–copper alloy was rapidly solidified via the electrospark deposition process. High-resolution scanning electron microscopy (HR-SEM), time-of-flight secondary-ion-mass-spectroscopy (TOF-SIMS) and atom probe tomography (APT) were employed to investigate the distribution of solute within the deposited materials. The TOF-SIMS data revealed evidence that solute trapping of lithium occurred during solidification, while SEM and APT revealed the presence of fine copper-rich cells within the microstructure (∼30–60 nm in width). This morphology correlated directly with the microstructural morphology predicted by the Kurz–Giovanola–Trivedi (KGT) model for microstructural development during rapid solidification. The KGT model, which can be used to describe the planar–cellular transition within a microstructure, then predicted a solidification front velocity of ∼1 m s−1 being realized during electrospark deposition solidification. This SFV corroborated the chemical mapping data, and therefore supported the solute trapping hypothesis, as the continuous growth model for solute trapping as developed by Aziz and Kaplan (Acta Metallurgica 1988; 36:2335) predicts significant trapping of lithium at a SFV of 1 m s−1. Finally APT revealed the presence of Al3Li phase upon the copper-rich cell walls. It was then determined that the Al3Li was not formed during solidification, as predicted by a time-dependent nucleation model for phase prediction during rapid solidification, and therefore is the result of a subsequent aging process.