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At least 883 records · Page 49

Characterising the Higgs boson with ATLAS data from the LHC Run-2

The Higgs boson was discovered by the ATLAS and CMS Collaborations in 2012 using data from Run 1 of the Large Hadron Collider (2010 2012). In Run 2 (2015 2018), about 140 fb -1 of proton–proton collisions at a centre-of-mass energy of 13 TeV were collected by the ATLAS experiment. This review presents the most important Run 2 results obtained by the ATLAS Collaboration regarding the properties of the Higgs boson and its interactions with other particles. The performed studies significantly enhance the understanding of the Higgs boson, while hunting for deviations from the predictions of the Standard Model of particle physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Overview of high-density QCD studies with the CMS experiment at the LHC

We review key measurements performed by CMS in the context of its heavy ion physics program, using event samples collected in 2010-2018 with several collision systems and energies. These studies provide detailed macroscopic and microscopic probes of the quark-gluon plasma (QGP) created at the LHC energies, a medium characterized by the highest temperature and smallest baryon-chemical potential ever reached in the laboratory. Numerous observables related to high-density quantum chromodynamics (QCD) were studied, leading to some of the most impactful and qualitatively novel results in the 40-year history of the field. Using a dedicated high-multiplicity trigger in the first pp run, CMS discovered that small collision systems can exhibit signs of collectivity, a generic phenomenon with significant implications and presently understood to affect essentially all soft physics processes. This observation opened new paths to understand how fluidity and plasma properties emerge in QCD matter as a function of system size. Measurements of jet quenching have reached a completely new level of detail by directly assessing, for the first time, the medium modification of parton showers, as opposed to simply observing leading hadrons or di-hadrons. The first fully reconstructed beauty hadron and heavy-flavor jet nuclear modifications were also measured. The large size of the event samples, the precision of the measurements, and the extension of the probed kinematical phase space, allowed many other hard probes of the QGP medium to be explored in detail, leading to multiple groundbreaking findings. In particular, the seminal measurements of bottomonium suppression patterns answer fundamental questions that have been actively pursued, both theoretically and experimentally, by the community since the mid-1980s. We conclude by outlining the opportunities offered by the continuation of this physics program at the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

From classical thermodynamics to phase-field method

Phase-field method is a density-based computational method at the mesoscale for modeling and predicting the temporal microstructure and property evolution during materials processes. The focus of this article is on connecting the most common phase-field equations to the very basic first and second laws of classical thermodynamics through rudimentary irreversible thermodynamics. It briefly discusses the relations of the continuum phase-field equations to their counter parts at the microscopic and atomic levels. It attempts to clarify the contributions of long-range elastic, electrostatic, and magnetic interactions to domain structure evolution during structural, ferroelectric, and ferromagnetic phase transformations by separating order parameter changes due to the presence of quasi-static fields and those arising from phase transformations. A few examples are presented to demonstrate the possibility of employing the phase-field method to provide guidance to designing materials for optimum properties or discovering novel mesoscale phenomena or new materials functionalities. Here, the article ends with a brief perspective on a number of potential future directions on the development and applications of phase-field method beyond its traditional applications to structural alloys.

36 MATERIALS SCIENCE↗

Ordinary and exotic mesons in the extended Linear Sigma Model

The extended Linear Sigma Model (eLSM) is a hadronic model based on the global symmetries of QCD and the corresponding explicit, anomalous, and spontaneous breaking patterns. In its basic three-flavor form, its mesonic part contains the dilaton/glueball as well as the nonets of pseudoscalar, scalar, vector, and axial–vector mesons, thus chiral symmetry is linearly realized. In the chiral limit and neglecting the chiral anomaly, only one term – within the dilaton potential – breaks dilatation invariance, and all terms are chirally symmetric. Spontaneous symmetry breaking is implemented by a generalization of the Mexican-hat potential, with explicit symmetry breaking responsible for its tilting. The overall mesonic phenomenology up to ~2 GeV is in agreement with the PDG compilation of masses and partial and total decay widths. The eLSM was enlarged in a straightforward way to include other conventional quark–antiquark nonets (pseudovector and orbitally excited vector mesons, tensor and axial-tensor mesons, radially excited (pseudo)scalar mesons, etc.), as well as two nonets of hybrid mesons, the lightest one with exotic quantum numbers J $\mathscr{PC}$ = 1 -+ not allowed for $\bar{q}q$ objects, such as the resonance π 1 (1600) and the recently discovered η 1 (1855) . In doing so, different types of chiral multiplets are introduced: heterochiral and homochiral multiplets, which differ in the way they transform under chiral transformations. Moreover, besides the scalar glueball that is present from the beginning as dilaton, other glueballs, the tensor, the pseudoscalar and the vector glueballs were coupled to the eLSM: the scalar resonance ƒ 0 (1710) turns out to be mostly gluonic, the tensor glueball couples strongly to vector mesons, and the pseudoscalar glueball couples sizably to $ππη'$ and can be assigned to X (2370) or X (2600). In all cases above, masses and decays can be analyzed allowing for a better understanding of both conventional and non-conventional mesons: whenever data are available, a comparison is performed and, when this is not the case, predictions of decay widths and decay ratios are outlined. The eLSM contains chiral partners on an equal footing and is therefore well suited for studies of chiral symmetry restoration at nonzero temperature and densities: this is done by coupling it to the Polyakov loop. Finally, the QCD phase diagram and the location of the critical endpoint were investigated within this framework.

Chiral symmetry↗

The impact of $γN$ and $γ^∗N$ interactions on our understanding of nucleon excitations

We review recent progress in our understanding of the nucleon excitation spectrum. Thanks to dedicated efforts at facilities such as ELSA, MAMI and Jefferson Lab, several new nucleon resonances have been discovered, and evidence for previously elusive states has been significantly improved. Numerous decay channels have been observed for the first time, and resonance properties are being extracted from these data by several groups through coupled-channel analyses of varying complexity. Electroproduction experiments have provided further insights into the internal structure of light baryon resonances – for example, the long-debated Roper resonance N (1440) is observed as a three-quark state with a significant meson-cloud component. While the non-relativistic quark model remains a valuable tool for organizing the spectrum of nucleon and Δ resonances, a variety of theoretical frameworks have emerged to offer deeper understanding, including phenomenological quark models, holographic QCD, functional methods, effective field theories, and lattice QCD. We examine the interplay between these approaches, highlight their respective strengths and explore how they complement each other in shaping our knowledge of light baryon resonances. We address several open questions in baryon spectroscopy, including the nature of the enigmatic Λ (1405), ongoing searches for exotic states such as hybrid baryons and pentaquarks, and the dichotomy between microscopic descriptions of baryons in terms of quarks and gluons versus effective hadronic descriptions based on meson-baryon dynamics.

Baryon resonances↗

A comparison of computational models for predicting yield sooting index

Sooting propensity, a measurement of how much particulate matter is produced when a fuel is burned, is a property of significant interest among researchers who are striving to discover the next generation of cleaner, more efficient fuels and fuel additives. Many compounds are not viable as fuels and/or fuel additives, and as a result, designing cleaner-burning biofuels using only experimental techniques is inefficient. Predictive models have been instrumental in reducing this inherent difficulty, providing researchers with a tool to preemptively screen compounds before production and testing. The present work compares the accuracies and interpretabilities of existing models used to predict a particular measure of sooting propensity, Yield Sooting Index (YSI). These models include artificial neural networks, graph neural networks, and multivariate equations. A novel equation for predicting YSI based on atom path count and bond order is proposed, which can highlight key structural components that contribute to YSI. It was found that artificial neural networks slightly outperform graph neural networks and greatly outperform multivariate equations in blind (test set) prediction accuracy; however, graph neural networks and multivariate equations provide significantly more interpretability as to how compound structure relates to YSI. Predictions of YSI are compared to experimental measurements for previously un-tested compounds with cetane numbers comparable to diesel fuel (50-60) (butyl decanoate, ethyl decanoate, 1,4-bis(ethenoxymethyl)cyclohexane, and 5-heptyloxolan-2-one), and it was found that these compounds produce significantly less soot compared to diesel fuel.

09 BIOMASS FUELS↗

An improved semi-global intrinsic kinetics model for high temperature carbon oxidation

Measurements of the oxidation rates of various forms of carbon (soot, graphite, coal char) have often shown an unexplained attenuation with increasing temperatures in the vicinity of 2000 K, even when accounting for diffusional transport limitations and gas-phase chemical effects (e.g. CO 2 dissociation). With the development of oxy-fuel combustion approaches for pulverized coal utilization with carbon capture, high particle temperatures are readily achieved in sufficiently oxygen-enriched environments. Here, in this work, a new semi-global intrinsic kinetics model for high temperature carbon oxidation is created by starting with a previously developed 5-step mechanism that was shown to reproduce all major known trends in carbon oxidation, except for its high temperature kinetic falloff, and incorporating a recently discovered surface oxide decomposition step. The predictions of this new model are benchmarked by deploying the kinetic model in a steady-state reacting particle code (SKIPPY) and comparing the simulated results against a carefully measured set of pulverized coal char combustion temperature measurements over a wide range of oxygen concentrations in N 2 and CO 2 environments. The results show that the inclusion of the spontaneous surface oxide decomposition reaction step significantly improves predictions at high particle temperatures. Furthermore, the simulations reveal that O atoms released from the oxide decomposition step enhance the radical pool in the near-surface region and within the particle interior itself. Incorporation of literature rates for O and OH reactions with the carbon surface results in a reduction in the predicted radical pool concentrations and a very minor enhancement of the overall carbon oxidation rate.

33 ADVANCED PROPULSION SYSTEMS↗

Machine learning and shallow groundwater chemistry to identify geothermal prospects in the Great Basin, USA

This study discovers various geothermal prospects in the Great Basin, USA based on shallow groundwater chemical (geochemical) data. The geochemical data are expected to include hidden (latent) information that is a proxy for geothermal prospectivity. We processed the sparse geochemical data in the Great Basin at 14,341 locations including 18 attributes. Next, a non-negative matrix factorization with customized k-means clustering is applied to the geochemical data matrix that automatically finds three hidden geothermal signatures representing modestly, moderately, and highly confident geothermal prospects. The algorithm also evaluated the probability of occurrence of these types of resources through the studied region. There is a consistency between regional geothermal prospectivity as estimated by our ML methodology and the traditional play fairway analysis conducted over a portion of the study area. We also identify the dominant data attributes associated with each signature. Finally, our ML analyses allow us to reconstruct attributes from sparse into continuous over the study domain. The predicted continuous attributes can be used for future detailed geothermal explorations in the Great Basin.

15 GEOTHERMAL ENERGY↗

Importance of viewing angle: Hotspot effect improves the ability of satellites to track terrestrial photosynthesis

The product of near-infrared reflectance of vegetation and photosynthetic active radiation (NIRvP) is a new tool for monitoring gross primary productivity (GPP) dynamics in terrestrial ecosystems, due to the discovered linear correlation between NIRvP and GPP. While remote sensing-based NIRvP is considerably influenced by sensor geometry, such geometry impacts on the NIRvP-GPP relationship remain underexplored. In this study, we calculate NIRvP using observations from the Deep Space Climate Observatory (DSCOVR) that provide unique hotspot observation geometry in which the sensor viewing angle coincides with the sun direction. We evaluated the linear correlation between NIRvP and GPP in both the common nadir direction and the special hotspot direction. The results indicate that NIRvP in the hotspot direction significantly outperforms that in the nadir direction for tracking GPP variations across different ecosystems from diurnal to daily scales. This conclusion is further supported by data from the MODerate resolution Imaging Spectroradiometer (MODIS) and simulations using the Soil Canopy Observation Photosynthesis Energy (SCOPE) model. Finally, our research highlights the value of using the unconventional hotspot-based sun-tracking satellite observations for a more accurate characterization of GPP dynamics in terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Advancing biological processing for valorization of plastic wastes

We report the useful applications of plastics are as significant as the problems associated with their disposal. Current waste management strategies are ineffective at preventing the flow of plastics into landfills, wastewater treatment, and the environment. Despite the importance of recycling technologies, most plastics are used for consumables and are discarded after limited usage. Moreover, only certain plastics are recycled, and those that are generally yield lower value products. Discovering alternative routes for valorizing plastic wastes is essential. Emerging research involves the use of biocatalysts (i.e., enzymes and microorganisms) to produce valuable products like specialty polymers, biosurfactants, and drug precursors from these feedstocks. These bioprocesses commonly integrate physio-chemical pretreatments (to generate biologically reactive intermediates) and biological upgrading (to convert intermediates to products). Herein, publications that explore plastic deconstruction technologies and bioprocesses are reviewed with an emphasis on plastic waste valorization. Understanding how microorganisms metabolize the intermediates of plastic degradation and manage their inhibitory effects is a prerequisite for engineering bioprocesses. For these heterogeneous wastes, a paradigm shift from axenic cultivation of microorganisms to cultivation of microbial consortia may benefit conversion efficiency and stress resilience. Thus, a summary is provided for metabolic pathways and constituent enzymes required to synthesize biofuels, biomaterials, and chemicals from biologically reactive intermediates. Colossal challenges associated with the use of plastics as feedstocks for direct biological processing highlight the need for integrating physical, chemical, and biological technologies.

59 BASIC BIOLOGICAL SCIENCES↗

Selenium tolerance, accumulation, localization and speciation in a Cardamine hyperaccumulator and a non-hyperaccumulator

Cardamine violifolia (family Brassicaceae ) is the first discovered selenium hyperaccumulator from the genus Cardamine with unique properties in terms of selenium accumulation, i.e., high abundance of selenolanthionine. In our study, a fully comprehensive experiment was conducted with the comparison of a non-hyperaccumulator Cardamine species, Cardamine pratensis , covering growth characteristics, chlorophyll fluorescence, spatial selenium/sulfur distribution patterns through elemental analyses (synchrotron-based X-Ray Fluorescence and ICP-OES) and speciation data through selenium K-edge micro X-ray absorption near-edge structure analysis (μXANES) and strong cation exchange (SCX)-ICP-MS. The results revealed remarkable differences in contrast to other selenium hyperaccumulators as neither Cardamine pecies showed evidence of growth stimulation by selenium. Also, selenite uptake was not inhibited by phosphate for either of the Cardamine species. Sulfate inhibited selenate uptake, but the two Cardamine species did not show any difference in this respect. However, μXRF derived speciation maps and selenium/sulfur uptake characteristics provided results that are similar to other formerly reported hyperaccumulator and non-hyperaccumulator Brassicaceae species. μXANES showed organic selenium, “C-Se-C”, in seedlings of both species and also in mature C. violifolia plants. In contrast, selenate-supplied mature C. pratensis contained approximately half “C-Se-C” and half selenate. SCX-ICP-MS data showed evidence of the lack of selenocystine in any of the Cardamine plant extracts. Thus, C. violifolia shows clear selenium-related physiological and biochemical differences compared to C. pratensis and other selenium hyperaccumulators.

Environmental Sciences & Ecology↗

Integrative investigation of dust emissions by dust storms and dust devils in North Africa

Dust aerosols in North Africa account for >50% of the global total; however dust emission areas are still unclear. Based on the analysis of dust storms simulated with the numerical Weather Research and Forecast (WRF) model, satellite aerosol index (AI), and the dust data observed at 300 meteorological stations over 20 years, the spatio-temporal distribution characteristics of dust storm, dust devil and AI are compared and analyzed. From this study, the results show that: 1) There are two dust emission mechanisms: the dynamically-dominated dust storm and thermally-dominated dust devil; 2) Dust storms occur most frequently in Spring and are concentrated in the areas of Grand Erg Occidental Desert to the Erg Chech-Adrar Desert, the northern part of Grand Erg Oriental, the Atouila Desert to the Ouarane Desert, the Mediterranean coast, the eastern side of Nubian Desert and Bodélé Depression; 3) Dust devils occur most frequently from April to August and are mainly concentrated in the central part of North Africa, especially in the southwest of Hoggar Mountains to the west of Air Mountains, the border area of Egypt - Sudan - Libya and the vicinity of Tibesti Plateau; 4) The spatio-temporal distribution of AI is correlated more with the dust devils emission whereas the annual average contributions by dust storms and dust devils are 61.3% and 38.7%, respectively. This study discovers a new area of dust emissions by dust devils, and provides a better explanation for the spatio-temporal distribution of AI in North Africa.

54 ENVIRONMENTAL SCIENCES↗

Investigation of pyruvic acid photolysis at the air-liquid interface as a source of aqueous secondary organic aerosols

Pyruvic acid (PA) is a ubiquitous 2-oxocarboxylic acid in the atmosphere. Its photochemical process at the air-liquid (a-l) interface has been suggested as an important source of aqueous secondary organic aerosols. Here, we investigated the photochemical reaction pathways of PA at the a-l interface using synchrotron-based vacuum ultraviolet single-photon ionization mass spectrometry (VUV SPI-MS) coupled with the System for Analysis at the Liquid Vacuum Interface (SALVI) microreactor. Results from mass spectral analysis and the determination of appearance energies (AEs) indicate that photolysis of PA can generate radicals, then they recombine with carboxylic acids and simple molecular oligomers. Furthermore, the preliminary products could form larger oligomers via radical reaction or esterification in the presence of hydroxyl and carboxyl functional groups. Mass spectral comparison shows that most photochemical reactions would complete within 4 h. The expanded photochemistry-driven reaction flowchart of PA is proposed based on the newly discovered products. Our results reveal that the interfacial PA photochemical reactions have different mechanisms from the bulk liquid due to the interfacial properties, such as molecular density, composition, and ion concentration. Our findings show that in situ mass spectral analysis with bright photon ionization is useful to elucidate the contribution of a-l interfacial reactions leading to aqSOA formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In-situ TEM observation of shear induced microstructure evolution in Cu-Nb alloy

Phase boundaries in multiphase alloys govern defect interaction and chemical intermixing across different phases during plastic deformation. Dynamic interaction of defects with phase boundaries in multiphase alloys, especially for immiscible alloys, has been topic of significant research interest in recent years. In this work, we describe a novel approach for carrying out in-situ TEM shear deformation to directly observe interfacial microstructural evolution of a Cu-Nb alloy. A unique double shear specimen geometry is microfabricated by a focused ion beam technique to apply shear deformation upon push loading inside the TEM. From the real-time observation, we discover that the phase boundary with a zigzag morphology effectively blocks stacking faults nucleated in a Cu grain from slipping into a Nb grain. Meanwhile, the Cu phase bears the most plastic deformation through slip or twinning mechanisms. This work sheds light on understanding the shear deformation and the behavior of phase boundaries in multiphase alloys during shear deformation.

36 MATERIALS SCIENCE↗

Drug discovery efforts at George Mason University

With over 39,000 students, and research expenditures in excess of $200 million, George Mason University (GMU) is the largest R1 (Carnegie Classification of very high research activity) university in Virginia. Mason scientists have been involved in the discovery and development of novel diagnostics and therapeutics in areas as diverse as infectious diseases and cancer. Below are highlights of the efforts being led by Mason researchers in the drug discovery arena. To enable targeted cellular delivery, and non-biomedical applications, Veneziano and colleagues have developed a synthesis strategy that enables the design of self-assembling DNA nanoparticles (DNA origami) with prescribed shape and size in the 10 to 100 nm range. The nanoparticles can be loaded with molecules of interest such as drugs, proteins and peptides, and are a promising new addition to the drug delivery platforms currently in use. The investigators also recently used the DNA origami nanoparticles to fine tune the spatial presentation of immunogens to study the impact on B cell activation. These studies are an important step towards the rational design of vaccines for a variety of infectious agents. To elucidate the parameters for optimizing the delivery efficiency of lipid nanoparticles (LNPs), Buschmann, Paige and colleagues have devised methods for predicting and experimentally validating the pKa of LNPs based on the structure of the ionizable lipids used to formulate the LNPs. These studies may pave the way for the development of new LNP delivery vehicles that have reduced systemic distribution and improved endosomal release of their cargo post administration. To better understand protein-protein interactions and identify potential drug targets that disrupt such interactions, Luchini and colleagues have developed a methodology that identifies contact points between proteins using small molecule dyes. The dye molecules noncovalently bind to the accessible surfaces of a protein complex with very high affinity, but are excluded from contact regions. When the complex is denatured and digested with trypsin, the exposed regions covered by the dye do not get cleaved by the enzyme, whereas the contact points are digested. The resulting fragments can then be identified using mass spectrometry. The data generated can serve as the basis for designing small molecules and peptides that can disrupt the formation of protein complexes involved in disease processes. For example, using peptides based on the interleukin 1 receptor accessory protein (IL-1RAcP), Luchini, Liotta, Paige and colleagues disrupted the formation of IL-1/IL-R/IL-1RAcP complex and demonstrated that the inhibition of complex formation reduced the inflammatory response to IL-1B. Working on the discovery of novel antimicrobial agents, Bishop, van Hoek and colleagues have discovered a number of antimicrobial peptides from reptiles and other species. DRGN-1, is a synthetic peptide based on a histone H1-derived peptide that they had identified from Komodo Dragon plasma. DRGN-1 was shown to disrupt bacterial biofilms and promote wound healing in an animal model. The peptide, along with others, is being developed and tested in preclinical studies. Other research by van Hoek and colleagues focuses on in silico antimicrobial peptide discovery, screening of small molecules for antibacterial properties, as well as assessment of diffusible signal factors (DFS) as future therapeutics. The above examples provide insight into the cutting-edge studies undertaken by GMU scientists to develop novel methodologies and platform technologies important to drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗

Root exudate lipids: Uncovering chemodiversity and carbon stability potential

Root-derived carbon has been shown to contribute more to soil carbon stocks than aboveground litter. Yet the molecular chemodiversity of root exudates remains poorly understood due to limited characterization and annotation. In this study, we characterized the molecular chemodiversity and production of metabolites and lipids in root exudates from field grown mature tall wheatgrass (Thinopyrum ponticum). We discovered a diversity of lipids, including substantial levels of triacylglycerols (∼19 μg/g fresh root per min), fatty acyls, sphingolipids, sterol lipids, and glycerophospholipids, some of which have not been previously documented in root exudates. By integrating tandem mass spectral library searching and deep learning-based chemical class assignment, our metabo-lipidomics approach significantly expanded the known molecular diversity of root exudates. Rates of lipid derived carbon production were approximately double that of polar metabolites (lipids: 81.52 ± 13.81 vs polar metabolites: 38.41 ± 5.93 μg C g −1 fresh root mass min −1 ) with an order of magnitude higher carbon to nitrogen ratios (lipids: 459 ± 90 vs polar metabolites: 14.40 ± 0.58). Exudate lipids displayed highly negative nominal oxidation state of carbon (−1.182 to −1.909), indicating that these compounds may be less favorable for microbial decomposition. Together our results suggest the potential of root exudate lipids to contribute to stable carbon pools in soil, supporting long-term carbon storage. This work advances understanding of plant-derived lipid inputs to soil and underscores the need for future studies on the functional roles of lipids in shaping root-microbe-soil interactions, microbial activity, soil structure, and nutrient availability – contributing to soil health.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Peptides from human BNIP5 and PXT1 and non-native binders of pro-apoptotic BAK can directly activate or inhibit BAK-mediated membrane permeabilization

Apoptosis is important for development and tissue homeostasis, and its dysregulation can lead to diseases, including cancer. As an apoptotic effector, BAK undergoes conformational changes that promote mitochondrial outer membrane disruption, leading to cell death. This is termed “activation” and can be induced by peptides from the human proteins BID, BIM, and PUMA. To identify additional peptides that can regulate BAK, we used computational protein design, yeast surface display screening, and structure-based energy scoring to identify 10 diverse new binders. We discovered peptides from the human proteins BNIP5 and PXT1 and three non-native peptides that activate BAK in liposome assays and induce cytochrome c release from mitochondria. Crystal structures and binding studies reveal a high degree of similarity among peptide activators and inhibitors, ruling out a simple function-determining property. Our results shed light on the vast peptide sequence space that can regulate BAK function and will guide the design of BAK-modulating tools and therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗

Crystal structure of Escherichia coli thiamine pyrophosphate-sensing riboswitch in the apo state

The thiamine pyrophosphate (TPP)-sensing riboswitch is one of the earliest discovered and most widespread riboswitches. Numerous structural studies have been reported for this riboswitch bound with various ligands. However, the ligand-free (apo) structure remains unknown. Here, we report a 3.1 Å resolution crystal structure of Escherichia coli TPP riboswitch in the apo state, which exhibits an extended, Y-shaped conformation further supported by small-angle X-ray scattering data and driven molecular dynamics simulations. The loss of ligand interactions results in helical uncoiling of P5 and disruption of the key tertiary interaction between the sensory domains. Opening of the aptamer propagates to the gene-regulatory P1 helix and generates the key conformational flexibility needed for the switching behavior. Much of the ligand-binding site at the three-way junction is unaltered, thereby maintaining a partially preformed pocket. Together, these results paint a dynamic picture of the ligand-induced conformational changes in TPP riboswitches that confer conditional gene regulation.

59 BASIC BIOLOGICAL SCIENCES↗