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At least 163 records · Page 9

Phage K gp102 Drives Temperature-Sensitive Antibacterial Activity on USA300 MRSA

There is widespread interest in using obligately lytic bacteriophages (“phages”) to treat human bacterial infections. Among Staphylococcus aureus infections, the USA300 lineage is a frequent cause of invasive disease. We observed that phage K, a model S. aureus myophage, exhibits temperature-sensitive growth on USA300 strains, with the wild-type phage providing poorer growth suppression in broth and forming smaller and fainter plaques at 37 °C vs. 30 °C. We isolated 65 mutants of phage K that had improved plaquing characteristics at 37 °C when compared to the parental phage. In all 65 mutants, this phenotype was attributable to loss-of-function (LoF) mutations in gp102, which encodes a protein of unknown function that has homologs only among the Herelleviridae (SPO1-like myophages infecting gram-positive bacteria). Additional experiments with representative mutants consistently showed that the temperature-sensitive plaque phenotype was specific to USA300 MRSA strains and that Gp102 disruption was correlated with improved suppression of bacterial growth in broth and improved antibacterial activity in a mouse model of upper respiratory tract infection. The same genotype and in vitro phenotypes could be replicated in close relatives of phage K. Gp102 disruption did not have a detectable effect on adsorption but did delay cell culture lysis relative to wild-type under permissive infection conditions, suggesting that gp102 conservation might be maintained by selective pressure for more rapid replication. Expression of gp102 on a plasmid was toxic to both an MSSA and a USA300 MRSA strain. Molecular modeling predicts a protein with two helix-turn-helix domains that displays some similarity to DNA-binding proteins such as transcription factors. While its function remains unclear, gp102 is a conserved gene that is important to the infection process of Kayvirus phages, and it appears that the manner in which USA300 strains defend against them at 37 °C can be overcome by gp102 LoF mutations.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamical experiments on models of colliding disk galaxies

Collisions between galaxies can induce large morphological changes in the participants and, in the case of colliding disk galaxies, bridges and tails are often formed. Observations of such systems indicate a wide variation in color (see Larson and Tinsley, 1978) and that some of the particpants are experiencing enhanced rates of star formation, especially in their central regions (Bushouse 1986, 1987; Kennicutt et al., 1987, Bushouse, Lamb, and Werner, 1988). Here the authors describe progress made in understanding some of the dynamics of interacting galaxies using N-body stellar dynamical computer experiments, with the goal of extending these models to include a hydrodynamical treatment of the gas so that a better understanding of globally enhanced star formation will eventually be forthcoming. It was concluded that close interactions between galaxies can produce large perturbations in both density and velocity fields. The authors measured, via computational experiments that represent a galaxy's stars, average radial velocity flows as large as 100 km/sec and 400 percent density increases. These can occur in rings that move outwards through the disk of a galaxy, in roughly homologous inflows toward the nucleus, and in off center, non-axisymmetric regions. Here the authors illustrate where the gas is likely to flow during the early stages of interaction and in future work they plan to investigate the fate of the gas more realistically by using an N-body/Smoothed Particle Hydrodynamics code to model both the stellar and gaseous components of a disk galaxy during a collision. Specifically, they will determine the locations of enhanced gas density and the strength and location of shock fronts that form during the interaction.

Gerber, Richard A.↗

Cryogenic and Temperature-Dependent Photoelectron Spectroscopy of Metal Complexes

Negative ion photoelectron spectroscopy (NIPES) coupled with electrospray ionization (ESI) has been proved to be a powerful gas-phase spectroscopic tool for characterizing electronic structures and chemical bonding of a variety of cluster anions and corresponding neutral radicals involved in the condensed phase reactions and transformations. Since the acquisition of cryogenic and temperature-controlling capabilities, broader range of research scope has been covered. This review summarizes our recent investigations on metal complexes employing cryogenic ESI-NIPES that provide us essential information towards understanding complicated condensed phase reactions including hydrocarbon activations and electron transfer reactions, and afford us spectroscopic probe of highly reactive transient species and intimate redox pairs. Special attention has been drawn to connect gas phase photodetachment processes with solution phase redox reactions. Photodetachment of transition metal-EDTA complexes has been systematically investigated to model the sequential oxidation reactions of these species in solutions. The obtained gas phase electron affinity (EA) is compared with the solution redox potential (E1/2) and the metal ionization potential (IP) for several series of homologous metal complexes to emphasize their intrinsic correlations with deviations being largely modulated by different degrees of ligand participations.

Yuan, Qinqin↗

PlasmidHostFinder: Prediction of Plasmid Hosts Using Random Forest

Plasmids play a major role facilitating the spread of antimicrobial resistance between bacteria. Understanding the host range and dissemination trajectories of plasmids is critical for surveillance and prevention of antimicrobial resistance. Identification of plasmid host ranges could be improved using automated pattern detection methods compared to homology-based methods due to the diversity and genetic plasticity of plasmids. In this study, we developed a method for predicting the host range of plasmids using machine learning—specifically, random forests. We trained the models with 8,519 plasmids from 359 different bacterial species per taxonomic level; the models achieved Matthews correlation coefficients of 0.662 and 0.867 at the species and order levels, respectively. Our results suggest that despite the diverse nature and genetic plasticity of plasmids, our random forest model can accurately distinguish between plasmid hosts. This tool is available online through the Center for Genomic Epidemiology (https://cge.cbs.dtu.dk/services/PlasmidHostFinder/).

59 BASIC BIOLOGICAL SCIENCES↗

Model of Mixing Layer With Multicomponent Evaporating Drops

A mathematical model of a three-dimensional mixing layer laden with evaporating fuel drops composed of many chemical species has been derived. The study is motivated by the fact that typical real petroleum fuels contain hundreds of chemical species. Previously, for the sake of computational efficiency, spray studies were performed using either models based on a single representative species or models based on surrogate fuels of at most 15 species. The present multicomponent model makes it possible to perform more realistic simulations by accounting for hundreds of chemical species in a computationally efficient manner. The model is used to perform Direct Numerical Simulations in continuing studies directed toward understanding the behavior of liquid petroleum fuel sprays. The model includes governing equations formulated in an Eulerian and a Lagrangian reference frame for the gas and the drops, respectively. This representation is consistent with the expected volumetrically small loading of the drops in gas (of the order of 10 3), although the mass loading can be substantial because of the high ratio (of the order of 103) between the densities of liquid and gas. The drops are treated as point sources of mass, momentum, and energy; this representation is consistent with the drop size being smaller than the Kolmogorov scale. Unsteady drag, added-mass effects, Basset history forces, and collisions between the drops are neglected, and the gas is assumed calorically perfect. The model incorporates the concept of continuous thermodynamics, according to which the chemical composition of a fuel is described probabilistically, by use of a distribution function. Distribution functions generally depend on many parameters. However, for mixtures of homologous species, the distribution can be approximated with acceptable accuracy as a sole function of the molecular weight. The mixing layer is initially laden with drops in its lower stream, and the drops are colder than the gas. Drop evaporation leads to a change in the gas-phase composition, which, like the composition of the drops, is described in a probabilistic manner

Bellan, Josette↗

The Scaling of Coronal Models from One Star to Another

The requirements that must be met in order that stationary numerical corona models can be scaled from one star to another are discussed. A corona model is a solution of the conservation equations for mass, momentum, and energy, subject to appropriate boundary conditions, and of the equation of state. In general, the mass M and radius R of the star enter these equations and boundary conditions as free parameters. A given solution can be scaled to other stars only if all equations can be rewritten in such a form that M and R do no longer appear explicitly as free parameters, but only implicitly as scaling factors of the variables. An adequate means to find these scaling factors is a homologous transformation: one multiplies all variables and parameters by separate constants (i.e., scaling factors) and requires that the equations and boundary conditions remain valid. This leads to a set of nonlinear relations between the transformation constants. Only if in this set the two constants associated with M and R can be chosen independently, can a given numerical corona model be scaled to arbitrary stars.

Hammer, R.↗

Dynamic Profiling of β-Coronavirus 3CL Mpro Protease Ligand-Binding Sites

β-coronavirus (CoVs) alone has been responsible for three major global outbreaks in the 21st century. The current crisis has led to an urgent requirement to develop therapeutics. Even though a number of vaccines are available, alternative strategies targeting essential viral components are required as a backup against the emergence of lethal viral variants. One such target is the main protease (Mpro) that plays an indispensable role in viral replication. The availability of over 270 Mpro X-ray structures in complex with inhibitors provides unique insights into ligand–protein interactions. Herein, we provide a comprehensive comparison of all nonredundant ligand-binding sites available for SARS-CoV2, SARS-CoV, and MERS-CoV Mpro. Extensive adaptive sampling has been used to investigate structural conservation of ligand-binding sites using Markov state models (MSMs) and compare conformational dynamics employing convolutional variational auto-encoder-based deep learning. Our results indicate that not all ligand-binding sites are dynamically conserved despite high sequence and structural conservation across β-CoV homologs. This highlights the complexity in targeting all three Mpro enzymes with a single pan inhibitor.

59 BASIC BIOLOGICAL SCIENCES↗

BioSentinel ISS Control Experiment Investigation Summary Form

The main science objective of BioSentinel is to develop biosensors to study the effects of the space radiation environment on biological organisms. Given its similarities to human cells, we decided to use the budding yeast Saccharomyces cerevisiae. Yeast cells share homology to human cells, particularly in the response to DNA damage caused by ionizing radiation. Most importantly, yeast cells can be desiccated and survive in that form for long periods of time. Thus, budding yeast is the ideal model organism for long-term experiments in preparation for future manned missions to deep space. In addition to the ISS mission, our biosensors will fly in a nanosatellite designed for deep space, which is manifested to fly as a secondary payload onboard NASA’s Artemis-1 rocket.

BioSentinel↗

Potential virus-mediated nitrogen cycling in oxygen-depleted oceanic waters

Viruses play an important role in the ecology and biogeochemistry of marine ecosystems. Beyond mortality and gene transfer, viruses can reprogram microbial metabolism during infection by expressing auxiliary metabolic genes (AMGs) involved in photosynthesis, central carbon metabolism, and nutrient cycling. While previous studies have focused on AMG diversity in the sunlit and dark ocean, less is known about the role of viruses in shaping metabolic networks along redox gradients associated with marine oxygen minimum zones (OMZs). Here, we analyzed relatively quantitative viral metagenomic datasets that profiled the oxygen gradient across Eastern Tropical South Pacific (ETSP) OMZ waters, assessing whether OMZ viruses might impact nitrogen (N) cycling via AMGs. Identified viral genomes encoded six N-cycle AMGs associated with denitrification, nitrification, assimilatory nitrate reduction, and nitrite transport. The majority of these AMGs (80%) were identified in T4-like Myoviridae phages, predicted to infect Cyanobacteria and Proteobacteria, or in unclassified archaeal viruses predicted to infect Thaumarchaeota. Four AMGs were exclusive to anoxic waters and had distributions that paralleled homologous microbial genes. Together, these findings suggest viruses modulate N-cycling processes within the ETSP OMZ and may contribute to nitrogen loss throughout the global oceans thus providing a baseline for their inclusion in the ecosystem and geochemical models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An optimal structure for a 34-meter millimeter-wave center-fed BWG antenna: The Cross-Box concept

An approach to the design of the planned NASA/JPL 34 m elevation-over-azimuth (Az-El) antenna structure at the Venus site (DSS-13) is presented. The antenna structural configuration accommodates a large (2.44 m) beam waveguide (BWG) tube centrally routed through the reflector-alidade structure, an elevation wheel design, and an optimal structural geometry. The design encompasses a cross-box elevation wheel-reflector base substructure that preserves homology while satisfying many constraints, such as structure weight, surface tolerance, stresses, natural frequency, and various functional constraints. The functional requirements are set to ensure that microwave performance at millimeter wavelengths is adequate. The cross-box configuration was modeled, optimized, and found to satisfy all DSN HEF baseline antenna specifications. In addition, the structure design was conceptualized and analyzed with an emphasis on preserving the structure envelope and keeping modifications relative to the HEF antennas to a minimum, thus enabling the transferability of the BWG technology for future retrofitting. Good performance results were obtained.

Chuang, K. L.↗

cTULIP: application of a human-based RNA-seq primary tumor classification tool for cross-species primary tumor classification in canine

The domestic dog, Canis familiaris, is quickly gaining traction as an advantageous model for use in the study of cancer, one of the leading causes of death worldwide. Naturally occurring canine cancers share clinical, histological, and molecular characteristics with the corresponding human diseases. In this study, we take a deep-learning approach to test how similar the gene expression profile of canine glioma and bladder cancer (BLCA) tumors are to the corresponding human tumors. We likewise develop a tool for identifying misclassified or outlier samples in large canine oncological datasets, analogous to that which was developed for human datasets. We test a number of machine learning algorithms and found that a convolutional neural network outperformed logistic regression and random forest approaches. We use a recently developed RNA-seq-based convolutional neural network, TULIP, to test the robustness of a human-data-trained primary tumor classification tool on cross-species primary tumor prediction. Our study ultimately highlights the molecular similarities between canine and human BLCA and glioma tumors, showing that protein-coding one-to-one homologs shared between humans and canines, are sufficient to distinguish between BLCA and gliomas. The results of this study indicate that using protein-coding one-to-one homologs as the features in the input layer of TULIP performs good primary tumor prediction in both humans and canines. Furthermore, our analysis shows that our selected features also contain the majority of features with known clinical relevance in BLCA and gliomas. Our success in using a human-data-trained model for cross-species primary tumor prediction also sheds light on the conservation of oncological pathways in humans and canines, further underscoring the importance of the canine model system in the study of human disease.

60 APPLIED LIFE SCIENCES↗

Reductive amination cascades in cell‐free and resting whole cell formats for valorization of lignin deconstruction products

Abstract The selective introduction of amine groups within deconstruction products of lignin could provide an avenue for valorizing waste biomass while achieving a green synthesis of industrially relevant building blocks from sustainable sources. Here, we built and characterized enzyme cascades that create aldehydes and subsequently primary amines from diverse lignin‐derived carboxylic acids using a carboxylic acid reductase (CAR) and an ω‐transaminase (TA). Unlike previous studies that have paired CAR and TA enzymes, here we examine multiple homologs of each of these enzymes and a broader set of candidate substrates. In addition, we compare the performance of these systems in cell‐free and resting whole‐cell biocatalysis formats using the conversion of vanillate to vanillyl amine as model chemistry. We also demonstrate that resting whole cells can be recycled for multiple batch reactions. We used the knowledge gained from this study to produce several amines from carboxylic acid precursors using one‐pot biocatalytic reactions, several of which we report for the first time. These results expand our knowledge of these industrially relevant enzyme families to new substrates and contexts for environmentally friendly and potentially low‐cost synthesis of diverse aryl aldehydes and amines.

Biotechnology & Applied Microbiology↗

Assessing the Impacts of Conformational Fluxionality on Copper(II/I) Electron Transfer Self-Exchange

Typical Cu(II/I) complexes exhibit hallmark structural changes during their electron transfer (ET) reactions that result from the (pseudo) Jahn-Teller distortions and changes in polarizability inherent to their d 10 / d 9 configurations. Given that such structural changes incur large reorganization energy penalties, slow the rates of ET are characteristic of these compounds. Notwithstanding, we recently reported a set of Cu(II/I) complexes that undergo significant and well-defined structural changes during their redox reactions yet exhibit rapid (> 10 5 M ‒1 s ‒1 ) ET self-exchange rate constants ( k 11 ). To explain these results we proposed a pre-equilibrium model in which inherent conformational fluxionality in one of the two oxidation states provides access to pathways involving lower reorganization energies during the ET event. Herein we report our results testing this hypothesis through the preparation and study of a homologous series of compounds exhibiting varying extents of con-formational fluxionality in the Cu(I) state. We characterize these compounds electrochemically, structurally, and by varia-ble temperature NMR spectroscopy to provide experimental evidence for increase fluxionality across the series. We then correlate the trend with increasing k 11 through NMR linewidth broadening experiments, further taking care to define the impacts of solvent impurities therein. Finally, the nature of the conformational rearrangements, and their relation to increased k 11 are explored computationally to reveal differential Boltzmann populations of conformers across the series. The cumulative results of these studies support a previously underappreciated strategy for overcoming barriers to slow ET kinetics: via the incorporation of conformational fluxionality.

Singh, Aditi↗

The spatial and temporal expression of Ch-en, the engrailed gene in the polychaete Chaetopterus, does not support a role in body axis segmentation

We are interested in understanding whether the annelids and arthropods shared a common segmented ancestor and have approached this question by characterizing the expression pattern of the segment polarity gene engrailed (en) in a basal annelid, the polychaete Chaetopterus. We have isolated an en gene, Ch-en, from a Chaetopterus cDNA library. Genomic Southern blotting suggests that this is the only en class gene in this animal. The predicted protein sequence of the 1.2-kb cDNA clone contains all five domains characteristic of en proteins in other taxa, including the en class homeobox. Whole-mount in situ hybridization reveals that Ch-en is expressed throughout larval life in a complex spatial and temporal pattern. The Ch-en transcript is initially detected in a small number of neurons associated with the apical organ and in the posterior portion of the prototrochophore. At later stages, Ch-en is expressed in distinct patterns in the three segmented body regions (A, B, and C) of Chaetopterus. In all segments, Ch-en is expressed in a small set of segmentally iterated cells in the CNS. In the A region, Ch-en is also expressed in a small group of mesodermal cells at the base of the chaetal sacs. In the B region, Ch-en is initially expressed broadly in the mesoderm that then resolves into one band/segment coincident with morphological segmentation. The mesodermal expression in the B region is located in the anterior region of each segment, as defined by the position of ganglia in the ventral nerve cord, and is involved in the morphogenesis of segment-specific feeding structures late in larval life. We observe banded mesodermal and ectodermal staining in an anterior-posterior sequence in the C region. We do not observe a segment polarity pattern of expression of Ch-en in the ectoderm, as is observed in arthropods. Copyright 2001 Academic Press.

Non-NASA Center↗

Two-Dimensional Energy Histograms as Features for Machine Learning to Predict Adsorption in Diverse Nanoporous Materials

A major obstacle for machine learning (ML) in chemical science is the lack of physically informed feature representations that provide both accurate prediction and easy interpretability of the ML model. In this work, we describe adsorption systems using novel two-dimensional energy histogram (2D-EH) features, which are obtained from the probe-adsorbent energies and energy gradients at grid points located throughout the adsorbent. The 2D-EH features encode both energetic and structural information of the material and lead to highly accurate ML models (coefficient of determination R2 ~ 0.94–0.99) for predicting single-component adsorption capacity in metal–organic frameworks (MOFs). Here, we consider the adsorption of spherical molecules (Kr and Xe), linear alkanes with a wide range of aspect ratios (ethane, propane, n-butane, and n-hexane), and a branched alkane (2,2-dimethylbutane) over a wide range of temperatures and pressures. The interpretable 2D-EH features enable the ML model to learn the basic physics of adsorption in pores from the training data. We show that these MOF-data-trained ML models are transferrable to different families of amorphous nanoporous materials. We also identify several adsorption systems where capillary condensation occurs, and ML predictions are more challenging. Nevertheless, our 2D-EH features still outperform structural features including those derived from persistent homology. The novel 2D-EH features may help accelerate the discovery and design of advanced nanoporous materials using ML for gas storage and separation in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Genomic adaptations of the green alga Dunaliella salina to life under high salinity

Life in high salinity environments poses challenges to cells in a variety of ways: maintenance of ion homeostasis and nutrient acquisition, often while concomitantly enduring saturating irradiances. Dunaliella salina has an exceptional ability to thrive even in saturated brine solutions. This ability has made it a model organism for studying responses to abiotic stress factors. Here we describe the occurrence of unique gene families, expansion of gene families, or gene losses that might be linked to osmoadaptive strategies. We discovered multiple unique genes coding for several of the homologous superfamily of the Ser-Thr-rich glycosyl-phosphatidyl-inositol-anchored membrane family and of the glycolipid 2-alpha-mannosyltransferase family, suggesting that such components on the cell surface are essential to life in high salt. Gene expansion was found in families that participate in sensing of abiotic stress and signal transduction in plants. One example is the patched family of the Sonic Hedgehog receptor proteins, supporting a previous hypothesis that plasma membrane sterols are important for sensing changes in salinities in D. salina. We also investigated genome-based capabilities regarding glycerol metabolism and present an extensive map for core carbon metabolism. We postulate that a second broader glycerol cycle exists that also connects to photorespiration, thus extending the previously described glycerol cycle. Further genome-based analysis of isoprenoid and carotenoid metabolism revealed duplications of genes for 1-deoxy-D-xylulose-5-phosphate synthase (DXS) and phytoene synthase (PSY), with the second gene copy of each enzyme being clustered together. Moreover, we identified two genes predicted to code for a prokaryotic-type phytoene desaturase (CRTI), indicating that D. salina may have eukaryotic and prokaryotic elements comprising its carotenoid biosynthesis pathways. In brief, our genomic data provide the basis for further gene discoveries regarding sensing abiotic stress, the metabolism of this halophilic alga, and its potential in biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗

Shock Connectivity and the Late Cycle 24 Solar Energetic Particle Events in July and September 2017

As solar activity steadily declined toward the cycle 24 minimum in the early months of 2017, the expectation for major solar energetic particle (SEP) events diminished with the sunspot number. It was thus surprising (though not unprecedented) when a new, potentially significant active region rotated around the East limb in early July that by midmonth was producing a series of coronal eruptions, reaching a crescendo around 23 July. This series, apparently associated with the birth of a growing pseudostreamer, produced the largest SEP event(s) seen since the solar maximum years. Activity abated with the decay of the active region, but a second episode of magnetic flux emergence in the same area in early September initiated a new round of eruptions. The western longitude of the erupting region, together with its similar coronal setting in both cases, resulted in a set of nearly homologous multipoint SEP event periods at Earth, Solar TErrestrial RElations Observatory-A and Mars (Mars Atmosphere and Volatile EvolutioN) for July and September 2017. We use a combination of WSA-ENLIL-cone heliospheric simulation results, together with SEPMOD SEP event modeling, to illustrate how the event similarities at the three observer sites can be understood from their relative positions and their connectivities to the generated interplanetary shocks.

Luhmann, J. G.↗

Structure and properties of densified silica glass: characterizing the order within disorder

The broken symmetry in the atomic-scale ordering of glassy versus crystalline solids leads to a daunting challenge to provide suitable metrics for describing the order within disorder, especially on length scales beyond the nearest neighbor that are characterized by rich structural complexity. Here, we address this challenge for silica, a canonical network-forming glass, by using hot versus cold compression to (i) systematically increase the structural ordering after densification and (ii) prepare two glasses with the same high-density but contrasting structures. The structure was measured by high-energy X-ray and neutron diffraction, and atomistic models were generated that reproduce the experimental results. The vibrational and thermodynamic properties of the glasses were probed by using inelastic neutron scattering and calorimetry, respectively. Traditional measures of amorphous structures show relatively subtle changes upon compacting the glass. The method of persistent homology identifies, however, distinct features in the network topology that change as the initially open structure of the glass is collapsed. The results for the same high-density glasses show that the nature of structural disorder does impact the heat capacity and boson peak in the low-frequency dynamical spectra. Densification is discussed in terms of the loss of locally favored tetrahedral structures comprising oxygen-decorated SiSi 4<:sub> tetrahedra.

36 MATERIALS SCIENCE↗