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At least 505 records · Page 28

Multi-omics data resource: Data package 23 (Pck023)

The data package consists of isolated pancreatic islets from adult male C57BL6/J mice treated with IL-1β + IFNγ, IL-1β + IFNγ + NMMA, or NMMA alone for 18 h and submitted for scRNA-seq. This study focused on the cell-type-specific effects of nitric oxide signaling in islets and characterized the heterogeneity of responses. Data contributors: Jennifer S Stancill & John A Corbett: Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA Data repository: GSE183010 Publication: 10.1093/function/zqab063

Sarkar, Soumyadeep [Pacific Northwest National Lab↗

Multi-omics data resource: Data package 24 (Pck024)

The data package consists of isolated pancreatic islets from 3 human donors treated with IL-1β, IFNγ or IL-1β + IFNγ for 6 h and IL-1β, IFNγ, IL-1β + IFNγ, IL-1β + IFNγ + NMMA or NMMA for 18 h and submitted for scRNA-seq. This study examines cytokine-stimulated changes in gene expression in human islets using single-cell RNA sequencing. Data contributors: Jennifer S Stancill & John A Corbett: Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA Data repository: GSE251730 Publication: 10.1093/function/zqae015

Sarkar, Soumyadeep [Pacific Northwest National Lab↗

MCPC Characterization Round 1

Characterization data for the MCPC LDRD Agile investment is collected in multiple rounds. Contained herein is data from Round 1 in which eleven distinct samples and one control sample are characterized by five modalities: EBSD, HARDNESS, OPTICAL, SEM, and ULTRASONIC. Data is organized in subdirectories for the five modalities and each one modality containing subdirectories for the datasets and other information.

36 MATERIALS SCIENCE↗

Prediction of non-intuitive metabolic targets with bayesian metabolic control analysis to improve 3-hydroxypropionic acid production in Aspergillus niger

Development of efficient bioconversion processes is limited by the ability to predictably improve metabolic flux. Here we deployed Bayesian Metabolic Control Analysis as a platform to integrate multi-omics data with metabolic modeling and evaluated its ability to predict genetic interventions that improve metabolic flux. Global Metabolomics and proteomics data was collected from 17 Aspergillus niger strains engineered to produce the platform biochemical 3-hydroxypropionic acid from which seven actional genetic interventions were predicted from significant flux control coefficients. Of the suggested genetic interventions, two were present within the intuitively designed strains used for training (malonic semialdehyde dehydrogenase and pyruvate carboxylase) while five predicted targets were present within non-intuitive areas of the metabolic network including 5-formyltetrahydrofolate deformylase and four mitochondrial enzymes, alcohol dehydrogenase, succinyl-CoA ligase, aspartate aminotransferase, and malate dehydrogenase. Six of the targets were validated in the highest performing 3-HP strain used for multi-omics data generation which contained a prior disruption of the highest scoring target malonic semialdehyde dehydrogenase. Predicted directional perturbation of five of the six tested targets significantly improved titer and rate of 3-HP production and two significantly improved yield. The greatest improvements were observed following disruption of the non-intuitive target succinyl-CoA ligase which increased titer by 39% and yield by 29% (to 20.4 g/L 3-HP and 0.31 g 3-HP/g glucose) over the strains used for training. This study demonstrates the utility of Bayesian Metabolic Control Analysis and highlights the ability to predict meaningful genetic targets in unexpected areas of metabolism to improve engineered strains for bioconversion.

3-hydroxypropionic acid↗

Sampling Microbial Dynamics in the Salish Sea Estuary: Evaluating Methods to Capture Cyanobacteria and Cyanophage

Introduction: Picocyanobacteria from the genera Prochlorococcus and Synechococcus thrive across the globe in aquatic environments, have relatively small genomes, and have growth dynamics regulated by both viral interactions and abiotic conditions, making them excellent model organisms for exploring host-pathogencoevolution. Methods: We developed and refined methods to sample and sequence cyanobacteria, cyanophages, and measured features of their abiotic environment. Results: The protocol described herein can successfully discriminate large-cell eukaryotic organisms, but size fractionation of picocyanobacteria appears to be affected by the presence of free DNA, multicellular structures, and abundant tycheposons. Our preferred final protocol from this exploratory effort included a combination of in-line and single vacuum flask filtrations, which reduced filtration processing time by over threefold in some cases compared to other tested methods, such as a fully in-line sequence or in-site filtrations. We successfully extracted an average of approximately 400–1200 ng for all filter fractions, with some variations between kits. Discussion: The protocol described herein can successfully discriminate large-cell eukaryotic organisms, but size fractionation of picocyanobacteria appears to be affected by the presence of free DNA, multicellular structures, and abundant tycheposons.

Salish Sea↗

Prescribing the aerosol effective radiative forcing in the Simple Cloud-Resolving E3SM Atmosphere Model v1

Aerosol effective radiative forcing critically influences climate projections but remains poorly constrained. Using the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) v1 configuration, we assess the sensitivity of the radiative forcing due to anthropogenic aerosol changes using a simplified prescribed aerosol scheme (SPA) derived from E3SM v3. Nudged simulations at 3 and 12 km horizontal grid spacings reveal a more negative aerosol forcing than the reference 100 km E3SM v3 whence the SPA properties are derived. The resulting globally averaged aerosol forcing signal is largely due to aerosol–cloud interactions and exhibits little overall resolution sensitivity, while hints of resolution sensitivity appear regionally between the 3 and 12 km runs. While the default SPA scheme overestimates cloud droplet dependence on aerosols, parameterization adjustments in the activation process reconcile forcing estimates with the reference model. Our results demonstrate the ability to use a prescribed aerosol scheme to hold aerosol forcing to a desired strength across resolutions.

54 ENVIRONMENTAL SCIENCES↗

CO 2 in Ionene–Ionic Liquid Composite Membranes

Abstract Ionene – ionic liquid (IL) composites are promising materials for CO 2 separation, yet a molecular‐level understanding of their structure and its impact on CO 2 speciation, solubility, rotation, and diffusivity remains unclear. Herein, using multimodal nuclear magnetic resonance (NMR), time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS), atomic force microscopy (AFM), and molecular dynamics (MD) simulations, we reveal that the composites contain IL‐rich domains extending across hundreds of nanometres within the ionene matrix, and these bicontinuous domains span the entire membrane depth. CO 2 also absorbs into the ionene matrix, with the distribution between two CO 2 species varying with temperature and time. The rotational correlation times of these two species are on the timescale of 0.1 and 1 ns, respectively. As IL content increases, the ionic domains expand, resulting in higher CO 2 solubility due to enhanced molecular dynamics and increased free volume in both ionene backbones and IL‐rich regions. Although CO 2 diffusion in the membranes is an order of magnitude slower than in bulk IL, the activation energy for CO 2 diffusion remains comparable. Ionene‐IL composites represent a promising platform for designing CO 2 separation membranes, offering enhanced CO 2 diffusion and selectivity through IL‐rich domains, and increased CO 2 solubility and mechanical integrity from the ionene matrix.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterization of Gas-Phase Native(-like) Proteins Using Structures for Lossless Ion Manipulations

High-resolution mobility-based ion separations in Structures for Lossless Ion Manipulations (SLIM) have been useful for ion mobility separations for a variety of molecular classes in the gas phase. Here, in this study, we present multipass SLIM separations for gas-phase proteins in their near-native state exhibiting charge-state-dependent arrival time distributions using carbonic anhydrase (29 kDa), alcohol dehydrogenase (148 kDa), and apo-transferrin (79 kDa). The experimental CCS values were obtained from calibration curves for the arrival times of Agilent Tune Mix ions. For multipass separations, the ATDs were converted to CCS values by deconvoluting the multipass arrival times into accurate single-pass values amenable to the single-pass calibration curves. Mass spectra of carbonic anhydrase (CA) showed three different charge states (z = 9+ to 11+). Their corresponding mobility peaks were baseline-separated by using 8-m single-pass separations. When compared to the corresponding drift tube ion mobility (DTIMS) measurements, the CCS values obtained from DTIMS and SLIM were in agreement within experimental error. Single-pass analysis of alcohol dehydrogenase (ADH) exhibits three predominant charge states (z = 23+ to 25+) with mobility overlap between adjacent charge states. The mobility peak resolution for ADH improved with multipass separations (up to 24-m path length). In addition, CCS distributions obtained for charge states z = 16+ to 18+ of apo-transferrin reveal a transition from a compact unimodal form (z = 18+ and 19+) to broader multimodal CCS distributions for z = 16+. For apo-transferrin, 40-m multipass separations were performed allowing for complete isolation of the selected mobility range corresponding to z = 17+, leading to selective isolation of a narrow arrival time window. The extended mobility separations provided minimal alterations to the structure of the proteins, and the experimentally derived CCS values showed minimal change as a function of the separation time or number of passes. Mobility-based ion separations for native-like proteins, using SLIM, open opportunities for native-IMS applications as well as other manipulations enabled by SLIM-like mobility-selective isolation and collection.

charge state distribution↗

Physicochemical and Molecular Insights into the Boundary Layer and Free Troposphere Aerosol Interactions over the Southern Great Plains

Ambient aerosols’ vertical profiles are critical for evaluating the role of aerosols in atmospheric chemistry and radiative transfer, but limited data on these profiles hinders our ability to fully assess their impact on the Earth's radiative balance. Here, in this study, we investigated the size-, time-, and altitude resolved composition of individual particles and bulk molecular composition of particle samples collected by an uncrewed aerial system–ArcticShark over the Southern Great Plains. Single particle microanalysis shows that, the free tropospheric (FT) samples are dominated (56-66%) by carbonaceous sulfate particles, while boundary layer (BL) samples are dominated (57-74%) by carbonaceous particles. Back trajectory simulations suggest that FT particles are likely influenced by long-range transport and have undergone aqueous-phase processing. Conversely, in-situ size distribution data shows evidence of particle growth in the upper BL and just below the FT. This observation may indicate vertical transport of particles from an elevated aerosol layer in the FT, possibly linked to a new particle formation event. This observation is further supported by high resolution molecular composition data, which reveals particle volatility increasing with increasing size, which aligns with the growth event. This study aids in fundamental understanding of the compositional and molecular specificity of vertically resolved organic aerosols to provide insights into particle size evolution for future atmospheric models.

ArcticShark↗

Human Coronavirus-229E Hijacks Key Host-Cell RNA-Processing Complexes for Replication

The recent rise in zoonotic coronavirus outbreaks underscores the urgency to understand virus-host interactions and develop potent antiviral therapeutics. Systems biology approaches, particularly proteomics have been invaluable in providing a global overview of such interactions. However, these conventional approaches rely on measuring protein abundance changes which don’t reflect functional shifts. In this study, we employed a high-throughput structural proteomics approach called limited proteolysis-based mass spectrometry (LiP-MS) to capture conformational changes, which we demonstrate are better proxies for functional alterations. We applied this tool to both immortalized and primary human lung cells following human coronavirus 229E (HCoV-229E) infection. We identified significant infection-induced structural changes within RNA processing complexes such as the spliceosome-C and NOP56-associated complex. These observations emphasize that HCoV-229E infection propagates a multi-pronged effort to obstruct the house keeping RNA processing functions in the host. Finally, we show that HCoV-229E replication can be attenuated by the targeted disruption of these complexes, indicating that the identified cellular factories are viable targets to prevent coronavirus infection.

coronavirus↗

Modulating Solvation Structure in Concentrated Aqueous Organic Redox Flow Battery Electrolyte for Solubility and Transport Enhancement via Polycomplex Ion

Aqueous organic redox flow batteries hold great promise as a technology for creating economical grid energy storage using sustainable materials. Nonetheless, the solubility limit presents a universal barrier for all redox-active organic molecules. In this paper, a new approach is proposed to surpass the solubility limit by manipulating the solvation structure with polycomplex ion additives (PIA). Using poly(3,4-ethylenedioxythiophene) polystyrenesulfonate colloids as one example, its role in dismantling the rigid supramolecular clusters within the highly concentrated 7,8-dihydroxyphenazine-2-sulfonic acid electrolyte is investigated. 1 H and 23 Na NMR spectra and molecular dynamics simulation studies demonstrate that the bipolar structure of the PIA effectively disrupts the aggregations of DHPS and Na + ion in the highly concentrated anolyte, thus rendering a more flexible solvation structure and less restrictive ion transport, leading to substantially improved battery performance of an AORFB cell. The anolyte with PIA achieved 1.6 M and 74.3 Ah L –1 anolyte energy capacity.

25 ENERGY STORAGE↗

Transformation of CeO 2 Nanoparticles into Atomically Dispersed Ce Cations Leads to Enhanced Reactivity for Automotive Emissions Control

Nanosized cerium oxide (CeO 2 ) has been extensively used as the oxygen storage component in automotive emission control systems. However, the possible influence of atomically dispersed Ce in these catalysts has not been recognized. Here, in this study, we demonstrate the controllable transformation of ceria nanoparticles into isolated cerium cations on γ-Al 2 O 3 via reductive atom trapping in 10% H 2 at 800 °C, achieving over half-monolayer coverage. Dispersed Ce 1 ions anchored by surface penta- and octa-coordinated Al sites exhibit outstanding thermal stability in air up to 500 °C, enabling further loading of active metals with well-defined catalyst structures. With this strategy, supported single-atom Rh 1 surrounded by dispersed Ce 1 is confirmed to exhibit much superior performance to Rh 1 on bare Al 2 O 3 or nanocrystalline CeO 2 in catalyzing NO reduction by CO, exhibiting a striking one-order-of-magnitude increase in activity. Dispersed Ce 1 exhibits greatly enhanced oxygen transfer capability compared to ceria nanoparticles and introduces a modified reaction mechanism that involves an adjacent Rh 1 –Ce 1 motif, resulting in a greatly decreased activation barrier (from 192 to 96 kJ/mol). The reactivity enhancements are also seen with Ce 1 -promoted Pt nanoparticles for oxidation of CO and hydrocarbons.

Jiang, Dong [Washington State Univ., Pullman, WA (↗

Isopentane Disproportionation in Lewis Acidic Chloroaluminate Ionic Liquid

Lewis acidic chloroaluminate ionic liquid diluted in dichloromethane catalyzes the disproportionation of alkanes, such as isopentane, via carbenium ions in a reaction readily initiated by carbenium ion precursors such as tert-butyl chloride (TBC). The carbenium ion-AlCl 4 – ion-pairs stabilized by the ionic liquid-dichloromethane solution are the key intermediates in two distinctive kinetic regimes, i.e., a transient regime (0–5 min) and a steady-state regime (after 5 min). The transient regime constitutes the majority of isopentane conversion and is governed by the initial carbenium ion concentration. In the steady-state regime, disproportionation occurs at a considerably lower rate, affected by the carbenium ion concentration, the concentration of the ionic liquid, and the reaction temperature. The formation of alkenes observed in the 1 H NMR spectra of the reacting substrates, along with the DFT calculations, suggests that deprotonation of carbenium ion-pairs reduces their concentration, decreasing, in turn, the reaction rate. Kinetic modeling indicates that the transient regime is significantly controlled by the hydride transfer (k HT ) and the deprotonation rate constants (k DP ), while the steady-state regime is additionally influenced by the alkene protonation rate constant (k –DP ). The overall activation energy of the reaction at the steady state, expressed as E a,steady-state regime = E a,HT – E a,DP + E a,–DP , was 54 kJ/mol. The reaction mechanism and the kinetics highlight the potential of Lewis acid-catalyzed conversions of hydrocarbons under remarkably mild conditions.

Deprotonation↗

Dynamics of phage-host interactions in Bacteroides fragilis resolved by single-cell transcriptomics

The interactions between lytic phages and their hosts are typically studied in bulk culture, which obscures cell-cell differences in infection susceptibility or expression of protective factors. Here, we use bacterial single-cell RNA sequencing to profile the transcriptomes of ~50,000 cells from cultures of a human pathobiont, Bacteroides fragilis, infected with a lytic bacteriophage. From a single sampling, we quantified the asynchronous progression of phage infection in individual bacterial cells and reconstructed the infection timeline, characterizing both host and phage transcriptomic changes as infection unfolded. Further, we discovered phenotypic subpopulations of bacteria that remained uninfected. Each cell’s vulnerability to phage infection was influenced by expression of multiple genetic loci, most prominently phase-variable capsular polysaccharide (CPS) biosynthesis pathways and an operon predicted to encode fimbrial genes. These findings uncovered genome-wide phase variation and stochasticity that enable bacterial survival and re-growth without acquiring additional mutations. Overall, we establish bacterial single-cell RNA sequencing as a powerful platform for investigating the dynamics of host-phage interactions and revealing the roles of phase variation and stochasticity in bacterial defenses.

Bacteria↗

Activity-targeted metaproteomics uncovers rare syntrophic bacteria central to anaerobic community metabolism

Syntrophic microbial consortia can contribute significantly to the activity and function of anoxic ecosystems, yet are often too rare to study their in situ physiologies using traditional molecular methods. Here, in this study, we describe a technical innovation combining bioorthogonal non-canonical amino acid tagging (BONCAT), stable isotope probing, and metaproteomics to improve the recovery of proteins from active community members and track isotope incorporation. Both click chemistry-enabled cell-sorting and direct protein pulldown coupled to metaproteomics improved recovery of isotopically labeled proteins during acetate oxidation within a full-scale anaerobic digester. Resulting labeled protein expression profiles revealed elevated activity of a rare and uncharacterized syntrophic bacterium belonging to the family Natronincolaceae. BONCAT-based capture of newly translated proteins provided direct molecular evidence for the expression of a previously hypothesized oxidative glycine pathway for syntrophic acetate oxidation by this microorganism, showcasing the potential of targeted metaproteomics to characterize rare and active cells central to community metabolism in natural and engineered ecosystems.

Friedline, Skyler [Univ. of British Columbia, Vanc↗

Evaluation of antifouling surfaces using a method that employs mussel larvae settlement quantified by machine learning

Antifouling coating development requires extensive performance testing. Coatings that prevent aquatic larval settlement are of interest because many forms of macrofouling begin at the larval stage. However, field testing can be time consuming and poorly controlled. Herein is reported a screening tool, Settlement of Larvae Assay using Mussels (SLAM), for down-selecting materials prior to field testing. The method entails using a dense concentration of mussel larvae that are allowed to settle on submerged test surfaces. Settled larvae are then quantified to provide a measure of antifouling performance. The SLAM test differentiated coatings with only slight differences in formulation. To enable efficient quantification of dense larvae settlement, an automated counting method was developed that combines two analyses: a color thresholding identifies larvae clumps, and a machine learning algorithm identifies non-clumped larvae. Finally, this automated ‘hybrid’ approach rapidly quantifies settled larvae as effectively as manual counting but in a fraction of the time.

Mytilus↗

Synergy and antagonism in a genome-scale model of metabolic hijacking by bacteriophages

Bacteriophage auxiliary metabolic genes (AMGs) alter host metabolism by hijacking reactions, but previous studies mostly inferred their roles from annotations, ignoring system-wide impacts and phage production. Here we integrate AMGs and phage assembly into a genome-scale metabolic model of Prochloroccocus marinus MED4 infected by P-HM2. We show that 17 directly hijacked reactions substantially affect more than 30% of the reactions in MED4 metabolism, including carbon fixation, photosynthesis, and nucleotide synthesis, distinguishing these AMGs as either phage aligned—shifting feasible reaction velocities in accordance with maximal phage production—or phage antialigned. Pareto optimization reveals that phage-aligned reactions alter phage-host growth trade-offs, while phage-antialigned reactions do not. We experimentally validate our predictions of system-level AMG impacts by measuring the N-dependent effect of P-HM2 cp12 expression on growth in a model relative of the genetically intractable MED4, Synechococcus elongatus. We also show that AMGs’ indirect impacts are synergistically and antagonistically coupled, providing systems-level insight into AMG perturbations and highlighting how nontrivial cascading effects shape host metabolism.

Rozum, Jordan C. [Pacific Northwest National Labor↗

Nitrogen limitation causes a seismic shift in redox state and phosphorylation of proteins implicated in carbon flux and lipidome remodeling in Rhodotorula toruloides

Background: Oleaginous yeast are prodigious producers of oleochemicals, offering alternative and secure sources for applications in foodstuff, skincare, biofuels, and bioplastics. Nitrogen starvation is the primary strategy used to induce oil accumulation in oleaginous yeast as part of a global stress response. While research has demonstrated that post-translational modifications (PTMs), including phosphorylation and protein cysteine thiol oxidation (redox PTMs), are involved in signaling pathways that regulate stress responses in metazoa and algae, their role in oleaginous yeast remain understudied and unexplored. Results: Towards linking the yeast oleaginous phenotype to protein function, we integrated lipidomics, redox proteomics, and phosphoproteomics to investigate Rhodotorula toruloides under nitrogen-rich and starved conditions over time. Our lipidomics results unearthed interactions involving sphingolipids and cardiolipins with ER stress and mitophagy. Our redox and phosphoproteomics data highlighted the roles of the AMPK, TOR, and calcium signaling pathways in regulation of lipogenesis, autophagy, and oxidative stress response. As a first, we also demonstrated that lipogenic enzymes including fatty acid synthase are modified as a consequence of shifts in cellular redox states due to nutrient availability. Conclusions: We conclude that lipid accumulation is largely a consequence of carbon rerouting and autophagy governed by changes to PTMs, and not increases in the abundance of enzymes involved in central carbon metabolism and fatty acid biosynthesis. Our systems-level approach sets the stage for acquiring multidimensional data sets for protein structural modeling and predicting the functional relevance of PTMs using Artificial Intelligence/Machine Learning (AI/ML). Coupled to those bioinformatics approaches, the putative PTM switches that we delineate will enable advanced metabolic engineering strategies to decouple lipid accumulation from nitrogen limitation.

Lipid Signalling↗