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At least 739 records · Page 41

Raman Microscopy Investigation of GLP-1 Peptide Association with Supported Phospholipid Bilayers

A wide range of important biological processes occur at phospholipid membranes including cell signaling, where a peptide or small molecule targets a membrane-localized receptor protein. In this work, we report the adaptation of confocal-Raman microscopy to quantify populations of unlabeled glucagon-like peptide-1 (GLP-1), a membrane-active 30-residue incretin peptide, in supported phospholipid bilayers deposited on the interior surfaces of wide-pore porous silica particles. Quantification of lipid bilayer-associated peptide is achieved by measuring the Raman scattering intensity of the peptide relative to that of the supported-lipid bilayer, which serves as an internal standard. The dependence of the bilayer-associated GLP-1 population on the solution-concentration of GLP-1 produces an isotherm used to determine the equilibrium constant for peptide-bilayer association and the maximum peptide surface coverage. The maximum coverage of GLP-1 in the lipid bilayer was found to be only 1/5th of a full monolayer based on its hydrodynamic radius. The saturation coverage, therefore, is not limited by the size of GLP-1 but by the ability of the bilayer to accommodate the peptide at high concentrations within the bilayer. Raman spectra show that GLP-1 association with the supported bilayer is accompanied by structural changes consistent with the intercalation of the peptide into bilayer, where the observed increase in acyl-chain order would increase the lipid density and provide free volume needed to accommodate the peptide. Furthermore, these results were compared with previous measurements of the association of fluorescently-labeled GLP-1 with a planar-supported bilayer; the unlabeled peptide exhibits a 3-fold greater affinity for the lipid-bilayer on the porous-silica support suggesting that the fluorescent label alters GLP-1 lipid-bilayer association.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Carbon–Nutrient Economy of the Rhizosphere: Improving Biogeochemical Prediction and Scaling Feedbacks from Ecosystem to Regional Scales

Our project has advanced the science of plant-soil-microbial dynamics across these areas: i) nutrient cycling and plant uptake; ii) root exudation and priming; and, iii) mycorrhizal dynamics. Our project has accomplished 5 main developments: 1) Incorporation of phosphorus cycling into the Fixation & Uptake of Nutrients (FUN 3.0) model. 2) Coupling of FUN 3.0 into the E3SM Land Model (ELM). 3) Data collection across a large mycorrhizal gradient in the US, as well data in the tropics, to parameterize, test, and validate the model. 4)Scaling up mycorrhizal association measurements across landscapes using airborne hyperspectral remote sensing data. 5) Evaluation of global carbon and nutrient cycle impacts in the Community Land Model (CLM5.0) from a suite of new global mycorrhizal association maps. Over 25 publications resulted from this project, with more continuing past the project funded lifetime. Paper highlights from most of these publications have already been submitted to the DOE paper submission online system. These publications include journals such as Science and PNAS, as well as top disciplinary journals from the Nature journals, Global Change Biology, New Phytologist, and Ecology Letters, for example. Our project also contributed to improving the process representation, capabilities, and accuracy of the DOE ELM. Overall, this project significantly advanced the science of belowground plant-soil-microbial interactions as well as technical capabilities from remote sensing to modeling.

59 BASIC BIOLOGICAL SCIENCES↗

Genomes_SET2_178 - Shared

The dataset consists of 178 bacterial genomes in total. Of these, 145 genomes were drawn from published literature linked to Biolog Gen III growth data, while 33 genomes came from soil isolates collected at the Cedar Creek Ecosystem Science Research Reserve (CCESR) in Minnesota. The isolates were sequenced on an Illumina HiSeq platform (~50× coverage), assembled with Megahit, and annotated using RAST at PATRIC, with strict quality filtering (<90% completeness or >5% contamination).

59 BASIC BIOLOGICAL SCIENCES↗

Effect of pH on the Activity of Ice-Binding Protein from Marinomonas primoryensis

The ability of an ice-binding protein (IBP) from Marinomonas primoryensis (MpIBP) to influence ice crystal growth and structure in nonphysiological pH environments was investigated in this work. The ability for MpIBP to retain ice interactivity under stressed environmental conditions was determined via (1) a modified splat assay to determine ice recrystallization inhibition (IRI) of polycrystalline ice and (2) nanoliter osmometry to evaluate the ability of MpIBP to dynamically shape the morphology of a single ice crystal. Circular dichroism (CD) was used to relate the IRI and DIS activity of MpIBP to secondary structure. The results illustrate that MpIBP secondary structure was stable between pH 6 and pH 10. It was found that MpIBP did not interact with ice at pH=4 or pH=13. At 6=pH=12 MpIBP exhibited a reduction in grain size of ice crystals as compared to control solutions and demonstrated dynamic ice shaping at 6=pH=10. The results substantiate that MpIBP retains some secondary structure and function in non-neutral pH environments; thereby, enabling its potential utility in nonphysiological materials science and engineering applications.

antifreeze proteins↗

Spin-phonon relaxation from a universal ab initio density-matrix approach

Designing new quantum materials with long-lived electron spin states urgently requires a general theoretical formalism and computational technique to reliably predict intrinsic spin relaxation times. We present a new, accurate and universal first-principles methodology based on Lindbladian dynamics of density matrices to calculate spin-phonon relaxation time of solids with arbitrary spin mixing and crystal symmetry. This method describes contributions of Elliott-Yafet and D’yakonov-Perel’ mechanisms to spin relaxation for systems with and without inversion symmetry on an equal footing. We show that intrinsic spin and momentum relaxation times both decrease with increasing temperature; however, for the D’yakonov-Perel’ mechanism, spin relaxation time varies inversely with extrinsic scattering time. We predict large anisotropy of spin lifetime in transition metal dichalcogenides. The excellent agreement with experiments for a broad range of materials underscores the predictive capability of our method for properties critical to quantum information science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Towards interpretable Cryo-EM: disentangling latent spaces of molecular conformations

Molecules are essential building blocks of life and their different conformations (i.e., shapes) crucially determine the functional role that they play in living organisms. Cryogenic Electron Microscopy (cryo-EM) allows for acquisition of large image datasets of individual molecules. Recent advances in computational cryo-EM have made it possible to learn latent variable models of conformation landscapes. However, interpreting these latent spaces remains a challenge as their individual dimensions are often arbitrary. The key message of our work is that this interpretation challenge can be viewed as an Independent Component Analysis (ICA) problem where we seek models that have the property of identifiability. That means, they have an essentially unique solution, representing a conformational latent space that separates the different degrees of freedom a molecule is equipped with in nature. Thus, we aim to advance the computational field of cryo-EM beyond visualizations as we connect it with the theoretical framework of (nonlinear) ICA and discuss the need for identifiable models, improved metrics, and benchmarks. Moving forward, we propose future directions for enhancing the disentanglement of latent spaces in cryo-EM, refining evaluation metrics and exploring techniques that leverage physics-based decoders of biomolecular systems. Moreover, we discuss how future technological developments in time-resolved single particle imaging may enable the application of nonlinear ICA models that can discover the true conformation changes of molecules in nature. The pursuit of interpretable conformational latent spaces will empower researchers to unravel complex biological processes and facilitate targeted interventions. This has significant implications for drug discovery and structural biology more broadly. More generally, latent variable models are deployed widely across many scientific disciplines. Thus, the argument we present in this work has much broader applications in AI for science if we want to move from impressive nonlinear neural network models to mathematically grounded methods that can help us learn something new about nature.

59 BASIC BIOLOGICAL SCIENCES↗

Small-scale roughness entraps water and controls underwater adhesion

While controlling underwater adhesion is critical for designing biological adhesives and in improving the traction of tires, haptics, or adhesives for health monitoring devices, it is hindered by a lack of fundamental understanding of how the presence of trapped water impedes interfacial bonding. Here, by using well-characterized polycrystal diamond surfaces and soft, nonhysteretic, low–surface energy elastomers, we show a reduction in adhesion during approach and four times higher adhesion during retraction as compared to the thermodynamic work of adhesion. Our findings reveal how the loading phase of contact is governed by the entrapment of water by ultrasmall (10-nanometer-scale) surface features. In contrast, the same nanofeatures that reduce adhesion during approach serve to increase adhesion during separation. The explanation for this counterintuitive result lies in the incompressibility-inextensibility of trapped water and the work needed to deform the polymer around water pockets. Unlike the well-known viscoelastic contribution to adhesion, this science unlocks strategies for tailoring surface topography to enhance underwater adhesion.

59 BASIC BIOLOGICAL SCIENCES↗

Light potentials of photosynthetic energy storage in the field: what limits the ability to use or dissipate rapidly increased light energy?

The responses of plant photosynthesis to rapid fluctuations in environmental conditions are critical for efficient conversion of light energy. These responses are not well-seen laboratory conditions and are difficult to probe in field environments. We demonstrate an open science approach to this problem that combines multifaceted measurements of photosynthesis and environmental conditions, and an unsupervised statistical clustering approach. In a selected set of data on mint (Mentha sp.), we show that ‘light potentials’ for linear electron flow and non-photochemical quenching (NPQ) upon rapid light increases are strongly suppressed in leaves previously exposed to low ambient photosynthetically active radiation (PAR) or low leaf temperatures, factors that can act both independently and cooperatively. Further analyses allowed us to test specific mechanisms. With decreasing leaf temperature or PAR, limitations to photosynthesis during high light fluctuations shifted from rapidly induced NPQ to photosynthetic control of electron flow at the cytochrome b 6 f complex. At low temperatures, high light induced lumen acidification, but did not induce NPQ, leading to accumulation of reduced electron transfer intermediates, probably inducing photodamage, revealing a potential target for improving the efficiency and robustness of photosynthesis. We discuss the implications of the approach for open science efforts to understand and improve crop productivity.

59 BASIC BIOLOGICAL SCIENCES↗

Bio-based oxalic acid production in Issatchenkia orientalis enables sustainable rare earth recovery

The growing demand for rare earth elements (REEs) in clean energy and high-tech industries underscores the need for sustainable recovery methods and a reliable supply of processing chemicals. Here, we establish a microbial platform using the acid-tolerant yeast Issatchenkia orientalis SD108 to produce bio-oxalic acid for REE recovery. By introducing an oxaloacetate cleavage pathway and applying metabolic engineering, the engineered strain produces 39.53 g·L -1 oxalic acid at pH 4.0 in fed-batch fermentation. The crude fermentation broth, used without purification, efficiently precipitates over 99% neodymium (Nd), 99% dysprosium (Dy), and 98% lanthanum (La) from individual REE chloride solutions. Recovery from a low-grade ore leachate achieves over 99% total recovery. X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR) confirm that REE oxalates precipitated with bio-oxalic acid closely resemble those obtained using commercial oxalic acid. Techno-economic analysis (TEA) and life cycle assessment (LCA) further demonstrate that bio-oxalic acid can be produced at a competitive price of $1.79·kg -1 while reducing carbon intensity (CI) by 112% to 63.5% with and without electricity displacement, respectively, relative to the fossil-based benchmark. These results highlight bio-oxalic acid as a green, economically viable alternative to synthetic oxalate for sustainable REE recovery.

59 BASIC BIOLOGICAL SCIENCES↗

Genomic analysis of Klebsiella aerogenes circulating in New Mexico

Klebsiella aerogenes is an opportunistic pathogen and a growing cause of healthcare-associated infections, characterized by multidrug resistance and the emergence of global high-risk clones. However, regional genomic surveillance data remain limited. Here, we sought to characterize the population structure, transmission dynamics and resistance mechanisms of clinical K. aerogenes in Albuquerque, New Mexico. We sequenced 177 clinical isolates collected between 2021 and 2023. We also developed a novel, species-specific PopPUNK database to facilitate rapid, high-resolution typing. The New Mexico K. aerogenes population was diverse but dominated by two global pandemic lineages, ST93 (47.5%) and ST4 (7.9%), which were significantly enriched for the virulence factors yersiniabactin and colibactin. Genomic evidence for recent local transmission was rare, with only four putative transmission pairs identified. The resistome was characterized by intrinsic and adaptive mutations. Nearly all isolates possessed gyrA mutations associated with decreased fluoroquinolone susceptibility. Mutations in the AmpC regulator AmpD and the outer membrane porin Omp36 were common, particularly within the dominant ST93 lineage. These mutations have been associated with increased AmpC-mediated carbapenem resistance. Our findings underscore the critical importance of genomic surveillance to monitor the transmission and evolution of adaptive resistance.

59 BASIC BIOLOGICAL SCIENCES↗

Workshop summary. Biomedical and Space-Related Research with Heavy Ions at the BEVALAC

The authors provide an overview of papers presented at a workshop on Biomedical and Space-Related Research with Heavy Ions at the BEVALAC at Lawrence Berkeley Laboratory. Goals of the meeting were to determine the critical experiments using heavy ions as probes in radiation physics, radiation chemistry, macromolecular and cellular biology, evolution science, basic neurophysiology, and medical therapies; how beam lines and facilities at Lawrence Berkeley Laboratory can be improved for these experiments; and implications in priorities and funding for national policy. Workshop topics included physics and facilities, cellular and molecular biology, tissue radiobiology, and the future of heavy ion research.

NASA Discipline Radiation Health↗

Continuous assessment of metabolic activity of mitochondria using resonance Raman microspectroscopy

Dysfunctional mitochondrial activity can lead to a variety of different diseases. As such, there exists a need to quantify changes in mitochondria function as it relates to these specific diseased states. Here, we present the use of resonance Raman (RR) spectroscopy as a tool to determine changes in isolated mitochondrial activity. RR spectroscopy, using 532 nm as the excitation source, specifically provides information on the reduction and oxidation (RedOx) state of cytochrome c, which is determined by the activity of protein complexes in the electron transport chain. In this model, injection of the substrate succinate into the mitochondrial sample is used to drive the electron transport chain, which causes a subsequent change in cytochrome c RedOx state. This change in RedOx state is tracked by RR spectroscopy. We report this tool gives real-time information on the rise and fall of the amount of reduced cytochrome c within the mitochondrial sample, providing a method for rapid assessment of mitochondrial metabolism that has broad applications in both basic science and medical research.

59 BASIC BIOLOGICAL SCIENCES↗

Mixed and membrane-separated culturing of synthetic cyanobacteria-yeast consortia reveals metabolic cross-talk mimicking natural cyanolichens

Metabolite exchange mediates crucial interactions in microbial communities, significantly impacting global carbon and nitrogen cycling. Understanding these chemically-mediated interactions is essential for elucidating natural community functions and developing engineered synthetic communities. This study investigated membrane-separated bioreactors (mBRs) as a novel tool to identify transient metabolites and their producers/consumers in mixed microbial communities. We compared three co-culture methods (direct mixed, 2-chamber mBR, and 3-chamber mBR) to grow a synthetic binary community of the cyanobacterium Synechococcus elongatus PCC 7942 and the fungus Rhodotorula toruloides NBRC 0880, as well as axenic S. elongatus. Despite not being natural lichen constituents, these organisms exhibited interactions resembling those in cyanolichens. S. elongatus fixed CO 2 into sugars as the primary shared metabolite, while R. toruloides secreted various biochemicals, predominantly sugar alcohols, mirroring the metabolite exchange observed in natural lichens. The mBR systems successfully captured metabolite gradients and revealed rapidly consumed compounds, including TCA cycle intermediates and amino acids. Our approach demonstrated that the 2-chamber mBR optimally balanced metabolite exchange and growth dynamics. This study provides insights into cross-species metabolic interactions and presents a valuable tool for investigating and engineering synthetic microbial communities with potential applications in biotechnology and environmental science.

59 BASIC BIOLOGICAL SCIENCES↗

Editorial: Artificial Intelligence and Machine Learning Applications in Plant Genomics and Genetics

In plants, as in other species, genotypic variation in combination with environmental variation leads to differences in the biochemical makeup of cells, measurable as molecular phenotypes. These in turn influence physiological and developmental traits such as organ formation and plant growth, and eventually traits relevant in agriculture, such as yield and stress tolerance. Thus, relating genotypes to phenotypes yields fundamental insights into the regulation of important processes in plant development and physiology, but also provides the ability to predict yield and quality traits in specific environments, which is essential in basic plant science and molecular breeding of resilient plants in changing environments.

59 BASIC BIOLOGICAL SCIENCES↗