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At least 937 records · Page 52

Carbon isotope effects associated with aceticlastic methanogenesis

The carbon isotope effects associated with synthesis of methane from acetate have been determined for Methanosarcina barkeri 227 and for methanogenic archaea in sediments of Wintergreen Lake, Michigan. At 37 degrees C, the 13C isotope effect for the reaction acetate (methyl carbon) --> methane, as measured in replicate experiments with M. barkeri, was - 21.3% +/- 0.3%. The isotope effect at the carboxyl portion of acetate was essentially equal, indicating participation of both positions in the rate-determining step, as expected for reactions catalyzed by carbon monoxide dehydrogenase. A similar isotope effect, - 19.2% +/- 0.3% was found for this reaction in the natural community (temperature = 20 degrees C). Given these observations, it has been possible to model the flow of carbon to methane within lake sediment communities and to account for carbon isotope compositions of evolving methane. Extension of the model allows interpretation of seasonal fluctuations in 13C contents of methane in other systems.

NASA Discipline Exobiology↗

A stochastic differential equation model of diurnal cortisol patterns

Circadian modulation of episodic bursts is recognized as the normal physiological pattern of diurnal variation in plasma cortisol levels. The primary physiological factors underlying these diurnal patterns are the ultradian timing of secretory events, circadian modulation of the amplitude of secretory events, infusion of the hormone from the adrenal gland into the plasma, and clearance of the hormone from the plasma by the liver. Each measured plasma cortisol level has an error arising from the cortisol immunoassay. We demonstrate that all of these three physiological principles can be succinctly summarized in a single stochastic differential equation plus measurement error model and show that physiologically consistent ranges of the model parameters can be determined from published reports. We summarize the model parameters in terms of the multivariate Gaussian probability density and establish the plausibility of the model with a series of simulation studies. Our framework makes possible a sensitivity analysis in which all model parameters are allowed to vary simultaneously. The model offers an approach for simultaneously representing cortisol's ultradian, circadian, and kinetic properties. Our modeling paradigm provides a framework for simulation studies and data analysis that should be readily adaptable to the analysis of other endocrine hormone systems.

NASA Discipline Space Human Factors↗

Comparison of metagenomes from fermentation of various agroindustrial residues suggests a common model of community organization

The liquid residue resulting from various agroindustrial processes is both rich in organic material and an attractive source to produce a variety of chemicals. Using microbial communities to produce chemicals from these liquid residues is an active area of research, but it is unclear how to deploy microbial communities to produce specific products from the different agroindustrial residues. To address this, we fed anaerobic bioreactors one of several agroindustrial residues (carbohydrate-rich lignocellulosic fermentation conversion residue, xylose, dairy manure hydrolysate, ultra-filtered milk permeate, and thin stillage from a starch bioethanol plant) and inoculated them with a microbial community from an acid-phase digester operated at the wastewater treatment plant in Madison, WI, United States. The bioreactors were monitored over a period of months and sampled to assess microbial community composition and extracellular fermentation products. We obtained metagenome assembled genomes (MAGs) from the microbial communities in each bioreactor and performed comparative genomic analyses to identify common microorganisms, as well as any community members that were unique to each reactor. Collectively, we obtained a dataset of 217 non-redundant MAGs from these bioreactors. This metagenome assembled genome dataset was used to evaluate whether a specific microbial ecology model in which medium chain fatty acids (MCFAs) are simultaneously produced from intermediate products (e.g., lactic acid) and carbohydrates could be applicable to all fermentation systems, regardless of the feedstock. MAGs were classified using a multiclass classification machine learning algorithm into three groups, organisms fermenting the carbohydrates to intermediate products, organisms utilizing the intermediate products to produce MCFAs, and organisms producing MCFAs directly from carbohydrates. This analysis revealed common biological functions among the microbial communities in different bioreactors, and although different microorganisms were enriched depending on the agroindustrial residue tested, the results supported the conclusion that the microbial ecology model tested was appropriate to explain the MCFA production potential from all agricultural residues.

60 APPLIED LIFE SCIENCES↗

The kinetics of root gravitropism: dual motors and sensors

The Cholodny-Went theory of tropisms has served as a framework for investigation of root gravitropism for nearly three quarters of a century. Recent investigations using modern techniques have generated findings consistent with the classical theory, including confirmation of asymmetrical distribution of polar auxin transport carriers, molecular evidence for auxin asymmetry following gravistimulation, and generation of auxin response mutants with predictable lesions in gravitropism. Other results indicate that the classical model is inadequate to account for key features of root gravitropism. Initiation of curvature, for example, occurs outside the region of most rapid elongation and is driven by differential acceleration rather than differential inhibition of elongation. The evidence indicates that there are two motors driving root gravitropism, one of which appears not to be auxin regulated. We have recently developed technology that is capable of maintaining a constant angle of gravistimulation at any selected target region of a root while continuously monitoring growth and curvature kinetics. This review elaborates on the advantages of this new technology for analyzing gravitropism and describes applications of the technology that reveal (1) the existence of at least two phases to gravitropic motor output, even under conditions of constant stimulus input and (2) the existence of gravity sensing outside of the root cap. We propose a revised model of root gravitropism including dual sensors and dual motors interacting to accomplish root gravitropism, with only one of the systems linked to the classical Cholodny-Went theory.

Review↗

Data for "Discovery, Characterization, and Application of Chromosomal Integration Sites in the Hyperthermophilic Archaeon Sulfolobus islandicus"

Sulfolobus islandicus , an emerging archaeal model organism, offers unique advantages for metabolic engineering and synthetic biology applications owing to its ability to thrive in extreme environments. Although several genetic tools have been established for this organism, the lack of well-characterized chromosomal integration sites has limited its potential as a cellular factory. Here, we systematically identified and characterized 13 artificial CRISPR RNAs targeting eight integration sites in S. islandicus using the CRISPR-COPIES pipeline and a multi-omics-informed computational workflow. We leveraged the endogenous CRISPR-Cas system to integrate the reporter gene lacS and validated heterologous expression through a β-galactosidase assay, revealing significant positional effects. As a proof of concept, we utilized these sites to genetically manipulate lipid ether composition by overexpressing glycerol dibiphytanyl glycerol tetraether (GDGT) ring synthase B (GrsB). This study expands the genetic toolbox for S. islandicus and advances its potential as a robust platform for archaeal synthetic biology and industrial biotechnology.

AI/ML↗

Increasing Data Discovery and Re-Use: The Space Life Sciences Ontology

Two of the most important goals of the adoption of the FAIR principles are increasing the ability of agents to find and re-use research data. Achieving these goals for space life sciences research is even more pressing, given the relatively expensive and scarce nature of these data. We have reported in the past on the progress made by exemplar life sciences data systems towards implementing FAIR, showing gaps particularly in the “interoperability area” of the principles; the lack of common conceptual models for space life science research is one reason for this gap. There were few available resources that define, annotate, categorize or otherwise relate various kinds of metadata describing the acquisition, nature, and intent of investigational space life sciences data. To address this gap, NASA is working with the Open Biological and Biomedical Ontology Foundry (https://obofoundry.org/) to develop the Space Life Science Ontology (SLSO) that is intended to support archival and other kinds of systems that operate using these data. The scope of the ontology includes concepts regarding those aspects of investigation design and execution specific or unique to space environments, such as types of specialized equipment, operating organizations, and documentation. The ontology is continually being developed and published to the life science community (https://github.com/nasa/LSDAO/); at the time of this publication, the SLSO newly and uniquely defines 30 types (classes), 90 properties, and 14 relations specific to space life sciences metadata. In addition, the SLSO reuses (imports) some 2,360 types (classes), 49 properties, and 393 relations from other ontologies that are relevant to these kinds of metadata. In addition to its role as a common conceptualization for space biomedical research activities, the SLSO can also be used to provide automated support for traditionally difficult and expensive activities such as data curation and cross-system data integration and analysis.

fair↗

Effects of marine organic aerosols as sources of immersion-mode ice-nucleating particles on high-latitude mixed-phase clouds

Mixed-phase clouds are frequently observed in high-latitude regions and have important impacts on the surface energy budget and regional climate. Marine organic aerosol (MOA), a natural source of aerosol emitted over ~70 % of Earth's surface, may significantly modify the properties and radiative forcing of mixed-phase clouds. However, the relative importance of MOA as a source of ice-nucleating particles (INPs) in comparison to mineral dust, and MOA's effects as cloud condensation nuclei (CCN) and INPs on mixed-phase clouds are still open questions. In this study, we implement MOA as a new aerosol species into the Community Atmosphere Model version 6 (CAM6), the atmosphere component of the Community Earth System Model version 2 (CESM2), and allow the treatment of aerosol–cloud interactions of MOA via droplet activation and ice nucleation. CAM6 reproduces observed seasonal cycles of marine organic matter at Mace Head and Amsterdam Island when the MOA fraction of sea spray aerosol in the model is assumed to depend on sea spray biology but fails when this fraction is assumed to be constant. Model results indicate that marine INPs dominate primary ice nucleation below 400 hPa over the Southern Ocean and Arctic boundary layer, while dust INPs are more abundant elsewhere. By acting as CCN, MOA exerts a shortwave cloud forcing change of -2.78 W m-2 over the Southern Ocean in the austral summer. By acting as INPs, MOA enhances the longwave cloud forcing by 0.35 W m-2 over the Southern Ocean in the austral winter. The annual global mean net cloud forcing changes due to CCN and INPs of MOA are -0.35 and 0.016 W m-2, respectively. These findings highlight the vital importance for Earth system models to consider MOA as an important aerosol species for the interactions of biogeochemistry, hydrological cycle, and climate change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rewiring the unfolded protein response for plant growth recovery after stress

The unfolded protein response (UPR) is a highly coordinated signaling network that alleviates endoplasmic reticulum (ER) stress, a condition induced by diverse environmental challenges in plants. Over the past two decades, substantial progress has been made in elucidating the genetic and molecular mechanisms of ER stress sensing and signal transduction in plants, largely through studies in the model plant Arabidopsis thaliana . These advances have established the UPR as a central regulator of proteostasis and underscored its broader relevance to plant growth and development and crop productivity under stress conditions. Despite this progress, critical knowledge gaps remain, particularly concerning the downstream biological processes required for growth recovery once ER stress has subsided and how these processes are coordinated by UPR regulators. Recent systems-level and integrative studies have begun to reveal critical roles of UPR signaling in pathways governing growth re-establishment and homeostasis of nutrient allocation and energy metabolism. In this review, we highlight recent findings on the functional roles of the plant UPR in recovery from ER stress, with a focus on mechanisms mediated by UPR regulators and downstream biological pathways that enable the transition from stress mitigation to growth restoration. Although this research area is still emerging, accumulating evidence supports a model in which the UPR functions as a dynamic regulatory network that actively coordinates post-stress physiological recovery to support plant fitness.

ER stress↗

Fabrication of Arrays of Topological Solitons in Patterned Chiral Liquid Crystals for Real-Time Observation of Morphogenesis

Topological solitons have knotted continuous field configurations embedded in a uniform background, and occur in cosmology, biology, and electromagnetism. However, real-time observation of their morphogenesis and dynamics is still challenging because their size and timescale are enormously large or tiny. Liquid crystal (LC) structures are promising candidates for a model-system to study the morphogenesis of topological solitons, enabling direct visualization due to the proper size and timescale. We report a new way is found to rationalize the real-time observation of the generation and transformation of topological solitons using cholesteric LCs confined in patterned substrates. The experimental demonstration shows the topologically protected structures arise via the transformation of topological defects. Numerical modeling based on minimization of free energy closely reconstructs the experimental findings. The fundamental insights obtained from the direct observations pose new theoretical challenges in understanding the morphogenesis of different types of topological solitons within a broad range of scales.

36 MATERIALS SCIENCE↗

Hexagonal Lattices of HIV Capsid Proteins Explored by Simulations Based on a Thermodynamically Consistent Model

HIV capsid proteins (CAs) may self-assemble into a variety of shapes under in vivo and in vitro conditions. Here, we employed simulations based on a residue-level coarse-grained (CG) model with full conformational flexibility to investigate hexagonal lattices, which are the underlying structural pattern for CA aggregations. Facilitated by enhanced sampling simulations to rigorously calculate CA dimerization and polymerization affinities, we calibrated our model to reproduce the experimentally measured affinities. Here using the calibrated model, we performed unbiased simulations on several large systems consisting of 1512 CA subunits, allowing reversible binding and unbinding of the CAs in a thermodynamically consistent manner. In one simulation, a preassembled hexagonal CA sheet developed spontaneous curvatures reminiscent of those observed in experiments, and the edges of the sheet exhibited local curvatures larger than those of the interior. In other simulations starting with randomly distributed CAs at different concentrations, existing CA assemblies grew by binding free capsomeres to the edges and by merging with other assemblies. At high CA concentrations, rapid establishment of predominant aggregates was followed by much slower adjustments toward more regular hexagonal lattices, with increasing numbers of intact CA hexamers and pentamers being formed. Our approach of adapting a general CG model to specific systems by using experimental binding data represents a practical and effective strategy for simulating and elucidating intricate protein aggregations.

59 BASIC BIOLOGICAL SCIENCES↗

Tunable Repression of Key Photosynthetic Processes Using Cas12a CRISPR Interference in the Fast-Growing Cyanobacterium Synechococcus sp. UTEX 2973

Cyanobacteria are photoautotrophic prokaryotes that serve as key model organisms to study basic photosynthetic processes and are potential carbon-negative production chassis for commodity and high-value chemicals. The development of new synthetic biology tools and improvement of current ones is a requisite for furthering these organisms as models and production vehicles. CRISPR interference (CRISPRi) allows for targeted gene repression using a DNase-dead Cas nuclease (“dCas”). Here, we describe a titratable dCas12a (dCpf1) CRISPRi system and apply it to repress key photosynthetic processes in the fast-growing cyanobacterium Synechococcus sp. UTEX 2973 (S2973). The system relies on a lac repressor system that retains tight regulation in the absence of inducer (0–10% repression) while maintaining the capability for >90% repression of high-abundance gene targets. We determined that dCas12a is less toxic than dCas9. We tested the efficacy of the system toward eYFP and three native targets in S2973: the phycobilisome antenna, glycogen synthesis, and photosystem I (PSI), an essential part of the photosynthetic electron transport chain in oxygenic photoautotrophs. PSI was knocked down indirectly by repressing the protein factor BtpA involved in stabilizing core PSI proteins. We could reduce cellular PSI titer by 87% under photoautotrophic conditions, and we characterized these cells to gain insights into the response of the strain to the low PSI content. The ability to tightly regulate and time the (de)repression of essential genes in trans will allow for the study of photosynthetic processes that are not accessible using knockout mutants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Volcanology, Geochemistry, and Petrology Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

This article is composed of a commentary about the state of Integrated, Coordinated, Open, and Networked (ICON) principles in Volcanology, Geochemistry, and Petrology (VGP), and discussion on the opportunities and challenges of adopting them. VGP encompasses a broad field that addresses volcanic, magmatic, hydrothermal, geomicrobial systems; process investigations that span the physical, geochemical and biological realms, including planetary geology; and one that is extensively supported by state-of-the-art research facilities. We suggest that an open, inclusive, collaborative and evolving model of an international coordinated network is critical to answering the most pressing challenges in VGP. In this commentary piece, we begin to discuss the elements of, challenges to, and path forward in developing such a model. For this team, ICON means collaboration, equitable access to data for the entire scientific community, and forging of partnerships that potentially contribute to more innovative ways of coordinating and sharing research. It also means bringing more equity to science, by implementing effective measures which consider access to funding, analytical equipment, resources, and mentors. More importantly, ICON to us means having important conversations around what we value in the advancement of science, perhaps exploring outside the idea of meritocracy and evaluating what individual traits can contribute to science outside what has traditionally been considered the norm.

58 GEOSCIENCES↗

Dataset for 'Ombadi et al. (2023). A warming-induced reduction in snow fraction amplifies rainfall extremes, Nature'

This package contains the main codes, sample input data and main result files to reproduce the analysis and results presented in the article: “Ombadi et al. (2023), A warming-induced reduction in snow fraction amplifies rainfall extremes, Nature”. The folder consists of the following: (1) “Raw data”: a folder that contains sample input data which is used in some of the codes for demonstration purposes. It also contains data that was not pre-processed such as Elevation data; (2) “Results”: this folder contains files of the main results presented in the paper including: “Annual-Max-Series”, “Change-rainfall-extremes”, “Change-snow-fraction”, “Warming levels_By scenario_model_year” and “Masks”. Description of these folders is detailed in the "Readme.rtf" file; (3) Python jupyter notebooks (Extract_Annual Max Series (AMS).ipynb, Elevation-dependent amplification of rainfall extremes.ipynb, Sensitivity_to_global_warming.ipynb) demonstrate the main steps of analysis. Further description of those notebooks is provided in the "Readme.rtf" file; (4) R code for extreme value analysis (Extreme_Value_Analysis.R). The sample and pre-processed dataset in "Raw data" is obtained from publicly available repositories of CMIP6 and ERA5 datasets; see Methods for more detail. This research was supported by Office of Science, Office of Biological and Environmental Research of the US Department of Energy under contract no. DE-AC02-05CH11231 for the CASCADE Scientific Focus (funded by the Regional and Global Model Analysis Program area within the Earth and Environmental Systems Modeling Program) and the iNAIADS Early Career Research Project (funded by the Environmental Systems Science program).

54 ENVIRONMENTAL SCIENCES↗

Understanding the Radiant Scattering Behavior of Vegetated Scenes

Knowledge of the physics of the scattering behavior of vegetation will ultimately serve the remote sensing and earth science community in many ways. For example, it will provide: (1) insight and guidance in developing new extraction techniques of canopy characteristics, (2) a basis for better interpretation of off-nadir satellite and aircraft data, (3) a basis for defining specifications of future earth observing sensor systems, and (4) a basis for defining important aspects of physical and biological processes of the plant system. The overall objective of the three-year study is to improve our fundamental understanding of the dynamics of directional scattering properties of vegetation canopies through analysis of field data and model simulation data. The specific objectives are to: (1) collect directional reflectance data covering the entire exitance hemisphere for several common vegetation canopies with various geometric structure (both homogeneous and row crop structures), (2) develop a scene radiation model with a general mathematical framework which will treat 3-D variability in heterogeneous scenes and account for 3-D radiant interactions within the scene, (3) conduct validations of the model on collected data sets, and (4) test and expand proposed physical scattering mechanisms involved in reflectance distribution dynamics by analyzing both field and modeling data.

Kimes, D. S.↗

Post-flight Analysis of the Argon Filled Ion Chamber

Atmospheric ionizing radiation is a complex mixture of primary galactic and solar cosmic rays and a multitude of secondary particles produced in collision with air nuclei. The first series of Atmospheric Ionizing Radiation (AIR) measurement flights on the NASA research aircraft ER-2 took place in June 1997. The ER-2 flight package consisted of fifteen instruments from six countries and were chosen to provide varying sensitivity to specific components. These AIR ER-2 flight measurements are to characterize the AIR environment during solar minimum to allow the continued development of environmental models of this complex mixture of ionizing radiation. This will enable scientists to study the ionizing radiation health hazard associated with the high-altitude operation of a commercial supersonic transport and to allow estimates of single event upsets for advanced avionics systems design. The argon filled ion chamber representing about 40 percent of the contributions to radiation risks are analyzed herein and model discrepancies for solar minimum environment are on the order of 5 percent and less. Other biologically significant components remain to be analyzed.

Tai, H.↗

Growth and Metabolism of the Green Alga, Chlorella Pyrenoidosa, in Simulated Microgravity

The effect of microgravity on living organisms during space flight has been a topic of interest for some time, and a substantial body of knowledge on the subject has accumulated. Despite this, comparatively little information is available regarding the influence of microgravity on algae, even though it has been suggested for long duration flight or occupancy in space that plant growth systems, including both higher plants and algae, are likely to be necessary for bioregenerative life support systems. High-Aspect-Ratio Rotating-Wall Vessel or HARV bioreactors developed at Johnson Space Center provide a laboratory-based approach to investigating the effects of microgravity on cellular reactions. In this study, the HARV bioreactor was used to examine the influence of simulated microgravity on the growth and metabolism of the green alga, Chlorella pyrenoidosa. After the first 2 days of culture, cell numbers increased more slowly in simulated microgravity than in the HARV gravity control; after 7 days, growth in simulated microgravity was just over half (58%) that of the gravity control and at 14 days it was less than half (42%). Chlorophyll and protein were also followed as indices of cell competence and function; as with growth, after 2-3 days, protein and chlorophyll levels were reduced in modeled microgravity compared to gravity controls. Photosynthesis is a sensitive biochemical index of the fitness of photosynthetic organisms; thus, CO2-dependent O2 evolution was tested as a measure of photosynthetic capacity of cells grown in simulated microgravity. When data were expressed with respect to cell number, modeled microgravity appeared to have little effect on CO2 fixation. Thus, even though the overall growth rate was lower for cells cultured in microgravity, the photosynthetic capacity of the cells appears to be unaffected. Cells grown in simulated microgravity formed loose clumps or aggregates within about 2 days of culture, with aggregation increasing over time. Presently, the basis for, or significance of, the cell aggregation is unknown. The results from this study suggest that cell growth and morphological characteristics of green algae may be altered by culture in simulated microgravity. The data obtained to date should provide a solid basis for additional experimentation regarding the influence of modeled microgravity on cell morphology, physiological activity, protein production and possibly gene expression in algal and plant cell systems. The final aim of the study is to provide useful information to elucidate the underlying mechanism for the biological effects of microgravity on cells.

Mills, W. Ronald↗

Atomistic simulations for investigation of substrate and salt effects on lipid in-source fragmentation in secondary ion mass spectrometry: A follow-up study

In-source fragmentation (ISF) poses a significant challenge in secondary ion mass spectrometry (SIMS). These fragment ions increase the spectral complexity and can lead to incorrect annotation of fragments as intact species. The presence of salt that is ubiquitous in biological samples can influence the fragmentation and ionization of analytes in a significant manner, but their influences on SIMS have not been well characterized. To elucidate the effect of substrates and salt on ISF in SIMS, we have employed experimental SIMS in combination with atomistic simulations of a sphingolipid on a gold surface with various NaCl concentrations as a model system. Our results revealed that a combination of bond dissociation energy and binding energy between N-palmitoyl-sphingomyelin and a gold surface is a good predictor of fragment ion intensities in the absence of salt. However, ion-fragment interactions play a significant role in determining fragment yields in the presence of salt. Additionally, the charge distribution on fragment species may be a major contributor to the varying effects of salt on fragmentation. This study demonstrates that atomistic modeling can help predict ionization potential when salts are present, providing insights for more accurate interpretations of complex biological spectra.

74 ATOMIC AND MOLECULAR PHYSICS↗

Modeling Plant Metabolism: From Network Reconstruction to Mechanistic Models

Mathematical modeling of plant metabolism allows the plant science community to understand the organization of plant metabolism, obtain quantitative insights into metabolic functions, and derive engineering strategies for manipulation of metabolism. Among the various modeling approaches, metabolic pathway analysis can dissect the basic functional modes of subsections of core metabolism, such as photorespiration, and reveal how classical definitions of metabolic pathways have overlapping functionality. In current research using constraint-based modeling in plants, numerous computational tools are currently available to analyze large-scale and genome-scale metabolic networks. For 13 C-metabolic flux analysis, principles of isotopic steady state have been used to study heterotrophic plant tissues, while nonstationary isotope labeling approaches are amenable to the study of photoautotrophic and secondary metabolism. Enzyme kinetic models explore pathways in mechanistic detail, and we discuss different approaches to determine or estimate kinetic parameters. In this review, we describe recent advances and challenges in modeling plant metabolism.

59 BASIC BIOLOGICAL SCIENCES↗