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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Biological dosimetry by interphase chromosome painting

Both fluorescence in situ hybridization of metaphase spreads with whole-chromosome probes and premature chromosome condensation in interphase nuclei have been used in the past to estimate the radiation dose to lymphocytes. We combined these techniques to evaluate the feasibility of using painted interphase chromosomes for biodosimetry. Human peripheral lymphocytes were exposed to gamma rays and fused to mitotic Chinese hamster cells either immediately after irradiation or after 8 h incubation at 37 degrees C. Interphase or metaphase human chromosomes were hybridized with a composite probe specific for human chromosomes 3 and 4. The dose-response curve for fragment induction immediately after irradiation was linear; these results reflected breakage frequency in the total genome in terms of DNA content per chromosome. At 8 h after irradiation, the dose-response curve for chromosome interchanges, the prevalent aberration in interphase chromosomes, was linear-quadratic and similar to that observed for metaphase chromosomes. These results suggest that painting prematurely condensed chromosomes can be useful for biological dosimetry when blood samples are available shortly after the exposure, or when interphase cells are to be scored instead of mitotic cells.

NASA Discipline Radiation Health↗
NASA NTRSDate not supplied

Rebuilding the Habitable Zone from the Bottom Up

The idea of habitability has been useful for categorizing places where life might exist in the universe. Circumstellar habitable zones estimate whether rocky planets might harbor liquid surface water, geophysical and tidal habitable zones gauge places like icy moons. Combined with biological constraints of energy and element availability, habitability can be key for eliminating false positive biosignatures. But is there a more fundamental and complete way to talk about all of this? I’ll share a proposal for a concept of “computational zones” that digs deep into the fundamentals of what we think we know about life, and its relationship to matter, energy, and thermodynamics. With some simple examples I’ll also show how we can apply this to real (and imagined) questions, and what it suggests for the kinds of measurements and missions that could have the greatest astrobiological impact.

icy moons↗
NASA NTRS2016

GeneLab Phase 2: Integrated Search Data Federation of Space Biology Experimental Data

The GeneLab project is a science initiative to maximize the scientific return of omics data collected from spaceflight and from ground simulations of microgravity and radiation experiments, supported by a data system for a public bioinformatics repository and collaborative analysis tools for these data. The mission of GeneLab is to maximize the utilization of the valuable biological research resources aboard the ISS by collecting genomic, transcriptomic, proteomic and metabolomic (so-called omics) data to enable the exploration of the molecular network responses of terrestrial biology to space environments using a systems biology approach. All GeneLab data are made available to a worldwide network of researchers through its open-access data system. GeneLab is currently being developed by NASA to support Open Science biomedical research in order to enable the human exploration of space and improve life on earth. Open access to Phase 1 of the GeneLab Data Systems (GLDS) was implemented in April 2015. Download volumes have grown steadily, mirroring the growth in curated space biology research data sets (61 as of June 2016), now exceeding 10 TB/month, with over 10,000 file downloads since the start of Phase 1. For the period April 2015 to May 2016, most frequently downloaded were data from studies of Mus musculus (39) followed closely by Arabidopsis thaliana (30), with the remaining downloads roughly equally split across 12 other organisms (each 10 of total downloads). GLDS Phase 2 is focusing on interoperability, supporting data federation, including integrated search capabilities, of GLDS-housed data sets with external data sources, such as gene expression data from NIHNCBIs Gene Expression Omnibus (GEO), proteomic data from EBIs PRIDE system, and metagenomic data from Argonne National Laboratory's MG-RAST. GEO and MG-RAST employ specifications for investigation metadata that are different from those used by the GLDS and PRIDE (e.g., ISA-Tab). The GLDS Phase 2 system will implement a Google-like, full-text search engine using a Service-Oriented Architecture by utilizing publicly available RESTful web services Application Programming Interfaces (e.g., GEO Entrez Programming Utilities) and a Common Metadata Model (CMM) in order to accommodate the different metadata formats between the heterogeneous bioinformatics databases. GLDS Phase 2 completion with fully implemented capabilities will be made available to the general public in September 2017.

Space Biology↗
DOE OSTI2025

RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species

Abstract We introduce RWRtoolkit, a multiplex generation, exploration, and statistical package built for R and command-line users. RWRtoolkit enables the efficient exploration of large and highly complex biological networks generated from custom experimental data and/or from publicly available datasets, and is species agnostic. A range of functions can be used to find topological distances between biological entities, determine relationships within sets of interest, search for topological context around sets of interest, and statistically evaluate the strength of relationships within and between sets. The command-line interface is designed for parallelization on high-performance cluster systems, which enables high-throughput analysis such as permutation testing. Several tools in the package have also been made available for use in reproducible workflows via the KBase web application.

Kainer, David (ORCID:0000000172714676)↗
NASA NTRS1994

Use of Molecular Fossils for the Interpretation of Paleoenvironments on Early Earth: The Synthesis of Lipid Biomarkers by Methane-Oxidizing Bacteria

Over the course of Earth's history, the most important biological influence has come from the evolution of oxygenic photosynthesis and the development of an oxygen-rich biosphere. Although the availability of free oxygen had profound effects on subsequent biological and planetary evolution, clear paleobiological evidence of the timing of this transition is lacking. Recent technical advances in the microanalysis of organic matter has made it possible to detect residual molecules (biomarkers) in proterozoic (2.5 to 0.6 billion years) sedimentary rock characteristic of specific groups of microorganisms. When coupled with the carbon isotopic fractionations characteristic of biological systems and the new field of compound specific isotope analysis, biomarkers could prove to be a powerful tool for decoding ancient biochemistry from the geological record. We have been studying the carbon isotope fractionations associated with the synthesis of organic biomarker molecules in several types of methane-oxidizing bacteria that should have been key to carbon cycling in paleoenvironments after the evolution of oxygenic photosynthesis.

Jahnke, Linda L.↗
DOE OSTI2024

Hierarchical Conditioning of Diffusion Models Using Tree-of-Life for Studying Species Evolution

A central problem in biology is to understand how organisms evolve and adapt to their environment by acquiring variations in the observable characteristics or traits of species across the tree of life. With the growing availability of large-scale image repositories in biology and recent advances in generative modeling, there is an opportunity to accelerate the discovery of evolutionary traits automatically from images. Toward this goal, we introduce Phylo-Diffusion, a novel framework for conditioning diffusion models with phylogenetic knowledge represented in the form of HIERarchical Embeddings (HIER-Embeds). We also propose two new experiments for perturbing the embedding space of Phylo-Diffusion: trait masking and trait swapping, inspired by counterpart experiments of gene knockout and gene editing/swapping. Our work represents a novel methodological advance in generative modeling to structure the embedding space of diffusion models using tree-based knowledge. Our work also opens a new chapter of research in evolutionary biology by using generative models to visualize evolutionary changes directly from images. We empirically demonstrate the usefulness of Phylo-Diffusion in capturing meaningful trait variations for fishes and birds, revealing novel insights about the biological mechanisms of their evolution. (Model and code can be found at imageomics.github.io/phylo-diffusion)

Khurana, Mridul↗
DOE OSTI2022

Allosteric regulation of glycogen breakdown by the second messenger cyclic di-GMP

Streptomyces are our principal source of antibiotics, which they generate concomitant with a complex developmental transition from vegetative hyphae to spores. c-di-GMP acts as a linchpin in this transition by binding and regulating the key developmental regulators, BldD and WhiG. Here we show that c-di-GMP also binds the glycogen-debranching-enzyme, GlgX, uncovering a direct link between c-di-GMP and glycogen metabolism in bacteria. Further, we show c-di-GMP binding is required for GlgX activity. We describe structures of apo and c-di-GMP-bound GlgX and, strikingly, their comparison shows c-di-GMP induces long-range conformational changes, reorganizing the catalytic pocket to an active state. Glycogen is an important glucose storage compound that enables animals to cope with starvation and stress. Our in vivo studies reveal the important biological role of GlgX in Streptomyces glucose availability control. Overall, we identify a function of c-di-GMP in controlling energy storage metabolism in bacteria, which is widespread in Actinobacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Optogenetics and biosensors set the stage for metabolic cybergenetics

We report cybergenetic systems use computer interfaces to enable feed-back controls over biological processes in real time. The complex and dynamic nature of cellular metabolism makes cybergenetics attractive for controlling engineered metabolic pathways in microbial fermentations. Cybergenetics would not only create new avenues of research into cellular metabolism, it would also enable unprecedented strategies for pathway optimization and bioreactor operation and automation. Implementation of metabolic cybergenetics, however, will require new capabilities from actuators, biosensors, and control algorithms. The recent application of optogenetics in metabolic engineering, the expanding role of genetically encoded biosensors in strain development, and continued progress in control algorithms for biological processes suggest that this technology will become available in the not so distant future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Active microbial biomass decreases, but microbial growth potential remains similar across soil depth profiles under deeply-vs. shallow-rooted plants

Climate-smart land management practices that replace shallow-rooted annual crop systems with deeply-rooted perennial plants can contribute to soil carbon sequestration. However, deep soil carbon accrual may be influenced by active microbial biomass and their capacity to assimilate fresh carbon at depth. Incorporating active microbial biomass, dormancy, and growth in microbially-explicit models can improve our ability to predict soil's capacity to store carbon. But, so far, the microbial parameters that are needed for such modeling are poorly constrained, especially in deep soil layers. Here, we used a lab incubation experiment and growth kinetics model to estimate how microbial parameters vary along 240 cm of soil depth in profiles under shallow- (soy) and deeply-rooted (switchgrass) plants 11 years after plant cover conversion. We also assessed resource origin and availability (total organic carbon, 14 C, extractable organic carbon, specific UV absorbance of K 2 SO 4 extractable organic C, total nitrogen, total dissolved nitrogen) along the soil profiles to examine associations between soil chemical and biological parameters. Even though root biomass was greater and rooting depth was deeper under switchgrass than soy, resource availability and microbial growth parameters were generally similar between vegetation types. Instead, depth significantly influenced soil chemical and biological parameters. For example, resource availability and total and relative active microbial biomass decreased with soil depth. Decreases in the relative active microbial biomass coincided with increased lag time (response time to external carbon inputs) along the soil profiles. Even at a depth of 210–240 cm, microbial communities were activated to grow by added resources within a day. Maximum specific growth rate decreased to a depth of 90 cm and then remained consistent in deeper layers. Our findings show that >10 years of vegetation and rooting depth changes may not be long enough to alter microbial growth parameters, and suggest that at least a portion of the microbial community in deep soils can grow rapidly in response to added resources. Our study determined microbial growth parameters that can be used in microbially-explicit models to simulate carbon dynamics in deep soil layers.

14C↗
NASA NTRS1988

USSR Space Life Sciences Digest, issue 14

This is the fourteenth issue of NASA's USSR Space Life Sciences Digest. It contains abstracts of 32 papers recently published in Russian language periodicals and bound collections and of three new Soviet monographs. Selected abstracts are illustrated with figures and tables from the original. Also included is a review of a recent Soviet conference on Space Biology and Aerospace Medicine. Current Soviet life sciences titles available in English are cited. The materials included in this issue have been identified as relevant to the following areas of aerospace medicine and space biology: adaptation, biological rhythms, body fluids, botany, cardiovascular and respiratory systems, developmental biology, endocrinology, enzymology, equipment and instrumentation, gastrointestinal systems, habitability and environment effects, human performance, immunology, life support systems, mathematical modeling, metabolism, musculoskeletal system, neurophysiology, nutrition, operational medicine, perception, personnel selection, psychology, radiobiology, and space biology and medicine.

Hooke, Lydia Razran↗
DOE OSTI2021

Light Regulation of Phytoplankton Growth in San Francisco Bay Studied Using a 3D Sediment Transport Model

In San Francisco Bay (SFB), light availability is largely determined by the concentration of suspended particulate matter (SPM) in the water column. SPM exhibits substantial variation with time, depth, and location. To study how SPM influences light and phytoplankton growth, we coupled a sediment transport model with a hydrodynamic model and a biogeochemical model. The coupled models were used to simulate conditions for the year of 2011 with a focus on northern SFB. For comparison, two simulations were conducted with ecosystem processes driven by SPM concentrations supplied by the sediment transport model and by applying a constant SPM concentration of 20 mg l –1 . The sediment transport model successfully reproduced the general pattern of SPM variation in northern SFB, which improved the chlorophyll-a simulation resulting from the biogeochemical model, with vertically integrated primary productivity varying greatly, from 40 g[C] m –2 year –1 over shoals to 160 g[C] m –2 year –1 in the deep channel. Primary productivity in northern SFB is influenced by euphotic zone depth ( Ze ). Our results show that Ze in shallow water regions (<2 m) is mainly determined by water depth, while Ze in deep water regions is controlled by SPM concentration. As a result, Ze has low (high) values in shallow (deep) water regions. Large (small) differences in primary productivity exist between the two simulations in deep (shallow) water regions. Furthermore, we defined a new parameter F light for “averaged light limitation” in the euphotic zone. The averaged chlorophyll-a concentration in the euphotic zone and F light share a similar distribution such that both have high (low) values in shallow (deep) water regions. Our study demonstrates that light is a critical factor in regulating the phytoplankton growth in northern SFB, and a sediment transport model improves simulation of light availability in the water column.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Biochemical Conversion of Lignocellulosic Biomass to Hydrocarbon Fuels and Products (2021 State of Technology and Future Research)

The annual State of Technology (SOT) assessment is an essential activity for biochemical platform research. It allows the impact of research progress to be quantified in terms of economic improvements in the overall cellulosic biofuel production process for a particular conversion pathway. As such, initial benchmarks can be established for currently demonstrated performance and progress can be tracked towards out-year goals to ultimately demonstrate cost-competitive cellulosic biofuel technology. The purpose of this report is to benchmark the latest experimental developments across a number of potential bioconversion pathways as quantified by modeled minimum fuel selling prices (MFSPs), as a measure of current status relative to those final targets. For this state of technology, TEA models were run for two separate biological conversion pathways to fuels, based on available data for integrated biomass deconstruction and hydrolysate processing; namely carboxylic acids (primarily butyric acid) and diols (2,3-butanediol [BDO]), reflecting NREL's recently-published 2018 biochemical design report focused on those two pathways. The models were run across three scenarios for lignin utilization, namely combustion, conversion to coproducts based on "base case" performance with biomass hydrolysate, and conversion to coproducts based on "high" performance demonstrated with model lignin monomer components. A key improvement reflected in the 2021 SOT is centered around making use of the latest lignin conversion data, which over the past year focused primarily on production of ß-ketoadipate (BKA) as a more optimal molecule compared to the closely-related adipic acid coproduct of prior recent focus, both in terms of superior product properties and biology, as well as reduced processing complexity (reducing two steps for sequential production of muconate followed by hydrogenation to adipic acid down to a single step for direct production of BKA). This update translated to a roughly 17% increase in mass yield of final coproduct output at a nearly four-fold increase in fermentation productivity on lignin monomers relative to prior 2020 SOT benchmarks for muconic/adipic acid production.

09 BIOMASS FUELS↗