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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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At least 541 records · Page 30
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DOE OSTI2024

Exabiome: Advancing Microbial Science through Exascale Computing

The Exabiome project seeks to improve the understanding of microbiomes through the development of methods for accelerating metagenomic science using exascale computing. This article gives an overview of scientific impact of the three components of the project: metagenome assembly, protein family detection, and comparative analysis of metagenomes. Exabiome developed MetaHipMer, the only metagenome assembler capable of scaling to full exascale systems. MetaHipMer has enabled ground-breaking assemblies on the Frontier supercomputer, with many scientific benefits, such as the discovery of rare species and viral genomes. To investigate protein families, Exabiome developed two exascale tools, PASTIS and HipMCL. Together, these can utilize exascale resources to understand the functional diversity of billions of dark matter proteins and novel protein families. For comparative analysis, Exabiome developed kmerprof, a tool that can be used to compare huge metagenomes for many different scientific purposes, for example, grouping human microbiomes according to body location.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

OrthoPhyl—streamlining large-scale, orthology-based phylogenomic studies of bacteria at broad evolutionary scales

Abstract There are a staggering number of publicly available bacterial genome sequences (at writing, 2.0 million assemblies in NCBI's GenBank alone), and the deposition rate continues to increase. This wealth of data begs for phylogenetic analyses to place these sequences within an evolutionary context. A phylogenetic placement not only aids in taxonomic classification but informs the evolution of novel phenotypes, targets of selection, and horizontal gene transfer. Building trees from multi-gene codon alignments is a laborious task that requires bioinformatic expertise, rigorous curation of orthologs, and heavy computation. Compounding the problem is the lack of tools that can streamline these processes for building trees from large-scale genomic data. Here we present OrthoPhyl, which takes bacterial genome assemblies and reconstructs trees from whole genome codon alignments. The analysis pipeline can analyze an arbitrarily large number of input genomes (>1200 tested here) by identifying a diversity-spanning subset of assemblies and using these genomes to build gene models to infer orthologs in the full dataset. To illustrate the versatility of OrthoPhyl, we show three use cases: E. coli/Shigella, Brucella/Ochrobactrum and the order Rickettsiales. We compare trees generated with OrthoPhyl to trees generated with kSNP3 and GToTree along with published trees using alternative methods. We show that OrthoPhyl trees are consistent with other methods while incorporating more data, allowing for greater numbers of input genomes, and more flexibility of analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Non-target RNA depletion strategy to improve sensitivity of next-generation sequencing for the detection of RNA viruses in poultry

PCR-based assays have become the benchmark for detecting pathogens of poultry and other livestock; however, these techniques are limited in their ability to detect multiple infecting agents, provide limited genetic information on the pathogen, and, for RNA viruses, must be reviewed frequently to assure high sensitivity and specificity. In contrast, untargeted, high-throughput sequencing can rapidly detect all infecting agents in a sample while providing genomic sequence information to allow more in-depth characterization of viruses. Although next-generation sequencing (NGS) offers many advantages, one of its primary limitations is low sensitivity to pathogens given the abundance of host and other non-target sequences in sequencing libraries. We explored methods for improving the sensitivity of NGS to detect respiratory and enteric viruses in poultry from RNA extracts of swab samples. We employed commercial and custom-designed negative enrichment strategies to selectively deplete the most abundant rRNA reads from the host and non-target bacteria; host RNA was diminished from up to 40% of total reads to as low as 3%, and the total number of reads assigned to abundant bacterial classes were reduced greatly. Our treatment resulted in up to a 700-fold increase in the number of viral reads, detection of a greater number of viral agents, and higher average genome coverage for pathogens. Depletion assays added only 2 h to the NGS library preparation workflow. Custom depletion probe design offered significant cost savings (US$7–12 per sample) compared to commercial kits (US$30–50 per sample).

Parris, D. Joshua↗
DOE OSTI2025

Community‐Level Metabolic Shifts Following Land Use Change in the Amazon Rainforest Identified by a Supervised Machine Leaning Approach

ABSTRACT The Amazon rainforest has been subjected to high rates of deforestation, mostly for pasturelands, over the last few decades. This change in plant cover is known to alter the soil microbiome and the functions it mediates, but the genomic changes underlying this response are still unresolved. In this study, we used a combination of deep shotgun metagenomics complemented by a supervised machine learning approach to compare the metabolic strategies of tropical soil microbial communities in pristine forests and long‐term established pastures in the Amazon. Machine learning‐derived metagenome analysis indicated that microbial community structures (bacteria, archaea and viruses) and the composition of protein‐coding genes were distinct in each plant cover type environment. Forest and pasture soils had different genomic diversities for the above three taxonomic groups, characterised by their protein‐coding genes. These differences in metagenome profiles in soils under forests and pastures suggest that metabolic strategies related to carbohydrate and energy metabolisms were altered at community level. Changes were also consistent with known modifications to the C and N cycles caused by long‐term shifts in aboveground vegetation and were also associated with several soil physicochemical properties known to change with land use, such as the C/N ratio, soil temperature and exchangeable acidity. In addition, our analysis reveals that these alterations in land use can also result in changes to the composition and diversity of the soil DNA virome. Collectively, our study indicates that soil microbial communities shift their overall metabolic strategies, driven by genomic alterations observed in pristine forests and long‐term established pastures with implications for the C and N cycles.

carbon and nitrogen cycles↗
DOE OSTI2022

Syntrophic Co-Cultures of Clostridium Organisms to Produce Higher Alcohols & Other C6-C8 Metabolites (Final Report)

The goal of this project was to advance the systems biology understanding and predictive modeling of synthetic & syntrophic Clostridium microbial consortia, focusing on elucidation of metabolic networks and environmental signals in the consortia. The project has direct applicability to lignocellulosic-biomass based production of higher alcohols as advanced biofuels and C6-C8 metabolites, that can be used as chemicals or serve as biofuel precursors. This project studied and optimized three synthetic syntrophic systems. It examined the population dynamics using flow-cytometry, time-lapse microscopy and PCR analysis. 13C-based tracer analyses was used to examine the metabolite exchange between the syntrophic cell populations and the impact of those interactions on the transcriptome of the individual populations. To enhance our analytical and predictive capabilities, genome-scale models (GSMs) for these syntrophies was developed. RNAseq data for these syntrophic coculture systems were acquired to enable a molecular level understanding of the syntrophies aiming to identify the genetic networks of each organism in the co-culture and compare those against the networks of pure cultures.

09 BIOMASS FUELS↗
DOE OSTI2020

Integrated Proteomic and Glycoproteomic Characterization of Human High-Grade Serous Ovarian Carcinoma

Many gene products exhibit great structural heterogeneity because of an array of modifications. These modifications are not directly encoded in the genomic template but often affect the functionality of proteins. Protein glycosylation plays a vital role in proper protein functions. However, the analysis of glycoproteins has been challenging compared with other protein modifications, such as phosphorylation. Here, we perform an integrated proteomic and glycoproteomic analysis of 83 prospectively collected high-grade serous ovarian carcinoma (HGSC) and 23 non-tumor tissues. Integration of the expression data from global proteomics and glycoproteomics reveals tumor-specific glycosylation, uncovers different glycosylation associated with three tumor clusters, and identifies glycosylation enzymes that were correlated with the altered glycosylation. In addition to providing a valuable resource, these results provide insights into the potentialroles of glycosylation in the pathogenesis of HGSC, with the possibility of distinguishing pathological outcomes of ovarian tumors from non-tumors, as well as classifying tumor clusters.

Hu, Yingwei↗
DOE OSTI2020

A genomic catalog of Earth’s microbiomes

Abstract The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to >10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, including metagenomes from human and animal hosts, engineered environments, and natural and agricultural soils, to capture extant microbial, metabolic and functional potential. This comprehensive catalog includes 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units spanning 135 phyla. The catalog expands the known phylogenetic diversity of bacteria and archaea by 44% and is broadly available for streamlined comparative analyses, interactive exploration, metabolic modeling and bulk download. We demonstrate the utility of this collection for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses. This resource underscores the value of genome-centric approaches for revealing genomic properties of uncultivated microorganisms that affect ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Multi-omics profiling of the cold tolerant Monoraphidium minutum 26B-AM in response to abiotic stress

Microalgae that are of interest for biofuel production must be able to tolerate environmental changes that occur in outdoor cultivation systems. While algal cultures may experience daily temperature fluctuations and seasonal environmental changes, the underlying mechanisms that control and regulate physiological responses and adaptation to environmental pressures are largely unknown. Systems-level characterization enabled by functional genomics can help identify biochemical pathways that promote stability and productivity of algae in various environmental conditions. Monoraphidium minutum 26B-AM, a freshwater green microalga, was identified as a top performer in biomass production in winter season screens. We sequenced the genome of M. minutum 26B-AM and applied our multi-omics pipeline to profile this high potential strain under high salt and cold temperature perturbations. Through comparative analysis, including other green algae in the class Chlorophyceae, we identified gene families unique to the genus Monoraphidium, including a desaturase that has been linked to cold tolerance in plants. We observed that osmolytes, such as trehalose, proline and betaine, accumulate under salt stress, coinciding with upregulation of genes involved in biosynthesis of these metabolites. From the genome annotation, we reconstructed a metabolic model to provide a detailed map of the metabolic pathways and can be used to simulate growth and reaction fluxes. This multi-omics analysis provides a foundation to explore algal strain potential for biofuel applications, guides strain engineering, and expands our understanding of metabolic and regulatory mechanisms of algae in applied systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Is selfing a reproductive assurance promoting polyploid establishment? Reduced fitness, leaky self‐incompatibility and lower inbreeding depression in neotetraploids

Premise Newly formed polyploids face significant obstacles to persistence and population establishment because of fitness costs of intercytotype mating. Selfing provides the opportunity to escape mate limitation, enabling production of new individuals and increasing the likelihood of fixation of new polyploid lineages. Still, association between self‐compatibility and polyploidy is not always clear. We compared self‐incompatibility and inbreeding depression in neotetraploids and their diploid progenitor to explore the direct effects of whole genome duplications on self‐incompatibility and the implications of ploidy‐driven changes for polyploid establishment. Methods Outcross and self‐pollinations were performed in diploids and synthetic neotetraploids of Jasione maritima var. maritima , and reproductive success was measured through fruit and seed production and seed germination. Self‐ and outcross offspring were grown under controlled conditions, and plant performance was measured through several fitness parameters. Results Neotetraploids showed an overall lower performance than diploids. Reproductive success was negatively affected by selfing in both cytotypes. However, greater variation in the expression of self‐incompatibility was observed in neotetraploids; additionally, developmental and physiological parameters were not affected by selfing on neotetraploids, with an overall similar fitness of outcrossed and selfed individuals, resulting in lower inbreeding depression indexes. Conclusions Neotetraploids might have benefited from selfing at initial stages after their formation. Genome duplications resulted in leaky self‐incompatibility, enabling the production of offspring under minority cytotype disadvantage with similar fitness as outcrossed offspring. Our results support theoretical assumptions that selfing might be important for neopolyploid establishment, although changes in self‐incompatibility might not be abrupt.

Siopa, Catarina↗
DOE OSTI2021

Trajectory of Growth of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants in Houston, Texas, January through May 2021, Based on 12,476 Genome Sequences

Certain genetic variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are of substantial concern because they may be more transmissible or detrimentally alter the pandemic course and disease features in individual patients. SARS-CoV-2 genome sequences from 12,476 patients in the Houston Methodist health care system diagnosed from January 1 through May 31, 2021 are reported here. Prevalence of the B.1.1.7 (Alpha) variant increased rapidly and caused 63% to 90% of new cases in the latter half of May. Eleven B.1.1.7 genomes had an E484K replacement in spike protein, a change also identified in other SARS-CoV-2 lineages. Compared with non–B.1.1.7-infected patients, individuals with B.1.1.7 had a significantly lower cycle threshold (a proxy for higher virus load) and significantly higher hospitalization rate. Other variants [eg, B.1.429 and B.1.427 (Epsilon), P.1 (Gamma), P.2 (Zeta), and R.1] also increased rapidly, although the magnitude was less than that in B.1.1.7. Twenty-two patients infected with B.1.617.1 (Kappa) or B.1.617.2 (Delta) variants had a high rate of hospitalization. Breakthrough cases (n = 207) in fully vaccinated patients were caused by a heterogeneous array of virus genotypes, including many not currently designated variants of interest or concern. Finally, in the aggregate, this study delineates the trajectory of SARS-CoV-2 variants circulating in a major metropolitan area, documents B.1.1.7 as the major cause of new cases in Houston, TX, and heralds the arrival of B.1.617 variants in the metroplex.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

CRISPR–Cas9-mediated nuclear transport and genomic integration of nanostructured genes in human primary cells

DNA nanostructures are a promising tool to deliver molecular payloads to cells. DNA origami structures, where long single-stranded DNA is folded into a compact nanostructure, present an attractive approach to package genes; however, effective delivery of genetic material into cell nuclei has remained a critical challenge. Here, we describe the use of DNA nanostructures encoding an intact human gene and a fluorescent protein encoding gene as compact templates for gene integration by CRISPR-mediated homology-directed repair (HDR). Our design includes CRISPR–Cas9 ribonucleoprotein binding sites on DNA nanostructures to increase shuttling into the nucleus. We demonstrate efficient shuttling and genomic integration of DNA nanostructures using transfection and electroporation. These nanostructured templates display lower toxicity and higher insertion efficiency compared to unstructured double-stranded DNA templates in human primary cells. Furthermore, our study validates virus-like particles as an efficient method of DNA nanostructure delivery, opening the possibility of delivering nanostructures in vivo to specific cell types. Together, these results provide new approaches to gene delivery with DNA nanostructures and establish their use as HDR templates, exploiting both their design features and their ability to encode genetic information. This work also opens a door to translate other DNA nanodevice functions, such as biosensing, into cell nuclei.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The parallelism motifs of genomic data analysis

Genomic datasets are growing dramatically as the cost of sequencing continues to decline and small sequencing devices become available. Enormous community databases store and share these data with the research community, but some of these genomic data analysis problems require large-scale computational platforms to meet both the memory and computational requirements. These applications differ from scientific simulations that dominate the workload on high-end parallel systems today and place different requirements on programming support, software libraries and parallel architectural design. For example, they involve irregular communication patterns such as asynchronous updates to shared data structures. We consider several problems in high-performance genomics analysis, including alignment, profiling, clustering and assembly for both single genomes and metagenomes. We identify some of the common computational patterns or ‘motifs’ that help inform parallelization strategies and compare our motifs to some of the established lists, arguing that at least two key patterns, sorting and hashing, are missing. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Building a framework to genetically characterize “feather spots” and understand demographic impacts of solar energy sites on migratory bird populations

The lack of data on the impact of utility-scale solar facilities on avian species and populations adds to the cost of siting and operation. As much as 32 percent of the avian biological material (feathers and carcasses) recovered from solar facilities remain unidentified, because they often take the form of “feather spots”. Feather spots are remains of impacted animals that can be separated into two broad categories: 1) those remains that may be visually identified to a species, or 2) those that cannot be visually identified to a species due to degradation from the environment and/or scavenger activity (listed as “unknown”). Even when feather spots can be identified to species, they cannot be visually assigned to particular breeding populations. In some cases, it is unknown whether multiple feather spots represent single or multiple individuals. This project’s objectives were to: 1. Use a developed, genetic-based technique to identify and determine the species, population of origin, and number of individuals found in feather spots recovered from solar facilities. 2. Implement collected data and resulting analyses to develop a publicly accessible web-based decision-making tool that can be used by the solar industry, regulators and other stakeholders to inform siting, mitigation, and conservation management efforts. 3. Establish a not-for-profit fee-for-service center at UCLA to ensure collection and identification of feather spots continue after the project period of performance. During the Project Period, we proposed to establish a pipeline for collecting, transporting, and storing of avian biological material collected at solar facilities and the collection and identification of feather spots to species and individual. We proposed the development of a genetic-based framework that would recover viable DNA from feather spots, amplify this DNA (i.e., make millions of copies of the original DNA), and use it to match the resulting sequences to a national database of known species of birds. The result would be the identification of feathers spots that were previously unidentified, and the incorporation of these samples into a larger database that included all samples recovered from solar facilities. The resulting report (below) details the result of this work and its alignment with proposed activities. We proposed the use of the data collected to assess the comparative risk to specific species or populations of species from solar facilities. For some species, we have already identified genomic markers of specific breeding populations and developed “genoscapes,” maps of unique genetic variation across the full breeding range of a species. We used these (previously and newly developed) genoscapes to probabilistically link a feather spot to the specific breeding populations from which it originated (assignment probabilities range from 75%-100% depending on species and population groups). For those species without genoscapes, we developed a vulnerability and susceptibility estimate that determines the relative local and regional risk to populations that are in geographic proximity to solar facilities, using citizen science data (Breeding Bird Survey (BBS) and eBird). These two feather spot processing pipelines (see Figure 1 below) provide quantitative estimates as to the numbers of individuals from a given population of origin that are affected by solar facilities, and ultimately can reduce costs to the consumer by reducing the industry costs associated with mitigation and siting strategies for future solar energy development.

14 SOLAR ENERGY↗
NASA NTRS2019

Predicting Cancer Risk from Ionizing Radiation

The ability to predict cancer risk associated with exposure to low doses of high-LET ionizing radiation (IR) remains a challenge. Epidemiological methods lack the sensitivity and power to provide detailed risk estimates for cancer and ignore individual variance in IR sensitivity. We have hypothesized that DNA repair capacity can be used as a marker to evaluate and differentiate individual radiation sensitivity. More specifically, this work is based on the concept that the combined time-dose dependence of radiation-induced foci (RIF) of p53-binding protein 1 (53BP1) following low-LET exposure contains sufficient information to infer sensitivity to any other LET. Our hypothesis was tested in 15 different mouse strains as well as in primary human immune cells. We first approached individual ionizing radiation sensitivity in a mouse model by culturing primary skin fibroblasts extracted from 76 mice of 15 different genetic backgrounds and exposing them to HZE particles and X-rays. This work is one of the most extensive studies on the kinetics and possible genetic underpinnings of radiation-induced DNA damage and repair. Our results is in agreement with a DNA repair model we previously postulated, where nearby DNA double strand breaks (DSB) in the nucleus are brought together for more efficient repair, leading to RIF clustering. Such mechanism was evidenced by a specific dose and LET dependence of RIF numbers. Briefly, RIF quantification after low-LET X-ray exposure showed an asymptotic saturation for doses between 1 Gy and 4 Gy 4 hours post-irradiation across all 15 strains. The clustering of DSB across all strains also led to more RIF/Gy for lower LET (X-ray and 350 MeV/n Ar) than for higher LET (600 MeV/n Fe) 4 hours post-exposure. Considering the fact that the number of DSB/Gy should be independent of LET, our data suggest there are more DSB in individual RIF as the LET increases. RIF numbers for 24 and 48 hours post-exposure led to the inverse trend, with more remaining RIF/Gy for higher LET (by 600 MeV/n Fe). This result suggests cells have more difficulty resolving RIF from higher LET as they the number DSB/RIF increases. Note that for most conditions, the variance of RIF/Gy was small within individual animals of the same strain and large between strains, suggesting a strong genetics component. Furthermore, we present our preliminary data from an ongoing study on human genetic associations with IR sensitivity. To address the human variability in responses to HZE particle irradiation in a maximally comprehensive manner, we are in the process of collecting and isolating primary blood mononuclear cells from 768 healthy subjects of European descent, 18-75 years of age, 50/50 male/female distribution. We have analyzed 53BP1+ RIF formation as well as oxidative stress and cell death in primary cells from 192 subjects in response to the same HZE particles as used in mice: 600 MeV/n Fe, 350 MeV/n Ar and 350 MeV/n Si, 1.1 and 3 particles/100m2, 4 and 24 hours after irradiation. We will next complete the quantification of HZE particle-induced DNA and cellular damage in the remaining subjects and compare it to their responses to low-LET irradiation. Finally, we will perform GWAS analysis to identify human genomic associations with IR sensitivity and potential targets for biomarker development.

High-LET radiation↗
NASA NTRS2016

Draft Genome Sequences of Biosafety Level 2 Opportunistic Pathogens Isolated From the Environmental Surfaces of the International Space Station

The draft genome sequences of 20 biosafety level 2 (BSL-2) opportunistic pathogens isolated from the environmental surfaces of the International Space Station (ISS) were presented. These genomic sequences will help in understanding the influence of microgravity on the pathogenicity and virulence of these strains when compared with Earth strains.

Aleksandra Checinska Sielaff↗
DOE OSTI2022

A Unified Protocol for CRISPR/Cas9-Mediated Gene Knockout in Tephritid Fruit Flies Led to the Recreation of White Eye and White Puparium Phenotypes in the Melon Fly

Abstract Tephritid fruit flies are among the most invasive and destructive agricultural pests worldwide. Over recent years, many studies have implemented the CRISPR/Cas9 genome-editing technology to dissect gene functions in tephritids and create new strains to facilitate their genetics, management, and control. This growing literature allows us to compare diverse strategies for delivering CRISPR/Cas9 components into tephritid embryos, optimize procedures, and advance the technology to systems outside the most thoroughly studied species within the family. Here, we revisit five years of CRISPR research in Tephritidae and propose a unified protocol for candidate gene knockout in fruit flies using CRISPR/Cas9. We demonstrated the efficiency of our protocol by disrupting the eye pigmentation gene white eye (we) in the melon fly, Zeugodacus cucurbitae (Coquillett) (Diptera: Tephritidae). High rates of somatic and germline mutagenesis were induced by microinjecting pre-assembled Cas9-sgRNA complexes through the chorion of embryos at early embryogenesis, leading to the rapid development of new mutant lines. We achieved comparable results when targeting the we orthologue in the oriental fruit fly, Bactrocera dorsalis (Hendel) (Diptera: Tephritidae), illustrating the reliability of our methods when transferred to other related species. Finally, we functionally validated the recently discovered white pupae (wp) loci in the melon fly, successfully recreating the white puparium phenotype used in suppression programs of this and other major economically important tephritids. This is the first demonstration of CRISPR-based genome-editing in the genus Zeugodacus, and we anticipate that the procedures described here will contribute to advancing genome-editing in other non-model tephritid fruit flies.

Entomology↗
DOE OSTI2025

Polyphenol rewiring of the microbiome reduces methane emissions

Methane mitigation is regarded as a critical strategy to combat the scale of global warming. Currently, ~40% of methane emissions originate from microbial sources, which is causing strategies to suppress methanogens—either through direct toxic effects or by diverting their substrates and energy—to gain traction. Problematically, current microbial methane mitigation knowledge lacks detailed microbiome-centered insights, limiting translation across conditions and ecosystems. Here we utilize genome-resolved metatranscriptomes and metabolomes to assess the impact of a proposed methane inhibitor, catechin, on greenhouse gas emissions for high-methane-emitting peatlands. In microcosms, catechin drastically reduced methane emissions by 72%–84% compared to controls. Longitudinal sampling allowed for reconstruction of a catechin degradation pathway involving Actinomycetota and Clostridium, which break down catechin into smaller phenolic compounds within the first 21 days, followed by degradation of phenolic compounds by Pseudomonas_E from Days 21 to 35. These genomes co-expressed hydrogen-uptake genes, suggesting hydrogenases may act as a hydrogen sink during catechin degradation and consequently reduce hydrogen availability to methanogens. In support of this idea, there was decreased gene expression by hydrogenotrophic and hydrogen-dependent methylotrophic methanogens under catechin treatment. There was also reduced gene expression from genomes inferred to be functioning syntrophically with hydrogen-utilizing methanogens. We propose that catechin metabolic redirection effectively starves hydrogen-utilizing methanogens, offering a potent avenue for curbing methane emissions across diverse environments including ruminants, landfills, and constructed or managed wetlands.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Nasa GeneLab Computomics Reveal Horizontal Gene Transfer on International Space Station Environmental Metagenomes

Prokaryotic lifeforms can be observed to demonstrate many keen adaptive advantages, perhaps facilitated by a nature simplistic relative to divergent domains of life. In particular, decompartmentalized gene expression facilitates adaptation by allowing free exchange of genetic material, albeit at the cost of increased susceptibility to genetic damage. Thus, these lifeforms must compensate by embracing diverse investment strategies in an attempt to “brute force” the evolvability equation through precipitous genesis, lean metabolic efficiency, and sheer population. This prokaryotic archetype also enables symbiotic relationships with secondary mobile genetic elements known as plasmids, which have been shown to drive evolution on rapid temporal scales through processes such as conjugation and transformation. This study attempts to decipher whether these mechanisms of horizontal gene transfer (HGT) are major factors in determining prokaryote fitness within a unique isolated environment, the International Space Station (ISS). The ISS Microbial Tracking (MT) project has generated a wealth of data concerning the successive reigns of microbial genera that appear to thrive amidst harsh conditions for life. Despite relatively higher doses of ionizing radiation as compared to Earth, complications associated with microgravity, and the anti-microbial mélange deployed, microbial life still persists in this environment. The NASA GeneLab serves as a data repository and analysis platform to enable researchers to access space flight factor related data. With the use of GeneLab’s modern computational suites (computomics), phylogenetic and functional genomic investigations of HGT events were conducted on the data generated from the MT-1 project. The putative data concerning the plasmid population (plasmidome) of the ISS was algorithmically derived and compared to those of habitats with similar environmental dynamics- such as living quarters and hospitals- to investigate whether these HGT elements may play crucial role(s) in shaping the microbiome of this closed habitat that serves as the only inhabited structure in space.

Bense, Nicholas↗