Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “rhizosphere”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Genome-wide fitness profiling reveals molecular mechanisms that bacteria use to interact with Trichoderma atroviride exometabolites

Trichoderma spp. are ubiquitous rhizosphere fungi capable of producing several classes of secondary metabolites that can modify the dynamics of the plant-associated microbiome. However, the bacterial-fungal mechanisms that mediate these interactions have not been fully characterized. Here, a random barcode transposon-site sequencing (RB-TnSeq) approach was employed to identify bacterial genes important for fitness in the presence of Trichoderma atroviride exudates. We selected three rhizosphere bacteria with RB-TnSeq mutant libraries that can promote plant growth: the nitrogen fixers Klebsiella michiganensis M5aI and Herbaspirillum seropedicae SmR1, and Pseudomonas simiae WCS417. As a non-rhizosphere species, Pseudomonas putida KT2440 was also included. From the RB-TnSeq data, nitrogen-fixing bacteria competed mainly for iron and required the siderophore transport system TonB/ExbB for optimal fitness in the presence of T . atroviride exudates. In contrast, P . simiae and P . putida were highly dependent on mechanisms associated with membrane lipid modification that are required for resistance to cationic antimicrobial peptides (CAMPs). A mutant in the Hog1-MAP kinase (Δ tmk 3) gene of T . atroviride showed altered expression patterns of many nonribosomal peptide synthetase (NRPS) biosynthetic gene clusters with potential antibiotic activity. In contrast to exudates from wild-type T . atroviride , bacterial mutants containing lesions in genes associated with resistance to antibiotics did not show fitness defects when RB-TnSeq libraries were exposed to exudates from the Δ tmk3 mutant. Unexpectedly, exudates from wild-type T . atroviride and the Δ tmk 3 mutant rescued purine auxotrophic mutants of H . seropedicae , K . michiganensis and P . simiae . Metabolomic analysis on exudates from wild-type T . atroviride and the Δ tmk 3 mutant showed that both strains excrete purines and complex metabolites; functional Tmk3 is required to produce some of these metabolites. This study highlights the complex interplay between Trichoderma -metabolites and soil bacteria, revealing both beneficial and antagonistic effects, and underscoring the intricate and multifaceted nature of this relationship.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Luteolibacter sp. strain Populi

Luteolibacter sp. strain Populi is bacterium from the phylum Verrucomicrobiota, isolated from the rhizosphere of a black cottonwood tree, Populus trichocarpa, from the Cascade mountains in Washington. Its 6.6 Mb chromosome was completely sequenced using Oxford Nanopore long-reads and is predicted to encode 5301 proteins and 60 RNAs. The bacteria was isolated from the rhizosphere of a mature Populus trichocarpa from the Tieton riverwatershed of Washington state, USA (Lat: 46°42’9” N, Lon: 120°25 39’36” W). A rhizosphere sample (fine roots and adhering soil) was used to obtain a microbial fraction by centrifugation on Histodenz (12) and stained with 5µM Syto59 (Thermo Fisher Scientific Inc). A Cytopeia Influx cell sorter (BD, Franklin Lakes, NJ) was used to sort and array single cells (100 per plate) based on forward-side scatter and fluorescence intensity on asparagine-glucose nutrient agar (ATCC medium 184). The Luteolibacter sp. Populi genome sequence has been deposited in GenBank under the accession number CP161812. A draft genome annotated with Prokka and DRAM is available in this Narrative as Luteolibacter_sp_Prokka.240711.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Assessment of Bacterial Inoculant Delivery Methods for Cereal Crops

Despite growing evidence that plant growth-promoting bacteria can be used to improve crop vigor, a comparison of the different methods of delivery to determine which is optimal has not been published. An optimal inoculation method ensures that the inoculant colonizes the host plant so that its potential for plant growth-promotion is fully evaluated. The objective of this study was to compare the efficacy of three seed coating methods, seedling priming, and soil drench for delivering three bacterial inoculants to the sorghum rhizosphere and root endosphere. The methods were compared across multiple time points under axenic conditions and colonization efficiency was determined by quantitative polymerase chain reaction (qPCR). Two seed coating methods were also assessed in the field to test the reproducibility of the greenhouse results under non-sterile conditions. In the greenhouse seed coating methods were more successful in delivering the Gram-positive inoculant (Terrabacter sp.) while better colonization from the Gram-negative bacteria (Chitinophaga pinensis and Caulobacter rhizosphaerae) was observed with seedling priming and soil drench. This suggested that Gram-positive bacteria may be more suitable for the seed coating methods possibly because of their thick peptidoglycan cell wall. We also demonstrated that prolonged seed coating for 12 h could effectively enhance the colonization of C. pinensis, an endophytic bacterium, but not the rhizosphere colonizing C. rhizosphaerae. In the field only a small amount of inoculant was detected in the rhizosphere. This comparison demonstrates the importance of using the appropriate inoculation method for testing different types of bacteria for their plant growth-promotion potential.

Terrabacter↗
DOE OSTI2024

Plant root associated chitinases: structures and functions

Chitinases degrade chitin, a linear homopolymer of β-1,4-linked N-acetyl-D-glucosamine (GlcNAc) residues found in the cell walls of fungi and the exoskeletons of arthropods. They are secreted by the roots into the rhizosphere, a complex and dynamic environment where intense nutrient exchange occurs between plants and microbes. Here we modeled, expressed, purified, and characterized Zea mays and Oryza sativa root chitinases, and the chitinase of a symbiotic bacterium, Chitinophaga oryzae 1303 for their activities with chitin, di-, tri-, and tetra-saccharides and Aspergillus niger, with the goal of determining their role(s) in the rhizosphere and better understanding the molecular mechanisms underlying plant-microbe interactions. We show that Zea mays basic endochitinase (ZmChi19A) and Oryza sativa chitinase (OsChi19A) are from the GH19 chitinase family. The Chitinophaga oryzae 1303 chitinase (CspCh18A) belongs to the GH18 family. The three enzymes have similar apparent K M values of (20-40 µM) for the substrate 4-MU-GlcNAc 3 . They vary in their pH and temperature optima with OsChi19A activity optimal between pH 5–7 and 30–40°C while ZmChi19A and CspCh18A activities were optimal at pH 7-9 and 50–60°C. Modeling and site-directed mutation of ZmChi19A identified the catalytic cleft and the active residues E147 and E169 strategically positioned at ~8.6Å from each other in the folded protein. Cleavage of 4-MU-GlcNAc 3 was unaffected by the absence of the CBD but diminished in the absence of the flexible C-terminal domain. However, unlike for the soluble substrate, the CBD and the newly identified flexible C-terminal domain were vital for inhibiting Aspergillus niger growth. The results are consistent with the involvement of the plant chitinases in defense against pathogens like fungi that have chitin exoskeletons. In summary, we have characterized the functional features and structural domains necessary for the activity of two plant root chitinases that are believed to be involved in plant defense and a bacterial chitinase that, along with the plant chitinases, may participate in nutrient recycling in the rhizosphere.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Microfabrication of a Chamber for High-Resolution, In Situ Imaging of the Whole Root for Plant–Microbe Interactions

Fabricated ecosystems (EcoFABs) offer an innovative approach to in situ examination of microbial establishment patterns around plant roots using nondestructive, high-resolution microscopy. Previously high-resolution imaging was challenging because the roots were not constrained to a fixed distance from the objective. Here, we describe a new ‘Imaging EcoFAB’ and the use of this device to image the entire root system of growing Brachypodium distachyon at high resolutions (20×, 40×) over a 3-week period. The device is capable of investigating root–microbe interactions of multimember communities. We examined nine strains of Pseudomonas simiae with different fluorescent constructs to B. distachyon and individual cells on root hairs were visible. Succession in the rhizosphere using two different strains of P. simiae was examined, where the second addition was shown to be able to establish in the root tissue. The device was suitable for imaging with different solid media at high magnification, allowing for the imaging of fungal establishment in the rhizosphere. Overall, the Imaging EcoFAB could improve our ability to investigate the spatiotemporal dynamics of the rhizosphere, including studies of fluorescently-tagged, multimember, synthetic communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Impacts of The Wetland Sedge Carex aquatilis on Microbial Community and Methane Metabolisms

Microbial activity in the soil of wetlands is responsible for the emission of more methane to the atmosphere than all other natural sources combined. This microbial activity is heavily impacted by plant roots, which influence the microbial community by exuding organic compounds and by leaking oxygen into an otherwise anoxic environment. This study compared the microbial communities of planted and unplanted wetland soil from an Alaskan bog to elucidate how plant growth influences populations and metabolisms of methanogens and methanotrophs. A common boreal wetland sedge, Carex aquatilis, was grown in the laboratory and DNA samples were sequenced from the rhizosphere, unplanted bulk soil, and a simulated rhizosphere with oxygen input but no organic carbon. The abundance of both methanogens and methanotrophs were positively correlated with methane emissions. Among the methanotrophs, both aerobic and anaerobic methane oxidizing microbes were more common in the rhizosphere of mature plants than in unplanted soil, while facultative methanotrophs capable of utilizing either methane or other molecules became relatively less common. Furthermore, these trends indicate that the roots in this experiment created an environment which favored highly specialized microbial metabolisms over generalist approaches. One aspect of this specialized microbiome is the presence of both aerobic and anaerobic metabolisms, which indicates that oxygen is present but is a limiting resource controlling competition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Synthetic Biology Toolbox for Nitrogen-Fixing Soil Microbes

The soil environment adjacent to plant roots, termed the rhizosphere, is home to a wide variety of microorganisms that can significantly affect the physiology of nearby plants. Microbes in the rhizosphere can provide nutrients, secrete signaling compounds, and inhibit pathogens. These processes could be manipulated with synthetic biology to enhance the agricultural performance of crops grown for food, energy, or environmental remediation, if methods can be implemented in these nonmodel microbes. A common first step for domesticating nonmodel organisms is the development of a set of genetic engineering tools, termed a synthetic biology toolbox. A toolbox comprises transformation protocols, replicating vectors, genome engineering (e.g., CRISPR/Cas9), constitutive and inducible promoter systems, and other gene expression control elements. Furthermore, this work validated synthetic biology toolboxes in three nitrogen-fixing soil bacteria: Azotobacter vinelandii, Stutzerimonas stutzeri (Pseudomonas stutzeri), and a new isolate of Klebsiella variicola. All three organisms were amenable to transformation and reporter protein expression, with several functional inducible systems available for each organism. S. stutzeri and K. variicola showed more reliable plasmid-based expression, resulting in successful Cas9 recombineering to create scarless deletions and insertions. Using these tools, we generated mutants with inducible nitrogenase activity and introduced heterologous genes to produce resorcinol products with relevant biological activity in the rhizosphere.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Co-occurrence networks reveal more complexity than community composition in resistance and resilience of microbial communities

Plant response to drought stress involves fungi and bacteria that live on and in plants and in the rhizosphere, yet the stability of these myco- and micro-biomes remains poorly understood. We investigate the resistance and resilience of fungi and bacteria to drought in an agricultural system using both community composition and microbial associations. Here we show that tests of the fundamental hypotheses that fungi, as compared to bacteria, are (i) more resistant to drought stress but (ii) less resilient when rewetting relieves the stress, found robust support at the level of community composition. Results were more complex using all-correlations and co-occurrence networks. In general, drought disrupts microbial networks based on significant positive correlations among bacteria, among fungi, and between bacteria and fungi. Surprisingly, co-occurrence networks among functional guilds of rhizosphere fungi and leaf bacteria were strengthened by drought, and the same was seen for networks involving arbuscular mycorrhizal fungi in the rhizosphere. We also found support for the stress gradient hypothesis because drought increased the relative frequency of positive correlations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Bioactive diterpenoids impact the composition of the root-associated microbiome in maize (Zea mays)

Abstract Plants deploy both primary and species-specific, specialized metabolites to communicate with other organisms and adapt to environmental challenges, including interactions with soil-dwelling microbial communities. However, the role of specialized metabolites in modulating plant-microbiome interactions often remains elusive. In this study, we report that maize ( Zea mays ) diterpenoid metabolites with known antifungal bioactivities also influence rhizosphere bacterial communities. Metabolite profiling showed that dolabralexins, antibiotic diterpenoids that are highly abundant in roots of some maize varieties, can be exuded from the roots. Comparative 16S rRNA gene sequencing determined the bacterial community composition of the maize mutant Zman2 ( anther ear 2 ), which is deficient in dolabralexins and closely related bioactive kauralexin diterpenoids. The Zman2 rhizosphere microbiome differed significantly from the wild-type sibling with the most significant changes observed for Alphaproteobacteria of the order Sphingomonadales. Metabolomics analyses support that these differences are attributed to the diterpenoid deficiency of the Zman2 mutant, rather than other large-scale metabolome alterations. Together, these findings support physiological functions of maize diterpenoids beyond known chemical defenses, including the assembly of the rhizosphere microbiome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Bio‐Imaging quorum sensing signal molecules in a soil‐mimic gel

Rhizosphere, the narrow region surrounding plant roots directly influenced by root exudates and the root associated microbiome, plays an important role in plant productivity and the rhizosphere is well known for stimulating microbial metabolic activities. How microbial communities interact to form stable, metabolically interconnected functional communities is an area of intense interest. The question remains on how microbially produced secreted molecules that function as intercellular communication signals shape the structure and function of microbial communities. Our goal is to detect and quantify signal molecules produced by microbes or plants in the root‐soil environment, spatially and temporarily. As a proof‐of‐concept, we are imaging diffusible extracellular microbial metabolites involved in a bacteria‐bacteria communication process called quorum‐sensing. Quorum‐sensing relies on the accumulation of high concentrations of signal molecules in the environment to control bacterial gene expression, influencing rhizosphere colonization and plant health. Local concentration of quorum sensing molecules are determined using aptamer based sensors. Aptamers that can specifically bind the desired signal molecules are selected through SELEX and immobilized on the surface of nano‐porous membranes. Binding of the signal molecules and aptamer covered surface results in changes in surface charge distribution and steric hinderance and thus modifying the transmembrane ionic transport. Changes in transmembrane impedance can be measured through electrochemical impedance spectroscopy methods to monitor local concentrations of signal molecules. Sensor responses were determined for different concentrations of signal molecules and results showed detection of C4‐HSL in a soil‐mimic solution with K D of 10 nM. We demonstrate that the quorum‐sensing signal molecule C4‐homoserine lactone and (C4‐HSL) can rapidly diffuse in a soil‐mimic gel, providing evidence for our use of a soil‐mimic for further aptasensor development and validation. The sensors were then inserted into soil mimic gel for monitoring C4‐HSL diffusion and the resulted impedance changes were used to determine the C4‐HSL concentration at different positions in the gel. Measurements of local C4‐HSL concentrations variation and numerical solution of diffusion equation were used to create 4D images of C4‐HSL molecule diffusion in the soil‐mimic gel.

Jiang, Nianyu↗
DOE OSTI2025

Bacterial fitness for plant colonization is influenced by plant growth substrate

Despite advances in our understanding of bacterial plant colonization, the extent to which growth substrate influences the molecular mechanisms enabling bacteria to efficiently colonize plants remains poorly understood. To address this, we used randomly barcoded transposon mutagenesis sequencing (RB-TnSeq) in Paraburkholderia graminis OAS925, an efficient rhizosphere colonizer, and Brachypodium distachyon grown in six different substrates. Of the 382 rhizosphere colonization genes that we identified in OAS925, 348 genes (91.1%) are dependent on the growth substrate evaluated, and 34 genes (8.9%) are shared across all the substrates. Both the core and substrate-dependent colonization genes are from multiple functional categories, demonstrating the multifaceted and major impact that plant growth substrate has on bacterial colonization. The identified colonization genes and their varied importance across plant growth substrates could not be readily explained by differences in root exudate profiles, suggesting that the substrate environment itself plays an outsized role in the ability of a bacterium to colonize the rhizosphere. Our data confirm that bacterial fitness for plant colonization is strongly influenced by plant growth substrate type and highlights the importance of taking this parameter into consideration when engineering bacterial strains for improved host colonization.

Paraburkholderia↗
DOE OSTI2024

Genetic modification of the shikimate pathway to reduce lignin content in switchgrass ( Panicum virgatum L.) significantly impacts plant microbiomes

Switchgrass (Panicum virgatum L.) is considered a sustainable biofuel feedstock, given its fast-impact growth, low input requirements, and high biomass yields. Improvements in bioenergy conversion efficiency of switchgrass could be made by reducing its lignin content. Engineered switchgrass that expresses a bacterial 3-dehydroshikimate dehydratase (QsuB) has reduced lignin content and improved biomass saccharification due to the rerouting of the shikimate pathway towards the simple aromatic protocatechuate at the expense of lignin biosynthesis. However, the impacts of this QsuB trait on switchgrass microbiome structure and function remain unclear. To address this, wild-type and QsuB-engineered switchgrass were grown in switchgrass field soils, and samples were collected from inflorescences, leaves, roots, rhizospheres, and bulk soils for microbiome analysis. We investigated how QsuB expression influenced switchgrass-associated fungal and bacterial communities using high-throughput Illumina MiSeq amplicon sequencing of ITS and 16S rDNA. Compared to wild-type, QsuB-engineered switchgrass hosted different microbial communities in roots, rhizosphere, and leaves. Specifically, QsuB-engineered plants had a lower relative abundance of arbuscular mycorrhizal fungi (AMF). Additionally, QsuB-engineered plants had fewer Actinobacteriota in root and rhizosphere samples. These findings may indicate that changes in the plant metabolism impact both AMF and Actinobacteriota similarly or potential interactions between AMF and the bacterial community. This study enhances understanding of plant-microbiome interactions by providing baseline microbial data for developing beneficial bioengineering strategies and by assessing nontarget impacts of engineered plant traits on the plant microbiome.

09 BIOMASS FUELS↗
DOE OSTI2023

Rhizogrids and 3D molecular root imaging workflow

Rhizogrid guided molecular root imaging workflow enables investigating root rhizosphere interactions in a near native environment. Non-invasive root images are captured, and three-dimensional root images are reconstructed using x-ray computed tomography technique. Root and rhizosphere samples are then harvested and processed for root-rhizosphere metabolite and microbial profiling.

Handakumbura, Pubudu↗
DOE OSTI2024

Untargeted metabolite data from a root surface in a rhizobox

Raw data is provided from samples analyzed using separate reverse phase chromatographic methods on a high performance liquid chromatograph with mass spectrometry. These porewater samples were collected from a microdialysis which generated samples along the surface of a growing A. sative root (all_hc). This data was used to answer questions connecting rhizosphere metabolite (putatively identified metabolites, hc_putative_norm) changes over time (root growth) with changes in the surrounding rhizosphere biogeochemistry (DOC, redox, pH). Rhizosphere biogeochemistry values are provided in the hc_putative_norm file as averages over their respective range of time that they were collected at. The hc_putative_norm file also contains all normalized values over only the intensity values collected for putatively identified metabolites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

FUN-BioCROP model with litter decomposition parameters derived from the LIDET dataset

This repository contains the code and data necessary to run the FUN-BioCROP (Fixation and Uptake of Nitrogen-Bioenergy Carbon, Rhizosphere, Organisms, and Protection) model with litter decomposition parameters derived from a modified Monte Carlo simulation that used the Long-term Intersite Decomposition Experiment Team dataset. Related publication:Juice, S.M., Ridgeway, J.R., Hartman, M.D., Parton, W.J., Berardi, D.M., Sulman, B.N., Allen, K.E., & Brzostek, E.R. Reparameterizing litter decomposition using a simplified Monte Carlo method improves litter decay simulated by a microbial model and alters bioenergy soil carbon estimates. Description of Files: FUNBioCROP_LIDET Study.Rmd R code with FUN-BioCROP model that can be run with 10 different sets of parameters for litter decomposition (Baseline, LIDET, or eight other best parameter sets identified in the modified Monte Carlo simulation. CORPSE Functions_Bioenergy_V2.R Code with CORPSE model functions, called by FUNBioCROP_LIDET Study.Rmd Model Input Data: bulk.csv, bulk_till.csv, rhizo.csv, rhizo_till.csv, litter.csv Initial C and N (kg C or N/m2) pool values for each soil compartment, final values from spin up. All five files have the same columns: (Column - Description - Units) uFastC - Unprotected fast decomposing carbon - kg carbon/m2 uSlowC - Unprotected slow decomposing carbon - kg carbon/m2 uNecroC - Unprotected necromass carbon - kg carbon/m2 pFastC - Protected fast decomposing carbon - kg carbon/m2 pSlowC - Protected slow decomposing carbon - kg carbon/m2 pNecroC - Protected necromass carbon - kg carbon/m2 livingMicrobeC - Carbon in living microbial biomass - kg carbon/m2 uFastN - Unprotected fast decomposing nitrogen - kg nitrogen/m2 uSlowN - Unprotected slow decomposing nitrogen - kg nitrogen/m2 uNecroN - Unprotected necromass nitrogen - kg nitrogen/m2 pFastN - Protected fast decomposing nitrogen - kg nitrogen/m2 pSlowN - Protected slow decomposing nitrogen - kg nitrogen/m2 pNecroN - Protected necromass nitrogen - kg nitrogen/m2 inorganicN - Inorganic nitrogen - kg nitrogen/m2 CO2 - Carbon in carbon dioxide - kg carbon/m2 livingMicrobeN - Nitrogen in living microbial biomass - kg nitrogen/m2 Model Input Data: FluxTower_AvgSoilT.csv: Average daily soil temperature (oC) at 10 cm depth at University of Illinois Urbana-Champaign (UIUC) Energy Farm flux tower from 7/2008-3/2016. (One year of averaged data) Model Input Data: FluxTower_AvgSoilVWC.csv: Average daily soil volumetric water content (VWC) at 10 cm depth at UIUC Energy Farm flux tower from 7/2008-3/2016. (One year of averaged data) Model Input Data: input_CCS_LIDET Study.csv: This file has daily data to run FUN-BioCROP (Column - Description - Units): yr - calendar year - year doy - day of year (1 to 365) (no leap year) - day anpp - aboveground NPP (DayCent) - kg C/m2/day bnpp - belowground NPP (DayCent) - kg C/m2/day aglivc - live aboveground biomass carbon (DayCent) - kg C/m2 bglivcj - live juvenile fine root biomass carbon (DayCent) - kg C/m2 bglivcm - live mature fine root biomass carbon (DayCent) - kg C/m2 aglivn - live aboveground biomass nitrogen (DayCent) - kg N/m2 bglivnj - live juvenile fine root biomass nitrogen (DayCent) - kg N/m2 bglivnm - live mature fine root biomass nitrogen (DayCent) - kg N/m2 nyr - simulation year - year cult - indicates a cultivation event (0 or 1) crop - indicates a new crop (0 or 1) fert - indicates a fertilizer event (0 or 1) frst - indicates the first day of the growing season (0 or 1) harv - indicates a harvest event (0 or 1) last - indicates the end of the growing season (0 or 1) croptype - crop type (0=none; 1=alfalfa; 2=corn; 3=grass clover pasture; 4=soybean; 5=wheat) cropsrl - crop specific root length - mm/g root cultrhizmix - fraction of rhizosphere mixed with bulk soil during cultivation (0.0-1.0) - fraction cultlitmix - fraction of litter mixed with bulk soil during cultivation (0.0-1.0) - fraction harvremov - fraction of above ground biomass removed during harvest (0.0-1.0) - fraction fertamt - fertilization amount - g N/m2 lifehist - plant life history (0 = annual, 1 = perennial) froot_turnover_c - amount of C in fine root turnover - kg C/m2 froot_turnover_n - amount of N in fine root turnover - kg N/m2 agrd_turnover_c - amount of C in aboveground biomass turnover - kg C/m2 agrd_turnover_n - amount of N in aboveground biomass turnover - kg N/m2 leaf_litter_fastfrac - Fast decomposing fraction of leaf litter (0.0-1.0) - fraction root_litter_fastfrac - Fast decomposing fraction of root litter (0.0-1.0) - fraction root_diameter - root diameter - mm root_length - root length - mm root/m2 rhizo_frac - fraction of total soil volume that is rhizosphere (0.0 - 1.0) - fraction date - date in format YYYY-MM-DD Instructions: Save the model code ("FUN-BioCROP_LIDET Study.Rmd") and accompanything files (data streams and CORPSE function code) in the same folder. In model code "Chunk 3: Load CORPSE Data Streams" set the working directory (setwd) to the folder with the files saved in step #1. In "Chunk 5: Define LIDET parameter sets" select the litter decomposition parameter set to be used in the run, and comment out all other sets. If changing any parameter values, edit them in "Chunk 6: Load parameters." Run all chunks up to and including "Chunk 10: Prepare Data for Export." In "Chunk 11: Export Output Data" edit data frames for export and filenames, as necessary. "Chunk 12: Graph Total Soil C" makes a figure of C remaining over the model run period. Description of each model chunk (in file FUN-BioCROP_LIDET Study.Rmd): Chunk 1: Remove all functions, clear memory. Removes all functions from R environment, clears the memory. Chunk 2: Load Packages. Loads packages necessary to run the code. Chunk 3: Load CORPSE Data Streams. Sets the working directory and loads the data files necessary to run CORPSE. Chunk 4: Load CORPSE Functions. Loads the R script with CORPSE functions from the working directory, "CORPSE Functions_Bioenergy_V2.R". Chunk 5: Define LIDET parameter sets. Has ten different parameter sets for litter decomposition tested in this study: Baseline parameters, LIDET parameters, and the other 8 best performing parameter sets identified in the modified Monte Carlo. To run the model, all but one parameter set must be commented out. Chunk 6: Load Parameters. Loads all fixed parameters to run the model. Data frame with definitions of parameters is in the CORPSE function script "CORPSE Functions_Bioenergy_V2.R" Chunk 7: Prepare Data Streams. Takes data streams loaded in Chunk 3 and puts them in the format necessary to run the model. The model is coded to run at least two sites at a time, so if only one site is being run it must be run in duplicate. Individual data tables of daily values are created in this chunk from the input data file. Chunk 8: Set Initial Conditions. Creates data tables of soil C and N pools for each soil compartment (rhizo_till, rhizo, bulk_till, bulk, litter) and loads initial values into the data tables. Creates lists for each soil compartment to hold model output. Chunk 9: Load FUN Data and Set Up Matrices. Uses DayCent data to calculate FUN input data: root and leaf N demand, total N demand, plant CN, leaf N available for retranslocation, and litter production. Creates matrices for FUN model outputs. Chunk 10: Run Model. Runs the model. Chunk 11: Prepare Data for Export. Combines data from each day saved as lists into data frames for each soil compartment. Adds values from all soil compartments together to calculate total soil values, creates separate data frames for each soil C and N pool (e.g., protected slow C) for the total soil value. Adds different C and N pools together to calculate total soil C and N for all layers. Creates data frame of ratio of protected to unprotected SOC. Organizes FUN data for export. Chunk 12: Export Results. Exports CSV files of model results to the working directory. Chunk 13: Graph Total Soil C. Makes figure of C remaining over time. Related Links: Original FUN-BioCROP model: https://github.com/BrzostekEcologyLab/FUN-BioCROP LIDET dataset: https://andlter.forestry.oregonstate.edu/data/abstract.aspx?dbcode=TD023

Juice, Stephanie↗
NASA NTRS2001

Culturability as an indicator of succession in microbial communities

Successional theory predicts that opportunistic species with high investment of energy in reproduction and wide niche width will be replaced by equilibrium species with relatively higher investment of energy in maintenance and narrower niche width as communities develop. Since the ability to rapidly grow into a detectable colony on nonselective agar medium could be considered as characteristic of opportunistic types of bacteria, the percentage of culturable cells may be an indicator of successional state in microbial communities. The ratios of culturable cells (colony forming units on R2A agar) to total cells (acridine orange direct microscopic counts) and culturable cells to active cells (reduction of 5-cyano-2,3-ditolyl tetrazolium chloride) were measured over time in two types of laboratory microcosms (the rhizosphere of hydroponically grown wheat and aerobic, continuously stirred tank reactors containing plant biomass) to determine the effectiveness of culturabilty as an index of successional state. The culturable cell:total cell ratio in the rhizosphere decreased from approximately 0.25 to less than 0.05 during the first 30-50 days of plant growth, and from 0.65 to 0.14 during the first 7 days of operation of the bioreactor. The culturable cell:active cell ratio followed similar trends, but the values were consistently greater than the culturable cell:total cell ratio, and even exceeded I in early samples. Follow-up studies used a cultivation-independent method, terminal restriction fragment length polymorphisms (TRFLP) from whole community DNA, to assess community structure. The number of TRFLP peaks increased with time, while the number of culturable types did not, indicating that the general decrease in culturability is associated with a shift in community structure. The ratio of respired to assimilated C-14-labeled amino acids increased with the age of rhizosphere communities, supporting the hypothesis that a shift in resource allocation from growth to maintenance occurs with time. Results from this work indicate that the percentage of culturable cells may be a useful method for assessing the successional state of microbial communities.

NASA Center KSC↗
NASA NTRS2000

Pythium invasion of plant-based life support systems: biological control and sources

Invasion of plant-based life support systems by plant pathogens could cause plant disease and disruption of life support capability. Root rot caused by the fungus, Pythium, was observed during tests of prototype plant growth systems containing wheat at the Kennedy Space Center (KSC). We conducted experiments to determine if the presence of complex microbial communities in the plant root zone (rhizosphere) resisted invasion by the Pythium species isolated from the wheat root. Rhizosphere inocula of different complexity (as assayed by community-level physiological profile: CLPP) were developed using a dilution/extinction approach, followed by growth in hydroponic rhizosphere. Pythium growth on wheat roots and concomitant decreases in plant growth were inversely related to the complexity of the inocula during 20-day experiments in static hydroponic systems. Pythium was found on the seeds of several different wheat cultivars used in controlled environmental studies, but it is unclear if the seed-borne fungal strain(s) were identical to the pathogenic strain recovered from the KSC studies. Attempts to control pathogens and their effects in hydroponic life support systems should include early inoculation with complex microbial communities, which is consistent with ecological theory.

NASA Discipline Life Support Systems↗
DOE OSTI2021

Optimally-controlled hybrid phytoremediation system

A method for treating chemicals below ground is provided. The system includes contacting the chemicals with a rhizosphere to maximize transpiration rate and minimize over-saturation of the rhizosphere. Also provided is a method for using contaminated groundwater as a sole source of irrigation. The method uses extracting the contaminated water and pumping the extracted water to an irrigation zone under the control of an autonomous irrigation system. Each zone includes some trees and the root system for each tree is modified to function as a treatment cell. The invention also provides a system for treating contaminated water, using a contaminated water source situated below ground surface. The system uses a pump for extracting contaminated water from the water source and prevents the contaminated water from directly contacting the atmosphere above the ground surface. Vegetation which defines an underground rhizosphere is adapted to directly receive the water.

Yan, Y. Eugene↗