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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Progress toward Accelogic compression in ROOT

For the last 7 years, Accelogic pioneered and perfected a radically new theory of numerical computing codenamed “Compressive Computing”, which has an extremely profound impact on real-world computer science [1]. At the core of this new theory is the discovery of one of its fundamental theorems which states that, under very general conditions, the vast majority (typically between 70% and 80%) of the bits used in modern large-scale numerical computations are absolutely irrelevant for the accuracy of the end result. This theory of Compressive Computing provides mechanisms able to identify (with high intelligence and surgical accuracy) the number of bits (i.e., the precision) that can be used to represent numbers without affecting the substance of the end results, as they are computed and vary in real time. The bottom-line outcome will be to provide state-of-the-art compression algorithms --and accompanying software libraries-- able to surpass the performance of the compression engines currently available in the ROOT [7] framework. The resulting technology has the capability to enable substantial economic and operational gains (including speedup) for High Energy and Nuclear Physics data storage/analysis. In our initial studies, a factor of nearly x4 (3.9) compression was achieved with RHIC/STAR data where ROOT compression managed only x1.4 [6].As a collaboration of experimental scientists, private industry, and the ROOT Team, our aim is to capitalize on the substantial success delivered by the initial effort and produce a robust technology properly packaged as an open-source tool that could be used by virtually every experiment around the world as means for improving data management and accessibility.In this contribution, we will present our efforts integrating our concepts of “functionally lossless compression” within the ROOT framework implementation, with the purpose of producing a basic solution readily integrated into HENP applications. We will also present our progress applying this compression through realistic examples of analysis from both the STAR and CMS experiments.

Canal, Ph.↗
DOE OSTI2021

Deeply Rooted: Evaluating Plant Rooting Depth as a Means for Enhanced Soil Carbon Sequestration (Abbreviated Final Report)

Soils store three times as much carbon (C) as the atmosphere, but are not at capacity, and enhanced soil C storage is considered an essential strategy to mitigate rising atmospheric CO 2 levels. Agricultural soils have experienced substantial C loss in the past century due to poor agricultural practices and erosion. A shift towards deep-rooting crops and low-impact soil management could potentially increase long-term sequestration of C fixed by plants and stored in their root tissues, particularly for crops that have naturally deep root systems (>1 meter). A substantial amount of the CO 2 taken up by plants is allocated to their root systems, and because C deposited in deep soil layers has a longer residence time (up to millennia, in contrast to C deposited in topsoils), C increases at depth may have better long-term C sequestration potential than topsoils. However, the accrual, turnover, and stabilization of C in subsoils is a critical knowledge gap.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

HL-LHC Analysis With ROOT: ROOT Project Input to the HL-LHC Computing Review (Stage 2)

ROOT is high energy physics' software for storing and mining data in a statistically sound way, to publish results with scientific graphics. It is evolving since 25 years, now providing the storage format for more than one exabyte of data; virtually all high energy physics experiments use ROOT. With another significant increase in the amount of data to be handled scheduled to arrive in 2027, ROOT is preparing for a massive upgrade of its core ingredients. As part of a review of crucial software for high energy physics, the ROOT team has documented its R&D plans for the coming years.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Assessing root–soil interactions in wetland plants: root exudation and radial oxygen loss

Abstract. Plant rhizosphere processes, such as root exudation and root oxygen loss (ROL), could have significant impacts on the dynamics and magnitude of wetland methane fluxes and other biogeochemical processes but are rarely measured directly. Here, we measure root exudation and ROL from Schoenoplectus americanus and Spartina patens, two plants that have had opposite relationships between biomass and methane flux in field experiments (positive in S. patens, negative in S. americanus). We found contrasting rates of ROL in the two species, with S. americanus releasing orders of magnitude more oxygen (O2) to the soil than S. patens. At the same time, S. patens exuded high amounts of carbon to the soil, and much of the rhizosphere carbon pool was reduced compared to exudates from other wetland species. This work suggests that the relative inputs of O2 and carbon to the rhizosphere vary significantly between wetland plant species, potentially with major consequences on biogeochemical cycling, and highlights the importance of understanding how plant rhizosphere processes mediate soil biogeochemistry at a community level. As global change drivers continue to affect wetlands, future research should consider how feedbacks from plant rhizosphere processes may exacerbate or mitigate coastal wetland methane emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Heterospecific Neighbor Plants Impact Root Microbiome Diversity and Molecular Function of Root Fungi

Within the forest community, competition and facilitation between adjacent-growing conspecific and heterospecific plants are mediated by interactions involving common mycorrhizal networks. The ability of plants to alter their neighbor’s microbiome is well documented, but the molecular biology of plant-fungal interactions during competition and facilitation has not been previously examined. We used a common soil-plant bioassay experiment to study molecular plant-microbial interactions among rhizosphere communities associated with Pinus taeda (native host) and Populus trichocarpa (non-native host). Gene expression of interacting fungal and bacterial rhizosphere communities was compared among three plant-pairs: Populus growing with Populus , Populus with Pinus , and Pinus with Pinus . Our results demonstrate that heterospecific plant partners affect the assembly of root microbiomes, including the changes in the structure of host specific community. Comparative metatranscriptomics reveals that several species of ectomycorrhizal fungi (EMF) and saprotrophic fungi exhibit different patterns of functional and regulatory gene expression with these two plant hosts. Heterospecific plants affect the transcriptional expression pattern of EMF host-specialists (e.g., Pinus -associated Suillus spp.) on both plant species, mainly including the genes involved in the transportation of amino acids, carbohydrates, and inorganic ions. Alteration of root microbiome by neighboring plants may help regulate basic plant physiological processes via modulation of molecular functions in the root microbiome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Rooting for survival: how plants tackle a challenging environment through a diversity of root forms and functions

Abstract The current climate crisis has global impacts and will affect the physiology of plants across every continent. Ensuring resilience of our agricultural and natural ecosystems to the environmental stresses imposed by climate change will require molecular insight into the adaptations employed by a diverse array of plants. However, most current studies continue to focus on a limited set of model species or crops. Root systems are particularly understudied even though their functions in water and nutrient uptake are likely pivotal for plant stress resilience and sustainable agriculture. In this review, we highlight anatomical adaptations in roots that enable plant survival in different ecological niches. We then present the current state of knowledge for the molecular underpinnings of these adaptations. Finally, we identify areas where future research using a biodiversity approach can fill knowledge gaps necessary for the development of climate-resilient crops of the future.

Plant Sciences↗
DOE OSTI2020

Mycorrhizal effector PaMiSSP10b alters polyamine biosynthesis in Eucalyptus root cells and promotes root colonization

Summary Pathogenic microbes are known to manipulate the defences of their hosts through the production of secreted effector proteins. More recently, mutualistic mycorrhizal fungi have also been described as using these secreted effectors to promote host colonization. Here we characterize a mycorrhiza‐induced small secreted effector protein of 10 kDa produced by the ectomycorrhizal fungus Pisolithus albus , PaMiSSP10b. We demonstrate that PaMiSSP10b is secreted from fungal hyphae, enters the cells of its host, Eucalyptus grandis, and interacts with an S‐adenosyl methionine decarboxylase (AdoMetDC) in the polyamine pathway. Plant polyamines are regulatory molecules integral to the plant immune system during microbial challenge. Using biochemical and transgenic approaches we show that expression of PaMiSSP10b influences levels of polyamines in the plant roots as it enhances the enzymatic activity of AdoMetDC and increases the biosynthesis of higher polyamines. This ultimately favours the colonization success of P. albus . These results identify a new mechanism by which mutualistic microbes are able to manipulate the host´s enzymatic pathways to favour colonization.

Plett, Jonathan M.↗
DOE OSTI2020

Metabolomic Profiling of Wild-type and Mutant Soybean Root Nodules Using Laser-ablation Electrospray Ionization Mass Spectrometry Reveals Altered Metabolism

The establishment of the nitrogen-fixing symbiosis between soybean and Bradyrhizobium japonicum is complex. In order to document the changes in plant metabolism due to the symbiosis, we utilized laser ablation electrospray ionization mass spectrometry (LAESI-MS) for in situ metabolic profiling of wild-type nodules, nodules infected with a B. japonicum nifH mutant unable to fix nitrogen, nodules doubly infected by both strains, and nodules formed on plants mutated in the stearoyl-acyl carrier protein desaturase (sacpd-c) gene, which were previously shown to have altered nodule ultrastructure. Results showed that the relative abundance of fatty acids, purines, and lipids was significantly changed in response to the symbiosis. The nifH mutant nodules had elevated levels of jasmonic acid (JA), correlating with signs of nitrogen deprivation. Nodules resulting from the mixed inoculant displayed similar, overlapping metabolic distributions within the sectors of effective (fix+) and ineffective (nifH mutant, fix-) endosymbionts. These data are inconsistent with the notion that plant sanctioning is cell autonomous. Nodules lacking sacpd-c displayed an elevation of soyasaponins and organic acids in the central necrotic regions. This study demonstrates the utility of LAESI-MS for high-throughput screening of plant phenotypes. Overall, nodules disrupted in the symbiosis were elevated in metabolites related to plant defense.

Agtuca, Beverly J.↗
DOE OSTI2024

Catabolic pathway acquisition by rhizosphere bacteria readily enables growth with a root exudate component but does not affect root colonization

Horizontal gene transfer (HGT) is a fundamental evolutionary process that plays a key role in bacterial evolution. The likelihood of a successful transfer event is expected to depend on the precise balance of costs and benefits resulting from pathway acquisition. Most experimental analyses of HGT have focused on phenotypes that have large fitness benefits under appropriate selective conditions, such as antibiotic resistance. However, many examples of HGT involve phenotypes that are predicted to provide smaller benefits, such as the ability to catabolize additional carbon sources. We have experimentally simulated the consequences of one such HGT event in the laboratory, studying the effects of transferring a pathway for catabolism of the plant-derived aromatic compound salicyl alcohol between rhizosphere isolates from the Pseudomonas genus. We find that pathway acquisition enables rapid catabolism of salicyl alcohol with only minor disruptions to the existing metabolic and regulatory networks of the new host. However, this new catabolic potential does not confer a measurable fitness advantage during competitive growth in the rhizosphere. We conclude that the phenotype of salicyl alcohol catabolism is readily transferable but is selectively neutral under environmentally relevant conditions. We propose that this condition is common and that HGT of many pathways will be self-limiting because the selective benefits are small.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Soil properties and root characteristics across four lowland Panamanian forests from 0 - 1 m soil depths

Objectives:Fine roots significantly influence ecosystem-scale cycling of nutrients, carbon (C), and water, yet there is limited understanding of how fine root traits vary across and within tropical forests, some of Earth's most C-rich ecosystems. The biomass of fine roots can impact soil carbon storage, as root mortality is a primary source of new carbon to soils. A positive relationship has been observed between fine root biomass and soil carbon stocks in Panama (Cusack et al 2018). Beyond biomass, root characteristics like specific root length (SRL) could also influence soil carbon, as roots with higher SRL are less dense and thinner, potentially decomposing more easily or promoting soil aggregation. Understanding the effects of root morphology and tissue quality on soil carbon storage and with soil properties in general can improve predictions of landscape-scale carbon patterns. We aggregated new data of root biomass, morphology and nutrient content at 0-10 cm, 10-20 cm, 20-50 cm and 50-100 cm depth increments across four distinct lowland Panamanian forests and paired with already published datasets (Cusack et al 2018; Cusack and Turner 2020) of soil chemistry from the same sites and soil depths to explore relationship between soil carbon stocks and root characteristics.Datasets included:The datasets provided include .csv and .xlsx files for fine root characteristics and soil chemistry from four different forests across 0-10 cm, 10-20 cm, 20-50 cm, and 50-100 cm depth increments. Root characteristics include live fine root biomass, dead fine root biomass, coarse root biomass, specific root length, root diameter, root tissue density, specific root area, root %N, root %C, and root C/N ratio. Soil chemistry data includes total carbon (TC), dissolved organic carbon (DOC), bulk density, total phosphorus (TP), available phosphorus (AEM Pi), and various Mehlich-extractable elements such as aluminum, calcium, iron, potassium, manganese, phosphorus, and zinc. Nitrogen content measures include ammonium, nitrate, total dissolved nitrogen (TDN), dissolved inorganic nitrogen (DIN), and dissolved organic nitrogen (DON). The dataset also includes total exchangeable bases (TEB) and effective cation exchange capacity (ECEC) in both centimoles of charge per kilogram and micromoles of charge per gram. The soil chemistry data was obtained from Cusack et al (2018) and Cusack and Turner (2020) and paired with root characteristics data for the same depth increments and sites. Additionally, a .kml file is provided with coordinates for all 32 plots included in the study across four forests (n = 8 plots per site). Root data was averaged across these 8 plots per site and soil data was collected in one pit in each site. This dataset serves as baseline data before a throughfall exclusion experiment, Panama Rainforest Changes with Experimental Drying (PARCHED), was implemented. No special software is needed to open these files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

DEEPER: An Intergrated Platform for Deeper Roots

Crops with deeper roots would have multiple benefits, including better drought tolerance, reduced requirement for nitrogen fertilizer, and better sequestration of atmospheric CO 2 . DEEPER is an integrated platform of phenomic, genomic, and in silico technologies to generate maize lines with deeper roots. DEEPER is: LEADER (Leaf Elemental Accumulation from Deep Roots) is a breakthrough technology to nondestructively measure rooting depth by using the plant itself as a sensor. LEADER uses handheld X-ray Fluorescence spectrometry to quantify foliar accumulation of elements that are differentially distributed in the soil profile. LEADER is nondestructive and is orders of magnitude cheaper, faster, and more precise than any competing assay of rooting depth in the field. LEADER is able to distinguish deep-rooted from shallow-rooted maize lines in the field without the need for costly and noisy soil coring. RootRobot/DIRT3D, to automatically phenotype root architecture in any field, combining RootRobot, a mechatronics platform to excavate, clean, section, and image mature root crowns, with DIRT3D, software to quantify architectural traits in 3D. Anatomics, a high-throughput platform to phenotype root anatomy, combining LAT 2.0, a technology for 3D imaging of root anatomy and composition, with RootScan3D, software to automatically extract 3D anatomical and cell wall composition metrics from LAT 2.0 output. Using this platform we discovered two novel root traits, parenchyma cell wall thickness and multiseriate cortical sclerenchyma, that improve rooting depth and drought tolerance in maize and wheat. OpenSimRoot/Deep, software to simulate root interaction with hard subsoils. Using this platform we discovered novel concepts regarding how to increase crop rooting depth by modulating how individual root axes respond to hard soil. DeepGenes, a toolkit of genes, parent lines, and genomic selection strategies to enable breeding hybrids with deeper roots. We discovered 3 novel root genes that increase rooting depth in maize and wheat. DEEPER discovered novel root phenotypes for deeper rooting, and delivered validated ideotypes for deeper-rooted maize; novel technologies to rapidly assess root depth, root architecture and anatomy in field-grown plants; novel software tools for root modeling and 3D image analysis of root architecture and anatomy; and validated genes and genomic selection models to deploy traits for deeper rooting in maize breeding. Each DEEPER technology is transformative in its own right, and exceeds existing technologies. They are mutually synergistic, deployable for field-grown plants, and are ready for application. The phenotyping and modeling technologies are readily applicable to many crops, and genetic leads in maize may have utility in other grasses. Taken as a whole they represent a transformative platform to develop deeper-rooted crops, with greater drought tolerance, reduced fertilizer requirement, and greater carbon sequestration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Root genetics in the field to understand drought adaptation and carbon sequestration (Final Scientific/Technical Report)

For all crop plants, roots play a critical role in growth. Roots anchor the plants, and are the primary site of nutrient and water uptake. Roots are also the main source of C to soil in the form of root tissues and exudates, and thus greatly influence SOM stocks. To perform these functions, primary roots extend into soil, producing a network of branching roots of characteristic form, known as its root system architecture (RSA). RSA varies among species, and among varieties within a species that are adapted to different environments. Root traits are major targets for the second green revolution because of their potential to improve crop productivity, increase drought tolerance and nutrient acquisition, and increase C capture of soil. Improving the quality of roots in maize will be particularly valuable, since this crop is planted on over 92 million acres annually in the US. The future sustainability of agricultural systems relies on their ability to enhance soil organic matter (SOM) storage and reduce GHG emissions, while maintaining or enhancing productivity. This program had two components, Sensors and Models. For the first component, we designed and built a high-throughput phenotyping platform for root pulling of maize plants. This eliminated the physical labor of manually pulling up plants and reduced the number of personnel required down to one. The standardized pulling mechanism allowed recording force curves during the pulling process, providing additional information. We validated that the maximum force for pulling the root system was well-correlated with the root system mass and provided root crowns for further RSA analysis. These root crowns identified significant correlations with 2D root area and root depth, along with 3D root volume, total root length and number of root tips. We then used this system for field-based studies in maize on the genetics of root system architecture and its relation to nitrogen-use efficiency (NUE), including using lines relevant to the Corteva breeding program. Varieties were also evaluated at Corteva sites in the cornbelt and Danforth farm in Missouri, to establish responses across sites. From these studies we have identified genetic loci associated with root traits and created mutant lines for these loci and correlations of root traits with NUE. For the Models component, we worked to incorporate root and soil characteristics into the MEMS 2.0 soil and ecosystem biogeochemical model. Existing soil C models, such as Century, are unable to represent specific root trait interactions with the soil environment and therefore to accurately forecast the potential C sequestration benefits of root breeding under different climatic and soil type conditions. We have developed the MEMS 2.0 ecosystem biogeochemical model to improve quantification of farm-scale soil carbon and greenhouse gas emissions. The new knowledge and large datasets produced by this project will be used to develop and drive an innovative model capable of forecasting the impacts on soil C stocks and nutrient dynamics. An innovation was to use the empirical data from the field studies (in 1, above) to model genetic variation in nitrogen use efficiencies and soil C input. Our work demonstrated that maize root-derived C rapidly replaces existing soil C and after 3 years of continuous maize, up to 20% of soil organic C in the topsoil (0-15cm) and 3% in the subsoil (15-30cm) was contributed by maize. However, this contribution did not entirely represent a net increase. Root C contribution to soil was affected by maize genetics. We have analyzed soils derived from the CSU field trials for C and N stocks, in the different soil physical fractions represented by the MEMS model, using both physical fractionation with elemental analyses, and Fourier transformed infrared spectroscopy. Data will be used to link crop nitrogen use efficiencies with soil C sequestration and provide data to bridge the field trials with the model development, for verification of model predictions. The project had a number of successful outcomes: we have used the new phenotyping platform to identify new genetic loci that can enhance root phenotypes; we have partnered with multiple maize seed companies phenotype varieties in their breeding programs; we have developed the MEMS model that can help inform industry on the potential for carbon sequestration in the agricultural sector, and which is now available at the CSU Soil Carbon Solutions Center for use.

59 BASIC BIOLOGICAL SCIENCES↗