30 Projects Awarded Funding from EMSL
Researchers will develop tools to mitigate climate change and engineer bioproducts
Scientists from across the globe are working on 30 projects to develop tools and processes to improve plant, crops, and bioproducts, as well as mitigate climate change.
This international effort to tackle the world’s greatest scientific hurdles is funded through the Environmental Molecular Sciences Laboratory (EMSL) Fiscal Year 2023 Call for Large-Scale Research Proposals. EMSL is a Department of Energy, Office of Science user facility sponsored by the Biological and Environmental Research (BER) program. Scientists with Large-Scale Research project funding have up to two years of access to EMSL’s world-class expertise and instrumentation.
The awarded projects support research in EMSL’s three science areas—environmental, biological, and computational sciences. Featured among the projects are investigations into global carbon cycling, plastic pollution, greenhouse gas emissions, and aerosols.
“We are thrilled to welcome new and returning users from universities and national laboratories to collaborate with EMSL on cutting-edge science,” said Nikki Powell, deputy of EMSL User Services. “This proposal funding provides researchers with the opportunity to delve into unprecedented areas of science using some of our most highly specialized instrumentation alongside EMSL research staff.”
EMSL offers 150 instruments and resources to researchers who submit a successful research proposal, some of which include the Tahoma supercomputer, high-resolution micro-X-ray computed tomography to characterize plant roots, and the cell-free expression pipeline to synthesize proteins.
The awarded projects include:
Melissa Duhaime
University of Michigan
Determining mechanisms and rates of microbial plastic
biodegradation and the consequences for freshwater
carbon cycling
Knowledge gaps regarding microbe–plastic interactions have limited innovation in plastics recycling and engineering of systems for plastic pollution bioremediation. Through this project, researchers will use EMSL’s multi-omics, metabolic modeling, and advanced microscopy capabilities to determine the mechanisms and rates of polyethylene and biodegradable polymer degradation in natural aquatic communities.
Erik Wright
University of Pittsburgh
Illuminating emergent properties underlying complex carbon degradation within communities of soil microorganisms
Soil microorganisms play a key role in global carbon cycling by degrading complex carbon molecules. Carbon degradation requires the contributions of multiple different soil microorganisms. This research aims to identify the set of small molecules that govern community assembly and the collective degradation of complex carbon molecules.
Song Feng
Pacific Northwest National Laboratory
Determination of the molecular architecture and temporal dynamics that drive microbial lignocellulose degradation
This project aims to generate information that aids in the development of rationally engineered communities expressing phenotypes.
Researchers will apply multi-omics analyses using a biology-informed, data-driven model and kinetic assays specific to lignocellulolytic activity levels to isolate and analyze microbes that degrade lignocellulose.
Lyle Whyte
McGill University
Cellular controls on carbon source–sink dynamics in deglaciated soils
Researchers seek to identify the microbial taxa and carbon pools that drive the carbon cycle in deglaciated soils of different ages. The expected outcome is to determine how predicted changes in the Arctic climate will shape future carbon source–sink dynamics by affecting underlying cellular processes.
Steven Hallam
University of British Columbia
Mass-spectral 'fingerprinting' of technical and native lignin substrates for improved biological funneling and enzyme discovery
Lignin derived from plant biomass is a potentially valuable resource for renewable energy and materials production. To address the challenges of lignin deconstruction, researchers will combine the biological and chemical signatures of transformed lignin to design, build, and test standardized workflows to compare biological treatments across lignin types. This will guide assembly of more efficient biotechnology platforms for energy and materials production.
Amy Marshall-Colon
University of Illinois at Urbana-Champaign
Uncovering dynamic changes in metabolism and signaling across cell types in the Sorghum bicolor stem using multi-omics
Sorghum is a bioenergy crop that produces a large quantity of biomass that can be processed into ethanol for biofuels. This project will use EMSL’s capabilities in multi-omics to build gene regulatory networks that direct experimental efforts to improve stem traits.
Francisco Javier Cejudo
Universidad de Sevilla
The thiol redox proteome dynamics in Arabidopsis thaliana in response to light
Plant performance relies on regulatory mechanisms that allow the rapid adaptation of their metabolism to light, which is the key stimulus for growth and development of photosynthetic organisms. This research will develop new tools to improve crop acclimation, given that climatic change is expected to affect Earth’s vegetation.
Kendall Corbin
University of Kentucky
Unraveling the biochemical and metabolic networks controlling bacterial cellulose biosynthesis
The project aims to unravel the complex relationship between gene function, metabolic pathways, and phenotype through
the integration of structural, biochemical, and ‘omics datasets. The comprehensive molecular-level information generated from this project will have broad application for the metabolic engineering of cellulose-producing bacteria.
James Umen
Donald Danforth Plant Science Center
Structural and functional dissection of a cell cycle
chromatin switch in green algae
Chlamydomonas reinhardtii will be used to develop a structural model for cell cycle control by a conserved chromatin-associated regulator, the retinoblastoma tumor suppressor complex. This data will provide a foundational resource on how cell growth is linked to cell cycle progression during the Chlamydomonas life cycle.
Michael Knoblauch
Washington State University
Deciphering the structure and function of the last unknown major plant organelle – Plasmodesma
EMSL’s sample preparation technology and cryo-electron tomography will be used to reveal in-situ structure of plasmodesmata, which is a nanoscale pore that is essential to plant performance. The combination of structural and functional data will be used to fundamentally refine current models.
Suping Zhou
Tennessee State University
Developing the proteome network regulating structure and function of root development of switchgrass on marginal lands
Researchers will select drought- and AI-treated biomass switchgrass to profile proteomes in each distinct type of cell found in root tips. Results are expected to advance understanding of the biological processes that regulate and coordinate cell division, cell differentiation, and cell growth in the root tip.
Setsuko Wakao
Lawrence Berkeley National Laboratory
The knowns against the unknowns: Photosynthesis gene discovery through multi-omic survey of photosynthetic
mutants
This research tackles a high-risk challenge of identifying novel gene functions related to photosynthesis using a large-scale mutant library. Researchers aim
to gain insight into the functions of unknown-function genes through mining multi-omic patterns across mutants and wildtypes during perturbation with photosynthetic stress.
Paul DeMott
Colorado State University
Single-particle characterization for interpreting ice-nucleating particle measurements in the SAIL field study
This project will use single-particle characterizations of aerosol samples to associate aerosol composition with simultaneous measurements of ice-nucleating particles (INPs). A synthesized description of INPs and their relationships to aerosol regimes will result, which are
useful for modeling studies of aerosol–cloud–precipitation interactions in weather and climate models.
Claudio Mazzoleni
Michigan Technological University
Transformations of organic coatings in light-absorbing aerosols released by biomass burning and associated impacts on the interactions with clouds
This project will use EMSL’s analytical capabilities to study the interactions of black-carbon-containing particles with clouds, including how these interactions drive direct and indirect radiative forcing, modify cloud microphysical properties, and govern the wet removal and transformations of black-carbon-containing particles.
Susannah Burrows
Pacific Northwest National Laboratory
Disentangling the impacts of particle mixing state on ice nucleation
This project will exploit a unique combination of EMSL capabilities to quantify droplet freezing under different conditions and to characterize the bulk and surface chemistry of individual particles and atmospheric ice-nucleating
particles to test theoretical model predictions of the impacts of particle mixing state on ice nucleation.
Alexander Laskin
Purdue University
Probing atmospheric nanoplastics: An unrecognized urban source of airborne particles
Environmental nanoplastic (EnvNP) particles are inadequately characterized pollutants with significant adverse effects on aquatic and atmospheric systems. A range of particle analysis and chemical imaging techniques hosted by EMSL will be used for extensive analysis of EnvNP particles collected in field and focused laboratory studies.
Debjani Sihi
Emory University
Coupling X-ray computed tomography images with ModEx inspired laboratory manipulation experiment for predicting greenhouse gas fluxes from terrestrial–aquatic interfaces
This project will generate fine-scale data to validate a computational tool to advance modeling from fine-scale processes to ecosystem-scale functions to improve understanding of multiscale Earth system dynamics and processes. EMSL capabilities will be used to evaluate how redox heterogeneity across soil microsites influences greenhouse gas emissions from terrestrial–aquatic interfaces.
Jean-Thomas Cornelis
University of British Columbia
Elucidating the effects of root responses to moderate soil nutrient limitation on mineral bioweathering processes
This project aims to advance understanding of soil controls on root exudation and their influence on bioweathering and the formation of organo-mineral associations. The research will catalyze the fundamental understanding of soil–plant feedback processes to propose new land management strategies that optimize soil nutrient acquisition and carbon storage.
Amisha Poret-Peterson
U.S. Department of Agriculture - Agricultural Research Service
Molecular controls of microbial nitrogen use efficiency in agricultural soils
Using stable isotope probing and tracing experiments, this project tests the hypothesis that biomass-amended soils will have higher microbial nitrogen use efficiency than unamended soils. This work provides mechanistic understanding of microbial processes involved in nutrient cycling and carbon sequestration in agricultural soil systems.
Daniel Knopf
State University of New York at Stony Brook
Towards aerosol-ice formation closure: Chemical imaging investigation of aerosol and ice-nucleating particles
This project applies chemical imaging to identify the physicochemical properties associated with soil-dust particles that make up ice-nucleating particles. This research will result in improved ice-nucleating particle parameterizations and contribute to the predictive understanding of cloud formation and the hydrological cycle.
Buck Hanson
Los Alamos National Laboratory
Revealing oxalate-mediated carbon flow through plant–fungal–bacterial rhizosphere interactions as part of a globally important carbon-sequestering biogeochemical process
This research will investigate the role of the plant root exudate oxalate in shaping bacterial-fungal-plant interactions in soil. Understanding how nutrients that plants secrete into soils influences microbial activities will advance strategies that aim to improve the management of plants for biofuel production, soil carbon sequestration, and soil fertility.
Kerri Pratt
University of Michigan
Identification of individual particle chemical composition, morphology, and ice nucleation properties in the Arctic
This project addresses gaps in understanding of Arctic aerosol chemical composition, mixing state, sources, and ice nucleation properties through chemical imaging and ice nucleation particle analysis. This work will provide insight into how natural and anthropogenic emissions and atmospheric processing are driving aerosol interactions with radiation, fog, and clouds.
Malak Tfaily
University of Arizona
Deciphering plant–plant, plant–microbe, and plant–soil interactions driving biological invasion in a southwestern desert grassland
Plant invasion is a major component of global change, leading to environmental transformations that alter
ecosystem services and associated biogeochemical cycles. This project aims to achieve a mechanistic understanding
of the role that belowground microbes play in conjunction with the plant metabolome to promote plant invasion.
Tim Scheibe
Pacific Northwest National Laboratory
Numerical modeling of hydrologic exchange and biogeochemistry in dynamic rivers
This project utilizes EMSL computational resources to support high-resolution numerical modeling and machine learning analyses at river corridor, watershed, and basin scales. Researchers will model groundwater–surface water interactions in the Hanford Reach of the Columbia River and watershed processes in the Yakima River Basin.
Bojana Ginovska
Pacific Northwest National Laboratory
Computational mechanistic studies of methyl-coenzyme M reductase enzyme
Methyl-coenzyme M reductase (MCR) is an enzyme in the methane biological conversion by microbial communities with sulfate- or nitrate-reducing bacteria. MCRs achieve a catalytic bias toward using/producing methane though changes in protein confinement of substrates.
Researchers will use computational approaches to explore how the protein environment contributes to the reactivity.
Pernilla Wittung-Stafshede
Chalmers University of Technology
Novel artificial intelligence approach to unravel complex protein folding landscapes: toward a better bioeconomy
Most proteins must fold to function. Today, researchers can predict structures of folded proteins but not their folding reactions. This project will uniquely combine artificial intelligence/machine learning code with experimental folding data to predict protein folding processes with atomistic detail. The AI developed from model systems will then be applied to enzymes used in bioeconomy processes.
Marcel Baer
Pacific Northwest National Laboratory
Atomistic simulations of the discriminatory power of desaturase
Desaturases catalyze regiospecific dehydrogenation of fatty acids. This project will use multiscale modeling to reveal atomistic details of how the metalloenzyme controls this process. This may help understand mechanisms governing carbon allocation and lipid synthesis that are keys to understanding and manipulating levels of lipid accumulation in plants.
Herbert Sauro
University of Washington
Inferring kinetic models for large-scale biochemical networks
This project will develop an iterative model ensemble approach for model building that incorporates existing knowledge
and is designed explicitly for hypothesis generation. Adversarial machine learning will be used to evaluate the ability of this method to recapitulate the benchmark models.
Carolyn Fitch
Johns Hopkins University
Plant proteome structure-function and pKa prediction augmented with environmental considerations, deep learning, and integrated datasets
Researchers will investigate determinants of pKa values for protein groups with low-accuracy prediction and that are often triggers of biological function. Solvation and environmental influences will be systematically addressed. These studies will contribute to developing and applying computational algorithms to the levels needed to model biological systems.
Hoshin Kim
Pacific Northwest National Laboratory
Understanding product selectivity of monoterpene synthases using atomistic simulations
This research uses computational tools to conduct atomistic simulations of enzymatic systems to understand the chemistry and mechanisms of monoterpene synthases (MTSs). MTSs catalyze biosynthesis of monoterpenes, which play a pivotal role in plant–plant communications and act as a key ingredient in industrial applications, including flavor additives, fragrances,
and biofuels.