Call for Large-Scale Research Proposals, FY 2025

The focus topics for this call are aligned with EMSL’s mission to accelerate scientific discovery and pioneer new capabilities to understand biological and environmental processes across temporal and spatial scales. The topics are organized by EMSL’s three science areas—Environmental Transformations and Interactions (ETI), Functional and Systems Biology (FSB), and Computing, Analytics, and Modeling (CAM). 

Environmental Transformations and Interactions (ETI) Science Area 

We seek projects that would use EMSL expertise and experimental capabilities to elaborate the molecular and microscale microbial, biogeochemical, and physical mechanisms governing transformations and the cycling of carbon, nutrients, and minerals in unmanaged natural terrestrial ecosystems (including watershed, coastal, and urban) and the processing of plant- and soil-derived volatile organic compounds and aerosols at the land surface up to the boundary layer. This call addresses the need to develop improved microbial, biogeochemical, and physical process representations to reduce the uncertainty in simulations of Earth and atmospheric systems up to regional and global scales. Proposals that integrate EMSL-based measurements within explicit model–experiment (ModEx) frameworks are encouraged. Proposals that address the behavior of terrestrial anthropogenic contaminants are not eligible. Learn more about the ETI Science Area on the EMSL website.

ETI-1: Soil carbon processes and upscaling (IRP: Biogeochemical Transformations, Emily Graham) 

We seek studies that elaborate microbial, geochemical, and transport processes governing carbon transformations, (de-)stabilization, and carbon uptake or release over scales ranging from a nanometer to a pedon in soils and subsoils down to the regolith. Proposed research should provide mechanistic knowledge needed to fill gaps in extant soil carbon process models. Topics of relevance include but are not limited to the nanometer- to pore-scale chemistry/microstructure of mineral-associated organic matter (OM), OM sorption/desorption, microbial processing of soil carbon, reduced complexity micromodel soil analogs, and measurements and proxies of soil carbon stability using spectroscopic or chemical probes. Research that supports the development of constitutive relations linking complex molecular and microstructural soil characteristics to macroscopic measurements or that links fundamental knowledge of soil characteristics to the improved interpretation of bulk soil measurements is encouraged. 

ETI-2: Nutrient cycling biogeochemistry (IRP: Biogeochemical Transformations, Emily Graham) 

We seek studies that investigate molecular and microscale biogeochemical processes controlling nutrient and micronutrient cycling, uptake, and release in subsurface terrestrial systems. Processes of interest include but are not limited to hotspot/hot-moment dynamics, biotic and abiotic responses to climate change and transient disturbance events (e.g., wildfire, drought, and saltwater intrusion), and watershed dynamics. Proposals that address soil carbon cycling should be submitted under ETI Topic 1; studies that focus on root-mediated processes should be submitted under ETI Topic 4. 

Overlap with CAM: Please contact us if you are interested in submitting a proposal within ETI-1 or ETI-2 that would test or develop innovative methods for the coanalysis of 2-D and 3-D chemical images using artificial intelligence (AI) or machine learning (ML) approaches to enable the mining of molecular information from images, the processing of multimodal data, coregistering spatial molecular data from different instruments, or expanding 2-D chemical information to 3-D space. (Contact: Satish Karra, Tamas Varga) 

ETI-3: Atmospheric processing of terrestrial-sourced emissions (IRP: Terrestrial–Atmospheric Processes, Swarup China) 

We seek projects that develop a mechanistic understanding of the molecular and physical processes that influence the behavior of plant- and soil-derived emissions, including volatiles and aerosols, in the atmosphere. Topics of interest include emissions and atmospheric processing of volatile organic compounds and particles from biomass burning and plants; spatiotemporal and compositional heterogeneity of biogenic and anthropogenic aerosols; airborne aerosol aging processes; experimental–molecular-modeling studies of aerosol reactivity, particle nucleation, and heterogeneous ice nucleation; physical, chemical, and optical properties of aerosols and their impacts on warm and cold cloud formation; and the deposition of aerosols that impact biogeochemical cycles and ecosystem properties. Anthropogenic aerosols that influence these processes are appropriate research subjects. Atmospheric systems above urban, agricultural, rangeland/grassland, forest, wetland, and water, including remote source points that contribute long-range transported aerosols, are appropriate for this call. 

Overlap with CAM: Investigations that couple molecular modeling with experimentation (joint ETI–CAM projects) are encouraged. Please contact Swarup China if you are interested in submitting a model–experimental proposal. 

ETI-4: Root–soil–microbe interactions (IRP: Rhizosphere Function, Amir Ahkami) 

We seek investigations that develop a mechanistic understanding of molecular and microscale root–microbe–mineral biogeochemical and transport processes that influence carbon and nutrient fluxes, support plant function, and underpin plant–microbe signaling. Topics of interest include (but are not limited to) coupled molecular and transport processes that facilitate carbon and nutrient retention, transformation, and release; root-microbiome chemical signaling; release and biogeochemical processing of metabolites and photosynthates; targeted and untargeted spatiotemporal metabolomic characterization of exudates at root–soil interfaces; and responses of rhizosphere processes and microbial communities to rhizodeposition and perturbations (e.g., drought, flooding, nutrient limitation, temperature, and elevated CO₂). Proposals that integrate 2-D and 3-D rhizosphere imaging (physical and/or chemical), multiomics, and sensing with root phenotyping are encouraged. 

Overlap with CAM: Please contact us if you are interested in submitting a proposal within ETI-4 that would test or develop innovative methods for the coanalysis of 2-D and 3-D chemical images using AI or ML approaches to enable the mining of molecular information from images, the processing of multimodal data, coregistering spatial molecular data from different instruments, or expanding 2-D chemical information to 3-D space. (Contact: Satish Karra, Tamas Varga) 

Functional and Systems Biology (FSB) Science Area 

We seek proposals utilizing EMSL capabilities for research focused on biological systems relevant to the sustainable production of biofuels, chemicals and biomaterials, environmental microbiology, and biosystems design. Learn more about the FSB Science Area on the EMSL website. Contact the FSB Science Area Leader, Scott Baker, if you have questions about these topics. 

FSB-1: Protein and protein complex structure and function (IRP: Structural Biology, Scott Lea) 

• The rapid pace of genome sequencing has uncovered a massive catalog of conserved genes encoding proteins of unknown function. The ability to predict, control, and engineer biochemical pathways relies on understanding the function of proteins in cellular processes. We seek proposals that target structure–function studies that elucidate the biochemical or biological activities essential to nutrient cycling or the production of biofuels, chemicals, or biomaterials. 
  • The 1000 Fungal Proteins project aims to utilize structural biology resources, both experimental and computational, to accelerate the annotation of proteins of unknown function that are highly conserved across the fungal kingdom. User samples can enter the pipeline at various points, including users who already have proteins or metabolites that are highly purified and available for shipment to those users who only have a gene sequence (such as those found in Mycocosm) and would utilize our computational or experimental workflows from gene to structure. 
• Proteins often function in complexes, many of which are not or poorly characterized. Comprehensive characterization of these complexes can be used to assign function(s) for new and unknown proteins. We seek proposals aimed at characterizing the composition, activities, and location of complexes that regulate biochemical pathways in plant and microbial systems. 
• Knowledge of molecular assembly and cellular component organization and behavior in time and space can provide unique clues about function and reveal opportunities for pathway engineering in plant and microbial systems. We seek proposals that focus on the characterization of the spatiotemporal relationships between proteins, protein complexes, and subcellular ultrastructure. 

Overlap with CAM: Reconstruction workflows for protein structure determination and subcellular 3-D mapping. (Contact: Satish Karra) 

FSB-2: Regulatory and biosynthetic pathways (IRP: Biomolecular Pathways, Mary Lipton) 

• Understanding the biological circuits in cells is crucial for simulation or the prediction of behavior and the design and engineering of new biological systems for enhanced performance. Projects probing the biological processes that mitigate the interconnections and interactions of proteins and metabolites in the context of environmental nutrient cycling or the production of biofuels, chemicals, or biomaterials in biological systems are desired. 
• The quantification of the functional components of the complex systems involved in metabolic and biosynthetic pathways is crucial to understanding how these pathways are regulated and controlled. Projects aimed at the quantitative characterization and integration of biomolecules central to these pathways in or the connection of these processes in plants, fungi, algae, microbes, and microbial communities including viruses are desired. 
• Our understanding of the regulation of biological circuits is growing but still has gaps. We seek proposals focused on regulatory pathways in microbes, plants, fungi, algae, and microbial communities involved environmental nutrient cycling or the production of biofuels, chemicals, or biomaterials. 

Overlap with CAM: Processing and integration of multiomics data for modeling and interpretation. (Contact: Kelly Stratton) 

FSB-3: Populations and communities (IRP: Cell Signaling and Communications, Alex Beliaev) 

• Capturing the breadth and complexity of organism (encompassing plants, bacteria, fungi, algae, and viruses) interactions and behaviors across space and time is essential to untangling the mechanisms that influence the intrinsic microbiome stability and robustness. We seek projects that develop and deploy multiomics approaches along with high-resolution dynamic imaging to investigate in situ biological activities controlling key environmental processes. 
• Understanding how individual cell outputs cascade into the cumulative behavior of natural and synthetic (isogenic and multispecies) populations is critical to our ability to predict microbiome function and dynamics. Studies aimed at developing and deploying single-cell measurements to understand how cells in these populations interact and acclimate to internal and external perturbations are desired. 
• The availability of tools and methods for manipulating microbiomes is a critical component for enabling the design of microbiomes with highly improved properties. Projects aiming at building and characterizing engineered consortia at a subspecies/subpopulation resolution for industrial or environmental applications are encouraged. 

Overlap with CAM: Computational approaches that facilitate data processing and analysis to integrate molecular measurements at the subpopulation and, when possible, single-cell levels. (Contact: Satish Karra) 

Computing, Analytics, and Modeling (CAM) Science Area 

The Computing, Analytics, and Modeling (CAM) Science Area focuses on combining advanced data analytics, visualization, computational modeling, and simulation with state-of-the-art experimental data generation to develop a predictive understanding of biological and environmental systems. Our cohesive approach to integrating experimental and computational methods advances predictive approaches for cellular metabolism towards the production of biofuels and bioproducts as well as material synthesis and degradation (e.g., biomineralization, plant biomass, and plastics). Moreover, our approach accelerates research to understand the molecular mechanisms underlying the biological and hydro-biogeochemical processes controlling the flux of materials (e.g., carbon, nutrients, and other constituents) in the environment. Please get in touch with Jaydeep Bardhan, CAM Science Area Leader, if you have questions about the following call topics or to discuss your project idea. 

CAM-1: Data-driven modeling of soil samples (IRP: Systems Modeling, Satish Karra) 

Data-driven approaches including statistical methods and the recent advances in AI/ML enable the “learning” of unknown processes in a system from data. We seek the application and testing of novel statistical/AI/ML methods that elucidate the underlying hydro-biogeochemical processes or process parameters (e.g., constitutive model parameters) from soil data. Hybrid approaches that combine statistical/AI/ML methods and mechanistic models (e.g., combining balance-law-based partial differential equations with ML) are also of interest. Data-driven models for bridging scales and that enable using information from one scale to another (e.g., molecular-to-pore or pore-to-continuum scales) are also of particular interest. 

CAM-2: Advanced data analytics and data integration methods (IRP: Data Transformations, Kelly Stratton) 

Rapid advances in data science, data integration, and AI/ML could significantly enhance BER science, especially for problems involving complex, heterogeneous data and data from various types of instrumentation. However, generating interpretable and actionable results can be challenging. We seek proposals that will leverage cutting-edge data science and statistical approaches and make use of existing BER domain-science repositories and other data resources in new ways to advance BER science priorities. Methods of particular interest include dimensionality reduction, data integration, the incorporation of pathway information from existing public data and metadata resources (including but not limited to NMDC, KEGG, STRING, etc.), topological or geometric approaches, Bayesian methods, and approaches designed for noisy, incomplete, or limited training data. 

CAM-3: Data science and statistical/AI/ML methods to advance data analysis and visualize spatially resolved molecular information in microbial communities (IRP: Data Transformations, Kelly Stratton) 

Spatially resolved molecular information (metabolic, lipidomic, proteomic, and transcriptomic) generated from microbial communities and, particularly, omics studies using hybrid mass spectrometry workflows (e.g., including chromatography, ion mobility spectrometry, or data-independent acquisition) provide valuable insights into molecular regulation, transformation, and activity. Complementary imaging studies of soil—for instance, X-ray computed tomography (XCT)—provide detailed structural information relevant to understanding environmental biogeochemical processes. Techniques to integrate these types of data frequently generated by EMSL represent an emerging research area of great potential for BER mission science. We seek proposals aimed at testing innovative methods to transform imaging-based structural information into scientific discovery through computational image analysis, data integration, and visualization, with the aim of enhancing capabilities to understand complex BER-relevant systems. 

CAM-4: Methods for modeling at the cellular and community levels (IRP: Systems Modeling, Satish Karra) 

Cutting-edge capabilities for modeling cellular behavior and microbial communities have shown substantial promise for understanding and controlling biological processes and the genotype/phenotype relationship. However, until recently, the effort and expertise required to build such models have prohibited their use more widely, and the growth in automation capabilities motivates improvements in understanding the creation, use, and refinement of cellular and community models. We therefore seek proposals leveraging existing genome-scale metabolic models or innovative methods to reduce barriers to creating such models. Proposals that would advance the use of EMSL’s experimental capabilities to create, refine, and validate cellular and community models are of particular interest. 

CAM-5: Advancing AI/ML for the modeling and simulation of biological and environmental molecules (IRP: Systems Modeling, Satish Karra) 

AI and ML are enabling simulation studies to reach unprecedented scales through predictive models for multiscale problems and to provide new insights into molecular structure/function relationships through analyses of simulation data. We therefore seek proposals that leverage AI/ML in novel ways to simulate complex systems that were not previously tractable, to accelerate the convergence of molecular simulations, to improve accuracy through multiscale modeling, or to gain new understanding of molecular behavior and regulation by post-simulation analyses. Proposals that advance the coupling of modeling and EMSL’s experimental capabilities are of particular interest. 

CAM-6: Methods for molecular identification and function annotation (IRP: Data Transformations, Kelly Stratton) 

Advances in statistics, data science, and simulation have led to powerful new tools for identifying molecules and for predicting the properties and functions of biological molecules including proteins, nucleic acids, small molecules, and lipids. However, the relevance and value of many data analytics tools for BER science remain relatively unrecognized because of the domain-expertise barriers between the developers of data analytics methods and domain scientists. We therefore seek proposals to test new identification and functional-annotation approaches to problems central to BER science priorities. We are particularly interested in advancing the application of AI/ML to make genome-scale predictions of protein regulation by post-translational modifications, protein–protein interactions, protein–nucleic-acid interactions, and protein–small-molecule interactions. We are also interested in proposals that leverage large-scale public datasets to provide new insights into EMSL data and proposals that leverage EMSL data to advance the development of new methods.