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DOE OSTI2021

Microbial production of megadalton titin yields fibers with advantageous mechanical properties

Manmade high-performance polymers are typically non-biodegradable and derived from petroleum feedstock through energy intensive processes involving toxic solvents and byproducts. While engineered microbes have been used for renewable production of many small molecules, direct microbial synthesis of high-performance polymeric materials remains a major challenge. Here we engineer microbial production of megadalton muscle titin polymers yielding high-performance fibers that not only recapture highly desirable properties of natural titin (i.e., high damping capacity and mechanical recovery) but also exhibit high strength, toughness, and damping energy — outperforming many synthetic and natural polymers. Structural analyses and molecular modeling suggest these properties derive from unique inter-chain crystallization of folded immunoglobulin-like domains that resists inter-chain slippage while permitting intra-chain unfolding. These fibers have potential applications in areas from biomedicine to textiles, and the developed approach, coupled with the structure-function insights, promises to accelerate further innovation in microbial production of high-performance materials.

36 MATERIALS SCIENCE↗

NASA NTRS2000

Hydrogen Biogeochemistry in Anaerobic and Photosynthetic Ecosystems

The simple biochemistry of molecular hydrogen is central to a large number of microbial processes, affecting the interaction of organisms with each other and with the environment. In anoxic sediments, a great majority of microbial redox processes involve hydrogen as a reactant, product or potential by-product. Accordingly, the energetics (thermodynamics) of each of these processes is affected by variations in local H2 concentrations. It has long been established that this effect is important in governing microbe-microbe interactions and there are multiple demonstrations that "interspecies hydrogen transfer" can alter the products of, inhibit/stimulate, or even reverse microbial metabolic reactions. In anoxic sediments, H2 concentrations themselves are thought to be controlled by the thermodynamics of the predominant H2-consuming microbial process. In sediments from Cape Lookout Bight, this relationship quantitatively describes the co-variation of H2 concentrations with temperature (for methanogens and sulfate reducers) and with sulfate concentration (for sulfate reducers). The quantitative aspect is import= for two reasons: 1) it permits the modeling of H2-sensitive biogeochemistry, such as anaerobic methane oxidation or pathways of organic matter remineralization, as a function of environmental controls; 2) for such a relationship to be observed requires that intracellular biochemistry and bioenergetics are being directly expressed in a component of the extracellular medium. H2 could therefore be utilized a non-invasive probe of cellular energetic function in intact microbial ecosystems. Based on the latter principle we have measured down-core profiles of H2 and other relevant physico-chemical parameters in order to calculate the metabolic energy yields (DG) that support microbial metabolism in Cape Lookout Bight sediments. Methanogens in this system apparently function with energy yields significantly smaller than the minimum requirements suggested by pure culture studies. Our recent work has extended the study of hydrogen to cyanobacterial mat communities. The large amounts of reducing power generated during photosynthetic activity carry the potential to contribute a swamping term to the H2 economy of the anaerobic microbial populations within the mat - and thereby to alter the population structure and biogeochemical function of the mat as a whole. In hypersaline microbial mats, we observe a distinct diel cycle in H2 production and a substantial corresponding flux. On an early Earth dominated by microbial mats, this transmission of photosynthetic reducing power may have carried important implications for both biospheric and atmospheric evolution.

Hoehler, Tori M.↗

NASA NTRSDate not supplied

Effects of Basalt Composition on a Martian Analogue Magma-Sediment Hydrothermal System Studied Through Thermochemical Modeling

High-temperature hydrothermal systems have been identified on Mars associated with both hypervelocity impacts and magmatic activity on Mars’s early history [1, 2]. These processes may have produced habitable environments by providing heat, energy, and volatile species necessary to support microbial life [3, 4]. Hydrothermal systems formed after the intrusion of mafic magmas in sedimentary rocks are of particular interest when investigating the habitability of high-temperature aqueous environments on Mars [5, 6],because during magma-sediment contact metamorphism bond fluids (e.g. in ice, pore spaces, minerals) are mobilized favoring the alteration of the country rocks and the release of bio-essential elements [7, 8]. The chemistry and mineralogy of these systems on Mars are not well constrained and, for this reason, terrestrial analogues need to be investigated. Costello et al. [5] and Crandall et al. [6] have studied a mafic dike intruding the Jurassic Entrada sandstone (Colorado Plateau, UT). The intrusion has produced a hydrothermal system with Cl-CO2 rich fluids and near-neutral pH, which induced chemical and mineralogical changes in the dike and in the sediments [5, 6]. The system reached temperatures higher than 700 °C around the contact zone [6], but lower temperatures (< 200 °C) were reached as the system cooled down [5] making the environment potentially habitable [6]. However, previous studies do not consider compositional differences between the terrestrial dike and basaltic rocks on Mars [9, 10] making difficult a direct comparison between alteration mineralogy and brine chemistry of terrestrial and martian systems. Here, we use thermochemical modelling to investigate how differences in bulk dike composition will affect secondary mineral assemblages and fluid chemistry.

S Cogliati↗

DOE OSTI2021

An evolutionary algorithm for designing microbial communities via environmental modification

Despite a growing understanding of how environmental composition affects microbial communities, it remains difficult to apply this knowledge to the rational design of synthetic multispecies consortia. This is because natural microbial communities can harbour thousands of different organisms and environmental substrates, making up a vast combinatorial space that precludes exhaustive experimental testing and computational prediction. Here, we present a method based on the combination of machine learning and metabolic modelling that selects optimal environmental compositions to produce target community phenotypes. In this framework, dynamic flux balance analysis is used to model the growth of a community in candidate environments. A genetic algorithm is then used to evaluate the behaviour of the community relative to a target phenotype, and subsequently adjust the environment to allow the organisms to approach this target. We apply this iterative process to thousands of in silico communities of varying sizes, showing how it can rapidly identify environments that yield desired taxonomic compositions and patterns of metabolic exchange. Moreover, this combination of approaches produces testable predictions for the assembly of experimental microbial communities with specific properties and can facilitate rational environmental design processes for complex microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Functional Traits Resolve Mechanisms Governing the Assembly and Distribution of Nitrogen-Cycling Microbial Communities in the Global Ocean

Microorganisms drive much of the marine nitrogen (N) cycle, which jointly controls the primary production in the global ocean. However, our understanding of the microbial communities driving the global ocean N cycle remains fragmented. Focusing on “who is doing what, where, and how?”, this study draws a clear picture describing the global biogeography of marine N-cycling microbial communities by utilizing the Tara Oceans shotgun metagenomes. The marine N-cycling communities are highly variable taxonomically but relatively even at the functional trait level, showing clear functional redundancy properties. The functional traits and taxonomic groups are shaped by the same set of geo-environmental factors, among which, depth is the major factor impacting marine N-cycling communities, differentiating mesopelagic from epipelagic communities. Latitudinal diversity gradients and distance-decay relationships are observed for taxonomic groups, but rarely or weakly for functional traits. The composition of functional traits is strongly deterministic as revealed by null model analysis, while a higher degree of stochasticity is observed for taxonomic composition. Integrating multiple lines of evidence, in addition to drawing a biogeographic picture of marine N-cycling communities, this study also demonstrated an essential microbial ecological theory—determinism governs the assembly of microbial communities performing essential biogeochemical processes; the environment selects functional traits rather than taxonomic groups; functional redundancy underlies stochastic taxonomic community assembly.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Differences in spore size and atmospheric survival shape stark contrasts in the dispersal dynamics of two closely related fungal pathogens

A frequently ignored but critical aspect of microbial dispersal is survival in the atmosphere. Here, we exposed spores of two closely related, morphologically dissimilar, and economically important fungal pathogens to typical atmospheric environments and modeled their movement in the troposphere. Alternaria solani conidia are nearly 10 times larger than A. alternata conidia, but in our experiments, most died within 24 h, while over half of A. alternata conidia remained viable on day 12. Next, we modeled the movement of spores across North America. We predict 99% of the larger A. solani conidia settle within 24 h, with a maximum dispersal distance of 100 km. By contrast, most A. alternata conidia remain airborne for more than 12 days, and dispersal over long distances(2000 km) is likely. Counterintuitively, the larger A. solani conidia survive poorly, as compared to smaller A. alternata conidia, but also land sooner and move over shorter distances.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Tapping the treasure trove of atypical phages

With advancements in genomics technologies, a vast diversity of ‘atypical’ phages, that is, with single-stranded DNA or RNA genomes, are being uncovered from different ecosystems. Though these efforts have revealed the existence and prevalence of these nonmodel phages, computational approaches often fail to associate these phages with their specific bacterial host(s), while the lack of methods to isolate these phages has limited our ability to characterize infectivity pathways and new gene function. In this review, we call for the development of generalizable experimental methods to better capture this understudied viral diversity via isolation and study them through gene-level characterization and engineering. Establishing a diverse set of new ‘atypical’ phage model systems has the potential to provide many new biotechnologies, including potential uses of these atypical phages in halting the spread of antibiotic resistance and engineering of microbial communities for beneficial outcomes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Compositional and temporal division of labor modulates mixed sugar fermentation by an engineered yeast consortium

Abstract Synthetic microbial communities have emerged as an attractive route for chemical bioprocessing. They are argued to be superior to single strains through microbial division of labor (DOL), but the exact mechanism by which DOL confers advantages remains unclear. Here, we utilize a synthetic Saccharomyces cerevisiae consortium along with mathematical modeling to achieve tunable mixed sugar fermentation to overcome the limitations of single-strain fermentation. The consortium involves two strains with each specializing in glucose or xylose utilization for ethanol production. By controlling initial community composition, DOL allows fine tuning of fermentation dynamics and product generation. By altering inoculation delay, DOL provides additional programmability to parallelly regulate fermentation characteristics and product yield. Mathematical models capture observed experimental findings and further offer guidance for subsequent fermentation optimization. This study demonstrates the functional potential of DOL in bioprocessing and provides insight into the rational design of engineered ecosystems for various applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

High yield production of 3-hydroxypropionic acid using Issatchenkia orientalis

Biomanufacturing provides a more sustainable alternative to fossil-based chemical manufacturing. 3-Hydroxypropionic acid (3HP) is a top Department of Energy value-added chemical and precursor to bioplastics, yet cost-effective microbial production remains elusive. Here, we establish the acid-tolerant yeast Issatchenkia orientalis as a robust host for low-pH 3HP biosynthesis. Genome-scale modeling identifies the β-alanine pathway as optimal, offering the highest theoretical yield and lowest oxygen requirement. Thermodynamic analysis confirms its favorability under acidic conditions. Using sequence similarity network analysis, we discover highly active aspartate 1-decarboxylase (PAND), β-alanine-pyruvate aminotransferase (BAPAT), and 3HP dehydrogenase (YDFG), which significantly improve the pathway efficiency. Next, to further elevate the production, pathway optimization through multi-copy PAND integration, byproduct elimination (knockouts of pyruvate decarboxylase and glycerol-3-phosphate dehydrogenase), and reinforcement of aspartate flux by overexpression of pyruvate carboxylase and aspartate amino transferase improves the titer to 29 g/L in shake flasks. Fed-batch fermentation at pH 4 with low-cost corn steep liquor medium further increases the production to 92 g/L with 0.7 g/g yield and 0.55 g/L/h productivity. Techno-economic analysis indicates that such performance could potentially enable a financially viable process for sustainable acrylic acid production. This work establishes I. orientalis as a next-generation platform for cost-effective 3HP production and paves the way toward industrial commercialization.

Biotechnology↗

DOE OSTI2023

High-throughput genetic engineering of nonmodel and undomesticated bacteria via iterative site-specific genome integration

Efficient genome engineering is critical to understand and use microbial functions. Despite recent development of tools such as CRISPR-Cas gene editing, efficient integration of exogenous DNA with well-characterized functions remains limited to model bacteria. Here, we describe serine recombinase–assisted genome engineering, or SAGE, an easy-to-use, highly efficient, and extensible technology that enables selection marker–free, site-specific genome integration of up to 10 DNA constructs, often with efficiency on par with or superior to replicating plasmids. SAGE uses no replicating plasmids and thus lacks the host range limitations of other genome engineering technologies. We demonstrate the value of SAGE by characterizing genome integration efficiency in five bacteria that span multiple taxonomy groups and biotechnology applications and by identifying more than 95 heterologous promoters in each host with consistent transcription across environmental and genetic contexts. We anticipate that SAGE will rapidly expand the number of industrial and environmental bacteria compatible with high-throughput genetics and synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1977

Engineering and simulation of life science Spacelab experiments

Approaches to the planning and realization of Spacelab life sciences experiments, which may involve as many as 16 Space Shuttle missions and 100 tests, are discussed. In particular, a Spacelab simulation program, designed to evaluate problems associated with the use of live animal specimens, the constraints imposed by zero gravity on equipment operation, training of investigators and data management, is described. The simulated facility approximates the hardware and support systems of a current European Space Agency Spacelab model. Preparations necessary for the experimental program, such as crew activity plans, payload documentation and inflight experimental procedures are developed; health problems of the crew, including human/animal microbial contamination, are also assessed.

Bush, B.↗

NASA NTRS2011

Isotopic Evidence for the Source and Fate of Phosphorus in Everglades Wetland Ecosystems

Phosphorus has historically been a limiting nutrient in the Florida Everglades. Increased P loading to the Everglades over the past several decades has led to significant changes in water quality and plant communities. Stormwater runoff that drains agricultural lands and enters the Water Conservation Areas (WCAs) are known to contain elevated levels of P, but the exact source of this P has not been fully determined. Here the results of an O isotope study of dissolved inorganic phosphate (DIP) in both polluted and relatively pristine (or reference) areas of the Everglades are reported. The data reveal spatial and temporal variations in the delta 18O signature of DIP, reflecting the source and the degree of cycling of P. The delta 18O values of DIP collected from the Everglades National Park were close or equal to the predicted delta 18O values of DIP formed in situ in equilibrium with ambient water, indicating that P is quickly cycled in the water column in oligotrophic ecosystems with very low P concentrations. However, most DIP samples collected from areas impacted by agricultural runoff yielded delta 18O values that deviated from the predicted equilibrium DIP delta 18O values based on the delta 18O of water and water temperature, suggesting that biological cycling of P was not rapid enough to remove the fertilizer ?18O signature in the DIP pool from areas receiving high P loading. The delta 18O signature of DIP in impacted areas reflects a mixing of fertilizer P and biologically cycled P, where the relative proportions of biologically cycled vs. fertilizer DIP are controlled by both biological (microbial activities and plant uptake) and hydrologic factors (loading rate and residence time). Using a two-end-member (i.e., fertilizer P and biologically cycled P) mixing model, fertilizers were estimated to contribute about 15 100% of the DIP pool in the highly impacted areas of the northern Everglades, whereas the DIP pool in the reference (i.e., relatively pristine) wetlands in the Everglades National Park was dominated by biologically cycled P. The study shows that O isotopic measurements of dissolved PO(exp 3-, sub 4) can be a useful tool for tracing the fertilizer P inputs to freshwater ecosystems.

Li, Xin↗

NASA NTRSDate not supplied

Microbial Responses to Radiation at the Single-Cell Level

Exploring the biological effects of deep space radiation is crucial for developing protective protocols for humans traveling beyond Earth’s magnetosphere. Saccharomyces cerevisiae, or budding yeast, is an ideal model organism to study the effects of radiation on eukaryotes as it shares several pathways with humans, including DNA repair mechanisms. Here, we used time-lapse imaging of colony growth on agar plates to monitor the effects of radiation exposure on individual yeast cells and their progeny.

Paola J. Maldonado Martinez↗

DOE OSTI2022

Global distribution, formation and fate of mineral‐associated soil organic matter under a changing climate: A trait‐based perspective

Abstract Soil organic matter (SOM) is the largest actively cycling reservoir of terrestrial carbon (C), and the majority of SOM in Earth's mineral soils (~65%) is mineral‐associated organic matter (MAOM). Thus, the formation and fate of MAOM can exert substantial influence on the global C cycle. To predict future changes to Earth's climate, it is critical to mechanistically understand the processes by which MAOM is formed and decomposed, and to accurately represent this process‐based understanding in biogeochemical and Earth system models. In this review, we use a trait‐based framework to synthesize the interacting roles of plants, soil micro‐organisms, and the mineral matrix in regulating MAOM formation and decomposition. Our proposed framework differentiates between plant and microbial traits that influence total OM inputs to the soil (‘feedstock traits’) versus traits that influence the proportion of OM inputs that are ultimately incorporated into MAOM (‘MAOM formation traits’). We discuss how these feedstock and MAOM formation traits may be altered by warming, altered precipitation and elevated carbon dioxide. At a planetary scale, these feedstock and MAOM formation traits help shape the distribution of MAOM across Earth's biomes, and modulate biome‐specific responses of MAOM to climate change. We leverage a global synthesis of MAOM measurements to provide estimates of the total amount of MAOM‐C globally (~840–1540 Pg C; 34%–51% of total terrestrial organic C), and its distribution across Earth's biomes. We show that MAOM‐C concentration is highest in temperate forests and grasslands, and lowest in shrublands and savannas. Grasslands and croplands have the highest proportion of soil organic carbon (SOC) in the MAOM fraction (i.e. the MAOM‐C:SOC ratio), while boreal forests and tundra have the lowest MAOM‐C:SOC ratio. Drawing on our trait framework, we then review experimental data and posit the effects of climate change on MAOM pools in different biomes. We conclude by discussing how MAOM is integrated into soil C models, and how feedstock and MAOM formation traits may be included in these models. We also summarize the projected fate of MAOM under climate change scenarios (Representative Concentration Pathways 4.5 and 8.5) and discuss key model uncertainties. Read the free Plain Language Summary for this article on the Journal blog.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Biochemical Process Modeling and Simulation (BPMS)

The Biochemical Process Modeling and Simulation project aims to reduce the cost and time of research by applying theory, modeling, and simulation to the most relevant bottlenecks in the biochemical process. We use molecular modeling, quantum mechanics, metabolic modeling, fluid dynamics, and reaction-diffusion methods in close collaboration with pretreatment, hydrolysis, upgrading, and TEA. The project's outcomes are increased yields and efficiency of the biochemical process, added value to products, and reduced price of fuels by specifically targeting catalytic efficiency, reactor design, enzyme efficiency, and microbial design. We work closely with experimental projects to identify problems and iterate with experiments to find and refine solutions. By working with experimentalists, we decide on problems that can be solved with simulation that could otherwise not be solved or would take too long with experiment alone to reach BETO's targets. Over the years, we have produced solutions that have resulted in determining the most likely fatty-acid derivative for passive transport out of bacteria that upgrade biomass, and we have also designed enzyme mutations for enhanced lignin upgrading. Metabolic models have been developed to tune the activity of 2,3 butanediol production for the 2030 target. A computational method to deliver understanding of how complex omics data can be interpreted in the metabolic pathways of organisms used in the Agile Biofoundry. We have found methods to overcome specific barriers and continue to develop those methods. Our reactor studies have guided the design of both the microbes and reactors for aerobic and micro-aerobic production at all scales and have been instrumental in improving the accuracy of techno-economic analysis models. This project is essential in the process of selecting the final processes for 2030 SAF production targets. More specifically, recently, we have: 1) Predicted the strength of the basic structural interactions in commodity plastics to provide guidance for plastics upcycling strategies. 2) Developed computational tool to improve the characterization of lignin-derived compounds 3) Developed new methodologies to enable Machine Learning-based Directed Evolution for protein engineering. 4) Developed Machine Learning methods to predict protein promiscuity and mutations to further improve microbial and enzymatic driven processes and demonstrated the utility of ML approaches to engineering proteins from sparse experimental datasets. 5) Developed new methods to enable high-fidelity simulation of aerobic fermentation at industrial scale and resolving mismatch of time scales through subcycling/operator splitting 7) Identified the difficulty in preventing local high-oxygen conditions in industrial bubble columns, which leads to less-desirable acetoin production, suggesting future research directions in alternative reactor configurations (e.g loop reactors, shallow-channel reactors).

BIOMASS FUELS↗

DOE OSTI2025

Structured interactions drive abrupt transitions in the spatial organization of microbial communities

Bacteria possess diverse mechanisms to regulate their motility in response to environmental and physiological signals, enabling them to navigate complex habitats and adapt their behavior. Some of these mechanisms are species specific and enable cells to modulate their movement based on the ecological identity of neighboring species. Here, we introduce a model in which bacteria interact via local signals that either enhance or suppress the motility of neighboring cells depending on species type. Through large-scale simulations and a coarse-grained stochastic model, we demonstrate the emergence of a sharp transition driven by nucleation processes: increasing the density of motility-suppressing interactions drives the system from a fully mixed, motile phase to a state characterized by large, stationary bacterial clusters. Remarkably, in systems with a large number of interacting species, this transition can be triggered solely by altering the structure of the motility-regulation interaction matrix while maintaining species and interaction densities constant. In particular, we find that heterogeneous and modular interactions promote the transition more readily than homogeneous random ones. These findings add a dimension to the theory of motility-induced phase separation and contribute to the ongoing effort to understand microbial interactions, suggesting that structured, nonrandom ones may be key to reproducing commonly observed spatial patterns in microbial communities.

bacterial communities↗

DOE OSTI2023

Development of molecular cluster models to probe pyrite surface reactivity

Abstract The recent discovery that anaerobic methanogens can reductively dissolve pyrite and utilize dissolution products as a source of iron and sulfur to meet their biosynthetic demands for these elements prompted the development of atomic‐scale nanoparticle models, as maquettes of reactive surface sites, for describing the fundamental redox steps that take place at the mineral surface during reduction. The given report describes our computational approach for modeling n (FeS 2 ) nanoparticles originated from mineral bulk structure. These maquettes contain a comprehensive set of coordinatively unsaturated Fe (II) sites that are connected via a range of persulfide (S 2 2− ) ligation. In addition to the specific maquettes with n = 8, 18, and 32 FeS 2 units, we established guidelines for obtaining low‐energy structures by considering the pattern of ionic, covalent, and magnetic interactions among the metal and ligand sites. The developed models serve as computational nano‐reactors that can be used to describe the reductive dissolution mechanism of pyrite to better understand the reactive sites on the mineral, where microbial extracellular electron‐transfer reactions can occur.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Stimulation of soil respiration by elevated CO 2 is enhanced under nitrogen limitation in a decade-long grassland study

Whether and how CO 2 and nitrogen (N) availability interact to influence carbon (C) cycling processes such as soil respiration remains a question of considerable uncertainty in projecting future C–climate feedbacks, which are strongly influenced by multiple global change drivers, including elevated atmospheric CO 2 concentrations (eCO 2 ) and increased N deposition. However, because decades of research on the responses of ecosystems to eCO 2 and N enrichment have been done largely independently, their interactive effects on soil respiratory CO 2 efflux remain unresolved. Here, we show that in a multifactor free-air CO 2 enrichment experiment, BioCON (Biodiversity, CO 2 , and N deposition) in Minnesota, the positive response of soil respiration to eCO 2 gradually strengthened at ambient (low) N supply but not enriched (high) N supply for the 12-y experimental period from 1998 to 2009. In contrast to earlier years, eCO 2 stimulated soil respiration twice as much at low than at high N supply from 2006 to 2009. In parallel, microbial C degradation genes were significantly boosted by eCO 2 at low but not high N supply. Further, incorporating those functional genes into a coupled C–N ecosystem model reduced model parameter uncertainty and improved the projections of the effects of different CO 2 and N levels on soil respiration. If our observed results generalize to other ecosystems, they imply widely positive effects of eCO 2 on soil respiration even in infertile systems.

54 ENVIRONMENTAL SCIENCES↗