Redirecting carbon to bioproduction via a growth arrest switch in a sucrose-secreting cyanobacterium
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Abramson, Bradley W.↗
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Regulated redirection of central carbon flux enhances anaerobic production of bioproducts in Zymomonas mobilis
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Biotechnology & Applied Microbiology↗
WBS 4.1.2.31 Bioproduct Transition System Dynamics
Bioproducts are chemicals derived from a biomass feedstock; they can be produced on their own or as co-products of a biorefinery that also produces biofuels. Bioproducts have historically been difficult to scale up and bring to market, despite a broad understanding developed within BETO of the various conversion processes that can be used to produce bioproducts. Expanding the bioproducts industry by bringing more bioproducts to market would have a variety of positive impacts. Growth in the bioproducts industry would support the biofuels industry by enabling biorefinery co-products that yield additional revenue streams, allowing biofuel selling prices to be reduced and expanding the biofuels market. A larger bioproducts industry also has the potential to reduce carbon and other emissions associated with the U.S. chemical sector and contribute to increased price stability in some areas of the chemical market by shifting portions of the chemical sector away from reliance on fossil feedstocks. The key barrier to realizing these positive impacts is a lack of knowledge around the factors that prevent or enable bioproducts to reach the commercial market. To date, there has been essentially no research done on how successful bioproducts (commercially produced bioproducts that have captured market share) become successful, why failed bioproducts fail, and what the similarities and differences are between successful and failed bioproducts. The current project addresses this knowledge gap with a decision support tool that can be used by investors, technology developers and government agencies to bring more bioproducts to market, thereby simultaneously growing the bioproducts and biofuels industries. Development of the decision support tool was based on research on the technology development process and success rates in analogous industries, data gathered during previous BETO-funded projects, and a series of interviews with subject-matter experts within BETO, the bioproducts industry, and the investment community. This information formed a knowledge base around how bioproducts are developed from applied research to commercial scale was assembled, which was used to build the Bioproduct Transition Dynamics (BTD) model, a system dynamics (SD) model that tracks bioproduct development projects from applied research through the 'valley of death' of piloting and demoing to commercial scale production. The end-of-project goal is to release the BTD, along with supporting documentation, as a transparent open-source model that will inform decisions around bioproduct development and investments and enable more bioproducts to reach the market. The BTD takes as inputs techno-economic data on specific bioproducts, behavioral parameters for developers and investors, expectations around government support, and exogenous market factors. Model outputs include bioproduct technological progress over time, a cash flow statement for the development project, and market share estimates. Following initial model development, a sensitivity analysis was performed on a subset of model inputs to determine, first, if the BTD could be used to answer analysis questions of interest to BETO, and second, which of the inputs considered were most influential on bioproduct success. Results indicate that the BTD can be used to identify scenarios that enable bioproduct development, and that 'soft' or semi-quantitative factors play a large role in determining if a bioproduct will reach the market. A workshop was also held for subject-matter experts and prospective BTD users in July 2018. The workshop covered BTD model logic, input data and assumptions as well as the sensitivity analysis results and a discussion of potential use cases. Workshop feedback was used to identify additional model development tasks and was incorporated into a draft technical report completed in September 2018. BTD model development, validation and application will continue through 2019.
09 BIOMASS FUELS↗
Introduction to the Bioproduct Transition Dynamics Model
The U.S. Department of Energy, Bioenergy Technologies Office has a broad understanding of different conversion processes that produce bioproducts (chemicals derived from biomass feedstocks) and the market attributes of those processes. However, bioproducts have in many cases proven to be difficult to scale up to commercial production and bring to market, and there is currently a need for greater understanding around the possible successful scenarios for advancing the bioproducts industry. Insight into the myriad factors that impact the success of individual bioproducts and the growth of the bioproducts industry will enable bioproduct stakeholders to evaluate strategies for development and investment that could achieve the greatest impact. An understanding of these factors will also enable the identification of synergies between the bioproducts and biofuels industries that occur through shared learning and co-production. The Bioproduct Transition Dynamics (BTD) model explores questions such as the following: what are the factors that separate a successful, commercially produced bioproduct like succinic acid from one that never progresses beyond bench-scale lab research? Can these factors be influenced by stakeholders, and to what extent? The BTD model uses system dynamics to capture the impacts of investor decision-making, bioproduct techno-economics, and market factors during the early stages of bioproduct development. Key components of the BTD model include techno-economic benchmarks that inform the investor decision-making process, failures and setbacks in development and the resulting need for additional work, and the impacts of effective or ineffective management during each development stage. These factors and their interactions are tracked through bench-scale laboratory research, piloting, demoing, and the construction and operation of the first commercial-scale plant. Bioproduct development is linked to the biofuels industry through a shared-learning model, enabling the benefit to biofuels from bioproduct technology and feedstock supply chain development to be quantified. A wide variety of bioproducts can be analyzed using the BTD model, including bioproducts that have been developed through economic or policy-driven mechanisms, and those with either niche (low volume) or scalable (high volume) markets. The BTD model also has the potential to apply to technology development processes outside the bioproducts industry; background research performed for this project has shown that the early stages of technology development are similar, and impacted by similar factors, regardless of the exact industry. This presentation will cover the BTD model logic, input data, validation process, and results of a sensitivity analysis based on techno-economic data for succinic acid. The sensitivity analysis was performed to identify factors with the largest impact on the eventual success or failure of a bioproduct. Results indicate that management effectiveness, which affects how efficiently money spent is converted into technological advancements, is the single most important factor in determining whether a bioproduct reaches commercial-scale production. The capacity of the first commercial plant and the type of biomass feedstock used, as well as the presence of government support in the form of cost-sharing, were also identified as significant factors.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
A System Dynamics Model of Early-Stage Transition Dynamics in the Bioproducts Industry
The U.S. Department of Energy, Bioenergy Technologies Office has a broad understanding of different conversion processes that produce bioproducts (chemicals derived from biomass feedstocks) and the techno-economic attributes of those processes. However, bioproducts have in many cases proven to be difficult to scale up to commercial production, and there is currently a need for greater understanding around the possible successful scenarios for advancing the bioproducts industry. Insight into the myriad factors that impact the success of individual bioproducts and the growth of the bioproducts industry will enable bioproduct stakeholders to evaluate strategies for development and investment that could achieve the greatest impact. An understanding of these factors will also enable the identification of synergies between the bioproducts and biofuels industries that occur through shared learning and co-production. The Bioproduct Transition Dynamics (BTD) model explores questions such as the following: what are the factors that separate a successful, commercially produced bioproduct like succinic acid from one that never progresses beyond bench-scale lab research? Can these factors be influenced by stakeholders, and to what extent? The BTD model uses system dynamics to capture the impacts of investor decision-making, bioproduct techno-economics, and end use factors during the early stages of bioproduct development. Key components of the BTD model include techno-economic benchmarks that inform the investor decision-making process, failures and setbacks in development and the resulting need for additional work, and the impacts of effective or ineffective management during each development stage. These factors and their interactions are tracked through bench-scale laboratory research, piloting, demoing, and the construction and operation of the first commercial-scale plant. Bioproduct development is linked to the biofuels industry through a shared-learning model, enabling the benefit to biofuels from bioproduct technology and feedstock supply chain development to be quantified. A wide variety of bioproducts can be analyzed using the BTD model, including bioproducts that have been developed through economic or policy-driven mechanisms, and those with either niche (low volume) or scalable (high volume) demand. The BTD model also has the potential to apply to technology development processes outside the bioproducts industry; background research performed for this project has shown that the early stages of technology development are similar, and impacted by similar factors, regardless of the exact industry. This presentation will cover the BTD model logic, input data, validation process, and results of a sensitivity analysis based on techno-economic data for succinic acid. The sensitivity analysis was performed to identify factors with the largest impact on the eventual success or failure of a bioproduct. Results indicate that management effectiveness, which affects how efficiently money spent is converted into technological advancements, is the single most important factor in determining whether a bioproduct reaches commercial-scale production. The capacity of the first commercial plant and the type of biomass feedstock used, as well as the presence of government support in the form of cost-sharing, were also identified as significant factors.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Transition Dynamics in the Nascent Bioproducts Industry
Bioproducts are chemicals derived from a biomass feedstock that can be produced on their own or as biofuel co-products. Historically, bioproduct developers have faced significant barriers in scaling up bioproduct technologies and in bringing bioproducts to market, resulting in a high failure rate for bioproduct development projects. To date, there has been essentially no research done on the factors that lead to a bioproduct successfully capturing market share and why bioproduct projects fail. We address this knowledge gap with a model of the transition dynamics involved in taking a bioproduct technology from applied research to commercial production and the interactions between bioproduct developers, investors providing private funds, and federal government agencies which may provide cost-sharing and production incentives. This model incorporates several novel techniques including stochastic submodels and forecasts of market shares and company performance. Our research objectives are to identify relevant factors and mechanisms that impact bioproduct success and to develop a decision support tool, the Bioproduct Transition Dynamics (BTD) system dynamics model, that can be used by investors, bioproduct developers and government agencies to bring more bioproducts to market and to grow the nascent bioproducts industry.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Supporting Bioproducts Industry Growth with a System Dynamics Decision-Support Tool
A bio-based economy requires chemical products as well as fuels to be produced from biomass. Although a variety of universities, government agencies, start-ups and established firms have engaged in bioproduct development, many projects have failed to reach the point of commercialization and commercialized bioproducts struggle to capture and maintain market share. To date, there has been no general research into the factors that contribute to bioproduct failure or success. This work presents the Bioproduct Transition Dynamics (BTD) system dynamics model, a decision-support tool that simulates the bioproduct development process from pre-piloting research through construction of the first commercial-scale plant, as well as the processes of obtaining funding from investors and government agencies. The core of the BTD is a feedback loop between bioproduct developers and funders, which relates development progress measured with indicators such as net present value to funders’ decisions to continue investing. External factors such as feedstock prices, market size and growth, and the existence of bioproduct consumers also influence a development project’s chances of receiving follow-on funding. Virtually any bioproduct can be represented with the BTD: direct replacements, performance-advantaged products, niche and commodity markets can all be modeled. The goal of the BTD project is to inform decisions made by developers in both established firms and start-ups, investors, government agencies, and other stakeholders interested in growing the nascent U.S. bioproducts industry. This talk will cover the general structure and functionality of the BTD, and present results from an analysis performed with the BTD to demonstrate its use as a decision-support tool and the insights it can provide. The goal of the analysis is to identify the most critical factors that lead to direct replacement and performance-advantaged bioproduct projects emerging successfully from the “Valley of Death”, and to determine if these factors differ between the two bioproduct types.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Microbial conversion of xylose into useful bioproducts
Microorganisms can produce a number of different bioproducts from the sugars in plant biomass. One challenge is devising processes that utilize all of the sugars in lignocellulosic hydrolysates. D-xylose is the second most abundant sugar in these hydrolysates. The microbial conversion of D-xylose to ethanol has been studied extensively; only recently, however, has conversion to bioproducts other than ethanol been explored. Moreover, in the case of yeast, D-xylose may provide a better feedstock for the production of bioproducts other than ethanol, because the relevant pathways are not subject to glucose-dependent repression. In this review, we discuss how different microorganisms are being used to produce novel bioproducts from D-xylose. As a result, we also discuss how D-xylose could be potentially used instead of glucose for the production of value-added bioproducts.
09 BIOMASS FUELS↗
BETO 2021 Peer Review - Inverse Bioproduct Design Through Machine Learning and Molecular Simulation
This work aims to identify performance advantaged bioproducts (PABPs) through property prediction, which will guide experimental synthesis. The impact of this work will be faster market adoption of bioproducts with greater performance relative to incumbent products. We have identified >106 bioproduct candidates, but only some will have superior performance to create a market pull. High-throughput property prediction, enabled by machine learning, and elucidation of structure-function relationships, enabled by molecular simulation, provide a hypothesis driven approach for down selection of candidate biomolecules to pursue experimentally. To enable machine learning and molecular simulation for bioproduct discovery, automated structure generation and embedding must capture relevant features for prediction, databases must cover domains applicable to biobased products, and best practices for simulation of polymer systems must be developed. To address these challenges, we have established bioproduct relevant datasets, developed high-throughput polymer structure generation, and built end-to-end neural networks that have predicted 8 properties for >1.4 x 106 biopolymers. A molecular simulation pipeline for building, running, and analyzing polymers and polymer additives is being used to predict performance and develop design principles of biobased products. In collaboration with the PABP synthesis project, these computational tools are guiding synthesis and informing design of PABPs.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
ATP biosensor reveals microbial energetic dynamics and facilitates bioproduction
Adenosine-5’-triphosphate (ATP), the primary energy currency in cellular processes, drives metabolic activities and biosynthesis. Despite its importance, understanding intracellular ATP dynamics’ impact on bioproduction and exploiting it for enhanced bioproduction remains largely unexplored. Here, we harness an ATP biosensor to dissect ATP dynamics across different growth phases and carbon sources in multiple microbial strains. We find transient ATP accumulations during the transition from exponential to stationary growth phases in various conditions, coinciding with fatty acid (FA) and polyhydroxyalkanoate (PHA) production in Escherichia coli and Pseudomonas putida, respectively. We identify carbon sources (acetate for E. coli, oleate for P. putida) that elevate steady-state ATP levels and boost FA and PHA production. Moreover, we employ ATP dynamics as a diagnostic tool to assess metabolic burden, revealing bottlenecks that limit limonene bioproduction. Our results not only elucidate the relationship between ATP dynamics and bioproduction but also showcase its value in enhancing bioproduction in various microbial species.
59 BASIC BIOLOGICAL SCIENCES↗
Bioproducts from high-protein algal biomass: An economic and environmental sustainability review and risk analysis
This report has High-protein algal biomass as an important bio-commodity that has the potential to provide a new source of sustainable protein products. Herein is a critical review that identifies 1) the most relevant sustainability findings related to the processing of proteinaceous algal biomass to higher value protein products and 2) the potential pathways to improve life cycle assessment (LCA) and techno-economic analysis (TEA) metrics, including life-cycle carbon dioxide equivalent (CO 2 eq), life cycle energy, and minimum selling price (MSP) of these products. The critical review of the literature revealed a large variation in model input parameters relating to these metrics. Therefore, a Monte Carlo analysis was conducted to assess the risk associated with these input variations. To understand the uncertainties that propagate into high-protein algae to products’ systems, we reviewed more than 20 state-of-the-art unit operations for algal biomass processing., including cell disruption, protein solubilization, protein precipitation and purification, and protein concentration. We evaluated displacement of proteinaceous products by algal-bioproducts, including ruminant feed, aquaculture feed, protein tablets, and biopolymers and biopolyesters, with prices in the market ranging from 1.9 to 120 $\$$ kg -1 protein. This review realized that the MSP of ruminant and non-ruminant feed ranges from 0.65±0.56 to 2.9±1.1 $\$$ kg -1 protein, and bioplastics’ MSP ranges from 0.97 to 7.0 $\$$ kg -1 protein. Regarding LCA metrics, there is limited research on life cycle energy in proteinaceous biomass concentration and bioproduct systems, reported at 32.7 MJ kg protein -1 , for animal feed displacement. Animal feed emissions in the literature report negative fluxes, representing environmental benefits, as low as -3.7 kgCO 2 eq kg -1 protein and positive fluxes, i.e., global warming potential, as high as 12.8 kgCO 2 eq kg -1 protein. There is limited research on bioplastics life cycle emissions reported at 0.6 kgCO 2 eq kg -1 protein. In general, the studies to date of algae-derived protein bioproducts showed similar life cycle emissions to soybean meals, nylon, polymers, and polystyrenes. Our risk analysis realized that more than 50% of scenarios can result in negative-net life cycle CO 2 eq emissions. This review and risk analysis assess and demonstrate the scenarios that improve economic and environmental sustainability metrics in high-protein algal bioproducts systems.
09 BIOMASS FUELS↗
Accumulation of high-value bioproducts in planta can improve the economics of advanced biofuels
Coproduction of high-value bioproducts at biorefineries is a key factor in making biofuels more cost-competitive. One strategy for generating coproducts is to directly engineer bioenergy crops to accumulate bioproducts in planta that can be fractionated and recovered at biorefineries. Here, we develop quantitative insights into the relationship between bioproduct market value and target accumulation rates by investigating a set of industrially relevant compounds already extracted from plant sources with a wide range of market prices and applications, including <$10/kg (limonene, latex, and polyhydroxybutyrate [PHB]), $10 to $100/kg (cannabidiol), and >$100/kg (artemisinin). These compounds are used to identify a range of mass fraction thresholds required to achieve net economic benefits for biorefineries and the additional amounts needed to reach a target $2.50/gal biofuel selling price, using cellulosic ethanol production as a test case. Bioproduct market prices and recovery costs determine the accumulation threshold; we find that moderate- to high-value compounds (i.e., cannabidiol and artemisinin) offer net economic benefits at accumulation rates of just 0.01% dry weight (dwt) to 0.02 dwt%. Lower-value compounds, including limonene, latex, and PHB, require at least an order-of-magnitude greater accumulation to overcome additional extraction and recovery costs (0.3 to 1.2 dwt%). We also find that a diversified approach is critical. For example, global artemisinin demand could be met with fewer than 10 biorefineries, while global demand for latex is equivalent to nearly 180 facilities. Our results provide a roadmap for future plant metabolic engineering efforts aimed at increasing the value derived from bioenergy crops.
09 BIOMASS FUELS↗
Cyanobacterial circadian regulation enhances bioproduction under subjective nighttime through rewiring of carbon partitioning dynamics, redox balance orchestration, and cell cycle modulation
Abstract Background The industrial feasibility of photosynthetic bioproduction using cyanobacterial platforms remains challenging due to insufficient yields, particularly due to competition between product formation and cellular carbon demands across different temporal phases of growth. This study investigates how circadian clock regulation impacts carbon partitioning between storage, growth, and product synthesis in Synechococcus elongatus PCC 7942, and provides insights that suggest potential strategies for enhanced bioproduction. Results After entrainment to light-dark cycles, PCC 7942 cultures transitioned to constant light revealed distinct temporal patterns in sucrose production, exhibiting three-fold higher productivity during subjective night compared to subjective day despite moderate down-regulation of genes from the photosynthetic apparatus. This enhanced productivity coincided with reduced glycogen accumulation and halted cell division at subjective night time, suggesting temporal separation of competing processes. Transcriptome analysis revealed coordinated circadian clock-driven adjustment of the cell cycle and rewiring of energy and carbon metabolism, with over 300 genes showing differential expression across four time points. The subjective night was characterized by altered expression of cell division-related genes and reduced expression of genes involved in glycogen synthesis, while showing upregulation of glycogen degradation pathways, alternative electron flow components, the pentose phosphate pathway, and oxidative decarboxylation of pyruvate. These molecular changes created favorable conditions for product formation through enhanced availability of major sucrose precursors (glucose-1-phosphate and fructose-6-phosphate) and maintained redox balance through multiple mechanisms. Conclusions Our analysis of circadian regulatory rewiring of carbon metabolism and redox balancing suggests two potential approaches that could be developed for improving cyanobacterial bioproduction: leveraging natural circadian rhythms for optimizing cultivation conditions and timing of pathway induction, and engineering strains that mimic circadian-driven metabolic shifts through controlled carbon flux redistribution and redox rebalancing. While these strategies remain to be tested, they could theoretically improve the efficiency of photosynthetic bioproduction by enabling better temporal separation between cell growth, carbon storage accumulation, and product synthesis phases.
59 BASIC BIOLOGICAL SCIENCES↗
Fast growth and high-titer bioproduction from renewable formate via metal-dependent formate dehydrogenase in Escherichia coli
Microbial bioproduction using one-carbon (C1) feedstocks has the potential to decarbonize the manufacturing of materials, fuels, and chemicals. Formate is a promising C1 feedstock, and the realization of industrial, formatotrophic platform organisms is a key goal for C1-based bioproduction. So far, a major limitation for synthetic formatotrophy has been slow energy supply due to slow formate dehydrogenase activity. Here, we implement a fast, metal-dependent formate dehydrogenase complex in a synthetic formatotrophic Escherichia coli utilizing the reductive glycine pathway. After a short-term evolution, we demonstrate formatotrophic growth of E. coli with a doubling time of less than 4.5 h, comparable to the fastest natural formatotrophs. To further explore the potential of a formate-based bioeconomy, this strain is engineered to produce mevalonate, as well as the terpenoid and aviation fuel precursor isoprenol, using formate we generate directly from the electrochemical reduction of CO2. This work demonstrates an improvement in bioproduct titer from formate, achieving the production of 3.8 g/L of mevalonate. Additionally, the abundant and recalcitrant polymer lignin is chemically decomposed into a formate-rich mixture of small organic acids and subsequently bioconverted into mevalonate. Overall, the described fast-growing, formatotrophic bioproduction strain demonstrates that a sustainable formate bioeconomy is within reach.
Cowan, Aidan E↗
Evaluation of engineered low-lignin poplar for conversion into advanced bioproducts
Lignocellulosic resources are promising feedstocks for the manufacture of bio-based products and bioenergy. However, the inherent recalcitrance of biomass to conversion into simple sugars currently hinders the deployment of advanced bioproducts at large scale. Lignin is a primary contributor to biomass recalcitrance as it protects cell wall polysaccharides from degradation and can inhibit hydrolytic enzymes via non-productive adsorption. Several engineering strategies have been designed to reduce lignin or modify its monomeric composition. For example, expression of bacterial 3-dehydroshikimate dehydratase (QsuB) in poplar trees resulted in a reduction in lignin due to redirection of metabolic flux toward 3,4-dihydroxybenzoate at the expense of lignin. This reduction was accompanied with remarkable changes in the pools of aromatic compounds that accumulate in the biomass. The impact of these modifications on downstream biomass deconstruction and conversion into advanced bioproducts was evaluated in the current study. Using ionic liquid pretreatment followed by enzymatic saccharification, biomass from engineered trees released more glucose and xylose compared to wild-type control trees under optimum conditions. Fermentation of the resulting hydrolysates using Rhodosporidium toruloides strains engineered to produce α-bisabolene, epi-isozizaene, and fatty alcohols showed no negative impact on cell growth and yielded higher titers of bioproducts (as much as + 58%) in the case of QsuB transgenics trees. Our data show that low-recalcitrant poplar biomass obtained with the QsuB technology has the potential to improve the production of advanced bioproducts.
09 BIOMASS FUELS↗
Enhancing chemical bioproduction with rational control of bacterial post-translational modifications
Efficient conversion of inexpensive feedstocks to valuable chemicals by microbes is critical for a robust bioeconomy, but the ability to rationally design bacteria is hampered by insufficient knowledge of how post translational modifications (PTMs) control bacterial protein function and thus bioproduction phenotypes. Our study will focus on the lysine acetylation, a ubiquitous bacterial PTM that can affect the function of enzymes in central metabolism that are often critical for bioproduction processes, disrupt transcriptional regulation, and reduce translation. However, most lysine acetylation data is observational, which means that we do not know when, how, and what specific acetylated residues affect protein function and bacterial physiology. For our model host, we will use a Pseudomonas putida strain that we previously engineered to convert lignocellulosic feedstocks into chemicals such as itaconic acid (ITA). With this strain, we use a dynamic two-stage bioproduction process in which ITA is produced during a non-growth associated production phase. Production is highest during growth stages when lysine acetylation is low in other organisms (early stationary phase) and stalls in conditions where acetylation is highest (late stationary phase). The switch from high to stalled ITA production is also correlated with an unexpected increase in acetate levels – the precursor to non-enzymatic lysine acetylation. As such, we predict that lysine acetylation plays a substantial role in regulating the metabolic pathways required for ITA production. We will develop a generalizable approach that combines high-throughput genetic screens and cutting-edge genome engineering with state-of-the-art proteomics, metabolomics, and genetic code expansion methods to identify and modulate lysine acetylation patterns in bacteria. Ultimately, these strategies aim to manipulate protein expression and acetylation patterns to enhance bioproduction phenotypes (e.g., sustained ITA production in late stationary phase).
60 APPLIED LIFE SCIENCES↗
Bioproduction, bioprotection, and biocontainment in multi-kingdom microbial systems with 3D spatial control
Engineered living materials (ELMs) are a class of hybrid materials that include engineered microbes encapsulated by a polymer matrix. The biotic and abiotic components define the ELMs design space and can be altered to improve performance and function. While current synthetic materials in the field display robust biocompatibility with both native and engineered living systems, we have a limited understanding of how to leverage three-dimensional (3D) form factors to spatially organize and control microbial dynamics within the material. Motivated by this knowledge gap, we employed extrusion-based 3D printing to fabricate multi-kingdom hydrogel constructs for the encapsulation of both single and multi-kingdom microbial systems. Core–shell cubic constructs enabled the spatial organization of a constitutive multi-kingdom system of levodopa (L-DOPA)-producing E. coli and betaxanthins (BXN)-producing S. cerevisiae. This spatial organization in 3D materials can introduce precise control over bioproduction, bioprotection, and biocontainment features that are critical to the efficacy of current ELMs. The relative spatial organization of the organisms, as well as the surface area-to-volume ratio were investigated to determine how these design elements impact microbial behavior (metabolite production, growth, expression, and cell distribution) over time. We demonstrated that F127-bis-urethane methacrylate (F127-BUM) core–shell geometries enable the hierarchical 3D printing of multi-kingdom constructs, offering customizable control over bioproduction, bioprotection, and biocontainment. With the optimization of these core–shell structures for continuous bioproduction, these ELMs could be deployed as compact and sustainable bioreactors in remote environments.
additive manufacturing↗
Acetate-based biological platforms: Bridging carbon dioxide utilization and high-value bioproduct production in oleaginous yeasts
Acetate is emerging as a promising two-carbon substrate in the circular bioeconomy, bridging the gap between single-carbon sources and high-value biofuels and bioproducts. This review examines the key pathways for acetate production, including the electrochemical reduction of carbon dioxide, syngas fermentation, and biological acetogenesis. It focuses on acetate metabolism in oleaginous yeasts, such as Yarrowia lipolytica and Rhodotorula toruloides, which efficiently convert acetate-derived acetyl-CoA units into diverse bioproducts such as lipids, fatty alcohols, triacetic acid lactone, and carotenoids. Recent advances in metabolic engineering, transcriptomics, and metabolic flux analysis have improved the understanding of acetate assimilation in these organisms, thereby increasing their potential for industrial applications. In addition, the feasibility of a biological gas-to-liquid platform that utilizes acetate as a central intermediate for scalable biomanufacturing is discussed. Integrating acetate utilization with sustainable production strategies offers a promising path to advance the bio-based economy. Using acetate as a versatile metabolic intermediate enables the conversion of industrial emissions into biofuels and bioproducts while avoiding the energetic and toxicity constraints associated with direct fermentation of gaseous substrates.
59 BASIC BIOLOGICAL SCIENCES↗