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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Preliminary Design of a Downstream Processing System for Protein Production in Space

Biomanufacturing is a promising technology to convert in situ resources into essential products including enzymes, therapeutics, biopolymers and other chemicals required to support deep-space missions that may not be easily supplied or produced by alternative means. In addition to the biomass production operations, vital down-stream steps including biomass harvesting/concentration, cell lysis, protein capture and purification are needed to produce an application-ready product. Commercially available terrestrial processes commonly require complex, heavy equipment and highly trained operators, which are not practical in deep space environments. In this work, we aim to identify approaches required to produce an intracellular, His-tagged recombinant enzyme using E. coli at 1 L production scales within the constraints of a deep-space mission as a model use-case scenario. Based on extensive literature review and commercially available products, we identified candidate technologies and products that could be integrated for deep space biomanufacturing. Different preliminary designs were then compared in terms of total system impacts on up-mass, processing time, and consumables required. Our analysis indicated that a biomass concentrator would significantly reduce the processing time and consumables required for the overall system without a large increase in the total mass. We also identified viable technologies for other steps such as cell lysis and protein purification. Predictions from our trade study will be validated in the laboratory by testing the most promising products with the results used to optimize the design. This research will help transfer technology that is well developed on Earth to a space-ready format to produce biological products from a wide variety of microorganisms that can support deep-space missions.

Biomanufacturing↗
DOE OSTI2024

Model acetylcholinesterase‐Fc fusion glycoprotein biotechnology system for the manufacture of an organophosphorus toxicant bioscavenging countermeasure

Abstract Organophosphate (OP) toxicants remain an active threat to public health and to warfighters in the military. Current countermeasures require near immediate administration following OP exposure and are reported to have controversial efficacies. Acetylcholinesterase (AChE) fused to the human immunoglobulin 1 (IgG1) Fc domain (AChE‐Fc) is a potential bioscavenger for OP toxicants, but a reproducible AChE‐Fc biomanufacturing strategy remains elusive. This report is the first to establish a comprehensive laboratory‐scale bioprocessing strategy that can reproducibly produce AChE‐Fc and AChE(W86A)‐Fc which is a mutated AChE protein with reduced enzymatic activity. Characterization studies revealed that AChE‐Fc and AChE(W86A)‐Fc are N ‐glycosylated dimeric fusion glycoproteins but only AChE‐Fc had the capability to bind to paraoxon (a model OP). This AChE‐Fc fusion glycoprotein bioprocessing strategy can be leveraged during industrial biomanufacturing development, while the research‐grade AChE‐Fc proteins can be used to determine the potential clinical relevance of the countermeasure against OP toxicants.

Biel, Thomas G.↗
DOE OSTI2023

Light‐Driven Metabolic Pathways in Non‐Photosynthetic Biohybrid Bacteria

Biomanufacturing via microorganisms relies on carbon substrates for molecular feedstocks and a source of energy to carry out enzymatic reactions. This creates metabolic bottlenecks and lowers the efficiency for substrate conversion. Nanoparticle biohybridization with proteins and whole cell surfaces can bypass the need for redox cofactor regeneration for improved secondary metabolite production in a non-specific manner. Here we propose using nanobiohybrid organisms (Nanorgs), intracellular protein-nanoparticle hybrids formed through the spontaneous coupling of core-shell quantum dots (QDs) with histidine-tagged enzymes in non-photosynthetic bacteria, for light-mediated control of bacterial metabolism. Furthermore, this proved to eliminate metabolic constrictions and replace glucose with light as the source of energy in Escherichia coli, with an increase in growth by 1.7-fold in 75 % reduced nutrient media. Metabolomic tracking through carbon isotope labeling confirmed flux shunting through targeted pathways, with accumulation of metabolites downstream of respective targets. Finally, application of Nanorgs with the Ehrlich pathway improved isobutanol titers/yield by 3.9-fold in 75 % less sugar from E. coli strains with no genetic alterations. These results demonstrate the promise of Nanorgs for metabolic engineering and low-cost biomanufacturing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Advances in genome-scale metabolic models of industrially important fungi

Many fungal species have been used in industrial production for biofuels and bioproducts. Developing strains with better performance in biomanufacturing requires systematic understanding of cellular metabolism. Genome-scale metabolic models (GEMs) offer a comprehensive view of interconnected pathways and a mathematical framework for downstream analysis. Recently, GEMs have been developed or updated in several industrially important fungi. Some of them incorporate enzyme constraints, enabling improved predictions of cell states and proteome allocation. In this report we provide an overview of these newly developed GEMs and computational methods that facilitate construction of enzyme-constrained GEMs and utilize flux predictions from GEMs. Furthermore, we highlight the pivotal roles of these GEMs in iterative design-build-test- learn cycles, ultimately advancing the field of fungal biomanufacturing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Author Correction: Building a global alliance of biofoundries

The original version of this Comment contained errors in the legend of Figure 2, in which the locations of the fifteenth and sixteenth GBA members were incorrectly given as '(15) Australian Genome Foundry, Macquarie University; (16) Australian Foundry for Advanced Biomanufacturing, University of Queensland'. The correct version replaces this with '(15) Australian Foundry for Advanced Biomanufacturing (AusFAB), University of Queensland and (16) Australian Genome Foundry, Macquarie University'. This has been corrected in both the PDF and HTML versions of the Comment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Merging the computational design of chimeric type I polyketide synthases with enzymatic pathways for chemical biosynthesis

Synthetic biology offers the promise of manufacturing chemicals more sustainably than petrochemistry. Yet, both the rate at which biomanufacturing can synthesize these molecules and the net chemical accessible space are limited by existing pathway discovery methods, which can often rely on arduous literature searches. Here, we introduce BioPKS pipeline, an automated retrobiosynthesis tool combining multifunctional type I polyketide synthases (PKSs) and monofunctional enzymes via two complementary tools: RetroTide and DORAnet. Monofunctional enzymes are valuable for carefully decorating a substrate’s carbon backbone while PKSs are unique in their ability to iteratively catalyze carbon-carbon bond formation reactions, thereby expanding carbon backbones in a predictable fashion. We evaluate the performance of BioPKS pipeline using a previously reported set of 155 biomanufacturing candidates, achieving exact synthetic designs for 93 compounds and generating chemically similar pathways for most remaining targets. Furthermore, BioPKS pipeline can propose pathways for the complex therapeutic natural products cryptofolione and basidalin.

Chainani, Yash↗
DOE OSTI2026

Expanding the genetic toolset: using serine recombinases to integrate riboregulatory elements into industrially relevant microbial chassis

To realize the full potential of biomanufacturing, the breadth of industrial microbes used to consume diverse feedstock and generate bioproducts needs to expand. As such, portable tools are required that can be used by multiple hosts for straightforward genomic manipulation and precise gene expression. Here, we demonstrate the co-utilization of two synthetic biology tools to achieve these goals: cis-repressors (CRs) and serine recombinase-assisted genome engineering (SAGE). CRs are small, noncoding RNAs that are placed upstream of the target gene to modulate bacterial translation rates at varying, discrete levels. SAGE uses site-specific serine recombinases to catalyze highly efficient, unidirectional insertion of DNA into the chromosome of diverse organisms. We used SAGE to integrate a suite of CRs into the industrially relevant hosts Pseudomonas putida, Corynebacterium glutamicum, and Cupriavidus necator. Using a fluorescent reporter as a readout of CR functionality, we found that CR performance across these backgrounds was similar—providing a range of translational repression up to 100-fold. Overall, these results demonstrate the high portability of CRs across bacterial genetic backgrounds, which ideally can be used in future microbial engineering efforts pertinent to biomanufacturing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Metatranscriptomic and Thermodynamic Insights into Medium-Chain Fatty Acid Production Using an Anaerobic Microbiome

Mixed communities of microbes play important roles in health, the environment, agriculture, and biotechnology. While tapping the combined activities of organisms within microbiomes may allow the utilization of a wider range of substrates in preference to the use of pure cultures for biomanufacturing, harnessing the metabolism of these mixed cultures remains a major challenge. Here, we predicted metabolic functions of bacteria in a microbiome that produces medium-chain fatty acids from a renewable feedstock. Our findings lay the foundation for efforts to begin addressing how to engineer and control microbiomes for improved biomanufacturing, how to build synthetic mixtures of microbes that produce valuable chemicals from renewable resources, and how to better understand the microbial communities that contribute to health, agriculture, and the environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Host Onboarding Tool (HObT) v1.0.0

The Host OnBoarding Tool (Hobt) is a publicly accessible, web-based software designed to organize and share information about microbial hosts under development at the Agile BioFoundry (ABF). It streamlines the assessment, tracking, and sharing of information related to microbial host development and provides a centralized platform where users can rapidly evaluate hosts' readiness for various bio processes. HObT leverages the Tier System, a standardized host development framework that organizes and assesses microbial hosts based on their readiness for biomanufacturing. Each tier outlines key targets—including genetic tools, growth conditions, omics data, and predictive models—needed to transform new or emerging microbes into established production platforms. By applying clear criteria for advancement, the Tier System helps users quickly evaluate each organism's current development status, identify gaps in available knowledge or tools, and prioritize future strain improvement efforts. Through its user-friendly interface, HObT encourages contributions of new data and insights from researchers, fostering collaboration and accelerating host development. By providing structured guidance for microbial strain advancement, HObT and the Tier System support more systematic, rapid, and cost-effective development of non-traditional microbial hosts, ultimately enhancing the efficiency and impact of biomanufacturing research and applications.

Plahar, Hector [Lawrence Berkeley National Laborat↗
DOE OSTI2026

Data for 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.

Bioproducts↗
DOE OSTI2022

Artificial Intelligence and Machine Learning for Bioenergy Research: Opportunities and Challenges

The integration of artificial intelligence and machine learning (AI/ML) with automated experimentation, genomics, biosystems design, and bioprocessing technologies is poised to revolutionize scientific investigation and, particularly, bioenergy research. To identify the opportunities and challenges in this emerging research area, the U.S. Department of Energy’s (DOE) Biological and Environmental Research program (BER) and Bioenergy Technologies Office (BETO) held a joint virtual workshop on AI/ML for Bioenergy Research (AMBER) on August 23–25, 2022. These interests have since been amplified in a September 2022 Executive Order, “Advancing Biotechnology and Biomanufacturing Innovation for a Sustainable, Safe, and Secure U.S. Bioeconomy,” to promote a whole-of government approach to biotechnology development (White House 2022). Approximately 50 scientists with various backgrounds and expertise from academia, industry, and DOE national laboratories met to discuss the opportunities and challenges of AI/ML for bioenergy research. Workshop participants were tasked with assessing the potential for AI/ML and laboratory automation to advance biological understanding and engineering in general. They particularly examined how integrating AI/ML tools with laboratory automation could accelerate biosystems design and optimize biomanufacturing. Discussions included the data and computational infrastructure needed to augment biosystems design applications and the expertise and workforce development efforts urgently required to shift integrated systems toward bioenergy research more broadly. Participants discussed many existing and future applications of AI/ML for biosystems design ranging from enzymes to plants and microbes, microbiomes, and bioprocess development. They also identified three key categories of scientific and technical opportunities and challenges: high-quality data, AI/ML algorithms, and laboratory automation. Several main takeaways emerged from the workshop: 1. Numerous AI/ML and automated experimentation applications exist for a variety of DOE mission needs in energy and the environment; 2. Exemplary research grand challenges for which AI/ML could provide solutions include: building microbes and microbial communities to specifications, developing closed-loop autonomous design and control for biosystems design, and advancing scale-up and automation; 3. Lack of sufficient high-quality, annotated data hinders the development of AI/ML applications; 4. New and improved AI/ML tools are needed, particularly those meeting the specific needs of the BER and BETO research communities; 5. Trade-offs in performance, cost, and reliability exist between deploying commercially available versus building custom-developed instrumentation and software for automated or autonomous experimentation; translation of manual to automated or autonomous methods is often a nontrivial endeavor; 6. Training a new generation of young scientists who can develop and apply AI/ML tools is needed to solve long-standing scientific challenges in bioenergy research. The integration of AI/ML tools and automated experimentation represents a new data-driven research paradigm complementary to the traditional hypothesis-driven research paradigm. This paradigm accelerates design and optimization of biological systems and processes for a variety of DOE mission needs in energy and the environment. The AMBER workshop broadly explored the potential of this new paradigm for bioenergy research, of particular interest to BER and BETO, and identified key challenges and opportunities that DOE can address in the coming years by leveraging its unique capabilities and resources.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Assessment of the bioconversion potential of minimally processed seaweed by halophilic yeasts

Building an advanced economy using biomanufacturing requires robust sources of carbon for converting into chemicals and products. Macroalgae hold significant potential due to their fast growth rates, lack of freshwater usage, and lack of land usage. To be used as a common feedstock, there are two primary challenges that need to be addressed: 1) unusual chemical composition and 2) high salinity. A solution to both issues is to use a resilient, salt-loving organism with a broad consumption profile for the conversion of macroalgae. Here we evaluate the ability of the oleaginous yeast Rhodosporidium toruloides to grow in wild macroalgae-derived feedstocks and identify a conversion process that is functional for two species of Sargassum collected from the Caribbean using R. toruloides that does not require washing of the input seaweed material. Together this demonstrates a future avenue of work that minimizes freshwater usage for incorporating macroalgae as a biomanufacturing carbon source.

09 BIOMASS FUELS↗
DOE OSTI2026

Optimizing enzymes for plastic upcycling using machine learning design and high throughput experiments

Plastic use is ubiquitous in the modern world, and polyethylene terephthalate (PET) is one of the most abundantly produced plastics (and the most highly produced polyester), with ~65 million metric tons manufactured annually. To the consumer, PET is likely most recognizable as the plastic used to make beverage bottles. Like many plastics, traditional mechanical or chemical means of PET deconstruction and upcycling are costly and inefficient. Because of these challenges, recycled plastic is generally of lower quality and is more expensive to produce than virgin plastic derived from petroleum. Ultimately, this results in most plastic ending up as waste. We view plastic waste as an underutilized resource which, with the development of more efficient and high-quality recycling processes, could (1) generate significant economic value while (2) decreasing petroleum usage and greenhouse gas emissions, as well as (3) minimizing its negative environmental and health impacts. Biocatalytic recycling, or biomanufacturing the basic building blocks of new plastic from plastic waste, is a promising approach to plastic reuse that complements existing recycling technologies. Recently, biological enzymes capable of breaking down PET have garnered significant attention as an attractive means of dealing with the plastic problem. These enzymes are currently undergoing pilot studies for implementation in industrial-scale enzyme-based recycling. However, there are significant limitations to current enzymes, including the need to perform costly pre-processing of the plastic waste before the enzymes are able to work. Further optimization of these enzymes is necessary to make these technologies competitive, and ultimately incentivise industry-wide adoption of this biology-based green recycling technology. n this work we demonstrate a means to design and generate performant biological enzymes, capable of efficiently deconstructing plastic waste. Specifically, we applied recent advances in artificial intelligence, machine learning, and statistical analysis to design new versions and discover natural enzymes capable of breaking down PET. We focused on optimizing key properties that are important for industrial-scale enzymatic recycling such as pH and thermotolerance. Normal testing of enzymatic plastic-deconstruction is extremely labor intensive and so through this work we also developed a robotic-assisted experimental pipeline capable of characterizing thousands of candidate enzymes. The results of this iterative, AI-guided, multi-discipline approach have led to increases in enzymatic breakdown of over 150X over starting enzymes. This work supports the rapidly developing and transformative field of biocatalytic solutions to environmental problems beyond the discovery and predictive understanding of enzymes for polymer recycling, and has wide implications for tackling numerous energy problems such as carbon capture and fixation (e.g., engineering carbon monoxide dehydrogenase and the rubisco-pathway), biomining (e.g., design of lanthanide-binding proteins) and biomanufacturing (e.g., lignin-deconstruction enzymes).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Bioreactor Optimization through Multi-Phase Flow Models (CRADA Final Report)

Chemical manufacturing uses 29% of energy in the United States and produces 925 million metric tons of CO2 annually. Biomanufacturing offers the potential to leverage America’s rich agricultural resources to produce critical chemicals such as lubricants, pharmaceutical precursors, and components of energetic materials that today are sourced extensively from overseas. The bioreactors used in biomanufacturing applications, such as one developed by Capra Biosciences, involve multiphase flow of biofilm-coated solid support particles that are continuously circulated in a fluidized state within the reactor along with a constant supply of oxygen via an aeration mechanism. In this project, Capra Biosciences and LBNL developed a multiscale modeling framework to simulate the multiphase flows of solid particles in a liquid-gas bubble mixture that occurs in the bioreactor using the current MFIX-Exa software, an opensource multiphase flow solver developed and maintained at LBNL and NETL. By leveraging HPC capabilities, this high-fidelity multiscale model was used to inform design decisions for bioreactor architecture to make them operationally efficient.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Integration of proteomics and metabolomics into the Design, Build, Test, Learn cycle to improve 3-hydroxypropionic acid production in Aspergillus pseudoterreus

Biological engineering of microorganisms to produce value-added chemicals is a promising route to sustainable manufacturing. However, overproduction of metabolic intermediates at high titer, rate, and yield from inexpensive substrates is challenging in non-model systems where limited information is available regarding metabolic flux and its control in production conditions. Integrated multi-omic analyses of engineered strains offers an in-depth look at metabolites and proteins directly involved in growth and production of target and non-target bioproducts. Here we applied multi-omic analyses to overproduction of the polymer precursor 3-hydroxypropionic acid (3HP) in the filamentous fungus Aspergillus pseudoterreus. A synthetic pathway consisting of aspartate decarboxylase, beta-alanine pyruvate transaminase, and 3HP dehydrogenase was designed and built for A. pseudoterreus. Strains with single- and multi-copy integration events were isolated and multi-omics analysis consisting of intracellular and extracellular metabolomics and targeted and global proteomics was used to interrogate the strains in shake-flask and bioreactor conditions. Production of a variety of co-products (organic acids and glycerol) and oxidative degradation of 3HP were identified as metabolic pathways competing with 3HP production. Intracellular accumulation of nitrogen as 2,4-diaminobutanoate was identified as an off-target nitrogen sink that may also limit flux through the engineered 3HP pathway. Elimination of the high-expression oxidative 3HP degradation pathway by deletion of a putative malonate semialdehyde dehydrogenase improved the yield of 3HP by 3.4× after 10 days in shake-flask culture. This is the first report of 3HP production in a filamentous fungus amenable to industrial scale biomanufacturing of organic acids at high titer and low pH.

Pomraning, Kyle R.↗
DOE OSTI2021

Omics-Driven Biotechnology for Industrial Applications

Biomanufacturing is a key component of biotechnology that uses biological systems to produce bioproducts of commercial relevance, which are of great interest to the energy, material, pharmaceutical, food, and agriculture industries. Biotechnology-based approaches, such as synthetic biology and metabolic engineering are heavily reliant on “omics” driven systems biology to characterize and understand metabolic networks. Knowledge gained from systems biology experiments aid the development of synthetic biology tools and the advancement of metabolic engineering studies toward establishing robust industrial biomanufacturing platforms. In this review, we discuss recent advances in “omics” technologies, compare the pros and cons of the different “omics” technologies, and discuss the necessary requirements for carrying out multi-omics experiments. We highlight the influence of “omics” technologies on the production of biofuels and bioproducts by metabolic engineering. Finally, we discuss the application of “omics” technologies to agricultural and food biotechnology, and review the impact of “omics” on current COVID-19 research.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

BioNutrients-2: Improvements to the BioNutrients-1 Nutrient Production System

The BioNutrients (BN) project aims to develop an on-demand nutrient production system capable of rapid and safe delivery of multiple nutrients in a single-use production pack for long-duration missions. The general concept of this system will be to develop an edible engineered microorganism capable of surviving during long-term storage, revival and growth of that microorganism for product production, and delivery of precise quantities of nutrients for human consumption. BN-1 is a five-year flight project currently on the International Space Station (ISS). It is testing the long-term storage of various microorganisms for the biomanufacturing of space relevant compounds and to validate the performance of the first generation (Gen-1) of production packs. The BN-2 project is a continuation of the BN-1 flight project and intends to expand the projects overall scope by introducing novel products, broadening the range of microbial food sources, and improving previously designed hardware from the BN-1 project. We are in the process of optimizing our platform biomanufacturing technology for in situ production of yogurt and kefir on the ISS. BN-2 will test the efficacy of this technology for future delivery of probiotic organisms which can be engineered to produce additional nutritional supplements (consumption by the crew is not planned in this project). Furthermore, to improve the feasibility of this technology for mission use we have transitioned from a hard-shell pack to a Gen-2, fluorinated ethylene propylene (FEP) bag. The single-use FEP bioreactor will facilitate growth of known organisms and ensure a contaminant free environment, while reducing mass and volume. These bioreactors will be employed for production of additional space relevant products in the BN-2 project. On-orbit testing of Gen-2 production packs will be necessary for future iterations, in order to optimize bag design and product production for eventual flight use by the crew.

BioNutrients↗
NASA NTRSDate not supplied

BioNutrients-2: Improvements to the BioNutrients-1 Nutrient Production System

The BioNutrients (BN) project aims to develop an on-demand biological production system capable of rapid and safe delivery of multiple nutrients in single-use production packs for long-duration missions. The general concept of this system is to develop edible engineered microorganisms that produce nutrients for human consumption following long-term storage, revival, and growth. BN-1 is a five-year flight project currently on the International Space Station (ISS). It is testing the long-term storage of various microorganisms for the biomanufacturing of space-relevant compounds and validating the performance of the first generation of production packs. The BN-2 project expands the BN-1 flight project scope by introducing novel products, broadening the range of microbial food sources, and improving upon production pack hardware. We are optimizing the biomanufacturing platform for in situ production of yogurt and kefir on the ISS. BN-2 also will test engineered microorganisms, including a probiotic strain, to produce carotenoids or follistatin. To improve the feasibility of this technology for mission use, we transitioned from a hard-shell pack to a second-generation fluorinated ethylene propylene (FEP) bag. The single-use FEP bioreactor facilitates growth of target organisms in a contaminant free environment, while reducing mass and volume compared to the BN-1 hardware. These bioreactors will be employed for production of additional space-relevant products in the BN-2 project. On-orbit testing of FEP production packs will enable optimization of the platform for eventual flight use by the crew.

Natalie Ball↗