Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Engine”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Enhancing lipid production in plant cells through automated high-throughput genome engineering and phenotyping

Plant bioengineering is a time-consuming and labor-intensive process with no guarantee of achieving desired traits. Here, we present a fast, automated, scalable, high-throughput pipeline for plant bioengineering (FAST-PB) in maize (Zea mays) and Nicotiana benthamiana. FAST-PB enables genome editing and product characterization by integrating automated biofoundry engineering of callus and protoplast cells with single-cell matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). We first demonstrated that FAST-PB could streamline Golden Gate cloning, with the capacity to construct 96 vectors in parallel. Using FAST-PB in protoplasts, we found that PEG2050 increased transfection efficiency by over 45%. For proof-of-concept, we established a reporter-gene-free method for CRISPR editing and phenotyping via mutation of high chlorophyll fluorescence 136. We show that diverse lipids were enhanced up to 6-fold using CRISPR activation of lipid controlling genes. In callus cells, an automated transformation platform was employed to regenerate plants with enhanced lipid traits through introducing multigene cassettes. Lastly, FAST-PB enabled high-throughput single-cell lipid profiling by integrating MALDI-MS with the biofoundry, protoplast, and callus cells, differentiating engineered and unengineered cells using single-cell lipidomics. Furthermore, these innovations massively increase the throughput of synthetic biology, genome editing, and metabolic engineering and change what is possible using single-cell metabolomics in plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Evolutionary trajectory of transcription factors and selection of targets for metabolic engineering

Transcription factors (TFs) provide potentially powerful tools for plant metabolic engineering as they often control multiple genes in a metabolic pathway. However, selecting the best TF for a particular pathway has been challenging, and the selection often relies significantly on phylogenetic relationships. Here, we offer examples where evolutionary relationships have facilitated the selection of the suitable TFs, alongside situations where such relationships are misleading from the perspective of metabolic engineering. We argue that the evolutionary trajectory of a particular TF might be a better indicator than protein sequence homology alone in helping decide the best targets for plant metabolic engineering efforts. This article is part of the theme issue ‘The evolution of plant metabolism’.

Life Sciences & Biomedicine - Other Topics↗
DOE OSTI2025

Floquet Engineering of Interactions and Entanglement in Periodically Driven Rydberg Chains

Neutral atom arrays driven into Rydberg states constitute a promising approach for realizing programmable quantum systems. Enabled by strong interactions associated with Rydberg blockade, they allow for simulation of complex spin models and quantum dynamics. We introduce a new Floquet engineering technique for systems in the blockade regime that provides control over novel forms of interactions and entanglement dynamics in such systems. Our approach is based on time-dependent control of Rydberg laser detuning and leverages perturbations around periodic many-body trajectories as resources for operator spreading. These time-evolved operators are utilized as a basis for engineering interactions in the effective Hamiltonian describing the stroboscopic evolution. As an example, we show how our method can be used to engineer strong spin exchange, consistent with the blockade, in a one-dimensional chain, enabling the exploration of gapless Luttinger liquid phases. In addition, we demonstrate that combining gapless excitations with Rydberg blockade can lead to dynamic generation of large-scale multipartite entanglement. Experimental feasibility and possible generalizations are discussed.

Floquet systems↗
DOE OSTI2021

Photon-Number-Dependent Hamiltonian Engineering for Cavities

Cavity resonators are promising resources for quantum technology, while native nonlinear interactions for cavities are typically too weak to provide the level of quantum control required to deliver complex targeted operations. Here we investigate a scheme to engineer a target Hamiltonian for photonic cavities using ancilla qubits. By off resonantly driving dispersively coupled ancilla qubits, we develop an optimized approach to engineering an arbitrary photon-number-dependent Hamiltonian for the cavities while minimizing the operation errors. Here, the engineered Hamiltonian admits various applications including canceling unwanted cavity self-Kerr interactions, creating higher-order nonlinearities for quantum simulations, and designing quantum gates resilient to noise. Our scheme can be implemented with coupled microwave cavities and transmon qubits in superconducting circuit systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Degeneracy engineering for classical and quantum annealing: A case study of sparse linear regression in collider physics

Classical and quantum annealing are computing paradigms that have been proposed to solve a wide range of optimization problems. In this paper, we aim to enhance the performance of annealing algorithms by introducing the technique of degeneracy engineering, through which the relative degeneracy of the ground state is increased by modifying a subset of terms in the objective Hamiltonian. We illustrate this novel approach by applying it to the example of ℓ 0 -norm regularization for sparse linear regression, which is, in general, an NP-hard optimization problem. Specifically, we show how to cast ℓ 0 -norm regularization as a quadratic unconstrained binary optimization (QUBO) problem, suitable for implementation on annealing platforms. As a case study, we apply this QUBO formulation to energy flow polynomials in high-energy collider physics, finding that degeneracy engineering substantially improves the annealing performance. Furthermore, our results motivate the application of degeneracy engineering to a variety of regularized optimization problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2010

Application of protein engineering to enhance crystallizability and improve crystal properties

This article presents an overview of protein-engineering methods designed to enhance crystallizability and discusses a number of examples of their successful application. Until recently, protein crystallization has mostly been regarded as a stochastic event over which the investigator has little or no control. With the dramatic technological advances in synchrotron-radiation sources and detectors and the equally impressive progress in crystallographic software, including automated model building and validation, crystallization has increasingly become the rate-limiting step in X-ray diffraction studies of macromolecules. However, with the advent of recombinant methods it has also become possible to engineer target proteins and their complexes for higher propensity to form crystals with desirable X-ray diffraction qualities. As most proteins that are under investigation today are obtained by heterologous overexpression, these techniques hold the promise of becoming routine tools with the potential to transform classical crystallization screening into a more rational high-success-rate approach. This article presents an overview of protein-engineering methods designed to enhance crystallizability and discusses a number of examples of their successful application.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

A Twin Spool Engine Emulator for the Study of Power Exchange Idea

The More Electric Aircraft (MEA) engine, with electrical machines on both HP and LP shafts, makes it possible to transfer power electrically from one spool to another. Preliminary results have shown considerable improvement in turbofan performance in terms of fuel consumption, engine stability and compatible thrust with flight mission. In order to prove the concept of power exchange between shafts, it is essential to design a subscale system to emulate the more electric engine (MEE). This paper describes the layout of the experimental system to emulate the MEE to study the idea of power exchange between shafts through a single dc bus architecture.

Enalou, Hossein↗
DOE OSTI2014

The Hidden Job Requirements for a Software Engineer

In a world increasingly operated by computers, where innovation depends on software, the software engineer’s role is changing continuously and gaining new dimensions. In commercial software development as well as scientific research environments, the way software developers are perceived is changing, because they are more important to the business than ever before. Nowadays, their job requires skills extending beyond the regular job description posted by HR, and more is expected. To advance and thrive in their new roles, the software engineers must embrace change, and practice the themes of the new era (integration, collaboration and optimization). The challenges may be somehow intimidating for freshly graduated software engineers. Through this paper the authors hope to set them on a path for success, by helping them relinquish their fear of the unknown.

Marinovici, Maria C.↗
DOE OSTI2025

Evolution at the Edge: Real-Time Evolution for Neuromorphic Engine Control

Neuromorphic computing systems are attractive for real-time control at the edge because of their low power operation, real-time processing capabilities and their potential ability to do online learning. In this work, we describe an approach for performing real-time evolution of spiking neural networks for neuromorphic systems at the edge called Neuromorphic Optimization using Dynamic Evolutionary Systems or NODES. We apply this approach to real-time combustion engine control and develop an engine-specific hardware platform for NODES called FireBox. We demonstrate how the real-time evolution approach works in simulation and the performance of networks trained in simulation on the physical engine.

Maldonado Puente, Bryan [ORNL] (ORCID:000000033880↗
DOE OSTI2024

Plant‐produced SARS ‐ CoV ‐2 antibody engineered towards enhanced potency and in vivo efficacy

Summary Prevention of severe COVID‐19 disease by SARS‐CoV‐2 in high‐risk patients, such as immuno‐compromised individuals, can be achieved by administration of antibody prophylaxis, but producing antibodies can be costly. Plant expression platforms allow substantial lower production costs compared to traditional bio‐manufacturing platforms depending on mammalian cells in bioreactors. In this study, we describe the expression, production and purification of the originally human COVA2‐15 antibody in plants. Our plant‐produced mAbs demonstrated comparable neutralizing activity with COVA2‐15 produced in mammalian cells. Furthermore, they exhibited similar capacity to prevent SARS‐CoV‐2 infection in a hamster model. To further enhance these biosimilars, we performed three glyco‐ and protein engineering techniques. First, to increase antibody half‐life, we introduced YTE‐mutation in the Fc tail; second, optimization ofN‐linked glycosylation by the addition of a C‐terminal ER‐retention motif (HDEL), and finally; production of mAb in plant production lines lacking β‐1,2‐xylosyltransferase and α‐1,3‐fucosyltransferase activities (FX‐KO). These engineered biosimilars exhibited optimized glycosylation, enhanced phagocytosis and NK cell activation capacity compared to conventional plant‐produced S15 and M15 biosimilars, in some cases outperforming mammalian cell produced COVA2‐15. These engineered antibodies hold great potential for enhancingin vivoefficacy of mAb treatment against COVID‐19 and provide a platform for the development of antibodies against other emerging viruses in a cost‐effective manner.

Biotechnology & Applied Microbiology↗
DOE OSTI2020

NUMERICAL INVESTIGATION OF FUEL PROPERTY EFFECTS ON MIXED-MODE COMBUSTION IN A SPARK-IGNITION ENGINE

In the present study, mixed-mode combustion of an E30 fuel in a direct-injection spark-ignition engine is numerically investigated at a fuel-lean operating condition using multidimensional computational fluid dynamics (CFD). A fuel surrogate matching Research Octane Number (RON) and Motor Octane Number (MON) of E30 is first developed using neural network based non-linear regression model. To enable efficient 3D engine simulations, a 164-species skeletal reaction mechanism incorporating NO, chemistry is reducedfrom a detailed chemical kinetic model. A hybrid approach that incorporates the G-equation model for tracking turbulentflame front, and the multi-zone well-stirred reactor model for predicting auto-ignition in the end gas, is employed to account for turbulent combustion interactions in the engine cylinder. Predicted in-cylinder pressure and heat release rate traces agree well with experimental measurements. The proposed modelling approach also captures moderated cyclic variability. Two different types of combustion cycles, corresponding to purely deflagrative and mixed-mode combustion, are observed. In contrast to the purely deflagrative cycles, mixed-mode combustion cycles feature early flame propagation followed by end-gas auto-ignition, leading to two distinctive peaks in heat release rate traces. The positive correlation between mixed-mode combustion cycles and early flame propagation is well captured by simulations. With the validated numerical setup, effects of NOx chemistry on mixed-mode combustion predictions are investigated. NOx chemistry is found to promote auto-ignition through residual gas recirculation, while the deflagrative flame propagation phase remains largely unaffected. Local sensitivity analysis is then performed to understand effects of physical and chemical properties of the fuel, i.e., heat of evaporation (HoV) and laminar flame speed (S-L). An increased HoV tends to suppress end-gas auto-ignition due to increased vaporization cooling, while the impact of HoV on flame propagation is insignificant. In contrast, an increased SL is found to significantly promote both flame propagation and auto-ignition. The promoting effect of SL on auto-ignition is not a direct chemical effect; it is rather caused by an advancement of the combustion phasing, which increases compression heating of the end gas.

detailed chemical kinetics↗
DOE OSTI2014

WE-A-17A-04: Development of An Ultra-Fast Monte Carlo Dose Engine for High Dose Rate Brachytherapy

Purpose: Current clinical brachytherapy dose calculations are based on AAPM TG43 guidelines, which approximate the patient geometry as a large water phantom. This ignores heterogeneities and tends to overestimate skin dose. Although Monte Carlo (MC) dose calculations have been recognized as the most accurate method, its associated long computational time is a major bottleneck for routine clinical applications. This work aims to develop a GPU-based ultra-fast MC dose engine (gBMC) for HDR brachytherapy to provide clinical users with accurate sub-minute dose calculations. Methods: Standard photon transport with discrete events including: Compton scattering, Rayleigh scattering and Photoelectric effect, was implemented. Secondary electrons were transported under the continuous slowing down approximation. To reduce the GPU thread divergence, photons and electrons were separately transported. Transport of photons was grouped according to energy. The source model in gBMC can be either a phase-space file generated using Geant4 or a parameterized source model. This dose engine was validated against TG43 in a water phantom and against Geant4 calculations in heterogeneous patient geometries. Results: A phase space file was generated for the Varian VS2000 Ir-192 source. In a water phantom, the calculated radial dose function was within 0.6% of the TG43 calculations for radial distances from 1 cm to 20 cm. The anisotropy functions were within 1% for radial distances from 1 cm to 20 cm except for polar angles larger than 173°. Local point-dose differences were within 2%. In a Mammosite breast cancer case with 22 dwell locations, gBMC and Geant4 isodose lines compared well. The computation time was about 28 seconds using the phase-space file source and 20 seconds using the parameterized source to simulate 1 billion particles, yielding less than 1% statistical uncertainty. Conclusion: The gBMC dose engine makes it possible to use fast and accurate MC dose calculations for clinical work.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-112: An OpenCL-Based Cross-Platform Monte Carlo Dose Engine (oclMC) for Coupled Photon-Electron Transport

Purpose: Low computational efficiency of Monte Carlo (MC) dose calculation impedes its clinical applications. Although a number of MC dose packages have been developed over the past few years, enabling fast MC dose calculations, most of these packages were developed under NVidia’s CUDA environment. This limited their code portability to other platforms, hindering the introduction of GPU-based MC dose engines to clinical practice. To solve this problem, we developed a cross-platform fast MC dose engine named oclMC under OpenCL environment for external photon and electron radiotherapy. Methods: Coupled photon-electron simulation was implemented with standard analogue simulation scheme for photon transport and Class II condensed history scheme for electron transport. We tested the accuracy and efficiency of oclMC by comparing the doses calculated using oclMC and gDPM, a previously developed GPU-based MC code on NVidia GPU platform, for a 15MeV electron beam and a 6MV photon beam in a homogenous water phantom, a water-bone-lung-water slab phantom and a half-slab phantom. We also tested code portability of oclMC on different devices, including an NVidia GPU, two AMD GPUs and an Intel CPU. Results: Satisfactory agreements were observed in all photon and electron cases, with ∼0.48%–0.53% average dose differences at regions within 10% isodose line for electron beam cases and ∼0.15%–0.17% for photon beam cases. It took oclMC 3–4 sec to perform transport simulation for electron beam on NVidia Titan GPU and 35–51 sec for photon beam, both with ∼0.5% statistical uncertainty. The computation was 6%–17% slower than gDPM due to the differences in both physics model and development environment, which is considered not significant for clinical applications. In terms of code portability, gDPM only runs on NVidia GPUs, while oclMC successfully runs on all the tested devices. Conclusion: oclMC is an accurate and fast MC dose engine. Its high cross-platform portability makes it clinically attractive.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-620: Development of a Convolution/Superposition Dose Engine for CyberKnife System

Purpose: Current CyberKnife treatment planning system (TPS) provided two dose calculation algorithms: Ray-tracing and Monte Carlo. Ray-tracing algorithm is fast, but less accurate, and also can’t handle irregular fields since a multi-leaf collimator system was recently introduced to CyberKnife M6 system. Monte Carlo method has well-known accuracy, but the current version still takes a long time to finish dose calculations. The purpose of this paper is to develop a GPU-based fast C/S dose engine for CyberKnife system to achieve both accuracy and efficiency. Methods: The TERMA distribution from a poly-energetic source was calculated based on beam’s eye view coordinate system, which is GPU friendly and has linear complexity. The dose distribution was then computed by inversely collecting the energy depositions from all TERMA points along 192 collapsed-cone directions. EGSnrc user code was used to pre-calculate energy deposition kernels (EDKs) for a series of mono-energy photons The energy spectrum was reconstructed based on measured tissue maximum ratio (TMR) curve, the TERMA averaged cumulative kernels was then calculated. Beam hardening parameters and intensity profiles were optimized based on measurement data from CyberKnife system. Results: The difference between measured and calculated TMR are less than 1% for all collimators except in the build-up regions. The calculated profiles also showed good agreements with the measured doses within 1% except in the penumbra regions. The developed C/S dose engine was also used to evaluate four clinical CyberKnife treatment plans, the results showed a better dose calculation accuracy than Ray-tracing algorithm compared with Monte Carlo method for heterogeneous cases. For the dose calculation time, it takes about several seconds for one beam depends on collimator size and dose calculation grids. Conclusion: A GPU-based C/S dose engine has been developed for CyberKnife system, which was proven to be efficient and accurate for clinical purpose, and can be easily implemented in TPS.

60 APPLIED LIFE SCIENCES↗
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↗
DOE OSTI2017

Engineering Cyanobacterial Cell Morphology for Enhanced Recovery and Processing of Biomass

Cyanobacteria are emerging as alternative crop species for the production of fuels, chemicals, and biomass. Yet, the success of these microbes depends on the development of cost-effective technologies that permit scaled cultivation and cell harvesting. Here, we investigate the feasibility of engineering cell morphology to improve biomass recovery and decrease energetic costs associated with lysing cyanobacterial cells. Specifically, we modify the levels of Min system proteins in Synechococcus elongatus PCC 7942. The Min system has established functions in controlling cell division by regulating the assembly of FtsZ, a tubulin-like protein required for defining the bacterial division plane. We show that altering the expression of two FtsZ-regulatory proteins, MinC and Cdv3, enables control over cell morphology by disrupting FtsZ localization and cell division without preventing continued cell growth. By varying the expression of these proteins, we can tune the lengths of cyanobacterial cells across a broad dynamic range, anywhere from an ~20% increased length (relative to the wild type) to near-millimeter lengths. Highly elongated cells exhibit increased rates of sedimentation under low centrifugal forces or by gravity-assisted settling. Furthermore, hyperelongated cells are also more susceptible to lysis through the application of mild physical stress. Collectively, these results demonstrate a novel approach toward decreasing harvesting and processing costs associated with mass cyanobacterial cultivation by altering morphology at the cellular level. We show that the cell length of a model cyanobacterial species can be programmed by rationally manipulating the expression of protein factors that suppress cell division. In some instances, we can increase the size of these cells to near-millimeter lengths with this approach. The resulting elongated cells have favorable properties with regard to cell harvesting and lysis. Furthermore, cells treated in this manner continue to grow rapidly at time scales similar to those of uninduced controls. To our knowledge, this is the first reported example of engineering the cell morphology of cyanobacteria or algae to make them more compatible with downstream processing steps that present economic barriers to their use as alternative crop species. Therefore, our results are a promising proof-of-principle for the use of morphology engineering to increase the cost-effectiveness of the mass cultivation of cyanobacteria for various sustainability initiatives.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Metabolic Engineering of Actinobacillus succinogenes Provides Insights into Succinic Acid Biosynthesis

Actinobacillus succinogenes , a Gram-negative facultative anaerobe, exhibits the native capacity to convert pentose and hexose sugars to succinic acid (SA) with high yield as a tricarboxylic acid (TCA) cycle intermediate. In addition, A. succinogenes is capnophilic, incorporating CO 2 into SA, making this organism an ideal candidate host for conversion of lignocellulosic sugars and CO 2 to an emerging commodity bioproduct sourced from renewable feedstocks. In this work, we report the development of facile metabolic engineering capabilities in A. succinogenes , enabling examination of SA flux determinants via knockout of the primary competing pathways—namely, acetate and formate production—and overexpression of the key enzymes in the reductive branch of the TCA cycle leading to SA. Batch fermentation experiments with the wild-type and engineered strains using pentose-rich sugar streams demonstrate that the overexpression of the SA biosynthetic machinery (in particular, the enzyme malate dehydrogenase) enhances flux to SA. Additionally, removal of competitive carbon pathways leads to higher-purity SA but also triggers the generation of by-products not previously described from this organism (e.g., lactic acid). The resultant engineered strains also lend insight into energetic and redox balance and elucidate mechanisms governing organic acid biosynthesis in this important natural SA-producing microbe. IMPORTANCE Succinic acid production from lignocellulosic residues is a potential route for enhancing the economic feasibility of modern biorefineries. Here, we employ facile genetic tools to systematically manipulate competing acid production pathways and overexpress the succinic acid-producing machinery in Actinobacillus succinogenes . Furthermore, the resulting strains are evaluated via fermentation on relevant pentose-rich sugar streams representative of those from corn stover. Altogether, this work demonstrates genetic modifications that can lead to succinic acid production improvements and identifies key flux determinants and new bottlenecks and energetic needs when removing by-product pathways in A. succinogenes metabolism.

09 BIOMASS FUELS↗
DOE OSTI2024

Metabolic engineering of Caldicellulosiruptor bescii for 2,3-butanediol production from unpretreated lignocellulosic biomass and metabolic strategies for improving yields and titers

ABSTRACT The platform chemical 2,3-butanediol (2,3-BDO) is used to derive products, such as 1,3-butadiene and methyl ethyl ketone, for the chemical and fuel production industries. Efficient microbial 2,3-BDO production at industrial scales has not been achieved yet for various reasons, including product inhibition to host organisms, mixed stereospecificity in product formation, and dependence on expensive substrates (i.e., glucose). In this study, we explore engineering of a 2,3-BDO pathway inCaldicellulosiruptor bescii, an extremely thermophilic (optimal growth temperature = 78°C) and anaerobic bacterium that can break down crystalline cellulose and hemicellulose into fermentable C 5 and C 6 sugars. In addition, C. besciigrows on unpretreated plant biomass, such as switchgrass. Biosynthesis of 2,3-BDO involves three steps: two molecules of pyruvate are condensed into acetolactate; acetolactate is decarboxylated to acetoin, and finally, acetoin is reduced to 2,3-BDO.C. besciinatively produces acetoin; therefore, in order to complete the 2,3-BDO biosynthetic pathway,C. besciiwas engineered to produce a secondary alcohol dehydrogenase (sADH) to catalyze the final step. Two previously characterized, thermostable sADH enzymes with high affinity for acetoin, one from a bacterium and one from an archaeon, were tested independently. When either sADH was present inC. bescii,the recombinant strains were able to produce up to 2.5-mM 2,3-BDO from crystalline cellulose and xylan and 0.2-mM 2,3-BDO directly from unpretreated switchgrass. This serves as the basis for higher yields and productivities, and to this end, limiting factors and potential genetic targets for further optimization were assessed using the genome-scale metabolic model ofC. bescii. IMPORTANCE Lignocellulosic plant biomass as the substrate for microbial synthesis of 2,3-butanediol is one of the major keys toward cost-effective bio-based production of this chemical at an industrial scale. However, deconstruction of biomass to release the sugars for microbial growth currently requires expensive thermochemical and enzymatic pretreatments. In this study, the thermo-cellulolytic bacteriumCaldicellulosiruptor besciiwas successfully engineered to produce 2,3-butanediol from cellulose, xylan, and directly from unpretreated switchgrass. Genome-scale metabolic modeling ofC. besciiwas applied to adjust carbon and redox fluxes to maximize productivity of 2,3-butanediol, thereby revealing bottlenecks that require genetic modifications.

Biotechnology & Applied Microbiology↗