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With climate change concerns deepening, CO₂ fixation pathways to produce value-added chemicals are currently of interest. In this work, synthetic biology and machine learning help developing such a pathway across modules that have been tested in vivo in Escherichia coli for the production of acetyl coenzyme A.

¹³C metabolic flux analysis is a powerful tool for metabolism characterization in metabolic engineering and synthetic biology. However, the widespread adoption of this tool is hindered by limited software availability and computational efficiency. Currently, the most widely accepted ¹³C-flux tools, such as INCA and 13CFLUX2, are developed in a closed-source environment. While several open-source packages or software are available, they are either computationally inefficient or only suitable for flux estimation at isotopic steady state. To address the need for a time-efficient computational tool for the more complicated flux analysis at an isotopically nonstationary state, especially for understanding the single-carbon substratemore » metabolism, we present FreeFlux. FreeFlux is an open-source Python package that performs labeling pattern simulation and flux analysis at both isotopic steady state and transient state, enabling a more comprehensive analysis of cellular metabolism. FreeFlux provides a set of interfaces to manipulate the objects abstracted from a labeling experiment and computational process, making it easy to integrate into other programs or pipelines. The flux estimation by FreeFlux is fast and reliable, and its validity has been confirmed by comparison with results from other computational tools using both synthetic and experimental data. FreeFlux is freely available at https://github.com/Chaowu88/freeflux with a detailed online tutorial and documentation provided at https://freeflux.readthedocs.io/en/latest/index.html.« less

Semiconductor-based biointerfaces are typically established either on the surface of the plasma membrane or within the cytoplasm. In Gram-negative bacteria, the periplasmic space, characterized by its confinement and the presence of numerous enzymes and peptidoglycans, offers additional opportunities for biomineralization, allowing for nongenetic modulation interfaces. We demonstrate semiconductor nanocluster precipitation containing single- and multiple-metal elements within the periplasm, as observed through various electron- and x-ray-based imaging techniques. The periplasmic semiconductors are metastable and display defect-dominant fluorescent properties. Unexpectedly, the defect-rich (i.e., the low-grade) semiconductor nanoclusters produced in situ can still increase adenosine triphosphate levels and malate production when coupled withmore » photosensitization. We expand the sustainability levels of the biohybrid system to include reducing heavy metals at the primary level, building living bioreactors at the secondary level, and creating semi-artificial photosynthesis at the tertiary level. The biomineralization-enabled periplasmic biohybrids have the potential to serve as defect-tolerant platforms for diverse sustainable applications.« less

¹³C metabolic flux analysis (MFA) has emerged as a powerful tool for synthetic biology. This optimization-based approach suffers long computation time and unstable solutions depending on the initial guess. Here, we develop a machine-learning-based framework for ¹³C fluxomics. Specifically, training and test data sets are generated by metabolic network decomposition and flux sampling, in which flux ratios at metabolic nodes and simulated labeling patterns of metabolites are used as training targets and features, respectively. To improve prediction accuracy and simplify the model, automated processes are developed for flux ratio selection based on solvability and feature screening based on importance. Wemore » found that predictive performance can be significantly improved using both amino acids and central carbon metabolites in comparison with amino acids alone. Together with measured external fluxes, the predicted flux ratios determine the mass balance system, yielding global flux distributions. This approach is validated by flux estimation using both simulated and experimental data in comparison with canonical ¹³C MFA. The approach represents a reliable fluxomics method readily applicable to high-throughput metabolic phenotyping, which highlights the advances of intelligent learning algorithms in synthetic biology, specifically in the Test and Learn stage of the Design-Build-Test-Learn cycle.« less

Nature's biocatalytic processes are driven by photosynthesis, whereby photosystems I and II are connected in series for light-stimulated generation of fuel products or electricity. Externally supplying electricity directly to the photosynthetic electron transfer chain (PETC) has numerous potential benefits, although strategies for achieving this goal have remained elusive. Here we report an integrated photo-electrochemical architecture which shuttles electrons directly to PETC in living cyanobacteria. The cathode of this architecture electrochemically interfaces with cyanobacterial cells that have a lack of photosystem II activity and cannot perform photosynthesis independently. Illumination of the cathode channels electrons from an external circuit to intracellular PETCmore » through photosystem I, ultimately fueling cyanobacterial conversion of CO₂ into acetate. We observed acetate formation when supplying both illumination and exogenous electrons under intermittent conditions (e.g., in a 30 s supply plus 30 min interval condition of both light and exogenous electrons). The energy conversion efficiency for acetate production under programmed intermittent LED illumination (400–700 nm) and exogenous electron supply reached ca. 9%, when taking into account the number of photons and electrons received by the biotic system, and ca. 3% for total photons and electrons supplied to the cyanobacteria. This approach is applicable for generating various CO₂ reduction products by using engineered cyanobacteria, one of which has enabled electrophototrophic production of ethylene, a broadly used hydrocarbon in the chemical industry. The resulting bio-electrochemical hybrid has the potential to produce fuel chemicals with numerous potential advantages over standalone natural and artificial photosynthetic approaches.« less

The development of an sustainable economy calls for improved energy utilization and storage technologies. Although battery- and carbon-based routes have gained tremendous attention, nitrogen-based routes have rarely been exploited so far. Guanidine (CH₅N₃) which contains 71.1% nitrogen by mass is an exemplary chemical to explore the nitrogen-based routes of energy utilization and storage. Guanidine has a variety of applications including its use as a slow-release fertilizer, a propellant, or as a precursor to pharmaceuticals and antimicrobial polymers. The conventional chemical synthesis of guanidine through the Frank–Caro process is energy-intensive, consumes fossil fuels, and is detrimental to the environment. Herein, amore » de novo guanidine biosynthesis (GUB) cycle is proposed with CO₂ and nitrate/ammonium as the carbon and nitrogen sources, respectively. The ATP and NAD(P)H needed to drive the GUB cycle are generated via photosynthesis in an engineered cyanobacterium Synechocystis sp. PCC 6803 expressing an ethylene-forming enzyme (EFE). Up to 586.5 mg L^-1 (9.9 mM) guanidine was produced after seven days of photoautotrophic cultivation, with an average productivity of 83.8 mg L^-1 day^-1. In addition, guanidine was directly biosynthesized from CO₂, N₂ and H₂O in an engineered N₂-fixing cyanobacterium Anabaena sp. PCC 7120 expressing the EFE. This work demonstrates the first biological conversion of renewable solar energy into chemical energy stored in the nitrogen-rich compound guanidine, which could shed light on harnessing the biological nitrogen metabolism for energy utilization and storage.« less

Mitigation of a bottleneck significantly improved ( R )-3HB productivity, and metabolic flux analysis delineated dramatic metabolic flux changes in cyanobacterium Synechocystis .

Hydrolysis of plant biomass generates a mixture of simple sugars that is particularly rich in glucose and xylose. Fermentation of the released sugars emits CO₂ as byproduct due to metabolic inefficiencies. Therefore, the ability of a microbe to simultaneously convert biomass sugars and photosynthetically fix CO₂ into target products is very desirable. In this work, the cyanobacterium, Synechocystis 6803, was engineered to grow on xylose in addition to glucose. Both the xylA (xylose isomerase) and xylB (xylulokinase) genes from Escherichia coli were required to confer xylose utilization, but a xylose-specific transporter was not required. Introducing xylAB into an ethylene-producing strainmore » increased the rate of ethylene production in the presence of xylose. Additionally, introduction of xylAB into a glycogen-synthesis mutant enhanced production of keto acids. Moreover, isotopic tracer studies found that nearly half of the carbon in the excreted keto acids was derived from the engineered xylose metabolism, while the remainder was derived from CO₂ fixation.« less