A Comprehensive Modeling Analysis of Formate-Mediated Microbial Electrosynthesis*

Seven critical challenges in synthetic one-carbon assimilation and their potential solutions

Synthetic C1 assimilation holds the promise of facilitating carbon capture while mitigating greenhouse gas emissions, yet practical implementation in microbial hosts remains relatively limited. Despite substantial progress in pathway design and prototyping, most efforts stay at the proof-of-concept stage, with frequent failures observed even under in vitro conditions. This review identifies seven major barriers constraining the deployment of synthetic C1 metabolism in microorganisms and proposes targeted strategies for overcoming these issues. A primary limitation is the low catalytic activity of carbon-fixing enzymes, particularly carboxylases, which restricts the overall pathway performance. In parallel, challenges in expressing multiple heterologous genes-especially those encoding metal-dependent or oxygen-sensitive enzymes-further hinder pathway functionality. At the systems level, synthetic C1 pathways often exhibit poor flux distribution, limited integration with the host metabolism, accumulation of toxic intermediates, and disruptions in redox and energy balance. These factors collectively reduce biomass formation and compromise product yields in biotechnological setups. Overcoming these interconnected challenges is essential for moving synthetic C1 assimilation beyond conceptual stages and enabling its application in scalable, efficient bioprocesses towards a circular bioeconomy.

Role of the cathode chamber in microbial electrosynthesis: A comprehensive review of key factors

The consumption of non-renewable fossil fuels has directly contributed to a dramatic rise in global carbon dioxide (CO2) emissions, posing an ongoing threat to the ecological security of the Earth. Microbial electrosynthesis (MES) is an innovative energy regeneration strategy that offers a gentle and efficient approach to converting CO2 into high-value products. The cathode chamber is a vital component of an MES system and its internal factors play crucial roles in improving the performance of the MES system. Therefore, this review aimed to provide a detailed analysis of the key factors related to the cathode chamber in the MES system. The topics covered include inward extracellular electron transfer pathways, cathode materials, applied cathode potentials, catholyte pH, and reactor configuration. In addition, this review analyzes and discusses the challenges and promising avenues for improving the conversion of CO2 into high-value products via MES.

Techno-Economic Assessment of Electromicrobial Production of n-Butanol from Air-Captured CO2

Electromicrobial production (EMP), where electrochemically generated substrates (e.g., H2) are used as energy sources for microbial processes, has garnered significant interest as a method of producing fuels and other value-added chemicals from CO2. Combining these processes with direct air capture (DAC) has the potential to enable a truly circular carbon economy. Here, we analyze the economics of a hypothetical system that combines adsorbent-based DAC with EMP to produce n-butanol, a potential replacement for fossil fuels. First-principles-based modeling is used to predict the performance of the DAC and bioprocess components. A process model is then developed to map material and energy flows, and a techno-economic assessment is performed to determine the minimum fuel selling price. Beyond assessing a specific set of conditions, this analytical framework provides a tool to reveal potential pathways toward the economic viability of this process. We show that an EMP system utilizing an engineered knallgas bacterium can achieve butanol production costs of <$6/gal ($1.58/L) if a set of optimistic assumptions can be realized.

Data-driven flow-map models for data-efficient discovery of dynamics and fast uncertainty quantification of biological and biochemical systems

Computational models are increasingly used to investigate and predict the complex dynamics of biological and biochemical systems. Nevertheless, governing equations of a biochemical system may not be (fully) known, which would necessitate learning the system dynamics directly from, often limited and noisy, observed data. On the other hand, when expensive models are available, systematic and efficient quantification of the effects of model uncertainties on quantities of interest can be an arduous task. This paper leverages the notion of flow-map (de)compositions to present a framework that can address both of these challenges via learning data-driven models useful for capturing the dynamical behavior of biochemical systems. Data-driven flow-map models seek to directly learn the integration operators of the governing differential equations in a black-box manner, irrespective of structure of the underlying equations. As such, they can serve as a flexible approach for deriving fast-to-evaluate surrogates for expensive computational models of system dynamics, or, alternatively, for reconstructing the long-term system dynamics via experimental observations. We present a data-efficient approach to data-driven flow-map modeling based on polynomial chaos Kriging. The approach is demonstrated for discovery of the dynamics of various benchmark systems and a coculture bioreactor subject to external forcing, as well as for uncertainty quantification of a microbial electrosynthesis reactor. Such data-driven models and analyses of dynamical systems can be paramount in the design and optimization of bioprocesses and integrated biomanufacturing systems.

Model development of bioelectrochemical systems: A critical review from the perspective of physiochemical principles and mathematical methods

Bioelectrochemical systems (BESs) are promising devices for wastewater treatment and bio-energy production. Since various processes are interacted and affect the overall performance of the device, the development of theoretical modeling is an efficient approach to understand the fundamental mechanisms that govern the performance of the BES. This review aims to summarize the physiochemical principle and mathematical method in BES models, which is of great importance for the establishment of an accurate model while has received little attention in previous reviews. In this review, we begin with a classification of existing models including bioelectrochemical models, electronic models, and machine learning models. Subsequently, physiochemical principles and mathematical methods in models are discussed from two aspects: one is the description of methodology how to build a framework for models, and the other is to further review additional methods that can enrich model functions. Finally, the advantages/disadvantages, extended applications, and perspectives of models are discussed. It is expected that this review can provide a viewpoint from methodologies to understand BES models.

Enhancing Biohybrid CO2 to Multicarbon Reduction via Adapted Whole-Cell Catalysts

Catalytic CO₂ conversion to renewable fuel is of utmost importance to establish a carbon-neutral society. Bioelectrochemical CO₂ reduction, in which a solid cathode interfaces with CO₂-reducing bacteria, represents a promising approach for renewable and sustainable fuel production. The rational design of biocatalysts in the biohybrid system is imperative to effectively reduce CO₂ into valuable chemicals. Here, we introduce methanol adapted Sporomusa ovata (S. ovata) to enhance the slow metabolic activity of wild-type microorganisms to our semiconductive silicon nanowires (Si NWs) array for efficient CO₂ reduction. The adapted whole-cell catalysts enable an enhancement of CO₂ fixation with a superior faradaic efficiency on the poised Si NWs cathode. The synergy of the high-surface-area cathode and the adapted strain achieves a CO₂-reducing current density of 0.88 ± 0.11 mA/cm², which is 2.4-fold higher than the wild-type strain. This new generation of biohybrids using adapted S. ovata also decreases the charge transfer resistance at the cathodic interface and facilitates the faster charge transfer from the solid electrode to bacteria.

Empower C1: Combination of Electrochemistry and Biology to Convert C1 Compounds

The idea to somehow combine electrical current and biological systems is not new. It was subject of research as well as of science fiction literature for decades. Nowadays, in times of limited resources and the need to capture greenhouse gases like CO₂, this combination gains increasing interest, since it might allow to use C1 compounds and highly oxidized compounds as substrate for microbial production by "activating" them with additional electrons. In this chapter, different possibilities to combine electrochemistry and biology to convert C1 compounds into useful products will be discussed. The chapter first shows electrochemical conversion of C1 compounds, allowing the use of the product as substrate for a subsequent biosynthesis in uncoupled systems, further leads to coupled systems of biology and electrochemical conversion, and finally reaches the discipline of bioelectrosynthesis, where electrical current and C1 compounds are directly converted by microorganisms or enzymes. This overview will give an idea about the potentials and challenges of combining electrochemistry and biology to convert C1 molecules.

Envisioning the “Air Economy” — Powered by Reticular Chemistry and Sunlight for Clean Air, Clean Energy, and Clean Water

Addressing the three major stresses facing our planet, clean air, clean energy, and clean water, is within our reach. At present, new materials such as metal-organic frameworks and covalent organic frameworks, produced by reticular chemistry, are at the forefront of efforts to capture carbon dioxide from air and harvest water from air. We envision that the products of these two capture processes (carbon dioxide and water) can be fed into a conversion cycle in which they are used to produce fuels and chemicals via artificial photosynthesis. The use of air as a nonpolluting, cyclable, and sustainable resource for carbon and water can be powered by sunlight. We describe how the scientific basis for realizing this vision is either already achieved or being established, and that in the fullness of time this paradigm may lead to new global industries and a thriving “air economy.”

A General Model for Biofilm-Driven Microbial Electrosynthesis of Carboxylates From CO2

Up to now, computational modeling of microbial electrosynthesis (MES) has been underexplored, but is necessary to achieve breakthrough understanding of the process-limiting steps. Here, a general framework for modeling microbial kinetics in a MES reactor is presented. A thermodynamic approach is used to link microbial metabolism to the electrochemical reduction of an intracellular mediator, allowing to predict cellular growth and current consumption. The model accounts for CO₂ reduction to acetate, and further elongation to n-butyrate and n-caproate. Simulation results were compared with experimental data obtained from different sources and proved the model is able to successfully describe microbial kinetics (growth, chain elongation, and product inhibition) and reactor performance (current density, organics titer). The capacity of the model to simulate different system configurations is also shown. Model results suggest CO₂ dissolved concentration might be limiting existing MES systems, and highlight the importance of the delivery method utilized to supply it. Simulation results also indicate that for biofilm-driven reactors, continuous mode significantly enhances microbial growth and might allow denser biofilms to be formed and higher current densities to be achieved.