Coenzyme A-transferase-independent butyrate re-assimilation in Clostridium acetobutylicum - evidence from a mathematical model

The hetero-dimeric CoA-transferase CtfA/B is believed to be crucial for the metabolic transition from acidogenesis to solventogenesis in Clostridium acetobutylicum as part of the industrial-relevant acetone-butanol-ethanol (ABE) fermentation. Here, the enzyme is assumed to mediate re-assimilation of acetate and butyrate during a pH-induced metabolic shift and to faciliate the first step of acetone formation from acetoacetyl-CoA. However, recent investigations using phosphate-limited continuous cultures have questioned this common dogma. To address the emerging experimental discrepancies, we investigated the mutant strain Cac-ctfA398s::CT using chemostat cultures. As a consequence of this mutation, the cells are unable to express functional ctfA and are thus lacking CoA-transferase activity. A mathematical model of the pH-induced metabolic shift, which was recently developed for the wild type, is used to analyse the observed behaviour of the mutant strain with a focus on re-assimilation activities for the two produced acids. Our theoretical analysis reveals that the ctfA mutant still re-assimilates butyrate, but not acetate. Based upon this finding, we conclude that C. acetobutylicum possesses a CoA-tranferase-independent butyrate uptake mechanism that is activated by decreasing pH levels. Furthermore, we observe that butanol formation is not inhibited under our experimental conditions, as suggested by previous batch culture experiments. In concordance with recent batch experiments, acetone formation is abolished in chemostat cultures using the ctfa mutant

Quantitative proteomic analysis of the influence of lignin on biofuel production by Clostridium acetobutylicum ATCC 824

Background: Clostridium acetobutylicum has been a focus of research because of its ability to produce high-value compounds that can be used as biofuels. Lignocellulose is a promising feedstock, but the lignin–cellulose–hemicellulose biomass complex requires chemical pre-treatment to yield fermentable saccharides, including cellulose-derived cellobiose, prior to bioproduction of acetone–butanol–ethanol (ABE) and hydrogen. Fermentation capability is limited by lignin and thus process optimization requires knowledge of lignin inhibition. The effects of lignin on cellular metabolism were evaluated for C. acetobutylicum grown on medium containing either cellobiose only or cellobiose plus lignin. Microscopy, gas chromatography and 8-plex iTRAQ-based quantitative proteomic technologies were applied to interrogate the effect of lignin on cellular morphology, fermentation and the proteome. Results: Our results demonstrate that C. acetobutylicum has reduced performance for solvent production when lignin is present in the medium. Medium supplemented with 1 g L−1 of lignin led to delay and decreased solvents production (ethanol; 0.47 g L−1 for cellobiose and 0.27 g L−1 for cellobiose plus lignin and butanol; 0.13 g L−1 for cellobiose and 0.04 g L−1 for cellobiose plus lignin) at 20 and 48 h, respectively, resulting in the accumulation of acetic acid and butyric acid. Of 583 identified proteins (FDR < 1 %), 328 proteins were quantified with at least two unique peptides. Up- or down-regulation of protein expression was determined by comparison of exponential and stationary phases of cellobiose in the presence and absence of lignin. Of relevance, glycolysis and fermentative pathways were mostly down-regulated, during exponential and stationary growth phases in presence of lignin. Moreover, proteins involved in DNA repair, transcription/translation and GTP/ATP-dependent activities were also significantly affected and these changes were associated with altered cell morphology. Conclusions: This is the first comprehensive analysis of the cellular responses of C. acetobutylicum to lignin at metabolic and physiological levels. These data will enable targeted metabolic engineering strategies to optimize biofuel production from biomass by overcoming limitations imposed by the presence of lignin

Mathematical modelling of clostridial acetone-butanol-ethanol fermentation

Clostridial acetone-butanol-ethanol (ABE) fermentation features a remarkable shift in the cellular metabolic activity from acid formation, acidogenesis, to the production of industrial-relevant solvents, solventogensis. In recent decades, mathematical models have been employed to elucidate the complex interlinked regulation and conditions that determine these two distinct metabolic states and govern the transition between them. In this review, we discuss these models with a focus on the mechanisms controlling intra- and extracellular changes between acidogenesis and solventogenesis. In particular, we critically evaluate underlying model assumptions and predictions in the light of current experimental knowledge. Towards this end, we briefly introduce key ideas and assumptions applied in the discussed modelling approaches, but waive a comprehensive mathematical presentation. We distinguish between structural and dynamical models, which will be discussed in their chronological order to illustrate how new biological information facilitates the ‘evolution’ of mathematical models. Mathematical models and their analysis have significantly contributed to our knowledge of ABE fermentation and the underlying regulatory network which spans all levels of biological organization. However, the ties between the different levels of cellular regulation are not well understood. Furthermore, contradictory experimental and theoretical results challenge our current notion of ABE metabolic network structure. Thus, clostridial ABE fermentation still poses theoretical as well as experimental challenges which are best approached in close collaboration between modellers and experimentalists

Risks and opportunities of open-source generative AI

Applications of Generative AI (Gen AI) are expected to revolutionize a number of different areas, ranging from science & medicine to education. The potential for these seismic changes has triggered a lively debate about the potential risks of the technology, and resulted in calls for tighter regulation, in particular from some of the major tech companies who are leading in AI development. This regulation is likely to put at risk the budding field of open-source generative AI. Using a three-stage framework for Gen AI development (near, mid and long-term), we analyze the risks and opportunities of open-source generative AI models with similar capabilities to the ones currently available (near to mid-term) and with greater capabilities (long-term). We argue that, overall, the benefits of open-source Gen AI outweigh its risks. As such, we encourage the open sourcing of models, training and evaluation data, and provide a set of recommendations and best practices for managing risks associated with open-source generative AI

Sensing human health from Space: An assessment of applications and big data platforms

The integration of Earth Observation (EO) into human health research has expanded significantly, particularly since 2009, highlighting its potential for disease modelling, environmental exposure assessment, and public health decision-making. This review explores the evolving role of EO in health applications through a bibliometric analysis of 1751 research documents retrieved from the Web of Science (WoS) database. These documents were selected using targeted keywords and after excluding non-primary literature such as reviews, editorials, and meeting abstracts. Findings revealed a substantial increase in EO-health research outputs, growing from 2 publications in 1991 to 266 in 2024, with a notable surge beginning in 2009. More than 65 % of the selected studies contributed to Sustainable Development Goal (SDG) 13 on Climate Action, followed by SDG 3 on Good Health and Wellbeing (n = 994) and SDG 11 on Sustainable Cities and Communities (n = 980), illustrating EO's cross-cutting relevance. Despite this growth, the field remains fragmented due to inconsistent data formats, limited accessibility, and weak interdisciplinary collaboration. A key challenge is the persistent divide between EO data producers and health practitioners, which hampers the effective translation of EO insights into practice. This review highlights the importance of co-production approaches that bring together researchers, policymakers, and communities to address these barriers. By promoting standardisation, enhancing data interoperability, and fostering interdisciplinary collaboration, EO can be more effectively leveraged to support disease surveillance, environmental health monitoring, and evidence-based policy interventions aligned with global health and sustainability goals

Optimized Expression and Purification for High-Activity Preparations of Algal [FeFe]-Hydrogenase

Background: Recombinant expression and purification of metallo-enzymes, including hydrogenases, at high-yields is challenging due to complex, and enzyme specific, post-translational maturation processes. Low fidelities of maturation result in preparations containing a significant fraction of inactive, apo-protein that are not suitable for biophysical or crystallographic studies. Principal Findings: We describe the construction, overexpression and high-yield purification of a fusion protein consisting of the algal [2Fe2S]-ferredoxin PetF (Fd) and [FeFe]-hydrogenase HydA1. The maturation of Fd-HydA1 was optimized through improvements in culture conditions and media components used for expression. We also demonstrated that fusion of Fd to the N-terminus of HydA1, in comparison to the C-terminus, led to increased expression levels that were 4-fold higher. Together, these improvements led to enhanced HydA1 activity and improved yield after purification. The strong binding-affinity of Fd for DEAE allowed for two-step purification by ion exchange and StrepTactin affinity chromatography. In addition, the incorporation of a TEV protease site in the Fd-HydA1 linker allowed for the proteolytic removal of Fd after DEAE step, and purification of HydA1 alone by StrepTactin. In combination, this process resulted in HydA1 purification yields of 5 mg L−1 of culture from E. coli with specific activities of 1000 U (U = 1 µmol hydrogen evolved mg−1 min−1). Significance: The [FeFe]-hydrogenases are highly efficient enzymes and their catalytic sites provide model structures for synthetic efforts to develop robust hydrogen activation catalysts. In order to characterize their structure-function properties in greater detail, and to use hydrogenases for biotechnological applications, reliable methods for rapid, high-yield expression and purification are required.United States. Dept. of Energy. (contract DE-AC36-08-GO28308

High-Yield Expression of Heterologous [FeFe] Hydrogenases in Escherichia coli

BACKGROUND: The realization of hydrogenase-based technologies for renewable H(2) production is presently limited by the need for scalable and high-yielding methods to supply active hydrogenases and their required maturases. PRINCIPAL FINDINGS: In this report, we describe an improved Escherichia coli-based expression system capable of producing 8-30 mg of purified, active [FeFe] hydrogenase per liter of culture, volumetric yields at least 10-fold greater than previously reported. Specifically, we overcame two problems associated with other in vivo production methods: low protein yields and ineffective hydrogenase maturation. The addition of glucose to the growth medium enhances anaerobic metabolism and growth during hydrogenase expression, which substantially increases total yields. Also, we combine iron and cysteine supplementation with the use of an E. coli strain upregulated for iron-sulfur cluster protein accumulation. These measures dramatically improve in vivo hydrogenase activation. Two hydrogenases, HydA1 from Chlamydomonas reinhardtii and HydA (CpI) from Clostridium pasteurianum, were produced with this improved system and subsequently purified. Biophysical characterization and FTIR spectroscopic analysis of these enzymes indicate that they harbor the H-cluster and catalyze H(2) evolution with rates comparable to those of enzymes isolated from their respective native organisms. SIGNIFICANCE: The production system we describe will facilitate basic hydrogenase investigations as well as the development of new technologies that utilize these prolific H(2)-producing enzymes. These methods can also be extended for producing and studying a variety of oxygen-sensitive iron-sulfur proteins as well as other proteins requiring anoxic environments