Syngas fermentation is a powerful platform for the conversion of waste streams to the sustainable creation of carboxylic acid precursors for value-added biochemicals. Steel mills are a large producer of syngas, but up until now, there has not yet been an industrial application of microbial syngas valorization. The most promising syngas-converting biocatalysts consist of Clostridia species, such as Clostridium kluyveri, Clostridium autoethanogenum, and Clostridium ljungdahlii. Clostridium luticellarii, a recently discovered species, shares close phylogenetic ties with these organisms. Preliminary metabolic studies suggest its potential for acetogenesis from syngas as well as chain elongation. In this study, we create iSJ444, a constraint-based metabolic model of Clostridium luticellarii using iHN637 of a close relative Clostridium ljungdahlii as a starting point. Model predictions support hypothesized methanol and syngas pathways from the metabolic characterization studies; however the use of propionate could not be accurately predicted. Thermodynamic Flux Analysis (TFA) reveals that C. luticellarii maintains stable energy dissipation across most reactions when exposed to varying pH, with significant increases observed in Wood-Ljungdahl Pathway (WLP)- associated reactions, such as the HACD1 reaction, at higher pH (6.5), suggesting an adaptive role in energy management under neutral conditions. Simulations of growth using flux sampling show that Clostridium luticellarii might fit into syngas fermenting platforms. In both cases, high hydrogen-to-carbon source ratios result in better production of (iso)butyrate and caproate. We provide a minimal metabolic model of Clostridium luticellarii, which can be used to facilitate further advancement. We show predictions of the metabolic behavior of C. luticellarii, which should be experimentally verified, but promote the use of C. luticellarii to improve syngas fermentation.

Implementation of a Clostridium luticellarii genome-scale model for upgrading syngas fermentations