Development of real-time PCR primer and probe sets for detecting degenerated and non-degenerated forms of the butanol-producing bacterium Clostridium acetobutylicum ATCC 824

Design and validation of a multiplex PCR method for the simultaneous quantification of Clostridium acetobutylicum, Clostridium carboxidivorans and Clostridium cellulovorans

Co-cultures of clostridia with distinct physiological properties have emerged as an alternative to increase the production of butanol and other added-value compounds from biomass. The optimal performance of mixed tandem cultures may depend on the stability and fitness of each species in the consortium, making the development of specific quantification methods to separate their members crucial. In this study, we developed and tested a multiplex qPCR method targeting the 16S rRNA gene for the simultaneous quantification of Clostridium acetobutylicum, Clostridium carboxidivorans and Clostridium cellulovorans in co-cultures. Designed primer pairs and probes could specifically quantify the three Clostridium species with no cross-reactions thus allowing significant changes in their growth kinetics in the consortia to be detected and correlated with productivity. The method was used to test a suitable medium composition for simultaneous growth of the three species. We show that higher alcohol productions were obtained when combining C. carboxidivorans and C. acetobutylicum compared to individual cultures, and further improved (> 90%) in the triplet consortium. Altogether, the methodology could be applied to fermentation processes targeting butanol productions from lignocellulosic feedstocks with a higher substrate conversion efficiency.

Clostridium beijerinckii strain degeneration is driven by the loss of Spo0A activity

Solventogenic clostridia represent a diverse group of anaerobic, spore-forming bacteria capable of producing acetone, butanol and ethanol through their unique biphasic metabolism. An intrinsic problem with these organisms however is their tendency to degenerate when repeatedly subcultured or when grown continuously. This phenomenon sees cells lose their ability to produce solvents and spores, posing a significant problem for industrial applications. To investigate the mechanistic and evolutionary basis of degeneration we combined comparative genomics, ultra-deep sequencing, and concepts of sociomicrobiology using Clostridium beijerinckii NCIMB 8052 as our model organism. These approaches revealed spo0A, the master regulator gene involved in spore and solvent formation, to be key to the degeneration process in this strain. Comparative genomics of 71 degenerate variants revealed four distinct hotspot regions that contained considerably more mutations than the rest of the genome. These included spo0A as well as genes suspected to regulate its expression and activity. Ultra-deep sequencing of populations during the subculturing process showed transient increases in mutations we believe linked to the spo0A network, however, these were ultimately dominated by mutations in the master regulator itself. Through frequency-dependent fitness assays, we found that spo0A mutants gained a fitness advantage, relative to the wild type, presumably allowing for propagation throughout the culture. Combined, our data provides new insights into the phenomenon of clostridial strain degeneration and the C. beijerinckii NCIMB 8052 solvent and spore regulation network.

Model-based quantification of metabolic interactions from dynamic microbial-community data

An important challenge in microbial ecology is to infer metabolic-exchange fluxes between growing microbial species from community-level data, concerning species abundances and metabolite concentrations. Here we apply a model-based approach to integrate such experimental data and thereby infer metabolic-exchange fluxes. We designed a synthetic anaerobic co-culture of Clostridium acetobutylicum and Wolinella succinogenes that interact via interspecies hydrogen transfer and applied different environmental conditions for which we expected the metabolic-exchange rates to change. We used stoichiometric models of the metabolism of the two microorganisms that represents our current physiological understanding and found that this understanding - the model - is sufficient to infer the identity and magnitude of the metabolic-exchange fluxes and it suggested unexpected interactions. Where the model could not fit all experimental data, it indicates specific requirement for further physiological studies. We show that the nitrogen source influences the rate of interspecies hydrogen transfer in the co-culture. Additionally, the model can predict the intracellular fluxes and optimal metabolic exchange rates, which can point to engineering strategies. This study therefore offers a realistic illustration of the strengths and weaknesses of model-based integration of heterogenous data that makes inference of metabolic-exchange fluxes possible from community-level experimental data.