Multi-feed simultaneous saccharification and fermentation: model-based development of high gravity lignocellulose-based bioprocesses

Övrigt konferensbidrag, 2018

Second generation bioethanol production can be viewed as a model biorefinery concept for biotechnological conversion of recalcitrant lignocellulosic raw materials to chemicals and other products. High Gravity operation, i.e. fermentation at high concentrations of water insoluble solids, pushes the process towards higher product concentrations and productivities, and improved energy and water economy. However, lignocellulosic processes are highly prone to batch-to batch variability in e.g. raw materials and enzyme activities. This variability can be propagated throughout system scales during process development and optimization, influencing the outputs of bioreaction models, techno-economic analyses and life cycle assessments. We have developed the variance-stabi­lizing Multi-Feed SSCF process: a systematic, model-driven design of fed-batch simultaneous saccharification and co-fermentation of lignocellulosic materials in standard stirred tank reactors [1-3]. The design includes feeding of the solid fraction of steam-pretreated material, enzymes, and robust cell factories propagated on the liquid fraction of the substrate. It has been applied to lignocellulosic ethanol production using S. cerevisiae, and to lactic acid production from wheat straw by the thermophilic, cellulolytic strain Bacillus coagulans MA-13 [4]. We used uncertainty analysis to quantify the effects of model input variations on outputs in the multi-feed simultaneous saccharification and co-fermentation of wheat straw. We show how un­certainty analysis can be used to guide process development by comparing different modes of operation, defining possible process ranges and developing experimental designs at laboratory scale. The method can identify economically feasible process ranges with low environmental impact while increasing the robustness of bioprocesses with high variation in raw material inputs.

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[2] Wang et al. (2016) Biotechnology for Biofuels, 9:88.
[3] Westman et al. (2017) Biotechnology for Biofuels, 10:213
[4] Aulitto et al. (2017) Biotechnology for Biofuels, 10:210