Extended fed-batch fermentation of a C5/C6 optimised yeast strain on wheat straw hydrolysate using an online refractive index sensor to measure the relative fermentation rate

Extended batch cultures for poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) production by Azotobacter vinelandii OP growing at different aeration rates

Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) is a polymer produced by Azotobacter vinelandii OP. In the bioreactor, PHBV production and its molar composition are affected by aeration rate. PHBV production by A. vinelandii OP was evaluated using extended batch cultures at different aeration rates, which determined different oxygen transfer rates (OTR) in the cultures. Under the conditions evaluated, PHBV with different 3-hydroxyvalerate (3HV) fractions were obtained. In the cultures with a low OTR (6.7 mmol L-1 h-1, at 0.3 vvm), a PHBV content of 38% w w-1 with 9.1 mol % 3HV was achieved. The maximum PHBV production (72% w w-1) was obtained at a high OTR (18.2 mmol L-1 h-1, at 1.0 vvm), both at 48 h. Thus, PHBV production increased in the bioreactor with an increased aeration rate, but not the 3HV fraction in the polymer chain. An OTR of 24.9 mmol L-1 h-1 (at 2.1 vvm) was the most suitable for improving the PHBV content (61% w w-1) and a high 3HV fraction of 20.8 mol % (at 48 h); and volumetric productivity (0.15 g L-1 h-1). The findings indicate that the extended batch culture at 2.1 vvm is the most adequate mode of cultivation to produce higher biomass and PHBV with a high 3HV fraction. Overall, the results have shown that the PHBV production and 3HV fraction could be affected by the aeration rate and the proposed approach could be applied to implement cultivation strategies to optimize PHBV production for different biotechnological applications.

Novel Propagation Strategy of Saccharomyces cerevisiae for Enhanced Xylose Metabolism during Fermentation on Softwood Hydrolysate

An economically viable production of second-generation bioethanol by recombinant xylose-fermenting Saccharomyces cerevisiae requires higher xylose fermentation rates and improved glucose–xylose co-consumption. Moreover, xylose-fermenting S. cerevisiae recognises xylose as a non-fermentable rather than a fermentable carbon source, which might partly explain why xylose is not fermented into ethanol as efficiently as glucose. This study proposes propagating S. cerevisiae on non-fermentable carbon sources to enhance xylose metabolism during fermentation. When compared to yeast grown on sucrose, cells propagated on a mix of ethanol and glycerol in shake flasks showed up to 50% higher xylose utilisation rate (in a defined xylose medium) and a double maximum fermentation rate, together with an improved C5/C6 co-consumption (on an industrial softwood hydrolysate). Based on these results, an automated propagation protocol was developed, using a fed-batch approach and the respiratory quotient to guide the ethanol and glycerol-containing feed. This successfully produced 71.29 ± 0.91 g/L yeast with an average productivity of 1.03 ± 0.05 g/L/h. These empirical findings provide the basis for the design of a simple, yet effective yeast production strategy to be used in the second-generation bioethanol industry for increased fermentation efficiency.

A brief review on recent development of multidisciplinary engineering in fermentation of Saccharomyces cerevisiae

Fermentation technology has unprecedented potential to upgrade state-of-art biotechnology and refine the processes used in existing ones, taking into account of complex technical, economic and environmental factors. Given the economic importance and ongoing challenges of biotech sector, multidisciplinary engineering technologies is poised to become an increasingly important tool along with the emergence of modern technology and innovation. This article reviews recent technology advancement in the field of fermentation using Saccharomyces cerevisiae. Interesting research progress has been made by leveraging multiple engineering fields such as electrical engineering, information engineering, electrochemical engineering and new material development, leading to recent development of novel real-time probes (electronic nose technology, analysis of yeast morphology and metabolites, timely control of glucose feed), improved understanding of electro-fermentation (enhanced electronic transfer provision), as well as application of cost-effective and sustainable materials (bioreactor vessel manufactured from textile, and yeast immobilisation support matrix made from abundant natural biomass). To the best of our knowledge, the subject is reviewed for the first time in recent years. Furthermore, this review also constitutes a futuristic S. cerevisiae fermentation process based on the recent advancement discussed.

Promoting the co-utilisation of glucose and xylose in lignocellulosic ethanol fermentations using a data-driven feed-back controller

BACKGROUND

The diauxic growth of Saccharomyces cerevisiae on glucose and xylose during cellulose-to-ethanol processes extends the duration of the fermentation and reduces productivity. Despite the remarkable advances in strain engineering, the co-consumption of glucose and xylose is still limited due to catabolite repression. This work addresses this challenge by developing a closed-loop controller that is capable of maintaining the glucose concentration at a steady set-point during fed-batch fermentation. The suggested controller uses a data-driven model to measure the concentration of glucose from 'real-time' spectroscopic data. The concentration of glucose is then automatically controlled using a control scheme that consists of a proportional, integral, differential (PID) algorithm and a supervisory layer that manipulates the feed-rates to the reactor accounting for the changing dynamics of fermentation.

RESULTS

The PID parameters and the supervisory layer were progressively improved throughout four fed-batch lignocellulosic-to-ethanol fermentations to attain a robust controller able of maintaining the glucose concentration at the pre-defined set-points. The results showed an increased co-consumption of glucose and xylose that resulted in volumetric productivities that are 20-33% higher than the reference batch processes. It was also observed that fermentations operated at a glucose concentration of 10 g/L were faster than those operated at 4 g/L, indicating that there is an optimal glucose concentration that maximises the overall productivity.

CONCLUSIONS

Promoting the simultaneous consumption of glucose and xylose in S. cerevisiae is critical to increase the productivity of lignocellulosic ethanol processes, but also challenging due to the strong catabolite repression of glucose on the uptake of xylose. Operating the fermentation at low concentrations of glucose allows reducing the effects of the catabolite repression to promote the co-consumption of the two carbon sources. However, S. cerevisiae is very sensitive to changes in the glucose concentration and deviations from a set-point result in notable productivity losses. The controller structure developed and implemented in this work illustrates how combining data-driven measurements of the glucose concentration and a robust yet effective PID-based supervisory control allowed tight control of the concentration of glucose to adjust it to the metabolic requirements of the cell culture that can unlock tangible gains in productivities.

Transforming data to information: A parallel hybrid model for real-time state estimation in lignocellulosic ethanol fermentation

Operating lignocellulosic fermentation processes to produce fuels and chemicals is challenging due to the inherent complexity and variability of the fermentation media. Real‐time monitoring is necessary to compensate for these challenges, but the traditional process monitoring methods fail to deliver actionable information that can be used to implement advanced control strategies. In this study, a hybrid‐modeling approach is presented to monitor cellulose‐to‐ethanol (EtOH) fermentations in real‐time. The hybrid approach uses a continuous‐discrete extended Kalman filter to reconciliate the predictions of a data‐driven model and a kinetic model and to estimate the concentration of glucose (Glu), xylose (Xyl), and EtOH. The data‐driven model is based on partial least squares (PLS) regression and predicts in real‐time the concentration of Glu, Xyl, and EtOH from spectra collected with attenuated total reflectance mid‐infrared spectroscopy. The estimations made by the hybrid approach, the data‐driven models and the internal model were compared in two validation experiments showing that the hybrid model significantly outperformed the PLS and improved the predictions of the internal model. Furthermore, the hybrid model delivered consistent estimates even when disturbances in the measurements occurred, demonstrating the robustness of the method. The consistency of the proposed hybrid model opens the doors towards the implementation of advanced feedback control schemes.