Comparative modeling of ABE fermentation using wild-type and engineered species

Abstract

In recent years, the continuous increase in population has led to a huge demand on fossil fuels products in the sector of transportation. This expansion in the use of gasoline fuel has caused a change in the climate. Therefore, research started to develop new alternative and ecofriendly ways to produce gasoline from renewable energy. ABE fermentation is one of the ways that can produce biofuels. After pre-treatment of lignocellulosic material, sugars are obtained and fermented in a batch reactor using the Clostridium Acetobutilicum as bacteria. Glucose, xylose, and arabinose are the three sugars used to produce bio butanol. Carbon catabolite repression, the inhibition of xylose or arabinose assimilation by glucose, is one of the challenges facing the fermentation pathway. Experimental work has been done to identify the behaviour of using single sugar, and to relieve the effect of carbon catabolite repression when multiple sugars exist together. On the other hand, mathematical modelling has assured to be an efficient way to test the metabolism under different hypotheses, and to save time and money. In this study Matlab 2021 (B) is used to develop and simulate a kinetic model of ABE fermentation using clostridium acetobutylicum ATCC824 or BOH3. Least square curve fit (Lsq) is used to estimate new parameters to get a fit with a good agreement with the experimental one. The simulation of diauxic growth was performed with deficiency of EIIAglcG and overexpression of Xylose uptake (XU), xylose isomerase (XI) and xylose kinase (XK). As a result, an improvement in xylose consumption and butanol production is obtained. Although arabinose is also inhibited by glucose, it is used in small quantities to be fully consumed without modifications. BOH3 is also simulated and does not require any gene modification or/and overexpression due to high activity of xylose isomerase and xylose kinase. This high activity of XI and XK ensures a full consumption of xylose and a high production of butanol. In addition, parameter sensitivity and confidence of intervals are generated and documented for all scenarios.