Page 76 - Advances in bioenergy (2016)

Box 2.2 Directed Evolution’s Black Box

Evolutionary engineering is often considered as a nontargeted strain improvement strategy.
It is though widely recognized as a very powerful tool for strain improvement. Insight on
the improved cell population is a major challenge for scientists in the field. Better and
deeper knowledge of the genetic modifications and the mechanisms responsible for the
improvements observed will allow the transfer of relevant traits among different
microorganisms. For inverse metabolic engineering, or in other words, for the elucidation
of the genetic basis for improved performance, the choice of the correct tools is of major
importance. S. cerevisiae, being the model microorganism once more, is showing the way
as long as integral analysis at different information levels (genome, proteome, and
metabolome) is already successful and economically reasonable for academic and
industrial research. Among all available tools, wide genome techniques seem the most
powerful and most promising.

Metabolic Engineering Strategies

Metabolic engineering is defined by Bailey 106 as the improvement of cellular activities by
manipulation of enzymatic, transport, and regulatory functions of the cell with the use of
recombinant DNA technology. Metabolic engineering efforts aim at introducing heterologous
enzymes in S. cerevisiae, overexpressing existing genes, or introducing whole enzymatic paths
in the cell. Deletion of one or more genes is also an interesting approach often supplementary
to the others, which aim at pointing the cell metabolism toward the desirable direction.

Increase in yeast tolerance to lignocellulosic hydrolysates has been achieved by
overexpressing homologous or heterologous genes encoding enzymes that confer resistance

toward specific inhibitors such as furan derivatives and phenolic compounds. 107 Recently,
rational experimental design combined a metabolomics approach with metabolic engineering,
giving promising results. 108 In that study, capillary electrophoresis–mass spectrometry (CE–
MS) and gas chromatography–mass spectrometry (GC–MS) were used to determine the effect
of acetic acid on xylose fermentation. It was shown that accumulation of metabolites involved
in the nonoxidative pentose phosphate pathway (PPP) increased with an increase in acetic acid
concentration. Based on this, S. cerevisiae genes encoding PPP-related enzymes, transaldolase
(TAL) or transketolase (TKL), were overexpressed in the strain, which achieved increased
ethanol productivity in the presence of acetic and formic acids.

Although pentose metabolism does not fall in the scope of this review, some key points have to
be mentioned because the cofermentation of hexoses and pentoses is a significant trend in
biotechnology for biofuels. Key points of the enzymatic paths of pentoses anaerobic

metabolism in S. cerevisiae are as follows: the xylose transport into the cell, bridging xylose
and xylulose, the relief of the redox imbalance, the flux of xylulose to xylulose-5-P, the
expression of key enzymes in the PPP, in many cases have been the targets of metabolic
engineering approaches.