Scheffersomyces stipitis (S. stipitis), formerly known as Pichia stipitis , is a hemiascomycetous yeast, closely related to several yeast endosymbionts of passalid beetles that inhabit and decay white-rotted hardwood [2, 3]. It has the highest native capacity for xylose fermentation of any known microbe [4, 5]. Fed batch cultures of S. stipitis produce around 47 g/l of ethanol with yields of 0.36 g/g xylose at 30°C . In addition to xylose, S. stipitis has the capability to ferment sugars from hydrolysates with yields equivalent to 80% of theoretical yield [6–8]. Auxotrophic strains have been created and methods for high efficiency transformation have been developed for S. stipitis [9, 10]. Genetic tools based on a loxP/Cre recombination system have been developed for functional genomics and metabolic engineering of this yeast . The availability of genetic tools and capability for fermentation of hydrolysates has made S. stipitis an attractive microorganism for bioconversion of lignocellulose to fuels and chemicals. S. stipitis has already been successfully engineered to produce lactic acid and xylitol [12, 13]. However, S. stipitis suffers from some drawbacks like lower fermentation rates, lower tolerance to ethanol and absence of anaerobic growth [5, 14, 15].
As a parallel approach, xylose utilization pathway from S. stipitis has been used to engineer xylose metabolism in Saccharomyces cerevisiae. Successive cycles of metabolic engineering have improved xylose utilization in recombinant S. cerevisiae [16, 17]. However, the ethanol productivity from xylose is still low. This has been attributed to: low substrate affinity of recombinant enzymes ; cofactor imbalance in the XR-XDH reactions [19, 20]; low xylose transport capacity [21, 22]; and failure to recognize xylose as a fermentable carbon source [23, 24]. The holistic analysis of metabolism in S. stipitis could provide useful insights to identify shortcomings in S. stipitis and S. cerevisiae metabolic networks.
The complete genome of S. stipitis has been sequenced . The functional annotation of the genome sequence showed numerous genes for lignocellulose bioconversion and systematic analysis of the genome sequence annotation is necessary to obtain useful insights. Genome scale metabolic models, which represent the link between the genotype and phenotype of the organism, can be reconstructed based on the genome sequence annotation and relevant biochemical and physiological information. These models have the ability to provide a holistic view of the metabolism of an organism. Once experimentally validated, these models can be used to characterize the metabolic resource allocation, generate experimentally testable predictions of cellular phenotypes, elucidate metabolic network evolution scenarios, design experiments that most effectively reveal the genotype-phenotype relationships, and design engineered microorganisms with desired properties like overproduction of commercially valuable chemicals [26–30]. Due to the genome wide-scale, these models enable systematic assessment of how perturbations in the metabolic network affect the organism as a whole which may not be possible by analyzing a set of enzymes or isolated pathways.
We have reported a framework for reconstruction of genome scale metabolic model of S. stipitis . In this study, a genome scale metabolic model has been developed for S. stipitis based on the proposed framework and a recently published protocol . Experimental procedure for the estimation of macromolecular composition of S. stipitis was standardized and used to obtain the biomass composition. Growth and non-growth associated maintenance energy requirements were also estimated from experimental data. The model was refined and validated based on the ability of S. stipitis to grow on different carbon, nitrogen, sulphur and phosphorus sources. In silico analysis of the model was used to identify biosynthetic requirements for anaerobic growth of S. stipitis in glucose and to analyze xylose utilization capability in S. stipitis. Model simulations were carried out to obtain insights on the recycling of nucleotide cofactors and mechanisms involved in mitochondrial respiration and oxidative phosphorylation.