A deeper mechanistic understanding of the saccharification of cellulosic biomass could enhance the efficiency of biofuels development. We report here the real-time visualization of crystalline cellulose degradation by individual cellulase enzymes through use of an advanced version of high-speed atomic force microscopy. Trichoderma reesei cellobiohydrolase I (TrCel7A) molecules were observed to slide unidirectionally along the crystalline cellulose surface but at one point exhibited collective halting analogous to a traffic jam. Changing the crystalline polymorphic form of cellulose by means of an ammonia treatment increased the apparent number of accessible lanes on the crystalline surface and consequently the number of moving cellulase molecules. Treatment of this bulky crystalline cellulose simultaneously or separately with T. reesei cellobiohydrolase II (TrCel6A) resulted in a remarkable increase in the proportion of mobile enzyme molecules on the surface. Cellulose was completely degraded by the synergistic action between the two enzymes.

Hydrophobins are surface active proteins produced by filamentous fungi. They have a role in fungal growth as structural components and in the interaction of fungi with their environment. They have, for example, been found to be important for aerial growth, and for the attachment of fungi to solid supports. Hydrophobins also render fungal structures, such as spores, hydrophobic. The biophysical properties of the isolated proteins are remarkable, such as strong adhesion, high surface activity and the formation of various self-assembled structures. The first high resolution three dimensional structure of a hydrophobin, HFBII from Trichoderma reesei, was recently solved. In this review, the properties of hydrophobins are analyzed in light of these new data. Various application possibilities are also discussed.

Genomic data now allow the large-scale manual or semi-automated reconstruction of metabolic networks. A network reconstruction represents a highly curated organism-specific knowledge base. A few genome-scale network reconstructions have appeared for metabolism in the baker’s yeast Saccharomyces cerevisiae. These alternative network reconstructions differ in scope and content, and further have used different terminologies to describe the same chemical entities, thus making comparisons between them difficult. The formulation of a ‘community consensus’ network that collects and formalizes the ‘community knowledge’ of yeast metabolism is thus highly desirable. We describe how we have produced a consensus metabolic network reconstruction for S. cerevisiae. Special emphasis is laid on referencing molecules to persistent databases or using database-independent forms such as SMILES or InChI strings, since this permits their chemical structure to be represented unambiguously and in a manner that permits automated reasoning. The reconstruction is readily available via a publicly accessible database and in the Systems Biology Markup Language, and we describe the manner in which it can be maintained as a community resource. It should serve as a common denominator for system biology studies of yeast. Similar strategies will be of benefit to communities studying genome-scale metabolic networks of other organisms.

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