Function diversification in large protein families is a major mechanism driving expansion of cellular networks, providing organisms with new metabolic capabilities and thus adding to their evolutionary success. However, our understanding of the evolutionary mechanisms of functional diversity in such families is very limited, which, among many other reasons, is due to the lack of functionally well-characterized sets of proteins. Here, using the FGGY carbohydrate kinase family as an example, we built a confidently annotated reference set (CARS) of proteins by propagating experimentally verified functional assignments to a limited number of homologous proteins that are supported by their genomic and functional contexts. Then, we analyzed, on both the phylogenetic and the molecular levels, the evolution of different functional specificities in this family. The results show that the different functions (substrate specificities) encoded by FGGY kinases have emerged only once in the evolutionary history following an apparently simple divergent evolutionary model. At the same time, on the molecular level, one isofunctional group (L-ribulokinase, AraB) evolved at least two independent solutions that employed distinct specificity-determining residues for the recognition of a same substrate (L-ribulose). Our analysis provides a detailed model of the evolution of the FGGY kinase family. It also shows that only combined molecular and phylogenetic approaches can help reconstruct a full picture of functional diversifications in such diverse families.

Isocitrate dehydrogenase 1 (IDH1) catalyzes the reversible NADP+-dependent conversion of isocitrate to α-ketoglutarate (αKG) to provide critical cytosolic substrates and drive NADPH-dependent reactions like lipid biosynthesis and glutathione regeneration. In biochemical studies, the forward reaction is studied at neutral pH, while the reverse reaction is typically characterized in more acidic buffers. This led us to question whether IDH1 catalysis is pH-regulated, which would have functional implications under conditions that alter cellular pH, like apoptosis, hypoxia, cancer, and neurodegenerative diseases. Here, we show evidence of catalytic regulation of IDH1 by pH, identifying a trend of increasing kcat values for αKG production upon increasing pH in the buffers we tested. To understand the molecular determinants of IDH1 pH sensitivity, we used the pHinder algorithm to identify buried ionizable residues predicted to have shifted pKa values. Such residues can serve as pH sensors, with changes in protonation states leading to conformational changes that regulate catalysis. We identified an acidic residue buried at the IDH1 dimer interface, D273, with a predicted pKa value upshifted into the physiological range. D273 point mutations had decreased catalytic efficiency and, importantly, loss of pH-regulated catalysis. Based on these findings, we conclude that IDH1 activity is regulated, at least in part, by pH. We show this regulation is mediated by at least one buried acidic residue ∼12 Å from the IDH1 active site. By establishing mechanisms of regulation of this well-conserved enzyme, we highlight catalytic features that may be susceptible to pH changes caused by cell stress and disease.

The release of the 1000th complete microbial genome will occur in the next two to three years. In anticipation of this milestone, the Fellowship for Interpretation of Genomes (FIG) launched the Project to Annotate 1000 Genomes. The project is built around the principle that the key to improved accuracy in high-throughput annotation technology is to have experts annotate single subsystems over the complete collection of genomes, rather than having an annotation expert attempt to annotate all of the genes in a single genome. Using the subsystems approach, all of the genes implementing the subsystem are analyzed by an expert in that subsystem. An annotation environment was created where populated subsystems are curated and projected to new genomes. A portable notion of a populated subsystem was defined, and tools developed for exchanging and curating these objects. Tools were also developed to resolve conflicts between populated subsystems. The SEED is the first annotation environment that supports this model of annotation. Here, we describe the subsystem approach, and offer the first release of our growing library of populated subsystems. The initial release of data includes 180 177 distinct proteins with 2133 distinct functional roles. This data comes from 173 subsystems and 383 different organisms.