C16orf57 encodes a human protein of unknown function, and mutations in the gene occur in poikiloderma with neutropenia (PN), which is a rare, autosomal recessive disease. Interestingly, mutations in C16orf57 were also observed among patients diagnosed with Rothmund-Thomson syndrome (RTS) and dyskeratosis congenita (DC), which are caused by mutations in genes involved in DNA repair and telomere maintenance. A genetic screen in Saccharomyces cerevisiae revealed that the yeast ortholog of C16orf57, USB1 (YLR132C), is essential for U6 small nuclear RNA (snRNA) biogenesis and cell viability. Usb1 depletion destabilized U6 snRNA, leading to splicing defects and cell growth defects, which was suppressed by the presence of multiple copies of the U6 snRNA gene SNR6. Moreover, Usb1 is essential for the generation of a unique feature of U6 snRNA; namely, the 39-terminal phosphate. RNAi experiments in human cells followed by biochemical and functional analyses confirmed that, similar to yeast, C16orf57 encodes a protein involved in the 29,39-cyclic phosphate formation at the 39 end of U6 snRNA. Advanced bioinformatics predicted that C16orf57 encodes a phosphodiesterase whose putative catalytic activity is essential for its function in vivo. Our results predict an unexpected molecular basis for PN, DC, and RTS and provide insight into U6 snRNA 39 end formation.

Methylation is one of the most common chemical modifications of biologically active molecules and it occurs in all life forms. Its functional role is very diverse and involves many essential cellular processes, such as signal transduction, transcriptional control, biosynthesis, and metabolism. Here, we provide further insight into the enzymatic methylation in S. cerevisiae by conducting a comprehensive structural and functional survey of all the methyltransferases encoded in its genome. Using distant homology detection and fold recognition, we found that the S. cerevisiae methyltransferome comprises 86 MTases (53 well-known and 33 putative with unknown substrate specificity). Structural classification of their catalytic domains shows that these enzymes may adopt nine different folds, the most common being the Rossmann-like. We also analyzed the domain architecture of these proteins and identified several new domain contexts. Interestingly, we found that the majority of MTase genes are periodically expressed during yeast metabolic cycle. This finding, together with calculated isoelectric point, fold assignment and cellular localization, was used to develop a novel approach for predicting substrate specificity. Using this approach, we predicted the general substrates for 24 of 33 putative MTases and confirmed these predictions experimentally in both cases tested. Finally, we show that, in S. cerevisiae, methylation is carried out by 34 RNA MTases, 32 protein MTases, eight small molecule MTases, three lipid MTases, and nine MTases with still unknown substrate specificity.

We present a general probabilistic framework for predicting the substrate specificity of enzymes. We designed this approach to be easily applicable to different organisms and enzymes. Therefore, our predictive models do not rely on species-specific properties and use mostly sequence-derived data. Maximum Likelihood optimization is used to fine-tune model parameters and the Akaike Information Criterion is employed to overcome the issue of correlated variables. As a proof-of-principle, we apply our approach to predicting general substrate specificity of yeast methyltransferases (MTases). As input, we use several physico-chemical and biological properties of MTases: structural fold, isoelectric point, expression pattern and cellular localization. Our method accurately predicts whether a yeast MTase methylates a protein, RNA or another molecule. Among our experimentally tested predictions, 89% were confirmed, including the surprising prediction that YOR021C is the first known MTase with a SPOUT fold that methylates a substrate other than RNA (protein). Our approach not only allows for highly accurate prediction of functional specificity of MTases, but also provides insight into general rules governing MTase substrate specificity.

BackgroundThe family of D-isomer specific 2-hydroxyacid dehydrogenases (2HADHs) contains a wide range of oxidoreductases with various metabolic roles as well as biotechnological applications. Despite a vast amount of biochemical and structural data for various representatives of the family, the long and complex evolution and broad sequence diversity hinder functional annotations for uncharacterized members.ResultsWe report an in-depth phylogenetic analysis, followed by mapping of available biochemical and structural data on the reconstructed phylogenetic tree. The analysis suggests that some subfamilies comprising enzymes with similar yet broad substrate specificity profiles diverged early in the evolution of 2HADHs. Based on the phylogenetic tree, we present a revised classification of the family that comprises 22 subfamilies, including 13 new subfamilies not studied biochemically. We summarize characteristics of the nine biochemically studied subfamilies by aggregating all available sequence, biochemical, and structural data, providing comprehensive descriptions of the active site, cofactor-binding residues, and potential roles of specific structural regions in substrate recognition. In addition, we concisely present our analysis as an online 2HADH enzymes knowledgebase.ConclusionsThe knowledgebase enables navigation over the 2HADHs classification, search through collected data, and functional predictions of uncharacterized 2HADHs. Future characterization of the new subfamilies may result in discoveries of enzymes with novel metabolic roles and with properties beneficial for biotechnological applications.Electronic supplementary materialThe online version of this article (10.1186/s12862-018-1309-8) contains supplementary material, which is available to authorized users.