Structural modeling of histone methyltransferase complex Set1C from Saccharomyces cerevisiae using constraint-based docking

Arabidopsis S2Lb links AtCOMPASS-like and SDG2 activity in H3K4me3 independently from histone H2B monoubiquitination

Background

The functional determinants of H3K4me3, their potential dependency on histone H2B monoubiquitination, and their contribution to defining transcriptional regimes are poorly defined in plant systems. Unlike in Saccharomyces cerevisiae, where a single SET1 protein catalyzes H3K4me3 as part of COMPlex of proteins ASsociated with Set1 (COMPASS), in Arabidopsis thaliana, this activity involves multiple histone methyltransferases. Among these, the plant-specific SET DOMAIN GROUP 2 (SDG2) has a prominent role.

Results

We report that SDG2 co-regulates hundreds of genes with SWD2-like b (S2Lb), a plant ortholog of the Swd2 axillary subunit of yeast COMPASS. We show that S2Lb co-purifies with the AtCOMPASS core subunit WDR5, and both S2Lb and SDG2 directly influence H3K4me3 enrichment over highly transcribed genes. S2Lb knockout triggers pleiotropic developmental phenotypes at the vegetative and reproductive stages, including reduced fertility and seed dormancy. However, s2lb seedlings display little transcriptomic defects as compared to the large repertoire of genes targeted by S2Lb, SDG2, or H3K4me3, suggesting that H3K4me3 enrichment is important for optimal gene induction during cellular transitions rather than for determining on/off transcriptional status. Moreover, unlike in budding yeast, most of the S2Lb and H3K4me3 genomic distribution does not rely on a trans-histone crosstalk with histone H2B monoubiquitination.

Conclusions

Collectively, this study unveils that the evolutionarily conserved COMPASS-like complex has been co-opted by the plant-specific SDG2 histone methyltransferase and mediates H3K4me3 deposition through an H2B monoubiquitination-independent pathway in Arabidopsis.

Electronic supplementary material

The online version of this article (10.1186/s13059-019-1705-4) contains supplementary material, which is available to authorized users.

Modeling protein assemblies in the proteome

Most (if not all) proteins function when associated in multimolecular assemblies. Attaining the structures of protein assemblies at the atomic scale is an important aim of structural biology. Experimentally, structures are increasingly available, and computations can help bridge the resolution gap between high- and low-resolution scales. Existing computational methods have made substantial progress toward this aim; however, current approaches are still limited. Some involve manual adjustment of experimental data; some are automated docking methods, which are computationally expensive and not applicable to large-scale proteome studies; and still others exploit the symmetry of the complexes and thus are not applicable to nonsymmetrical complexes. Our study aims to take steps toward overcoming these limitations. We have developed a strategy for the construction of protein assemblies computationally based on binary interactions predicted by a motif-based protein interaction prediction tool, PRISM (Protein Interactions by Structural Matching). Previously, we have shown its power in predicting pairwise interactions. Here we take a step toward multimolecular assemblies, reflecting the more prevalent cellular scenarios. With this method we are able to construct homo-/hetero-complexes and symmetric/asymmetric complexes without a limitation on the number of components. The method considers conformational changes and is applicable to large-scale studies. We also exploit electron microscopy density maps to select a solution from among the predictions. Here we present the method, illustrate its results, and highlight its current limitations.

Three-dimensional modeling of protein interactions and complexes is going 'omics

High-throughput interaction discovery initiatives have revealed the existence of hundreds of multiprotein complexes whose functions are regulated through thousands of protein-protein interactions (PPIs). However, the structural details of these interactions, often necessary to understand their function, are only available for a tiny fraction, and the experimental difficulties surrounding complex structure determination make computational modeling techniques paramount. In this manuscript, we critically review some of the most recent developments in the field of structural bioinformatics applied to the modeling of protein interactions and complexes, from large macromolecular machines to domain-domain and peptide-mediated interactions. In particular, we place a special emphasis on those methods that can be applied in a proteome-wide manner, and discuss how they will help in the ultimate objective of building 3D interactome networks.