Aalt D. J. van Dijk

Information-driven protein–DNA docking using HADDOCK: it is a matter of flexibility

Intrinsic flexibility of DNA has hampered the development of efficient protein−DNA docking methods. In this study we extend HADDOCK (High Ambiguity Driven DOCKing) [C. Dominguez, R. Boelens and A. M. J. J. Bonvin (2003) J. Am. Chem. Soc. 125, 1731–1737] to explicitly deal with DNA flexibility. HADDOCK uses non-structural experimental data to drive the docking during a rigid-body energy minimization, and semi-flexible and water refinement stages. The latter allow for flexibility of all DNA nucleotides and the residues of the protein at the predicted interface. We evaluated our approach on the monomeric repressor−DNA complexes formed by bacteriophage 434 Cro, the Escherichia coli Lac headpiece and bacteriophage P22 Arc. Starting from unbound proteins and canonical B-DNA we correctly predict the correct spatial disposition of the complexes and the specific conformation of the DNA in the published complexes. This information is subsequently used to generate a library of pre-bent and twisted DNA structures that served as input for a second docking round. The resulting top ranking solutions exhibit high similarity to the published complexes in terms of root mean square deviations, intermolecular contacts and DNA conformation. Our two-stage docking method is thus able to successfully predict protein−DNA complexes from unbound constituents using non-structural experimental data to drive the docking.

Arabidopsis Class I and Class II TCP Transcription Factors Regulate Jasmonic Acid Metabolism and Leaf Development Antagonistically.

TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR1 (TCP) transcription factors control developmental processes in plants. The 24 TCP transcription factors encoded in the Arabidopsis (Arabidopsis thaliana) genome are divided into two classes, class I and class II TCPs, which are proposed to act antagonistically. We performed a detailed phenotypic analysis of the class I tcp20 mutant, showing an increase in leaf pavement cell sizes in 10-d-old seedlings. Subsequently, a glucocorticoid receptor induction assay was performed, aiming to identify potential target genes of the TCP20 protein during leaf development. The LIPOXYGENASE2 (LOX2) and class I TCP9 genes were identified as TCP20 targets, and binding of TCP20 to their regulatory sequences could be confirmed by chromatin immunoprecipitation analyses. LOX2 encodes for a jasmonate biosynthesis gene, which is also targeted by class II TCP proteins that are under the control of the microRNA JAGGED AND WAVY (JAW), although in an antagonistic manner. Mutation of TCP9, the second identified TCP20 target, resulted in increased pavement cell sizes during early leaf developmental stages. Analysis of senescence in the single tcp9 and tcp20 mutants and the tcp9tcp20 double mutants showed an earlier onset of this process in comparison with wild-type control plants in the double mutant only. Both the cell size and senescence phenotypes are opposite to the known class II TCP mutant phenotype in JAW plants. Altogether, these results point to an antagonistic function of class I and class II TCP proteins in the control of leaf development via the jasmonate signaling pathway.

Bayesian Markov Random Field Analysis for Protein Function Prediction Based on Network Data

Inference of protein functions is one of the most important aims of modern biology. To fully exploit the large volumes of genomic data typically produced in modern-day genomic experiments, automated computational methods for protein function prediction are urgently needed. Established methods use sequence or structure similarity to infer functions but those types of data do not suffice to determine the biological context in which proteins act. Current high-throughput biological experiments produce large amounts of data on the interactions between proteins. Such data can be used to infer interaction networks and to predict the biological process that the protein is involved in. Here, we develop a probabilistic approach for protein function prediction using network data, such as protein-protein interaction measurements. We take a Bayesian approach to an existing Markov Random Field method by performing simultaneous estimation of the model parameters and prediction of protein functions. We use an adaptive Markov Chain Monte Carlo algorithm that leads to more accurate parameter estimates and consequently to improved prediction performance compared to the standard Markov Random Fields method. We tested our method using a high quality S.cereviciae validation network with 1622 proteins against 90 Gene Ontology terms of different levels of abstraction. Compared to three other protein function prediction methods, our approach shows very good prediction performance. Our method can be directly applied to protein-protein interaction or coexpression networks, but also can be extended to use multiple data sources. We apply our method to physical protein interaction data from S. cerevisiae and provide novel predictions, using 340 Gene Ontology terms, for 1170 unannotated proteins and we evaluate the predictions using the available literature.

Towards recommendations for metadata and data handling in plant phenotyping

Recent methodological developments in plant phenotyping, as well as the growing importance of its applications in plant science and breeding, are resulting in a fast accumulation of multidimensional data. There is great potential for expediting both discovery and application if these data are made publicly available for analysis. However, collection and storage of phenotypic observations is not yet sufficiently governed by standards that would ensure interoperability among data providers and precisely link specific phenotypes and associated genomic sequence information. This lack of standards is mainly a result of a large variability of phenotyping protocols, the multitude of phenotypic traits that are measured, and the dependence of these traits on the environment. This paper discusses the current situation of standardization in the area of phenomics, points out the problems and shortages, and presents the areas that would benefit from improvement in this field. In addition, the foundations of the work that could revise the situation are proposed, and practical solutions developed by the authors are introduced.

Analysis of functional redundancies within the Arabidopsis TCP transcription factor family

Analyses of the functions of TEOSINTE-LIKE1, CYCLOIDEA, and PROLIFERATING CELL FACTOR1 (TCP) transcription factors have been hampered by functional redundancy between its individual members. In general, putative functionally redundant genes are predicted based on sequence similarity and confirmed by genetic analysis. In the TCP family, however, identification is impeded by relatively low overall sequence similarity. In a search for functionally redundant TCP pairs that control Arabidopsis leaf development, this work performed an integrative bioinformatics analysis, combining protein sequence similarities, gene expression data, and results of pair-wise protein–protein interaction studies for the 24 members of the Arabidopsis TCP transcription factor family. For this, the work completed any lacking gene expression and protein–protein interaction data experimentally and then performed a comprehensive prediction of potential functional redundant TCP pairs. Subsequently, redundant functions could be confirmed for selected predicted TCP pairs by genetic and molecular analyses. It is demonstrated that the previously uncharacterized class I TCP19 gene plays a role in the control of leaf senescence in a redundant fashion with TCP20. Altogether, this work shows the power of combining classical genetic and molecular approaches with bioinformatics predictions to unravel functional redundancies in the TCP transcription factor family.

Comparative analysis indicates that alternative splicing in plants has a limited role in functional expansion of the proteome.

BackgroundAlternative splicing (AS) is a widespread phenomenon in higher eukaryotes but the extent to which it leads to functional protein isoforms and to proteome expansion at large is still a matter of debate. In contrast to animal species, for which AS has been studied extensively at the protein and functional level, protein-centered studies of AS in plant species are scarce. Here we investigate the functional impact of AS in dicot and monocot plant species using a comparative approach.ResultsDetailed comparison of AS events in alternative spliced orthologs from the dicot Arabidopsis thaliana and the monocot Oryza sativa (rice) revealed that the vast majority of AS events in both species do not result from functional conservation. Transcript isoforms that are putative targets for the nonsense-mediated decay (NMD) pathway are as likely to contain conserved AS events as isoforms that are translated into proteins. Similar results were obtained when the same comparison was performed between the two more closely related monocot species rice and Zea mays (maize).Genome-wide computational analysis of functional protein domains encoded in alternatively and constitutively spliced genes revealed that only the RNA recognition motif (RRM) is overrepresented in alternatively spliced genes in all species analyzed. In contrast, three domain types were overrepresented in constitutively spliced genes. AS events were found to be less frequent within than outside predicted protein domains and no domain type was found to be enriched with AS introns. Analysis of AS events that result in the removal of complete protein domains revealed that only a small number of domain types is spliced-out in all species analyzed. Finally, in a substantial fraction of cases where a domain is completely removed, this domain appeared to be a unit of a tandem repeat.ConclusionThe results from the ortholog comparisons suggest that the ability of a gene to produce more than one functional protein through AS does not persist during evolution. Cross-species comparison of the results of the protein-domain oriented analyses indicates little correspondence between the analyzed species. Based on the premise that functional genetic features are most likely to be conserved during evolution, we conclude that AS has only a limited role in functional expansion of the proteome in plants.

Sequence Motifs in MADS Transcription Factors Responsible for Specificity and Diversification of Protein-Protein Interaction

Protein sequences encompass tertiary structures and contain information about specific molecular interactions, which in turn determine biological functions of proteins. Knowledge about how protein sequences define interaction specificity is largely missing, in particular for paralogous protein families with high sequence similarity, such as the plant MADS domain transcription factor family. In comparison to the situation in mammalian species, this important family of transcription regulators has expanded enormously in plant species and contains over 100 members in the model plant species Arabidopsis thaliana. Here, we provide insight into the mechanisms that determine protein-protein interaction specificity for the Arabidopsis MADS domain transcription factor family, using an integrated computational and experimental approach. Plant MADS proteins have highly similar amino acid sequences, but their dimerization patterns vary substantially. Our computational analysis uncovered small sequence regions that explain observed differences in dimerization patterns with reasonable accuracy. Furthermore, we show the usefulness of the method for prediction of MADS domain transcription factor interaction networks in other plant species. Introduction of mutations in the predicted interaction motifs demonstrated that single amino acid mutations can have a large effect and lead to loss or gain of specific interactions. In addition, various performed bioinformatics analyses shed light on the way evolution has shaped MADS domain transcription factor interaction specificity. Identified protein-protein interaction motifs appeared to be strongly conserved among orthologs, indicating their evolutionary importance. We also provide evidence that mutations in these motifs can be a source for sub- or neo-functionalization. The analyses presented here take us a step forward in understanding protein-protein interactions and the interplay between protein sequences and network evolution.

Predicting the impact of alternative splicing on plant MADS domain protein function.

Several genome-wide studies demonstrated that alternative splicing (AS) significantly increases the transcriptome complexity in plants. However, the impact of AS on the functional diversity of proteins is difficult to assess using genome-wide approaches. The availability of detailed sequence annotations for specific genes and gene families allows for a more detailed assessment of the potential effect of AS on their function. One example is the plant MADS-domain transcription factor family, members of which interact to form protein complexes that function in transcription regulation. Here, we perform an in silico analysis of the potential impact of AS on the protein-protein interaction capabilities of MIKC-type MADS-domain proteins. We first confirmed the expression of transcript isoforms resulting from predicted AS events. Expressed transcript isoforms were considered functional if they were likely to be translated and if their corresponding AS events either had an effect on predicted dimerisation motifs or occurred in regions known to be involved in multimeric complex formation, or otherwise, if their effect was conserved in different species. Nine out of twelve MIKC MADS-box genes predicted to produce multiple protein isoforms harbored putative functional AS events according to those criteria. AS events with conserved effects were only found at the borders of or within the K-box domain. We illustrate how AS can contribute to the evolution of interaction networks through an example of selective inclusion of a recently evolved interaction motif in the MADS AFFECTING FLOWERING1-3 (MAF1–3) subclade. Furthermore, we demonstrate the potential effect of an AS event in SHORT VEGETATIVE PHASE (SVP), resulting in the deletion of a short sequence stretch including a predicted interaction motif, by overexpression of the fully spliced and the alternatively spliced SVP transcripts. For most of the AS events we were able to formulate hypotheses about the potential impact on the interaction capabilities of the encoded MIKC proteins.

Valencene synthase from the heartwood of Nootka cypress (Callitropsis nootkatensis) for biotechnological production of valencene

Nootkatone is one of the major terpenes in the heartwood of the Nootka cypress Callitropsis nootkatensis. It is an oxidized sesquiterpene, which has been postulated to be derived from valencene. Both valencene and nootkatone are used for flavouring citrus beverages and are considered among the most valuable terpenes used at commercial scale. Functional evaluation of putative terpene synthase genes sourced by large-scale EST sequencing from Nootka cypress wood revealed a valencene synthase gene (CnVS). CnVS expression in different tissues from the tree correlates well with nootkatone content, suggesting that CnVS represents the first dedicated gene in the nootkatone biosynthetic pathway in C. nootkatensis The gene belongs to the gymnosperm-specific TPS-d subfamily of terpenes synthases and its protein sequence has low similarity to known citrus valencene synthases. In vitro, CnVS displays high robustness under different pH and temperature regimes, potentially beneficial properties for application in different host and physiological conditions. Biotechnological production of sesquiterpenes has been shown to be feasible, but productivity of microbial strains expressing valencene synthase from Citrus is low, indicating that optimization of valencene synthase activity is needed. Indeed, expression of CnVS in Saccharomyces cerevisiae indicated potential for higher yields. In an optimized Rhodobacter sphaeroides strain, expression of CnVS increased valencene yields 14-fold to 352 mg/L, bringing production to levels with industrial potential.

Simulation of Organ Patterning on the Floral Meristem Using a Polar Auxin Transport Model

An intriguing phenomenon in plant development is the timing and positioning of lateral organ initiation, which is a fundamental aspect of plant architecture. Although important progress has been made in elucidating the role of auxin transport in the vegetative shoot to explain the phyllotaxis of leaf formation in a spiral fashion, a model study of the role of auxin transport in whorled organ patterning in the expanding floral meristem is not available yet. We present an initial simulation approach to study the mechanisms that are expected to play an important role. Starting point is a confocal imaging study of Arabidopsis floral meristems at consecutive time points during flower development. These images reveal auxin accumulation patterns at the positions of the organs, which strongly suggests that the role of auxin in the floral meristem is similar to the role it plays in the shoot apical meristem. This is the basis for a simulation study of auxin transport through a growing floral meristem, which may answer the question whether auxin transport can in itself be responsible for the typical whorled floral pattern. We combined a cellular growth model for the meristem with a polar auxin transport model. The model predicts that sepals are initiated by auxin maxima arising early during meristem outgrowth. These form a pre-pattern relative to which a series of smaller auxin maxima are positioned, which partially overlap with the anlagen of petals, stamens, and carpels. We adjusted the model parameters corresponding to properties of floral mutants and found that the model predictions agree with the observed mutant patterns. The predicted timing of the primordia outgrowth and the timing and positioning of the sepal primordia show remarkable similarities with a developing flower in nature.