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Sequence motifs in MADS transcription factors responsible for specificity and diversification of protein-protein interaction.

van Dijk AD, Morabito G, Fiers M, van Ham RC, Angenent GC, Immink RG - PLoS Comput. Biol. (2010)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Plant Research International, Bioscience, Wageningen, The Netherlands.

ABSTRACT
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.

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Effect of motif-based mutations on interaction patterns.(A) Mutations were introduced based on predicted interaction motifs as explained in Figure 2. Different domains in MIKC MADS domain proteins are shown with colored boxes indicating the various regions in which point mutations were introduced. Below these, the various mutant MADS domain proteins that were generated are listed. The descriptions of the mutated proteins are colored based on the domain in which the mutation was generated. The mutated MADS domain proteins are SHORT VEGETATIVE PHASE (SVP1), AGAMOUS LIKE 24 (AGL24), SUPPRESSOR OF OVEREXPRESSION OF CO 1 (SOC1), APETALLA1 (AP1), CAULIFLOWER (CAL), and AGAMOUS (AG). Note that there are two double mutations for which one mutation occurs in the MADS/I domain and one in the K-box. Below each mutated protein, the number of losses and gains of protein-protein interactions in the yeast two-hybrid assay for the mutated proteins in comparison to the native MADS domain proteins is indicated (see Table 1 for interaction partner identities). (B) Histogram of F-scores for prediction of effect of mutants based on randomized input data (see text for details). The arrow indicates the F-score obtained by the predictor trained on experimental input data.
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pcbi-1001017-g003: Effect of motif-based mutations on interaction patterns.(A) Mutations were introduced based on predicted interaction motifs as explained in Figure 2. Different domains in MIKC MADS domain proteins are shown with colored boxes indicating the various regions in which point mutations were introduced. Below these, the various mutant MADS domain proteins that were generated are listed. The descriptions of the mutated proteins are colored based on the domain in which the mutation was generated. The mutated MADS domain proteins are SHORT VEGETATIVE PHASE (SVP1), AGAMOUS LIKE 24 (AGL24), SUPPRESSOR OF OVEREXPRESSION OF CO 1 (SOC1), APETALLA1 (AP1), CAULIFLOWER (CAL), and AGAMOUS (AG). Note that there are two double mutations for which one mutation occurs in the MADS/I domain and one in the K-box. Below each mutated protein, the number of losses and gains of protein-protein interactions in the yeast two-hybrid assay for the mutated proteins in comparison to the native MADS domain proteins is indicated (see Table 1 for interaction partner identities). (B) Histogram of F-scores for prediction of effect of mutants based on randomized input data (see text for details). The arrow indicates the F-score obtained by the predictor trained on experimental input data.

Mentions: All mutations that we introduced led to changes in interactions. Overall, in eight out of 15 cases (∼53%) the mutations we introduced led specifically to loss of interactions, in three cases (∼20%) specifically to gain of interactions, and in the remaining ∼27% of cases, both loss and gain were obtained (Figure 3, Table 1, and Table S6). The number of gains and losses that our IMSS method (“ara_new” model) predicted, displayed a good correlation with the experimentally observed number of gains and losses (Pearson correlation coefficient 0.76, p-value 0.0005). When separating gains and losses, the correlation coefficient values are 0.63 and 0.67, respectively (p-value<0.006).


Sequence motifs in MADS transcription factors responsible for specificity and diversification of protein-protein interaction.

van Dijk AD, Morabito G, Fiers M, van Ham RC, Angenent GC, Immink RG - PLoS Comput. Biol. (2010)

Effect of motif-based mutations on interaction patterns.(A) Mutations were introduced based on predicted interaction motifs as explained in Figure 2. Different domains in MIKC MADS domain proteins are shown with colored boxes indicating the various regions in which point mutations were introduced. Below these, the various mutant MADS domain proteins that were generated are listed. The descriptions of the mutated proteins are colored based on the domain in which the mutation was generated. The mutated MADS domain proteins are SHORT VEGETATIVE PHASE (SVP1), AGAMOUS LIKE 24 (AGL24), SUPPRESSOR OF OVEREXPRESSION OF CO 1 (SOC1), APETALLA1 (AP1), CAULIFLOWER (CAL), and AGAMOUS (AG). Note that there are two double mutations for which one mutation occurs in the MADS/I domain and one in the K-box. Below each mutated protein, the number of losses and gains of protein-protein interactions in the yeast two-hybrid assay for the mutated proteins in comparison to the native MADS domain proteins is indicated (see Table 1 for interaction partner identities). (B) Histogram of F-scores for prediction of effect of mutants based on randomized input data (see text for details). The arrow indicates the F-score obtained by the predictor trained on experimental input data.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2991254&req=5

pcbi-1001017-g003: Effect of motif-based mutations on interaction patterns.(A) Mutations were introduced based on predicted interaction motifs as explained in Figure 2. Different domains in MIKC MADS domain proteins are shown with colored boxes indicating the various regions in which point mutations were introduced. Below these, the various mutant MADS domain proteins that were generated are listed. The descriptions of the mutated proteins are colored based on the domain in which the mutation was generated. The mutated MADS domain proteins are SHORT VEGETATIVE PHASE (SVP1), AGAMOUS LIKE 24 (AGL24), SUPPRESSOR OF OVEREXPRESSION OF CO 1 (SOC1), APETALLA1 (AP1), CAULIFLOWER (CAL), and AGAMOUS (AG). Note that there are two double mutations for which one mutation occurs in the MADS/I domain and one in the K-box. Below each mutated protein, the number of losses and gains of protein-protein interactions in the yeast two-hybrid assay for the mutated proteins in comparison to the native MADS domain proteins is indicated (see Table 1 for interaction partner identities). (B) Histogram of F-scores for prediction of effect of mutants based on randomized input data (see text for details). The arrow indicates the F-score obtained by the predictor trained on experimental input data.
Mentions: All mutations that we introduced led to changes in interactions. Overall, in eight out of 15 cases (∼53%) the mutations we introduced led specifically to loss of interactions, in three cases (∼20%) specifically to gain of interactions, and in the remaining ∼27% of cases, both loss and gain were obtained (Figure 3, Table 1, and Table S6). The number of gains and losses that our IMSS method (“ara_new” model) predicted, displayed a good correlation with the experimentally observed number of gains and losses (Pearson correlation coefficient 0.76, p-value 0.0005). When separating gains and losses, the correlation coefficient values are 0.63 and 0.67, respectively (p-value<0.006).

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Plant Research International, Bioscience, Wageningen, The Netherlands.

ABSTRACT
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.

Show MeSH