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Predicted protein-protein interactions in the moss Physcomitrella patens: a new bioinformatic resource.

Schuette S, Piatkowski B, Corley A, Lang D, Geisler M - BMC Bioinformatics (2015)

Bottom Line: This method has been used to successfully predict interactions for a number of angiosperm plants.Most conserved interactions among proteins were those associated with metabolic processes.Included with this dataset is a method for characterizing subnetworks and investigating specific processes, such as the Calvin-Benson-Bassham cycle.

View Article: PubMed Central - PubMed

Affiliation: Department of Plant Biology, Southern Illinois University, Carbondale, IL, USA. swschuette@gmail.com.

ABSTRACT

Background: Physcomitrella patens, a haploid dominant plant, is fast becoming a useful molecular genetics and bioinformatics tool due to its key phylogenetic position as a bryophyte in the post-genomic era. Genome sequences from select reference species were compared bioinformatically to Physcomitrella patens using reciprocal blasts with the InParanoid software package. A reference protein interaction database assembled using MySQL by compiling BioGrid, BIND, DIP, and Intact databases was queried for moss orthologs existing for both interacting partners. This method has been used to successfully predict interactions for a number of angiosperm plants.

Results: The first predicted protein-protein interactome for a bryophyte based on the interolog method contains 67,740 unique interactions from 5,695 different Physcomitrella patens proteins. Most conserved interactions among proteins were those associated with metabolic processes. Over-represented Gene Ontology categories are reported here.

Conclusion: Addition of moss, a plant representative 200 million years diverged from angiosperms to interactomic research greatly expands the possibility of conducting comparative analyses giving tremendous insight into network evolution of land plants. This work helps demonstrate the utility of "guilt-by-association" models for predicting protein interactions, providing provisional roadmaps that can be explored using experimental approaches. Included with this dataset is a method for characterizing subnetworks and investigating specific processes, such as the Calvin-Benson-Bassham cycle.

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A bait and prey method was used to reconstruct a sub-network using thePhyscomitrellapredicted interactome. Two proteins known to be involved in the Calvin-Benson-Bassham cycle were used as bait (blue color nodes) and their first neighbors are the captured prey (green color nodes). These two known CBB-cycle proteins do not directly interact, but interact with several other proteins that serve as intermediates. Additional file 8: Table S7 contains the complete protein list and annotations used for this analysis.
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Fig7: A bait and prey method was used to reconstruct a sub-network using thePhyscomitrellapredicted interactome. Two proteins known to be involved in the Calvin-Benson-Bassham cycle were used as bait (blue color nodes) and their first neighbors are the captured prey (green color nodes). These two known CBB-cycle proteins do not directly interact, but interact with several other proteins that serve as intermediates. Additional file 8: Table S7 contains the complete protein list and annotations used for this analysis.

Mentions: This Physcomitrella interactome can be used to analyze specific subnetworks and further characterize key interacting proteins. Using the interactome, one can view interactions between proteins that are known to be involved in a certain processes (bait) and others that directly interact with the bait (prey). Of all known CBB-associated proteins, 23 were found to exist in the dataset and were chosen as bait resulting in a prey capture 242 proteins (Figure 7, Additional file 8: Table S7). Finding key prey proteins can be accomplished by look at the ratio of that protein’s connectivity within the subnetwork to its overall connectivity. Prey proteins that exclusively occur in this subnetwork include a carbohydrate transmembrane transporter (Pp1s88_88V6.1), isocitrate dehydrogenase (Pp1s78_143V6.1), glycosyltransferase (Pp1s90_132V6.1), UDP-acetylglucosamine acyltransferase (Pp1s377_21V6.1), and a protein with a domain of unknown function (Pp1s30_41V6.1). The average connectivity ratio in this subnetwork was 0.33 suggesting that many of these proteins are specific to this process. Reconstruction of subnetworks is aided through this “bait and prey” model and can help elucidate mechanisms that emerge from the network’s activity.Figure 7


Predicted protein-protein interactions in the moss Physcomitrella patens: a new bioinformatic resource.

Schuette S, Piatkowski B, Corley A, Lang D, Geisler M - BMC Bioinformatics (2015)

A bait and prey method was used to reconstruct a sub-network using thePhyscomitrellapredicted interactome. Two proteins known to be involved in the Calvin-Benson-Bassham cycle were used as bait (blue color nodes) and their first neighbors are the captured prey (green color nodes). These two known CBB-cycle proteins do not directly interact, but interact with several other proteins that serve as intermediates. Additional file 8: Table S7 contains the complete protein list and annotations used for this analysis.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4384322&req=5

Fig7: A bait and prey method was used to reconstruct a sub-network using thePhyscomitrellapredicted interactome. Two proteins known to be involved in the Calvin-Benson-Bassham cycle were used as bait (blue color nodes) and their first neighbors are the captured prey (green color nodes). These two known CBB-cycle proteins do not directly interact, but interact with several other proteins that serve as intermediates. Additional file 8: Table S7 contains the complete protein list and annotations used for this analysis.
Mentions: This Physcomitrella interactome can be used to analyze specific subnetworks and further characterize key interacting proteins. Using the interactome, one can view interactions between proteins that are known to be involved in a certain processes (bait) and others that directly interact with the bait (prey). Of all known CBB-associated proteins, 23 were found to exist in the dataset and were chosen as bait resulting in a prey capture 242 proteins (Figure 7, Additional file 8: Table S7). Finding key prey proteins can be accomplished by look at the ratio of that protein’s connectivity within the subnetwork to its overall connectivity. Prey proteins that exclusively occur in this subnetwork include a carbohydrate transmembrane transporter (Pp1s88_88V6.1), isocitrate dehydrogenase (Pp1s78_143V6.1), glycosyltransferase (Pp1s90_132V6.1), UDP-acetylglucosamine acyltransferase (Pp1s377_21V6.1), and a protein with a domain of unknown function (Pp1s30_41V6.1). The average connectivity ratio in this subnetwork was 0.33 suggesting that many of these proteins are specific to this process. Reconstruction of subnetworks is aided through this “bait and prey” model and can help elucidate mechanisms that emerge from the network’s activity.Figure 7

Bottom Line: This method has been used to successfully predict interactions for a number of angiosperm plants.Most conserved interactions among proteins were those associated with metabolic processes.Included with this dataset is a method for characterizing subnetworks and investigating specific processes, such as the Calvin-Benson-Bassham cycle.

View Article: PubMed Central - PubMed

Affiliation: Department of Plant Biology, Southern Illinois University, Carbondale, IL, USA. swschuette@gmail.com.

ABSTRACT

Background: Physcomitrella patens, a haploid dominant plant, is fast becoming a useful molecular genetics and bioinformatics tool due to its key phylogenetic position as a bryophyte in the post-genomic era. Genome sequences from select reference species were compared bioinformatically to Physcomitrella patens using reciprocal blasts with the InParanoid software package. A reference protein interaction database assembled using MySQL by compiling BioGrid, BIND, DIP, and Intact databases was queried for moss orthologs existing for both interacting partners. This method has been used to successfully predict interactions for a number of angiosperm plants.

Results: The first predicted protein-protein interactome for a bryophyte based on the interolog method contains 67,740 unique interactions from 5,695 different Physcomitrella patens proteins. Most conserved interactions among proteins were those associated with metabolic processes. Over-represented Gene Ontology categories are reported here.

Conclusion: Addition of moss, a plant representative 200 million years diverged from angiosperms to interactomic research greatly expands the possibility of conducting comparative analyses giving tremendous insight into network evolution of land plants. This work helps demonstrate the utility of "guilt-by-association" models for predicting protein interactions, providing provisional roadmaps that can be explored using experimental approaches. Included with this dataset is a method for characterizing subnetworks and investigating specific processes, such as the Calvin-Benson-Bassham cycle.

Show MeSH