Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours
Abstract Despite the current wealth of sequencing data, one‐third of all biochemically characterized metabolic enzymes lack a corresponding gene or protein sequence, and as such can be considered orphan enzymes. They represent a major gap between our molecular and biochemical knowledge, and conseque...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Springer Nature
2012-05-01
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| Series: | Molecular Systems Biology |
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| Online Access: | https://doi.org/10.1038/msb.2012.13 |
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| _version_ | 1849389479736901632 |
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| author | Takuji Yamada Alison S Waller Jeroen Raes Aleksej Zelezniak Nadia Perchat Alain Perret Marcel Salanoubat Kiran R Patil Jean Weissenbach Peer Bork |
| author_facet | Takuji Yamada Alison S Waller Jeroen Raes Aleksej Zelezniak Nadia Perchat Alain Perret Marcel Salanoubat Kiran R Patil Jean Weissenbach Peer Bork |
| author_sort | Takuji Yamada |
| collection | DOAJ |
| description | Abstract Despite the current wealth of sequencing data, one‐third of all biochemically characterized metabolic enzymes lack a corresponding gene or protein sequence, and as such can be considered orphan enzymes. They represent a major gap between our molecular and biochemical knowledge, and consequently are not amenable to modern systemic analyses. As 555 of these orphan enzymes have metabolic pathway neighbours, we developed a global framework that utilizes the pathway and (meta)genomic neighbour information to assign candidate sequences to orphan enzymes. For 131 orphan enzymes (37% of those for which (meta)genomic neighbours are available), we associate sequences to them using scoring parameters with an estimated accuracy of 70%, implying functional annotation of 16 345 gene sequences in numerous (meta)genomes. As a case in point, two of these candidate sequences were experimentally validated to encode the predicted activity. In addition, we augmented the currently available genome‐scale metabolic models with these new sequence–function associations and were able to expand the models by on average 8%, with a considerable change in the flux connectivity patterns and improved essentiality prediction. |
| format | Article |
| id | doaj-art-fa24e5949f5f4ce1828fa5e67e126118 |
| institution | Kabale University |
| issn | 1744-4292 |
| language | English |
| publishDate | 2012-05-01 |
| publisher | Springer Nature |
| record_format | Article |
| series | Molecular Systems Biology |
| spelling | doaj-art-fa24e5949f5f4ce1828fa5e67e1261182025-08-20T03:41:57ZengSpringer NatureMolecular Systems Biology1744-42922012-05-018111210.1038/msb.2012.13Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighboursTakuji Yamada0Alison S Waller1Jeroen Raes2Aleksej Zelezniak3Nadia Perchat4Alain Perret5Marcel Salanoubat6Kiran R Patil7Jean Weissenbach8Peer Bork9Structural and Computational Biology Unit, European Molecular Biology LaboratoryStructural and Computational Biology Unit, European Molecular Biology LaboratoryMolecular and Cellular Interactions Department, VIBStructural and Computational Biology Unit, European Molecular Biology LaboratoryCommissariat à l'Energie AtomiqueCommissariat à l'Energie AtomiqueCommissariat à l'Energie AtomiqueStructural and Computational Biology Unit, European Molecular Biology LaboratoryCommissariat à l'Energie AtomiqueStructural and Computational Biology Unit, European Molecular Biology LaboratoryAbstract Despite the current wealth of sequencing data, one‐third of all biochemically characterized metabolic enzymes lack a corresponding gene or protein sequence, and as such can be considered orphan enzymes. They represent a major gap between our molecular and biochemical knowledge, and consequently are not amenable to modern systemic analyses. As 555 of these orphan enzymes have metabolic pathway neighbours, we developed a global framework that utilizes the pathway and (meta)genomic neighbour information to assign candidate sequences to orphan enzymes. For 131 orphan enzymes (37% of those for which (meta)genomic neighbours are available), we associate sequences to them using scoring parameters with an estimated accuracy of 70%, implying functional annotation of 16 345 gene sequences in numerous (meta)genomes. As a case in point, two of these candidate sequences were experimentally validated to encode the predicted activity. In addition, we augmented the currently available genome‐scale metabolic models with these new sequence–function associations and were able to expand the models by on average 8%, with a considerable change in the flux connectivity patterns and improved essentiality prediction.https://doi.org/10.1038/msb.2012.13genomicsmetabolic pathwaysmetagenomicsneighbourhood informationorphan enzymes |
| spellingShingle | Takuji Yamada Alison S Waller Jeroen Raes Aleksej Zelezniak Nadia Perchat Alain Perret Marcel Salanoubat Kiran R Patil Jean Weissenbach Peer Bork Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours Molecular Systems Biology genomics metabolic pathways metagenomics neighbourhood information orphan enzymes |
| title | Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours |
| title_full | Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours |
| title_fullStr | Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours |
| title_full_unstemmed | Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours |
| title_short | Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours |
| title_sort | prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours |
| topic | genomics metabolic pathways metagenomics neighbourhood information orphan enzymes |
| url | https://doi.org/10.1038/msb.2012.13 |
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