Using Functional Annotations to Study Pairwise Interactions in Urinary Tract Infection Communities
The behaviour of microbial communities depends on environmental factors and on the interactions of the community members. This is also the case for urinary tract infection (UTI) microbial communities. Here, we devise a computational approach that uses indices of complementarity and competition based...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-08-01
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| Series: | Genes |
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| Online Access: | https://www.mdpi.com/2073-4425/12/8/1221 |
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| author | Elena G. Lara Isabelle van der Windt Douwe Molenaar Marjon G. J. de Vos Chrats Melkonian |
| author_facet | Elena G. Lara Isabelle van der Windt Douwe Molenaar Marjon G. J. de Vos Chrats Melkonian |
| author_sort | Elena G. Lara |
| collection | DOAJ |
| description | The behaviour of microbial communities depends on environmental factors and on the interactions of the community members. This is also the case for urinary tract infection (UTI) microbial communities. Here, we devise a computational approach that uses indices of complementarity and competition based on metabolic gene annotation to rapidly predict putative interactions between pair of organisms with the aim to explain pairwise growth effects. We apply our method to 66 genomes selected from online databases, which belong to 6 genera representing members of UTI communities. This resulted in a selection of metabolic pathways with high correlation for each pairwise combination between a complementarity index and the experimentally derived growth data. Our results indicated that <i>Enteroccus</i> spp. were most complemented in its metabolism by the other members of the UTI community. This suggests that the growth of <i>Enteroccus</i> spp. can potentially be enhanced by complementary metabolites produced by other community members. We tested a few putative predicted interactions by experimental supplementation of the relevant predicted metabolites. As predicted by our method, folic acid supplementation led to the increase in the population density of UTI <i>Enterococcus</i> isolates. Overall, we believe our method is a rapid initial in silico screening for the prediction of metabolic interactions in microbial communities. |
| first_indexed | 2024-03-10T08:47:38Z |
| format | Article |
| id | doaj.art-465b4e84e9e148088d914f72dd9923e5 |
| institution | Directory Open Access Journal |
| issn | 2073-4425 |
| language | English |
| last_indexed | 2024-03-10T08:47:38Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Genes |
| spelling | doaj.art-465b4e84e9e148088d914f72dd9923e52023-11-22T07:46:15ZengMDPI AGGenes2073-44252021-08-01128122110.3390/genes12081221Using Functional Annotations to Study Pairwise Interactions in Urinary Tract Infection CommunitiesElena G. Lara0Isabelle van der Windt1Douwe Molenaar2Marjon G. J. de Vos3Chrats Melkonian4Systems Biology Lab, AIMMS, Vrije Universiteit, 1081 HZ Amsterdam, The NetherlandsGELIFES, Universtity of Groningen, 9747 AG Groningen, The NetherlandsSystems Biology Lab, AIMMS, Vrije Universiteit, 1081 HZ Amsterdam, The NetherlandsGELIFES, Universtity of Groningen, 9747 AG Groningen, The NetherlandsSystems Biology Lab, AIMMS, Vrije Universiteit, 1081 HZ Amsterdam, The NetherlandsThe behaviour of microbial communities depends on environmental factors and on the interactions of the community members. This is also the case for urinary tract infection (UTI) microbial communities. Here, we devise a computational approach that uses indices of complementarity and competition based on metabolic gene annotation to rapidly predict putative interactions between pair of organisms with the aim to explain pairwise growth effects. We apply our method to 66 genomes selected from online databases, which belong to 6 genera representing members of UTI communities. This resulted in a selection of metabolic pathways with high correlation for each pairwise combination between a complementarity index and the experimentally derived growth data. Our results indicated that <i>Enteroccus</i> spp. were most complemented in its metabolism by the other members of the UTI community. This suggests that the growth of <i>Enteroccus</i> spp. can potentially be enhanced by complementary metabolites produced by other community members. We tested a few putative predicted interactions by experimental supplementation of the relevant predicted metabolites. As predicted by our method, folic acid supplementation led to the increase in the population density of UTI <i>Enterococcus</i> isolates. Overall, we believe our method is a rapid initial in silico screening for the prediction of metabolic interactions in microbial communities.https://www.mdpi.com/2073-4425/12/8/1221urinary tract infectionmicrobial communitymicrobial interactiongene annotation |
| spellingShingle | Elena G. Lara Isabelle van der Windt Douwe Molenaar Marjon G. J. de Vos Chrats Melkonian Using Functional Annotations to Study Pairwise Interactions in Urinary Tract Infection Communities Genes urinary tract infection microbial community microbial interaction gene annotation |
| title | Using Functional Annotations to Study Pairwise Interactions in Urinary Tract Infection Communities |
| title_full | Using Functional Annotations to Study Pairwise Interactions in Urinary Tract Infection Communities |
| title_fullStr | Using Functional Annotations to Study Pairwise Interactions in Urinary Tract Infection Communities |
| title_full_unstemmed | Using Functional Annotations to Study Pairwise Interactions in Urinary Tract Infection Communities |
| title_short | Using Functional Annotations to Study Pairwise Interactions in Urinary Tract Infection Communities |
| title_sort | using functional annotations to study pairwise interactions in urinary tract infection communities |
| topic | urinary tract infection microbial community microbial interaction gene annotation |
| url | https://www.mdpi.com/2073-4425/12/8/1221 |
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