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On the origin of mitochondria: a multilayer network approach

BACKGOUND: The endosymbiotic theory is widely accepted to explain the origin of mitochondria from a bacterial ancestor. While ample evidence supports the intimate connection of Alphaproteobacteria to the mitochondrial ancestor, pinpointing its closest relative within sampled Alphaproteobacteria is s...

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Autores principales: Borges, Dérick Gabriel F., Carvalho, Daniel S., Bomfim, Gilberto C., Ramos, Pablo Ivan P., Brzozowski, Jerzy, Góes-Neto, Aristóteles, F. S. Andrade, Roberto, El-Hani, Charbel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9828282/
https://www.ncbi.nlm.nih.gov/pubmed/36632145
http://dx.doi.org/10.7717/peerj.14571
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author Borges, Dérick Gabriel F.
Carvalho, Daniel S.
Bomfim, Gilberto C.
Ramos, Pablo Ivan P.
Brzozowski, Jerzy
Góes-Neto, Aristóteles
F. S. Andrade, Roberto
El-Hani, Charbel
author_facet Borges, Dérick Gabriel F.
Carvalho, Daniel S.
Bomfim, Gilberto C.
Ramos, Pablo Ivan P.
Brzozowski, Jerzy
Góes-Neto, Aristóteles
F. S. Andrade, Roberto
El-Hani, Charbel
author_sort Borges, Dérick Gabriel F.
collection PubMed
description BACKGOUND: The endosymbiotic theory is widely accepted to explain the origin of mitochondria from a bacterial ancestor. While ample evidence supports the intimate connection of Alphaproteobacteria to the mitochondrial ancestor, pinpointing its closest relative within sampled Alphaproteobacteria is still an open evolutionary debate. Many different phylogenetic methods and approaches have been used to answer this challenging question, further compounded by the heterogeneity of sampled taxa, varying evolutionary rates of mitochondrial proteins, and the inherent biases in each method, all factors that can produce phylogenetic artifacts. By harnessing the simplicity and interpretability of protein similarity networks, herein we re-evaluated the origin of mitochondria within an enhanced multilayer framework, which is an extension and improvement of a previously developed method. METHODS: We used a dataset of eight proteins found in mitochondria (N = 6 organisms) and bacteria (N = 80 organisms). The sequences were aligned and resulting identity matrices were combined to generate an eight-layer multiplex network. Each layer corresponded to a protein network, where nodes represented organisms and edges were placed following mutual sequence identity. The Multi-Newman-Girvan algorithm was applied to evaluate community structure, and bifurcation events linked to network partition allowed to trace patterns of divergence between studied taxa. RESULTS: In our network-based analysis, we first examined the topology of the 8-layer multiplex when mitochondrial sequences disconnected from the main alphaproteobacterial cluster. The resulting topology lent firm support toward an Alphaproteobacteria-sister placement for mitochondria, reinforcing the hypothesis that mitochondria diverged from the common ancestor of all Alphaproteobacteria. Additionally, we observed that the divergence of Rickettsiales was an early event in the evolutionary history of alphaproteobacterial clades. CONCLUSION: By leveraging complex networks methods to the challenging question of circumscribing mitochondrial origin, we suggest that the entire Alphaproteobacteria clade is the closest relative to mitochondria (Alphaproteobacterial-sister hypothesis), echoing recent findings based on different datasets and methodologies.
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spelling pubmed-98282822023-01-10 On the origin of mitochondria: a multilayer network approach Borges, Dérick Gabriel F. Carvalho, Daniel S. Bomfim, Gilberto C. Ramos, Pablo Ivan P. Brzozowski, Jerzy Góes-Neto, Aristóteles F. S. Andrade, Roberto El-Hani, Charbel PeerJ Bioinformatics BACKGOUND: The endosymbiotic theory is widely accepted to explain the origin of mitochondria from a bacterial ancestor. While ample evidence supports the intimate connection of Alphaproteobacteria to the mitochondrial ancestor, pinpointing its closest relative within sampled Alphaproteobacteria is still an open evolutionary debate. Many different phylogenetic methods and approaches have been used to answer this challenging question, further compounded by the heterogeneity of sampled taxa, varying evolutionary rates of mitochondrial proteins, and the inherent biases in each method, all factors that can produce phylogenetic artifacts. By harnessing the simplicity and interpretability of protein similarity networks, herein we re-evaluated the origin of mitochondria within an enhanced multilayer framework, which is an extension and improvement of a previously developed method. METHODS: We used a dataset of eight proteins found in mitochondria (N = 6 organisms) and bacteria (N = 80 organisms). The sequences were aligned and resulting identity matrices were combined to generate an eight-layer multiplex network. Each layer corresponded to a protein network, where nodes represented organisms and edges were placed following mutual sequence identity. The Multi-Newman-Girvan algorithm was applied to evaluate community structure, and bifurcation events linked to network partition allowed to trace patterns of divergence between studied taxa. RESULTS: In our network-based analysis, we first examined the topology of the 8-layer multiplex when mitochondrial sequences disconnected from the main alphaproteobacterial cluster. The resulting topology lent firm support toward an Alphaproteobacteria-sister placement for mitochondria, reinforcing the hypothesis that mitochondria diverged from the common ancestor of all Alphaproteobacteria. Additionally, we observed that the divergence of Rickettsiales was an early event in the evolutionary history of alphaproteobacterial clades. CONCLUSION: By leveraging complex networks methods to the challenging question of circumscribing mitochondrial origin, we suggest that the entire Alphaproteobacteria clade is the closest relative to mitochondria (Alphaproteobacterial-sister hypothesis), echoing recent findings based on different datasets and methodologies. PeerJ Inc. 2023-01-06 /pmc/articles/PMC9828282/ /pubmed/36632145 http://dx.doi.org/10.7717/peerj.14571 Text en © 2023 Borges et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Borges, Dérick Gabriel F.
Carvalho, Daniel S.
Bomfim, Gilberto C.
Ramos, Pablo Ivan P.
Brzozowski, Jerzy
Góes-Neto, Aristóteles
F. S. Andrade, Roberto
El-Hani, Charbel
On the origin of mitochondria: a multilayer network approach
title On the origin of mitochondria: a multilayer network approach
title_full On the origin of mitochondria: a multilayer network approach
title_fullStr On the origin of mitochondria: a multilayer network approach
title_full_unstemmed On the origin of mitochondria: a multilayer network approach
title_short On the origin of mitochondria: a multilayer network approach
title_sort on the origin of mitochondria: a multilayer network approach
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9828282/
https://www.ncbi.nlm.nih.gov/pubmed/36632145
http://dx.doi.org/10.7717/peerj.14571
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