On the origin of mitochondria: a multilayer network approach.


Journal

PeerJ
ISSN: 2167-8359
Titre abrégé: PeerJ
Pays: United States
ID NLM: 101603425

Informations de publication

Date de publication:
2023
Historique:
received: 21 12 2021
accepted: 28 11 2022
entrez: 12 1 2023
pubmed: 13 1 2023
medline: 14 1 2023
Statut: epublish

Résumé

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. We used a dataset of eight proteins found in mitochondria ( 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. 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.

Identifiants

pubmed: 36632145
doi: 10.7717/peerj.14571
pii: 14571
pmc: PMC9828282
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e14571

Informations de copyright

© 2023 Borges et al.

Déclaration de conflit d'intérêts

Aristóteles Góes-Neto is an Academic Editor for PeerJ.

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Auteurs

Dérick Gabriel F Borges (DGF)

Institute of Physics, Federal University of Bahia, Salvador, Bahia, Brazil.

Daniel S Carvalho (DS)

Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.

Gilberto C Bomfim (GC)

Institute of Biology, Federal University of Bahia, Salvador, Bahia, Brazil.

Pablo Ivan P Ramos (PIP)

Gonçalo Moniz Institute, Oswaldo Cruz Foundation, Salvador, Bahia, Brazil.

Jerzy Brzozowski (J)

Philosophy Department, Federal University of Santa Catarina, Florianópolis, Santa Catarina, Brazil.

Aristóteles Góes-Neto (A)

Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
Graduate Program in Bioinformatics, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.

Roberto Andrade (R)

Institute of Physics, Federal University of Bahia, Salvador, Bahia, Brazil.
National Institute of Science and Technology in Interdisciplinary and Transdisciplinary Studies in Ecology and Evolution (INCT IN-TREE), Salvador, Bahia, Brazil.

Charbel El-Hani (C)

Institute of Biology, Federal University of Bahia, Salvador, Bahia, Brazil.
National Institute of Science and Technology in Interdisciplinary and Transdisciplinary Studies in Ecology and Evolution (INCT IN-TREE), Salvador, Bahia, Brazil.

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