Mots-Clés

comparative genomics protein targeting evolution yeasts mitochondria

Description

Mitochondria and Chloroplasts arose through endosymbiosis and retain their own genomes, yet the vast majority of organellar proteins is encoded in the nucleus, translated in the cytosol and imported into the organelles (Wiedemann and Pfanner 2017; Chotewutmontri et al. 2017). Most nuclear-encoded proteins found in organelles harbor a targeting peptide (TP) at their N-terminal end, determining their subcellular localization. It has been shown in yeast, that some proteins targeted to mitochondria harbor additional targeting-like sequences, located in the internal part of the protein, that are proposed to enhance the efficiency of the protein import, via binding to Tom70, a receptor of the translocase of the outer membrane of mitochondria (TOM) (Backes et al. 2018). Were internal targeting-like sequences already present in bacterial homologs, before the endosymbiosis, or were they acquired in eukaryotes to enhance targeting, early after the emergence of the mitochondria or later in specific eukaryotic groups? In the latter case, how did they arise? From chromosomal rearrangements or “de novo” from previously non-targeting sequences? (Garrido et al. 2020; Caspari et al. 2021)

The goal of this proposal is to systematically determine the presence/absence of internal TP-like sequences among protein families conserved from bacteria to eukaryotes in order to retrace their evolutionary history. We will also compare them, at the molecular level, to the classical N-terminal targeting sequences to establish their contrasting properties.

Classical comparative genomics approaches will be used (multiple alignments, gene tree phylogenies, inference of gains/losses by phyletic pattern analysis), together with machine learning approaches to identify targeting peptides based on their primary sequence and/or their physico-chemical properties, that was developed in the lab or by collaborators. Those approaches are already available in the lab, with room for improvements.

We are looking for a candidate interested in the fundamental mechanisms of genetics and genome evolution, with strong skills in programming and statistical analysi