Biology subjects

Puente-Lelievre, C.

Publications and source records attributed to Puente-Lelievre, C..

5 recordsLinked to original sources

bioRxiv2025

The prokaryotic origins of the COMMD protein family involved in eukaryotic membrane trafficking

The ten eukaryotic COMMD proteins are core components of the Commander complex, with central roles in endosomal membrane trafficking and signalling. Each protein has an -helical N-terminal (HN) domain with a C-terminal copper metabolism gene MURR1 (COMM) domain. These ten family members assemble into a heterodecameric ring composed of five specific heterodimers. In this work we have combined structural homology searches with genome-wide predicted structures to identify ancestral COMMD-like proteins that exist as single genes in Bacteria and Archaea. Although there is limited sequence similarity to the eukaryotic proteins the bacterial and archaeal COMMD-like proteins are predicted to form homomeric ring-shaped assemblies like their eukaryotic counterparts. Our biophysical studies, crystal and cryo-EM structures confirm COMMD-like proteins readily form homooligomeric rings composed of eight or ten subunits assembled from core dimeric building blocks and inter-dimer interactions that are analogous to the heterodecameric core structure of the eukaryotic Commander complex. Phylogenetic analyses using amino acid sequences and FoldSeek structural alphabet (3Di) infer that the closest identified relatives to the eukaryotic COMMD proteins are found in Myxococcota bacteria. These findings indicate that COMMD genes emerged early in eukaryotic evolution through multiple rounds of duplication from a single ancestral gene likely acquired from bacteria.

biochemistry↗

bioRxiv2025

Adding 3Di characters to amino acid datasets can improve resolution, but the effect is weaker in shorter and alpha-helical proteins such as histones

The recent introduction of Foldseeks 3Di character alphabet to encode 3D protein structure has opened up new possibilities for structural phylogenetics. These characters, like protein structure, are more conserved than amino acids, raising the possibility of better resolution of very deep branches on the tree of life. As 3Di characters have a 20-letter alphabet, they are readily treatable with off-the-shelf algorithms for model-based phylogenetic inference and related methods such as bootstrapping. However, it remains to be seen if 3Di phylogenies are broadly more resolved than sequence-based phylogenies. We present data using samples from nine protein superfamilies showing that 3Di combines with sequence to produce better resolved phylogenies than either sequence or 3Di alone. We also show that information-theoretic measures, applied to superfamily alignments, significantly correlate with resolution in phylogenies derived from these alignments. Further, we identify the proportion of alpha helices in proteins as a major driver in reducing the information carried by 3Di character alignments, explaining the relatively poor performance of 3Di characters on superfamilies with highly-conserved structure but high alpha helical content. Our results provide encouragement for the further use of 3Di to address challenging questions in deep history, but also sound a note of caution about which proteins it is most suitable for. SIGNIFICANCE3Di characters have been suggested as a method to generate well-resolved deep phylogenies. Our results show that 3Di characters combined with sequences can improve resolution in the deepest nodes of protein superfamily trees. However, our results also show that 3Di characters may not be suitable for all protein types.

evolutionary biology↗

bioRxiv2024

Molecular and structural innovations of the stator motor complex at the dawn of flagellar motility

The rotation of the bacterial flagellum is powered by the MotAB stator complex, which converts ion flux into torque. The origin and evolution of this remarkable complex is understudied. Here, we perform the first phylogenetic and structural characterisation and classification of MotAB and nonflagellar relatives. Using 193 genomes sampled across 27 bacterial phyla, we estimated phylogenies and ancestral sequences, and generated AlphaFold predictions for all extant and reconstructed proteins. We then mapped them onto the phylogeny to determine patterns of diversity and distribution of structural innovations. We identify two discrete groups: the Flagellar Ion Transporters (FIT) and the Generic Ion Transporters (GIT). The FIT proteins are structurally conserved and have a square fold domain and a torque-generating interface (TGI). FIT proteins are divided into two clades, termed TGI4 and TGI5, referring to whether there have 4 or 5 short helices in the TGI. TGI5 motors are predominantly found in Proteobacteria and include the well-studied E. coli K12 system, while TGI4 motors are found in diverse phyla and include the Na+-powered polar motors of Vibrio (PomAB). The GIT proteins, on the other hand, are structurally diverse and lack these attributes. The interaction between the A and B subunits is conserved across the FIT and GIT proteins. The two subunits are jointly necessary for function, with the genes typically adjacent within an operon. Motility assays in E. coli show that the structural elements unique to FIT play an important role in flagellar motility. Our results indicate that the stator motor complex has a single origin and shares unique motility-related structural traits. Significance StatementFlagellar motility is a key feature in bacterial pathogenicity and survival. It allows bacteria to propel themselves and direct movement according to environmental conditions. We investigated the molecular and structural diversity of the stator motor proteins that provide the ion motive force to power flagellar rotation. This study integrates phylogenetics, 3D protein structure modeling, motility assays and ancestral state reconstruction (ASR) to provide insights into the structural mechanisms that first powered the flagellar motor. We provide the first phylogenetic and structural characterisation and classification of MotAB and relatives.

evolutionary biology↗

bioRxiv2024

On use of tertiary structure characters in hidden Markov models for protein fold prediction

While advances in protein structure prediction have opened up insights into arcane proteins, weak sequence homology makes functional characterisation challenging. To overcome this challenge, we use structure-based hidden Markov models of groupings in SCOP, CATH and ECOD to predict folds in proteins and thereby infer function. Conservation of structure and ability of hidden Markov models to detect remote signals make this a powerful resource for complete characterisation of arcane proteins.

bioinformatics↗

bioRxiv2023

Tertiary-interaction characters enable fast, model-based structural phylogenetics beyond the twilight zone

Protein structure is more conserved than protein sequence, and therefore may be useful for phylogenetic inference beyond the "twilight zone" where sequence similarity is highly decayed. Until recently, structural phylogenetics was constrained by the lack of solved structures for most proteins, and the reliance on phylogenetic distance methods which made it difficult to treat inference and uncertainty statistically. AlphaFold has mostly overcome the first problem by making structural predictions readily available. We address the second problem by redeploying a structural alphabet recently developed for Foldseek, a highly-efficient deep homology search program. For each residue in a structure, Foldseek identifies a tertiary interaction closest-neighbor residue in the structure, and classifies it into one of twenty "3Di" states. We test the hypothesis that 3Dis can be used as standard phylogenetic characters using a dataset of 53 structures from the ferritin-like superfamily. We performed 60 IQtree Maximum Likelihood runs to compare structure-free, PDB, and AlphaFold analyses, and default versus custom model sets that include a 3DI-specific rate matrix. Analyses that combine amino acids, 3Di characters, partitioning, and custom models produce the closest match to the structural distances tree of Malik et al. (2020), avoiding the long-branch attraction errors of structure-free analyses. Analyses include standard ultrafast bootstrapping confidence measures, and take minutes instead of weeks to run on desktop computers. These results suggest that structural phylogenetics could soon be routine practice in protein phylogenetics, allowing the re-exploration of many fundamental phylogenetic problems.

evolutionary biology↗