Biology subjects

Pellarin, R.

Publications and source records attributed to Pellarin, R..

3 recordsLinked to original sources

bioRxiv2018

In situ and high-resolution Cryo-EM structure of the Type VI secretion membrane complex

Bacteria have evolved macromolecular machineries that secrete effectors and toxins to survive and thrive in diverse environments. The type VI secretion system (T6SS) is a contractile machine that is related to Myoviridae phages. The T6SS is composed of a baseplate that contains a spike onto which an inner tube is built, surrounded by a contractile sheath. Unlike phages that are released to and act in the extracellular medium, the T6SS is an intracellular machine inserted in the bacterial membranes by a trans-envelope complex. This membrane complex (MC) comprises three proteins: TssJ, TssL and TssM. We previously reported the low-resolution negative stain electron microscopy structure of the enteroaggregative Escherichia coli MC and proposed a rotational 5-fold symmetry with a TssJ:TssL:TssM stoichiometry of 2:2:2. Here, cryo-electron tomography analysis of the T6SS MC confirmed the 5-fold symmetry in situ and identified the regions of the structure that insert into the bacterial membranes. A high resolution model obtained by single particle cryo-electron microscopy reveals its global architecture and highlights new features: five additional copies of TssJ, yielding a TssJ:TssL:TssM stoichiometry of 3:2:2, a 11-residue loop in TssM, protruding inside the lumen of the MC and constituting a functionally important periplasmic gate, and hinge regions. Based on these data, we revisit the model on the mechanism of action of the MC during T6SS assembly and function.

microbiology↗

bioRxiv2017

Simultaneous Determination of Protein Structure and Dynamics Using Cryo-Electron Microscopy

Cryo-electron microscopy is rapidly emerging as a powerful technique to determine the structures of complex macromolecular systems elusive to other techniques. Since many of these systems are highly dynamical, characterising also their movements is a crucial step to unravel their biological functions. To achieve this goal, we report an integrative modelling approach to simultaneously determine structure and dynamics from cryo-electron microscopy density maps. By quantifying the level of noise in the data and dealing with their ensemble-averaged nature, this approach enables the integration of multiple sources of information to model ensembles of structures and infer their populations. We illustrate the method by characterising structure and dynamics of the integral membrane receptor STRA6, thus providing insights into the mechanisms by which it interacts with retinol binding protein and translocates retinol across the membrane.

bioinformatics↗

bioRxiv2017

Multi-scale Bayesian modeling of cryo-electron microscopy density maps

SummaryCryo-electron microscopy (cryo-EM) has become a mainstream technique for determining the structures of complex biological systems. However, accurate integrative structural modeling has been hampered by the challenges in objectively weighing cryo-EM data against other sources of information due to the presence of random and systematic errors, as well as correlations, in the data. To address these challenges, we introduce a Bayesian scoring function that efficiently and accurately ranks alternative structural models of a macromolecular system based on their consistency with a cryo-EM density map and other experimental and prior information. The accuracy of this approach is benchmarked using complexes of known structure and illustrated in three applications: the structural determination of the GroEL/GroES, RNA polymerase II, and exosome complexes. The approach is implemented in the open-source Integrative Modeling Platform (http://integrativemodeling.org), thus enabling integrative structure determination by combining cryo-EM data with other sources of information.\n\nHighlightsO_LIWe present a modeling approach to integrate cryo-EM data with other sources of information\nC_LIO_LIWe benchmark our approach using synthetic data on 21 complexes of known structure\nC_LIO_LIWe apply our approach to the GroEL/GroES, RNA polymerase II, and exosome complexes\nC_LI

bioinformatics↗