Reconstruction of plasmids by shotgun sequencing from environmental DNA: which bioinformatic workflow?

Plasmids play important roles in microbial evolution and also in the spread of antibiotic resistance. Plasmid sequences are extensively studied from clinical isolates but rarely from the environment with a metagenomic approach focused on the plasmid fraction referred to as the plasmidome. A clear challenge in this context is to define a workflow for discriminating plasmids from chromosomal contaminants existing in the plasmidome. For this purpose, we benchmarked existing tools from assembly to detection of the plasmids by reference-free methods (cBar and PlasFlow) and database-guided approaches. Our simulations took into account short-reads alone or combined with moderate long-reads like those actually generated in environmental genomics experiments. This benchmark allowed us to select the best tools for limiting false-positives associated to plasmid prediction tools and a combination of reference-guided methods based on plasmid and bacterial databases.

Facilitating CG Simulations with MAD: The MArtini Database Server.

The MArtini Database (MAD - https://mad.ibcp.fr) is a web server designed for the sharing of structures and topologies of molecules parametrized with the Martini coarse-grained (CG) force field. MAD can also convert atomistic structures into CG structures and prepare complex systems (including proteins, lipids, etc.) for molecular dynamics (MD) simulations at the CG level. It is dedicated to the generation of input files for Martini 3, the most recent version of this popular CG force field. Specifically, the MAD server currently includes tools to submit or retrieve CG models of a wide range of molecules (lipids, carbohydrates, nanoparticles, etc.), transform atomistic protein structures into CG structures and topologies, with fine control on the process and assemble biomolecules into large systems, and deliver all files necessary to start simulations in the GROMACS MD engine.

Targeted-antibacterial-plasmids (TAPs) combining conjugation and CRISPR/Cas systems achieve strain-specific antibacterial activity.

The global emergence of drug-resistant bacteria leads to the loss of efficacy of our antibiotics arsenal and severely limits the success of currently available treatments. Here, we developed an innovative strategy based on targeted-antibacterial-plasmids (TAPs) that use bacterial conjugation to deliver CRISPR/Cas systems exerting a strain-specific antibacterial activity. TAPs are highly versatile as they can be directed against any specific genomic or plasmid DNA using the custom algorithm (CSTB) that identifies appropriate targeting spacer sequences. We demonstrate the ability of TAPs to induce strain-selective killing by introducing lethal double strand breaks (DSBs) into the targeted genomes. TAPs directed against a plasmid-born carbapenem resistance gene efficiently resensitise the strain to the drug. This work represents an essential step toward the development of an alternative to antibiotic treatments, which could be used for in situ microbiota modification to eradicate targeted resistant and/or pathogenic bacteria without affecting other non-targeted bacterial species.

Predicting lipid sorting in curved membranes.

Most biological membranes are curved, and both lipids and proteins play a role in generating curvature. For any given membrane shape and composition, it is not trivial to determine whether lipids are laterally distributed in a homogeneous or inhomogeneous way, and whether the inter-leaflet distribution is symmetric or not. Here we present a simple computational tool that allows to predict the preference of any lipid type for membranes with positive vs. negative curvature, for any given value of curvature. The tool is based on molecular dynamics simulations of tubular membranes with hydrophilic pores. The pores allow spontaneous, barrierless flip-flop of most lipids, while also preventing differences in pressure between the inner and outer water compartments and minimizing membrane asymmetric stresses. Specifically, we provide scripts to build and analyze the simulations. We test the tool by performing simulations on simple binary lipid mixtures, and we show that, as expected, lipids with negative intrinsic curvature distribute to the tubule inner leaflet, the more so when the radius of the tubular membrane is small. Compared to other existing computational methods, relying on membrane buckles and tethers, our method is based on spontaneous inter-leaflet transport of lipids, and therefore allows to explore lipid distribution in asymmetric membranes. The method can easily be adapted to work with any molecular dynamics code and any force field.

The Det.Belt Server: A Tool to Visualize and Estimate Amphipathic Solvent Belts around Membrane Proteins.

Detergents wrap around membrane proteins to form a belt covering the hydrophobic part of the protein serving for membrane insertion and interaction with lipids. The number of detergent monomers forming this belt is usually unknown to investigators, unless dedicated detergent quantification is undertaken, which for many projects is difficult to setup. Yet, having an approximate knowledge of the amount of detergent forming the belt is extremely useful, to better grasp the protein of interest in interaction with its direct environment rather than picturing the membrane protein "naked". We created the Det.Belt server to dress up membrane proteins and represent in 3D the bulk made by detergent molecules wrapping in a belt. Many detergents are included in a database, allowing investigators to screen in silico the effect of different detergents around their membrane protein. The input number of detergents is changeable with fast recomputation of the belt for interactive usage. Metrics representing the belt are readily available together with scripts to render quality 3D images for publication. The Det.Belt server is a tool for biochemists to better grasp their sample.

Evaluation of CONSRANK-Like Scoring Functions for Rescoring Ensembles of Protein-Protein Docking Poses.

Scoring is a challenging step in protein-protein docking, where typically thousands of solutions are generated. In this study, we ought to investigate the contribution of consensus-rescoring, as introduced by Oliva et al. (2013) with the CONSRANK method, where the set of solutions is used to build statistics in order to identify recurrent solutions. We explore several ways to perform consensus-based rescoring on the ZDOCK decoy set for Benchmark 4. We show that the information of the interface size is critical for successful rescoring in this context, but that consensus rescoring in itself performs less well than traditional physics-based evaluation. The results of physics-based and consensus-based rescoring are partially overlapping, supporting the use of a combination of these approaches.