Biology subjects

Nilges, M.

Publications and source records attributed to Nilges, M..

12 recordsLinked to original sources

bioRxiv2026

A structural trade-off balances mechanical resilience and supramolecular adaptability in type IV pili

Biological machines operate under mechanical load, requiring architectures that simultaneously resist force and remain functionally dynamic. Type IV pili (T4P) are bacterial filaments that experience large tensile forces during motor-driven retraction. Here, we combine cryo-electron microscopy, molecular dynamics simulations, optical tweezers, and functional analyses to define the structural basis of T4P mechanical adaptation. We determined a 2.8 [A] cryo-EM structure of the Pseudomonas aeruginosa T4P and integrated it with comparative all-atom simulations across six bacterial strains to identify a conserved force-bearing electrostatic network. Simulations predicted that this network tunes filament elasticity under load, a finding validated by single-filament force spectroscopy. Rewiring these interactions experimentally produced hyper-rigid pili that assembled normally but exhibited impaired twitching motility. Together, our findings uncover a structural trade-off between force-resistant architecture and reversible supramolecular adaptability.

biophysics↗

bioRxiv2026

The NMR Exchange Format (NEF): Specification and Applications

The NMR Exchange Format (NEF) is a community-driven standard for representing NMR experimental data in a consistent, interoperable, and machine-readable form. Built on the STAR syntax, NEF provides a structured framework for storing and exchanging chemical shifts, peak lists, various types of structural restraints, and related metadata, thus allowing for data exchange across software platforms. By enabling direct, lossless transfer of information, NEF simplifies multi-software workflows, improves reproducibility, and supports FAIR (Findable, Accessible, Interoperable, Reusable) data principles. We describe the NEF specification, its current implementation across commonly used NMR software packages, and its application in areas including biomolecular structure determination, metabolomics, and ligand screening. Testing demonstrates that NEF can be used to exchange complete datasets between programs without loss of information or functionality. We also outline recent developments and future directions, such as inclusion of NMR relaxation data and support for non-standard residue topologies. NEFs growing adoption highlights its potential as a unifying standard for NMR data, enabling more efficient, transparent and collaborative research.

biochemistry↗

bioRxiv2026

Structural determinants of endopilus assembly, stability and functional specificity in bacterial type II secretion

Gram-negative bacteria employ the type II secretion system (T2SS) to transport folded protein effectors across the outer membrane. This multiprotein nanomachine assembles the endopilus, a periplasmic helical polymer composed of one major and four minor pilin subunits. Endopili are structurally related to type IV pili but exhibit distinct features including a conserved calcium-binding site stabilizing their major pilin subunits. Endopilus polymerisation is coupled to substrate translocation through a dedicated outer membrane channel. To investigate the structural basis of endopilus assembly, stability and functional specificity, we performed a comparative analysis of the Out T2SS from the plant pathogen Dickeya dadantii and the Pul T2SS from the human pathogen Klebsiella oxytoca. Although their major pilins OutG and PulG share over 77% sequence identity, these bacteria differ markedly in ecological niche and range of secreted effectors. We report here the NMR structure of calcium-bound OutG monomer and cryo-EM structures of OutG and PulG endopili at 3.6 [A] resolution. The integration of structural, mutational, and biophysical analyses with in vivo assays, allowed us to identify the molecular determinants of secretion specificity and endopilus stability. These findings demonstrate how subtle sequence variations in conserved nanomachines have evolved to optimize their function and adapt to their local environments.

microbiology↗

bioRxiv2023

The increased hinge flexibility of an IgG1-IgG3 hybrid monoclonal enhances Fc-mediated protection against group A streptococci

Antibodies are central to the immune response against microbes. We have previously generated a protective IgG1 monoclonal antibody targeting the M protein, a critical virulence factor of Streptococcus pyogenes. Here, we generated this antibody in all human IgG subclasses and evaluated their function. Despite significantly reduced binding, the IgG3 subclass antibody demonstrated remarkably enhanced opsonic function. We hypothesized that increased Fc flexibility could explain this improved efficacy. We engineered a hybrid IgG subclass antibody, IgGh, containing the backbone of IgG1 with the hinge of IgG3, leaving the Fabs unchanged. The IgGh maintained a similar binding ability as IgG1 while gaining the strong opsonic function seen with IgG3. Molecular dynamics simulations of the different antibodies showed altered IgG Fab-antigen interactions, reflecting the differences observed in affinity. More importantly, when the antibodies were bound to the antigen, the simulations showed that the Fc of both IgGh and IgG3 exhibited extensive movement in 3D space relative to the M protein. The increased flexibility of IgGh directly translated to enhanced opsonic function and significantly increased the protection against infection with Streptococcus pyogenes in mice. Our findings demonstrate how altering Fc flexibility can improve Fc-mediated opsonic function and how modifications in the constant domain can regulate Fab-antigen interactions. In addition, the enhanced in vivo function of a more flexible IgG provides new therapeutic opportunities for monoclonal antibodies. One sentence summaryAntibody Fc flexibility in 3D space correlates with efficient Fc-mediated phagocytosis of streptococci

immunology↗

bioRxiv2022

Structure and dynamic association of an assembly platform subcomplex of the bacterial type II secretion system

Type II secretion systems (T2SS) allow diderm bacteria to secrete hydrolytic enzymes, adhesins or toxins important for growth and virulence. In T2SS, secretion of folded proteins from the periplasm to the cell surface requires assembly of periplasmic filaments called pseudopili. Like the related type IV pili, pseudopili are polymerized in the inner membrane through addition of subunits at the filament base, mediated by the essential assembly platform (AP). To understand the structure and molecular role of the AP, we focused on its components PulL and PulM from the Klebsiella oxytoca T2SS. By combining biophysical methods, NMR and X-ray crystallography we studied the structure and associations of their periplasmic domains. We describe the first structure of the heterodimer complex formed by the PulL and PulM ferredoxin-like domains and show how their structural complementarity and plasticity favor their association during the secretion process. Cysteine scanning and cross-linking of transmembrane segments provided additional constraints to build a structural model of the PulL-PulM complex and assembly in the cellular context. Together with the relative abundance of PulL, PulM and their partners our findings suggest a model of the AP as a dynamic hub that orchestrates pseudopilus polymerization.

microbiology↗

bioRxiv2021

InDeep : 3D fully convolutional neural networks to assist in silico drug design on protein-protein interactions

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSMotivationC_ST_ABSProtein-protein interactions (PPIs) are key elements in numerous biological pathways and the subject of a growing number of drug discovery projects including against infectious diseases. Designing drugs on PPI targets remains a difficult task and requires extensive efforts to qualify a given interaction as an eligible target. To this end, besides the evident need to determine the role of PPIs in disease-associated pathways and their experimental characterization as therapeutics targets, prediction of their capacity to be bound by other protein partners or modulated by future drugs is of primary importance. ResultsWe present InDeep, a tool for predicting functional binding sites within proteins that could either host protein epitopes or future drugs. Leveraging deep learning on a curated data set of PPIs, this tool can proceed to enhanced functional binding site predictions either on experimental structures or along molecular dynamics trajectories. The benchmark of InDeep demonstrates that our tool outperforms state of the art ligandable binding sites predictors when assessing PPI targets but also conventional targets. This offers new opportunities to assist drug design projects on PPIs by identifying pertinent binding pockets at or in the vicinity of PPI interfaces. AvailabilityThe tool is available on GitHub3 along with a PyMol plugin for visualization. Predictions of InDeep can be consulted at iPPI-DB4

bioinformatics↗

bioRxiv2021

Interaction of the TonB dependent transporter HasR with its cognate TonB-like protein HasB in a membrane environment

The envelope of Gram-negative bacteria is composed of a double membrane separated by the periplasmic space. This organization imposes geometrical and distance constraints that are key for the mechanism of action of multicomponent systems spanning the envelope. However, consideration of all three compartments by experimental approaches is still elusive. Here we used the state-of-the-art molecular dynamics simulation in an Escherichia coli envelope model to obtain a dynamic view of molecular interactions between the outer membrane heme transporter HasR and the inner membrane TonB-like protein HasB. Their interaction allows the transfer of the inner membrane proton motive force derived energy to the transporter for heme internalization. The simulations which incorporate both membranes show the key role of periplasmic domains of both proteins, and their dynamics in the complex formation and stability. They revealed a previously unidentified atomic network of interactions, as well as the sequences of the interactions and their variations with the presence of external substrates. Experimental validation (mutations, phenotypic and in vitro assays) confirms the robustness of our approach and provides verification of the simulation-predicted interactions. Based on structural and sequence conservation, the network of interaction revealed in this study is expected to occur in other nutrient import systems. The integrative approach presented here is highly useful to study the dynamic interplay between components of any other bacterial transmembrane systems.

biophysics↗

bioRxiv2021

Computational and biochemical analysis of type IV Pilus dynamics and stability

Type IV pili (T4P) are distinctive dynamic filaments at the surface of many bacteria that can rapidly extend, retract and withstand strong forces. T4P are important virulence factors in many human pathogens, including Enterohemorrhagic Escherichia coli (EHEC). The structure of the EHEC T4P has been determined by integrating Nuclear Magnetic Resonance (NMR) and cryo-electron microscopy data. To better understand pilus assembly, stability and function, we performed a total of 108 s all-atom molecular dynamics simulations of wild-type and mutant T4P. Extensive characterization of the conformational landscape of T4P in different conditions of temperature, pH and ionic strength was complemented by targeted mutagenesis and biochemical analyses. Our simulations and NMR experiments revealed a conserved set of residues defining a novel calcium-binding site at the interface between three pilin subunits. Calcium binding enhanced T4P stability ex vivo and in vitro, supporting the role of this binding site as a potential pocket for drug design.

biochemistry↗

bioRxiv2020

Structural determination of Streptococcus pyogenes M1 protein interactions with human immunoglobulin G using integrative structural biology

Streptococcus pyogenes (Group A streptococcus; GAS) is an important human pathogen responsible for mild to severe, life-threatening infections. GAS expresses a wide range of virulence factors, including the M family proteins. The M proteins allow the bacteria to evade parts of the human immune defenses by triggering the formation of a dense coat of plasma proteins surrounding the bacteria, including IgGs. However, the molecular level details of the M1-IgG interaction have remained unclear. Here, we characterized the structure and dynamics of this interaction interface in human plasma on the surface of live bacteria using integrative structural biology, combining cross-linking mass spectrometry and molecular dynamics (MD) simulations. We show that the primary interaction is formed between the S-domain of M1 and the conserved IgG Fc-domain. In addition, we show evidence for a so far uncharacterized interaction between the A-domain and the IgG Fc-domain. Both these interactions mimic the protein G-IgG interface of group C and G streptococcus. These findings underline a conserved scavenging mechanism used by GAS surface proteins that block the IgG-receptor (Fc{gamma}R) to inhibit phagocytic killing. We additionally show that we can capture Fab-bound IgGs in a complex background and identify the specific M1 epitopes targeted on live bacteria. Our results elucidate the M1-IgG interaction network involved in inhibition of phagocytosis and reveal important M1 peptides that can be further investigated as future vaccine targets.

molecular biology↗

bioRxiv2020

Automatic building of protein atomic models from cryo-EM density maps using residue co-evolution

Electron cryo-microscopy (cryo-EM) has emerged as a powerful method to obtain three-dimensional (3D) structures of macromolecular complexes at atomic or near-atomic resolution. However, de novo building of atomic models from near-atomic resolution (3-5 [A]) cryo-EM density maps is a challenging task, in particular since poorly resolved side-chain densities hamper sequence assignment by automatic procedures at a lower resolution. Furthermore, segmentation of EM density maps into individual subunits remains a difficult problem when no three-dimensional structures of these subunits exist, or when significant conformational changes occur between the isolated and complexed form of the subunits. To tackle these issues, we have developed a graph-based method to thread most of the C- trace of the protein backbone into the EM density map. The EM density is described as a weighted graph such that the resulting minimum spanning tree encompasses the high-density regions of the map. A pruning algorithm cleans the tree and finds the most probable positions of the C- atoms, using side-chain density when available, as a collection of C- trace fragments. By complementing experimental EM maps with contact predictions from sequence co-evolutionary information, we demonstrate that our approach can correctly segment EM maps into individual subunits and assign amino acids sequence to backbone traces to generate full-atom models.

bioinformatics↗

bioRxiv2018

Bayesian inference of chromatin structure ensembles from population Hi-C data

High-throughput chromosome conformation capture (Hi-C) experiments are typically performed on a large population of cells and therefore only yield average numbers of genomic contacts. Nevertheless population Hi-C data are often interpreted in terms of a single genomic structure, which ignores all cell-to-cell variability. We propose a probabilistic, statistically rigorous method to infer chromatin structure ensembles from population Hi-C data that takes the ensemble nature of the data explicitly into account and allows us to infer the number of structures required to explain the data.

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↗