Optimal Sacrificial Domains in Mechanical Polyproteins: S. epidermidis Adhesins Are Tuned for Work Dissipation

Abstract

The opportunistic pathogen Staphylococcus epidermidis utilizes a multidomain surface adhesin protein to bind host components and adhere to tissues. While it is known that the interaction between the SdrG receptor and its fibrinopeptide target (FgB) is exceptionally mechanostable (∼2 nN), the influence of downstream B domains (B1 and B2) is unclear. Here, we studied the mechanical relationships between folded B domains and the SdrG receptor bound to FgB. We used protein engineering, single-molecule force spectroscopy (SMFS) with an atomic force microscope (AFM), and Monte Carlo simulations to understand how the mechanical properties of folded sacrificial domains, in general, can be optimally tuned to match the stability of a receptor–ligand complex. Analogous to macroscopic suspension systems, sacrificial shock absorber domains should neither be too weak nor too strong to optimally dissipate mechanical energy. We built artificial molecular shock absorber systems based on the nanobody (VHH) scaffold and studied the competition between domain unfolding and receptor unbinding. We quantitatively determined the optimal stability of shock absorbers that maximizes work dissipation on average for a given receptor and found that natural sacrificial domains from pathogenic S. epidermidis and Clostridium perfringens adhesins exhibit stabilities at or near this optimum within a specific range of loading rates. These findings demonstrate how tuning the stability of sacrificial domains in adhesive polyproteins can be used to maximize mechanical work dissipation and serve as an adhesion strategy by bacteria.

Mechanistic basis of staphylococcal interspecies competition for skin colonization

“…Under tensile loading, the repeats will act as force buffers capable of relieving mechanical stress. Folded sacrificial domains in S. epidermidis adhesive polyproteins have been shown to maximize mechanical work dissipation and were suggested to serve as an adhesion strategy by bacteria 64 . The B-repeat superdomain may play a role in strengthening of the lectin-domain mediated interaction.…”

Engineering an artificial catch bond using mechanical anisotropy

“…The most probable rupture force of each population was linearly fitted against the logarithm of loading rate to extract k 0 and Δx ‡ using Bell-Evans model (see Eq. 2 and Table 1 ) 60 . The rupture force distributions were fitted with one or two Gaussian peaks.…”

Iterative Machine Learning for Classification and Discovery of Single-Molecule Unfolding Trajectories from Force Spectroscopy Data

“…The code and the data used in this work are available free of charge on our group GitHub repository. This includes the Monte Carlo algorithm 39 used to generate the simulated data (https://github.com/Nash-Lab/Monte-Carlo-Methods), the raw data (Zenodo https://doi.org/10.5281/zenodo.8224236), and the script to reproduce this work (https://github.com/ Nash-Lab/Fusion-Learning).…”

“…To verify the applicability of our framework, we first employed it on synthetic data generated with a Monte Carlo algorithm 39 (Simulated, Figure 1D). This case study served as a proof-of-concept, where each good trace was clearly defined, separable, and virtually noise free.…”