Proteolytic Performance is Dependent on Binding Efficiency, Processivity and Turnover: Single Protease Insights

Soerensen, E. W.; Reinholt, F. B.; Faber, A.; Bender, S. W.; Kaestel-Hansen, J.; Lundin, J. d. S.; Voutyritsa, E.; Hedegaard, P.; Christensen, S.; Hatzakis, N. S.

doi:10.1101/2024.06.10.598230

bioRxiv · 10.1101/2024.06.10.598230

Proteolytic Performance is Dependent on Binding Efficiency, Processivity and Turnover: Single Protease Insights

Soerensen, E. W.·Reinholt, F. B.·Faber, A.·Bender, S. W.·Kaestel-Hansen, J.·Lundin, J. d. S.·Voutyritsa, E.·Hedegaard, P.·Christensen, S.·Hatzakis, N. S.

View original source ↗Export metadata ↓

Abstract

Proteases are essential enzymes for a plethora of biological processes and biotechnological applications, e.g., within the dairy, pharmaceutical, and detergent industries. Decoding the molecular level mechanisms that drive protease performance is key to designing improved biosolutions. However, direct dynamic assessment of the fundamental partial reactions of substrate binding and activity has proven a challenge with conventional ensemble approaches. We developed a single-molecule (SM) assay for the direct and parallel recording of the stochastic binding interaction of Savinase, a serine-type protease broadly employed in biotechnology, with casein synchronously with monitoring proteolytic degradation of the substrate. SM recordings enabled us to determine how the overall activity of Savinase and two mutants relies on binding efficiency, enzymatic turnover and activity per binding event. Analysis of residence times revealed three characteristic binding states. Mutations were found to dominantly alter the likelihood of sampling the long lived state, with lifetimes longer than 30 seconds, indicating this state contributes to overall activity and supporting a level of processivity for Savinase. This observation challenges conventional expectations, as the protease has no characterized substrate binding site, or binding domain, aside from the active site. These insights, inaccessible through conventional assays, offer new perspectives for engineering proteases with improved hydrolytic performance.

Source connections

Published article ↗

Explore related subjects

biophysics Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Soerensen, E. W., Reinholt, F. B., Faber, A., Bender, S. W., Kaestel-Hansen, J., Lundin, J. d. S., Voutyritsa, E., Hedegaard, P., Christensen, S., Hatzakis, N. S.. 2024-06-11. Proteolytic Performance is Dependent on Binding Efficiency, Processivity and Turnover: Single Protease Insights. https://doi.org/10.1101/2024.06.10.598230

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Expression-System Biases Compromise the Functional Assessment of KCNH2 Variants and Clinical Risk Assessment

Background: Functional characterization of KCNH2 variants is essential for assessing pathogenicity in long QT syndrome type 2. Because hERG channels assemble as tetramers, the relative expression of wild-type (WT) and variant subunits critically influences channel function and pathogenicity assessment. However, commonly used experimental systems may not reproduce the balanced allelic expression observed in heterozygous patients. Methods: Allele-specific KCNH2 expression was analyzed in two independent RNA-sequencing datasets from human left ventricular tissue. Using the dominant-negative T74R hERG variant as a model, we calibrated the relationship between WT-to-variant expression ratios and hERG current amplitude. Using automated patch-clamp electrophysiology, we compared 3 dual-expression strategies: internal ribosome entry site (IRES), P2A-linked tandem constructs, and dual cytomegalovirus promoter (dCMV) constructs. Co-electroporation of WT and variant plasmids in different ratios was the reference. Results: Allele-specific expression analysis supported balanced KCNH2 expression in human left ventricular tissue. At a 1:1 WT-to-T74R expression ratio, hERG current amplitude was reduced to 31.0% of WT, consistent with a dominant-negative mechanism in which incorporation of 2 or more T74R subunits renders the channel nonfunctional. All 3 dual-expression strategies produced substantial expression imbalances, with the first cassette consistently favored. IRES constructs showed the greatest asymmetry. P2A constructs partially improved expression balance but introduced an additional N-terminal proline in the second cassette altering T74R-associated trafficking and channel biophysics. The dCMV system also failed to achieve balanced expression, including after stable integration. Co-electroporation of separate WT and variant plasmids provided the most reliable means of controlling their relative expression. Conclusions: Commonly used dual-expression constructs do not reliably reproduce balanced WT and variant hERG expression, potentially distorting assessments of dominant-negative effects and variant pathogenicity. Co-electroporation of separate plasmids provides a robust approach for high-throughput functional phenotyping under heterozygous conditions, with implications for the interpretation of KCNH2 variants and potentially other genes encoding multimeric ion channels.

biophysics↗

bioRxiv2026

Learning from Hi-C reveals nuclear dynamical reorganization in budding yeast across the cell cycle

Hi-C contact maps provide population-averaged measurements of chromosomal contacts. Converting these measurements, however, into three-dimensional structures and associated dynamics remains an underdetermined problem. Existing approaches broadly fall into two classes. Data-driven reconstruction methods that infer either a consensus structure or an ensemble of conformations, but do not inform on chromosome dynamics. Physics-based models, which generate dynamical trajectories, but require prior assumptions about nuclear geometry, chromatin mechanics, tethering, or molecular interactions. Here, we bridge these approaches using the Full-Inversion Chromatin model, a data-driven whole-genome polymer framework that learns an effective force field directly from Hi-C contact probabilities, integrated with Serpentine, a tool to quantify contact-map discrepancies while accounting for differences in sequencing coverage and sparsity. This generates structural ensembles of chromosomes and effective chromatin dynamics. We apply this method at 5-kb resolution to Saccharomyces cerevisiae in G1, mid-S, S/G2, G2/M, anaphase, and quiescence. Without explicitly imposing the spindle pole body, centromere or telomere tethering, predefined chromatin states, or nuclear-envelope interactions, the inferred ensembles recover these major features of yeast nuclear organization. Importantly, although dynamical information is not used during model training, the resulting polymer trajectories reproduce the subdiffusive scaling and chromosomal variations of independently measured chromatin motion. The model further predicts heterogeneous mobility along chromosomes and a distinctive telomere-dependent dynamical organization. Thus, population-averaged Hi-C contacts contain sufficient information to infer not only three-dimensional genome organization, but also effective, locus-dependent chromatin dynamics.

biophysics↗

bioRxiv2026

One high-order ion-coupling mechanism generates multiple SLC1A stoichiometries

Human excitatory amino acid transporter 2 (hEAAT2) is a glial transporter that clears glutamate and aspartate from the extracellular space to terminate neurotransmission. When this essential role is disrupted, excess extracellular glutamate causes excitotoxicity and neurological disease. hEAAT2 transports amino acids into cells against their concentration gradients by coupling uptake to the co-transport of Na+ and H+, and counter-transport of K+. Substrate transport also activates a thermodynamically uncoupled Cl- conductance, whose significance is unknown. Here, to dissect the molecular mechanisms underlying coupled and uncoupled ion transport by EAATs, we leverage the tractable Drosophila melanogaster homologue dEAAT2, which transports taurine as well as glutamate and aspartate. By functionally characterising dEAAT2, we confirmed it has features of a canonical EAAT transport cycle, including an uncoupled Cl- conductance. However, it functions an ion-independent electroneutral exchanger, in stark contrast to its ion-coupled electrogenic human counterpart. Cryo-electron microscopy (cryo-EM) and computational simulations confirmed the inability of dEAAT2 to transport cations, but just two point mutations conferred Na+, H+, and K+ dependence, reconstituting the complex ion coupling profile of human transporters in the Drosophila exchanger. We also showed that dEAAT2 transports taurine in a complex with Cl-, bestowing a unique Cl--dependence on taurine transport, independent of uncoupled Cl- flux. Our findings show that ancestral exchangers in the EAAT family preserve the machinery to achieve complex ion-coupled transport, revealing the molecular basis of high-order ion coupling in hEAATs.

biophysics↗