bioRxiv Science⌕ Search

bioRxiv · 10.1101/2024.02.02.578706

Modeling reveals the strength of weak interactions in stacked ring assembly

Abstract

Cells employ many large macromolecular machines for the execution and regulation of processes that are vital for cell and organismal viability. Interestingly, cells cannot synthesize these machines as functioning units. Instead, cells synthesize the molecular parts that must then assemble into the functional complex. Many important machines, including chaperones like GroEL and proteases like the proteasome, are comprised protein rings that are stacked on top of one another. While there is some experimental data regarding how stacked-ring complexes like the proteasome self-assemble, a comprehensive understanding of the dynamics of stacked ring assembly is currently lacking. Here, we developed a mathematical model of stacked trimer assembly, and performed an analysis of the assembly of the stacked homomeric trimer, which is the simplest stacked ring architecture. We found that stacked rings are particularly susceptible to a form of kinetic trapping that we term "deadlock," in which the system gets stuck in a state where there are many large intermediates that are not the fully-assembled structure, but that cannot productively react. When interaction affinities are uniformly strong, deadlock severely limits assembly yield. We thus predicted that stacked rings would avoid situations where all interfaces in the structure have high affinity. Analysis of available crystal structures indicated that indeed the majority - if not all - of stacked trimers do not contain uniformly strong interactions. Finally, to better understand the origins of deadlock, we developed a formal pathway analysis and showed that, when all the binding affinities are strong, many of the possible pathways are utilized. In contrast, optimal assembly strategies utilize only a small number of patwhays. Our work suggests that deadlock is a critical factor influencing the evolution of macromolecular machines, and provides general principles for not only understanding existing machines but also for the design of novel structures that can self-assemble efficiently. Statement of SignificanceUnderstanding the assembly macromolecular machines is important for understanding a wide range of cellular processes. Here, we use mathematical models to study the assembly of stacked rings, which are a common motif in these machines. Our models revealed that these complexes can readily get "stuck" during assembly when the binding affinity between subunits is too strong. This suggests an evolutionary pressure to favor weaker interactions, and our analysis of solved structures confirmed this prediction. Our findings not only contribute to the fundamental understanding of assembly but also offer insights into the evolutionary pressures shaping the architecture of stacked rings, and have implications for both cell and synthetic biology.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Lagunes, L., Briggs, K., Martin-Holder, P., Xu, Z., Maurer, D., Ghabra, K., Deeds, E. J.. 2024-02-07. Modeling reveals the strength of weak interactions in stacked ring assembly. https://doi.org/10.1101/2024.02.02.578706

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

KEEP EXPLORING

Related preprints

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↗

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↗

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↗