Systematic assessment of the accuracy of subunit counting in biomolecular complexes using automated single molecule brightness analysis

Analysis of single molecule brightness allows subunit counting of high-order oligomeric biomolecular complexes. Although the theory behind the method has been extensively assessed, systematic analysis of the experimental conditions required to accurately quantify the stoichiometry of biological complexes remains challenging. In this work, we develop a high-throughput, automated computational pipeline for single molecule brightness analysis that requires minimal human input. We use this strategy to systematically quantify the accuracy of counting under a wide range of experimental conditions in simulated ground-truth data and then validate its use on experimentally obtained data. Our approach defines a set of conditions under which subunit counting by brightness analysis is designed to work optimally and helps establishing the experimental limits in quantifying the number of subunits in a complex of interest. Finally, we combine these features into a powerful, yet simple, software that can be easily used for the stoichiometry analysis of such complexes.

Weak Multivalent Biomolecular Interactions: A Strength vs Numbers Tug of War with Implications for Phase Partitioning

In this short perspective, we discuss how recent dynamic live cell imaging experiments have challenged our understanding of mechanisms driving functional molecular interactions in vivo. While we have generally considered the formation of functional biomolecular complexes as resulting from the stable assembly of two or more partner molecules, here we entertain the possibility that function may actually be maintained while molecules are rapidly exchanged within a complex. We postulate that at high effective concentrations, even very weak interactions can lead to strong binding site occupancy and thereby, mediate function in a highly dynamic fashion. This new perspective in our definition of what represents a functional complex in living cells and in vivo could significantly alter how we define the nature of molecular transactions critical for mediating regulation in the cellular context. These less conventional principles also allow a broadening of the mechanistic options we should explore when interpreting essential biological processes such as gene regulation.

Cooperative electrolyte-PEG interactions drive the signal amplification in a solid-state nanopore

Nanopore systems have emerged as a leading platform for the analysis of biomolecular complexes with single molecule resolution. However, the analysis of several analytes like short nucleic acids or proteins with nanopores represents a sensitivity challenge, because their translocation lead to small signals difficult to distinguish from the noise. Here, we report a simple method to enhance the signal to noise ratio in nanopore experiments by a simple modification of the solution used in nanopore sensing. The addition of poly-ethylene glycol (PEG) and the careful selection of the supporting electrolyte leads to large signal enhancement. We observed that the translocation dynamics are in good agreement with an established method that uses the lattice energy of an electrolyte to approximate the affinity of an ion to PEG. We identified CsBr as the optimal supporting electrolyte to complement PEG to enable the analysis of dsDNA at 500 kHz bandwidth, and the detection of dsDNA as short as 75 bp.

Visualizing conformational space of functional biomolecular complexes by deep manifold learning

The cellular functions are executed by biological macromolecular complexes in nonequilibrium dynamic processes, which exhibit a vast diversity of conformational states. Solving conformational continuum of important biomolecular complexes at atomic level is essential to understand their functional mechanisms and to guide structure-based drug discovery. Here we introduce a deep learning framework, named AlphaCryo4D, which enables atomic-level cryogenic electron microscopy reconstructions of conformational continuum. AlphaCryo4D integrates 3D deep residual learning with manifold embedding of energy landscapes, which directs 3D clustering of markedly improved accuracy via an energy-based particle-voting algorithm. By applications of this approach to analyze five experimental datasets, we examine its generality in breaking resolution limit of visualizing dynamic components of functional complexes, in discovering 'invisible' lowly populated intermediates and in exploring their hidden conformational space. Our approach expands the realm of structural ensemble determination to the nonequilibrium regime at atomic level, thus potentially transforming biomedical research and therapeutic development.

Independent Markov decomposition: Toward modeling kinetics of biomolecular complexes

To advance the mission of in silico cell biology, modeling the interactions of large and complex biological systems becomes increasingly relevant. The combination of molecular dynamics (MD) simulations and Markov state models (MSMs) has enabled the construction of simplified models of molecular kinetics on long timescales. Despite its success, this approach is inherently limited by the size of the molecular system. With increasing size of macromolecular complexes, the number of independent or weakly coupled subsystems increases, and the number of global system states increases exponentially, making the sampling of all distinct global states unfeasible. In this work, we present a technique called independent Markov decomposition (IMD) that leverages weak coupling between subsystems to compute a global kinetic model without requiring the sampling of all combinatorial states of subsystems. We give a theoretical basis for IMD and propose an approach for finding and validating such a decomposition. Using empirical few-state MSMs of ion channel models that are well established in electrophysiology, we demonstrate that IMD models can reproduce experimental conductance measurements with a major reduction in sampling compared with a standard MSM approach. We further show how to find the optimal partition of all-atom protein simulations into weakly coupled subunits.

Structural analysis of the Sulfolobus solfataricus TF55β chaperonin by cryo-electron microscopy

Chaperonins are biomolecular complexes that assist in protein folding. Thermophilic factor 55 (TF55) is a group II chaperonin found in the archaeal genus Sulfolobus that has α, β and γ subunits. Using cryo-electron microscopy, structures of the β-only complex of S. solfataricus TF55 (TF55β) were determined to 3.6–4.2 Å resolution. The structures of the TF55β complexes formed in the presence of ADP or ATP highlighted an open state in which nucleotide exchange can occur before progressing in the refolding cycle.

Role of complementary shape in protein dimerization

Shape guides colloidal nanoparticles to form complex assemblies, but its role in defining interfaces in biomolecular complexes is less clear. In this work, we isolate the role of shape in...

Strategies to identify and suppress crosstalk signals in double electron–electron resonance (DEER) experiments with gadolinium^III and nitroxide spin-labeled compounds

Double electron–electron resonance (DEER) spectroscopy applied to orthogonally spin-labeled biomolecular complexes simplifies the assignment of intra- and intermolecular distances, thereby increasing the information content per sample. In fact, various spin labels can be addressed independently in DEER experiments due to spectroscopically nonoverlapping central transitions, distinct relaxation times, and/or transition moments; hence, they are referred to as spectroscopically orthogonal. Molecular complexes which are, for example, orthogonally spin-labeled with nitroxide (NO) and gadolinium (Gd) labels give access to three distinct DEER channels that are optimized to selectively probe NO–NO, NO–Gd, and Gd–Gd distances. Nevertheless, it has been previously recognized that crosstalk signals between individual DEER channels can occur, for example, when a Gd–Gd distance appears in a DEER channel optimized to detect NO–Gd distances. This is caused by residual spectral overlap between NO and Gd spins which, therefore, cannot be considered as perfectly orthogonal. Here, we present a systematic study on how to identify and suppress crosstalk signals that can appear in DEER experiments using mixtures of NO–NO, NO–Gd, and Gd–Gd molecular rulers characterized by distinct, nonoverlapping distance distributions. This study will help to correctly assign the distance peaks in homo- and heterocomplexes of biomolecules carrying not perfectly orthogonal spin labels.