Solutes unmask differences in clustering versus phase separation of FET proteins.

Phase separation and percolation contribute to phase transitions of multivalent macromolecules. Contributions of percolation are evident through the viscoelasticity of condensates and through the formation of heterogeneous distributions of nano- and mesoscale pre-percolation clusters in sub-saturated solutions. Here, we show that clusters formed in sub-saturated solutions of FET (FUS-EWSR1-TAF15) proteins are affected differently by glutamate versus chloride. These differences on the nanoscale, gleaned using a suite of methods deployed across a wide range of protein concentrations, are prevalent and can be unmasked even though the driving forces for phase separation remain unchanged in glutamate versus chloride. Strikingly, differences in anion-mediated interactions that drive clustering saturate on the micron-scale. Beyond this length scale the system separates into coexisting phases. Overall, we find that sequence-encoded interactions, mediated by solution components, make synergistic and distinct contributions to the formation of pre-percolation clusters in sub-saturated solutions, and to the driving forces for phase separation.

An optofluidic antenna for enhancing the sensitivity of single-emitter measurements.

Many single-molecule investigations are performed in fluidic environments, for example, to avoid unwanted consequences of contact with surfaces. Diffusion of molecules in this arrangement limits the observation time and the number of collected photons, thus, compromising studies of processes with fast or slow dynamics. Here, we introduce a planar optofluidic antenna (OFA), which enhances the fluorescence signal from molecules by about 5 times per passage, leads to about 7-fold more frequent returns to the observation volume, and significantly lengthens the diffusion time within one passage. We use single-molecule multi-parameter fluorescence detection (sm-MFD), fluorescence correlation spectroscopy (FCS) and Förster resonance energy transfer (FRET) measurements to characterize our OFAs. The antenna advantages are showcased by examining both the slow (ms) and fast (50 µs) dynamics of DNA four-way (Holliday) junctions with real-time resolution. The FRET trajectories provide evidence for the absence of an intermediate conformational state and introduce an upper bound for its lifetime. The ease of implementation and compatibility with various microscopy modalities make OFAs broadly applicable to a diverse range of studies.

IHMCIF: An Extension of the PDBx/mmCIF Data Standard for Integrative Structure Determination Methods.

IHMCIF (github.com/ihmwg/IHMCIF) is a data information framework that supports archiving and disseminating macromolecular structures determined by integrative or hybrid modeling (IHM), and making them Findable, Accessible, Interoperable, and Reusable (FAIR). IHMCIF is an extension of the Protein Data Bank Exchange/macromolecular Crystallographic Information Framework (PDBx/mmCIF) that serves as the framework for the Protein Data Bank (PDB) to archive experimentally determined atomic structures of biological macromolecules and their complexes with one another and small molecule ligands (e.g., enzyme cofactors and drugs). IHMCIF serves as the foundational data standard for the PDB-Dev prototype system, developed for archiving and disseminating integrative structures. It utilizes a flexible data representation to describe integrative structures that span multiple spatiotemporal scales and structural states with definitions for restraints from a variety of experimental methods contributing to integrative structural biology. The IHMCIF extension was created with the benefit of considerable community input and recommendations gathered by the Worldwide Protein Data Bank (wwPDB) Task Force for Integrative or Hybrid Methods (wwpdb.org/task/hybrid). Herein, we describe the development of IHMCIF to support evolving methodologies and ongoing advancements in integrative structural biology. Ultimately, IHMCIF will facilitate the unification of PDB-Dev data and tools with the PDB archive so that integrative structures can be archived and disseminated through PDB.

PARP1-DNA co-condensation drives DNA repair site assembly to prevent disjunction of broken DNA ends.

DNA double-strand breaks (DSBs) are repaired at DSB sites. How DSB sites assemble and how broken DNA is prevented from separating is not understood. Here we uncover that the synapsis of broken DNA is mediated by the DSB sensor protein poly(ADP-ribose) (PAR) polymerase 1 (PARP1). Using bottom-up biochemistry, we reconstitute functional DSB sites and show that DSB sites form through co-condensation of PARP1 multimers with DNA. The co-condensates exert mechanical forces to keep DNA ends together and become enzymatically active for PAR synthesis. PARylation promotes release of PARP1 from DNA ends and the recruitment of effectors, such as Fused in Sarcoma, which stabilizes broken DNA ends against separation, revealing a finely orchestrated order of events that primes broken DNA for repair. We provide a comprehensive model for the hierarchical assembly of DSB condensates to explain DNA end synapsis and the recruitment of effector proteins for DNA damage repair.

Glutamate helps unmask the differences in driving forces for phase separation versus clustering of FET family proteins in sub-saturated solutions.

Multivalent proteins undergo coupled segregative and associative phase transitions. Phase separation, a segregative transition, is driven by macromolecular solubility, and this leads to coexisting phases above system-specific saturation concentrations. Percolation is a continuous transition that is driven by multivalent associations among cohesive motifs. Contributions from percolation are highlighted by the formation of heterogeneous distributions of clusters in sub-saturated solutions, as was recently reported for Fused in sarcoma (FUS) and FET family proteins. Here, we show that clustering and phase separation are defined by a separation of length- and energy-scales. This is unmasked when glutamate is the primary solution anion. Glutamate is preferentially excluded from protein sites, and this enhances molecular associations. Differences between glutamate and chloride are manifest at ultra-low protein concentrations. These differences are amplified as concentrations increase, and they saturate as the micron-scale is approached. Therefore, condensate formation in supersaturated solutions and clustering in sub-saturated are governed by distinct energy and length scales. Glutamate, unlike chloride, is the dominant intracellular anion, and the separation of scales, which is masked in chloride, is unmasked in glutamate. Our work highlights how components of cellular milieus and sequence-encoded interactions contribute to amplifying distinct contributions from associative versus segregative phase transitions.

Recognition of polymorphic Csd proteins determines sex in the honeybee.

Sex in honeybees, Apis mellifera, is genetically determined by heterozygous versus homo/hemizygous genotypes involving numerous alleles at the single complementary sex determination locus. The molecular mechanism of sex determination is however unknown because there are more than 4950 known possible allele combinations, but only two sexes in the species. We show how protein variants expressed from complementary sex determiner (csd) gene determine sex. In females, the amino acid differences between Csd variants at the potential-specifying domain (PSD) direct the selection of a conserved coiled-coil domain for binding and protein complexation. This recognition mechanism activates Csd proteins and, thus, the female pathway. In males, the absence of polymorphisms establishes other binding elements at PSD for binding and complexation of identical Csd proteins. This second recognition mechanism inactivates Csd proteins and commits male development via default pathway. Our results demonstrate that the recognition of different versus identical variants of a single protein is a mechanism to determine sex.

Glutamate helps unmask the differences in driving forces for phase separation versus clustering of FET family proteins in sub-saturated solutions.

Multivalent proteins undergo coupled segregative and associative phase transitions. Phase separation, a segregative transition, is driven by macromolecular solubility, and this leads to coexisting phases above system-specific saturation concentrations. Percolation is a continuous transition that is driven by multivalent associations among cohesive motifs. Contributions from percolation are highlighted by the formation of heterogeneous distributions of clusters in sub-saturated solutions, as was recently reported for Fused in sarcoma (FUS) and FET family proteins. Here, we show that clustering and phase separation are defined by a separation of length- and energy-scales. This is unmasked when glutamate is the primary solution anion. Glutamate is preferentially excluded from protein sites, and this enhances molecular associations. Differences between glutamate and chloride are manifest at ultra-low protein concentrations. These differences are amplified as concentrations increase, and they saturate as the micron-scale is approached. Therefore, condensate formation in supersaturated solutions and clustering in sub-saturated are governed by distinct energy and length scales. Glutamate, unlike chloride, is the dominant intracellular anion, and the separation of scales, which is masked in chloride, is unmasked in glutamate. Our work highlights how components of cellular milieus and sequence-encoded interactions contribute to amplifying distinct contributions from associative versus segregative phase transitions.

Integrative dynamic structural biology unveils conformers essential for the oligomerization of a large GTPase.

Guanylate binding proteins (GBPs) are soluble dynamin-like proteins that undergo a conformational transition for GTP-controlled oligomerization and disrupt membranes of intracellular parasites to exert their function as part of the innate immune system of mammalian cells. We apply neutron spin echo, X-ray scattering, fluorescence, and EPR spectroscopy as techniques for integrative dynamic structural biology to study the structural basis and mechanism of conformational transitions in the human GBP1 (hGBP1). We mapped hGBP1's essential dynamics from nanoseconds to milliseconds by motional spectra of sub-domains. We find a GTP-independent flexibility of the C-terminal effector domain in the µs-regime and resolve structures of two distinct conformers essential for an opening of hGBP1 like a pocket knife and for oligomerization. Our results on hGBP1's conformational heterogeneity and dynamics (intrinsic flexibility) deepen our molecular understanding relevant for its reversible oligomerization, GTP-triggered association of the GTPase-domains and assembly-dependent GTP-hydrolysis.

Resolution of Maximum Entropy Method-Derived Posterior Conformational Ensembles of a Flexible System Probed by FRET and Molecular Dynamics Simulations.

Maximum entropy methods (MEMs) determine posterior distributions by combining experimental data with prior information. MEMs are frequently used to reconstruct conformational ensembles of molecular systems for experimental information and initial molecular ensembles. We performed time-resolved Förster resonance energy transfer (FRET) experiments to probe the interdye distance distributions of the lipase-specific foldase Lif in the apo state, which likely has highly flexible, disordered, and/or ordered structural elements. Distance distributions estimated from ensembles of molecular dynamics (MD) simulations serve as prior information, and FRET experiments, analyzed within a Bayesian framework to recover distance distributions, are used for optimization. We tested priors obtained by MD with different force fields (FFs) tailored to ordered (FF99SB, FF14SB, and FF19SB) and disordered proteins (IDPSFF and FF99SBdisp). We obtained five substantially different posterior ensembles. As in our FRET experiments the noise is characterized by photon counting statistics, for a validated dye model, MEM can quantify consistencies between experiment and prior or posterior ensembles. However, posterior populations of conformations are uncorrelated to structural similarities for individual structures selected from different prior ensembles. Therefore, we assessed MEM simulating varying priors in synthetic experiments with known target ensembles. We found that (i) the prior and experimental information must be carefully balanced for optimal posterior ensembles to minimize perturbations of populations by overfitting and (ii) only ensemble-integrated quantities like inter-residue distance distributions or density maps can be reliably obtained but not ensembles of atomistic structures. This is because MEM optimizes ensembles but not individual structures. This result for a highly flexible system suggests that structurally varying priors calculated from varying prior ensembles, e.g., generated with different FFs, may serve as an ad hoc estimate for MEM reconstruction robustness.

Enhanced Solid-State Fluorescence of Flavin Derivatives by Incorporation in the Metal-Organic Frameworks MIL-53(Al) and MOF-5.

The flavin derivatives 10-methyl-isoalloxazine (MIA) and 6-fluoro-10-methyl-isoalloxazine (6F-MIA) were incorporated in two alternative metal-organic frameworks, (MOFs) MIL-53(Al) and MOF-5. We used a post-synthetic, diffusion-based incorporation into microcrystalline MIL-53 powders with one-dimensional (1D) pores and an in-situ approach during the synthesis of MOF-5 with its 3D channel network. The maximum amount of flavin dye incorporation is 3.9 wt% for MIA@MIL-53(Al) and 1.5 wt% for 6F-MIA@MIL-53(Al), 0.85 wt% for MIA@MOF-5 and 5.2 wt% for 6F-MIA@MOF-5. For the high incorporation yields the probability to have more than one dye molecule in a pore volume is significant. As compared to the flavins in solution, the fluorescence spectrum of these flavin@MOF composites is broadened at the bathocromic side especially for MIA. Time-resolved spectroscopy showed that multi-exponential fluorescence lifetimes were needed to describe the decays. The fluorescence-weighted lifetime of flavin@MOF of 4 ± 1 ns also corresponds to those in solution but is significantly prolonged compared to the solid flavin dyes with less than 1 ns, thereby confirming the concept of "solid solutions" for dye@MOF composites. The fluorescence quantum yield (ΦF) of the flavin@MOF composites is about half of the solution but is significantly higher compared to the solid flavin dyes. Both the fluorescence lifetime and quantum yield of flavin@MOF decrease with the flavin loading in MIL-53 due to the formation of various J-aggregates. Theoretical calculations using plane-wave and QM/MM methods are in good correspondence with the experimental results and explain the electronic structures as well as the photophysical properties of crystalline MIA and the flavin@MOF composites. In the solid flavins, π-stacking interactions of the molecules lead to a charge transfer state with low oscillator strength resulting in aggregation-caused quenching (ACQ) with low lifetimes and quantum yields. In the MOF pores, single flavin molecules represent a major population and the computed MIA@MOF structures do not find π-stacking interactions with the pore walls but only weak van-der-Waals contacts which reasons the enhanced fluorescence lifetime and quantum yield of the flavins in the composites compared to their neat solid state. To analyze the orientation of flavins in MOFs, we measured fluorescence anisotropy images of single flavin@MOF-5 crystals and a static ensemble flavin@MIL53 microcrystals, respectively. Based on image information, anisotropy distributions and overall curve of the time-resolved anisotropy curves combined with theoretical calculations, we can prove that all fluorescent flavins species have a defined and rather homogeneous orientation in the MOF framework. In MIL-53, the transition dipole moments of flavins are orientated along the 1D channel axis, whereas in MOF-5 we resolved an average orientation that is tilted with respect to the cubic crystal lattice. Notably, the more hydrophobic 6F-MIA exhibits a higher degree order than MIA. The flexible MOF MIL-53(Al) was optimized essentially to the experimental large-pore form in the guest-free state with QuantumEspresso (QE) and with MIA molecules in the pores the structure contracted to close to the experimental narrow-pore form which was also confirmed by PXRD. In summary, the incorporation of flavins in MOFs yields solid-state materials with enhanced rigidity, stabilized conformation, defined orientation and reduced aggregations of the flavins, leading to increased fluorescence lifetime and quantum yield as controllable photo-luminescent and photo-physical properties.

Reliability and accuracy of single-molecule FRET studies for characterization of structural dynamics and distances in proteins.

Single-molecule Förster-resonance energy transfer (smFRET) experiments allow the study of biomolecular structure and dynamics in vitro and in vivo. We performed an international blind study involving 19 laboratories to assess the uncertainty of FRET experiments for proteins with respect to the measured FRET efficiency histograms, determination of distances, and the detection and quantification of structural dynamics. Using two protein systems with distinct conformational changes and dynamics, we obtained an uncertainty of the FRET efficiency ≤0.06, corresponding to an interdye distance precision of ≤2 Å and accuracy of ≤5 Å. We further discuss the limits for detecting fluctuations in this distance range and how to identify dye perturbations. Our work demonstrates the ability of smFRET experiments to simultaneously measure distances and avoid the averaging of conformational dynamics for realistic protein systems, highlighting its importance in the expanding toolbox of integrative structural biology.

A blind benchmark of analysis tools to infer kinetic rate constants from single-molecule FRET trajectories.

Single-molecule FRET (smFRET) is a versatile technique to study the dynamics and function of biomolecules since it makes nanoscale movements detectable as fluorescence signals. The powerful ability to infer quantitative kinetic information from smFRET data is, however, complicated by experimental limitations. Diverse analysis tools have been developed to overcome these hurdles but a systematic comparison is lacking. Here, we report the results of a blind benchmark study assessing eleven analysis tools used to infer kinetic rate constants from smFRET trajectories. We test them against simulated and experimental data containing the most prominent difficulties encountered in analyzing smFRET experiments: different noise levels, varied model complexity, non-equilibrium dynamics, and kinetic heterogeneity. Our results highlight the current strengths and limitations in inferring kinetic information from smFRET trajectories. In addition, we formulate concrete recommendations and identify key targets for future developments, aimed to advance our understanding of biomolecular dynamics through quantitative experiment-derived models.

Fuzzy supertertiary interactions within PSD-95 enable ligand binding.

The scaffold protein PSD-95 links postsynaptic receptors to sites of presynaptic neurotransmitter release. Flexible linkers between folded domains in PSD-95 enable a dynamic supertertiary structure. Interdomain interactions within the PSG supramodule, formed by PDZ3, SH3, and Guanylate Kinase domains, regulate PSD-95 activity. Here we combined discrete molecular dynamics and single molecule Förster resonance energy transfer (FRET) to characterize the PSG supramodule, with time resolution spanning picoseconds to seconds. We used a FRET network to measure distances in full-length PSD-95 and model the conformational ensemble. We found that PDZ3 samples two conformational basins, which we confirmed with disulfide mapping. To understand effects on activity, we measured binding of the synaptic adhesion protein neuroligin. We found that PSD-95 bound neuroligin well at physiological pH while truncated PDZ3 bound poorly. Our hybrid structural models reveal how the supertertiary context of PDZ3 enables recognition of this critical synaptic ligand.

Phase-separating RNA-binding proteins form heterogeneous distributions of clusters in subsaturated solutions.

Macromolecular phase separation is thought to be one of the processes that drives the formation of membraneless biomolecular condensates in cells. The dynamics of phase separation are thought to follow the tenets of classical nucleation theory, and, therefore, subsaturated solutions should be devoid of clusters with more than a few molecules. We tested this prediction using in vitro biophysical studies to characterize subsaturated solutions of phase-separating RNA-binding proteins with intrinsically disordered prion-like domains and RNA-binding domains. Surprisingly, and in direct contradiction to expectations from classical nucleation theory, we find that subsaturated solutions are characterized by the presence of heterogeneous distributions of clusters. The distributions of cluster sizes, which are dominated by small species, shift continuously toward larger sizes as protein concentrations increase and approach the saturation concentration. As a result, many of the clusters encompass tens to hundreds of molecules, while less than 1% of the solutions are mesoscale species that are several hundred nanometers in diameter. We find that cluster formation in subsaturated solutions and phase separation in supersaturated solutions are strongly coupled via sequence-encoded interactions. We also find that cluster formation and phase separation can be decoupled using solutes as well as specific sets of mutations. Our findings, which are concordant with predictions for associative polymers, implicate an interplay between networks of sequence-specific and solubility-determining interactions that, respectively, govern cluster formation in subsaturated solutions and the saturation concentrations above which phase separation occurs.

Unraveling multi-state molecular dynamics in single-molecule FRET experiments. II. Quantitative analysis of multi-state kinetic networks.

Single-molecule Förster Resonance Energy Transfer (smFRET) experiments are ideally suited to resolve the structural dynamics of biomolecules. A significant challenge to date is capturing and quantifying the exchange between multiple conformational states, mainly when these dynamics occur on the sub-millisecond timescale. Many methods for quantitative analysis are challenged if more than two states are involved, and the appropriate choice of the number of states in the kinetic network is difficult. An additional complication arises if dynamically active molecules coexist with pseudo-static molecules in similar conformational states with undistinguishable Förster Resonance Energy Transfer (FRET) efficiencies. To address these problems, we developed a quantitative integrative analysis framework that combines the information from FRET-lines that relate average fluorescence lifetimes and intensities in two-dimensional burst frequency histograms, fluorescence decays obtained by time-correlated single-photon-counting, photon distribution analysis of the intensities, and fluorescence correlation spectroscopy. Individually, these methodologies provide ambiguous results for the characterization of dynamics in complex kinetic networks. However, the global analysis approach enables accurate determination of the number of states, their kinetic connectivity, the transition rate constants, and species fractions. To challenge the potential of smFRET experiments for studying multi-state kinetic networks, we apply our integrative framework using a set of synthetic data for three-state systems with different kinetic connectivity and exchange rates. Our methodology paves the way toward an integrated analysis of multiparameter smFRET experiments that spans all dimensions of the experimental data. Finally, we propose a workflow for the analysis and show examples that demonstrate the usefulness of this toolkit for dynamic structural biology.

Unraveling multi-state molecular dynamics in single-molecule FRET experiments. I. Theory of FRET-lines.

Conformational dynamics of biomolecules are of fundamental importance for their function. Single-molecule studies of Förster Resonance Energy Transfer (smFRET) between a tethered donor and acceptor dye pair are a powerful tool to investigate the structure and dynamics of labeled molecules. However, capturing and quantifying conformational dynamics in intensity-based smFRET experiments remains challenging when the dynamics occur on the sub-millisecond timescale. The method of multiparameter fluorescence detection addresses this challenge by simultaneously registering fluorescence intensities and lifetimes of the donor and acceptor. Together, two FRET observables, the donor fluorescence lifetime τD and the intensity-based FRET efficiency E, inform on the width of the FRET efficiency distribution as a characteristic fingerprint for conformational dynamics. We present a general framework for analyzing dynamics that relates average fluorescence lifetimes and intensities in two-dimensional burst frequency histograms. We present parametric relations of these observables for interpreting the location of FRET populations in E-τD diagrams, called FRET-lines. To facilitate the analysis of complex exchange equilibria, FRET-lines serve as reference curves for a graphical interpretation of experimental data to (i) identify conformational states, (ii) resolve their dynamic connectivity, (iii) compare different kinetic models, and (iv) infer polymer properties of unfolded or intrinsically disordered proteins. For a simplified graphical analysis of complex kinetic networks, we derive a moment-based representation of the experimental data that decouples the motion of the fluorescence labels from the conformational dynamics of the biomolecule. Importantly, FRET-lines facilitate exploring complex dynamic models via easily computed experimental observables. We provide extensive computational tools to facilitate applying FRET-lines.

Fundamental photophysics of isomorphic and expanded fluorescent nucleoside analogues.

Fluorescent nucleoside analogues (FNAs) are structurally diverse mimics of the natural essentially non-fluorescent nucleosides which have found numerous applications in probing the structure and dynamics of nucleic acids as well as their interactions with various biomolecules. In order to minimize disturbance in the labelled nucleic acid sequences, the FNA chromophoric groups should resemble the natural nucleobases in size and hydrogen-bonding patterns. Isomorphic and expanded FNAs are the two groups that best meet the criteria of non-perturbing fluorescent labels for DNA and RNA. Significant progress has been made over the past decades in understanding the fundamental photophysics that governs the spectroscopic and environmentally sensitive properties of these FNAs. Herein, we review recent advances in the spectroscopic and computational studies of selected isomorphic and expanded FNAs. We also show how this information can be used as a rational basis to design new FNAs, select appropriate sequences for optimal spectroscopic response and interpret fluorescence data in FNA applications.

A comprehensive analysis of RAS-effector interactions reveals interaction hotspots and new binding partners.

RAS effectors specifically interact with GTP-bound RAS proteins to link extracellular signals to downstream signaling pathways. These interactions rely on two types of domains, called RAS-binding (RB) and RAS association (RA) domains, which share common structural characteristics. Although the molecular nature of RAS-effector interactions is well-studied for some proteins, most of the RA/RB-domain-containing proteins remain largely uncharacterized. Here, we searched through human proteome databases, extracting 41 RA domains in 39 proteins and 16 RB domains in 14 proteins, each of which can specifically select at least one of the 25 members in the RAS family. We next comprehensively investigated the sequence-structure-function relationship between different representatives of the RAS family, including HRAS, RRAS, RALA, RAP1B, RAP2A, RHEB1, and RIT1, with all members of RA domain family proteins (RASSFs) and the RB-domain-containing CRAF. The binding affinity for RAS-effector interactions, determined using fluorescence polarization, broadly ranged between high (0.3 µM) and very low (500 µM) affinities, raising interesting questions about the consequence of these variable binding affinities in the regulation of signaling events. Sequence and structural alignments pointed to two interaction hotspots in the RA/RB domains, consisting of an average of 19 RAS-binding residues. Moreover, we found novel interactions between RRAS1, RIT1, and RALA and RASSF7, RASSF9, and RASSF1, respectively, which were systematically explored in sequence-structure-property relationship analysis, and validated by mutational analysis. These data provide a set of distinct functional properties and putative biological roles that should now be investigated in the cellular context.

Automated and optimally FRET-assisted structural modeling.

FRET experiments can provide state-specific structural information of complex dynamic biomolecular assemblies. However, to overcome the sparsity of FRET experiments, they need to be combined with computer simulations. We introduce a program suite with (i) an automated design tool for FRET experiments, which determines how many and which FRET pairs should be used to minimize the uncertainty and maximize the accuracy of an integrative structure, (ii) an efficient approach for FRET-assisted coarse-grained structural modeling, and all-atom molecular dynamics simulations-based refinement, and (iii) a quantitative quality estimate for judging the accuracy of FRET-derived structures as opposed to precision. We benchmark our tools against simulated and experimental data of proteins with multiple conformational states and demonstrate an accuracy of ~3 Å RMSDCα against X-ray structures for sets of 15 to 23 FRET pairs. Free and open-source software for the introduced workflow is available at https://github.com/Fluorescence-Tools . A web server for FRET-assisted structural modeling of proteins is available at http://nmsim.de .