Structure-Function Properties in Disordered Condensates

Abstract

Biomolecular condensates appear throughout the cell serving a wide variety of functions. Many condensates appear to form by the assembly of multivalent molecules, which produce phase-separated networks with liquidlike properties. These networks then recruit client molecules, with the total composition providing functionality. Here we use a model system of poly-SUMO and poly-SIM proteins to understand client-network interactions and find that the structure of the network plays a strong role in defining client recruitment and thus functionality. The basic unit of assembly in this system is a zipperlike filament composed of alternating poly-SUMO and poly-SIM molecules. These filaments have defects of unsatisfied bonds that allow for both the formation of a 3D network and the recruitment of clients. The filamentous structure constrains the scaffold stoichiometries and the distribution of client recruitment sites that the network can accommodate. This results in a nonmonotonic client binding response that can be tuned independently by the client valence and binding energy. These results show how the interactions within liquid states can be disordered yet still contain structural features that provide functionality to the condensate.

Figure 1:. Poly-SUMO and poly-SIM assemble into zipper-like filaments.

(a) SUMO/SIM droplets are composed of decavalent scaffolds and clients of valence 1, 2, and 3. (b) Intermolecular bonding is most efficient when the scaffolds align to form zipper-like structures. The zippers have bonding defects including sticky ends and gaps. Overlap defects are also possible but neglected in our calculation. (c) Zipper defects provide binding sites to recruit clients or (d) assemble the zippers into a 3D network. The short linker connecting modules favors consecutive bonds with the same molecule rather than the formation of a random network.

Figure 2:. Model parameters are obtained from poly-SUMO/poly-SIM dimerization experiments.

Plot of the dimer association constant, K_2v, vs. the valence, v. The module binding free energy, ϵ, is obtained from the slope of lnK_2v (blue line), while the intercept provides the reference concentration c₀. Clients (mono-, bi-, or trivalent SIM) have a lower binding affinity than scaffolds in the droplet phase, which we attribute to steric interactions between the network and the fluorescent labels. We account for this with a free energy offset, f_RFP, for clients in the dense phase (purple line).

Figure 3:. Filament length and defect density depend on stoichiometry.

(a) At equal stoichiometry most scaffolds are fully bound resulting in few defects. As the stoichiometric imbalance increases, the number of unbound SUMO modules increases while the number of unbound SIM sites decreases. (b) The average length of filaments is a non-monotonic function of scaffold stoichiometry. A small excess of one scaffold leads to an increase in the filament length because unpaired scaffolds are available to stabilize sticky ends resulting from mis-aligned states. Larger stoichiometric mismatches result in a decline in filament length, which provides more sticky ends to bind the excess scaffold. (c) Filaments with equal number of SUMO and SIM scaffolds are favored at symmetric mixing, but unequal stoichiometries favor odd length filaments.

Figure 4:. Model captures the droplet scaffold composition observed in experiment.

(a) The ratio of poly-SUMO to poly-SIM (N_U/N_I) calculated from our theory agrees well with the droplet stoichiometry in experiments. At high stoichiometric mismatches the approximation of purely 1D filaments breaks down because the concentration of free scaffolds is high enough to allow binding in the gaps. A correction accounting for monovalent scaffold-gap binding (inset cartoon) resolves the discrepancy with experiment (dotted line). (b) Excess SUMO scaffold accumulates in the dilute phase and depletes the concentration of monomeric SIM scaffolds. (c) Small stoichiometric mismatches promote increased scaffold accumulation in the droplet phase, but the trend reverses as the average filament size drops. The discrepancy at 90 μM can be explained by a breakdown of the 1D approximation as depicted in the cartoons of panel (a). In all panels lines indicate theory and circles denote the experiments of

Figure 5:. The scaffold composition that optimizes client recruitment depends on the client valence.

(a) The transfer matrix theory (lines) captures the shift in the experimental (dots) partition coefficient peak as the client valence increases. The high affinity of trivalent clients is more sensitive to both the appearance of defects in the droplet and the presence of free scaffold in the bulk. Experimental data from. (b) Concentration of unbound SUMO modules in the dense and dilute phases. Excess scaffolds, and associated defect sites, are initially bound in the droplet as shown by the blue curve (given by ρ_g times the droplet poly-SUMO concentration). However, above 70 μM additional poly-SUMO accumulates primarily in the bulk phase, which has a defect density of 10c_U (red). The scaling factor applied to the droplet curve is approximately equal to the ~ 0.01 volume fraction of the droplets. Therefore, these curves approximately represent the number of defects sites in each phase.

Figure 6:. Increasing the client module binding affinity enhances client recruitment with minimal effect on the location of the peak.

This provides separate mechanisms to tune the location and magnitude of client recruitment. (a) Monovalent SIM and (b) Trivalent SIM at different module binding affinities. The different effects of client valence and affinity on the PC curve allow the network to switch between the recruitment of different clients. (c) With tuned client affinities, it is possible for the network to selectively recruit either the monovalent or trivalent client in different regimes of parameter space.

Figure 7:. The microscopic connectivity of biomolecule condensates imparts specific properties.

While both poly-SUMO/poly-SIM and SPOP/DAXX condensates form by the association of multivalent molecules, the assemblies have very different properties. Poly-SUMO/poly-SIM condensates are composed of linear filaments that provide a client binding response that is sensitive to the scaffold stoichiometry. SPOP/DAXX assemblies contain a “kinetic switch” that allows the system to convert between gel states with arrested dynamics and fluid droplets. Here the black lines represent bivalent DAXX molecules, while the rectangles represent polymerized SPOP rods. Adapted with permission from. Copyright 2020 by the American Chemical Society.

Figure 8:

Excess monomer scaffold concentration binding at defect sites in crosslinked fashion.