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. 2020 Jan 15;142(2):874-883.
doi: 10.1021/jacs.9b10066. Epub 2020 Jan 3.

Protein Network Structure Enables Switching between Liquid and Gel States

Jeremy D Schmit  1 , Jill J Bouchard  2 , Erik W Martin  2 , Tanja Mittag  2
Affiliations

Protein Network Structure Enables Switching between Liquid and Gel States

Jeremy D Schmit et al. J Am Chem Soc. .

Abstract

Biomolecular condensates are emerging as an important organizational principle within living cells. These condensed states are formed by phase separation, yet little is known about how material properties are encoded within the constituent molecules and how the specificity for being in different phases is established. Here we use analytic theory to explain the phase behavior of the cancer-related protein SPOP and its substrate DAXX. Binary mixtures of these molecules have a phase diagram that contains dilute liquid, dense liquid, and gel states. We show that these discrete phases appear due to a competition between SPOP-DAXX and DAXX-DAXX interactions. The stronger SPOP-DAXX interactions dominate at sub-stoichiometric DAXX concentrations leading to the formation of cross-linked gels. The theory shows that the driving force for gel formation is not the binding energy, but rather the entropy of distributing DAXX molecules on the binding sites. At high DAXX concentrations the SPOP-DAXX interactions saturate, which leads to the dissolution of the gel and the appearance of a liquid phase driven by weaker DAXX-DAXX interactions. This competition between interactions allows multiple dense phases to form in a narrow region of parameter space. We propose that the molecular architecture of phase-separating proteins governs the internal structure of dense phases, their material properties and their functions. Analytical theory can reveal these properties on the long length and time scales relevant to biomolecular condensates.

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Figures

Figure 1:
Figure 1:
(A) The three domains of SPOP determine its assembly behavior. (B) BTB-BTB interactions lead to the formation of dimers with a nM affinity. BACK-BACK interactions allow for the polymerization of dimers to form linear rods. The MATH domain binds to substrates such as DAXX. (C) cDAXX, which is the intrinsically disordered C-terminus of DAXX and encompasses residues 495-740 of DAXX, has five SPOP binding (SB) motifs. Four of these are arranged in pairs that bind cooperatively to pairs of MAT14 domains. The remaining SB motif is weak and is neglected in our model. (D) Average length of SPOP assemblies (measured in dimer units) for three values of the polymerization constant, as calculated from Eq. 3. In the absence of ficoll the polymerization constant is . The other two curves represent the range of values consistent with the phase diagram observed in 4% ficoll.
Figure 2:
Figure 2:
(A) Double bound DAXX molecules are only found in a limited concentration behavior of n2. At low DAXX concentration there is an abundance of free binding sites and most DAXX molecules are double bound. However, as the number of binding sites saturates, it becomes progressively harder to find a nearby second binding site. Eventually, all binding sites are filled with single bound DAXX. (B) Comparison of the free energy for two different binding site densities (zg = 2zv). The high density system is lower in free energy for values of c1D where DAXX is double bound. (inset) Free energy difference between the gel phase and the vapor phase.
Figure 3:
Figure 3:
Binding curves in the presence and absence of ficoll. Representative fluorescence anisotropy direct binding curves of A) WT SPOP28–359 and B) SPOP ΔBACK28–337 from triplicate measurements with rhodamine-labeled His-cDAXX ±4% ficoll. Experimental data points are shown as circles, and non-linear least squares fits are shown as lines. Average KD values from triplicate experiments are reported in the legends, the errors represent standard deviations.
Figure 4:
Figure 4:
(top) Micrographs (fluorescence overlaid with DIG) of 15 μM SPOP solutions with increasing concentrations of cDAXX showing the vapor, gel, and liquid phases in 4% ficoll. (middle) Phase diagram calculated from Eq. 25, Eq. 26, and Eq. 28. Circles, squares, and diamonds indicate vapor, gel, and liquid phases observed experimentally. The calculation shows the behavior of SPOP assemblies and does not account for the pure DAXX fluid, (bottom) Cartoon of the progression of structures along the arrow in the phase diagram. At low DAXX concentration there are insufficient crosslinks to drive condensation and the SPOP assemblies are in the vapor phase. The gel is formed when the excess entropy of arranging the DAXX molecules is enough to offset the translational entropy of condensation. When the binding sites become saturated, double bound DAXX molecules become rare, however, the SPOP assemblies are still held together in the liquid phase by weak DAXX-DAXX interactions. Finally, at very high concentrations, DAXX monomers condense into a liquid that dissolves the SPOP assemblies.
Figure 5:
Figure 5:
Experimental (points) and computed (lines) protein concentrations in the condensed phases. In the gel phase (left of the dashed line) the SPOP concentration is determined by a kinetic arrest of the network condensation. The cDAXX concentration (black) is given by the binding of cDAXX to this network (Eq. 14). In the liquid phase the SPOP (red) and cDAXX (black) concentrations (Eq. 32 and Eq. 33) are initially given by the excluded volume of the cylindrical SPOP-cDAXX assemblies (plateau region), before relaxing toward the values expected for a pure cDAXX solution (blue points).
Figure 6:
Figure 6:
SAXS characterization of cDAXX. (A) Raw SAXS data of cDAXX, where I(q) normalized by the forward scattering, is plotted versus q, defined as q = 4π sin(2θ)/λ. Here, θ is the scattering angle and λ is the X-ray wavelength (~ 0.1 nm). Experimental data were logarithmically smoothed. Calculated scattering profiles from the empirically derived molecular form factor (MFF) (bottom) are overlaid as a solid line. (B) Raw SAXS data in normalized Kratky representation, logarithmically smoothed. Rg and n are a result from the fit to the empirical MFF (solid line). (C) Guinier transformation of the SAXS data. The black line is a linear fit to the Guinier equation with resulting Rg value; the residuals are shown below.
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