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Biomolecular condensates help cells organise their content in space and time. Cells harbour a variety of condensate types with diverse composition and many are likely yet to be discovered. Here, we develop a methodology to predict the composition of biomolecular condensates. We first analyse available proteomics data of cellular condensates and find that the biophysical features that determine protein localisation into condensates differ from known drivers of homotypic phase separation processes, with charge mediated protein-RNA and hydrophobicity mediated protein-protein interactions playing a key role in the former process. We then develop a machine learning model that links protein sequence to its propensity to localise into heteromolecular condensates. We apply the model across the proteome and find many of the top-ranked targets outside the original training data to localise into condensates as confirmed by orthogonal immunohistochemical staining imaging. Finally, we segment the condensation-prone proteome into condensate types based on an overlap with biomolecular interaction profiles to generate a Protein Condensate Atlas. Several condensate clusters within the Atlas closely match the composition of experimentally characterised condensates or regions within them, suggesting that the Atlas can be valuable for identifying additional components within known condensate systems and discovering previously uncharacterised condensates. Biomolecular condensates help cells organise their content in space and time. Here the authors report a machine learning driven methodology to predict the composition of biomolecular condensates and they then validate their predictions against the composition of known biomolecular condensates.

Multicomponent phase-separating molecular systems play a key role as membraneless organelles in living cells. Phase diagrams are indispensable for probing the concentration-dependent behaviour of these condensates, yet their interpretation has remained largely qualitative due to the challenges of modelling complex, multicomponent interactions. Here, we present a generic framework for quantitative analysis of phase diagrams. We derive an analytical expression for the phase boundary normal vector, which reveals two distinct scaling regimes: one for associative phase separation, characterised by a power-law scaling analogous to mass-action kinetics that allows for direct extraction of dense phase solute molar ratios, and another for condensate dissolution, where an exponential scaling quantifies three-body repulsion effects triggered by the addition of a new component. We demonstrate the practical utility of our framework by applying it to a range of experimentally measured phase diagrams, including those for proteins such as NSP5, NSP2, FUS, Whi3, G3BP1, and antimicrobial peptides. Collectively, our work not only provides a clear quantitative interpretation of phase diagrams but also opens new avenues for the rigorous characterisation of multicomponent phase-separating systems.

Bio-molecular condensates formed in the cytoplasm of cells are increasingly recognised as key spatiotemporal organisers of living matter and are implicated in a wide range of functional or pathological processes. This opens up a new avenue for condensate-based applications and a crucial step in controlling this process is to understand the underlying interactions driving their formation or dissolution. However, these condensates are highly multi-component assemblies and many inter-component interactions are present, rendering it difficult to identify key drivers of phase separation. In this work, we employ the recently formulated dominance analysis to modulations of condensate formation, centred around dilute phase solute concentration measurements. We posit that mechanisms of action of modulators can be categorised into 4 generic classes with respect to a target solute, motivated by theoretical insights. These classes serve as a general guide towards deducing possible mechanisms on the molecular level, which can be complemented by orthogonal measurements. As a case study, we investigate the modulation of suramin on condensates formed by G3BP1 and RNA, and the dominance measurements point towards a dissolution mechanism where suramin acts on G3BP1 to disrupt G3BP1/RNA interactions, as confirmed by a diffusional sizing assay. Our approach and the dominance framework have a high degree of adaptability and can be applied in many other condensate-forming systems.Competing Interest StatementParts of this work have been the subject of a patent application filed by Cambridge Enterprise Limited, a fully owned subsidiary of the University of Cambridge. T. P. J. K. and P. St G. H. are founders, and W. E. A., T. K., N. E. and S. Q. are employees of Transition Bio Ltd.Footnotes* typo correction

Electrochemical gradients are essential to the functioning of cells and form across membranes using active transporters. Here, we show in contrast that condensed biomolecular systems sustain significant pH gradients without any external energy input. By studying individual condensates on the micron scale using a microdroplet platform, we reveal dense phase pH shifts towards conditions of minimal electrostatic repulsion. We demonstrate that by doing so protein condensates can drive substantial alkaline and acidic gradients which are compositionally tuneable and can extend to complex architectures sustaining multiple unique pH conditions simultaneously. Through in silico characterisation of human proteomic condensate networks, we further highlight potential wide ranging electrochemical properties emerging from condensation in nature, while correlating intracellular condensate pH gradients with complex biomolecular composition. Together, the emergent nature of condensation shapes distinct pH microenvironments, thereby creating a unique regulatory mechanism to modulate biochemical activity in living systems.

Thyroid hormones are produced by the thyroid gland and are essential for regulating metabolism, growth and development. Maintenance of circulating thyroid hormone levels within an appropriate range is thus a prerequisite for health. In vivo, this objective is, at least in part, facilitated through an extracellular storage depot of thyroglobulin, the glycoprotein precursor for thyroid hormones, in the thyroid follicular lumen. The molecular basis for how soluble thyroglobulin molecules form such dense depot assemblies remains elusive. Here, we describe in vitro biophysical analysis of thyroglobulin phase behaviour, suggesting that thyroglobulin is prone to undergoing ionic strength-dependent phase separation, leading to the formation of liquid-like condensates. Fluorescence photobleaching measurements further show that these condensates age as a function of time to form reversible gel-like high density storage depots of thyroglobulin. IF experiments on mouse and human thyroid follicles ex vivo reveal that spherical globules of Tg protein dense phase are present in the follicular lumen, consistent with the idea that Tg undergoes phase separation. These findings reveal a molecular mechanism for the last-come-first-served process of thyroglobulin storage and release, suggesting a role for extracellular phase separation in thyroid hormone homeostasis by providing organizational and architectural specificity without requiring membrane-mediated confinement. A biophysical study on phase separation behaviour of thyroglobulin (Tg) in vitro, combined with ex vivo immunofluorescence experiments, suggests that extracellular phase separation mediates storage and release of Tg in the thyroid follicular lumen.

Thyroid hormones are produced by the thyroid gland and are essential for regulating metabolism, growth and development. Maintenance of circulating thyroid hormone levels within an appropriate range is thus a prerequisite for health. In vivo, this objective is, at least in part, facilitated through an extracellular storage depot of thyroglobulin, the glycoprotein precursor for thyroid hormones, in the thyroid follicular lumen. The molecular basis for how soluble thyroglobulin molecules form such dense depot assemblies remains elusive. Here, we describe in vitro biophysical analysis of thyroglobulin phase behaviour, suggesting that thyroglobulin is prone to undergoing ionic strength-dependent phase separation, leading to the formation of liquid-like condensates. Fluorescence photobleaching measurements further show that these condensates age as a function of time to form reversible gel-like high density storage depots of thyroglobulin. Immunofluorescence experiments on mouse and human thyroid follicles ex vivo reveal that spherical globules of Tg protein dense phase are present in the follicular lumen, consistent with the idea that Tg undergoes phase separation. These findings reveal a molecular mechanism for the last-come-first-served process of thyroglobulin storage and release, suggesting a role for extracellular phase separation in thyroid hormone homeostasis by providing organizational and architectural specificity without requiring membrane-mediated confinement.

Biomolecular condensates have emerged as prominent regulators of dynamic subcellular organisation and essential biological processes. Temperature, in particular, exerts a significant influence on the formation and behaviour of biomolecular condensation. For example, during cellular heat stress, stress granules (SGs) are formed from RNA-binding proteins (RBPs) and RNA, forming liquid condensates to protect the RNA from damage. However, the molecular mechanisms leading to changes in protein phase behaviour are not well understood. To answer how temperature modulates protein interactions and phase behaviour, we developed a high-throughput microfluidic platform, capable of mapping the phase space and quantifying protein interactions in a temperature-dependent manner. Specifically, our approach measures high-resolution protein phase diagrams as a function of temperature, while accurately quantifying changes in the binodal, condensate stoichiometry and free energy contribution of a solute, hence, providing information about the underlying mechanistic driving forces. We employ this approach to investigate the effect of temperature changes on the phase separation of the stress granule scaffold protein Ras GTPase-activating protein-binding protein 1 (G3BP1) with PolyA-RNA. Surprisingly, we find that the G3BP1/RNA phase boundary remains unaffected by the increasing temperature but the underlying stoichiometry and energetics shift, which can only be revealed with high-resolution phase diagrams. This indicates that temperature-induced dissolution is counteracted by entropic processes driving phase separation. With increasing temperature, the G3BP1 content in condensates decreases alongside with a reduction of the free energy of protein interactions, while the RNA content increases driven by entropically favoured hydrophobic interactions. In the context of cellular heat SG formation, these findings could indicate that during heat shock, elevated temperatures directly induce RNA recruitment to stress granules as a cytoprotective mechanism by finetuning the strength of protein and RNA interactions.Competing Interest StatementThe Authors declare the following competing interests: T.P.J.K. and P.S.G.-H. are a co-founders and H.A., D.Q., R.S. and S.Q. are employees or consultants for Transition Bio; C.M.F. and T.S. declare no competing interests.