Shunsuke F. Shimobayashi, Pierre Ronceray, David W. Sanders, Mikko P. Haataja & Clifford P. Brangwynne
TL;DR Classical nucleation theory can describe the initial stages of condensate formation not only in non-living systems but also in living cells. The proposed framework is validated for biomimetic condensates with or without nucleation sites (seeds) and also for endogenous condensates.
Liquid-liquid phase separation (LLPS) governs the formation of cellular condensates such as stress granules, Cajal bodies, or condensates forming in processes such as DNA repair or gene expression. In non-living systems, classical nucleation theory (CNT) can be used to describe the initial stages of nucleated phase separation, establishing a relationship between the rate of droplet nucleation and supersaturation. Could the CNT framework also be valid in living systems, where the heterogeneity and complexity of the cellular environment is at play? To address this question, Shimobayashi et al. probe the relationships between condensate nucleation rate and supersaturation and other parameters in living cells. To this end, they employ endogenous condensates (stress granules), as well as optogenetically controlled phase-separating systems (Corelets) acting as biomimetic condensates. Various experiments with Corelets show that, despite the complexity of the cellular environment, CNT could adequately describe their data. Moreover, to quantify the spatially varying nucleation landscape in cells, they probe the effect of seeding (nucleation sites) on the nucleation rate of condensates. They find that nucleation seeds can enhance nucleation rates in a manner dependent on the supersaturation value, as well as on the specific interactions between the seeds and the condensates. In particular, they note that these interactions are highly sensitive to molecular features such as amino acid patterning. Furthermore, to compare the nucleation kinetics of biomimetic condensates to those of endogenous condensates, they use optogenetically-controlled and endogenous stress granules. They find that optogenetically controlled stress granules recapitulate most features of the endogenous ones, especially upon continuous activation. In summary, this work shows that CNT is an adequate framework for the quantification and modeling of condensate nucleation in living cells. The proposed framework may be useful not only in understanding the kinetics of nucleation in endogenous frameworks, but also in the design of novel condensates for a variety of purposes.
Clifford P. Brangwynne is June K. Wu ‘92 Professor of Engineering and Professor of Chemical and Biological Engineering at Princeton University, USA.
Manzar Abbas, Wojciech P. Lipiński, Karina K. Nakashima, Wilhelm T. S. Huck & Evan Spruijt
TL; DR: Short peptide derivatives based on hydrophobic pairs form LLPS-driven coacervates controlled by redox chemistry that concentrate nucleic acid and have catalytic properties.
Peptide-based coacervates emerge via liquid-liquid phase separation and are promising candidates for engineering biomimetic protocells. Common examples are complex coacervates, resilin-like and elastin-like polypeptides and ampholytic block copolymers with a length of about 50-100 amino acids. In this work, Abbas et al report for the first time the synthesis of short (<1kDa) disulfide-linked dipeptides with tunable phase separation propensity, selectivity in exogenous molecule uptake, and catalytic activity. Among a small library of different hydrophobic dipeptide derivatives conjugated by different polar spacers, phenyl-alanyl/phenylalanine stickers joined by a cystamine linker (FFssFF) was the most soluble while exhibiting the most favorable coacervation at sub-mM concentrations. Interestingly, these coacervates could undergo redox-controlled phase transitions reversibly. Upon treatment with reducing agents, FFssFF turbidity was decreased and recovered again with the addition of an oxidative such as ferricyanide or peroxide. Next, using fluorescence microscopy they found that FFssFF is a minimal coacervate that can concentrate a wide range of solutes including small fluorophores such as ThT, DAPI and SYBR Green as well as nucleic acid – albeit to a lesser extent compared to complex coacervates. Remarkably, a short hairpin RNA was not only sequestered but also melted in the FFssFF coacervates. Finally, Abbas et al bridged elegantly the properties of simple coacervates with their function as catalytic microreactors. Using 1H NMR, they demonstrated how FFssFF coacervates catalyze two types of addition reactions (aldol and hydrazone formation) by concentrating reactants and lowering the energy barrier. This work paves the road for the engineering of peptide-based protocells that can recapitulate the origins of life.
Evan Spruijt is an Assistant Professor of Physical Organic Chemistry at Radboud University, Netherlands.
Marco Necci, Damiano Piovesan, CAID Predictors*, DisProt Curators* and Silvio C. E. Tosatto
TL;DR: Assessment on precision and speed of intrinsically disordered protein predictors.
Currently, the intrinsically disordered protein regions (IDR) predictor is one of the most important resources to identify intrinsic structural disorder(ID) in the proteome. The large-scale assessment of the ID prediction methods has ceased after the CASP10. In this paper, the authors describe the first edition of the Critical Assessment of Protein Intrinsic Disorder prediction(CAID), a community-based blind test, aiming at establishing a standard and improving the prediction accuracy and efficiency of ID prediction methods.
Participants will submit their prediction method to the CAID organizer. Prediction software will run locally on the MobiDB servers for the evaluating process. Two datasets are selected for the evaluation procedure. Disprot, a database containing over 10000 experimental validated IDRs, has been used as the main resource for disordered regions. They also created a Disprot-PDB database that considers the structural domain in the PDB database as the true negative to reduce the impact of unrevealed IDRs in the proteome. Besides evaluating the F-score of the predictor based on True/False negative/positive in these two prediction datasets, they also set up a fully disordered region prediction test and a binding-region test. Several predictors can generate good prediction results in all these tests and datasets.
Nevertheless, the prediction of ID is still a challenging task. No predictor successfully predicted all sequences in a fully intrinsically disordered test, even with an optimized sensitivity setting at the expense of accuracy. The usability and technical detail of these predictors should also be further improved. Errors within the configuration file and unexpected errors for long sequences have been discovered during the assessment. The running time of these predictors has been tested and varies from orders of magnitudes. Indicating further optimization can be performed in these prediction methods.
In conclusion, CAID provides a platform for the comprehensive evaluation of ID predictors. This will encourage the development and improvement of ID predictors. With the increasing IDR data, these ID predictors are expected to be more reliable and accurate in the future.
CAID Predictors and DisProt Curators are a series of researchers coming from Australia, Belgium, Canada, China, France, Germany, Japan, Russia, the UK, and the USA.
Prof. Dr. Silvio C. E. Tosatto is a Principal Investigator at the BioComputing UP lab of the Dept. of Biomedical Sciences, Università degli Studi di Padova.
Felix Wiggers, Samuel Wohl, Artem Dubovetskyi, Gabriel Rosenblum, Wenwei Zheng & Hagen Hofmann
TL;DR: Transient multivalent low-affinity contacts reconciles high affinity, specificity and plasticity in IDP complex
IDPs often bind partners with high specificity and affinity despite retaining significant plasticity and dynamics in the bound state; how IDPs achieve such molecular recognition poses a conundrum.
In this work Wiggers et al., with a combination of detailed smFRET experiments and experiment guided coarse grained simulations dissect the dynamic yet high affinity interaction between the disordered tail of the cell adhesion protein E-cadherin and its partner the protooncogene β-catenin. smFRET probing different regions of E-cadherin showed it to be expanded in solution, likely owing to a high negative net charge. smFRET titrations reveal the interaction to be high affinity (low nanomolar). Lifetime analysis of smFRET histograms and nanosecond-FCS shows E-cadherin to be highly dynamic in the bound state. The bound state shows significant broadening of the smFRET histograms suggesting presence of micro-millisecond dynamics, RASP analysis of the smFRET data shows that E-cadherin samples different β-catenin bound conformers on a microsecond to millisecond timescale. A coarse grained model, where crystallographically resolved interactions sites in the complex were weighted with an interaction strength such that it recapitulated the smFRET data in the complex, suggested that E-cadherin explores the surface of β-catenin diffusively without any major energy barriers. The smFRET-validated coarse grained model differs from the X-Ray structure in one key manner; the interaction sites are spread all over the E-cadherin sequence in the coarse-grained model; while the coarse grained model shows the stretch of E-cadherin that is resolved in the crystal structure to be most strongly interacting with β-catenin, it underscores the fact that numerous transient interactions happen between β-catenin surface and all of the E-cadherin chain. Careful analysis of temperature dependant RASP data from smFRET indeed shows that the slowing down of intrachain diffusion in E-cadherin in the bound state vis-à-vis the free state could be explained by a ruggedness of the order of 3-4 kBT in the energy landscape, than a kinetic barrier. The results indicate that while the slow dynamics in the complex seen from the perspective of E-cadherin originates from contact with β-catenin surface, such contacts do not encode a significant free energy barrier that differentiates one conformer from the other; instead these numerous transient interactions engenders a rugged energy landscape with several local minima, neither of which are deep enough to arrest a particular conformation but in combination makes the interaction high affinity. Numerous transient low affinity contacts in addition to a few persistent interactions reconciles specificity, high affinity, and structural plasticity, which might apparently seem at odds with one another from conventional notions of molecular recognition.
Wenwei Zheng is an Assistant Professor at the Arizona State University Polytechnic, USA. Hagen Hofmann is a Senior Scientist at the Weizmann Institute of Science, Israel.