Tyler S. Harmon

Intrinsically disordered linkers determine the interplay between phase separation and gelation in multivalent proteins

Phase transitions of linear multivalent proteins control the reversible formation of many intracellular membraneless bodies. Specific non-covalent crosslinks involving domains/motifs lead to system-spanning networks referred to as gels. Gelation transitions can occur with or without phase separation. In gelation driven by phase separation multivalent proteins and their ligands condense into dense droplets, and gels form within droplets. System spanning networks can also form without a condensation or demixing of proteins into droplets. Gelation driven by phase separation requires lower protein concentrations, and seems to be the biologically preferred mechanism for forming membraneless bodies. Here, we use coarse-grained computer simulations and the theory of associative polymers to uncover the physical properties of intrinsically disordered linkers that determine the extent to which gelation of linear multivalent proteins is driven by phase separation. Our findings are relevant for understanding how sequence-encoded information in disordered linkers influences phase transitions of multivalent proteins.

Hamiltonian Switch Metropolis Monte Carlo Simulations for Improved Conformational Sampling of Intrinsically Disordered Regions Tethered to Ordered Domains of Proteins.

There is growing interest in the topic of intrinsically disordered proteins (IDPs). Atomistic Metropolis Monte Carlo (MMC) simulations based on novel implicit solvation models have yielded useful insights regarding sequence-ensemble relationships for IDPs modeled as autonomous units. However, a majority of naturally occurring IDPs are tethered to ordered domains. Tethering introduces additional energy scales and this creates the challenge of broken ergodicity for standard MMC sampling or molecular dynamics that cannot be readily alleviated by using generalized tempering methods. We have designed, deployed, and tested our adaptation of the Nested Markov Chain Monte Carlo sampling algorithm. We refer to our adaptation as Hamiltonian Switch Metropolis Monte Carlo (HS-MMC) sampling. In this method, transitions out of energetic traps are enabled by the introduction of an auxiliary Markov chain that draws conformations for the disordered region from a Boltzmann distribution that is governed by an alternative potential function that only includes short-range steric repulsions and conformational restraints on the ordered domain. We show using multiple, independent runs that the HS-MMC method yields conformational distributions that have similar and reproducible statistical properties, which is in direct contrast to standard MMC for equivalent amounts of sampling. The method is efficient and can be deployed for simulations of a range of biologically relevant disordered regions that are tethered to ordered domains.

CAMELOT: A machine learning approach for coarse-grained simulations of aggregation of block-copolymeric protein sequences

We report the development and deployment of a coarse-graining method that is well suited for computer simulations of aggregation and phase separation of protein sequences with block-copolymeric architectures. Our algorithm, named CAMELOT for Coarse-grained simulations Aided by MachinE Learning Optimization and Training, leverages information from converged all atom simulations that is used to determine a suitable resolution and parameterize the coarse-grained model. To parameterize a system-specific coarse-grained model, we use a combination of Boltzmann inversion, non-linear regression, and a Gaussian process Bayesian optimization approach. The accuracy of the coarse-grained model is demonstrated through direct comparisons to results from all atom simulations. We demonstrate the utility of our coarse-graining approach using the block-copolymeric sequence from the exon 1 encoded sequence of the huntingtin protein. This sequence comprises of 17 residues from the N-terminal end of huntingtin (N17) followed by a polyglutamine (polyQ) tract. Simulations based on the CAMELOT approach are used to show that the adsorption and unfolding of the wild type N17 and its sequence variants on the surface of polyQ tracts engender a patchy colloid like architecture that promotes the formation of linear aggregates. These results provide a plausible explanation for experimental observations, which show that N17 accelerates the formation of linear aggregates in block-copolymeric N17-polyQ sequences. The CAMELOT approach is versatile and is generalizable for simulating the aggregation and phase behavior of a range of block-copolymeric protein sequences.

Profilin reduces aggregation and phase separation of huntingtin N-terminal fragments by preferentially binding to soluble monomers and oligomers

Huntingtin N-terminal fragments (Htt-NTFs) with expanded polyglutamine tracts form a range of neurotoxic aggregates that are associated with Huntingtons disease. Here, we show that aggregation of Htt-NTFs, irrespective of polyglutamine length, yields at least three phases (designated M, S, and F) that are delineated by sharp concentration thresholds and distinct aggregate sizes and morphologies. We found that monomers and oligomers make up the soluble M phase, ∼25-nm spheres dominate in the soluble S phase, and long, linear fibrils make up the insoluble F phase. Previous studies showed that profilin, an abundant cellular protein, reduces Htt-NTF aggregation and toxicity in cells. We confirm that profilin achieves its cellular effects through direct binding to the C-terminal proline-rich region of Htt-NTFs. We show that profilin preferentially binds to Htt-NTF M-phase species and destabilizes aggregation and phase separation by shifting the concentration boundaries for phase separation to higher values through a process known as polyphasic linkage. Our experiments, aided by coarse-grained computer simulations and theoretical analysis, suggest that preferential binding of profilin to the M-phase species of Htt-NTFs is enhanced through a combination of specific interactions between profilin and polyproline segments and auxiliary interactions between profilin and polyglutamine tracts. Polyphasic linkage may be a general strategy that cells utilize to regulate phase behavior of aggregation-prone proteins. Accordingly, detailed knowledge of phase behavior and an understanding of how ligands modulate phase boundaries may pave the way for developing new therapeutics against a variety of aggregation-prone proteins.

Quantitative analysis of multilayer organization of proteins and RNA in nuclear speckles at super resolution

ABSTRACT Nuclear speckles are self-assembled organelles composed of RNAs and proteins. They are proposed to act as structural domains that control distinct steps in gene expression, including transcription, splicing and mRNA export. Earlier studies identified differential localization of a few components within the speckles. It was speculated that the spatial organization of speckle components might contribute directly to the order of operations that coordinate distinct processes. Here, by performing multi-color structured illumination microscopy, we characterized the multilayer organization of speckles at a higher resolution. We found that SON and SC35 (also known as SRSF2) localize to the central region of the speckle, whereas MALAT1 and small nuclear (sn)RNAs are enriched at the speckle periphery. Coarse-grained simulations indicate that the non-random organization arises due to the interplay between favorable sequence-encoded intermolecular interactions of speckle-resident proteins and RNAs. Finally, we observe positive correlation between the total amount of RNA present within a speckle and the speckle size. These results imply that speckle size may be regulated to accommodate RNA accumulation and processing. Accumulation of RNA from various actively transcribed speckle-associated genes could contribute to the observed speckle size variations within a single cell. Summary: Multi-color structured illumination microscopy imaging studies reveal a multilayer organization of nuclear speckles due to the interplay between favorable sequence-encoded intermolecular interactions of speckle-resident proteins and RNAs.

GADIS: Algorithm for designing sequences to achieve target secondary structure profiles of intrinsically disordered proteins

Many intrinsically disordered proteins (IDPs) participate in coupled folding and binding reactions and form alpha helical structures in their bound complexes. Alanine, glycine, or proline scanning mutagenesis approaches are often used to dissect the contributions of intrinsic helicities to coupled folding and binding. These experiments can yield confounding results because the mutagenesis strategy changes the amino acid compositions of IDPs. Therefore, an important next step in mutagenesis-based approaches to mechanistic studies of coupled folding and binding is the design of sequences that satisfy three major constraints. These are (i) achieving a target intrinsic alpha helicity profile; (ii) fixing the positions of residues corresponding to the binding interface; and (iii) maintaining the native amino acid composition. Here, we report the development of a G: enetic A: lgorithm for D: esign of I: ntrinsic secondary S: tructure (GADIS) for designing sequences that satisfy the specified constraints. We describe the algorithm and present results to demonstrate the applicability of GADIS by designing sequence variants of the intrinsically disordered PUMA system that undergoes coupled folding and binding to Mcl-1. Our sequence designs span a range of intrinsic helicity profiles. The predicted variations in sequence-encoded mean helicities are tested against experimental measurements.

To Mix, or To Demix, That Is the Question

Membraneless organelles are micron or sub-micron-sized bodies that consist of multiple proteins and, in many cases, RNA molecules (1,2). Unlike typical intracellular organelles such as mitochondria and nuclei, membraneless organelles lack a surrounding phospholipid membrane. A variety of nuclear (1–3) and cytoplasmic functions (1,2,4–6) are associated with membraneless organelles and these include ribosomal biogenesis, RNA processing, and stress response. How do membraneless organelles form, and how are the hundreds of distinct protein and RNA molecules organized within these organelles? In 2009, Brangwynne et al.

Injectable tissue integrating networks from recombinant polypeptides with tunable order

Emergent properties of natural biomaterials result from the collective effects of nanoscale interactions among ordered and disordered domains. Here, using recombinant sequence design, we have created a set of partially ordered polypeptides to study emergent hierarchical structures by precisely encoding nanoscale order–disorder interactions. These materials, which combine the stimuli-responsiveness of disordered elastin-like polypeptides and the structural stability of polyalanine helices, are thermally responsive with tunable thermal hysteresis and the ability to reversibly form porous, viscoelastic networks above threshold temperatures. Through coarse-grain simulations, we show that hysteresis arises from physical crosslinking due to mesoscale phase separation of ordered and disordered domains. On injection of partially ordered polypeptides designed to transition at body temperature, they form stable, porous scaffolds that rapidly integrate into surrounding tissue with minimal inflammation and a high degree of vascularization. Sequence-level modulation of structural order and disorder is an untapped principle for the design of functional protein-based biomaterials.A protein-based material with temperature-modulated mechanical properties and function is achieved by the rational incorporation of structural ordering and disordering elements into its polypeptide sequence.