Biology subjects

Holehouse, A. S.

Publications and source records attributed to Holehouse, A. S..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Wrapping of single-stranded DNA by Replication Protein A and modulation through phosphorylation

Single-stranded DNA (ssDNA) intermediates, which emerge during DNA metabolic processes are shielded by Replication Protein A (RPA). RPA binds to ssDNA and acts as a gatekeeper, directing the ssDNA towards downstream DNA metabolic pathways with exceptional specificity. Understanding the mechanistic basis for such RPA-dependent specificity requires a comprehensive understanding of the structural conformation of ssDNA when bound to RPA. Previous studies suggested a stretching of ssDNA by RPA. However, structural investigations uncovered a partial wrapping of ssDNA around RPA. Therefore, to reconcile the models, in this study, we measured the end-to-end distances of free ssDNA and RPA-ssDNA complexes using single-molecule FRET and Double Electron-Electron Resonance (DEER) spectroscopy and found only a small systematic increase in the end-to-end distance of ssDNA upon RPA binding. This change does not align with a linear stretching model but rather supports partial wrapping of ssDNA around the contour of DNA binding domains of RPA. Furthermore, we reveal how phosphorylation at the key Ser-384 site in the RPA70 subunit provides access to the wrapped ssDNA by remodeling the DNA-binding domains. These findings establish a precise structural model for RPA-bound ssDNA, providing valuable insights into how RPA facilitates the remodeling of ssDNA for subsequent downstream processes.

biochemistry↗

bioRxiv2024

Mutational scanning of CRX classifies clinical variants and reveals biochemical properties of the transcriptional effector domain

Cone-Rod Homeobox, encoded by CRX, is a transcription factor (TF) essential for the terminal differentiation and maintenance of mammalian photoreceptors. Structurally, CRX comprises an ordered DNA-binding homeodomain and an intrinsically disordered transcriptional effector domain. Although a handful of human variants in CRX have been shown to cause several different degenerative retinopathies with varying cone and rod predominance, as with most human disease genes the vast majority of observed CRX genetic variants are uncharacterized variants of uncertain significance (VUS). We performed a deep mutational scan (DMS) of nearly all possible single amino acid substitution variants in CRX, using an engineered cell-based transcriptional reporter assay. We measured the ability of each CRX missense variant to transactivate a synthetic fluorescent reporter construct in a pooled fluorescence-activated cell sorting assay and compared the activation strength of each variant to that of wild-type CRX to compute an activity score, identifying thousands of variants with altered transcriptional activity. We calculated a statistical confidence for each activity score derived from multiple independent measurements of each variant marked by unique sequence barcodes, curating a high-confidence list of nearly 2,000 variants with significantly altered transcriptional activity compared to wild-type CRX. We evaluated the performance of the DMS assay as a clinical variant classification tool using gold-standard classified human variants from ClinVar, and determined that activity scores could be used to identify pathogenic variants with high specificity. That this performance could be achieved using a synthetic reporter assay in a foreign cell type, even for a highly cell type-specific TF like CRX, suggests that this approach shows promise for DMS of other TFs that function in cell types that are not easily accessible. Per-position average activity scores closely aligned to a predicted structure of the ordered homeodomain and demonstrated position-specific residue requirements. The intrinsically disordered transcriptional effector domain, by contrast, displayed a qualitatively different pattern of substitution effects, following compositional constraints without specific residue position requirements in the peptide chain. The observed compositional constraints of the effector domain were consistent with the acidic exposure model of transcriptional activation. Together, the results of the CRX DMS identify molecular features of the CRX effector domain and demonstrate clinical utility for variant classification.

genomics↗

bioRxiv2024

Disordered proteins interact with the chemical environment to tune their protective function during drying

The conformational ensemble and function of intrinsically disordered proteins (IDPs) are sensitive to their solution environment. The inherent malleability of disordered proteins combined with the exposure of their residues accounts for this sensitivity. One context in which IDPs play important roles that is concomitant with massive changes to the intracellular environment is during desiccation (extreme drying). The ability of organisms to survive desiccation has long been linked to the accumulation of high levels of cosolutes such as trehalose or sucrose as well as the enrichment of IDPs, such as late embryogenesis abundant (LEA) proteins or cytoplasmic abundant heat soluble (CAHS) proteins. Despite knowing that IDPs play important roles and are co-enriched alongside endogenous, species-specific cosolutes during desiccation, little is known mechanistically about how IDP-cosolute interactions influence desiccation tolerance. Here, we test the notion that the protective function of desiccation-related IDPs is enhanced through conformational changes induced by endogenous cosolutes. We find that desiccation-related IDPs derived from four different organisms spanning two LEA protein families and the CAHS protein family, synergize best with endogenous cosolutes during drying to promote desiccation protection. Yet the structural parameters of protective IDPs do not correlate with synergy for either CAHS or LEA proteins. We further demonstrate that for CAHS, but not LEA proteins, synergy is related to self-assembly and the formation of a gel. Our results suggest that functional synergy between IDPs and endogenous cosolutes is a convergent desiccation protection strategy seen among different IDP families and organisms, yet, the mechanisms underlying this synergy differ between IDP families.

biochemistry↗

bioRxiv2023

Sequence-ensemble-function relationships for disordered proteins in live cells

Despite lacking a stable three-dimensional structure, intrinsically disordered protein regions (IDRs) are ubiquitous across all kingdoms of life and play essential cellular roles. While rational design of folded proteins has seen substantial recent progress, our ability to design IDRs remains limited. Here, we present GOOSE, a comprehensive computational framework for the rational design of IDRs. GOOSEs versatility and throughput enable us to test thousands of IDR sequences, revealing distinct sequence-ensemble-function relationships. By using GOOSE to rapidly explore these relationships, we design IDRs that can alter their ensembles in response to cell volume changes, create scaffolds for the self-assembly of specific clients, and protect cells from desiccation. Taken together, this work highlights how sequence-function relationships are encoded in IDRs and provides a powerful tool for further exploration.

biophysics↗

bioRxiv2023

Conserved molecular recognition by an intrinsically disordered region in the absence of sequence conservation

Intrinsically disordered regions (IDRs) are critical for cellular function, yet often appear to lack sequence conservation when assessed by multiple sequence alignments. This raises the question of if and how function can be encoded and preserved in these regions despite massive sequence variation. To address this question, we have applied coarse-grained molecular dynamics simulations to investigate non-specific RNA binding of coronavirus nucleocapsid proteins. Coronavirus nucleocapsid proteins consist of multiple interspersed disordered and folded domains that bind RNA. We focussed here on the first two domains of coronavirus nucleocapsid proteins, the disordered N-terminal domain (NTD) followed by the folded RNA binding domain (RBD). While the NTD is highly variable across evolution, the RBD is structurally conserved. This combination makes the NTD-RBD a convenient model system to explore the interplay between an IDR adjacent to a folded domain, and how changes in IDR sequence can influence molecular recognition of a partner. Our results reveal a surprising degree of sequence-specificity encoded by both the composition and the precise order of the amino acids in the NTD. The presence of an NTD can - depending on the sequence - either suppress or enhance RNA binding. Despite this sensitivity, large-scale variation in NTD sequences is possible while certain sequence features are retained. Consequently, a conformationally-conserved fuzzy RNA:protein complex is found across nucleocapsid protein orthologs, despite large-scale changes in both NTD sequence and RBD surface chemistry. Taken together, these insights shed light on the ability of disordered regions to preserve functional characteristics despite their sequence variability.

biophysics↗

bioRxiv2023

Helicity of a tardigrade disordered protein promotes desiccation tolerance

In order to survive extreme drying (anhydrobiosis), many organisms, spanning every kingdom of life, accumulate intrinsically disordered proteins (IDPs). For decades, the ability of anhydrobiosis-related IDPs to form transient amphipathic helices has been suggested to be important for promoting desiccation tolerance. However, evidence empirically supporting the necessity and/or sufficiency of helicity in mediating anhydrobiosis is lacking. Here we demonstrate that the linker region of CAHS D, a desiccation-related IDP from tardigrades that contains significant helical structure, is the protective portion of this protein. Perturbing the sequence composition and grammar of the linker region of CAHS D, through the insertion of helix-breaking prolines, modulating the identity of charged residues, sequence scrambling, or replacement of hydrophobic amino acids with serine or glycine residues results in variants with different degrees of helical structure. Importantly, the resulting helicity of these variants generated through similar helix breaking modalities correlates strongly with their ability to promote desiccation tolerance, providing direct evidence that helical structure is necessary for robust protection conferred by this desiccation-related IDP. However, correlation of protective capacity and helical content in variants generated through different helix perturbing modalities do not show as strong a trend, suggesting that while helicity is important it is not the only property that makes a protein protective during desiccation. These results provide direct evidence for the decades old theory that helicity of desiccation-related IDPs is linked to their anhydrobiotic capacity.

biochemistry↗

bioRxiv2023

Labile assembly of a tardigrade protein induces biostasis

Tardigrades are microscopic animals that survive desiccation by inducing biostasis. To survive drying tardigrades rely on intrinsically disordered CAHS proteins that form gels. However, the sequence features and mechanisms underlying gel formation and the necessity of gelation for protection have not been demonstrated. Here we report a mechanism of gelation for CAHS D similar to that of intermediate filaments. We show that gelation restricts molecular motion, immobilizing and protecting labile material from the harmful effects of drying. In vivo, we observe that CAHS D forms fiber-like condensates during osmotic stress. Condensation of CAHS D improves survival of osmotically shocked cells through at least two mechanisms: reduction of cell volume change and reduction of metabolic activity. Importantly, condensation of CAHS D is reversible and metabolic rates return to control levels after CAHS condensates are resolved. This work provides insights into how tardigrades induce biostasis through the self-assembly of CAHS gels.

physiology↗

bioRxiv2023

Direct prediction of intrinsically disordered protein conformational properties from sequence

Intrinsically disordered regions (IDRs) are ubiquitous across all domains of life and play a range of functional roles. While folded domains are generally well-described by a single 3D structure, IDRs exist in a collection of interconverting states known as an ensemble. This structural heterogeneity means IDRs are largely absent from the PDB, contributing to a lack of computational approaches to predict ensemble conformational properties from sequence. Here we combine rational sequence design, large-scale molecular simulations, and deep learning to develop ALBATROSS, a deep learning model for predicting IDR ensemble dimensions from sequence. ALBATROSS enables the instantaneous prediction of ensemble average properties at proteome-wide scale. ALBATROSS is lightweight, easy-to-use, and accessible as both a locally installable software package and a point-and-click style interface in the cloud. We first demonstrate the applicability of our predictors by examining the generalizability of sequence-ensemble relationships in IDRs. Then, we leverage the high-throughput nature of ALBATROSS to characterize emergent biophysical behavior of IDRs within and between proteomes. Update from previous versionO_LIThis preprint reports an updated version of the ALBATROSS network weights trained on simulations of over 42,000 sequences. C_LIO_LIIn addition, we provide new colab notebooks that enable proteome-wide IDR prediction and annotation in minutes. C_LIO_LIAll conclusions and observations made in versions 1 and 2 of this manuscript remain true and robust. C_LI

biophysics↗

bioRxiv2023

FIREBALL: A tool to fit protein phase diagrams based on mean-field theories for polymer solutions

Biomolecular condensates form via phase transitions of condensate-specific biomacromolecules. Intrinsically disordered regions (IDRs) featuring the appropriate sequence grammar can contribute homotypic and heterotypic interactions to the driving forces for phase separation of multivalent proteins. At this juncture, experiments and computations have matured to the point where the concentrations of coexisting dense and dilute phases can be quantified for individual IDRs in complex milieus both in vitro and in vivo. For a macromolecule such as a disordered protein in a solvent, the locus of points that connects concentrations of the two coexisting phases defines a phase boundary or binodal. Often, only a few points along the binodal, especially in the dense phase, are accessible for measurement. In such cases and for quantitative and comparative analysis of parameters that describe the driving forces for phase separation, it is useful to fit measured or computed binodals to well-known mean-field free energies for polymer solutions. Unfortunately, the non-linearity of the underlying free energy functions makes it challenging to put mean-field theories into practice. Here, we present FIREBALL, a suite of computational tools designed to enable efficient construction, analysis, and fitting to experimental or computed data of binodals. We show that depending on the theory being used, one can also extract information regarding coil-to-globule transitions of individual macromolecules. Here, we emphasize the ease-of-use and utility of FIREBALL using examples based on data for two different IDRs. Statement of SignificanceMacromolecular phase separation drives the assembly of membraneless bodies known as biomolecular condensates. Measurements and computer simulations can now be brought to bear to quantify how the concentrations of macromolecules in coexisting dilute and dense phases vary with changes to solution conditions. These mappings can be fit to analytical expressions for free energies of solution to extract information regarding parameters that enable comparative assessments of the balance of macromolecule-solvent interactions across different systems. However, the underlying free energies are non-linear and fitting them to actual data is non-trivial. To enable comparative numerical analyses, we introduce FIREBALL, a user-friendly suite of computational tools that allows one to generate, analyze, and fit phase diagrams and coil-to-globule transitions using well-known theories.

biophysics↗

bioRxiv2023

The analytical Flory random coil is a simple-to-use reference model for unfolded and disordered proteins

Denatured, unfolded, and intrinsically disordered proteins (collectively referred to here as unfolded proteins) can be described using analytical polymer models. These models capture various polymeric properties and can be fit to simulation results or experimental data. However, the model parameters commonly require users decisions, making them useful for data interpretation but less clearly applicable as stand-alone reference models. Here we use all-atom simulations of polypeptides in conjunction with polymer scaling theory to parameterize an analytical model of unfolded polypeptides that behave as ideal chains ({nu} = 0.50). The model, which we call the analytical Flory Random Coil (AFRC), requires only the amino acid sequence as input and provides direct access to probability distributions of global and local conformational order parameters. The model defines a specific reference state to which experimental and computational results can be compared and normalized. As a proof-of-concept, we use the AFRC to identify sequence-specific intramolecular interactions in simulations of disordered proteins. We also use the AFRC to contextualize a curated set of 145 different radii of gyration obtained from previously published small-angle X-ray scattering experiments of disordered proteins. The AFRC is implemented as a stand-alone software package and is also available via a Google colab notebook. In summary, the AFRC provides a simple-to-use reference polymer model that can guide intuition and aid in interpreting experimental or simulation results.

biophysics↗

bioRxiv2023

Aberrant phase separation is a common killing strategy of positively charged peptides in biology and human disease

Positively charged repeat peptides are emerging as key players in neurodegenerative diseases. These peptides can perturb diverse cellular pathways but a unifying framework for how such promiscuous toxicity arises has remained elusive. We used mass-spectrometry-based proteomics to define the protein targets of these neurotoxic peptides and found that they all share similar sequence features that drive their aberrant condensation with these positively charged peptides. We trained a machine learning algorithm to detect such sequence features and unexpectedly discovered that this mode of toxicity is not limited to human repeat expansion disorders but has evolved countless times across the tree of life in the form of cationic antimicrobial and venom peptides. We demonstrate that an excess in positive charge is necessary and sufficient for this killer activity, which we name polycation poisoning. These findings reveal an ancient and conserved mechanism and inform ways to leverage its design rules for new generations of bioactive peptides.

cell biology↗

bioRxiv2023

SOURSOP: A Python package for the analysis of simulations of intrinsically disordered proteins

Conformational heterogeneity is a defining hallmark of intrinsically disordered proteins and protein regions (IDRs). The functions of IDRs and the emergent cellular phenotypes they control are associated with sequence-specific conformational ensembles. Simulations of conformational ensembles that are based on atomistic and coarse-grained models are routinely used to uncover the sequence-specific interactions that may contribute to IDR functions. These simulations are performed either independently or in conjunction with data from experiments. Functionally relevant features of IDRs can span a range of length scales. Extracting these features requires analysis routines that quantify a range of properties. Here, we describe a new analysis suite SOURSOP, an object-oriented and open-source toolkit designed for the analysis of simulated conformational ensembles of IDRs. SOURSOP implements several analysis routines motivated by principles in polymer physics, offering a unique collection of simple-to-use functions to characterize IDR ensembles. As an extendable framework, SOURSOP supports the development and implementation of new analysis routines that can be easily packaged and shared.

biophysics↗

bioRxiv2023

The disordered N-terminal tail of SARS CoV-2 Nucleocapsid protein forms a dynamic complex with RNA

The SARS-CoV-2 Nucleocapsid (N) protein is responsible for condensation of the viral genome. Characterizing the mechanisms controlling nucleic acid binding is a key step in understanding how condensation is realized. Here, we focus on the role of the RNA Binding Domain (RBD) and its flanking disordered N-Terminal Domain (NTD) tail, using single-molecule Forster Resonance Energy Transfer and coarse-grained simulations. We quantified contact site size and binding affinity for nucleic acids and concomitant conformational changes occurring in the disordered region. We found that the disordered NTD increases the affinity of the RBD for RNA by about 50-fold. Binding of both nonspecific and specific RNA results in a modulation of the tail configurations, which respond in an RNA length-dependent manner. Not only does the disordered NTD increase affinity for RNA, but mutations that occur in the Omicron variant modulate the interactions, indicating a functional role of the disordered tail. Finally, we found that the NTD-RBD preferentially interacts with single-stranded RNA and that the resulting protein:RNA complexes are flexible and dynamic. We speculate that this mechanism of interaction enables the Nucleocapsid protein to search the viral genome for and bind to high-affinity motifs.

biophysics↗

bioRxiv2022

A condensate forming tether for lariat debranching enzyme is defective in non-photosensitive trichiothiodystrophy

The pre-mRNA life cycle requires intron processing; yet, how intron processing defects influence splicing and gene expression is unclear. Here, we find TTDN1, which is frequently mutated in non-photosensitive trichothiodystrophy (NP-TTD), functionally links intron lariat processing to the spliceosome. The conserved TTDN1 C-terminal region directly binds lariat debranching enzyme DBR1, while its N-terminal intrinsically disordered region (IDR) binds the intron binding complex (IBC). The IDR forms condensates in vitro and is needed for IBC interaction. TTDN1 loss causes significant intron lariat accumulation, as well as splicing and gene expression defects, mirroring phenotypes observed in NP-TTD patient cells. Ttdn1{Delta}/{Delta} mice recapitulate intron processing defects and neurodevelopmental phenotypes seen in NP-TTD. A DBR1-IDR fusion recruits DBR1 to the IBC and circumvents the requirement for TTDN1, indicating this tethering role as its major molecular function. Collectively, our findings unveil key functional connections between lariat processing, splicing outcomes, and NP-TTD molecular pathology.

biochemistry↗

bioRxiv2022

SHEPHARD: a modular and extensible software architecture for analyzing and annotating large protein datasets

The emergence of high-throughput experiments and high-resolution computational predictions has led to an explosion in the quality and volume of protein sequence annotations at proteomic scales. Unfortunately, integrating and analyzing complex sequence annotations remains logistically challenging. Here we present SHEPHARD, a software package that makes large-scale integrative protein bioinformatics trivial. SHEPHARD is provided as a stand-alone package and with a pre-compiled set of human annotations in a Google Colab notebook.

bioinformatics↗

bioRxiv2022

Metapredict V2: An update to metapredict, a fast, accurate, and easy-to-use predictor of consensus disorder and structure

Intrinsically disordered proteins and protein regions make up 20-40% of most eukaryotic proteomes and play essential roles in a wide gamut of cellular processes, from intracellular trafficking to epigenetic silencing. Given their importance, the ability to robustly, quickly, and easily identify IDRs within large proteins is critical. Here we present metapredict V2, an update to our deep-learning-based disorder predictor metapredict. Metapredict V2 has substantially improved accuracy, more features, and a more user-friendly interface via our web server (https://metapredict.net/), Python package, and command-line tool. To illustrate V2s improved performance we undertake a systematic analysis of human transcription factors, as well as illustrate that metapredict V2 works well for synthetic or non-natural proteins. KEY POINTSO_LIMetapredict is a fast and easy-to-use disorder predictor released in 2021. C_LIO_LIMetapredict V2 was released in March 2022 and includes improved accuracy and new features. C_LIO_LIMetapredict V2 is now the default metapredict implementation, although the original implementation is available as legacy metapredict. C_LIO_LIThis manuscript provides a summary of how we improved the accuracy of metapredict and compares the original version (legacy) to our improved version (V2) C_LIO_LIThis manuscript will not be submitted to a journal; if you use metapredict V2 please cite the original paper and make reference to the fact that V2 is being used. C_LI

bioinformatics↗

bioRxiv2022

The kinetic landscape of human transcription factors

Cell-to-cell variability is shaped by transcription dynamics because genes are transcribed in bursts interspersed with inactive periods. The stochasticity of bursting means that genes transcribed in rare bursts exhibit more heterogeneity at the single cell level than genes that burst often 1, 2. Transcription starts with the binding of Transcription Factors (TFs) to specific sequence motifs where they recruit the transcription machinery 3. In some systems, individual TF binding events temporally correlate with the firing of transcriptional bursts, defining the target genes frequency and duration 4-6. However, in the absence of methods that assess the impact of different TFs on transcription dynamics at the same genetic loci, it remains unclear whether DNA binding kinetics are the sole determinant of bursting. Here we develop an imaging-based synthetic recruitment assay, CRISPRburst, and measure how 92 human TFs impact bursting kinetics. We show that TFs recruited to chromatin under identical conditions generate diverse bursting signatures, some TFs increasing the probability of the gene turning on while others increase the number of mRNA molecules transcribed per burst. We find that the association of TFs with specific protein partners determines their bursting output, and train a model to predict the kinetic signatures of all human TFs. These kinetic signatures can be used as a TF classification system complementary to existing families based on DNA binding domains. Additionally, kinetic signatures provide a rational framework to design synthetic activators, model transcription regulation, and understand expression heterogeneity.

biophysics↗

bioRxiv2022

Composition can buffer protein dynamics within liquid-like condensates.

Most non-membrane-bound compartments in cells that form via phase separation have complex composition. While phase separation of individual proteins that form these compartments is well-documented, the mechanisms that modulate dynamics of individual proteins in multicomponent systems remain unclear. Here, we used in vitro reconstitution and in vivo experiments to investigate how the dynamics of a scaffold protein PGL-3 is regulated within the liquid-like P granule compartment in C. elegans. Using mutational and biophysical perturbations, we generated PGL-3 constructs that form condensates in vitro with widely varying dynamics. Using these PGL-3 constructs, we show that introducing other P granule components buffers against change of dynamics within liquid-like condensates. This dynamics-buffering effect is mediated by weak interactions among two or more components. Such dynamics-buffering may contribute to robust functional output of cellular liquid-like compartments.

cell biology↗