Biology subjects

Curtis, J. E.

Publications and source records attributed to Curtis, J. E..

4 recordsLinked to original sources

bioRxiv2025

Solution conformational differences between conventional and CENP-A nucleosomes are accentuated by reversible deformation under high pressure

Solution-based interrogation of the physical nature of nucleosomes has its roots in X-ray and neutron scattering experiments, including those that provided the initial observation that DNA wraps around core histones. In this study, we performed a comprehensive small-angle scattering study to compare canonical nucleosomes with variant centromeric nucleosomes harboring the histone variant, CENP-A. We used nucleosome core particles (NCPs) assembled on an artificial positioning sequence (Widom 601) and compared these to those assembled on a natural -satellite DNA cloned from human centromeres. We establish the native solution properties of octameric H3 and CENP-A NCPs using analytical ultracentrifugation (AUC), small-angle X-ray scattering (SAXS), and contrast variation small-angle neutron scattering (CV-SANS). Using high-pressure SAXS (HP-SAXS), we discovered that both histone identity and DNA sequence have an impact on the stability of octameric nucleosomes in solution under high pressure (300 MPa), with evidence of reversible unwrapping in these experimental conditions. Both canonical nucleosomes harboring conventional histone H3 and their centromeric counterparts harboring CENP-A have a substantial increase in their radius of gyration, but this increase is much less prominent for centromeric nucleosomes. More broadly for chromosome-related research, we note that as HP-SAXS methodologies expand in their utility, we anticipate this will provide a powerful solution-based approach to study nucleosomes and higher-order chromatin complexes.

biophysics↗

bioRxiv2024

SAXS/MC studies of the mixed-folded protein Cdt1 reveal monomeric, folded over conformations

Cdt1 is a protein critical for DNA replication licensing and is well-established to be a binding partner of the minichromosome maintenance (MCM) complex. Cdt1 has also been demonstrated to have an emerging, "moonlighting" role at the kinetochore via direct binding to microtubules and to the Ndc80 complex. However, it is not known how the structure and conformations of Cdt1 could allow for these multiple, completely unique sets of protein complexes. And while there exist multiple robust methods to study entirely folded or entirely unfolded proteins, structure-function studies of combined, mixed folded/disordered proteins remain challenging. It this work, we employ multiple orthogonal biophysical and computational techniques to provide a detailed structural characterization of human Cdt1 92-546. DSF and DSCD show both folded winged helix (WH) domains of Cdt1 are relatively unstable. CD and NMR show the N-terminal and the linker regions are intrinsically disordered. Using DLS and SEC-MALS, we show that Cdt1 is polydisperse, monomeric at high concentrations, and without any apparent inter-molecular self-association. SEC-SAXS of the monomer in solution enabled computational modeling of the protein in silico. Using the program SASSIE, we performed rigid body Monte Carlo simulations to generate a conformational ensemble. Using experimental SAXS data, we filtered for conformations which did and did not fit our data. We observe that neither fully extended nor extremely compact Cdt1 conformations are consistent with our SAXS data. The best fit models have the N-terminal and linker regions extended into solution and the two folded domains close to each other in apparent "folded over" conformations. The best fit Cdt1 conformations are consistent with a function as a scaffold protein which may be sterically blocked without the presence of binding partners. Our studies also provide a template for combining experimental and computational biophysical techniques to study mixed-folded proteins.

biophysics↗

bioRxiv2021

Cell surface hydrophobicity determines Pseudomonas aeruginosa aggregate assembly

Bacteria live in spatially organized aggregates during chronic infections, where they adapt to the host environment, evade immune responses and resist therapeutic interventions. Although it is known that environmental factors such as polymers influence bacterial aggregation, it is not clear how bacterial adaptation during chronic infection impacts the formation and spatial organization of aggregates in the presence of polymers. Here we show that in an in vitro model of cystic fibrosis (CF) containing the polymers eDNA and mucin, O-specific antigen is a major factor in determining the formation of two distinct aggregate assembly types of Pseudomonas aeruginosa due to alterations in cell surface hydrophobicity. Our findings suggest that during chronic infection, interplay between cell surface properties and polymers in the environment may influence the formation and structure of bacterial aggregates, which would shed new light on the fitness costs and benefits of O-antigen production in environments such as CF lungs. ImportanceDuring chronic infection, several factors contribute to the biogeography of microbial communities. Heterogeneous populations of Pseudomonas aeruginosa form aggregates in cystic fibrosis airways, however, the impact of this population heterogeneity on spatial organization and aggregate assembly is not well understood. In this study we found that changes in O-specific antigen determine the spatial organization of P. aeruginosa cells by altering the relative cell surface hydrophobicity. This finding suggests a role for O-antigen in regulating P. aeruginosa aggregate size and shape in cystic fibrosis airways.

microbiology↗

bioRxiv2018

BEES: Bayesian Ensemble Estimation from SAS, a SASSIE-web Module

1Many biomolecular complexes exist in a flexible ensemble of states in solution which are necessary to perform their biological function. Small angle scattering (SAS) measurements are a popular method for characterizing these flexible molecules due to their relative ease of use and ability to simultaneously probe the full ensemble of states. However, SAS data is typically low-dimensional and difficult to interpret without the assistance of additional structural models. In theory, experimental SAS curves can be reconstituted from a linear combination of theoretical models, although this procedure carries significant risk of overfitting the inherently low-dimensional SAS data. Previously, we developed a Bayesian-based method for fitting ensembles of model structures to experimental SAS data that rigorously avoids overfitting. However, we have found that these methods can be difficult to incorporate into typical SAS modeling workflows, especially for users that are not experts in computational modeling. To this end, we present the "Bayesian Ensemble Estimation from SAS" (BEES) program. Two forks of BEES are available, the primary one existing as module for the SASSIE webserver and a developmental version that is a standalone python program. BEES allows users to exhaustively sample ensemble models constructed from a library of theoretical states and to interactively analyze and compare each models performance. The fitting routine also allows for secondary data sets to be supplied, thereby simultaneously fitting models to both SAS data as well as orthogonal information. The flexible ensemble of K63-linked ubiquitin trimers is presented as an example of BEES capabilities.

biophysics↗