Biology subjects

Bracken, C.

Publications and source records attributed to Bracken, C..

5 recordsLinked to original sources

bioRxiv2022

An environmentally ultrasensitive fluorine-19 NMR probe for monitoring protein conformational equilibria

Limited chemical shift dispersion represents a significant barrier to studying multi-state equilibria of large membrane proteins by 19F NMR. We describe a novel monofluoroethyl 19F probe that dramatically increases the chemical shift dispersion. The improved conformational sensitivity and line shape enable the detection of previously unresolved states in 1D NMR spectra of a 134 kDa membrane transporter. Changes in the populations of these states in response to ligand binding, mutations, and temperature correlate with population changes of distinct conformations in structural ensembles determined by single-particle cryo-electron microscopy. Thus, 19F NMR can guide sample preparation to discover and visualize novel conformational states and facilitate image analysis and 3D classification.

biophysics↗

bioRxiv2020

DriverGroup: A novel method for identifying drivergene groups

MotivationIdentifying cancer driver genes is a key task in cancer informatics. Most exisiting methods are focused on individual cancer drivers which regulate biological processes leading to cancer. However, the effect of a single gene may not be sufficient to drive cancer progression. Here, we hypothesise that there are driver gene groups that work in concert to regulate cancer and we develop a novel computational method to detect those driver gene groups. ResultsWe develop a novel method named DriverGroup to detect driver gene groups by using gene expression and gene interaction data. The proposed method has three stages: (1) Constructing the gene network, (2) Discovering critical nodes of the constructed network, and (3) Identifying driver gene groups based on the discovered critical nodes. Before evaluating the performance of DriverGroup in detecting cancer driver groups, we firstly assess its performance in detecting the influence of gene groups, a key step of DriverGroup. The application of DriverGroup to DREAM4 data demonstrates that it is more effective than other methods in detecting the regulation of gene groups. We then apply DriverGroup to the BRCA dataset to identify coding and non-coding driver groups for breast cancer. The identified driver groups are promising as several group members are confirmed to be related to cancer in literature. We further use the predicted driver groups in survival analysis and the results show that the survival curves of patient subpopulations classified using the predicted driver groups are significantly differentiated, indicating the usefulness of DriverGroup. Availability and implementationDriverGroup is available at https://github.com/pvvhoang/DriverGroup ContactThuc.Le@unisa.edu.au Supplementary informationSupplementary data are available at Bioinformatics online.

systems biology↗

bioRxiv2020

pDriver: A novel method for unravelling personalised coding and miRNA cancer drivers

MotivationUnravelling cancer driver genes is important in cancer research. Although computational methods have been developed to identify cancer drivers, most of them detect cancer drivers at population level. However, two patients who have the same cancer type and receive the same treatment may have different outcomes because each patient has a different genome and their disease might be driven by different driver genes. Therefore new methods are being developed for discovering cancer drivers at individual level, but existing personalised methods only focus on coding drivers while microRNAs (miRNAs) have been shown to drive cancer progression as well. Thus, novel methods are required to discover both coding and miRNA cancer drivers at individual level. ResultsWe propose the novel method, pDriver, to discover personalised cancer drivers. pDriver includes two stages: (1) Constructing gene networks for each cancer patient and (2) Discovering cancer drivers for each patient based on the constructed gene networks. To demonstrate the effectiveness of pDriver, we have applied it to five TCGA cancer datasets and compared it with the state-of-the-art methods. The result indicates that pDriver is more effective than other methods. Furthermore, pDriver can also detect miRNA cancer drivers and most of them have been confirmed to be associated with cancer by literature. We further analyse the predicted personalised drivers for breast cancer patients and the result shows that they are significantly enriched in many GO processes and KEGG pathways involved in breast cancer. Availability and implementationpDriver is available at https://github.com/pvvhoang/pDriver ContactThuc.Le@unisa.edu.au Supplementary informationSupplementary data are available at Bioinformatics online.

systems biology↗

bioRxiv2019

Monitoring Dynamics of Large Membrane Proteins by 19F Paramagnetic Longitudinal Relaxation: Domain Movement in a Glutamate Transporter Homolog

In proteins where conformational changes are functionally important, the number of accessible states and their dynamics are often difficult to establish. Here we describe a novel 19F-NMR spectroscopy approach to probe dynamics of large membrane proteins. We labeled a glutamate transporter homologue with a 19F probe via cysteine chemistry and with a Ni2+ ion via chelation by a di-histidine motif. We used distance-dependent enhancement of the longitudinal relaxation of 19F nuclei by the paramagnetic metal to assign the observed resonances. We identified two outward- and one inward-facing states of the transporter, in which the substrate-binding site is near the extracellular and intracellular solutions, respectively. We then resolved the structure of the unanticipated second outward-facing state by Cryo-EM. Finally, we showed that the rates of the conformational exchange are accessible from measurements of the metal-enhanced longitudinal relaxation of 19F nuclei.

biophysics↗

bioRxiv2018

Neutralization of a Distributed Coulombic Switch Precisely Tunes Reflectin Assembly

Reflectin proteins are widely distributed in reflective structures in cephalopods, but only in Loliginid squids are they and the sub-wavelength photonic structures they control dynamically tunable, driving changes in skin color for camouflage and communication. The reflectins are block copolymers with repeated canonical domains interspersed with cationic linkers. Neurotransmitter-activated signal transduction culminates in catalytic phosphorylation of the tunable reflectins cationic linkers, with the resulting charge-neutralization overcoming Coulombic repulsion to progressively allow condensation and concommitant assembly to form multimeric spheres of tunable size. Structural transitions of reflectins A1 and A2 were analyzed by dynamic light scattering, transmission electron microscopy, solution small angle x-ray scattering, circular dichroism, atomic force microscopy, and fluorimetry. We analyzed the assembly behavior of phospho-mimetic, deletion, and other mutants in conjunction with pH-titration as an in vitro surrogate of phosphorylation to discover a predictive relationship between the extent of neutralization of the proteins net charge density and the size of resulting multimeric protein assemblies of narrow polydispersity. Comparison of mutants shows this sensitivity to neutralization resides in the linkers and is spatially distributed along the protein. These results are consistent with the behavior of a charge-stabilized colloidal system, while imaging of large particles, and analysis of sequence composition, suggest that assembly may proceed through a transient liquid-liquid phase separated intermediate. These results offer insights into the basis of reflectin-based tunable biophotonics and open new paths for the design of new reflectin mutants with tunable properties.

molecular biology↗