Biology subjects

Telfer, A.

Publications and source records attributed to Telfer, A..

4 recordsLinked to original sources

bioRxiv2025

Time-resolved ligand dynamics revealed in a β-lactamase using room-temperature serial crystallography

{beta}-Lactamases catalyze {beta}-lactam antibiotic hydrolysis and are important contributors to bacterial antimicrobial resistance; {beta}-lactamase inhibitors are widely used to overcome {beta}-lactamase-mediated antibiotic resistance. Nucleophilic serine {beta}-lactamases (SBLs) react with their substrates and clinically available inhibitors via a covalent reaction to give complexes which can undergo further reaction. Using room temperature drop on fixed target serial crystallography, where ligands are rapidly mixed with microcrystals, and classical single-crystal crystallography at cryogenic temperatures, we investigate the reversible covalent reaction of the SBL CTX-M-15 with the diazobicyclooctane inhibitor avibactam. We observe avibactam covalently reacted (ring-opened) with the nucleophilic Ser70, at timepoints from 80 ms to minutes (room temperature) and hours (100 K). These crystallographic data reveal time-dependent movement of the avibactam carbamoyl complex, from 1.3 s onwards, that has implications for the 5-exo-trig recyclization mechanism that determines inhibitor reformation. Combined with molecular dynamics simulations and quantum mechanics calculations at the density functional theory level, the results show that in the first seconds of the reaction the avibactam N-sulfate nitrogen is poorly positioned for recyclization. This subsequently equilibrates after 10 s to a stable endpoint that is in a conformation potentially primed to initiate recyclization through attack of the N-sulfate nitrogen on the carbamoyl carbon. These results further demonstrate the capacity of room-temperature serial crystallography to capture time-resolved changes in ligand conformation at an enzyme active site, complementing discrete classical cryo-crystallography. These data inform on ligand dynamics and the stereoelectronics of diazobicyclooctane inhibition, aiding drug discovery efforts to develop inhibitors of nucleophilic enzymes.

biochemistry↗

bioRxiv2025

Hundred-Picolitre Droplet on Demand Tape Drive and XES Prototypes for Time-Resolved Serial Crystallography at VMXi, Diamond Light Source

Time resolved X-ray crystallography is experiencing a resurgence, in part, because of serial methods that readily allow scientists to create stop-motion movies of macromolecular function of photoactivation, enzyme catalysed reactions, and ligand-induced conformational changes triggering further downstream signalling events. While some reactions can be initiated with light, either naturally or using photocaged compounds, a more generally applicable approach is to mix microcrystals with reagents at varying time points prior to exposure to the X-ray beam. A powerful approach has been to combine droplet on demand tape drive sample delivery with X-ray emission spectroscopy (XES) that correlates atomic structure with electronic states of metal ions within the sample. To our knowledge, such a combined methodology has not been deployed previously at a synchrotron beamline and has been restricted to XFELs. Here we describe prototype experiments along the development pathway to a combined droplet on demand diffraction and XES system at the microfocus beamline VMXi at Diamond Light Source. We demonstrate the collection of a high-quality serial diffraction data set from microcrystals within hundreds of picolitre-volume droplets deposited on a moving tape. In separate experiments at VMXi, we collected XES data from microcrystals of a copper enzyme delivered using a high viscosity extruder. Together, these results demonstrate the feasibility of combined droplet on demand serial crystallography and XES experiments using a third-generation synchrotron beamline; project work currently underway at Diamond Light Source. SynopsisWe describe proof of concept experiments towards correlated serial crystallography (SSX) and X-ray emission spectroscopy (XES) from microcrystals at a microfocus synchrotron beamline. A droplet on demand tape drive system delivers microcrystals to the beam within well-separated, hundreds of picolitre-volume droplets while XES allows validation of redox states of metals within protein crystals.

biophysics↗

bioRxiv2024

Inverse Reinforcement Learning to Study Motivation in Mouse Behavioral Paradigms

Motivation describes the underlying goals that drive animal and agent behavior. In Neuroscience, behavioral paradigms are used to quantify the motivations of mice and used to gain insights into traits and diseases which can be translated to humans. In recent years, Computer Vision models are becoming widely adopted by Neuroscientists to score mouse behavior associated with motivations such as hunger and anxiety. However, a single motivation can be expressed by multiple different behaviors, and a single behavior can be linked to multiple motivations. Therefore the ideal analysis of motivational paradigms would attempt to directly recover the underlying motivations guiding behavior, rather than indirectly score their associated behaviors. In this paper, we move towards this goal by applying Inverse Reinforcement Learning to study the underlying motivations that drive mouse behavior.

animal behavior and cognition↗

bioRxiv2024

Scale-sensitive Mouse Facial Expression Pipeline using a Surrogate Calibration Task

Emotions are complex neuro-physiological states that influence behavior. While emotions have been instrumental to our survival, they are also closely associated with prevalent disorders such as depression and anxiety. The development of treatments for these disorders has relied on animal models, in particular, mice are often used in pre-clinical testing. To compare effects between treatment groups, researchers have increasingly used machine learning to help quantify behaviors associated with emotionality. Previous work has shown that computer vision can be used to detect facial expressions in mice. In this work, we create a novel dataset for depressive-like mouse facial expressions using varying LypoPolySaccharide (LPS) dosages and demonstrate that a machine learning model trained on this dataset was able to detect differences in magnitude via dosage amount.

animal behavior and cognition↗