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Usselmann, L.

Publications and source records attributed to Usselmann, L..

3 recordsLinked to original sources

Denaturation-sensitive BRET probes enable intracellular thermal shift measurements across diverse protein targets and biomolecular complexes

Thermal shift assays have revolutionized drug discovery, but can be limited in sensitivity and scalability. Combining the unique attributes of differential scanning fluorimetry (DSF) and cellular thermal shift (CETSA), we report the methodological framework for the bioluminescence resonance energy transfer shift assay (BRETSA). BRETSA utilizes denaturation sensitive BRET probes, in combination with luciferase-tagged target proteins, to track and longitudinally record thermal shift in living cells. Denaturation profiles were successfully measured for over 500 globular proteins, spanning 24 target families in diverse cellular compartments. Among these, target engagement was confirmed for over 200 proteins; including validated drug targets as well as understudied members of the kinase subfamily. Leveraging orthosteric, allosteric, and covalent ligands in potency studies, this method offers improved sensitivity and scalability compared to other thermal shift methods. We extend the utility of BRETSA to interrogate target engagement at biomolecular complexes and query cooperative binding for molecular glues and emerging tricomplex drug modalities.

pharmacology and toxicology↗

TimeTeller: a tool to probe the circadian clock as a multigene dynamical system

AO_SCPLOWBSTRACTC_SCPLOWRecent studies have established that the circadian clock influences onset, progression and therapeutic outcomes in a number of diseases including cancer and heart diseases. Therefore, there is a need for tools to measure the functional state of the molecular circadian clock and its downstream targets in patients. Moreover, the clock is a multi-dimensional stochastic oscillator and there are few tools for analysing it as a system. In this paper we consider the methodology behind Time-Teller, a machine learning tool that analyses the clock as a system and aims to estimate circadian clock function from a single transcriptome by modelling the multi-dimensional state of the clock. We demonstrate its potential for clock systems assessment by applying it to mouse, baboon and human microarray and RNA-seq data and show how to visualise and quantify the global structure of the clock, quantitatively stratify individual transcriptomic samples by clock dysfunction and globally compare clocks across individuals, conditions and tissues thus highlighting its potential relevance for advancing circadian medicine.

systems biology↗

Sleep and circadian rhythm disruption alters the lung transcriptome to predispose to viral infection

Sleep and circadian rhythm disruption (SCRD), as encountered during shift work, increases the risk of respiratory viral infection including SARS-CoV-2. However, the mechanism(s) underpinning higher rates of respiratory viral infection following SCRD remain poorly characterised. To address this, we investigated the effects of acute sleep deprivation on the mouse lung transcriptome. Here we show that sleep deprivation profoundly alters the transcriptional landscape of the lung, causing the suppression of both innate and adaptive immune systems, disrupting the circadian clock, and activating genes implicated in SARS-CoV-2 replication, thereby generating a lung environment that promotes viral infection and associated disease pathogenesis. Our study provides a mechanistic explanation of how SCRD increases the risk of respiratory viral infections including SARS-CoV-2 and highlights therapeutic avenues for the prevention and treatment of COVID-19.

neuroscience↗