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

Recent 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 noisy multigene dynamical system. In this paper we consider the methodology behind TimeTeller, a machine learning tool that analyses the clock as a noisy multigene dynamical 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.

A perspective on the changing landscape of HTS.

Recently, there has been a change in the types of drug target entering early drug discovery portfolios. A significant increase in the number of challenging targets, or which would have historically been classed as intractable, has been observed. Such targets often have shallow or non-existent ligand-binding sites, can have disordered structures or domains or can be involved in protein-protein or protein-DNA interactions. The nature of the screens required to identify useful hits has, by necessity, also changed. The range of drug modalities explored has also increased and the chemistry required to design and optimise these molecules has adapted. In this review, we discuss this changing landscape and provide insights into the future requirements for small-molecule hit and lead generation.

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 characterized. 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 could promote 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 possible therapeutic avenues for the prevention and treatment of respiratory viral infection.

Thermal unfolding methods in drug discovery.

Thermal unfolding methods, applied in both isolated protein and cell-based settings, are increasingly used to identify and characterize hits during early drug discovery. Technical developments over recent years have facilitated their application in high-throughput approaches, and they now are used more frequently for primary screening. Widespread access to instrumentation and automation, the ability to miniaturize, as well as the capability and capacity to generate the appropriate scale and quality of protein and cell reagents have all played a part in these advances. As the nature of drug targets and approaches to their modulation have evolved, these methods have broadened our ability to provide useful chemical start points. Target proteins without catalytic function, or those that may be difficult to express and purify, are amenable to these methods. Here, we provide a review of the applications of thermal unfolding methods applied in hit finding during early drug discovery.

Cancer clocks in tumourigenesis: the p53 pathway and beyond.

Circadian rhythms regulate a vast array of physiological and cellular processes, as well as the hormonal milieu, to keep our cells synchronised to the light-darkness cycle. Epidemiologic studies have implicated circadian disruption in the development of breast and other cancers, and numerous clock genes are dysregulated in human tumours. Here we review the evidence that circadian rhythms, when altered at the molecular level, influence cancer growth. We also note some common pitfalls in circadian-cancer research and how they might be avoided to maximise comparable results and minimise misleading data. Studies of circadian gene mutant mice, and human cancer models in vitro and in vivo, demonstrate that clock genes can impact tumourigenesis. Clock genes influence important cancer-related pathways, ranging from p53-mediated apoptosis to cell cycle progression. Confusingly, clock dysfunction can be both pro- or anti-tumourigenic in a model and cell type-specific manner. Due to this duality, there is no canonical mechanism for clock interaction with tumourigenic pathways. To understand the role of the circadian clock in patients' tumours requires analysis of the molecular clock status compared to healthy tissue. Novel mathematical approaches are under development, but this remains largely aspirational, and is hampered by a lack of temporal information in publicly available datasets. Current evidence broadly supports the notion that the circadian clock is important for cancer biology. More work is necessary to develop an overarching model of this connection. Future studies would do well to analyse the clock network in addition to alterations in single clock genes.

A flexible high content imaging assay for profiling macrophage efferocytosis.

Macrophages are a diverse population of cells originating from the myeloid lineage, which form an important component of the innate immune system, helping to regulate immune response through secretion of pro/anti-inflammatory cytokines. However they also have an important homeostatic role - helping to remove cellular debris and apoptotic cells from the body (a phagocytic process known as efferocytosis). Here we describe a robust 384 well microplate based imaging assay, using apoptotic target cells for the specific quantification of efferocytosis in human primary monocyte derived macrophages. The methodology described allows for the assay to run in either fixed end-point or live-cell format (the former offering multiple morphological and intensity-based readouts, whilst the latter opens the possibility for future expansion of the methodology to encompass kinetic profiling). Within the methodology described we couple high content image acquisition (on the Cell Voyager 7000S) with multi-parametric image analysis - using Perkin Elmer Columbus combined with GeneData Screener.