cellPLATO - an unsupervised method for identifying cell behaviour in heterogeneous cell trajectory data.

Advances in imaging, segmentation and tracking have led to the routine generation of large and complex microscopy datasets. New tools are required to process this 'phenomics' type data. Here, we present 'Cell PLasticity Analysis Tool' (cellPLATO), a Python-based analysis software designed for measurement and classification of cell behaviours based on clustering features of cell morphology and motility. Used after segmentation and tracking, the tool extracts features from each cell per timepoint, using them to segregate cells into dimensionally reduced behavioural subtypes. Resultant cell tracks describe a 'behavioural ID' at each timepoint, and similarity analysis allows the grouping of behavioural sequences into discrete trajectories with assigned IDs. Here, we use cellPLATO to investigate the role of IL-15 in modulating human natural killer (NK) cell migration on ICAM-1 or VCAM-1. We find eight behavioural subsets of NK cells based on their shape and migration dynamics between single timepoints, and four trajectories based on sequences of these behaviours over time. Therefore, by using cellPLATO, we show that IL-15 increases plasticity between cell migration behaviours and that different integrin ligands induce different forms of NK cell migration.

A randomized, double-blind, placebo-controlled, crossover study of respiratory safety of lemborexant in moderate to severe obstructive sleep apnea.

STUDY OBJECTIVES: To evaluate the respiratory safety of lemborexant among adults and older adults with moderate to severe obstructive sleep apnea (OSA). METHODS: E2006-A001-113 (Study 113; NCT04647383) was a double-blind, two-period crossover, placebo-controlled study in adults (ages ≥ 45 to ≤ 90 years, n = 33) with moderate (apnea-hypopnea index [AHI] score ≥ 15 to < 30 events/h, n = 13) or severe (AHI ≥ 30 events/h, n = 20) OSA. Participants were randomized to lemborexant 10 mg (LEM10) or placebo (PBO) for two treatment periods of 8 nights with a ≥ 14-day washout period. AHI and peripheral oxygen saturation were evaluated after treatment on Day 1 (after a single dose) and Day 8 (after multiple doses). RESULTS: No significant differences in AHI were observed after single and multiple doses of LEM10 compared with PBO in participants with moderate to severe OSA (least-squares mean: single-dose LEM10, 41.7; PBO, 44.8; multiple-dose LEM10, 44.9; PBO, 45.7). In addition, there were no significant differences between treatments in peripheral oxygen saturation (least-squares mean: single-dose LEM10, 93.0; PBO, 93.1; multiple-dose LEM10, 93.1; PBO, 93.4). Further, there were no significant differences between treatments in percentage of total sleep time with peripheral oxygen saturation < 90%, < 85%, or < 80%. No significant differences were observed between treatments when AHI and peripheral oxygen saturation outcomes were analyzed by OSA severity. Altogether, 6/33 (18.2%) participants receiving LEM10, vs 3/33 (9.1%) PBO, reported treatment-emergent adverse events, mostly mild in severity. CONCLUSIONS: LEM10 demonstrated respiratory safety and was well tolerated with single-dose and multiple-dose administration in participants with moderate to severe OSA. This suggests that LEM may be a treatment option for patients with OSA and comorbid insomnia. CLINICAL TRIAL REGISTRATION: Registry: ClinicalTrials.gov; Name: A Study to Evaluate the Respiratory Safety of Lemborexant in Adult and Elderly Participants With Moderate to Severe Obstructive Sleep Apnea and in Adult and Elderly Participants With Moderate to Severe Chronic Obstructive Pulmonary Disease; URL: https://clinicaltrials.gov/ct2/show/NCT04647383; Identifier: NCT04647383. CITATION: Cheng JY, Lorch D, Lowe AD, et al. A randomized, double-blind, placebo-controlled, crossover study of respiratory safety of lemborexant in moderate to severe obstructive sleep apnea. J Clin Sleep Med. 2024;20(1):57-65.

cellPLATO: an unsupervised method for identifying cell behaviour in heterogeneous cell trajectory data.

Advances in imaging, cell segmentation, and cell tracking now routinely produce microscopy datasets of a size and complexity comparable to transcriptomics or proteomics. New tools are required to process this 'phenomics' type data. Cell PLasticity Analysis TOol (cellPLATO) is a Python-based analysis software designed for measurement and classification of diverse cell behaviours based on clustering of parameters of cell morphology and motility. cellPLATO is used after segmentation and tracking of cells from live cell microscopy data. The tool extracts morphological and motility metrics from each cell per timepoint, before being using them to segregate cells into behavioural subtypes with dimensionality reduction. Resultant cell tracks have a 'behavioural ID' for each cell per timepoint corresponding to their changing behaviour over time in a sequence. Similarity analysis allows the grouping of behavioural sequences into discrete trajectories with assigned IDs. Trajectories and underlying behaviours generate a phenotypic fingerprint for each experimental condition, and representative cells are mathematically identified and graphically displayed for human understanding of each subtype. Here, we use cellPLATO to investigate the role of IL-15 in modulating NK cell migration on ICAM-1 or VCAM-1. We find 8 behavioural subsets of NK cells based on their shape and migration dynamics, and 4 trajectories of behaviour. Therefore, using cellPLATO we show that IL-15 increases plasticity between cell migration behaviours and that different integrin ligands induce different forms of NK cell migration.

Machine learning enhanced cell tracking.

Quantifying cell biology in space and time requires computational methods to detect cells, measure their properties, and assemble these into meaningful trajectories. In this aspect, machine learning (ML) is having a transformational effect on bioimage analysis, now enabling robust cell detection in multidimensional image data. However, the task of cell tracking, or constructing accurate multi-generational lineages from imaging data, remains an open challenge. Most cell tracking algorithms are largely based on our prior knowledge of cell behaviors, and as such, are difficult to generalize to new and unseen cell types or datasets. Here, we propose that ML provides the framework to learn aspects of cell behavior using cell tracking as the task to be learned. We suggest that advances in representation learning, cell tracking datasets, metrics, and methods for constructing and evaluating tracking solutions can all form part of an end-to-end ML-enhanced pipeline. These developments will lead the way to new computational methods that can be used to understand complex, time-evolving biological systems.

Convolutional Neural Networks for Classifying Chromatin Morphology in Live-Cell Imaging.

Chromatin is highly structured, and changes in its organization are essential in many cellular processes, including cell division. Recently, advances in machine learning have enabled researchers to automatically classify chromatin morphology in fluorescence microscopy images. In this protocol, we develop user-friendly tools to perform this task. We provide an open-source annotation tool, and a cloud-based computational framework to train and utilize a convolutional neural network to automatically classify chromatin morphology. Using cloud compute enables users without significant resources or computational experience to use a machine learning approach to analyze their own microscopy data.

Cell-scale biophysical determinants of cell competition in epithelia.

How cells with different genetic makeups compete in tissues is an outstanding question in developmental biology and cancer research. Studies in recent years have revealed that cell competition can either be driven by short-range biochemical signalling or by long-range mechanical stresses in the tissue. To date, cell competition has generally been characterised at the population scale, leaving the single-cell-level mechanisms of competition elusive. Here, we use high time-resolution experimental data to construct a multi-scale agent-based model for epithelial cell competition and use it to gain a conceptual understanding of the cellular factors that governs competition in cell populations within tissues. We find that a key determinant of mechanical competition is the difference in homeostatic density between winners and losers, while differences in growth rates and tissue organisation do not affect competition end result. In contrast, the outcome and kinetics of biochemical competition is strongly influenced by local tissue organisation. Indeed, when loser cells are homogenously mixed with winners at the onset of competition, they are eradicated; however, when they are spatially separated, winner and loser cells coexist for long times. These findings suggest distinct biophysical origins for mechanical and biochemical modes of cell competition.

Changes in headache characteristics with oral appliance treatment for obstructive sleep apnea.

Changes in headache characteristics in obstructive sleep apnea (OSA) patients following oral appliance treatment was investigated for the first time. Thirteen OSA patients with headaches treated with a mandibular advancement device were investigated. Level I polysomnography and Migraine Disability Assessment Questionnaire were completed before and after treatment. Various headache characteristics and concomitant conditions were analyzed. The patient was considered a headache responder when ≥ 30% reduction in headache frequency following treatment. Differences in headache and polysomnographic parameters were compared between headache responder groups. Eight patients (62%) were headache responders. Eleven patients (85%) before and 7 (54%) after treatment reported morning headaches. Significantly more patients had bilateral headache in the responder group before treatment (P = 0.035). The severest headache intensity (P = 0.018) at baseline showed a significant decrease in the headache responder group after treatment. The time spent in N2 (r = - 0.663, P = 0.014), REM sleep (r = 0.704, P = 0.007) and mean oxygen saturation (r = 0.566, P = 0.044) showed a significant correlation with post-treatment average headache intensity. Pre-treatment lower PLM index (r = - 0.632, P = 0.027) and higher mean oxygen saturation levels (r = 0.592, P = 0.043) were significantly correlated with higher post-treatment severest headache intensity. Treatment with an oral appliance is beneficial for many OSA patients with headaches. It should be considered as an alternative treatment in headache patients with mild to moderate OSA.

Single-cell approaches to cell competition: High-throughput imaging, machine learning and simulations.

Cell competition is a quality control mechanism in tissues that results in the elimination of less fit cells. Over the past decade, the phenomenon of cell competition has been identified in many physiological and pathological contexts, driven either by biochemical signaling or by mechanical forces within the tissue. In both cases, competition has generally been characterized based on the elimination of loser cells at the population level, but significantly less attention has been focused on determining how single-cell dynamics and interactions regulate population-wide changes. In this review, we describe quantitative strategies and outline the outstanding challenges in understanding the single cell rules governing tissue-scale competition dynamics. We propose quantitative metrics to characterize single cell behaviors in competition and use them to distinguish the types and outcomes of competition. We describe how such metrics can be measured experimentally using a novel combination of high-throughput imaging and machine learning algorithms. We outline the experimental challenges to quantify cell fate dynamics with high-statistical precision, and describe the utility of computational modeling in testing hypotheses not easily accessible in experiments. In particular, cell-based modeling approaches that combine mechanical interaction of cells with decision-making rules for cell fate choices provide a powerful framework to understand and reverse-engineer the diverse rules of cell competition.

Miro clusters regulate ER-mitochondria contact sites and link cristae organization to the mitochondrial transport machinery.

Mitochondrial Rho (Miro) GTPases localize to the outer mitochondrial membrane and are essential machinery for the regulated trafficking of mitochondria to defined subcellular locations. However, their sub-mitochondrial localization and relationship with other critical mitochondrial complexes remains poorly understood. Here, using super-resolution fluorescence microscopy, we report that Miro proteins form nanometer-sized clusters along the mitochondrial outer membrane in association with the Mitochondrial Contact Site and Cristae Organizing System (MICOS). Using knockout mouse embryonic fibroblasts we show that Miro1 and Miro2 are required for normal mitochondrial cristae architecture and Endoplasmic Reticulum-Mitochondria Contacts Sites (ERMCS). Further, we show that Miro couples MICOS to TRAK motor protein adaptors to ensure the concerted transport of the two mitochondrial membranes and the correct distribution of cristae on the mitochondrial membrane. The Miro nanoscale organization, association with MICOS complex and regulation of ERMCS reveal new levels of control of the Miro GTPases on mitochondrial functionality.

Context-Dependent Energetics of Loop Extensions in a Family of Tandem-Repeat Proteins.

Consensus-designed tetratricopeptide repeat proteins are highly stable, modular proteins that are strikingly amenable to rational engineering. They therefore have tremendous potential as building blocks for biomaterials and biomedicine. Here, we explore the possibility of extending the loops between repeats to enable further diversification, and we investigate how this modification affects stability and folding cooperativity. We find that extending a single loop by up to 25 residues does not disrupt the overall protein structure, but, strikingly, the effect on stability is highly context-dependent: in a two-repeat array, destabilization is relatively small and can be accounted for purely in entropic terms, whereas extending a loop in the middle of a large array is much more costly because of weakening of the interaction between the repeats. Our findings provide important and, to our knowledge, new insights that increase our understanding of the structure, folding, and function of natural repeat proteins and the design of artificial repeat proteins in biotechnology.

A Liquid to Solid Phase Transition Underlying Pathological Huntingtin Exon1 Aggregation.

Huntington's disease is caused by an abnormally long polyglutamine tract in the huntingtin protein. This leads to the generation and deposition of N-terminal exon1 fragments of the protein in intracellular aggregates. We combined electron tomography and quantitative fluorescence microscopy to analyze the structural and material properties of huntingtin exon1 assemblies in mammalian cells, in yeast, and in vitro. We found that huntingtin exon1 proteins can form reversible liquid-like assemblies, a process driven by huntingtin's polyQ tract and proline-rich region. In cells and in vitro, the liquid-like assemblies converted to solid-like assemblies with a fibrillar structure. Intracellular phase transitions of polyglutamine proteins could play a role in initiating irreversible pathological aggregation.

PyFolding: Open-Source Graphing, Simulation, and Analysis of the Biophysical Properties of Proteins.

For many years, curve-fitting software has been heavily utilized to fit simple models to various types of biophysical data. Although such software packages are easy to use for simple functions, they are often expensive and present substantial impediments to applying more complex models or for the analysis of large data sets. One field that is reliant on such data analysis is the thermodynamics and kinetics of protein folding. Over the past decade, increasingly sophisticated analytical models have been generated, but without simple tools to enable routine analysis. Consequently, users have needed to generate their own tools or otherwise find willing collaborators. Here we present PyFolding, a free, open-source, and extensible Python framework for graphing, analysis, and simulation of the biophysical properties of proteins. To demonstrate the utility of PyFolding, we have used it to analyze and model experimental protein folding and thermodynamic data. Examples include: 1) multiphase kinetic folding fitted to linked equations, 2) global fitting of multiple data sets, and 3) analysis of repeat protein thermodynamics with Ising model variants. Moreover, we demonstrate how PyFolding is easily extensible to novel functionality beyond applications in protein folding via the addition of new models. Example scripts to perform these and other operations are supplied with the software, and we encourage users to contribute notebooks and models to create a community resource. Finally, we show that PyFolding can be used in conjunction with Jupyter notebooks as an easy way to share methods and analysis for publication and among research teams.

Local cellular neighborhood controls proliferation in cell competition.

Cell competition is a quality-control mechanism through which tissues eliminate unfit cells. Cell competition can result from short-range biochemical inductions or long-range mechanical cues. However, little is known about how cell-scale interactions give rise to population shifts in tissues, due to the lack of experimental and computational tools to efficiently characterize interactions at the single-cell level. Here, we address these challenges by combining long-term automated microscopy with deep-learning image analysis to decipher how single-cell behavior determines tissue makeup during competition. Using our high-throughput analysis pipeline, we show that competitive interactions between MDCK wild-type cells and cells depleted of the polarity protein scribble are governed by differential sensitivity to local density and the cell type of each cell's neighbors. We find that local density has a dramatic effect on the rate of division and apoptosis under competitive conditions. Strikingly, our analysis reveals that proliferation of the winner cells is up-regulated in neighborhoods mostly populated by loser cells. These data suggest that tissue-scale population shifts are strongly affected by cellular-scale tissue organization. We present a quantitative mathematical model that demonstrates the effect of neighbor cell-type dependence of apoptosis and division in determining the fitness of competing cell lines.

Conformational transition of FGFR kinase activation revealed by site-specific unnatural amino acid reporter and single molecule FRET.

Protein kinases share significant structural similarity; however, structural features alone are insufficient to explain their diverse functions. Thus, bridging the gap between static structure and function requires a more detailed understanding of their dynamic properties. For example, kinase activation may occur via a switch-like mechanism or by shifting a dynamic equilibrium between inactive and active states. Here, we utilize a combination of FRET and molecular dynamics (MD) simulations to probe the activation mechanism of the kinase domain of Fibroblast Growth Factor Receptor (FGFR). Using genetically-encoded, site-specific incorporation of unnatural amino acids in regions essential for activation, followed by specific labeling with fluorescent moieties, we generated a novel class of FRET-based reporter to monitor conformational differences corresponding to states sampled by non phosphorylated/inactive and phosphorylated/active forms of the kinase. Single molecule FRET analysis in vitro, combined with MD simulations, shows that for FGFR kinase, there are populations of inactive and active states separated by a high free energy barrier resulting in switch-like activation. Compared to recent studies, these findings support diversity in features of kinases that impact on their activation mechanisms. The properties of these FRET-based constructs will also allow further studies of kinase dynamics as well as applications in vivo.

Effect of orthodontic treatment on the upper airway volume in adults.

INTRODUCTION: The aim of this study was to examine the effects of orthodontic treatment with and without extractions on the anatomic characteristics of the upper airway in adults. METHODS: For this retrospective study, the pretreatment and posttreatment cone-beam computed tomography scans of 74 adult patients meeting defined eligibility criteria were analyzed. Imaging software was used to segment and measure upper airway regions including the nasopharynx, the retropalatal, and retroglossal areas of the oropharynx, as well as the total airway. The Wilcoxon signed rank test was used to compare volumetric and minimal cross-sectional area changes from pretreatment to posttreatment. RESULTS: The reliability values were high for all measurements, with intraclass correlation coefficients of 0.82 or greater. The volumetric treatment changes for the extraction and nonextraction groups were as follows: total airway, 1039.6 ± 3674.3 mm3 vs 1719.2 ± 4979.2 mm3; nasopharynx, 136.1 ± 1379.3 mm3 vs -36.5 ± 1139.8 mm3; retropalatal, 412.7 ± 3042.5 mm3 vs 399.3 ± 3294.6 mm3; and retroglossal, 412.5 ± 1503.2 mm3 vs 1109.3 ± 2328.6 mm3. The treatment changes in volume or minimal cross-sectional area for all airway regions examined were not significantly (P >0.05) different between the extraction and nonextraction groups. CONCLUSIONS: Orthodontic treatment in adults does not cause clinically significant changes to the volume or the minimally constricted area of the upper airway. These results suggest that dental extractions in conjunction with orthodontic treatment have a negligible effect on the upper airway in adults.

Single-Molecule Imaging to Characterize the Transport Mechanism of the Nuclear Pore Complex.

In the eukaryotic cell, a large macromolecular channel, known as the Nuclear Pore Complex (NPC), mediates all molecular transport between the nucleus and cytoplasm. In recent years, single-molecule fluorescence (SMF) imaging has emerged as a powerful tool to study the molecular mechanism of transport through the NPC. More recently, techniques such as single-molecule localization microscopy (SMLM) have enabled the spatial and temporal distribution of cargos, transport receptors and even structural components of the NPC to be determined with nanometre accuracy. In this protocol, we describe a method to study the position and/or motion of individual molecules transiting through the NPC with high spatial and temporal precision.

Sleep Stage Coordination of Respiration and Swallowing: A Preliminary Study.

Swallowing is an important physiological response that protects the airway. Although aspiration during sleep may cause aspiration pneumonia, the mechanisms responsible have not yet been elucidated. We evaluated the coordination between respiration and swallowing by infusing water into the pharynx of healthy young adults during each sleep stage. Seven normal subjects participated in the study. During polysomnography recordings, to elicit a swallow we injected distilled water into the pharynx during the awake state and each sleep stage through a nasal catheter. We assessed swallow latency, swallow apnea time, the respiratory phase during a swallow, the number of swallows, and coughing. A total number of 79 swallows were recorded. The median swallow latency was significantly higher in stage 2 (10.05 s) and stage 3 (44.17 s) when compared to awake state (4.99 s). The swallow latency in stage 3 showed a very wide interquartile range. In two subjects, the result was predominantly prolonged compared to the other subjects. There was no significant difference in the swallow apnea time between sleep stages. The presence of inspiration after swallowing, repetitive swallowing, and coughing after swallowing was more frequent during sleep than when awake. This study suggests that the coordination between respiration and swallowing as a defense mechanism against aspiration was impaired during sleep. Our results supported physiologically the fact that healthy adult individuals aspirate pharyngeal secretions during sleep.

Cyanobacteria use micro-optics to sense light direction.

Bacterial phototaxis was first recognized over a century ago, but the method by which such small cells can sense the direction of illumination has remained puzzling. The unicellular cyanobacterium Synechocystis sp. PCC 6803 moves with Type IV pili and measures light intensity and color with a range of photoreceptors. Here, we show that individual Synechocystis cells do not respond to a spatiotemporal gradient in light intensity, but rather they directly and accurately sense the position of a light source. We show that directional light sensing is possible because Synechocystis cells act as spherical microlenses, allowing the cell to see a light source and move towards it. A high-resolution image of the light source is focused on the edge of the cell opposite to the source, triggering movement away from the focused spot. Spherical cyanobacteria are probably the world's smallest and oldest example of a camera eye.

Cyanobacteria are blue-green bacteria that are abundant in the environment. Cyanobacteria in the oceans are among the world's most important oxygen producers and carbon dioxide consumers. Synechocystis is a spherical single-celled cyanobacterium that measures about three thousandths of a millimetre across. Because Synechocystis needs sunlight to produce energy, it is important for it to find places where the light is neither too weak nor too strong. Unlike some bacteria, Synechocystis can't swim, but it can crawl across surfaces. It uses this ability to move to places where the light conditions are better. It was already known that Synechocystis cells move towards a light source that is shone at them from one side, which implies that the cyanobacteria can "see" where the light is. But how can such a tiny cell accurately detect where light is coming from? Schuergers et al. tracked how Synechocystis moved in response to different light conditions, and found that the secret of "vision" in these cyanobacteria is that the cells act as tiny spherical lenses. When a light is shone at the cell, an image of the light source is focused at the opposite edge of the cell. Light-detecting molecules called photoreceptors respond to the focused image of the light source, and this provides the information needed to steer the cell towards the light. Although the details are different, and although a Synechocystis cell is in terms of volume about 500 billion times smaller than a human eyeball, vision in Synechocystis actually works by principles similar to vision in humans. Schuergers et al.'s findings open plenty of further questions, as other types of bacteria may also act as tiny lenses. More also remains to be learnt about how the cyanobacteria process visual information.

Prediction of oral appliance treatment outcomes in obstructive sleep apnea: A systematic review.

While oral appliances (OA) have demonstrated good efficacy in patients ranging from mild to severe levels of obstructive sleep apnea (OSA), this form of treatment is not completely effective in all patients. As a successful treatment response is not dependent solely on apnea hypopnea index severity, the prediction of OA treatment efficacy is of key importance for efficient disease management. This systematic review aims to investigate the accuracy of a variety of clinical and experimental tests for predicting OA treatment outcomes in OSA. A systematic literature review was conducted and the quality of the selected studies was assessed using the quality assessment of diagnostic accuracy studies (QUADAS-2) tool. Some 17 studies involving various prediction methods were included in this review. The predictive accuracy varied depending on the definitions of treatment success used as well as the type of index test. The studies with the best predictive accuracy and lowest risk of bias and concerns of applicability used a multisensor catheter. While a remotely controlled mandibular positioner study showed high accuracy, there was a high risk of bias. The available information on the validity of predictive index tests is very useful in clinical practice and allows for greater disease management efficiency.