The FAM13A Long Isoform Regulates Cilia Movement and Co-ordination in Airway Mucociliary Transport.

SNPs in the FAM13A locus are amongst the most commonly reported risk alleles associated with chronic obstructive pulmonary disease (COPD) and other respiratory diseases, however the physiological role of FAM13A is unclear. In humans, two major protein isoforms are expressed at the FAM13A locus: 'long' and 'short', but their functions remain unknown, partly due to a lack of isoform conservation in mice. We performed in-depth characterisation of organotypic primary human airway epithelial cell subsets and show that multiciliated cells predominantly express the FAM13A long isoform containing a putative N-terminal Rho GTPase activating protein (RhoGAP) domain. Using purified proteins, we directly demonstrate RhoGAP activity of this domain. In Xenopus laevis, which conserve the long isoform, Fam13a-deficiency impaired cilia-dependent embryo motility. In human primary epithelial cells, long isoform deficiency did not affect multiciliogenesis but reduced cilia co-ordination in mucociliary transport assays. This is the first demonstration that FAM13A isoforms are differentially expressed within the airway epithelium, with implications for the assessment and interpretation of SNP effects on FAM13A expression levels. We also show that the long FAM13A isoform co-ordinates cilia-driven movement, suggesting that FAM13A risk alleles may affect susceptibility to respiratory diseases through deficiencies in mucociliary clearance. This article is open access and distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

A common polymorphism in the Intelectin-1 gene influences mucus plugging in severe asthma.

By incompletely understood mechanisms, type 2 (T2) inflammation present in the airways of severe asthmatics drives the formation of pathologic mucus which leads to airway mucus plugging. Here we investigate the molecular role and clinical significance of intelectin-1 (ITLN-1) in the development of pathologic airway mucus in asthma. Through analyses of human airway epithelial cells we find that ITLN1 gene expression is highly induced by interleukin-13 (IL-13) in a subset of metaplastic MUC5AC+ mucus secretory cells, and that ITLN-1 protein is a secreted component of IL-13-induced mucus. Additionally, we find ITLN-1 protein binds the C-terminus of the MUC5AC mucin and that its deletion in airway epithelial cells partially reverses IL-13-induced mucostasis. Through analysis of nasal airway epithelial brushings, we find that ITLN1 is highly expressed in T2-high asthmatics, when compared to T2-low children. Furthermore, we demonstrate that both ITLN-1 gene expression and protein levels are significantly reduced by a common genetic variant that is associated with protection from the formation of mucus plugs in T2-high asthma. This work identifies an important biomarker and targetable pathways for the treatment of mucus obstruction in asthma.

In vitro platform to model the function of ionocytes in the human airway epithelium.

BACKGROUND: Pulmonary ionocytes have been identified in the airway epithelium as a small population of ion transporting cells expressing high levels of CFTR (cystic fibrosis transmembrane conductance regulator), the gene mutated in cystic fibrosis. By providing an infinite source of airway epithelial cells (AECs), the use of human induced pluripotent stem cells (hiPSCs) could overcome some challenges of studying ionocytes. However, the production of AEC epithelia containing ionocytes from hiPSCs has proven difficult. Here, we present a platform to produce hiPSC-derived AECs (hiPSC-AECs) including ionocytes and investigate their role in the airway epithelium. METHODS: hiPSCs were differentiated into lung progenitors, which were expanded as 3D organoids and matured by air-liquid interface culture as polarised hiPSC-AEC epithelia. Using CRISPR/Cas9 technology, we generated a hiPSCs knockout (KO) for FOXI1, a transcription factor that is essential for ionocyte specification. Differences between FOXI1 KO hiPSC-AECs and their wild-type (WT) isogenic controls were investigated by assessing gene and protein expression, epithelial composition, cilia coverage and motility, pH and transepithelial barrier properties. RESULTS: Mature hiPSC-AEC epithelia contained basal cells, secretory cells, ciliated cells with motile cilia, pulmonary neuroendocrine cells (PNECs) and ionocytes. There was no difference between FOXI1 WT and KO hiPSCs in terms of their capacity to differentiate into airway progenitors. However, FOXI1 KO led to mature hiPSC-AEC epithelia without ionocytes with reduced capacity to produce ciliated cells. CONCLUSION: Our results suggest that ionocytes could have role beyond transepithelial ion transport by regulating epithelial properties and homeostasis in the airway epithelium.

Multipad agarose plate: a rapid and high-throughput approach for antibiotic susceptibility testing.

We describe a phenotypic antibiotic susceptibility testing (AST) method that can provide an eightfold speed-up in turnaround time compared with the current clinical standard by leveraging advances in microscopy and single-cell imaging. A newly developed growth plate containing 96 agarose pads, termed the multipad agarose plate (MAP), can be assembled at low cost. Pads can be prepared with dilution series of antibiotics. Bacteria are seeded on the pads and automatically imaged using brightfield microscopy, with a fully automated segmentation pipeline quantifying microcolony formation and growth rate. Using a test set of nine antibiotics with very different targets, we demonstrate that accurate minimum inhibitory concentration (MIC) measurements can be performed based on the growth rate of microcolonies within 3 h of incubation with the antibiotic when started from exponential phase. Faster, reliable and high-throughput methods for AST, such as MAP, could improve patient care by expediting treatment initiation and alleviating the burden of antimicrobial resistance.

Surface Cross-Linking by Macromolecular Tethers Enhances Virus-like Particles' Resilience to Mucosal Stress Factors.

Virus-like particles (VLPs) are emerging as nanoscaffolds in a variety of biomedical applications including delivery of vaccine antigens and cargo such as mRNA to mucosal surfaces. These soft, colloidal, and proteinaceous structures (capsids) are nevertheless susceptible to mucosal environmental stress factors. We cross-linked multiple capsid surface amino acid residues using homobifunctional polyethylene glycol tethers to improve the persistence and survival of the capsid to model mucosal stressors. Surface cross-linking enhanced the stability of VLPs assembled from Acinetobacter phage AP205 coat proteins in low pH (down to pH 4.0) and high protease concentration conditions (namely, in pig and mouse gastric fluids). Additionally, it increased the stiffness of VLPs under local mechanical indentation applied using an atomic force microscopy cantilever tip. Small angle X-ray scattering revealed an increase in capsid diameter after cross-linking and an increase in capsid shell thickness with the length of the PEG cross-linkers. Moreover, surface cross-linking had no effect on the VLPs' mucus translocation and accumulation on the epithelium of in vitro 3D human nasal epithelial tissues with mucociliary clearance. Finally, it did not compromise VLPs' function as vaccines in mouse subcutaneous vaccination models. Compared to PEGylation without cross-linking, the stiffness of surface cross-linked VLPs were higher for the same length of the PEG molecule, and also the lifetimes of surface cross-linked VLPs were longer in the gastric fluids. Surface cross-linking using macromolecular tethers, but not simple conjugation of these molecules, thus offers a viable means to enhance the resilience and survival of VLPs for mucosal applications.

Effects of the G-quadruplex-binding drugs quarfloxin and CX-5461 on the malaria parasite Plasmodium falciparum.

Plasmodium falciparum is the deadliest causative agent of human malaria. This parasite has historically developed resistance to most drugs, including the current frontline treatments, so new therapeutic targets are needed. Our previous work on guanine quadruplexes (G4s) in the parasite's DNA and RNA has highlighted their influence on parasite biology, and revealed G4 stabilising compounds as promising candidates for repositioning. In particular, quarfloxin, a former anticancer agent, kills blood-stage parasites at all developmental stages, with fast rates of kill and nanomolar potency. Here we explored the molecular mechanism of quarfloxin and its related derivative CX-5461. In vitro, both compounds bound to P. falciparum-encoded G4 sequences. In cellulo, quarfloxin was more potent than CX-5461, and could prevent establishment of blood-stage malaria in vivo in a murine model. CX-5461 showed clear DNA damaging activity, as reported in human cells, while quarfloxin caused weaker signatures of DNA damage. Both compounds caused transcriptional dysregulation in the parasite, but the affected genes were largely different, again suggesting different modes of action. Therefore, CX-5461 may act primarily as a DNA damaging agent in both Plasmodium parasites and mammalian cells, whereas the complete antimalarial mode of action of quarfloxin may be parasite-specific and remains somewhat elusive.

The structure of a Plasmodium vivax Tryptophan Rich Antigen domain suggests a lipid binding function for a pan-Plasmodium multi-gene family.

Tryptophan Rich Antigens (TRAgs) are encoded by a multi-gene family found in all Plasmodium species, but are significantly expanded in P. vivax and closely related parasites. We show that multiple P. vivax TRAgs are expressed on the merozoite surface and that one, PVP01_0000100 binds red blood cells with a strong preference for reticulocytes. Using X-ray crystallography, we solved the structure of the PVP01_0000100 C-terminal tryptophan rich domain, which defines the TRAg family, revealing a three-helical bundle that is conserved across Plasmodium and has structural homology with lipid-binding BAR domains involved in membrane remodelling. Biochemical assays confirm that the PVP01_0000100 C-terminal domain has lipid binding activity with preference for sulfatide, a glycosphingolipid present in the outer leaflet of plasma membranes. Deletion of the putative orthologue in P. knowlesi, PKNH_1300500, impacts invasion in reticulocytes, suggesting a role during this essential process. Together, this work defines an emerging molecular function for the Plasmodium TRAg family.

Assessing motile cilia coverage and beat frequency in mammalian in vitro cell culture tissues.

Cilia density, distribution and beating frequency are important properties of airway epithelial tissues. These parameters are critical in diagnosing primary ciliary dyskinesia and examining in vitro models, including those derived from induced pluripotent stem cells. Video microscopy can be used to characterize these parameters, but most tools available at the moment are limited in the type of information they can provide, usually only describing the ciliary beat frequency of very small areas, while requiring human intervention and training for their use. We propose a novel and open-source method to fully characterize cilia beating frequency and motile cilia coverage in an automated fashion without user intervention. We demonstrate the ability to differentiate between different coverage densities, identifying even small patches of cilia in a larger field of view, and to fully characterize the cilia beating frequency of all moving areas. We also show that the method can be used to combine multiple fields of view to better describe a sample without relying on small pre-selected regions of interest. This is released with a simple graphical user interface for file handling, enabling a full analysis of individual fields of view in a few minutes on a typical personal computer.

Centripetal nuclear shape fluctuations associate with chromatin condensation in early prophase.

The nucleus plays a central role in several key cellular processes, including chromosome organisation, DNA replication and gene transcription. Recent work suggests an association between nuclear mechanics and cell-cycle progression, but many aspects of this connection remain unexplored. Here, by monitoring nuclear shape fluctuations at different cell cycle stages, we uncover increasing inward fluctuations in late G2 and in early prophase, which are initially transient, but develop into instabilities when approaching the nuclear-envelope breakdown. We demonstrate that such deformations correlate with chromatin condensation by perturbing both the chromatin and the cytoskeletal structures. We propose that the contrasting forces between an extensile stress and centripetal pulling from chromatin condensation could mechanically link chromosome condensation with nuclear-envelope breakdown, two main nuclear processes occurring during mitosis.

A Synthetic Signaling Network Imitating the Action of Immune Cells in Response to Bacterial Metabolism.

State-of-the-art bottom-up synthetic biology allows to replicate many basic biological functions in artificial-cell-like devices. To mimic more complex behaviors, however, artificial cells would need to perform many of these functions in a synergistic and coordinated fashion, which remains elusive. Here, a sophisticated biological response is considered, namely the capture and deactivation of pathogens by neutrophil immune cells, through the process of netosis. A consortium consisting of two synthetic agents is designed-responsive DNA-based particles and antibiotic-loaded lipid vesicles-whose coordinated action mimics the sought immune-like response when triggered by bacterial metabolism. The artificial netosis-like response emerges from a series of interlinked sensing and communication pathways between the live and synthetic agents, and translates into both physical and chemical antimicrobial actions, namely bacteria immobilization and exposure to antibiotics. The results demonstrate how advanced life-like responses can be prescribed with a relatively small number of synthetic molecular components, and outlines a new strategy for artificial-cell-based antimicrobial solutions.

DNA-Origami Line-Actants Control Domain Organization and Fission in Synthetic Membranes.

Cells can precisely program the shape and lateral organization of their membranes using protein machinery. Aiming to replicate a comparable degree of control, here we introduce DNA-origami line-actants (DOLAs) as synthetic analogues of membrane-sculpting proteins. DOLAs are designed to selectively accumulate at the line-interface between coexisting domains in phase-separated lipid membranes, modulating the tendency of the domains to coalesce. With experiments and coarse-grained simulations, we demonstrate that DOLAs can reversibly stabilize two-dimensional analogues of Pickering emulsions on synthetic giant liposomes, enabling dynamic programming of membrane lateral organization. The control afforded over membrane structure by DOLAs extends to three-dimensional morphology, as exemplified by a proof-of-concept synthetic pathway leading to vesicle fission. With DOLAs we lay the foundations for mimicking, in synthetic systems, some of the critical membrane-hosted functionalities of biological cells, including signaling, trafficking, sensing, and division.

Evaluating Listening Performance for COVID-19 Detection by Clinicians and Machine Learning: Comparative Study.

BACKGROUND: To date, performance comparisons between men and machines have been carried out in many health domains. Yet machine learning (ML) models and human performance comparisons in audio-based respiratory diagnosis remain largely unexplored. OBJECTIVE: The primary objective of this study was to compare human clinicians and an ML model in predicting COVID-19 from respiratory sound recordings. METHODS: In this study, we compared human clinicians and an ML model in predicting COVID-19 from respiratory sound recordings. Prediction performance on 24 audio samples (12 tested positive) made by 36 clinicians with experience in treating COVID-19 or other respiratory illnesses was compared with predictions made by an ML model trained on 1162 samples. Each sample consisted of voice, cough, and breathing sound recordings from 1 subject, and the length of each sample was around 20 seconds. We also investigated whether combining the predictions of the model and human experts could further enhance the performance in terms of both accuracy and confidence. RESULTS: The ML model outperformed the clinicians, yielding a sensitivity of 0.75 and a specificity of 0.83, whereas the best performance achieved by the clinicians was 0.67 in terms of sensitivity and 0.75 in terms of specificity. Integrating the clinicians' and the model's predictions, however, could enhance performance further, achieving a sensitivity of 0.83 and a specificity of 0.92. CONCLUSIONS: Our findings suggest that the clinicians and the ML model could make better clinical decisions via a cooperative approach and achieve higher confidence in audio-based respiratory diagnosis.

A summary of the ComParE COVID-19 challenges.

The COVID-19 pandemic has caused massive humanitarian and economic damage. Teams of scientists from a broad range of disciplines have searched for methods to help governments and communities combat the disease. One avenue from the machine learning field which has been explored is the prospect of a digital mass test which can detect COVID-19 from infected individuals' respiratory sounds. We present a summary of the results from the INTERSPEECH 2021 Computational Paralinguistics Challenges: COVID-19 Cough, (CCS) and COVID-19 Speech, (CSS).

Controlling and scripting laboratory hardware with open-source, intuitive interfaces: OpenFlexure Voice Control and OpenFlexure Blockly.

Making user interaction with laboratory equipment more convenient and intuitive should promote experimental work and help researchers to complete their tasks efficiently. The most common form of interaction in current instrumentation is either direct tactile, with buttons and knobs, or interfaced through a computer, using a mouse and keyboard. Scripting is another function typical of smart and automated laboratory equipment, yet users are currently required to learn bespoke programming languages and libraries for individual pieces of equipment. In this paper, we present two open-source, novel and intuitive ways of interacting with and scripting laboratory equipment. We choose the OpenFlexure family of microscopes as our exemplar, due to their open-source nature and smart control system. Firstly, we demonstrate 'OpenFlexure Voice Control' to enable users to control the microscope hands-free. Secondly, we present 'OpenFlexure Blockly' which uses the Blockly Visual Programming Language to enable users to easily create scripts for the microscope, using a drag and drop Web interface. We explain the design choices when developing these tools, and discuss more typical use cases and more general applications.

Multi-modal microscopy imaging with the OpenFlexure Delta Stage.

Microscopes are vital pieces of equipment in much of biological research and medical diagnostics. However, access to a microscope can represent a bottleneck in research, especially in lower-income countries. 'Smart' computer controlled motorized microscopes, which can perform automated routines or acquire images in a range of modalities are even more expensive and inaccessible. Developing low-cost, open-source, smart microscopes enables more researchers to conceive and execute optimized or more complex experiments. Here we present the OpenFlexure Delta Stage, a 3D-printed microscope designed for researchers. Powered by the OpenFlexure software stack, it is capable of performing automated experiments. The design files and assembly instructions are freely available under an open licence. Its intuitive and modular design-along with detailed documentation-allows researchers to implement a variety of imaging modes with ease. The versatility of this microscope is demonstrated by imaging biological and non-biological samples (red blood cells with Plasmodium parasites and colloidal particles in brightfield, epi-fluorescence, darkfield, Rheinberg and differential phase contrast. We present the design strategy and choice of tools to develop devices accessible to researchers from lower-income countries, as well as the advantages of an open-source project in this context. This microscope, having been open-source since its conception, has already been built and tested by researchers around the world, promoting a community of expertise and an environment of reproducibility in science.

DNA-assisted selective electrofusion (DASE) of Escherichia coli and giant lipid vesicles.

Synthetic biology and cellular engineering require chemical and physical alterations, which are typically achieved by fusing target cells with each other or with payload-carrying vectors. On one hand, electrofusion can efficiently induce the merging of biological cells and/or synthetic analogues via the application of intense DC pulses, but it lacks selectivity and often leads to uncontrolled fusion. On the other hand, synthetic DNA-based constructs, inspired by natural fusogenic proteins, have been shown to induce a selective fusion between membranes, albeit with low efficiency. Here we introduce DNA-assisted selective electrofusion (DASE) which relies on membrane-anchored DNA constructs to bring together the objects one seeks to merge, and applying an electric impulse to trigger their fusion. The DASE process combines the efficiency of standard electrofusion and the selectivity of fusogenic nanostructures, as we demonstrate by inducing and characterizing the fusion of spheroplasts derived from Escherichia coli bacteria with cargo-carrying giant lipid vesicles.

Reaction-Diffusion Patterning of DNA-Based Artificial Cells.

Biological cells display complex internal architectures with distinct micro environments that establish the chemical heterogeneity needed to sustain cellular functions. The continued efforts to create advanced cell mimics, namely, artificial cells, demands strategies for constructing similarly heterogeneous structures with localized functionalities. Here, we introduce a platform for constructing membraneless artificial cells from the self-assembly of synthetic DNA nanostructures in which internal domains can be established thanks to prescribed reaction-diffusion waves. The method, rationalized through numerical modeling, enables the formation of up to five distinct concentric environments in which functional moieties can be localized. As a proof-of-concept, we apply this platform to build DNA-based artificial cells in which a prototypical nucleus synthesizes fluorescent RNA aptamers that then accumulate in a surrounding storage shell, thus demonstrating the spatial segregation of functionalities reminiscent of that observed in biological cells.

Modulating membrane fusion through the design of fusogenic DNA circuits and bilayer composition.

Membrane fusion is a ubiquitous phenomenon linked to many biological processes, and represents a crucial step in liposome-based drug delivery strategies. The ability to control, ever more precisely, membrane fusion pathways would thus be highly valuable for next generation nano-medical solutions and, more generally, the design of advanced biomimetic systems such as synthetic cells. In this article, we present fusogenic nanostructures constructed from synthetic DNA which, different from previous solutions, unlock routes for modulating the rate of fusion and making it conditional to the presence of soluble DNA molecules, thus demonstrating how membrane fusion can be controlled through simple DNA-based molecular circuits. We then systematically explore the relationship between lipid-membrane composition, its biophysical properties, and measured fusion efficiency, linking our observations to the stability of transition states in the fusion pathway. Finally, we observe that specific lipid compositions lead to the emergence of complex bilayer architectures in the fusion products, such as nested morphologies, which are accompanied by alterations in biophysical behaviour. Our findings provide multiple, orthogonal strategies to program lipid-membrane fusion, which leverage the design of either the fusogenic DNA constructs or the physico/chemical properties of the membranes, and could thus be valuable in applications where some design parameters are constrained by other factors such as material cost and biocompatibility, as it is often the case in biotechnological applications.

Exploring Longitudinal Cough, Breath, and Voice Data for COVID-19 Progression Prediction via Sequential Deep Learning: Model Development and Validation.

BACKGROUND: Recent work has shown the potential of using audio data (eg, cough, breathing, and voice) in the screening for COVID-19. However, these approaches only focus on one-off detection and detect the infection, given the current audio sample, but do not monitor disease progression in COVID-19. Limited exploration has been put forward to continuously monitor COVID-19 progression, especially recovery, through longitudinal audio data. Tracking disease progression characteristics and patterns of recovery could bring insights and lead to more timely treatment or treatment adjustment, as well as better resource management in health care systems. OBJECTIVE: The primary objective of this study is to explore the potential of longitudinal audio samples over time for COVID-19 progression prediction and, especially, recovery trend prediction using sequential deep learning techniques. METHODS: Crowdsourced respiratory audio data, including breathing, cough, and voice samples, from 212 individuals over 5-385 days were analyzed, alongside their self-reported COVID-19 test results. We developed and validated a deep learning-enabled tracking tool using gated recurrent units (GRUs) to detect COVID-19 progression by exploring the audio dynamics of the individuals' historical audio biomarkers. The investigation comprised 2 parts: (1) COVID-19 detection in terms of positive and negative (healthy) tests using sequential audio signals, which was primarily assessed in terms of the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity, with 95% CIs, and (2) longitudinal disease progression prediction over time in terms of probability of positive tests, which was evaluated using the correlation between the predicted probability trajectory and self-reported labels. RESULTS: We first explored the benefits of capturing longitudinal dynamics of audio biomarkers for COVID-19 detection. The strong performance, yielding an AUROC of 0.79, a sensitivity of 0.75, and a specificity of 0.71 supported the effectiveness of the approach compared to methods that do not leverage longitudinal dynamics. We further examined the predicted disease progression trajectory, which displayed high consistency with longitudinal test results with a correlation of 0.75 in the test cohort and 0.86 in a subset of the test cohort with 12 (57.1%) of 21 COVID-19-positive participants who reported disease recovery. Our findings suggest that monitoring COVID-19 evolution via longitudinal audio data has potential in the tracking of individuals' disease progression and recovery. CONCLUSIONS: An audio-based COVID-19 progression monitoring system was developed using deep learning techniques, with strong performance showing high consistency between the predicted trajectory and the test results over time, especially for recovery trend predictions. This has good potential in the postpeak and postpandemic era that can help guide medical treatment and optimize hospital resource allocations. The changes in longitudinal audio samples, referred to as audio dynamics, are associated with COVID-19 progression; thus, modeling the audio dynamics can potentially capture the underlying disease progression process and further aid COVID-19 progression prediction. This framework provides a flexible, affordable, and timely tool for COVID-19 tracking, and more importantly, it also provides a proof of concept of how telemonitoring could be applicable to respiratory diseases monitoring, in general.