Human NLRP1 is a sensor of pathogenic coronavirus 3CL proteases in lung epithelial cells.

Inflammation observed in SARS-CoV-2-infected patients suggests that inflammasomes, proinflammatory intracellular complexes, regulate various steps of infection. Lung epithelial cells express inflammasome-forming sensors and constitute the primary entry door of SARS-CoV-2. Here, we describe that the NLRP1 inflammasome detects SARS-CoV-2 infection in human lung epithelial cells. Specifically, human NLRP1 is cleaved at the Q333 site by multiple coronavirus 3CL proteases, which triggers inflammasome assembly and cell death and limits the production of infectious viral particles. Analysis of NLRP1-associated pathways unveils that 3CL proteases also inactivate the pyroptosis executioner Gasdermin D (GSDMD). Subsequently, caspase-3 and GSDME promote alternative cell pyroptosis. Finally, analysis of pyroptosis markers in plasma from COVID-19 patients with characterized severe pneumonia due to autoantibodies against, or inborn errors of, type I interferons (IFNs) highlights GSDME/caspase-3 as potential markers of disease severity. Overall, our findings identify NLRP1 as a sensor of SARS-CoV-2 infection in lung epithelia.

Light management by algal aggregates in living photosynthetic hydrogels.

Rapid progress in algal biotechnology has triggered a growing interest in hydrogel-encapsulated microalgal cultivation, especially for the engineering of functional photosynthetic materials and biomass production. An overlooked characteristic of gel-encapsulated cultures is the emergence of cell aggregates, which are the result of the mechanical confinement of the cells. Such aggregates have a dramatic effect on the light management of gel-encapsulated photobioreactors and hence strongly affect the photosynthetic outcome. To evaluate such an effect, we experimentally studied the optical response of hydrogels containing algal aggregates and developed optical simulations to study the resultant light intensity profiles. The simulations are validated experimentally via transmittance measurements using an integrating sphere and aggregate volume analysis with confocal microscopy. Specifically, the heterogeneous distribution of cell aggregates in a hydrogel matrix can increase light penetration while alleviating photoinhibition more effectively than in a flat biofilm. Finally, we demonstrate that light harvesting efficiency can be further enhanced with the introduction of scattering particles within the hydrogel matrix, leading to a fourfold increase in biomass growth. Our study, therefore, highlights a strategy for the design of spatially efficient photosynthetic living materials that have important implications for the engineering of future algal cultivation systems.

Red blood cell tension protects against severe malaria in the Dantu blood group.

Malaria has had a major effect on the human genome, with many protective polymorphisms-such as the sickle-cell trait-having been selected to high frequencies in malaria-endemic regions1,2. The blood group variant Dantu provides 74% protection against all forms of severe malaria in homozygous individuals3-5, a similar degree of protection to that afforded by the sickle-cell trait and considerably greater than that offered by the best malaria vaccine. Until now, however, the protective mechanism has been unknown. Here we demonstrate the effect of Dantu on the ability of the merozoite form of the malaria parasite Plasmodium falciparum to invade red blood cells (RBCs). We find that Dantu is associated with extensive changes to the repertoire of proteins found on the RBC surface, but, unexpectedly, inhibition of invasion does not correlate with specific RBC-parasite receptor-ligand interactions. By following invasion using video microscopy, we find a strong link between RBC tension and merozoite invasion, and identify a tension threshold above which invasion rarely occurs, even in non-Dantu RBCs. Dantu RBCs have higher average tension than non-Dantu RBCs, meaning that a greater proportion resist invasion. These findings provide both an explanation for the protective effect of Dantu, and fresh insight into why the efficiency of P. falciparum invasion might vary across the heterogenous populations of RBCs found both within and between individuals.

The FAM13A Long Isoform Regulates Cilia Movement and Coordination in Airway Mucociliary Transport.

Single nucelotide polymorphisms (SNPs) at the FAM13A locus are among 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 because of a lack of isoform conservation in mice. We performed in-depth characterization 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 the 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 coordination 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 coordinates cilia-driven movement, suggesting that FAM13A risk alleles may affect susceptibility to respiratory diseases through deficiencies in mucociliary clearance.

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.

Threshold accumulation of a constitutive protein explains E. coli cell-division behavior in nutrient upshifts.

Despite a boost of recent progress in dynamic single-cell measurements and analyses in Escherichia coli, we still lack a mechanistic understanding of the determinants of the decision to divide. Specifically, the debate is open regarding the processes linking growth and chromosome replication to division and on the molecular origin of the observed "adder correlations," whereby cells divide, adding roughly a constant volume independent of their initial volume. In order to gain insight into these questions, we interrogate dynamic size-growth behavior of single cells across nutrient upshifts with a high-precision microfluidic device. We find that the division rate changes quickly after nutrients change, much before growth rate goes to a steady state, and in a way that adder correlations are robustly conserved. Comparison of these data to simple mathematical models falsifies proposed mechanisms, where replication-segregation or septum completions are the limiting step for cell division. Instead, we show that the accumulation of a putative constitutively expressed "P-sector divisor" protein explains the behavior during the shift.

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.

Entrainment of mammalian motile cilia in the brain with hydrodynamic forces.

Motile cilia are widespread across the animal and plant kingdoms, displaying complex collective dynamics central to their physiology. Their coordination mechanism is not generally understood, with previous work mainly focusing on algae and protists. We study here the entrainment of cilia beat in multiciliated cells from brain ventricles. The response to controlled oscillatory external flows shows that flows at a similar frequency to the actively beating cilia can entrain cilia oscillations. We find that the hydrodynamic forces required for this entrainment strongly depend on the number of cilia per cell. Cells with few cilia (up to five) can be entrained at flows comparable to cilia-driven flows, in contrast with what was recently observed in Chlamydomonas Experimental trends are quantitatively described by a model that accounts for hydrodynamic screening of packed cilia and the chemomechanical energy efficiency of the flagellar beat. Simulations of a minimal model of cilia interacting hydrodynamically show the same trends observed in cilia.

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.

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.

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.

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.

A Modular, Dynamic, DNA-Based Platform for Regulating Cargo Distribution and Transport between Lipid Domains.

Cell membranes regulate the distribution of biological machinery between phase-separated lipid domains to facilitate key processes including signaling and transport, which are among the life-like functionalities that bottom-up synthetic biology aims to replicate in artificial-cellular systems. Here, we introduce a modular approach to program partitioning of amphiphilic DNA nanostructures in coexisting lipid domains. Exploiting the tendency of different hydrophobic "anchors" to enrich different phases, we modulate the lateral distribution of our devices by rationally combining hydrophobes and by changing nanostructure size and topology. We demonstrate the functionality of our strategy with a bioinspired DNA architecture, which dynamically undergoes ligand-induced reconfiguration to mediate cargo transport between domains via lateral redistribution. Our findings pave the way to next-generation biomimetic platforms for sensing, transduction, and communication in synthetic cellular systems.

Thermally Driven Membrane Phase Transitions Enable Content Reshuffling in Primitive Cells.

Self-assembling single-chain amphiphiles available in the prebiotic environment likely played a fundamental role in the advent of primitive cell cycles. However, the instability of prebiotic fatty acid-based membranes to temperature and pH seems to suggest that primitive cells could only host prebiotically relevant processes in a narrow range of nonfluctuating environmental conditions. Here we propose that membrane phase transitions, driven by environmental fluctuations, enabled the generation of daughter protocells with reshuffled content. A reversible membrane-to-oil phase transition accounts for the dissolution of fatty acid-based vesicles at high temperatures and the concomitant release of protocellular content. At low temperatures, fatty acid bilayers reassemble and encapsulate reshuffled material in a new cohort of protocells. Notably, we find that our disassembly/reassembly cycle drives the emergence of functional RNA-containing primitive cells from parent nonfunctional compartments. Thus, by exploiting the intrinsic instability of prebiotic fatty acid vesicles, our results point at an environmentally driven tunable prebiotic process, which supports the release and reshuffling of oligonucleotides and membrane components, potentially leading to a new generation of protocells with superior traits. In the absence of protocellular transport machinery, the environmentally driven disassembly/assembly cycle proposed herein would have plausibly supported protocellular content reshuffling transmitted to primitive cell progeny, hinting at a potential mechanism important to initiate Darwinian evolution of early life forms.

The use of biophysical approaches to understand ciliary beating.

Motile cilia are a striking example of the functional cellular organelle, conserved across all the eukaryotic species. Motile cilia allow the swimming of cells and small organisms and transport of liquids across epithelial tissues. Whilst the molecular structure is now very well understood, the dynamics of cilia is not well established either at the single cilium level nor at the level of collective beating. Indeed, a full understanding of this requires connecting together behaviour across various lengthscales, from the molecular to the organelle, then at the cellular level and up to the tissue scale. Aside from the fundamental interest in this system, understanding beating is important to elucidate aspects of embryonic development and a variety of health conditions from fertility to genetic and infectious diseases of the airways.

Cilia density and flow velocity affect alignment of motile cilia from brain cells.

In many organs, thousands of microscopic 'motile cilia' beat in a coordinated fashion generating fluid flow. Physiologically, these flows are important in both development and homeostasis of ciliated tissues. Combining experiments and simulations, we studied how cilia from brain tissue align their beating direction. We subjected cilia to a broad range of shear stresses, similar to the fluid flow that cilia themselves generate, in a microfluidic setup. In contrast to previous studies, we found that cilia from mouse ependyma respond and align to these physiological shear stress at all maturation stages. Cilia align more easily earlier in maturation, and we correlated this property with the increase in multiciliated cell density during maturation. Our numerical simulations show that cilia in densely packed clusters are hydrodynamically screened from the external flow, in agreement with our experimental observation. Cilia carpets create a hydrodynamic screening that reduces the susceptibility of individual cilia to external flows.

Thermal-driven domain and cargo transport in lipid membranes.

Domain migration is observed on the surface of ternary giant unilamellar vesicles held in a temperature gradient in conditions where they exhibit coexistence of two liquid phases. The migration localizes domains to the hot side of the vesicle, regardless of whether the domain is composed of the more ordered or disordered phase and regardless of the proximity to chamber boundaries. The distribution of domains is explored for domains that coarsen and for those held apart due to long-range repulsions. After considering several potential mechanisms for the migration, including the temperature preferences for each lipid, the favored curvature for each phase, and the thermophoretic flow around the vesicle, we show that observations are consistent with the general process of minimizing the system's line tension energy, because of the lowering of line interface energy closer to mixing. DNA strands, attached to the lipid bilayer with cholesterol anchors, act as an exemplar "cargo," demonstrating that the directed motion of domains toward higher temperatures provides a route to relocate species that preferentially reside in the domains.

Synergistic malaria vaccine combinations identified by systematic antigen screening.

A highly effective vaccine would be a valuable weapon in the drive toward malaria elimination. No such vaccine currently exists, and only a handful of the hundreds of potential candidates in the parasite genome have been evaluated. In this study, we systematically evaluated 29 antigens likely to be involved in erythrocyte invasion, an essential developmental stage during which the malaria parasite is vulnerable to antibody-mediated inhibition. Testing antigens alone and in combination identified several strain-transcending targets that had synergistic combinatorial effects in vitro, while studies in an endemic population revealed that combinations of the same antigens were associated with protection from febrile malaria. Video microscopy established that the most effective combinations targeted multiple discrete stages of invasion, suggesting a mechanistic explanation for synergy. Overall, this study both identifies specific antigen combinations for high-priority clinical testing and establishes a generalizable approach that is more likely to produce effective vaccines.