Time-dependent cell-state selection identifies transiently expressed genes regulating ILC2 activation.

The decision of whether cells are activated or not is controlled through dynamic intracellular molecular networks. However, the low population of cells during the transition state of activation renders the analysis of the transcriptome of this state technically challenging. To address this issue, we have developed the Time-Dependent Cell-State Selection (TDCSS) technique, which employs live-cell imaging of secretion activity to detect an index of the transition state, followed by the simultaneous recovery of indexed cells for subsequent transcriptome analysis. In this study, we used the TDCSS technique to investigate the transition state of group 2 innate lymphoid cells (ILC2s) activation, which is indexed by the onset of interleukin (IL)-13 secretion. The TDCSS approach allowed us to identify time-dependent genes, including transiently induced genes (TIGs). Our findings of IL4 and MIR155HG as TIGs have shown a regulatory function in ILC2s activation.

Accumulation of TERT in mitochondria exerts two opposing effects on apoptosis.

Telomerase reverse transcriptase (TERT) is a protein that catalyzes the reverse transcription of telomere elongation. TERT is also expected to play a non-canonical role beyond telomere lengthening since it localizes not only in the nucleus but also in mitochondria, where telomeres do not exist. Several studies have reported that mitochondrial TERT regulates apoptosis induced by oxidative stress. However, there is still some controversy as to whether mitochondrial TERT promotes or inhibits apoptosis, mainly due to the lack of information on changes in TERT distribution in individual cells over time. Here, we simultaneously detected apoptosis and TERT localization after oxidative stress in individual HeLa cells by live-cell tracking. Single-cell tracking revealed that the stress-induced accumulation of TERT in mitochondria caused apoptosis, but that accumulation increased over time until cell death. The results suggest a new model in which mitochondrial TERT has two opposing effects at different stages of apoptosis: it predetermines apoptosis at the first stage of cell-fate determination, but also delays apoptosis at the second stage. As such, our data support a model that integrates the two opposing hypotheses on mitochondrial TERT's effect on apoptosis. Furthermore, detailed statistical analysis of TERT mutations, which have been predicted to inhibit TERT transport to mitochondria, revealed that these mutations suppress apoptosis independent of mitochondrial localization of TERT. Together, these results imply that the non-canonical functions of TERT affect a wide range of mitochondria-dependent and mitochondria-independent apoptosis pathways.

Annexin A1 is a cell-intrinsic metalloregulator of zinc in human ILC2s.

Group 2 innate lymphoid cells (ILC2s) produce large amounts of type 2 cytokines including interleukin-5 (IL-5) and IL-13 in response to various stimuli, causing allergic and eosinophilic diseases. However, the cell-intrinsic regulatory mechanisms of human ILC2s remain unclear. Here, we analyze human ILC2s derived from different tissues and pathological conditions and identify ANXA1, encoding annexin A1, as a commonly highly expressed gene in non-activated ILC2s. The expression of ANXA1 decreases when ILC2s activate, but it increases autonomously as the activation subsides. Lentiviral vector-based gene transfer experiments show that ANXA1 suppresses the activation of human ILC2s. Mechanistically, ANXA1 regulates the expression of the metallothionein family genes, including MT2A, which modulate intracellular zinc homeostasis. Furthermore, increased intracellular zinc levels play an essential role in the activation of human ILC2s by promoting the mitogen-activated protein kinase (MAPK) and nuclear factor κB (NF-κB) pathways and GATA3 expression. Thus, the ANXA1/MT2A/zinc pathway is identified as a cell-intrinsic metalloregulatory mechanism for human ILC2s.

N-terminal region of Drosophila melanogaster Argonaute2 forms amyloid-like aggregates.

BACKGROUND: Argonaute proteins play a central role in RNA silencing by forming protein-small RNA complexes responsible for the silencing process. While most Argonaute proteins have a short N-terminal region, Argonaute2 in Drosophila melanogaster (DmAgo2) harbors a long and unique N-terminal region. Previous in vitro biochemical studies have shown that the loss of this region does not impair the RNA silencing activity of the complex. However, an N-terminal mutant of Drosophila melanogaster has demonstrated abnormal RNA silencing activity. To explore the causes of this discrepancy between in vitro and in vivo studies, we investigated the biophysical properties of the region. The N-terminal region is highly rich in glutamine and glycine residues, which is a well-known property for prion-like domains, a subclass of amyloid-forming peptides. Therefore, the possibility of the N-terminal region functioning as an amyloid was tested. RESULTS: Our in silico and biochemical assays demonstrated that the N-terminal region exhibits amyloid-specific properties. The region indeed formed aggregates that were not dissociated even in the presence of sodium dodecyl sulfate. Also, the aggregates enhanced the fluorescence intensity of thioflavin-T, an amyloid detection reagent. The kinetics of the aggregation followed that of typical amyloid formation exhibiting self-propagating activity. Furthermore, we directly visualized the aggregation process of the N-terminal region under fluorescence microscopy and found that the aggregations took fractal or fibril shapes. Together, the results indicate that the N-terminal region can form amyloid-like aggregates. CONCLUSIONS: Many other amyloid-forming peptides have been reported to modulate the function of proteins through their aggregation. Therefore, our findings raise the possibility that aggregation of the N-terminal region regulates the RNA silencing activity of DmAgo2.

Whole-embryonic identification of maternal microchimeric cell types in mouse using single-cell RNA sequencing.

Even though the mother and the fetus of placental mammals are immunologically non-self with respect to one other, mutual exchange of small numbers of cells between them is known to occur. Maternal cells entering the fetus, called maternal microchimeric cells (MMc cells), are thought to be involved in different physiological phenomena, such as establishing immune tolerance, tissue repair, and the pathogenesis or deterioration of some inflammatory diseases and congenital malformations. While specific MMc cell types have been reported as associated with these phenomena, the contribution of MMc cells to these different outcomes remains unknown. As one possibility, we hypothesized that different embryos have differing repertoires of MMc cell types, leading to or biasing embryos toward different fates. To date, no studies have succeeded in identifying the MMc cell type repertoire of a single embryo. Accordingly, here, we isolated MMc cells from whole mouse embryos, determined their types, and analyzed their MMc cell type variability. By combining our previously established, whole-embryonic MMc isolation method with single-cell RNA sequencing, we successfully estimated the cell type repertoires of MMc cells isolated from 26 mouse embryos. The majority of MMc cells were immune-related cells, such as myeloid cells and granulocytes. We also detected stem cell-like MMc cells expressing proliferation marker genes and terminally differentiated cells. As hypothesized, we noted statistically significant inter-individual variation in the proportion of immune-related cells in the different embryos. We here successfully estimated MMc cell types in individual whole mouse embryos. The proportion of immune-related cells significantly differed among the individual embryos, suggesting that the variations are one of the potential mechanisms underlying the differing MMc-related physiological phenomena in offspring. These findings provide insight into cell-level epigenetics by maternal cells.

Zero-mode waveguides and nanopore-based sequencing technologies accelerate single-molecule studies.

Single-molecule technologies can provide detailed information regarding molecular mechanisms and interactions that cannot easily be studied on the bulk scale; generally, individual molecular behaviors cannot be distinguished, and only average characteristics can be measured. Nevertheless, the development of the single-molecule sequencer had a significant impact on conventional in vitro single-molecule research, featuring automated equipment, high-throughput chips, and automated analysis systems. However, the utilization of sequencing technology in in vitro single-molecule research is not yet globally prevalent, owing to the large gap between highly organized single-molecule sequencing and manual-based in vitro single-molecule research. Here, we describe the principles of zero-mode waveguides (ZMWs) and nanopore methods used as single-molecule DNA sequencing techniques, and provide examples of functional biological measurements beyond DNA sequencing that contribute to a global understanding of the current applications of these sequencing technologies. Furthermore, through a comparison of these two technologies, we discuss future applications of DNA sequencing technologies in in vitro single-molecule research.

Upregulation of IL-4 receptor signaling pathway in circulating ILC2s from asthma patients.

Background: Group 2 innate lymphoid cells (ILC2s) produce type 2 cytokines by stimulation with epithelial cell-derived cytokines and are implicated in the pathogenesis of various allergic diseases, including asthma. However, differences in the molecular characteristics of ILC2s between patients with asthma and healthy subjects remain unclear. Objective: We sought to evaluate differences in cytokine production capacity and gene expression profile of ILC2s in the peripheral blood of patients with asthma and healthy subjects. Methods: We evaluated ILC2s derived from 15 patients with asthma and 7 healthy subjects using flow cytometry, live-cell imaging of secretion activity analysis, and RNA-sequencing. Results: ILC2s were sorted as CD45+Lineage-CRTH2+CD127+CD161+ cells from the peripheral blood of patients with asthma and healthy subjects, and the number of ILC2s was decreased in patients with asthma (851 ± 1134 vs 2679 ± 3009 cells/20 mL blood; P = .0066). However, patient-derived ILC2s were activated to produce more IL-5 and IL-13 in response to stimulation with IL-2, IL-33, and thymic stromal lymphopoietin compared with healthy subject-derived ILC2s (P = .0032 and P = .0085, respectively). Furthermore, RNA-sequencing analysis revealed that patient-derived ILC2s had different gene expression profiles, such as increased expression in cell growth-related genes (CDKN1b, CCNG2, CCND2, CCN1), prostaglandin E receptor (PTGER2), and IL-4 receptor. In addition, a gene set of the IL-4 receptor signaling pathway was significantly upregulated in ILC2s in patients with asthma (P = .042). Conclusions: Our results suggest that circulating ILC2s in patients with asthma are preactivated via the IL-4 receptor signaling pathway and produce IL-5 and IL-13 vigorously by stimulation.

Heterogeneous dissociation process of truncated RNAs by oligomerized Vasa helicase.

RNA helicases are enzymes that generally unwind double-stranded RNA using ATP hydrolysis energy, mainly involved in RNA metabolism, transcription, translation, and mRNA splicing. While the helicase core is crucial for RNA unwinding activity, N- and C-terminal extensions of specific helicases may contain an intrinsically disordered region for electrostatic interaction, resulting in the formation of droplets in the cytoplasm. However, how the disordered region of the RNA helicase contributes to RNA unwinding and dissociation remains unclear. Here, we focused on Bombyx mori Vasa, which unwinds truncated target transposon RNAs from the piRNA-induced silencing complex piRISC. In this study, we used single-molecule techniques to visualise how Vasa dynamically interacts with piRISC and investigate how Vasa oligomerization is involved in the process of piRNA amplification, named the ping-pong pathway. We found that Vasa's oligomerization is required during these processes in vitro and in vivo, and that Vasa triggers the dissociation of truncated RNA in heterogeneous pathways. Our single-molecule results suggest that oligomerized Vasa guides the timing of the process regulating overall dissociation efficiency.

Development of a sequencing system for spatial decoding of DNA barcode molecules at single-molecule resolution.

Single-cell transcriptome analysis has been revolutionized by DNA barcodes that index cDNA libraries, allowing highly multiplexed analyses to be performed. Furthermore, DNA barcodes are being leveraged for spatial transcriptomes. Although spatial resolution relies on methods used to decode DNA barcodes, achieving single-molecule decoding remains a challenge. Here, we developed an in-house sequencing system inspired by a single-molecule sequencing system, HeliScope, to spatially decode DNA barcode molecules at single-molecule resolution. We benchmarked our system with 30 types of DNA barcode molecules and obtained an average read length of ~20 nt with an error rate of less than 5% per nucleotide, which was sufficient to spatially identify them. Additionally, we spatially identified DNA barcode molecules bound to antibodies at single-molecule resolution. Leveraging this, we devised a method, termed "molecular foot printing", showing potential for applying our system not only to spatial transcriptomics, but also to spatial proteomics.

Raman image-activated cell sorting.

The advent of image-activated cell sorting and imaging-based cell picking has advanced our knowledge and exploitation of biological systems in the last decade. Unfortunately, they generally rely on fluorescent labeling for cellular phenotyping, an indirect measure of the molecular landscape in the cell, which has critical limitations. Here we demonstrate Raman image-activated cell sorting by directly probing chemically specific intracellular molecular vibrations via ultrafast multicolor stimulated Raman scattering (SRS) microscopy for cellular phenotyping. Specifically, the technology enables real-time SRS-image-based sorting of single live cells with a throughput of up to ~100 events per second without the need for fluorescent labeling. To show the broad utility of the technology, we show its applicability to diverse cell types and sizes. The technology is highly versatile and holds promise for numerous applications that are previously difficult or undesirable with fluorescence-based technologies.

Intelligent image-activated cell sorting 2.0.

The advent of intelligent image-activated cell sorting (iIACS) has enabled high-throughput intelligent image-based sorting of single live cells from heterogeneous populations. iIACS is an on-chip microfluidic technology that builds on a seamless integration of a high-throughput fluorescence microscope, cell focuser, cell sorter, and deep neural network on a hybrid software-hardware data management architecture, thereby providing the combined merits of optical microscopy, fluorescence-activated cell sorting (FACS), and deep learning. Here we report an iIACS machine that far surpasses the state-of-the-art iIACS machine in system performance in order to expand the range of applications and discoveries enabled by the technology. Specifically, it provides a high throughput of ∼2000 events per second and a high sensitivity of ∼50 molecules of equivalent soluble fluorophores (MESFs), both of which are 20 times superior to those achieved in previous reports. This is made possible by employing (i) an image-sensor-based optomechanical flow imaging method known as virtual-freezing fluorescence imaging and (ii) a real-time intelligent image processor on an 8-PC server equipped with 8 multi-core CPUs and GPUs for intelligent decision-making, in order to significantly boost the imaging performance and computational power of the iIACS machine. We characterize the iIACS machine with fluorescent particles and various cell types and show that the performance of the iIACS machine is close to its achievable design specification. Equipped with the improved capabilities, this new generation of the iIACS technology holds promise for diverse applications in immunology, microbiology, stem cell biology, cancer biology, pathology, and synthetic biology.

Virtual-freezing fluorescence imaging flow cytometry.

By virtue of the combined merits of flow cytometry and fluorescence microscopy, imaging flow cytometry (IFC) has become an established tool for cell analysis in diverse biomedical fields such as cancer biology, microbiology, immunology, hematology, and stem cell biology. However, the performance and utility of IFC are severely limited by the fundamental trade-off between throughput, sensitivity, and spatial resolution. Here we present an optomechanical imaging method that overcomes the trade-off by virtually freezing the motion of flowing cells on the image sensor to effectively achieve 1000 times longer exposure time for microscopy-grade fluorescence image acquisition. Consequently, it enables high-throughput IFC of single cells at >10,000 cells s-1 without sacrificing sensitivity and spatial resolution. The availability of numerous information-rich fluorescence cell images allows high-dimensional statistical analysis and accurate classification with deep learning, as evidenced by our demonstration of unique applications in hematology and microbiology.

Author Correction: A practical guide to intelligent image-activated cell sorting.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A practical guide to intelligent image-activated cell sorting.

Intelligent image-activated cell sorting (iIACS) is a machine-intelligence technology that performs real-time intelligent image-based sorting of single cells with high throughput. iIACS extends beyond the capabilities of fluorescence-activated cell sorting (FACS) from fluorescence intensity profiles of cells to multidimensional images, thereby enabling high-content sorting of cells or cell clusters with unique spatial chemical and morphological traits. Therefore, iIACS serves as an integral part of holistic single-cell analysis by enabling direct links between population-level analysis (flow cytometry), cell-level analysis (microscopy), and gene-level analysis (sequencing). Specifically, iIACS is based on a seamless integration of high-throughput cell microscopy (e.g., multicolor fluorescence imaging, bright-field imaging), cell focusing, cell sorting, and deep learning on a hybrid software-hardware data management infrastructure, enabling real-time automated operation for data acquisition, data processing, intelligent decision making, and actuation. Here, we provide a practical guide to iIACS that describes how to design, build, characterize, and use an iIACS machine. The guide includes the consideration of several important design parameters, such as throughput, sensitivity, dynamic range, image quality, sort purity, and sort yield; the development and integration of optical, microfluidic, electrical, computational, and mechanical components; and the characterization and practical usage of the integrated system. Assuming that all components are readily available, a team of several researchers experienced in optics, electronics, digital signal processing, microfluidics, mechatronics, and flow cytometry can complete this protocol in ~3 months.

A20 prevents inflammasome-dependent arthritis by inhibiting macrophage necroptosis through its ZnF7 ubiquitin-binding domain.

Deficiency in the deubiquitinating enzyme A20 causes severe inflammation in mice, and impaired A20 function is associated with human inflammatory diseases. A20 has been implicated in negatively regulating NF-κB signalling, cell death and inflammasome activation; however, the mechanisms by which A20 inhibits inflammation in vivo remain poorly understood. Genetic studies in mice revealed that its deubiquitinase activity is not essential for A20 anti-inflammatory function. Here we show that A20 prevents inflammasome-dependent arthritis by inhibiting macrophage necroptosis and that this function depends on its zinc finger 7 (ZnF7). We provide genetic evidence that RIPK1 kinase-dependent, RIPK3-MLKL-mediated necroptosis drives inflammasome activation in A20-deficient macrophages and causes inflammatory arthritis in mice. Single-cell imaging revealed that RIPK3-dependent death caused inflammasome-dependent IL-1ß release from lipopolysaccharide-stimulated A20-deficient macrophages. Importantly, mutation of the A20 ZnF7 ubiquitin binding domain caused arthritis in mice, arguing that ZnF7-dependent inhibition of necroptosis is critical for A20 anti-inflammatory function in vivo.

Addendum: A FRET biosensor for necroptosis uncovers two different modes of the release of DAMPs.

The cDNA sequence of human SMART described in this Article was misreported, as described in the accompanying Addendum. This error does not affect the results or any conclusion of the Article.

Comment on "Ghost cytometry".

Ota et al (Reports, 15 June 2018, p. 1246) report using pseudo-random optical masks and a spatial-temporal transformation to perform blur-free, high-frame rate imaging of cells in flow with a high signal-to-noise ratio. They also claim sorting at rates of 3000 cells per second, based on imaging data. The experiments conducted and results reported in their study are insufficient to support these conclusions.

A FRET biosensor for necroptosis uncovers two different modes of the release of DAMPs.

Necroptosis is a regulated form of necrosis that depends on receptor-interacting protein kinase (RIPK)3 and mixed lineage kinase domain-like (MLKL). While danger-associated molecular pattern (DAMP)s are involved in various pathological conditions and released from dead cells, the underlying mechanisms are not fully understood. Here we develop a fluorescence resonance energy transfer (FRET) biosensor, termed SMART (a sensor for MLKL activation by RIPK3 based on FRET). SMART is composed of a fragment of MLKL and monitors necroptosis, but not apoptosis or necrosis. Mechanistically, SMART monitors plasma membrane translocation of oligomerized MLKL, which is induced by RIPK3 or mutational activation. SMART in combination with imaging of the release of nuclear DAMPs and Live-Cell Imaging for Secretion activity (LCI-S) reveals two different modes of the release of High Mobility Group Box 1 from necroptotic cells. Thus, SMART and LCI-S uncover novel regulation of the release of DAMPs during necroptosis.

Kinesin-binding-triggered conformation switching of microtubules contributes to polarized transport.

Kinesin-1, the founding member of the kinesin superfamily of proteins, is known to use only a subset of microtubules for transport in living cells. This biased use of microtubules is proposed as the guidance cue for polarized transport in neurons, but the underlying mechanisms are still poorly understood. Here, we report that kinesin-1 binding changes the microtubule lattice and promotes further kinesin-1 binding. This high-affinity state requires the binding of kinesin-1 in the nucleotide-free state. Microtubules return to the initial low-affinity state by washing out the binding kinesin-1 or by the binding of non-hydrolyzable ATP analogue AMPPNP to kinesin-1. X-ray fiber diffraction, fluorescence speckle microscopy, and second-harmonic generation microscopy, as well as cryo-EM, collectively demonstrated that the binding of nucleotide-free kinesin-1 to GDP microtubules changes the conformation of the GDP microtubule to a conformation resembling the GTP microtubule.

Intelligent Image-Activated Cell Sorting.

A fundamental challenge of biology is to understand the vast heterogeneity of cells, particularly how cellular composition, structure, and morphology are linked to cellular physiology. Unfortunately, conventional technologies are limited in uncovering these relations. We present a machine-intelligence technology based on a radically different architecture that realizes real-time image-based intelligent cell sorting at an unprecedented rate. This technology, which we refer to as intelligent image-activated cell sorting, integrates high-throughput cell microscopy, focusing, and sorting on a hybrid software-hardware data-management infrastructure, enabling real-time automated operation for data acquisition, data processing, decision-making, and actuation. We use it to demonstrate real-time sorting of microalgal and blood cells based on intracellular protein localization and cell-cell interaction from large heterogeneous populations for studying photosynthesis and atherothrombosis, respectively. The technology is highly versatile and expected to enable machine-based scientific discovery in biological, pharmaceutical, and medical sciences.