Pigmentation level of human iPSC-derived RPE does not indicate a specific gene expression profile.

Retinal pigment epithelium (RPE) cells show heterogeneous levels of pigmentation when cultured in vitro. To know whether their color in appearance is correlated with the function of the RPE, we analyzed the color intensities of human-induced pluripotent stem cell-derived RPE cells (iPSC-RPE) together with the gene expression profile at the single-cell level. For this purpose, we utilized our recent invention, Automated Live imaging and cell Picking System (ALPS), which enabled photographing each cell before RNA-sequencing analysis to profile the gene expression of each cell. While our iPSC-RPE were categorized into four clusters by gene expression, the color intensity of iPSC-RPE did not project any specific gene expression profiles. We reasoned this by less correlation between the actual color and the gene expressions that directly define the level of pigmentation, from which we hypothesized the color of RPE cells may be a temporal condition not strongly indicating the functional characteristics of the RPE.

The backs of our eyes are lined with retinal pigment epithelial cells (or RPE cells for short). These cells provide nutrition to surrounding cells and contain a pigment called melanin that absorbs excess light that might interfere with vision. By doing so, they support the cells that receive light to enable vision. However, with age, RPE cells can become damaged and less able to support other cells. This can lead to a disease called age-related macular degeneration, which can cause blindness. One potential way to treat this disease is to transplant healthy RPE cells into eyes that have lost them. These healthy cells can be grown in the laboratory from human pluripotent stem cells, which have the capacity to turn into various specialist cells. Stem cell-derived RPE cells growing in a dish contain varying amounts of melanin, resulting in some being darker than others. This raised the question of whether pigment levels affect the function of RPE cells. However, it was difficult to compare single cells containing various amounts of pigment as most previous studies only analyzed large numbers of RPE cells mixed together. Nakai-Futatsugi et al. overcame this hurdle using a technique called Automated Live imaging and cell Picking System (also known as ALPS). More than 2300 stem cell-derived RPE cells were photographed individually and the color of each cell was recorded. The gene expression of each cell was then measured to investigate whether certain genes being switched on or off affects pigment levels and cell function. Analysis did not find a consistent pattern of gene expression underlying the pigmentation of RPE cells. Even gene expression related to the production of melanin was only slightly linked to the color of the cells. These findings suggests that the RPE cell color fluctuates and is not primarily determined by which genes are switched on or off. Future experiments are required to determine whether the findings are the same for RPE cells grown naturally in the eyes and whether different pigment levels affect their capacity to protect the rest of the eye.

Identifying a Lung Stem Cell Subpopulation by Combining Single-Cell Morphometrics, Organoid Culture, and Transcriptomics.

Single-cell RNA sequencing is a valuable tool for dissecting cellular heterogeneity in complex systems. However, it is still challenging to estimate the proliferation and differentiation potentials of subpopulations within dormant tissue stem cells. Here, we established a new single-cell analysis method for profiling the organoid-forming capacity and differentiation potential of tissue stem cells to disclose stem cell subpopulations by integrating single-cell morphometrics, organoid-forming assay, and RNA sequencing, a method named scMORN. To explore lung epithelial stem cells, we initially developed feeder-free culture system, which could expand all major lung stem cells, including basal, club, and alveolar type 2 (AT2) cells, and found that club cells contained a subpopulation, which showed better survival rate and high proliferation capacity and could differentiate into alveolar cells. Using the scMORN method, we discovered a club cell subpopulation named Muc5b+ and large club (ML-club) cells that efficiently formed organoids than other club or AT2 cells in our feeder-free organoid culture and differentiated into alveolar cells in vitro. Single-cell transcriptome profiling and immunohistochemical analysis revealed that ML-club cells localized at the intrapulmonary proximal airway and distinct from known subpopulations of club cells such as BASCs. Furthermore, we identified CD14 as a cell surface antigen of ML-club cells and showed that purified CD14+ club cells engrafted into injured mouse lungs had better engraftment rate and expansion than other major lung stem cells, reflecting the observations in organoid culture systems. The scMORN method could be adapted to different stem cell tissues to discover useful stem-cell subpopulations.

Robotic data acquisition with deep learning enables cell image-based prediction of transcriptomic phenotypes.

Single-cell whole-transcriptome analysis is the gold standard approach to identifying molecularly defined cell phenotypes. However, this approach cannot be used for dynamics measurements such as live-cell imaging. Here, we developed a multifunctional robot, the automated live imaging and cell picking system (ALPS) and used it to perform single-cell RNA sequencing for microscopically observed cells with multiple imaging modes. Using robotically obtained data that linked cell images and the whole transcriptome, we successfully predicted transcriptome-defined cell phenotypes in a noninvasive manner using cell image-based deep learning. This noninvasive approach opens a window to determine the live-cell whole transcriptome in real time. Moreover, this work, which is based on a data-driven approach, is a proof of concept for determining the transcriptome-defined phenotypes (i.e., not relying on specific genes) of any cell from cell images using a model trained on linked datasets.

A circulating subset of iNKT cells mediates antitumor and antiviral immunity.

Invariant natural killer T (iNKT) cells are a group of innate-like T lymphocytes that recognize lipid antigens. They are supposed to be tissue resident and important for systemic and local immune regulation. To investigate the heterogeneity of iNKT cells, we recharacterized iNKT cells in the thymus and peripheral tissues. iNKT cells in the thymus were divided into three subpopulations by the expression of the natural killer cell receptor CD244 and the chemokine receptor CXCR6 and designated as C0 (CD244-CXCR6-), C1 (CD244-CXCR6+), or C2 (CD244+CXCR6+) iNKT cells. The development and maturation of C2 iNKT cells from C0 iNKT cells strictly depended on IL-15 produced by thymic epithelial cells. C2 iNKT cells expressed high levels of IFN-γ and granzymes and exhibited more NK cell-like features, whereas C1 iNKT cells showed more T cell-like characteristics. C2 iNKT cells were influenced by the microbiome and aging and suppressed the expression of the autoimmune regulator AIRE in the thymus. In peripheral tissues, C2 iNKT cells were circulating that were distinct from conventional tissue-resident C1 iNKT cells. Functionally, C2 iNKT cells protected mice from the tumor metastasis of melanoma cells by enhancing antitumor immunity and promoted antiviral immune responses against influenza virus infection. Furthermore, we identified human CD244+CXCR6+ iNKT cells with high cytotoxic properties as a counterpart of mouse C2 iNKT cells. Thus, this study reveals a circulating subset of iNKT cells with NK cell-like properties distinct from conventional tissue-resident iNKT cells.

Different cell imaging methods did not significantly improve immune cell image classification performance.

Developments in high-throughput microscopy have made it possible to collect huge amounts of cell image data that are difficult to analyse manually. Machine learning (e.g., deep learning) is often employed to automate the extraction of information from these data, such as cell counting, cell type classification and image segmentation. However, the effects of different imaging methods on the accuracy of image processing have not been examined systematically. We studied the effects of different imaging methods on the performance of machine learning-based cell type classifiers. We observed lymphoid-primed multipotential progenitor (LMPP) and pro-B cells using three imaging methods: differential interference contrast (DIC), phase contrast (Ph) and bright-field (BF). We examined the classification performance of convolutional neural networks (CNNs) with each of them and their combinations. CNNs achieved an area under the receiver operating characteristic (ROC) curve (AUC) of ~0.9, which was significantly better than when the classifier used only cell size or cell contour shape as input. However, no significant differences were found between imaging methods and focal positions.

B cell-derived GABA elicits IL-10+ macrophages to limit anti-tumour immunity.

Small, soluble metabolites not only are essential intermediates in intracellular biochemical processes, but can also influence neighbouring cells when released into the extracellular milieu1-3. Here we identify the metabolite and neurotransmitter GABA as a candidate signalling molecule synthesized and secreted by activated B cells and plasma cells. We show that B cell-derived GABA promotes monocyte differentiation into anti-inflammatory macrophages that secrete interleukin-10 and inhibit CD8+ T cell killer function. In mice, B cell deficiency or B cell-specific inactivation of the GABA-generating enzyme GAD67 enhances anti-tumour responses. Our study reveals that, in addition to cytokines and membrane proteins, small metabolites derived from B-lineage cells have immunoregulatory functions, which may be pharmaceutical targets allowing fine-tuning of immune responses.

Mitochondrial reactive oxygen species trigger metformin-dependent antitumor immunity via activation of Nrf2/mTORC1/p62 axis in tumor-infiltrating CD8T lymphocytes.

BACKGROUND: Metformin (Met) is the first-line treatment for type 2 diabetes mellitus and plays an effective role in treating various diseases, such as cardiovascular disease, neurodegenerative disease, cancer, and aging. However, the underlying mechanism of Met-dependent antitumor immunity remains to be elucidated. METHODS: MitoTEMPO, a scavenger of mitochondrial superoxide, abolished the antitumor effect of Met, but not antiprogrammed cell death (PD-1) antibody (Ab) treatment. Consequently, we studied the mechanism of the Met-induced antitumor effect. Expressions of glucose transporter (Glut)-1, mitochondrial reactive oxygen species (mtROS), interferon (IFN)-γ, Ki67, autophagy markers, activation markers for NF-E2-related factor 2 (Nrf2), and mammalian target of rapamaycin complex 1 (mTORC1) in CD8+ tumor-infiltrating T lymphocytes (CD8TILs) were examined by flow cytometry analysis. In addition, conditional knockout mice for Nrf2 and p62 were used to detect these markers, together with the monitoring of in vivo tumor growth. RNA sequencing was performed for CD8TILs and tumor cells. Melanoma cells containing an IFN-γ receptor (IFNγR) cytoplasmic domain deletion mutant was overexpressed and used for characterization of the metabolic profile of those tumor cells using a Seahorse Flux Analyzer. RESULTS: Met administration elevates mtROS and cell surface Glut-1, resulting in the production of IFN-γ in CD8TILs. mtROS activates Nrf2 in a glycolysis-dependent manner, inducing activation of autophagy, glutaminolysis, mTORC1, and p62/SQSTM1. mTORC1-dependent phosphorylation of p62 at serine 351 (p-p62(S351)) is also involved in activation of Nrf2. Conditional deletion of Nrf2 in CD8TILs abrogates mTORC1 activation and antitumor immunity by Met. In synergy with the effect of anti-PD-1 Ab, Met boosts CD8TIL proliferation and IFN-γ secretion, resulting in decreased glycolysis and oxidative phosphorylation in tumor cells. Consequently, Glut-1 is elevated in CD8TILs, together with the expansion of activated dendritic cells. Moreover, tumor cells lacking in IFNγR signaling abolish IFN-γ production and proliferation of CD8TILs. CONCLUSIONS: We found that Met stimulates production of mtROS, which triggers Glut-1 elevation and Nrf2 activation in CD8TILs. Nrf2 activates mTORC1, whereas mTORC1 activates Nrf2 in a p-p62(S351)-dependent manner, thus creating a feedback loop that ensures CD8TILs' proliferation. In combination with anti-PD-1 Ab, Met stimulates robust proliferation of CD8TILs and IFN-γ secretion, resulting in an IFN-γ-dependent reprogramming of the tumor microenvironment.

HaloTag-based conjugation of proteins to barcoding-oligonucleotides.

Highly sensitive protein quantification enables the detection of a small number of protein molecules that serve as markers/triggers for various biological phenomena, such as cancer. Here, we describe the development of a highly sensitive protein quantification system called HaloTag protein barcoding. The method involves covalent linking of a target protein to a unique molecule counting oligonucleotide at a 1:1 conjugation ratio based on an azido-cycloalkyne click reaction. The sensitivity of the HaloTag-based barcoding was remarkably higher than that of a conventional luciferase assay. The HaloTag system was successfully validated by analyzing a set of protein-protein interactions, with the identification rate of 44% protein interactions between positive reference pairs reported in the literature. Desmoglein 3, the target antigen of pemphigus vulgaris, an IgG-mediated autoimmune blistering disease, was used in a HaloTag protein barcode assay to detect the anti-DSG3 antibody. The dynamic range of the assay was over 104-times wider than that of a conventional enzyme-linked immunosorbent assay (ELISA). The technology was used to detect anti-DSG3 antibody in patient samples with much higher sensitivity compared to conventional ELISA. Our detection system, with its superior sensitivity, enables earlier detection of diseases possibly allowing the initiation of care/treatment at an early disease stage.

Processive Nanostepping of Formin mDia1 Loosely Coupled with Actin Polymerization.

Formins are actin-binding proteins that construct nanoscale machinery with the growing barbed end of actin filaments and serve as key regulators of actin polymerization and depolymerization. To maintain the regulation of actin dynamics, formins have been proposed to processively move at every association or dissociation of a single actin molecule toward newly formed barbed ends. However, the current models for the motile mechanisms were established without direct observation of the elementary processes of this movement. Here, using optical tweezers, we demonstrate that formin mDia1 moves stepwise, observed at a nanometer spatial resolution. The movement was composed of forward and backward steps with unitary step sizes of 2.8 and -2.4 nm, respectively, which nearly equaled the actin subunit length (∼2.7 nm), consistent with the generally accepted models. However, in addition to steps equivalent to the length of a single actin subunit, those equivalent to the length of two or three subunits were frequently observed. Our findings suggest that the coupling between mDia1 stepping and actin polymerization is not tight but loose, which may be achieved by the multiple binding states of mDia1, providing insights into the synergistic functions of biomolecules for the efficient construction and regulation of nanofilaments.

The efficacy and further functional advantages of random-base molecular barcodes for absolute and digital quantification of nucleic acid molecules.

Accurate quantification of biomolecules in system-wide measurements is in high demand, especially for systems with limited sample amounts such as single cells. Because of this, digital quantification of nucleic acid molecules using molecular barcodes has been developed, making, e.g., transcriptome analysis highly reproducible and quantitative. This counting scheme was shown to work using sequence-restricted barcodes, and non-sequence-restricted (random-base) barcodes that may provide a much higher dynamic range at significantly lower cost have been widely used. However, the efficacy of random-base barcodes is significantly affected by base changes due to amplification and/or sequencing errors and has not been investigated experimentally or quantitatively. Here, we show experimentally that random-base barcodes enable absolute and digital quantification of DNA molecules with high dynamic range (from one to more than 104, potentially up to 1015 molecules) conditional on our barcode design and variety, a certain range of sequencing depths, and computational analyses. Moreover, we quantitatively show further functional advantages of the molecular barcodes: the molecular barcodes enable one to find contaminants and misidentifications of target sequences. Our scheme here may be generally used to confirm that the digital quantification works in each platform.

Biphasic Effect of Profilin Impacts the Formin mDia1 Force-Sensing Mechanism in Actin Polymerization.

Formins are force-sensing proteins that regulate actin polymerization dynamics. Here, we applied stretching tension to individual actin filaments under the regulation of formin mDia1 to investigate the mechanical responses in actin polymerization dynamics. We found that the elongation of an actin filament was accelerated to a greater degree by stretching tension for ADP-G-actin than that for ATP-G-actin. An apparent decrease in the critical concentration of G-actin was observed, especially in ADP-G-actin. These results on two types of G-actin were reproduced by a simple kinetic model, assuming the rapid equilibrium between pre- and posttranslocated states of the formin homology domain two dimer. In addition, profilin concentration dramatically altered the force-dependent acceleration of actin filament elongation, which ranged from twofold to an all-or-none response. Even under conditions in which actin depolymerization occurred, applications of a several-piconewton stretching tension triggered rapid actin filament elongation. This extremely high force-sensing mechanism of mDia1 and profilin could be explained by the force-dependent coordination of the biphasic effect of profilin; i.e., an acceleration effect masked by a depolymerization effect became dominant under stretching tension, negating the latter to rapidly enhance the elongation rate. Our findings demonstrate that the biphasic effect of profilin is controlled by mechanical force, thus expanding the function of mDia1 as a mechanosensitive regulator of actin polymerization.

Torsional stress in DNA limits collaboration among reverse gyrase molecules.

Reverse gyrase is an enzyme that can overwind (introduce positive supercoils into) DNA using the energy obtained from ATP hydrolysis. The enzyme is found in hyperthermophiles, and the overwinding reaction generally requires a temperature above 70 °C. In a previous study using microscopy, we have shown that 30 consecutive mismatched base pairs (a bubble) in DNA serve as a well-defined substrate site for reverse gyrase, warranting the processive overwinding activity down to 50 °C. Here, we inquire how multiple reverse gyrase molecules may collaborate with each other in overwinding one DNA molecule. We introduced one, two, or four bubbles in a linear DNA that tethered a magnetic bead to a coverslip surface. At 40-71 °C in the presence of reverse gyrase, the bead rotated clockwise as viewed from above, to relax the DNA twisted by reverse gyrase. Dependence on the enzyme concentration indicated that each bubble binds reverse gyrase tightly (dissociation constant < 0.1 nm) and that bound enzyme continuously overwinds DNA for > 5 min. Rotation with two bubbles was significantly faster compared with one bubble, indicating that overwinding actions are basically additive, but four bubbles did not show further acceleration except at 40 °C where the activity was very low. The apparent saturation is due to the hydrodynamic friction against the rotating bead, as confirmed by increasing the medium viscosity. When torsional stress in the DNA, determined by the friction, approaches ~ 7 pN·nm (at 71 °C), the overwinding activity of reverse gyrase drops sharply. Multiple molecules of reverse gyrase collaborate additively within this limit.

Direct observation of DNA overwinding by reverse gyrase.

Reverse gyrase, found in hyperthermophiles, is the only enzyme known to overwind (introduce positive supercoils into) DNA. The ATP-dependent activity, detected at >70 °C, has so far been studied solely by gel electrophoresis; thus, the reaction dynamics remain obscure. Here, we image the overwinding reaction at 71 °C under a microscope, using DNA containing consecutive 30 mismatched base pairs that serve as a well-defined substrate site. A single reverse gyrase molecule processively winds the DNA for >100 turns. Bound enzyme shows moderate temperature dependence, retaining significant activity down to 50 °C. The unloaded reaction rate at 71 °C exceeds five turns per second, which is >10(2)-fold higher than hitherto indicated but lower than the measured ATPase rate of 20 s(-1), indicating loose coupling. The overwinding reaction sharply slows down as the torsional stress accumulates in DNA and ceases at stress of mere ∼ 5 pN ⋅ nm, where one more turn would cost only sixfold the thermal energy. The enzyme would thus keep DNA in a slightly overwound state to protect, but not overprotect, the genome of hyperthermophiles against thermal melting. Overwinding activity is also highly sensitive to DNA tension, with an effective interaction length exceeding the size of reverse gyrase, implying requirement for slack DNA. All results point to the mechanism where strand passage relying on thermal motions, as in topoisomerase IA, is actively but loosely biased toward overwinding.

Direct observation of strand passage by DNA-topoisomerase and its limited processivity.

Type-II DNA topoisomerases resolve DNA entanglements such as supercoils, knots and catenanes by passing one segment of DNA duplex through a transient enzyme-bridged double-stranded break in another segment. The ATP-dependent passage reaction has previously been demonstrated at the single-molecule level, showing apparent processivity at saturating ATP. Here we directly observed the strand passage by human topoisomerase IIα, after winding a pair of fluorescently stained DNA molecules with optical tweezers for 30 turns into an X-shaped braid. On average 0.51 ± 0.33 µm (11 ± 6 turns) of a braid was unlinked in a burst of reactions taking 8 ± 4 s, the unlinked length being essentially independent of the enzyme concentration between 0.25-37 pM. The time elapsed before the start of processive unlinking decreased with the enzyme concentration, being ~100 s at 3.7 pM. These results are consistent with a scenario where the enzyme binds to one DNA for a period of ~10 s, waiting for multiple diffusional encounters with the other DNA to transport it across the break ~10 times, and then dissociates from the binding site without waiting for the exhaustion of transportable DNA segments.