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.

High-throughput identification and quantification of bacterial cells in the microbiota based on 16S rRNA sequencing with single-base accuracy using BarBIQ.

Bacteria often function as a community, called the microbiota, consisting of many different bacterial species. The accurate identification of bacterial types and the simultaneous quantification of the cells of each bacterial type will advance our understanding of microbiota; however, this cannot be performed by conventional 16S rRNA sequencing methods as they only identify and quantify genes, which do not always represent cells. Here, we present a protocol for our developed method, barcoding bacteria for identification and quantification (BarBIQ). In BarBIQ, the 16S rRNA genes of single bacterial cells are amplified and attached to a unique cellular barcode in a droplet. Sequencing the tandemly linked cellular barcodes and 16S rRNA genes from many droplets (representing many cells with unique cellular barcodes) and clustering the sequences using the barcodes determines both the bacterial type for each cell based on 16S rRNA gene and the number of cells for each bacterial type based on the quantity of barcode types sequenced. Single-base accuracy for 16S rRNA sequencing is achieved via the barcodes and by avoiding chimera formation from 16S rRNA genes of different bacteria using droplets. For data processing, an easy-to-use bioinformatic pipeline is available ( https://github.com/Shiroguchi-Lab/BarBIQ_Pipeline_V1_2_0 ). This protocol allows researchers with experience in molecular biology but without bioinformatics experience to perform the process in ~2 weeks. We show the application of BarBIQ in mouse gut microbiota analysis as an example; however, this method is also applicable to other microbiota samples, including those from the mouth and skin, marine environments, soil and plants, as well as those from other terrestrial environments.

Sensory neuronal STAT3 is critical for IL-31 receptor expression and inflammatory itch.

IL-31 receptor blockade suppresses pruritus of atopic dermatitis. However, cell-type-specific contributions of IL-31 receptor to itch, its expression mechanism, and the downstream signaling pathway to induce itch remain unknown. Here, using conditional knockout mice, we demonstrate that IL-31-induced itch requires sensory neuronal IL-31 receptor and STAT3. We find that IL-31 receptor expression is dependent on STAT3 in sensory neurons. In addition, pharmacological experiments suggest that STAT3 activation is important for the itch-inducing signaling downstream of the IL-31 receptor. A cutaneous IL-31 injection induces the nuclear accumulation of activated STAT3 first in sensory neurons that abundantly express IL-31 receptor and then in other itch-transmitting neurons. IL-31 enhances itch induced by various pruritogens including even chloroquine. Finally, pruritus associated with dermatitis is partially dependent on sensory neuronal IL-31 receptor and strongly on sensory neuronal STAT3. Thus, sensory neuronal STAT3 is essential for IL-31-induced itch and further contributes to IL-31-independent inflammatory itch.

KaScape: a sequencing-based method for global characterization of protein‒DNA binding affinity.

It is difficult to exhaustively screen all possible DNA binding sequences for a given transcription factor (TF). Here, we developed the KaScape method, in which TFs bind to all possible DNA sequences in the same DNA pool where DNA sequences are prepared by randomized oligo synthesis and the random length can be adjusted to a length such as 4, 5, 6, or 7. After separating bound from unbound double-stranded DNAs (dsDNAs), their sequences are determined by next-generation sequencing. To demonstrate the relative binding affinities of all possible DNA sequences determined by KaScape, we developed three-dimensional KaScape viewing software based on a K-mer graph. We applied KaScape to 12 plant TF family AtWRKY proteins and found that all AtWRKY proteins bound to the core sequence GAC with similar profiles. KaScape can detect not only binding sequences consistent with the consensus W-box "TTGAC(C/T)" but also other sequences with weak affinity. KaScape provides a high-throughput, easy-to-operate, sensitive, and exhaustive method for quantitatively characterizing the relative binding strength of a TF with all possible binding sequences, allowing us to comprehensively characterize the specificity and affinity landscape of transcription factors, particularly for moderate- and low-affinity binding sites.

CD45 alleviates airway inflammation and lung fibrosis by limiting expansion and activation of ILC2s.

Group 2 innate lymphoid cells (ILC2s) are critical for the immune response against parasite infection and tissue homeostasis and involved in the pathogenesis of allergy and inflammatory diseases. Although multiple molecules positively regulating ILC2 development and activation have been extensively investigated, the factors limiting their population size and response remain poorly studied. Here, we found that CD45, a membrane-bound tyrosine phosphatase essential for T cell development, negatively regulated ILC2s in a cell-intrinsic manner. ILC2s in CD45-deficient mice exhibited enhanced proliferation and maturation in the bone marrow and hyperactivated phenotypes in the lung with high glycolytic capacity. Furthermore, CD45 signaling suppressed the type 2 inflammatory response by lung ILC2s and alleviated airway inflammation and pulmonary fibrosis. Finally, the interaction with galectin-9 influenced CD45 signaling in ILC2s. These results demonstrate that CD45 is a cell-intrinsic negative regulator of ILC2s and prevents lung inflammation and fibrosis via ILC2s.

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.

High-throughput identification and quantification of single bacterial cells in the microbiota.

The bacterial microbiota works as a community that consists of many individual organisms, i.e., cells. To fully understand the function of bacterial microbiota, individual cells must be identified; however, it is difficult with current techniques. Here, we develop a method, Barcoding Bacteria for Identification and Quantification (BarBIQ), which classifies single bacterial cells into taxa-named herein cell-based operational taxonomy units (cOTUs)-based on cellularly barcoded 16S rRNA sequences with single-base accuracy, and quantifies the cell number for each cOTU in the microbiota in a high-throughput manner. We apply BarBIQ to murine cecal microbiotas and quantify in total 3.4 × 105 bacterial cells containing 810 cOTUs. Interestingly, we find location-dependent global differences in the cecal microbiota depending on the dietary vitamin A deficiency, and more differentially abundant cOTUs at the proximal location than the distal location. Importantly, these location differences are not clearly shown by conventional 16S rRNA gene-amplicon sequencing methods, which quantify the 16S rRNA genes, not the cells. Thus, BarBIQ enables microbiota characterization with the identification and quantification of individual constituent bacteria, which is a cornerstone for microbiota studies.

Cancer biology deciphered by single-cell transcriptomic sequencing.

Tumors are complex ecosystems in which heterogeneous cancer cells interact with their microenvironment composed of diverse immune, endothelial, and stromal cells. Cancer biology had been studied using bulk genomic and gene expression profiling, which however mask the cellular diversity and average the variability among individual molecular programs. Recent advances in single-cell transcriptomic sequencing have enabled a detailed dissection of tumor ecosystems and promoted our understanding of tumorigenesis at single-cell resolution. In the present review, we discuss the main topics of recent cancer studies that have implemented single-cell RNA sequencing (scRNA-seq). To study cancer cells, scRNA-seq has provided novel insights into the cancer stem-cell model, treatment resistance, and cancer metastasis. To study the tumor microenvironment, scRNA-seq has portrayed the diverse cell types and complex cellular states of both immune and non-immune cells interacting with cancer cells, with the promise to discover novel targets for future immunotherapy.

Nonspecific DNA Binding of cGAS N Terminus Promotes cGAS Activation.

The cytosolic DNA sensor cyclic GMP-AMP synthase (cGAS) mediates innate immune responses against invading pathogens, or against self-dsDNA, which causes autoimmune disorders. Upon nonspecific binding of cytosolic B-form DNA, cGAS synthesizes the second messenger 2'3'-cGAMP and triggers STING-dependent signaling to produce type I IFNs. The cGAS comprises less-conserved N-terminal residues and highly conserved nucleotidyltransferase/Mab21 domains. The function and structure of the well-conserved domains have been extensively studied, whereas the physiological function of the N-terminal domain of cGAS is largely uncharacterized. In this study we used a single-molecule technique combined with traditional biochemical and cellular assays to demonstrate that binding of nonspecific dsDNA by the N-terminal domain of cGAS promotes its activation. We have observed that the N terminus of human cGAS (hcGAS-N160) undergoes secondary structural change upon dsDNA binding in solution. Furthermore, we showed that the hcGAS-N160 helps full length hcGAS to expand the binding range on λDNA and facilitates its binding efficiency to dsDNA compared with hcGAS without the 160 N-terminal residues (hcGAS-d160). More importantly, hcGAS-N160 endows full length hcGAS relatively higher enzyme activity and stronger activation of STING/IRF3-mediated cytosolic DNA signaling. These findings strongly indicate that the N-terminal domain of cGAS plays an important role in enhancing its function.

Deep sequencing reveals global patterns of mRNA recruitment during translation initiation.

In this work, we developed a method to systematically study the sequence preference of mRNAs during translation initiation. Traditionally, the dynamic process of translation initiation has been studied at the single molecule level with limited sequencing possibility. Using deep sequencing techniques, we identified the sequence preference at different stages of the initiation complexes. Our results provide a comprehensive and dynamic view of the initiation elements in the translation initiation region (TIR), including the S1 binding sequence, the Shine-Dalgarno (SD)/anti-SD interaction and the second codon, at the equilibrium of different initiation complexes. Moreover, our experiments reveal the conformational changes and regional dynamics throughout the dynamic process of mRNA recruitment.

The effects of cytosine methylation on general transcription factors.

DNA methylation on CpG sites is the most common epigenetic modification. Recently, methylation in a non-CpG context was found to occur widely on genomic DNA. Moreover, methylation of non-CpG sites is a highly controlled process, and its level may vary during cellular development. To study non-CpG methylation effects on DNA/protein interactions, we have chosen three human transcription factors (TFs): glucocorticoid receptor (GR), brain and muscle ARNT-like 1 (BMAL1) - circadian locomotor output cycles kaput (CLOCK) and estrogen receptor (ER) with methylated or unmethylated DNA binding sequences, using single-molecule and isothermal titration calorimetry assays. The results demonstrated that these TFs interact with methylated DNA with different effects compared with their cognate DNA sequences. The effects of non-CpG methylation on transcriptional regulation were validated by cell-based luciferase assay at protein level. The mechanisms of non-CpG methylation influencing DNA-protein interactions were investigated by crystallographic analyses and molecular dynamics simulation. With BisChIP-seq assays in HEK-293T cells, we found that GR can recognize highly methylated sites within chromatin in cells. Therefore, we conclude that non-CpG methylation of DNA can provide a mechanism for regulating gene expression through directly affecting the binding of TFs.

Probing allostery through DNA.

Allostery is well documented for proteins but less recognized for DNA-protein interactions. Here, we report that specific binding of a protein on DNA is substantially stabilized or destabilized by another protein bound nearby. The ternary complex's free energy oscillates as a function of the separation between the two proteins with a periodicity of ~10 base pairs, the helical pitch of B-form DNA, and a decay length of ~15 base pairs. The binding affinity of a protein near a DNA hairpin is similarly dependent on their separation, which-together with molecular dynamics simulations-suggests that deformation of the double-helical structure is the origin of DNA allostery. The physiological relevance of this phenomenon is illustrated by its effect on gene expression in live bacteria and on a transcription factor's affinity near nucleosomes.

Highly sensitive identification of cancer cells by combining the new tetrathiafulvalene derivative with a ß-cyclodextrin/multi-walled carbon nanotubes modified GCE.

In this contribution, we have prepared and explored a novel nano-interface based probe for the rapid identification and highly sensitive detection of cancer cells by means of an electrochemical study. The new probe tetrathiafulvalene (TTF) carboxylate salt (TTF-(COONBu(4))(2), ditetrabutylammonium salt for propylenedithio-4',5'-tetrathiafulvalene-4,5-dicarboxylate), which has specific spectral and electrochemical properties, has been synthesized and assembled with carbon nanotubes to form a new type of nanocomposite. A simple method of fabricating the ß-CD/MWCNT modified electrodes based on functionalized multi-walled carbon nanotubes (MWCNTs) and ß-cyclodextrin (ß-CD) has been explored by using glassy carbon electrodes (GCEs), which could remarkably enhance the sensitivity of the biomolecular detection. Our results demonstrate that the combination of the new probe TTF-(COONBu(4))(2) with ß-CD/MWCNT modified electrodes could be readily utilized to sensitively detect cancer cells such as liver cancer cells SMMC-7721 and HepG2, drug sensitive leukemia K562/B.W cells and drug resistant leukemia K562/ADM cells, with a detection limit of ~10(3) cells mL(-1). This may provide a novel strategy for the potential and promising application of the new TTF molecular probe in the development of multi-signal responsive biosensors for the early diagnosis of cancers.