Single-cell Level Research Articles

Label-Free Raman Probing of the Intrinsic Electric Field for High-Efficiency Screening of Electricity-Producing Bacteria at the Single-Cell Level.

The fabrication of high-performance microbial fuel cells requires the evaluation of the activity of electrochemically active bacteria. However, this is challenging because of the time-consuming nature of biofilm formation and the invasive nature of labeling. To address this issue, we developed a fast, label-free, single-cell Raman spectroscopic method. This method involves investigating the "pure" linear Stark effect of endogenous CO in the silent region of biological samples, which allows for probing the intrinsic electric field in the outer-membrane cytochromes of live bacterial cells. We found that reduced outer-membrane cytochromes can generate an additional intrinsic electric field equivalent to an applied potential of +0.29 V. We also found that the higher the electrical activity of the cell, the larger the generated electric field. This was also reflected in the output current of the constructed microbial fuel cells. Raman spectroscopy was employed to facilitate the assessment of electrochemical activity at the single-cell level in highly-diluted bacterial samples. After analysis, inactive bacteria were ablated by laser heating, and 20 active cells were cultured for further testing. The rapid and high-throughput probing of the intrinsic electric field offers a promising platform for high-efficiency screening of electrochemically active bacterial cells for bioenergetic and photosynthetic research.

Viscoelastic Fluid Focusing Chip-ICP-MS Single-Cell Analysis Enables Elucidating the Effect of Extracellular Polymeric Substances on Bioaccumulation of Hg2+/HgS in Microcystis aeruginosa Cell.

Understanding the interactions between mercury and microalgae, especially the interactions between inorganic mercury (IHg) and extracellular polymeric substances (EPS, a protective barrier between cells and their external environment), is essential for elucidating mercury's toxicological mechanisms. Given the inherent cell heterogeneity, a novel analysis system of an online viscoelastic fluid focusing chip-time-resolved analysis inductively coupled plasma mass spectrometry has been developed to investigate the bioaccumulation of HgS nanoparticles and Hg2+ in single Microcystis aeruginosa (M. aeruginosa) cells, exploring the interaction mechanisms between HgS/Hg2+ accumulation in algal cells and EPS. The single-cell analysis results reveal minimal bioavailability of HgS within algal cells, with mercury's toxicity to M. aeruginosa being species-dependent. Notably, algal cells exhibited more heterogeneity in HgS uptake than in Hg2+ uptake. Under Hg2+/HgS stress, M. aeruginosa cells with EPS removed (EPS-R algal cells) showed an increased level of bioaccumulation of mercury compared to those with EPS (EPS-C algal cells), highlighting the critical role of EPS in mercury bioaccumulation. Overall, the designed viscoelastic fluid microfluidic focusing chip integrates focusing and cleaning functions, featuring easy fabrication, simple operation, low sample loss, and relatively high throughput. Under the optimal conditions, the sample throughput is 1195 min-1 and the cell recovery is 90%. Besides, this research offers novel insights into the interaction mechanisms between Hg2+/HgS and EPS in microalgal cells and unveils the specific toxic effects of Hg2+/HgS on M. aeruginosa at the single-cell level, contributing to a deeper understanding of mercury's ecological and toxicological impact in aquatic environments.

The gene expression signature of electrical stimulation in the human brain.

Direct electrical stimulation has been used for decades as a gold standard clinical tool to map cognitive function in neurosurgery patients 1-8 . However, the molecular impact of electrical stimulation in the human brain is unknown. Here, using state-of-the-art transcriptomic and epigenomic sequencing techniques, we define the molecular changes in bulk tissue and at the single-cell level in the human cerebral cortex following direct electrical stimulation of the anterior temporal lobe in patients undergoing neurosurgery. Direct electrical stimulation surprisingly had a robust and consistent impact on the expression of genes related to microglia-specific cytokine activity, an effect that was replicated in mice. Using a newly developed deep learning computational tool, we further demonstrate cell type-specific molecular activation, which underscores the effects of electrical stimulation on gene expression in microglia. Taken together, this work challenges the notion that the immediate impact of electrical stimulation commonly used in the clinic has a primary effect on neuronal gene expression and reveals that microglia robustly respond to electrical stimulation, thus enabling these non-neuronal cells to sculpt and shape the activity of neuronal circuits in the human brain.

Histamine and Th2 cytokines independently and synergistically upregulate MMP12 expression in human M2 macrophages.

Beyond Th2 cells and various immune cells, M2 macrophages have been identified in lesional skin of atopic dermatitis (AD) indicating their involvement in the disease's underlying mechanisms. MMP12, a matrix-degrading enzyme, which is predominantly produced by macrophages, is increased in skin lesions of AD patients. In this study we investigated the expression of MMP12 mRNA in lesional AD skin at single cell level through RNA sequencing (scRNA-seq) and the expression of MMP12 in M2 macrophages from healthy individuals and AD patients in response to Th2 cytokines and histamine using quantitative PCR and ELISA. Additionally, we analyzed macrophages from dupilumab-treated AD patients using the same methods to assess the influence of Th2 cytokines on MMP12 expression ex-vivo. ScRNA-seq identified macrophages as the primary producers of MMP12 in lesional AD skin. In-vitro, both MMP12 mRNA and protein expression were significantly increased in monocytes during differentiation to M2 macrophages in the presence of histamine, of Th2 cytokines or of Th2 cytokines in combination with histamine. In M2 macrophages obtained from dupilumab-treated AD patients, the upregulation of MMP12 expression by IL-4 and IL-13 was attenuated. Our findings unveil a novel mechanism whereby Th2 cytokines and histamine regulate MMP12 expression, potentially impacting skin barrier homeostasis in AD.

MetsDB: a knowledgebase of cancer metastasis at bulk, single-celland spatial levels.

Cancer metastasis, the process by which tumour cells migrate and colonize distant organs from a primary site, is responsible for the majority of cancer-related deaths. Understanding the cellular and molecular mechanisms underlying this complex process is essential for developing effective metastasis prevention and therapy strategies. To this end, we systematically analysed 1786 bulk tissue samples from 13 cancer types, 988463 single cells from 17 cancer types, and 40252 spots from 45 spatial slides across 10 cancer types. The results of these analyses are compiled in the metsDB database, accessible at https://relab.xidian.edu.cn/metsDB/. This database provides insights into alterations in cell constitutions, cell relationships, biological pathways, molecular biomarkers, and drug responses during cancer metastasis at bulk, single-cell, and spatial levels. Users can perform cell or gene searches to obtain multi-view and multi-scale metastasis-related data. This comprehensive resource is invaluable for understanding the metastasis process and for designing molecular therapies.

Cancer new treatment series: Comparison immune changes of HCC by scRNA-Seq following HELC treatment one case study

Immunotherapy has emerged as a novel treatment strategy for many types of cancers, among them, liver cancer. The major advances and achievements in recent years is the use of programmed death-1 (PD-1) blockers for cancer treatment. Since patients’ immune systems are already weak following concurrent surgery plus chemo or radiotherapy, it is necessary to restore and awake their immune cells to maximize the effect for immune therapy. Methods: Liver cancers were treated twice with hapten enhanced local chemotherapy (HELC) like tumor lysates vaccine and following PD-1. Single-cell RNA sequencing (scRNA-seq) was used to analyze the changes of immune responses prior and after treatments. Results: We observed upregulation of cytotoxicity-related genes of CD8 effector T cells and NK cells in untreated tumor; Both Bmem and Naive B cells in untreated tumor showed a significant increase in MHC II signaling pathway-related genes, while MHC I-related genes was upregulated in plasma cells. Significant tumor size shrinkage was observed in both treated and untreated tumors following the HELC+PD-1 therapy. Conclusions: This study provides new biological insights into the abscopal effect at the single-cell level related to the composition of T and B cells in untreated liver cancers before and after major primary tumors treated by HELC. Our data showed that intra-tumor HELC can kill tumor cells and induced immune activity, which is likely vital in modifying tumor associate antigens (TAAs) into neo TAAs. It induces immune response just like vaccine can wake up immune cells and therefore increasing the efficacy of PD1 therapy.

DMF-Bimol: Counting mRNA and Protein Molecules in Single Cells with Digital Microfluidics.

Analyzing single-cell protein and mRNA levels yields invaluable insights into cellular functions and the intricacies of biologically heterogeneous systems. Current joint mRNAs and protein analysis methodologies suffer from relative quantification, low sensitivity, possible background interference, and tedious manual manipulation. Therefore, we propose DMF-Bimol that leverages addressable digital microfluidics to automate digital counting of single-cell mRNA and protein based on proximity ligation assay (PLA) and one-step RT-droplet digital PCR (RT-ddPCR). Through an engineered hydrophilic-hydrophobic interface, DMF-Bimol enables efficient single-cell isolation and lossless protein and nucleic acid processing. The closed droplet reaction system enhances the protein concentration and isolates exogenous contaminants, thereby dramatically improving the efficiency of the PLA reaction. The limit of detection of this approach achieves 3313 protein copies, marking a significant 17-fold enhancement in sensitivity over traditional benchtop PLA. This heightened sensitivity also uncovers a lower correlation between mRNA and protein levels in individual cells (Spearman r = 0.255) than bulk results, reflecting the complex relationship in heterogeneous cells. Using DMF-Bimol, we observed a significant upsurge of CD147 protein in CD138+ myeloma cells but consistent levels of CD147 mRNAs compared with normal leukocytes. This discovery indicates a possible consequence of CD147 oncogenic activation that tends to harness protein translation to bolster tumor cell survival and enhance invasiveness, highlighting the potential of DMF-Bimol in unveiling intricate dynamics in translation processes at the single-cell level.

Single Cell VDJ Sequencing of Normal and Malignant B and T Cells.

Recent developments in single cell sequencing technologies enable researchers to examine heterogeneity of cell types and subclusters even deeper. First assays were only available for transcriptome analysis of up to 10,000 cells, but nowadays up to 60,000 cells or even more can be analyzed. Whereas initially only analysis of mRNA expression was possible, currently single cell methods multiplied, with extension of assays for examination of surface molecule expression, DNA accessibility (ATAC-seq), antigen specificity, and B or T cell receptor repertoires. Also, spatial transcriptomics or CRISPR screenings, augmenting classical CRISPR/Cas9 screens by combining them with transcriptomic data at single cell level, can be evaluated. The composition of B and T cell clones-of malignant cells in lymphomas and leukemia, as well as of infiltrating B or T cell clones in other types of cancer-is especially important in tumor research, as these clones may give valuable hints for tumor development and control. This chapter presents detailed methods for implementation and analysis of single cell B and/or T cell receptor repertoire sequencing on the Chromium system from 10× Genomics and the Rhapsody™ system from BD Bioscience.

Dynamic dysregulation of retrotransposons in neurodegenerative diseases at the single-cell level.

Retrotransposable elements (RTEs) are common mobile genetic elements comprising ∼42% of the human genome. RTEs play critical roles in gene regulation and function, but how they are specifically involved in complex diseases is largely unknown. Here, we investigate the cellular heterogeneity of RTEs using 12 single-cell transcriptome profiles covering three neurodegenerative diseases, Alzheimer's disease (AD), Parkinson's disease, and multiple sclerosis. We identify cell type marker RTEs in neurons, astrocytes, oligodendrocytes, and oligodendrocyte precursor cells that are related to these diseases. The differential expression analysis reveals the landscape of dysregulated RTE expression, especially L1s, in excitatory neurons of multiple neurodegenerative diseases. Machine learning algorithms for predicting cell disease stage using a combination of RTE and gene expression features suggests dynamic regulation of RTEs in AD. Furthermore, we construct a single-cell atlas of retrotransposable elements in neurodegenerative disease (scARE) using these data sets and features. scARE has six feature analysis modules to explore RTE dynamics in a user-defined condition. To our knowledge, scARE represents the first systematic investigation of RTE dynamics at the single-cell level within the context of neurodegenerative diseases.

Single-cell technology for drug discovery and development

The success rate of drug development today remains low, with long development cycles and high costs, especially in areas such as oncology, neurology, immunology, and infectious diseases. Single-cell omics, encompassing transcriptomics, genomics, epigenomics, proteomics, and metabolomics enable the analysis of gene expression profiles and cellular heterogeneity from the perspective of individual cells, offering a high-resolution view of their functional diversity. These technologies can help reveal disease mechanisms, drug target identification and validation, selection of preclinical models and candidate drugs, and clinical decision-making based on disease response to drugs, all at the single-cell level. The development of deep learning technology has provided a powerful tool for research in drug discovery based on single-cell techniques, which has evolved with the advent of large-scale public databases to predict drug responses and targets. In addition, traditional Chinese medicine (TCMs) research has also entered the era of single-cell technology. Single-cell omics technologies offer an alternative way in deciphering the mechanisms of TCMs in disease treatment, revealing drug targets, screening new drugs, and designing combinations of TCMs. This review aims to explore the application of single-cell omics technologies in drug screening and development comprehensively, highlighting how they accelerate the drug development process and facilitate personalized medicine by precisely identifying therapeutic targets, predicting drug responsiveness, deciphering mechanisms of action. It is also concluded that drug development process and therapeutic efficacy of drugs can be improved by combining single-cell omics and artificial intelligence techniques.

Multi-scalar data integration decoding risk genes for chronic kidney disease

BackgroundChronic Kidney Disease (CKD) impacts over 10% of the global population, and recent advancements in high-throughput analytical technologies are uncovering the complex physiology underlying this condition. By integrating Genome-Wide Association Studies (GWAS), RNA sequencing (RNA-seq/RNA array), and single-cell RNA sequencing (scRNA-seq) data, our study aimed to explore the genes and cell types relevant to CKD traits.MethodsGWAS summary data for end-stage renal failure (ESRD) and decreased eGFR (CKD) with or without diabetes and (micro)proteinuria were obtained from the GWAS Catalog and the UK Biobank (UKB) database. Two gene Expression Omnibus (GEO) transcriptome datasets were used to establish glomerular and tubular gene expression differences between CKD patients and healthy individuals. Two scRNA-seq datasets were utilized to obtain the expression of key genes at the single-cell level. The expression profile, differentially expressed genes (DEGs), gene-gene interaction, and pathway enrichment were analysed for these CKD risk genes.ResultsA total of 779 distinct SNPs were identified from GWAS across different CKD traits, involving 681 genes. While many of these risk genes are specific to the CKD traits of renal failure, decreased eGFR, and (micro)proteinuria, they share common pathways, including extracellular matrix (ECM). ECM modeling was enriched in upregulated glomerular and tubular DEGs from CKD kidneys compared to healthy controls, with the expression of relevant collagen genes, such as COL1A2, prevalent in fibroblasts/myofibroblasts. Additionally, immune responses, including T cell differentiation, were dysregulated in CKD kidneys. The late podocyte signature gene THSD7A was enriched in podocytes but downregulated in CKD. We also highlighted that the regulated risk genes of CKD are mainly expressed in tubular cells and immune cells in the kidney.ConclusionsOur integrated analysis highlight the genes, pathways, and relevant cell types associational with the pathogenesis of kidney traits, as a basis for further mechanistic studies to understand the pathogenesis of CKD.

Single cell-inductively coupled plasma-mass spectrometry (SC-ICP-MS) reveals metallic heterogeneity in a macrophage model of infectious diseases.

Single cell-inductively coupled plasma-mass spectrometry (SC-ICP-MS) offers an attractive option for rapidly measuring trace metal heterogeneity at the single cell level. Chemical fixation has been previously applied to mammalian cells prior to sample introduction so that they can be resuspended in a solution suitable for SC-ICP-MS. However, the effect of fixation on the elemental composition of suspended cells is unknown, and robust methodologies are urgently needed so that the community can measure the effects of intracellular pathogens on elemental composition of their host cells. We demonstrate that different fixatives impact measured cell elemental composition. We have compared suspensions treated using different fixatives (methanol 60-100% in H2O and 4% paraformaldehyde in phosphate-buffered saline solution), and the number of distinguishable single cell events, keeping a constant particle number concentration. Significantly more single cell events (n = 3, P ≤ 0.05) were observed for Ca and Mg when cells were fixed in 4% paraformaldehyde than for the methanol-based fixatives, confirming the hypothesis that methanol fixatives cause leaching of these elements from the cells. The impact of fixation on Mn and Zn was less pronounced. Microbial and viral infection of eukaryotic cells can have profound effects on their elemental composition, but chemical fixation is necessary to render infected cells safe before analysis. We have successfully applied our methodology to a macrophage model of tuberculosis demonstrating utility in understanding metal homeostasis during microbial infection of mammalian cells.

Rapid Detection of Single Bacteria Using Filter-Array-Based Hyperspectral Imaging Technology.

Rapid and accurate detection of bacterial pathogens is crucial for preventing widespread public health crises, particularly in the food industry. Traditional methods are often slow and require extensive labeling, which hampers timely responses to potential threats. In response, we introduce a groundbreaking approach using filter-array-based hyperspectral imaging technology, enhanced by a super-resolution demosaicking technique. This innovative technology streamlines the detection process and significantly enhances the resolution of mosaic hyperspectral imaging. By utilizing a snapshot hyperspectral camera with a 15 ms integration time, it facilitates the identification of bacteria at the single-cell level without requiring chemical labels. The integration of a 3D convolutional neural network optimizes the recognition of pathogenic bacteria, achieving an impressive accuracy of 91.7%. Our approach dramatically improves the efficiency and effectiveness of bacterial detection, providing a promising solution for critical applications in public health and the food industry.

Identifying HIF1A and HGF as two hub genes in aortic dissection and function analysis by integrating RNA sequencing and single-cell RNA sequencing data.

Aortic dissection (AD) is a severe aortic disease with high mortality, and its pathogenesis remains elusive. To explore the regulatory mechanisms of AD, we integrated public RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) datasets to screen the hub genes of AD and further analyzed their functions, which may provide references to the diagnosis and treatment of AD. Four AD-related datasets were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis and differential expression analysis were applied to identify overlapping genes in dataset GSE153434. Protein-protein interaction (PPI) network was constructed based on overlapping genes. Five methods (closeness, degree, EPC, MCC, and MNN) were used to pick hub genes. The receiver operating characteristic curve was used to evaluate the diagnostic efficiency of the hub genes in extra datasets GSE98770 and GSE52093. scRNA-seq dataset GSE213740 was used to explore the expression and function of the hub genes at the single-cell level. Quantitative real-time polymerase chain reaction was used to verify the expression of hub genes in beta-aminopropionitrile (BAPN)-induced mouse thoracic aortic aneurysm and dissection (TAAD) model. A total of 71 overlapping genes were screened by intersecting the significant genes in the pink module and the differentially expressed genes. A PPI network with 45 nodes and 74 edges was generated, and five top hub genes (HIF1A, HGF, HMOX1, ITGA5, and ITGB3) were identified. All the hub genes had area under the curve values above 0.55. scRNA-seq data analysis showed that HIF1A was significantly upregulated in macrophages and HGF was significantly upregulated in vascular smooth muscle cells (SMCs) of the ascending aortas in AD patients. HIF1A may transcriptionally regulate multiple downstream target genes involving inflammation (TLR2, ALOX5AP, and MIF), glycolysis (ENO1, LDHA, and GAPDH), tissue remodeling (PLAU), and angiogenesis (SERPIN and VEGFA). HGF may participate in the signaling among SMCs, fibroblasts, and endothelial cells through binding to different receptors (MET, EGFR, IGF1R, and KDR). The mRNA expression of Hif1a, Hgf, and their target genes, including Alox5ap, Serpine1, Tlr2, Plau, Egfr, and Igf1r, was significantly upregulated in aortic tissues of BAPN-treated mice. By integrating RNA-seq and scRNA-seq data, we identified HIF1A and HGF as two hub genes with good diagnostic efficiency for AD. HIF1A in macrophages may promote AD formation by promoting inflammation, glycolysis, tissue remodeling, and angiogenesis, and HGF may mediate signaling among SMCs, fibroblasts, and endothelial cells in the development of AD.

Theoretical framework for the difference of two negative binomial distributions and its application in comparative analysis of sequencing data.

High-throughput sequencing (HTS) technologies have been instrumental in investigating biological questions at the bulk and single-cell levels. Comparative analysis of two HTS data sets often relies on testing the statistical significance for the difference of two negative binomial distributions (DOTNB). Although negative binomial distributions are well studied, the theoretical results for DOTNB remain largely unexplored. Here, we derive basic analytical results for DOTNB and examine its asymptotic properties. As a state-of-the-art application of DOTNB, we introduce DEGage, a computational method for detecting differentially expressed genes (DEGs) in scRNA-seq data. DEGage calculates the mean of the sample-wise differences of gene expression levels as the test statistic and determines significant differential expression by computing the P-value with DOTNB. Extensive validation using simulated and real scRNA-seq data sets demonstrates that DEGage outperforms five popular DEG analysis tools: DEGseq2, DEsingle, edgeR, Monocle3, and scDD. DEGage is robust against high dropout levels and exhibits superior sensitivity when applied to balanced and imbalanced data sets, even with small sample sizes. We utilize DEGage to analyze prostate cancer scRNA-seq data sets and identify marker genes for 17 cell types. Furthermore, we apply DEGage to scRNA-seq data sets of mouse neurons with and without fear memory and reveal eight potential memory-related genes overlooked in previous analyses. The theoretical results and supporting software for DOTNB can be widely applied to comparative analyses of dispersed count data in HTS and broad research questions.

Electroacupuncture Slows Experimental Myopia Progression by Improving Retinal Mitochondrial Function: A Study Based on Single-Cell RNA Sequencing.

This study aimed to establish a complete atlas of retinal cells in lens-induced myopia (LIM) and electroacupuncture (EA) intervention by single-cell RNA sequencing (scRNA-seq) and to explore the potential mechanism of EA in improving experimental myopia progression in guinea pigs. scRNA-seq is used to assess changes in individual cellular gene levels in the retina of LIM- and EA-treated guinea pigs. In addition, the role of EA in slowing myopia progression by improving retinal mitochondrial function is further investigated. scRNA-seq identified ten cell clusters in the retina of LIM and EA guinea pigs and mitochondrial respiratory chain-related genes in Cones and Muller-glia cells-Cytochrome oxidase subunit III (COX3), NADH dehydrogenase subunit 4 (ND4), and NADH dehydrogenase subunit 2 (ND2) are closely related to lens-induced myopia. A comprehensive atlas in the retina of LIM and EA guinea pigs at a single-cell level is established, and the positive role of EA in improving retinal mitochondrial function to slow the experimental myopia progression in guinea pigs is revealed.

Unraveling the metastasis-preventing effect of miR-200c in vitro and in vivo.

Advanced breast cancer, as well as ineffective treatments leading to surviving cancer cells, can result in the dissemination of these malignant cells from the primary tumor to distant organs. Recent research has shown that microRNA 200c (miR-200c) can hamper certain steps of the invasion-metastasis cascade. However, it is still unclear whether miR-200c expression alone is sufficient to prevent breast cancer cells from metastasis formation. Hence, we performed a xenograft mouse experiment with inducible miR-200c expression in MDA-MB 231 cells. The ex vivo analysis of metastatic sites in a multitude of organs, including lung, liver, brain, and spleen, revealed a dramatically reduced metastatic burden in mice with miR-200c-expressing tumors. A fundamental prerequisite for metastasis formation is the motility of cancer cells and, therefore, their migration. Consequently, we analyzed the effect of miR-200c on collective- and single-cell migration in vitro, utilizing MDA-MB 231 and MCF7 cell systems with genetically modified miR-200c expression. Analysis of collective-cell migration revealed confluence-dependent motility of cells with altered miR-200c expression. Additionally, scratch assays showed an enhanced predisposition of miR-200c-negative cells to leave cell clusters. The in-between stage of collective- and single-cell migration was validated using transwell assays, which showed reduced migration of miR-200c-positive cells. Finally, to measure migration at the single-cell level, a novel assay on dumbbell-shaped micropatterns was performed, which revealed that miR-200c critically determines confined cell motility. All of these results demonstrate that sole expression of miR-200c impedes metastasis formation in vivo and migration in vitro and highlights miR-200c as a metastasis suppressor in breast cancer.

Peripheral mononuclear cells and systemic lupus erythematosus association: Integrated study of single-cell sequencing and mendelian randomization analysis.

Systemic Lupus Erythematosus (SLE) is a complex autoimmune disease predominantly affecting women. Despite advances in treatment, recent developments in single-cell RNA sequencing (scRNA-seq) and Mendelian randomization (MR) continue to facilitate the need for precision medicine. Data obtained from the GSE135779 dataset underwent quality control, normalization, and dimensionality reduction using Seurat and MonacoImmuneData. Marker genes identified subgroups for analysis with CellChat and ClusterProfilerR. MR analysis of these genes' eQTLs was performed to establish causal relationships with SLE using IEU Open GWAS project data. Single-cell analysis revealed distinct cellular subtypes and highlighted increased monocyte levels in patients with SLE. MR analysis revealed 12 genes, particularly interferon induced protein with tetratricopeptide repeats 3 (IFIT3), causally related to SLE. Gene ontology and the Kyoto encyclopedia of genes and genomes analyses identified pathways significant to SLE pathogenesis. Visualization of these genes at the single-cell level revealed their role in disease progression. Cell communication differences between IFIT3-positive and -negative groups were also observed. This study demonstrates the potential of scRNA-seq and MR in identifying critical factors in SLE pathogenesis, thereby supporting the need for targeted therapies. Identifying IFIT3, among other genes, as central to SLE progression opens new avenues for precision medicine approaches in SLE management.

Assessment of NK cytotoxicity and interactions with porcine endothelial cells by live-cell imaging in 2D static and 3D microfluidic systems

Natural Killer (NK) cells are pivotal in immune responses to viral infections, malignancies, autoimmune diseases, and transplantation. Assessment of NK cell adhesion, migration, and cytotoxicity is fundamental for in vitro studies. We propose a novel live-cell tracking method that addresses these three major aspects of NK cell function using human NK cells and primary porcine aortic endothelial cells (PAECs) in two-dimensional (2D) static assays and an in-house cylindrical 3D microfluidic system. The results showed a significant increase of NK cytotoxicity against pTNF-activated PAECs, with apoptotic cell death observed in the majority of dead cells, while no difference was observed in the conventional Delfia assay. Computed analysis of NK cell trajectories revealed distinct migratory behaviors, including trajectory length, diameter, average speed, and arrest coefficient. In 3D microfluidic experiments, NK cell attachment to pTNF-activated PAECs substantially increased, accompanied by more dead PAECs compared to control conditions. NK cell trajectories showed versatile migration in various directions and interactions with PAECs. This study uniquely demonstrates NK attachment and killing in a 3D system that mimics blood vessel conditions. Our microscope method offers sensitive single-cell level results, addressing diverse aspects of NK functions. It is adaptable for studying other immune and target cells, providing insights into various biological questions.

Root-specific theanine metabolism and regulation at the single-cell level in tea plants (Camellia sinensis)

Root-synthesized secondary metabolites are critical quality-conferring compounds of foods, plant-derived medicines, and beverages. However, information at a single-cell level on root-specific secondary metabolism remains largely unexplored. L-Theanine, an important quality component of tea, is primarily synthesized in roots, from which it is then transported to new shoots of tea plant. In this study, we present a single-cell RNA sequencing (scRNA-seq)-derived map for the tea plant root, which enabled cell-type-specific analysis of glutamate and ethylamine (two precursors of theanine biosynthesis) metabolism, and theanine biosynthesis, storage, and transport. Our findings support a model in which the theanine biosynthesis pathway occurs via multicellular compartmentation and does not require high co-expression levels of transcription factors and their target genes within the same cell cluster. This study provides novel insights into theanine metabolism and regulation, at the single-cell level, and offers an example for studying root-specific secondary metabolism in other plant systems.