Methods for Single-Cell Isolation and Preparation

Transcriptomics, single-cell sequencing and spatial sequencing-based studies of cerebral ischemia

With high disability and mortality rate as well as highly complex pathogenesis, cerebral ischemia is highly morbid, prone to recurrence. To comprehensively understand the pathophysiological process of cerebral ischemia and to find new therapeutic strategies, a new approach to cerebral ischemia transcriptomics has emerged in recent years. By integrating data from multiple levels of transcriptomics, such as transcriptomics, single-cell transcriptomics, and spatial transcriptomics, this new approach can provide powerful help in revealing the molecular mechanisms of cerebral ischemia occurrence and development. Key findings highlight the critical roles of inflammation, blood-brain barrier dysfunction, and mitochondrial dysregulation in cerebral ischemia, offering potential biomarkers and therapeutic targets for early diagnosis and personalized treatment. A review of the research progress of cerebral ischemic injury mechanism under the analysis of the comprehensive transcriptomics research method was presented in this article, aiming to study the potential mechanism to provide new, innovative therapeutic strategies for this disease.

Lab-in-a-Fiber detection and capture of cells

A lab-in-a-fiber component was fabricated using an optical fiber and a fiber capillary. It was used in a test suspension of fluorescently labeled and unlabeled cells and enabled detection of the labeled cells. Subsequently the labeled cells were selectively collected via suction into the capillary. A novel sampling technique reduced photobleaching of the labeled cells, extending the measurement time. The collected cells remained viable for downstream analysis. This platform's low fabrication cost, simplicity, compatibility with standard laboratory equipment, and capacity for fully automated cell capture highlights its potential for future applications in minimally invasive sample collection and point-of-care diagnostics. We demonstrate this LiF device to showcase the capability of optical fiber technology in creating low-cost, low-complexity cancer diagnostic devices. Furthermore, the LiF device holds promise for in vivo diagnostics, facilitating cell isolation and analysis.

Proteomic Insight Into Alzheimer's Disease Pathogenesis Pathways

Alzheimer's disease (AD) is a leading cause of dementia, but the pathogenesis mechanism is still elusive. Advances in proteomics have uncovered key molecular mechanisms underlying AD, revealing a complex network of dysregulated pathways, including amyloid metabolism, tau pathology, apolipoprotein E (APOE), protein degradation, neuroinflammation, RNA splicing, metabolic dysregulation, and cognitive resilience. This review examines recent proteomic findings from AD brain tissues and biological fluids, highlighting potential biomarkers and therapeutic targets. By examining the proteomic landscape of them, we aim to deepen our understanding of the disease and support developing precision medicine strategies for more effective interventions.

Parkin modulates the hepatocellular carcinoma microenvironment by regulating PD-1/PD-L1 signalling

INTRODUCTION

Parkin-mediated mitophagy is essential for clearing damaged mitochondria, and it inhibits tumour development. The role of mitophagy in modulating tumour immunity is becoming clearer, but the underlying mechanism is still poorly understood.

OBJECTIVE

This study was designed to examine the role of Parkin in the immune microenvironment of liver tumours induced by carbon tetrachloride (CCl4).

METHODS

Single-cell RNA sequencing analysis, Western blot, immunofluorescence and co-immunoprecipitation were used to verify the mechanism of Parkin affecting the tumour microenvironment by altering the expression of PD-1.

RESULTS

Our data revealed that Park2-/- mice showed severe liver damage and increased malignancy. Single-cell RNA sequencing analysis of T lymphocytes in liver tumours showed that the number of cytotoxic CD8+ T cells (Gzmb/Ifng/Fasl) was significantly decreased and the number of exhausted CD8+ T cells (Pdcd1/Lag3/Tigit/Havcr2/Ctla4) was significantly increased in Park2-/- mice, indicating the immune suppressive microenvironment. Single-cell RNA sequencing analysis of myeloid-derived cells also displayed the increase of M2-like macrophages in Park2-/- mice. Through quantitative proteomic analysis, it was found that the differential protein expression between the two groups mainly localized in the plasma membrane and extracellular, including PD-1, MHC-Ⅰ molecules etc., and was mainly associated with PD-1 and antigen presentation pathways. It could impair the antitumour immune response with Parkin deficiency. Parkin deficiency leads to the decrease of hepatic mitophagy levels and the formation of an immune suppressive microenvironment, which promotes the tumourigenesis of liver cancer.

CONCLUSION

As an E3 ubiquitin ligase, Parkin induces the ubiquitination and degradation of PD-1 in liver cancer and could influence antitumour immunity through the PD-1/PD-L1 signalling pathway. Thus, remodeling the tumour microenvironment through the reintroduction of Parkin or enhancement of mitophagy could activate the anti-tumour immune response and improve the immunotherapy efficacy, which may be a promising strategy for the treatment of HCC.

Single-Cell Transcriptomic Analysis of Normal and Malignant B Cells

In the past decade, single-cell (sc) transcriptomics has overcome the limitations of bulk analysis by measuring gene expression in individual cells, not just a population average. This can identify diverse cell types and states within a sample with high resolution, even without prior purification. Various technologies exist, each with its own capture, barcoding, and library preparation methods. This chapter focuses on the analysis of normal and malignant mature B cells using the 10× Genomics 5' sc-gene expression in parallel with B cell immune repertoire profiling. By integrating the gene expression data from similar cells, the complete transcriptome for each population can be reconstructed, while the identification of the expressed immunoglobulin genes allows investigating clonotype evolution and the detection of tumor clones that share the same clonally rearranged B cell receptor sequence. Researchers are guided through both the experimental protocols and data analysis with a comprehensive, step-by-step walkthrough of how to use some of the more popular single-cell software tools.

Advances and applications in single-cell and spatial genomics

The applications of single-cell and spatial technologies in recent times have revolutionized the present understanding of cellular states and the cellular heterogeneity inherent in complex biological systems. These advancements offer unprecedented resolution in the examination of the functional genomics of individual cells and their spatial context within tissues. In this review, we have comprehensively discussed the historical development and recent progress in the field of single-cell and spatial genomics. We have reviewed the breakthroughs in single-cell multi-omics technologies, spatial genomics methods, and the computational strategies employed toward the analyses of single-cell atlas data. Furthermore, we have highlighted the advances made in constructing cellular atlases and their clinical applications, particularly in the context of disease. Finally, we have discussed the emerging trends, challenges, and opportunities in this rapidly evolving field.

Single-cell sequencing: Current applications in various tuberculosis specimen types

Tuberculosis (TB) is a chronic disease caused by Mycobacterium tuberculosis (M.tb) and responsible for millions of deaths worldwide each year. It has a complex pathogenesis that primarily affects the lungs but can also impact systemic organs. In recent years, single-cell sequencing technology has been utilized to characterize the composition and proportion of immune cell subpopulations associated with the pathogenesis of TB disease since it has a high resolution that surpasses conventional techniques. This paper reviews the current use of single-cell sequencing technologies in TB research and their application in analysing specimens from various sources of TB, primarily peripheral blood and lung specimens. The focus is on how these technologies can reveal dynamic changes in immune cell subpopulations, genes and proteins during disease progression after M.tb infection. Based on the current findings, single-cell sequencing has significant potential clinical value in the field of TB research. Next, we will focus on the real-world applications of the potential targets identified through single-cell sequencing for diagnostics, therapeutics and the development of effective vaccines.

Single-cell spatial transcriptomics in cardiovascular development, disease, and medicine

Cardiovascular diseases (CVDs) impose a significant burden worldwide. Despite the elucidation of the etiology and underlying molecular mechanisms of CVDs by numerous studies and recent discovery of effective drugs, their morbidity, disability, and mortality are still high. Therefore, precise risk stratification and effective targeted therapies for CVDs are warranted. Recent improvements in single-cell RNA sequencing and spatial transcriptomics have improved our understanding of the mechanisms and cells involved in cardiovascular phylogeny and CVDs. Single-cell RNA sequencing can facilitate the study of the human heart at remarkably high resolution and cellular and molecular heterogeneity. However, this technique does not provide spatial information, which is essential for understanding homeostasis and disease. Spatial transcriptomics can elucidate intracellular interactions, transcription factor distribution, cell spatial localization, and molecular profiles of mRNA and identify cell populations causing the disease and their underlying mechanisms, including cell crosstalk. Herein, we introduce the main methods of RNA-seq and spatial transcriptomics analysis and highlight the latest advances in cardiovascular research. We conclude that single-cell RNA sequencing interprets disease progression in multiple dimensions, levels, perspectives, and dynamics by combining spatial and temporal characterization of the clinical phenome with multidisciplinary techniques such as spatial transcriptomics. This aligns with the dynamic evolution of CVDs (e.g., "angina-myocardial infarction-heart failure" in coronary artery disease). The study of pathways for disease onset and mechanisms (e.g., age, sex, comorbidities) in different patient subgroups should improve disease diagnosis and risk stratification. This can facilitate precise individualized treatment of CVDs.

Comprehensive review on single-cell RNA sequencing: A new frontier in Alzheimer's disease research

Alzheimer's disease (AD) is a multifaceted neurodegenerative condition marked by gradual cognitive deterioration and the loss of neurons. While conventional bulk RNA sequencing techniques have shed light on AD pathology, they frequently obscure the cellular diversity within brain tissues. The advent of single-cell RNA sequencing (scRNA-seq) has transformed our capability to analyze the cellular composition of AD, allowing for the detection of unique cell populations, rare cell types, and gene expression alterations at an individual cell level. This review examines the use of scRNA-seq in AD research, focusing on its contributions to understanding cellular diversity, disease progression, and potential therapeutic targets. We discuss key technological innovations, data analysis techniques, and challenges associated with scRNA-seq in studying AD. Furthermore, we highlight recent studies that have utilized scRNA-seq to identify novel biomarkers, uncover disease-associated pathways, and elucidate the role of non-neuronal cells, such as microglia and astrocytes, in AD pathogenesis. By providing a comprehensive overview of advancements in scRNA-seq for unraveling cellular heterogeneity in AD, this review highlights the transformative impact of scRNA-seq on our comprehension of disease mechanisms and the creation of targeted treatments.

Applications of single-cell multi-omics in liver cancer

Primary liver cancer, more specifically hepatocellular carcinoma (HCC), remains a significant global health problem associated with increasing incidence and mortality. Clinical, biological, and molecular heterogeneity are well-known hallmarks of cancer and HCC is considered one of the most heterogeneous tumour types, displaying substantial inter-patient, intertumoural and intratumoural variability. This heterogeneity plays a pivotal role in hepatocarcinogenesis, metastasis, relapse and drug response or resistance. Unimodal single-cell sequencing techniques have already revolutionised our understanding of the different layers of molecular hierarchy in the tumour microenvironment of HCC. By highlighting the cellular heterogeneity and the intricate interactions among cancer, immune and stromal cells before and during treatment, these techniques have contributed to a deeper comprehension of tumour clonality, hematogenous spreading and the mechanisms of action of immune checkpoint inhibitors. However, major questions remain to be elucidated, with the identification of biomarkers predicting response or resistance to immunotherapy-based regimens representing an important unmet clinical need. Although the application of single-cell multi-omics in liver cancer research has been limited thus far, a revolution of individualised care for patients with HCC will only be possible by integrating various unimodal methods into multi-omics methodologies at the single-cell resolution. In this review, we will highlight the different established single-cell sequencing techniques and explore their biological and clinical impact on liver cancer research, while casting a glance at the future role of multi-omics in this dynamic and rapidly evolving field.

Secondary metabolites of mulberry leaves exert anti-lung cancer activity through regulating the PD-L1/PD-1 signaling pathway

Lung cancer ranks the top of malignancies that cause cancer-related deaths worldwide. The leaves of Morus alba L are traditional Chinese medicine widely applied in respiratory diseases. Our previous work has demonstrated the anti-lung cancer effect of secondary metabolites of mulberry leaf, but their mechanism of action has still not fully elucidated. We synthesized Moracin N (MAN)-Probe conjugated with alkyne to label lung cancer cells and identified protein targets by chemical proteomic analysis. MAN and its probe exerted similar growth-inhibitory effect on human lung cancer cells. Chemical proteomic results showed that MAN targeted the programmed death ligand 1 (PD-L1) checkpoint pathway and T cell receptor (TCR) signaling pathway, indicating its immune-regulatory function. Cell-free surface plasmon resonance (SPR) results showed the direct interaction of MAN with PD-L1 protein. Molecular docking analysis demonstrated that MAN bound to E158 residue of PD-L1 protein. MAN downregulated the expression levels of PD-L1 in a time- and dose-dependent manner and disrupted the PD-L1/programmed death 1 (PD-1) binding, including other secondary metabolites of mulberry leaves Guangsangon E (GSE) and Chalcomoracin (CMR). Human peripheral blood mononuclear cells (PBMCs) co-cultured with MAN-treated A549 cells, resulting in the increase of CD8+ GZMB+ T cells and the decrease of CD8+ PD-1+ T cells. It suggested that MAN exerts anti-cancer effect through blocking the PD-L1/PD-1 signaling. In vivo, MAN combined with anti-PD-1 antibody significantly inhibited lung cancer development and metastasis, indicating their synergistic effect. Taken together, secondary metabolites of mulberry leaves target the PD-L1/PD-1 signaling, enhance T cell-mediated immunity and inhibit the tumorigenesis of lung cancer. Their modulatory effect on tumor microenvironment makes them able to enhance the therapeutic efficacy of immune checkpoint inhibitors in lung cancer.

Digital PCR for Single-Cell Analysis

Single-cell analysis provides an overwhelming strategy for revealing cellular heterogeneity and new perspectives for understanding the biological function and disease mechanism. Moreover, it promotes the basic and clinical research in many fields at a single-cell resolution. A digital polymerase chain reaction (dPCR) is an absolute quantitative analysis technology with high sensitivity and precision for DNA/RNA or protein. With the development of microfluidic technology, digital PCR has been used to achieve absolute quantification of single-cell gene expression and single-cell proteins. For single-cell specific-gene or -protein detection, digital PCR has shown great advantages. So, this review will introduce the significance and process of single-cell analysis, including single-cell isolation, single-cell lysis, and single-cell detection methods, mainly focusing on the microfluidic single-cell digital PCR technology and its biological application at a single-cell level. The challenges and opportunities for the development of single-cell digital PCR are also discussed.

Emerging applications of single-cell profiling in precision medicine of atherosclerosis

Atherosclerosis is a chronic, progressive, inflammatory disease that occurs in the arterial wall. Despite recent advancements in treatment aimed at improving efficacy and prolonging survival, atherosclerosis remains largely incurable. In this review, we discuss emerging single-cell sequencing techniques and their novel insights into atherosclerosis. We provide examples of single-cell profiling studies that reveal phenotypic characteristics of atherosclerosis plaques, blood, liver, and the intestinal tract. Additionally, we highlight the potential clinical applications of single-cell analysis and propose that combining this approach with other techniques can facilitate early diagnosis and treatment, leading to more accurate medical interventions.

Mass Spectrometry-Based Proteogenomics: New Therapeutic Opportunities for Precision Medicine

Proteogenomics refers to the integration of comprehensive genomic, transcriptomic, and proteomic measurements from the same samples with the goal of fully understanding the regulatory processes converting genotypes to phenotypes, often with an emphasis on gaining a deeper understanding of disease processes. Although specific genetic mutations have long been known to drive the development of multiple cancers, gene mutations alone do not always predict prognosis or response to targeted therapy. The benefit of proteogenomics research is that information obtained from proteins and their corresponding pathways provides insight into therapeutic targets that can complement genomic information by providing an additional dimension regarding the underlying mechanisms and pathophysiology of tumors. This review describes the novel insights into tumor biology and drug resistance derived from proteogenomic analysis while highlighting the clinical potential of proteogenomic observations and advances in technique and analysis tools.

Omics and Multi-Omics in IBD: No Integration, No Breakthroughs

The recent advent of sophisticated technologies like sequencing and mass spectroscopy platforms combined with artificial intelligence-powered analytic tools has initiated a new era of "big data" research in various complex diseases of still-undetermined cause and mechanisms. The investigation of these diseases was, until recently, limited to traditional in vitro and in vivo biological experimentation, but a clear switch to in silico methodologies is now under way. This review tries to provide a comprehensive assessment of state-of-the-art knowledge on omes, omics and multi-omics in inflammatory bowel disease (IBD). The notion and importance of omes, omics and multi-omics in both health and complex diseases like IBD is introduced, followed by a discussion of the various omics believed to be relevant to IBD pathogenesis, and how multi-omics "big data" can generate new insights translatable into useful clinical tools in IBD such as biomarker identification, prediction of remission and relapse, response to therapy, and precision medicine. The pitfalls and limitations of current IBD multi-omics studies are critically analyzed, revealing that, regardless of the types of omes being analyzed, the majority of current reports are still based on simple associations of descriptive retrospective data from cross-sectional patient cohorts rather than more powerful longitudinally collected prospective datasets. Given this limitation, some suggestions are provided on how IBD multi-omics data may be optimized for greater clinical and therapeutic benefit. The review concludes by forecasting the upcoming incorporation of multi-omics analyses in the routine management of IBD.

A Roadmap for the Human Gut Cell Atlas

The number of studies investigating the human gastrointestinal tract using various single-cell profiling methods has increased substantially in the past few years. Although this increase provides a unique opportunity for the generation of the first comprehensive Human Gut Cell Atlas (HGCA), there remains a range of major challenges ahead. Above all, the ultimate success will largely depend on a structured and coordinated approach that aligns global efforts undertaken by a large number of research groups. In this Roadmap, we discuss a comprehensive forward-thinking direction for the generation of the HGCA on behalf of the Gut Biological Network of the Human Cell Atlas. Based on the consensus opinion of experts from across the globe, we outline the main requirements for the first complete HGCA by summarizing existing data sets and highlighting anatomical regions and/or tissues with limited coverage. We provide recommendations for future studies and discuss key methodologies and the importance of integrating the healthy gut atlas with related diseases and gut organoids. Importantly, we critically overview the computational tools available and provide recommendations to overcome key challenges.

Single cell quantification of microRNA from small numbers of non-invasively sampled primary human cells

Expression levels of microRNAs (miRNAs) in single cells are low and conventional miRNA detection methods require amplification that can be complex, time-consuming, costly and may bias results. Single cell microfluidic platforms have been developed; however, current approaches are unable to absolutely quantify single miRNA molecules expressed in single cells. Herein, we present an amplification-free sandwich hybridisation assay to detect single miRNA molecules in single cells using a microfluidic platform that optically traps and lyses individual cells. Absolute quantification of miR-21 and miR-34a molecules was achieved at a single cell level in human cell lines and validated using real-time qPCR. The sensitivity of the assay was demonstrated by quantifying single miRNA molecules in nasal epithelial cells and CD3⁺ T-cells, as well as nasal fluid collected non-invasively from healthy individuals. This platform requires ~50 cells or ~30 µL biofluid and can be extended for other miRNA targets therefore it could monitor miRNA levels in disease progression or clinical studies.

Application of Single-Cell RNA Sequencing in Ovarian Development

The ovary is a female reproductive organ that plays a key role in fertility and the maintenance of endocrine homeostasis, which is of great importance to women's health. It is characterized by a high heterogeneity, with different cellular subpopulations primarily containing oocytes, granulosa cells, stromal cells, endothelial cells, vascular smooth muscle cells, and diverse immune cell types. Each has unique and important functions. From the fetal period to old age, the ovary experiences continuous structural and functional changes, with the gene expression of each cell type undergoing dramatic changes. In addition, ovarian development strongly relies on the communication between germ and somatic cells. Compared to traditional bulk RNA sequencing techniques, the single-cell RNA sequencing (scRNA-seq) approach has substantial advantages in analyzing individual cells within an ever-changing and complicated tissue, classifying them into cell types, characterizing single cells, delineating the cellular developmental trajectory, and studying cell-to-cell interactions. In this review, we present single-cell transcriptome mapping of the ovary, summarize the characteristics of the important constituent cells of the ovary and the critical cellular developmental processes, and describe key signaling pathways for cell-to-cell communication in the ovary, as revealed by scRNA-seq. This review will undoubtedly improve our understanding of the characteristics of ovarian cells and development, thus enabling the identification of novel therapeutic targets for ovarian-related diseases.

Single-Cell Sequencing in Rheumatic Diseases: New Insights from the Perspective of the Cell Type

Rheumatic diseases are a group of highly heterogeneous autoimmune and inflammatory disorders involving multiple systems. Dysfunction of immune and non-immune cells participates in the complex pathogenesis of rheumatic diseases. Therefore, studies on the abnormal activation of cell subtypes provided a specific basis for understanding the pathogenesis of rheumatic diseases, which promoted the accuracy of disease diagnosis and the effectiveness of various treatments. However, there was still a far way to achieve individualized precision medicine as the result of heterogeneity among cell subtypes. To obtain the biological information of cell subtypes, single-cell sequencing, a cutting-edge technology, is used for analyzing their genomes, transcriptomes, epigenetics, and proteomics. Novel results identified multiple cell subtypes in tissues of patients with rheumatic diseases by single-cell sequencing. Consequently, we provide an overview of recent applications of single-cell sequencing in rheumatic disease and cross-tissue to understand the cell subtypes and functions.

Single-Cell Sequencing and Its Applications in Liver Cancer

As one of the most lethal cancers, primary liver cancer (PLC) has high tumor heterogeneity, including the heterogeneity between cancer cells. Traditional methods which have been used to identify tumor heterogeneity for a long time are based on large mixed cell samples, and the research results usually show average level of the cell population, ignoring the heterogeneity between cancer cells. In recent years, single-cell sequencing has been increasingly applied to the studies of PLCs. It can detect the heterogeneity between cancer cells, distinguish each cell subgroup in the tumor microenvironment (TME), and also reveal the clonal characteristics of cancer cells, contributing to understand the evolution of tumor. Here, we introduce the process of single-cell sequencing, review the applications of single-cell sequencing in the heterogeneity of cancer cells, TMEs, oncogenesis, and metastatic mechanisms of liver cancer, and discuss some of the current challenges in the field.

Microfluidics applications for high-throughput single cell sequencing

The inherent heterogeneity of individual cells in cell populations plays significant roles in disease development and progression, which is critical for disease diagnosis and treatment. Substantial evidences show that the majority of traditional gene profiling methods mask the difference of individual cells. Single cell sequencing can provide data to characterize the inherent heterogeneity of individual cells, and reveal complex and rare cell populations. Different microfluidic technologies have emerged for single cell researches and become the frontiers and hot topics over the past decade. In this review article, we introduce the processes of single cell sequencing, and review the principles of microfluidics for single cell analysis. Also, we discuss the common high-throughput single cell sequencing technologies along with their advantages and disadvantages. Lastly, microfluidics applications in single cell sequencing technology for the diagnosis of cancers and immune system diseases are briefly illustrated.