Progress and applications of single-cell sequencing techniques

Systems biology of Haemonchus contortus - Advancing biotechnology for parasitic nematode control

Parasitic nematodes represent a substantial global burden, impacting animal health, agriculture and economies worldwide. Of these worms, Haemonchus contortus - a blood-feeding nematode of ruminants - is a major pathogen and a model for molecular and applied parasitology research. This review synthesises some key advances in understanding the molecular biology, genetic diversity and host-parasite interactions of H. contortus, highlighting its value for comparative studies with the free-living nematode Caenorhabditis elegans. Key themes include recent developments in genomic, transcriptomic and proteomic technologies and resources, which are illuminating critical molecular pathways, including the ubiquitination pathway, protease/protease inhibitor systems and the secretome of H. contortus. Some of these insights are providing a foundation for identifying essential genes and exploring their potential as targets for novel anthelmintics or vaccines, particularly in the face of widespread anthelmintic resistance. Advanced bioinformatic tools, such as machine learning (ML) algorithms and artificial intelligence (AI)-driven protein structure prediction, are enhancing annotation capabilities, facilitating and accelerating analyses of gene functions, and biological pathways and processes. This review also discusses the integration of these tools with cutting-edge single-cell sequencing and spatial transcriptomics to dissect host-parasite interactions at the cellular level. The discussion emphasises the importance of curated databases, improved culture systems and functional genomics platforms to translate molecular discoveries into practical outcomes, such as novel interventions. New research findings and resources not only advance research on H. contortus and related nematodes but may also pave the way for innovative solutions to the global challenges with anthelmintic resistance.

Inflammatory Cell Interactions in the Rotator Cuff Microenvironment: Insights From Single-Cell Sequencing

Rotator cuff injuries are a common cause of shoulder pain and dysfunction, with chronic inflammation complicating recovery. Recent advances in single-cell RNA sequencing (scRNA-seq) have provided new insights into the immune cell interactions within the rotator cuff microenvironment during injury and healing. This review focuses on the application of scRNA-seq to explore the roles of immune and nonimmune cells, including macrophages, T-cells, fibroblasts, and myofibroblasts, in driving inflammation, tissue repair, and fibrosis. We discuss how immune cell crosstalk and interactions with the extracellular matrix influence the progression of healing or pathology. Single-cell analyses have identified distinct molecular signatures associated with chronic inflammation, which may contribute to persistent tissue damage. Additionally, we highlight the therapeutic potential of targeting inflammation in rotator cuff repair, emphasizing personalized medicine approaches. Overall, the integration of scRNA-seq in studying rotator cuff injuries enhances our understanding of the cellular mechanisms involved and offers new perspectives for developing targeted treatments in regenerative medicine.

Transcriptomics in Human Septic Shock: State of the Art

Background: Septic shock is a complex syndrome characterized by signs of intense systemic inflammation and a profound dysregulation of the immune response. Large-scale gene expression analysis is a valuable tool in this scenario because sepsis affects various cellular components and signaling pathways. Results: In this article, we provide an overview of the transcriptomic studies that investigated human sepsis from 2007 to 2024, highlighting their major contributions. Conclusions: The field, however, still faces substantial limitations and several challenges. To advance further, we believe that standardization of sample collection and data analysis, preservation of cell and tissue architecture, and integration with other omics techniques are crucial for a broader understanding of this lethal disease.

Single-cell Technology in Stem Cell Research

Single-cell technology (SCT), which enables the examination of the fundamental units comprising biological organs, tissues, and cells, has emerged as a powerful tool, particularly in the field of biology, with a profound impact on stem cell research. This innovative technology opens new pathways for acquiring cell-specific data and gaining insights into the molecular pathways governing organ function and biology. SCT is not only frequently used to explore rare and diverse cell types, including stem cells, but it also unveils the intricacies of cellular diversity and dynamics. This perspective, crucial for advancing stem cell research, facilitates non-invasive analyses of molecular dynamics and cellular functions over time. Despite numerous investigations into potential stem cell therapies for genetic disorders, degenerative conditions, and severe injuries, the number of approved stem cell-based treatments remains limited. This limitation is attributed to the various heterogeneities present among stem cell sources, hindering their widespread clinical utilization. Furthermore, stem cell research is intimately connected with cutting-edge technologies, such as microfluidic organoids, CRISPR technology, and cell/tissue engineering. Each strategy developed to overcome the constraints of stem cell research has the potential to significantly impact advanced stem cell therapies. Drawing on the advantages and progress achieved through SCT-based approaches, this study aims to provide an overview of the advancements and concepts associated with the utilization of SCT in stem cell research and its related fields.

Single-cell omics: experimental workflow, data analyses and applications

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

Advances in single-cell sequencing technology in microbiome research

With the rapid development of histological techniques and the widespread application of single-cell sequencing in eukaryotes, researchers desire to explore individual microbial genotypes and functional expression, which deepens our understanding of microorganisms. In this review, the history of the development of microbial detection technologies was revealed and the difficulties in the application of single-cell sequencing in microorganisms were dissected as well. Moreover, the characteristics of the currently emerging microbial single-cell sequencing (Microbe-seq) technology were summarized, and the prospects of the application of Microbe-seq in microorganisms were distilled based on the current development status. Despite its mature development, the Microbe-seq technology was still in the optimization stage. A retrospective study was conducted, aiming to promote the widespread application of single-cell sequencing in microorganisms and facilitate further improvement in the technology.

Multi-Omics Research Strategies for Psoriasis and Atopic Dermatitis

Psoriasis and atopic dermatitis (AD) are multifactorial and heterogeneous inflammatory skin diseases, while years of research have yielded no cure, and the costs associated with caring for people suffering from psoriasis and AD are a huge burden on society. Integrating several omics datasets will enable coordinate-based simultaneous analysis of hundreds of genes, RNAs, chromatins, proteins, and metabolites in particular cells, revealing networks of links between various molecular levels. In this review, we discuss the latest developments in the fields of genomes, transcriptomics, proteomics, and metabolomics and discuss how they were used to identify biomarkers and understand the main pathogenic mechanisms underlying these diseases. Finally, we outline strategies for achieving multi-omics integration and how integrative omics and systems biology can advance our knowledge of, and ability to treat, psoriasis and AD.

Comprehensive analysis to identify the influences of SARS-CoV-2 infections to inflammatory bowel disease

BACKGROUND

Coronavirus disease 2019 (COVID-19) and inflammatory bowel disease (IBD) are both caused by a disordered immune response and have direct and profound impacts on health care services. In this study, we implemented transcriptomic and single-cell analysis to detect common molecular and cellular intersections between COVID-19 and IBD that help understand the linkage of COVID-19 to the IBD patients.

METHODS

Four RNA-sequencing datasets (GSE147507, GSE126124, GSE9686 and GSE36807) from Gene Expression Omnibus (GEO) database are extracted to detect mutual differentially expressed genes (DEGs) for IBD patients with the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to find shared pathways, candidate drugs, hub genes and regulatory networks. Two single-cell RNA sequencing (scRNA-eq) datasets (GSE150728, PRJCA003980) are used to analyze the immune characteristics of hub genes and the proportion of immune cell types, so as to find common immune responses between COVID-19 and IBD.

RESULTS

A total of 121 common DEGs were identified among four RNA-seq datasets, and were all involved in the functional enrichment analysis related to inflammation and immune response. Transcription factors-DEGs interactions, miRNAs-DEGs coregulatory networks, and protein-drug interactions were identified based on these datasets. Protein-protein interactions (PPIs) was built and 59 hub genes were identified. Moreover, scRNA-seq of peripheral blood monocyte cells (PBMCs) from COVID-19 patients revealed a significant increase in the proportion of CD14+ monocytes, in which 38 of 59 hub genes were highly enriched. These genes, encoding inflammatory cytokines, were also highly expressed in inflammatory macrophages (IMacrophage) of intestinal tissues of IBD patients.

CONCLUSIONS

We conclude that COVID-19 may promote the progression of IBD through cytokine storms. The candidate drugs and DEGs-regulated networks may suggest effective therapeutic methods for both COVID-19 and IBD.

Single cell RNA sequencing research in maternal fetal interface

The maternal-fetal interface is an essential environment for embryonic growth and development, and a successful pregnancy depends on the dynamic balance of the microenvironment at the maternal-fetal interface. Single-cell sequencing, which unlike bulk sequencing that provides averaged data, is a robust method for interpreting the cellular and molecular landscape at single-cell resolution. With the support of single-cell sequencing, the issue of maternal-fetal interface heterogeneity during pregnancy has been more deeply elaborated and understood, which is important for a deeper understanding of physiological and pathological pregnancy. In this paper, we analyze the recent studies of single-cell transcriptomics in the maternal-fetal interface, and provide new directions for understanding and treating various pathological pregnancies.

Characterization of diverse populations of sinoatrial node cells and their proliferation potential at single nucleus resolution

Background

Each heartbeat is initiated in the sinoatrial node (SAN), and although a recent study (GSE130710) using single nucleus RNA-seq had discovered different populations of cell types within SAN tissue, the distinct potential functions of these cell types have not been delineated.

Methods

To infer some special potential functions of different SAN cell clusters, we applied principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP) to the GSE130710 dataset to reduce dimensions, followed by Pseudotime trajectory and AUCell analyses, ANOVA and Hurdle statistical models, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichments to determine functional potential of cell types. Nuclear EdU immuno-labeling of SAN tissue confirmed cell type proliferation.

Findings

We identified elements of a coupled clock system known to drive SAN cell pacemaking within the GSE130710 sinus node myocyte cluster, which, surprisingly, manifested signals of suppressed fatty acid and nitrogen metabolism and reduced immune gene expression. Proliferation signaling was enriched in endocardial, epicardial, epithelial cells, and macrophages, in which, fatty acid and nitrogen metabolic signals were also suppressed, but immune signaling was enhanced. EdU labeling was rare in pacemaker cells but was robust in interstitial cells.

Interpretation

Pacemaker cells that initiate each heartbeat manifest suppressed fatty acid and nitrogen metabolism and limited immune signaling and proliferation potential. In contrast, other populations of SAN cells not directly involved in the initiation of heartbeats, manifest robust proliferation and immune potential, likely to ensure an environment required to sustain healthy SAN tissue pacemaker function.

Translational Bioinformatics for Human Reproductive Biology Research: Examples, Opportunities and Challenges for a Future Reproductive Medicine

Since 1978, with the first IVF (in vitro fertilization) baby birth in Manchester (England), more than eight million IVF babies have been born throughout the world, and many new techniques and discoveries have emerged in reproductive medicine. To summarize the modern technology and progress in reproductive medicine, all scientific papers related to reproductive medicine, especially papers related to reproductive translational medicine, were fully searched, manually curated and reviewed. Results indicated whether male reproductive medicine or female reproductive medicine all have made significant progress, and their markers have experienced the progress from karyotype analysis to single-cell omics. However, due to the lack of comprehensive databases, especially databases collecting risk exposures, disease markers and models, prevention drugs and effective treatment methods, the application of the latest precision medicine technologies and methods in reproductive medicine is limited.

The Transition from Cancer "omics" to "epi-omics" through Next- and Third-Generation Sequencing

Deciphering cancer etiopathogenesis has proven to be an especially challenging task since the mechanisms that drive tumor development and progression are far from simple. An astonishing amount of research has revealed a wide spectrum of defects, including genomic abnormalities, epigenomic alterations, disturbance of gene transcription, as well as post-translational protein modifications, which cooperatively promote carcinogenesis. These findings suggest that the adoption of a multidimensional approach can provide a much more precise and comprehensive picture of the tumor landscape, hence serving as a powerful tool in cancer research and precision oncology. The introduction of next- and third-generation sequencing technologies paved the way for the decoding of genetic information and the elucidation of cancer-related cellular compounds and mechanisms. In the present review, we discuss the current and emerging applications of both generations of sequencing technologies, also referred to as massive parallel sequencing (MPS), in the fields of cancer genomics, transcriptomics and proteomics, as well as in the progressing realms of epi-omics. Finally, we provide a brief insight into the expanding scope of sequencing applications in personalized cancer medicine and pharmacogenomics.

Advances in Single-Cell Sequencing Technology and Its Application in Poultry Science

Single-cell sequencing (SCS) uses a single cell as the research material and involves three dimensions: genes, phenotypes and cell biological mechanisms. This type of research can locate target cells, analyze the dynamic changes in the target cells and the relationships between the cells, and pinpoint the molecular mechanism of cell formation. Currently, a common problem faced by animal husbandry scientists is how to apply existing science and technology to promote the production of high-quality livestock and poultry products and to breed livestock for disease resistance; this is also a bottleneck for the sustainable development of animal husbandry. In recent years, although SCS technology has been successfully applied in the fields of medicine and bioscience, its application in poultry science has been rarely reported. With the sustainable development of science and technology and the poultry industry, SCS technology has great potential in the application of poultry science (or animal husbandry). Therefore, it is necessary to review the innovation of SCS technology and its application in poultry science. This article summarizes the current main technical methods of SCS and its application in poultry, which can provide potential references for its future applications in precision breeding, disease prevention and control, immunity, and cell identification.

Pueraria lobata Potentially Treating Prostate Cancer on Single-Cell Level by Network Pharmacology and AutoDock: Clinical Findings and Drug Targets

Background. Prostate cancer (PCa) is one of the common malignant tumors of the urological system, and metastasis often occurs in advanced stages. Chemotherapy is an effective treatment for advanced PCa but has limitations in terms of efficacy, side effects, multidrug resistance, and high treatment costs. Therefore, new treatment modalities for PCa need to be explored and improved. Methods. R language and GEO database were used to obtain differentially expressed genes for PCa single-cell sequencing. TCMSP, STITCH, SwissTargetPrediction, and PubChem databases were used to obtain the active ingredients and targets of Pueraria lobata (PL). Next, Cytoscape software was used to draw the interactive network diagram of “drug–active component–target pathway.” Based on the STRING database, the protein–protein interaction network was constructed. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes were applied for the genes. Molecular docking was used to visualize the drug–target interaction via AutoDock Vina and PyMOL. Finally, prognosis-related genes were found by survival analysis, and Protein Atlas was used for validation. Results. Four active components and 31 target genes were obtained through the regulatory network of PL. Functional enrichment analysis showed that PL played a pharmacological role in the treatment of PCa by regulating the metabolic processes of reactive oxygen species, response to steroid hormones, and oxidative stress as well as IL-17 signaling pathway, PCa, and estrogen signaling pathway. Single-cell data showed that AR, MIF, HSP90B1, and MAOA genes were highly expressed, and molecular docking analysis showed that representative components had a strong affinity with receptor proteins. Survival analysis found that APOE, CA2, IGFBP3, MIF, F10, and NR3C1 could predict progression-free survival (PFS), and some of them could be validated in PCa. Conclusion. In this paper, a drug–active ingredient–target pathway network of PL at the single-cell level of PCa was constructed, and the findings revealed that it acted on genes such as AR, MIF, HSP90B1, and MAOA to regulate several biological processes and related signaling pathways to interfere with the occurrence and development of PCa. APOE, CA2, IGFBP3, MIF, F10, and NR3C1 were also important as target genes in predicting PFS.

Discovery and characterization of SARS-CoV-2 reactive and neutralizing antibodies from humanized CAMouseHG mice through rapid hybridoma screening and high-throughput single-cell V(D)J sequencing

The coronavirus disease 2019 pandemic has caused more than 532 million infections and 6.3 million deaths to date. The reactive and neutralizing fully human antibodies of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are effective detection tools and therapeutic measures. During SARS-CoV-2 infection, a large number of SARS-CoV-2 reactive and neutralizing antibodies will be produced. Most SARS-CoV-2 reactive and neutralizing fully human antibodies are isolated from human and frequently encoded by convergent heavy-chain variable genes. However, SARS-CoV-2 viruses can mutate rapidly during replication and the resistant variants of neutralizing antibodies easily survive and evade the immune response, especially in the face of such focused antibody responses in humans. Therefore, additional tools are needed to develop different kinds of fully human antibodies to compensate for current deficiency. In this study, we utilized antibody humanized CAMouse^HG mice to develop a rapid antibody discovery method and examine the antibody repertoire of SARS-CoV-2 RBD-reactive hybridoma cells derived from CAMouse^HG mice by using high-throughput single-cell V(D)J sequencing analysis. CAMouse^HG mice were immunized by 28-day rapid immunization method. After electrofusion and semi-solid medium screening on day 12 post-electrofusion, 171 hybridoma clones were generated based on the results of SARS-CoV-2 RBD binding activity assay. A rather obvious preferential usage of IGHV6-1 family was found in these hybridoma clones derived from CAMouse^HG mice, which was significantly different from the antibodies found in patients with COVID-19. After further virus neutralization screening and antibody competition assays, we generated a noncompeting two-antibody cocktail, which showed a potent prophylactic protective efficacy against SARS-CoV-2 in cynomolgus macaques. These results indicate that humanized CAMouse^HG mice not only provide a valuable platform to obtain fully human reactive and neutralizing antibodies but also have a different antibody repertoire from humans. Thus, humanized CAMouse^HG mice can be used as a good complementary tool in discovery of fully human therapeutic and diagnostic antibodies.

Sample-multiplexing approaches for single-cell sequencing

Single-cell sequencing is widely used in biological and medical studies. However, its application with multiple samples is hindered by inefficient sample processing, high experimental costs, ambiguous identification of true single cells, and technical batch effects. Here, we introduce sample-multiplexing approaches for single-cell sequencing in transcriptomics, epigenomics, genomics, and multiomics. In single-cell transcriptomics, sample multiplexing uses variants of native or artificial features as sample markers, enabling sample pooling and decoding. Such features include: (1) natural genetic variation, (2) nucleotide-barcode anchoring on cellular or nuclear membranes, (3) nucleotide-barcode internalization to the cytoplasm or nucleus, (4) vector-based barcode expression in cells, and (5) nucleotide-barcode incorporation during library construction. Other single-cell omics methods are based on similar concepts, particularly single-cell combinatorial indexing. These methods overcome current challenges, while enabling super-loading of single cells. Finally, selection guidelines are presented that can accelerate technological application.

Research Progress of Cell Lineage Tracing and Single-Cell Sequencing Technology in Malignant Skin Tumors

Cell lineage tracing and single-cell sequencing have been widely applied in development biology and oncology to reveal the molecular mechanisms in multiple basic biological processes and the differentiation of stem cells, as well as quantify the differences between single cells. They provide new methods for in-depth understanding of the origin of tumors, the heterogeneity of tumor cells, and the drug resistance mechanism of tumors, thus inspiring new strategies for tumor treatment. In this review, we summarized the progress of cell lineage tracing technology and single-cell sequencing technology in the research of malignant melanoma and cutaneous squamous cell carcinoma, attempting to spark new ideas for further research on skin tumors.

One Cell at a Time: Advances in Single-Cell Methods and Instrumentation for Discovery in Aquatic Microbiology

Studying microbes from a single-cell perspective has become a major theme and interest within the field of aquatic microbiology. One emerging trend is the unfailing observation of heterogeneity in activity levels within microbial populations. Wherever researchers have looked, intra-population variability in biochemical composition, growth rates, and responses to varying environmental conditions has been evident and probably reflect coexisting genetically distinct strains of the same species. Such observations of heterogeneity require a shift away from bulk analytical approaches and development of new methods or adaptation of existing techniques, many of which were first pioneered in other, unrelated fields, e.g., material, physical, and biomedical sciences. Many co-opted approaches were initially optimized using model organisms. In a field with so few cultivable models, method development has been challenging but has also contributed tremendous insights, breakthroughs, and stimulated curiosity. In this perspective, we present a subset of methods that have been effectively applied to study aquatic microbes at the single-cell level. Opportunities and challenges for innovation are also discussed. We suggest future directions for aquatic microbiological research that will benefit from open access to sophisticated instruments and highly interdisciplinary collaborations.

Molecular analysis of vascular gene expression

A State of the Art lecture entitled "Molecular Analysis of Vascular Gene Expression" was presented at the ISTH Congress in 2021. Endothelial cells (ECs) form a critical interface between the blood and underlying tissue environment, serving as a reactive barrier to maintain tissue homeostasis. ECs play an important role in not only coagulation, but also in the response to inflammation by connecting these two processes in the host defense against pathogens. Furthermore, ECs tailor their behavior to the needs of the microenvironment in which they reside, resulting in a broad display of EC phenotypes. While this heterogeneity has been acknowledged for decades, the contributing molecular mechanisms have only recently started to emerge due to technological advances. These include high-throughput sequencing combined with methods to isolate ECs directly from their native tissue environment, as well as sequencing samples at a high cellular resolution. In addition, the newest technologies simultaneously quantitate and visualize a multitude of RNA transcripts directly in tissue sections, thus providing spatial information. Understanding how ECs function in (patho)physiological conditions is crucial to develop new therapeutics as many diseases can directly affect the endothelium. Of particular relevance for thrombotic disorders, EC dysfunction can lead to a procoagulant, proinflammatory phenotype with increased vascular permeability that can result in coagulopathy and tissue damage, as seen in a number of infectious diseases, including sepsis and coronavirus disease 2019. In light of the current pandemic, we will summarize relevant new data on the latter topic presented during the 2021 ISTH Congress.

The Promise of Patient-Derived Colon Organoids to Model Ulcerative Colitis

Physiologic, molecular, and genetic findings all point to impaired intestinal epithelial function as a key element in the multifactorial pathogenesis of ulcerative colitis (UC). The lack of epithelial-directed therapies is a conspicuous weakness of our UC therapeutic armamentarium. However, a critical barrier to new drug discovery is the lack of preclinical human models of UC. Patient tissue-derived colon epithelial organoids (colonoids) are primary epithelial stem cell-derived in vitro structures capable of self-organization and self-renewal that hold great promise as a human preclinical model for UC drug development. Several single and multi-tissue systems for colonoid culture have been developed, including 3-dimensional colonoids grown in a gelatinous extracellular matrix, 2-dimensional polarized monolayers, and colonoids on a chip that model luminal and blood flow and nutrient delivery. A small number of pioneering studies suggest that colonoids derived from UC patients retain some disease-related transcriptional and epigenetic changes, but they also raise questions regarding the persistence of inflammatory transcriptional programs in culture over time. Additional research is needed to fully characterize the extent to which and under what conditions colonoids accurately model disease-associated epithelial molecular and functional aberrations. With further advancement and standardization of colonoid culture methodology, colonoids will likely become an important tool for realizing precision medicine in UC.

Single cell RNA sequencing techniques and applications in research of ovary development and related diseases

The ovary is a highly organized composite of germ cells and various types of somatic cells, whose communications dictate ovary development to generate functional oocytes. The differences between individual cells might have profound effects on ovary functions. Single cell RNA sequencing techniques are promising approaches to explore the cell type composition of organisms, the dynamics of transcriptomes, the regulatory network between genes and the signaling pathways between cell types at the single cell resolution. In this review, we provide an overview of the currently available single cell RNA sequencing techniques including Smart-seq2 and Drop-seq, as well as their applications in biological and clinical research to provide a better understanding on the molecular mechanisms underlying ovary development and associated diseases.

Application of single-cell RNA sequencing technology in liver diseases: a narrative review

Objective

This review aimed to summarize the application of single-cell transcriptome sequencing technology in liver diseases.

Background

The increasing application of single-cell ribonucleic acid (RNA) sequencing (scRNA-seq) in life science and biomedical research has greatly improved our understanding of cellular heterogeneity in immunology, oncology, and developmental biology. scRNA-seq has proven to be a powerful tool for identifying and classifying cell subsets, characterizing rare or small cell subsets and tracking cell differentiation along the dynamic cell stages. Globally, liver disease has high rates of morbidity and mortality, and its exact pathological mechanism remains unclear, current treatment options are limited to clearance of the underlying cause or liver transplantation, which cannot overwhelm and cure liver diseases. scRNA-seq provides many novel insights for healthy and diseased livers.

Methods

In this review, we searched for related articles in the PubMed database and summarized the advances of scRNA-seq in revealing the molecular mechanisms of liver development, regeneration, and disease. We also discussed the challenges and future application potential of scRNA-seq, which is expected to enhance the ability to explore the field of liver research and accelerate the clinical application of liver precision medicine.

Conclusions

With the continuous improvement of scRNA-seq technology, scRNA-seq is expected to unlock new avenues for liver biology exploration, liver disease diagnosis, and personalized treatment, which will pave the way for breakthrough innovation in personalized medicine.

Johne's Disease in Dairy Cattle: An Immunogenetic Perspective

Johne's disease (JD), also known as paratuberculosis, is a severe production-limiting disease with significant economic and welfare implications for the global cattle industry. Caused by infection with Mycobacterium avium subspecies paratuberculosis (MAP), JD manifests as chronic enteritis in infected cattle. In addition to the economic losses and animal welfare issues associated with JD, MAP has attracted public health concerns with potential association with Crohn's disease, a human inflammatory bowel disease. The lack of effective treatment options, such as a vaccine, has hampered JD control resulting in its increasing global prevalence. The disease was first reported in 1895, but in recognition of its growing economic impact, extensive recent research facilitated by a revolution in technological approaches has led to significantly enhanced understanding of the immunological, genetic, and pathogen factors influencing disease pathogenesis. This knowledge has been derived from a variety of diverse models to elucidate host-pathogen interactions including in vivo and in vitro experimental infection models, studies measuring immune parameters in naturally-infected animals, and by studies conducted at the population level to enable the estimation of genetic parameters, and the identification of genetic markers and quantitative trait loci (QTL) putatively associated with susceptibility or resistance to JD. The main objectives of this review are to summarize these recent developments from an immunogenetics perspective and attempt to extract the principal and common findings emerging from this wealth of recent information. Based on these analyses, and in light of emerging technologies such as gene-editing, we conclude by discussing potential future avenues for effectively mitigating JD in cattle.

Towards high throughput and high information coverage: advanced single-cell mass spectrometric techniques

Mass spectrometry (MS) is attractive for single-cell analysis because of its high sensitivity, rich information, and large dynamic ranges, especially for the single-cell metabolome and proteome analysis. Efforts have been made to deal with the throughput and information coverage problems in typical manual single-cell MS techniques. In this review, advanced techniques to improve the automation and throughput for single-cell sampling and single-cell metabolome and proteome MS detection have been discussed. Furthermore, representative MS-based strategies that can increase the in-depth cellular information coverage and achieve the more comprehensive single-cell multiomics information during high throughput detection have been highlighted, providing an ongoing perspective of the MS performance for the single-cell research.

Tumor-Associated Microglia and Macrophages in the Glioblastoma Microenvironment and Their Implications for Therapy

Glioblastoma is the most frequent and malignant primary brain tumor. Standard of care includes surgery followed by radiation and temozolomide chemotherapy. Despite treatment, patients have a poor prognosis with a median survival of less than 15 months. The poor prognosis is associated with an increased abundance of tumor-associated microglia and macrophages (TAMs), which are known to play a role in creating a pro-tumorigenic environment and aiding tumor progression. Most treatment strategies are directed against glioblastoma cells; however, accumulating evidence suggests targeting of TAMs as a promising therapeutic strategy. While TAMs are typically dichotomously classified as M1 and M2 phenotypes, recent studies utilizing single cell technologies have identified expression pattern differences, which is beginning to give a deeper understanding of the heterogeneous subpopulations of TAMs in glioblastomas. In this review, we evaluate the role of TAMs in the glioblastoma microenvironment and discuss how their interactions with cancer cells have an extensive impact on glioblastoma progression and treatment resistance. Finally, we summarize the effects and challenges of therapeutic strategies, which specifically aim to target TAMs.

Analyzing Modern Biomolecules: The Revolution of Nucleic-Acid Sequencing - Review

Recent developments have revolutionized the study of biomolecules. Among them are molecular markers, amplification and sequencing of nucleic acids. The latter is classified into three generations. The first allows to sequence small DNA fragments. The second one increases throughput, reducing turnaround and pricing, and is therefore more convenient to sequence full genomes and transcriptomes. The third generation is currently pushing technology to its limits, being able to sequence single molecules, without previous amplification, which was previously impossible. Besides, this represents a new revolution, allowing researchers to directly sequence RNA without previous retrotranscription. These technologies are having a significant impact on different areas, such as medicine, agronomy, ecology and biotechnology. Additionally, the study of biomolecules is revealing interesting evolutionary information. That includes deciphering what makes us human, including phenomena like non-coding RNA expansion. All this is redefining the concept of gene and transcript. Basic analyses and applications are now facilitated with new genome editing tools, such as CRISPR. All these developments, in general, and nucleic-acid sequencing, in particular, are opening a new exciting era of biomolecule analyses and applications, including personalized medicine, and diagnosis and prevention of diseases for humans and other animals.

Mixed Distribution Models Based on Single-Cell RNA Sequencing Data

Progress in single-cell RNA sequencing (scRNA-seq) has yielded a lot of valuable data. Analysis of these data can provide a new perspective for studying the intratumoral heterogeneity and identifying gene markers. In this paper, the scRNA-seq data of colorectal cancer (CRC) are analyzed, and it is found that the shape of the gene expression difference (GED) data shows certain distribution regularity. To study the distribution regularity, mixed stable-normal distribution (MSND) model and mixed stable-exponential distribution (MSED) model are constructed to fit the GED data. And the estimated parameters of MSND and MSED are used to describe some characteristics of their distribution. Through the comparison of root mean square error and the chi-squared goodness of fit test, it is found that the fitting effect of MSED and MSND are both better than that of stable distribution and Cauchy distribution. Considering the given quantile thresholds, MSND and MSED can be used to identify tumor-related genes. The results of functional analysis indicate that the selected genes are highly correlated with CRC. In addition, the parameters of MSND and MSED exhibit a certain trend with the development of CRC. To explore the association, Gene-set enrichment analysis (GSEA) is performed. The results of GSEA reveal that the trend can well characterize the intratumoral heterogeneity of CRC. In addition, the application of MSED model on hepatocellular carcinoma shows that our model can analyze other cancers. Overall, MSND model and MSED model can well fit the GED data in different disease stages, the parameters of the two models can characterize the heterogeneity of CRC tumor cells, and the two models can be used to identify genes highly correlated with tumors.

Multi-omics approaches to improve malaria therapy

Malaria contributes to the most widespread infectious diseases worldwide. Even though current drugs are commercially available, the ever-increasing drug resistance problem by malaria parasites poses new challenges in malaria therapy. Hence, searching for efficient therapeutic strategies is of high priority in malaria control. In recent years, multi-omics technologies have been extensively applied to provide a more holistic view of functional principles and dynamics of biological mechanisms. We briefly review multi-omics technologies and focus on recent malaria progress conducted with the help of various omics methods. Then, we present up-to-date advances for multi-omics approaches in malaria. Next, we describe resistance phenomena to established antimalarial drugs and underlying mechanisms. Finally, we provide insight into novel multi-omics approaches, new drugs and vaccine developments and analyze current gaps in multi-omics research. Although multi-omics approaches have been successfully used in malaria studies, they are still limited. Many gaps need to be filled to bridge the gap between basic research and treatment of malaria patients. Multi-omics approaches will foster a better understanding of the molecular mechanisms of Plasmodium that are essential for the development of novel drugs and vaccines to fight this disastrous disease.

Harnessing Single-Cell RNA Sequencing to Better Understand How Diseased Cells Behave the Way They Do in Cardiovascular Disease

The transition of healthy arteries and cardiac valves into dense, cell-rich, calcified, and fibrotic tissues is driven by a complex interplay of both cellular and molecular mechanisms. Specific cell types in these cardiovascular tissues become activated following the exposure to systemic stimuli including circulating lipoproteins or inflammatory mediators. This activation induces multiple cascades of events where changes in cell phenotypes and activation of certain receptors may trigger multiple pathways and specific alterations to the transcriptome. Modifications to the transcriptome and proteome can give rise to pathological cell phenotypes and trigger mechanisms that exacerbate inflammation, proliferation, calcification, and recruitment of resident or distant cells. Accumulating evidence suggests that each cell type involved in vascular and valvular diseases is heterogeneous. Single-cell RNA sequencing is a transforming medical research tool that enables the profiling of the unique fingerprints at single-cell levels. Its applications have allowed the construction of cell atlases including the mammalian heart and tissue vasculature and the discovery of new cell types implicated in cardiovascular disease. Recent advances in single-cell RNA sequencing have facilitated the identification of novel resident cell populations that become activated during disease and has allowed tracing the transition of healthy cells into pathological phenotypes. Furthermore, single-cell RNA sequencing has permitted the characterization of heterogeneous cell subpopulations with unique genetic profiles in healthy and pathological cardiovascular tissues. In this review, we highlight the latest groundbreaking research that has improved our understanding of the pathological mechanisms of atherosclerosis and future directions for calcific aortic valve disease.

Application of single-cell RNA sequencing in embryonic development

Embryonic development is a complex process that is regulated by a series of precise cellular behaviours. The limited number of cells in the early stages of embryonic development represents a challenge for studying early gene regulation and maintaining cell sternness. Single-cell sequencing is a new technology for high-throughput sequencing analysis at the single-cell level that not only reflects the heterogeneity between cells but also reveals gene expression characteristics in different cells from limited samples. Currently, the widespread application of single-cell RNA sequencing technology is gradually changing our understanding of disease pathogenesis. This article reviews the application of single-cell RNA sequencing in embryonic development in recent years and provides innovative ideas for research on embryonic development and the treatment of diseases related to embryonic development.