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  • Editorial 2023-02-28

    0 212 59

    Single-Cell Analysis: Technology, Data Analysis, and Applications

    Daehee Hwang

    Mol. Cells 2023; 46(2): 69-70
  • Journal Club 2023-02-28

    0 161 45

    Quo Vadis Experimental Structural Biology?

    Hyun Kyu Song

    Mol. Cells 2023; 46(2): 71-73
  • Minireview 2023-02-28

    0 224 84

    Single-Cell Molecular Barcoding to Decode Multimodal Information Defining Cell States

    Ik Soo Kim

    Mol. Cells 2023; 46(2): 74-85

    Abstract : Single-cell research has provided a breakthrough in biology to understand heterogeneous cell groups, such as tissues and organs, in development and disease. Molecular barcoding and subsequent sequencing technology insert a singlecell barcode into isolated single cells, allowing separation cell by cell. Given that multimodal information from a cell defines precise cellular states, recent technical advances in methods focus on simultaneously extracting multimodal data recorded in different biological materials (DNA, RNA, protein, etc.). This review summarizes recently developed singlecell multiomics approaches regarding genome, epigenome, and protein profiles with the transcriptome. In particular, we focus on how to anchor or tag molecules from a cell, improve throughputs with sample multiplexing, and record lineages, and we further discuss the future developments of the technology.

  • Minireview 2023-02-28

    0 254 112

    Epigenetic Regulations in Mammalian Cells: Roles and Profiling Techniques

    Uijin Kim and Dong-Sung Lee

    Mol. Cells 2023; 46(2): 86-98

    Abstract : The genome is almost identical in all the cells of the body. However, the functions and morphologies of each cell are different, and the factors that determine them are the genes and proteins expressed in the cells. Over the past decades, studies on epigenetic information, such as DNA methylation, histone modifications, chromatin accessibility, and chromatin conformation have shown that these properties play a fundamental role in gene regulation. Furthermore, various diseases such as cancer have been found to be associated with epigenetic mechanisms. In this study, we summarized the biological properties of epigenetics and single-cell epigenomic profiling techniques, and discussed future challenges in the field of epigenetics.

  • Minireview 2023-02-28

    0 193 67

    A Comprehensive Overview of RNA Deconvolution Methods and Their Application

    Yebin Im and Yongsoo Kim

    Mol. Cells 2023; 46(2): 99-105

    Abstract : Tumors are surrounded by a variety of tumor microenvironmental cells. Profiling individual cells within the tumor tissues is crucial to characterize the tumor microenvironment and its therapeutic implications. Since single-cell technologies are still not cost-effective, scientists have developed many statistical deconvolution methods to delineate cellular characteristics from bulk transcriptome data. Here, we present an overview of 20 deconvolution techniques, including cutting-edge techniques recently established. We categorized deconvolution techniques by three primary criteria: characteristics of methodology, use of prior knowledge of cell types and outcome of the methods. We highlighted the advantage of the recent deconvolution tools that are based on probabilistic models. Moreover, we illustrated two scenarios of the common application of deconvolution methods to study tumor microenvironments. This comprehensive review will serve as a guideline for the researchers to select the appropriate method for their application of deconvolution.

  • Minireview 2023-02-28

    0 379 144

    Integration of Single-Cell RNA-Seq Datasets: A Review of Computational Methods

    Yeonjae Ryu , Geun Hee Han , Eunsoo Jung , and Daehee Hwang

    Mol. Cells 2023; 46(2): 106-119

    Abstract : With the increased number of single-cell RNA sequencing (scRNA-seq) datasets in public repositories, integrative analysis of multiple scRNA-seq datasets has become commonplace. Batch effects among different datasets are inevitable because of differences in cell isolation and handling protocols, library preparation technology, and sequencing platforms. To remove these batch effects for effective integration of multiple scRNA-seq datasets, a number of methodologies have been developed based on diverse concepts and approaches. These methods have proven useful for examining whether cellular features, such as cell subpopulations and marker genes, identified from a certain dataset, are consistently present, or whether their condition-dependent variations, such as increases in cell subpopulations in particular disease-related conditions, are consistently observed in different datasets generated under similar or distinct conditions. In this review, we summarize the concepts and approaches of the integration methods and their pros and cons as has been reported in previous literature.

  • Minireview 2023-02-28

    0 285 121

    Single-Cell Genomics for Investigating Pathogenesis of Inflammatory Diseases

    Seyoung Jung and Jeong Seok Lee

    Mol. Cells 2023; 46(2): 120-129

    Abstract : Recent technical advances have enabled unbiased transcriptomic and epigenetic analysis of each cell, known as “single-cell analysis”. Single-cell analysis has a variety of technical approaches to investigate the state of each cell, including mRNA levels (transcriptome), the immune repertoire (immune repertoire analysis), cell surface proteins (surface proteome analysis), chromatin accessibility (epigenome), and accordance with genome variants (eQTLs; expression quantitative trait loci). As an effective tool for investigating robust immune responses in coronavirus disease 2019 (COVID-19), many researchers performed single-cell analysis to capture the diverse, unbiased immune cell activation and differentiation. Despite challenges elucidating the complicated immune microenvironments of chronic inflammatory diseases using existing experimental methods, it is now possible to capture the simultaneous immune features of different cell types across inflamed tissues using various single-cell tools. In this review, we introduce patient-based and experimental mouse model research utilizing single-cell analyses in the field of chronic inflammatory diseases, as well as multi-organ atlas targeting immune cells.

Mol. Cells
Feb 28, 2023 Vol.46 No.2, pp. 69~129
The bulk tissue is a heterogeneous mixture of various cell types, which is depicted as a skein of intertwined threads with diverse colors each of which represents a unique cell type. Single-cell omics analysis untangles efficiently the skein according to the color by providing information of molecules at individual cells and interpretation of such information based on different cell types. The molecules that can be profiled at the individual cell by single-cell omics analysis includes DNA (bottom middle), RNA (bottom right), and protein (bottom left). This special issue reviews single-cell technologies and computational methods that have been developed for the single-cell omics analysis and how they have been applied to improve our understanding of the underlying mechanisms of biological and pathological phenomena at the single-cell level.

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