A new "single" era of biomedicine and implications in disease research

Abstract

In recent decades, single-cell (SC) technologies and applications have been a very hot topics in the field of biology and medicine. In fact, early studies involving a single cell were on the malignant process of acute nonlymphocytic leukemia and inherited or sporadic genetic disease in the 1980s. And since the RhD gene in a single cell from maternal plasma was detected by fluorescence-based polymerase chain reaction (PCR) in the 1990s, “SC biopsies”[1] were widely used for early diagnosis in clinical practice in the 2000s. Previous studies showed that SC RNA sequencing (scRNA-seq) was used to evaluate patterns of allelic gene expression at the allele-specific mRNA level, and SC genome analysis can be used for genetic diagnosis. Imprinted genes are linked to the etiology of some genetic syndromes and common diseases, such as cardiovascular diseases (CVDs), diabetes, and cancer. As a powerful tool, there are obvious advantages of scRNA-seq to identify imprinted genes in human and mouse models. Moreover, a combination of scRNA-seq and whole-genome sequencing can be used for the analysis of genomic imprinting in specific cell types and in different individuals. For example, a comparative analysis of scRNA-seq data helped to disclose the genetic mechanisms of Klinefelter syndrome and understand the causes of infertility.[2] Recently, Zhang et al integrated >1.3 million SC chromatin profiles from adult/fetal human tissues[3] and helped us interpret noncoding variants associated with complex traits and diseases. Currently, SC heteroplasmy and cell state have been assayed for the analysis of genetic diseases, and data from scRNA-seq have also been used as a standard control in clinical studies or for the evaluation of novel gene expression in vascular genetic diseases. Herein, this article thinks that a new “single” era of biomedicine has come and reviewed its application in both CVDs and coronavirus disease 2019 (COVID-19). A new “single” era in biomedicine SC techniques are essential for studying and understanding cell heterogeneity, cell differentiation, carcinogenesis, and other important cellular processes, and they have become very popular in recent years. With the development of cellular, chemical, and molecular biology techniques, such as SC, single molecule, single nucleus, single chromosome, and other related biotechnologies, there have been many novel breakthroughs in the field of life science and medicine. It can be said that a new “single” era of biomedicine has come. First, SC and single-molecule resolutions were used early for drug screening, the study of G protein–coupled receptor pharmacology, and RNA polymerases. However, some tools (such as transmission electron microscopy) and technologies (such as whole-genome amplification) are necessary, and many novel strategies are worthy of development, for example, SC meta-analysis and multiomics analysis for COVID-19 studies[4,5] and super-resolution microscopy with optical cell imaging of single-molecule electrochemical reactions in live cells.[6] Targeted SC and single-molecule sequencing have important implications in cancer for its diagnosis, treatment, and evolution,[7] and SC analysis and different omics techniques have been successfully translated to the fields of cancer, regenerative medicine, drug discovery and immunology, as well genomic blueprints.[8] These techniques include strategies for multiplex sequencing for chromatin interactions, named chromatin-interaction analysis via droplet-based and barcode-linked sequencing (named ChIA-Drop),[9] and assaying transcriptional activity.[10] Due to technological advances, single-molecule real-time sequencing is successfully used, and novel technologies, such as single-molecule fluorescence in situ hybridization (smFISH) and SMOOTH-seq (a novel third-generation sequencing platform-based SC whole-genome sequencing method, that is single-molecule real-time sequencing of long fragments amplified through transposon insertion), are also used in studies of viral infection and cell fates in single living cells[11,12] and have opened a new chapter in the field of biomedicine.[13] To date, SC technologies have been successfully used for the analysis of the molecular genetic mechanisms of complex diseases, diabetes risk, origins of cancer, and potential therapeutic targets.[14–18] Second, through single-chromosome technologies, after the development of synthetic organisms Syn 1.0 and Syn 3.0,[19,20] eukaryotic cells with a pair of chromosomes or the lone-chromosome yeast strain were artificially created by clustered regularly interspaced short palindromic repeats (CRISPR) technology.[21,22] The 16 chromosomes in yeast were synthesized into just one or two chromosomes, that is, all of the gene vectors “in parallel” were fused or chimerized and concatenated together into new chromosomes (Fig. 1). Novel chimeric chromosomes or new organisms of yeast have marked great success in biological structure and gene editing.Figure 1.: A new method for single chromosome. Here is a chromosome that has been restructured or chimerized through CRISPR-based gene-editing technology. It is easy to understand that the 16 chromosomes (16 C) in yeast cells were artificially fused or chimerized into only one chromosome (1 C). This new organism is also a novel chimeric gene vector. The author thinks that it’s also another classical example of combinatorial biomedicine, which was designed and developed according to previous studies done by the famous scientists.[ 21 , 22 ] CRISPR=clustered regularly interspaced short palindromic repeats.Chimeric vectors and chimeric gene therapy were just a good idea at the beginning of the 2000s, and they were also a promising direction. However, a perfect vector system had not been constructed at that time. Thus, new chromosomes created by CRISPR gene editing marked great success in the construction of chimeric vectors. Even if current chromosome fusion is not for gene therapy, it creates a method of restructuring or chimerizing vectors and still belongs to gene therapy. These methods are worthy of conduction in the field of biomedicine and will help to develop novel gene therapies and artificial life. However, how to assay, analyze, and apply this new artificial life of a single chromosome is still a developing hot topic. Currently, through SC cleavage under targets and tagmentation (CUT&Tag) (scCUT&Tag) technology for the analysis of chromatin regions, research in epigenomic landscapes and tumor treatment of the central nervous system has improved and been more successful.[23,24] Hence, it is also possible to use scCUT&Tag technology for the analysis of a single chromosome. Although there is rapid growth in experimental studies, gene therapy faces major challenges in its clinical translation. It is believed that a breakthrough in COVID-19 therapy will occur with the help of novel CRISPR technologies to tackle unprecedented variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). DNA or RNA base editors directly convert one base or base pair into another, enabling the efficient installation of specific and precise point mutations in genomic DNA and RNA in nondividing cells.[25] Recent studies found that there are durable therapeutic responses after the induction of a single-nucleotide, loss-of-function mutation. These studies highlight adenine base editors for research and therapeutic applications in monogenic diseases.[26,27] When SC resolutions are integrated with other techniques (such as mass spectrometry or a machine learning approach) for increased sensitivity, the translational process in single cells can be precisely measured.[28] Integrating scRNA-seq with spatial transcriptomics can help to elucidate intercellular tissue dynamics.[13,29] Due to its combination with bioinformatics, computational biology, and spatial information, SC analysis of multiomics (genomes, epigenomes, transcriptomes, and proteomics) data is increasingly used by researchers.[30,31] Finally, with the combination of applications of other “single” cellular and molecular biotechnologies and biochemical strategies, such as C-H activation[32] and C-H functionalization,[33] as powerful platforms for molecular syntheses, more landmark achievements are expected in biomedicine. Scientists will open up a new “single” era for clinical medicine and life science (Table 1)[34–41] with the help of SC and single-molecule analysis of human diseases in the brain and heart.[42–44] Table 1 - SC and single-molecule technologies for analysis and research in biomedicine[34–41] Items SC technology Single-molecule technology Mass cytometryMass spectrometry A MC protocol for SC analysis of organoid signaling networksLive scMS: direct metabolomic analysis for plant cells RNA sequencing Massively parallel scRNA sequencing (MARS-seq2.0)An automated protocol for full-length scRNA sequencingSmall-RNA including miRNAs, fragments of tRNAs and snoRNAs sequencingstRNA sequencing in cancer applications Single-molecule RNA sequencing in cancer applications Omics analysis scOmics analysis(a high-throughput platform) Single-molecule detection for structural and functional cellular diversity Imaging scImaging: A new preclinical drug discovery platformDFM imagingFM imagingSEM imagingFor the clinical application of nanoparticles and nanomedicine Single-molecule imagingFor understanding the dynamic molecular mechanisms of cells in nanomedicineFor signaling pathways of single live cells in real-time at single-molecule and nanomedicine resolutionsFor the mechanism of RAD-51 nucleation and filament growth and RAD51 paralogue complex function Gene expression The novoSpaRc algorithm: A computational framework for spatial reconstruction of sc gene expression(https://pypi.org/project/novosparc)Sc qRT–PCR combined with high-throughput arrays for the analysis of gene expression profiles at a molecular level Other seq technologies scDNase-seq: A method of detecting genome-wide DHSsG&T-seq: Separation and parallel sequencing of the genomes and transcriptomes of single cellsscATAC-seq: For mouse CPCs marked by Nkx2-5 and Isl1 expression; for human immunophenotypic blood cells from fetal liver and bone marrow Other analyses SC Hi-C for genome-wide detection of chromatin interactions: a powerful method for snapshots of thousands of chromatin interactions that occur simultaneously in a single cellSCRAMFACS-based single-cell genomics Western blotting SC western blotting for direct measurement of proteins pH measurement SC pH monitoring in human lung cancer A549 cells CPCs=cardiac progenitor cells, DFM=dark-field microscopy, DHSs=DNase I hypersensitive sites, FACS=fluorescence-activated cell sorting, FM=fluorescence microscopy, G&T-seq=genomes and transcriptomes sequencing, MARS-seq2.0=massively parallel RNA single-cell sequencing, MC=mass cytometry, miRNAs=microRNAs, MS=mass spectrometry, qRT–PCR=quantitative real-time PCR, SC=single-cell, scDNase-seq=single-cell DNase sequencing, scOmics=single-cell Omics, SCRAM=SC restriction analysis of DNA methylation, SEM=scanning electron microscopy, seq=sequencing, snoRNAs=small nucleolar RNAs, stRNA sequencing=spatial transcriptome RNA sequencing, tRNAs=transfer RNAs. scRNA-seq and its role in precision medicine Currently, scRNA-seq is a novel high-throughput technique that enables the investigation of the entire transcriptome of a single cell, and it has rapidly gained popularity over the last few years for profiling the transcriptomes of thousands to millions of single cells. This technology is now being used to analyze experiments with complex designs, including biological replication experiments (Fig. 2). scRNA-seq can be used to elucidate intricate cellular networks and generate indices that will eventually enable the development of more targeted and personalized medications. At the same time, scRNA-seq is valuable for analyzing cellular heterogeneity. Cell composition accuracy is critical for analyzing cell–cell interaction networks from scRNA-seq data. Moreover, scRNA-seq platforms and methods can be developed for high-sensitivity gene detection, the detection of important cell–cell interactions and the expression of growth factors/interleukins in cell subsets, and improved understanding and atlas construction of lung biology at the SC level. It is easy to set up a real-time database for secure data management and an efficient investigation of the activation of gene sets on a SC basis.Figure 2.: Schematic workflow of scRNA-seq. FACS=fluorescence-activated cell sorting, LCM=laser capture microdissection, MARS-Seq=massively parallel RNA single-cell sequencing, SMART-Seq2=Switching Mechanism at 5′ end of RNA Template Sequencing 2, PCR=polymerase chain reaction, UMIs=unique molecular identifiers.With vital advances in SC technology, scRNA-seq provides an opportunity to accurately map the tissue architecture, characterize rare cell types, and define function at a SC level. For example, scRNA-seq was used to perform a detailed transcriptomic analysis of lymphoid-derived leukocytes to better understand the pathology of some diseases. scRNA-seq was used to compare cells from the brain to primary cultures to identify which cells as a therapeutic in lung In fact, scRNA-seq techniques have the opportunity to and the scRNA-seq of a of cells from many tumor helped to a cell transcriptome In recent efficient scRNA-seq methods have been enabling the transcriptome profiling of single cells in The of and the of targeted help personalized treatment for in clinical Herein, the of scRNA-seq has been in complex biological such as cancer, and the which cellular heterogeneity. For example, scRNA-seq is being for its potential in the development of precision for cancer. In the new era of precision medicine, the are to better understand the cellular and molecular mechanisms that to the of major diseases and to treatment, to identify novel therapeutic and to more and treatment SC For example, as an increasingly popular study scRNA-seq data are from to genes that are two of individuals. scRNA-seq technologies for cell However, SC transcriptomic of complex of cells, and and scRNA-seq techniques have cell that the cell composition of scRNA-seq Moreover, cell from scRNA-seq data are and there are in cell composition experimental to gene expression and the or of a cell an integrated on scRNA-seq and other techniques for the analysis of cell or tissue major cell types and can be scRNA-seq can be combined with to the cell atlas of some diseases. In fact, sequencing and multiomics have helped us more precisely in the last signaling pathways can be by scRNA-seq and data combined with interactions in the biological of cells. However, the of current analyses from scRNA-seq data on direct networks of from of with different With novel can from scRNA-seq data and complex networks at a analyses of the cellular transcriptomic and can more detailed molecular mechanisms of some diseases. of scRNA-seq in COVID-19 at SC has been a hot in biomedicine. However, current studies are and the and understanding of the of infection on the cardiovascular system and other the author the current and the related applications of SC technologies in both CVDs and Previous studies on SC technologies in from to (Table on blood diseases acute and brain diseases vascular and or brain disease infection and or inherited liver and other and cell or diseases In since signaling pathways are linked to the molecular mechanisms of human cancer, and the of the SC technologies also help to understand viral and the development of new diseases and cancer. 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genes and is in with and severe COVID-19 in In scRNA-seq data also showed that mechanisms the clinical of SC can be used to identify the molecular of and that are in critical Moreover, can complex data through analysis of SC In maternal infection the fetal system in the of At the same time, scRNA-seq that the to infection was the And with targets through and Moreover, scRNA-seq has been used to evaluate the to different platforms and In fact, SC technologies are not only tools for studying CVDs and CVDs research also tools for diseases, complex and For example, SC transcriptional profiling has applications in and fields and an essential role in biology to its precise In recent advances in the field of SC biology will understanding of it is believed that the and treatment of both CVDs and COVID-19 will be more more and more in the to the mechanisms and pathways through the use of novel Finally, will both CVDs and COVID-19 with new and strategies, including specific and technologies, if 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As powerful tools and biological and molecular technologies, SC strategies can help to understand the molecular mechanisms of both COVID-19 and including or and as well as to develop novel therapeutic targets and studies highlight the new “single” era of biomedicine and its applications in CVDs and CVDs and COVID-19 research are only two of many which from of SC technologies, and there are many other applications The and editors are for on this in and and the of the for this was of are of is from the

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