Journal Of Cell Science & Therapy Impact Factor – Single-cell molecular tools have been developed at incredible speed over the past five years as sequencing costs have continued to decline and many molecular tests have been combined with sequencing readouts. This rapid period of technological development has facilitated the delineation of individual molecular characteristics, including the genome, transcriptome, epigenome, and proteome of individual cells, leading to an unprecedented resolution of the molecular networks that control complex biological systems. The immense power of single-cell molecular screens has been particularly highlighted through work in systems where cellular heterogeneity is a major feature, such as stem cell biology, immunology, and tumor cell biology. Single-cell-omics technologies have already contributed to the identification of novel disease biomarkers, cellular subsets, therapeutic targets and diagnostics, many of which would have remained unknown by bulk sequencing approaches. Recently, efforts to integrate single-cell multi-omics with single cell functional output and/or physical space have been challenging but have led to considerable progress. Perhaps most excitingly, with recent advances in the modulation of cells through CRISPR technology, opportunities are emerging to reach beyond the description of stable cellular conditions, particularly with the development of base editors, which may facilitate cell and gene therapy. Increases the chances significantly. In this review, we provide a brief overview of emerging single-cell technologies and discuss current developments in integrating single-cell molecular screens and performing single-cell multi-omics for clinical applications . We also discuss how single-cell molecular assays can be usefully combined with functional data to elucidate mechanisms of cellular decision making. Finally, we consider the introduction of spatial transcriptomics and proteomics, its complementary role with single-cell RNA sequencing (scRNA-seq), and potential application in cellular and gene therapy.
The important role of single-cell approaches in understanding cell function has been recognized for decades. Early advances in immunology and particularly hematopoiesis have demonstrated the power of such approaches to confer functional properties to a single cell. The pioneering work of Till and McCulloch highlighted the functional diversity of hematopoietic stem cells (HSCs) by using a single cell-derived assay called the colony-forming unit spleen, or CFU-S, assay (1, 2). Similarly, early studies of single multipotent progenitors provided insight into progenitor cell commitment and the development of mature immune cells such as T and B lymphocytes (3, 4). Perhaps most transformative was the introduction of fluorescence-activated cell sorting (FACS) that enabled nearly ubiquitous adaptation of single-cell functional assays in immunology, hematopoiesis, and beyond (5–7).
Journal Of Cell Science & Therapy Impact Factor
Efforts to characterize the cellular function of single cells have fueled the desire to understand detailed molecular mechanisms, but the technologies to do so in single cells have largely lagged behind. The development of the polymerase chain reaction (PCR) to amplify DNA eventually led to the first glimpse into the transcriptome of single cells (8, 9). The initial protocol for amplification of cDNA using PCR from single macrophages was introduced by Brady et al. ( 10 ), where robust exponential amplification was achieved without disturbing the relative abundance of mRNA sequences, making it possible to observe rare transcripts in a complex single cell-derived cDNA library. In parallel, Eberwein and coworkers developed a linear RNA amplification approach based on amplification of antisense RNA using T7 RNA polymerase ( 11 , 12 ). By observing mRNA from single pyramidal neurons isolated from rat brains, they provided the first evidence for global molecular diversity between morphologically similar cells (11).
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While targeted single-cell PCR-based molecular screens revolutionized molecular biology, the low throughput and hypothesis-driven nature prevented unbiased exploratory screening. In 1991, Fodor and colleagues developed a new photolithography-based approach for the efficient synthesis of complex oligonucleotides on a microscale (13). This pioneering work would lead to the development of microarray technology where several years later, Shena et al. This method was first applied to monitor gene expression, examining the expression of 45 Arabidopsis genes from total mRNA (14). The following decade saw a rapid expansion of the technology, resulting in genome-wide genomic, transcriptomic, and epigenetic screening using microarrays [reviewed elsewhere: (15–18)]. This ultimately enabled microarray analysis at the single cell level (19), providing insight into the molecular pathways controlling cell fate (20, 21).
Microarray, a hybridization-based approach, assays known transcripts and is therefore unsuitable for unbiased identification of novel transcripts. In 1977, Sanger and colleagues published the first genome to be sequenced ( 22 ) and soon after, first-generation sequencing methods began to develop rapidly ( 23 ). However, these approaches were extremely expensive and time-consuming (23). This opened up the space for next-generation sequencing (NGS), which revolutionized molecular profiling, enabling low-cost, high-throughput, and highly parallel sequencing of nucleic acids. To date, a wide variety of NGS platforms have been developed [reviewed in (24, 25)] and in all cases, sheared DNA is bound to adapter sequences that are immobilized within flow cells, allowing for subsequent amplification. Facilitate the synthesis of complementary DNA fragments. (26). By using fluorophore-labeled nucleotides and simultaneous fluorescence readouts throughout the flow cell, related sequences can be determined and ultimately mapped against the reference genome (24, 27, 28). NGS offers several advantages over microarray technology for routine DNA and RNA sequencing, including low background noise, an increased dynamic range, and detection of novel transcripts (25, 29, 30).
For these reasons, NGS was rapidly adapted to a variety of model systems, including the observation of rare cell types at single cell resolution (31–36). Tang et al. pioneered the first protocol for single-cell RNA sequencing (scRNA-seq) in single mouse blastomeres with improved performance compared to microarray-based single-cell protocols (36). This has been followed by an explosion of single-cell molecular technologies, which enable unbiased investigation of the transcriptome (37, 38), genome (39, 40), DNA methylation (41), chromatin accessibility (42) and spatial resolution of gene expression. Is. (43). Although these methods provide comprehensive snapshots of molecular states, their integration with cellular phenotype and function is less common and important for observation of tissue complexity, disease progression, therapeutic intervention, and beyond. To achieve this goal, pioneering work to integrate omics protocols led to the development of several multimodal technologies. These include I) simultaneous screening of cell surface proteins and mRNA (44, 45), II) DNA methylation and mRNA (46), III) perturbation and mRNA (47), IV) DNA and mRNA (48), V) lineage tracing. Is included. and mRNA, and VI) cellular function and mRNA (44, 49, 50).
Single-cell technologies have thus far provided insight into a wide range of disease mechanisms, particularly in diseases with significant heterogeneity (51), leading to a long list of potential new therapeutic options. In recent years, the fields of cellular and gene therapy for the treatment of some monogenic diseases (gene therapy) and especially B cell leukemia (cell therapy) have been continuously developing (52, 53). However, to enable further improvements and applications in other more complex disease types such as autoimmune type 1 diabetes, key aspects such as characterizing target tissues, identifying new targets in heterogeneous diseases, and assessing the efficacy of therapeutic interventions are needed. A thorough investigation is required. Recent advances in single-cell technologies are ideally designed to address these unmet needs (51).
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In this review, we outline a wide range of recent technologies for screening the genome, epigenome, transcriptome, and proteome of single cells and the multimodal integration of these platforms. We focus on the integration of functional cellular phenotypes with molecular profiles and emphasize the use of single-cell technologies in gene and cell therapy.
In its simplest form, gene therapy aims to cure a patient’s disease by introducing a normal or correct copy of a gene into target cells. In 1972, Friedman and Roblin first proposed the concept of gene therapy as a treatment for inherited genetic defects that largely affected children, many of whom experienced severe, life-threatening symptoms (54 ). Initially, HSC transplantation represented the primary therapeutic option for many of these disorders, but the availability of matched sibling donors and the risk of severe graft-versus-host disease were barriers for many patients (55). To avoid these issues, the first gene therapy clinical trials used patient-derived differentiated (T lymphocytes) or immature (hematopoietic stem and progenitor cells, HSPCs) cells that were injected with disease-modifying transgenes (56, 57 ) were engineered ex vivo to express. Pioneering studies in the late 1990s and early 2000s initially reported successful treatment of adenosine deaminase deficiency severe combined immunodeficiency (ADA-SCID) and other hematological disorders (56–59); However, these successes were soon overshadowed by reports of patients who experienced significant adverse events, including the development of treatment-related leukemia and severe immune reactions (60–65). Many of these unexpected biological effects were later directly linked to viral vectors used for transgene delivery (66, 67). As a result, research efforts became focused on improving the safety of viral vectors (68–70) and monitoring of pre-leukemic mutations became a standard feature of treatment follow-up (71–74).
Following these improvements, several clinical trials have demonstrated the long-term benefits obtained in individuals with various primary immunodeficiencies and monogenic blood disorders who have received gene therapy treatment (75–84). The follow-up data being reported for these patients focuses primarily on disease-related parameters such as blood counts and overall clinical symptoms. As a result, many questions remain regarding the gene therapy process (Figure 1). For example, which HSPC populations are easily transferred during drug product manufacturing and what impact does this have on outcomes?
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