Single-cell sequencing technology: applications in biomedical and clinical research
Dr. Anantha Kethireddy, MedGenome Scientific Affairs
Modern medicine is now deriving its insights through a deeper understanding of cellular and molecular mechanisms, including altering cellular behavior through targeted molecular approaches. Experimental biologists and clinicians currently use a variety of techniques to assess the intrinsic behavior of cells in different ways, including analysis of genomic DNA sequences, chromatin structure, messenger RNA (mRNA) sequences, non-protein-coding RNAs, and protein expression. It uses molecular technology. , protein modifications and metabolites.
Today, single-cell RNA expression profiling is becoming an irreplaceable tool for a wide variety of studies, including humans, animals, and plants, providing unprecedented ways to more accurately and rapidly identify rare and novel cells within tissues. can be identified (Fig. 1). Moreover, this information on gene expression, metabolites, cell-to-cell communication, and spatial landscape at the mRNA and protein level will enable us to unravel the mysteries of cellular composition and function in health and disease.
Although single-cell sequencing research has been primarily carried out by research groups for several years, it has become clear that biomedical researchers and clinicians can use this powerful approach to make important new discoveries. I was. Technological advances in every field show great promise, from single cells to tissues, with great potential to transform current protocols in diagnosing the genetic drivers of disease and therapeutic response mechanisms.
There is now a growing demand for single-cell techniques, with approximately 200 different methods for profiling not only the transcriptomic information of individual cells, but also the genetic, epigenetic, and proteomic information.
Overview of single-cell technology:
Single-cell techniques can be loosely categorized into DNA (genomics, epigenomics) or RNA (transcriptomics) analysis, with new applications just around the corner, trying to combine both within the same cell. I’m doing it.
single cell genomics
Relevant to cancer biology is the ability to study genetic variation in individual cells. Bulk DNA sequencing (DNA-seq) can be used to infer clonal subpopulations based on variant allele frequency analysis, but for conclusively testing the co-occurrence of specific mutations in individual cells. cannot be used for Therefore, single-cell DNA sequencing (scDNA-seq) can reveal cancer clonal structures in greater detail.
single cell transcriptomics
Single-cell transcriptomics can be applied to cancer stem cells, metastasis-initiating cells, chemotherapy resistance, and cancer immune responses.
single cell epigenomics
Many epigenetic processes (DNA methylation, histone modifications, chromatin accessibility, etc.) are dysregulated in cancer and this fact has been exploited for various clinical applications. Single-cell epigenomics can reveal regulatory processes leading to transcriptional heterogeneity in cancer, with important clinical implications. Single-cell DNA methylation analysis has also been applied to characterize circulating tumor cells and their response to epigenetic therapy.
single-cell multi-omics
It is also possible to combine genomic, transcriptome, epigenome, and other modality analyzes using single-cell multi-omics analysis. These combinatorial approaches allow us to study gene regulation in incredible detail and were named 2019 Method of the Year. natural way.
Single cell and CRISPR
Although the human genome was sequenced 20 years ago, the cellular functions of most genes are still unknown. Single-cell CRISPR screens are an excellent method for clustering phenotypic genetic perturbations such as differentiation, chromosomal instability, cell cycle, retroviral activation, and alternative polyadenylation. Or protein measurement. Understanding the mechanisms should facilitate rational targeting of multiple genetic dependencies in cancer.
Spatial transcriptomics
Spatial single-cell transcriptomics is the next wave of single-cell analysis and is particularly useful for laboratories studying human disease. Spatial transcriptomics is Nature’s 2020 “Method of the Year” and can be performed on tissue sections using barcode arrays that record the coordinates of mRNA molecules in a sample. This technique was first applied in prostate cancer research.
Spatial techniques can be divided into those that involve gene expression analysis of microdissected tissues and those that involve them. there hybridization, there sequencing, there Spatial data capture and computational reconstruction.
single molecule fluorescence there Hybridization (smFISH) is the “beginning of hybridization-based approaches” using spatial techniques. In this method, multiple oligonucleotides carry fluorescent labels and bind to RNA molecules. smFISH provides a quantitative mRNA readout with “near 100% detection sensitivity”.
single cell proteomics
Recent studies have achieved single-cell proteomics using high-sensitivity mass spectrometry. Another report combines click chemistry and mass spectrometry to study lipid metabolism in single cells. Therefore, it will soon be possible to study changes in cell signaling pathways and metabolism in single cells.
Single-cell techniques offer unique insights into disease biology and response to therapy.
The “cost per cell” currently remains prohibitive for routine analysis. However, these costs are expected to decline over time, as is the case for bulk sequencing, eventually leading to the use of this technique in routine patient care. Perhaps talking about these numbers seems impossible, overwhelming and ambitious, but that’s what was said about the Human Genome Project more than 20 years ago.
Pushing single-cell sequencing into clinical applications is one of the key missions of clinical and translational medicine (CTM), but there are still many challenges to overcome.
References
- 1. Single Cell RNA Sequencing Techniques and Applications: An Overview, Dragomirka Jovic et.al, Clin Transl Med, 12 Mar 2022
- 2. Single-cell genomics to understand disease pathogenesis: Seitaro Nomura J Ham Genet, 2021, 66, 75-84
- 3. Method of the Year: Spatially Resolved Transcriptomics, Nature Methods, 2021, 18(1)
- 4. Method of the Year 2019: Single-cell multimodal omics, Nature Methods, 2020, 17(1)
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