With the continuous maturation of single-cell transcriptomics research technology, it is estimated that in the next few years, single-cell gene expression and regulation research will become a popular topic, and the scientific research community will soon obtain enough quantitative transcript research data. This information can help us answer many important scientific questions and can also lay the foundation for quantitative research on cell types and heterogeneity in the future. Based on this information, the transcriptome of almost all types of cells in a complex multicellular organ can also be determined. Moreover, single-cell transcriptomics information can also help us improve the ability to manually manipulate gene expression regulatory networks, because a large amount of single-cell data truly reflects the biological disturbances faced by cells, and this information can help us deepen our understanding of regulatory networks.
- Prospects of single cell sequencing technology
Usually we will regard a cell with the same phenotype as a whole with a specific function, and call it a tissue or an organ. However, deep DNA and RNA sequencing of a single cell will reveal a variety of cell states that constitute a complex ecosystem, and then such a complex system forms the overall function of tissues and organs. The continuous development of high-information, real-time, multi-mode single-cell detection technology will help us truly understand the function of a single cell in a microenvironment system.
Although early morphological studies have clearly identified a variety of cell morphologies, recent studies have unexpectedly discovered many new and different cell states. A standard human cell contains approximately 6 billion DNA base pairs, and 600 million bases of mRNA (an mRNA of this size is already sufficient to provide super coding capacity). Deep sequencing of DNA and RNA of single cells can more fully grasp the functions of cells with unprecedented higher resolution. Scientists' ability to specifically recognize the state of cells helps us better understand the normal functions and abnormalities of cells.
Single-cell sequencing can detect differences between cells at a higher resolution, which also raises a series of new problems. The most fundamental problem may be that it is not necessarily meaningful to find and measure such cell-to-cell differences, that is, we do not know which cell state is the truly functional cell state. Since in a typical human cell, there are only dozens of copies of each mRNA on average. How do individual cells interact with each other to achieve functions at the organizational level? This essential study of cellular ecology is a brand-new field that is worth digging into. In addition, if we think that the phenotype of a cell is the function of a local ecosystem formed by multiple cells, then, in a tissue composed of multiple cells, how do so many local ecosystems coexist together? Is there a mutual exchange effect?
Although single-cell sequencing technology has brought us many surprises, and we are optimistic for the technology, but the technology is not currently a routine detection technology in the laboratory. Because the continuous advancement of basic technology and data analysis and interpretation technology is the key to improving the accuracy of single cell sequencing technology, and to understand the role of single cells at the system level, it is necessary to conduct single cell sequencing research on a large number of cells. We will comment on these issues next, will also focus on the future development of single-cell sequencing technology, as well as the newly emerging single-cell sequencing supplementary technology, and will introduce the specific functions of single cells in the overall ecological environment.
5.1 Important questions about single cell research
There are several important issues that affect the quality of data obtained by the Single Cell Sequencing Institute. Among them, the inevitable problem that needs special attention is that the transcriptome will change according to various stimuli, and this change is more prominent at the single cell level. With this in mind, we should treat single-cell transcriptome data with caution (at least to some extent) as the result of a perturbation experiment unless a less destructive RNA isolation technique can be developed.
5.1.1 Cell separation
Single-cell separation technology is almost the technology that needs to be developed most and needs to establish a standardized system. The use of patch pipettes or nanotubes to obtain the cytoplasmic content of individual cells is currently the conventional method of isolating cellular RNA, but this operation is prone to omission of organelle components. Using a microfluidic device can separate cells in individual reaction chambers, but the cells need to be separated from other substrates, and these substrates may interfere with the transcription status of the cells. During the process of cell dissociation, classification and enrichment, whether the transcription state of the cell changes is a question that needs special attention. Scattered cells are very easy to separate, but experiments with such cells require very good experimental design to avoid problems in interpreting the experimental results due to the lack of microenvironment. The most ideal situation is to separate the contents of single cells in a tissue or natural microenvironment. Only in this way, single cell mRNA detection can reflect the most real state of the cell under overall conditions, and only in this way can the effect of human operations on the cell be reduced as much as possible.
To be continued in Part X…