Single Cell Sequencing: The Technology, Challenge and Future (III)
|31.5.2020||Posted by tactical33 under Advertising & Marketing|
The biggest difficulty in single-cell sequencing is that the amplification efficiency of some DNA fragments is much higher than that of others. Xie et al. invented a new multiple annealing and looping-based amplification cycles (MALBAC) in 2012. This technology first requires 5 rounds of MDA pre-amplification, and then you can use the newly obtained amplification products form closed circular molecules (Science 338, 1622–1626, 2012). Since these circular molecules cannot be further amplified, the entire amplification process becomes linear amplification. Then, the conventional PCR amplification is performed. Since the template used at this time is more uniform, it is not easy to cause a large difference when performing PCR amplification. Xie et al. Used this MALBAC technology to obtain 93% coverage of the human genome amplification product, and also detected CNV mutations in single tumor cells.
Soon, scientists will be able to conduct a more in-depth study of the genome of a single cell, they will be able to find smaller deletions and repeated mutations, and even single base mutations. Although uniform genome amplification is still a problem, experts believe that reducing the reaction volume should bring some help.
For example, Zhang and others from the University of California, San Diego recently introduced a MIDAS technology, that is, micro-well displacement amplification system, which can be used with this system. Nano-upgraded reaction systems simultaneously perform thousands of MDA reactions (Nat. Biotechnol., 31, 1126–1132, 2013). Researchers can take out these amplified products by hand or use robots to sequence them. With the help of this MIDAS system, Zhang et al.’S research team found a single-copy-number change in human neuronal cells with very little sequencing work, and the resolution reached 1 to 2MB.
This MIDAS system is a high-throughput single cell separation, amplification and sequencing technology.
2.4 Differences in cell expression
At the Broad Institute in the United States, Aviv Regev and Joshua Levin and others compared multiple RNA sequencing technologies with tissue samples of poor quality and severe degradation before using single-cell RNA sequencing, and finally they decided Smart-Seq technology was used to study dendritic cells derived from bone marrow. These dendritic cells are a type of mitotic immune cell that can produce a very strong transcriptional response to antigens.
A total of 18 cells were selected by Regev et al., and the experiments were conducted in batches over a week. They tried various methods, and they all failed. But this time it succeeded once. The study found that every cell expresses the so-called ‘housekeeping’ genes in a unified manner, but each cell also has its own unique expression profile. The expression levels of genes related to immune regulatory functions are very high in some cells. But in some cells, it doesn’t express at all. This phenomenon of polarization has never been found in dendritic cells before, because a lot of cells have been studied all the time, and the differences between the cells have been averaged out. The research results were published. The article reported for the first time a “hidden” cell type, namely the very rare “first responder cell” (Nature 498, 236-240, 2013). From a broader perspective, this discovery helps us to re-understand these dendritic cells, as well as their signaling pathways and functions.
The first attempt of single-cell RNA sequencing technology was successful.
Single-cell transcriptome sequencing can also help researchers study gene expression and regulation in early development, and this technology can also carry out scientific research on rare samples with unprecedented precision. For example, Guoping Fan of the University of California, Los Angeles and his collaborators in China published an article that performed transcriptome sequencing on 33 single cells. These 33 cells were all taken from embryos at different stages of development. Based on the sequencing results, they determined the order of gene expression at the early stage of development, and also found the difference in gene expression time limit between human and mouse embryo development (Nature 500, 593– 597, 2013).
Single-cell sequencing technology is a very powerful technology that can help us discover genomic variations in tumor cells.
At the same time, Tang’s group is also carefully separating cell specimens from several early human embryos and performing single-cell transcriptome sequencing on these cells one by one. According to Tang, they are very nervous because these specimens are hard-won and very precious. However, their work has paid off. They have discovered more than 2,700 new long noncoding RNA molecules, which may be related to early gene regulation (Nat. Struct. Mol. Biol. 20, 1131 –1139, 2013). According to Tang, prior to this, all single-cell RNA sequencing work was only to analyze known genes, and at best, it only increased the alternative splicing isoforms of known genes.
2.5 Mixed tumor cells
From the prognosis of the disease to the monitoring of the disease, oncology researchers can get great help from single-cell sequencing technology. We all know that the mutation rate of tumor cells is very fast, and the tumor tissue is a highly heterogeneous tissue. Determining which cell subpopulations (or clones) in tumor tissue have the ability to metastasize and which clones are sensitive to chemotherapy drugs, this information is very helpful for clinical work. Especially for the whole genome or transcriptome sequencing of circulating tumor cells (CTC) hidden in the human circulatory system, because these CTC cells are the culprits leading to tumor metastasis, information about them Both monitoring and treatment are essential.
For example, Navin published an article in Nature in 2011, introducing their single-cell genome research results. They found that CNV mutations are related to the tumor’s evolutionary pattern, and the tumor will suddenly become genomically unstable after steady growth. According to Navin, who is currently working at the MD Anderson Cancer Center at the University of Texas, the discovery surprised them because they always thought that tumor cells had been accumulating mutations slowly. The research work also confirmed that the single-cell technology is very powerful, at least to help them find variations in the copy number of genes in a single tumor cell in the human body. Navin and his collaborators continue to conduct research on patients with triple negative breast cancer, mainly wanting to understand the situation of CNV, but also hope to better understand the problem of tumor metastasis.
In addition to Navin et al., Several other research groups are also using single cell sequencing technology to carry out tumor-related research work. For example, Xie introduced earlier and Fan Bai of Peking University in China, and Jie Wang of Harvard University in the United States found a specific CNV mutation in CTC cells of a lung cancer subtype (excluding other subtypes) (Proc. Natl. Acad. Sci. USA, doi: 10.1073 / pnas.1320659110, 9 December 2013). Xie believes that these latest developments will help us develop early diagnostic products and technologies.
Mike McConnell found large DNA deletions or repeated mutations in a single human brain neuron cell.
The differences in the transcriptome also help us understand the progress of the tumor. For example, Sandberg ’s team used their own Smart-Seq technology to perform RNA sequencing studies on individual CTC cells and validated their method. Using the latest version of Smart-Seq2 technology, they can observe more cells at a lower cost than before. Due to the larger number of cells observed, the problem of experimental errors, which is a headache for researchers working in CTC research, can be better controlled. According to Sandberg, they really hope to come up with a more systematic solution to help everyone better understand the heterogeneity of CTC cells and help them better understand the gene expression of CTC cells when they enter the blood circulation system.
To be continued in Part IV…