In recent years, organoids derived from induced pluripotent stem cells have provided a model for studying the development of human organs. It is reported that single-cell transcriptomics can highly resolve the cellular state in these systems. However, there was no way to directly measure ancestry.
Based on this, Zhejiang University alumnus He Zhisong and colleagues jointly developed the lineage recorder iTracer, which combines reporting barcodes with inducible CRISPR–Cas9 scars and is compatible with single-cell and spatial transcriptomics to explore clonality and phylogenetics during brain organoid development.
In detail, the recorder allows clonal tracking from the initialized iPSC pool, while also using induced scars for lineage recording at different time points, both for clonal analysis and to explore the temporal dynamics of cell fate establishment, circumventing the inefficiencies of multiple rounds of induced scar markers.
Figure | He Zhisong (Source: He Zhisong)
On December 30, 2021, the paper was published in Nature Methods under the title Lineage recording in human cerebral organoids.[1]
Figure | Related papers (Source: Nature Methods)
For a long time, He Zhisong's research group has been interested in the central nervous system, especially brain development, the pathogenesis of neurodevelopment-related diseases during early human embryonic development, and the performance of development.
In the study, they used brain organoid miniature three-dimensional tissue culture technology to induce human embryonic stem cells, or induce pluripotent stem cells to differentiate into different types of brain neurons and other cell types, thereby simulating and studying the early development of the human brain.
In order to fully depict the changes in the molecular characteristics of cells in this process, they made extensive use of single-cell sequencing techniques, especially single-cell transcriptome techniques, to obtain dynamic cell states that may occur during the period, and to infer the occurrence of different cell types by integrating sample data at different time points and various computational analysis methods.
However, this method also has limitations, and current single-cell sequencing techniques require destructive measurements of cells, so only a single snapshot of the cell's state at the time of the final measurement can be obtained.
This makes it impossible to know the historical state of the cell, let alone obtain the lineage information of the cell, that is, the progeny cells produced by the division and differentiation of these cell lines at a specific time.
This information is crucial to better characterize the brain's early developmental processes. To do this, He and his colleagues need a new technology that can further obtain cell lineage information, that is, cell lineage tracking, while being compatible with current single-cell sequencing techniques.
Currently, cell lineage tracking techniques that are compatible with single-cell transcriptome sequencing are mainly divided into two categories:
One is static sequence labeling, that is, building a highly complex barcode sequence library, transfection and integration into stem cells, thereby labeling different stem cells;
The other is dynamic sequence labeling based on CRISPR technology, that is, by inducing a CRISPR editing system, introducing a series of random mutations into a specific sequence, and constructing cell lineage information through the combination of mutations detected in each stem cell.
Both techniques have advantages and disadvantages: static sequence labeling can only obtain spectral information at a single time point; dynamic labeling based on CRISPR technology has a more serious label collision problem, and multiple independent editing events will produce the same mutation, resulting in inaccurate reconstructed lineage information.
To better solve this problem, He Zhisong and his colleagues integrated these two types of technologies to develop iTracer technology. iTracer contains static sequence marker originals that can be used to label different stem cells at the start time point, as well as dynamic sequence markers based on the CRISPR editing system, combined with stem cells with genes that induce the Cas9 protein, to generate additional random mutations at specific time points to obtain a second layer of cell lineage information.
(Source: Nature Methods)
In summary, this technique combines the advantages of two types of existing technologies, which can obtain genealogical-level information at multiple time points and reduce the impact of marker collision problems.
They then used iTracer technology in brain organoid systems to study the lineage associations between different types of neurons in brain organoids.
He found that neurons representing different brain regions tend to be produced by different pluripotent stem cells, and that the offspring cells produced by the same pluripotent stem cells show the characteristics of clustered distribution in spatial distribution.
This phenomenon implies that during the process of division and differentiation, the cells of the brain organoids do not undergo significant cell migration, so their progenitor cells are clustered and distributed, and under the action of similar microenvironment, they are induced to be the same type of neurons.
This hypothesis is further demonstrated by tracking the organoids of the brain labeled with sparse nuclei by using long-duration light-sheet microscopy techniques.
On this basis, by introducing dynamic sequence markers at different time points, it is also possible to obtain the fate of different cell types in brain organoids, especially different types of neurons, and compare the differentiation of different offspring neurons produced by the same pluripotent stem cell.
In addition, by introducing an additional gRNA for the target gene on the basis of iTracer, the target gene can be knocked out based on CRISPR technology while the iTracer can be used to record cell lineage information, and how gene knockout affects the development and differentiation of cell lineages can be studied accordingly.
According to reports, He Zhisong and colleagues also used the iTracer-perturb technology in brain organoids, and conducted a preliminary discussion on the impact of TSC2 gene on neuronal development in brain organoids.
Combined with iTracer technology based on CRISPR technology gene knockout
The study began in 2017. He Zhisong's group is mainly concerned with biological systems, generally related to tissue development, tissue regeneration, stem cell differentiation, etc., which contain a large number of dynamic transitions in cell states.
As a result, large-scale single-cell transcriptome sequencing techniques that had matured at that time allowed him to study these dynamic processes. However, limited by the destructive nature of single-cell sequencing technology on the measured cells, how to directly obtain the lineage relationship between different cells through experimental means has become a problem that He Zhisong and his colleagues are eager to solve.
At the time, celltag, a static sequence labeling technique by Sam Morris, a professor in the Department of Genetics and Developmental Biology at the University of Washington, and LinnaEUS, a dynamic sequence labeling technique by Jan Philipp Junker's team at the Institute for Systems Biology (BIMSB) in Berlin, Germany, had just emerged.
They are all cell lineage tracking technologies that are compatible with single-cell transcriptome sequencing technology, and He Zhisong's research team has also begun to use them. But then, they quickly discovered the limitations of the technique and wanted to develop a way to combine static sequence markers with dynamic sequence markers.
The idea became a subject and began in 2018, when they first built a transposon plasmid vector containing an iTracer element and began using bulk sequencing in brain organoids to demonstrate the feasibility of iTracer technology.
After determining that the technology is feasible, they used iTracer technology in brain organoid systems from 2019 onwards, whereby data were obtained and analyzed for data analysis of brain organoid single-cell transcriptome sequencing induced by dynamic sequence labeling at different time points.
At the beginning of 2020, the preliminary results of data analysis are ushered in. He Zhisong learned that pluripotent stem cells did not undergo significant migration in the process of division and differentiation and the production of brain organoids. Based on this, he made the hypothesis that cells of the same lineage converge in space.
To justify this hypothesis, he and other members of the research team combined iTracer technology with spatial transcriptomes to observe the distribution of different cell lineages in brain organoids; on the other hand, they also used long-term light-lens microscopy to record the early development of brain organoids and track several of them that were tagged with nuclei, as well as their progeny cells.
Both methods validate the above assumptions. Then, by comparing the samples introduced dynamic sequence markers at different time points, He Zhisong inferred the important time nodes of "fate generation" of different neurons in brain organoids, and confirmed the existence of different neural progenitor cells at this time point by generating single-cell transcriptome data of brain organoids corresponding to the time.
Considering that the single-cell sequencing technology of 10x Genomics used this time actually measured only a very few cells in each brain organoid, this resulted in only a few cells per cell lineage, which also made direct comparisons between the lineages difficult.
To this end, the research team also microdiscised individual organoids and performed deep single-cell transcriptome sequencing of each part of the obtained parts, thus achieving adequate sampling of cell lineages.
Finally, they expanded the iTracer technology by introducing a gRNA that targets the target knockout gene on top of the original iTracer vector, thereby combining it with gene knockout based on CRISPR technology.
This led them to make a preliminary application of the resulting iTracer-perturb technology and to study the role of the TSC2 gene in the development of brain organoids and the potential effects on cell lineage.
Can be used in all in vitro cell culture systems
There was also a small episode in the study, He Zhisong said: "For different neurons to enrich different pluripotent stem cell lineages, this result was very unexpected at first. Because we believe that the pluripotent stem cells used to grow brain organoids are uniform, it is natural to feel that different stem cells will produce various neurons with equal probability. ”
Therefore, his first reaction at the time was that there might be problems with the analytical methods, or that for some reason led to different stem cells, there was indeed a tendency to produce different neurons.
It wasn't until a discussion that he suddenly realized that this result could be explained by the non-uniform distribution of cell lineages caused by the low migration of stem cells, and the spatial non-uniform distribution of different neurons.
To further confirm the idea, he designed the combination of iTracer with spatial transcriptomics and experiments with long-duration light-sheet microscopy, which confirmed the idea.
For potential applications, he said: The current application of the technology should stay in the field of basic research, but it is by no means limited to the brain organoid system. Theoretically, iTracer technology can be used in all in vitro cell culture systems, with the only requirement that the stem cells used must have an inducible CRISPR editing system. ”
Born in Guangdong, he studied at the College of Life Sciences of Zhejiang University
He Zhisong is a native of Zhongshan, Guangdong Province, born in 1987. In 2009, he was admitted to the Max Planck-Computational Biology Partnership Institute of the Chinese Academy of Sciences at the Shanghai Institute of Biological Sciences of the Chinese Academy of Sciences under the tutelage of Philipp Khaitovich, a researcher.
After graduating with a Ph.D. in 2015, he continued his research stay until 2017. During his time at the Chinese Academy of Sciences, He Zhisong published several papers as the first author or corresponding author in journals such as Nature Neuroscience and Molecular Psychiatry.
In 2018, he came to the Institute of Evolutionary Anthropology of the Max Planck Society in Leipzig, Germany, and joined Professor Barbara Treutlein's single-cell genomics research group for post-bodily research.
In 2019, he moved with his team to the Department of Biosystems Science and Engineering at the Swiss Federal Institute of Technology in Zurich, where he continued his post-Doctoral work in the Truttling team.
During this period, He Zhisong's research direction was the analysis and method development of single-cell functional genomics, especially single-cell transcriptomics data, and used brain organoids and other organoid systems as models to study the determining mechanism of cell fate during the development of the early human brain and other organs.
After coming to Switzerland, he published papers as a first-book or corresponding author in Nature, Genome Biology and Stem Cell Report.
In July 2021, He Zhisong became the senior research assistant of the team, and on the basis of doing scientific research, he began to be responsible for the management of computing resources and the guidance of some students.
Commenting on the follow-up to the paper, he said: "We are using iTracer technology for several other studies within the group and have achieved good results. At the same time, I also hope to make further improvements to iTracer, mainly to study the crispR system to introduce dynamic sequence marking is less efficient. ”
-End-
reference: