Periodic Reporting for period 3 - MicroBar (Microsatellite Barcoding: reconstructing the family tree of hematopoietic cells)
Periodo di rendicontazione: 2021-08-01 al 2023-01-31
One could think that nowadays the production of blood cells starting from stem cells in the bone marrow is well characterized. However, this is not the case. Recent technologies that allow to study single cells have allowed to follow the fate of cells at an unprecedent resolution in mice. It has resulted that the family of tree of murine blood cells from textbooks was partially wrong and is currently under revision. In parallel, blood cell production in human was assumed to be similar to the murine production mostly because we lack methods to study human blood cell production. To increase our knowledge of human blood cell production, we need new single cell technologies adapted to work in human to reconstruct the family tree of cells in vivo. This project aims at generating such innovative method.
The method takes advantage of recent developments in single cell sequencing technologies to provide a method for in vivo use in human. We will use the microsatellite regions of the human genome that mutate during cell division to create a natural barcode for each cell. The family tree will be reconstructed based on the microsatellite relationship using bioinformatics pipelines. Our technique, will be highly detailed with respect to current versions and will provide a higher molecular resolution of the family tree.
To achieve this goal, we will first develop the bioinformatic pipeline to reconstruct trees from microsatellite mutation. We will then study the murine blood cell production to validate our method. Finally, we will use our method to reconstruct the family tree of human blood cells.
The knowledge of the family tree of human blood cells will have important long-term implications for disease related to blood cell production such as leukemia or bone marrow transplant.
The method takes advantage of recent developments in single cell sequencing technologies to provide a method for in vivo use in human. We will use the microsatellite regions of the human genome that mutate during cell division to create a natural barcode for each cell. The family tree will be reconstructed based on the microsatellite relationship using bioinformatics pipelines. Our technique, will be highly detailed with respect to current versions and will provide a higher molecular resolution of the family tree.
To achieve this goal, we will first develop the bioinformatic pipeline to reconstruct trees from microsatellite mutation. We will then study the murine blood cell production to validate our method. Finally, we will use our method to reconstruct the family tree of human blood cells.
The knowledge of the family tree of human blood cells will have important long-term implications for disease related to blood cell production such as leukemia or bone marrow transplant.
During the first 30 months we made seminal progress on the first aim of our proposal.
We have developed two new bioinformatic tools. First, we have built a simulation tool to compare different published method to reconstruct family trees and have compared their performance when using microsatellite mutations. The results were published last year (Lyne et al, IEEE/ACM 2020). Secondly, we have developed a bioinformatic tool to extract microsatellite mutations from sequencing data. We have used this pipeline on published data sets as well as our own data sets. This has allowed us to establish the feasibility of our single cell technologies to reconstruct the family tree of human blood cells in vivo.
The simulation tool was also used to address a question related to the dynamics of stem cells in leukemia. In particular, we revisited if natural selection at the level of stem cells was the only explanation of the architecture of the mutations present in leukemia patients. Surprisingly, we found that both selection on a large number of stem cells and no selection on a small number of stem cells can produce the same clonal architecture. Presently, the number of stem cells in leukemic patients is unknown. Therefore both natural selection and no selection can act on stem cells in leukemic patients. As some treatments depend on natural selection to work (eg adaptative therapy), this result has important implications for the clinician and the patients. This work has been published by the journal Blood in 2021.
We have developed two new bioinformatic tools. First, we have built a simulation tool to compare different published method to reconstruct family trees and have compared their performance when using microsatellite mutations. The results were published last year (Lyne et al, IEEE/ACM 2020). Secondly, we have developed a bioinformatic tool to extract microsatellite mutations from sequencing data. We have used this pipeline on published data sets as well as our own data sets. This has allowed us to establish the feasibility of our single cell technologies to reconstruct the family tree of human blood cells in vivo.
The simulation tool was also used to address a question related to the dynamics of stem cells in leukemia. In particular, we revisited if natural selection at the level of stem cells was the only explanation of the architecture of the mutations present in leukemia patients. Surprisingly, we found that both selection on a large number of stem cells and no selection on a small number of stem cells can produce the same clonal architecture. Presently, the number of stem cells in leukemic patients is unknown. Therefore both natural selection and no selection can act on stem cells in leukemic patients. As some treatments depend on natural selection to work (eg adaptative therapy), this result has important implications for the clinician and the patients. This work has been published by the journal Blood in 2021.
By the end of the project, we hope to have validated our single cell technologies to reconstruct the family tree of human blood cells in vivo providing a new method to study human blood cell production. We will use this method to reconstruct the family trees of blood cells in healthy humans. We aim at identifing new paths as well as new mechanisms involved in blood cell production that could be the basis for therapeutical intervention when blood cell production is not working well.