Abstract
Hematopoiesis is the process of blood and immune cell generation and is essential for human life. It is organized as a cellular differentiation hierarchy residing in the bone marrow and ensures the life-long production of hematopoietic cells.
Hematopoietic stem cells reside at the apex of this hierarchy, giving rise to intermediate progenitors that then form mature and specialized cells. Acute myeloid leukemia is an aggressive cancer where mutations result in a malignant differentiation hierarchy, leading to bone marrow failure. The molecular characterization of single cells has helped us to understand the gradual progression through cell states during differentiation in health and disease. Specifically, single-cell transcriptomics has provided the required throughput and sensitivity. However, relying on transcript levels misses important processes in gene expression, where proteins are produced via translation and regulated via degradation. Recent advances in mass spectrometry-based proteomics have enabled measurements on single-cell level that could provide more phenotypical information than transcriptomics.
In this thesis, we tap into the potential of single-cell proteomics to characterize
cellular states in healthy and malignant hematopoiesis.
In the first article, we implement a single-cell proteomics workflow in our laboratory, evaluate its quantitative output and develop a computational analysis pipeline. Subsequently, we apply the workflow to characterize the differentiation hierarchy of an acute myeloid leukemia model system. Here, we exemplify the ability of scp-MS to characterize the proteome of single leukemic stem cells.
Furthermore, we find evidence for an alternative differentiation trajectory in
that system. In the second article, we implement real-time search assisted mass
spectrometry acquisition methods that outperform our previous method. We evaluate the quantitative output of these methods and specify their respective use-case.
In the third article, we apply our workflow to the human hematopoietic stem and
progenitor compartment. Our dataset recapitulates the in-vivo differentiation hierarchy of this system and enables the proteome characterization on single-cell level.
We integrate this dataset with single-cell transcriptome measurements to compare these two modalities. We find proteins that are relevant for hematopoietic stemcells that are not that apparent on transcriptome level. Furthermore, we find functional protein covariation that is not detected on transcriptome level. Finally, we use this multi-omics data to model translation dynamics during erythroid differentiation.
Collectively, we exemplify how single-cell proteomics can be used to characterize
single cells in the hematopoietic system by their proteome profile and show
how this information can be advantageous because it can be complementary to
the transcriptome.
Hematopoietic stem cells reside at the apex of this hierarchy, giving rise to intermediate progenitors that then form mature and specialized cells. Acute myeloid leukemia is an aggressive cancer where mutations result in a malignant differentiation hierarchy, leading to bone marrow failure. The molecular characterization of single cells has helped us to understand the gradual progression through cell states during differentiation in health and disease. Specifically, single-cell transcriptomics has provided the required throughput and sensitivity. However, relying on transcript levels misses important processes in gene expression, where proteins are produced via translation and regulated via degradation. Recent advances in mass spectrometry-based proteomics have enabled measurements on single-cell level that could provide more phenotypical information than transcriptomics.
In this thesis, we tap into the potential of single-cell proteomics to characterize
cellular states in healthy and malignant hematopoiesis.
In the first article, we implement a single-cell proteomics workflow in our laboratory, evaluate its quantitative output and develop a computational analysis pipeline. Subsequently, we apply the workflow to characterize the differentiation hierarchy of an acute myeloid leukemia model system. Here, we exemplify the ability of scp-MS to characterize the proteome of single leukemic stem cells.
Furthermore, we find evidence for an alternative differentiation trajectory in
that system. In the second article, we implement real-time search assisted mass
spectrometry acquisition methods that outperform our previous method. We evaluate the quantitative output of these methods and specify their respective use-case.
In the third article, we apply our workflow to the human hematopoietic stem and
progenitor compartment. Our dataset recapitulates the in-vivo differentiation hierarchy of this system and enables the proteome characterization on single-cell level.
We integrate this dataset with single-cell transcriptome measurements to compare these two modalities. We find proteins that are relevant for hematopoietic stemcells that are not that apparent on transcriptome level. Furthermore, we find functional protein covariation that is not detected on transcriptome level. Finally, we use this multi-omics data to model translation dynamics during erythroid differentiation.
Collectively, we exemplify how single-cell proteomics can be used to characterize
single cells in the hematopoietic system by their proteome profile and show
how this information can be advantageous because it can be complementary to
the transcriptome.
| Originalsprog | Engelsk |
|---|
| Antal sider | 153 |
|---|---|
| Status | Udgivet - nov. 2024 |