| 1. |
- Niemi, MEK, et al.
(författare)
-
- 2021
-
swepub:Mat__t
|
|
| 2. |
- Mahdessian, Diana, et al.
(författare)
-
Spatiotemporal dissection of the cell cycle with single-cell proteogenomics
- 2021
-
Ingår i: Nature. - : Springer Nature. - 0028-0836 .- 1476-4687. ; 590:7847
-
Tidskriftsartikel (refereegranskat)abstract
- Spatial and temporal variations among individual human cell proteomes are comprehensively mapped across the cell cycle using proteomic imaging and transcriptomics. The cell cycle, over which cells grow and divide, is a fundamental process of life. Its dysregulation has devastating consequences, including cancer(1-3). The cell cycle is driven by precise regulation of proteins in time and space, which creates variability between individual proliferating cells. To our knowledge, no systematic investigations of such cell-to-cell proteomic variability exist. Here we present a comprehensive, spatiotemporal map of human proteomic heterogeneity by integrating proteomics at subcellular resolution with single-cell transcriptomics and precise temporal measurements of individual cells in the cell cycle. We show that around one-fifth of the human proteome displays cell-to-cell variability, identify hundreds of proteins with previously unknown associations with mitosis and the cell cycle, and provide evidence that several of these proteins have oncogenic functions. Our results show that cell cycle progression explains less than half of all cell-to-cell variability, and that most cycling proteins are regulated post-translationally, rather than by transcriptomic cycling. These proteins are disproportionately phosphorylated by kinases that regulate cell fate, whereas non-cycling proteins that vary between cells are more likely to be modified by kinases that regulate metabolism. This spatially resolved proteomic map of the cell cycle is integrated into the Human Protein Atlas and will serve as a resource for accelerating molecular studies of the human cell cycle and cell proliferation.
|
|
| 3. |
- Cho, Nathan H., et al.
(författare)
-
OpenCell : Endogenous tagging for the cartography of human cellular organization
- 2022
-
Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 375:6585, s. 1143-
-
Tidskriftsartikel (refereegranskat)abstract
- Elucidating the wiring diagram of the human cell is a central goal of the postgenomic era. We combined genome engineering, confocal live-cell imaging, mass spectrometry, and data science to systematically map the localization and interactions of human proteins. Our approach provides a data-driven description of the molecular and spatial networks that organize the proteome. Unsupervised clustering of these networks delineates functional communities that facilitate biological discovery. We found that remarkably precise functional information can be derived from protein localization patterns, which often contain enough information to identify molecular interactions, and that RNA binding proteins form a specific subgroup defined by unique interaction and localization properties. Paired with a fully interactive website (opencell.czbiohub.org), our work constitutes a resource for the quantitative cartography of human cellular organization.
|
|
| 4. |
- Gnann, Christian, 1994-
(författare)
-
Finding order in chaos : Dissecting single-cell heterogeneity in space and time
- 2024
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The cell is the smallest unit of life and contains DNA, RNA, proteins and a variety of other macromolecules. In recent years, technological advances in the field of single cell biology have revealed a staggering amount of phenotypic heterogeneity between cells in a population, which were previously considered homogenous. Previous work has largely been focused on studies of RNA. As proteins however are the ultimate effectors of genetic information, this thesis aims to provide a protein-centered view on cellular heterogeneity, particularly focusing on cell cycle and cellular metabolism.Most of my work has been performed within the framework of the Human Protein Atlas project. In the context of this project, we mapped the spatial distribution of more than 13.000 human proteins with subcellular resolution and found that around a quarter of all human proteins exhibit protein expression heterogeneity.In Paper I, we hypothesized that a majority of the observed cellular heterogeneity can be explained by differences in cell cycle progression. Therefore, we generated a map of proteomic and transcriptomic heterogeneity at subcellular resolution, which we precisely aligned to the cell cycle position of individual cells. This approach allowed us to identify hundreds of previously unknown cell cycle-related proteins. With sustained proliferative signaling representing a hallmark of cancer, novel cell-cycle proteins could serve as potential new drug targets against cancer. We further show that a large part of cell cycle dependent proteome variability is not established by transcriptomic cycling. This suggests that post-translational modifications are a major contributor to the regulation of cell cycle dependent protein level changes. Therefore, in Paper II, we carried out a deep phosphoproteome mass spectrometry profiling of the same cellular model as in Paper I and identified almost 5,000 cell cycle dependent phosphosites on over 2,000 proteins. The unprecedented scale of our phosphoproteomic data allows us to link cell cycle dependent protein expression dynamics to phosphorylation events. Furthermore, we identify a large set of proteins with stable expression levels and fluctuating phosphorylation patterns along cell cycle progression that likely alters protein function.Despite identifying hundreds of novel cell cycle dependent proteins in paper I, we observed that the majority of heterogeneously expressed proteins display variable expression independent of cell cycle progression, among them a large number of metabolic enzymes. Thus, we sought to describe the extent of subcellular metabolic complexity in human cells and tissues in Paper III. While we confirm metabolic compartmentalization in our dataset, we show that around 50% of metabolic enzymes localize to multiple cellular compartments. By integrating public protein-protein interaction data with our subcellular location information, we identify several enzymes with novel compartment-specific functions. Additionally, we observe a strongly elevated number of heterogeneously expressed enzymes compared to the background of the human proteome that is largely independent of cell cycle progression. We show that this heterogeneity can be manifested in the lineage of a single cell and is conserved in situ. To conclude, we suggest that the extensive metabolic heterogeneity can establish functional metabolic states in a population of human cells.Finally, in Paper IV, we assessed the heterogeneity of the mitochondrial proteome as they are metabolic powerhouses containing an elevated number of cell cycle independent variably expressed proteins. In this study, we correlated the variable expression of over 400 mitochondrial proteins to the expression of rate limiting enzymes in important mitochondrial pathways; such as the TCA cycle and ROS metabolism. We show that enzymes in the same pathways often correlate in their expression, indicating that their expression variability may contribute to the establishment of metabolic states.Altogether, the thesis illuminates the spatiotemporal complexity of the human proteome established by protein multilocalization and expression heterogeneity as fundamental non-genetic means of functional cell regulation.
|
|
| 5. |
- Gnann, Christian, et al.
(författare)
-
Widespread enzyme expression variations underlie diverse metabolic capacities within cell types
-
Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Metabolic enzymes perform life-sustaining functions in various compartments of the cell. Recent studies have shown some enzymes to exhibit varied expression or localization between genetically identical cells and that this heterogeneity impacts drug resistance, metastasis, differentiation, and immune cell activation. However, no systematic analysis of metabolic cellular heterogeneity has been performed. Here, we leverage imaging-based single-cell spatial proteomic data to reveal the extent of non-genetic partitioning of the metabolic proteome. Over half of all enzymes localize to multiple cellular compartments, hinting at moonlighting potential. In addition, nearly two fifths of metabolic enzymes exhibit cell-to-cell variable expression. We demonstrate that individual cells reproduce these highly heterogeneous cell populations using clonal expansion, establishing that cells recapitulate myriad metabolic phenotypes over just a few cell divisions. To identify multifunctional moonlighting enzymes, we mine protein-protein interaction datasets to find interacting proteins with distinct functional roles, and using a timeresolved transcriptomic dataset, we find that metabolic heterogeneity arises largely independently of cell cycle progression and is established mostly post-transcriptionally or posttranslationally. Taken together, our data suggest that the heterogeneity of metabolic enzymes establish diverse cellular phenotypes, which are reflected in tissues, and which may ultimately allow targeted studies of their roles in health and disease.
|
|
| 6. |
- Stenström, Lovisa, et al.
(författare)
-
Mapping the nucleolar proteome reveals a spatiotemporal organization related to intrinsic protein disorder
- 2020
-
Ingår i: Molecular Systems Biology. - : Wiley. - 1744-4292 .- 1744-4292. ; 16:8
-
Tidskriftsartikel (refereegranskat)abstract
- The nucleolus is essential for ribosome biogenesis and is involved in many other cellular functions. We performed a systematic spatiotemporal dissection of the human nucleolar proteome using confocal microscopy. In total, 1,318 nucleolar proteins were identified; 287 were localized to fibrillar components, and 157 were enriched along the nucleoplasmic border, indicating a potential fourth nucleolar subcompartment: the nucleoli rim. We found 65 nucleolar proteins (36 uncharacterized) to relocate to the chromosomal periphery during mitosis. Interestingly, we observed temporal partitioning into two recruitment phenotypes: early (prometaphase) and late (after metaphase), suggesting phase-specific functions. We further show that the expression ofMKI67 is critical for this temporal partitioning. We provide the first proteome-wide analysis of intrinsic protein disorder for the human nucleolus and show that nucleolar proteins in general, and mitotic chromosome proteins in particular, have significantly higher intrinsic disorder level compared to cytosolic proteins. In summary, this study provides a comprehensive and essential resource of spatiotemporal expression data for the nucleolar proteome as part of the Human Protein Atlas.
|
|
