The human secretome

The proteins secreted by human cells (collectively referred to as the secretome) are important not only for the basic understanding of human biology but also for the identification of potential targets for future diagnostics and therapies. Here, we present a comprehensive analysis of proteins predicted to be secreted in human cells, which provides information about their final localization in the human body, including the proteins actively secreted to peripheral blood. The analysis suggests that a large number of the proteins of the secretome are not secreted out of the cell, but instead are retained intracellularly, whereas another large group of proteins were identified that are predicted to be retained locally at the tissue of expression and not secreted into the blood. Proteins detected in the human blood by mass spectrometry-based proteomics and antibody-based immuno-assays are also presented with estimates of their concentrations in the blood. The results are presented in an updated version 19 of the Human Protein Atlas in which each gene encoding a secretome protein is annotated to provide an open-access knowledge resource of the human secretome, including body-wide expression data, spatial localization data down to the single-cell and subcellular levels, and data about the presence of proteins that are detectable in the blood

Spatiotemporal characterization of the human proteome

Characterizing the molecular components of the basic unit of life; the cell, is crucial for a complete understanding of human biology. The cell is divided into compartments to create a suitable environment for the resident proteins to fulfill their functions. Therefore, spatial mapping of the human proteome is essential to understand protein function in health and disease.   Spatial proteomics is most commonly investigated using mass spectrometry or imaging, combined with machine learning for the data analysis. Until now, studies have been limited to high abundant proteins and relied on the purification of organelle fractions from a bulk of cells. Within the scope of this thesis, we were able to systematically localize proteins in their native cellular environment using antibody-based imaging techniques, and to investigate protein subcellular localization and dynamics on a single cell level, introducing a major advance within the field of spatial proteomics.   Paper I of this thesis presents a subcellular map of the human proteome, where the spatial distribution of 12,003 human proteins was mapped into 30 subcellular structures, half of which were not previously localized. Besides providing a valuable dataset for cell biology, this study is the first to reveal the spatial complexity of human cells with proteins localizing to multiple compartments and pronounced single cell variations. Paper II reports on the systematic temporal dissection of these single cell variations and the identification of cell cycle correlated variations. We identified 258 novel cell cycle regulated proteins and showed that several of these proteins may be connected to proliferative diseases. A key finding of Paper II is that proteins showing non-cell cycle dependent variations are significantly enriched in mitochondria, whereas cell cycle dependent proteins are enriched in nucleoli. In Paper III and IV, we spatiotemporally characterized the proteomes of these two organelles, mitochondria and nucleoli, in greater detail. In Paper III, we expanded the mitochondrial proteome with 560 novel proteins. As many as 20% of the mitochondrial proteome showed variations in their expression pattern at the single cell level, most often independent of the cell cycle. Paper IV provides a complete characterization of the nucleolar proteome. Nucleoli are not only important for ribosome synthesis and assembly, but are also crucial for cell cycle regulation through the recruitment of its proteins to the chromosomal periphery during cell division. Here, we presented the first proteome-wide spatiotemporal analysis of the nucleolus with its sub-compartments, and identified 69 nucleolar proteins that relocated to the chromosomes periphery during mitosis.   In conclusion, this thesis unravels the spatiotemporal proteome organization of the human cell over the course of a cell cycle and offers a valuable starting point for a better understanding of human cell biology in health and disease.QC 2019-10-04</p

Mapping the nucleolar proteome reveals a spatiotemporal organization related to intrinsic protein disorder

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 of MKI67 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

Mapping the nucleolar proteome reveals a spatiotemporal organization related to intrinsic protein disorder

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 of MKI67 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

Comparative cell cycle transcriptomics reveals synchronization of developmental transcription factor networks in cancer cells

<div><p>The cell cycle coordinates core functions such as replication and cell division. However, cell-cycle-regulated transcription in the control of non-core functions, such as cell identity maintenance through specific transcription factors (TFs) and signalling pathways remains unclear. Here, we provide a resource consisting of mapped transcriptomes in unsynchronized HeLa and U2OS cancer cells sorted for cell cycle phase by Fucci reporter expression. We developed a novel algorithm for data analysis that enables efficient visualization and data comparisons and identified cell cycle synchronization of Notch signalling and TFs associated with development. Furthermore, the cell cycle synchronizes with the circadian clock, providing a possible link between developmental transcriptional networks and the cell cycle. In conclusion we find that cell cycle synchronized transcriptional patterns are temporally compartmentalized and more complex than previously anticipated, involving genes, which control cell identity and development.</p></div

E2F1-controlled gene expression is compartmentalized.

<p>(A-D) Comparative analysis of E2F (A, C) and non-E2F targets (B, D) was performed using both the HeLa-Fucci and U2OS-Fucci cell cycle-dependent transcriptomes by plotting θ-values, with expression groups 2–5 highlighted by a pink box (A, B), and a distribution analysis with a log-likelihood ratio statistical comparison using the HeLa-Fucci cell θ-values (C, D). (E-H) mRNA expression in the HeLa-Fucci data set (RPKM), and protein levels as Tukey boxplots of average antibody intensities per cell nucleus, subdivided by cell cycle phase according to the quantification of Fucci reporters using fluorescent imaging. Error bars denote SEM. (I) An example of known temporal relationships among cell cycle-controlled TFs, verified by our data.</p

Transcriptional networks in G2/M-G1 phases are associated with developmental programmes.

<p>(A, B) Circular plot of θ and r coordinates for selected cell type-specific TF subfamilies expressed in (A) Hela-Fucci cells or (B) U2OS-Fucci cells (FDR ≤0.001, logCPM ≥1, FC ≥1.5). (C, D) GO enrichment analysis of the identified oscillating TFs against a background of all TFs. (E) NOTCH mRNA expression levels (RPKM) in HeLa-Fucci and U2OS-Fucci cells. (F) Representative western blot of total full-length (FL) NOTCH2 and the transmembrane/intracellular region (NTM/ICD) in sorted HeLa-Fucci cells. (G) Quantitation of western blot data for total NOTCH2 protein expression relative to the unsorted sample (Student’s t-test; * p<0.05). (H, J, K) mRNA expression of Notch signalling target genes HES7, NRARP and LFNG in the HeLa-Fucci data set (RPKM). (I) Map of a Notch-dependent oscillator as expressed during embryonic somitogenesis, indicating the key oscillators HES7, NRARP and LFNG. (L-M) Examples of known relationships between TFs identified to oscillate in synchrony with the cell cycle in the (L) HeLa-Fucci and (M) U2OS-Fucci data sets. Error bars denote SEM.</p

Large TF families oscillate and show differential distribution during the cell cycle.

<p>(A-D) θ-value plots for all TFs and TF families with a significantly differing pattern in (A, C) HeLa-Fucci cells and (B, D) U2OS-Fucci cells (FDR ≤0.001; logCPM ≥1; FC ≥1.5). (E) θ-value plot of cell-cycle-synchronized TFs in HeLa-Fucci cells versus U2OS-Fucci cells, with suggested phase-specific expression groups denoted I-VI and the main TFs involved in G1 restriction and onset of S phase indicated in red. (F) Schematic showing how repressor activity may shape transcriptional boundaries during the cell cycle, exemplified by E2F7/8 repression of E2F1/2 expression.</p

The circadian clock transcriptional network is synchronized with the cell cycle.

<p>(A) Schematic illustrating the feedback loops of the circadian clock oscillators. (B) Plot of the θ-value for core circadian genes in HeLa-Fucci cells (p-value≤0.001). (C) Protein expression levels of core components of the circadian clock in HeLa-Fucci cells analysed by correlating fluorescent immunostaining intensity to cell cycle phase determined by Fucci reporters or DNA content (DAPI); bars represent the mean of the logarithmic intensity of cells relative the average mean logarithmic intensity of all cells. Error bars denote SEM. (D) Comparison between cell cycle oscillating transcripts in HeLa-Fucci cells (FDR≤0.001) and a published circadian clock transcriptome in non-proliferating liver cells[<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0188772#pone.0188772.ref055" target="_blank">55</a>]. (E) Plot of the θ-values for core circadian genes in HeLa-Fucci cells (FDR≤0.001) versus the circadian peak values in liver cells reported by Yoshitane H, <i>et al</i>. 2014. (F) Proposed model of the integration of cell cycle, circadian clock and genes associated with development found to be synchronized with the cell cycle.</p