scholarly journals Single-cell RNA-Seq Resolves Cellular Heterogeneity and Transcriptional Dynamics in Spermatogonial Stem Cells Establishment

2017 ◽  
Author(s):  
Jinyue Liao ◽  
Shuk Han Ng ◽  
Jiajie Tu ◽  
Alfred Chun Shui Luk ◽  
Yan Qian ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Cycle Progression ◽  
Cellular Heterogeneity ◽  
Stem Cell Marker ◽  
Expression Change ◽  
Cycle Progression ◽  
Oct4 Expression ◽  
Transcriptional Dynamics ◽  
Systematic Understanding ◽  
Developmental Dynamics

SummaryThe transition of gonocytes to spermatogonia and subsequent differentiation provide the foundation of spermatogenesis. However, systematic understanding on the cellular and molecular basis of this process is still limited, mainly impeded by the asynchrony in development and the lack of stage-specific markers. Using single-cell RNA sequencing on Oct4-GFP+/KIT- cells isolated from PND5.5 mice, we dissected the cellular heterogeneity and established molecular regulations. We demonstrated that gonocyte-spermatogonial transition was characterized by gene expression change related to apoptosis, cell cycle progression, and regulation of migration processes. Pseudotime analysis reconstructed developmental dynamics of the spermatogonial populations and unraveled sequential cellular and molecular transitions. We also identified CD87 as a neonatal stem cell marker which are potentially involved in the intial establishment of SSC pool. Lastly, we uncovered an unexpected subpopulation of spermatogonia primed to differentiation within the undifferentiated compartment, which is characterized by the lack of self-renewal genes and enhanced Oct4 expression and retinoic acid signaling response. Our study thus provides a novel understanding of cellular and molecular changes during spermatogonial establishment.

scholarly journals Characterizing and inferring quantitative cell cycle phase in single-cell RNA-seq data analysis

2019 ◽  
Author(s):  
Chiaowen Joyce Hsiao ◽  
PoYuan Tung ◽  
John D. Blischak ◽  
Jonathan E. Burnett ◽  
Kenneth A. Barr ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Single Cell ◽  
Cell Cycle Progression ◽  
Cell Types ◽  
Cell Cycle Phase ◽  
Cellular Heterogeneity ◽  
Cycle Phase ◽  
Cycle Progression ◽  
Cellular Environment

AbstractCellular heterogeneity in gene expression is driven by cellular processes such as cell cycle and cell-type identity, and cellular environment such as spatial location. The cell cycle, in particular, is thought to be a key driver of cell-to-cell heterogeneity in gene expression, even in otherwise homogeneous cell populations. Recent advances in single-cell RNA-sequencing (scRNA-seq) facilitate detailed characterization of gene expression heterogeneity, and can thus shed new light on the processes driving heterogeneity. Here, we combined fluorescence imaging with scRNA-seq to measure cell cycle phase and gene expression levels in human induced pluripotent stem cells (iPSCs). Using these data, we developed a novel approach to characterize cell cycle progression. While standard methods assign cells to discrete cell cycle stages, our method goes beyond this, and quantifies cell cycle progression on a continuum. We found that, on average, scRNA-seq data from only five genes predicted a cell’s position on the cell cycle continuum to within 14% of the entire cycle, and that using more genes did not improve this accuracy. Our data and predictor of cell cycle phase can directly help future studies to account for cell-cycle-related heterogeneity in iPSCs. Our results and methods also provide a foundation for future work to characterize the effects of the cell cycle on expression heterogeneity in other cell types.

scholarly journals A single-cell atlas of human glioblastoma reveals a single axis of phenotype in tumor-propagating cells

2018 ◽  
Author(s):  
Sören Müller ◽  
Elizabeth Di Lullo ◽  
Aparna Bhaduri ◽  
Beatriz Alvarado ◽  
Garima Yagnik ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Cycle Progression ◽  
Molecular Subtypes ◽  
Suppressor Cells ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Myeloid Derived Suppressor Cells ◽  
Cycle Progression ◽  
Anatomical Structures ◽  
Quantitative Immunohistochemistry

AbstractTumor-propagating glioblastoma (GBM) stem-like cells (GSCs) of the proneural and mesenchymal molecular subtypes have been described. However, it is unknown if these two GSC populations are sufficient to generate the spectrum of cellular heterogeneity observed in GBM. The lineage relationships and niche interactions of GSCs have not been fully elucidated. We perform single-cell RNA-sequencing (scRNA-seq) and matched exome sequencing of human GBMs (12 patients; >37,000 cells) to identify recurrent hierarchies of GSCs and their progeny. We map sequenced cells to tumor-anatomical structures and identify microenvironment interactions using reference atlases and quantitative immunohistochemistry. We find that all GSCs can be described by a single axis of variation, ranging from proneural to mesenchymal. Increasing mesenchymal GSC (mGSC) content, but not proneural GSC (pGSC) content, correlates with significantly inferior survival. All clonal expressed mutations are found in the GSC populations, with a greater representation of mutations found in mGSCs. While pGSCs upregulate markers of cell-cycle progression, mGSCs are largely quiescent and overexpress cytokines mediating the chemotaxis of myeloid-derived suppressor cells. We find mGSCs enriched in hypoxic regions while pGSCs are enriched in the tumor’s invasive edge. We show that varying proportions of mGSCs, pGSCs, their progeny and stromal/immune cells are sufficient to explain the genetic and phenotypic heterogeneity observed in GBM. This study sheds light on a long-standing debate regarding the lineage relationships between GSCs and other glioma cell types.

scholarly journals The adult stem cell marker Musashi-1 modulates endometrial carcinoma cell cycle progression and apoptosisviaNotch-1 and p21WAF1/CIP1

2011 ◽  
Vol 129 (8) ◽  
pp. 2042-2049 ◽  
Author(s):  
Martin Götte ◽  
Burkhard Greve ◽  
Reinhard Kelsch ◽  
Heike Müller-Uthoff ◽  
Kristin Weiss ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Stem Cell ◽  
Endometrial Carcinoma ◽  
Cell Cycle Progression ◽  
Carcinoma Cell ◽  
Adult Stem Cell ◽  
Stem Cell Marker ◽  
Cell Marker ◽  
Cycle Progression ◽  
Endometrial Carcinoma Cell

scholarly journals Single-cell intracellular pH measurements reveal cell-cycle linked pH dynamics

2021 ◽  
Author(s):  
Julia S Spear ◽  
Katharine A White
Keyword(s):  
Cell Cycle ◽  
Single Cell ◽  
Intracellular Ph ◽  
Cell Cycle Progression ◽  
Single Cells ◽  
Population Level ◽  
Growth Factor Signaling ◽  
Cycle Progression ◽  
Cell Behaviors ◽  
Sinusoidal Pattern

Transient changes in intracellular pH (pHi) have been shown to regulate normal cell behaviors like migration and cell-cycle progression, while dysregulated pHi dynamics are a hallmark of cancer. However, little is known about how pHi heterogeneity and dynamics influence population-level measurements or single-cell behaviors. Here, we present and characterize single-cell pHi heterogeneity distributions in both normal and cancer cells and measure dynamic pHi increases in single cells in response to growth factor signaling. Next, we measure pHi dynamics in single cells during cell cycle progression. We determined that single-cell pHi is significantly decreased at the G1/S boundary, increases from S phase to the G2/M transition, rapidly acidifies during mitosis, and recovers in daughter cells. This sinusoidal pattern of pHi dynamics was linked to cell cycle timing regardless of synchronization method. This work confirms prior work at the population level and reveals distinct advantages of single-cell pHi measurements in capturing pHi heterogeneity across a population and dynamics within single cells.

scholarly journals Predicting Individual Cell Division Events from Single-Cell ERK and Akt Dynamics

2021 ◽  
Author(s):  
Alan D Stern ◽  
Gregory R Smith ◽  
Luis C Santos ◽  
Deepraj Sarmah ◽  
Xiang Zhang ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Cell Division ◽  
Single Cell ◽  
Cell Cycle Progression ◽  
Time Window ◽  
Single Cells ◽  
Machine Learning Algorithms ◽  
Cycle Progression ◽  
Restriction Point ◽  
Activity Dynamics

Predictive determinants of stochastic single-cell fates have been elusive, even for the well-studied mammalian cell cycle. What drives proliferation decisions of single cells at any given time? We monitored single-cell dynamics of the ERK and Akt pathways, critical cell cycle progression hubs and anti-cancer drug targets, and paired them to division events in the same single cells using the non-transformed MCF10A epithelial line. Following growth factor treatment, in cells that divide both ERK and Akt activities are significantly higher within the S-G2 time window (~8.5-40 hours). Such differences were much smaller in the pre-S-phase, restriction point window which is traditionally associated with ERK and Akt activity dependence, suggesting unappreciated roles for ERK and Akt in S through G2. Machine learning algorithms show that simple metrics of central tendency in this time window are most predictive for subsequent cell division; median ERK and Akt activities classify individual division events with an AUC=0.76. Surprisingly, ERK dynamics alone predict division in individual cells with an AUC=0.74, suggesting Akt activity dynamics contribute little to the decision driving cell division in this context. We also find that ERK and Akt activities are less correlated with each other in cells that divide. Network reconstruction experiments demonstrated that this correlation behavior was likely not due to crosstalk, as ERK and Akt do not interact in this context, in contrast to other transformed cell types. Overall, our findings support roles for ERK and Akt activity throughout the cell cycle as opposed to just before the restriction point, and suggest ERK activity dynamics are substantially more important than Akt activity dynamics for driving cell division in this non-transformed context. Single cell imaging along with machine learning algorithms provide a better basis to understand cell cycle progression on the single cell level.

scholarly journals Functional oscillation of a multienzyme glucosome assembly during cell cycle progression

2022 ◽  
Author(s):  
Miji Jeon ◽  
Danielle L Schmitt ◽  
Minjoung Kyoung ◽  
Songon An
Keyword(s):  
Cell Cycle ◽  
Glucose Metabolism ◽  
Single Cell ◽  
Cell Biology ◽  
Cell Cycle Progression ◽  
Metabolic Adaptation ◽  
Dependent Manner ◽  
Cycle Progression ◽  
Size Dependent ◽  
A Cell

Glucose metabolism has been studied extensively to understand functional interplays between metabolism and a cell cycle. However, our understanding of cell cycle-dependent metabolic adaptation particularly in human cells remains largely elusive. Meanwhile, human enzymes in glucose metabolism are shown to functionally organize into three different sizes of a multienzyme metabolic assembly, the glucosome, to regulate glucose flux in a size-dependent manner. Here, using fluorescence single-cell imaging techniques, we discover that glucosomes spatiotemporally oscillate during a cell cycle in an assembly size-dependent manner. Importantly, their oscillation at single-cell levels is in accordance with functional contributions of glucose metabolism to cell cycle progression at a population level. Collectively, we demonstrate functional oscillation of glucosomes during cell cycle progression and thus their biological significance to human cell biology.

scholarly journals Disentangling Pro-mitotic Signaling during Cell Cycle Progression using Time-Resolved Single-Cell Imaging

Cell Reports ◽  
2020 ◽  
Vol 31 (2) ◽  
pp. 107514 ◽  
Author(s):  
Manuela Benary ◽  
Stefan Bohn ◽  
Mareen Lüthen ◽  
Ilias K. Nolis ◽  
Nils Blüthgen ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Single Cell ◽  
Cell Cycle Progression ◽  
Cell Imaging ◽  
Cycle Progression ◽  
Time Resolved ◽  
Single Cell Imaging

scholarly journals The Putative Cancer Stem Cell Marker USP22 Is a Subunit of the Human SAGA Complex Required for Activated Transcription and Cell-Cycle Progression

2008 ◽  
Vol 29 (1) ◽  
pp. 102-111 ◽  
Author(s):  
Xiao-Yong Zhang ◽  
Maya Varthi ◽  
Stephen M. Sykes ◽  
Charles Phillips ◽  
Claude Warzecha ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Stem Cell ◽  
Cancer Stem Cell ◽  
Cell Cycle Progression ◽  
Stem Cell Marker ◽  
Saga Complex ◽  
Cancer Stem Cell Marker ◽  
Cell Marker ◽  
Cycle Progression ◽  
A Subunit

scholarly journals Single cell transcriptomics and developmental trajectories of murine cranial neural crest cell fate determination and cell cycle progression

2021 ◽  
Author(s):  
Yu Ji ◽  
Shuwen Zhang ◽  
Kurt Reynolds ◽  
Ran Gu ◽  
Moira McMahon ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Neural Crest ◽  
Single Cell ◽  
Cell Fate ◽  
Cell Cycle Progression ◽  
Developmental Trajectories ◽  
Cell Fate Determination ◽  
Cycle Progression ◽  
Fate Determination ◽  
Neural Lineage

Cranial neural crest (NC) cells migrate long distances to populate the future craniofacial regions and give rise to various tissues, including facial cartilage, bones, connective tissues, and cranial nerves. However, the mechanism that drives the fate determination of cranial NC cells remains unclear. Using single-cell RNA sequencing combined genetic fate mapping, we reconstructed developmental trajectories of cranial NC cells, and traced their differentiation in mouse embryos. We identified four major cranial NC cell lineages at different status: pre-epithelial-mesenchymal transition, early migration, NC-derived mesenchymal cells, and neural lineage cells from embryonic days 9.5 to 12.5. During migration, the first cell fate determination separates cranial sensory ganglia, the second generates mesenchymal progenitors, and the third separates other neural lineage cells. We then focused on the early facial prominences that appear to be built by undifferentiated, fast-dividing NC cells that possess similar transcriptomic landscapes, which could be the drive for the facial developmental robustness. The post-migratory cranial NC cells exit the cell cycle around embryonic day 11.5 after facial shaping is completed and initiates further fate determination and differentiation processes. Our results demonstrate the transcriptomic landscapes during dynamic cell fate determination and cell cycle progression of cranial NC lineage cells and also suggest that the transcriptomic regulation of the balance between proliferation and differentiation of the post-migratory cranial NC cells can be a key for building up unique facial structures in vertebrates.

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