Single cell transcriptomic analysis of bloodstream form Trypanosoma brucei reconstructs cell cycle progression and differentiation via quorum sensing

2020 ◽  
Author(s):  
Mariana De Niz
Keyword(s):  
Cell Cycle ◽  
Quorum Sensing ◽  
Single Cell ◽  
Trypanosoma Brucei ◽  
Cell Cycle Progression ◽  
Transcriptomic Analysis ◽  
Bloodstream Form ◽  
Cycle Progression

scholarly journals Single-cell transcriptomic analysis of bloodstream Trypanosoma brucei reconstructs cell cycle progression and developmental quorum sensing

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Emma M. Briggs ◽  
Federico Rojas ◽  
Richard McCulloch ◽  
Keith R. Matthews ◽  
Thomas D. Otto
Keyword(s):  
Cell Cycle ◽  
Single Cell ◽  
Trypanosoma Brucei ◽  
Cell Cycle Progression ◽  
Expression Patterns ◽  
Tsetse Fly ◽  
Cycle Progression ◽  
Progressive Development ◽  
Asynchronous Development

AbstractDevelopmental steps in the trypanosome life-cycle involve transition between replicative and non-replicative forms specialised for survival in, and transmission between, mammalian and tsetse fly hosts. Here, using oligopeptide-induced differentiation in vitro, we model the progressive development of replicative ‘slender’ to transmissible ‘stumpy’ bloodstream form Trypanosoma brucei and capture the transcriptomes of 8,599 parasites using single cell transcriptomics (scRNA-seq). Using this framework, we detail the relative order of biological events during asynchronous development, profile dynamic gene expression patterns and identify putative regulators. We additionally map the cell cycle of proliferating parasites and position stumpy cell-cycle exit at early G1 before progression to a distinct G0 state. A null mutant for one transiently elevated developmental regulator, ZC3H20 is further analysed by scRNA-seq, identifying its point of failure in the developmental atlas. This approach provides a paradigm for the dissection of differentiation events in parasites, relevant to diverse transitions in pathogen biology.

Control of G1 to S cell cycle progression of Trypanosoma brucei S427c11 organisms under axenic conditions

1993 ◽  
Vol 57 (2) ◽  
pp. 241-252 ◽  
Author(s):  
Grant A. Morgan ◽  
Harrington B. Laufman ◽  
Frederick P. Otieno-Omondo ◽  
Samuel J. Black
Keyword(s):  
Cell Cycle ◽  
Trypanosoma Brucei ◽  
Cell Cycle Progression ◽  
Cycle Progression ◽  
Axenic Conditions

Identification of a protein phosphatase 2A family member that regulates cell cycle progression in Trypanosoma brucei

2014 ◽  
Vol 194 (1-2) ◽  
pp. 48-52 ◽  
Author(s):  
Karen G. Rothberg ◽  
Neal Jetton ◽  
James G. Hubbard ◽  
Daniel A. Powell ◽  
Vidya Pandarinath ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Family Member ◽  
Trypanosoma Brucei ◽  
Protein Phosphatase ◽  
Cell Cycle Progression ◽  
Protein Phosphatase 2A ◽  
Cycle Progression ◽  
Phosphatase 2A

scholarly journals Single cell transcriptomic analysis of bloodstream form Trypanosoma brucei reconstructs cell cycle progression and differentiation via quorum sensing

2020 ◽  
Author(s):  
Emma Marie Briggs ◽  
Richard McCulloch ◽  
Keith Roland Matthews ◽  
Thomas Dan Otto
Keyword(s):  
Cell Cycle ◽  
Single Cell ◽  
Trypanosoma Brucei ◽  
Expression Patterns ◽  
Life Cycles ◽  
Bloodstream Form ◽  
Cycle Phase ◽  
Mammalian Host ◽  
Marker Genes ◽  
African Trypanosomes

The life cycles of African trypanosomes are dependent on several differentiation steps, where parasites transition between replicative and non-replicative forms specialised for infectivity and survival in mammal and tsetse fly hosts. Here, we use single cell transcriptomics (scRNA-seq) to dissect the asynchronous differentiation of replicative slender to transmissible stumpy bloodstream form Trypanosoma brucei. Using oligopeptide-induced differentiation, we accurately modelled stumpy development in vitro and captured the transcriptomes of 9,344 slender and stumpy stage parasites, as well as parasites transitioning between these extremes. Using this framework, we detail the relative order of biological events during development, profile dynamic gene expression patterns and identify putative novel regulators. Using marker genes to deduce the cell cycle phase of each parasite, we additionally map the cell cycle of proliferating parasites and position stumpy cell cycle exit at early G1, with subsequent progression to a distinct G0 state. We also explored the role of one gene, ZC3H20, with transient elevated expression at the key slender to stumpy transition point. By scRNA-seq analysis of ZC3H20 null parasites exposed to oligopeptides and mapping the resulting transcriptome to our atlas of differentiation, we identified the point of action for this key regulator. Using a developmental transition relevant for both virulence in the mammalian host and disease transmission, our data provide a paradigm for the temporal mapping of differentiation events and regulators in the trypanosome life cycle.

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 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.

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