scholarly journals Dependence of fluorodeoxyglucose (FDG) uptake on cell cycle and dry mass: a single-cell study using a multi-modal radiography platform

2019 ◽  
Author(s):  
Yongjin Sung ◽  
Marc-Andre Tetrault ◽  
Kazue Takahashi ◽  
Jinsong Ouyang ◽  
Guillem Pratx ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Cell Division ◽  
Single Cell ◽  
Hela Cells ◽  
Building Blocks ◽  
Dry Mass ◽  
Proliferation Index ◽  
Cycle Phase ◽  
Proliferative Potential ◽  
Fdg Uptake

AbstractHigh glucose uptake by cancer compared to normal tissues has long been utilized in fluorodeoxyglucose-based positron emission tomography (FDG-PET) as a contrast mechanism. The FDG uptake rate has been further related to the proliferative potential of cancer, specifically the proliferation index (PI) − the proportion of cells in S, G2 or M phases. The underlying hypothesis was that the cells preparing for cell division would consume more energy and metabolites as building blocks for biosynthesis. Despite the wide clinical use, mixed reports exist in the literature on the relationship between FDG uptake and PI. This may be due to the large variation in cancer types or methods adopted for the measurements. Of note, the existing methods can only measure the average properties of a tumor mass or cell population with highly-heterogeneous constituents. In this study, we have built a multi-modal live-cell radiography system and measured the [18F]FDG uptake by single HeLa cells together with their dry mass and cell cycle phase. The results show that HeLa cells take up twice more [18F]FDG in S, G2 or M phases than in G1 phase, which confirms the association between FDG uptake and PI at a single-cell level. Importantly, we show that [18F]FDG uptake and cell dry mass have a positive correlation in HeLa cells, which suggests that high [18F]FDG uptake in S, G2 or M phases can be largely attributed to increased dry mass, rather than the activities preparing for cell division. This interpretation is consistent with recent observations that the energy required for the preparation of cell division is much smaller than that for maintaining house-keeping proteins.

scholarly journals Dependence of fluorodeoxyglucose (FDG) uptake on cell cycle and dry mass: a single-cell study using a multi-modal radiography platform

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Yongjin Sung ◽  
Marc-Andre Tetrault ◽  
Kazue Takahashi ◽  
Jinsong Ouyang ◽  
Guillem Pratx ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Single Cell ◽  
Dry Mass ◽  
Fdg Uptake ◽  
Cell Study

scholarly journals Label-Free and Quantitative Dry Mass Monitoring for Single Cells during In Situ Culture

Cells ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1635
Author(s):  
Ya Su ◽  
Rongxin Fu ◽  
Wenli Du ◽  
Han Yang ◽  
Li Ma ◽  
...  
Keyword(s):  
Cell Growth ◽  
Single Cell ◽  
Hela Cells ◽  
Quantitative Measurement ◽  
Single Cells ◽  
Dry Mass ◽  
Quantitative Detection ◽  
Label Free ◽  
Mass Sensitivity

Quantitative measurement of single cells can provide in-depth information about cell morphology and metabolism. However, current live-cell imaging techniques have a lack of quantitative detection ability. Herein, we proposed a label-free and quantitative multichannel wide-field interferometric imaging (MWII) technique with femtogram dry mass sensitivity to monitor single-cell metabolism long-term in situ culture. We demonstrated that MWII could reveal the intrinsic status of cells despite fluctuating culture conditions with 3.48 nm optical path difference sensitivity, 0.97 fg dry mass sensitivity and 2.4% average maximum relative change (maximum change/average) in dry mass. Utilizing the MWII system, different intrinsic cell growth characteristics of dry mass between HeLa cells and Human Cervical Epithelial Cells (HCerEpiC) were studied. The dry mass of HeLa cells consistently increased before the M phase, whereas that of HCerEpiC increased and then decreased. The maximum growth rate of HeLa cells was 11.7% higher than that of HCerEpiC. Furthermore, HeLa cells were treated with Gemcitabine to reveal the relationship between single-cell heterogeneity and chemotherapeutic efficacy. The results show that cells with higher nuclear dry mass and nuclear density standard deviations were more likely to survive the chemotherapy. In conclusion, MWII was presented as a technique for single-cell dry mass quantitative measurement, which had significant potential applications for cell growth dynamics research, cell subtype analysis, cell health characterization, medication guidance and adjuvant drug development.

scholarly journals Scheduling Chemotherapy: Catch 22 between Cell Kill and Resistance Evolution

2000 ◽  
Vol 2 (3) ◽  
pp. 215-232 ◽  
Author(s):  
Shea N. Gardner
Keyword(s):  
Cell Cycle ◽  
Cell Division ◽  
Drug Exposure ◽  
Drug Application ◽  
Growth Fraction ◽  
Cycle Phase ◽  
Response Curves ◽  
Division Rate ◽  
Drug Concentrations ◽  
Cns Drugs

Dose response curves show that prolonged drug exposure at a low concentration may kill more cells than short exposures at higher drug concentrations, particularly for cell cycle phase specific drugs. Applying drugs at low concentrations for prolonged periods, however, allows cells with partial resistance to evolve higher levels of resistance through stepwise processes such as gene amplification. Models are developed for cell cycle specific (CS) and cell cycle nonspecific (CNS) drugs to identify the schedule of drug application that balances this tradeoff.The models predict that a CS drug may be applied most effectively by splitting the cumulative dose into many (>40) fractions applied by long-term chemotherapy, while CNS drugs may be better applied in fewer than 10 fractions applied over a shorter term. The model suggests that administering each fraction by continuous infusion may be more effective than giving the drug as a bolus, whether the drug is CS or CNS. In addition, tumors with a low growth fraction or slow rate of cell division are predicted to be controlled more easily with CNS drugs, while those with a high proliferative fraction or fast cell division rate may respond better to CS drugs.

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

2020 ◽  
Vol 30 (4) ◽  
pp. 611-621 ◽  
Author(s):  
Chiaowen Joyce Hsiao ◽  
PoYuan Tung ◽  
John D. Blischak ◽  
Jonathan E. Burnett ◽  
Kenneth A. Barr ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Data Analysis ◽  
Single Cell ◽  
Cell Cycle Phase ◽  
Cycle Phase ◽  
Rna Seq

The competence of cells for cell division and regeneration in tobacco explants depends on cellular location, cell cycle phase and ploidy level

Plant Science ◽  
1994 ◽  
Vol 103 (1) ◽  
pp. 81-91 ◽  
Author(s):  
Luud J.W. Gilissen ◽  
Marjo J. van Staveren ◽  
Johanna C. Hakkert ◽  
Marinus J.M. Smulders ◽  
Harrie A. Verhoeven ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Cell Division ◽  
Ploidy Level ◽  
Cell Cycle Phase ◽  
Cycle Phase ◽  
Cellular Location

Dynamically-enhanced retention of gold nanoclusters in HeLa cells following X-rays exposure: A cell cycle phase-dependent targeting approach

2016 ◽  
Vol 119 (3) ◽  
pp. 544-551 ◽  
Author(s):  
Yan Liu ◽  
Weiqiang Chen ◽  
Pengcheng Zhang ◽  
Xiaodong Jin ◽  
Xinguo Liu ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Hela Cells ◽  
Gold Nanoclusters ◽  
Cell Cycle Phase ◽  
Cycle Phase ◽  
X Rays ◽  
A Cell

scholarly journals Classic “broken cell” techniques and newer live cell methods for cell cycle assessment

2013 ◽  
Vol 304 (10) ◽  
pp. C927-C938 ◽  
Author(s):  
Lindsay Henderson ◽  
Dante S. Bortone ◽  
Curtis Lim ◽  
Alexander C. Zambon
Keyword(s):  
Cell Cycle ◽  
Cell Division ◽  
Single Cell ◽  
Living Cells ◽  
Cell Division Cycle ◽  
Live Cell ◽  
Nucleotide Analogs ◽  
Protein Ubiquitination ◽  
Cell Cycle Pathway ◽  
Cell Niche

Many common, important diseases are either caused or exacerbated by hyperactivation (e.g., cancer) or inactivation (e.g., heart failure) of the cell division cycle. A better understanding of the cell cycle is critical for interpreting numerous types of physiological changes in cells. Moreover, new insights into how to control it will facilitate new therapeutics for a variety of diseases and new avenues in regenerative medicine. The progression of cells through the four main phases of their division cycle [G0/G1, S (DNA synthesis), G2, and M (mitosis)] is a highly conserved process orchestrated by several pathways (e.g., transcription, phosphorylation, nuclear import/export, and protein ubiquitination) that coordinate a core cell cycle pathway. This core pathway can also receive inputs that are cell type and cell niche dependent. “Broken cell” methods (e.g., use of labeled nucleotide analogs) to assess for cell cycle activity have revealed important insights regarding the cell cycle but lack the ability to assess living cells in real time (longitudinal studies) and with single-cell resolution. Moreover, such methods often require cell synchronization, which can perturb the pathway under study. Live cell cycle sensors can be used at single-cell resolution in living cells, intact tissue, and whole animals. Use of these more recently available sensors has the potential to reveal physiologically relevant insights regarding the normal and perturbed cell division cycle.

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.

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