Modeling Progression of Single Cell Populations Through the Cell Cycle as a Sequence of Switches

Zinovyev, Andrei; M, Sadovsky; Calzone, Laurence; Fouché, Aziz; Groeneveld, Clarice S.; Chervov, Alexander; Barillot, Emmanuel; Gorban, Alexander N.

doi:10.3389/fmolb.2021.793912

Cited by 4 publications

(4 citation statements)

References 57 publications

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“…When passing the next boundary, the rates of change in cellular variables switch. This model was further developed (Zinovyev et al, 2022) and demonstrated strong agreement with experimental data.…”

Section: Introductionmentioning

confidence: 69%

A phenomenological model of non-genomic variability of luminescent bacterial cells

Bartsev

2023

Vestn. VOGiS

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The light emitted by a luminescent bacterium serves as a unique native channel of information regarding the intracellular processes within the individual cell. In the presence of highly sensitive equipment, it is possible to obtain the distribution of bacterial culture cells by the intensity of light emission, which correlates with the amount of luciferase in the cells. When growing on rich media, the luminescence intensity of individual cells of brightly luminous strains of the luminescent bacteria Photobacterium leiognathi and Ph. phosporeum reaches 104–105 quanta/s. The signal of such intensity can be registered using sensitive photometric equipment. All experiments were carried out with bacterial clones (genetically homogeneous populations). A typical dynamics of luminous bacterial cells distributions with respect to intensity of light emission at various stages of batch culture growth in a liquid medium was obtained. To describe experimental distributions, a phenomenological model that links the light of a bacterial cell with the history of events at the molecular level was constructed. The proposed phenomenological model with a minimum number of fitting parameters (1.5) provides a satisfactory description of the complex process of formation of cell distributions by luminescence intensity at different stages of bacterial culture growth. This may be an indication that the structure of the model describes some essential processes of the real system. Since in the process of division all cells go through the stage of release of all regulatory molecules from the DNA molecule, the resulting distributions can be attributed not only to luciferase, but also to other proteins of constitutive (and not only) synthesis.

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Section: Introductionmentioning

confidence: 69%

A phenomenological model of non-genomic variability of luminescent bacterial cells

Bartsev

2023

Vestn. VOGiS

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“…Gene expression modulation during the cell cycle can be visualized and interpreted by looking at the so-called cell cycle plots. In these plots, each cell is reduced to a small set of coordinates (typically between 2 and 4 ( 32 )), each of those corresponding to the average transcription activity of genes associated with a specific cell cycle signal (e.g. G1/S phase, G2/M phase, histones) (Figure 4A).…”

Section: Resultsmentioning

confidence: 99%

Transmorph: a unifying computational framework for modular single-cell RNA-seq data integration

Fouché

Chadoutaud

Delattre

et al. 2023

NAR Genomics and Bioinformatics

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Data integration of single-cell RNA-seq (scRNA-seq) data describes the task of embedding datasets gathered from different sources or experiments into a common representation so that cells with similar types or states are embedded close to one another independently from their dataset of origin. Data integration is a crucial step in most scRNA-seq data analysis pipelines involving multiple batches. It improves data visualization, batch effect reduction, clustering, label transfer, and cell type inference. Many data integration tools have been proposed during the last decade, but a surge in the number of these methods has made it difficult to pick one for a given use case. Furthermore, these tools are provided as rigid pieces of software, making it hard to adapt them to various specific scenarios. In order to address both of these issues at once, we introduce the transmorph framework. It allows the user to engineer powerful data integration pipelines and is supported by a rich software ecosystem. We demonstrate transmorph usefulness by solving a variety of practical challenges on scRNA-seq datasets including joint datasets embedding, gene space integration, and transfer of cycle phase annotations. transmorph is provided as an open source python package.

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“…S5A-D). Several reports recently showed that the stereotypical clocklike progression of cells through the cell cycle can be identified from single-cell RNA-seq data (13)(14)(15). Schwabe et al and Zinovyev et al both revealed that immortalized cycling cells embedded in a linear PCA space form a circular path along which they advance as a cycle (14,15).…”

Section: Deuterosomal Cells Progress Through Differentiation By Follo...mentioning

confidence: 99%

“…Several reports recently showed that the stereotypical clocklike progression of cells through the cell cycle can be identified from single-cell RNA-seq data (13)(14)(15). Schwabe et al and Zinovyev et al both revealed that immortalized cycling cells embedded in a linear PCA space form a circular path along which they advance as a cycle (14,15). PCA integration of our primary cycling progenitors (n = 759 cells) highlighted that these cycling primary cells also form a planar circular path in linear 2D space (Fig.…”

Section: Deuterosomal Cells Progress Through Differentiation By Follo...mentioning

confidence: 99%

Identification of a new cell cycle variant during multiciliated cell differentiation

Serizay,

Damaa,

Boudjema

et al. 2024

Preprint

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A complex and conserved regulatory network drives the cell cycle. Individual components of this network are sometimes used in differentiated cells, i.e. to control organelle destruction in mammalian lens cells or light response in land plants. Some differentiated cells co-opt cell-cycle regulators more largely, to increase their ploidy using a cell cycle variant named endoreplication. Using single-cell RNA-seq profiling and functional assays in differentiating multiciliated cells, we identified a novel type of cell cycle variant that supports cytoplasmic organelle, rather than nuclear content amplification. This variant operates in post-mitotic, centriole-amplifying differentiating multiciliated cells and is characterized by (i) a circular trajectory of the transcriptome, (ii) sequential expression of more than 70% of the genes involved in S, G2 and M-like progression along this trajectory, and (iii) successive waves of cyclins. This cell cycle variant is tailored by the expression of the non-canonical cyclins O and A1 - which replace the transcriptionally silent cyclins E2 and A2 - and by the silencing of the APC/C inhibitor Emi1, two switches also detected in male meiosis, another variant of the canonical cell cycle where centriole and DNA replications are uncoupled. Re-expressing Cyclin E2, cyclin A2 or Emi1 is sufficient to induce partial replication and mitosis, suggesting that change in the regulation of expression of a few cell cycle key players drives a qualitative and quantitative tuning of Cdk activity, allowing the diversion of the cell cycle in the multiciliation variant. We also propose that this new cell cycle variant relies on the existence of a cytoplasmic - or centriolar - Cdk threshold, lower than the S-phase threshold, which affects only the cytoplasmic reorganization.

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Modeling Progression of Single Cell Populations Through the Cell Cycle as a Sequence of Switches

Cited by 4 publications

References 57 publications

A phenomenological model of non-genomic variability of luminescent bacterial cells

A phenomenological model of non-genomic variability of luminescent bacterial cells

Transmorph: a unifying computational framework for modular single-cell RNA-seq data integration

Identification of a new cell cycle variant during multiciliated cell differentiation

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