Minimally disturbed, multicycle, and reproducible synchrony using a eukaryotic “baby machine”

Cooper, Stephen

doi:10.1002/bies.10108

Cited by 25 publications

(23 citation statements)

References 8 publications

(10 reference statements)

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“…To date, most studies aimed at cell cycle regulated gene transcription were based on large cultures and artificial cell synchronization. We and others (Cooper, 2002, 2003) have observed that standard synchronization strategies affect cell states in unintended ways as they cause cell stress and abnormal expression profiles (Figures 1A, 2A). Our approach to collect unsynchronized individual cells avoids these issues and our data clearly demonstrate some of the benefits using single-cell analysis.…”

Section: Discussionmentioning

confidence: 91%

Cell Cycle and Cell Size Dependent Gene Expression Reveals Distinct Subpopulations at Single-Cell Level

et al. 2017

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Cell proliferation includes a series of events that is tightly regulated by several checkpoints and layers of control mechanisms. Most studies have been performed on large cell populations, but detailed understanding of cell dynamics and heterogeneity requires single-cell analysis. Here, we used quantitative real-time PCR, profiling the expression of 93 genes in single-cells from three different cell lines. Individual unsynchronized cells from three different cell lines were collected in different cell cycle phases (G0/G1 – S – G2/M) with variable cell sizes. We found that the total transcript level per cell and the expression of most individual genes correlated with progression through the cell cycle, but not with cell size. By applying the random forests algorithm, a supervised machine learning approach, we show how a multi-gene signature that classifies individual cells into their correct cell cycle phase and cell size can be generated. To identify the most predictive genes we used a variable selection strategy. Detailed analysis of cell cycle predictive genes allowed us to define subpopulations with distinct gene expression profiles and to calculate a cell cycle index that illustrates the transition of cells between cell cycle phases. In conclusion, we provide useful experimental approaches and bioinformatics to identify informative and predictive genes at the single-cell level, which opens up new means to describe and understand cell proliferation and subpopulation dynamics.

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Section: Discussionmentioning

confidence: 91%

Cell Cycle and Cell Size Dependent Gene Expression Reveals Distinct Subpopulations at Single-Cell Level

et al. 2017

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“…The released newborn cells have been found to grow synchronously with no overt evidence of growth disturbances. Although this technique has been shown to function well (e.g., Cooper 2002;Helmstetter et al 2003;Eward et al 2004a, b;Grover et al 2004), in all instances the newborn cells were collected during the first few generations of growth after transfer from batch to immobilized growth.…”

Section: Introductionmentioning

confidence: 99%

Technology for cell cycle research with unstressed steady-state cultures

et al. 2006

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A culture system for performing cell cycle analyses on cells in undisturbed steady-state populations was designed and tested. In this system, newborn cells are shed continuously from an immobilized, perfused culture rotating about the horizontal axis. As a result of this arrangement, the number of newborn cells released into the effluent medium each generation is identical to the number of cells residing in the immobilized population, indicating that one of the two new daughter cells is shed at each cell division. Thus, the immobilized cells constitute a continuous, steady-state culture because the concentrations, locations and microenvironments of the cells in the culture vessel do not vary with time. In tests with mouse L1210 lymphocytic leukemia cells, about 10 8 newborn cells were produced per day. This new culture system enables a multiplicity of cell cycle analyses on large numbers of cells assured to be from populations in steady-state growth.

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“…There are many specific mechanisms of synchronization and desynchronysation in physics and biology (see, for example [405][406][407][408][409]). We described here very simple mechanism: it requires only that the time of the life cycle is fixed, in this case in a generic situation we should observe the self-synchronization.…”

Section: Post-navier-stokes Equationsmentioning

confidence: 99%

Invariant Manifolds for Physical and Chemical Kinetics

Gorban¹,

Karlin²

2005

Lecture Notes in Physics

211

416

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Of course, it is physics. Model reduction in kinetics requires physical concepts and structures; it is impossible to make an expedient reduction of a kinetic model without thermodynamics, for example. The entropy, the Legendre transformation generated by the entropy, and the Riemann structure defined by the second differential of the entropy provide the elementary geometrical basis for the first approximation. The physical sense of the models gives many hints for their further processing. So, it is not mathematics; we care about the physical sense more than about rigorous proofs. We should deal with equations even in the absence of theorems about existence and uniqueness of solutions. Mathematics assimilates the physical notions with a considerable delay in time, but any such an assimilation leads to further insights. 1But, without doubt, it is mathematics. The story about invariant manifolds for differential equations began inside mathematics. The first significant steps were taken by two great mathematicians, A.M. Lyapunov and H. Poincaré, at the end of the XIXth century. Then N.M. Krylov and N.N. Bogolyubov, A.N. Kolmogorov, V.I. Arnold and J. Moser, J.E. Marsden, M.I. Vishik, R. Temam, and many other mathematicians developed this field of science, and many elegant theorems and useful methods were created. This is not only pure mathematics, the wide field of applications was developed too, from hydrodynamics to process engineering and control theory and methods. This is pure and applied dynamics. The language of model reduction, the basic notions that we use, the theorems and methods, all this either came from 1 The closest example: after mathematicians discovered how the entropy functional may be important for the theory of the Boltzmann equation, then they proved the existence theorem (P.L. Lions and R. DiPerna, this work was awarded the Fields medal in 1994). VIIIPreface pure and applied dynamics directly, or bears the visible imprint of its ideas and methods. Maybe the book presents a specific chapter on this subject? But, of course, the problems came from physics, from engineering. Maybe it is both physics and mathematics? Or perhaps it is something different, but what can it be? It is not so easy to answer the question, what is the subject of our book, even for the authors. But we can say what we want it to be. We want it to be a special "meeting point" of pure and applied dynamics, of physics, and of engineering sciences. This meeting point has a sufficient number of specific problems, methods and results to deserve a special name. We propose the name Model Engineering. As long as it is engineering, it is synthetic subject: if it is possible to prove something exactly, this is great, and we should follow this possibility, but if the physical sense gives us a seminal hint, well, we should use it even if the rigorous foundations are far from complete. The result is the model that works. In this enormous field of intellectual activity our book tends to be in the theoretical corner; we focus our study on c...

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Minimally disturbed, multicycle, and reproducible synchrony using a eukaryotic “baby machine”

Cited by 25 publications

References 8 publications

Cell Cycle and Cell Size Dependent Gene Expression Reveals Distinct Subpopulations at Single-Cell Level

Cell Cycle and Cell Size Dependent Gene Expression Reveals Distinct Subpopulations at Single-Cell Level

Technology for cell cycle research with unstressed steady-state cultures

Invariant Manifolds for Physical and Chemical Kinetics

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