Intermitotic Time Research Articles

The role of mitosis in generating fitness heterogeneity.

Cancer cells have heterogeneous fitness, and this heterogeneity stems from genetic and epigenetic sources. Here, we sought to assess the contribution of asymmetric mitosis (AM) and time on the variability of fitness in sister cells. Around one quarter of sisters had differences in fitness, assessed as the intermitotic time (IMT), from 330 to 510 min. Phenotypes related to fitness, such as ERK activity (herein referring to ERK1 and ERK2, also known as MAPK3 and MAPK1, respectively), DNA damage and nuclear morphological phenotypes were also asymmetric at mitosis or turned asymmetric over the course of the cell cycle. The ERK activity of mother cell was found to influence the ERK activity and the IMT of the daughter cells, and cells with ERK asymmetry at mitosis produced more offspring with AMs, suggesting heritability of the AM phenotype for ERK activity. Our findings demonstrate how variabilities in sister cells can be generated, contributing to the phenotype heterogeneities in tumor cells.

Intracellular Crowding by Bio-Orthogonal Hydrogel Formation Induces Reversible Molecular Stasis.

To survive extreme conditions, certain animals enter a reversible protective stasis through vitrification of the cytosol by polymeric molecules such as proteins and polysaccharides. In this work, synthetic gelation of the cytosol in living cells is used to induce reversible molecular stasis. Through the sequential lipofectamine-mediated transfection of complementary poly(ethylene glycol) macromers into mammalian cells, intracellular crosslinking occurs through bio-orthogonal strain-promoted azide-alkyne cycloaddition click reactions. This achieves efficient polymer uptake with minimal cell death (99% viable). Intracellular crosslinking decreases DNA replication and protein synthesis, and increases the quiescent population by 2.5-fold. Real-time tracking of single cells containing intracellular crosslinked polymers identifies increases in intermitotic time (15 hvs 19 h) and decreases in motility (30 µm h-1 vs 15µm h-1 ). The cytosol viscosity increases threefold after intracellular crosslinking and results in disordered cytoskeletal structure in addition to the disruption of cellular coordination in a scratch assay. By incorporating photodegradable nitrobenzyl moieties into the polymer backbone, the effects of intracellular crosslinking are reversed upon exposure to light, thereby restoring proliferation (80% phospho-Rb+ cells), protein translation, and migration. Reversible intracellular crosslinking provides a novel method for dynamic manipulation of intracellular mechanics, altering essential processes that determine cellular function.

Data Driven Cell Cycle Model to Quantify the Efficacy of Cancer Therapeutics Targeting Specific Cell-Cycle Phases From Flow Cytometry Results.

Many chemotherapeutic drugs target cell processes in specific cell cycle phases. Determining the specific phases targeted is key to understanding drug mechanism of action and efficacy against specific cancer types. Flow cytometry experiments, combined with cell cycle phase and division round specific staining, can be used to quantify the current cell cycle phase and number of mitotic events of each cell within a population. However, quantification of cell interphase times and the efficacy of cytotoxic drugs targeting specific cell cycle phases cannot be determined directly. We present a data driven computational cell population model for interpreting experimental results, where in-silico populations are initialized to match observable results from experimental populations. A two-stage approach is used to determine the efficacy of cytotoxic drugs in blocking cell-cycle phase transitions. In the first stage, our model is fitted to experimental multi-parameter flow cytometry results from untreated cell populations to identify parameters defining probability density functions for phase transitions. In the second stage, we introduce a blocking routine to the model which blocks a percentage of attempted transitions between cell-cycle phases due to therapeutic treatment. The resulting model closely matches the percentage of cells from experiment in each cell-cycle phase and division round. From untreated cell populations, interphase and intermitotic times can be inferred. We then identify the specific cell-cycle phases that cytotoxic compounds target and quantify the percentages of cell transitions that are blocked compared with the untreated population, which will lead to improved understanding of drug efficacy and mechanism of action.

Hidden heterogeneity and circadian-controlled cell fate inferred from single cell lineages

The origin of lineage correlations among single cells and the extent of heterogeneity in their intermitotic times (IMT) and apoptosis times (AT) remain incompletely understood. Here we developed single cell lineage-tracking experiments and computational algorithms to uncover correlations and heterogeneity in the IMT and AT of a colon cancer cell line before and during cisplatin treatment. These correlations could not be explained using simple protein production/degradation models. Sister cell fates were similar regardless of whether they divided before or after cisplatin administration and did not arise from proximity-related factors, suggesting fate determination early in a cell’s lifetime. Based on these findings, we developed a theoretical model explaining how the observed correlation structure can arise from oscillatory mechanisms underlying cell fate control. Our model recapitulated the data only with very specific oscillation periods that fit measured circadian rhythms, thereby suggesting an important role of the circadian clock in controlling cellular fates.

Abstract 2833: Single-cell imaging reveals MAPK pathway reactivation in drug-tolerant melanoma cells

Abstract Spontaneous genetic mutations allow an initially drug-sensitive population of cancer cells to acquire a drug-resistant phenotype. However, little is known about how drug-sensitive cells first evade drug action and survive in the presence of drug, referred to as "drug tolerance," a crucial step on the road to resistance. In this study, we combined single-cell time-lapse microscopy and MATLAB-based automated cell tracking to identify the molecular basis of drug tolerance. By simultaneously monitoring CDK2 and ERK activity in single cells, we found that melanoma cells harboring a BRAF-V600E mutation have high ERK activity and consecutively cycled with an inter-mitotic time of around 14 hr in full growth media. Upon treatment with dabrafenib, an ATP competitive B-Raf inhibitor, all cells entered a CDK2-low quiescence with reduced ERK activity. Strikingly, after 72 hr of dabrafenib treatment, a fraction of cells escaped drug action, re-entered the cell cycle, and divided once in presence of drug before re-entering a transient quiescence. Additional cells continued to escape and divide in the presence of drug, with a steady-state level of about 10% of the population engaged in the cell cycle at any point during the week-long observation period. We refer to cells that re-entered the cell cycle as "escapees" and cells that stayed in quiescence during the observation period as "non-escapees." Remarkably, we found that escapees showed significantly higher ERK activity than non-escapees after a few days of treatment, even though their initial ERK activities were indistinguishable. To test whether reactivation of the MAPK pathway is the cause of cell cycle re-entry, we co-treated cells with dabrafenib and the MEK inhibitor trametinib. This co-treatment resulted in even lower ERK activity and elimination of the escapee population. This result implies that dabrafenib, even at high doses, does not fully turn off the MAPK pathway, thereby enabling eventual escape from drug. By monitoring escaping cells at the molecular level in real time, our work thus suggests a possible mechanism for cells to develop drug tolerance in less than three days, long before acquiring genetic mutations. Citation Format: Chen Yang, Chengzhe Tian, Sabrina L. Spencer. Single-cell imaging reveals MAPK pathway reactivation in drug-tolerant melanoma cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2833.

A drift-diffusion checkpoint model predicts a highly variable and growth-factor-sensitive portion of the cell cycle G1 phase.

Even among isogenic cells, the time to progress through the cell cycle, or the intermitotic time (IMT), is highly variable. This variability has been a topic of research for several decades and numerous mathematical models have been proposed to explain it. Previously, we developed a top-down, stochastic drift-diffusion+threshold (DDT) model of a cell cycle checkpoint and showed that it can accurately describe experimentally-derived IMT distributions [Leander R, Allen EJ, Garbett SP, Tyson DR, Quaranta V. Derivation and experimental comparison of cell-division probability densities. J. Theor. Biol. 2014;358:129–135]. Here, we use the DDT modeling approach for both descriptive and predictive data analysis. We develop a custom numerical method for the reliable maximum likelihood estimation of model parameters in the absence of a priori knowledge about the number of detectable checkpoints. We employ this method to fit different variants of the DDT model (with one, two, and three checkpoints) to IMT data from multiple cell lines under different growth conditions and drug treatments. We find that a two-checkpoint model best describes the data, consistent with the notion that the cell cycle can be broadly separated into two steps: the commitment to divide and the process of cell division. The model predicts one part of the cell cycle to be highly variable and growth factor sensitive while the other is less variable and relatively refractory to growth factor signaling. Using experimental data that separates IMT into G1 vs. S, G2, and M phases, we show that the model-predicted growth-factor-sensitive part of the cell cycle corresponds to a portion of G1, consistent with previous studies suggesting that the commitment step is the primary source of IMT variability. These results demonstrate that a simple stochastic model, with just a handful of parameters, can provide fundamental insights into the biological underpinnings of cell cycle progression.

Unbiased measurements of postnatal cerebellar cortical growth interpreted quantitatively through topological constraints suggest prolonging of cell cycle time in Superficial EGL progenitors

Postnatal cerebellar folial surface area expansion promotes cerebellar cortical cytoarchitectural lamination. We developed a stream‐lined sampling scheme/work‐flow to generate objective/unbiased estimates of cerebellar surface area and volume using stereological principles. Our data demonstrate that during the proliferative phase of EGL and folial surface area expansion, EGL thickness does not change and thus is a topological proxy for progenitor self‐renewal. These topological constraints indicate that during proliferative phases, migration out of the EGL is balanced by self‐renewal. Progenitor self‐renewal must therefore include mitotic events yielding either two cells in the same layer to increase surface area (b‐events) and mitotic events yielding two cells, with one cell in a superficial layer and one cell in a deeper layer (a‐events). Using a mathematical model constrained by these macroscopic observations, we were able to relate easily‐obtained global measurements of volume and surface area to the underlying cellular physiology. We used this overall method to quantify the lengthening of inter‐mitotic times for b‐events on a per‐cell basis. Similar methodology may prove useful by providing another layer of depth to the interpretation of results from stereological studies.

Mitotic Events in Cerebellar Granule Progenitor Cells That Expand Cerebellar Surface Area Are Critical for Normal Cerebellar Cortical Lamination in Mice

Late embryonic and postnatal cerebellar folial surface area expansion promotes cerebellar cortical cytoarchitectural lamination. We developed a streamlined sampling scheme to generate unbiased estimates of murine cerebellar surface area and volume using stereologic principles. We demonstrate that, during the proliferative phase of the external granular layer (EGL) and folial surface area expansion, EGL thickness does not change and thus is a topological proxy for progenitor self-renewal. The topological constraints indicate that, during proliferative phases, migration out of the EGL is balanced by self-renewal. Progenitor self-renewal must, therefore, include mitotic events yielding 2 cells in the same layer to increase surface area (β events) and mitotic events yielding 2 cells, with 1 cell in a superficial layer and 1 cell in a deeper layer (α events). As the cerebellum grows, therefore, β events lie upstream of α events. Using a mathematical model constrained by the measurements of volume and surface area, we could quantify intermitotic times for β events on a per-cell basis in postnatal mouse cerebellum. Furthermore, we found that loss of CCNA2, which decreases EGL proliferation and secondarily induces cerebellar cortical dyslamination, shows preserved α-type events. Thus, CCNA2-null cerebellar granule progenitor cells are capable of self-renewal of the EGL stem cell niche; this is concordant with prior findings of extensive apoptosis in CCNA2-null mice. Similar methodologies may provide another layer of depth to the interpretation of results from stereologic studies.

How long does it take a cell to divide?

This is one of the oldest questions asked in cell biology. Some bacterial cells can divide in as few as 20 min. The life cycle of many mammalian cells in culture takes >10 h to complete. One of the earliest techniques for determining cell growth rates is by measuring the number of cells in a culture versus time. The number of adherent cells can be measured at inoculation of a culture and again at a single succeeding time point. For suspension cultures, the culture can be sampled at numerous time points to provide a better estimate of the growth rate. These methods assume that all of the cells are playing the game, that is, that they are all growing and that none are in Go or are dying/dead. Newer methods focus on labeling of molecules within cells that are associated with specific stages of the cell cycle 1-4. The article by Summers et al. appearing in this issue of Cytometry Part A (page 385) presents a novel approach to determining cell division times. It involves recording over time a series of images of a field in a monolayer cell culture, identifying mitotic cells, and applying a non-homogeneous Poisson-based analysis to determine the inter-mitotic times. Low magnification images of a region of cells growing in a tissue culture flask are recorded at 15 min intervals. The only information extracted from the images is the presence and location of mitotic cells. This is accomplished by identifying the morphology of the mitotic cells, which is circular, as they lift off of the surface of the dish. The circular morphology is easily recognized manually as it uniquely identifies mitotic cells. An image analysis protocol was also developed to automate identification of the mitotic cells. It located 87% of the mitotic cells found manually. This approach eliminates tedious analytical methods often necessary to extract biologically relevant information from cellular images. The second novel aspect of this article is the analytical procedure—non-homogeneous Poisson time series analysis—used to determine the inter-mitotic times. When cytometrists think of Poisson statistics they usually think of counting statistics: the standard deviation of the number of events. That measure of uncertainty is applicable to the number of counts in each channel of a histogram—be it univariate or bivariate. However, that is not the Poisson statistical analysis used in this article. In order to understand the non-homogeneous Poisson analysis, it is illustrative to first describe a situation in which homogeneous Poisson analysis applies. A homogeneous Poisson process is one in which events occur at a non-varying rate and there is no memory in the system, i.e., the events are independent. An example of this is the decay of a very large number of radioactive nuclei with a very long lifetime. The decay rate is constant over the course of any measurement. The data recorded are the times of detected decay events. The lifetime is then determined by forming the distribution of times between detected decays. This time interval distribution is a negative exponential whose exponent is proportional to the radioactive lifetime. Thus, it is possible to measure very long lifetimes by recording the times of detected decays and transforming that data into an inter-time distribution. Direct measurement of the decay rate is impossible for long lifetimes, say a million years. For a phenomenon described by a non-homogeneous Poisson time series, the event rate is not constant. For the data analyzed in this article, the time series of the appearance of mitotic figures in a cell culture, the rate of detection of the mitotic figures increases with time as the measurements progress. That is, the event rate is not constant over time and the homogeneous Poisson approach does not apply. The analysis presented determines the inter-mitotic division times and is used to detect cell synchronization and quantify the degree of synchronization. What future developments might we expect? In the area of data acquisition, a fully automated identification of mitotic figures with 100% efficiency should be possible 5-7. The mitotic cell detection method presented is only applicable to growth of cells attached to a substrate. What about suspension cultures? By sequentially analyzing a fixed volume of such a culture by flow cytometry and identifying the mitotic cells, a similar analysis could be performed.

Flow-Based Cytometric Analysis of Cell Cycle via Simulated Cell Populations

We present a new approach to the handling and interrogating of large flow cytometry data where cell status and function can be described, at the population level, by global descriptors such as distribution mean or co-efficient of variation experimental data. Here we link the “real” data to initialise a computer simulation of the cell cycle that mimics the evolution of individual cells within a larger population and simulates the associated changes in fluorescence intensity of functional reporters. The model is based on stochastic formulations of cell cycle progression and cell division and uses evolutionary algorithms, allied to further experimental data sets, to optimise the system variables. At the population level, the in-silico cells provide the same statistical distributions of fluorescence as their real counterparts; in addition the model maintains information at the single cell level. The cell model is demonstrated in the analysis of cell cycle perturbation in human osteosarcoma tumour cells, using the topoisomerase II inhibitor, ICRF-193. The simulation gives a continuous temporal description of the pharmacodynamics between discrete experimental analysis points with a 24 hour interval; providing quantitative assessment of inter-mitotic time variation, drug interaction time constants and sub-population fractions within normal and polyploid cell cycles. Repeated simulations indicate a model accuracy of ±5%. The development of a simulated cell model, initialized and calibrated by reference to experimental data, provides an analysis tool in which biological knowledge can be obtained directly via interrogation of the in-silico cell population. It is envisaged that this approach to the study of cell biology by simulating a virtual cell population pertinent to the data available can be applied to “generic” cell-based outputs including experimental data from imaging platforms.

Exponentially modified Gaussian (EMG) relevance to distributions related to cell proliferation and differentiation

Positively skewed distributions common in biology are often approximated with lognormal or gamma functions. It is shown here that for some classes of phenomena, including intermitotic time and protein expression variabilities, exponentially modified Gaussian (EMG) may provide better fit. EMG is generated by processes involving normally distributed entry rates and exponentially distributed exit rates; therefore, its parameters may be straightforwardly interpreted in biologically meaningful terms and thus may help to choose between theoretical models of the respective phenomena. In particular, EMG is consistent with the transition probability model of cell cycle and may be used to estimate its deterministic and probabilistic parts. EMG is also consistent with the assumption that the probabilistic part is determined by competing stochastic transcriptional events committing cells to proliferative mitoses, differentiation, or apoptosis. Discrete event simulation modelling of this situation suggests that cell differentiation rate is primarily increased by decreasing the frequencies of the events that result in the realisation of the competing options, including proliferation, rather than by the direct changes in the differentiation-inducing events.

Growth kinetics of human large bowel cancer growing in immune-deprived mice and some chemotherapeutic observations.

Xenografts of human large bowel cancer have been grown in immune-deprived mice. Studies have been made of their intermitotic time and other proliferative characteristics, and their response to single doses of a number of chemotherapeutic agents has been measured. The indications from this study are that, although the growth rate of xenografts is much faster than that for tumors in man, this is likely to be due largely to a difference in rate of cell loss, and the intermitotic time and growth fraction may not have changed substantially. The spectrum of response to chemotherapeutic agents is in line with clinical experience and, although there are many uncertainties and problems still to be resolved, it is indicated that xenografts could provide a useful experimental system for the laboratory study of the chemotherapy of large bowel cancer.

Rapid turnover of effector-memory CD4(+) T cells in healthy humans.

Memory T cells can be divided into central–memory (TCM) and effector–memory (TEM) cells, which differ in their functional properties. Although both subpopulations can persist long term, it is not known whether they are maintained by similar mechanisms. We used in vivo labeling with deuterated glucose to measure the turnover of CD4+ T cells in healthy humans. The CD45R0+CCR7− TEM subpopulation was shown to have a rapid proliferation rate of 4.7% per day compared with 1.5% per day for CD45R0+CCR7+ TCM cells; these values are equivalent to average intermitotic (doubling) times of 15 and 48 d, respectively. In contrast, the CD45RA+CCR7+ naive CD4+ T cell population was found to be much longer lived, being labeled at a rate of only 0.2% per day (corresponding to an intermitotic time of approximately 1 yr). These data indicate that human CD4+ TEM cells constitute a short-lived cell population that requires continuous replenishment in vivo.

Persistence of foreign cells: microchimerism in the healthy adult

The lifespan of our own cells is a curiously muddy area of medical science. If we are to correct genes, transplant new tissues or correct biochemical defects in individuals we need more information on such cellular ecology: what are the cellular birth rates, intermitotic times and death rates? We need to know the same parameters for populations of foreign cells too, as we are born with a population of circulating maternal cells and probably acquire more from breast-feeds and therapeutic interventions such as blood transfusions or transplants.

TGFbeta1 induces a cell-cycle-dependent increase in motility of epithelial cells.

We have previously shown that addition of type 1 transforming growth factor-beta (TGFbeta1) to an exponentially growing population of mink lung CCl64 cells increases their average intermitotic time from 14.4 to 20.3 hours, predominantly by extending G1 from 7.5 to 13.5 hours. Here we have used the DRIMAPS system (digitally recorded interference microscopy with automatic phase-shifting) for obtaining data on cellular mass distribution, cell motility and morphology. We found no significant change in the cells' rate of mass increase following TGFbeta1 treatment, which implies that the treated cells attained a higher mass during their extended cell cycle and this was confirmed by direct measurement of cell size. However, the cells showed a dramatic motile response to treatment: TGFbeta1-treated cells had a significantly higher time-averaged speed of 36.2 microm hour-1 compared to 14.5 microm hour-1 for the control cells. The time course of the response was gradual, reaching a maximum mean speed of 52.6 microm hour-1 after 15 hours exposure. We found that the gradual onset of the response was probably not due to a slow accumulation of a secondary factor but because cells were dividing throughout the experiment and most of the response to TGFbeta1 occurred only after the first cell division in its presence. Thus, taking only those cells that had not yet divided, the time-averaged speed of treated cells (26.1 micrometer hour-1) was only moderately higher than that of untreated cells (14.9 micrometer hour-1) whereas, for those cells that had divided, the difference in speed between treated cells (45.1 micrometer hour-1) and untreated cells (14.1 microm hour-1) was much greater. Increased speed was a consequence of enhanced protrusion and retraction of the cell margin coupled with an increase in cell polarity. TGFbeta1 also increased the mean spreading of the cells, measured as area-to-mass ratio, from 3.2 to 4.4 micrometer2 pg-1, and the intracellular mass distribution became more asymmetric. The observations indicate that a G2 signal may be necessary to reach maximal motility in the presence of TGFbeta1.

Embryonic cell commitment by a simultaneous alteration in nucleo/cytoplasmic ratio in sibling cells between subsequent cell cycles.

Studies on murine embryonal carcinoma (EC) cell lines have revealed a mechanism for commitment of early embryonic cells. By means of a particular intraclonal cell surface glycoprotein and intermitotic time heterogeneity found in the EC lines used, we have devised a cell cycle model and written a computer program for cell cycle stimulation. In the present investigation experimental tissue culture data obtained from the EC lines were inserted into the computer program and the simulations represent a good fit to experimental data. It is shown that the dynamics of the driving forces in the 'cell growth cycle' and the 'DNA-division cycle', when assumed to be loosely coupled and analyzed in subsequent cell cycles, reveal a mechanism that can commit the mother cell to impel her daughter cells into the next stage in embryonic development by altering the relationship between those two uncoupled subcycles. Thereby the nucleo/cytoplasmic ratio (DNA/mass) is altered in a similar way in the two daughter cells. The simulations increase the reliability of the model and open up possibilities to test other embryonic cell systems.

Keratins (Kl6 and Kl7) as markers of keratinocyte hyperproliferation in psoriasis in vivo and in vitro

Keratinocyte differentiation in psoriasis was examined using a panel of monospecific monoclonal antibodies to keratins (K), including two recently developed monoclonal antibodies raised to carboxy terminal peptides of K6 (LL020) and K16 (LL025). Keratinocytes from normal skin, untreated psoriatic plaques and non-lesional psoriatic skin, were cultured using multiple in vitro systems. Time-lapse cinephotography was used to measure the intermitotic time of normal and psoriatic keratinocytes in both low calcium-defined and serum-containing media. The intermitotic time did not differ significantly between psoriatic and normal keratinocytes. Keratin expression of psoriatic and normal keratinocytes in vitro was examined by both gel electrophoresis and immunocytochemistry. K6, K16 and K17 were detected suprabasally in all culture systems in vitro, but only in interfollicular psoriatic epidermis in vivo, and not in normal skin. Small subpopulations of keratinocytes expressed simple epithelial keratins K7, K8, K18 and K19 in cultures on plastic substrates, but these keratins were absent in skin equivalents of normal or psoriatic skin. No psoriasis-specific pattern of differentiation was found in vitro. As the K6 peptide antibody reacted with basal cells of normal skin, probably due to K5 cross-reactivity, K16 expression determined by LL025 was found to be the most sensitive indicator of the psoriatic state of differentiation, and this antibody is recommended for future work on psoriasis. K17 had a distinct pattern of tissue distribution in normal skin: K17, but not K16, was present in basal myoepithelial cells in sweat glands, and the deep outer root sheath, but K17 distribution paralleled that of K16 in suprabasal psoriatic epidermis. As keratins K6, K16 and K17 are expressed in keratinocyte hyperproliferation, when high levels of certain cytokines are also expressed, the role of growth factors and regulatory nuclear transcription factors in the control of K6, K16 and K17 expression in psoriasis requires further study, in order to provide insight into the relationship between proliferation and differentiation.

Patterns of oscillation during mitosis in plasmodia ofPhysarum polycephalum

The rhythmic contraction pattern in plasmodia ofPhysarum polycephalum was studied to determine whether characteristic changes occur during the synchronized nuclear division. An electrical method that measures the contraction rhythm in situ during several cell cycles was used. Biopsies of the plasmodia were taken at 17 min intervals for precise determination of the cell cycle stages and were correlated with the simultaneously measured contraction rhythm. All measurements were performed in a temperature controlled environment (27 °C) at 100% relative humidity with the plasmodia (less than 24 h old) growing on a semi-defined agar medium. A total of 14 different plasmodia have been examined, and on one occasion the plasmodium was followed through 3 subsequent mitoses. The mitotic stages were identified with aceto-orcein coloring techniques and by fluorescence methods. Except for a few cases where a mitotic asynchrony of 2–3 min was observed, the mitotic events occurred simultaneously in the nuclei within a single plasmodium. Both the occurrence of the first mitosis after inoculation and the intermitotic times were highly variable. Our study indicates that the contraction rhythm in plasmodia ofPhysarum is unperturbed during the synchronized nuclear division. However, in 5 of the 17 examined mitoses an amplitude decay was observed. We discuss possible explanations for the obtained results with emphasis on the applied techniques, interpretation of the oscillation patterns, and possible restrictions in the cell itself.

Existence of a commitment program for mitosis in early G1 in tumour cells

The proliferation of normal non-tumourigenic mouse fibroblasts is stringently controlled by regulatory mechanisms located in the postmitotic stage of G1 (which we have designated G1pm). Upon exposure to growth factor depletion or a lowered de novo protein synthesis, the normal cells leave the cell cycle from G1pm and enter G0. The G1 pm phase is characterized by a remarkably constant length (the duration of which is 3 h in Swiss 3T3 cells), whereas the intercellular variability of intermitotic time is mainly ascribable to late G1 or pre S phase (G1ps) (Zetterberg & Larsson (1985) Proc. Natl. Acad. Sci. USA 82, 5365). As shown in the present study two tumour-transformed derivatives of mouse fibroblasts, i.e. BPA31 and SVA31, did not respond at all, or only responded partially, respectively, to serum depletion and inhibition of protein synthesis. If the tumour cells instead were subjected to 25-hydroxycholesterol (an inhibitor of 3-hydroxy-3 methyglutaryl coenzyme A reductase activity), their growth was blocked as measured by growth curves and [3H]-thymidine uptake. Time-lapse analysis revealed that the cells were blocked specifically in early G1 (3-4 h after mitosis), and DNA cytometry confirmed that the arrested cells contained a G1 amount of DNA. Closer kinetic analysis revealed that the duration of the postmitotic phase containing cells responsive to 25-hydroxycholesterol was constant. These data suggest that transformed 3T3 cells also contain a 'G1pm program', which has to be completed before commitment to mitosis. By repeating the experiments on a large number of tumour-transformed cells, including human carcinoma cells and glioma cells, it was demonstrated that all of them possessed a G1pm-like stage. Our conclusion is that G1pm is a general phenomenon in mammalian cells, independent of whether the cells are normal or neoplastic.

Initiation of growth inhibition by TGFβ1 is unlikely to occur in G1

Type beta transforming growth factors represent a family of polypeptides that modulate growth and differentiation. They exert their effect on target cells through interaction with multiple cell surface receptors. Transforming growth factor-beta 1 has a strong inhibitory action on cell division in mink lung CC164 cells, a process that is initiated by immediate induction of junB and phosphorylation of nuclear protein followed by a reduced expression of cdk4. However, its signal transduction pathways are still unresolved. In this study we report a detailed analysis of cell kinetic events following addition of transforming growth factor-beta 1 to mink lung CCL64 cells. We show that transforming growth factor-beta 1 reduces [3H]thymidine incorporation after a delay of 8 hours, which reaches its nadir at 16 hours. The reduced growth rate is maintained for at least 48 hours as shown by flow cytometric analysis of DNA content. Using time-lapse video microscopy it was shown that control cells double on average every 14.4 hours, whereas the transforming growth factor-beta 1-treated cells have a doubling time of on average 20.3 hours. The difference in intermitotic time is a consequence of a prolonged G1 phase (a shift from 7.5 to 13.5 hours on average). However, changes in intermitotic times occur only after cells have undergone division in the presence of transforming growth factor-beta 1 and treated cells finish the ongoing cell cycle exactly like control cells. From these findings we conclude that transforming growth factor-beta 1 may change cell cycle parameters by interfering with cellular events prior to G1.(ABSTRACT TRUNCATED AT 250 WORDS)