A new biomarker for mitotic cells. Cytometry A

Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio 44106, USA.
Cytometry Part A (Impact Factor: 2.93). 01/2008; 73(1):5-15. DOI: 10.1002/cyto.a.20501
Source: PubMed


Many epitopes are phosphorylated during mitosis. These epitopes are useful biomarkers for mitotic cells. The most commonly used are MPM-2 and serine 10 of histone H3. Here we investigated the use of an antibody generated against a phospho peptide matching residues 774-788 of the human retinoblastoma protein 1 (Rb) to detect mitotic cells. Human cell lines were stained with DNA dyes and antibodies reactive with epitopes defined by antibody MPM-2, phospho-S10-histone-H3, and the phospho-serine peptide, TRPPTLSPIPHIPRC (phospho-S780-Rb). Immunoreactivity and DNA content were measured by flow and image cytometry. Correlation and pattern recognition analyses were performed on list mode data. Western blots and immunoprecipitation were used to investigate the number of peptides reactive with phospho-S780-Rb and the relationship between reactivity with this antibody and MPM-2. Costaining for bromodeoxyuridine (BrdU) was used to determine acid resistance of the phospho-S780-Rb epitope. Cell cycle related phospho-S780-Rb immunofluorescence correlated strongly with that of MPM-2. Laser scanning cytometry showed that phospho-S780-Rb immunofluorescence is expressed at high levels on all stages of mitotic cells. Western blotting and immunoprecipitation showed that the epitope is expressed on several peptides including Rb protein. Costaining of BrdU showed that the epitope is stable to acid. Kinetic experiments showed utility in complex cell cycle analysis aimed at measuring cell cycle transition state timing. The phospho-S780-Rb epitope is a robust marker of mitosis that allows cytometric detection of mitotic cells beginning with chromatin condensation and ending after cytokinesis. Costaining of cells with DNA dyes allows discrimination and counting of mitotic cells and post-cytokinetic ("newborn") cells. To facilitate use without confusion about specificity, we suggest the trivial name, pS780 for this mitotic epitope.

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Available from: James W. Jacobberger
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    • "As shown in Figure 5, including this regulation allowed us to model the delay in detectable cyclin A2 levels until close to the start of S phase. Biologically, this second mechanism is likely dominant, since cells like DU-145 with inactivating mutations in Rb (resulting in constitutively active E2F) do not express appreciable cyclin A2 in G1 [73]. "
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    ABSTRACT: Few of >150 published cell cycle modeling efforts use significant levels of data for tuning and validation. This reflects the difficultly to generate correlated quantitative data, and it points out a critical uncertainty in modeling efforts. To develop a data-driven model of cell cycle regulation, we used contiguous, dynamic measurements over two time scales (minutes and hours) calculated from static multiparametric cytometry data. The approach provided expression profiles of cyclin A2, cyclin B1, and phospho-S10-histone H3. The model was built by integrating and modifying two previously published models such that the model outputs for cyclins A and B fit cyclin expression measurements and the activation of B cyclin/Cdk1 coincided with phosphorylation of histone H3. The model depends on Cdh1-regulated cyclin degradation during G1, regulation of B cyclin/Cdk1 activity by cyclin A/Cdk via Wee1, and transcriptional control of the mitotic cyclins that reflects some of the current literature. We introduced autocatalytic transcription of E2F, E2F regulated transcription of cyclin B, Cdc20/Cdh1 mediated E2F degradation, enhanced transcription of mitotic cyclins during late S/early G2 phase, and the sustained synthesis of cyclin B during mitosis. These features produced a model with good correlation between state variable output and real measurements. Since the method of data generation is extensible, this model can be continually modified based on new correlated, quantitative data.
    Full-text · Article · May 2014 · PLoS ONE
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    • "In a third step, cyclin B1 is degraded through a similar process, initiated by Cdc20 and enforced by Cdh1. Finally, histone H3 is incompletely dephosphorylated by phosphatases, and cells divide with residual phosphorylation [15]. For more detail on this complex, and as yet incompletely understood process, see [16]–[18]. "
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    ABSTRACT: Cytometry of asynchronous proliferating cell populations produces data with an extractable time-based feature embedded in the frequency of clustered, correlated events. Here, we present a specific case of general methodology for calculating dynamic expression profiles of epitopes that oscillate during the cell cycle and conversion of these values to the same scale. Samples of K562 cells from one population were labeled by direct and indirect antibody methods for cyclins A2 and B1 and phospho-S10-histone H3. The same indirect antibody was used for both cyclins. Directly stained samples were counter-stained with 4'6-diamidino-2-phenylindole and indirectly stained samples with propidium to label DNA. The S phase cyclin expressions from indirect assays were used to scale the expression of the cyclins of the multi-variate direct assay. Boolean gating and two dimensional, sequential regions set on bivariate displays of the directly conjugated sample data were used to untangle and isolate unique, unambiguous expression values of the cyclins along the four-dimensional data path through the cell cycle. The median values of cyclins A2 and B1 from each region were correlated with the frequency of events within each region. The sequential runs of data were plotted as continuous multi-line linear equations of the form y = [(y(i+1)-y(i))/(x(i+1)-x(i))]x + y(i)-[(y(i+1)-y(i))/(x(i+1)-x(i))]x(i) (line between points (x(i),y(i)) and (x(i+1), y(i+1))) to capture the dynamic expression profile of the two cyclins. This specific approach demonstrates the general methodology and provides a rule set from which the cell cycle expression of any other epitopes could be measured and calculated. These expression profiles are the "state variable" outputs, useful for calibrating mathematical cell cycle models.
    Full-text · Article · Jul 2012 · PLoS ONE
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    • "This is valid provided that a cell's residence in any “state” described by a segmented region is dependent on having existed in a previous “state” described by an adjacent region at an immediately earlier time, and that all previous regions are to one side of the immediate region - i.e., the “states” and regions are contiguous, ordered, and unidirectional. This requirement can be satisfied either from direct experimentation - e.g., [4], prior knowledge, or inferred logic. The directionality for cyclin A2 versus PHH3 is shown by arrows in Figure 3B. "
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    ABSTRACT: An imprecise quantitative sense for the oscillating levels of proteins and their modifications, interactions, and translocations as a function of the cell cycle is fundamentally important for a cartoon/narrative understanding for how the cell cycle works. Mathematical modeling of the same cartoon/narrative models would be greatly enhanced by an open-ended methodology providing precise quantification of many proteins and their modifications, etc. Here we present methodology that fulfills these features. Multiparametric flow cytometry was performed on Molt4 cells to measure cyclins A2 and B1, phospho-S10-histone H3, DNA content, and light scatter (cell size). The resulting 5 dimensional data were analyzed as a series of bivariate plots to isolate the data as segments of an N-dimensional "worm" through the data space. Sequential, unidirectional regions of the data were used to assemble expression profiles for each parameter as a function of cell frequency. Analysis of synthesized data in which the true values where known validated the approach. Triplicate experiments demonstrated exceptional reproducibility. Comparison of three triplicate experiments stained by two methods (single cyclin or dual cyclin measurements with common DNA and phospho-histone H3 measurements) supported the feasibility of combining an unlimited number of epitopes through this methodology. The sequential degradations of cyclin A2 followed by cyclin B1 followed by de-phosphorylation of histone H3 were precisely mapped. Finally, a two phase expression rate during interphase for each cyclin was robustly identified. Very precise, correlated expression profiles for important cell cycle regulating and regulated proteins and their modifications can be produced, limited only by the number of available high-quality antibodies. These profiles can be assembled into large information libraries for calibration and validation of mathematical models.
    Full-text · Article · Feb 2012 · PLoS ONE
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