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Dynamic epitope expression from static cytometry data: principles and reproducibility.

Jacobberger JW, Avva J, Sreenath SN, Weis MC, Stefan T - PLoS ONE (2012)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio, United States of America. jwj@case.edu

ABSTRACT

Background: 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.

Methodology: 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.

Results: 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.

Conclusions: 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.

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Related in: MedlinePlus

Defining ambiguity.Molt4 cells were stained for phospho-S10-histone H3 (PHH3-A488), cyclin A2 (Cyclin A2-A647), and DNA content. A: typical view for counting mitotic cells (green dots). This view provides ambiguous data vis-à-vis profile extraction since the cells between the G2 cluster and the bulk of mitotic events at the highest PHH3 levels represent cells that were in the processes of net gain and net loss of PHH3 (A, dual arrows). The ambiguity can be resolved by plotting PHH3 versus cyclin A2 (B). Arrows show the direction of movement through the data space of cell traversing the cell cycle.
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pone-0030870-g003: Defining ambiguity.Molt4 cells were stained for phospho-S10-histone H3 (PHH3-A488), cyclin A2 (Cyclin A2-A647), and DNA content. A: typical view for counting mitotic cells (green dots). This view provides ambiguous data vis-à-vis profile extraction since the cells between the G2 cluster and the bulk of mitotic events at the highest PHH3 levels represent cells that were in the processes of net gain and net loss of PHH3 (A, dual arrows). The ambiguity can be resolved by plotting PHH3 versus cyclin A2 (B). Arrows show the direction of movement through the data space of cell traversing the cell cycle.

Mentions: To perform the same procedure as illustrated for DNA content with more complex data, it is necessary for the analytical setup to provide data that unambiguously captures cells at each point along the expression profile. At a minimum, for each dimension, we need defined variation to create ends for each expression profile, and over any region of each profile, “x”, that oscillates, another parameter, “y”, must either be rising or falling sufficiently to allow separation of the rise and fall of parameter, “x”. The concept is illustrated in Figure 3. Expression of PHH3 versus DNA content provides a bivariate view that captures expression in G0/G1, S, G2, and M. However, the mitotic cells that represent rising expression of PHH3 map to the same data space as cells that represent falling expression. The first are at the beginning of mitosis and the last are at the end of mitosis (arrows, Figure 3A). In this case, during the period when PHH3 is rising then falling, DNA content does not change, and therefore, the rise and fall of PHH3 cannot be resolved. Addition of cyclin A2 provides a complete, unambiguous data trajectory that can be traced from the beginning of the cell cycle to the end (Figure 3B). When PHH3 is rising, so is cyclin A2, but when cyclin A2 is falling, PHH3 is ∼constant, then PHH3 falls when cyclin A2 is essentially nil. Note, however, that this is not independent of DNA content. Figure S1 shows that segmentation of the 2C stemline from the 4C and higher sub-cycles requires the combination of the three parameters, DNA content, PHH3, and cyclin A2. The unidirectional progression of a hypothetical cell through the data space, as depicted in Figure 3B can be verified by monitoring the passage of a BrdU-label through segments of the data space [4].


Dynamic epitope expression from static cytometry data: principles and reproducibility.

Jacobberger JW, Avva J, Sreenath SN, Weis MC, Stefan T - PLoS ONE (2012)

Defining ambiguity.Molt4 cells were stained for phospho-S10-histone H3 (PHH3-A488), cyclin A2 (Cyclin A2-A647), and DNA content. A: typical view for counting mitotic cells (green dots). This view provides ambiguous data vis-à-vis profile extraction since the cells between the G2 cluster and the bulk of mitotic events at the highest PHH3 levels represent cells that were in the processes of net gain and net loss of PHH3 (A, dual arrows). The ambiguity can be resolved by plotting PHH3 versus cyclin A2 (B). Arrows show the direction of movement through the data space of cell traversing the cell cycle.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3275612&req=5

pone-0030870-g003: Defining ambiguity.Molt4 cells were stained for phospho-S10-histone H3 (PHH3-A488), cyclin A2 (Cyclin A2-A647), and DNA content. A: typical view for counting mitotic cells (green dots). This view provides ambiguous data vis-à-vis profile extraction since the cells between the G2 cluster and the bulk of mitotic events at the highest PHH3 levels represent cells that were in the processes of net gain and net loss of PHH3 (A, dual arrows). The ambiguity can be resolved by plotting PHH3 versus cyclin A2 (B). Arrows show the direction of movement through the data space of cell traversing the cell cycle.
Mentions: To perform the same procedure as illustrated for DNA content with more complex data, it is necessary for the analytical setup to provide data that unambiguously captures cells at each point along the expression profile. At a minimum, for each dimension, we need defined variation to create ends for each expression profile, and over any region of each profile, “x”, that oscillates, another parameter, “y”, must either be rising or falling sufficiently to allow separation of the rise and fall of parameter, “x”. The concept is illustrated in Figure 3. Expression of PHH3 versus DNA content provides a bivariate view that captures expression in G0/G1, S, G2, and M. However, the mitotic cells that represent rising expression of PHH3 map to the same data space as cells that represent falling expression. The first are at the beginning of mitosis and the last are at the end of mitosis (arrows, Figure 3A). In this case, during the period when PHH3 is rising then falling, DNA content does not change, and therefore, the rise and fall of PHH3 cannot be resolved. Addition of cyclin A2 provides a complete, unambiguous data trajectory that can be traced from the beginning of the cell cycle to the end (Figure 3B). When PHH3 is rising, so is cyclin A2, but when cyclin A2 is falling, PHH3 is ∼constant, then PHH3 falls when cyclin A2 is essentially nil. Note, however, that this is not independent of DNA content. Figure S1 shows that segmentation of the 2C stemline from the 4C and higher sub-cycles requires the combination of the three parameters, DNA content, PHH3, and cyclin A2. The unidirectional progression of a hypothetical cell through the data space, as depicted in Figure 3B can be verified by monitoring the passage of a BrdU-label through segments of the data space [4].

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio, United States of America. jwj@case.edu

ABSTRACT

Background: 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.

Methodology: 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.

Results: 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.

Conclusions: 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.

Show MeSH
Related in: MedlinePlus