Variance within homogeneous phytoplankton populations, I: Theoretical framework for interpreting histograms

Area of Science:

• Marine biology
• Cell biology
• Biophysics

Background:

• Flow cytometry is crucial for analyzing phytoplankton populations.
• Interpreting frequency distributions (histograms) of cell volume or fluorescence requires robust methods.
• Understanding population synchronicity is key to cell cycle studies.

Purpose of the Study:

• To develop and present a framework for interpreting flow cytometry frequency distributions of phytoplankton.
• To differentiate between asynchronous and synchronous/phased phytoplankton populations based on histogram analysis.
• To provide a method for estimating cell volume parameters at cell age 0.

Main Methods:

• Utilized a simulation model to generate frequency distributions for various phytoplankton population types (asynchronous, synchronous, phased).
• Simulated populations with constant and variable growth patterns across the cell cycle.
• Derived a probability density function for asynchronous populations with constant growth rates.

Main Results:

• Simulations generated diverse histogram shapes, including multimodal distributions.
• The primary distinction between asynchronous and synchronous/phased populations is temporal variation in histograms.
• Constant histograms indicate asynchronous populations, while varying histograms suggest synchronicity tied to the cell cycle.
• The derived probability density function accurately estimated mean and variance of cell volume at age 0 when fitted to simulated asynchronous population histograms.

Conclusions:

• The presented framework effectively interprets flow cytometry frequency distributions for phytoplankton.
• Temporal analysis of histograms is a key differentiator for asynchronous versus synchronous/phased populations.
• The derived probability density function offers a quantitative method for parameter estimation in asynchronous phytoplankton populations.