Abstract
Uncovering the number of stem cells necessary for organ growth has been challenging in vertebrate systems. Here, we developed a mathematical model characterizing stem cells in the fish gill, an organ displaying non-exhaustive growth. We employ a Markov model, stochastically simulated via an adapted Gillespie algorithm, and further improved through probability theory. The stochastic algorithm produces a simulated dataset for comparison with experimental clonal data by inspecting quantifiable properties. The analytical approach skips the step of artificial data generation and goes directly to the quantification, being more abstract and efficient. We report that a reduced number of stem cells actively contribute to growing and maintaining the gills. The model also highlights a functional heterogeneity among the stem cells involved, where activation and quiescence phases determine their relative growth contribution. Overall, our work presents a method for inferring the number and properties of stem cells required in a lifelong growing system.