Autocatalytic growth offset by constant degradation explains mass accumulation during B cell activation

Abstract

How cells regulate growth is a fundamental question in cell biology. Here we use quantitative phase imaging (QPI) to measure the dry mass of individual naive primary mouse B cells during ex vivo stimulation. B cells undergo an approximately 4-fold increase in mass prior to first division, far exceeding the doubling in size typical of immortalized cell lines and enabling discrimination of growth models that are otherwise indistinguishable. We find that a pure exponential model of mass accumulation exhibits systematic error that is resolved by an offset exponential model, indicating that only an active fraction of cell mass participates in biosynthesis. Monte Carlo simulations establish when these two models can be discriminated as a function of final to initial mass ratio, the magnitude of the degradative pressure, and measurement precision. Analysis of growth rate versus mass independently confirms the offset exponential model and implies that it can be interpreted as indicating a constant degradative pressure that opposes exponential biosynthesis. This model is structurally equivalent to super-exponential growth models derived from autocatalytic ribosome dynamics in bacteria, with the exponential rate reflecting autocatalytic accumulation of biosynthetic machinery and the active mass fraction serving as a proxy for initial ribosomal capacity. Here, the low active fraction in quiescent B cells ([~]20%) is consistent with a limited ribosomal content of resting lymphocytes. Comparison of follicular and marginal zone B cells stimulated with CpG reveals a conserved degradative pressure across subtypes and stimulation conditions. These results demonstrate that deviations from pure exponential growth, previously identified in bacteria, extend to mammalian cells, suggesting that autocatalytic ribosome accumulation offset by constitutive protein turnover is a conserved feature of single-cell growth dynamics across domains of life.