The biophysics of cellular counting — uncovering how viral copy number drives cell-fate decision

After infecting an E. coli cell, the virus lambda either kills the host cell (lysis) or enters a stable, dormant state (lysogeny). Such cell-fate decisions are ubiquitous in biology, but few are well understood mechanistically. The lambda decision is an attractive model system, as it is comparatively simple, well-studied, and shares multiple features with more complex systems. A key factor affecting the decision is the multiplicity of infection (MOI), i.e. the number of co-infecting viruses. Increasing MOI raises the likelihood of a lysogenic outcome, but the mechanisms by which viral copy number drives the decision are unclear. To determine these mechanisms, we combine single-cell resolution experiments with coarse-grained modeling of infection over a range of MOI. We find that the expression of essential genes in the decision network exhibits power-law scaling with MOI. Notably, the expression of cro, a key lytic gene, scales sublinearly, whereas the expression of cI, the gene responsible for establishing the lysogenic state, scales superlinearly. This nonlinear, gene-specific response to MOI is a consequence of negative and positive feedback loops in the regulatory network. This feedback causes increasing MOI to drive expression of cI, pushing the decision towards lysogeny.