Multi-Layer Autocatalytic Feedback Enables Integral Control Amidst Resource Competition and Across Scales

Abstract

Integral feedback control strategies have proven effective in regulating protein expression in unpredictable cellular environments. These strategies, grounded in model-based designs and control theory, have advanced synthetic biology applications. Autocatalytic integral feed-back controllers, utilizing positive autoregulation for integral action, are particularly promising due to their similarity to natural behaviors like self-replication and positive feedback seen across biological scales. However, their effectiveness is often hindered by resource competition and context-dependent couplings. This study addresses these challenges with a multi-layer feedback strategy, enabling population-level integral feedback and multicellular integrators. We provide a generalized mathematical framework for modeling resource competition in complex genetic networks, supporting the design of intracellular control circuits. Our controller motif demonstrated precise regulation in tasks ranging from gene expression control to population growth in multi-strain communities. We also explore a variant capable of ratiometric control, proving its effectiveness in managing gene ratios and co-culture compositions in engineered microbial ecosystems. These findings offer a versatile approach to achieving robust adaptation and homeostasis from subcellular to multicellular scales.