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Biology subjects

Namboothiri, H. R.

Publications and source records attributed to Namboothiri, H. R..

2 recordsLinked to original sources

Closed-loop Optogenetic Control in a Microplate Reader

Optogenetics integrates living cells and electronics into powerful cell-silicon systems, but prototyping their dynamics remains challenging. Current tools either require robotic liquid transfers into flow cytometers or rely on custom sensors with narrow dynamic range that limit controller performance. Additionally, current successful optogenetic feedback controllers only operate in chemostats or microfluidic devices that enforce constant growth, because models for growth-aware controller design in batch culture are lacking. Here we present LEMOS, a low-cost LED-embedded microplate that runs inside a commercial microplate reader. Coupled to a growth-aware multiscale model of gene expression for controller tuning, this platform enables rapid design-build-test-learn cycles for cell-silicon systems. We demonstrate closed loop setpoint tracking of gene expression in batch cultures within a standard microplate reader and show how growth dynamics complicates controller selection and tuning. Together, this platform reduces setup overhead and speed up iteration, enabling accurate real-time optogenetic feedback control.

synthetic biology↗

Resolving Emergent Oscillations in Gene Circuits with a Growth-Coupled Model

Synthetic gene circuits often behave unpredictably in batch cultures, where shifting physiological states are rarely accounted for in conventional models. Here, we find that degradation-tagged protein reporters could exhibit transient oscillatory expression, which standard single-scale models do not capture. We resolve this discrepancy by developing Gene Expression Across Growth Stages (GEAGS), a dual-scale modeling framework that explicitly couples intracellular gene expression to logistic population growth. Using a chemical reaction network (CRN) model with growth-phase-dependent rate-modifying functions, GEAGS accurately reproduces the observed transient oscillations and identifies amino acid recycling and growth-phase transition as key drivers. We reduce the model to an effective form for practical use and demonstrate its adaptability by applying it to layered feedback circuits, resolving long-standing mismatches between model predictions and measured dynamics. These results establish GEAGS as a generalizable platform for predicting emergent behaviors in synthetic gene circuits and underscore the importance of multiscale modeling for robust circuit design in dynamic environments. TeaserMultiscale modeling reveals how growth and proteolysis-linked recycling cause transient oscillations in synthetic gene circuits.

synthetic biology↗