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Biology subjects

Blanchini, F.

Publications and source records attributed to Blanchini, F..

3 recordsLinked to original sources

Temporal dose inversion properties of adaptive biomolecular circuits

Cells have the capacity to encode and decode information in the temporal features of molecular signals. Many pathways, for example, generate either sustained or pulsatile responses depending on the context, and such diverse temporal behaviors have a profound impact on cell fate. Here we focus on how molecular pathways can convert the temporal features of dynamic signals, in particular how they can convert transient signals into persistent downstream events and vice versa. We refer to this type of behavior as temporal dose inversion, and we demonstrate that it can be achieved through adaptive molecular circuits. Using a cell-free synthetic gene circuit implementing an incoherent feedforward loop (IFFL), we experimentally demonstrate the temporal dose inversion. To understand the design principles of the temporal dose inversion, we analyze adaptive circuit motifs including incoherent feedforward loops (IFFLs) and negative feedback loops (NFLs). Through numerical simulations with expensive parameter exploration, we identify parametric regimes in which these circuits exhibit temporal dose inversion. We further examine more detailed biological models of the IFFL and NFL circuits, including enzymatic signaling models and gene regulatory network models, showing that the IFFL circuits is more likely to exhibit temporal dose inversion compared with the NFL circuits. Finally, we analyze a generalized IFFL topology, and we find that both the time delay in the inhibition pathway and the relative signal intensities of the activation and inhibition signals are key determinants for temporal dose inversion. Together, our results establish a design principle of temporal dose inversion on the adaptive biomolecular circuits and provide mechanistic insight into how molecular networks process temporal information in dynamic signals.

systems biology↗

Design of a sequestration-based network with tunable pulsing dynamics

Incoherent feedforward networks exhibit the ability to generate temporal pulse behavior. However, exerting control over specific dynamic properties, such as amplitude and rise time, poses a challenge and is intricately tied to the networks implementation. In this study, we focus on analyzing sequestration-based networks capable of exhibiting pulse behavior. By employing time-scale separation in the fast sequestration regime, we approximate the temporal dynamics of these networks. This approach allows us to establish a mapping that elucidates the impact of varying the kinetic rates and pulse specifications, including amplitude and rise time. Furthermore, we introduce a positive feedback mechanism to regulate the amplitude of the pulsing response.

synthetic biology↗

Neural networks built from enzymatic reactions can operate as linear and nonlinear classifiers

The engineering of molecular programs capable of processing patterns of multi-input biomarkers holds great potential in applications ranging from in vitro diagnostics (e.g., viral detection, including COVID-19) to therapeutic interventions (e.g., discriminating cancer cells from normal cells). For this reason, mechanisms to design molecular networks for pattern recognition are highly sought after. In this work, we explore how enzymatic networks can be used for both linear and nonlinear classification tasks. By leveraging steady-state analysis and showing global stability, we demonstrate that these networks can function as molecular perceptrons, fundamental units of artificial neural networks--capable of processing multiple inputs associated with positive and negative weights to achieve linear classification. Furthermore, by composing orthogonal enzymatic reactions, we show that multi-layer networks can be constructed to achieve nonlinear classification.

synthetic biology↗