Life is inherently dynamic and complex. In order to survive, cells must rely on sensing and responding to their environment through interconnected pathways that transduce different signals into gene expression patterns, thus shaping cell’s behaviour. Some regulatory signals change over time in a pulsatile manner, offering precise control over cellular responses, especially in noisy environments. Understanding which signal features—such as frequency and amplitude—optimize the activation of specific targets is essential.
Identifying the key properties that make a signal most effective in activating a target is crucial for understanding how cells manage their responses to pulsatile signals. This study focuses on how frequency influences cellular responses.
But how is the response computed? The answer depends on the biological attributes considered relevant and the timing of the measurement. While steady-state measurements are often emphasized, transient information can be equally important.
Why should transient information also be considered? In some cases, oscillations are brief and activate processes that are also short-lived, meaning the system may not reach a steady-state behaviour. Even with prolonged signals, components might still operate in a pre-equilibrium state if downstream elements respond more quickly than initial ones.
It’s clear that the duration of signals is crucial for regulating biological processes. For instance, sustained stimulation doesn’t always lead to prolonged responses, while short-term stimulation can sometimes trigger persistent responses. Additionally, signal duration impacts cellular responses in ways where timing is crucial, a concept known as temporal filtering. This means that a cell might only respond to a signal if it lasts beyond a certain minimum time. Related phenomena like kinetic proofreading and persistence detection highlight the system’s ability to interpret and manage signals based on their timing and duration. Therefore, understanding transient responses can offer valuable insights into how cells process and react to oscillatory stimuli.
Time-limited oscillations can act as repetitive stimuli for downstream processes. Because they are brief, they have the potential to specifically activate transient aspects of these processes. In this article, we focus on early-stage responses in simple systems to pulsatile stimuli and explores their properties in terms of signal frequency.
A signaling component C can be stimulated by time-limited (A) or long-lasting (B) stimulations. Signal A activates the transient phase of the response in C, whereas signal B enables the response to stabilize at a steady state. Only signal A leads to a frequency preference response.
Biological systems can exhibit different responses in terms of frequency, depending on the attribute and the timing of the measurement. Some systems are insensitive to frequency changes, while other respond preferentially to low or high frequencies. Interestingly, certain systems show optimal responses at intermediate input frequencies.
We find that some signaling components, during their initial phase, can reveal a preference for specific frequencies. Transient responses can uncover these preferences and show how cells might use short-term changes for decision-making.
The key question we address is how minimal a system can be while still exhibiting frequency selectivity. We examined factors such as the number of connected nodes, their connectivity, kinetic mechanisms, nonlinearities, and feedback connections.
Starting with simple, isolated systems like ligand-receptor pairs or synthesis-degradation components, we explored the behavior of two coupled systems without feedback. Finally, we applied a well-known signaling model, such as the MAPK cascade, which can display diverse behaviors.
Previous studies suggested that feedback connections are essential for frequency selectivity and that simple systems cannot exhibit this selectivity. We hypothesized that both the dynamics of the input and the system’s structure are important, but we also believe that the specific observable and the time window of measurement are crucial. By focusing on early-stage responses, we show that even simple systems without feedback connections can exhibit frequency preference. Moreover, this behavior can be transmitted to downstream components depending on their relative timescales. This suggests that a single level can convey two different messages downstream based on the dynamics of the subsequent component. A fast-responding component can decode the transient frequency preference, while a slower one may not, leading to different interpretations of the same signal.
Our results support the hypothesis that frequency preference is not an inherent property of a system or its connectivity. Instead, it emerges from the dynamic interplay between stimulus and response, including how the response is defined and when it is measured. This also implies that the selectivity observed in more complex models does not necessarily arise solely from their complexity.
Our studies indicate that transient frequency preferences might be critical dynamic features of cell signaling and gene expression systems that are often overlooked. This highlights the remarkable versatility of biological systems, enabling the transmission of multiple messages through a single signal while also exhibiting high specificity based on the characteristics of the signal-processing systems.
Szischik Candela L., Reves Szemere Juliana, Balderama RocÃo, Sánchez de la Vega Constanza, Ventura Alejandra C.Â