Titile
Modeling Cell-Cell Communicational Mechanisms in the Circadian Timing System
Background and questions being investigated
Due to the 24-hour rotation of the earth around its axis, biological systems experience environmental recurring changes. To promote survival and optimize energy resource allocation, the circadian time-keeping mechanism was evolved to maintain homeostasis by synchronizing internal physiology with predictable variations in the environment, such as light/dark cycles. Nearly every cell in our body has a self-sustained rhythm rooted in the translational-transcriptional feedback loop involving numerous circadian clock genes and proteins [1]. Through various coupling mechanisms, these cells consist of oscillators at the cellular, tissue, organ, and system levels, resulting in a highly tuned network of the endogenous circadian timing system.
The hypothalamic suprachiasmatic nuclei (SCN) have been widely identified as the central pacemaker that transduces photic information to the downstream clocks of the periphery. The SCN consists of ~20,000 of neurons, where clock genes are exposed in most of the neurons. These neurons are organized as a coupled network through neural projections and humoral signals, as cells communicate with each other and convey the temporal information to the downstream compartments [2]. Entrained by the SCN, cortisol, the downstream effector of hypothalamic-pituitary-adrenal (HPA) activity, facilitates the synchronization of peripheral biological processes to the environment [3]. Taken together, the circadian timing system senses, transduces, and integrates environmental signals to optimize the performance of endogenous physiological rhythms to external changes. To achieve this, clocks in the physiological system communicate with each other in a complex hierarchical manner. Due to the technical difficulties and limitations in experiments, the inter-cellular and inter-compartmental communication mechanisms in the circadian timing system are currently poorly understood. Building upon the limited amount of information, deciphering systemic clock-to-clock communication remains one of the most challenging and critical investigations in chronobiology and chrono-pharmacology, as a misaligned circadian system is commonly associated with adverse health outcomes.
The current project suggests an ODE-based mathematical modeling approach, integrating the experimental data, to obtain more insights into the detailed cell-cell communication mechanisms in the circadian timing system. Our exploration includes the coupling mechanisms within the SCN as well the systematic signal transduction mechanisms between key compartments in the circadian timing system.
Issue and aim of the project
Our project can be divided into two parts:
In the first part, we specifically explore the detailed coupling mechanisms of neurons in the SCN. The goal of this part is to decipher the clock cell network morphology within the circadian central pacemaker.
In the second part, we aim to investigate the communication mechanisms between circadian compartments on a systemic level (including the SCN, the HPA axis, and the peripheral tissues and organs). We aim to simulate the light transduction pathway within the circadian timing system and investigate the consequences of circadian misalignment induced by disturbed light/feeding schedules as they are associated with numerous diseases.
Rational for approach
While it’s well established that synchronization through cell-cell communication in the circadian timing system is critical for the host’s fitness, many unclear facts are still open for discussion. For example, the detailed mechanisms for SCN neurons to adjust their coupling network to adapt to seasonal changes are unclear [4]. And how the coupling mechanisms between different clock compartments, leads to individualized recovery responses under jet lag and shift work schedules require a detailed investigation [5; 6]. A comprehensive understanding of this complex, dynamic system necessitates a holistic approach. And we believe mathematical models will be increasingly beneficial in virtually assessing the system under experimentally challenging conditions with greater specificity in integrating multiple physiological compartments. In one of our previous studies, we provided a first attempt at modeling the hierarchical structure of the circadian timing system, taking into account the interactions between the SCN and the HPA axis in studying individualized flexibility and rigidity in the exposure of perturbed light-dark schedules [7]. More detailed models are anticipated to be developed for assessing wider aspects of the circadian organization induced by cell-cell communication, and the systemic behavior during desynchronization and misalignment.
Details of the suggested approach
To accomplish our first goal, we plan to build a detailed SCN model incorporating both single-cellular oscillators and the different types of coupling effects between neurons. Currently, the SCN neuronal network topology is highly unknown even with recent technologies in neuroscience. Therefore, our project plan is to come up with a mathematical model of the SCN that well matches those limited experimental findings. By testing and comparing the synchronization predictions generated by our model, we aim to identify a more realistic SCN topology in guidance for future experimental studies.
To accomplish our second goal, we plan to incorporate both central and peripheral clocks into the model, as well as multiple systemic entrainment cues such as light/dark and feeding/fasting. Parameter estimation will be done to calibrate the model with experimental data, and the model will be verified by its ability to generate experimentally already observed data. Based on that, we will further conduct simulations on experimentally challenging conditions, such as the interaction of seasonal changes on jetlag and shift work as non-pharmacological jetlag interventions, effects of food/light misalignment, and personal differential responses of synthetic glucocorticoids.
How it will affect the broader field
The robust synchronization of the circadian timing system is critical as the perturbed rhythms increase the risks of diseases such as cancer, cardiovascular diseases, and metabolic disorders [8]. Although the negative impact of circadian rhythm disruption is well recognized, due to the incomplete understanding of the complex system, circadian rhythms are currently only occasionally considered in clinical practice. In parallel with the experimental progress in understating cell-cell communication in the circadian timing system, mathematical models show their unique advantages in understanding different aspects of physiological systems integrating different scales. In this context, our project will not only stress the significance of mathematical modeling in studying the biological system in a quantitative manner, but also provide interventional guidance for experimental studies to minimize the detrimental effects of circadian disruptions and thus contribute to the treatment of chronic disease.
References
[1] A.M. Finger, C. Dibner, and A. Kramer, Coupled network of the circadian clocks: a driving force of rhythmic physiology. FEBS letters 594 (2020) 2734-2769.
[2] D. Ono, K.-i. Honma, and S. Honma, Roles of Neuropeptides, VIP and AVP, in the Mammalian Central Circadian Clock. Frontiers in neuroscience 15 (2021).
[3] I.P. Androulakis, Circadian rhythms and the HPA axis: A systems view. WIREs Mechanisms of Disease 13 (2021) e1518.
[4] C. Gu, J. Li, J. Zhou, H. Yang, and M. Wang, Strengthen the circadian rhythms by the mathematical model of the SCN. The European Physical Journal Special Topics 231 (2022) 827-832.
[5] J.F. Díaz-Morales, and C. Escribano, Social jetlag, academic achievement and cognitive performance: Understanding gender/sex differences. Chronobiology international 32 (2015) 822-831.
[6] I.E. Ashkenazi, A.E. Reinberg, and Y. Motohashi, Interindividual differences in the flexibility of human temporal organization: pertinence to jet lag and shiftwork. Chronobiology international 14 (1997) 99-113.
[7] Y. Li, and I.P. Androulakis, Light entrainment of the SCN circadian clock and implications for personalized alterations of corticosterone rhythms in shift work and jet lag. Scientific reports 11 (2021).
[8] E.N.C. Manoogian, and S. Panda, Circadian rhythms, time-restricted feeding, and healthy aging. Ageing Research Reviews 39 (2017) 59-67.