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Mitochondria form a dynamic tubular reticulum within eukaryotic cells. Currently, quantitative understanding of its morphological characteristics is largely absent, despite major progress in deciphering the molecular fission and fusion machineries shaping its structure. Here we address the principles of formation and the large-scale organization of the cell-wide network of mitochondria. On the basis of experimentally determined structural features we establish the tip-to-tip and tip-to-side fission and fusion events as dominant reactions in the motility of this organelle. Subsequently, we introduce a graph-based model of the chondriome able to encompass its inherent variability in a single framework. Using both mean-field deterministic and explicit stochastic mathematical methods we establish a relationship between the chondriome structural network characteristics and underlying kinetic rate parameters. The computational analysis indicates that mitochondrial networks exhibit a percolation threshold. Intrinsic morphological instability of the mitochondrial reticulum resulting from its vicinity to the percolation transition is proposed as a novel mechanism that can be utilized by cells for optimizing their functional competence via dynamic remodeling of the chondriome. The detailed size distribution of the network components predicted by the dynamic graph representation introduces a relationship between chondriome characteristics and cell function. It forms a basis for understanding the architecture of mitochondria as a cell-wide but inhomogeneous organelle. Analysis of the reticulum adaptive configuration offers a direct clarification for its impact on numerous physiological processes strongly dependent on mitochondrial dynamics and organization, such as efficiency of cellular metabolism, tissue differentiation and aging.
Mitochondrial dynamics and mitophagy play a key role in ensuring mitochondrial quality control. Impairment thereof was proposed to be causative to neurodegenerative diseases, diabetes, and cancer. Accumulation of mitochondrial dysfunction was further linked to aging. Here we applied a probabilistic modeling approach integrating our current knowledge on mitochondrial biology allowing us to simulate mitochondrial function and quality control during aging in silico. We demonstrate that cycles of fusion and fission and mitophagy indeed are essential for ensuring a high average quality of mitochondria, even under conditions in which random molecular damage is present. Prompted by earlier observations that mitochondrial fission itself can cause a partial drop in mitochondrial membrane potential, we tested the consequences of mitochondrial dynamics being harmful on its own. Next to directly impairing mitochondrial function, pre-existing molecular damage may be propagated and enhanced across the mitochondrial population by content mixing. In this situation, such an infection-like phenomenon impairs mitochondrial quality control progressively. However, when imposing an age-dependent deceleration of cycles of fusion and fission, we observe a delay in the loss of average quality of mitochondria. This provides a rational why fusion and fission rates are reduced during aging and why loss of a mitochondrial fission factor can extend life span in fungi. We propose the ‘mitochondrial infectious damage adaptation’ (MIDA) model according to which a deceleration of fusion–fission cycles reflects a systemic adaptation increasing life span.
Mathematische Methoden in der Biologie haben sich in den vergangenen 25 Jahren zunehmend etabliert. Etwa in den Bereichen der Entwicklung von Organen und Organismen sind große Anstrengungen in der Mathematik unternommen worden, die grundlegenden Mechanismen der Entwicklung aufzudecken. Der einfache Gedanke, auf dem diese Methode aufbaut, ist ein reduktionistischer: Man verwendet einen minimalen Satz von in der Biologie beobachteten Wechselwirkungen – etwa zwischen den Zellen, die das betrachtete Gewebe aufbauen –, übersetzt sie in ein mathematisches System von dynamischen Gleichungen, löst diese auf dem Computer und prüft, ob sich in der Lösung die erwartete Struktur zeigt. Wenn dies allein aufgrund experimenteller Daten aus der Biologie nicht möglich ist, ergibt sich der größte Nutzen der mathematischen Beschreibung: Dann sind neue Hypothesen im mathematischen Modell notwendig, um das reale System beschreiben zu können. Damit sagen die Theoretiker Zusammenhänge voraus, die aus der Biologie alleine nicht ableitbar sind. Diese können durch neue gezielte Experimente verifiziert werden. Ein ähnlicher Ansatz wurde in jüngerer Zeit von unserer Gruppe am Frankfurter Instute for Advanced Studies (FIAS) in der Immunologie verwendet.
Control of cell proliferation is critical for the lymphocyte life cycle. However, little is known on how stage-specific alterations in cell-cycle behavior drive proliferation dynamics during T-cell development. Here, we employed in vivo dual-nucleoside pulse labeling combined with determination of DNA replication over time as well as fluorescent ubiquitination-based cell-cycle indicator mice to establish a quantitative high-resolution map of cell-cycle kinetics of thymocytes. We developed an agent-based mathematical model of T-cell developmental dynamics. To generate the capacity for proliferative bursts, cell-cycle acceleration followed a 'stretch model', characterized by simultaneous and proportional contraction of both G1 and S phase. Analysis of cell-cycle phase dynamics during regeneration showed tailored adjustments of cell-cycle phase dynamics. Taken together, our results highlight intrathymic cell-cycle regulation as an adjustable system to maintain physiologic tissue homeostasis and foster our understanding of dysregulation of the T-cell developmental program.
High-resolution mapping of cell cycle dynamics during T-cell development and regeneration in vivo
(2024)
Control of cell proliferation is critical for the lymphocyte life cycle. However, little is known on how stage-specific alterations in cell cycle behavior drive proliferation dynamics during T-cell development. Here, we employed in vivo dual-nucleoside pulse labeling combined with determination of DNA replication over time as well as fluorescent ubiquitination-based cell cycle indicator mice to establish a quantitative high-resolution map of cell cycle kinetics of thymocytes. We developed an agent-based mathematical model of T-cell developmental dynamics. To generate the capacity for proliferative bursts, cell cycle acceleration followed a ‘stretch model’, characterized by simultaneous and proportional contraction of both G1 and S phase. Analysis of cell cycle phase dynamics during regeneration showed tailored adjustments of cell cycle phase dynamics. Taken together, our results highlight intrathymic cell cycle regulation as an adjustable system to maintain physiologic tissue homeostasis and foster our understanding of dysregulation of the T-cell developmental program.