The central conceptual move in the paper is a reframing of what distinguishes a quiescent cell from a senescent one. Rather than treating the two states as fundamentally different biological categories, Yilmaz and Shay describe them as positions along a spectrum of arrested states, defined by two parameters: the stability of the arrest and the magnitude of the perturbation required to reverse it. A deeply stable senescent cell and a shallowly arrested quiescent cell are, in this view, points on the same landscape of cell-cycle exit decisions, separated not by kind but by degree. The reframing does not erase the distinctive biology of senescence. The authors retain the senescence-associated secretory phenotype, known as SASP, along with metabolic reprogramming and chromatin remodeling, as active, context-dependent components of the senescent program. What changes is the interpretation: senescence is no longer a unique or exceptional state, but one outcome among several within a broader decision-making architecture.

To give this continuum quantitative teeth, the authors introduce what they call the Maintenance Threshold Model, or MTM. The model proposes that the stability of any arrested state emerges from a balance between two competing quantities: the cell’s maintenance capacity, meaning its ability to repair and renew its own components, and the accumulated cellular stress it carries. When maintenance capacity exceeds stress, an arrest remains reversible; when stress overwhelms maintenance, the cell tips into stable senescence. Critically, the model does not pool these inputs into a single average. Instead, it proposes that they are gated in series, a design principle with a striking technical implication: proteostatic and organellar maintenance capacity determines whether an arrested cell can complete division independently of whether the Rb-E2F restriction point is traversed. In other words, having an intact cell-cycle brake is not enough; a cell must also possess the protein-quality and organelle-renewal machinery to survive what comes after reactivation.

This serial gating has deep roots in systems biology. Switch-like, bistable behavior in stress-response networks is what allows cells to integrate signals about cellular stress, metabolic capacity, and quality-control machinery into discrete fate outcomes rather than graded drift. The review argues that such switch-like regulatory behavior, not categorical state identity alone, governs whether an arrested cell stays reversible, progresses toward stable senescent arrest, or resumes proliferation. Bistability, in this framework, means that two stable outcomes can coexist for the same set of underlying conditions, with the direction a cell takes determined by threshold crossings rather than by continuous adjustment. That architecture explains why cells exposed to similar levels of damage can end up in radically different fates, and why intervention at the right moment can, in principle, push an arrested cell back toward a reversible state or forward into irreversible arrest.

One of the model’s most consequential claims concerns why senescent cells persist. The authors propose that senescent-cell persistence is set not by one threshold but by two independent ones, both of which become less reliable with age. The first is cell-autonomous: the intrinsic maintenance capacity of the cell itself, its proteostasis, its macroautophagy, its organellar quality control. The second is non-cell-autonomous: immune surveillance, the ability of the surrounding organism to recognize and clear arrested cells. A senescent cell accumulates when its own maintenance systems fail to restore reactivation competence and when the immune system fails to remove it. Aging degrades both thresholds simultaneously, which, in the MTM framework, explains the age-dependent accumulation of senescent cells far more naturally than any single-mechanism account. The model thereby connects intracellular biochemistry and organism-level immunology in a single quantitative picture of tissue decline.

The review’s synthesis spans three traditionally separate research communities: aging biology, stem cell biology, and cancer research. In aging, the model provides a mechanistic rationale for why senescent cells accumulate in old tissues and why clearing them can restore function. In stem cell biology, it clarifies how tissue reserves maintain the option of re-entry into the cycle, a property essential for homeostasis and regeneration. In cancer, it speaks directly to a long-standing clinical puzzle: therapy-induced senescence. Many cancer treatments, from chemotherapy to radiation, work in part by driving tumor cells into a senescence-like arrest. But therapy-induced senescent cells are not always a victory. Some eventually escape arrest and resume proliferation, often with more aggressive behavior, and their SASP can remodel the tumor microenvironment in ways that support disease progression. The MTM offers a principled way to think about when arrested tumor cells will stay locked down and when they will rebound.

Because fate is plastic under this framework, the authors argue it can be deliberately manipulated, and they lay out a three-part therapeutic framework that exploits that plasticity. The first strategy is state-locking: pushing arrested cells firmly past the point of reversibility so that tumor cells driven into arrest by treatment never escape. The second is metabolic inflexibility targeting: senescent cells typically rely on particular metabolic configurations, and attacking those dependencies selectively eliminates them. The third, and perhaps most conceptually adventurous, is program hijacking: co-opting the senescent program itself, including its secretory machinery, for therapeutic benefit rather than simply suppressing it. Each strategy treats the arrest-state continuum as a control surface with tunable dials rather than a fixed landscape, aiming interventions at the thresholds that determine outcomes.

The same logic runs in reverse for aging interventions. If senescent-cell burden is set by two aging-sensitive thresholds, then interventions could target either side: bolstering cell-autonomous maintenance capacity, through approaches that support proteostasis and macroautophagy, or strengthening non-cell-autonomous immune surveillance, so that the aging immune system regains its ability to find and clear arrested cells. The framework also suggests caution for senolytic approaches: rather than viewing all senescent cells as targets for elimination, a threshold-based view encourages asking whether individual arrested cells sit near the reversible end of the continuum, where restoring maintenance capacity might be preferable to killing. Fate plasticity cuts both ways, offering opportunities to restore youthful function as well as risks of reactivating the wrong cells.

The technical vocabulary of the model is worth pausing on, because it encodes the review’s central bet. The Rb-E2F pathway is the canonical molecular restriction point governing G1-to-S transition, long treated as the decisive gate for cell-cycle re-entry. By insisting that proteostatic and organellar maintenance is gated in series with, and independent of, that restriction point, the MTM makes a falsifiable prediction: cells that pass the cell-cycle gate but lack maintenance capacity should fail to complete division or collapse into stress, while cells with robust maintenance should remain reactivation-competent even after prolonged arrest. Experiments that independently titrate CDK2 activity, autophagic flux, and proteostatic load against one another would directly test this claim. Similarly, the two-threshold account of senescent-cell persistence predicts that impairing immune surveillance should raise senescent-cell burden multiplicatively with intrinsic maintenance decline, a prediction testable in aging animal models.

What emerges from the review is a decision-centric framework in which quiescence, senescence, and proliferation are dynamically stabilized states shaped by tunable regulatory thresholds rather than fixed endpoints. Cellular fate, on this account, is a dynamic balance between damage accumulation and the capacity of quality-control systems to preserve reactivation competence, and the balance can be tipped deliberately. For a field that has spent decades cataloging markers of senescence and debating definitions, the shift from taxonomy to dynamics is significant. If the thresholds the model identifies can be measured, modulated, and eventually targeted in patients, the arrested cell may stop being a biological verdict and become, instead, a clinical choice, one that physicians could push toward clearance, commitment, or recovery depending on what the disease and the patient demand.

Subject of Research: Threshold control of cell fate decisions between quiescence and senescence in aging and cancer

Article Title: Threshold control of growth arrest in quiescence and senescence: implications for cell fate plasticity in aging and cancer

Article References: Threshold control of growth arrest in quiescence and senescence: implications for cell fate plasticity in aging and cancer. (n.d.). https://doi.org/10.1186/s12943-026-02782-8

Image Credits: AI Generated

DOI: 10.1186/s12943-026-02782-8

Keywords: cellular senescence, quiescence, cell fate plasticity, Maintenance Threshold Model, SASP, Rb-E2F, CDK2, proteostasis, macroautophagy, immune surveillance, therapy-induced senescence, aging

Macroautophagy, the best-studied form of autophagy, is an intracellular degradation system that is essential for cellular homeostasis. In this process, a double-membraned vesicle called an autophagosome forms around cytoplasmic cargo, including damaged organelles and aggregated proteins, and delivers the cargo to the lysosome or vacuole for destruction and recycling. Building an autophagosome requires the concerted action of around twenty autophagy-related genes, known as ATG genes, together with components of the cytoskeleton and the endomembrane systems. Because this machinery involves membrane deformation on a massive scale, its origin poses a striking evolutionary puzzle: how did a process requiring such elaborate coordination arise in the first eukaryotic cells?

The review argues that the autophagy pathway likely already existed in the last eukaryotic common ancestor, often abbreviated LECA, the hypothetical organism from which all living eukaryotes descend. This conclusion rests on the observation that core components of the autophagy machinery are found across the major eukaryotic supergroups, suggesting that the pathway was present before those groups diverged. Rather than being an invention of any single lineage, autophagy appears to be an ancestral eukaryotic innovation that was subsequently modified, expanded or trimmed as different branches of the eukaryotic tree pursued their own evolutionary paths.

Interestingly, the pathway itself does not exist in prokaryotes. Bacteria and archaea lack autophagosomes, lysosomes and the endomembrane systems on which eukaryotic autophagy depends. Yet when researchers search prokaryotic genomes for sequences resembling ATG genes, they find remote homologs of several of them. These distant relatives of eukaryotic autophagy genes hint that the raw materials from which the autophagy machinery was built were available long before eukaryotic cells existed, and that the pathway was assembled by repurposing pre-existing protein modules for new cellular functions.

Zhang and Mizushima organize their review around three major themes. The first concerns the evolutionary context surrounding the emergence of the autophagy pathway during eukaryogenesis, the series of events by which complex eukaryotic cells arose from prokaryotic ancestors. The second addresses how ATG genes diversified in different eukaryotic lineages through gene duplications, gene losses, and lineage-specific gains, producing the varied complements of autophagy genes observed in fungi, plants, animals and protists today. The third explores the functions that remote homologs of ATG genes carried out in prokaryotes and the phylogenetic and evolutionary relationships linking the eukaryotic and prokaryotic versions of these genes.

The eukaryogenesis story is central to understanding autophagy’s origin. The autophagosome depends on membranes, vesicle trafficking and cytoskeletal dynamics, all hallmarks of the eukaryotic cell plan. As the ancestors of eukaryotes acquired endomembrane compartments and an elaborate cytoskeleton, the molecular tools needed for autophagosome formation became available. The review suggests that the pathway’s emergence was tied to this broader cellular transformation, with ancestral protein families that carried out simpler membrane-related or stress-related functions in prokaryotes being recruited and elaborated into the coordinated autophagy machinery of early eukaryotes. In this view, autophagy is not an isolated invention but an integrated product of the cellular revolution that created the eukaryotic cell.

The diversification of ATG genes across eukaryotic lineages reveals how evolution both conserves and reshapes essential systems. Core autophagy genes have been retained across vast evolutionary distances, reflecting the fundamental importance of intracellular degradation to cell survival. At the same time, gene duplications have produced expanded families in some lineages, allowing functional specialization of related proteins, while gene losses have streamlined the machinery in others, and lineage-specific gains have introduced novel components not found elsewhere. These patterns mean that different organisms deploy partially distinct sets of ATG proteins to accomplish a fundamentally conserved process, and they complicate the task of identifying autophagy genes by sequence similarity alone, particularly in poorly studied protist groups.

The prokaryotic homologs of ATG genes add an intriguing dimension to this picture. Although bacteria and archaea do not perform macroautophagy, several of their proteins are recognizably related in structure or sequence to eukaryotic autophagy factors. Understanding what these remote homologs do in prokaryotic cells, whether they handle membrane remodeling, stress responses, protein trafficking or other tasks, offers clues about the ancestral functions from which autophagy components were drawn. Tracing the phylogenetic relationships between the eukaryotic and prokaryotic versions of these genes helps distinguish scenarios in which eukaryotes inherited the genes vertically from archaeal ancestors from those in which lateral gene transfer or other routes contributed to the modern complement of autophagy factors.

The implications of this evolutionary perspective extend well beyond comparative genomics. Autophagy is implicated in human health in contexts ranging from neurodegenerative disease to cancer and immunity, and much of what is known about the pathway comes from studies of yeast and mammalian cells. Recognizing which components are ancestral and universal, which are lineage-specific innovations, and which features of the machinery have been reshaped by evolution can guide researchers in choosing appropriate model systems and in interpreting similarities and differences between organisms. The review’s evolutionary framework provides a map for predicting where the pathway may vary and which of its elements represent the ancient core.

Zhang and Mizushima also look forward, outlining possible future directions for the field. These include filling in the distribution of autophagy genes across under-sampled eukaryotic lineages to better resolve when and how duplications and losses occurred, deepening the functional characterization of prokaryotic homologs to illuminate the pre-eukaryotic roles of ancestral proteins, and refining models of eukaryogenesis to place autophagy’s emergence within a firmer chronology. As genome data from diverse organisms continue to accumulate, the authors anticipate that the boundary between what is known about autophagy in model organisms and what can be inferred across the tree of life will continue to blur, yielding a more complete account of how one of the cell’s most sophisticated degradation systems came to be.

The review, which is open access, was supported by a Grant-in-Aid for Specially Promoted Research from the Japan Society for the Promotion of Science awarded to Noboru Mizushima. By gathering the threads of genomics, phylogenetics and cell biology into a single evolutionary narrative, the work underscores a theme that resonates throughout modern biology: even the most intricate molecular machines of complex cells are built from parts with far older histories, and reconstructing those histories is essential for understanding how the machinery works today.

Subject of Research: Evolutionary origins and diversification of autophagy-related genes across prokaryotes and eukaryotes

Article Title: Autophagy genes across the tree of life: from prokaryotic homologs to eukaryotic complexity

Article References: Zhang, S., & Mizushima, N. (2026). Autophagy genes across the tree of life: from prokaryotic homologs to eukaryotic complexity. Cellular and Molecular Life Sciences. https://doi.org/10.1007/s00018-026-06423-7

Image Credits: AI Generated

DOI: 10.1007/s00018-026-06423-7

Keywords: autophagy, ATG genes, macroautophagy, eukaryogenesis, last eukaryotic common ancestor, prokaryotic homologs, gene duplication, genome evolution, phylogenetics, autophagosomes, cellular degradation, evolution