Dormancy is colloquially considered as extending lifespan by being still. Starved yeasts form dormant spores that wake-up (germinate) when nutrients reappear but cannot germinate (die) after some time. What sets their lifespans and how they age are open questions because what processes occur-and by how much-within each dormant spore remains unclear. With single-cell-level measurements, we discovered how dormant yeast spores age and die: spores have a quantifiable gene-expressing ability during dormancy that decreases over days to months until it vanishes, causing death. Specifically, each spore has a different probability of germinating that decreases because its ability to-without nutrients-express genes decreases, as revealed by a synthetic circuit that forces GFP expression during dormancy. Decreasing amounts of molecules required for gene expression-including RNA polymerases-decreases gene-expressing ability which then decreases chances of germinating. Spores gradually lose these molecules because they are produced too slowly compared with their degradations, causing gene-expressing ability to eventually vanish and, thus, death. Our work provides a systems-level view of dormancy-to-death transition.

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The conventional view is that high temperatures cause microorganisms to replicate slowly or die. In this view, microorganisms autonomously combat heat-induced damages. However, microorganisms co-exist with each other, which raises the underexplored and timely question of whether microorganisms can cooperatively combat heat-induced damages at high temperatures. Here, we use the budding yeast Saccharomyces cerevisiae to show that cells can help each other and their future generations to survive and replicate at high temperatures. As a consequence, even at the same temperature, a yeast population can exponentially grow, never grow or grow after unpredictable durations (hours to days) of stasis, depending on its population density. Through the same mechanism, yeasts collectively delay and can eventually stop their approach to extinction, with higher population densities stopping faster. These features arise from yeasts secreting and extracellularly accumulating glutathione—a ubiquitous heat-damage-preventing antioxidant. We show that the secretion of glutathione, which eliminates harmful extracellular chemicals, is both necessary and sufficient for yeasts to collectively survive at high temperatures. A mathematical model, which is generally applicable to any cells that cooperatively replicate by secreting molecules, recapitulates all of these features. Our study demonstrates how organisms can cooperatively define and extend the boundaries of life-permitting temperatures.

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Cells form spatial patterns by coordinating their gene expressions. How a group of mesoscopic numbers (hundreds to thousands) of cells, without pre-existing morphogen gradients and spatial organization, self-organizes spatial patterns remains poorly understood. Of particular importance are dynamic spatial patterns such as spiral waves that perpetually move and transmit information. We developed an open-source software for simulating a field of cells that communicate by secreting any number of molecules. With this software and a theory, we identified all possible “cellular dialogues”—ways of communicating with two diffusing molecules—that yield diverse dynamic spatial patterns. These patterns emerge despite widely varying responses of cells to the molecules, gene-expression noise, spatial arrangements, and cell movements. A three-stage, “order-fluctuate-settle” process forms dynamic spatial patterns: cells form long-lived whirlpools of wavelets that, following erratic dynamics, settle into a dynamic spatial pattern. Our work helps in identifying gene-regulatory networks that underlie dynamic pattern formations. Dang et al. developed a software and a theoretical framework to discover and classify all moving spatial patterns (e.g., waves) that cells can form by secreting two diffusible molecules that control their gene expressions. They identified all gene regulations that the molecules can have for forming moving patterns, which self-organize through a three-stage, “order-fluctuate-settle” dynamic.

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One snapshot of the peer review process for “Death Rate of E. coli during Starvation Is Set by Maintenance Cost and Biomass Recycling” (Schink et al., 2019).

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Communicating is crucial for cells to coordinate their behaviors. Immunological processes, involving diverse cytokines and cell types, are ideal for developing frameworks for modeling coordinated behaviors of cells. Here, we review recent studies that combine modeling and experiments to reveal how immune systems use autocrine, paracrine, and juxtacrine signals to achieve behaviors such as controlling population densities and hair regenerations. We explain that models are useful because one can computationally vary numerous parameters, in experimentally infeasible ways, to evaluate alternate immunological responses. For each model, we focus on the length-scales and time-scales involved and explain why integrating multiple length-scales and time-scales in a model remain challenging. We suggest promising modeling strategies for meeting this challenge and their practical consequences.

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Communicating cells can coordinate their gene expressions to form spatial patterns, generating order from disorder. Ubiquitous “secrete-and-sense cells” secrete and sense the same molecule to do so. Here we present a modeling framework—based on cellular automata and mimicking approaches of statistical mechanics—for understanding how secrete-and-sense cells with bistable gene expression, from disordered beginnings, can become spatially ordered by communicating through rapidly diffusing molecules. Classifying lattices of cells by two “macrostate” variables—“spatial index,” measuring degree of order, and average gene-expression level—reveals a conceptual picture: a group of cells behaves as a single particle, in an abstract space, that rolls down on an adhesive “pseudo-energy landscape” whose shape is determined by cell-cell communication and an intracellular gene-regulatory circuit. Particles rolling down the landscape represent cells becoming more spatially ordered. We show how to extend this framework to more complex forms of cellular communication.@en

Living systems, particularly multicellular systems, often seem hopelessly complex. But recent studies have suggested that, beneath this complexity, there may be unifying quantitative principles that are only now starting to unravel. All cells interact with their environments and with other cells. Communication among cells is a primary means for cells to interact with each other. The complexity of these multicellular systems, due to the large numbers of cells and the diversity of intracellular and intercellular interactions, makes understanding multicellular systems a daunting task. To overcome this challenge, we will likely need judicious simplifications and conceptual frameworks, which can reveal design principles that are shared among diverse multicellular systems. Here we review some recent progress toward developing such frameworks.@en