Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session S14: Optimal Trade-Offs Determining Quantitative Biological ParametersInvited Live Streamed
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Sponsoring Units: DBIO Chair: Massimo Vergassola Room: McCormick Place W-183B |
Thursday, March 17, 2022 8:00AM - 8:36AM |
S14.00001: The cost-performance tradeoffs in biochemical clocks Invited Speaker: Yuansheng Cao Biological systems need to function accurately in the presence of strong noise and at the same time respond sensitively to subtle external cues. One example is the circadian clock in a broad range of biological systems. Biochemical clocks are composed of chemical reactions that consume free energy; they need to operate in a precise period to maintain their biological functions while remaining susceptible to day-night shifts. Moreover, molecular clocks have multiple copies in many living systems. The fluctuations between different clocks introduce even more uncertainty for the performance of their functions. Here we present a series of work on how biochemical clocks can utilize free energy to reduce phase fluctuations, enhance response sensitivity and achieve synchronization between molecular clocks. The free energy cost-performance tradeoffs are given in quantitative relations, from where we outline several design principles for optimal biochemical clocks. |
Thursday, March 17, 2022 8:36AM - 9:12AM |
S14.00002: Optimization of lysogeny frequency for temperate phages Invited Speaker: Kim Sneppen Upon infection temperate phages chose between lysogenic and lytic developmental strategies. We suggest to apply the game-theoretic bet-hedging strategy introduced by Kelly to derive the optimal lysogenic fraction of the total population of phages. Our proposed "Well-temperate" phage is realized when the lysogenization frequency is approximately equal to the probability of lytic population collapse.. We further predict the existence of sharp boundaries in system's environmental parameters separating the regions where this temperate strategy is optimal from those dominated by purely virulent or dormant strategies. Our formalism predict that progressively more temperate or even dormant strategies are favored in highly fluctuating environments. |
Thursday, March 17, 2022 9:12AM - 9:48AM |
S14.00003: Non-genetic variability in microbes: Benefits and detriments Invited Speaker: Ariel Amir The observation that non-genetic variability is ubiquitous in microbial populations has led to a multitude of experimental and theoretical studies seeking to probe the causes and consequences of this variability. Whether it be in the context of antibiotic treatments or exponential growth in constant environments, variability has significant effects on population dynamics. I will first present a coarse-grained model for cell growth, inspired by the Langevin equation, which incorporates stochasticity in both biomass growth rates and generation times. Building on it, we will connect single-cell variability to the population growth, showing that in contrast to the dogma growth-rate fluctuations may lower the population growth. Analogous results are derived in the case where the variability arises from the asymmetric partitioning of a cellular resource, where we find a phase transition between a regime where variability is beneficial to one where it is detrimental. |
Thursday, March 17, 2022 9:48AM - 10:24AM |
S14.00004: Transport in insect respiratory systems Invited Speaker: Tatyana Gavrilchenko Biological flow networks, present in the vasculature of plants and animals, are a foundational feature of life. The connection between structure and function in these systems is key for understanding their development as well as their ability to adapt to adverse conditions. The problem of how vasculature delivers oxygen to tissues has been studied in many contexts, yet a comprehensive data set to test transport models is lacking due to the inherent complications of imaging a significant portion of living vasculature in full detail. The respiratory system of insects is an ideal model system: its structure can be imaged clearly and entirely because it is relatively simple compared to mammalian vasculature and because it can be tagged with fluorescent protein markers to increase image contrast. In Drosophila melanogaster larvae, the respiratory system is a dense tubular network of hollow channels permeating the body, reaching within microns of each living cell. Oxygen delivery is driven by diffusion: air enters through external openings and fills the channels. Gas exchange occurs primarily in branched tree-like structures known as terminal cells, which have permeable walls allowing oxygen to leak out and become absorbed by the surrounding tissue. We present a model of perfusion-based transport on a network, analyzing the oxygen concentration field predicted by this model when applied to our data set of hundreds of terminal cells. This physical modeling allows us to map the distribution of cellular structures to a distribution of oxygen fluxes that these cells deliver. |
Thursday, March 17, 2022 10:24AM - 11:00AM |
S14.00005: The optimal checkpoint strategy predicts experimental checkpoint override times Invited Speaker: Sahand Rahi Why biological quality-control systems fail is often mysterious. Specifically, checkpoints in yeast and animals are overridden after prolonged arrests allowing self-replication to proceed despite the continued presence of errors. Although critical for the organism, checkpoint override is not understood quantitatively by experiment or theory. To uncover laws governing the dynamics of error-correction systems, we derived a general theory of optimal checkpoint strategies, balancing the trade-off between risk and self-replication opportunity. We show that the mathematical problem of finding the optimal strategy maps onto the question of calculating the optimal absorbing boundary for a random walk, which we show can be solved efficiently recursively. The theory predicts the optimal override time without free parameters based on the statistics i) of error correction and ii) of survival. We applied the theory experimentally to the DNA damage checkpoint in budding yeast, an intensively researched model for eukaryotic checkpoints, whose override is nevertheless not understood quantitatively, functionally, or at the system level. Using a novel fluorescent construct which allowed cells with DNA breaks to be isolated by flow cytometry, we quantified i) the probability distribution of repair for a double-strand DNA break (DSB), including for the critically important, rare events deep in the tail of the distribution and ii) the survival probability after override. Based on these two measurements, the optimal checkpoint theory predicted remarkably accurately the DNA damage checkpoint override times as a function of DSB numbers, which we also measured for the first time precisely. Thus, a first-principles calculation uncovered hitherto hidden patterns underlying the highly noisy checkpoint override process. The universal nature of the balance between risk and self-replication opportunity is in principle relevant to many other systems, suggesting further applications. |
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