Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session A06: Non-Equilibrium Thermodynamics: From Natural Selection to Chemical Reaction NetworksFocus
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Sponsoring Units: DBIO Chair: William Cannon, Pacific Northwest Natl Lab Room: Room 129 |
Monday, March 6, 2023 8:00AM - 8:36AM |
A06.00001: Metabolic constraints in the evolution of biochemical networks Invited Speaker: Efe Ilker Metabolism and evolution are closely connected: if a mutation incurs extra energetic costs for an organism, there is a baseline selective disadvantage that may or may not be compensated for by other adaptive effects. In our recent work, we prove a mathematical relationship between the added bioenergetic burden of newly emerging biochemical networks and the fitness disadvantage for the organism. The derivation is based on a general growth model and can be extended to capture the effects of other limiting factors constraining the growth. I will discuss the significance of this contribution from metabolic expenditures in the course of evolution, by considering the population dynamics. As an example, I will illustrate the trade-offs in the evolution of noise control in microRNA-regulated gene networks which play a critical role by controlling developmental processes of complex organisms and related diseases. |
Monday, March 6, 2023 8:36AM - 9:12AM |
A06.00002: From Metabolites to Cells: A Perspective on Non-Equilibrium Thermodynamics Connah G Johnson Cells may be seen as chemical factories, processing a fuel source taken from the environment and producing the chemical building blocks vital for life. However, cells are rarely found in isolation with many biological systems being spatially organised. Understanding the non-equilibrium thermodynamics behind cell growth, cell death, and self-organisation is of great importance for when we want to program bio-systems for "useful" work such as biofuel production or industrial chemical synthesis. |
Monday, March 6, 2023 9:12AM - 9:24AM |
A06.00003: Efficient Two-Dimensional Control of Barrier Crossing Steven Blaber, David A Sivak Modern advances in single-molecule biophysics make possible the precise spatial and temporal control of biological systems. Despite the relative freedom of control, experiments and simulations rarely exploit the possibility of optimized control protocols, and the ones that do are generally limited to optimization of a single control parameter. We design minimum-dissipation protocols for harmonic trapping potentials under two-dimensional control (of both trap center and stiffness), for driven barrier crossing. This greater control allows specification of both the time-dependent mean and variance of the position distribution, and results in qualitatively distinct designed protocols. For any duration, the designed protocols significantly improve performance in terms of both dissipation and flux compared to naive and one-dimensional control. |
Monday, March 6, 2023 9:24AM - 9:36AM |
A06.00004: Stochasticity and Homeostasis in Macromolecular Crowding and its Effects on the Rates of Reproduction Andreas E Vasdekis, Shahla Nemati, Abhyudai Singh, Scott Dhuey, Armando McDonald, Daniel Weinreich Binary fission can be prone to noise and stochasticity, with daughter cells rarely born at identical sizes with each other. Here, we will present our recent results on how the mother's mass and macromolecular load is also not necessarily divided equally between daughter cells. This phenomenon gives rise to a non-genetic form of cell-to-cell variability in the intracellular levels of macromolecular crowding. We will discuss how this form of stochasticity in macromolecular load levels is subject to homeostasis. In this context, individual cells undergo a form growth differentiation with some exhibiting higher mass accumulation rates identical size and mass rates. This form of differentiation not only acts as a homeostatic mechanism against crowding noise, but also has distinct impacts on the reproduction rates of single-bacteria and, as such, the growth-rates of a population. We will conclude with the dedicated quantitative-mass imaging method we developed for this work, as well as the invisible microfluidics we deployed to specifically enhance the precision of our measurements by more than 60%. |
Monday, March 6, 2023 9:36AM - 9:48AM |
A06.00005: Quantifying biochemical reaction rates from static population variability within incompletely observed complex networks Andreas Hilfinger, Nava Leibovich, Timon Wittenstein Testing mechanistic models of complex cellular processes remains a key challenge of systems biology despite the availability of high-throughput snapshot data from single-cells. That is because completely specified mechanistic models typically have to make so many assumptions that each individual assumption is only marginally tested in global model comparisons with data. We show how incompletely specified mechanistic models can be used to translate qualitative knowledge of molecular interactions into reaction rate functions from covariability data between pairs of components. In contrast to existing methods, our approach does not require perturbations, temporal information, observing all components within a complex network, or complete model knowledge. Its key ingredients are universal probability balance equations for stationary stochastic processes combined with partial knowledge of qualitative network interactions and high precision probability distributions to quantify fluctuations within biochemical reaction networks. This approach promises to turn a globally intractable problem into a sequence of solvable inference problems to quantify complex interaction networks from snapshots of their stochastic fluctuations. |
Monday, March 6, 2023 9:48AM - 10:00AM |
A06.00006: How to suppress stochastic fluctuations while achieving adaptation with biologically realistic integral controllers Brayden J Kell, Andreas Hilfinger, Ryan Ripsman A key challenge in biology is identifying biochemical modules with network-independent properties. Antithetic integral feedback (AIF) is a recently proposed module in which two species perfectly annihilate each other's biological activity. The AIF module ensures the steady-state average level of any cellular component remains constant under sustained perturbations, regardless of that component's uncontrolled dynamics. However, recent work has suggested that such robustness comes at the expense of increased stochastic fluctuations. We present theoretical results that support and quantify this trade-off for the commonly analyzed AIF variant in the non-biological limit with perfect annihilation. However, we find that this trade-off is a singular behaviour of the idealized module: even minute deviations from perfect adaptation permit significant noise suppression. While our results highlight the energetic cost of simultaneously achieving robust averages and reducing stochastic fluctuations, they show that there is no fundamental trade-off between the two. This is further supported by data for other variants of the AIF module that can reduce noise even in the idealized case, which highlights that some realizations of the AIF module have preferrable noise properties for synthetic biology applications. |
Monday, March 6, 2023 10:00AM - 10:12AM |
A06.00007: Degrading a gradient: information transmission in yeast mating Ryan LeFebre, Joseph Landsittel, David Stone, Andrew Mugler Chemical gradient sensing is ubiquitous in biology. From development to migration, it plays a significant role in both multi-cellular and single-celled organisms. In haploid yeast cells of two types, the detection of chemical gradients is used to find a suitable mating partner. Each mating type secretes a pheromone that is sensed by the partner type. Paradoxically, one of the mating types also secretes an enzyme that degrades the attractant pheromone of its partner type. This degradation is vital for efficient mating. It is thought that degradation leads to a steepened gradient, but the roles of noise and information transmission are poorly understood. Can destroying part of a signal you detect increase the amount of information you receive? Using both stochastic spatiotemporal modeling and tools from information theory, we find that the answer is yes: both the signal-to-noise ratio and information transmission increase with degradation. Our work helps explain a counterintuitive signaling strategy in yeast and offers insights into optimal sensory strategies more generally. |
Monday, March 6, 2023 10:12AM - 10:24AM |
A06.00008: Analysis of the dynamics of the growing and branching network of filamentous fungus Podospora anserina. Thibault Chassereau, Éric Herbert, Florence Chapeland-Leclerc The success of filamentous fungi in colonizing most natural environments can be largely attributed to their ability to form an expanding interconnected network, the mycelium, or thallus, constituted by a collection of growing hyphal apexes producing hyphae and subject to branching and fusion. In this work, we characterize the hyphal network expansion and the structure of the filamentous fungus Podospora anserina under controlled culture conditions. To this end, temporal series of pictures of the network dynamics are produced, starting from germinating ascospores (1 node) and ending when the network reaches thousands of connections. The completely automated image reconstruction steps allow a post-processing and a quantitative analysis of the spatio-temporal dynamics. Taking advantage of the network's properties we can numerically identify each individual hypha and its nature (apical or lateral). With this method we plan to discriminate hyphal fusion (anastomoses) from mere overlapping. Thanks to the reconstruction of each hypha, we can analyse the growth of the network at both local and global scale. |
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