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 PP08: V: Multicellular Phenomena IIFocus
|
Hide Abstracts |
Sponsoring Units: DBIO Chair: Dominic Alfonso, National Energy Technology Laboratory Room: Virtual Room 8 |
Tuesday, March 21, 2023 9:00AM - 9:36AM |
PP08.00001: Non-Gaussian random matrices predict the stability of feasible Lotka-Volterra communities Invited Speaker: Tobias Galla 50 years ago Robert May sparked the `diversity-stability debate' in ecology. He assumed that the "community matrix" describing the interactions in an ecosystem has random entries. May concluded from the analysis of the eigenvalues of these matrices that large ecosystems would be less stable than smaller ones. A decade-long debate ensued, including a number of recent high-profile papers extending May’s work to matrices with more structure. Much of the work in this area relies on random matrix theory, that is, techniques for the calculation of the eigenvalue spectrum of ensembles of random matrices. One major criticism of May’s approach is that it does not address the question how the ecological community arises from a dynamics, and whether the equilibrium is `feasible' or not. Here, I will first discuss recent work in which we calculate the bulk and outlier eigenvalues of the most general Gaussian ensemble of random matrices, which does not systematically give preference to any species over another. I will then show how May’s approach can be used for feasible communities arising from the survivors in a dynamic Lotka-Volterra model with random interactions. The ensemble of interactions among extant species turns out to be non-Gaussian, even if the original interaction matrix among all species is Gaussian. I will then demonstrate that random-matrix universality does not apply, i.e. a Gaussian calculation fails to predict the leading eigenvalue correctly. I will show how tools from the theory of disordered systems can be used to account for non-Gaussian features of the interactions, and to obtain the spectra of the community matrix of survivors. The stability criteria from these eigenvalue spectra agree with those obtained from the Lotka-Volterra equations. Hence, we have demonstrated how May’s random-matrix approach can be used to characterise the stability of feasible equilibria. Feasibility is encoded in the higher-order non-Gaussian statistics of the community matrices arising from the survivors in Lotka-Volterra systems. |
Tuesday, March 21, 2023 9:36AM - 9:48AM Author not Attending |
PP08.00002: Population Diversity and Fitness Uncertainty Allow for Faster Evolutionary Rates Luis Pedro P Garcia-Pintos I show uncertainty relations that bound the rate of evolutionary processes driven by natural selection, mutations, or by stochastic forces. These rate limits imply that diversity in a population allows for faster evolutionary rates. In particular, the uncertainty of the fitness function is singled out as necessary for fast evolution driven by natural selection. These results generalize Fisher's fundamental theorem of natural selection to dynamics that allow for mutations in terms of uncertainty relations that constrain evolutionary rates. |
Tuesday, March 21, 2023 9:48AM - 10:00AM |
PP08.00003: A simplified drift-diffusion model for Pandemic Propagation Abhimanyu Ghosh, Clara Bender, Preetam Ghosh, Hamed Vakili We present a simplification of the susceptible-infected-recovery (SIR) and SIRS models for pandemic propagation that allows a quasi-analytical treatment of COVID-19 propagation across multiple countries. We discuss various sources of errors and uncertainty in the underlying parameters, ranging from complexity of interactions, finite sample effects and reporting uncertainty. We show how we can interpret the evolution of the probability density function in terms of an overdamped classical particle diffusing in a tunable potential. |
Tuesday, March 21, 2023 10:00AM - 10:12AM |
PP08.00004: Synthetic Gene Circuits: Evolution of Drug Resistance Evolution in Fluctuating Drug Conditions Harold G Flohr Genetically identical cells can produce different levels of gene expression products due to stochastic or “noisy” processes inside the cell. This phenomenon has been shown to enable bacterial and fungal cell populations with resistance to constant drug treatment. We investigated drug resistance arising from gene expression noise using genetically engineered yeast (S. cerevisiae) exposed to fluctuating drug conditions. Growth rates, gene expression means, and noise levels were experimentally measured for a drug resistance gene controlled by an inducible synthetic gene circuit. These laboratory evolution experiments were conducted for low-, medium-, and high-drug concentrations. Our results show that most replicates evolved to lower gene expression in low-drug conditions, and increase gene expression in higher-drug conditions. Counterintuitively, for all drug concentrations, the gene expression noise levels were often lower in fluctuating drug conditions compared to constant drug conditions. |
Tuesday, March 21, 2023 10:12AM - 10:24AM |
PP08.00005: High-dimensional characterization of phototroph-heterotroph interactions Chandana Gopalakrishnappa, Zeqian Li, Seppe Kuehn Interactions between phototrophic and heterotrophic microbes lie at the heart of global biogeochemistry, ecosystem productivity, and biofuel generation. These microbes are known to interact with each other via resource exchange and competition - Phototrophs provide organic carbon to heterotrophs and heterotrophs provide essential micronutrients to phototrophs while they compete with each other for inorganic nutrients such as phosphorus and nitrogen. However, we lack a quantitative understanding of how the interactions between phototrophs and heterotrophs are impacted by the chemical nature of the environment. To address this, we conducted experimental studies to assay interactions between the phototroph, Chlamydomonas reinhardtii, and the heterotroph, Escherichia coli, as a function of five environmental parameters - pH, buffering capacity,availability of three non-substitutable resources - carbon, nitrogen, and light. To aid this high-dimensional study, a high throughput droplet-based microfluidic platform that allows us to rapidly construct thousands of environmental conditions was implemented. Using this platform, we have screened for interactions in our model phototroph-heterotroph system in ~840 environmental conditions, by setting up ~200,000 microcosms on the microfluidic platform. Using machine learning, we show that the parameters pH and buffering capacity control the interaction structure in phototroph-heterotroph communities. Further, we find that the nature of the carbon source driving heterotroph growth - glycolytic or gluconeogenic alters the interaction structure via impacting pH. These results are in contrast to the prevailing view that phototroph-heterotroph interactions are governed primarily by the exchange of and competition for nutrients. Our work presents a new view of how the chemical environment impacts phototroph-heterotroph interactions. |
Tuesday, March 21, 2023 10:24AM - 10:36AM |
PP08.00006: Structured interactions explain the absence of keystone species in synthetic marine microcosms Sivan Pearl, Hyunseok Lee, Akshit Goyal, Jeffrey C Gore From oceans to guts, ecosystems are held together by complex interspecies interactions, and can experience dramatic impacts when certain "keystone" species are removed. Yet, both the prevalence of keystone species and the ecological factors that favor their emergence remain unknown. Here, by experimentally assembling complex marine microcosms in a range of controlled environmental conditions, we find that dramatic impacts (extinctions or blooms of other species) are exceedingly rare upon removal of a species, consistent with no species being a keystone. By mathematically modeling communities with interspecies interactions, we show how progressively structured interactions, as opposed to independent interactions, can systematically reduce the incidence of keystone species. Finally, using statistical learning, we infer the interspecies interactions in our laboratory microcosms and test this theoretical prediction, finding that the interactions are indeed strongly structured. Specifically, species with large abundance experience strong interactions from others, but interact weakly with them in return. Our results suggest that structured interactions may be prevalent in communities, and connect them with the apparent absence of keystone species with dramatic impacts. |
Tuesday, March 21, 2023 10:36AM - 10:48AM |
PP08.00007: Optical reflection statistics from a thin weakly disordered optical media: application to detection of structural alterations in cells/tissues Alexander Punnoose, Shirsendu Nanda, Prabhakar Pradhan Light-scattering from a weakly disordered optical medium with a mean refractive index different from the embedding medium is studied. In the disordered thin-film limit, a linearized one-dimensional stochastic model is introduced to derive the full statistics of the reflected light. A new decorrelation length scale arises from the interplay between disorder scattering and thin-film interference. |
Tuesday, March 21, 2023 10:48AM - 11:00AM |
PP08.00008: Flow Physics Explains Morphological Diversity of Ciliated Organs Feng Ling, Eva Kanso, Janna C Nawroth Ciliated organs that pump luminal fluids are integral to animal physiology. For example, millions of short epithelial cilia direct mucus flow to continuously clear pathogens out of the human airways. However, many other ciliated organs in the animal kingdom admit drastically different morphology and cilia organization to this familiar ciliary carpet archetype, and it is unclear how this structural diversity relates to the fluid pumping abilities of ciliated organs in general. Here, we apply morphometric and mechanistic analyses to ciliated ducts across all animal phyla. We find that two structural parameters, lumen diameter and cilia-to-lumen ratio, organize the observed duct diversity into a continuous spectrum that connects ciliary carpet designs to ciliary flame designs where long beating cilia can fill most of the luminal space. Using our unified fluid model, we further establish that carpets and flames, respectively, maximize flow rate and pressure generation, which is consistent with physiological requirements for bulk transport and filtration, whereas intermediate designs along the morphological spectrum constitute optimally efficient hybrids. We propose that convergence of ciliated organ designs follows functional constraints rather than phylogenetic distance, and we present universal design rules that can also guide the design of synthetic ciliary pumps. |
Follow Us |
Engage
Become an APS Member |
My APS
Renew Membership |
Information for |
About APSThe American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics. |
© 2024 American Physical Society
| All rights reserved | Terms of Use
| Contact Us
Headquarters
1 Physics Ellipse, College Park, MD 20740-3844
(301) 209-3200
Editorial Office
100 Motor Pkwy, Suite 110, Hauppauge, NY 11788
(631) 591-4000
Office of Public Affairs
529 14th St NW, Suite 1050, Washington, D.C. 20045-2001
(202) 662-8700