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 Y08: Evolutionary Dynamics IFocus
|
Hide Abstracts |
Sponsoring Units: DBIO Chair: Antun Skanata, Syracuse University Room: Room 131 |
Friday, March 10, 2023 8:00AM - 8:36AM |
Y08.00001: Ecological feedbacks in evolutionary rescue Invited Speaker: Jeremy Draghi
|
Friday, March 10, 2023 8:36AM - 8:48AM |
Y08.00002: Self-propelled adaptive evolution on malleable dynamic fitness landscapes Alexander Heyde, L Mahadevan Evolving populations, from cells to organisms, adapt to the demands of their environment, yet in modifying their environment, they directly alter the selective pressures they experience, thereby reshaping their local fitness landscape. Here we present a minimal two-field model to capture this eco-evolutionary feedback loop. We consider two coupled, antisymmetric dynamical equations, one to govern the adapting population, and another to govern the shifting landscape that it traverses, with a scalar parameter to set the relative balance of evolutionary and ecological change. We analyze these joint dynamics to quantify the extent to which this feedback loop can dramatically accelerate the rate of evolution and enable a population to self-propel through trait space, not only to climb local selection gradients, but also to evolve in the absence of or against these gradients. We calculate the speciation (evolutionary branching) rate and the onset of chaos, derive approximate moment equations to extend Fisher's fundamental theorem, and highlight connections with adaptive dynamics and the generalized Lotka-Volterra formalism. We comment on the interpretation of our equations in the context of niche construction, ecological inheritance, and climate change. |
Friday, March 10, 2023 8:48AM - 9:00AM |
Y08.00003: Frequent hybridization and gene sweeps shape evolution of a natural bacterial population Gabriel Birzu, Daniel S Fisher, Devaki Bhaya Genetic sequencing of natural bacterial populations often reveal distinct genomic clusters. At the same time, recent studies have shown extensive recombination across a wide range of genetic divergences, raising the question of how can clusters be maintained over time. Previous studies have shown that ecological separation can emerge within highly-recombining bacterial populations. However, whether this mechanism can prevent the hybridization and merging of distinct clusters is not known. Here, we use the evolution of a diverse population of cyanobacteria from the Yellowstone hot springs as natural experiment to address this question. |
Friday, March 10, 2023 9:00AM - 9:12AM Author not Attending |
Y08.00004: Characterizing diversity and genetic exchange in marine Prochlorococcus Alana Papula, Daniel S Fisher Marine Prochlorococcus is the most abundant photosynthetic organism on Earth, responsible for about 10% of global carbon fixation. It is a very diverse species with many layers of population structure. Despite the importance of the species, little is known about gene flow across its many scales of diversity. I will describe our recent efforts using hundreds of single cell genomes to elucidate a quantitative description of horizontal transfer of core genes in Prochlorococcus. These cells range from the most closely-related cells sequenced to date, whose genomes are largely asexual punctuated by discrete transfer events, to cells whose genomes have been overwritten and shuffled by recombination, to the most disparate Prochlorococcus cells, which are more than 50% diverged. We find that gene flow connects the entire species, identify the scale at which genomes become completely unlinked, estimate the distribution of recombination rates as a function of sequence divergence , and hope to connect these findings to ecology. |
Friday, March 10, 2023 9:12AM - 9:48AM |
Y08.00005: Evolution of microbial growth dynamics Invited Speaker: Michael Manhart The relationship between nutrient availability and growth rate is key to predicting the behavior of microbial ecosystems. Like all biological traits, the nutrient-growth relationship is subject to the fundamental evolutionary processes of mutation, selection, and genetic drift. Using a combination of empirical data and mathematical models, I will show how these evolutionary processes address two longstanding questions about the nutrient-growth relationship. 1) Should an organism's growth affinity for a nutrient be commensurate with that nutrient's environmental concentration? Since environmental concentrations (especially from the past) are often difficult to measure, a proportionality between these quantities has been assumed by many previous studies to infer the environment from growth traits. I will show that this is false under some modes of population dynamics, due to different environmental dependences of selection and genetic drift. This means that populations evolving in nutrient-rich environments can still have fast growth in nutrient-poor environments. 2) Are microbes limited by only one nutrient at a time, or can they be colimited by multiple nutrients? Colimitation has long been suspected in aquatic environments, where multiple nutrients are simultaneously rare. I will show that selection should indeed drive populations toward colimitation in general. When some of the nutrients are cross-fed between species, I will show how the evolved degree of colimitation corresponds to a balance between competition and cooperation between the species. Altogether these results demonstrate the importance of evolutionary processes in shaping fundamental aspects of microbial ecology. |
Friday, March 10, 2023 9:48AM - 10:00AM |
Y08.00006: Inferring epistasis for HIV evolution Kai Shimagaki, John P Barton Biological systems such as viruses evolve under natural selection as well as stochastic fluctuations. Often, such natural selection is characterized as a fitness landscape that is closely related to the free energy landscape in statistical physics and can involve pairwise interactions between mutantions. Inferring fitness landscapes is theoretically and practically important to predict patterns of future evolution. |
Friday, March 10, 2023 10:00AM - 10:12AM |
Y08.00007: Inferring mutation rates from evolutionary histories with path integral methods Uchenna D Nwaege, John P Barton Living things evolve to increase their chances of survival within their environment. The same process also occurs for pathogens such as viruses or bacteria within a host. Better understanding the evolution of antibiotic resistance or how pathogens escape from immune responses may inform the design of better treatment techniques and vaccines. Evolutionary models such as the Wright-Fisher model can simulate such processes. However, these models depend on knowing detailed properties of a pathogen, such as its mutation rate and how mutations affect its fitness. Here we study how such properties can be inferred from data, in particular, genetic sequences collected over time from a population. Recent work applied techniques from statistical physics to models from population genetics to derive a path integral that efficiently quantifies the probability of an evolutionary history of a population. This allowed for the estimation of the fitness effects of mutations from data, assuming that the underlying mutation rates were known. Here, we consider the opposite case: how can mutation rates be estimated from data, assuming that the underlying fitness effects of mutations are given. We derive an approximate expression to estimate mutation rates from data in this scenario and show its performance in example simulations. |
Friday, March 10, 2023 10:12AM - 10:24AM |
Y08.00008: Quantifying adaptive landscapes of commensal gut bacteria using high-resolution lineage tracking Daniel Wong, Benjamin H Good Gut microbiota can adapt to their host environment by rapidly acquiring new mutations. However, the evolutionary dynamics of process are difficult to characterize in dominant gut species in their complex in vivo environment. In this talk, I will show how the fine-scale dynamics of genome-wide transposon libraries can enable quantitative inferences of these in vivo evolutionary forces. By modeling the collective behavior of >400,000 lineages across four human gut bacteria in germ-free mice, we detected positive selection on thousands of previously hidden mutations – most of which were unrelated to their original gene knockouts. We found that the spectrum of fitness benefits varied between closely related gut species, and displayed diverse tradeoffs over time and in different dietary conditions. However, our broader characterization revealed few global tradeoffs in the underlying fitness landscapes. This suggests that long-term fitness tradeoffs under different diets may not reflect a fundamental physiological constraint, but simply the entropic sampling of the adaptive landscape. |
Friday, March 10, 2023 10:24AM - 10:36AM |
Y08.00009: Evolution of Evolvability in Rapidly Evolving Populations James Ferrare, Benjamin H Good Mutations can affect the short-term fitness of an organism, as well as the rates and benefits of future mutations. While numerous examples of these evolvability modifiers have been observed in rapidly adapting microbial populations, existing theory struggles to predict when they will be favored by natural selection. Here, we develop a mathematical framework for predicting the fates of mutations that modify the rates and fitness benefits of future mutations. We derive analytical expressions showing how the fixation probabilities of these mutations depend on the size of the population and the diversity of competing mutations. We find that competition between linked mutations can dramatically enhance selection for modifiers that increase the benefits of future mutations, even when they impose a strong direct cost on fitness. Conversely, we find that relatively modest direct benefits can be sufficient to drive evolutionary dead-ends to fixation. Our results suggest that subtle differences in evolvability could play an important role in shaping the long-term success of genetic variants in rapidly evolving microbial populations. |
Friday, March 10, 2023 10:36AM - 10:48AM |
Y08.00010: Linkage equilibrium between rare alleles Anastasia S Lyulina, Zhiru Liu, Benjamin H Good Recombination is ubiquitous among bacteria, but the extent to which it shapes genetic diversity within bacterial populations remains elusive. Classical approaches for measuring recombination focus on the correlations between alleles ("linkage disequilibrium"), and how they decay with the distance between loci. However, the overall levels of linkage disequilibrium are influenced by other evolutionary forces like natural selection and genetic drift, which makes it difficult to tease out the effects of recombination. Here, we introduce an alternative metric ("linkage equilibrium") that vanishes in the absence of recombination and approaches one for unlinked loci. We derive analytical expressions that predict how this metric scales with the rate of recombination, the strength of selection, and the present-day frequencies of the two alleles. We find that our linkage equilibrium metric strongly depends on this frequency scale, which reflects the underlying timescales over which these mutations occurred. We show how this scaling could be used to quantify the relative strengths of selection and recombination, and discuss their implications for recombination patterns in bacteria. |
Friday, March 10, 2023 10:48AM - 11:00AM |
Y08.00011: Predicting the structure of GxE and GxGxE interactions in Saccharomyces cerevisiae Sarah Ardell, Alena Martsul, Milo Johnson, Sergey Kryazhimskiy Evolutionary dynamics depend on how segregating alleles affect organismal fitness. A major obstacle to understanding these dynamics is that the fitness effect of an allele often changes across genetic backgrounds (GxG interactions) and environments (GxE interactions) or both (GxGxE interactions). The statistics of these interactions are in general poorly characterized, but a recently discovered heuristic rule, called "diminishing returns epistasis" (DRE), predicts a substantial fraction of GxG interactions. Here, we show that a straightforward extension of this rule also predicts the statistics of GxE and GxGxE interactions. To test this prediction, we carried out RB-TnSeq experiments where we measured the fitness effects of ~100 insertion mutations across 42 strains of yeast Saccharomyces cerevisiae in 6 environments that vary by temperature and pH, two stressors with global effects on yeast physiology. We find that our predictions explain a substantial fraction of measured GxE and GxGxE effects. Additionally, we uncover that the environment impacts only the intercept, and not the slope, of the DRE patterns (e.g how selection coefficient changes with strain fitness) for the majority of mutations measured. These findings are a substantial step forward toward the goal of predicting fitness trajectories in variable environments. |
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