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  • 1.
    Andersson, Rebecka
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Isaksson, Hanna
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Libby, Eric
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Santa Fe Institute, NM, Santa Fe, USA.
    Multi-species multicellular life cycles2022Ingår i: The evolution of multicellularity, CRC Press, 2022, s. 343-356Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    Textbook examples of multicellular organisms vary in their scale and complexity but are typically composed of a single species. The prevalence of entities such as lichens, however, suggest that two different species may be capable of forming a type of multi-species multicellularity-though it may not resemble its clonal counterparts. In this chapter, we consider the possibility of multi-species multicellularity and in particular its origins. Drawing upon previous studies of the evolutionary origins of clonal multicellularity, we focus on the emergence of simple reproducing groups that have the capacity to gain adaptations. We present a framework for organizing these initial multi-species group life cycles based on whether the constituent species are unicellular or multicellular and whether the groups reproduce via fragmentation or cycles of dissociation and re-association. We discuss characteristics of each type of multi-species multicellularity and representative examples to assess their likely evolutionary trajectories. Ultimately, we conclude that the multi-species groups that most resemble textbook multicellular organisms are composed of unicellular and multicellular species and reproduce via cycles of dissociation and re-association.

  • 2. Berdahl, Andrew
    et al.
    Brelsford, Christa
    De Bacco, Caterina
    Dumas, Marion
    Ferdinand, Vanessa
    Grochow, Joshua A.
    Hebert-Dufresne, Laurent
    Kallus, Yoav
    Kempes, Christopher P.
    Kolchinsky, Artemy
    Larremore, Daniel B.
    Libby, Eric
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Power, Eleanor A.
    Stern, Caitlin A.
    Tracey, Brendan D.
    Dynamics of beneficial epidemics2019Ingår i: Scientific Reports, E-ISSN 2045-2322, Vol. 9, artikel-id 15093Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Pathogens can spread epidemically through populations. Beneficial contagions, such as viruses that enhance host survival or technological innovations that improve quality of life, also have the potential to spread epidemically. How do the dynamics of beneficial biological and social epidemics differ from those of detrimental epidemics? We investigate this question using a breadth-first modeling approach involving three distinct theoretical models. First, in the context of population genetics, we show that a horizontally-transmissible element that increases fitness, such as viral DNA, spreads superexponentially through a population, more quickly than a beneficial mutation. Second, in the context of behavioral epidemiology, we show that infections that cause increased connectivity lead to superexponential fixation in the population. Third, in the context of dynamic social networks, we find that preferences for increased global infection accelerate spread and produce superexponential fixation, but preferences for local assortativity halt epidemics by disconnecting the infected from the susceptible. We conclude that the dynamics of beneficial biological and social epidemics are characterized by the rapid spread of beneficial elements, which is facilitated in biological systems by horizontal transmission and in social systems by active spreading behavior of infected individuals.

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  • 3.
    Bozdag, G. Ozan
    et al.
    School of Biological Sciences, Georgia Institute of Technology, GA, Atlanta, United States.
    Libby, Eric
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Santa Fe Institute, NM, Santa Fe, United States.
    Pineau, Rozenn
    School of Biological Sciences, Georgia Institute of Technology, GA, Atlanta, United States; Interdisciplinary Graduate Program in Quantitative Biosciences, Georgia Institute of Technology, GA, United States.
    Reinhard, Christopher T.
    School of Earth and Atmospheric Sciences, Georgia Institute of Technology, GA, Atlanta, United States; NASA Astrobiology Institute, Alternative Earths Team, CA, Riverside, United States.
    Ratcliff, William C.
    School of Biological Sciences, Georgia Institute of Technology, GA, Atlanta, United States; NASA Astrobiology Institute, Reliving the Past Team, GA, Atlanta, United States.
    Oxygen suppression of macroscopic multicellularity2021Ingår i: Nature Communications, E-ISSN 2041-1723, Vol. 12, nr 1, artikel-id 2838Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Atmospheric oxygen is thought to have played a vital role in the evolution of large, complex multicellular organisms. Challenging the prevailing theory, we show that the transition from an anaerobic to an aerobic world can strongly suppress the evolution of macroscopic multicellularity. Here we select for increased size in multicellular ‘snowflake’ yeast across a range of metabolically-available O2 levels. While yeast under anaerobic and high-O2 conditions evolved to be considerably larger, intermediate O2 constrained the evolution of large size. Through sequencing and synthetic strain construction, we confirm that this is due to O2-mediated divergent selection acting on organism size. We show via mathematical modeling that our results stem from nearly universal evolutionary and biophysical trade-offs, and thus should apply broadly. These results highlight the fact that oxygen is a double-edged sword: while it provides significant metabolic advantages, selection for efficient use of this resource may paradoxically suppress the evolution of macroscopic multicellular organisms.

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  • 4. Estrela, Sylvie
    et al.
    Libby, Eric
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Santa Fe Institute, Santa Fe, NM, USA.
    Van Cleve, Jeremy
    Debarre, Florence
    Deforet, Maxime
    Harcombe, William R.
    Pena, Jorge
    Brown, Sam P.
    Hochberg, Michael E.
    Environmentally Mediated Social Dilemmas2019Ingår i: Trends in Ecology & Evolution, ISSN 0169-5347, E-ISSN 1872-8383, Vol. 34, nr 1, s. 6-18Artikel, forskningsöversikt (Refereegranskat)
    Abstract [en]

    By consuming and producing environmental resources, organisms inevitably change their habitats. The consequences of such environmental modifications can be detrimental or beneficial not only to the focal organism but also to other organisms sharing the same environment. Social evolution theory has been very influential in studying how social interactions mediated by public 'goods' or 'bads' evolve by emphasizing the role of spatial structure. The environmental dimensions driving these interactions, however, are typically abstracted away. We propose here a new, environment-mediated taxonomy of social behaviors where organisms are categorized by their production or consumption of environmental factors that can help or harm others in the environment. We discuss microbial examples of our classification and highlight the importance of environmental intermediates more generally.

  • 5.
    Isaksson, Hanna
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Brännström, Åke
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Advancing Systems Analysis Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria; Complexity Science and Evolution Unit, Okinawa Institute of Science and Technology Graduate University, Japan.
    Libby, Eric
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Minor variations in multicellular life cycles have major effects on adaptation2023Ingår i: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 19, nr 4, artikel-id e1010698Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Multicellularity has evolved several independent times over the past hundreds of millions of years and given rise to a wide diversity of complex life. Recent studies have found that large differences in the fundamental structure of early multicellular life cycles can affect fitness and influence multicellular adaptation. Yet, there is an underlying assumption that at some scale or categorization multicellular life cycles are similar in terms of their adaptive potential. Here, we consider this possibility by exploring adaptation in a class of simple multicellular life cycles of filamentous organisms that only differ in one respect, how many daughter filaments are produced. We use mathematical models and evolutionary simulations to show that despite the similarities, qualitatively different mutations fix. In particular, we find that mutations with a tradeoff between cell growth and group survival, i.e. "selfish" or "altruistic" traits, spread differently. Specifically, altruistic mutations more readily spread in life cycles that produce few daughters while in life cycles producing many daughters either type of mutation can spread depending on the environment. Our results show that subtle changes in multicellular life cycles can fundamentally alter adaptation.

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  • 6.
    Isaksson, Hanna
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Integrated Science Lab, Umeå University, Umeå, Sweden.
    Conlin, Peter L.
    Georgia Institute of Technology, School of Biological Sciences, GA, Atlanta, United States.
    Kerr, Ben
    BEACON Center for the Study of Evolution in Action, Department of Biology, University of Washington, WA, Seattle, United States.
    Ratcliff, William C.
    Georgia Institute of Technology, School of Biological Sciences, GA, Atlanta, United States.
    Libby, Eric
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Integrated Science lab, Umeå University, Umeå, Sweden; Santa Fe Institute, NM, Santa Fe, United States.
    The consequences of budding versus binary fission on adaptation and aging in primitive multicellularity2021Ingår i: Genes, ISSN 2073-4425, E-ISSN 2073-4425, Vol. 12, nr 5, artikel-id 661Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Early multicellular organisms must gain adaptations to outcompete their unicellular ancestors, as well as other multicellular lineages. The tempo and mode of multicellular adaptation is influenced by many factors including the traits of individual cells. We consider how a fundamental aspect of cells, whether they reproduce via binary fission or budding, can affect the rate of adaptation in primitive multicellularity. We use mathematical models to study the spread of beneficial, growth rate mutations in unicellular populations and populations of multicellular filaments reproducing via binary fission or budding. Comparing populations once they reach carrying capacity, we find that the spread of mutations in multicellular budding populations is qualitatively distinct from the other populations and in general slower. Since budding and binary fission distribute age-accumulated damage differently, we consider the effects of cellular senescence. When growth rate decreases with cell age, we find that beneficial mutations can spread significantly faster in a multicellular budding population than its corresponding unicellular population or a population reproducing via binary fission. Our results demonstrate that basic aspects of the cell cycle can give rise to different rates of adaptation in multicellular organisms.

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  • 7.
    Libby, Eric
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Modularity of the life cycle2019Ingår i: Nature Ecology & Evolution, E-ISSN 2397-334X, Vol. 3, nr 8, s. 1142-1143Artikel i tidskrift (Övrigt vetenskapligt)
    Abstract [en]

    Life stages in Bacillus subtilis are controlled by regulatory blocks that can be kept or lost across species in response to selection in different environments.

  • 8.
    Libby, Eric
    et al.
    Santa Fe Institute, Santa Fe, NM, 87501, USA.
    Driscoll, William W.
    Ecology, Evolution and Behavior, University of Minnesota, Minneapolis, MN, 55108, USA.
    Ratcliff, William C.
    School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
    Programmed cell death can increase the efficacy of microbial bet hedging2018Ingår i: Scientific Reports, E-ISSN 2045-2322, Vol. 8, nr 1, artikel-id 1120Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Programmed cell death (PCD) occurs in both unicellular and multicellular organisms. While PCD plays a key role in the development and maintenance of multicellular organisms, explaining why single-celled organisms would evolve to actively commit suicide has been far more challenging. Here, we explore the potential for PCD to act as an accessory to microbial bet-hedging strategies that utilize stochastic phenotype switching. We consider organisms that face unpredictable and recurring disasters, in which fitness depends on effective phenotypic diversification. We show that when reproductive opportunities are limited by carrying capacity, PCD drives population turnover, providing increased opportunities for phenotypic diversification through stochastic phenotype switching. The main cost of PCD, providing resources for growth to a PCD(−) competitor, is ameliorated by genetic assortment in spatially structured populations. Using agent -based simulations, we explore how basic demographic factors, namely bottlenecks and local dispersal, can generate sufficient spatial structure to favor the evolution of high PCD rates.

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  • 9.
    Libby, Eric
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Santa Fe Institute, Santa Fe, New Mexico, United States of America.
    Hebert-Dufresne, Laurent
    Hosseini, Sayed-Rzgar
    Wagner, Andreas
    Syntrophy emerges spontaneously in complex metabolic systems2019Ingår i: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 15, nr 7, artikel-id e1007169Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Syntrophy allows a microbial community as a whole to survive in an environment, even though individual microbes cannot. The metabolic interdependence typical of syntrophy is thought to arise from the accumulation of degenerative mutations during the sustained co-evolution of initially self-sufficient organisms. An alternative and underexplored possibility is that syntrophy can emerge spontaneously in communities of organisms that did not co-evolve. Here, we study this de novo origin of syntrophy using experimentally validated computational techniques to predict an organism's viability from its metabolic reactions. We show that pairs of metabolisms that are randomly sampled from a large space of possible metabolism and viable on specific primary carbon sources often become viable on new carbon sources by exchanging metabolites. The same biochemical reactions that are required for viability on primary carbon sources also confer viability on novel carbon sources. Our observations highlight a new and important avenue for the emergence of metabolic adaptations and novel ecological interactions.

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  • 10.
    Libby, Eric
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Santa Fe Institute, Santa Fe, Argentina.
    Kempes, Christopher P.
    Santa Fe Institute, Santa Fe, Argentina.
    Okie, Jordan G.
    School of Earth and Space Exploration, Arizona State University, Tempe, Italy.
    Metabolic compatibility and the rarity of prokaryote endosymbioses2023Ingår i: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 120, nr 17, artikel-id e2206527120Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The evolution of the mitochondria was a significant event that gave rise to the eukaryotic lineage and most large complex life. Central to the origins of the mitochondria was an endosymbiosis between prokaryotes. Yet, despite the potential benefits that can stem from a prokaryotic endosymbiosis, their modern occurrence is exceptionally rare. While many factors may contribute to their rarity, we lack methods for estimating the extent to which they constrain the appearance of a prokaryotic endosymbiosis. Here, we address this knowledge gap by examining the role of metabolic compatibility between a prokaryotic host and endosymbiont. We use genome-scale metabolic flux models from three different collections (AGORA, KBase, and CarveMe) to assess the viability, fitness, and evolvability of potential prokaryotic endosymbioses. We find that while more than half of host-endosymbiont pairings are metabolically viable, the resulting endosymbioses have reduced growth rates compared to their ancestral metabolisms and are unlikely to gain mutations to overcome these fitness differences. In spite of these challenges, we do find that they may be more robust in the face of environmental perturbations at least in comparison with the ancestral host metabolism lineages. Our results provide a critical set of null models and expectations for understanding the forces that shape the structure of prokaryotic life.

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  • 11.
    Libby, Eric
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. IceLab.
    Lind, Peter A.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för molekylärbiologi (Teknisk-naturvetenskaplig fakultet).
    Probabilistic models for predicting mutational routes to new adaptive phenotypes2019Ingår i: Bio-protocol, E-ISSN 2331-8325, Vol. 9, nr 20, artikel-id 3407Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Understanding the translation of genetic variation to phenotypic variation is a fundamental problem in genetics and evolutionary biology. The introduction of new genetic variation through mutation can lead to new adaptive phenotypes, but the complexity of the genotype-to-phenotype map makes it challenging to predict the phenotypic effects of mutation. Metabolic models, in conjunction with flux balance analysis, have been used to predict evolutionary optimality. These methods however rely on large scale models of metabolism, describe a limited set of phenotypes, and assume that selection for growth rate is the prime evolutionary driver.

    Here we describe a method for computing the relative likelihood that mutational change will translate into a phenotypic change between two molecular pathways. The interactions of molecular components in the pathways are modeled with ordinary differential equations. Unknown parameters are offset by probability distributions that describe the concentrations of molecular components, the reaction rates for different molecular processes, and the effects of mutations. Finally, the likelihood that mutations in a pathway will yield phenotypic change is estimated with stochastic simulations.

    One advantage of this method is that only basic knowledge of the interaction network underlying a phenotype is required. However, it can also incorporate available information about concentrations and reaction rates as well as mutational biases and mutational robustness of molecular components. The method estimates the relative probabilities that different pathways produce phenotypic change, which can be combined with fitness models to predict evolutionary outcomes.

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  • 12.
    Libby, Eric
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Ratcliff, William C.
    Lichens and microbial syntrophies offer models for an interdependent route to multicellularity2021Ingår i: The Lichenologist, ISSN 0024-2829, E-ISSN 1096-1135, Vol. 53, nr 4, s. 283-290Artikel, forskningsöversikt (Refereegranskat)
    Abstract [en]

    The evolution of multicellularity paved the way for significant increases in biological complexity. Although multicellularity has evolved many times independently, we know relatively little about its origins. Directed evolution is a promising approach to studying early steps in this major transition, but current experimental systems have examined only a subset of the possible evolutionary routes to multicellularity. Here we consider egalitarian routes to multicellularity, in which unrelated unicellular organisms evolve to become a multicellular organism. Inspired by microbial syntrophies and lichens, we outline three such routes from a system of different species to an interdependent relationship that replicates. We compare these routes to contemporary experimental systems and consider how physical structure, the threat of invasion, division of labour and co-transmission affect their evolution.

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  • 13.
    Libby, Eric
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Santa Fe Institute, Santa Fe, New Mexico.
    Ratcliff, William C.
    Shortsighted Evolution Constrains the Efficacy of Long-Term Bet Hedging2019Ingår i: American Naturalist, ISSN 0003-0147, E-ISSN 1537-5323, Vol. 193, nr 3, s. 409-423Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    To survive unpredictable environmental change, many organisms adopt bet-hedging strategies that are initially costly but provide a long-term fitness benefit. The temporal extent of these deferred fitness benefits determines whether bet-hedging organisms can survive long enough to realize them. In this article, we examine a model of microbial bet hedging in which there are two paths to extinction: unpredictable environmental change and demographic stochasticity. In temporally correlated environments, these drivers of extinction select for different switching strategies. Rapid phenotype switching ensures survival in the face of unpredictable environmental change, while slower-switching organisms become extinct. However, when both switching strategies are present in the same population, then demographic stochasticity-enforced by a limited population size-leads to extinction of the faster-switching organism. As a result, we find a novel form of evolutionary suicide whereby selection in a fluctuating environment can favor bet-hedging strategies that ultimately increase the risk of extinction. Population structures with multiple subpopulations and dispersal can reduce the risk of extinction from unpredictable environmental change and shift the balance so as to facilitate the evolution of slower-switching organisms.

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  • 14.
    Lind, Peter A
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för molekylärbiologi (Teknisk-naturvetenskaplig fakultet). New Zealand Institute for Advanced Study, Massey University at Albany, Auckland, New Zealand.
    Libby, Eric
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. New Zealand Institute for Advanced Study, Massey University at Albany, Auckland, New Zealand ; 3 Santa Fe Institute, New Mexico, United States.
    Herzog, Jenny
    Rainey, Paul B
    Predicting mutational routes to new adaptive phenotypes2019Ingår i: eLIFE, E-ISSN 2050-084X, Vol. 8, s. 1-31, artikel-id e38822Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Predicting evolutionary change poses numerous challenges. Here we take advantage of the model bacterium Pseudomonas fluorescens in which the genotype-to-phenotype map determining evolution of the adaptive ‘wrinkly spreader’ (WS) type is known. We present mathematical descriptions of three necessary regulatory pathways and use these to predict both the rate at which each mutational route is used and the expected mutational targets. To test predictions, mutation rates and targets were determined for each pathway. Unanticipated mutational hotspots caused experimental observations to depart from predictions but additional data led to refined models. A mismatch was observed between the spectra of WS-causing mutations obtained with and without selection due to low fitness of previously undetected WS-causing mutations. Our findings contribute toward the development of mechanistic models for forecasting evolution, highlight current limitations, and draw attention to challenges in predicting locus-specific mutational biases and fitness effects.

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  • 15.
    Pentz, Jennifer T.
    et al.
    Los Alamos National Laboratory, Los Alamos, United States.
    MacGillivray, Kathryn
    School of Biological Sciences, Georgia Institute of Technology, Atlanta, United States; Interdisciplinary Graduate Program in Quantitative Biosciences, Georgia Institute of Technology, Atlanta, United States.
    DuBose, James G.
    School of Biological Sciences, Georgia Institute of Technology, Atlanta, United States.
    Conlin, Peter L.
    School of Biological Sciences, Georgia Institute of Technology, Atlanta, United States.
    Reinhardt, Emma
    Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, United States.
    Libby, Eric
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Ratcliff, William C.
    School of Biological Sciences, Georgia Institute of Technology, Atlanta, United States.
    Evolutionary consequences of nascent multicellular life cycles2023Ingår i: eLIFE, E-ISSN 2050-084X, Vol. 12, artikel-id e84336Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A key step in the evolutionary transition to multicellularity is the origin of multicellular groups as biological individuals capable of adaptation. Comparative work, supported by theory, suggests clonal development should facilitate this transition, although this hypothesis has never been tested in a single model system. We evolved 20 replicate populations of otherwise isogenic clonally reproducing 'snowflake' yeast (Δace2/∆ace2) and aggregative 'floc' yeast (GAL1p::FLO1 /GAL1p::FLO1) with daily selection for rapid growth in liquid media, which favors faster cell division, followed by selection for rapid sedimentation, which favors larger multicellular groups. While both genotypes adapted to this regime, growing faster and having higher survival during the group-selection phase, there was a stark difference in evolutionary dynamics. Aggregative floc yeast obtained nearly all their increased fitness from faster growth, not improved group survival; indicating that selection acted primarily at the level of cells. In contrast, clonal snowflake yeast mainly benefited from higher group-dependent fitness, indicating a shift in the level of Darwinian individuality from cells to groups. Through genome sequencing and mathematical modeling, we show that the genetic bottlenecks in a clonal life cycle also drive much higher rates of genetic drift-a result with complex implications for this evolutionary transition. Our results highlight the central role that early multicellular life cycles play in the process of multicellular adaptation.

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  • 16.
    Pentz, Jennifer T.
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för molekylärbiologi (Teknisk-naturvetenskaplig fakultet). School of Biological Sciences, Georgia Institute of Technology, Atlanta, USA.
    Marquez-Zacarias, Pedro
    Bozdag, G. Ozan
    Burnetti, Anthony
    Yunker, Peter J.
    Libby, Eric
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Ratcliff, William C.
    Ecological Advantages and Evolutionary Limitations of Aggregative Multicellular Development2020Ingår i: Current Biology, ISSN 0960-9822, E-ISSN 1879-0445, Vol. 30, nr 21, s. 4155-4164Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    All multicellular organisms develop through one of two basic routes: they either aggregate from free-living cells, creating potentially chimeric multicellular collectives, or they develop clonally via mother-daughter cellular adhesion. Although evolutionary theory makes clear predictions about trade-offs between these developmental modes, these have never been experimentally tested in otherwise genetically identical organisms. We engineered unicellular baker's yeast (Saccharomyces cerevisiae) to develop either clonally ("snowflake''; Dace2) or aggregatively ("floc''; GAL1p::FLO1) and examined their fitness in a fluctuating environment characterized by periods of growth and selection for rapid sedimentation. When cultured independently, aggregation was far superior to clonal development, providing a 35% advantage during growth and a 2.5-fold advantage during settling selection. Yet when competed directly, clonally developing snowflake yeast rapidly displaced aggregative floc. This was due to unexpected social exploitation: snowflake yeast, which do not produce adhesive FLO1, nonetheless become incorporated into flocs at a higher frequency than floc cells themselves. Populations of chimeric clusters settle much faster than floc alone, providing snowflake yeast with a fitness advantage during competition. Mathematical modeling suggests that such developmental cheating may be difficult to circumvent; hypothetical "choosy floc'' that avoid exploitation by maintaining clonality pay an ecological cost when rare, often leading to their extinction. Our results highlight the conflict at the heart of aggregative development: non-specific cellular binding provides a strong ecological advantage-the ability to quickly form groups-but this very feature leads to its exploitation.

  • 17.
    Pineau, Rozenn M.
    et al.
    School of Biological Sciences, Georgia Institute of Technology, GA, Atlanta, United States; Interdisciplinary Graduate Program in Quantitative Biosciences, Georgia Institute of Technology, GA, Atlanta, United States.
    Libby, Eric
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Integrated Science Lab, Umeå university, Umeå, Sweden.
    Demory, David
    CNRS, Sorbonne Université, USR 3579 Laboratoire de Biodiversité et Biotechnologies Microbiennes (LBBM), Observatoire Océanologique, Banyuls-sur-Mer, France.
    Lac, Dung T.
    School of Biological Sciences, Georgia Institute of Technology, GA, Atlanta, United States.
    Day, Thomas C.
    School of Physics, Georgia Institute of Technology, GA, Atlanta, United States; Department of Biological Sciences, University of Southern California, CA, Los Angeles, United States.
    Bravo, Pablo
    Interdisciplinary Graduate Program in Quantitative Biosciences, Georgia Institute of Technology, GA, Atlanta, United States; School of Physics, Georgia Institute of Technology, GA, Atlanta, United States.
    Yunker, Peter J.
    School of Physics, Georgia Institute of Technology, GA, Atlanta, United States.
    Weitz, Joshua S.
    School of Biological Sciences, Georgia Institute of Technology, GA, Atlanta, United States; School of Physics, Georgia Institute of Technology, GA, Atlanta, United States; Department of Biology, University of Maryland, MD, College Park, United States; Department of Physics, University of Maryland, MD, College Park, United States.
    Bozdag, G. Ozan
    School of Biological Sciences, Georgia Institute of Technology, GA, Atlanta, United States.
    Ratcliff, William C.
    School of Biological Sciences, Georgia Institute of Technology, GA, Atlanta, United States; Department of Biology, University of Maryland, MD, College Park, United States.
    Emergence and maintenance of stable coexistence during a long-term multicellular evolution experiment2024Ingår i: Nature Ecology & Evolution, E-ISSN 2397-334XArtikel i tidskrift (Refereegranskat)
    Abstract [en]

    The evolution of multicellular life spurred evolutionary radiations, fundamentally changing many of Earth’s ecosystems. Yet little is known about how early steps in the evolution of multicellularity affect eco-evolutionary dynamics. Through long-term experimental evolution, we observed niche partitioning and the adaptive divergence of two specialized lineages from a single multicellular ancestor. Over 715 daily transfers, snowflake yeast were subjected to selection for rapid growth, followed by selection favouring larger group size. Small and large cluster-forming lineages evolved from a monomorphic ancestor, coexisting for over ~4,300 generations, specializing on divergent aspects of a trade-off between growth rate and survival. Through modelling and experimentation, we demonstrate that coexistence is maintained by a trade-off between organismal size and competitiveness for dissolved oxygen. Taken together, this work shows how the evolution of a new level of biological individuality can rapidly drive adaptive diversification and the expansion of a nascent multicellular niche, one of the most historically impactful emergent properties of this evolutionary transition.

  • 18.
    Smith, Hillary H.
    et al.
    Department of Geosciences, The Pennsylvania State University, PA, University Park, United States; Earth and Environmental Systems Institute, The Pennsylvania State University, PA, University Park, United States.
    Hyde, Andrew S.
    Department of Geosciences, The Pennsylvania State University, PA, University Park, United States; Earth and Environmental Systems Institute, The Pennsylvania State University, PA, University Park, United States.
    Simkus, Danielle N.
    NASA Goddard Space Flight Center, MD, Greenbelt, United States; NASA Postdoctoral Program, USRA, MD, Columbia, United States; Department of Physics, Catholic University of America, DC, Washington, United States.
    Libby, Eric
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Santa Fe Institute, NM, Santa Fe, United States.
    Maurer, Sarah E.
    Department of Chemistry and Biochemistry, Central Connecticut State University, CT, New Britain, United States.
    Graham, Heather V.
    NASA Goddard Space Flight Center, MD, Greenbelt, United States; Department of Physics, Catholic University of America, DC, Washington, United States.
    Kempes, Christopher P.
    Santa Fe Institute, NM, Santa Fe, United States.
    Lollar, Barbara Sherwood
    Department of Earth Sciences, University of Toronto, ON, Toronto, Canada.
    Chou, Luoth
    NASA Goddard Space Flight Center, MD, Greenbelt, United States; NASA Postdoctoral Program, USRA, MD, Columbia, United States; Department of Biology, Georgetown University, DC, Washington, United States.
    Ellington, Andrew D.
    Department of Molecular Biosciences, College of Natural Sciences, The University of Texas at Austin, TX, Austin, United States; Center for Systems and Synthetic Biology, The University of Texas at Austin, TX, Austin, United States.
    Fricke, G. Matthew
    Department of Computer Science, University of New Mexico, NM, Albuquerque, United States.
    Girguis, Peter R.
    Department of Organismic and Evolutionary Biology, Harvard University, MA, Cambridge, United States.
    Grefenstette, Natalie M.
    Santa Fe Institute, NM, Santa Fe, United States; Blue Marble Space Institute of Science, WA, Seattle, United States.
    Pozarycki, Chad I.
    NASA Goddard Space Flight Center, MD, Greenbelt, United States; Department of Biology, Georgetown University, DC, Washington, United States.
    House, Christopher H.
    Department of Geosciences, The Pennsylvania State University, PA, University Park, United States; Earth and Environmental Systems Institute, The Pennsylvania State University, PA, University Park, United States.
    Johnson, Sarah Stewart
    Department of Biology, Georgetown University, DC, Washington, United States; Science, Technology and International Affairs Program, Georgetown University, DC, Washington, United States.
    The grayness of the origin of life2021Ingår i: Life, E-ISSN 2075-1729, Vol. 11, nr 6, artikel-id 498Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In the search for life beyond Earth, distinguishing the living from the non-living is paramount. However, this distinction is often elusive, as the origin of life is likely a stepwise evolutionary process, not a singular event. Regardless of the favored origin of life model, an inherent “grayness” blurs the theorized threshold defining life. Here, we explore the ambiguities between the biotic and the abiotic at the origin of life. The role of grayness extends into later transitions as well. By recognizing the limitations posed by grayness, life detection researchers will be better able to develop methods sensitive to prebiotic chemical systems and life with alternative biochemistries.

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