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Publications (7 of 7) Show all publications
Berdahl, A., Brelsford, C., De Bacco, C., Dumas, M., Ferdinand, V., Grochow, J. A., . . . Tracey, B. D. (2019). Dynamics of beneficial epidemics. Scientific Reports, 9, Article ID 15093.
Open this publication in new window or tab >>Dynamics of beneficial epidemics
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2019 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 9, article id 15093Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Nature Publishing Group, 2019
National Category
Evolutionary Biology
Identifiers
urn:nbn:se:umu:diva-166448 (URN)10.1038/s41598-019-50039-w (DOI)000491306500002 ()31641147 (PubMedID)
Available from: 2019-12-16 Created: 2019-12-16 Last updated: 2019-12-16Bibliographically approved
Estrela, S., Libby, E., Van Cleve, J., Debarre, F., Deforet, M., Harcombe, W. R., . . . Hochberg, M. E. (2019). Environmentally Mediated Social Dilemmas. Trends in Ecology & Evolution, 34(1), 6-18
Open this publication in new window or tab >>Environmentally Mediated Social Dilemmas
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2019 (English)In: Trends in Ecology & Evolution, ISSN 0169-5347, E-ISSN 1872-8383, Vol. 34, no 1, p. 6-18Article, review/survey (Refereed) Published
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.

Place, publisher, year, edition, pages
Elsevier, 2019
National Category
Evolutionary Biology
Identifiers
urn:nbn:se:umu:diva-155646 (URN)10.1016/j.tree.2018.10.004 (DOI)000454871000001 ()30415827 (PubMedID)
Available from: 2019-01-25 Created: 2019-01-25 Last updated: 2019-01-25Bibliographically approved
Libby, E. (2019). Modularity of the life cycle. Nature Ecology & Evolution, 3(8), 1142-1143
Open this publication in new window or tab >>Modularity of the life cycle
2019 (English)In: Nature Ecology & Evolution, E-ISSN 2397-334X, Vol. 3, no 8, p. 1142-1143Article in journal, Editorial material (Other academic) Published
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.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2019
National Category
Genetics
Identifiers
urn:nbn:se:umu:diva-162310 (URN)10.1038/s41559-019-0956-5 (DOI)000477903700006 ()31332335 (PubMedID)
Available from: 2019-08-19 Created: 2019-08-19 Last updated: 2019-08-19Bibliographically approved
Lind, P. A., Libby, E., Herzog, J. & Rainey, P. B. (2019). Predicting mutational routes to new adaptive phenotypes. eLIFE, 8, 1-31, Article ID e38822.
Open this publication in new window or tab >>Predicting mutational routes to new adaptive phenotypes
2019 (English)In: eLIFE, E-ISSN 2050-084X, Vol. 8, p. 1-31, article id e38822Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
eLife Sciences Publications, 2019
Keywords
evolutionary forecasting, pseudomonas, biofilm, genetics
National Category
Evolutionary Biology Microbiology Other Mathematics
Identifiers
urn:nbn:se:umu:diva-155079 (URN)10.7554/eLife.38822 (DOI)000455079000001 ()
Available from: 2019-01-08 Created: 2019-01-08 Last updated: 2019-01-28Bibliographically approved
Libby, E. & Lind, P. A. (2019). Probabilistic Models for Predicting Mutational Routes to New Adaptive Phenotypes. Bio-protocol, 9(20), Article ID 3407.
Open this publication in new window or tab >>Probabilistic Models for Predicting Mutational Routes to New Adaptive Phenotypes
2019 (English)In: Bio-protocol, ISSN 2331-8325, Vol. 9, no 20, article id 3407Article in journal (Refereed) Published
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.

Keywords
Evolutionary forecasting, Mathematical modeling, Adaptation, Mutation, Evolution, Genotype-to-phenotype map
National Category
Evolutionary Biology Mathematics
Research subject
evolutionary genetics; Mathematics
Identifiers
urn:nbn:se:umu:diva-164303 (URN)10.21769/BioProtoc.3407 (DOI)000492148000015 ()
Available from: 2019-10-21 Created: 2019-10-21 Last updated: 2019-11-20Bibliographically approved
Libby, E. & Ratcliff, W. C. (2019). Shortsighted Evolution Constrains the Efficacy of Long-Term Bet Hedging. American Naturalist, 193(3), 409-423
Open this publication in new window or tab >>Shortsighted Evolution Constrains the Efficacy of Long-Term Bet Hedging
2019 (English)In: American Naturalist, ISSN 0003-0147, E-ISSN 1537-5323, Vol. 193, no 3, p. 409-423Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
University of Chicago Press, 2019
Keywords
bet hedging, extinction, stochastic switching, evolutionary suicide
National Category
Ecology Evolutionary Biology
Identifiers
urn:nbn:se:umu:diva-157571 (URN)10.1086/701786 (DOI)000459624900009 ()30794447 (PubMedID)
Available from: 2019-04-01 Created: 2019-04-01 Last updated: 2019-04-01Bibliographically approved
Libby, E., Hebert-Dufresne, L., Hosseini, S.-R. & Wagner, A. (2019). Syntrophy emerges spontaneously in complex metabolic systems. PloS Computational Biology, 15(7), Article ID e1007169.
Open this publication in new window or tab >>Syntrophy emerges spontaneously in complex metabolic systems
2019 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 15, no 7, article id e1007169Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Public Library Science, 2019
National Category
Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:umu:diva-162885 (URN)10.1371/journal.pcbi.1007169 (DOI)000481577700033 ()31339876 (PubMedID)
Available from: 2019-09-04 Created: 2019-09-04 Last updated: 2019-09-04Bibliographically approved
Projects
The Origin of the Eukaryotic Endosymbiosis: A theoretical framework for assessing the likelihood and impact of the mitochondrion [2018-03630_VR]; Umeå University
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-6569-5793

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