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      Long-term experimental evolution decouples size and production costs in Escherichia coli

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          Populations of larger organisms should be more efficient in their resource use, but grow more slowly, than populations of smaller organisms. The relations between size, metabolism, and demography form the bedrock of metabolic theory, but most empirical tests have been correlative and indirect. Experimental lineages of Escherichia coli that evolved to make larger cells provide a unique opportunity to test how size, metabolism, and demography covary. Despite the larger cells having a relatively slower metabolism, they grow faster than smaller cells. They achieve this growth rate advantage by reducing the relative costs of producing their larger cells. That evolution can decouple the costs of production from size challenges a fundamental assumption about the connections between physiology and ecology.

          Abstract

          Body size covaries with population dynamics across life’s domains. Metabolism may impose fundamental constraints on the coevolution of size and demography, but experimental tests of the causal links remain elusive. We leverage a 60,000-generation experiment in which Escherichia coli populations evolved larger cells to examine intraspecific metabolic scaling and correlations with demographic parameters. Over the course of their evolution, the cells have roughly doubled in size relative to their ancestors. These larger cells have metabolic rates that are absolutely higher, but relative to their size, they are lower. Metabolic theory successfully predicted the relations between size, metabolism, and maximum population density, including support for Damuth’s law of energy equivalence, such that populations of larger cells achieved lower maximum densities but higher maximum biomasses than populations of smaller cells. The scaling of metabolism with cell size thus predicted the scaling of size with maximum population density. In stark contrast to standard theory, however, populations of larger cells grew faster than those of smaller cells, contradicting the fundamental and intuitive assumption that the costs of building new individuals should scale directly with their size. The finding that the costs of production can be decoupled from size necessitates a reevaluation of the evolutionary drivers and ecological consequences of biological size more generally.

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          Fitting Linear Mixed-Effects Models Usinglme4

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            Fitting Linear Mixed-Effects Models Using lme4

            Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer. Journal of Statistical Software, 67 (1) ISSN:1548-7660
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              TOWARD A METABOLIC THEORY OF ECOLOGY

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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc Natl Acad Sci U S A
                pnas
                pnas
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                20 May 2022
                24 May 2022
                20 November 2022
                : 119
                : 21
                : e2200713119
                Affiliations
                [1] aCentre for Geometric Biology, School of Biological Sciences, Monash University , Melbourne, VIC 3800, Australia;
                [2] bCentre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University , Melbourne, VIC 3125, Australia;
                [3] cSchool of Agriculture, Food and Wine, University of Adelaide , Adelaide, SA 5005, Australia;
                [4] dDepartment of Microbiology and Molecular Genetics, Michigan State University , East Lansing, MI 48824;
                [5] eProgram in Ecology, Evolution, and Behavior, Michigan State University , East Lansing, MI 48824
                Author notes
                1To whom correspondence may be addressed. Email: dustin.marshall@ 123456monash.edu .

                Edited by Ruth Shaw, Department of Ecology Evolution and Behavior, University of Minnesota, St. Paul, MN; received January 13, 2022; accepted March 25, 2022

                Author contributions: D.J.M., R.E.L., and M.J.M. designed research; M.J.M., T.L., A.L.S., C.M.H., and M.J.M. performed research; R.E.L. contributed new reagents/analytic tools; D.J.M., M.M., and T.L. analyzed data; and D.J.M., R.E.L., and M.J.M. wrote the paper.

                Author information
                https://orcid.org/0000-0002-7480-4779
                https://orcid.org/0000-0002-6802-7694
                https://orcid.org/0000-0002-1933-1817
                https://orcid.org/0000-0002-1064-8375
                https://orcid.org/0000-0002-5735-960X
                Article
                202200713
                10.1073/pnas.2200713119
                9173777
                35594402
                38f2939c-fc43-4447-b847-4b6380ae7c89
                Copyright © 2022 the Author(s). Published by PNAS.

                This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                History
                : 25 March 2022
                Page count
                Pages: 8
                Categories
                414
                Biological Sciences
                Ecology

                metabolic scaling,cell size,damuth’s law,metabolic ecology

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