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Demographic variability and heterogeneity among individuals within and among clonal bacteria strains.

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Title: Demographic variability and heterogeneity among individuals within and among clonal bacteria strains.
Authors: Jouvet, Lionel1, Rodríguez-Rojas, Alexandro2 usteiner@biology.sdu.dk, Steiner, Ulrich K.1,3 usteiner@biology.sdu.dk
Source: Oikos. May2018, Vol. 127 Issue 5, p728-737. 10p. 2 Diagrams, 2 Charts, 1 Graph.
Subjects: Escherichia coli, Clone cells, Bacterial reproduction, Cellular aging, Bacterial genes, Ecological heterogeneity
Abstract: Identifying what drives individual heterogeneity has been of long interest to ecologists, evolutionary biologists and biodemographers, because only such identification provides deeper understanding of ecological and evolutionary population dynamics. In natural populations one is challenged to accurately decompose the drivers of heterogeneity among individuals as genetically fixed or selectively neutral. Rather than working on wild populations we present here data from a simple bacterial system in the lab, Escherichia coli. Our system, based on cutting‐edge microfluidic techniques, provides high control over the genotype and the environment. It therefore allows to unambiguously decompose and quantify fixed genetic variability and dynamic stochastic variability among individuals. We show that within clonal individual variability (dynamic heterogeneity) in lifespan and lifetime reproduction is dominating at about 90–92%, over the 8–10% genetically (adaptive fixed) driven differences. The genetic differences among the clonal strains still lead to substantial variability in population growth rates (fitness), but, as well understood based on foundational work in population genetics, the within strain neutral variability slows adaptive change, by enhancing genetic drift, and lowering overall population growth. We also revealed a surprising diversity in senescence patterns among the clonal strains, which indicates diverse underlying cell‐intrinsic processes that shape these demographic patterns. Such diversity is surprising since all cells belong to the same bacteria species, E. coli, and still exhibit patterns such as classical senescence, non‐senescence, or negative senescence. We end by discussing whether similar levels of non‐genetic variability might be detected in other systems and close by stating the open questions how such heterogeneity is maintained, how it has evolved, and whether it is adaptive. [ABSTRACT FROM AUTHOR]
Copyright of Oikos is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Demographic variability and heterogeneity among individuals within and among clonal bacteria strains.
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  Data: <searchLink fieldCode="AR" term="%22Jouvet%2C+Lionel%22">Jouvet, Lionel</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Rodríguez-Rojas%2C+Alexandro%22">Rodríguez-Rojas, Alexandro</searchLink><relatesTo>2</relatesTo><i> usteiner@biology.sdu.dk</i><br /><searchLink fieldCode="AR" term="%22Steiner%2C+Ulrich+K%2E%22">Steiner, Ulrich K.</searchLink><relatesTo>1,3</relatesTo><i> usteiner@biology.sdu.dk</i>
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  Data: <searchLink fieldCode="JN" term="%22Oikos%22">Oikos</searchLink>. May2018, Vol. 127 Issue 5, p728-737. 10p. 2 Diagrams, 2 Charts, 1 Graph.
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  Data: <searchLink fieldCode="DE" term="%22Escherichia+coli%22">Escherichia coli</searchLink><br /><searchLink fieldCode="DE" term="%22Clone+cells%22">Clone cells</searchLink><br /><searchLink fieldCode="DE" term="%22Bacterial+reproduction%22">Bacterial reproduction</searchLink><br /><searchLink fieldCode="DE" term="%22Cellular+aging%22">Cellular aging</searchLink><br /><searchLink fieldCode="DE" term="%22Bacterial+genes%22">Bacterial genes</searchLink><br /><searchLink fieldCode="DE" term="%22Ecological+heterogeneity%22">Ecological heterogeneity</searchLink>
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  Data: Identifying what drives individual heterogeneity has been of long interest to ecologists, evolutionary biologists and biodemographers, because only such identification provides deeper understanding of ecological and evolutionary population dynamics. In natural populations one is challenged to accurately decompose the drivers of heterogeneity among individuals as genetically fixed or selectively neutral. Rather than working on wild populations we present here data from a simple bacterial system in the lab, <italic>Escherichia coli</italic>. Our system, based on cutting‐edge microfluidic techniques, provides high control over the genotype and the environment. It therefore allows to unambiguously decompose and quantify fixed genetic variability and dynamic stochastic variability among individuals. We show that within clonal individual variability (dynamic heterogeneity) in lifespan and lifetime reproduction is dominating at about 90–92%, over the 8–10% genetically (adaptive fixed) driven differences. The genetic differences among the clonal strains still lead to substantial variability in population growth rates (fitness), but, as well understood based on foundational work in population genetics, the within strain neutral variability slows adaptive change, by enhancing genetic drift, and lowering overall population growth. We also revealed a surprising diversity in senescence patterns among the clonal strains, which indicates diverse underlying cell‐intrinsic processes that shape these demographic patterns. Such diversity is surprising since all cells belong to the same bacteria species, <italic>E. coli</italic>, and still exhibit patterns such as classical senescence, non‐senescence, or negative senescence. We end by discussing whether similar levels of non‐genetic variability might be detected in other systems and close by stating the open questions how such heterogeneity is maintained, how it has evolved, and whether it is adaptive. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Oikos is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/oik.04292
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        Text: English
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        Type: general
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      – SubjectFull: Bacterial reproduction
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      – SubjectFull: Cellular aging
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      – SubjectFull: Bacterial genes
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              Text: May2018
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