Literature DB >> 28303312

Neutral Evolution and Dispersal Limitation Produce Biogeographic Patterns in Microcystis aeruginosa Populations of Lake Systems.

Sahar Shirani1, Ferdi L Hellweger2.   

Abstract

Molecular observations reveal substantial biogeographic patterns of cyanobacteria within systems of connected lakes. An important question is the relative role of environmental selection and neutral processes in the biogeography of these systems. Here, we quantify the effect of genetic drift and dispersal limitation by simulating individual cyanobacteria cells using an agent-based model (ABM). In the model, cells grow (divide), die, and migrate between lakes. Each cell has a full genome that is subject to neutral mutation (i.e., the growth rate is independent of the genome). The model is verified by simulating simplified lake systems, for which theoretical solutions are available. Then, it is used to simulate the biogeography of the cyanobacterium Microcystis aeruginosa in a number of real systems, including the Great Lakes, Klamath River, Yahara River, and Chattahoochee River. Model output is analyzed using standard bioinformatics tools (BLAST, MAFFT). The emergent patterns of nucleotide divergence between lakes are dynamic, including gradual increases due to accumulation of mutations and abrupt changes due to population takeovers by migrant cells (coalescence events). The model predicted nucleotide divergence is heterogeneous within systems, and for weakly connected lakes, it can be substantial. For example, Lakes Superior and Michigan are predicted to have an average genomic nucleotide divergence of 8200 bp or 0.14%. The divergence between more strongly connected lakes is much lower. Our results provide a quantitative baseline for future biogeography studies. They show that dispersal limitation can be an important factor in microbe biogeography, which is contrary to the common belief, and could affect how a system responds to environmental change.

Entities:  

Keywords:  Agent-based modeling; Biogeography; Cyanobacteria; Dispersal limitation; Lake systems; Neutral evolution

Mesh:

Year:  2017        PMID: 28303312     DOI: 10.1007/s00248-017-0963-5

Source DB:  PubMed          Journal:  Microb Ecol        ISSN: 0095-3628            Impact factor:   4.552


  28 in total

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Journal:  Science       Date:  2002-01-25       Impact factor: 47.728

2.  Average number of nucleotide differences in a sample from a single subpopulation: a test for population subdivision.

Authors:  C Strobeck
Journal:  Genetics       Date:  1987-09       Impact factor: 4.562

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Journal:  Proc Natl Acad Sci U S A       Date:  2007-12-11       Impact factor: 11.205

Review 4.  Beyond biogeographic patterns: processes shaping the microbial landscape.

Authors:  China A Hanson; Jed A Fuhrman; M Claire Horner-Devine; Jennifer B H Martiny
Journal:  Nat Rev Microbiol       Date:  2012-05-14       Impact factor: 60.633

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Authors:  Nadav Kashtan; Sara E Roggensack; Sébastien Rodrigue; Jessie W Thompson; Steven J Biller; Allison Coe; Huiming Ding; Pekka Marttinen; Rex R Malmstrom; Roman Stocker; Michael J Follows; Ramunas Stepanauskas; Sallie W Chisholm
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Review 7.  Genetic drift, selection and the evolution of the mutation rate.

Authors:  Michael Lynch; Matthew S Ackerman; Jean-Francois Gout; Hongan Long; Way Sung; W Kelley Thomas; Patricia L Foster
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8.  A selective force favoring increased G+C content in bacterial genes.

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Journal:  Proc Natl Acad Sci U S A       Date:  2012-08-20       Impact factor: 11.205

9.  Antibiotic treatment enhances the genome-wide mutation rate of target cells.

Authors:  Hongan Long; Samuel F Miller; Chloe Strauss; Chaoxian Zhao; Lei Cheng; Zhiqiang Ye; Katherine Griffin; Ronald Te; Heewook Lee; Chi-Chun Chen; Michael Lynch
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10.  The role of nitrogen fixation in cyanobacterial bloom toxicity in a temperate, eutrophic lake.

Authors:  Lucas J Beversdorf; Todd R Miller; Katherine D McMahon
Journal:  PLoS One       Date:  2013-02-06       Impact factor: 3.240

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  3 in total

1.  Hydrological and soil physiochemical variables determine the rhizospheric microbiota in subtropical lakeshore areas.

Authors:  Xiaoke Zhang; Huili Wang; Zhifei Li; Jun Xie; Jiajia Ni
Journal:  PeerJ       Date:  2020-09-29       Impact factor: 2.984

2.  Carbon limitation drives GC content evolution of a marine bacterium in an individual-based genome-scale model.

Authors:  Ferdi L Hellweger; Yongjie Huang; Haiwei Luo
Journal:  ISME J       Date:  2018-01-12       Impact factor: 10.302

3.  Circadian clock helps cyanobacteria manage energy in coastal and high latitude ocean.

Authors:  Ferdi L Hellweger; Maria Luísa Jabbur; Carl Hirschie Johnson; Erik van Sebille; Hideharu Sasaki
Journal:  ISME J       Date:  2019-11-04       Impact factor: 10.302

  3 in total

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