Parallel adaptive evolution cultures of Escherichia coli lead to convergent growth phenotypes with different gene expression states

被引:201
作者
Fong, SS
Joyce, AR
Palsson, BO [1 ]
机构
[1] Univ Calif San Diego, Dept Bioengn, La Jolla, CA 92093 USA
[2] Univ Calif San Diego, Boinformat Program, La Jolla, CA 92093 USA
关键词
D O I
10.1101/gr.3832305
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Laboratory evolution can be used to address fundamental questions about adaptation to selection pressures and, ultimately, the process of evolution. In this Study, we investigated the reproducibility of growth phenotypes and global gene expression states during adaptive evolution. The results from parallel, replicate adaptive evolution experiments of Escherichia coli K-12 MG1655 grown on either lactate or glycerol minimal media showed that (1) growth phenotypes at the endpoint Of evolution are convergent and reproducible; (2) endpoints of evolution have different underlying gene expression states; and (3) the evolutionary gene expression response involves a large number of compensatory expression changes and a smaller number of adaptively beneficial expression changes common across evolution strains. Gene expression changes initially showed a large number of differentially expressed genes in response to an environmental change followed by a return of most genes to a baseline expression level, leaving a relatively small set of differentially expressed genes at the endpoint that varied between evolved populations.
引用
收藏
页码:1365 / 1372
页数:8
相关论文
共 37 条
[11]   Quantitative analysis of Escherichia coli metabolic phenotypes within the context of phenotypic phase planes [J].
Ibarra, RU ;
Fu, P ;
Palsson, BO ;
DiTonno, JR ;
Edwards, JS .
JOURNAL OF MOLECULAR MICROBIOLOGY AND BIOTECHNOLOGY, 2003, 6 (02) :101-108
[12]   Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth [J].
Ibarra, RU ;
Edwards, JS ;
Palsson, BO .
NATURE, 2002, 420 (6912) :186-189
[13]   Exploration, normalization, and summaries of high density oligonucleotide array probe level data [J].
Irizarry, RA ;
Hobbs, B ;
Collin, F ;
Beazer-Barclay, YD ;
Antonellis, KJ ;
Scherf, U ;
Speed, TP .
BIOSTATISTICS, 2003, 4 (02) :249-264
[14]  
Jablonka E, 2002, ANN NY ACAD SCI, V981, P82
[15]   The experimental evolution of specialists, generalists, and the maintenance of diversity [J].
Kassen, R .
JOURNAL OF EVOLUTIONARY BIOLOGY, 2002, 15 (02) :173-190
[16]   EcoCyc:: a comprehensive database resource for Escherichia coli [J].
Keseler, IM ;
Collado-Vides, J ;
Gama-Castro, S ;
Ingraham, J ;
Paley, S ;
Paulsen, IT ;
Peralta-Gill, M ;
Karp, PD .
NUCLEIC ACIDS RESEARCH, 2005, 33 :D334-D337
[17]   Lateral flagella and swarming motility in Aeromonas species [J].
Kirov, SM ;
Tassell, BC ;
Semmler, ABT ;
O'Donovan, LA ;
Rabaan, AA ;
Shaw, JG .
JOURNAL OF BACTERIOLOGY, 2002, 184 (02) :547-555
[18]   Evolution of competitive fitness in experimental populations of E-coli:: What makes one genotype a better competitor than another? [J].
Lenski, RE ;
Mongold, JA ;
Sniegowski, PD ;
Travisano, M ;
Vasi, F ;
Gerrish, PJ ;
Schmidt, TM .
ANTONIE VAN LEEUWENHOEK INTERNATIONAL JOURNAL OF GENERAL AND MOLECULAR MICROBIOLOGY, 1998, 73 (01) :35-47
[19]   Global transcriptional programs reveal a carbon source foraging strategy by Escherichia coli [J].
Liu, MZ ;
Durfee, T ;
Cabrera, JE ;
Zhao, K ;
Jin, DJ ;
Blattner, FR .
JOURNAL OF BIOLOGICAL CHEMISTRY, 2005, 280 (16) :15921-15927
[20]   The effects of alternate optimal solutions in constraint-based genome-scale metabolic models [J].
Mahadevan, R ;
Schilling, CH .
METABOLIC ENGINEERING, 2003, 5 (04) :264-276