PT  - JOURNAL ARTICLE
AU  - Richard E. Lenski
AU  - Michael J. Wiser
AU  - Noah Ribeck
AU  - Zachary D. Blount
AU  - Joshua R. Nahum
AU  - J. Jeffrey Morris
AU  - Luis Zaman
AU  - Caroline B. Turner
AU  - Brian D. Wade
AU  - Rohan Maddamsetti
AU  - Alita R. Burmeister
AU  - Elizabeth J. Baird
AU  - Jay Bundy
AU  - Nkrumah A. Grant
AU  - Kyle J. Card
AU  - Maia Rowles
AU  - Kiyana Weatherspoon
AU  - Spiridon E. Papoulis
AU  - Rachel Sullivan
AU  - Colleen Clark
AU  - Joseph S. Mulka
AU  - Neerja Hajela
TI  - Sustained fitness gains and variability in fitness trajectories in the long-term evolution experiment with <em>Escherichia coli</em>
AID  - 10.1101/027391
DP  - 2015 Jan 01
TA  - bioRxiv
PG  - 027391
4099  - http://biorxiv.org/content/early/2015/09/22/027391.short
4100  - http://biorxiv.org/content/early/2015/09/22/027391.full
AB  - Many populations live in environments subject to frequent biotic and abiotic changes. Nonetheless, it is interesting to ask whether an evolving population’s mean fitness can increase indefinitely, and potentially without any limit, even in a constant environment. A recent study showed that fitness trajectories of Escherichia coli populations over 50,000 generations were better described by a power-law model than by a hyperbolic model. According to the power-law model, the rate of fitness gain declines over time but fitness has no upper limit, whereas the hyperbolic model implies a hard limit. Here, we examine whether the previously estimated power-law model predicts the fitness trajectory for an additional 10,000 generations. To that end, we conducted more than 1100 new competitive fitness assays. Consistent with the previous study, the power-law model fits the new data better than the hyperbolic model. We also analysed the variability in fitness among populations, finding subtle, but significant, heterogeneity in mean fitness. Some, but not all, of this variation reflects differences in mutation rate that evolved over time. Taken together, our results imply that both adaptation and divergence can continue indefinitely— or at least for a long time—even in a constant environment.