scispace - formally typeset
Search or ask a question
Journal ArticleDOI

Empirical fitness landscapes and the predictability of evolution

01 Jul 2014-Nature Reviews Genetics (Nature Publishing Group)-Vol. 15, Iss: 7, pp 480-490
TL;DR: This work reviews recent empirical and theoretical developments of the genotype–fitness map, identifies methodological issues and organizing principles, and discusses possibilities to develop more realistic fitness landscape models.
Abstract: A central topic in biology concerns how genotypes determine phenotypes and functions of organisms that affect their evolutionary fitness. This Review discusses recent advances in the development of empirical fitness landscapes and their contribution to theoretical analyses of the predictability of evolution. The genotype–fitness map (that is, the fitness landscape) is a key determinant of evolution, yet it has mostly been used as a superficial metaphor because we know little about its structure. This is now changing, as real fitness landscapes are being analysed by constructing genotypes with all possible combinations of small sets of mutations observed in phylogenies or in evolution experiments. In turn, these first glimpses of empirical fitness landscapes inspire theoretical analyses of the predictability of evolution. Here, we review these recent empirical and theoretical developments, identify methodological issues and organizing principles, and discuss possibilities to develop more realistic fitness landscape models.
Citations
More filters
Journal ArticleDOI
TL;DR: Escherichia coli sequence type 131 (ST131) and Klebsiella pneumoniae ST258 emerged in the 2000s as important human pathogens, have spread extensively throughout the world, and are responsible for the rapid increase in antimicrobial resistance among E. coli and K. pneumoniae strains.
Abstract: SUMMARY Escherichia coli sequence type 131 (ST131) and Klebsiella pneumoniae ST258 emerged in the 2000s as important human pathogens, have spread extensively throughout the world, and are responsible for the rapid increase in antimicrobial resistance among E. coli and K. pneumoniae strains, respectively. E. coli ST131 causes extraintestinal infections and is often fluoroquinolone resistant and associated with extended-spectrum β-lactamase production, especially CTX-M-15. K. pneumoniae ST258 causes urinary and respiratory tract infections and is associated with carbapenemases, most often KPC-2 and KPC-3. The most prevalent lineage within ST131 is named fimH30 because it contains the H30 variant of the type 1 fimbrial adhesin gene, and recent molecular studies have demonstrated that this lineage emerged in the early 2000s and was then followed by the rapid expansion of its sublineages H30-R and H30-Rx. K. pneumoniae ST258 comprises 2 distinct lineages, namely clade I and clade II. Moreover, it seems that ST258 is a hybrid clone that was created by a large recombination event between ST11 and ST442. Epidemic plasmids with blaCTX-M and blaKPC belonging to incompatibility group F have contributed significantly to the success of these clones. E. coli ST131 and K. pneumoniae ST258 are the quintessential examples of international multidrug-resistant high-risk clones.

597 citations


Cites background from "Empirical fitness landscapes and th..."

  • ...Antimicrobial therapy with the subsequent selection of antimicrobial-resistant mutations is considered to be one of the most efficient artificial selection pressures introduced by humans (203)....

    [...]

Journal ArticleDOI
11 May 2016-Nature
TL;DR: An extensive region of the local fitness landscape of the green fluorescent protein from Aequorea victoria (avGFP) is visualize by measuring the native function (fluorescence) of tens of thousands of derivative genotypes of avGFP, indicating congruence between the fitness landscape properties at the local and global scales.
Abstract: Fitness landscapes depict how genotypes manifest at the phenotypic level and form the basis of our understanding of many areas of biology, yet their properties remain elusive. Previous studies have analysed specific genes, often using their function as a proxy for fitness, experimentally assessing the effect on function of single mutations and their combinations in a specific sequence or in different sequences. However, systematic high-throughput studies of the local fitness landscape of an entire protein have not yet been reported. Here we visualize an extensive region of the local fitness landscape of the green fluorescent protein from Aequorea victoria (avGFP) by measuring the native function (fluorescence) of tens of thousands of derivative genotypes of avGFP. We show that the fitness landscape of avGFP is narrow, with 3/4 of the derivatives with a single mutation showing reduced fluorescence and half of the derivatives with four mutations being completely non-fluorescent. The narrowness is enhanced by epistasis, which was detected in up to 30% of genotypes with multiple mutations and mostly occurred through the cumulative effect of slightly deleterious mutations causing a threshold-like decrease in protein stability and a concomitant loss of fluorescence. A model of orthologous sequence divergence spanning hundreds of millions of years predicted the extent of epistasis in our data, indicating congruence between the fitness landscape properties at the local and global scales. The characterization of the local fitness landscape of avGFP has important implications for several fields including molecular evolution, population genetics and protein design.

453 citations

Journal ArticleDOI
09 Nov 2018-Science
TL;DR: The authors' review of many such experiments indicates that responses across replicate populations are often repeatable to some degree, although divergence increases as analyses move from overall fitness to underlying phenotypes and genetic changes.
Abstract: Historical processes display some degree of "contingency," meaning their outcomes are sensitive to seemingly inconsequential events that can fundamentally change the future. Contingency is what makes historical outcomes unpredictable. Unlike many other natural phenomena, evolution is a historical process. Evolutionary change is often driven by the deterministic force of natural selection, but natural selection works upon variation that arises unpredictably through time by random mutation, and even beneficial mutations can be lost by chance through genetic drift. Moreover, evolution has taken place within a planetary environment with a particular history of its own. This tension between determinism and contingency makes evolutionary biology a kind of hybrid between science and history. While philosophers of science examine the nuances of contingency, biologists have performed many empirical studies of evolutionary repeatability and contingency. Here, we review the experimental and comparative evidence from these studies. Replicate populations in evolutionary "replay" experiments often show parallel changes, especially in overall performance, although idiosyncratic outcomes show that the particulars of a lineage's history can affect which of several evolutionary paths is taken. Comparative biologists have found many notable examples of convergent adaptation to similar conditions, but quantification of how frequently such convergence occurs is difficult. On balance, the evidence indicates that evolution tends to be surprisingly repeatable among closely related lineages, but disparate outcomes become more likely as the footprint of history grows deeper. Ongoing research on the structure of adaptive landscapes is providing additional insight into the interplay of fate and chance in the evolutionary process.

364 citations

Journal ArticleDOI
TL;DR: Improving enzymes by directed evolution requires the navigation of very large search spaces; this work surveys how to do this intelligently.
Abstract: The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the ‘search space’ of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (Kd) and catalytic (kcat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving kcat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the ‘best’ amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole, simultaneously, this offers opportunities for protein improvement not readily available to natural evolution on rapid timescales. Intelligent landscape navigation, informed by sequence-activity relationships and coupled to the emerging methods of synthetic biology, offers scope for the development of novel biocatalysts that are both highly active and robust.

337 citations

References
More filters
Journal ArticleDOI
01 Mar 1931-Genetics
TL;DR: Page 108, last line of text, for "P/P″" read "P′/ P″."
Abstract: Page 108, last line of text, for "P/P″" read "P′/P″." Page 120, last line, for "δ v " read "δ y ." Page 123, line 10, for "4Nn" read "4Nu." Page 125, line 1, for "q" read "q." Page 126, line 12, for "q" read "q." Page 135, line 5 from bottom, for "y4Nsq" read "e4Nsq." Page 141, lines 8

7,850 citations

Journal ArticleDOI
TL;DR: The frequency of a given gene in a population may be modified by a number of conditions including recurrent mutation to and from it, migration, selection of various sorts and, far from least in importance, were chance variation.

4,833 citations

Book
05 May 1993

2,454 citations

Book
01 Jan 1989
TL;DR: In this article, the authors explore what the Burgess Shale tells us about evolution and the nature of history and find that it holds the remains of an ancient sea where dozens of strange creatures lived.
Abstract: High in the Canadian Rockies is a small limestone quarry formed 530 million years ago called the Burgess Shale. It hold the remains of an ancient sea where dozens of strange creatures lived-a forgotten corner of evolution preserved in awesome detail. In this book Stephen Jay Gould explores what the Burgess Shale tells us about evolution and the nature of history.

1,901 citations

Journal ArticleDOI
TL;DR: There is a renewed appreciation both for the importance of studying gene interactions and for addressing these questions in a unified, quantitative manner with the advent of high-throughput functional genomics.
Abstract: Epistasis, or interactions between genes, has long been recognized as fundamentally important to understanding the structure and function of genetic pathways and the evolutionary dynamics of complex genetic systems. With the advent of high-throughput functional genomics and the emergence of systems approaches to biology, as well as a new-found ability to pursue the genetic basis of evolution down to specific molecular changes, there is a renewed appreciation both for the importance of studying gene interactions and for addressing these questions in a unified, quantitative manner.

1,387 citations


Additional excerpts

  • ...f(σ) = a(0) + ai((1))σi + aij((2))σiσj + aijk((3))σiσjσk + ....

    [...]