Chapter 21 : Modularization and Evolvability in Antibiotic Resistance

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In the real natural world, the term evolvability is used to mean the actual propensity for any biological structure to evolve-evolutionary rates. Antibiotic resistance is not only a clinical problem, but also a unique opportunity of observing “evolution in real time,” and therefore constitutes a privileged meeting point for clinical and evolutionary microbiologists. This chapter stresses the notion of modules as anatomical, structural genetic modules. Modules are also evolutionary entities, and a general view on modular evolution is presented. Modularization might be first understood as an increasing-variability process that adds modular units within a given local genetic structure. This type of first-order (essentially quantitative) modularization has a limit, because modules might tend to be either deleted or fused to other modules in a reducing-variability process. Second-order modularization might be the result of selective events acting on groups of modules produced by the first-order process. Most observed second-order modularization is possibly the result of selective events. Plasmids made by second-order modularization of other plasmid modules are probably frequent. Techniques of comparative genomics have been used to infer functional associations between proteins, based on common phylogenetic distributions, conserved gene neighborhood, or gene fusions. Similar types of methods could be developed to predict functional associations between modules involved in the emergence, expression, mobilization, or evolution of antibiotic resistance. Probably the evolutionary consequences of modularization are far more significant than those related to mutation in terms of genetic innovation, including antibiotic resistance.

Citation: Baquero F. 2008. Modularization and Evolvability in Antibiotic Resistance, p 233-247. In Baquero F, Nombela C, Cassell G, Gutiérrez-Fuentes J (ed), Evolutionary Biology of Bacterial and Fungal Pathogens. ASM Press, Washington, DC. doi: 10.1128/9781555815639.ch21
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Image of Figure 1.
Figure 1.

In panel a, a tri-modular structure, where the central black module facilitates the insertion of the hatched module, and as an effect of it the black module is duplicated, which facilitates a second module insertion (which might also happen by in situ duplication) and further sequential insertions in the same area (nested modular recruitment), producing a multimodular structure. Each of these modules might be translocated within other modular structures sharing the black module (c). In panel b, such an entire multimodular structure might now translocate as a single module (dark gray) into a new recipient modular structure, and from there might be deleted (down) or translocate again into another multimodule (d). Note that all changes are exerted in hot zones without altering the integrity of side modules.

Citation: Baquero F. 2008. Modularization and Evolvability in Antibiotic Resistance, p 233-247. In Baquero F, Nombela C, Cassell G, Gutiérrez-Fuentes J (ed), Evolutionary Biology of Bacterial and Fungal Pathogens. ASM Press, Washington, DC. doi: 10.1128/9781555815639.ch21
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Image of Figure 2.
Figure 2.

Plasticity zones. The figure illustrates the heterogeneity among different unique or shared sets of genes of plasmids R478, pHCM1, and R27 in hosting simple modules (IS). The density in vertical lines represents the frequency of ISs. Note that the density in IS modules tends to condense in particular sets of genes (principal plasticity zones). The larger sets, probably corresponding to the plasmid genetic core, are rarely interrupted by ISs. This figure is a graphic interpretation of Fig. 6 of Gilmour et al., 2004.

Citation: Baquero F. 2008. Modularization and Evolvability in Antibiotic Resistance, p 233-247. In Baquero F, Nombela C, Cassell G, Gutiérrez-Fuentes J (ed), Evolutionary Biology of Bacterial and Fungal Pathogens. ASM Press, Washington, DC. doi: 10.1128/9781555815639.ch21
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Image of Figure 3.
Figure 3.

A linguistic representation of a modular accretion process and its influence on selection. Different characters are sequentially added to “d” (up in the figure) and “e” (down) to reach the final nine-character words “darwinism” and “evolution.” In ordinates, the number of Google citations for each growing array of characters, as expressed in abscissa. This representation mimics an adaptive landscape. Low numbers of associated characters are extremely frequent, as many words include such arrays. When the number of characters increases, the number of words steeply decreases until the array reaches a “meaning” and is consequently selected (many quotes). In the upper part of the figure, the array “darwin” is selected; a second peak appears with “darwinism,” which obviously depends on the earlier success of “darwin.” In the lower part, selection of a multicharacter array (a multimodule) only occurs when the word “evolution” emerges. Note that simple arrays (at the left of the distributions) occur frequently, and then further accretion of characters might decrease significance, until reaching a significant word, which might facilitate further derivative words (“darwin” facilitates “darwinism”). This metaphor illustrates nonlinear behavior between sequential collections of modules (characters) and adaptive significance and the influence of a modular complex in the emergence of new derivative complexes.

Citation: Baquero F. 2008. Modularization and Evolvability in Antibiotic Resistance, p 233-247. In Baquero F, Nombela C, Cassell G, Gutiérrez-Fuentes J (ed), Evolutionary Biology of Bacterial and Fungal Pathogens. ASM Press, Washington, DC. doi: 10.1128/9781555815639.ch21
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