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Each of 3,323 Metabolic Innovations in the Evolution of E. Coli Arose Through the Horizontal Transfer of a Single DNA Segment

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Each of 3,323 Metabolic Innovations in the Evolution of E. Coli Arose Through the Horizontal Transfer of a Single DNA Segment Each of 3,323 metabolic innovations in the evolution of E. coli arose through the horizontal transfer of a single DNA segment Tin Yau Panga,b and Martin J. Lerchera,b,1 aInstitute for Computer Science, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany; and bDepartment of Biology, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany Edited by W. Ford Doolittle, Dalhousie University, Halifax, Nova Scotia, Canada, and approved November 15, 2018 (received for review October 31, 2017) Even closely related prokaryotes often show an astounding to efficiently metabolize nutrient sources is an essential determi- diversity in their ability to grow in different nutritional environ- nant of bacterial fitness (12), and flux balance analysis (FBA) has ments. It has been hypothesized that complex metabolic adapta- been established as a robust and reliable modeling framework for tions—those requiring the independent acquisition of multiple the prediction of this ability (13, 14). new genes—can evolve via selectively neutral intermediates. A computational analysis of approximate metabolic models However, it is unclear whether this neutral exploration of pheno- generated automatically from genome sequences suggested that type space occurs in nature, or what fraction of metabolic adap- within-species phenotypic divergence is almost instantaneous, tations is indeed complex. Here, we reconstruct metabolic models whereas divergence between genera is gradual or “clock-like” for the ancestors of a phylogeny of 53 Escherichia coli strains, (12). Accordingly, the genetic distance calculated from multi- linking genotypes to phenotypes on a genome-wide, macroevolu- tionary scale. Based on the ancestral and extant metabolic models, locus sequence typing data is a weak indicator of how similar two we identify 3,323 phenotypic innovations in the history of the E. E. coli strains are in terms of the carbon sources they can me- coli clade that arose through changes in accessory genome con- tabolize (15). How can within-species divergence be so much tent. Of these innovations, 1,998 allow growth in previously in- faster than between-species divergence? The answer likely lies in EVOLUTION accessible environments, while 1,325 increase biomass yield. frequent recombination and the HGT events it facilitates be- Strikingly, every observed innovation arose through the horizon- tween bacterial strains belonging to the same species (16): A tal acquisition of a single DNA segment less than 30 kb long. Al- small set of new genes acquired through HGT can potentially though we found no evidence for the contribution of selectively lead to drastic phenotypic changes (4, 12). neutral processes, 10.6% of metabolic innovations were facilitated Horizontally transferred genes that do not provide fitness by horizontal gene transfers on earlier phylogenetic branches, benefits are likely to be lost quickly, not least because of a mu- consistent with a stepwise adaptation to successive environments. tational bias toward deletions in bacterial genomes (17). This Ninety-eight percent of metabolic phenotypes accessible to the logic suggests that successful HGTs—that is, those events that combined E. coli pangenome can be bestowed on any individual left their traces in extant genomes—were individually adaptive. strain by transferring a single DNA segment from one of the ex- A requirement for individually adaptive DNA acquisitions would tant strains. These results demonstrate an amazing ability of the E. coli lineage to adapt to novel environments through single hori- impose a strong barrier on the emergence of complex pheno- zontal gene transfers (followed by regulatory adaptations), an types that require multiple gene acquisitions, because the size of ability likely mirrored in other clades of generalist bacteria. horizontally transferred DNA segments is limited by the mech- anisms of cellular DNA uptake (18, 19). For example, DNA horizontal gene transfer | lateral gene transfer | Escherichia coli | transfers by phages (transduction), a major mechanism of HGT metabolic adaptation | flux balance analysis Significance n many ways, homologous recombination between the strains Iof a prokaryotic species is analogous to meiotic recombination Bacteria often evolve by copying genes from other strains, a in eukaryotes: It contributes to the efficient purging of delete- process termed horizontal gene transfer. As a consequence, rious mutations (1, 2) and brings together beneficial mutations different strains of the bacterial species Escherichia coli differ that arose in different genetic backgrounds (i.e., it counters substantially in the sets of genes they possess. Here, we use clonal interference) (3). Similar to recombination in eukaryotes, the inferred gene sets of all recent ancestors of 53 E. coli strains prokaryotic recombination may sometimes break up beneficial to reconstruct the ancestors’ abilities to grow in different nu- combinations of epistatically interacting sequences (1). Crucially, tritional environments. This allows us to infer over 3,000 meta- prokaryotic recombination of genomic regions that are only bolic innovations in E. coli’s evolutionary history. All innovations partially homologous facilitates horizontal gene transfer (HGT) arose through the copying (transfer) of only one small piece of between strains, a phenomenon contributing to prokaryotic ad- DNA from another strain, demonstrating an amazing capacity of aptation (4). The role of recombination in the evolution of E. coli to quickly adapt to new environments. Escherichia coli and its relationship to HGT has been studied extensively over the past 70 y (4–11). Author contributions: T.Y.P. and M.J.L. designed research; T.Y.P. performed research; With the advent of high-throughput DNA sequencing, com- T.Y.P. analyzed data; and T.Y.P. and M.J.L. wrote the paper. parative genomics all but replaced the comparison of phenotypes The authors declare no conflict of interest. as the basis for understanding evolution and natural selection. This article is a PNAS Direct Submission. However, it is the phenotype that natural selection acts upon; to Published under the PNAS license. fully appreciate the patterns and driving forces of adaptation, we 1To whom correspondence should be addressed. Email: [email protected]. need to link genotypes to phenotypes on both the genomic scale This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. and an evolutionary timescale. Bacterial metabolism is arguably 1073/pnas.1718997115/-/DCSupplemental. the most promising model system for such an endeavor. The ability Published online December 18, 2018. www.pnas.org/cgi/doi/10.1073/pnas.1718997115 PNAS | January 2, 2019 | vol. 116 | no. 1 | 187–192 Downloaded by guest on October 3, 2021 in E. coli (20), are limited by the carrying capacity of the phage size distribution of domesticated prophages in E. coli genomes capsid (18, 21). (21). Although a comparative analysis of E. coli genomes identi- Did ancient strains of the E. coli lineage find a way to cir- fied “hot” genomic regions with elevated rates of homologous cumvent the barrier to complex adaptations imposed by the size recombination that exceeded 100 kb in size, these appear to result limit on HGTs? It has been proposed that complex metabolic from the superposition of multiple smaller HGT events (28). adaptations may evolve via a neutral exploration of phenotype space (22, 23), hypothesizing that “many additions of individual Reconstruction of Ancestral E. coli Metabolic Systems. Here, to track reactions to a metabolic network will not change a metabolic phenotypic innovations in the evolutionary history of the E. coli phenotype until a second added reaction connects the first re- clade, we first reconstructed the metabolic networks of the 52 action to an already existing metabolic pathway” (23). However, ancestral strains based on a consensus annotation of the extant no empirical data from bacterial metabolism supports this sce- metabolic networks published by Monk et al. (25) and the gene nario (24); bacterial genomes appear compact and almost devoid presence and absence data inferred by Pang and Lercher (18) of nonfunctional DNA sequences (17). (see Fig. 1 for an overview and SI Appendix, Detailed Materials An alternative explanation for the emergence of complex ad- and Methods for details). We then performed FBA on the an- aptations was put forward by Szappanos et al. (24), who sug- cestral and extant networks, testing their ability to grow in gested that metabolic complexity may arise through successive 200,000 randomly generated nutritional environments as well as noncomplex adaptations to changing environments. However, in 2,418 environments used in previous simulations of E. coli K- the relative roles in bacterial evolution of simple adaptations 12 metabolic adaptation (24) (Dataset S2). Thirty extant and 46 (proceeding through individually adaptive DNA acquisitions) vs. ancestral networks were each able to grow in more than 20% of complex adaptations are currently unknown. What proportion of the environments (SI Appendix, Fig. S3 and Dataset S1). Due to metabolic innovations in a given bacterial clade was complex auxotrophies or gaps in essential pathways, the remaining models (i.e., required multiple independent HGT events)? Did such produced biomass in a small minority of the tested environments multiple DNA acquisitions occur in quick succession, or were (≤0.5%) and were excluded from further analyses. they
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