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Abstract Background We introduce several forest-based and network-based methods for exploring microbial evolution, and apply them to the study of thousands of genes from 30 strains of E. coli. This case study illustrates how additional analyses could offer fast heuristic alternatives to standard tree of life (TOL) approaches. Results We use gene networks to identify genes with atypical modes of evolution, and genome networks to characterize the evolution of genetic partnerships between E. coli and mobile genetic elements. We develop a novel polychromatic quartet method to capture patterns of recombination within E. coli, to update the clanistic toolkit, and to search for the impact of lateral gene transfer and of pathogenicity on gene evolution in two large forests of trees bearing E. coli. We unravel high rates of lateral gene transfer involving E. coli (about 40% of the trees under study), and show that both core genes and shell genes of E. coli are affected by non-tree-like evolutionary processes. We show that pathogenic lifestyle impacted the structure of 30% of the gene trees, and that pathogenic strains are more likely to transfer genes with one another than with non-pathogenic strains. In addition, we propose five groups of genes as candidate mobile modules of pathogenicity. We also present strong evidence for recent lateral gene transfer between E. coli and mobile genetic elements. Conclusions Depending on which evolutionary questions biologists want to address (i.e. the identification of modules, genetic partnerships, recombination, lateral gene transfer, or genes with atypical evolutionary modes, etc.), forest-based and network-based methods are preferable to the reconstruction of a single tree, because they provide insights and produce hypotheses about the dynamics of genome evolution, rather than the relative branching order of species and lineages. Such a methodological pluralism - the use of woods and webs - is to be encouraged to analyse the evolutionary processes at play in microbial evolution. This manuscript was reviewed by: Ford Doolittle, Tal Pupko, Richard Burian, James McInerney, Didier Raoult, and Yan Boucher

Abstract Background Improving knowledge of biodiversity will benefit conservation biology, enhance bioremediation studies, and could lead to new medical treatments. However there is no standard approach to estimate and to compare the diversity of different environments, or to study its past, and possibly, future evolution. Presentation of the hypothesis We argue that there are two conditions for significant progress in the identification and quantification of biodiversity. First, integrative metagenomic studies - aiming at the simultaneous examination (or even better at the integration) of observations about the elements, functions and evolutionary processes captured by the massive sequencing of multiple markers - should be preferred over DNA barcoding projects and over metagenomic projects based on a single marker. Second, such metagenomic data should be studied with novel inclusive network-based approaches, designed to draw inferences both on the many units and on the many processes present in the environments. Testing the hypothesis We reached these conclusions through a comparison of the theoretical foundations of two molecular approaches seeking to assess biodiversity: metagenomics (mostly used on prokaryotes and protists) and DNA barcoding (mostly used on multicellular eukaryotes), and by pragmatic considerations of the issues caused by the 'species problem' in biodiversity studies. Implications of the hypothesis Evolutionary gene networks reduce the risk of producing biodiversity estimates with limited explanatory power, biased either by unequal rates of LGT, or difficult to interpret due to (practical) problems caused by type I and type II grey zones. Moreover, these networks would easily accommodate additional (meta)transcriptomic and (meta)proteomic data. Reviewers This article was reviewed by Pr. William Martin, Dr. David Williams (nominated by Pr. J Peter Gogarten) & Dr. James McInerney (nominated by Pr. John Logsdon).