Table 1.

A proposed strategy for developing and validating models of bacterial evolution that might eventually be used to classify genetic diversity data and provide a firm foundation for a bacterial species concept.

  1. Collect samples according to systematic ecological stratification. Focus on longitudinal studies, geographical studies, and measurement of physical and chemical gradients affecting bacterial growth. Consider biotic factors such as the presence of other competing bacteria or parasitic phage.

  2. For each isolate, sequence as much as possible and affordable (16S rRNA, MLSA, auxiliary genes, full genomes, etc.).

  3. Use empirical classification algorithms that use genetic and ecological data to jointly map isolates.

  4. To guide model formulation, use population genetic tests on observed clusters, focusing on tests for selection, population structure, and gene flow.

  5. Generate evolutionary models and simulate populations.

  6. Test, then reject or adapt, evolutionary models according to agreement between simulations and real populations; if necessary, return to step 1.

  7. For successful models, develop model-based methods for interpreting pure genetic data (without ecological covariates) and test on new data.

  8. If one or more validated models emerge, use these to classify genetic data and to develop bacterial species concepts.