At the heart of microbial evolution is a process of genome streamlining that rapidly discards genetic material that is not under selection, a process that appears to carry an advantage to the organism (Lynch, 2006; Koskiniemi et al., 2012).
The immune system is composed of innate and adaptive immune systems, in which the machinery behind innate immune system is very ingenious due to the conserved ability to recognize microbial components during evolution process.
Life's early history is a process of microbial evolution, where neither the evolutionary events linking the evolution of genes across prokaryotic genomes nor the processes linking prokaryotes to eukaryotes are strictly tree-like in nature [ 3].
Genome sequence analyses indicate that preferential transfer of genes is strongly correlated with gene function and is a frequent process in microbial evolution [13] accounting for much of the biodiversity among isolates [14] [15].
Lateral gene transfer (LGT) is an important evolutionary process in microbial evolution.
Networks do not confine our thinking to the preconcieved notion that microbial evolution corresponds solely to a process of pure clonal lineage splittings that, over time, generate the patterns of recurrently bifurcating trees.
Although network methods have limitations [ 112], they should nonetheless permit progress towards more accurate representations of the process of microbial evolution as it occurs in nature, as opposed to depicting how some of us think it might occur by extrapolation from observations and experience in the study of vertebrates.
A deluge of whole-genome sequencing has begun to give insights into the patterns and processes of microbial evolution, but genome sequences have accrued in a haphazard manner, with biased sampling of natural variation that is driven largely by medical and epidemiological priorities.
In the first section, the 5 chapters introduce the basic processes affecting microbial evolution, from the individual molecular level to the genomic, cellular, and population levels.
Then, as a proof of concept, we show how EGN can be used to study the complexity of evolutionary processes affecting microbial evolution.
