Adaptation of cells to new environments

Generation and properties of networks. Networks are a useful formalism to represent, catalog, and analyze biological information. (a) Networks are generic entities that are used to represent many types of biological interactions. The fundamental units of a network (or graph) are nodes and edges. Three types of biological information are commonly represented as a network: transcriptional, metabolic, and protein–protein interactions. The types of data used to build the network and the features that define nodes and edges vary by application. (b) Biological networks share common features. Here, we represent a transcriptional network. Three features commonly define network topology and have important dynamic consequences for the behavior of the network: (1) Hierarchy: transcriptional networks are close to scale‐free in the distribution of regulatory connections and exhibit hierarchical arrangement of connections.59 At the beginning of many biological pathways are few ‘master regulators’ that initiate response to environmental or internal cues. These master regulators propagate information to ‘middle managers’ that have many additional regulatory connections, mostly to ‘lower‐tier’ regulators that mediate specific biological functions60 (2) Modularity: biological networks aggregate pathways and functions into modules, which are defined by groups of genes, regulators, and gene products that are somehow interconnected and interdependent.61 Here, we denote a transcriptional ‘module’ by a purple ring surrounding the nodes in the module, although we note that biological modules are often composed of a diversity of part types that need not be co‐regulated. (3) Motifs: interesting dynamic behaviors of gene circuits are often mediated by particular wiring of the parts, which defines a motif. The members of a particularly well‐studied motif, the feed‐forward loop, are depicted in this illustration by green circles surrounding the nodes.62 (c) Biological networks learned from experimental data, such as the Environmental and Gene Regulatory Influence Network (EGRIN) for H. salinarum sp. NRC‐1, contain many layers of information that can be mined to aid hypothesis generation.63 (d) that yield functional and mechanistic insights, such as regulation of copper efflux in Halobacterium.64

Molecular changes that shape GRN evolution. Several molecular mechanisms mediate topological changes within GRNs. (a) Duplication of transcription factor (TF) and/or target genes (TG). Duplicated copies of a TF or downstream gene initially share the same interactions as its ancestor. Following duplication, however, either copy can subfunctionalize to contain a subset of those ancestral connections or neofunctionalize by gaining new interactions. Subfunctionalization and neofunctionalization generally occur via random mutations. (b) Mutations can occur in the coding or cis‐regulatory sequences of either TFs or TGs. Mutations in the cis‐regulatory sequences of a TG only affect interaction with that particular target, whereas mutations in coding and cis regions of TF may affect all downstream interactions. (c) Microbial genomes can be extensively modified by horizontal gene transfers (HGTs). Genomes can horizontally inherit new TF (green circle), TG (yellow circle), or both TF and its target simultaneously (not shown). TFs and TG are depicted in blue and orange circles, respectively. The cis‐regulatory regions are denoted by gray boxes attached to the circles.