IAMBEE

IAMBEE identifies adaptive mutations in bacterial evolution experiments by performing network-based genotype–phenotype mapping across independently evolved clonal populations to pinpoint pathways involved in adaptation.

Key Features:

• Input data: Accepts genotype information derived from independently evolved clonal populations or strains.
• Clonal-focus: Targets clonal populations that exhibit identical adapted behaviors or phenotypes.
• Adaptive vs passenger discrimination: Distinguishes adaptive mutations from passenger mutations based on recurrent patterns and additional evidence.
• Network-based analysis: Searches for recurrently mutated neighborhoods within organism-specific interaction networks as proxies for adaptive pathways.
• Functional and temporal integration: Incorporates data on the functional impact of genetic changes and their dynamics during adaptive evolution.
• Mutation rate normalization: Explicitly accounts for differences in mutation rates across independently evolved populations.
• Parallel evolution exploitation: Leverages parallel evolution to highlight pathways repeatedly involved in adaptation.

Scientific Applications:

• Experimental bacterial evolution: Identification of adaptive genetic changes arising in laboratory-evolved bacterial populations.
• Genotype–phenotype mapping: Network-based mapping of mutations to phenotypes across clonal strains.
• Pathway discovery: Pinpointing pathways and network neighborhoods recurrently involved in adaptation through parallel evolution.
• Clonal adaptation dynamics: Comparative analysis of mutation patterns and dynamics across independently evolved strains or populations.

Methodology:

Searches for recurrently mutated neighborhoods within organism-specific interaction networks, integrates functional-impact and temporal dynamics of genetic changes, and explicitly accounts for differences in mutation rates across independently evolved populations.