Cross-Study Transcriptomic Meta-Analysis Reveals Conserved Adaptive Programs in Escherichia coli K-12

Adaptive laboratory evolution (ALE) provides a powerful framework for investigating the molecular basis of bacterial adaptation, yet the extent to which transcriptional responses recur across independent evolutionary trajectories remains poorly understood. Here, we performed a cross-study transcriptomic meta-analysis of Escherichia coli K-12 ALE experiments conducted under diverse genetic and environmental selective conditions. Seven study-level inputs were integrated, including a combined signature derived from three related menF-associated comparisons and six independent transcriptomic datasets. Study-specific transcriptional responses were harmonized according to their direction and statistical evidence, followed by rank-based meta-analysis to identify genes showing recurrent expression changes across evolutionary contexts. We identified 109 conserved core genes, comprising 32 upregulated and 77 downregulated genes, that were supported across the majority of independent study-level inputs. Functional enrichment and protein-protein interaction analyses revealed that these conserved responses were organized into distinct biological modules, with prominent representation of flagellar assembly, chemotaxis, and motility, together with transport and curli/biofilm-associated functions. Highly connected genes included fliC, fliA, cheA, cheB, cheW, cheY, motA, and motB within the flagellar and chemotaxis-associated network, and csgA, csgD, csgE, csgF, and csgG within the curli-associated module. Overall, these findings demonstrate that, despite substantial diversity in evolutionary conditions and trajectories, E. coli adaptation is accompanied by a reproducible transcriptional component involving coordinated remodeling of motility, environmental sensing, transport, and surface-associated functions. Cross-study integration of ALE transcriptomes therefore provides a framework for distinguishing recurrent features of bacterial adaptation from context-specific transcriptional responses.