Primer choice shapes microbial community interpretation across habitats and informs short-term structured enrichment in environmental and applied systems.

Microbial communities play central roles in ecosystem functioning across natural and engineered environments, yet their accurate characterization remains challenging due to methodological biases in amplicon sequencing. Primer choice can strongly influence taxonomic resolution, diversity estimates, and ecological interpretation. Here, we systematically compared primer performance across multiple ribosomal marker genes (16S, 18S, 28S rRNA, and ITS) and contrasting habitats, including soil, wastewater, and a photobioreactor-derived suspension. Amplicon-based profiles were benchmarked against shotgun metagenomic data. Primer choice significantly affected community composition, diversity metrics, and concordance with metagenomic profiles across all habitats and markers. Although 16S rRNA gene primers targeting the V3 region showed the highest agreement, no primer set fully reconstructed community structure. Applying the best-performing primer to a structured soil enrichment system using MESIF chips revealed rapid divergence from native soil and convergence toward less diverse communities, consistently favoring copiotrophic, surface-associated taxa while characteristic soil taxa declined. Across the 21-day incubation period, MESIF-associated communities diverged strongly from native soil, whereas medium-specific differences were comparatively smaller. This suggests that early enrichment was dominated by colonization of the structured matrix, while longer incubations and functional analyses will be needed to resolve substrate-specific selection. Overall, our findings highlight primer selection as a critical factor in microbial community analysis and show that combining optimized amplicon sequencing with structured cultivation enables reproducible enrichment, improved community monitoring, and targeted recovery of functionally relevant microorganisms. These insights are relevant for environmental monitoring, wastewater treatment, biotechnology, and controlled environment agriculture.