The "great plate count anomaly" represents a fundamental challenge in microbiome research, with vast microbial diversity remaining uncultivable. We systematically compared three methodological approaches for characterizing plant-associated bacterial communities: conventional plate cultivation, the high-throughput Prospector platform, and full-length 16S rRNA nanopore sequencing. Using mucilage-associated bacteria from teosinte and sorghum as model systems, we evaluated efficiency, taxonomic coverage, and inherent biases. The Prospector platform dramatically outperformed conventional cultivation, achieving 8x to 13.5x improvements in isolate recovery (342 vs. 43 isolates from sorghum; 379 vs. 28 from teosinte) and 1.5x to 1.8x improvements in genus-level detection. While metabarcoding detected 82 total genera, cultivation methods captured only 35.4% of this diversity, with Prospector recovering 16.9%-25.7% compared to 11.3%-14.3% for conventional methods. Each approach exhibited distinct taxonomic biases: conventional plating favored fast-growing taxa (Pseudomonas, Pantoea, Bacillus), Prospector accessed slower-growing bacteria (Sphingomonas, Curtobacterium), while metabarcoding exclusively detected 59-85 cultivation-resistant genera. We propose an integrated framework leveraging complementary strengths: metabarcoding for comprehensive profiling, Prospector for enhanced cultivation efficiency, and conventional isolation for targeted applications. Together, our findings establish quantitative benchmarks for method comparison and support an integrative framework that combines metabarcoding for comprehensive profiling, the Prospector platform for enhanced cultivation efficiency, and conventional isolation for targeted applications, highlighting how methodological choices fundamentally shape our understanding of microbial diversity.
Vega‐Camarillo et al. (Sun,) studied this question.