Background: Subunits of ribosomal RNA genes (rDNAs) characterized by PCR-based protocols have been the proxy for studies in microbial taxonomy, phylogenetics, evolution and ecology. However, relevant factors have shown to interfere in the experimental outputs in a variety of systems. In this work, a 'theoretical' to 'actual' delta approach was applied to data on culturable mock bacterial communities (MBCs) to study the levels of losses in operational taxonomic units (OTUs) detectability. Computational and lab-bench strategies based on 16S rDNA amplification by 799F and U1492R primers were employed, using a fingerprinting method with highly improved detectability of fragments as a case-study tool. MBCs were of two major types: in silico MBCs, assembled with database-retrieved sequences, and in vitro MBCs, with AluI digestions of PCR data generated from culturable endophytes isolated from cacao trees.
Results: Interfering factors for the 16 s rDNA amplifications, such as the type of template, direct and nested PCR, proportion of chloroplast DNA from a tropical plant source (Virola officinalis), and biased-amplification by the primers resulted in altered bacterial 16S rDNA amplification, both on MBCs and V. officinalis leaf-extracted DNA. For the theoretical data, the maximum number of fragments for in silico and in vitro cuts were not significantly different from each other. Primers' preferences for certain sequences were detected, depending on the MBCs' composition prior to PCR. The results indicated overall losses from 2.3 up to 8.2 times in the number of OTUs detected from actual AluI digestions of MBCs when compared to in silico and in vitro theoretical data.
Conclusions: Due to all those effects, the final amplification profile of the bacterial community assembled was remarkably simplified when compared to the expected number of detectable fragments known to be present in the MBC. From these findings, the scope of hypotheses generation and conclusions from experiments based on PCR amplifications of bacterial communities was discussed.
Keywords: 16S rDNA metagenomics; ARDRA; CAPS; Chimeric sequences; Community structure; Fingerprinting methods; Hypervariable regions; Microbial ecology and diversity; PCR-RFLP; Plant-associated bacteria.