Abstract
BACKGROUND: Targeted amplicon sequencing of the 16S ribosomal RNA gene is one of the key tools for studying microbial diversity. The accuracy of this approach strongly depends on the choice of primer pairs and, in particular, on the balance between efficiency, specificity and sensitivity in the amplification of the different bacterial 16S sequences contained in a sample. There is thus the need for computational methods to design optimal bacterial 16S primers able to take into account the knowledge provided by the new sequencing technologies. RESULTS: We propose here a computational method for optimizing the choice of primer sets, based on multi-objective optimization, which simultaneously: 1) maximizes efficiency and specificity of target amplification; 2) maximizes the number of different bacterial 16S sequences matched by at least one primer; 3) minimizes the differences in the number of primers matching each bacterial 16S sequence. Our algorithm can be applied to any desired amplicon length without affecting computational performance. The source code of the developed algorithm is released as the mopo16S software tool (Multi-Objective Primer Optimization for 16S experiments) under the GNU General Public License and is available at http://sysbiobig.dei.unipd.it/?q=Software#mopo16S . CONCLUSIONS: Results show that our strategy is able to find better primer pairs than the ones available in the literature according to all three optimization criteria. We also experimentally validated three of the primer pairs identified by our method on multiple bacterial species, belonging to different genera and phyla. Results confirm the predicted efficiency and the ability to maximize the number of different bacterial 16S sequences matched by primers.