AUTHOR=Pinna Nishal Kumar , Dutta Anirban , Monzoorul Haque Mohammed , Mande Sharmila S. 

TITLE=Can Targeting Non-Contiguous V-Regions With Paired-End Sequencing Improve 16S rRNA-Based Taxonomic Resolution of Microbiomes?: An In Silico Evaluation

JOURNAL=Frontiers in Genetics

VOLUME=Volume 10 - 2019

YEAR=2019

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2019.00653

DOI=10.3389/fgene.2019.00653

ISSN=1664-8021

ABSTRACT=Background: Next generation sequencing (NGS) technologies have enabled probing of microbial diversity in different environmental niches with unprecedented sequencing depth. However, due to read-length limitations of popular NGS technologies, 16S amplicon sequencing based microbiome studies rely on targeting short stretches of the 16S rRNA gene encompassing a selection of variable (V) regions. In most cases such a short stretch constitutes a single V-region or a couple of V-regions placed adjacent to each other on the 16S rRNA gene. Given that different V-regions have different resolving ability with respect to various taxonomic groups, selecting the optimal V-region(or a combination thereof) remains a challenge.
Methods: The accuracy of taxonomic profiles generated from sequences encompassing (1) individual V-regions (2) adjacent V- regions, and (3) pairs of non-contiguous V-regions, were assessed and compared.Subsequently, the discriminating capability of different V-regions with respect to different taxonomic lineages was assessed. The possibility of using paired-end sequencing protocols to target combinations of non adjacent V-regions was finally evaluated with respect to the utility of such an experimental design in providing improved taxonomic resolution.
Results: Extensive validation with simulated microbiome datasets mimicking different environmental and host-associated microbiome samples suggest that targeting certain combinations of non-contiguously placed V-regionsmight yield better taxonomic classification accuracy compared to conventional 16S amplicon sequencing targets.This work also puts forward a novel in silico combinatorial strategy that enables creation of consensus taxonomic profiles from experiments targeting multiple pair-wise combinations of V-regions to improve accuracy in taxonomic classification.
Conclusion: The study suggests that targeting non-contiguous V-regions with paired-end sequencing can improve 16S rRNA based taxonomic resolution of microbiomes. Furthermore, employing thenovel in silico combinatorial strategy can improve taxonomic classification without any additional experimental costs and/or efforts. The empirical observations obtained can potentially serve as a guideline for future 16S microbiome studies, and facilitate researchers in choosing the optimal combination of V-regions for a specific experiment/ sampled environment.