Diazotroph Community Characterization via a High-Throughput nifH Amplicon Sequencing and Analysis Pipeline
Document Type
Article
Publication Date
2-2018
Keywords
bioinformatics, metagenomics, next-generation sequencing, nitrogen fixation, sequence analysis, taxonomy
Digital Object Identifier (DOI)
https://doi.org/10.1128/AEM.01512-17
Abstract
The dinitrogenase reductase gene (nifH) is the most widely established molecular marker for the study of nitrogen-fixing prokaryotes in nature. A large number of PCR primer sets have been developed for nifH amplification, and the effective deployment of these approaches should be guided by a rapid, easy-to-use analysis protocol. Bioinformatic analysis of marker gene sequences also requires considerable expertise. In this study, we advance the state of the art for nifH analysis by evaluating nifH primer set performance, developing an improved amplicon sequencing workflow, and implementing a user-friendly bioinformatics pipeline. The developed amplicon sequencing workflow is a three-stage PCR-based approach that uses established technologies for incorporating sample-specific barcode sequences and sequencing adapters. Based on our primer evaluation, we recommend the Ando primer set be used with a modified annealing temperature of 58°C, as this approach captured the largest diversity of nifH templates, including paralog cluster IV/V sequences. To improve nifH sequence analysis, we developed a computational pipeline which infers taxonomy and optionally filters out paralog sequences. In addition, we employed an empirical model to derive optimal operational taxonomic unit (OTU) cutoffs for the nifH gene at the species, genus, and family levels. A comprehensive workflow script named TaxADivA (TAXonomy Assignment and DIVersity Assessment) is provided to ease processing and analysis of nifH amplicons. Our approach is then validated through characterization of diazotroph communities across environmental gradients in beach sands impacted by the Deepwater Horizon oil spill in the Gulf of Mexico, in a peat moss-dominated wetland, and in various plant compartments of a sugarcane field.
Was this content written or created while at USF?
No
Citation / Publisher Attribution
Environmental Microbiology, v84, issue 4, art. e01512-17
Scholar Commons Citation
Gaby, John Christian; Rishishwar, Lavanya; Valderrama-Aguirre, Lina C.; Green, Stefan J.; Valderrama-Aguirre, Augusto; Jordan, I. King; and Kostka, Joel E., "Diazotroph Community Characterization via a High-Throughput nifH Amplicon Sequencing and Analysis Pipeline" (2018). C-IMAGE Publications. 35.
https://digitalcommons.usf.edu/cimage_pubs/35
