Functional genes to assess nitrogen cycling and aromatic hydrocarbon degradation: primers and processing matter

Abstract

Targeting sequencing to genes involved in key environmental processes, i.e., ecofunctional genes, provides an opportunity to sample nature's gene guilds to greater depth and help link community structure to process-level outcomes. Vastly different approaches have been implemented for sequence processing and, ultimately, for taxonomic placement of these gene reads. The overall quality of next generation sequence analysis of functional genes is dependent on multiple steps and assumptions of unknown diversity. To illustrate current issues surrounding amplicon read processing we provide examples for three ecofunctional gene groups. A combination of in silico, environmental and cultured strain sequences was used to test new primers targeting the dioxin and dibenzofuran degrading genes dxnA1, dbfA1, and carAa. The majority of obtained environmental sequences were classified into novel sequence clusters, illustrating the discovery value of the approach. For the nitrite reductase step in denitrification, the well-known nirK primers exhibited deficiencies in reference database coverage, illustrating the need to refine primer-binding sites and/or to design multiple primers, while nirS primers exhibited bias against five phyla. Amino acid-based OTU clustering of these two N-cycle genes from soil samples yielded only 114 unique nirK and 45 unique nirS genus-level groupings, likely a reflection of constricted primer coverage. Finally, supervised and non-supervised OTU analysis methods were compared using the nifH gene of nitrogen fixation, with generally similar outcomes, but the clustering (non-supervised) method yielded higher diversity estimates and stronger site-based differences. High throughput amplicon sequencing can provide inexpensive and rapid access to nature's related sequences by circumventing the culturing barrier, but each unique gene requires individual considerations in terms of primer design and sequence processing and classification.

Microbial N Transformations and N 2 O Emission after Simulated Grassland Cultivation: Effects of the Nitrification Inhibitor 3,4-Dimethylpyrazole Phosphate (DMPP)

“…While both nirK-and nirS-type denitrifiers were found in this study, a correlation between the number of mRNA copies and DEA was found only for nirS, which may suggest that nirS denitrifiers were primarily responsible for denitrification in these soils. However, Penton et al (44) tested the coverage of several commonly used nirK and nirS primer sets and found that they can capture only a subset of known denitrifiers, and especially the coverage of nirK primers was extremely low. Therefore, the abundance of nirK denitrifiers and their involvement in DEA may be underestimated in the present study.…”

High levels of heterogeneity in diazotroph diversity and activity within a putative hotspot for marine nitrogen fixation

“…Raw sequences were quality filtered, whereby sequences with a quality score o25 and reads o200-bp long were removed and clustered into operational taxonomic units (OTUs) at 95% sequence identity (Penton et al, 2013) using UCLUST (Edgar, 2010) and rarefied to the lowest number of sequences per sample (872 sequences) in QIIME (Caporaso et al, 2010). To assign putative taxonomy, representative sequences from nifH OTUs were aligned to the closest sequence in a custom nifH database (updated in April 2014) (Zehr et al, 2003;Heller et al, 2014) and placed in a phylogenetic tree using the maximum parsimony tool in ARB (Westram et al, 2011).…”

Prokaryotic and diazotrophic population dynamics within a large oligotrophic inverse estuary

“…Between 902 and 2517 nifH sequences were recovered from each sample. Raw sequences were quality filtered, clustered at 95% sequence identity (Penton et al 2013) using UCLUST (Edgar 2010) and rarefied to 902 sequences per sample in QIIME (Caporaso et al 2010). This resulted in 285 nifH operational taxonomic units (OTUs), and putative taxonomy was assigned using BLASTn (Altschul et al 1990) against the NCBI Nucleotide collection database.…”

“…Clustering of 902 nifH se quences per sample resulted in a total of 285 nifH OTUs (Edgar 2010) at 95% nucleotide sequence similarity (Penton et al 2013). Among these, there were 14 OTUs that contributed to ~60% of sequences across all samples (Fig.…”