Abstract
Steps in the global nitrogen cycle are mainly catalyzed by microorganisms. Accordingly, the activities of these microorganisms affect the health and productivity of ecosystems. Their activities are also used in wastewater treatment systems to remove reactive nitrogen compounds and prevent eutrophication events triggered by nutrient discharges. Therefore, tracking the activities of these microorganisms can provide insights into the functioning of these systems. The presence and abundance of genes encoding nitrogen-metabolizing enzymes can be traced via polymerase chain reaction (PCR); however, this requires primers that are sensitive to a heterogenous gene pool yet specific enough to the target biomarker. The ever-expanding diversity of sequences available from databases includes many sequences relevant to nitrogen metabolism that match poorly with primers previously designed to track their presence and/or abundance. This includes genes encoding ammonia monooxygenase (AMO) of ammonia oxidizing microorganisms, nitrite oxidoreductase (NXR) of nitrite oxidizing bacteria, and nitrous oxide reductase (NOS) of denitrifying bacteria. Some primers are also not designed to generate the short (~200 nucleotides) amplicons required for real-time quantitative PCR (qPCR) and reverse-transcriptase qPCR (qRT-PCR). In this study, genes collected from the Integrated Microbial Genomes database (IMG) were aligned to design PCR primers that could capture more sequence diversity than is possible using existing primers. Primers were designed to target three clades of AMO (Betaproteobacteria, Chrenarchaeota, and complete ammonia oxidizing Nitrospira), periplasmic NXR and two clades of NOS (Proteobacteria and Bacteroidetes/Firmicutes). These primers successfully amplified target sequences from two wastewater treatment plants with biological nitrogen removal (one with simultaneous nitrification/denitrification and one with distinct anoxic/oxic zones) and estuary sediment. Nucleotide sequences of the amplicons retrieved homologs when used to query GenBank by BLAST. While convincingly identified as target sequences for these primer pairs, these amplicons were divergent from each other, and quite divergent (as low as 73%) from those present in GenBank, suggesting these primers are capable of capturing a diverse range of sequences. A direct comparison showed that primers designed here are better suited to environmental samples, such as wastewater treatment facilities, by producing a greater number of amplicons from the same sample than primers currently established in literature.
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