Metagenomic analysis reveals distinct patterns of denitrification gene abundance across soil moisture, nitrate gradients.

This study coupled a landscape-scale metagenomic survey of denitrification gene abundance in soils with in situ denitrification measurements to show how environmental factors shape distinct denitrification communities that exhibit varying denitrification activity. Across a hydrologic gradient, the distribution of total denitrification genes (nap/nar + nirK/nirS + cNor/qNor + nosZ) inferred from metagenomic read abundance exhibited no consistent patterns. However, when genes were considered independently, nirS, cNor and nosZ read abundance was positively associated with areas of higher soil moisture, higher nitrate and higher annual denitrification rates, whereas nirK and qNor read abundance was negatively associated with these factors. These results suggest that environmental conditions, in particular soil moisture and nitrate, select for distinct denitrification communities that are characterized by differential abundance of genes encoding apparently functionally redundant proteins. In contrast, taxonomic analysis did not identify notable variability in denitrifying community composition across sites. While the capacity to denitrify was ubiquitous across sites, denitrification genes with higher energetic costs, such as nirS and cNor, appear to confer a selective advantage in microbial communities experiencing more frequent soil saturation and greater nitrate inputs. This study suggests metagenomics can help identify denitrification hotspots that could be protected or enhanced to treat non-point source nitrogen pollution.

Modularity of nitrogen-oxide reducing soil bacteria: linking phenotype to genotype.

Model denitrifiers convert NO3- to N2 , but it appears that a significant fraction of natural populations are truncated, conducting only one or two steps of the pathway. To better understand the diversity of partial denitrifiers in soil and whether discrepancies arise between the presence of known N-oxide reductase genes and phenotypic features, bacteria able to reduce NO3- to NO2- were isolated from soil, N-oxide gas products were measured for eight isolates, and six were genome sequenced. Gas phase analyses revealed that two were complete denitrifiers, which genome sequencing corroborated. The remaining six accumulated NO and N2 O to varying degrees and genome sequencing of four indicated that two isolates held genes encoding nitrate reductase as the only dissimilatory N-oxide reductase, one contained genes for both nitrate and nitric oxide reductase, and one had nitrate and nitrite reductase. The results demonstrated that N-oxide production was not always predicted by the genetic potential and suggested that partial denitrifiers could be readily isolated among soil bacteria. This supported the hypothesis that each N-oxide reductase could provide a selectable benefit on its own, and therefore, reduction of nitrate to dinitrogen may not be obligatorily linked to complete denitrifiers but instead a consequence of a functionally diverse community.

Transparent DNA/RNA Co-extraction Workflow Protocol Suitable for Inhibitor-Rich Environmental Samples That Focuses on Complete DNA Removal for Transcriptomic Analyses.

Adequate comparisons of DNA and cDNA libraries from complex environments require methods for co-extraction of DNA and RNA due to the inherent heterogeneity of such samples, or risk bias caused by variations in lysis and extraction efficiencies. Still, there are few methods and kits allowing simultaneous extraction of DNA and RNA from the same sample, and the existing ones generally require optimization. The proprietary nature of kit components, however, makes modifications of individual steps in the manufacturer's recommended procedure difficult. Surprisingly, enzymatic treatments are often performed before purification procedures are complete, which we have identified here as a major problem when seeking efficient genomic DNA removal from RNA extracts. Here, we tested several DNA/RNA co-extraction commercial kits on inhibitor-rich soils, and compared them to a commonly used phenol-chloroform co-extraction method. Since none of the kits/methods co-extracted high-quality nucleic acid material, we optimized the extraction workflow by introducing small but important improvements. In particular, we illustrate the need for extensive purification prior to all enzymatic procedures, with special focus on the DNase digestion step in RNA extraction. These adjustments led to the removal of enzymatic inhibition in RNA extracts and made it possible to reduce genomic DNA to below detectable levels as determined by quantitative PCR. Notably, we confirmed that DNase digestion may not be uniform in replicate extraction reactions, thus the analysis of "representative samples" is insufficient. The modular nature of our workflow protocol allows optimization of individual steps. It also increases focus on additional purification procedures prior to enzymatic processes, in particular DNases, yielding genomic DNA-free RNA extracts suitable for metatranscriptomic analysis.