Rapid Succession of Actively Transcribing Denitrifier Populations in Agricultural Soil During an Anoxic Spell

Genome-Resolved Metagenomics and Denitrifying Strain Isolation Reveal New Insights into Microbial Denitrification in the Deep Vadose Zone

The heavy use of nitrogen fertilizer in intensive agricultural areas often leads to nitrate accumulation in subsurface soil and nitrate contamination in groundwater, which poses a serious risk to public health. Denitrifying microorganisms in the subsoil convert nitrate to gaseous forms of nitrogen, thereby mitigating the leaching of nitrate into groundwater. Here, we investigated denitrifying microorganisms in the deep vadose zone of a typical intensive agricultural area in China through microcosm enrichment, genome-resolved metagenomic analysis, and denitrifying bacteria isolation. A total of 1000 metagenome-assembled genomes (MAGs) were reconstructed, resulting in 98 high-quality, dereplicated MAGs that contained denitrification genes. Among them, 32 MAGs could not be taxonomically classified at the genus or species level, indicating that a broader spectrum of taxonomic groups is involved in subsoil denitrification than previously recognized. A denitrifier isolate library was constructed by using a strategy combining high-throughput and conventional cultivation techniques. Assessment of the denitrification characteristics of both the MAGs and isolates demonstrated the dominance of truncated denitrification. Functional screening revealed the highest denitrification activity in two complete denitrifiers belonging to the genus Pseudomonas. These findings greatly expand the current knowledge of the composition and function of denitrifying microorganisms in subsoils. The constructed isolate library provided the first pool of subsoil-denitrifying microorganisms that could facilitate the development of microbe-based technologies for nitrate attenuation in groundwater.

Modified microbiology through enhanced denitrification by addition of various organic substances-temperature effect

Worldwide, the environmental nitrate (NO₃^-) problem is increasingly coming into focus. These increases in NO₃^- concentration result mainly from agricultural inputs and are further exacerbated by decreasing and finite geogenic NO₃^- degradation capacity in aquifers. Thus, treatment methods are becoming more and more important. In this study, the effects of enhanced denitrification with addition of organic carbon (C) on thereby autochthonous occurring microbiology and compared at room temperature as well as 10 °C were investigated. Incubation of bacteria and fungi was carried out using natural sediments without degradation capacity and groundwater with high NO₃^- concentrations. Addition of the four applied substrates (acetate, glucose, ascorbic acid, and ethanol) results in major differences in microbial community. Cooling to 10 °C changes the microbiology again. Relative abundances of bacteria are strongly influenced by temperature, which is probably the explanation for different denitrification rates. Fungi are much more sensitive to the milieu change with organic C. Different fungi taxa preferentially occur at one of the two temperature approaches. Major modifications of the microbial community are mainly observed whose denitrification rates strongly depend on the temperature effect. Therefore, we assume a temperature optimum of enhanced denitrification specific to each substrate, which is influenced by the microbiology.

Coal-mining subsidence changed distribution of the microbiomes and their functional genes in a farmland

Land subsidence is a serious geological event, and can trigger severe environmental and ecological issues. In this study, the influences of coal-mining subsidence on distribution of farmland microbiomes and their functional genes were investigated by 16 S ribosomal RNA (rRNA) gene and metagenome sequencing. The results showed the existence of a core microbiome, which determined the community compositions across the subsidence farmland. Subsidence decreased the relative abundances of dominant Streptomyces, Nocardioides, and Rhizophagus, but increased the relative abundances of dominant Bradyrhizobium, Rhizobium, and Trichoderma. Subsidence also decreased the relative abundances of genes related to carbon metabolism, Quorum sensing, aminoacyl-transfer RNA (tRNA) biosynthesis, and oxidative phosphorylation, and increased the relative abundances of genes related to two-component system and bacterial chemotaxis. Furthermore, subsidence weakened the biosynthesis of organic carbons by decreasing the relative abundances of genes encoding glycosyl transferases, and strengthened decomposition of degradable organic carbons of the microbiomes and auxiliary activities by increasing the relative abundances of genes encoding glycoside hydrolases and polysaccharide lyases. The concentrations of total phosphorus, Mg²⁺ , and Ca²⁺ at the lower areas were significantly higher than those at the upper areas, indicating an associated loss of soil nutrients. Canonical correspondence analysis showed that soil moisture, pH, and the concentrations of NH₄ ⁺ and Ca²⁺ were the main factors affecting the distribution of the microbiomes and their functional genes. Collectively, this study shows that coal-mining subsidence alters soil physicochemical properties and distribution of farmland microbiomes and their functional genes.

A review on nirS-type and nirK-type denitrifiers via a scientometric approach coupled with case studies

The denitrification process plays an important role in improving water quality and is a source/sink of nitrous oxide to the atmosphere. The second important rate-limiting step of the denitrification process is catalyzed by two enzymes with different structures and unrelated evolutionary relationships, namely, the Cu-type nitrite reductase encoded by the nirK gene and the cytochrome cd1-type nitrite reductase encoded by the nirS gene. Although some relevant reviews have been published on denitrifiers, most of these reviews do not include statistical analysis, and do not compare the nirS and nirK communities in-depth. However, a systematic study of the nirS-type and nirK-type denitrifying communities and their response to environmental factors in different ecosystems is needed. In this review, a scientometric approach combined with case studies was used to study the nirS-type and nirK-type denitrifiers. The scientometric approach demonstrated that Pseudomonas, Paracoccus, and Thauera are the most frequently mentioned nirS-type denitrifiers, while Pseudomonas and Bradyrhizobium are the top two most frequently mentioned nirK-type denitrifiers. Among various environmental factors, the concentrations of nitrite, nitrate and carbon sources were widely reported factors that can influence the abundance and structure of nirS-type and nirK-type denitrifying communities. Case studies indicated that Bradyrhizobium was the major genus detected by high-throughput sequencing in both nirS and nirK-type denitrifiers in soil systems. nirS-type denitrifiers are more sensitive to the soil type, soil moisture, pH, and rhizosphere effect than nirK. To clarify the relationships between denitrifying communities and environmental factors, the DNA stable isotope probe combined with metagenomic sequencing is needed for new denitrifier detections.

Linking meta-omics to the kinetics of denitrification intermediates reveals pH-dependent causes of N2O emissions and nitrite accumulation in soil

Soil pH is a key controller of denitrification. We analysed the metagenomics/transcriptomics and phenomics of two soils from a long-term liming experiment, SoilN (pH 6.8) and un-limed SoilA (pH 3.8). SoilA had severely delayed N2O reduction despite early transcription of nosZ (mainly clade I), encoding N2O reductase, by diverse denitrifiers. This shows that post-transcriptionally hampered maturation of the NosZ apo-protein at low pH is a generic phenomenon. Identification of transcript reads of several accessory genes in the nos cluster indicated that enzymes for NosZ maturation were present across a range of organisms, eliminating their absence as an explanation for the failure to produce a functional enzyme. nir transcript abundances (for NO2- reductase) in SoilA suggest that low NO2- concentrations in acidic soils, often ascribed to abiotic degradation, are primarily due to biological activity. The accumulation of NO2- in neutral soil was ascribed to high nar expression (nitrate reductase). The -omics results revealed dominance of nirK over nirS in both soils while qPCR showed the opposite, demonstrating that standard primer pairs only capture a fraction of the nirK pool. qnor encoding NO reductase was strongly expressed in SoilA, implying an important role in controlling NO. Production of HONO, for which some studies claim higher, others lower, emissions from NO2- accumulating soil, was estimated to be ten times higher from SoilA than from SoilN. The study extends our understanding of denitrification-driven gas emissions and the diversity of bacteria involved and demonstrates that gene and transcript quantifications cannot always reliably predict community phenotypes.

Competition and community succession link N transformation and greenhouse gas emissions in urine patches

Nitrous oxide (N₂O) is a strong greenhouse gas produced by biotic/abiotic processes directly linked to both fungal and prokaryotic communities that produce, consume or create conditions leading to its emission. In soils exposed to nitrogen (N) in the form of urea, an ecological succession is triggered resulting in a dynamic turnover of microbial populations. However, knowledge of the mechanisms controlling this succession and the repercussions for N₂O emissions remain incomplete. Here, we monitored N₂O production and fungal/prokaryotic community changes (via 16S and 18S amplicon sequencing) in soil microcosms exposed to urea. Contributions of microbes to emissions were determined using biological inhibitors. Results confirmed that urea leads to shifts in microbial community assemblages by selecting for certain microbial groups (fast growers) as dictated through life history strategies. Urea reduced overall community diversity by conferring dominance to specific groups at different stages in the succession. The diversity lost under urea was recovered with inhibitor addition through the removal of groups that were actively growing under urea indicating that species replacement is mediated in part by competition. Results also identified fungi as significant contributors to N₂O emissions, and demonstrate that dominant fungal populations are consistently replaced at different stages of the succession. These successions were affected by addition of inhibitors which resulted in strong decreases in N₂O emissions, suggesting that fungal contributions to N₂O emissions are larger than that of prokaryotes.

Reduced metagenome sequencing for strain-resolution taxonomic profiles

BACKGROUND

Studies of shifts in microbial community composition has many applications. For studies at species or subspecies levels, the 16S amplicon sequencing lacks resolution and is often replaced by full shotgun sequencing. Due to higher costs, this restricts the number of samples sequenced. As an alternative to a full shotgun sequencing we have investigated the use of Reduced Metagenome Sequencing (RMS) to estimate the composition of a microbial community. This involves the use of double-digested restriction-associated DNA sequencing, which means only a smaller fraction of the genomes are sequenced. The read sets obtained by this approach have properties different from both amplicon and shotgun data, and analysis pipelines for both can either not be used at all or not explore the full potential of RMS data.

RESULTS

We suggest a procedure for analyzing such data, based on fragment clustering and the use of a constrained ordinary least square de-convolution for estimating the relative abundance of all community members. Mock community datasets show the potential to clearly separate strains even when the 16S is 100% identical, and genome-wide differences is < 0.02, indicating RMS has a very high resolution. From a simulation study, we compare RMS to shotgun sequencing and show that we get improved abundance estimates when the community has many very closely related genomes. From a real dataset of infant guts, we show that RMS is capable of detecting a strain diversity gradient for Escherichia coli across time.

CONCLUSION

We find that RMS is a good alternative to either metabarcoding or shotgun sequencing when it comes to resolving microbial communities at the strain level. Like shotgun metagenomics, it requires a good database of reference genomes and is well suited for studies of the human gut or other communities where many reference genomes exist. A data analysis pipeline is offered, as an R package at https://github.com/larssnip/microRMS . Video abstract.