Nitrous Clone

[Catherine Rubeo]

Thisenzyme catalyses the conversion of Nitrous Oxide, a greenhouse gas to Nitrogen gas. The NosZ gene is cloned under the control of a strong Promoter with a Ribosome Binding Site for optimum expression.

NosZ gene encodes for the dissimilatory Nitrous Oxide reductase protein. This enzyme, localized in the periplasmic space of the bacterium, catalyzes the conversion of Nitrous Oxide to molecular Nitrogen gas, which is then released by the host into the atmosphere. Thus, denitrification, which is an ecologically important step, is catalyzed by this enzyme.

Team IIT Delhi has designed a bacterial system that overexpresses the dissimilatory Nitrous Oxide Reductase enzyme. We cloned the NosZ gene encoding the enzyme onto an expression vector pSB1C3 under the control of a strong promoter. The recombinant DNA vector can be stably maintained in the host under antibiotic selection pressure. This engineered bacterium is capable of reducing the levels of Nitrous Oxide, a potent greenhouse gas, by a process known as denitrifiication.

The enzyme Nitrous Oxide Reductase has been found in many prokaryotes like Pseudomonas stutzeri that respire anaerobically in environments rich in Nitrates. Nitrates are transported by Nitrate transporters into the cell, which are then converted eventually into Nitrous Oxide by the enzymes of the denitrification pathway. This is then converted into Nitrogen gas that is released into the atmosphere.

Thus, the activity of dissimilatory Nitrous Oxide Reductase is one part of the big pathway of conversion of Nitrates to Nitrogen gas.The engineered bacterial system would catalyze the final step in the pathway thereby reducing the levels of Nitrous Oxide in the feed.

We performed a double digestion by EcoRI and PstI to release the cloned fragment from the recombinant vector. The digestion products were resolved on an Agarose Gel by Electrophoresis and the size of the fragment confirmed the correct clone.

The real-life problem that we thought of addressing was the reduction of the levels of harmful greenhouse gases like Nitrogen oxides that are usually found in the exhaust fumes of Diesel-based engines.

To test the effectiveness of our prototype, we used the exhaust of a diesel generator as a feed to the system and analyzed the outlet for the presence of the Nesseler-Ammonium precipitate based on the idea that the quantity of the precipitate would be proportional to the quantity of the reactant (Nitric Oxide) in the feed.

We could, thus, successfully confirm the reduction in the levels of Nitrous Oxides in the exhaust fumes of an actual diesel generator. The prototype can be optimized further for increasing the efficiency of the system.

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Agriculture, forestry and other land uses are the third-highest sources of anthropogenic GHG emissions (24% of total GHG emissions4, mainly through crop cultivation and tropical deforestation. Owing to high levels of deforestation, land use change, and improper land use practices, Brazil has been ranked as the fourth-highest emitter of GHGs in the world5.

Planted forests cover 7.8 million ha in Brazil6, and they are thought to play many positive roles in the context of climate change and deforestation through restoration of degraded land, soil conservation, CO2 sequestration, and protection of biodiversity. Their appropriate use in many industrial applications also reduce pressures on native forests7.

Of these Brazilian planted forests, 5.56 million ha are dedicated to Eucalyptus. Eucalyptus are fast-growing trees with high carbon sequestration potential during development8,9. Eucalyptus plantations have been reported to be a source of N2O and CO2 and a sink of CH4 in semi-arid and subtropical climates, as observed for most forest ecosystems10,11. However, GHG fluxes in Eucalyptus plantations have not yet been well described in the tropics, so a greater understanding of the impacts of Eucalyptus plantation management on these fluxes is still needed.

Soil behaves as both source and sink for GHGs12, as it represents the living space for the microbial communities responsible for nutrient cycling13. Accordingly, microbial activities in the N and C cycles are central to GHG fluxes in soil.

The link between soil microbial communities and GHG fluxes has previously been described14. Soil microbial processes are particularly impacted by land use practices, which can deregulate nutrient cycles and thereby increase or reduce GHG emissions15,16. Some studies have revealed a correlation between the abundance and/or expression of functional genes involved in N and C cycles and GHG fluxes in forest soils16,17,18. However, until now, no study has focused on the link between a microbial community and the GHG fluxes in the soil of Eucalyptus plantations.

To address this topic, we studied GHG fluxes and the microbial community associated with Eucalyptus plantations at two growth stages (i.e., one with new seedlings and one with 6-year-old trees), and with a native Brazilian tropical forest (Atlantic Forest). We hypothesized that: (1) replacement of native vegetation by Eucalyptus plantation or Eucalyptus plantation rotation would lead to changes in microbial community structure and functional gene abundance; and (2) changes in microbial community would alter GHG flux dynamics at each site.

The experimental field was originally covered by Atlantic Forest, a native tropical forest. Since 1960, CENIBRA has managed Eucalyptus plantations in this area and adopts regular rotation cycles of 7 to 9 years between planting seedlings and tree-cutting. Part of the area has been retained as native vegetation, in accordance with Brazilian law, which allowed us to compare adjacent areas covered by native forest or Eucalyptus plantation. Planted seedlings are clones of Eucalyptus urograndis produced by the company.

We chose an area under Eucalyptus plantation since 1978, immediately adjacent to a fragment of Atlantic Forest to perform this study. The most recent Eucalyptus rotation started in 2011, with trees in the 6th year growth in the beginning of 2017. To understand the short-term impact of a new rotation, we manually logged approximately half of this 6-year-old Eucalyptus plantation in February 2017 and replanted it immediately with new Eucalyptus seedlings. Sampling for our analyses was conducted at the end of March 2017.

Gas analyses were performed using a gas chromatograph (GC 2014, Shimadzu, Japan). For each sampling run, N2O and CH4 standards were used to build an analytical curve to transform the integrated areas of each sample peak into gas concentrations.

Finally, we clustered the sequences into operational taxonomic units (OTUs), with a 3% dissimilarity threshold. To avoid bias due to sampling effort, the samples were randomly normalized to the same number of sequences (35028). We employed a taxonomic summary to assess the bacterial composition of each sample.

Genes were chosen based on their involvement in the soil nitrogen and methane cycles. Primers were selected according to the literature and assessed with the Primer blast tool of the National Center of Biotechnology Information (NCBI) ( -blast/). We chose primers with the highest number of results and lacking non-specificity (Table 1).

The standards were constructed by amplifying each gene from DNA extracted from soil or activated sludge, ligating them into plasmids (CloneJET PCR Cloning Kit, Thermo Fisher Scientific, USA), and transforming them into E. coli DH5alpha plasmid (heat shock method, Froger and Hall, 2007). The plasmids were recovered using the PureYield Plasmid Miniprep system (Promega, USA). Based on the size of each gene, the weight of one nucleotide, and the plasmid concentration, we generated ten-fold serial dilutions in RNase- and DNase-free water for each plasmid to reach 1010 to 102 gene copies per reaction.

We assessed a total of 525,420 sequences (35,028 per sample) after applying quality filters and data normalization, clustered into 6,831 OTUs (3% dissimilarity threshold). Rarefaction curves show that our sequencing effort describes well the diversity of each sample (Supplemental Fig. 1). Bacterial richness (represented by numbers of OTUs) was significantly different among treatments, being highest in YE, followed by OE, and lastly NF (Table 4). Shannon diversity indices also differed significantly among treatments, being higher in YE and OE than in NF (Table 4). No significant difference was found between the two Eucalyptus plantations.

Taxonomic assignments revealed that all treatment areas were dominated by the same phyla, but with significant differences in the abundances of some phyla among treatments (Fig. 1A). Eight phyla were found in all treatments: Proteobacteria, Acidobacteria, Actinobacteria, Verrucomicrobia, Chloroflexi, Firmicutes and Bacteroidetes. The three most dominant phyla (Proteobacteria, Acidobacteria and Actinobacteria) represented at least 74% of the communities in each of the three treatments. We could classify approximately 88% of sequences into 16 different classes (Fig. 1B). Alphaproteobacteria were dominant in all treatments, representing 25 to 32% of the entire bacterial community.

Most significant differences in the relative abundances of bacterial taxa were observed between the native forest treatment (NF) and the two Eucalyptus plantations (YE and OE). However, there were also significant differences in the microbial community between the YE and OE treatments.

Our qPCRs were efficient in terms of quantifying functional gene copy numbers (Fig. 3). Dissociation curves indicated that the reactions were specific for all genes (data not shown), with R-squared values of the standard curves ranging from 0.98 to 0.99.

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