Effects Of Human Settlement On The Environment

Effects Of Human Settlement On The Environment – Effects of human settlement on the abundance and structure of ammonia oxidizers in tropical stream sediments

Ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) are different and officially important groups in the nitrogen cycle. However, the AOA and AOB communities acting on this process remain in their typical tropical freshwater sediment. The effects of human settlement on AOA and AOB diversity and abundance were assessed by phylogenetic and quantitative PCR analyses, using archaeal and bacterial amoA and 16S rRNA genes. Overall, each environment contained distinct clades of amoA and 16S rRNA gene sequences, suggesting that selective pressures lead to AOA and AOB inhabiting distinct ecological domains. Human composting activities, such as increased nitrogen content of metals and minerals, seem to cause a response among the AOB community, with the use of Nitrosomonas over Nitrosospira in impacted environments. We also observed dominance of AOB over AOA in mining-impacted sediments, suggesting that AOB may be the primary drivers of ammonia oxidation in these sediments. Furthermore, ammonia concentrations have been shown to be drivers of AOA abundance, being inversely proportional between them. Our findings also revealed the presence of new ecotypes of Thaumarchaeota, such as those reported to be obligate acidophilic nitrosotale devanaterra in ammonia-rich environments at around neutral pH. These data add new information about AOA and AOB from tropical freshwater sediments, although future studies are required to provide further insights into the angle of difference between these microorganisms.

Effects Of Human Settlement On The Environment

Effects Of Human Settlement On The Environment

Nitrification, in which ammonia is converted to nitrite and then to nitrate, is a key process in the global nitrogen cycle that is essential to the functioning of many ecosystems. Aerobic ammonia oxidation, the first step in nitrification, converts reduced to oxidized inorganic nitrogen species (Gruber and Galloway, 2008). This process is mediated by autotrophic ammonia-oxidizing bacteria (AOB) (Purkhold et al., 2000), as well as autotrophic ammonia-oxidizing archaea (AOA) of the phylum Thaumarchaeotae (Wuchter et al., 2006).

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The environmental drivers that shape the structure of microbial communities provide a fundamental understanding of the maintenance of biodiversity and the role they play. The distribution or abundance of AOA and AOB is thought to be influenced mainly by pH (Nicol et al., 2004; Ipse et al., 2007; Daebeler et al., 2012), temperature (Tourna et al., 2008), ammonium availability (Martens-Habbena) et al., 2009; Lehtovirta-Morley et al., 2011; and metal concentrations (Stephen et al., 1999; Li et al., 2009; Mertens et al., 2009; Vasileiadis et al., 2012; Liu et al. ., 2014). Interestingly, many studies have revealed the dominance of AOA over AOB in many environments (Francis et al. 2005; Leininger et al., 2006; Wuchter et al., 2006; Zhang et al., 2008; ). But AOB in appears to be more abundant in metal-polluted environments than AOA (Ruyters et al., 2013; Liu et al., 2014).

Although efforts have been made to understand the community structure of AOB and AOA and their ecological functions, the effect of human settlement associated with tropical metals on the diversity, abundance and distribution of these communities is still unknown. In this, it is assumed that such human settlement, which is also associated with mineral nitrogen pollution, induces different responses on the abundance and composition of AOA and AOB communities. From such different responses it would be possible to detect some species or groups as potential bioindicators of metal pollution or water quality. For this hypothesis, we used the archaeal and bacterial amoA genes as a molecular marker together with Betaproteobacteria- and Thaumarchaeota-specific 16S rRNA gene targeting primers, to distribute AOA and AOB in the sediment of tropical streams with different metal concentrations due to historical contamination. from metal and foundry activities. In addition, a quantitative approach was used to detect the abundance of amoA genes in the prokaryotic community present in these freshwater sediment samples.

The Iron Quadrangle region (Minas Gerais, Brazil) is extremely rich in minerals and has been historically explored. A total of six sites were sampled: three sites in mining river sediments, i.e., located in the river Mina (MS, 19° 58′46.80″S and 43°49′17.07″W), in the river Tulipa (TS. , 19 °59′08.1″S, 43°28′15.2″), and in the Carrapatos river (CS, 19° 58′15.4S and 43°27′50.7″W); and the remaining sites from non-impact streams, i.e., two sites separated from each other by 50 m in the low stream (S1 and S2, 19°59′12.1″S and 43°29′27.5″W). and one site in the Mutuca river (MTS, 20°00′37.23″S and 43°58′8.92″W). The collection of sediment samples previously described by our group (Reis et al., 2014), except for the MTS, which is not subject to the influence of human settlement and belongs to the environmental protection of the state of Minas Geraes source of sanitation. company Only the names of the Mina river and the Mutuca river are formal names.

All stream water samples are analyzed for temperature, pH, and dissolved oxygen (DO). Total nitrogen (TN), total phosphorus (TP), nitrite (NO.)

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N) was measured according to Koroleff (1976). The results were presented in the previous study (Reis et al. 2014), except for MTS, which was characterized physicochemically in the present study (Tables 1 and 2). The total phosphorus concentration allowed the categorization of rivers as eutrophic (MS), mesotrophic (CS), oligotrophic (non-impact rivers S1, S2, MTS), and ultraoligotrophic (TS).

Table 2. Concentration of metals and metalloids in water and sediment samples (mg l-1 in water, mg kg-1 in sediment).

Total DNA was extracted from the sediment samples (10 g wet weight) using the PowerMax soil DNA kit (MoBio Laboratories, USA) according to the manufacturer’s instructions. DNA samples were stored at -20°C until processed. Table 3 gives details of all the primers and conditions used in this study. Model numbers of archaeal and bacterial amoA genes were quantified using the primary set Arch-amoAF and Arch-amoAR (Francis et al., 2005), and amoA-1F and amoA-2R (Rotthauwe et al., 1997; Stephen et al., 1999 ), respectively. Each reaction was performed in a 20 µL volume containing 10 ng of DNA, 1 µL of each 5 µM primers and 10 µL of SYBR green using the Rotor-Gene SYBR Green PCR Kit (Qiagen, Hilden, Germany), specifically for Rotor. -Gene Q2 complex HRM Platform (Qiagen, Hilden, Germany). In the qPCR assay, clones of Escherichia coli JM109 containing fragments of the archaeal and bacterial amoA gene were included as a standard, generating standard curves from seven dilutions. A control reaction without DNA template was included in each qPCR assay. All DNA samples and the negative control were analyzed in triplicate to obtain an accurate value for the abundance of the amoA gene in each sample. Aliquots of the qPCR products were run on an agarose gel to identify non-specific PCR products such as first dimers or fragments with unexpected lengths (data not shown). Amplification rates from AOB and AOA amoA gene were 90 and 109%, respectively, with r

Effects Of Human Settlement On The Environment

In an attempt to assess the diversity and distribution of ammonia oxidizers, denaturing gradient gel electrophoresis (DGGE) of the AOA 16S rRNA gene was performed by nested PCR with the archaeal primer set 21F and 958R followed by the thaumarchaeotal primer set Parch519F and Arch915R-GC. described by Vissers et al. (2009). To detect the presence of archaeal amoA genes in the community, the first Arch-amoAF and Arch-amoAR were described by Wuchter et al. (2006) and Vissers et al. (2012) (Table 3).

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For PCR-DGGE from the AOB 16S rRNA gene, a nested PCR was performed using the bacterial primer βAMOf and βAMOr, which are selective but not completely specific for betaproteobacterial ammonia oxidizers, followed by a second PCR using the betaproteobacterial primer CTO189f-GC. and CTO654r, described by Laanbroek and Speksnijder (2008). To detect the bacterial amoA gene, we used the primer set amoA-1F (Nicolaisen and Ramsing, 2002) and amoA-2R (Rotthauwe et al., 1997). The GC primer described by Muyzer and Smalla (1998) was inserted into the 5′ end of the primers as indicated in Table 3.

The final PCR products were separated by DGGE on a 7% polyacrylamide gel with a vertical gradient of 35–60% formamide and denaturing urea. The running conditions were 100 V at a constant temperature of 60°C for 18 h.

The phylogenetic assignment of sequences of ammonia-oxidizing prokaryotes was determined by prominent bands excised from DGGE gels by eluting in 20 μl of sterile Milli-Q water at room temperature for 2 h. After this, the amplicons were processed under the conditions described above and submitted to Macrogen Inc., Amsterdam. To identify the closest relatives the obtained sequences were compared to the available database using the BLASTn search tool from GenBank

Phylogenetic relationships of the 16S rRNA gene were inferred with the nearest-joining algorithm (Saitou and Nei, 1987) with the Jukes-Cantor correction (Jukes and Cantor, 1969), using the ARB (version 6.0.1) software package and SSU-Ref. -115 database (Ludwig et al., 2004; Pruesse et al., 2007).

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For the amoA gene, the retrieved nucleotide sequences for the amoA gene sequences are available in GenBank.

Database Evolutionary history was estimated using the nearest-neighbor algorithm (Saitou and Nei, 1987) with Jukes-Cantor correction.

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