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18S rRNA Identification of Hydrobionts of Nizhniy Kaban Lake & Diversity Study through Next Generation Sequencing Method

The paper presents the results of a study of the species diversity of freshwater Nizhniy Kaban Lake (Kazan, Russia) by the gene 18S rRNA based on the next-generation sequencing method. Nizhniy Kaban, Verhniy Kaban, and Sredniy Kaban Lakes are included in the system of urban Kaban Lakes, which are polluted lakes according to ecological studies. Sequences of the 18S rRNA gene fragment of the freshwater Nizhniy Kaban Lake hydrobionts were submitted to the international SRA database on NCBI website in fastq format with numbers SRR7510988, SRR7516481, SRR7465568. A total of 39505 (2016) and 22619 (2017) high-quality reads were obtained; 89.4% (2016) and 83.8% (2017) of the hydrobionts was classified to the kingdom level, while 74.7% (2016) and 81% (2017) was classified to the phylum level, 48.2% (2016) and 79.5% (2017) was classified to the class level, 80% (2017) was classified to the family level, 79.6% (2017) was classified to the genus level, and 41.9% (2017) was classified to the species level. Analysis of the metagenomic data for Nizhniy Kaban Lake shows that indicator organisms identified by the 18S rRNA gene are grouped near the bmesosaprobity. Nizhniy Kaban Lake can be characterized as contaminated, in terms of water quality, transitional from bto a-mesosaprobity.


Introduction
At present time, the rapid development of metagenomics is associated with the proliferation of next-generation sequencing methods. Metagenomics can provide valuable information on the functional ecology of environmental communities [1]. We previously used metagenomic DNA sequencing to analyze species diversity by marker genes СО1 of animal organisms and rbcL of plants to assess the ecological state of freshwater Nizhniy Kaban Lake by bioindication [2,3]. In contrast to the marker genes СО1 and rbcL, the gene 18S rRNA is present in all eukaryotes. The ribosomal genes (rRNA) are one of the most conserved genes. Therefore, the systematic position of the organism and the time of discrepancy with similar species can be determined on the basis of the analysis of similarities and differences in rRNA sequences [4]. For eukaryotes, it is most convenient to analyze 18S rRNA of the three types of rRNA. The paper presents the results of a study of the species diversity of the freshwater Nizhniy Kaban Lake (Kazan, Russia) according to the gene 18S rRNA of freshwater organisms based on the next generation sequencing method. Nizhniy Kaban, Verhniy Kaban, and Sredniy Kaban Lakes are included in the system of urban Kaban Lakes, which are polluted lakes according to ecological studies.

Methods
Sampling from Nizhniy Kaban Lake (Kazan, Russia) was carried out in 2016-2017 in accordance with standard hydrobiological methods [5]. DNA was isolated from the precipitate obtained by centrifuging 50 ml of the sample at a speed of 10,000 g for 15 min using the FAST DNA Kit (MP biomedicals) according to the manufacturer's protocol. Amplification of the extracted DNA was carried out by Phusion High-Fidelity DNA polemerase (Thermo Fisher) using primers (Table 1).

Primers
Sequences

Results and Discussion
In 2016-2017 the next-generation sequencing method was used to identify hydrobionts by 18S rRNA gene from Nizhniy Kaban Lake. It is a lake about 2 km in length and 0.3 km in wide and has geographical coordinates of 55°46'35.6"N and 49°07'25.0" E ( Fig. 1). Nizhniy Kaban Lake is located in the center of an industrial city, thus experiencing anthropogenic pressure. According to ecological studies, Nizhniy Kaban Lake is a polluted lake. The percentage distribution of hydrobionts of Nizhniy Kaban Lake by reads for 2016 is shown in Fig. 2. The percentage distribution of hydrobionts of Nizhniy Kaban Lake by reads for 2017 is shown in Fig. 3. Each circle represents the kingdom, phylum, class, order, family, genus, and species from the inside to the outside of the circle, respectively, indicated by percent diversity.   The percentage of 18S rRNA hydrobionts of Nizhniy Kaban Lake by phylum The percentage of species diversity and reads of 18S rRNA hydrobionts of Nizhniy Kaban Lake by phylum (2016-2017) shown in Figure 6. As can be seen from Fig. 6, the most numerous at the phylum level for 2016 are Ciliophora (14.89%), Cercozoa (12.77%), Bigyra and Cryptophyta (6.38%), and Unclassified (46.81%) by species diversity; 2017 -Ochrophyta (15.94%), Chlorophyta (15.46%), Ciliophora (13.04%) and Unclassified (6.28%).  122 hydrobionts of Nizhniy Kaban Lake were identified by 18S rRNA gene. Among them, there are 14 hydrobionts with saprobities in Sladechek's list [9]. Table 2 shows the saprobionts of Nizhniy Kaban Lake.  Table 2 : Hydrobionts with Saprobities in Sladechek's List of Nizhniy Kaban Lake 5 Freshwater invertebrates. It lives along the plant-covered banks of stagnant and slow-flowing bodies of water, where it feeds on small fragments of plant material, animals or carrion. Cyclops has the capacity to survive unsuitable conditions by forming a cloak of slime [16]. 6 Keratella cochlearis is a rotifer [17]. The planktonic animal occurs worldwide in freshwater and marine habitats. 7 Tintinnidium fluviatile -unicellular eukaryotes. A review of the ecology of the fresh-water Tintinnina indicated that water temperature seems to be the most essential ecologic factor [18]. 8 Green eukaryotic microalgae, which has been present on earth since the Precambrian period [19]. 9 Botryococcus braunii is a green planktonic microalga. The species is notable for its ability to produce high amounts of hydrocarbons, that are typically around 30-40% of their dry weight [20,21]. 10 Choanoflagellata is a type of unicellular eukaryote. Sphaeroeca volvox is the type species of the genus Sphaeroeca of Choanoflagellata [22]. 11 A freshwater species of unicellular diatoms [23]. An important factor for the development of diatoms is temperature, the degree of illumination, and the quality of light [24]. 12 Dinobryon is a type of microscopic algae. Dinobryon is mixotrophs, capable of obtaining energy and carbon through photosynthesis and phagotrophy of bacteria. D. divergens blooms in lakes and ponds. Such blooms may produce volatile organic compounds that produce odors and affect water quality [25,26]. 13 Cyclotella is a centric diatom. Cyclotella occurs in stagnant waters. The nutrient content does not matter. They live both floating (plankton) and on the ground (benthos). C. meneghiniana was firstly described by Kützing [27]. 14 Chlamydomonas reinhardtii is a single-cell green algae. C. reinhardtii is a well-studied biological model of the organism, partly due to its ease of culturing and the ability to manipulate its genetics. When illuminated, C. reinhardtii can grow photoautotrophically, but it can also grow in the dark if supplied with organic carbon [23].  As can be seen from Fig. 8, most indicator organisms are grouped near b-mesosaprobity, which, in accordance with the classification of water quality, is characterized as polluted.

Summary
Based on the results of the study, the next-generation sequencing method was used to identify hydrobionts by 18S rRNA gene for Nizhniy Kaban Lake for 2016-2017. A total of 39505 (2016) and 22619 (2017) high-quality reads were obtained; 89.4% (2016) and 83.8% (2017) of the hydrobionts was classified to the kingdom, while 74.7% (2016) and 81% (2017) was classified to the phylum level, 48.2% (2016) and 79.5% (2017) was classified to the class level, 80% (2017) was classified to the family level, 79.6% (2017) was classified to the genus level, and 41.9% (2017) was classified to the species level. A total of 122 species were identified, among them there are 14 species with saprobity from Sladechek's list. Algae Cryptomonas curvata of b-mesosaprobity is the most numerous by reads. Cryptomonas are also photolithotrophs that contribute to oxygenic carbon fixation making them highly critical to the carbon levels of fresh water environments [11]. b-mesosaprobity indicates that the water is polluted.

Conclusions
Usage of the next-generation sequencing method allows the identification of a large number of hydrobionts. The method can be used for bioindication for assessing the ecological state of water reservoirs. This is great practical interest in the field of monitoring of water reservoirs.