Journal of Environmental Treatment Techniques  
2019, Special Issue on Environment, Management and Economy, Pages: 1016-1025  
J. Environ. Treat. Tech.  
ISSN: 2309-1185  
Journal web link: http://www.jett.dormaj.com  
The Monitoring of Sredniy Kaban Lake by 16s  
Rrna Gene Amplicon Data Set-Based Bacterial  
Diversity  
Anthony Elias Sverdrup, Ludmila L. Frolova*, Stella Sagdeeva  
Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia  
Received: 05/08/2019  
Accepted: 20/11/2019  
Published: 20/12/2019  
Abstract  
The paper presents the results of research of bacterial diversity of Sredniy Kaban Lake (Kazan, Russia) for 2016-2017, using  
the marker gene 16S rRNA of aquatic organisms, based on the method of next-generation sequencing. Sredniy Kaban, Verhniy  
Kaban and Nizhniy Kaban are included in the system of Kaban Lakes. They are located in the center of a large industrial city,  
and are exposed to anthropogenic load. According to ecological studies, Kaban Lakes are polluted. The sequences of 16S rRNA  
Bacteria gene fragment of the freshwater lake Sredniy Kaban were submitted to the international database in fastq format on the  
website NCBI with the numbers SRR7510929 (2016) and SRR7516240 (2017). The comparative analysis of metagenomic data  
showed a significant change in bacterial diversity over the years. A total of 98822 (2016) and 26046 (2017) high-quality reads  
were obtained; 67% (2016) and 54% (2017) of the bacterial population were classified to the genus level, while 3% (2017) was  
classified to the species level. In total, 15 species of Bacteria were identified. Among them, the dangerous bacteria  
Acinetobacter, occurring universally, were found the most often. This type of bacteria can pose a threat to human health.  
Therefore, the species composition of Bacteria community should be taken into account when assessing the ecological state of  
water reservoirs.  
Keywords: Gene 16S rRNA, next-generation sequencing, Freshwater lake, Bacteria  
1
functional ecology of environmental communities (5). We  
1
Introduction  
previously used metagenomic DNA sequencing for the  
identification of zooplankton by СО1 gene, in order to  
assess the ecological state of the freshwater lake Sredniy  
Kaban by the method of bioindication (6).  
The work presents the results of research of bacterial  
diversity of Sredniy Kaban Lake (Kazan, Russia) for 2016-  
Poor water quality is an important problem of public  
health and environment. The presence of pathogens in  
water can adversely affect human and animal health.  
Contaminated water is connected with the transmission of  
such diseases as cholera, diarrhea, dysentery, hepatitis A,  
typhoid fever and poliomyelitis (1). To assess the diversity  
of microorganisms in various environments, for example, in  
human intestine, bottom sediments of Lake Baikal or in the  
hot springs of Kamchatka, the methods of next-generation  
sequencing are used (2). High-performance sequencing  
technology can significantly accelerate and reduce the cost  
of determining the genome sequences of millions of  
organisms (3).  
2017, using the marker gene 16S rRNA of aquatic  
organisms, based on the method of next-generation  
sequencing. Sredniy Kaban, Verhniy Kaban and Nizhniy  
Kaban are included in the system of Kaban Lakes. They are  
located in the center of a large industrial city, and are  
exposed to anthropogenic load. According to ecological  
studies, Kaban Lakes are polluted.  
Sequencing of 16S rRNA gene is a universal and  
effective approach for taxonomic characterization, as this  
gene is present in genomes of all prokaryotes, and has  
relatively low variability (4).  
2 Methods  
The sampling from Sredniy Kaban Lake (Kazan,  
Russia) was carried out during 2016-2017, in accordance  
with the standard hydrobiological methods (7).  
Metagenomics can provide valuable information on the  
Isolation of DNA from the precipitate obtained by  
centrifugation of 50 ml of the sample at a rate of 10,000 g  
for 15 min was carried out using the FAST DNA Kit (MP  
biomedicals) according to the manufacturer's protocol.  
Amplification of the isolated DNA was performed by  
Corresponding author: Ludmila L. Frolova, Institute of  
Fundamental Medicine and Biology, Kazan Federal  
University,  
Kazan,  
Russia.  
E-mail:  
Lucie.Frolova@gmail.com.  
1016  
Journal of Environmental Treatment Techniques  
2019, Special Issue on Environment, Management and Economy, Pages: 1016-1025  
Phusion High-Fidelity DNA polymerase (Thermo Fisher)  
using the Eurogen primers (http://evrogen.ru) (Table 1).  
obtained nucleotide sequences of 16SrRNA Bacteria gene  
were aligned, using the software BLAST+, in order to  
establish the taxonomic composition.  
Table 1 Primers for PCR of 16S rRNA gene  
The software Krona chart (9) and GraphPad (10) were  
used to build charts.  
Primers  
Sequences  
5
'-  
3
Results and Discussion  
tcgtcggcagcgtcagatgtgtataagagacagcctacgggng  
gcwgcag-3'  
16SF_I  
In 2016-2017, the next-generation sequencing method  
(
forward)  
was applied with the aim to identify Bacteria from Sredniy  
Kaban Lake.  
5
'-  
1
6SR_I  
gtctcgtgggctcggagatgtgtataagagacaggactachvg  
ggtatctaatcc-3'  
(
reverse)  
3.1 Krona chart of the bacteria represented by 16S  
rRNA gene amplicon-based bacterial diversity  
The percentage distribution of Bacteria of Sredniy  
Kaban Lake by species and reads for 2016 is shown in Fig.  
-2. The percentage distribution of Bacteria of Sredniy  
Kaban Lake by species and reads for 2017 is shown in Fig.  
-4.  
After this, the second PCR cycle was performed in  
order to index the samples (Nextera XT indices).  
Purification of PCR products was performed using  
Agencourt AMPure XP beads (Beckman Coulter).  
The obtained DNA libraries were sequenced on the  
device Illumina MiSeq (MiSeq Reagent kit v3).  
Metagenomic data were entered into the international SRA  
database on the website NCBI with numbers: SRR7510929  
and SRR7516240 (8).  
1
3
Each circle represents the phylum, class, order,  
family, genus, and species from the inside to the outside of  
the circle, respectively, indicated by the percent diversity,  
based on the absolute number of representative bacteria.  
After filtering the reads by quality, trimming of  
sequences and removing of chimeric sequences, the  
Figure 1: The percentage of 16S rRNA Bacteria species of Sredniy Kaban Lake (2016)  
1017  
Journal of Environmental Treatment Techniques  
2019, Special Issue on Environment, Management and Economy, Pages: 1016-1025  
Figure 2: The percentage of 16S rRNA Bacteria reads of Sredniy Kaban Lake (2016)  
Figure 3: The percentage of 16S rRNA Bacteria species of Sredniy Kaban Lake (2017)  
1018  
Journal of Environmental Treatment Techniques  
2019, Special Issue on Environment, Management and Economy, Pages: 1016-1025  
Figure 4: The percentage of 16S rRNA Bacteria reads of Sredniy Kaban Lake (2017)  
The percentage of 16S rRNA Bacteria of Sredniy  
Kaban Lake by phylum. The percentage of species diversity  
of 16S rRNA Bacteria of Sredniy Kaban Lake by phylum  
(
5
/
2016-2017) is shown in Figure 5. As can be seen from Fig.  
, Proteobacteria (59.7%/50.43%), Actinobacteria (5.97%  
13.48%) and Bacteroidetes (10.45%/10%) are the most  
numerous by species diversity at the level of phylum,  
respectively by years.  
Figure 6: The percentage of 16S rRNA Bacteria reads of Sredniy  
Kaban Lake by phylum (2016-2017)  
3.2 The percentage of 16S rRNA Bacteria of Sredniy  
Kaban Lake by class  
The percentage of species diversity of 16S rRNA  
Bacteria of Sredniy Kaban Lake by class (2016-2017) is  
shown in Fig. 7, parts 1-2. As can be seen from Fig. 7,  
Alphaproteobacteria (19.4%/18.7%), Betaproteobacteria  
(
(
25.37%/13.48%)  
11.94%/12.17%) are the most numerous by species.  
The percentage of 16S rRNA Bacteria reads of Sredniy  
and  
Gammaproteobacteria  
Figure 5: The percentage of species diversity of 16S rRNA  
Bacteria of Sredniy Kaban Lake by phylum (2016-2017)  
Kaban Lake by class (2016-2017) is shown in Fig. 8, parts  
-2. As can be seen from Fig. 8, Oscillatoriophycideae  
42.42%/44.41%), Actinobacteria (21.91%/10.2%),  
Acidimicrobiia (15.51%, 2016), Gammaproteobacteria  
15.33%, 2017) are the most numerous by species.  
The percentage of 16S rRNA Bacteria reads of Sredniy  
Kaban Lake by phylum (2016-2017) is shown in Figure 6.  
As can be seen from Fig. 6, Cyanobacteria  
1
(
(
42.59%/45.53%), Actinobacteria (37.41%/12.37%) and  
(
Proteobacteria (10.67%/35.12%) are the most numerous by  
reads.  
1019  
Journal of Environmental Treatment Techniques  
2019, Special Issue on Environment, Management and Economy, Pages: 1016-1025  
(
2
(
5.97%/21.91%), Burkholderiales (22.39%/5.88%); in  
017: Oscillatoriales (0.43%/44.39%), Enterobacteriales  
1.74%/10.3%), Burkholderiales (8.7%/8.29%),  
Actinomycetales (10%/10.20%).  
Figure 7: part 1. The percentage of species diversity of 16S rRNA  
Bacteria of Sredniy Kaban Lake by class (2016-2017)  
Figure 8: part 2. The percentage of 16S rRNA Bacteria reads of  
Sredniy Kaban Lake by class (2016-2017)  
Figure 7: part 2. The percentage of species diversity of 16S rRNA  
Bacteria of Sredniy Kaban Lake by class (2016-2017)  
Figure 10: The percentage of species diversity and reads of 16S  
rRNA Bacteria of Sredniy Kaban Lake by order (2016): (1 –  
Oscillatoriales (1.49%/42.42%), 2 – Frankiales (5.97%/21.91%), 3  
–
Burkholderiales (22.39%/5.88%))  
Figure 8: part 1. The percentage of 16S rRNA Bacteria reads of  
Sredniy Kaban Lake by class (2016-2017)  
3
.3 The percentage of 16S rRNA Bacteria of Sredniy  
Figure 11: The percentage of species diversity and reads of 16S  
rRNA Bacteria of Sredniy Kaban Lake by order (2017): (1 –  
Kaban Lake by order  
The percentage of species diversity and reads of 16S  
rRNA Bacteria of Sredniy Kaban Lake by order (2016-  
017) is shown in Fig. 9-11. As can be seen from Fig. 9-11,  
Oscillatoriales  
(1.74%/10.3%1),  
Actinomycetales (10.00%/10.20%))  
(0.43%/44.39%), Enterobacteriales  
2
–
3
–
Burkholderiales (8.70%/8.29%),  
4 –  
2
the following orders were of the greatest importance in  
terms of species diversity and/or reads, in 2016:  
Oscillatoriales  
(1.49%/42.42%),  
Frankiales  
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2019, Special Issue on Environment, Management and Economy, Pages: 1016-1025  
Figure 9: The percentage of species diversity and reads of 16S rRNA Bacteria of Sredniy Kaban Lake by order (2016-2017)  
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2019, Special Issue on Environment, Management and Economy, Pages: 1016-1025  
Table 2: Summary of bacteria identified to the species level from 16S rRNA gene-based metagenomic study of freshwater from  
Sredniy Kaban Lake (2017)  
Phylum  
Class  
Order  
Family  
Species  
%
Edaphobacter  
modestum  
Acidobacteria  
Acidobacteriia  
Acidobacteriales  
Acidobacteriaceae  
0.0064  
1
Agromyces mediolanus2 0.0593  
Candidatus Aquiluna  
Microbacteriaceae  
0
.0572  
3
rubra  
Actinobacteria  
Actinobacteria  
Actinomycetales  
Micrococcaceae  
Micrococcus luteus4  
0.0032  
0.0244  
Propionibacterium  
Propionibacteriaceae  
5
acnes  
Flavobacterium  
succinicans  
Bacteroidetes  
Firmicutes  
Flavobacteriia  
Bacilli  
Flavobacteriales  
Bacillales  
Flavobacteriaceae  
Staphylococcaceae  
0.0064  
0.0074  
6
Staphylococcus  
7
epidermidis  
Faecalibacterium  
Clostridia  
Clostridiales  
Ruminococcaceae  
Caulobacteraceae  
0.0053  
0.0530  
8
prausnitzii  
Brevundimonas  
Caulobacterales  
Alpha-  
Proteobacteria  
9
diminuta  
Rickettsiales  
Rickettsiaceae  
Orientia tsutsugamushi10 0.0053  
Burkholderiales  
Comamonadaceae  
Variovorax paradoxus11  
Chitinilyticum  
0.0095  
0.0074  
Beta-  
proteobacteria  
Proteobacteria  
Neisseriales  
Neisseriaceae  
12  
litopenaei  
Gamma-  
proteobacteria  
Epsilon-  
proteobacteria  
Acinetobacter  
Pseudomonadales  
Campylobacterales  
Verrucomicrobiales  
Moraxellaceae  
3.0645  
13  
rhizosphaerae  
Helicobacteraceae  
Sulfuricurvum kujiense14 0.0117  
Prosthecobacter  
0.0222  
Verrucomicrobia  
Verrucomicrobiae  
Verrucomicrobiaceae  
15  
debontii  
1
2
3
4
It is a type species of the genus Edaphobacter; it was initially isolated from alpine soil, rich in calcium carbonate (11).  
Aniline-assimilating bacteria. They occur in the soil; there are cases of human infection (12).  
It can be found in fresh and salt water (13).  
It is an obligate aerobe, widely distributed in the environment. It can be found in soils, dust, water and air. It is also a part of the normal  
microflora of the skin surface of humans and mammals (14).  
It occurs on the skin and in the gastrointestinal tract of humans and animals. It can cause the skin diseases in humans.  
Phosphite-assimilating bacteria. They were isolated from the intestines of zooplankton Daphnia magna (14).  
It is a gram-positive bacteria, one of more than 40 species of the genus Staphylococcus (15). It is a part of the normal microflora of human skin,  
and mucous membranes (less often) (16).  
5
6
7
8
9
1
1
It is one of the most common and important commensal bacteria of human intestinal microbiota (17).  
It was isolated from clinical samples of patients with mucoviscidosis. It is used as a potential bioremediator of marine oil pollution (18).  
0
O.tsutsugamushi is a mite-borne bacterium, which causes the life-threatening human disease scrub typhus (19).  
It can be found everywhere. It is abundantly present in environments, which are contaminated with organic compounds or heavy metals  
1
(
20,26,30-32).  
1
1
2
It was isolated from surface water of an aquaculture pond, containing Pacific white shrimp. It is susceptible to ampicilin, chloramphenicol,  
kanamycin, nalidixic, acid, novobiocin, rifampicin and tetracycline; resistant to erythromycin, gentamicin, penicillin G and streptomycin  
(21,33,34).  
3
Gram-negative bacteria, chemorganotrophs with oxidative metabolism. They are saprophytes, and universal in occurrence. They may be the  
cause of many infectious processes, including meningitis, septic disease in humans, and septicemia, abortion in animals. In February 2017,  
WHO ranked acinetobacteria among the most dangerous bacteria, due to their resistance to existing antibacterial drugs (22,25).  
It is a facultative anaerobe, chemolithoautotrophic sulfur-oxidizing bacterium, typical representative of the genus. The cells have the shape of  
curved rods, they are mobile, and have a single polar flagellum (23, 28).  
1
1
4
5
It was isolated from fresh water (24, 27, 29).  
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2019, Special Issue on Environment, Management and Economy, Pages: 1016-1025  
3.4 The percentage of 16s rrna bacteria of sredniy  
(0,31%/0,63%), Variovorax (0,03%/0,01%), Zymomonas  
kaban lake by family  
(0,13%/0,02%).  
The total number of identified Bacteria by family is  
3
7/94 families, respectively for 2016/2017. The families by  
3.6 The Percentage of 16s Rrna Bacteria of Sredniy  
Kaban Lake by Species  
The species diversity of Bacteria in 2017 was 3.29% of  
the total number of organisms by reads. Table 2 shows the  
classification of bacterial organisms in Sredniy Kaban  
Lake.  
species are presented in Fig. 12 a), b). The families by  
reads are shown in Fig. 12 c), d); among them 10% (2016),  
and 17% (2017) are not classified. The following families  
are the most represented: Microcoleaceae – 38% (2016),  
42.5% (2017), Sporichthyaceae 20.5% (2016),  
–
Acidimicrobiaceae – 14% (2016); Enterobacteriaceae –  
9.8% (2017), Pelagibacteriaceae – 5.7% (2017).  
Figure 13: The percentage of 16S rRNA Bacteria of Sredniy Kaban  
Lake by genus (2016-2017)  
Figure 12: The percentage of species diversity and reads of 16S  
rRNA Bacteria of Sredniy Kaban Lake by family (2016-2017)  
3
.5 The percentage of 16S rRNA Bacteria of Sredniy  
Figure 14: The percentage of species diversity by reads of 16S  
rRNA Bacteria of Sredniy Kaban Lake (2017)  
Kaban Lake by genus  
The percentage of 16S rRNA Bacteria of Sredniy  
Kaban Lake by genus (2016-2017) is shown in Fig. 13. As  
can be seen from Fig. 13, at the level of genus, 12.4% of  
groups were unique for the bacterial community in 2016;  
4 Summary  
According to the results of the study, using the modern  
method of next-generation sequencing, the bacterial profile  
of Sredniy Kaban Lake for 2016-2017 was characterized.  
The comparative analysis of metagenomic data showed a  
significant change in bacterial diversity over the years.  
A total of 98822 (2016) and 26046 (2017) high-quality  
reads were obtained; 97% (2016) and 99% (2017) of the  
bacterial population were classified to the phylum, while  
96% (2016) and 98% (2017) were classified to the class  
level, 94% (2016) and 97% (2017) were classified to the  
order level, 90% (2016) and 83% (2017) were classified to  
the family level, 67% (2016) and 54% (2017) were  
classified to the genus level, and 3% (2017) was classified  
19.4% of groups were common for 2016-2017, and 68.2%  
were unique for the bacterial community in 2017. Common  
genera for 2016-2017 were the following: Dechloromonas  
(
0.13%/0,1%),  
Flavobacterium  
(0.13%/0.64%),  
Hyphomicrobium  
(0.06%/0.02%),  
Legionella  
(
(
(
0.66%/0.19%), Limnobacter (0.38%/0.15), Limnohabitans  
0.63%/0.02%), Mycobacterium (0.18%/0.04%), Opitutus  
0.03%/0.08%),  
Phenylobacterium  
(0,03%/0,01%),  
(0,03%/0,02%),  
Planktothrix  
Planctomyces  
38,34%/42,40%),  
Rickettsia  
(
Polynucleobacter  
(0,72%/0,01%),  
(1,10%/0,06%),  
Sediminibacterium  
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Journal of Environmental Treatment Techniques  
2019, Special Issue on Environment, Management and Economy, Pages: 1016-1025  
to the species level. In total, 15 species of Bacteria were  
identified. Among them, the dangerous bacteria  
Acinetobacter, occurring universally, were found the most  
often. This type of bacteria can pose a threat to human  
health. Thus, according to bacterial diversity, Sredniy  
Kaban Lake is estimated as contaminated. The percentage  
of species diversity by reads of 16S rRNA Bacteria of  
Sredniy Kaban Lake for 2017 is shown in Fig. 14.  
evolutionary microbiology. 2009 Jan;59(0 1):112.  
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1
4. Poehlein A, Najdenski H, Simeonova DD. Draft Genome  
Sequence of Flavobacterium succinicans Strain DD5b.  
Genome Announc.. 2017 Jan 12;5(2):e01492-16.  
5. Schleifer KH, Kloos WE. Isolation and characterization of  
Staphylococci from human skin I. Amended descriptions of  
Staphylococcus  
epidermidis  
and  
Staphylococcus  
saprophyticus and descriptions of three new species:  
Staphylococcus cohnii, Staphylococcus haemolyticus, and  
Staphylococcus xylosus. International Journal of Systematic  
and Evolutionary Microbiology. 1975 Jan 1;25(1):50-61.  
6. Fey PD, Olson ME. Current concepts in biofilm formation of  
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5
Conclusions  
The results obtained are of great practical interest in the  
1
field of monitoring of water reservoirs. The method of  
next-generation sequencing can be successfully used for the  
control of water reservoirs, in particular, and for the  
assessment of ecological state of water reservoirs, in  
general.  
1
7.  
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1
8. Ryan MP, Pembroke JT. Brevundimonas spp: emerging global  
opportunistic pathogens. Virulence. 2018 Dec 31;9(1):480-93.  
9. Seong SY, Choi MS, Kim IS. Orientia tsutsugamushi infection:  
overview and immune responses. Microbes and Infection.  
2001 Jan 1;3(1):11-21.  
0. Satola B, Wübbeler JH, Steinbüchel A. Metabolic  
characteristics of the species Variovorax paradoxus. Applied  
microbiology and biotechnology. 2013 Jan 1;97(2):541-60.  
Acknowledgements  
The work is performed according to the Russian  
Government Program of Competitive Growth of Kazan  
Federal University. The authors would like to thank Dr.  
S.Malanin and E.Boulygina, the scientists of Kazan Federal  
University, for their assistance in experimental work.  
2
2
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Abis  
Encyclopedia  
–
http://www.tgw1916.net/Chromobacteriaceae/chitinilyticum_li  
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which-new-antibiotics-are-urgently-needed  
23. Kodama Y, Watanabe K. Sulfuricurvum kujiense gen. nov., sp.  
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oxidizing bacterium isolated from an underground crude-oil  
storage cavity. International journal of systematic and  
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