Abstract

East Kolkata Wetlands (EKW) is designated as International Ramsar site and are the hotspot for large-scale wastewater aquaculture practices. However, the continued surveillance of physicochemical properties of water and application of an eco-friendly approach are essential to ensure safe aquaculture practices. In the present study, we assessed the seasonal variation in physicochemical parameters of water across EKW and investigated the role of nitrifying bacteria as probiotics. We statistically analyzed various physicochemical properties of water samples from EKW. Results of the statistical analysis indicated a significant variation in all the physicochemical parameters across the selected water bodies of EKW (p < 0.01). We isolated and enumerated Nitrosomonas sp. and Nitrobacter sp. and assessed their ability to degrade trichloroethylene (TCE). The role of Nitrosomonas sp. and Nitrobacter sp. were further investigated and established through a small-scale experiment. Two microbial isolates, NSW3 and NBW2, displayed superior TCE degradation ability at pH 5, and the application of these strains as probiotics were found to improve the quality of water and survival rate of fishes in the treated experimental tanks. Our findings suggest that the application of the above mixed bacterial cultures in aquaculture could be an effective and environment-friendly approach for safe and productive aquaculture operations.

HIGHLIGHTS

  • East Kolkata Wetlands, an International Ramsar site and hotspot for aquaculture.

  • Statistical correlations of physicochemical parameters shown significant variation.

  • Standardized the role of nitrifying bacteria as probotics for aquaculture practices.

  • Trichloroethylene degradation by bacteria were analysed for reducing pollutants.

  • Establishment of bioremediation and bio-security protocol of wastewater management.

INTRODUCTION

Fish is considered as one of the best protein source not only in India, but all over the world (Thilsted et al. 2016). To achieve the demands, aquaculture industry has flourished a lot with high rate of fish production. Huge production of fish is related with intense culture methods like high rearing and stocking densities and excessive application of protein supplement as feed (Lieke et al. 2019). These approaches are responsible for water quality deterioration and proliferation of pathogenic microbes (Hura et al. 2018). Although water quality is an important parameter for the operation of the aquaculture sector, the sector itself has become a major source of pollution in several water bodies and wetlands mainly because of extensive use of protein supplemented feed, chemicals, and antibiotics for enhancing water quality and fish survival. Moreover, excessive human interference leading to vulnerability of several wetlands necessitates the execution of appropriate steps toward conserving wetlands as well as many endangered and threatened species (Boyd et al. 2020). To avoid the adverse effects of chemicals and antibiotics, the use of microorganisms as bioremediators is considered an eco-friendly approach, and studies have reported that this approach effectively improves the growth, immune responses, and survival of species grown in aquaculture (Padmavathi et al. 2012). Use of probiotics have been associated with the selective growth of beneficial microbes and decline in the population of pathogenic microbes (Padmavathi et al. 2012; Sunitha & Krishna 2016). Various attempts are taken towards the use of probiotics for the enhancement of water quality in aquaculture (Hura et al. 2018). Benefits of probiotics are associated with healthy growth of fish by inhibiting the growth of pathogenic microbes in water, utilization or conversion of toxic elements in the water by their enzymes, and enhancement of fish immuno-system to resistant pathogens (Hoseinifar et al. 2018; Van Doan et al. 2019). Role of Nitrosomonas sp. and Nitrobacter sp. as probiotics were found to be significant in maintaining the water quality properties and in reducing the load of pathogenic bacteria (Sunitha & Krishna 2016). Nitrifying microbial community has the ability for better fish production by promoting water parameters (Roalkvam et al. 2020; Xu et al. 2020). Therefore, the application of probiotics could effectively decrease the contaminant levels in water bodies, reducing the load of pathogenic microbes and enhance survival of aquatic animals.

West Bengal, India is famous for pisciculture. Indian Major Carps (IMC) (Catla (Catla catla), Rohu (Labeo rohita) and Mrigal (Cirrhinus mrigala)) are considered some of the best protein sources in West Bengal and India (Bais 2018). Sewage fed fisheries and floodplain wetlands are important fishery resources in West Bengal. East Kolkata Wetland (EKW), designated as an ‘International Ramsar Site’ in November 2002 by Ramsar Convention (1975) (Heinen, 1999; Kumar 2018), and a unique agroecosystem located at the eastern outskirt of Kolkata and comprises a series of natural and manmade wetlands (Saha et al. 2013; Singha Roy & Pal 2015; Pal et al. 2016). Because of a widely known attribute of EKW in the recycling of wastewater in the metropolitan city Kolkata, it has been named as the ‘kidney of the city’ (Vicziany et al. 2017). EKW was selected for the study because it is the ‘World's Largest Integrated Wastewater Fisheries’. This is the best example of efficient use of valuable resources and providing employment for 17,000 families. About 286 bheries (a local term of fishery pond) plays a major role in purifying the sewage of Kolkata (Kumar 2018). Wastewater in EKW is extensively used in both agriculture and aquaculture for a few decades (Pal et al. 2016). According to the recent reports by East Kolkata Wetland Management Authority (EKWMA) and Wetland International South Asia (WISA) 2021, around 260 fish ponds receive approximately 900 million litres per day (MLD) sewage via different canals. 20,000 metric tons (MT) of fish and 50,000 MT of vegetables are produced annually along with huge rice farming (EKWMA & WISA 2021). The produced fish, vegetables and rice in EKW is consumed by the large population in and around Kolkata. EKW is also a land of diverse species constituting of 380 taxa under major flora (EKWMA & WISA 2021). Therefore, EKW is ecologically and economically important. Loss of this wetland will not only hamper the livelihood of the people associated here but diverse species of organisms will lose their shelter. Domestic and industrial wastes from different parts of the city enters into the EKW via canals. While passing through these different canals, the waste gets diluted and finally enter the fish ponds in different proportion. Detoxification of pollutant in EKW involves various self-purification techniques and thus it is one of the best agro-economic areas of Kolkata. Consequently, measurement of some physicochemical quality of water is important. Multi-disciplinary approach in aquaculture and scientific attention to the water quality parameters is the best way to restore this wetland. Seasonal variation is an important factor in this tropical region as temperature and rainfall varies a lot during pre-monsoon and post-monsoon. The important physicochemical parameters of water such as temperature, pH, dissolved oxygen (DO), total dissolved solids (TDS), biological oxygen demand (BOD), chemical oxygen demand (COD), nitrate-nitrogen (NO3-N), ammonia-nitrogen (NH3-N) and phosphate-phosphorous need to be assessed properly in different seasons for fish-health management. EKW not only serves as a rich source of nutrients but also harbours efficient and commercially important bacteria, such as nitrifying bacteria and heavy metal utilizing bacteria and microbes, that act as bioremediators by assimilating nitrogen and producing extracellular enzymes (Ghosh et al. 2007; Saha et al. 2013, 2014; Sahaya Sukeetha et al. 2019).

Apart from physicochemical properties and analysis of water samples, another prime focus of our present research is to identify the role of nitrifying bacteria (Nitrosomonas sp. and Nitrobacter sp.). Gene amoA codes for the active site of ammonia monooxygenase (Yu & Chandran 2010; Pjevac et al. 2017), and it has been extensively used for the detection of ammonia oxidizers. Nitrite oxidoreductase (nxr) is the key enzyme responsible for the oxidation of NO2 to NO3 by nitrite-oxidizing bacteria (Koch et al. 2015; Hemp et al. 2016). Application of probiotic for bioremediation of water quality and enhancement of fish production tool can be the most effective strategy (Jahangiri & Esteban 2018; Hasan & Banerjee 2020). Nitrifying bacteria generally carry out the nitrogen cycling process and few strains also help in co-metabolic bioremediation of trichloroethylene (TCE) and other halogenated compounds (Berrelleza-Valdez et al. 2019). Thus, they play a vital role in water quality control. TCE is an environmental pollutant and hazardous for human health (Dumas et al. 2018; Zhang et al. 2018). The presence of TCE in sewage-fed fisheries is considered extremely dangerous to the environment and human health. However, some microorganisms can survive in extreme environmental conditions and few microbes can co-metabolize contaminants and other intermediate products. Studies have reported that some microbes are capable of degrading TCE (Siggins et al. 2021). Many studies on the use of microbial consortia for co-metabolic degradation of TCE have been conducted. Reports also suggest that nitrifying bacteria, particularly Nitrosomonas europaea, play a major role in detoxifying the industrial and sewage waste and in the degradation of TCE and other halogenated hydrocarbons (Suttinun et al. 2013; Baskaran & Rajamanickam 2019).

Wetland conservation is the need of the hour to accommodate various environmental and other pressures. Continuous monitoring of the water quality parameters and maintaining all information are the best management policy for EKW. Considering the significance of water quality in determining the feasibility and success of the aquaculture practice and growth of cultured animals, we aimed to determine the physical and chemical parameters of water of bheries located in EKW in the present study. The main objective of our study was to predict the quality of water and facilitate the utilization of wastewater in aquaculture in a hygienic manner. We emphasized mainly on the bheries located in EKW because the region harbors enormous bacterial species involved in bioremediation; based on our knowledge of microbial diversity in EKW, we hypothesized that the concentration of ammonia and nitrate in outlet fisheries in the region is within the safe tolerable range due to the presence of nitrifying and other commercially important bacteria. Moreover, the investigation on the effect of microbial community in EKW on the ecological, environmental, and societal aspects has been scant. Therefore, we also assessed the role of nitrifying bacteria isolated from EKW in TCE degradation to gain in-depth understanding of the advantages of utilizing these microbes in bioremediation and as probiotics to enhance the overall fish health and survival.

MATERIALS AND METHODS

Sampling sites

Nalban Fisheries (owned by the Government of West Bengal and runed by State Fisheries Development Co-operation) and Jhagrasisa bhery (owned by a private organization) in EKW, were selected for the present study. The EKW (22024/ - 22036/ N to 88023/ - 88032/ E) is a series of wetlands and lie in the eastern fringe of the metropolitan city of West Bengal, India. Sampling sites of EKW included the following: Topsia (sewage pumping station); Ambedkar Bridge, Bantala, Bamunghata, Ghosher Khal and Ghusighata (outlet); these sites were selected for sampling in order to assess the sewage purification capacity (from inlet to outlet) of EKW considering its crucial role in waste recycling. In addition, three sites from each fish ponds, namely Nalban (N1, N2, N3) and Jhagrasisa (J1, J2, J3), were selected because they represent the major fish rearing ponds in EKW and are connected to the selected inlet and outlet water bodies. Detail description of sampling sites in EKW is provided in Table 1. A total of 196 water samples from the selected sites were collected and samples were processed following the standard protocol of water and wastewater by American Public Health Association (APHA) (1989).

Table 1

Detail description of sampling sites in East Kolkata Wetland

Sl. No.Name of the sampling sites of EKWDescription of the sites
a) Jhagrasisa(east) A total of 3 tanks were selected and marked as J1, J2, J3 
b) Nalban fisheries A total of 3 tanks were selected and marked as N1, N2, N3 
c) Topsia point A This site receives pumped sewage from the city. 
d) Ambedkar bridge It is 4 km downstream of Topsia Point A. 
e) Bantala A major regulator point, 6 km downstream of Topsia Point A. 
f) Bamunghata This site enters a series of fish ponds, which are runed by a fishery co-operative. 
g) Ghosher khal The primary canals connected to the fish pond. 
h) Ghusighata 36 km downstream from Topsia Point A. Final discharge site. 
Sl. No.Name of the sampling sites of EKWDescription of the sites
a) Jhagrasisa(east) A total of 3 tanks were selected and marked as J1, J2, J3 
b) Nalban fisheries A total of 3 tanks were selected and marked as N1, N2, N3 
c) Topsia point A This site receives pumped sewage from the city. 
d) Ambedkar bridge It is 4 km downstream of Topsia Point A. 
e) Bantala A major regulator point, 6 km downstream of Topsia Point A. 
f) Bamunghata This site enters a series of fish ponds, which are runed by a fishery co-operative. 
g) Ghosher khal The primary canals connected to the fish pond. 
h) Ghusighata 36 km downstream from Topsia Point A. Final discharge site. 

N1 and J1 is the nursery tank, N2 and J2 is the rearing tank and N3 and J3 is the stocking tank.

Evaluation of water quality parameters

Physicochemical and biological parameters were studied, checked and analyzed from the water samples collected from different areas of EKW.

Analysis of physicochemical properties

Physicochemical properties such as pH, temperature, TDS, and DO were determined electrometrically by using a multiparameter portable water quality testing kit (350i- Merck, Germany). BOD was measured using the dilution method described by APHA (2005). COD was measured through titration with a strong oxidizing agent, potassium dichromate, under acidic conditions. The concentration of ammonia (NH3) and nitrate (NO3) was measured using the standard protocol of APHA (1989). All the data was analyzed statistically through ANOVA.

Bacteriological analyses

Total heterotrophic bacteria (THB), Nitrosomonas sp., and Nitrobacter sp. were isolated and enumerated for further analysis. Samples were collected in sterile plastic bottles (Tarson). Column water samples were collected for the analysis of THB, whereas bottom water samples were collected for the analysis of Nitrosomonas and Nitrobacter (Odokuma & Akponah 2008). THB was enumerated using the spread plate method (Cappuccino & Sherman 1992); 0.1 mL of the sample was spread in the plates and incubated in an inverted position at 37 °C for 20–24 h.

Simultaneously collected samples were processed on Winogradskyi medium for the isolation of nitrifying bacteria. Nitrosomonas sp. was isolated using Winogradsky phase-I medium ((NH4)2SO4, 2.0 g; K2HPO4, 1.0 g; MgSO4, 7H2O, O.5 g; NaCl, 2.0 g; FeSO4,7H2O, 0.4 g; CaCO3, 0.01 g, and miliQ water upto 1,000 mL, pH 7.8). Nitrobacter sp. was isolated using Winogradsky phase-II medium (KNO2, 0.1 g; Na2CO3, 1.0 g; NaCl, 0.5 g; FeSO4, 7H2O, 0.4 g, and miliQ water upto 1,000 mL, pH 7.8). Tubes were incubated at 28 °C for 90 h aerobically. Cultures were initially identified by gram staining. Suspected cultures were evaluated for presence of ammonia and nitrite and vice versa for production of nitrite and nitrate (Saha et al. 2014; Roalkvam et al. 2020). Identification of Nitrosomonas was tested by the Nessler's reagent (Raud et al. 2013; Agus Fitri et al. 2017) and Nitrosomonas and Nitrobacter were confirmed through Trommsdrof's reagent (Hanks & Weintraub 1936; Kshatri et al. 2017). Selected cultures were preserved at −80 °C with 30–40% glycerol stock for further studies. All the experiments were performed in triplicates.

Screening of nitrifying bacterial isolates on medium with TCE

Pure cultures of 3 Nitrobacter sp. and 4 Nitrosomonas sp. isolates were characterized through the 16SrRNA PCR technique (Saha et al. 2014), and gene sequences were analysed and submitted to the NCBI-GenBank (accession numbers: KF618620, KF618621, and KF618622 for Nitrobacter sp.; KF618623, KF618626, KF618624, and KF618625 for Nitrosomonas sp.). After identification of the genus and species, the isolates were preserved in 1% glycerol stock in –20 °C for subsequent analyses. In the present study, the selected strains were revived and used in the initial screening. Their ability to grow on TCE as the sole carbon source was assessed at pH ranging from 3 to 13; the optimum pH for growth was found between 5.0 and 7.0. Trichloroethylene (GC 99.5%) was purchased from Merck Ltd India. Cultures (100 μL) were transferred to tubes containing 5 mL of minimal broth and TCE at pH 7. The amount of TCE used in the experiment ranged from 0.1% to 0.5% because excess TCE is toxic and can inhibit the bacterial growth (Moss & Rylance 1966). We determined the amount of TCE that can be endured by the isolates. All the test tubes were incubated at 28 °C for 72 h.

Of the seven isolates, only two strains (Nitrobacter hamburgensis NBW2 strain and Nitrosomonas europaea NSW3 strain) were able to survive and their growth pattern was recorded. Fujiwara test was performed to screen the TCE degradation activity in the TCE-positive isolates by calculating the amount of TCE remaining in the medium inoculated with these isolates. In the Fujiwara reaction, polychlorinated hydrocarbons produce a red-coloured compound in the presence of alkali and pyridine (John & Okpokwasili 2012). Winogradsky medium (Phases I and II) was further used for culturing the TCE resistant bacterial strains. Isolated genomic DNA from TCE resistant strain NSW3 was amplified using ammonia monooxygenase gene specific primer amoA-3F 5′-GGT GAG TGG GYT AAC MG-3′ and amoB-4R 5′-GCT AGC CAC TTT CTG G-3′ and the genomic DNA of another TCE resistant strain NBW2 was amplified using nitrate oxidoreductase gene specific primers F1norA 5′- CAG ACC GAC GTG TGC GAA AG-3′ for forward reaction and the R1norA 5′- TCY ACA AGG AAC GGA AGG TC-3′ (Y = C/T) for reverse reaction. Amplicons were checked in 2.0% agarose gel and processed for sequencing. NBW2 cells were grown in Winogradsky phase-II medium (50 mL) with 0.2% TCE at pH 5, and NSW3 cells were grown in Winogradsky phase-I medium (50 mL) with 0.2% TCE at pH 7. Cells were pelleted by centrifugation and suspended in 10 mL phosphate buffer (pH 5) with TCE in acetone. Aliquots of 7.2 mL were taken at the beginning (immediately after inoculation) and after every 30-min interval up to 120 min and mixed with 2 mL 5N NaOH and 2 mL pyridine, followed by heating at 80 °C for 2 min. Absorbance of the upper red phase was recorded at 470 nm (OD470) by using a spectrophotometer. An E. coli culture in LB medium with 0.3% TCE was used as the control. A standard curve plotted between time and varying concentrations of TCE (0.01–0.48%) was used to calculate the amount of TCE remaining in the medium at each time point.

Assessment of nitrifying bacteria as probiotics

A small-scale experiment was performed to assess the potential of nitrifying bacteria as probiotics. Four fish rearing barrel-shaped (FRB) tanks of 500-L capacity were used; the tanks were labelled as C (control, without microbes); NS (Nitrosomonas culture alone); NB (Nitrobacter culture alone); and NSB (Nitrosomonas and Nitrobacter mixed culture). In the tanks labelled as NS, NB, and NSB, Catla catla (n = 25) and Labeo rohita (n = 25) were stocked in a ratio of 1.1 (n = 50). Fishes were fed daily with supplementary feed, mostly de-oiled rice bran, groundnut oil cake, and slaughter wastes at the rate of 2% body weight of fish per day.

To assess the impact of nitrifying bacteria on the overall fish health and water quality in terms of reduced levels of pollutants, we determined the levels of ammonia, nitrite, and nitrate in the tanks and assessed the growth, survival rates, and health of fishes. The in-culture application of probiotics mostly requires proper water quality management, optimum aeration facility, superior-quality and correct feeding schedule, proper check tray management, and strong biosecurity. In this study, we ensured optimum water quality parameters, effective aeration, competent feeding program, and check tray management to enhance the probiotics efficiency after in-culture application. Probiotics were used at 15-day intervals, with Nitrosomonas probiotics at 1.5 kg/ha and Nitrobacter probiotics at 0.75 kg/ha.

In the post culture application of probiotics in fish culture tanks, one of the most important aquaculture management practices, excess organic loads were removed. The post culture probiotic application in our experimental tanks resulted in a healthy bottom condition. Superior-quality fishes were stocked on the basis of uniform weight, size, and health. Water samples were collected in morning between 7 and 8 AM, and their physicochemical parameters such as temperature, dissolved oxygen, pH, total dissolved solids, nitrite, nitrate, ammonia, and phosphorus, as well as the bacterial loads were assessed at 15-day intervals by following the methods described by Wetzel and Likens and APHA (Palissa 1972; Wetzel & Likens 1979; APHA 1999).

Statistical analysis

Obtained data were subjected to statistical analysis using statistical package for social sciences (SPSS v 26.0, IBM). All numerical data are expressed as mean and standard deviation. To analyze the variation in physicochemical parameters as a function of sampling site and season, inter group comparison with two factors was performed using two-way ANOVA. For all the statistical tests, a p value of <0.05 was considered statistically significant, keeping α error at 5% and β error at 20%, thus giving a power to the study as 80%.

RESULTS AND DISCUSSION

Results

Analysis of physicochemical parameters of water

The result of all the physicochemical properties after seasonal study of the selected water bodies were found within the permissible range for fish production as per West Bengal Pollution Control Board (WBPCB). Seasonal variation was observed among the parameters. Statistical analysis of the data (Table 2) depicted that the water quality was significant for aquaculture practices. The effect of sampling sites and seasons as well as the effect of interaction between these two factors on the studied physicochemical parameters are illustrated in Tables 310.

Table 2

Two-way ANOVA results for the effect of sampling regions and seasons as well as their interaction effect on the studied physicochemical parameters

VariableSourceF valuep value
BOD SR Hypothesis 102.895 .000** 
Error 
SS Hypothesis 28.386 .000** 
Error 
SR * SS Hypothesis — — 
Error 
COD SR Hypothesis 18.208 .000** 
Error 
SS Hypothesis 5.362 .004** 
Error 
SR * SS Hypothesis — — 
Error 
TDS SR Hypothesis 14.424 .000** 
Error 
SS Hypothesis .744 .534# 
Error 
SR * SS Hypothesis — — 
Error 
Phosphate SR Hypothesis 39.453 .000** 
Error  
SS Hypothesis 7.296 .001** 
Error 
SR * SS Hypothesis — — 
Error 
Ammonia SR Hypothesis 6.367 .000** 
Error 
SS Hypothesis 10.120 .000** 
Error 
SR * SS Hypothesis — — 
Error 
Nitrate SR Hypothesis 16.160 .000** 
Error 
SS Hypothesis 5.261 .005** 
Error 
SR * SS Hypothesis — — 
Error 
Temp SR Hypothesis 1.719 .191# 
Error 
SS Hypothesis 280.272 .000** 
Error 
SR * SS Hypothesis — — 
Error 
DO SR Hypothesis 7.088 .001** 
Error 
SS Hypothesis 44.035 .000** 
Error 
SR * SS Hypothesis — — 
Error 
VariableSourceF valuep value
BOD SR Hypothesis 102.895 .000** 
Error 
SS Hypothesis 28.386 .000** 
Error 
SR * SS Hypothesis — — 
Error 
COD SR Hypothesis 18.208 .000** 
Error 
SS Hypothesis 5.362 .004** 
Error 
SR * SS Hypothesis — — 
Error 
TDS SR Hypothesis 14.424 .000** 
Error 
SS Hypothesis .744 .534# 
Error 
SR * SS Hypothesis — — 
Error 
Phosphate SR Hypothesis 39.453 .000** 
Error  
SS Hypothesis 7.296 .001** 
Error 
SR * SS Hypothesis — — 
Error 
Ammonia SR Hypothesis 6.367 .000** 
Error 
SS Hypothesis 10.120 .000** 
Error 
SR * SS Hypothesis — — 
Error 
Nitrate SR Hypothesis 16.160 .000** 
Error 
SS Hypothesis 5.261 .005** 
Error 
SR * SS Hypothesis — — 
Error 
Temp SR Hypothesis 1.719 .191# 
Error 
SS Hypothesis 280.272 .000** 
Error 
SR * SS Hypothesis — — 
Error 
DO SR Hypothesis 7.088 .001** 
Error 
SS Hypothesis 44.035 .000** 
Error 
SR * SS Hypothesis — — 
Error 

SR, sampling region; SS, sampling season; * = statistically significant difference (p < 0.05); ** = statistically highly significant difference (p < 0.01); # = nonsignificant difference (p > 0.05).

BOD – biological oxygen demand, COD – chemical oxygen demand, TDS – total dissolved solid, Temp – temperature, DO – dissolved oxygen.

Table 3

Seasonal variation in temperature across the selected fish tanks of Jhagrasisha and Nalban fisheries, all the J1, J2, and J3: Jhagrahisa fisheries; N1, N2, N3: Nalban fisheries

SeasonJ1(°C)J2(°C)J3(°C)N1(°C)N2(°C)N3(°C)
Winter 19.90 20.55 20.22 19.70 19.87 19.95 
Summer 27.73 27.90 28.70 27.50 27.60 28.00 
Monsoon 28.56 27.86 28.56 27.00 26.10 27.50 
Post Monsoon 24.50 23.40 23.45 24.20 23.60 24.00 
SeasonJ1(°C)J2(°C)J3(°C)N1(°C)N2(°C)N3(°C)
Winter 19.90 20.55 20.22 19.70 19.87 19.95 
Summer 27.73 27.90 28.70 27.50 27.60 28.00 
Monsoon 28.56 27.86 28.56 27.00 26.10 27.50 
Post Monsoon 24.50 23.40 23.45 24.20 23.60 24.00 
Table 4

Seasonal variation in dissolved oxygen levels in selected fish tanks of Jhagrasisha and Nalban fisheries J1, J2, and J3: Jhagrahisa fisheries; N1, N2, N3: Nalban fisheries. DO were measured using the unit mg/L

SeasonJ1J2J3N1N2N3
Winter 6.00 6.27 5.85 5.00 5.68 4.89 
Summer 6.12 6.91 6.80 6.00 7.01 5.76 
Monsoon 4.45 5.12 5.03 4.98 5.53 5.08 
Post Monsoon 5.10 5.74 5.42 6.20 6.54 5.88 
SeasonJ1J2J3N1N2N3
Winter 6.00 6.27 5.85 5.00 5.68 4.89 
Summer 6.12 6.91 6.80 6.00 7.01 5.76 
Monsoon 4.45 5.12 5.03 4.98 5.53 5.08 
Post Monsoon 5.10 5.74 5.42 6.20 6.54 5.88 
Table 5

Seasonal variation in the biological oxygen demand level across the selected water bodies

Sampling SeasonTABBNBNGJ1J2J3N1N2N3G
Winter 90.25 86.75 75.25 69.25 29.50 20.75 16.37 29.50 21.50 20.75 13.75 
Summer 121.33 109.66 88.00 75.33 50.00 37.33 30.00 49.33 37.00 32.66 27.33 
Monsoon 144.33 128.00 98.33 75.00 58.00 59.33 34.33 60.33 49.33 34.00 29.00 
Post-monsoon 131.50 119.00 87.50 68.00 35.50 35.50 28.50 37.00 34.00 23.50 20.50 
Sampling SeasonTABBNBNGJ1J2J3N1N2N3G
Winter 90.25 86.75 75.25 69.25 29.50 20.75 16.37 29.50 21.50 20.75 13.75 
Summer 121.33 109.66 88.00 75.33 50.00 37.33 30.00 49.33 37.00 32.66 27.33 
Monsoon 144.33 128.00 98.33 75.00 58.00 59.33 34.33 60.33 49.33 34.00 29.00 
Post-monsoon 131.50 119.00 87.50 68.00 35.50 35.50 28.50 37.00 34.00 23.50 20.50 

BOD were measured using the unit mg/L. T – Topsia, AB – Ambedkar Bridge, BN – Bantala, BNG – Bamunghata, J1, J2, and J3: Jhagrahisa fisheries; N1, N2, N3: Nalban fisheries, G – Ghusighata.

Table 6

Seasonal variation in the COD level across the selected water bodies

Sampling SeasonTABBNBNGJ1J2J3N1N2N3G
Winter 132.50 126.50 110.50 94.25 81.50 70.50 52.75 85.00 72.50 61.00 54.25 
Summer 253.00 230.66 173.33 113.00 86.00 59.66 47.00 86.33 62.33 57.33 79.33 
Monsoon 345.66 304.66 224.33 131.66 112.66 84.33 39.33 109.00 82.33 37.33 87.00 
Post-monsoon 275.50 261.50 214.50 124.50 96.50 79.00 42.50 92.50 81.50 35.00 68.50 
Sampling SeasonTABBNBNGJ1J2J3N1N2N3G
Winter 132.50 126.50 110.50 94.25 81.50 70.50 52.75 85.00 72.50 61.00 54.25 
Summer 253.00 230.66 173.33 113.00 86.00 59.66 47.00 86.33 62.33 57.33 79.33 
Monsoon 345.66 304.66 224.33 131.66 112.66 84.33 39.33 109.00 82.33 37.33 87.00 
Post-monsoon 275.50 261.50 214.50 124.50 96.50 79.00 42.50 92.50 81.50 35.00 68.50 

COD were measured using the unit mg/l. T – Topsia, AB – Ambedkar Bridge, BN – Bantala, BNG – Bamunghata, J1, J2, and J3: Jhagrahisa fisheries; N1, N2, N3: Nalban fisheries, G – Ghusighata.

Table 7

Seasonal variation in the total dissolved solids across the selected water bodies

Sampling SeasonTABBNBNGJ1J2J3N1N2N3G
Winter 574.50 541.50 469.50 429.50 361.50 332.00 336.00 375.00 350.50 338.25 405.25 
Summer 568.33 552.33 496.66 411.66 371.00 376.00 335.00 381.66 370.00 342.66 559.33 
Monsoon 568.33 552.33 496.66 411.66 371.00 376.00 335.00 399.66 365.33 343.00 559.33 
Post-monsoon 586.00 508.50 482.50 367.50 386.50 340.00 327.50 386.00 340.50 327.50 790.00 
Sampling SeasonTABBNBNGJ1J2J3N1N2N3G
Winter 574.50 541.50 469.50 429.50 361.50 332.00 336.00 375.00 350.50 338.25 405.25 
Summer 568.33 552.33 496.66 411.66 371.00 376.00 335.00 381.66 370.00 342.66 559.33 
Monsoon 568.33 552.33 496.66 411.66 371.00 376.00 335.00 399.66 365.33 343.00 559.33 
Post-monsoon 586.00 508.50 482.50 367.50 386.50 340.00 327.50 386.00 340.50 327.50 790.00 

TDS were measured using the unit mg/L. T – Topsia, AB – Ambedkar Bridge, BN – Bantala, BNG – Bamunghata, J1, J2, and J3: Jhagrahisa fisheries; N1, N2, N3: Nalban fisheries, G – Ghusighata.

Table 8

Seasonal variation in the orthophosphate level across the selected water bodies

Sampling SeasonTABBNBNGJ1J2J3N1N2N3G
Winter 2.23 2.37 1.80 1.30 0.85 0.67 0.65 0.86 0.75 0.66 0.70 
Summer 2.50 2.50 1.83 1.00 1.36 1.51 1.02 1.47 0.97 0.99 0.87 
Monsoon 2.36 2.16 1.83 0.93 1.56 1.30 1.00 1.56 1.20 0.93 0.80 
Post-monsoon 2.06 2.09 1.79 1.10 1.15 0.85 0.72 1.17 0.93 0.72 0.82 
Sampling SeasonTABBNBNGJ1J2J3N1N2N3G
Winter 2.23 2.37 1.80 1.30 0.85 0.67 0.65 0.86 0.75 0.66 0.70 
Summer 2.50 2.50 1.83 1.00 1.36 1.51 1.02 1.47 0.97 0.99 0.87 
Monsoon 2.36 2.16 1.83 0.93 1.56 1.30 1.00 1.56 1.20 0.93 0.80 
Post-monsoon 2.06 2.09 1.79 1.10 1.15 0.85 0.72 1.17 0.93 0.72 0.82 

Phosphate were measured using the unit mg/L. T – Topsia, AB – Ambedkar Bridge, BN – Bantala, BNG – Bamunghata, J1, J2, and J3: Jhagrahisa fisheries; N1, N2, N3: Nalban fisheries, G – Ghusighata.

Table 9

Seasonal variations in the ammonia level across the selected water bodies and were measured using the unit mg/L

Sampling SeasonTABBNBNGJ1J2J3N1N2N3G
Winter 7.37 7.87 7.75 5.25 3.85 3.02 2.4 4.32 3.52 2.9 2.05 
Summer 3.8 4.7 5.3 4.26 3.2 3.26 2.8 3.06 2.46 3.07 
Monsoon 2.2 3.1 3.66 3.4 2.96 2.26 1.73 3.1 2.43 1.76 2.03 
Post-monsoon 3.95 4.15 4.8 4.75 3.3 2.8 2.95 3.55 3.15 2.55 2.55 
Sampling SeasonTABBNBNGJ1J2J3N1N2N3G
Winter 7.37 7.87 7.75 5.25 3.85 3.02 2.4 4.32 3.52 2.9 2.05 
Summer 3.8 4.7 5.3 4.26 3.2 3.26 2.8 3.06 2.46 3.07 
Monsoon 2.2 3.1 3.66 3.4 2.96 2.26 1.73 3.1 2.43 1.76 2.03 
Post-monsoon 3.95 4.15 4.8 4.75 3.3 2.8 2.95 3.55 3.15 2.55 2.55 

T – Topsia, AB - Ambedkar Bridge, BN - Bantala, BNG - Bamunghata, J1, J2, and J3: Jhagrahisa fisheries; N1, N2, N3: Nalban fisheries, G – Ghusighata.

Table 10

Seasonal variations in the nitrate level across the selected water bodies and were measured using the unit mg/L

Sampling SeasonTABBNBNGJ1J2J3N1N2N3G
Winter 0.90 1.15 1.92 2.57 4.02 3.42 4.17 3.55 3.95 4.22 3.72 
Summer 0.82 1.18 1.93 3.46 2.46 3.26 2.80 2.53 3.26 2.93 3.07 
Monsoon 0.70 1.00 2.33 2.50 1.56 3.23 3.66 1.56 3.26 3.96 2.90 
Post-monsoon 0.70 1.03 2.10 3.20 3.83 3.90 4.13 3.95 4.30 4.15 2.97 
Sampling SeasonTABBNBNGJ1J2J3N1N2N3G
Winter 0.90 1.15 1.92 2.57 4.02 3.42 4.17 3.55 3.95 4.22 3.72 
Summer 0.82 1.18 1.93 3.46 2.46 3.26 2.80 2.53 3.26 2.93 3.07 
Monsoon 0.70 1.00 2.33 2.50 1.56 3.23 3.66 1.56 3.26 3.96 2.90 
Post-monsoon 0.70 1.03 2.10 3.20 3.83 3.90 4.13 3.95 4.30 4.15 2.97 

T – Topsia, AB – Ambedkar Bridge, BN – Bantala, BNG – Bamunghata, J1, J2, and J3: Jhagrahisa fisheries; N1, N2, N3: Nalban fisheries, G – Ghusighata.

pH, temperature, and dissolved oxygen

pH indicates the intensity of the acidic or basic character of a solution at a given temperature, and it is one of the most important water quality parameters. A pH value of more than 7 indicates that water is probably hard, and an alkaline pH is indicative of waste deposition. In our study, pH levels of the water samples were not found to vary substantially (data not shown), with the minimum (6.75) and maximum (7.27) pH recorded in Ghusighata and N2 tank, respectively. However, seasonal variation in the temperature of fish ponds was found to be highly significant (p < 0.01), with high values in summer, and was found to fluctuate between 19.70 °C and 28.70 °C. The difference in the temperature across different sampling sites was found to be nonsignificant (p = 0.191), and no interaction effect of area and sampling season was observed (p > 0.05). Table 3 presents the temperature profiles of fish ponds in Nalban bhery (N1, N2 and N3) and Jhagrasisa bhery (J1, J2 and J3). The lowest temperature (19.5 °C) was recorded during winter in all the ponds, whereas it was increased to 28 °C during summer.

Seasonal variation in DO was also found to be highly significant (range, 4.5 to 7.0 mg/L; p < 0.01) in water bodies of the selected sites, with high values during summer (Table 4). The DO level was found to be the lowest during the post-monsoon season; however, it was found to be more than 6.0 mg/L (range, 5.7 to 7.0 mg/L) during summer. The DO level was also found to vary significantly across different sampling sites (p < 0.01), with the highest level in the N2 fishery; the interaction effect of area and sampling season on the DO level was not observed (p > 0.05).

Biological oxygen demand

Table 5 presents the BOD of the selected water bodies. The lowest average value of BOD (13.75 mg/L) was recorded in winter, and the highest average value of BOD of 144.33 mg/L was recorded during monsoon. Variation in the BOD level as a function of sampling season and site was found to be significant (p < 0.01), with high levels recorded during monsoon and the highest BOD range of 140 mg/L–90 mg/L recorded in Topsia. In the Nalban bhery N1, the highest average BOD was 60 mg/L and the minimum average was up to 24 mg/L, whereas the BOD level was extremely low (13–25 mg/L) in Ghusighata. The BOD level was found to decrease gradually with increase in the distance from Topsia region; the interaction effect of area and sampling season on BOD was not observed (p > 0.05).

Chemical oxygen demand

Similar to BOD, variation in the BOD level as a function of sampling season and site was found to be significant (p < 0.01), with high levels recorded during monsoon and in Topsia. Table 6 presents the seasonal variation in COD across the selected sites in the present study. The COD was lowest in the Ghusighata region, with the average value of 60–70 mg/L, which is much lower than the permissible limit of 250 mg/L. COD levels during monsoon at the nursery tanks (J1 and N1) were slightly higher (112.66 and 109 mg/L, respectively) than the fisheries located at other sites. In Topsia, COD was high (253 mg/L) during summer, whereas it reduced to 132.5 mg/L during winter. Moreover, the COD levels declined with increase in the distance from Topsia, with COD range of 304.66–126.5 mg/L in Ambedkar bridge, 224.33–110.5 mg/L in Bantala, and 131.66–94.2 mg/L in Bamunghata. The interaction effect of the sampling site and sampling season on COD was not observed (p > 0.05).

Total dissolved solid

Differences in the TDS concentration between different sampling sites were found to be highly significant (p < 0.01). TDS concentration was found to be the highest (790 mg/L) in Ghusighata, followed by that observed in the Topsia during the post monsoon season (Table 7), whereas the average TDS concentration was comparatively low (333 to 399 mg/L) in the fish tanks (J1, J2, J3, N1, N2, and N3). However, the seasonal variation in the TDS concentration was found to be nonsignificant (p = 0.534), and no interaction effect of the sampling season and site was observed (p > 0.05).

Orthophosphate phosphorus

Orthophosphate concentration was found to differ significantly across different sampling seasons and sites (p < 0.01), with high values recorded during summer in Topsia; however, no interaction effect of the sampling season and site on the orthophosphate concentration was observed (p > 0.05). The value ranged between 0.93 and 2.5 mg/L in Topsia, Ambedkar Bridge, Bantala, and Bamunghata. Moreover, the concentration was found in the range of 0.56 mg/L to 1.56 mg/L in the J and N fish tank series and in Ghushighata (Table 8).

Ammonia

Table 9 indicates the ammonia levels observed in the selected fisheries. Differences in the ammonia level across different sampling seasons and sites were found to be highly significant (p < 0.01); however, no interaction effect of the sampling season and site was observed (p > 0.05). The levels were found to be the highest during winter and in the Ambedkar bridge (7.87 mg/L), followed by Bantala (7.75 mg/L), and Bamunghata (5.25 mg/L).

Nitrate

Table 10 presents the average range of nitrate concentration recorded in the selected ponds. Differences in the nitrate concentration between the selected sampling sites and the sampling seasons were found to be highly significant; however, no interaction effect of the sampling season and site was observed (p > 0.05). Nitrate concentrations in Ghusighata during winter, summer, monsoon, and post-monsoon were found to be 3.72 mg/L, 3.07 mg/L, 2.90 mg/L, and 2.97 mg/L, respectively, whereas in the J and N tank series, the concentration ranged between 1.56 mg/L and 4.22 mg/L. The lowest range of nitrate concentration (0.7–0.9 mg/L) was observed in the Topsia, followed by Ambedkar bridge (1.0–1.18 mg/L), Bantala (1.92–2.33 mg/L), and Bamunghata (2.5–3.46 mg/L).

Biochemical tests of nitrifying bacterial isolates

Nessler's reagent was used to detect the presence of ammonia in the Phase I medium (Hanks & Weintraub 1936). Before inoculation, yellowish brown color of medium indicated the presence of ammonia. After inoculation, absence of the yellowish-brown color of medium indicated the utilization of ammonia by Nitrosomonas sp. Similarly, Trommsdrof's reagent (black color) in Phase I medium indicates the production of nitrites and thus conferring Nitrosomonas and simultaneously disappearance of black color indicated the presence of Nitrobacter sp. Again, presence of the black colour in Phase II medium by adding diphenylamine reagent indicates the presence of nitrate (Kshatri et al. 2017).

TCE degradation activity of the isolates

Of the seven pure culture isolates, NSW3 and NBW2 displayed the maximum TCE degradation activity (Figure 1(a) and 1(b)). In the Fujiwara test, the two strains demonstrated decrease in the color intensity and absorbance of the upper phase with time, which confirmed TCE degradation. No change in color was observed in the control E. coli strain. Initially, 0.3% TCE was added; in case of NBW2, the percentage of TCE remaining after 120 min at pH 7 and pH 5 was 0.068% and 0.039%, respectively (Figure 2(a) and 2(b)). Similarly, in the case of NSW3, the percentage of TCE remaining after 120 min at pH 7 was 0.084% and that at pH 5 was 0.095% of the initial 0.3% TCE (Figure 3(a) and 3(b)). The findings suggest that the TCE degradation activity of microbes at pH 5 is higher than that at pH 7.

Figure 1

(a) TCE degradation activity of NSW3 and NBW2 strains; (b) standard curve of % of TCE plotted against the absorbance. With increase in percentage of TCE added to the medium, intensity of color also increased, causing a rise in OD recorded at 470 nm.

Figure 1

(a) TCE degradation activity of NSW3 and NBW2 strains; (b) standard curve of % of TCE plotted against the absorbance. With increase in percentage of TCE added to the medium, intensity of color also increased, causing a rise in OD recorded at 470 nm.

Figure 2

Line graph showing the decrease in absorbance corresponding to the catabolism of TCE by NBW2 at (a) pH 7 and (b) pH 5. Secondary vertical axis represents the % of TCE remaining at different time intervals as calculated from the standard curve.

Figure 2

Line graph showing the decrease in absorbance corresponding to the catabolism of TCE by NBW2 at (a) pH 7 and (b) pH 5. Secondary vertical axis represents the % of TCE remaining at different time intervals as calculated from the standard curve.

Figure 3

Line graph showing the decrease in absorbance corresponding to the catabolism of TCE by NSW3 at (a) pH 7 and (b) pH 5. Secondary vertical axis represents the % of TCE remaining at different time intervals as calculated from the standard curve.

Figure 3

Line graph showing the decrease in absorbance corresponding to the catabolism of TCE by NSW3 at (a) pH 7 and (b) pH 5. Secondary vertical axis represents the % of TCE remaining at different time intervals as calculated from the standard curve.

Molecular identification of TCE resistant strains

Isolated TCE resistant strains (NSW3 and NBW2) were confirmed through polymerase chain reaction (PCR) amplification. Amplicons were visualized on 2.0% agarose gel. 415 bp amoA gene for NSW3 (Nitrosomonas europaea) and 322 bp nxrA gene for NBW2 (Nitrobacter hamburgensis) was found and confirmed the presence of functional gene in TCE-degradable isolates.

Application and assessment of ammonia- and nitrite-oxidizing bacteria as probiotics in aquaculture operations

Table 11 shows the mean ± SD values of all the studied physicochemical properties of water in the experimental tanks C, NS, NB, and NSB. The water quality parameters of all the ponds treated with probiotics were found to be superior, which indicates the beneficial roles of microbes as probiotics. Furthermore, the total heterotrophic bacteria (THB) population was found to be high in the experimental tanks NS (5.25 × 105 to 7.80 × 105 cfu/mL), NB (5.42 × 105 to 7.90 × 105 cfu/mL), and NSB (5.25 × 105 to 8.20 × 105 cfu/mL), whereas it was found to be low in the tank C (2.05 × 105 to 4.72 × 105 cfu/mL). The Nitrosomonas (ammonia-oxidizing bacteria) and Nitrobacter (nitrite-oxidizing bacteria) loads in the tank NSB were relatively higher than those in other tanks; the Nitrosomonas load ranged from 2.01 × 103 to 4.80 × 103 cfu/mL in the tank NS and from 2.38 × 103 to 4.90 × 103 cfu/mL in the tank NB.

Table 11

Physicochemical parameters of water in fish culture tanks

Physicochemical parametersTank C
Tank NS
Tank NB
Tank NSB
Mean ± SDRangeMean ± SDRangeMean ± SDRangeMean± SDRange
Water temp (°C) 29.93 ± 1.35 27.60–32.50 29.93 ± 1.35 27.60–32.50 29.17 ± 2.32 25.30–31.40 29.66 ± 2.11 25.20–32.70 
DO (mg/L) 3.50 ± 0.88 2.00–5.20 3.50 ± 0.88 2.00–5.20 4.80 ± 0.81 3.20–6.20 4.09 ± 1.30 2.40–6.40 
pH 7.92 ± 0.40 7.44–8.65 7.92 ± 0.40 7.44–8.65 7.87 ± 0.43 7.29–8.88 7.92 ± 0.35 7.50–8.56 
TDS (ppt) 7.64 ± 4.37 2.41–16.70 7.64 ± 4.37 2.41–16.70 12.48 ± 6.47 4.28–23.60 12.05 ± 6.39 5.24–24.90 
NH3-N(mg/L) 0.51 ± 0.08 0.38–0.73 0.51 ± 0.08 0.38–0.73 0.41 ± 0.07 0.28–0.53 0.38 ± 0.06 0.27–0.50 
NO2-N(mg/L) 7 ± 0.02 0.02–0.11 7 ± 0.02 0.02–0.11 0.04 ± 0.05 0.08–0.25 03 ± 0.01 0.09–0.07 
NO3-N(mg/L) 0.21 ± 0.07 0.09–0.41 0.21 ± 0.07 0.09–0.41 0.26 ± 0.09 0.10–0.45 0.26 ± 0.09 0.12–0.46 
PO43−(mg/L) 0.56 ± 0.09 0.42–0.75 0.56 ± 0.09 0.42–0.75 0.41 ± 0.09 0.25–0.59 0.45 ± 0.06 0.32–0.58 
Gross Primary Productivity (gc/m3/h) 0.09 ± 0.15 0.02–0.75 0.09 ± 0.15 0.02–0.75 0.19 ± 0.19 0.07–0.87 0.14 ± 0.11 0.05–0.40 
Net Primary Productivity (gc/m3/h) 0.09 ± 0.07 0.02–0.26 0.09 ± 0.07 0.02–0.26 0.09 ± 0.05 0.02–0.24 0.06 ± 0.10 0.02–0.37 
Community respiration (gc/m3/h) 0.05 ± 0.03 0.02–0.16 0.05 ± 0.03 0.02–0.16 0.08 ± 0.13 0.02–0.62 0.07 ± 0.08 0.02–0.38 
Physicochemical parametersTank C
Tank NS
Tank NB
Tank NSB
Mean ± SDRangeMean ± SDRangeMean ± SDRangeMean± SDRange
Water temp (°C) 29.93 ± 1.35 27.60–32.50 29.93 ± 1.35 27.60–32.50 29.17 ± 2.32 25.30–31.40 29.66 ± 2.11 25.20–32.70 
DO (mg/L) 3.50 ± 0.88 2.00–5.20 3.50 ± 0.88 2.00–5.20 4.80 ± 0.81 3.20–6.20 4.09 ± 1.30 2.40–6.40 
pH 7.92 ± 0.40 7.44–8.65 7.92 ± 0.40 7.44–8.65 7.87 ± 0.43 7.29–8.88 7.92 ± 0.35 7.50–8.56 
TDS (ppt) 7.64 ± 4.37 2.41–16.70 7.64 ± 4.37 2.41–16.70 12.48 ± 6.47 4.28–23.60 12.05 ± 6.39 5.24–24.90 
NH3-N(mg/L) 0.51 ± 0.08 0.38–0.73 0.51 ± 0.08 0.38–0.73 0.41 ± 0.07 0.28–0.53 0.38 ± 0.06 0.27–0.50 
NO2-N(mg/L) 7 ± 0.02 0.02–0.11 7 ± 0.02 0.02–0.11 0.04 ± 0.05 0.08–0.25 03 ± 0.01 0.09–0.07 
NO3-N(mg/L) 0.21 ± 0.07 0.09–0.41 0.21 ± 0.07 0.09–0.41 0.26 ± 0.09 0.10–0.45 0.26 ± 0.09 0.12–0.46 
PO43−(mg/L) 0.56 ± 0.09 0.42–0.75 0.56 ± 0.09 0.42–0.75 0.41 ± 0.09 0.25–0.59 0.45 ± 0.06 0.32–0.58 
Gross Primary Productivity (gc/m3/h) 0.09 ± 0.15 0.02–0.75 0.09 ± 0.15 0.02–0.75 0.19 ± 0.19 0.07–0.87 0.14 ± 0.11 0.05–0.40 
Net Primary Productivity (gc/m3/h) 0.09 ± 0.07 0.02–0.26 0.09 ± 0.07 0.02–0.26 0.09 ± 0.05 0.02–0.24 0.06 ± 0.10 0.02–0.37 
Community respiration (gc/m3/h) 0.05 ± 0.03 0.02–0.16 0.05 ± 0.03 0.02–0.16 0.08 ± 0.13 0.02–0.62 0.07 ± 0.08 0.02–0.38 

C – Control, without microbes, NS – Nitrosomonas culture alone, NB – Nitrobacter culture alone, NSB – Nitrosomonas and Nitrobacter mixed culture, Water Temp – water temperature, DO – dissolved oxygen, TDS – total dissolved solid, NH3-N – ammonia, NO2-N – nitrite, NO3-N – nitrate, PO43− – orthophosphate.

Effect of probiotics on ammonia and nitrite levels

In the tank NS, the ammonia level was decreased, whereas the nitrite level was increased, following the addition of the Nitrosomonas pure culture. However, the addition of Nitrobacter pure culture as probiotics in the culture tank NB resulted in no change in the ammonia level because Nitrobacter sp. cannot degrade ammonia; however, nitrite was completely degraded and not detected in the tank. No changes were found in the ammonia level in tank C probably due to the absence of microbes in the control tank. Moreover, the levels of ammonia, nitrite, and nitrate were drastically reduced and microbial mass was increased in the tank NSB.

Effect of probiotics on fish health, growth, and survival

The health status and survival of fishes were assessed until half of the fish population died and calculated the mean lethal time (LT50) both in the absence and presence of Nitrosomonas sp. and Nitrobacter sp. as probiotics. The groups treated with probiotics demonstrated greater tolerance to stress (ammonia, nitrite, and nitrate concentrations) than the control group. The survival rates of fish in the tanks NS and NB (18 and 8%, respectively) were significantly lower than that found in the tank NSB (70%) (Figure 4).

Figure 4

The survival rate of cultured fishes in FRB tanks in the in vivo probiotic therapy experiment.

Figure 4

The survival rate of cultured fishes in FRB tanks in the in vivo probiotic therapy experiment.

Discussion

EKW is the best example of a sustainable ecosystem. EKW is a region of international importance, and thus, the traditional fish farming and species diversity in this region have received considerable attention; however, none of the experiments have extensively studied the variability in the physicochemical parameters of water bodies in EKW. Due to increase in anthropogenic activities, load of heavy metals and other pollutants have increased enormously. Therefore, quality profiling of the wastewater entering the wetland is the utmost target to achieve better fish production. Water quality is deteriorating with progress in time, thus major attention must be given for pollution control program and maintaining a proper data bank. A report by GFES 2 (Grassroots Field Exposer Season, 46) group stated the presence of the contaminants is below the permissible level, but heavy metals or pollutants can accumulate in the water which will change the human health and fish anatomy (Dutta et al. 2016; Dutta et al. 2017; CPCB 2019). Apart from EKW, a study described by Das & Bandyopadhyay (2019) reported that pisciculture is a very famous practice in other parts of West Bengal like Sundarban, the estuarine coastal area (Das & Bandyopadhyay 2019). Thus, the present study has been conducted and surveillance of physicochemical properties of selected water bodies were performed in EKW to evaluate the seasonal variation, and found to be satisfactory. Range of physicochemical parameters within the permissible limit is ideal for aquaculture in EKW (Sona et al. 2019). Water quality properties (BOD, pH, ammonia, and phosphate) within safe tolerance level is viable for fish production in the wetland (Mohan et al. 2019). Sometimes a small variation can be observed in a different location of wetland due to the weather and amount of sewage intake (EKWMA & WISA 2021). Moreover, the potential of nitrifying bacteria as environment-friendly probiotics and bioremediators were assessed for enhancing survival and fecundity of fish in the fisheries located in this region.

pH ranges between 4.0–6.5 and 9.0–11.0 are considered lethal for fishes because the pH of fish blood is 7.4 and larger deviation of the surrounding pH from the blood pH is undesirable (Viadero 2005). In this study, the pH value of the selected water bodies ranged between 6.75 and 7.27, which is within the permissible limit (7.0–8.5) for the biological productivity of fishes and that is recommended by the WBPCB. Similarly, a study by GFES working group (India-UK Water Centre) showed that pH got elevated and the range lies within 6.7 to 8.2 due to the regular use of lime by the farmers to maintain the acid–base balance (Allan & Tiwari 2020).

EKW has a tropical wet and dry climate (EKWMA & WISA 2021). Thus the variation in weather is a very common factor and the temperature variation may be due to change in climate and can be directly co-related with global warming (Roy et al. 2016). The temperature of water affects various other parameters of water, for instance, the viscosity of water increases at low temperature, which in turn diminishes the sedimentation efficiency of solid particles in water because high viscosity offers resistance to downward motion of particles. In addition, temperature is a key factor associated with the growth and survival of fishes. The optimum range of temperature for fish growth is 13–21 °C (Pörtner & Peck 2010); although the tolerable temperature range varies depending on the latitude (Jena et al. 2002). Variation in temperature (19.7–28.7 °C) was found to be within the desirable range for the growth and survival of fishes in the present study.

DO is essential for the sustenance of higher life forms; it maintains the balance of the population of various aquatic organisms and keeps the water body healthy. DO enters into the aquatic body mainly by direct diffusion through air and photosynthetic machinery of aquatic autotrophs. Similar to temperature, the DO level is also primarily related to the growth and survival of fishes. DO concentrations ranging from 5.0 to 6.5 mg/L in ponds are considered optimal for fish production. The DO may be higher due to the presence of probiotics by enhancing the mineralization of organic matter, and the photosynthesis is simultaneously elevating the level of DO by releasing oxygen (Padmavathi et al. 2012). EKWMA and WISA (EKWMA & WISA 2021) analyzed and reported that the DO may be increased in different sites of EKW in various season. A low DO level indicates a high degree of deterioration of water quality in terms of ammonia and nitrite toxicity and a high stocking density (Makori et al. 2017), which causes physiological stress to fishes (Mueller et al. 2017). In the present study, the DO level was found to be low during post-monsoon, which may be attributed to the increased run-off of agricultural wastes and industrial effluents into the drains, leading to high demand of DO. Trend in decreasing DO observed due to heavy sewage load (Roy et al. 2016).

BOD and COD are the two major properties that determine the quality of wastewater and thus their measurement is very important (Mukherjee & Dutta 2016). High contents of organic load as well as the high proliferation rate of microorganisms are considered as the causative factors for high BOD in water. Shallow ponds are efficient in removing BOD because of their low surface loading (Raud et al. 2013). In this study, we observed seasonal variations in the levels of BOD (13.75–144.33 mg/L) and COD (39.33–354.66 mg/L); the high BOD level during summer may be attributed to the increased metabolic activity of microbes. A gradual decline in the rate of BOD with increase in distance from Topsia suggests that lowering of BOD in fish tanks and at the discharge point is satisfactory for survival of fish in this region. A similar trend was observed in the seasonal variability of COD levels across different water bodies, which suggests that the microbial activity in fish ponds efficiently degrades organic pollutants that enter into the ponds through sewage discharges and agricultural runoffs. This result is further illustrated by Ghosh (2018) and WBPCB Report 2019–2020 (WBPCB 2019-20) that significant reduction in BOD and COD can be observed in the end point as compared to the start point.

TDS concentration may get elevated due to stagnation (Campos et al. 1992). Another study showed that TDS was highest in the monsoon and this range varied seasonally (Sheetal et al. 2016). In our study, variable TDS levels (less than 399.66 mg/L in fish tanks) were found in the selected ponds.

Phosphates are generally introduced in the form of orthophosphates, condensed phosphates, and organically bound phosphates. Low phosphate concentration in water is essential for plant growth; however, its excess concentration causes excessive growth of phytoplanktons, leading to the clogging of water ways and use of large amounts of oxygen that is toxic to aquatic species. Nitrate and phosphate showed a great degree of variation year wise in different water bodies depending on the amount of effluents (Roy et al. 2016). In this study, low level of orthophosphate was found in J tanks, N tanks and Ghusighata which indicates the removal of ortho-phosphate was satisfactory.

High ammonia and nitrite concentration negatively affects growth of aquatic species (Panigrahi et al. 2018). The concentration of nitrate in water increases probably because of nitrification, which involves the conversion of ammonia into nitrite and subsequently to nitrate. Therefore, in-pond measurements of both nitrate and ammonia are crucial to assess the extent of nitrification (Ebeling et al. 2006; Schveitzer et al. 2017). In the present study, a gradual decline in the level of ammonia (from 7.37 to 2.05 mg/L) and increase in level of nitrate (from 0.9 to 4.22 mg/L) from the inlet to the outlet point were observed, which suggests the role of microbial activity in optimizing water for fish survival. Furthermore, the seasonal variation in the levels of ammonia and nitrate could be attributed to the number of nitrifying bacteria in a particular season; a high level of ammonia during the post-monsoon period could be due to the low count of nitrifying bacteria in this season. Cébron et al. (2003) reported that the low concentration of ammonia and high concentration of nitrate in summer can be directly related with the presence of nitrifying bacteria. The amount of nitrifying bacteria decreases in late summer and early autumn (Cébron et al. 2003). Ammonia and nitrite concentration are the prime problem in fish farms, and this can be overcome by using probiotics responsible for nitrification like Nitrobacter and Pseudomonas (Suguna 2020).

Considering the optimum range of ammonia and nitrate concentrations in some water channels, selected strains were identified by 16S rDNA-PCR analysis using universal primers (NCBI-GenBank accession numbers: KF618620, KF618621, and KF618622 for Nitrobacter sp.; KF618623, KF618626, KF618624, and KF618625 for Nitrosomonas sp.) was previously published and reported (Saha et al. 2014). Further confirmation was carried out through amoA and nxrA functional gene analysis. This is more significant strategy for identification of nitrifying bacteria. amoA and nxrA genes are promising function-specific candidate to detect AOBs and NOBs in wastewater samples. AMO in Nitrosomonas sp. helps in ammonia oxidation, catalyzes the oxidation of TCE and other halogenated hydrocarbons. Thus, activated amoA is important for TCE degradation (Vannelli et al. 1990; Sayavedra-Soto et al. 2010; Qin 2015). TCE degradation activity of two strains (NSW3 and NBW2) were found to be excellent. Thus, application of these nitrifying bacteria (NSW3 and NBW2) are appropriate examples of co-metabolic bioremediation strategy which can also be used for other halogenated hydrocarbons bioremediation. Similar experiment was done by Berrelleza-Valdez et al. 2019 for bioremediation of TCE using nitrifying bacteria. They also developed lab-scale packed bed bioreactors for TCE removal in wastewater ecosystem (Berrelleza-Valdez et al. 2019).

Furthermore, the predominance of THB has been reported to decrease the load of pathogenic bacteria (Sehrawat et al. 2021) and control the level of ammonia and other harmful metabolites by converting waste into beneficial food resources (De et al. 2014). In our study, the THB count was found to be higher in the Nitrobacter- and Nitrosomonas-treated experimental tanks than in the control tanks, which suggest that the introduction of Nitrobacter sp. and Nitrosomonas sp. plays an important role in promoting the growth of beneficial bacteria. Taken together, our findings suggest that these microbial strains could be utilized as efficient bioremediators.

Probiotics provide numerous benefits to the host animal by improving the microbial balance in their intestine. They also promote the innate immunity of animals to fight against virus and bacteria. Studies have indicated that Nitrobacter and Nitrosomonas can be used as probiotics to improve the health and performance of cultured aquatic species (Sunitha & Padmavathi 2013). However, the results of studies regarding the benefits of probiotics are inconsistent, and no standardized protocol is available to assess the beneficial effects of probiotics on growth and health status of farmed fishes. Moreover, the selection of microorganism is a crucial step in the application of probiotics and depends on the host species and environment (De et al. 2014). To the best of our knowledge, this is the first study to assess the potential of nitrifying bacteria as probiotics in the bheries located in EKW. The results of our experiments indicated that the introduction of Nitrosomonas and Nitrobacter as probiotics improves the water quality. Additionally, drastic reduction in levels of ammonia, nitrite and a high survival rate of fish in the tank further indicated that the combination of Nitrosomonas and Nitrobacter could be an effective probiotic approach to improve the fish survival capacity. Therefore, the use of Nitrosomonas and Nitrobacter as probiotics improve the water quality and increase the tolerance of fish in contaminated water. This pilot scale experiment targeted towards the development of a starter nitrifying culture as probiotics to revive potential water pollution for aquaculture farms, but needs more validation. Ammonia is considered as one of the pollutants that affects the shrimp production. Thus, to reduce the ammonia concentration in shrimp farm nitrifying microbial community was applied for better shrimp production (Xu et al. 2020). Nitrifying bacteria along with lactobacillus is one of the best probiotic for enhancing fish production and maintenance of water quality parameters like temperature, DO, pH, ammonia, nitrite and nitrate (Karthik et al. 2016). Small scale experiments in different aquaculture farms using nitrifying bacteria as probiotics to promote the water quality and reduction in load of pathogenic bacteria were conducted (Padmavathi et al. 2012; Barik et al. 2018; Baskaran et al. 2020). Consequently, nitrifying bacteria can be used extensively as water probiotics in aquaculture for bioremediation.

Investigating the role of nitrifying bacteria only in TCE degradation is the limitation of our study. Because various contaminants are present in water, studies should assess the potential of these bacterial strains in degrading other harmful pollutants. Second, the isolation and characterization of other microbial communities were not performed. Because EKW plays a crucial role in detoxifying industrial effluents, the presence of other more efficient microbial communities is likely in this region. Further studies should focus on identifying other microbial communities capable of degrading harmful organic pollutants in EKW by using molecular approach owing to great diversity of the genus Nitrobacter and Nitrosomonas and inefficacy of conventional methods for the precise identification of microbial species.

CONCLUSION

With modernization and industrial development in and around Kolkata, threats like huge discharge of domestic sewage, industrial effluents, changes in weather condition and other factors are increasing rapidly. The problem is not only limited to the environmental protection but also an increasing thrust for the livelihood of the associated people. Sustainable development is the goal of modern biological research. Proper management, effective conservation and remediation strategy in EKW is important to achieve ecological sustainability and maintenance of socio-economic condition of the dependent livelihoods. Water quality is the key factor for a successful aquaculture operation. Our findings indicate that the water quality parameters vary significantly across the water bodies located in EKW and that the removal of sewage effluents from the inlet to outlet point is satisfactory. Comparative analysis of the physicochemical parameters showed that water was significant for fish production. The optimum range of nitrate and ammonia in water showed the extent of nitrification which indicates the presence of nitrifying bacteria in the selected ponds in our study. The previously identified nitrifying bacterial strains, NSW3 and NBW2, were found to degrade TCE. Nitrifying bacteria in bioremediation helps in regulating the wastewater. Integrated maintenance plan and preservation policy are the prime focus in the present time for water management, pollution control and sustainable development. To conclude, the application of ammonia and nitrite-oxidizing bacterial cultures directly into the aquaculture tanks is a promising, economical and eco-friendly approach to reduce the level of pollutants, improve the water quality, and promote the growth of cultured aquatic species. The findings can be useful as a reference for further research on bioremediation and application of probiotics in aquaculture. A multidisciplinary approach is required to eliminate all the serious threats and proper flourishment of EKW. Sufficient knowledge and information can be the key strategy for this approach along with strict government policies and regulations for monitoring the related aspects. The present study provides an excellent management approach for upgradation of economic value and ecological aspect of EKW in the near future.

ACKNOWLEDGEMENT

We thank Oriental Institute of Science and Technology, Burdwan, West Bengal, India for providing laboratory facilities, high-speed internet and computational laboratory facilities. We are also thankful to Jalla Bhumi Bachao Committee for providing us with the study area and permission for samples collection.

FUNDING INFORMATION

Dr Mousumi Saha acknowledges the financial support from the Department of Science and Technology, Government of India [No.F.SSD/SS/013/2009]. The contingency grant was used for the purchase of chemicals used in the different experiments. No additional grants were available to support the research and article processing charges.

DATA AVAILABILITY STATEMENT

All relevant data are included in the paper or its Supplementary Information.

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