Introduction

Freshwater is an irreplaceable source incessantly contaminated by anthropogenic activities (Mapfumo et al. 2002), and diminishing its quantity and quality (Dudgeon et al. 2006). Within the field of ecotoxicology, toxic metal comprising the plays an imperative implication (Ebrahimpour and Mushrifah 2010). Since their protracted persistence, lethality, and bioaccumulation, they get magnified through the ecological pyramid (Yousafzai et al. 2010) and lastly, assimilated by humans resulting in health risks (Agah et al. 2009). The toxic metals are accumulated in the aquatic ecosystems through the anthropogenic sources through wastewater from industries, sewage discharges, and atmospheric deposition (Sekabira et al. 2010). Toxic metal available in the sediments prove as good indicators of man-induced pollution, consequently transforming the geochemical nature (Jain et al. 2008; Chandrasekaran et al. 2015). The existence of metal traces and therefore, the quality of aquatic ecosystems are often assessed by examining the fish tissues in the tainted river systems. Fish gills embracing the lipophilic membrane transports the ingested particulate material, nutrients, and other feed together with the dissolved metals in water through ion exchange that are often absorbed into the body through ingestion (Mendil et al. 2005). Moreover, in fish liver is destained as the organ where the persistence of these pollutants takes place (Shinn et al. 2009). In which facilitates the contribution of supporting knowledge to analyze the changes in different fish tissues histological examination literally includes both acute and chronic cases (Stentiford et al. 2003). The assessment of lethal effects in water, sediment, and fish is of massive suggestion mutually for environmental protection and socio-economic reasons (Lin and Hwang 1998).

Freshwater fishes are now threatened on a global scale, substantiating the very fact that a vast number of fish species are getting imperiled (Jelks et al. 2008). Increase of fish populations may lead to an extensive significant natural source (Ebrahimi and Taherianfard 2011). Likewise, a cyprinid fish species Dawkinsia filamentosa (Valenciennes, 1844), in river Tamiraparani, Southern Western Ghats of India, has been declining recently because of the anthropogenic activities placing this under IUCN red list (Dahanukar et al. 2011). In the anthropogenic activities, such as the discharge of domestic sewage, agricultural runoff, sand mining, and the inflow of industrial wastewaters into the river Tamiraparani, are also responsible for heavy metals, which cause thorny interactions between water, soil, and tissues (Mohan et al. 2018). From that the previously reported as toxic metals are Pb, Cr and Cd content analysis on endemic fish species of Dawkinsia tambraparniei (Mohan et al. 2018) and Devario aequipinnatus (Arumugam and Ramaiah 2018) and sediments (Chandrasekaran et al. 2015). Ardura et al. (2013), DNA barcoding is often applied for fish diversity evaluation. The present study confirms that the utilization of COI gene barcoding will help classify the bulk of fish species in numerous river systems. This data might also help the conservation of threatened endemic fish (Bhat 2004), considering the toxic metal contents on the riverine environment. In the heavy metal contamination process, embedded multi-level factors must be discussed from the local level to the greater position to assess the molecular basis at the individual, population, and community levels (Picado et al. 2007). The phylogenetic analysis provides high-resolution documentation by comparing based on the genetic level within the population and demonstrates genetic variability with some other species of the genus (Arumugam and Ramaiah 2018). Therefore, this study was carried out to investigate the impact of toxic metals contamination levels in the water, sediment, and its accumulation in vital organs of Dawkinsia filamentosa. Based on the criteria, the present investigation focused on histological examination, length-weight relationship and molecular phylogenetic analysis of Dawkinsia filamentosa from five different trophic levels to check the hypothesis and to validate the fate of the species within the river Tamiraparani.

Material and methods

Study area

The Tamiraparani, one amongst the perennial river, and its covered area of the river basin is 5942 sq.km. It’s originated at the slope of Western Ghats ridge connecting Agasthiyamalai. More than 12 tributaries join the rivers as it runs down of which Servalar, Manimuthar, Gadana nadhi, Pachaiar and Chittar can be termed as major ones. The principal rainy season is from October to middle December. The geology of river basins it comprises of crystalline rocks of Archean age on the western portion and sedimentary rocks of tertiary and quaternary age on the eastern coastal area. From that, our study sites were lies between the longitudes N 08o41′00.1ʺ to 08o42′46.5ʺ and latitude E 77o25′44.6ʺ to 77o50′11.7ʺ. Samples were collected during the dry season (March to May) from five different sites of mid-reach river Tamiraparani like Aladiyur, Cheranmadevi, Kokkirakulam, Vannarapettai, and Vallanadu as shown in Fig. 1.

Fig. 1
figure 1

Map points out the study sites of River Tamiraparani, Tirunelveli, Tamil Nadu (S1- Aladiyur; S2- Cheranmadevi; S3- Kokkirakulam; S4- Vannarapettai; S5- Vallanadu)

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Sample collections

From the selected sites of the river Tamiraparani, the water and sediment samples were collected in polythene bottles and were refrigerated at 4 °C. The chosen fish D. filamentosa was collected from all the five localities by using mono filamentous gill nets and that they were kept in a plastic bucket containing water. The total length of each fish from the collected fish samples was measured by using the digital caliber in the millimeter (0.1–200 mm). Before weighing the fish samples, it had been blot dried with a portion of a clean and tidy hand towel. Later, the fish sampling weight was measured by using a digital weighing balance having a weighing range was from 0.1 mg to 1 kg. After measurements, fishes were released into the system without harm (Arumugam and Ramaiah 2018). Two samples of D. filamentosa were collected from each study site for toxic metals and genetic analysis. Specimens from wild populations were collected from local fishermen. None of the sampled species were endangered or protected. No permit was required for this study to be performed. There were no ethical considerations related to the experiment.

Toxic metal analyses

After capture, the fishes were frozen instantly at −20 °C for future scrutiny. Tissues such as gills and liver were detached from each specimen and stored in separate vials until analysis. Prior to the analysis, water, sediment and tissues were digested by using conc. nitric acid for 3 h at 120 °C in heat block equipped with appropriate glassware’s (APHA 2012). All the results were expressed in dry mass. All the matrixes were analyzed for Pb, Cd, and Cr by Atomic Absorption Spectrophotometer (AA-6300) (ROM Version 1.03). The operational parameter conditions for the measurement of toxic metals in the sample by AAS.

The results were expressed as µg L−1 for water, mg Kg−1 for sediments, and µg g−1 for fish tissue samples. All glassware and containers were cleaned with 20% nitric acid, finally rinsed with de-ionized ultrapure Milli-Q water for several times and oven-dried prior to use. Analytical grade nitric acid (Merck, Darmstadt, Germany) was used for each analysis.

Ecological Potential Risk index

The quality of sediment, approaches of potential ecological risk index (RI) of the metals was calculated in line with (Weber et al. 2013) and (Hakanson 1980), using the subsequent formula as

$$C_f^i = C_s^i/C_r^i \times T_r^i = E_r^i,\,RI = {\sum} {E_r^i}$$

Where Cif is that the element contamination factor, Cis is the concentration of the elements in sediments; Cir is a reference value for toxic metals. Tir is the toxic-response factor for given toxic metals. Further, the potential ecological risk indices Eir and RI are the sum of the potential risk of the individual toxic metal. The potential ecological risk for a single regulator (Eir) follows a ranking with the low risk (<40), moderate (40 ≤ Eir < 80), considerable (80 ≤ Eir < 160), high (160 ≤ Eir < 320) and extremely high (Eir ≥ 80). RI is that the total toxic metals potential ecological risk index and represents the sensitivity of various biological communities to toxic compounds (Van Dyk and Pieterse 2008).

Histology analysis

The fish organs of D. filamentosa gill and liver samples were embedded in paraffin blocks. The embedded organs were sectioned at 4–5 μm thickness on a wax microtome and mounted on the glass slides for staining. Dried sections were stained with the Haematoxylin and Eosin (H&E) for the standard histological examination (Yi et al. 2011) and microscopic structure of tissues were observed under light microscopy (Optika vision Lite 2.1 version).

Length–weight relationship analysis

The data were being used to assess the correlation between total length and body weight of various individuals of D. filamentosa. The relationship between the total length and weight was determined according to a generalized linear regression model by using the subsequent formula as Cube law’s equation (Froese 2006).

$$W = aL^b$$

Where W = body weight of the fish, L = total length of the fish and ‘a’ & ‘b’ are the intercept and slope of the regression analysis.

In general, the length–weight relationship is calculated from the logarithmic base equivalent as log W = log a + b* log L as computed by using Microsoft Excel 2007. Prior to regression analysis of log W on log L, log-log plots of length and weight values were performed, and also Fulton’s type condition factor was calculated by K = W10/L3 (Le Cren 1951). Where, K = condition factor; W = weight of the fish in grams; L = length of the fish in millimeters. The 95% confidence limits of ‘b’ were calculated to estimate the differences between sexes and growth.

DNA extraction and amplification

Genomic DNA was isolated from the fin clips using NucleoSpin® Tissue Kit (Macherey-Nagel) following the manufacturer’s instructions. The extracted DNA sample was stored at −20 °C after confirmation by 1% agarose gel electrophoresis. After the PCR amplification of COI gene was amplified, reactions were carried out in a 20 μl reaction volume, which contained 1X Phire PCR buffer (contains 1.5 mM MgCl2), 0.2 mM each dNTPs (dATP, dGTP, dCTP and dTTP), 1 μl DNA, 0.2 μl Phire Hotstart II DNA polymerase enzyme, 5pM of forward COIAL 5ʹTCAACCAACCACAAAGACATTGGCAC3ʹ and COIAR 5ʹTAGACTTCTGGGTGGCCAAAGAATCA3ʹ reverse primers (Ward 2009). The PCR amplification was carried out in a PCR thermal cycler (Gene Amp PCR System 9700, Applied Biosystems) using the Big Dye Terminatorv3.1 Cycle Sequencing Kit (Applied Biosystems, USA) following manufactures protocol in ABI 3500 DNA Analyzer.

Sequence analysis

Geneious Pro v5.1 was used to perform sequence alignment and editing. The MEGA5 software package has been used to execute the phylogenetic interpretation of COI gene sequence data (Tamura et al. 2011). From the evolutionary of phylogenetic and number substitutions measured in five nucleotide sequences based on the Tamura–Nei model (Tamura and Nei 1993).

Statistical analysis

The data were performed statistically through the analysis of Principal components and correlation matrix and two-way ANOVA process. A Correlation significant at 0.01 levels was performed with IBM SPSS Statistics ver. 20. The Positive Matrix Factorization (PMF) was applied to the data sets using the EPA PMF5.0 software. PMF is an advanced factor analysis technique based on a least-square fit approach (Paatero and Hopke 2003).The regression parameters of coefficient value r2, ‘a’ and ‘b’ value were calculated by using the paleontological statistics package of PAST 2.14 version software.

Results

Water quality parameters

The physicochemical parameters of the river water like temperature, pH, dissolved oxygen (DO), biological oxygen demand (BOD), etc., are represented in Table 1. The values of temperature were ranged from 21 to 24.33 °C at the sites of river Tamiraparani. The average pH values were ranged from 7.38 to 7.78, (Table 1). The values of dissolved oxygen were decreased, ranged from 5.32 to 5.90 mg/l, due to the domestic wastages disposal, which leads to an increase in temperature and affects the water body determined by the oxygen imbalance of the riverine ecosystem. Biological Oxygen Demand was recorded higher value as 4.67 mg/l at the sampling site. In the present study, water hardness ranged from 80 to 88.6 mg/l in river Tamiraparani, indicating the level of hardness was slightly declined in the river conditions.

Table 1 Physico-chemical conditions in the preferred areas of river Tamiraparani
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Concentration of toxic metals

The results of toxic elements concentrations for each sampling site for water, sediments, and tissues are shown in Table 2. The significance of toxic metals in contaminated water included lead, cadmium and chromium, and metal accumulation was found to have been in the order of Pb > Cr > Cd in the Tamiraparani River. The metal content ranges as follows: Pb (0.56–0.46), Cr (1.89–1.70), Cd (1.35–1) µg/L in water; Pb (4–2), Cr (55–26), Cd (16–8) µg/Kg in sediment; Pb (0.16–0.06), Cr (0.15–0.12), Cd (0.17–11) µg/g in gill and Pb (0.11–0.05), Cr (0.12–0.10), Cd (0.12–06) µg/g in liver. The mean concentrations of these metals were 0.52, 1.79 and 1.13 in water; 2.60, 42.60 and 11.80 in sediments; 0.12, 0.14, 0.14 in gill and 0.08, 0.11 and 0.08 in liver respectively. Among the PCA analysis shows the variability of 94.66% in water, 89.52% in sediment, and 96.83 in gills and 79.14 in the liver; Eigenvalue variability in water, sediments, and tissues of gill and liver (4.30, 10.08, 2.79, and 18.21%, respectively) are presented in Table 2.The obtained results indicated that the Cr and Cd levels found in the sediments, water, and tissues of species D. filamentosa from the study area seem to be toxic to the riverine ecosystems and public health. Among them, the observed concentration ranges were found in the order as Pb > Cr > Cd.

Table 2 Toxic metals content in Water, Sediments and tissues of D. filamentosa, and PCA analysis and Correlation coefficient from the samples of river Tamiraparani
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Likewise, Statistical analysis remains to comprehend the association of metals with water, sediment, and organs to infer the hidden manner (El-Hasan et al. 2006). Pearson’s correlation of toxic metals studied in the river Tamiraparani is summarized in Table 2, which shows a very strong correlation between Pb–Cr (r = 0.95), Cd–Pb (r = 0.93) and Cd–Cr (r = 0.87) at P < 0.01 level of significant Pb–Cd–Cr. Toxic metals showing a very high correlation may indicate the same source. Cr also showed a positive correlation with Pb (r = 0.93) at P < 0.05 level significant, indicating its relationship with the Cr–Pb group. Pb–Cr–Cd comes mainly from the industrial activities and effluents through untreated domestic sewage discharges, and traffic sources also contribute to it. The mean concentration of toxic metals (Pb, Cd, and Cr) between the sites and within the fish species organ as the insignificant at P < 0.01 was shown in Table S1.

The correlation matrix for sediment properties was in a deliberate manner to interrelate with each other, and some of the parameter results were presented in Table 2. In addition, the Positive Matrix Factorization was applied to evaluate the quality of water with elements humiliating the river ecosystems. Overall, factor solution with the exception of a concentration with a percentage of elements can be found. In the resulting constrained run, the ratio moves to 60, and the Cr and Cd were also significantly reduced to around 40%, shown in Fig. 2.

Fig. 2
figure 2

PMF source profiles for the study sites of water parameters with metals concentration and percentage at Tamiraparani river (Blue squares indicate % contribution to total mass)

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Potential Ecological Risk Index

Table 3 revealed the order of the possible risk factor for toxic metals in sediments, both separately and absolutely. The terminology used to describe the risk factors Eir and RI were proposed (Weber et al. 2013), whereas Eir < 40 implies a low possible ecological risk; 40 < 80 is a significant ecological risk; 80 < 170 is a very high ecological risk. A low potential ecological risk is indicated by RI < 90; a mild ecological risk is 90 < RI < 160; a major ecological risk is 160 < RI < 180; and a very high ecological risk is RI > 180. As for all the five sites below 40, Table 3 indicates the possible ecological risk indices for Pb, Cr, indicating a slight potential ecological risk for all three metals at five locations. The significant factor triggering an ecological hazard was Cd the risk factor Eir values moderately increases at all the five study sites as 88.89–177.78. Although, the significant ecological risk (RI) shows at Vannarapettai (S4) was 180.41. These indexes for favored metals (Pb > Cr > Cd) showed that all samples were at low ecological risk as their individual values (Eir) were all below 40 and RI less than 90, except for Cd which had a high ecological risk potential at all sites of the Tamiraparani River.

Table 3 Reference values (Cin), Toxicity coefficient (Tir) and Potential risk indexes of Toxic metals in sediments from the study sites of the river Tamiraparani
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Histological examination of organs in Dawkinsia filamentosa

The histological examination of gill in Dawkinsia filamentosa showed significant variations in the selected five sites of river Tamiraparani. Such as Atrophy in Gill Filaments (AGF), Destruction of Primary Lamella (DPL), Dilation and Congestion in Blood vessels (D&C), Accumulation of Leukocytes (AL), Dilation and Congestion in Blood Vessels (D&CBV), Damage in Epithelial Lining (DEL), Lamellar Aneurysm (LA), Blood Congestion (BC), Complete Destruction of Primary Lamella & Secondary Lamella (CDPL&SL), Destruction of Pillar Cells (DPC), Cellular Degeneration (CD), Areas of Complete Architectural Loss (ACAL), Telangiectasis (T), Cellular Hypertrophy (CH), and Overall Edema (OE) are clearly visible in Fig. 3.

Fig. 3
figure 3

A–E Photomicrograph of Gill tissue damages showed in panel A Aladiyur (S1) DPL-Destruction of Primary Lamella; AL-Accumulation of Leukocytes; AGF- Atrophy in Gill Filaments; D&C- Dilation and Congestion in Blood vessels; B Cheranmadevi (S2) D&CBV- Dilation and Congestion in Blood Vessels; DA- Degenerative Alteration; C Kokkirakulam (S3) LA- Lamellar Aneurysm; DEL- Damage in Epithelial Lining; BC- Blood Congestion; D Vannarapettai (S4) CD- Cellular Degeneration; DPC- Destruction of Pillar Cells; CDPL&SL- Complete destruction of Primary Lamella & Secondary Lamella; E Vallanadu (S5) ACAL- Areas of Complete Architectural Loss; T-Telangiectasis; CH- Cellular Hypertrophy; OE- Overall Edema (S1- S3 & S5–40X; S4-100X; H&E) Bar = 25 µm for (A–E)

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Subsequently, the histological examination of liver in Dawkinsia filamentosa showed significant variations like Nuclear Degeneration (ND), Accumulation of Leukocytes (AL), Widened Sinusoids (WS), Leukocyte Infiltration (LI), Cytoplasmic Vacuolation (CV), Disintegration of Cell Boundaries (DCB), Hypertrophy Induction (HI) and Irregular Shaped Hepatocytes (ISH) are observed in Fig. 4.

Fig. 4
figure 4

A–E Photomicrograph of Liver tissue damages showed in panel (A) Aladiyur (S1) WS-Widened Sinusoids; ND-Nuclear Degeneration; AL-Accumulation of Leukocytes; B Cheranmadevi (S2) LI-Leukocyte Infiltration; ND-Nuclear Degeneration; V-Vacuolation; C Kokkirakulam (S3) ND-Nuclear Degeneration; LI-Leukocyte Infilteration; D Vannarapettai (S4) WS- Widened Sinusoids; CV- Cytoplasmic Vacuolation; E Vallanadu (S5) DCB- Disintegration of Cell Boundaries; HI-Hypertrophy Induction; ISH- Irregular Shaped Hepatocytes (S1-S5–40X; H&E). Bar = 25 µm for (A–E)

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Length–weight relationship of Dawkinsia filamentosa

A total of 92 fishes were evaluated in the present investigation. Estimated parameters of the length-weight relationship of the selected localization of D. filamentosa fish sample information were generated. The sampled varied from 72.04–137.81 mm of the total length and 17.78–26.96 g of the weight individually (Table 4). This evidence was inferred by a linear regression model revealing that the coefficient of determination (r2) was between 0.921–0.976 when the log weight figures were plotted for the corresponding log lengths as shown in Table 4. The utmost regression coefficient (r2 = 0.976) was obtained for Vallanadu (S5) site, and instead on the contrary in fact, the lowest regression coefficient (r2 = 0.921) was obtained for Cheranmadevi (S2) site as shown in Fig S1. Slope regression values of ‘b’ above 3 were observed in all sample locations. The value of the condition factor (K) was determined for D. filamentosa and extensively tested for the various positions of the river and mean K values were 1.62, 1.83, 1.63, 1.92 and 1.83 for Aladiyur (S1), Cheranmadevi (S2), Kokkirakulam (S3), Vannarapettai (S4) and Vallanadu (S5) respectively (Table 4). A similar mean K value was observed for filamentosa in nearly all study areas.

Table 4 Length–weight relationships regression parameter analysis of D. filamentosa from the selected locations of Tamiraparani River (‘a’ and ‘b’= parameters of the equation; r2 = Co-efficient of the determination)
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Phylogenetic analysis of Dawkinsia filamentosa

Identification of the genetic level variations among the fish species of Dawkinsia filamentosa was selected from the five sites of river Tamiraparani. The five sequences were examined using phylogenetic tree and also the similarity of nucleotide sequences were identified (Fig. 5). Among them, the populations of D. filamentosa have shown that Aladiyur (SITE–I) and Vallanadu (SITE–V) sites have been strongly dispersed relative to other sample sites. In the Vannarapettai (SITE–IV) site was entirely separate from the other four sites of the Tamiraparani River. However, the genetic variance of Dawkinsia filamentosa populations were explored in BLAST search with NCBI database was analyzed. As a result, the phylogenetic similarity sequences of D. filamentosa have been closely linked within the genus of the Dawkinsia species. Eventhough, the species showed analogy between the other groups of Clade I consisting of the D. tambraparniei, D. rubrotinctus, D. arulius, D. rohani and D. exclamatio. In the Clade II showed that the species were closely correlated with the Puntius sp. and P. conchonius. And in Clade III were intimately related within the same population of D. filamentosa respectively (Fig. 5). In order to contribute, the resemblance sequences of genetic distances for each species and closely related species as well as other outgroup fish species.

Fig. 5
figure 5

Molecular Phylogenetic analysis on five study sites of D. filamentosa with similarity sequences of BLAST in NCBI database by Maximum Likelihood method

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Discussion

The water quality parameter governs the hygienic nature of the river ecosystem (Effendi et al. 2015). Among them, the water temperature is one of the significant factors for a stream or river, which can cause harm to the aquatic organisms (Rathod and Khedkar 2011). In the present study, the dissolved oxygen was decreased and higher of biological oxygen demand levels, due to the wastewater from industries, and domestic wastages disposal, which leads to an increase in temperature at the sampling site. Saksena et al. (2008) reported that the implication in the dissolved oxygen is the concentration of oxygen dissolved in water is essential for several aquatic lives. However, the freshwater problems such as severe dissolved oxygen depletion and the fishes were killed in receiving water bodies (Penn et al. 2004). Despite that, the total hardness of water, which involves an ecological relay on the steady concentration of calcium and bicarbonate, delivers a major impact on the fish species as well as many other species (Sallenave 2012).

Among them, the unknown biological function of Pb, Cr, and non-essential toxic metal of Cd are harassing the aquatic lives (Munger et al. 1998; Sfakianakis et al. 2015). Our acquired results were also similar to the results reported by (Mastan 2014), as metals content was highly assembled in the livers of freshwater fish Labeo rohita and Channa striatus, indicating the stronger affinity of metallothioneins between lead and chromium (Ikem et al. 2003). The riverine areas and its aquatic species were highly contaminated through the contents of the metal of Cr and Cd since these study areas were located near to the textile mills, direct disturbances of agricultural wastes, fertilizers, transport corporations and other domestic wastes (Mohiuddin et al. 2012; Islam et al. 2015).

The toxic elements in samples showed a significant positive correlation suggestive of related sources on contribution to these toxic metals in the riverine ecosystem by the influencing anthropogenic activities (Bastami et al. 2012). The explicit of toxic metals in river water may reflect similar levels of contamination and loading pollution from the sources and identical behavior during their transport in the river systems (Ali et al. 2016). These results resolved along with the statistical tools that the dispersions of toxic substances were high and the significant correlations between these toxic metals, water, sediments in the study area (Alberto et al. 2001), may due to certain environmental conditions and biotic factors instigating ecological damage (Ural et al. 2012; Antal et al. 2013), in addition to the health of the public was confirmed statistically through risk assessment (Krishna and Mohan 2014). The danger of these toxic metals is in their persistent nature as they remain in the biota for a long period of time (Bolormaa et al. 2006; Yoon et al. 2008). In the dataset portion for each element, unexplained by model divided uncertainly and normally distributed as suggested by (Paatero and Hopke 2003). Reminisce that Pb, Cr and Cd will be shifted to destruct the environmental factor (Pancras et al. 2006).

The ecological risk index was used to measure the possible ecological risk of a potential element of contamination (Weber et al. 2013). The toxic metals and their effect on the ecological risk index used were model-based (Janadeleh and Jahangiri 2016). This hypothesis stated that the sediment was a significant sink for metal contamination and played a key role in the intake of toxic metals by fish (Yi et al. 2011). Cadmium has demonstrated that a high level of pollutants often gives the necessary information to decision-makers on the contamination status of the study area (Suresh et al. 2012). Toxic metals in sediments in the present study region, thus indicate a possible ecological risk due to the presence of Cd. Undoubtedly, the deposition of toxic metals would serve as histological damage to fish organs in the environment (Velma and Tchounwou 2010; Yancheva et al. 2016). Nevertheless, recent histological observations of gill and liver have indicated significant variations in the specified five sites of the Tamiraparani River. Hepatocyte vacuolization, hepatic cirrhosis, necrosis, shrinkage, parenchyma degeneration, nuclear pyknosis and increased of sinusoidal spaces are distinct differences between the toxic metals obtained, which appear to be countervailing mechanisms for proliferating a range of structural alterations (Olojo et al. 2005; Mohan et al. 2018; Arumugam and Ramaiah 2018).

As a result, lethal metals may influence fish development rate, and its condition factor demonstrated the exponential estimation of the slant relapse ‘b’ of the LWRs is the fundamental parameter, which clarifies the development example of fish (Froese 2006). Nonetheless, the condition factor K gives data on the physiological state of fish in connection and its welfare (Abdullahi et al. 2014). During the current investigation, it was confirmed that the riverine system generated a remarkable production of all the local rivers of D. filamentosa from their identical ‘b’ values above 3 in all areas, while the condition factor was the most suitable (K = 1.83) for the population. Based on the determined emphasis, the amassed toxic metals are all lethal accounts that have been largely expressed in the growth rate and the condition factor has fluctuated from one another in the different local investigations due to the dirtied natural sources (Sabaridasan et al. 2015; Arumugam and Ramaiah 2018) and diversification of D. tambraparniei in the encountered surveillance of the particular taxa leading to the evolutionary circumstances (Mohan et al. 2018). In the current analysis of phylogenetic study, the connection with the other classes of Clade I was rendered between D. tambraparniei, D. rubrotinctus, D. arulius, D. rohani,and D. exclamatio. Clade II also found that the species were significantly related with Puntius sp. and P. conchonius. D. filamentosa is a genetically distinct genus, according to evidence from the phylogenetic tree constructed for the partial sequence of genes from COI, and thus our data validated its recorded validity (Pethiyagoda et al. 2005). These essential structural differences dramatically reduce the rate of evolution within certain sequences and may result in a significant degree of conservation (Isenbarger et al. 2008). The present findings have shown that the diversity of fish declined due to the deposition of metals in riverine environments due to the drainage of domestic and industrial waste.

Comparison of the toxic metals with other studies

In previous studies of river Tamiraparani (Chandrasekaran et al. 2015) concluded that Cr and Cd create more toxic to the contaminated aquatic systems by inferring that the level of cadmium 1.64 ml/l at river Gadilam (Ambedkar and Muniyan 2012) and permissible limits of 0.005 ppm for fish food, even in low concentration could be harmful to living organisms (Tsui and Wang 2004). However, the present study reveals the fact that the Cr concentrations were correlating with river Cauvery, the level of Cr, 58.5 mg/kg−1(Bhuvaneshwari et al. 2016) and river Gomati, 8.15 mg kg−1 (Singh et al. 2005). Also, the earlier studies reported at Nigeria river as Cd level was 1.32 (Ekeanyanwu et al. 2010) and 6.46 in Karnaphulli river, Bangladesh (Ali et al. 2016). Even though, it might cause, at least, a minimum hazard to the aquatic systems indicating the moderate pollution to rivers (USEPA 2000; Gupta et al. 2008; BIS 2012; WHO 2012). The comparison of toxic metal contents with India’s local region and other rivers is shown (Table 5). It exposed that they are blooming near to the permissible limits and fascinates by reminding that the river showed a high proportion of natural process than the other river systems in India and references of toxicology in the world. In these consequences, Cr and Cd levels found in the samples of the river Tamiraparani areas were hazardous to the aquatic systems and also to the healthiness of the community.

Table 5 Comparison of the metals in the river (µg kg−1/µg L−1) with other studies in the world
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Conclusion

On the basis of the investigations at five sites, the metal concentration was highest in the sediment, water, and lowest in the gills and livers on the species of D. filamentosa. The present study also revealed the concentration of the toxic metal of Cr and Cd indicated that the major contaminants in sediments of the river Tamiraparani. The toxic metals of Pb and Cr have low potential risk from that the potential ecological risk values, but Cd showed higher ecological risk at study sites. As a result, the impact of toxic metals accumulation was significantly varied the histological alterations of gill and liver in D. filamentosa. In which was reflected extremely in the growth rate and condition factor of D. filamentosa and their genetic heterogeneity within the populations, it includes the creation of strategies to preserve genetic diversity. It may have their sources influenced by the discharge point of the textile industries, agricultural fertilizers, and other anthropogenic activities. So this study proves that the sources of toxic metals may cause hazardous to the aquatic systems and public health. However, our study may suggests that prior to conserve the river Tamiraparani from the proper guidelines of pollution control board to industrial and municipal wastewater drainage effluent treatment process, and create awareness to public by the government policy.