Introduction
The use of bioassays with standard test organisms represents a fundamental approach
in the definition of ecological risk in the aquatic environment for _I
chemicals products (Smiglak et al.,
2006). The microbial growth rate decreases with increased toxicity (Pardos, Benninghoff & Thomas, 1998; Gabrielson et al., 2002) and
to determine and to evaluate the presence of toxic substances in the aquatic
environment, the micro-algae Pseudokirchneriella subcapitata
(formerly known as Selenastrum capricornutum), have been used
(Wells & Coombe, 2006; Cho, Pham, Jeon & Yun, 2008). Aquatic
organisms that may be affected by pollutants are primary producers, which are
essential for the maintenance ofthe structure and function ofaquatic ecosystems, so
any negative effect on them will affect the primary trophic levels. Highly sensitive
microalgae to a high variety of toxic substances as P. subcapitata
are used as model systems for toxicity bioassays (Castillo, Vila & Neild, 2000; O'Farrel, Lombardo, Tezanos & Loez, 2002).
P. subcapitata is a planktonic species that lives in freshwater
ponds, lakes and rivers. Cells in cultures are solitary except during cell division.
The cells are helical, usually semi-circular curved in vegetative phase. The
diameter of the arc (154 - 360°) oscillates between 4.8 and 10.8 μm, width ratio of
1.6-4.4 μm. The chloroplast is parietal and lacks in pyrenoide. The reproduction is
by division of the stem cell in 2, 4 or 8 autosporas (Nygaard, Komárek, Kristiansen & Skulberg, 1986).
The strains of Pseudokirchneriella subcapitata used in laboratories
around the world have been isolated from the Nidelva River, Akershus, Norway, by
Olav Skulberg in 1959 (Norwegian Institute for Water Research (NIVA) - CHL 1) (Aruoja, 2011).
According to aquatic ecosystems classification, there are ecosystems of type lotic
(rivers, ravines), lentic (lakes) and lentic-lotic temporal (flooded jungle during
river overflow). The velocity of the current, the permanence of the water and the
temporary flood of each type determine aspects such as the ease of establishment of
aquatic communities, contributions and washes of nutrients and productivity, among
others (Pinilla, 2005). The lotic ecosystems
present a constant movement of water with hydrological, chemical and biological
characteristics determined by the climate, geology and vegetation of the watershed
(Payne, 1986; Allan, 1995).
Many developed and developing countries face serious ecological and toxicological
problems derivative of the release of complex effluents and toxic substances to the
environment. To contend with this problem a wide range of biological tests are used
with fish and other aquatic organisms of various trophic levels for biological
monitoring and evaluation of toxicity (Bringmann
& Kuhn, 1980; Cairns, Dickson &
Westlake, 1976; Little, 1978;
Maciorowski, Sims, Little & Gerrard,
1981).
The lotic ecosystems of the rivers of the watershed of Camana and Majes are located
in southern Peru; their area of influence is mainly the Arequipa Region, but it also
includes a part of the Cusco and Puno regions. Along the watershed of Camana and
Majes the following activities are carried out: economic, agricultural-livestock
farming, mining and fishing; as a result of such human activities multiple
pollutants are discharged into the environment, under that consideration the
sampling stations were selected (Taparza, Grande, Majesl, Majes2, Camanal and
Camana2), from the watershed of Camana and Majes which are located in the provinces
such as Castilla, Caylloma, Camana, Condesuyos and Arequipa in the Peru's Arequipa
region (ANA, 2012).
This research proposes to determine the reliability of fast and simple
ecotoxicological bioassays in lotic ecosystems such as the rivers of Taparza, Grande
and Camana - Majes (Arequipa, Peru), using the Mean Effective Concentration
(EC50), categorizing it according to the toxicity range and growth
inhibition of Pseudokirchneriella subcapitata and compared to
physico-chemical analyzes that exceed the values of the National Environmental
Quality Standards (EQSs) and water quality guidelines of the World Health
Organization (WHO).
Materials and methods
Test organism
The microalga Pseudokirchneriella subcapitata (Korshikov) Hindak
(formerly named Raphidocelis subcapitata Korshikov and
Selenastrum capricornutum Printz), was the species used to
carry out ecotoxicological bioassays. They are easily available species (from
crop collections) and maintained in the laboratory under controlled conditions
and currently approved for regulatory purposes (Nalewajko & Olaveson, 1998; Lewis, 1990; Weyers,
Sokull-Kluttgen, Baraibar.Fentanes & Vollmer, 2000).
The microalga, kindly provided by NEC (National Environment Center) of the
University of Chile, Metropolitan Region, Santiago, Chile, was kept in the
Microbiology and Biotechnology Laboratory of the National University of San
Agustin (UNSA), Arequipa, Peru, from June to August 2016. It was cultured in 250
mL Erlenmeyer flasks, with 100 mL of culture medium adding one milliliter of
macronutrients and micronutrients in approximately 900 mL of purified water
(MILLI-Qs, Millipore, Billerica, MA, USA) according the EPA manual (USEPA, 1994). The culture of P.
subcapitata was maintained in a lighting chamber using an air pump
at 2000 lux continuous illumination and temperature at 24 - 25°C; Medium's pH
was adjusted to = 7.5 + 0.1 with 1N of NaOH or HCl. At the end of the culture,
an inoculum of 2.5 x 106 cells/ mL was normalized by counting the
Neubauer chamber from which 2 mL were diluted in 18 mL of fresh culture medium
in order to obtain an initial concentration of 104 cells/mL in each
test vial for ecotoxicological bioassays.
Study area
To evaluate the selected area of the lotic ecosystems of the Arequipa, Peru
region with the bioassays of the microalga P. subcapitata, the
identification of contaminant sources; the classification of natural bodies of
surface water and the parameters established in the National Environmental
Quality Standards (EQSs) was taken into account for water where the sampling
station E1 = Taparza river (791888 UTM East, 8333378 UTM North at 1544 meters
above sea level), located at 20 meters before the confluence with the Tipan
river, this place was chosen by the existing thermal waters, like the thermal
baths of Taparza, to about 10 Km bathed by a stream that descends of the skirts
of Coropuna, where are the springs of sulphurous thermal water. The thermal
water of Taparza in different points has cracks, it is a sandstone rock and
something metamorphic, giving off a strong smell of sulfuric gas.
In that spring, the water at the exit of the land has the temperature of 46.6 °C
and in the circular pool that serves as a bath reaches 44 °C. E2 = Grande river
(UTM East, 8238815 UTM North at 1386 meters above sea level), located at the
height of the Huario Bridge, passing through the Chuquibamba district of the
province of Condesuyos, which has important economic activities such as
agriculture and cattle. E3 = Majes1 river (769459 UTM Este, 8220997 UTM Norte at
619 meters above sea level, located at the height of the Huancarqui Bridge in
the district of Huancarqui and the E4 = Majes2 river (772525 UTM Este, 8198706
UTM Norte at 373 meters above sea level), of the bridge Punta Colorada of the
district of Corire; between the E3 and E4 are the district of Aplao, Huancarqui,
Uraca and Corire unloading their dumps to the Maj es river, also agriculture
predominates. E5 = The Camana1 river (745343 UTM East, 8169611 UTM North at 68
meters above sea level), located at the height of the Bocatoma El Brazo, place
chosen for sampling because it is located before all the discharges of Camana.
E6 = Camana2 river (740355 UTM Este, 8162246 UTM Norte at 17 meters above sea
level), located in the Montes Nuevos sector after all the discharges of Camana
and before reaching the sea (Figure 1)
(COPASA, 2012; ANA, 2012; UNSA,
2001).
Figure 1
Map of the sampling stations of the watershed Camana, Majes and
Colca; Arequipa - Peru : E1 = Taparza; E2 = Grande; E3 = Majes1; E4
= Majes2; E5 = Camana1; E6 = Camana2.
Physicochemical analysis
A analyzes of pH, dissolved oxygen (DO), chemical oxygen demand (COD),
biochemical oxygen demand (BOD), total suspended solids (TSS), electrical
conductivity, oils and fats, cyanide, Sulphides, Phosphates and Nitrates, of the
water samples, were determined according to the methodology described by APHA (2000).
Metal levels were determined by emission spectroscopy with source of inductively
coupled plasma ICP (Ocampo-Duque, Sierra,
Ferré-Huguet, Schuhmacher & Domingo, 2008). The physicochemical
data are shown in Table I.
Table I
Physicochemical analyzes of the sampling stations E1, E2, E3, E4,
E5 and E6 of the Camana Majes, Colca watershed, Arequipa, Peru 2016
and comparison with the “Peruvian of Environmental Quality Standards
(EQSs)” with categories 3 and 4 and water quality guidelines of the
World Health Organization (WHO
|
(EQS) Category 3* |
(EQS) Category 4 |
WHO |
Parameter |
Analysis |
Unity |
E1 |
E2 |
E3 |
E4 |
E5 |
E6 |
Irrigation of low and high steam
vegetables |
Animal drink |
Conservation of the aquatic
environmental |
Guidelines |
Flow |
in situ |
m3/s |
1.3 |
5 |
154.6 |
154.2 |
149.2 |
149.03 |
|
|
|
|
Temperature |
in situ |
(°C) |
20.6 |
21.6 |
18.75 |
18.45 |
18.5 |
18.75 |
|
|
|
|
pH |
in situ |
- |
8.6 |
8.75 |
8.2 |
8.06 |
8.41 |
8.41 |
6,5- 8,5 |
6,5- 8,5 |
6,5- 8,5 |
6,5- 8,5 |
Conductivity |
in situ |
μS/cm |
885.5 |
1172 |
561.6 |
996.1 |
650.5 |
655.2 |
<2000 |
≤5000 |
- |
n.a |
Dissolved Oxygen |
in situ |
mg/L |
6.42 |
6.78 |
7.08 |
6.75 |
8.24 |
8.32 |
≥4 |
> 5 |
≥4 |
n.a |
N-NO3- |
Laboratory |
mg/L |
<0.030 |
<0.030 |
0.231 |
0.363 |
0.341 |
0.396 |
10 |
50 |
10 |
50 |
PO43- |
Laboratory |
mg/L |
<0.030 |
<0.030 |
<0.030 |
<0.030 |
0.031 |
0.036 |
1 |
- |
0.5 |
n.a |
N-NH3 |
Laboratory |
mg/L |
0.021 |
<0.020 |
0.034 |
0.103 |
0.056 |
0.045 |
- |
- |
0.02 |
1.5 y 35 |
DBO5 |
Laboratory |
mg/L |
<2.00 |
<2.00 |
<2.00 |
<2.00 |
<2.00 |
<2.00 |
15 |
≤15 |
<10 |
n.a |
DQO |
Laboratory |
mg/L |
<10.0 |
<10.0 |
<10.0 |
<10.0 |
<10.0 |
<10.0 |
40 |
40 |
- |
n.a |
TC |
Laboratory |
NMP /100mLa |
//// |
490 |
79 |
7900a |
23 |
49 |
1000 |
1000 |
2000 |
n.a |
Oils and fats |
Laboratory |
mg/L |
<1.00 |
<1.00 |
<1.00 |
<1.00 |
<1.00 |
<1.00 |
1 |
1 |
- |
n.a |
Total Nitrogen |
Laboratory |
mg/L |
<1.00 |
<1.00 |
<1.00 |
<1.00 |
<1.00 |
<1.00 |
- |
- |
1.6 |
n.a |
Sulfide |
Laboratory |
mg/L |
<0.002 |
<0.002 |
<0.002 |
<0.002 |
<0.002 |
<0.010 |
0.05 |
0.05 |
0.002 |
n.a |
Wad Cyanide |
Laboratory |
mg/L |
<0.006 |
<0.006 |
<0.006 |
<0.006 |
<0.006 |
<0.006 |
0,1 |
0,1 |
- |
n.a |
B |
Laboratory |
mg/L |
0.553 |
1.385 |
0.36 |
0.384 |
0.477 |
0.47 |
0,5 - 6 |
5 |
- |
2.4 |
Na |
Laboratory |
mg/L |
185.94 |
301.44 |
226.65 |
194.83 |
171.33 |
232.74 |
200 |
- |
- |
50 |
Al |
Laboratory |
mg/L |
0.55 |
0.02 |
18.05a |
19.64a |
1.68 |
1.68 |
5 |
5 |
- |
0.2 |
Ti |
Laboratory |
mg/L |
0.0158 |
0.0052 |
0.091 |
0.087 |
0.038 |
0.0393 |
- |
- |
- |
n.a |
Cr |
Laboratory |
mg/L |
0.006 |
0.005 |
0.0098 |
0.0136 |
<0.0004 |
<0.0004 |
- |
- |
- |
0,05 |
Mn |
Laboratory |
mg/L |
0.0202 |
0.0424 |
0.7426a |
0.8144a |
0.1583a |
0.1528a |
0,2 |
0,2 |
- |
0.1 |
Cu |
Laboratory |
mg/L |
0.0202 |
0.0012 |
0.0363 |
0.0407 |
0.0044 |
0.0039 |
0,2 |
0,05 |
0,02 |
2 |
Zn |
Laboratory |
mg/L |
0.008 |
0.005 |
0.019 |
0.163 |
0.053 |
0.026 |
2 |
24 |
0,03 |
3 |
As |
Laboratory |
mg/L |
0.003 |
0.062 |
0.019 |
0.017 |
0.014 |
0.012 |
0,05 |
0.1 |
0,05 |
0.01 |
Se |
Laboratory |
mg/L |
0.005 |
<0.003 |
<0.003 |
<0.003 |
<0.003 |
<0.003 |
0,05 |
0,05 |
- |
n.a |
Ag |
Laboratory |
mg/L |
<0.0005 |
<0.0005 |
<0.0005 |
<0.0005 |
<0.0005 |
<0.0005 |
0,05 |
0,05 |
- |
n.a |
Cd |
Laboratory |
mg/L |
<0.0004 |
<0.0004 |
0.0018 |
0.0023 |
<0.0004 |
<0.0004 |
0,005 |
0.01 |
0,004 |
0.003 |
Sn |
Laboratory |
mg/L |
<0.001 |
0.001 |
<0.001 |
<0.001 |
<0.001 |
<0.001 |
- |
- |
- |
- |
Sb |
Laboratory |
mg/L |
<0.002 |
<0.002 |
<0.002 |
<0.002 |
<0.002 |
<0.002 |
- |
- |
- |
n.a |
Ba Total |
Laboratory |
mg/L |
0.025 |
0.046 |
0.298 |
0.293 |
0.064 |
0.063 |
0.7 |
- |
0.7 |
0.7 |
Hg |
Laboratory |
mg/L |
<0.0001 |
<0.0001 |
<0.0001 |
<0.0001 |
<0.0001 |
<0.0001 |
0,001 |
0,001 |
0,001 |
0.006 |
Pb |
Laboratory |
mg/L |
0.0102 |
0.0095 |
0.0413 |
0.046 |
0.0113 |
0.0109 |
0,05 |
0,05 |
0,001 |
0.01 |
Fe |
Laboratory |
mg/L |
0.382 |
0.026 |
15.120a |
19.510a |
1.9a |
1.893a |
1 |
1 |
- |
n.a |
P Total |
Laboratory |
mg/L |
0.023 |
0.014 |
1.049 |
1.348 |
0.173 |
0.168 |
- |
- |
- |
n.a |
Be Total |
Laboratory |
mg/L |
<0.0002 |
0.0002 |
0.0009 |
0.0011 |
<0.0002 |
<0.0002 |
- |
0.1 |
- |
n.a |
Ca Total |
Laboratory |
mg/L |
<0.0002 |
0.0002 |
0.0009 |
0.0011 |
<0.0002 |
<0.0002 |
200 |
- |
- |
200 |
Ce |
Laboratory |
mg/L |
0.006 |
0.003 |
0.054 |
0.05 |
0.006 |
0.008 |
- |
- |
- |
n.a |
Co Total |
Laboratory |
mg/L |
<0.0003 |
<0.0003 |
0.0108 |
0.0132 |
<0.0003 |
<0.0003 |
0,05 |
1 |
- |
n.a |
K Total |
Laboratory |
mg/L |
9.33 |
20.19 |
8.03 |
9.9 |
5.89 |
5.85 |
- |
- |
- |
n.a |
Li Total |
Laboratory |
mg/L |
0.027 |
0.177 |
0.128 |
0.157 |
0.109 |
0.108 |
2,5 |
2,5 |
- |
n.a |
Mg Total |
Laboratory |
mg/L |
34.15 |
28.46 |
24.39 |
39.5 |
13.25 |
12.97 |
150 |
150 |
- |
n.a |
Mo Total |
Laboratory |
mg/L |
<0.002 |
0.002 |
<0.002 |
<0.002 |
<0.002 |
<0.002 |
- |
- |
- |
n.a |
Ni Total |
Laboratory |
mg/L |
<0.0004 |
<0.0004 |
0.012 |
0.0206 |
<0.0004 |
<0.0004 |
0.2 |
0.2 |
0.025 |
0.07 |
STS |
Laboratory |
mg/L |
24.94 |
<3.00 |
1315a |
1493a |
106.4a |
114a |
- |
- |
≤25-100 |
n.a |
Free cyanide |
Laboratory |
mg/L |
<0.004 |
<0.004 |
<0.004 |
<0.004 |
<0.004 |
<0.004 |
- |
- |
0,022 |
n.a |
Ecotoxicological Bioassays
Ecotoxicological bioassays with P. subcapitata were carried out
on samples of water from the watershed of Majes, Camana and Colca at the
sampling stations: E1, E2, E3, E4, E5, E6 of static type, with the following
design: four concentrations per Bioassay; three replicates, 104
cell/mL exposure in each sampling unit. The concentrations were expressed in
percentages of 50%; 25%; 12.5% and 6.25% in relation to a positive control
consisting in water of a problem sample and a negative control consisting of a
buffer solution of 15 mg/L of NaHCO3. The sample unit for the
bioassays was test tubes containing 2.5 mL of solution. Growth and inhibition of
cell growth were evaluated at the same concentrations and expressed as volume
percentages of water. The cell density (N) was determined by direct count in a
microscope using the Neubauer camera of bright-line at 24, 48 and 72 h of
exposure and the growth rate (μ) in number of divisions (ISO, 1989).
Toxicity Tests
The results ofthe toxicity test were quantified in terms of average growth of
P. subcapitata by calculating the 10, 15, 20, 25 and 50% of
Effective Concentration (EC) values determined by the dose-response curve (Nyholm, Sorensen, Kusk & Christensen,
1992). At the same time, the toxicity units (TU) for each sampling
point in the growth of P. subcapitata were calculated according
to the Sprague equation (Sprague & Ramsay,
1965):
UT= (EC50)-1 x 100
Based on the toxicity values obtained in each bioassay for each mean Effective
Concentration (EC50) a toxicological category was attributed,
following the guidelines of Bulich (1982)
and Coleman & Quershi (1985) (Table II).
Table II
Toxicological categories of the aqueous samples according to the
results obtained using the ecotoxicological bioassays with
Pseudokirchneriella subcapitata (Bulich 1982; Coleman & Quershi,
1985).
EC
50
|
Toxicity Category |
Rank |
Toxicity Units |
< 25 |
Very Toxic |
1 |
>4 |
25 - 50 |
Toxic |
2 |
2 - 3.99 |
51 - 75 |
Moderately Toxic |
3 |
1.33 - 1.99 |
76-100 |
Slightly Toxic |
4 |
1.01-1.32 |
>100 |
Not Toxic |
5 |
< 1 |
Determination of pigment
The extraction and spectrophotometric determination of algal pigments were based
on APHA (1998). These measurements were
made on basis of protocols described by Rowan,
(1989) with the following formulas to calculate chlorophyll:
Where V1 is the extract volume (1); V2 is the volume of the
sample (l); L the length of the cuvette; 664a and 665b the optical density of
90% Acetone before and after of the acidification at 664 and 665 nm; to OD647,
OD664 and OD630 the optical density is 647, 664 and 630 nm; Ca and
Cb of chlorophylls a and b, respectively (mg/L) (Rai, Singh & Mallick, 1990).
Digital image analysis
Samples of the microalgae P. subcapitata from cultures grown
stained with acridine orange and mounted on slides with Dako to visualized in
Leica TCS-SP8 spectral confocal microscope (Wavelength, 425-520 nm) at Institute
of Antofagasta, Chile, for measuring the mean fluorescence intensity (MFI) of
data sets xy, using the software Leica confocal (Leica Microsystems CMS GmbH)
with the regions of interest (ROI.001) as a function of the software. Digital
image analyzes were performed using the free ImageJ 1.29 software, downloadable
from the http://rsb.info.nih.gov/ij site.
Analysis of data
The water samples were taken following the "National Protocol for Monitoring
the Quality of Natural Surface Water Bodies" (ANA, 2011).
For the evaluation of the surface water quality of the sampling stations, the
National Environmental Quality Standards (EQSs) for Water, established in
Supreme Decree N° 002-2008-MINAM, were used; and water quality guidelines for
the World Health Organization (WHO) (WHO,
1996; WHO, 2011) in order to
establish the level of concentration or the degree of elements, substances or
physical, chemical and biological, parameters present in water, in its condition
of receptor body and basic component of aquatic ecosystems, which do not
represent significant risk to human health neither the environment. The
parameters that were evaluated in situ correspond to the
measurement of pH, Dissolved Oxygen (DO), temperature and electrical
conductivity, using the Multiparameter Equipment, according to the application
of the "Peruvian national protocol for monitoring the quality of natural
bodies of surface water".
A multivariate Principal Component Analysis (PCA) was used to relate and order
the physicochemical analyzes and sampling points of the watershed of Camana and
Majes with the statistical program Minitab 17 (http://www.minitab.com).
Data processing was performed using an Analysis of Variance ANOVA to evaluate the
growth of P. subcapitata by effect of different
ecotoxicological bioassays and concentrations every 24 hours for three days and
a Tukey multiple contrast test was used to evaluate the Growth groups to
bioassays and concentrations using the statistical program SPSS vers. 20.0
(http://www-01.ibm.com).
To correlate the growth inhibition of P. subcapitata and
physicochemical analyzes of the sampling stations E1, E2, E3, E4, E5 and E6, a
Student's t test of bivariate relation was used from the statistical program
SPSS vers. 20.0 (http://www-01.ibm.com).
At the end of the biological tests, the concentration % of the sample, which
produces 50% of the specified effect (Mean Effective Concentration,
EC50), was determined using the statistical program
Regtox_EV7.0.7 (http://eric.vindimian.9online.fr).
Results
Physical-chemical analysis of lotic systems
The results of the physicochemical analysis of samples collected in July 2016, in
the different monitored stations and their comparison with "Peruvian of
Environmental Quality Standards (EQSs)", in categories 3 and 4 and water
quality guidelines of the World Health Organization (WHO) are shown in the Table I.
Figure 2 shows the graph of Principal
Component Analysis (PCA) performed between physicochemical analyzes and sampling
points of the watershed Majes, Camana and Colca Arequipa- Peru, 2016. The
Principal Component 1 (PC) presented 78.9% of the variance and Principal
Component 2 (PC) presented 20.2% of the variance. The six sampling stations: E1;
E2; E3; E4; E5 and E6 were found to be associated with the first principal
component with positive correlation. The stations E1, E2, E5 and E6 had a
negative correlation to the second principal component.
Figure 2
Graph of Principal Component Analysis (PCA) between the
physicochemical analyzes and the six sampling points in the Taparza,
Grande and Camana-Majes rivers (Arequipa, Peru). E1 = Taparza; E2 =
Grande; E3 = Majes1; E4 = Majes2; E5 = Camana1 and E6 =
Camana2.
Evaluation of the growth rate of Pseudokirchneriella
subcapitata
In bioassays of 72 hours of exposure was observed a higher growth rate of
P. subcapitata in the sampling points of E2 = Grande river
at concentrations of 6.25%, and E2 = Grande river, E1 = Tapas river, E3 = Majes1
river at concentrations of 12.5%.
In concentrations of 50 and 100% the bioassays of E4 = Majes2 river and E3 =
Majes1 river, have a growth rate below zero, respectively (Figure 3a).
Figure 3
Rate growth and concentration vs. growth (%). a. Growth rate of
Pseudokirchneriella subcapitata according to
zones of the watershed of Camana and Majes (Arequipa, Peru) at 72
hours of the bioassay. Graphs of the Concentration-Response showing
the effects of the bioassay of the sampling point with the growth of
P. subcapitata with Effective Concentration
(EC) at different percentages at 72 hours. b. E1 = Taparza; c. E2 =
Grande; d. E3 = Majes1; e. E4 = Majes2; f. E5 = Camana1; g. E6 =
Camana2.
Ecotoxicity
The results indicated that at 72 h the values of the mean Effective Concentration
(EC50) for the growth of P. subcapitata at the
six sampling points presented the following decreasing order E1 (Taparza) = E6
(Camana2) > E2 (Grande) > E5 (Camana1) > E3 (Majes1) > E4 (Majes2),
where the lowest EC50 are observed at sampling points E4 with 57.43%
and E3 with 60.7%, being concentrations for growth of half of the population of
P. subcapitata (Figure
3b, c, d, e, f, g and
Table III).
Table III
Results of the toxicity test (EC50 = Mean Effective Concentration
in percentage) with the growth inhibition of P
subcapitata at 72 hours.
Sampling points
|
EC5
|
EC10
|
EC15
|
EC20
|
EC25
|
EC50
|
TU50
|
TC
|
E1=Taparza
|
23.97 |
36.31 |
48.05 |
60.04 |
72.68 |
157.14 |
0.64 |
5 |
E2=Grande
|
2.59 |
5.59 |
9.39 |
14.18 |
20.2 |
84.2 |
1.19 |
4 |
E3=Majes1
|
27.27 |
32.54 |
36.66 |
40.3 |
43.72 |
60.7 |
1.65 |
3 |
E4=Majes2
|
14.57 |
19.72 |
24.2 |
28.47 |
32.72 |
57.43 |
1.74 |
3 |
E5=Camana1
|
8.79 |
13.66 |
18.38 |
23.27 |
28.49 |
64.5 |
1.5 |
3 |
E6=Camana2
|
89.07 |
93.88 |
96.99 |
99.39 |
>100 |
109.57 |
0.91 |
5 |
Besides, the values of the Effective Concentration (EC) at different percentages
(EC5, EC10, EC15, EC25,
EC50) in the growth of P. sub capitata were
calculated to compare the relative toxicity of the river water using the
Toxicity Units (TU). According to the data shown in the Table III, the sampling
points E1 and E5 were categorized as non-toxic; E2 as slightly toxic, and; E3
and E4 as moderately toxic.
Sensitivity of P. subcapitata to exposure of metals
that exceeded the limits of EQSs and WHO
The sensitivity of the microalga was evaluated by determination of pigments
(chlorophyll a and b), growth rate, EC50 and use of confocal
fluorescence microscopy, together considered as a versatile, reliable and fast
method with multi-parametric optical detection having defined advantages in
bioassays of growth inhibition.
There was a decrease in the growth rate of P. subcapitata as the
concentrations of Al, Fe and Mn increased, which was accompanied with a decrease
in concentrations of chlorophyll a and chlorophyll b. The lowest growth rates of
P. subcapitata were observed in bioassays with high
concentrations of Al and Fe. The concentrations of chlorophyll "a"
were higher than the concentrations of chlorophyll "b" in the
bioassays with Al, Fe and Mn with EC50 in the growth inhibition of
the microalga at 72 hours of exposure of 5.875 mg/L to Al; 0.548 mg/L to Fe; and
0.375 mg/L to Mn showing statistically highly significant differences (p <
0.01) (Figure 4a, b, c).
Figure 4
Effect of the concentration of Al, Fe and Mn on the microalga
Pseudokirchneriella subcapitata based in the
growth rate, concentration of chlorophyll a and b (Chl-a and Chl-b)
and mean effective concentration (EC50) at 72 hrs of
exposure. (a) Toxicity of
Al2(SO4)3, (b) Toxicity of
FeCl3, (c) Toxicity of MnCl2 in P.
subcapitata and (d) Graph in 3D with antagonistic
interaction between the bacterial growth of E. coli
and microalgal growth P. subcapitata.
In Figure 4d, bacterial-microalga
interactions were evaluated in laboratory conditions simulating freshwater
environments, where an antagonistic interaction between growth of microalgal
P. subcapitata and bacterial growth of Escherichia
coli, was observed; that is, a decrease in the growth of P.
subcapitata and an increase in the growth of E.
coli as the dilutions of LB liquid medium with E.
coli decrease.
The fluorescence detected in cultures of P. subcapitata
corresponding to an optical section "x" and "y" is shown in
Figures 5a, b, c, d, e,
f, g, h, i, j.
Figure 5
Images of Pseudokirchneriella subcapitata (a, c,
e, g, i). Representative confocal microscopy images of P.
subcapitata (63X, 40X) (b, d, f, h, j). Representative
phase contrast microscopy images of P. subcapitata
(63X, 40X) Bar scale 10 μm. MFI: emission ("y" axis) to
several wavelengths, ("x" axis); obtained from algae
cultures of P. subcapitata grown to different
concentrations of Al (k), Fe (l) and Mn (m).
In addition, the mean fluorescence intensities (MFI) at different wavelengths of
algae cultures grown at different concentrations of Al (Figure 5k), Fe (Figure
5l) and Mn (Figure 5m) were
plotted. In such graphs it is shown that:
(A) The maximum fluorescence (F) peak in the presence of aluminum corresponds to
518.6 nm in any element concentration (Figure
5k). That peak of fluorescence decreases while the concentration of
Al increases, and all the data showed statistically significant differences at P
< 0.05 (F = 125.3).
(B) The fluorescence at different concentrations of Fe (0, 1, 10 and 20 mg/L;
Figure 5l) and Mn (0; 0.4; 0.8 and 1
mg/L; Figure 5m), also showed a decrease as
the concentration of the elements increases, showing the maximum peak of
fluorescence to 518 nm. To both elements also statistically significant
differences were found at P < 0.05 Fe, F = 391,333; Mn, F = 19,896.
Discussion
We studied the ecotoxicological bioassays with Pseudokirchneriella
subcapitata in lotic ecosystems of the Arequipa Peruvian Region, like
the stations E1, E2, E3, E4, E5 and E6 compared to National Environmental Quality
Standards (EQSs) and guidelines of the water quality of the World Health
Organization (WHO), that will allow a rapid estimation of the effects of pollutants
on the growth ofP. subcapitata. This method involves three steps:
(1) Exposure of P. subcapitata to water samples from lotic
ecosystems; (2) Bioassays of 72 hours; and (3) Measurement of growth inhibition
every 24 hours.
This study has two important results. First, the intensity of the most polluted
points in lotic ecosystems through inhibition the growth of P.
subcapitata compared to the National Environmental Quality Standards
(EQSs) and guidelines of the water quality of the World Health Organization (WHO).
Second, the growth of P. subcapitata, Mean Effective Concentration
(EC50) and Toxicity Units (TU) at 72 hours in bioassays at the
sampling points were compared to toxicological categories established by Bulich (1982) and Coleman & Quershi (1985). The studies about the evaluation
of the growth rate of P. subcapitata in bioassays with samples from
the watershed of Camana, Majes and Colca, Arequipa, Peru were also reported by Huarachi et al. (2014), who
evaluated the toxicity in different points of the watershed.
Figure 3a presents the growth rate of
P. subcapitata to the water exposure of the different stations:
E1, E2, E3, E4, E5 and E6 where the lowest growth rate is reached at E3 with an
EC50 = 60.7% and E4 with an EC50 = 57.43% categorized as
moderately toxic according to Coleman & Qureshi
(1985), due to the presence of thermotolerant coliforms, aluminum,
manganese and iron surpassing the limit values of the EQSs for the districts of
Aplao, Huancarqui, Uraca and Corire unloading their dumping to the river of Majes
where a population dump was identified by a national company of sewage service
located in Majes; which there are collapsed oxidation ponds, an industrial dump was
also identified by a dairy company located in Majes that does not have a treatment
system to their effluent (ANA, 2012). After
exposure to the lotic ecosystems of the waters of the Limache estuary (central
Chile), it shows a lower growth rate of P. subcapitata in stations
with greater anthropic activity and in the discharge zone of the effluent of a water
treatment plant (Córdova, Gaete, Aránguiz &
Figueroa, 2009). The investigation of acute toxicity in P.
subcapitata in industrial effluents in the Delta region of the Pearl
River in China showed sensitivity to effluents from factories of electroplating and
electronic (Fang et al.,
2012). In the lotic ecosystem, Delta of the Ebro river, Spain the
microalga P. subcapitata presented sensitivity to herbicides such
as diuron, simazine and terbuthylazine (36%, 26% and 17% of toxicity, respectively),
(Köck et al., 2010).
Along the Sava river in the countries of Slovenia, Croatia, Bosnia and Herzegovina
and Serbia, the sampling positions were chosen to cover the Sava River watershed
Majes, Camana and Colca Arequipa- Peruvian, 2016, considering the impact of the Sava
River's pollution by their principal effluents (Savinja, Krka, Kolpa, Una, Vrbas,
Bosna and Drina), with 14 sampling stations where the Lukavec station presents a
growth rate of P. subcapitata in 40% being the most toxic sample
causing a growth inhibition of 20% (Källqvist
et al., 2008). In the Vistula river upstream of
Cracovia, Poland with six sampling stations (Lipowiec, Gora, Chelmek, Bobrek, Metkow
and Tyniec), the high toxicity with P. subcapitata is observed in
Chelmek and Teniec stations with high concentrations of Zn (Guéguen, Gilbin, Pardos & Dominik, 2004). The Wangyang
river in northern of China recorded the presence of sixteen antibiotics and the
ecotoxicological risk with P. subcapitata showed sensitivity with
Sulfadiazine, Ofloxacin, Roxithromycin and Erythromycin (Jiang et al., 2014). The toxicity tests of
water on a small urban river (Store Vejleâ, Denmark), which receives discharges from
urban runoff; a sample taken from this river was analyzed by a combination of
toxicity tests and chemical analysis, the tests with P. subcapitata
showed that the toxicity was due to the presence of copper (25 mg/L), (Christensen, Nakajima & Baun, 2006).
In the north of Morocco, the Sebou river and its affluent the Fez river, the highest
toxic effects are obtained with the inhibition of growth using the microalga
P. subcapitata being observed in a point of the Fez river where
the limit for ammonium and chromium is exceeded in comparison with the guidelines of
water quality of the World Health Organization's (Koukal et al., 2004). The effect of dissolved organic
matter on the growth of the microalga P. subcapitata in the lakes
of Korea, where the results demonstrated a high growth rate of P.
subcapitata, correlated with the dissolved organic matter hydrophobic
in five lakes under controlled conditions of nutrients (Lee et al., 2009). In the growth test with
P. subcapitata by leaching water from the hot pile of PCM -
Plovdiv, significant growth inhibition was observed from 24 to 72 hours of exposure
(Ivanova & Groudeva, 2006). In an in
situ bioassay with P. subcapitata, for freshwater environments,
growth inhibition was observed in impacted sites, demonstrating the sensitivity of
the test, where the nearest site was impacted by the discharge of effluents and the
farther downstream was moderately impacted (Moreira,
Soares & Ribeiro, 2004). A rapid and simple ecotoxicological analysis
allowed a reliable estimation of the effects of Simazine (CAT) or 3,5-dichlorophenol
(3,5 DCP) on the growth of P. subcapitata with the results of
inhibition tests of the standard growth with 72 hours of exposure (Katsumata, Koike, Nishikawa, Kazumura & Tsuchiya,
2006).
In the evaluation of impact of metals that exceeded the EQSs and WHO, in bioassays of
P. subcapitata with Al the CE50-96 = 5.875 mg/L
compared to the results of Satizabal, Andrade &
Zuñiga (1999), with an EC50-48 = 5.51 mg/L in
bioassays with Daphnia magna.
In the exposure to different concentrations of Fe inP subcapitata
the EC50-96 = 0.548 mg/L compared to the result of Shuhaimi-Othman, Nadzifah, Nur-Amalina & Umirah 2012 with
EC50-96 = 0.75 mg/L in aquatic organisms and in bioassays
with Mn EC50-96 = 0.375 mg/L compared to the value of EC50-96
= 8.3 mg/L in P. subcapitata according to Reimer (1999), being greater its found value. In interaction
bacterium-microalga according to Riquelme &
Avendaño-Herrera (2003), the mechanisms of these interactions are poorly
understood; future research should be directed at understanding the mode of action
of bacterium-microalga interactions at the molecular level.
In this work, was evaluated the fluorescence in the microalgae P.
subcapitata in response to different concentrations of
Al2(SO4)3, FeCl3 and
MnCl2 for a lapse of 72 hours. The toxic effect of the metals on
microalgal cells was evaluated using the orange acridine fluorochrome where a
decrease in fluorescence is observed as the concentration of metals increases.
Conclusions
The physicochemical analyzes present thermotolerant coliforms, Manganese and total
suspended solids in the Majes River that surpass the National Environmental Quality
Standards (EQSs) and water quality guidelines of the World Health Organization
(WHO), compared to a higher inhibition of growth of P. subcapitata
and a Mean Effective Concentration (EC50) categorized with moderate
toxicity. The principal advantages of these test systems are simple, cheap,
sensitive and reproducible, providing profitable results in a fast way. Considering
all the results presented in this work, along with other investigators (Huarachi et al. ,2004; Moreira et al., 2004), we
evaluated the impact of metals that exceeded the EQSs and WHO, so in the diversity,
the ecological importance of the metallic contamination could be applied with
techniques of confocal microscopy of fluorescence contributing with a model of broad
perspectives in future studies of the ecotoxicity of metals. Besides, our results,
according to Machado & Soares (2015),
support a fluorescence-based approach being useful to detect disturbance of cellular
characteristics. Therefore, fluorescent probes are useful diagnostic tools for
assessing the impact of toxins on specific targets of microalgae cells of P.
subcapitata.
Acknowledgements
The authors thank to Rodrigo Ramos Jiliberto of the NEC (National Environment Center)
of the University of Chile, Metropolitan Region Santiago, Chile; To the Thesis
Research Fund 2015 MEM; ATI15-02/ATI15-03 and seed project 5302 MEM from University
of Antofagasta, Chile. To Jaime Iglesias, German Flores and Jose Irigoin of the
Local Administration of Water Camana, Majes,Arequipa, Peru. The first author is
grateful to the Institute of Antofagasta, Chile and to the scholarship of studies of
the University of Antofagasta, Chile.
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