Prevalence of Autochthonous Vibrio cholerae and Role of Abiotic Environmental Factors in their Distribution along the Kerala-Karnataka Coast, India
Occurrence and distribution of Vibrio cholerae (VC) with respect to different abiotic environmental factors were studied for a period of three year from 2003-2005 and interpreted using Principal component analysis and Pearson correlation. Study reveals the serious dimensions of increase in VC population (2.67% in 2003, 5.33% in 2004 and 92% in 2005 in Mangalore) over the years. Among all stations, Kochi and Mangalore seems to be highly polluted. The PCA extracted four significant main components explains more than 75% of the variance. Of them the most contributing descriptors in the first PC (24.29%) were total nitrogen, silicate, temperature and V.cholerae. On the other hand V. cholerae showed significant positive correlation against temperature (0.01 levels) and also with total nitrogen and silicate (0.05 levels). Component plot showed that variables have tendency to accumulate into three distinct groups. V. cholerae and temperature belongs to one group and nutrients on the other group, which indicate that temperature and nutrients are the major factor governing the distribution of V. cholerae. The result of the study provides insight into the ecology of this aquatic species and is potentially important to the understanding of the epidemiology of cholerae on a global scale.
Received: November 09, 2009;
Accepted: June 12, 2010;
Published: July 01, 2010
Cholera has historically occurred in periodic epidemics, with the most severe
epidemics limited to few countries, namely India, Bangladesh and countries in
Africa and South America (World Health Organization, 2000)
and was suggested to be an autochthonous member of the aquatic environment (Thompson
et al., 2004). Nearly 200 V. cholerae serogroups have been
identified to date (Yamai et al., 1997), but
only two serogroups, serogroups 01 and 0139, are associated with epidemic cholera
(Keimer et al., 2007). Although, majority of
the environmental isolates of Vibrio cholerae are members of non-01,
non-139 serogroups which is considered to be non pathogenic, recent studies
have confirmed that natural population of Vibrio cholerae including Vibrio
cholerae non-01, non-139 isolates can serve as a precursor for new pathogenic
or epidemic strains (Faruque et al., 2002; Bik
et al., 1995).
Because of this inherent risk, it is relevant to understand the mechanisms
that affect the natural population of Vibrio cholerae in the environment.
Colwell (1996) reported that the presence of cholerae in the Indian subcontinent
and the re-emergence of cholera in other continents may highly dependent on
environmental factors. So, a better understanding of the relation to climate
would allow better planning for epidemics (Rodo et al.,
2000). In the present study, our first objective was to investigate the
occurrence of V. cholerae with respect to different abiotic environmental
factors (salinity, nutrients, temperature etc.) in order to understand how changing
environmental conditions might affect the ecology of V. cholerae in the
environment. Secondly we aimed to investigate the spatial variability and annual
distributional status of V. cholerae along the Kerala-Kernataka coast.
MATERIALS AND METHODS
The study area comprising five different stations, Veli, Neendakara, Kochi,
Mangalore and Karwar (Fig. 1), each with 5 sampling locations
nearshore (NS), 1, 3, 5 and 10 km from shore. Samples were collected during
the cruises of Sagar Purvi and Sagar Paschimi, the coastal research vessel of
DOD (Department of Ocean Development, Govt. of India) for a period of 3 years
(2003-2005). Water samples from surface, mid and bottom region were collected
using Niskin water sampler and sediment samples by Van-Veen grab. Analysis of
several parameters of water samples like pH, temperature, salinity, DO (dissolved
oxygen), BOD (bio-chemical oxygen demand), TSS (total suspended solids), turbidity
and nutrients (NO2-N, NO3-N, PO4-P) have been
carried out using standard procedures (Grasshoff, 1983).
Spread plate technique using 0.1 to 0.5 mL sample, was adopted for the Vibrio
cholerae and the results were reported in Colony Forming Units (CFU mL-1).
|| Study area
One gram of the sediment was dissolved in 100 mL sterile water was used for
the isolation of Vibrio cholerae from the sediment samples and the results
were expressed in CFU g-1. All the samples were plated onto TCBS
(thiosulphate citrate bile salts sucrose) agar, a medium that inhibits most
other normal faecal flora but supports the growth of the vibrios and were incubated
for 18-24 h. Vibrio cholerae colonies appear as smooth yellow colonies
with slightly raised centres (AOAC, 1995).
Each water quality data of a transect represent the over all mean of three
different seasons, i.e., pre-monsoon, monsoon and post-monsoon, including their
average values of surface, mid and bottom and it can mitigate the seasonal influence.
A correlation matrix was generated for understanding the degree of mutually
shared variability between different chemical water quality parameters and Vibrio
cholerae. Eigenvalues and Factor loadings for the correlation matrix also
were estimated. An Eigenvalue gives a measure of significance of the factor.
The Eigen values > 1 were considered as prominent factors as per the Kaiser
criterion (Kaiser, 1960), the factors with the highest
Eigenvalues are the most significant. After the correlation and Eigen values
were obtained, factor loadings were used to measure both the correlations and
regression weights between factors and variables. A rule of thumb frequently
used is that the absolute value of the factor loading greater than 0.3 is considered
significant, greater than 0.4 is more important and greater than 0.50 is very
important (Lawley and Maxwell, 1971).
RESULTS AND DISCUSSION
Distributional Status of Vibrio cholerae
Vibrio cholerae population showed wider fluctuation during the entire
annual study period (Fig. 2-6). During the
study the population level kept low in all stations during 2003 and 2004, but
has produced an increase in their population towards 2005. Almost all the stations
V. cholerae levels were 2 to 5 fold higher in 2005 than the values found
during 2003 and 2004. Sediment also produced the same output. Sediments reported
to have fairly high bacterial population than water. In general, V. cholerae
hoards in sediments at very high levels than the overlying water column. The
same was also reported by Nandini and Somashekar (1999),
who stated that sedimentation and adsorption of the microorganisms to sand and
clay particles culminated in the increase in the density of bacteria at the
bottom zone. Of the study Mangalore estuary reported with comparatively high
bacterial population of 3335 CFU mL-1 in water and 12500 CFU g-1
in sediment during 2005.
In all the stations V. cholerae population were more concentrated towards
shore region except in Veli where they are more documented towards the offshore
region. Ouseph et al. (2009) reported that the
fairly low microbial population reported in Veli near shore is attributed to
the discharge of acidic effluents from the nearby Titanium factory. Progressing
V. cholerae annual population in both water and sediment are depicted
in Fig. 7 and 8, respectively. The maximum percentage population
of 92% in water and 86.57% in sediment, both documented from Mangalore station
in 2005. In contradiction to the above high value the minimum of 2.67 and 2.99%,
respectively in both water and sediment were also reported from Mangalore in
2003, which clearly reveals progressing V. cholerae population over the
Status of Physico-Chemical Parameters
Water temperature showed variation from 24.0 to 34.0°C (mean of 28.56±2.07°C)
during the study period. The minimum and maximum temperature was noticed at
nearshore region of Veli (2003) and 5 km of Kochi (2003), respectively. Throughout
the study, the temperature of the bottom water was lower than the surface water.
Salinity ranged from 15.10 (Kochi-Estuary-2003) to 34.90 psu (Veli-10 km-2005)
with an overall mean of 30.60±5.19. The lower salinity in the Cochin
estuary may be due to the riverine influence. The pH fluctuated between 2.60
(Veli- NS-2003) and 8.27(Veli-5-2005) with mean of 7.81±0.97 and that
of total suspended solids accounted a variation of 2.30 mg L-1 (Karwar-NS-2005)
to 21.80 mg L-1 (Veli-1 km-2003) with mean of 8.17±4.45. The
low pH attributed in Veli may due to the impact of acidic effluents from the
TTP industry (Ouseph, 1993). The BOD oscillated between
0.52 mg L-1 (Veli-Nearshore-2003) to 2.02 mg L-1 (Neendakara-1
km-2005) with mean of 1.15±0.35. Dissolved oxygen fluctuated from 3.02
to 6.96 mg L-1 with a mean of 4.93± 0.67 mg L-1
and the lowest and highest was noticed at nearshore region of Veli (2005) and
5 km of Kochi (2005), respectively. In the over all scenario DO values were
comparatively higher in surface water than the bottom region which may be probably
due to the atmospheric turbulence. The lower oxygen content at the bottom could
also be attributed to oxygen consumption during the decomposition of organic
matter (Abowei, 2010).
Generally, bottom water showed higher concentrations of nutrients than the
surface water. Of the nutrient species, the nitrite-N varied from 0.04 μmol
L-1 (Veli-10 km-2003) to 1.38 μmol L-1 (Veli-10 km-2004)
with an over all mean of 0.52±0.30 and that of nitrate-N showed a variation
of 0.16 μmol L-1 (Veli-5 km-2003) to 11.23 μmol L-1
(Kochi-3 km-2003) with a mean of 4.15±2.21. The higher nitrite concentration
in Kochi may due to the increased nitrification process (Miranda
et al., 2008) prevailing in the environment. The average concentration
of silicate during the intact study period was 3.66±1.88 μmol L-1.
Inorganic phosphate concentration varied between 0.35 μmol L-1
(Mangalore-10 km-2005) to 2.95 μmol L-1 (Veli-Nearshore-2005)
with a mean of 1.45±0.60 and that of total phosphorous registered a variation
of 2.12 μmol L-1 (Veli-5 km-2003) to 10.0 μmol L-1
(Kochi-3 km-2003) with a mean of 4.15±1.62. The minimum concentration
of total nitrogen was 3.92 μmol L-1 (Veli-1 km-2005) and the
maximum was 33.14 μmol L-1 (Cochin-5 km-2003) with an overall
mean value of 12.11±4.52. Broadly, Cochin reported with higher concentration
of nutrients, may probably due to the release of nutrients from the interstitial
sediments owing to prevalent dredging activities (Joseph and
Ouseph, 2009; Sudhanandh et al., 2010) and
also owing to the unabated domestic waste disposal.
Correlation matrix (Table 1) revealed the existence of
a strong relation between V. cholerae and temperature at 0.01 level (p<0.01),
with total nitrogen at 0.05 level (p<0.05), and also with silicate at 0.01
level (p<0.01). Vibrio cholerae also showed a negative correlation
with salinity. Association found with Vibrio cholerae to temperature
were also reported by Siddique et al. (1992),
Glass et al. (1982) and Sack
et al. (2003) who stated that cholera outbreaks occur each year corresponding
to the warm seasons before and after the monsoon rains.
|| Correlation matrix showing the interrelationship of different
abiotic environmental factors and Vibrio cholerae
|**Correlation is significant at the 0.01 level (2-tailed),
*Correlation is significant at the 0.05 level (2-tailed)
|| Factor loading for different water quality parameters
Quick et al. (1995) reported that cholera epidemics
are strictly confined to the warm season. Thus temperature seems to be related
to the ability of vibrios to grow rapidly in aquatic environment. Furthermore,
the positive correlation found between V. cholerae to total nitrogen
suggest that Vibrios are favored in waters rich in organic nutrients
such as might be expected in areas heavily impacted by land runoff and wastewater
discharges. On the other hand negative correlation of salinity with total nitrogen,
nitrate and also with silicate 0.05 level (p<0.05) pointed out that sea water
was not the source for nutrients. Hence other human anthropogenic activities
including the sewage discharge and also the fresh water input which carry industrial
and agricultural wastes and other land drainage in the immediate vicinity of
the shore region are the major reasons for nutrient enrichment. Joseph
et al. (2008) observed fresh water run-off, sewage input from the
upper reaches of the backwaters and localized disturbance in the harbor as the
major sources of nutrients in the Cochin estuary which is in concordance with
Principal Component Analysis (PCA) extracted five Principal Components (PCS)
from the variance present in the data (Table 2). Of them the
first four factors (Eigen value >1) accounted for 75.67% of the observed
variation in water quality observations. Additional factors (5th) provided marginally
less explanatory capability and were not examined further.
|| PCA component plot showing the relativeness of different
Factor loadings (correlations between the variables and the extracted factors)
for the four retained Eigen values are also incorporated with the Table
2. The first principal component has a high positive loading of total nitrogen,
silicate, temperature, pH, Vibrio cholerae and negative loading of dissolved
oxygen and explains 24.29% of the total variance. This factor can be ascribed
to the variation of natural condition due to the influx of water which carries
heavy nutrient load and also global warming which effect the gases concentration,
temperature and influences the bacterial load. So, these components represent
the backwater discharge and global warming. Singh and Sarkar
(2003) observed an increasing trend of surface water temperature almost
through out the year with an increase of 0.03°C year-1 in the
annual mean due to global warming.
The second PC explained 20.70% of the total variance is found to be strongly
associated with NO2-N NO3-N and TSS with strong negative
loading of salinity and moderately negative loading of DO and pH which strongly
indicates that sea water is not the source of pollution. So this component represents
anthropogenic pollution sources and can be explained that high levels of dissolved
organic matter consume large amount of oxygen which is indicative of the negative
loading of DO (Panda et al., 2006) and nitrification
under oxic condition causes the reduction in water pH values (Kim
et al., 2003). The third factor is positively loaded with TSS, TP
and BOD and explained 18.46% of the total variance. This factor may be correlated
with the resuspended sediments through churning action by tidal currents. The
fourth factor is loaded with strong positive loading of TP and BOD and strong
negative loading of V. cholerae. This factor represents industrial effluents
especially acidic in nature which reduces the growth potential of V. choleare.
On the other hand, higher correlations were found with temperature to Vibrio
cholerae and Total nitrogen to silicate in the correlation matrix (Table
1) and also in the first principal component, explaining themselves as the
observed variance and could be considered the most descriminant variables.
The PCA loading plot, representing the scores of the sample (PC1 vs. PC2 vs. PC3) and relationship between the variable is shown in Fig. 9. All the variables were found to be distributed in three groups. Vibrio cholerae, temperature, salinity, biological oxygen demand and dissolved oxygen showed one group formed by temperature, attributed to the increased V. cholerae population due to global warming, second group constituted by total phosphorous, total nitrogen, silicate, nitrate and inorganic phosphate, might be due to an increase provoked by the nutrient enrichment and the third group constituted by total suspended solids and nitrite due to remobilization of sediments through churning action by tidal currents.
Study recapitulated that our coastal waters are stock up with autochthonous Vibrio cholerae and make an ample chance for disease out break. It is evident from the study that V. cholerae population demonstrates spatiotemporal correspondences with the environmental variations. Varifactors obtained from factor analysis and also significant correlation found with Vibrio cholerae to temperature and nutrients suggests that nutrient loading and global warming makes the organism thrive in the environment.
The authors wish to express deep sense of gratitude to Dr. M. Baba, Director, Centre for Earth Science Studies for providing facilities and encouragement. They are also grateful to Ministry of Earth Sciences for financial support to carry out the study under COMAPS programme.
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