Molecular characterization and the effect of salinity on cyanobacterial diversity in the rice fields of Eastern Uttar Pradesh, India

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Background Salinity is known to affect almost half of the world's irrigated lands, especially rice fields. Furthermore, cyanobacteria, one of the critical inhabitants of rice fields have been characterized at molecular level from many different
  BioMed   Central Page 1 of 17 (page number not for citation purposes) Saline Systems Open Access Research Molecular characterization and the effect of salinity on cyanobacterial diversity in the rice fields of Eastern Uttar Pradesh, India  AshishKumarSrivastava 1 , PoonamBhargava 2 , ArvindKumar  2 , LalChandRai* 2  and BrettANeilan* 3  Address: 1 Department of Botany, School of Life Sciences, Mizoram University, Tanhril Campus, Aizawl-796009, India, 2 Molecular Biology Section, Center of Advanced Study in Botany, Banaras Hindu University, Varanasi-221005, India and 3 School of Biotechnology and Biomolecular Science,  The University of New South Wales, Sydney, NSW 2052, AustraliaEmail:;;; LalChandRai*; BrettANeilan** Corresponding authors Abstract Background: Salinity is known to affect almost half of the world's irrigated lands, especially ricefields. Furthermore, cyanobacteria, one of the critical inhabitants of rice fields have beencharacterized at molecular level from many different geographical locations. This study, for the firsttime, has examined the molecular diversity of cyanobacteria inhabiting Indian rice fields whichexperience various levels of salinity. Results: Ten physicochemical parameters were analyzed for samples collected from twentyexperimental sites. Electrical conductivity data were used to classify the soils and to investigaterelationship between soil salinity and cyanobacterial diversity. The cyanobacterial communitieswere analyzed using semi-nested 16S rRNA gene PCR and denaturing gradient gel electrophoresis.Out of 51 DGGE bands selected for sequencing only 31 which showed difference in sequenceswere subjected to further analysis. BLAST analysis revealed highest similarity for twenty nine of thesequences with cyanobacteria, and the other two to plant plastids. Clusters obtained based onmorphological and molecular attributes of cyanobacteria were correlated to soil salinity. Amongsix different clades, clades 1, 2, 4 and 6 contained cyanobacteria inhabiting normal or low saline(having EC < 4.0 ds m -1 ) to (high) saline soils (having EC > 4.0 ds m -1 ), however, clade 5 representedthe cyanobacteria inhabiting only saline soils. Whilst, clade 3 contained cyanobacteria from normalsoils. The presence of DGGE band corresponding to  Aulosira strains were present in large numberof soil indicating its wide distribution over a range of salinities, as were Nostoc  ,  Anabaena , and Hapalosiphon although to a lesser extent in the sites studied. Conclusion: Low salinity favored the presence of heterocystous cyanobacteria, while very highsalinity mainly supported the growth of non-heterocystous genera. High nitrogen content in thelow salt soils is proposed to be a result of reduced ammonia volatilization compared to the highsalt soils. Although many environmental factors could potentially determine the microbialcommunity present in these multidimensional ecosystems, changes in the diversity of cyanobacteriain rice fields was correlated to salinity. Published: 6 April 2009 Saline Systems  2009, 5 :4doi:10.1186/1746-1448-5-4Received: 13 January 2009Accepted: 6 April 2009This article is available from:© 2009 Srivastava et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (   ), which permits unrestricted use, distribution, and reproduction in any medium, provided the srcinal work is properly cited.  Saline Systems   2009, 5 :4 2 of 17 (page number not for citation purposes) Background  The Indian agriculture is suffering with many man-madeproblems like canal irrigation, pesticide and chemical fer-tilization application. However, the former is responsiblefor salt accumulation in the soil which is further expand-ing due to water-logging in paddy fields. Salinization ispredicted to result in 30% of farmable land loss globally  within the next 25 years, and up to 50% by the year 2050[1]. In developing countries like India and China, theproblem could be more serious due to the increasing demand for rice as a staple food. If water-logged condi-tions prevail for lengthy durations salinization of the soiloccurs and, in India, this is commonly known as the for-mation of Usar land [2]. High salt concentrations lead toa decline in soil fertility by adversely affecting the soilmicrobial flora, including nitrogen-fixing cyanobacteriaand therefore further decreasing rice productivity.Cyanobacteria, the ancient oxygen-evolving photoau-totrophs, are the dominant microbial inhabitants of ricefields. Members of the orders Nostocales and Stigonemat-ales assume a special significance in this environment [3].Salinity adversely affects photosynthesis and thereforeproductivity [4], the functioning of plasma membranes[5], ionic balance in the cells [6] and protein profiles [7,8] of some phototrophs including cyanobacteria. However,salinity does not affect all cyanobacteria to the sameextent due to their morphological and genomic diversity [9,10], and therefore the distribution of cyanobacterialcommunities in natural habitats is not uniform. The adap-tive ability of cyanobacteria to salinity makes them thesubject of intense biochemical and ecological investiga-tion [11]. The classical methods for cyanobacterial identificationand community assessment involve microscopic exami-nation [3,12,13]. This assessment has, however, been crit-icized on the grounds that morphology can vary considerably in response to fluctuations in environmentalconditions [14]. In addition, the perennating bodies of cyanobacteria such as hormogonia, akinetes and hetero-cysts may be difficult to characterize by microscopy andthus the actual diversity can be underestimated [15]. In view of the above, cyanobacterial diversity assessmentsand community analysis should be investigated by micro-scopic observation supplemented with a molecular taxon-omy. Therefore, cyanobacterial diversity assessmentsusing molecular tools have been widely applied [16]. Theapplication of denaturing gradient gel electrophoresis(DGGE) along with PCR for studying natural cyanobacte-rial assemblages has increased our understanding of their complexity in environmental samples [17]. Among the various gene sequences used to assess cyanobacterial bio-diversity, 16S rRNA gene has been applied most often[16].Cyanobacterial diversity has been assessed from a variety of geographical locations, including the Colorado plateau[18,19], exposed dolomite in central Switzerland [20], hot  springs [21], the McMurdo Ice Self [22], and Southern Bal-tic Sea [23] using a combination of 16S rRNA gene PCR and DGGE. A considerable number of studies have beendone on DGGE based identification and phylogenetic characterization of toxic cyanobacteria [24-26]. In con- trast to above, cyanobacteria have been characterized only at morphological level in rice fields of India [27,28],Bangladesh [29], Chile [30], Pakistan [31], Korea [32] and Uruguay [33]. However, the work of Song et al. [34] con- stitutes the only known report on the biodiversity assess-ment of cyanobacteria in rice paddy fields (Fujian, China)during September 2001 to January 2002 using molecular tools.Despite the considerable negative impact of salinity onphysiology of pure cultured cyanobacterium as observedunder laboratory conditions, nothing is known regarding its effect on the biodiversity of cyanobacteria in rice fieldshaving different salt levels. Thus there is a need to exam-ine how salinity-induced changes among other physico-chemical properties of soil affect the distribution of cyanobacteria in paddy fields. In view of the reports by Stal [35,10] that cyanobacteria have a remarkable yet var- ying flexibility to adapt to a wide range of environmentalconditions, we propose that the resilient physiologies of certain cyanobacteria, including exopolysaccharide pro-duction, afford resistance to higher salinity compared tostrains with relatively simpler morphologies. Further,high salinity inhibits ammonia volatilization [36], andthis would result in soils with high nitrogen content andfavor the proliferation of non-heterocystous cyanobacte-rial genera. This study was undertaken to provide first hand data on cyanobacterial diversity using PCR-DGGE,and correlate it to different salt levels of soil to investigatesalinity-induced changes in the distribution of cyanobac-teria in Indian rice fields. Further, how far the salinity affects the agriculturally important cyanobacteria was alsoexamined. Results and discussion Physicochemical analyses of soil Eight different parameters, Na + , K  + , Ca 2+ , Mg  2+ , Na +  /K  + ratio, SAR, EC and pH were taken into consideration for the measurement of salinity levels in soil. In addition tothis, available phosphorus and total nitrogen were alsoestimated to determine the nutritional status of the soil.PCA analysis was performed to correlate the soil proper-ties, especially those related to salinity, with the cyanobac-terial diversity. Soil properties change significantly due tosalinity in rice fields, which can ultimately determine bio-diversity and hence productivity. The PCA analysisrevealed two principal components (PC1 and PC2) with  Saline Systems   2009, 5 :4 3 of 17 (page number not for citation purposes) percentage variances of 43.51 and 19.42, respectively. Theabove-mentioned ten parameters distributed into threeclusters (Figure 1A): (i) phosphorus, Na +  /K  + ratio andMg  2+ , (ii) K  + alone, and (iii) the remaining six parameters. This suggests that there are three major physicochemical variables that could significantly affect the cyanobacterialdiversity in these rice fields. Among the different cationsexamined, Na + , which constituted the largest fraction of both soluble and exchangeable ions in the soil, had themost obvious influence on cyanobacterial distribution(indicated by the longest distance from the point of srcinin the PCA plot) [37]. This result is reflected in the obser- vation of Onkware [38] who observed deleterious effectsof soil salinity (mainly Na + ) on plant diversity and distri-bution in the Loburu delta of Kenya. The sampling sites showed a wide range of Na + concentra-tions (2.12 – 9.15 ppm) and EC (1.89 – 7.55 ds m -1 ),thereby indicating a saline-sodic nature of the soils [39].However, the highest EC (7.55 ds m -1 ) and Na + (9.15ppm) were observed in the soil of Rauri. In contrast tothis, the soils of Madhopur and Parasurampur had thelowest EC (1.89 ds m -1 ) and Na + (2.12 ppm) levels,respectively. The regression analysis between Na + and EC( P < 0.05) also showed a wide distribution of soil samples(Figure 1B). Further, K  + content in saline soils was very low; lowest in the Rajatalab soil samples. This probably contributes to high Na +  /K  + and thus the sparse populationof cyanobacteria observed since K  + is essential for mainte-nance of cellular homeostasis, cell turgor and protein syn-thesis [40]. K  + also plays a vital role in extremeenvironments, both as an extracellular signal and as anintracellular metabolic regulator [40] essential for growthand metabolism. Microscopically, the lower Na +  /K  + ratio was shown to support luxuriant growth of cyanobacterialmats. Although regression analysis revealed that cyano-bacterial diversity decreased with an increase in Na +  /K  + ratio, a significant correlation between the number of cyanobacterial phylotypes (in terms of DGGE bands) andNa +  /K  + ratio was not confirmed. This result is in contrast to that reported by Parker et al. [41] who demonstrated K  + toxicity to  Microcystis in natural ponds. The soil of Makaraalso had a low Na +  /K  + ratio but was associated with asparse cyanobacterial population, however, this could beattributed to a high pH in this case. A high SAR recorded for these soils (Table 1), ensues lim-itation of Ca 2+ and Mg  2+ due to Na + -induced displacement of these cations [42], which may be responsible for thincyanobacterial population in these soils [39]. A relatively low concentration of Ca 2+ and very high Mg  2+ content of the soil from Jaddopur was due to the Mg  2+ induced defi-ciency of Ca 2+ [42]. In addition, the pH was found torange from neutral (Anei and Parsurampur, 7.40) tohighly alkaline (Rauri, 9.04). A significant negative corre-lation ( P < 0.05) observed between pH and the number of cyanobacteria in every soil sample, reflects the optimal pHfor cyanobacterial growth at 7.5. This is supported by thefact that most diverse cyanobacterial group of this study,  Anabaena and  Nostoc prefer neutral to slightly alkaline soil[27]. Further, the concentration of available phosphorusin the soils varied between 13.65 (Chauki) and 103.71ppm (Parsurampur). This fluctuation in the availability of phosphorus may also be due to the relative presence of monovalent (Na + and K  + ) and divalent (Ca 2+ and Mg  2+ )cations since the former are responsible for soluble andthe latter for insoluble phosphorus. However, the regres-sion analysis between available phosphorus and cyano-bacterial populations does not demonstrate any significant relation. This can be due to the fact that 1.0ppm available phosphorus has been reported to be suffi-cient for the growth of plants [43,44]. In contrast to this,available nitrogen was found to be negatively correlated( P < 0.05) with number of cyanobacteria (Figure 2B). Thiscan be explained in the light of the observation of Fernán-dez-Valiente et al. [45] who demonstrated inhibitory effect of nitrogen fertilizers on the growth of nitrogen-fix-ing cyanobacteria in paddy fields. Since the studied paddy fields have high diversity and population of nitrogen-fix-ing cyanobacteria, salinity-induced increase in availablenitrogen [36] may eliminate their population. The posi-tive correlation between available nitrogen with EC, Na + content, pH and SAR ( P < 0.05) finds support with theobservation of El-Karim et al. [36] that nitrogen availabil-ity in saline soil depends on EC, Na + and Ca 2+ content vis-a-vis SAR and pH.EC, the most appropriate parameter to characterize soilsalinity [46], was employed to classify the soil samplesinto two categories, normal (hereafter low) (< 4.0 ds m -1 )and saline (hereafter high salinity) (> 4.0 ds m -1 ) soil [39]. This classification divided the sample soils into the fol-lowing: (i) low salinity: Anei, Bardah, Bakesh, BHU, Jad-dopur, Kataka, Madhopur, Maharupur, Makara,Misirpura, and Phootia, and (ii) high salinity: Aswania,Bithwal, Chauki, Kartihan, Parsurampur, Rajatalab, Rauri,Sewapuri and Teduababa. The regression analysis showeda significant negative correlation ( P < 0.05) between thecyanobacterial population and EC (Figure 2A). Further,the influence of EC on cyanobacterial population wasfound highest among other parameters as reflected by ahigh r  value (0.75) in regression analysis.  Microscopic observation of cyanobacterial community  Microscopic observation of the samples revealed the pres-ence of diverse forms of cyanobacteria with most belong-ing to the order Nostocales. Cyanobacterial communitiesof rice fields were composed of the morphologically-defined genera  Anabaena, Nostoc, Aulosira, Cylindrosper-mum, Gloeotrichia, Rivularia and Tolypothrix of the order   Saline Systems   2009, 5 :4 4 of 17 (page number not for citation purposes) Statistical analysis of the data of soil samples Figure 1Statistical analysis of the data of soil samples . (A) The principal component analysis of the physicochemical properties of soil, and (B) the regression analysis between Na + concentration and electrical conductivity showing distribution of experimen-tal sites across the regression line. A  Electrical Conductivity (dS/m)    S  o   d   i  u  m    (  p  p  m   ) 1234567891012345678 r 2 = 0.8651, p < 0.005 B  Saline Systems   2009, 5 :4 5 of 17 (page number not for citation purposes) Regression analysis between number of cyanobacteria (DGGE bands) and (A) electrical conductivity, (B) total nitrogen Figure 2Regression analysis between number of cyanobacteria (DGGE bands) and (A) electrical conductivity, (B) total nitrogen . Analyses depict the effects of these parameters on cyanobacterial abundance in selected rice fields. Electrical conductivity (ds m -1 )    N  u  m   b  e  r  o   f  c  y  a  n  o   b  a  c   t  e  r   i  a   (   D   G   G   E   b  a  n   d  s   ) 1234561234567 Ar 2 = 0.8521, p < 0.005 Available nitrogen (ppm X 10 -1 )    N  u  m   b  e  r  o   f  c  y  a  n  o   b  a  c   t  e  r   i  a   (   D   G   G   E   b  a  n   d  s 2345612345 r 2 = 0.7651, p < 0.05 B
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