Biochemical parameters and 18S rRNA gene sequence analysis amongst green microalgal strains from selected aquatic sites of Eastern India

Microalgae have been studied extensively due to their numerous applications in varied fields. Ecologically, microalgae occupy an important position at the base of aquatic food webs. Nutrient cycling and evolution of oxygen are the critical attributes which govern the equilibrium of an ecosystem, where microalgae play an essential role (Demirbas 2009). They possess a vast repertoire of high value products and can be used as biodiesel feedstock because of high rate of biomass production as compared to oil yielding plants (Chisti 2007; Groom et al. 2008; Stephens et al. 2010; Arbib et al. 2014). Therefore, it is desirable to identify, isolate and characterize new strains from different natural environments with high value content of bioproducts for use in commercial and industrial applications.

Morphological convergence has been reported in several commonly known groups of algae, where taxonomic units with similar morphologies are distantly placed in a phylogenetic tree (Krienitz et al. 2004). More than 35,000 species of microalgae are described in literature (Cheng & Ogden 2011) and their diversity is known to be far greater. The divergence of green lineage into distinct clades is established through molecular methods which confirms the structure-based hypothesis. According to this, the clade Chlorophyta comprises the green algae, of which several have been described, and the clade Streptophyta, which comprises a paraphyletic assembly of freshwater algae, has led to the evolution of land plants. A limited number of taxa have been studied for their multigene relationship data, due to which phylogenetic relationships between and within the main clades of the chlorophytes, namely Ulvophyceae, Trebouxiophyceae and Chlorophyceae, have not been completely recognized (Leliaert et al. 2012).

Screening and collection of microalgae is therefore vital to select optimal performing strains with desired traits. Moreover, ‘indigenous’ strains, which are naturally adapted to specific environments and climates, will be more competitive, efficient and sustainable. In this paper, we report an intensive study of 24 microalgal strains isolated from selected aquatic sites and one reference strain (MCC 25), for their specific biochemical parameters.

Water samples were collected from selected aquatic sites of India with the details mentioned in Table 1. The green microalgal strains were isolated following single cell isolation method using glass capillary tube having straight or curved tip (Andersen & Kawachi 2005). In total 24 green microalgal strains were isolated and purified from various aquatic sites. The reference strain (Nannochloropsis sp., MCC 25) was kindly given by Dr. Lothar Krinitz, Germany. These were grown and maintained in BG-11 (+N) medium, pH 7.0 at 28 ± 2 °C under a photoperiod of 16:8 h light–dark cycle with light intensity of 52–55 μmole photon/m²/s provided with cool white fluorescent tubes. Further, purification of the isolated cultures was attempted through serial dilution and plating. The cultures were hand shaken 2–3 times to avoid adherence to the sides of the flasks and the purity was routinely checked through microscopic observations. The isolated green algae were identified using keys given in standard monographs for morphological parameters (Iyengar & Desikachary 1981; Komárek & Fott 1983; Hindak 1988). The isolated and identified strains were maintained in N-enriched BG-11 medium under standard cultural conditions (Andersen & Kawachi 2005).

Out of 24 microalgal strains used for biochemical parameters, five selected strains, namely MCC 3, MCC 9, MCC 10, MCC 12, and MCC 19 were used for 18S rRNA gene sequencing. These five genera were selected for molecular identification based upon their area of isolation. These also showed desired content of total soluble proteins, carbohydrates and lipids. Homogenised suspension from the exponential phase of incubation (14th day) was disrupted by grinding in a sterile mortar and pestle, and DNA was extracted using the DNeasy Plant Mini Kit (Promega) according to the manufacturer's instructions. Isolated DNA was verified by running in 0.8% agarose gel electrophoresis and quantified by Nanodrop (Thermofisher) and stored at −20 °C. The extracted DNA was used for PCR amplification of 18S rRNA gene with universal primers (Duff et al. 2008; Forward Primer 5′- CGAATTCAACCTGGTTGATCCTGCCAGT-3′ and Reverse Primer 5′- CCGGATCCTGATCCTTCTGCAGGTTCACCTAC-3′). The reaction was performed in a total volume of 25 μL having 1X TAE buffer containing 10X Taq buffer, 2 mM of dNTPs (dATP, dCTP, dGTP, dTTP), 18S primers (FP and RP 5 pmole each) and 1 U of Taq polymerase (Fermentas, USA). Amplification was achieved in a Mastercycler gradient program for initial denaturation (94 °C for 5 min) followed by 35 cycles composed of denaturation (94 °C for 30 s), annealing (61 °C for 45 s) and extension (72 °C for 2 min) and final extension of 72 °C for 10 min. The amplified PCR products were kept on hold at 4 °C for 24 h and gel electrophoresis of the PCR product was carried out (Ratha et al. 2012). 10 μL of the amplified PCR product was loaded on horizontal 1.2% (w/v) agarose (Pronadisa, Europe) gel in 1X TAE buffer (0.5 M EDTA, 1 M Tris acetate, pH 8.0 and electrophoresed at 75 volts for about 1 h. The standard marker of 1 kb molecular size (Fermentas) was also used as a reference along with the amplified products. Gels were stained with ethidium bromide solution (0.5 μg/mL). The amplified products were visualized and documented on AlphaImager gel documentation system (Alpha Innotech, USA).

PCR amplified products of 18S rRNA gene was subjected to sequence analysis using Applied Biosystems ABI prism automated DNA sequencer. The partial 18S rRNA gene sequences were analysed and homologous sequences were searched using BLAST available in NCBI database (Altschul et al. 1990). Identification of isolates was done on the basis of gene sequence similarity of ≥97% with the sequences in Genbank. Sequence alignment and comparison was performed using multiple sequence alignment tool CLUSTAL W (Thompson et al. 1994) with default parameters. The sequence results of 18S rRNA gene of the five strains have been submitted to NCBI GenBank with Accession Numbers as KT808247-KT808251.

The phylogenetic tree was constructed using neighbor-joining method (NJ) as executed in the program MEGA package version 6.1 (Saitou & Nei 1987; Tamura et al. 2011). The NJ stability of the relationships was assessed by boot-strapping (1,000 replicates) (Felsenstein 1985). The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1,000 replicates) are shown above the branches. The tree was drawn to scale, with branch lengths in correlation with the evolutionary distances used to infer the phylogenetic tree. All positions containing gaps and missing data were eliminated from the dataset.

Ecological habitats ranging from streams, ponds, Eastern ghats over Odisha along with coastal areas of West Bengal and North Eastern regions have been reported to be the most vibrant biodiversity sites, hence, the selected aquatic sites were used for the isolation of microalgae for their possible economic application (Jena et al. 2005, 2008; Prasanna & Kaushik 2005; Rath & Adhikary 2005; Ratha et al. 2012). The possibility of obtaining promising isolates from aquatic, terrestrial and extreme environments has been reported in earlier studies as well (Spolaore et al. 2006; Ratha & Prasanna 2012).

Green microalgal strains were microscopically identified based on microscopic observations and morphological features and these have been submitted in the germplasm collection of CCUBGA, ICAR-IARI (Figure 1, Table 1). 24 strains along with one reference strain were studied for their specific biochemical parameters namely total soluble proteins, carbohydrates and lipids as these constitute a major proportion of the cellular contents (Um & Kim 2009). Total soluble proteins enhanced with incubation time with highest recorded at 28th day of incubation. Total soluble proteins were maximum (419.4 μg/mg dry wt.) in Chlamydomonas sp. (MCC 2) isolated from Rohtang pass (Table 2). Studies conducted in the isolated green microalgal strains indicated that carbohydrates enhanced from the 14th day until the 21st day of incubation followed by a decline at the 28th day. Mean carbohydrates calibrated during the incubation period indicated that Scenedesmus sp. (MCC 9) isolated from Pond, Khurda, exhibited highest carbohydrates (267.85 μg/mg dry wt.) and Chlorella sp. (MCC 19) from Anusupa Lake showed the lowest carbohydrates (61.92 μg/mg dry wt.) (Table 3). Lipids were highest on the 21st day of incubation as compared to the 14th and the 28th day of incubation and Chlorella sp. (MCC 5) from Nandankanan Lake, Odisha showed the highest value of lipids (10.8%) on a dry wt. basis (Table 4). Such analyses on biochemical parameters have been carried out in different strains of microalgae under selected growing conditions (Becker 2004; Spolaore et al. 2006; Rodriguez-Garcia & Guil-Guerrerro 2008). Studies have also been conducted showing the applicability of biomass and extracts of microalgae for human consumption (Colla et al. 2007; Gouveia et al. 2007; Valencia et al. 2007). Varied potentials of microalgae have been documented extensively in a review by Shukla & Wattal (2013). The maximum protein content of 41.9% in MCC 2 followed by 40.3% in MCC 5 and 36.9% in MCC 12 showed the relevance of these as a protein source. The average protein quality of most of the algae examined is equal, sometimes even superior, to that of conventional plant proteins (Becker 2007).

The comparative study on carbohydrates (Table 3) showed the highest content of 26.7% in Scenedesmus sp. (MCC 9) followed by 25.5% in Chlorella sp. (MCC 5) and 24.3% in Scenedesmus sp. (MCC 8). The lowest carbohydrate content of 6.1% was recorded in Chlorella sp. (MCC 19). Studies conducted on different microalgal biomass reported proteins in the range of 6–71% and carbohydrates as 4–64%, whereas, lipids ranged from 1 to 70% (Chisti 2007; Becker 2013). Chlorella pyrenoidosa also depicted carbohydrate content of 26% whereas Chlorella vulgaris showed carbohydrate content of 12–17% on a dry wt. basis (Um & Kim 2009). However, the Chlamydomonas reinhardtii reported protein content of 48% on a dry matter basis (Um & Kim 2009; Sydney et al. 2010). The protein content of 8–18%, 50–56% and 47% has been reported in different species of Scenedesmus, namely S. dimorphus; S. obliquus and S. quadricauda (Um & Kim 2009).

Strain MCC 5 (Chlorella sp.) showed maximum lipid content of 10.8% on a dry wt. basis which was at par with the lipid content of 10–22% in Chlorella vulgaris. The lowest lipid content of 3.5% recorded in MCC 19 (Chlorella sp.) was higher than the reported content of 2% from Chlorella vulgaris (Um & Kim 2009; Sydney et al. 2010). The compositional analysis of Chlorella sp., Scenedesmus sp., and Nannochloropsis have reported varied proteins (7.4–42.5%), carbohydrates (9.5–52.3%), and lipids (6.8–53.0%) on a dry wt. basis (Laurens & Wolfrum 2013).

The results have clearly indicated that microalgae have a potential in nutritional value of food and feed and can be effectively used in the aquaculture as well as fish feeding. Out of 24 microalgal strains isolated from selected aquatic sites, five strains were subjected to axenization using triple antibiotic solution. Based on the best performing strains, five microalgal genera were used for 18S rRNA gene amplification and sequencing. The microscopy-based identification was supported with BLAST analysis of 18S ribosomal DNA using specific primers (Duff et al. 2008) for five isolates (MCC 3, MCC 9, MCC 10, MCC 12, MCC 19). Based upon results, identification was authenticated as Scenedesmus sp. MCC 3; Scenedesmus sp. MCC 9; Dictyosphaerium sp. MCC 10; Dictyosphaerium sp. MCC 12 and Chlorella sp. MCC 19. These were given the accession numbers as KT 808247-KT808248 (Scenedesmus sp.), KT 808249-KT808250 (Dictyosphaerium sp.), KT 808251 (Chlorella sp.) (NCBI database). Identification of Scenedesmus sp. was in accordance with the morphological characters. Scenedesmus strains are known to form colonies of 2–8 cells called coenobia (Hegewald et al. 2013). This morphological feature was authenticated through 18S rRNA sequences which showed a similarity of >95% with other Scenedesmus sp. deposited in Genbank. The cells in Scenedesmus can be linearly or laterally arranged surrounded by mucilage. Cells are elongate and cylindrical or ovoid or rounded and the walls can be smooth, toothed or granular.

18S rRNA gene sequence analysis identified MCC 10 and MCC 12 as Dictyosphaerium sp. The morphophyte of Dictyosphaerium is characterised by spherical or oval cells connected by gelatinised strands to microscopic colonies and according to molecular studies Dictyosphaerium belongs to Chlorellaceae (Krienitz et al. 2004). Two strains of Dictyosphaerium sp. belonging to different clusters were the isolates of Khurda lake and Nandankanan lake. The molecular phylogenetic studies of Dictyosphaerium morphophytes indicates close relationship to the members of Chlorella and polyphyletic origin of Dictyosphaerium morphophytes has been reported (Luo et al. 2010; Krienitz & Bock 2012).

The strain MCC 19 was identified microscopically as Chlorella sp. Chlorella comprises unicellular green algae belonging to the family Chlorellaceae and the cells are solitary, spherical or globular in shape without flagella having cup-shaped chloroplast with a single pyrenoid surrounded within a thin wall (Tale et al. 2014). The identification of Chlorella is one of the most difficult and a large number of species have been isolated from different ecosystems (Krienitz et al. 2004). Based on sequence homology with >95% similarity, the strain MCC 19 was identified as Chlorella sp. (KT808251).

The evolutionary history was inferred using neighbor-joining method (Saitou & Nei 1987). The tree is drawn to scale (Figure 2), with branch lengths (0.53579240) which can be used to infer the evolutionary distances in the phylogenetic tree. The evolutionary distances were computed using the Maximum Composite Likelihood method (Tamura et al. 2004) and are in the units of the number of base substitutions per site. The analysis involved six nucleotide sequences. Codon positions included were 1st + 2nd + 3rd + Noncoding. All ambiguous positions were removed for each sequence pair. There was a total of 973 positions in the final dataset. Evolutionary analyses were conducted in MEGA5 (Tamura et al. 2011).

One-way analysis of variance (ANOVA) was used to evaluate the differences among different strains under study. The statistical analysis using one-way ANOVA indicated an average of total soluble proteins, carbohydrates and lipids with the degrees of freedom between groups and within groups (Table 5). Linear regression curve plotted amongst carbohydrates vs lipids and proteins vs lipids of 25 microalgal strains is depicted in Figure 3. Fitted curves can be used as an aid for data visualization, which can infer values of a function where no data are available, and such information can also help to summarize the relationships among different variables. Curve estimation is shown to be appropriate when the relationship between the dependent variable(s) and the independent variable is not necessarily linear. Based on the regression analyses, it could be inferred that the carbohydrates, proteins and lipids exhibited random distribution amongst green microalgal strains at different stages of growth. The correlation matrix showed positive correlation between carbohydrates and lipids, while negative correlation was seen between proteins and carbohydrates and between proteins and lipids.

Aquatic sites of Odisha represent a microalgal biodiversity hotspot as a large number of green algae were isolated from such habitats. Dictyosphaerium sp., Scenedesmus sp. and Chlorella sp. were the most dominant and representative genera. Some of them recorded a high concentration of proteins and carbohydrates; hence, they exhibit important and valuable germplasm for further utilization in the area of food or feed.

The authors declare no conflict of interest.

The authors are grateful to the Director, ICAR-IARI, New Delhi for the necessary facilities and the Department of Biotechnology for financial support under Indo-Denmark Collaborative Project, GOI, India.