Bioprospecting microalgae harnessed from the coastal belt of Mangalore, India as prospective nutraceutical and biofuel candidates

ABSTRACT The nature of global dietary supplements is transitioning from animal derivatives to plant based. Industries around the world are seeking vegan alternatives to animal-derived supplements. The microalgal industry is expected to undergo a market boom in the current decade. Microalgal supplements (power based and extracts) as well as microalgal fuels are expected to show a significant increase in market value. Microalgae are an under-utilized source of high-value products. They are rich reservoirs of multiple compounds capable of enhancing immunity, fortifying nutritional diets and improving cardiovascular health. Microalgae are also high lipid producing organisms, which make them viable candidates in the global search for energy alternatives. However, the inability to translate in vitro results onto the industrial scale is a major drawback of the microalgal research landscape. It is therefore, vital to find a robust microalgal species capable of producing a feasible quantity of high-value compounds. This paper investigates the potential of four microalgae sourced from the coastal town of Mangalore, India as candidates for nutraceutical industries and the clean energy industry. Desmodesmus komareikii (MK990101) was found to be rich in total lipid, while the three Chlorella species were found to be relatively richer in total protein yields. Chlorella thermophila (MN006612) is capable of yielding harvests up to nearly 280 tonnes/acre/year. Chlorella thermophila (MN006612) yielded the highest amount of both mono and polyunsaturated fatty acids. The fatty acid profiles of Chlorella thermophila (MN006612), Chlorella vulgaris (MN252517-18) and Chlorella sorokiniana (MN011568) can be explored as an alternative edible oil. Desmodesmus komareikii (MK990101) yielded the highest amount of saturated fatty acids, which are used in the production of clean and quality biofuels.


Introduction
Microalgae and their components have been used in multiple industrial applications for decades. Their diverse nutritive characteristics combined with their ability to grow rapidly make them a viable option as dietary supplements (Paniagua-Michel, 2015). It is expected that the microalgal market (biomass or algalbased products) could generate up to $76.68 million USD by 2028 with a compounded annual growth rate of 6.9% (Data Bridge Market Research, 2021). Microalgae are notably rich in saturated fatty acids, unsaturated fatty acids and proteins. Their rich biochemistry showcases an immense potential as immune enhancing supplements (Bishop & Zubeck, 2012). A lot of biochemical analyses of microalgae have unveiled a dynamic array of metabolites that include omega-3 fatty acids, sulphated polysaccharides and carotenoids, which have anti-inflammatory/viral/bacterial properties (Barkia, Saari, & Manning, 2019). Algal proteins have been found to be helpful as broad spectrum anti-viral compounds, inhibiting viral entry and replication in cells (Ahmadi, Moghadamtousi, Abubakar, & Zandi, 2015). Their extracts also help in promoting cardiovascular health by lowering cholesterol (Reyna-Martinez et al., 2018;Ryu et al., 2014). Microalgal derived peptides have been used to derive Angiotensin Converting Enzyme (ACE) inhibitory peptides, which helps to lower blood pressure (Sheih, Fang, & Wu, 2009). Approximately 40-60% of the microalgal body weight (species dependent) is comprised of protein (Shim et al., 2008). Microalgal proteins can compete both qualitatively and quantitatively with the conventional sources. The market ready Chlorella based products contain high quantities of all the essential amino acids, while most commercially available non-algal protein sources tend to be deficient in a few (Williams & Laurens, 2010). Bioactive peptides from Chlorella pyrenoidosa, Nannochloropsis oculata, Arthrospira maxima and Tetraselmis suecica have proven to show anti-oxidant /inflammatory/tumour properties and also reduce hypertension (Wang & Zhang, 2013). Arthrospira is sold globally with sole emphasis on its high-quality protein content. Microalgal commercial cultivation for nutraceuticals began about 60 years ago in Japan and Taiwan with Chlorella vulgaris being the highest massproduced chlorophycean microalgae (Beetul et al., 2016). Eventually, Japan, the United States, Israel, Australia and China branched out into the mass production of Hematococcus pluvialis and Spirulina. As per reports given by Barkia et al. (2019), Taiwan remains the highest producer of single-cell protein (SCP) products of Chlorella, producing over 2000 tons/year of the whole dried microalgae.
The unsaturated fatty acid profiles of microalgae are rich with Ω3 and Ω6 fatty acids (Simoons, 2014), both of which are known to promote cardiovascular health (Sayanova & Napier, 2004). Lipids are also crucial to the structural integrity of a cell and as energy reservoirs (Qu, Ren, & Huang, 2013). PUFAs have been investigated for their role in reducing inflammation, a major causative factor of Alzheimer's (Talero et al., 2015). Several microalgae (Cryptothecodininum, Schizochytrium, Ulkenia) are cultivated for docosahexaenoic acid (DHA) which is incorporated in infant formula (Chu, 2012;Horrocks & Yeo, 1999). This product alone has an estimated market demand of $9 billion USD year -1 (Martek Biosciences Corporation Annual Report, 2007). Docosapentanoic acid (DPA) has also been reported to inhibit the synthesis of the tumour necrosis factor alpha (TNF-α) (Nauroth et al., 2010). Thus, microalgae would make impressive candidates for the nutraceutical market (Paniagua-Michel, 2015). Polyunsaturated fatty acids are currently valued at $140 USD kg -1 (Borowitzka, 2013). Their diverse protein and fatty acid profiles also make them an impressive candidate as feed for aquacultured species. It is well known that fish oils are recommended sources of Ω3/Ω6 fatty acids. However, fishes generally derive their lipid constitution from microalgal diets (Medina, Grima, Giménez, & González, 1998). Additionally, microalgal oils have lower levels of contamination relative to fish oils (Gerber, Karimi, & Fitzgerald, 2012;Ryckebosch et al., 2014). Microalgal-derived feed is also utilized to increase pigmentation in shellfish (Kumar, Deviram, Mathimani, Duc, & Pugazhendhi, 2019).
The rapid depletion of energy resources has led to the seeking out of alternatives like biofuels (Kumar et al., 2019). Thus, first-generation biofuels from lipid-heavy plant crops and second-generation biofuels from edible oil were developed. However, the production of fuels from edible oil is economically disadvantageous owing to the fact that edible oil is required to meet 60% of the food requirement in India (Demirbas, 2007). Furthermore, both first-and second-generation biofuels require a lot of land and time to reach effective yield (Kumar et al., 2019). The solution to this problem lies in microalgae, resulting in third generation algal-derived fuels (Teri Energy Data Directory and Yearbook, 2011). Incidentally, the saturated fatty acid profiles of microalgae can be considered instrumental in the development of biofuels. Biofuels generated from saturated fatty acids have superior density and viscosity as well as calorific value (Talebi et al., 2013). Palmitic acid, stearic acid and lauric acid are valuable for biodiesel production (Rohit & Venkata Mohan, 2018). Generation of algal biomass does not require large allocations of land and resources, as compared to traditional fuel crops (Koyande et al., 2019). Considering that most microalgae can be grown alongside or as part of waste water systems, it creates an added advantage of combining bioremediation of water reserves with biomass development, thereby considerably reducing the overall cost of production (Yen et al., 2013).
A common issue with microalgal studies is the inability to translate in vitro results onto the outdoor massscale scenario. Although a lot of research is being driven into the development of microalgal derivatives, it is important to find a robust microalgal species capable of producing a feasible quantity of high-value compounds (Steinrücken, Erga, Mjøs, Kleivdal, & Prestegard, 2017). An algal candidate with great lipid and protein productivity might have low biomass productivity and vice versa (Mandotra, Kumar, Suseela, Nayaka, & Ramteke, 2016). Biomass productivity, therefore, becomes a crucial characteristic for the selection of high output species. High biomass productivity favours scale-up processes by reducing the energy and cost of biomass processing (Fozer et al., 2019). Many countries are foraying into this line of research voraciously. The Indian government has pledged $87 million USD to develop algal resources of the country (Ferrer, 2021), while the Saudi government has joined hands with an Indian company, Zaara, investing $10 million USD for the development of microalgal-based food products (Mint, 2021). Indigenous microalgae display a natural tendency to adapt to changing environmental conditions (Rizza, Smachetti, Do Nascimento, Salerno, & Curatti, 2017). Identification and specific utilization of robust microalgal strains is a key step in targeted production of high-value compounds. Bioprospecting native naturally available microalgae is therefore a crucial investigative process in order to exploit them in the relative sectors of production (Matos et al., 2016). Mangalore is a coastal city with an abundance of marine, brackish and freshwater resources. It experiences a wide variation in temperatures ranging from cooler monsoons to scorching summers. The seasonal variations result in a constant intermixing of the water bodies, thereby causing a constant fluctuation in the aquatic temperature, salinity and pH, amongst other factors. It can therefore be logically presumed that the aquatic life, specifically microalgae would be capable of resisting and thereby adapting to a wide range of culture condition variations by altering their biochemistry. The present study seeks to isolate robust indigenous microalgae found in the water reservoirs of Mangalore, India and explore the possibility of utilizing the native strains as prospective microalgal industrial candidates. The investigation is based on the premise that microalgal strains found in a system that experiences frequent changes in weather pattern would be better capacitated to adapt and thrive by modulating their biochemical parameters. This study seeks to bioprospect robust microalgal strains capable of naturally yielding high volumes of high-value compounds.

Isolation and cultivation of microalgal strains
Freshwater samples were collected from different water reservoirs across Mangalore, Karnataka, India. The physico-chemical properties of the water samples were measured in situ using the multi-parameter PCSTestr TM 35 (Eutech instruments, Oaklon, Singapore). Various microalgae were isolated from the upper littoral zone (within 10 cm) of freshwater sources across Mangalore, Karnataka, India (Makandar & Bhatnagar, 2010). The isolates were streaked onto BG11 (Modified) agar plates (Andersen, 2005). The pH of the culture media was set to 7.4 and kept constant for all cultures. Colonies were isolated using the quadrant streak method. This was done repeatedly to isolate axenic cultures. The axenic cultures were grown at 27 ± 1°C, 16: 8 light: dark cycle at 20-24 µmol m -2 s -1 PPFD/1600 lux using fluorescent white tubes (to reduce the probability of photoinhibition). Growth was analysed periodically at a five-day interval. It was estimated as a measure of the optical density at 600 nm (Mandotra et al., 2016). Biomass productivity was assessed as per Mandotra et al. (2016): Where BP is the biomass productivity (mg l -1 day -1 ), B2 and B1 are the biomass harvested (mg l -1 ) at two sampling times T2 and T1 respectively. The data obtained for biomass were extrapolated to calculate the possible harvest outcomes in terms of tonnes acre -1 year -1 . The biomass extrapolation was performed by considering an open raceway pond as a means of biomass generation. The extrapolation is based on the existing pond cultures employed in our laboratory's investigations, in order to ensure a realistic extrapolation.
Our study employed open raceway ponds of 15 ft 2 area bearing the volume capacity of 500 l. The extrapolation was performed considering the use of the open ponds for the parameters mentioned against a land area of one acre.
For the purpose of this paper, the first four isolates showing maximum growth are discussed. Algal cells were harvested on the 45 th day post-inoculation to ensure sufficient biomass volume by centrifuging at 8534 G (10 min, 25°C) and subjected to further testing. The wet weights and dry weights of the algal biomass were determined gravimetrically. The algal pellet was subsequently dried at 40°C for 36 h, following which the biomass was ground and sieved through a 45 µm mesh to obtain uniformly sized algal powder. The powder was transferred to vials flushed with nitrogen gas, sealed and stored at -20°C for further analysis.

Strain identification (Fawley & Fawley, 2020)
For strain identification, three-week-old axenic strains were selected for morphological analyses. The light microscopic investigation was done by suspending the strain in 1% Lugol's Iodine solution for 24 h, with subsequent photographic documentation using Olympus BX-41 (Japan) light microscope with an attached CCD camera (Olympus DP 73, Japan). Axenic cells were harvested by centrifugation and broken into a bead mill. DNA was extracted using the HI Media Hi-Pur A Marine Algae DNA purification kit. The 18S rDNA sequence was amplified and sequencing of molecular data was outsourced to Eurofins Scientific, Bangalore, India. Forward and reverse DNA sequencing reaction of PCR amplicon was carried out with NS1 and NS4 primers bearing sequences GTAGTCATATGCTTGTCTC and CTTCCGTCAATTCCTTTAAG respectively using BDT v3.1 Cycle sequencing kit on ABI 3730xl Genetic Analyser (Thermo Fischer Scientific, Japan). Sequence data was cross-referenced using BLAST against available data sequences in the NCBI GenBank Database. The first 10 sequences with maximum identity scores were selected and aligned using ClustalW. A phylogenetic tree was constructed using MEGA7. The evolutionary history was inferred by using the Maximum Likelihood method based on the Kimura-2 parameter model (Kimura, 1980). The strain sequence data was registered and deposited with GenBank.

Total protein and amino acid analyses
The total protein analysis was determined using a modified version of the method described by Slocombe, Ross, Thomas, McNeill, and Stanley (2013). Briefly, 100 mg algal biomass powder was hydrolysed using 200 µl of tricarboxylic acid (24% w/v), incubated at 85°C for one hour and cooled. To this, 800 µl double distilled water was added and the suspension was centrifuged (19,202 G, 4°C, 15 min). The supernatant was discarded and the pellet resuspended in 2 ml Lowry's D Reagent. The suspension was incubated at 55°C for two hours, cooled and centrifuged. The supernatant was used for further quantification as described by Slocombe et al. (2013).
Once the total protein was estimated, the biomass was subjected to amino acid profiling as given by Kent, Welladsen, Mangott, and Li (2015). Oven dried samples and amino acid standards were hydrolysed and then subjected to derivatization using derivatization kit (AccQ. Fluor, Waters, USA). This was followed by an analysis using HPLC-FLD (Waters, USA). For HPLC analyses, 0.5 g of the sample was taken in a Wheaton screw cap vial. To this, 4 ml of 6 M boiling HCl and a crystal of phenol was added. This was flushed alternatively with nitrogen and vacuum. The vial was sealed and hydrolysed at 115°C for 24 h. It was cooled, diluted and subsequently filtered using 0.22 µm filter paper. 50 µl of the diluted sample was then taken and dried under nitrogen at 40°C. To the dried sample, 40 µl of 20 mM HCl was added and this was derivatized as per the kit instructions given in AccQ Fluor Reagent kit, Waters. For analysis, the HPLC-FLD parameters were maintained at a flow rate of 1.0 ml min -1 , column temperature of 37°C, excitation wavelength: 250 nm, emission wavelength: 395 nm. The column used was Waters AP 150 × 4.6 × 5 µm.

Total lipid and fatty acid analyses
For lipid analyses, 2 g of the algal biomass was resuspended and washed thrice with distilled water. The washed pellets were oven dried at 40°C, overnight. The dry cell biomass was subjected to the modified Bligh and Dyer (1959) method using chloroform and methanol (3:2) as per Ming et al. (2012). To maximize lipid yield, extraction was repeated thrice. To the pooled extract, 1% sodium chloride and sodium sulphate crystals were added to remove any water-soluble impurities and moisture. The lipid extracts were dried under nitrogen gas and the weight of the lipids were determined gravimetrically (Prabharan & Uma, 2017).
For fatty acid analysis (Prabharan & Uma, 2017), the lipid extracts were refluxed with 1% v/v sulphuric acid in methanol at 70°C for two hours. The esterified contents were transferred to a centrifuge tube and equal volumes of distilled water and hexane were added. The upper layer containing the fatty acid methylated esters (FAMEs) were collected and dried under nitrogen gas following which gas chromatographic analyses were carried out (Feng, Chen, Xue, & Zhang, 2011). 2 µl of the lipid samples were injected into the gas chromatograph (Agilent/7890B). The fatty acid profile was measured using gas chromatograph-flame ionization detector (GC-FID) have a DB-23 Agilent column (60 mm × 0.32 mm, 0.25 µm thick). The temperature of both the injector and detector were maintained at 250°C (Hena, Fatimah, & Tabassum, 2015). The oven temperature was initially maintained at 50°C for three minutes, followed by an incremental increase of 10°C to the final temperature of 130°C for one minute. The oven temperature was increased incrementally (4.5°C) to a final temperature of 245°C for a total of seven minutes. Nitrogen gas was used as the carrier gas, maintaining the flow rate at 1 ml min -1 . Supelco CRM47885 was used as the standard FAME mix to calculate the retention time of each FAME.

Statistical analyses
All experimental setups were maintained in triplicates. The data were analysed and plotted using MS Excel Professional Plus (2019). To elucidate the relationships between the microalgal strains, all data values were subjected to ANOVA.

Strain identification and cultivation
Our study allowed us to isolate and identify four chlorophycean microalgal species. The sequence data of each species was deposited into GenBank and an accession code was allocated (Table 1). Microalgal growth occurs relative to the interactions of physical and chemical parameters. Elevated parameters support the inclination of the water body towards eutrophication (Naik, Vinod, & Kusuma, 2010). Physico-chemical analyses of the sampling site parameters showed that while all three Chlorella species grew in moderate (pH 7.3-7.5) to highly alkaline waters (pH 9.35), D. komareikii (MK990101) grew in mildly acidic waters. Alkaline pH usually signifies high photosynthetic activity pointing to a probability of eutrophication of the water bodies (Naik et al., 2010). Salinity and total dissolved solids (TDS) are inversely proportional to the level of dissolved oxygen in the water bodies (Shrivastava, Bharadwaj, & Shrivastava, 2014). Table 1 indicates that all four microalgal strains were isolated from water bodies having low levels of salinity and TDS. This indicates a high level of dissolved oxygen. Eutrophied water bodies display high levels of dissolved oxygen during the day, on account of the high photosynthetic activity of algal blooms (Horrigan, Lawrence, & Walker, 2002). Considering that all algal sampling of this study was performed during daylight, it would be safe to assume that at the time of sampling, the microalgae were isolated from eutrophied water bodies.

Chlorella thermophila (MN006612)
This species was isolated from a freshwater pond near the Surathkal lighthouse, Mangalore overlooking the Arabian sea. Investigation of the axenic cultures by bright field microscopy revealed unicellular solitary spherical chlorophyceans. The cells have cup-shaped chloroplasts with a single pyrenoid (Fig 2A). Molecular amplicon of the 18S DNA sequence gave a 1118 bp long sequence that showed high similarity with C. thermophila KF 661,334 (99.32%) (Fig 1A), against the outgroup of C. vulgaris. Sequence data was deposited in GENBANK. Axenic cultures were upscaled in BG11 solid and liquid media.

Chlorella vulgaris (MN252517-18)
C. vulgaris is characterized by a distinct rigid cell wall housing dense green cytoplasm (Fig 2B). This particular strain was isolated from a freshwater well in Falnir, Mangalore. Morphologically, it is similar to other species described here such as C. thermophila and C. sorokiniana. However, molecular data identified the molecular amplicon (763 bp) of this strain as a relative  to 10 other strains of C. vulgaris, showing the highest percentage similarity with KX639565 (94.77%) (Fig 1B).

Chlorella sorokiniana (MN011568)
As is typical of any Chlorella species, C. sorokiniana too is a chlorophycean microalgae, found as unicellular organism in water. The cells have cup shaped chloroplasts with a single pyrenoid (Fig 2C). The molecular amplicon (1124 bp) of this organism placed it close to both C. thermophila and C. sorokiniana, against the outgroup of C. vulgaris. However, the percentage similarity to C. sorokiniana (MG597606) was higher (99.71%) (Fig 1C).

Desmodesmus komareikii (MK990101)
Desmodesmus species are colonial chlorophycean microalgae usually found as multiples of two. These microalgae have the presence of a pyrenoid at either end of the oblong cell body (Fig 2D). The outer cell bodies have the presence of two thick spines running at both corners. D. komareikii was isolated from a freshwater pond in Iddya, Surathkal, Mangalore. The 18s DNA amplicon (1023bp) of this species showed 99.23% percentage identity with D. komareikii (AB818541) (Fig 1D) against the outgroup of D. armatus.

Proximate analyses
Proximate analyses of the microalgae showed that the dry weight of the identified freshwater microalgae is made up of 41.5%-26.7% protein. This corroborates the data given by Boyd (1973). Of the four microalgal species studied, C. thermophila (MN006612) and D. komareikii (MK990101) produced the highest biomass of more than 9 g l -1 of the algal culture suspension. Their biomass productivity was also higher with D. komareikii (MK990101) showing the highest productivity at 482.4 ± 0.2 mg l -1 d -1 . The biomass and biomass productivity of both C. vulgaris (MN252517-18) and C. sorokiniana (MN011568) were not significantly different from each other. However, all three Chlorella species produced significantly higher quantities of total protein (p < 0.05) relative to D. komareikii (MK990101) which yielded only about 26% protein of its total biomass. Proximate analyses of the microalga confirm the studies of Fabregas and Herrero (1985) stating that Chlorella species would be better suited for the production of single-cell proteins (SCPs). In contrast, the analysis of total lipids showed that D. komareikii (MK990101) yielded significantly higher volume of lipids (p < 0.05) with up to 178.5 mg g -1 biomass. However, all three Chlorella species yielded lower quantities of lipid (2.3-5.5% lipids). The proximate analyses of the microalgae conclusively prove that Chlorella species would be better suited for protein investigation and products, while D. komareikii (MK990101) has potential in lipid-related ventures. The data obtained for biomass, protein and lipid was extrapolated to calculate the possible harvest outcomes in terms of tonnes acre -1 year -1 . As represented in Table 2, C. thermophila (MN006612) is capable yielding harvests up to nearly 280 tonnes acre -1 year -1 , with estimated harvest of 2800 tonnes year -1 over 10 acres. This is considerably higher than Taiwan, which currently produces the highest yields of C. vulgaris, of nearly 2000 tonnes year -1 ( Barkia et al., 2019). Due to the advancing interests in microalgal lipids, many species have been cultured on a mass scale for lipid harvests. However, D. komareikii (MK990101) remains an underutilized species. Table 2 suggests that D. komareikii (MK990101) is capable of producing nearly 37.4 ton acre -1 year -1 lipids.

Monounsaturated fatty acids (MUFAs)
Monounsaturated fatty acids are commonly used as edible oils. The monounsaturation is a great characteristic for cooking oils and can help to reduce the low- density lipoproteins (Teres et al., 2008). Palmitoleic acid (C16:1) and oleic acid (C18:1) have been reported to reduce blood pressure and thereby play a role in preventing heart ailments (Rohit & Venkata Mohan, 2018). The highest amount of MUFAs were detected in C. thermophila (MN006612) (12.2%). Of the five MUFAs detected, cis-10 heptadecenoic acid (C17:1) was found predominantly in the three Chlorella species. Oleic acid (C18:1) was significantly higher in D. komareikii (MK990101), constituting 5.6% of the total lipid yield. López et al., (2019) reported that C18:1 play a role in the structure of ceramides and sphingolipids. This makes C18:1 a key fatty acid in the anti-inflammatory pathway (Kapoor & Huang, 2006). Apart from this, C18:1 is also used in relieving pain, anxiety and other mental disorders such as bulimia (Whiley, Godzien, Ruperez, Legido-Quigley, & Barbas, 2012).

Conclusion
Microalgae have long been explored as viable alternatives to both energy resources as well as health supplementation. Even though the microalgal supplements have received negative attention, for containing heavy metal contaminants, the microalgal industry is expected to undergo a huge boom between 2021 and 2028 (Data Bridge Market Research, 2021). Whole microalgal biomass and its derivates are vegan alternatives to traditionally processed protein and lipid supplements. Powder or capsule forms of the microalgal supplements are expected to dominate the markets for the next decade (Data Bridge Market Research, 2021). The current market focuses on using and exploiting Spirulina and C. vulgaris for SCP production. However, most other species of Chlorella remain unharnessed on an industrial scale. Chlorella species are considered a superfood, superior to recommended animal-derived supplements (Koyande et al., 2019). This investigation looked into harnessing the local microalgae of Mangalore, India as potent industrial candidates. Of the microalgae investigated, D. komareikii (MK990101) was found to be rich in total lipid, while the three Chlorella species were found to be relatively richer in total protein yields. C. thermophila (MN006612) is capable yielding harvests up to nearly 280 tonnes acre -1 year -1 . It can be noted that D. komareikii (MK990101) was considerably richer in the essential amino acids, relative to the other algal species as well as to the regularly recommended natural protein source of an egg. Therefore, D. komareikii (MK990101) has potential to be explored as a vegan protein supplement, for both human as well as aquaculture feed. Unsaturated fatty acids play a key role in maintaining cardiovascular health. All three Chlorella species showed high yields of both mono and polyunsaturated fatty acids. C. thermophila  the highest amount of saturated fatty acids, which are used in the production of clean and quality biofuels. D. komareikii (MK990101) is capable of producing nearly 37.4 ton acre -1 year -1 of oil. It would be worthwhile to explore these robust strains of D. komareikii(MK990101) in the production of biofuels.