Bioresource Technology 211 (2016) 556–565

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Bioresource Technology

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The isolation and identification of new microalgal strains producing oiland carotenoid simultaneously with biofuel potential

http://dx.doi.org/10.1016/j.biortech.2016.03.1210960-8524/� 2016 Elsevier Ltd. All rights reserved.

⇑ Corresponding author.E-mail addresses: aloka@teri.res.in, adholeya1@gmail.com (A. Adholeya).

Amritpreet Kaur Minhas a,c, Peter Hodgson b, Colin J. Barrow c, Burla Sashidhar a, Alok Adholeya a,⇑a TERI�Deakin Nanobiotechnology Centre, Biotechnology and Management of Bioresources Division, The Energy and Resources Institute, New Delhi, Indiab Institute for Frontier Materials, Deakin University, Geelong campus at Waurn Ponds, Victoria 3217, Australiac School of Life and Environmental Sciences, Deakin University, Geelong campus at Waurn Ponds, Victoria 3217, Australia

h i g h l i g h t s

� Four algal isolates from diverse habitats showed potential to produce multiple products.� Functional variations for lipid and carotenoids production between isolates reported.� Major fatty acids were palmitic, stearic, oleic, linoleic, and linolenic acid.� Scenedesmus bijugus showed highest biomass productivity and multiple products potential.

a r t i c l e i n f o

Article history:Received 3 January 2016Received in revised form 20 March 2016Accepted 21 March 2016Available online 23 March 2016

Keywords:MicroalgaeCarotenoidsLipidsBioprospectingBiofuel

a b s t r a c t

Taxonomy and phylogeny of twenty two microalgal isolates were examined using both universal andnewly designed molecular primers. Among the isolates, Scenedesmus bijugus, Coelastrella sp.,Auxenochlorella protothecoides, and Chlorella sp. were particularly promising in terms of producing lipidsas measured by fatty acid methyl esters (FAME) analysis and significant concentration of carotenoids. Acomparative experiment showed that S. bijugus and Chlorella sp. were the most promising candidates(L�1 d�1, with biomass) 174.77 ± 6.75, 169.81 ± 5.22 mg, lipids 40.14 ± 3.31, 39.72 ± 3.89 mg, lutein0.47, 0.36 mg, and astaxanthin 0.27, 0.18 mg respectively. The fatty acids produced by these microalgalisolates were mainly palmitic, stearic, oleic, linoleic, and linolenic acid. The freshwater microalgal isolateS. bijugus be the most suitable isolate for producing biodiesel and carotenoids, due to high productivity ofbiomass, lipids, metabolites, and its suitable fatty acid profile.

� 2016 Elsevier Ltd. All rights reserved.

1. Introduction

Microalgae, widely distributed, and with a longer evolutionaryhistory than terrestrial plants, show a rich diversity among theirmore than 200,000 species (Guiry and Guiry, 2014). However,30,000 species have been studied but so far not fully exploited(Mata et al., 2010). Bioprospecting of microalgae has been carriedout from ecologically diverse habitats such as the deep seas(Boeuf and Kornprobst, 2009) and polluted waters (Sterrenburget al., 2007). Such diverse habitats may harbour distinct isolateswith unique properties and multiple applications. During the pastfew years, microalgae have been extensively explored for biofueland for bioactive compounds. In recent years, unique strains havebeen isolated from a range of habitats in the tropics including bothaquatic (lakes, streams, and backwaters) and terrestrial habitats.

Such extremes as very high temperatures and prolonged exposureto intense light found in the tropics have conferred on the extre-mophiles some distinctive physiological properties (Gouveiaet al., 2009). Since the early 1970s, bioprospecting of microalgae(such as green algae, cyanobacteria, and diatoms) has beenattempted for various uses, and their ability to consume carbondioxide during photosynthesis and to act as a sustainable sourceof biofuels has led to increasing attention in recent years (Jonesand Mayfield, 2011). Both lipid and biomass content are equallyimportant for achieving higher lipid productivity (Yen et al.,2013). Microalgae lipids are divided in two main categories, thoseused as biofuel (with 14–20 carbon chains) and those used as food(containing 20 carbon chains) because they are rich in essentialnutrients that are not synthesized by higher eukaryotic organisms(Jacob-Lopes et al., 2015). Deriving multiple products such as lipidsand high-value by-products from the same biomass in one growthcycle is one way to make process economically sustainable(Nobre et al., 2013). Biologically active compounds derived from

A.K. Minhas et al. / Bioresource Technology 211 (2016) 556–565 557

microalgae have attracted increasing industrial attention (DeMorais et al., 2015). The diverse gene pool of microalgae stillremains to be fully explored for production of bioactive com-pounds, particularly using the biorefinery approach. So far, themarket for carotenoids is primarily based on b-carotene and astax-anthin whereas lutein have not been similarly exploited. Theimportance of lutein and astaxanthin from microalgae has grownsignificantly in recent years. Lutein has multiple applications: itprevents some degenerative diseases of the eye; it is used as a fooddye and as a food additive in aquaculture; and it can help preventcardiovascular diseases as well as age-related macular degenera-tion. Astaxanthin is used in the pigmentation of salmonids, orna-mental fish, and in the poultry industry (Lorenz and Cysewski,2000). The market for these bioactive compounds continues toexpand. Thus, new microalgal species that can produce these orother useful compounds is a continuing area of research.

It is against this background that the present study sought tocompare twenty two microalgal isolates for identifying the strainsmost suitable for biofuel and carotenoids production. The approachwas to isolate a number of microalga from a range of diverse habi-tats and to characterise the isolates using 18S rDNA analysis. Theselection criteria were the ability to produce (1) lipids with fattyacid methyl ester (FAME) profiles suitable for biofuels and (2) car-otenoids, which are valuable compounds that can be readily sepa-rated from oils and would potentially offset the cost of biofuelproduction.

2. Materials and methods

2.1. Collection, isolation, and purification of microalgal isolates

A total of two hundred isolates were collected from differenthabitats – aquatic and terrestrial rocky– in Asia, North America,and the Middle East (Table 1). The aquatic habitats included fresh-water, chemically polluted river water, and backwater. Twenty twomicroalgal isolates from Chlorellaceae and Scenedesmaceae wereselected based on their molecular taxonomy and assessed for theirpotential to produce biofuel and carotenoids. The isolates fromthese two families were priorities for selection because underlow light conditions, in Chlorella sp. lipid production is increased(Takeshita et al., 2014) whereas Scenedesmaceae family membersyield both lipid and carotenoids (Peng et al., 2012). For photoau-totrophic cultivation, primary stock cultures from different habi-tats were incubated up to the late exponential phase in full-strength Bold’s basal medium (BBM) (Andersen et al., 2005) in100 mL Erlenmeyer flasks at 25 �C with orbital shaking at150 rpm and under 16 h of light (100 lE/m2/s) alternating with8 h of darkness. After 2 weeks, the pre-cultured samples were puri-fied by serial dilution and plated on sterile agar plates (1.6% w/v).Individual colonies were isolated and grown in BBM medium until

Table 1Collection sites of microalgal isolates from diverse habitats.

Region and country of collection Number of isolates Sampand y

Middle East, Qatar 15 AugusNorth America, St. Louis, USA 8 NovemAsia, Hussain Sagar, Hyderabad, India 8 AugusAsia, Rocky beach, Goa, India 7 May 2North America, Tree bark, St. Louis, USA 6 DecemAsia, Chennai, Tamil Nadu, India 25 June 2Asia, Vishakhapatnam river, Andhra Pradesh, India 30 July 2Asia, Pangong lake, Ladakh, Jammu and Kashmir, India 6 AprilAsia, Mangalore, south-western Karnataka, India 20 June 2Asia, Yamuna river, India 60 July 2Asia, Yamuna river, Delhi, India 15 June 2

sufficient biomass was produced (Lee et al., 2014). Grown cultureswere passed through glass fibre prefilters (Millipore, USA) in a vac-uum filtration unit (Tarsons Products, Kolkata, India) with repeatedwashing with milli-Q water and intermittent washing withchloramine T (0.2% w/v) from Sigma Aldrich (St. Louis, MO, USA).Axenicity of the isolates was confirmed by mounting a drop ofthe suspension of treated algal cells on a small nutrient agar plateand incubating for 72 h at 30 �C as well as by examining live cellsunder a light microscope (Olympus, Tokyo, Japan) fitted withbright-field and phase-contrast optics (�63 oil immersion objec-tive). All microalgal isolates were also tested under bright fieldmicroscope (Olympus, Tokyo, Japan) to ensure that none had beencontaminated with other microalgal isolates during handling.

2.2. Culturing of microalgal isolates

The twenty two isolates were grown in 250 mL Erlenmeyerflasks containing 100 mL BBMmedium and incubated for nine daysat 25 �C under 16 h of fluorescent white light (120 lE/m2/s) alter-nating with 8 h of darkness and with constant shaking (150 rpm).Cell suspensions of equal strength of the isolates were also grownin experimental tubes containing 70 mL of the medium in Multi-Cultivator (MC) 1000-OD (Photon Systems Instruments, Drasov,Czech Republic). To ensure that cell counts for the comparativegrowth experiments the same initially, the number of cells wascounted using a Neubauer haemocytometer (Rohem Instruments,Nashik, Maharashtra, India). The initial optical density (OD) ofthe cell suspension with a concentration of 3 � 106 cells/mL wasrecorded. All the tested isolates were maintained at an illumina-tion intensity of 120 lE/m2/s as a standard growth condition. Thesource of illumination was placed 2.0 cm away from the externalwall of the vessel, the internal diameter of which was 15 mm at25 �C. Cultures were aerated with plain air at rate of 0.12 mL/minthroughout the experiment.

2.3. Characterisation of isolates by scanning electron microscopy

For examining the cultures under a scanning electronmicroscope, 2 mL of the fully grown culture was centrifuged at6000 rpm for 5 min. Primary fixation of the algal cells was per-formed by incubating them in 2.5% glutaraldehyde at room tem-perature in the dark for at least 4 h followed by secondaryfixation in 1% osmium tetraoxide overnight at 4 �C. The algal cellswere dehydrated gradually in increasing ethanol series (10%, 30%,50%, 70%, 90%, and 100%), critical point dried, sputter coated withgold palladium using a polaron SC7640 auto/manual high resolu-tion sputter coater (Quorum Technologies, Lewes, East Sussex,UK) and examined under a FEI Quanta 200 scanning electronmicroscope (FEI, Hillsboro, Oregon, USA) at 10 kV.

ling monthear

Habitat Latitude Longitude

t 2012 Backwater 25� 170 700 N 51� 310 5100 Eber 2012 Freshwater 38� 470 5100 N 90� 470 800 Wt 2012 Freshwater 7� 250 2500 N 78� 280 25.700 E012 Backwater terrestrial, rocky 15� 170 5700 N 74� 70 2600 Eber 2012 Freshwater terrestrial, rocky 38� 370 3700 N 90� 110 5700 W012 Backwater 11� 70 3700 N 78� 390 2400 E012 Freshwater 41� 420 4400 N 81� 150 1400 W2012 Freshwater 33� 440 1600 N 79� 00 2700 E012 Backwater 12� 540 5000 N 74� 510 2100 E012 Chemically polluted river water 28� 360 5000 N 77� 120 3200 E012 Chemically polluted river water 28� 20 5600 N 79� 290 2300 E

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2.4. Identification of microalgal strains

2.4.1. PCR amplification, cloning and sequence analyses of 18S rDNAFor molecular confirmation of isolates, genomic DNA from the

maceratedbiomasswas extractedwith aDNeasyplantmini kit (Qia-gen GmbH, Hilden, Germany) following themanufacturer’s instruc-tions. The extracted DNA was either used for polymerase chainreaction (PCR) or stored at �20 �C for further use. The genomicDNA containing 18S rDNA gene was amplified using two universaleukaryotic primers, namely (EUF: 50 GTCAGAGGTGAAATTCTTGGATTTA-30 as the forward primer and EUR: 50-AGGGCACGACGTAATCAACG-30 as the reverse primer), which are expected to amplify the�700 bp region of 18S rDNA (Rasoul-Amini et al., 2009). The PCRreaction was performed in a total volume of 25 lL containing 2 lLof extractedDNAas template, 200 lMof eachdNTPs, 1.5 mMMgCl2,0.5 lM forward & reverse primer and 0.5 U Taq DNA polymerase.The amplification was performed in a ABI Veriti thermo-cycler gra-dient with the PCR program conditions as described by Ghasemiet al. (2008). Similarly, the PCR reaction was performed usingdesigned algae-specific primers, namely (FP1:50-GCCCGTAGTAAWWCTASAGCTAATAC-30 as the forward primer and RP1:50-AAAAACGGGCGGTGTGTACAAAGGGC-30) as the reverse primer withthe following conditions for the PCR: 4 min initial denaturation at95 �C; 35 cycles of 1 min denaturation at 95 �C, 1 min annealing at56 �C and 2.5 min elongation at 72 �C; and a 10 min final elongation.The sequences of purified products (PCR purification kit, Qiagen,Germany) were determined using an ABI 310 automatic DNAsequencer (Applied Biosystems, California, and USA). The 18S rDNAsequences were comparedwith published sequences from the NCBIdatabase to determine the nearest homologous sequences and therelative phylogenetic positions of individual isolates by ML treeanalysis using MEGA ver. 6. In the present study, we mapped theexisting universal primers from the literature as well as self-designed primers and evaluated them for their appropriateness forstudying eukaryotic biodiversity.

2.4.2. Construction of degenerate algal-specific 18S rDNA primersTo confirm the results obtained using the universal primers,

algae-specific degenerate primers were designed based on multi-ple sequence alignment of the 18S rDNA sequences using the soft-ware package BioEdit and Clustal W. The ribosomal encoded 18SrDNA gene sequences from a large data set corresponding to differ-ent genera of algae were obtained from NCBI. The specificity of thedegenerate primer sets was chosen for amplifying a �1.5–2.8 kblength, depending on the algal isolates. The specificity of thesedesigned primers was also tested in silico using NCBI-BLAST toknow the non-specific binding. The products of PCR (amplicons)were purified using a gel extraction kit (Qiagen, Hilden, Germany)and were cloned using the pGEM-T (Promega, USA) vector systemfollowing the manufacturer’s instructions. Colony-PCR was per-formed using universal M13 forward and reverse primers to con-firm the positive clones. Two individual clones from each isolatewere sequenced by Xcelris Genomics Pvt. Ltd (Ahmedabad, India).The NCBI-BLAST program was used to determine the sequencesshowing maximum homology.

2.5. Phylogenetic analysis

To ascertain the phylogeny of the isolated microalgae, their 18SrDNA sequences were aligned with the sequences of differentclosely related species that have been reported earlier. Multiplealignments were performed using Bio-Edit Sequence AlignmentEditor ver. 7.2.5. The algorithms available in MEGA ver. 6, namelyMaximum Likelihood (ML), Neighbour-Joining (NJ), and MaximumParsimony (MP), were employed for constructing phylogeneticrelationships among the algal isolates, and the reliability of the

branches was assessed by bootstrapping the data with 1000replicates.

2.6. Screening of microalgal isolates

Data on the growth curves of all the isolates were obtained dur-ing their cultivation. All the cultures with an initial cell count of3 � 106 cells /mL were cultivated under photoautotrophic condi-tions in a MC 1000-OD at 25 �C under 16 h of light (120 lE/m2/s)alternating with 8 h of darkness. The aeration rate was maintainedat 0.12 mL/min. Microalgal growth was monitored by measuringthe daily changes in OD at 680 nm with an OD viewer softwareattached to the cultivator. For studying growth kinetics, all isolateswere cultivated in BBM media. The growth rate of microalgalisolates was estimated by fitting the OD at the exponential phaseof each isolates to an exponential function in Eq. (1) (Wang et al.,2010).

GRðmuÞ ¼ ðlnODt� lnOD0Þ=t ð1Þwhere OD0 is the initial OD and ODt is the optical density measuredon day t.

The microalgal cells were cultured for about 9 days on averageand then cells were harvested, by centrifuging (10 min at 6000 rpmat 4 �C) followed by lyophilisation. The twenty two characterisedisolates were further evaluated for their efficiency in producingbiomass (dry biomass produced, expressed in milligrams per litreper day) and lipids (expressed as a percentage of total biomasson dry weight basis). The pellets were washed twice with steriledeionized water, lyophilized for 48 h, and their dry weight wasdetermined gravimetrically.

2.7. Lipid extraction and preparation of FAME

Total lipids were extracted from the freeze-dried biomass fol-lowing the method developed by Lewis et al. (2000) with somemodifications: a known quantity (10 mg) of dried cell biomasswas extracted in chloroform : methanol (2:1, v/v); the suspensionwas homogenised using vortex (Spinix, Maharashtra, India) for2 min followed by centrifuging for 15 min at 10,000g. The extrac-tion was repeated three times until the biomass became colourless.Method described by Christie and Han (2010) was employed tostudy FAME profiles. For preparation of FAME, 500 lL of toluenewas added into dried lipid samples followed by 10 lL of internalstandard (50 mg of C19:0-Methyl nonadecanoate), 400 lL offreshly prepared hydrogen chloride in methanol (prepared by add-ing 1 mL acetyl chloride drop wise to 10 mL of methanol on ice),200 ll of antioxidant butylated hydroxyl toluene (BHT) and incu-bated at 50 �C overnight. Following day, 1 mL of 5% NaCl and1 mL of hexane was added to dried samples. Finally, solvent layercontaining hexane were analysed using Gas chromatography.

2.8. Gas chromatography

The samples of FAMEs were analysed by gas chromatography(GC) (Agilent 122-2332 column, Santa Clara, California, USA) withmass spectrometry (MS). Each sample (2 lL) was injected into acapillary column (DB-23; 30 mm � 0.25 mm; film thickness,0.25 lm). The initial oven temperature of 70 �C was graduallyincreased by 10� C/min until it reached 180 �C, which was main-tained for 14 min. The oven temperature was raised again at4 �C/min to reach 220 �C, which was maintained for 36 min. Thedetector temperature was set at 250 �C. The injector was main-tained at 250 �C and a sample volume of 1 lL was injected. The car-rier gas, namely helium, was released at 2.0 mL/min. A hexaneinjection was used as a blank. The sample injections used C19:0(methyl nonadecanoate) as an internal standard to verify the

A.K. Minhas et al. / Bioresource Technology 211 (2016) 556–565 559

alignment of retention time with the calibration injection. The runtime for a single sample was 36 min. Fatty acids were quantified byusing the internal standard and identified by comparing the reten-tion time with that of a known standard mixture of FAs (SupelcoFAME mix C4-C24 (Bellefonte, Pennsylvania, USA). Fatty acid peakswere further analysed and integrated using a chemstation chro-matography software (Agilent Technologies, Germany).

2.9. Evaluation of microalgal oil properties for biofuel

Some properties of the microalgal isolates were evaluated toscreen them for biofuel production. A high cetane number (CN)of a FA denotes better combustion quality whereas the iodine value(IV) denotes the degree of unsaturation of the microalgal oil. A highIV indicates low oxidative stability of the fuel (Knothe, 2012).Hence, in the present study, CN, saponification value (SV), and IVwere used in evaluating the FAME profiles using the followingempirical Eqs. (2)–(4) proposed by Mandotra et al. (2014)

CN ¼ 46:3þ 5458SV

� ð0:225� IV ð2Þ

IV ¼X

½ð254� F � DÞ �MWÞ� ð3Þ

Table 2Molecular determination of microalgal isolates.

Microalgal isolate Designed primeramplicon product (kb)

Closest relative and GenBank acce

Chlorella sp. (Q12) 1.53 Chlorella sp. ZB-2014 KJ734869 (99Parachlorella kessleri

(Y8)1.77 Parachlorella kessleri strain SAG 21

KM020114 (99%)Chlorella sorokiniana

(USA)1.53 Chlorella sorokiniana strain UKM 2

(99%)Chlorella sorokiniana

(HS)1.49 Chlorella sorokiniana strain SAG 21

KF673387 (99%)Auxenochlorella

protothecoides(Goa)

1.53 Auxenochlorella protothecoides stra211-10a KM020150 (98%)

Scenedesmus sp. (V8) 2.06 Scenedesmus sp. KGU-D002 AB743Scenedesmus sp.

(Mn25)2.81 Scenedesmus sp. KGU-D002 AB743

Coelastrella sp. (Tn1) 2.81 Coelastrella striolata var. multistriat309 JX513880 (91%)

Coelastrella sp. (V3) 2.81 Coelastrella striolata var. multistriatCCALA; JX513880 (92%)

Coelastrella sp. (P19) 1.93 Coelastrella striolata var. multistriatCCALA; JX513880 (98%)

Coelastrella sp. (Tree) 2.40 Coelastrella terrestris strain CCALA476JX513882 (92%)

Scenedesmus sp.(Mn9)

2.81 Scenedesmus sp. NJ-1 JX286515 (9

Scenedesmus sp.(P155)

2.4 Scenedesmus sp. KGU-D002 AB743

Scenedesmus sp. (P58) 2.81 Scenedesmus sp. KGU-D002 AB743Scenedesmus sp.

(P115)2.63 Scenedesmus sp. NJ-1 JX286515 (9

Scenedesmus sp.(V11)

2.63 Scenedesmus sp. KGU-D002 AB743

Scenedesmus sp. (V9) 2.81 Scenedesmus sp. KGU-D002 AB743Scenedesmus sp.

(P152)2.63 Scenedesmus sp. KGU-D002 AB743

Scenedesmus bijugus(Ladakh)

1.55 Scenedesmus bijugus var. obtusiuscvoucher IZTA: 1830|KJ808696 (99%

Scenedesmus sp.(V15)

2.81 Scenedesmaceae sp. Tow 9/21 P-14AY197639 (93%)

Coelastrella sp. (P63) 2.40 Coelastrella sp. BUM11113; KC218Vischeria stellata

(P11)1.51 Vischeria stellata strain SAG 33.83

(98%)

NI: not identified. The species codes were defined based on the location from where thefrom Hyderabad (HS), from St. louis ‘‘USA”, from Vishakapatnam ‘‘V”, from Delhi ‘‘P”, frofrom Tree bark ‘‘Tree”, and from Jammu and Kashmir ‘‘Ladakh” respectively.

SV ¼X

½ð560� FÞ �MWÞ� ð4Þ

where, F is the percentage of each FA, D is the number of doublebonds, and MW is the molecular weight of the FA. The standard bio-fuel properties as laid down in ASTM D6751 and EN 14214 wereconsidered for evaluating the data.

2.10. Determination of microalgal carotenoids

Total carotenoids were obtained using the method described byGarcía-Plazaola et al. (2012). In general, 25 mg of freeze-dried bio-mass was subjected to sonication at 40 kHz for 5 min at room tem-perature (Branson, Danbury, Connecticut, USA) to break the cellwalls, and carotenoids and other compounds were extracted inacetone by continuous agitation for 3 min. The mixture of microal-gal cells was then centrifuged at 4000 rpm for 15 min. The super-natant contained pigments, and the extraction process wasrepeated two more times so that the supernatant was colourless.All the extractions were carried out under darkness or under dimlight to avoid photo-oxidation of the carotenoids. In the presentstudy, we maintained all the isolates under uniform conditions toenable an accurate comparison of lipids and carotenoids productiv-ities (expressed in milligrams per litre per day). The carotenoids

ssion No. Universal primeramplicon product (bp)

Phylogenetic relative position usinguniversal amplicon sequences

%) 669 Auxenochlorella sp. CCAP 211/611-11c 661 Chlorella sp. BUM11098

KP262476 350 Micractinium sp. TP-2008a CCAP 271/1

1-31 337 Chlorella sp. ZB-2014

in SAG 643 Auxenochlorella sp.

827 (91%) 401 Eustigmatos vischeri CCAP 860/7827 (92%) NI NI

a CCALA NI NI

a strain NI NI

a strain 342 Coelastrella striolata CAUP H 3602

NI NI

3%) 353 Chlorella emersonii CCAP 211/8P

827 (92%) 341 Chlorella emersonii CCAP 211/8P

827 (92%) 339 Coelastrella sp. SAG 24713%) 343 Coelastrella striolata CAUP H 3602

827 (92%) 658 Vischeria helvetica CCALA 514

827 (92%) 656 Poterioochromonas malhamensis DS827 (89%) 343 Chlorella emersonii CCAP 211/8P

ulus)

NI NI

w 667 Scenedesmaceae sp. Tow 9/21 P-14w

497 (95%) NI NIKF848919 338 Eustigmatos vischeri CCAP 860/7

y were collected. The isolates collected from Qatar were designated with code ‘‘Q”,m Mangalore ‘‘Mn”, from Yamuna river ‘‘Y”, from Tamil nadu ‘‘Tn”, from Goa ‘‘Goa”,

560 A.K. Minhas et al. / Bioresource Technology 211 (2016) 556–565

were analysed by injecting 10 lL of the carotenoid into an HPLCsystem (Shimazdu Co., Japan) equipped with a photodiode arraydetector. The pigments were separated using a reverse-phase C18

column coupled with a security guard column (Lune 3.0 mm C18

250 mm � 4.6 mm, 5 lm, Phenomenex, Torrance, California,USA). The binary mobile phase consisted of solvent A (acetonitrile:methanol, 7:1 v/v) and solvent B (acetonitrile:methanol:water:ethyl acetate, 7:0.96:0.04:2 v/v), and the following gradient methodwas used to separate the pigments, as recommended by García-Plazaola et al. (2012). The flow rate was set at 1.0 mL/min, and pig-ment content was detected by measuring the absorbance at450 nm. The chromatographic peaks were analysed by comparingthe retention time against the standard. The standards for luteinand canthaxanthin were bought from Sigma Chemical Co. (St.Louis, Missouri, USA); for astaxanthin and zeaxanthin, from Cay-man Chemical Co.; and HPLC-grade acetonitrile, methanol, andethyl acetate, from Fisher Scientific, USA.

3. Results and discussion

3.1. Isolation and identification of microalgae

The study aimed at to find species with the potential to producea range of useful product, particularly carotenoids and biofuel. Twohundred samples were collected from aquatic and terrestrial rockyhabitats from Asia, North America, and the Middle East (Table 1).Scanning electron microscopy imaging have been conducted inthe selected species which showed the lipids and biofuel potentialas depicted in Supplementary Fig. 1A–D. To further characterise,phylogenetic analysis using 18S rDNA sequences was performed.

Fig. 1. Phylogenetic analysis of algal isolates by the Maximum Likelihood method basedpercentage, based on 1000 replicates) that a given isolate belongs to the cluster in questout-group, (B) phylogenetic analysis of Scenedesmus sp. isolates by the Maximum Likelshows the ML (as a percentage, based on 1000 replicates) that a given isolate belongs to tZJU0205 was an out-group, (C) 18S rDNA sequence alignment of Scenedesmus sp. using Biofrom other species of Scenedesmus reported earlier and gathered from NCBI. Broken line

3.2. Molecular identification of microalgal isolates

Confirming the true phylogeny of an organism is importantbecause it can predict the adaptive traits developed through natu-ral selection and their usefulness in biotechnology. In the presentstudy, amplification of 18S rDNA sequence was carried out usingboth universal and self-designed primers. The amplification of18S rDNA using universal eukaryotic primers showed efficientamplification of a unique single band varying in size from 341 bpto 669 bp (Table 2) in P155 (Scenedesmus sp.) from chemically pol-luted river water and in Q12 (Chlorella sp.) from a backwater. Foraccurate identification of the isolates, we designed new algae-specific degenerate primers based on the complete 18S rDNAsequences of widely different species of algae that belonged to afew representative species of Chlorophyta, Charophyta, Ochro-phyta, Cryptophyta, Haptophyta, Rhodophyta, and Bacillariophyta.The newly designed primers aligned with and amplified more orless complete 18S rDNA sequences ranging from 1.5 kb to 2.8 kbdepending on the algal strain. The identity index was 88% for theforward primer (GCCCGTAGTAAWWCTASAGCTAATAC) and didnot amplify up in any other environmental cultures except algae,whereas that for the reverse primer (AAAAACGGGCGGTGTGTA-CAAAGGGC) was 92%; however, that primer also detected anotherclass of higher-order organisms. We tested the specificity of theprimers using different samples of algae from the environment,which were PCR-amplified, cloned, and sequenced. In none of theclones, DNA sequences from other microbes from higher-orderorganisms highlighted; these primer combinations were consid-ered useful as molecular tools for specific amplification of 18SrDNA gene of algal species alone. The primers used to amplifythe rDNA region successfully amplified DNA from all the twenty

on the Tamura-Nei model. (A) The value at each branching point shows the ML (as aion. Evolutionary analyses were conducted in MEGA6, Rhidospirillim rubrum was anihood method based on the Tamura-Nei model. The value at each branching pointhe cluster in question. Evolutionary analyses were conducted in MEGA6, Chlorella sp.-edit. 18S rDNA sequences from Scenedesmus sp. isolates were compared with thoses indicate the intron/gap regions.

Fig. 2. Biomass (mg/L/d) and lipid productivity (mg/L/d) of twenty two microalgal isolates in 9 days old culture.

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two microalgae isolates. The PCR products fell into two sizecategories, namely 1.491–1.938 kb and 2.4–2.8 kb. The amplifiedand cloned 18S rDNA sequences using degenerate algae-specificprimers were sequenced to obtain detailed information on theirclose relatives through GenBank accessions number (Table 2).Although we tried to analyse all the sequences together, due tothe differences in size, no common sequences were found forpair-wise analysis and for multiple sequence alignments. The phy-logenetic positions of the 18S rDNA sequences in the size category1.491–1.938 kb were analysed separately along with other closerelatives of algal species obtained through NCBI-BLAST (Fig. 1A

Fig. 3. Growth pattern of different microalgal species from diverse habitats cultivatedalternating with 8 h of darkness. (A) Freshwater isolates, (B) isolates from polluted rive

and B). Percentage similarity values obtained after pair-wise align-ment of the rDNA sequences of the isolates in that size category arelisted in Table 2. The relative phylogenetic positions based on thedesigned primers sequence were matched with the results ofmorphological studies and served to further confirm the identifica-tion of the isolates. Other unique intronic positions were observedin the isolates of Scenedesmus sp. collected from diverse habitats.These sequences were compared using the software Bio-edit todefine the novel pattern of intronic that aligned with known Scene-desmus sp. reported earlier (Fig. 1C). Although the use of universalprimers allows direct comparison between studies, in analysing

in BBM in MC 1000-OD for 10 days at 25 �C under 16 h of light (120 lE/m2/s)r water, (C) isolates from backwater, (D) isolates from terrestrial sites.

Table 3Biomass productivities, lipid content, lipid productivities, lutein content, astaxanthin and lutein productivity of twenty-two microalgal isolates under photoautotrophicconditions.

Isolates Growth rate(OD, mu)

Biomassproductivity(mg L�1 d�1)

Lipid productivity(mg L�1 d�1)

Lipid content(% dry wt.)

Astaxanthinproductivity(mg L�1 d�1)

Luteincontent (mg/g)

Lutein productivity(mg L�1 d�1)

Chlorella sp. (Q12) 0.40 169.81 ± 5.22 39.72 ± 3.89 24.97 ± 2.69 0.18 2.26 0.36Parachlorella kessleri

(Y8)0.39 159.49 ± 7.63 31.71 ± 4.34 21.42 ± 3.19 0.07 0.28 0.04

⁄Chlorella sorokiniana(USA)

0.32 134.94 ± 12.52 31.94 ± 1.26 28.58 ± 1.33 n.d. 0.68 0.07

Chlorella sorokiniana(HS)

0.27 102.26 ± 9.65 11.51 ± 2.61 13.55 ± 2.77 0.06 5.90 0.5

Auxenochlorellaprotothecoides(Goa)

0.53 167.11 ± 12.22 31.33 ± 3.64 24.97 ± 2.69 0.06 0.76 0.11

Scenedesmus sp.(Mn25)

0.30 103.23 ± 8.38 34.57 ± 2.64 36.53 ± 2.13 n.d. 0.0 0.00

Coelastrella sp. (Tn1) 0.36 124.51 ± 10.18 20.41 ± 5.32 13.15 ± 1.87 0.08 0.93 0.10Coelastrella sp. (V 3) 0.25 112.19 ± 14.98 26.91 ± 6.11 21.98 ± 1.72 0.07 6.49 0.81Coelastrella sp. (P19) 0.29 147.38 ± 12.87 38.96 ± 4.99 26.47 ± 1.41 0.08 0.47 0.05Coelastrella sp. (Tree) 0.32 90.18 ± 18.79 10.05 ± 1.98 15.83 ± 1.65 n.d. n.d. n.d.⁄Coelastrella sp. (P63) 0.37 152.93 ± 13.35 43.55 ± 6.28 23.94 ± 2.65 0.13 0.64 0.08Scenedesmus sp.

(Mn9)0.29 120.06 ± 17.89 22.86 ± 3.29 27.22 ± 1.60 0.08 1.33 0.12

Scenedesmus sp.(P155)

0.38 147.64 ± 11.95 33.53 ± 2.55 26.34 ± 1.97 n.d. 1.13 0.14

⁄Scenedesmus sp.(P58)

0.47 155.71 ± 14.34 43.81 ± 5.15 32.35 ± 2.49 n.d. 0.67 0.08

Scenedesmus sp.(P115)

0.35 106.76 ± 13.69 25.25 ± 6.32 23.61 ± 2.10 n.d. n.d. n.d.

Scenedesmus sp. (V11) 0.23 133.32 ± 16.71 22.17 ± 2.65 19.86 ± 2.29 0.03 0.26 0.03Scenedesmus sp. (V9) 0.42 138.44 ± 17.30 29.90 ± 5.13 23.13 ± 2.07 0.23 0.48 0.05Scenedesmus sp.

(P152)0.40 144.08 ± 5.59 22.67 ± 4.75 13.60 ± 1.96 0.09 1.8 0.24

Coelastrella sp. (V8) 0.37 83.33 ± 8.51 37.32 ± 1.95 36.52 ± 1.81 0.05 1.31 0.09⁄Scenedesmus bijugus

(Ladakh)0.31 174.77 ± 6.75 40.14 ± 3.31 24.24 ± 1.76 0.27 2.9 0.47

Scenedesmus sp. (V15) 0.41 127.71 ± 15.63 26.66 ± 2.62 25.15 ± 2.04 0.08 1.00 0.10Vischeria Stellata

(P11)0.26 120.24 ± 16.01 16.24 ± 1.73 17.15 ± 1.31 0.08 1.50 0.13

Data calculated at average of nine days; n.d. not detectable. Experiments were performed in triplicates and data for biomass and lipid productivities are expressed asmean ± SD.

Table 4Comparison of lipid productivity of microalgal isolates with other published data.

Microalgal isolates Lipid productivity(mg L�1d�1)

References

Chlorella sp.(Q12) 39.72 ± 3.89 This study16h

Chlorella SDEC-6 9.6 Song et al.(2014)24h

Chlorella sp. 83.3 Cheirsilp and Torpee(2012)16h

Scenedesmus sp.(P58)

43.81 ± 5.15 This study16h

Scenedesmus bijugus(Ladakh)

40.14 ± 3.31 This study16hr

Scenedesmus bijuga 8.22 Shin et al.(2015)Scenedesmus sp. 21.5 Tripathi et al.(2015)AG,18hr

Scenedesmus sp.SDEC-8

13.52 Song et al.(2014)no aeration,N

and P limitations

Coelastrella sp. (P63) 43.55 ± 6.28 This study16h

Coelastrella sp. M60 13.9 Karpagam et al.(2015)AG,12hr

16hCulture grown with 16 h light and air.24hCulture grown with 24 h light and air.AG,18hCulture grown with agitation and 18 h light.AG,12hCulture grown with agitation and 12 h light.N and P limitationsCultures supplemented with low nitrogen and phosphorusconcentrations.

562 A.K. Minhas et al. / Bioresource Technology 211 (2016) 556–565

environmental samples, such use places some limitations on theinterpretation of results. These limitations can be overcome byobtaining whole sequences from 18S rRNA genes as referencetrees. Since the selection of primers has a significant impact on

the results obtained from environmentally diverse ecosystems,such reference trees could be used for studying large algal popula-tions. The present study thus provided a designed primer pair moresuitable as a molecular marker in studying eukaryotic diversity orin characterising microalgae. However, the overall morphologicalfeatures and 18S rDNA sequences confirm the taxonomical posi-tions of these isolates to great extent.

3.3. Comparative analysis of photo-autotrophic growth, biomass,lipids, and FAME profile of microalgal isolates

Rapid growth is an important prerequisite to obtaining a highcell density, intracellular lipids, under optimal culture conditions(Talebi et al., 2013). Under identical conditions, the isolates varieda great deal in their ability to produce biomass: the productivityranged from 83.33 ± 8.51 mg L�1 d�1 to 174.77 ± 6.75 mg L�1 d�1

(Fig. 2). Microalgal growth as assessed by OD in the isolates drawnfrom four different habitats, namely freshwater, chemically pol-luted river water, backwater, and land, is shown in (Fig. 3A–D).The average specific growth rate was estimated at the exponentialgrowth phase (Table 3). The growth varied among the isolates inthe same medium (BBM) under similar culture conditions. In thepresent study, lipid productivity and biomass productivity –expressed as daily production, in milligrams, of biomass or lipidsproduced per litre of the medium – were considered equallyimportant in selecting appropriate strains for biofuel production.

A.K. Minhas et al. / Bioresource Technology 211 (2016) 556–565 563

Under experimental conditions, total lipid content of freshwaterisolates was highly variable (13.15 ± 1.87–36.52 ± 1.81% of the dryweight) whereas that of backwater isolates peaked at36.53 ± 2.13% and that of land isolates was average 15.83 ± 1.65(Table 3). Lipidproductivity variedbetween10.05 ± 1.98 mg L�1 d�1

and 43.81 ± 5.15 mg L�1 d�1. Of all the Scenedesmus isolates studied,one from chemically polluted river water (P58) and one from fresh-water (Ladakh), showed higher productivity 43.81 ± 5.15 mg L�1

d�1 and 40.14 ± 3.31 mg L�1 d�1 for lipids and 155.71 ±14.34 mg L�1 d�1 and 174.77 ± 6.75 mg L�1 d�1 for biomass, respec-tively (Table 3) – than that reported elsewhere, such as (1) Scenedes-mus sp. (Tripathi et al., 2015), and Scenedesmus SDEC-8 (Song et al.,2014) under non-aerated conditions. Chlorella sp. (Q12) showedhigher productivity (39.72 ± 3.89 mg L�1 d�1 for lipids and169.81 ± 5.22 mg L�1 d�1 for biomass) among previously reportedChlorella sp., including one reported by Cheirsilp and Torpee(2012), Chlorella sp. SDEC-6 (Song et al., 2014) as shown in Table 4.The isolate from high altitudes, namely Scenedesmus bijugus(Ladakh), also produced more biomass (174.77 ± 6.75 mg L�1 d�1)and lipids (40.14 ± 3.31 mg L�1 d�1) than the figures reported for S.bijuga grown on wastewater effluent diluted with BG11 medium(Shin et al., 2015). The other group of isolates including Coelastrellashowed high biomass and lipid productivity. Coelastrella sp. (P63)from chemically polluted river water produced 152.93 ±13.35 mg L�1 d�1 of biomass and 43.55 ± 6.28 mg L�1 d�1 of lipids– figures that were comparable to those reported by others, suchas Coelastrella M 60 (Karpagam et al., 2015) (Table 4). From aboveresults, microalgal isolates from highly chemically polluted as wellas backwater habitats demonstrated the potential to produce largequantities of lipids and biomass. Scenedesmus sp. (P58), S. bijugus(from Ladakh), Coelastrella sp. (P63), and Chlorella sorokiniana(USA) were themost promising lipid and biomass producers amongall the twenty two isolates (marked by an asterisk in Fig. 2).

Besides lipid productivity, FA profiles of the isolates were fur-ther examined and compared because FA composition and thetypes of FAs produced are considered important for the quality ofbiodiesel. The quality depends mainly on the unsaturation ratiobecause unsaturated fatty acids (UFA) enhance cold-flow proper-ties whereas saturated FAs maintain good oxidative stability (Wuand Miao, 2014). In the present study, the FAs were predominantlyesterified and the proportions of major FAs were determined at the

Fig. 4. Fatty acid composition (wt%) of twenty two microalgal isolates under tested condiatoms in each.

average of nine days by GC–MS. Although the FAs were very simi-lar, the level of each FA varied significantly (Fig. 4). Compared toother isolates, Scenedesmus sp. (V15) produced 23.4% more oleicacid; Scenedesmus sp. (Mn25) produced 22.8% more; Chlorellasorokiniana (USA), 21.7%; and S. bijugus (from Ladakh, India),22.9% (Fig. 4). In fact oleic acid is one of the most desirable oil com-ponents for biofuel since it gives a good balance between cold flowproperty and oxidative stability (Hoekman et al., 2012). All theabove four isolates showed a good biofuel characteristics. In thepresent study, Parachlorella kessleri was the only isolate that pro-duced large amounts of C 16:0 (up to 59.1%). Microalgae rich inMUFA (particularly, palmitoelic acid (16:1) and oleic acid (18:1)(Hoekman et al., 2012) and SFAs are good for biodiesel production(Stansell et al., 2012).

To ascertain the suitability of the isolates as producers of bio-fuel, a few other properties of the lipids, namely CN, IV, and SV,were analysed based on FAME profiling. According to theEN14214 standard, SV and CN should be neither higher than120 g I2/100 g not lower than 47 g I2/100 g (Sun et al., 2014). Sixisolates in the present study met the CN norms specified in USA(ASTM D6751) and twelve, those in Europe (EN 14214) (Fig. 4).Four isolates failed to meet any of the above specifications; how-ever, they be important because they have a high (>13%) propor-tion of C18:3 acids. In the present study, IV for Chlorella sp.(between 12 g I2/100 g and 103 g I2/100 g) was consistent with thatreported for Chlorella sp. by Wu and Miao (2014). Thus, many ofthe isolates among the twenty two were suitable for biofuel pro-duction and the rest had other valuable properties (Table 5). Thehigh content of SFAs and oleic acid in a few of the microalgae iso-lated in the present study shows their potential for biofuelproduction.

3.4. Lutein and astaxanthin productivity

It is vital to select isolates that have the potential to producelarge quantities of the targeted products, lipids and carotenoids iftheir use is to be commercially cost effective. The ability of theisolates to produce lutein and astaxanthin was also assessed. Themajor carotenoid was lutein, followed by astaxanthin. The isolateswere grown autotrophically and without any known stress inMC 1000-OD and their production of intracellular lutein and

tions. In each bar, fatty acids are shown in descending order of the number of carbon

Table 5Percentage of SFA, MUFA, PUFA and estimated biodiesel properties from the FAME profile of twenty two microalgal isolates under photoautotrophic conditions.

Microalga isolate SFA(%)

MUFA(%)

PUFA(%)

CN SV(mg NaOH/gof oil)

IV (g/100 gof oil)

Heating value(MJ/kg)

Biodiesel standardspecification

Chlorella sp. (Q12) 27.0 8.39 54.78 47.55 188.41 123.17 39.80 ASTM D6751Parachlorella kessleri (Y8) 70.6 0.53 0 80.19 159.46 1.46 42.86 EN 14214Chlorella sorokiniana (USA) 24.67 22.32 37.04 53.98 176.08 103.61 40.63 EN 14214Chlorella sorokiniana (HS) 33.08 3.5 47.36 50.79 172.88 120.34 42.34 ASTM D6751Auxenochlorella protothecoides (Goa) 24.15 10.48 44.1 50.90 172.93 119.78 40.50 ASTM D6751Scenedesmus sp. (Mn25) 30.86 25.83 27.2 48.74 197.37 112.03 42.65 ASTM D6751Coelastrella sp. (Tn1) 31.2 13.49 47.4 68.88 137.77 75.70 39.60 EN 14214Coelastrella sp. (V3) 18.43 2.94 68.3 45.52 192.50 129.45 39.43 –Coelastrella sp. (P19) 34.28 13.04 47.7 39.29 184.35 162.71 42.13 –Coelastrella sp. (Tree) 23.94 15.761 30.74 64.10 86.40 146.10 39.83 EN 14214Coelastrella sp. (P63) 30.1 18.03 44.7 49.61 193.40 110.69 40.08 ASTM D6751Scenedesmus sp. (Mn9) 13.8 1.75 50.3 47.03 179.70 131.73 39.56 ASTM D6751Scenedesmus sp.(P155) 19.4 11.22 56.4 55.52 140.08 132.16 41.70 EN 14214Scenedesmus sp. (P58) 35.6 19.79 23.0 42.36 183.09 149.96 39.67 –Scenedesmus sp. (P115) 35.3 21.73 24.4 63.74 162.66 71.60 41.60 EN 14214Scenedesmus sp. (V11) 35.37 21.75 24.4 61.26 168.94 77.08 41.31 EN 14214Scenedesmus sp. (V9) 20.0 5.88 57.86 42.31 176.13 155.42 39.92 –Scenedesmus sp. (P152) 31.57 24.09 35.22 51.95 188.72 103.41 40.10 EN 14214Scenedesmus sp. (V8) 30.6 22.09 34.0 54.59 180.24 97.70 40.58 EN 14214Scenedesmus bijugus (Ladakh) 33.51 26.02 31.49 53.37 188.89 96.96 40.23 EN 14214Scenedesmus sp. (V15) 41.9 24.46 31.3 55.79 178.55 93.64 40.00 EN 14214Vischeria stellata (P11) 21.84 26.51 7.3 82.59 130.53 24.53 43.70 EN 14214

CN, cetane number; SV, saponification value; IV, iodine value; SFA, saturated fatty acid; MUFA, monounsaturated fatty acid; PUFA, polyunsaturated fatty acids.

Fig. 5. Top ten isolates showing lipids, biomass and lutein productivity (mg/L/d).

564 A.K. Minhas et al. / Bioresource Technology 211 (2016) 556–565

astaxanthin as well as of biomass was recorded at average of ninedays (Table 3). Chlorella sp. (Q12), the most productive isolate inthe present study, producedmore biomass, lutein, and astaxanthin.S. bijugus (Ladakh), the second most productive isolate, was com-parable to Scenedesmus sp. (Yen et al., 2011). Sánchez et al.(2008) claimed that Scenedesmus almeriensis are the best candi-dates with high lutein content. Two other isolates, namely Coelas-trella sp. P63 and V3, were also highly productive. Whereas theisolates (V3) in the present study recorded the highest lutein con-tent (up to 6.49 mg/g) with high lutein productivity (0.81 mg L�1

d�1). The present study shows that a few of the isolates demon-strated the potential to produce carotenoids as well as lipids, apotential that could be exploited for obtaining multiple products.

On basis of overall results top ten isolates considering lipids, luteinand biomass productivity is depicted in Fig. 5.

4. Conclusions

The overall results from the present study confirm that some ofthe isolates S. bijugus, Coelastrella sp., Chlorella sp., and Auxenochlor-ella protothecoides showed the potential to produce significantquantities of multiple products. The designed primer sets providedbetter insights into biodiversity and helped in finding new speciesthat would have been hard to find through microscopic observa-tions alone. S. bijugus was the most productive among the four

A.K. Minhas et al. / Bioresource Technology 211 (2016) 556–565 565

promising microalgal isolates selected. To the best of our knowl-edge this is the first report of a microalgal isolate with multiplepotential. Future studies can further maximise metabolites produc-tivity potential.

Acknowledgement

The first author acknowledges fellowship provided by DeakinUniversity and infrastructure support extended by The Energyand Resources Institute. The assistance provided Ms. Deeprajnifor GC–MS, and by Ms. Shikha and Mr. Chandrakant for SEM is dulyacknowledged. Mr Pavan Sunkireddy and Mr Sachin Rastogi contri-bution for assisting in collections is duly acknowledged. The sup-port extended by Dr R K Pachauri (Director-General, TERI) and byProf Jane Dan Hollander (Vice Chancellor, Deakin University) is alsogratefully acknowledged.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.biortech.2016.03.121.

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