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Chapter I: Characterization of indigenous Botryococcus sp. and microalgal lipid production

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Chapter I

Characterization of Indigenous Botryococcus sp. and

Microalgal Lipid Production


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Summary

This chapter includes the experimental procedures; materials and methodologies adopted

for the isolation, characterization, growth and lipids production from microalgae.

Botryococcus species procured from different culture collection centers were evaluated

for their adaptability to different culture conditions like different nitrogen sources, pH,

Salinity, different autotrophic media and the influence of media constituents on growth of

the algae using response surface methodology. RSM studies revealed that the nitrogen:

phosphate at the ratio of 1:0.5 was found to influence the growth and biomass yields of

the organism. Among the different autotrophic media used (Bold basal medium (BBM),

and bold basal with ammonium carbonate (BBMa), BG11 and modified Chu 13 medium,

BG11 was found to be the best medium for the growth and biomass production, although

the organism showed appreciable level of growth and biomass production in all the tested

media. It has shown its adaptability to varied range of salinity as well (17 mM to 85

mM). Among the different nitrogen sources tested (ammonium nitrate, calcium nitrate,

urea, sodium nitrate and potassium nitrate), potassium nitrate exhibited maximum

biomass yield. Botryococcus species were grown in different pH ranging from 6 to 8.5

and has shown its tolerance to the tested range. Race A strains of the genus Botryococcus

were found to produce lipid rich biomass (15 to 35% on dry weight) and upon fatty acid

analysis they were found to produce oleic, lenolenic, stearic and palmitic acids as major

fatty acids along with traces of pharmaceutically important alkyl substituted fatty acids

such as 12-methyl hexadecanoic acid, 14-methyl tetradecanoic acid and 16-methyl

heptadecanoic acid. Thus the algae Botryococcus appears to be potential organism for

lipid rich biomass production.

Therefore the study involved the isolation of indigenous Botryococcus species for

its possible industrial exploitation. Samples of the green, colonial, unicellular microalgae

Botryococcus sp. were collected from freshwater ponds in Mahabalipuram (Latitude

12o37' in the North to Longitude 80

o14' in the East.) Tamil Nadu, India. It was tentatively

identified to be Botryococcus sp. The hydrocarbon analysis of its hexane extracts showed

hexadecane (10.15%), heptadecane (17.82%) and pentacosane (18.74%) as its major

hydrocarbons. Further the 18S rRNA sequence (GU182893.1) analysis has confirmed its

taxonomical relationship to the order Trebouxiophyceae and has shown similarities with


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the reported species of the genus Botryococcus and in particular to Botryococcus braunii.

Based on morphological features and 18S rRNA sequence analysis the Indian isolate was

assigned as Botryococcus mahabali. Botryococcus braunii (LB 572) was obtained from

the University of Texas, U.S.A. B. braunii (SAG 30.81) was from the Sammlung von

AlgenKulturen, pflanzenphysiologisches Institut, Universitat Gottingen, Germany. B.

braunii (Strain 1) and B. braunii (Strain 2) obtained from university of Berkeley, UK.

Botryococcus Sp. (DB-8) was from University of Pune, Pune, India and Botryococcus Sp.

(MCRC) was of Murugappa Chattiar Research Centre, Chennai, India. The CFTRI isolate

B. mahabali was evaluated for its genetic variations & genetic relationships with the

other species belonging to different geographical locations and different chemical race

using 35 decamer RAPD primers. Several RAPD primers were selected after their

preliminary screening for their ability to produce clear and multiple bands. The analyses

resulted in the amplification of totally 407 bands of 100-3000 bp, of which 380 bands

were polymorphic, corresponds to 93.3% genetic diversity. The ability to distinguish

genotypes and the Resolving power (Rp) of the primer showed a linear relationship. From

these data, a genetic similarity matrix and the dendrogram were obtained by using the

unweighted pair group method with arithmetic mean (UPGMA). The RAPD analysis

produced genetic similarity coefficients ranged from 0.3312 to 0.7388. The study resulted

in the identification and molecular classification of Indian strains with that of other

strains belonging to different geographical locations. The study also revealed the clear

genetic distances between A race strains of B. braunii and B race strains of the same

species. Indigenous strains of Botryococcus sp. were further analyzed for their

hyrocarbons and fatty acids profiles and have shown some common chemical profiles.

All the three Indigenous strains of Botryococcus species and other microalgae such as

Dunaliella bardawil and Haematococcus pluvialis were evaluated for their lipid

production and for specialty lipids like poly unsaturated fatty acids have been detailed.

Analysis of fatty acids profiles of Dunaliella and Haematococcus has revealed that they

were found to produce hexadecanoic acid (16:0), oleic (18:1), linoleic (18:2), and

linolenic acids (18:3) as their major fatty acids. Dodecanoic acid (12:0), tetradecanoic

acid (14:0), hexadecanoic acid (16:0), oleic (18:1), linoleic (18:2) and linolenic acids

(18:3) were the major fatty acids produced by Botryococcus mahabali.


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2.1. Introduction

There is an increasing quest all over the world for the exploration of potential microalgae

for various industrial applications from nutraceutical to biodiesel feed stock. The green

colonial lipid rich microalgae Botryococcus is widespread in freshwater, brackish lakes,

reservoirs and ponds (Metzger and Largeau 2005). Botryococcus is characterized by its

ability to synthesise and accumulate very high levels of lipids. These lipid substances

include numerous hydrocarbons, i.e. highly reduced compounds comprising only carbon

and hydrogen as elements (Brown et al., 1969). Being a photosynthetic organism, it has

been reported to reduce CO2 emissions by 1.5 X 105

tons/yr /8.4 × 103 ha (Sawayama et

al., 1999) and thus it offers an eco friendly process for production of lipid and other

bioactive compounds along with its carbon dioxide mitigation credits. The existence of

Botryococcus sp. in USA, Ivory Coast, Portugal, Bolivia, Morocco, India, Philippines,

Thailand, France and West Indies has confirmed its wide distribution (Chandra 1964;

Metzger et al., 1985; Wolf et al., 1985; Okada et al., 2000). Further, these geographical

regions belong to different climatic zones like continental, temperate, tropical and alpine

indicating its ability to grow in varied climatic conditions (Tyson, 1995). Because of its

potential to produce large amounts of lipids and hydrocarbons, exploration for newer

strains and species of the genus Botryococcus is increasing day by day and till date more

than 60 Botryococcus strains were cultivated in laboratory (For a non-exhaustive list, see

Metzger and Largeau 1999) and the exploration is still on. Most of the Botryococcus

strains cultivated in laboratory and wild samples collected from lakes are analyzed for

their lipid production (Metzger and Largeau, 1999) and are reported to produce 5 to 42%

of lipids and 0.1 to 61.0% hydrocarbons on their dry weight (Metzger and Largeau 1999,

2005; Dayananda et al., 2007a; Ranga Rao et al., 2007; Tran et al., 2009; Eroglu and

Melis, 2010; Samori et al., 2010). Therefore there is an increasing quest to isolate newer

species and strains of the genus Botryococcus produce lipids and other chemicals of

industrial importance. Morphological heterogeneity and the chemical nature of

hydrocarbons and the degree of lipid and polysaccharide production were found to exist

within the species and among the other species of the genus Botryococcus. Finding the

genetic polymorphism in different species of the genus Botryococcus and within the

species belonging to different chemical races of B. brauni using RAPD (random


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amplified polymorphic DNA) technique was employed. RAPD technique is being used

widely as an efficient technique in detecting genetic variations (Williams et al., 1990)

even in closely related organisms such as two near isogenic lines (NIL). At present,

RAPD markers have been successfully applied to detect the genetic similarities or

dissimilarities in various plants, algae, fungi and bacteria. (Carvalho et al., 2004; Comeau

et al., 2004; Martins et al., 2004; Ramage et al., 2004; Modgil et al., 2005; Martinez et

al., 2006; Touzet et al., 2007; Zhao et al., 2007, 2008; Olmos et al., 2009; Small et al.,

2009; Tilman et al., 2009). RAPD was employed here to differentiate the genetic

variations among the different chemical races of B. braunii and between the indigenous

strains of Botryococcus.

2.2. Materials and methods

2.2.1. Source of Botryococcus sp.

Botryococcus braunii (LB 572) was procured from the University of Texas, U.S.A.

Botryococcus braunii (SAG 30.81) from the Sammlung von AlgenKulturen,

pflanzenphysiologisches Institut, Universitat Gottingen, Germany. Botryococcus braunii

(Strain 1) and Botryococcus braunii (Strain 2) were obtained from university of Berkeley,

UK. Botryococcus sp. (DB-8) was obtained from the University of Pune, Pune, India and

Botryococcus sp. (MCRC) from Murugappa Chattiar Research Centre, Chennai, India.

Stock cultures were maintained routinely on both liquid and agar slants of Modified Chu

13 medium (Table 4) (Largeau et al., 1980) by regular sub-culturing at two-week

intervals. Cultures were maintained at 25 ± 1°C with 1.2 ± 0.2 klux and a 16:8 light: dark

cycle.


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2.2.2. Dunaliella bardawil strain and culture condition

Indigenous strain of D. bardawil was isolated from the Sambar lake of Rajasthan, India

and was maintained in Plant Cell Biotechnology Department of CFTRI. The culture was

maintained in both agar slant and liquid AS-100 medium (Vonshak, 1986) by regular sub

culturing at two-week intervals. Cultures were maintained at 25 ± 1°C with 1.2 ± 0.2 klux

and a 16:8 light: dark cycle. Chemical composition of the AS-100 medium is shown in

Table 5. Two weeks grown stock cultures of Dunaliella bardawil were inoculated into

freshly prepared AS-100 media and incubated for four weeks at 25 ± 1oC temperature

with 1.2 ± 0.2 klux and 16:8 light dark cycle for two weeks. Cultures were harvested and

estimated for biomass and total lipid yields. Fatty acid profiles were analyzed by GCMS.

Table 4. Chemical composition of modified CHU 13

Constituent Gram/Liter

KNO3 0.2

K2HPO4 0.04

MgSO4 7H2O 0.1

CaCl2 6H2O 0.08

Ferric citrate 0.01

Citric acid 0.02

pH 7.5

Micro nutrients ppm

Boron 0.5

Manganese 0.5

Zinc 0.05

Copper 0.02

Cobalt 0.02

Molybdenum 0.02

Source: Largeau et al. (1980)


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2.2.3. Haematococcus pluvialis strain and culture condition

Haematococcus pluvialis (SAG 19-a) culture was obtained from Sammlung von

Algenkulturen, Pflanzen Physiologisches Institüt, Universität Göttingen,

Göttingen,Germany. Stock cultures of H. pluvialis were maintained on both semisolid

and liquid autotrophic Bold’s basal medium (BBM) (Kanz and Bold, 1969). The

composition of the BBM is provided in Table 6.1 and Table 6.2. All the cultures were

maintained at 25 ± 1oC temperature with 1.2 ± 0.2 klux and a 16:8 light dark cycle. Two

weeks grown stock cultures of Haematococcus pluvialis were inoculated into freshly

prepared Bold’s basal medium media and incubated for four weeks at 25 ±1ºC

temperatures with 1.2 ± 0.2 klux and 16:8 light dark cycle for two weeks. Cultures were

harvested and estimated for biomass and total lipid yields. Fatty acid profiles were

analyzed by GCMS.

Table 5. Chemical composition of AS-100 media

Chemicals Quantity (g L-1)

MgSO4 2.44

CaCl2 0.3

KH2PO4 0.05

KCl 0.6

NaNO3 1.0

NaCl 50.0

Tris buffer 1.0

Trace metal solution (10.0 mL L-1)

H3BO3 3.426 mg L-1

CoCl2.6H2O 1.215 mg L-1

MnCl2.4H2O 0.432 mg L-1

ZnCl2 31.5 mg L-1

(NH4)6.Mo7O2.4H2O 31.19 mg L-1

Conc.H2SO4 1.0 mL

*Chelated Iron solution (3.0 mL L-1)

Na2EDTA 10gL-1

FeCl3.6H2O 0.81 mg L-1

Source: Vonshak (1986)


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Table 6.1 Chemical composition of BBM

Constituents g L-1

FeSO4.7H2O 0.005

CaCI2.2H2O 0.024

NaNO3 0.25

MgSO4.7H2O 0.073

EDTA 0.045

K2HPO4 0.074

KH2PO4 0.175

Trace elements (Table 6.2) 1 ml

2.3. Studies on effect of culture conditions on Botryococcus sp.

2.3.1. Effect of different nitrogen sources

The experiment was carried out in Erlenmeyer flasks (250 ml) containing 80 ml of Chu

13 modified medium (Largeau et al., 1980) with different nitrogen sources such as

sodium nitrate, potassium nitrate, ammonium nitrate, calcium nitrate and urea in terms of

nitrogen equivalent to potassium nitrate, which is a nitrogen source in modified Chu 13

medium (Table 4), to study their effect on B. braunii (SAG 30.81 and LB 572) growth

Table 6.2 Composition of BBM trace elements

Trace constituents g/100ml-1

H3BO3 0.3100

MnSO4.4H2O 0.2230

ZnSO4.7H2O 0.0287

(NH4)6MoO 24.4H2O 0.0088

(CoNO3)2.4H2O 0.0146

Na2WO4.2H2O 0.0033

KBr 0.0119

KI 0.0083

Cd(NO3)2.4H2O 0.0154

NiSO4(NH4)2SO4.6H2O 0.0198

VoSO4.2H2O 0.0020

AlCl3.6H2O 0.00237

Source: Kanz and Bold (1969)


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and biomass yields. The culture flasks were incubated for 4 weeks at 25 ± 1oC

temperature with 1.2 ± 0.2 klux and 16:8 light dark cycle.

2.3.2. Effect of pH

The experiment was carried out in Erlenmeyer flasks (150ml) containing 40 ml of Chu 13

modified medium and the pH of the medium was adjusted to 6.0, 6.5, 7.0, 7.5, 8.0 and 8.5

before autoclaving. All the flasks were inoculated with uniform volume of B. braunii

(LB 572) and B. braunii (SAG 30.81) cultures. The culture flasks were incubated for four

weeks at 25 ± 1oC temperature with 1.2 ± 0.2 klux and 16:8 light dark cycle and the

biomass yields were analyzed.

2.3.3. Effect of Salinity

A set of 500 ml Erlenmeyer conical flasks were taken and 200 ml of modified Chu 13

medium was distributed and sodium chloride was added in the range of 17 mM to 85 mM

to the flasks and inoculated with two weeks old culture of B. braunii LB 572. The culture

flasks were incubated for 18 days at 25 ±1oC temperatures under 1.2 ± 0.2 klux light

intensity and 16:8 hr light dark cycle.

2.3.4. Effect of different autotrophic media

As shown in Table 7, various autotrophic media differed mainly in their nitrogen source

and concentration. BG 11 contains high amount of sodium nitrate while modified Chu 13

contained potassium nitrate and modified BBM contained ammonium carbonate. A two

week old cultures of both B. braunii LB 572 and SAG 30.81 grown in modified Chu 13

(1X) media were used as inoculum at 25% for all experiments. Cultures were grown

autotrophically in Bold Basal (BBM) (Kanz and Bold, 1969) and modified BBM, BG11

(Richmond, 1986), modified Chu13 media (Largeau et al., 1980). Cultures of B. braunii

were incubated in three different culture conditions. One set at 25 ±1oC temperature with

1.2 ± 0.2 klux light intensity and 16:8 light dark cycle; second set at 25 ±1oC temperature

with continuous light intensity of 1.2 ± 0.2 klux and third set at 25 ±1oC temperature

with continuous light intensity of 1.2 ± 0.2 klux on shaker with 90 rotations per minute.

All the cultures were harvested after 6 weeks and estimated for growth in terms of their

biomass yields.


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Table 7. Composition of autotrophic culture media*

Composition (g L-1)

Modified Chu 13

BG11

BBM

BBMa 0.25X 0.5X 0.75X 1X 2X

KNO3 0.05 0.1 0.15 0.2 0.4 - - -

NaNO3 - - - - - 1.5 0.25

K2HPO4 0.01 0.02 003 0.04 0.08 0.04 0.074 0.074

KH2PO4 - - - - - - 0.0175 0.0175

CaCl2.2H2O 0.02 0.04 0.06 0.08 0.16 0.036 0.024 0.024

MgSO4. 7H2O 0.025 0.05 0.075 0.1 0.2 0.075 0.073 0.073

Na2CO3 - - - - - 0.02 - -

NaCl - - - - - - 0.025 0.025

FeSO4 - - - - - - 0.005 0.005

EDTA - - - - - 0.001 0.045 0.045

Citric acid 0.025 0.05 0.075 0.1 0.2 0.006 - -

Ferric ammonium citrate - - - - - 0.006 - -

Ferric citrate 0.0025 0.005 0.0075 0.01 0.02 - - -

Ammonium carbonate - - - - - - - 0.157

*The respective trace solution were added

2.3.5. Influence of Culture age

Experiment was conducted to study the effect of culture age on B. braunii growth. Two

weeks old cultures of B. braunii (LB 572 and SAG 30.81) were used as inoculum at 20%

(v/v) and added to the Erlenmeyer flasks (150ml) containing 40 ml of Chu 13 modified

medium and incubated at 25 ± 1oC temperature with 1.2 ± 0.2 klux and 16:8 light dark

cycle. The culture flasks were harvested at regular intervals of 7 days (week) and

biomass yields were analyzed.

2.3.6. Influence of media constituents on Botryococcus growth using RSM

Botryococcus braunii (SAG 30.81) was obtained from Algal Culture Centre, University

of Gottingen, Germany. The stock culture was maintained on modified Chu13 medium

(Largeau et al., 1980) both in liquid medium and in slants. All the experiments were

carried in 150 ml Erlenmeyer flasks containing 40 ml CHU 13 medium with varied

concentrations of potassium nitrate, potassium dihydrogen phosphate, magnesium

sulphate and ferric citrate as given in Table 4. Ferric citrate-citric acid mixture was

maintained in the ratio of 1:10 by adding citric acid and keeping other constituents of the

medium constant. The culture flasks were incubated at 25 ± 1oC temperature, 1 ± 0.2 klux


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light intensity with 16hr: 8hr light dark cycle. The culture flasks were inoculated with

25% (v/v) of inoculum.

2. 3.6.1. Experimental design and analysis of data

The experimental design employed was a 4-variable (5 levels of each variable), second

order orthogonal design with 5 replications at the centre points (0, 0, 0, 0) in coded levels

of variables (-1.414, -1, 0, 1, 1.414) (Akhnazarova and Kafarov,1982). The four

independent variables for growth were concentrations of X1 potassium dihydrogen

phosphate, X2 potassium nitrate, X3 magnesium sulphate and X4 ferric citrate.

The experimental design in the actual (X) and coded (x) levels of variables is shown in

Table 8. The yield of biomass in the culture was approximated by a second degree

polynomial (Eq.1) with linear, quadratic and interaction effects (in coded level of

variables) using the method of least squares (Little and Hills, 1978).

ijkj

n

i

n

jiiji

n

iiijk xxbxbby ∈+++= ∑∑∑

= == 1 110 (1)

i ≤ j

The number of variables, denoted by n, and i, j and k, are integers. The coefficients of the

polynomials are represented by bo, bi and bij, and ∈ijk is the random error; when i < j,

bij represents the interaction effects of the variables xi and xj. The response surface graphs

were obtained from the regression equations in actual level of variables, keeping the

response function on the Z axis with X and Y axes representing the two independent

variables while keeping the other (third) variable constant at their centre (corresponding

to 0 level in coded level) points. The detailed analysis of variance (ANOVA) was

conducted in coded level of variables to know the effects of individual variables.

Stepwise deletion of individual non-significant (p ≤ 0.10) terms were conducted followed

by recalculation of the coefficients of the regression equation, to arrive at the final

regression equation in coded level which is better converted to actual level of variables.


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2.3.6.2. Optimization

Optimization was done by employing canonical analysis (Myers, 1971; Khuri and

Cornell, 1989) wherein the levels of the variables (x1, x2, x3, x4) (within the

experimental range) were determined to obtain the maximum yield of biomass

production. Optimization of the response function consists of the translation of the

response function (yk) from the origin to the stationary points (xo) (Myers, 1971). Then

the response function was expressed in terms of the new variables, the axes of which

correspond to the principal axes of the contour system. Further the roots (λ1, λ2, λ3, λ4)

of the auxiliary equation (λ2 - λ+1 =0) were calculated initially to know the nature of

optimum. The response function is maximum if all the roots have negative values, and

minimum if all roots have positive values. If some of the roots have positive values and

some negative, then it is the situation of a saddle point (Myers, 1971; Bhattacharya and

Prakash, 1994). Finally, the optimum levels of the variables were obtained by

superimposing the contours.


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Table 8. Orthogonal experimental design in coded and actual level of variables

Exp. No

Potassium dihydrogen phosphate

Potassium nitrate

Magnesium sulphate7-hydrate

Ferric citrate

coded level (x1)

actual level (g L-1) (X1)

coded level

(x2)

actual level

(g L-1) (X2)

coded level

(x3)

actual level (g L-1)

(X3)

coded level (x4)

actual level (g L-1) (X4)

1 1 0.172 1 0.861 1 0.43 1 0.043 2 -1 0.038 -1 0.189 1 0.43 1 0.043 3 1 0.172 -1 0.189 -1 0.09 1 0.043 4 -1 0.038 1 0.861 -1 0.09 1 0.043 5 1 0.172 -1 0.189 1 0.43 -1 0.012

6 -1 0.038 1 0.861 1 0.43 -1 0.012 7 1 0.172 1 0.861 -1 0.09 -1 0.012 8 -1 0.038 -1 0.189 -1 0.09 -1 0.012 9 1 0.172 -1 0.189 1 0.43 1 0.043 10 -1 0.038 1 0.861 1 0.43 1 0.043

11 1 0.172 1 0.861 -1 0.09 1 0.043 12 -1 0.038 -1 0.189 -1 0.09 1 0.043 13 1 0.172 1 0.861 1 0.43 -1 0.012 14 -1 0.038 -1 0.189 1 0.43 -1 0.012 15 1 0.172 -1 0.189 -1 0.09 -1 0.012

16 -1 0.038 1 0.861 -1 0.09 -1 0.012 17 0 0.105 0 0.525 0 0.26 0 0.028 18 1.414 0.2 0 0.525 0 0.26 0 0.028 19 -1.414 0.01 0 0.525 0 0.26 0 0.028 20 0 0.105 1.414 1.0 0 0.26 0 0.028

21 0 0.105 -1.414 0.05 0 0.26 0 0.028 22 0 0.105 0 0.525 1.414 0.5 0 0.028 23 0 0.105 0 0.525 -1.414 0.02 0 0.028 24 0 0.105 0 0.525 0 0.26 1.414 0.05 25 0 0.105 0 0.525 0 0.26 -1.414 0.005

26 0 0.105 0 0.525 0 0.26 0 0.028 27 0 0.105 0 0.525 0 0.26 0 0.028 28 0 0.105 0 0.525 0 0.26 0 0.028 29 0 0.105 0 0.525 0 0.26 0 0.028 30 0 0.105 0 0.525 0 0.26 0 0.028


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2.3.7. Isolation and purification of Botryococcus sp.

The algal samples were collected from the blooms in freshwater ponds of Mahabalipuram

(Latitude 12o37' in the North to Longitude 80

o14' in the East.) Tamil Nadu, India. The

samples were cultured in modified Chu 13 medium and subjected to purification by serial

dilution. The individual colonies were microscopically observed for their colonial and

morphological features. Pure culture was obtained from single colony and the culture was

established in both liquid and agar slants of modified Chu 13 medium, incubated at 25 ±

1°C under of 1.2 ± 0.2 klux irradiance with 16h: 8h light dark cycle. The purity of the

culture was ensured by repeated plating and by regular observation under microscope.

The Indian isolate was analyzed for its 18S rRNA sequence along with hydrocarbons,

carotenoids and fatty acids profiles.

2.3.7.1. Light Microscopy and Scanning Electron Microscopy

The algal cells were observed under light microscopy for their morphological features

and for other cellular details, the cells were further studied using scanning electron

microscopy (SEM) according to the method of Fowke et al. (1994). The samples were

fixed in 2% glutaraldehyde in 0.2 M phosphate buffer (pH 6.8) for 12 h, dried in alcohol

series up to 100%, sputter coated with gold and examined in a LEO Scanning Electron

Microscope 435 VP (Leo Electron Microscopy Ltd. Cambridge UK).

2.3.7.2. Biomass estimation

The known volume of cultures was harvested by centrifugation at 5000 rpm for 5 minutes

and the pellet was washed at least twice with distilled water and freeze dried. The dry

weight of algal biomass was determined gravimetrically and growth was expressed in

terms of dry weight gram per liter.

2.3.7.3. Chlorophyll and carotenoids estimation

A known volume of culture was centrifuged at 5000 rpm for 5 min and the pellet was

treated with known volume of methanol (1:1) and kept in water bath for 30 min at 60ºC.

Absorbance of the pooled extracts was measured at 450, 652 and 665 nm and total

chlorophyll and total carotenoids were estimated using Lichtenthaler equations

(Lichtenthaler, 1987).


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2.3.7.4. Hydrocarbon extraction and Analysis by GC-MS

Hydrocarbons were extracted by homogenizing the dry biomass with n-hexane for 30 min

intermittently. Supernatant recovered was evaporated to complete dryness under the

stream of nitrogen. Hydrocarbon content was measured gravimetrically and expressed as

percentage dry weight by the method of Sawayama et al. (1999). The hydrocarbon

samples were analyzed on SPB-5 column (30m × 0.32mm ID × 0.25 µm film thickness)

using GCMS equipped with FID and were identified by Dayananda et al. (2005)

comparing their fragmentation pattern with standards (Sigma chemicals USA) and with

NIST library.

2.3.7.5. Total Lipid estimation and Fatty acid Analysis

Total lipids were extracted with chloroform-methanol (2:1) and quantified

gravimetrically. The fatty acid methyl esters (FAME) were prepared by following the

procedure of Christie (1982). FAME were analyzed by GC-MS (PerkinElmer, Turbomass

Gold, Mass spectrometer) equipped with FID using SPB-1 (poly(dimethysiloxane))

capillary column (30m × 0.32mm ID × 0.25 µm film thickness) with a temperature

programming of 150°C(3’) to 280°C (5’) at a rate of 5°C/min. The FAMEs were

identified by comparing their fragmentation pattern with authentic standards (Sigma) and

with NIST library.

2.3.7.6. HPLC analysis of carotenoids

The acetone extract of the alga B. mahabali was analyzed by HPLC using a reversed

phase C18 column (4.5 cm ×150 mm) with an isocratic solvent system consisting of

acetonitrile/methanol/dichloromethane (7:1:2) at a flow rate of 1.0 ml/min and the

compounds were detected at 450 nm. Lutein and β-carotene were identified in the algal

extracts by comparing the retention time of the standards lutein and β-carotene procured

from sigma chemicals (Sigma chemicals, USA).

2.3.7.7. Extraction of genomic DNA and 18S rRNA amplification

Genomic DNA was extracted from the lyophilized algal biomass by liquid nitrogen using

the GenElute™ Plant Genomic DNA Mini prep kit (Sigma, St. Louis, USA). The RNA

contamination was removed by digesting the extract with 10 µg of RNase-A (Bangalore

Genei, Bangalore, India) for 30 min at 37 ºC. Quality and quantity of DNA preparations

were checked by standard spectrophotometry and the samples were diluted to a


Page 36

concentration of 25 ng µL-1

and used for PCR reactions. The 18S rRNA gene specific

primers for the Botryococcus sp. were designed from the reported sequences at NCBI

data base, 5’-CTGTGAAACTGCGAATGGC3’ as forward primer and 5’-

5’CTCCAATCCCTAGTCGGCATCG-3’ as reverse primer. PCR reaction was

performed in thermo-cycler using a PCR programme with 4 min initial denaturation at

94ºC and 35 cycles of 1 min denaturation at 94ºC, 1 min annealing at 52

ºC and 30 sec

extension at 72ºC with final extension at 72ºC for 10 min. The PCR products were

separated on agarose gels and stained with ethidium bromide and the gels were recorded

with a Hero Lab gel documentation system. The PCR was performed at least thrice to

check the reproducibility and then the PCR product was purified by the purification kit

supplied by Sigma and was again checked by gel electrophoresis. The PCR product was

cloned in T/A cloning vector (kit supplied by Invitrogen) and was sequenced after

confirmation by both PCR and restriction digestion. The sequence was submitted to

NCBI data base and was accorded with an accession number GU182893.1.

2.3.8. Preparation of template DNA for RAPD analysis

The genomic DNA from the two weeks grown cultures was extracted by using the

GenEluteTM

Plant Genomic DNA Mini prep kit supplied by Sigma (USA). RNA

contamination in all the samples were removed using RNase-A by following the

manufacturers protocol (100 µg mL-1

; Bangalore Genei, India) for 30 min at 37°C. The

quality and quantity of DNA were analyzed by standard spectrophotometry and the

samples were diluted to 25ng µL-1

.

2.3.8.1. DNA amplification for RAPD analysis

RAPD amplifications were performed using PCR mixture (25µL) having 1µL of genomic

DNA as template, 1X PCR buffer, 200 µM dNTPs, 1 unit (U) of Taq DNA polymerase

and 1 µM of each primer (Table 16, Results and discussion section) with an initial

denaturation at 93ºC for 4 min followed by 40 cycles of 1 min denaturation at 94°C, 1

min annealing at 36°C and 2 min extension at 72°C with a terminal extension of 72°C for

10 min using a thermal cycler (Eppendorf Thermal cycler, Model: 5332). The amplified

fragments were eletrophoretically separated in 2% agarose gels in TAE and stained in

ethidium bromide (0.001%) and documented in a gel documentation system (Hero-Lab


Page 37

GMBH, Germany). The size of the amplification products was estimated from 10kb DNA

ladder (Fermentas GMBH, Germany).

2.3.8.2. Resolving power (Rp) for RAPD analysis

Resolving power (Rp) for each primer was calculated following the method of Prevost

and Wilkinson (1999) for selecting primers that can distinguish a maximal number of

accessions. Resolving power (Rp) of a primer is = Ib where Ib (band informativeness)

takes the value of: Ib = 1 - [2 x |0.5 - p|], p being the proportion of the 7 genotypes (algal

strain analyzed) containing the bands.

2.3.8.3. Data analysis for RAPD analysis

The well-resolved RAPD fragments ranging from 100 to 3000 bp were scored as present

(1) or absent (0) for each primer analysis. Bands with the same migration distance were

considered homologous. The data was computed and analyzed with NTSYS pc (Rohlf

1998) version 2.02 using the simple matching coefficient (Sokal and Michener 1958).

Cluster analyses were obtained based on similarity matrices, using the unweighted pair

group method with arithmetic mean (UPGMA), and relationships between accessions

were visualized as dendrogram.


Page 38

2.4. Results and Discussion

2.4.1. Effect of culture conditions on Botryococcus sp.

2.4.1.1. Effect of different nitrogen sources

Data obtained for autotrophic media with different nitrogen sources on growth are given

in Figures 4 & 5. Both SAG 30.81 and LB 572 strains grew better in the presence of

potassium, sodium and calcium nitrates compared to urea and ammonium nitrate. In the

absence of nitrates the growth was poor and the cells were bleached or turned brown.

Among the nitrates tested, potassium nitrate appeared to be more effective compared to

calcium and sodium nitrates. From the Figures 4 & 5, it is evident that the optimum

yields 1.2 g/L for B. braunii LB 572 and 0.6 g/L for SAG 30.81) of biomass were

achieved for both the strains of B braunii which received potassium nitrate as a source of

nitrogen than the others nitrogen sources. Similar observations were also made by Sarada

et al. (2002) for the green algae Haematococcus pluvialis.

Figure 4. Biomass yields of B. braunii (SAG 30.81) grown with different nitrogen

sources

0

0.2

0.4

0.6

0.8

Calcium

Nitrate

Potassium

Nitrate

Sodium

Nitrate

Urea Ammonium

Nitrate

Bio

mass

(gL

-1)


Page 39

Figure 5. Biomass yields of B. braunii (LB 572) grown with different nitrogen sources

The fatty acid profiles of B. braunii grown in ammonium, potassium and calcium

nitrates are given in Table 9. Oleic acid is found to be the major fatty acid in both the

strains as well as in all the nitrogen sources studied. The next dominating fatty acid was

palmitic acid, which was relatively high in the strain SAG 30.81 compared to LB 572.

The two strains exhibited variations in their fatty acid profiles under the influence of

different nitrogen sources, especially in C18:0, C16:0, C18:2, C18:3, C24:0 C26:0 and

C28:0. Odd chain fatty acids were also present in lower quantities in both the strains

(Table 9).

However there was no significant effect of ammonium, calcium and potassium

nitrates on total lipid content of SAG 30.81. In LB 572 calcium and potassium nitrate

supplementation resulted in production of 28% of fat whereas in ammonium nitrate it was

15% (Figure 6).

0

0.4

0.8

1.2

1.6

Calcium

Nitrate

Potassium

Nitrate

Sodium

Nitrate

Urea Ammonium

Nitrate

Bio

mass

(gL

-1)


Page 40

Table 9. The fatty acid profile of B. braunii grown in different nitrogen sources

Fatty acids

B. braunii (SAG 30.81) B. braunii (LB-572)

Ammonium nitrate

Potassium nitrate

Calcium nitrate

Ammonium nitrate

Potassium nitrate

Calcium nitrate

12:0 0.65 ± 0.06 0.74 ±0.04 0.8 ± 0.46 0.82 ±0.05 0.92 ± 0.52 0.5 ± 0.28

14:0 2.26 ±1.24 7.6 ± 0.46 0.88 ± 0.24 1.17 ± 0.06 1.44 ±0.63 Trace

15:0 1.71 ±0.51 0.39± 0.06 1.68 ±1.0 0.36 ± 0.10 0.59 ±0.05 0.41±0.06

16:1 1.39 ±0.19 3 ±0.32 2.28 ±1.19 0.54 ±0.03 0.71 ±0.21 0.6 ± 0.02

16:0 21.25± .23 15.1 ±1.19 0.15±1.49 13.84±0.66 9.81 ±39 9.69 ±0.42

18:3 3.39 ±0.90 0.79 ±0.01 5.25 ±1.26 0.66 ±0.14 22.83±0.62 10.79 ±4.2

18:2 Trace 7.61 ±0.50 0.95 ±0.5 1.19±0.2 Trace Trace

18:1 48.46±1.66 54.1 ±1.02 56.27±0.96 60.05±6.96 54.34±6.15 69.1 ±6.42

18:0 8.75 ±0.66 1.2 ±0.4 1.96 ±0.52 12.49±1.48 3.54 ±2.7 1.62 ±0.37

19:0 Trace Trace Trace 0.26 ±0.12 Trace Trace

19:1 0.96 (±0.05) Trace Trace 1.02 ±0.22 2.84 ±1.7 Trace

20:0 Trace Trace Trace 2.5 ±1.04 Trace 0.22 ±0.01

20:1 Trace Trace Trace 2.01(±1.14 Trace Trace

22:1 0.79 ±0.01 0.5 ±0.03 0.15±0.02 1.06 ±0.06 Trace Trace

24:0 8.1 ±2.1 1.59 ±0.24 0.15 ±0.02 0.93 ±0.14 Trace 0.36 ±0.03

26:0 1.08 (±0.22) Trace 7.73 ±1.86 0.31 ±0.08 0.9 ±0.6 0.98 ±0.03

28:0 1.25 ±0.19 Trace 0.79 ±0.01 0.32 ±0.1 1.43 ±0.85 4.78 ±3.43


Page 41

Both the strains B. braunii produced methyl branched fatty acids viz; 16-methyl

heptadecanoic, 12-methyl tetradecanoic acid, 14-methyl hexadecanoicacid and 25-methyl

heptacosanoic acids in trace amounts which were identified by GCMS by comparing their

fragmentation pattern with NIST library spectra (Figure 7). Although, the significance of

these fatty acids is not known, Krishnan (2003) and Krishnan and Collin (2003) reported

that alkyl substituted fatty acids such as 16- methyl heptadecanoic acids were reported as

capable of inhibiting endothelial cell and leukocyte proliferation.

Figure 6. Total lipid yields of B. braunii grown in different nitrogen sources

0

10

20

30

40

Calcium nitrate Potassium nitrate Ammonium nitrate

Tota

l li

pid

% (

w/w

)

SAG 30.81 LB 572


Page 42

Figure 7. Mass spectra of 12-methyl hexadecanoic acid (A), 14-methyl tetradecanoic

acid (B) and 25-methyl heptacosanoic acid (C)

2.4.1.2. Effect of pH

B. braunii (SAG 30.81and LB 572) showed their growth (Figure 8) in a wide range of pH

6.0 to 8.5, although higher biomass, 0.77 and 1.9 g L-1

obtained respectively for SAG

30.81 and LB 572 cultures at pH 6.0. Irrespective of the initial pH, the final pH (after 4

weeks) was recorded in the range 8.0 to 8.8, and this indicates the depletion of CO2 or

HCO3 through photosynthesis. However, the optimum biomass yields were generally

reported to be at neutral pH with lowest in alkaline pH 9.0 (Banerjee et al., 2002). In the

present study also the organism showed its better growth from acidic to neutral pH than

the alkaline. Though, the algae have showed their tolerance to the tested pH range (pH 6

to 8.5). These results exhibit its adaptability for varied pH which is generally suitable for

any successful algal outdoor ventures.


Page 43

Figure 8. Biomass and hydrocarbon yield of B. braunii (LB 572 and SAG 30) cultures

grown under the influence of different pH

2.4.1.3. Effect of Salinity

B. braunii (LB 572) showed its tolerance to the tested concentrations of sodium chloride

from 17mM to 85 mM. Interestingly the biomass yields were found to be increased with

increasing concentration of sodium chloride and maximum biomass was achieved in 17

mM and 34 mM sodium chloride (Figure 9). However the biomass yields were higher in

the cultures supplemented with sodium chloride than their control counterpart. This

could be possibly due to the adaptation of the organism to the lower salinity (17mM to 85

mM). In contrast Hart et al. (1991) showed the reduced growth at higher salinities due to

decrease in photosynthetic rate. Decreased yields of biomass under saline conditions were

reported by Vazquez- Duhalt and Arredondo-Vega (1991) and Ben-Amotz et al. (1985).

Probably this decrease may be due to the non adaptability of the organism to higher

salinity (0.1–0.75 M).

0.0

0.4

0.8

1.2

1.6

2.0

2.4

6 6.5 7 7.5 8 8.5

Bio

mass

(gL

-1)

pH

LB 572 SAG 30.81


Page 44

Figure 9. Effect of salinity on biomass yields of B. braunii (LB 572)

2.4.1.4. Effect of different autotrophic media

Growth profiles of B .braunii LB 572 and SAG 30.81 in different autotrophic media are

shown respectively in Figures 10 & 11. The biomass yields of SAG 30.81 were

comparatively lower than LB 572 under all the tested conditions. The biomass yields

were comparatively high with cultures exposed to continuous light and agitation for SAG

30.81 while stationary culture with 16h: 8h light and dark cycle was favorable to LB 572.

In both the cultures, maximum biomass was obtained in BG 11 followed by BBM.

However modified BBMa (with ammonium carbonate) resulted in lower biomass yields

compared to BBM. All the combinations of modified Chu 13 media have shown

relatively lesser yields than the other tested media. However the organism showed

considerable growth to all the autotrophic media used in the study. So these results

suggest that the algae B. braunii can be of good choice for its possible outdoor or

commercial scale up studies for various applications from environmental to food.


Page 45

Figure 10. Biomass yields of B. braunii (LB 572) cultured in different culture media and

culture conditions

Figure 11. Biomass yields of B. braunii (SAG 30.81) cultured in different culture media

and culture conditions


Page 46

2.4.1.5. Influence of culture age

A time course study was carried out on growth of Botryococcus braunii strains SAG

30.81 and LB 572. The result showed a continuous but slow and steady increase in

growth of the organism during the eight week study (Figure 12).

Figure 12. Growth curve of B. braunii (LB 572 and SAG 30.81) cultures grown over an

eight weeks culture period

The growth of LB 572 was higher than SAG 30.81 since the biomass yields were found

to be 1.2 g/L and 0.56g /L respectively. The culture pH was in the range of 7.5 to 8.6 and

7.5 to 9.2 were recorded respectively for LB 572 and SAG 30.81. The results showed the

steady growth of the algae during the experimental period.

2.4.1.6. Influence of media constituents on biomass production using RSM

The experimental result on the effect of the four independent variables (concentrations of

potassium dihydrogen phosphate, potassium nitrate, magnesium sulphate and ferric

citrate) on biomass production by B. braunii is showed in Table 10. The analysis of

variances (ANOVA) (in coded level of variables) for a response function of biomass

yields is given in Table 11.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 1 2 3 4 5 6 7 8

Bio

mass

(g

L-1

)

Weeks

SAG 30.81 LB 572


Page 47

Table 10. Experimental results for the response function (biomass production

Exp. No Yield of biomass (mgL-1)

1 467 ± 16 2 471 ± 07 3 517 ± 05 4 441 ± 15 5 603 ± 02 6 520 ± 03 7 569 ± 07 8 587 ± 07 9 415 ± 10

10 363 ± 15 11 474 ± 02 12 548 ± 03 13 635 ± 01 14 637 ± 05 15 477 ± 10 16 462 ± 18 17 469 ± 13 18 474 ± 03 19 485 ± 05 20 410 ± 05 21 406 ± 01 22 496 ± 02 23 501 ± 08 24 339 ± 04 25 528 ± 08 26 439 ± 12 27 443 ± 07 28 443 ± 09 29 441 ± 05 30 442 ± 10


Page 48

Table 11. ANOVA table for the yield of biomass in coded level of variables

Variables: x1: Conc. of potassium dihydrogen phosphate, x2: conc. of potassium nitrate,

x3: conc. of magnesium sulphate, and x4:conc. of ferric citrate

Source of variation Coefficient of polynomial for biomass yields F-value

Constant 0.436 _

x1 0.006 0.85NS

x2 -0.016 6.78**

x3 0.001 0.06NS

x4 -0.053 75.38***

x12 0.030 11.46***

x22 -0.006 0.37NS

x32 0.040 19.77***

x42 0.007 0.66NS

x1x2 0.037 29.12***

x1x3 0.008 1.41NS

x1x4 -0.002 0.07NS

x2x3 0.003 0.15NS

x2x4 -0.006 0.65NS

x3x4 -0.035 26.61***

TLE _ 20.77***

TQE _ 8.07***

TIE _ 9.67***

R 0.96*** _

* Significant at p ≤ 0.10 TLE: Total linear effect

** Significant at p ≤ 0.05 TQE: Total quadratic effect

*** Significant at p ≤ 0.01 TIE: Total interaction effect NS Non-significant at p ≤ 0.1

The coefficients of the second order polynomial (in actual level of variables) are cited in

Table 12, for ease in using them to predict the response function (biomass yields). The

response surfaces (Figures 13 & 14) are presented to aid in visualizing the effect of the

four variables on biomass yields.


Page 49

Table 12. Regression equation for the response function of biomass yields in the actual level of variables

Variables: X1 = Conc. of potassium dihydrogen phosphate (g L-1), X2 = Conc. of potassium nitrate (g L-1),

X3 = Conc. of magnesium sulphate (g L-1), and X4 = Conc. of ferric citrate (g L-1). Response function: Y1 =

Yield of biomass (g L-1)

Parameter Regression equation

Yield of biomass Y1 = 0.728 – 2.363 X1 – 0.219 X2 – 0.418 X3 + 6.671 X1

2 +

1.638 X1X2 + 0.713 X1X3 + 1.377 X32 – 13.20 X3X4

Figure 13. Yield of biomass as a function of at potassium nitrate and potassium

dihydrogen phosphate when ferric citrate and magnesium sulphate were supplied at 0.028

gL-1

and 0.26 gL-1,

respectively


Page 50

Figure 14. Yield of biomass as a function of ferric citrate and magnesium when

potassium nitrate and potassium dihydrogen phosphate were supplied at 0.0525 gL-1

and

0.105 gL-1

, respectively

The yield of biomass varied between 0.339 and 0.637 gL-1

at different combinations of

variables (Table 10). A high multiple correlation coefficient (r = 0.96, p ≤ 0.01) indicated

the suitability of the second order polynomial to predict the yield of biomass in terms of

these four variables (Table 11). The total linear effect (p ≤ 0.01) dominated over total

interaction effects and total quadratic effects (p ≤ 0.01). Ferric citrate has the maximum

linear negative effect (p ≤ 0.01) on Y1 followed by linear negative effect of potassium

nitrate concentration (p ≤ 0.05) (Figures. 9 and 10). Positive quadratic effect of phosphate

and sulphate were significant (p ≤ 0.01). Among the various interactions, positive effect

of phosphate x nitrate concentration, and negative effect of sulphate x ferric-citrate

concentration have predominant effects on yield of biomass (p ≤ 0.01). These significant

interaction effects mean that the effect of phosphate on biomass yield is dependent on the

level of nitrate used. The effect of sulphate in a similar manner depends on citrate level.

The linear effect of phosphate and sulphate concentration on biomass yield was

negligible but their quadratic effects were significant (p ≤ 0.01). This means that a low

level of their concentrations has marginal effect but at a high level, they tend to increase


Page 51

the yield of biomass markedly. Therefore, high levels of potassium hydrogen phosphate

and magnesium sulphate concentration are expected to increase the yield of biomass in

the experimental ranges used.

It is concluded that high levels of phosphate and sulphate in the range of

experimental variables are desirable but their individual effects depend on the

concentrations of nitrate and citrate, respectively. The optimum medium conditions of

dihydrogen potassium phosphate, potassium nitrate, magnesium sulphate and ferric

citrate concentration were found to be 0.0195, 0.05, 0.02 and 0.0185 gL-1

respectively for

biomass yield of 0.65 gL-1

. Whereas in the control (modified Chu 13) medium yielded

only 0.45 gL-1

of biomass. Banerjee et al. (2002) reported a noticeable increase in the

amount of hydrocarbon production in the presence of excess phosphate. However there

are no reports on the interaction effects of phosphate and nitrate or sulphate and citrate.

2.4.1.6.1. Optimization by RSM

The process of optimization (maximization) of the yield of biomass was conducted using

the response surface methodology. The optimized conditions for growth of Botryococcus

braunii as depicted from its biomass indicated that when N: P of 1:0.5 favours both

growth & biomass yields. As the results indicates the possibility of using cultivation of

lipid rich algae for biomass and can be achieved in nitrate rich medium. As mentioned

previously, N: P ratio plays a significant role for biomass production. Botryococcus

braunii has received attention as a rich source of lipids rich biomass, therefore is a need

of the time to understand the influence of cultural conditions, which will facilitate its

mass cultivation.

2.4.2. Isolation and identification of Botryococcus sp.

Colony characteristics and morphological features of the Indian isolate have been

demonstrated to exhibit close similarity with the genus Botryococcus. The individual

cells of the colonies were in the range of 3 to 11 µm and the colonies were found to be

between 25 to 150 µm. However even bigger aggregates of colonies were also observed

in natural habitat as well as during their stationary growth phase (Figure 15). Cells are

spherical in shape and the variation in colonial size of the Indian isolate is depending

upon the daughter colonies which remain attached to one another. Generally cells are

green to yellowish green and under some stressed conditions they shown to have orange


Page 52

yellow as well. Similar observations were made by Chandra in Miocene lignites of

Kerala, India (Chandra 1964).

Figure 15. Scanning electron microscopic and light microscopic images of B. mahabali

Further the 18S rRNA sequence (GU182893.1) analysis was carried out to know the

taxonomical identity of the Indian isolate and the studies revealed its taxonomical

relationship to the order Trebouxiophyceae, subsequently the sequence analysis has

shown more than 90% similarities with the reported 18S rRNA sequences of genus

Botryococcus, in particular to the species Botryococcus braunii. The species of the genus

Botryococcus were mainly distinguished based on colony size and details of cell shape.

Therefore, based on its distinctive morphological and cellular features with that of the

reported Botryococcus species the Indian isolate was assigned as Botryococcus mahabali.

The production of hydrocarbons is one of the characteristic features of

Botryococcus species and hence hydrocarbons analysis was also carried out to understand

the nature of hydrocarbons produced by the Indian isolate. Hydrocarbons of

Botryococcus mahabali were identified by comparing their mass spectra with standard

hydrocarbons (Sigma) and also with the NIST library. The types of hydrocarbons

produced by the Indian isolate were identified as saturated hydrocarbons in the range of

C13 to C26 (Table 13). The Indian isolate has produced hexadecane (10.15%),

heptadecane (17.82 %) and pentacosane (18.74%) as its major hydrocarbons (Table 13).

Similar types of saturated hydrocarbons (C21 to C31) were also reported by Yang et al.

(2004) from the Chinese strain of B. braunii with heptacosane as its major constituent.

Volova et al. (2003) has also reported the presence of saturated straight-chain and


Page 53

branched-chain (C14–C28) and long-chain linear aliphatic (C20–C27) hydrocarbons.

.Dennies and Kolattukudy (1992) have demonstrated the alkane biosynthesis by

decarbonylation of aldehyde catalyzed reactions in the absence of oxygen in the

microsomal preparations of B. braunii. Audino et al. (2001) identified the macrocyclic

alkanes (ranging from C15 to C34) and their methylated analogues (ranging from C17 to

C26) in B. braunii rich sediment (torbanite). These hydrocarbons served as another

chemical marker for the Indian isolate B. mahabali to assign to the genus Botryococcus.

B. mahabali was evaluated for its lipid content and was found to be 14 % on dry weight

basis and its fatty acids analysis has revealed hexadecadienoic acid (16:2), oleic (18:1),

linoleic (18:2), and linolenic acids (18:3) as its major fatty acids (Table 14). Similarly

Fang et al. (2004) have also reported palmitic acid and oleic acids as major components

in the Botryococcus sp. The algal biomass was also analyzed for total carotenoids

contents (3.2 µg /g DW) which constituted predominantly lutein (24.75%) and β-carotene

(42.64%) as its chief components (Figure 16). These carotenoids are well known for their

Table 13. Hydrocarbons of Botryococcus mahabali

Hydrocarbons Relative %

C13 0.04

C14 3.64

C15 7.64

C16 10.15

C17 17.82

C18 6.2

C19 4.19

C20 8.21

C21 2.57

C22 5.8

C23 6.35

C24 4.81

C25

C26

18.74

4.33


Page 54

pharmaceutical, nutraceutical and cosmetic applications (Murthy et al., 2005; Vanitha et

al., 2007; Ranga Rao et al., 2006).

Figure 16. HPLC profile of carotenoids from Botryococcus mahabali

Table 14. Fatty acid profile of Botryococcus mahabali

Fatty acids % Composition

14:0 00.05

15:0 00.10

16:0 28.90

16:1 01.92

16:2 02.90

18:0 02.35

18:1 22.81

18:2 14.94

18:3 25.28

20:0 00.32


Page 55

2.4.3. Selection of primers and RAPD analysis

Three indigenous strains of Botryococcus sp. and other four strains of the same genus

obtained from different culture collection centers (two each of race-A and race-B) were

subjected for genetic analysis using RAPD markers. Several decamer primers were

screened for their ability to amplify DNA fragments. Based on the results of their ability

to produce good number of distinct bands, 35 RAPD primers were selected. DNA

samples from all the 7 strains of Botryococcus (Table 15) were amplified using the

decamers listed in Table 16, where all the primers produced polymorphic bands. The

majority of band positions varied between the strains. The polymorphisms were scored

visually based on the presence or absence of amplified fragments.

All the primers used in the study produced large numbers of polymorphic bands

(Table 16). The total number of bands (TNB), number of polymorphic bands (NPB),

percentage of polymorphic bands (%PB), Resolving power (Rp), amplified fragment size

(AFS) obtained for each primer are detailed in Table 16. The total amplified products of

35 RAPD primers was 407 (average of 11.62 bands per primer) ranging from 100 to 3000

bp, of which 380 were polymorphic (93.3%). The number of bands for each RAPD

primer varied from 5 (OPN 14) to 16 (OPA-09). The resolving power of the 35 RAPD

primers ranged from 3.43 for primer OPN-14 to 8.86 for primer OPD-07 and the samples

of RAPD analysis are visualized in Figure 17.

Table 15. Botryococcus strains used for the study

Algal strains

Botryococcus brauni[Strain 1]

Botryococcus brauni[Strain 2]

Botryococcus brauni[LB-572]

Botryococcus brauni[SAG 30.81]

Botryococcus sp. [DB-8]

Botryococcus sp.[MCRC]

Botryococcus mahabali[CFTRI]


Page 56

Table 16. List of RAPD primers selected from Operon Technologies

Primer Primer sequence (5’_ 3’) TNB NPB %PB RP AFS

OPA 03 AGTCAGCCAC 15 15 100 7.71 250-3000 OPA 04 AATCGGGCTG 14 11 78.57 5.14 200-3000 OPA 09 GGGTAACGCC 16 14 87.50 7.14 250-2200 OPA 11 CAATCGCCGT 13 12 92.31 7.14 200-2500 OPC 06 GAACGGACTC 12 11 91.66 6.85 200-1500 OPC 08 TGGACCGGTG 11 11 100 6.28 200-1500 OPC 13 AAGCCTCGTC 11 11 100 5.43 350-1500 OPD 07 TTGGCACGGG 15 15 100 8.86 250-2000 OPD 08 GTGTGCCCCA 12 11 91.66 7.71 250-1800 OPD 11 AGCGCCATTG 13 9 69.23 5.14 250-3000 OPD 16 AGGGCGTAAG 11 10 90.91 6.29 400-2500 OPB 07 GGTGACGCGA 12 12 100 7.71 100-1500 OPC 03 GGGGGTCTTT 14 9 64.28 6.28 300-3000 OPF 12 ACGGTACCAG 14 11 78.57 6.00 300-3000 OPM 20 AGGTCTTGGG 11 11 100 6.57 400-2000 OPA 20 GTTGCGATCC 11 11 100 7.14 400-2500 OPJ 10 AAGCCCGAGG 13 13 100 6.86 200-2500 OPN 09 TGCCGGCTTG 12 11 91.67 7.14 200- 2000 OPN 10 ACAACTGGGG 10 9 90 5.71 350-1500 OPN 14 TCGTGCGGGT 5 5 100 3.43 700-3500 OPC 01 TTCGAGCCAG 11 11 100 7.43 200-2500 OPC 05 GATGACCGCC 10 10 100 5.71 350-1500 OPJ 18 TGGTCGCAGA 9 9 100 5.14 400-2000 OPJ 20 AAGCGGCCTC 10 10 100 6.00 250-1500 OPJ 09 TGAGCCTCAC 9 9 100 6.00 400-2000 OPJ 01 CCCGGCATAA 11 9 81.81 6.57 300-1300 OPJ 11 GTCCCGTGGT 13 13 100 8.29 250-2000 OPJ 19 GGACACCACT 11 10 90.91 5.71 200-1500 OPJ 13 CCACACTACC 10 10 100 6.00 200-2500 OPC 02 GTGAGGCGTC 11 11 100 6.57 200-2500 OPN 06 GAGACGCACA 12 12 100 4.29 400-2500 OPC 9 CTCACCGTCC 9 8 88.88 3.71 200-1200 OPJ 11 ACTCCTGCGA 14 14 100 8.29 400- 2500 OPN 4 GAGACGCACA 10 10 100 4.85 400-1500 OPC 7 GTCCCGACGA 12 12 100 8.85 300-3000

Total 407 380 93.3 223.94

Total number of bands (TNB), number of polymorphic bands (NPB), percentage of polymorphic bands (%PB), resolving power (Rp) and amplified fragment size (AFS) obtained per RAPD primer


Page 57

Figure. 17. RAPD profile of DNA from 7 strains of Botryococcus (Primers OPC-07 (A),

OPC-09 (B) and OPN-04(C). Lane marker represents 10 kbp DNA ladder


Page 58

2.4.3. 1. Molecular analysis and fingerprinting of Botryococcus strains

The genetic similarity coefficients for 7 strains of Botryococcus species were obtained

with RAPD markers ranged from 0.3312 to 0.7388between the strains evaluated. The

unweighted pair group method with arithmetic mean (UPGMA) analysis made it possible

to discriminate all the genotypes of Botryococcus sp. used in this study. The dendrogram

obtained based on RAPD data showed a clear distinction into two major clusters (Figure

18). The dendrogram (Figure 18) obtained using per cent disagreement coefficient (Table

17) showed the presence of 2 main clusters (Cluster 1 and 2, having 2 and 5 strains in

each, respectively). The cluster 1 had two strains (Strain 1 and Strain 2) which belong to

B race, while the A race strains LB -572 and SAG 30.81 formed a sub -cluster A1 in

cluster 2 and the other 3 indigenous strains (CFTRI, MCRC and DB-8) formed an

another sub cluster A2 of cluster 2. The similarity coefficient matrix (Table 17) and the

dendrogram data have shown clear distinction between all the strains of Botryococcus

species studied and have also revealed a genetic relationship between the race A and race

B strains. All the indigenous strains have shown their genetic relationship with A race

strains and among the indigenous strains, Botryococcus sp. (DB-8) have shown its

genetic diversity with that of the other two indigenous strains (MCRC and CFTRI).

Morphological details of 7 strains of Botryococcus species (Figure 19) shows that

the features of A race strains, B race strains and indigenous strains were found to

substantiate the observations of RAPD data as well. Gomez and Gonzalez (2004) have

also used RAPD technique to see the genetic variations among the several strains of

microalgae Dunaliella salina.


Page 59

Figure 18. Dendrogram displaying the genetic distances among Botryococcus strains

obtained from cluster analysis of RAPD data

Table 17. Genetic similarity coefficient among the 7 strains of Botryococcus species based on

RAPD analysis

Strains Strain 1 Strain 2 SAG-0.81 LB-572 CFTRI MCRC DB-8

Strain 1 1

Strain 2 0.7388 1

SAG-30.81 0.3846 0.3806 1

LB-572 0.4359 0.3918 0.5254 1 CFTRI 0.3896 0.3766 0.4333 0.4481 1

MCRC 0.3980 0.3940 0.4474 0.4430 0.4947 1

DB-8 0.3485 0.3312 0.3595 0.3628 0.4256 0.4765 1


Page 60

Figure 19. Scanning electron microscopic images of different strains of Botryococcus sp.

used for RAPD analysis


Page 61

Genetic diversity studies will also gives the details of exotic genotypes. RAPD has been

successfully used to identify the genetic variation in both micro- and macroalgae (Neilan,

1995; Nishihara et al., 1997; Bolch et al., 1999a, 1999b; Gomez and Gonzalez, 2004;

Martinez et al., 2006; Zhao et al., 2007; Touzet et al., 2007; Zhao et al., 2008; Small et

al., 2009; Tilman et al., 2009; Olmos et al., 2009). The genetic diversity among the

different strains of Botryococcus is a clear demonstration of the genome participation in

determining the attributes related to production of different nature of hydrocarbons and

morphological features. The results of the study are very important since the existence of

genetically characterized strains will reduce incorrect assumptions about the

biotechnologically important traits of different strains, which could be due to phenotypic

flexibility. RAPD markers having high resolution power appear to offer many advantages

in establishing genetic distances among the microalgae. They were found to be effective

for assessing genetic variation in different species and strains of Botryococcus belonging

to various geographic locations and climatic zones as well. Thus diversity analysis by

RAPD technique efficiently discriminate phenotypic and environmentally acquired

characteristics. RAPD primes have been applied for establishing diversity of algal forms.

2.4.4. Microalgal lipid production

All the three indigenous strains Botryococcus sp. (DB-8), Botryococcus sp.(MCRC) and

the new CFTRI isolate Botryococcus mahabali (indigenous strains were shown in Figure

20) were evaluated for their total lipid and biomass productivities (Figure 21 & 22) after

their growth in modified Chu 13 medium for four weeks. Similarly other two

commercially important green microalgal species Dunaliella bardawil and

Haematococcus pluvialis (Figure 20) were grown for four weeks and evaluated for their

lipid contents and biomass yields (Figures 23 & 24). The gas chromatographams of their

respective fatty acid methyl esters were shown in Figures 25-29. Representative mass

spectra for few major microalgal fatty acid methyl esters are shown in Figure 30.


Page 62

Figure 20. Light microscopic images of microalgae used for the study, A: H. pluvialis; B

D. bardawil; C: Botryococcus sp. [MCRC]; D: Botryococcus mahabali [CFTRI]; E:

Botryococcus sp. [DB-8]


Page 63

Figure 21. Biomass yields of indigenous Botryococcus strains cultivated for four weeks

Figure 22. Total lipids yields of indigenous Botryococcus species

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

CFTRI DB-8 MCRC

Botryococcus strains

Bio

mass

gL

-1

0

2

4

6

8

10

12

14

16

18

CFTRI DB-8 MCRC

Botryococcus strains

Tota

l li

pid

s %

(w

/w)


Page 64

Figure 23. Biomass yields of Haematococcus pluvialis and Dunaliella bardawil

Figure 24. Total lipids yields of Dunaliella bardawil and Haematococcus pluvialis

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

H. pluvialis D. bardawil

Bio

mass

gL

-1

0.0

5.0

10.0

15.0

20.0

25.0

30.0

D. bardawil H. pluvialis

Tota

l li

pid

s %

(w

/w)


Page 65

Figure 25. Gas chromatogram of fatty acid methyl ester profiles of Botryococcus

mahabali

Figure 26. Gas chromatogram of fatty acid methyl ester profiles of Botryococcus sp.

[DB-8]

3.50 8.50 13.50 18.50 23.50 28.50 33.50

Time 0

100

%

12.39

15.48

15.32

15.06

22.51

15.99

4.50 6.50 8.50 10.50 12.50 14.50 16.50 18.50 20.50 22.50 24.50 26.50 28.50 30.50 32.50 Time0

100

%

d

15.7012.50

11.54

8.56

8.74

15.57

15.23

14.73

22.72

16.21

23.40


Page 66

Figure 27. Gas chromatogram of fatty acid methyl ester profiles of Botryococcus sp.

[MCRC]

Figure 28. Gas chromatogram of fatty acid methyl ester profiles of D. bardawil

6.01 8.01 10.01 12.01 14.01 16.01 18.01 20.01 22.01

Time 0

100

%

12.39

5.488.70

15.48

15.31 22.50

15.99

17.03 19.49

4.39 6.39 8.39 10.39 12.39 14.39 16.39 18.39 20.39 22.39 24.39

Time0

100

%

12.42

11.48

15.42

15.08

14.60

13.51 17.0616.03 22.55


Page 67

Figure 29. Gas chromatogram of fatty acid methyl ester profiles of H. pluvialis

All the three indigenous Botryococcus strains showed presence of hexadecanoic (16:0),

oleic (18:1), linoleic (18:2), and linolenic acids (18:3) as their major fatty acids (Table

18-20). Analyses of fatty acids profiles of Dunaliella and Haematococcus have revealed

them to produce hexadecanoic acid (16:0), oleic (18:1), linoleic (18:2), and linolenic

acids (18:3) as their major fatty acids (Table 21 & 22). Similarly Fang et al., (2004) have

also reported palmitic acid and oleic acids as major components in Botryococcus sp.

Botryococcus braunii also produces large amounts of fatty acids, comprising mainly the

palmitic (16:0), oleic (18:1), linoleic (18:2), and linolenic acids (18:3). The yield of total

lipids ranges from 10 to 75 % (w/w) and it depends on the physiological conditions and

also the race (different chemical races) they belongs (Audino et al., 2001; Chisti, 2007).

Vazquez-Duhalt and Greppin (1987) have reported that oil composition the species of the

genus Botryococcus resembles that of the olive oil. It is evident from the results that the

indigenous Botryococcus do produce oil which comprise a reasonably good composition

which can be used in place of vegetable oil since it does contain lutein and beta-carotene

as additional nutritional components. Hence its biomass could be of use in various feed

and food formulations. In addition the whole biomass Botryococcus could be used as an

aquaculture feed.

4.84 6.84 8.84 10.84 12.84 14.84 16.84 18.84 20.84 22.84 24.84 Time 0

100

%

12.42

6.37

15.53

15.37

16.05


Page 68

Figure 30. Mass spectra of microalgal fatty acid methyl esters. A: Hexadecanoic acid, B:

Linolenic acid, C: Linoleic acid, D: Oleic acid and D: Stearic acid


Page 69

Dunaliella and Haematococcus are known for their ability to accumulate very high levels

of beta–carotene and astaxanthin and are presently used for various applications from

food to medicine. In view of this Dunaliella bardawil was evaluated for its fatty acid

composition and has exhibited a very high level of unsaturated fatty acids than the

saturated ones and similarly H. pluvialis also exhibited similar profile which is rich in

unsaturated fatty acids oleic (18:1), linoleic (18:2), and linolenic acids (18:3). Similar

results were reported for both Dunaliella and Haematococcus species by various

researchers (Borowitzka and Borowitzka, 1988; Lamers et al., 2010; Zhekisheva et al.,

2002; Danmiani et al., 2010). All the three indigenous species of Botryococcus, D.

bardawil and H. pluvialis produced appreciable amounts of lipids with relatively good

quality fatty acid profiles which could be of use from food to fuel in the nearing future.

Table 18. Fatty acid profile of Botryococcus mahabali


14:0 0.54 ± 0.21

15:0 0.38 ± 0.29

16:0 31.91 ± 4.38

16:1 1.97 ± 1.45

16:2 2.15 ± 0.88

18:0 2.45 ± 1.26

18:1 38.91 ± 14.38

18:2 10.15 ± 4.31

18:3 11.51 ± 4.74

Values represents Mean ± SD of three replicates


Page 70

Table 19. Fatty acid profile of Botryococcus sp. [DB-8]


C 14:0 0.36 ± 0.01

C 16:3 0.60 ± 0.55

C 16:2 3.27 ± 2.34

C 16:1 3.01 ± 1.47

C 16:0 43.96 ± 2.91

C 17:0 0.15 ± 0.11

C 18:2 13.41 ± 8.91

C 18:1 27.37 ± 3.1

C 18:0 7.8 ± 5.57


Table 20. Fatty acid profile of Botryococcus sp. [MCRC]


C 12:0 0.26 ± 0.15

C 14:0 0.51 ± 0.31

C 16:1 1.85 ± 0.29

C 16:0 64.51 ± 12.76

C 18:2 8.44 ± 5.15

C 18:1 21 ± 06

C 18:0 3.32 ± 1.68



Page 71

Table 21. Fatty acid profile of Dunalleila bardawil

Fatty acids % composition

C 14:0 0.43 ± 0.20

C 15:0 0.24 ±0.02

C 16:3 4.11±2.7

C 16:1 1.24±0.14

C 16:0 39.11 ± 5.8

C 18:3 35.24 ± 7.7

C 18:2 16.04 ± 4.8

C 18:1 2.55 ± 0.83

C 18:0 0.95 ±0.44


Table 22. Fatty acid profile of Haematococcus pluvialis

Fatty acids % composition

C 14:1 0.82 ± 0.16

C 16:3 0.79 ± 0.35

C 16:1 0.10 ± 0.03

C 16:0 46.66 ± 10.23

C 17:0 0.15 ± 05

C 18:3 5.27 ± 1.13

C 18:2 19.54 ± 6.12

C 18:1 20.44 ± 4.58

C18:0 4.87 ± 1.86

C19:0 Trace

C20:0 0.93 ± 0.35


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