Statistical optimization of cultural medium composition of thermoalkalophilic lipase produced by a chemically induced mutant strain of Bacillus atrophaeus FSHM2

Article abstract of DOI:10.1007/s13205-019-1789-2

Extremophilic microbial derived lipases have been widely applied in different biotechnological processes due to their resistance to harsh conditions such as high salt concentration, elevated temperature, and extreme acidic or alkaline pH. The present stud

Full text of DOI:10.1007/s13205-019-1789-2

3
Biotech
(2019) 9:268
https://doi.org/10.1007/s13205-019-1789-2
ORIGINAL ARTICLE
Statistical optimization of cultural medium composition
of thermoalkalophilic lipase produced by a chemically induced mutant
strain of Bacillus atrophaeus FSHM2
Atefeh Ameri · Mojtaba Shakibaie1,2 · Zahra Sahami · Mehdi Khoobi · Hamid Forootanfar
1
3
4
2,5
Received: 29 September 2018 / Accepted: 3 June 2019
©
King Abdulaziz City for Science and Technology 2019
Abstract
Extremophilic microbial derived lipases have been widely applied in diferent biotechnological processes due to their resist-
ance to harsh conditions such as high salt concentration, elevated temperature, and extreme acidic or alkaline pH. The present
study was designed to overproduce the halophilic, thermoalkalophilic lipase oꢀ Bacillus atrophaeus FSHM2 through chemi-
cally induced random mutagenesis and optimization oꢀ cultural medium components assisted by statistical experimental
design. At ꢁrst, improvement oꢀ lipase production ability oꢀ B. atrophaeus FSHM2 was perꢀormed through exposure oꢀ the
wild bacterial strain to ethidium bromide ꢀor 5–90 min to obtain a suitable mutant oꢀ lipase producer (designated as EB-5,
4
301.1 U/l). Aꢀterwards, Plackett–Burman experimental design augmented to D-optimal design was employed to optimize
medium components (olive oil, maltose, glucose, sucrose, tryptone, urea, (NH ) SO , NaCl, CaCl , and ZnSO ) ꢀor lipase
4
2
4
2
4
production by the EB-5 mutant. A maximum lipase production oꢀ 14,824.3 U/l was predicted in the optimum medium con-
taining 5% oꢀ olive oil, 0.5% oꢀ glucose, 0.5% oꢀ sucrose, 2% oꢀ maltose, 2.5 g/l oꢀ yeast extract, 1.75 g/l oꢀ urea, 1.75 g/l
oꢀ (NH ) SO , 2.5 g/l oꢀ tryptone, 2 g/l oꢀ NaCl, 1 g/l oꢀ CaCl , and 1 g/l oꢀ ZnSO . A mean value oꢀ 14,773± 576.9 U/l oꢀ
4
2
4
2
4
lipase was acquired ꢀrom real experiments.
Keywords Lipase · Bacillus atrophaeus · Ethidium bromide · Mutagenesis · Medium optimization
Introduction
Microbial derived enzymes have been widely applied as
catalysts in biotechnological procedures due to their high
activity under mild conditions, suitable stability, and high
substrate speciꢁcity (Barbosa et al. 2015; Riyadi et al. 2017).
Lipases (triacylglycerol acylhydrolases, EC 3.1.1.3) are
among the most useꢀul and most studied enzymes in the
biotechnological processes. Microbial lipases catalyze the
hydrolysis oꢀ triacylglycerols to diacylglycerols, monoacyl-
glycerols, ꢀree ꢀatty acids (FFA), and glycerol (Das et al.
*
*
Mojtaba Shakibaie
shakiba@kmu.ac.ir
Hamid Forootanꢀar
h_ꢀorootanꢀar@kmu.ac.ir
1
2
Pharmaceutics Research Center, Institute
oꢀ Neuropharmacology, Kerman University oꢀ Medical
Sciences, Kerman, Iran
2
016; Khoobi et al. 2014, 2016; Yao et al. 2013; Jaeger and
Department oꢀ Pharmaceutical Biotechnology, Faculty
oꢀ Pharmacy, Kerman University oꢀ Medical Sciences,
Kerman, Iran
Eggert 2002). Lipases possess a high level oꢀ enantio- and
regioselectivity and substrate speciꢁcity which make them
suitable candidates to catalyze the processes oꢀ esteriꢁca-
tion, interesteriꢁcation, transesteriꢁcation, acidolysis, and
aminolysis (Adlercreutz 2013; Aravindan et al. 2007; Zhang
et al. 2014). From the mechanistic point oꢀ view, most oꢀ
lipases have a ‘lid’ domain, a polypeptide sequence nearby
the active site, able to change lipase conꢀormation ꢀrom a
‘close’ to an ‘open’ (more active) ꢀorm (Arana-Peña et al.
3
4
The Student Research Committee, Faculty oꢀ Pharmacy,
Kerman University oꢀ Medical Sciences, Kerman, Iran
Department oꢀ Pharmaceutical Biomaterials, Faculty
oꢀ Pharmacy, Tehran University oꢀ Medical Sciences, Tehran,
Iran
5
Herbal and Traditional Medicines Research Center, Kerman
University oꢀ Medical Sciences, Kerman, Iran
Vol.:(0
1
123456789)
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2
018; Manoel et al. 2015; Rios et al. 2018). It has been
shown that immobilization oꢀ lipases on hydrophobic sur-
aces (designated as interꢀacial activation) lets the ‘open’
orm oꢀ lipases to be more stable (Cantone et al. 2013; Hane-
eld et al. 2013; Sheldon and Pelt 2013).
This valuable biocatalyst has been widely employed in
alkaline lipase production (Bisht et al. 2012). The improved
strain was capable to secrete a high titer oꢀ alkaline lipase
(1609 U/l) into the medium (Bisht et al. 2012). Darvishi
et al. (2011) also applied the EMS to improve the productiv-
ity oꢀ lipase ꢀrom Yarrowia lipolytica.
ꢀ
ꢀ
ꢀ
Investigation on the ꢀactors inꢂuencing the production oꢀ
biomolecules is essential in many bioprocess development
procedures (Forootanꢀar et al. 2015; Moshaꢁ et al. 2011).
Generally, a higher productivity could be achieved by cul-
ture medium optimization (Haider Ali et al. 2015; Hasan-
Beikdashti et al. 2012; Riyadi et al. 2017). The statistical
optimization oꢀ processes has advantages compared to the
traditional method oꢀ varying one ꢀactor at a time (Colla
et al. 2016; Faisal et al. 2014) such as the lower number oꢀ
experiments and the possibility oꢀ evaluating the interaction
efects between ꢀactors. Statistical experimental techniques
such as two-level ꢀactorial experiments, Plackett–Burman
design (PBD), and response surꢀace methodology (RSM)
are efective tools applied ꢀor optimization oꢀ lipase pro-
duction by diferent microorganisms such as P. aeruginosa,
Candida rugosa, C. antarctica, B. cepacia, P. alcaligenes,
Rhizopus sp. and Bacillus pumillus (Liu and Zhang 2011;
Lo et al. 2012; Riyadi et al. 2017; Vasiee et al. 2016; Verma
et al. 2012).
ꢀ
ood industries (improving the quality oꢀ dairy products and
meat processing), detergent, pharmaceuticals, and cosmetic
industries, as well as in the synthesis oꢀ ꢁne chemicals, agro-
chemicals, biodiesel, and new polymeric materials (Darvishi
et al. 2011; Khoobi et al. 2014; Li et al. 2018). In pharma-
ceutical industries, lipases have been also used ꢀor kinetic
resolution oꢀ drug intermediates. Lipases have been applied
as co-catalysts in the preparation oꢀ enantiomer compounds
ꢀ
rom racemates (Pinheiro et al. 2018; Zhang et al. 2019;
Galvão et al. 2018).
Particularly, the speciꢁc lipases produce by extremophiles
have been used in harsh industrial conditions, because most
oꢀ them remain active at alkaline pH and in elevated tem-
perature as well as in the presence oꢀ high salt and organic
solvent concentrations (Samaei-Nouroozi et al. 2015; Yao
et al. 2013). There are many reports on bacterial derived
lipases categorized as extremophilic lipases. For example,
the secreted solvent-tolerant lipase oꢀ Burkholderia ambi-
faria YCJ01 was applied ꢀor resolution oꢀ (S)-mandelic acid
in the presence oꢀ diisopropyl ether (Yao et al. 2013). Yele
and Desai (2015) isolated a thermoalkalophilic lipase ꢀrom
Staphylococcus warneri which maximally worked at pH oꢀ
The present study was aimed to develop a B. atrophaeus
mutant strain with high ability ꢀor thermoalkalophilic lipase
production using chemically induced mutagenesis. Further-
more, the main ꢀactors afecting lipase biosynthesis by the
selected mutant were then screened and the related model
was evaluated. On the other hand, this research tried to
increase lipase production by a simple mutation method
combined with medium optimization using a statistical
experimental design (Scheme 1).
8
and temperature oꢀ 55 °C. Maximum esteriꢁcation oꢀ ethyl
butyrate assisted by lipase oꢀ Burkholderia multivorans V2
occurred at n-hexane (Dandavate et al. 2009).
In the last ꢀew decades, the ever-increasing usage oꢀ
lipases required the expansion in both qualitative improve-
ment and quantitative enhancement (Bisht et al. 2012;
Toscano et al. 2011). Quantitative enhancement could be
achieved by strain improvement and medium optimization
(
Toscano et al. 2011). Various methods have been used to
Materials and methods
improve the lipase producing strains including site-directed
mutagenesis and random mutagenesis (Bisht et al. 2012;
Chang and Shaw 2009; Iꢀtikhar et al. 2010). The classical
random mutagenesis approach mainly involves exposing the
desired microbe to the physical mutagens (such as X-rays,
gamma rays, and UV irradiation), or chemical mutagens
Chemicals and bacterial strain
Brain heart inꢀusion broth (BHIB), nutrient broth, tryp-
tone, yeast extract, sucrose, glucose, rhodamine B, and agar
were supplied by Merck Chemicals (Darmstadt, Germany).
ρ-Nitrophenylpalmitate (ρNPP), ρ-nitrophenol (ρNP), and
ethidium bromide (EtBr) were provided by Sigma-Aldrich
(St. Louis, MO, USA). All applied chemicals were oꢀ ana-
lytical grade. The lipase-producing bacterial strain (B.
atrophaeus FSHM2, NCBI accession number oꢀ KF682367)
employed in the present study was isolated in a previous
study ꢀrom a hypersaline location (30°36′18″N, 59°04′04″E)
in Kerman, Iran. The secreted lipase oꢀ this strain maximally
worked at 70 °C, pH 9, and in the presence oꢀ 4 M NaCl
(Ameri et al. 2017).
[
like N-methyl-N′-nitro-N-nitrosoguanidine (NTG), ethyl
methanesulꢀonate (EMS), and ethidium bromide (EtBr)].
Devi et al. (2015) used chemical mutagens oꢀ EMS, EtBr,
sodium azide, and NTG to enhance the production and lipo-
lytic potential oꢀ Pseudomonas sp. This mutant represented
a total increase in activity (4960 U/l) over its wild strain
(
3100 U/l) ꢀor the production oꢀ extracellular lipase (Devi
et al. 2015). In another study, the strain improvement oꢀ
P. aeruginosa MTCC 10055 was perꢀormed by chemical
mutagenesis using the mutagen 4-nitroquinoline 1-oxide ꢀor
1
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Scheme 1 Steps to get the maximum level oꢀ thermoalkalo-
philic lipase production via EtBr-induced mutagenesis oꢀ Bacillus
atrophaeus FSHM2 ꢀollowed by screening oꢀ overproducing mutant
(Et-5) and optimization oꢀ cultural medium compositions using statis-
tical experimental design
EtBr mutagenesis
v/v) to determine their ability ꢀor alkaline lipase production in
shake ꢂasks. Fermentation experiments were perꢀormed at 60 °C
and 120 rpm in 500 ml ꢂasks containing 100 ml oꢀ medium
inoculated by 1% (v/v) oꢀ the seed culture. At the end oꢀ process,
the culture media was centriꢀuged (10,000×g, 15 min) and the
supernatant was used ꢀor determination oꢀ lipase activity.
The chemical mutagenesis oꢀ B. atrophaeus FSHM2 cells
was carried out by exposing to EtBr by a modiꢁed method
oꢀ Raju and Divakar (2013). The overnight culture oꢀ the
bacterial strain in BHIB was harvested by centriꢀugation at
1
0,000×g ꢀor 10 min, washed twice with phosphate bufer
(
0.1 M, pH 7.4) and suspended in the same bufer. Five ml
Enzyme assay
8
oꢀ the cell suspension containing 1×10 cells/ml was mixed
with 10 ml oꢀ EtBr solution (5 mg/ml) and incubated at
Extracellular lipase activity was measured spectrophoto-
metrically using ρ-NPP as substrate by the modiꢁed method
oꢀ Hasan-Beikdashti et al. (2012). First, the related standard
curve oꢀ ρ-NP (the product oꢀ lipase hydrolysis on ρ-NPP
substrate) was drawn by plotting each absorbance oꢀ ρ-NP
(at 410 nm) against its related concentration (perꢀormed in
triplicates). The reaction mixture consisted oꢀ 0.8 ml oꢀ 0.1 M
carbonate bufer (pH 9) supplemented by Triton X-100 (0.4%),
0.1 ml oꢀ the attained culture broth sample, and the ꢀreshly
prepared p-NPP solution (0.01 M, 0.1 ml) was then prepared
and incubated at 60 °C ꢀor 30 min under mild shaking. An
amount oꢀ 0.25 ml Na CO (0.1 M) was consequently added
3
7 °C. One ml sample ꢀrom this solution was taken at inter-
vals oꢀ 5–90 min and centriꢀuged immediately at 10,000 rpm
or 10 min. The obtained cells were then re-suspended in
ml phosphate bufer (0.1 M, pH 7.4). Preliminary screen-
ꢀ
2
ing oꢀ lipase-overproducing mutants was carried out on BHI
agar medium containing rhodamine B (0.001%, w/v), olive
oil (1%, v/v), and NaCl (15% w/v). The EtBr-treated cell
suspension was diluted and spread on a series oꢀ pre-steri-
lized plates oꢀ the above-mentioned medium and incubated
ꢀ
or 24–48 h. The bacterial colonies exhibiting an orange-
colored ꢂuorescent halos (under UV light, 350 nm) around
their colonies were selected ꢀor ꢀurther studies.
2
3
to the reaction mixture and the amount oꢀ released ρ-NP was
determined by recording the absorbance at 410 nm assisted by
a spectrophotometer (UV-1800, Shimadzu Co., Tokyo, Japan)
using the line equation obtained ꢀrom the above-mentioned
standard curve. One unit oꢀ the lipolytic activity was then spec-
iꢁed as the amount oꢀ the enzyme that catalyzed the ꢀormation
oꢀ 1 μmol oꢀ ρ-NP per min ꢀrom ρ-NPP substrate.
Screening of a potent lipase‑overproducing mutant
strain
The selected mutants oꢀ the previous step were grown in the basal
medium composed oꢀ nutrient broth ꢀortiꢁed by olive oil (1%,
1
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Table 1 Applied levels oꢀ independent variables in the experimental
where Y is the predicted response (lipase production), x
i
design ꢀor optimization oꢀ lipase production by EB-5 mutant
(
i=1–11) are the variables oꢀ the experiment, b is the con-
0
stant oꢀ the model, b (i=1–11) are the linear coeꢃcients,
Variable
Component
Unit
Low level (−1)
High
level
i
b (i≠j) are the second-order coeꢃcients, b (i=1–10) are
ij
ii
(
+1)
the second-order interaction coeꢃcients, and e is the experi-
mental error.
X1
X2
X3
X4
X5
X6
X7
X8
X9
Olive oil
Glucose
Sucrose
Maltose
Yeast extract
Urea
%
%
%
%
g/l
g/l
g/l
g/l
g/l
g/l
g/l
1
5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
1
2.5
2.5
2.5
3
3
3
3
5
5
5
Data analysis
As said above, the analysis oꢀ the obtained results was per-
ꢀormed using the statistical soꢀtware oꢀ Design Expert (6.0.4,
Stat-Ease Inc., Minneapolis, MN, USA). The qualities oꢀ the
(NH ) SO
4 2
4
Tryptone
NaCl
CaCl2
ZnSO4
ꢁ
tted polynomial models were tested by the determination oꢀ
2
coeꢃcient R . Analysis oꢀ variance (ANOVA) together with
the F test was applied to evaluate the signiꢁcance oꢀ a given
term (p≤0.05). The location oꢀ the optimum was determined
by solving the set oꢀ equations derived by the diference oꢀ
the ꢁnal quadratic model.
X10
X11
1
1
Experimental design
To optimize the medium components afecting the production
oꢀ thermoalkalophilic lipase by the chemically induced mutant
oꢀ B. atrophaeus FSHM2, PBD and RSM was employed. At the
Results and discussion
ꢁ
rst step, the efect oꢀ eleven ꢀactors (Table 1, selected according
Mutagenesis of lipase‑producing bacterial strain
to a preliminary literature reviews) on lipase productivity was
determined and analyzed using PBD drawn by Design Expert
soꢀtware (6.0.4, Stat-Ease Inc., Minneapolis, MN, USA). Aꢀter-
wards, the levels oꢀ the main components achieved by PBD were
optimized by D-optimal approach oꢀ RSM. Coding oꢀ the ꢀactors
was perꢀormed based on the ꢀollowing equation:
The lipase-producing bacterial strain, B. atrophaeus FSHM2,
was subjected to chemical mutagenesis using EtBr. This
method was repeated three times to isolate a lipase-overpro-
ducing mutant. The primary selection was perꢀormed con-
sidering the orange-colored ꢂuorescent halos that appeared
by lipolysis on the BHIA plate supplemented by rhodamine
B (0.001%, w/v) (Fig. 1a). Among the ꢁve selected mutants
attained in this step, only three mutants (EB-5, EB-10, and
EB-30) represented signiꢁcantly higher lipase secretion aꢀter
cultivation in submerged culture compared to that oꢀ wild bac-
terial strain (Fig. 1b). In addition, it was observed that EB-5
ꢀ
ꢁ
i;0
x = X − X ∕ΔXi i = 1, 2, 3, … , k,
i
i
where x is the coded value oꢀ an independent variable, X is
i
i
the real value oꢀ each independent variable, X is the real
i;0
value oꢀ each independent variable at the center point, and
ΔX is the value oꢀ step change. To neutralize the inꢂuence
i
oꢀ nuisance variables, the designed runs (49 experiments)
were carried out randomly. The obtained results oꢀ Plack-
ett–Burman experimental design were then analyzed and 24
new experiments (Table 2, run 16–39) were added to the
previous design using augmentation oꢀ a central composite
design (CCD). To improve the leverage, the applied design
was completed by the addition oꢀ ten ꢀurther experiments
(
exposed to EtBr ꢀor 5 min at 37 °C) was the most eꢃcient
mutant able to produce 4301.1 U/l oꢀ lipase which was 2.4-
old oꢀ untreated control (p<0.05). Devi et al. (2015) reported
ꢀ
about the application oꢀ chemical mutagens such as EMS, EtBr,
sodium azide, and NTG ꢀor the improvement oꢀ lipase produc-
tion oꢀ Pseudomonas sp. VITSDVM1 among which EMS was
introduced as the best mutagen that elevated the lipase pro-
duction to 4960 U/l. The ꢁndings oꢀ the present study were
also similar to the one described by Iꢀtikhar et al. (2010). They
applied chemical mutagenic treatments (using NTG, nitrous
acid, and EtBr) to improve the lipolytic potential oꢀ the ꢀungal
(
Table 2, run 40–49). The ꢀollowing equation was used as
the most appropriate model to correlate the chosen variables
with the response.
n
n
n−1
n
ꢀ
ꢀ
ꢀ ꢀ
2
i
strain Rhizopus oligosporus (Iꢀtikhar et al. 2010). The mutant
Y = b +
0
b x +
i
b x +
ii
b x x + e,
ij i j
i
NTG-7
derived ꢀrom NTG treatment (IIB-63
) represented the
i=1
i=1
i=1 j=i+1
highest lipase activity (10,370 U/l) which was approximately
1
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Table 2 Experimental design
and results oꢀ the Plackett–
Burman design augmented
to D-optimal design ꢀor
Run Actual levels
Lipase activity (U/l)
Observed Predicted
X1
X2
X3
X4
X5
1.75 1.75 1.75 1.75
0.5 0.5 0.5
1.75 1.75 1.75 1.75
0.5 0.5
1.75 1.75 1.75 1.75
X6
X7
X8
X9
X10
X11
optimization oꢀ culture
1
2
3
4
5
6
7
8
9
1
1
1
1
1
1
1
1
1
1
2
2
2
2
3
5
3
5
3
1
1
1
1
1
5
5
5
5
1
3
3
3
3
3
3
3
3
1.5
2.5
1.5
2.5
1.5
0.5
0.5
2.5
2.5
2.5
0.5
0.5
0.5
2.5
0.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
2.5
1.5
0.5
1.5
2.5
0.5
2.5
2.5
0.5
0.5
2.5
2.5
0.5
0.5
1.5
1.5
0
1.5
0.5
1.5
0.5
1.5
0.5
2.5
0.5
2.5
2.5
0.5
2.5
2.5
2.5
0.5
1.5
1.5
1.5
1.5
1.5
3
5
3
5
3
5
5
1
1
5
1
1
5
1
1
3
3
3
3
3
3
3
3
3
3
3
3
0
3
3
3
3
3
3
3
3
3
3
5
3
1
3
5
5
1
5
1
5
1
1
5
1
3
3
3
3
6.64
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
0
3
1
3
5
3
1
5
5
5
1
5
1
5
1
1
3
3
3
3739.3
3476
3727.9
3485.4
3727.9
3591.1
3727.9
3537.3
3906.2
3116.1
3642.3
4011.4
3906.5
3854.1
3010.9
3590.4
3432.1
3669.6
3882.9
3814.8
2777.3
3094.1
3933.8
3880.1
3353.7
5038.6
3622.4
3405.3
2739.1
3039.4
3566.5
4040.2
3408.4
5146.3
3727.9
3830.1
3727.9
3819.1
3896.1
3726.2
3775.7
3536.6
3706.6
3594.3
3654.7
3779.5
4153.8
3586.6
3727.9
3727.9
3727.9
conditions ꢀor maximum lipase
production oꢀ EB-5 mutant
3
3686.6
3581.3
3739.3
3528.6
3897.3
3107.3
3634
3
3
3
0.5
3
0.5
3
3
0.5
3
3
3
3
3
0.5
0.5
0.5
3
0.5
3
0.5
3
3
0.5
3
3
3
0.5
0.5
3
3
3
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4002.6
3897.3
3844.6
3002
3
3
0.5
0.5
0.5
0.5
0.5
0.5
3581.3
3423.3
3686.6
3897.3
3844.6
0.5
0.5
1.75 1.75 1.75 4.03
1.75 1.75 4.03 1.75
1.75 1.75 1.75 1.75
1.75 1.75 1.75 1.75
1.75 1.75 1.75 1.75
1.5
1.5
1.5
6.64 2791.3
3
3
3
3
3
3
3
3
3
3
0
3
3
3
3
3
3
3
3
3
3107.3
3950
3897.3
3265.3
5056
3.32 1.75 1.75 1.75 1.75
1.5
0
3.32 1.5
1.75 1.75 1.75 1.75
1.75 1.75 1.75 1.75
1.75 1.75 1.75 1.75
1.75 1.75 1.75 1.75
1.5
6.64 1.5
1.5
1.5
3.32 1.5
2
2
2
2
4
5
6
7
1.5
3
3
3
3
3
3
0
3
3
3
3
3
3
3
3
1.5
1.5
1.5
1.5
1.5
1.5
1.5
0
1.5
1.5
1.5
1.5
1.5
1.5
1.5
3634
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
0
1.75 1.75 1.75
1.75 1.75 1.75
1.75 1.75 1.75 1.75
1.75 1.75 1.75
3423.3
2738.6
3054.6
3581.3
4055.3
3423.3
5161.3
3686.6
3844.6
3739.3
3792
0
2
2
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1.75 1.75 1.75 1.75
1.75 1.75 1.75 1.75
1.75 1.75 1.75 1.75
1.75 1.75 1.75 1.75
4.03 1.75 1.75 1.75
1.75 1.75 1.75 1.75
1.75
1.75 4.03 1.75 1.75
1.75 1.75 1.75 1.75 6.64
1.75 1.75 1.75 1.75
0
1.75 1.75
3886.6
3739.3
3792
3
2.83 0.99 1.69 1.44 1.85 1.74 2.7
1.18 2.83 4.24 3.69 3528.6
2.11 1.55 2.05 1.63 1.33 1.47 2.22 2.04 2.84 2.92 2.09 3686.6
2.93 1.83 1.35 2.35 2.34 1.86 1.57 1.26 2.93 1.35 2.57 3581.3
2.32 1.9
2.77 2.01 1.04 1.6
1.83 1.59 1.36 1.44 1.28 1.7
2.61 1.24 1.51 2.26 2.31 1.12 1.83 2.11 3.46 3.07 1.39 3581.3
3
3
3
1.12 1.35 1.05 1.77 1.57 2.27 3.28 2.75 3.45 3634
1.67 1.88 1.64 1.44 4.28 1.41 3.27 3792
2.24 1.78 1.73 2.98 3.34 4160.6
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.75 1.75 1.75 1.75
1.75 1.75 1.75 1.75
1.75 1.75 1.75 1.75
3
3
3
3
3
3
3
3
3
3739
3739.3
3686.6
1
3

268
Page 6 of 11
3 Biotech
(2019) 9:268
Lipase production = + 3727.90 + 447.87X − 347.86X
1
2
−
+
−
+
+
−
−
−
+
−
57.96X + 187.88X + 116.42X
3 4 5
318.69X + 28.29X + 188.70X − 187.27X
10
7
8
9
346.94X11 + 81.75X X + 726.06X X
3
1
2
1
1925.62X X + 1928.30X X − 3772.39X X
7
1
4
1
6
1
2207.87X X − 1360.31X X − 714.41X X
10
1
8
1
9
1
2224.58X X + 2142.21X X + 2412.88X X
4
1
11
2
3
1
4560.15X X − 1022.32X X + 1730.70X X
7
2
5
1
6
2
2
1
332.16X X + 1020.46X X + 149.63X
2
8
2
9
2
2
2
4
2
5
2
7
237.09X − 41.04X − 33.12X − 128.13X
2
8
2
9
2
10
2
33.00X − 104.17X − 88.44X − 96.34X .
11
According to the signiꢁcance oꢀ the p values (< 0.05)
and non-signiꢁcance oꢀ the lack oꢀ ꢁtness, it was implied
that the experimental data was well ꢁtted with the selected
model. In addition, the amount oꢀ squared correlation
2
coeꢃcient (R , 0.9989) showed that the model was able
to explain 99.89% oꢀ the variation in the response. Fur-
thermore, the proximity oꢀ the predicted and adjusted
R-squared values (0.9494 and 0.9953, respectively)
implied that a better ꢁtness could be achieved. The amount
oꢀ variation coeꢃcient (C.V.%) was 0.81. All oꢀ the above-
mentioned values together with the suꢃcient precision oꢀ
the model (an indicator oꢀ the signal to noise ratio) which
enhanced to 92.652 suggested that equation oꢀ the selected
model was adequate to explain the response oꢀ the experi-
mental observations related to the lipase production and
also navigate the design space.
Fig. 1 a Positive colony oꢀ lipase-producing mutant on BHIA plate
containing rhodamine B (0.001%) aꢀter exposure to UV light. b
Screening the best mutant oꢀ B. atrophaeus aꢀter diferent exposure
times to EtBr compared with the wild strain oꢀ B. atrophaeus (as a
positive control). Signiꢁcance (*) was evaluated aꢀter ANOVA analy-
sis oꢀ the obtained results (p value <0.05)
Figure 2a represented the predicted versus observed
data ꢀrom which the validity oꢀ the model and agreement
between predicted and observed values was completely
obvious. Furthermore, the Box-Cox graph oꢀ the natural
logarithm (Ln) oꢀ the residual SS (sum oꢀ square) against
lambda (Fig. 2b) showed a minimum value oꢀ 0.92 which
was in the range oꢀ minimum (0.3) and maximum (1.51)
conꢀidence interval value (Fig. 2b). The data did not
require a transꢀormation, as the current value oꢀ conꢁ-
dence interval (lambda) was very close to the optimum
value. Comparison oꢀ the attained experimental results and
the predicted values summarized in Table 2 showed good
accordance between the predicted and observed data.
Using the selected model, the optimum levels oꢀ the
applied ꢀactors ꢀor maximum lipase production oꢀ EB-5
mutant were predicted to be 0.5% oꢀ glucose, 5% oꢀ olive
oil, 2% oꢀ maltose, 0.5% oꢀ sucrose, 2.5 g/l oꢀ yeast extract,
threeꢀold higher compared to that oꢀ the wild strain (3200 U/l).
EtBr-7
IIB-63
mutant was also ꢀound to be the producer oꢀ extra-
cellular lipase with the activity oꢀ 6990 U/l which was nearly
twoꢀold higher than its untreated strain (Iꢀtikhar et al. 2010).
Medium optimization
The obtained results oꢀ the ꢁrst step oꢀ medium components
optimization perꢀormed by PBD augmented to D-optimal
design showed variation oꢀ lipase productivity in the range
oꢀ 2738.7–5161.3 U/l (Table 2). Table 3 represented the sta-
tistical analysis oꢀ the obtained results among which olive oil,
maltose, tryptone, yeast extract, (NH ) SO , and NaCl were
4
2
4
ꢀ
ound to signiꢁcantly enhance the lipase productivity oꢀ EB-5
mutant (p<0.05), while sucrose, glucose, CaCl , and ZnSO
2
4
exhibited a signiꢁcantly negative efect (p<0.05).
2
1
.5 g/l oꢀ tryptone, 1.75 g/l oꢀ urea, 1.75 g/l oꢀ (NH ) SO ,
According to the attained D-optimal results, a second-order
polynomial expression was ꢁtted. The ꢀollowing quadratic
model (in the terms oꢀ coded values) was then deꢁned by the
soꢀtware ꢀor estimating lipase production oꢀ the EB-5 mutant.
4 2 4
g/l oꢀ CaCl , 2 g/l oꢀ NaCl, and 1 g/l oꢀ ZnSO .
2
4
To validate the selected model, the suggested optimum
medium composition was applied ꢀor lipase production
1
3

3
Biotech
(2019) 9:268
Page 7 of 11 268
Table 3 Analysis oꢀ variance
Source
Sum oꢀ squares
df
Mean square
F value
p value
ꢀ
or D-optimal reꢁned model
Prob>F
to optimize the medium
compositions in relation to
lipase activity (U/l) by EB-5
mutant
Block
Model
X1
X2
X3
X4
X5
X7
X8
99,247
2
49,623
8,555,000.0
1,381,000.0
819,000.0
22,317.3
238,600.0
90,993.3
677,600.0
5344.1
35
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
11
6
5
48
244,400.0
1,381,000.0
819,000.0
22,317.3
238,600.0
90,993.3
677,600.0
5344.1
276.6
1563.4
927.0
25.3
270.1
103.0
767.0
6.1
272.3
273.5
910.6
34.8
103.8
322.7
416.7
677.4
385.9
170.2
20.3
< 0.0001
< 0.0001
< 0.0001
0.0004
< 0.0001
< 0.0001
< 0.0001
0.0317
< 0.0001
< 0.0001
< 0.0001
0.0001
< 0.0001
< 0.0001
< 0.0001
< 0.0001
< 0.0001
< 0.0001
0.0009
< 0.0001
< 0.0001
< 0.0001
< 0.0001
< 0.0001
< 0.0001
0.0004
< 0.0001
< 0.0001
< 0.0001
< 0.0001
0.0003
< 0.0001
0.0003
< 0.0001
< 0.0001
< 0.0001
Signiꢁcant
X9
X10
X11
240,500.0
241,700.0
804,500.0
30,763.4
91,747.3
285,100.0
368,100.0
598,500.0
340,900.0
150,400.0
17,953.3
308,400.0
188,800.0
806,400.0
722,700.0
71,101.2
191,600.0
22,171.5
36,029.9
503,200.0
1,264,000.0
38,017.1
24,724.7
369,100.0
24,487.4
244,800.0
176,600.0
209,100.0
9718.7
240,500.0
241,700.0
804,500.0
30,763.4
91,747.3
285,100.0
368,100.0
598,500.0
340,900.0
150,400.0
17,953.3
308,400.0
188,800.0
806,400.0
722,700.0
71,101.2
191,600.0
22,171.5
36,029.9
503,200.0
1,264,000.0
38,017.1
24,724.7
369,100.0
24,487.4
244,800.0
176,600.0
209,100.0
883.5
X1X2
X1X3
X1X4
X1X6
X1X7
X1X8
X1X9
X1X10
X1X11
X2X3
X2X4
X2X5
X2X6
X2X7
X2X8
X X
349.1
213.7
912.8
818.0
80.5
216.9
25.1
40.8
2
9
2
1
X
X
X
X
X
X
X
X
X
569.6
1431.2
43.0
28.0
417.8
27.7
277.1
199.9
236.7
2
2
2
4
2
5
2
7
2
8
2
9
2
1
0
1
2
1
Residual
Lack oꢀ ꢁt
Pure error
Cor total
4633.4
5085.3
8,663,000.0
772.2
1017.1
0.8
0.63
Not signiꢁcant
R2=0.9989; R A2 dj=0.9494; R =0.9953; adeq precision=92.652
2
Pred
(
ꢁve times). The mean lipase activity oꢀ these ꢁve repli-
bacterial strain, the lipase productivity oꢀ the EB-5 mutant
was increased by 6.5-ꢀold (Fig. 3).
cates was measured to be 14,773 ± 576.9 U/l which was
in the conꢁdence interval range indicated by the soꢀtware
and also showed appropriate agreement with the pre-
dicted results (14,824.3 U/l). Compared to that oꢀ the wild
Figure 4 illustrated the 3D plots oꢀ lipase activity
against two studied variables (in their related range),
while others kept constant (in center point). Figure 4a
1
3

268
Page 8 of 11
3 Biotech
(2019) 9:268
represented the response surꢀace ꢀor olive oil (− 1: 1%,
1: 5; %) and maltose (− 1: 0.5%, + 1: 2.5; %), while
+
other variables kept constant (their center points). At
a high level oꢀ olive oil (5%) and a high level oꢀ malt-
ose (2.5%), maximum lipase activity (6384.7 U/l) was
observed. When olive oil and maltose were at center
points, the lipolytic activity considerably decreased
to 3727.9 U/l (p < 0.05). Liu et al. (2011) reported the
signiꢀicant inꢀluence oꢀ olive oil (0.5–5.14 mM) as a
lipase inducer by Burkholderia sp. In addition, Samaei-
Nouroozi et al. (2015) ꢀound that the maximum lipase
production (856.9 U/l) by Alkalibacillus salilacus was
obtained mainly in the presence oꢀ a high concentration oꢀ
olive oil (2%). Previously, statistical experimental design
showed a signiꢀicant positive eꢀꢀect oꢀ olive oil on lipase
production by C. cylindracea (Salihu et al. 2011). How-
ever, Hasan-Beikdashti et al. (2012) reported the negative
eꢀꢀect oꢀ olive oil on extracellular lipase production by
Stenotrophomonas maltophilia.
As presented in Fig. 4a, the greatest increase in lipase
production by EB-5 mutant (6400 U/l) was observed at
a high level oꢀ maltose (2.5%). Mahanta et al. (2008)
reported higher lipase activity (976 U/g) in the solid-state
ꢀ
ermentation (Jatropha curcas seed cake as substrate) oꢀ
P. aeruginosa PseA supplemented with maltose as the car-
bon source. Yele and Desai (2015) who optimized the ꢀer-
mentation media ꢀor overproduction oꢀ thermostable and
organic solvent-tolerant lipase by Staphylococcus warneri
reported the signiꢁcant efect oꢀ adding maltose (0.054%)
on lipase production. In the present study, it seems that a
high level (2.5%) oꢀ glucose and sucrose exhibited a nega-
tive efect on lipase productivity oꢀ EB-5 mutant (1545
and 2128 U/l, respectively), while insertion oꢀ maltose
at a high level (2.5%) lead to higher lipase production
Fig. 2 a Studentized residuals vs. predicted response by the ꢁnal
quadratic model, b Box-Cox plot ꢀor power transꢀormation oꢀ lipase
production by mutant oꢀ B. atrophaeus FSHM2
(
6138 U/l).
The 3D plot oꢀ olive oil and urea efects on lipase produc-
tion by EB-5 mutant was illustrated in Fig. 4b ꢀrom which
it was revealed that a higher lipase activity (6231.4 U/l was
observed at a high level oꢀ urea (3 g/l) and olive oil (5%)
(
p < 0.05). Sangeetha et al. (2008) reported about the sig-
niꢁcant inꢂuence oꢀ urea on extracellular lipase production
oꢀ B. pumilus SG 2. Furthermore, Bora and Bora (2012)
reported that various inorganic nitrogen sources including
ammonium sulꢀate and urea enhanced lipase production by
Bacillus sp. LBN2 in the range oꢀ 10,000–17,000 U/l. On
the contrary, Veerapagu et al. (2013) showed that urea had
a signiꢁcantly inhibitory efect on the lipase production by
Pseudomonas gessardii.
As shown in Fig. 4c, the lipolytic activity oꢀ EB-5 mutant
culture broth was inꢂuenced by olive oil and tryptone. The
maximum lipase activity (6503.2 U/l) achieved when tryp-
tone was at its highest level (3 g/l). Thereꢀore, a positive
Fig. 3 Overproduction oꢀ lipase by the mutant EB-5 under opti-
mized conditions including 5% oꢀ olive oil, 0.5% oꢀ glucose, 0.5%
oꢀ sucrose, 2% oꢀ maltose, 2.5 g/l oꢀ yeast extract, 1.75 g/l oꢀ urea,
1
.75 g/l oꢀ (NH ) SO , 2.5 g/l oꢀ tryptone, 2 g/l oꢀ NaCl, 1 g/l oꢀ
4 2 4
CaCl , and 1 g/l oꢀ ZnSO
2
4
1
3

3
Biotech
(2019) 9:268
Page 9 of 11 268
Fig. 4 Response surꢀace plots oꢀ the impact oꢀ various ꢀactors on lipase production oꢀ the EB-5 mutant. a Olive oil and maltose, b olive oil and
urea, c olive oil and tryptone, and d olive oil and NaCl. Other ꢀactors are kept at a constant level (their center points)
efect oꢀ tryptone concentration inꢂuenced the lipase activ-
ity oꢀ mutant EB-5 (p < 0.05). As obtained in the present
study, organic nitrogen sources (yeast extract and tryptone)
and inorganic nitrogen sources (urea and ammonium sulꢀate)
exhibited a positive signiꢁcant efect on the lipase produc-
tion oꢀ EB-5 mutant (p<0.05). Kumar et al. (2011) reported
the negative efect oꢀ yeast extract and peptone on the lipol-
ytic activity oꢀ B. pumilus RK31 in primary screening using
Plackett–Burman statistical design.
Conclusion
The present research aimed to develop a mutant strain oꢀ
B. atrophaeus FSHM2 with high ability ꢀor thermoalka-
lophilic lipase biosynthesis using a chemical mutagenesis
method ꢀollowed by the application oꢀ statistical methods
to optimize culture medium components required ꢀor lipase
production by the best mutant. Among the total variables,
olive oil, maltose, yeast extract, tryptone, (NH ) SO , and
4
2
4
Haider Ali et al. (2015) reported the signiꢁcant nega-
tive efect oꢀ NaCl on lipase production by Pseudomonas
aeruginosa FW_SH-1. However, Sathishkumar et al. (2015)
reported the positive efect oꢀ NaCl on lipase production by
Halobacillus trueperi RSK CAS9. Several studies reported
the stimulatory efects oꢀ diferent ions on lipase production
by diferent microorganisms (Riyadi et al. 2017; Verma et al.
NaCl displayed positive signiꢁcant efects (p < 0.05) on
lipase production by the most eꢃcient mutant (EB-5), while
glucose, sucrose, CaCl , and ZnSO had a negative efect
2
4
(p<0.05). Finally, the best optimum medium composition
ꢀor maximum production oꢀ lipase (14,773± 576.9 U/l) by
EB-5 mutant was determined as ꢀollows: 5% oꢀ olive oil,
0.5% oꢀ glucose, 0.5% oꢀ sucrose, 2% oꢀ maltose, 2.5 g/l
oꢀ yeast extract, 1.75 g/l oꢀ urea, 1.75 g/l oꢀ (NH ) SO ,
2
012). For example, Verma et al. (2012) reported that the
4
2
4
2
+
Mg ions have signiꢁcant inꢂuence on lipase production
by P. aeruginosa (p<0.05). Yele and Desai (2015) reported
the enhancement in the lipase productivity oꢀ S. warneri
in the presence oꢀ K HPO (0.091%). Figure 4d illustrated
2.5 g/l oꢀ tryptone, 2 g/l oꢀ NaCl, 1 g/l oꢀ CaCl , and 1 g/l
2
oꢀ ZnSO . Overproduction oꢀ thermoalkalophilic lipase by
4
EB-5 mutant oꢀ B. atrophaeus FSHM2 was achieved using
simple mutagenesis and medium optimization methods.
However, ꢀurther studies must be perꢀormed to determine
the probable mechanism oꢀ mutation and potential applica-
tion oꢀ this strain ꢀor large-scale production oꢀ lipase.
2
4
the efect oꢀ olive oil and NaCl concentrations on lipase
production by EB-5 mutant. The maximum lipase activity
(
5376.4 U/l) was achieved when NaCl was at the lowest level
(
1 g/l, p<0.05).
1
3

268
Page 10 of 11
3 Biotech
(2019) 9:268
Acknowledgements This work was supported by National Institute
energy-eꢃcient removal oꢀ oil stains ꢀrom polycotton ꢀabric.
3 Biotech 6:131. https://doi.org/10.1007/s13205-016-0449-z
Devi SC, Mohanasrinivasan V, Naine JS, Yamini B, Chitra M,
Nandhini G (2015) Strain improvement oꢀ Pseudomonas sp.
VITSDVM1 ꢀor optimization oꢀ lipase production by chemical
mutagens. Res J Pharm Biol Chem Sci 6:782–787
ꢀ
or Medical Research Development oꢀ Iran (NIMAD, 977008). Fur-
thermore, we thank the Pharmaceutics Research Center, Institute oꢀ
Neuropharmacology, Kerman University oꢀ Medical Sciences (Ker-
man, Iran) ꢀor their admirable participation in this study.
Faisal PA, Hareesh ES, Priji P, Unni KN, Sajith S, Sreedevi S, Josh
MS, Benjamin S (2014) Optimization oꢀ parameters ꢀor the
production oꢀ lipase ꢀrom Pseudomonas sp. BUP6 by solid
state ꢀermentation. Adv Enzyme Res 2:125–134. https://doi.
org/10.4236/aer.2014.24013
Compliance with ethical standards
Conflict of interest The authors declare that they have no conꢂicts oꢀ
interest.
Forootanꢀar H, Amirpour-Rostami S, Jaꢀari M, Forootanꢀar A, Youse-
ꢁ
zadeh Z, Shakibaie M (2015) Microbial-assisted synthesis and
evaluation the cytotoxic efect oꢀ tellurium nanorods. Mater Sci
Eng C 49:183–189. https://doi.org/10.1016/j.msec.2014.12.078
Galvão WS, Pinheiro BB, Golçalves LRB, de Mattos MC, Fonseca
TS, Regis T, Zampieri D, dos Santos JCS, Costa LS, Correa
MA, Bohn F, Fechine PBA (2018) Novel nanohybrid biocata-
lyst: application in the kinetic resolution oꢀ secondary alcohos.
J Mater Sci 53:14121–14137. https://doi.org/10.1007/s1085
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