Pranhita R Nimbalkar1,2, Manisha A Khedkar2, Rishikesh S Parulekar3, Vijaya K Chandgude1, Kailas D Sonawane3,4, Prakash V Chavan2, Sandip B Bankar1. 1. Department of Bioproducts and Biosystems, School of Chemical Engineering, Aalto University P.O. Box 16100, FI-00076 Aalto, Finland. 2. Department of Chemical Engineering, Bharati Vidyapeeth Deemed University College of Engineering, Pune 411043, India. 3. Department of Microbiology, Shivaji University, Kolhapur 416004, India. 4. Department of Biochemistry, Structural Bioinformatics Unit, Shivaji University, Kolhapur 416004, India.
Abstract
Metabolic engineering has the potential to steadily enhance product titers by inducing changes in metabolism. Especially, availability of cofactors plays a crucial role in improving efficacy of product conversion. Hence, the effect of certain trace elements was studied individually or in combinations, to enhance butanol flux during its biological production. Interestingly, nickel chloride (100 mg L-1) and sodium selenite (1 mg L-1) showed a nearly 2-fold increase in solvent titer, achieving 16.13 ± 0.24 and 12.88 ± 0.36 g L-1 total solvents with yields of 0.30 and 0.33 g g-1, respectively. Subsequently, the addition time (screened entities) was optimized (8 h) to further increase solvent production up to 18.17 ± 0.19 and 15.5 ± 0.13 g L-1 by using nickel and selenite, respectively. A significant upsurge in butanol dehydrogenase (BDH) levels was observed, which reflected in improved solvent productions. Additionally, a three-dimensional structure of BDH was also constructed using homology modeling and subsequently docked with substrate, cofactor, and metal ion to investigate proper orientation and molecular interactions.
Metabolic engineering has the potential to steadily enhance product titers by inducing changes in metabolism. Especially, availability of cofactors plays a crucial role in improving efficacy of product conversion. Hence, the effect of certain trace elements was studied individually or in combinations, to enhance butanol flux during its biological production. Interestingly, nickel chloride (100 mg L-1) and sodium selenite (1 mg L-1) showed a nearly 2-fold increase in solvent titer, achieving 16.13 ± 0.24 and 12.88 ± 0.36 g L-1 total solvents with yields of 0.30 and 0.33 g g-1, respectively. Subsequently, the addition time (screened entities) was optimized (8 h) to further increase solvent production up to 18.17 ± 0.19 and 15.5 ± 0.13 g L-1 by using nickel and selenite, respectively. A significant upsurge in butanol dehydrogenase (BDH) levels was observed, which reflected in improved solvent productions. Additionally, a three-dimensional structure of BDH was also constructed using homology modeling and subsequently docked with substrate, cofactor, and metal ion to investigate proper orientation and molecular interactions.
Butanol is an imperative industrial chemical,
possessing excellent
fuel properties, and thus can be thought to have potential to replace/supplement
fossil gasoline.[1,2] Especially, the Asia–Pacific
region is known to cover the biggest market of n-butanol,
which accounted for 51.3% consumption by volume in 2014.[3] Moreover, the global n-butanol
market is expected to reach USD 9.9 billion by 2020.[4] Due to such an eye-catching worldwide market, the historical
biobutanol production, usually referred to as acetone-butanol-ethanol
(ABE) fermentation by solventogenic Clostridia, has reannounced its
importance as a green alternate renewable fuel.[4]Conventional ABE fermentation process observed major
challenges
viz. low butanol concentration, yield, productivity, and solvent intolerance
resulting in a high overall production cost, thus impeding its commercialization.[5] To alleviate these concerns, increasing butanol
concentration and the B:A (butanol:acetone) ratio without sacrificing
the total solvent productivity have been considered to be key points
by many research groups.[6,7] In this view, a couple
of techniques including strain mutagenesis, genetic engineering, and
metabolic regulation have been implemented.[8] Additionally, overexpression of targeted functional genes in the
engineered host has also been practiced to overcome butanol toxicity
obstruction in microorganisms.[9] However,
unstable butanol production shows difficulty and complexity in transferring
related pathways to host bacteria, due to the inherent instability
and inactive expression in contrast to a wild-type strain.[10]In relation to the aforesaid approaches,
studies pertaining to
alteration in metabolic flux with the help of microbial electro-synthesis
and electro-fermentation have demonstrated potential and feasibility
in enhancing microbial production.[11−13] Additionally, cofactors
involved in biosynthetic pathways would be considered to be possible
targets to induce changes in metabolism.[9] In the case of solventogenic Clostridia, butanol dehydrogenase (BDH)
is a key enzyme that catalyzes conversion of butyraldehyde to butanol,
and the reaction is cofactor dependent (Figure ). Thus, constant availability of cofactor
(NADH and NADPH) in the solventogenic phase is essential to achieve
a redox balance so as to improve butanol titer.[10,14] Recently, numerous electron carriers/pigments are studied to overproduce
NADH which ultimately accelerates butanol flux.[15] On the other hand, literature reports also explain the
role of trace elements as cofactors for enzymes involved in the metabolic
pathway.[16] Rajagopalan et al.[14] discussed that BDH from C. acetobutylicum ATCC 824 requires a metal ion and a reduced condition for its activity.
However, BDH from Clostridium sp. BOH3 requires neither
any metal ion nor reduced conditions thus inferring that enzyme requirements
differ from species to species.
Figure 1
Reaction catalyzed by BDH from C. acetobutylicum ATCC 824.
Reaction catalyzed by BDH from C. acetobutylicum ATCC 824.Several in silico approaches have been usually performed
to reveal
the interactions involved in enzyme–substrate/inhibitor binding.[17−19] Further, the protein sequences of BDH from different Clostridia
are also available at the National Center for Biotechnology Information
(NCBI). However, the 3D structure of BDH from C. acetobutylicum ATCC 824 is neither determined experimentally (X-ray and/or NMR)
nor predicted by computational techniques, to date. Hence, the crystal
structure of BDH from Clostridia is not available in the Protein Databank
(PDB). Indeed, to understand the biophysical properties of enzymes,
it is essential to have 3D structures of the target molecule. At the
same time, obtaining X-ray diffraction quality crystals of a protein
is quite difficult.[20] Thus, homology modeling
is thought to be reliable and an efficient method for 3D structure
prediction.[21] Besides, active sites in
crystal structures can be resolved using molecular docking protocols.[22]The present study attempted to enhance
butanol titer in fermentation
broth by using Clostridium acetobutylicumNRRL B-527
(ATCC 824). Therefore, trace elements (act as enzyme cofactors) were
screened to investigate their effect for improved production. Additionally,
this study also highlights physiological changes occurring during
ABE fermentation. Furthermore, the 3D model was constructed with the
help of homology modeling and assessed using different assessment
tools to reveal the catalytic potential of BDH from C. acetobutylicum ATCC 824. The current study also enlightens the mode of possible
interactions of the substrate and/or inhibitor with BDH, using molecular
docking studies. This work proves the significance of trace elements
in enhancing butanol production, and in silico studies confirm that
BDH is a metalloenzyme possessing a Rossmann fold in its structural
domain.
Materials and Methods
Cell Culture and Fermentation
Experiments
The bacterial
strain of C. acetobutylicumNRRL B-527 was a kind
gift from ARS Culture Collection, U.S.A. The cells were stored as
spores in 6% (w/v) starch solution. These spores were activated in
reinforced clostridial medium (RCM) as mentioned by Harde et al.[23] and further used as seed inoculum for fermentation
batches.The production medium used in this study consisted
of the following (g L–1): glucose (60), magnesium
sulfate (0.2), sodium chloride (0.01), manganese sulfate (0.01), iron
sulfate (0.01), dipotassium hydrogen phosphate (0.5), potassium dihydrogen
phosphate (0.5), ammonium acetate (2.2), biotin (0.01), thiamin (0.1),
and p-aminobenzoic acid (0.1), at pH 6.5. Fermentation
experiments were performed in 100 mL airtight glass bottles with 80
mL of production medium. The production medium was purged with nitrogen
to maintain anaerobic environment and sterilized at 121 °C for
20 min.Trace elements investigated in this study were: sodiumselenite
(Na2SeO3·5H2O), sodium tungstate
(Na2WO4·2H2O), nickel chloride
(NiCl2·6H2O), zinc sulfate (ZnSO4), and iron(II) chloride (FeCl2·4H2O).
Each element was prepared in a varied concentration range (1–100
mg L–1) and added by filter sterilization (0.22
μm), before inoculation. Subsequently, 5% (v/v) (OD600 = 1.56) of actively growing cells (from seed culture) were inoculated
and fermentation was continued until 120 h at 37 ± 2 °C.
All of the chemicals used in this study were of analytical grade.
All experiments were carried out at least in triplicate, and the results
mentioned are average ± standard deviation.
Analytical
Methods
Fermentation samples were withdrawn
at regular time intervals and centrifuged at 20 000g for 10 min. The resulting supernatant was analyzed for
total solvents (acetone, butanol, and ethanol) and total acids (acetic
and butyric acid) by gas chromatography (Agilent Technologies 7890B)
equipped with a DB-WAXetr column (30 m × 0.32 mm × 1 μm)
and a flame ionization detector. The oven temperature was programmed
as 80 (1 min hold) to 200 °C at 30 °C/min rise (1 min hold),
and the injector and detector were set at 200 and 250 °C, respectively.
A 0.5 μL sample was injected with a split ratio of 20:1. Clostridial
growth was also monitored by measuring optical density (OD) at 600
nm using UV–visible spectrophotometer (3000+, LabIndia).
In addition, a medium pH was observed throughout the fermentation
process by using a laboratory pH meter (Global, India). The glucose
concentration was determined by phenol-sulfuric acid method.[24] Besides, BDH activity was also assayed at certain
times of interest according to the method reported by Rajagopalan
et al.[14]
Homology Modeling and Structural
Assessment
Amino acid
sequence of targeted protein, BDH (accession no. AAA23206) was retrieved
from NCBI (https://www.ncbi.nlm.nih.gov/). The online BLAST (Basic Local Alignment Search Tool) search algorithm
was used in order to find out homologous template. Afterward, the
pairwise sequence alignment between target and template sequences
was carried out using CLUSTALW to discover sequence similarity.[25] Further, MODELLER 9.19 software was employed
to build a 3D structure of the target protein.[21] The best model was opted among 50 generated structures,
which was based on certain scoring parameters such as MODELLER objective
function, DOPE (discrete optimized protein energy) pseudoenergy value,
and GA341 score.[21] The predicted model
was evaluated using ERRAT, PROCHECK, and ProSA which was then visualized
with UCSF Chimera.[26−29] Moreover, unfavorable nonbonded contacts were removed by energy
minimization using the steepest decent algorithm in UCSF Chimera.
Molecular Docking Studies
Molecular docking is a simulation
process in which a receptor–ligand conformation can be predicted.
The receptor can either be a protein or nucleic acid, whereas the
ligand is quite a tiny molecule which can be any organic compound.[22] In the present study, the stabilized 3D structure
of BDH was used to dock ligand (NADH) and substrate (butyraldehyde)
to binding-site using PATCHDOCK online program.[30] On the other hand, experimentally known fermentation inhibitors
such as furan derivatives and weak acids were also docked with BDH
protein to investigate the binding mode between them. Particularly,
3D structures of the ligand, substrate, and inhibitor were retrieved
from the PubChem database in SDF (Structure data file) format. Furthermore,
these structures were converted to PDB format using Openbabel.[31] Finally, they were individually sent along with
the receptor (BDH) to PATCHDOCK server for docking. The resulting
docked complex with best geometric shape complementarity score was
analyzed using UCSF Chimera to elucidate interacting residues.
Results
and Discussion
Effect of Varying Trace Element Concentration
on Biobutanol
Production
The impact of different trace elements namely
sodium selenite, nickel chloride, zinc sulfate, iron chloride, and
sodium tungstate was studied with respect to butanol production and
overall solvent yield by using C. acetobutylicum NRRL
B-527. These elements were selected based on their active role in
different biochemical reactions. Various concentration ranges for
each element were individually supplemented to fermentation medium
in order to find the optimal concentration responsible for the increment
in butanol level. Figure highlights butanol and total solvent production under varied
trace elements concentration. It was observed that the addition of
almost all trace elements had significantly improved biobutanol production
when compared with the control experiment.
Figure 2
Effect of trace elements
on butanol (A) and total solvent production
(B) in batch fermentation by C. acetobutylicum NRRL
B-527: SE, selenite; FE, iron; WO, tungstate; ZN, zinc; NI, nickel.
Effect of trace elements
on butanol (A) and total solvent production
(B) in batch fermentation by C. acetobutylicum NRRL
B-527: SE, selenite; FE, iron; WO, tungstate; ZN, zinc; NI, nickel.Regular P2 medium (control) produced
butanol up to 5.34 ±
0.10 g L–1 with a total ABE of 7.88 ± 0.25
g L–1 after 120 h fermentation. On the other hand,
selenite addition (1 mg L–1) enhanced butanol production
up to 8.21 ± 0.13 g L–1 with total solvents
of 12.88 ± 0.36 g L–1. Further increase in
selenite concentration up to 100 mg L–1 drastically
reduced solvent production, because of restricted Clostridial growth.
Kousha et al.[32] observed a similar finding,
and they concluded that higher selenium concentration (>1 mg L–1) activates the detoxification processes, which transforms
selenite to elemental selenium which gets deposited near the periphery
of bacterial cells thus affecting microbial growth.Supplementation
of iron chloride also showed significant increment
in butanol concentration, irrespective of its concentration addition
(Figure ). A similar
trend was observed when the fermentation medium was supplemented with
tungstate with butanol accumulation up to 7.02 ± 0.29 g L–1. Interestingly, zinc sulfate also showed a positive
effect on butanol production accounting to have 9.09 ± 0.12 g
L–1 butanol together with 14.08 ± 0.48 g L–1 total ABE. The highest butanol (10.81 ± 0.15
g L–1) and total solvent (16.13 ± 0.24 g L–1) production were achieved in a medium supplemented
with 100 mg L–1 nickel chloride, which is around
50% higher than in the control experiment (without trace element).
The butanol concentration remained unchanged with further addition
(>100 mg L–1) of nickel chloride.Interestingly,
an exogenous inclusion of trace elements in this
study have led to step up in ABE and butanol concentrations which
thought to be due to enrichment of BDH activity.[10] Several researchers have also studied the effect of reducing
agents and/or precursors for improved butanol titer.[7,10,33] Isar and Rangaswamy[34] showed moderate increase in butanol production
by using Clostridium beijerinckii when the medium
has been supplemented with calcium ions. Furthermore, Saxena and Tanner[35] also demonstrated that ethanol production by C. ragsdalei was improved 4-fold by optimizing the trace
metal concentrations because of enhanced metalloenzyme activities.
The improved performance by nickel, selenite, and zinc propelled us
to evaluate their performance with a more detailed study such as time
of addition during the fermentation experiment.
Time of Trace
Element Addition for Enhanced Butanol Production
Nickel chloride,
sodium selenite, and zinc sulfate with optimal
concentrations of 100, 1, and 100 mg L–1, respectively,
were used to study their effect on “addition time” in
fermentation medium. These elements were added at different fermentation
time intervals of 0, 4, 8, 18, and 24 h. Since, Clostridia tend to
enter into the stationary phase after 36 h, to produce solvents, this
study was not extended after 24 h of fermentation.From Figure A, it was found that
the highest butanol concentration (12.22 ± 0.09 g L–1) was achieved when nickel chloride was added after 8 h of fermentation.
Initial supplementation (0 h) of nickel chloride resulted in comparatively
lower butanol production (9.32 ± 0.19 g L–1). Interestingly, the growth profiles of C. acetobutylicum B-527 (data not shown) with and without nickel chloride did not
show any substantial difference. Furthermore, the ethanol production
profile was also unaffected without change in concentration. Incidentally,
acetone production was slightly fluctuated with a different time of
addition.
Figure 3
Time course of trace elements addition: (A) nickel chloride, (B)
sodium selenite, and (C) zinc sulfate.
Time course of trace elements addition: (A) nickel chloride, (B)
sodium selenite, and (C) zinc sulfate.Sodium selenite was also effective in enhancing the butanol
concentration
when included after 8 h of fermentation. The maximum amount of butanol
achieved was 10.69 ± 0.52 g L–1 along with
4.67 ± 0.21 g L–1 acetone and 1.37 ± 0.12
g L–1 ethanol. Considering the time profile of addition,
selenite did not show remarkable variations in individual solvent
production (Figure B). Conversely, it significantly affected growing Clostridia, which
was indicated by the growth profile (data not shown). This was evident
from the observation that selenite slowed down the growth (OD600 = 1.55) when added at beginning (0 h) and supported the
growth (OD600 = 2.12) after intermittent additions. Usually,
the initial time of the growth curve corresponds to adaptation of
microbial cells, and incorporation of selenite during this period
may alter the physiological environment, causing oxidative stress
to reduce microbial growth.[36] On the other
hand, zinc sulfate showed improvement in butanol production when added
after 4 h of fermentation. Wu et al.[37] also
reported an increase in butanol concentration of around 77% with zinc
supplementation, and attributed this increase to rapid acids reassimilation
to solvents. However, results obtained by zinc sulfate addition in
this study were not significantly higher than other trace elements
used (Figure C).Many researchers reported that the addition time of stimulators
and/or activators influences the solvent production. Ding et al.[38] added 2 g L–1 sodium sulfate
(electron receptor) after 24 h fermentation and reported 12.96 g L–1 butanol, which was 34.8% higher than in the control.
Furthermore, Nasser Al-Shorgani et al.[33] also showed the highest butanol concentration (18.05 g L–1) when benzyl viologen was incorporated after 4 h of fermentation.
Moreover, in order to enhance the butanol/acetone ratio, Li et al.[39] added neutral red at 60 h when the butanol production
rate was relatively higher.Therefore, it was concluded that
the addition of nickel chloride
and sodium selenite to the fermentation medium was of vital importance
which ultimately resulted in better solvent production. Hence, nickel
chloride and sodium selenite were critically investigated further
in order to study their effect on growth, pH, glucose consumption,
and total solvent production.
ABE Fermentation Profile
in the Presence of Nickel and Selenite
According to earlier
results, nickel chloride (100 mg L–1) and sodiumselenite (1 mg L–1) were individually
added to the fermentation medium at 8 h, and their effects were evaluated
by analyzing the samples at particular time intervals. The obtained
results were then compared with control experiment in order to figure
out the changes during fermentation operation.As can be seen
in Figure a, the
cell growth was comparatively increased in the presence of trace elements.
Supplementation of nickel and selenite resulted in higher biomass
formation at 72 h compared to that in the control, although its behavior
was quite aligned until 24 h. A lag period of ∼4 h was observed
(with or without trace element) wherein Clostridial cells adapted
themselves to growth conditions. Thereafter, a gradual increase in
cell density was recorded indicating exponential behavior of cells.
Trace element incorporation positively affected cell behavior without
being lethal to budding Clostridia. This outcome is in agreement with
Li et al.,[10] who found improved cell growth due to a large quantity of reduced
equivalents (NADH and NADPH) with the aid of a precursor (nicotinic
acid) in the fermentation medium.
Figure 4
ABE fermentation profile by C.
acetobutylicum NRRL
B-527: (a) Clostridial growth, (b) pH, (c) residual
sugar, (d) acetone, (e) butanol, (f) ethanol, (g) acetic acid, and
(h) butyric acid.
ABE fermentation profile by C.
acetobutylicum NRRL
B-527: (a) Clostridial growth, (b) pH, (c) residual
sugar, (d) acetone, (e) butanol, (f) ethanol, (g) acetic acid, and
(h) butyric acid.Furthermore, medium pH
plays a crucial role during ABE fermentation,
thus being responsible for shifting microbial acidogenic phase toward
solventogenesis. However, addition of trace elements during fermentation
did not severely affect the pH profile (Figure b). A classical pH trend was observed both
in the control and trace element supplemented experiments.The
sugar consumption profile was also studied to see the effect
of trace elements on sugar uptake and solvent production. Residual
glucose concentrations in the control and in selenite were nearly
similar (Figure c). However, a suitable amount of selenium in the fermentation medium
may elevate the content of essential elements and total amino acids
which in turn enhances bacterial growth followed by better solvent
production.[32] On the other hand, nickel
supplementation aided almost complete sugar utilization which is thought
to be because of the regulatory effect on sugar utilization and metabolism.
However, in-depth transcriptional analysis should be essential to
elucidate the detailed mechanism underlying complete utilization.
Xue et al.[8] explained that micronutrients
have a regulatory effect on sugar utilization and showed significant
improvement in butanol production and fructose utilization with the
addition of zinc in a culture medium.Solvent production profiles
were also studied with the addition
of trace elements in order to get detailed insight on its effectiveness
for biobutanol production (Figure d−f). The highest butanol and ABE as 10.08 ±
0.14 and 18.17 ± 0.19 g L–1, respectively,
were achieved by nickel supplementation (Figure e). Nickel supplementation improved biobutanol
production up to 68% higher than in the control (Figure e). Looking into Figure d,f, acetone and
ethanol production were started late (18–24 h) while butanol
production was initiated at 8 h (Figure e) in the control as well as in the trace
element supplemented medium. Nair and Papoutsakis[40] also demonstrated that butanol production gets initiated
in priority than acetone and ethanol when cells sense a hostile environment
(reduced pH), which is mainly due to the active role of aldehyde-alcohol
dehydrogenase (AAD).Acetic and butyric acid are main metabolic
precursors for solvent
formation. Figure g,h shows the acid formation profiles. A time course revealed that
the first acidogenic phase was supplemented at 36 h with a second
acidogenic phase with rapid reassimilation of acids into solvents
thereafter. This indicates acidogenesis and solventogenesis took place
twice during the entire fermentation process. The dual acidogenesis
in the current study is also supported by Pang et al.,[41] who carried out fed-batch fermentation for butanol
production using sugar cane baggase by Clostridium acetobutylicum GX01. They observed second acidogenesis after 40 h fermentation,
mainly due to rapid assimilation of produced acids into solvents during
early stages. Acetic acid levels were also comparatively elevated
during the current fermentation experiments with trace element addition,
thereby observed an increase in acetone concentration and thus unimproved
B:A ratio.Of interest, both solvent yield and productivity
were notably higher
with trace element addition suggesting their consequent effect on
aforesaid parameters. Certainly, selenite was found to be more effective
in enhancing solvent yield (0.33 g g-1) than nickel
(0.30 g g-1) with solvent productivities to be 0.12
g L–1 h–1 and 0.15 g L–1 h–1, respectively. Therefore, the synergistic
effect of selenite (1 mg L–1) and nickel (100 mg
L–1) was investigated by adding them after 8 h fermentation.
The resulting total solvents (16.78 ± 0.21 g L–1) were fairly less as compared to individual addition of nickel (data
not shown), thus proving the fact that higher metal ions in medium
could be detrimental to microorganisms.[32,42] Overall, nickel
was found to be potent cofactor which significantly improved the solvent
titer.The improved butanol concentration in the presence of
nickel was
attributed to BDH activity at particular instances viz. in acidogenic
and solventogenic phases. As expected, NADH-dependent BDH exhibited
reasonably higher activities of about 0.41–0.44 (acidogenic
phase) and 0.63–0.69 U mg–1 protein (solventogenic
phase) with trace element addition. Similarly, Li et al.[10] reported NADH-dependent BDH activity in the
range of 0.40–0.60 U mg–1 when nicotinic
acid was used as a precursor in culture medium. On the other hand,
Rajagopalan et al.[14] detected comparatively
lower BDH activity (0.03 U mg–1) in cell extract
of Clostridium sp. BOH3 after 24 h of fermentation.
Overall, the activity of NADH-dependent BDH was improved by 42% with
the addition of trace elements as compared to control. Hence, it was
thought desirable to characterize BDH by developing a three-dimensional
structure and subsequently molecular docking studies to elucidate
interactions involved.
Homology Modeling and Structural Assessment
The retrieved
target sequence of BDH enzyme from C. acetobutylicum ATCC 824 (accession no. AAA23206) comprises 389 amino acids. The
template of NADH-dependent BDH from Thermotoga maritima was identified using the BLASTp program which showed 41% identity
and 99% query coverage with target BDH sequence. In addition, sequence
alignment which was carried out using CLUSTALW also showed homology
between the target and template sequences with conserved regions (Figure S1).[25] A three-dimensional
structure of target BDH was constructed by homology modeling based
on the crystal structure of chain A of Thermotoga maritimaBDH (resolution = 1.78 Å, PDB: 1VLJ, chain A). The model was built with the
help of MODELLER 9.19 software. A total of 50 models were generated,
out of which the best model with the lowest DOPE score and highest
GA341 value was selected for further processing. Additionally, the
initial selected model was refined by 5000 steps of energy minimization
using the steepest descent with the help of UCSF Chimera to eliminate
nonbonded interactions.The final refined model was superimposed
with the template structure which showed a root-mean-square deviation
(RMSD) value of 0.265 Å and thus implies a close relationship
between these structures (Figure A). Usually, RMSD is calculated between C-alpha atoms
of matched residues in 3D superposition of the target and template.[22] The RMSD values indicate a closeness among superimposed
structures. The greater the RMSD value, the more distant the matched
structures.[19] Further, the Ramachandran
plot shows the relationship between phi and psi angles of a protein
which can be helpful for determining the role of the amino acid in
the secondary structure. It is derived through the PROCHECK online
server and depicted the backbone dihedral angle distributions of all
amino acid residues.[43] The Ramachandran
plot showed that 94.4% of residues were to be in the core region while
5% were in the allowed region and only 0.3% in the disallowed region,
thereby showing that the backbone dihedral angles of the model are
reasonably perfect (Figure B). Besides, ERRAT analyzes statistics of nonbonded interactions
between different atom types, and its score was found to be 96.54%
signifying the constructed structure is of good quality with high
resolution (Figure C). On the other hand, the ProSA web server compares the Z-score
of the predicted model with all protein chains present in protein
data bank which have already been determined experimentally through
X-ray diffraction and NMR techniques.[28] In present study, the Z-scores estimated by ProSA were −9.38
and −11.51 for target and template, respectively, which also
supported the quality of the model (Figure S2). All of these findings indicate that the 3D structure of BDH obtained
by homology modeling is acceptable and can be used for subsequent
docking studies.
Figure 5
(A) Overlay similarity between BDH (cyan) and template
1VLJ (magenta).
(B) Ramachandran plot of BDH model. (C) ERRAT analysis of refined
BDH model.
(A) Overlay similarity between BDH (cyan) and template
1VLJ (magenta).
(B) Ramachandran plot of BDH model. (C) ERRAT analysis of refined
BDH model.The validated model was further
used for the docking study to examine the interactions between ligand–receptor
bindings. Interestingly, the structure of BDH represents a typical
α/β fold particularly dominated by helical bundles that
are linked by unordered loops. Like other NADH/NADPH dependent dehydrogenases,
BDH features an extended β-sheet domain, which contains the
Rossmann fold[44,45] and is crucial for cofactor (NADH)
binding (Figure ).
A similar motif was reported by Sommer et al.[46] during characterization of ß-hydroxybutyryl CoA dehydrogenase.
Additionally, Sulzenbacher et al.[45] identified
the glycine-rich cofactor (NADH and/or NADPH) binding site in alcohol
dehydrogenase (ADH). However, such region was not found in NADH-docked
BDH from the current study which is in line with the report by Walter
et al.[47] Since, BDH is involved in conversion
of butyraldehyde to butanol,[47] their docking
was carried out using the PATCHDOCK server. Figure shows the binding pose of butyraldehyde
in BDH. The substrate is situated in front of the cofactor binding
domain, near to the catalytic site. Similar conformations have been
reported by other researchers.[46,48] The interactions of
butyraldehyde in active cleft are shown in the “substrate-inhibitor
pocket” callout (Figure ). Furthermore, the substrate docked structure exhibited proper
intermolecular hydrogen bonding, and possible interacting residues
are TYR276, TYR277, GLU272, and PHE385.
Figure 6
Structural overview with
substrate (blue = butyraldehyde), inhibitor
(red = acetic acid and yellow = hydroxymethylfurfural), cofactor (green
= NADH), and metal ion.
Structural overview with
substrate (blue = butyraldehyde), inhibitor
(red = acetic acid and yellow = hydroxymethylfurfural), cofactor (green
= NADH), and metal ion.Our previous studies reported that numerous inhibitors hamper
the
solvent production during ABE fermentation.[5,49] Hence,
it was decided to investigate the effect of few inhibitors on BDH
by incorporating in silico techniques. Two experimentally known inhibitors
namely acetic acid and hydroxymethyl furfural were docked with BDH
protein using the PATCHDOCK server. Surprisingly, these inhibitors
were found to have similar binding domain as like substrate (butyraldehyde)
with consistent interacting residues (Figure ). This resemblance may result in competitive
inhibition which in turn affects BDH activity resulting in lowered
solvent titer.BDH is a metalloenzyme and thus requires a metal
ion for its effective
activity. Figure callout
“catalytic triad” revealed that three histidine residues
along with aspartate formed a perfect metal binding groove, and residues
involved are conserved with template BDH protein for ferrous ion,
depicted by sequence alignment (Figure S1). This perfect metal binding groove formed is mainly due to the
hydrophobic nature of BDH which is evaluated through amino acid composition
and hydrophobicity profile (Figure S3).
Furthermore, an analogous metal binding groove within modeled BDH
is expected to form when nickel is present in culture medium. Hence,
all together (BDH + cofactor + metal ion) drives the reduction of
butyraldehyde, and proper possible interactions confirmed the major
role of BDH in enhancement of butanol concentration with trace element
incorporation. Schwarzenbacher et al.[44] demonstrated the same interacting residues in catalytic cleft with
square pyramidal coordination for iron in 1,3-propanediol dehydrogenase
(TM0920) from Thermotoga maritima.
Conclusions
The purpose of the present research was to improve butanol concentration
in order to make it a future alternate liquid biofuel. Hence, supplementation
of cofactors in the fermentation medium would be considered as a potential
approach to increase solvent titers in C. acetobutylicumNRRL B-527. The addition of trace elements viz. nickel chloride,
and sodium selenite have led to significant improvement in butanol
concentrations which is thought to be due to redirection of metabolic
flux toward more reduced products. This study also showed the remarkable
impact of varying the addition time on solvent production (10–20%
increment in solvent titer). Furthermore, fermentation profiling revealed
that the solvent production was positively triggered as soon as cells
entered into the stationary phase and achieved maximum butanol concentration
of 8–10 g L–1 which is higher than that of
the control. Additionally, the 3D structure of the crucial BDH enzyme
was also developed. The subsequent molecular docking experiments helped
to understand the possible substrate–inhibitor interactions
in the BDH protein.
Authors: Rishikesh S Parulekar; Sagar H Barage; Chidambar B Jalkute; Maruti J Dhanavade; Prayagraj M Fandilolu; Kailas D Sonawane Journal: Protein J Date: 2013-08 Impact factor: 2.371
Authors: Manisha A Khedkar; Pranhita R Nimbalkar; Shashank G Gaikwad; Prakash V Chavan; Sandip B Bankar Journal: Bioresour Technol Date: 2016-11-18 Impact factor: 9.642
Authors: Manisha A Khedkar; Pranhita R Nimbalkar; Prakash V Chavan; Yogesh J Chendake; Sandip B Bankar Journal: Bioprocess Biosyst Eng Date: 2017-07-03 Impact factor: 3.210