Geobacillus thermoleovorans MTCC 13131: An Amide-Hydrolyzing Thermophilic Bacterium Isolated from a Hot Spring of Manikaran

Abstract

Geobacillus thermoleovorans MTCC 13131, an amide hydrolyzing bacteria was isolated from a hot spring in Himachal Pradesh and identified through 16S rRNA gene sequence analysis. The amidase derived from this bacterium exhibited hydrolyzing catalytic ability against aliphatic and aromatic amides. The isolate was characterized for morphological and biochemical properties. Further, the production of amidase enzyme from this isolate was evaluated using approach of one-variable-at-a-time and response surface method. The Response Surface Methodology based study indicated the importance of nitrogen sources and growth period for amidase production. Optimal production was achieved at a temperature 55 °C, and production pH 7.5 in the production medium comprising diammonium hydrogen phosphate (0.4%), peptone (0.45%) and yeast extract (0.3%). The wide substrate affinity of the strain suggests its potential role in biotransformation of amides to corresponding acids of industrial significance along with its strong capacity to degrade the toxic amide in polluted environmental samples.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12088-022-01042-9.

Introduction

The Indian Himalayan regions are valuable ecosystems for providing microbial communities both from hot and cold springs. Hot springs have microbial diversity which has the potential to tolerate extreme environments and has been reported to be used in various diverse fields like agriculture, medical, and industrial processes. The hot spring of Manikaran has always remained a site of attraction for exploring the microbial diversity Rhodococcus pyridinivorans NIT-36 [1], Geobacillus subterraneus RL-2a [2], and Geobacillus pallidus BTP-5 × MTCC 9225 [3] with extreme stability. Biocatalytic processes to bio-transform and produce nitrile and amides-based products of industrial significance are equipped with techno-economic advantageous over chemical methods along with sustainable nature [4]. Among nitrile metabolizing enzymes, amidase (EC 3.5.1.4) hydrolyze non-peptide amide bonds (–CO–NH–) to corresponding carboxylic acids. In addition to hydrolysing catalytic potential, the enzyme also exhibits acyl transferase activity in presence of hydroxylamine as a co-substrate to produce hydroxamic acids of high therapeutic significance [5, 6]. Dual activity, stereo-selective characteristics and optically pure amide synthesis are the factors for its extensive involvement in research [7, 8]. Its wide commercial applications are in chemical synthesis of carboxylic acids, pharmaceutical drugs, agriculture and bioremediation [7].

Enzymes are widely distributed in microorganisms, plants, and animals; however, microorganisms as biocatalyst or a source of enzymes are preferred due to ease of production and other benefits for broad industrial, and environmental applications [6, 9, 10]. A few among reported microbial sources and amide biotransformation are nicotinic acid by Microbacterium imperiale [11], isonicotinic acid by Geobacillus subterraneus RL-2a [2], acetohydroxamic acid by Bacillus sp. APB-6 [12] and Geobacillus pallidus BTP-5 × MTCC9225 [3], benzohydroxamic acid by Alcaligenes sp. MTCC 10674 [13], vorinostat by Bacillus smithi IIMB2907 [14] etc. Amidases have also been reported from diverse conditions of temperature and pH along with varied substrate specificities against aliphatic, aromatic, heterocyclic, and α-amino acids amides [7, 15]. Bacterial sourced thermoactive amidases have been reported from G. pallidus BTP-5 × MTCC 9225 [16], G. subterraneus RL-2a [17], Pyrococcus yayanosii CH1 [18], and Burkholderia phytofirmans ZJB-15079[19].

In order to measure the interactions between the studied variables, an experimental fractional factorial experimental designs using Response Surface Methodology (RSM) method have been employed in the optimization. RSM is an statistical tool to optimise different experimental procedures for achieving maximum output using combinations of individual factors in study. In comparison to the traditional one-factor-at-a-time strategy, the fractional factorial experimental design, such as RSM, reduces the number of experimental tests and saves time. It aids in the creation of models for simple optimization studies and the evaluation of the effects of various factors with fewer experiments [20–22]. Versatile nature of enzymes with tolerance to extreme conditions, wide substrate specificity and enantioselectivity are among the factors for being industrially important [7, 23, 24]. Hence, the current study was aimed and report isolation, characterization, and phylogenetic relationship of a thermostable amide-hydrolysing bacterium from extreme conditions of temperature. Enzyme production was achieved using response surface methodology and substrate specificity were evaluated. Furthermore, the potential of G. thermoleovorans MTCC13131 was explored for substrate specificity.

Materials and Methods

Chemicals

Amides were procured from Bio-Rad (USA) and Sigma-Aldrich (USA). All other chemicals and medium components were of AR grade and procured from Merck (USA) and Hi-Media Chemicals Ltd. (India).

Isolation of Amide-Hydrolyzing Bacterium

Water samples were collected from the lakeside distributed hot springs of Manikaran, Himachal Pradesh, approximately 1 m from the shore and at 0.5 m depth. Soil samples were collected at a depth of ~ 5 cm from the surface. Isolation was performed using nutrient agar at 50 °C. Different bacterial colonies were selected based on morphological appearance and sub-cultured. Each isolate was screened using a sterilized basal medium supplemented with 20 mM of either acetamide or acrylamide in 250 ml Erlenmeyer flask at 55 °C and 250 rpm for 24 h. Grown bacterial strains in the presence of amides were repeatedly sub-cultured, and pure colonies were analyzed for amide-hydrolyzing catalytic potential. The pure cultures were cryopreserved using 25% glycerol stock at -80 °C until further characterization.

Enzyme Assay

The amidase assay for hydrolytic activity was performed as mentioned previously [21] in a two millilitre reaction mixture containing acrylamide, potassium phosphate buffer (0.1 M, pH 7.0), and resting cells at 70 °C for 15 min in a water bath shaker (700 rpm; Thermomixer Eppendorf Compact). Two millilitre of 0.1 N HCl was added to stop the reaction. The ammonia estimation was performed calorimetrically [25].

Identification of the Bacterium

Polymerase chain reaction (PCR) amplifications were performed on bacterial cell lysates to identify the strain.

Bacterial 16S rRNA gene universal forward 27F (5′-AGAGTTTGATCCTGGCTCAG-3′) and reverse 1492R (5′-ACGGCTACCTTGTTACGACTT-3′) primers were utilized to amplify 16S rRNA gene fragment of the isolate [26]. Amplicon sequences were determined by the Sanger sequencing method. Evolutionary analyses were conducted in MEGAX and the Maximum Likelihood method was applied for evolutionary history.

Morphological, Biochemical, and Growth Characteristics

The bacterial strain grown on a nutrient agar plate for 20 h was analysed for the phenotypic characterization, color, and margin. Compound light and scanning electron microscopies were performed to determine the cell’s shape and the biochemical characterization of the isolate was performed appropriately. The effect of temperature, and pH for the enzyme production, growth curve of the strain and substrate specificity were evaluated accordingly.

Experimental Design

The amidase production optimal conditions were investigated using the response surface method. A set of experimental conditions was determined by a CCD (Table S1). Five variables that influenced catalytic amidase production, namely di-ammonium-hydrogen phosphate, peptone, yeast extract concentration, time, and, pH were varied based on primary experimental results. Predicted responses were analyzed using RSM with the Design Expert Software (version 13). The experiment was designed as 32 runs with 6 central and 26 axial points. 1-run was performed using an un-optimized medium. Each experiment was run in triplicate, and the average of the experiments was used for final evaluation.

Results and Discussion

Isolation, Molecular Characterization and Phylogenetic Analyses of Amide-Hydrolyzing Bacterium

The single bacterial colonies with amide-hydrolyzing ability were isolated from water and soil samples. Among isolates, ten potential bacteria were found positive for the activity, and the isolate with the highest amidase catalytic efficiency was selected for further experimental studies.

The 16S rRNA gene analysis was performed to identify and assess the phylogeny. Analysis indicated that isolated amide-hydrolyzing bacterium MTCC 13131 was a member of the genus Geobacillus (Fig. S1) with high sequence similarity to G. thermoleovorans KCTC 3570(T) (99.93%), G. kaustophilus NBRC 102445(T) (99.86%), G. zalihae T1(T) (99.79%), G. vulcani 3S-1(T) (99.72%), G. proteiniphilus 1017(T) (99.37%), G. thermocatenulatus KCTC 3921(T) (99.02%), G. lituanicus N-3(T) (98.95%) G. stearothermophilus NBRC 12550(T) (98.88%) and G. subterraneus spp. Aromaticivorans Ge1(T) (98.74%). 16S rRNA sequence data are accessible in DDBJ/EMBL/GenBank databases under the accession number OK314859. Bacillus is an industrially important microbe with a broad biotechnological application, including enzymes and biomolecules [27, 28].

Morphological, Biochemical, and Growth Characteristics

Phenotypic strain characterization was performed on bacterial colonies grown on the nutrient agar plate. It showed circular, convex, irregular, cream-colored opaque, and rough surface morphology (Fig. 1a). Long rod-shaped bacteria were observed using light microscopy at 100X magnification (Fig. 1b) and the same result was confirmed through scanning electron microscopy (Fig. 1c). The strain exhibited negative results for Voges Proskauer, indole, methyl red, and citrate agar tests whereas, oxidase, and catalase tests were positive (Table S2). The bacterial cells were gram-positive and had subterminal and terminal endospores.

Fig. 1.

Morphological observation of the strain Geobacillus thermoleovorans MTCC 13131 (a) cells on the nutrient agar plate: colonies were cream-colored, opaque, and a transparent colloidal substance at the edge of the strain, (b) Compound microscopy at 100 × magnification: rod-shaped, (c) Scanning electron microscope: rod shaped

Maximum amidase production was achieved in the culture medium containing di-ammonium hydrogen phosphate (4 g/L), peptone (4.5 g/L), yeast extract (3 g/L), pH 7.5 grown for 20 h at 55 °C, and 250 rpm (Fig. 2). Maximum growth of the strain was observed at 22 h in the production medium of pH 7.5 at 55 °C, 250 rpm, and further increasing cultivation period resulted in decreased growth (Fig. S2). Likewise, optimal amidase activity was observed at 20 h of incubation, and a decline was estimated further.

Fig. 2.

Growth characteristics. a Effect of production pH: growth occurs at pH ranging from 6 to 9 (optimum 7.5); b Effect of production temperature: growth analysis at a temperature ranging from 40 to 60 °C (optimum 55 °C)

A total of five independent factor RSM using di-ammonium-hydrogen phosphate, peptone, yeast extract concentration, time, and, pH was carried out and results of central composite design (CCD) experiments i.e., mean predicted and observed responses are shown in Table 1.

Table 1.

Amidase production using various experimental conditions (varying nitrogen sources concentration, pH, and time) determined by RSM using CCD approach

Std	Run	Factor 1	Factor 2	Factor 3	Factor 4	Factor 5	Response 1	Response 2
		A: Di-ammonium hydrogen phosphate (gm)	B: Peptone (gm)	C: Yeast Extract (gm)	D: Growth Time (h)	E: Media pH	Actual enzyme activity	Predicted enzyme activity
		(X1)	(X2)	(X3)	(X4)	(X5)	(U/g dcm)	(U/g dcm)
28	1	0.2	0.225	0.15	20	7.5	779.46	695.53
19	2	0.2	0.075	0.15	20	7.5	782.78	817.05
32	3	0.2	0.225	0.15	20	7.5	909.792	695.53
21	4	0.2	0.225	0.05	20	7.5	384.62	400.28
20	5	0.2	0.375	0.15	20	7.5	778.00	786.02
3	6	0.1	0.3	0.1	16	6	627.04	618.60
5	7	0.1	0.15	0.2	16	6	561.50	543.76
18	8	0.4	0.225	0.15	20	7.5	829.98	818.83
27	9	0.2	0.225	0.15	20	7.5	816.22	695.53
11	10	0.1	0.3	0.1	24	9	502.78	483.24
25	11	0.2	0.225	0.15	20	4.5	440.06	469.12
15	12	0.1	0.3	0.2	24	6	431.34	405.10
6	13	0.3	0.15	0.2	16	9	730.56	732.92
7	14	0.1	0.3	0.2	16	9	442.59	435.36
17	15	0	0.225	0.15	20	7.5	821.14	874.57
12	16	0.3	0.3	0.1	24	6	782.78	775.43
4	17	0.3	0.3	0.1	16	9	143.07	154.73
14	18	0.3	0.15	0.2	24	6	806.24	789.59
2	19	0.3	0.15	0.1	16	6	146.53	147.67
31	20	0.2	0.225	0.15	20	7.5	425.30	695.53
9	21	0.1	0.15	0.1	24	6	857.84	827.78
30	22	0.2	0.225	0.15	20	7.5	505.65	695.53
1	23	0.1	0.15	0.1	16	9	164.67	153.62
16	24	0.3	0.3	0.2	24	9	297.09	290.95
29	25	0.2	0.225	0.15	20	7.5	779.04	695.53
13	26	0.1	0.15	0.2	24	9	648.42	619.57
8	27	0.3	0.3	0.2	16	6	745.12	750.08
10	28	0.3	0.15	0.1	24	9	232.64	222.69
26	29	0.2	0.225	0.15	20	10.5	14.66	27.89
23	30	0.2	0.225	0.15	12	7.5	137.60	128.63
22	31	0.2	0.225	0.25	20	7.5	669.54	696.17
24	32	0.2	0.225	0.15	28	7.5	296.78	348.04
	33	0.3	0.1	0.1	24	7.5	0.232704

The relationship between obtained enzyme activity as dependent variable in each experimental condition was established by a second order polynomial equation (Eq. 1) that includes linear, quadratic, and interaction term correspond to CCD.

$$\begin{array}{cc}\hfill \text{Y}=& 0.8089-0.0098\left({\text{X}}_1\right)-0.0036\left({\text{X}}_2\right)+0.0698\left({\text{X}}_3\right)\hfill \\ \hfill & +0.0590\left({\text{X}}_4\right)-0.1095\left({\text{X}}_5\right)+0.0119{\left({\text{X}}_1\right)}^2\hfill \\ \hfill & +0.0006{\left({\text{X}}_2\right)}^2-0.0627{\left({\text{X}}_3\right)}^2-0.1402{\left({\text{X}}_4\right)}^2\hfill \\ \hfill & & \hfill -0.1327{\left({\text{X}}_5\right)}^2+0.0113\left({\text{X}}_1{\text{X}}_2\right)+0.0902\left({\text{X}}_1{\text{X}}_3\right)\\ \hfill & -0.0244\left({\text{X}}_1{\text{X}}_4\right)-0.0286\left({\text{X}}_1{\text{X}}_5\right)-0.0865\left({\text{X}}_2{\text{X}}_3\right)\hfill \\ \hfill & -0.0616\left({\text{X}}_2{\text{X}}_4\right)-0.0441\left({\text{X}}_2{\text{X}}_5\right)-0.0932\left({\text{X}}_3{\text{X}}_4\right)\hfill \\ \hfill & +0.0653\left({\text{X}}_3{\text{X}}_5\right)-0.0436\left({\text{X}}_4{\text{X}}_5\right)\hfill \\ \hfill \end{array}$$ 1

Y = Amidase activity (U/g dcm) as dependent variable. The independent variables were X₁ = Di-ammonium hydrogen phosphate (DAHP) (gm), X₂ = Peptone (gm), X₃ = Yeast extract (gm), X₄ = Time, X₅ = pH. The regression coefficient: 0.8089 is a constant coefficient; − 0.0098, − 0.0036, 0.0698, 0.0590, and − 0.1095 are the linear coefficients; 0.0113, 0.0902, − 0.0244, − 0.0286, − 0.0865, − 0.0616, − 0.0441, − 0.0932, 0.0653, and − 0.0436 are the interaction coefficient; 0.0119, 0.0006, − 0.0627, − 0.1402, and − 0.1327 are the quadratic coefficients between variable X₁, X₂, X₃, X₄, and X₅.

The correlation significance of each independent factor was observed based on probability (p) values (Table S3), where, among the five tested factors, yeast extract and growth time had the maximum effect on amidase production as they showed maximum linear coded coefficient and their p-value was < 0.05. The negative square coefficient found for nitrogen sources, time, and pH indicated that these independent variables were already in its optimum range. In term of interaction between the five tested independent variables, the factors which showed p-values of > 0.05 indicated that there was no significant interaction between those independent variables for amidase production. In this software design C, D, E, AC, BC, BD, BE, CD, CE, DE, C², D², and E² were significant model terms.

The quadratic model was validated using analysis of variance (ANOVA). This model resulted highest amidase activity using di-ammonium hydrogen phosphate (4 gm), peptone (4.5gm), and yeast extract (3 gm) as nitrogen sources, medium pH 7.5, and growth interval of 20 h. The experiment resulted in amidase activity of 909 U/g dcm in average whereas the predicted enzyme activity was 695 U/g dcm with correlation coefficient (R²) and p-values of 98.55% and < 0.0001 respectively. The correlation coefficient value of 98.55% implies the sample variation for amidase production i.e., the model explained more than 98.55% of the variability in response and only 1.45% of the total variation was not explained by the model. The experimental values agreed with the model predicted value, indicating the model's strength. Further, signal to noise ratio of 18.557 indicates an adequate signal as the value of more than 4 is desirable for signal to noise ratio and thus model is fit and can be used to navigate the design space. In the model, the F-value indicated the ratio of mean squares of regression to error and indicates the influence of each controlled factor on tested model, where F-value of 37.42 implies that the model is significant. There is only 0.01% possibility that this large F-value could occur due to noise (Table S4). The lack of Fit F-value of 1.49 implies that the lack of fit is insignificant relative to the pure error. There is a 33.84% chance that a lack of fit F-value this large could occur due to noise.

The Pareto plot obtained in CCD showed a more satisfactory correlation between the experimental and predicted values, wherein more points clustered on and around the diagonal line validate the goodness of model fit (Fig. S3a). The perturbation plot illustrates the validation of the model, and effect of all factors at the center point in the design space (Fig. S3b). It showed optimum value for the variables DAHP 4 gm, peptone 4.5 gm, yeast extract 3 gm, growth time 20 h, and media pH 7.5 per liter of production medium. Perturbation plot shows that yeast extract had crucial role in enzyme production followed by growth time, peptone, di-ammonium hydrogen phosphate, and media pH. Previously, RSM-based studies using Delftia tsuruhatensis ZJB-05174 [29] and Rhodococcus erythropolis MTCC 1526 [23] reported maximum enzyme production of 528.21 U/I and 1086.57 U/g dcw, respectively, where 11.59 g/L and 4 g/L of yeast extract were used for maximum amidase production. Both strains mentioned above were not thermostable. The strain used in our study, on the other hand, is thermophile and produces highly thermostable amidase. The model was experimentally validated by performing it under optimum conditions which resulted in 909 U/g dcm activity and proved the validity of the statistical model. Approximately 4 folds increase in the amidase activity was recorded after RSM based optimization.

The impact of the three separate sets of factor interactions (AC, CD, and CE) on enzyme production is depicted in Fig. 3. These response graphs were produced by changing any two independent variables at a time and keeping other independent factors as constant. Figure 3a, b showed the interaction between concentrations of yeast extract and DAHP, where increasing the concentration of both elements up to a certain limit increased the enzyme production but no further increase in enzyme production was noticed even after increasing the concentration of either factor. This may be due to the presence of inorganic source (DAHP) in the media which generally repress the cell mass production, whereas the organic source (yeast extract) helped in increasing amidase production. Growth time and yeast extract combination also determined a crucial role in producing amidase (Fig. 3c, d). Likewise, the effect of yeast extract and media pH also influenced enzyme production, as shown in Fig. 3e, f. An increase in either media pH or growth time resulted in decrease of enzyme production which may be due to the production of some secondary metabolites in the media due to high pH and longer growth duration of the culture, and may be these metabolites are inhibiting the amidase production by the G. thermoleovorans MTCC 13131. Interactions among the factors with all possible combinations, visualize the relationship between the response and experimental level for maximum amidase production. Prabha and Nigam reported increased acrylamidase production from thermostable Bacillus tequilensis, with maximal strain growth and enzyme activity at 45 °C and 50 °C [30]. In this investigation, the RSM-based strategy enhanced amidase production by roughly four times (Run 3) compared to the unoptimized media (Run 33) (Fig. 4).

Fig. 3.

RSM-based, 3D-surface and Contour-plot showing the effect of independent variables: a and b Yeast-Peptone concentration; c and d Growth time and media pH; e and f DAHP-Growth time, effect on the amidase activity by Geobacillus thermoleovorans MTCC 13131

Fig. 4.

RSM-based amidase activity optimization of the Geobacillus thermoleovorans MTCC13131

Similar studies based on RSM approach to produce amidase using organic nitrogen sources previously, however indicated temperature tolerance varied from moderate to high. Vaidya et al. [23] achieved amidase activity of 1.1 U/mg dcw through same approach reported but the microbial source of amidase was mesophilic strain. Mehta et al. [21] has reported the maximum amidase production (0.62 U/mg dcw) from a thermophilic strain Geobacillus subterraneus RL-2a. Compared to these studies based on methodology, high amidase production was achieved under thermophilic condition using the reported new isolate in this study. The strain exhibited amide-hydrolysing activity against aliphatic and aromatic substrates (Table 2). Higher amide specificity was recorded for acrylamide and benzamide, which can be further studied to perform biotransformation at pilot-scale to produce corresponding acids.

Table 2.

Substrate specificity

Amides (100 mM)	Structure of amide	Amidase activity (%)
Acetamide		100 ± 2.9
Acrylamide		173 ± 5.3
Benzamide		126 ± 3.3
Butyramide		75.3 ± 3.0
Isonicotinamide		78.6 ± 3.0

Conclusion

The amidase-producing thermophilic bacterial strain was isolated from a hot spring of Manikaran, India. It showed the catalytic ability against aliphatic and aromatic amides and thereby can catalyze amides biotransformation to produce corresponding carboxylic acids of industrial significance. Geobacillus thermoleovorans MTCC 13131 is a facultative anaerobe and thermostable. The cells grown for 20 h at 50 °C in nutrient agar were long-rod shaped and positive for gram-staining. Based on one-variable-at-a-time and response surface methodology approaches, the strain showed growth in the varied range of temperature (optimum 55 °C), pH (optimum 7.5), and time (optimum 20 h). RSM-based study indicated the crucial role of the nitrogen sources (mainly yeast extract), and cultivation time for amidase production. The amidase production by the bacterium G. thermoleovorans MTCC13131 with higher temperature tolerance and with wide substrate specificity can be further used for pilot scale production of acrylic acid and benzoic acid in an environment-friendly manner.

Supplementary Information

Below is the link to the electronic supplementary material.

Declarations

Conflict of interest

The authors declare no conflict of interest.