α-Amylases: An Overview on Molecular Structure and Biotechnological Perspectives

Introduction

Alpha-amylase (EC 3.2.1.1, a-l,4-glucan-4-glucanohydrolase) randomly cleaves a-1,4 glycosidic bonds of starch, amylose, amylopectin and related polysaccharides in endo-attacking fashion and produces oligosaccharides in an a-anomeric configuration (Kubrak et al. 2010). Amylases are commonly distributed in the animals, plant and microbial kingdoms. Among the microbes, several species of genus Bacillus and Aspergillus are the good sources of industrially important amylases. Sivaramakrishnan et al. (2006) reported that the world’s production of a-amylases from B. licheniformis and Aspergillus sp. was about 300 tons. The conventional method of submerged fermentation technique is commonly used for production of amylase from bacteria. However, low cost agro-products are used to produce extracellular fungal amylase through solid state fermentation process.

In modern biotechnological era, microbial amylolytic enzymes completely replace the chemical hydrolysis of starch in industrial sectors; thus, its demand is increasing day by day. The area of applications of amylases has been expanded from clinical system to waste management. Approximate market share of amylase is about 25% in the world’s enzyme market (Rajagopalan and Krishnan 2008). The global industrial enzymes market has grown exponentially from the last decade and this trend is projected to continue. According to the global industrial enzymes market report, the estimated value of industrial enzymes was about US$4.61 billion in 2016, is projected to grow at a CAGR (compound annual growth rate) of 5.8% from 2017, and reach up to US$6.3 billion in 2022 (https://www.marketsandmarkets.com/Market- Reports/industrial-enzymes-market-237327836). The production of commercially useful enzymes has grown enormously in the last few decades. Several leading multinational companies are involved in the production of commercial enzymes. Among them, Novozymes (Denmark), DuPont Danisco (USA), AB enzymes (Germany), Dyadic (USA), BASF (Germany), DSM (Netherlands), etc. cover more than 70% of the total enzyme market.

History of Amylase

Amylase was recognized as biocatalysts in history of enzyme chemistry. The history of amylases was started in 1811 when Russian chemist Kirchhoff first discovered starch degrading enzyme in wheat. In 1833, the major breakthrough came when French chemists Anselme Payen and Jean-Francois Persoz isolated an enzyme complex from germinating barley which can convert gelatinized starch into sugars, primarily into maltose, and was termed “diastase”. Japanese scientist Jokichi Takamine had isolated fungal a-amylase from the surface culture of Aspergillus oryzae on wheat bran in 1894. The product was named “Takadiastase” and it is still used as a digestive aid.

In 1917, French scientists Boidin and Effront had isolated bacterial a-amylase from Bacillus subtilis, which was used for desizing (Singh et al. 2011). They also pioneered of alpha amylase production on a commercial scale by using submerged fermentation.

Family of Amylases and Their Classification

Carbohydrates are ubiquitously present in all living organisms and all the carbohydrate-splitting enzymes belong to a different glycosyl hydrolases family (GH family). Basically, there are 156 glycosyl hydrolases families (GH1-GH156) with 18 clans (A-R). According to the carbohydrate-active enzymes database (CAZy), starch-degrading enzymes are found in GH families 3, 13, 14, 15, 31, 57, 119 and 126. The a-amylase (O-glycosyl hydrolases) family is the largest family, comprising more than 30 different enzymes. The main enzyme a-amylase (EC 3.2.1.1) primarily belongs to glycosyl hydrolases family 13 (GH-13 family); the other two types of amylases (3 and у belong to GH-14 and GH-15 family respectively. The common features of GH13 family are: (i) they act on a-glycosidic bonds and hydrolyse this bond to produce a-anomeric mono- or oligosaccharides, form a-1-4 or 1-6 glycosidic linkages (transglycosylation), or a combination of both activities; (ii) they possess a (a/p)a or TIM-barrel structure containing the catalytic site residues; (iii) they have four highly conserved regions in their primary sequence and the amino acids of these regions form the catalytic site and stabilize the TIM-barrel topology; (iv) Asp, Glu and Asp residues are responsible for catalysis. Generally, amylases are divided into three major groups: a-amylases (EC 3.2.1.1), (3-amylase (EC 3.2.1.2) and y-amylase (EC 3.2.1.3). The detail classification of microbial amylolytic enzymes has been represented in Table 2.1.

Production and Purification of Amylase

Several biotech companies produce varieties of useful enzymes for green technology. Microbes are the major source of extracellular enzymes, particularly a-amylase (Table 2.2). Production of amylase by using microbes is advantageous due to bulk production capacity, less expensive and manipulation facilities to obtain desired characteristics of the enzymes (Gupta et al. 2003). Production of a-amylase has been carried out in both solid state fermentation (SSF) and submerged fermentation (SmF) (Table 2.2). Several physicochemical parameters including nutrient supplementation (carbon, nitrogen and phosphate), pH of the medium, degree of aeration and regulation of temperature are being considered for optimum microbial growth and enzyme production.

Generally, SmF is done in liquid medium where the microorganisms are able to grow freely in presence of high content of free water. It is more applicable for production of a-amylase from bacterial species, mostly from genus Bacillus. Synthetic media containing nitrogen sources, soluble starch, as well as other components is used in this purpose, which increase the production cost; but, it has some positive features like easy handling and greater control of process optimization factors like temperature, pH, aeration, etc. Currently, SSF has gained more interest among the researchers and industries for the production of enzyme in view of its several economic and

Different Types of Amylases, Their Mode of Action and Reaction Products from Starch and Related Polymers

Types of Amylases

Common Name

E.C. No.

Mode of Action

Reaction

Substrate

Main Products

a-Amylase Family

Endo and exoamylases

a- amylase

3.2.1.1

Endo-acting; randomly hydrolyses a-1.4 glucosidic linkages

Starch and related polysaccharides

Several maltooligomcrs, branched dextrins, maltose. Products are in alpha-configuration and reducing sugar

«-glucosidasc

3.2.1.20

Exo-acting; hydrolyses terminal a-1,4 bond from non-reducing end

Starch

Single glucose molecule in alpha-configuration

Maltogenic-amylase

3.2.1.133

Exo-acting; cleaves a-1,4 linkages in the substrates containing only two glucose units at the non-reducing end

Starch

Maltose

Maltotetraose forming amylase

3.2.1.60

Exo-acting; hydrolyses starch from its non-reducing end

Starch

Maltotetraose.

Maltohexaose forming amylase

3.2.1.98

Exo-acting; attacks definite a-1,4 glucosidic linkages from non-reducing end

Starch

Maltohexaose.

Debranching

enzymes

Isoamylase

3.2.1.68

De branching, endo-acting; cleaves a-1,6 glucosidic linkages

Amylopectin and (3-limit dextrins

Certain maltooligomers.

Pullulanasc

3.2.1.41

Endo-acting; attacks a-1.6 glucosidic linkages

Pullulan, (3-limit dextrins and starch

Maltotriosc, maltose and amylosc

Transferases

Cyclodcxtrin glycosyl transferase

2.4.1.19

Transferase; forms a-1.4 glucosidic linkages. It can catalyse different reactions; cyclization, coupling and hydrolysis

Starch

Cyclodcxtrins and few maltooligomcrs

Branching enzyme

2.4.1.18

Transferase; forms a-1,6 glucosidic linkages.

It transfers a segment of a-1,4 D-glucan chain to the similar glucan chain

Starch

Branched oligosaccharides

f)-Amylase Family

p- Amylase

[3-amylase

3.2.1.2

Exo-acting; cleaves a-1-4 glucosidic bond from the non-reducing ends

Starch

Maltose and [3-limit dextrin

y-Amylase

Glucoamylase

3.2.1.3

Exo-acting; hydrolyses terminal «-1-4 glucosidic linkages from non-reducing end

Starch

Beta-D-glucose

Physicochemical Characteristics and Microbial Sources of a-Amylase

Source

Molecular

Weight

(kl))

Optimum

pH

Optimum

Temperature

(°C)

Fermentation

Enzyme Production

Substrate

References

Fungal

Aspergillus oryzae IFO 30103

66

5.0

50

SSF

11296 U/gds

Spent-brewing

grains

Patel et al. (2005)

Aspergillus niger, JGI24

43

9.5

30

SSF SmF

SSF: 74.0 U/mL SmF: 58.06 U/mL

SSF: Wheat bran SmF: Wheat bran

Varalakshmi et al. (2009)

Aspergillus terreus NCFT4269.10

15.3

5.0

60

SSF

SSF: 19.19 ± 0.9 U/g

Pearl millet

Sethi et al. (2016)

Penicillium cilrinwn HBF62

65

5.5

55

SmF

190.0 U/mL

Potato starch

Metin et al. (2010)

PenicilliumjamhineUum NCIM

42.7

5.0

50

SSF

-

Wheat bran

Sindhu et al. (2011)

Bacterial

Bacillus subtilis ITBCCB148

67

6.0

60

SmF

-

Amylum

Yandri et al. (2010)

Bacillus amyloliquefaciens P-001

6.5

60

SmF

35.0 U/mL

Starch

Deb etal. (2013)

Bacillus amyloliquifaciens

42

7.0

70

SmF

210 U/mL

Starch

Kikani and Singh (2011)

Bacillus methylotrophicus PI 1-2

44

7.0

70

SmF

144 U/mL

Starch

Xie et al. (2014)

B. licheniformis AI20

55

6-7.5

60-80

SmF

384 U/mL/min

Starch

Abdel-Fattah etal. (2013)

B. licheniformis

100

7.5

90

SmF

-

Cassava starch

Adeyanju et al. (2007)

Geobacillus sp. IIPTN

97

5.0

80

SmF

135 U/mL

Soybean meal, Starch

Dheeran et al. (2010)

Bacillus megaterium VUMB109

150

7.75

93

SmF

20.0 U/mL

Starch

Jana et al. (2013)

engineering advantages. This process is convenient as the microbial fermentation has been carried out in an environment that contains no or very little amount of water. SSF is the best choice for production of extracellular enzymes at an industrial scale from fungal sources, especially from filamentous fungi and yeast as they are able to grow in a low water activity. Filamentous fungi have the capacity to penetrate into the solid agro-industrial substrates by generating the turgor pressure at the tip of the mycelium (Sivaramakrishnan et al. 2006).

Several factors like surface area, porosity, moisture content, particle size and nutrient supplementation are considered during process optimization (Singhania et al. 2009; Farinas 2015). SSF is the more useful technique in terms of production cost because the moist agricultural polymeric substrates such as wheat bran, rice bran, rice husk, cassava, sunflower meal, cottonseed meal, soybean meal, pearl millet, etc. are used in this purpose (Rahardjo et al. 2005; Soccol et al. 2017). Applications of agro-wastes increase the possibility of waste recycling and lower the rate of pollution as the agro-wastes are mostly destroyed by burning. In spite of these, there are many other advantages in SSF such as simplicity of the technique, low capital investment, high production rate, lower levels of catabolite repression and end product inhibition, low waste water output, better product recovery, low purification cost and high quality product extraction (Soccol et al. 2017).

The conventional method of process optimization has been done by altering one variable at a time (OVAT), in which various independent factors and their levels are separately optimized. Recently, response surface methodology (RSM) has been applied to simplify the task of optimization of the culture medium for enhanced production of enzyme in industrial fermenters. This process helps to identify the significant influencing factors responsible to increase a-amylase yield in reactors (Wei et al. 2011). RSM is operated by design of experiments (DOE). The objective of DOE is the selection of the points where the response should be evaluated. In microbiological study, this technique is used for process optimization, which can assess the individual impact of each process condition on overall efficiency. Thus, RSM provides information about the optimum levels of each variable, interactions among them and their effects on the product yield (Rao and Satyanarayana 2007).

The modern approach for process optimization is artificial neural networks (ANN). Basically, ANN has at least three layers of connection (neurons). The first layer is inputs of the independent variables (neurons); second layer and third layer are hidden neurons that represent nonlinear activation functions and output neurons respectively. Each of the neurons in the first layer is connected to one or more layers of hidden neurons which are connected to a final level of output neurons. To minimize the deviation of predictions from experimental results, a trial-and-error method has been applied to determine the number of neurons required in the hidden layer. At least ten neurons are required to develop the model through ANN. The algorithms have been developed on the basis of influencing input neurons and their complex interactions on the observed result. A multilayer perceptron (MLP) is possible to develop through computer software (MATLAB).

Purification of enzyme is the major part of downstream processing. Purification processes start after fermentation; performance strongly depends on the available technology, market demand and cost investment. Most of the extracellular enzymes are purified by chromatographic techniques up to its homogeneity. The conventional multi-step purification process is cost expensive, time consuming and always has a chance of loss of the desired product with low yield (Arauza et al. 2009). The large-scale, cost-effective purification of bulk enzyme for commercial purposes was developed after the evolution of purification techniques that had fast, efficient and economical protocols with fewer processing steps (Amritkar et al. 2004). Forced affinity chromatography, expanded bed/fluidized bed chromatography, high speed counter current chromatography (HSCCC) and magnetic affinity adsorption chromatography provide the effective results for purification of amylase in industrial scale.

 
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