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Lupine Publishers | The Loop Regions and Substrate Specificity of GH 27 Familiy α-Galactosidases

 Lupine Publishers | Scholarly Journal of Food and Nutrition

Abstract

α-Galactosidases as natural biocatalysts have important application value in various industries. In this paper, we reviewed their physiological functions, biological sources, classification, and protein structure and substrate specificity relationships of Glycoside hydrolase (GH) family 27, aiming at providing references for related experiments and studies.

Keywords: GH27α-Galactosidase, Loop region, Substrate specificity, Thermo stability, Stability at low pH 29

Abbreviations: GH: Glycoside Hydrolase

Introduction

Galacto-oligosaccharides (i.e. stachyose and raffinose) commonly exist in food and feed and are indigestible by human and animals, thereby causing flatulence, gastrointestinal disturbance and low feed efficiency. [1] α-Galactosidases (EC. 3.2.1.22) has hydrolysis ability to degrade these anti-nutritional factors, decrease the viscosity of the diet, reduce the occurrence of diarrhoea, destroy the structure of the cell wall of the plant, promote the nutrition release, improve the utilization efficiency of the nutrients in the feed, increases lean meat rate, enhances immune function and disease resistance of animals. [2,3] α-Galactosidases has great application value in industrial processes of feed, food, and beet sugar production. α-Galactosidases are widely distributed in fungi, bacteria, plants and human (www.cazy.org). Fungal α-galactosidases have maximal activity at pH 3-5, but bacterial α-galactosidases are the optimal pH of 6-7.5.1, [4-6] Some thermostable α-galactosidases have been identified from thermophilic fungi, such as thermomyces lanuginosus, Talaromecys emersonii, and Rhizomucor miehei. [7- 9] Due to high processing temperatures and acidic environment of the gastrointestinal tract, the highly efficient, thermostable and acidicphilic α-galactosidases with broad substrate specificity is of great interest. [10] Base on the sequence similarities, α-galactosidases are divided into Glycoside Hydrolase (GH) families 4, 27, 36, 57, 97, and 110. [11] Most fungal α-galactosidases belong to GH27 and have conserved YLKYDNC catalytic motif and DD(G/C) W binding motif. [12,13] The resolved crystal structures of two GH27 α-galactosidases from Trichoderma reesei (1t0oA) and Saccharomyces cerevisiae (ScAGal, 3LRK) share a (β/α)8 barrel fold and a retaining reaction mechanism. [13,14] Sequence analysis indicated Loops 1, 2, and 4 of α-galactosidase from T. reesei and corresponding loops 1-3 and 6 from ScAGal create new binding sites for formation and breakdown of a covalent glycosyl enzyme intermediate.13,14 In our study, two α-galactosidases Gal27A and Gal27B of family GH27 from the thermophilic Neosartorya fischeri had similar tertiary structures but varied in loop regions and substrate specificity. [15,16] Gal27A had far separate loops and showed higher activity towards raffinose, which was 4.9 - and 3.8- fold for that of melibiose and stachyose.

[15] Whereas stachyose was a preferred substrate for Gal27B with closely proximate loops and its activity to stachyose was 9.6- and 4.4-fold of melibiose and raffinose, respectively.16 Introduction of loop 4 of Gal27A into Gal27B elevated the activity to raffinose and broaded the substrate specificity (data not shown). Kinetic analysis of prolyl oligopeptidase indicated the loop splitting decreased the affinity of the enzyme to the substrate. [17] Sitedirected mutagenesis revealed loops facing the active site of prolyl oligopeptidase can regulate the substrate gating and specificity. [18] Thus the flexibility and motility of loops are presumed to be involved in enzyme-substrate interactions. The transformation of the zymoproteins is an important source to obtain excellent zymoproteins for various industries. With the development and accumulation of structural biological information of protein structure and function, protein rational design will inevitably become an important means to improve the properties of enzyme proteins.

https://lupinepublishers.com/food-and-nutri-journal/pdf/SJFN.MS.ID.000102.pdf

https://lupinepublishers.com/food-and-nutri-journal/fulltext/the-loop-regions-and-substrate-specificity-of-gh-27-familiy-galactosidases.ID.000102.php

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Lupine Publishers | Body Mass Index of Kaani Tribes from Kanyakumari District in Tamil Nadu, India

 Lupine Publishers | Scholarly Journal of Food And Nutrition

Abstract

BMI provides the most useful population-level measure of overweight and obesity as it is the same for both sexes and for all ages of adults. However, it should be considered a rough guide because it may not correspond to the same degree of fatness in different individuals. There is a difference in BMI values for the Asians as compared to the WHO criteria. Our study focused on the BMI of the Kaani tribes in Kanyakumari District of Tamil Nadu, India. We categorized them as two groups, viz. those who lived in the forest area and those who had moved out of the forest into neighbouring villages. We found that among the forest dwellers there was a greater percentage in the underweight category, indicating energy deficiency, while those in the rural areas were moving to a greater BMI. This is of concern as the sequel of thinness and overweight represent major public health problems.

Keywords: BMI, Kaani tribes, Public health, Lifestyle, Chronic energy deficiency, Obesity

Abbreviations: BMI: Body Mass Index, WHO: World Health Organization, CED: Chronic Energy Deficiency

Introduction

Body mass index is considered as an index for assessing the nutritional status. The 1993 WHO Expert Committee WHO [1] reported that weight gain in adult life was associated with increased morbidity and mortality at higher BMI range. Therefore, BMI cutoff for overweight should be interpreted based on risk factors of morbidity and mortality. Smalley et al. [2] reported that type 2 diabetes mellitus, cardiovascular disease and increased mortality are the most important sequels of obesity and abdominal fatness, but other associations like musculoskeletal disorders, limitations of respiratory function and reduced physical functioning and quality of life were also observed.

Methodology

The study area Kanyakumari is located in Tamil Nadu in South India, about 700 Kms. from Chennai the capital city of Tamil Nadu. The nearest major city is Trivandrum in the neighbouring state of Kerala. Kerala border is very near to Kanyakumari, which is why a mixed culture of Kerala and Tamil Nadu is seen in the area. A crosssectional study was carried out as it provides a clear ‘snapshot’ of the outcome and the characteristics associated with it, at a specific point in time. The investigator collected quantitative data; the Auxiliary Nurse Midwife accompanied her from the Primary Health Centre to establish a rapport with the local leaders and Kaani heads. Anthropometric measurements were collected using standard instruments and protocol. Measurements were recorded for adult’s males and females in the age group of 25 to 55 years from the forest and rural areas. The sample size was calculated based on the 2011 census population size of Kaanis in Kanyakumari district.

Result and Discussion

A BMI< 18.5 kg/m² is widely used as a practical measure of chronic energy or hunger deficiency (CED), i.e., a “steady” underweight in which an individual is in energy balance irrespective of a loss in body weight or body energy stores Khongsdier [3]. Thus, the use of BMI as an anthropometric indicator of nutritional status can be more appropriate in a country with diverse ethnic groups, such as India Khongsdier [4] (Table 1). Majority of the male and female in forest area (52.8 % and 52.7%) and in rural area (51.65% and 59.7%) belonged to normal weight with a BMI of 18.5 - 22.9, followed by (45.9%) percent of the female in forest areas being underweight with a BMI of < 18.5. Alarmingly about 41.5 percent of the male in forest area were underweight with a BMI of < 18.5. 5.3 percent of male in rural were obese. Body mass index is used as an index to assess the extent of chronic energy deficiency (CEO) in adults. In adult males, the mean BMI was 20.38kg/m², 19.53kg/m², 20.25kg/m² for the age groups 30-35 years, 36-55 years and above 55 years respectively.

Adult under nutrition very simply happens, due to hunger and lack of food. Body Mass Index (BMI) can measure adult malnutrition and a BMI below 18.5 indicates chronic under nutrition. Statistics have shown how 37% of adult Indians, 50% of adults belonging to the Scheduled Tribes and 60% of adult Indians belonging to the Scheduled Castes have a BMI below 18.5, which makes them chronically undernourished. The overall CED was highest in Madhya Pradesh (76.0%) followed by Maharastra (71.9%), Jharkhand (58.5%), Tamil Nadu (55.0%), Andhra Pradesh (50.1%), Odisha (49.5%), West Bengal (45.9%), Kerala (37.8%), Andaman & Nicobar Island (29.5%), Assam (21.5%), while Meghalaya shows the least (14.3%) prevalence of under nutrition among the tribes in all the studied states of India Das and Bose [5] . Asian Indians have a characteristic obesity phenotype, consisting of relatively lower BMI, excess body fat percentage, abdominal and truncal adiposity and less lean tissue Banerji et al. [6]; Dudeja et al. [7]. WHO [8] Expert Consultation proposed a new BMI cut-off of 23.0 kg/m2 for public health action in Asia. There has been limited data on the anthropometric and nutritional status of various tribal populations of India Bose et al. [9] to plan intervention strategies.

Conclusion

Many researchers report the relationship between BMI and diabetes mellitus. Misra and Vikram [10] reported that 67% diabetics were found as either over weight (or) obese subjects. We have found that under-weight is predominant in the Kaanis of the forest area, while those who have moved to rural areas outside the forest have a greater percentage who are over-weight. We would like to conclude that life-style in the forest is not conducive to maintaining healthy body weight; while those who have moved out of the forest are heading towards problems of over-weight. One is a consequence of insufficient food intake, the other is leading to overnutrition and consequently to lifestyle diseases in the future.

https://lupinepublishers.com/food-and-nutri-journal/fulltext/body-mass-index-of-kaani-tribes-from-kanyakumari-district-in-tamil-nadu-india.ID.000101.php

https://lupinepublishers.com/food-and-nutri-journal/pdf/SJFN.MS.ID.000101.pdf

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