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Starch granule size and amylopectin chain length distribution affect in-vitro enzymatic digestibility and resistant starch content in the selected rice mutants
- Mutation breeding (γ-radiation) was used to develop mutant with increased RS with reduced digestibility
- Amylopectin chain length variation and starch granule size distribution influenced the RS and digestibility in the mutant lines RSML 184 and RSML 278.
- Increased amylose content with reduced granule size in mutant line RSML 352 showed higher rate of digestibility than other mutants
RS = resistant starch
RDS = rapidly digestible starch
SDS = slowly digestible starch
TDF = total dietary fibre
RSML = RS in meal
RSPS = RS on pure starch
RDSM = RDS in meal
RDSPS = RDS in pure starch
SDSM = SDSM in meal
SDSPS = SDS in pure starch
DP = degree of polymerization
SEM = Scanning electron microscopy
The selected rice (Oryza sativa L.) mutant lines, developed using gamma (γ) radiation, were characterized and compared with the wild type rice (ADT 43) for their starch characteristics, non-starch constituents and in-vitro enzymatic digestibility. The mutants contained significantly (P < 0.05) higher concentrations of amylose, protein, total dietary fibre (TDF), crude fat, total phenol, and ash compared to the wild type whereas, thousand-grain weight (TGW) and starch concentration were significantly (P < 0.05) lower in the mutants compared to the wild type. Starch analysis of mutants revealed that RSML 184 and RSML 278 had significantly (P < 0.05) higher proportion of bigger starch (5-15 µm) granules and significantly (P < 0.05) increased area of amylopectin chains of DP 13-24. Correlation and dendrogram analysis revealed that grain constituents does not influence in-vitro enzymatic hydrolysis. On the other hand, starch granule size and amylopectin chain length variation contributed towards increased RS and reduced starch digestibility in mutant rice.
Rice, Mutants, Resistant starch, In-vitro enzymatic hydrolysis, Amylopectin chain length, Starch granule size
Among the cereal grains, rice (Oryza sativa L.) is staple food of more than half of the world’s population (Boonyaves, Wu, Gruissem, & Bhullar, 2017). The global demand for rice in 2010 was 676 million tonnes that would increase to 763 million tonnes in 2020 and 852 million tonnes in 2035 (Khush, 2013). Therefore, rice improvement programs are focused to increase the yield/production to assure food security worldwide (Khush, 2013). The improved economic growth and affluence around the world also contributed in steady demand for rice varieties with improved grain quality (Pang et al., 2016). Consequently, improvement of rice productivity traits by selecting superior yield components and ideal plant types has been widely investigated during last decade (Khush, 1999; Peng, Khush, Virk,Tang, & Zou, 2008). However, improvement of rice nutritional quality by reducing its digestibility or increasing the concentration of dietary fibres/resistant starch has been rarely attempted.
In the earlier days, whole grains loaded with fibres used to be consumed that, after the introduction of processing technologies, have been replaced by refined grains devoid of dietary fibres like the modern milling technology in rice (Chattopadhyay, 2005; Shobana et al., 2011). Rice goes through a variety of processes before it is ready for cooking and consumption. Most people are accustomed to white rice rather than brown rice (Sudha et al., 2013) and the steps to turn brown rice into white rice remove almost 75 per cent of the total dietary fibre content. Therefore, higher consumption of white rice was significantly associated with the increased incidence of type 2 diabetes (T2D) (Radhika, Van Dam, Sudha, Ganesan, & Mohan, 2009) after studying 13,284 cases of T2D among 352,384 Asian participants (Hu, Pan, Malik, & Sun 2012). Dietary fibres are mainly present in rice seed coat therefore, increasing their concentration to reduce the calorie value of rice is not a viable solution as the seed coat will be removed during processing. Therefore, to address this problem, main seed storage constituent should be targeted, viz. starch composition (Rahman et al., 2007).
Rice grain predominantly contains starch (~90%) (Zhou, Robards, Helliwell, & Blanchard, 2002) which is composed of amylose (% of total rice starch; linear glucan molecule) and amylopectin (% of total rice starch; branched glucan molecule). Rice starch may be divided into three fractions based on the enzymatic hydrolysis: readily digestible- (RDS), slowly digestible- (SDS), and resistant- starch (RS) (Englyst and Hudson, 1996). RS is the starch fraction or product of starch degradation which escapes digestion in small intestine and can be completely or partially fermented in the large intestine by the microflora (Berry, 1986; Faraj Vasanthan, & Hoover, 2004;). Therefore, RS concentration in the rice starch is negatively correlated to its calorie value. This characteristic of RS can be implemented to help persons with diabetes to maintain their postprandial blood glucose level. Several studies have been reported to increase the RS concentration through physical starch modifications using diverse industrial processing technologies (Topping and Clifton, 2001) however, it increases the cost of the food. Alternatively, amylose concentration in starch can be targeted to improve RS content in the rice grains. Amylose, an important determinant of RS formation, is more resistant to enzymatic hydrolysis compared to its counterpart amylopectin (Leeman, Karlsson, Eliasson, & Björck, 2006; Lehman and Robin, 2007) and therefore, is being widely used to enhance the RS content of processed foods. Rice, wheat and barley cultivars with enhanced amylose and RS concentrations, have shown potential health benefits through reduction of plasma cholesterol and production of increased large-bowel short-chain fatty acids (Evans and Thompson, 2004; Bird, Flory, Davies, Usher, & Topping, 2004; Slade et al., 2012). Starch is an integral component of rice grains endosperm and largely unaffected by the processing techniques. Therefore, modulating starch composition (amylose and RS concentrations) is a potential target to develop rice varieties with low calorie value using selective breeding or genetic engineering (Gearing, 2015).
In the present study, 3000 M2 rice mutants were developed through gamma (γ) irradiation (Agasimani, Selvakumar, Joel, & Ganesh Ram, 2013) of ADT 43, a well-adapted and popular short duration rice variety of Tamil Nadu, India. Mutants (RSML 184, RSML 278 and RSML 372) with the best agronomic performance were compared with wild type for their starch and non-starch constituents.
2. Materials and methods
2.1. Plant material
The rice mutants RSML 184, RSML 278 and RSML 352 developed through gamma (γ) irradiation of the rice variety ADT 43, were selected for this study along with the wild type ADT 43, a popular short duration rice variety of Tamil Nadu (India) derived from the cross between IR 50 and Improved White Ponni (IWP). It was released in 1998 and is being widely cultivated annually in around 250,000 hectares of Tamil Nadu, India. This cultivar is resistant to green leaf hopper (GLH) whereas, moderately resistant to brown plant hopper (BPH), shoot borer (SB) and gall midge (GM). This variety also possesses acceptable milling and cooking qualities. The starch and non-starch composition of the isolated mutants (RSML 184, RSML 278 and RSML 352) along with wild type were investigated in this study. The selected mutants were grown at Paddy Breeding Station (PBS), Tamil Nadu Agricultural University (TNAU), Coimbatore, Tamil Nadu (11.1176° N, 76.9944° E) India in 2013. For best crop establishment, standard agronomic practices were followed as per the crop production guide 2012, TNAU, Coimbatore (http://agritech.tnau.ac.in/pdf/2013/CPG%202012.pdf).
2.2. Thousand grain weight
Thousand grain weights of the mutants were determined using a precision electronic balance (Mettler Toledo, USA) and 1,000 well developed whole grains dried to 13 % moisture content.
2.3. Preparation of samples
Paddy samples were dehulled (Satake THU35A dehusker, Satake Engineering Co Ltd, Tokyo, Japan), milled (MC250 Satake one-pass mill, Satake Engineering Co. Ltd, Tokyo, Japan), and aspirated to produce white rice. Dehulled rice grains were ground using a cyclone mill (UDY Corp., Fort Collins, CO, USA) with a 0.5 mm sieve. The ground rice meal was used for biochemical characterization. Moisture content of the meal samples were estimated by hot air oven method and used to calculate dry weight basis of individual biochemical constituents.
2.4. Total starch concentration
Total starch content was determined based on the AACC International approved method (AACCI Approved Method 76-13.01) using a commercial kit (Megazyme International Ireland Ltd., Bray, Ireland).
2.5. Protein concentration
Nitrogen concentration was determined by combustion method using a FP-528 Protein/Nitrogen Analyzer (LECO Corporation, St, Joseph, MI) (AACCI Approved Method 46-30.01).
2.6. Crude fat determination
Crude fat concentration was determined by AOCS (AOCS Am 5-04) approved method, using hexane as the extraction solvent. Rice meal samples ( ̴ 1 g) were measured in XT4 (ANKOM Technology, Macedon NY, USA) filter bags, and sealed by using electronic sealer. The filter bags were dried at 105oC for 3 h to remove the moisture. After drying, the filter bags were stored in moisture proof bags cool down to room temperature, weighed, and stored in desiccators till use. The filter bags were placed in the ANKOMXT15 Extractor (ANKOM Technology, Macedon NY) at 105oC for 2 h to extract fat from the samples. Thereafter, the filter bags were dried at 105oC for 30 min to remove the residual hexane, cooled to room temperature in moisture proof bags, and weighed. The fat % was expressed as the weight of fat per gram of dry weight of initial meal sample used for extraction.
2.7. Total dietary fibre (TDF)
TDF was determined by AOAC (AOAC Approved method 991.43) International approved method.
2.8. Determination of Phenolic Content
Free phenolics from the meal samples were extracted as reported previously (Adom, Sorrells, & Liu, 2003) with slight modifications. The rice meal samples (1 g) with 4ml of 80 % (v/v) cold ethanol taken for extraction and dispersed for 10 min using vortexer and then centrifuged at 2500 g for 10 min. This process was repeated, the supernatant was collected and pooled together. The pooled supernatant was rotary evaporated at 45 0C to <5 ml and reconstituted to 5ml with distilled water. The reconstituted samples were stored at -20 0C until further analysis.
The acid and alkaline soluble phenolics were extracted as previously described by Krygier, Sosulski, & Hogge, (1982) with slight modification for hydrolysis. Meal sample (1 g) was weighed and mixed with 6M HCL which previously had the free phenolics removed. The container was purged with nitrogen to minimize the oxidation loss of phenolic compounds. The reaction mixture was kept for shaking in rotary shaker at 2000 rpm for 4 h. After the incubation, pH of the solution was adjusted to 2 with 6M NaOH. A 50 ml of 1:1 ratio of diethyl ether and ethyl acetate was added to the mixture and container was inverted 11 to 12 times then container was centrifuged at 1000 g for 10 min. repeated this step and supernatant was collected and pooled. The pooled supernatant was evaporated at 45 0C to <5 ml and reconstituted to 5ml with distilled water. The reconstituted samples were stored at -20 0C until further analysis.
The alkaline hydrolysis was carried out to an additional hydrolysis step. Meal sample (1g) (free and acid phenolics removed) was weighted and mixed with 75 ml of 6M NaOH. The container was purged with nitrogen to minimize the loss due to oxidation of phenolic compounds. The reaction mixture was kept for shaking in a rotary shaker at 2000rpm for 4 h. After the incubation, pH of the solution was adjusted to two with 6M HCL. A 50ml of 1:1 ratio of diethyl ether and ethyl acetate was added to the mixture and container was inverted 11 to 12 times and was centrifuged at 1000g for 10 min. This step was repeated and supernatant was collected and pooled. The pooled supernatant was evaporated at 45 0C to <5 ml and reconstituted to 5ml with distilled water. The reconstituted samples were stored at -20 0C until further analysis.
Total Phenolic content (Free, acid and alkali soluble) of the extracted samples was determined as described by Verma, Hucl, Chibbar, (2008) with some modification. A 100 µl of the extract was oxidized with 50 µl of half strength (1N) Folin-Ciocalteau reagent, and neutralized with 200 µl of 7.5 % of sodium carbonate solution with 650 µl of distilled water. The reaction mixture was incubated at 40oC for 30 min. The absorbance of the solution was measured on a DU 800 spectrophotometer (Beckman Coulter, Fullerton, CA, USA) at 750 nm and total (free, acid and alkaline soluble) phenolic concentration of the samples were determined against external standards of Gallic acid (Sigma Aldrich, USA). Therefore, the total phenolic content of the sample was expressed as mg of GAE g-1 of meal sample.
2.9. Determination of ash content
Ash content of the samples were analysed using AACC International (AACCI Method 08-01.01) approved method.
2.10. Starch extraction
Starch extraction was carried out as described by Lumdubwong & Seib (2000) with some modification. The ground rice meal (1g) was steeped overnight with 0.01M NaOH (5 mL) and 100 µL of 1% protease at 37oC, and neutralized using 1M HCl. The solution was centrifuged at 3,000g and the supernatant was discarded. The precipitate was suspended in water (1 mL), layered over 80% (w/v) Cesium Chloride solution (1 mL) and centrifuged at 13,000 rpm for 20 min. The pellet obtained was suspended with water and filtered through 100 µm pore size nylon filter. Supernatant was discarded and dark tailing layer was removed with spatula. The starch pellet was washed thrice with 1 mL of water and centrifuged at 13,000 rpm for 10 min, followed by acetone (1 mL) and centrifuged at 13,000 rpm for 10 min and finally air dried overnight.
2.11. Amylose concentration determination
The extracted starch was used for analyzing the amylose concentration. Amylose concentration was determined using high performance size exclusion liquid chromatography as described (Demeke, Hucl, Abdel-Aal, Båga, & Chibbar, 1999).
2.12. In-vitro enzymatic hydrolysis of meal and pure starch
In vitro enzymatic hydrolysis was carried out for both meal and pure starch samples to study the kinetics of enzymatic digestion as described (Ahuja, Jaiswal, Hucl, & Chibbar, 2014).
2.13. Starch granule size distribution
Starchgranule size distribution of the extracted starch was determined by laser diffraction technique using particle size analyser (Mastersizer 2000, Malvern Instruments, Malvern, England). The pure starch (30 mg) was weighed and dispersed in 1ml of 1% Sodium dodecyl sulfate (SDS; Fisher scientific, USA). About 200 µl of starch slurry was used for size analysis at a pump speed of 1700 rpm (Asare et al., 2011).
2.14. Scanning electron microscopy (SEM) studies
Dried starch samples were adhered to pin stub mount using carbon conductive tabs, and then coated with 20 mm gold in Gold Sputter Coater (Edwards S150B). The prepared specimens were viewed for their morphologies by a scanning electron microscope (Hitachi-SU8000,) at an accelerating voltage of 5 kV.
2.15. Amylopectin chain length distribution analysis
Amylopectin Chain length distribution was determined by fluorophore-assisted capillary electrophoresis (FACE) using aProteome Lab PA800 (Beckman Coulter, Fulerton, CA) equipped with a 488-nm laser module. A modified debranching protocol (Asare et al., 2011) was used to obtain unit amylopectin chains, which were labelled with 8-aminopyrene 1, 2, 6-triphosphate sodium cyanoborohydride in the presence of sodium cyano-borohydride/tetrahydrofuran. The N-CHO capillary with polyvinyl alcohol coating and a pre-burned window (50 μm inner diameter, 50.2 cm total length) was used to separate amylopectin chains of diverse degree of polymerization (DP) in a debranched starch sample. Maltose was used as an internal standard. Samples were injected at 0.5 psi for 3 seconds and separated at constant voltage of 30 kV for 30 min. Data was recorded and analysed using 32-karat software (Beckman Coulter, USA). The DP was assessed to peak based on relative migration time of maltose.
2.16. Statistical analysis
All the experiments were done on three botanical replicates. The pair-wise comparisons were performed using the Tukey’s range test at p < 0.05 confidence level and Pearson’s correlation studies were carried out using MINITAB 16.0 statistical software (Minitab Inc., State College, PA, USA). Data was analyzed for linkage between different samples using average linkage Pearson distance method of Cluster analysis using Minitab 16.0 statistical software (Minitab Inc., State College, PA, USA)
3.1. Grain analysis of mutants and wild type
The grain analysis was carried out to compare the mutant and wild type grain constituents. TGW was severely affected in the mutants genotypes (range 11.6 to 12.9 g) than the wild type (15.7 g). It was reduced significantly (p < 0.05) in the mutants over wild type. RSML 352, RSML 184, and RSML 278 had 26.1, 20.3 and 17% lower TGW compared to the wild type, respectively. Mutant genotypes contained significantly (p < 0.05) lower starch concentrations (67.5-79.7 %) compared to the wild type (82.0 %) (Table 1). Wild type recorded the protein concentration of 8.5% while, value for the mutants ranged from 9.7 – 11.0 %. Protein concentration varied significantly (p < 0.05) among the rice mutants, RSML 278 had the highest protein concentration (11.0%) followed by RSML 352 (10.1%) and RSML 184 (9.7%).
Starch concentration in rice showed a positive (r = 0.59) correlation to TGW whereas, negative (r = -0.96) to protein concentration significant at P < 0.05 and 0.01, respectively (Table 4). The negative correlation between starch and protein can be explained by the carbon partitioning between the two seed constituents and concurred with the results of Asare et al. (2011). The carbohydrate biosynthesis requires less energy compared to protein and fat biosynthesis therefore, shows a positive correlation to the seed weight (Asare et al., 2011). This positive correlation between seed weight and starch concentration has also been reported in other crops like barley (Asare et al., 2011), lentil (Tahir, Lindeboom, Båga, Vandenberg, & Chibbar, 2011), kabuli chick pea (Frimpong et al. 2009) and wheat (Hucl & Chibbar, 1996).
Total dietary fiber concentration of the wild type recorded the value of 2.2 % while, mutants varied from 3.0 to 6.1 % and differed significantly (p < 0.05) among RSML 278 and RSML 352 (Table 1). RSML 278 had the highest TDF of 6.1% while RSML 184 mutant had the lowest TDF value of 3.0%. Variation in the TDF content among the mutants was 0.8% to 3.9% over wild type. These findings concur with an earlier finding that dietary fiber content is higher in increased amylose genotypes. The fat concentration ranged from 1.2 to 2.6% in the mutants. The mutants significantly differ (p < 0.05) in their crude fat content from their wild type (Table 1).
Phenolic compounds are major secondary metabolites (Klepacka & Fornal, 2006) which is present in both free and bound form in cereal grains (Krygier et al., 1982). Significantly (p < 0.05) higher amount of total phenolic content was observed in mutants compared to the wild type. Total phenolic content of the mutants varied from 2.1 – 3.4 mg of GAE g-1 whilewild type recorded the value of 1.1 mg of GAE g-1 (Table 1). RSML 278 and RSML 352 had highest ash content of 1.54 and 1.51 % respectively compared to wild type (0.68 %). The increased ash content in the mutants (RSML 278 and RSML 352) clearly indicates the presence of minerals. Presence of minerals in the starch influences the viscosity and paste clarity and stability (Bao & Bergman, 2004).
3.2. Starch analysis
3.2.1. Amylose concentration
All the mutants used in this study showed significant (p < 0.05) increase (~3-4%) in amylose concentration compared to the wild type ADT 43. Wild type genotype ADT 43 recorded the amylose concentration of 21.4%. Amylose concentration ranged from 24.3-25.8% and significantly (p < 0.05) varied between mutants and wild type (Table 1). The structure and amount of amylose affect the enzymatic hydrolysis rates of starches by altering its stability (Lu, Jane, & Keeling, 1997; Kim et al., 2004; Jane, 2006). Although relationship studies showed increased amylose concentration influence the starch digestibility, however no such significant relationship was detected in this genotype which clear the doubt that apart from amylose, other factors influence the digestibility of mutants.
3.2.2. Starch granule size distribution
The mutants showed starch granule size distribution ranging from 1.25 to 104.71 µm. Starch granule size distribution varied significantly (p < 0.05) between wild type and mutants. The proportion of small (<5 µm) and median size (5-15 µm) starch granule showed significant difference in mutants and wild type. The mutants, RSML 184 and RSML 278 had significantly (p < 0.05) reduced proportion of small size (<5 µm) granule with a value of 26.4% and 28.5% respectively (Table 3). On the other hand, RSML 352 showed significantly increased proportion (52.9%) of small starch granules which makes RSML 352 highly susceptible to enzymatic reaction and showed increased HI both in meal and pure starch samples. The micrographs of SEM (Fig 2) were used to confirm the starch granule size variation observed in the x-ray diffraction technique (Fig 1). All the mutants except RSML 352 showed increased granule size over wild type genotype. Increased RS (pure starch) in mutants showed perfect negative correlation (r = -0.96, p < 0.01) with small granule size, consequently, median granule size recorded a perfect positive correlation with a r value of 0.89 (p < 0.01) (Table 5). Similarly, HI in pure starch showed significant (r = 0.98, p < 0.01) positive relationship with small (<5 µm) starch granule size and negative correlation (r = 0.98, p < 0.01) with median (5-15 µm) granule size. Therefore, increased proportion of median and decreased proportion of small size granules reduced the digestibility which is otherwise desirable for slowing down the digestibility of starch.
3.2.3. Amylopectin chain length distribution
The amylopectin chain length distribution is classified into the following chain types as: A chains (DP 6-12), B1 chains (DP 13-24), B2 chains (DP 25-36) and B3+ chains (DP ≥ 37) (Hanashiro, Abe, Hizukuri, 1996). The average DP of amylopectin chains in mutants and wild type varied significantly (p < 0.05). However, B1 chains were significantly (p < 0.05) higher in RSML 184 and RSML 278, conversely, A chains showed significant (p < 0.05) reduction. RSML 352 recorded significantly (p < 0.05) higher proportion of A chains and decreased B1 chains (Table 3, Fig 3). Increased RS in mutant showed significant positive correlation with all the medium and long chains (DP 13-24 (r = 0.99, p < 0.01), DP 25-36 (r = 0.95, p < 0.01), and DP ≥ 37(r = 0.89, p < 0.01). In contrary, HI recorded significant negative correlation with all the medium and long chain amylopectin (Table 5). DP 6-12 showed significantly negative (r = -0.96, p < 0.01) and positive (r = 0.75, p < 0.01) relationship with RS and HI respectively. Rice mutant showing increased B1 and decreasing short and long chain amylopectin might play important role in the increased RS and slow digestibility (Shu et al., 2006). Similar results were also reported in maize (Hasjim, Srichuwong, Scott, & Jane, 2009). In earlier studies by Aramaki et al. (2004) showed a positive correlation between amylopectin short A chains (DP 6-12) and enzyme digestibility of rice grains but a negative correlation was observed between amylopectin chain length of DP 35–41. This distribution pattern of amylopectin in mutant lines RSML 184 and RSML 278 is responsible for reduced digestibility and increased RS. Increased digestibility with reduced RS in RSML 352 is mainly because of increased proportion of short A chains (DP 6-12) (Table 3) which is already reported in japonica rice (Umemoto, Terashima, Nakamura, & Satoh, 1999; Hanashiro et al., 1996).
3.3. In-vitro enzymatic starch hydrolysis
The mechanisms governing RS even though may be related to amylose concentration and structural modifications of amylopectin, there are also reports that mention the complexion of starch with other macro molecules such as protein (Goddard, Young, & Marcus, 1984; Guraya, Kadan, & Champagne, 1997), lipid (Englyst & Cummings, 1987; Eerlingen, 1994; Philpot, Martin, Butardo, Willoughby, & Fitzgerald, 2006), and phenols (Verma, Hucl, & Chibbar, 2009), have also responsible for rate of starch digestibility in grains. In vitro enzymatic hydrolysis was performed both in meal and pure starch to know the effect of grain constituents concentration and structure on starch digestibility. Based on kinetics, starch can be divided into rapidly digestible (RDS), slowly digestible (SDS), and resistant starch (RS). Both in meal and pure starch, RDS, SDS, and RS values showed significant difference between the mutants and wild type (Table 2). SDS (meal) was lowest in RSML 184 (52.0%), and highest in RSML 278 (57.0%) compared to the wild type and mutant studied. In meal, RS was lowest in ADT 43 (14.5%), and highest in RSML 184 followed by RSML 278 (20.3%). Mutant RSML 352 recorded least RS value of 4.4% and 3.8% in meal and pure starch respectively. Hydrolysis index (HI) is a predictor of glycemic index (GI), the postprandial blood glucose response (Goñi, Garcia-Alonso, & Saura-Calixto, 1997). HI in both meal and pure starch showed significant (p < 0.05) differences among mutants and wild type. Wild type recorded the HI value of ~50% both in meal and pure starch (Table 2). HI for meal was lowest in RSML 184 (35.9%) and RSML 278 (46.0%) while, HI for pure starch was lowest in RSML 278 (45.4%) which is otherwise highly desirable as compared to wild type genotype ADT 43, due to higher proportion of RS and low in HI.
In the recent years, much research has been focused on studying the functional properties of foods. These properties are ascribed to the presence of a substance or a group of substances that, when consumed in adequate quantity or periodicity, have beneficial effects on the human health (Walter, Da Silva, & Denardin, 2005). In this context, breeding rice varieties with increased RS is essential for reducing the incidence of T2D and to promote healthy living.
Earlier studies on grain constituents and starch properties have been demonstrated to affect the hydrolysis of different crop plants (Themeier, Hollmann, Neese, & Lindhauer, 2005; Sang, Bean, Seib, Pedersen, & Shi, 2008). High amylose rice, maize and barley have shown the formation of increased RS and reduced digestibility (Zhu, Liu, Wilson, Gu, & Shi, 2011; Zhang, Sofyan, & Hamaker, 2008; Asare et al., 2011). In this study, mutants recorded significant increase in the amylose concentration (Table 1). However, it does not show any positive correlation/association with digestibility parameters. The proteins present in the grains could also limit the kinetics of enzymatic hydrolysis by blocking the adsorption sites and therefore influences enzyme binding (Singh, Dartois, & Kaur, 2010; Tester, Qi, & Karkalas, 2006). They form a protective network with starch granule which leads to lower digestion of starch and influence the rate of starch digestion (Lehmann and Robin, 2007). In addition to this, proteins network (disulfide-linked polymers) in cereal grains may possibly reduce the glycemic response and reduced starch digestion (Sajilata, Singhal, & Kulkarni, 2006; Singh et al., 2010). Other grain constituents such as TDF, phenol and fat were also influence the starch digestion. The viscosity and bulking property of TDF slowdown the starch digestion, consequently the blood glucose concentration does not increase dramatically upon consumption (Fennema, 1996). Phenolic compounds are major secondary metabolites (Klepacka and Fornal 2006) and occur in both free and bound form in a grain (Krygier et al 1982; Abdel-Aal et al., 2001). They found in carbohydrate ester form and which may inhibit the pancreatic α-amylase activity (Singh et al., 2010). Lipids or fat present in the grains limit/reduce the contact between alpha amylase and substrate (Tester et al., 2006). These findings clearly suggest that lipids have a significant role in influencing the hydrolysis and physiochemical properties of rice such as retrogradation which is directly associated with RS formation and reduction of HI (Singh et al., 2010). However, correlation/association analysis between grain constituents and in-vitro enzymatic hydrolysis of meal samples clearly showed that there is no significant relationship between RS and HI with any grain constituents except ash (r = 0.63, p < 0.05) (Table 4). On the other hand, RDS in meal recorded significantly positive correlation with amylose (r = 0.61, p < 0.05), protein (r = 0.68, p < 0.05), TDF (r = 0.83, p < 0.01), fat (r = 0.85, p < 0.01), total phenol (r = 0.81, p < 0.01) and ash (r = 0.86, p < 0.01) (Table 4). Therefore, these factors including amylose concentration does not significantly influence the rate of digestibility of starch in the mutants.
Amylopectin chain length distribution and starch granule size distribution also affects starch digestibility. In this study, short chain amylopectin (DP 6-12) were positively associated with RDS (r = 0.88, p < 0.01) and HI (r = 0.75, p < 0.01) of pure starch and negatively associated with RS (r = -0.96, p < 0.01) and SDS (r = -0.76, p < 0.01) (Table 5). Comparable findings were observed in barley by Asare et al. (2011). DP 13-24 showed perfect positive correlation with RS (r = 0.99, p < 0.01), SDS (r = 0.80, p < 0.01) and negative correlation with HI (r = -0.86, p < 0.01). similar trend was also observed with DP 25-36, DP 37-50. As a result, based on correlation analysis we suggest that these fractions of chain length distribution might be controlling/contributing towards increased RS and reduced digestibility in rice mutants.
In addition to amylose concentration and amylopectin chain length distribution other factors might also influence the starch digestibility. The smaller size granules are highly amenable for enzymatic hydrolysis and vice versa (Asare et al., 2011). The higher susceptibility of smaller granules may be attributed to the bigger surface area which can increase the extent of enzyme binding (Tester et al., 2006). Similarly, in the present study, smaller size granules (< 5 µm) were correlated positively with RDS and HI and negatively correlated with SDS and RS of pure starch sample. Recent studies on in vitro enzymatic studies on wheat, barley also showed similar correlation/association with starch granule size distribution (Ahuja et al., 2014; Asare et al., 2011). The finding clearly suggests beyond any doubt that, the main reason for the low digestibility and increased RS in mutants is mainly due to increased proportion of medium and long chain amylopectin chain length and median and large starch granule proportion in the mutants.
Dendrogram analysis of grain constituents and starch related parameters revealed relationship between them. Based on similarity (based on average linkage) variability showing relationship are grouped in to four groups. The first group of clusters exhibited strong correlation between total starch and SDS of meal with a similarity percentage of >90%. Similar correlation was also observed between TGW and > 15 µm (Fig 4). Second group of clusters recorded inter and intra correlation between RS in meal, DP 13-24, RS in pure starch, DP 25-36, starch granule size (5 to 15 µm), DP 37-50 and SDS in pure starch with a similarity value of >80 %. The third group of clusters exhibited intra and inter correlation between grain constituents such as protein, TDF, ash, crude fat, total phenolics and RDS in meal with a similarity percentage of >85%. Final group of clusters showed correlation between RDS in pure starch, starch granule size (<5 µm), HI in pure starch and meal, with DP 6-12 with a similarity value of >90%. This analysis also revealed ~100% of relationship between RS (both meal and pure starch) with DP 13-24, RDS starch granule (<5µm) and HI in pure starch. The findings from this dendrogram analysis revealed that variation in amylopectin chain length and starch granule size distribution significantly influenced the resistant starch content and digestibility of mutants studied.
The mutant lines RSML 184 and RSML 278 were significantly different from the wild type (ADT 43) in different aspects of starch and non-starch constituents such as amylose concentration, starch granule size distribution, RS, protein, TDF, Phenols, amylopectin chain length variation and digestibility. However, correlation and dendrogram analysis clearly showed there is no significant correlation/association observed between hydrolysis parameters with grain constituents (Fig 4). The previous reports focused individually on amylose concentration or on amylopectin structure, the actual reasons that affect the digestibility of rice remain badly understood. Many investigations on rice demonstrated that amylose to amylopectin and the structural feature of amylopectin influence the digestibility of rice starch (Jane et al., 1999; Jobling, Westcott, Tayal, Jeffcoat, & Schwall, 2002; Okamoto, Kobayashi, Hirasawa, & Umemoto, 2002). Apart from all these factors, other parameters such as non-starch (protein, crude fat and phenol) constituents may also contribute to increase the RS and slow down the digestibility by making complexes with the starch structure.
In this investigation, increased RS and reduction in digestibility was mainly due to structural changes in the granule size and chain length variation of the amylopectin. With this finding, breeding for RS or digestibility in rice is redirected by designing the objectives based on the finding of this investigation will help to select superior rice genotype with highly desirable quality parameter for the health benefits of growing population of T2D.
The present study showed that the starch granule size and amylopectin chain length distribution plays major role in increasing RS content and reducing the digestibility of starch. Correlation analysis reveals that other non-starch constituents had an insignificant impact on RS content and digestibility of mutant lines. Both increased RS and reduced digestibility of mutants RSML 184 and RSML 278 will play important role in the dietary management of metabolic disorder such as T2D. Hence, this study provides useful information for rice breeders to identify or frame the breeding program to isolate or screen the rice cultivar or mutants for the development of better rice with reduced starch digestibility.
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