Relationship between the molecular structure of duckweed starch and its in vitro enzymatic degradation kinetics

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Abstract

Starch molecular structural effects in duckweed (Lemna minor and Landoltia punctata) controlling in vitro enzymatic degradation kinetics was studied. The molecular size distributions of fully-branched starches and the chain length distributions (CLDs) of enzymatically debranched duckweed starches were obtained using size-exclusion-chromatography (SEC). The CLDs of both debranched amylose and amylopectin were fitted with models using biologically-meaningful parameters. While there were no significant correlations between amylose content and starch degradation rate, the total amounts of amylose with shorter chain length negatively correlated with undigested starch content, and the amount of amylopectin long chains negatively correlated with the degradation rate coefficient. This provides new knowledge for the utilization of duckweed starches in bioethanol production.

Introduction

Bioethanol can be produced from a variety of feedstocks used as carbon source, including first-generation feedstocks (such as sugarcane, corn, triticale, wheat and cassava) and second-generation feedstocks (agricultural and municipal waste, grasses and trees) [1,2]. However, there is a concern about the use of first-generation feedstocks for ethanol production, since they inevitably compete for cropland used for food/feed production and biodiverse landscapes, such as rainforests [3].

Duckweed, a floating aquatic plant of the Lamnaceae family, is a potential alternative to resolve this problem since it is used for the decontamination of wastewater by absorbing problematic minerals [4]. This usage however means that its starch cannot be used in the food or animal feed industries, but, by the same token, duckweed is a more promising raw material than corn for ethanol production. Duckweed starch content varies with species and growth conditions, ranging from 3% to 75% of dry weight [3]. Duckweed may produce biomass up to 64 g/g-week [5], which is higher than generally seen in larger aquatic or terrestrial plants. The starch production rate from duckweed can be as much as 28 t/ha-year, which is considerably greater than from corn (about 5 t/ha-year) [6].

Previous studies on duckweed starch have focused on growth conditions, starch accumulation and application as feedstock and/or for ethanol production [1,3,[7], [8], [9], [10]]. There has been no systematic research on how the duckweed starch molecular structural influences starch enzymatic degradation rate (see e.g. [11]), which is of importance in determining the production of glucose, a key precursor in ethanol production. A study of the correlation between duckweed starch structural parameters and its degradation kinetics would help understand the role played by molecular structure in starch hydrolysis, and reveal structural features linked to higher yields and production rates of fermentable sugar.

To understand this, starch molecular structures, specifically the molecular size distributions of the fully branched molecules and the chain length distributions (CLDs) of enzymatically debranched starches, were obtained using size exclusion chromatography (SEC, a type of gel permeation chromatography, GPC). The CLDs of both amylopectin and amylose were fitted by biosynthetic models [[11], [12], [13]]. The kinetics of the cooked duckweed starch degradation rates were estimated using logarithm-of-slope analysis (LOS) combined with a modified nonlinear least-square (NLLS) method, as reported previously [11]. This yields the values of k (the digestion rate coefficient) and C (the residual undigested starch). Correlations between the structural parameters obtained from the model fitting and the digestion properties were then obtained using standard statistical methods.

Section snippets

Materials

Five duckweed samples, two from Brazil and three from Australia, were chosen in this study, as shown in Table 1. The samples were dried in an oven at 50 °C for 48 h and stored at room temperature for future starch extraction.

Dimethyl sulfoxide (DMSO, GR grade) was from Merck Co. Inc.; LiBr (Reagent-Plus), protease from Streptomyces (Type XIV) and porcine pancreatic α-amylase were from Sigma-Aldrich (St. Louis, USA). Isoamylase (from Pseudomonas), total starch (AA/AMG) assay kit and

Starch molecular structure

SEC weight distributions of debranched starch samples are shown in Fig. 1. As always seen for all except some high-amylose starches, these show the amylopectin chains with DP ≲ 100, separated from the longer chains, which are amylose, by the noticeable minimum in the weight CLD at DP ~ 100. All starch samples showed two peaks for amylopectin branches, as seen in many examples in the literature; the first component at X ≲ 34 is for chains confined to one lamella, and the second is for chains

Conclusion

This study examines, for the first time, the fine molecular structure of amylose and amylopectin extracted from duckweed starch and its relationship to starch degradation. Amylose and amylopectin CLDs are different between the samples, suggesting, as is well accepted, that starch biosynthesis in duckweed is affected by their nutritional conditions during plant growth and development. Correlations between structural fitting parameters suggested that amylose is perhaps synthesized by extension

Abbreviations

    AA

    alpha amylase

    AMG

    amyloglucosidase

    ANOVA

    analysis of variance

    ADP-glucose

    adenosine diphosphate glucose

    CLD

    chain-length distribution

    C

    undigested starch

    DB

    degree of branching

    DBE

    starch debranching enzymes

    DMSO

    dimethyl sulfoxide

    DP

    degree of polymerization

    GBSS

    granule-bound starch synthase

    k

    degradation rate coefficient

    LOS

    logarithm of slope

    NLLS

    non-linear least squares

    SBE

    starch branching enzyme

    SEC

    size-exclusion chromatography

    SS

    starch synthase

Compliance with ethical standards

This article does not contain any studies with human participants or animals.

Declaration of competing interest

The authors declare that they have no conflict of interest.

Acknowledgments

The authors would like to thank Dr. Bernadine Flanagan for helpful discussions and MM thanks Timothy Phillips for English editing. RGG gratefully acknowledges the support of a National Natural Science Foundation of China grant C1304013151101138 and Marcia Maria de Souza Moretti gratefully acknowledges the support of the Brazil scholarship FAPESP (BEPE process 2016/22136-0). A project funded by the Priority Academic Program of Jiangsu Higher Education Institutions.

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