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Cheng, H.N.; Asakura, T.; Suganuma, K.; Lagaron, J.M.; Melendez-Rodriguez, B.; Biswas, A. Polysaccharide Sequence Determination. Encyclopedia. Available online: https://encyclopedia.pub/entry/56129 (accessed on 14 April 2024).
Cheng HN, Asakura T, Suganuma K, Lagaron JM, Melendez-Rodriguez B, Biswas A. Polysaccharide Sequence Determination. Encyclopedia. Available at: https://encyclopedia.pub/entry/56129. Accessed April 14, 2024.
Cheng, Huai N., Tetsuo Asakura, Koto Suganuma, Jose M. Lagaron, Beatriz Melendez-Rodriguez, Atanu Biswas. "Polysaccharide Sequence Determination" Encyclopedia, https://encyclopedia.pub/entry/56129 (accessed April 14, 2024).
Cheng, H.N., Asakura, T., Suganuma, K., Lagaron, J.M., Melendez-Rodriguez, B., & Biswas, A. (2024, March 11). Polysaccharide Sequence Determination. In Encyclopedia. https://encyclopedia.pub/entry/56129
Cheng, Huai N., et al. "Polysaccharide Sequence Determination." Encyclopedia. Web. 11 March, 2024.
Polysaccharide Sequence Determination
Edit

NMR analysis combined with statistical modeling offers a useful approach to investigate the microstructures of biobased polymers. In particular, this approach may be used to study the microstructures of polysaccharides. If the polysaccharides are composed of two or three monosaccharide units, and the NMR spectral features are sensitive to the different sequence placements of these units, then a detailed analysis of a polysaccharide (or its fractions) can be made by NMR with the help of statistical modeling.   

alginate biobased polymers chitosan NMR pectin polysaccharides carbohydrates

1. Introduction

In recent years, polysaccharides have emerged as possible alternatives to synthetic plastics due to their abundant natural sources, renewability, and biodegradability [1][2]. Through appropriate modifications and/or processing techniques [3][4][5][6], polysaccharides can be transformed into a range of functional materials with properties suitable for packaging, biomedical applications, and various other industries.
As expected, the structure of polysaccharides can be studied with NMR [7][8][9], and the information available includes the composition, type, and degree of substituents, the presence of minor components and impurities, and sometimes even the number-average molecular weight. Moreover, NMR can be utilized in combination with other analytical techniques, such as methylation, esterification, fractionation, mass spectrometry, and chromatographic methods, to analyze complex polysaccharides or mixtures [10][11].
As for the use of NMR for the direct comonomer sequence determination of copolysaccharides, its feasibility depends on the polymers involved [7][8]. In some copolysaccharides, one or more NMR peaks in a saccharide residue of the polymer are split due to the sensitivity of the chemical shifts to the presence of different neighboring saccharide units. In this case, the split peaks need to be assigned to the appropriate sequences (e.g., diads, triads, or tetrads), and the percent distribution of the sequences can be determined by taking the areas of the resolvable peaks. However, if the NMR peaks of a copolysaccharide do not show resolvable peaks for different sequences, then NMR cannot be easily used for sequence determination for that copolymer. Three examples of polysaccharides where the NMR sequence peaks are resolvable are alginate, pectin, and chitosan. The NMR/statistical modeling of these polymers is shown below.

2. Alginate Mannuronic/Guluronic Sequence Analysis

Alginate is a naturally occurring polysaccharide found in various types of brown seaweed, including kelp and other marine brown algae [3][12][13]. It is used as a thickener, gelling agent, controlled release agent, coating, and stabilizing agent in the food industry, pharmaceuticals, and various other applications. Structurally, alginate is a linear copolymer made up of two types of monosaccharides: β-D-mannuronic acid (M) and α-L-guluronic acid (G). The sequence distribution of M and G residues along the polymer chain, as well as the overall composition (M-to-G ratio), determines many of the physical and chemical properties of alginate.
For alginate, 1H NMR can be used to compute overall composition (% M and % G), diad sequences, and G-centered triads, and 13C NMR can provide both M- and G-centered triad intensities. Previously, the NMR data of the whole polymer and fractions of alginate extracted from Laminaria digitata, as published in the literature [14][15], were analyzed [16], and four structural components were found: two mostly homopolymer blocks, one somewhat alternating copolymer block, and one or more random copolymer blocks.
An alternative approach is to use the hyphenated size exclusion chromatography (SEC)-NMR method [17][18]. The SEC instrument is connected to the NMR probe, and NMR spectra are obtained by stopping the flow during NMR data acquisition. Three commercial alginate samples were evaluated in this way. The NMR data were satisfactorily treated with two-component first-order Markov statistical models. The results were consistent with the earlier finding [16] that these alginate samples are compositionally heterogeneous, consisting of mixtures of components with different microstructures.
The NMR triad data for two commercial alginate samples with different M/G ratios were reported earlier by Kawarada et al. [19]. These data have been analyzed by both discrete and continuous models [20] and are reported. As an example of the analysis, the triad data and model results for the sample with a high M/G ratio are shown in Table 1 (column 2). The one-component B model clearly did not fit the data well (column 3, with a mean deviation of 5.4). In contrast, both the discrete two-component B/B model (column 4) and the continuous perturbed B model (column 5) gave a mean deviation of 0.6, indicating a much better fit with the observed data. Thus, this alginate sample was heterogeneous in M/G sequence distribution, just like the earlier alginate samples from L. digitata.
Table 1. The triad sequence intensities (in mole %) of a commercial alginate sample; observed triad data were taken from ref. [19].
NMR Triad Obsd
%
Discrete Models Continuous Model
Calc % (for B) Calc % (for B/B) Calc % (for Perturbed B)
MMM 39 39 39 39
MMG 17 29 19 18
GMG 8 5 7 7
MGM 10 14 9 9
GGM 14 11 14 15
GGG 12 2 12 12
Mean dev.   5.4 0.6 0.6
Reaction
probabilities
  PM = 0.731 Component 1:
w1 = 0.592
PM = 0.858
Component 2:
w2 = 0.408
PM = 0.338
PM = 0.648
σ = 0.253
τ = −0.004

3. Pectin Galacturonic Acid/Ester Sequence Analysis

Pectin is a well-known commercial product, typically produced from citrus peels and used as a gelling agent (especially in jams and jellies, dessert fillings, and sweets), as a food stabilizer in fruit juices and milk drinks, and as a source of dietary fiber [3][21][22]. It is commonly found in the cell walls of terrestrial plants. It has a complex structure, but the major functional unit is galacturonic acid. This acid can exist either as a carboxylic acid or as a methyl ester, and the plant can carry out this conversion enzymatically as needed. The gelling properties are related to the ratio of galacturonic acid to its ester. For high-methoxy (HM) pectin, pectin is usually mixed with sucrose to form a gel. For low-methoxy (LM) pectin, it is mixed with a calcium salt for gel formation. Thus, the amount and the placement of the acid and the ester along the polymer chain are important information for product development and formulation.
NMR is a good technique to measure the amount of acid/ester present in pectin, as well as the heterogeneity of their placements along the polymer chains [7]. It is known that selected peaks in 1H and 13C spectra are split by the acid/ester sequence effects so that the triad sequence distributions can be obtained. Analyses were previously reported for selected pectin samples using statistical modeling [23][24], and the data were shown to fit well to both discrete and continuous models. For illustration, the reported triad distribution data for an HM pectin sample [24] extracted from lemon peel are shown in column 2 of Table 2, where G and E denote galacturonic acid and the ester, respectively. The data were re-analyzed for three types of Bernoullian (B) models: a simple B model, a two-component (B/B) model, and a continuous perturbed B model. From the analysis shown in Table 5, the simple B model (column 3) gave a mean deviation of 1.2, the two-component B/B model (column 4) 0.6, and the perturbed B model (column 5) 0.4. Thus, the NMR triad sequence data suggest that the particular HM pectin sample was compositionally heterogeneous, and the NMR data could be fitted with either the two-component B/B model or the perturbed B model.
Table 2. The triad sequence analysis of an HM pectin sample; observed triad data were taken from ref. [24].
NMR Triad Obsd.
%
Discrete Models Continuous Model
Calc % (for B) Calc % (for B/B) Calc % (for Perturbed B)
EEE 32.4 32.4 32.5 32.4
EEG 28.0 29.5 28.0 27.5
GEG 6.4 6.7 7.1 6.7
EGE 13.0 14.8 14.0 13.8
GGE 14.0 13.5 14.0 13.4
GGG 6.2 3.1 4.4 6.2
Mean dev.   1.2 0.6 0.4
Reaction
probabilities
  PE = 0.687 Component 1:
w1 = 0.793
PE = 0.724
Component 2:
w2 = 0.207
PE = 0.489
PE = 0.675
σ = 0.118
τ = −0.008
A second example can be given using an LM pectin sample. The reported triad distribution data for such a sample (also from lemon peel) [24] are shown in column 2 of Table 3, and the analysis results of these data using the same three models are given in columns 3–5 of Table 3. In this case, the mean deviations for the three models (B, B/B, and perturbed B) were 0.8, 0.1, and 0.1, respectively, also suggesting that the NMR triad sequence data conformed better to the two-component B/B model or the continuous perturbed B model.
Table 3. The triad sequence analysis of an LM pectin sample; observed triad data were taken from ref. [24].
NMR Triad Obsd.
%
Discrete Models Continuous Model
Calc % (for B) Calc % (for B/B) Calc % (for Perturbed B)
EEE 2.1 1.6 2.4 2.5
EEG 10.6 9.6 10.6 10.6
GEG 13.4 14.1 13.3 13.3
EGE 5.5 4.8 5.3 5.3
GGE 26.7 28.2 26.7 26.6
GGG 41.7 41.7 41.7 41.7
Mean dev.   0.8 0.1 0.1
Reaction
probabilities
  PE = 0.253 Component 1:
w1 = 0.337
PE = 0.586
Component 2:
w2 = 0.159
PE = 0.414
PE = 0.264
σ = 0.0928
τ = 0.0003
The above analyses suggest that both HM pectin and LM pectin samples extracted from lemon peels are compositionally heterogeneous. In a separate work [17], pectin fractions from the same source material were analyzed in combination with NMR, and this is another way to confirm the compositional heterogeneity. Thus, NMR and statistical modeling can be helpful for the analysis of citrus pectin samples.

4. Sequence Analysis of Partially Deacetylated Chitosan

Chitin is abundant in the exoskeletons of crustaceans, insects, and fungi. Structurally, it is a homopolymer of 2-acetamido-2-deoxy-β-D-glucopyranose (GlcNAc). Chitosan is obtained by partially deacetylating chitin and may be regarded as a copolymer of GlcNAc units and 2-amino-2-deoxy-β-D-glucopyranose (GlcN) units [3][25][26]. Chitosan is a versatile polymer with a myriad of applications. Its unique properties, including biocompatibility, biodegradability, and non-toxicity, make it invaluable in various applications. It also has notable antimicrobial properties, making it a possible additive for use in wound healing, tissue engineering, and other medical products. Moreover, it is employed in the food and pharmaceutical industries for its ability to function as a natural preservative and a controlled delivery vehicle.
For partially deacetylated chitosan, the NMR spectra can detect chemical shift differences for the different sequences of acetylated and deacetylated units. Previously, the 1H and 13C NMR spectra of chitosan were published by Varum et al., who also reported the triad sequence intensities of selected samples [27][28]. The triad sequence intensities for one sample are shown in column 2 of Table 4. In an earlier analysis [29], the NMR data of chitosan were shown to be compatible with a compositionally heterogeneous polymer.
Table 4. The triad sequence analysis of partially deacetylated chitosan; observed triad data were taken from refs. [27][28].
NMR Triad Obsd.
%
Discrete Models Continuous Model
Calc % (for B) Calc % (for B/B) Calc % (for Perturbed B)
AAA 15 15 16 15
AAD 28 27 25 28
DAD 10 12 10 9
ADA 14 13 13 14
DDA 16 23 20 17
DDD 17 10 17 17
Mean dev.   3.0 1.5 0.4
Reaction
probabilities
  PA = 0.531 Component 1:
w1 = 0.906
PA = 0.357
Component 2:
w2 = 0.094
PA = 0.009
PA = 0.547
σ = 0.083
τ = −0.031
From the analysis of the results in Table 4, the use of the simple B model clearly gave a rather large mean deviation of 3.0 (column 3). In the two-component B/B model (column 4), a second minor component (9.4%) consisting of mostly deacetylated units (PA = 0.009) was incorporated, and the mean deviation was reduced to 1.5. The best result was found for the perturbed B model (column 5), where the mean deviation was cut down to 0.4. Thus, this chitosan sample was heterogeneous in composition, as shown by the analysis of NMR data with statistical modeling.

5. Comments

It may be noted that only some polysaccharides are amenable to being studied by the NMR/statistical methods described herein. First, the polysaccharide in question should have a structure that contains only two or three repeating units, thereby generating a manageable number of structural sequences. (Thus, a complex polysaccharide with many different types of monosaccharide units may be too complex to be studied; sometimes, fractionation or other separation procedures may be needed prior to NMR analysis.) Secondly, the different structural sequences should give detectable differences in the NMR spectra, typically through chemical shift differences. If the shift difference in a polymer spectrum is too small to be resolved by NMR, then NMR microstructural studies of this polymer will be difficult. However, as the NMR instrumentation continues to improve in sensitivity, resolution, and magnetic field strength [30][31], it is possible that small chemical shift differences may be resolvable in the future, thereby rendering more polymer microstructures accessible to NMR sequence analysis.

References

  1. Abe, M.M.; Martins, J.R.; Sanvezzo, P.B.; Macedo, J.V.; Branciforti, M.C.; Halley, P.; Botaro, V.R.; Brienzo, M. Advantages and Disadvantages of Bioplastics Production from Starch and Lignocellulosic Components. Polymers 2021, 13, 2484.
  2. Lim, C.; Yusoff, S.; Ng, C.G.; Lim, P.E.; Ching, Y.C. Bioplastic made from seaweed polysaccharides with green production methods. J. Environ. Chem. Eng. 2021, 9, 105895.
  3. Whistler, R.L.; BeMiller, J.N. (Eds.) Industrial Gums: Polysaccharides and their Derivatives, 3rd ed.; Academic Press: San Diego, CA, USA, 1993.
  4. Shaghaleh, H.; Xu, X.; Wang, S. Current progress in production of biopolymeric materials based on cellulose, cellulose nanofibers, and cellulose derivatives. RSC Adv. 2018, 8, 825–842.
  5. Cheng, H.N.; Biswas, A.; Furtado, R.F.; Alves, C.A. Hydrophobic Modifications of Agro-based Polymers—A Selected Review. ACS Symp. Ser. 2023, 1450, 249–258.
  6. Cheng, H.N. Use of green chemistry for process development and improvement. In Green Chemistry: Research and Connections to Climate Change; Benvenuto, M.A., Welch, L., Eds.; De Gruyter: Berlin, Germany; Boston, MA, USA, 2023; pp. 1–12.
  7. Cheng, H.N.; Neiss, T.G. NMR Spectroscopy of Food Polysaccharides in Solution. Polym. Rev. 2012, 52, 81–114.
  8. Yao, H.Y.; Wang, J.; Yin, J.; Nie, S.; Xie, M. A review of NMR analysis in polysaccharide structure and conformation: Progress, challenge and perspective. Food Res. Int. 2021, 143, 110290.
  9. Yang, L.; Zhang, L. Chemical structural and chain conformational characterization of some bioactive polysaccharides isolated from natural sources. Carbohydr. Polym. 2009, 76, 349–361.
  10. Ren, Y.; Bai, Y.; Zhang, Z.; Cai, W.; Flores, A.D.R. The Preparation and Structure Analysis Methods of Natural Polysaccharides of Plants and Fungi: A Review of Recent Development. Molecules 2019, 24, 3122.
  11. Pettolino, F.A.; Walsh, C.; Fincher, G.B.; Bacic, A. Determining the polysaccharide composition of plant cell walls. Nat. Protoc. 2012, 7, 1590–1607.
  12. Lee, K.Y.; Mooney, D.J. Alginate: Properties and biomedical applications. Prog. Polym. Sci. 2012, 37, 106–126.
  13. Pawar, S.N.; Edgar, K.J. Alginate derivatization: A review of chemistry, properties and applications. Biomaterials 2012, 33, 3279–3305.
  14. Grasdalen, H.; Larsen, B.; Smidsrod, O. 13C-n.m.r. studies of monomeric composition and sequence in alginate. Carbohydr. Res. 1981, 89, 179–191.
  15. Grasdalen, H. High-field ‘H-n.m.r. spectroscopy of alginate: Sequential structure and linkage conformations. Carbohydr. Res. 1983, 118, 255–260.
  16. Cheng, H.N. Compositional Heterogeneity of Alginates through NMR Analysis. Polym. Bull. 1999, 43, 247.
  17. Neiss, T.G.; Cheng, H.N. Analysis of Polysaccharides by NMR and Separation Techniques. ACS Polym. Prepr. 2001, 42, 76–77.
  18. Neiss, T.G.; Cheng, H.N. Coupled SEC-NMR Analysis of Alginates. ACS Symp. Ser. 2002, 834, 382–395.
  19. Kawarada, H.; Hirai, A.; Odani, H.; Lida, T.; Nakajima, A. Structure characterization of alginate and conformational behaviors of various alkali-metal alginates in solution. Polym. Bull. 1990, 24, 551–557.
  20. Cheng, H.N.; USDA-ARS-SRRC, New Orleans, LA, USA. Personal communication.
  21. Freitas, C.M.P.; Coimbra, J.S.R.; Souza, V.G.; Sousa, R.C.S. Structure and Applications of Pectin in Food, Biomedical, and Pharmaceutical Industry: A Review. Coatings 2021, 11, 922.
  22. Mohnen, D. Pectin structure and biosynthesis. Curr. Opin. Plant Biol. 2008, 11, 266–277.
  23. Neiss, T.G.; Cheng, H.N.; Daas, P.J.H.; Schols, H.A. NMR and statistical analysis of the galacturonic acid and methyl ester distributions in pectic polysaccharides. ACS Polym. Prepr. 1998, 39, 688–689.
  24. Neiss, T.G.; Cheng, H.N.; Daas, P.J.H.; Schols, H.A. Compositional Heterogeneity in Pectic Polysaccharides: NMR and Statistical Analysis. Macromol. Symp. 1999, 140, 165–178.
  25. Kou, S.G.; Peters, L.M.; Mucalo, M.R. Chitosan: A review of sources and preparation methods. Int. J. Biol. Macromol. 2021, 169, 85–94.
  26. Ali, A.; Ahmed, S. A review on chitosan and its nanocomposites in drug delivery. Int. J. Biol. Macromol. 2018, 109, 273–286.
  27. Varum, K.M.; Anthonsen, M.W.; Grasdalen, H.; Smidsrod, O. Determination of the degree of N-acetylation and the distribution of N-acetyl groups in partially N-deacetylated chitins (chitosans) by high-field n.m.r. spectroscopy. Carbohydr. Res. 1991, 211, 17–23.
  28. Varum, K.M.; Anthonsen, M.W.; Grasdalen, H.; Smidsrod, O. 13C-N.m.r. studies of the acetylation sequences in partially N-deacetylated chitins (chitosans). Carbohydr. Res. 1991, 217, 19–27.
  29. Cheng, H.N. Compositional Heterogeneity in NMR Polymer Analysis. ACS Polym. Prepr. 2003, 44, 261–262.
  30. Moser, E.; Laistler, E.; Schmitt, F.; Kontaxis, G. Ultra-High Field NMR and MRI—The Role of Magnet Technology to Increase Sensitivity and Specificity. Front. Phys. 2017, 5, 33, Corrigendum Front. Phys. 2017, 5, 41.
  31. Wren, E. Evidence that NMR Chemical Shifts Depend on Magnetic Field Strength. Chemistry World. 29 April 2020. Available online: https://www.chemistryworld.com/news/evidence-that-nmr-chemical-shifts-depend-on-magnetic-field-strength/4011613.article (accessed on 6 January 2024).
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