Letter pubs.acs.org/journal/ascecg
Direct Analysis of Succinic Acid Fermentation Broth by 1H DiffusionOrdered NMR Spectroscopy and Quantitative 1H NMR Technique Limin Wang,‡ Ying Yang,† Haiyan Yang,† Ruchen Qiu,*,‡ and Shaohua Huang*,† †
Shandong Provincial Key Laboratory of Synthetic Biology, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, No. 189 Songling Road, Laoshan District, Qingdao 266101, People’s Republic of China ‡ College of Chemical Engineering, Qingdao University of Science and Technology, No. 53 Zhengzhou Road, Sifang District, Qingdao 266042, People’s Republic of China S Supporting Information *
ABSTRACT: The diffusion-ordered NMR spectroscopy (DOSY) protocol was first introduced to analyze directly the mixture samples of succinic acid fermentation broth. The NMR signals of the model mixtures and the practical mixture were facilely separated, and each component was fully assigned in the diffusion dimension of DOSY spectra. The composition of succinic acid fermentation broth could be rapidly determined according to the DOSY experiments. In contrast, this qualitative analysis could not be implemented through ionchromatography technique. On the basis of DOSY experimental results, the quantitative 1H NMR (qHNMR) technique was further used to determinate successfully the components of one mixture sample of practical fermentation broth, which agreed well with the high-performance liquid chromatographic experimental result. The excellent qualitative and quantitative analysis results demonstrate that the DOSY technique and the qHNMR technique can play a great role in the determination of the product quality of succinic acid fermentation broth. KEYWORDS: Succinic acid fermentation broth, Diffusion-ordered NMR spectroscopy, Quantitative 1H NMR technique, Qualitative analysis, Quantitative analysis
■
tography is still time-consuming.15 Therefore, it is significant for the development of the analytic method for succinic acid fermentation broth. Recently, DOSY is often utilized as a noninvasive technique to involve the separation of NMR signals corresponding to individual component in a mixture.16 It allows NMR signals of different species to be distinguished by the different diffusion coefficients of the components. The diffusion coefficients related to the separated components are plotted on the vertical axis (F1), whereas the chemical shifts in the spectrum yielded by each component are plotted on the horizontal axis (F2). In general, diffusion coefficient (D) is closely related to molecular weight (MW), molecular size and shape, sample temperature, and viscosity of the system under analysis according to the Stokes−Einstein eq 1:
INTRODUCTION As an important C4 platform chemical, succinic acid is widely used as the precursor of numerous products, such as pharmaceuticals, food additives, green solvents, and biodegradable polymers.1−4 Over the past decades, succinic acid is usually prepared from the petroleum-based raw materials, which are expensive with severe environmental pollution.5 Therefore, much attention has been paid to the microbial fermentation of succinic acid production due to the reproducibility and the environmental friendliness.6,7 It is considered as a sustainable pathway to yield succinic acid. As we well-known, some byproducts, such as formic acid, ethanol, acetic acid (Scheme 1), are usually yielded in the process of microbial fermentation of succinic acid production.8 These byproducts could influence the quality of succinic acid. Hence, it is important to determine these components in a fermentation broth.9 As reported in literatures, various chromatographic methods had been used to analyze the components of succinic acid fermentation broth, but with many disadvantages. For instance, high-performance liquid chromatography (HPLC) with refractive index detection suffers from the poor sensitivity and the high cost of eluent;10,11 gas chromatography (GC) has to confront the inconvenience of silylation;12,13 ion-exclusion chromatography needs the expensive chromatography columns;14 and thin layer chroma© 2017 American Chemical Society
D=
kT 6πηrs
(1)
Received: December 28, 2016 Revised: March 10, 2017 Published: March 17, 2017 2824
DOI: 10.1021/acssuschemeng.6b03184 ACS Sustainable Chem. Eng. 2017, 5, 2824−2828
Letter
ACS Sustainable Chemistry & Engineering Scheme 1. Simplified Scheme of Actinobacillus succinogenes Metabolic Pathwaysa
a
Dotted lines, EMP not a step reaction; EMP, glycolysis pathway; PEPCK, PEP carboxykinase; PK, pyruvate kinase; OAAdec, oxaloacetate decarboxylase; MDH, malate dehydrogenase; MF, malic enzyme; FM, fumarase; FR, fumarate reductase; PFL, pyruvate formate-lyase; ADH, alcohol dehydrogenase; AK, acetate kinase.
Figure 1. 2D 1H DOSY spectrum recorded at 600 MHz in D2O of sample 1 at 298 K.
As expected, the components of sample 1 were well separated in the diffusion dimension of DOSY spectrum. From top to bottom in the spectrum, glucose (MW = 180) (Da = 5.78 × 10−10 m2 s−1), succinic acid (MW = 118) (Da = 7.59 × 10−10 m2 s−1), acetic acid (MW = 60) (Da = 10.40 × 10−10 m2 s−1), ethanol (MW = 46) (Da = 10.64 × 10−10 m2 s−1), and formic acid (MW = 46) (Da = 12.76 × 10−10 m2 s−1) showed their corresponding signals, respectively. Glucose had a minimal diffusion value due to its maximal MW. With the decrease of MW, succinic acid and acetic acid displayed the increasing diffusion values, respectively. Interestingly, ethanol and formic acid revealed different diffusion values although these two compounds have the same MWs. We consider that the distinguished diffusions were due to the different solvation of these two solutes.22 Ethanol has one hydrophobic group (CH3CH2−) and one hydrophilic group (HO−) and formic acid has only one hydrophilic group (HOOC−). Formic acid holds stronger hydration power than ethanol due to the forceful hydrogen-bond and/or ion−dipole interactions between HOOC− group and water, thus forming a compact hydration shell around the formic acid molecule. Ethanol has also a hydration shell due to the hydrophilic group (HO−). However, this hydration shell may grow large because there is a hydrophobic layer inside of the hydration shell due to the hydrophobic group (CH3CH2−).23 This large incompact hydration shell around the ethanol molecule could hinder the molecular motion of ethanol in aqueous phase, which leads to a less diffusion value for ethanol than formic acid. According to this DOSY experiment, we could easily determine the presence of each component in the mixture and make a rough estimate of how much succinic acid would be yielded. Noticeably, the standard deviation (SD) values of the diffusion coefficients for these analytes are available (Table 1), meaning DOSY technique is valid in analysis of sample 1. To demonstrate further the potential of the DOSY technique, another model mixture of six organic acids in D2O (sample 2, please see the sample preparation in the SI) was designed and used to be performed by this new method (Figure 2). In this case, six components, which could be present in the succinic acid fermentation process, were determined according
where k is the Boltzmann constant, T is the temperature, η is the viscosity of the liquid, and rs is the (hydrodynamic) radius of the molecule.17,18 Because the signals from different compounds are disentangled without the need for physical separation, DOSY is also considered as a pseudo separation. The main advantages of this technique include operational convenience, robustness, and economy.19 Therefore, the DOSY technique has begun to be used in analysis of biological samples.20,21 In this study, the DOSY technique was first introduced as an alternative method for the analysis of components in a succinic acid broth sample. Glucose, succinic acid, formic acid, ethanol, and acetic acid were selected as the model compounds to mimic fermentation broth because these five compounds often occur in the Actinobacillus succinogenes metabolic C3 pathway. LTartaric acid, L-malic acid, fumaric acid, maleic acid, citric acid, and succinic acid were chosen for the another organic acid model compounds because these six compounds are usually produced in the A. succinogenes metabolic C4 pathway. It was found that the DOSY technique can effectively distinguish the signals of each component in these two model mixtures. It was also available when using DOSY to analyze a practical sample of succinic acid fermentation. Furthermore, we used the qHNMR technique to determinate the components of the practical fermentation broth, which was in accord with the HPLC experimental result.
■
RESULTS AND DISCUSSION 2D 1H DOSY Analysis. Figure 1 displays the 1H DOSY spectrum (please see the parameter specification in the Supporting Information (SI)) of a mixture of glucose, succinic acid, formic acid, ethanol, and acetic acid in D2O (sample 1, please see the sample preparation in the SI). All signals of the same component were indicated by color dotted lines according to the characteristic chemical shifts of the corresponding compounds. The MWs and diffusion values (including the mean diffusion values of three measurements, Da) for the analytes in sample 1 are summarized and tabulated in Table 1. 2825
DOI: 10.1021/acssuschemeng.6b03184 ACS Sustainable Chem. Eng. 2017, 5, 2824−2828
Letter
ACS Sustainable Chemistry & Engineering Table 1. Molecular Weights and Diffusion Values of the Analytes in Sample 1
a
compound
MW
D1 (10−10 m2 s−1)
D2 (10−10 m2 s−1)
D3 (10−10 m2 s−1)
Da (10−10 m2 s−1)a
SDb
glucose succinic acid acetic acid ethanol formic acid
180 118 60 46 46
5.52 7.31 10.00 10.21 12.30
5.90 7.67 10.47 10.81 12.90
5.92 7.79 10.73 10.90 13.08
5.78 7.59 10.40 10.64 12.76
0.23 0.25 0.37 0.38 0.41
Da is the mean value of Dn, which is the diffusion value of the same analyte in three measurements. bSD is calculated according to the following
formula: SD =
2
∑in= 1(Dn − Da )2 (n − 1)
× 10−10 m2 s−1), fumaric acid (MW = 116) (Da = 7.50 × 10−10 m2 s−1), and maleic acid (MW = 116) (Da = 8.05 × 10−10 m2 s−1) were also recognized in the spectrum according to their exclusive chemical shifts although they have similar MWs, even fumaric acid is the isomeric compound of maleic acid. These three compounds are all dicarboxylic acids with different molecular structures, thus leading to different solvation in solvent. Therefore, succinic acid, fumaric acid, and maleic acid displayed different diffusion behaviors. This demonstrates that molecular size and shape could actually influence the diffusions of components. It is significant for DOSY technique to separate the compounds with similar molecular structures by means of this property. In contrast, the chromatographic techniques, such as HPLC, GC, and ion chromatography (IC) may fail to meet the demand of analysis for these similar compounds. For instance, we used IC technique to analyze the model mixture of sample 2, but with unsatisfactory separation result (Figure 3). It is found that the peaks of malic acid and succinic acid were completely overlapping. Fumaric acid and maleic acid suffered from the same trouble. And tartaric acid was also not separated baseline. Only citric acid was fully separated from the other five organic acids. This chromatographic result corroborates the merit of the DOSY technique. Finally, a practical mixture of succinic acid fermentation broth (sample 3, please see the sample preparation in the SI) was selected to illustrate the application of the DOSY technique. Experimentally, it is found that the 2D 1H DOSY spectrum of sample 3 was clean with only three components with different D values (Figure 4). According to the characteristic chemical shifts of all compounds of sample 1, it is verified that the component with a D value of 5.87 × 10−10 m2 s−1 was glucose, the one with a D value of 6.24 × 10−10 m2 s−1 was succinic acid, and the one with a D value of 8.95 × 10−10 m2 s−1 was acetic acid. The other signals could not match the chemical shifts of all compounds in sample 1, therefore they could be regarded as other unknown byproducts. From this result, we could successfully perform the qualitative analysis of sample 3, demonstrating the DOSY technique is robust and can work well for the practical mixture.
Figure 2. 2D 1H DOSY spectrum recorded at 600 MHz in D2O of sample 2 at 298 K.
to the different D values and their chemical shifts, and were indicated by color dotted lines. The MWs and diffusion values for the analytes in sample 2 are summarized and tabulated in Table 2. It was found that the component with a minimal D value (Da = 5.94 × 10−10 m2 s−1) was citric acid due to its largest MW (192). Surprisingly, L-tartaric acid (MW = 150) (Da = 7.35 × 10−10 m2 s−1) diffused faster than L-malic acid (MW = 134) (Da = 6.56 × 10−10 m2 s−1). This interesting phenomenon should be due to their different solvation. In L-tartaric acid, two hydroxyl groups can form two hydrogen-bonds with two carboxyl groups, whereas in L-malic acid, only one hydroxyl group makes one hydrogen-bond with one carboxyl group, and the other carboxyl group has to interact with aqueous phase. Therefore, L-malic acid can form a larger hydration shell than Ltartaric acid, thus leading to a less diffusion value for L-malic acid than L-tartaric acid. Succinic acid (MW = 118) (Da = 7.59
Table 2. Molecular Weights and Diffusion Values of the Analytes in Sample 2 compound
MW
D1 (10−10 m2 s−1)
D2 (10−10 m2 s−1)
D3 (10−10 m2 s−1)
Da (10−10 m2 s−1)a
SDb
citric acid L-tartaric acid L-malic acid succinic acid fumaric acid maleic acid
192 150 134 118 116 116
5.78 6.49 6.16 7.40 7.42 7.75
5.96 7.66 6.51 7.68 7.44 8.18
6.08 7.90 7.01 7.69 7.64 8.22
5.94 7.35 6.56 7.59 7.50 8.05
0.15 0.55 0.43 0.16 0.12 0.26
a,b
Given in Table 1. 2826
DOI: 10.1021/acssuschemeng.6b03184 ACS Sustainable Chem. Eng. 2017, 5, 2824−2828
Letter
ACS Sustainable Chemistry & Engineering
hydrogen number of TMSP, MWc is the MW of component, MW TMSP is the MW of TMSP, Cc is the calculated concentration of component, and CTMSP is standard concentration of TMSP. Integral values of each component, obtained from the qHNMR spectrum (see Figure S1 in the SI), are summarized and tabulated in Table S1 (SI). And the results of the qHNMR experiment are presented in Table 3. Table 3. Results of Quantitative Analysis for Sample 3 by qHNMR Technique and HPLC Technique compound succinic acid glucose acetic acid
qHNMR (g L−1)
HPLC (g L−1)
practical succinic acid fermentation broth (g L−1)a
0.2782
0.3151
13.91
0.5923 0.2242
0.5622 0.2574
29.62 11.21
a
The concentration of the practical succinic acid fermentation broth is the 50 times of the sample 3 measured by the qHNMR technique.
Figure 3. IC separation of sample 2 on the ICS-5000 with conductivity detection. Peaks: 1, L-malic acid; 2, succinic acid; 3, L-tartaric acid; 4, fumaric acid; 5, maleic acid; 6, citric acid. Chromatographic conditions: mobile phase, 30 mM KOH aqueous solution; flow rate, 1.0 mL min−1; column temperature, 303 K.
To confirm the accuracy of the qHNMR methodology, sample 3 was also measured by quantitative HPLC technique (see Figure S2 in the SI), and the corresponding results are also given in Table 1. As a result, the qHNMR experiment shows that sample 3 contained 0.2782 g L−1 of succinic acid, 0.5923 g L−1 of glucose, and 0.2242 g L−1 of acetic acid, meaning the practical succinic acid fermentation broth held 13.91 g L−1 of succinic acid, 29.62 g L−1 of glucose, and 11.21 g L−1 of acetic acid. The calculated concentrations of the three main components in the fermentation broth by these two different quantitative methods were approximately consistent with each other. However, the qHNMR technique is simpler and more convenient than the HPLC technique both in sample preparation and in operation.
■
CONCLUSIONS In this study, the DOSY technique could be effectively used to determine directly the compositions of two model mixtures and one practical mixture of succinic acid fermentation broth. Each component in the mixtures was fully separated and well assigned according to the corresponding diffusion coefficient and chemical shift. Interestingly, the compounds with same or similar MWs were clearly distinguished in the DOSY spectra according to their different solvation. However, these compounds could not be separated baseline by the IC technique. The peaks of some isomers were even completely overlapping in the IC chromatogram. Moreover, the composition of the practical mixture sample was further quantitatively determined by the qHNMR technique, which was consistent with the HPLC experimental result. Therefore, the DOSY technique and the qHNMR technique provide an alternative powerful protocol for the analysis of succinic acid fermentation broth.
Figure 4. 2D 1H DOSY spectrum recorded at 600 MHz in D2O of sample 3 at 298 K.
Quantitative 1H NMR Analysis. Based on the qualitative analysis of the practical mixture of sample 3, the qHNMR technique was applied to determine quantitatively the composition of glucose, succinic acid, and acetic acid. The 1H NMR spectrum was recorded at 600 MHz in D2O using the Bruker pulse sequence ZG, and the concentration of each component was calculated according to eq 2: Cc =
Ic ITMSP
N MWc × TMSP × × C TMSP Nc MWTMSP
■
ASSOCIATED CONTENT
S Supporting Information *
The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acssuschemeng.6b03184.
(2)
where Ic is the integral of component, ITMSP is the integral of TMSP, Nc is the hydrogen number of component, NTMSP is the
Experimental methods and supplementary data (PDF) 2827
DOI: 10.1021/acssuschemeng.6b03184 ACS Sustainable Chem. Eng. 2017, 5, 2824−2828
Letter
ACS Sustainable Chemistry & Engineering
■
metabolites in fermenting wheat straight-dough reveals succinic acid as pH-determining factor. Food Chem. 2013, 136, 301−308. (15) Agarwal, L.; Isar, J.; Saxena, R. K. Rapid screening procedures for identification of succinic acid producers. J. Biochem. Biophys. Methods 2005, 63, 24−32. (16) Cohen, Y.; Avram, L.; Frish, L. Diffusion NMR spectroscopy in supramolecular and combinatorial chemistry: an old parameter–new insights. Angew. Chem., Int. Ed. 2005, 44, 520−554. (17) Huang, S.; Gao, J.; Wu, R.; Li, S.; Bai, Z. Polydimethylsiloxane: a general matrix for high-performance chromatographic NMR spectroscopy. Angew. Chem., Int. Ed. 2014, 53, 11592−11595. (18) Johnson, C. S. Diffusion ordered nuclear magnetic resonance spectroscopy: principles and applications. Prog. Nucl. Magn. Reson. Spectrosc. 1999, 34, 203−256. (19) Evans, R.; Day, I. J. Matrix-assisted diffusion-ordered spectroscopy. RSC Adv. 2016, 6, 47010−47022. (20) Ge, W.; Zhang, J. H.; Pedersen, C. M.; Zhao, T.; Yue, F.; Chen, C.; Wang, P.; Wang, Y.; Qiao, Y. DOSY NMR: a versatile analytical chromatographic tool for lignocellulosic biomass conversion. ACS Sustainable Chem. Eng. 2016, 4, 1193−1200. (21) Qiao, Y.; Pedersen, C. M.; Huang, D.; Ge, W.; Wu, M.; Chen, C.; Jia, S.; Wang, Y.; Hou, X. NMR study of the hydrolysis and dehydration of inulin in water: comparison of the catalytic effect of lewis acid SnCl4 and brønsted acid HCl. ACS Sustainable Chem. Eng. 2016, 4, 3327−3333. (22) Yang, Y.; Wu, R.; Huang, S.; Bai, Z. Silica sol assisted chromatographic NMR spectroscopy for resolution of trans- and cisisomers. J. Magn. Reson. 2016, 265, 210−214. (23) Laurette, S.; Treizebre, A.; Affouard, F.; Bocquet, B. Subterahertz characterization of ethanol hydration layers by microfluidic system. Appl. Phys. Lett. 2010, 97, 111904−111906.
AUTHOR INFORMATION
Corresponding Authors
*R. Qiu. E-mail:
[email protected]. *S. Huang. E-mail:
[email protected]. ORCID
Shaohua Huang: 0000-0003-2407-949X Notes
The authors declare no competing financial interest.
■
ACKNOWLEDGMENTS We gratefully acknowledge the financial aid for this work by the National Natural Science Foundation of China (grant number 21105108) and the Chinese Academy of Sciences Key Technology Talent Program (2015). We appreciate the donated sample of practical succinic acid fermentation broth from Key laboratory of based materials of Chinese Academy of Sciences.
■
REFERENCES
(1) Bechthold, I.; Bretz, K.; Kabasci, S.; Kopitzky, R.; Springer, A. Succinic acid: a new platform chemical for biobased polymers from renewable resources. Chem. Eng. Technol. 2008, 31, 647−654. (2) Zeikus, J. G.; Jain, M. K.; Elankovan, P. Biotechnology of succinic acid production and markets for derived industrial products. Appl. Microbiol. Biotechnol. 1999, 51, 545−552. (3) Delhomme, C.; Weuster-Botz, D.; Kuehn, F. E. Succinic acid from renewable resources as a C4 building-block chemicala review of the catalytic possibilities in aqueous media. Green Chem. 2009, 11, 13−26. (4) Li, S. L.; Zeng, J.; Wu, F.; Yang, Y.; Wang, Y. Z. Succinic acid based biodegradable thermoplastic poly(ester urethane) elastomers: effects of segment ratios and lengths on physical properties. Ind. Eng. Chem. Res. 2014, 53, 1404−1414. (5) Zhu, S.; Bo, T.; Wang, X.; Long, M. Separation of succinic acid from aqueous solution by macroporous resin adsorption. J. Chem. Eng. Data 2016, 61, 856−864. (6) Harry-O’kuru, R. E.; Gordon, S. H.; Klokkenga, M. Biogeneration of succinic acid by fermentation of physaria fendleri seed polysaccharides. Ind. Crops Prod. 2015, 77, 116−122. (7) Meynial-Salles, I.; Dorotyn, S.; Soucaille, P. A new process for the continuous production of succinic acid from glucose at high yield, titer, and productivity. Biotechnol. Bioeng. 2008, 99, 129−135. (8) Sun, L.; Zhang, H.; Yuan, H.; Tu, R.; Wang, Q.; Ma, Y. A doubleenzyme-coupled assay for high-throughput screening of succinic acidproducing strains. J. Appl. Microbiol. 2013, 114, 1696−1701. (9) Munson, M. S.; Karp, E. M.; Nimlos, C. T.; Salit, M. L.; Beckham, G. T. Gradient elution moving boundary electrophoresis enables rapid analysis of acids in complex biomass-derived streams. ACS Sustainable Chem. Eng. 2016, 4, 7175−7185. (10) Bradfield, M. F. A.; Nicol, W. Continuous succinic acid production from xylose by actinobacillus succinogenes. Bioprocess Biosyst. Eng. 2016, 39, 233−244. (11) Wang, C.; Ming, W.; Yan, D.; Zhang, C.; Yang, M.; Liu, Y.; Zhang, Y.; Guo, B.; Wan, Y.; Xing, J. Novel membrane-based biotechnological alternative process for succinic acid production and chemical synthesis of bio-based poly (butylene succinate). Bioresour. Technol. 2014, 156, 6−13. (12) Lee, D. G.; Park, J. H.; Yun, J. H.; Song, M. C.; Ahn, E. M.; Chung, I. S.; Baek, N. I. Alternative extraction technique for the quantitative analysis of succinic acid in a chitosan-succinic acid powder mixture using GC-MS. Food Sci. Biotechnol. 2011, 20, 1609−1614. (13) Poulin, J.; Helwig, K. Class Id resinite from Canada: a new subclass containing succinic acid. Org. Geochem. 2012, 44, 37−44. (14) Jayaram, V. B.; Cuyvers, S.; Lagrain, B.; Verstrepen, K. J.; Delcour, J. A.; Courtin, C. M. Mapping of saccharomyces cerevisiae 2828
DOI: 10.1021/acssuschemeng.6b03184 ACS Sustainable Chem. Eng. 2017, 5, 2824−2828
