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Online multi-channel microfluidic chip-mass spectrometry and its application for quantifying noncovalent protein–protein interactions† Wu Liu, Qiushui Chen, Xuexia Lin and Jin-Ming Lin* To establish an automatic and online microfluidic chip-mass spectrometry (chip-MS) system, a device was designed and fabricated for microsampling by a hybrid capillary. The movement of the capillary was programmed by a computer to aspirate samples from different microfluidic channels in the form of microdroplets (typically tens of nanoliters in volume), which were separated by air plugs. The droplets were then directly analyzed by MS via paper spray ionization without any pretreatment. The feasibility and
Received 24th December 2014, Accepted 6th January 2015 DOI: 10.1039/c4an02370f www.rsc.org/analyst
performance were demonstrated by a concentration gradient experiment. Furthermore, after eliminating the effect of nonuniform response factors by an internal standard method, determination of the association constant within a noncovalent protein–protein complex was successfully accomplished with the MS-based titration indicating the versatility and the potential of this novel platform for widespread applications.
Microfluidic devices have aroused great interest due to the reduced analysis time and reagent consumption, high integration and throughput.1–4 During the past decade, the detection methods incorporated into microfluidic devices have been mainly optical5–8 and electrochemical sensors.9,10 Nevertheless, activities with the corresponding responses of the analytes are necessitated by these techniques. Mass spectrometry (MS) is a powerful tool for label-free, sensitive and simultaneous detection of multiple analytes, and therefore offers an attractive alternative detection approach for microfluidic systems.11,12 Recently, many efforts have been directed toward the coupling of microfluidic devices and MS.13–17 Biological applications including metabolite detection18–20 and intercellular communication21,22 were successfully implemented on chip-MS platforms. However, in most of these bioanalytical studies, MS detection was manipulated in the off-line mode: pretreatment of the samples was demanded in order to yield interpretable mass spectra. Although chromatographic or dialysis-based approaches might be introduced for online desalting,23,24 a significant reduction of the temporal resolution would also be introduced.
Beijing Key Laboratory of Microanalytical Methods and Instrumentation, Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China. E-mail: [email protected]; Fax: +86 10 62792343; Tel: +86 10 62792343 † Electronic supplementary information (ESI) available: General experimental details; volume and the time interval of sampled microdroplets; derivation of eqn (2) and (3) and other details mentioned in this communication. See DOI: 10.1039/c4an02370f
This journal is © The Royal Society of Chemistry 2015
Fig. 1 Setup for coupling multi-channel microfluidic chips with mass spectrometry by paper spray ionization of microdroplets. The integrated chip-MS system consists of four major components: the manipulator, the capillary, the PDMS microfluidic chip and the ionization unit. The operation of this sampling and online analytical system for multiple microfluidic channels relies on repeating the two general steps: (1) insert the capillary inlet into the “spy hole” of a microfluidic channel, when the liquid in the channel is suctioned into the capillary; (2) lift the capillary and move it to the “spy hole” of the next channel, during which process the air-plug enters the capillary and acts as the “barrier” between the samples. The paper applied with high voltage not only acts as the ionization source, but also offers a driving force for the flow in the capillary together with gravity. The manipulator is programmed by a controller, which is connected to a computer.
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Fig. 2 Generation and paper spray ionization-MS analysis of microdroplets from multi-channel microfluidic chips. (a) Sampled microdroplets in the capillary tube (inner diameter: 100 μm). (b) XIC at m/z 166.1 for the sample carry-over experiment: the first droplet (sample droplet) and the subsequent ones (“clean-up” droplets) were suctioned respectively from a channel infused with 0.1 mM phenylalanine and channels infused with water. (c) XIC at m/z 166.1 and 176.1 for the phenylalanine–citrulline concentration gradient experiment. Three droplets were sampled from each spy hole and the concentrations of the two initial solutions pumped into the microfluidic device were both 0.1 mM. (d) The peak area ratio calculated from XIC as a function of the concentration ratio between phenylalanine and citrulline in the droplets. Average mass spectra over the whole range of the respective peak for the droplets generated from microfluidic channel (e) #3 and (f ) #5.
Paper spray ionization, as a novel atmospheric pressure ESIbased technique,25,26 may be employed as the interface to bypass this difficulty. The matrix-tolerance of paper spray ionization enables immediate MS analysis without desalting processes.27 In our earlier work, direct localization of molecules in fruits and online chemical monitoring of cell culture were accomplished,28,29 which demonstrated the feasibility of interfacing droplet-based systems and online MS analysis by paper spray ionization. Herein, we have further constructed a microfluidic chip-MS platform, as shown in Fig. 1. A homemade device for microsampling by the cartridge droplet generation technique was utilized. The capillary was moved by a digital and automatic manipulator to aspirate and transport different samples, which were miniaturized into droplets of tens of nanoliters. Just as presented in our previous studies,28,29 the contents in these droplets were ionized by paper spray and detected by the mass spectrometer. Thinner capillaries would facilitate the generation of smaller droplets, but lead to a remarkable increment of the frictional resistance to the flow at the same time.29 To address this contradiction, a hybrid capillary was fabricated by fitting together two fused silica capillaries (20 cm × 100 μm i.d. ×
1552 | Analyst, 2015, 140, 1551–1554
164 μm o.d. and 5 cm × 20 μm i.d. × 90 μm o.d.). As a result, microdroplets with an average volume at 53.5 nL (RSD = 6.41%, n = 20; Fig. 2a) were sampled, segmented by air plugs and smoothly conducted to the spraying paper by the capillary, when the sampling and spacing time were set at 11.6 s and 8.4 s, respectively. No discernible leakage of the solution from the spy holes was observed during the operation of the system. Thus, MS monitoring at any position in the microchannels was principally possible. The volume and time interval of the droplets could be regulated by altering the sampling and spacing time (ESI, S5†). Based on a signal-to-noise (S/N) ratio of 3, the limit of detection (LOD) for phenylalanine was measured to be 2 μM. Although the presence of the “air barrier” could effectively prevent the merging of different samples, an overall carry-over of 10.74% was found, which is because of the molecule adsorption on the inner wall of the capillary (Fig. 2b). Thus, for experiments that require a high accuracy, a “clean-up droplet” is suggested following each sample droplet, in which case the risk of cross-contamination could be almost eliminated (∼1%). As a proof-of-principle study, a phenylalanine–citrulline concentration gradient was generated in a microfluidic chip to
This journal is © The Royal Society of Chemistry 2015
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Fig. 3 Direct and automatic microfluidic chip-paper spray ionization-MS assay for quantifying the self-association of Con A at pH 6.8. (a, b) Mass spectra obtained from the droplets including Con A at an analytical concentration ([D0]) of 4 μM, 20 μM in 100 mM ammonium acetate. (c) Plots of the ratio of areas under the peaks representing the dimeric populations of Con A and lysozyme (ID/IStd) versus those under the peaks representing the tetramer populations of Con A and lysozyme (IT/IStd). Lysozyme was spiked as the internal standard to the initial Con A solution at the concentration ratio of 1/10. The data fitting allowed the determination of the relative response factor R. (d) Plot of the ratio of areas under the peaks of dimers and tetramers (ID/IT) versus [D0]. The data fitting allowed the determination of the association constant (Ka) of dimer–tetramer interaction.
assess the performance of this method. For each droplet, the analytes could easily be identified (Fig. 2e, f; ESI, Fig. S4†), and the corresponding MS signal was displayed as an individual peak in the extracted ion chronogram (XIC). As shown in Fig. 2c, d, XIC at m/z 166.1 and 176.1 clearly reflects the relative abundance of the analytes in the droplets, since the peak area ratio shows an approximately linear correlation with the calculated concentration ratio. The intensities of droplets sampled from each spy hole and the time intervals also exhibited satisfactory reproducibilities. These results indicated the feasibility and practicality of this integrated microfluidic chipMS system. Moreover, we have proposed to apply this platform in MSbased titration for the quantitation of protein–protein interactions within noncovalent complexes. Direct ESI-MS assay is promising for the identification and quantification of protein– ligand interactions because of its simplicity, low sample and time consumption, and the ability to provide information on stoichiometry.30–32 Nevertheless, before it become a routine tool, there are still several methodological challenges, one of which is the automation of the technique.33 In this respect, chip-MS could play an important role. Besides, while paper spray ionization is free from the clogging problem, it also holds the softness comparable to nanospray ionization,26 which would benefit the determination of the dissociation constants (ESI, S9†).34,35 Dimer–tetramer equilibrium of concanavalin A (Con A) was employed as a model. By cascading two microfluidic concen-
This journal is © The Royal Society of Chemistry 2015
tration gradient generators with 6 channels and switching the connection interface, solutions of 25 (52) gradually-changed concentrations could be obtained and analyzed, acquiring the peak areas representing the dimeric (ID) and the tetrameric (IT) populations (Fig. 3a, b). However, the existence of nonuniform response factors for different analytes is a common source of error for quantitative MS analysis.33 To solve this problem, an internal standard (lysozyme) was introduced to the Con A solution to determine the relative response factor (R, as defined in eqn (1)). At each analytical concentration of Con A ([D0]) ranging from 0.8 to 20 μM, the peak-area ratios of Con A dimer and tetramer to lysozyme were measured (ID/IStd and IT/IStd). As shown in Fig. 3c, the value of R was thus determined to be 3.43 by fitting the curve to eqn (2) (for the derivation, see ESI, S7†). In the following, the ratio of ID to IT was plotted as a function of the analytical concentration of the dimer (D0), then the association constant Ka could be calculated utilizing eqn (3). By a nonlinear curve fitting (Fig. 3d), we have obtained a Ka value of (2.98 ± 0.06) × 104 M−1 at pH 6.8, which was consistent with the result ((4.1 ± 1.8) × 104 M−1) obtained by isothermal titration calorimetry (ITC).36 R¼
RT RD
IT RT ½D0 R I D ¼ I Std 2RStd ½Std 2 I Std
ð1Þ
ð2Þ
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Paper
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pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi I D 1 þ 1 þ 8K a ½D0 ¼ 2RK a ½D0 IT
ð3Þ
In summary, we have integrated MS with multi-channel microfluidics as an automatic, label-free and online analytical tool, with paper spray as the interface and ionization technique. Benefiting from these above unique features, the presented chip-MS has been successfully applied to the determination of the self-association constant of Con A. Therefore, with further developments, this platform holds great potential for applications such as in microfluidic-based large-scale in vitro drug screening, chemical monitoring of cellular metabolism and rapid point-of-care testing.
Acknowledgements This work was financially supported by the National Natural Science Foundation of China (no. 21227006, 91213305, and 81373373) and the China Equipment and Education Resources System (no. CERS-1-75).
Notes and references 1 A. J. DeMello, Nature, 2006, 442, 394–402. 2 E. W. Young and D. J. Beebe, Chem. Soc. Rev., 2010, 39, 1036–1048. 3 V. Sivagnanam and M. A. M. Gijs, Chem. Rev., 2013, 113, 3214–3247. 4 K. S. Elvira, X. C. I. Solvas, R. C. R. Wootton and A. J. DeMello, Nat. Chem., 2013, 5, 905–915. 5 W. Liu, H. Wei, Z. Lin, S. Mao and J.-M. Lin, Biosens. Bioelectron., 2011, 28, 438–442. 6 M. S. Wu, D. J. Yuan, J. J. Xu and H. Y. Chen, Chem. Sci., 2013, 4, 1182–1188. 7 M. Yu, D. T. Ting, S. L. Stott, B. S. Wittner, F. Ozsolak, S. Paul, J. C. Ciciliano, M. E. Smas, D. Winokur, A. J. Gilman, M. J. Ulman, K. Xega, G. Contino, B. Alagesan, B. W. Brannigan, P. M. Milos, D. P. Ryan, L. V. Sequist, N. Bardeesy, S. Ramaswamy, M. Toner, S. Maheswaran and D. A. Haber, Nature, 2012, 487, 510– 513. 8 Y. Wakamoto, N. Dhar, R. Chait, K. Schneider, F. Signorino-Gelo, S. Leibler and J. D. McKinney, Science, 2013, 339, 91–95. 9 K. Hsieh, A. S. Patterson, B. S. Ferguson, K. W. Plaxco and H. T. Soh, Angew. Chem., Int. Ed., 2012, 51, 4896–4900. 10 Y. Sameenoi, K. Koehler, J. Shapiro, K. Boonsong, Y. Sun, J. Collett, J. Volckens and C. S. Henry, J. Am. Chem. Soc., 2012, 134, 10562–10568. 11 S. Fritzsche, S. Ohla, P. Glaser, D. S. Giera, M. Sickert, C. Schneider and D. Belder, Angew. Chem., Int. Ed., 2011, 50, 9467–9470.
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12 L. M. Fidalgo, G. Whyte, B. T. Ruotolo, J. L. P. Benesch, F. Stengel, C. Abell, C. V. Robinson and W. T. S. Huck, Angew. Chem., Int. Ed., 2009, 48, 3665–3668. 13 D. Gao, H. Liu, Y. Jiang and J.-M. Lin, Lab Chip, 2013, 13, 3309–3322. 14 C. A. Croushore and J. V. Sweedler, Lab Chip, 2013, 13, 1666–1676. 15 X. He, Q. Chen, Y. Zhang and J.-M. Lin, TrAC Trends Anal. Chem., 2014, 53, 84–97. 16 Y. Su, Y. Zhu and Q. Fang, Lab Chip, 2013, 13, 1876–1882. 17 N. Gasilova, Q. Yu, L. Qiao and H. H. Girault, Angew. Chem., Int. Ed., 2014, 53, 4408–4412. 18 Q. Chen, J. Wu, Y. Zhang and J.-M. Lin, Anal. Chem., 2012, 84, 1695–1701. 19 S. Mao, D. Gao, W. Liu, H. Wei and J.-M. Lin, Lab Chip, 2012, 12, 219–226. 20 C. A. Croushore, S. Supharoek, C. Y. Lee, J. Jakmunee and J. V. Sweedler, Anal. Chem., 2012, 84, 9446–9452. 21 S. Mao, J. Zhang, H. Li and J.-M. Lin, Anal. Chem., 2013, 85, 868–876. 22 H. Wei, H. Li, S. Mao and J.-M. Lin, Anal. Chem., 2011, 83, 9306–9313. 23 J. Cavanagh, L. M. Benson, R. Thompson and S. Naylor, Anal. Chem., 2003, 75, 3281–3286. 24 D. Olivero, M. LaPlaca and P. A. Kottke, Anal. Chem., 2012, 84, 2072–2075. 25 J. Liu, H. Wang, N. E. Manicke, J.-M. Lin, R. G. Cooks and Z. Ouyang, Anal. Chem., 2010, 82, 2463–2471. 26 H. Wang, J. Liu, R. G. Cooks and Z. Ouyang, Angew. Chem., Int. Ed., 2010, 49, 877–880. 27 H. Wang, N. E. Manicke, Q. Yang, L. Zheng, R. Shi, R. G. Cooks and Z. Ouyang, Anal. Chem., 2011, 83, 1197– 1201. 28 W. Liu, N. Wang, X. Lin, Y. Ma and J.-M. Lin, Anal. Chem., 2014, 86, 7128–7134. 29 W. Liu, S. Mao, J. Wu and J.-M. Lin, Analyst, 2013, 138, 2163–2170. 30 A. J. R. Heck and R. H. H. van den Heuvel, Mass Spectrom. Rev., 2004, 23, 368–389. 31 C. V. Robinson, A. Sali and W. Baumeister, Nature, 2007, 450, 973–982. 32 M. Zhou, N. Morgner, N. P. Barrera, A. Politis, S. C. Isaacson, D. Matak-Vinkovic, T. Murata, R. A. Bernal, D. Stock and C. V. Robinson, Science, 2011, 334, 380– 385. 33 E. N. Kitova, A. El-Hawiet, P. D. Schnier and J. S. Klassen, J. Am. Soc. Mass Spectrom., 2012, 23, 431–441. 34 M. C. Jecklin, D. Touboul, C. Bovet, A. Wortmann and R. Zenobi, J. Am. Soc. Mass Spectrom., 2008, 19, 332–343. 35 Y. Zhang, Y. Ju, C. Huang and V. H. Wysocki, Anal. Chem., 2014, 86, 1342–1346. 36 E. Boeri Erba, K. Barylyuk, Y. Yang and R. Zenobi, Anal. Chem., 2011, 83, 9251–9259.
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Online multi-channel microfluidic chip-mass spectrometry and its application for quantifying noncovalent protein–protein interactions† Wu Liu, Qiushui Chen, Xuexia Lin and Jin-Ming Lin* To establish an automatic and online microfluidic chip-mass spectrometry (chip-MS) system, a device was designed and fabricated for microsampling by a hybrid capillary. The movement of the capillary was programmed by a computer to aspirate samples from different microfluidic channels in the form of microdroplets (typically tens of nanoliters in volume), which were separated by air plugs. The droplets were then directly analyzed by MS via paper spray ionization without any pretreatment. The feasibility and
Received 24th December 2014, Accepted 6th January 2015 DOI: 10.1039/c4an02370f www.rsc.org/analyst
performance were demonstrated by a concentration gradient experiment. Furthermore, after eliminating the effect of nonuniform response factors by an internal standard method, determination of the association constant within a noncovalent protein–protein complex was successfully accomplished with the MS-based titration indicating the versatility and the potential of this novel platform for widespread applications.
Microfluidic devices have aroused great interest due to the reduced analysis time and reagent consumption, high integration and throughput.1–4 During the past decade, the detection methods incorporated into microfluidic devices have been mainly optical5–8 and electrochemical sensors.9,10 Nevertheless, activities with the corresponding responses of the analytes are necessitated by these techniques. Mass spectrometry (MS) is a powerful tool for label-free, sensitive and simultaneous detection of multiple analytes, and therefore offers an attractive alternative detection approach for microfluidic systems.11,12 Recently, many efforts have been directed toward the coupling of microfluidic devices and MS.13–17 Biological applications including metabolite detection18–20 and intercellular communication21,22 were successfully implemented on chip-MS platforms. However, in most of these bioanalytical studies, MS detection was manipulated in the off-line mode: pretreatment of the samples was demanded in order to yield interpretable mass spectra. Although chromatographic or dialysis-based approaches might be introduced for online desalting,23,24 a significant reduction of the temporal resolution would also be introduced.
Beijing Key Laboratory of Microanalytical Methods and Instrumentation, Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China. E-mail: [email protected]; Fax: +86 10 62792343; Tel: +86 10 62792343 † Electronic supplementary information (ESI) available: General experimental details; volume and the time interval of sampled microdroplets; derivation of eqn (2) and (3) and other details mentioned in this communication. See DOI: 10.1039/c4an02370f
This journal is © The Royal Society of Chemistry 2015
Fig. 1 Setup for coupling multi-channel microfluidic chips with mass spectrometry by paper spray ionization of microdroplets. The integrated chip-MS system consists of four major components: the manipulator, the capillary, the PDMS microfluidic chip and the ionization unit. The operation of this sampling and online analytical system for multiple microfluidic channels relies on repeating the two general steps: (1) insert the capillary inlet into the “spy hole” of a microfluidic channel, when the liquid in the channel is suctioned into the capillary; (2) lift the capillary and move it to the “spy hole” of the next channel, during which process the air-plug enters the capillary and acts as the “barrier” between the samples. The paper applied with high voltage not only acts as the ionization source, but also offers a driving force for the flow in the capillary together with gravity. The manipulator is programmed by a controller, which is connected to a computer.
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Paper
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Fig. 2 Generation and paper spray ionization-MS analysis of microdroplets from multi-channel microfluidic chips. (a) Sampled microdroplets in the capillary tube (inner diameter: 100 μm). (b) XIC at m/z 166.1 for the sample carry-over experiment: the first droplet (sample droplet) and the subsequent ones (“clean-up” droplets) were suctioned respectively from a channel infused with 0.1 mM phenylalanine and channels infused with water. (c) XIC at m/z 166.1 and 176.1 for the phenylalanine–citrulline concentration gradient experiment. Three droplets were sampled from each spy hole and the concentrations of the two initial solutions pumped into the microfluidic device were both 0.1 mM. (d) The peak area ratio calculated from XIC as a function of the concentration ratio between phenylalanine and citrulline in the droplets. Average mass spectra over the whole range of the respective peak for the droplets generated from microfluidic channel (e) #3 and (f ) #5.
Paper spray ionization, as a novel atmospheric pressure ESIbased technique,25,26 may be employed as the interface to bypass this difficulty. The matrix-tolerance of paper spray ionization enables immediate MS analysis without desalting processes.27 In our earlier work, direct localization of molecules in fruits and online chemical monitoring of cell culture were accomplished,28,29 which demonstrated the feasibility of interfacing droplet-based systems and online MS analysis by paper spray ionization. Herein, we have further constructed a microfluidic chip-MS platform, as shown in Fig. 1. A homemade device for microsampling by the cartridge droplet generation technique was utilized. The capillary was moved by a digital and automatic manipulator to aspirate and transport different samples, which were miniaturized into droplets of tens of nanoliters. Just as presented in our previous studies,28,29 the contents in these droplets were ionized by paper spray and detected by the mass spectrometer. Thinner capillaries would facilitate the generation of smaller droplets, but lead to a remarkable increment of the frictional resistance to the flow at the same time.29 To address this contradiction, a hybrid capillary was fabricated by fitting together two fused silica capillaries (20 cm × 100 μm i.d. ×
1552 | Analyst, 2015, 140, 1551–1554
164 μm o.d. and 5 cm × 20 μm i.d. × 90 μm o.d.). As a result, microdroplets with an average volume at 53.5 nL (RSD = 6.41%, n = 20; Fig. 2a) were sampled, segmented by air plugs and smoothly conducted to the spraying paper by the capillary, when the sampling and spacing time were set at 11.6 s and 8.4 s, respectively. No discernible leakage of the solution from the spy holes was observed during the operation of the system. Thus, MS monitoring at any position in the microchannels was principally possible. The volume and time interval of the droplets could be regulated by altering the sampling and spacing time (ESI, S5†). Based on a signal-to-noise (S/N) ratio of 3, the limit of detection (LOD) for phenylalanine was measured to be 2 μM. Although the presence of the “air barrier” could effectively prevent the merging of different samples, an overall carry-over of 10.74% was found, which is because of the molecule adsorption on the inner wall of the capillary (Fig. 2b). Thus, for experiments that require a high accuracy, a “clean-up droplet” is suggested following each sample droplet, in which case the risk of cross-contamination could be almost eliminated (∼1%). As a proof-of-principle study, a phenylalanine–citrulline concentration gradient was generated in a microfluidic chip to
This journal is © The Royal Society of Chemistry 2015
View Article Online
Published on 06 January 2015. Downloaded by Seton Hall University on 27/04/2015 15:51:52.
Analyst
Paper
Fig. 3 Direct and automatic microfluidic chip-paper spray ionization-MS assay for quantifying the self-association of Con A at pH 6.8. (a, b) Mass spectra obtained from the droplets including Con A at an analytical concentration ([D0]) of 4 μM, 20 μM in 100 mM ammonium acetate. (c) Plots of the ratio of areas under the peaks representing the dimeric populations of Con A and lysozyme (ID/IStd) versus those under the peaks representing the tetramer populations of Con A and lysozyme (IT/IStd). Lysozyme was spiked as the internal standard to the initial Con A solution at the concentration ratio of 1/10. The data fitting allowed the determination of the relative response factor R. (d) Plot of the ratio of areas under the peaks of dimers and tetramers (ID/IT) versus [D0]. The data fitting allowed the determination of the association constant (Ka) of dimer–tetramer interaction.
assess the performance of this method. For each droplet, the analytes could easily be identified (Fig. 2e, f; ESI, Fig. S4†), and the corresponding MS signal was displayed as an individual peak in the extracted ion chronogram (XIC). As shown in Fig. 2c, d, XIC at m/z 166.1 and 176.1 clearly reflects the relative abundance of the analytes in the droplets, since the peak area ratio shows an approximately linear correlation with the calculated concentration ratio. The intensities of droplets sampled from each spy hole and the time intervals also exhibited satisfactory reproducibilities. These results indicated the feasibility and practicality of this integrated microfluidic chipMS system. Moreover, we have proposed to apply this platform in MSbased titration for the quantitation of protein–protein interactions within noncovalent complexes. Direct ESI-MS assay is promising for the identification and quantification of protein– ligand interactions because of its simplicity, low sample and time consumption, and the ability to provide information on stoichiometry.30–32 Nevertheless, before it become a routine tool, there are still several methodological challenges, one of which is the automation of the technique.33 In this respect, chip-MS could play an important role. Besides, while paper spray ionization is free from the clogging problem, it also holds the softness comparable to nanospray ionization,26 which would benefit the determination of the dissociation constants (ESI, S9†).34,35 Dimer–tetramer equilibrium of concanavalin A (Con A) was employed as a model. By cascading two microfluidic concen-
This journal is © The Royal Society of Chemistry 2015
tration gradient generators with 6 channels and switching the connection interface, solutions of 25 (52) gradually-changed concentrations could be obtained and analyzed, acquiring the peak areas representing the dimeric (ID) and the tetrameric (IT) populations (Fig. 3a, b). However, the existence of nonuniform response factors for different analytes is a common source of error for quantitative MS analysis.33 To solve this problem, an internal standard (lysozyme) was introduced to the Con A solution to determine the relative response factor (R, as defined in eqn (1)). At each analytical concentration of Con A ([D0]) ranging from 0.8 to 20 μM, the peak-area ratios of Con A dimer and tetramer to lysozyme were measured (ID/IStd and IT/IStd). As shown in Fig. 3c, the value of R was thus determined to be 3.43 by fitting the curve to eqn (2) (for the derivation, see ESI, S7†). In the following, the ratio of ID to IT was plotted as a function of the analytical concentration of the dimer (D0), then the association constant Ka could be calculated utilizing eqn (3). By a nonlinear curve fitting (Fig. 3d), we have obtained a Ka value of (2.98 ± 0.06) × 104 M−1 at pH 6.8, which was consistent with the result ((4.1 ± 1.8) × 104 M−1) obtained by isothermal titration calorimetry (ITC).36 R¼
RT RD
IT RT ½D0 R I D ¼ I Std 2RStd ½Std 2 I Std
ð1Þ
ð2Þ
Analyst, 2015, 140, 1551–1554 | 1553
View Article Online
Paper
Analyst
Published on 06 January 2015. Downloaded by Seton Hall University on 27/04/2015 15:51:52.
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi I D 1 þ 1 þ 8K a ½D0 ¼ 2RK a ½D0 IT
ð3Þ
In summary, we have integrated MS with multi-channel microfluidics as an automatic, label-free and online analytical tool, with paper spray as the interface and ionization technique. Benefiting from these above unique features, the presented chip-MS has been successfully applied to the determination of the self-association constant of Con A. Therefore, with further developments, this platform holds great potential for applications such as in microfluidic-based large-scale in vitro drug screening, chemical monitoring of cellular metabolism and rapid point-of-care testing.
Acknowledgements This work was financially supported by the National Natural Science Foundation of China (no. 21227006, 91213305, and 81373373) and the China Equipment and Education Resources System (no. CERS-1-75).
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