Chapter 3. Pinch-valve interface for automated sampling and monitoring of dynamic
3.3.4. Application in time-resolved extraction of plant tissue samples
To further demonstrate the capabilities of the proposed automated sampling system, we applied it in time-resolved monitoring of the extraction of a real sample (fresh peel of citrus fruit). In this experiment, the sample vial was filled with 5 mL of pure acetonitrile, incubated at 25
C, and shaken. At time “zero”, a small fragment of freshly obtained fruit peel was
inserted to the vial, and the monitoring started. As the chromatograms were recorded, the increasing signals of certain plant metabolites could readily be observed. For example, the on-line extraction of lemon peel led to the emergence of several signals, including those identified as limonene, pinene and terpinene (Figures 3.12 and 3.13), which are abundant ingredients of citrus fruit.104, 105 In the case of lemon, the signals of the three identified metabolites became strong after 30 min extraction, and they were constant till the end of the experiment (Figure 3.12A). In the case of the kumquat sample, a substantial amount of limonene was extracted immediately on contact with extractant (Figure 3.12B). The time-resolved extraction profiles provide information on the availability of target analytes for extraction. In fact, a previous study – conducted in this laboratory (N.B. also utilizing universal electronic modules) – clearly demonstrated the usefulness of time-resolved extraction monitoring to reveal extractability of sample/specimen constituents.106 Although no generalizations can be made based on the limited number of real samples, the current result proves that the method can reveal differences in extractability of selected plant tissue specimens. The extraction monitoring in real time – enabled by the proposed analytical system – can further facilitate optimization of extraction conditions by reducing the number of manual operations to minimum.Figure 3.12 Monitoring extraction of real samples in real time. Time evolution of the extraction profiles.
Extraction solvent: 5 mL acetonitrile. Temperature: 25 C. Shaking speed: 20 rpm. Internal standard:
10-5 M thymol. (A) Lemon peel (m = 3.81 mg): (●) limonene, (▓) pinene, (▲) terpinene. (B) Kumquat peel (m = 4.00 mg): (●) limonene. The analyses were conducted in duplicate and representative results are displayed.
54
Figure 3.13 Monitoring extraction of the lemon peel sample in real time. Extraction solvent: 5 mL acetonitrile.
Temperature: 298 K. Shaking speed: 20 rpm. Internal standard: 10-5 M thymol. (A) EIC at m/z 93 0.5 u e-1 obtained at time “zero” (right after inserting the sample to the extraction solvent), and (B) EIC at m/z 93 0.5 u e-1 obtained at a later stage of extraction (140 min). These mass spectra are from the same experiment as the one illustrated in Figure 3.12A.
3.4. Summary
We have demonstrated a simple device for automated sampling of dynamic chemical processes, and instantaneous analysis by GC-MS. The device coupled with a GC-MS apparatus is easy to use. It also offers the advantage of reducing the extent of mechanical operations during sampling and analysis. As exemplified in this report, it enables analyses of dynamic processes such as enzymatic reaction and extraction. The optimum conditions for these processes (e.g. temperature, shaking) can readily be achieved and maintained. One disadvantage of using this system is that the septum of the injector has to be replaced often in order to prevent leakage of the carrier gas. This problem can readily be rectified by substituting septum with a metal plate to which the needle of the injection system could be soldered permanently. Another consideration is that the current setup is mainly applicable to
55
short term monitoring since a few hundred microliters are withdrawn from the sample chamber – depleting the medium of reaction or extraction. This issue can be mitigated by using larger volumes of reaction/extraction solvents, in which case the depletion of solvent during sampling would only have negligible effect on the analysis result. To further improve the quantitative aspects of the presented method, it is suggested that isotopically labeled internal standards are used as additives to the reaction or extraction mixtures. Nonetheless, when doing so, attention must be paid so as to avoid experimental artifacts (by possible shifting of the reaction/extraction equilibria). Overall, we envisage that the proposed system can further be used for monitoring, optimization, and mechanistic studies on other chemical and biochemical processes. Following additional alterations to the valve unit assembly and the program, one might also consider coupling this system with other types of analytical instruments (for example, mass spectrometers, without separation systems), which would increase the range of potential applications. It is also interesting to note that – in this study – we have demonstrated the usefulness of a popular microcomputer (Raspberry Pi) in the construction of automated analytical systems, thus expanding the application realm of universal electronic modules in chemistry laboratories. Down this path, we believe that such miniature electronic systems will soon become an indispensable component of the instrumental tacklebox in chemistry, enticing industrious analysts into development of automated systems for a wide range of analytical tasks.
56
Chapter 4.
Summary and conclusions
In the two studies described above, mass spectrometry-based methods have been developed and used in the enzymatic reaction monitoring.
In the first study (Chapter 2), an atmospheric pressure ionization mass spectrometric method was implemented in the analysis of a bienzymatic reaction in a high aspect ratio cell.
Using this simple analysis system, we demonstrated chemical signal transduction due to the progress of the enzymatic reaction in real time. The non-labelled and isotopically labeled ATP was used to trigger the reaction. This allowed us to disentangle the contributions of passive and active transport. The use of isotopic label helped to overcome the repeatability problems associated with experimental instabilities. The results shown in this thesis may give the aspect of mimicking the signal transduction triggered by ATP in model reaction and observe the behavior of bioautocatalytic reaction processes. also, others enzyme catalyzed reaction can be monitoring by this method.
In the second study (Chapter 3), we developed an automated injection system for sampling and temporal analysis of dynamic samples. In this system, all the electronic elements were controlled by the Raspberry Pi microcomputer programmed in C language. The system automatically withdrew aliquots of samples from the vial (e.g. reaction chamber) and transferred them to the injection port of a GC-MS apparatus. Transesterification was selected as a model of enzymatic reaction to demonstrate the capabilities of the proposed approach.
The reaction was catalyzed by immobilized lipase beads. For the first time, we demonstrated the ability to monitor transesterification reaction catalyzed by single beads of lipase. Catalytic heterogeneity of immobolized beads of lipase was revealed. The interesting thing is that catalytic activities of lipase beads and beads size are not correlated. It shows that the immobilized lipase biocatalyst is not uniform. Furthermore, using this system, we demonstrated real-time monitoring of extraction of biological samples. Terpenes from plant tissue sample were identified. Quantitative analysis of of transesterification of product and the extracted terpene species were accomplished. We expect that this automated system can be further used not only in enzyme assay, but also in other applications. For example, it may potentially be used to monitor wastewater discharge by factory, and evaluate the level of pollutants or toxic substances in the environment.
57
Appendix
Permission for Figure 1.3 (reproduced from ref.28)
Permission for Figure 1.7 (reproduced from ref.41)
58
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