Comparison of various sampling materials - Facile sampling of sweat combined with direct analys

CHAPTER 3: Facile sampling of sweat combined with direct analysis of

3.3.4 Comparison of various sampling materials

The goal of this experiment was to find a suitable material for sampling sweat from skin.

We have tested five different materials (Table 3.1). The commercial plasters were most convenient because they have an adhesive layer and can be applied to human skin without safety concerns. Other materials tested (filter paper, Teflon) had other advantages, for

example, they have greater sorptive capabilities, or they are more resistant to solvents than the adhesive plasters.

We further carried out analysis of the sample targets (without samples present), which were chosen for sampling sweat directly from human skin (Table 3.1). Initially, we recorded a nanoDESI spectrum of a commercial plaster (A, cf. Table 3.1). As shown in Figure 3.4, spectral background in the positive-ion mode is quite strong. The high peak at the m/z 149 is attributed to the common plasticizer: phthalic anhydride (molecular weight: 148.1 g mol^-1).

Another high peak, at the m/z 145 can be attributed to polyethylene glycol present in the solvent mixture used. The high background is due to the high sensitivity of MS; in other words, even little qualities of contaminants cause high background. We also found that the plaster A gave high spectral background in the negative-ion mode (see section 3.3.4).

One important parameter of the sample support is the wettability of the surface by solvents. The glue-coated area of the plaster is hydrophobic; therefore, it is more compatible with the nanoDESI setup. When using the fabric area of the plaster for analysis, we found that the liquid bridge formed between the two capillaries was not stable, and much higher flow rates had to be used. In the positive-ion mode, a high spectral background was observed – in particular when using filter paper and Teflon tape as blank sample targets (Figure 3.5). In the positive-ion mode, most of the signals found in the spectra of plasters A, B and C essentially correspond to the solvent blank. However, in the negative-ion mode, we observed significant differences in the mass spectra recorded with different materials (Figure 3.6). Plaster A shows a spectral profile similar to the solvent spectrum recorded without any sample support (i.e. solvent blank). On the other hand, the analysis of plasters B and C yielded signals at the m/z 121 and m/z 165. Unfortunately, we could not identify the corresponding substances.

Since plaster A relatively has a simple spectral background, we chose it for further work.

Figure 3.4. A positive-ion mode nano-DESI mass spectrum of plaster A (cf. Table 3.1). No sample has been deposited. The solvent mixture used in this nanoDESI experiment was composed of methanol and acetonitrile in the volume ratio 1:1, spiked with acetic acid (final concentration,  0.1%). Several signals can be observed; for example, the peak at the m/z 149 is most probably related to phthalic anhydride (molecular weight: 148.1 g mol^-1), which is frequently used as plasticizer in consumer products.

The other materials tested appear to be less suitable sample supports for nanoDESI-MS operated in the negative-ion mode. Although these materials might have absorbed considerable volumes of sweat, they did not accommodate stable operation of the nanoDESI setup. In these cases, the liquid junction formed by the nanoDESI solvent was not stable due to a higher wettability as compared with the glue-coated plaster area. Therefore, we conclude that plaster A is a more compatible sampling material with the nanoDESI-MS system.

Figure 3.5. A blank nanoDESI mass spectrum recorded in the positive-ion mode; no sample target was present in the solvent junction area. The solvent used in this nanoDESI experiment was pure methanol (LC-MS grade). Comparison of different solvent systems used in nanoDESI experiments is presented in Table 3.2.

Figure 3.6. Comparison of negative-ion mode nanoDESI mass spectra obtained for various materials tested in this study. No samples were spotted. The solvent used in this nanoDESI experiment was pure methanol (LC-MS grade).

56 3.3.5 Analysis of a sweat sample

In the next experiment, we attempted using the nanoDESI-MS platform in the analysis of a real sample. A 2-µL aliquot of the liquid sample was spotted on the plaster A, and it was dried before analysis. Subsequently, we placed the plaster A beneath the liquid junction of the nano-DESI interface. The solvent mixture used in this nanoDESI experiment was composed of methanol and acetonitrile in the volume ratio 1:1, and it was spiked with acetic acid (final concentration,  0.1%). Figures 3.7 and 3.8 present the results obtained in the positive- and negative-ion modes, respectively.

Figure 3.7. Analysis of a dry sweat deposit on plaster A by nanoDESI-MS operated in the positive-ion mode.

Initially, the sweat sample was centrifuged at 8000 rpm for 20 min, and subsequently filtered using a 0.2-μm syringe filter. The solvent mixture used in this nanoDESI-MS experiment was composed of methanol and acetonitrile in the volume ratio 1:1, spiked with acetic acid (final concentration,  0.1%).

Figure 3.8. Analysis of a dry sweat deposit on plaster A by nanoDESI-MS operated in the negative-ion mode.

The MS signals from contaminants recorded in the positive-ion mode were relatively high. Some of the peaks present in these spectra cannot be found in the blank spectrum (cf.

Figure 3.4), which suggests that these may be metabolites present in sweat. Nevertheless, we

could not find the peaks corresponding to two metabolites which are normally abundant in sweat: urea and creatinine.⁶⁹ Interestingly, in the negative-ion mode, we could see a high peak at the m/z 187. In an attempt to identify the corresponding metabolite, we carried out tandem MS analysis of this ion; however, we could not observe any significant fragment peaks even we amplify the drive level of Ion trap. Based on the a database search (Human Metabolome Database, Edmonton, Canada),⁷⁰ we suspect that this peak may correspond to N-acetyl-L-glutamine (molecular weight: 188 g mol^-1), which is normally found in human

urine and is the acetylated form of the most abundant amino acid glutamine found in skeletal muscle tissue.⁷¹ The intensities of other MS signals in the negative-ion mode were also higher than in the blank. However, due to possible overlap, based on the current data, it is hard to judge on the possibility to detect other metabolites. For example, a peak at the m/z 255 appeared in the blank spectrum of pure methanol (Figure 3.6), and a relatively high peak at the same m/z was observed in the real sample. This peak could potentially be assigned to palmitic acid (molecular weight: 256 g mol^-1). Overall, the high signal of N-acetyl-L-glutamine may suggest that (i) this compound is highly abundant in sweat, (ii) this compound has a high ionization efficiency in nanoDESI, or (iii) a combination of both.

In summary, we have demonstrated the feasibility of the analysis of sweat deposited on plaster by nanoDESI-MS. We have carried out optimization of solvent system, and pre-selected the sampling material. We have also analysed a real sample, deposited on adhesive plaster by nanoDESI-MS.

3.3.6 Direct sampling of sweat from skin followed by nanoDESI-MS

The next step in this project was an attempt to analyze metabolites sampled directly from skin (i.e. without the intermediate steps of collecting liquid samples, and pretreatment).

The plaster was attached to skin of a volunteer for  1 h: during this period, the metabolites secreted with sweat were supposed to adsorb on the glue-coated surface of the plaster A. The plasters were subsequently analyzed by nanoDESI-MS without further treatment. The solvent mixture used in this nanoDESI-MS experiment was composed of methanol and acetonitrile in the volume ratio 1:1, spiked with acetic acid (final concentration,  0.1%). The quality of positive-ion spectra (Figure 3.9) was comparable to that in the previous experiment with sample pretreatment (Figure 3.7). For example, in one test, the volunteer who donated their

sweat samples drank a cup of coffee just before the sampling; however, we could not find the anticipated peak of caffeine at the m/z 195 (Figure 3.9). On the other hand, in the negative-ion mode, a strong signal at the m/z 187 was recorded (Figure 3.10). Other signals – which were observed in the blank spectra in the negative-ion mode (cf. Figure 3.6) – had lower intensity; most probably due to ion suppression. The signal-to-noise ratios of the peak at the m/z 187, in the spectra obtained during the analysis of the liquid sample (Figure 3.8), and the “dry” sample collected directly on the plaster, were similar (Figure 3.10). Therefore, the basic concept of facile sampling (using passive samplers) used in conjunction with the nanoDESI-MS detection has been shown. However, further optimization of the sampling and the detection systems is necessary in order to detect not just one ‒ but many ‒ metabolites with high sensitivity.

Figure 3.9. Analysis of a dry sweat collected directly on the plaster A by nanoDESI-MS operated in the positive-ion mode. The solvent mixture used in this nanoDESI-MS experiment was composed of methanol and acetonitrile in the volume ratio 1:1, spiked with acetic acid (final concentration,  0.1%).

Figure 3.10. Analysis of a dry sweat collected directly on the plaster A by nanoDESI-MS operated in the negative-ion mode. The solvent mixture used in this nanoDESI-MS experiment was composed of methanol and acetonitrile in the volume ratio 1:1, spiked with acetic acid (final concentration,  0.1%).

In an attempt to improve the quality of the mass spectra, we also tested pure methanol (LC-MS grade) as the nanoDESI solvent. Although the spectral background became lower, the sensitivity (as judged based on m/z 187) also decreased (Figure 3.11). The knowledge – regarding spectral quality and sensitivity – gathered in this study – is presented in Table 3.2.

Based on the current results, we advocate using the solvent mixture composed of methanol and acetonitrile in the volume ratio 1:1, spiked with acetic acid (final concentration,  0.1%), as the nanoDESI solvent. We also suggest using high-purity (LC-MS) grade chemicals (acetonitrile, acetic acid) in future work. We conclude that the analysis of sweat samples by nano-DESI-MS combined with plaster-based sampling is more promising in the negative-ion mode than in the positive-ion mode.

Figure 3.11. Analysis of a sweat sample on plaster A, following incubation of the plaster with skin of a volunteer, using nanoDESI-MS operated in the negative-ion mode. The solvent mixture used in this nanoDESI-MS experiment was pure methanol (LC-MS grade).

3.3.7 The influence of sampling time

In the final experiment, we evaluated the influence of sampling time on the signal-to-noise ratio. A series of samples were collected at varied sampling times: from 1 to 300 s. Interestingly, already after 10 s, a peak at the m/z 187 could be recorded (Figure 3.12).

The signal-to-noise ratio generally increased with the sampling time. The result confirms that sweat is secreted by skin all the time, and plaster patches can readily be used to collect samples of sweat from skin prior to the analysis by MS.

Figure 3.12. Analysis of a sweat sample on plaster A, following incubation of the plaster with skin of a volunteer, using nanoDESI-MS operated in the negative-ion mode. The sampling time was varied (1 – 300 s). The solvent mixture used in this nanoDESI-MS experiment was composed of methanol and acetonitrile in the volume ratio 1:1, spiked with acetic acid (final concentration,  0.1%).

63 recorded by mass spectrometer. For example, creatine and urea could be detected in the dry sample deposits. We further optimized the way of collecting sweat samples as well as the key parameters of the nanoDESI-MS method in order to ensure satisfactory quality of mass spectra. The optimized parameters included: type of sampling material, nanoDESI solvent system, as well as the MS ion mode. It is noteworthy that the presented analytical method takes advantage of commercial plasters as simple sampling tools which enable facile collection of sweat samples. We have found that such plasters are also compatible with the nanoDESI-MS setup used as the main analytical platform. Signal of metabolite (N-acetyl-L-glutamine) could be detected by nanoDESI-MS following a very short sampling period (a few seconds). In future, one can apply this method to sweat analysis and further clinical diagnosis of sweat. The biggest problem observed during the development of this

Solvent Baseline Sensitivity

MeOH/Acetonitrile 0.1% acetic acid +++ +++

MeOH/ACN ++ +

MeOH + ++

Acetonitrile ++ +

method was a relatively high spectral background due to the contamination signals the solvent system or sampling plasters. To mitigrate this problem high quality solvents adoption should be used in future work. Although commercial plasters are a convenient facilitating tool, they may also contribute to spectral background. To further develop this method, one needs to find or develop more reliable materials that would not increase the spectral noise, and could concerntrate metabolites at the same time. In addition, one may consider using this simple sampling method with another ion source, for example direct analysis in real time (DART)⁷² and easy ambient sonic-spray ionization EASI⁷³.

CHAPTER 4:

Conclusions

This reasearch work has led to the development of two methods for the analysis of metabolites in different kinds of biological samples by mass spectrometry. In the first study, we have developed a protocol for the analysis of small metazoan samples by matrix-assisted laser desorption/ionization mass spectrometry. The study has shown the feasibility of isotopic labeling of fruit flies with the purpose of pursuing metabolic effects of the circadian clock and environmental cues by mass spectrometry. The results also reveal a substantial metabolic inertia of the circadian clock: once adapted to the day/night cycle, the incorporation of ¹³C to UDP-Glc was not significantly altered by acute perturbation of the illumination cycle. We believe the method may also help to explore other biochemical phenomena in fruit fly as well as other metazoan species, which are commonly studied as model biological organisms. In the second part of this work, we have proposed application of adhesive plasters as sampling tools for sweat and subsequent analysis of such samples by nanospray desorption electrospray ionization. Following a short contact of plaster with skin (a few seconds), we could record one peak corresponding to a metabolite. The development of new sampling materials, which could reduce ion supperssion and enhance sensitivity, is needed. If successful, in future, the method may find applications in analysis and doping control. Overall, the work shows a broad applicability of mass spectrometric platforms in the analysis of metabolites in biological

samples. We have successfully used mass spectrometry in the analysis of different kinds of samples (microscale biological specimens and sweat). This confirms that, mass spectrometry can play an important role in future discoveries in bioscience.

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