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Breath gas monitoring during a glucose challenge by a combined PTR-QMS/GC×GC-TOFMS approach for the verification of potential volatile

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Journal of Breath Research J. Breath Res. 10 (2016) 036003 doi:10.1088/1752-7155/10/3/036003

J. Breath Res.

10

Paper 2016 Breath gas monitoring during a glucose challenge by a combined received © 2016 IOP Publishing Ltd 4 March 2016 PTR-QMS/GC×GC-TOFMS approach for the verification of potential revised 19 May 2016 JBROBW volatile biomarkers accepted for publication 30 May 2016 Beate Gruber1,3, Stefan Keller2, Thomas Groeger1,4, Georg Matuschek1,5, Wilfried Szymczak2 published 036003 1,3 24 June 2016 and Ralf Zimmermann 1 Joint Mass Spectrometry Centre, Comprehensive Molecular Analytics, Helmholtz Zentrum München, Ingolstädter Landstr. 1, B Gruber et al Neuherberg 85764, Germany 2 Research Unit Medical Radiation Physics and Diagnostics, Helmholtz Zentrum München, Ingolstädter Landstr. 1, Neuherberg 85764, Germany 3 Joint Mass Spectrometry Centre, Chair of Analytical Chemistry, University of Rostock, Dr. Lorenz Weg 1, Rostock 18059, Germany 4 Author to whom any correspondence should be addressed 5 Present address: Research Unit Medical Radiation Physics and Diagnostics, Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany Printed in the UK E-mail: [email protected]

Keywords: volatile organic compounds (VOCs), short chain fatty acids (SCFA), glucose , needle trap device (NTD), JBR needle trap micro extraction (NTME), glucose test, comprehensive 2D gas chromatography–time-of-flight mass spectrometry (GC×GC-TOFMS)

10.1088/1752-7155/10/3/036003 Supplementary material for this article is available online

3 Abstract Breath gas profiles, which reflect metabolic disorders like , are the subject of scientific focus.

1752-7155 Nevertheless, profiling is still a challenging task that requires complex and standardized methods. This study was carried out to verify breath gas patterns that were obtained in previous proton- transfer reaction–quadrupole mass spectrometry (PTR-QMS) studies and that can be linked to 1 glucose metabolism. An experimental setup using simultaneous PTR-QMS and complementary highly time-resolved needle trap micro extraction (NTME) combined with comprehensive 2D 11 gas chromatography–time-of-flight mass spectrometry (GC×GC-TOFMS) was established for the analysis of highly polar volatile organic compounds (VOCs). The method was applied to the breath gas analysis of three volunteers during a glucose challenge, whereby subjects ingested a glucose solution orally. Challenge responsive PTR-QMS target VOCs could be linked to small n-carbonic (C2–C4) alcohols and short chain fatty acids (SCFA). Specific isomers could be identified by simultaneously applied NTME-GC×GC-TOFMS and further verified by their characteristic time profiles and concentrations. The identified VOCs potentially originate from bacteria that are found in the oral cavity and gastrointestinal tract. In this study breath gas monitoring enabled the identification of potential VOC metabolites that can be linked to glucose metabolism.

1. Introduction depth so far [15–18] like [19–23], which is controversially discussed in [9, 14]. Volatolomics is of growing interest for screening and Halbritter et al [13] successfully applied on-line diagnosis of the health state [1–3]. Breath breath gas analysis by proton-transfer reaction–quad- analysis offers potential advantages for the medical rupole mass spectrometry (PTR-QMS) for the screen- diagnosis of (early stage) diseases over analysis ing of gestational diabetes mellitus (GDM). Challenge including that breath testing is non-invasive and responsive mass-to-charge ratios (m/z) during an oral painless [4–9]. For instance, diabetic state related glucose tolerance test (oGTT) could be correlated with metabolic changes could be monitored by the GDM diagnosis. Specific m/z signals were tentatively exhaled breath profile [10–14], but only a few breath associated with potential metabolites, mostly highly 24 gas compounds have been investigated more-in- polar compounds like alcohols and acids, but could not

June © 2016 IOP Publishing Ltd

2016 J. Breath Res. 10 (2016) 036003 B Gruber et al be identified distinctly due to the limitations of PTR- described by Trefz et al [59], broadens the application QMS. Generally, it is not possible to separate isomeric to point-of-care breath analysis. and isobaric compounds by the applied PTR-QMS. The main objective of this study was the identifi- Besides, interfering compounds, fragmentation pro- cation of individual components behind selected m/z cesses and the formation of clusters affect PTR-QMS values, found to be significant by PTR-QMS during a results [24]. glucose challenge. To benefit from highly sensitive and Many studies are focused on monitoring changes highly selective off-line analytical methods, the simul- in concentration of target volatile organic compounds taneous application and the comparison of the results (VOCs) in breath as in pharmacokinetic studies is a promising step [34]. With this aim, an analytical [25–27] or metabolic tracer tests [28–30]. Here, on- method for the off-line time-resolved breath gas analy- line real-time analysis based on direct inlet and soft sis based on automated NTME and GC×GC-TOFMS, ionization–mass spectrometric approaches including which complies with the restrictions during a paral- proton-transfer reaction–mass spectrometry (PTR- lel on-line PTR-QMS sampling, was established. This MS [13, 27–29, 31–35]), selected ion flow tube–mass technique was optimized for time resolution to enable spectrometry (SIFT-MS [36–38]), single-photon the comparison with highly time-resolved PTR-QMS ioniz­ation–time-of-flight mass spectrometry (SPI- data and for highly polar compounds including short TOFMS [39, 40]) and secondary electrospray ioniz­ chain fatty acids (SCFA) as they were associated as ation–mass spectrometry (SESI-MS [41, 42]) have potential target metabolites in preliminary studies. So been reported in literature. Nevertheless, off-line far, these compounds have not been the focus in breath screening of human breath samples is still an essential gas analysis in connection with diabetes research [9]. step for discovery [6, 38, 43–45]. GC-MS is The off-line analysis of SCFA in breath needed a spe- considered as the ‘gold standard’ in off-line breath gas cial adaption, because of their high polarity and vola- analysis [46]. Compared to GC-MS, comprehensive tility. As a further significant step, the paper presents 2D gas chromatography–time-of-flight mass spec- the simultaneous application of on-line PTR-QMS and trometry (GC×GC-TOFMS) offers significant advan- off-line NTME-GC×GC-TOFM during a glucose chal- tages including higher sensitivity due to the refocusing lenge of three volunteers for the comprehensive moni- during the modulation step and higher selectivity by toring of dynamic changes in concentration of highly increasing the separation capacity [47]. GC×GC- volatile compounds. In the end a characterization of the TOFMS has been proven to be a powerful molecular obtained breath profiles is discussed. profiling technique for the study of VOCs in exhaled human breath [2, 48–52]. Due to the high moisture 2. Methods content, the off-line analysis of exhaled breath is quite challenging and requires a sophisticated adaption of 2.1. Chemicals and materials the sampling as well as analysis method to the part­ A SilcoCan® containing calibration gas standards in icular sampling situation. Off-line GC×GC-TOFMS concentrations of approximately 1 ppmv was obtained analysis of human breath gas has been applied in com- from Ionicon Analytik GmbH (Innsbruck, Austria). bination with pre-concentration techniques such as Gaseous chemical standards for method evaluation were multibed sorption tubes [48, 49, 53], solid phase micro generated and humidified to 100% relative humidity (RH) extraction (SPME) [51] and needle trap micro extrac- at 37 °C by means of a gas calibration unit (GCU-a, Ionicon tion (NTME) by needle trap devices (NTDs) [50]. Analytik GmbH) and filled in 1 l gas sampling bags (Supel™- A simultaneous application of comprehensive off- Inert) from Sigma-Aldrich Chemie GmbH (Schnelldorf, line analytical techniques and highly time-resolved Germany) immediately before sampling. By usage of on-line methodology offers some benefits for the GCU-a concentration ranges from 0.2 ppbv–90 ppbv monitoring and characterization of dynamic breath (optimal concentration ranges from 0.4 ppbv–20 ppbv) profiles during metabolic challenges. King et al [29] could be generated for compounds included in the 1 demonstrated the suitability of combined on- and off- ppmv multi-component gas standard. For the generation line breath gas analysis for the characterization of rapid of higher concentrations (>90 ppbv) and gas standards changes in concentrations of breath gas compounds containing further relevant compounds like acids, under exercise conditions. However, for pre-concen- liquid reference standards were purchased from Sigma- tration by means of SPME as well as multibed sorption Aldrich Chemie GmbH (Schnelldorf, Germany) and tubes the use of gas sampling bags or other storage con- evaporated by means of a liquid calibration unit (LCU, tainers is inevitable [54]. By comparison, breath sam- Ionicon Analytik GmbH) up to 100% RH at 40 °C. The pling using NTME has been proven to be a powerful dilution of deuterated reference standards for internal tool for the identification and quantification of VOCs in standardization (ISTD) was done by evaporation in 0.5 breath gas by direct sampling [50, 55–60]. NTME ena- l gas bulbs from Th.Geyer (Renningen, Germany) using bles time-resolved sampling due to enhanced detection gas tight syringes purchased from Hamilton (Bonaduz, limits, reduced sampling volume and sampling time Switzerland). Details of the reference standards are [59]. Automatic, on-site alveolar breath gas sampling given in the supporting information (stacks.iop.org/ by NTDs using a portable sampling device, previously JBR/10/036003/mmedia).

2 J. Breath Res. 10 (2016) 036003 B Gruber et al

Figure 1. Schematic representation of the experimental setup for end-tidal breath gas sampling by automated NTME in parallel to PTR-QMS. The volunteer breathes out into the buffered end-tidal sampler (BET) a, which is connected to the PTR-QMS. The NTD b is fixed to the BET. Sampling is triggered by a CO2-sensor c and automated using a sampling case d, consisting of a pump d1, mass flow controller d2, particle filter d3, vacuum controller d4 and NTD valve connection d5. Adapted with permission from Hakim et al [62].

The glucose challenge was carried out with an with the blood glucose meter ACCU-CHEK® Aviva Accu-Chek Dextro O.G.-T. solution (Roche Pharma Nano prior to glucose administration, after 30 min and AG, Mannheim, Germany) consisting of glucose syrup, after 60 min by the volunteers. blackcurrant juice, potassium sorbate and purified Figure 1 shows a schematic representation of the water (contains 0.01–0.06 Vol.% alcohol). For blood experimental setup for end-tidal breath gas sampling glucose measurements an ACCU-CHEK® Aviva Nano by automated NTME in parallel to PTR-QMS using a (Roche Pharma AG), Fine Touch lancets from TER- commercially available sampling case for NTDs from UMO® (Eschborn, Germany) and ACCU-CHEK Aviva PAS Technology Deutschland GmbH (Magdala, Ger- test strips (Roche Pharma AG) were used. many) including a pump, a mass flow controller, a par- In this study triple bed 22-gauge NTDs packed with ticle filter, a vacuum controller and a valve connection 1 cm of Tenax TA, Carbopack X and Carboxen 1000 for the NTD. CO2-controlled sampling was ensured by respectively, made by Shinwa Chemical Industries connection of a Capnostat 5 mainstream CO2-sensor Ltd. (Kyoto, Japan), were used. Prior to each usage the from Respironics (Pittsburgh, USA) via a custom- NTDs were conditioned at 300 °C under permanent made interface (Roth ITK, Munich, Germany) with a nitrogen flow in a special custom-made heating device rise time of less than 100 ms. The volunteers exhaled from PAS Technology (Magdala, Germany). The NTDs continuously at regular intervals through the one-way were sealed on both ends with Teflon caps and stored mouthpiece into the buffered end-tidal sampler (BET in purged glass tubes from SciLabware Ltd. (Stafford- sampler) from Ionicon Analytik GmbH (Innsbruck, shire, United Kingdom) immediately before and after Austria), which was connected to the PTR-QMS [61]. sampling. One lasted circa 10 s, taking care to avoid hyperventilation of the volunteers. The total sample 2.2. Breath sampling during a glucose challenge volume was set to 20 ml (approximately four exhala- In order to identify the PTR-QMS targets, three male tions) at flow rates of 20 ml min−1 to have an adequate volunteers (basic data are given in the supporting compromise between sensitivity and sampling time. information), who did not show symptoms of diabetes Hence, a time resolution of two minutes could be at the time of testing, took part in three glucose achieved for NTME. Triple packed NTDs tolerate high challenges respectively. The study was approved by the sampling flow rates, which is required for a high time Ethics Committee (registration number A2015-0050) resolution in sampling [59]. of the Medical Faculty of the University of Rostock. All volunteers gave their written informed consent. 2.3. GC×GC-TOFMS The glucose challenge was performed based on an GC×GC-TOFMS analysis was performed on an Agilent oGTT after a fasting period of ~12 h (overnight) by 7890A gas chromatograph from Agilent Technologies administering 300 ml glucose solution (equivalent to (Palo Alto, USA) equipped with a ZX1 liquid nitrogen 75 g glucose) in a non-clinical laboratory with constant cooled loop modulation system (Zoex Europe BV, conditions and in a seated position. Breath samples Eindhoven, Netherlands) coupled to a time-of-flight were taken before glucose administration for measur- mass spectrometer from TOFWerk (Thun, Switzerland). ing a fasting value (xt=0). During the glucose challenge For gas chromatographic separation two column breath samples were collected consecutively within the combinations were tested. Column combination first 30 min and then after approximately 40 min and 1 (CC1) consisted of a 30 m cyanopropylphenyl 55 min. Capillary blood glucose values were measured polysiloxane capillary column (0.25 mm ID; 1.4 μm

3 J. Breath Res. 10 (2016) 036003 B Gruber et al film, BPX-Volatiles) from SGE Analytical Science concentrations in the ambient air, relations between (United Kingdom) in the first dimension and a 1.5 m the initial fasting values and the determined concen- poly-trifluoropropylmethylsiloxane capillary column trations during the metabolic challenge were consid- (0.1 mm ID; 0.1 μm film, Rtx-200) from RESTEK (Bad ered. Quantification­ was performed on extracted ion Homburg, Germany) in the second dimension. This signals and concentrations were determined by cali- enabled a separation of the analytes by polarity and bration curves. For method evaluation gas standards boiling point as well as of intermediate polar analytes generated by GCU or LCU were used and analyzed by that display lone pair electrons such as acetone. The high CC1 or CC2. Method precision was investigated by humidity in breath gas samples often causes problems means of repeatability and intermediate precision. in chromatographic separations. The application of Regarding method repeatability, three concentrations CC1 allows a good separation of water and CO2, column with six replications (intra-day) were sampled and bleed and a wide range of common breath gas analytes. analyzed. The intermediate precision was calculated Column combination 2 (CC2) consisted of a 30 m by comparing the results of a series of measurements nitroterephthalic acid modified polyethylene glycol over a number of days. Therefore, the sampling of six (PEG) polymer capillary column (0.25 mm ID; 1 μm replicates of a single concentration was repeated on film, 007-FFAP) from QUADREX (Bethany, USA) in six different days. For determining limits of detection the first dimension and a 3 m 14% cyanopropylphenyl (LODs) and limits of quantification (LOQs), calibra- methylpolysiloxane capillary column (0.1 mm ID; tions of the different standard substances in expected 0.5 μm film, 007-1701) from QUADREX (Bethany, concentration ranges were carried out, followed by USA) in the second dimension. This enabled the regression analysis according to DIN 32645 [63] using investigation of highly polar analytes such as free fatty Microsoft Excel 2010. acids. Approximately 1 m of the second dimension columns was placed in the modulation loops. 2.4. PTR-QMS The acquisition frequency of the TOFMS was set In order to collect and to analyze VOCs in human to 100 Hz and the solvent delay time to 5.5 min (CC1) breath on-line, a PTR-QMS from Ionicon Analytik and 2 min (CC2). The NTDs were introduced via GmbH (Innsbruck, Austria) in combination with a CONCEPT autosampler from PAS Technology (Mag- BET sampler (Ionicon Analytik GmbH, Innsbruck, dala, Germany) into a heated injection port (300 °C) Austria) were used. This setup enables the detection of equipped with a 0.75 mm ID strait/SPME inlet liner VOCs in the human end-tidal breath fraction down to using splitless injection. The carrier gas was helium. the pptv level, if their proton affinity is higher than that + The MS transfer line temperature was 280 °C and the of hydronium ions (H3O ) [61, 64]. ion source temperature was 200 °C. The following oven The PTR-QMS was operated at 2.2 mbar drift tube + temperature program was used for the CC1. Prior to pressure with H3O as primary ions. The count rate of + 6 −1 a GC×GC run the oven temperature was equilibrated H3O was set to ~5.0 × 10 s and oxygen was kept to 10 °C by means of liquid nitrogen cooling. After lower than 2% of that value. In order to prevent con- injection, this temperature was held for 5 min, raised densation of humidity, the inlet system and the BET with a temperature ramp of 5 °C min−1 to 230 °C sampler were heated up to 80 °C. Twelve preselected m/z and held for 5 min. The injector inlet pressure was set values (21, 32, 33, 37, 43, 47, 57, 59, 61, 75, 76, 89) were to 2 bar and increased simultaneously with the oven separated by a quadrupole and measured with dwell temperature to an end pressure of 5 bar. A modulation times between 100 ms and 500 ms, leading to a time time of 1 s with a hot-jet width of 100 ms was chosen as resolution of 3.1 s. Additionally, m/z = 87 was moni- the best combination regarding separation, resolution tored in four glucose challenges. Calibration by means and wrap-around. For CC2 the oven temperature was of a GCU was carried out after breath gas measurement. equilibrated to 100 °C. During a run the oven temper­ Counts per second (cps) were converted into ppbv ature was held for 5 min, raised with temperature ramps using the standard formula for PTR-MS concentrations of 10 °C min−1 to 140 °C, 2 °C min−1 to 170 °C and [65]. All breaths were identified by acetone (m/z = 59) 10 °C min−1 to 220 °C. The injector inlet pressure was and humidity (m/z = 37), which shows a strong set to 3.5 bar and increased simultaneously with the increase compared to the ambient concentration. The oven temperature to an end pressure of 5.5 bar. In this signals from five consecutive breaths were averaged case a modulation time of 5 s with a hot-jet width of using the plateau values of each single breath in order 500 ms was chosen. to obtain similar time resolution as NTME. Addition- Data evaluation was done using the automated ally, the average time and the standard error of the mean data processing software GC-Image (Zoex Europe were calculated. BV, Eindhoven, Netherlands). For the identification of compounds, obtained mass spectra were compared 3. Results and discussion with those of the National Institute of Standards and Technology (NIST 11, Mass Spectral Library v.2.0) and The precision of the established time-resolved breath the retention times were matched with those of the ref- gas analysis using NTME-GC×GC-TOFMS is erence substances. To minimize influences of analyte shown in table 1 by the relative standard deviations

4 J. Breath Res. 10 (2016) 036003 B Gruber et al

Table 1. Method precision of selected VOCs without (a) and with (b) ISTD (n = 6). CC2 was used.

Repeatability Intermediate precision

RSD (%) RSD (%) RSD (%)

Substance Generation method Level 1 Level 2 Level 3 RSD (%)

a 2-Propenal GCU 26.5(5ppbv) 35.4(10ppbv) 24.8(20 ppbv) 18.3(15 ppbv)

Acetone LCU 52.2(904 ppbv) 39.3(1785 ppbv) 62.3(2645 ppbv) 8.6(714 ppbv)

Benzene GCU 24.5(5ppbv) 23.8(10ppbv) 33.8(20 ppbv) 13.1(15 ppbv)

Chloro-benzene GCU 15.8(5ppbv) 23.4(10ppbv) 7.4(20 ppbv) 12.6(15 ppbv)

Ethanol GCU 51.2(5ppbv) 36.7(10ppbv) 60.5(20 ppbv) 21.5(15 ppbv)

o-Xylene GCU 21.7(5ppbv) 13.9(10ppbv) 18.7(20 ppbv) 10.2(15 ppbv)

b Acetic acid LCU 38.1(774 ppbv) 20.5(1528 ppbv) 22.4(2265 ppbv) 29.4(917 ppbv)

Butanoic acid LCU 17.7(48 ppbv) 8.2(95 ppbv) 5.2(141 ppbv) 17.8(76 ppbv)

Propanoic acid LCU 21.2(89 ppbv) 13.4(175 ppbv) 11.3(260 ppbv) 25.2(164 ppbv)

Table 2. LODs and LOQs for selected reference substances investigated by NTME-GC×GC-TOFMS.

Substance Cas number Generation method Column combination LOD/ppbv LOQ/ppbv

1-Butanol 71-36-3 LCU CC2 11 33 1-Propanol 71-23-8 LCU CC2 10 37 2,3-Butanedione 431-03-8 LCU CC2 6 19 2-Butanone 78-93-3 GCU CC1 1 3 2-Propenal 107-02-8 GCU CC1 2 6 Acetic acida 64-19-7 LCU CC2 70 263 Acetic acid, methylester 79-20-9 LCU CC2 7 23 Acetoin 513-86-0 LCU CC2 27 104 Acetone 67-64-1 GCU CC1 2 14 Benzaldehyde 100-52-7 LCU CC2 1 4 Benzene 71-43-2 GCU CC1 1 2 Chloro-benzene 108-90-7 GCU CC1 1 3 Butanoic acida 107-92-6 LCU CC2 1 4 Ethanol 64-17-5 LCU CC2 22 97 Isoprene 78-79-5 GCU CC1 2 8 n-Hexane 110-54-3 LCU CC2 9 32 o-Xylene 95-47-6 GCU CC1 1 3 Propanoic acida 79-09-4 LCU CC2 2 7 Toluene 108-88-3 GCU CC1 1 2 α-Pinene 80-56-8 GCU CC1 1 3 a With ISTD.

(RSDs) of selected VOCs. The RSDs of the methods’ noic acid and butanoic acid by means of deuterated repeatability without internal standardization ISTD. The RSDs of their repeatability were between (table 1(a)) were between 7.4% for chlorobenzene 5.2% for butanoic acid and 38.1% for acetic acid. Here, and 62.3% for acetone. In this case RSDs did not an expected relation between RSD, concentration and depend on the sample concentrations. In particular, the molecular mass was observed and the influence NTME is highly affected by the sample humidity and of the performance of the individual NTD could be the adsorbent material (comparisons are given in the leveled out. Therefore, deuterated acids were used for supporting information) [59, 66]. The extraction NTME of SCFA in the following. Limits of detection efficiencies deviate up to 70% for different NTDs with were determined in the range of 1 ppbv–70 ppbv. Lim- the same adsorbent composition in triple packed NTDs its of quanti­fication ranged from 2 ppbv–263 ppbv. due to the manufacturing process [60]. Nevertheless, An overview of LODs and LOQs for all standard sub- there was no pre-selection of NTDs according to their stances investigated by NTME-GC×GC-TOFMS is inter-needle variability for further studies. given in table 2. Although small sample volumes of In order to enhance the precision of the method, only 20 ml were used, the values are in the lower ppbv the use of internal standards, if possible, is crucial. range as typically found in breath gas [60]. Further- Table 1(b) presents the methods precision for NTME more, the results are comparable to other methods [9] of the highly polar volatile SCFA: acetic acid, propa- despite using NTME with small sample volumes, high

5 J. Breath Res. 10 (2016) 036003 B Gruber et al

Figure 2. Representative time profiles of PTR-QMS targets during a glucose challenge. Left: absolute concentrations in ppbv are plotted against the glucose challenge time. Right: relative concentrations (ct/ct=0) are plotted against the glucose challenge time. Start of the glucose challenge at t = 0. flow rates and humid sampling conditions. NTME The time profiles of the seven challenge responsive was carried out in parallel to PTR-QMS for breath gas PTR-QMS m/z values of the volunteers during all glu- monitoring during glucose challenges of three volun- cose challenges are given in the supporting information. teers. Regarding inter-individual variability, statistical differ- For the verification of normal glucose tolerances ences between volunteers were investigated by one-way capillary blood glucose levels were monitored during ANOVA using maximal relative concentrations of the the tests and ranged from 90 mg dl−1–108 mg dl−1 at seven challenge responsive m/z values during the glucose t = 0 min, from 120 mg dl−1–188 mg dl−1 at t = 30 min challenges (data are given in the supporting informa- and from 107 mg dl−1–132 mg dl−1 at t = 60 min (data tion). ANOVA indicated a statistically significant differ- are given in the supporting information). According to ence (p < 0.05) between the volunteers regarding m/z 47 ‘2006 World Health Organization recommendations (F(2,6) = 9.80, p = 0.0129) and m/z 89 (F(2,6) = 6.10, for the diagnostic criteria for diabetes and intermedi- p = 0.0358). Nevertheless, there are high variances ated hyperglycemia’, the determined blood glucose within the same volunteer caused e.g. by environ­mental concentrations after 0 min and 60 min of the three vol- influences or physiological changes due to diet or sport unteers imply no diabetes (⩾126 mg dl−1 at t = 0 min activities. The volunteers have not been supervised or ⩾200 mg dl−1 at t = 120 min), no impaired glucose prior to the glucose challenges to match real conditions. tolerance (<126 mg dl−1 at t = 0 min and ⩾140 mg dl−1 Despite a high intra-individual variability, inter-individ- and <200 mg dl−1 at t = 120 min) and no impaired fast- ual differences regarding m/z 47 and m/z 89 might allow ing glucose (110–125 mg dl−1 at t = min and <140 mg for differentiation of the three volunteers. However, for dl−1 at t = 120 min). Therefore, blood glucose levels had more precise information on intra- and inter-individual already reached normal values after 60 min in all tests. variability the number of volunteers and glucose chal- Breath gas data were monitored continuously dur- lenges respectively would need to be increased, which was ing the glucose challenges. Seven of the selected PTR- not within the objective of this study. QMS m/z values (43, 47, 57, 61, 75, 76, 89) reflected the The potential molecular masses of the seven PTR- progression of the metabolic challenge and showed a QMS targets were investigated by NTME-GC×GC- time profile with a significant increase in concentra- TOFMS, identified by NIST as well as retention times tion till a peak around five to ten minutes and a rapid and verified by comparing the glucose challenge time. decline in concentration till base level within 30 min By soft ionization PTR-QMS fragmentations, clus- after glucose ingestion. Unlike invasive blood glucose tering and the formation of artefacts can occur. This testing, breath gas analysis is able to monitor more com- is shown in figure 3 for propanoic acid where m/z 57, pounds that reflect the metabolic state of the volunteer. 75 and 76 could be related to a major protonated frag- + In addition, the predication of a classical oGTT could be ment ([C3H4O + H] ), the protonated molecular ion + achieved already after approximately 60 min, because of ([C3H6O2 + H] ) and the protonated C-13 isotope of 12 13 + the fast challenge response of the breath gas compounds the molecular ion ([ CC2 HO62+H] ). Furthermore, [13]. In figure 2 exemplary concentration profiles by isomeric and isobaric compounds and fragments could PTR-QMS can be seen on the left and for comparative not be separated by the applied PTR-QMS. As a conse- reasons relative values related to the fasting value on the quence, one m/z signal by PTR-QMS might reflect more right. The kinetics obtained by Halbritter et al [13] show than one compound and one compound could also be similar profiles with slower rise and decline in concen- described by more than one m/z. Besides, influencing tration of metabolites during an oGTT of women. That factors using NTME like the adsorbent based selectivity can be explained by having the same glucose challenge could lead to deviating results. For these reasons, dif- conditions, but differences in health status and body ferences in absolute concentrations were obtained by size between men and women [67]. comparing the results of both methods.

6 J. Breath Res. 10 (2016) 036003 B Gruber et al

Figure 3. Representative time profiles of propanoic acid by NTME-GC×GC-TOFMS and the corresponding m/z ratios 57, 75 and 76 by PTR-QMS during a glucose challenge. Left: absolute concentrations in ppbv are plotted against the glucose challenge time. Right: relative concentrations (ct/ct=0) are plotted against the glucose challenge time. Start of the glucose challenge at t = 0.

Figure 4. Representative time profiles of ethanol, 1-propanol, acetic acid and butanoic acid by NTME-GC×GC-TOFMS and their corresponding m/z ratios by PTR-QMS during a glucose challenge. Relative concentrations (ct/ct=0) are plotted against the glucose challenge time. Start of the glucose challenge at t = 0.

Using NTME-GC×GC-TOFMS, small n-carbonic In six glucose challenges the increase in concentra- (C2–C4) alcohols and acids showed similar concentra- tion of butanoic acid by NTME-GC×GC-TOFMS and tion profiles as their corresponding m/z ratios in PTR- m/z = 89 by PTR-QMS differed strongly from each other QMS. After glucose ingestion, there is a significant rise despite good correlations, which can be seen in the exam- in concentration till a peak around 5–10 min, followed ple in figure 4. Therefore, closer investigation of further by a rapid decrease till base level within 30 min of the compounds with the same corresponding molecular glucose challenge. Concentration ranges of target m/z ion was carried out by GC×GC-TOFMS measurements at t = 0 are listed in the supporting information. As an and led to the identification of acetoin (3-hydroxy- example, figure 4 shows the time profiles during one 2-butanone). This breath gas compound is an isomer glucose challenge of one volunteer. For better illustra- of butanoic acid (C4H8O2). PTR-QMS measurements tion, relative concentrations were used for compariso­n. were applied without prior chromatographic separation. Six of the seven challenge responsive m/z targets could Therefore, substances with identical m/z could not be dif- be assigned with significant correlation to the small ferentiated. Acetoin is produced to a large extent during n-carbonic (C2–C4) alcohols and acids: ethanol, 1-pro- glucose metabolization by bacteria in the mouth. Fur- panol, acetic acid, propanoic acid and butanoic acid thermore, 2,3-butanedione is involved in the same met- (table 3). abolic pathway [21]. The concentration of acetoin and

7 J. Breath Res. 10 (2016) 036003 B Gruber et al

Table 3. Correlations of the exemplary concentration profiles of challenge responsive m/z by PTR-QMS and small n-carbonic (C2–C4) alcohols/ acids.

m/z Substance Ion r p n

+ 43 Acetic acid, [C2H2O + H] r = 0.77 p = 0.0022 13 Butanoic acid, r = 0.65 p = 0.0217 12 1-Propanol r = 0.85 p = 0.0217 17 + 47 Ethanol [C2H6O + H] r = 0.94 p = 2 E-08 17 + 57 Propanoic acid [C3H4O + H] r = 0.79 p = 0.0008 14 + 61 Acetic acid [C2H4O2 + H] r = 0.77 p = 0.0021 13 + 75 Propanoic acid [C3H6O2 + H] r = 0.79 p = 0.0008 14 12 13 + 76 Propanoic acid [ CC2 HO62+H] r = 0.80 p = 0.0005 14

Figure 5. Representative time profiles of 2,3-butanedione and acetoin by NTME-GC×GC-TOFMS and their corresponding m/z ratios by PTR-QMS during a glucose challenge. Relative concentrations (ct/ct=0) are plotted against the glucose challenge time. Start of the glucose challenge at t = 0.

2,3-butanedione increased rapidly more than tenfold five tests as well as butanoic acid and acetoin in six tests after glucose intake, peaked around 5 min and dropped respectively. In six cases m/z = 47 could be related to within 15 min (figure 5). A significant correlation ethanol and m/z = 61 was correlated with acetic acid could be observed for acetoin with m/z = 43 (r = 0.88, in five of the glucose challenges. PTR-QMS data of p = 3 × 10−5) and m/z = 89 (r = 0.91, p = 6 × 10−6). m/z = 87 could be assigned to 2,3-butanedione in one Thereby, the characteristics of the challenge response by of four tests and the signals of m/z = 89 were related PTR-QMS can clearly be traced by NTME-GC×GC- to acetoin in seven glucose challenges. Other isomeric TOFMS. Additionally, a distinction can be made between compounds like hydroxyacetone were also investigated the profile of butanoic acid and acetoin. This highlights but showed different time profiles. the advantage and usefulness of NTME for this special The formation of the detected metabolites can be application, which provides a high selectivity, but also explained partly by various metabolic pathways of differ- allows for time resolved monitoring. However, the glu- ent bacteria in the oral cavity or gastrointestinal passage. cose challenge will remain necessary as only the time Ethanol is produced partly due to alcoholic fermentation profiles after glucose ingestion allow for discrimina- of glucose by gut bacteria and yeast and following diffu- tion. No significant relationship for 2,3-butanedione siveness into the respiratory system [16]. Another part of at m/z = 87 (r = 0.42, p = 0.0894) was observed. This the detected breath ethanol can also be explained by the could be in part because of oxidation processes of acetoin alcohol content of the glucose solution (0.01–0.06 Vol.%). to 2,3-butanedione by NTME-GC×GC-TOFMS during Unlike butanol, the concentration profiles of ethanol and desorption in the injection port due to tough settings like the relating m/z = 47 show two maxima (figure 4). The first high temperature­ as well as humid and acidic conditions. peak (around 3 min) can be assigned to the alcohol con- A derivatization for the stabilization of the compound tent of the glucose solution and the second peak (around was not possible due to the special characteristics of the 11 min) to alcoholic ­fermentation of glucose. SCFA like end-tidal breath gas sampling by NTDs. propionic acid and acetic acid are for instance the main Propionic acid showed a significant response in end products of glucose fermentation by bacteria e.g. all glucose challenges performed and could be corre- Propionibacterium, which are found in saliva and gut lated to m/z = 57, 75 and 76, which also correlate very [1, 31, 68, 69]. Therefore, SCFA are increased in breath strongly (r57,75 = 0.90, a57,75 = 1.677, r57,76 = 0.90, gas due to metabolization of unabsorbed glucose, which a57,76 = 0.062, r75,76 = 0.96, a75,76 = 0.036) with one can describe the concentration profiles (figure 4). The another. The PTR-QMS m/z = 43 showed a significant assumption of oral and gastrointestinal fermenta- correlation with 1-propanol in three tests, acetic acid in tion of carbohydrates by local bacteria is confirmed by

8 J. Breath Res. 10 (2016) 036003 B Gruber et al

­Martinez-Lozano et al and Bikov et al [70, 71]. Neverthe- remarks and suggestions significantly improved clarity less, the involvement of other biochemical pathways can- and precision of the paper. not be excluded.

4. Conclusion References

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