The Potential of Volatile Organic Compounds

Study of VOCs in Biological Matrices by GC-MS & Gas-Sensors

  • Fig. 1: Example of VOC analysis through SPME-GC/MS and GC/gas sensor (A) and 4-sensor array (B).

The analysis of VOCs emanating from biological samples appears as one of the most promising approaches in metabolomics for the study of diseases. The presence of volatile markers has been explored in exhaled breath, urine, blood, saliva, feces, human semen and cell cultures. Detection and quantification of VOCs are carried out by gas chromatograph-mass spectrometer system (GC-MS) and/or gas sensors.

The Importance of VOCs

Volatile Organic Compounds (VOCs) represent a wide range of small (molecular weight 50-200 Dalton) stable molecules, volatile at ambient temperature, often lipophilic with a high vapour pressure [1]. Volatile composition in all biological matrices is composed by two important and heterogeneous fractions: endogenous and exogenous compounds. The endogenous one regards molecules which are produced by cell metabolism (in vivo and/or in vitro) and could potentially be markers of physiological and pathological conditions. Instead, exogenous VOCs originate from current or previous environmental exposures [2-3] which indicate the substances to which we are daily exposed, and which induce alterations at our normal metabolism; other external sources are related to lifestyle, diet, microbiome, drugs. What changes is the cause-effect relationship: in the first group, VOCs are the effect; in the second, the cause.

Analysis of endogenous compounds of cell culture or biofluids can help to understand physiopathological mechanisms which are at the basis of a disease, such as bacterial infection [4], inflammation [5], cancers [6]. On the other side, exogenous are important in exposome research for assessing the environmental impact on human health, gaining insight into pharmacokinetics and monitoring the health-related effects due to other external factors. In a new research paradigm for such complex scenario both endogenous and exogenous VOCs can provide important clinical information and may revolutionize our understanding of later onset diseases.

How Can We Study VOC Fingerprinting?

The principal system for VOC detection and quantification is the gas-chromatography (GC) coupled by mass spectrometer (MS) associated with a good extractive method.

One of the most used is solid phase microextraction (SPME) [7]. Another approach is based on the use of gas sensors [7].

For the analysis of volatile compounds, usually experiments with three methodologies are set in parallel: SPME-GC/MS, SPME-GC/sensor gas and gas sensor array.

The first two are carried out thanks to a particular rearrangement of traditional GC-MS system in which the gas chromatographic column is linked by a splitter to MS and a gas sensor. In this way, the eluted compound is detected by the two detectors at the same time [8]. The overlapping of chromatograms and corresponding “sensorgrams” (variation of resistance in relation to run time) permitted both to connect the sensor responses to a specific VOCs’ pattern both to eliminate general background contamination, such as column bleed, that is not perceived by VOC sensor (Fig. 1A).

Using exclusively sensor resistance profiles, we have an high discrimination of our samples (for example, human semen ones) by the most well-known classification procedures in chemometrics, the Partial Least Squares-Discriminant Analysis (PLS-DA) [9].

The third approach is based on a 4-sensor array placed in a home-made chamber. Also, this electronic nose-based approach allows a good reproducibility and classification power.


Solid-phase microextraction (SPME) was invented by Pawliszyn and co-workers [10] in 1989 to redress limitations inherent in solid-phase extraction and liquid–liquid extraction techniques. SPME integrates sampling, extraction, concentration and sample introduction into a single solvent-free step thanks to a fused-silica fibre that is coated on the outside with an appropriate stationary phase. It has been routinely used in combination with GC/MS and successfully applied to extraction of volatile and semi-volatile organic compounds from environmental, biological and food samples.

VOC collection is allowed thanks to distribution of volatile compounds between liquid fraction (biofluid or cell medium) and headspace (HS). Headspace concentration values are based on Henry’s law constants and depend to specific chemical-physical characteristics of the sample.

By SPME, the amount of VOC removed by the fibre is proportioned to the concentration of the compounds in the sample. For this reason, it is possible to make a quantitative as well as a qualitative analysis.

To qualitative analysis is necessary the use of spectral libraries such as NIST 14 (National Institute of Standards and Technology, USA) which permit to identify (based on mass spectrum) the specific compound. Usually, in our laboratory the identification is confirmed by external standards, using the same method of the samples.

To lead a quantitative study is obligatory the addition to the samples of specific internal standards. We ordinarily used commercial multiple standards (EPA8260) in which are present molecules not presented in our samples in order to avoid contamination and additive effect. Standard curves were created based on the peak areas, which were obtained from Enhanced Data Analysis software. The data were analysed in triplicate. Due to the different density and viscosity of samples which in general we study, for each type of biological fluid we draw a specific calibration curve.

GC/Gas Sensor System

Chromatographic column is connected simultaneously to two detectors, mass spectrometer and metal-oxide (MOX) gas sensors, which work in parallel by a two-way splitter, that splits the helium (He) flow in 1:1 ratio towards the two detectors through two segments of defunctionalized chromatographic column. For GC/gas sensor analysis the capillary column was inserted, by a splitter (Agilent G3180B Two-Way Splitter), into a tiny chamber hosting a VOC sensor (MiCS-5521, e2v technologies, UK) and it was positioned near sensor surface. The MOX sensor operating temperature was 400°C. The MOX sensor traces (resistance vs. time) (Fig. 1A) were used for data analysis. In particular, to ensure that each profile is on the same scale, resistance profiles were standardized using range-scaling between 0 and 1 [11].

4-Sensor Array

The third and last approach that we apply to study VOCs in biological matrices is based on a 4-sensor array with 4 MOX sensing elements operating at a temperature of 250 °C which are positioned in a home-made gas-tight chamber. The sensor responses towards the volatile compounds of the different samples were acquired by applying a constant voltage of 1 V across the electrodes and measuring the electrical current by an electrometer Keithley mod. 6517A equipped with an internal multiplexer module (Keithley mod. 6521).

The baseline was acquired in dry air in a continuous total flow of 25 sccm, whereas, for the measurement, the sample headspace, was stripped by means of a deviation of flow into the vial, kept at room temperature for 4 min, into the sensor chamber. All fluxes were controlled by mass flow controllers (MFCs) and a multichannel mass flow programmer (MKS mod. 647B). LabView software controlled all the gas-mixing protocol and the sensor signal acquiring [12]. The gas-sensing response of the device is defined by the ratio Rair/Ranalyte, where Ranalyte and Rair denoted the measured resistance in the presence of the VOCs and in dry air carrier, respectively (Fig. 1B).

Conclusion and Outlook

Several methods to analyse volatile component of biological matrices exist, pointing out the importance of this metabolome fraction.
The methods to detect VOCs are very fast, economic, reproducible and allow population screening on a large scale. The implementation of protocols to VOC analyse is an important step on this long and uphill way, but several research group (such as our laboratory staff) they are working hard in this direction.


Valentina Longo1, Angiola Forleo1, Simonetta Capone1, Pietro Siciliano1


1Institute for microelectronics and microsystems of National Research Council (IMM-CNR), Lecce, Italy


Valentina Longo

Institute for microelectronics and microsystems of National Research Council (IMM-CNR),
Lecce, Italy


Further articles on chromatography



  1. Rowan, D.D. Volatile metabolites. Metabolites 2011,1(1), 41-63. doi:10.3390/metabo1010041.
  2. Longo V, Forleo A, Pinto Provenzano S, Coppola L, Zara V, Ferramosca A, Siciliano P, Capone S. 2019 Biomed. Phys. Eng. Express 5 015006
  3. Baranska A, Smolinska A, Boots AW, Dallinga JW, van Schooten FJ. Dynamic collection and analysis of volatile organic compounds from the headspace of cell cultures. J Breath Res. 2015 Oct 15;9(4):047102. doi: 10.1088/1752-7155/9/4/047102.
  4. Sohrabi M, Zhang L, Zhang K, Ahmetagic A, Wei MQ (2014) Volatile Organic Compounds as Novel Markers for the Detection of Bacterial Infections. Clin Microbial 3:151. Doi: 10.4172/2327-5073.1000151
  5. Forleo A, Capone S, Longo V, Casino F, Radogna AV, Siciliano P, Massaro M,  Scoditti E, Calabriso N, Carluccio MA.  Evaluation of the Volatile Organic Compounds Released from Peripheral Blood Mononuclear Cells and THP1 Cells Under Normal and Proinflammatory Conditions. In: Leone A., Forleo A., Francioso L., Capone S., Siciliano P., Di Natale C. (eds) Sensors and Microsystems. AISEM 2017. Lecture Notes in Electrical Engineering, vol 457. Springer, Cham.  269-277
  6. Khalid T, Aggio R, White P, De Lacy Costello B, Persad R, Al-Kateb H, Jones P,Probert CS, Ratcliffe N. Urinary Volatile Organic Compounds for the Detection of Prostate Cancer. PLoS One. 2015 Nov 24;10(11):e0143283. doi:10.1371/journal.pone.0143283.
  7. Thriumani R, Zakaria A, Hashim YZH, Jeffree AI, Helmy KM, Kamarudin LM, Omar MI, Shakaff AYM, Adom AH, Persaud KC. A study on volatile organic compounds emitted by in-vitro lung cancer cultured cells using gas sensor array and SPME-GCMS. BMC Cancer. 2018 Apr 2;18(1):362. doi: 10.1186/s12885-018-4235-7.
  8. Longo V, Forleo A, Pinto Provenzano S, Montagna DD, Coppola L, Zara V, Ferramosca A, Siciliano P, Capone S.   Characterization of human semen by GC-MS and VOC sensor: an unexplored approach to the study on infertility. In: Sensors - Proceedings of the Fourth National Conference on Sensors. CNS 2018. Lecture Notes in Electrical Engineering.
  9. Longo V, Forleo A, Pinto Provenzano S, Montagna DD, Coppola L, Zara V, Ferramosca A, Siciliano P, Capone S.  SPME-GC/MOX sensor system: a new method for the evaluation of human semen quality. Abstract of XXII International Mass Spectrometry Conference, Florence, August 26-31, 2018.
  10. Belardi RG, Pawliszyn J. Water Pollut. Res. J. Can. 1989; 24: 179
  11. Weber, C.M., Cauchi, M., Patel, M., Bessant, C., Turner, C., Britton, L.E., Willis, C.M.: Evaluation of a gas sensor array and pattern recognition for the identification of bladder cancer from urine headspace. Analyst. 21;136(2):359-64 (2011). doi:10.1039/c0an00382d
  12. A. Forleo, A.M. Taurino, S. Capone, M. Epifani, L. Francioso, J. Spadavecchia, P. Siciliano. Sensor Lett., 4 (2006), 229–234


Institute for microelectronics and microsystems of National Research Council (IMM-CNR)

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