Recent Applications of Gas Chromatography in Bioanalysis

Abstract

Bioanalysis involves a broad range of chemical analyzes. These analyzes include that of biotics, such as natural components of living organisms, as well as xenobiotics, such as drugs and their metabolites in biological systems. Because many biotics and xenobiotics are not volatile molecules, the main technique for bioanalysis is high-performance liquid chromatography (HPLC) and the limitation of GC utilization is caused by the fact that GC is applicable only to volatile samples. However, gas chromatography (GC) in particular coupled with mass spectrometry (MS) as detection is also a very useful technique in bioanalysis. A considerable number of analytes in bioanalysis are volatile or can be made volatile following, for example, derivatization. As a result, GC (and GC/MS) are commonly utilized for the analysis of biotics, such as amino acids, fatty acids, various metabolites in biological fluids, and in particular of a large number of xenobiotics, such as drugs, drug metabolites, toxicants, and certain metabolic compounds caused by toxicants. The chapter will present progress in the GC methodology for extending its applicability to bioanalysis and will provide a review of more recent applications.

1. Introduction

Biological samples include biotics, which are natural components of living organisms, as well as xenobiotics, such as drugs and their metabolites, toxicants, certain metabolic products caused by toxicants, and other components of biological systems. Biometrics may consist of various body tissues, blood, plasma, serum, hair, milk, saliva, sweat and skin surface lipids, urine, fecal materials, and breath. Biological samples typically have a very complex composition and provenience. Bioanalysis involves a broad range of chemical analyzes and chromatographic techniques are the ones most frequently utilized for this purpose. The most common chromatographic technique used in bioanalysis is high-performance liquid chromatography (HPLC), but gas chromatography (GC) is also frequently utilized. The present chapter describes some of the more recent applications of GC in bioanalysis.

2. Short overview of gas chromatography

Gas chromatography (GC) is one of the main types of chromatographic techniques that has gas as the mobile phase, usually helium or hydrogen. As an analytical technique, the separation by GC is always coupled with a detection technique. Gas chromatography requires the sample to be in gas form during the separation, and this causes its limitation to the analysis of only volatile compounds. However, many nonvolatile compounds can be transformed into volatile compounds by chemical modifications (derivatization).

The separation in GC takes place in a chromatographic column, the modern instruments use open-tubular columns (capillary columns), while packed columns that were used in the past are now much less utilized. The capillary column, commonly made from silica, has an inner coating with a film that acts as a stationary phase that can have different chemical structures. The stationary phase film is selected based on the intended separation, and a variety of such phases are commercially available. The chromatographic column is placed in an oven with a controlled temperature kept constant during the separation process (isocratic conditions) or modified following a specific program (gradient conditions). The sample to be analyzed is introduced at the head of the chromatographic column using an injector. For liquid samples, the injector typically uses a syringe placing a precise volume, such as 0.5, 1.0, or 2.0 μL, into the injection port of the GC that is heated at a specific temperature, volatizes the liquid, and places the sample in the gas flow of the chromatographic column. The gas samples are usually placed in the gas flow of the GC using a loop of specific volume that is connected to the gas flow of the instrument. Various solvent-less type injections are also possible [1]. The separated components of the sample are carried into a detector that generates an electric signal. The signal is proportional to the instantaneous concentration (or amount) of the analyte passing through the detector, allowing the use of the signal for quantitative measurements. Several types of detectors are used in GC. The most common detectors in GC are probably the flame ionization detector (FID) and the mass spectrometer (MS). Other detectors, such as thermal conductivity (TCD), nitrogen phosphorus (NPD), electron capture (ECD), photoionization (PID), are also used in GC. Some of these detectors have a universal response to the analytes and provide only quantitative information (e.g., FID), other detectors are element specific (e.g., NPD), and others offer both the capability of quantitative and qualitative identification (e.g., MS). The MS detector generates a total signal that can be used for quantitation, but also mass spectra for the compounds passing the detector. Large libraries of mass spectra (some libraries containing spectra for over 800,000 compounds) allow qualitative identification of unknown components in the sample, or confirmation of the nature of the evaluated analyte. The detectors have different sensitivities and linear ranges, this depending on the type of detector but also on the detector manufacturer.

3. Gas versus liquid chromatography in bioanalysis

Because of the common complexity of biological samples, bioanalyses usually include separations that are carried out with chromatographic techniques [2, 3, 4]. These analyses produce quantitative and/or qualitative information about biotics, as well as xenobiotics. A biomatrix typically consists of three main components: large molecules, such as proteins, small (non-polymeric) organic molecules that are typically the target for analysis in GC, and inorganic content. Bioanalytical investigations are commonly based on a protocol that should be focused on two aspects, namely, the sample preparation and chromatographic methodology.

Although high-performance liquid chromatography (HPLC) can be considered as the technique most commonly utilized in bioanalysis due to the more options to investigate the complex biological matrix and the more large area of compound amenable to the analysis by this technique, GC in spite of its smaller covered domain of applications has several advantages, such as higher separation capacity, excellent sensitivity, and much better capability of unknown compound identification (when coupled with MS). Besides sample enrichment and interferences removal from the biological matrix, which is common to both GC and HPLC [5, 6], sample preparation for GC can include the role of transforming the nonvolatile analytes in volatile compounds. This can be performed by various techniques and can use a range of derivatization reagents [7, 8, 9, 10]. Generally, the sample preparation is carried out by extraction techniques, including liquid-liquid, supercritical fluid, solid-phase, or microextractions, which may include or not a derivatization step for improving volatility, detectability, or improvement of separation capability [8]. In conclusion, sample preparation for GC analysis has the main role of sample simplification, analyte concentration, or analyte structure modification (derivatization). Derivatization in GC can be used to render the analytes more volatile and thermally stable, to improve separation, detectability, and accuracy of analysis.

4. GC determination of volatile organic compounds of biological origin

Usually, a volatile organic compound (VOC) is characterized by a minimum 0.13 kPa vapor pressure at 20°C [11] and can belong to various classes, such as aliphatic and aromatic hydrocarbons, alcohols, amines, ketones, aldehydes, acids and their derivatives, sulfur compounds, and many compounds with multiple functionalities. Volatile organic compounds (VOC) of biological origin (e.g., human) are chemical components from breath [12], as well as volatiles emitted from the skin, or bodily fluids (urine and feces), many of them being odorous and different from the metabolites produced in the axillae (underarms) [13]. Identification of these compounds and their concentrations could be useful for assessing various diseases that include pulmonary diseases, liver dysfunctions, kidney diseases [14], gastrointestinal problems, diabetes, and others. Therefore, the investigation of the content of such samples by various analytical techniques, including GC, can be considered a potentially noninvasive means of diagnosis, monitoring of pathological processes, and assessment of pharmacological response, being fast, simple, and acceptable to patients [15]. However, unlike solid or liquid biomatrices, gaseous samples are more difficult to be sampled and sampling is critical in the analytical process.

Gaseous samples of biological provenience can be collected by different techniques, including solid-phase microextraction (SPME) [16], adsorption on graphitized carbon, molecular sieve, various resins (e.g., XAD resins), or by condensation in cold traps (cryfocusing), when the water should be removed selectively before analysis [17]. Also, a sampler can be a cylinder that can be placed on the skin surface in order to create a headspace [18]. In the case of using SPME for breath sampling, this approach should avoid the collection of droplet phases of exhaled breath by using a filter-incorporated needle-trap device [19]. Needle-trap devices are recommended for the extraction of VOCs from biological solid and liquid samples. They are capable of satisfying many actual demands, as green analytical methods, eliminating solvent consumption, and performing an on-site sampling. After extraction of VOCs, they are thermally desorbed and automatically injected into the GC system for separation and quantitation [20]. Specifically for breath analysis, sampling and storage can also be chosen from several modalities, such as polymeric sampling bags (Tedlar^®, Nalophan, Cali-5-Bond), syringes, gas evacuated steel, or glass containers [21]. Sample collection can be performed offline, preserving stability in a time of the samples, or online, which is less used in practice [22].

Analytical methodologies based on GC with mass spectrometry (MS) have been developed for the determination of exhaled VOCs pattern and have become a potential method for early diagnosis of lung cancer. Thus, GC-MS analysis for many patients revealed that 1-butanol and 3-hydroxy-2-butanone are biomarkers that at significantly higher concentrations in breath can diagnose lung cancer [23]. There are other studies that reported the analysis of exhaled volatile carbonyl compounds for the identification of specific carbonyl cancer markers to differentiate benign pulmonary disease from early-stage lung cancer and to compare its diagnostic accuracy with positron emission tomography scans [24]. Asthma can be diagnosed by measuring the concentration levels of ethane, pentane, 8-isoprostane, and NO [25].

Other examples of VOCs as biomarkers determined by GC technique and their concentrations used for illness diagnostics include, for example, (i) alkanes, monomethylated alkanes for breast cancer; (ii) S-containing compounds, such as methyl mercaptan, dimethylsulfide for hepatic coma and cholera [15, 26]; (iii) carbon disulfide, pentane, ethane for schizophrenia; (iv) hexanal, 1-octen-3-ol and octane for liver cancer [27]; and (v) nonanal, 2-ethylhexan-1-ol, 5-ethyl-3-methyloxolan-2-one, heptan-2-one, 1,1,4a-trimethyl-4,5,6,7-tetrahydro-3H-naphthalen-2-one and propan-2-one from urine as surveillance biomarker of bladder cancer [28].

One of the common possibilities to diagnose gastrointestinal disease relies on the analysis of VOCs from fecal materials. For example, the analysis of several VOCs from chicken feces with and without Campylobacter jejuni revealed the abundance of six VOCs, considered fecal biomarker for this bacteria in chicken feces, namely, hexanal, 2-octenal, pyrrole, ethyl acetate, methanol, and 2-heptanone [29].

5. GC analysis of biotics in biological fluids

There is a large variety of chemical species as part of the biomatrices. Among them, amine-type compounds, including polyamines, amino acids, catecholamines, fatty acids, and carbohydrates (monosaccharides, disaccharides, oligosaccharides, and polysaccharides), are essential for cell metabolism. These compounds are very polar and many of them are lacking a chromophore moiety in order to be detected by UV–Vis spectrometry [30].

The determination of amino acids in biological fluids can serve as cancer biomarkers [31, 32]. The first choice in selecting chromatographic techniques is liquid chromatography, which offers various retention mechanisms for amino acids [33], but gas chromatography coupled with mass spectrometry is still being used for the analysis of these compounds from biomatrices due to its advantage in compound identification. The difficulty in GC determination of these very polar compounds is their lack of volatility, and the only possibility to use this chromatographic technique is to apply a derivatization procedure in order to decrease their polar character and transform amino acids and more volatile species. The derivatization procedure can take place simultaneously with an extraction operation, or can be performed separately, before extraction [34]. Besides isolating the derivatives from an aqueous medium, the extraction has the role of eliminating part of the sample matrix, and in some cases the enrichment of the target analytes [8].

Derivatization of amino acids with alkyl chloroformates, such as propyl chloroformate [35], is commonly used and the derivatization can be carried out directly in the biological samples that do not need prior protein precipitation or solid phase extraction of the amino acids. The reaction takes place rapidly (less than 1 min) in a water/propanol/pyridine medium. The analytes are further extracted in chloroform and analyzed by GC or GC-MS. Other alkyl chloroformates can be used for the same purpose [36]. The derivatization at both functional groups, amino, and carboxyl, of amino acids, will lead to stable volatile derivatives that are further extracted in an organic solvent (e.g., chloroform or isooctane) and injected into the GC-MS system. By these GC-MS methods, a large number of amino acids and dipeptides were determined allowing limits of detection (LOD) situated in the range of 0.03–12 μmoles/L [37].

An older study compared the main derivatization reagents used for GC analysis of amino acids in complex samples (lyophilized E. coli microbial culture) [38]. These reagents were N,O-bis(trimethylsilyl)trifluoroacetamide (BSTFA), N-methyl-N-(tert-butyldimethylsilyl) trifluoroacetamide (MTBSTFA), and isobutyl chloroformate (iBuCF). The study showed that the performances in the case of silylation with the aid of MTBSTFA are comparable to those obtained for acylation with iBuCF, but require a more laborious extraction procedure to isolate the amino acids prior to derivatization, and determination of amino acids as N(O,S)-alkoxycarbonyl alkyl esters is more advantageous for this type of application.

Derivatization with BSTFA of amino acids, attaching trimethylsilyl at both functional groups, was applied for their analysis in urine and cerebrospinal fluid collected from rats [39]. The derivatives of amino acids were isolated with the aid of hollow fiber solid phase microextraction (HF-SPME) and were analyzed by GC-MS. This method generated limits of detection (LOD) situated in the range of 0.3–17 ng/mL [40]. A version of this derivatization reaction, assisted by microwave, was used for the determination of the concentrations of L-amino acids in cerebrospinal fluid in order to have a biochemical insight into central nervous system disorders [41]. A review on this topic has been very recently published and offers information on new potential biomarkers of central nervous system diseases investigated by GC-MS [42].

A variety of fatty acids play critical roles in biological systems. They exist in the diet of humans, in the bloodstream, cells and tissues of humans, both being an energy sources and membrane constituents. GC with different detections is the most widely used analytical technique for the separation and quantitation of fatty acids as methyl ester derivatives. Complete separation of common fatty acids is currently carried out by using capillary columns with polar stationary phases, and the use of a flame ionization detector (FID) offers sufficient sensitivity to measure them from complex samples. In specific applications, depending on the class of lipids to be separated, further separation and fractionation should be necessary or different columns required for GC separations [43].

Fatty acids can influence cell and tissue metabolism, function, and responsiveness to hormonal and other signals, and imbalances in fatty acids are related to a variety of diseases, which makes the measurement of fatty acids in biological samples very important [44]. For example, fatty acids (octadecanoic acid, heptadecanoic acid, tetradecanoic acid, eicosanoic acid, and cis-vaccenic acid) and their esters showed altered levels in breast cancer patients in several studies, and the oxidation of these acids is important in the development of tumor cells [45]. The use of GC-MS-based investigations allowed the identification of several metabolites resulting from metabolic processes [46, 47]. Some of the main strategies include extraction methods (e.g., liquid-liquid extraction and solid-phase microextraction), derivatization methods, column selections, and internal standard selections, in order to identify and measure the concentration of various fatty acids in biomatrices. A recent GC-MS analytical procedure for the rapid and selective derivatization of free fatty acids into methyl esters directly in plasma without transmethylation of lipid-bound fatty acids was developed based on the reaction with CH₃I in dimethyl sulfoxide and in the presence of solid bases (sodium carbonate) [48]. The method requires a very small volume of plasma (50 μL) and has a detection limit of 0.1 ng/mL. The relationships between fatty acid imbalances and the investigated diseases [44], or the influence of the use of drugs [49] have been recently reviewed.

Lipids are also frequently analyzed using GC. A variety of lipids are present in living organisms, such as glycerolipids, sterols, stanols, prenols, and phosphoglycerides. Although the direct analysis of lipids is difficult using GC, the technique is commonly used for the analysis of fatty acids present in lipids and of other lipid components [50]. Some lipids can be directly analyzed using GC-MS [51], but hydrolysis of lipids and derivatization of the fatty acids is a common procedure for analysis using GC separation.

Determinations of carbohydrates by GC are limited to mono-, di- and trisaccharides, and these can be performed after derivatization to enhance their volatility and thermal stability [46]. Upper saccharides are less stable at elevated temperatures used in GC, and only a few applications are known for these compounds. Generally, the lower saccharides are transformed into methyl ethers, acetate, trifluoroacetate, and trimethylsilyl derivatives that are separated and detected by GC.

Silylation reagents used for carbohydrate analysis include hexamethyldisilazane (HMDS), trimethylchlorosilane (TMCS), N-trimethylsilylimidazole (TMSI), N-methyl-N-trimethylsilylacetamide (MSA), N-trimethylsilyldiethylamine (TMSDEA), N-trimethylsilyldimethylamine (TMSDMA), N-methyl-N-trimethylsilyltrifluoroacetamide (MSTFA), N,O-bis(trimethylsilyl)acetamide (BSA) and N,O-bis(trimethylsilyl)trifluoroacetamide (BSTFA) [52]. The derivation conditions depend on the type of reagent and samples to be analyzed. Comparison of the analytical performances of GC-MS based on silylation derivatization with other derivatization procedures based on other chromatographic techniques, mainly with hydrophilic interaction liquid chromatography (HILIC), reversed-phase liquid chromatography (RP-LC) applied to biological samples has been recently reported [53].

From the class of derivatization of carbohydrates by alkylation reactions, the most convenient is permethylation. In practice, this reaction can be achieved using CH₃I, in the presence of dimethyl sulfoxide and a solid base (NaOH, KOH, and potassium tert-butoxide) [54, 55].

The alkylation of sugars can be performed in only one step by adding dimethyl sulfoxide, powdered sodium hydroxide, and methyl iodide directly to an aqueous solution of the sample. This procedure can be applied also to aqueous samples by an additional excess of sodium hydroxide [56]. The procedure has been applied to many biological systems, for example, ref. [57, 58, 59].

A few analytical studies have been dedicated to the determination of fatty alcohols, attempting to elucidate the role of fatty alcohols in biological systems which is still uncertain. So far, it is known that an inherited disorder of fatty alcohols metabolism, known as Sjögren-Larsson syndrome, is a consequence of a deficiency in fatty alcohols oxidation. A report describing the determination of these compounds in rat plasma samples is known, based on derivatization with pentafluorobenzoyl chloride and gas chromatography/electron capture negative ion chemical ionization-MS [60].

6. GC analysis of drugs and metabolites in main biological matrices

Drugs and, in many cases, their metabolites are of interest of being analyzed in biomatrices for clinical and pharmacological purposes. Biological samples are frequently processed in the view of GC analysis. The processing can be achieved by several liquid-liquid or solid-phase extraction techniques. This part of sample preparation has the role of simplification of sample composition and in several circumstances to enrich the sample. The main purpose of sample preparation is however to enhance the volatility of target compounds, drugs or their metabolites, which are nonvolatile in many cases. Therefore, this task is crucial for the performance of GC analysis, the method is usually applied to a large number of samples [5]. Derivatization can take place before, simultaneously with or after the extraction. This process is dependent on the detection used in GC analysis. Validation is another important part of the GC protocol and should take into consideration all aspects of the analytical process based on GC separation and detection [61]. The criteria for GC methods have not changed too much in time and they include the proof for stability, selectivity, accuracy, precision (intra- and inter-day), recovery, response linearity, computation of detection limit (LOD) and quantitation limit (LOQ), ruggedness, and other issues important to be applied to a large number of biosamples. The protocol for validation may also require re-validation, cross-validation, endogenous drug evaluation, and evaluation of matrix effects [62].

The derivatization method is usually chosen from this list of reactions: silylation, alkylation, acylation, and the formation of cyclic derivatives. A long list of derivatization reagents is available for these applications, but in practice, methodologies based on the several formations of trimethylsilyl, perfluoroacyl, or methylated-derivatives have proved to be the most versatile and extensively used [63]. The use of GC-MS systems for bioanalysis is almost always recommended for structural confirmation, and this is facilitated by the existence of comprehensive libraries containing reference MS spectra for different derivatives of many drugs and their metabolites [63]. Although much less utilized, GC coupled to Fourier transform infrared spectroscopy (FTIR) is also an alternative technique to GC-MS, providing structural information that allows, for example, the discrimination between isobars and isomers [64].

The literature reports several reviews focused on GC applications for bioanalysis for specific classes of drugs and their metabolites [65, 66, 67]. Some examples of analytical methods based on GC techniques are listed in Table 1. The majority of these techniques are applied to detect drugs of abuse, such as opiates, cocaine, cannabis, amphetamines, or benzodiazepines.

Drug name	Biological matrix	Sample preparation	GC details	Analytical performances	Ref.
Opioids: codeine, morphine, heroin, 6-acetylmorphine, desomorphine, ethylmorphine, methadone, 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine, 2-ethyl-5-methyl-3,3- diphenyl-1-pyrroline, papaverine, tramadol, O-desmetyltramadol, tapentadol	Whole blood	QuEChERS method consisted of the pretreatment of the whole blood samples using ultrasonication, the use of ethyl acetate as extraction solvent, and a previous step of sample alkalinization; phenacetin as internal standard (IS).	Capillary column (30 m; 0.25 mm; 0.25 μm, cross-linked 5% diphenyl and 95% dimethyl polysiloxane); splitless injection; MS detection in ion monitoring mode (SIM).	Linearity between 31 and 2000 ng/mL;	[68]
Glimepiride	Urine, tissues sample (a portion of the kidney, liver, spleen, and intestine)	Liquid-liquid extraction method was employed by using 1-butanol: hexane (50:50, v/v); derivatization employing N-methyl-N-(trimethylsilyl) trifluoroacetamide	30m × 0.32 mm, 0.25 μm, and 1,4-bis (dimethylsiloxy)phenylene dimethylpolysiloxane column; MS detection in TIC mode	Linearity between 500 to 2500 ng/ml	[69]
Cocaine (metabolites), methadone, and morphine	Postmortem adipose tissue	Aqueous acid extraction of analytes, alkalinization of the extract, solid-phase extraction + elution with CHCl3, and derivatization with BSTFA.	Capillary column EVDX-5MS 5% PH ME Siloxane (12.5 m × 0.20-mm i.d., 0.33-μm film thickness); Deuterated compounds are used as internal standards.	Linearity between 0.1 to 1.000 μg/g; Limits of detection: − 0.005 μg/g for cocaine cocaethylene and methadone, − 0.02 μg/g for benzoylecgonine, − 0.01 μg/g for ecgonine methyl ester and morphine	[70]
Clozapine	Human plasma	Dispersive liquid-liquid microextraction with CHCl3, and derivatization with trifluoroacetic anhydride (TFAA).	Capillary column 30m x 250 μm i.d. internally coated with 0.35 μm thick film of 5%-(phenyl)methylpolysiloxane, MS detection in SIM (selected ion monitoring) mode; Clozapine-d4 as IS.	Linearity domain over 50–800 ng/mL; Limit of quantification was set at 50 ng/mL	[71]
Cannabinoids: cannabidiol (CBD); tetrahydrocannabinol (THC) cannabinol (CBN)	Hair samples from patients	Extraction from hair in NaOH solution + Solid-phase extraction followed by derivatization with MSTFA	No detail on GC separation; MS detection in multiple reaction-monitoring (MRM) mode; deuterated internal standards: CBD-D3, THC-D3, and CBN-D3	CBD concentrations ranged from 10 to 325 pg/mg of hair	[72]
Prednisolone, prednisone, cortisol, and cortisone	Plasma samples from patients with nephrotic syndrome during oral prednisolone therapy	SPE on Sep-Pak C18 Plus short-body cartridge; derivatization with heptafluoro-n-butyric anhydride (HFBA).	Capillary GC with SPB-1 fused silica capillary column (15 m length × 0.25 mm i.d.) with 0.25 μm film thickness of stationary phase; MS detection in SIM mode	Linearity between 10 and 500 ng/mL for prednisolone; 10 and 115 ng/mL for prednisone; 1 and 140 ng/mL for cortisol; 1 and 65 ng/mL for cortisone.	[73]
Alfentanil; fentanyl and sufentanil	Urine and plasma	Hollow fiber liquid-phase microextraction using hexyl acetate as extraction solvent	DB–35MS, 30 m×0.25 mm, capillary column with a 0.15 μm stationary phase thickness; nitrogen phosphorus detection (NPD)	LODs between f 8 and 15 ng/L.	[74]
Amphetamine-type stimulants: amphetamine, methamphetamine, para-methoxyamphetamine, and (±)-3,4-methylenedioxy methamphetamine); synthetic cathinones: mephedrone, buphedrine (buphedrone ephedrine metabolite), 4-methylephedrine (mephedrone metabolite), and pentylone).	Urine samples	SPME with fiber tips C18, C18-SCX (mixed mode), and PDMS-DVB; derivatization with pentafluoropropionic anhydride (PFPA) in ethyl acetate.	DB-5ms (5% phenyl/95% methylpolysiloxane); 30 m x 0.25 mm, 0.25 μm thickness) column; MS detection in selected ion monitoring (SIM) mode; Deuterated internal standards	Limits of detection (LOD) between 5 and 25 ng/mL; Low limits of quantification (LLOQ) between 25 and 100 ng/mL.	[75]
Cathinone-type synthetic drugs: 4-fluoromethcathinone, methcathinone, 4-methylethcathinone, 3,4-dimethylmethcathinone 4-ethylmethcathinone	Human urine	The two-step derivatization: (1) oximation with hydroxylamine hydrochloride; and (2) trimethylsilylation with MSTFA.	Capillary GC column: BPX5, 30 m × 0.25 mm; 0.25 μm thickness; MS detection.	Limit of quantitation (LOQ): 15–24 μg/mL.	[76]
Catecholamine metabolite: 3,4-dihydroxyphenylglycol	Human urine patients suffering from chronic inflammatory rheumatic diseases	Extraction in ethyl acetate and derivatization with pentafluorobenzyl bromide.	DB-5ht fused silica column (15 m × 0.25 mm i.d., 0.1μ m film thickness); MS with electron-capture negative-ion chemical ionization; trideutero 3,4-dihydroxyphenylglycol	LOD: 76 amol	[77]
Carvedilol	Human plasma; bioequivalence study.	Extraction with diethyl ether and ethyl acetate and derivatization with MSTFA.	Separation with HP-5 MS column with 0.25 μm film thickness; 30 m length × 0.25 mm i.d.; MS detection	Linearity between 15 and 500 ng/mL; LOD = 5 ng/mL, and LOQ = 15 ng/mL	[78]
Diclofenac	Human plasma; bioequivalence study.	Extraction in hexane; derivatization with pentafluoropropionic anhydride (PFPA).	BP-1 fused silica capillary column (15 m × 250 μm × 0.25 μm); MS in SIM mode; 4-hydroxydiclofenac as internal standard	Linearity between 0.25 and 50 ng/mL; LOD = 0.125 and LOQ = 0.25 ng/mL	[79]
Metformin	Human serum and urine	Derivatization with pentafluoropropionic anhydride in ethyl acetate; extraction with toluene.	Capillary column Optima 17 (15 m x 0.25 mm I.D. 0.25 μm film thickness); MS detection in negative-ion chemical ionization; metformin-d6 as internal standard.	Detection limit of 300 fmol	[80]

Table 1.

GC methods for the determination of drugs in biological matrices.

Various technical aspects of using GC/MS analysis in bioanalysis are related to the complexity of the matrix of the samples of biological origin. For example, in using GC/MS on biological samples one problem is the possibility that the matrix is influencing the intensity of MS signals by the co-eluting species with the target analytes. Interferences effects are characterized by signal enhancement or suppression [81]. This phenomenon is known as the matrix effect and can be observed also in liquid chromatography coupled to electrospray ionization MS. In GC-MS the matrix effect is usually less important compared to LC-MS or LC/LC-MS. For this reason, in GC-MS the possibility of interference is frequently neglected in spite of the fact that it still should be taken into consideration when sample preparation does not remove entirely the sample matrix. The difference between the effect of matrix on the two chromatographic techniques HPLC-MS and GC-MS is caused by the fact that the two methods are based on different ionization mechanisms, and the matrix effects can have different intensities in affecting ionization. In HPLC-MS the ionization mechanism is a soft process in the interface of MS, while in GC-MS this process involves higher energy that overcomes the competition with the other possible co-eluted compounds. One of the solutions to compensate for the interference effects is the use of stable isotopically labeled standards of the target analytes [82, 83], such that both the analytes and the standard are equally affected by interferences.

7. GC determination of toxicants in biological matrices

Forensic toxicology deals with the investigation of all substances of exogenous origin that do not have a normal physiological role in the biochemical processes of the organisms [84, 85]. This includes analytical toxicology, which is focused on methodologies for the identification and quantitation of chemical substances that have adverse effects on living organisms. These analyses in biomatrices are very important, and frequently the interest is directed toward the analytical investigation of toxic species in various consumable products (e.g., food, beverages, nutraceuticals, agricultural products, pharmaceuticals, environment, or tobacco products), and also to the detection of various metabolites of these species in biological fluids and living organisms. The domain of concentrations that need to be determined by GC is generally very broad and depends on the sample provenience and the degree of contamination of investigated samples. Some recent applications of the use of GC-MS in this domain are further presented.

GC-MS techniques can be utilized, for example, for the evaluation of certain metabolic disruptions caused by various toxicants [86]. Thus, the high sensitivity of GC-MS was useful for investigating the effect of different concentration levels (toxic and subtoxic) of 3,4-methylenedioxypyrovalerone on the metabolic profile of primary mouse hepatocytes, under normothermic and hyperthermic conditions, providing new insights into the mechanism of hepatotoxicity induced by this cathinone derivative as well as the higher risks occurring under hyperthermic conditions [87]. In another study, GC-MS has been used to analyze the metabolomic changes in the rat liver after chlorpyriphos, cadmium, and their mixtures treatment [88]. By this technique, a number of eleven biomarkers have been identified, among them being butanedioic acid, myo-inositol, and urea. Another example is the use of a GC-MS-based metabolomic approach for the investigation of the metabolic mechanism of triptolide-induced reproductive toxicity in order to identify potential novel biomarkers for the early detection of spermatogenesis dysfunction [89].

Several studies are reported for measuring the toxicant levels in biological specimens. A group of four synthetic insecticides from the class of pyrethroids (tefluthrin, bifenthrin, α-cypermethrin, and deltamethrin) were determined collected samples of blood, liver, and cerebellum were analyzed 6 hours after administration with the aid of GC with electron capture detector (GC-ECD) [90]. The results provided information regarding the exposure-dose-effect relation for pyrethroids and were useful for designing pharmacokinetic models for environmentally relevant exposures to pyrethroid mixtures. Polychlorinated biphenyls (PCBs) are another class of toxicants that can be determined by GC. Their concentrations (at levels of pg/g), for example, in maternal blood during pregnancy for 169 participants, and the associations between prenatal exposure to various PCBs and the gene methylation levels were evaluated in infants by GC coupled to high-resolution mass spectrometry (GC-HRMS), after extraction with organic solvent [91].

An important class of applications refers to the investigations of specific pharmaceuticals used for reducing the effect of certain toxicants. For example, sodium salicylate has been shown to be a promising antidote for the treatment of paraquat (N,N′-dimethyl-4,4′-biphenyl dichloride) poisonings [92]. Besides the modulation of the pro-oxidant and pro-inflammatory pathways and anti-thrombogenic properties of sodium salicylate, this study was focused on proving the possibility that a direct chemical reaction may take place between sodium salicylate and paraquat as a result of charge-transfer complexes, whose stoichiometry was established from GC-MS experiments. The possibility of formation of specific adducts in biological matrices can be made using a variety of techniques including GC-MS. An example is the investigation of detoxification of severe nerve agents like cyclosarin, sarin, tabun, and VX (ethyl N-2-diisopropylaminoethyl methylphosphonothiolate) using β-cylodextrin derivatized with iodosobenzoic acid (CD-IBA) [93]. The biochemical assay was based on GC-MS determinations of the nerve agent concentrations in the extracts of chloroform obtained from biomatrix, using propyl-N,N-dimethylphosphoramidocyanidate as internal standard [93]. The possibility of the identification of toxic effects of approved drugs by using GC for their measure in biological fluids is another example of the utilization of this technique. Toxicological analysis by means of GC-MS and GC-MS-TOF for the determination of propofol in the blood and urine were used in real situations of suspected acute and lethal intoxication caused by this pharmaceutical compound [94]. Other examples are the designer drugs: α-pyrrolidinovalerophenone and its metabolites in urine and blood in an acute poisoning case [95, 96], zolpidem in postmortem specimens in a voluntary intoxication [97], antiepileptic drugs (pentobarbital, phenobarbital, and carbamazepine), and antipsychotic drugs (chlorpromazine and thioridazine) in blood samples [98], or drugs and pesticides in postmortem blood [99].

Another toxicological example is the GC determination of two β-carbolines alkaloids (harmine and harmaline), as well as the potent hallucinogen N,N-dimethyltryptamine as the main active components in ayahuasca, which is a hallucinogenic beverage used in religious rituals in South America. In this particular case, sweat was the biological matrix selected for the investigation of these species found in ayahuasca, because this can be collected by a simple and non-invasive procedure, subjected to solid-phase extraction (SPE), and followed by GC-MS analysis [100]. In general, sweat analysis has become a very useful tool in toxicology for monitoring the therapeutic drugs and drugs of abuse [101, 102].

8. Perspectives

Gas chromatography with MS or other types of detection is a mature analytical technique with broad applications in various fields, including bioanalysis. In a few examples of applications of GC in bioanalysis presented in this chapter one may conclude that its performances (separation capacity, detection limits, and complex information provided by MS) are exceeded by other related separation techniques, such as LC-MS. However, GC-MS potential in bioanalysis can be very much enhanced by the versatile sample preparation that makes biocompounds amenable to GC analysis. Generally, the new applications of GC depend on both methodology and instrumental developments and improvements. Advances in sample preparation coupled with on-line GC, high-resolution MS, bidimensional and comprehensive GC, and chemometrics are only a few directions of developing this technique and improving its analytical performances [103, 104]. GC and GC-MS perspectives in bioanalysis have been extended for different types of applications, such as for example in the case of omics-based domains [105, 106].