**Biomarkers**

Yasser M. Moustafa and Rania E. Morsi *Egyptian Petroleum Research Institute, Egypt* 

#### **1. Introduction**

164 Chromatography and Its Applications

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Patchouli Oil and Patchouli Alcohol against Formosan Subterranean Termites *Coptotermes formosanus* Shiraki (Isoptera: Rhinotermitidae). *Journal of Agricultural*  Generally, biomarkers are naturally occurring, ubiquitous and stable complexes that are objectively measured and evaluated as an indicator of a certain state. It is used in many scientific fields; medicine, cell biology, exposure assessment, astrobiology, geology and petroleum.

Biomarkers "biological markers" in medicine are complex compounds that can be used as an indicator of a particular disease state or some other physiological state of an organism. Biomarkers have been defined also as cellular, biochemical or molecular alterations that are measurable in biological media such as human tissues, cells or fluids (Hulka et al., 1990). Broader definitions include biological characteristics that can be objectively measured and evaluated as an indicator of normal or abnormal biological processes, pathogenic processes or pharmacological responses to a therapeutic intervention (Naylor, 2003).

Biomarkers can also reflect the entire spectrum of disease from the earliest manifestations to the terminal stages. Characterization of the healthy and diseased cells, when identifying a specific biomarker as an indicator of cancer, is a needed research strategy for validating biomarkers. For the nervous system, as an example, there is a wide range of techniques used to gain information about the brain in both the healthy and diseased state. These may involve measurements directly on biological media (e.g. blood or cerebrospinal fluid) or measurements such as brain imaging which do not involve direct sampling of biological media but measure changes in the composition or function of the nervous system (Mayeux , 2004). Moreover, the pharmaceutical industry is beginning to rely on biomarkers information and their importance to the future of drug discovery and development.

In practice, biomarkers science includes tools and technologies that can aid in understanding the prediction, cause, diagnosis, progression, regression, and/or the outcome of disease treatment which provide a dynamic and powerful approach to understand the spectrum markers and offer the means for homogeneous classification of a disease and risk factors which can extend the base information about the underlying pathogenesis of disease.

#### **2. Petroleum biomarkers**

Due to the variety of geological conditions and ages under which oil was formed, every crude oil exhibits a unique biomarker fingerprint. Crude oils compositions vary widely depending on the oil sources, the thermal regime during oil generation, the geological migration and the reservoir conditions. Crude oils can have large differences in:

Biomarkers 167

used methods. GC-MS can be considered as the most popular method used in the characterization of major biomarker groups. GC provides the significant advantage of the separation of different structures of biomarkers while MS can accurately detect and identify these structures. The concept and the development of these instrumentations will be briefly

Chromatography is the separation of a mixture of compounds into their individual components primarily according to their volatilities. There are numerous chromatographic techniques but gas chromatography (GC) is the most important one. It has a number of advantages over other separation techniques. It can identify (qualitate) and measure the

The GC column is the heart of the system; the structure of the stationary phase and the packed material greatly influence the separation of the compounds and affect the time of separation (retention time). Two types, packed and capillary columns, have been used. The advantages in capillary columns over packed columns are in obtaining practically improved resolution in order to give fine structured chromatographic fingerprints. The column is placed in an oven where the temperature can be controlled very accurately over a wide range of temperatures. As compounds come off the column, they enter a detector for identification. Figure 2 represent the carbon number range distribution of common

There are different types of detectors that can be employed depending on the compounds to be analyzed. Mass spectrometry (MS) has very common use in analytical laboratories that study a great variety of compounds and provides a satisfactory tool for obtaining specific fingerprints for classes and homologous series of compounds resolved by gas chromatography. The technique has both qualitative and quantitative uses include identifying and determining the structure of a compound by observing its fragments.

The mass spectrometer has long been recognized as the most powerful detector for gas chromatography. Typical MS instruments consist of three modules; an ion source: which can

mentioned.

**2.1.1 Separation by chromatographic techniques** 

amount (quantitate) various sample components.

Fig. 1. Schematic diagram of gas chromatograph.

hydrocarbons in crude oil and petroleum products.

**2.1.2 Identification by spectroscopic techniques** 

1- distribution patterns of the n- alkanes, iso-alkanes and cyclic- alkanes as well as the unresolved complex mixture (UCM) profiles 2- relative ratios of isoprenoid to normal alkanes 3- distribution patterns and concentrations of alkylated polynuclear aromatic hydrocarbons (PAHs) homologues. Most of these constituents undergo changes in their chemical structure by time as an effect of several factors among which are the biodegradation and weathering. Relative to other hydrocarbon groups in oil, there are some compounds that are more degradation-resistant in the environment as for example; *Pristane, phytane, steranes, triterpanes and porphyrins*. These undegradable compounds are known as *Biomarkers*.

Trebs (1934) was the first one to develop the biomarkers concept, with his pioneering work on the identification of porphyrins in crude oils suugesting that these porphyrins are generated from chlorophyll of plants. Blumer et al. (1963) and Blumer & Thomas (1965) isolated pristane from recent marine sediments and concluded that it was derived from the phytol side chain of chlorophyll. Later, other workers reported the present of various classes of degradationresistant organic compounds and recognized their biomarker implementations.

Petroleum biomarkers can thus be defined as complex organic compounds derived from formerly living organisms found in oil (Mobarakabad et al., 2011). They show little or no changes in their structure from the parent organic molecules and this distinguishes biomarkers from other compounds (Maioli et al., 2011). Various biomarkers formed under different geological conditions and ages can occur in different carbon ranges exhibiting different biomarker fingerprints.

From the identification point of view, biomarkers are the most important hydrocarbon groups in petroleum because they can be used for chemical fingerprinting which provides unique clues to the identity of source rocks from which petroleum samples are derived, the biological source organisms which generated the organic matter, the environmental conditions that prevailed in the water column and sediment at the time, the degree of microbial biodegradation and the thermal history (maturity) of both the rock and the oil. The information from biomarker analysis can be used also to determine the migration pathways from a source rock to the reservoir for the correlation of oils in terms of oil-to-oil and oil-to-source rock and the source potential. Also chemical analysis of biomarkers generates information of great importance to environmental forensic investigations in terms of determining the source of spilled oil, differentiating and correlating oils and monitoring the degradation process and weathering state of oils under a wide variety of conditions.

Terpanes and steranes are highly resistant to biodegradation but few studies have shown that they can be degraded to certain degree under severe weathering conditions i.e, extensive microbial degradation (Chosson, 1991).

#### **2.1 Biomarkers analysis**

The commercial availability of Gas Chromatography- Mass Spectroscopy (GC-MS) and associated data systems in the mid-1970s led to use the biomarkers for a wide variety purposes. The complex structure of biomarkers and the possible presence in low concentrations make a pressing need for more sensitive and precise analysis. The development of analytical methodologies and the combination between these methods are of great importance to separate, monitor and detect the absolute concentrations and structure of petroleum biomarkers. The use of "hybrid" or "hyphenated" techniques, which are a combination of different separate techniques, increases the analytical power of the

1- distribution patterns of the n- alkanes, iso-alkanes and cyclic- alkanes as well as the unresolved complex mixture (UCM) profiles 2- relative ratios of isoprenoid to normal alkanes 3- distribution patterns and concentrations of alkylated polynuclear aromatic hydrocarbons (PAHs) homologues. Most of these constituents undergo changes in their chemical structure by time as an effect of several factors among which are the biodegradation and weathering. Relative to other hydrocarbon groups in oil, there are some compounds that are more degradation-resistant in the environment as for example; *Pristane, phytane, steranes,* 

Trebs (1934) was the first one to develop the biomarkers concept, with his pioneering work on the identification of porphyrins in crude oils suugesting that these porphyrins are generated from chlorophyll of plants. Blumer et al. (1963) and Blumer & Thomas (1965) isolated pristane from recent marine sediments and concluded that it was derived from the phytol side chain of chlorophyll. Later, other workers reported the present of various classes of degradation-

Petroleum biomarkers can thus be defined as complex organic compounds derived from formerly living organisms found in oil (Mobarakabad et al., 2011). They show little or no changes in their structure from the parent organic molecules and this distinguishes biomarkers from other compounds (Maioli et al., 2011). Various biomarkers formed under different geological conditions and ages can occur in different carbon ranges exhibiting

From the identification point of view, biomarkers are the most important hydrocarbon groups in petroleum because they can be used for chemical fingerprinting which provides unique clues to the identity of source rocks from which petroleum samples are derived, the biological source organisms which generated the organic matter, the environmental conditions that prevailed in the water column and sediment at the time, the degree of microbial biodegradation and the thermal history (maturity) of both the rock and the oil. The information from biomarker analysis can be used also to determine the migration pathways from a source rock to the reservoir for the correlation of oils in terms of oil-to-oil and oil-to-source rock and the source potential. Also chemical analysis of biomarkers generates information of great importance to environmental forensic investigations in terms of determining the source of spilled oil, differentiating and correlating oils and monitoring the degradation process and weathering state of oils under a wide variety of conditions.

Terpanes and steranes are highly resistant to biodegradation but few studies have shown that they can be degraded to certain degree under severe weathering conditions i.e,

The commercial availability of Gas Chromatography- Mass Spectroscopy (GC-MS) and associated data systems in the mid-1970s led to use the biomarkers for a wide variety purposes. The complex structure of biomarkers and the possible presence in low concentrations make a pressing need for more sensitive and precise analysis. The development of analytical methodologies and the combination between these methods are of great importance to separate, monitor and detect the absolute concentrations and structure of petroleum biomarkers. The use of "hybrid" or "hyphenated" techniques, which are a combination of different separate techniques, increases the analytical power of the

*triterpanes and porphyrins*. These undegradable compounds are known as *Biomarkers*.

resistant organic compounds and recognized their biomarker implementations.

different biomarker fingerprints.

extensive microbial degradation (Chosson, 1991).

**2.1 Biomarkers analysis** 

used methods. GC-MS can be considered as the most popular method used in the characterization of major biomarker groups. GC provides the significant advantage of the separation of different structures of biomarkers while MS can accurately detect and identify these structures. The concept and the development of these instrumentations will be briefly mentioned.

#### **2.1.1 Separation by chromatographic techniques**

Chromatography is the separation of a mixture of compounds into their individual components primarily according to their volatilities. There are numerous chromatographic techniques but gas chromatography (GC) is the most important one. It has a number of advantages over other separation techniques. It can identify (qualitate) and measure the amount (quantitate) various sample components.

Fig. 1. Schematic diagram of gas chromatograph.

The GC column is the heart of the system; the structure of the stationary phase and the packed material greatly influence the separation of the compounds and affect the time of separation (retention time). Two types, packed and capillary columns, have been used. The advantages in capillary columns over packed columns are in obtaining practically improved resolution in order to give fine structured chromatographic fingerprints. The column is placed in an oven where the temperature can be controlled very accurately over a wide range of temperatures. As compounds come off the column, they enter a detector for identification. Figure 2 represent the carbon number range distribution of common hydrocarbons in crude oil and petroleum products.

#### **2.1.2 Identification by spectroscopic techniques**

There are different types of detectors that can be employed depending on the compounds to be analyzed. Mass spectrometry (MS) has very common use in analytical laboratories that study a great variety of compounds and provides a satisfactory tool for obtaining specific fingerprints for classes and homologous series of compounds resolved by gas chromatography. The technique has both qualitative and quantitative uses include identifying and determining the structure of a compound by observing its fragments.

The mass spectrometer has long been recognized as the most powerful detector for gas chromatography. Typical MS instruments consist of three modules; an ion source: which can

Biomarkers 169

The m/z 191 fragment is often the base peak of mass spectra of biomarkers. In general, GC/MS chromatograms of terpanes (m/z 191) are characterized by the terpane distribution in a wide range from C19 to C35 with C29 αβ- and C30 αβ-pentacyclic hopanes and C23 and C24 tricyclic terpanes being often the most abundant. As for steranes (at m/z 217 and 218), the dominance of C27,C28 and C29 homologues. Figure 4, as a representative model, shows

API: American Petroleum Institute. The larger the API, the greater the amount of the light components the oil contains and with decreasing the API, the amounts of medium and heavy weight components increase.

Fig. 4. GC-MS chromatograms at m/z 191 for light to heavy crude oils.

isoalkanes and isoprenoids: m/z 113, 127, 183

 adamantanes: m/z 135, 136, 149, 163, 177, and 191 diamantanes: m/z 187, 188, 201, 215 and229 tri-, tetra-, penta-cyclic terpanes: m/z 191

sesquiterpanes: m/z 123

25-norhopanes: m/z 177

steranes: m/z 217, 218

28,30-bisnorhopanes: m/z 163, 191

 5*α*(H)-steranes: m/z 149, 217, 218 5*β*(H)-steranes: m/z 151, 217, 218 X diasteranes: m/z 217, 218, 259 methyl-steranes: m/z 217, 218, 231, 232 monoaromatic steranes: m/z 253 triaromatic steranes: m/z 231

Fig. 2. Representative model of carbon number distribution in petroleum hydrocarbons.

Fig. 3. Schematic diagram of mass spectrometer.

convert the separated constituent into ions, a mass analyzer: which sorts and separates ions by their masses by applying electromagnetic fields and a detector: which calculate the abundances of each ion present by a quantitative method to generate signals. The size of the signals corresponds to the amount the compound present in the sample.

Characterization of some major biomarker groups is largely achieved using the following MS fragment ions:


Fig. 2. Representative model of carbon number distribution in petroleum hydrocarbons.

convert the separated constituent into ions, a mass analyzer: which sorts and separates ions by their masses by applying electromagnetic fields and a detector: which calculate the abundances of each ion present by a quantitative method to generate signals. The size of the

Characterization of some major biomarker groups is largely achieved using the following

signals corresponds to the amount the compound present in the sample.

Fig. 3. Schematic diagram of mass spectrometer.

MS fragment ions:

alkyl-cyclohexanes: m/z 83

methyl-alkyl-cyclohexanes: m/z 97


The m/z 191 fragment is often the base peak of mass spectra of biomarkers. In general, GC/MS chromatograms of terpanes (m/z 191) are characterized by the terpane distribution in a wide range from C19 to C35 with C29 αβ- and C30 αβ-pentacyclic hopanes and C23 and C24 tricyclic terpanes being often the most abundant. As for steranes (at m/z 217 and 218), the dominance of C27,C28 and C29 homologues. Figure 4, as a representative model, shows

API: American Petroleum Institute. The larger the API, the greater the amount of the light components the oil contains and with decreasing the API, the amounts of medium and heavy weight components increase. Fig. 4. GC-MS chromatograms at m/z 191 for light to heavy crude oils.

Biomarkers 171

Relative distribution of regular C27-C28-C29 steranes

C30 sterane index: C30/(C27 to C30) steranes selected

C27-C28-C29 monoaromatic steranes (MA) distribution.

C26 TA (20S)/sum of C26 TA (20S) through C28 TA (20R)

Regular C27-C28-C29 steranes/C30αβ-hopanes

C26 TA (20S)/[C26 TA (20S) +C28 TA (20S)] C28 TA (20S)/[C26 TA (20S) +C28 TA (20S)]

The distribution of n-alkanes in crude oils can be used to indicate the organic matter source (Duan and Ma, 2001). For example, the increase in the n-C15 to n-C20 suggests marine organic matters with contribution to the biomass from algae and plankton (Peters and Moldowan, 1993). Oil samples characterized by uniformity in n-alkanes distribution patterns suggest that they are related and have undergone similar histories with no signs of

Carbon preference index, obtained from the distribution of n-alkanes, is the ratio obtained by dividing the sum of the odd carbon-numbered alkanes to the sum of the even carbonnumbered alkanes. CPI is affected by both source and maturity of crude oils (Tissot and Welte, 1984). CPI of petroleum oils ranging about 1.00 generally shows no even or odd carbon preference indicates mature samples. Also, it can be used in source identification; petroleum

The degree of waxiness can be expressed by the ΣC21-C31/ΣC15-C20 ratios. The oils characterized by high abundance of n-C15to n-C20 n-alkanes in the saturate fractions

origin contaminants characteristically have CPI values close to one (Maioli et al., 2011).

**Biomarker classes Diagnostic ratios** 

C27 αββ*/*C29 αββ steranes (at m/z 218)

C28 αββ*/*C29 αββ steranes (at m/z 218)

C27 αββ*/*(C27 αββ + C28 αββ + C29αββ) (at m/z 218)

 C28 αββ*/*(C27 αββ + C28 αββ + C29 αββ) (at m/z 218) C29 αββ*/*(C27 αββ + C28 αββ + C29 αββ) (at m/z 218)

diasteranes/regular steranes

C20 TA/(C20 TA + C21 TA)

C27 TA (20R)/C28 TA (20R) C28 TA (20R)/C28 TA (20S)

Table 1. Examples of some diagnostic ratios of biomarkers frequently used for the

**4. Examples of parameters used in fingerprinting** 

biodegradation (Ficken et al. 2000 and Duan and Ma, 2001).

*Steranes*

*Monoaromatic steranes* 

*Triaromatic steranes*

environmental forensic studies.

**4.1 Normal -alkanes characteristics** 

**4.2 Carbon preference index (CPI)** 

**4.3 Degree of waxiness** 

GC-MS chromatograms at m/z 191 for light (API > 35), medium (API: 25–35), and heavy (API < 25) crude oils (Wang et al., 2006).

#### **3. Diagnostic ratios of biomarkers**

Biomarker diagnostic parameters have been long established and are widely used by geochemists for oil correlation; determination of organic input and precursors, depositional environment, assessment of thermal maturity and evaluation of in-reservoir oil biodegradation (Peters et al., 2005). Diagnostic ratios (DRs) can either be calculated from quantitative (i.e., compound concentrations) or semi-quantitative data (i.e., peak areas or heights). Also, many diagnostic ratios currently used in oil spill and environmental studies. Oil–oil correlations are based on the concept that the composition of biomarkers in spill samples does not differ from those of the candidate source oils. Most biomarkers in spill samples and source oils, in particular those homologous series of biomarkers with similar structure, show little or no changes in their diagnostic ratios. An important benefit of comparing diagnostic ratios of spilled oil and suspected source oils is that concentration effects are minimized. In addition, the use of ratios (rather than absolute values) tends to induce a self-normalizing effect on the data because the variations due to the fluctuation of instrument operating conditions day-to-day, operator, and matrix effects are minimized. Therefore, comparison of diagnostic ratios reflects more directly differences of the target biomarker distribution between samples.


GC-MS chromatograms at m/z 191 for light (API > 35), medium (API: 25–35), and heavy

Biomarker diagnostic parameters have been long established and are widely used by geochemists for oil correlation; determination of organic input and precursors, depositional environment, assessment of thermal maturity and evaluation of in-reservoir oil biodegradation (Peters et al., 2005). Diagnostic ratios (DRs) can either be calculated from quantitative (i.e., compound concentrations) or semi-quantitative data (i.e., peak areas or heights). Also, many diagnostic ratios currently used in oil spill and environmental studies. Oil–oil correlations are based on the concept that the composition of biomarkers in spill samples does not differ from those of the candidate source oils. Most biomarkers in spill samples and source oils, in particular those homologous series of biomarkers with similar structure, show little or no changes in their diagnostic ratios. An important benefit of comparing diagnostic ratios of spilled oil and suspected source oils is that concentration effects are minimized. In addition, the use of ratios (rather than absolute values) tends to induce a self-normalizing effect on the data because the variations due to the fluctuation of instrument operating conditions day-to-day, operator, and matrix effects are minimized. Therefore, comparison of diagnostic ratios reflects more directly differences of the target

(API < 25) crude oils (Wang et al., 2006).

**3. Diagnostic ratios of biomarkers** 

biomarker distribution between samples.

*Acyclic Isoprenoids* 

*Terpanes* 

**Biomarker classes Diagnostic ratios** 

 pristane/phytane pristane/n-C17 phytane/n-C18

> C21/C23 tricyclic terpane C23/C24 tricyclic terpane

C23 tricyclic terpane/C30αβ hopane C24 tricyclic terpane/C30αβ hopane

tricyclic terpanes (C19-C26)*/*C30 αβ hopane C31 homohopane (22S)/C31 homohopane (22R) C32 bishomohopane (22S)/C32 bishomohopane (22R) C33 trishomohopane (22S)/C33 trishomohopane (22R)

Relative homohopane distribution

 C2718α*,* 21β-trisnorhopane/C27 17α*,* 21β-trisnorhopane C28 bisnorhopane/C30αβ hopane

 C29αβ-25-norhopane/C30αβ hopane C29αβ-30-norhopane/C30αβ hopane

moretane(C30 βα hopane)/C30αβ hopane

homohopane index

oleanane/C30 αβ hopane

(C31-C35)*/*C30 αβ hopane

gammacerane/C30αβ hopane

C24 tertracyclic/C26 tricyclic (S)/C26 tricyclic (R) terpane


Table 1. Examples of some diagnostic ratios of biomarkers frequently used for the environmental forensic studies.
