|Year : 2019 | Volume
| Issue : 1 | Page : 13-19
Estimation of the postmortem interval using chromatographic fingerprints of volatile organic compounds from muscle
Zhiyuan Xia1, Beibei Liu2, Haimei Zhou2, Ping Lv2, Jinqi Ma2
1 Institute of Evidence Law and Forensic Science, Key Laboratory of Evidence Science, China University of Political Science and Law, Ministry of Education, Beijing, China
2 Department of Forensic Medicine, Henan University of Science and Technology, Luoyang, Henan, China
|Date of Web Publication||28-Mar-2019|
Dr. Haimei Zhou
Department of Forensic Medicine, Henan University of Science and Technology, Luoyang, Henan 471003
Source of Support: None, Conflict of Interest: None
Estimation of the postmortem interval (PMI) is a crucial task in the field of forensic pathology and has unfortunately not been properly resolved. In this study, we analyzed volatile organic compounds (VOCs) in rat muscle samples collected at different PMIs and studied the feasibility of muscle VOC fingerprinting as a new method for PMI estimation. In total, 110 rats were sacrificed and stored at a constant temperature (25°C). Rat skeletal muscle samples were collected at 0–10-day postmortem, and then the VOCs were determined using a method of headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry. The correlations between the VOCs (species and quantities) and PMIs were carefully analyzed and standard muscle VOC fingerprints at 25°C were established for different PMIs. To further test the accuracy of muscle VOC fingerprinting as a method for PMI estimation, ten additional rats with known PMIs were studied. We identified 15 kinds of VOCs and the number of VOC species increased with the PMI. The total peak areas of the VOCs increased significantly with the postmortem day (adjusted R2 = 0.96–0.97). The mean error of the VOC fingerprinting for PMI estimation was 0.5 days and the mean relative error was 8.33%. We concluded that muscle VOC fingerprinting combining the use of VOC species and peak areas is accurate and effective and could be used as an alternative approach for PMI estimation in forensic practice. Although the preliminary results are encouraging, further studies in human cadavers under real case conditions are needed.
Keywords: Chromatographic fingerprint, gas chromatography-mass spectrometry, muscle, postmortem interval, solid-phase microextraction, volatile organic compound
|How to cite this article:|
Xia Z, Liu B, Zhou H, Lv P, Ma J. Estimation of the postmortem interval using chromatographic fingerprints of volatile organic compounds from muscle. J Forensic Sci Med 2019;5:13-9
|How to cite this URL:|
Xia Z, Liu B, Zhou H, Lv P, Ma J. Estimation of the postmortem interval using chromatographic fingerprints of volatile organic compounds from muscle. J Forensic Sci Med [serial online] 2019 [cited 2019 Sep 15];5:13-9. Available from: http://www.jfsmonline.com/text.asp?2019/5/1/13/255126
| Introduction|| |
Estimation of the postmortem interval (PMI) or time since death is a crucial but challenging task in the field of forensic pathology. Accurate PMI determination is helpful for indicating the timeline of events associated with death or limiting the number of possible suspects in criminal cases. In practice, PMI estimations are usually based on postmortem changes, including supravital reactions, algor mortis, rigor mortis, livor mortis, and stages of decomposition (i.e., fresh, bloated, active decay, advanced decay, and dry/remains). These traditional methods are subjective and insensitive. Improved methods such as infrared spectroscopy, DNA and RNA quantification, protein degradation, and analysis of adenosine triphosphate levels have been applied in recent studies.,,,, However, most of these methods are in experimental stages or have their own limitations in forensic practice. To date, no single method has been developed to accurately determine the PMI, especially when the body is found in an advanced stage of decomposition.
Decomposition of a human body results in production of volatile organic compounds (VOCs) that accumulate in the body or released into the surrounding environment. The investigation of VOCs associated with human body decomposition is an emerging field in forensic taphonomy and shows potential for locating human remains or clandestine graves of missing homicide victims.,,,,
Studies in food science have indicated that VOCs produced by animal meat do not appear simultaneously during tissue spoilage but occur in a particular chronological order, and the amounts and species of VOCs are significantly correlated with the shelf life and quality of the meat.,,,, Currently, VOC-based odor fingerprinting is used in food sanitation as a useful indicator of the shelf life and freshness of meat products.,,, Cadaver muscle and meat products have a lot in common, especially with respect to the process of biological tissue decomposition. The decomposition of both samples is caused by the action of microorganisms and enzymes, and the PMI in forensic pathology and in shelf life calculation in food science both require estimation of a time interval. Therefore, we hypothesized that time-dependent VOC profiles or VOC fingerprints of cadaver muscle could be useful for estimation of PMIs in forensic pathology.
Headspace solid-phase microextraction (SPME) and gas chromatography-mass spectrometry (GC-MS) are rapid and sensitive techniques for the analysis of VOC fingerprints. Methods based on SPME-GC-MS can provide systematic characterization of the substances detected, ratios of all analytes (instead of a single target), and construction of specific spectra for different compounds. Chromatographic fingerprints have been successfully used for quality control of many products, including herbal extracts, olive oil, and wine.,, Therefore, we believed that cadaver muscle chromatographic fingerprints could also be acquired using headspace SPME-GC-MS.
In this context, we designed the present research aiming to (i) identify VOCs from postmortem rat muscle using headspace SPME-GC-MS, (ii) investigate the relationships between VOC changes and the PMI, (iii) establish reference chromatographic fingerprints for different postmortem days, and (iv) study the accuracy of PMI estimation using muscle VOC fingerprinting.
| Materials and Methods|| |
One hundred and ten healthy Sprague-Dawley rats, either sex, ranging from 200 to 300 g were euthanized by cervical vertebrae dislocation. The animals were randomly divided into 11 groups of 10 rats each. All animals were placed in foam boxes, which were sealed with thin and breathable silk cloth and kept at a constant temperature (25°C). The temperature was controlled by an air-conditioner. A skeletal muscle sample was obtained from the left lower hind limb of each rat at PMIs of 0 (immediate), 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10 days. Muscle tissue was chosen because of its slower rate of degradation than subcutaneous fat and internal organs. Then, the samples were immediately sent to the laboratory for VOC characterization.
Characterization of volatile organic compounds from postmortem rat muscle
Headspace solid-phase microextraction
A muscle sample (3 g) from each individual was cut up and transferred to a 50-mL glass bottle. The bottle was hermetically sealed and kept at 50°C for 10 min. A 4-cm length of SPME fiber (DVB/CAR/PDMS 50/30 mm, Supelco, Bellefonte, PA, USA) was exposed to the headspace in the bottle at 50°C for 30 min.
Gas chromatography-mass spectrometry analysis
For identification of VOCs, the adsorbates on the SPME fiber were analyzed by GC-MS after desorption by exposure to the injection port for 2 min at 250°C. GC separations and the mass spectrometric measurements were performed on an Agilent 6890/5973N series GC-MS (Agilent, Santa Clara, CA, USA) with a HP-5 ms column (30 m × 0.25 mm × 0.25 μm). The carrier gas was helium (1.0 mL/min). The oven temperature was maintained at 35°C for 3 min, ramped to 85°C 10°C/min, to 140°C at 2°C/min, to 230°C at 50°C/min, and then maintained at 230°C for 5 min. The injection temperature was 250°C and the injection mode was splitless. The MS detector was operated in electron ionization mode (70 eV). The scan range was m/z19–350 m/z. The interface temperature was 280°C and the ion source temperature was 230°C. Compounds were identified by interpreting fragmentation spectra and by comparison with the NIST/EPA/NIH Mass Spectral Library 2005 (Agilent NIST05a Libraries, Agilent, Santa Clara, CA, USA). The amount of each VOC was estimated using the peak areas obtained from the total ion chromatograms.
Data processing was performed using OriginPro software version 8 (OriginLab Corporation, Northampton, MA, USA).
| Results and Discussion|| |
Identification of volatile organic compounds from postmortem rat muscle
We investigated VOCs generated by postmortem rat muscle for 10 d at 25°C using headspace SPME-GC-MS. False-positive results caused by feces of insects (e.g., flies) were avoided by placing the animals in foam boxes and sealing the boxes with thin and breathable silk cloth. The equilibrium temperature, equilibrium period, extraction period, desorption period, and decontamination period of the fiber were monitored or strictly controlled to guarantee the reliability of results. Fifteen VOC species were identified [Table 1].
|Table 1: Volatile organic compound species identified by solid-phase microextraction-gas chromatography-mass spectrometry of postmortem rat muscle|
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These VOCs consisted of nine aromatic compounds, three sulfur compounds, two organic acids, and one heterocyclic compound. Compared with an earlier study on VOC species, we identified the same organic sulfides, more aromatic compounds (i.e., 3-methyl-1H-indole, benzenepropanoic acid, ethyl ester, and N-benzylidene-2-phenylethanamine), and fewer organic acids, ketones, and alcohols. The decrease in organic acids, ketones, and alcohols could be attributed to their main source being fat degradation, which means they will not be prevalent in muscle decomposition. The increase in aromatic compounds could be attributed to the cutting up of the sample and thus better exposure of VOC to the microextraction fiber. In addition, the sample pretreatment improved the degree of VOC volatilization and VOC concentrations so that VOC could be better extracted. We detected different VOCs in this study than those in meat products primarily because the meat products were exposed to the environment where aerobic bacteria contributed to the decomposition process. By contrast, in our study, the rat muscle was protected by the skin and mainly affected by anaerobic bacteria inside the body.
Volatile organic compound changes with the postmortem interval
Significant correlations between VOC changes in meat products and the storage period have been found in food science. It is generally accepted that VOCs are primarily produced by decomposition of proteins, fats, and sugars. For instance, aromatic compounds, nitrogen compounds, and sulfur compounds are primarily degradation products of proteins, whereas organic acids, aldehydes, ketones, and esters are primarily produced by degradation of fats and sugars. Moreover, microbiological studies have indicated that VOC profiles are strongly correlated with bacterial species, and the appearance of certain VOCs can suggest the presence of specific bacteria. Examples of such relationships are indoles and Escherichia More Details coli, dimethyl disulfide, and Pseudomonas aeruginosa or Staphylococcus aureus, and propionic acid and Staphylococcus., From this perspective, changes in VOCs are the result of transition or succession of dominant bacteria, which is largely influenced by accumulation of harmful products, pH changes, or depletion of essential nutrients in the system.
The VOC distributions at different PMIs are shown in [Figure 1].
|Figure 1: Volatile organic compound distributions at different postmortem intervals|
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Our results indicated that the number of VOC species increased significantly with the PMI in rat muscle. No VOCs were identified on the 1st-day postmortem. The number of VOCs identified on days 2, 3, 4, 5–7, and 8–10 was 3, 8, 11, 14, and 15, respectively. Interestingly, a number of amine VOCs were identified, particularly at later PMIs.
The correlations between the peak areas of the 15 VOCs and PMI are shown in [Table 2].
|Table 2: Relationships between the 15 volatile organic compounds from postmortem rat muscle and the postmortem interval|
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The levels of dimethyl disulfide and dimethyl trisulfide tended to decrease with increasing PMI, whereas phenylethyl alcohol, 2-piperidinone, epsilon-thiocaprolactam, and 4-methylpentanoic acid increased with increasing PMI. Benzaldehyde levels decreased from days 3 to 8 and recovered from days 9 to 10, whereas 4-methylphenol levels increased from days 2 to 7 but decreased from days 8 to 10. The adjusted R2 of the regression functions for different VOCs ranged from 0.15 to 0.96. The peak areas of indole, 4-methylphenol, sulfur compounds, and 2-piperidinone were larger than those of other VOCs. The relationship between the total peak area of the 15 VOCs and the PMI is shown in [Figure 2]. The total peak area was increased by 35 × 105/day from day 2 to day 5 and 10 × 105/day from day 6 to day 10. The regression functions were y = 17.05x2 + 164.36x − 246.36 (adjusted R2 = 0.96) for day 2–5 and y = 2.24x+ 101.13 (adjusted R2 = 0.97) for day 6–10.
|Figure 2: Changes in the volatile organic compound total peak areas with the postmortem interval|
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Both the VOC species and total peak area revealed a similar three-stage decomposition model. In Stage 1 (1-day postmortem), no compounds were detected. In Stage 2 (2–5 days postmortem), the number of VOCs increased rapidly and the total peak areas increased by 35 × 105/day. In Stage 3 (6–10 days postmortem), the number of VOCs increased slowly and the total peak areas increased by 10 × 105 but were smaller than those in Stage 2. These changes are supported by the bacterial growth model and the forensic cadaver decomposition stages (i.e., fresh, active decay, and advanced decay).
Establishing standard chromatographic fingerprints for different postmortem days
It was not necessary to establish reference fingerprints for day 0 (immediate) and day 1 because no VOCs were detected within the first 24 h, which indicated that the decomposition rate during this period was relatively slow. Reference chromatographic fingerprints for days 2–10 were established using both the mean peak area of each VOC at different PMIs and the corresponding retention times [Figure 3]. In our results, the standard chromatographic fingerprints for each day (day 2 to day 10) were different from one another. This will be useful for distinguishing the postmortem day and quickly obtaining a rough estimate of the PMI.
|Figure 3: Reference volatile organic compound chromatographic fingerprints at different postmortem days|
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Validation of chromatographic fingerprints and their potentials in postmortem interval estimation
It is widely believed that a function consisting of multiple parameters can increase the accuracy of PMI estimation. However, it is usually very difficult to obtain such regression function as most parameters have complicated nonlinear correlations with PMI, which makes it impossible to integrate them into one function. The fingerprinting technique provides a solution to this problem because we can evaluate whether a tested sample is from a certain source by comparing many parameters or markers between suspicious samples and reference sources. As an example of this in forensic science, DNA fingerprinting or DNA profiling is often used to confirm or eliminate suspects in criminal cases.
In this study, we hypothesized that the chromatographic fingerprinting technique could be used to compare muscle samples at different postmortem days and serve as an alternative approach for PMI estimation. Cosine similarity was used to determine the similarities between the tested VOCs and the reference chromatographic VOC fingerprints. This method can be used to measure the distance between two points in a high-dimensional space. The formula is written as follows:
where T is the similarity, xi is the peak area of each VOC from the ten additional tested samples, and yi is the peak area of each VOC from the reference chromatographic fingerprints.
The similarity of each tested sample with each reference chromatographic fingerprint was calculated separately and the highest similarities were selected for the final PMI estimation [Table 3]. For example in line 6 of [Table 3], the sample (actual PMI = 6 days) was most similar to the reference chromatographic fingerprints on 4 days, so the estimated PMI was 4 days. The maximum error for PMI estimation was 2 days (see actual PMIs for day 6 and day 8) and the determined PMI was consistent with the actual PMI for days 2, 3, 5, 7, 9, and 10. In general, the mean error was 0.5 day and relative error was 8.33%. These results suggest that PMI determinations using the VOC chromatographic fingerprint are relatively accurate and effective, and this technique shows potential for future forensic applications.
|Table 3: Accuracy of postmortem interval estimation using chromatographic fingerprinting|
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Limitations of our experiment
Although our preliminary results are promising and encouraging, there are several limitations that are worth mentioning. First, rats are small animals and are easy to obtain for research. However, cadavers of other animals, such as pigs or monkeys, would be better models for human cadavers, and human cadavers would be the best models. Second, intertransformation between the VOCs should be investigated and may clarify how certain VOCs change or interact with others. Third, data based on only one controlled temperature are not applicable to the complicated environments in real forensic practice. Therefore, further studies on humans under different conditions are needed.
| Conclusion|| |
In this study, VOC production from postmortem rat muscle was investigated for 10 days at 25°C and reference VOC chromatographic fingerprints were established for day 2 to day 10 postmortem. We found that different VOCs correlated with the PMI to various degrees. Both VOC species and total area were significantly correlated with the PMI. PMI estimation using VOC chromatographic fingerprints is rapid and accurate. The results are encouraging, but more research on human cadavers under real conditions is needed in the future.
Financial support and sponsorship
This research was partially supported by China Scholarship Council (CSC 201707070113).
Conflicts of interest
The authors declare there is no conflict of interest regarding the publication of this paper.
| References|| |
Lee Goff M. Early post-mortem changes and stages of decomposition in exposed cadavers. Exp Appl Acarol 2009;49:21-36.
Yao Y, Wang Q, Jing XL, Li B, Zhang YM, Wang ZJ, et al.
Relationship between PMI and ATR-FTIR spectral changes in swine costal cartilages and ribs. Fa Yi Xue Za Zhi 2016;32:21-5.
Johnston E, Stephenson M. DNA profiling success rates from degraded skeletal remains in Guatemala. J Forensic Sci 2016;61:898-902.
Ma J, Pan H, Zeng Y, Lv Y, Zhang H, Xue A, et al.
Exploration of the R code-based mathematical model for PMI estimation using profiling of RNA degradation in rat brain tissue at different temperatures. Forensic Sci Med Pathol 2015;11:530-7.
Pittner S, Ehrenfellner B, Monticelli FC, Zissler A, Sänger AM, Stoiber W, et al.
Postmortem muscle protein degradation in humans as a tool for PMI delimitation. Int J Legal Med 2016;130:1547-55.
Sun T, Yang T, Zhang H, Zhuo L, Liu L. Interpolation function estimates post mortem interval under ambient temperature correlating with blood ATP level. Forensic Sci Int 2014;238:47-52.
Forbes SL, Perrault KA. Decomposition odour profiling in the air and soil surrounding vertebrate carrion. PLoS One 2014;9:e95107.
Cablk ME, Szelagowski EE, Sagebiel JC. Characterization of the volatile organic compounds present in the headspace of decomposing animal remains, and compared with human remains. Forensic Sci Int 2012;220:118-25.
Brasseur C, Dekeirsschieter J, Schotsmans EM, de Koning S, Wilson AS, Haubruge E, et al.
Comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry for the forensic study of cadaveric volatile organic compounds released in soil by buried decaying pig carcasses. J Chromatogr A 2012;1255:163-70.
Stefanuto PH, Perrault KA, Stadler S, Pesesse R, LeBlanc HN, Forbes SL, et al.
GC × GC-TOFMS and supervised multivariate approaches to study human cadaveric decomposition olfactive signatures. Anal Bioanal Chem 2015;407:4767-78.
Perrault KA, Stefanuto PH, Stuart BH, Rai T, Focant JF, Forbes SL. Detection of decomposition volatile organic compounds in soil following removal of remains from a surface deposition site. Forensic Sci Med Pathol 2015;11:376-87.
Forbes SL, Troobnikoff AN, Ueland M, Nizio KD, Perrault KA. Profiling the decomposition odour at the grave surface before and after probing. Forensic Sci Int 2016;259:193-9.
Ma Y, Zhu B, Zhang L, Xu X. Evaluation of pork freshness by HS-SPME-GC-MS. Food Sci 2011;32:253-6.
Zhu Y, Zou X, Huang X, Shi J, Hong Z. Volatile components of variation in pork storage process. Sci Technol Food Ind 2012;33:374-8.
Wang X, Chai C. Determination of volatile components of pork during spoilage. Food Sci Technol 2012;37:148-52.
Saraiva C, Oliveira I, Silva JA, Martins C, Ventanas J, García C. Implementation of multivariate techniques for the selection of volatile compounds as indicators of sensory quality of raw beef. J Food Sci Technol 2015;52:3887-98.
Xu Y, Liu Y, Jiang C, Zhang C, Li X, Zhu D, et al.
Determination of volatile compounds in turbot (Psetta maxima
) during refrigerated storage by headspace solid-phase microextraction and gas chromatography-mass spectrometry. J Sci Food Agric 2014;94:2464-71.
Zhang Z, Li G, Luo L, Chen G. Study on seafood volatile profile characteristics during storage and its potential use for freshness evaluation by headspace solid phase microextraction coupled with gas chromatography-mass spectrometry. Anal Chim Acta 2010;659:151-8.
Mikš-Krajnik M, Yoon YJ, Ukuku DO, Yuk HG. Identification and quantification of volatile chemical spoilage indexes associated with bacterial growth dynamics in aerobically stored chicken. J Food Sci 2016;81:M2006-14.
Wang L, Tian X, Wei W, Chen G, Wu Z. Fingerprint analysis and quality consistency evaluation of flavonoid compounds for fermented Guava leaf by combining HPLC-TOF-ESI-MS and chemometric methods. J Sep Sci 2016;39:3906-16.
Bagur-González MG, Pérez-Castaño E, Sánchez-Viñas M, Gázquez-Evangelista D. Using the liquid-chromatographic-fingerprint of sterols fraction to discriminate virgin olive from other edible oils. J Chromatogr A 2015;1380:64-70.
Song L, Wang S, Duan X, Liu X, Li Z, Nie L, et al.
Chromatographic fingerprint combined with content of asperosaponin VI and antioxidant activity for quality evaluation of wine-fried dipsaci radix. Nat Prod Commun 2014;9:773-8.
Bos LD, Sterk PJ, Schultz MJ. Volatile metabolites of pathogens: A systematic review. PLoS Pathog 2013;9:e1003311.
Boots AW, Smolinska A, van Berkel JJ, Fijten RR, Stobberingh EE, Boumans ML, et al.
Identification of microorganisms based on headspace analysis of volatile organic compounds by gas chromatography-mass spectrometry. J Breath Res 2014;8:027106.
Paczkowski S, Nicke S, Ziegenhagen H, Schütz S. Volatile emission of decomposing pig carcasses (Sus scrofa domesticus
L.) as an indicator for the postmortem interval. J Forensic Sci 2015;60 Suppl 1:S130-7.
Zwietering MH, Jongenburger I, Rombouts FM, van 't Riet K. Modeling of the bacterial growth curve. Appl Environ Microbiol 1990;56:1875-81.
Vennemann M, Koppelkamm A. MRNA profiling in forensic genetics I: Possibilities and limitations. Forensic Sci Int 2010;203:71-5.
Murphy E. Forensic DNA typing. Annu Rev Criminol 2017;1:497-515.
[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3]