Metabolic Profiling of Femoral Muscle from Rats at Different Periods of Time After Death

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2018 Sep 15

PMID 30216363

Citations 7

Authors

Tieshuai Du

Zebin Lin

Yaling Xie

Xing Ye

Chunyan Tu

Kaidi Jin

Jianhui Xie

Yiwen Shen

Affiliations

Soon will be listed here.

Abstract

Clarification of postmortem metabolite changes can help characterize the process of biological degradation and facilitate investigations of forensic casework, especially in the estimation of postmortem interval (PMI). Metabolomics can provide information on the molecular profiles of tissues, which can aid in investigating postmortem metabolite changes. In this study, liquid chromatography-mass spectrometric (LC-MS) analysis was performed to identify the metabolic profiles of rat femoral muscle at ten periods of time after death within 168 h. The results obtained by reversed-phase liquid chromatography (RPLC)- and hydrophilic interaction liquid chromatography (HILIC)- electrospray ionization (ESI±) have revealed more than 16,000 features from all four datasets. Furthermore, 915 of these features were identified using an in-house database. Principal component analysis (PCA) demonstrated the time-specific features of molecular profiling at each period of time after death. Moreover, results from partial least squares projection to latent structures-discriminant analysis (PLS-DA) disclosed a strong association of metabolic alterations of at least 59 metabolites with the time since death, especially within 48 h after death, which expounds these metabolites as potential indicators in PMI estimation. Altogether, our results illustrate the potentiality of metabolic profiling in the evaluation of PMI and provide candidate metabolite markers with strong correlation with time since death for forensic purpose.

Citing Articles

"Omics" and Postmortem Interval Estimation: A Systematic Review.

Secco L, Palumbi S, Padalino P, Grosso E, Perilli M, Casonato M Int J Mol Sci. 2025; 26(3).

PMID: 39940802 PMC: 11817326. DOI: 10.3390/ijms26031034.

A fundamental study on postmortem submersion interval estimation by metabolomics analyzing of gastrocnemius muscle from submersed rat models in freshwater.

Zhang F, Wang L, Zeng K, Dong W, Yuan H, Ma X Int J Legal Med. 2024; 138(5):2037-2047.

PMID: 38802694 DOI: 10.1007/s00414-024-03258-4.

Postmortem metabolomics: influence of time since death on the level of endogenous compounds in human femoral blood. Necessary to be considered in metabolome study planning?.

Steuer A, Wartmann Y, Schellenberg R, Mantinieks D, Glowacki L, Gerostamoulos D Metabolomics. 2024; 20(3):51.

PMID: 38722380 PMC: 11081988. DOI: 10.1007/s11306-024-02117-y.

The Role of Protein Degradation in Estimation Postmortem Interval and Confirmation of Cause of Death in Forensic Pathology: A Literature Review.

Huang W, Zhao S, Liu H, Pan M, Dong H Int J Mol Sci. 2024; 25(3).

PMID: 38338938 PMC: 10855206. DOI: 10.3390/ijms25031659.

A preliminary study on early postmortem submersion interval (PMSI) estimation and cause-of-death discrimination based on nontargeted metabolomics and machine learning algorithms.

Zhang F, Wang L, Dong W, Zhang M, Tash D, Li X Int J Legal Med. 2022; 136(3):941-954.

PMID: 35099605 DOI: 10.1007/s00414-022-02783-4.

References

Kordalewska M, J Markuszewski M . Metabolomics in cardiovascular diseases. J Pharm Biomed Anal. 2015; 113:121-36. DOI: 10.1016/j.jpba.2015.04.021. View

Rodgers M, Saghatelian A, Yang P . Identification of an overabundant cholesterol precursor in hepatitis B virus replicating cells by untargeted lipid metabolite profiling. J Am Chem Soc. 2009; 131(14):5030-1. PMC: 4166558. DOI: 10.1021/ja809949r. View

Hubig M, Muggenthaler H, Mall G . Confidence intervals in temperature-based death time determination. Leg Med (Tokyo). 2014; 17(1):48-51. DOI: 10.1016/j.legalmed.2014.08.002. View

Gottfries C . HUMAN BRAIN LEVELS OF MONOAMINES AND THEIR METABOLITES. POSTMORTEM INVESTIGATIONS. Acta Psychiatr Scand. 2017; 61(S280):49-61. DOI: 10.1111/acps.1980.61.s280.49. View

Endo T, Hara S, Kuriiwa F, Kano S . Postmortem changes in the levels of monoamine metabolites in human cerebrospinal fluid. Forensic Sci Int. 1990; 44(1):61-8. DOI: 10.1016/0379-0738(90)90168-x. View

Wang T, Gupta D . Metabolite profiles in heart failure: looking for unique signatures in a heterogeneous syndrome. J Am Coll Cardiol. 2015; 65(15):1521-4. DOI: 10.1016/j.jacc.2015.02.019. View

Kaszynski R, Nishiumi S, Azuma T, Yoshida M, Kondo T, Takahashi M . Postmortem interval estimation: a novel approach utilizing gas chromatography/mass spectrometry-based biochemical profiling. Anal Bioanal Chem. 2016; 408(12):3103-12. DOI: 10.1007/s00216-016-9355-9. View

Madea B, Rodig A . Time of death dependent criteria in vitreous humor: accuracy of estimating the time since death. Forensic Sci Int. 2006; 164(2-3):87-92. DOI: 10.1016/j.forsciint.2005.12.002. View

Hirakawa K, Koike K, Uekusa K, Nihira M, Yuta K, Ohno Y . Experimental estimation of postmortem interval using multivariate analysis of proton NMR metabolomic data. Leg Med (Tokyo). 2009; 11 Suppl 1:S282-5. DOI: 10.1016/j.legalmed.2009.02.007. View

10.

Madea B, Henssge C, Honig W, Gerbracht A . References for determining the time of death by potassium in vitreous humor. Forensic Sci Int. 1989; 40(3):231-43. DOI: 10.1016/0379-0738(89)90181-3. View

11.

Eriksson L, Andersson P, Johansson E, Tysklind M . Megavariate analysis of environmental QSAR data. Part I--a basic framework founded on principal component analysis (PCA), partial least squares (PLS), and statistical molecular design (SMD). Mol Divers. 2006; 10(2):169-86. DOI: 10.1007/s11030-006-9024-6. View

12.

Ith M, Scheurer E, Kreis R, Thali M, Dirnhofer R, Boesch C . Estimation of the postmortem interval by means of ¹H MRS of decomposing brain tissue: influence of ambient temperature. NMR Biomed. 2011; 24(7):791-8. DOI: 10.1002/nbm.1623. View

13.

Griffiths W, Wang Y . Mass spectrometry: from proteomics to metabolomics and lipidomics. Chem Soc Rev. 2009; 38(7):1882-96. DOI: 10.1039/b618553n. View

14.

Aydin B, Aydn B, Colak B, Balci Y, Balc Y, Demirustu C . Consistency of postmortem interval estimations of physicians using only postmortem changes of putrefied dead bodies. Am J Forensic Med Pathol. 2010; 31(3):243-6. DOI: 10.1097/PAF.0b013e3181ee01d9. View

15.

Deng W, Wang Y, Liu Z, Cheng H, Xue Y . HemI: a toolkit for illustrating heatmaps. PLoS One. 2014; 9(11):e111988. PMC: 4221433. DOI: 10.1371/journal.pone.0111988. View

16.

Ivanisevic J, Zhu Z, Plate L, Tautenhahn R, Chen S, OBrien P . Toward 'omic scale metabolite profiling: a dual separation-mass spectrometry approach for coverage of lipid and central carbon metabolism. Anal Chem. 2013; 85(14):6876-84. PMC: 3761963. DOI: 10.1021/ac401140h. View

17.

Tomita Y, Nihira M, Ohno Y, Sato S . Ultrastructural changes during in situ early postmortem autolysis in kidney, pancreas, liver, heart and skeletal muscle of rats. Leg Med (Tokyo). 2004; 6(1):25-31. DOI: 10.1016/j.legalmed.2003.09.001. View

18.

Madea B, Kaferstein H, Hermann N, Sticht G . Hypoxanthine in vitreous humor and cerebrospinal fluid--a marker of postmortem interval and prolonged (vital) hypoxia? Remarks also on hypoxanthine in SIDS. Forensic Sci Int. 1994; 65(1):19-31. DOI: 10.1016/0379-0738(94)90296-8. View

19.

Mohamed R, Varesio E, Ivosev G, Burton L, Bonner R, Hopfgartner G . Comprehensive analytical strategy for biomarker identification based on liquid chromatography coupled to mass spectrometry and new candidate confirmation tools. Anal Chem. 2009; 81(18):7677-94. DOI: 10.1021/ac901087t. View

20.

van Dam N, Bouwmeester H . Metabolomics in the Rhizosphere: Tapping into Belowground Chemical Communication. Trends Plant Sci. 2016; 21(3):256-265. DOI: 10.1016/j.tplants.2016.01.008. View