The assessment of postmortem degradation of skeletal muscle proteins has emerged as a novel approach to estimate the time since death in the early to mid-postmortem phase (approximately 24 h postmortem (hpm) to 120 hpm). Current protein-based methods are limited to a small number of skeletal muscle proteins, shown to undergo proteolysis after death. In this study, we investigated the usability of a target-based and unbiased system-wide protein analysis to gain further insights into systemic postmortem protein alterations and to identify additional markers for postmortem interval (PMI) delimitation. We performed proteomic profiling to globally analyze postmortem alterations of the rat and mouse skeletal muscle proteome at defined time points (0, 24, 48, 72, and 96 hpm), harnessing a mass spectrometry-based quantitative proteomics approach. Hierarchical clustering analysis for a total of 579 (rat) and 896 (mouse) quantified proteins revealed differentially expressed proteins during the investigated postmortem period. We further focused on two selected proteins (eEF1A2 and GAPDH), which were shown to consistently degrade postmortem in both rat and mouse, suggesting conserved intra- and interspecies degradation behavior, and thus preserved association with the PMI and possible transferability to humans. In turn, we validated the usefulness of these new markers by classical Western blot experiments in a rat model and in human autopsy cases. Our results demonstrate the feasibility of mass spectrometry–based analysis to discover novel protein markers for PMI estimation and show that the proteins eEF1A2 and GAPDH appear to be valuable markers for PMI estimation in humans.
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Madea B (2016) Methods for determining time of death. Forensic Sci Med Pathol 12:451–485. https://doi.org/10.1007/s12024-016-9776-y
Henssge C, Madea B (2004) Estimation of the time since death in the early post-mortem period. Forensic Sci Int 144:167–175. https://doi.org/10.1016/j.forsciint.2004.04.051
Amendt J, Campobasso CP, Gaudry E, Reiter C, LeBlanc HN, J. R. Hall M (2007) Best practice in forensic entomology--standards and guidelines. Int J Legal Med 121:90–104. https://doi.org/10.1007/s00414-006-0086-x
Megyesi MS, Nawrocki SP, Haskell NH (2005) Using accumulated degree-days to estimate the postmortem interval from decomposed human remains. J Forensic Sci 50:618–626
Sampaio-Silva F, Magalhães T, Carvalho F, Dinis-Oliveira RJ, Silvestre R (2013) Profiling of RNA degradation for estimation of post morterm interval. PLoS One 8:e56507. https://doi.org/10.1371/journal.pone.0056507
Bauer M, Gramlich I, Polzin S, Patzelt D (2003) Quantification of mRNA degradation as possible indicator of postmortem interval—a pilot study. Legal Med 5:220–227. https://doi.org/10.1016/j.legalmed.2003.08.001
Rhein M, Hagemeier L, Klintschar M, Muschler M, Bleich S, Frieling H (2015) DNA methylation results depend on DNA integrity-role of post mortem interval. Front Genet 6:182. https://doi.org/10.3389/fgene.2015.00182
Perry WL, Bass WM, Riggsby WS, Sirotkin K (1988) The autodegradation of deoxyribonucleic acid (DNA) in human rib bone and its relationship to the time interval since death. J Forensic Sci 33:144–153
Wehner F, Wehner H-D, Schieffer MC, Subke J (1999) Delimitation of the time of death by immunohistochemical detection of insulin in pancreatic β-cells. Forensic Sci Int 105:161–169. https://doi.org/10.1016/S0379-0738(99)00124-3
Wehner F, Wehner H-D, Schieffer MC, Subke J (2000) Delimitation of the time of death by immunohistochemical detection of thyroglobulin. Forensic Sci Int 110:199–206. https://doi.org/10.1016/S0379-0738(00)00177-8
Kumar S, Ali W, Singh US, Kumar A, Bhattacharya S, Verma AK, Rupani R (2016) Temperature-dependent postmortem changes in human cardiac troponin-T (cTnT): an approach in estimation of time since death. J Forensic Sci 61:S241–S245. https://doi.org/10.1111/1556-4029.12928
Kumar S, Ali W, Singh US, Kumar A, Bhattacharya S, Verma AK (2015) The effect of elapsed time on the cardiac troponin-T (cTnT) proteolysis in case of death due to burn: a study to evaluate the potential forensic use of cTnT to determine the postmortem interval. Sci Justice 55:189–194. https://doi.org/10.1016/j.scijus.2014.12.006
Poloz YO, O’Day DH (2009) Determining time of death: temperature-dependent postmortem changes in calcineurin a, MARCKS, CaMKII, and protein phosphatase 2A in mouse. Int J Legal Med 123:305–314. https://doi.org/10.1007/s00414-009-0343-x
Geesink GH, Koohmaraie M (1999) Postmortem proteolysis and calpain/calpastatin activity in callipyge and normal lamb biceps femoris during extended postmortem storage. J Anim Sci 77:1490–1501
Pittner S, Monticelli FC, Pfisterer A, Zissler A, Sänger AM, Stoiber W, Steinbacher P (2016) Postmortem degradation of skeletal muscle proteins: a novel approach to determine the time since death. Int J Legal Med 130:421–431. https://doi.org/10.1007/s00414-015-1210-6
Zissler A, Ehrenfellner B, Foditsch EE, Monticelli FC, Pittner S (2018) Does altered protein metabolism interfere with postmortem degradation analysis for PMI estimation? Int J Legal Med 132:1349–1356. https://doi.org/10.1007/s00414-018-1814-8
Lee D-G, Yang KE, Hwang JW, Kang HS, Lee SY, Choi S, Shin J, Jang IS, An HJ, Chung H, Jung HI, Choi JS (2016) Degradation of kidney and psoas muscle proteins as indicators of post-mortem interval in a rat model, with use of lateral flow technology. PLoS One 11:e0160557. https://doi.org/10.1371/journal.pone.0160557
Pittner S, Ehrenfellner B, Zissler A, Racher V, Trutschnig W, Bathke AC, Sänger AM, Stoiber W, Steinbacher P, Monticelli FC (2017) First application of a protein-based approach for time since death estimation. Int J Legal Med 131:479–483. https://doi.org/10.1007/s00414-016-1459-4
Xie F, Liu T, Qian W-J, Petyuk VA, Smith RD (2011) Liquid chromatography-mass spectrometry-based quantitative proteomics. J Biol Chem 286:25443–25449. https://doi.org/10.1074/jbc.R110.199703
Hawkridge AM, Muddiman DC (2009) Mass spectrometry-based biomarker discovery: toward a global proteome index of individuality. Annu Rev Anal Chem Palo Alto Calif 2:265–277. https://doi.org/10.1146/annurev.anchem.1.031207.112942
Zhou W, Petricoin EF, Longo C (2017) Mass spectrometry-based biomarker discovery. Methods Mol Biol Clifton NJ 1606:297–311. https://doi.org/10.1007/978-1-4939-6990-6_19
Tavichakorntrakool R, Prasongwattana V, Sriboonlue P, Puapairoj A, Pongskul J, Khuntikeo N, Hanpanich W, Yenchitsomanus PT, Wongkham C, Thongboonkerd V (2008) Serial analyses of postmortem changes in human skeletal muscle: a case study of alterations in proteome profile, histology, electrolyte contents, water composition, and enzyme activity. Proteomics Clin Appl 2:1255–1264. https://doi.org/10.1002/prca.200800051
Procopio N, Williams A, Chamberlain AT, Buckley M (2018) Forensic proteomics for the evaluation of the post-mortem decay in bones. J Proteome 177:21–30. https://doi.org/10.1016/j.jprot.2018.01.016
Cox J, Mann M (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26:1367–1372. https://doi.org/10.1038/nbt.1511
Kim J-Y, Welsh EA, Fang B, Bai Y, Kinose F, Eschrich SA, Koomen JM, Haura EB (2016) Phosphoproteomics reveals MAPK inhibitors enhance MET- and EGFR-driven AKT signaling in KRAS-mutant lung cancer. Mol Cancer Res MCR 14:1019–1029. https://doi.org/10.1158/1541-7786.MCR-15-0506
Chawade A, Alexandersson E, Levander F (2014) Normalyzer: a tool for rapid evaluation of normalization methods for omics data sets. J Proteome Res 13:3114–3120. https://doi.org/10.1021/pr401264n
Pittner S, Ehrenfellner B, Monticelli FC, Zissler A, Sänger AM, Stoiber W, Steinbacher P (2016) Postmortem muscle protein degradation in humans as a tool for PMI delimitation. Int J Legal Med 130:1547–1555. https://doi.org/10.1007/s00414-016-1349-9
Ferguson RE, Carroll HP, Harris A, Maher ER, Selby PJ, Banks RE (2005) Housekeeping proteins: a preliminary study illustrating some limitations as useful references in protein expression studies. PROTEOMICS 5:566–571. https://doi.org/10.1002/pmic.200400941
Kim HJ, Na JI, Min BW, Na JY, Lee KH, Lee JH, Lee YJ, Kim HS, Park JT (2014) Evaluation of protein expression in housekeeping genes across multiple tissues in rats. Korean J Pathol 48:193–200. https://doi.org/10.4132/KoreanJPathol.2014.48.3.193
Blair JA, Wang C, Hernandez D, Siedlak SL, Rodgers MS, Achar RK, Fahmy LM, Torres SL, Petersen RB, Zhu X, Casadesus G, Lee HG (2016) Individual case analysis of postmortem interval time on brain tissue preservation. PLoS One 11. https://doi.org/10.1371/journal.pone.0151615
Abbas W, Kumar A, Herbein G (2015) The eEF1A proteins: at the crossroads of oncogenesis, apoptosis, and viral infections. Front Oncol 5:75. https://doi.org/10.3389/fonc.2015.00075
Li D, Wei T, Abbott CM, Harrich D (2013) The unexpected roles of eukaryotic translation elongation factors in RNA virus replication and pathogenesis. Microbiol Mol Biol Rev MMBR 77:253–266. https://doi.org/10.1128/MMBR.00059-12
Tomlinson VA, Newbery HJ, Wray NR et al (2005) Translation elongation factor eEF1A2 is a potential oncoprotein that is overexpressed in two-thirds of breast tumours. BMC Cancer 5:113. https://doi.org/10.1186/1471-2407-5-113
Baron CP, Jacobsen S, Purslow PP (2004) Cleavage of desmin by cysteine proteases: calpains and cathepsin B. Meat Sci 68:447–456. https://doi.org/10.1016/j.meatsci.2004.03.019
Ehrenfellner B, Zissler A, Steinbacher P, Monticelli FC, Pittner S (2017) Are animal models predictive for human postmortem muscle protein degradation? Int J Legal Med 131:1615–1621. https://doi.org/10.1007/s00414-017-1643-1
Open access funding provided by Austrian Science Fund (FWF). This work is supported by research fund of the Chungnam National University, National Research Foundation of Korea (2017R2014R1A6A9064166, 2016M3A9E1918321), the Korea Basic Science Institute under the R&D program (Project No. T38641) supervised by the Ministry of Science of Korea, and the Austrian Science Fund (FWF), grant P31490.
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Choi, K., Zissler, A., Kim, E. et al. Postmortem proteomics to discover biomarkers for forensic PMI estimation. Int J Legal Med 133, 899–908 (2019). https://doi.org/10.1007/s00414-019-02011-6
- Postmortem interval (PMI)
- Skeletal muscle