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

Postmortem tissues are frequently used in forensic investigation, clinical studies, and biomedical research. It is well known that the shorter period from death to analyses provides the more accurate results. However, the longest postmortem interval that still provides the reliable data remains unclear. We performed serial analyses of postmortem changes in proteome profile, histology, electrolyte contents, water composition, and enzyme activity in human vastus lateralis muscle from a male cadaver (died from a motorcycle accident). This uninjured muscle was sectioned into several 1‐cm3 cubes and stored in individual closed tubes at 4 or 25°C for 0, 2, 4, 6, 12, 24 or 48 h prior to proteomic, histological, chemical and biochemical analyses. At 4°C, the 2‐DE proteome profile remained unchanged until 24 h, when some poorly focused protein spots and significant decrease in the total number of visualized spots were observed. These changes were detectable earlier (12 h) in the samples stored at 25°C. Profound vacuolization and autolysis started at 24 and 6 h for the samples stored at 4ºC and 25°C, respectively. K and Mg contents began to increase at 12 and 48 h, respectively, for both temperatures. However, the increase in Na and Ca contents began at 24 h in the samples stored at 4°C, but started earlier (12 h) in those stored at 25°C. Water content started to decline at 48 and 24 h in the samples stored at 4 and 25°C, respectively. Muscle lactate dehydrogenase activity began to be out of range at 12 h for both temperatures. These findings demonstrate that storing the samples at 4°C could delay some of the aforementioned changes, which occurred more rapidly at 25°C. Our results also suggest that muscle proteome profile, histology, electrolyte contents, water composition, and enzyme activity should be analyzed within the optimal postmortem intervals, which vary among individual analyses, to obtain the most reliable data.