Department of Entomology, 2475 TAMU, Texas A&M University, College Station, TX, 77843, USA,
Int J Legal Med. 2014 Jan;128(1):193-205. doi: 10.1007/s00414-013-0872-1. Epub 2013 Jun 10.
Decomposition studies of vertebrate remains primarily focus on data that can be seen with the naked eye, such as arthropod or vertebrate scavenger activity, with little regard for what might be occurring with the microorganism community. Here, we discuss the necrobiome, or community of organisms associated with the decomposition of remains, specifically, the "epinecrotic" bacterial community succession throughout decomposition of vertebrate carrion. Pyrosequencing was used to (1) detect and identify bacterial community abundance patterns that described discrete time points of the decomposition process and (2) identify bacterial taxa important for estimating physiological time, a time-temperature metric that is often commensurate with minimum post-mortem interval estimates, via thermal summation models. There were significant bacterial community structure differences in taxon richness and relative abundance patterns through the decomposition process at both phylum and family taxonomic classification levels. We found a significant negative linear relationship for overall phylum and family taxon richness as decomposition progressed. Additionally, we developed a statistical model using high throughput sequencing data of epinecrotic bacterial communities on vertebrate remains that explained 94.4 % of the time since placement of remains in the field, which was within 2-3 h of death. These bacteria taxa are potentially useful for estimating the minimum post-mortem interval. Lastly, we provide a new framework and standard operating procedure of how this novel approach of using high throughput metagenomic sequencing has remarkable potential as a new forensic tool. Documenting and identifying differences in bacterial communities is key to advancing knowledge of the carrion necrobiome and its applicability in forensic science.
脊椎动物遗骸的分解研究主要集中在可以用肉眼观察到的数据上，例如节肢动物或脊椎动物食腐动物的活动，而很少关注微生物群落可能发生的情况。在这里，我们讨论了尸体生物群，或者与遗骸分解相关的生物体群落，特别是在脊椎动物腐肉分解过程中“上皮坏死”细菌群落演替。我们使用焦磷酸测序来 (1) 检测和识别描述分解过程中离散时间点的细菌群落丰度模式，以及 (2) 通过热总和模型识别对于估计生理时间（通常与最低死后间隔估计相符的时间-温度指标）很重要的细菌分类群。在门和科分类水平上，通过分解过程中的细菌群落结构在分类丰富度和相对丰度模式上存在显著差异。我们发现，随着分解的进行，总体门和科分类群丰富度呈显著负线性关系。此外，我们还使用脊椎动物遗骸上皮坏死细菌群落的高通量测序数据开发了一个统计模型，该模型解释了遗骸在野外放置后的时间的 94.4%，这与死亡后 2-3 小时内的时间相符。这些细菌分类群可能有助于估计最低死后间隔。最后，我们提供了一个新的框架和标准操作程序，说明使用高通量宏基因组测序的这种新方法具有作为一种新的法医工具的巨大潜力。记录和识别细菌群落的差异是推进腐肉尸体生物群及其在法医学中应用的知识的关键。
