Thanatometabolomics: introducing NMR-based metabolomics to identify metabolic biomarkers of the time of death

Abstract

Introduction Death is the permanent cessation of the critical functions of the organism as a whole. However, the shutdown of a complex biological organism does not abruptly terminate at time of death. New high-throughput technologies allow the systematic investigation of the biochemical modulations occurring after death. Recent genomics studies have demonstrated that genes remain active after death, triggering upregulation of some genes and initiating feedback loops. These genes were mostly involved in pathways related to immunity, inflammation and cancer. These genetic modulations suggest many biochemical events persist after death, which can be captured using a metabolomics approach. Objectives This proof of concept work aimed to determine whether NMR spectroscopy could identify metabolomics changes occurring after death, and characterise the nature of these metabolomics modulations. Methods High-resolution 1 H-NMR spectroscopy was applied to six biological matrices: heart, kidney, liver, spleen, skin and white adipose tissue of ten adult mice at three different type points. Results Forty-three metabolites were associated with post mortem metabolomics modulations. Kidney, heart and spleen showed the highest metabolic perturbations. Conversely, skin and white adipose tissue were the least altered matrices. Early metabolic modulations were associated with energy metabolism and DNA synthesis, by contrast, late metabolomics modulations were associated with microbial metabolism. Conclusions NMR has proven potential to determine the time of death based on post-mortem metabolomics modulations. This could be useful in the context of transplants, forensic studies and as internal quality control in metabolomics studies. Further investigations are required to validate these findings in humans in order to determine which compounds robustly reflect post-mortem metabolic fluctuations to accurately determine the time of death. Electronic supplementary material The online version of this article (10.1007/s11306-019-1498-1) contains supplementary material, which is available to authorized users.

NMR metabolomics identifies over 60 biomarkers associated with Type II Diabetes impairment in db/db mice

“…Aliphatic and aromatic regions from urine datasets, where glucose signal is not present, were further studied applying a normalisation under total area (Dieterle et al 2006 ) and interrogated by O-PLS DA model as described above. Metabolite identification was done using Chenomx NMR Suite 8.2 from Chenomx Inc (Edmonton, Canada), online publicly available databases: the Human Metabolome Data Base (HMDB, http://www.hmdb.ca ), the Biological Magnetic Resonance data bank (BMRB, http://www.bmrb.wisc.edu ) and published literature (Claus et al 2011 , 2008 , Mora-Ortiz et al 2019 ). A heatmap was calculated in R using the metabolites relative modulations (i.e.…”

“…Systematic metabolomics characterisation of various research models such as rodents, chickens, pigs, humans and horses have been published in the past (Claus et al 2008 ; Le Roy et al 2016 ; Martin et al 2007 ; Merrifield et al 2011 ; Ndagijimana et al 2009 ; Holmes et al 1997 ; Escalona et al 2015 ; Mora-Ortiz et al 2019 ), but to date, a comprehensive metabolic phenotyping of the leptin receptor defective ( db/db ) T2D mouse model: BKS.Cg-Dock7 < m > +/+ Lepr < db >/J is missing. Previous reports have characterised relevant biological matrices such as urine, plasma and kidneys, showing an increase in glucose levels and modulations in the tricarboxylic acid cycle (TCA cycle), branched-chain amino acids (BCAAs) levels, homocysteine-methionine metabolism and ketone and fatty acid metabolism at different stages of the disease.…”

Forensic NMR metabolomics: one more arrow in the quiver

“…1 H NMR metabolomics was applied to investigate mice organ (heart, kidney, liver, spleen, skin, and white adipose tissue) samples collected from ten animals at three different PMI (Mora-Ortiz et al 2019 ). Metabolomic alterations were recorded and pairwise Orthogonal Projection to Latent Structure Discriminant Analysis (OPLS-DA) was used to compare two time points for each organ.…”

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An overview on NMR spectroscopy based metabolomics

“…The H-NMR can be utilized to put the complete structure of the metabolite together using the components of the spectra like signals, chemical shift, and integration and splitting patterns. The C-NMR spectroscopy abolishes some structures that can be possible if we use H-NMR spectrumFigure 4[14].…”