The Application of Eukaryotic Community Succession for Postmortem Interval Estimation
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB31601 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR3201780_1.fastq.gz | Fastqsanger.gz | |||
| ERR3201780_2.fastq.gz | Fastqsanger.gz | |||
| ERR3201790_1.fastq.gz | Fastqsanger.gz | |||
| ERR3201790_2.fastq.gz | Fastqsanger.gz | |||
| ERR3201800_1.fastq.gz | Fastqsanger.gz |
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Project description:We examined the genetic profile of postmortem brain (hippocampal) samples; 15 brains from patients diagnosed with MDD were matched to brains from healthy subjects based on gender, race and age. Gene expression profiles in the dentate gyrus and CA1 subregions of the hippocampus were assessed by cDNA hybridization to 48K human HEEBO whole genome microarrays (Microarray, Inc). Two-group comparison: MDD (13 male, 8 female) vs. Control (11 male, 7 female). Dentate Gyrus (DG): 15 pairs of samples (1 array per pair); CA1: 15 pairs of samples (1 array per pair). Biological replicates. We can not provide a list of normalized values for each individual hybridization (per chip), but rather have a list of average expression values for all hybridizations used in the experiment (n=15). See supplementary files below. CODES: AAm, African American; C, Caucasian; CO, carbon monoxide; CVD, cardiovascular disease; ETOH, ethanol; F, female; Hx, history of alcohol abuse but not currently active; M, male; MDD, Major Depressive disorder, ND, no psychotropic medication detected; NOS, not otherwise specified, OD, drug overdose; PE, prior episode of major depression with psychotic features; PMI, postmortem interval (hours); SIGSW, self-inflicted gunshot wound; [1], Psychotrophic prescriptions within last month; [2], MDD in remission; [3], prescriptions for six days prior to death; *, samples present only in array sets for the dentate gyrus; **, samples present only in array sets for CA1.
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Project description:The establishment of postmortem interval is one of the most important aspects of forensic expertise. Microbes may provide a novel way to estimate the postmortem intervals in order to avoid many of these limitations. The oral cavity harbors one of the most diverse microbiomes that play a key role in the decomposition of corpses. In this study, the oral bacterial community showed obvious changes in relative abundance during the process of mice decomposition. Meanwhile, at different taxonomic levels, specific bacteria were found to be significantly correlated with the postmortem interval. Linear regression models between relative abundance and the postmortem interval were constructed. Among these species, Gamma-proteobacteria and Proteus were the best ones that can be used to infer the postmortem interval, especially late postmortem interval. Therefore, we suggest that succession of oral microbial community can be developed as a forensic tool for estimating the postmortem interval.
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Project description:The combined use of multiple omics methods to answer complex system biology questions is growing in biological and medical sciences, as the importance of studying interrelated biological processes in their entirety is increasingly recognized. We applied a combination of metabolomics, lipidomics and proteomics to human bone to investigate the potential of this multi-omics approach to estimate the time elapsed since death (i.e., the post-mortem interval, PMI). This “ForensOMICS” approach has the potential to improve accuracy and precision of PMI estimation of skeletonized human remains, thereby helping forensic investigators to establish the timeline of events surrounding death. Anterior midshaft tibial bone was collected from four female body donors in a fresh stage of decomposition before placement of the bodies to decompose outdoors at the human taphonomy facility managed by the Forensic Anthropological Center at Texas State (FACTS). Bone samples were again collected at selected PMIs (219, 790, 834 and 872 days). Liquid chromatography mass spectrometry (LC-MS) was used to obtain untargeted metabolomic, lipidomic and proteomic profiles from the pre- and post-placement bone samples. Multivariate analysis was used to investigate the three omics blocks by means of Data Integration Analysis for Biomarker discovery using Latent variable approaches for Omics studies (DIABLO), to identify the reduced number of markers that could effectively describe post-mortem changes and classify the individuals based on their PMI. The resulting model showed that pre-placement bone metabolome, lipidome and proteome profiles were clearly distinguishable from post-placement profiles. Metabolites associated with the pre-placement samples, suggested an extinction of the energetic metabolism and a switch towards another source of fuelling (e.g., structural proteins). We were able to identify certain biomolecules from the three groups that show excellent potential for estimation of the PMI, predominantly the biomolecules from the metabolomics block. Our findings suggest that, by targeting a combination of compounds with different post-mortem stability, in future studies we could be able to estimate both short PMIs, by using metabolites and lipids, and longer PMIs, by including more stable proteins.
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Project description:<p><strong>INTRODUCTION:</strong> Application of metabolomic methods to forensic studies may expand the limits of the post-mortem interval (PMI) estimation, and improve the accuracy of the estimation. To this end, it is important to determine which tissue is the most suitable for analysis, and which compounds are the most promising candidates for PMI estimation.</p><p><strong>OBJECTIVES:</strong> This work is aimed at the comparison of human serum, aqueous humor (AH), and vitreous humor (VH) as per- spective tissues for metabolomic-based PMI estimation, at the determination of most promising PMI biomarkers, and at the development of method of PMI estimation based on the measurement of concentrations of PMI biomarkers.</p><p><strong>METHODS:</strong> Quantitative metabolomic pro ling of samples of the human serum, AH, and VH taken at di erent PMIs has been performed with the use of NMR spectroscopy.</p><p><strong>RESULTS:</strong> It is found that the metabolomic changes in anatomically isolated ocular uids are slower and smoother than that in blood. A good positive time correlation (Pearson coe cient r > 0.5) was observed for several metabolites, including hypox- anthine, choline, creatine, betaine, glutamate, and glycine. A model for PMI estimation based on concentrations of several metabolites in AH and VH is proposed.</p><p><strong>CONCLUSIONS:</strong> The obtained results demonstrate that the metabolomic analysis of AH and VH is more suitable for the PMI estimation than that of serum. The compounds with good positive time correlation can be considered as potential PMI biomarkers.</p><p><br></p>
2021-02-02 | MTBLS1518 | MetaboLights