A large-scale survey of the postmortem human microbiome, and its potential to provide insight into the living health condition

Abstract

The microbiome plays many roles in human health, often through the exclusive lens of clinical interest. The inevitable end point for all living hosts, death, has its own altered microbiome configurations. However, little is understood about the ecology and changes of microbial communities after death, or their potential utility for understanding the health condition of the recently living. Here we reveal distinct postmortem microbiomes of human hosts from a large-scale survey of death cases representing a predominantly urban population, and demonstrated these microbiomes reflected antemortem health conditions within 24-48 hours of death. Our results characterized microbial community structure and predicted function from 188 cases representing a cross-section of an industrial-urban population. We found strong niche differentiation of anatomic habitat and microbial community turnover based on topographical distribution. Microbial community stability was documented up to two days after death. Additionally, we observed a positive relationship between cell motility and time since host death. Interestingly, we discovered evidence that microbial biodiversity is a predictor of antemortem host health condition (e.g., heart disease). These findings improve the understanding of postmortem host microbiota dynamics, and provide a robust dataset to test the postmortem microbiome as a tool for assessing health conditions in living populations.

Figure 1

Host filtering of the postmortem microbiome. (A) The principal coordinate analysis (PCoA) indicates differences among anatomic location microbiota. PERMANOVA detected significant differences (P < 0.05) among anatomic locations, and all pairwise differences were statistically significant with p-value adjusted for FDR (P < 0.001). (B) Faith’s phylogenetic distance (PD) (mean ± standard error mean) was statistically reduced (Mann-U t-test, P < 0.05) for each anatomic location, except the rectum, after 48 h postmortem. (C) The relationship between the mean relative abundance and variance (SD) for taxa that were >0.25% relative abundance demonstrated decreased variability in the microbiota in the first two days after death.

Figure 2

Microbial community profiles from death investigation. (A) The proportion of shared OTUs demonstrated substantial taxon overlap among anatomic areas throughout decomposition (>53%), and decreased unique taxa 48 h after host death. (B) The relative abundance of predominant taxa changed within two days after death. (C) These changes were also detected in the log₂-transformed fold changes of indicator KO pathways based on in silico functional pathways. (D) Bacterial motility and flagellar assembly had the greatest increase in relative abundance (mean ± standard error mean) over time by 54–84% and 59–87%, respectively, and were statistically different (Mann-U t-test, P < 0.05) between estimated postmortem intervals.

Figure 3

Potential utility of the postmortem microbiome for detecting antemortem health. (A) A binomial logistic regression model determined the relationship between Faith’s phylogenetic distance and evidence of heart disease; the odds of a case with a heart condition was 28.8% less likely to occur for each unit increase in phylogenetic diversity. (B) The log₂-transformed fold changes (median) of potential biomarkers for heart disease determined Rothia had the only detectable increase in abundance. (C) Additionally, the odds of a case resulting from a violent death was 65.2% more likely to occur for each unit increase in Faith’s phylogenetic diversity using a binomial logistic regression model. (D) The abundance of Rothia was the only taxon detected to increase in non-violent deaths based on log₂-transformed fold changes (median).