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Updated: Jun 25, 2025

Removal of Exogenous Materials from the Outer Portion of Frozen Cores to Investigate the Ancient Biological Communities Harbored Inside

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Decomposition in an extreme cold environment and associated microbiome-prediction model implications for the

Lavinia Iancu¹, Andrea Bonicelli², Noemi Procopio²

¹Department of Criminal Justice, University of North Dakota, Grand Forks, ND, United States.

Frontiers in Microbiology

|May 28, 2024

Summary

Forensic scientists can now estimate postmortem interval (PMI) in extreme cold using a novel microbial model. This breakthrough offers accurate time-since-death estimations even when decomposition is halted by freezing temperatures.

Keywords:

North Dakota extreme environment microbiome postmortem interval prediction model

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Last Updated: Jun 25, 2025

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Area of Science:

Forensic Science
Microbiology
Environmental Science

Background:

Accurate postmortem interval (PMI) estimation is critical in forensic investigations.
Estimating PMI in extreme cold presents significant challenges due to slowed decomposition and potential for error.
Existing methods are often unreliable in prolonged cold conditions.

Purpose of the Study:

To address the lack of data on decomposition in extreme cold environments.
To develop and validate the first postmortem microbiome prediction model for PMI estimation in cold climates.
To provide a reliable method for PMI determination when visual decomposition is arrested.

Main Methods:

Conducted a 23-week experiment on animal models in Grand Forks, North Dakota (extreme cold, down to -39°C).
Collected 393 samples, utilizing 16S rRNA gene microbial data from nasal swabs.
Developed Random Forest analysis models incorporating microbial data and environmental parameters (snow depth, temperature).

Main Results:

The best model, using both internal and external swabs, achieved a Mean Absolute Error (MAE) of 1.36 weeks and R2 of 0.91.
A model relying solely on external swabs had a higher MAE of 2.89 weeks and R2 of 0.73.
Key microbial predictors identified across models included genera: *Psychrobacter*, *Carnobacterium*, and *Pseudomonas*.

Conclusions:

The study presents the first microbial model for predicting PMI in extreme winter conditions over six months.
The model demonstrates an accuracy of 9.52 days for postmortem interval estimation.
This research offers a novel forensic tool for cold environments, overcoming limitations of traditional methods.