Measuring the microbes that feed on the dead can determine the time of death when maggots and flies fail, Viviane Richter discovers.
(Cosmos) – The number of blowflies feasting on a corpse can be the crucial detail that leads to a murderer’s conviction. But the insect method of working out the time of death, made famous by Patricia Cornwell’s crime fiction novel The Body Farm, is not always reliable.
So Jack Gilbert and colleagues at the University of California in San Diego have developed a new technique for when the blowfly method fails. They have used high-speed gene-sequencing to monitor microbes on decomposing corpses to determine the time of death. They reported their method in Science in December.
When forensic entomologists use blowflies to determine time of death they need to consider the habits of local blowfly species, and weather conditions — flies tend to breed more rapidly when it is warm and moist. The best scientists can hope for is a probable time of death, within a day or two. And sometimes the insect method doesn’t work – for instance if the body is buried deep underground.
“We’re always looking for more accurate methods,” says Shari Forbes, forensic scientist at the University of Technology Sydney.
Gilbert and his team turned to the bacteria and fungi that break down animals after death. These live in the environment in small numbers, but rapidly multiply when they are feasting on a corpse. What’s more, their populations change in a highly predictable fashion as a body decomposes.
Until recently, capturing a snapshot of that macabre and transient ecosystem required culture dishes and microscopes, as well as time for the microbes to grow. But with today’s chip-based RNA-sequencing, a visual readout of the abundance of various types of microorganisms can be had in minutes.
To test this approach, Gilbert’s team travelled to the Southeast Texas Applied Forensic Science Facility – an outdoor human decomposition lab, or “body farm”. There, the team swabbed four human cadavers every few days for more than 80 days, using RNA sequencing to track what microbes species were on the bodies and their numbers.
Microbial decomposer communities are similar across environments.

(A) Results of principal coordinates analysis (PCoA) based on unweighted UniFrac distances for mouse skin bacterial and archaeal communities. Samples are colored by days of decomposition (left) and soil type (right). (B) Log scale heat map of 16S rRNA operational taxonomic units (OTUs) colonizing the skin of human corpses. (C) A 16S rRNA–based Random Forests (RF) model using our winter-season skin-and-soil data set to train the model and predict the PMI of human bodies in the spring. Each point indicates a sample collected at a certain PMI, with RF-predicted PMIs shown in red and randomly guessed PMIs in gray. RMSE, root mean square error. (D) Percentage of top 100 PMI regression features from each environment that were shared (colored lines) versus number of shared features from randomly selected subsets of size 100 (gray lines). ITS, internal transcribed spacer.
The approach proved as accurate as blowfly counts in determining the time of death. The team’s studies on dead mice showed that microbial populations change in a consistent way across a range of conditions — in desert, grassland or forest.
Forbes, whose team is setting up a body farm close to Sydney, the first outside the US, says more bodies need to be tested to ensure the method is robust. But the approach has great potential. The microbes alone could be used where the insect method fails – or perhaps, by combining the two approaches, forensic scientists could narrow the time of death even further.
Source – Cosmos by Viviane Richter
[box type=”shadow” align=”alignleft” ]Metcalf JL et al. (2016)
Microbial community assembly and metabolic function during mammalian corpse decomposition.
Science 351(6269):158-62. [
article][/fusion_text][/fusion_builder_column_inner][/fusion_builder_row_inner][/fusion_builder_column]
Measuring the microbes that feed on the dead can determine the time of death when maggots and flies fail, Viviane Richter discovers.
(Cosmos) – The number of blowflies feasting on a corpse can be the crucial detail that leads to a murderer’s conviction. But the insect method of working out the time of death, made famous by Patricia Cornwell’s crime fiction novel The Body Farm, is not always reliable.
So Jack Gilbert and colleagues at the University of California in San Diego have developed a new technique for when the blowfly method fails. They have used high-speed gene-sequencing to monitor microbes on decomposing corpses to determine the time of death. They reported their method in Science in December.
When forensic entomologists use blowflies to determine time of death they need to consider the habits of local blowfly species, and weather conditions — flies tend to breed more rapidly when it is warm and moist. The best scientists can hope for is a probable time of death, within a day or two. And sometimes the insect method doesn’t work – for instance if the body is buried deep underground.
Gilbert and his team turned to the bacteria and fungi that break down animals after death. These live in the environment in small numbers, but rapidly multiply when they are feasting on a corpse. What’s more, their populations change in a highly predictable fashion as a body decomposes.
Until recently, capturing a snapshot of that macabre and transient ecosystem required culture dishes and microscopes, as well as time for the microbes to grow. But with today’s chip-based RNA-sequencing, a visual readout of the abundance of various types of microorganisms can be had in minutes.
To test this approach, Gilbert’s team travelled to the Southeast Texas Applied Forensic Science Facility – an outdoor human decomposition lab, or “body farm”. There, the team swabbed four human cadavers every few days for more than 80 days, using RNA sequencing to track what microbes species were on the bodies and their numbers.
Microbial decomposer communities are similar across environments.
(A) Results of principal coordinates analysis (PCoA) based on unweighted UniFrac distances for mouse skin bacterial and archaeal communities. Samples are colored by days of decomposition (left) and soil type (right). (B) Log scale heat map of 16S rRNA operational taxonomic units (OTUs) colonizing the skin of human corpses. (C) A 16S rRNA–based Random Forests (RF) model using our winter-season skin-and-soil data set to train the model and predict the PMI of human bodies in the spring. Each point indicates a sample collected at a certain PMI, with RF-predicted PMIs shown in red and randomly guessed PMIs in gray. RMSE, root mean square error. (D) Percentage of top 100 PMI regression features from each environment that were shared (colored lines) versus number of shared features from randomly selected subsets of size 100 (gray lines). ITS, internal transcribed spacer.
The approach proved as accurate as blowfly counts in determining the time of death. The team’s studies on dead mice showed that microbial populations change in a consistent way across a range of conditions — in desert, grassland or forest.
Forbes, whose team is setting up a body farm close to Sydney, the first outside the US, says more bodies need to be tested to ensure the method is robust. But the approach has great potential. The microbes alone could be used where the insect method fails – or perhaps, by combining the two approaches, forensic scientists could narrow the time of death even further.
Source – Cosmos by Viviane Richter
[box type=”shadow” align=”alignleft” ]Metcalf JL et al. (2016) Microbial community assembly and metabolic function during mammalian corpse decomposition. Science 351(6269):158-62. [article][/fusion_text][/fusion_builder_column_inner][/fusion_builder_row_inner][/fusion_builder_column]Related Posts
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Measuring the microbes that feed on the dead can determine the time of death when maggots and flies fail, Viviane Richter discovers.
(Cosmos) – The number of blowflies feasting on a corpse can be the crucial detail that leads to a murderer’s conviction. But the insect method of working out the time of death, made famous by Patricia Cornwell’s crime fiction novel The Body Farm, is not always reliable.
So Jack Gilbert and colleagues at the University of California in San Diego have developed a new technique for when the blowfly method fails. They have used high-speed gene-sequencing to monitor microbes on decomposing corpses to determine the time of death. They reported their method in Science in December.
When forensic entomologists use blowflies to determine time of death they need to consider the habits of local blowfly species, and weather conditions — flies tend to breed more rapidly when it is warm and moist. The best scientists can hope for is a probable time of death, within a day or two. And sometimes the insect method doesn’t work – for instance if the body is buried deep underground.
Gilbert and his team turned to the bacteria and fungi that break down animals after death. These live in the environment in small numbers, but rapidly multiply when they are feasting on a corpse. What’s more, their populations change in a highly predictable fashion as a body decomposes.
Until recently, capturing a snapshot of that macabre and transient ecosystem required culture dishes and microscopes, as well as time for the microbes to grow. But with today’s chip-based RNA-sequencing, a visual readout of the abundance of various types of microorganisms can be had in minutes.
To test this approach, Gilbert’s team travelled to the Southeast Texas Applied Forensic Science Facility – an outdoor human decomposition lab, or “body farm”. There, the team swabbed four human cadavers every few days for more than 80 days, using RNA sequencing to track what microbes species were on the bodies and their numbers.
Microbial decomposer communities are similar across environments.
(A) Results of principal coordinates analysis (PCoA) based on unweighted UniFrac distances for mouse skin bacterial and archaeal communities. Samples are colored by days of decomposition (left) and soil type (right). (B) Log scale heat map of 16S rRNA operational taxonomic units (OTUs) colonizing the skin of human corpses. (C) A 16S rRNA–based Random Forests (RF) model using our winter-season skin-and-soil data set to train the model and predict the PMI of human bodies in the spring. Each point indicates a sample collected at a certain PMI, with RF-predicted PMIs shown in red and randomly guessed PMIs in gray. RMSE, root mean square error. (D) Percentage of top 100 PMI regression features from each environment that were shared (colored lines) versus number of shared features from randomly selected subsets of size 100 (gray lines). ITS, internal transcribed spacer.
The approach proved as accurate as blowfly counts in determining the time of death. The team’s studies on dead mice showed that microbial populations change in a consistent way across a range of conditions — in desert, grassland or forest.
Forbes, whose team is setting up a body farm close to Sydney, the first outside the US, says more bodies need to be tested to ensure the method is robust. But the approach has great potential. The microbes alone could be used where the insect method fails – or perhaps, by combining the two approaches, forensic scientists could narrow the time of death even further.
Source – Cosmos by Viviane Richter
[box type=”shadow” align=”alignleft” ]Metcalf JL et al. (2016) Microbial community assembly and metabolic function during mammalian corpse decomposition. Science 351(6269):158-62. [article][/fusion_text][/fusion_builder_column_inner][/fusion_builder_row_inner][/fusion_builder_column]Related Posts
An anti-senescence gene may fight spinal disc deterioration
Scientists identify the neuroblastoma cells that signal poor outcomes
Urine test may improve bladder cancer diagnosis and guide treatment decisions
Tracing 700 million years of cell evolution
RNA-Seq reveals a new way the developing heart controls its growth
The Human RNome Project Consortium seeks to publish first-ever complete sequence of the body’s RNA
Unmasking “zombie cells” in aging tissue with an AI-powered barcode
RNA variant imaging for cancer diagnosis
Autism-risk mutations reveal two opposing patterns of brain gene activity
Avoiding a sticky situation: how cells stop messenger RNAs from clumping together
RNA Sequencing identifies new tick-borne virus that causes flu-like illness
Worm’s radical transformation shows metamorphosis can change the functions of cells
RNA sequencing reveals functional chimeric mRNAs in mammalian immunity
Atlas of the brain’s striatum could guide researchers to new drug treatments
Immune cells offer insights on billion-dollar virus
A functionally integrated cross-tissue alternative splicing program during short-term calorie restriction
Dietary oxidized plant sterol shifts macrophage state to fuel aortic inflammation
Unlocking the past – new method helps gain insights into old tissue
Novel AI model trained on RNA-Seq data accurately detects key gene mutations and predicts biomarkers across 32 cancer types
Transcriptomic aging clock reveals age-related molecular patterns in opioid dependence
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