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Research Article
Zhenyuan Wang
Xi'an Jiaotong University
Corresponding Author
ORCiD: https://orcid.org/0000-0003-3561-6414
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Microorganism plays a vital role in the decomposition of vertebrate remains in nature nutrient cycling, where the postmortem microbial succession patterns during decomposition remain unclear. Here, hierarchical clustering based on Manhattan distances analyzed the similarity and difference among postmortem intestine microbial succession patterns from microbial 16S rDNA sequences in a mouse decomposition model. Based on the similarity, seven different classes of succession patterns are obtained. Generally, the normal intestinal flora in the cecum gradually decreases with changes in living conditions after death, while some facultative anaerobes and obligate anaerobes grew and multiplied with oxygen consumption. Furthermore, a random forest regression model is developed to predict postmortem interval with the microbial succession trend data set. The model demonstrates a mean absolute error of 20.01 hours and a squared correlation coefficient of 0.95 during 15-day decomposition. Lactobacillus, Dubosiella, Enterococcus, and Lachnospiraceae NK4A136 group are considered as significant biomarkers for this model according to the ranked list. This study explores microbial succession patterns in terms of relative abundances and variety, aiding in predicting postmortem intervals, offering some knowledge of microbial behaviors in decomposition ecology.
Keywords
16S RNA, gut microbiota, microbial dynamic analysis, time-series study, postmortem interval estimation
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View the published article at Microbial Ecology.
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Posted 13 Apr, 2021
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Editorial decision: Major Revisions Needed
On 10 May, 2021
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A new preprint design is coming!
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See the published version of this preprint at Microbial Ecology.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
Zhenyuan Wang
Xi'an Jiaotong University
Corresponding Author
ORCiD: https://orcid.org/0000-0003-3561-6414
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at Microbial Ecology.
Version 1
Posted 13 Apr, 2021
No community comments so far
Editorial decision: Major Revisions Needed
On 10 May, 2021
Reviewers invited
Invitations sent on 10 Apr, 2021
Reviews received
Received 09 Apr, 2021
First submitted
On 06 Apr, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Microbial Ecology.
Microorganism plays a vital role in the decomposition of vertebrate remains in nature nutrient cycling, where the postmortem microbial succession patterns during decomposition remain unclear. Here, hierarchical clustering based on Manhattan distances analyzed the similarity and difference among postmortem intestine microbial succession patterns from microbial 16S rDNA sequences in a mouse decomposition model. Based on the similarity, seven different classes of succession patterns are obtained. Generally, the normal intestinal flora in the cecum gradually decreases with changes in living conditions after death, while some facultative anaerobes and obligate anaerobes grew and multiplied with oxygen consumption. Furthermore, a random forest regression model is developed to predict postmortem interval with the microbial succession trend data set. The model demonstrates a mean absolute error of 20.01 hours and a squared correlation coefficient of 0.95 during 15-day decomposition. Lactobacillus, Dubosiella, Enterococcus, and Lachnospiraceae NK4A136 group are considered as significant biomarkers for this model according to the ranked list. This study explores microbial succession patterns in terms of relative abundances and variety, aiding in predicting postmortem intervals, offering some knowledge of microbial behaviors in decomposition ecology.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
This is a list of supplementary files associated with this preprint. Click to download.
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