Evidence map›Paper›PMID 33050884›Full record

ArticleBMC microbiology2020

Microbial succession from a subsequent secondary death event following mass mortality.

Lindsay Harrison, Emilia Kooienga, Cori Speights, Jeffery Tomberlin, Marcus Lashley, Brandon Barton, Heather Jordan

Abstract read
In one paragraph

Article in BMC microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Lindsay HarrisonDepartment of Biological Sciences, Mississippi State University, PO Box GY, Mississippi State, MS, 39762, USA.
Emilia KooiengaDepartment of Biological Sciences, Mississippi State University, PO Box GY, Mississippi State, MS, 39762, USA.
Cori SpeightsDepartment of Biological Sciences, Mississippi State University, PO Box GY, Mississippi State, MS, 39762, USA.
Jeffery TomberlinDepartment of Entomology, Texas A&M University, Minnie Bell Heep Center, Suite 412, College Station, TX, 77843, USA.
Marcus LashleyDepartment of Wildlife, Fisheries and Aquaculture, Mississippi State University, Box 9680, Mississippi State, MS, 39762, USA.
Brandon BartonDepartment of Biological Sciences, Mississippi State University, PO Box GY, Mississippi State, MS, 39762, USA.
Heather JordanDepartment of Biological Sciences, Mississippi State University, PO Box GY, Mississippi State, MS, 39762, USA. jordan@biology.msstate.edu.ORCID 0000-0002-4197-2194

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEach death event can be characterized by its associated microbes - a living community of bacteria composed of carcass, soil, and insect-introduced bacterial species - a necrobiome. With the possibility for close succession of these death events, it may be beneficial to characterize how the magnitude of an initial death event may impact the decomposition and necrobiomes of subsequent death events in close proximity. In this paper we hope to characterize the microbial communities associated with a proximate subsequent death event, and distinguish any changes within those communities based on the magnitude of an initial death event and the biomass of preexisting carcass (es) undergoing decomposition. For this experiment, 6 feral swine carcasses in containers were placed in the vicinity of preexisting and ongoing carcass decomposition at sites of three different scales of decomposing carcass biomass. Swab samples were collected from the skin and eye sockets of the container pigs and subjected to 16 s rRNA sequencing and OTU assignment.

resultsPERMANOVA analysis of the bacterial taxa showed that there was no significant difference in the bacterial communities based on initial mortality event biomass size, but we did see a change in the bacterial communities over time, and slight differences between the skin and ocular cavity communities. Even without soil input, necrobiome communities can change rapidly. Further characterization of the bacterial necrobiome included utilization of the Random Forest algorithm to identify the most important predictors for time of decomposition. Sample sets were also scanned for notable human and swine-associated pathogens.

conclusionsThe applications from this study are many, ranging from establishing the environmental impacts of mass mortality events to understanding the importance of scavenger, and scavenger microbial community input on decomposition.

Indexed as

Postmortem ChangesSoil MicrobiologyAnimalsBacteriaBiomassInsectaModels, AnimalRNA, Ribosomal, 16SSequence Analysis, RNASwineRNA, Ribosomal, 16SDecompositionMass mortalityMicrobial succession

Identifiers

PMID33050884
PMCPMC7557037

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.