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Microbial community assembly and metabolic function during mammalian corpse decomposition

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Science  08 Jan 2016:
Vol. 351, Issue 6269, pp. 158-162
DOI: 10.1126/science.aad2646
  • Fig. 1 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.

  • Fig. 2 Bacterial and archaeal decomposers emerge from multiple environments, but primarily from soil.

    (A) Dynamic Bayesian inference networks: A neural information flow network of microbial taxa during decomposition shows soils as the most common source of decomposers. (B) Results from deeply sequencing 16S rRNA amplicons from samples collected on the first day of each experiment. The y axis indicates the proportion of abdominal, skin, and soil decomposer OTUs (x axis) detected in each environment at the start of the experiment. Bars with standard error are ordered by soil type [desert (d), shortgrass (s), and forest (f)] (left) or season [winter (w) and spring (s)] (right). Decomposers were detected in soils more frequently than in the abdomen in every comparison (Mann-Whitney U test: P < 0.05).

  • Fig. 3 Succession of decomposer communities in the abdominal cavity.

    (A) Dynamic Bayesian network of interactions between archaea, bacteria, microbial eukaryotes, and environmental abundance measurements during decomposition. Arrows indicate the direction of causality, and the network is arranged hierarchically so that it is a proxy for succession. (B and C) Results of PCoA of cecum, with all of the PICRUSt-predicted KEGG orthologies (KOs) (B) or KOs only classified as “metabolism” in KEGG functional hierarchies (C). (D) PICRUSt-predicted nitrite reductase, lysine decarboxylase, and ornithine decarboxylase enzyme-level genes in the mouse abdominal cavity during decomposition.

  • Fig. 4 Effect of mammalian decomposition on soils.

    (A) pH, ammonium, and nitrate concentrations in mouse gravesoils and control soils. Error bars indicate 1 SD from the mean of five sample measurements. (B) Canonical correspondence analysis (CCA) of gravesoil bacterial predicted gene ontologies during decomposition. PICRUSt-predicted function data are based on KOs, with only genes classified as “metabolism” included in this analysis. (C) Predicted gene abundances of glutamate dehydrogenase and nitrate reductase in soils during decomposition.

Supplementary Materials

  • Microbial community assembly and metabolic function during mammalian corpse decomposition

    Jessica L. Metcalf, Zhenjiang Zech Xu, Sophie Weiss, Simon Lax, Will Van Treuren, Embriette R. Hyde, Se Jin Song, Amnon Amir, Peter Larsen, Naseer Sangwan, Daniel Haarmann, Greg C. Humphrey, Gail Ackermann, Luke R. Thompson, Christian Lauber, Alexander Bibat, Catherine Nicholas, Matthew J. Gebert, Joseph F. Petrosino, Sasha C. Reed, Jack A. Gilbert, Aaron M. Lynne, Sibyl R. Bucheli, David O. Carter, Rob Knight

    Materials/Methods, Supplementary Text, Tables, Figures, and/or References

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    • Materials and Methods
    • Supplementary Text
    • Figs. S1 to S19
    • Tables S1 to S17 and S20
    • Captions for Tables S18 and S19
    • Full Reference List
    Table S18
    Soil chemistry data is reported by sample
    Table S19
    Nearest Sequenced Taxon Index scores for PICRUSt gene predictions are reported

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