Computational protocol: Temporal and Spatial Impact of Human Cadaver Decomposition on Soil Bacterial and Arthropod Community Structure and Function

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Protocol publication

[…] DNA was extracted from soil samples using a modified cetyltrimethyl ammonium bromide (CTAB) extraction method as described in . Once extracted, DNA was cleaned using PowerClean® DNA Clean-Up Kit (MO BIO Laboratories, Inc., United States) and the concentration and purity of cleaned DNA were quantified using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Inc., United States). Bacterial community composition was assessed via amplification of the bacterial variable region V1–V3 of 16S rRNA gene using the universal bacterial primer pair 27F (5′- GAGTTTGATCNTGGCTCAG) and 519R (5′- GTNTTACNGCGGCKGCTG). Amplicons were subjected to 454-pyrosequencing by bacterial tag-encoded FLX-Titanium pyrosequencing (bTEFAP) method () in the Genome Sequencer FLX System (Roche, Inc., United States). All FLX related procedures were performed following Genome Sequencer FLX System manufacturers instructions (Roche, Nutley, NJ, United States). Sequencing errors from all sequences were minimized using program PyroNoise () as implemented in Mothur v 1.32 (). Low quality regions of the sequences (total count of sequences = 127944) were trimmed using a sliding window (50 bp; Q35) option in Mothur v 1.32 (). Sequence with homopolymer length > 8 bp, and total length < 250 bp were removed from further analyses (). USEARCH was used for quality filtering and clustering reads into operational taxonomic units (OTUs) at 97% identity threshold, following the customized UPARSE pipeline described in . Taxonomy was assigned to OTUs at 97% identity threshold via the RDP classifier, using the GreenGenes 13.8 reference database for bacteria/archaea (; ). QIIME version 1.8.0 was used to generate rarefied OTU tables (rarefaction cutoff = 134 count/sample) and Chao 1 diversity estimates (). All raw sequence files were submitted to the European Nucleotide Archive (ENA) database as a part of the study PRJEB16630 (accession # ERS1420653 to ERS1420705). [...] The effect of distance from cadaver on soil bacterial community composition, function, and arthropod community composition was tested via permutation-MANOVA (PERMANOVA) and visualized using principal coordinates analysis (PCoA). Bray–Curtis distances were calculated for bacterial (based on OTU table) and arthropod composition while Euclidian distances were calculated for function. Specifically, for the PERMANOVA () (9,999 permutations), distance from the cadaver was the independent variable, and cadaver identity (see Supplementary Table ) was treated as a random effect to account for repeated sampling of soil from a subset of cadavers across time. Pair-wise differences between distances were also determined via PERMANOVA. Homogeneity of dispersions from the centroids was also determined, allowing the assessment of variation in composition or function associated with a given distance. To determine which component of microbial community composition or function contributed to differences between distances, the percentage contribution of taxa for community composition or of substrate for function to dissimilarity between distances (i.e., 0, 1, or 5 m) was determined using the SIMPER test in Primer (). Mantel tests were used to examine relationships between bacterial community composition, function, and arthropod community composition.Linear mixed effects models were used to assess the effect of distance on bacterial diversity, total arthropod abundance, and soil characteristics (i.e., soil pH, active microbial biomass, and mineralizable-C). Specifically, for each of these models, distance from the cadaver was the independent variable, and cadaver identity was treated as a random effect to account for repeated sampling of soil from a subset of cadavers across time. Pair-wise differences between distances were determined via Tukey’s HSD (P < 0.05) for bacterial data, and via LS means for arthropod data (as shown in Supplementary Table ).For the 0 m samples (i.e., those taken directly beneath the cadaver), a combination of linear and non-linear regression was used to assess the relationships between principal components axes and factors associated with temporal (i.e., accumulated degree day, cumulative precipitation) and cadaver specific dynamics (i.e., cadaver mass). If significant (P < 0.05) relationships with an axis were noted, this relationship was further examined by assessing the components of either composition or function associated with that axis. Additionally, linear and non-linear regression was used to assess the relationship between soil characteristics and temporal dynamics. Regression and linear mixed-effects models, using tem nlme package version 3.1-131, were conducted in R version 3.2.3 () and bacterial community, arthropod community, and functional analyses were conducted in Primer (). Arthropod data shown in Supplementary Table were analyzed using SAS v9.3 (SAS Institute, Cary, NC, United States). […]

Pipeline specifications

Software tools lme4, nlme
Application Mathematical modeling
Organisms Homo sapiens, Bacteria, Bacteroidetes, Firmicutes
Chemicals Carbon