Soil microbes and oxygen inuence the changes in bacterial community composition during swine carcass decomposition

Carcass decomposition is inuenced by various factors such as temperature, humidity, microorganisms, invertebrates, and scavengers. Soil microbes play a signicant role in the decomposition process. In this study, we investigated the changes in the bacterial community during carcass decomposition in soil with an intact microbial community and soil which was sterilized decomposed with and without oxygen access using 16s rRNA metagenomic sequencing. Based on the 16S rRNA metagenomic sequencing, a total of 988 operational taxonomic units (OTUs) representing 16 phyla and 533 genera were detected. The bacterial diversity varied across the based on the alpha diversity indices. The bacterial composition in the unsterilized soil – aerobic condition (U_A) and unsterilized soil – anaerobic condition (U_An) set-ups have higher alpha diversity than the other burial set-ups. Beta diversity analysis revealed a close association in the samples according to the burial type and decomposition day. Firmicutes was the dominant phylum across all samples regardless of the burial type and decomposition day. The bacterial community composition changed throughout the decomposition process in all burial set-up. Meanwhile, the genus Bacillus dominated the bacterial community towards the end of decomposition period.

polymers of organic matter into oligomeric and monomeric molecules [3]. Soil microbial proteases synthesized in response to the supply of animal organic matter were able to degrade prion protein in vitro [5].
The deposition of animal carcasses and their decomposition can in uence the soil microbial communities. This causes great impact in the soil microbiome as the carcass in uences both biotic and abiotic factors [6]. In addition, a succession within the microbial community will occur after the introduction of a carcass, hence, changing abundances in accordance with nutrients being released during carcass decomposition [6,7]. In addition to soil microbes, carcasses also possess a diverse microbiome which is introduced into the soil as decomposition progresses. During the decomposition process, it causes signi cant and sequential changes in the bacterial communities within the soil and these changes can be correlated with various stages of decomposition.
The microbial communities plays an important role in maintaining soil quality due to their involvement in organic matter dynamics, nutrient cycling and decomposition [8]. However, metabolites from decomposing carcasses can affect the land and surrounding environment [9]. Therefore, it is important to investigate the composition of the bacterial community after soil burial. In our present study, swine carcasses were decomposed on either (i) soil with an intact microbial community (unsterilized soil) or (ii) soil that was sterilized, and each incubated under aerobic (with oxygen) and anaerobic (without oxygen) condition. Metagenomic sequencing of samples obtained through the carcass decomposition was conducted to investigate the bacterial community structure. Speci cally, the changes in the bacterial community composition in each experimental set-up was determined.

Swine carcass decomposition
Carcass decomposition was conducted in unsterilized and sterilized soil under aerobic and anaerobic conditions. Moisture percentage in the swine carcass was observed for 60 days. Moisture content ranged between 55.75 % to 66.50 % and was relatively constant throughout the experiment, except between days 5 to 10 (Fig. 1a). Signi cant differences in moisture content between the set-ups were observed at 30 and 60 days of incubation (p<0.05). At 60 days of incubation, higher moisture (p<0.05) was observed in the unsterilized soil-anaerobic burial set-up. In terms of pH, the value ranged from 6.10 to 8.16. The pH increased as decomposition progressed and remained relatively constant between days 30 to 60 ( Fig.   1b). At the end of day 60 of decomposition, higher pH 8.15 and 8.16 (p<0.05), respectively, was observed in both the sterilized and unsterilized soil-aerobic condition burial set-ups.

Diversity of bacterial communities
The changes in the bacterial community during decomposition of swine carcasses over a 60-day period were investigated using Illumina metagenomic sequencing technology. The boxplot representation of alpha diversity indices is shown in Fig. 2. The boxplot of observed OTUs from the samples showed that OTUs in unsterilized soil -anaerobic condition (U_An) was higher compared to the other burial set-ups ( Fig. 2a). Chao1 which represents the OTU abundance in the samples showed that unsterilized soilanaerobic condition (U_An) was the highest followed by unsterilized soil -aerobic condition (U_A) (Fig.   2b). Shannon index which re ects the diversity of the OTUs in the samples showed that unsterilized soilanaerobic condition (U_An) is the most diverse among the burial set-up and sterilized soil -aerobic condition (S_A) being the least (Fig. 2c). This could indicate that bacterial communities changed at each period and were consisted of various bacterial species. Overall, our results showed that the bacterial composition of unsterilized soil -anaerobic condition (U_An) and unsterilized soil -aerobic condition (U_A) had higher alpha diversity than the other burial set-ups, although no signi cant difference was observed.
Changes in the bacterial community composition Bacterial community composition of each sample was analyzed and compared at the phylum, genus and species levels ( Fig. 3 -5). A total of 988 OTUs were detected in all samples. Sixteen phyla and 533 genera were identi ed from the samples in the burial set-ups throughout the decomposition period. Overall, the majority of the sequences belonged to Firmicutes (84%) (Fig. 3a). At phylum level (Fig. 3b), Firmicutes in the set-up with unsterilized soil both incubated under aerobic and anaerobic condition increased from day 0 to 5 of decomposition. Meanwhile, Firmicutes decreased in abundance from day 0 to 5 in the set-up with sterilized soil both incubated under aerobic and anaerobic condition. In terms of genus level (Fig. 4), the bacterial community composition varied at each sampling day in all burial set-up. During days 0 to 30, the bacterial community in the samples were dominated by Lactobacillus, Escherichia, and Clostridium. Meanwhile, at days 30 and 60, the samples were dominated by Bacillus. In terms of species level (Fig. 5), the bacterial communities varied at each sampling period. During days 5 and 10, there was a high abundance of Escherichia fergusonii. The dominant bacterial species towards the end of decomposition belongs to Bacillus. Meanwhile, Bacillus haynesii was dominant at day 60 in all burial setups.
The differentially abundant bacterial orders across different burial groups for each sampling period was presented as hierarchical clustering heatmap in Fig. 6. The normalized data presented shows the clustering based on the similarity of relative abundance between representative orders of OTUs (row) and burial groups for each sampling period (column). Lactobacillales was mostly found at day 0 and 5 of decomposition in all groups and was detected in high abundance at day 5 in sterilized soil -aerobic condition (S_A) group. The order Clostridiales was more dominant in U_An at day 5 than in other groups. Meanwhile, Bacillales was mostly present at days 30 and 60 of decomposition in all burial groups.
Pseudomonadales has higher abundance unsterilized soil -anaerobic condition (U_An) and sterilized soil -aerobic condition (S_A) group at day 10 of decomposition, while Corynebacteriales was more abundant in sterilized soil -aerobic condition (S_A) at day 10 than in other groups.
The comparison of the bacterial communities by non-metric multidimensional scaling (NMDS) is presented in Fig. 7. Beta diversity did not vary signi cantly between the different burial groups at different time points. Beta diversity analysis revealed a close association between the burial type and sampling period.

Core microbiome
A Venn diagram was used to compare the similarities and differences between the bacterial communities in the different burial set-ups during carcass decomposition (Fig. 8). The U_A, S_A, U_An, and S_An communities had 308 observed species in common which corresponds to 31.17 % of the total observed species. Meanwhile a total of 400 (40.49 %) were shared by 2 or 3 samples, and 280 (28.34 %) of observed species were speci c and distributed to the four burial set-ups. Speci cally, 111 were uniquely found in the U_A, 33 in S_A, 96 in U_An, and 40 in S_An.

Swine carcass decomposition
In the present study, the moisture content at 60 days of decomposition was observed to be high in the unsterilized soil-anaerobic burial set-up. This indicates that microbes present in the soil and carcass may have contributed to the high moisture during decomposition. This result is similar to previous studies which suggest that decomposition is affected by moisture. In terms of the effect of soil pH on the decomposition process, several research papers have suggested that bacterial growth is enhanced in neutral or slightly alkaline conditions, whereas acidic conditions promote fungal growth [10]. The pH values obtained in our study ranged from 6.50 to 8.16. The pH progressively increased with increasing time of decomposition and remained relatively constant between days 30 to 60. The increase in soil pH is attributed to the release of nitrogen mineralization by-products from the degradation of macromolecules [11]. Although the pH of the burial soil was highly variable, there were signi cant differences in soil pH between the set-ups at days 30 and 60. In the study by Ki et al. (2018) [3], the pH at the beginning of decomposition was 6.9, then decreased at day 54 before increasing up to 7.9. Several decomposition studies have provided contradictory results on the variation of soil pH over time [4]. A long-held belief is that cadaver decomposition results in increased pH values because of the accumulation of NH 4 + in the soil [11]. This indicates that the high pH of the samples could be a result of the ammoni cation of proteins and organic nitrogen [11].
Bacterial diversity during carcass decomposition The bacterial communities are essential for maintenance of soil quality because of their involvement in organic matter dynamics, nutrient cycling and decomposition [8]. However, metabolites produced by the microorganism can affect the balance of the ecosystem [9]. Several studies were also conducted to investigate bacterial communities from leachates in animal carcass disposal sites [12] and groundwater around carcass disposal sites [13]. These studies provided vital information on the bacterial populations, as well as the bacteria which can adversely affect the environment and human health. Thus, an investigation of bacterial community composition in soil burial is important, because compounds from decomposing carcasses could affect the land and surrounding environment, and may pose human health risk.
In this study, the bacterial community analysis of animal carcass disposal soil was investigated using Illumina Miseq sequencing and the bacterial populations over the course of the decomposition period were determined. Firmicutes was found to be the dominant phylum in all samples. According to Li et al. (2013) [14], Firmicutes reduce large macromolecules such as proteins, complex fats and polycarbohydrates to their building blocks. Furthermore, Firmicutes are more prominent during active decomposition [15,16].
On the other hand, phylum Proteobacteria was also abundant during days 5 and 10 of decomposition. However, there was a reduction in population after 10 days of decomposition. The phylum Proteobacteria includes α-Proteobacteria, β-Proteobacteria, γ-Proteobacteria, and δ-Proteobacteria. Of these, γ-Proteobacteria are common in soil and plays an important role in the decomposition of fats and carbohydrates [17].
Bacillus, Clostridium, Lactobacillus, Escherichia, and Enterococcus were among the common genera found at days 5 and 10 of decomposition, indicating the presence of potentially pathogenic microbes in soil samples during carcass decomposition. Meanwhile, Lactobacillus spp. decreased in abundance after 10 days of decomposition.
The abundance of Clostridium spp. is high at days 5 to 30 of incubation in the unsterilized soil both incubated aerobic and anaerobic conditions. However, abundance of Clostridium spp. under anaerobic conditions is relatively higher than in anaerobic conditions. Several studies reported that the anaerobic layer that develops around a carcass during decomposition is associated for the increase in abundance of Clostridium spp. which plays an important role in the biomass digestion. It produces a wide variety of extracellular enzymes which helps in the degradation of large biological molecules [18][19][20]. At the end of the decomposition period, the predominant genus in all burial set-ups was Bacillus, in which a number of species are capable of denitri cation [21]. Microbial analysis suggest that anaerobic bacteria ourished at most times during decomposition. Meanwhile, aerobic bacteria ourish during the early stages of the decomposition process as there is oxygen present within the body. However, as the microbial population increases, the accumulation of gases during the decomposition process makes the environment anaerobic which prompts the microbial community to shift to anaerobic bacteria [22]. Additionally, the changes in bacterial communities suggest that various bacterial species played a role during the decomposition period.

Conclusions
In this study, we evaluated the changes in the bacterial communities in decomposing swine carcasses over 60 days period. Different bacterial genera dominated at speci c period during decomposition. The composition of the bacterial community during carcass decomposition was affected by the presence or absence of soil microorganisms and the oxygen access. The dominant phylum in all samples throughout the experimental period was Firmicutes. The genera Bacillus was dominant in the burial set-ups starting from day 30 of decomposition. Overall, our results indicate that bacterial communities in the burial set-up changes continuously throughout the decomposition process of carcass.

Preparation of carcass samples
A domestic pig (Sus scrofa), weighing 10.0±2.0 kg was purchased commercially. All the experimental protocol in this study was approved by the Animal Care and Use Committee (Approval number: SCNU IACUC-2019-7) of Sunchon National University (Suncheon, Jeollanam-do, Korea), and performed in accordance with the guidelines and regulation set by this governing body. All methods in this experiment was carried out in compliance with the Animal Research Reporting In Vivo Experiments (ARRIVE) guidelines. The swine was euthanized and its carcass was separated from the bones, while the blood and internal organs were taken. After removing the bone, the carcass, skin, blood, and internal organs were homogenized in a blender and used for the microcosm burial set-up.

Soil preparation
To simulate conditions similar to the burial of deceased animals on a farm, soil samples were obtained from the experimental farm of Sunchon National University. Soil samples were sieved (mesh size: 2 mm) and divided into two set-ups: (1) soil with an intact microbial community (unsterilized) and (2) soil that was sterilized. Soil sample was sterilized by autoclaving at 121˚C, 15 psi thrice in four days to destroy microbes, fungi and their spores [1].
In vitro set-up for carcass decomposition A 2 x 2 carcass burial set-up in a laboratory setting was made using two types of soil (i. soil with an intact microbial community; ii. sterilized soil) under two incubation conditions (a. with oxygen access; b. without oxygen access). The treatment set-ups were as follows: unsterilized soil -aerobic condition (U_A), sterilized soil -aerobic condition (S_A), unsterilized soil -anaerobic condition (U_An), and sterilized soilanaerobic condition (S_An). The microcosm burial set-up used was based on the study conducted by Han et al [23] with some modi cations. Sixty sterilized containers (450 mL) containing 120 g of soil and 45 g of meat were placed in each container. The soil/carcass ratio were homogenized thoroughly in order to evenly distribute the meat within the soil. The mixture of soil and meat was decomposed under aerobic and anaerobic conditions. Anaerobic conditions were created by sealing all parts of the container and placed in an incubator with 5% owing CO 2 . For simulating aerobic conditions, the lid of the reactor was punctured so that air could pass through the hole prior to placing it in an incubator. All experimental setups were conducted in triplicate, incubated at 25°C for a total period of 60 days and sampled at days: 0, 5, 10, 30, and 60. Day 0 is the initial placement followed by subsequent sample collections on days 5, 10, 30, and 60. Two grams of samples were taken from each container and stored at -20 °C for chemical and metagenomic analyses.

Chemical analysis
Samples were collected at days 0, 5, 10, 30, and 60. To measure the pH of the sample, 1 g of soil was suspended in 5 ml sterilized distilled water and vortexed for 1 min. The supernatant was collected after allowing the large particles to settle for 5 min and the pH was measured with a pH meter (SevenCompact™ pH/Ion meter S220, Mettler Toledo, Switzerland). The average readings of the three samples was used to estimate the pH for each soil [1]. The moisture content of the soil and carcass mixture was estimated according to the standard method AS 1289 B1.1. One gram of burial soil was weighed, placed in an aluminum plate, and oven-dried overnight at 105 °C.

DNA extraction, PCR ampli cation and sequencing
Metagenomic DNA was extracted from 0.25 g of soil samples obtained from each burial set-up were using the DNeasy® PowerSoil® Kit (Qiagen, Hilden, Germany) according to the manufacturer's instructions. The extracted DNA was stored at -20 °C until further processing. The quality and quantity of the extracted DNA was checked using Quant-IT PicoGreen (Invitrogen, Grand Island, NY, USA). DNA sequencing libraries targeting the V3-V4 hypervariable region of the 16S rRNA gene were performed according to the Illumina 16S metagenomic sequencing library preparation method [24]. This consists of two PCR steps. In the rst ampli cation, speci c primers were used, while in the second, index information for sample identi cation was added. The DNA was ampli ed by primary PCR using universal primer pair with Illumina adapter overhang sequences, S-D-Bact-0341-b-S-1 (5′-TCG TCG GCA GCG TCA  GAT GTG TAT AAG AGA CAG CCT ACG GGN GGC WGC A-3′) and S-D-Bact-0785-a-A-21 (5′-GTC TCG  TGG GCT CGG AGA TGT GTA TAA GAG ACA GGA CTA CHV GGG TAT CTA

Sequence data processing and analysis
The raw data les (fastq) containing the sequenced paired-end reads were obtained using the bcls2fastq package (Illumina Inc., San Diego, CA, USA) from the base call binary data produced by real-time analysis. Raw sequences were pre-processed to lter the adaptor sequences and remove low-quality sequences using the Trimmomatic v0.38 [26] and assembled using Fast Length Adjustment of Short Reads (FLASH 1.2.11) [27]. Sequences shorter than 400 bp were discarded to ensure that any subsequent analysis was highly accurate. The obtained sequences were subjected to CD-HIT-OTU [28] to remove lowquality sequences, ambiguous sequences, and chimera sequences, which are considered as sequencing errors. The ltered reads were clustered and identi ed as OTU at 97% sequence similarity using CD-HIT-OTU [28], and chimeric sequences were identi ed and removed using rDnaTools (https://github.com/Paci cBiosciences/rDnaTool). The representative sequences from the clustered OTU were taxonomically assigned using Quantitative Insights Into Microbial Ecology (QIIME Version 1) [29] from the NCBI 16S rRNA database, and the taxonomy composition from phylum to species level was generated using QIIME-UCLUST [30].
The metagenomic data was visualized using a biom formatted OTU table [31] in the MicrobiomeAnalyst tool (http://www.microbiomeanalyst.ca) [32]. The OTU data were ltered in order to remove low quality or uninformative feature. The following criteria were used: low count lter was set using default minimum count of 4 and the prevalence in samples was set at 20%, while the low variance lter was set at interquartile range and the percentage to remove was set at 10%. The data were normalized by rarefying to the minimum library size and scaled by total sum scaling before further downstream processing.
Alpha diversity of each sample was assessed using the observed OTU number and Chao1 to measure the species richness, whereas species evenness was measured using Shannon index. Signi cant differences between samples in alpha-diversity were assessed using a non-parametric Kruskal-Wallis test. Beta diversity was calculated based on Bray-Curtis dissimilarity and statistical signi cance of the clustering pattern in the ordination plot was evaluated by permutational multivariate analysis of variance (PERMANOVA). The ordination plot was visualized using non-metric multidimensional scaling (NMDS) graph. The core microbiome analysis was done as described in MicrobiomeAnalyst [32]. To detect the core microbiome, 20% prevalence and 0.01% relative abundance was used. The relative abundances of the phylum, genus, and species levels were plotted as a bar graph. Hierarchical cluster analysis was visualized using the MicrobiomeAnalyst tool using Euclidean distance measure and Ward clustering algorithm of relative abundances of bacterial OTUs at the order level. In addition, a Venn diagram of the membership-based representation of unique, shared and core bacterial community was generated in MetaCOMET [33] using jvenn [34].

Statistical Analysis
Data for moisture and pH were subjected to analysis of variance (ANOVA) using the general linear model (GLM) procedure of Statistical Analysis Systems (SAS) version 9.4 (SAS Institute Inc., Cary, NC, USA). All analyses were conducted in triplicate and Duncan's multiple range test was used to identify differences between speci c treatments. Differences with p values less than 0.05 were considered statistically signi cant.  Bacterial community structure at the genus level during carcass decomposition.

Figure 5
Bacterial community structure at the species level during carcass decomposition. Hierarchical clustering heatmap of bacterial orders from the swine carcass decomposition set-up generated by MicrobiomeAnalyst using Euclidean distance measure and Ward clustering algorithm. Normalized relative abundance are plotted from low (blue), mid (peach), and high (red). U_A (unsterilized soil -aerobic condition), S_A (sterilized soil -aerobic condition), U_An (unsterilized soil -anaerobic condition), and S_An (sterilized soil -anaerobic condition). The 0, 5, 10, 30, and 60 represents sampling period.  Membership-based representation of unique, shared and core bacterial community of decomposing swine carcass under different burial set-up conditions, and the total size of observed species per set-up. U_A (unsterilized soil, aerobic condition), S_A (sterilized soil, aerobic condition), U_An (unsterilized soil, anaerobic condition), and S_An (sterilized soil, anaerobic condition).