Microbiome pattern of Lucilia sericata (Meigen) (Diptera: Calliphoridae) and feeding substrate in the presence of the foodborne pathogen Salmonella enterica

The microbial diversity and quantitative dynamics during the insect’s development stages constitute recently developed putative tools in forensic and medical studies. Meanwhile, little is known on the role of insects in spreading foodborne pathogenic bacteria and on the impact of these pathogens on the overall insects and feeding substrate microbiome composition. Here, we provide the first characterization of the bacterial communities harbored in adult and immature stages of Lucilia sericata, one of the first colonizers of decomposed human remains, in the presence of the foodborne pathogen Salmonella enterica using 16S rRNA Illumina sequencing and qPCR. The pathogen transmission from the wild adults to the second generation was observed, with a 101.25× quantitative increase. The microbial patterns from both insect and liver samples were not influenced by the artificial introduction of this pathogenic foodborne bacteria, being dominated by Firmicutes and Proteobacteria. Overall, our results provided a first detailed overview of the insect and decomposed substrate microbiome in the presence of a human pathogen, advancing the knowledge on the role of microbes as postmortem interval estimators and the transmission of pathogenic bacteria.


Scientific Reports
| (2021) 11:15296 | https://doi.org/10.1038/s41598-021-94761-w www.nature.com/scientificreports/ adults, with values ranging between 10 3.60 and 10 3.84 . The bacterial concentration in the new generation was 10 1.03 × higher than the initially assimilated one. Regarding the differences between the specimens fed with low and high S. enterica inoculated liver, the most noticeable difference was recorded for the third instar larvae, with 10 -1.21 × lower concentration in the larvae fed with the low inoculated liver. S. enterica content from the low and high initial inoculations was very similar in value between several samples, such as the adult (10 2.59 , 10 2.81 ), third instar larvae (10 3.59 , 10 3.74 ), pupa (10 3.53 , 10 3.55 ) and teneral specimens (10 3.60 , 10 3.84 ) (Fig. 1a). Moreover, the specimens fed with both concentrations showed a similar dynamic, namely an ascending trend up to the third larval stage and then a descending slope to the new generation.
No S. enterica could be identified in the fresh liver samples, as in the case of the wild L. sericata adults. The pathogen content after the first day of inoculation increased up to 10 3.79 and 10 4.38 (Fig. 1b). Subsequently the trend was slightly ascendent, reaching a maximum value of 10 5.33 in the last experimental day. The increase in bacterial abundance of 10 4.65 (Fig. 1b) corresponded to an increased value in the third larvae stage of 10 5. 15 . The liver samples were collected and analyzed as long as the larvae fed on it. Therefore, there are fewer liver sampling points than insect sampling points. Nevertheless, the liver samples may have undergone changes in S. enterica concentration due to the actively feeding larvae and the progress of decomposition.
Bacterial community diversity and profile throughout Lucilia sericata life stages and from the liver associated-samples. The bacterial diversity and composition were investigated and found to be specific and clearly delimited for L. sericata life stages, represented by the adult, larvae stages, pupa and teneral specimens. Overall, there were 14 phyla, 117 orders, and 274 genera identified for the insect samples, while the liver tissue bacterial diversity contained 28 phyla, 113 orders and 183 genera.
Out of a total of 155 identified families, Lactobacillaceae and Corynebacteriaceae had the highest relative abundance values (Fig. 3b)   www.nature.com/scientificreports/ No significant differences in the bacterial communities' diversity were observed in the untreated and treated liver samples with S. enterica, while variable community structure was visible during the decomposition process being time dependent (Fig. 4a). The fresh liver samples used as control showed a completely different bacterial community as compared to the decomposed liver tissues (Fig. 4a). While in most samples, Firmicutes constitute the dominant phyla, in the control tissues Actinobacteria had the highest relative abundance (52.81 ± 24.11%), followed by Proteobacteria (30.69 ± 4.75%) (Fig. 4a). During liver decomposition, Firmicutes relative content increased from 83.72 ± 14.70% to 91.32 ± 9.63%, while Proteobacteria registered lower abundances in the first 3 days of decay, recording an average value of 29.09 ± 12.40% (Fig. 4a). A similar pattern was registered at the Order level, Bacilli being the most representative in most samples (86.61 ± 13.45%), except for the control liver tissue (Fig. 4b). Corynebacteriales represented by Corynebacteriaceae (50.86 ± 26.37%) were dominant in the untreated liver, while Lactobacillales represented by Lactobacillaceae (66.84 ± 21.32%) showed the highest relative content in all treated samples (Fig. 5a, b). At the family level, the highest diversity registered during the first experimental days comprised Lactobacillaceae, Enterobacteriaceae, Streptococcaceae, Hafniacea, Leuconostocaceae, i.eg. (Fig. 5b), with Lactobacillus (60.94 ± 27.75%) dominating the bacterial community from decomposed liver samples, while Lawsonella (50.55 ± 26%) was dominant in the untreated liver.
Regarding the genera consistence within the investigated samples, Lactobacillus was prevalent in both insect (95.24%) and liver (100%) samples (Fig. 6). Among the other common genera identified (Fig. 7), Weissella had different prevalence values, being 29% higher in the liver tissues, representing the second most prevalent genus of this sample type (Fig. 6). Furthermore, Citrobacter, Acinetobacter, and Vagococcus were the among the prevalent genera detected in both insect and liver samples.
Among the total of 457 identified genera, eight were shared by all sample types, from which the most abundant taxa were represented by Myroides, Kurthia, Lawsonella, Acinetobacter, and Lactobacillus, while the pupa and the liver samples presented the highest number of distinct genera (Fig. 7). When testing for a differential prevalence of bacterial genera, 54 genera were differentially represented between liver and insect samples. Seven genera prevailed in the liver samples, including Enterobacter, Aeromonas, Lelliotia, Serratia, Citrobacter, Hafnia Obesumbacterium and an Enterobacteriaceae, while 47 genera prevailed in insect samples, including Comamonas, Lawsonella, Stenotrophomonas, Pseudochrobactrum, Providencia and Morganella among others.
The Shannon alpha diversity index showed no significant variation among the insect samples subject to Salmonella feeding treatment and the samples of insects fed with non-inoculated liver (Fig. 8a). The pupa stage displayed significantly higher values in terms of richness, Shannon index and evenness, while the teneral stage  (Fig. 8a). Moreover, the presence of S. enterica in the feeding substrate did not affect the overall microbiome diversity of the insect specimens, as the two-way ANOVA revealed that the pathogen concentration accounts for < 0.1% of the total variance, while time represented by the development stages (adult, larva, pupa and teneral specimens) accounts for 66.97% (p < 0.0001) of the total variance. On the other hand, for the liver samples collected immediately after being purchased the microbiome diversity was the lowest, according to the Shannon index, while the overall diversity observed between treatments showed slight differences (Fig. 8b). The concentration interactions given by the Salmonella treatment accounted for 30.08% (p = 0.0156), while time accounted for 31.67% (p = 0.0127) of the total variance, suggesting that the diversity differences recorded are likely due in part to the pathogens' presence but also to the decomposition process over time. Furthermore, the alpha diversity for the insect samples had a slightly higher range compared to the liver samples ( Fig. 8a,b). The PCoA based on weighted UniFrac distances was used to further investigate and explain the grouping of samples according to Salmonella treatment. In the insect case, the PCoA explained only 88.3% of the variance on the two axes (A1 and A2), where R was − 0.026 and p = 0.966 (Fig. 8c). The PCoA results were similar for the liver associated samples, where the analysis explained 89.4% of the variance, at an R value of 0.256 and p = 0.002 (Fig. 8d).

Discussion
Salmonella enterica was introduced in the experimental model to observe whether or not this foodborne pathogenic bacterium can cause changes in the general structure of the microbiome during L. sericata development, as well as in the inoculated substrate, and whether or not these quantitative and qualitative changes would affect a possible estimation of the insect development stage. At the same time, the pathogen transfer during fly development was investigated. Given the interaction of blowflies with a large number of bacterial species they are ideal candidates for the study of fly-bacteria interactions. Our study involving L. sericata and S. enterica helps to understand these interactions in the wild, and their forensic and medical repercussions, by providing data on the bacterial specificity for certain insect life stages that can be used to track their transfer in the colonized tissues. By identifying bacteria-life stages specificity the development stage of the insect along with the body decomposition can be estimated.
For humans, the infectious dose of Salmonella strains depends on age, physical condition, health status, as well as the bacterial strains involved in the infection. In general, 10 5 -10 6 CFU (colony forming unit) bacterial www.nature.com/scientificreports/ cells are necessary to induce acute salmonellosis 42 . This large inoculum is needed due to gastro-intestinal tract conditions, such as low acidity, presence of bile salts and enzymes, and normal intestinal microbiome which generates nutrient competition. A low gastric acidity related to a variety of medical conditions or in the elderly population can decrease the infectious dose to 10 3 cells 43 . Consequently, for the current study the feeding environment of L. sericata was inoculated with 10 2 CFU/ml and 10 4 CFU/ml. An important aspect from a forensic perspective is that there was no registered delay in the colonization of the Salmonella inoculated liver by L. sericata, indicating that the presence of this pathogen did not prevent the feeding of the adult specimens. A previous study 44 , where pigs were exposed to contamination with Salmonella enterica subsp. enterica serovar Typhimurium by direct intranasal inoculation, or indirect, by environmental contamination required more than 10 3 Salmonella to induce an acute infection. Moreover, the market-exposed pigs during routine resting or holding could be infected by Salmonella when subjected to a bacterial concentration of 10 3 CFU 45 . As resulted from these previous studies 44, 45 , a Salmonella concentration of 10 4 × can cause an infection in a weakened animal or human, by food/surface contamination. Regarding the overall microbiome characterization, studies investigating the fly's bacterial content showed that Proteobacteria, Firmicutes, Bacteroidetes and Actinobacteria prevailed in both blowfly and housefly life stages 9,13,46 , while another study 36 revealed that Flavobacteria dominated the pupa stage. Singh and collaborators research 36 showed that the microbiome pattern was specific and similar for the adult and larva stages, being characterized by Firmicutes with Lactobacillales, for the pupa being dominated by Proteobacteria with the greatest order and family diversity, and for the teneral stage prevailing Actinobacteria with Corynebacteriales. In a recent study, Actinobacteria was not that consistent among L. sericata and L. cuprina dissected organs, however, were more abundant 46 . Interestingly, during the present research Actinobacteria was present in high abundances in the teneral specimens, suggesting that this phylum can play a role within the species metabolic activities. In contrast, another study revealed that the microbiome between the adult and eggs, and between the pupa and larvae stages was similar 33 . Although a bacterial diversity delimitation, characteristic for certain stages www.nature.com/scientificreports/ of development could be emphasized, this was not reflected in the diversity dynamics of the liver samples, which were dominated by Firmicutes. Most studies revealed Gammaproteobacteria as the main class identified from the blowfly specimens 9,11,33,35 , with a relative abundance of up to 81% 11 . Furthermore, in Maleki-Ravasan et al. 11 Morganellaceae represented the most abundant family detected both by culture-dependent and independent methods, while in the current survey Lactobacillaceae dominated, along with Corynebacteriaceae. At genera level, Citrobacter was identified among the most prevalent taxa, being also identified by both methods mentioned above from L. sericata life stages 11 . This genus plays a role in the production of putrefaction products, such as www.nature.com/scientificreports/ indole, by converting tryptophan, but also has the ability to ferment lactose 47 , being among the most prevalent genera detected in our samples. The same recent studies on L. sericata bacterial content 11,35 revealed Proteus as the most abundant genus detected, being identified from the digestive tract, salivary glands and the adult stage 48,49 . However, the study of Gasz et al. 46 revealed the dominant presence of Pseudomonas and Corynebacterium in all L. sericata organs, while Proteus was observed in low abundances. During our investigation, this taxon was the 7th most abundant genera, Lactobacillus being the most abundant in all investigated samples. The presence in high number of Lactobacillus can be explained by this genus fermentative abilities, being also well adapted to the insect hosts 50 . This genus was identified as being more abundant in the insect salivary gland 36 , and was able to inhibit other bacterial growth by producing bacteriocins 51 . However, in the recent study of Gasz et al. 46 , Lactobacillus was identified in lower quantities, compared to our study, where this taxon prevailed. The presence of Lactobacillus in low abundance 46 can be a consequence of the investigated organs and feeding substrate that differed from the initial bait (dog dung), the later one could also explain the variation between insect and bait samples. Furthermore, Proteus was previously identified as less abundant as 0.4% in L. sericata specimens 33 , however, it was demonstrated that this bacterium can transmit swarming signals to attract blowflies 52 , so its presence in insects may be explained by its acquisition from the surrounding environment. Even though in our study Proteus was one of the top ten most abundant genera, it was ranked 16th in prevalence in the insect samples, and 26th in the liver; the highest values being recorded in the last experimental day; 18.86% and 28.75%, respectively. In the insect samples, the higher relative abundance of 37.02% was recorded for the pupa stage, not being detected in the adult, first and second larvae life stages. In addition, Providencia, Vagococcus, Lactococcus, and Leuconostoc prevailed as main genera detected in L. sericata life stages 33 . Lactococcus was previously reported as being associated with L. sericata 11,36 , while in our study it was among the top ten genera in the insect and liver samples, constituting a shared taxon for the adult, larva, pupa and liver samples. Lactococcus has a homofermentative metabolism 53 , while Leuconostoc is a heterofermentative bacteria 54 , their presence being associated with the fermentative phase of decomposition. Furthermore, Providencia was previously associated with insects 55 , being considered as an opportunistic human pathogen, similar to Vagococcus 56 . www.nature.com/scientificreports/ Regarding the investigated life stages, several authors researched the eggs from the first and second generation, third instar larvae, pupa and first-generation adult 33 . Others studied the first and second instars, male and female specimens, and the digestive tract of the third instar larvae 11 , as well as the internal and external contents of the third instar larvae. These type of studies revealed via culture-based bacteriological method that more bacterial species were present in the third instar larvae after feeding, opposite to the unfed specimens, with a three to seven ratio, respectively 11 , but also that the larvae external content presented significant higher Enterobacteria abundances. Simultaneously, the same study showed that several bacteria genera, such as Enterococcus faecalis and Proteus spp., were present in most of L. sericata life stages, having transstadial and transovarial transmission routes 11 . Our data revealed Lactobacillus dominated in the adult and larvae stages being present in all investigated life stages.
In terms of pathogen introduction in an experimental model, a study of bacterial transmigration emphasized that the inoculation of mouse bodies with Staphylococcus aureus did not affect the overall microbial diversity pattern 22 , not even in organisms that have been sterilized on the surface. However, even if our data showed a similar trend, it is of note that both the inoculated substrate and L. sericata life stages that fed on it were investigated, unlike the previous research that limited the access of invertebrate decomposers 22 . This aspect is very important, since it is known that the insect presence can have an influence on the microbial composition of the feeding substrate. Concerning the blowfly's ability to perform the microbiome exchange in and from the living environment, carrying and transmitting pathogens, was demonstrated by the same microbial patterns identified both in flies and the feces of sympatric animals 9 . Additionally, during the decomposed tissue pre-digestion, blowflies secrete certain enzymes that have antimicrobial actions, thus having the potential to alter the microbial pattern of the substrate 36,57 . These excretions/secretions (ES) with antimicrobial properties can be one of the reasons why many of the bacteria identified in the liver samples were not transferred to the insect specimens. However, the interaction between S. enterica and L. sericata life stages and liver samples must be considered, as these interactions can play a role in the bacterial acquisition and transmission 58 . www.nature.com/scientificreports/ As revealed from the present and past studies, flies can contain numerous pathogens of human and veterinary importance, such as Enterococcus, Streptococcus, Pseudomonas, Proteus, and Serratia 9 . All of these genera comprise numerous species, that can cause different infections in animals and humans, from minor illnesses to deadly diseases, such as the streptococcal toxic shock syndrome 59 . Some species are present in the gastrointestinal tract of healthy people, such as Enterococcus species, but they are also the cause of severe nosocomial infections in hospitalized patients, being inherently resistant to various antibiotics 60 . These infections often target people who are hospitalized or have a compromised immune system, but the infection in healthy individuals can also occur through the consumption of contaminated food or water 61 . Staphylococcus, another bacterium with pathological significance, was detected only in the wild adults and teneral specimens with relative abundance values ranging from 9.6 up to 16.18%, data observed in other research where the values were higher in adults than in the larval stage 33 . Among all identified pathogens, Salmonella spp. exhibited low abundances of 0.01% in the investigated blowflies and in the initial feeding substrate, assuming that the presence of larvae caused an increase in the substrate abundance of up to 2.01% 36 . Our data could support this statement, given that an increase in the liver bacterial abundance corresponded to an increased S. enterica value in the third larvae stage.
Considering all these aspects, the identification of these possible bacterial pathogens in different insect species is very important, in order to monitor their transfer in both invertebrates and humans' living environments. However, the living environment must be also examined, as most studies investigated only the fly bacterial content, and as has been demonstrated so far 36 , L. sericata microbiome is thoroughly connected to the feeding substrate represented by the decomposed organic matter. As such, an increase in abundance of several pathogenic bacteria in the liver samples, identified at the same time in lower abundance in the insect samples, could suggest that the feeding substrate abundances were increased by the feeding larvae 36 . In addition, the experimental introduction of a potential "disturbing" element, as the inoculation of the feeding substrate with S. enterica, could bring new and interesting information about the overall microbiome structure. Moreover, by studying the transmission of these pathogens and the environment of the serovars, that can be represented by the gastro-intestinal tract of humans, farm animals, reptiles, birds, and insects, we can have a better understanding on the dispersal of these microorganisms.
Regardless of the acquired pathogens throughout their lifetime, the fly's microbiome can provide useful data during forensic studies regarding the presence or even the development stage of the insects present on the body, since it was not influenced by the artificial introduction of a specific bacterial taxa. Nevertheless, other pathogens (with increased antibiotic resistance) must be tested to see if their presence alters the microbiome structure during the different development stages of various necrophagous insect species.

Material and methods
Experimental setup. The hypothesis of this study relied on the blowfly's potential of transmitting pathogens and on their role as main colonizers of decomposed human remains. Thus, the quantitative transmission of Salmonella enterica subsp. enterica serovar Typhimurium ATCC 14028 through one generation of L. sericata life stages (adult to teneral specimens) was investigated, as well as the dynamics within the inoculated feeding www.nature.com/scientificreports/ substrate (swine liver) via qPCR. Moreover, for an in-depth investigation of the pathogen impact and bacterial putative role as PMI estimators, both insect and liver microbiome were investigated via 16S rRNA gene Illumina MiSeq sequencing (Fig. 9).
Lucilia sericata sampling and laboratory rearing. Lucilia sericata adults were collected from an urban area of Bucharest (Romania) (N 44° 26′ 49.349′′ E 26° 2′ 45.352′′) during August 2019. Liver tissue was used as bait and the adult sampling was performed via entomological net. Further, the specimens were immediately transferred to a 46 cm rearing cage (BioQuip Products, Rancho Dominguez, CA, USA), transported to the laboratory and reared under constant laboratory conditions (25 °C ± 1 and 60% relative humidity, LD 13:11) (Fig. 9). The species has been taxonomically identified and genetically confirmed. Adult specimens were subsequently transferred to nine sterilized rearing jars, 21 × 12 cm (BioQuip Products, Rancho Dominguez, CA, USA). Each rearing jar contained 300 g of swine liver. Three jars contained liver without S. enterica, three contained liver inoculated with 10 2 CFU/ml S. enterica, while the last three contained liver inoculated with 10 4 CFU/ml S. enterica. Under these conditions the adult specimens were allowed to feed for three hours and to lay egg clusters. After feeding, they were immediately collected and preserved in 200 µl Tris-EDTA pH 8 (TE) buffer at − 20 °C until further investigations. Under aseptic conditions, using a microbiological safety cabinet, and sterilized rearing jars, the egg clusters (one egg cluster/rearing jar) were transferred on the liver containing the same S. enterica concentrations, and monitored under constant laboratory conditions (25 °C ± 1 and 60% relative humidity, LD 13:11) (Fig. 9).
All experimental steps (rearing, transfer, isolation, inoculation, molecular assays) were performed under aseptic conditions to avoid any microbial cross contamination.
Bacterial cultivation and inoculation. Salmonella enterica subsp. enterica serovar Typhimurium ATCC 14028 was cultivated in BHI broth (Brain Heart Infusion-Merck, Darmstadt, Germany) at 37 °C in aerobic conditions. Fresh over-night culture was washed two times and resuspended in sterile saline buffer. Dilutions of 10 2 CFU/ml and 10 4 CFU/ml were obtained. The bacterial concentrations were obtained by serial dilutions (1/10) of the over-night culture (washed and resuspended in sterile saline buffer) with sterile saline buffer.
Samples of 1 ml of the dilutions were inoculated on the entire surface of each liver and the feeding substrates were incubated for two hours at room temperature for colonization. The liver surface was inoculated by five consecutive times with 200 µl bacterial culture of appropriate concentration (10 2 or 10 4 ) using a sterile cotton swab. The bacterial concentration was measured by CFU counting per ml. From previous experiments and determinations, the concentration of the fresh, over-night culture of Salmonella enterica subsp. enterica serovar Typhimurium ATCC 14028 was predictable, consequently, the desired inoculants were obtained by appropriate dilutions. To confirm the prospective results, the CFU/ml was determined for each inoculum by spreading 100 µl of serial dilutions onto solid BHI medium (BHI supplemented with 1.5% (w/v) agar), followed by incubation at 37 °C until colonies were observed. To calculate the number of CFU/ml, the number of colony forming units on the countable plate was multiplied by 10 (100 µl to ml) × 10 the dilution of the sample . The results confirmed the expected bacterial concentrations. Salmonella enterica quantitative PCR assays. Control adults and liver samples were tested for the presence of Salmonella via PCR amplification and no bacteria could be identified. Salmonella enterica quantification from the insect specimens and liver tissues was carried out using Sal_enterF/Sal_enterR (5′-AGC GTA CTG GAA AGG GAA AG-3′; 5′-ATA CCG CCA ATA AAG TTC ACA AAG -3′) specific primers 62 . The primers were selected given their capability to detect up to 329 Salmonella isolates, belonging to all subspecies of S. enterica 62 . For the qPCR assays the total DNA was extracted from the liver and insect samples as previously described.
Thermo Scientific Maxima SYBR Green (1×) Master Mix (ThermoFisher Scientific) reagents were used for the investigation in a total volume of 10 µl, containing 10 µM of each forward and reverse primer, 200 ng DNA template and nuclease free water. All reaction components were thawed and kept on ice, while the entire procedure was performed under a microbiological safety cabinet.
The qPCR amplifications were carried out using a Mastercycler ep gradient S thermocycler PCR (Eppendorf, Wien, Austria) and protocol: initial incubation step of 10 min at 95 °C followed by 40 cycles of 15 s at 95 °C, 30 s at 47 °C, and 30 s at 72 °C. A melting curve analysis was included at the end of each program, being used as amplification control.
Quantification was performed by interpolation in a standard regression curve of cycle threshold (Ct) values generated from samples of known concentration of DNA and plotted as C t versus log 10 (ng DNA/reaction) and considered when R 2 > 0.99. Standard curve was generated using corresponding PCR amplified DNA fragments from the known pure culture of S. enterica.
The DNA decimal dilutions series used for the standard curve ranged between 5.8 × 10 -2 and 5.8 × 10 -9 ng/ μl. Samples were run in triplicate, with a Ct threshold value over 35 not considered, while no-template controls were included in all PCR runs.
The gene copy number per reaction was calculated according to Staroscik 63 : Copy number = (ng DNA × 6.023 × 10 23 )/(length × 1 × 10 9 × 650), and the plot was performed between the logarithmic scale (base 10) of copy gene number and the sampling points.
16S rRNA gene Illumina sequencing and data analysis. The concentration of the total genomic DNA from the liver tissue and insects was measured with Qubit fluorometer (ThermoFisher Scientific). The primer pair 341F/805R 64 was used for the PCR amplification of the 16S rRNA gene fragments (V3-V4 variable region) (McGill University and Génome Québec Innovation Centre, Canada). The amplicons pooled in equal concentrations were sequenced at the McGill University and Génome Québec Innovation Centre via Illumina MiSeq PE300 sequencing platform.
Taxonomic assignment of the ASVs was performed using the Silva v138 16S rRNA database. The community analysis was performed in R environment with the phyloseq and MicrobiomeSeq packages 66 . The sequencing depth varied between 601 and 729.269 sequences per sample with a median of 120,703 sequences. The final dataset consisted of a total of 2798 ASVs from 96 samples. The raw data were deposited in the NCBI SRA Sequence Read Archive under the BioProject: PRJNA646601.
Alpha-diversity was used to evaluate the diversity differences at the ASVs level using Shannon's diversity index, and significant differences were evaluated using t-tests 67,68 . Principal coordinate analysis (PCoA) based on Bray-Curtis dissimilarities 69 was used to assess the beta diversity. PERMANOVA and ANOSIM tests were performed in MicrobiomeAnalyst platform 67,68 to determine statistical differences between a priori groups. Microbial community profiles of the variable V3/V4 region of the 16S rRNA gene sequences and graphical visualization were conducted using MicrobiomeAnalyst 67 with the parameters for counter filters = 4, prevalence in samples = 20%, and inter-quartile variance filter percentage to remove = 10%. Data were normalized using the Total Sum Scaling (TSS) method 67 . Additional statistical analysis was performed using R version 3.6.3 70 , to investigate statistical differences among treatments using a two-way ANOVA, followed by the Tukey multiple comparison test a posteriori using the package dplyr 71 .
Venn diagram of all identified genera was generated using the Bioinformatics and Evolutionary Genomics online calculator 72