A New Technique for Use in Culturing Prokaryotes Comprising the Mouse Intestinal Microbiome ()
1. Introduction
The gastrointestinal (GI) tract of multicellular eukaryotic organisms contains an assortment of diverse microbes and their associated genes, which is defined as the microbiome [1] . Within this system, the GI tract is extremely dynamic due to the interactions between the host and the microbes [2] . The dynamic nature of the GI tract is further confounded by the fact that it does not contain a uniform level of oxygen, temperature, or pH throughout [2] [3] . As a result of the robust variability of the GI tract, the microbiome is known to be highly specific, highly transient, and highly variable between individual organisms [4] [5] . Although the host’s core microbiome is relatively stable [6] , there are many transient microbial species due to variations in age, diet, or health that differ from host to host [5] [7] [8] .
The microbiome forms a symbiotic relationship with its host, and impacts metabolism, response to nutrients, and physiological and immunological development [9] . Essentially, microbes have a cooperative role in the GI tract and contribute to a host’s immune system and metabolism [10] [11] [12] [13] with Firmicutes and Bacteroidetes being the predominant Gram-positive and Gram-negative phyla, respectively [9] . Although the natural relationship between the microbiome and the host is essential, overpopulation by an undesirable species, or dysbiosis, has been linked to particular diseases and phenomena such as autism spectrum disorder [14] , cancer [11] , and obesity [15] .
Research is needed to investigate the interactions of the microorganisms of the microbiome and how various stimuli affect them, but many of the species cannot persist in culture [16] [17] . Therefore, most research currently relies on germ-free mice for microbiome studies, which can be cost-prohibitive for many laboratories [15] [18] . One consideration worth noting is the financial burden of raising, sacrificing, and housing vertebrate animals; therefore, it would be beneficial to develop techniques to save organisms and further decrease costs. To begin assessing the transient mixture of microbiota [19] , scientists have been utilizing culture-independent, massively parallel sequencing to inquire about shifts within the microbiome and what stimuli affect these changes in composition [20] . With the decreasing cost of DNA sequencing, an influx of research has been possible in this area [21] , however, there are still limitations to using strictly genomic sequencing so the culturing of organisms from the microbiome would still be beneficial. In this study, we adapted a 3D culture model from eukaryotic cell culture systems [22] [23] to culture and maintain prokaryotic cultures from the GI microbiomes of four laboratory-bred female Balb/c mice in three-dimensional (3D) well plates, placed into 2 oxygen levels. The distal colons of the mice were homogenized and added to culture air-lift transwell systems with standard cell culture media and incubated for 24 hours to determine viability and microbiome stability. Due to the variable nature of the oxygen levels of the GI tract [3] , we cultured 3D plates in both a conventional incubator and an anaerobic chamber, both at 37 degrees Celsius. Additionally, we attempted to determine the microbial composition of the mouse stool and the distal colon to observe if future studies may utilize feces and avoid sacrificing organisms altogether. We employed massively parallel DNA sequencing to verify final proportional community composition of each sample.
2. Materials and Methods
2.1. Mice
The study was performed under a protocol approved by the Tarleton State University Institutional Animal Care and Usage Committee (Animal Use Protocol 12-009-2016-A1). Four Balb/c females 8 weeks in age were utilized in this experiment. Females were housed together and raised on similar chow diets and similarly weaned. Mice 1 and 2 were siblings while mice 3 and 4 were siblings. All mice were euthanized with 150 microliters of sodium pentobarbital delivered intraperitoneally. Post injection, mice shed two to three samples of stool which were recovered utilizing sterile forceps and immediately frozen. Once deceased, 2.5 cm of the large distal colon from each mouse was removed. After, two small additional 0.5 cm samples of the large distal colon were excised from the specimen and immediately frozen. Colon tissue extractions were added to a sterile tissue grinder along with 5 mL of Dulbecco’s Modified Eagle Medium (DMEM; VWR, Radnor, PA). The sample was manually homogenized into a liquid solution.
2.2. Culture Methods
Hydrogel (Corning, Corning, NY) was prepared using 8 mL of molecular grade water and 20 microliters of hydrogel to create a 0.25% solution. 150 microliters of the prepared solution were added to 6.5 mm transwell inserts (n = 8; Corning, Corning, NY) that were placed into a 24 well tissue culture plate (Corning, Corning, NY). In addition, 500 microliters of supplementary Dulbecco’s Modified Eagle Medium (DMEM) was added under each well insert. Once the culture plates were prepared, 250 microliters of the homogenized colon were added to the top of the hydrogel in the transwell inserts [22] [23] . Plates were checked for baseline pH by transferring a small drop of medium with a mechanical pipette onto litmus paper. The plates were then added to a single incubator, but to create an anoxic environment, plates were incubated in an anaerobic system (BD Diagnostics, Franklin Lakes, NY). Plates were incubated for 24 hours. The medium below each insert was again tested for pH again and the culture was transferred into sterile 2.5 mL storage tubes and frozen for future DNA extraction.
2.3. DNA Extraction and Library Production
DNA was extracted from each sample using a modified protocol from Brady et al. [24] . After extraction, DNA was amplified utilizing prokaryote specific primers, 519F 5’-CAGCMGCCGCGGTAA-3’) and 785R (5’-TACNVGGGTATCTAATCC-3’), that target the V4 region of the 16S rRNA [25] [26] . PCR amplification was accomplished through denaturation at 95˚C for 3 minutes, followed by 35 cycles of 95˚C for 10 seconds, 55˚C for 30 seconds, and 72˚C for 30 seconds. DNA barcodes were added to samples with 10 cycles of the same PCR protocol. To prevent inhibition during PCR, samples underwent an additional cleanup with 20% Chelex 100. Sequences were size-selected with a Pippin Prep instrument (Sage Science, Beverly, MA) to a length of 300 - 600 base pairs. Sequencing was conducted on the Illumina MiSeq platform using 600 cycle paired end v3 sequencing kits at the Texas A&M University Genomics Core Facility. Raw sequences were processed through QIIME [27] and USEARCH [28] . Taxonomy was assigned using Greengenes 13.8 database [29] as a reference with UCLUST [28] , and OTU picking was conducted at 97% sequence similarity with the RDP [30] method in QIIME.
The microbes from four mouse distal colons were cultured in 12 cell culture lift inserts in a 24 well plate system. Additionally, a total of 9 fecal and 9 colon samples distributed across 4 mice were prepared for DNA extraction. Due limited spacing in the 96 well plate DNA extraction method, only one colon and fecal sample could be performed in triplicate, and it was randomly selected to be mouse 3.
2.4. Statistical Analysis
Cumulative sum scaling was used to normalize the data and account for uneven sequencing depth between samples [31] . Biom files were constructed through QIIME and transferred into R [32] for further statistical analysis. Phyloseq [33] , ggplot2 [34] , and vegan [35] packages were utilized to evaluate alpha and beta diversity with seed set at 1400. Alpha diversity was assessed using the Shannon diversity index. Variation in alpha diversity for oxygen, pH, mouse, feces, and colon comparisons were first checked for normality using the Shapiro-Wilk test for normality [36] . The data was non-normal in distribution (Shapiro-Wilk test, w = 0.9506, p < 0.01); therefore, comparisons were made with non-parametric tests. All multivariate tests were corrected using false discovery rate (FDR) [31] . Comparisons of alpha diversity were assessed using Kruskal Wallis one-way analysis of variance (KW ANOVA) or Wilcoxon rank sums test (Wilcoxon test) while comparisons of beta diversity were assessed with unweighted unifrac distance metrics at 1000 permutations using permutational multivariate analysis of variance (PERMANOVA). Dunn’s test post-hoc analysis was done through the dunn.test package in R [37] . In addition, non-parametric t-tests were used for comparisons of mean abundance in individual bacterial strains between samples. A microbial network was constructed using the Co-occurrence Network Interferences (CoNet) application for Cytoscape [38] . Feces and colon data were removed before CoNet analysis. CoNet has been utilized in previous studies to investigate defined interactions between microbes [39] [40] . Spearman correlation coefficient with a cutoff ratio of 0.6 was utilized, and to focus the network, only microbes with sequence counts greater or equal to 20 were included. 1000 permutations were accomplished through a bootstrapping method with an FDR correction [40] .
3. Results
3.1. pH and Oxygen
pH readings of each plate were taken before and after incubation. As shown in Table 1, pH fluctuated from the original baseline of 8. In addition, mice maintained varying levels of pH due to differences in oxygen concentration (Table 1). Sample sizes are uneven due to losses during cleanup or DNA extractions.
3.2. Fecal and Colon Comparison
After quality filtering, we had a total sample size of 111 samples and 3,133,666 sequences total (Supplemental Table S1). The sequence files were submitted to the National Center for Biotechnology Information (NCBI) database (Supplemental Table S2). The profile of the feces and the colon were characterized for microbial composition at the phylum (Figure 1(A)) and family (Figure 1(B)) levels. There was some variation between samples, even within the same mouse, but the core phylum composition of the colon and fecal samples was dominated by Firmicutes and Bacteroidetes (Figure 1(A)), with means of 47% and 49%, respectively, and standard deviations (SD) of 23%. In addition, the family S24-7 (order Bacteroidales) was highly abundant in all samples with a mean of 42% and a SD of 20% (Figure 1(B)). Analysis of beta diversity for each of the feces and colon samples revealed no difference in composition (Supplemental Table S3), and analysis of alpha (Shannon) diversity (Figure 1(C)) also revealed no difference (KW ANOVA P = 0.47). Therefore, samples were pooled together for comparison between feces and colon. Shannon diversity index was utilized for comparison of the bulk samples (Figure 1(D)). Results showed no difference
![]()
Table 1. pH and oxygen level per sample.
between the pooled feces and colon samples (Wilcoxon test, P = 0.44). In addition, beta diversity comparison of pooled samples showed no difference (data not shown, PERMANOVA, pseudo-F = 1.06, P = 0.37). Since it was determined that feces and colon samples are similar, all samples were pooled into one bulk sample, named “pooled microbiome”, for diversity comparisons with cultured prokaryotes.
3.3. Microbiome Comparison
In the cultured samples with 24-hour incubation, Firmicutes and Bacteroidetes were the dominant phyla (Figure 2(A)). Firmicutes had the highest average relative abundance, 70% (SD 28%), with Bacteroidetes averaging 18% (SD 16%). Mice 1 and 2 exhibited more species richness in the cultures than mice 3 and 4 at the phylum level (Figure 2(A)). Across all cultures, the impacts of oxygen levels were not evident at the phylum level (Figure 2(A)), at the genus level differences were observed in transient genera (data not shown), although these differences were not significant (Figure 2(B)). Shannon diversity index shows a difference between some of the cultures and the colon and fecal microbiome of the mice (KW ANOVA, Dunn’s test, Figure 2(B)). Post-hoc analysis shows that, compared to the microbiome, mouse cultures 1 and 2 were statistically similar to the pooled microbiome from colon and fecal isolates while mouse cultures 3 and 4 differed significantly (Supplemental Table S4, Figure 2(B)).
![]()
(A)![]()
(B)
Figure 2. Community composition of cultures and comparison of pooled microbiome. Cultured prokaryotes from mice (M) at 0 or 20% oxygen tolerance have few differences in relative abundance at the phylum (A) level, with observations less than 1% pooled into “Other” category. Post-hoc, Shannon Diversity, pairwise comparison between cultured samples and the pooled colon microbiome (B) demonstrated that mice 1 and 2 are more representative than mice 3 and 4, P < 0.05 is noted by “*”, P < 0.0001 is noted by “****”, and non-significance is noted by “ns.”
3.4. Environmental Variables
A community profile of cultural composition due to varying levels of oxygen and pH exposure was constructed (Figures 3(A)-(D)). The cultures were placed overnight into aerobic (20%) or anoxic (0%) conditions, and the dominant bacteria in the cultures produced pH shifts. The overnight culture of colon samples from mice 3 and 4 resulted in a final pH between 6 - 7 (Table 1) and the cultures are dominated by Firmicutes and Bacteroidetes with few transient phyla (Figure 3(A)). The overnight incubation of the cultures from mice 1 and 2 resulted in a higher final pH (9 - 10; Table 1) which resulted in more observed phyla (Figure 3(A)), and these cultures were more representative of the in vivo microbiome (Figure 2(B)). Comparison of Shannon diversity revealed that variation in pH led to significant differences in alpha diversity (KW ANOVA, Dunn’s test). Post-hoc
analysis revealed that plates reaching a pH of 6 and 7 were similar while all other comparisons differed (Figure 3(B)). Analysis of beta diversity also revealed differences in prokaryotic communities between plates of varying pH levels (Supplemental Table S5).
When samples cultured at identical oxygen concentration were pooled together, no difference in alpha diversity existed between the two oxygen levels among genera (Wilcoxon test, P = 0.34; Figure 3(C), Figure 3(D). However, shifts in the individual mice can be noted, especially with between the two oxygen concentrations. Additionally, distance-based linear modeling revealed that oxygen did not contribute significantly to community clustering (Supplemental Table S6).
3.5. Siblings
Mice 1 and 2 were a sibling pair. Mice 3 and 4 were a sibling pair. A marked difference in prokaryote cultural composition was noted by familial relationship (Supplemental Table S7, Figure 4, Figure 5(A), Figure 5(B)). Mice 1 and 2 had greater diversity in their cultures than mice 3 and 4 (Figure 5(A)). Mouse 1 had much higher Lactobacillus, HA73 (Phylum Synergistetes), and Ruminofilibacter than mice 3 and 4 (Figure 5(B)) and mouse 2 had even more diversity with increases in the genus Clostridium (Figure 5(B)). Sibling relationship explains the changes in community composition as time elapsed in the incubators (Supplemental Table S6). Distance-based linear modeling indicated pH, individual mouse, and sibling effects all significantly contributed to microbial community variation when considered independently (P < 0.001), accounting for 20%, 18%, and 22% of the variation, respectively, while oxygen level did not impact the microbiota (Supplemental Table S6). However, when these variables were considered together, a most parsimonious model containing individual
![]()
Figure 4. CCA for the effects of pH, oxygen, and sibling relationship on community structuring. Data was first square-root transformed and then ordinated by Bray-Curtis distance metric.
mouse and sibling relationship accounted for 29.0% of the variation while pH did not contribute to explaining microbial variation if individual mouse and sibling relationship were already in the model. Additionally, Shannon diversity significantly varied between sibling groups (KW ANOVA, P < 0.01). Post-hoc analysis showed mouse 1 and mouse 2 were similar and varied from mouse 3 and mouse 4, which were also similar (Dunn’s test, Supplemental Table S4 and Figure 5(C)). Additionally, beta diversity varied according to familial relationship (PERMANOVA, P < 0.01).
3.6. Microbial Network
The OTUs in the microbial network represent 88% of the relative sequence count for the cultured well plates (Figure 6). Many of the interactions were positive in
![]()
(A)![]()
(B)![]()
(C)
Figure 5. Microbial composition by mouse. Relative abundance of bacteria phyla (A) and genera (B). Observations less than 0.03% are pooled into “Other” category. (C) Shannon diversity index comparison using mouse 2 as a reference group. “****” means significant at P < 0.0001 while “ns” means non-significant.
![]()
Figure 6. Microbial network generated using Spearman’s rank correlation at the taxonomic level of genus. Most of the edges, 54 of 58, are of a positive correlation. The rest are negative.
nature meaning co-presence in a shared-niche is the most abundant interaction type. Negative, mutually exclusive interactions are only between the microbial genus Enterococcus and an unclassified strain of Bacteroidales (Figure 5). The interaction between the 4 mutually exclusive OTUs account for 50% of all sequences. Enterococcus species were more well represented in the cultured samples than the colon and fecal samples (“pooled microbiome”), especially in cultures from mice 3 and 4 (Figure 7(A); Supplemental Table S8), which had the lower pH (Table 1, Figure 7(B)). The low pH of these cultures may be influenced by an increase in Lactobacillus (Figure 7(C)). The increase in Enterococcus and Lactobacillus in mice 3 and 4 resulted in a decline in genera from the phylum Proteobacteria (Figure 7(D), Supplemental Table S9). Although perhaps not proportional to the in vivo colonic microbiome, most representative
prokaryotes, including the hard to grow Archaea (Figure 7(E)) and Clostridium (Figure 7(F)) were isolated from these cultures. The addition of the chemical propidium monoazide (PMA) to the preparations indicated that the cultures were not just present, but also alive, as no significant differences were observed with or without PMA treatment at the level of family (Figure 8(A)). To conclude, the stability of the cultures was confirmed when a plate of eight transwells were frozen for one month at −80˚C, and again there were no statistically significant changes in the cultures at the level of family (Figure 8(B)).
4. Discussion
Current studies of the microbiome utilize germ-free mice, which are expensive to house and breed [20] . In this study, we attempted to culture a representative population of prokaryotes from the distal colon in 3D transwell culture plates to allow for an alternative for product testing prior to the germ-free animals. We found that oxygen level had little impact, but ultimately the population of microbes at the initiation of cultures, which contributes to the stability of pH, impacted the ability to culture (Figure 2, Figure 3). Cultures for mouse 1 and 2 were comparable in alpha diversity to the microbial population of the colon and feces (Supplemental Table S4, Supplemental Table S5, Figure 2(B)), which is very promising, and these microbes produced a pH of 9 - 10 when cultured (Table 1).
![]()
(A)![]()
(B)
Figure 8. Taxa summary plots compiled. The cultures from the mice were subjected to treatment with PMA (A) or were frozen (B) to determine culture stability. There is no statistical difference between either of these comparisons.
These cultures contained a high percentage of Bacteroidetes and Firmicutes (Figure 2(A)), which is consistent with recent data on the colon microbe populations in mammals [9] [41] [42] [43] , along with some other minor phyla (Figure 2(A)). Some factors, most likely bacterial, caused the pH of the cultures from mice 3 and 4 to decline from baseline to 6 - 7 (Table 1). This low pH dramatically altered the cultures obtained from the colon samples of these animals (Figure 2, Figure 3), and they were less consistent with the normal GI microflora of animals [42] . The cultures from mice 3 and 4 were predominantly Firmicutes, with a smaller percentage of Bacteroidetes.
Although oxygen did not specifically result in significant changes when observed collectively (Figure 3(C), Figure 3(D)), it may have been a factor influencing the pH (Table 1). There were different microbes present in the 0% and 20% cultures, and these microbes likely caused a pH shift. For example, Lactobacillus, a lactic acid producing bacterial genus, increased in the pH 6 cultures (Figure 7(C)), which appeared to be a result of the mice 3 and 4 colon extracts being incubated in the absence of oxygen (Table 1). Lactobacillus spp. has been shown to grow better in anaerobic conditions [44] , leading to increased lactic acid production and lower pH. Lactobacillus has also been shown to be present in commercially-available mouse food, and thus feeding selection may impact its presence or absence in the gastrointestinal microbiome [9] . The presence of oxygen also likely affected species from the genus Enterococcus as it significantly increased between mice cultures and the pooled microbiome, especially those with a lower pH (Figure 7(A), Figure 7(B); Supplemental Table S9). The upsurge of bacteria from the Enterococcus genus likely minimized the role of oxygen in incubating these fecal anaerobes. Enterococcus is a facultative anaerobe [45] ; therefore, since it is a known pioneer colonizer of the GI tract, its presence possibly established the anoxic environment [46] . The presence of oxygen also likely led to the increase in Proteobacteria, as these organisms are often amenable to laboratory culture, and likely have a preference for the incubator (Figure 2(A), Figure 7(D)). However, they did appear to be repressed in the lower pH range (Figure 3(A), Figure 7(D)), and their presence may have been a factor that contributed to the shift from the distal colon physiological pH of 6.6 - 6.9 [47] to that of 9 - 10. The metabolism of proteins to release amine groups by species of this phylum perhaps led to the increase in pH in these cultures [48] . pH was a strong influence in the growth of Archaea. Few Archaea were observed in the cultures, but those detected grew more readily in plates with a higher pH (Supplemental Table S9, Figure 7(E)). Not only are Archaea difficult to culture, but also their diversity is not well studied in regard to the gut microbiome [49] , making this system a potentially advantageous method to understand their role in the GI tract.
Microbiome acquisition is passed on from mother to litter [18] [50] . Our microbiome cultures were highly impacted by familial relationships (Supplemental Table S7). One such example was that the mice differed in the amount of Clostridium cultured. Sibling pair mice 1 and 2 had more numerous strains of Clostridium than sibling pair mice 3 and 4 (Supplemental Table S10, Figure 7(F)). Not only were these mice siblings but were also weaned by different mothers. The effects of weaning are similar to Bian et al. wherein the abundance of species from the family Clostridiaceae was affected by the nursing mother [51] . Our result not only solidifies the impact of the mother on the microbiome, but also shows this dynamic still occurs even explanted from the source.
Ultimately, we showed that the feces and large distal colon are highly similar; therefore, future experiments may avoid sacrificing mice by culturing feces. Future experiments will need to control for pH to acquire the highest amount of diversity possible, and perhaps use a mixed fecal source to avoid sibling biases. Since none of the plates maintained the original baseline pH, using a biological buffer may create a closer replica of the microbiome. Even without additional measures for controlling media pH, we have succeeded in creating a method to culture bacteria of the microbiome that are difficult to culture. Ultimately, this study found that pH was a stronger influencer of community composition than oxygen, but it seems as though the oxygen levels led to a proliferation of certain microbes that impacted pH. The microbes in culture impacted the pH of the media, and future goals would be to establish a physiological pH by maintaining the correct proportions of microbes. The use of an anaerobic chamber during necropsy and culture would have likely aided the survival rate of more strict anaerobes, and perhaps limited the Proteobacteria. Additionally, the use of different matrices that might produce a more solidified platform than hydrogel might create more of an anaerobic niche to prevent loss of organisms like the Bacteroidetes, which are mostly strict anaerobes [52] .
Ultimately, our culture mimic of the distal colon microbiome did not maintain the full proportions of microbes, but we were able to culture a majority of the prokaryotes of the GI microbiome providing a collection of a diverse number of prokaryotic strains for microbiome analysis. Optimizing efforts in culture media, matrices, fecal extraction, and atmospheric gradients is extremely important in culturing all desired microbes [53] . However, even with this preliminary study, we were able to culture a majority of the prokaryotic microbes of the GI tract, including very-difficult-to-culture strains, for example, Methanobacteria [54] , mean of 0.57 (SD 4.31) (Figure 7(E)).
Acknowledgements
We would like to thank the staff at Texas A&M AgriLife Research and Extension Center for aiding in the project, the Tarleton State University Office of Student Research and Creative Activities, and the College of Science and Technology for funding this research, and the Tarleton State University College of Graduate Studies for the assistantship for Mr. Castaneda.
Supplemental Table
Supplemental Table S1. Sequence count per mouse.
Supplemental Table S2. NCBI database submissions.
Supplemental Table S3. Results of the pairwise PERMANOVA tests.
Supplemental Table S4. Results of the Dunn’s post-hoc test. Pooled microbiome refers to the pooled feces and colon samples for all mice. Comparisons are based on each 12 well plate, incubated in one of two incubators, compared to the microbiome.
Supplemental Table S5. Results of the pairwise PERMANOVA test.
Supplemental Table S6. Hypothesis testing for sources of variation by distance-based linear modeling. Abbreviations: df, degrees of freedom; SS, sum of squares; Prop, proportion of variation.
Supplemental Table S7. Results of Dunn’s test for each mouse comparison.
Supplemental Table S8. Results of the comparison of Enterococcus between plates and the pooled microbiome. Results generated from a non-parametric t-test using 1000 permutations.
Supplemental Table S9. Results of the comparison between strains of Proteobacteria, Enterococcus, Lactobacillus, and Archaea between mice. Results generated from a non-parametric t-test using 1000 permutations.
Supplemental Table S10. Results of the comparison. Results generated from a non-parametric t-test using 1000 permutations.
NOTES
*First author.
#Corresponding author.