Described here is a protocol to investigate the interactions between endobiotics and human gut microbiota using in vitro batch fermentation systems.
Cite this ArticleCopy Citation | Download Citations | Reprints and Permissions
Hu, Y., Chen, H., Li, P., Li, B., Cao, L., Zhao, C., Gu, Q., Yin, Y. Analysis of Interactions between Endobiotics and Human Gut Microbiota Using In Vitro Bath Fermentation Systems. J. Vis. Exp. (150), e59725, doi:10.3791/59725 (2019).
Translate text to:
Human intestinal microorganisms have recently become an important target of research in promoting human health and preventing diseases. Consequently, investigations of interactions between endobiotics (e.g., drugs and prebiotics) and gut microbiota have become an important research topic. However, in vivo experiments with human volunteers are not ideal for such studies due to bioethics and economic constraints. As a result, animal models have been used to evaluate these interactions in vivo. Nevertheless, animal model studies are still limited by bioethics considerations, in addition to differing compositions and diversities of microbiota in animals vs. humans. An alternative research strategy is the use of batch fermentation experiments that allow evaluation of the interactions between endobiotics and gut microbiota in vitro. To evaluate this strategy, bifidobacterial (Bif) exopolysaccharides (EPS) were used as a representative xenobiotic. Then, the interactions between Bif EPS and human gut microbiota were investigated using several methods such as thin-layer chromatography (TLC), bacterial community compositional analysis with 16S rRNA gene high-throughput sequencing, and gas chromatography of short-chain fatty acids (SCFAs). Presented here is a protocol to investigate the interactions between endobiotics and human gut microbiota using in vitro batch fermentation systems. Importantly, this protocol can also be modified to investigate general interactions between other endobiotics and gut microbiota.
Gut microbiota play an important role in the functioning of human intestines and in host health. Consequently, gut microbiota have recently become an important target for disease prevention and therapy1. Moreover, gut bacteria interact with host intestinal cells and regulate fundamental host processes, including metabolic activities, nutrient availabilities, immune system modulation, and even brain function and decision-making2,3. Endobiotics have considerable potential to influence the bacterial composition and diversity of gut microbiota. Thus, interactions between endobiotics and human gut microbiota have attracted increasing research attention4,5,6,7,8,9.
It is difficult to evaluate interactions between endobiotics and human gut microbiota in vivo due to bioethics and economic constraints. For example, experiments investigating the interactions between endobiotics and human gut microbiota cannot be performed without permission of the Food and Drug Administration, and recruitment of volunteers is expensive. Consequently, animal models are often used for such investigations. However, the use of animal models is limited due to different microbiota compositions and diversity in animal- vs. human-associated communities. An alternative in vitro method to explore the interactions between endobiotics and human gut microbiota is through the use of batch culture experiments.
Exopolysaccharides (EPSs) are prebiotics that significantly contribute to the maintenance of human health10. Distinct EPSs that consist of different monosaccharide compositions and structures can exhibit distinct functions. Previous analyses have determined the composition of Bif EPSs, which are the representative xenobiotic targeted in the current study11. However, host-associated metabolic effects have not been considered with regard to EPS composition and diversity.
The protocol described here uses the fecal microbiota from 12 volunteers to ferment Bif EPSs. Thin-layer chromatography (TLC), 16S rRNA gene high-throughput sequencing, and gas chromatography (GC) are then used in combination to investigate the interactions between EPSs and human gut microbiota. Distinct advantages of this protocol compared to in vivo experiments are its low cost and avoidance of interfering effects from the host’s metabolism. Furthermore, the described protocol can be used in other studies that investigate interactions between endobiotics and human gut microbiota.
This protocol follows the guidelines of the ethics committee of Hunan University of Science and Engineering (Hunan, China), and the Zhejiang Gongshang University (Zhejiang, China).
1. Preparation of bacteria
- Preparation of bifidobacterium medium broth
- Combine the following components in 950 mL of distilled water: meat extract, 5 g/L; yeast extract, 5 g/L; casein peptone, 10 g/L; soytone, 5 g/L; glucose, 10 g/L; K2HPO4, 2.04 g/L; MgSO4·7H2O, 0.22 g/L; MnSO4.H20, 0.05 g/L; NaCl, 5 g/L; Tween 80, 1 mL; salt solution, 40 mL (CaCl2.2H2O, 0.25 g/L; KH2PO4, 1 g/L; NaHCO3, 10 g/L; NaCl, 2 g/L); and resazurin, 0.4 mL (2.5 mg/L). Adjust the pH to 6.8 with 2 M NaOH.
- Autoclave at 121 °C for 15 min and allow the broth to cool to room temperature (RT) under anaerobic conditions (10% H2, 10% CO2, 80% N2). Add filter-sterilized cysteine-HCl (0.5 g/L) and mupirocin (5 mg/L) to the medium.
- Add an aliquot (50 μL) of frozen Bifidobacterium longum to a culture tube with 5 mL of bifidobacterium medium broth under anaerobic conditions, then culture in an anaerobic incubator for 24 h at 37 °C.
2. Preparation of bifidobacterial EPSs
- Preparation of PYG agar medium
- Combine the following: peptone, 20 g/L; yeast extract, 10 g/L; glucose, 5 g/L; NaCl, 0.08 g/L; CaCl2, 0.008 g/L; MgSO4·7H2O, 0.008 g/L; K2HPO4, 0.04 g/L; KH2PO4, 0.04 g/L; NaHCO3, 0.4 g/L; agar, 12 g/L. Adjust the pH to 7.2 using 10 M NaOH.
- Autoclave the media at 121 °C for 15 min and cool to ~50 °C. Then, per 1 L of medium, add 0.5 mL of filter-sterilized vitamin K1 solution (1 g of vitamin K1 dissolved in 99 mL of 99% ethanol), 5 mL of haemin solution (0.5 g of haemin dissolved in 1 mL of 1 mol/L NaOH, then brought up to 100 mL with distilled water), and 0.5 g of cysteine-HCl.
- Before pouring the PYG plates, add filter-sterilized 5-bromo-4-chloro-3-indolyl β-D-galactopyranoside (X-Gal, 0.06 g/L), LiCl·3H2O (5.7 g/L) and mupirocin (5 mg/L) to the medium.
NOTE: X-Gal and LiCl.3H2O allow the identification of B. longum colonies on plates via coloration changes.
- Inoculate 20 μL of B. longum strains (step 1.2) to PYG plates and place in an anaerobic incubator at 37 °C for 72 h.
- Collect mucoid bacterial colonies from the PYG plates using a weighing scoop, then completely resuspend in 10 mL of phosphate-buffered saline (PBS) using a vortex oscillator.
NOTE: The bacterial and EPS mixtures should be resuspended completely by vortexing or pipetting up and down repeatedly until the fibers are completely dissolved in PBS.
- Centrifuge the suspension at 6,000 x g for 5 min.
- Carefully transfer the supernatants to a new centrifuge tube and mix completely with three volumes of cold 99% ethanol by repeated inversion and blending.
- Centrifuge the mixture at 6,000 x g for 5 min and completely remove the supernatants.
- Remove the precipitates from the centrifuge tubes by scraping and drying the EPS extracts overnight using a speed vacuum.
3. Preparation of fermentation medium
- Preparation of basic culture medium VI
- Combine the following: peptone, 3 g/L; tryptone, 3 g/L; yeast extract, 4.5 g/L; mucin, 0.5 g/L; bile salts No. 3, 0.4 g/L; NaCl, 4.5 g/L; KCl, 2.5 g/L; MgCl2·6H2O, 4.5 g/L; 1 mL Tween 80; CaCl2.6H2O, 0.2 g/L; KH2PO4, 0.4 g/L; MgSO4·7H2O, 3.0 g/L; MnCl2·4H2O, 0.32 g/L; FeSO4·7H2O, 0.1 g/L; CoSO4·7H2O, 0.18 g/L; CaCl2·2H2O, 0.1 g/L; ZnSO4·7H2O, 0.18 g/L; CuSO4·5H2O, 0.01 g/L; and NiCl2·6H2O, 0.092 g/L. Adjust the pH to 6.5 with 1 M HCl.
- Prepare haemin and cysteine as done in section 2.1 and add after autoclaving and cooling.
- Prepare culture media that contains different carbon sources with a VI base media. Prior to autoclaving, add 8 g/L of Bif EPS fibers to medium VI, comprising group VI_Bif. In addition, add 8 g/L starch to medium VI to represent group VI_Starch. Finally, medium VI without addition of a carbon source is used as the control (group VI).
NOTE: Bif EPS and starch are first dissolved in hot water using a magnetic agitator, then mixed with prepared VI medium.
- Autoclave all media at 121 °C for 15 min and allow to cool to RT.
- Transfer a subsample (5 mL) of each medium to culture tubes in an anaerobic incubator, and store the remaining media at 4 °C.
4. Human fecal sample preparation
- Collect fresh fecal samples immediately following fresh defecation from healthy adult human volunteers using feces containers, and subsequently use for slurry preparation.
NOTE: Prior to sample collection, all the volunteers should be screened to ensure no receiving of antibiotics, probiotics, or prebiotic treatments for at least 3 months prior to donating samples. In addition, all donors must provide informed, written consent.
- Transfer a fresh fecal sample (1 g) to 10 mL of 0.1 M anaerobic PBS (pH 7.0) into glass beakers, then use glass rods to prepare a 10% (w/v) slurry.
- Use a 0.4 mM sieve to filter the fecal slurry. Then, use a subsample of the filtered slurry to inoculate batch culture fermentation experiments, and store the remainder at -80 °C for further analyses.
NOTE: Steps 4.2–4.3 are conducted in an anaerobic chamber.
5. In vitro batch fermentation
- Add filtered fecal slurry (500 μL) to the fermentation medium prepared in step 3.2 within an anaerobic chamber, then incubate at 37 °C.
- Collect 2 mL of fermented samples at 24 h and 48 h in the anaerobic chamber and then centrifuge outside of the chamber at 6,000 x g for 3 min.
- Carefully transfer the supernatants to a new centrifuge tube that will be used for polysaccharide degradation analysis and short-chain fatty acids (SCFAs) measurements.
- Store the centrifugation pellets at -80 °C and subsequently use for bacterial genomic DNA extraction.
6. EPS degradation by human fecal microbiota
- Load 0.2 μL of fermented supernatants onto pre-coated silica gel-60 TLC aluminum plates, then dry using a hair drier.
- Develop the plates in 20 mL of a formic acid/n-butanol/water (6:4:1, v:v:v) solution and dry using a hair drier.
- Soak the plates in the orcinol reagent to dye, then dry using a hair drier.
- Prepare orcinol reagents by dissolving 900 mg of Lichenol in 25 mL of distilled water then adding 375 mL of ethanol. Subsequently, concentrated sulfuric acid should be slowly added and the solution thoroughly mixed.
- Heat plates at 120 °C for 3 min in a baking oven and evaluate degradation of EPS by measuring TLC bands.
7. Effects of EPS on human intestinal microbiota
- Freeze-thaw the original fecal samples prepared in step 4.3 and fermented samples prepared in step 5.4.
- Extract bacterial genomic DNA (gDNA) from all the samples using a stool bacterial genomic DNA extraction kit following the manufacturer’s instructions.
- Determine DNA concentrations, integrities, and size distributions using a micro-spectrophotometer and agar gel electrophoresis.
- Conduct PCR of bacterial 16S rRNA genes from the extracted gDNA using the following previously described forward and reverse primers12:
-forward primer (barcoded primer 338F): ACTCCTACGGGAGGCAGCA
-reverse primer (806R): GGACTACHVGGGTWTCTAAT
Use the following thermal cycler conditions:
- 94 °C for 5 min.
- 94 °C for 30 s.
- 55 °C for 30 s.
- 72 °C for 1 min.
- Repeat 2–4 for 35 cycles
- 72 °C for 5 min.
- 4 °C hold until removal from thermal cycler.
- Conduct high-throughput sequencing of PCR products at a DNA sequencing company using ultra-high throughput microbial community analysis.
- Obtain clean, high quality sequences using the Quantitative Insights into Microbial Ecology (QIIME) sequence analysis pipeline13.
- Define operational taxonomic units (OTUs) for 16S rRNA gene sequences with greater than 97% nucleotide similarity using bioinformatics tools such as the Mothur software suite14.
- Choose a representative sequence from each OTU and use the RDP classifier along with the SILVA taxonomic database to classify representative sequences15.
- Calculate Good’s coverage, alpha diversity metrics (including Simpson and Shannon index), and richness (observed number of OTUs) using bioinformatics tools16.
8. Effects of EPS on SCFA production by human intestinal microbiota
- Add fermented supernatants (1 mL) prepared in step 5.3 to 2 mL centrifuge tubes.
- Add 0.2 mL of 25% (w/v) metaphosphoric acid to each of the samples and thoroughly mix the solutions by vortexing.
- Centrifuge the mixtures at 13,000 x g for 20 min and transfer the supernatants to fresh tubes.
- Concomitantly, prepare solutions of 120 mM acetic, propionic, butyric, isobutyric, valeric and isovaleric acids. Then, add 1 mL of each prepared acid to 1.2 mL of 25% (w/v) metaphosphoric acid and use as the standard cocktails.
- Filter the samples using a 0.22 μM membrane.
- Detect SCFA concentrations using high performance gas chromatography according to previously described protocols11,17.
NOTE: An InertCap FFAP column (0.25 mM x 30 m x 0.25 μM) is used for gas chromatography (GC). SCFA concentrations are then quantified based on peak areas using the single-point internal standard method in the GC Solution software package.
The production of mucoid EPS could be observed in B. longum cultures on PYG plates after anaerobic incubation for 72 h (Figure 1A). Centrifugation of culture scrapes, followed by ethanol precipitation and drying, resulted in the collection of cellulose-like EPS (Figure 1B). Dried EPS and soluble starch were then used as carbon sources for fermentation cultures. TLC was used for oligosaccharide separation and purity analysis due to its low cost and rapid results turnaround18. Although the degradation rate of starch by human fecal microbiota was faster than that of Bif EPS (Figure 2), Bif EPS degradation was clearly observed for some EPS-inoculated samples.
Community compositional analysis via 16S rRNA gene high-throughput sequencing and principal coordinate analysis (PCoA) was then performed to investigate the effects of Bif EPS on human gut microbiota. Samples from the VI_Bif and VI_Starch groups clustered separately from each other in the PCoA analysis (Figure 3A), indicating that EPS and starch availability differentially shape human fecal bacterial communities. Linear discriminant analysis effect size (LEfSe) was further used to distinguish the specific bacterial taxa that differed between the VI_Bif and VI_Starch treatments. The genera Collinsella, Coprococcus, Parabacteroides, and Rhodopseudomonas were significantly more abundant in the VI_Bif samples than in the VI_Starch samples (Figure 3B). Furthermore, GC measurements were made for several SCFAs to evaluate their production following the addition of different carbon sources. SCFAs that were measured from fermentation cultures included acetic, propionic, isobutyric, butyric, isovaleric, and valeric acids. Following fermentation for 24 h and 48 h, five of the six aforementioned SCFA concentrations were similar among treatments and not statistically different between the VI_Bif, VI_Starch, and VI groups. However, propionic acid concentrations were significantly higher in the VI_Bif group than in the VI_Starch group (Figure 4).
Figure 1: EPS produced by B. longum.
Frozen B. longum was restored in Bifidobacterium medium broth and then streaked onto PYG plates, followed by anaerobic incubation at 37 °C for 72 h (A). The EPS produced by bacterial cultures were scraped from plate cultures, precipitated using ethanol, and dried overnight using a speed vacuum (B). Please click here to view a larger version of this figure.
Figure 2: TLC analysis of in vitro EPS and starch degradation by human gut microbiota.
TLC analysis was conducted on 0.2 μL samples collected at 24 h and 48 h from each fermentation culture grown under anaerobic conditions. VI, VI_Starch, and VI_Bif indicate VI media, VI media + starch supplement, and VI media + EPS supplement, respectively. The numbers 1–12 indicate fecal bacterial samples from the 12 volunteers that were used to inoculate the fermentation experiments. The control group represents treatment without additional carbon supplements. This figure is modified from Yin et al.11. Please click here to view a larger version of this figure.
Figure 3: Effects of Bif EPS availability on human gut microbiota communities.
(A) PCoA plot of gut microbiota community compositional dissimilarities based on the unweighted UniFrac metric. (B) LEfSE analysis of bacterial taxa that were differentially abundant among treatment groups. A cutoff of p < 0.05 was used to assess the statistical significance of bacterial taxonomic differences among groups. Ori indicates the gut microbiota of the volunteer fecal samples. VI_Bif and VI_Starch indicate the gut microbiota from fermentation samples using VI media with EPS and starch as carbon substrates, respectively. VI represents the control group with gut microbiota inoculated fermentations in VI media without supplementation of other carbohydrates. This figure is modified from Yin et al.11 Please click here to view a larger version of this figure.
Figure 4: Effects of EPS availability on SCFA production after 24 h and 48 h of fermentation.
Acetic, propionic, isobutyric, butyric, isovaleric, and valeric acids were detected using gas chromatography. VI_Bif, VI_Starch, and VI indicate the samples that were collected after cultivation using VI media + EPS, VI media + starch, and VI media, respectively. All samples were measured in triplicate. The figures were generated using GraphPad Prism Version 5.01. Panels represent organic acid concentrations within each fermented sample for A, acetic acid; B, propionic acid; C, isobutyric acid; D, butyric acid; E, isovaleric acid; and F, valeric acid. This figure is modified from Yin et al.11 Please click here to view a larger version of this figure.
Significant progress has been made towards understanding human gut microbiota composition and activities over the last decade. As a consequence of these studies, the holobiont concept has emerged, which represents the interactions between hosts and associated microbial communities, such as in between humans and their gut microbiota19,20. Furthermore, humans are even now regarded as superorganisms21, wherein the gut microbiota have been recognized as one of the functional organs in humans22,23. The human body hosts a complex microbial ecosystem, consisting of approximately 1013 microbial cells24. Moreover, the genomes of gut microbiota are considered auxiliary genomes from humans that encode numerous metabolic-related genes that expand the host’s metabolic capabilities4. However, xenobiotics, including therapeutic drugs and diet-derived bioactive compounds, can potentially alter the gut microbiome community structure and associated functions5. Increasing numbers of studies have indicated that interactions between gut microbiota and xenobiotics play important roles in mediating chemical toxicity and causing, or otherwise exacerbating, human diseases6,7. Thus, investigations of the interactions between xenobiotics and the human gut microbiota have recently garnered significant research attention.
Mouse models have been the most widely used methods to investigate interactions between microbiota and hosts. However, differences in composition and activities between the gut microbiota of humans and mice25 may result in inadequate modeling of human interactions through studies of mice. Nevertheless, bioethics considerations require minimal use of mice. An alternative to the above in vivo models is batch fermentation, which can be used to simulate human gut microbiota in vitro26. Consequently, fermentation experiments have been used to investigate the interactions between xenobiotics and human gut microbiota. For example, Yin et al.17 have used batch fermentation experiments to investigate the interactions between polysaccharides and human gut microbiota. The results from this study indicate that some polysaccharides can be metabolized by the human gut microbiota, and that polysaccharides modulate the human bacterial community and metabolites that they produce in vitro, including SCFAs. However, some methodological considerations are critical for use of this protocol. For example, fecal samples should be collected as soon as possible, and an anaerobic chamber should be used to ensure the growth of obligate anaerobes. The latter consideration is particularly critical, because oxygen exposure can lead to the death of some gut bacterial populations and thus, alteration of the bacterial community. In addition, xenobiotics are metabolized in the upper digestive system. Consequently, modeling the interactions between xenobiotics and the lower digestive system microbiota is an important consideration for in vivo modeling.
Batch fermentation experiments have clear advantages over in vivo human and animal studies because they are more economically feasible and convenient. Moreover, they can be used to investigate interindividual variation of human gut microbiota responses to xenobiotic exposure. Moreover, batch fermentation can be easily applied to manipulate microbiota communities and evaluate their associated metabolic functions. However, batch fermentation systems suffer from the limitation of static state dynamics. Future investigations could implement bioreactor chemostats that allow the dynamic modulation of pH, temperature, and peristalsis, while maintaining a steady supply of nutrients and the continuous removal of waste. Such activities would allow experiments to better mimic in vivo intestinal tracts and provide new insights to supplement those from batch fermentation experiments. An additional limitation of batch fermentation experiments is that they remove all microbiome-host tissue interactions. This could be a particularly important consideration, as some xenobiotics (e.g., methamphetamine) can be co-metabolized by human cells and gut microbiota27. Moreover, recent studies have indicated that gut metagenome (GM) can indirectly regulate xenobiotic metabolism via regulating host gene expression regulation8.
Although developments of batch fermentation systems are still needed, these systems can be widely used for high-throughput and rapid screening of interactions between xenobiotics and human gut microbiota. Elucidating the mechanisms underlying xenobiotic resistance and metabolism in active human gut microbiomes will provide important insights into unexplained patient-to-patient variation in drug efficacy and toxicity8,9. Furthermore, a more detailed understanding of how diets and specific food components alter microbial metabolisms and consequently effect host health is the first step towards realizing the goal of personalized medicine via microbiota modulation.
The authors declare that they have no conflicts of interest. The figures were cited in Yin et al.11.
This study was funded by the National Nature Science Foundation of China (No. 31741109), the Hunan Natural Science Foundation (No. 2018JJ3200), and the construct program of applied characteristic discipline in Hunan University of Science and Engineering. We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript.
|0.22 µm membrane filters||Millipore||SLGP033RB||Use to filter samples|
|0.4-mm Sieve||Thermo Fischer||308080-99-1||Use to prepare human fecal samples|
|5-bromo-4-chloro-3-indolyl β-D-galactopyranoside (X-Gal)||Solarbio||X1010||Use to prepare color plate|
|Acetic||Sigma-Aldrich||71251||Standard sample for SCFA|
|Agar||Solarbio||YZ-1012214||The component of medium|
|Anaerobic chamber||Electrotek||AW 400SG||Bacteria culture and fermentation|
|Autoclave||SANYO||MLS-3750||Use to autoclave|
|Bacto soytone||Sigma-Aldrich||70178||The component of medium|
|Baking oven||Shanghai Yiheng Scientific Instruments Co., Ltd||DHG-9240A||Use to heat and bake|
|Beef Extract||Solarbio||G8270||The component of medium|
|Bifidobacterium longum Reuter||ATCC||ATCC® 51870™||Bacteria|
|Bile Salts||Solarbio||YZ-1071304||The component of medium|
|Butyric||Sigma-Aldrich||19215||Standard sample for SCFA|
|CaCl2||Solarbio||C7250||Salt solution of medium|
|Capillary column||SHIMADZU-GL||InertCap FFAP (0.25 mm × 30 m × 0.25 μm)||Used to SCFA detection|
|Casein Peptone||Sigma-Aldrich||39396||The component of medium|
|Centrifuge||Thermo Scientific||Sorvall ST 8||Use for centrifugation|
|CoSO4.7H2O||Solarbio||C7490||The component of medium|
|CuSO4.5H2O||Solarbio||203165||The component of medium|
|Cysteine-HCl||Solarbio||L1550||The component of medium|
|Ethanol||Sigma-Aldrich||E7023||Use to prepare vitamin K1|
|FeSO4.7H2O||Solarbio||YZ-111614||The component of medium|
|Formic Acid||Sigma-Aldrich||399388||Used to TLC|
|Gas chromatography||Shimadzu Corporation||GC-2010 Plus||Used to SCFA detection|
|Glass beaker||Fisher Scientific||FB10050||Used for slurry preparation|
|Glucose||Solarbio||G8760||The component of medium|
|Haemin||Solarbio||H8130||The component of medium|
|HCl||Sigma-Aldrich||30721||Basic solution used to adjust the pH of the buffers|
|Isobutyric||Sigma-Aldrich||46935-U||Standard sample for SCFA|
|Isovaleric Acids||Sigma-Aldrich||129542||Standard sample for SCFA|
|K2HPO4||Solarbio||D9880||Salt solution of medium|
|KCl||Solarbio||P9921||The component of medium|
|KH2PO4||Solarbio||P7392||Salt solution of medium|
|LiCl.3H2O||Solarbio||C8380||Use to prepare color plate|
|Meat Extract||Sigma-Aldrich-Aldrich||70164||The component of medium|
|Metaphosphoric Acid||Sigma-Aldrich||B7350||Standard sample for SCFA|
|MgCl2.6H2O||Solarbio||M8160||The component of medium|
|MgSO4.7H2O||Solarbio||M8300||Salt solution of medium|
|MISEQ||Illumina||MiSeq 300PE system||DNA sequencing|
|MnSO4.H20||Sigma-Aldrich||M8179||Salt solution of medium|
|NaCl||Solarbio||YZ-100376||Salt solution of medium|
|NaHCO3||Sigma-Aldrich||792519||Salt solution of medium|
|NanoDrop ND-2000||NanoDrop Technologies||ND-2000||Determine DNA concentrations|
|NaOH||Sigma-Aldrich||30620||Basic solution used to adjust the pH of the buffers|
|n-butanol||ChemSpider||71-36-3||Used to TLC|
|NiCl2||Solarbio||746460||The component of medium|
|Orcinol||Sigma-Aldrich||447420||Used to prepare orcinol reagents|
|Propionic||Sigma-Aldrich||94425||Standard sample for SCFA|
|QIAamp DNA Stool Mini Kit||QIAGEN||51504||Extract bacterial genomic DNA|
|Ready-to-use PBS powder||Sangon Biotech (Shanghai) Co., Ltd.||A610100-0001||Used to prepare the lipid suspension|
|Speed Vacuum Concentrator||LABCONCO||CentriVap||Use to prepare EPSs|
|Starch||Solarbio||YZ-140602||Use to the carbon source|
|Sulfuric Acid||Sigma-Aldrich||150692||Used to prepare orcinol reagents|
|T100 PCR||BIO-RAD||1861096||PCR amplification|
|TLC aluminium sheets||MerckMillipore||116835||Used to TLC|
|Trypticase Peptone||Sigma-Aldrich||Z699209||The component of medium|
|Tryptone||Sigma-Aldrich||T7293||The component of medium|
|Tween 80||Solarbio||T8360||Salt solution of medium|
|Valeric||Sigma-Aldrich||75054||Standard sample for SCFA|
|Vitamin K1||Sigma-Aldrich||V3501||The component of medium|
|Vortex oscillator||Scientific Industries||Vortex.Genie2||Use to vortexing|
|Yeast Extract||Sigma-Aldrich||Y1625||The component of medium|
|ZnSO4.7H2O||Sigma-Aldrich||Z0251||The component of medium|
- Maarten, V. D. G., Blottière Hervé, M., Doré, J. Humans as holobionts: implications for prevention and therapy. Microbiome. 6, (1), 81 (2018).
- Allen, A. P., Dinan, T. G., Clarke, G., Cryan, J. F. A psychology of the human brain-gut-microbiome axis. Social and Personality Psychology Compass. 11, (4), e12309 (2017).
- Arora, T., Bäckhed, F. The gut microbiota and metabolic disease: current understanding and future perspectives. Journal of Internal Medicine. 280, 39-349 (2016).
- Maurice, C., Haiser, H., Turnbaugh, P. Xenobiotics shape the physiology and gene expression of the active human gut microbiome. Cell. 152, (1-2), 39-50 (2013).
- Carmody, R. N., Turnbaugh, P. J. Host-microbial interactions in the metabolism of therapeutic and diet-derived xenobiotics. Journal of Clinical Investigation. 124, (10), 4173-4181 (2014).
- Lu, K., Mahbub, R., Fox, J. G. Xenobiotics: interaction with the intestinal microflora. ILAR Journal. 56, (2), 218-227 (2015).
- Taguer, M., Maurice, C. The complex interplay of diet, xenobiotics, and microbial metabolism in the gut: implications for clinical outcomes. Clinical Pharmacology & Therapeutics. 99, (6), 588-599 (2016).
- Anubhav, D., Meenakshi, S., Shankar, G. T., Mande, S. S., Wilson, B. A. Xenobiotic metabolism and gut microbiomes. PLoS One. 11, (10), e0163099 (2016).
- Koppel, N., Rekdal, V. M., Balskus, E. P. Chemical transformation of xenobiotics by the human gut microbiota. Science. 356, (6344), 1246-1257 (2017).
- Hidalgo-Cantabrana, C., et al. Genomic overview and biological functions of exopolysaccharide biosynthesis in Bifidobacterium spp. Applied and Environmental Microbiology. 80, (1), 9-18 (2014).
- Liu, G., et al. Effects of bifidobacteria-produced exopolysaccharides on human gut microbiota in vitro. Applied Microbiology and Biotechnology. 1-10 (2018).
- Tang, R., et al. Gut microbial profile is altered in primary biliary cholangitis and partially restored after UDCA therapy. Gut. 67, (3), 534-541 (2018).
- Kuczynski, J., et al. Using QIIME to analyze 16S rRNA gene sequences from microbial communities. Current Protocols in Microbiology. 27, (1), 1-28 (2012).
- Hiltemann, S. D., Boers, S. A., van der Spek, P. J., Jansen, R., Hays, J. P., Stubbs, A. P. Galaxy mothur Toolset (GmT): a user-friendly application for 16S rRNA gene sequencing analysis using mothur. GigaScience. giy166 (2018).
- Wang, Q., Garrity, G. M., Tiedje, J. M., Cole, J. R. Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and Environmental Microbiology. 73, (16), 5261-5267 (2007).
- Schloss, P. D., et al. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environmental Microbiology. 75, (23), 7537-7541 (2009).
- Bai, S., et al. Comparative study on the in vitro effects of pseudomonas aeruginosa and seaweed alginates on human gut microbiota. Plos One. 12, (2), e0171576 (2017).
- Zhang, Z., Xie, J., Zhang, F., Linhardt, R. J. Thin-layer chromatography for the analysis of glycosaminoglycan oligosaccharides. Analytical Biochemistry. 371, 118-120 (2007).
- Simon, J. C., Marchesi, J. R., Mougel, C., Selosse, M. A. Host-microbiota interactions: from holobiont theory to analysis. Microbiome. 7, (5), (2019).
- Postler, T. S., Ghosh, S. Understanding the Holobiont: how microbial metabolites affect human health and shape the immune system. Cell Metabolism. 26, (1), 110-130 (2017).
- Kramer, P., Bressan, P. Humans as superorganisms: how microbes, viruses, imprinted genes, and other selfish entities shape our behavior. Perspectives on Psychological Science. 10, (4), 464-481 (2015).
- Malfertheiner, P., Nardone, G. Gut microbiota: the forgotten organ. Digestive Diseases. 29, (6), (2011).
- Andoh, A. The gut microbiota is a new organ in our body. The Japanese journal of Gastro-Enterology. 112, (11), 1939-1946 (2015).
- Mika, A., Van, W. T., González, A., Herrera, J. J., Knight, R., Fleshner, M. Exercise is more effective at altering gut microbial composition and producing stable changes in lean mass in juvenile versus adult male f344 rats. PLoS One. 10, (5), e0125889 (2015).
- Hugenholtz, F., de Vos, W. M. Mouse models for human intestinal microbiota research: a critical evaluation. Cellular and Molecular Life Sciences. 75, (1), 149-160 (2018).
- Takagi, R., et al. A single-batch fermentation system to simulate human colonic microbiota for high-throughput evaluation of prebiotics. PLoS One. 11, (8), e0160533 (2016).
- Ning, T., Gong, X., Xie, L., Ma, B. Gut microbiota analysis in rats with methamphetamine-induced conditioned place preference. Frontiers in Microbiology. 8, (1), 1620 (2017).