A subscription to JoVE is required to view this content. Sign in or start your free trial.
Method Article
* These authors contributed equally
This protocol describes an in vitro batch-culture fermentation system of human fecal microbiota, using inulin (a well-known prebiotic and one of the most widely studied microbiota modulators) to demonstrate the use of this system in estimating effects of specific interventions on fecal microbiota composition and metabolic activities.
The emerging role of the gut microbiome in several human diseases demands a breakthrough of new tools, techniques and technologies. Such improvements are needed to decipher the utilization of microbiome modulators for human health benefits. However, the large-scale screening and optimization of modulators to validate microbiome modulation and predict related health benefits may be practically difficult due to the need for large number of animals and/or human subjects. To this end, in vitro or ex vivo models can facilitate preliminary screening of microbiome modulators. Herein, it is optimized and demonstrated an ex vivo fecal microbiota culture system that can be used for examining the effects of various interventions of gut microbiome modulators including probiotics, prebiotics and other food ingredients, aside from nutraceuticals and drugs, on the diversity and composition of the human gut microbiota. Inulin, one of the most widely studied prebiotic compounds and microbiome modulators, is used as an example here to examine its effect on the healthy fecal microbiota composition and its metabolic activities, such as fecal pH and the fecal levels of organic acids including lactate and short-chain fatty acids (SCFAs). The protocol may be useful for studies aimed at estimating the effects of different interventions of modulators on fecal microbiota profiles and at predicting their health impacts.
The human microbiota is a complex community consisting of bacteria, archaea, viruses and eukaryotic microbes1, that inhabit the human body internally and externally. Recent evidences have established the fundamental role of the gut microbiota and the gut microbiome (the entire collection of microbes and their genes found in the human gastrointestinal tract) in various human diseases including obesity, diabetes, cardiovascular diseases, and cancer1,2,3. Additionally, the microorganisms living in our gut produce a wide spectrum of metabolites which significantly affect our health and can also contribute to the pathophysiology of several diseases as well as a variety of metabolic functions4,5. Abnormal changes (perturbations) in the composition and function of this gut microbial population are generally termed as "gut dysbiosis". Dysbiosis is usually associated with an unhealthy state of the host and hence can be differentiated from the normal (homeostatic) microbial community associated with a healthy control state of the host. Specific patterns of gut microbiome dysbiosis are often found in various different diseases1,2,3,6,7.
The fermentation of undigested food, particularly the fermentable carbohydrates/fibers, by the gut microbiota not only yields energy but also produces divergent metabolites including short-chain fatty acids (SCFAs), lactate, formate, carbon dioxide, methane, hydrogen, and ethanol6. In addition, the gut microbiota also produces a number of other bioactive substances such as folate, biotin, trimethylamine-N-oxide, serotonin, tryptophan, gamma-aminobutyric acid, dopamine, norepinephrine, acetylcholine, histamine, deoxycholic acid, and 4-ethylphenyl sulfate. This occurs primarily through the utilization of intrinsic metabolic fluxes within the host-microbe niche, which contributes in several body processes, metabolic functions and epigenetic changes1,8,9,10. However, the effects of various interventions on such microbial products remain unkown or unclear due to the lack of easy, efficient and reproducible protocols. The human gut microbiota composition is an extremely complex and diverse ecosystem, and hence, many questions about its role in human health and disease pathology still remain unanswered. The effects of many common gut microbiome modulators (e.g., probiotics, prebiotics, antibiotics, fecal transplantation and infections) on the composition and metabolic functions of the intestinal microbiota remain largely elusive. In addition, the examination and validation of these effects in vivo is difficult, particularly because most of the nutrients and metabolites produced by the gut microbiota are absorbed or disposed of simultaneously and rapidly in the gut; therefore, measuring the production, amount and processing of these metabolites (e.g., SCFAs) in vivo still remains a practical challenge. Indeed, physiological models such as animals and human subjects are critical for determining the role of gut microbiome and its modulation on host health, but these may not be suitable for large-scale screening of different types of microbiome modulators due to ethical, monetary or time constraints. To this end, in vitro and/or ex vivo models, such as culturing of gut microbiota in vitro and then intervening with different microbiota modulators, can offer time- and money-saving opportunities and hence can allow for preliminary or large-scale screening of various components (such as probiotics, prebiotics, and other interventional compounds) to examine/predict their effects on the fecal microbiota diversity, composition and metabolic profiles. Studies using such in vitro and ex vivo systems of the gut microbiome may facilitate further understanding of the host-microbiome interactions that contribute to host health and disease, and could also lead to finding novel therapies that target the microbiome to ameliorate host health and prevent and treat various diseases1.
Although the in vitro gut microbiota culture systems cannot truly replicate the actual intestinal conditions, several laboratories have endeavored to develop such models, some of which have been found practicable to some extent and have been successfully used for different purposes. One of the recent gut models is the Simulator of the Human Intestinal Microbial Ecosystem, which mimics the entire human gastrointestinal tract, including the stomach, small intestine, and different regions of the colon. However, such technically complex models may not be accessible to other research facilities worldwide. Therefore, there is still a critical need for the development of new alternative models that are relatively simple, affordable and practical for laboratories studying the microbiome modulators and their effects on gut microbiota and host health. Hence, the use of an in vitro (or ex vivo) fecal microbiota culture system would be useful for studying the effects of such interventions11,12. Specifically, the effect of different prebiotics on the microbiota fermentation capacity in terms of periodic changes in the gut microbiota diversity and composition, the fecal pH, and the levels of microbial metabolites including SCFAs and lactate can be studied13. Herein, using inulin (one of the most widely studied prebiotic components) as an example of the microbiome modulator, a step-by-step protocol of this simple ex vivo microbiota batch-culture system is described to demonstrate its use to estimate the changes in the fecal microbiota and microbial metabolites following intervention with the microbiome modulators.
Access restricted. Please log in or start a trial to view this content.
CAUTION: Consult the appropriate Material Safety Data Sheets and follow the instructions and guidelines for appropriate Biosafety Level 2 (BSL-2) training. Follow all the culturing steps as per the standard biosafety rules and use a BSL-2 cabinet using aseptic conditions. Furthermore, fecal samples from different models and human subjects may have potential risk of spreading microbial borne diseases. Immediately seek medical aid in the occurrence of any injury and infection. In addition, the use of human and animal stool samples should be approved through institutional ethical committees and must compliant with protocols to use samples and subject information.
1. Preparation of Culture Media
2. Preparation of Anaerobic Chamber and Required Material
3. Preparation of Tubes and Fibers
4. Preparation of Inoculum
5. Fermentation and Sampling
6. Short Chain Fatty Acids (SCFAs) and Lactate Quantification
NOTE: The SCFAs and lactate in the supernatant of microbiome culture can be measured exactly according to the methods detailed elsewhere13,14,15,16.
7. Fecal Microbiome Analysis
NOTE: Perform microbiome analysis following the methods and pipeline detailed elsewhere7,13,14,17.
Access restricted. Please log in or start a trial to view this content.
The protocol is used to demonstrate the effect of a specific prebiotic (i.e., inulin on the microbiota composition and metabolic activities in terms of changes in the fecal pH and the concentration of lactate and SCFAs in the feces of healthy human subjects over different time-points following treatment with inulin). The fecal pH, the fecal levels of lactate and SCFAs (Figure 1), and the microbiota composition (Figure 2 and
Access restricted. Please log in or start a trial to view this content.
The in vitro fecal slurry fermentation model presented here is a simple single-batch model to approximate the effects of different substrates and microbial strains (e.g., prebiotics and probiotics) on the composition of human fecal microbiota as well as its metabolic activities in terms of fecal pH and SCFAs levels. The results presented herein demonstrate that the inoculation of inulin decreases the fecal pH and significantly increases the levels of SCFAs and lactate in inulin-treated fecal specimen as compared to non-t...
Access restricted. Please log in or start a trial to view this content.
The authors have nothing to disclose.
The authors gratefully acknowledge funding support from the Center for Diabetes, Obesity and Metabolism and the Clinical and Translational Science Center, the Wake Forest School of Medicine, the Department of Defense funding (Grant number: W81XWH-18-1-0118), the Kermit Glenn Phillips II Chair in Cardiovascular Medicine; the National Institutes of Health funded Claude D. Pepper Older Americans Center (funded by P30AG12232); R01AG18915; R01DK114224 and the Clinical and Translational Science Center (Clinical Research Unit, funded by UL1TR001420), is also thankfully acknowledged. We also thank the volunteers for providing fecal samples, and our other lab members for their technical helps during this experiment.
Access restricted. Please log in or start a trial to view this content.
Name | Company | Catalog Number | Comments |
Ammonium Bicarbonate (NH4HCO3) | Sigma-Aldrich | 217255 | |
Ammonium Sulfate (NH4)2SO4 | TGI | C2388 | Toxic |
Calcium Chloride Dihydrate (CaCl2•2H2O) | Sigma-Aldrich | C3306 | Irritating |
Cobaltous Chloride Hexahydrate (CoCl2•6H2O) | Sigma-Aldrich | 255599 | |
Cupric Chloride Dihydrate (CuCl2•2H2O) | Acros organics | 2063450000 | Toxic, Irritating |
Cysteine-HCl | Sigma-Aldrich | C121800 | |
D-biotin | Sigma-Aldrich | B4501 | |
D-Pantothenic acid | Alfa Aesar | A16609 | |
Disodium Ethylenediaminetetraacetate Dihydrate (Na2EDTA) | Biorad | 1610729 | |
DL-α-methylbutyrate | Sigma-Aldrich | W271918 | |
Ferrous Sulfate Heptahydrate (FeSO4•7H2O) | Sigma-Aldrich | F8263 | Toxic |
Folic acid | Alfa Aesar | J62937 | |
Glucose | Sigma-Aldrich | G8270 | |
Hemin | Sigma-Aldrich | H9039 | |
Hepes | Alfa Aesar | A14777 | |
Isobutyrate | Alfa Aesar | L04038 | |
Isovalerate | Alfa Aesar | A18642 | |
Magnesium Chloride Hexahydrate (MgCl2•6H2O) | Sigma-Aldrich | M8266 | |
Manganese Chloride Tetrahydrate (MnCl2•4H2O) | Sigma-Aldrich | 221279 | |
Niacin (Nicotinic acid) | Sigma-Aldrich | N4126 | |
Nickel(Ii) Chloride Hexahydrate (NiCl2•6H2O) | Alfa Aesar | A14366 | Toxic |
N-valerate | Sigma-Aldrich | 240370 | |
P-aminobenzoic acid | MP China | 102569 | Toxic, Irritating |
Phosphoric Acid (H3PO4) | Sigma-Aldrich | P5811 | |
Potassium Dihydrogen Phosphate (KH2PO4) | Sigma-Aldrich | P5504 | |
Potassium Hydrogen Phosphate (K2HPO4) | Sigma-Aldrich | 1551128 | |
Pyridoxine | Alfa Aesar | A12041 | |
Resazurin | Sigma-Aldrich | R7017 | |
Riboflavin | Alfa Aesar | A11764 | |
Sodium carbonate (Na2CO3) | Sigma-Aldrich | 1613757 | |
Sodium chloride (NaCl) | Fisher BioReagents | 7647-14-5 | |
Sodium hydroxide (NaOH) | Fisher Chemicals | S320 | |
Sodium Molybdate Dihydrate (Na2MoO4•2H2O) | Acros organics | 206375000 | |
Thiamine Hydrochloride (Thiamin-HCl) | Acros organics | 148991000 | |
Trypticase | BD Biosciences | 211921 | |
Vitamin B12 | Sigma-Aldrich | V2876 | |
Yeast extract | Sigma-Aldrich | 70161 | |
Zinc Sulfate Heptahydrate (ZnSO4•7H2O) | Sigma-Aldrich | Z0251 | |
0.22 µm membrane filter | |||
AMPure magnetic purification beads | Agencourt | ||
Anaerobic chamber with incubatore | Forma anaerobic system, Thermo Scientific, USA | ||
Bottle filter | Corning | ||
Cheesecloth | |||
Illumina MiSeq sequencer | Miseq reagent kit v3 | ||
pH meter | |||
Qiagen PowerFecal kit | Qiagen | ||
Quantitative Insights into Microbial Ecology (QIIME) software | |||
Qubit-3 fluorimeter | InVitrogen | ||
Vortex | Thermoscientific | ||
Waters-2695 Alliance HPLC system | Waters Corporation |
Access restricted. Please log in or start a trial to view this content.
Request permission to reuse the text or figures of this JoVE article
Request PermissionThis article has been published
Video Coming Soon
Copyright © 2025 MyJoVE Corporation. All rights reserved