The importance of a healthy gut is increasingly recognized as key to modern production systems—particularly as it relates to the reduction of antibiotics and improvement in animal welfare. The gut is the first line of a body’s defense: a sufficient balance of beneficial intestinal microbiota and a tight gut barrier both protect animals against pathogens and toxins. The gastrointestinal tract acts as an interface between diet, host, and gut microbiota, and plays a clear role in an animal’s health status (Figure 1). Diet, including feed and feed additives, constitutes a major factor that affects the composition and the activity of the gut microorganisms and gut peformance.
Researchers and scientists at the BIOMIN Research Center utilize a range of different methods to characterize the intestinal microbiota and substances that increase the overall gut health. Here, we examine three molecular methods to assess gut microbiota that allow analysis of samples ex vivo, and three cell culture based models for gut performance that simulate the gut intestine/epithelia in vitro. The former constitute a major improvement to analyze bacterial communities and allow us to take a closer look on microbiota composition and diversity as well as quantity of particular bacterial groups. The latter allow for mimicking of infections and screening of beneficial substances without harming animals by using animal specific cell lines, e.g. the intestinal porcine epithelial cell line (IPEC-J2).
Denaturing gradient gel electrophoresis
Denaturing gradient gel electrophoresis (DGGE) takes an overall profile of the microbial community, and can quickly process a large number of intestinal or fecal samples.
DGGE is based on amplification of a specific gene, typically 16S rRNA used as a molecular marker, and separation of the different variants of the gene in the community sample by electrophoresis in a denaturing gel. After staining, differences in the gene sequence result in the appearance of characteristic band patterns in the gel, so-called ‘fingerprints’. DGGE allows comparison of microbial communities by cluster analysis of these fingerprints, which can be further used to monitor the effects of feed additives on the diversity and dynamics of fecal microbiota of animals (Figure 2).
Sequence based Gut Microbiome Profiling
For detailed information on the bacterial composition, 16S rRNA based amplicon sequencing enables identification of the entire microbial community within a sample up to the species level. Total sample DNA is first amplified by PCR using 16S rRNA oligonucleotides and using specific adapters and barcodes, many samples can be combined in one sequencing run. PCR amplicons are therefore coupled to spherical particles and loaded on disposable sequencing chips.
Using e.g Illumina Miseq as sequencing platform, out of complex samples 5 to 10 GB of sequence data (approx. 10 to 15 million sequencing reads, depending on sequencing depth) can be expected. Bioinformatic evaluation includes processing of raw reads and clustering of related sequences. These clusters of similar sequencing reads are referred to as operational taxonomic units (OTUs). Microbial identification is accomplished by comparison to sequences in 16S based reference databases (e.g. RDP II or Silva).
Quantitative polymerase chain reaction
For quantitative information on bacterial group or species level, real-time polymerase chain reaction (qPCR) using specific oligonucleotides (targeting the 16S rRNA gene or other marker genes) can be used. It allows direct identification of dietary effects on beneficial and harmful bacteria. Furthermore, it can be used to specifically detect probiotic strains, like Lactobacillus reuteri, within the gastrointestinal tract.
The anti-oxidative potential of phytogenics in IPEC-J2 is assessed by using 2’, 7’- dichlorodihydrofluorescein diacetate (DCFH-DA) which is able to incorporate into cells and become fluorescent upon exposure to reactive oxygen species (ROS). ROS are induced by stimulation with H2O2 and are determined via measurement of fluorescence, directly proportional to the amount of intracellular ROS. Potent phytogenic test substances can counteract the ROS production, indicated by a decreased fluorescence (Figure 3A). The reduction of oxidative stress supports animal performance.
Figure 3. Three cell culture assays used to investigate the anti-oxidative (A) and anti-inflammatory (B) properties of phytogenic test substances as well as to study the epithelial barrier integrity (C) in an intestinal porcine epithelial cell line (IPEC-J2).
To screen for anti-inflammatory activity of phytogenic test substances in IPEC-J2, levels of the pro-inflammatory transcription factor NF-κB are monitored via the luminescence based NF-κB reporter gene assay. Cells are transfected with the NF-κB reporter vector and are pre-incubated with phytogenics. Followed by the activation of NF-κB by stimulation with the pro-inflammatory cytokine TNF-α, the potential of test substances to attenuate TNF-α-induced inflammation is determined via measurement of luminescence, directly proportional to the amount of activated NF-κB (Figure 3B). By reducing inflammation, animals have more energy to put towards growth.
The transepithelial electrical resistance (TEER) assay (Figure 3c) is a cell culture model to assess gut barrier function in vitro. Therefore, IPEC-J2 are seeded in transwell-inserts with a porous membrane imitating the apical (luminal) and the basolateral (blood) side of the gut. After 8 days of differentiation, the ohmic resistance between the two compartments is measured, indicating intactness of the intestinal epithelium. A reduction of the TEER value is an early marker for disruption of the epithelial barrier. The TEER model offers the opportunity to assess the effect of mycotoxins on gut barrier integrity and to screen for bioprotective substances that are able to counteract these negative effects.