| Literature DB >> 30828329 |
Roberto Berni Canani1,2,3,4, Lorella Paparo1,3, Rita Nocerino1,3, Carmen Di Scala1,3, Giusy Della Gatta1,3, Ylenia Maddalena1, Aniello Buono1,3, Cristina Bruno1,3, Luana Voto1, Danilo Ercolini4,5.
Abstract
The dramatic increase in food allergy prevalence and severity globally requires effective strategies. Food allergy derives from a defect in immune tolerance mechanisms. Immune tolerance is modulated by gut microbiota function and structure, and microbiome alterations (dysbiosis) have a pivotal role in the development of food allergy. Environmental factors, including a low-fiber/high-fat diet, cesarean delivery, antiseptic agents, lack of breastfeeding, and drugs can induce gut microbiome dysbiosis, and have been associated with food allergy. New experimental tools and technologies have provided information regarding the role of metabolites generated from dietary nutrients and selected probiotic strains that could act on immune tolerance mechanisms. The mechanisms are multiple and still not completely defined. Increasing evidence has provided useful information on optimal bacterial species/strains, dosage, and timing for intervention. The increased knowledge of the crucial role played by nutrients and gut microbiota-derived metabolites is opening the way to a post-biotic approach in the stimulation of immune tolerance through epigenetic regulation. This review focused on the potential role of gut microbiome as the target for innovative strategies against food allergy.Entities:
Keywords: butyrate; dysbiosis; gut microbiota; gut microbiota metabolites; immune tolerance; mediterranean diet; probiotics; short chain fatty acids
Mesh:
Substances:
Year: 2019 PMID: 30828329 PMCID: PMC6384262 DOI: 10.3389/fimmu.2019.00191
Source DB: PubMed Journal: Front Immunol ISSN: 1664-3224 Impact factor: 7.561
Figure 1Gut microbiome as a target of intervention against food allergy. Several genetic, environmental, and dietary factors could modulate the gut microbiome-immune system axis influencing the occurrence of FA. For instance, increased family size, exposure to pets and/or rural environment, healthy diet (full of fibers, fermented foods, antioxidants, omega-3), breastfeeding and use of probiotics are associated with protection to FA. Conversely, C-section, prenatal, and early-life exposure to antibiotics/gastric acidity inhibitors/antiseptic agents, unhealthy diet (low fibers/high saturated fats and junk foods) may increase the risk for the development of FA. All these environmental factors act mainly on a modulation of gut microbiota structure and function which in turn could be responsible for the epigenetic regulation of genes involved in immune tolerance.
Figure 2The Food Allergy pyramid. Children with FA present an increased risk to develop other conditions such as allergic disorders (atopic march), inflammatory bowel diseases (IBD), functional gastrointestinal disorders (FGIDs), and neuropsychiatric disorders. Several genetic factors are implicated in the pathogenesis of these conditions, but recent evidence suggest the pivotal role of gut microbiome dysbiosis (induced by environmental factors). Emerging evidence support the hypothesis of dysbiosis as the first hit in the development of alterations in intestinal barrier and immune system function (responsible for the occurrence of FA and atopic march) and dysregulation of the brain-gut endocrine-immune system axis (responsible for the occurrence of FGIDs, IBD, and neuropsychiatric disorders), at least in part through an activation of epigenetic mechanisms.
Main gut microbiome features in food allergy.
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| Thompson-Chagoyan et al. ( | N.R. | N.R. | ( | ||
| Nakayama et al. ( | = | = | 16s rRNA sequencing | ( | |
| Ling et al. ( | = | 16s rRNA sequencing | ( | ||
| Azad et al. ( | = | 16s rRNA sequencing | ( | ||
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| Berni Canani et al. ( | N.R. | 16s rRNA sequencing | ( | ||
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FA, food allergy; FS, sensitization to food antigens; OTUs, operational taxonomic units; N.R., not reported; .
Main preclinical evidences on the probiotics role against food allergy.
| Intestinal barrier maturation | ( | |
| Th1/Th2 response balance: Th1 stimulation | ( | |
| Th1/Th2 response balance: Th2 suppression | ( | |
| Immune system regulation: Tregs development | ( | |
| Increase in B and T cell proliferation with enhanced production of Th1 and regulatory cytokines | ( | |
| Immune system regulation: tolerogenic DCs development | ( | |
| Suppression of IgE production | ( | |
| Epigenetic modulation of Th1/Th2 genes expression | ( | |
| Increase in the production of the regulatory cytokine IL-10 by monocytes and dendritic cells; enhance of IFN-γ production by T cells | ( | |
| Increase in the population of CD4+FoxP3+ T cells, up-regulation of FoxP3 and down-regulation of GATA-3 | ( | |
| Reduction of allergic reaction; reduction of IL-4, IL-5, IL-13 and specific IgE production | ( | |
| Improvement of anaphylaxis symptoms and increase of sIgA and CD4+ CD25+ FoxP3Treg cell | ( |
Figure 3The structure of the gut microbiome-immune system axis. Within the gut microbiome-immune system axis the cross talk between microbes and the immune system may occur directly through microbial components or indirectly through the action of metabolites, such as SCFAs. A positive modulation of this axis can counteract the pathogenesis of FA by promoting epithelial integrity, gut permeability, mucus production, CD103+ tolerogenic DCs, Treg differentiation, cytokines production, and sIgA release from plasma cells.
Figure 4Toward a gut microbiome-based precision medicine against food allergy. We are approaching an era where the metagenomic and metabolomic evaluation of gut microbiota in children at risk for FA will drive personalized intervention to preserve or restore an “eubiosis” state based on nutritional counseling and educational programs.
A brief glossary for a better understanding of the potential of gut microbiota as target against food allergy.
| Microbiota | The community of microbes in a particular ecosystem |
| Microbiome | The sum of micro-organisms, and their total genome capacity, in a particular environment |
| Operational taxonomic unit | A clusters of micro-organisms, grouped by DNA sequence similarity of a specific taxonomic marker gene. Operational taxonomic units are defined based on the similarity threshold (usually 97% similarity) set by the researcher |
| Microbiota diversity | A measure of how many different species are distributed in the community |
| Eubiosis | Healthy balance in a microbial ecosystem |
| Dysbiosis | A state of imbalance in a microbial ecosystem |
| Metagenomics | The study of the metagenome; the metagenome is the collective assembly of genomes from an environment (for example, the gut) |
| Metabolomics | The study of the metabolome; the metabolome is the collective array of metabolites present in a biological sample |
Techniques used to investigate the gut microbiota metagenomic and metabolomic features.
| Culture | Isolation of bacteria on selective media | Cheap, semi-quantitative | Labor intensive |
| qPCR | Amplification and quantification of 16S rRNA. Reaction mixture contains a compound that fluoresces when it binds to double-stranded DNA | Fast,quantitative, Phylogenetic identification | PCR bias, unable to identify unknown species |
| DGGE/TGGE | Gel separation of 16S rRNA amplicons using denaturant/ temperature | Fast, semi-quantitative, bands can be excised for further analysis | No phylogenetic identification, PCR bias |
| T-RFLP | Fluorescently labeled primers are amplified and then restriction enzymes are used to digest the 16S rRNA amplicon. Digested fragments separated by gel electrophoresis | Fast, cheap, semi-quantitative | No phylogenetic identification, PCR bias, low resolution |
| Fish | Fluorescently labeled oligonucleotide probes hybridize complementary target 16S rRNA sequences. When hybridization occurs, fluorescence can be enumerated using flow cytometry | Phylogenetic identification, semi-quantitative, no PCR bias | Dependent on probe sequences— unable to identify unknown species |
| DNA microarrays | Fluorescently labeled oligonucleotide probes hybridize with complementary nucleotide sequences. Fluorescence detected with a laser | Fast, Phylogenetic identification, semi-quantitative | Cross hybridization, PCR bias, species present in low levels can be difficult to detect |
| Cloned 16S rRNA gene sequencing | Cloning of full-length 16S rRNA amplicon, Sanger sequencing and capillary electrophoresis | Phylogenetic identification, quantitative | PCR bias, laborious, expensive, cloning bias |
| Direct sequencing of 16S rRNA amplicons | Massive parallel sequencing of partial 16S rRNA amplicons for example, 454 Pyrosequencing® (Roche Diagnostics GMBH Ltd, Mannheim, Germany) (amplicon immobilized on beads, amplified by emulsion PCR, addition of luciferase results in a chemoluminescent signal) | Fast, Phylogenetic identification, quantitative, identification of unknown bacteria | PCR bias, expensive, laborious |
| Microbiome shotgun sequencing | Massive parallel sequencing of the whole genome (e.g., 454 pyrosequencing® or Illumina®, San Diego, CA, USA) | Phylogenetic identification, quantitative | Expensive, analysis of data is computationally intense |
| Gas Chromatography Mass Spectrometry (GC-MS) | Thermally stable and volatile compounds are separated by GC and the eluting metabolites are detected by electron-impact (EI) mass spectrometers. | High efficiency, reproducibility and sensitivity | It can only be performed for volatile compounds |
| Liquid Chromatography Mass Spectrometry (LC) | Allows to separate compounds with little effort in a few pre-analytics steps (compared to GC-MS). The metabolite separation obtained with LC is followed by electro spray ionization (ESI) or atmospheric chemical ionization under pressure (APCI) | Lower temperatures of analysis, and it does not require sample volatility. Sensitivity, specificity, resolving power, and capability to extract additional information about metabolites from their retention time (RT) domain. | |
| Capillary Electrophoresis Mass Spectrometry (CE) | Offers high-analyte resolution and detect a wider spectrum of (polar) compounds compared to HPLC. | High resolution | It is properly applicable only to charged analytes |
| Fourier Transform Infrared Spectroscopy (FTIR) | Allows rapid, non-destructive and high-throughput determination of different sample types. This technique allows detecting different molecules, such as lipids and fatty acids (FAs), proteins, peptides, carbohydrates, polysaccharides, nucleic acids. | Ultra-high mass resolution able to distinguish slight variations in a wide number of mass signals, and allowing to obtain the structural identification of new biomarkers | Not high sensitivity and selectivity |
| Nuclear Magnetic Resonance Spectroscopy (NMR) | It uses the intramolecular magnetic field around atoms in molecules to change the resonance frequency, thus allowing access to details of molecules' electronic structure and obtaining information about their dynamics, reaction state, and chemical environment. | Useful to determine metabolic fingerprints leading to the identification and quantification of compounds in a non-targeted large-scale, in a non-destructive way, and with a high reproducibility | It is a relatively insensitive technique, and can only detect metabolites in high concentrations |
Targeting gut microbiota against FA: a research agenda.
| Identifying specific gut microbiota features associated with FA | To comparatively analyze metagenomics and metabolomics features of well-characterized populations of patients affected by different types of FA(naive of any dietary treatment) and healthy well-matched controls. |
| Characterizing the effect of dietary intervention and probiotic therapy | Prospective studies analyzing gut metagenomic and metabolomics changes in well-characterized populations. |
| Identifying the best probiotic strain to treat FA | Studies on mechanisms action in |
| Optimizing the post-biotic approach to treat FA | Full characterization of the bio-functional features of gut microbiota metabolites that could be used against FA. Studies on mechanisms action in |