| Literature DB >> 36253412 |
Yuheng Luo1, Cong Lan2, Hua Li2, Qingyuan Ouyang3, Fanli Kong4, Aimin Wu2, Zhihua Ren5, Gang Tian2, Jingyi Cai2, Bing Yu2, Jun He2, André-Denis G Wright6.
Abstract
As one of the promising next-generation probiotics (NGPs), Akkermansia muciniphila, a well-known mucin-degrading bacterium, has been proven to be closely related to the metabolic diseases of its human host. However, the role of A. muciniphila in the host's intestinal health remains ambiguous. Here, we comprehensively summarize and discuss the characteristics, the distribution, and the colonization of A. muciniphila in the human gastrointestinal tract (GIT). We propose that the application of A. muciniphila as a biomarker for longevity, for diagnostics and prognostics of intestinal diseases, or for intestinal health should be cautiously considered. Precise dietary regulation can mediate the treatment of intestinal diseases by altering the abundance of A. muciniphila. Although the beneficial role of A. muciniphila and its component in intestinal inflammation has been discovered, in gnotobiotic mice with specific gut microbiota, certain genotype, and colorectal cancer, or in animal models infected with a specific pathogen, A. muciniphila may be related to the occurrence and development of intestinal diseases. Genomic analysis, emphasizing the strain-level phylogenetic differences of A. muciniphila, indicates that a clear description and discussion of each strain is critical before its practical application. Our review provides much needed insight for the precise application of A. muciniphila.Entities:
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Year: 2022 PMID: 36253412 PMCID: PMC9576740 DOI: 10.1038/s41522-022-00338-4
Source DB: PubMed Journal: NPJ Biofilms Microbiomes ISSN: 2055-5008 Impact factor: 8.462
Fig. 1The abundance and role of A. muciniphila with spatial and temporal change in the GIT.
a The distribution of A. muciniphila along the GIT (small and large intestine) and in the lumen and mucosal layer. b The schematic diagram of A. muciniphila abundance changing with age in the human and mouse GIT. c The mechanisms of A. muciniphila ameliorating aging in mice. All figures are created with Biorender.com.
The abundance of A. mucinihlia varies with age.
| Author/Year | Volunteers | Geographic area | Method | Main Findings |
|---|---|---|---|---|
| Elena Biagi et al. 2016[ | 22–48 years: | Emilia Romagna and surrounding area, Italy | 16S rRNA gene sequencing | The relative abundance of |
| Fanli Kong et al. 2016[ | 24–64 years: | Dujiangyan and Ya’an, Sichuan, China | 16S rRNA gene sequencing | Relative abundance of |
| Simone Rampelli et al. 2020[ | 22–48 years: | Emilia Romagna, Italy | Shotgun sequencing | Compared with younger individuals, long-lived humans show a significantly increase of |
| Nuria Salazar et al. 2019[ | <50 years: | The central area of the Asturias Region, northern Spain | Real-time PCR | The counts of |
| Bong-Soo Kim et al. 2019[ | 26–43 years: 9 67–79 years: 17 95–108 years: 30 | The neighboring counties of Gurye, Gokseong, Sunchang, and Damyang, located in the southwestern part of Korea | 16S rRNA gene sequencing | Centenarians have higher levels of |
Fig. 2The possible mechanisms of A. muciniphila regulating intestinal barrier summarized according to existing references.
All figures are created with Biorender.com.
Fig. 3The possible mechanisms of A. muciniphila regulating intestinal immunity in host with intestinal inflammation and colon cancer.
All figures are created with Biorender.com.
The negative effects of A. muciniphila on intestinal disease in some special cases.
| Author/Year | Object | Model | Experimental design | Negative effect |
|---|---|---|---|---|
| Mahesh S. Desai et al.[ | Mouse | Low-fiber diet and pathogen infection | Gnotobiotic mice are constructed with a synthetic gut microbiota from fully sequenced human gut bacteria, fed a fiber-deprivation diet (chronic or intermittent) and used | Low-fiber diet promotes expansion and activity of mucus-degrading bacteria, such as |
| Sergey S. Seregin et al.[ | Mouse | Immune deficiency disorders associated with IBD | 16 S rRNA sequencing is used to analyze the change of gut microbiota in | 1. The relative abundance of 2. |
| Héctor Argüello et al.[ | Pig | 16 S rRNA sequencing is used to analyze the composition of mucosa microbiome in the ileum of 28 days old pigs with | 1. Genus 2. Epithelial damage is positively correlated to taxa belonging to the phyla | |
| Bhanu Priya Ganesh et al.[ | Mouse | Oral gavage of | 1. After 5 days infection, 2. Co-colonization of 3. The number of mucin-filled goblet cells, the thickness of mucus and mucus sulphation are significantly decreased by the co-colonization of 4. The existence of | |
| Nielson T Baxter et al.[ | Mouse | CRC | The fecal microbiota from three CRC patients and three healthy individuals are transplanted into germ-free mice, respectively. then, these mice are chemically induced to CRC resulting in different levels of tumorigenesis. The change of gut microbiome is investigated using 16 S rRNA sequencing and metagenomic analysis. | The taxa most strongly positively correlate with increased tumor burden are several Gram-negative species including |
| Joseph P. Zackular et al.[ | Mouse | CRC | The development of microbiome during the tumorigenesis in a mouse model with inflammation-driven colon cancer is investigated using 16 S rRNA sequencing. | 1. Tumor-bearing mice show an enrichment in OTUs affiliated with members of 2. The tumorigenesis in the colon of germ-free mice transplanted with the fecal microbiota from mice with tumor is increased. |
| Celia Dingemanse et al.[ | Mouse | CRC | Shotgun metagenomic sequencing plus quantitative PCR is used to analyze the gut microbiota in intestine-specific conditional | 1. Metagenomic sequencing shows that the genus 2. The oral gavage of 3. |
Fig. 4A schematic diagram of workflow on the precise application of NGP.
All figures are created with Biorender.com.