|Year : 2022 | Volume
| Issue : 5 | Page : 495-503
|Analysis of alterations of the gut microbiota in moderate to severe psoriasis patients using 16s rRNA gene sequencing
Xiaomeng Wang1, Zheng Chen1, Song Qiao1, Qiming Zhu1, Zongbao Zuo2, Birong Guo1
1 Department of Dermatology, The Third Affiliated Hospital of Anhui Medical University, The First People's Hospital of Hefei, Hefei, Anhui, China
2 Department of Plastic Surgery, The Second People's Hospital of Anhui Province, Hefei, Anhui, China
|Date of Web Publication||29-Dec-2022|
Department of Dermatology, The Third Affiliated Hospital of Anhui Medical University, The First People's Hospital of Hefei, Huaihe Road and 390, Hefei, Anhui - 230000
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Psoriasis is an inflammatory skin disease. The correlation between intestinal microbiota and immune-mediated diseases makes scientists pay attention to the pathogenic role of microbiota. Objective: The aim of this study was to identify the gut microbial composition of patients with psoriasis. Methods: 16S rRNA gene sequencing method was used to analyse the faecal samples which was collected from 28 moderately severe psoriasis patients and 21 healthy controls and was followed by the analysing of informatics methods. Results: No visible differences can be observed in the diversity of gut microbiota between the psoriasis and the healthy patients, but the composition of the gut microbiota illustrate significant distinction between these two groups. At the phylum level, compared to the healthy control group, the psoriasis group shows higher relative abundance of Bacteroidetes and lower relative abundance of Proteobacteria (P < 0.05). At the genus level, unidentified_Enterobacteriaceae, unidentified_Lachnospiraceae, Romboutsia, Subdoligranulum, unidentified_Erysipelotrichaceae, Dorea were relatively less abundant in psoriasis patients, whereas Lactobacillus, Dialister were relatively more abundant in psoriasis group (all P < 0.05). LefSe analysis (linear discriminant analysis effect size) indicated that Negativicutes and Bacteroidia were potential biomarkers for psoriasis. Conclusion: This study identified the intestinal microecological environment of patients with psoriasis and healthy people, proving that psoriasis patients have a remarkably disturbed microbiome, and found several biomarkers of intestinal microorganisms in patients with psoriasis.
Keywords: 16S rRNA gene, intestinal microorganism, psoriasis
|How to cite this article:|
Wang X, Chen Z, Qiao S, Zhu Q, Zuo Z, Guo B. Analysis of alterations of the gut microbiota in moderate to severe psoriasis patients using 16s rRNA gene sequencing. Indian J Dermatol 2022;67:495-503
|How to cite this URL:|
Wang X, Chen Z, Qiao S, Zhu Q, Zuo Z, Guo B. Analysis of alterations of the gut microbiota in moderate to severe psoriasis patients using 16s rRNA gene sequencing. Indian J Dermatol [serial online] 2022 [cited 2023 Feb 8];67:495-503. Available from: https://www.e-ijd.org/text.asp?2022/67/5/495/366118
| Introduction|| |
Psoriasis is considered as a kind of chronic inflammatory autoimmune skin disease affecting about 2% of the world's population.,,, There are five categories that can be divided as plaque psoriasis (also known as psoriasis Vulgaris), guttate (droplet) or eruptive psoriasis, inverse psoriasis, pustular psoriasis and erythrodermic psoriasis, while the most common condition is chronic plaque psoriasis (psoriasis vulgaris), which accounts for around 90% of all cases. Although the aetiology remains poorly understood, it is generally considered to be the result of the interplay among genetic, epigenetic factors and environmental influences.
In recent years, the relationship between gut microbiota and immune-mediated diseases has drawn people's attention to the pathogenic role of the intestinal microbiota. For example, as for some systemic immune diseases (e.g. rheumatoid arthritis, inflammatory bowel disease (IBD), type 1 diabetes, and asthma), it had been proved that the dysbiosis in the gut microbiota can play an important role in the development of or predisposition for these diseases.,,, Moreover, the meticulous profound study of gut microbiome may lead to a more comprehensive understanding of the potential role in the pathogenesis of skin diseases. Meanwhile, the investigation of the association between the gut microbiome and the dermatologic conditions significantly complements our knowledge of the pathogenic role of psoriasis, rosacea, atopic dermatitis, scleroderma, acne, and so on. All these researches demonstrate that there is an intimate relationship between the gut microbiota and the stability of the intradermal environment.,,,
Given the overwhelming evidence that the dysbiosis of the gut microbiota may contribute to the pathogenesis of chronic inflammatory disease, the question whether there is a causal relationship between gut microbes and psoriasis has arisen.
Until now, several studies have shown that microbial infections are not only a risk or aggravating factor for psoriasis, but they may also be the cause of increased inflammation in psoriasis., What is more, a growing number of animal and human studies suggest that gut microbiota may play a role in the pathogenesis of psoriasis.,, Therefore, to evaluate the specificity of intestinal bacteria in psoriasis patients and to investigate the link between psoriasis and gut microbiota, we collected faecal samples from both psoriasis patients and healthy controls and analysed the microbiota by informatics methods.
| Materials and Methods|| |
We collected 28 patients with chronic plaque psoriasis from September 2019 to December 2020. The diagnosis of psoriasis was confirmed as chronic plaque psoriasis by a dermatologist who provided written, informed consent to participate. The patients included in this study were all adults, aged between 18 and 65, and ten of them were female, and they had a Psoriasis Area and Severity Index (PASI) score of ≥12 (baseline characteristics are described in [Table S1]). Patients were excluded from this group if they receive antibiotics or psoriasis-related treatment for at least 1 month prior to the collection of stool samples. In the control group, the same sex, race and age (±5 years) as the patient group were selected as the healthy control group (aged 20–64 years). No history of psoriasis was found, and those who met any of the following conditions were excluded: previous diagnoses of gastrointestinal diseases (such as Celiac disease, IBD, food allergies, lactose intolerance, cirrhosis of the liver, chronic pancreatitis and gastrointestinal malabsorption), glomerular filtration rate <60 mL min * 1.73 m2, pregnant women.
Sample collection and DNA extraction
All samples were collected by the same experimenter using a sterile cup to collect fresh faeces of the researchers, the collection process strictly follow the sterile principle, so as to avoid contamination of the samples by the environment. All stool samples were stored in a freezer at −80°C for 30 min after collection. Total genomic DNA was extracted by CTAB/SDS method. The concentration and purity of DNA were determined by 1% agarose gel. Dilute the DNA with sterile water to 1 ng/μL according to the concentration.
PCR amplification, Library preparation and sequencing
We selected specific primers to attach to the unique barcodes and amplified the V4 region of the 16SrRNA gene (515F,5'-GTGCCAGCMGCCGCGGTAA-3'; 806R,5'-GGACTACNNGGGTATCTAAT-3'). All PCR reactions were performed in 30 μL reactions with 15 μL of Phusion® High-Fidelity PCR Master Mix (New England Biolabs), 0.2 μM of forward and reverse primers, and about 10 ng template DNA. The PCR cycling conditions composed of initial denaturation at 98°C for 1 min, then 30 cycles of denaturation at 98°C for 10 s, annealing at 50°C for 30 s, and elongation at 72°C for 30 s. Lastly with extension at 72°C for 5 min (The results of agarose gel electrophoresis are showed in [Figure S1], [Figure S2], [Figure S3]).
Sequencing library generation using Ion Plus Fragment Library Suite 48 RXNS (Thermal Science) follows manufacturer's recommendations. The quality of the library was evaluated using [email protected] fluorometer (Thermo Scientific). Finally, 400/600 bp single-ended reading fragments were generated by sequencing on ION S5TM XL platform.
The clean reads of high quality can be obtained through the CUTADAPT (V1.9.1) quality control process by quality filtering of sequencing data under specific filtering conditions. Using the UCHIME algorithm (UCHIME algorithm), we compare the reads with the reference database (Silva Database) to detect the chimera sequences, and then remove the chimera sequences, finally Clean Reads were obtained. The UPARSE software (Uparsev7.0.1001) were used for the sequence analysis. And the sequences with similarity ≥97% were assigned to the same OTU's. Alpha diversity was used to analyse the complexity of species diversity in a sample or population by four indices: Chao1, Shannon, Simpson and abundance-based coverage estimator (ACE), which were calculated with Quantitative Insights into Microbial Ecology (QIIME Version 1.7.0). To evaluate the differences in community structure between groups (beta diversity), weighted UniFrac distances were calculated using QIIME. The WGCNA, stat and GGPLOT2 packages in R software are used to construct the principal coordination analysis (PCOA) plots based on weighted UniFrac distance. The linear discriminant analysis effect (LefSe) was used to detect significant changes in the relative abundance of microbiota at all levels (biomarkers) between groups.
| Results|| |
Based on the IonS5 TMXL platform, V4 regions of 16S rDNA were sequenced from stool samples of 28 psoriasis patients and 21 healthy controls by single-end sequencing. Through shearing and filtering of reads, 84,172 effective data were obtained through quality control. A total of 1,437 OTUs were obtained by clustering the sequences at 97% sequence similarity (raw and clean number of sequences can be found at [Supplementary Table S1]). A Venn diagram visually displayed the number of common/unique OTUs in multi-samples/groups, and the result showed that approximately 68% of the OTUs were shared between the two groups, while 209 and 245 OTUs were individual to healthy control and psoriasis groups, respectively, as shown in [Figure 1].
|Figure 1: Venn diagram showed the difference in OTUs in psoriasis and healthy control groups. Each circle in the diagram represents each (group) sample. The numbers of the circles and the overlapping parts of the circles represent the total number of OTUs between the samples (groups). The numbers without the overlapping parts represent the unique number of OTUs of the samples (groups)|
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Community richness and diversity
The species richness was estimated by ACE index and Chao index, and the species diversity and evenness were estimated by Simpson index and Shannon index, respectively. Through the Wilcoxon rank-sum test, the results showed that there was no significant difference in Shannon, Simpson, Chao1, Ace between the PSO Group and the Healthy Group [Figure 2]. Although there was no significant difference between the two groups, the diversity of psoriasis patients decreased slightly compared with the healthy control group.
|Figure 2: ACE (a), chao1 (b), Shannon (c) and Simpson (d) index among psoriasis patients (PSO) and healthy individuals groups (Control) were separately visualized by box plots based on their quartiles|
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Significant differences in the intestinal microflora between psoriasis patients and healthy individuals
Bacterial communities of healthy controls and patients with psoriasis were analysed. The overall microbial composition of both the groups at each rank are shown in [Figure 3]. Principal Coordinate Analysis (PCoA) was used to get principal coordinates and visualize from complex, multidimensional data. We perform a PCoA analysis based on Unweighted UNIFRAC distances and select the combination of principal coordinates with the highest contribution, as shown in [Figure 4]. The results showed that there was a significant segregation of microbial community composition between psoriasis patients and healthy individuals, the scores of PC1 and PC2 were 14.87% and 12.15%, respectively. The significant separation indicated obvious differences in the community structure between the two groups. At the phylum level, the results revealed that the most major phylum of the intestinal microbiota in both healthy controls and psoriasis patients was Firmicutes, with a proportion of 66.32% and 58.48%, respectively. Bacteroidetes were the second most dominant phylum in the healthy group and the psoriasis group (accounting for 19.10% and 34.68%, respectively, P = 0.0153). Besides, the proportion of Proteobacteria was 13.11% and 3.02%, respectively (P = 0.026), and that of Actinobacteria was 1.21% and 3.28%. At the genus level, we identified the presence of eight different genera in which the abundance of bacteria was >1%. The T test showed that unidentified_Enterobacteriaceae, unidentified_Lachnospiraceae, Romboutsia, Subdoligranulum,
|Figure 3: Top ten bacteria Phylum (a), Class (b), Order (c), Family (d), Genus (e), Species (f) of relative abundance between psoriasis patients (PSO) and healthy individuals groups (Control)|
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|Figure 4: PCOA: Horizontal and vertical coordinates are the first and second principal components, respectively, and the percentage represents the explanation of the principal component for the sample difference; each point in the figure represents a sample, and the same group of samples are represented by the same colour|
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unidentified_Erysipelotrichaceae, Dorea were relatively less abundant in psoriasis patients, whereas Lactobacillus, Dialister were relatively enriched in psoriasis patients (all P < 0.05). The composition of faecal bacteria which is significantly different between the two groups were shown in [Figure 5]. The details are in [Table S2], [Table S3], [Table S4], [Table S5], [Table S6], [Table S7] (supplementary information).
|Figure 5: The results of species difference analysis diagrams between T_TEST groups of all taxonomic levels (Phylum (a), Class (b), Order (c), Family (d), Genus (e), Species (f)). The figure on the left shows the abundance of species with significant differences between the groups. Each bar in the figure represents the mean value of species with significant differences in abundance between groups in each group. The right graph shows the confidence of inter-group differences. The leftmost endpoint of each circle in the graph represents the lower 95% confidence interval of the mean difference, and the rightmost endpoint of each circle represents the upper 95% confidence interval of the mean difference. The center of the circle is the difference of the mean. The groups represented by the circle colour are the groups with the highest mean value. At the far right of the results are the P values of the inter-group significance test for the species that differ|
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To identify the specific bacterial taxa associated with psoriasis, LEfSe was used to compare the composition of gut microbiota. The results of LEfSe analysis of PSO–Control showed that there were 16 biomarkers of LDA >4 [Figure 6]. Among them, Negativicutes and Bacteroidia were the key bacteria with high relative abundances that conduce to the dysbiosis of microbiota in psoriasis patients. In the healthy control group, Enterobacteriales and Clostridiales were revealed as the key types of bacteria [Figure 6]a and [Figure 6]b.
|Figure 6: (a) The histogram of LDA value distribution shows that the LDA score is higher than the set value of the species (default setting is 4), that is, the biomarkers in the various groups have statistical differences. It shows that there are significant differences in abundance between groups, and the length of the histogram indicates the size of the impact of different species (LDA score). (b) In the cladistics, a circle radiating inward and outward indicates a taxonomic level from a phylum to a genus (or species). Each small circle at the different classification level represents the classification at that level, and the diameter of the circle is proportional to the relative abundance. Colouring principle: species with no significant difference are uniformly coloured yellow, and the difference species, Biomarker, is coloured according to the group, and the red nodes represent the microbial communities that play an important role in the red group. The green nodes represent microbiota that play an important role in the green group. The names of the species in English letters are shown in the legend on the right|
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| Discussion|| |
Psoriasis is considered a chronic inflammation disease, promoted by Th1, Th17, and TH22 cells, resulting in Keratinocyte proliferation.,, The data so far suggest that dysbiosis of the gut microbiota can contribute to several immune disorders through promotion of regulatory T cells. Profiling studies have recently identified the possibility that gut microbiota are also related to the development and/or pathogenesis of psoriasis.
Findings on species richness of gut microbiota in psoriasis patients reported by different studies were inconsistent. In a study by Scher and colleagues, they found that the gut microbiota in psoriatic arthritis and psoriasis of the skin patients was less diverse, compared to healthy controls. While another study found that the microbiome in psoriasis patients was shown more diverse than healthy controls. In contrast, in the present study, we found that there are no significant differences between the two groups, but subjects with psoriasis showed slightly decreased diversity compared to healthy controls. which is in agreement with the findings in Tan's study. This suggests that alteration of richness of species may not be the dominant feature in psoriasis patients.
Studies have also compared the composition of the gut microbiome between the psoriatic patients and the healthy controls. At the phylum level, both Masallat's study and Scher's study found that psoriasis patients had lower levels of Actinobacteria compared to controls., Tan's group found that the relative abundance of Verrucomicrobia and Tenericutes were significantly decreased in psoriatic patients. Another study conducted with 35 psoriasis patients and 27 healthy controls in Huang's group found that the Firmicutes was more abundant in healthy individuals. At the class and order level, Tan's group found that the abundance of Mollicutes and Verrucomicrobiae, as well as Verrucomicrobiaes and RF39, was reduced in psoriatic patients. Huang's group found that Bacteroidia was in higher abundance in the microbiota of psoriasis patients and was the key type contributing to the dysbiosis of microbiota in psoriasis patients, which is consistent with the findings of our study. At the family level, Tan's group found that the relative abundance of Verrucomicrobiaceae and S24-7 was decreased, whereas the relative abundance of Bacteroidaceae and Enterococcaceae was enriched in psoriasis. At the genus level, Scher and colleagues found psoriasis patients had lower Parabacteroides and Coprobacillus than healthy controls. In Huang's study, 16 kinds of phylotype were found with significant difference. In addition, Tan's group found that Akkermansia was less abundant, while the abundance of Enterococcus and Bacteroides was enriched in psoriatic patients.
The large intestine microbiome is composed of five major phyla: Firmicutes, Bacteroidetes, Verrucomicrobia (mainly the genus Akkermansia), Proteobacteria and Actinobacteria. Here, we found that Firmicutes, Bacteroidetes and Proteobacteria were the dominant ones, and the phylum Bacteroidetes were increased in the gut microbiota of psoriatic patients, while the phylum Proteobacteria were depleted in psoriatic patients. What is more, at the class level, we found that Negativicutes and Bacteroidia were more abundant in psoriatic patients, Other researchers have found that Negativicutes were predominant among the obese T2DM patients. At the family level, Veillonellaceae is enriched in psoriatic patients. It was found that Veillonellaceae is more abundant in patients with Crone disease confirming the presence of a gut-skin axis in both psoriasis and IBD, and Huang's study also proved that the abundance of genus Veillonellais was higher in intestinal mucosa psoriasis patients. At the genus level, we found a lower relative abundance of Subdoligranulum and Romoutsia. Indeed, one association study have indicated that Subdoligranulum genus is related to a healthier metabolic status. Furthermore, several human studies revealed that the increase of Subdoligranulum was related to improved metabolic health including in intervention with prebiotics.,,
Romoutsia is a newly described genus of bacteria first isolated in 2014 by Jacoline Gerritsen et al. from the gastrointestinal tract of a rat, a species of Gastrococci. Many of these members are common gut microbes, including the well-known Clostridium Difficile and Escherichia coli. All species belonging to this genus are obligate anaerobe, commonly found in the human gut and associated with the patient's state of health., Polypoid-related mucosal lesions were found to have a sharp reduction in this particular genus member, which may be a potential microbial indicator of disease status. Another study of the gut microflora of colorectal polyps found that Romoutsia appeared to be depleted in carcinogen-causing mucosa and adenomatous polyps, suggesting that it may represent a new microbial biomarker associated with early colorectal tumor formation. Dietary polyphenol is considered as a new type of prebiotic, which can play a role by regulating the intestinal microflora. It was found that the probiotics increased the relative abundance of Romboutsia in the intestinal tract, suggesting that Romboutsia may have a potential role in the regulation of the stability of the microflora.
An animal model study of obesity in mice found that obese mice with a high fat diet improved their imbalanced gut microbiota after treatment, it indicated that the relative abundance of Romboutsia increased in the gut microbiome of the treated mice, suggesting a potential link between the reduction of Romboutsia and the onset of obesity, as well as its role in maintaining intestinal stability and health.
We also found that the psoriatic group showed a greater abundance of Megamonas. Studies have shown that there was a positive correlation between genus Megamonas and systemic inflammatory cytokines, which may promote the inflammatory response in metabolic diseases. In a study of the link between Type 2 diabetes and gut microbiota, Megamonas was also identified as a biomarker of Type 2 diabetes. Moreover, a study of childhood obesity in Mexico showed that the number of Megamonas was twice that of normal weight children, according to the report, members of the genus isoprene contribute to the biosynthesis of isoprene cholesterol via the propionic acid-mediated pyruvic acid pathway and Alanine,, which may explain their abundance in obesity. In addition, in a separate report, a decrease in the abundance of the intestinal microflora of adults treated with oral anticholesterol drugs in Africa and China was observed to increasing its role in cholesterol biosynthesis.
Taken together all the above results show an increase in harmful microbes and a decrease in beneficial microbes in psoriasis patients, which may confirm the hypothesis that dysbiosis of the gut microbiota may contribute to the development of psoriasis. Besides, epidemiological studies have found that psoriasis is associated with the components of the metabolic syndrome, particularly obesity and type 2 diabetes mellitus. It was shown that obesity and type 2 diabetes are about twice as prevalent in patients with psoriasis compared with the general population., This association between psoriasis and metabolic syndrome may be related to genetics, e environmental exposures, and shared immune inflammatory pathways. Here, we found that changes in certain intestinal flora in patients with psoriasis were consistent with the changes in patients with type 2 diabetes and obesity, thus providing a new idea for understanding the pathogenesis of psoriasis.
| Conclusion|| |
Our study shows that the composition of intestinal microflora of psoriasis has changed, and reveals the relationship between psoriasis and intestinal microbes, offering a novel insight to understand the pathogenesis of psoriasis through the human intestinal microflora. However, the question of “cause or effect?” still remains unknown. Moreover, we described only the characteristics of microbiome, not its effects on the immune system, whereas how the microbiome alters immune function still remains an important issue. Besides, only 49 samples were analysed in this study. Further work should be carried out to verify the number of samples. What is more, future larger-scale and longitudinal studies that include functional metagenomic and metabolomic analysis should be added to enhance the understanding of the relationship between gut microbiota and psoriasis and to provide new insights into the preventative or therapeutic strategies.
We thank the third Affiliated Hospital of Anhui Medical University for providing valuable powerful support with sampling.
Statement of ethics
All procedures performed in the studies involving human participants were in accordance with the ethical standards of the Clinical Medical Ethics Committee of Third Affiliated Hospital of Anhui Medical University and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Written informed consent was obtained from all subjects included in the study.
XMW and BRG conceived and designed the hypotheses and performed the study and analysis and. All the authors contributed to the scientific discussion of the data and of the manuscript. All the authors performed the experiments. XMW wrote the paper. BRG reviewed and edited the manuscript. All the authors contributed to the scientific discussion of the data and of the manuscript.
Financial support and sponsorship
This work was supported by the grants from the National Natural Science Foundation of China (No. 81301352), the Anhui Provincial Hefei City Program (No. hwk2017yb008), the Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support (No. 20161417), and the Research Fund of Anhui Medical University (No. 2020xkj238).
Conflicts of interest
There are no conflicts of interest.
| Supplementary Information|| |
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