key: cord-0928444-2l4ql6k9
authors: Shinno-Hashimoto, Hiroyo; Hashimoto, Yaeko; Wei, Yan; Chang, Lijia; Fujita, Yuko; Ishima, Tamaki; Matsue, Hiroyuki; Hashimoto, Kenji
title: Abnormal composition of microbiota in the gut and skin of imiquimod-treated mice
date: 2021-05-28
journal: Sci Rep
DOI: 10.1038/s41598-021-90480-4
sha: 1a1341e478c87c634287bdb4517c9b28cd8b205a
doc_id: 928444
cord_uid: 2l4ql6k9

Psoriasis is a chronic, inflammatory skin disease. Although the precise etiology of psoriasis remains unclear, gut–microbiota axis might play a role in the pathogenesis of the disease. Here we investigated whether the composition of microbiota in the intestine and skin is altered in the imiquimod (IMQ)-treated mouse model of psoriasis. Topical application of IMQ to back skin caused significant changes in the composition of microbiota in the intestine and skin of IMQ-treated mice compared to control mice. The LEfSe algorithm identified the species Staphylococcus lentus as potential skin microbial marker for IMQ group. Furthermore, there were correlations for several microbes between the intestine and skin, suggesting a role of skin–gut–microbiota in IMQ-treated mice. Levels of succinic acid and lactic acid in feces from IMQ-treated mice were significantly higher than control mice. Moreover, the predictive functional analysis of the microbiota in the intestine and skin showed that IMQ caused alterations in several KEGG pathways. In conclusion, the current data indicated that topical application with IMQ to skin alters the composition of the microbiota in the gut and skin of host. It is likely that skin–gut microbiota axis plays a role in pathogenesis of psoriasis.

www.nature.com/scientificreports/ Composition of skin microbiota. The composition of the microbiota on the back skin was analyzed.

Mann-Whitney U-test showed significant differences in the observed OTUs, ACE, and Shannon ( Fig. 3a-c) . Beta-diversity analysis using PCA demonstrated significant differences between IMQ group and control group (ANOSIM, R = 1.000, P = 0.001) (Fig. 3d) . Furthermore, significant separation was observed between the two groups on PCoA of weighted UniFrac distances (ANOSIM, R = 0.7293, P = 0.001) (Fig. 3e) .

LEfSe difference analysis showed that IMQ group produced significant differential effects on skin microbiota (Fig. 3f) . Six mixed-level phylotypes, including the species Staphylococcus lentus, the genus Staphylococcus, the family Staphylcoccaceae, the order Bacillales, the class Bacilli, and the phylum Firmicutes were identified as potential skin microbial markers for the IMQ group (Fig. 3g) .

Composition of the skin microbiota at the taxonomic level. At the phylum level, the abundance of Firmicutes, Proteobacteria, Cyanobacteria, Actinobacteria, and Bacteroidetes was significantly different between the two groups ( Figure S4 and Table S3) . At the genus level, the most abundant bacteria on the skin of IMQtreated mice was Staphylococcus (the mean = 98.5%) whereas the level of Staphylococcus on the skin of control mice was low (the mean = 16.2%) ( Figure S5 ). Furthermore, the abundance of sixteen bacteria was significantly different between the two groups ( Figure S5 and Table S4) . At the species level, the most abundant bacteria on the skin of IMQ-treated mice was Staphylococcus lentus (the mean is 93.5%) whereas the level of Staphylococcus lentus on the skin of control mice was very low (the mean is 7.14%) ( Figure S6 ). Furthermore, the abundance of fourteen bacteria were significantly different between the two groups ( Figure S6 and Table S5 ).

Correlations between the skin microbiota and the gut microbiota. At the species level, we found several microbes which were significantly altered in the intestine and on the skin between the two groups (Tables S2 and S5) . Interestingly, there were negative correlations for Lactobacillus intestinalis, Lactobacillus reuteri, and Lactobacillus taiwanensis between the intestine and the skin (Fig. 4a-c) . In contrast, there was a positive correlation for Staphylococcus lentus between the intestine and the skin (Fig. 4d) . www.nature.com/scientificreports/ SCFAs in fecal samples and their correlations with the relative bacterial abundance. The levels of succinic acid and lactic acid in the IMQ group were significantly higher than the control groups (Table 1 ). In contrast, there were no changes for acetic acid, propionic acid, and n-butyric acid between the two groups (Table 1) . Next, we examined the possible correlations between the relative abundance of microbes and SCFA levels in fecal samples. The succinic acid was significantly correlated with the relative abundance of the genus Parabacteroides (r = − 0.464, P = 0.0393) (Fig. 5a) , the genus Staphylococcus (r = 0.4981, P = 0.0254) (Fig. 5b) , the species Parabacteroides distasonis (r = − 0.485, P = 0.0302) (Fig. 5c) , the species Staphylococcus lentus (r = 0.4807, P = 0.0319) (Fig. 5d ) and the species Lactobacillus intestinalis (r = 0.4492, P = 0.0469) (Fig. 5e ) in the two groups. A significant negative correlation between the relative abundance of the genus Parabacteroides (r = − 0.5079, P = 0.0222) and lactic acid was observed in two groups (Fig. 5f ).

Predictive functional metagenomes. In gut microbiota, two pathways on KEGG level 2, including cardiovascular disease, and endocrine and metabolic disease were significantly different between the two groups ( Fig. 6 ). In skin microbiota, four pathways on KEGG level 3, including sphingolipid signaling pathway, coronavirus disease (COVID-19), steroid degradation, and renin secretion were significantly different between the two groups ( Fig. 7 ).

The major findings of this study were as follows. First, topical application of IMQ to skin caused psoriasis-like phenotypes in mice. Second, IMQ caused significant alterations in the alpha-and beta-diversity of the microbiota in the intestine and on the skin. The LEfSe algorithm of gut microbiota identified the species Lactobacillus intestinalis, Lactobacillus reuteri, and Bacteroides uniformis as potential gut microbial markers for the IMQ group. Furthermore, the LEfSe algorithm of skin microbiota identified the species Staphylococcus lentus as potential skin microbial marker for the IMQ group. Interestingly, correlations for several microbes between the intestine and the skin were observed, suggesting a role of skin-gut-microbiota in IMQ-treated mice. Third, levels of succinic www.nature.com/scientificreports/ acid and lactic acid in feces increased in the IMQ group compared to control group. Interestingly, we found that the levels of succinic acid (or lactic acid) were correlated with the relative abundance of several microbes in the fecal samples. Finally, the predictive functional analysis of the microbiota of gut and skin showed that IMQ caused alterations in several KEGG pathways. Taken all together, the present data show that topical treatment with IMQ alters the composition of the microbiota in the intestine and on the skin of host. At the species level, the three Lactobacillus microbes such as Lactobacillus intestinalis, Lactobacillus reuteri, and Lactobacillus taiwanensis were significantly higher in the intestine of IMQ-treated mice compared to control mice. A recent study showed that Lactobacillus intestinalis and Lactobacillus reuteri may be responsible for the depression-like behavior in mice after transplantation of "depression-related microbes" 40 . The increased abundance of Lactobacillus intestinalis, Lactobacillus reuteri and Lactobacillus taiwanensis by IMQ treatment may contribute to the increased levels of lactic acid in the IMQ-treated mice since Lactobacilli ferment lactose into lactic acid 41 . Collectively, it is likely that increased abundance of Lactobacillus bacteria may contribute to increased levels of lactic acid in the host gut although further detailed study is needed. Considering the beneficial actions of Lactobacillus reuteri on the host immune system 41, 42 , it seems that IMQ-induced increases in the abundance of bacteria might reflect a compensatory response in the host. There are many species of Lactobacillus which may have beneficial and harmful effects in the host 43 . Nonetheless, future studies are needed to investigate the mechanisms underpinning increases of these Lactobacillus bacteria in the intestine of IMQ-treated mice.

Furthermore, we found significant differences for Bacteroides uniformis, Bacteroides acidifaciens, Bacteroides sartorii, Staphylococcus lentus and Parabacteroides distasonis in the intestine between the two groups. As far as we know, there are no reports showing alterations in these three Bacteroides bacteria in IMQ-treated mice and patients with psoriasis. Pretreatment with the antibiotic metronidazole increased the abundance of www.nature.com/scientificreports/ Parabacteroides distasonis in the intestine of IMQ-treated mice 30 . In contrast, Parabacteroides distasonis were significantly decreased in the patients with psoriasis 44 . At the species level, we found many skin microbes which altered in the IMQ-treated mice (Table S5) . Importantly, the most abundant microbe on the skin from IMQ-treated mice was Staphylococcus lentus, and the abundance of Staphylococcus lentus in the IMQ-treated mice were significantly higher than control mice (Table S5) . Staphylococcus lentus are commensal bacterium colonizing the skin of animals and has been associated with infections in animals 45 . It seems that high abundance of Staphylococcus lentus may play a role in IMQ-induced psoriasis-like symptoms in mice. However, the precise mechanisms underlying high abundance of Staphylococcus lentus on the skin of IMQ-treated mice are currently unclear. Further study is needed to examine the role of Staphylococcus lentus in psoriasis-like symptom of IMQ-treated mice.

In this study, we found several microbes which altered in the both intestine and skin. Interestingly, we found significant correlations for Lactobacillus intestinalis, Lactobacillus reuteri, Lactobacillus taiwanensis, and Staphylococcus lentus between the intestine and the skin. To the best of our knowledge, this is the first report showing the correlations for microbes in both the intestine and the skin, supporting the skin-gut microbiota axis 46, 47 . From the current data, it is unclear whether changes in gut microbiota can affect skin microbiota or these two phenomena are independent. In this study, we found that topical treatment with IMQ caused increased volume of spleen through systemic inflammation, resulting in abnormal changes in the microbiota composition in the intestine and on the skin of mice. Although the precise mechanisms underlying the association between the skin and the intestine remain unclear, the current data strongly suggest a role of skin-gut microbiota axis in IMQtreated mice. Therefore, it is of great interest to investigate whether the composition of microbiota in the intestine and on the skin from patients with psoriasis is altered compared to healthy control subjects.

Succinic acid is produced in large amounts during bacterial fermentation of dietary fiber, and it is considered as a key intermediate in the synthesis of propionic acid 48, 49 . Interestingly, germ-free mice have little or no detectable levels of succinic acid in feces compared to conventional mice, indicating that gut microbiota are the predominant source for succinic acid. Higher levels of succinic acid may be related with high abundance of Bacteroides in fecal samples since succinic acid is produced by primary fermenters such as Bacteroides 49 . It is also shown that elevated levels of succinic acid in the feces are associated with intestinal inflammation 48, 49 . Collectively, higher levels of succinic acid in the feces of IMQ-treated mice might be associated with intestinal inflammation although further study is needed.

To understand the role of altered composition of microbiota in the intestine and skin of IMQ-treated mice, we examined the predictable function of the microbiota. The current data show that IMQ treatment may contribute to the altered metabolism (i.e., cardiovascular disease, and endocrine and metabolic disease) induced by gut microbiota. In addition, the current data show that IMQ treatment could produce the altered metabolism (i.e., sphingolipid signaling pathway, coronavirus disease-COVID-19, steroid degradation, and renin secretion) www.nature.com/scientificreports/ induced by skin microbiota. It is noteworthy that we could detect the altered metabolism of endocrine disease in IMQ-treated mice since the neuroendocrine system plays a role in the skin function 31, 32 . Furthermore, it is likely that gut microbiota is more complex than skin microbiota since we detected many pathways for gut microbiota compared to skin microbiota. Taken together, it is likely that these KEGG pathways provide a new functional view for understanding the gut and skin microbiota that contribute to psoriasis-like symptoms. Finally, this study has a potential limitation. A future study using antibiotic cocktail is needed to ascertain the correlation between skin microbiota and gut microbiota in IMQ-treated mice.

In conclusion, this study shows that topical treatment with IMQ causes abnormal changes in the microbiota composition in the intestine and on the skin of adult mice, and that levels of succinic acid were associated with the relative abundance of several microbes. Furthermore, we found correlations for several microbes between the intestine and the skin, suggesting a role of skin-gut microbiota in psoriasis.

Relative abundance of KEGG pathways of functional categories in the gut microbiota. Functional predictions of the gut microbiota between the control group and IMQ group. Significant differences of KEGG pathways at level 2 were detected using STAMP software based on the KEGG pathway database (www. kegg. jp/ kegg1. html). *P < 0.05. 

Animals. Female C57BL/6 mice (9 weeks old, weighing 18-21 g, n = 20, Japan SLC Inc., Hamamatsu, Shizuoka, Japan) were used. Mice were housed (5 per cage) under a 12-h/12-h light/dark cycle (lights on between 07:00 and 19:00), with ad libitum access to food access to food (CE-2; CLEA Japan, Inc., Tokyo, Japan) and water. The experimental protocol was approved by Chiba University Institutional Animal Care and Use Committee (Permission number: 2-433) 50 . This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health, USA 50 . This study was also carried out in compliance with the ARRIVE guidelines. All efforts were made to minimize animal suffering.

The shaved back skin of mice was treated with 62.5 mg of 5% IMQ cream (Beselna cream; Mochida Pharmaceutical Co., Tokyo, Japan) daily for 5 consecutive days. Control mice were treated similarly with 62.5 mg of white petrolatum (Maruishi Pharmaceutical Co., Osaka, Japan). Skin, fecal and spleen samples were collected on day 6. The clinical skin score was measured on day 1 and day 6. The degree of skin inflammation was scored by cumulative disease severity score, similar to the human Psoriasis Area and Severity Index, but not taking the area into account. Erythema, scaling, and thickening were scored independently from 0 to 4: 0, none; 1, slight; 2, moderate; 3, marked; 4, very marked. The single scores were summed, resulting in a theoretical maximal total score of 12 27 . Fresh fecal samples of mice were collected from 7:30 to 8:30 on day 6 to exclude any circadian effects on the microbes. The fecal samples were placed into sterilized screw-cap microtubes immediately after defecation, and they were frozen in liquid-nitrogen immediately. The samples were stored at − 80 °C until use 51 .

Skin swabs from the shaved back skin of IMQ-treated mice or control mice were put into extraction tube containing a solution (0.15 M NaCl and 0.1% Tween20) and rotated for at least 20 times. After squeezing as much liquid as possible from the swab by pushing the swabs against the sides of the tubes, the tubes were stored at − 80 °C until analysis.

Histology. Back skin samples from control and IMQ-treated groups were collected and fixed in 10% formalin (FUJIFILM Wako Pure Chemical Corp.). Staining with hematoxylin and eosin (HE) was performed at Biopathology Institute Co., Ltd (Kunisaki, Oita, Japan). Back skin samples were embedded in paraffin, and sections of 3 μm were prepared and subjected to HE staining. Representative images of two groups were obtained using a Keyence BZ-9000 Generation II microscope (Osaka, Japan).

16S rRNA analysis. The DNA extractions from the fecal and skin samples and 16S rRNA sequencing analyses were performed by MyMetagenome Co., Ltd. (Tokyo, Japan), as reported previously 40, [50] [51] [52] . DNA extraction from mouse samples and purification were performed according to the method of the previous report 53, 54 . The 16S rRNA analysis of samples was performed as previously reported 53, 54 . Briefly, PCR was performed using 27Fmod 5′-AGR GTT TGATYMTGG CTC AG-3′ and 338R 5′-TGC TGC CTC CCG TAG GAG T-3′ to amplify the V1-V2 region of the bacterial 16S rRNA gene. The 16S amplicons were then sequenced using MiSeq according to the Illumina protocol. Taxonomic assignment of OTUs was made by similarity searches against the Ribo- www.nature.com/scientificreports/ somal Database Project and the National Center for Biotechnology Information genome database using the GLSEARCH program.

Alpha diversity was used to analyze the species diversity, composed of richness and evenness, within a sample through three indices including the observed OTU, ACE, and Shannon indices 55 . Beta diversity was used to measure differences of species diversity among samples, including PCA and PCoA with ANOSIM. Differences in bacterial taxa between groups at the species or higher level (depending on the taxon annotation) were calculated based on linear discriminant analysis (LDA) effect size (LEfSe) using LEfSe software (LDA score > 4.0, P < 0.05) (https:// www. omics tudio. cn/ tool/) 56 . Prediction of functional profiles of gut microbiota using PICRUSt. Using the 16S rRNA gene sequencing data and KEGG (Kyoto Encyclopedia of Genes and Genome) orthology (http:// www. kegg. jp/ kegg1. html) 57 , we performed PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) analysis and STAMP (Statistical Analysis of Metagenomic Profiles) software v2.1.3 (http:// kiwi. cs. dal. ca/ Softw are/ STAMP) for the functional prediction of microbiota in the intestine and skin 55,58,59 . Measurement of short-chain fatty acid (SCFA) levels. Concentrations of SCFAs (i.e., acetic acid, propionic acid, butyric acid, lactic acid, succinic acid) in fecal samples were measured at TechnoSuruga Laboratory, Co., Ltd. (Shizuoka, Japan), as reported previously 50, 51, 55, 60 . The data of SCFAs were shown as milligrams per gram of feces. Statistical analysis. Data are shown as the mean ± standard error of the mean (S.E.M.). Alpha-diversity of the gut and skin microbiota were analyzed using Mann-Whitney U-test. Analysis of beta-diversity of the gut and skin microbiota including PCA of OTU level and PCoA of weighted UniFrac distances were performed based on ANOSIM by R package vegan (2.5.4) (https:// CRAN.R-proje ct. org/ packa ge= vegan) 61 . Data for SCFA levels were analyzed using Student t-test. Correlations between SCFAs and the relative bacterial abundance were analyzed using Spearman's correlation analysis. Correlations between the relative abundance of bacteria in the skin and intestine were also analyzed using Spearman's correlation analysis. P < 0.05 was considered statistically significant.

The data that support the findings of this study are available from the corresponding author upon reasonable request. www.nature.com/scientificreports/

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This study was in part supported by grant-in-Aid for the National Natural Science Foundation of China (NSFC) (to Y.W., 31701009). Dr. Yan Wei was supported by the China Scholarship Council (China). Dr. Lijia Chang was supported by the Japan China Sasakawa Medical Fellowship (Tokyo, Japan). 

The authors declare no competing interests.

Supplementary Information The online version contains supplementary material available at https:// doi. org/ 10. 1038/ s41598-021-90480-4.Correspondence and requests for materials should be addressed to K.H.Reprints and permissions information is available at www.nature.com/reprints.Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.