Metagenomic gut microbiome analysis of Japanese patients with multiple chemical sensitivity/idiopathic environmental intolerance.
Central nervous system
Gut microbiome
Multiple chemical sensitivity
Shotgun metagenomic sequencing
Journal
BMC microbiology
ISSN: 1471-2180
Titre abrégé: BMC Microbiol
Pays: England
ID NLM: 100966981
Informations de publication
Date de publication:
11 Mar 2024
11 Mar 2024
Historique:
received:
03
01
2023
accepted:
26
02
2024
medline:
12
3
2024
pubmed:
12
3
2024
entrez:
12
3
2024
Statut:
epublish
Résumé
Although the pathology of multiple chemical sensitivity (MCS) is unknown, the central nervous system is reportedly involved. The gut microbiota is important in modifying central nervous system diseases. However, the relationship between the gut microbiota and MCS remains unclear. This study aimed to identify gut microbiota variations associated with MCS using shotgun metagenomic sequencing of fecal samples. We prospectively recruited 30 consecutive Japanese female patients with MCS and analyzed their gut microbiomes using shotgun metagenomic sequencing. The data were compared with metagenomic data obtained from 24 age- and sex-matched Japanese healthy controls (HC). We observed no significant difference in alpha and beta diversity of the gut microbiota between the MCS patients and HC. Focusing on the important changes in the literatures, at the genus level, Streptococcus, Veillonella, and Akkermansia were significantly more abundant in MCS patients than in HC (p < 0.01, p < 0.01, p = 0.01, respectively, fold change = 4.03, 1.53, 2.86, respectively). At the species level, Akkermansia muciniphila was significantly more abundant (p = 0.02, fold change = 3.3) and Faecalibacterium prausnitzii significantly less abundant in MCS patients than in HC (p = 0.03, fold change = 0.53). Functional analysis revealed that xylene and dioxin degradation pathways were significantly enriched (p < 0.01, p = 0.01, respectively, fold change = 1.54, 1.46, respectively), whereas pathways involved in amino acid metabolism and synthesis were significantly depleted in MCS (p < 0.01, fold change = 0.96). Pathways related to antimicrobial resistance, including the two-component system and cationic antimicrobial peptide resistance, were also significantly enriched in MCS (p < 0.01, p < 0.01, respectively, fold change = 1.1, 1.2, respectively). The gut microbiota of patients with MCS shows dysbiosis and alterations in bacterial functions related to exogenous chemicals and amino acid metabolism and synthesis. These findings may contribute to the further development of treatment for MCS. This study was registered with the University Hospital Medical Information Clinical Trials Registry as UMIN000031031. The date of first trial registration: 28/01/2018.
Sections du résumé
BACKGROUND
BACKGROUND
Although the pathology of multiple chemical sensitivity (MCS) is unknown, the central nervous system is reportedly involved. The gut microbiota is important in modifying central nervous system diseases. However, the relationship between the gut microbiota and MCS remains unclear. This study aimed to identify gut microbiota variations associated with MCS using shotgun metagenomic sequencing of fecal samples.
METHODS
METHODS
We prospectively recruited 30 consecutive Japanese female patients with MCS and analyzed their gut microbiomes using shotgun metagenomic sequencing. The data were compared with metagenomic data obtained from 24 age- and sex-matched Japanese healthy controls (HC).
RESULTS
RESULTS
We observed no significant difference in alpha and beta diversity of the gut microbiota between the MCS patients and HC. Focusing on the important changes in the literatures, at the genus level, Streptococcus, Veillonella, and Akkermansia were significantly more abundant in MCS patients than in HC (p < 0.01, p < 0.01, p = 0.01, respectively, fold change = 4.03, 1.53, 2.86, respectively). At the species level, Akkermansia muciniphila was significantly more abundant (p = 0.02, fold change = 3.3) and Faecalibacterium prausnitzii significantly less abundant in MCS patients than in HC (p = 0.03, fold change = 0.53). Functional analysis revealed that xylene and dioxin degradation pathways were significantly enriched (p < 0.01, p = 0.01, respectively, fold change = 1.54, 1.46, respectively), whereas pathways involved in amino acid metabolism and synthesis were significantly depleted in MCS (p < 0.01, fold change = 0.96). Pathways related to antimicrobial resistance, including the two-component system and cationic antimicrobial peptide resistance, were also significantly enriched in MCS (p < 0.01, p < 0.01, respectively, fold change = 1.1, 1.2, respectively).
CONCLUSIONS
CONCLUSIONS
The gut microbiota of patients with MCS shows dysbiosis and alterations in bacterial functions related to exogenous chemicals and amino acid metabolism and synthesis. These findings may contribute to the further development of treatment for MCS.
TRIAL REGISTRATION
BACKGROUND
This study was registered with the University Hospital Medical Information Clinical Trials Registry as UMIN000031031. The date of first trial registration: 28/01/2018.
Identifiants
pubmed: 38468206
doi: 10.1186/s12866-024-03239-y
pii: 10.1186/s12866-024-03239-y
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
84Subventions
Organisme : Grant-in-Aid for Evidence-Based Medicine Research from the National Hospital Organization, Japan
ID : 2015-EBM-02
Organisme : Grant-in-Aid for Evidence-Based Medicine Research from the National Hospital Organization, Japan
ID : 2015-EBM-02
Informations de copyright
© 2024. The Author(s).
Références
American Academy of Allergy, Asthma and Immunology (AAAAI) Board of Directors. Idiopathic environmental intolerances. J Allergy Clin Immunol. 1999;103(1 Pt 1):36–40.
College of Occupational and Environmental Medicine. ACOEM position statement. Multiple chemical sensitivities: idiopathic environmental intolerance. J Occup Environ Med. 1999;41(11):940–2.
doi: 10.1097/00043764-199911000-00003
Yunus MB. Fibromyalgia and overlapping disorders: the unifying concept of central sensitivity syndromes. Semin Arthritis Rheum. 2007;36(6):339–56.
pubmed: 17350675
doi: 10.1016/j.semarthrit.2006.12.009
Sharon G, Sampson TR, Geschwind DH, Mazmanian SK. The central nervous system and the gut microbiome. Cell. 2016;167:915–32.
pubmed: 27814521
pmcid: 5127403
doi: 10.1016/j.cell.2016.10.027
Jangi S, Gandhi R, Cox LM, Li N, von Glehn F, Yan R, et al. Alterations of the human gut microbiome in multiple sclerosis. Nat Commun. 2016;7:12015.
pubmed: 27352007
pmcid: 4931233
doi: 10.1038/ncomms12015
Ma B, Liang J, Dai M, Wang J, Luo J, Zhang Z, et al. Altered gut microbiota in Chinese children with autism spectrum disorders. Front Cell Infect Microbiol. 2019;9:40.
pubmed: 30895172
pmcid: 6414714
doi: 10.3389/fcimb.2019.00040
Dantoft TM, Nordin S, Andersson L, Petersen MW, Skovbjerg S, Jørgensen T. Multiple chemical sensitivity described in the Danish general population: cohort characteristics and the importance of screening for functional somatic syndrome comorbidity-The DanFunD study. PLoS One. 2021;16(2):e0246461.
pubmed: 33626058
pmcid: 7904225
doi: 10.1371/journal.pone.0246461
Watai K, Fukutomi Y, Hayashi H, Kamide Y, Sekiya K, Taniguchi M. Epidemiological association between multiple chemical sensitivity and birth by caesarean section: a nationwide case-control study. Environ Health. 2018;17(1):30547814.
doi: 10.1186/s12940-018-0438-2
Galazzo G, van Best N, Bervoets L, Dapaah IOO, Savelkoul PH, Hornef MW, et al. Development of the microbiota and associations with birth mode, diet, and atopic disorders in a longitudinal analysis of stool samples, collected from infancy through early childhood. Gastroenterology. 2020;158(6):1584–96.
pubmed: 31958431
doi: 10.1053/j.gastro.2020.01.024
Yatsunenko T, Rey FE, Manary MJ, Trehan I, Dominguez-Bello MG, Contreras M, Magris M, et al. Human gut microbiome viewed across age and geography. Nature. 2012;486(7402):222–7.
pubmed: 22699611
pmcid: 3376388
doi: 10.1038/nature11053
Clemente JC, Ursell LK, Parfrey LW, Knight R. The impact of the gut microbiota on human health: an integrative view. Cell. 2012;148(6):1258–70.
pubmed: 22424233
pmcid: 5050011
doi: 10.1016/j.cell.2012.01.035
Imhann F, Bonder MJ, Vila AV, Fu J, Mujagic Z, Vork L, et al. Proton pump inhibitors affect the gut microbiome. Gut. 2016;65(5):740–8.
pubmed: 26657899
doi: 10.1136/gutjnl-2015-310376
Lin CY, Cheng HT, Kuo CJ, Lee YS, Sung CM, Keidan M, et al. Proton pump inhibitor-induced gut dysbiosis increases mortality rates for patients with Clostridioides difficile infection. Microbiol Spectr. 2022;10(4):e0048622.
pubmed: 35863023
doi: 10.1128/spectrum.00486-22
Nishino K, Nishida A, Inoue R, Kawada Y, Ohno M, Sakai S, et al. Analysis of endoscopic brush samples identified mucosa-associated dysbiosis in inflammatory bowel disease. J Gastroenterol. 2018;53(1):95–106.
pubmed: 28852861
doi: 10.1007/s00535-017-1384-4
Hashimoto Y, Hamaguchi M, Kaji A, Sakai R, Osaka T, Inoue R, et al. Intake of sucrose affects gut dysbiosis in patients with type 2 diabetes. J Diabetes Investig. 2020;11(6):1623–34.
pubmed: 32412684
pmcid: 7610116
doi: 10.1111/jdi.13293
Jiang H, Peng Y, Zhang W, Chen Y, Jiang Q, Zhou Y. Gut microbiome-targeted therapies in liver cirrhosis: a protocol for systematic review and meta-analysis. Syst Rev. 2022;11(1):181.
pubmed: 36042459
pmcid: 9429623
doi: 10.1186/s13643-022-02059-3
Yachida S, Mizutani S, Shiroma H, Shiba S, Nakajima T, Sakamoto T, et al. Metagenomic and metabolomic analyses reveal distinct stage-specific phenotypes of the gut microbiota in colorectal cancer. Nat Med. 2019;25(6):968–76.
pubmed: 31171880
doi: 10.1038/s41591-019-0458-7
Nishijima S, Suda W, Oshima K, Kim SW, Hirose Y, Morita H, et al. The gut microbiome of healthy Japanese and its microbial and functional uniqueness. DNA Res. 2016;23(2):125–33.
pubmed: 26951067
pmcid: 4833420
doi: 10.1093/dnares/dsw002
Kim SW, Suda W, Kim S, Oshima K, Fukuda S, Ohno H, et al. Robustness of gut microbiota of healthy adults in response to probiotic intervention revealed by high-throughput pyrosequencing. DNA Res. 2013;20(3):241–53.
pubmed: 23571675
pmcid: 3686430
doi: 10.1093/dnares/dst006
Li W, Godzik A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics. 2006;22(13):1658–9.
pubmed: 16731699
doi: 10.1093/bioinformatics/btl158
Good IJ. The population frequencies of species and the estimation of population parameters. Biometrika. 1953;40:237–64.
doi: 10.1093/biomet/40.3-4.237
Kanehisa M, Sato Y, Furumichi M, Morishima K, Tanabe M. New approach for understanding genome variations in KEGG. Nucleic Acids Res. 2019;47(D1):D590–5.
pubmed: 30321428
doi: 10.1093/nar/gky962
Li J, Jia H, Cai X, Zhong H, Ffeng Q, Sunagawa S, et al. An integrated catalog of reference genes in the human gut microbiome. Nat Biotechnol. 2014;32(8):834–41.
pubmed: 24997786
doi: 10.1038/nbt.2942
Hojo S, Kumano H, Yoshino H, Kakuta K, Ishikawa S. Application of Quick Environment Exposure Sensitivity Inventory (QEESI) for Japanese population: study of reliability and validity of the questionnaire. Toxicol Ind Health. 2003;19(2–6):41–9.
pubmed: 15697173
doi: 10.1191/0748233703th180oa
Miller CS, Prihoda TJ. A controlled comparison of symptoms and chemical intolerances reported by Gulf War veterans, implant recipients and persons with multiple chemical sensitivity. Toxicol Ind Health. 1999;15(3–4):386–97.
pubmed: 10416290
doi: 10.1177/074823379901500312
Miller CS, Prihoda TJ. The Environmental Exposure and Sensitivity Inventory (EESI): a standardized approach for measuring chemical intolerances for research and clinical applications. Toxicol Ind Health. 1999;15(3–4):370–85.
pubmed: 10416289
doi: 10.1177/074823379901500311
Schnakenberg E, Fabig KR, Stanulla M, Strobl N, Lustig M, Fabig N, et al. A cross-sectional study of self-reported chemical-related sensitivity is associated with gene variants of drug-metabolizing enzymes. Environ Health. 2007;6:6.
pubmed: 17291352
pmcid: 1802749
doi: 10.1186/1476-069X-6-6
Skovbjerg S, Berg ND, Elberling J, Christensen KB. Evaluation of the quick environmental exposure and sensitivity inventory in a Danish population. J Environ Public Health. 2012;2012:304314.
pubmed: 22529872
pmcid: 3317206
doi: 10.1155/2012/304314
Derrien M, Vaughan EE, Plugge CM, de Vos WM. Akkermansia muciniphila gen nov, sp nov, a human intestinal mucin-degrading bacterium. Int J Syst Evol Microbiol. 2004;54(5):1469–76.
pubmed: 15388697
doi: 10.1099/ijs.0.02873-0
Shin NR, Lee JC, Lee HY, Kim MS, Whon TW, Lee MS, et al. An increase in the Akkermansia spp population induced by metformin treatment improves glucose homeostasis in diet-induced obese mice. Gut. 2014;63(5):727–35.
pubmed: 23804561
doi: 10.1136/gutjnl-2012-303839
Cani PD, de Vos WM. Next-generation beneficial microbes: the case of Akkermansia muciniphila. Front Microbiol. 2017;8:1765.
pubmed: 29018410
pmcid: 5614963
doi: 10.3389/fmicb.2017.01765
Murakami T, Kamada K, Mizushima K, Higashimura Y, Katada K, Uchiyama K, et al. Changes in intestinal motility and gut microbiota composition in a rat stress model. Digestion. 2017;95(1):55–60.
pubmed: 28052282
doi: 10.1159/000452364
Wang K, Wu W, Wang Q, Yang L, Bian X, Jiang X, et al. The negative effect of Akkermansia muciniphila-mediated post-antibiotic reconstitution of the gut microbiota on the development of colitis-associated colorectal cancer in mice. Front Microbiol. 2022;13:932047.
pubmed: 36312913
pmcid: 9614165
doi: 10.3389/fmicb.2022.932047
Desai MS, Seekatz AM, Koropatkin NM, Kamada N, Hickey CA, Wolter M, et al. A dietary fiber-deprived gut microbiota degrades the colonic mucus barrier and enhances pathogen susceptibility. Cell. 2016;167(5):1339-53.e21.
pubmed: 27863247
pmcid: 5131798
doi: 10.1016/j.cell.2016.10.043
Dong TS, Gupta A. Influence of early life, diet, and the environment on the microbiome. Clin Gastroenterol Hepatol. 2019;17(2):231–42.
pubmed: 30196160
doi: 10.1016/j.cgh.2018.08.067
Naito Y, Kashiwagi K, Takagi T, Andoh A, Inoue R. Intestinal dysbiosis secondary to proton-pump inhibitor use. Digestion. 2018;97(2):195–204.
pubmed: 29316555
doi: 10.1159/000481813
Fukui A, Takagi T, Naito Y, Inoue R, Kashiwagi S, Mizushima K, et al. Higher levels of Streptococcus in upper gastrointestinal mucosa associated with symptoms in patients with functional dyspepsia. Digestion. 2020;101(1):38–45.
pubmed: 31752012
doi: 10.1159/000504090
Park SH, Kim KA, Ahn YT, Jeong JJ, Huh CS, Kim DH. Comparative analysis of gut microbiota in elderly people of urbanized towns and longevity villages. BMC Microbiol. 2015;15:49.
pubmed: 25887483
pmcid: 4345030
doi: 10.1186/s12866-015-0386-8
Tana C, Umesaki Y, Imaoka A, Handa T, Kanazawa M, Fukudo S. Altered profiles of intestinal microbiota and organic acids may be the origin of symptoms in irritable bowel syndrome. Neurogastroenterol Motil. 2010;22(5):512–9, e114-515.
pubmed: 19903265
Kato K, Ishida S, Tanaka M, Mitsuyama E, Xiao JZ, Odamaki T. Association between functional lactase variants and a high abundance of Bifidobacterium in the gut of healthy Japanese people. PLoS One. 2018;13(10):e0206189.
pubmed: 30339693
pmcid: 6195297
doi: 10.1371/journal.pone.0206189
Miyake S, Kim S, Suda W, Oshima K, Nakamura M, Matsuoka T, et al. Dysbiosis in the gut microbiota of patients with multiple sclerosis, with a striking depletion of species belonging to Clostridia XIVa and IV clusters. PLoS One. 2015;10(9):e0137429.
pubmed: 26367776
pmcid: 4569432
doi: 10.1371/journal.pone.0137429
Leylabadlo HE, Ghotaslou R, Feizabadi MM, Farajnia S, Moaddab SY, Ganbarov K, et al. The critical role of Faecalibacterium prausnitzii in human health: an overview. Microb Pathog. 2020;149:104344.
pubmed: 32534182
doi: 10.1016/j.micpath.2020.104344
Wan Y, Wang F, Yuan J, Li J, Jiang D, Zhang J, et al. Effects of dietary fat on gut microbiota and faecal metabolites, and their relationship with cardiometabolic risk factors: a 6-month randomised controlled-feeding trial. Gut. 2019;68(8):1417–29.
pubmed: 30782617
doi: 10.1136/gutjnl-2018-317609
Ozato N, Saito S, Yamaguchi T, Katashima M, Tokuda I, Sawada K, et al. Blautia genus associated with visceral fat accumulation in adults 20–76 years of age. NPJ Biofilms Microbiomes. 2019;5(1):28.
pubmed: 31602309
pmcid: 6778088
doi: 10.1038/s41522-019-0101-x
Zsido RG, Heinrich M, Slavich GM, Beyer F, Masouleh SK, Kratzsch J, et al. Association of estradiol and visceral fat with structural brain networks and memory performance in adults. JAMA Netw Open. 2019;2(6):e196126.
pubmed: 31225892
pmcid: 6593958
doi: 10.1001/jamanetworkopen.2019.6126
Wang H, Hu X, Zheng Y, Chen J, Tan B, Shi L, et al. Effects of replacing fish meal with cottonseed protein concentrate on the growth, immune responses, digestive ability and intestinal microbial flora in litopenaeus vannamei. Fish Shellfish Immunol. 2022;128:91–100.
pubmed: 35921932
doi: 10.1016/j.fsi.2022.07.067
Stock AM, Robinson VL, Goudreau PN. Two-component signal transduction. Annu Rev Biochem. 2000;69:183–215.
pubmed: 10966457
doi: 10.1146/annurev.biochem.69.1.183
Lingzhi L, Haojie G, Dan G, Hongmei M, Yang L, Mengdie J, et al. The role of two-component regulatory system in β-lactam antibiotics resistance. Microbiol Res. 2018;215:126–9.
pubmed: 30172298
doi: 10.1016/j.micres.2018.07.005
Nagata N, Nishijima S, Miyoshi-Akiyama T, Kojima Y, Kimura M, Aoki R, et al. Population-level metagenomics uncovers distinct effects of multiple medications on the human gut microbiome. Gastroenterology. 2022;163(4):1038–52.
pubmed: 35788347
doi: 10.1053/j.gastro.2022.06.070
Vila AV, Collij V, Sanna S, Sinha T, Imhann F, Bourgonje AR, et al. Impact of commonly used drugs on the composition and metabolic function of the gut microbiota. Nat Commun. 2020;11(1):362.
doi: 10.1038/s41467-019-14177-z
Maier L, Pruteanu M, Kuhn M, Zeller G, Telzerow A, Anderson EE, et al. Extensive impact of non-antibiotic drugs on human gut bacteria. Nature. 2018;555(7698):623–8.
pubmed: 29555994
pmcid: 6108420
doi: 10.1038/nature25979
Sasabe J, Miyoshi Y, Rakoff-Nahoum S, Zhang T, Mita M, Davis BM, et al. Interplay between microbial d-amino acids and host D-amino acid oxidase modifies murine mucosal defence and gut microbiota. Nat Microbiol. 2016;1(10):16125.
pubmed: 27670111
pmcid: 5074547
doi: 10.1038/nmicrobiol.2016.125
Suzuki M, Sujino T, Chiba S, Harada Y, Goto M, Takahashi R, et al. Host-microbe cross-talk governs amino acid chirality to regulate survival and differentiation of B cells. Sci AdV. 2021;7(10):33658193.
doi: 10.1126/sciadv.abd6480