Postinfective bowel dysfunction following Campylobacter enteritis is characterised by reduced microbiota diversity and impaired microbiota recovery

Jonna Jalanka, David Gunn, Gulzar Singh, Shanthi Krishnasamy, Melanie Lingaya, Fiona Crispie, Laura Finnegan, Paul Cotter, Louise James, Adam Nowak, Giles Major, Robin C Spiller, Jonna Jalanka, David Gunn, Gulzar Singh, Shanthi Krishnasamy, Melanie Lingaya, Fiona Crispie, Laura Finnegan, Paul Cotter, Louise James, Adam Nowak, Giles Major, Robin C Spiller

Abstract

Objectives: Persistent bowel dysfunction following gastroenteritis (postinfectious (PI)-BD) is well recognised, but the associated changes in microbiota remain unclear. Our aim was to define these changes after gastroenteritis caused by a single organism, Campylobacter jejuni, examining the dynamic changes in the microbiota and the impact of antibiotics.

Design: A single-centre cohort study of 155 patients infected with Campylobacter jejuni. Features of the initial illness as well as current bowel symptoms and the intestinal microbiota composition were recorded soon after infection (visit 1, <40 days) as well as 40-60 days and >80 days later (visits 2 and 3). Microbiota were assessed using 16S rRNA sequencing.

Results: PI-BD was found in 22 of the 99 patients who completed the trial. The cases reported significantly looser stools, with more somatic and gastrointestinal symptoms. Microbiota were assessed in 22 cases who had significantly lower diversity and altered microbiota composition compared with the 44 age-matched and sex-matched controls. Moreover 60 days after infection, cases showed a significantly lower abundance of 23 taxa including phylum Firmicutes, particularly in the order Clostridiales and the family Ruminoccocaceae, increased Proteobacteria abundance and increased levels of Fusobacteria and Gammaproteobacteria. The microbiota changes were linked with diet; higher fibre consumption being associated with lower levels of Gammaproteobacteria.

Conclusion: The microbiota of PI-BD patients appeared more disturbed by the initial infection compared with the microbiota of those who recovered. The prebiotic effect of high fibre diets may inhibit some of the disturbances seen in PI-BD.

Trial registration number: NCT02040922.

Keywords: CAMPYLOBACTER JEJUNI; INTESTINAL MICROBIOLOGY; IRRITABLE BOWEL SYNDROME.

Conflict of interest statement

Competing interests: GM is now an employee of Société des Produits Nestlé S.A. which provides products and services relevant to this condition. RCS has received research grants from Zespri International and Sanofi-Aventis and speaker fees from Ardelyx, Menarini & Ferrer. The other authors have no conflicting interests to declare.

© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1
Figure 1
CONSORT diagram. The 48 mechanistic controls were chosen because they provided the most complete set of stool samples. The mechanistic study was confirmed to be unbiased from the larger clinical study by demonstrating there were no significant differences in demographics, psychological scores nor markers of initial illness severity (online supplemental tables S6–7). CONSORT, Consolidated Standards of Reporting Trials; IBD, inflammatory bowel disease; IBS, irritable bowel syndrome.
Figure 2
Figure 2
Differences in patients’ symptoms 3 months after gastroenteritis (A) average PHQ-12S scores for cases and controls, showing the increased prevalence of trouble sleeping (p

Figure 3

Microbiota recovery after infection in…

Figure 3

Microbiota recovery after infection in cases and controls. (A) PCoA plot with Bray-Curtis…

Figure 3
Microbiota recovery after infection in cases and controls. (A) PCoA plot with Bray-Curtis dissimilarity from all subjects. The largest variation in microbiota composition is due to time since infection, samples obtained early after infection being significantly different from the later ones (MANOVA multivariate analysis of variance, p=0.001). The coloured circles represent 50% of the data. (B) Inverse Simpson diversity. Microbial recovery during the follow-up period was different between cases and controls. The inverse Simpson diversity shows that cases fail to recover to normal levels in samples collected more than 80 days after infection. (C) Proportion of total of Clostridia, Coriobacteriia and Fusobacteria. There were also significant class level differences including lower clostridia, but higher Coriobacteriia and Fusobacteria (for details, see online supplemental table S8-S10). SE of mean is shown as whiskers and statistically significant difference (p<0.05) is shown with asterisk. PCoA, principal co-ordinate analysis.

Figure 4

Association between fibre consumption and…

Figure 4

Association between fibre consumption and gammaproteobacterial abundance. The association was statistically significant (q=0.032),…

Figure 4
Association between fibre consumption and gammaproteobacterial abundance. The association was statistically significant (q=0.032), where low consumption of fibre was associated with high Gammaprotebacteria abundance. Light area indicates SE of mean.
Figure 3
Figure 3
Microbiota recovery after infection in cases and controls. (A) PCoA plot with Bray-Curtis dissimilarity from all subjects. The largest variation in microbiota composition is due to time since infection, samples obtained early after infection being significantly different from the later ones (MANOVA multivariate analysis of variance, p=0.001). The coloured circles represent 50% of the data. (B) Inverse Simpson diversity. Microbial recovery during the follow-up period was different between cases and controls. The inverse Simpson diversity shows that cases fail to recover to normal levels in samples collected more than 80 days after infection. (C) Proportion of total of Clostridia, Coriobacteriia and Fusobacteria. There were also significant class level differences including lower clostridia, but higher Coriobacteriia and Fusobacteria (for details, see online supplemental table S8-S10). SE of mean is shown as whiskers and statistically significant difference (p<0.05) is shown with asterisk. PCoA, principal co-ordinate analysis.
Figure 4
Figure 4
Association between fibre consumption and gammaproteobacterial abundance. The association was statistically significant (q=0.032), where low consumption of fibre was associated with high Gammaprotebacteria abundance. Light area indicates SE of mean.

References

    1. Klem F, Wadhwa A, Prokop LJ, et al. . Prevalence, risk factors, and outcomes of irritable bowel syndrome after infectious enteritis: a systematic review and meta-analysis. Gastroenterology 2017;152:1042–54. 10.1053/j.gastro.2016.12.039
    1. Card T, Enck P, Barbara G, et al. . Post-Infectious IBS: defining its clinical features and prognosis using an Internet-based survey. United European Gastroenterol J 2018;6:1245–53. 10.1177/2050640618779923
    1. Barman M, Unold D, Shifley K, et al. . Enteric salmonellosis disrupts the microbial ecology of the murine gastrointestinal tract. Infect Immun 2008;76:907–15. 10.1128/IAI.01432-07
    1. Fujita K, Kaku M, Yanagase Y, et al. . Physicochemical characteristics and flora of diarrhoeal and recovery faeces in children with acute gastro-enteritis in Kenya. Ann Trop Paediatr 1990;10:339–45. 10.1080/02724936.1990.11747455
    1. Ramakrishna BS, Mathan VI. Colonic dysfunction in acute diarrhoea: the role of luminal short chain fatty acids. Gut 1993;34:1215–8. 10.1136/gut.34.9.1215
    1. Hsiao A, Ahmed AMS, Subramanian S, et al. . Members of the human gut microbiota involved in recovery from Vibrio cholerae infection. Nature 2014;515:423–6. 10.1038/nature13738
    1. Lloyd-Price J, Abu-Ali G, Huttenhower C. The healthy human microbiome. Genome Med 2016;8:51. 10.1186/s13073-016-0307-y
    1. Sommer F, Anderson JM, Bharti R, et al. . The resilience of the intestinal microbiota influences health and disease. Nat Rev Microbiol 2017;15:630–8. 10.1038/nrmicro.2017.58
    1. Lahti L, Salojärvi J, Salonen A, et al. . Tipping elements in the human intestinal ecosystem. Nat Commun 2014;5:4344. 10.1038/ncomms5344
    1. Marciani L, Garsed KC, Hoad CL, et al. . Stimulation of colonic motility by oral PEG electrolyte bowel preparation assessed by MRI: comparison of split vs single dose. Neurogastroenterol Motil 2014;26:1426–36. 10.1111/nmo.12403
    1. Jalanka J, Salonen A, Salojärvi J, et al. . Effects of bowel cleansing on the intestinal microbiota. Gut 2015;64:1562–8. 10.1136/gutjnl-2014-307240
    1. Dunlop SP, Jenkins D, Neal KR, et al. . Relative importance of enterochromaffin cell hyperplasia, anxiety, and depression in postinfectious IBS. Gastroenterology 2003;125:1651–9. 10.1053/j.gastro.2003.09.028
    1. Tam CC, Rodrigues LC, Viviani L, et al. . Longitudinal study of infectious intestinal disease in the UK (IID2 study): incidence in the community and presenting to general practice. Gut 2012;61:69–77. 10.1136/gut.2011.238386
    1. Jalanka-Tuovinen J, Salojärvi J, Salonen A, et al. . Faecal microbiota composition and host-microbe cross-talk following gastroenteritis and in postinfectious irritable bowel syndrome. Gut 2014;63:1737–45. 10.1136/gutjnl-2013-305994
    1. Jalanka J, Salonen A, Fuentes S, et al. . Microbial signatures in post-infectious irritable bowel syndrome--toward patient stratification for improved diagnostics and treatment. Gut Microbes 2015;6:364–9. 10.1080/19490976.2015.1096486
    1. Neal KR, Hebden J, Spiller R. Prevalence of gastrointestinal symptoms six months after bacterial gastroenteritis and risk factors for development of the irritable bowel syndrome: postal survey of patients. BMJ 1997;314:779–82. 10.1136/bmj.314.7083.779
    1. Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand 1983;67:361–70. 10.1111/j.1600-0447.1983.tb09716.x
    1. Spiller RC, Humes DJ, Campbell E, et al. . The patient health questionnaire 12 somatic symptom scale as a predictor of symptom severity and consulting behaviour in patients with irritable bowel syndrome and symptomatic diverticular disease. Aliment Pharmacol Ther 2010;32:811–20. 10.1111/j.1365-2036.2010.04402.x
    1. Sloan TJ, Jalanka J, Major GAD, et al. . A low FODMAP diet is associated with changes in the microbiota and reduction in breath hydrogen but not colonic volume in healthy subjects. PLoS One 2018;13:e0201410. 10.1371/journal.pone.0201410
    1. Santiago A, Panda S, Mengels G, et al. . Processing faecal samples: a step forward for standards in microbial community analysis. BMC Microbiol 2014;14:112. 10.1186/1471-2180-14-112
    1. Salonen A, Nikkilä J, Jalanka-Tuovinen J, et al. . Comparative analysis of fecal DNA extraction methods with phylogenetic microarray: effective recovery of bacterial and archaeal DNA using mechanical cell lysis. J Microbiol Methods 2010;81:127–34. 10.1016/j.mimet.2010.02.007
    1. Klindworth A, Pruesse E, Schweer T, et al. . Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res 2013;41:e1. 10.1093/nar/gks808
    1. Korpela K. Mare: microbiota analysis in R easily. R package version 1.0, 2016. Available:
    1. Marshall JK, Thabane M, Garg AX, et al. . Incidence and epidemiology of irritable bowel syndrome after a large waterborne outbreak of bacterial dysentery. Gastroenterology 2006;131:445–50. 10.1053/j.gastro.2006.05.053
    1. Marshall JK, Thabane M, Garg AX, et al. . Prognosis of post infectious irritable bowel syndrome (PI-IBS) four years after the Walkerton outbreak of waterborne gastroenteritis (gE). Gastroenterology 2006;130:A52.
    1. Manichanh C, Rigottier-Gois L, Bonnaud E, et al. . Reduced diversity of faecal microbiota in Crohn's disease revealed by a metagenomic approach. Gut 2006;55:205–11. 10.1136/gut.2005.073817
    1. Kang S, Denman SE, Morrison M, et al. . Dysbiosis of fecal microbiota in Crohn's disease patients as revealed by a custom phylogenetic microarray. Inflamm Bowel Dis 2010;16:2034–42. 10.1002/ibd.21319
    1. Nelson AM, Walk ST, Taube S, et al. . Disruption of the human gut microbiota following norovirus infection. PLoS One 2012;7:e48224. 10.1371/journal.pone.0048224
    1. Lupp C, Robertson ML, Wickham ME, et al. . Host-mediated inflammation disrupts the intestinal microbiota and promotes the overgrowth of Enterobacteriaceae. Cell Host Microbe 2007;2:204. 10.1016/j.chom.2007.08.002
    1. Simpson HL, Campbell BJ. Review article: dietary fibre-microbiota interactions. Aliment Pharmacol Ther 2015;42:158–79. 10.1111/apt.13248
    1. Duncan SH, Louis P, Thomson JM, et al. . The role of pH in determining the species composition of the human colonic microbiota. Environ Microbiol 2009;11:2112–22. 10.1111/j.1462-2920.2009.01931.x
    1. De Filippo C, Cavalieri D, Di Paola M, et al. . Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Natl Acad Sci U S A 2010;107:14691–6. 10.1073/pnas.1005963107
    1. Vandeputte D, Falony G, Vieira-Silva S, et al. . Stool consistency is strongly associated with gut microbiota richness and composition, enterotypes and bacterial growth rates. Gut 2016;65:57–62. 10.1136/gutjnl-2015-309618
    1. Taco-Masias AA, Fernandez-Aristi AR, Cornejo-Tapia A, et al. . Gut microbiota in hospitalized children with acute infective gastroenteritis caused by virus or bacteria in a regional Peruvian Hospital. PeerJ 2020;8:e9964. 10.7717/peerj.9964
    1. Ni J, Wu GD, Albenberg L, et al. . Gut microbiota and IBD: causation or correlation? Nat Rev Gastroenterol Hepatol 2017;14:573–84. 10.1038/nrgastro.2017.88
    1. Masoodi I, Alshanqeeti AS, Alyamani EJ, et al. . Microbial dysbiosis in irritable bowel syndrome: a single-center metagenomic study in Saudi Arabia. JGH Open 2020;4:649–55. 10.1002/jgh3.12313
    1. Vich Vila A, Imhann F, Collij V, et al. . Gut microbiota composition and functional changes in inflammatory bowel disease and irritable bowel syndrome. Sci Transl Med 2018;10. 10.1126/scitranslmed.aap8914. [Epub ahead of print: 19 12 2018].
    1. Kassinen A, Krogius-Kurikka L, Mäkivuokko H, et al. . The fecal microbiota of irritable bowel syndrome patients differs significantly from that of healthy subjects. Gastroenterology 2007;133:24–33. 10.1053/j.gastro.2007.04.005
    1. Liu H, Zhang H, Wang X, et al. . The family Coriobacteriaceae is a potential contributor to the beneficial effects of Roux-en-Y gastric bypass on type 2 diabetes. Surg Obes Relat Dis 2018;14:584–93. 10.1016/j.soard.2018.01.012
    1. Xu J, Chen N, Wu Z, et al. . 5-Aminosalicylic acid alters the gut bacterial microbiota in patients with ulcerative colitis. Front Microbiol 2018;9:1274. 10.3389/fmicb.2018.01274
    1. Zhou X-Y, Li M, Li X, et al. . Visceral hypersensitive rats share common dysbiosis features with irritable bowel syndrome patients. World J Gastroenterol 2016;22:5211–27. 10.3748/wjg.v22.i22.5211
    1. Gu X, Song L-J, Li L-X, et al. . Fusobacterium nucleatum Causes Microbial Dysbiosis and Exacerbates Visceral Hypersensitivity in a Colonization-Independent Manner. Front Microbiol 2020;11:1281. 10.3389/fmicb.2020.01281
    1. Spiller RC, Jenkins D, Thornley JP, et al. . Increased rectal mucosal enteroendocrine cells, T lymphocytes, and increased gut permeability following acute Campylobacter enteritis and in post-dysenteric irritable bowel syndrome. Gut 2000;47:804–11. 10.1136/gut.47.6.804
    1. Gwee KA, Leong YL, Graham C, et al. . The role of psychological and biological factors in postinfective gut dysfunction. Gut 1999;44:400–6. 10.1136/gut.44.3.400
    1. Klem F, Wadhwa A, Prokop LJ, et al. . Prevalence, risk factors, and outcomes of irritable bowel syndrome after infectious enteritis: a systematic review and meta-analysis. Gastroenterology 2017;152:1042–54. 10.1053/j.gastro.2016.12.039
    1. McNulty CAM, Lasseter G, Newby K, et al. . Stool submission by general practitioners in SW England - when, why and how? A qualitative study. BMC Fam Pract 2012;13:77. 10.1186/1471-2296-13-77
    1. Dicksved J, Ellström P, Engstrand L, et al. . Susceptibility to Campylobacter infection is associated with the species composition of the human fecal microbiota. mBio 2014;5:e01212–4. 10.1128/mBio.01212-14

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