Urinary microbes and postoperative urinary tract infection risk in urogynecologic surgical patients
Introduction and hypothesis
Women have a 20% risk of developing a urinary tract infection (UTI) following urogynecologic surgery. This study assessed the association of postoperative UTI with bacteria in preoperative samples of catheterized urine.
Immediately before surgery, vaginal swabs, perineal swabs, and catheterized urine samples were collected, and the V4 region of the 16S ribosomal RNA (rRNA) gene was sequenced. The cohort was dichotomized in two ways: (1) standard day-of-surgery urine culture result (positive/negative), and (2) occurrence of postoperative UTI (positive/negative). Characteristics of bladder, vaginal, and perineal microbiomes were assessed to identify factors associated with postoperative UTI.
Eighty-seven percent of the 104 surgical patients with pelvic organ prolapse/urinary incontinence (POP/UI) were white; mean age was 57 years. The most common genus was Lactobacillus, with a mean relative abundance of 39.91% in catheterized urine, 53.88% in vaginal swabs, and 30.28% in perineal swabs. Two distinct clusters, based on dispersion of catheterized urine (i.e., bladder) microbiomes, had highly significant (p < 2.2–16) differences in age, microbes, and postoperative UTI risk. Postoperative UTI was most frequently associated with the bladder microbiome; microbes in adjacent pelvic floor niches also contributed to UTI risk. UTI risk was associated with depletion of Lactobacillus iners and enrichment of a diverse mixture of uropathogens.
Postoperative UTI risk appears to be associated with preoperative bladder microbiome composition, where an abundance of L. iners appears to protect against postoperative UTI.
KeywordsUrinary tract infection Urobiome Surgical infection Postoperative infection
We kindly thank Mary Tulke RN for her assistance with participant recruitment and sample collection; we thank Noriko Shibata MS for her assistance with sample analysis. We also thank Dr. Michael Zilliox and Gina Kuffel of the Loyola Genomics Facility for performing the DNA sequencing.
This study was supported by a grant from the Falk Foundation (LU#202567) and by NIH grants R21 DK097435 and P20 DK108268.
Compliance with ethical standards
Conflicts of interest
Dr. Wolfe discloses research support from Astellas and Kimberly Clark; Dr. Mueller discloses research support from Astellas and Boston Scientic. The remaining authors (Thomas-White, Gao, Lin, Fok, Ghanayem, Dong, and Brubaker) report no disclosures.
- 5.Fouts DE, Pieper R, Szpakowski S, Pohl H, Knoblach S, Suh MJ, et al. Integrated next-generation sequencing of 16S rDNA and metaproteomics differentiate the healthy urine microbiome from asymptomatic bacteriuria in neuropathic bladder associated with spinal cord injury. J Transl Med. 2012;10:174.CrossRefGoogle Scholar
- 17.Jari Oksanen FGB, Roeland Kindt, Pierre Legendre, Peter R. Minchin, R., B. O'Hara GLS, Peter Solymos, M. Henry H. Stevens and Helene Wagner vegan: Community Ecology Package. R package version 2.2-1. 2015, http://CRAN.R-project.org/package=vegan.
- 22.Bolker B, Skaug H, Magnusson A, Nielsen A. Getting started with the glmmADMB 2012.Google Scholar
- 24.Schreiber HLT, Conover MS, Chou WC, Hibbing ME, Manson AL, Dodson KW, Hannan TJ, Roberts PL, Stapleton AE, Hooton TM, Livny J, Earl AM, Hultgren SJ. Bacterial virulence phenotypes of Escherichia coli and host susceptibility determine risk for urinary tract infections. Sci Transl Med 2017;9.Google Scholar
- 25.Coorevits L, Heytens S, Boelens J, Claeys G. The resident microflora of voided midstream urine of healthy controls: standard versus expanded urine culture protocols. Eur J Clin Microbiol Infect Dis 2016.Google Scholar