The microbiome of calcium-based urinary stones


Historically, the role of bacteria in urinary stone disease (USD) has been limited to urease-producing bacteria associated with struvite stone formation. However, growing evidence has revealed bacteria associated with stones of non-struvite composition. These bacteria may be derived from either urine or from the stones themselves. Using 16S rRNA gene sequencing and an enhanced culture technique (EQUC), we identified the urine and stone microbiota of USD patients and then determined if bacteria were statistically enriched in the stones relative to the urine. From 52 patients, bladder urine and urinary stones were collected intraoperatively during ureteroscopy. Stone homogenate and urine specimens were subjected to 16S rRNA gene sequencing and EQUC. Standard Chi-squared tests were applied to determine if the relative abundance of any bacterial taxon was significantly enriched in urinary stones compared to urine. Stones were primarily calcium-based. 29/52 (55.8%) stones had bacteria detected by 16S rRNA gene sequencing. Of these, dominant bacterial taxa were enriched from 12 stones. Bacterial taxa isolated by EQUC include members of the genera Staphylococcus, Enterobacter, Escherichia, Corynebacterium, and Lactobacillus. Dominant bacterial genera were enriched compared to paired bladder urine. Differences between the stone and urine microbiota may indicate that certain bacteria contribute to USD pathophysiology. Further investigation is warranted.

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We would like to thank Janet McGarr for consenting patients and collecting samples and Tatevik Broutian for organizing the background data. We acknowledge the assistance of John Ketz and Vijay Saxena in processing urine and kidney stone samples. We would also like to acknowledge Evann Hilt, Travis Price, Roberto Limeira, Thomas Halverson and Gina Kuffel for their assistance in processing samples for EQUC and/or 16S rRNA gene sequencing. The work was supported by intramural funds from Nationwide Children’s Hospital, Indiana University and Loyola University Chicago.

Author information




RAD: data acquisition, interpretation, and manuscript drafting; PB: data acquisition, interpretation, and manuscript revisions; MK: data acquisition, interpretation, and manuscript revisions; AJ: data interpretation and manuscript drafting; HL: data interpretation and manuscript revisions; XG: data interpretation and manuscript revisions; BK: sample acquisition, data interpretation, and manuscript revisions; QD: study design, data interpretation, and manuscript drafting; AJW: study design, data acquisition, interpretation, and manuscript drafting; ALS: study design, data acquisition, interpretation, and manuscript drafting. All authors have given approval for the final version of the manuscript

Corresponding authors

Correspondence to Qunfeng Dong or Alan J. Wolfe or Andrew L. Schwaderer.

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Conflict of interest

Alan Wolfe: Investigator Initiated Studies funded by Kimberly Clark Corporation and Astellas Scientific and Medical Affairs. Andrew Schwaderer: consulting for Allena Pharmaceuticals. Bodo Knudsen: consulting for Boston Scientific, Olympus Surgical, and Bard Medical. Ryan Dornbier, Petar Bajic, Michelle Van Kuiken, Ali Jardaneh, Huaiying Li, Xiang Gao, and Qunfeng Dong: no disclosures.

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Supplementary material 1 (TIFF 175 kb). PCoA analysis of Bray–Curtis distance between paired upper tract (N = 10) and bladder urine (N = 11). Each symbol represents a bacterial community from either bladder urine or upper tract urine for six subjects. Principal coordinate analysis (PCoA) was applied to visualize the dissimilarity of the bacterial communities amongst different samples based on Bray–Curtis distances. The PERMANOVA test indicated that bacterial communities from bladder urines are not separated in a statistically significant manner from the communities of upper tract urines based on our current sample size (p = 0.41)

Supplementary material 2 (DOCX 117 kb). Stone composition and demographic information for stones negative by sequencing

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Dornbier, R.A., Bajic, P., Van Kuiken, M. et al. The microbiome of calcium-based urinary stones. Urolithiasis 48, 191–199 (2020).

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  • Microbiota
  • Urinary stones
  • Nephrolithiasis
  • 16S rRNA gene sequencing