Table 1 The microbiome in urinary tract diseases.

Urinary stone disease—mouse model of fecal transplantation

Investigation of the gastrointestinal microbial community and the effect of fecal transplantation on urinary stone risk parameters in a murine model.

Microbiome analysis by 16S rRNA gene amplification and sequencing.

Post-fecal transplantation (4 weeks):

↓ Urinary calcium (>50%)

↓ Urinary oxalate levels

↓ Clostridiaceae family

↑ Urinary pH

↑ Cecum Solute Carrier Family 26 Member 6 (Slc26a6) expression

Fecal transfer from donor to recipient mice can impact urinary parameters associated with stone formation.

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Kidney stone disease and hypertension—a clinical study

Investigation of the relationship between the urinary microbiome and blood pressure in patients with kidney stone disease and hypertension by 16S rRNA sequencing and PCR.

Patients with kidney stone disease had an altered urinary microbiome compared to healthy controls. Predominant species identified;

Healthy controls: Gardnerella

Non-hypertensive kidney stone disease: Staphylococcus

Hypertensive kidney stone disease: Sphingomonas

Patients with kidney stone disease and hypertension have a unique urinary microbiome. Monitoring alterations in the microbiome may be advantageous in determining disease progression and/or severity.

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Urinary stone disease—an animal model

Fecal transplant via oral gavage of microbes isolated from a high oxalate diet-adapted mammalian herbivore.

Fecal transplant animals had enhanced oxalate metabolism, which increased bacterial diversity.

Targeted bacteriotherapy may be used to reduce urinary oxalate excretion in patients at high risk of recurrent calcium oxalate stones.

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AKI—mouse model

Broad-spectrum antibiotic-induced depletion of microbiota and induction of AKI via renal ischemia-reperfusion injury in mice.

Depletion of the gastrointestinal microbiota attenuated renal damage and dysfunction after renal ischemia-reperfusion injury.

Microbiota depletion reduced the number of kidney resident F4/80⁺ macrophages compared to controls.

Antibiotic-induced depletion of the gastrointestinal microbiota protects against renal ischemia–reperfusion injury. Reducing the macrophage response by targeting microbiota-derived mediators may be a promising therapeutic avenue.

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AKI—clinical and mouse model

Murine model of ischemia-reperfusion injury, bacterial analysis by 16S rRNA sequencing, and analysis of chiral amino acid by 2D high-performance liquid chromatography (HPLC).

Gastrointestinal microbiota protected against renal tubular injury.

AKI-induced gastrointestinal dysbiosis and altered metabolism of d-amino acids.

Serum d-serine levels were significantly correlated with decreased kidney function in human AKI patients.

Gastrointestinal-derived d-serine has a protective effect in AKI and can be used as a serum biomarker for disease progression.

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CKD—clinical study (adult cohort)

Urine and plasma biochemical analysis and PCR.

Increased mRNA expression of decapentaplegic homolog 3(SMAD3) and NLR Family Pyrin Domain Containing 3 (NLRP3) and increased serum transforming growth factor-beta (TGF‐β)1 and interleukin‐1β protein levels, were associated with increased microbiota‐dependent metabolite trimethylamine N‐oxide (TMAO) levels.

Serum and/or urine TMAO along with key immune factors may be used as biomarkers to evaluate CKD progression.

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CKD—clinical study (children and adolescent cohort)

Gastrointestinal microbial composition and TMAO metabolic pathway were assessed by mass spectrometry and PCR. Correlation with blood-pressure and vascular abnormalities in children with early-stage CKD was evaluated.

Children with later stage CKD had a lower urinary level of TMAO. Urinary TMAO levels were correlated with an abundance of the genera Bifidobacterium and Lactobacillus. CKD in children with abnormal ambulatory blood pressure had a lower abundance of Prevotella.

Early detection and stratification by microbial signatures may assist in preventive care to improve cardiovascular outcomes in children with CKD.

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CKD—clinical study (adult cohort)

Short Chain Fatty Acids (SCFAs) were measured in plasma using targeted liquid chromatography-mass spectrometry.

Increased plasma levels of valerate, an SCFA generated by the gastrointestinal microbiota, was found in patients with CKD; this increased level of plasma valerate positively correlated with cardiovascular disease.

Improving stratification of cardiovascular risk in patients with CKD based on plasma levels of SCFAs may help identify patients with the subclinical disease to facilitate early intervention.

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CKD—clinical study (adult cohort)

Pilot study characterizing urinary microbiome in patients with non-dialysis-dependent CKD.

Midstream urine microbiomes are diverse in adults with CKD; however, diversity was lower with reduced glomerular filtration rate, and more advanced CKD.

Association between microbiome diversity and kidney function. Further studies are required to determine whether kidney disease influences the microbiome or vice versa.

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CKD—rat model

Adenine diet-induced CKD in rats followed by a lactulose-containing diet. Renal function, uremic toxins, and gastrointestinal microbiota were assessed.

Lactulose containing diet improved levels of serum blood urea nitrogen and creatinine, whilst tubulointerstitial fibrosis and microbiota-derived serum indoxyl sulfate levels were suppressed compared to the control diet group.

Lactulose by diet modifies gastrointestinal microbiota and improves CKD disease progression by suppressing uremic toxin production.

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Recurrent (rUTI)—mouse model

Mouse model of cystitis with two different clinical uropathogenic (UPEC) isolates, UTI89, a cystitis isolate, or CFT073, pyelonephritis isolates.

Mice infected with CFT073 and treated with antibiotics were protected against reinfection with the same isolate but not secondary infection with UTI89.

Mice infected with UTI89 were highly susceptible to a secondary infection with either strain.

Depletion of T cell subsets impaired bacteria clearance and increased susceptibility to rUTI.

UPEC has to strain-specific implications to the host and a more advanced understanding of host–pathogen interactions is required for improved effective drug development.

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Neurogenic bladder—a clinical study

Urinary microbiome analyzed by 16S rRNA pyrosequencing, from asymptomatic patients with and without a neurogenic bladder.

Neurogenic bladder patients are more likely to have bacteriuria than patients without a neurogenic bladder. Female patients with neurogenic bladder had a greater abundance of Lactobacillus crispatus in their urine while male patients had Staphylococcus haemolyticus. In both sexes, patients with neurogenic bladder had greater proportions of Enterococcus faecalis, Proteus mirabilis, and Klebsiella pneumonia.

16S pyrosequencing was able to identify unique, phenotype dependent urinary microbiome populations, even in asymptomatic cohorts. The Lactobacillus community in urine from females with neurogenic bladder differed depending on bladder function.

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Neurogenic bladder—a clinical study

Urine was collected from both healthy controls and healthy subjects with neurogenic bladder. Urinalysis, urine culture, and NextGen16S rDNA sequencing were used with further metaproteomic analysis.

The bacterial taxa showing the highest relative abundance and change, include Lactobacillales, Enterobacteriales, Actinomycetales, Bacillales, Clostridiales, Bacteroidales, Burkholderiales, Pseudomonadales, Bifidobacteriales, and Coriobacteriales.

The healthy urine microbiome is characterized by an abundance of Lactobacillales in women and Corynebacterium in men. Integrating 16S rDNA sequencing with metaproteomics can improve diagnostics and more targeted use of therapeutics in patients with neurogenic bladder.

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Neurogenic bladder—clinical study (children cohort)

Urinary microbiome analysis by 16SrRNA sequencing, from children with neurogenic bladder (both with UTI, and asymptomatic bacteriuria)

Children with neurogenic bladder had an increased abundance of members of the Enterobacteriaceae family. However, there was no difference between those with UTI and those with asymptomatic bacteriuria.

In children with neurogenic bladder, it is difficult to distinguish between UTI and asymptomatic bacteriuria. Analysis of the urinary microbiome may provide further differentiation to aid incorrect diagnosis. Although with only a small cohort further work is needed to determine if the urinary microbiome varies in larger cohorts.

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