Chronic kidney disease (CKD) is an increasing global health burden. Current treatments for CKD include therapeutics to target factors that contribute to CKD progression, including renin–angiotensin–aldosterone system inhibitors, and drugs to control blood pressure and proteinuria control. Recently, associations between chronic disease processes and the human microbiota and its metabolites have been demonstrated. Dysbiosis—a change in the microbial diversity—has been observed in patients with CKD. The relationship between CKD and dysbiosis is bidirectional; gut-derived metabolites and toxins affect the progression of CKD, and the uremic milieu affects the microbiota. The accumulation of microbial metabolites and toxins is linked to the loss of kidney functions and increased mortality risk, yet renoprotective metabolites such as short-chain fatty acids and bile acids help restore kidney functions and increase the survival rate in CKD patients. Specific dietary interventions to alter the gut microbiome could improve clinical outcomes in patients with CKD. Low-protein and high-fiber diets increase the abundance of bacteria that produce short-chain fatty acids and anti-inflammatory bacteria. Fluctuations in the urinary microbiome are linked to increased susceptibility to infection and antibiotic resistance. In this review, we describe the potential role of the gut, urinary and blood microbiome in CKD pathophysiology and assess the feasibility of modulating the gut microbiota as a therapeutic tool for treating CKD.

Background The genetic factors associated with insulin resistance (IR) are not well understood. Clinical studies on first-degree relatives of type 2 diabetic (T2D) patients, which have the highest genetic predisposition to T2D, have given insights into the role of IR in T2D pathogenesis. Induced pluripotent stem cells (iPSCs) are excellent tools for disease modeling as they can retain the genetic imprint of the disease. Therefore, in this study, we aimed to investigate the genetic perturbations associated with insulin resistance (IR) in the offspring of T2D parents using patient-specific iPSCs. Methods We generated iPSCs from IR individuals (IR-iPSCs) that were offspring of T2D parents as well as from insulin-sensitive (IS-iPSCs) individuals. We then performed transcriptomics to identify key dysregulated gene networks in the IR-iPSCs in comparison to IS-iPSCs and functionally validated them. Results Transcriptomics on IR-iPSCs revealed dysregulated gene networks and biological processes indicating that they carry the genetic defects associated with IR that may lead to T2D. The IR-iPSCs had increased lactate secretion and a higher phosphorylation of AKT upon stimulation with insulin. IR-iPSCs have increased cellular oxidative stress indicated by a high production of reactive oxygen species and higher susceptibility to H2O2 -induced apoptosis. Conclusions IR-iPSCs generated from offspring of diabetic patients confirm that oxidative stress and increased lactate secretion, associated with IR, are inherited in this population, and may place them at a high risk of T2D. Overall, our IR-iPSC model can be employed for T2D modeling and drug screening studies that target genetic perturbations associated with IR in individuals with a high risk for T2D.

Recent advances in next-generation sequencing and metagenomic studies have provided insights into the microbial profile of different body sites. However, research on the microbial composition of urine is limited, particularly in children. The goal of this study was to optimize and develop reproducible metagenome and virome protocols using a small volume of urine samples collected from healthy children. We collected midstream urine specimens from 40 healthy children. Using the metagenomics shotgun approach, we tested various protocols. Different microbial roots such as Archaea, Bacteria, Eukaryota, and Viruses were successfully identified using our optimized urine protocol. Our data reflected much variation in the microbial fingerprints of children. Girls had significantly higher levels of Firmicutes, whereas boys had significantly higher levels of Actinobacteria. The genus Anaerococcus dominated the urinary bacteriome of healthy girls, with a significant increase in Anaerococcus prevotii, Anaerococcus vaginalis, and Veillonella parvula (p-value < 0.001) when compared with that of boys. An increased relative abundance of Xylanimonas and Arthrobacter, with a significantly high abundance of Arthrobacter sp. FB24 (p-value 0.0028) and Arthrobacter aurescences (p-value 0.015), was observed in boys. The urinary mycobiome showed a significant rise in the genus Malassezia and Malassezia globose fungus (p-value 0.009) in girls, whereas genus Saccharomyces (p-value 0.009) was significantly high in boys. The beta diversity of the urinary mycobiome was found to differ between different age groups. Boys had significantly more Mastadenovirus and Human mastadenovirus-A in their urinary virome than girls. With increasing age, we noticed an increase in the relative abundance of the order Caudovirales. Our optimized protocols allowed us to identify the unique microbes for each sex by using an adequate volume of urine (3–10 mL) to screen for the bacteriome, mycobiome, and virome profiles in the urine of healthy children. To the best of our knowledge, this is the first study to characterize the metagenomics profiles of urine in a healthy pediatric population.