Tubular injury and interstitial fibrosis are the hallmarks of chronic kidney disease. While recent studies have verified that proximal tubular injury triggers interstitial fibrosis, the impact of fibrosis on tubular injury and regeneration remains poorly understood. We generated a novel mouse model expressing diphtheria toxin receptor on renal fibroblasts to allow for the selective disruption of renal fibroblast function. Administration of diphtheria toxin induced upregulation of the tubular injury marker Ngal and caused tubular proliferation in healthy kidneys, whereas administration of diphtheria toxin attenuated tubular regeneration in fibrotic kidneys. Microarray analysis revealed down-regulation of the retinol biosynthesis pathway in diphtheria toxin-treated kidneys. Healthy proximal tubules expressed retinaldehyde dehydrogenase 2 (RALDH2), a rate-limiting enzyme in retinoic acid biosynthesis. After injury, proximal tubules lost RALDH2 expression, whereas renal fibroblasts acquired strong expression of RALDH2 during the transition to myofibroblasts in several models of kidney injury. The retinoic acid receptor (RAR) RARg was expressed in proximal tubules both with and without injury, and aBcrystallin, the product of an RAR target gene, was strongly expressed in proximal tubules after injury. Furthermore, BMS493, an inverse agonist of RARs, significantly attenuated tubular proliferation in vitro. In human biopsy tissue from patients with IgA nephropathy, detection of RALDH2 in the interstitium correlated with older age and lower kidney function. These results suggest a role of retinoic acid signaling and cross-talk between fibroblasts and tubular epithelial cells during tubular injury and regeneration, and may suggest a beneficial effect of fibrosis in the early response to injury.Kidney International (2019) 95, 526-539; https://doi.

Cigarette smoking affects the oral microbiome, which is related to various systemic diseases. While studies that investigated the relationship between smoking and the oral microbiome by 16S rRNA amplicon sequencing have been performed, investigations involving metagenomic sequences are rare. We investigated the bacterial species composition in the tongue microbiome, as well as single-nucleotide variant (SNV) profiles and gene content of these species, in never and current smokers by utilizing metagenomic sequences. Among 234 never smokers and 52 current smokers, beta diversity, as assessed by weighted UniFrac measure, differed between never and current smokers (pseudo-F = 8.44, R 2 = 0.028, p = 0.001). Among the 26 species that had sufficient coverage, the SNV profiles of Actinomyces graevenitzii, Megasphaera micronuciformis, Rothia mucilaginosa, Veillonella dispar, and one Veillonella sp. were significantly different between never and current smokers. Analysis of gene and pathway content revealed that genes related to the lipopolysaccharide biosynthesis pathway in Veillonella dispar were present more frequently in current smokers. We found that species-level tongue microbiome differed between never and current smokers, and 5 species from never and current smokers likely harbor different strains, as suggested by the difference in SNV frequency.

Background: Automated classification of glomerular pathological findings is potentially beneficial in establishing an efficient and objective diagnosis in renal pathology. While previous studies have verified the artificial intelligence (AI) models for the classification of global sclerosis and glomerular cell proliferation, there are several other glomerular pathological findings required for diagnosis, and the comprehensive models for the classification of these major findings have not yet been reported. Whether the cooperation between these AI models and clinicians improves diagnostic performance also remains unknown. Here, we developed AI models to classify glomerular images for major findings required for pathological diagnosis and investigated whether those models could improve the diagnostic performance of nephrologists. Methods: We used a dataset of 283 kidney biopsy cases comprising 15,888 glomerular images that were annotated by a total of 25 nephrologists. AI models to classify seven pathological findings: global sclerosis, segmental sclerosis, endocapillary proliferation, mesangial matrix accumulation, mesangial cell proliferation, crescent, and basement membrane structural changes, were constructed using deep learning by fine-tuning of InceptionV3 convolutional neural network. Subsequently, we compared the agreement to truth labels between majority decision among nephrologists with or without the AI model as a voter. Results: Our model for global sclerosis showed high performance (area under the curve: periodic acid-Schiff, 0.986; periodic acid methenamine silver, 0.983); the models for the other findings also showed performance close to those of nephrologists. By adding the AI model output to majority decision among nephrologists, out of the 14 constructed models, the results of the majority decision showed improvement in sensitivity for 10 models (four of them were statistically significant) and specificity for eight models (five significant). Conclusion: Our study showed a proof-of-concept for the classification of multiple glomerular findings in a comprehensive method of deep learning and suggested its potential effectiveness in improving diagnostic accuracy of clinicians.

Background: The oral microbiome, which consists of various habitats, has been shown to be influenced by smoking. However, differences in the tongue microbiomes of current and former smokers, as well as their resultant functional consequences, have rarely been investigated in East Asian populations. Methods: We used 16S rRNA amplicon sequencing of tongue-coating samples obtained from East Asian subjects who were current, former, or never smokers to identify differences in their tongue microbiomes and related metagenomic functions. Two sets of participants from 2016 to 2017 (n = 657 and n = 187, respectively) were analyzed separately. Results: We found significant differences between the overall microbiome compositions of current versus never smokers (p = 0.0015), but not between former versus never smokers (p = 0.43) based on the weighted UniFrac distance. Twenty-nine of 43 investigated genera showed significantly different expression levels in current versus never smokers. Neisseria and Capnocytophaga were less abundant, and Streptococcus and Megasphaera were more abundant in current smokers. Moreover, the abundances of metagenomic pathways, including those related to nitrate reduction and the tricarboxylic acid cycle, were significantly different between current and never smokers. Conclusions: The tongue microbiomes and related metagenomic pathways of current smokers differ from those of never smokers among East Asians.

BackgroundDepletion of ATP in renal tubular cells plays the central role in the pathogenesis of kidney diseases. Nevertheless, inability to visualize spatiotemporal in vivo ATP distribution and dynamics has hindered further analysis.MethodsA novel mouse line systemically expressing an ATP biosensor (an ATP synthase subunit and two fluorophores) revealed spatiotemporal ATP dynamics at single-cell resolution during warm and cold ischemic reperfusion (IR) with two-photon microscopy. This experimental system enabled quantification of fibrosis 2 weeks after IR and assessment of the relationship between the ATP recovery in acute phase and fibrosis in chronic phase.ResultsUpon ischemia induction, the ATP levels of proximal tubule (PT) cells decreased to the nadir within a few minutes, whereas those of distal tubule (DT) cells decreased gradually up to 1 hour. Upon reperfusion, the recovery rate of ATP in PTs was slower with longer ischemia. In stark contrast, ATP in DTs was quickly rebounded irrespective of ischemia duration. Morphologic changes of mitochondria in the acute phase support the observation of different ATP dynamics in the two segments. Furthermore, slow and incomplete ATP recovery of PTs in the acute phase inversely correlated with fibrosis in the chronic phase. Ischemia under conditions of hypothermia resulted in more rapid and complete ATP recovery with less fibrosis, providing a proof of concept for use of hypothermia to protect kidney tissues.ConclusionsVisualizing spatiotemporal ATP dynamics during IR injury revealed higher sensitivity of PT cells to ischemia compared with DT cells in terms of energy metabolism. The ATP dynamics of PTs in AKI might provide prognostic information.