Lithium, given to bipolar disorder patients, causes nephrogenic diabetes insipidus (Li-NDI), a urinary-concentrating defect. Li-NDI occurs due to downregulation of principal cell AQP2 expression, which coincides with principal cell proliferation. The metabolic effect of lithium on principal cells, however, is unknown and investigated here. In earlier studies, we showed that the carbonic anhydrase (CA) inhibitor acetazolamide attenuated Li-induced downregulation in mouse-collecting duct (mpkCCD) cells. Of the eight CAs present in mpkCCD cells, siRNA and drug treatments showed that downregulation of CA9 and to some extent CA12 attenuated Li-induced AQP2 downregulation. Moreover, lithium induced cell proliferation and increased the secretion of lactate. Lithium also increased urinary lactate levels in wild-type mice that developed Li-NDI but not in lithium-treated mice lacking ENaC, the principal cell entry site for lithium. Inhibition of aerobic glycolysis with 2-deoxyglucose (2DG) attenuated lithium-induced AQP2 downregulation in mpkCCD cells but did not attenuate Li-NDI in mice. Interestingly, NMR analysis demonstrated that lithium also increased the urinary succinate, fumarate, citrate, and NH levels, which were, in contrast to lactate, not decreased by 2DG. Together, our data reveal that lithium induces aerobic glycolysis and glutaminolysis in principal cells and that inhibition of aerobic glycolysis, but not the glutaminolysis, does not attenuate Li-NDI.
Circadian variability in kidney function is well recognized but is often ignored as a potential confounding variable in physiological experiments. Here, we have created a data resource consisting of expression levels for mRNA transcripts in microdissected proximal tubule segments from mice as a function of the time of day. Small-sample RNA-sequencing (RNA-seq) was applied to microdissected S1 proximal convoluted tubules (PCTs) and S2 proximal straight tubules (PSTs). After stringent filtering, the data were analyzed using JTK-Cycle to detect periodicity. The dataset is provided as a user-friendly webpage at https://esbl.nhlbi.nih.gov/Databases/Circadian-Prox2/. In PCTs, 234 transcripts varied in a circadian manner (4.0 % of total). In PSTs, 334 transcripts varied in a circadian manner (5.3 %). Transcripts previously known to be associated with corticosteroid action and with increased flow were found to be overrepresented among circadian transcripts peaking during the "dark" portion of the day (Zeitgeber Time [ZT] 14-22), corresponding to the peak levels of corticosterone and glomerular filtration rate in mice. To ask whether there is time-of-day dependence of protein abundances in the kidney, we carried out LC-MS/MS-based proteomics in whole mouse kidneys at ZT12 and ZT0. The full data set (n=6546 proteins) is available at https://esbl.nhlbi.nih.gov/Databases/Circadian-Proteome/. Overall, 293 proteins were differentially expressed between ZT12 and ZT0 (197 greater at ZT12; 96 greater at ZT0). Among the regulated proteins, only 9 had been found to be periodic in the RNA-seq analysis, suggesting a high level of post-transcriptional regulation of protein abundances.
Circadian variability in kidney function has long been recognized but is often ignored as a potential confounding variable in in vivo physiological experiments. To provide a guide for physiological studies on the kidney proximal tubule, we have now created a data resource consisting of expression levels for all measurable mRNA transcripts in microdissected proximal tubule segments from mice as a function of the time of day. This approach employs small-sample RNA-sequencing (RNA-seq) applied to microdissected renal proximal tubules including both S1 proximal convoluted tubules (PCTs) and S2 proximal straight tubules (PSTs). The data were analyzed using JTK-Cycle to detect periodicity. The data are provided as a user-friendly web page at https://esbl.nhlbi.nih.gov/Databases/Circadian-Prox/. In PCTs, 234 transcripts were found to vary in a circadian manner (3.7 % of total quantified). In PSTs, 334 transcripts were found to vary in a circadian manner (5.3 % of total quantified). Transcripts previously known to be associated with corticosteroid action and transcripts associated with increased flow were found to be overrepresented among circadian transcripts peaking during the dark portion of the day (Zeitgeber 14-22), corresponding to the peak levels of corticosterone and glomerular filtration rate in mice.
RNA sequencing (RNA‐Seq) is a sensitive means of global identification and quantification of mRNAs. In kidney, we have carried out RNA‐Seq analysis to identify transcriptomes of single microdissected renal tubules and single cells. The resulting datasets provide a community resource for gene expression in kidney structures in the form of a publicly accessible website at https://hpcwebapps.cit.nih.gov/ESBL/Database/Targets/TranscriptomicData.html. We now have added new whole‐kidney RNA‐Seq data for mice (male, age 8 weeks). This dataset reports 13,334 transcripts with mean TPM (“normalized transcripts per million”) greater than 1 for whole kidney (n=3). A large fraction of these are housekeeping genes or genes expressed in multiple cell types. Whole‐kidney RNA‐Seq analysis is of limited use in studying responses in these genes since the responses may be variable among cell types. However, signals were readily quantified for major cell‐type specific transcripts including podocytes (podocin, Nphs2), proximal convoluted tubule (sodium coupled glucose transporter 2, Slc5a2), proximal straight tubule (sodium coupled glucose transporter 1, Slc5a1), thin descending limb of Henle (follistatin, Fst), thin ascending limb (chloride channel ClC‐Ka, Clcnka), thick ascending limb (NKCC2, Slc12a1), distal convoluted tubule (NCC, Slc12a3), principal cell of collecting duct (ENaC gamma subunit, Scnn1g), type A intercalated cell (AE1, Slc4a1), type B intercalated cell (pendrin, Slc26a4), and inner medullary collecting duct cell (urea channel UT‐A1, Slc14a2 long isoform). Beyond this, transcripts were quantifiable for marker genes corresponding to rare cell types in the kidney including granular cells of the afferent arteriole (renin, Ren1), macrophages (macrophage colony‐stimulating factor 1 receptor, Csf1r), dendritic cells (dendritic cell‐specific ICAM‐3‐grabbing non‐integrin, Cd209a), and umbrella cells of the transitional epithelium (uroplakin 1a, Upk1a). In conclusion, numerous cell‐type specific mRNAs are represented in whole‐kidney RNA‐Seq analysis. These markers provide a means of measuring physiological regulatory responses (e.g. renin expression in granular cells) or measuring changes in cell numbers, which can occur with proliferative responses or infiltration of the kidney as part of inflammatory responses (e.g. macrophages and dendritic cells).This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
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