Unraveling the genetics of arsenic toxicity with cellular morphology QTL.

The health risks that arise from environmental exposures vary widely within and across human populations, and these differences are largely determined by genetic variation and gene-by-environment (gene-environment) interactions. However, risk assessment in laboratory mice typically involves isogenic strains and therefore, does not account for these known genetic effects. In this context, genetically heterogenous cell lines from laboratory mice are promising tools for population-based screening because they provide a way to introduce genetic variation in risk assessment without increasing animal use. Cell lines from genetic reference populations of laboratory mice offer genetic diversity, power for genetic mapping, and potentially, predictive value for in vivo experimentation in genetically matched individuals. To explore this further, we derived a panel of fibroblast lines from a genetic reference population of laboratory mice (the Diversity Outbred, DO). We then used high-content imaging to capture hundreds of cell morphology traits in cells exposed to the oxidative stress-inducing arsenic metabolite monomethylarsonous acid (MMAIII). We employed dose-response modeling to capture latent parameters of response and we then used these parameters to identify several hundred cell morphology quantitative trait loci (cmQTL). Response cmQTL encompass genes with established associations with cellular responses to arsenic exposure, including Abcc4 and Txnrd1, as well as novel gene candidates like Xrcc2. Moreover, baseline trait cmQTL highlight the influence of natural variation on fundamental aspects of nuclear morphology. We show that the natural variants influencing response include both coding and non-coding variation, and that cmQTL haplotypes can be used to predict response in orthogonal cell lines. Our study sheds light on the major molecular initiating events of oxidative stress that are under genetic regulation, including the NRF2-mediated antioxidant response, cellular detoxification pathways, DNA damage repair response, and cell death trajectories.

Genome-wide transcript and protein analysis highlights the role of protein homeostasis in the aging mouse heart.

Investigation of the molecular mechanisms of aging in the human heart is challenging because of confounding factors, such as diet and medications, as well as limited access to tissues from healthy aging individuals. The laboratory mouse provides an ideal model to study aging in healthy individuals in a controlled environment. However, previous mouse studies have examined only a narrow range of the genetic variation that shapes individual differences during aging. Here, we analyze transcriptome and proteome data from 185 genetically diverse male and female mice at ages 6, 12, and 18 mo to characterize molecular changes that occur in the aging heart. Transcripts and proteins reveal activation of pathways related to exocytosis and cellular transport with age, whereas processes involved in protein folding decrease with age. Additional changes are apparent only in the protein data including reduced fatty acid oxidation and increased autophagy. For proteins that form complexes, we see a decline in correlation between their component subunits with age, suggesting age-related loss of stoichiometry. The most affected complexes are themselves involved in protein homeostasis, which potentially contributes to a cycle of progressive breakdown in protein quality control with age. Our findings highlight the important role of post-transcriptional regulation in aging. In addition, we identify genetic loci that modulate age-related changes in protein homeostasis, suggesting that genetic variation can alter the molecular aging process.

Effects of a Global Rab27a Null Mutation on Murine PVAT and Cardiovascular Function.

BACKGROUND: RAB27A is a member of the RAS oncogene superfamily of GTPases and regulates cell secretory function. It, is expressed within blood vessels and perivascular adipose tissue. We hypothesized that loss of RAB27A would alter cardiovascular function. METHODS: Body weight of Rab27aash mice was measured from 2 to 18 months of age, along with glucose resorption at 6 and 12 months of age and glucose sensitivity at 18 months of age. Body weight and cellular and molecular features of perivascular adipose tissue and aortic tissue were examined in a novel C57BL/6J Rab27a null strain. Analyses included morphometric quantification and proteomic analyses. Wire myography measured vasoreactivity, and echocardiography measured cardiac function. Comparisons across ages and genotypes were evaluated via 2-way ANOVA with multiple comparison testing. Significance for myography was determined via 4-parameter nonlinear regression testing. RESULTS: Genome-wide association data linked rare human RAB27A variants with body mass index and glucose handling. Changes in glucose tolerance were observed in Rab27aash male mice at 18 months of age. In WT (wild-type) and Rab27a null male mice, body weight, adipocyte lipid area, and aortic area increased with age. In female mice, only body weight increased with age, independent of RAB27A presence. Protein signatures from male Rab27a null mice suggested greater associations with cardiovascular and metabolic phenotypes compared with female tissues. Wire myography results showed Rab27a null males exhibited increased vasoconstriction and reduced vasodilation at 8 weeks of age. Rab27a null females exhibited increased vasoconstriction and vasodilation at 20 weeks of age. Consistent with these vascular changes, male Rab27a null mice experienced age-related cardiomyopathy, with severe differences observed by 21 weeks of age. CONCLUSIONS: Global RAB27A loss impacted perivascular adipose tissue and thoracic aorta proteomic signatures, altered vasocontractile responses, and decreased left ventricular ejection fraction in mice.

Genetic drivers of age-related changes in urinary magnesium excretion.

Although age-dependent alterations in urinary magnesium (Mg2+) excretion have been described, the underlying mechanism remains elusive. As heritability significantly contributes to variations in urinary Mg2+excretion, we measured urinary Mg2+ excretion at different ages in a cohort of genetically variable Diversity Outbred (DO) mice. Compared to animals aged 6 months, an increase in Mg2+ excretion was observed at 12 and 18 months. Quantitative trait locus (QTL) analysis revealed an association of a locus on chromosome 10 with Mg2+ excretion at 6 months of age, with Oit3 (encoding oncoprotein-induced transcript 3; OIT3) as our primary candidate gene. To study the possible role of OIT3 in renal Mg2+ handling, we generated and characterized Oit3 knockout (Oit3-/-) mice. Although a slightly lower serum Mg2+ concentration was present in male Oit3-/- mice, this effect was not observed in female Oit3-/- mice. Additionally, urinary Mg2+ excretion and the expression of renal magnesiotropic genes was unaltered in Oit3-/- mice. For animals aged 12 and 18 months, QTL analysis revealed an association with a locus on chromosome 19, which contains the gene encoding TRPM6, a known Mg2+ channel involved in renal Mg2+ reabsorption. Comparison with RNAseq data revealed that Trpm6 mRNA expression is inversely correlated with the QTL effect, implying that TRPM6 may be involved in age-dependent changes in urinary Mg2+ excretion in mice. In conclusion, we show here that variants in Oit3 and Trpm6 are associated with urinary Mg2+ excretion at distinct periods in life, although OIT3 is unlikely to affect renal Mg2+ handling.

Using Genetic and Species Diversity to Tackle Kidney Disease.

Progress in the identification of causal genes and understanding of the mechanism underlying kidney disease is hindered by the almost exclusive use of a few animal models with restrictive monogenic backgrounds that may be more resistant to kidney disease compared with humans and, therefore, poor models. Exploring the large genetic diversity in classical animal models, such as mice and rats, and leveraging species diversity will allow us to use the genetic advantages of zebrafish, Drosophila, and other species, to develop both new animal models that are more relevant to the study of human kidney disease and potential therapies.

The impact of genetic background on mouse models of kidney disease.

The mouse is the most commonly used mammalian model to study disease, including kidney disease. However, close attention needs to be paid to the differences and effects of genetic background. The default choice of most investigators is to use C57BL/6 mice, but not all C57BL/6 mice are the same. Ever since the C57BL/6 line was first established, differences in the genetic background have risen between substrains, which have major implications in the phenotypes expressed in kidney disease. Furthermore, considering that C57BL/6 substrains are relatively resistant to kidney damage, there can be major benefits in selecting other mouse inbred strains when studying kidney disease. These strains can show more similar responses regarding kidney damage as in humans, and results may therefore translate better to human application. Genetically diverse mice, such as the Diversity Outbred mice, allow investigators to study kidney phenotypes with comparable levels of genetic diversity as seen in humans, which yield results that more closely reflect the variation in human disease outcomes due to genetic variation. Hence, embracing the genetic diversity that is present in mice can lead to better translational research methods. Investigators need to always take into consideration that genetic background is a variable that can alter results significantly, and optimization of translational research asks for careful strain selection and more rigorous reporting of the genetic background that is being used in experiment.

Sequencing and assembling bear genomes: the bare necessities.

Unique genetic adaptations are present in bears of every species across the world. From (nearly) shutting down important organs during hibernation to preventing harm from lifestyles that could easily cause metabolic diseases in humans, bears may hold the answer to various human ailments. However, only a few of these unique traits are currently being investigated at the molecular level, partly because of the lack of necessary tools. One of these tools is well-annotated genome assemblies from the different, extant bear species. These reference genomes are needed to allow us to identify differences in genetic variants, isoforms, gene expression, and genomic features such as transposons and identify those that are associated with biomedical-relevant traits. In this review we assess the current state of the genome assemblies of the eight different bear species, discuss current gaps, and the future benefits these reference genomes may have in informing human biomedical applications, while at the same time improving bear conservation efforts.

Uncovering Modifier Genes of X-Linked Alport Syndrome Using a Novel Multiparent Mouse Model.

BACKGROUND: Mutations in COL4A5 are responsible for 80% of cases of X-linked Alport Syndrome (XLAS). Although genes that cause AS are well characterized, people with AS who have similar genetic mutations present with a wide variation in the extent of kidney impairment and age of onset, suggesting the activities of modifier genes. METHODS: We created a cohort of genetically diverse XLAS male and female mice using the Diversity Outbred mouse resource and measured albuminuria, GFR, and gene expression. Using a quantitative trait locus approach, we mapped modifier genes that can best explain the underlying phenotypic variation measured in our diverse population. RESULTS: Genetic analysis identified several loci associated with the variation in albuminuria and GFR, including a locus on the X chromosome associated with X inactivation and a locus on chromosome 2 containing Fmn1. Subsequent analysis of genetically reduced Fmn1 expression in Col4a5 knockout mice showed a decrease in albuminuria, podocyte effacement, and podocyte protrusions in the glomerular basement membrane, which support the candidacy of Fmn1 as a modifier gene for AS. CONCLUSION: With this novel approach, we emulated the variability in the severity of kidney phenotypes found in human patients with Alport Syndrome through albuminuria and GFR measurements. This approach can identify modifier genes in kidney disease that can be used as novel therapeutic targets.

Deep Learning-Based Segmentation and Quantification in Experimental Kidney Histopathology.

BACKGROUND: Nephropathologic analyses provide important outcomes-related data in experiments with the animal models that are essential for understanding kidney disease pathophysiology. Precision medicine increases the demand for quantitative, unbiased, reproducible, and efficient histopathologic analyses, which will require novel high-throughput tools. A deep learning technique, the convolutional neural network, is increasingly applied in pathology because of its high performance in tasks like histology segmentation. METHODS: We investigated use of a convolutional neural network architecture for accurate segmentation of periodic acid-Schiff-stained kidney tissue from healthy mice and five murine disease models and from other species used in preclinical research. We trained the convolutional neural network to segment six major renal structures: glomerular tuft, glomerulus including Bowman's capsule, tubules, arteries, arterial lumina, and veins. To achieve high accuracy, we performed a large number of expert-based annotations, 72,722 in total. RESULTS: Multiclass segmentation performance was very high in all disease models. The convolutional neural network allowed high-throughput and large-scale, quantitative and comparative analyses of various models. In disease models, computational feature extraction revealed interstitial expansion, tubular dilation and atrophy, and glomerular size variability. Validation showed a high correlation of findings with current standard morphometric analysis. The convolutional neural network also showed high performance in other species used in research-including rats, pigs, bears, and marmosets-as well as in humans, providing a translational bridge between preclinical and clinical studies. CONCLUSIONS: We developed a deep learning algorithm for accurate multiclass segmentation of digital whole-slide images of periodic acid-Schiff-stained kidneys from various species and renal disease models. This enables reproducible quantitative histopathologic analyses in preclinical models that also might be applicable to clinical studies.

Association of Coding Variants in Hydroxysteroid 17-beta Dehydrogenase 14 (HSD17B14) with Reduced Progression to End Stage Kidney Disease in Type 1 Diabetes.

BACKGROUND: Rare variants in gene coding regions likely have a greater impact on disease-related phenotypes than common variants through disruption of their encoded protein. We searched for rare variants associated with onset of ESKD in individuals with type 1 diabetes at advanced kidney disease stage. METHODS: Gene-based exome array analyses of 15,449 genes in five large incidence cohorts of individuals with type 1 diabetes and proteinuria were analyzed for survival time to ESKD, testing the top gene in a sixth cohort (n=2372/1115 events all cohorts) and replicating in two retrospective case-control studies (n=1072 cases, 752 controls). Deep resequencing of the top associated gene in five cohorts confirmed the findings. We performed immunohistochemistry and gene expression experiments in human control and diseased cells, and in mouse ischemia reperfusion and aristolochic acid nephropathy models. RESULTS: Protein coding variants in the hydroxysteroid 17-ß dehydrogenase 14 gene (HSD17B14), predicted to affect protein structure, had a net protective effect against development of ESKD at exome-wide significance (n=4196; P value=3.3 × 10-7). The HSD17B14 gene and encoded enzyme were robustly expressed in healthy human kidney, maximally in proximal tubular cells. Paradoxically, gene and protein expression were attenuated in human diabetic proximal tubules and in mouse kidney injury models. Expressed HSD17B14 gene and protein levels remained low without recovery after 21 days in a murine ischemic reperfusion injury model. Decreased gene expression was found in other CKD-associated renal pathologies. CONCLUSIONS: HSD17B14 gene is mechanistically involved in diabetic kidney disease. The encoded sex steroid enzyme is a druggable target, potentially opening a new avenue for therapeutic development.

Genetic background determines renal response to chronic lithium treatment in female mice.

Chronic lithium treatment for bipolar disease causes mainly side effects in the kidney. A subset of lithium users develops nephrogenic diabetes insipidus (NDI), a urinary concentrating disorder, and chronic kidney disease (CKD). Age, lithium dose, and duration of treatment are important risk factors, whereas genetic background might also play an important role. To investigate the role of genetics, female mice of 29 different inbred strains were treated for 1 year with control or lithium chow and urine, blood, and kidneys were analyzed. Chronic lithium treatment increased urine production and/or reduced urine osmolality in 21 strains. Renal histology showed that lithium increased interstitial fibrosis and/or tubular atrophy in eight strains, whereas in none of the strains glomerular injury was induced. Interestingly, lithium did not elevate urinary albumin-creatinine ratio (ACR) in any strain, whereas eight strains even demonstrated a lowered ACR. The protective effect on ACR coincided with a similar decrease in urinary IgG levels, a marker of glomerular function, whereas the adverse effect of lithium on interstitial fibrosis/tubular atrophy coincided with a severe increase in urinary ß2-microglobulin (ß2M) levels, an indicator of proximal tubule damage. Genetic background plays an important role in the development of lithium-induced NDI and chronic renal pathology in female mice. The strong correlation of renal pathology with urinary ß2M levels indicates that ß2M is a promising biomarker for chronic renal damage induced by lithium.

A Translational Model for Venous Thromboembolism: MicroRNA Expression in Hibernating Black Bears.

BACKGROUND: Hibernating American black bears have significantly different clotting parameters than their summer active counterparts, affording them protection against venous thromboembolism during prolonged periods of immobility. We sought to evaluate if significant differences exist between the expression of microRNAs in the plasma of hibernating black bears compared with their summer active counterparts, potentially contributing to differences in hemostasis during hibernation. MATERIALS AND METHODS: MicroRNA sequencing was assessed in plasma from 21 American black bears in summer active (n = 11) and hibernating states (n = 10), and microRNA signatures during hibernating and active state were established using both bear and human genome. MicroRNA targets were predicted using messenger RNA (mRNA) transcripts from black bear kidney cells. In vitro studies were performed to confirm the relationship between identified microRNAs and mRNA expression, using artificial microRNA and human liver cells. RESULTS: Using the bear genome, we identified 15 microRNAs differentially expressed in the plasma of hibernating black bears. Of these microRNAs, three were significantly downregulated (miR-141-3p, miR-200a-3p, and miR-200c-3p), were predicted to target SERPINC1, the gene for antithrombin, and demonstrated regulatory control of the gene mRNA expression in cell studies. CONCLUSIONS: Our findings suggest that the hibernating black bears' ability to maintain hemostasis and achieve protection from venous thromboembolism during prolonged periods of immobility may be due to changes in microRNA signatures and possible upregulation of antithrombin expression.

Detection and Classification of Novel Renal Histologic Phenotypes Using Deep Neural Networks.

With the advent and increased accessibility of deep neural networks (DNNs), complex properties of histologic images can be rigorously and reproducibly quantified. We used DNN-based transfer learning to analyze histologic images of periodic acid-Schiff-stained renal sections from a cohort of mice with different genotypes. We demonstrate that DNN-based machine learning has strong generalization performance on multiple histologic image processing tasks. The neural network extracted quantitative image features and used them as classifiers to look for differences between mice of different genotypes. Excellent performance was observed at segmenting glomeruli from non-glomerular structure and subsequently predicting the genotype of the animal on the basis of glomerular quantitative image features. The DNN-based genotype classifications highly correlate with mesangial matrix expansion scored by a pathologist (R.E.C.), which differed in these animals. In addition, by analyzing non-glomeruli images, the neural network identified novel histologic features that differed by genotype, including the presence of vacuoles, nuclear count, and proximal tubule brush border integrity, which was validated with immunohistologic staining. These features were not identified in systematic pathologic examination. Our study demonstrates the power of DNNs to extract biologically relevant phenotypes and serve as a platform for discovering novel phenotypes. These results highlight the synergistic possibilities for pathologists and DNNs to radically scale up our ability to generate novel mechanistic hypotheses in disease.

Identification of Acer2 as a First Susceptibility Gene for Lithium-Induced Nephrogenic Diabetes Insipidus in Mice.

BACKGROUND: Lithium, mainstay treatment for bipolar disorder, causes nephrogenic diabetes insipidus and hypercalcemia in about 20% and 10% of patients, respectively, and may lead to acidosis. These adverse effects develop in only a subset of patients treated with lithium, suggesting genetic factors play a role. METHODS: To identify susceptibility genes for lithium-induced adverse effects, we performed a genome-wide association study in mice, which develop such effects faster than humans. On day 8 and 10 after assigning female mice from 29 different inbred strains to normal chow or lithium diet (40 mmol/kg), we housed the animals for 48 hours in metabolic cages for urine collection. We also collected blood samples. RESULTS: In 17 strains, lithium treatment significantly elevated urine production, whereas the other 12 strains were not affected. Increased urine production strongly correlated with lower urine osmolality and elevated water intake. Lithium caused acidosis only in one mouse strain, whereas hypercalcemia was found in four strains. Lithium effects on blood pH or ionized calcium did not correlate with effects on urine production. Using genome-wide association analyses, we identified eight gene-containing loci, including a locus containing Acer2, which encodes a ceramidase and is specifically expressed in the collecting duct. Knockout of Acer2 led to increased susceptibility for lithium-induced diabetes insipidus development. CONCLUSIONS: We demonstrate that genome-wide association studies in mice can be used successfully to identify susceptibility genes for development of lithium-induced adverse effects. We identified Acer2 as a first susceptibility gene for lithium-induced diabetes insipidus in mice.

Hearing loss without overt metabolic acidosis in ATP6V1B1 deficient MRL mice, a new genetic model for non-syndromic deafness with enlarged vestibular aqueducts.

Mutations of the human ATP6V1B1 gene cause distal renal tubular acidosis (dRTA; OMIM #267300) often associated with sensorineural hearing impairment; however, mice with a knockout mutation of Atp6v1b1 were reported to exhibit a compensated acidosis and normal hearing. We discovered a new spontaneous mutation (vortex, symbol vtx) of Atp6v1b1 in an MRL/MpJ (MRL) colony of mice. In contrast to the reported phenotype of the knockout mouse, which was developed on a primarily C57BL/6 (B6) strain background, MRL-Atp6v1b1vtx/vtx mutant mice exhibit profound hearing impairment, which is associated with enlarged endolymphatic compartments of the inner ear. Mutant mice have alkaline urine but do not exhibit overt metabolic acidosis, a renal phenotype similar to that of the Atpbv1b1 knockout mouse. The abnormal inner ear phenotype of MRL- Atp6v1b1vtx/vtx mice was lost when the mutation was transferred onto the C57BL/6J (B6) background, indicating the influence of strain-specific genetic modifiers. To genetically map modifier loci in Atp6v1b1vtx/vtx mice, we analysed ABR thresholds of progeny from a backcross segregating MRL and B6 alleles. We found statistically significant linkage with a locus on Chr 13 that accounts for about 20% of the hearing threshold variation in the backcross mice. The important effect that genetic background has on the inner ear phenotype of Atp6v1b1 mutant mice provides insight into the hearing loss variability associated with dRTA caused by ATP6V1B1 mutations. Because MRL-Atp6v1b1vxt/vtx mice do not recapitulate the metabolic acidosis of dRTA patients, they provide a new genetic model for nonsyndromic deafness with enlarged vestibular aqueduct (EVA; OMIM #600791).

APOBEC1 complementation factor (A1CF) is dispensable for C-to-U RNA editing in vivo.

Editing of the human and murine ApoB mRNA by APOBEC1, the catalytic enzyme of the protein complex that catalyzes C-to-U RNA editing, creates an internal stop codon within the APOB coding sequence, generating two protein isoforms. It has been long held that APOBEC1-mediated editing activity is dependent on the RNA binding protein A1CF. The function of A1CF in adult tissues has not been reported because a previously reported null allele displays embryonic lethality. This work aimed to address the function of A1CF in adult mouse tissues using a conditional A1cf allele. Unexpectedly, A1cf-null mice were viable and fertile with modest defects in hematopoietic, immune, and metabolic parameters. C-to-U RNA editing was quantified for multiple targets, including ApoB, in the small intestine and liver. In all cases, no changes in RNA editing efficiency were observed. Blood plasma analysis demonstrated a male-specific increase in solute concentration and increased cellularity in the glomeruli of male A1cf-null mice. Urine analysis showed a reduction in solute concentration, suggesting abnormal water homeostasis and possible kidney abnormalities exclusive to the male. Computational identification of kidney C-to-U editing sites from polyadenylated RNA-sequencing identified a number of editing sites exclusive to the kidney. However, molecular analysis of kidney C-to-U editing showed no changes in editing efficiency with A1CF loss. Taken together, these observations demonstrate that A1CF does not act as the APOBEC1 complementation factor in vivo under normal physiological conditions and suggests new roles for A1CF, specifically within the male adult kidney.

Hierarchical analysis of RNA-seq reads improves the accuracy of allele-specific expression.

Motivation: Allele-specific expression (ASE) refers to the differential abundance of the allelic copies of a transcript. RNA sequencing (RNA-seq) can provide quantitative estimates of ASE for genes with transcribed polymorphisms. When short-read sequences are aligned to a diploid transcriptome, read-mapping ambiguities confound our ability to directly count reads. Multi-mapping reads aligning equally well to multiple genomic locations, isoforms or alleles can comprise the majority (>85%) of reads. Discarding them can result in biases and substantial loss of information. Methods have been developed that use weighted allocation of read counts but these methods treat the different types of multi-reads equivalently. We propose a hierarchical approach to allocation of read counts that first resolves ambiguities among genes, then among isoforms, and lastly between alleles. We have implemented our model in EMASE software (Expectation-Maximization for Allele Specific Expression) to estimate total gene expression, isoform usage and ASE based on this hierarchical allocation. Results: Methods that align RNA-seq reads to a diploid transcriptome incorporating known genetic variants improve estimates of ASE and total gene expression compared to methods that use reference genome alignments. Weighted allocation methods outperform methods that discard multi-reads. Hierarchical allocation of reads improves estimation of ASE even when data are simulated from a non-hierarchical model. Analysis of RNA-seq data from F1 hybrid mice using EMASE reveals widespread ASE associated with cis-acting polymorphisms and a small number of parent-of-origin effects. Availability and implementation: EMASE software is available at https://github.com/churchill-lab/emase. Supplementary information: Supplementary data are available at Bioinformatics online.

FAR2 is associated with kidney disease in mice and humans.

Mesangial matrix expansion is an important process in the initiation of chronic kidney disease, yet the genetic factors driving its development are unknown. Our previous studies have implicated Far2 as a candidate gene associated with differences in mesangial matrix expansion between mouse inbred strains. Consistent with the hypothesis that increased expression of Far2 leads to mesangial matrix expansion through increased production of platelet-activating factor precursors, we show that FAR2 is capable of mediating de novo platelet-activating factor synthesis in vitro and driven by the transcription factor NKX3.2. We demonstrate that knockdown of Far2 in mice delays the progression of mesangial matrix expansion with at least six months (equivalent to ~15 yr in human). Furthermore, we show that increased FAR2 expression in human patients is associated with diabetic nephropathy, lupus nephritis, and IgA nephropathy. Taken together, these results highlight FAR2's role in the development of mesangial matrix expansion and chronic kidney disease.

Automatic glomerular identification and quantification of histological phenotypes using image analysis and machine learning.

Current methods of scoring histological kidney samples, specifically glomeruli, do not allow for collection of quantitative data in a high-throughput and consistent manner. Neither untrained individuals nor computers are presently capable of identifying glomerular features, so expert pathologists must do the identification and score using a categorical matrix, complicating statistical analysis. Critical information regarding overall health and physiology is encoded in these samples. Rapid comprehensive histological scoring could be used, in combination with other physiological measures, to significantly advance renal research. Therefore, we used machine learning to develop a high-throughput method to automatically identify and collect quantitative data from glomeruli. Our method requires minimal human interaction between steps and provides quantifiable data independent of user bias. The method uses free existing software and is usable without extensive image analysis training. Validation of the classifier and feature scores in mice is highlighted in this work and shows the power of applying this method in murine research. Preliminary results indicate that the method can be applied to data sets from different species after training on relevant data, allowing for fast glomerular identification and quantitative measurements of glomerular features. Validation of the classifier and feature scores are highlighted in this work and show the power of applying this method. The resulting data are free from user bias. Continuous data, such that statistical analysis can be performed, allows for more precise and comprehensive interrogation of samples. These data can then be combined with other physiological data to broaden our overall understanding of renal function.

Lithium induces aerobic glycolysis and glutaminolysis in collecting duct principal cells.

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 NH4+ 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.