Unique metabolite preferences of the drug transporters OAT1 and OAT3 analyzed by machine learning

In Vivo Regulation of Small Molecule Natural Products, Antioxidants, and Nutrients by OAT1 and OAT3

The organic anion transporters OAT1 (SLC22A6) and OAT3 (SLC22A8) are drug transporters that are expressed in the kidney, with well-established roles in the in vivo transport of drugs and endogenous metabolites. A comparatively unexplored potential function of these drug transporters is their contribution to the in vivo regulation of natural products (NPs) and their effects on endogenous metabolism. This is important for the evaluation of potential NP interactions with other compounds at the transporter site. Here, we have analyzed the NPs present in several well-established databases from Asian (Chinese, Indian Ayurvedic) and other traditions. Loss of OAT1 and OAT3 in murine knockouts caused serum alterations of many NPs, including flavonoids, vitamins, and indoles. OAT1- and OAT3-dependent NPs were largely separable based on a multivariate analysis of chemical properties. Direct binding to the transporter was confirmed using in vitro transport assays and protein binding assays. Our in vivo and in vitro results, considered in the context of previous data, demonstrate that OAT1 and OAT3 play a pivotal role in the handling of non-synthetic small molecule natural products, NP-derived antioxidants, phytochemicals, and nutrients (e.g., pantothenic acid, thiamine). As described by remote sensing and signaling theory, drug transporters help regulate redox states by meditating the movement of endogenous antioxidants and nutrients between organs and organisms. Our results demonstrate how dietary antioxidants and other NPs might feed into these inter-organ and inter-organismal pathways.

Inhibition of human drug transporter activities by succinate dehydrogenase inhibitors

Succinate dehydrogenase inhibitors (SDHIs) are widely-used fungicides, to which humans are exposed and for which putative health risks are of concern. In order to identify human molecular targets for these environmental chemicals, the interactions of 15 SDHIs with activities of main human drug transporters implicated in pharmacokinetics were investigated in vitro. 5/15 SDHIs, i.e., benzovindiflupyr, bixafen, fluxapyroxad, pydiflumetofen and sedaxane, were found to strongly reduce activity of the renal organic anion transporter (OAT) 3, in a concentration-dependent manner (with IC50 values in the 1.0-3.9 μM range), without however being substrates for OAT3. Moreover, these 5/15 SDHIs decreased the membrane transport of estrone-3 sulfate, an endogenous substrate for OAT3, and sedaxane was predicted to inhibit in vivo OAT3 activity in response to exposure to the acceptable daily intake (ADI) dose. In addition, pydiflumetofen strongly inhibited the renal organic cation transporter (OCT) 2 (IC50 = 2.0 μM) and benzovindiflupyr the efflux pump breast cancer resistance protein (BCRP) (IC50 = 3.9 μM). Other human transporters, including organic anion transporting polypeptide (OATP) 1B1 and OATP1B3 as well as multidrug and toxin extrusion protein (MATE) 1 and MATE2-K were moderately or weakly inhibited by SDHIs, whereas P-glycoprotein, multidrug resistance-associated protein (MRP), OCT1 and OAT1 activities were not or only marginally impacted. Then, some human drug transporters, especially OAT3, constitute molecular targets for SDHIs. This could have toxic consequences, notably with respect to levels of endogenous compounds and metabolites substrates for the considered transporters or to potential SDHI-drug interactions. This could therefore contribute to putative health risk of these fungicides.

Utilising Endogenous Biomarkers in Drug Development to Streamline the Assessment of Drug-Drug Interactions Mediated by Renal Transporters: A Pharmaceutical Industry Perspective

The renal secretion of many drugs is facilitated by membrane transporters, including organic cation transporter 2, multidrug and toxin extrusion protein 1/2-K and organic anion transporters 1 and 3. Inhibition of these transporters can reduce renal excretion of drugs and thereby pose a safety risk. Assessing the risk of inhibition of these membrane transporters by investigational drugs remains a key focus in the evaluation of drug-drug interactions (DDIs). Current methods to predict DDI risk are based on generating in vitro data followed by a clinical assessment using a recommended exogenous probe substrate for the individual drug transporter. More recently, monitoring plasma-based and urine-based endogenous biomarkers to predict transporter-mediated DDIs in early phase I studies represents a promising approach to facilitate, improve and potentially avoid conventional clinical DDI studies. This perspective reviews the evidence for use of these endogenous biomarkers in the assessment of renal transporter-mediated DDI, evaluates how endogenous biomarkers may help to expand the DDI assessment toolkit and offers some potential knowledge gaps. A conceptual framework for assessment that may complement the current paradigm of predicting the potential for renal transporter-mediated DDIs is outlined.

Distinguishing Molecular Properties of OAT, OATP, and MRP Drug Substrates by Machine Learning

The movement of organic anionic drugs across cell membranes is partly governed by interactions with SLC and ABC transporters in the intestine, liver, kidney, blood-brain barrier, placenta, breast, and other tissues. Major transporters involved include organic anion transporters (OATs, SLC22 family), organic anion transporting polypeptides (OATPs, SLCO family), and multidrug resistance proteins (MRPs, ABCC family). However, the sets of molecular properties of drugs that are necessary for interactions with OATs (OAT1, OAT3) vs. OATPs (OATP1B1, OATP1B3) vs. MRPs (MRP2, MRP4) are not well-understood. Defining these molecular properties is necessary for a better understanding of drug and metabolite handling across the gut-liver-kidney axis, gut-brain axis, and other multi-organ axes. It is also useful for tissue targeting of small molecule drugs and predicting drug-drug interactions and drug-metabolite interactions. Here, we curated a database of drugs shown to interact with these transporters in vitro and used chemoinformatic approaches to describe their molecular properties. We then sought to define sets of molecular properties that distinguish drugs interacting with OATs, OATPs, and MRPs in binary classifications using machine learning and artificial intelligence approaches. We identified sets of key molecular properties (e.g., rotatable bond count, lipophilicity, number of ringed structures) for classifying OATs vs. MRPs and OATs vs. OATPs. However, sets of molecular properties differentiating OATP vs. MRP substrates were less evident, as drugs interacting with MRP2 and MRP4 do not form a tight group owing to differing hydrophobicity and molecular complexity for interactions with the two transporters. If the results also hold for endogenous metabolites, they may deepen our knowledge of organ crosstalk, as described in the Remote Sensing and Signaling Theory. The results also provide a molecular basis for understanding how small organic molecules differentially interact with OATs, OATPs, and MRPs.

Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives

Solute carrier transporters (SLCs) are a class of important transmembrane proteins that are involved in the transportation of diverse solute ions and small molecules into cells. There are approximately 450 SLCs within the human body, and more than a quarter of them are emerging as attractive therapeutic targets for multiple complex diseases, e.g., depression, cancer, and diabetes. However, only 44 unique transporters (∼9.8% of the SLC superfamily) with 3D structures and specific binding sites have been reported. To design innovative and effective drugs targeting diverse SLCs, there are a number of obstacles that need to be overcome. However, computational chemistry, including physics-based molecular modeling and machine learning- and deep learning-based artificial intelligence (AI), provides an alternative and complementary way to the classical drug discovery approach. Here, we present a comprehensive overview on recent advances and existing challenges of the computational techniques in structure-based drug design of SLCs from three main aspects: (i) characterizing multiple conformations of the proteins during the functional process of transportation, (ii) identifying druggability sites especially the cryptic allosteric ones on the transporters for substrates and drugs binding, and (iii) discovering diverse small molecules or synthetic protein binders targeting the binding sites. This work is expected to provide guidelines for a deep understanding of the structure and function of the SLC superfamily to facilitate rational design of novel modulators of the transporters with the aid of state-of-the-art computational chemistry technologies including artificial intelligence.

In Silico prediction of inhibitors for multiple transporters via machine learning methods

Transporters play an indispensable role in facilitating the transport of nutrients, signaling molecules and the elimination of metabolites and toxins in human cells. Contemporary computational methods have been employed in the prediction of transporter inhibitors. However, these methods often focus on isolated endpoints, overlooking the interactions between transporters and lacking good interpretation. In this study, we integrated a comprehensive dataset and constructed models to assess the inhibitory effects on seven transporters. Both conventional machine learning and multi-task deep learning methods were employed. The results demonstrated that the MLT-GAT model achieved superior performance with an average AUC value of 0.882. It is noteworthy that our model excels not only in prediction performance but also in achieving robust interpretability, aided by GNN-Explainer. It provided valuable insights into transporter inhibition. The reliability of our model's predictions positioned it as a promising and valuable tool in the field of transporter inhibition research. Related data and code are available at https://gitee.com/wutiantian99/transporter_code.git.

Identification and characterization of an endogenous biomarker of the renal vectorial transport (OCT2-MATE1)

The renal tubular organic cation transporter 2 (OCT2) and multidrug and toxin extrusion protein 1 (MATE1) mediate the vectorial elimination of many drugs and toxins from the kidney, and endogenous biomarkers for vectorial transport (OCT2-MATE1) would allow more accurate drug dosing and help to characterize drug-drug interactions and toxicity. Human serum uptake in OCT2-overexpressing cells and metabolomics analysis were carried out. Potential biomarkers were verified in vitro and in vivo. The specificity of biomarkers was validated in renal transporter overexpressing cells and the sensitivity was investigated by Km . The results showed that the uptake of thiamine, histamine, and 5-hydroxytryptamine was significantly increased in OCT2-overexpressing cells. In vitro assays confirmed that thiamine, histamine, and 5-hydroxytryptamine were substrates of both OCT2 and MATE1. In vivo measurements indicated that the serum thiamine level was increased significantly in the presence of the rOCT2 inhibitor cimetidine, and the level in renal tissue was increased significantly by the rMATE1 inhibitor pyrimethamine. There were no significant changes in the uptake or efflux of thiamine in cell lines overexpressed OAT1, OAT2, OAT3, MRP4, organic anion transporting polypeptide 4C1, P-gp, peptide transporter 2, urate transporter 1, and OAT4. The Km for thiamine with OCT2 and MATE1 were 71.2 and 10.8 μM, respectively. In addition, the cumulative excretion of thiamine at 2 and 4 h was strongly correlated with metformin excretion (R2  > 0.6). Thus, thiamine is preferentially secreted by the OCT2 and MATE1 in renal tubules and can provide a reference value for evaluating the function of the renal tubular OCT2-MATE1.

Computational and artificial intelligence-based approaches for drug metabolism and transport prediction

Drug metabolism and transport, orchestrated by drug-metabolizing enzymes (DMEs) and drug transporters (DTs), are implicated in drug-drug interactions (DDIs) and adverse drug reactions (ADRs). Reliable and precise predictions of DDIs and ADRs are critical in the early stages of drug development to reduce the rate of drug candidate failure. A variety of experimental and computational technologies have been developed to predict DDIs and ADRs. Recent artificial intelligence (AI) approaches offer new opportunities for better predicting and understanding the complex processes related to drug metabolism and transport. We summarize the role of major DMEs and DTs, and provide an overview of current progress in computational approaches for the prediction of drug metabolism, transport, and DDIs, with an emphasis on AI including machine learning (ML) and deep learning (DL) modeling.

Machine Learning Techniques Applied to the Study of Drug Transporters

With the advancement of computer technology, machine learning-based artificial intelligence technology has been increasingly integrated and applied in the fields of medicine, biology, and pharmacy, thereby facilitating their development. Transporters have important roles in influencing drug resistance, drug-drug interactions, and tissue-specific drug targeting. The investigation of drug transporter substrates and inhibitors is a crucial aspect of pharmaceutical development. However, long duration and high expenses pose significant challenges in the investigation of drug transporters. In this review, we discuss the present situation and challenges encountered in applying machine learning techniques to investigate drug transporters. The transporters involved include ABC transporters (P-gp, BCRP, MRPs, and BSEP) and SLC transporters (OAT, OATP, OCT, MATE1,2-K, and NET). The aim is to offer a point of reference for and assistance with the progression of drug transporter research, as well as the advancement of more efficient computer technology. Machine learning methods are valuable and attractive for helping with the study of drug transporter substrates and inhibitors, but continuous efforts are still needed to develop more accurate and reliable predictive models and to apply them in the screening process of drug development to improve efficiency and success rates.

Loss of the Kidney Urate Transporter, Urat1, Leads to Disrupted Redox Homeostasis in Mice

High uric acid is associated with gout, hypertension, metabolic syndrome, cardiovascular disease, and kidney disease. URAT1 (SLC22A12), originally discovered in mice as Rst, is generally considered a very selective uric acid transporter compared to other closely-related kidney uric acid transporters such as OAT1 (SLC22A6, NKT) and OAT3 (SLC22A8). While the role of URAT1 in regulating human uric acid is well-established, in recent studies the gene has been linked to redox regulation in flies as well as progression of renal cell carcinoma. We have now identified over twenty metabolites in the Urat1 knockout that are generally distinct from metabolites accumulating in the Oat1 and Oat3 knockout mice, with distinct molecular properties as revealed by chemoinformatics and machine learning analysis. These metabolites are involved in seemingly disparate aspects of cellular metabolism, including pyrimidine, fatty acid, and amino acid metabolism. However, through integrative systems metabolic analysis of the transcriptomic and metabolomic data using a human metabolic reconstruction to build metabolic genome-scale models (GEMs), the cellular response to loss of Urat1/Rst revealed compensatory processes related to reactive oxygen species handling and maintaining redox state balances via Vitamin C metabolism and cofactor charging reactions. These observations are consistent with the increasingly appreciated role of the antioxidant properties of uric acid. Collectively, the results highlight the role of Urat1/Rst as a transporter strongly tied to maintaining redox homeostasis, with implications for metabolic side effects from drugs that block its function.

Inhibition of proteasome, but not lysosome, upregulates organic anion transporter 3 in vitro and in vivo

Organic anion transporter 3 (OAT3), an indispensable basolateral membrane transporter predominantly distributed in the kidney proximal tubules, mediated the systemic clearance of substrates including clinical drugs, nutrients, endogenous and exogenous metabolites, toxins, and critically sustains body homeostasis. Preliminary data in this study showed that classical proteasome inhibitors (e.g., MG132), but not lysosome inhibitors, significantly increased the OAT3 ubiquitination and OAT3-mediated transport of estrone sulfate (ES) in OAT3 stable expressing cells, indicating that proteasome rather than lysosome is involved in the intracellular fate of OAT3. Next, bortezomib and carfilzomib, two FDA-approved and widely applied anticancer agents through selective targeting proteasome, were further used to define the role of inhibiting proteasome in OAT3 regulation and related molecular mechanisms. The results showed that 20S proteasome activity in cell lysates was suppressed with bortezomib and carfilzomib treatment, leading to the increased OAT3 ubiquitination, stimulated transport activity of ES, enhanced OAT3 surface and total expression. The upregulated OAT3 function by proteasome inhibition was attributed to the augment in maximum transport velocity and stability of membrane OAT3. Lastly, in vivo study using Sprague Dawley rats validated that proteasome inhibition using bortezomib induced enhancement of OAT3 ubiquitination and membrane expression in kidney. These data suggest that activity of proteasome but not lysosome could have an impact on the physiological function of OAT3, and proteasome displayed a promising target for OAT3 regulation in vitro and in vivo, and could be used in restoring OAT3 impairment under pathological conditions, avoiding OAT3-associated toxicity and diseases, ensuring drug efficacy and safety.

The kidney drug transporter OAT1 regulates gut microbiome-dependent host metabolism

Organic anion transporter 1 (OAT1/SLC22A6, NKT) is a multispecific drug transporter in the kidney with numerous substrates, including pharmaceuticals, endogenous metabolites, natural products, and uremic toxins. Here, we show that OAT1 regulates levels of gut microbiome-derived metabolites. We depleted the gut microbiome of Oat1-KO and WT mice and performed metabolomics to analyze the effects of genotype (KO versus WT) and microbiome depletion. OAT1 is an in vivo intermediary between the host and the microbes, with 40 of the 162 metabolites dependent on the gut microbiome also impacted by loss of Oat1. Chemoinformatic analysis revealed that the altered metabolites (e.g., indoxyl sulfate, p-cresol sulfate, deoxycholate) had more ring structures and sulfate groups. This indicates a pathway from gut microbes to liver phase II metabolism, to renal OAT1-mediated transport. The idea that multiple gut-derived metabolites directly interact with OAT1 was confirmed by in vitro transport and magnetic bead binding assays. We show that gut microbiome-derived metabolites dependent on OAT1 are impacted in a chronic kidney disease (CKD) model and human drug-metabolite interactions. Consistent with the Remote Sensing and Signaling Theory, our results support the view that drug transporters (e.g., OAT1, OAT3, OATP1B1, OATP1B3, MRP2, MRP4, ABCG2) play a central role in regulating gut microbe-dependent metabolism, as well as interorganismal communication between the host and microbiome.

Pancreatic Hormone Insulin Modulates Organic Anion Transporter 1 in the Kidney: Regulation via Remote Sensing and Signaling Network

Organic anion transporter 1 (OAT1) expressed in the kidney plays an important role in the elimination of numerous anionic drugs used in the clinic. We report here that insulin, a pancreas-secreted hormone, regulated the expression and activity of kidney-specific OAT1 both in cultured cells and in rats. We showed that treatment of OAT1-expressing cells with insulin led to an increase in OAT1 expression, transport activity, and SUMOylation. Such insulin-induced increase was blocked by afuresertib, a specific inhibitor for protein kinase B (PKB), suggesting insulin regulates OAT1 through PKB signaling pathway. Furthermore, insulin stimulated transport activity and SUMOylation of endogenously expressed OAT1 in rat kidneys. In conclusion, our data support a remote sensing and signaling model, in which OAT1 plays an essential role in intercellular and inter-organ communication and in maintaining local and whole-body homeostasis. Such complex and dedicated communication is carried out by insulin, and PKB signaling and membrane sorting.

Protein Kinases and Cross-talk between Post-translational Modifications in the Regulation of Drug Transporters

Drug transporters are modulators for drug absorption, distribution, and excretion. Key drug transporters including P-glycoprotein and breast cancer resistance protein of the ABC superfamily; organic anion transporting polypeptide 1B1 and 1B3, organic anion transporter 1 and 3, and organic cation transporter 2, as well as multidrug and toxin extrusion 1 and 2 of the SLC superfamily have been recommended by regulatory agencies to be investigated and evaluated in drug-drug interaction (DDI) studies due to their important roles in determining the efficacy, toxicity and DDI of various drugs. Drug transporters are subjected to multiple levels of control and post-translational modifications (PTMs) provide rapid and versatile ways of regulation. Under pathologic and/or pharmacological conditions, PTMs may be altered in the cellular system, leading to functional changes of transporter proteins. Phosphorylation is by far the most actively investigated form of PTMs in the regulation of transporters. Further, studies in recent years also found that protein kinases coordinate with other PTMs for the dynamic control of these membrane proteins. Here we summarized the regulation of major drug transporters by protein kinases and their cross-talking with other PTMs that may generate a complex regulatory network for fine-tuning the function of these important drug processing modulators. SIGNIFICANCE STATEMENT: Kinases regulate drug transporters in versatile manners; Kinase regulation cross-talks with other PTMs, forming a complex network for transporter regulation; Pathological and/or pharmacological conditions may alter PTMs and affect transporter function with different molecular mechanisms.

Machine Learning Models Identify New Inhibitors for Human OATP1B1

The uptake transporter OATP1B1 (SLC01B1) is largely localized to the sinusoidal membrane of hepatocytes and is a known victim of unwanted drug-drug interactions. Computational models are useful for identifying potential substrates and/or inhibitors of clinically relevant transporters. Our goal was to generate OATP1B1 in vitro inhibition data for [3H] estrone-3-sulfate (E3S) transport in CHO cells and use it to build machine learning models to facilitate a comparison of seven different classification models (Deep learning, Adaboosted decision trees, Bernoulli naïve bayes, k-nearest neighbors (knn), random forest, support vector classifier (SVC), logistic regression (lreg), and XGBoost (xgb)] using ECFP6 fingerprints to perform 5-fold, nested cross validation. In addition, we compared models using 3D pharmacophores, simple chemical descriptors alone or plus ECFP6, as well as ECFP4 and ECFP8 fingerprints. Several machine learning algorithms (SVC, lreg, xgb, and knn) had excellent nested cross validation statistics, particularly for accuracy, AUC, and specificity. An external test set containing 207 unique compounds not in the training set demonstrated that at every threshold SVC outperformed the other algorithms based on a rank normalized score. A prospective validation test set was chosen using prediction scores from the SVC models with ECFP fingerprints and were tested in vitro with 15 of 19 compounds (84% accuracy) predicted as active (≥20% inhibition) showed inhibition. Of these compounds, six (abamectin, asiaticoside, berbamine, doramectin, mobocertinib, and umbralisib) appear to be novel inhibitors of OATP1B1 not previously reported. These validated machine learning models can now be used to make predictions for drug-drug interactions for human OATP1B1 alongside other machine learning models for important drug transporters in our MegaTrans software.

Drug transporters OAT1 and OAT3 have specific effects on multiple organs and gut microbiome as revealed by contextualized metabolic network reconstructions

In vitro and in vivo studies have established the organic anion transporters OAT1 (SLC22A6, NKT) and OAT3 (SLC22A8) among the main multi-specific "drug" transporters. They also transport numerous endogenous metabolites, raising the possibility of drug-metabolite interactions (DMI). To help understand the role of these drug transporters on metabolism across scales ranging from organ systems to organelles, a formal multi-scale analysis was performed. Metabolic network reconstructions of the omics-alterations resulting from Oat1 and Oat3 gene knockouts revealed links between the microbiome and human metabolism including reactions involving small organic molecules such as dihydroxyacetone, alanine, xanthine, and p-cresol-key metabolites in independent pathways. Interestingly, pairwise organ-organ interactions were also disrupted in the two Oat knockouts, with altered liver, intestine, microbiome, and skin-related metabolism. Compared to older models focused on the "one transporter-one organ" concept, these more sophisticated reconstructions, combined with integration of a multi-microbial model and more comprehensive metabolomics data for the two transporters, provide a considerably more complex picture of how renal "drug" transporters regulate metabolism across the organelle (e.g. endoplasmic reticulum, Golgi, peroxisome), cellular, organ, inter-organ, and inter-organismal scales. The results suggest that drugs interacting with OAT1 and OAT3 can have far reaching consequences on metabolism in organs (e.g. skin) beyond the kidney. Consistent with the Remote Sensing and Signaling Theory (RSST), the analysis demonstrates how transporter-dependent metabolic signals mediate organ crosstalk (e.g., gut-liver-kidney) and inter-organismal communication (e.g., gut microbiome-host).

Construction and Evaluation of a Novel Organic Anion Transporter 1/3 CRISPR/Cas9 Double-Knockout Rat Model

BACKGROUND

Organic anion transporter 1 (OAT1) and OAT3 have an overlapping spectrum of substrates such that one can exert a compensatory effect when the other is dysfunctional. As a result, the knockout of either OAT1 or OAT3 is not reflected in a change in the excretion of organic anionic substrates. To date, only the mOAT1 and mOAT3 individual knockout mouse models have been available.

METHODS

In this study, we successfully generated a Slc22a6/Slc22a8 double-knockout (KO) rat model using CRISPR/Cas9 technology and evaluated its biological properties.

RESULTS

The double-knockout rat model did not expression mRNA for rOAT1 or rOAT3 in the kidneys. Consistently, the renal excretion of p-aminohippuric acid (PAH), the classical substrate of OAT1/OAT3, was substantially decreased in the Slc22a6/Slc22a8 double-knockout rats. The relative mRNA level of Slco4c1 was up-regulated in KO rats. No renal pathological phenotype was evident. The renal elimination of the organic anionic drug furosemide was nearly abolished in the Slc22a6/Slc22a8 knockout rats, but elimination of the organic cationic drug metformin was hardly affected.

CONCLUSIONS

These results demonstrate that this rat model is a useful tool for investigating the functions of OAT1/OAT3 in metabolic diseases, drug metabolism and pharmacokinetics, and OATs-mediated drug interactions.

Interaction of the main active components in Shengmai formula mediated by organic anion transporter 1 (OAT1)

ETHNOPHARMACOLOGICAL RELEVANCE

Shengmai formula (SMF) is a classical traditional Chinese medicine prescription, which is widely used in the treatment of cardiovascular and cerebrovascular diseases. Our previous studies have demonstrated that some components in SMF can interact with each other through breast cancer resistance protein, sodium taurocholate co-transporting polypeptide, organic anion transporting polypeptide 1B1 and 1B3. Organic anion transporter 1 (OAT1) is highly expressed in kidney, mediating the elimination of many endogenous and exogenous substances. However, the interaction between the main active components in SMF and OAT1 is not clear.

AIM OF THE STUDY

This study aimed to investigate the interactions of the major bioactive components in SMF mediated by OAT1.

MATERIALS AND METHODS

Four main fractions, namely, ginseng total saponins (GTS), ophiopogon total saponins (OTS), ophiopogon total flavonoids (OTF), fructus schisandrae total lignans (STL), and 12 active components, namely, ginsenoside Rg1, Re, Rd and Rb1, ophiopogonin D and D', methylophiopogonanone A and B, schizandrol A and B, schizandrin A and B, were selected to explore the interactions of SMF with OAT1 using cell and rat models.

RESULTS

The above four main fractions in SMF all exhibited inhibitory effects on the uptake of 6-carboxyfluorescein (6-CF), a classic substrate of OAT1. Among the 12 main effective components, only ginsenoside Re, Rd, and methylophiopogonanone A showed inhibition of 6-CF uptake. Additionally, we found that schizandrin B was transported by HEK293-OAT1 cells, and schizandrin B uptake was markedly inhibited by GTS, OTS, OTF, ginsenoside Re, Rd, and methylophiopogonanone A. In rats, ginsenoside Re, Rd, and methylophiopogonanone A jointly increased the AUC_(0-t), AUC_(0-∞), and C_max of schizandrin B, but they decreased its clearance in plasma and excretion in urine.

CONCLUSIONS

Ginsenoside Re, Rd, and methylophiopogonanone A were the potential inhibitors of OAT1, and may interact with some drugs serving as OAT1 substrates clinically. Schizandrin B was a potential OAT1 substrate, and its OAT1-mediated transport was inhibited by ginsenoside Re, Rd, and methylophiopogonanone A. OAT1-mediated interactions of the main active components in SMF can be regarded as one of the important compatibility mechanisms of traditional Chinese medicine preparations.

Blockade of Organic Anion Transport in Humans After Treatment With the Drug Probenecid Leads to Major Metabolic Alterations in Plasma and Urine

Probenecid is used to treat gout and hyperuricemia as well as increase plasma levels of antiviral drugs and antibiotics. In vivo, probenecid mainly inhibits the renal SLC22 organic anion transporters OAT1 (SLC22A6), OAT3 (SLC22A8), and URAT1 (SLC22A12). To understand the endogenous role of these transporters in humans, we administered probenecid to 20 healthy participants and metabolically profiled the plasma and urine before and after dosage. Hundreds of metabolites were significantly altered, indicating numerous drug-metabolite interactions. We focused on potential OAT1 substrates by identifying 97 metabolites that were significantly elevated in the plasma and decreased in the urine, indicating OAT-mediated clearance. These included signaling molecules, antioxidants, and gut microbiome products. In contrast, urate was the only metabolite significantly decreased in the plasma and elevated in the urine, consistent with an effect on renal reuptake by URAT1. Additional support comes from metabolomics analyses of our Oat1 and Oat3 knockout mice, where over 50% of the metabolites that were likely OAT substrates in humans were elevated in the serum of the mice. Fifteen of these compounds were elevated in both knockout mice, whereas six were exclusive to the Oat1 knockout and 4 to the Oat3 knockout. These may be endogenous biomarkers of OAT function. We also propose a probenecid stress test to evaluate kidney proximal tubule organic anion transport function in kidney disease. Consistent with the Remote Sensing and Signaling Theory, the profound changes in metabolite levels following probenecid treatment support the view that SLC22 transporters are hubs in the regulation of systemic human metabolism.

Aristolochic acid I induces proximal tubule injury through ROS/HMGB1/mt DNA mediated activation of TLRs

Aristolochic acids (AAs) are extracted from certain plants as folk remedies for centuries until their nephrotoxicity and carcinogenicity were recognized. Aristolochic acid I (AAI) is one of the main pathogenic compounds, and it has nephrotoxic, carcinogenic and mutagenic effects. Previous studies have shown that AAI acts mainly on proximal renal tubular epithelial cells; however, the mechanisms of AAI‐induced proximal tubule cell damage are still not fully characterized. We exposed human kidney proximal tubule cells (PTCs; HK2 cell line) to AAI in vitro at different time/dose conditions and assessed cell proliferation, reactive oxygen species (ROS) generation, nitric oxide (NO) production, m‐RNA/ protein expressions and mitochondrial dysfunction. AAI exposure decreased proliferation and increased apoptosis, ROS generation / NO production in PTCs significantly at 24 h. Gene/ protein expression studies demonstrated activation of innate immunity (TLRs 2, 3, 4 and 9, HMGB1), inflammatory (IL6, TNFA, IL1B, IL18, TGFB and NLRP3) and kidney injury (LCN2) markers. AAI also induced epithelial‐mesenchymal transition (EMT) and mitochondrial dysfunction in HK2 cells. TLR9 knock‐down and ROS inhibition were able to ameliorate the toxic effect of AAI. In conclusion, AAI treatment caused injury to PTCs through ROS‐HMGB1/mitochondrial DNA (mt DNA)‐mediated activation of TLRs and inflammatory response.

Insights into the structure and function of the human organic anion transporter 1 in lipid bilayer membranes

The human SLC22A6/OAT1 plays an important role in the elimination of a broad range of endogenous substances and xenobiotics thus attracting attention from the pharmacological community. Furthermore, OAT1 is also involved in key physiological events such as the remote inter-organ communication. Despite its significance, the knowledge about hOAT1 structure and the transport mechanism at the atomic level remains fragmented owing to the lack of resolved structures. By means of protein-threading modeling refined by μs-scaled Molecular Dynamics simulations, the present study provides the first robust model of hOAT1 in outward-facing conformation. Taking advantage of the AlphaFold 2 predicted structure of hOAT1 in inward-facing conformation, we here provide the essential structural and functional features comparing both states. The intracellular motifs conserved among Major Facilitator Superfamily members create a so-called “charge-relay system” that works as molecular switches modulating the conformation. The principal element of the event points at interactions of charged residues that appear crucial for the transporter dynamics and function. Moreover, hOAT1 model was embedded in different lipid bilayer membranes highlighting the crucial structural dependence on lipid-protein interactions. MD simulations supported the pivotal role of phosphatidylethanolamine components to the protein conformation stability. The present model is made available to decipher the impact of any observed polymorphism and mutation on drug transport as well as to understand substrate binding modes.

Impaired Tubular Secretion of Organic Solutes in Advanced Chronic Kidney Disease

BACKGROUND

The clearance of solutes removed by tubular secretion may be altered out of proportion to the GFR in CKD. Recent studies have described considerable variability in the secretory clearance of waste solutes relative to the GFR in patients with CKD.

METHODS

To test the hypothesis that secretory clearance relative to GFR is reduced in patients approaching dialysis, we used metabolomic analysis to identify solutes in simultaneous urine and plasma samples from 16 patients with CKD and an eGFR of 7±2 ml/min per 1.73 m2 and 16 control participants. Fractional clearances were calculated as the ratios of urine to plasma levels of each solute relative to those of creatinine and urea in patients with CKD and to those of creatinine in controls.

RESULTS

Metabolomic analysis identified 39 secreted solutes with fractional clearance >3.0 in control participants. Fractional clearance values in patients with CKD were reduced on average to 65%±27% of those in controls. These values were significantly lower for 18 of 39 individual solutes and significantly higher for only one. Assays of the secreted anions phenylacetyl glutamine, p-cresol sulfate, indoxyl sulfate, and hippurate confirmed variable impairment of secretory clearances in advanced CKD. Fractional clearances were markedly reduced for phenylacetylglutamine (4.2±0.6 for controls versus 2.3±0.6 for patients with CKD; P<0.001), p-cresol sulfate (8.6±2.6 for controls versus 4.1±1.5 for patients with CKD; P<0.001), and indoxyl sulfate (23.0±7.3 versus 7.5±2.8; P<0.001) but not for hippurate (10.2±3.8 versus 8.4±2.6; P=0.13).

CONCLUSIONS

Secretory clearances for many solutes are reduced more than the GFR in advanced CKD. Impaired secretion of these solutes might contribute to uremic symptoms as patients approach dialysis.

Molecular Properties of Drugs Handled by Kidney OATs and Liver OATPs Revealed by Chemoinformatics and Machine Learning: Implications for Kidney and Liver Disease

In patients with liver or kidney disease, it is especially important to consider the routes of metabolism and elimination of small-molecule pharmaceuticals. Once in the blood, numerous drugs are taken up by the liver for metabolism and/or biliary elimination, or by the kidney for renal elimination. Many common drugs are organic anions. The major liver uptake transporters for organic anion drugs are organic anion transporter polypeptides (OATP1B1 or SLCO1B1; OATP1B3 or SLCO1B3), whereas in the kidney they are organic anion transporters (OAT1 or SLC22A6; OAT3 or SLC22A8). Since these particular OATPs are overwhelmingly found in the liver but not the kidney, and these OATs are overwhelmingly found in the kidney but not liver, it is possible to use chemoinformatics, machine learning (ML) and deep learning to analyze liver OATP-transported drugs versus kidney OAT-transported drugs. Our analysis of >30 quantitative physicochemical properties of OATP- and OAT-interacting drugs revealed eight properties that in combination, indicate a high propensity for interaction with "liver" transporters versus "kidney" ones based on machine learning (e.g., random forest, k-nearest neighbors) and deep-learning classification algorithms. Liver OATPs preferred drugs with greater hydrophobicity, higher complexity, and more ringed structures whereas kidney OATs preferred more polar drugs with more carboxyl groups. The results provide a strong molecular basis for tissue-specific targeting strategies, understanding drug-drug interactions as well as drug-metabolite interactions, and suggest a strategy for how drugs with comparable efficacy might be chosen in chronic liver or kidney disease (CKD) to minimize toxicity.

Renal and non-renal response of ABC and SLC transporters in chronic kidney disease

INTRODUCTION

The solute carrier (SLC) and the ATP-binding cassette (ABC) transporter superfamilies play essential roles in the disposition of small molecules (endogenous metabolites, uremic toxins, drugs) in the blood, kidney, liver, intestine, and other organs. In chronic kidney disease (CKD), the loss of renal function is associated with altered function of remote organs. As renal function declines, many molecules accumulate in the plasma. Many studies now support the view that ABC and SLC transporters as well as drug metabolizing enzymes (DMEs) in renal and non-renal tissues are directly or indirectly affected by the presence of various types of uremic toxins, including those derived from the gut microbiome; this can lead to aberrant inter-organ communication.

AREAS COVERED

Here, the expression, localization and/or function of various SLC and ABC transporters as well as DMEs in the kidney and other organs are discussed in the context of CKD and systemic pathophysiology.

EXPERT OPINION

According to the Remote Sensing and Signaling Theory (RSST), a transporter and DME-centric network that optimizes local and systemic metabolism maintains homeostasis in the steady state and resets homeostasis following perturbations due to renal dysfunction. The implications of this view for pharmacotherapy of CKD are also discussed.

Uremic Toxins in Organ Crosstalk

Many putative uremic toxins—like indoxyl sulfate, p-cresol sulfate, kynurenic acid, uric acid, and CMPF—are organic anions. Both inter-organ and inter-organismal communication are involved. For example, the gut microbiome is the main source of indole, which, after modification by liver drug metabolizing enzymes (DMEs), becomes indoxyl sulfate. Various organic anion transporters (organic anion transporters, OATs; organic anion-transporting polypeptides, OATPs; multidrug resistance-associated proteins, MRPs, and other ABC transporters like ABCG2)—often termed “drug transporters”—mediate movement of uremic toxins through cells and organs. In the kidney proximal tubule, critical roles for OAT1 and OAT3 in regulating levels of protein-bound uremic toxins have been established using knock-out mice. OATs are important in maintaining residual tubular function in chronic kidney disease (CKD); as CKD progresses, intestinal transporters like ABCG2, which extrude urate and other organic anions into the gut lumen, seem to help restore homeostasis. Uremic toxins like indoxyl sulfate also regulate signaling and metabolism, potentially affecting gene expression in extra-renal tissues as well as the kidney. Focusing on the history and evolving story of indoxyl sulfate, we discuss how uremic toxins appear to be part of an extensive “remote sensing and signaling” network—involving so-called drug transporters and drug metabolizing enzymes which modulate metabolism and signaling. This systems biology view of uremic toxins is leading to a new appreciation of uremia as partly due to disordered remote sensing and signaling mechanisms–resulting from, and causing, aberrant inter-organ (e.g., gut-liver- kidney-CNS) and inter-organismal (e.g., gut microbiome-host) communication.

A key role for the transporter OAT1 in systemic lipid metabolism

Organic anion transporter 1 (OAT1/SLC22A6) is a drug transporter with numerous xenobiotic and endogenous substrates. The Remote Sensing and Signaling Theory suggests that drug transporters with compatible ligand preferences can play a role in “organ crosstalk,” mediating overall organismal communication. Other drug transporters are well known to transport lipids, but surprisingly little is known about the role of OAT1 in lipid metabolism. To explore this subject, we constructed a genome-scale metabolic model using omics data from the Oat1 knockout mouse. The model implicated OAT1 in the regulation of many classes of lipids, including fatty acids, bile acids, and prostaglandins. Accordingly, serum metabolomics of Oat1 knockout mice revealed increased polyunsaturated fatty acids, diacylglycerols, and long-chain fatty acids and decreased ceramides and bile acids when compared with wildtype controls. Some aged knockout mice also displayed increased lipid droplets in the liver when compared with wildtype mice. Chemoinformatics and machine learning analyses of these altered lipids defined molecular properties that form the structural basis for lipid-transporter interactions, including the number of rings, positive charge/volume, and complexity of the lipids. Finally, we obtained targeted serum metabolomics data after short-term treatment of rodents with the OAT-inhibiting drug probenecid to identify potential drug–metabolite interactions. The treatment resulted in alterations in eicosanoids and fatty acids, further supporting our metabolic reconstruction predictions. Consistent with the Remote Sensing and Signaling Theory, the data support a role of OAT1 in systemic lipid metabolism.

Coordinate regulation of systemic and kidney tryptophan metabolism by the drug transporters OAT1 and OAT3

How organs sense circulating metabolites is a key question. Here, we show that the multispecific organic anion transporters of drugs, OAT1 (SLC22A6 or NKT) and OAT3 (SLC22A8), play a role in organ sensing. Metabolomics analyses of the serum of Oat1 and Oat3 knockout mice revealed changes in tryptophan derivatives involved in metabolism and signaling. Several of these metabolites are derived from the gut microbiome and are implicated as uremic toxins in chronic kidney disease. Direct interaction with the transporters was supported with cell-based transport assays. To assess the impact of the loss of OAT1 or OAT3 function on the kidney, an organ where these uptake transporters are highly expressed, knockout transcriptomic data were mapped onto a “metabolic task”-based computational model that evaluates over 150 cellular functions. Despite the changes of tryptophan metabolites in both knockouts, only in the Oat1 knockout were multiple tryptophan-related cellular functions increased. Thus, deprived of the ability to take up kynurenine, kynurenate, anthranilate, and N-formylanthranilate through OAT1, the kidney responds by activating its own tryptophan-related biosynthetic pathways. The results support the Remote Sensing and Signaling Theory, which describes how “drug” transporters help optimize levels of metabolites and signaling molecules by facilitating organ cross talk. Since OAT1 and OAT3 are inhibited by many drugs, the data implies potential for drug–metabolite interactions. Indeed, treatment of humans with probenecid, an OAT-inhibitor used to treat gout, elevated circulating tryptophan metabolites. Furthermore, given that regulatory agencies have recommended drugs be tested for OAT1 and OAT3 binding or transport, it follows that these metabolites can be used as endogenous biomarkers to determine if drug candidates interact with OAT1 and/or OAT3.

Identification of Novel High-Affinity Substrates of OCT1 Using Machine Learning-Guided Virtual Screening and Experimental Validation

OCT1 is the most highly expressed cation transporter in the liver and affects pharmacokinetics and pharmacodynamics. Newly marketed drugs have previously been screened as potential OCT1 substrates and verified by virtual docking. Here, we used machine learning with transport experiment data to predict OCT1 substrates based on classic molecular descriptors, pharmacophore features, and extended-connectivity fingerprints and confirmed them by in vitro uptake experiments. We virtually screened a database of more than 1000 substances. Nineteen predicted substances were chosen for in vitro testing. Sixteen of the 19 newly tested substances (85%) were confirmed as, mostly strong, substrates, including edrophonium, fenpiverinium, ritodrine, and ractopamine. Even without a crystal structure of OCT1, machine learning algorithms predict substrates accurately and may contribute not only to a more focused screening in drug development but also to a better molecular understanding of OCT1 in general.

(-)-Epigallocatechin-3-gallate Inhibits Human and Rat Renal Organic Anion Transporters

Organic anion transporter 1 (OAT1, SLC22A6) and 3 (OAT3, SLC22A8) are multispecific drug transporters highly expressed on the basolateral membranes of the renal proximal tubules. OAT1 and OAT3 mediate the tubular secretion of clinically significant drugs; thus, they influence the pharmacokinetics of drugs and further determine their efficacy and toxicity. OAT1 and OAT3 are also the target of drug-drug interactions. In this study, we examined the effects of the tea catechin (-)-epigallocatechin-3-gallate (EGCG) on human (h) and rat (r) OAT1 and OAT3 using the fluorescent organic anion 6-carboxyfluorescein (6-CF) and hOAT1-, hOAT3-, rOat1-, or rOat3-expressing HEK293 cells and on renal elimination of 6-CF in rats. 6-CF is transported by hOAT1, hOAT3, rOat1, and rOat3. 6-CF is urinary excreted by Oats in rats. EGCG, a dominant catechin in green tea leaf, inhibits human and rat OAT1 and OAT3 and reduces the renal elimination of 6-CF in rats. Our findings are useful for the assessment of food-drug interactions mediated by renal OATs.

Post-translational regulation of the major drug transporters in the families of organic anion transporters and organic anion-transporting polypeptides

The organic anion transporters (OATs) and organic anion-transporting polypeptides (OATPs) belong to the solute carrier (SLC) transporter superfamily and play important roles in handling various endogenous and exogenous compounds of anionic charge. The OATs and OATPs are often implicated in drug therapy by impacting the pharmacokinetics of clinically important drugs and, thereby, drug exposure in the target organs or cells. Various mechanisms (e.g. genetic, environmental, and disease-related factors, drug-drug interactions, and food-drug interactions) can lead to variations in the expression and activity of the anion drug-transporting proteins of OATs and OATPs, possibly impacting the therapeutic outcomes. Previous investigations mainly focused on the regulation at the transcriptional level and drug-drug interactions as competing substrates or inhibitors. Recently, evidence has accumulated that cellular trafficking, post-translational modification, and degradation mechanisms serve as another important layer for the mechanisms underlying the variations in the OATs and OATPs. This review will provide a brief overview of the major OATs and OATPs implicated in drug therapy and summarize recent progress in our understanding of the post-translational modifications, in particular ubiquitination and degradation pathways of the individual OATs and OATPs implicated in drug therapy.

Drug Metabolites Potently Inhibit Renal Organic Anion Transporters, OAT1 and OAT3

Human OAT1 and OAT3 play major roles in renal drug elimination and drug-drug interactions. However, there is little information on the interactions of drug metabolites with transporters. The goal of this study was to characterize the interactions of drug metabolites with OAT1 and OAT3 and compare their potencies of inhibition with those of their corresponding parent drugs. Using HEK293 cells stably transfected with OAT1 and OAT3, 25 drug metabolites and their corresponding parent drugs were screened for inhibitory effects on OAT1-and OAT3-mediated 6-carboxyfluorescein uptake at a screening concentration of 200 μM for all but 3 compounds. 20 and 24 drug metabolites were identified as inhibitors (inhibition > 50%) of OAT1 and OAT3, respectively. Seven drug metabolites were potent inhibitors of either or both OAT1 and OAT3 with K_i values less than 1 μM. 22 metabolites were more potent inhibitors of OAT3 than OAT1. Importantly, one drug and four metabolites were predicted to inhibit OAT3 at unbound plasma concentrations achieved clinically (C_max,u/K_i values ≥ 0.1). In conclusion, our study highlights the potential interactions of drug metabolites with OAT1 and OAT3 at clinically relevant concentrations, suggesting that drug metabolites may modulate therapeutic and adverse drug response by inhibiting renal drug transporters.

Impaired Tubular Secretion of Organic Solutes in Acute Kidney Injury

BACKGROUND

Impairment of kidney function is routinely assessed by measuring the accumulation of creatinine, an organic solute cleared largely by glomerular filtration. We tested whether the clearance of solutes that undergo tubular secretion is reduced in proportion to the clearance of creatinine in humans with AKI.

METHODS

Four endogenously produced organic solutes (phenylacetylglutamine [PAG], hippurate [HIPP], indoxyl sulfate [IS], and p-cresol sulfate [PCS]) were measured in spot urine and plasma samples from ten patients with AKI and 17 controls. Fractional clearance relative to creatinine was calculated to assess tubular secretion. Fractional clearance values were calculated in terms of the free, unbound levels of HIPP, IS, and PCS that bind to plasma proteins.

RESULTS

Fractional clearance values for PAG, HIPP, IS, and PCS were >1.0 in patients with AKI as well as controls, indicating that these solutes were still secreted by the tubules of the injured kidneys. Fractional clearance values were, however, significantly lower in patients with AKI than controls, indicating that kidney injury reduced tubular secretion more than glomerular filtration (AKI versus control: PAG, 2.1±0.7 versus 4.6±1.4, P<0.001; HIPP, 10±5 versus 15±7, P=0.02; IS, 10±6 versus 28±7, P<0.001; PCS, 3.3±1.8 versus 10±3, P<0.001). Free plasma levels rose out of proportion to total plasma levels for each of the bound solutes in AKI, so that calculating their fractional clearance in terms of their total plasma levels failed to reveal their impaired secretion.

CONCLUSIONS

Tubular secretion of organic solutes can be reduced out of proportion to glomerular filtration in AKI. Impaired secretion of protein-bound solutes may be more reliably detected when clearances are expressed in terms of their free, unbound levels in the plasma.

Regulation of organic anion transporters: Role in physiology, pathophysiology, and drug elimination

The members of the organic anion transporter (OAT) family are mainly expressed in kidney, liver, placenta, intestine, and brain. These transporters play important roles in the disposition of clinical drugs, pesticides, signaling molecules, heavy metal conjugates, components of phytomedicines, and toxins, and therefore critical for maintaining systemic homeostasis. Alterations in the expression and function of OATs contribute to the intra- and inter-individual variability of the therapeutic efficacy and the toxicity of many drugs, and to many pathophysiological conditions. Consequently, the activity of these transporters must be highly regulated to carry out their normal functions. This review will present an update on the recent advance in understanding the cellular and molecular mechanisms underlying the regulation of renal OATs, emphasizing on the post-translational modification (PTM), the crosstalk among these PTMs, and the remote sensing and signaling network of OATs. Such knowledge will provide significant insights into the roles of these transporters in health and disease.

The Systems Biology of Drug Metabolizing Enzymes and Transporters: Relevance to Quantitative Systems Pharmacology

Quantitative systems pharmacology (QSP) has emerged as a transformative science in drug discovery and development. It is now time to fully rethink the biological functions of drug metabolizing enzymes (DMEs) and transporters within the framework of QSP models. The large set of DME and transporter genes are generally considered from the perspective of the absorption, distribution, metabolism, and excretion (ADME) of drugs. However, there is a growing amount of data on the endogenous physiology of DMEs and transporters. Recent studies—including systems biology analyses of “omics” data as well as metabolomics studies—indicate that these enzymes and transporters, which are often among the most highly expressed genes in tissues like liver, kidney, and intestine, have coordinated roles in fundamental biological processes. Multispecific DMEs and transporters work together with oligospecific and monospecific ADME proteins in a large multiorgan remote sensing and signaling network. We use the Remote Sensing and Signaling Theory (RSST) to examine the roles of DMEs and transporters in intratissue, interorgan, and interorganismal communication via metabolites and signaling molecules. This RSST‐based view is applicable to bile acids, uric acid, eicosanoids, fatty acids, uremic toxins, and gut microbiome products, among other small organic molecules of physiological interest. Rooting this broader perspective of DMEs and transporters within QSP may facilitate an improved understanding of fundamental biology, physiologically based pharmacokinetics, and the prediction of drug toxicities based upon the interplay of these ADME proteins with key pathways in metabolism and signaling. The RSST‐based view should also enable more tailored pharmacotherapy in the setting of kidney disease, liver disease, metabolic syndrome, and diabetes. We further discuss the pharmaceutical and regulatory implications of this revised view through the lens of systems physiology.

Gut-derived uremic toxin handling in vivo requires OAT-mediated tubular secretion in chronic kidney disease

The role of the renal organic anion transporters OAT1 (also known as SLC22A6, originally identified as NKT) and OAT3 (also known as SLC22A8) in chronic kidney disease (CKD) remains poorly understood. This is particularly so from the viewpoint of residual proximal tubular secretion, a key adaptive mechanism to deal with protein-bound uremic toxins in CKD. Using the subtotal nephrectomy (STN) model, plasma metabolites accumulating in STN rats treated with and without the OAT inhibitor, probenecid, were identified. Comparisons with metabolomics data from Oat1-KO and Oat3-KO mice support the centrality of the OATs in residual tubular secretion of uremic solutes, such as indoxyl sulfate, kynurenate, and anthranilate. Overlapping our data with those of published metabolomics data regarding gut microbiome-derived uremic solutes - which can have dual roles in signaling and toxicity - indicates that OATs play a critical role in determining their plasma levels in CKD. Thus, the OATs, along with other SLC and ABC drug transporters, are critical to the movement of uremic solutes across tissues and into various body fluids, consistent with the remote sensing and signaling theory. The data support a role for OATs in modulating remote interorganismal and interorgan communication (gut microbiota-blood-liver-kidney-urine). The results also have implications for understanding drug-metabolite interactions involving uremic toxins.

Drosophila SLC22 Orthologs Related to OATs, OCTs, and OCTNs Regulate Development and Responsiveness to Oxidative Stress

The SLC22 family of transporters is widely expressed, evolutionarily conserved, and plays a major role in regulating homeostasis by transporting small organic molecules such as metabolites, signaling molecules, and antioxidants. Analysis of transporters in fruit flies provides a simple yet orthologous platform to study the endogenous function of drug transporters in vivo. Evolutionary analysis of Drosophila melanogaster putative SLC22 orthologs reveals that, while many of the 25 SLC22 fruit fly orthologs do not fall within previously established SLC22 subclades, at least four members appear orthologous to mammalian SLC22 members (SLC22A16:CG6356, SLC22A15:CG7458, CG7442 and SLC22A18:CG3168). We functionally evaluated the role of SLC22 transporters in Drosophila melanogaster by knocking down 14 of these genes. Three putative SLC22 ortholog knockdowns-CG3168, CG6356, and CG7442/SLC22A-did not undergo eclosion and were lethal at the pupa stage, indicating the developmental importance of these genes. Additionally, knocking down four SLC22 members increased resistance to oxidative stress via paraquat testing (CG4630: p < 0.05, CG6006: p < 0.05, CG6126: p < 0.01 and CG16727: p < 0.05). Consistent with recent evidence that SLC22 is central to a Remote Sensing and Signaling Network (RSSN) involved in signaling and metabolism, these phenotypes support a key role for SLC22 in handling reactive oxygen species.

Systems Biology Analysis Reveals Eight SLC22 Transporter Subgroups, Including OATs, OCTs, and OCTNs

The SLC22 family of OATs, OCTs, and OCTNs is emerging as a central hub of endogenous physiology. Despite often being referred to as “drug” transporters, they facilitate the movement of metabolites and key signaling molecules. An in-depth reanalysis supports a reassignment of these proteins into eight functional subgroups, with four new subgroups arising from the previously defined OAT subclade: OATS1 (SLC22A6, SLC22A8, and SLC22A20), OATS2 (SLC22A7), OATS3 (SLC22A11, SLC22A12, and Slc22a22), and OATS4 (SLC22A9, SLC22A10, SLC22A24, and SLC22A25). We propose merging the OCTN (SLC22A4, SLC22A5, and Slc22a21) and OCT-related (SLC22A15 and SLC22A16) subclades into the OCTN/OCTN-related subgroup. Using data from GWAS, in vivo models, and in vitro assays, we developed an SLC22 transporter-metabolite network and similar subgroup networks, which suggest how multiple SLC22 transporters with mono-, oligo-, and multi-specific substrate specificity interact to regulate metabolites. Subgroup associations include: OATS1 with signaling molecules, uremic toxins, and odorants, OATS2 with cyclic nucleotides, OATS3 with uric acid, OATS4 with conjugated sex hormones, particularly etiocholanolone glucuronide, OCT with neurotransmitters, and OCTN/OCTN-related with ergothioneine and carnitine derivatives. Our data suggest that the SLC22 family can work among itself, as well as with other ADME genes, to optimize levels of numerous metabolites and signaling molecules, involved in organ crosstalk and inter-organismal communication, as proposed by the remote sensing and signaling theory.