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      A Network of SLC and ABC Transporter and DME Genes Involved in Remote Sensing and Signaling in the Gut-Liver-Kidney Axis

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          Abstract

          Genes central to drug absorption, distribution, metabolism and elimination (ADME) also regulate numerous endogenous molecules. The Remote Sensing and Signaling Hypothesis argues that an ADME gene-centered network—including SLC and ABC “drug” transporters, “drug” metabolizing enzymes (DMEs), and regulatory genes—is essential for inter-organ communication via metabolites, signaling molecules, antioxidants, gut microbiome products, uremic solutes, and uremic toxins. By cross-tissue co-expression network analysis, the gut, liver, and kidney (GLK) formed highly connected tissue-specific clusters of SLC transporters, ABC transporters, and DMEs. SLC22, SLC25 and SLC35 families were network hubs, having more inter-organ and intra-organ connections than other families. Analysis of the GLK network revealed key physiological pathways (e.g., involving bile acids and uric acid). A search for additional genes interacting with the network identified HNF4α, HNF1α, and PXR. Knockout gene expression data confirmed ~60–70% of predictions of ADME gene regulation by these transcription factors. Using the GLK network and known ADME genes, we built a tentative gut-liver-kidney “remote sensing and signaling network” consisting of SLC and ABC transporters, as well as DMEs and regulatory proteins. Together with protein-protein interactions to prioritize likely functional connections, this network suggests how multi-specificity combines with oligo-specificity and mono-specificity to regulate homeostasis of numerous endogenous small molecules.

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          What do drug transporters really do?

          Potential drug-drug interactions mediated by the ATP-binding cassette (ABC) transporter and solute carrier (SLC) transporter families are of clinical and regulatory concern. However, the endogenous functions of these drug transporters are not well understood. Discussed here is evidence for the roles of ABC and SLC transporters in the handling of diverse substrates, including metabolites, antioxidants, signalling molecules, hormones, nutrients and neurotransmitters. It is suggested that these transporters may be part of a larger system of remote communication ('remote sensing and signalling') between cells, organs, body fluid compartments and perhaps even separate organisms. This broader view may help to clarify disease mechanisms, drug-metabolite interactions and drug effects relevant to diabetes, chronic kidney disease, metabolic syndrome, hypertension, gout, liver disease, neuropsychiatric disorders, inflammatory syndromes and organ injury, as well as prenatal and postnatal development.
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            The organic anion transporter (OAT) family: a systems biology perspective.

            The organic anion transporter (OAT) subfamily, which constitutes roughly half of the SLC22 (solute carrier 22) transporter family, has received a great deal of attention because of its role in handling of common drugs (antibiotics, antivirals, diuretics, nonsteroidal anti-inflammatory drugs), toxins (mercury, aristolochic acid), and nutrients (vitamins, flavonoids). Oats are expressed in many tissues, including kidney, liver, choroid plexus, olfactory mucosa, brain, retina, and placenta. Recent metabolomics and microarray data from Oat1 [Slc22a6, originally identified as NKT (novel kidney transporter)] and Oat3 (Slc22a8) knockouts, as well as systems biology studies, indicate that this pathway plays a central role in the metabolism and handling of gut microbiome metabolites as well as putative uremic toxins of kidney disease. Nuclear receptors and other transcription factors, such as Hnf4α and Hnf1α, appear to regulate the expression of certain Oats in conjunction with phase I and phase II drug metabolizing enzymes. Some Oats have a strong selectivity for particular signaling molecules, including cyclic nucleotides, conjugated sex steroids, odorants, uric acid, and prostaglandins and/or their metabolites. According to the "Remote Sensing and Signaling Hypothesis," which is elaborated in detail here, Oats may function in remote interorgan communication by regulating levels of signaling molecules and key metabolites in tissues and body fluids. Oats may also play a major role in interorganismal communication (via movement of small molecules across the intestine, placental barrier, into breast milk, and volatile odorants into the urine). The role of various Oat isoforms in systems physiology appears quite complex, and their ramifications are discussed in the context of remote sensing and signaling.
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              Systematic Evaluation of Molecular Networks for Discovery of Disease Genes

              Gene networks are rapidly growing in size and number, raising the question of which networks are most appropriate for particular applications. Here, we evaluate 21 human genome-wide interaction networks for their ability to recover 446 disease gene sets identified through literature curation, gene expression profiling, or genome-wide association studies. While all networks have some ability to recover disease genes, we observe a wide range of performance with STRING, ConsensusPathDB and GIANT networks having the best performance overall. A general tendency is that performance scales with network size, suggesting that new interaction discovery currently outweighs the detrimental effects of false positives. Correcting for size, we find that the DIP network provides the highest efficiency (value per interaction). Based on these results we create a parsimonious composite network with both high efficiency and performance. This work provides a benchmark for selection of molecular networks in human disease research. We evaluate 21 human genome-wide interaction networks for their ability to recover 446 disease gene sets. While all networks can recover disease genes, we observe STRING, ConsensusPathDB and GIANT networks having the best performance overall. Performance scales with network size, suggesting that comprehensive interaction inclusion outweighs the detrimental effects of false positives. We create a parsimonious composite network with both high efficiency and performance. This work provides a benchmark for selection of molecular networks in human disease research.
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                Author and article information

                Contributors
                snigam@ucsd.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                15 August 2019
                15 August 2019
                2019
                : 9
                : 11879
                Affiliations
                [1 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Departments of Pediatrics, , University of California at San Diego, ; La Jolla, CA 92093-0693 USA
                [2 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Departments of Medicine, , University of California at San Diego, ; La Jolla, CA 92093-0693 USA
                [3 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Center for Computational Biology and Bioinformatics, , University of California at San Diego, ; La Jolla, CA 92093-0693 USA
                Author information
                http://orcid.org/0000-0002-6548-9658
                Article
                47798
                10.1038/s41598-019-47798-x
                6695406
                31417100
                ef7dad52-76ff-45d7-a518-31650aed3e21
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 10 January 2019
                : 23 July 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/100009633, U.S. Department of Health & Human Services | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD);
                Award ID: U54-HD090259
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000062, U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases);
                Award ID: DK109392
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                gene regulatory networks,functional clustering
                Uncategorized
                gene regulatory networks, functional clustering

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