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Artigo Modulo 1 - Hugh Davson Distinguished Lectureship of the Cell and Molecular Physiology Section, 2012_ Systems Biology in Physiology_ the Vasopressin Signaling Network in Kidney

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  6/1/2014Hugh Davson Distinguished Lectureship of the Cell and Molecular Physiology Section, 2012: Systems biology in physiology: the vasopressin signaling net…http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3530773/?report=printable1/21  Am J Physiol Cell Physiol. Dec 1, 2012; 303(11): C1115–C1124.Published online Aug 29, 2012. doi: 10.1152/ajpcell.00270.2012PMCID: PMC3530773 Hugh Davson Distinguished Lectureship of the Cell and Molecular Physiology Section, 2012 Systems biology in physiology: the vasopressin signaling network in kidney Mark A. Knepper  Epithelial Systems Biology Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MarylandCorresponding author. Address for reprint requests and other correspondence: M. A. Knepper, National Institutes of Health, 10 Center Dr., Bldg. 10, Rm. 6N260,Bethesda, MD 20892-1603 (e-mail: knep@helix.nih.gov).Received August 14, 2012; Accepted August 27, 2012.Copyright notice Abstract Over the past 80 years, physiological research has moved progressively in a reductionist direction, providingmechanistic information on a smaller and smaller scale. This trend has culminated in the present focus on“molecular physiology,” which deals with the function of single molecules responsible for cellular function. There isa need to assemble the information from the molecular level into models that explain physiological function atcellular, tissue, organ, and whole organism levels. Such integration is the major focus of an approach called“systems biology.” The genome sequencing projects provide a basis for a new kind of systems biology called“data-rich” systems  biology that is based on large-scale data acquisition methods including protein massspectrometry, DNA microarrays, and deep sequencing of nucleic acids. These techniques allow investigators tomeasure thousands of variables simultaneously in response to an external stimulus. My laboratory is applying suchan approach to the question: “How does the peptide hormone vasopressin regulate water permeability in the renalcollecting duct?” We are using protein mass spectrometry to identify and quantify the phosphoproteome of collecting duct cells. The response to vasopressin, presented in the form of a network model, includes a generaldownregulation of proline-directed kinases (MAP kinases and cyclin-dependent kinases) and upregulation of  basophilic kinases (ACG kinases and calmodulin-dependent kinases). Further progress depends oncharacterization and localization of candidate protein kinases in these families. The ultimate goal is to usemultivariate statistical techniques and differential equations to obtain predictive models describing vasopressinsignaling in the renal collecting duct. Keywords: aquaporin-2, signaling networks, collecting duct, phosphoproteomics, mass spectrometry, Nedd4-2 Vasopressin Action in the Kidney The most distal segments of the renal tubule, the connecting tubules and collecting ducts, have variable water  permeability that is controlled in response to the peptide hormone vasopressin, allowing water excretion to vary physiologically (46). These renal tubule segments express three molecular water channels called “aquaporins”(57). These are aquaporin-2 (AQP2), aquaporin-3 (AQP3) and aquaporin-4 (AQP4). AQP2 is present in theapical plasma membrane and in endosomes (6, 20, 56). The latter two aquaporins are seen chiefly in the  basolateral plasma membrane (16, 71). Although there is evidence for regulation of the basolateral water channels  by vasopressin (15, 16), it seems clear that the regulation of water permeability of the collecting duct epithelium is  6/1/2014Hugh Davson Distinguished Lectureship of the Cell and Molecular Physiology Section, 2012: Systems biology in physiology: the vasopressin signaling net…http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3530773/?report=printable2/21 mediated largely through vasopressin's effects on AQP2 (57).There are at least two modes of water permeability regulation in the kidney corresponding to two processes thatcontrol the amount of active AQP2 in the apical plasma membrane. The first mode is “short-term regulation”occurring over a period of 5–30 min as a result of the regulation of trafficking of AQP2-containing membranevesicles to and from the apical plasma membrane in response to vasopressin (55). The second mode is “long-termregulation” occurring over a period of hours to days as a result of regulation of whole cell AQP2 abundance byvasopressin (13, 28, 56). Both modes depend on the binding of vasopressin to V2-type vasopressin receptors (gene symbol:  Avpr2 ) present in the basolateral membrane. The downstream signaling events that are pertinent tothe two modes of regulation are, however, largely undiscovered. In this review, I discuss application of systems biology techniques to the discovery of the signaling processes that are triggered by V2 receptor occupation in therenal collecting duct. Reductionist Versus Integrative Approaches to Biology Over the past 80 years, research in the field of physiology (and biological study in general) has proceeded in areductionist direction, dealing with smaller and smaller structural levels (Fig. 1). Taking renal physiology as anexample, in the 1930s, whole animal or whole person studies were the major sources of information employingclearance techniques. This allowed information to be gleaned about the three major processes determiningexcretion, namely glomerular filtration, secretion, and reabsorption (69   ). The rise of micropuncture (21) and theisolated perfused tubule technique (7) during the 1960s changed the focus of renal physiology to a tissue level, providing information about each of the nephron segments or about the glomerulus. Application of thesetechniques together with biochemically based techniques such as transport measurements in isolated brush border vesicles (54) provided a wealth of detail about transport mechanisms. This knowledge paved the way for the nextmajor era in renal physiology in the 1980s and 90s, during which cDNAs for many of the important renaltransporters were cloned and sequenced. This development switched the emphasis from a tissue and cellular leveldown to a molecular level. Success in cloning many of these cDNAs was greatly abetted by the development of the  Xenopus  oocyte expression system (12). This expression cloning approach allowed cDNA pools andultimately single cDNAs to be selected on the basis of functional assays that were designed utilizing the findings of isolated perfused tubule experiments, micropuncture experiments, and isolated brush-border vesicle experimentsdone in the preceding decades. Thus by the mid- to late 1990s renal physiologists had obtained the primarystructure of the proteins that mediate the most important transport processes along the nephron. The cDNAscould then be expressed in cultured cell lines or in  Xenopus  oocytes and studied, either in native form or mutatedform, to gain a greater understanding of the relationship between protein structure and function. Thus, by the endof the 20th century there had been a spectacular expansion of information about transport in the kidney based on a progression of knowledge from reductionist approaches.Because of the drive toward reductionism in physiology, we have achieved a high level of understanding of structure and function of many of the individual proteins that mediate important physiological processes includingtransport along the renal tubule. However, knowledge of molecular structure and function does not necessarilyimply a mastery over the physiological knowledge needed to understand disease processes in humans. Mosthuman disease is not easily explained as an effect of a single dysfunctional gene and protein, but rather oftenrepresents complex phenomena that depend on nonlinear integration of the functional properties of many proteins.Even so-called “monogenic” diseases have polygenic consequences. Likewise, normal physiological phenomena atthe organism or organ level can rarely be understood from knowledge about a single protein. Therefore, there is aneed to develop methods to integrate information about the molecular functions of individual proteins and their molecular interactions to create predictive models of cellular, tissue, organ, and whole organism function (Fig. 1).The ultimate goal is to understand disease processes and to discover how to treat them. Thus, there is a need for integration, i.e., learning how many small pieces can assemble into larger ones to create complex emergent behavior. This integration process has been referred to as “systems biology.” 12  6/1/2014Hugh Davson Distinguished Lectureship of the Cell and Molecular Physiology Section, 2012: Systems biology in physiology: the vasopressin signaling net…http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3530773/?report=printable3/21 Systems Biology and PhysiologyData-poor systems biology. Systems biology is not a new approach. Starting in the 1960s and 70s with the advent of mainframe computers,various investigators used differential equation-based mathematical modeling to integrate data from the literature.The differential equations were constructed to represent physical principles such as mass balance, energy balance,and various laws that represent the relationships between driving forces and movements of various substances,e.g., nonequilibrium thermodynamics (42). Typically, data from a myriad of sources were used in parameter estimation in these models, a labor intensive process that could only be done manually, assigning one parameter ata time. This type of systems biology has been referred to by Westerhoff and Palsson (74) as “data-poor” systems biology. Despite its laborious nature, this approach has been very productive. For example, models of the kidneyconcentrating mechanism (75) have been useful in generating hypotheses that could be tested experimentally (26). My own mathematical modeling of the kidney medulla [done as part of my PhD dissertation (44)] led to theconclusion that a specialized urea transport mechanism was required in the inner medullary portion of the collectingduct to explain the observed cortico-medullary urea gradient. This observation from mathematical modelingstimulated a series of studies using isolated perfused inner medullary collecting ducts that ultimately demonstratedthe predicted transporter (10, 11, 45, 65), eventually leading to the cloning of corresponding cDNAs (41, 68, 76) and gene knockouts of collecting duct urea transporters in mice (17, 18). Data-rich systems biology. With the advent of genome sequencing projects for various animals, plants, and microorganisms at the beginning of the current century, systems biology has moved to a so-called “data-rich” format (74). As a result of thesesequencing projects, we can now limit our view to a finite set of protein-coding genes (approximately 21,000 inhumans, mice, and rats) when looking for protein species that may explain a particular physiological phenotype.This translates to a finite set of molecular hypotheses. More importantly, the genome sequence information hasmade possible a set of technologies that are capable of providing genome- or proteome-wide read-outs of  physiological experiments. These large-scale data acquisition techniques include protein mass spectrometry (58),hybridization-based expression microarrays (3), and deep sequencing of nucleic acids (27). Each of these modalities allows the experimenter to identify the cellular responses to physiological stimuli comprehensively acrossthe entire proteome, transcriptome, or epi-genome. Such experimental approaches are becoming relativelystraightforward and can be readily applied to a variety of physiological problems at the cellular level.To some extent such experiments can be interpreted through direct perusal of the data. For example, a proteinmass spectrometry study of renal inner medullary collecting duct cells isolated from rat kidneys showed thatvasopressin changes the phosphorylation of the aquaporin-2 water channel at four sites near the carboxyl terminusof the protein (30, 34), a finding that has spawned numerous follow-up studies both within our own laboratory and in others. Additional studies revealed the presence of three vasopressin-regulated phosphorylation sites in thevasopressin-regulated urea transporter UT-A (5).However, most of the information present in large-scale data sets from these technologies cannot be so easilyinterpreted, and requires computational approaches aimed at achieving large-scale data integration to createmodels describing the interactions among the relevant proteins. In a particular physiological experiment involving agiven physiological perturbation, the large-scale integration task often consists of two major elements: 1 ) analysisof the responding proteins, transcripts, or genes within a data set to determine how the responding entities arerelated to one another functionally; and 2 ) analysis of the responding proteins, transcripts, or genes to determinetheir relationships to information that has been obtained in previous studies. The latter analysis typically results inthe generation of a so-called “network” consisting of “nodes” and “edges” (Fig. 2). For a protein network, thenodes represent individual proteins and the edges are the relationships between proteins. A pair of nodes andedges that connect them can be viewed as a grammatical sentence known as a “triplet,” where one node is the  6/1/2014Hugh Davson Distinguished Lectureship of the Cell and Molecular Physiology Section, 2012: Systems biology in physiology: the vasopressin signaling net…http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3530773/?report=printable4/21 subject, the edge is the verb, and the other node is the direct object. In the example shown in Fig. 2, the sentencerepresented is “Protein kinase A catalytic subunit phosphorylates aquaporin-2.” Large numbers of triplets can bemerged into directed graphs like that shown in Fig. 3 depicting the vasopressin-signaling network for the renalinner medullary collecting duct based on phosphoproteomic studies (33   ).To carry out large-scale data integration needed for generation of network models, databases of triplets (alsoknown as “protein interactions”) can be gleaned from the general literature to identify possible interactions between nodes of the physiological system under study. There is a major effort within systems biology to developcomputer-based text mining algorithms that can extract appropriate information (i.e., triplets) from the literature tocreate these databases (29). Lacking full success in this area, a number of databases have been constructed chieflythrough manual curation. These include two commercially available databases within Ingenuity Pathway Analysisand Metacore software suites. These approaches and others like them are useful in organizing large data sets butcontinue to have significant limitations with regard to the ability to construct causal models (43, 53, 67). Consequently, the network models that can be produced with today's technologies fall short of having the predictive power of differential equation-based models. Nevertheless, network models like that shown in Fig. 3 provide a useful way to consolidate and visualize the findings of large-scale experiments. Using Mass Spectrometry to Construct a Vasopressin-Signaling Network for the Renal CollectingDuct My laboratory is using systems biology approaches to identify the vasopressin-signaling network responsible for regulation of water permeability in the renal collecting duct. The studies use liquid chromatography coupled totandem mass spectrometry (LC-MS/MS) to identify and quantify thousands of phosphorylation sites in nativeinner medullary collecting ducts isolated from rat kidneys (5, 33, 34) and in cultured mouse mpkCCD(clone 11) cells (62). Figure 4 shows a general scheme describing how LC-MS/MS can be used to identify thousands of   peptides in a given biological sample. Application of the method to identification and quantification of  phosphopeptides has been the subject of several reviews (31, 32, 59, 61). The studies aim to identify a signaling network (Fig. 5) linking the input (a change in the concentration of vasopressin in the extracellular environment) to a key output (a change in the amount of active aquaporin-2 in theapical plasma membrane). The signaling network to be identified (yellow box) is the set of proteins in the collectingduct cell that link the input to the output, carrying information via a sequence of biochemical changes in the cell.We can identify two subtasks (Fig. 5, bottom ): 1 ) identification of the protein components of the system, i.e., the proteins expressed in collecting duct cells including their posttranslational modifications; and 2 ) determination of how these components interact. Identification of system components. The former subtask is the easiest of the two. Application of standard transcriptomics (from microarray studies or RNA-seq) and proteomics analysis has identified most of the gene products expressed in native inner medullarycollecting duct cells and in mpkCCD(clone 11) cells. This information has been placed on publicly accessibledatabases described by Huling et al. (37   ) and available at http://helixweb.nih.gov/ESBL/Database/ or https://intramural.nhlbi.nih.gov/labs/LKEM_G/LKEM/Pages/--TranscriptomicandProteomicDatabases.aspx.Collecting duct cells appear to express approximately 8,000 out of the 21,000 protein coding genes in thegenome, and the user can easily identify by searching these databases whether a given protein or a related proteinis expressed in these cells. Indeed, these databases can be interrogated online in a variety of ways or the entiredatabase can be downloaded by the user.Databases enumerating phosphorylation sites that have been identified in collecting duct proteins (as well as proteins in other renal tubule segments) are available at the same URLs listed in the previous paragraph. Ingeneral, these phosphorylation sites are modifications of the side-chains of serines, threonines, or tyrosines through
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