WO2008016995A2 - Methods of identifying modulators of insulin signalling - Google Patents

Abstract

This invention relates to methods of identifying drugs for the treatment of insulin resistance and diabetes.

Description

Methods of Identifying Modulators of Insulin Signalling

FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with Government support under Grant Nos. DK33201, and DK55545 awarded by the National Institutes of Health. The Government has certain rights in the invention.

TECHNICAL FIELD

This invention relates to methods of identifying drugs for the treatment of insulin resistance and diabetes.

BACKGROUND

Twenty-one million people in the U.S. have diabetes mellitus, and -95% of these have the Type 2 form of the disease. In addition, over 25 million people have impaired fasting glucose, i.e., prediabetes, and many more have the metabolic syndrome, hepatic steatosis and/or obesity. Furthermore, these disorders are increasing at epidemic rates in both adults and children, and each is a source of major morbidity and mortality. Type 2 diabetes is the leading cause of kidney failure, blindness, and amputations, and is a major risk factor for heart disease and stroke.

Hepatic steatosis is the second most common cause of liver failure in the U.S., and the metabolic syndrome is a major risk factor in as many as 60% of individuals suffering heart attack or stroke. As a result, over 12% of healthcare dollars and 25% of Medicare dollars are spent on people with type 2 diabetes and related disorders, and these numbers grow as the number of people affected continues to increase.

A central component of nearly all of these disorders is insulin resistance at the cellular level. The key intermediate in insulin signaling to control these metabolic pathways is the enzyme phosphatidylinositol 3-kinase (PI 3-kinase or PI3K). This enzyme pathway also plays key regulatory roles in growth, differentiation and control of apoptosis, and is a regulator of longevity in lower organisms, such as C. elegans.

SUMMARY

The present invention is based, at least in part, on novel mechanistic insights into the connection between PI3K/JNK signalling and improved insulin sensitivity. Provided herein are a number of screening methods that use the proteins in this pathway as targets.

In one aspect, the invention provides methods for identifying candidate compounds for improving insulin sensitivity, e.g., in a mammal in need thereof. The methods include providing a sample comprising p85α and cdc42; contacting the sample with a test compound, and evaluating binding of p85α to cdc42 in the sample. A test compound that decreases binding of p85α to cdc42 is a candidate compound for improving insulin sensitivity in a mammal.

In another aspect, the invention provides methods for identifying candidate compounds for improving insulin sensitivity, e.g., in a mammal in need thereof. The methods include providing a sample comprising cdc42 and MLK3; contacting the sample with a test compound, and evaluating phosphorylation of MLK3 by cdc42 in the sample. A test compound that decreases phosphorylation of MLK3 by cdc42 is a candidate compound for improving insulin sensitivity in a mammal. In an additional aspect, the invention provides methods for identifying candidate compounds for improving insulin sensitivity, e.g., in a mammal in need thereof. The methods include providing a sample comprising MLK3 and MKK4; contacting the sample with a test compound, and evaluating phosphorylation of MKK4 by MLK3 in the sample. A test compound that decreases phosphorylation of MKK4 by MLK3 is a candidate compound for improving insulin sensitivity in a mammal.

In a further aspect, the invention provides methods for identifying candidate compounds for improving insulin sensitivity, e.g., in a mammal in need thereof. The methods include providing a sample comprising MKK4 and JNK; contacting the sample with a test compound, and evaluating phosphorylation of JNK by MKK4 in the sample. A test compound that decreases phosphorylation of JNK by MKK4 is a candidate compound for improving insulin sensitivity in a mammal.

In yet another aspect, the invention provides methods for identifying candidate compounds for improving insulin sensitivity, e.g., in a mammal in need thereof. The methods include providing a sample comprising PTEN and JNK; contacting the sample with a test compound, and evaluating phosphorylation of PTEN by JNK in the sample. A test compound that decreases phosphorylation of PTEN by JNK is a candidate compound for improving insulin sensitivity in a mammal. In one aspect, the invention provides methods for identifying candidate compounds for improving insulin sensitivity, e.g., in a mammal in need thereof. The methods include providing a sample comprising one or more target proteins selected from the group consisting of cdc42, MLK3, or MKK4; contacting the sample with a test compound; evaluating binding of the test compounds to the target protein; and selecting the test compound as a candidate compound if it binds to the target protein.

In some embodiments, the methods include providing a cell having a functional insulin signalling pathway comprising p85α, cdc42, MLK3, MKK4, and JNK; contacting the cell with the candidate compound; contacting the cell with an amount of insulin sufficient to activate said pathway; evaluating activation of said pathway in the cell in the presence of the test compound; comparing activation of said pathway in the cell in the presence of the test compound to a reference representing activation of said pathway in the cell in the absence of the test compound, and selecting the candidate compound as a candidate therapeutic agent for improving insulin sensitivity in a mammal if activation of said pathway is reduced in the presence of the test compound as compared to activation of said pathway in the absence of the test compound. In some embodiments, activation of said pathway is determined by one or more of detecting cdc42 activation of MLK3; detecting binding of cdc42 to MLK3; detecting MLK3 kinase activity; detecting phosphorylation of MKK4; or detecting JNK activation.

In some embodiments of the methods described herein, the test compound can be, e.g., a small molecule, or a peptide or peptidomimetic. As used herein, "small molecules" refers to small organic or inorganic molecules of molecular weight below about 3,000 Daltons. In some embodiments of the methods described herein, the sample is or includes a cell, e.g., a cell expressing the recited proteins, either endogenously or exogenously..

In some embodiments, the methods described herein further include administering the candidate compound to a mammal, e.g., a mammal in need of increased insulin sensitivity, and evaluating whether the candidate compound increases insulin sensitivity in the mammal. In some embodiments, the mammal is a non-human experimental animal. In some embodiments, the methods further include selecting the compound if is increases insulin sensitivity and evaluating the compound in a clinical trial.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Methods and materials are described herein for use in the present invention; other, suitable methods and materials known in the art can also be used. The materials, methods, and examples are illustrative only and not intended to be limiting. All publications, patent applications, patents, sequences, database entries, and other references mentioned herein are incorporated by reference in their entirety, including the priority application, USSN 60/821, 118, filed August 1 , 2006. In case of conflict, the present specification, including definitions, will control.

Other features and advantages of the invention will be apparent from the following detailed description and figures, and from the claims.

DESCRIPTION OF DRAWINGS FIG. IA is a set of Western blots for Pϊkirl gene products with an antibody against the N-terminal SH2 domain (pan-p85) in tissues lysates, as indicated, from control, heterozygous KO and L-Pik3rlKO mice. Tissues were collected from mice after an overnight fast, and proteins were extracted and processed as described in the Methods section. Each lane represents lysates from a different mouse. FIGs. IB are line graphs of fasted blood glucose (IB) and fasted serum insulin levels (1C) at 8, 16, and 24 weeks of age in lox/lox and KO mice. Open circles (O) — lox/lox; closed circles (•)— L-Pik3rlKO.

FIGs. ID and IE are bar graphs of serum triglycerides (ID) and serum non- esterified free fatty acid levels (IE) from lox/lox or KO mice in the fasted state. FIG. IF is a line graph showing the results of Glucose tolerance tests (2 g/kg, intraperitoneally) performed on mice following a 16 hour fast for five days; blood samples were collected and glucose measured at the times indicated. All values are presented as mean±SEM (n=6-20). Open circles (O) — lox/lox; closed circles (•) — L-Pik3rlKO. FIGs. 2A-2E are bar graphs illustrating the results of hyperinsulinemic- euglycemic clamp analyses and gene expression changes in L-Pik3rlKO mice. Male mice (n=l 1) of the indicated genotype at 10-12 weeks of age were subjected to hyperinsulinemic-euglycemic clamp analysis. A number of parameters were evaluated, including insulin suppression of hepatic glucose production (2A), glucose infusion rates (2B), and in vivo ¹⁴C-deoxyglucose uptake in muscle (2C) and epididymal fat tissue (2D). FIG. 2E is a bar graph showing the results of quantitative RT-PCR analysis of mRNA levels in lox/lox and L-Pik3r IKO mice of phosphoenolpyruvate carboxykinase (Pckl), glucose-6-phosphatase (G6Pc), fructose- 1,6-bisphosphatase (Fbpl), peroxisome proliferator-activated receptor (PPAR)-γ coactivator-1 alpha (Ppargcl) and tribbles3 (trib3) and glucokinase (Gckl). N=8 for each genotype for RT-PCR experiments. *p<0.05 vs lox/lox mice. FIG. 3A is a bar graph illustrating enhanced Akt activation in L-Pik3rlKO mice. PI3K activity was assayed in IRS-I, IRS-2 and phospho-Tyrosine (pTyr) immunoprecipitates (bars represent mean ± SEM, n=5, *p<0.05).

FIGs. 3B is a Western blot of pi 10a and p85α from pi 10a immunoprecipitates. FIG. 3 C is a par of blots of pTyr (upper panel) and insulin receptor (lower panel) in insulin receptor (β-subunit) immunoprecipitates.

FIG. 3D is a blot showing Ser473 phosphorylation of Akt. FIG. 3 E is a bar graph illustrating Akt kinase activity as measured from Akt immunoprecipitates using Crosstide as a substrate. Bars represent mean±SEM, n=8, *p<0.05.

FIG. 4A is a set of six photomicrographs illustrating enhanced PIP3 levels in L-Pik3rlKO mice (bottom three panels) as compared to lox/lox mice (top three panels) due to decreased PTEN activity. Immunofluorescent staining with a primary anti-PIP₃ antibody (IgM) and an anti-mouse secondary antibody conjugated to Alexafluor Red and counterstained with DAPI. Following an overnight fast, mice were injected with saline (time=0) or 5U of insulin for 5 or 15 minutes. N = six mice in each genotype/treatment group.

FIG. 4B is a bar graph of the results of quantification of the immunofluorescence from PIP3 staining shown in FIG. 4A. Representative slides were chosen from each mouse and the fluorescence intensity was measured and analyzed with VH-H 1A5 Analyzer software (KEYENCE, Osaka, Japan). FIGs. 4C and 4D are bar graphs of insulin-stimulated pTyr-associated PI3K activity (4C) and PTEN activity (4D) in lox/lox or KO animals at the indicated timepoints.

FIG. 4E is a Western blot showing PTEN levels in lox/lox and KO mice at the indicated timepoints.

FIG. 5 A is a blot showing expression levels of hepatic p85α and p50 in lox/lox and KO mice. Six-week-old L-Pik3rl KO mice and lox/lox controls were fed a normal chow (NC) or a high fat diet (HFD) for a total of 8 weeks.

FIG. 5B is a line graph indicating body weight for each week on either diet. Open squares (D)- lox/lox, NC, Open circles (O)- L-Pik3r IKO, NC; Closed squares (■)— lox/lox, HFD; closed circles (•)— L-Pik3rlK0, HFD.

FIG. 5C is a trio of Western blots performed against liver lysates of mice of indicated genotype and diet using the phosphoserine 473 Akt antibody, phospho-JNK antibody, phosphoserine307 IRS-I antibodies. The phospho-specific antibody blots were stripped and re-probed with the antibody for total levels of the corresponding proteins, which in each case did not change and are therefore not shown. The bars represent ± SEM (n=6-8).

FIG. 5D is a line graph of fasting blood glucose from mice of the indicated genotype and diet. *p<0.05, **p<0.01 FIG. 6 is a series of seven immunoblots of pJNK, JNK, pS307IRS-l, IRS-I, pAkt, Akt, and p85 in lox/lox and KO mice.

FIG. 7 A is a bar graph illustrating cdc42 activity as determined by PAKl pulldown assay from liver lysates after three minutes of insulin stimulation via the portal vein. FIG. 7B is a quartet of Western blots against phosphor-MKK4 (pMM4),

MKK4, phospho-JNK (pJNK) and JNK from liver lysates of mice of indicated genotypes.

FIG. 7C is a series of five phosphoimmunoblots from primary hepatocytes against pJNK, pMKK4, pAkt, Myc tag, and p85. FIG. 8A is an immunoblot of LacZ, p85α, p55α, and p50α. Recombinant adenoviruses were injected via tail-vein into 10-12 week old male mice of the indicated genotype. Mice were injected with adenoviruses encoding control LacZ, or one of the Pik3rl gene products, p85α, p55α, and p50α. An extra band of approximately 5OkD appears in the livers treated with p55α adenovirus, and this likely represents a proteolytic breakdown product of p55α.

FIG. 8B is a line graph of PBK activity from the mice injected with the indicated adenoviruses is 8A. 5 FIG. 8C is a trio of Western blots performed against liver lysates of mice treated with adenovirus, using phospho-JNK and phosphoserine307 antibodies. The phospho-specific antibody blots were stripped and re-probed with the antibody for total levels of the corresponding proteins (data not shown).

FIGs. 8D and 8E are bar graphs of fasted blood glucose (8D) and fasted serum o insulin (8E) in mice treated with the indicated adenoviruses.

FIG. 8F is a line graph of the results of GTTs in mice whose livers were reconstituted with one of the Pϊkirl gene products. The bars represent ±SEM (n=6- 8).

FIG. 9A is trio of immunoblots of LacZ, p85α, p55α, and p50α. Recombinant5 adenoviruses were injected via tail-vein into 10-12 week old male mice of the indicated genotype. Mice were injected with adenoviruses encoding control LacZ, or one of the Pik3rl gene products, p85α, p55α, and p50α. An extra band of approximately 5OkD appears in the livers treated with p55α adenovirus, and this likely represents a proteolytic breakdown product of p55α. 0 FIGs. 9B and 9C are bar graphs of PDK activity (9B) and cdc42 activity (9C) in the mice injected with the indicated adenoviruses.

FIG. 9D is a line graph of fasted blood glucose levels in mice treated with the indicated adenoviruses. The bars represent ± SEM (n=6-8).

FIG. 1OA is an immunoblot of LacZ, p85α, ΔSH3, ΔBH, and ΔΔ expression,5 showing that the Activation of cdc42 Requires an Intact N-terminus of p85α.

Recombinant adenoviruses were injected via tail-vein into 10-12 week old male mice of the indicated genotype. Mice were injected with adenoviruses encoding control LacZ, or one of the Pik3rl gene products, p85α, p55α, and p50α. Immunoblots were then performed. 0 FIGs. 1OB and 1OC are bar graphs of PI3K activity (10B) and cdc42 activity

(10C) from the mice injected with the indicated adenoviruses. The bars represent ±SEM (n=6-8). FIG. 11 is a schematic illustration of a hypothetical assignment of functions to the regions of p85α. This regulatory subunit of PI3K regulates insulin sensitivity through both positive and negative mechanisms. p85α regulates PIP3 levels through its traditional role as a regulator of PDK activity, but it also independently regulates PIP₃ levels via the activation of JNK via cdc42 and possibly through the activation of a lipid phosphatase or by the alteration of subcellular localization of PDK.

FIG. 12A is a gar graph illustrating the average weekly food intake of lox/lox (FLOX) or KO mice of either normal chow (NC) or high- fat diet HFD) over a week, expressed in grams. Genotypes of animals are indicated directly on the bars. FIGs. 12B and 12C are bar graphs illustrating fasting blood glucose (12B)and fasting serum insulin (12C) in lox/lox or KO mice after an eight-week treatment with either normal chow or high-fat diet.

FIGs. 13A-B are schematic illustrations of natural variants (13A) or artificial mutants (13B) of p85α, with their effect on PDK activity, JNK activity, or insulin sensitivity.

FIG. 14 is a schematic illustration of the structure of the PTEN (top) and a phosphoimmunoblot of PTEN showing phosphorylation by JNK (bottom).

DETAILED DESCRIPTION

The present invention describes methods of identifying novel modulators of the PI3-kinase/p85α signalling pathway that eventually modulate JNK and PTEN activity, thereby regulating insulin action and sensitivity.

PI 3-kinase regulatory subunits as modulators of the stress kinases JNK and p38

The enzyme phosphatidylinositol 3-kinase is central to the metabolic actions of insulin. The enzyme itself is comprised of a regulatory subunit and a catalytic subunit. The catalytic subunit is either pi 10a (GenBank Ace. No. NM_006218.2) or pi lOβ (GenBank Ace. No. BCl 14432.1). The most common forms of regulatory subunit are p85α (GenBank Ace. No. NM_181523.1) and p85β (GenBank Ace. No. BC090249.1 or BC070082.1), which are products of separate genes. In addition, GRBl, the gene encoding p85α, also produces several alternatively spliced variants, p55α, p50α and forms with small additional inserted exons. These different regulatory subunits are expressed to different levels in different tissues and also differentially regulated in disease states such as obesity. In US Pat. App. Pub. No. 2002-0051786-A1, the present inventors demonstrated that heterozygous deletion of p85α improves insulin sensitivity and can protect mice with genetic and acquired forms of insulin resistance, including the insulin resistance associated with high fat diet, from developing diabetes. Furthermore, this effect can be mimicked by reducing expression of p85α in liver only via tissue specific knockout (see Barbour et al, J. Biol. Chem. 280(45):37489-94 (2005). Epub 2005 Sep 8).

The work described herein demonstrates novel mechanistic insights into this connection between p85α and improved insulin sensitivity. One aspect of the improved sensitivity is the result of a decrease in serine phosphorylation of the insulin receptor substrate IRS-I . Serine phosphorylation of IRS-I has been previously shown to reduce its tyrosine phosphorylation and reduce its ability to activate the PI 3-kinase pathway, thus reducing insulin's metabolic actions. Several protein kinases have been shown to phosphorylate IRS-I on serine residues, but a key kinase in this pathway is JNK. As described herein, p85α plays a novel role in JNK activation by binding to and activating the small GTPase cdc42, which leads to the activation of Mixed Lineage Kinase-3 (MLK3), which phosphorylates Mitogen-Activated Protein Kinase Kinase 4 (MKK4), leading to JNK activation. A potential schematic is as follows:

P85 -> cdc42 -*?^ MLK3 -> MKK4 -> JNK

Furthermore, this pathway is normally increased in obesity-related insulin resistance, and reducing the level of p85 improves insulin sensitivity, as least in part, by reducing activation of cdc42, MMK4 and JNK, leading to reduced serine phosphorylation of IRS-I . Therefore, modulation of this pathway provides a number of novel targets for drugs that improve insulin sensitivity.

Thus, the methods described herein can be used to identify and optimize small molecule inhibitors that reduce the interaction of cdc42 with p85 and/or reduce cdc42- mediated activation of MKK4, thereby reducing JNK activation and serine phosphorylation of IRS-I, and enhancing insulin sensitivity in insulin resistant states. In some embodiments, the methods include the use of a high throughput in vitro assay system to identify test compounds, e.g., small molecules, that have this property and can therefore serve as drugs for diabetes, metabolic syndrome and related disorders. PI 3-kinase regulatory subunits as modulators of the lipid phosphatase PTEN

As noted above, PI 3-kinase is central to the metabolic actions of insulin. This occurs via formation of its phospholipid products, in particular PIP3, which activates downstream enzymes like Akt and the atypical PKCs λ and ζ. This process is antagonized or reverse by the action of lipid phosphatases, which break down PIP3, the most important of which is the enzyme "phosphatase and tensin homolog," or PTEN.

Regulation of PTEN activity is multi-factorial and includes allosteric regulation of PTEN by its lipid products, subcellular targeting, cofactor interactions, as well as post-translational modifications (Gericke, Gene. 2006 Jun 7;374: l-9. Epub 2006 Mar 14). Although there is phosphorylation of PTEN in a number of cell types, the functional consequences of PTEN phosphorylation have been largely uncharacterized. The vast majority of PTEN phosphorylation occurs on serine residues (>90%), especially serine residues 370 and 385. In addition, phosphorylation has been reported on other serines (e.g., serine 229, 360, 362, and/or 380) and threonines (e.g., threonine 223, 319, 321, 366, 382, 383, and/or 401), residues that map to the C2 lipid binding domain (amino acids (a. a.) 190-351) and a region proximal to the PDZ ligand sequence (a.a. 401-403) at the C-terminus. Some recent evidence suggests that the phosphorylation of PTEN may regulate its stability and play an important role in modulating biological activity (Vazquez et al, MoI. Cell. Biol. 20:5010-5018 (2000); Okahara et al., J. Biol. Chem. 279:45300-45303 (2004)), serving to inactivate the enzyme. Upon dephosphorylation, PTEN becomes active with a commensurate decrease in protein stability (Vazquez, 2000, supra; Vazquez et al., J.Biol. Chem. (2001) 276(52):48627-30. Epub 2001 Nov 13; Okahara, 2004, supra).

In immunoblotting experiments performed with an antibody that recognizes the phosphorylation of PTEN on sites in the distal C2 domain (Ser³⁸⁰/Thr^382/383), it was discovered that PTEN undergoes phosphorylation in response to insulin stimulation. More important, this phosphorylation is increased substantially in p85 ^~'^~ cells as compared to p85 ^+/+ cells, and that this correlates with a decrease in PTEN activity. This results in more sustained PIP₃ levels following insulin stimulation in liver p85α knockout mice and another mechanism for enhanced insulin sensitivity in these animals. Based in the above observations, a key regulator of PTEN would be the kinase that phosphorylates PTEN in response to p85 regulation. As described herein, there is considerable evidence that JNK is the critical PTEN Kinase. First, there is a conserved JNK-binding motif (K/RXXXXLXL) at residues 313-320 of PTEN based 5 upon similar motifs obtained from established JNK substrates (Dickens et al., Science, 277(5326):693-696 (1997); Yang et al., EMBO J., 17(6):1740-1749 (1998)). Moreover, two potential phosphorylation sites (Ser³³⁸ and Thr³⁶⁶) for JNK/MAP kinase family exist in the C-terminal region of PTEN, and this region has been shown to be important for stability and/or activity of PTEN. Since JNK activity is decreased o in p85α KO mice and cells, a decrease in JNK would also be expected to result in a change in serine phosphorylation and activity of PTEN.

Target Sequences

Sequences for the protein and nucleic acid targets useful in the methods described herein are known in the art. The following is a list of exemplary sequences5 that can be used. As one of skill in the art will appreciate, homologs of these sequences from other species can also be used. For example, nucleic acids that hybridize under stringent conditions to a sequence listed herein, or a polypeptide encoded by such a sequence, can equally be used. As used herein, the term "hybridizes under stringent conditions" describes conditions for hybridization and0 washing. Stringent conditions are known to those skilled in the art and can be found in Current Protocols in Molecular Biology, John Wiley & Sons, N.Y. (1989), 6.3.1- 6.3.6. Aqueous and nonaqueous methods are described in that reference and either can be used. As used herein, stringency conditions are 0.5 M sodium phosphate, 7% SDS at 65°C, followed by one or more washes at 0.2 X SSC, 1% SDS at 65°C. 5 Alternatively, a sequence that is at least 80%, e.g., at least 85%, 90%, 95%, 96%, 97%, 98%, 99%, or more identical to a sequence listed herein can be used. The comparison of sequences and determination of percent identity between two sequences can be accomplished using a mathematical algorithm. For purposes of the present methods, the percent identity between two amino acid sequences is 0 determined using the Needleman and Wunsch ((1970) J. MoI. Biol. 48:444-453 ) algorithm which has been incorporated into the GAP program in the GCG software package (available on the world wide web at gcg.com), using the default parameters, i.,e., a Blossum 62 scoring matrix with a gap penalty of 12, a gap extend penalty of 4, and a frameshift gap penalty of 5.

PTEN - Phosphatase and Tensin Homolog

The mouse PTEN sequences are available at:

See also: HomoloGene:265.

JNKl /2 - c-Jun N -Terminal Kinases 1 and 2

Sequences of JNKl, also known as mitogen-activated protein kinase 8, can be found at:

Sequences of JNK2, also known as mitogen activated protein kinase 9

(MAPK9), can be found at:

cdc42 - Cell Division Cycle 42 Sequences of cdc42 can be found at:

MLKi - Mixed Lineage Kinase 3

Sequences of MLK3, also known as Mitogen- Activated Protein Kinase Kinase Kinase 11 (MAPKKl 1) can be found at:

MKK4 - MAP Kinase Kinase 4

Sequences of MKK4, also known as mitogen-activated protein kinase kinase 4 (MAP2K4), can be found at:

p85a-p85 alpha, regulatory subunit

Sequences of p85, also known as PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (PIK3R1), can be found at:

Methods of Screening

The invention includes methods for screening of test compounds, to identify compounds that modulate a pathway described herein, e.g., compounds that (i) reduce the interaction of cdc42 with p85, thereby reducing cdc42 activity, or (ii) reduce the activation of MLK3 by cdc42, thereby reducing MLK3 activity, or (iii) reduce the phosphorylation of MKK4 by MLK3, thereby reducing MKK4 activity, thus reducing JNK activation and serine phosphorylation of IRS-I, and enhancing insulin action and sensitivity. In addition, each of cdc42, MLK3, and MKK4 are novel targets for inhibition, and can be used as targets for a screening method described herein. The methods described herein can be used to identify compounds that bind to p85, cdc42, MLK3, or MKK4. In addition, the effect of a test compound on the p85 signalling pathway can be determined. For example, the methods can be used to identify compounds that demonstrate (i) binding to p85 and/or cdc42, and/or decrease p85-mediated activation of cdc42, (ii) binding to cdc42 and/or MLK3, and/or decrease csc42-mediated activation of MLK3, or (iii) binding to MLK3 and/or MKK4, and/or decrease MLK3 -mediated phosphorylation of MKK4.

Thus, in general, the methods will include providing a sample that includes one or more of p85, cdc42, MLK3, and MKK4.

For example, in some embodiments, the sample can include p85α and cdc42, e.g., isolated and purified p85α and cdc42 proteins, and the methods include identifying a compound that affects binding between p85 and cdc42. Screening methods suitable for use in these embodiments are known in the art and include, but are not limited to, yeast or mammalian 2-hybrid systems, tagged protein assays, immunoprecipitation assays, and proteomics assays. These methods can be used to identify natural (i.e., endogenous) regulators of cdc42, for example.

In some embodiments, the sample includes isolated and purified cdc42 and MLK3, with or without MKK4, and the methods include detecting identifying compounds that affect activation of MLK3 by cdc42, and/or phosphorylation of MKK4. In some embodiments, the sample includes isolated and purified MLK3 and

MKK4, and the methods include detecting identifying compounds that affect phosphorylation of MKK4. In some embodiments of the methods described herein, MKK7 can be used in place of MKK4.

In some embodiments, the methods include identifying isoform-specific inhibitors of JNK, i.e., inhibitors that substantially reduce the activity of JNKl while not substantially affecting the activity of JNK2, or vice-versa. As described herein, the different isoforms have different activities depending on the tissues, therefore, it may be desirable to affect only the isoform that is active in the particular cell type. In addition, it may be desirable to affect only the ability of JNK to phosphorylate PTEN, e.g., drugs that bind to either JNK1/2 or PTEN and prevent phosphorylation.

In order to evaluate the ability of a compound to affect signalling, it will generally be desirable to test the compound in a cell. For example, the methods can include adding the compound to cells that express all of these proteins, and exhibit p85 signalling via cdc42 and MKK4 that results in JNK activation and serine phosphorylation of IRS- 1 and/or PTEN. The methods can then include contacting the cells with the compound, and evaluating an effect of the compound on JNK activity (e.g., serine phosphorylation of IRS-I or PTEN). In some embodiments, the methods further include determining whether the compound has an effect on phosphorylation of other substrates by JNK, and selecting a test compound if it selectively inhibits JNK phosphorylation of PTEN. For example, such a compounds might be designed such that it binds a JNK-recognition site, or a JNK-phosphorylation site, on PTEN. A number of suitable assays are known in the art, see, e.g., Methods in Enzymology. Volume 201 : Protein Phosphorylation. Part B: Analysis of Protein Phosphorylation. Protein Kinase Inhibitors, and Protein (Methods in Enzymology) by John N. Abelson, Melvin I. Simon, Tony Hunter, and Bartholomew M. Sefton (Hardcover - Jan 15, 1991), Protein Phosphorylation. Part A: Protein Kinases: Assays. Purification.

Antibodies. Functional Analysis. Cloning, and Expression. Volume 200: Volume 200, Part A (Methods in Enzymology) by John N. Abelson, Melvin I. Simon, Tony Hunter, and Bartholomew M. Sefton (Hardcover - JuI 28, 1991).

Test Compounds The test compounds can be, e.g., natural products or members of a combinatorial chemistry library. In some embodiments, the test compounds are initially members of a library, e.g., an inorganic or organic chemical library, peptide library, oligonucleotide library, or mixed-molecule library. In some embodiments, the methods include screening small molecules, e.g., natural products or members of a combinatorial chemistry library. These methods can also be used, for example, to screen a library of proteins or fragments thereof, e.g., proteins that are expressed in liver or pancreatic cells. A given library can comprise a set of structurally related or unrelated test compounds. Preferably, a set of diverse molecules should be used to cover a variety of functions such as charge, aromaticity, hydrogen bonding, flexibility, size, length of side chain, hydrophobicity, and rigidity. Combinatorial techniques suitable for creating libraries are known in the art, e.g., methods for synthesizing libraries of small molecules, e.g., as exemplified by Obrecht and Villalgordo, Solid-Supported Combinatorial and Parallel Synthesis of Small-Molecular- Weight Compound Libraries. Pergamon-Elsevier Science Limited (1998). Such methods include the "split and pool" or "parallel" synthesis techniques, solid-phase and solution-phase techniques, and encoding techniques (see, for example, Czarnik, Curr. Opin. Chem. Bio. 1 :60-6 (1997)). In addition, a number of libraries, including small molecule libraries, are commercially available.

In some embodiments, the test compounds are peptide or peptidomimetic molecules, e.g., peptide analogs including peptides comprising non-naturally occurring amino acids or having non-peptide linkages; peptidomimetics (e.g., peptoid oligomers, e.g., peptoid amide or ester analogues, β-peptides, D-peptides, L-peptides, oligourea or oligocarbamate); small peptides (e.g., pentapeptides, hexapeptides, heptapeptides, octapeptides, nonapeptides, decapeptides, or larger, e.g., 20-mers or more); cyclic peptides; other non-natural or unnatural peptide-like structures; and inorganic molecules (e.g., heterocyclic ring molecules). In some embodiments, the test compounds are nucleic acids, e.g., DNA or RNA oligonucleotides.

In some embodiments, test compounds and libraries thereof can be obtained by systematically altering the structure of a first test compound. Taking a small molecule as an example, e.g., a first small molecule is selected that is, e.g., structurally similar to a known phosphorylation or protein recognition site. For example, in one embodiment, a general library of small molecules is screened, e.g., using the methods described herein, to select a fist test small molecule. Using methods known in the art, the structure of that small molecule is identified if necessary and correlated to a resulting biological activity, e.g., by a structure-activity relationship study. As one of skill in the art will appreciate, there are a variety of standard methods for creating such a structure-activity relationship. Thus, in some instances, the work may be largely empirical, and in others, the three-dimensional structure of an endogenous polypeptide or portion thereof can be used as a starting point for the rational design of a small molecule compound or compounds. In some embodiments, test compounds identified as "hits" (e.g., test compounds that demonstrate activity in a method described herein) in a first screen are selected and optimized by being systematically altered, e.g., using rational design, to optimize binding affinity, avidity, specificity, or other parameter. Such potentially optimized structures can also be screened using the methods described herein. Thus, in one embodiment, the invention includes screening a first library of test compounds using a method described herein, identifying one or more hits in that library, subjecting those hits to systematic structural alteration to create one or more second generation compounds structurally related to the hit, and screening the second generation compound. Additional rounds of optimization can be used to identify a test compound with a desirable therapeutic profile.

Test compounds identified as hits can be considered candidate therapeutic compounds, useful in treating disorders described herein. Thus, the invention also includes compounds identified as "hits" by a method described herein, and methods for their administration and use in the treatment, prevention, or delay of development or progression of a disease described herein.

EXAMPLES

The invention is further described in the following examples, which do not limit the scope of the invention described in the claims.

Example 1 : Phosphoinositide 3-Kinase Regulatory Subunit p85α Suppresses Insulin Action via Positive Regulation of PTEN

Insulin action on the liver is required for the proper maintenance of metabolic homeostasis. Under normal conditions, insulin inhibits gluconeogenesis and activates lipogenesis to promote proper fuel utilization in the fed state. The failure of insulin to regulate hepatic function can lead to unfettered hepatic glucose output and elevated lipogenesis in the liver, which are two key features of the metabolic syndrome (Shimomura, et al., (2000) MoI. Cell, 6(l):77-86). Not surprisingly, an overwhelming amount of epidemiological (Tripathy et al., (2004) Diabetologia, 47(5):782-93) and physiological (Fisher and Kahn, (2003) J. Clin. Invest., 111(4):463-468) evidence links hepatic insulin resistance to the development of type 2 diabetes.

The molecular mechanisms that maintain hepatic insulin sensitivity are likely linked to the class IA phosphoinositide 3-kinase (PI3K) pathway, which is a critical regulator of insulin action (Saltiel and Kahn, (2001) Nature, 414(6865):799-806). PI3K is an obligate heterodimer, with an SH2-containing regulatory subunit (p85) and a catalytic subunit (pi 10). The regulatory subunit mediates the binding, activation and localization of the PI3K enzyme (Virkamaki, et al., (1999) J. Clin. Invest. 103(7):931-43), (Backer et al., (1992) EMBO J., 11(9):3469-79), (Fruman et al., (1996) Genomics, 37(1): 113-21). Despite the crucial role that the regulatory subunits play in mediating insulin- dependent PI3K signaling, insulin sensitivity correlates inversely with regulatory subunit expression. This paradoxical relationship is demonstrated by knockouts of the different regulatory subunits. For instance, the deletion of the less abundant isoforms of Pik3rl (p55α/p50α), (Chen et al., (2004) MoI. Cell. Biol. 24:320-9) or the minor isoform p85beta (Ueki et al., (2002) Proc. Natl. Acad. Sci. U.S.A., 99(l):419-24) mildly improve insulin sensitivity, while the knockout of more abundant p85α markedly improves glucose homeostasis (Terauchi et al., (1999) Nat. Genet. 21(2):230-235). Germline deletion of all three products of the Pik3rl gene (p85α, p55α, and p50α) also enhances insulin sensitivity, though these mice die perinatally (Fruman et al., (2000) Nat. Genet. 26(3):379-82). These data indicate that in addition to its traditional positive function as a component of the PI3K holoenzyme, p85α is also a potent negative regulator of insulin signaling.

The negative effects of p85α on insulin action may have important consequences in the pathophysiology of insulin resistance and diabetes. For example, the increased expression of p85α in mouse models of gestational diabetes (Barbour et al., (2004) Endocrinology 145(3): 1144-50) and in obese humans (Bandyopadhyay et al., (2005) Diabetes 54(8):2351-9) is strongly linked with insulin resistance. Conversely, heterozygosity for Pϊkirl prevents the onset of diabetes in genetically insulin resistant mice (Mauvais-Jarvis et al, (2002) J. Clin. Invest. 109, 141-149).

The physiologic and molecular mechanisms that underlie this negative regulation by p85α have been difficult to determine. At the physiologic level, germline knockouts that delete p85 isoforms in all tissues throughout development cannot discriminate whether the negative action of p85α occurs as a tissue- autonomous effect or as a consequence of altered endocrine communication between insulin responsive tissues. This situation may also be complicated by potential compensatory adjustments to loss of p85 during development. Similarly, the molecular mechanisms of p85α's negative effects are still understood only at rudimentary level. To clarify the mechanisms by which p85α regulates insulin sensitivity in vivo, at the physiologic and molecular level, mice with a liver-specific deletion oiPik3rl (L-Pik3rlKO) were created. This conditional knockout oiPik3rl (p85α, p55α, and p50α) in hepatocytes circumvents the perinatal lethality observed in the corresponding germline knockout mice and furthermore allows the investigation of the specific role of the liver in the physiological actions of p85α. As described herein, L-Pik3rlKO mice have enhanced hepatic and whole body insulin sensitivity as well as increased Akt activity in liver, despite decreased total hepatic PBK activity. Furthermore, p85α mediates its negative effect on insulin sensitivity at least in part via the activation of PTEN lipid phosphatase activity.

Experimental Procedures

All animals were housed on a 12-hour light-dark cycle and fed a standard rodent chow. All mice used in this study were on a 129Sv-C57BL/6-FVB mixed genetic background. Metabolic studies. For glucose tolerance testing (GTT), blood samples were obtained at 0, 15, 30, 60, and 120 minutes after intraperitoneal injection of 2 g/kg dextrose. Insulin tolerance tests were performed by injecting 1 U/kg insulin (Novolin, Novo Nordisk, Denmark) intraperitoneally, followed by blood collection at 0, 15, 30 and 60 minutes after injection. Blood glucose values were determined using a One Touch II glucose monitor (Lifescan Inc., Milipitas, CA). Plasma insulin levels were measured by ELISA using mouse insulin as a standard (Crystal Chem Inc., Chicago, IL). Non-esterified free fatty acid levels were measured from random fed mice using a kit from Wako Diagnostics, while serum triglycerides were measured by Anilytics (Gaithersburg, MD).

Hyperinsulinemic-euglycemic clamp. Mice were anaesthetized with a 1.2% solution of 2,2,2-tribromoethanol in normal saline, followed by the microsurgical insertion of a catheter into the right jugular vein. Approximately 7 days of recovery, mice were fasted for 5 hours and were infused with a constant (2.5 mU/kg/min) dose of insulin and a variable glucose infusion rate to maintain euglycemia and assess whole-body insulin sensitivity. An infusion of a [3-³H]-glucose tracer was used to ascertain hepatic glucose production, and a bolus of 2-deoxy -D-[I -¹⁴C] glucose was administered during steady state conditions to determine fat and muscle-specific glucose uptake.

In vivo insulin signaling. Following an overnight fast, the mice were anesthetized with Avertin (2,2,2-tribromoethanol in PBS), and injected with 5 U of regular human insulin (Novolin, Novo Nordisk, Denmark) via the inferior vena cava. Five minutes after the insulin bolus, tissues were removed and frozen in liquid nitrogen. Immunoprecipitation and immunoblot analysis of insulin signaling molecules was performed as previously described (Taniguchi et al, (2005) J. Clin. Invest. 115(3):718-27).

Quantitative Reverse Transcription (RT) -PCR analysis. Total RNA was isolated from mouse tissues using an RNeasy kit (QIAGEN, Valencia, CA), and cDNA was prepared using the Advantage RT-PCR kit (BD Biosciences, Palo Alto, CA) with random hexamer primers, according to manufacturer's instructions. PCR reactions were run in triplicate and quantitated in the ABI Prism 7700 Sequence Detection System. Ct values were normalized to TATA box binding protein (TBP) expression, and the results were expressed as a fold change of mRNA compared to control lox/lox mice.

Antibodies. Rabbit polyclonal anti-IRS-1 antibody (IRS-I), anti-IRS-2 antibody (IRS-2), anti-IR antibody (IR) and pan-p85α antibody were generated as described previously (Ueki et al., (2002) Proc. Natl. Acad. Sci. U.S.A., 99(l):419-24). The anti-TRB3 antibody was a gift from Marc Montminy (Du et al., (2003) Science 300, 1574-7). Rabbit polyclonal anti-Akt, anti-phospho Akt (S473) anti-PTEN were purchased from Cell Signaling Technology (Beverly, MA). The phosphotyrosine (pTyr) antibody, 4G10, was purchased from Upstate Biotechnology, Inc. (Lake Placid, NY). Goat polyclonal anti-Aktl/2 antibody (Akt) was purchased from Santa Cruz Biotechnology, Inc. (Santa Cruz, CA).

In vitro kinase assays. Tissue homogenates from liver, muscle or fat were extracted with tissue homogenization buffer and subjected to immunoprecipitation with IRS-I, IRS-2, or pTyr antibodies followed PI3K assay as described previously (Taniguchi et al, (2005) J. Clin. Invest. 115(3):718-27). For Akt kinase activity, the enzyme was immunoprecipitated from lysates with a goat polyclonal Akt 1/2 antibody, and kinase activity measured using CROSSTIDE™ (Upstate) as a substrate peptide. PTEN activity assay. Phosphatidylinositol (Avanti Polar Lipids) was in vitro phosphorylated to form phosphatidylinositol 3 -phosphate (PI-3P) by recombinant PI3K (Upstate) with [³²P]γ-ATP. The phosphorylated lipid was extracted with methanol/chloroform, dried under nitrogen gas, reconstituted into PTEN assay buffer (10 mM Tris HCl, 25 mM NaCl, />H=7.5) then incubated with PTEN immunoprecipitates from lox/lox or L-Pik3rlKO liver lysates. The PI-3P was re- extracted with methanol/choloroform and run on a TLC plate with a n-propanaol:2M acetic acid (65:35). The intensity of PI-3P spots were quantitated with NIH Image. PTEN activity was determined relative to IgG immunoprecipiates from lox/lox livers. Relative PTEN activity was compared with lox/lox without insulin stimulation. Statistics. Data are presented as ± s.e.m. Student's t-test was used for statistical analysis between two groups, while statistical significance between multiple treatment groups was determined by analysis of variance (ANOVA) and Tukey's t- test.

Results L-Pik3rl KO mice are insulin sensitive

Mice with a liver-specific deletion oiPik3rl were generated via the Cre-loxP system using animals carrying a floxed exon 7, which encodes the N-terminal SH2 domain (Luo, et al., (2005) MoI. Cell. Biol. 25:491-502) and mice carrying the Cre transgene driven by the albumin promoter (Postic and Magnuson, (2000) Genesis 26(2): 149-50). The presence of loxP sites in the Pik3rl gene did not affect expression of p85α as compared to WT littermate controls (Luo et al., (2005) MoI. Cell. Biol. 25:491-502) nor did the presence of albumin-Cre (Michael et al., (2000) MoI Cell

6(l):87-97). The L-Pik3rl KO mice were born in a normal Mendelian distribution and exhibited normal postnatal growth (data not shown). Western blots of liver extracts of L-Pik3rl KO mice revealed an 80-90% decrease in p85α and a complete loss of p50α (FIG. IA), consistent with complete ablation in hepatocytes. The expression of p85α was unaltered in brain, skeletal muscle and fat. Despite the lack of p85α and p50α in liver, L-Pik3rl KO mice exhibited significant improvements in serum metabolic chemistries. Compared to littermate lox/lox controls, L-Pik3rl KO mice displayed lower fasted blood glucose and fasted serum insulin levels at 8, 16, and 24 weeks of age (FIG. IB and 1C). In addition, L-Pik3rlKO mice exhibited decreased levels of serum triglycerides and circulating free fatty acids (FIGs. ID and IE). At 16 weeks of age, L-Pik3rl KO mice were significantly more glucose tolerant to an intraperitoneal glucose challenge (FIG. IF), but this was observed as early as eight weeks of age and was maintained through 24 weeks of age (data not shown).

To further quantify this insulin sensitivity and to determine which tissues were involved in the phenotype, L-Pik3rl KO mice were subjected to a hyperinsulinemic- euglycemic clamp. This revealed increased hepatic insulin sensitivity such that hepatic glucose production was suppressed by 25% more in the L-Pik3rl KO mice compared to controls (FIG. 2A). Somewhat surprisingly, L-Pik3rl KO mice displayed improved peripheral insulin sensitivity, as determined by a two-fold increase in glucose infusion rates (FIG. 2B). This correlated with a 1.5-fold increase in glucose uptake in muscle (FIG. 2C) and a three-fold increase in glucose uptake in fat (FIG. 2D). Thus, improving insulin sensitivity in the liver secondarily improved insulin sensitivity in peripheral tissues.

The physiologic data indicating increased hepatic insulin sensitivity corresponded with decreased expression of several key gluconeogenic genes. Quantitative RT-PCR analysis found a decrease in phosphoenolpyruvate carboxykinase (Pckl), glucose-6 phosphatase (G6pc) and fructose- 1,6-bisphosphatase (Fbpl) mRNAs in liver by 30%, 70%, and 60%, respectively (FIG. 2e). The mRNA levels of the gluconeogenic regulators, peroxisome proliferator-activated receptor (PPAR)-γ coactivator-1 alpha (Ppargcla) and tribbles3 (Trb3) were also decreased by 50% and 60%, respectively, while glucokinase was upregulated by three-fold. These molecular and physiologic data suggest that the loss of Pik3rl in the liver improves hepatic insulin sensitivity. L-Pik3rl KO mice display significantly improved activation of Akt despite reduced total PI3K activity

To determine a molecular mechanism of the improved insulin sensitivity, PI3K function was characterized in L-Pik3rlKO mice. As expected, a 50% decrease in IRS-I -associated PBK activity was observed, as was a 60% decrease in IRS-2- associated PDK activity, which together resulted in a 50% reduction in total PBK activity, as measured from pTyr-immunoprecipitates (FIG. 3A). These decreases in PBK were concordant with a 70% decrease in the expression of the pi 10a catalytic subunit (FIG. 3B), but were not associated with decreased insulin receptor activation in the L-Pik3rl KO mice (FIG. 3C). The parallel decrease in expression of pi 10a was expected, since the regulatory subunits are known to stabilize the catalytic subunit (Yu et al., (1998) MoI. Cell. Biol. 18(3): 1379-87).

Despite these decreases in IRS-I, IRS-2 and pTyr-associated PBK activity, both Ser473 phosphorylation of Akt and Akt kinase activity were upregulated by 1.5 fold (FIG. 3E). This enhanced Akt activation could be in part related to the decreased TRB3 levels (FIG. 3F and FIG. 2E), however it seems more likely that the decreased TRB3 expression is merely an indirect marker of insulin sensitivity, since TRB3 levels are directly regulated by insulin (Koo et al., (2004) Nat. Med. 10(5):530-4). Akt is activated by the lipid product of PBK, phosphatidylinositol(3,4,5)- trisphosphate (PIP₃). To determine if changes in PIP₃ levels might help to explain the increased Akt activation, an immunofluorescent histology technique with an anti-PIP₃ antibody was used to estimate the accumulation of PIP3 levels in vivo (FIG. 4A and (Kitamura et al., (2004) J. Clin. Invest. 113(2):209-19). After 5 minutes of insulin stimulation, PIP3 levels increased, but did not differ between control and KO animals; however, after 15 minutes of stimulation, PIP₃ levels in the L-Pik3rlKO remained high at 74 ± 3.3% of maximum stimulation, while PIP₃ levels in the control decreased to 37.7 ± 2.5% of peak levels (FIG. 4B). These data indicate that although less PBK is associated with IRS-I and IRS-2 in the Pik3rlKO livers, more PIP₃ accumulates over time. To determine whether this increased accumulation of PIP3 is due to enhanced

PBK activity or decreased turnover, total PBK activity and the activity of the lipid phosphatase, PTEN, which degrades the PIP3 formed by PBK were directly assessed. Over 15 minutes, pTyr-associated PBK activity was not changed in the livers of either the lox/lox or L-Pik3rlKO mice, though the insulin-stimulated PI3K activity of the knockout mice remained at only half the level of the controls (FIG. 4C). On the other hand, the lipid phosphatase activity of the negative regulator PTEN was consistently decreased by 40% in L-Pik3rlKO at all timepoints (FIG. 4D). Moreover, insulin had no effect on PTEN activation in either the control or knockout mice. This decrease in PTEN activity is not due to decreased PTEN expression (FIG. 4E), but must be due to some other aspect of the actions of the regulatory subunit of PI3K.

Additional References

Cai et al, (2005) Nat. Med. 11,(2): 183-90. Luo et al., (2005) Proc. Natl. Acad. Sci. U.S.A. 102(29): 10238-43.

Example 2: The p85α Regulatory Subunit of Phosphoinositide 3 -Kinase activates JNK via a cd c42/MKK4 pathway

Insulin resistance is an underlying feature of type 2 diabetes and the metabolic syndrome (Reaven, (2005) Cell. Metab. 1 :9-14). Physiologic and epidemiologic studies have demonstrated strong links between obesity and the development of insulin resistance (Hu et al., (2001) N. Engl. J. Med. 345:790-7; Sinha et al., (2002) N. Engl. J. Med. 346:802-10). Not surprisingly, the rise of type 2 diabetes in the United States over the last decade has paralleled the rapid rise in obesity (Mokdad et al., (2003) JAMA 289:76-9). While there are multiple mechanisms involved in obesity linked insulin resistance, one important mediators of the process is the stress kinase, c-Jun-N-terminal kinase (JNK), which is activated by insulin (Miller et al., (1996) Biochemistry 35:8769-75) and cytokines (Baud et al., (1999) Genes Dev. 13: 1297-308) in obesity and other insulin resistant states and phosphorylates IRS-I on serine residues decreasing its ability to mediate insulin signaling (Ozcan et al., (2004) Science 306:457-61, Pirola et al, (2004) Diabetologia 47: 170-84). The importance of this stress kinase is illustrated by that fact that genetic deletion of JNKl can prevent insulin resistance in severely obese mice (Hirosumi et al., (2002) Nature 420:333-6).

While it is clear that the activation of JNK contributes to the pathophysiology of obesity, the molecules that are directly involved with the activating JNK in this disorder not well understood. One interesting and perhaps counterintuitive candidate molecule is the p85α regulatory subunit of phosphoinositide 3-kinase. PI3K is an obligate heterodimer, with an SH2 -containing regulatory subunit (p85) and a catalytic subunit (pi 10). The regulatory subunit mediates the binding, activation and localization of the PBK enzyme (Backer et al., (1992) EMBO J. 1 1 :3469-79, Fruman et al., (1996) Genomics 37: 113-21, Virkamaki et al., (1999) J. Clin. Invest. 103 :931- 43). While the p85 subunit is an important link in the metabolic actions of insulin as a component of the PI3K holoenzyme (Taniguchi et al., (2006) Cell. Metab. 3 :343-53), it also plays a role as an independent negative regulator. Indeed, full or partial deletions of the p85 subunit significantly can prevent high-fat diet- induced induced insulin resistance (Terauchi et al., (2004) Diabetes 53:2261-70), as well as diabetes in mice with heterozygous deletions of the insulin receptor and IRS-I (Mauvais-Jarvis et al., (2002) J. Clin. Invest. 109: 141-9).

Several studies have linked p85α circumstantially to the activation of JNK. For instance, cells lacking p85α have diminished JNK activation in response to insulin/IGF- 1, and this is reversed with re-expression of p85α. The p85 regulatory subunit has also been identified as part of a complex that is involved in JNK activation (Zhu et al., (1998) J. Biol. Chem. 273:33864-75), and has been shown to bind to the small GTPase cdc42 (Tolias et al., (1995) J. Biol. Chem. 270: 17656-9; Zheng et al., (1994) J. Biol. Chem. 269: 18727-30) which is an upstream activator of JNK (Minden et al., (1995) Cell 81 : 1 147-57). Moreover, muscle biopsies from obese diabetic patients found a strong positive correlation of p85 expression and JNK.

Although these data suggest an intriguing and novel connection between the PI3K and stress kinase pathways, this question has been difficult to address in vivo, because mice carrying germline deletion of the Pϊkirl gene that encodes p85α and its shorter isoforms p55α and p50α die perinatally (Fruman et al., (2000) Nat Genet 26:379-82). To circumvent the problems of germline knockout models of p85, and to investigate the links between p85α and JNK activation in vivo, mice with a liver- specific deletion oiPik3rl gene (L-Pik3rlKO) were created. As described herein, mice lacking p85α in liver have diminished hepatic activation of JNK and improved whole body insulin sensitivity. In addition, p85α activates JNK via the cdc42-MKK4 pathway and that this interaction requires both an intact N-terminus and functional SH2 domains in the C-terminus of the p85a regulatory subunit. Thus, p85α may regulate insulin sensitivity in both lean and obese mice via crosstalk with the stress kinase pathway. Experimental Procedures

Animals and high fat diet. All animals were housed on a 12-h light-dark cycle and fed a standard rodent chow (Purina). High fat chow (45% kcal from fat) was purchased from Research Diets. All mice in this study were on a 129Sv- C57BL/6-FVB mixed genetic background, and littermates of the same mixed genetic background were used as controls.

Metabolic studies. Metabolic studies were performed as described above in Example 1.

Recombinant Adenoviruses. The p50α and p55α adenoviruses were constructed as previously described (Ueki et al., (2000) MoI. Cell. Biol. 20:8035-46). The constitutively active MKK4 adenovirus was purchased from CellBio Labs (San Diego, CA), and the constitutively active cdc42 adenovirus was a gift from James Bamburg (Kuhn et al., (2000) J. Neurobiol. 44: 126-144). The wild type (WT) p85α, ΔSH3, ΔBH, ΔiSH2, RARA and ΔΔp85 constructs were made as follows. Cloning ofp85 constructs

The p85 constructs were cloned from a cDNA of human p85α using the following PCR primers:

1. WT p85α with C-terminal FLAG tag

5' : AGTGCTGAGGGGTACCAGTACAGA (SEQ ID NO: ) 3' (3 'p85 FLAG tag primer):

GCGTCGACTAACTACTTATCGTCGTCATCCTTGTAATCTCGCCTCTGCTG TGCATATAC (SEQ ID NO: )

2. ΔSH3 (Deleted aa 1-81) (Xbal on 5', Sail on 3', FLAG tagged on N and Cterm):

5' ITAGGCTCTAGACGCCGCCACCATGGATTACAAGGATGACGACGA TAAG AAAATCTCGCCTCCCACAC (SEQ ID NO: ) 3' : 3'p85 FLAG tag primer (see above)

3. ΔBH (Deleted aa 136-308, Xbal on 5', Sail on 3', internal FLAG and C- term FLAG)

1^st half: (Xba on 5', BamHI on 3 ') 5':

TAGTAGGCTCTAGACGCCGCCACCATGTACCCATACGATGTTCCAGATTAC GCAAGTGCTGAGGGGTACCAGTACAGA (SEQ ID NO: )

3': CTACTAGGATCCTTTCTTTTCAATGGCTTCCAC (SEQ ID NO: ) 2^nd half (BamHI on 5', Sail on 3 ')

5' ITAGTAGGGATCCGATTACAAGGATGACGACGATAAGCCTCCTAA ACCACCAAAACCT (SEQ ID NO: )

3': 3'p85 FLAG tag primer (see above)

4. ΔiSH2 fragment (Deleted pi 10 binding domain from aa 480-510, internal and C-terminal FLAG tag) l^st half (BamHI on 3' end)

5': CCTCCTAAACCACCAAAACCTAC (SEQ ID NO: ) 3': CTAATCGATAGAGGTCTGGCACTGTTCTTCAAAT(SEQ ID NO: ) 2^nd half (BamHI on 5', Sail on 3')

5 ' : AGT ATCGATGATTAC AAGGATGACGACGAT AAGTTGAAGTCTCG AATCAGTGAAA (SEQ ID NO: )

3': 3'p85 FLAG tag primer (see above)

The PCR fragments from the WT, and ΔSH3 reactions were digested with Xbal/Sall then ligated into pBluescript (pBS). The 5' portion of the ΔBH reaction was digested with Xbal/BamHI and the 3' fragment was digested with BamHI/Sall. The two fragments were ligated together in pBS. The ΔiSH2 construct was made by cutting the above 1.5 kb PCR fragment with EcoRV and Sail, then fusing it with the Xbal-EcoRV fragment of the WTp85α. The ΔΔp85 construct was made by ligating the Xbal-EcoRV fragment of WTp85α FLAG construct (N-terminus) to the EcoRV- SaII ΔiSH2 fragment (C-terminal half).

The above fragments (excised by either Notl/Sall or Xbal/Sall) were ligated into a custom pShuttle vector with a chicken β-actin/CMV enhacer sequence (CAG) and BGH poly A sequence (CAG pShuttle), which was made by simply ligating the CAG enhancer into an empty pShuttle vector. A new multiple cloning site (MCS) was then inserted between the CAG enhancer and the polyA sequence. The MCS was as follows: NotI-NheI-SwaI-EcoRV-Hind3-SbfI-SalI. After subcloning the p85 constructs into this vector, the adenoviruses were then produced according to the standard AdEasy protocol.

To create the recombinant adenoviruses, the above constructs were ligated into an empty pShuttle vector with a CAG promoter and BGH poly A sequence (CAGpShuttle). A new multicloning site was inserted into the vector containing the following restriction sites in sequence: NotI-NheI-SwaI-EcoRV-Hind3-Sbfl-SalI. The adenoviruses were then produced according to the standard AdEasy protocol (He et al, (1998) Proc. Natl. Acad. Sci. U.S.A. 95:2509-14).

Adenovirus-mediated gene transfer and in vivo insulin stimulation. Prior to use on primary hepatocytes or in vivo, all adenoviruses were purified on sequential cesium chloride gradients then dialyzed into PBS containing 10% glycerol. 10-12 week-old male mice were injected via tail vein with an adenoviral dose of 5xlθ⁸ pfu/g body weight as described previously (Taniguchi et al., (2005) J. Clin. Invest. 1 15:718- 27). On the fifth day after injection, following an overnight fast, the mice were anesthetized with Avertin (1.2% 2,2,2-tribromoethanol in PBS), and injected with 5 U of regular human insulin (Novolin, Novo Nordisk, Denmark) via the inferior vena cava. Five minutes after the insulin bolus, tissues were removed and frozen in liquid nitrogen. Immunoprecipitation and immunoblot analysis of insulin signaling molecules were performed using tissue homogenates prepared in a tissue homogenization buffer that contained 25 mM Tris-HCl (pH 7.4), 10 mM Na₃VO₄, 100 mM NaF, 50 mM Na₄P₂O₇, 10 mM EGTA, 10 mM EDTA, 2 mM phenylmethylsulfonyl fluoride, 1% Nonidet-P40 supplemented with the Complete protease inhibitor cocktail (Roche). All protein expression data were quantified by densitometry using NIH Image software. Antibodies. Rabbit polyclonal anti-IRS-1 antibody (IRS-I), anti-IRS-2 antibody (IRS-2), anti-IR antibody (IR) and pan-p85α antibody were generated as described previously (Ueki et al., (2002) Proc. Natl. Acad. Sci. U.S.A. 99:419-24). Rabbit polyclonal anti-Akt, anti-phospho Akt (S473) anti-phospho GSK3 (Ser9), anti- GSK3, anti-phospho FoxOl (Ser256), anti FoxOl, anti-phospho MAPK, anti-MAPK, anti-phospho JNK, anti- JNK, anti-phospho MKK4, and anti-MKK4 antibodies were purchased from Cell Signaling Technology (Beverly, MA). Anti-phosphoserine 307 IRS-I antibody, cdc42 antibody and phosphotyrosine (pTyr) antibody, 4G10, was purchased from Upstate Biotechnology, Inc. (Lake Placid, NY). Goat polyclonal anti- Aktl/2 antibody (Akt) was purchased from Santa Cruz Biotechnology, Inc. (Santa Cruz, CA).

In vivo cdc42 activation assay. Mice were anesthetized and injected with 5U of insulin via the portal vein. Three minutes after the injection, the right lobe of the liver was quickly dissected and snap frozen directly into liquid nitrogen.

Approximately 200-300 mg of the liver sample was used to measure cdc42 activity in the livers with a PAKl pulldown assay (Upstate). The kit was used essentially as directed, but with the addition of 10 mM ortho vanadate to the reaction buffer.

Primary Hepatocyte Isolation. Hepatocytes were isolated as described previously (Block et al, (1996). J. Cell. Biol. 132: 1133-49). Briefly, the mice were anesthetized with a 1.2% solution of 2,2,2-tribromoethanol and the portal vein was cannulated with a 24.5 G catheter, and the liver perfused for 15 minutes at a rate of 7 mL/min with calcium-free perfusion buffer. The blanched liver is perfused with collagenase solution (200U/mL) for 10 minutes at 7 mL/min to release hepatocytes from the extracellular matrix. The digested liver was excised and placed in preservation buffer, where the digested cells were gently scraped from the liver sac, washed and purified with Percoll to remove dead cells and enrich the hepatocyte fraction. Typical viabilities are between 85-90%, with cell yields of 1.0-1.5 x 10⁶ cells/g mouse. The isolated hepatocytes are then grown on collagen-coated plates in Advanced DMEM (Gibco) supplemented with glutamine, antibiotic cocktail and 10% FBS.

Statistics. Data are presented as ±s.e.m. Student's t-test was used for statistical analysis between two groups, while statistical significance between multiple treatment groups was determined by analysis of variance (ANOVA) and Tukey's t- test.

Results

Blunted JNK Activation in L-Pik3rlKO Mice Ameliorates Obesity- Induced Diabetes

To study the crosstalk between p85α and JNK, mice with a liver-specific deletion oiPik3rl via the Cre-loxP system (L-Pik3rlKO) were generated as described previously (Postic and Magnuson. (2000) Genesis 26: 149-50). Mice carrying a floxed exon 7, which encodes the N-terminal SH2 domain common to all three transcripts, p85α, p55α and p50α (Luo et al., (2005) MoI. Cell. Biol. 25:491-502), were crossed with mice carrying the Cre transgene driven by the albumin promoter. Western blots of liver extracts of L-Pik3rl KO mice revealed an 80-90% decrease in p85α and a complete loss of p50α (FIG. 5A), consistent with complete ablation oiPik3rl in hepatocytes. Obesity is a powerful physiologic activator of JNK, particularly in the liver.

To investigate if p85α played a role in activation of JNK in vivo, six-week old L- Pik3rlKO mice were placed on a high fat diet (45% of calories from fat) for a total of eight weeks. At the end of the treatment, both lox/lox and L-Pik3rlKO mice were equally obese (FIG. 5B) and consumed an equal amount of calories (FIG. 12A). Interestingly, while insulin increased JNK activity by three-fold in lean lox/lox animals, L-Pik3rlKO animals showed a 60% reduction in insulin-simulated JNK activation (FIG. 5C). After high-fat feeding, basal and insulin-stimulated JNK activation increased by two-fold in both lox/lox and L-Pik3rlKO animals, but JNK activation in obese knockout animals reached only 50-60% the level observed in obese control animals. The attenuated JNK activity in both lean and obese L- Pik3rlKO mice directly correlated with decreased levels of serine-307 phosphorylation of IRS-I and increased Akt activity compared to controls.

These reductions in stress kinase activation translated to marked improvements in glucose homeostasis. L-Pik3rlKO mice maintained lower fasting blood glucose and fasting serum insulin levels when fed either a high- fat diet or normal chow (FIGs. 12B and 12C). In addition, while obese lox/lox mice were severely glucose intolerant, obese L-Pik3rlKO mice exhibited normal to improved glucose tolerance even when compared against control mice on normal chow (FIG. 5C). Thus, the loss of p85α expression in liver protected against obesity-induced insulin resistance and diabetes.

L-Pik3rlKO Hepatocytes are Resistant to JNK-induced insulin resistance.

To determine if JNK resistance was a cell autonomous effect oiPik3rl deletion, JNKl was overexpressed in primary hepatocytes isolated from lox/lox or L- Pik3rlKO mice using adenovirus-mediate gene transfer. The JNKl isoform was chosen because it is the only one of the three JNK isoforms that has been shown to have a significant role in mediating obesity -related insulin resistance in the liver

(Hirosumi et al, (2002) Nature 420:333-6). Following adenoviral infection, JNKl was overexpressed by six-fold in both p85α knockout and control primary hepatocytes (FIG. 6). This forced expression of JNKl led to significant increases in JNK phosphorylation and serine phosphorylation of IRS-I in lox/lox hepatocytes. By contrast, an equal level of JNKl overexpression resulted in only a 2-fold increase in cells derived from L-Pik3rl mice (FIG. 6) (p < 0.05 knockout vs. control cells).

Likewise, overexpression of JNK reduced insulin-stimulated Akt phosphorylation in lox/lox hepatocytes by 85%, while the same level of overexpression in L-Pik3rlKO hepatocytes did not significantly reduce insulin stimulated Akt signaling.

The p85α regulatory subunit activates JNK via a cdc42/MKK4 pathway The defects in JNK activation by insulin in the L-Pik3rlKO hepatocytes in vivo and in vitro indicated that the one of the gene products oiPik3rl regulated some effector of this system. One candidate effector is the small GTPase cdc42, which is known to activate both SEK1/MKK4 and JNK (Gallo and Johnson, (2002) Nat. Rev. MoI. Cell. Biol. 3:663-72), and has been shown to interact with p85α, but it was unknown whether this interaction had any functional consequences in vivo (Zheng et al, (1994) J. Biol. Chem. 269: 18727-30). To assess activation of cdc42, the ability of this protein in its activated form to bind to p21 -associated kinase- 1 (PAKl) was utilized. Using tagged or embolized PAKl protein in a pulldown assay, the level of activated cdc42 was significantly reduced in knockout animals (FIG. 7A). This decrease is cdc42 activation correlated with a decrease in MKK4 phosphorylation/activation (FIG. 7B). Since MKK4 is the direct upstream kinase of JNK, this would result in the observed decrease in JNK activation.

To confirm that this cdc42/MKK4/JNK signaling pathways is an intrinsic property of hepatic insulin signaling, primary hepatocytes from L-Pik3rlKO livers and lox/lox controls were infected with constitutively active forms of MKK4 and cdc42 and stimulated with either insulin or saline control (FIG. 7C). Expression of activated MKK4 or cdc42 enhanced JNK phosphorylation, indicating that these enzymes were upstream of this pathway in hepatocytes. Moreover, consistent with the role of JNK as an antagonist of insulin signaling, expression of active cdc42 or MKK4 led to significant reduction in Akt phosphorylation by insulin, indicating that these molecules could play a role in regulating hepatic insulin sensitivity in vivo. The Negative Effects on Insulin Signaling are Specific to p85α

Since Pϊkirl encodes three different regulatory subunit isoforms, the possibility emerged that the negative regulation of insulin signaling could be isoform specific. To address this possibility, adenovirus-mediated gene transfer was used to reconstitute the livers of L-Pik3rlKO mice with each of the three Pik3rl gene products: p85α, p55α, or p50α. As was previously observed in other cell types, the hepatic reconstitution of L-Pik3rl KO mice with each of the three Pik3rl isoforms restored pTyr-associated PI3K activity to similar extents (FIG. 8B).

Despite the fact the PI3K activity enabled by each of these isoforms was nearly equal, Akt activation was differentially affected by the expression of p85α. Thus, while the expression of control LacZ, p55α, or p50α maintained the elevated Akt activation observed in L-Pik3rlKO mice, the expression of p85α caused a relative decrease in Akt phosphorylation to a level similar to lox/lox controls. In addition, re-expression of p85α specifically restored several mechanisms of negative regulation to L-Pik3rlKO animals. The expression of p85α restored insulin- stimulated JNK activation and levels of IRS-I serine phosphorylation back to levels comparable to lox/lox controls (FIG. 8C).

These changes at the molecular level correlated with changes at the physiologic level. The reconstitution of L-Pik3rlKO mice with p85α, but not its short isoforms, reversed the improvements in fasting blood glucose and fasting serum insulin levels and restored them to the levels of lox/lox controls (FIG. 8D). Moreover, re-expression of p85α produced a relative glucose intolerance in L- Pik3rlKO mice compared to LacZ-treated KO mice (FIG. 8E), such that the glucose excursion curves of p85α-expressing mice were indistinguishable from lox/lox controls.

Potentiation of JNK Activation by p85 Occurs Independently of PI3K Activity

Since insulin can activate small GTPases like Rac and cdc42 by PB K- dependent mechanisms, experiments were performed to determine whether the decreased cdc42/JNK activation in L-Pik3rl merely reflect decreased PI3K activity, or is due specifically to some aspect p85α expression. To this end, the livers of L- Pik3rlKO animals were reconstituted with either WT p85α, or one of two p85α mutants that are incapable of activating PB K by adenovirus-mediated gene transfer. One mutant substitutes a FLAG tag for the inter-SH2 (ΔiSH2) domain, which mediates the binding and activation of pi 10 (Dhand et al., (1994) EMBO J. 13:511- 21). When overexpressed in cells or in mouse livers, the ΔiSH2 construct has a dominant negative effect (Miyake et al., (2002) J. Clin. Invest. 110: 1483-91). The other p85 mutant contains arginine to alanine substitutions in critical residues in both SH2 domains in the C-terminus (RARA); this mutant is able to bind pi 10, but cannot bind to phosphorylated IRS proteins, which is required for the proper activation and localization of the PI3K holoenzyme (Hill et al., (2001) J. Biol. Chem. 276: 16374-8). Interestingly, JNK activity and serine phosphorylation of IRS-I was restored by either WTp85α or the ΔiSH2 mutant, but not by the RARA mutant (FIG. 9A). This activation of JNK could not have occurred by a PI3K dependent mechanisms, since the ΔiSH2 mutant drastically inhibited total PI3K in these livers, while the re- expression of WT p85a restored PI3K back to levels of lox/lox animals (FIG. 9B). These experiments suggest that p85α expression may thus be the more critical link to JNK activation than the generation of PIP₃, at least in the liver. Interestingly, the RARA mutant, which also cannot activate PI3K, was also unable to activate JNK, which indicates that functional SH2 domains are necessary for p85-JNK crosstalk.

To further determine the extent to which PI3K activity is necessary to activate cdc42, the same p85α mutants were expressed in L-Pik3rlKO primary hepatocytes and insulin-stimulated cdc42 activity was measured (FIG. 9C). As with the JNK activity in whole livers, both the WT and the ΔiSH2 versions of p85a fully restored the cdc42 response, despite their dichotomous effects on PI3K activity. On the other hand, the RARA mutant had neutral effects on both PI3K and cdc42 activity. These data correspond with the in vivo JNK data (FIG. 9A) that indicates that full-length p85α with functional SH2 domains is necessary for the insulin-dependent activation of cdc42/JNK, while PI3K activity is not.

These molecular changes in cdc42/JNK corresponded to physiologic changes, where increased JNK activity led to decreased insulin sensitivity. For instance, the expression of either WTp85α and ΔiSH2, which increased cdc42 and JNK activation, led to worsened glucose tolerance compared to L-Pik3rlKO mice treated with control LacZ adenovirus (FIG. 9D), which normally possess heightened insulin sensitivity

(Taniguchi et al., (2006) Cell. Metab. 3:343-53). The ΔiSH2 mutant caused significant glucose intolerance consistent with diabetes, probably due to the inhibition of the positive effects of PBK in addition to the negative effects of JNK activation. Consistent with the cdc42/JNK data, the RARA p85a mutant had negligible effects on insulin sensitivity.

An intact N-terminus of p85 is required for the activation of cdc42

That only full-length forms of p85α are able to activate JNK and suppress insulin action suggested that unique structural features of p85α may account for the functional differences. All regulatory subunits of Class I_A PDK share a common C- terminus, but diverge greatly in the length and composition of their N-termini (Carpenter and Cantley, (1996) Curr. Opin. Cell. Biol. 8: 153-8). While the N-termini of short isoforms p55α and p50α are only 34 and 6 amino acids long, respectively (Antonetti et al, (1996) MoI. Cell. Biol .16:2195-203), Inukai et al, (1996) J. Biol. Chem. 271 :5317-20), the N-terminus of p85α is 339 amino acids long and contains an SH3 domain, two proline rich regions, and a domain homologous to a portion of breakpoint cluster region (bcr) gene product (BH domain).

To investigate whether the negative effects of p85α are specific to one of the domains in the N-terminus, adenoviral p85 constructs were created which substitute a FLAG tag for either the -80 amino acid SH3 domain (ΔSH3) or the -170 amindacid BH domain (ΔBH), which effectively deleted the domain while providing an epitope tag for easy detection by Western. One construct with a combination deletion of both the SH3 domain and inter-SH2 domain (ΔΔp85) was also created to serve as a control for PI3K activity (FIG. 10A). Primary hepatocytes from L-Pik3rlKO mice were infected with ΔSH3, ΔBH, ΔΔp85 adenoviruses and total insulin-stimulated (pTyr- associated) PI3K and cdc42 activity were measured. The loss of either the SH3 or BH domain from the N-terminus of p85α did not affect the ability of p85 to rescue PI3K activity in L-Pik3rlKO hepatocytes (FIG. 10B). On the other hand, the control ΔΔp85 adenovirus, which lacks the pi 10 binding region in the C-terminus fully inhibited PI3K activation (FIG. 10B). However, despite normal PI3K activity in the cells infected with ΔSH3 and ΔBH, cdc42 activity was significantly ablated (FIG. 10C). This abrogation of cdc42 activity also occurred in the ΔΔp85 adenovirus cells, which indicates that a fully intact N-terminus of p85 is also necessary for the activation of cdc42. These data support the notion that the expression so some aspect of the N-terminus of p85, and not PDK activity, is required for the insulin-stimulated activation of cdc42/JNK.

Discussion

Selective ablation oiPik3rl in the liver improves insulin sensitivity and protects mice against obesity-induced insulin resistance. These physiologic changes appear to be due, at least in part, to a diminution of JNK activation and a decrease in the serine phosphorylation of IRS- 1 normally observed in obese insulin resistant states. Thus, obese L-Pik3rlKO mice remained insulin sensitive compared to obese controls due to abrogated JNK activity. Moreover, even in the face of forced overexpression of JNKl, L-Pik3rlKO hepatocytes exhibit decreased JNKl phosphorylation/activity and remain fully capable of activating Akt, while control cells exhibit significant defects in Akt activation. The activation of JNK, particularly in the liver, has been shown previously to be a major mediator of the insulin resistance that occurs in obesity (Ozcan et al., (2004) Science 306:457-61). Consequently, one of the mechanisms by which p85α suppresses insulin action in vivo may occur through the JNK-mediated negative feedback on insulin signaling.

These results are similar to those observed in the whole-body knockout of

JNKl (Hirosumi et al., (2002) Nature 420:333-6), except that that latter was against both insulin resistance and obesity of HFD feeding, whereas in L-Pik3rlKO mice improved insulin sensitivity occurs without protectect against HFD-induced obesity. These data suggest that the chief disorders of obesity — weight gain and insulin resistance — have physiologically distinct mechanisms, where the liver plays a critical role in maintaining insulin sensitivity, even in the face of massive obesity. On the other hand, the mechanisms that control body weight and food intake must lie in other tissues, mostly likely in the central nervous system (Howard et al., (2004) Nat. Med. 10:734-8).

The data of this study also directly identify p85α as an important regulator of cdc42 and JNK activity in vivo, as L-Pik3rlKO mice exhibited a three-fold decrease in insulin-stimulated cdc42 activity, which correlates with a -75% decrease in the activity of downstream kinases MKK4 and JNK. Conversely, the expression of constitutively active forms of cdc42 or MKK4 leads to marked upregulation in JNK activity in Pik3rlKO hepatocytes. The possibility that MKK7, which is similar in structure to MKK4 and also activates JNK (Gallo and Johnson, (2002) Nat. Rev. MoI. Cell. Biol. 3:663-72), may also contribute to the effects of p85 cannot be excluded, since no good antibodies exist to activated forms of MKK7. Thus, in the methods described herein, MKK7 may be substituted for MKK4.

While the exact mechanism by which p85α activates cdc42 and JNK needs further study, the current work has revealed several interesting aspects of this regulation. First, JNK activity is restored by p85α, but not by p55α and p50α, indicating that the activation of cdc42 and JNK is dependent on some particular property of p85α as compared to the shorter regulatory subunits. As described herein, this effect of p85α is not dependent upon PI3K activation, since dominant negative forms of p85 can fully activate cdc42 and JNK, while inhibiting PI3K. On the other hand, deletion of either the SH3 domain or BH domain from the N-terminus is sufficient to ablate the ability of p85 to activate cdc42, while fully maintaining PI3K activity (FIG. 1OB and Beeton et al, (1999) MoI. Cell Biol. Res. Commun. 1 : 153-7). Interestingly, the functional inactivation of the SH2 domains in p85 also rendered it unable to activate either PI3K or cdc42/JNK, suggesting that the proper localization in the cell or within a complex may be required for JNK activation. Thus, the data define the minimal requirements for the activation of JNK by p85 as a fully intact N- terminus of p85 and functional SH2 domains.

The data of the current study are consistent with other reports that suggest that the N-terminus of p85 may have unique properties apart from its role as a component of PI3K holoenzyme. Notably, p85 has been demonstrated as an essential activator of small GTPases such as cdc42 or Rac (reviewed in Burridge and Wennerberg, (2004) Cell 116: 167-79) that mediate PDGF or EGF-induced cytoskeletal changes, such as membrane ruffling or stress fiber disassembly (Brachmann et al., (2005) MoI. Cell. Biol. 25:2593-606; Hill et al., (2001) J. Biol. Chem. 276: 16374-8). Interestingly, consistent with these findings, two other studies have found that p85 can potentiate small GTPases like cdc42 even in the presence of wortmannin (Jimenez et al., (2000) J. Cell. Biol. 151 :249-62, Kang et al., (2002) J. Biol. Chem. 277:912-21). Furthermore, in the study by Hill, et al (Hill et al., (2001) J. Biol. Chem. 276: 16374- 8), it appeared that while wild-type p85 could activate JNK, deletions in either the N- terminus or SH2 domains rendered p85 ineffective in activating JNK.

The mechanism by which the N-terminus of p85 activates cdc42, while still unknown, likely involves specific roles for each of the N-terminal domains (FIG. 11 and Okkenhaug and Vanhaesebroeck. (2001) Sci. STKE 2001:PEl). The BH domain is similar in structure to the Rho-GTPase activating protein (GAP) domain of the breakpoint cluster region (bcr) protein (Musacchio et al., (1996) Proc. Natl. Acad. Sci. U.S.A. 93: 14373-8), and can bind activated cdc42, but has no intrinsic GAP activity because it lacks certain conserved residues in the switch domains (Fidyk and Cerione, (2002) Biochemistry 41: 15644-53). The data also indicate that the SH3 and SH2 domains must also be involved in the activation of since deletion of either of these domains abrogated cdc42 activation (FIG. 11). These domains could function to recruit a cdc42 guanine nucleotide exchange factor (GEF), thereby providing a positive feedback loop for further activation of cdc42 protein, and ultimately, JNK (Bertagnolo et al., (2004) Cell Signal. 16:423-33). In addition, these domains might be responsible for the proper intracellular localization of the cdc42/JNK-activating complex. The p85 subunit has been found to form insulin-dependent protein aggregates that do not generate PIP₃ (Luo et al., (2005) J. Cell. Biol. 170(3):455-64). These aggregates were proposed as sequestration complexes, but an alternate interpretation is that these complexes could be active negative regulatory complexes that activate cdc42 and JNK. Interestingly, these complexes do not form with RARA p85 or with the shorter p55α or p50α isoforms, suggesting a similar requirement of an intact N-terminus and functional SH2 domains for full negative regulation by p85 (Luo et al., (2005) J. Cell. Biol. 170(3):455-64).

The apparent paradox of the improved insulin action afforded by p85 deletion may be partially resolved by the finding that p85 may regulate the activity of PTEN in vivo. L-Pik3rlKO mice displayed decreased PIP₃ turnover during prolonged insulin stimulation (FIG. 8A). PIP₃ levels were also elevated in a previous germline knockout of p85α but it was unclear whether the increase was due to an alteration in PIP₃ turnover or increased kinase activity. That previous study attributed the elevated PIP3 levels to the upregulation of the short isoforms, p55α and p50α (Dhand et al., (1994) EMBO J. 13:511-21). This mechanism, however, cannot account for the elevated PIP3 levels observed in L-Pik3rlKO mice, since deletion oiPϊkirl ablates both p55α and p50αin addition to p85α. Exactly how p85α might regulate PTEN is not known, though it is possible that p85α could modulate PTEN indirectly by altering some post-translational modification of PTEN or possibly its subcellular localization. Taken together, these data demonstrate a unique role for the p85α regulatory subunit in insulin signaling and the physiologic regulation of glucose homeostasis. Although p85 is an essential part of the PDK heterodimer, it also plays a novel role in regulating a cdc42/MKK4/JNK pathway that suppresses insulin action in both lean and obese mice. These mechanisms not only provide a level of internal negative feedback on this critical node (Taniguchi et al, (2006) Nat. Rev. MoI. Cell. Biol. 7:85-96) in insulin and growth factor signaling, but also allow crosstalk between the PBK signaling pathway and the stress or inflammatory responses, thus creating an important connection that could have broad impact in the basic understanding of cell growth and metabolism. This powerful link between p85α and JNK activation might also represent an exciting new therapeutic intervention into type 2 diabetes.

Additional Reference:

Ueki et al., (2003) J. Biol. Chem. 278(48):48453-66

Example 3; JNK phosphorylates PTEN Since JNK activity is decreased in p85α KO mice and cells, it is possible that a decrease in JNK could also result in a change in serine phosphorylation and activity of PTEN.

To begin to assess this possibility, an in vitro kinase assay was performed using 100 ng GST-PTEN fusion protein (Upstate Biotechnology) and activated JNK prepared by immunoprecipitating cell lysate from insulin-stimulated brown adipocytes with JNK antibody or control IgG in the presence of 5 μCi of [γ-³²P]-ATP. PTEN Activity Assay: Phosphatidylinositol (Avanti Polar Lipids) was in vitro- phosphorylated to form phosphatidylinositol 3 -phosphate (PI-3-P) by recombinant PI3K (Upstate) with [gamma-32P]ATP. The phosphorylated lipid was extracted with 1: 1 methanolxhloroform, dried under nitrogen gas, reconstituted into PTEN assay buffer (10mMTris-HCl/25mMNaCl, pH 7.5), and incubated with PTEN immunoprecipitates from lox/lox or L-Pik3rlKO liver lysates (Miller et al., FEBS Lett. 528:145-153 (2005)). The PI-3-P was re-extracted with methanokchloroform and run on a TLC plate with n-propanol:2 M acetic acid (65:35). The intensities of PI-3-P spots were quantified with NIH IMAGE (rsb.info.nih.gov/nih-image). PTEN activity was determined by decreased intensity of the PI-3-P spot relative to IgG immunoprecipitates from lox/lox livers. Relative PTEN activity was determined by normalizing PTEN activity to lox/lox livers without insulin stimulation. SDS-PAGE and autoradiography revealed that JNK was able to phosphorylate PTEN in vitro (FIG. 14). To further assess this phosphorylation of PTEN by JNK, mutants of PTEN were generated with substitution of the two potential JNK phosphorylation sites (PTEN-S338A, and PTEN-T366A). These mutants, as well as wild-type PTEN, were then subcloned into pCMV-Tag2 vector that introduced an N- terminal FLAG tag. 5 μg of each construct was transfected into COS7 cells and the activities of Akt and p70S6 kinase following IGF-I stimulation was evaluated. In cells expressing these mutants, two downstream targets of the PI 3-kinase pathway (Akt and p70S6 kinase) were maintained at higher levels of activity than observed in wild-type control cells.

These data suggest that insulin-dependent JNK activation via p85-mediated signaling may result in the increased phosphorylation of PTEN, thereby enhancing its lipid phosphatase activity and/or increasing its stability. These data also indicate that drugs which target the PTEN kinase and reduce phosphorylation of PTEN should also reduce its activity, thereby potentiating insulin action and improving insulin sensitivity.

Additional Reference:

Taniguchi et al, Proc. Natl. Acad. Sci. U.S.A. 103(32)12093-12097 (2006)

OTHER EMBODIMENTS It is to be understood that while the invention has been described in conjunction with the detailed description thereof, the foregoing description is intended to illustrate and not limit the scope of the invention, which is defined by the scope of the appended claims. Other aspects, advantages, and modifications are within the scope of the following claims.

Claims

WHAT IS CLAIMED IS:

1. A method of identifying a candidate compound for improving insulin sensitivity in a mammal in need thereof, the method comprising: providing a sample comprising p85α and cdc42; contacting the sample with a test compound, and evaluating binding of p85α to cdc42 in the sample, wherein a test compound that decreases binding of p85α to cdc42 is a candidate compound for improving insulin sensitivity in a mammal.

2. A method of identifying a candidate compound for improving insulin sensitivity in a mammal in need thereof, the method comprising: providing a sample comprising cdc42 and MLK3; contacting the sample with a test compound, and evaluating phosphorylation of MLK3 by cdc42 in the sample, wherein a test compound that decreases phosphorylation of MLK3 by cdc42 is a candidate compound for improving insulin sensitivity in a mammal.

3. A method of identifying a candidate compound for improving insulin sensitivity in a mammal in need thereof, the method comprising: providing a sample comprising MLK3 and MKK4; contacting the sample with a test compound, and evaluating phosphorylation of MKK4 by MLK3 in the sample, wherein a test compound that decreases phosphorylation of MKK4 by MLK3 is a candidate compound for improving insulin sensitivity in a mammal.

4. A method of identifying a candidate compound for improving insulin sensitivity in a mammal in need thereof, the method comprising: providing a sample comprising MKK4 and JNK; contacting the sample with a test compound, and evaluating phosphorylation of JNK by MKK4 in the sample, wherein a test compound that decreases phosphorylation of JNK by MKK4 is a candidate compound for improving insulin sensitivity in a mammal.

5. A method of identifying a candidate compound for improving insulin sensitivity in a mammal in need thereof, the method comprising: providing a sample comprising PTEN and JNK; contacting the sample with a test compound, and evaluating phosphorylation of PTEN by JNK in the sample, wherein a test compound that decreases phosphorylation of PTEN by JNK is a candidate compound for improving insulin sensitivity in a mammal.

6. A method of identifying a candidate compound for improving insulin sensitivity in a mammal in need thereof, the method comprising: providing a sample comprising one or more target proteins selected from the group consisting of cdc42, MLK3, or MKK4; contacting the sample with a test compound; evaluating binding of the test compounds to the target protein; and selecting the test compound as a candidate compound if it binds to the target protein.

7. The method of claim 6, further comprising: providing a cell having a functional insulin signalling pathway comprising p85α, cdc42, MLK3, MKK4, and JNK; contacting the cell with the candidate compound; contacting the cell with an amount of insulin sufficient to activate said pathway; evaluating activation of said pathway in the cell in the presence of the test compound; comparing activation of said pathway in the cell in the presence of the test compound to a reference representing activation of said pathway in the cell in the absence of the test compound, and selecting the candidate compound as a candidate therapeutic agent for improving insulin sensitivity in a mammal if activation of said pathway is reduced in the presence of the test compound as compared to activation of said pathway in the absence of the test compound.

8. The method of claim 7, wherein activation of said pathway is determined by one or more of detecting cdc42 activation of MLK3; detecting binding of cdc42 to MLK3; detecting MLK3 kinase activity; detecting phosphorylation of MKK4; or detecting JNK activation.

9. The method of any of claims 1-6, wherein the test compound is a small molecule.

10. The method of any of claims 1-6, wherein the test compound is a peptide or peptidomimetic.

11. The method of any of claims 1-6, wherein the sample comprises a cell.

12. The method of any of claims 1-6, further comprising administering the candidate compound to a mammal, and evaluating whether the candidate compound increases insulin sensitivity in the mammal.

13. The method of claim 12, wherein the mammal is in need of increased insulin sensitivity.

14. The method of claim 12, wherein the mammal is a non-human experimental animal.

15. The method of claim 12, further comprising selecting the compound if is increases insulin sensitivity and evaluating the compound in a clinical trial.