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Comprehensive Gene Expression Profiling Reveals Synergistic Functional Networks in Cerebral Vessels after Hypertension or Hypercholesterolemia

Atherosclerotic stenosis of cerebral arteries or intracranial large artery disease (ICLAD) is a major cause of stroke especially in Asians, Hispanics and Africans, but relatively little is known about gene expression changes in vessels at risk. This study compares comprehensive gene expression profiles in the middle cerebral artery (MCA) of New Zealand White rabbits exposed to two stroke risk factors i.e. hypertension and/or hypercholesterolemia, by the 2-Kidney-1-Clip method, or dietary supplementation with cholesterol. Microarray and Ingenuity Pathway Analyses of the MCA of the hypertensive rabbits showed up-regulated genes in networks containing the node molecules: UBC (ubiquitin), P38 MAPK, ERK, NFkB, SERPINB2, MMP1 and APP (amyloid precursor protein); and down-regulated genes related to MAPK, ERK 1/2, Akt, 26 s proteasome, histone H3 and UBC. The MCA of hypercholesterolemic rabbits showed differentially expressed genes that are surprisingly, linked to almost the same node molecules as the hypertensive rabbits, despite a relatively low percentage of ‘common genes’ (21 and 7%) between the two conditions. Up-regulated common genes were related to: UBC, SERPINB2, TNF, HNF4A (hepatocyte nuclear factor 4A) and APP, and down-regulated genes, related to UBC. Increased HNF4A message and protein were verified in the aorta. Together, these findings reveal similar nodal molecules and gene pathways in cerebral vessels affected by hypertension or hypercholesterolemia, which could be a basis for synergistic action of risk factors in the pathogenesis of ICLAD.

Introduction
Atherosclerotic stenosis of large arteries at the base of the brain or intracranial large artery disease (ICLAD) is a major cause of stroke especially in Asians, Hispanics and Africans [1], and is possibly the most common vascular lesion in the world [2]. It affects the middle cerebral artery (MCA), intracranial portion of the internal carotid artery, vertebrobasilar artery and the posterior and anterior cerebral arteries [1]. ICLAD carries a poor prognosis in terms of subsequent vascular event and death, and there is 25 -30% incidence of recurrence in the 2 years after stroke [3,4]. The disease is also prevalent among 53% of vascular dementia and 18% of Alzheimer's disease patients of Asian ethnicity [1,5].
The risk factors for ICLAD include hypertension, diabetes, hypercholesterolemia and cigarette smoking [6], and a strong association is found between asymptomatic ICLAD presenting as intracranial stenosis or calcification with large artery stiffness, and patients with untreated hypertension [7]. Arterial stiffness is a major determinant of increased systolic blood pressure, and is associated with lesions in intracranial arteries [8]. Prolonged elevation of blood pressure leads to reduction in vessel cross sectional area, increased wall thickness and accelerated plaque formation [9,10]. Moreover, hypertension is thought to drive the atherosclerotic changes from larger to smaller vessels, and from extracranial-to intracranial vessels [11,12]. Hypercholesterolemia is also a risk factor for ICLAD [6], and ischemic stroke from both extracranial and intracranial large-artery atherothromboembolism is associated with increased dietary intake of saturated fat, physical inactivity, obesity, and diabetes [13]. Reduction of cholesterol levels with statin treatment delays the progression of lesions in patients with ICLAD [14]. Increased lipoprotein is an independent biochemical risk factor for the development of ICLAD [15], and increased serum cholesterol is associated with elevated levels of oxidized low density lipoprotein [16]. The latter inhibits nitric oxide in endothelial cells to induce vasospasm [17] or increases tissue factor activity in these cells, to promote thrombosis [18]. Other factors that could contribute to ICLAD include increased oxidative stress in vessel walls [19]. A combination of hypercholesterolemia and hypertension may result in greater damage to vessels [9,20].
Epidemiological studies indicate that there is increased risk of a second stroke especially in the first 1 or 2 years of post-stroke event [3,4,21,22]. The reasons for this are not fully understood, but almost certainly involve gene expression changes at the vascular level that drive the atherothrombotic process. Thus far, however, there have been no studies to delineate global gene expression or gene network profiles in large intracerebral arteries at risk of atherothrombosis.
The present study was carried out to compare gene expression and morphological changes in intracranial vessels of rabbits, after exposure to hypertension and/or hypercholesterolemia. These conditions were induced by mostly non-genetically based methods, to reduce possible confounding effects during microarray analysis. The middle cerebral artery (MCA) was chosen for study, as this vessel is often affected in ICLAD [1,23,24,25].

Animals
Male New Zealand White rabbits were used as it is the gold standard in atherosclerosis studies [26]. Although it is possible to produce hypertension in rats and mice, it is difficult to produce hypercholesterolemia in these animals [27]. The very small size of the MCA in rats and mice also hinders gene expression analyses of these vessels. Rabbits were approximately 8 weeks old (young adults) and weighed 2.0-2.5 kg each at the start of the experiments. Two sets of experiments were carried out: i) to determine gene expression changes in the MCA after hypertension, and ii) to determine gene expression changes in the MCA after hypercholesterolemia plus sham operation, and gene expression changes in the MCA after hypertension plus hypercholesterolemia. The first set of experiments were carried on 6 rabbits with the Goldblatt 2-Kidney 1-Clip (2K1C) method used to induce hypertension and fed with normal diet, vs. 6 sham operated controls on a normal diet. The second set of experiments were carried out on 6 rabbits on a high cholesterol diet with sham operation, 6 rabbits with 2K1C to induce hypertension plus a high cholesterol diet, and 6 rabbits on a normal diet.
The 2K1C procedure to induce hypertension was carried out as previous described [28]. In brief, animals were anesthetized with ketamine (75 mg/kg)/xylazine (10 mg/kg) cocktail followed by isoflurane maintenance, and the left renal artery exposed. The artery was partially occluded by attachment of a U-shaped silver 'clip' with a 0.6 mm slot. The clip was in left in place until the animals were sacrificed. Sham operated animals received the same surgical procedures as the 2K1C group, except that the renal artery was not partially occluded after its exposure. Animals that were subsequently treated with high cholesterol diet were allowed to recover from surgery for 1 week before treatment with diet containing cholesterol. Rabbits on this diet were fed with GPR diet +1% cholesterol (Glen Forrest Stockfeeders, Australia). Sham operated control rabbits were fed with GPR diet without cholesterol. All procedures including animals were approved by the Institutional Animal Care and Use Committee of the National University of Singapore, and carried out in accordance with guidelines of the National Advisory Committee for Laboratory Animal Research.

Measurement of Body Weight, Mean Arterial Pressure and Serum Total Cholesterol
Rabbits were anaesthetized by intramuscular injection of ketamine/xylazine cocktail, followed by mean arterial pressure measurements, and collection of blood. Mean arterial pressure was recorded from the 'middle' ear artery (Powerlab 4/30, AD Instruments, CO, USA), and blood samples obtained for cholesterol analysis, at 0, 4, 10 and 12 weeks. Approximately 3 mL of blood was withdrawn from the artery and collected in BD VacutainerH Serum Tubes with Clot activator and silicone-coated interior (Becton Dickinson, NJ, USA). Whole blood was centrifuged at 1,000 g for 15 min, and the serum transferred to new vials and kept frozen at 280uC till analysis. Serum total cholesterol levels were measured by a fluorometric assay (Ex/Em 535/ 587 nm, BioVision Inc., CA, USA). Samples were analyzed in triplicates and read with a microplate reader (InfiniteH i-control, Tecan Trading AG, Switzerland).

Tissue Harvesting and RNA Extraction
The 2K1C rabbits on normal diet, sham operated control rabbits on normal diet, or hypercholesterolemia plus sham operated rabbits and hypertension plus hypercholesterolemia rabbits were sacrificed 12 weeks after surgery. Sham operated control rabbits or untreated controls on a normal diet were sacrificed after a similar time. Animals were deeply anaesthetized by ketamine/xylazine cocktail and euthanized by intravenous injection of pentobarbital (250 mg/kg). The brains were removed and hemisected. The left half of the brain was immersed in 4% paraformaldehyde in 0.1M phosphate buffer in preparation for histology or electron microscopy (see below). The right MCA was identified and quickly stripped off the surface of the brain without any underlying cortical tissue, immersed in RNAlaterH (Ambion, TX, USA), frozen in liquid nitrogen and stored in 280uC till further analysis. Total RNA was extracted using TRizol reagent (Invitrogen, CA, USA) according to the manufacturer's protocol. Extracted RNA was purified using the RNeasyH Micro Kit (Qiagen, CA, USA). The cerebral neocortex, hippocampus, liver, kidney, aorta and other organs were also removed and snap frozen or stored in paraformaldehyde for future analyses.

DNA Microarray Analysis
Ten mL of total RNA from the MCA of four rabbits from each group were submitted to Genomax Technologies, Singapore. RNA quality was confirmed using an Agilent 2100 Bioanalyzer. cRNA was then generated and labeled using the one-cycle target labeling method, and hybridized to the 1-colour Agilent Rabbit Microarray (G2519F-020908; Agilent Technologies, CA, USA), according to the manufacturer's protocol. Data was collected and exported into GeneSpring v11 software (Agilent Technologies) for analysis, using a parametric test based on the cross gene error model. Differentially expressed genes (DEGs) are those that show significantly increased or decreased expression compared to shamoperated controls using one-way ANOVA with Tukey HSD posthoc test and corrected for multiple comparisons using Benjamini Hochberg FDR. P,0.01 was considered significant. In this study, to reduce false positives, only DEGs with greater than 4-fold change (or in the case of common genes between two data sets, greater than 4-fold change in at least one data set) were presented and used in IPA network analyses.

Network Analyses
The gene sets were analyzed using the Ingenuity Pathway Analysis (IPA) software (IngenuityH Systems, www.ingenuity.com). Gene identifiers and corresponding expression values of upregulated or down-regulated DEGS with more than 4-fold change was uploaded into IPA application. Each identifier mapped to its corresponding object in Ingenuity's Knowledge Base, and was overlaid onto a global molecular network developed from information contained in the Ingenuity Knowledge Base. ''Focus Genes'' (Network Eligible genes) are defined as DEGs that have at least one other molecule in the Knowledge Base that interacts with it to form a ''network''. The latter shows interactions between focus genes and 'node molecules' in the network, and how they work together at the molecular level. incubation of 50uC for 2 min and 95uC for 10 min, followed by 40 cycles of 95uC for 15 sec and 60uC for 1 min. Rabbit TaqManH probe for HNF4A was purchased from Applied Biosystems. Rabbit ß-actin TaqManH probe was used as an internal control. The fold change in expression was calculated using the 2-delta delta CT method as described previously [29]. Possible significant differences between the means were analyzed, using one-way ANOVA with Bonferroni's multiple comparison post hoc test. p,0.05 was considered significant.

Western Blot Analysis
Aorta samples were homogenized in 10 volumes of ice-cold lysis buffer (150 mM sodium chloride, 50 mM Tris-hydrochloride, 0.25 mM EDTA, 1% Triton X-100, 0.1% sodium orthovanadate, and 0.1% protease inhibitor cocktail, pH 7.4), followed by centrifugation at 10,000 g for 10 min at 4uC. The supernatant was then collected, and protein concentrations measured using the Bio-Rad protein assay kit. The homogenates (20 mg) were resolved in 10% SDS-polyacrylamide gels under reducing conditions and electrotransferred to a polyvinylidene difluoride (PVDF) membrane. Non-specific binding sites on the PVDF membrane were blocked by incubation in 5% non-fat milk in tris-buffered saline-0.1% Tween 20 (TBST) for 1 h. The PVDF membrane was incubated overnight at 4uC with a mouse monoclonal anti-HNF4A antibody (K9218, Abcam, Cambridge, UK) diluted 1:500 in 5% non-fat milk/TBST. After washing with TBST, the membrane was incubated with horseradish peroxidase-conjugated secondary anti-mouse IgG (Pierce, IL, USA) for 1 h at room temperature. Immunoreactivity was visualized using a chemiluminescence substrate (Millipore, MA, USA). Loading controls were carried out by incubating the blots at room temperature for 30 min with stripping buffer (100 mM 2-mercaptoethanol, 2% SDS, and 62.5 mM Tris-hydrochloride, pH 6.7), followed by reprobing with a mouse monoclonal antibody to ß-actin (Sigma, MO, USA; diluted 1:10,000 in TBST). Exposed films containing blots were scanned and densities of the bands normalized to those of ß-actin. Possible significant differences between the values from treated and control rabbits were analyzed, using one-way ANOVA with Bonferroni's multiple comparison post hoc test. p,0.05 was considered significant.

Histochemistry and Immunohistochemistry
Aorta samples were sectioned at 40 mm using a freezing microtome. Sections were processed for histochemistry using Masson's Trichrome histochemical stain, or immunoperoxidase staining. The latter sections were incubated in a blocking solution composed of 5% donkey serum (Vector) and 0.1% Triton X-100 for 1 h, followed by incubation with mouse monoclonal antibody to HNF4A (diluted 1:100 in PBS) overnight. The sections were then washed three times in PBS and incubated with biotinylated anti-mouse secondary antibody. Immunoreaction product was visualized using an avidin-biotinylated horseradish peroxidase kit (Vector Laboratories, Burlingame, USA). Histochemically or immunohistochemically stained sections were mounted on glass slides and viewed using a light microscope (IX70, Olympus, Japan).

Body Weight, Mean Arterial Pressure and Serum Total Cholesterol Levels
The average body weight was not significantly different between the 2K1C and sham operated groups (data not shown),but mean arterial pressure of 2K1C group was markedly higher than that of sham group at 4, 10, 12 weeks after the surgery ( Figure 1A). The serum total cholesterol level remained at a low level (,100 mg/dl) for both groups throughout the experiment, and no difference was found between the groups, except for a slightly lower value in the 2K1C group on week 4 ( Figure 1B). The average body weight among all groups was not significantly different (data not shown).
Increased mean arterial pressure was found in the 2K1C plus cholesterol-fed rabbits ( Figure 1C), and markedly elevated serum total cholesterol levels (.200mg/dl) were found in both the hypercholesterolemia plus sham-and 2K1C plus hypercholesterolememia groups at 4, 10 and 12 weeks, compared to control rabbits on a normal diet ( Figure 1D).

Microarray analyses of the hypertension only
group. The gene expression profile in the MCA of the hypertension only group was compared with that of sham operated controls on a normal diet. After unknown genes and repeated probes of the same genes were omitted, 51 up-regulated and 97 down-regulated genes (greater than 4-fold change) were found in the MCA (Figure 2). Among the highly up-regulated genes in the MCA of the hypertension only group compared to sham controls were FAM167A, CERS3 and FAM53C (Table 1). Among the highly down-regulated genes were FOXN1, NSRP1 and THUMPD3 ( Table 2). The panel of genes was imported into IPA to analyze network interactions.   The IPA network with the 'largest number of up-regulated focus genes', contained 16 focus genes with functions in Cancer, Connective Tissue Disorders, Skeletal and Muscular Disorders. Focus genes in this network were ASB4, C1orf50, CCDC89, CSDE1, DIS3L2, EHBP1, FAM167A, GIT1, KIAA0232, NAA25, NAE1, PHRF1, SIPA1L3, TAF15, TESK2 and TTLL5. They were related to the 'node molecule', UBC (ubiquitin) ( Figure 3, Table 1). The network with the second largest number of up-regulated focus genes had 12 focus genes, with functions in Cell-mediated Immune Response, Cellular Development, Cellular Function and Maintenance. Focus genes were CCL1, CD46, CYP1A2, FANCC, MEP1B, MFI2, MMP1, PDCD11, RNASE1, SERPINB2, SPAG6 and ZDHHC23; they were related to P38 MAPK, ERK, NFkB, SERPINB2, MMP1 and APP ( Figure 4, Table 1).

Microarray analyses of the hypercholesterolemia
plus sham group. The gene expression profile in the MCA of the hypercholesterolemia plus sham group was compared with that of sham controls on a normal diet. After unknown and repeated genes were omitted, 107 up-regulated and 351 downregulated genes (greater than 4-fold change) were found ( Figure 2). Among the highly up-regulated genes in the MCA of the hypercholesterolemia plus sham group compared to sham controls were SLFN14, CA1, and LOC100357902 (Table 3). Among the highly down-regulated genes were LOC100125984, PFDN5 and CUL3 ( Table 4).

Microarray analyses of the hypertension plus
hypercholesterolemia group. The gene expression profile in the MCA of the hypertension plus hypercholesterolemia group was compared with that of sham controls on a normal diet. After unknown and repeated genes were omitted, 222 up-regulated and 133 down-regulated genes (greater than 4-fold change) were found ( Figure 2). Among the highly up-regulated genes in the MCA of the hypertension plus hypercholesterolemia group compared to sham controls were EPHA1, SP110, SLFN14 (Table 5). Among      Table 3. Up-regulated genes in the MCA of 'hypercholesterolemia plus sham' rabbits vs. sham controls with greater than 4-fold change.  (complex), CD2, CD4 and CD244 ( Figure 11, Table 5). The next network of up-regulated focus genes had 18 focus genes, with functions in Organ Morphology, Visual System Development and Function, Lipid Metabolism. Focus genes were CA2, CDH17, COL17A1, ELOVL3, FANCC, FCRLA, FLT3, HRH1, MAP3K4, MEP1B, MMP1, NFkBID, NR1D1, PIGR, RET, SERPINB2, SPINK1 and TINF2; they were related to P38 MAPK, NFkB, SERPINB2, MMP1 and TNF ( Figure 12, Table 5).

Microarray analyses of the common area between hypertension only-and hypercholesterolemia plus sham
groups. The gene expression profile in the common area between the hypertension only-and hypercholesterolemia plus sham groups was also compared with that of sham controls on a normal diet ( Fig. 2A). After unknown and repeated genes were omitted, 18 up-regulated and 13 down-regulated genes (greater than 4-fold change) were found ( Figure 2). Among the highly upregulated genes in the MCA of the hypertension only group compared to sham controls were Nibrin like (LOC100352398), TAF15 and ANKAR (Table 7). Among the highly down-regulated genes in the MCA of the hypertension only group were FOXN1, ribosomal protein S3a-like and ADAMTS17 (Table 8).

Microarray analyses of the 'exclusive area' in the
hypertension plus hypercholesterolemia group. The gene expression profile in the exclusive area of the hypertension plus hypercholesterolemia group was compared with that of sham controls on a normal diet ( Fig. 2A). After unknown and repeated genes were omitted, 132 up-regulated and 22 down-regulated genes (greater than 4-fold change) were found ( Figure 2). Among the highly up-regulated genes in the MCA of the hypertension plus hypercholesterolemia compared to sham controls were SLFN, MRS2 and HEAT repeat containing (LOC100357872) ( Table 9). Among the highly down-regulated genes in the MCA of the hypertension group were SST, ADAM6, and PRLR (Table 10). The panel of genes was analyzed by IPA.

Electron Microscopy of the MCA
The MCA of sham operated rabbits on a normal diet showed continuous healthy appearing endothelial cells ( Figure 21A). In comparison, the MCA of hypertension only rabbits contained pyknotic endothelial cells ( Figure 21B), while that of hypercholesterolemia plus sham rabbits showed large intracellular vacuoles in endothelial cells ( Figure 21C). The above changes were exacerbated in the hypertension plus hypercholesterolemia rabbits, and pyknotic endothelial cells, breaks in the basement membrane, and large extracellular spaces were present between the basement membrane and underlying smooth muscle cells ( Figure 21D, E). In addition, subendothelial foam cells were observed ( Figure 21E, F) consistent with early atherosclerotic changes. The tunica media and tunica adventitia had a normal appearance.

Western blot analyses.
The antibody to HNF4A detected a 53 kDa band in homogenates of the aorta consistent with the expected molecular weight of the protein ( Figure 22B). Increased density of the HNF4A band relative to beta actin was found in homogenates from hypercholesterolemia plus sham-and hypertension plus hypercholesterolemia group compared to controls, indicating up-regulation of HNF4A protein expression after exposure to hypertension and/or hypercholesterolemia ( Figure 22C).

Histochemistry and immunohistochemistry.
The general structure of the aorta was examined by Masson's Trichrome staining (Figure 23A-C). Hypercholesterolemia plus sham rabbits as well as the hypertension plus hypercholesterolemia rabbits showed neointimal formation along part of the circumference of the vessel. This was associated with migration of redstaining, smooth muscle cells from the tunica media into the neointima ( Figure 23C). The changes were more pronounced in the hypertension plus hypercholesterolemia than the hypercholes- Differentially expressed genes that are common between 'hypertension only' and 'hypercholesterolemia plus sham' groups (both vs. sham controls). + Differentially expressed genes that are common among 'hypertension only', 'hypercholesterolemia plus sham', and 'hypertension plus hypercholesterolemia' groups (all vs. sham controls). doi:10.1371/journal.pone.0068335.t005 Table 6. Down-regulated genes in the MCA of 'hypertension plus hypercholesterolemia' rabbits vs. sham controls with greater than 4-fold change.   terolemia plus sham rabbits ( Figure 23A-C). The tunica media and tunica adventitia had a normal appearance.
Immunostaining of the aorta with HNF4A antibody showed that the endothelial layer of hypercholesterolemia plus sham group and the hypertension plus hypercholesterolemia group were densely stained for HNF4A, compared to controls ( Figure 23D-I). Immunolabel was observed in the nucleus and cytoplasm of endothelial cells and other cells near the endothelial layer. No staining was observed in the tunica media or adventitia ( Figure 23D-I). These results indicate that increased HNF4A gene expression in the aorta occurred mainly in endothelial cells.

Discussion
The present study was carried out to elucidate differential gene expression changes in the MCA of rabbits exposed to two stroke risk factors, i.e. hypertension and/or hypercholesterolemia. Of the DEGs in the MCA that were altered by a single risk factor, hypertension alone vs. sham controls on a normal diet, FAM167A had the highest fold change, followed by CERS3 and FAM53C. FAM167A encodes a ubiquitously expressed gene, the function of which remains unknown. CERS3 (ceramide synthase 3) catalyzes the condensation of sphinganine and fatty acyl-coenzyme A to form dihydroceramide, which is oxidized to ceramide [30]. Among the down-regulated DEGs in the MCA of the hypertension only group were FOXN1, NSRP1 and THUMPD3. Forkhead transcription factor is essential for thymus development [31] and keratinocyte differentiation [32].
Of the DEGs in the MCA that were up-regulated in the hypercholesterolemia plus sham group vs. sham controls on a normal diet, SLFN14 had the largest fold change, followed by CA1 and Gap protein alpha-3 protein-like (LOC100357902). SLFN14 is part of the Schlafen family of proteins which have growth regulatory properties [33]. CA1 (carbonic anhydrase I) is a member of the carbonic anhydrase family that catalyzes the hydration and dehydration of CO 2 /H 2 CO 3 [34] and gene mutation is associated with rheumatoid arthritis [35].
Among the DEGs that were down-regulated in the hypercholesterolemia plus sham group vs. sham controls were beta tropomyosin (LOC100125984), PFDN5 and CUL3. The latter is a member of the cullin protein family [36,37] involved in ubiquitination [38], and gene polymorphism is associated with hypertension [39].
Of the DEGs in the MCA that were up-regulated in the hypertension plus hypercholesterolemia group vs. sham controls on a normal diet, EPHA1 had the largest fold change, followed by SP110, and SLFN14. EPHA1 (Ephrin receptor A1) has recently been identified in large-scale genome-wide association studies to be one of the risk genes for late onset Alzheimer's disease (AD) [40,41]. SLFN14 has been mentioned in the hypertension only group.
Among the DEGs that were down-regulated in the hypertension plus hypercholesterolemia group were FOXN1, TNFRSF11B, and GAPDHS. TNFRSF11B (tumor necrosis factor receptor superfamily, member 11b) is the gene encoding osteoprotegerin, a member of the tumor necrosis factor receptor superfamily of cytokines [42] involved in bone resorption [43] and vascular diseases [44,45]. Gene polymorphism of TNFRSF11B is a risk factor for ischemic stroke [46]. FOXN1 has been mentioned in the hypertension only group.
Of the DEGs in the that were up-regulated in common between the hypertension only-and hypercholesterolemia plus sham groups (both vs. sham controls), Nibrin like (LOC100352398) showed the largest fold change, followed by TAF15, and ANKAR. TAF15 (TATA box binding protein associated factor 15) is a member of the FET family of RNA-binding proteins [47]. ANKAR (ankyrin and armadillo repeat containing) is one of the genes affected in aortic dilatation/dissection [48].
Among the DEGs that were down-regulated in common, between the hypertension only, and hypercholesterolemia plus sham groups (both vs. sham controls) were FOXN1, Ribosomal protein S3-like (LOC100354966) and ADAMTS17 (ADAM metallopeptidase with thrombospondin type 1 motif, 17). The ADAMTS family of genes is involved in cancer, arthritis and coagulation [49], and variants of ADAMTS17 are associated with pediatric stroke [50].
The network in the MCA with largest number of up-regulated focus genes affected by hypertension showed many focus genes related to the 'node molecule', ubiquitin, a regulatory protein that directs other proteins to the proteasome [51]. Apart from chronic neurodegenerative diseases, the ubiquitin-proteasome system is implicated in brain ischemia by inducing cell damage or leukocyte infiltration into the brain [51]. The network with the second largest number of up-regulated molecules was related to P38 MAPK and ERK. P38 MAPK (mitogen-activated protein kinase) is a member of the MAPK family involved in stress-related signal transductions [52], and sustained activation can result in apoptosis in various cell types [53,54,55]. Inhibition of P38 activity is reported to reduce infarct volume and neurological deficits [52,56] as well as cytokine expression after stroke [52]. ERK1/2 (extracellular signal-regulated kinase 1/2) is a well-characterized member of the MAPK family that is activated by mitogens or stressors, and plays an important role in cell differentiation and proliferation [57,58]. Phosphorylated ERK1/2 is increased after cerebral ischemia/reperfusion, and the ERK pathway is involved in both neuroprotection and cell death [58]. Other focus genes in this network were related to NF-kB, SERPINB2, MMP1 and APP. NF-kB (nuclear factor-kappa B) is a central regulator of inflammation and apoptosis [59] and is active in many chronic inflammatory diseases including atherosclerosis [60]. It could have damaging effects in cerebral ischemia [61,62], and inhibition of NF-kB decreases neointimal formation [63,64,65] and reduces Table 7. Up-regulated genes in the MCA that are common between 'hypertension only' and 'hypercholesterolemia plus sham' rabbits (both vs. sham controls) with greater than 4-fold change (see Fig. 2).     infarct volume and neurological deficits after stroke [66]. On the other hand, NF-kB activation could also be neuroprotective [67,68], as it participates in cell death/survival pathways through regulation of pro-and anti-apoptotic genes [69,70]. SERPINB2 (serpin peptidase inhibitor, clade B (ovalbumin), member 2), also known as plasminogen activator inhibitor (PAI) type 2 is a physiological inhibitor of urokinase plasminogen activator (uPA) [71]. Increased SERPINB2 expression is found in the AD brain [72], and after brain ischemia or trauma, particularly in the basement membrane and endothelial cells of vessels adjacent to the lesion [73]. MMP1 (matrix metallopeptidase 1) belongs to a family of protein-digesting enzymes that degrades the extracellular matrix in both physiological and pathological conditions including stroke [74]. MMP1 is increased in atherosclerotic plaques [75] and gene polymorphism is suggested to influence the risk of coronary heart disease [76]. APP (b-amyloid precursor protein) can be processed by an amyloidogenic pathway to form A-beta. The latter and vascular risk factors [77,78] play important roles in the pathogenesis of AD [79,80], and endothelial dysfunction in APP overexpressing mice increases the susceptibility of the brain to AD pathology [81] and cerebral ischemia [82]. The network in the MCA with the largest number of downregulated focus genes affected by hypertension was related to MAPK, ERK 1/2, Akt, 26s proteasome, histone and PKC, while the network with the second largest number of down-regulated focus genes was related to UBC. Akt is a serine/threonine kinase that is activated by PI3K in various growth factors-mediated signaling cascades [83]. The PI3K/Akt signaling pathway is important in mediating cell survival [83,84] and Akt activity is shown to confer neuroprotection after ischemic brain injury [85,86]. PKC (protein kinase C) is a serine-threonine kinase family that is important in regulating cellular functions, and several isozymes of PKC such as PKC , PKCd and PKCc, are associated with cerebral ischemic and reperfusion injury [87,88]. The use of PKCd peptide inhibitors is reported to alleviate reperfusion injury and reduce stroke infarct size [87,88,89]. 26s Proteasome is an essential component of the ubiquitin-proteasome system which functions to degrade cellular proteins [90]. The exact role of the ubiquitin-proteasome system in cerebral ischemia is at present unclear, and deleterious effects of proteasome malfunction, as well as beneficial effects of proteasome inhibition on cerebral ischemia have been reported [51,90]. Histones affect gene transcription by binding to DNA; hence changes in histone H3 may affect the expression of downstream molecules in vessels during hypercholesterolemia. Interestingly, promising outcomes from the use of histone deacetylase (HDACs) inhibitors have been reported in preclinical stroke models [91].
Gene network analysis of the MCA after hypercholesterolemia (plus sham operation), surprisingly, showed very similar networks as that the hypertension only group. This was despite a relatively low percentage of genes in the common area between these two conditions (20.8% of hypertension genes and 6.8% of hypercholesterolemia genes were in the common area, respectively). The results suggest recruitment of different focus genes that are related to similar 'node molecules', as in the following example: the network in the MCA with largest number of up-regulated focus genes affected by hypercholesterolemia showed many molecules related to APP. This is similar to hypertension only rabbits, and could indicate synergism of the two risk factors in affecting the expression of molecules related to APP. Other focus genes were related to tretinoin or all-trans retinoic acid (ATRA) [92], a molecule known to modulate A-beta associated memory deficits and neuropathological alterations in animal models of AD [92,93].
The network with the second largest number of up-regulated focus genes also had many similarities with the hypertension only group, with P38 MAPK, ERK 1/2, NFkB, SERPINB2 and Akt    being central players, together with focus genes related to interferon alpha and VEGF. Interferon alpha is a member of a family of nonspecific antiviral agents with immunomodulatory and cytostatic properties [94]. Although other isoforms of the interferon family such as interferon beta and gamma are associated with atherosclerosis [94], a possible role of interferon alpha in this condition is yet unknown. Vegf (vascular endothelial growth factor) is involved in conditions such as atherosclerosis, cerebral edema, brain and vascular repair following ischemia [95], and plasma vegf values are increased immediately after stroke [96]. The network in the MCA with largest number of downregulated focus genes affected by hypercholesterolemia is related to ubiquitin, 26s proteasome and Akt, and the network with the second largest number of down-regulated focus genes is related to histone H3 and F actin. These changes in ubiquitin, proteasome, and histone H3 are very similar to that of hypertension only animals. Down-regulation of genes related to actin may affect process outgrowth or motility of vascular cells, and actin cytoskeleton signaling is one of the functional pathways that are related to male-specific ischemic stroke genes [97].
The network in the MCA with largest number of up-regulated focus genes affected by hypertension plus hypercholesterolemia showed many molecules related to ERK 1/2, interferon alpha, IL12, SYK, CD2, CD4, and CD244. IL12 (interleukin 12) is a proinflammatory and immunomodulatory cytokine [98] released in response to tissue injury [99]. Elevated serum levels of IL12 are observed in patients with acute myocardial infarction [100], traumatic brain injury [101] and ischemic stroke [102]; in addition, IL 12 signaling is related to female-specific ischemic stroke genes [97]. SYK (spleen tyrosine kinase) is a non-receptor tyrosine kinase [103] involved in signaling cascades in platelets  factor that regulates the expression of many genes involved in lipid transport and glucose metabolism and are associated with cell cycle, immunity, apoptosis, stress response and cancer [128]. Increased expression of HNF4A was shown by RT-PCR and Western blot, and the protein immunolocalized to endothelial cells in the aorta. Since HNF4A suppresses hepatocyte proliferation in adult mice [129], increased expression may likewise affect the turnover of endothelial cells. The effect of this on atherosclerosis is unclear, although excess proliferation of vascular smooth muscle cells is known to have an atherogenic effect [130].
The hypertension plus hypercholesterolemia 'exclusive' area showed up-regulated and down-regulated pathways, related to many of the node molecules mentioned above. This area is tentatively interpreted as containing genes that are exacerbated by two risk factors, and the effects tends towards recruitment of additional molecules into existing networks rather than initiation of new networks. An ischemic cerebrovascular event or transient ischemic attack is a risk factor for a subsequent event [21,22,131]. The reasons for this are multifactorial [132] and may be partly due to presence of existing atherosclerotic lesions. The present findings extend these concepts to the gene network level, and delineates pathways related to NF-kB and TNF that are involved in inflammation and atherosclerosis [60,133], as well as focus genes related to ubiquitin, proteasome, histone, HNF4A, insulin and APP. It is hoped that these could provide a framework for better understanding of pathophysiological mechanisms, and development of new therapies for ICLAD.


extfieldsofstudy: Biology Medicine

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Whole genome phylogeny for 21 Drosophila species using predicted 2b-RAD fragments

Type IIB restriction endonucleases are site-specific endonucleases that cut both strands of double-stranded DNA upstream and downstream of their recognition sequences. These restriction enzymes have recognition sequences that are generally interrupted and range from 5 to 7 bases long. They produce DNA fragments which are uniformly small, ranging from 21 to 33 base pairs in length (without cohesive ends). The fragments are generated from throughout the entire length of a genomic DNA providing an excellent fractional representation of the genome. In this study we simulated restriction enzyme digestions on 21 sequenced genomes of various Drosophila species using the predicted targets of 16 Type IIB restriction enzymes to effectively produce a large and arbitrary selection of loci from these genomes. The fragments were then used to compare organisms and to calculate the distance between genomes in pair-wise combination by counting the number of shared fragments between the two genomes. Phylogenetic trees were then generated for each enzyme using this distance measure and the consensus was calculated. The consensus tree obtained agrees well with the currently accepted tree for the Drosophila species. We conclude that multi-locus sub-genomic representation combined with next generation sequencing, especially for individuals and species without previous genome characterization, can accelerate studies of comparative genomics and the building of accurate phylogenetic trees.

INTRODUCTION
Evolutionary relationships of species derived by comparing single orthologous genes or groups of genes can be negatively affected by potential horizontal gene transfers, incomplete lineage-sorting, introgression, and the unrecognized comparison of paralogous genes (Delsuc, Brinkmann & Philippe, 2005). However, with the advent of the genomic era, it is now possible for researchers to use the complete genomes of fully sequenced organisms for building trees. Though such trees offer robustness for analysis, it becomes impractical to use traditional methods for constructing large scale alignments and for generating trees from these alignments, mainly because of their large size and their highly heterogeneous nature. As a result, there are now sophisticated methods that don't rely on alignment and are optimized for large scale data. These methods generally use vector representation of genes (Qi, Luo & Hao, 2004;Stuart, Moffett & Leader, 2002) or features such as gene content (Huson & Steel, 2004;Snel, Bork & Huynen, 1999;Tekaia, Lazcano & Dujon, 1999), gene order (Bourque & Pevzner, 2002;Korbel et al., 2002), intron positions (Roy & Gilbert, 2005), or protein domain structure (Lin & Gerstein, 2000;Yang, Doolittle & Bourne, 2005).
Despite a strong recent interest in the various large-scale non-alignment methods, they are often viewed as somewhat less rigorous and less reliable. In addition, even with the dramatic decrease in the cost of genome sequencing, it is still not attractive to sequence the genomes of those organisms that have little economical value, especially if their genomes are extremely large. On the other hand, the possibility of obtaining a large and representative set of fragments, instead of the whole genome sequence, can be economically feasible even for the lesser known species and can provide a valuable alternative for many types of genomic scale studies, including phylogenomics.
Recently, several approaches have been developed to represent the genome by randomly sampling the entire genome. These approaches give a good reduced representation of the genome and are based on restriction sites on the genome combined with the next generation sequencing methods. Some popular methods include Complexity Reduction of Polymorphic Sequences (CRoPS) (van Orsouw et al., 2007); restriction site-associated DNA sequencing (RAD-seq) (Baird et al., 2008;Etter et al., 2011); Genotyping by Sequencing method (GBS); double-digest RAD-seq (Peterson et al., 2012), and 2bRAD (Wang et al., 2012). All these methods provides good subsamples from homologous locations within genomes and are widely used to study population genetics (Baxter et al., 2011;Hohenlohe et al., 2010). These methods have the potential to uncover detailed information about a wealth of genomic markers. Complex interactions among markers can also be extracted at the population level (Baird et al., 2008;Davey & Blaxter, 2010). Recently, these fragments have also been used for evolutionary studies (Emerson et al., 2010;Rubin, Ree & Moreau, 2012;Yi & Jin, 2013).
A novel class of enzymes, known as Type IIB restriction endonucleases (Roberts et al., 2003b), are site-specific endonucleases that cut both strands of double-stranded DNA upstream and downstream of their recognition sequences. These restriction enzymes have recognition sequences that are generally interrupted and range from 5 to 7 bases long. They produce DNA fragments which are of uniform length, ranging from 21 to 33 base pairs in length (without cohesive ends) (Roberts et al., 2003a). The fragments are generated from throughout the entire length of a genomic DNA providing an excellent fractional representation of the genome. This method of generating fragments using Type IIB enzymes is termed 2bRAD (Wang et al., 2012) and these fragments have been used for various purposes including population studies, digital karyotyping (Stebbins, 1950), for pathogen identification by computational subtraction (Tengs et al., 2004) and genomic profiling to identify and quantitatively analyze genomic DNAs (Dunn et al., 2002). In this study, we show that these fragments can be used for efficient phylogenetic study for determining evolutionary relationships between distinct species. We have tested this method in silico and shown that 13 different types of IIB restriction enzymes can be used to accurately reconstruct the phylogeny of a diverse set of 21 Drosophila species that are currently available.

Obtaining datasets
Whole genome, nucleotide sequences for the 21 Drosophila species were downloaded from the FlyBase (McQuilton, St Pierre & Thurmond, 2012), NCBI databases and from the Princeton University website (Rebeiz et al., 2009) on July 10, 2010.

Simulated restriction digestion
The PERL program "Phyper" was used to simulate restriction digestion for all 16 Type IIB endonuclease enzymes and for processing the obtained fragments. This program generated a representative list of unique fragments i.e., single-copy fragments (most abundant) and fragments that are present as multiple identical copies (less frequent). The remaining fragments belong to divergent fragment families within a given genome that display one or a few mutations relative to each other and were identified and removed from the analysis. The representative list of fragments were generated for each genome, for each enzyme separately.

Fragment comparisons
The representative lists of fragments were then used with another PERL program "Phyppa" for comparative analyses. This program compares each fragment of a genome with every fragment of another genome in order to find identical fragments and similar fragments (fragments with up to 5 mismatches for ensuring more than 80% similarity among sequences). A total of 210 such comparisons were done in order to generate the full list of shared fragments (identical fragments and similar fragments) for every pair of genomes (both PERL scripts are available upon request). Analyses was performed on a standard laptop with a quad core processor (1.73 GHz Intel Core i7) and with 6 GB RAM. For each enzyme, the scripts required about 6 h to finish for both fragment generation and comparison between all genomes.

Distance calculations
The number of shared fragments between a pair of genomes was then used to calculate the evolutionary distance by calculating the ratio of shared fragment to the total fragments and converting them to negative natural log (Eq. (1)). Conversion to negative natural log was essential to ensure that the distances computed were always positive.

Building trees
Distance measures for all the pairwise comparisons for a particular enzyme were used to build trees using the neighbor program from the Phylip (Felsenstein, 2005) package.
A consensus tree was them produced by combining trees for all the enzymes with the consensus program from Phylip. The flowchart for the entire process is given in Fig. 1.

Datasets
The full nucleotide sequences for 21 Drosophila species downloaded from various sources are listed in Table 1

Type IIB restriction enzymes
The 16 Type IIB restriction endonucleases that could be used for simulating the restriction digestion of Drosophila genomes along with their recognition sites, average distance between the restriction sites assuming random distribution of nucleotides and without any compositional bias, and the size of fragment (blunt) that the enzymes leaves behind are given in Table 2 (Tengs et al., 2004). Unlike traditional Type II enzymes, Type IIB enzymes cleave on both sides of the recognition sequence (about 7-15 bases upstream and downstream, depending on enzyme) generating a fragment of uniform length. Also, the recognition site is usually split into two parts by some fixed number of random bases. They normally leave 2-3 base overhangs on the generated fragment.

Fragment analyses
The numbers of representative fragments obtained from each genome for each enzyme are listed in Table 3. The most frequent cutting enzymes such as BslFI had generally higher numbers of fragments within all genomes compared to other enzymes. Also, D. pseudoobscura and D. persimilis had relatively higher numbers of fragments compared to other genomes with most of the enzymes. Following fragment extraction, the original genomic sequences downloaded from various source databases were represented as a collection of fragments of uniform length. For each genome a total of 16 fragment sets were generated by using 16 different type IIB enzymes. The number of fragments generated by each genome was not closely related to the size of their genomes but they were related to the GC content. Most of the enzymes used in the analysis recognized a GC rich recognition site which is reflected in the number of fragments generated with GC rich genomes. The genomes that were GC rich such as D. pseudoobscura and D. persimilis had higher numbers of fragments compared to other genomes. Similarly the genomes that had lower GC content such as D. willistoni and D. grimshawi generated fewer fragments. Overall, the number of fragments obtained for each species were within the range of expected fragments based on their genome size and estimated distance between restriction cut sites (assuming random sequence without GC content bias). Most enzymes predicted to be frequent cutters generated large number of fragments like BslFI. Predicted rare cutters like PsrI, PpiI, AloI and CspCI generated fewer fragments than other enzymes.

Distance matrices and phylogenetic trees
A comparison of fragments between genomes provided a list of fragments that were shared by those genomes. Closely related organisms are expected to share higher numbers of similar fragments (including identical fragments) compared to other distantly related genomes. Similar fragments are defined as those with 6 or fewer mismatches. Since the average length of fragments generated from various enzymes was around 27 bases, allowing 5 bases mismatch ensured at least 80% similarity among the sequences. The fragments being compared between 2 genomes ranged from 21 bp to 33 bp long (average size of 27 bp). The identical fragments between the 2 genomes are most likely to represent homologous or even orthologous sections of the genomes. Even for a fragment length of 21 bp (smallest fragment size produced by these enzymes), the probability that a particular 21 bp sequence exists one or more times in a genome of 150 Mb is 0.00341%. The pair-wise distance matrices constructed using the similar fragments detected by each enzyme were used to estimate phylogenetic trees (Fig. 2). The individual NJ trees obtained for each enzyme were largely consistent with the currently accepted relationships among the various Drosophila groups and subgroups, as was the single consensus tree obtained (Fig. 3). Per cent support values were calculated based on number of enzymes supporting the particular branch.

CONCLUSIONS
The 21 species of Drosophila used here included the subgenus Sophophora and the subgenus Drosophila. The Sophophora group was represented by melanogaster, obscura and willistoni and the Drosophila group was represented by virilis, repleta and mojavensis. Out of the 12 subgroups within the melanogaster group, 9 subgroups viz., ananassae, montium, melanogaster, suzukii, takahashii, ficusphila, elegans, rhopaloa and eugracilis were represented by 15 species. Of these, only 2 subgroups had multiple members within our data set, but both displayed a monophyletic arrangement within the final tree shown in Fig. 2. The placement of the 12 well-studied Drosophila species viz., D. simulans, D. sechellia, D. melanaogaster, D. erecta, D. ananassae, D. yakuba, D. pseudoobscura, D. persimilis, D. willistoni, D. mojavensis, D. virilis and D. grimshawi within our tree corresponds exactly to the currently accepted phylogeny (Clark et al., 2007;Hahn, Han & Han, 2007;Haubold & Pfaffelhuber, 2012;Stark et al., 2007). Overall, the topology of our 21 species tree agrees precisely with those presented by van der Linde et al. (2010), Haubold & Pfaffelhuber (2012) and Yang et al. (2012 and all the branches were completely resolved. The subgenus Sophophora was clearly distinguished into old world clades melanogaster/obscura and neo world clade willistoni in our tree (van der Linde & Houle, 2008). The largest group melanogaster, had multiple subgroups viz., melanogaster, montium, ananassae and oriental subgroup cluster (eugaracilis, suzukii, takahashii, elegans, rhopaloa, ficusphila). Many previous studies have failed to completely resolve the nodes within the oriental subgroup cluster (Da Lage et al., 2007;Toda, 1991). In our tree, ananassae group formed the earliest branch in the melanogaster group followed by montium subgroup with strong branch support values. Most of the earlier studies confirmed this topology (Da Lage et al., 2007;Kopp, 2006;Prud'homme et al., 2006) except for two studies that placed them together as a sister clade from the rest of the subgroups (Schawaroch, 2002) or reversed the order of branching (Yang et al., 2004). Both these studies had poor branch support. The oriental subgroups cluster formed three sub-clades.
The first sub-clade included elegans and rhopaloa with ficusphila as the sister sub-group, the second sub-clade included suzukii and takahashii and the third sub-clade included the eugracilis sub-group. The placements of these sub-clades were controversial among the literature surveyed and was attributed to the explosive radiation of these oriental groups (van der Linde & Houle, 2008). The eugracilis clade consisting of D. eugracilis is most inconsistently placed clade and it is either placed as sister species of melanogaster sub group, as in our tree (Haubold & Pfaffelhuber, 2012;Pelandakis & Solignac, 1993;van der Linde et al., 2010) or as sister species of the sub clade formed by suzukii and takahashii (Yang et al., 2004) or as sister species of elegans and rhopaloa within the elegans -rhopaloa -ficusphila clade (Yang et al., 2012). The placements of the other two clades, suzukiitakahashii and elegans -rhopaloa -ficusphila within the melanogaster group in our tree is in agreement with other published studies (Kopp, 2006;Kopp & True, 2002). The sub-clade formed by suzukii and takahashii is well supported by most studies including ours with the strong branch support (Da Lage et al., 2007;Kopp & True, 2002;Schawaroch, 2002;Yang et al., 2004). Most studies have confirmed that the rhopaloa subgroup is the sister group of the elegans subgroup but the ficusphila sub group is considered to be polytomic branching clade in the melanogaster group (van der Linde & Houle, 2008). However, in our tree ficusphila sub group is presented as the sister species of rhopaloa -elegans subgroups, albeit with low branch support. Within the Drosophila subgenus, all three groups (virilis, repleta and grimshawi) exhibited a topology frequently observed in other studies (van der Linde & Houle, 2008).
A variety of sub-genomic sampling methods have been used previously for population studies and are especially effective on non-model organisms, but are rarely used for generating phylogenies for a diverse set of distinct species. We show here that multi-locus data obtained from short sub-genomic fragment sets, essentially 2b-RAD, provides good phylogenetic signal and produces a well resolved and well-supported species phylogeny. The wide adoption of various RAD-like methods is due to the fact that deep sequencing of the fragments produced can be easily accomplished following two simple steps: adapter ligation, and then PCR. These methods are applicable to any organism irrespective of its genome size. The 2b-RAD approach to fragment generation and characterization in particular is simple, quick and cost effective (Wang et al., 2012). This method also shares some similarity with the recently described, alignment free multi-locus "co-phylog" method (Yi & Jin, 2013). Both use a large number of short homologous fragments and, consequently, both can be profitably applied to short sequence reads derived via next generation sequencing, even prior to assembly. However, the co-phylog method is distinct in that it makes use of standard alignment algorithms applied to each locus to generate estimates of relatedness for building phylogenies. Effective application of the co-phylog method generally requires that the genomes being compared be closely related, and this would be expected to be true for our method as well, since effective matching of homologous short fragments in either case requires a significant degree of local sequence similarity. Despite this expected limitation, we note that the Drosophila species compared herein are relatively diverse, spanning approximately 40-50 million years of evolution.


s2fieldsofstudy: Biology Chemistry

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Structural Insights into the Role of the Cyclic Backbone in a Squash Trypsin Inhibitor*

Background: MCoTI-II is a potent serine protease inhibitor with a cyclic protein backbone. Results: Its three-dimensional structure and dynamics in complex with trypsin were determined using x-ray and NMR methods. Conclusion: The cyclic backbone of MCoTI-II participates in favorable interactions with trypsin. Significance: We demonstrate a new role for backbone cyclization in enhancing enzyme inhibitory activity. MCoTI-II is a head-to-tail cyclic peptide with potent trypsin inhibitory activity and, on the basis of its exceptional proteolytic stability, is a valuable template for the design of novel drug leads. Insights into inhibitor dynamics and interactions with biological targets are critical for drug design studies, particularly for protease targets. Here, we show that the cyclization and active site loops of MCoTI-II are flexible in solution, but when bound to trypsin, the active site loop converges to a single well defined conformation. This finding of reduced flexibility on binding is in contrast to a recent study on the homologous peptide MCoTI-I, which suggested that regions of the peptide are more flexible upon binding to trypsin. We provide a possible explanation for this discrepancy based on degradation of the complex over time. Our study also unexpectedly shows that the cyclization loop, not present in acyclic homologues, facilitates potent trypsin inhibitory activity by engaging in direct binding interactions with trypsin.

MCoTI-I and II are potent trypsin inhibitors isolated from the seeds of Momordica cochinchinensis and are members of the squash trypsin inhibitor family (1,2). Peptides in this family contain ϳ30 amino acids and have a cystine knot (or knottin) arrangement of their three conserved disulfide bonds. In contrast to the majority of squash trypsin inhibitors, MCoTI-I and II both contain an amide-cyclized backbone and consequently are classified as cyclotides (3), ultra-stable plant defense miniproteins that contain a cystine knot and cyclic backbone. This unique structural motif, present only in the cyclotides, is referred to as a cyclic cystine knot (4).
Cyclotides are gene-encoded, and although the organization of the genes differs in different plants, the common feature is a conserved Asn/Asp residue at the C-terminal of the mature peptide sequence (5)(6)(7)(8). This C-terminal residue appears to be critical for cyclization via an asparaginyl endopeptidase. The sequences of selected cyclotides, including MCoTI-I and II, are shown in Fig. 1A. There are six backbone loops between the cysteine residues, with loop 6 forming as a result of the cyclization. MCoTI-I and II were the first cyclic peptides isolated from M. cochinchinensis, but three additional cyclic peptides with homologous sequences to MCoTI-I and II have recently been discovered in this plant (7). A database (Cybase) (9) has been established to collate the sequences of cyclotides, and there are now Ͼ250 sequences characterized.
Both MCoTI-I and MCoTI-II are stable in human serum, with MCoTI-I reported to have a half-life of more than 2 days (10,11). The stability of cyclotides, coupled with their high sequence diversity, has led to the suggestion they might be useful in the design of novel drug leads (12). In support of this suggestion, there are now several examples of the use of cyclotides as templates, including re-engineering kalata B1, the prototypical cyclotide, to incorporate and stabilize a bioactive peptide sequence with anti-cancer activity (13). Similarly, recent studies have shown that MCoTI-II can be used as a template to develop therapeutic angiogenic agents (11), as well as inhibitors of ␤-tryptase and human leukocyte elastase, therapeutic targets in inflammatory disorders (14,15). MCoTI-I has been used to design inhibitors of HIV-1 viral replication (16) and a compound that activates the p53 tumor suppressor pathway in vivo (10). The latter example is an intracellular target, consistent with the finding that MCoTI-II is able to penetrate cells (17).
To exploit the potential of cyclotide frameworks such as MCoTI-II in drug delivery, it is important to understand their structure and dynamics. Several three-dimensional structures of cyclotides have been determined using NMR spectroscopy, and they generally highlight the well defined structures present in this family (18). Surprisingly, however, the solution structure of MCoTI-II showed loop 6 to be highly disordered as shown in Fig. 1B (3,19). Although the structures of a range of cyclotides have been determined, there have been limited studies on the dynamics and interactions of cyclotides with biological targets. The most extensive analysis was done on MCoTI-I (20) where analysis of the dynamics with NMR spectroscopy suggested a lower order parameter for the cyclization loop (loop 6), indicative of greater structural flexibility for this region of the peptide compared with other loops. Interestingly, an analysis of the dynamics of MCoTI-I bound to trypsin was also carried out, and it was reported that several residues, including the active site lysine residue, become more flexible upon binding to trypsin (20). This is a very surprising result given that the MCoTI peptides have picomolar K i values against trypsin (21) and that protein binding is generally thought to result in reduced rather than increased flexibility (22,23). However, a limited number of binding interactions involving localized increases in flexibility reflective of enthalpy-entropy compensation are known to occur (23). In this study, we have analyzed the dynamics of MCoTI-II in solution and determined its crystal structure bound to trypsin. This is the first structure of a peptide containing a cyclic cystine knot motif bound to trypsin and, indeed, the first resolution of the structure of any cyclotide bound to a defined macromolecular target. Although MCoTI-II differs from MCoTI-I by just two residues (Fig. 1A), our results differ strikingly with the study by Puttamadappa et al. (20) and definitively reveal a tight rigid complex formed between trypsin and MCoTI-II. We believe that the earlier result of an apparently looser structure on binding probably reflects a previously undetected cleavage reaction in the complex. Furthermore, our study reveals a number of interactions between the cyclization loop and trypsin and provides new insights into the role of the cyclic backbone in enhancing the potency of protease inhibitors.

Extraction of MCoTI-II from M. cochinchinensis-Native
MCoTI-II was purified from the seeds of M. cochinchinensis as described previously (19). The mass of the purified peptide was analyzed by electrospray ionization mass spectrometry, and purity was assessed by analytical RP-HPLC.
Synthesis of MCoTI-II-MCoTI-II was synthesized using native chemical ligation with methods established previously for disulfide-rich cyclic peptides (24 -26).
NMR Spectroscopy-T 1 and heteronuclear NOE experiments on free MCoTI-II (6 mM in 100% D 2 O) were recorded at 293 K on 500 and 600 MHz Bruker spectrometers using pulse programs based on those described by Farrow et al. (27). A recycle delay of 2 s was used, and for the T 1 experiments, variable relaxation delays of 10, 20, 40, 50, 75, 100, 200, 300, 400, 500, 700, 1000, 1250, and 1300 ms were used. The data were analyzed with Topspin (Bruker), and the experimental 13 C␣ T 1 and NOE data were fitted using the model-free approach (28). The fit of the experimental and calculated T 1 and NOE values was assessed using an r.m.s. 7 analysis (29).
Here, the experimental values are denoted as "exp," and the calculated values are denoted as "calc." The final r.m.s. was weighted toward the T 1 fit, with W ϭ 1 for T 1 values and W ϭ 0.5 for NOEs, as the T 1 is more accurate than the NOE (29). The overall r.m.s. for the model-free fit was 1.97%. Based on the model-free analysis, the average overall correlation time 0 was calculated to 2.4 Ϯ 0.05 ns, the average internal correlation time i was 20 Ϯ 0.4 ps, and the overall average of the order parameters S 2 was calculated to be 0.84 Ϯ 0.02. The two parameters used to describe the internal dynamics, i , and S 2 , were recalculated with the overall correlation time fixed to 2.4 ns for all data points. The resulting average i and S 2 were 22 Ϯ 0.8 ps and 0.84 Ϯ 0.03, respectively, and the overall r.m.s. value was 3.66%. All experimental and calculated T 1 and NOE values are shown in Table 1 and Fig. 2.
Analytical HPLC and LC-MS-A solution of 10:1 MCoTI-II/ trypsin (0.2 mM MCoTI-II and 0.02 mM L-1-tosylamido-2-phenylethyl chloromethyl ketone-treated bovine pancreatic trypsin (Sigma Aldrich)) in 100 l of 10 mM KH 2 PO 4 , pH 7, was incubated at room temperature for 1 week. The stability of MCoTI-II in the presence of trypsin was monitored by analytical HPLC and LC-MS after 16, 40, 64, 112, and 164 h. At each time point, 20 l of the reaction mixture was quenched with 4 l of 4% TFA. The samples were immediately analyzed by analytical HPLC and LC-MS.
Purification of MCoTI-II Trypsin Complex-A complex of MCoTI-II bound to L-1-tosylamido-2-phenylethyl chlorom- ethyl ketone-treated bovine pancreatic trypsin (Sigma Aldrich) was purified by cation exchange chromatography at 4°C using FPLC (GE Healthcare). MCoTI-II and trypsin were combined in 50 mM NaCl, 50 mM Tris, pH 8, at a molar ratio of 1:2. The trypsin⅐MCoTI-II complex was loaded onto a 1-ml HiTrap SP HP column (GE Healthcare) and eluted using a 0.5%/min gradient of 0 -20% 1 M NaCl, 50 mM Tris, pH 8. The absorbance of the eluted complex was monitored at 280 nm, and mass and purity were evaluated by MALDI-TOF mass spectrometry and SDS-PAGE, respectively. FPLC-purified trypsin-MCoTI-II was concentrated in an Amicon Ultra 4 centrifugal filter device with a 5-kDa cut-off. The final protein concentration of 77 mg/ml was measured at 280 nm on a NanoDrop ND-1000 using an extinction coefficient of 37,650 M Ϫ1 cm Ϫ1 .
Crystal Structure Determination of the MCoTI-II Trypsin Complex-Crystals were grown at 4°C by hanging drop vapor diffusion in drops composed of 1-l well condition and 1 l 23 mg/ml trypsin⅐MCoTI-II complex in 24-well plates containing shallow gradients of PEG 3350 and ammonium acetate in 0.1 M BisTris, pH 6.5, buffer. The buffer used for crystallization was 15 mM Tris, pH 8.0, containing 30 mM NaCl, and crystals grown with 28% PEG 3350 and 0.24 M ammonium acetate in 0.1 M BisTris, pH 6.5, buffer as the well solution were selected for data collection and cryoprotected by the addition of ethylene glycol to 20% (v/v). Data were measured on beamline MX1 (30) of the Australian Synchrotron (wavelength, 0.953645 Å). Data were processed using HKL2000 (31), and the structure was solved by molecular replacement with Phaser (32) from the structure of bovine trypsin (Protein Data Bank code 2UUY (33)). Refine-ment was performed with Phenix (34), and model building was performed with COOT (35). Statistics are given in Table 2.

RESULTS
Synthesis and Characterization of MCoTI-II-MCoTI-II was synthesized using native chemical ligation (36) with methods established previously for other cyclotides (26). Cyclization and oxidation were achieved in a single step in 0.1 M ammonium bicarbonate, pH 8. Purified samples were analyzed by RP-HPLC and electrospray ionization MS.
Analysis of Backbone Dynamics of MCoTI-II-To determine whether the disorder in the three-dimensional structure of MCoTI-II is a result of flexibility or simply a lack of distance restraints in the structure calculations, the backbone dynamics of MCoTI-II in solution were analyzed using NMR relaxation experiments. Natural abundance 13 C T 1 and NOE spectra were recorded at several field strengths on the synthetic version of MCoTI-II. In these spectra, the signals for Cys 21 and Arg 24 appear to be overlapped with Lys 10 and Lys 9 , respectively, and hence, these residues were not part of the relaxation analysis, which included 23 non-Gly residues of MCoTI-II. To describe the MCoTI-II backbone flexibility, the 13 C relaxation data were analyzed using the Lipari-Szabo model-free approach (37), in which the order parameter, S 2 , reflects the nano-to picosecond dynamics of the ␣-carbon backbone. S 2 can be between 0 and 1, with a high value representing small amplitude internal motions and a low value reflecting larger amplitude internal motions.

Structural Analysis of MCoTI-II
The T 1 and NOE data for MCoTI-II are given in Table 1 and Fig. 2. The 13 C-1 H HSQC NMR spectrum of MCoTI-II and S 2 values for the intercysteine loops and individual residues are shown in Fig. 3. The overall correlation time for MCoTI-II is 2.4 Ϯ 0.2 ns, and the average order parameter is 0.84 Ϯ 0.06. Loop 6, with a significantly lower order parameter than the other loops (S 2 ϭ 0.76) is more flexible in solution (Fig. 3). In addition, the order parameter for loop 1 (S 2 ϭ 0.79, excluding residues 9 and 10) is smaller than the average order parameter, indicating that this loop is more flexible than other parts of the molecule. Interestingly, the residues on each side of Lys 6 , the active site residue for trypsin inhibitory activity, have order parameters ϳ0.1 lower than the rest of the loop, with Pro 5 and Ile 7 at S 2 ϭ 0.75. Loops 2, 3 and 4 have order parameters (S 2 ϭ 0.84, 0.85, and 0.85, respectively) close to the average order parameter. Loop 5 appears to be the most ordered loop with S 2 ϭ 0.88. This high value reflects the conformation of loop 5, which comprises a ␤-hairpin, consistent with a lack of flexibility in this loop. The cysteine residues have a considerably higher average order parameter (S 2 ϭ 0.90) than the rest of the molecule, indicating that the core of the cystine knot motif is the most rigid part of MCoTI-II.
Determination of the Crystal Structure of MCoTI-II Bound to Trypsin-The crystal structure of MCoTI-II bound to trypsin was determined at 1.8 Å resolution (Fig. 4A and Table 2) and indicates that MCoTI-II binds to trypsin in a similar orientation to other squash trypsin inhibitors such as CMTI-I (38), with loop 1, the reactive site loop, forming the primary contact with trypsin, and Lys 6 from this loop engaging the active site. Upon binding to trypsin the Lys 6 side chain adopts a single conformation, in contrast to the disorder observed in the solution structure. The side chain of the active site Lys residue is shown in Fig.  4B, highlighting its well defined conformation.
Loop 6, the cyclization loop, which is not present in acyclic squash trypsin inhibitors, forms several interactions with trypsin, including a direct hydrogen bond between the side chain of Ser 31 and the backbone of Gly 219 of trypsin. Interestingly, despite the interactions of loop 6 with trypsin, the crystallographic B-factors indicate that this region of the structure remains the most flexible (Fig. 4C). The cyclization loop of MCoTI-II, therefore, has a propensity for flexibility whether bound to trypsin or free in solution.
A comparison of the bound and solution structures of MCoTI-II is shown in Fig. 4D. Overall, the structure of bound MCoTI-II is similar to that determined in solution. An overlay of the lowest energy NMR-derived structure with the bound form has an r.m.s. deviation of 1.7 Å over the backbone. The orientation of the active site Lys side chain and the structure of loop 6 differ significantly in the lowest energy solution and bound structures. However, in the structural ensemble representing the solution structure, the Lys side chain and loop 6 have a range of conformations that encompass the orientations found in the bound state.
Analysis of the crystal contacts in each of the three distinct complexes observed in the unit cell indicate that in complex 3, loop 6 is more ordered than in the other two complexes because it interacts with a neighboring cyclotide. In all three complexes, loop 2 has limited contacts with neighboring trypsin molecules. Loop 1, including the active site residue, is buried in the complex and does not have crystal contacts with neighboring molecules. This excludes the possibility that any changes in the mobility of loop 1 on binding are the result of crystal contacts.
HPLC Analysis of the MCoTI-II Complex with Trypsin-To determine the stability of the MCoTI-II complex in solution, MCoTI-II was incubated with trypsin and subsequently analyzed with RP-HPLC and mass spectrometry. Although highly resistant to trypsin, MCoTI-II is slowly cleaved after extended incubation with trypsin as shown in Fig. 5. After a 40-h incubation, a peak eluting at 20 min became evident, and the intensity of this peak increased over time. The LC-MS analysis of this peak indicates an increase in mass of 18 Da, compared with cyclic MCoTI-II, which is consistent with conversion to hydrolyzed MCoTI-II, presumably with the backbone linearized C-terminally to the active site Lys. After 112 h of incubation, another peak with a mass of 3245.4 Da appears at 18.5 min. This peak corresponds to MCoTI-II with the binding site Pro-Lys fragment excised. Trypsin has been shown to cleave at the N terminus of Pro in other proteins (39) and appears to do so in the hydrolyzed form of MCoTI-II subsequent to initial cleavage at Lys.

DISCUSSION
In this study, we analyzed the dynamics of MCoTI-II, a promising scaffold in drug design, and determined its structure bound to trypsin. Despite flexibility in loops 1 and 6 in solution, a well defined complex is formed upon binding to trypsin.

and NOE values for MCoTI-II at 500 and 600 MHz, and calculated T 1 and NOE values based on the Lipari-Szabo modelfree approach
The r.m.s. was calculated according to the equation under "Experimental Procedures" and measures the percent deviation between the experimental value and the calculated/fitted value. The overall average correlation time ( 0 ) was calculated to be 2.4 ns in a preliminary free-fitting analysis. The calculation of the internal motional parameters, order parameters (S 2 ), and internal correlation time ( i ) was then carried out with 0 fixed at 2.4 ns.    DECEMBER 13, 2013 • VOLUME 288 • NUMBER 50

JOURNAL OF BIOLOGICAL CHEMISTRY 36145
Unexpectedly, the cyclization loop is involved in the interaction with trypsin, providing an explanation for the highly potent subnanomolar inhibitory activity observed for MCoTI-II (21). The similarity between the crystal structure and solution structures of MCoTI-II suggests that no major conformational changes occur on binding, but there are minor local changes, including the selection of a specific conformation of the active site Lys residue in the complex. Analysis of the dynamics of MCoTI-II free in solution suggests that the flexibility observed for the residues adjacent to the active site residue and for residues in loop 6 might contribute to the peptide being able to adopt a conformation allowing optimal binding. The flexibility observed for the cyclization loop in MCoTI-II is consistent with the presence of several small amino acids such as glycine and serine and is also consistent with the dynamics analysis of MCoTI-I in solution (20). Despite this localized flexibility in solution, MCoTI-II is very stable in human serum, as is the case for other cyclotides such as kalata B1 (11). Presumably, the well defined structural core, conferred primarily by the cystine knot motif, is sufficient to prevent degradation by proteases. The NMR relaxation data reported here unequivocally demonstrate the rigidity of the cystine knot core.
Although cyclization is thought to have evolved primarily because of advantages conferred by enhanced structural stability, this study demonstrates that another benefit of cyclization is that it creates an additional structural loop that can be involved in target interactions as shown in Fig. 6. These additional interactions probably explain the enhanced trypsin inhibitory potency of the cyclic peptide compared with linear forms; MCoTI-II has a K i of 0.03 nM compared with 0.3 nM for a version devoid of loop 6 (21). A role in target interaction has previously been postulated for the cyclic backbone of MCoTI-II (40), but here, we provide the first experimental evidence to support this suggestion. The detailed structural information regarding the binding of MCoTI-II to trypsin should be valuable for subsequent modeling and the design of novel peptides with potential therapeutic activities, particularly for the design of novel enzyme inhibitors. Such modeling and design approaches have already been proven successful for modifying the smaller cyclic trypsin inhibitor sunflower trypsin inhibitor-1 to target kallikrein-4, a protease overexpressed in prostate cancers (41).
The crystal structure of MCoTI-II bound to trypsin appears to be inconsistent in several ways, with the surprising recent report that MCoTI-I apparently becomes more flexible upon binding to trypsin than it is in solution (20). That study originally reported a generalized increase in flexibility of the active site loop (loop 1) of MCoTI-I on binding to trypsin but was modified in a corrigendum (where an error in NMR data analysis was corrected) to conclude that only five residues have increased flexibility upon binding to trypsin, including the active site Lys residue. This interpretation seems to be questionable, given that the side chain amino group of the active site residue in MCoTI-I is clearly detectable in the HSQC spectrum of the complex. Conformationally exchanging or solvent-exposed primary amino groups are not normally visible in NMR spectra due to exchange, so the clear appearance of the Lys amino group in the spectrum is consistent with protection from solvent (19) and a well defined (i.e. not flexible) bound conformation. Furthermore, the other putatively flexible residues are very well defined in the complex of MCoTI-II with trypsin and are involved in either intra-or intermolecular hydrogen bonds. Finally, given that MCoTI-I and II differ by only two residues and as we show that there is a well defined complex between  MCoTI-II and trypsin, it seems highly unusual that the active site residue in MCoTI-I would have enhanced flexibility upon binding to trypsin. Indeed, we propose here that this enhanced flexibility is not intrinsic to the binding process but reflects flexibility in a cleaved product. We found that MCoTI-II bound to trypsin is partially cleaved over a period of days; it is likely that MCoTI-I is also cleaved over a similar time scale, and the presence of an undetected open form of MCoTI-I in the Puttamadappa et al. (20) study could provide an explanation for the apparent flexibility of some residues, as the termini of the open form are likely to be highly flexible. Further study is required to confirm if this is the reason for the discrepancy with the previously published work on MCoTI-I.
Analysis of the structure of MCoTI-II bound to trypsin reported here also provides significant new insights and a different interpretation of the chemical shift changes observed for MCoTI-I upon binding to trypsin to that reported earlier (20). Several chemical shift changes in MCoTI-I were observed upon binding to trypsin. For instance, the chemical shift of the amide proton of Ala 20 in loop 3 changes by 0.45 ppm upon binding with trypsin (20) and that of Cys 17 changes by 0.46 ppm. Our crystal structure reveals that several MCoTI-II residues are involved in binding with trypsin (Fig. 6, A and B) but that Ala 20 forms an intramolecular hydrogen bond with Val 3 , as shown in Fig. 6C, and Asp 16 forms a hydrogen bond with Lys 9 (Fig. 6D). Therefore, although these chemical shift changes were interpreted (20) to be associated with direct interactions with trypsin, our study indicates that they are actually the result of intramolecular structural changes at sites either involving or adjacent to these residues and are not directly a consequence of interaction with trypsin.
In summary, we report the structure of a cyclotide bound to a protein target and provide mechanistic insights into the biological role of the cyclic backbone. We show that MCoTI-II forms a tight complex with trypsin and that the flexibility in the solution state around the active site residue and throughout cyclization, loop 6, relative to the rest of the molecule, allows the peptide to modify its conformation in these regions upon binding to trypsin to maximize favorable interactions. These interactions provide an explanation for the high potency of MCoTI-II. Interestingly, backbone cyclization appears to not only assist in the stabilization of proteins but also facilitates extra binding interactions that can enhance potency. Naturally occurring cyclic proteins such as cyclotides have significant potential as templates in drug design and, in particular, MCoTI-II has been used as a scaffold in the design of a range of novel protease inhibitors. The data obtained from the current study that define the interactions of MCoTI-II with a serine protease might therefore be useful in the design of more potent inhibitors and in understanding how to tailor the specificity of this inhibitor to other related proteases of pharmaceutical interest.