This review deals with the methods of identifying genes that have been activated by inner or outer impulses. The activation and subsequent expression of a gene can be detected by its transcription into a corresponding messenger ribonucleic acid (mRNA). Principles of the methods for identification of individual activated genes, as well as groups of activated genes are described, the former methods being mostly based on subtractive hybridization and serial analysis of gene expression (SAGE), the latter on microarrays. Examples of gene activation by the hormone 17beta-estradiol (E2) are given. In previous reviews, methods for the measurement of receptors and their interactions with other transcription factors and genes were described -3. In thThe life of humans and animals is influenced by the activity of a series of genes that are kept in a silent state, or are activated, depending on the temporary needs of the body. This switching on and off of each gene is executed by an assembly of transcription factors forming a transcription initiation complex (TIC).Examples of such transcription factors are estrogen receptors  that, before being incorporated into a TIC, have to be activated by E2. This hormone itself is synthesized, when an initial signal is given, by virtue of an activation of a series of appropriate genes. Via ER, E2 has manifold biological effects. Biological targets of E2 are, inter alia, blood vessel walls -8, bloodIt is evident that E2 is associated with many biological effects and that many genes must be involved. Consequently, ER must be able to bind to DNA segments, called response elements, in the neighborhood of various genes. The response elements participate, together with other transcription factors, in the formation of TICs that are specific for each gene.An important problem, currently studied in many laboratories, is to find out which genes are activated in various circumstances. The methods that solve this problem are based on a comparative  approach. A test (target) sample, containing active genes is compared with a control sample in which the genes have not been activated. Using this approach, the active genes are singled out among the multitude of inactive genes. However, the comparisons may reveal the opposite of activation, i.e., downregulation of genes.Generally, the activity of a gene is characterized by its transcription into mRNAs as the first step leading to the synthesis of specific proteins. Non-activated genes in the control tissue do not produce any corresponding mRNAs. In most methods, the mRNAs prepared from the test and control tissue are each reverse transcribed into the corresponding complementary deoxyribonucleic acid (cDNA), in order to enable a substantial increase of the material for analysis by polymerase chain reaction (PCR) . As most and Celera .The methods used for the identification of active genes are sketched below. Included are even methods that have not yet been used for the identification of E2-activated genes. It has to be mentioned that only principles, not technical details are dealt with in this review. Neither the techniques of cloning or of identification of genes by sequencing are described here. The readers who are not familiar with these techniques are advised to consult appropriate textbooks [e.g., ]. The deActivated (expressed) genes can be found by comparison of gene contents in the test and control tissues. There are essentially two approaches for finding activated genes: (i) an individual identification, or (ii) an identification of expression profiles after hybridization to a set of known gene fragments (probes) attached to chips in microarrays.This approach means that genes are identified individually, even if several genes can eventually be picked up after cloning. There are several methods that can be used.Differential display seems to be the technically simplest method. Its name stems from the end-point that is a comparison of a side-by-side display of the test and control preparations by electrophoresis. In its basic form, total RNA of the test and control samples is separately subjected to reverse transcription into cDNA that, in turn, is PCR-amplified using arbitrarily chosen primers. The products are applied to a gel electrophoresis and the band(s) that are specific for one of the preparations are cut from the gel, further amplified by PCR (using the same primers) and eventually sequenced .In a more advanced version, mRNAs of the test and control cells are separately reverse transcribed to cDNA Fig. . Each trThe test mRNA is reverse transcribed into cDNA . This isIn another variant , the tesRsaI to obtain shorter, blunt-ended fragments. The test cDNA is divided into two portions  was used to isolate the ESTs specific for one of the libraries. For example, a fibroblast cell line cDNA library was hybridized with a hippocampus library; the common sequences were removed and the specific hippocampus sequences remained. Using the EST method, more than 2000 human brain genes were identified .The SAGE allows serial analysis of gene expression, an analysis of thousands of transcripts. It is based on the assumption that a short nucleotide sequence 10 base pairs (bp) – a tag – contains sufficient information to uniquely identify a transcript. In this respect SAGE differs from the EST approach.)  are cloned into a plasmid vector to create a SAGE library. Individual clones are then sequenced. SAGE is carried out for each sample to be compared.The principle of SAGE is as follows: mRNA is reverse transcribed into cDNA with use of a biotinylated primer, the cDNA is cleaved with a restriction endonuclease and the 3' portions are then isolated by binding to streptavidin beads . In anot) Fig. , mRNAs aThanks to the concatenation, many tags can be detected in a single clone . As eachStill, the specificity of detection of genes with use of the short tags is not absolute. There are two main problems . The firOne such method is called GLGI (Generation of Longer cDNA fragments from SAGE tags for Gene Identification) ,38,40. TMmeI. The longer tags increase the power of identification of genes, while not diminishing the sensitivity of SAGE given by the use of PCR and concatenation. Theoretical calculations showed that >99.8% of the 21 bp tags were expected to occur only once in a genome.Better of seems to be another variant of SAGE, the LongSAGE . This isSAGE was used for the investigation of differences in gene expression in various health conditions. In the studies of breast tumors , global The DNA microarray analysis is used to identify profiles of expressed genes in a given tissue and time. Thousands of known cDNA sequences or oligonucleotides are imprinted on a solid support, sometimes called a chip (e.g., a microscope slide or a nylon membrane), using application robots. Typically, individual spots are 100–300 micrometers in size and are spaced about the same distance apart . More thsingle chip technique [.In the echnique , mRNAs fechnique . AlternaUsing a variant of the method ,47, certtwo-chip technique, mRNAs of the test and control tissues/cells is reverse transcribed into a double-stranded cDNA from which a cRNA is prepared. In the course of the cRNA synthesis biotin molecules are incorporated [In the rporated . The conrporated  where tw] produce chips by a photolithographic method in which thousands of different oligonucleide probes are synthesized in situ on the chip [ and Clondiag Chip Technologies .Commercial systems are available from several sources. For example, Affymetrix (GeneChip) [the chip . A compathe chip . In a sithe chip . Other sAs a rule, more than one gene is activated, and a spectrum of genes is discovered either occurring sporadically or in clusters . For exa offering selected profiles of genes in the macroarray format for various areas (e.g., cancer, cell cycle, cytokine and inflammatory response, etc.).Sometimes a technically easier macroarray is used, e.g., on a 96-well plate . Obvious]. A negative identification can be achieved by the use of siRNA . siRNAs are short RNA duplexes between 15 to 21 nucleotides in length. Once transfected into cells, a siRNA targets the mRNA containing an identical sequence and degrades it in a catalytic manner. The degraded message is no longer functional in translation (the biosynthesis of protein) and thus in the expression of the corresponding gene. SuperArray Corp. provides a line of validated populations of siRNAs in the form of SureSilencing siRNA kits.Quite often the gene identification obtained by an array is confirmed by other methods such as Northern blot analysis , or realThe methods described above can suit two purposes. The single-gene methods can detect and identify new, previously unknown, genes, whereas microarrays can handle a great number of known genes to establish profiles of their expression.SAGE seems to have advantages over hybridization-based methods for the studies of gene expression, such as differential display and subtractive hybridization. SAGE is superior to the EST approach in providing high efficiency in identifying the genes that are expressed at low levels and that represent a majority of genes in the human genome .Microarray techniques usually detect activation of a multitude of genes – a gene profile – that differs from the profile in control tissues/cells and thus – in medicine – may have a diagnostic and/or prognostic value. However, the microarray techniques usually require commercially produced chips as well as specialized equipment and advanced, powerful, computing facilities. Thus they are hardly affordable for small or medium-size laboratories unless they have substantial financial resources.A big question at another level remains so far unanswered: which is the biological "chain of commands" in a given tissue and time resulting in the activation of genes enabling the biosynthesis of cornerstones for gene activation, such as ligands (e.g., E2), receptors (e.g., ER) and other transcription factors, the entire machinery leading to gene activation and expression.


Leptin and insulin are long-term regulators of body weight. They act in hypothalamic centres to modulate the function of specific neuronal subtypes, by altering transcriptional control of releasable peptides and by modifying neuronal electrical activity. A key cellular signalling intermediate, implicated in control of food intake by these hormones, is the enzyme phosphoinositide 3-kinase. In this study we have explored further the linkage between this enzyme and other cellular mediators of leptin and insulin action on rat arcuate nucleus neurones and the mouse hypothalamic cell line, GT1-7.ATP channels in a PI3K dependent manner, and to increase levels of PtdIns(3,4,5)P3. KATP activation by these hormones in arcuate neurones was also sensitive to the presence of the actin filament stabilising toxin, jasplakinolide. Using confocal imaging of fluorescently labelled actin and direct analysis of G- and F-actin concentration in GT1-7 cells, leptin was demonstrated directly to induce a re-organization of cellular actin, by increasing levels of globular actin at the expense of filamentous actin in a PI3-kinase dependent manner. Leptin stimulated PI3-kinase activity in GT1-7 cells and an increase in PtdIns(3,4,5)P3 could be detected, which was prevented by PI3K inhibitors.Leptin and insulin increased the levels of various phosphorylated signalling intermediates, associated with the JAK2-STAT3, MAPK and PI3K cascades in the arcuate nucleus. Inhibitors of PI3K were shown to reduce the hormone driven phosphorylation through the PI3K and MAPK pathways. Using isolated arcuate neurones, leptin and insulin were demonstrated to increase the activity of KATP channel activation in arcuate neurones is sensitive to PI3K inhibition, thus strengthening further the likely importance of this enzyme in leptin and insulin mediated energy homeostasis control. The sensitivity of leptin and insulin stimulation of KATP channel opening in arcuate neurones to jasplakinolide indicates that cytoskeletal remodelling may be an important contributor to the cellular signalling mechanisms of these hormones in hypothalamic neurones. This hypothesis is reinforced by the finding that leptin induces actin filament depolymerization, in a PI3K dependent manner in a mouse hypothalamic cell line.Leptin and insulin mediated phosphorylation of cellular signalling intermediates and of K Leptin and insulin function as peripherally-derived hormone signals involved in the long-term regulation of energy balance -4. TheirATP channels have been identified as an effector mechanism through which leptin and insulin elicit neuronal inhibition. Consequently, leptin and insulin signal the status of body energy stores by activating their receptors on ARC neurones, eliciting changes in the electrical activity and amounts of releasable peptides in specific neuronal populations, leading to compensatory effector outputs, such as changes in food intake, energy balance and glucose homeostasis [However, transcriptional control is not the only effector mechanism elicited by these hormones on ARC neurones. Electrophysiological studies have shown that leptin depolarizes and increases the firing rate of ARC POMC neurones and inhibits the tone of NPY/AgRP neurones . Althougeostasis .Obese humans have elevated leptin and insulin levels, indicative of central resistance to these hormones . The mecATP channel activation.Thus, to elucidate further the pathways that contribute to convergent actions of leptin and insulin on ARC neurones, we have examined the phosphorylation status of key leptin and insulin signalling intermediates in the ARC and have explored the linkage, with a focus on PI3K mediated signal transduction pathways, between these hormones and ARC neurone Kper se reduced p-PKB and p-GSK3 levels significantly, indicating that PI3K is active to a limited degree in these ARC neurones. Similar results were obtained for wortmannin (data not shown). However, surprisingly the PI3K inhibitors also reduced the leptin- and insulin-stimulated phosphorylation of MAPK  or insulin  for 1, 5, 15 and 30 minutes. Leptin and insulin stimulation induced comparable immunoblot profiles . Mean channel activity (Nf.Po), 1–2 minutes following cell attached formation was 0.08 ± 0.02 and increased to 0.38 ± 0.03 (n = 10, P < 0.01) after peak activation had occurred (10.6 ± 1.0 minutes after patch formation). In control cell-attached recordings of between 10–25 minutes, with 10 nM leptin in the pipette solution, there was no effect on K+ channel currents observed in other ARC neurones (n = 30). During peak KATP channel activation by leptin, bath application of the KATP channel inhibitor tolbutamide (200 μM), reduced mean channel activity by 56 ± 12% , an effect reversible on washout of drug . The sensitivity to tolbutamide, ATP and single channel characteristics are consistent with leptin activation of the large conductance KATP channel of GR neurones [ATP channel activity in 45% of unidentified neurones (n = 14/31). Nf.Po increased from 0.14 ± 0.03 under control conditions to 0.49 ± 0.08  after approximately 10 – 20 minutes exposure to insulin . Consequently, these data are in agreement with previous studies on rat ARC GR neurones [Cell-attached recordings from rat isolated ARC neurones were used to confirm that leptin and insulin activate the large conductance Kescribed ,7. Leptig Figure . Followig Figure  reversibneurones . In a sen Figure . InsulinATP channels in ARC neurones is rapid (<5–10 minutes) and the leptin increase in KATP activity demonstrated in isolated patches [ATP channel activity, application of the MAPK pathway inhibitor, PD98059  had no effect on Nf.Po  increased KATP mean Nf.Po from 0.21 ± 0.10 to 0.68 ± 0.28 (n = 3, P < 0.02), and subsequent bath application of 10 nM wortmannin reduced KATP activity to a mean value of 0.33 ± 0.13 (n = 3, P < 0.02) over a period of 15–20 minutes, an Nf.Po indistinguishable from control (P > 0.4). Similarly, in a separate series, leptin increased Nf.Po from 0.15 ± 0.04 to 0.35 ± 0.05 (n = 4, P < 0.05) and subsequent application of 10 μM LY294002 reduced Nf.Po to 0.19 ± 0.04 (n = 4, P < 0.01) within 15–20 minutes. Essentially identical data have been reported previously for the effects of these PI3K inhibitors on insulin-activated ARC KATP channel activity [As leptin and insulin activation of K patches , this aco Figure . A previnhibitor . Howeveractivity . Thus th3 may serve as an important second messenger for downstream effectors such as the KATP channel. The mechanism by which PtdIns(3,4,5)P3 recognises downstream target proteins is by binding to specialised phosphatidylinositol recognition sites, such as the pleckstrin homology (PH) domain [3 production is elevated in ARC neurones following exposure to leptin and insulin, we used the PH domain of GRP-1, which selectively binds PtdIns(3,4,5)P3 [3 [3 levels in ARC neurones, are only indicative of increased PI3K activity. Thus we examined IRS-2 associated PI3K activity [Such a central role for PI3K suggests that its main lipid product, PtdIns3,4,5)P) domain . Thus, t3,4,5)P3  coupled P) domain,5)P3 [3 ,22, dispactivity  in isola3 activates KATP channels in an insulin-secreting cell line when applied directly to the internal aspect of isolated patches [ATP is probably not due to direct binding of the lipid to channel subunits, as the effect of PtdIns(3,4,5)P3 on KATP was prevented by the presence of the actin stabilizing agent, phalloidin. Additionally, leptin-induced opening of this insulin-secreting cell KATP channel was occluded when phalloidin was present in the cell interior [ATP channels. As our assessment of hormone activation of GR neurone KATP channels uses cell-attached recordings, we used the membrane permeable actin stabilizing toxin, jasplakinolide to induce actin polymerization [ATP channels . Cell-attached recordings with leptin (10 nM) present in the pipette solution, increased mean KATP channel activity from 0.07 ± 0.02 to 0.44 ± 0.07 . Subsequent bath application of jasplakinolide (50 – 100 nM) reversed the leptin-induced KATP activation  and subsequent bath application of jasplakinolide (100 nM), in the continuous presence of insulin, reduced channel activity to 0.17 ± 0.06  within 5–10 minutes P patches . Howeverinterior . Thus werization . In preln Figure , with chs Figure . The inh3 levels in GT1-7 cells demonstrate that leptin increases PI3K activity concurrently with the re-organization of cortical actin in this cell line, with leptin stimulation inducing little change in the K273A mutant PH-GRP1-GFP binding to these cells  phosphorylation of MAPK (ERK1 & 2 subfamilies), STAT3 and the PI3K activity indicators, PKB and its downstream target GSK3. These hormone-induced increases in phosphorylation were transient in the majority of experiments, usually lasting 1–5 minutes at ~34°C with return to control levels of phosphorylation within 30 minutes. Such rapid recovery has also been noted in other studies [Previous studies have demonstrated that leptin applied activity ,29. Here studies ,30 and m studies ,31. The  studies  or lepti studies  on energ studies . in vivo application of insulin (icv) demonstrated no such change, unless leptin was co-applied. The data reported here indicate that insulin per se is capable of increasing STAT3 phosphorylation, as no exogenous leptin was present or endogenous leptin likely to remain in the ARC sections following the extensive washes and incubations prior to stimulation. This difference may be due to an increased signal to noise delivered using ARC tissue over whole hypothalamus and that rapid transient signals are more readily detectable by this method. Both leptin and insulin rapidly increased the phosphorylation of PKB and its downstream effector GSK3 in a wortmannin and LY294002 sensitive manner, indicative of increased PI3K activity in ARC neurones, in agreement with previous in vivo studies [As expected, exposure of ARC wedges to leptin induced an increase in tyrosine phosphorylated STAT3 ,13,29,34 studies ,35.However, our results did not demonstrate that either leptin or insulin induced a significant increase in IRS-2-associated PI3K activity measured directly in ARC tissue. This may be due to a low signal to noise ratio, as only a (unknown) proportion of cells would be expected to respond to the hormones in the ARC tissue block, and/or that hormone mediated increases in PI3K activity are limited to plasma membrane microdomains. This is supported by the very modest increase in PI3K activity detected in GT1-7 cells when stimulated by leptin. Although hypothalamic activation of PKB by insulin has been reported previously , these aInterestingly one pathway candidate for phosphorylating serine-727 is the Ras/Raf/MEK signalling cascade, and indeed a recent study has demonstrated that leptin can induce S727 phosphorylation of STAT3 in a PD98059 dependent manner in macrophages, and this is required to produce full stimulation of STAT3 . InsulinThe importance of STAT3 signalling to the central mechanisms that control energy homeostasis has recently been directly demonstrated by transgenic mouse studies. Using a 'knock-in' strategy to induce defective STAT3 binding to ObRb  or a 'kn+ conductance, of a subset of hypothalamic neurones, defined by their acute sensitivity to changes in external glucose concentration, termed GR neurones [+ channel, the sulphonylurea-sensitive large conductance KATP channel. This action is rapid and independent of transcriptional events, so most likely is mediated by MAPK or PI3K signalling. Pharmacological inhibition of the MAPK pathway with PD98059 did not reverse leptin (as shown above) or insulin [ATP activity, abrogating this pathway from causing the hyperpolarising response. In contrast, inhibition of PI3K with either wortmannin or LY294002, reversed both leptin (as shown above) and insulin [ATP activity. Furthermore, use of the fusion protein PH-GRP1-GFP as a specific detector of PtdIns(3,4,5)P3 in isolated neurones also demonstrated that both hormones rapidly increase the cellular content of this PI3K lipid product in a sub-population of neurones. These results are consistent with class 1 PI3K [ATP channels in GR neurones. The functional significance of PI3K in the control of energy balance has been demonstrated by in vivo studies, which show that leptin [Leptin and insulin cause inhibition, by hyperpolarization through activation of a sulphonylurea-sensitive Kneurones ,7,19. Sis 1 PI3K  acting at leptin  and insut leptin  stimulatt leptin .ATP activity in isolated ARC neurones was also reversed, within 5–10 minutes, by the marine sponge toxin, jasplakinolide. This toxin binds to F-actin with high affinity, resulting in its stabilization and prevention of depolymerization to its monomer G-actin [ATP activation to occur. Such a mechanism is supported by reports that agents, which promote actin depolymerization, activate KATP channels in cardiac myocytes [ATP channel activity was also shown to depend on actin filament depolymerization. Insulin is also well documented to cause actin filament re-organization in peripheral cells associated with various functional outputs, which depend on PI3K activity, including metabolic and mitogenic effects [ATP activity by jasplakinolide was faster (5–10 minutes) than for the PI3K inhibitors (15–20 minutes). This temporal difference suggests that the site of jasplakinolide action is downstream from the PI3K signal transduction pathway to KATP channels.Leptin and insulin stimulated K G-actin . These dmyocytes ,46 and tmyocytes . Further effects . The rev3 production, as determined by PH-GRP1-GFP binding, and actin filament depolymerization. Thus, leptin and insulin signalling in, at least some sub-groups of hypothalamic neurones maintains a close parallel with leptin signalling in insulin-secreting cells, where it has been reported that leptin increases KATP activity by a PI3K-dependent cortical actin re-arrangement [However, alteration of the cellular cortical actin structure is inferred through the use of natural agents like jasplakinolide. In order to verify directly that hormone-driven structural re-arrangements did occur we decided to use the hypothalamic cell line, GT1-7, as preliminary experiments using freshly isolated neurones did not produce reliable and reproducible data due to the presence of dead and dying cells showing as false positives for hormone induced actin depolymerization. Use of this cell line also obviated any problems with identification of ObRb containing neurones and neuronal subtypes in slices. RT-PCR analysis indicates that this cell line does express the main signalling form of the leptin receptor and analysis of PI3K activity shows functional coupling of this receptor to this signalling pathway. We have shown, by cell staining of fixed cells and, independently by analysis of cellular G- and F-actin concentration from live cells, that leptin disrupts cortical actin structure by disturbing the processes that maintain the equilibrium between F-actin and G-actin, in the direction of depolymerization to G-actin. This effect of leptin was completely inhibited by the presence of either jasplakinolide or the PI3K inhibitors. In addition, there is a good temporal and spatial association between PtdIns(3,4,5)Pangement .ATP channel activation in arcuate neurones indicates that both hormones activate the same signalling cascades, and can produce common outputs. The sensitivity of both KATP opening and the phosphorylation of certain intermediates to PI3K inhibition is significant as this enzyme has been previously demonstrated to play an important role in leptin and insulin mediated energy homeostasis control. Furthermore it is interesting that leptin and insulin induce rapid phosphorylation of MAPK and STAT3 as these data support the view that these hormones may influence genomic and membrane neuronal outputs by common mechanisms. The inhibition of leptin and insulin stimulation of KATP channel opening of arcuate neurones by jasplakinolide suggests a role for cytoskeletal dynamics in modulation of membrane events such as neuronal hyperpolarization. This hypothesis is further strengthened by the finding that leptin induces actin filament depolymerization in a mouse hypothalamic cell line, which is PI3K dependent, demonstrating that this cell line may be a useful model for further analysis of leptin signalling mechanisms in hypothalamic neurones.The effect of leptin and insulin on the phosphorylation status of various cellular signalling intermediates and on K2PO4, 26 NaHCO3, 1.2 CaCl2, 2.4 MgSO4, and 10 glucose, equilibrated with 95% O2, 5% CO2 to give a pH of 7.4. The tissue was maintained in ice-cold aCSF whilst horizontal 400 μm coronal brain slices were prepared using a Vibratome (Intracel, Royston, Herts. UK). Slices containing the ARC were incubated in aCSF at room temperature for 20 minutes, and then at 33–35°C for 1 hour. Hypothalamic wedges, predominantly containing the ARC were cut, and these were incubated in aCSF ± hormones and/or kinase inhibitors (10 mls) for the required time. The reaction was stopped by the addition of 2 ml of cold lysis buffer containing (in mM) 100 NaCl, 10 NaF, 25 Tris HCl, 10 NaPPi, 5 EGTA, 1 EDTA, 1 Na3VO4, 1 Benzamidine, 0.1 PMSF, 0.1% (v/v) mercaptoethanol, 1% Tritron X-100 (v/v) and 92 mg ml-1 sucrose. The tissue was homogenised on ice, the lysate sonicated for two 10 s periods and then centrifuged for 10 minutes at 12000 rpm at 4°C. The supernatant was retained and the pellet discarded. The protein content of the clarified lysate was determined by the method of Bradford [Male Sprague-Dawley rats (50–100 g) were killed by cervical dislocation in accordance with Schedule 1 of the UK Government Animals (Scientific Procedures) Act (1986). The brain was rapidly transferred to ice-cold aCSF solution, containing (in mM): 128 NaCl, 5 KCl, 1.2 NaHBradford . Protein32P]PtdIns(3)P were located using a phosphorimager (Fuji FLA 5000) and analyzed with AIDA software.Cell and tissue lysates were made as described. The immunoprecipitation and PI3K activity assay were carried out as previously described . Briefly-1 protease XIV (Sigma-Aldrich, Dorset, U.K) and incubated for 1 hour at room temperature. The aCSF was continuously gassed with 95% O2: 5% CO2 for the entire incubation period. Sections were removed and washed in 50 ml aCSF five times prior to re-suspension in 5 ml normal saline containing (in mM): 135 NaCl, 5 KCl, 1 MgCl2, 1 CaCl2, 10 HEPES, 3 glucose, pH 7.4. Sections were sequentially triturated with fire polished Pasteur pipettes with decreasing tip size. The cell suspension was evenly distributed onto concanavalin A (Sigma-Aldrich) pre-treated 35 mm diameter culture dishes. The culture dishes were left for 15–20 minutes allowing cell adhesion prior to use.Coronal slices containing the medial hypothalamus were obtained (as described above) and sections containing the ARC were removed. The sections were transferred to 5 ml aCSF containing 1 mg ml+ solution containing (in mM) 140 KCl, 1 MgCl2, 1 CaCl2, 10 HEPES, pH 7.2. This solution was used in order to allow easy identification of K+ currents in the cell-attached configuration [+ conditions with the intracellular aspect of the membrane exposed to a bathing solution containing (in mM): 140 KCl, 1 MgCl2, 2.7 CaCl2, EGTA 10 (free Ca2+ of 100 nM), HEPES 10, pH 7.2.Cell-attached single channel currents were recorded from single neurones at room temperature, using an Axopatch 200B amplifier (Axon Instruments, Foster City, CA USA). Patch pipettes were prepared from thick walled borosilicate glass and had open tip resistances of 8 – 15 MΩ when filled with high Kguration . All celf.Po) determined as described previously [f is the number of functional channels and Po is the open probability. Drug effects were measured by comparison of Nf.Po from individual patches in the presence and absence of the drug. Data for a given set of experiments were normalised and statistical significance determined by employing the Students t-test for unpaired data. Results are presented as mean ± SEM and the number of experiments denoted by 'n.'Data were recorded onto digital audio-tape using a Biologic DTR 1200 recorder and analysed off-line. Pre-recorded data were transferred via a Digidata 1200 interface into a PC, digitised at 10 kHz and measured using the PCLAMP6 software, Fetchan 6. The mean current (I) and single channel amplitude (i) were determined for recordings ranging in duration from 30 s to 120 s and channel activity 18, 4 μg RNA and 1 μl (200 U) M-MLV Reverse Transcriptase (Gibco), at 25°C for 5 minutes, 42°C for 60 minutes, 70°C for 15 minutes and stored at -20°C. After RT, a 2 μl aliquot of the reaction was added to 48 μl of PCR mix. The mix containing 1 × PCR buffer, 2.5 mM MgClact; ref ) and 5 u2. Cells were passaged every 3–4 days, plated on poly-L-lysine (Sigma) coated glass coverslips in 3.5 cm Petri dishes and used 1–2 days after plating. Cells were treated with 10 μM LY294002 or 10 nM wortmannin or 100 nM jasplakinolide  in normal saline for 10 minutes, prior to a challenge with 10 nM leptin , in the continuous presence of inhibitor, for 20 or 60 minutes before fixing. GT1-7 cells were fixed in 4% methanol-free formaldehyde in cytoskeletal buffer (10 mM MES, 3 mM MgCl2, 138 mM KCl, 2 mM EGTA, pH 6.1) with 0.32 M sucrose for 30 minutes [-1 Alexa 594-DNase I and 2 U ml-1 Alexa 488-phalloidin  for 90–120 minutes, rinsed in PBS, and mounted on coverslips. Cells were observed with a 63X oil objective and images acquired using a laser-scanning confocal microscope (Zeiss LSM 510), under identical conditions with randomly selected regions of each coverslip. For quantitative analysis of G- and F-actin cellular pools, we used a direct method to partition the actin pools from live cells [-1 phalloidin (to prevent filament dissociation). Cells were then washed with PBS, and the Triton-X-100 insoluble pool (F-actin) prepared by addition of 1 ml of PBS lysis buffer, containing 1% Triton-X-100, protease inhibitors, 2% SDS and 1 μg ml-1 phalloidin for 5 minutes prior to harvesting cells from dishes. For determination of total actin, cells were exposed to the second step only. Each cellular pool was passed through a 25 gauge needle and total protein concentration determined, before equal amounts of protein were loaded onto SDS-PAGE gels, and actin detected using an actin monoclonal antibody (Chemicon). Quantitative measurements of G- and F-actin in fixed cells were made using Velocity software (Improvision), where individual cell total fluorescence, normalized to cell area, was determined and background fluorescence subtracted. Average fluorescence intensity was calculated for 8 cells in each experiment, and expressed relative to control (non-drug exposed cells). Actin bands on gels were quantified by densitometry, where total density was determined with respect to constant area, background subtracted and average relative band density calculated.The mouse hypothalamic cell line GT1-7  was grow minutes . They weve cells . In brie-1) fusion protein for 1 hour at room temperature, and images acquired by confocal microscopy.Following stimulation with hormone for 10–20 minutes, acutely isolated neurones (room temperature) or GT1-7 cells (37°C) were fixed at room temperature with 2–4% paraformaldehyde for 15 and 30 mins, respectively. Cells were permeabilized by washing with 0.05% PBS-Tween 20 . Non-specific binding was minimised by blocking with 3% BSA for 1 hour at room temperature. Cells were subsequently washed with 0.05% PBS-T prior to incubation with wild type PH-GRP1-GFP or K273A mutant PH-GRP1-GFP P3, phosphatidylinositol 3,4,5-trisphosphate; STAT3, signal transducer and activator of transcription 3;ACSF, artificial cerebrospinal fluid; AgRP, agouti-related protein; ARC, arcuate nucleus; NPY, neuropeptide Y; POMC, proopiomelanocortin; KSM carried out the electrophysiology studies, participated in the western blot and protein overlay experiments. HL carried out the arcuate western blot experiments and PI3K activity measurements. KN carried out the actin imaging and actin quantitative analysis experiments. EA contributed to the actin imaging experiments, western blots and participated in the protein overlay experiments. LB performed all tissue culture and participated in the western blot experiments. AG made the fusion proteins and participated in the design of the overlay experiments. CS participated in the design and implementation of the western blot experiments. MA conceived of the study, participated in its design and co-ordination and drafted the manuscript. All authors read and approved the final manuscript.


The duplication of genes and their subsequent diversification has had a key role in evolution. A range of fates can befall a duplicated gene If necessity is the mother of invention, then its father is an inveterate tinkerer, with a large garage full of spare parts. Innovation (like homicide) requires motive and opportunity. Clearly, the predominant ‘motive’ during the evolution of a novel gene function is to gain a selective advantage. To understand why gene duplications represent the major ‘opportunities’ from which new genes evolve, we must first consider what constrains genic evolution.The vast majority of genes in every genome are selectively constrained, in that most nucleotide changes that alter the fitness of the organism are deleterious. How do we know this? Comparisons between genomes clearly demonstrate that coding sequences diverge at slower rates than non-coding regions, largely due to a deficit of mutations at positions where a base change would cause an amino-acid change. Gene duplication provides opportunities to explore this forbidden evolutionary space more widely by generating duplicates of a gene that can ‘wander’ more freely, on condition that between them they continue to supply the original function.Evolution by Gene Duplication, published more than 30 years ago  species. This is the first time that copy number changes among apes have been assayed for the vast majority of human genes, and we can expect that the biological consequences of the 140 human-specific copy number changes identified in this study will be heavily investigated over the coming years.Given the apparent importance of gene duplication for the evolution of new biological functions over all evolutionary timescales, it is of great interest to be able to comprehensively document the duplicative differences that exist between our own species and our closest relatives, the great apes. The study by The various mechanisms by which genes become duplicated are often classified on the basis of the size of duplication generated, and whether they involve an RNA intermediate .‘Retrotransposition’ describes the integration of reverse transcribed mature RNAs at random sites in a genome. The resultant duplicated genes (retrogenes) lack introns and have poly-A tails. Separated from their regulatory elements, these integrated sequences rarely give rise to expressed full-length coding sequences, although functional retrogenes have been identified in most genomes.Tandem duplication of a genomic segment  is one of the possible outcomes of ‘unequal crossing over’, which results from homologous recombination between paralogous sequences. These recombination events can also give rise to the deletion or inversion of intervening sequences. Recent evidence suggests that the explosion of segmental duplications in recent primate evolution has been caused in part by the rapid proliferation of Alu elements about 40 MYA. Alu elements are derived from the 7SL RNA gene and represent the most frequent dispersed repeat in the human genome, with the approximately 1 million copies of the 300-bp Alu element representing around 10% of the entire genome. The striking enrichment of Alu elements at the junctions between duplicated and single copy sequences implicates unequal crossing over between these repeats in the generation of segmental duplications .The observation of segmental duplication events with no evidence for homology-driven unequal crossing over suggests that segmental duplications can also arise through non-homologous mechanisms. A recent screen for spontaneous duplications in yeast suggests that replication-dependent chromosome breakages also play a significant role in generating tandem duplications, because duplication breakpoints are enriched at replication termination sites .Genome duplication events generate a duplicate for every gene in the genome, representing a huge opportunity for a step-change in organismal complexity. However, genome duplication presents significant problems for the faithful transmission of a genome from one generation to the next, and is consequently a rare event, at least in Metazoa. In principle, genome duplications should be easily identified through the coincident emergence within a phylogeny of many gene families. Unfortunately, this signal is complicated by subsequent piecemeal loss and gain of gene family members. Consequently, there is heated debate over possible ancient genome duplication events in early vertebrate evolution and more recently in teleost fish, both of which must have occurred hundreds of millions of years ago .So what are the relative contributions of these different mechanisms? Not all interspersed duplicate genes are generated by retrotransposition. The initially tandem arrangement of segmental duplications can be broken up by subsequent rearrangements. In keeping with this hypothesis, duplicated genes in a tandem arrangement typically represent more recent duplication events . Recent A duplicated gene newly arisen in a single genome must overcome substantial hurdles before it can be observed in evolutionary comparisons. First, it must become fixed in the population, and second, it must be preserved over time. Population genetics tells us that for new alleles, fixation is a rare event, even for new mutations that confer an immediate selective advantage. Nevertheless, it has been estimated that one in a hundred genes is duplicated and fixed every million years , althougDespite the slackened selective constraints, mutations can still destroy the incipient functionality of a duplicated gene: for example, by introducing a premature stop codon or a mutation that destroys the structure of a major protein domain. These degenerative mutations result in the creation of a pseudogene . Over time, the likelihood of such a mutation being introduced increases. Recent studies suggest that there is a relatively narrow time window for evolutionary exploration before degradation becomes the most likely outcome, typically of the order of 4 million years .ECP gene in Old World Monkeys and hominoids after a burst of amino-acid changes following the tandem duplication of the progenitor gene EDN (a ribonuclease) some 30 MYA . This can be revealed by an accelerated rate of amino-acid change after duplication in one of the gene copies. This burst of selection is necessarily episodic—once a new function is attained by one of the duplicates, selective constraints on this gene are reasserted. These patterns of selection can be observed in real data: most recently duplicated gene pairs in the human genome have diverged at different rates from their ancestral amino-acid sequence . A convie 30 MYA . The divRather than one gene duplicate retaining the original function, while the other either degrades or evolves a new function, the original functions of the single-copy gene may be partitioned between the duplicates . Many genes perform a multiplicity of subtly distinct functions, and selective pressures have resulted in a compromise between optimal sequences for each role. Partitioning these functions between the duplicates may increase the fitness of the organism by removing the conflict between two or more functions. This outcome has become associated with a population genetic model known as the Duplication–Degeneration–Complementation (DDC) model, which focuses attention on the regulatory changes after duplication . In thisCDYL gene to Y chromosome (forming CDY). In the mouse, both Cdyl genes produce two distinct transcripts, one of which is expressed ubiquitously while the other is testis-specific. By contrast, in humans both CDYL genes produce a single ubiquitously expressed transcript, and CDY exhibits testis-specific expression. As CDY is a retrogene (see above) that has not been duplicated together with its ancestral regulatory sequences, it is clear that the DDC model is not the only route by which to achieve spatial partitioning of ancestral expression patterns.A recent study by Dorus and colleagues  investig2 binding affinity of haemoglobin is optimised for each developmental stage. This coupling between coding and regulatory change is similarly noted at a genomic level when expression differences between many duplicated genes pairs are correlated with their coding sequence divergence . Extensive functional studies targeted at duplicated genes are required if we are to more fully understand the range of evolutionary outcomes. Moreover, collaborations between the proteomics and evolutionary genetics communities would facilitate investigation of the potential role of gene duplication during the evolution of the protein–protein and cell–cell interactions that are fundamental to the biology of multicellular organisms.


The FTI tipifarnib (ZARNESTRA™, R115777) has recently demonstrated clinical responses in adults with refractory and relapsed acute leukemias. This study was conducted to identify genetic markers and pathways that are regulated by tipifarnib in acute myeloid leukemia (AML).Farnesyl protein transferase inhibitors (FTIs) were originally developed to inhibit oncogenic Tipifarnib-mediated gene expression changes in 3 AML cell lines and bone marrow samples from two patients with AML were analyzed on a cDNA microarray containing approximately 7000 human genes. Pathways associated with these expression changes were identified using the Ingenuity Pathway Analysis tool.The expression analysis identified a common set of genes that were regulated by tipifarnib in three leukemic cell lines and in leukemic blast cells isolated from two patients who had been treated with tipifarnib. Association of modulated genes with biological functional groups identified several pathways affected by tipifarnib including cell signaling, cytoskeletal organization, immunity, and apoptosis. Gene expression changes were verified in a subset of genes using real time RT-PCR. Additionally, regulation of apoptotic genes was found to correlate with increased Annexin V staining in the THP-1 cell line but not in the HL-60 cell line.The genetic networks derived from these studies illuminate some of the biological pathways affected by FTI treatment while providing a proof of principle for identifying candidate genes that might be used as surrogate biomarkers of drug activity. The investigative agent tipifarnib is a member of a new class of drugs that were designed to function as a non-peptidomimetic competitive farnesyltransferase inhibitor (FTI). The principal behind this drug class is that protein farnesylation is required for many cell-signaling processes and that dysregulation of cell signaling is thought to be instrumental in driving cell proliferation in several malignancies. The hypothesis that gave rise to this exciting class of drugs is that the inhibition of this enzyme would reduce the uncontrolled cell signaling and provide some control over cell division and malignant cell proliferation.in vitro and in vivo [In hematological cancers, tipifarnib has shown significant inhibition of the proliferation of a variety of human tumor cell lines both  in vivo -3. A rec in vivo . Further in vivo ,6, multi in vivo , and chr in vivo .Mechanism of action (MOA) and biomarker studies with tipifarnib have focused on the oncogenic Ras protein. However, it has since been shown that inhibition of Ras farnesylation does not account for all of the compound's actions. For example, FTIs do not require the presence of mutant Ras protein to produce anti-tumor effects . SeveralWhere there are multiple candidate pharmacologic biomarkers as is the case with tipifarnib, a comprehensive, parallel study of all candidates is required. Here we describe the application of DNA microarray technology to the measurement of the steady-state mRNA level of thousands of genes simultaneously. This comprehensive experimental approach allows for the simultaneous analysis of candidate biomarkers as well as the generation of novel hypothesis on MOA and previously uncharacterized biomarkers. Biomarkers that enable the monitoring of drug response have the potential to facilitate clinical evaluation of the compound's safety and efficacy in humans. In the present paper we describe the use of global gene expression monitoring to identify genes and gene pathways that are modulated in acute myeloid leukemia (AML) following treatment with tipifarnib. Several genes involved in FTI biology were identified as being modulated following treatment with tipifarnib in addition to pathways involved with cytoskeletal organization, cell signaling, immunity, and apoptosis. This genome-wide approach of gene expression analysis has provided insight into genes that can be used as surrogate biomarkers for FTI drug activity as well as identifying putative pathways that are involved in the drug's anti-leukemic mechanism of action. This is the first successful report of the application of genomics to this novel class of drugs.50 was defined as the dose at which the number of viable cells in the treated sample was 50% of that in the control. This was determined after 7 days of drug treatment. Cytotoxicity assays were performed in duplicate. Control cultures were grown in medium containing vehicle (0.1% DMSO) only. Cells were analyzed for apoptosis by treating with vehicle or tipifarnib (100 nM and 1 μM) over a 5-day time course. Cells were stained with Annexin V and propidium iodide daily according to the manufacturers protocol (Roche Applied Science, Indianapolis, IN) and analyzed by FACS.The AML cell lines AML-193, HL-60, THP-1, and U-937 were obtained from the American Type Culture Collection (Manassas, VA). Cells were grown in RPMI supplemented with 20% FBS. AML-193 was also supplemented with GM-CSF , insulin , and transferrin . Cell numbers were counted in a hemocytometer and cell viability was determined by trypan blue dye exclusion assay. Tipifarnib was dissolved in 0.1% DMSO. The ICBone marrow samples were collected from consenting patients both before and during treatment with tipifarnib , dilutedras, K-ras, and H-ras codons was determined by PCR and RFLP analysis as previously described [Analysis of activating mutations in N-escribed .th percentile of the expression levels was equal across micro-arrays. To control for chip errors, replicate clones on each chip that displayed a coefficient of variance (CV) greater than 50% of the mean were excluded from the analysis. Since background intensity was a maximum of 30 relative fluorescent units (RFU) for all experiments, a threshold of 30 RFU was assigned to all clones exhibiting an expression level lower than this. The microarray data were then normalized by quantile normalization and logarithmically transformed before further analysis.Total RNA was isolated using the Qiagen RNeasy kit  and treated with DNase1  to remove any residual genomic DNA. Probe preparation was performed as previously described . Linear Analysis of variance (ANOVA) and t-tests were used to investigate the effect of drug treatment and time and their interactions for each gene. Multiple hypotheses testing was controlled by applying the false discovery rate (FDR) algorithm . All staA total of 1198 genes that had a false discovery rate (FDR) < 0.1 (p < 0.05) in at least one cell line were used for the pathway analysis. Gene refseq accession numbers were imported into the Ingenuity Pathway Analysis software (Ingenuity Systems). 898 of these genes were mapped to the Ingenuity database. Seventy-two of these genes were also affected in patient samples (p < 0.05, FDR < 0.3) and were, therefore considered to be significantly regulated by tipifarnib. The identified genes were mapped to genetic networks available in the Ingenuity database and were then ranked by score. The score is the probability that a collection of genes equal to or greater than the number in a network could be achieved by chance alone. A score of 3 indicates that there is a 1/1000 chance that the focus genes are in a network due to random chance. Therefore, scores of 3 or higher have a 99.9% confidence of not being generated by random chance alone. This score was used as the cut-off for identifying gene networks significantly affected by tipifarnib.The genes and primers used for RT-PCR are listed in Table 50 of these cell lines when treated with tipifarnib ranged from 19 to 134 nM  tool. Seventy-nine (72 unique) of these 180 genes mapped to genetic networks as defined by the IPA tool. These networks describe functional relationships between gene products based on known interactions in the literature. The tool then associates these networks with known biological pathways. Five networks were found to be highly significant in that they had more of the identified genes present than would be expected by chance Table . These nThe 79 genes were then analyzed by two-way hierarchical clustering to compare the expression profiles of the AML samples Fig . A numbeWhile the cell lines portrayed higher heterogeneity in expression changes compared with the patient samples, the hierarchical clustering did reveal a common set of up- and down-regulated genes. A set of 23 genes was found to be down-regulated in the cell line and patient samples Fig. . The majDue to the stringency of our gene selection process it is likely that many genes that are indeed regulated by FTIs, were not identified. For instance, as noted above, of the targets known to be affected by FTIs we identified only k-ras at the transcriptional level. However, the use of pathway analysis tools allows for the identification of networks of genes that are known to interact with each other. This procedure therefore provides additional confidence in the selected genes as well as clues to other genes that may also be regulated but not identified as being significant by the microarray analysis. For example, the network of up-regulated genes Fig  includesSince a number of apoptotic genes were identified as being affected by tipifarnib we performed experiments in THP-1 and HL-60 cell lines to verify if they were indeed undergoing apoptosis. Previous reports have shown that two other FTIs can induce apoptosis in myeloid leukemia cell lines  and thatras oncogene it has been recently demonstrated that there is no correlation between patient response and ras mutational status [Tipifarnib is one of three FTIs that are currently in clinical trials for treating a variety of cancers  and it il status . Additiol status , are dirl status . We are MR, RTB, DA, and YW are employees of Veridex LLC., a Johnson and Johnson company. JEK and JEL have received fees from Johnson & Johnson Pharmaceutical Research and Development in the last 5 years.MR wrote the manuscript and performed experiments. RTB performed Ras analysis. DA helped conceive the experiments. JEK and JEL were principal investigators in the clinical trials from which samples were received. YW helped conceive the experiments. All authors read and approved the final manuscript.AML: acute myeloid leukemia; FDR: false discovery rate; FTI: farnesyltransferase inhibitor; MDS: myelodysplastic syndrome; MOA: mechanism of action; MM: multiple myeloma; CML: chronic myeloid leukemiaThe pre-publication history for this paper can be accessed here:A. Two-way hierarchical clustering of 1198 genes regulated in three AML cell lines after tipifarnib treatment. A fold-change ratio was calculated using the treated sample and its matched untreated sample. B. Gene expression changes in patient AML cells. Two-way hierarchical clustering of 1016 genes regulated in two AML patients over a three-week time course.Click here for fileA list of 141 genes with known function that were regulated in both the cell line and patient data sets.Click here for file


The genomes of an increasing number of species are being investigated through generation of expressed sequence tags (ESTs). However, ESTs are prone to sequencing errors and typically define incomplete transcripts, making downstream annotation difficult. Annotation would be greatly improved with robust polypeptide translations. Many current solutions for EST translation require a large number of full-length gene sequences for training purposes, a resource that is not available for the majority of EST projects.As part of our ongoing EST programs investigating these "neglected" genomes, we have developed a polypeptide prediction pipeline, prot4EST. It incorporates freely available software to produce final translations that are more accurate than those derived from any single method. We show that this integrated approach goes a long way to overcoming the deficit in training data..prot4EST provides a portable EST translation solution and can be usefully applied to >95% of EST projects to improve downstream annotation. It is freely available from  Complete genome sequencing is a major investment and is unlikely to be applied to the vast majority of organisms, whatever their importance in terms of evolution, health or ecology. Complete genome sequences are available for only a few eukaryote genomes, most of which are model organisms. The focus of eukaryote genome sequencing has been on a restricted subset of known diversity, with, for example, nearly half of the completed or draft stage genomes being from vertebrates. While Arthropoda and Nematoda have two completed genomes each, with a dozen others in progress, compared to predicted diversity (over a million species each) current genome sequencing illuminates only small parts of even these phyla. The disparity between sequence data and motivation for biological study is significant. Allied to this bias in genome sequence is a bias in functional annotation for the derived proteomes: a vertebrate gene is more likely to have been assigned a function due to the focus of biomedical research on humans and closely related model species such as mouse .Shotgun sample sequencing of additional genomes through expressed sequence tags (EST) or genome survey sequences (GSS) has proved to be a cost-effective and rapid method of identifying a significant proportion of the genes of a target organism. Thus many genome initiatives on non-traditional model organisms have utilised EST and GSS strategies to gain an insight into "wild" biology. An EST strategy does not yield sequence for all of the expressed genes of an organism, because some genes may not be expressed under the conditions sampled, and others may be expressed at very low levels and missed through the random sampling that underlies the strategy. However the creation of EST libraries from a range of conditions, such as different developmental stages or environmental exposures, promotes a closer examination of the biology of these species.The well documented phylogenetic sequence deficit  has led The PartiGene software suite  simplifiPrediction of the correct polypeptide from ESTs is not trivial:1. The inherent low quality of EST sequences may result in shifts in the reading frame (missing or inserted bases) or ambiguous bases. These errors impede the correct recognition of coding regions. The initiation site may be lost, or an erroneous stop codon introduced to the putative translation.de novo programs which use the initiation methionine to identify the coding region (described below).2. ESTs are often partial segments of a mRNA, and as most cloning technology biases representation to the internal parts of genes, the initiation methionine codon may be missed. This is a problem for some of the Sequence quality can be improved by clustering the sequences based on identity. For each cluster a consensus can be determined . This apCaenorhabditis elegans proteome shows that only ~50% of the 22000 predictions contain Pfam-annotated protein domains [A robust method to determine the correct encoded polypeptide is to map a nucleotide sequence onto a known protein. This concept is the basis for BLASTX , FASTX  and Prot domains ,13, and  domains . This feProtEST uses a slightly different similarity-based approach . A protede novo approaches based on recognition of potential coding regions within poor quality sequences, reconstruction of the coding regions in their correct frame, and discrimination between ESTs with coding potential and those derived from non-coding regions have been developed [To overcome the reliance upon sequence similarity, eveloped -18.DIANA-EST , combineEach of these methods has different strengths in their attempt to identify the precise coding region; all require prior data to train their models. Published descriptions of their utility are based on training with human full length coding sequences (mRNAs), and thus tens of thousands of training sequences (many million coding nucleotides) were used to achieve optimum results. As stressed above, this amount of prior data is not available for the vast majority of EST project species Figure .Prior to this project, nematode ESTs available through NEMBASE  had beenThe DECODER program  was deveHidden Markov models (HMM) can represent known sequence composition in a probabilistic manner . This ha1. Modeling mRNA structure: ESTScan separates the probable CDS from the untranslated regions (UTRs). The core of the coding sequence is represented by a 3-periodic inhomogeneous hidden Markov model. Flanking this core model are start and stop profiles for the codons observed at these positions. The profiles for untranslated regions flank the start and stop states.2. Error tolerance: ESTScan allows insertions and deletions (indels) in the EST sequence. For example, if it is more probable that a particular nucleotide is the result of an insertion event then it is omitted from the 'corrected' sequence. Conversely, if the HMM probability scores suggest that a nucleotide has been deleted then the model inserts an X into the 'corrected' sequence to denote this prediction.3. EST structure: ESTScan recognises that the EST may be composed of a combination of 5' UTR, CDS and 3' UTR.ESTScan's hidden Markov models are trained using complete CDS entries from either the EMBL or RefSeq databases. Scripts included with the distribution parse the data files, extracting the necessary sequence information to produce the model files. The major issue considered at this point is redundancy. If the training data is internally redundant then the resultant model will be fully successful only in finding what is known and will have reduced power in detecting novel transcripts. Default parameters were used in ESTScan for building the HMM and in predicting polypeptides.The BLASTX program  allows aprot4EST is an integrated pipeline utilising freely available software in a tiered, rule-based system Figure .The protein databases contain (probably spurious) translations of ribosomal RNA genes and gene fragments, and thus it is important to identify and remove putative rRNA derived sequences before further processing. A BLASTN search is performed against a database of rRNA sequences obtained from the Ribosomal Database II , took less than an hour for a 2316-sequence input with an Athlon 1400 Mhz processor. The BLASTX searches were carried out separately and used as input to prot4EST (for details see the userguide, availabile from the program web page).We benchmarked five translation methods to test their relative performance. DECODER is designed to consider only the forward strand of the nucleotide sequence, as it was originally designed for full-length CDSs. When applied to ESTs it is imperative that both strands are analysed, as both 5' and 3' ESTs are generated. Therefore the reverse complement of each nucleotide consensus was also analysed. DECODER_default (1) considers only the prediction from the forward strand, whilst DECODER_best (2) uses the more accurate prediction. ESTScan (3) considers both strands of the nucleotide sequence, and was run as a stand-alone process with default settings.Two arrangements of components within prot4EST were tested. prot4EST_ed (4) implements ESTScan before using DECODER on any remaining untranslated sequences. Conversely, prot4EST_de (5) uses DECODER first followed by ESTScan. The DECODER module in prot4EST considers translations on both the foward and reverse strands of the query sequence.Caenorhabditis elegans ESTs from dbEST [C. elegans cDNA dataset available from Wormbase (version 117) [C. elegans protein dataset (Wormpep version 117), thus associating each nucleotide sequence with a corresponding reference polypeptide. A final test set of 2316 consensus sequences was produced.We randomly selected 4000 om dbEST . To reduom dbEST . phrap [om dbEST  was thenion 117) . SignifiC. elegans RefSeq collection was obtained, comprising 21033 entries . A Perl script was written to extract the CDS entries and construct a RefSeq-style resource for each prokaryote species (available upon request). If a taxon's genome consisted of more than one megaplasmid the sequences were combined. CDS annotation was not available for 11 genomes. We used the CDS collections for the 156 taxa to determine AT content, construct hidden Markov models and codon usage tables.A. thaliana were obtained from the RefSeq database [28960 complete CDS entries for database .We queried GenBank for all complete CDS entries from species in the nematode order Spirurida.SwissProt (release 42.7) and TrEMBL (release 25.7)  were comC. elegans test dataset to its cognate reference protein using bl2seq from the NCBI distribution. Default parameters were used except for the theoretical database size (-d), set to 130000, the size of SwissProt. The blast reports were parsed using BioPerl modules [C. elegans reference protein sequence was also compared to itself using bl2seq with default parameters. The raw and bit scores were recorded.We compared each putative polypeptide predicted from the  modules . Each C.The raw and bit scores were normalised for length and against their theoretical maximum using equation 1, where:BITlocal is the bit score of the local alignment between the predicted polypeptide and its cognate reference protein,BITmax is the bit score for the alignment between the reference protein and its self,WPlength is the length of the wormpep protein that is the reference of the nucleotide consensus translated,ESTlength is the length of the nucleotide consensus that has been translated.(equation 1)coverage is the percentage of the predicted polypeptide that aligns with the reference. The bit score represents the total of the alignment's pair-wise scores, normalised with respect to the substitution matrix used to calculate these scores. In this study the bit score was itself normalised to compensate for EST length and the maximum possible bit score for each comparison (see Methods, equation 1). The number of consensuses translated that had a significant match to their cognate reference C. elegans protein was also recorded for each run.To measure the accuracy of translation two statistics were derived from the comparison of the predicted and reference polypeptides. The Both variants of DECODER were unable to produce robust translations for over half the nucleotide sequences no matter how many nucleotides were in the training set Figure . As expeC. elegans transcriptome. In a genuine situation, when only a small number of full-length CDS exist in the public databases, a significant number will be from highly expressed genes with atypical codon bias and structure. This bias will be evident in real-world CDS sets with fewer than 200 members (150000–200000 coding nucleotides).The effect of the number of training nucleotides on ESTScan performance is pronounced. For the majority of the replicates, at each training set size the fraction of predictions that have significant matches to their reference sequence was around 75%, but the number of translations dropped significantly below 250000 training nucleotides. However, for 10000 coding nucleotides or less no robust translations are produced. Additionally, there was variance in the performance of ESTScan when there were between 20000 and 50000 training nucleotides. Examination of these training sets showed no difference in AT content compared to larger training sets, but did suggest that fluctuations in codon usage bias might be involved. The replicates that performed less well comprised sequences with shorter mean length, and had codon biases that were at the extremes of the distribution (not shown). This variation in sequence composition clearly has an effect on the probabilities that populate the HMM used by ESTScan. We suspect that the ability of ESTScan to predict robust translations when trained by datasets of 150000 to 200000 coding nucleotides is inflated as a consequence of the random selection of the training set from the complete When the training sets contained a large number of non-redundant coding nucleotides (> 150000), prot4EST_ed and ESTScan performed equally well Figure . When thThe translations produced by prot4EST_ed were the most robust across all totals of coding nucleotides, for both coverage and bit score Figures  & 3c. Asprot4EST_ed produced more robust translations for higher numbers of training sequences. However when smaller totals of training nucleotides were used the translations produced by the alternative architecture, prot4EST_de, were slightly better Figure , althougThe better performance of prot4EST_ed was examined by following the fate of individual test sequences through the prot4EST pipeline. By employing ESTScan before DECODER, larger training sets allowed the deployment of well trained HMMs .de novo translation methods need to be trained to as high a level as possible. The question is how this should be done, given the paucity of prior sequence data for individual species. Should CDS from species considered phylogenetically related be combined or should a large set from a model organism be used? A recent study of gene finding in novel genomes has shown a significant effect of sequence composition upon gene structure prediction, with more closely related model genomes providing poor training if the codon bias differs significantly from the genome of interest [Streptomyces coelicolor) to 78% (Wigglesworthia glossinidia), independent of any bias due the organisms' relatedness to C. elegans. The lowest number of non-redundant coding nucleotides was 461,299, in excess of the minimum number suggested for robust training. To explore datasets from more closely related sources all available CDS entries for the nematode order Spirurida , and ththaliana  were obtC. elegans proteins (r = 0.49 P > 0.001) . We note that some prokaryote training sets with AT contents close to C. elegans performed poorly: homogeneity of AT content is thus not a panacea. The best performance was obtained using the A. thaliana training set, with significantly better coverage than achieved with the more closely related Spirurida. As the plant dataset contained 130 times as many coding nucleotides as did the Spirurida training set, four random A. thaliana training sets of comparable size to the Spirurida were built. These smaller training sets still performed better than the Spirurida training set, though not as well as the full CDS collection.There was a significant correlation between AT content of the training set and the coverage by the putative polypeptides of their reference ) Figure . The mosde novo methods. Given the increase in protein sequences submitted to SwissProt/TrEMBL, prot4EST's ability and accuracy can only increase over time. These more accurate translations provide the platform for more rigorous down-stream annotation. Currently we are using the prot4EST pipeline to translate ~95000 nematode consensus sequences from 30 species. These translations will then be passed onto other tools we are developing for EST analysis and annotation (see ).prot4EST is a protein translation pipeline that utilises the advantages of a number of publicly available tools. We have shown that it produces significantly more robust translations than single methods for species with little or no prior sequence data. Around three quarters of current EST projects are associated with training sets of < 50000 coding nucleotides Figure . Thus prProject name: prot4ESTProject home page: Operating system(s): Fully tested on Linux – Redhat9.0, Fedora2.0.Programming language: PerlOther requirements:ESTScan2.0 DECODER rgscerg@gsc.riken.go.jpBioPerl 1.4 Transeq License: GNU GPLAny restrictions to use by non-academics: None for prot4EST source code. DECODER requires a license. See User Guide.JW performed all the analyses and wrote all the Perl code. MB oversaw the project and suggested additional features.Both authors shared responsibility for writing this manuscript.


The predictive role of many cytokines has not been well defined in Acute Respiratory Distress Syndrome (ARDS).We measured prospectively IL-4, IL-6, IL-6 receptor, IL-8, and IL-10, in the serum and bronchoalveolar lavage fluid (BALF) in 59 patients who were admitted to ICU in order to identify predictive factors for the course and outcome of ARDS. The patients were divided into three groups: those fulfilling the criteria for ARDS (n = 20, group A), those at risk for ARDS and developed ARDS within 48 hours (n = 12, group B), and those at risk for ARDS but never developed ARDS (n = 27, group C).An excellent negative predictive value for ARDS development was found for IL-6 in BALF and serum (100% and 95%, respectively). IL-8 in BALF and IL-8 and IL-10 serum levels were higher in non-survivors in all studied groups, and were associated with a high negative predictive value. A significant correlation was found between IL-8 and APACHE score (r = 0.60, p < 0.0001). Similarly, IL-6 and IL-6r were highly correlated with PaO2/FiO2 (r = -0.27, p < 0.05 and r = -0.55, p < 0.0001, respectively).BALF and serum levels of the studied cytokines on admission may provide valuable information for ARDS development in patients at risk, and outcome in patients either in ARDS or in at risk for ARDS. Acute respiratory distress syndrome (ARDS) is characterized by respiratory failure of acute onset as a result of acute lung injury (ALI) either directly or indirectly via the blood. The main characteristics of the syndrome are diffuse inflammation and increased microvascular permeability that cause diffuses interstitial and alveolar oedema and persistent refractory hypoxemia . AlthougCytokines are produced in the lung by local resident cells such as alveolar macrophages, lung epithelial cells, and fibroblasts or by cells such as neutrophils, lymphocytes, monocytes and platelets as a response to local or systemic injury -12. CytoInflammatory cytokines are of critical importance in the pathophysiology of septic shock, a condition frequently leading to ARDS . It has Predictive levels of inflammatory cytokines (IL-1, IL-2, IL-6, IL-8) for ARDS development in at risk patients have been reported with controversial results ,11,15,16The purpose of this study is to evaluate the role of inflammatory cytokines IL-4, IL-6, IL-6r, IL-8, and IL-10 in serum and bronchoalveolar lavage (BALF) as possible prognostic indicators for the development, severity, and outcome of patients with ARDS or at risk for ARDS.We studied prospectively 59 consecutive patients who were admitted in our Intensive Care Units (ICU) Table . The fir2/FiO2 ratio of ≤ 300 torr for ALI and ≤ 200 torr for ARDS. 2. The high-risk criteria for ARDS development according to Fowler et al [For patients' classification, the following criteria were employed: 1. The ARDS criteria of the American-European Consensus Conference on ARDS (1): a. acute onset, b. bilateral chest radiographic infiltrates, c. pulmonary artery occlusion pressure of ≤18 mm Hg, or no evidence of left atrial hypertension, and d. impaired oxygenation regardless of the PEEP concentration, with a PaOer et al . Acute PThe main clinical features of the patients are shown in Table 2/FiO2 values were obtained at the time of sample collection. The blood was collected in a heparinized vacutainer tube and kept immediately at 4°C. After centrifugation at 1500 g at 4°C, the plasma was kept at -80°C until the measurement. Immediately after blood collection BALF was obtained by fiberoptic bronchoscopy. The fluid was filtered through nylon net to remove the mucous secretions, and centrifuged at 500 g for 10 min to remove cells. The supernatant was kept in cryotubes at -80°C in aliquots of 0.5 ml. The method of micro-lavage was used as described previously [After admission to the ICU blood samples were obtained from a central venous line within 2 hours. APACHE II score and PaOeviously . The foleviously . To checThe assay method for cytokine measurement was the same for blood and BALF samples. Determination of plasma cytokines was done with solid phase enzyme-linked immunosorbent assay (ELISA) methodology based on the quantitative immunometric sandwich enzyme immunoassay technique . ReagentData analysis was carried out using SPSS 8.0 statistical software (SPSS Inc., Chicago, IL). Results are expressed as mean ± 1SD, or median (range), unless otherwise indicated. The Mann-Whitney non-parametric test was used to compare the mean values of the cytokines in the blood and BALF in the various groups. Receiver-operating characteristic (ROC) correlation was used to find the optimal cut-off values of the studied cytokines for ARDS development in patient at risk and survival of the patient population . For tesThere was no significant difference in the mean age of the patients among the three studied groups. Using APACHE-II score to determine the severity of the disease, significant difference between group A and group C (p = 0.04) and group B and C (p = 0.045) was found, and not between groups A and B (p = 0.06). The mean time of staying in the ICU did not differ among the three groups.The mean values (+/- SD) of the measured cytokines in BALF and serum in the three studied patient groups are shown in Table Serum levels of IL-4 were higher in group A compared to groups B and C (p < 0.0001). Serum IL-6 was higher in group B compared to group A and C (p < 0.05). Serum levels of IL-8 was higher in group A and group B compared to group C (p < 0.0001) Table . PredictMean (SEM) values in BALF and serum of the studied mediators in the survivors and non-survivors (groups A+B+C) are shown in Table Patients with ARDS (group A) who did not survive had significantly higher BALF levels of IL-8 (p < 0.0001) and significantly lower BALF levels of IL-10 (p < 0.001) Table . PatientCytokine concentration cut off predictive values for surviving patients are shown in Table In survivors BALF/serum ratios were significantly higher for IL-4, IL-8, IL-10 (p < 0.0001, p < 0.001 and p < 0.0001, respectively), due to lower serum levels and not to higher BALF levels.Furthermore, the serum levels of all studied mediators were significantly correlated to APACHE II score. Serum IL-8 exhibited the strongest correlation with APACHE II score Figure . The lev2/FiO2 ratio was significantly correlated to the BALF levels of IL-6 and IL-6r  , while no difference was observed in serum levels among the three groups of patients. Interestingly, the BALF and serum levels of cytokine IL-6 were significantly higher in patients at risk who developed ARDS (group B) compared to the other two groups. This observation differs from previous studies ,25, probPatients of group A and group B had higher serum levels of the inflammatory cytokine IL-8 compared to the patients of group C, but neither serum nor BALF IL-8 levels were predictive for ARDS development. In two studies, Miller et al,  found thHowever, in other studies increased levels of IL-4, and IL-10 in serum and/or BALF were found to have beneficial effect in pre-ARDS patients ,14. ThusPatients who died had significantly higher levels of IL-6, IL-6r and IL-8 in BALF than those who finally survived, while all mediators studied were significantly higher in the serum of non-survivors. The rationale for analysis of cytokine concentrations in BAL fluid is that inflammatory cytokines, like IL-6 and IL-8 are known to be produced by airway epithelial cells and activated pulmonary macrophages in response to a variety of infectious agents and other triggers of airway inflammation . During Regarding the relation of the studied molecules and the severity of lung injury, a negative correlation was found between BALF IL-6, and IL-6r and PaO2/FiO2. The same was true for serum IL-4 and PaO2/FiO2. All the studied molecules in the serum were positively correlated with the APACHE II score, as was BALF IL-8. It is probable that this cytokine is closely related to the extension of tissue damage and organ failure.In conclusion, our data show that the predictive role of most of the studied molecules both in serum and BALF for ARDS development is valuable. In addition, almost all of them are good predictors of outcome in these patients. Further studies with greater number of patients with various subgroups of ARDS as well as stricter grouping criteria should be designed to investigate the complex network of these molecules and their receptors in ARDS and their value as predictive factors in these patients.None declared.DB conceived of the study, and participated in its design and coordination and drafted the manuscriptMGA participated in the design of the study, carried out immunoassays and drafted the manuscriptKMA carried out immunoassays and drafted the manuscriptPA patients data and samples collectionIP patients data and samples collectionSA patients data and samples collectionGP Performed statistical analysisAP patients data and samples collectionNK carried out RIA measurementsDP KMA carried out immunoassays and drafted the manuscriptAll authors read and approved the final manuscriptThe pre-publication history for this paper can be accessed here: