The completion of the human genome sequence has made possible genome-wide studies of retroviral DNA integration. Here we report an analysis of 3,127 integration site sequences from human cells. We compared retroviral vectors derived from human immunodeficiency virus (HIV), avian sarcoma-leukosis virus (ASLV), and murine leukemia virus (MLV). Effects of gene activity on integration targeting were assessed by transcriptional profiling of infected cells. Integration by HIV vectors, analyzed in two primary cell types and several cell lines, strongly favored active genes. An analysis of the effects of tissue-specific transcription showed that it resulted in tissue-specific integration targeting by HIV, though the effect was quantitatively modest. Chromosomal regions rich in expressed genes were favored for HIV integration, but these regions were found to be interleaved with unfavorable regions at CpG islands. MLV vectors showed a strong bias in favor of integration near transcription start sites, as reported previously. ASLV vectors showed only a weak preference for active genes and no preference for transcription start regions. Thus, each of the three retroviruses studied showed unique integration site preferences, suggesting that virus-specific binding of integration complexes to chromatin features likely guides site selection. Retroviruses have potential for gene therapy only if they do not activate endogenous genes. Of three tested retroviral vectors, ASLV showed no preference for integration into human transcription start regions Retroviral replication requires reverse transcription of the viral RNA genome and integration of the resulting DNA copy into a chromosome of the host cell. A topic of long standing interest has been the chromosomal and nuclear features dictating the location of integration target sites  and IMR90 lung fibroblasts. Several previously described datasets were also subjected to further analysis in parallel—HIV integration sites in three transformed cell lines . Analysis using the different catalogs of human genes suggests that somewhat different fractions of the human genome are transcribed, and new information indicates that an unexpectedly large fraction of the human genome may be transcribed into noncoding RNAs . Howeverp = 1.4 × 10−14). No such bias was seen for ASLV (p > 0.05). For the HIV datasets, two of the four sets showed modest bias . For HIV, the observed statistical significance was sensitive to the details of analytical approach used and is of questionable biological importance. Thus, ASLV and HIV do not strongly favor integration at transcription start sites as was seen with MLV.We next assessed the placement of integration sites within genes and intergenic regions. A previous study revealed that integration by MLV is favored near transcription start sites, but no such bias was seen for HIV . We inveTranscriptional profiling analysis was carried out in some of the cell types studied, allowing the influence of transcriptional activity on integration site selection to be assessed. Transcriptional profiling was carried out on infected cells so that the data reflected the known influence of infection on cellular gene activity . Prior tThe median expression level  of genes hosting integration events was consistently higher than the median of all genes assayed on the microarrays. The ratios  for HIV ranged from 1.6 to 3.0, indicating that integration targeting in human primary cells (PBMC and IMR90) favored active genes, as shown previously for transformed cell lines . For MLVAll three HIV datasets showed reduced integration in the most highly expressed category of genes analyzed, suggesting that although transcription favors integration, very high level transcription may actually be less favorable . A fourtp < 0.05 using the Chi-square test for linear trend in proportions). We note, however, that the differences were quantitatively modest, perhaps because much of the cellular program of gene activity is shared among many cell types , to allow us to control for the effects of infection on transcription. Pairwise comparisons of the microarray datasets for the three cell types showed that the correlation coefficients ranged only from 0.64 to 0.79, indicating that transcriptional activity indeed differed among cell types. We reasoned that since active transcription favors integration, then the genes targeted by integration should on average be more highly expressed in the cell type that hosted the integration event than in either of the other two. Statistical analysis  showed tll types .We next analyzed factors influencing the placement of integration sites at the chromosomal level, taking into account both gene density and expression see . Transcrp = 1.8 × 10−12 to 3.2 × 10−38, depending on the dataset; MLV, p = 2.4 × 10−22; ASLV, p = 3.2 × 10−9) and a stronger association with transcriptional intensity . Overall, ASLV showed the weakest association with gene density and transcriptional intensity.Statistical analysis was carried out comparing integration frequencies to (1) gene density or (2) transcriptional intensity, as measured by the EST counts. All analyses incorporated a comparison to the matched random control set of integration sites. Each type of vector showed a significant positive correlation with gene density , and the model based on the above parameters predicted the placement of ASLV integration sites least well. Thus ASLV is least responsive to the effects of the parameters so far known to affect integration site selection in human cells.A statistical model was constructed to examine the relative contributions to integration intensity of (1) gene density, (2) gene activity, (3) proximity to CpG islands, (4) G/C content, and (5) location within genes (p < 2.22 × 10−16). Evidently there are factors—so far unknown—affecting integration targeting that operate at the level of whole chromosomes, and for HIV these were interspersed with unfavorable regions near CpG islands. CpG islands are thought to be regulatory regions that bind distinctive sets of transcription factors. Thus, a simple model to explain targeting is that a distinctive set of sequence-specific DNA-binding proteins bound at or near CpG islands disfavor HIV integration, while proteins bound in active transcription units are favorable. For MLV, the proteins bound at CpG islands instead favor integration.For ASLV, it is possible that the viral integration machinery does not interact with factors bound in or near genes, explaining the more random distribution of integration sites in the genome. Such a pattern might have evolved to minimize disruption to the host cell chromosomes due to integration. Another possibility, however, is that ASLV does have stricter target site preferences during normal integration in chicken cells, but the targeting system does not function properly in the human cells studied here. According to this idea, putative chicken chromosomal proteins normally bind ASLV integration complexes and direct integration, but the homologous human proteins may be too different to interact properly. It should be possible to investigate this possibility by characterizing ASLV integration in chicken cells, now that the draft chicken genome sequence is completed .One consequence of the above findings is that integration will differ from tissue to tissue as a consequence of cell-type-specific transcription. To assess effects of tissue-specific transcription, we analyzed HIV integration in three different cell types . Transcriptional profiling data showed that transcription was significantly different among the three. This allowed an analysis of integration targeting, which showed that highly expressed genes particular to each tissue were favored for integration in that tissue. However, the magnitude of the tissue-specific biases on integration were modest, probably because most of the cellular transcriptional program appears to be common among cell types .Additional mechanisms could also contribute to targeting. For example, we and others have detected statistically significant biases in integration frequency in whole chromosomes that do not appear to be fully explained by gene density or gene activity .Our data indicate that ASLV has integration site preferences that may make it attractive as a vector for human gene therapy. MLV-based vectors have the unfavorable preference for integration near transcription start sites . The advHincII adaptor, GTAATACGACTCACTATAGGGCACGCGTGGTCGACGGCCCGGGCTGC, adapter for use with DNA cleaved by 6-cutter restriction enzymes, top strand; mNheIAvrIISpeII adaptor, P-CTAGGCAGCCCG-NH2, adapter for 6-cutter restriction enzymes, bottom strand; ASB-9, GACTCACTATAGGGCACGCGT, adapter primer for PCR for I/SupT1, PBMC, and IMR-90; SB-76, GAGGGATCTCTAGTTACCAGAGTCACA, HIV primer for PCR for I/SupT1; ASB-19, GAGATTTTCCACACTGACTAAAAGGGTC, HIV primer for PCR for I/PBMC and IMR-90; ASB-16, GTCGACGGCCCGGGCTGCCTA, adapter primer for nested PCR for I/SupT1, PBMC, and IMR-90; ASB-1, AGCCAGAGAGCTCCCAGGCTCAGATC, HIV primer for nested PCR for I/SupT1; ASB-20, CTGAGGGATCTCTAGTTACCAGAGTCA, HIV primer for nested PCR forPBMC and IMR-90; MseI linker +, GTAATACGACTCACTATAGGGCTCCGCTTAAGGGAC, MseI linker, top strand; MseI linker −, P-TAGTCCCTTAAGCGGAG-NH2, MseI linker, bottom strand; MseI linker primer, GTAATACGACTCACTATAGGGC, MseI linker primer for first round of PCR; MseI linker nested primer, AGGGCTCCGCTTAAGGGAC, MseI linker nested primer for second round of PCR; BB389, GATGGCCGGACCGTTGATTC, inner ASLV LTR primer for second round of “nested” PCR; BB390, CGATACAATAAACGCCATTTGACCATTC, outer ASLV LTR primer for first round of PCR.Each oligonucleotide is described by its name, sequence (written 5′ to 3′), and use, in that order. VSV-G (pMD.G)  , the sec (pMD.G) . Forty-e7 PHA, IL-2 prestimulated PBMCs, or IMR-90 cells (passage #36) at 30%–50% confluency (1–2 × 106 cells) were infected with the HIV-based vector at an moi of 10 (60 ng p24 per 5 × 10 5 cells). The vector was added to the cells with DEAE-dextran at a final concentration of 5 μg/ml. Forty-eight hours after infection, the cells were pelleted. For RNA isolation, cells were resuspended in 250 μl of PBS and 750 μl of TRIzol and frozen in liquid nitrogen. To determine the extent of infection, cells were analyzed by flow cytometry. For ASLV, supernatant containing RCASBP(A)GFP particles was added to 293T-TVA cells  at 30%–50% confluency. Forty-eight hours post infection, green fluorescence was seen in approximately 30% of the cells, as determined by examination of the cultures with a fluorescence microscope. DNA was harvested at this point . RNA from infected cells was also isolated at 48 h post infection (TRIzol) and stored at −80 °C until used for transcriptional profiling analysis. RNA was isolated from infected cell cultures, and samples from each were used for hybridization on one Affymetrix  microarray.PBMCs were separated from human blood using a ficoll gradient . 1 × 10HIV integration sites were cloned by ligation-mediated PCR essentially as described in Transcriptional profiling was carried out using Affymetrix microarrays as described in A detailed description of the statistical methods used is presented in Protocols Protocol S1(322 KB PDF).Click here for additional data file.Protocol S2(128 KB PDF).Click here for additional data file.http://www.ncbi.nlm.nih.gov/) accession numbers for the novel integration site sequences discussed in this paper are CL528318–CL529767. The GenBank GEO dataset numbers for the novel transcriptional profiling datasets reported here are GSE1407, GSE1408, GSE1409, and GSE1410.The GenBank (


Burkholderia cepacia complex [BCC] or Pseudomonas aerugionsa [PA] in comparison to those who are not infected with either of these organisms [NI].Patients with cystic fibrosis [CF] have frequent pulmonary exacerbations associated with the isolation of bacterial organisms from sputum samples. It is not clear however, if there are differences in the types of additional organisms isolated from patients who are infected with Adult patients attending the regional CF unit were followed over a two year period and patients were assigned to three groups depending on whether they were known to be chronically infected with BCC, PA or NI. We compared the numbers and types of organisms which were isolated in each of these groups.Information was available on a total of 79 patients; BCC 23, PA 30 and NI 26. Total numbers of organisms isolated, expressed as median and IQR for each group, [P = 0.045] and numbers of co-infecting organisms [P = 0.003] were significantly higher in the BCC group compared to PA, and in the PA group  compared to NI patients. The pattern of co-infecting organisms was similar in all three groups.Total numbers of organisms isolated and numbers of co-infecting organisms were significantly higher in the BCC group compared to PA, and in the PA group compared to NI patients. Types of co-infecting organisms are similar in all groups of patients. P. aeruginosa [PA] [B. cepacia complex [BCC] have a worse prognosis and often a more rapid decline in lung function with increased mortality  -6. It isortality . Previouathogens ,8.This study examines the bacterial organisms cultured from an adult CF population, subdividing them into three groups; BCC, PA and those who were not infected with either of these organisms [NI] and to correlate with several clinical parameters. We hypothesized that those patients with BCC have more co-infection with other bacteria and this contributes to the greater morbidity in these patients.Data were collected on all patients [>18 years old] attending the regional adult CF unit at the Belfast City Hospital for two consecutive years. Sputum specimens were obtained for each patient at regular clinic attendances [patients were reviewed at 3 monthly intervals] as well as twice during hospital admissions. BCC was cultured from sputum employing selective agar . All isolates were grouped into cultural phenotypes displaying similar visual characteristics and one colony from each phenotype identified by API. Sputum samples were well taken samples following physiotherapy.P. aeruginosa, S. aureus, H. influenza, S. pneumonia, S. maltophilia and all other organisms including fungi. The facility to detect respiratory viral infection was not available at the time of this study.Sputum culture results were retrieved from the Bacteriology database for all samples submitted over the study time period. Patients were then divided into three groups using the following criteria; BCC if there was ever any sputum culture positive for these organisms. PA, if this bacterium was identified on two or more occasions over a twelve month period, and NI for all other patients who were not chronically infected with either of these organisms. It was noted as to whether the positive culture consisted of one organism or if there were additional organisms identified. In the BCC and PA groups, when more than one organism was identified from a sputum culture the additional organism [s] where recorded as 'co-infecting', as where all organisms in cultures of two or more infecting organisms in the NI group. Co-infecting organisms were divided into groups; Spirometry  and oxygen saturation measurements were noted at the start and end of the study as well as the best measurement for each year. Weight was recorded at the beginning and end of the two year period. Other measurements included; smoking history, use of prophylactic and number of courses of intravenous antibiotics and a history of diabetes mellitus.Statistical analyses were performed using the SPSS version 11 package. The Chi-square test was used to analyse differences in the sex, smoking status and incidence of diabetes mellitus between groups. The Kruskal-Wallis and Mann Whitney test were used to compare antibiotic use and organisms isolated across groups. Lung Function and Oxygen saturation means were compared by one-way analysis of variance followed by the Student-Newman-Keuls method. A probability (P) value of less than 0.05 was considered statistically significant.Burkholderia multivorans, 21 Burkholderia cenocepacia, all ET -12], PA 30 and NI 26. Those patients in the BCC group had a mean duration of infection of 67 months. There was no difference in the sex distribution between the groups, P = 0.18. There were a total of 10 [12.7%] patients with diabetes, but they had no relationship with the groupings [P = 0.19]. There were significantly more smokers in the BCC group [P = 0.005] in comparison to PA and NI. Prophylactic antibiotic use was similar throughout all groups, P = 0.14. Intravenous antibiotic use was similar in the BCC and PA patient groups but significantly higher compared to NI [P < 0.001], table Information was available on a total of 79 patients, mean [Standard Deviation] age 26 [7.9] years. Numbers in each group were as follows; BCC 23 .Median and interquartile ranges of organism numbers [total numbers and numbers of co-infecting organisms] and specimen numbers in each group are shown in table This study identified individuals with BCC and PA more frequently require courses of IV antibiotic therapy in comparison to CF adults in whom neither pathogen was identified [NI]. This is in keeping with previous findings in which patients colonized with BCC ,10 and PThe BCC group were also noted to have significant weight loss over the study period, again this has been shown to act as an independent predictor of survival in this group . No signOn comparison of PA and BCC patients to those in the NI group, investigators have previously demonstrated higher morbidity ,12. In tIt is well documented that CF patients experience a more rapid decline in their lung function . HoweverInvestigators have shown evidence of this type of risk taking behaviour in these patients, however it is actually lower when compared than their peer group . This emPatients with BCC and PA infection have a similar use of antibiotics. Total numbers of organisms isolated and numbers of co-infecting organisms are significantly higher in the BCC group compared to PA, and in the PA group compared to NI patients. Types of co-infecting organisms are similar in all groups of patients.BCC Burkholderia cepacia complexCF Cystic fibrosis1 Forced expiratory volume in one secondFEVNI 'Neither Isolated' groupNo. NumberP ProbabilityPA Pseudomonas aeruginosa2 Oxygen SaturationSAOSD Standard DeviationSE Standard ErrorSPSS Statistical Package for the Social SciencesSPECIAL CHARACTERS:< Less thanα AlphaThe authors' declare that they have no competing interests.Collected data relating to the study and drafted the paper.Participated in the analysis of clinical specimens and contributed to the manuscript content.Participated in the study design and coordination.Conceived of the study and participated in its design and coordination.All authors read and approved the final manuscript


Exposure to CCl4 also induces acute and chronic renal injuries. The present study was designed to establish the protective effect of hesperidin (HDN), a citrus bioflavonoid, on CCl4-induced oxidative stress and resultant dysfunction of rat liver and kidney.CCl4 (2 ml/kg/s.c.) in olive oil. Rats were sacrificed by carotid bleeding under ether anesthesia. Liver enzymes, urea and creatinine were estimated in serum. Oxidative stress in liver and kidney tissue was estimated using Thiobarbituric acid reactive substances (TBARS), glutathione (GSH) content, superoxide dismutase(SOD), and Catalase (CAT)Animals were pretreated with HDN  for one week and then challenged with CCl4 caused a marked rise in serum levels of ALT and AST (P < 0.05). TBARS levels were significantly increased whereas GSH, SOD and CAT levels decreased in the liver and kidney homogenates of CCl4 treated rats. HDN (200 mg/kg) successfully attenuated these effects of CCl4CCl4 induced oxidative stress in rat liver and kidney. This protective effect of HDN can be correlated to its direct antioxidant effect.In conclusion, our study demonstrated a protective effect of HDN in CCl Lipid peroxidation initiated by free radicals is considered to be deleterious for cell membranes and has been implicated in a number of pathological situations. Carbontetrachloride  and AST (control = 135 IU/L) demonstrating a marked liver damage. Treatment with HDN decreases the elevated levels of ALT and AST in serum (P < 0.05).CCl4 challenge caused a marked lipid peroxidation in both liver (control = 1.5 micromoles/mg protein) and kidney (control = 33.86 nmoles/mg protein). Both the doses of HDN decreased the level of lipid peroxidation in liver, but in the kidney, no effect on lipid peroxidation was seen with 100-mg/kg dose, and only the higher dose of HDN (200 mg/kg) could attenuate the increased level of lipid peroxidation (P < 0.05)  and kidneys (control = 27.99 micromoles/mg protein) demonstrating oxidative stress. HDN (200 mg/kg) per se did not produce any change in the levels of reduced glutathione either in liver or kidney. HDN (100 mg/kg) showed no effect on the levels of reduced glutathione either in liver or kidney in CCl4 treated rats whereas HDN (200 mg/kg) significantly ameliorated CCl4-induced depletion of GSH in both liver and kidney (P < 0.05) and kidneys . HDN per se (200 mg/kg) had no effect on these enzymes either in liver or in kidneys. HDN (100 mg/kg) failed to improve the levels of SOD or catalase either in liver or kidneys of CCl4 administered rats but HDN (200 mg/kg) significantly increased the levels of both enzymes in liver and kidneys of CCl4 treated rats (P < 0.05) was able to show improvement in the levels of endogenous antioxidant enzymes  and GSH in liver. Improvement of hepatic GSH levels in HDN-treated rats in comparison to CCl4 intoxicated rats demonstrates the antioxidant effect of HDN.Protective effects of various natural products in CClreported . Studies in rats . In the 4 on renal function. Neither BUN nor serum creatinine levels increased after CCl4 administration (data not shown). Studies by Zimmerman et al [4 in nephrectomized rats. They found an increased frequency of glomerulosclerosis and tubulointerstitial alterations in rats with reduced renal mass on CCl4 administration thereby indicating nephrotoxicity on long-term CCl4 administration in rats. These findings raise the possibility that renal disease in man is related to hydrocarbon solvent exposure and may also be potentiated by concomitant renal disease or impaired renal function. Ogawa et al [4 intoxication. On the contrary, we estimated the renal function just after 48 hrs of CCl4 challenge. Thus this brief period might not be sufficient to demonstrate any rise in serum BUN and creatinine levels. Though renal function did not alter after 48 hrs of CCl4 administration but even this short period of exposure led to a significant oxidative stress in kidneys. Fadhel and coworkers [4 exposure which could be improved by black tea extract. Similar observations were also reported with certain Indian ayurvedic Indian preparations [We failed to observe any effect of CClan et al  also didwa et al  also repoworkers  had alsoarations .HDN treatment has been previously demonstrated to improve GSH levels in liver and kidneys of diabetic rats and a decrease in levels of 8-hydroxydeoxyguanosine (8-OHdG), a marker of DNA fragmentation, in the urine of diabetic rats . HDN in 4 induces a marked oxidative stress in rat liver and kidney, which is amenable to attenuation by HDN. This protective effect of HDN can be correlated directly to its antioxidant property.In conclusion, our study demonstrated that CClMale wistar rats (150 g–200 g), bred in the central animal house of Panjab University  were used. The animals were housed under standard conditions of light and dark cycle with free access to food  and water. The experimental protocols were approved by the Institutional Ethical Committee of Panjab University, Chandigarh.Chemicals employed in these studies were reagent grade. Carbon tetrachloride  was administered subcutaneously in olive oil Hesperidin  was suspended in 0.5% sodium carboxy methyl cellulose (CMC) and administered orally.Control: These animals received a vehicle for HDN (i.e. CMC) by oral route for eight days and on 8th day, they were administered the subcutaneous injection of olive oil. 4 groupCCl: These animals received vehicle for 10 days and were challenged with CCl4 2 ml/kg/s.c. (40% v/v in olive oil) on 8th day. In the preliminary studies done in our lab, we observed a very high mortality rate (50–60%) when CCl4 was administered interaperitoneally. Thus we adopted the subcutaneous route of CCl4 administration as reported in the literature [4, the mortality rate reduced to about 20% HDN group: These rats received only HDN 200 mg/kg/p.o. daily for 10 days CCl4+ HDN (100): Rats received HDN continuously for 8 days. On eight day just after HDN treatment they received CCl4 2 ml/kg/s.c in olive oil. HDN was further continued for 2 more days. CCl4+ HDN (200): This group is similar to the above one except that the dose of HDN administered was 200 mg/kg/p.o. On the 10th day, animals were sacrificed 2 hr, after the last dose of HDN and blood was collected, by carotid bleeding, in centrifuge tubes. Serum was separated and was used freshly for the assessment of renal and liver function tests. Both the kidneys and the liver were quickly harvested and immediately stored at -20°C till further biochemical estimations.Animals were divided into following groups, each containing 6–8 animals: terature . With thBefore sacrifice, rats were kept individually in metabolic cages for 24 h to collect urine for estimation of renal function. Serum samples were assayed for blood urea nitrogen (BUN), urea clearance, serum creatinine & creatinine clearance by using standard diagnostic kits .Serum alanine aminotransferase (ALT) and serum aspartate aminotransferase (AST) were estimated by International Federation of Clinical Chemistry   and homogenized in chilled potassium chloride (1.17%) using a homogenizer. The homogenates were centrifuged at 800 g for 5 minutes at 4°C to separate the nuclear debris. The supernatant so obtained was centrifuged at 10,500 g for 20 minutes at 4°C to get the post mitochondrial supernatant which was used to assay catalase and superoxide dismutase (SOD) activity.5 M-1/cm-1 and expressed as nmol of TBARS per mg protein. Tissue protein was estimated using Biuret method of protein assay and the TBARS content expressed as nanomoles per milligram of protein.The malondialdehyde (MDA) content, a measure of lipid peroxidation, was assayed in the form of thiobarbituric acid reacting substances (TBARS) by method of Okhawa et al.  Briefly,Reduced glutathione (GSH) in the kidneys and liver was assayed by the method of Jollow et al . BrieflySOD activity was assayed by the method of Kono et al. The assa-1.Catalase activity was assayed by the method of Claiborne et al . BrieflyResults were expressed as mean ± SEM. The intergroup variation was measured by one way analysis of variance (ANOVA) followed by Fischer's LSD test. Statistical significance was considered at p < 0.05. The statistical analysis was done using the Jandel Sigma Stat Statistical Software version 2.0.Naveen Tirkey, Sangeeta Pilkhwal and Anurag did all the biochemical estimations in kidney and liver. Kanwaljit Chopra did the data interpretation after statistical analysis and contributed in manuscript preparation.


The importance of β-chemokines (or CC chemokine ligands – CCL) in the development of inflammatory lesions in the central nervous system of patients with multiple sclerosis and rodents with experimental allergic encephalomyelitis is strongly supported by descriptive studies and experimental models. Our recent genetic scans in families identified haplotypes in the genes of CCL2, CCL3 and CCL11-CCL8-CCL13 which showed association with multiple sclerosis. Complementing the genetic associations, we also detected a distinct regional expression regulation for CCL2, CCL7 and CCL8 in correlation with chronic inflammation in multiple sclerosis brains. These observations are in consensus with previous studies, and add new data to support the involvement of CCL2, CCL7, CCL8 and CCL3 in the development of inflammatory demyelination. Along with our own data, here we review the literature implicating CCLs and their receptors (CCRs) in multiple sclerosis and experimental allergic encephalomyelitis. The survey reflects that the field is in a rapid expansion, and highlights some of the pathways which might be suitable to pharmaceutical interventions. Multiple sclerosis (MS) is a disabling disease of the central nervous system (CNS) with features of autoimmunity and neurodegeneration. Although the identity of primary antigenic determinant(s) is uncertain, an interaction between β-chemokine ligands and their receptors plays a central role in the recruitment and retention of inflammatory cells in the CNS. Thus, both the disease relevant chemokine ligands and their receptors represent potential therapeutic targets in MS.Chemokines are a group of small, structurally related chemoattractant molecules that regulate cell trafficking through interactions with a set of receptors . Evidenc3C  chemokine families have one or three intervening amino acids, respectively, between the two cysteines. In the XC family (SCYC or lymphotactin), only one cysteine is present ) into inflammatory lesions of MS.A meta-analysis of raw genotype data from three genome scans in MS families revealed the highest nonparametric linkage (NPL) score = 2.58 at 17q11 [eae6 and eae7 were identified. While these loci control the severity and duration of EAE, eae7 is also a susceptibility locus for the monophasic remitting / non-relapsing subtype of the disease [Scya1 (TCA-3 or CCL1), Scya2 (MCP-1 or CCL2) and Scya12 (MCP-5 or CCL12) in eae7 showed striking segregations among mouse strains resistant or susceptible to EAE.Within the orthologous mouse chromosome 11, two quantitative trait loci (QTL),  disease . Sequenceae18 and identified two adjacent QTLs, eae18a and eae18b, on the rat chromosome 10 in a myelin-oligodendrocyte glycoprotein (MOG)-induced, chronic relapsing EAE. The eae18b locus is also orthologous to human chromosome 17q11 and encodes a cluster of β-chemokine genes.Using an advanced intercross line in combination with congenic strains, Jagodic et al.  fine mapThe recognition of β-chemokine genes as susceptibility and quantitative trait loci in mouse and rat EAE along with the human data revealing the β-chemokine gene cluster as a susceptibility locus in MS, strongly suggest the involvement of β-chemokine variants in the development of inflammatory demyelination.EAE is a valuable model for studying the effector arm of immune response in inflammatory demyelination. It can be induced in susceptible strains of inbred and outbred species by active immunization with myelin related proteins and their peptides  emulsified in Freund's complete adjuvant along with intravenous Pertussis toxin, or with a passive transfer of myelin antigen specific T cell lines into naïve recipients. Using various immunization protocols, acute and chronic relapsing (CR-EAE) models have been developed. In both the active immunization and the passive transfer models of EAE, the efferent arm of immune response involves the migration of monocytes / macrophages, dendritic cells and activated myelin-antigen-specific T lymphocytes from the blood circulation into the CNS, where a reactivation of specific lymphocytes by myelin-antigen-presenting dendritic cells, macrophages and residential microglia takes place, and the sequential development of perivascular and parenchymal inflammation is followed by demyelination and neuronal degeneration.Encephalitogenic T lymphocytes have CD4+ TH1 phenotype characterized by the production of interleukin (IL)-2 and interferon-γ. TH2 lymphocytes producing IL4, IL5, IL6 and IL10 cytokines are involved in the counter-regulation of TH1 effects, and promote clinical recovery. The TH1 / TH2 polarization is regulated by cytokines and chemokines. The transmigration of immune competent cells via the blood-brain barrier is aided by a temporal and spatial regulation of adhesion molecules on T lymphocytes and their counterparts on endothelial cells, and of chemokine ligands and their receptors in the residential CNS and hematogenous mononuclear cells.One of the most comprehensively studied CC chemokines in inflammatory demyelination is MCP-1 (CCL2). MCP-1 (CCL2) influences both innate immunity through its chemoattractant effect on monocytes / macrophages, and adaptive immunity through its effect on T cell polarization towards the TH2 subtype . CCL2 prMIP proteins have both chemotactic and proinflammatory effects, but also promote homeostasis . The MIPOur understanding concerning the role of these CC chemokines and their receptors in inflammatory demyelination was greatly advanced by studies in the EAE model. In mice, the increased expression of MCP-1 (CCL2) by CNS immune cells is closely associated with the clinical activity of EAE -14. SomeJee et al  comparedin vivo immune response to these CCL molecules differentially influenced the evolution of EAE. MIP-1α (CCL3) and MCP-1 (CCL2) DNA vaccines prevented EAE, while MIP-1β (CCL4) aggravated the disease and RANTES (CCL5) did not have an effect on the course of EAE. This study emphasizes the importance of CCL2 and CCL3 in the development of active EAE in rats.Youseff et al  observedeae7 encoding CCL1 and other chemokines as a susceptibility locus and QTL in murine EAE. SNPs in CCL1 differentially segregated in mouse strains susceptible or resistant to EAE. mRNA molecules for both CCL1 and its receptor CCR8 were detected in spinal cord lesions of EAE, in correlation with the expression of tumor necrosis factor (TNF)-α by inflammatory leukocytes [CCL1 also attracted attention in EAE. Teutscher et al  identifiukocytes -19. As bin situ hybridization and immunohistochemistry on brain and spinal cord sections of mice with EAE. Constitutive expression of the lymphoid chemokine called EBV-induced molecule 1 ligand chemokine (ELC) / CCL19 in a subpopulation of CNS venules and induced expression of the secondary lymphoid chemokine (SLC) / CCL21 in inflamed CNS venules was detected. CCR7, the common receptor for these two chemokines was expressed on a subpopulation of cells in the perivascular cuffs. Encephalitogenic T cells in vitro showed expression of CCR7 and CXCR3, the alternative receptor for CCL21, and chemotaxed towards both CCL19 and CCL21 in a concentration-dependent and a Pertussis toxin-sensitive manner similar to naïve T cells. Functional deletion of CCR7 and CXCR3 or immune blockade of CCL19 and CCL21 reduced the binding of encephalitogenic T cells to inflamed venules in frozen brain sections. Altogether, these data suggest that CCL19 and CCL21 are expressed in cerebral endothelial cells and are involved in α4-integrin mediated adhesion strengthening of autoreactive T cells and subsequently of other inflammatory cells to the endothelial layer of the BBB. These molecular interactions may lead to permanent inflammatory cell immigration into the CNS in chronic autoimmune disease.Recent studies addressed the role of chemokines at the blood-brain barrier. Using intravital fluorescence videomicroscopy, Vajkoczy et al  demonstrCCL20 or MIP-3α (exodus-3 / LARC) is a chemokine active on dendritic cells and lymphocytes that express CCR6 . SerafinIn vitro activation of microglia resulted in secretion of bioactive MDC / CCL22 that induced chemotaxis of TH2 lymphocytes. This study concludes that MDC / CCL22 produced by microglia may play a role in a TH1 mediated CNS inflammation by inducing the homing of TH2 regulatory cells into the lesion site.CCL22 or macrophage-derived chemokine (MDC) is chemoattractant for monocytes, dendritic and NK cells, and T lymphocytes of the TH2 subtype. MDC / CCL22 acts via CCR4 which is preferentially detected on TH2 type, memory and regulatory T cells [in vitro reactivated T cells. Normal resting CD4+ T cells and primed non-activated T cells expressed mRNA for CCR1, CCR2, CCR3, CCR5, CCR6, CCR7 and CCR8. In vitro activated T cells expressed in higher amounts most of the CCRs found in normal T cells as well as CCR4. After passive transfer of encephalitogenic activated T cells in naïve recipients, the donor derived encephalitogenic cells and the host-derived CD4+ T cells isolated only from the CNS lesions but not from spleen expressed mRNA for CCR1. This latter observation was confirmed at protein level, and appeared to be specific for acute EAE. Neutralization of the CCR1 ligand CCL3 (MIP-1α) diminished the inflammatory infiltrate in the CNS.To further clarify the role of chemokine receptors involved in EAE, Fife et al  examinedThe effects of anti-chemokine treatments in the mouse EAE is summarized by Elhofy et al  and Karplck  or MBP promoters (which directs the expression of transgene to the CNS), a spontaneous infiltration of monocytes / macrophages in the thymus and CNS was observed, respectively [Genetic manipulations of the murine model provide further insights in the characterization of CCL / CCR molecules in EAE. In mice with the CCL2 transgene under the control of the ectively . LPS injectively  examinedThe CCL2 knock out (-/-) mice showed resistance to EAE and significantly decreased macrophage infiltration in the CNS following active immunization with MOG35–55 peptide. While T cells from CCL2 (-/-) mice transferred EAE to wild type mice, wild type T cells did not induce EAE in CCL2 (-/-) recipient mice. These observations suggest a key role for CCL2 in the recruitment of macrophages into the CNS and thus, in the pathogenesis of EAE ,30,4. ThThe clinical phenotype of CCR2 (-/-) genotype was similar to that of the CCL2 (-/-) genotype, characterized by a reduced macrophage infiltration in the spinal cord and a decreased susceptibility to actively (MOG35–55) induced acute EAE in the studies by Fife et al  and IzikFurther studies demonstrated an approximately 50% reduction of clinical EAE activity in the CCR1 (-/-) mice, likely involving the altered migration of monocytes and lymphocytes . In contIn sum, CCL and CCR data from rodent EAE models using inbred, transgenic and knockout strains along with data from chemokine-specific antibody treatments or CCL DNA immunization in EAE suggest that concentration gradients of CCL2 and CCL3 decreasing from the CNS to the peripheral circulation are involved in the spatially and temporally regulated recruitment of mononuclear cells into the CNS which correlates with the course of clinical disease. CCL2 may play a more significant role during relapses than during the induction phase of the disease. CCL5 is expressed by mononuclear cells in the perivascular space during the recovery phase of an acute event, and may therefore be involved in the regulation of recovery rather than in the initiation of the disease. In addition, CCL19 and CCL21 are expressed by endothelial cells of the BBB, and are involved in the strengthening of leukocyte adhesion to inflamed venules followed by homing of encephalitogenic T lymphocytes to the CNS. CCL20 can control the recruitment of dendritic cells into lesions, whereas CCL22 may be involved in a TH2 mediated regulatory process during EAE. CCL1 is likely playing an important role in the autocrine regulation of activation of macrophages and microglia in EAE lesions. Thus, the functional involvement of CCL chemokines during EAE is not only restricted to a well orchestrated recruitment of dendritic cells, monocytes, macrophages, T effector and regulatory cells into the CNS, but also includes a temporal and spatial regulation of TH1  or TH2  polarization, and monocyte, macrophage and microglial activation . Their receptors, the CCRs play equally important roles in these processes. Experimental evidence now suggests that CCR1, CCR2, CCR3, CCR4, CCR5, CCR6, CCR7, CCR8 and CXCR3 on hematogenous mononuclear cells recognize these chemoattractant and regulatory molecules to induce cell differentiation, adhesion or migration of distinct inflammatory cells in peripheral lymphoid organs, at the BBB and in the CNS during the course of EAE. Even taking into consideration the complex and promiscuous nature of the CCL – CCR network, certain pathways may be associated with distinct biological function amenable to intervention. Targeting CCR molecules either by monoclonal antibodies or by small functional antagonists has become a novel and realistic strategy in the treatment and prevention of autoimmune diseases.The complexity of disease pathogenesis, difficulties accessing the site of pathology and the descriptive nature of studies explain why the available CCL / CCR data are less comprehensive in MS as compared to those in EAE. Nevertheless, new observations support the generally accepted views that MS is a predominantly TH1 lymphocyte mediated disease, and CCL – CCR molecules play a significant part in the regulation of intercellular interactions in the peripheral lymphoid organs, at the BBB and in the CNS. In addition to defining chemotaxis, CCL-CCR interactions are involved in TH1 / TH2 polarization and regulation in MS. Recent studies also raise the possibility that distinct molecular mechanisms with characteristic CCL-CCR kinetics correlate with the development of histological subtypes of the disease.A recent review of chemokines and their receptors  suggestsWhile control brain specimens had only scarce appearance of CCR positive  cells throughout the CNS, foamy macrophages, microglia, perivascular lymphocytes and occasionally, astrocytes were positive for CCR2, CCR3 and CCR5 in chronic active plaques ,40. In oTrebst et al  investigCCR2 may also play a key role in the lesion development based on more indirect information. CCR2 is the main, but not exclusive, functional receptor for CCL2 , and as in vitro on TH2 and regulatory lymphocytes, macrophages and microglia. Using immunohistochemistry, Trebst et al [CCR8, the receptor for CCL1, has been detected st et al  detectedin situ hybridization, McManus et al [In situ hybridization confirmed the observation for CCL2 at mRNA level. There seemed to be an inverse correlation between the age of plaques and expression of these three CCL molecules, with only a scanty appearance of immunoreactive astrocytes in chronic silent lesions. These methods did not detect MCP chemokines in the brains of normal controls.Using methods of immunohistochemistry and us et al  investigAdditional studies demonstrated the expression of CCL3 and CCL4 in macrophages and microglia, and CCL3 also in astrocytes -49. CCL52-microglobulin [While most of the above studies used the method of immunohistochemistry, we recently assessed the mRNA expression levels for CCL2, CCL3, CCL5, CCL7, CCL8, CCL13 and CCL15 relative to β-actin in corresponding normal appearing white matter (NAWM), normal appearing gray matter (NAGM) and chronic active plaque containing specimens from ten post mortem MS brains. These specimens were characterized by hematoxyllin & eosin, Luxol Fast Blue and immune staining specific for CD68 and βglobulin . In addiglobulin . The selglobulin ,46. WhilRelatively limited numbers of studies are available regarding chemokines and their receptors in the blood circulation and in the cerebrospinal fluid (CSF) in MS patients. The expression of CCR5 was found to be higher on circulating T lymphocytes from MS patients than on those from normal controls. These T cells showed an increased migration towards CCL3 and CCL5, suggesting a functional significance of the altered receptor expression ,52. The Sorensen and Sellebjerg  assessedHowever, CCR5 on peripheral MNCs was not uniformly found to be differentially expressed in MS subtypes . MNCs frThere is relatively limited information available regarding CCR and CCL expression levels in the CSF. Some investigators showed that CCR5+ mononuclear cells of MS patients were enriched in the CSF, representing a significant proportion of monocytes and only a minority of T cells. However, neither cell population differed quantitatively from those of controls, suggesting that CSF leukocytes may not be fully reflective of CNS inflammation ,55.in vitro towards CXCL10, CXCL12 and CCL5. CXCL10, CXCL12 and CCL19 were increased in the CSF of these patients [Giunti et al  detectedpatients .Amongst CC chemokines, CCL3 and CCL5 were most consistently found to be elevated in the CSF of MS patients during relapses as compared to normal controls -61. In cPashenkov et al  studied To correlate previous data on CCL concentrations in the CSF of MS patients, Kivisakk et al  measuredIn sum, the above data suggest that CCL1, CCL2, CCL3, CCL4, CCL5, CCL7 and CCL8 are expressed by residential glia and perivascular leukocytes in plaques. Expression of the corresponding CCR1, CCR2, CCR3, CCR5 and CCR8 receptors has been demonstrated on infiltrating leukocytes, but also on microglia, dendritic cells and astrocytes. While the expression kinetics of CCR1 and CCR5 may discriminate between histological type II and type III lesions of MS, CCR8 is similarly expressed in both lesions types  . This inStudies on EAE and MS suggest that CC chemokine ligands  expressed by residential immune cells in the CNS or by endothelial cells at the BBB are major chemoattractants for hematogenic immune cells  via interactions with their G-protein-coupled receptors (CCR1-CCR10). These CCL – CCR interactions play a key role in the recruitment, activation and retention of immune competent cells in the CNS, with the CCL1 – CCR8, CCL2 – CCR2, CCL3 – CCR1 / CCR5, CCL5 – CCR1 / CCR5, CCL7 – CCR1 / CCR2 / CCR3, CCL8 – CCR3, CCL20 – CCR6, CCL19 / CCL21 – CCR7, CCL22 – CCR4 interactions being the best characterized among them  declare that they have no competing interests.Ileana Banisor, research assistant, was involved in the acquisition and analyses of our research data mentioned in the paper. She prepared the figure. Thomas P. Leist, collaborator, critically reviewed and edited the manuscript. Bernadette Kalman, P.I., designed the research studies mentioned from her lab, supervised the work processes, interpreted the data and drafted this manuscript. She also generated funding supports.


The enzyme glucose-6-phosphatase catalyzes the dephosphorylation of glucose-6-phosphatase to glucose, the final step in the gluconeogenic and glycogenolytic pathways. Expression of the glucose-6-phosphatase gene is induced by glucocorticoids and elevated levels of intracellular cAMP. The effect of cAMP in regulating glucose-6-phosphatase gene transcription was corroborated by the identification of two genetic motifs CRE1 and CRE2 in the human and murine glucose-6-phosphatase gene promoter that resemble cAMP response elements (CRE).The cAMP response element is a point of convergence for many extracellular and intracellular signals, including cAMP, calcium, and neurotrophins. The major CRE binding protein CREB, a member of the basic region leucine zipper (bZIP) family of transcription factors, requires phosphorylation to become a biologically active transcriptional activator. Since unphosphorylated CREB is transcriptionally silent simple overexpression studies cannot be performed to test the biological role of CRE-like sequences of the glucose-6-phosphatase gene. The use of a constitutively active CREB2/CREB fusion protein allowed us to uncouple the investigation of target genes of CREB from the variety of signaling pathways that lead to an activation of CREB. Here, we show that this constitutively active CREB2/CREB fusion protein strikingly enhanced reporter gene transcription mediated by either CRE1 or CRE2 derived from the glucose-6-phosphatase gene. Likewise, reporter gene transcription was enhanced following expression of the catalytic subunit of cAMP-dependent protein kinase (PKA) in the nucleus of transfected cells. In contrast, activating transcription factor 2 (ATF2), known to compete with CREB for binding to the canonical CRE sequence 5'-TGACGTCA-3', did not transactivate reporter genes containing CRE1, CRE2, or both CREs derived from the glucose-6-phosphatase gene.bona fide CRE. This study further shows that the expression vectors encoding C2/CREB and catalytic subunit of PKA are valuable tools for the study of CREB-mediated gene transcription and the biological functions of CREB.Using a constitutively active CREB2/CREB fusion protein and a mutant of the PKA catalytic subunit that is targeted to the nucleus, we have shown that the glucose-6-phosphatase gene has two distinct genetic elements that function as  The glucose-6-phosphatase system consists of the glucose-6-phosphate catalytic subunit EC 3.1.3.9), embedded in the membrane of the endoplasmic reticulum (ER) via nine transmembrane domains, and the membrane spanning translocases, responsible in carrying either the substrate into the ER or the product from the ER .3.9, emb. In animThe glucose-6-phosphatase encoding gene is regulated by a variety of extracellular signaling molecules, including glucose, insulin, glucocorticoids, and cAMP. Insulin decreases the level of glucose-6-phosphatase mRNA in the liver and in hepatoma cells and three functionally distinct insulin response elements have been identified . GlucocoThe most important and best characterized protein that connects an elevation of intracellular cAMP concentrations with enhanced transcription of selected genes is the CRE binding protein CREB, a basic region leucine zipper protein. CREB plays an essential role in the regulation of glucose-6-phosphatase gene transcription in the liver, as exemplified by the fact that transgenic mice expressing a dominant-negative CREB mutant in the liver show reduced mRNA levels of glucose-6-phosphatase . CREB noInstead of increasing the intracellular levels of cAMP some investigators employed an overexpression strategy using the catalytic subunit of cAMP-dependent protein kinase to analyze cAMP regulated genes. This approach has the advantage that by excluding a parallel signaling cascade via the cAMP-inducible nucleotide exchange factor EPAC, only the biological outcome of cAMP-dependent protein kinase activation is studied. However, the translocation of the catalytic subunit of cAMP-dependent protein kinase into the nucleus is not very efficient and may rely solely on diffusion . Thus hiHere, we report on the regulation of glucose-6-phosphatase gene transcription by CREB and PKA. Using a constitutively active CREB2/CREB fusion protein, that does not require phosphorylation for activation, and a nuclear-targeted mutant of the catalytic subunit of PKA, we show that CREB activates transcription of glucose-6-phosphatase promoter/luciferase reporter genes via two distinct genetic elements. In contrast, the bZIP protein ATF2, known to compete with CREB for binding to the canonical CRE, did not transactivate these reporter genes containing CRE1, CRE2, or both CREs derived from the glucose-6-phosphatase gene.Fig. The fact that unphosphorylated CREB is transcriptionally silent excludes a simple overexpression strategy to analyze the biological impact of the CRE-like sequences within the glucose-6-phosphatase gene. The use of natural inducers of CREB such as glucagon or epinephrine, that all elevate the cAMP concentration in the cells, also triggers pleiotropic responses by activating the cAMP-dependent protein kinase and the EPAC/Rap1 pathway, so that the biological outcome cannot be attributed solely to CREB activation. We therefore designed a constitutively active CREB2/CREB fusion protein to uncouple the investigation of glucose-6-phosphatase gene transcription from signaling pathways in the cell. Fig. 2luc reporter plasmid that contains two copies of the composite CRE/AP1 element of the TNFα promoter. We transfected additionally plasmid pRSVβ, encoding β-galactosidase under the control of the Rous sarcoma virus long-terminal repeat, to correct for variations in transfection efficiencies. Luciferase activities were normalized for transfection efficiency by dividing luciferase light units by β-galactosidase activities. The results of the transfection experiments are depicted in Fig. bona fide CREs. This conclusion was confirmed by transfection experiments of reporter plasmids having only one of the CRE-like sequences in the regulatory regions. Fig. 2luc reporter gene via the CRE/AP1 element  are depicted in Fig. 5luc that contains five copies of the GAL4 binding site termed "upstream activating sequence" (UAS) upstream of a luciferase reporter gene  or expression vectors encoding Cα or NLSCα. Transfection efficiency was monitored by co-transfecting pRSVβ. As a control, plasmid pM1 encoding only the DNA binding domain of GAL4 (GAL4DBD) was transfected. Cell extracts were prepared forty-eight hours later and β-galactosidase and luciferase activities were determined. Fig. To test the biological activity of NLSCα, in comparison to the wild-type form of the catalytic subunit (Cα), we measured the activity of the phosphorylation-regulated transcription factor CREB using a fusion protein consisting of the GAL4 DNA-binding domain fused to the kinase inducible activation domain of CREB. The modular structure of the GAL4-CREB fusion protein is depicted in Fig. ene Fig. . Since mNext, we tested the biological activity of NLSCα with regard to transcription of the glucose-6-phosphatase promoter/luciferase reporter genes. In the experiments, we additionally overexpressed wild-type CREB, the CREBS133A containing a serine to alanine mutation at position 133, and K-CREB, a CREB mutant containing the point mutation R286L within the basic DNA-binding domain, impairing DNA-binding . Transfe2luc. The results show that C2/ATF2 was unable to transactivate the reporter genes containing CRE1, CRE2, or both CRE-like sequences derived from the glucose-6-phosphatase gene in the regulatory region, indicating that glucose-6-phosphatase gene transcription is not regulated by ATF2 via the two CRE-like sequences. In contrast, C2/ATF2 strongly activated transcription of the pTNFα(CRE/AP1)2luc reporter gene, confirming that TNFα gene transcription is regulated by ATF2.The transcription factor ATF2, a substrate of stress-activated protein kinases, has been reported to bind to the classical cAMP responsive element (CRE) 5'-TGACGTCA-3' . Recentlcis-acting sites for transactivation by CREB and that also respond to activated PKA in the nucleus. Two distinct genetic elements had been suggested to couple enhanced levels of cAMP and elevated PKA activity with increased glucose-6-phosphatase gene transcription [The gene encoding glucose-6-phosphatase is regulated by increased levels of intracellular cAMP, but the regulatory sites responsible for cAMP-induced gene transcription are still a matter of controversy. The objective of this study was to characterize the genetic elements that function as cription ,17 and win vitro binding assay, does not necessarily prove an enhanced transcriptional activation potential of this protein [The reason for the differences in the published reports concerning cAMP-regulated glucose-6-phosphatase gene transcription can be explained by the technical problems that occurs following elevation of the intracellular cAMP concentration, as outlined in the introduction section. To solve these problems, we prefered to measure "transcriptional activation" instead of "transcription factor/DNA-binding" because although DNA-binding is required for a subsequent transcriptional activation by CREB, an enhanced binding activity of a transcription factor to DNA, monitored by an  protein . In addi protein  and the  protein  of the h protein .bona fide CRE [bona fide CRE. We also observed an activation of glucose-6-phosphatase promoter/luciferase reporter gene transcription following coexpression of CREBS133A with NLSCα. Phosphorylation of the serine 133 residue of CREB is the predominant mechanism to enhance the transcriptional activation potential of CREB via recruitment of the coactivator CREB binding protein (CBP) and its paralogue p300 to the promoter. Accordingly, we observed a clear reduction of reporter gene transcription in coexpression studies of NLSCα together with CREBS133A instead of wild-type CREB. However, expression of CREBS133A still contributed to reporter gene transcription in the presence of NLSCα, suggesting that either other residues of CREBS133A or other promoter-bound proteins involved in the regulation of CREB-mediated transcription are phosphorylated. PKA can phosphorylate CBP directly or other components of the transcriptional machinery downstream from CREB [Using an overexpression strategy for the catalytic subunit of PKA, it has been reported that PKA directly stimulates reporter gene transcription under control of CRE1, whereas CRE2 was unable to connect elevated PKA activity with enhanced CRE2-controlled reporter gene transcription . The autfide CRE . In thisfide CRE ,31 and ofide CRE . Transferom CREB ,33. NoneIn contrast to the expression experiments involving C2/CREB, we did not detect an effect of C2/ATF2, a constitutively active CREB2/ATF2 fusion protein, on glucose-6-phosphatase promoter/luciferase reporter gene transcription, despite the fact that the sequence 5'-TTACGTAA-3', which is identical to the CRE1 site of the glucose-6-phosphatase promoter, has been shown to function as a high affinity binding site for ATF2 in vitro . This diWe have shown that there are two distinct CREB-responsive sites in the glucose-6-phosphatase gene promoter that are responding to either a constitutively active CREB or elevated concentrations of the catalytic subunit of cAMP-dependent protein kinase in the nucleus. This study further shows that the expression vectors encoding C2/CREB and NLSCα are valuable tools for the investigation of CREB-mediated gene transcription and the biological functions of CREB. CREB is a key molecule in neuronal survival, as demonstrated by the fact that a dominant-negative A-CREB induced apoptosis in sympathetic neurons grown in NGF . The C2/2luc, that contains two copies of the CRE/AP1 element of the human tumor necrosis factor α gene, was generated in a similar way with annealed oligonucleotides encompassing the sequence depicted in Fig. 5luc containing the luciferase reporter gene, a TATA box derived from the HIV long terminal repeat, an initiator element from the adenovirus major late promoter, and five binding sites for GAL4  has been described [The glucose-6-phosphatase promoter/luciferase reporter genes pG6PCRE1/CRE2luc, pG6PCRE1mut/CRE2luc, and pG6PCRE1/CRE2mutluc were constructed by the insertion of the annealed oligonucleotides depicted in Fig. escribed .The expression vector pCMV-FLAG-C2/CREB, encoding a constitutively active CREB2/CREB chimera, has been described . The CREHuman HepG2 hepatoma cells were cultured and transfected as described . The amoNuclear extracts were prepared as described . 20 μg oATF activating transcription factorbZIP basic region leucine zipperCRE cAMP response elementCREB cAMP response element binding proteinG6P glucose-6-phosphatasePKA protein kinase ATNF tumor necrosis factorGT designed the study, generated the reporter plasmids and the expression vectors encoding C2/CREB, C2/ATF2, and NLSCα, performed part of the transfection experiments and drafted the manuscript. JAS performed the transfection experiments depicted in Figs.


Modern developmental biology relies heavily on the analysis of embryonic gene expression patterns. Investigators manually inspect hundreds or thousands of expression patterns to identify those that are spatially similar and to ultimately infer potential gene interactions. However, the rapid accumulation of gene expression pattern data over the last two decades, facilitated by high-throughput techniques, has produced a need for the development of efficient approaches for direct comparison of images, rather than their textual descriptions, to identify spatially similar expression patterns.The effectiveness of the Binary Feature Vector (BFV) and Invariant Moment Vector (IMV) based digital representations of the gene expression patterns in finding biologically meaningful patterns was compared for a small (226 images) and a large (1819 images) dataset. For each dataset, an ordered list of images, with respect to a query image, was generated to identify overlapping and similar gene expression patterns, in a manner comparable to what a developmental biologist might do. The results showed that the BFV representation consistently outperforms the IMV representation in finding biologically meaningful matches when spatial overlap of the gene expression pattern and the genes involved are considered. Furthermore, we explored the value of conducting image-content based searches in a dataset where individual expression components (or domains) of multi-domain expression patterns were also included separately. We found that this technique improves performance of both IMV and BFV based searches.We conclude that the BFV representation consistently produces a more extensive and better list of biologically useful patterns than the IMV representation. The high quality of results obtained scales well as the search database becomes larger, which encourages efforts to build automated image query and retrieval systems for spatial gene expression patterns. Drosophila melanogaster (the fruit fly) has been a canonical model animal for understanding this developmental process in the laboratory. The raw data from experiments consist of photographs  of the Drosophila embryo showing a particular gene expression pattern revealed by a gene-specific probe in wildtype and mutant backgrounds. Manual, visual comparison of these spatial gene expressions is usually carried out to identify overlaps in gene expression and to infer interactions . As a ra genome . In addiWith this rapid increase in the amount of available primary gene expression images, searchable textual descriptions of images have become available ,10,11. HWe previously proposed a binary coded bit stream pattern to represent gene expression pattern images . In thisIn this paper, we explore how a more sophisticated Invariant Moment Vectors  based dPreviously, we had examined the performance of the BFV representation for a limited dataset of early stage images . Here weDuring these investigations, we also developed another measure of image-to-image similarity for the BFV representation. This measure is aimed at finding images that contain as much of the query image expression pattern as possible, but without penalizing for the presence of any expression outside the overlap region in the target image. In addition, we examined whether partitioning a multi-domain expression pattern into multiple BFV representations, each containing only one domain, yields a better result set.Recently, Peng and Myers  have proAn image database of 226 gene expression pattern images was initially generated using data from the literature -29. All In order to present comprehensible result sets in this paper, we have primarily discussed the findings from the dataset of 226 and provided information on how those queries scaled when they were conducted for the larger dataset. In general, our focus was to show the retrieval of biologically significant matches based on both the visual overlap of the spatial gene expression pattern and the genes associated with the pattern retrieved.φ1 through φ7), and binary feature representations were stored in a database. We also calculated and stored the expression area (the count of the number of 1's in the binary feature represented image), the X and Y coordinates of the centroid , and the principal angle (θ) for each extracted pattern.Each image was standardized and the binary expression pattern extracted following the procedures described previously . These eSS, SC) based on the BFV representation (See equations 2 and 3 in Methods). SS is designed to find gene expression patterns with overall similarity to the query image, whereas SC is for finding images that contain as much of the query image expression pattern as possible without penalizing for the presence of any expression outside the overlap region in the target image. For a given pair of gene expression patterns (A and B), SS is the same irrespective of which image in the pair is the query image. That is, SS = SS . This is not so for SC, because SC measures how much of the query gene expression pattern is contained in the image. Therefore, SC  ≠ SC.To quantify the similarity of gene expressions in two images, we computed two measures . Results from Dφ should be compared to that from SS, as both of these measurements do not depend on the reference image, i.e., Dφ  = Dφ and, also they capture overall similarity or dissimilarity.For IMV representation, we computed one dissimilarity measure  gene in a wildtype embryo. The BESTi-matches based on the SS measure for the representations are given in Figure sloppy paired genes (slp1 and slp2) in a variety of genetic backgrounds or in combination with a head gap gene orthodentical (otd); all of these genes are essential for the pattern formation in Drosophila head development  or m or mcis-Separating multi-domain gene expression patterns into individual components was straightforward; we simply generated multiple images from the same initial image and included them in the target dataset. This resulted in 192 additional images  in the database all of which were components of the initial gene expression patterns. The images were separated into expression regions horizontally and/or vertically depending on the gene expression. For this new set of images, the IMV as well as BFV representations were re-calculated and the BESTi query constructed as above.SS and IMV queries for this data set are given in Figures tailless (tll), which is known to interact with slp1 in defining the embryonic head [race (related to angiotensin converting enzyme), sog (short gastrulation) and eve (even-skipped) due to enhanced race expression in the anterior domain caused by a transgenic construct causing ectopic expression of sog [Results from BFV-nic head , and witn of sog . TherefoSS, SC and Dφ in finding BESTi matches for a query pattern with multiple regions of expression  mutant background, and a middle stripe due to misexpressed sog using an eve stripe-2 enhancer [Figure SS finds many images from the same paper as well as some images from other research articles with similar expression patterns. The results correctly include expression pattern of eve  value calculated does not show a significant difference in the early stage embryos used in this study. The results using the SC based search are given in Figure SS results. However, as expected, there are significant differences between the two searches.When t Figure . HoweverSS as the search criterion. These searches are based on the complete expression . This is referred to as the Binary Sequence Vector (BSV) in . In otheDE, between the binary feature vectors of every possible pair of images in the dataset. DE was introduced in [The expression patterns are ordered by evaluating a set of difference values, duced in  and is fDE = Count(A XOR B)/Count(A OR B)     (1)Count(A XOR B) corresponds to the number of pixels not spatially common to the two images and the term Count(A OR B) provides the normalizing factor, as it refers to the total number of stained pixels (expression area) depicted in either of the two images being compared. For simplicity, we use the one's complement of DE, as a measure of similarity of gene expression patterns between two images, SS, is given by the equationThe term SS = (1 - DE).     (2)SS quantifies the amount of similarity based on the overlap between two expression patterns. SS is equal to 1 when the two expression patterns are identical (DE = 0).SC quantifies the amount of similarity based on the containment of one expression pattern in the other given byWe introduce a new similarity measure in this paper that does not penalize for any non-overlapping region. The measure SC = Count(A AND B)/Count (A)     (3)i.e., there is complete overlap (with respect to the query image) SC is equal to 1. Note that, SC ≠ SC, because the denominator corresponds to the gene expression area of the query image.If the entire query image is contained within the result set images found in the database, Some methodologies of image analysis produce numeric descriptors that compensate for variations of scale, translation and rotation. In the following section, we describe the invariant moment analysis of gene expression data. Invariant moment calculations have been used in optical character recognition and other applications for many years .To calculate these invariant moment descriptors the standardized binary image  is conveMpq = ∬xp yq fdxdy,     (4)Mpq is the two-dimensional moment of the function of the gene expression pattern, f. The order of the moment is defined as (p + q), where both p and q are positive natural numbers. When implemented in a digital or discrete form this equation becomeswhere  and  which are the coordinates of the center of gravity, centroid, of the area showing expression. They are calculated asWe then normalize for image translation using Discrete representations of the central moments are then defined as follows:A further normalization for variations in scale can be implemented using the formula, is the normalization factor. From the central moments, the following values are calculated:and φ7 is a skew invariant to distinguish mirror images. In the above, φ1 and φ2 are second order moments and φ3 through φ7 are third order moments. φ1 (the sum of the second order moments) may be thought of as the "spread" of the gene expression pattern; whereas the square root of φ2 (the difference of the second order moments) may be interpreted as the "slenderness" of the pattern. Moments φ3 through φ7 do not have any direct physical meaning, but include the spatial frequencies and ranges of the image.where f is the angular displacement of the minimum rotational inertia line that passes through the centroid  and is given as:In order to provide a discriminator for image inversion (and rotation), sometimes called the "6", "9" problem, it has been suggested ,42 that θ. It is calculated knowing that the moment of inertia of f around the line  is a line through  with slope θ. We can find the θ value at which the momentum is minimum by differentiating this equation with respect to θ and setting the results equal to zero. This produces the following equation:The slope of the principal axis is called the principal angle θ| < 45° one can distinguish the "6" from the "9" and rotationally similar gene expression patterns.Using the condition |φ1 through φ7) and combinations of these moments. For example, if the first two invariant moments are used, thenIn invariant moment analysis, our initial method of image comparison calculates the Euclidean distance between the images using all moments (Dij, between a pair of images i and j where i, j = 1, 2,...n is given byand the distance Dφ, between any two images is calculated asThis can be expanded to use all of the moment variables. Here, the Euclidean distance, i and q designate images whose distance is being calculated and j designates the parameters used in the distance calculation and j = 1, 2, ..., 7. This assumes that all moments have the same dimensions or that they are dimensionless.where φ1 has the dimension of distance squared, while φ2 has the dimension of the fourth power of distance, thus requiring the square root function to equalize dimensions for comparable distance calculation purposes. In general, the greater number of invariant moments used in the distance calculation, the more selective the ranking. We have also allowed for the use of the centroids and principal angle as a means of list limiting.Using this method, it is possible to rank each of the images in order of their similarity based on, for example, the first two invariant moments that have clear-cut physical meanings. Expansion to include additional moments or parameters can be performed in a number of ways. It is possible to add additional parameters to the distance calculation making sure that each of the parameters has the same dimension. For example, SK originally conceived the project, developed the image distance measures based on the BFV representation, wrote an early version of the manuscript, and edited it until the final version. RG was responsible for writing new and using pre-existing programs to perform the image distance and parameter calculations, helped prepare the figures, searched the literature for gene expression data, maintained the database of gene expression pattern images, and helped in writing the manuscript. BVE provided the IMV method description, managed the day-to-day activities in the project, and did significant editing to produce the manuscript in the desired format for the journal. SP originally proposed the use of invariant moment vectors for biological image analysis, contributed significantly for the image distance and parameter calculations and provided critical feedback during the later stages of revision.


Drosophila and vertebrate development and are misregulated in many cancers. While a major step forward in understanding the molecular mechanism(s) surrounding Hairy-mediated repression was made with the identification of Groucho, Drosophila C-terminal binding protein (dCtBP), and Drosophila silent information regulator 2 (dSir2) as Hairy transcriptional cofactors, the identity of Hairy target genes and the rules governing cofactor recruitment are relatively unknown. We have used the chromatin profiling method DamID to perform a global and systematic search for direct transcriptional targets for Drosophila Hairy and the genomic recruitment sites for three of its cofactors: Groucho, dCtBP, and dSir2. Each of the proteins was tethered to Escherichia coli DNA adenine methyltransferase, permitting methylation proximal to in vivo binding sites in both Drosophila Kc cells and early embryos. This approach identified 40 novel genomic targets for Hairy in Kc cells, as well as 155 loci recruiting Groucho, 107 loci recruiting dSir2, and wide genomic binding of dCtBP to 496 loci. We also adapted DamID profiling such that we could use tightly gated collections of embryos (2–6 h) and found 20 Hairy targets related to early embryogenesis. As expected of direct targets, all of the putative Hairy target genes tested show Hairy-dependent expression and have conserved consensus C-box–containing sequences that are directly bound by Hairy in vitro. The distribution of Hairy targets in both the Kc cell and embryo DamID experiments corresponds to Hairy binding sites in vivo on polytene chromosomes. Similarly, the distributions of loci recruiting each of Hairy's cofactors are detected as cofactor binding sites in vivo on polytene chromosomes. We have identified 59 putative transcriptional targets of Hairy. In addition to finding putative targets for Hairy in segmentation, we find groups of targets suggesting roles for Hairy in cell cycle, cell growth, and morphogenesis, processes that must be coordinately regulated with pattern formation. Examining the recruitment of Hairy's three characterized cofactors to their putative target genes revealed that cofactor recruitment is context-dependent. While Groucho is frequently considered to be the primary Hairy cofactor, we find here that it is associated with only a minority of Hairy targets. The majority of Hairy targets are associated with the presence of a combination of dCtBP and dSir2. Thus, the DamID chromatin profiling technique provides a systematic means of identifying transcriptional target genes and of obtaining a global view of cofactor recruitment requirements during development.Members of the widely conserved Hairy/Enhancer of split family of basic Helix-Loop-Helix repressors are essential for proper  A new chromatin profiling technique identifies targets of the transcription factor Hairy -- as well as targets of three co- repressors -- which implicate Hairy in several developmental processes Drosophila embryogenesis is marked by the subdivision of the embryo into progressively more precise spatial domains, achieved through the coordinated functions of both transcriptional activators and repressors  pair-rule gene, fushi tarazu  subclass of repressor bHLH proteins . These pac has been shown to be a direct transcriptional target of Hairy during peripheral nervous system development .HES proteins have been shown to bind preferentially to Class C sites  as homodimers in vitro . The preelopment . HoweverDrosophila C-terminal binding protein (dCtBP), and Drosophila silent information regulator 2 (dSir2)  . None ofhairy mutant phenotype (Drosophila histone deacetylase 1 homolog), but the evidence for the significance of this interaction is somewhat mixed  acid dehydrogenases  family members are an interesting new class of transcriptional coregulators that encode nicotinamide adenine dinucleotidedSir2 encodes NAD+-dependent histone deacetylase activity that is required for heterochromatic silencing  tethered to a chromatin binding protein leads to specific methylation of DNA adjacent to the protein binding/recruitment sites (Drosophila Kc cells (see Drosophila microarray chip containing approximately 6200 full-length Drosophila Gene Collection (DGC) cDNAs and ESTs , those affecting cell cycle or cell growth , ImpL2, Idgf2), and those with unknown/unlinked functions. Unfortunately, the two previously identified Hairy targets, ftz and ac, are not present in the DGC Release 1 cDNA set used to generate our microarray chips.We identified 40 statistically significant putative direct Hairy transcriptional targets in Kc cells . For jusDrosophila Myc/Max/Mad-Mnt network of bHLH leucine zipper proteins , or because the mechanism by which Hairy acts during segmentation is different than expected. To begin distinguishing among these possibilities, we used the DamID approach to identify Hairy targets in Drosophila embryos during segmentation.Since Hairy is part of the segmentation gene transcriptional regulatory cascade, we expected to find segmentation-related transcription factors as downstream targets of Hairy. The putative Hairy targets we identified in Kc cells do not fulfill this expectation, but rather suggest roles for Hairy in cell cycle, cell growth, and morphogenesis; these putative targets are likely targets for Hairy during its other developmental roles. This could be because of cellular context , or because only half of the Towards this aim, we generated functional transgenic flies carrying a UAS–Dam or UAS–Dam–Hairy fusion gene construct see . As withegh, overlapped between the datasets , is a homeobox-encoding transcription factor known to function in segmentation  in a hairy mutant background  or its target gene  alone were viable. The reduction of Hairy in this target-gene-sensitized background allows inappropriate target gene regulation .If Hairy is a direct regulator of a particular target gene, genetic interaction might be expected between th hairy . In all stg, a series of transgenic lines have been generated in which lacZ expression is driven from different promoter fragments , but not the other two (pstg β-E2.2 and pstg β-E6.7). Consistent with the presence of Hairy binding sites, the lacZ expression from pstg β-E4.9 and pstg β-E6.4, but not from pstg β-E2.2 or pstg β-E6.7, was derepressed (expanded) in a hairy mutant background compared to wild-type (TCGCA) to generate pstg β-E4.9Δhairy. This mutation abolishes Hairy binding in vitro . Wild-type flies carrying this pstg β-E4.9Δhairy reporter exhibit the same lacZ derepression as observed for the original pstg β-E4.9 reporter when in a hairy mutant background, indicating that the derepression is due to Hairy binding  that contain the canonical core Hairy site (CACGCG). We searched for this consensus site within the promoter and transcribed regions of three Hairy targets: stg, egh, and prd. We identified one site in prd, three in egh, and four in the stg genomic region (hairy mutant background (see above). We tested whether the identified sites are direct Hairy binding sites in electromobility shift assays (EMSAs), utilizing bacterially purified full-length Hairy protein and 32P-labeled oligos containing the appropriate Hairy binding sites , a zinc-finger-encoding transcription factor  reporter at cytological location 1F, the transgene insertion site .If particular Hairy targets require specific cofactors to be appropriately regulated, we would expect their expression to be altered (deregulated) in a cofactor mutant background. We performed RNA in situ hybridization for two Hairy Kc cell targets that differentially recruit Groucho, dCtBP, and dSir2. We chose to examine the expression of two ally cf. . Consistkgrounds A–8D. Simkgrounds E–8H. Whikgrounds I–8L, sugWhen DamID data for the three Hairy cofactors and Hairy itself are graphically projected onto chromosomes, several interesting features come to light A. For exWe have known for almost two decades that Hairy plays a pivotal role in the segmentation hierarchy, as well as other developmental processes, but the details of Hairy action have not been easy to tease apart. An important step in understanding the molecular mechanisms surrounding Hairy-mediated repression was made with the identification of Groucho as a Hairy binding protein . One of Drosophila cDNAs, we estimate the actual number of Hairy targets to be approximately twice that number . This predicted number of Hairy targets is close to the approximately 120 strongly staining sites we observe on polytene chromosomes. Of the 59 putative Hairy targets we identified in both the Kc cell and embryo DamID experiments, 58 correspond to bands of Hairy staining on the polytene chromosomes, suggesting that polytene chromosome staining is representing Hairy binding sites without regard to tissue specificity. It is not yet clear what is limiting Hairy accessibility in different tissues or why Hairy's access does not appear to be limited in salivary glands. It may be that polytene chromosome organization necessitates a looser chromatin structure or that the large number of factors that seem to be endogenously expressed in salivary glands affects accessibility. Ultimately, additional confirmation of the DamID and polytene staining correspondence will require microarray tiling chips containing overlapping genomic DNA fragments; however, such genomic DNA tiling chips are currently unavailable.The 59 putative Hairy targets we identified in the embryo and Kc cell DamID experiments correspond to bands of Hairy immunostaining on polytene chromosomes, suggesting that the polytene chromosome staining faithfully represents Hairy binding. Polytene chromosomes are functionally similar in transcriptional activity and display factor/cofactor binding properties similar to chromatin of diploid interphase cells, despite their DNA endoreplication , 2002. SDrosophila microarray chip we used was generated using full-length cDNAs. Indeed, as Hairy has been described as a long-range repressor  have been shown to function as either positive or negative regulators of transcription depending on promoter context and cofactor recruitment  was generated by standard PCR using primers containing a BamHI 5′ site and a NotI 3′ site, cut with BamHI and NotI, and subcloned into the BglII and NotI sites of pCMycDam plasmid, as described previously . As in Kc cells, induced expression of these Dam fusion constructs leads to high levels of nonspecific methylation. Therefore we utilized low-level leaky expression from the minimal promoter of the pUASp vector for these experiments. 2–6-h embryos were collected and dechorionated with 100% bleach. Approximately 500 μl of embryos were crushed in 1 ml of lysis buffer . SDS (to 0.5%) and proteinase K (to 100 μg/ml) were added immediately after homogenization, followed by incubation at 55 °C for 2 h. SDS was increased to 1.5%, followed by incubation for an additional 2–3 h. The genomic DNA was isolated and processed for microarray hybridizations essentially as described previously  for the Northwest Fly Consortium and contain approximately 6200 full-length DGC cDNAs . We employed the default window size of 101 and used a confidence value of ten in our CyberT analysis. The null hypothesis was rejected and a spot ratio was called significantly changed if pBon ≤ 0.05, where pBon is the Bayesian p-value adjusted for multiple hypothesis tests using the conservative Bonferroni correction. Based on prior “self versus self” DamID comparisons, we empirically determined a lower-bound ln(ratio) threshold = |0.405| as an additional significance criterion to discriminate spot intensity signals from the inherent noise in the hybridization process. For each protein analyzed, a fluor-reversed array comparison was performed and used to screen all significant calls for fluor-specific artifacts. For our analyses, we treated the small subset of replicated spots on the array independently. For those cases, both spots were required to be called significant. Reported ratio values were retransformed to log2 as a matter of convention. The complete raw and processed datasets can be accessed at http://www.fhcrc.org/labs/parkhurst/supplementary-data/.Arrays were scanned using a GenePix 4000 scanner , and image analysis was performed using GenePix Pro 3.0. For each array, spot intensity signals were filtered and removed if the values did not exceed 3 standard deviations above the background signal in at least one channel or if the spot was flagged as questionable by the GenePix Pro software. For each spot, background-corrected ratios were natural log transformed and a median-centered normalization strategy was applied across each array. Dam–protein and Dam transfections were independently replicated three times, and the subsequent array comparisons  were analyzed using CyberT , a Bayes7H rucucah/ TM3, 12C st eh/ TM3, Df(3 l)i22 Ki roe pph/TM3, and 2.45.17prd/CyO (D. Ish-Horowicz); FRT82B- P{ry+t7.2=PZ}03463 ry506CtBP/TM3 (N. Perrimon); FRT 82B- E47gro/TM3 , KG02223ImpL2 (#14083), k06602mae/CyO (#10633), Δ88pnt/TM3 (#861), and KG03110rgr (#13770) . Details of these strains are found on FlyBase (http://flybase.bio.indiana.edu:82/). AR2stg and the stg-lacZ reporter lines  were described previously (dCtBP and groucho were generated as previously described (Δhairy transgenic flies were generated by injecting vector (500 μg/ml) along with the pTURBO helper plasmid (100 μg/ml)   into isoLarval cuticle preparations were prepared and analyzed as described by Immunohistochemical whole mount RNA in situ hybridization was performed according to the protocol of 32P-end-labeled probe of each oligo was incubated with either GST– or GST–Hairy–purified proteins (200 ng each), in a 25-μl reaction supplemented with binding buffer  at room temperature. Where indicated, the binding was preformed in the presence of 15-fold excess of unlabeled wild-type or mutated ac competitor oligos. Following incubation, the complexes were resolved using 0.5% TBE-PAGE gels and visualized by autoradiograms. The following oligos were used (forward primers are shown): ac 5′-TAAACCGGTTGGCAGCCGGCACGCGACAGGGCCAGGTTTT-3′; egh egh1 5′-TGCGCGTCACGCGCCGTTC-3′, egh2 5′-TCATTCGCACGCGGAATCT-3′, and egh 3 5′-GCCGGACACGCGATGATGG-3′; mutated ac oligo 5′-TAAACCGGTTGGCAGCCGGGACGCGACAGGGCCAGGTTTT-3′; mutated stg oligo 5′-TCTACCACACACAAACACTCGCACGCGAAAACTGGG -3′; prd 5′-AAGTGACACGCGCTCCGCT-3′; and stg 5′-AAACACACGCGCGCGAAAA-3′.EMSA was carried out using either bacterially expressed GST or GST–Hairy ( full-length) proteins, similar to the procedure described by Drosophila promoter sequences were captured using Apollo Genome Sequence and Annotation Tool . Using the Hairy site closest to transcription start site, the composition of transcription factor binding sites adjacent to (within 500 bp of) the Hairy site was assessed. This was also performed for non-Hairy targets selected because they contained one or more core C-box sequences. Matrices were compared that matched percentages of known Hairy targets  to C-box–containing nontargets.Several bioinformatics approaches were employed to analyze Hairy target gene promoters. In particular, ion Tool . Match vWild-type or pstg βE4.9 third instar larval salivary gland polytene chromosomes were prepared and stained for endogenous proteins essentially as described by The insertion site for the pstg β-E4.9 reporter line was performed as described by Dataset S1(2.9 MB XLS).Click here for additional data file.Dataset S2(11.8 MB XLS).Click here for additional data file.Dataset S3(11.8 MB XLS).Click here for additional data file.Dataset S4(11.8 MB XLS).Click here for additional data file.Dataset S5(11.8 MB XLS)Click here for additional data file.Dataset S6(11.8 MB XLS)Click here for additional data file.Dataset S7(230 KB XLS).Click here for additional data file.Dataset S8(276 KB XLS).Click here for additional data file.Dataset S9(44 KB XLS).Click here for additional data file.