Striking individual differences in severity of group A streptococcal (GAS) sepsis have been noted, even among patients infected with the same bacterial strain. We had provided evidence that HLA class II allelic variation contributes significantly to differences in systemic disease severity by modulating host responses to streptococcal superantigens. Inasmuch as the bacteria produce additional virulence factors that participate in the pathogenesis of this complex disease, we sought to identify additional gene networks modulating GAS sepsis. Accordingly, we applied a systems genetics approach using a panel of advanced recombinant inbred mice. By analyzing disease phenotypes in the context of mice genotypes we identified a highly significant quantitative trait locus (QTL) on Chromosome 2 between 22 and 34 Mb that strongly predicts disease severity, accounting for 25%–30% of variance. This QTL harbors several polymorphic genes known to regulate immune responses to bacterial infections. We evaluated candidate genes within this QTL using multiple parameters that included linkage, gene ontology, variation in gene expression, cocitation networks, and biological relevance, and identified interleukin1 alpha and prostaglandin E synthases pathways as key networks involved in modulating GAS sepsis severity. The association of GAS sepsis with multiple pathways underscores the complexity of traits modulating GAS sepsis and provides a powerful approach for analyzing interactive traits affecting outcomes of other infectious diseases. Group A streptococci (GAS) cause a wide variety of human diseases ranging from mild pharyngitis to streptococcal toxic shock syndrome and necrotizing faciitis. Our previous studies have shown that host immunogenetic variation can dictate the clinical outcome of GAS sepsis. As in most human disease, GAS sepsis is likely to be affected by complex interactions between more than one polymorphic gene. We addressed this issue in our study where we present an approach that allowed us to identify multi genetic factors that likely contribute to sepsis severity. We mapped susceptibility to severe GAS sepsis to quantitative trait loci on Chromosome 2 using a panel of genetically diverse inbred mice. The mapped regions have high single nucleotide polymorphism (SNP) density that harbor genes known to play an important role in innate immune response to bacteria. Several of those genes are differentially expressed between susceptible and resistant strains of mice. Our overall approach of systematic dissection of genetic and molecular basis of host susceptibility is not unique to GAS infections, but can be applied to other infectious diseases to develop better diagnostics, design effective therapeutics and predict disease severity based on a set of genetic and soluble biomarkers. Infectious diseases, like most human diseases, are modulated by complex traits. Susceptibility and clinical outcomes of infections are often a manifestation of interactions between the host's complex traits and the pathogen's virulence components. Identification of genes and molecular networks that influence host responses to infectious agents can provide a disease road map that would focus the discovery of effective diagnostics and therapeutics.Group A streptococci (GAS) are classified on the basis of surface M protein antigens into more than 100 serotypes, but recent studies showed a high degree of diversification within a serotype that is driven primarily by horizontal gene transfer To identify additional host factors involved in GAS severity we needed an approach that allowed us to uncover the effect of interactions between complex, polymorphic genetic traits that may modulate sepsis outcomes. Previous animal models for GAS sepsis included various regular conventional inbred mouse strains In this study, we used a panel of advanced recombinant inbred (ARI) mice as a genetically diverse, segregating reference population that affords a powerful tool for systems genetics approaches. Recombinant inbred (RI) strains have been successfully used to map quantitative trait loci (QTLs) associated with various phenotypes and diseases Our initial studies 7 CFU/mouse). Survival was expressed as normalized corrected relative survival indices (cRSI) calculated for each of the 32 strains as detailed in We infected mice (n = 5–26 mice per strain), belonging to 32 strains , intravenously (i.v.) with the same bacterial dose , 2 = 51.4%), Similarly, we determined bacterial load in blood (log CFU/ml blood), 24 h post-infection and found considerable variation across the strains. In general there was an inverse correlation between mice survival and extent of bacteremia  to link measured phenotypes to strains genotypes. Each of the quantified phenotypes was analyzed in the context of the studied mice genotypes and single nucleotide polymorphism (SNPs) using 3795 SNPs and microsatellite markers for BXD strains. Significant QTLs modulating survival, bacteremia 24 h post-infection, and bacterial dissemination to spleen mapped to mouse Chromosome (Chr) 2.The strongest QTL modulating mouse survival (cRSI) mapped to mouse Chr 2 between 22–34 Mb, with an likelihood ratio statistic (LRS) of 34.2 (P≤0.0000001), To further investigate and narrow down the mapped region on Chr 2, we resorted to haplotype maps of BXD strains to select additional strains that may be informative in validating, and further confirming mapped QTLs.D haplotype at Chr 2 between 22–34 Mb region, B haplotype in the same region and this strain as predicted, exhibited a resistant phenotype. To further narrow down the mapped QTLs, we chose strains with breakage in the mapped interval, i.e. with recombination at Chr 2 region 22–34 Mb for further survival testing . We parsed our genes into 50 functional networks; the most relevant networks involved those associated with immune response, cell signaling, cellular assembly and organization, and lipid metabolism. From these interrelated pathways, we selected 37 representative genes to study their role in GAS susceptibility QTL by quantitative analysis of their expression levels in selected resistant and susceptible strains (groups) pre- and post-infection  (nfection .Il1 α), and Il1 receptor antagonist (Il1rn) respectively. By contrast, in the resistant BXD strains, most of the tested genes showed a decrease (23 genes) in expression levels post-infection with few exceptions (five genes) e.g. TNF receptor associated factor 1 (Traf1) , and Ptges2 were up regulated in susceptible strains, whereas their levels decreased in resistant strains. Several of the differentially expressed genes show polymorphisms as SNPs between the parental strains B6 and D2, suggesting that these polymorphic genes modulate differential response to infection (α was confirmed at the protein level (data not shown).We found that 28 out of a representative 37 genes were differentially expressed post-infection , of thos (Traf1) . Differenfection . The dif−27) comprised of genes related to lipid metabolism and innate immunity, e.g. Il1a, Il1rn, Ptges, while second network (P<0.01) contained genes modulating nucleic acid metabolism, energy production and host responses to injury e.g. Ectonucleoside triphosphate diphosphohydrolase 2 (Entpd2)  .It has been established that networks of multiple pathways, rather than a single gene, modulate traits and affect susceptibility and outcomes of virtually all diseases. The ARI strains used in this study afford one of the best unbiased forward genetics approaches to determine how different combinations of polymorphic genes interact to shape disease phenotypes. Using this panel of genetically diverse reference population, we were able to map QTLs modulating specific phenotypes associated with severe GAS sepsis.GAS causes a wide range of diseases depending on multiple factors including site and route of infection, interplay of the pathogen virulence factors with host immune defenses that are affected by the host immune status and difference in the genetic make up of the host 7 CFU/mouse, and indicated the need to use mice with an age range of 40–120 days for linear correlation with survival. In addition, these pilot studies determined that sex has insignificant effect in this GAS sepsis model We invested time and effort to standardize the GAS infection model using a large number of BXD mice (n = 717) and this allowed us to optimize infection dose and identify significant covariates (e.g. age and sex) needed to be accounted for in our final analysis With a total of 30 BXD strains and an average of 15 mice per strain, we mapped QTLs on Chr 2 that modulate severity to GAS sepsis, measured by comparing mice survival post-infection, bacterial load in blood, and bacterial dissemination to spleen across the BXD strains. Inasmuch as the BXD strains are heavily genotyped with more than 3600 genomic markers, identifying QTLs is relatively straightforward. The mapped QTLs on Chr 2 harbor a relatively large number of candidate genes associated with various functional networks and signaling pathways including nuclear factor-κB (NF-κB) and p38 mitogen activated protein kinases (MAPK) pathways, proliferation of immune cells, and eicosanoid signaling. Such output is typical of unbiased genome-wide analysis studies, and required further analyses to determine which of these genes are the key modulators of the studied trait.To narrow down the gene list to a handful of genes that can be experimentally validated, we used multiple methods including linkage, gene ontology, and differential gene expression analyses. Our quantitative PCR analysis of 37 representative candidate genes showed that 28 genes were differentially expressed in selected susceptible and resistant strains post-infection. These differentially expressed genes fell into three main categories, genes associated with innate and adaptive immune response, and genes associated with apoptosis. Differentially expressed genes associated with innate immune response were both pro- and anti-inflammatory as well as adaptive immune response genes associated with T and B cell proliferation and differentiation, cell signaling and antigen processing and presentation.Il1 levels in the susceptible strains was accompanied by an increase in its endogenous antagonist Il1rn. This was not the case in the resistant strains that showed decreased levels of expression of pro- and anti-inflammatory related genes both pre- and post-infection. These findings suggest that susceptibly to GAS sepsis is associated with an overzealous innate immune response as observed in susceptible BXD strains only. These results mirror previous findings in humans, where association of exaggerated inflammatory responses, including IL-1, with susceptibility to GAS sepsis was detected Differentially expressed genes associated with innate immune response were either related to pro- or anti-inflammatory responses. Both pro- and anti-inflammatory associated genes were up-regulated in the selected susceptible strains post-infection, and this is in agreement with a recent study by Goldmann, et al. Anapc2) that was slightly increased in susceptible strains post-infection , Traf1, Traf2, Notch gene homolog 1 (Notch1), and signal-regulatory protein alpha (Sirpa). It is worthy to note the link between these genes is as they are involved directly and indirectly with activation of early adaptive response. Hspa5 is an Hsp70, which is associated with cytoprotection, anti-apoptosis, and anti-inflammation Notch1 has been associated with the signaling involved in regulation of lymphocytes development and activation to effector cells Notch1 was associated with macrophage activation Another interesting observation was that the relative expression level of genes measured in the selected resistant strains showed a pattern of decrease post-infection, with the exception of five genes, heat shock 70KDa protein 5  mice at UTHSC by crossing B6 and D2 mice to generate F1 hybrids, which were crossed to generate F2 progeny, each with random patterns of recombination. Random crossing of F2 mice generated F3 and so on, till F11 generation, after which we designated pairs of F11 hybrids as parents of each BXD line, and inbred them by sib mating for >20 generations to achieve homozygosity for each genetically distinct BXD line. This breeding scheme was done to increase recombination events resulting in roughly double the number of recombinations per strain compared to conventional RI strains www.genenetwork.org/webqtl/snpBrowser.py). Simple sequence length polymorphism (SSLP) markers were typed for all BXD RI strains as previously described www.genenetwork.org/genotypes/BXD.geno.The genomes of the B6 and D2 parental strains have been sequenced and a database of their SNPs is available at the Gene Network (GN) web site  Groups of 5–26 mice from a total of 30 BXD lines and their parental strains (B6 and D2) were injected via tail vein with 2±1.5×10−6 fold, and each dilution was cultured for determination of bacterial load in spleens (CFU/ml) that was then normalized to spleen weight and expressed as CFU/spleen.We designed experiments for the assessment of survival, bacteremia, and bacterial dissemination to spleen. We assessed relative mice survival and bacteremia in the same experiment. We measured bacteremia as CFU/ml by culturing serial dilutions of blood drawn from mice tails 24 h post-injection. We determined bacterial load in spleen by homogenizing spleens of expired mice using tissue homogenizer, TH . Each tissue homogenate was serially diluted 10 folds to 10We performed QTL mapping using web-based complex trait analysis available on the GN website and the mapping module which analyzes phenotypes in context of mouse genotypic differences. Interval mapping evaluates potential QTL at regular intervals and estimates the significance at each location using 1000 permutation tests 7 CFU/mouse of clinical isolate GAS 5448 (M1T1) and RNA from individual mice was extracted from spleens. Bacteremia was determined as described above. We isolated RNA using RNA-STAT 60 method and when necessary, we purified RNA samples using RNeasy mini kit clean up columns . We pooled RNA samples per strain with A260/280 ratios≥1.8 for cDNA synthesis with SuperScript III reverse transcriptase kit  using oligo dT primers. We designed real time PCR assays, hydrolysis probes, and gene specific primers that span long introns to distinguish cDNA from genomic DNA using primer design online software universal probe library (UPL) at www.roche-applied-science.com/sis/rtpcr/upl/index.jsp. We performed quantitative TaqMan PCR on light cycler LC480 . We used the mouse housekeeping gene, hypoxanthine guanine phosphoribosyl transferase (Hprt1) as an endogenous control to which we normalized gene expression data. Primer sequences are listed in We investigated the differential expression of target genes in spleen of infected vs. control PBS-injected mice at selected time points, we selected strains based on their susceptibility, BXD61 and 90 representing susceptible strains, and BXD73 and 87, representing resistant strains. We performed 2–3 biological replicates of each set of paired susceptible and resistant (n = 6–8 per strain). Mice were sacrificed 40 h post i.v. injection with 2±1.5×10www.ingenuity.com). Each data set containing gene identifiers was uploaded into the online application, and each gene was overlaid onto a molecular network developed from information contained in the ingenuity pathways database. Networks of genes were then generated based on their connectivity, and we chose the top 50 significant networks. The significance of the association between the data set and the pathways was measured in two ways: (1) the ratio of the number of genes from the data set that map to the pathway divided by the total number of genes that map to the pathway; and (2) by Fischer's exact test with P<0.001.We generated functional analyses of genes within the QTLs using Ingenuity pathways analysis (IPA) (www.datadesk.com) to calculate mean survival indices, corrected survival indices, and correlation coefficients. Covariates association was evaluated for significant associations by Spearman correlation as described previously We used the DataDesk 6.2 (www.genenetwork.org) under BXD published phenotypes record ID 10836.Our data sets stored in WebQTL can be found at Gene Network (Table S1Primer sequences used in quantitative PCR assays for candidate genes.(0.08 MB DOC)Click here for additional data file.Table S2Relative expression levels of candidate gene list expressed as mean fold difference between pre- and post-infection±standard deviation (SD) in selected resistant and susceptible strains.(0.09 MB DOC)Click here for additional data file.Table S3SNP analysis between parental strains C57Bl/6J and DBA/2J of selected genes in the mapped QTLs.(0.05 MB XLS)Click here for additional data file.


Hyperthermic chemotherapy applies thermal energy to both abdominal wall as well as the intra-abdominal viscera. The combination of the hyperthemia, chemotherapy and cytoreductive surgery (CRS) is associated with a defined risk of abdominal wall and intestinal morbidity reported to be as high as 15%, respectively to date, no studies have evaluated the use of biomaterial mesh as adjuvant to abdominal wall closure in this group of patients. In the present report, we hypothesized that post HIPEC closure with a biomaterial can reduce abdominal wall morbidity after CRS and hyperthermic intraperitoneal chemotherapy.All patients treated with HIPEC in a tertiary care center over 12 months (2008-2009) period were included. Eight patients received cytoreductive surgery followed by HIPEC for 90 minutes using Mitomycin C (15 mg q 45 minutes × 2). Abdominal wall closure was performed using Surgisis (Cook Biotech.) mesh in an underlay position with 3 cm fascial overlap-closure. Operative time, hospital length of stay (LOS) as well as postoperative outcome with special attention to abdominal wall and bowel morbidity were assessed.Eight patients, mean age 59.7 ys (36-80) were treated according to the above protocol. The primary pathology was appendiceal mucinous adenocarcinoma (n = 3) colorectal cancer (n = 3), and ovarian cancer (n = 2). Four patients (50%) presented initially with abdominal wall morbidity including incisional ventral hernia (n = 3) and excessive abdominal wall metastatic implants (n = 1). The mean peritoneal cancer index (PCI) was 8.75. Twenty eight CRS were performed (3.5 CRS/patient). The mean operating time was 6 hours. Seven patients had no abdominal wall or bowel morbidity, the mean LOS for these patients was 8 days. During the follow up period (mean 6.3 months), one patient required exploratory laparotomy 2 weeks after surgery and subsequently developed an incisional hernia and enterocutaneous fistula.The use of biomaterial mesh in concert with HIPEC enables the repair of concomitant abdominal wall hernia and facilitates abdominal wall closure following the liberal resection of abdominal wall tumors. Biomaterial mesh prevents evisceration on repeat laparotomy and resists infection in immunocompromised patients even when associated with bowel resection. Hyperthermic intraperitoneal chemotherapy (HIPEC) has emerged as an effective method of managing peritoneal carcinomatosis for different abdominal malignancies particularly of colorectal and ovarian origin -3. Most Multiple studies have reported that chemotherapy administration impairs wound healing and that there is associated increase in wound complications in chemotherapy exposed patients ,5. The eHIPEC impairment of wound healing is not limited to the abdominal wall, but also anastomosed segments of the gastrointestinal tract after cytoreductive surgery bowel resections. In small animal models, HIPEC was found to significantly decrease both colonic anastomotic bursting pressure and abdominal wall strength in association with decreased local protein production ,9. In clMoreover, postoperative bowel morbidity often required reoperation , in thisBiomaterial mesh has emerged as an attractive option for complex abdominal wall reconstruction providing an additional reinforcement to the abdominal wall with an absorbable material resistant to infection and with potential remodeling to host own tissue. Therefore, we used a biomaterial mesh to reinforce the abdominal wall closure at the end of CRS-HIPEC procedure. We hypothesized that this approach could minimize the rate of postoperative abdominal wall complications reported after CRS-HIPEC.Under institutional IRB approval, all patients treated with HIPEC at a tertiary care center over a12 months interval (2008-2009) period were identified using a prospectively maintained departmental database. Records were reviewed for preoperative, operative and postoperative data. Pertinent information for analysis included gender, age, primary malignancy, number of previous abdominal operations, peritoneal cancer index [®  database. Descriptive statistics, including means, standard deviations or counts and percentages were calculated.Data was recorded in a Microsoft ExcelAbdominal exploration was performed through midline laparotomy incision. Lysis of adhesions, when needed was performed, followed by assessment of the intra-abdominal extent of the disease and the peritoneal cancer index (PCI). Appropriate cytoreductive surgery was then performed with an attempt for complete removal of all macroscopic tumor deposits on parietal and visceral peritoneal surfaces and resection of involved viscera.After completion of the CRS, HIPEC was immediately performed during the same surgical procedure for all patients using a closed-abdomen technique Figure . Two inf®  solution containing Mitomycin C was obtained and maintained during the whole HIPEC time. Mitomycin C was used at a standard dose of 15 mg q 45 minutes × 2 for all patients. Hyperthermia was obtained by a heating unit in the cardiopulmonary bypass pump maintaining inflow temperature at 42°C, while the abdominal temperature was continuously checked by the needle probe to confirm a minimu of 41°C in the outflow. A total HIPEC time of 90 minutes was applied to all patients.After priming the circuit, a flow of 2.0-2.4 L/minute of DIANEAL PD-2, dextrose 1.5%At the end of the 90 minutes dwell time, the HIPEC solution was retrieved through the cardiopulmonary pump outflow catheters and disposed; the abdominal cavity was flushed with the effluent removed via the outflow catheters and the abdominal incision was reopened.® mesh . Abdominal wall closure was performed by the same surgeon performing the CRS-HIPEC procedure. Surgisis mesh was placed in underlay position and secured to the anterior abdominal wall using circumferential transfascial absorbable sutures (#1 PDS) 2 cm apart. When possible, the native fascia was closed over the Surgisis mesh using absorbable sutures and the skin was closed using skin stapler.The abdominal wall was closed using a 20 × 20 cm piece of SurgisisThe RWMC HIPEC program started on June 2008; over one year period eleven patients received HIPEC, including three patients who received totally laparoscopic HIPEC for persistent PET scan evident activity from colorectal cancer in the mesenteric or retroperitoneal lymph nodes after standard adjuvant chemotherapy. Eight patients received exploratory laparotomy, CRS and HIPEC and were included in this study (Table Patients' mean age was 59.7 years (36-80), M: F ratio was 1:1 and the origin of the primary malignant disease was colorectal (n = 4), appendiceal (n = 2) and ovarian (n = 2). All patients had prior abdominal surgeries and three patients had > two prior abdominal explorations. Peritoneal cancer index varied from 0-18 with a mean of 8.75. Prior to HIPEC therapy, four patients  presented with abdominal wall morbidities including incisional hernias (n = 3) and abdominal wall metastatic implants (n = 1).A total 28 CRS procedures were performed (average 3.5/patient). One third of the CRS included bowel resection-anastomosis  all performed by linear staplers.Mean total surgical procedure time was 5 h 49 minutes ± 1 h 10 minutes including 90 minutes devoted for HIPEC Table . There wOne patient required re-exploration two weeks after HIPEC procedure and subsequently developed incisional hernia and enterocutaneous fistula. This patient is a 59 year old patient with ovarian cancer and three prior abdominal surgeries including two debulking procedures. Prior to HIPEC procedure, the patient physical examination was significant for extensive abdominal wall metastatic implants.The patient PCI was 12 and CRS included bowel resection/anastomosis x2, splenectomy and abdominal wall resection. The patient post-operative period was marked by respiratory failure requiring reintubation. On post-operative day 15, a brown discharge was noted from the surgical incision and a decision for surgical re-exploration was made.Upon re-exploration, the previously placed Surgisis mesh was intact and easily dissected from the underlying bowel, prior anastomoses were intact and there was no evidence of gastrointestinal leak. Blood culture was obtained when the postoperative wound discharge was initially noted and intravenous antibiotic therapy was started imperatively with the hypothesis of sepsis. During re-exploration cultures from the peritoneal fluid were also obtained; both blood and peritoneal cultures did not support an infectious etiology. A dramatic lysis of residual tumor implants was noted producing a melted brown discharge. A new Surgisis mesh was placed and the fascia was closed as previously described. Subsequently, the patient developed wound dehiscence with no evisceration as well as enterocutaneous fistula. A negative pressure dressing was applied to the abdominal wound and the patient was discharged home three months after the HIPEC procedure.The introduction of biomaterial mesh had revolutionized the field of abdominal wall closure ,14. BroaSurgisis mesh was utilized in all open HIPEC procedures. This biomaterial mesh is composed of lyophilized porcine small intestinal submucosa, is known to attract cells to the wound area and signaling surrounding tissues to grow across the scaffold . The choAll Surgisis meshes were placed in underlay position with a minimum of a bilateral 3 cm fascial overlap-closure using absorbable number one PDS transfascial sutures placed circumferentially no more than two cm apart. Underlay repairs, such as Rivers-Stoppa retro-rectus repair, have been reported to result in improved recurrence rate and allow for re-approximation of the midline, thus potentially improving the mechanical function of the abdominal wall ,22.The HIPEC protocol employed was the well-described regimen of single agent (Mitomycin C) at a dose (15 mg q 45 minutes x2) with a cumulative dwell time of 90 minutes, for all patients regardless of the origin of the primary malignancy and the body surface area of the patient . The preSeven of eight patients included in this study did not develop abdominal wall or bowel/intra-abdominal morbidities postoperatively and were discharged home after a mean length of stay of eight days. A single patient did sustain the complication of suspicious for enterocutaneous fistula wound discharge with associated with respiratory failure 7 days after HIPEC necessitating re-exploration. Upon re-exploration, the integrity of the abdominal wall and gastrointestinal were verified. The Surgisis mesh was found intact and the bowel was easily dissected from the mesh as has been previously described in experimental models ,28. At oSubsequent to HIPEC, perioperative abdominal wall and bowel/intra-abdominal complications may require surgical exploration . In thisThe authors would emphasize the limitations of this study. This series represents early results of an abdominal wall reconstructive technique that in our experience was found to be safe and effective in preventing abdominal wall complications in a cohort of patients at high risk in the short term postoperative period. However, this report represents the experience of a single institution with a modest cohort and a short follow up. Long term follow up is needed before complete success for the use of biomaterial mesh can be declared to more define the role for biomaterial mesh in treatment and prevention of surgical site hernia following HIPEC and cytoreductive surgery. This may be limited by the inherent limited survival of many patients with disseminated peritoneal malignancy.In this small series biomaterial mesh was applied at the end of all CRS-HIPEC procedure and showed a beneficial effect in minimizing early postoperative abdominal wall complications. However, extrapolating these results to be applied to all CRS-HIPEC patients as a universal approach will probably reveal that only a group of high risk patients including those with multiple abdominal wall surgeries, preoperative abdominal wall hernia or metastatic implants to the abdominal wall will benefit from such approach.The selection of Surgisis mesh, was based on results of other studies reporting its resistant to infection and total remodeling in settings other than HIPEC. It will be necessary to document remodeling in this setting by histopathology incorporating tissue samples during the various stages of wound healing at distinct intervals after HIPEC with and without Surgisis mesh abdominal wall reconstruction.Finally, the HIPEC protocol used only Mitomycin C as single agent chemotherapy. Although, chemotherapeutic agents share an inhibitory effect on wound healing, it is possible, although not yet investigated that in the setting of HIPEC, that this known inhibitory effect varies significantly between different agents.In this series, the use of a biomaterial mesh for abdominal wall reconstruction following CRS and HIPEC enabled the repair of concomitant abdominal wall hernias and facilitated liberal resection of abdominal wall tumors. Biomaterial mesh prevented evisceration on repeat laparotomy and resists infection in immunocompromised patients even when associated with bowel resection.The senior author, Dr. Espat has previously received honoraria from Cook as a speaker.CB assisted with acquisition of data and drafting the manuscript, PS assisted with revision of the manuscript, NJE assisted with study design and revision of the manuscript. All authors read and approved the final manuscript


Arabidopsis thaliana miRNA families; this has been achieved using artificial miRNA target mimics, a recently developed technique fashioned on an endogenous mechanism of miRNA regulation. Morphological defects in the aerial part were observed for ∼20% of analyzed families, all of which are deeply conserved in land plants. In addition, we find that non-cleavable mimic sites can confer translational regulation in cis. Phenotypes of plants expressing target mimics directed against miRNAs involved in development were in several cases consistent with previous reports on plants expressing miRNA–resistant forms of individual target genes, indicating that a limited number of targets mediates most effects of these miRNAs. That less conserved miRNAs rarely had obvious effects on plant morphology suggests that most of them do not affect fundamental aspects of development. In addition to insight into modes of miRNA action, this study provides an important resource for the study of miRNA function in plants.Many targets of plant microRNAs (miRNAs) are thought to play important roles in plant physiology and development. However, because plant miRNAs are typically encoded by medium-size gene families, it has often been difficult to assess their precise function. We report the generation of a large-scale collection of knockdowns for  Arabidopsis thaliana and have observed their effects on plant development. We found that deeply conserved miRNAs tend to have a strong impact on plant growth, while more recently evolved ones had generally less obvious effects, suggesting either that they primarily affect processes other than development, or else that they have more subtle or conditional functions or are even dispensable. In several cases, the effects on plant development that we observed closely resembled those seen in plants expressing miRNA–resistant versions of the major predicted targets, indicating that a limited number of targets mediates most effects of these miRNAs. Analyses of mimic expressing plants also support that plant miRNAs affect both transcript stability and protein accumulation. The artificial target mimic collection will be a useful resource to further investigate the function of individual miRNA families.MiRNAs are small RNA molecules that play an important role in regulating gene function, both in animals and in plants. In plants, miRNA target mimicry is an endogenous mechanism used to negatively regulate the activity of a specific miRNA family, through the production of a false target transcript that cannot be cleaved. This mechanism can be engineered to target different miRNA families. Using this technique, we have generated artificial target mimics predicted to reduce the activity of most of the miRNA families in  MicroRNAs (miRNAs) are a class of small RNA (sRNA) molecules that has recently emerged as a key regulator of gene activity. In plants, miRNAs are released from larger precursors (pri-miRNAs) in the nucleus mainly, by DICER-LIKE1 (DCL1) IPS1 (INDUCED BY PHOSPHATE STARVATION 1) encodes a non-coding RNA with a short motif that is highly complementary to the sequence of miR399, which like IPS1 is involved in the response to phosphate starvation IPS1 sequence contains a three-nucleotide insertion in the center, corresponding to the position where normally miRNA-guided cleavage takes place, and this bulge in the miRNA/target pair prevents endonucleolytic cleavage of IPS1 transcripts. This results in sequestration of RISCmiR399, leading to a reduction of miR399 activity. A similar phenomenon, negative regulation of small RNA activity by a partially complementary mRNA, has been recently described in bacteria as well The spatio-temporal expression pattern of miRNA genes is regulated to a large extent at the transcriptional level, and different members of a miRNA family can have distinct, specialized expression domains MiRNA target mimicry can be exploited to study the effects of reducing the function of entire miRNA families Arabidopsis thaliana miRNA families. One fifth of these lines have obvious morphological defects, which is in the same range as the approximately 10% of miRNA knockouts that caused phenotypic abnormalities or lethality in Caenorhabditis elegansHere, we present a collection of transgenic plants expressing artificial target mimics designed to knockdown the majority of Arabidopsis thaliana plants under the control of the constitutive 35S CaMV promoter. As described IPS1. The different constructs, and the corresponding transgenic lines, are named “MIM”, followed by the numeric identifier of the targeted miRNA family or subfamily. We targeted all miRNA families reported in miRBase (http://microrna.sanger.ac.uk/sequences/index.shtml) and ASRP (http://asrp.cgrb.oregonstate.edu) Arabidopsis thaliana and Arabidopsis lyrataMIM constructs, and the primer pairs used to generate them, can be found in We generated artificial target mimics for 73 different families or subfamilies of miRNAs and expressed them in PPR gene family A single artificial target mimic could be designed for most miRNA families. The mature miRNAs produced by members of the miR169 and miR171 families differ slightly, and different target mimics were designed for these subfamilies. Two target mimics were also designed for the miR161 family, which produce two mature miRNAs that have only partially overlapping sequences, and that target similar subsets of the IPS1 in MIM172 could have reconstituted a cleavage site for miR172. Consistent with such modifications being important, plants expressing the appropriately modified version of MIM172 showed an altered phenotype (see below), whereas plants expressing an initial version of MIM172 in which a putative miR172 cleavage site was present (MIM172cs) did not. Moreover, plants expressing a MIM172 version with only a single-nucleotide mismatch corresponding to position 11 of the mature miRNA (MIM172sn) did not show any abnormal phenotype either, suggesting that the three-nucleotide bulge is required for target mimic activity  leaves in long days, compared to 13.0±0.9 rosette leaves in wild-type plants  rosette leaves in long days . In contrast to plants that express a non-targetable version of AP2MIM172 plants were normal. These differential effects could be due to the particularly high levels of miR172 levels during early flower development ong days , consistMIM393 plants had mild defects in leaf morphology, with narrow leaves that were curled downward  reporter; stable recruitment of RISCmiR399 to the mimic site could be expected to interfere with EYFP translation. In 80% of MIM159 expressing T1 plants, as in control plants, the EYFP transgene was completely silenced. In the remaining 20%, we detected EYFP signal that was strongly reduced in the region where MIR159 genes are known to be expressed  genes. Certain mutations in the miR398 complementary motif site reduced the effects of miR398 on CSD mRNA, but not on protein levels It has recently been suggested that plant miRNAs could also repress the translation of target mRNAs that have only limited sequence complementarity, as often happens in animals Nevertheless, as pointed out before se-1, ago1-27, and hyl1-2 and dcl1-100 mutants have been described MIM834 plants were grown on MS media plates supplemented with 1% sucrose for 14 days in long days at 23°C. Plants overexpressing viral proteins Hc-Pro, P0, P19 and P21 were a kind gift from the Carrington lab.Plants were grown on soil in long days (16 h light/8 hours dark) under a mixture of cool and warm white fluorescent light at 23°C and 65% humidity. The IPS1 gene MYB33:GUS reporter, a MYB33 genomic fragment was PCR amplified, cloned into the TOPO-PCR8 Gateway vector (Invitrogen), and recombined through LR clonase reaction into pGWB433 MIM159 construct was introduced into three independent MYB33-GUS T2 lines. A MIM159 site was placed in the 3′-UTR of a triple-EYFP sequence linked to a fragment encoding a nuclear localization signal (NLS) and driven by a CaMV 35S promoter. Constructs were introduced into A. thaliana (accession Col-0) plants by Agrobacterium tumefaciens-mediated transformation Artificial target mimics were generated by modifying the sequence of the Nine-day-old seedlings from three independent T2 lines for all the GUS reporter backgrounds were fixed in acetone 90%. GUS activity was assayed as described MIM172 lines), using TRIzol Reagent (Invitrogen). For dcl-100, 13-day old seedlings were collected, to obtain a similar developmental stage compared to the other plants. For real time RT-PCR, two biological replicates with tissue pooled from 8 to 10 plants were assayed from two independent MIM lines per miRNA family or subfamily. Complementary DNA was produced with the RevertAid First Strand cDNA Synthesis Kit (Fermentas), using as starting material 4 µg of total RNA that had been treated with DNase I (Fermentas). PCR was carried out in presence of SYBR Green (Invitrogen) and monitored in real time with the Opticon Continuous Fluorescence Detection System (MJR). Oligonucleotide primers are given in Total RNA was extracted from 11-day old seedlings and 30-day old inflorescences . Protein concentration was measured using a commercial Bradford assay (BioRad). 50 µg of raw protein extract per sample were resolved on an 8% acrylamide gel. Blotting and antibody incubation were performed as described http://rsbweb.nih.gov/ij/).Proteins were extracted from four Figure S1MIM167 and MIM172 plants. Five-week-old, long-day grown plants expressing MIM167 (A) and MIM172 (B) next to wild-type Col-0 plants on the left.Flowering behavior of (0.89 MB PDF)Click here for additional data file.Figure S2MIM167 plants and Col-0 controls. Distribution of flowering times of primary transformants of plants transformed with MIM167 or empty pGREEN binary vector, grown at 23°C in long days.Flowering time of (0.09 MB PDF)Click here for additional data file.Figure S3MIM lines. Transcript levels of select miRNA targets in two independent lines for each MIM construct (represented by bars of different shades of gray). Expression levels are reported as the average of two biological and two technical replicates, and are normalized to the expression levels in wild-type Col-0 plants (dotted line).Expression of miRNA targets in inflorescences of (0.10 MB PDF)Click here for additional data file.Table S1MIM constructs.Oligonucleotide primers used to modify the IPS1 sequence in (0.11 MB PDF)Click here for additional data file.Table S2Oligonucleotide primers for qRT-PCR.(0.07 MB PDF)Click here for additional data file.


The rising temperature of the world's oceans has become a major threat to coral reefs globally as the severity and frequency of mass coral bleaching and mortality events increase. In 2005, high ocean temperatures in the tropical Atlantic and Caribbean resulted in the most severe bleaching event ever recorded in the basin.Satellite-based tools provided warnings for coral reef managers and scientists, guiding both the timing and location of researchers' field observations as anomalously warm conditions developed and spread across the greater Caribbean region from June to October 2005. Field surveys of bleaching and mortality exceeded prior efforts in detail and extent, and provided a new standard for documenting the effects of bleaching and for testing nowcast and forecast products. Collaborators from 22 countries undertook the most comprehensive documentation of basin-scale bleaching to date and found that over 80% of corals bleached and over 40% died at many sites. The most severe bleaching coincided with waters nearest a western Atlantic warm pool that was centered off the northern end of the Lesser Antilles.Thermal stress during the 2005 event exceeded any observed from the Caribbean in the prior 20 years, and regionally-averaged temperatures were the warmest in over 150 years. Comparison of satellite data against field surveys demonstrated a significant predictive relationship between accumulated heat stress  and bleaching intensity. This severe, widespread bleaching and mortality will undoubtedly have long-term consequences for reef ecosystems and suggests a troubled future for tropical marine ecosystems under a warming climate. Satellite-based sea surface temperature (SST) observations from the U.S. National Oceanic and Atmospheric Administration (NOAA) NOAA's Coral Reef Watch (CRW) developed and maintains a suite of operational satellite sea surface temperature (SST)-based products that provide coral bleaching nowcasts and alerts NOAA measured sustained thermal stress in 2005 that exceeded 16°C-weeks in some regions, far greater than the thresholds that have usually been associated with the onset of mass coral bleaching (DHW  = 4°C-weeks) and mortality (DHW  = 8°C-weeks) The timeline for the geographic spread of the 2005 Caribbean thermal stress was decomposed into seven major phases as identified in i.e., states, territories) in 22 countries  deployed throughout the region to monitor the bleaching event as it developed, and subsequently to monitor coral mortality. Coral bleaching, other disease conditions, and mortality extended across the entire Caribbean – bleaching was especially intense along the Antilles , and wasountries . After qMillepora alcicornis and Montastraea cavernosa colonies; and the first reported mass bleaching of Acropora palmata in Virgin Islands National Park (VINP), a species listed as threatened under the US Endangered Species Act (ESA) since 2006 Several species and sites were reported to bleach for the first time, including: the first known bleaching at Saba; the first documented mass bleaching of the Flower Garden Banks, including at least partial bleaching of all Surveys conducted from the peak of thermal stress through January 2007 were analyzed to assess coral mortality. Detailed and repeated monitoring revealed that a combination of bleaching and other disease outbreaks killed coral colonies stressed by high temperatures A. palmataA. palmata also revealed that bleached corals suffered greater disease-associated mortality than unbleached colonies, indicating that disease severity was dependent on host susceptibility Montastraea annularis species complex, which are now under consideration for ESA protection In the Florida Keys in 2005, bleaching was less severe than in the Caribbean proper. However, increased temperatures were quickly followed by a loss of resistance to pathogenic disease and an increased abundance of microbial pathogens in e.g., hydrodynamics, light, community composition). Consistent with CRW's previously established bleaching levels, significant coral bleaching began near 4°C-weeks . Despite local variability, thermal stress values exceeding approximately 8°C-weeks successfully predicted significant mortality. Thermal stress of this magnitude should be weighed carefully by reef managers. In 2005, little mortality was seen below 8°C-weeks of thermal stress while above it there was an ecologically important 1-in-3 risk of mortality. The slow rate of recovery seen in Caribbean reefs In the areas where thermal stress levels were less than 8°C-weeks, significant mortality was rare  was attributable to monotonic climate change, while only 0.2°C was attributable to the weak 2004–05 El Niño, and even less to the Atlantic Multi-decadal Oscillation (<0.1°C). Despite the lack of strong tropical forcing, 2005 fell among the warmest years on record Unlike many past Caribbean bleaching years, strong tropical climate forcing was only a minor driver of Caribbean SSTs in 2005. In their analysis of temperature anomalies across the tropical North Atlantic in 2005, Trenberth and Shea Dennis, Emily, Katrina, Rita, Wilma) were strong enough to reduce the Caribbean-average HotSpots  thermal stress products used in this study were based on nighttime-only Advanced Very High Resolution Radiometer (AVHRR) sea surface temperature (SST) data from sensors aboard operational NOAA Polar-Orbiting Environmental Satellites (POES), produced in near-real-time at 0.5-degree (50-km) spatial resolution. SST anomalies compared the measured temperature with the expected value at that time of year for each pixel. HotSpots were computed as positive anomalies above the mean temperature of the climatologically warmest month at each satellite data pixel, based on the NOAA operational climatology from years 1985–1990 and 1993. Degree Heating Weeks (DHWs) for any given time accumulated HotSpot values ≥1°C over the preceding 12-week period The DHW map  includedCRW operational products were first made available on 12-Sep-2000. The 22-year time series of annual maximum DHW  was prodn) and total number of colonies surveyed (N), or both; and/or 2) measures of coral mortality as coral cover dead (%), number of coral colonies dead (n) and total number of colonies surveyed (N), or both; 3) average observation depth (m); 4) observation date; and 5) observation location, including latitude, longitude, and reef site name. Data were quality controlled to exclude observations that met any of the following criteria: 1) bleaching observations taken before the onset of thermal stress ; 2) bleaching observations taken after subsidence of thermal stress, defined as the 90th day following the date of the last No Stress alert in 2005; and 3) mortality observations taken before the maximum DHW value occurred in 2005. Multiple observations (quadrats or transects) taken at any reef site on the same date and depth (±5 m) were combined into a single survey of either means of percent cover data or proportion of the number of colonies surveyed. The 2575 bleaching surveys used in this analysis  measures of coral bleaching as coral cover bleached (%), number of coral colonies bleached . Given the variability of monitoring techniques employed, sampling errors within each technique, and local factors at individual reef sites , the explicative power of the satellite metric  supported the predictive relationship between the thermal stress monitored by CRW satellite products and the observed bleaching during this event. However, it was clear that inclusion of other information, including higher spatial resolution SST-based products, may further refine bleaching predictions in the future.Operational satellite products from the co-located (or next-nearest) satellite pixel were compared with all field observations . A lineai.e., the maximum DHW) within a pixel and were analyzed against the maximum thermal stress . Surface temperatures in this region remained above climatological values throughout the May-December period, with no respite from thermal stress  averaged across the 0.5-degree pixels that contained or were nearest Caribbean reef locations . The ‘+’ symbols indicate the average climatological temperature during each month and the dashed line shows the maximum of these, an indication of the expected warmest  temperature. The SST trace shows that, on average, temperatures around Caribbean reefs exceeded climatological values by close to 1°C for a period of more than four months. The magnitude and extended duration of the basin-wide thermal anomaly resulted in widespread coral bleaching and lowered the ability of corals to resist other disease conditions.(0.69 MB ZIP)Click here for additional data file.Figure S2Animation of the development of thermal stress during the 2005 Caribbean bleaching event, measured using NOAA Coral Reef Watch Degree Heating Week product from 4 June 2005 to 14 February 2006 with a pause during the peak of the event at 28 October 2005.(5.54 MB TIF)Click here for additional data file.Figure S3Locations of 2575 bleaching surveys submitted from sites across the greater Caribbean region. Colors denote number of surveys at each of the 1212 sites. See (0.18 MB TIF)Click here for additional data file.Figure S42 = 0.26; colonies slope  = 3.43, intercept  = 29.46, df  = 304, p<0.0001, r2 = 0.24) and indicated no difference in slopes, suggesting comparable results.Comparison of bleaching survey methods. All observations of percent coral colonies (gray circles) and cover (black diamonds) are plotted versus observed Degree Heating Week (DHW). Linear regressions for colonies (gray line) and cover (black line) were highly significant Click here for additional data file.Table S1Complete data record for all survey data used in the analyses. Multiple observations from the same reef site, date and depth (±5 m) were combined as either means of percent cover data or proportion of the number of colonies surveyed to provide 2575 bleaching surveys and 1077 mortality surveys.(0.17 MB PDF)Click here for additional data file.


Drosophila systems). We also included in the comparison the TRE promoter, which can be activated by the rtTA transcriptional activator in a doxycycline-inducible manner. To make our findings representative, we conducted the comparison in a variety of cell types derived from several species. We found that these promoters vary considerably from one another in their strength. Most promoters have fairly consistent strengths across different cell types, but the CMV promoter can vary considerably from cell type to cell type. At maximal induction, the TRE promoter is comparable to a strong constitutive promoter. These results should facilitate more rational choices of promoters in ectopic gene expression studies.Constitutive promoters are used routinely to drive ectopic gene expression. Here, we carried out a systematic comparison of eight commonly used constitutive promoters (SV40, CMV, UBC, EF1A, PGK and CAGG for mammalian systems, and COPIA and ACT5C for  While a number of studies have evaluated the strengths of these promoters in various cellular contexts Drosophila systems, including copia transposon promoter (COPIA) and actin 5C promoter (ACT5C). Finally, we included in the comparison the doxycycline-inducible system with reverse tetracycline-controlled transactivator (rtTA) and tetracycline-responsive element promoter (TRE).Many constitutive promoters are used to drive ectopic gene expression in various Drosophila promoters, we used two Drosophila melanogaster cell lines, including the ML-DmBG3-c2 cell line (C2) derived from larval central nervous system We investigated these promoters in multiple cell lines derived from several species to get a general sense of their behaviors. For the mammalian promoters, we used mouse tail fibroblasts (129TF), mouse embryonic fibroblasts (MEF), mouse myoblasts (C2C12), rat mesenchymal stem cells (MSC), human fibroblasts (MRC5), human fibrosarcoma cells (HT1080), human embryonic kidney cells (293T), and rhesus macaque mammary tumor cells (CMMT). For e.g., 293T and CMMT) and rather weak in others . This variability is consistent with the silencing of this promoter in some cells as reported before For the six mammalian constitutive promoters, each one was inserted into a lentiviral expression vector in front of the GFP reporter Drosophila cells. In our hands, lentiviral transduction killed Drosophila cells. We therefore used conventional transient transfection to deliver the vectors into the cells. We took care to use identical transfection conditions so as to achieve comparable transfection efficiencies between the COPIA-containing construct and the ACT5C-containing construct. The two promoters produced similar GFP signals in C2 and S2R+ cells, with ACT5C being slightly stronger than COPIA  with a vector carrying the rtTA gene driven by the EF1A promoter. This vector also carries neomycin resistance, which was used to select for transduced mammalian cells. A range of doxycycline concentrations were used to induce the TRE promoter, followed by flow cytometry analysis of GFP intensity  reached plateau at a much lower doxycycline concentration. The maximum expression level from the TRE promoter in any of the cell types is comparable to, or only slightly less than, a strong constitutive promoter such as EF1A or CAGG in that cell type  using the same conditions. We observed that doubly infected cells (which display both GFP and RFP) represented <5% of total infected cells. Drosophila cells were treated one day after transient transfection. Gene expression was induced within 12 hours and becomes stable after another day of treatment.For doxycycline induction of the TRE promoter, mammalian cells are treated with doxycycline right after drgu selection while Flow cytometry analysis was carried out on populations (as opposed to clones) of cells. GFP fluorescence was measured on a BD LSR II machine, with all the cells measured under the same machine parameters. Each cell type and promoter combination was done with three independent replicas, and each cytometric measurement was done on 100,000 cells.Text S1Promoter sequences.(0.03 MB DOC)Click here for additional data file.


Multiple discrete regions at 8q24 were recently shown to contain alleles that predispose to many cancers including prostate, breast, and colon. These regions are far from any annotated gene and their biological activities have been unknown. Here we profiled a 5-megabase chromatin segment encompassing all the risk regions for RNA expression, histone modifications, and locations occupied by RNA polymerase II and androgen receptor (AR). This led to the identification of several transcriptional enhancers, which were verified using reporter assays. Two enhancers in one risk region were occupied by AR and responded to androgen treatment; one contained a single nucleotide polymorphism (rs11986220) that resides within a FoxA1 binding site, with the prostate cancer risk allele facilitating both stronger FoxA1 binding and stronger androgen responsiveness. The study reported here exemplifies an approach that may be applied to any risk-associated allele in non-protein coding regions as it emerges from genome-wide association studies to better understand the genetic predisposition of complex diseases. Genome-wide scans of inherited genetic variation in the normal population have recently identified many sites (loci) associated with the predisposition to complex diseases such as cancer. Some of these cancer-associated loci, however, are devoid of genes  and the mechanism(s) of the association are not readily apparent. In the work reported here, we show that loci associated with several cancers in a gene desert found at chromosomal area 8q24 have embedded regulatory sequences affecting gene expression as enhancers, and in one case this activity is modulated by genetic variation. The results provide insight into the mechanism(s) governing genetic cancer risk. Chromosome 8q24 is an established risk locus for many common epithelial cancers. The region was originally discovered by fine-mapping of a prostate cancer linkage peak from a family-based study by deCODE genetics in cis. The ENCODE project and the recent reports on long noncoding RNAs Since the consequences of sequence changes in non protein-coding regions of the genome are more difficult to predict than changes in coding regions, defining the mechanisms by which the 8q24 alleles confer risk has so far been challenging. Another complication is that genetic variants discovered through association studies are rarely the actual causal variant, since they may be associated with disease risk simply due to linkage disequilibrium, which sometimes extends over relatively large distances in the human genome. Because of these factors, understanding the mechanisms that increase cancer risk requires an integrated and systematic approach. One hypothesis is that the 8q24 alleles affect the sequence of unannotated transcripts (e.g. noncoding RNAs or unknown protein-coding genes) or change the regulation of such transcripts Post-translational modifications of histones  have proven useful in annotating sites of regulatory activity in the human genome. Histone 3 acetylation (AcH3) is typically associated with chromatin accessibility and transcriptional activity, and widely used for the prediction of functional elements such as promoters and enhancers The overall objective of this study was to systematically evaluate the possible role(s) of regions within the 8q24 genomic risk interval, overcoming the aforementioned difficulties using a combination of epigenetic, bioinformatic, and molecular biological analyses on multiple cell lines and tissue samples. We report here two main findings: (i) evidence is presented that certain 8q24 risk regions exhibit minimal RNA transcriptional output but bear the markers of regulatory elements that are functionally active as enhancers. (ii) More specifically, we demonstrate that a new androgen-dependent enhancer in one of the prostate cancer risk regions is functionally influenced by a risk-associated single nucleotide polymorphism (SNP) via differential FoxA1 binding.A high resolution tiling array comprising 5-megabases (Mb) of 8q24 was designed and probed with cDNA from cancer cell lines and normal tissue, as well as with DNA obtained by chromatin immunoprecipitation (ChIP) using antibodies for histone modifications and transcription factors. We reasoned that the combination of a focused transcriptional map and a high-resolution epigenomic profile To study the transcriptional landscape at the 8q24 region, we generated double-stranded cDNA from 20 normal prostate tissue samples, the prostate cancer cell lines LNCaP and PC3, the colon cancer line HCT116 and the breast cancer line MCF7. We hybridized each of these cDNA samples to our custom tiling array and normalized the probe intensity values against their genomic DNA background. As shown in In parallel, we generated high-resolution epigenomic profiles for the entire 5-Mb interval using ChIP-chip. For this purpose we hybridized ChIP material to the same tiling array used earlier for transcriptional profiling. Initially, we analyzed AcH3 in three cell lines representing prostate (LNCaP), breast (MCF7) and colorectal (HCT116) cancer. Because three regions independently impose prostate cancer risk, we also interrogated two prostate cancer cell lines (PC3 & LNCaP) more extensively for other key epigenetic marks at high resolution. Additional histone modifications chosen were the activation marks H3K4me1 & H3K4me3 Spatial clustering of the 5-Mb region surrounding and including the 8q24 risk loci is shown in in cis or remote active transcriptional units in trans. We note that we could not rule out the possibility of small non-coding RNAs being transcribed from the region, since RNA species shorter than 200-bp were excluded from our preparation. In order to investigate the regulatory potential of the loci exhibiting active chromatin marks, we next performed a systematic series of heterologous enhancer assays, focusing initially on defined acetylation peaks contained within the cancer risk intervals  minimal promoter. Enhancer activities of the fragments were determined by transient transfection and luciferase assays in LNCaP & PC3 (prostate cancer cells), HCT116 & COLO 205  and MCF7 (breast cancer cells)  . AcP6 . Through this effort we identified two SNPs in AROR15 that were strongly correlated with the risk variant rs10090154 (reported in What are the mechanism(s) that govern the SNP effect on the DHT-mediated enhancer activity described above? Interestingly, the SNP at rs11986220 resides within a putative binding site for forkhead transcription factors, with the A allele better matching the consensus sequence . An intein vivo enhancer activity from this region.Since the histone acetyl transferase and transcriptional coactivator p300 accurately predicts enhancer activity at many loci To follow up on our functional assays, we next genotyped rs11986220 in prostate cancer cases and controls from five ethnic populations in the Multiethnic Cohort . The frequency of the A allele and the magnitude of the association was the same as those of the T allele of rs10090154  in European Americans, Latinos, Native Hawaiians and Japanese , but notA main question remaining is what are the gene targets of our identified enhancers? We suspect that they loop to their target(s) at some distance. Such looping in the three dimensional space of the nucleus may represent the underlying mechanism of transcriptional regulation Since transcript abundance is a heritable trait, associations between risk allele status and mRNA transcript levels can serve as a powerful way to evaluate potential candidate genes. Recently, our group studied the association between 6 prostate cancer risk alleles at the 8q24 locus and MYC mRNA expression in prostate tissue. A large number of specimens (280) were evaluated  and no association was observed With the advent of genome-wide associations of alleles with major diseases, the challenge of characterizing the biological function that is associated with the genomic region of interest is becoming more acute than ever. This challenge is particularly difficult when risk alleles are not located near annotated genes. We need to establish methodologies that can comprehensively and rapidly characterize the main genomic features in a region of interest, which can then be used to lay the foundation for follow-up studies that may lead to the uncovering of disease mechanisms. Here we have shown how the combination of high-density tiling arrays, transcript and epigenetic profiling, and computational analysis can facilitate functional characterizations, which may be tested directly with molecular biology techniques. Accordingly, we used the above-mentioned approach to identify how prostate cancer risk SNPs may affect enhancer activity at the gene-poor 8q24 region. Our chromatin analyses narrowed the location of putative functional domains to regions less than 1.5-kb in size, containing gene enhancers that may influence cancer risk via regulation of gene expression at a distance. We verified that gene regulation is involved by using reporter assays and further showed that the androgen-responsive activity of a strong enhancer in region 1 is affected by a SNP (rs11986220) associated with prostate cancer risk.LNCaP and PC3 cells were maintained in RPMI 1640 supplemented with 5% (v/v) fetal bovine serum (FBS). HCT 116 and COLO 205 cells were cultured in McCoy's 5A with 10% FBS, and MCF7 cells were cultured in DMEM with 10% FBS. All cell lines were obtained from the American Type Culture Collection , except PC3 cells, originally from ATCC, which were derived by us as strongly AR-transcriptionally competent, although not expressing functional AR ChIP analyses were performed as described previously About 100 µg total RNA was extracted from each cell line  using Aurum Total RNA Kit (Bio-Rad). Ribosomal RNA (rRNA) was depleted using RiboMinus Transcriptome Isolation Kit (Invitrogen) according to manufacturer's protocol. About 5 µg double strand cDNA was made from recovered RNA after rRNA depletion using Superscript Double-Stranded cDNA Synthesis Kit (Invitrogen), and then submitted to NimbleGen, Inc. along with 5 µg sonicated genomic DNA (size between 500–2000 bp) from each cell line as a reference. The DNA samples were labeled and hybridized to the same custom tiling array used in ChIP-chip.Twenty fresh frozen radical prostatectomy (RP) samples were derived from an institutional review board-approved study cohort at Dana-Farber Cancer Institute (DFCI) Array data were normalized by estimating the curve of log channels intensity ratio [log(cy5/cy3)] as a function of the control channel [usually log(cy3)]. This curve was subtracted from the observed log intensity ratio and used in subsequent analysis. We also computed the effect of variable probes' G+C content on the array binding ratios, but decided not to use this for further normalization due to the relatively small region covered by the array and the danger of systematic biases. We note that the RNA hybridization readouts were distributed in a highly non-normal fashion, with a significant fraction of the probes covering intronic regions and having higher than average readouts, and a smaller fraction of the probes covering exonic regions that are highly enriched. Since the study focused on a very high resolution mapping of a region that include only a few genes, we decided not to explicitly model RNA data as the product of some putative exonic structure, but focused on an unsupervised analysis of a combined dataset that included both RNA and ChIP data.The spatial clustering algorithm is an unsupervised hidden markov model (HMM)-based method that identifies a set of common pattern in multi-dimensional data that is defined over contiguous genomic segments. The method uses a probabilistic model describing a set of states (clusters in this case) and the probability of transitioning to a particular state Y given that one is presently at state X . Each cluster defines a distribution of values for the measured data tracks and an algorithm assigns each data instance (the measurements for each track at a given locus in the genome) to the cluster that describes it best. The algorithm iteratively updates the distributions defined by the clusters, the data points assigned to the clusters, and the transition probabilities from one cluster to another, until all data points are assigned to clusters that describe them well and which are highly likely to self-transition. This last property ensures that data points representing adjacent regions in the genome are likely to belong to the same cluster, maintaining the biological tendency of contiguous genomic regions to behave similarly. To dissect the 8q24 into regions with distinct epigenomic behaviors we used our recently described implementation of the algorithm firefly-luciferase vector in both directions. All clones were confirmed by sequencing. The primers for subcloning are listed in Renilla luciferase plasmid (Promega) using Lipofectamine LTX Reagent (Invitrogen) according to the manufacturer's protocol. Dual luciferase activities were measured as previously described p-values between alleles were calculated using the student t-test.Fifteen enhancer candidates (∼1500-bp sequence surrounding the AcH3 peak center) and three ARORs (∼500 bp sequence surrounding the AROR peak center) were amplified from LNCaP genomic DNA using High Fidelity Platinum Tag DNA polymerase (Invitrogen). The amplified sequences were then subcloned in either the KpnI or Sac II restriction sites upstream of a thymidine kinase (TK) minimal promoter-Whole cell extracts were prepared from LNCaP cells, cultured in 5% FBS RPMI 1640, and EMSA was performed all as previously described Figure S1Shown are the cumulative distributions of RNA array signal (LNCaP data) for intergenic, intronic and exonic probes. The data show that our data is sensitive to the difference between strongly expressed spliced RNAs, pre-spliced unprocessed transcripts and untranscribed, intergenic sequence.(0.04 MB PDF)Click here for additional data file.Figure S2Possible transcription around the POU5F1 gene fragment. Shown are RNA array readouts in region 3 and the Breast cancer associated locus. Probes at the POU5F1 are enriched in all cell types and in normal prostate tissue, possibly reflecting cross hybridization from the original POU5F1 gene. In LNCaP and in the prostate tissues we also observe RNA signal from strictly unique probes (see the self-chain track in the lower part of the figure) around the POU5F1 fragment and in other proximal probes that were also associated before with spliced ESTs. This suggests that some transcription may be originating from a long region involving risk region 3 and the breast cancer linked region.(0.17 MB PDF)Click here for additional data file.Figure S3Significance of H3K27me3 domains. Shown are aggregate statistics from Kolmogorov-Smirnov tests performed on the H3K27me3 distributions in LNCaP and PC3. For each probe, the distribution of log(IP/input) values centered on that probe and within a window of given size was compared to the distribution of all the values outside the window. The color-coded p-values indicate the significance of the dissimilarity between that window and the rest of the 5 Mb region. Each row within a cell-line corresponds to a different window size . High p-values indicate the presence of significant H3K27me3 domains, with the right-most domain appearing only in LNCaP.(0.13 MB PDF)Click here for additional data file.Figure S4http://www.cbil.upenn.edu/cgi-bin/tess/tess). A potential FoxA1/HNF3α binding site coincided with rs11986220, with the A allele forming a more perfect FoxA1/HNF3α binding site than the T allele.Fifty-bp DNA sequences centered on rs11986220 were scanned for transcription factor binding motifs using Transcription Element Search System (TESS) website ((0.06 MB PDF)Click here for additional data file.Figure S5P300 occupancies AROR15. LNCaP cells were cultured in 5% FBS RPMI 1640 media for 3 days. ChIP analyses were performed using antibody against p300 . DNA samples from ChIP preparation were quantified by qPCR using TaqMan PCR Master Mix (Applied Biosystems). Data were average of triplicate qPCR determinations. The relative enrichment of p300 at PSA enhancer (positive control) and AROR 15 was normalized against neighboring 8q24 control region (negative control defined as 1).(0.03 MB PDF)Click here for additional data file.Table S1Oligonucleotide sequences.(0.02 MB XLS)Click here for additional data file.


BG01805E74, was found to confer an early-eclosion phenotype reminiscent of that displayed by a mutant with decreased LARK gene dosage. Molecular analyses demonstrate that E74A protein shows diurnal changes in abundance, similar to LARK. In addition, the BG01805E74 allele enhances the lethal phenotype associated with a lark null mutation, whereas overexpression of LARK suppresses the early eclosion phenotype of BG01805E74, consistent with the idea that E74 is a target, in vivo. Our results suggest a model wherein LARK mediates the transfer of temporal information from the molecular oscillator to different output pathways by interacting with distinct RNA targets.Despite substantial progress in defining central components of the circadian pacemaker, the output pathways coupling the clock to rhythmic physiological events remain elusive. We previously showed that LARK is a Drosophila RNA-binding protein which functions downstream of the clock to mediate behavioral outputs. To better understand the roles of LARK in the circadian system, we sought to identify RNA molecules associated with it, in vivo, using a three-part strategy to (1) capture RNA ligands by immunoprecipitation, (2) visualize the captured RNAs using whole-genome microarrays, and (3) identify functionally relevant targets through genetic screens. We found that LARK is associated with a large number of RNAs, in vivo, consistent with its broad expression pattern. Overexpression of LARK increases protein abundance for certain targets without affecting RNA level, suggesting a translational regulatory role for the RNA-binding protein. Phenotypic screens of target-gene mutants have identified several with rhythm-specific circadian defects, indicative of effects on clock output pathways. In particular, a hypomorphic mutation in the E74 gene,  Neurospora to define clock-controlled genes  the intrinsic pacemaker to environmental cues, and output pathways that couple the clock to individual physiological processes. In recent years, there has been significant progress towards understanding clock entrainment mechanisms and the molecular es CCGs, . More reRNA Recognition Motif (RRM) class of RNA binding proteins, and more specifically defines a class of RRM proteins containing a retroviral-type zinc finger Several RNA-binding proteins with presumed post-transcriptional roles in the circadian system have been defined in vivo. Our techniques were based on those of Tenenbaum et al (2002) but they differed from the previously published methods in several ways  contain an A-rich region. Similar results  were observed in experiment two . These bAn interesting organizational feature of the transcription units expressing LARK target RNAs is the presence of at least one large intron. Our survey found that 6.5% of the intron-containing genes in the entire Drosophila genome contain an intron larger than 10 kb; a similar proportion (6.9% to 8.5%) is observed for genes expressed in the pharate adult brains . In contIt is also of interest that many of the LARK RNA ligands appear to be targets of microRNAs (miRNAs). miRNAs are small RNA molecules that repress mRNA translation in a sequence-specific manner elav-gal4/+; UAS-lark/+ flies  and elav-gal4/+; +/+ (control) flies, respectively. We found that for experiment one, only 14.6% (21/144) target RNAs show greater than a two-fold change (increased or decreased) in abundance when LARK is overexpressed. A similar result (16.6% or 25/151) was observed for the targets identified in experiment two. Thus, for the majority of the targets, there is not a significant effect of LARK overexpression on RNA abundance, as assayed by microarray analysis. We note that there were other RNAs, besides potential targets, which displayed significant changes in abundance in response to LARK overexpression (GEO accession number: GSE6420); these may be expressed from genes downstream of LARK. Presumably they are in some way indirectly regulated by LARK. They have not been further studied.To determine whether a change in LARK abundance altered target RNA levels, we queried whole genome microarrays with total RNA samples from We next asked whether LARK might influence the translation of particular target RNAs by performing immunoblotting experiments for two target-encoded proteins, Vap33-1 and E74A, for which antibodies were available. As shown in dunce (dnc), No Receptor Potential A (NorpA), flap wing (flw) and discs overgrown , have been shown in previous studies to be relevant for circadian functions bona fide target molecules. At present, we have assayed eclosion rhythms or locomotor activity rhythms for mutants of 69 genes or 14 genes, respectively. This ongoing screen has validated our biochemical genetic approach and identified several new mutants with defective eclosion or activity rhythms. These include mutants of the Ecdysone-induced-protein 74EF  gene. Interestingly, the E74 transcription unit displays features common to other potential LARK targets: it contains an A-rich element in the 3′UTR, the transcription unit contains a large ∼37-kb intron, and the 3′UTR contains binding sites for several miRNAs including miR-34, miR-9b, miR312, miR275, and miR-iab-4-5p. We note that E74 was identified in only one of the two immunoprecipitation experiments, justifying the behavioral screen of mutants representing all presumptive target genes. We have characterized E74 mutants in more detail as a proof of principle for our biochemical approach that identified LARK target RNAs.Four of the LARK targets, E74 locus is known to be essential for ecdysis in Drosophila –many hours earlier than normal–when populations were entrained to a cycle consisting of 12 hours of light and 12 hours of dark (LD 12∶12). Reproducibly, the mutant eclosion profile was observed to have two peaks: a minor one at ZT16 and a major peak after the lights-on signal 81k19, breakpoints 73A3; 74F1-4] displayed a severe eclosion phenotype, in which the majority of flies eclosed during the night portion of the cycle  was slightly decreased compared to either revertant . In contrast, the 1lark mutation is a recessive lethal, although most mutant homozygotes survive until the early pupal stage (94±2.5% in the present study). Interestingly, only 12±2.7% of the homozygous 1; E74BG01805lark double mutants survived to the early pupal stage; i.e., most of them died prior to or at the third-instar larval stage, indicating that the BG01805 mutation enhanced the lethal phenotype of 1lark. This observation also indicates that LARK is not absolutely required for synthesis of E74A; i.e., there must be some E74 synthesis in the complete absence of LARK, as the phenotype of the 1lark mutant becomes more severe with decreased E74 gene function.Consistent with a physical interaction between LARK and the BG01805E74, as expected if LARK promotes E47 production. The BG01805E74 mutation was generated by a “gene trap” insertion that includes a GAL4 coding segment downstream of the E74 gene promoter in an orientation appropriate for expression under control of the promoter BG01805E74 mutants, GAL4 expression ought to be driven by the native promoter of the E74 gene. We introduced a UAS-lark transgene, genetically, into the BG01805E74 background and examined eclosion in BG01805E74 , UAS-lark and mutant control populations. We found that overexpression of LARK partially or fully suppressed night-time eclosion events for the BG01805E74 mutant population on two consecutive days of LD  increases LARK abundance without significantly altering the phase of the LARK oscillation (unpublished results). These results suggest that rhythmic changes in LARK abundance may drive rhythms in E74 levels in vivo.Previous research found that LARK abundance oscillates in a circadian manner in vivo targets of LARK. First, known targets of RBM4 (mLARK), a mammalian homolog of fly LARK, were identified in our studies. Second, most of the identified transcription units have features in common. Third, the overexpression of LARK caused increased abundance for two target-encoded proteins for which antisera are available. Fourth, consistent with a circadian role for LARK, target genes with circadian functions were identified. Lastly, we have documented genetic interactions between lark and one target gene (E74). Although direct binding of LARK to target RNAs has not been verified in vitro, the aggregate of our results suggests that many of these RNAs are biological targets of LARK in vivo.We have employed a microarray-based Ribonomics approach to define RNAs that are associated with LARK in vivo. This was followed by a phenotypic screen of relevant mutants to select functionally relevant targets from the candidate pool. Several lines of evidence suggest that many of the RNAs identified in our analysis represent Given that LARK is an essential protein with a broad expression pattern in the CNS and other tissues Recent studies in other organisms have found that most cellular processes, including the cell cycle, are regulated by the circadian clock The RRM class of RNA binding proteins are known to function in post-transcriptional regulatory processes, including the control of RNA splicing, intracellular transport, stability and translation mPer1 clock RNA Per RNA is not among the collection. Thus, at present there is no evidence that Per represents a target of LARK in the fly circadian system.Previous studies have shown that decreased or increased LARK expression results in altered rhythmicity, with overexpression of the protein leading to arrhythmicity for both the eclosion and locomotor activity rhythms E74 encodes two transcription factor isoforms, E74A and E74B, which act to induce and repress, respectively, transcription of downstream genes, thus achieving a precise regulation of the timing of downstream responsive genes during ecdysis E74 mutant, suggesting that one or both of the E74 isoforms serves to regulate the circadian timing of adult eclosion. Interestingly, the ecdysis triggering hormone (ETH) promoter contains an imperfect E74 binding site Drosophila which indicate that the prothoracic gland (which synthesizes and releases ecdysone) contains a PER-based oscillator E74 expression in neurons relevant for rhythmicity and that LARK serves a post-transcriptional role within such neurons that further coordinates the temporal expression of E74 protein and the daily gating of eclosion events.Our ongoing behavioral screen has identified mutants of several different targets that exhibit altered locomotor or eclosion rhythms , suggesting a model wherein LARK regulates different output pathways by interacting with distinct RNA targets. Of the identified LARK targets, we have characterized one–E74–in some detail. E74 is one of several early response genes that are induced directly by ecdysone, the steroid hormone triggering insect ecdysis  and hybridized to Drosophila whole genome microarrays (Affymetrix 900335). Microarray hybridization, washing and scanning were carried out on an Affymetrix Fluidics Station 400 and an Agilent GeneArray Scanner according to standard protocols provided by Affymetrix, Inc. For the identification of potential LARK targets, equal amounts of RNA (about 3 ug) from the total RNA sample or the immunoprecipitated LARK-RNPs were labeled and hybridized to Drosophila Genome Arrays chips. Due to the large amount of starting material (∼1000 brains per experiment), and the mild washing conditions employed after the IP, a similar spectrum of RNA species was detected in the IP and total RNA arrays; this facilitated normalization using the total intensity of the arrays. Signals were scaled to the same target intensity for the IP and total RNA arrays. Data were analyzed using the Affymetrix Microarray Suite 5.0. The default settings were used for all tunable parameters . The following criteria were used to identify a differential expression between samples: first, it was required that the signal for a given gene be identified as “present” in the experimental array; although it was considered acceptable that the signal for the same gene in the baseline array was “marginal” or “absent”. The total number of genes identified as “present” in the IP array was 1880 for experiment one and 1885 for experiment two. Second, we required a change in p value of less than 0.001 for an increase or greater than 0.999 for a decrease. Finally, it was a requirement that the signal log ratio was greater than 1 for an increase or smaller than -1 for a decrease, either of which translates into a two-fold difference in signal intensity between the two samples.elav-gal4/+; UAS-lark/+ flies and elav-gal4/+; +/+ flies, respectively. About 10 µg of total RNA from each sample was used for labeling and hybridization to one gene chip. Three independent labeling and hybridization experiments were performed for each genotype. Raw data were normalized using the GCRMA package. After normalization, a filter was applied to select for genes that had a raw expression value of greater than 40 on at least one of the arrays. The filtered data sets were then analyzed using the R statistical software package with Bioconductor. Linear models were used in assessing the differential expression between conditions For comparisons between LARK overexpression and control flies, total RNA samples were prepared from adult heads of The Multiple Alignment Construction and Analysis Workbench (MACAW) program A database of intron number and size for all intron-containing genes of Drosophila was kindly provided by Flybase. Percentages were calculated for genes that contain at least one intron bigger than 10kb or 40kb for the whole genome pool, the pool of genes that were detected in the brain total RNA samples and the pool of LARK targets. Chi-square tests were performed to determine differences in frequency distribution for given intron sizes between the different types of gene collections.To calculate the frequency of consensus miRNA sequences within targets, genes containing an annotated 3′UTR longer than 30 bp  were scanned using the Drosophila miRNA database constructed by Enright et al elav-gal4/+; UAS-lark/+ or elav-gal4/+; +/+ populations and reverse-transcribed into cDNAs using Superscript II-RT (Invitrogen). Quantitative PCR was performed in a Strategene Maxpro×using the SYBR green method. Primers used for amplifying Vap33-1 specific fragments were: CCGGCCGTCAAACAGGTG and TGCCCAGCAGGAGGCTAACG. Primers used for amplifying E74 specific fragments were: GGAGCGAATGGACAAGCTCA and GCTGTTGCAGGTGGTGCT. Primers used for amplifying the Rp49 specific fragments were as previously described Total RNA samples were prepared from adult fly heads of either elav-gal4/+; UAS-lark/+ or elav-gal4/+; +/+ population were homogenized in polysome lysis buffer The Vap33-1 and E74A proteins were visualized by Western blotting. Antibody for fly Vap33-1 was obtained from Hugo Bellen BG01805E74 insertion and a UAS-lark transgene was generated using standard genetic techniques. To screen mutant populations for altered eclosion rhythms, fly stocks were maintained in vials at 18°C under a LD 12:12 schedule for at least 5 days prior to adult eclosion. At the time of the eclosion experiment, the vials were cleared of adult flies at around ZT 11 and then examined at approximately ZT 0 to identify those with significant night-time eclosion. If a relatively large number of flies were seen at ZT 0, then the mutant was designated as having an early-eclosion profile. The vials were cleared of adults again at ZT 6 and then examined at ZT 11 to determine if a large number of flies emerged late in the daily gate; such mutants were presumptively designated late-eclosion strains. To examine complete profiles of population eclosion, cultures were maintained at 18°C in LD 12∶12 for at least 5 days prior to the eclosion experiment. At the time of the eclosion experiment, emerging adults were collected every two hours under the same LD 12∶12 schedule or in constant darkness (DD). A lamp with a 7.5 watt bulb and Kodak GBX-2 filter provided red light in DD.Mutants of LARK targets were obtained from the Bloomington, Szeged and Harvard/Exelixis stock centers and from GenExel, Inc. . A recombinant chromosome carrying the To screen for mutants with a defective locomotor activity rhythm and to further characterize new activity mutants, stocks were raised at 25°C in LD 12∶12. After eclosion, newly emerged male flies were loaded into glass tubes with medium and monitored using the Drosophila Activity Monitoring (DAM) system. Activity was recorded at 23°C in LD 12∶12 for 3–4 days and then in constant darkness (DD) for at least 7 days. Activity data were analyzed for circadian periodicity using the Fly Toolbox algorithms developed by Levine et al Table S1(0.04 MB XLS)Click here for additional data file.Table S2(0.09 MB DOC)Click here for additional data file.