Robotically assisted colon resection is a new type of surgery for colon cancer. However, the evidence is inadequate for the general adaptation of robotic colon surgery. This study aimed to show the oncologic and perioperative clinical results of robotically assisted anterior resection (R-AR) compared with those of laparoscopically assisted anterior resection (L-AR) for sigmoid colon cancer.n = 34) or L-AR (n = 146) between April 2006 and September 2008. Patient characteristics, perioperative clinical results, and long-term oncologic outcomes were compared between the two groups.A total of 180 patients (sigmoid colon cancer stages 1–3) were assigned to receive either R-AR (p = 0.016). The total postoperative complication rate was 10.3 % for R-AR versus 5.9 % for L-AR (p = 0.281). The 3-year overall survival rate for all the patients was 93.4 % for L-AR versus 92.1 % for R-AR (p = 0.723). The 3-year overall survival rate was 100 % for both L-AR and R-AR in stage 1, 95.5 % for L-AR versus 100 % for R-AR (p = 0.386) in stage 2, and 88.4 % for L-AR versus 72.9 % (p = 0.881) for R-AR in stage 3.The patient characteristics did not differ significantly between the two groups. The mean operation time was 217.6 ± 70.7 min for L-AR versus 252.5 ± 94.9 min for R-AR (In this study, R-AR showed safety and feasibility in terms of perioperative clinical and long-term oncologic outcomes. However, the advanced technologies of R-AR did not translate into better long-term oncologic outcomes compared with L-AR. Laparoscopically assisted colectomy has been accepted as a safe minimally invasive procedure since several large-scale randomized clinical trials reported the oncologic safety and better short-term outcomes compared with those of open surgery –3.Robotically assisted colectomy, introduced by Weber and coworker  in 2001,The technological advantages of the robotic system are a three-dimensional surgical view using a stable camera platform, fine and free movements of the robotic arm in the surgical fields, tremor elimination, motion scaling, dexterity, and ambidextrous capability , 6. It hReports from several case series have described the feasibility and safety of robotic surgery for colon cancer –9. Howevn = 146) and robotically assisted anterior resection  using the da Vinci surgical system , and 154 patients underwent open surgery according to the decision of the patient with his or her informed consent. This study enrolled 180 patients who underwent either L-AR or R-AR.Between April 2006 and December 2008, 334 sigmoid colon cancer patients (stages 1–3 adenocarcinoma) underwent a curative anterior resection at Severance Hospital, Yonsei University, Seoul, South Korea. Of these 334 patients, 180 consecutive patients with a diagnosis of sigmoid colon cancer underwent curative minimally invasive surgery, which included laparoscopically assisted anterior resection  score , historyPostoperative complications were categorized using the Accordion severity-grading system . ConversFor the postoperative pathologic results, tumor node metastasis (TNM) stage (American Joint Committee on Cancer [AJCC] 6th) , grade oThis study was approved by the Institutional Review Board of Severance Hospital, and informed consent was obtained from all the patients.o.A standard mechanical bowel preparation was performed 24 h before the operation. The patient was placed in a modified lithotomy position with the legs apart. After achievement of pneumoperitoneum , a 12-mm trocar was placed through an incision just above the umbilicus. A 30° laparoscope then was inserted through the 12-mm trocar. The second 12-mm trocar was inserted at the lower right quadrant of the abdomen. The third 5-mm trocar was inserted at the upper right quadrant of the abdomen. The fourth and fifth 5-mm trocars were inserted at the upper and the lower left quadrants. The patient then was placed in a modified lithotomy position with the legs apart in a 30° Trendelenburg position with the right side down at 15After ligation of the inferior mesenteric artery and vein, medial-to-lateral dissection is performed to the left lateral gutter. The sigmoid colon itself was divided using an endo-GIA (Covidien Echelon). The specimen was extracted though the left lower trocar incision, which was enlarged to ~3–4 cm, after protection. An end-to-end anastomosis (EEA) anvil then was inserted into the proximal colon and secured with a purse-string suture. The colon was placed back into the abdomen, and the port site was closed. Pneumoperitoneum was restored, and a circular stapler was used to create an end-to-end anastomosis.After induction of general anesthesia, the patient was placed in a modified lithotomy position with the legs apart. A 12-mm trocar was placed through an incision just below the umbilicus after achievement of pneumoperitoneum. A 30° standard 12-mm robotic laparoscope then was inserted through the 12-mm trocar. The first 8-mm da Vinci trocar was placed in the middle point on the line between the infraumbilical 12-mm trocar and the right anterior superior iliac supine. The second 8-mm da Vinci trocar was inserted into the right upper abdomen. The third 8-mm da Vinci trocar was inserted 2 cm below the xiphoid process. The 11-mm trocar was placed in the right midabdomen lateral to the umbilicus and 3 cm lateral from the midaxillary line to allow access of the assistant for mobilization of the left colon. The remainder of the procedure was the same as in laparoscopic surgery except for the specimen extraction site and the infraumblilical trocar, which was enlarged to 3–4 cm. An EEA was used in both the laparoscopic and robotic procedures.t test or the Mann–Whitney test for continuous variables were used for statistical comparisons of perioperative clinical outcomes. Cumulative-incidence methods were used to estimate the rate of cancer recurrence. Overall survival and disease-free survival were analyzed using the Kaplan–Meier method, and a comparison was performed using the log-rank test. Converted cases were considered on an intention-to-treat basis. All p values lower than 0.05 were considered statistically significant.Data were analyzed using the SPSS statistical program . The Chi-square test for categorical variables and the Student’s In this study, 146 patients underwent L-AR, and 34 patients underwent R-AR. The following parameters were evaluated as the characteristics of the patients: age, sex, weight, height, mean BMI, ASA score, tumor location from the anal verge, and operation history. None of these parameters differed significantly between the groups (Table p = 0.016). The hemoglobin change did not differ significantly between the two groups (p = 0.546). Days to first gas passing and stool passing, days to soft diet, and days of hospitalization were statistically fewer in the R-AR group than in the L-AR group.The mean operating time was 217.6 ± 70.7 min  in the L-AR group and 252.5 ± 94.9 min  in the R-AR group . The rate for severe complications requiring reoperation was 1.4 % in the L-AR group and 0 % in the R-AR group.The overall postoperative complication rate during fewer than 30 postoperative days was 10.3 % in the L-AR group and 5.9 % in the R-AR group . The mean proximal resection margin was 8.2 ± 2.9 cm in the L-AR group and 10.7 ± 3.4 cm in the R-AR group (p = 0.026). The mean distal resection margin and the mass size did not differ significantly between the two groups (Table The distribution of the TNM stage and the histologic grade of differentiation did not differ significantly between the two groups. The mean number of harvested lymph nodes was 16.5 ± 11.3 in the L-AR group and 12.0 ± 7.9 in the R-AR group (p = 0.723). The 3-year disease-free survival rate for all the patients was 90.9 % in the L-AR group and 89.2 % in the R-AR group (p = 0.890)  . The 3-year disease-free survival rate for the stage 3 patients was 80.1 % in the L-AR group and 72.9 % in the R-AR group (p = 0.454) . The 3-year overall survival rate for the all the patients was 93.5 % in the L-AR group and 92.1 % in the R-AR group (The data from the study showed the feasibility and safety of R-AR, with oncologic and perioperative outcomes similar to those of L-AR. The mean operation time was significantly longer in the R-AR group than in the L-AR group. The short-term outcomes of this study showed patterns similar to those of previous published studies , 13, 14.During the postoperative course, the amount of intraoperative bleeding did not differ significantly between the R-AR and L-AR groups. However, the clinical parameters related to a fast recovery. The days to first gas passing, the days to first stool passing, the days to soft diet, and the days of hospitalization were significantly fewer in the R-AR group than in the L-AR group. These results showed a pattern similar to that in our previous report .Core advanced technologies of the robotic system may have had a positive influence in the R-AR group. Relatively lower complication rates in the R-AR group than in the L-AR group also may be positively related to the technological advantages of the robotic system, although the difference was not statistically significant. Consequently, the relatively lower complication rates in the R-AR group may shorten the hospital stay, the time to first gas passing, and the time to first stool passing. However, the exact cause for the shorter hospital stay and lower complication rate cannot be assessed based on the study design.Rawlings et al.  reportedThe aforementioned considerations imply that a minimally invasive surgery expert can overcome the technological advantages of the robotic system by just using conventional laparoscopic instruments. The current generation of the robotic system has no voluntary action or decision and mimics the surgeon’s hand motion. This fact is the main reason for the difficulty evaluating the objective efficacy of the robotic system.The 3-year overall survival and the 3-year disease-free survival of the R-AR group did not differ with those of the L-AR group. The oncologic outcomes according to the stages of R-AR showed results similar to those of the R-AR group.The oncologic safety of laparoscopic colon surgery for cancer has been proven by large multicenter randomized clinical trials –3. In thIn the same manner, the quality of the resected specimen did not differ between the R-AR and L-AR groups in this study. The concepts of standard oncologic resection depend on the range of resection . Thus, iThe total number of harvested lymph nodes is related to understaging and poor oncologic outcomes . In thisThe robotic system has several disadvantages despite its many advanced technological advantages. The robotic system has no tactile sense. Thus, all instruments should be moved very precisely and carefully in the small surgical field generated by the camera to prevent dangerous injuries around the site. Moreover, the operator cannot know the power of holding the tissue and the tension of traction or countertraction during the procedure. Just a visual cue can compensate for this disadvantage.These disadvantages can be related to the longer operation time in the R-AR group compared with that in the L-AR group in this study because fast instrument movement and movement around the site are possible with the laparoscopic procedure, which has tactile sense. Docking time of robotic instruments and disengagement can be another explanation for the longer operation time in the R-AR group. Similarly, with this study, Rawlings et al.  reportedCompared with L-AR, R-AR was technically safe and feasible and had similar oncologic safety and perioperative outcomes. No extra-significant morbidity or mortality was noted in the R-AR group. However, the high cost might be a further debatable issue for general adaption of R-AR.This study had a potential selection bias because randomization was not performed and the study had a retrospective case–control design. Thus, future large-scale randomized clinical trials and objective cost-effectiveness analysis should evaluate the efficacy of robotically assisted colon surgery.


Simple sequence repeats (SSRs) are not only applied as genetic markers in evolutionary studies but they also play an important role in gene regulatory activities. Efficient identification of conserved and exclusive SSRs through cross-species comparison is helpful for understanding the evolutionary mechanisms and associations between specific gene groups and SSR motifs. In this paper, we developed an online cross-species comparative system and integrated it with a tag cloud visualization technique for identifying potential SSR biomarkers within fourteen frequently used model species. Ultraconserved or exclusive SSRs among cross-species orthologous genes could be effectively retrieved and displayed through a friendly interface design. Four different types of testing cases were applied to demonstrate and verify the retrieved SSR biomarker candidates. Through statistical analysis and enhanced tag cloud representation on defined functional related genes and cross-species clusters, the proposed system can correctly represent the patterns, loci, colors, and sizes of identified SSRs in accordance with gene functions, pattern qualities, and conserved characteristics among species. RUNX2 (CBFA1) [IGF1) which was confirmed as one of the growth control genes. The IGF1 gene contains “AC” repeats located within the upstream regions and is a major determinant of small body size in dogs [Simple sequence repeats (SSRs) are nonrandom distributed nucleotides in genomes of different organisms with repeated basic patterns of lengths from mononucleotide to hexanucleotide . SSRs ha (CBFA1) . Another (CBFA1) . In addi in dogs –9. From To efficiently identify SSR biomarkers from large amount of genes in different species, considering a few interested genes at a time provides an intuitive and effective approach. One possible approach of selecting interested gene groups from gene ontology (GO) terms was employed in this study. The GO is a set of structured vocabularies defined by Gene Ontology Consortium , which iTo enhance the ranking and readability of identified SSR motifs, a tag cloud technique was adopted to display the comparative results of cross-species SSRs. Tag cloud representation is a widespread visualization technology which provides users with an informative image from a designated set of data. Tags of different phases or short sentences represent key information of each entry in the dataset. Multiple tags for various data entries could be displayed in an image simultaneously, and which are manually assigned by users or automatically generated by computer algorithms. Each tag cloud could be shown with different visual attributes such as different sizes or colors. In tradition, different sizes of tags are designed to indicate various levels of representativeness of tags within the dataset . CurrentIn this study, we have collected complete genome sequences of 14 model species as the fundamental dataset. All SSR motifs in each gene were extracted and saved in the designed database in advance. Users can prepare a set of genes or assign keywords to defined query genes and then choose model species of interest for cross-species cluster comparison. Model species of interest could be manually clustered or automatically categorized into two groups of mammal and marine species clusters. SSR retrieval and distribution analysis for single species is also available from the developed system. Once all parameters have been settled, the system will perform online comparison and display all grouped SSR motifs in a tag cloud visualization approach. All significantly conserved or exclusive SSR motifs located within the specified gene sets from two species clusters will be efficiently identified and displayed. In addition, all retrieved SSR biomarker candidates will be shown in a tag cloud representation with occurrence frequency, conserved ratio, gene annotation, sequence contents, and corresponding translated proteins through a fast, responsive, and user-friendly web page design.In this study, there are fourteen initially selected genomes obtained from Ensembl database , and allDanio rerio), stickleback (Gasterosteus aculeatus), medaka (Oryzias latipes), fugu (Takifugu rubripes), tetraodon (Tetraodon nigroviridis), and cod (Gadus morhua) as fishery species; human (Homo sapiens), gorilla (Gorilla gorilla), macaque (Macaca mulatta), mouse (Mus musculus), cow (Bos taurus), and dog (Canis familiaris) as mammal species; roundworm (Caenorhabditis elegans) and fruit fly (Drosophila melanogaster) as extra two popular experimental species. These downloaded data include sequence contents, coordinates of exons/introns and UTRs for each gene, and upstream and downstream regions with a length of 2,000 nucleotides.To obtain genome sequences of various organisms, the developed system employed Ensembl release 65 as the major data resource. Ensembl database provides complete genome information on multiple eukaryotic model organisms including whole genome sequence, gene annotations, and molecular functions. To lay emphasis on identification of consensus and unique features of SSRs among different species, two species clusters including fishery and mammal species were initially selected for comparison. Since there were only 6 fishery species that could be collected from Ensembl release 65, we therefore selected another 6 popular mammal species for equivalent status. Besides, two famous research organisms in experimental studies were also included in our database. These intentionally selected model species are zebrafish , 3′ UTR, and upstream and downstream regions. In this system, the upstream and downstream regions are defined as an extended range of 2000 nucleotides from the start and end positions of transcription. In addition, according to the shifting mechanism of repeating segments and the complementary based-paired nature in DNA double-stranded helical structures, several possible combinations of SSR patterns could be considered as an identical SSR motif within genetic loci. For example, any rotation of a basic repeat pattern is considered as the same SSR element, such as a “TA” repeat could be also defined as an equivalent repeat motif as an “AT” repeat pattern through one nucleotide shifting. Another situation of an identical SSR motif with different appearance is through complementary based paring and inverse reading from the DNA sequences. For example, the repeat pattern of “AGC” would appear as “GCT” within the other complementary strands of DNA. Therefore, to enumerate all possible SSR patterns in all DNA sequences under these two constraints, there are exactly 501 fundamental basic SSR patterns from 1 to 6 nucleotides in length . However Bos taurus, Canis familiaris, Homo sapiens, Gorilla gorilla, Macaca mulatta, and Mus musculus; the second group represents the fishery species including Danio rerio, Gadus morhua, Gasterosteus aculeatus, Oryzias latipes, Takifugu rubripes, and Tetraodon nigroviridis. In addition to these twelve clustered species, we also included two widely used model organisms including Drosophila melanogaster and Caenorhabditis elegans. Nevertheless, in this developed system, users can either apply the previously defined two species groups or manually assign them into two clusters without any limitation. By integrating with cross-species comparison techniques and overrepresentation analysis from assigned gene sets, the SSR patterns with conserved and exclusive characteristics in selected genes between different species clusters can be recognized and treated. An identified conserved SSR motif would be initially defined as an orthologous SSR motif if the conserved ratio meets the minimum threshold in an assigned species cluster. For example, a conserved ratio of 80% denotes the identified conserved SSR pattern that could be found in at least 80% of species in the assigned species cluster, which indicated that there are at least 5 (6∗80% = 4.8) different species possessing the orthologous gene(s) and holding the specific SSR pattern located within the same genetic region among all orthologous gene(s). Regarding the conditions of many-to-many orthologous genes, an SSR motif is defined as holding conserved feature as long as it could be detected in any one of its orthologous genes. The threshold level of conserved ratio can be assigned by users through interactive webpage settings.Due to tremendous amount of SSRs nonrandomly distributed in genome sequences, it is not an intuitive task to observe SSR biomarkers or identify gene regulatory related SSR motifs from an individual genome. Hence, we assume the conserved or exclusive SSR motifs providing important clues for identifying functional SSR motifs or representative biomarkers among various species. To emphasize the long-distance relationship from an evolutionary point of view, we have selected two groups of model vertebrate species for orthologous SSR motif comparison. The first group represents the mammalian species includingThrough cross-species comparison between two clustered groups, retrieving conserved or exclusive SSR motifs could help biologists in choosing significant biomarkers from a previously defined gene set before performing biological experiments. On the other hand, exclusive or common SSR motifs between two different species clusters might be regarded as important genetic markers under the evidences of biological evolution and functional conservation.Tag cloud visualization technique provides keyword representation of text data by showing each tag in various font sizes and colors. To enhance the importance of conserved and exclusive SSR motifs extracted from a set of specified homologous genes between two different species clusters, we adopted the tag cloud representation to display these identified SSR motifs according to their calculated weighting coefficients from query gene sets. In an SSR tag cloud, the tag size of each SSR motif not only indicates the conservation status of the motif among orthologous genes, but also displays the representativeness among different species clusters. A linear accumulation formula and normalization procedures for deciding SSR weighting coefficients were performed for tag size selection. This formula simply counts the number of occurrence times of each SSR motif found from each individual gene in different species clusters. According to the definitions of occurrence rate, if an identified SSR motif is well conserved in two different species clusters or highly represented in the specified gene set, the SSR tag will be assigned with a larger weighting coefficient. Accordingly, the SSR tag will be displayed with a bigger font size in the tag cloud.In order to visually emphasize identified SSR motifs belonging to different species clusters, we applied different colors on SSR tags to distinguish the conserved and/or exclusive features of SSR biomarkers between two species clusters. In this study, red tags represent consensus SSR motifs for the first species cluster only and satisfy the conservation threshold in the first species cluster; pink tags are applied for representing consensus SSR motifs for the first species cluster only, but the conservation threshold is not satisfied; dark green tags represent consensus SSR motifs well conserved within the second species cluster only and these motifs also satisfied the conservation criterion in the second species cluster; light green tags denote consensus SSR motifs in the second species cluster only, but the conservation threshold is not satisfied; blue tags represent the identified SSR patterns well conserved in both species clusters and satisfy the species conservation percentage as well; yellow tags are applied to show identified SSR patterns conserved, but the species conservation criterion is not satisfied for the query gene set from both species clusters. The color-coded information in a resulting tag cloud is shown in In the developed system, users can also try to identify imperfect SSR biomarkers by setting different tolerant levels, and the number of retrieved imperfect SSR motifs would be in accordance with the settings proportionally. Higher noisy rates allow more tolerant repeat patterns and reflect larger number of possible SSR motifs. Accordingly, the corresponding tag clouds could be depicted in multiscale representations under various noise threshold settings. In other words, different scales of tag clouds are composed of SSR motifs of different tolerant qualities. For instance, the highest quality of SSR tag cloud represents that all identified conserved SSR motifs are with perfect repeating patterns among different genes and group species. Contrarily, lower quality SSR tag clouds contain more tolerant SSR motifs within the tag image, and which may reflect evolutionary status due to gene specification and/or duplication events from either distant or close species. Multiscale tag clouds provide biologists with an easier way to compare and select suitable SSR candidate motifs as biomarkers through a progressive approach on different tolerance levels, which could be applied in various situations for further design of biological experiments.http://ssrtc.cs.ntou.edu.tw/) for identifying conserved and exclusive SSR biomarkers through cross-species cluster comparison. The main interface of the developed web system is shown in  minimum SSR length is applied to define the minimal length for identification of SSR motifs. The SSR quality factor represents a tolerance threshold for allowing imperfect SSRs as candidate biomarkers. The developed system initially provides three available settings for efficient identification: 1.0 for perfect SSRs, 0.8 and 0.9 for imperfect SSRs with 20% and 10% tolerant percentages for an identified SSR motif. The function of species cluster assignment is provided for cross-species comparison by classifying species of interest into two clusters. The parameter of motif conserved ratio is designed as the percentage of qualified species within a cluster possessing the conserved SSR motif within a target gene. Two different operation modes were designed for the motif conserved ratio. If a user chooses the condition of larger than or equal to motif conserved ratio, the system will display a resulting SSR tag cloud in 6 colors; otherwise an SSR tag cloud will appear in 3 colors only. Different color modes of an SSR tag cloud are defined in the previous section. Once all parameters and operation modes are defined, the system performs SSR biomarker evaluation automatically and generates a final SSR tag cloud for visualization. The font color of each SSR tag is mainly decided by the motif conserved ratio parameter, and the font size depends only on the occurrence frequency of an SSR element. Users can move the mouse device over any SSR item within the resulting tag clouds, and a total appearance number and conserved ratio of the selected SSR motif from the target genes of assigned species cluster will be displayed. The detailed information of each SSR tag is also available in a floating dialog box by clicking on it, which includes Ensembl gene ID, transcript ID of the specified gene possessing the target SSR motif, species name, coordinates in genomes, and DNA sequence contents. Additionally, if an SSR appears within coding regions, then its corresponding protein sequences could be recalled from Ensembl database and shown in an additional window.In this study, we have developed an online web system . All selected genes possess sequence identities higher than 80% compared to human genome individually. Under this criterion, there are totally 162 orthologous genes selected for the first testing case. If these twelve vertebrate species were classified into two species clusters including mammal and fishery species clusters for comparison, the conserved and exclusive SSR motifs for each gene could be successfully identified and significant SSR biomarker candidates for each individual gene were included in the Supplementary Material available online at VPS35) which possesses an average sequence identity of 80% by taking pairwise alignment between human and the other eleven model species. The resulting SSR tag cloud for VPS35 was shown in  SSR quality of 80%, minimum SSR length of 20 nucleotides, and motif conserved ratio of 60% . The first species cluster was assigned as the mammal group including human, macaque, mouse, cow, dog, and gorilla, and the second species cluster was assigned as the fishery group including zebrafish, stickleback, medaka, fugu, tetraodon, and cod. The genetic region parameters were set as searching for all regions except introns, and the length of basic pattern was selected from 1 to 6 nucleotides for comprehensive representation.The Ensembl gene ID of ENSG00000069329 is a vacuolar protein sorting gene  which possesses an average sequence identity of 80% by taking pairwise alignment between human species and other 11 model species individually. The resulting SSR tag cloud for EFTUD2 was shown in  Motif Conserved Ratio. Similarly, the light green coded SSR tags represented consensus SSR motifs only found in the fishery species cluster exclusively with less than 4 fishery species. In addition, the red SSR tag of “A@Downstream” was shown with the biggest font size, which implied the SSR holding as the most representative and exclusive for mammal species compared to all other SSR candidates.The Ensemble gene ID of ENSG00000108883 is an elongation factor Tu GTP binding domain ( VPS35 (ENSG00000069329), is associated with “Parkinson's disease (PD)” [ EFTUD2 (ENSG00000108883), causes “mandibulofacial dysostosis with microcephaly” [ in silico SSR biomarker detection by our proposed system, we could efficiently identify many important conserved and exclusive SSRs between two grouped species as biomarkers. However, without experimental verification, we could not make sure whether both diseases possess a true correlation with identified SSR motifs. To gain more confidence on the proposed system, we verified on some disease genes which were known to be associated with some specific SSR biomarkers. If a genetic disease is indeed caused by abnormal distributions of SSR motifs, we expect that our proposed SSR tag cloud representation system could identify those significant SSR biomarkers in an efficient and effective way.Interestingly, the first gene,se (PD)” , and thecephaly” . In both HOXA11, ZIC2, ALX4, HOXA2, DLX2, HOXA7, TWIST1, HOXC13, RUNX2, SOX9, HOXD11, HOXD13, GDF11, HLX, SIX3, HOXD8, and HOXA10 [To demonstrate functionally related SSR motifs, we have selected a gene set containing specific function of skeletal development. A total of 17 genes associated with such function are selected and these genes ared HOXA10 . In this SSR quality of 90% for perfect SSR patterns, minimum SSR length of 20 nucleotides, motif conserved ratio of 80% , and all possible SSR candidates were shown. The first species cluster was assigned as the mammal group including human, macaque, mouse, cow, dog, and gorilla; the second species cluster was assigned as the fishery group including zebrafish, stickleback, medaka, fugu, tetraodon, and cod. The filter of genetic region was selected for coding region only, and the length of basic pattern was selected from 1 to 6 nucleotides for comprehensive representation. According to these settings, the simulated results were shown in GDF11) gene is located at chromosome 12 and its coordinates are from 56137185 to 56137224. Since the CCG repeated pattern was found in coding regions, the table also provided the detailed information of DNA, cDNA, and corresponding protein sequence contents. Actually, this repeated pattern in RUNX2 gene at coding region is a polyalanine peptide (GCC repeat in coding region), and it indeed plays a crucial role in cellular development function. Abnormal distribution of this polyalanine repeat biomarker might cause dysplasia disease, a genetic disorder of abnormal cellular development.The resulting SSR tag clouds from different combinatorial settings for 17 skeletal development related genes were shown in In  TBX15, SIX4, DLX2, PRRX1, TWIST1, BMP4, SIX1, SMAD2, NIPBL, NODAL, WNT9B, TGFBR2, GAS1, SIX2, FOXC2, SMAD3, TBX1, TGFBR2, TBX15, GNAS, PRRX2, TGFBR1, TFAP2A, SMAD2, SETD2, BMP4, SMAD3, TWIST2, TFAP2A, SMAD3, TGFBR1, and BMP4. To compare and show different results by various settings, we have tried several combinations of input parameters which were different from system default settings. In this case study, the parameter settings were defined as follows: SSR quality of 90% for perfect SSR patterns, minimum SSR length of 20 nucleotides, motif conserved ratio of 80%  and showed all possible SSR candidates. The first species cluster was assigned as mammal group and the second species cluster for fishery group as default settings. The filter of genetic region was selected for analyzing on coding regions only, and the length of basic pattern was selected from 1 to 6 nucleotides. According to these settings, the simulated results were shown in To demonstrate functionally related SSR motifs through GO term assignment, we selected a GO term of “embryonic cranial skeleton morphogenesis.” The related genes annotated by this GO term include motif conserved ratio to 60% and the resulting SSR tag cloud was shown in  motif conserved ratio to 100%, the result was shown in  motif conserved ratio adjustments. The higher setting of motif conserved ratio reduces the amount of red, green, and blue color coded tags.Then, we lowered down theHTT) gene at chromosome 4 [To demonstrate genetic diseases caused by abnormal distribution of SSR motifs, we have selected a well-known neurodegenerative genetic disease “Huntington's disease (HD)” as an example. HD was found as an irregular distribution of polyglutamine expansions (CAG repeats) located within the coding regions of ENSG00000197386 , and with a selection of “show all SSRs”. The first species cluster was assigned as mammal group while the second species cluster as fishery group. In  SSR quality settings. This repeat motif in coding regions appears in most mammal species except macaque with a minimum length requirement of 20 nucleotides. Besides, only zebrafish possesses a similar repeat motif in coding region among all fishery species. When the parameter of SSR quality was increased to 100% (without any tolerance), the pattern of “AGC@Coding”  could be retrieved from both cattle and human in mammal species only. We could observe that the font size and color of each SSR tag were gradually changed according to different settings of tolerance rate. Accordingly, the tag of “AGC@Coding” appeared with the biggest icon in pink when compared to all other SSRs in coding regions, and it reflected the significance of exclusive features for mammal species compared to fishery species. These observations might also provide important information for biologists for animal species selection in future experimental studies regarding specific diseases.The verification results of SSR tag cloud were shown in  motif conserved ratio. Different conserved ratio values change colors of SSR tags. When the motif conserved ratio increased, the amount of red, green, and blue tags might decrease. In  species cluster and Cluster II represents the second species cluster. The horizontal straight line in the figure represents a motif conserved ratio value. When the CR% threshold value is increased, the areas of red, blue, and dark green decreased. In contrast, when the CR% threshold value is decreased, the areas of red, blue, and dark green increased. The area is proportional to the amount of SSR tags.Two key parameters affect the color and size distribution within an SSR tag cloud. The first one is the SSR quality threshold. As shown in  SSR quality values were not only changing the number of SSR tags but also transforming the colors. Increment of SSR quality value may reduce the amount of SSR tags, since the SSRs with higher qualities are always a subset of SSRs with lower qualities. When a quality threshold decreases to gain more SSR candidates, part of red and green tags might change their colors into yellow or blue tags, respectively. This is mainly caused by newly intersecting region after expanding SSR candidates.The second important parameter for a tag cloud is the SSR length of 20 nucleotides. The SSR quantities for mammal species are usually more than fishery species, and the increment of SSR quality value reduces the amount of SSR motifs in each species generally.Besides, a few common SSR tags originally coded in yellow might be transformed into either red or green through increasing the quality factors, which is mainly because the total number of species possessing certain SSR tag is decreased, and therefore the conserved SSR motifs between two species clusters might become representative SSR tags for one species cluster exclusively. In  in silico comparison of SSR motifs across different species clusters may provide the clues and evidences for further understanding of evolutionary development and functional associations.SSRs are nonrandomly distributed nucleotides in the genomes with repeating basic patterns of lengths from 1 to 6 nucleotides, and a large number of functional SSR motifs have been demonstrated as important biomarkers involved within various biological processes and gene regulations. Due to abundant number of SSRs in each species genomes, it is difficult to recognize significant SSR biomarkers or gene regulation related SSRs mainly based on repeat sequence length, genetic locations, and fundamental repeat pattern of an SSR motif. In this paper, we proposed the concept of identifying SSR biomarker candidate through cross-species cluster comparison on a specified set of target genes. The developed system provides an online tool with multiparameter selection functions, and the identified SSR motifs are displayed by a tag cloud visualization method. The exclusive and consensus SSR motifs between two species clusters are shown in different font colors and sizes in an efficient approach. TheThe Supplementary Material provides an orthologous gene list which contains 162 genes from 12 selected model species. Each gene possesses a sequence identity higher than 80% compared to its corresponding orthologous gene in human genome respectively.Click here for additional data file.


It binds to both the DNA binding domain (DBD) and the ligand-binding domain (LBD) of AR and disrupts the N/C terminal interaction of AR. Furthermore, COUP-TF II competes with coactivators such as ARA70, SRC-1, and GRIP1 to modulate AR transactivation as well as inhibiting the recruitment of AR to its ARE-containing target promoter. Taken together, our findings suggest that COUP-TF II is a novel corepressor of AR, and provide an insight into the role of COUP-TF II in prostate cancers.Androgen receptor (AR) is involved in the development and progression of prostate cancers. However, the mechanisms by which this occurs remain incompletely understood. In previous reports, chicken ovalbumin upstream promoter-transcription factor II (COUP-TF II) has been suggested to play a role in the development of cancers. In the present study, we explored a putative role of COUP-TF II in prostate cancers by investigating its effect on cell proliferation and a cross-talk between COUP-TF II and AR. Overexpression of COUP-TF II results in the inhibition of androgen-dependent proliferation of prostate cancer cells. Further studies show that COUP-TF II functions as a corepressor of AR. It represses AR transactivation on target promoters containing the androgen response element (ARE) in a dose-dependent manner. In addition, COUP-TF II interacts physically with AR  The normal growth, differentiation, and function of the prostate gland are largely regulated by androgens, which act through androgen receptor (AR) AR, a ligand-dependent transcription factor, regulates the expression of target genes when activated by androgens The chicken ovalbumin upstream promoter-transcription factors (COUP-TFs) are orphan members of nuclear receptor superfamily that activate or repress gene transcription by directly binding DNA sequence COUP-TF interacts with other nuclear receptors, including estrogen receptor (ER), the retinoid X receptor (RXR), peroxisome proliferator-activated receptors (PPAR), and the vitamin D receptor (VDR) In the present study, we demonstrate that COUP-TF II represses the transactivation of AR in prostate cancer cells, resulting in the inhibition of androgen-dependent cell growth. COUP-TF II directly binds AR, preventing the N/C terminal interaction of AR. Furthermore, COUP-TF II inhibits the ligand-induced recruitment of AR to the PSA promoter and competes with AR coactivators to modulate AR transactivation. All together, our results suggest COUP-TF II as a potent AR corepressor and provide an insight into the role of COUP-TF II in prostate cancers.3H]-thymidine, specific activity 80 Ci/mmol) was obtained from Perkin Elmer Life Science. Trichostation A was purchased from Sigma-Aldrich Co., and Sodium butylate and Nicotinamide (NIC) were purchased from Calbiochem.Antibodies for AR (sc-815), PSA (sc-7638), HA (sc-7392), GFP (sc-9996), and α-tubulin (sc-5286) were obtained from Santa Cruz Biotechnology, Inc. and antibody for AR  was obtained from EMD Millipore Corporation. Antibody for COUP-TF II (PP-H7147-00), which does not recognize COUP-TF I MslI/XhoI-digested fragment from pCR3.1-mouse COUP-TF II into EcoRV/XhoI-digested HA epitope-tagged pcDNA3 vector (pcDNA3HA). GFP-COUP-TF II and GST-COUP-TF II full length were subcloned by insertion of EcoRI/XhoI-digested fragment from pcDNA3HA-COUP-TF II into XmaI-digested pEGFP-C1 vector and EcoRI/XhoI-digested pGEX4T-1 vector, respectively. GST-COUP-TF II full length and deletion mutants, AF1, DBD+hinge (DBDh), and ΔAF1 regions, were constructed by self-ligation of SmaI/XhoI-, SphI/XhoI-, and EcoRI/SmaI-digested fragment from GST-COUP-TF II full length, respectively. The mammalian expression plasmids VP-AR1-660 and GAL-AR624-919 and the reporter construct 5XGAL4-Luc3  were kindly provided as gifts by Dr. Elizabeth M. Wilson (University of North Carolina) The mammalian expression plasmids of mouse AR (pcDNA3-AR), pcDNA3-ARA70, pcDNA3-p300, pSG5HA GRIP1, and pCR3.1 SRC-1, and MMTV-Luc and PSA-Luc reporter plasmids have been previously described For the ectopic expression of the mouse COUP-TF II, an adenoviral delivery system was used COS-7 and PPC-1 cells were maintained in Dulbecco's minimum essential medium (DMEM)  supplemented with 10% FBS and 100 units/ml penicillin/streptomycin. LNCaP cells (American Type Culture Collection) were maintained in RPMI 1640 medium (Life Technologies Inc.) supplemented with 10% FBS, 100 units/ml of penicillin/streptomycin, and 2 mM L-glutamine.Twenty-four hours prior to transfection, cells were plated in 24-well plates and transfected with the indicated amount of expression plasmids, a reporter construct and the control lacZ expression plasmid pCMVß using the SuperFect (Qiagen) or Lipo2000 (Invitrogen) transfection reagent. Total amounts of expression vectors were kept constant by adding appropriate amounts of the depleted vector. Twenty-four hours after transfection, the medium was replaced with fresh medium containing 10% charcoal-stripped serum and either DHT or vehicle. Cells were harvested 24 h after the addition of hormone, and luciferase and ß-galactosidase activities were assayed as previously described 5′-AAGCTGTACAGAGAGGCAGGA-3′ and reverse 5′-AGAGCTTTCCGAACCGTGTT-3′ for COUP-TF II; forward 5′-GGCCAGGTATTTCAGGTCAG-3′ and reverse 5′-CCACGATGGTGTCCTTGATC-3′ for PSA; and forward 5′- GAGACCTTCAACACCCCAGCC -3′ and reverse 5′- CCGTCAGGCAGCTCATAGCTC -3′ for β-actin.Total RNA was extracted from the prostate with Tri reagent solution . For RT-PCR, 1 µg of total RNA was reverse-transcribed and PCR-amplified with COUP-TF II-specific primers, which amplify a 650 bp fragment spanning ORF. Quantitative analysis of PSA gene expression in LNCaP cells infected with AdGFP or AdCOUP-TF II was assessed by qRT-PCR with PSA-specific primers, which amplify a 517 bp region spanning ORF, using a SYBR Green PCR kit and a Rotor-Gene RG3000 Real-Time PCR system (Corbett Research). As an internal control, PCR reactions were also performed using β-actin-specific primers, which amplify a 362 bp region spanning exon 4. The oligonucleotide sequences were as follows: forward E. coli BL21 cells and isolated with glutathione-Sepharose-4B beads . Immobilized GST fusion proteins were then incubated with [35S] methionine-labeled COUP-TF II or AR proteins produced by in vitro translation using the TNT-coupled transcription-translation system (Promega). The binding reactions were carried out in 250 µl of GST-binding buffer  overnight at 4°C. The beads were washed five times with 1 ml of GST-binding buffer. Bound proteins were eluted by the addition of 20 µl of SDS-PAGE sample buffer, and were analyzed by SDS-PAGE and autoradiography GST, GST-AR domain mutants, and GST-COUP-TF II deletion mutants were expressed in 35S] methionine-labeled AR AF1DBDh proteins produced by in vitro translation. For competition analysis, 2, 5, and 10-fold excess of in vitro translated COUP-TF II proteins was added together with radiolabeled AR AF1DBDh proteins.In order to determine interfering with the interaction occurring between DBD and LBD of AR by COUP-TF II, we conducted GST pull-down competition assay. Immobilized GST-AR LBD proteins were incubated with -thymidine  for 4 h. Cells were harvested onto a glass microfiber filter  and intensively washed with distilled water. Incorporation of thymidine into DNA is measured by counting the filters with a scintillation counter.LNCaP cells were cultured in 24-well plates at a density of 2×103 cells in 0.35% agar over 0.7% agar layer in six-well culture dishes. Fresh complete growth medium or charcoal-stripped serum medium containing absence or present of 1 nM DHT was changed every 2 days for 2 weeks. Colonies larger than diameter of 300 mm were scored.LNCaP cells were infected with either AdCOUP-TF II or AdGFP in 10% charcoal-stripped serum-supplied medium. After 24 h of infection, the cells were trypsinized and seeded at 5×10A statistical analysis was performed by utilizing Student’s t-test with the PRISM software system for Windows. In all cases probability (P) values below 0.05 were considered significant.COUP-TF II is highly expressed in the mesenchymal compartments of developing organs including the prostate 3H]-thymidine incorporation assay. COUP-TF II expression completely blocked androgen-induced DNA synthesis in LNCaP cells . Overexpressed COUP-TF II significantly downregulated the androgen-induced expression of endogenous PSA mRNA  and protin vitro translated COUP-TF II interacted with GST-AR AF1DBDh, GST-AR DBDh, and GST-AR LBD, but not with GST-AR TAU, suggesting the involvement of the DBDh and LBD domains of AR in its interaction with COUP-TF II. COUP-TF II domains responsible for its interaction with AR were then investigated using GST fusion protein of COUP-TF II deletion mutants , suggesting AR interaction with multiple domains of COUP-TF II.GST pull-down assay was performed in order to examine whether AR repression by COUP-TF II is mediated through direct protein-protein interaction. Interactions of AR with COUP-TF II, as well as AR domains responsible for the interaction, were investigated using different AR deletion mutants fused to the GST protein . The in  mutants . The in in vivo interaction between COUP-TF II and AR, we performed coimmunoprecipitation assay with PPC-1 cells which were cotransfected with AR and GFP-fused COUP-TF II expression plasmids. Immunoprecipitations using anti-AR or anti-GFP antibody, followed by Western blot analysis of the immunoprecipitated complexes for AR and COUP-TF II, revealed that AR and COUP-TF II were efficiently coprecipitated , which also targets non-histone proteins including transcription factors and coregulators affecting their transcriptional function , interference with coactivator interactions, and inhibition of DNA binding activity. Our results showed that COUP-TF II competed with some coactivators such as ARA70, SRC-1, and GRIP1 to modulate AR transactivation. ARA70 and SRC-1 exhibit strong hormone-dependent interaction with the AR LBD through the FXXLF motif within the coactivators, and bridge the AR DBD/LBD complex AR also performs a crucial function in prostate cancer cell proliferation, and thus the levels of COUP-TF II expression may affect prostate cancer growth. Consistent with this prediction, COUP-TF II expression is down-regulated in prostate cancers as compared with the normal prostate in an animal model of prostate cancer, namely Myc-driven transgenic mice In the present study, we have shown that COUP-TF II modulates AR function in prostate cancer cells, affecting androgen-dependent cell proliferation. COUP-TF II prevents the N/C terminal interaction of AR, inhibits AR recruitment to its target promoter, and competes with AR coactivators to modulate AR transactivation. The ability of COUP-TF II to repress AR function and inhibit the growth of prostate cancer cells makes COUP-TF II a new candidate as a therapeutic target for prostate cancers.


Although the sebaceous gland (SG) plays an important role in skin function, the mechanisms regulating SG differentiation and carcinoma formation are poorly understood. We previously reported that c-MYC overexpression stimulates SG differentiation. We now demonstrate roles for the androgen receptor (AR) and p53. MYC-induced SG differentiation was reduced in mice lacking a functional AR. High levels of MYC triggered a p53-dependent DNA damage response, leading to accumulation of proliferative SG progenitors and inhibition of AR signaling. Conversely, testosterone treatment or p53 deletion activated AR signaling and restored MYC-induced differentiation. Poorly differentiated human sebaceous carcinomas exhibited high p53 and low AR expression. Thus, the consequences of overactivating MYC in the SG depend on whether AR or p53 is activated, as they form a regulatory axis controlling proliferation and differentiation. ► Myc-induced sebaceous differentiation depends on the androgen receptor and p53 ► The androgen receptor promotes sebocyte differentiation ► Myc induces a p53 response that promotes sebocyte proliferation ► p53 and the androgen receptor are mutually antagonistic The mechanism of Myc-induced sebaceous gland differentiation is largely unexplored. Watt and colleagues now demonstrate that the levels of androgen receptor (AR) and p53 determine whether Myc drives proliferation or differentiation in the murine sebaceous gland. The AR promotes differentiation, whereas p53 responses to Myc activation impair differentiation by inhibiting the AR and thereby promote proliferation. Examination of human tumors suggests that mutual antagonism between AR and p53 may contribute to progression of sebaceous carcinoma. The sebaceous gland (SG) is part of the epidermis and produces the sebum that lubricates the skin surface. SGs are often associated with hair follicles (HFs), and loss of sebocyte function can lead to scarring alopecia, indicating a dependence of HFs on SGs . SG prodMyc was first identified as the cellular homolog of the avian myelocytomatosis viral oncogene (v-Myc)  promoter as a fusion protein with a mutant mouse estrogen receptor (ER) α ligand-binding domain. The MycER transgene is constitutively expressed in the basal layer of the epidermis, but MYCER protein (henceforth MYC) is only activated upon topical activation of 4-hydroxytamoxifen (4OHT). Low levels of MYC activation promote SG expansion and differentiation, whereas high levels stimulate SG proliferation and inhibit differentiation ( (v-Myc)  and origular-Myc . MYC is ular-Myc . K14MycEntiation . MYC is ntiation  and may Ar has been identified by chromatin immunoprecipitation (ChIP) as a MYC target gene in mouse epidermis  layer that gives rise to centrally located differentiating sebocytes. As they accumulate lipids, differentiating sebocytes increase in size , eventuaAR-TFM mice, which lack functional ARs (In telogen back skin of wild-type (WT) mice A–1M, strMyc corepressor, B-lymphocyte induced maturation protein (BLIMP1)  and peroxisome proliferator activated receptor γ (PPARγ) E and 1F.(BLIMP1) G, and we(BLIMP1)   H. Althou(BLIMP1) , we only(BLIMP1)  and in k(BLIMP1)   .K14MycER and epidermal Myc knockout mice  and SG than HFs , consistK14MycER mice were treated once with a low (0.1 mg) or high (1.5 mg) dose of 4OHT or vehicle (acetone) and examined for up to 8 days  staining  levels were reduced throughout the epidermis .To examine whether p53 activation in  for p53 A–6C. IVL for p53 B. Genetip53 deletion did not increase Ar (Nucleolin mRNA expression (Fasn and Pparγ (Ki67 (Keratin 7 (K7), a sebaceous lineage marker    F and S2G in combination with a high dose 4OHT did not promote sebocyte differentiation in  in vivo A and S3C in vivo B and S3C in vivo E, as theWhen 4x2mg casodex treatment was combined with 4x2mg testosterone and a high dose of 4OHT sebocytes differentiation was stimulated to a greater extent than with testosterone alone F and S3GK14MycER mice were treated with a higher dose of casodex (4x8mg) for 4 days, SG differentiation was impaired, mimicking the phenotype of K14MycER AR-TFM mice. The block in differentiation was overcome by addition of testosterone .When low dose 4OHT osterone I and S3JOur results indicate that in undifferentiated sebaceous gland cells, the AR functions as a differentiation enhancer by promoting cell cycle exit and triggering initial lipid accumulation. However, the AR inhibits the later stages of maturation. Our findings may explain some of the conflicting effects of androgens on sebocyte growth, proliferation and differentiation reported in vitro and in vivo .K14MycER mice showed SG enlargement after 4 days, which progressed to SG hyperplasia by 8 days. While the overall differentiation compartment was expanded, this coincided with a partial reduction in AR activity, reduced FASN expression, and accumulation of sebocytes at the top of the gland, suggesting decreased turnover , German Medical Council, and/or the Japanese Ministry of Health, Labor, and Welfare.Quantitation of Ki67, p53+ve cells, and the average cross-sectional area of the SG differentiation compartment were determined from at least ten 10x images of H&E-stained tissue sections per mouse. Only vertical sections of back skin were quantitated. The SG differentiation compartment was identified in H&E sections on the basis of differentiating sebocytes exhibiting pale and enlarged cytoplasm from lipid accumulation. Examples of how measurements were made are shown in Extended Experimental Proceduresp53null mice , AR-Shah mice  and Eda (Ta-6J) x AR-TFM mice . p53null and AR-Shah strains were first crossed onto a C57/Bl6 x CBA F1 background to match our K14MycER mice prior to further breeding. AR-Shah and Eda (Ta-6J) x AR-TFM mice were first crossed to create a compound strain of AR-Shah and AR-TFM and bred onto a near C57/Bl6 x CBA F1 background, before further crossing with K14MycER mice.The following additional strains were used in this analysis: AR-Shah allele contains an IRES Alkaline phosphatase IRES LacZ reporter cassette knocked into the Ar locus following the stop codon  (Jackson ImmunoResearch laboratories Inc 711-065-152) used at 1:300 dilution from a 0.65mg/ml stock solution.Primary antibodies are listed in Samples of mouse back skin were fixed overnight in 4% paraformaldehyde or 10% neutral buffered formalin and stored in 70% ethanol prior to embedding in paraffin or else frozen in OCT compound (Miles) for horizontal whole mounts . ParaffiThe procedure for automated immunohistochemistry was to dewax and rehydrate sections on a Leica ST 5020 and then stain sections on a Leica Bond Max or Ventana Discovery. On the Leica Bond Max p53 was labeled with anti-p53 (DO-7) followed a 30’ citrate treatment, and AR was labeled with anti-AR (AR27) followed by a 20’ EDTA treatment using the Leica Bond Polymer system (DS9800). AR was detected with anti-AR (N-20) followed by a 20’ EDTA treatment, and Ki67 with anti-Ki67 (Tec-3) followed by a 20’ citrate pre-treatment, performed using Vision Biosystems Bond Intense R biotin/streptavidin Detection system (DS9263). Signals were enhanced by 10’ incubation with Bond DAB Enhancer (AR9432-Lecia). All antigen retrieval was performed at 100°C.The Ventana Discovery system was used for labeling sections with anti-c-MYC, anti-p53 (CM5) and anti-Ki67 (SP6) as described previously . Mouse oMicroscopy was performed with a Leica SP5 confocal, Zeiss Axiophot or Zeiss AxioImager M2 fluorescent microscope, using 10x and 20x objectives.2 pieces of back skin were collected, snap frozen and stored in liquid nitrogen until use. All surfaces and equipment were cleaned with RNase Zap. Samples were placed into round-bottom tubes containing 1.5ml Trizol and homogenized using a polytron (setting 11-15), then transferred into 2ml RNase-free tubes and placed on ice until all samples had been processed. Between samples, the polytron was washed sequentially with 1x9ml DEPC water, 1x9ml 70% Ethanol in DEPC water, 1x9ml 1M NaOH in DEPC water and 3x9ml DEPC water, on setting 15. Samples were incubated at RT for 5′ and then 300ul of BCP reagent was added. Samples were capped and shaken vigorously for 15 s until mixed, and left to separate for an additional 3′ at RT. Samples were next centrifuged for 15’ at 12,000 g at 4°C and the aqueous layer transferred to fresh RNase-free tubes. 750ul Isopropanol was added and mixed by inversion then incubated for 10’ at RT before being centrifuged for 10’ at 12,000 g at 4°C. The supernatant was discarded and the pellet washed in 1ml 70% Ethanol in DEPC, then centrifuged for 1’ at 12,000 g at 4°C. The supernatant was again discarded, samples were again centrifuged for 1’ at 12,000 g at 4°C and the last traces of ethanol were removed. Samples were left to dry for 10’ in a fume hood before addition of 50ul nuclease-free water. Samples were incubated for 10’ at 55°C to resuspend RNA. RNA concentration was determined using a nanodrop and preparations stored at −80°C until use. RNAase-free plugged tips were used throughout.0.25-0.5cmGapdh 4352932-1005035, Ar Mm00442688_m1, Keratin 7 Mm00466677_m1, Fasn Mm00662319_m1, Ki67 Mm01278617_m1, Pcna Mm00448100_g1, Pparγ Mm011843222_m1, Nucleolin Mm01290591_m1, p53 Mm01337166_mH, pan p63 Mm00495788_m1, and pan p73 Mm00660220_m1.2 μg of RNA was collected and treated with RQ1 DNase (Promega M610A) according to the manufacturer’s protocol. cDNA was prepared using Superscript III First-Strand Synthesis SuperMix for qRT-PCR Kit (Invitrogen 11752-250). For qRT-PCR 20 μl reactions were established in 96well plate format, each containing 1 μl of probe, 1 μl cDNA, 8 μl nuclease-free water and 10 μl of 2x Taqman Fast universal reaction master mix (Applied Biosystems). Reactions were performed on a StepOne Real-time PCR machine (Applied Biosystems) using a quick-start protocol. Quantitation was performed using the ΔCT method and normalized relative to GAPDH. Taqman probes (Applied Biosystems) were as follows: pRetroQ-mCherry, a mammalian mCherry expression construct, was cloned by excision of mCherry from pmCherry-N1 (Clontech) and exchange with AcGFP in pRetroQ-AcGFP-N1 (Clontech). pRetroQ-Flag-AR-T2A-mCherry, a mammalian dual non-covalently-linked AR and mCherry expression construct, was cloned by PCR addition of an N-terminal Flag-tag and C-terminal T2A linkage sequence to mouse AR cDNA using template pENTR233.1-AR  with product subcloned into pRetroQ-mCherry. pCDNA4-Myc, a kind gift from Dr. Alastair Lamb , was generated by excision of Myc from pBABEpuro c-mycER  and liga4 cells per well and allowed to adhere overnight. Adherent sebocytes were transfected with 0.2 μl Xfect (Clontech), mixed with 0.24 μg pRetroQ-mCherry (parent-vector) or pRetroQ-Flag-AR-T2A-mCherry (AR) and 0.24 μg pCDNA4 (parent-vector) or pCDNA4-Myc (Myc), with 0.2 μg pTA-Luc  or pAR-Luc  firefly luciferase plasmids and 0.02 μg pCMV-RL Renilla luciferase reporter (Promega) for 4 hr according to the manufacturer’s protocol. Total DNA was maintained at 0.7 μg per well by inclusion of parent-vectors as needed.SebE6E7 immortalized human sebocytes were cultured in serum and growth factor supplemented Sebomed medium (Biochrom) as previously described . SebE6E7Sebocytes were incubated in supplemented Sebomed medium overnight, then transferred to medium containing 20 μM testosterone  and/or 10 μM casodex  or DMSO-vehicle for 24 hr. Testosterone and casodex stocks in DMSO were prepared at 1000x. Cells were lysed and assayed using the Promega dual luciferase reporter kit according to the manufacturer’s instructions. Data were collected on a Glomax luminometer (Promega). Luciferase values were normalized by dividing with Renilla luciferase activity values to adjust for transfection efficiency. Each experiment was performed in triplicate and values averaged for each condition. pAR-Luc data are expressed as fold change over values obtained from equivalent conditions with pTA-Luc to adjust for global transcriptional changes and highlight Androgen Response Element-dependent changes. Changes are expressed relative to vehicle (defined as 1) for each transfection combination. This experiment was performed 5 times with independent cell populations.


This virtual screening has successfully identified an α1A/D-AR selective antagonist, with low µM affinity with a novel structural scaffold of a an isoquinoline fused three-ring system and good lead-like qualities ideal for further drug development.In this study four and five-feature pharmacophores for selective antagonists at each of the three α Ligands that can discriminate between α1-AR subtypes based on 100–1000 fold differences in affinity would therefore greatly enhance the task of establishing the distribution and physiological functions of the individual α1-AR subtypes.The α1-AR subtype selective antagonists towards their intended target is a crucial issue due to similarity in receptor structure within the biogenic amine GPCRs 1-AR antagonist therapeutics used for the treatment of hypertension and benign prostatic hypertension (BPH) are associated with side effects such as increased incidence of heart failure, orthostatic hypotension, erectile dysfunction and dizziness The specificity of α1A-AR is the most commonly targeted subtype for the treatment of BPH, the α1D-AR may also be considered a suitable target for both BPH and hypertension. α1D-AR knockout mice display a reduction of systolic and arterial blood pressure 1D-AR is also the predominant subtype in the human bladder detrusor 1D-AR selective antagonist BMY7378 and the selective α1A/D-AR drug tamsulosin indicate α1D-AR blockade improves the lower urinary tract symptoms of BPH 1D-AR antagonist may thus have therapeutic potential for the treatment of hypertension and BPH. It is therefore the aim of our research to identify a structurally novel antagonist characterized by high affinity and selectivity towards the α1D-AR compared to α1A- and α1B-ARs, and other biogenic amine GPCRs.Although the α1A, α1B and α1D -ARs, that were developed using training sets of subtype selective antagonists i values from competition assays using recombinant receptors expressed in cell lines) for as wide a range of structural classes of antagonists as was possible. For α1A and α1D pharmacophores only those compounds that exhibited >100-fold selectivity over α1B and >40-fold selectivity over the other subtype  were included. A set of conformations for each compound in each training set was also generated within the pharmacophore development program Catalyst. As described in our publication 1 –ARs. The α1A pharmacophore consists of four features, describing a hydrogen bond acceptor (HBA), a hydrophobic aliphatic  and a hydrophobic aromatic group (Har), and a basic amine (PI). The training set for this pharmacophore included the two classes of antagonists as described by Klabunde and Evers 1B pharmacophore was generated from antagonists showing selectivity over the other two subtypes, which were predominantly prazosin analogues. This pharmacophore did not include a basic amine feature, as may have been expected, but included 2HBA, Har and Hal features. A five-feature pharmacophore was generated for α1D antagonists. The pharmacophore consisted of HBA, 2Hal, Har and PI features. The training set was heavily populated with analogues of BMY-7378, as these compounds were the only antagonists available which exhibit the appropriate type of selectivity. Despite this limitation of the training set, the pharmacophore was able to accurately predict the affinities of structurally distinct antagonists within a test set.Recently we reported four and five-feature antagonist pharmacophores for the α1D-AR. 9 of the 12 isolated compounds displayed affinity at the α1A and α1D -AR subtypes, and all compounds with α1-AR affinity displayed negative efficacy. A lead compound with α1A/D-AR selectivity and a novel structural scaffold of an isoquinoline fused three-ring system was identified for future drug development projects.In this study, use of these pharmacophores in virtual screening of the National Cancer Institute and Tripos LeadQuest compound databases has identified 12 compounds with predicted high affinity and selectivity for the α1–6 were purchased from Tripos, Inc. (England) and compounds 7–12 were obtained via the Developmental Therapeutics Program of the National Cancer Institute (USA) (http://dtp.cancer.gov/). Drugs were solubilised in dimethyl sulfoxide (DMSO) at 10 mM and stored at −80°C. (-)-Epinephrine, (-)-norepinephrine, phentolamine hydrocholoride, lithium chloride (LiCl) and ±-propanolol were purchased from Sigma-Aldrich. [3H]Prazosin (85 Ci mmol−1) was from Perkin Elmer and myo-[3H]-Inositol (13 Ci mmol−1) was from Amersham. AG 1-X8 resin  was from Bio-Rad. Chemicals for buffered solutions  were obtained from Sigma-Aldrich. Other chemicals used were of the highest purity available.Compounds 1A-, α1B- and α1D-ARs were compared to each other and only unique hits (hits found only in one of the three lists) were kept. Estimates of fit were determined individually for each compound using the ‘Rigid’ fit option after ‘Best’ conformational searching, with the number of features allowed to miss set to one.The chemical databases NCI2000  and Tripos' LeadQuest Sample GPCR subset (3040 compounds) were searched in Catalyst version 4.11  using four and five feature subtype specific pharmacophores that we have previously developed −1 penicillin and 100 µg ml−1 streptomycin. Cells were maintained and passaged upon reaching confluence by standard cell culture techniques. pMT4 plasmids containing rodent α1-AR  were used to transfect cells. Transient expression in COS-1 cells was accomplished using two techniques; the diethylaminoethane-dextran (DEAE-dextran) and Lipofectamine 2000  methods. Briefly, the DEAE-dextran method involved washing of cells with phosphate buffered saline (PBS), followed by the addition of the DNA mixture (12–25 µg/4×106 cells) in DEAE-dextran (10 mg ml−1) to cells at 60–80% confluency. Following a 3 h incubation, a PBS wash with 10% DMSO was used to shock the cells. Cells were harvested 72 h post transfection. For the Lipofectamine 2000 method, cells were incubated for 12 h with Opti-MEM  containing Lipofectamine 2000.COS-1 cells  were cultured in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% (v/v) heat inactivated fetal bovine serum (FBS), 100 µg ml2) containing 10% (v/v) glycerol and stored at −80°C until use. Protein concentration was determined using Bradford reagent .Membranes were prepared as described previously 3H]Prazosin, COS-1 membranes, and increasing amounts of unlabelled National Cancer Institute or Tripos LeadQuest compounds in a total volume of 200 µL. In saturation binding experiments, membranes in HEM buffer were incubated with various concentrations of [3H]Prazosin in a total volume of 200 µL. For all binding experiments, the reaction mixture was incubated for 1 h at room temperature, stopped by the addition of 4°C PBS and filtered with a Brandel cell harvester  on GF/C filters. Nonspecific binding was defined as binding in the presence of 100 µM phentolamine hydrochloride.Competition binding reactions contained HEM buffer, 200 pM of [3H] inositol phosphates (IPs) was determined as described previously 1A, α1B and α1D - AR pMT4 plasmids using the Lipofectamine method. 24 h after transfection, cells were seeded into 96 well plates and labelled overnight with 20 µCi ml−1 [3H]myo-inositol in inositol free DMEM supplemented with 5% charcoal stripped FBS. Cells were washed twice with inositol free DMEM, and incubated in inositol free DMEM for 2 h at 37°C. Cells were treated for 20 minutes with LiCl (20 mM) and propanolol (20 µM) in the presence or absence of tested compounds. Agonists were then added for 30 min, and the reaction was terminated by addition of 0.4 M formic acid. Cells were lysed by freeze thawing twice and were applied to AG 1-X8 columns. Total IPs were eluted with 1 M ammonium formate in 0.1 M formic acid. 200 µL of eluted sample was diluted with 1 mL reverse osmosis water and 5 mL Ultimaflow scintillation fluid (Perkin Elmer), and were counted in a liquid scintillation counter.Accumulation of [Ki) were determined by transformation of the program-calculated IC50 (concentration of ligand resulting in 50% inhibition of [3H]prazosin) value using the Cheng-Prusoff equation. The competitive binding data for each ligand was tested for both one and two -site binding. Subsequently a one-site binding model was determined as the appropriate form of analysis for all binding data. Receptor densities (Bmax) and the dissociation constant (DK) for [3H]-prazosin were calculated using the specific binding of the radioligand. Statistically significant differences (p<0.05) in the affinities of compounds were determined using one way ANOVA and Student-Newman-Keuls multiple comparison test.Nonlinear regression analysis of saturation and competition binding assay data was performed using the noniterative curve fitting program GraphPad Prism . Inhibition constants , Boolean operators were used in Catalyst. Using this method it was determined that there were 1866 unique α1A hits (0.78% of the whole database), 37746 unique α1B hits (15.81%) and 446 unique α1D hits (0.19%). It is interesting that substantially more hits were returned by the α1B pharmacophore than by α1A and α1D. This may well be due to the ‘positive ionisable’ (PI) features of the α1A and α1D pharmacophores being more restrictive in terms of database searching. The PI feature in Catalyst is used to describe an atom which is expected to be positively charged at physiological pH. In the case of ligands at adrenergic receptors, this is usually a basic nitrogen atom.Searching the NCI2000 database returned 7630 hits for α1-AR subtype. The α1A-AR pharmacophore returned 11 compounds with predicted picomolar activity. Many of the top compounds exhibited three fused rings, one compound (NCI0025463) had six fused rings. The α1B pharmacophore returned 25 hits with predicted affinities in the picomolar range. Many of the returned hits were structurally similar to cyclazosin, a known α1B selective ligand, displaying fused rings with substituents on analogous ring atoms. The α1D pharmacophore returned a number of low nanomolar unique hitters with a variety of structures. Compound NCI0009677 is an adrenaline analogue with two long carbon chains. Two hits (NCI0169489 and NCI0167773) have a fused ring system similar to the compounds boldine and IQC, which have been previously investigated for their activity at the ARs All unique hits were fitted to the pharmacophores to estimate their affinities at each α1A-AR, 2144 hits for α1B-AR and 944 hits for α1D-AR. These hit-lists contained 157 unique α1A-AR hits (5.16%), 732 unique α1B-AR hits (24.1%) and 97 unique α1D-AR hits (3.19%). Of these unique hits 33 of the α1A-AR, 5 of the α1B-AR and 1 of the α1D-AR hits had picomolar predicted affinities. The top hits for α1A-AR were all relatively linear structures and most contained aromatic rings at both ends of the structure and a piperazinyl, or similar, central ring. The α1B-AR hits were similar, but had more branching evident in the central parts of the structures. The best α1D-AR hits exhibited a similar structural layout to the α1A-AR hits, but in general were shorter in length.The GPCR subset of the Tripos LeadQuest database contains compounds which fit a general pharmacophore of a basic nitrogen and an aromatic centre. Our pharmacophore screen returned 1125 hits for α1D-AR hitlists for in vitro testing at the α1 ARs . All competition radioligand binding curves displayed sigmoidal binding with the Hill slope for all experiments not significantly different from 1.0 (p<0.05), suggesting all compounds compete at one site with [3H]-Prazosin.The selected compounds  were ass4, 5 and 10, all compounds displayed affinity for the α1-ARs in the micromolar range (Ki<2 µM) was exhibited by compound 1 at all α1-AR subtypes, with compound 11 also displaying moderate affinity at the α1A- and α1D- ARs. Compound 2 displayed the highest affinity of all compounds with a Ki of 0.49 µM at the α1A-AR. Six of the nine compounds which had α1-AR affinity exhibited selectivity for α1A-AR and/or α1D-AR over α1B-AR . Increased selectivity for α1A (7-fold) and α1D (17-fold) compared to α1B (p<0.005) was observed with compound 11.With the exception of compounds ar range . Moderatr α1B-AR . The gre1-AR affinity (Ki) at concentrations less than 100 µM were subsequently screened to determine their efficacy at all α1-AR subtypes using a phosphatidylinositol hydrolysis assay. Compounds were administered alone (100 µM) or prior to the addition of 10 µM (-)-epinephrine, to screen for agonist or antagonist activity respectively. This dosage of (-) epinephrine was chosen as it resulted in a sub-maximal inositol phosphate (IP) response.Those compounds displaying α1-AR subtypes, treatment with compounds alone did not result in changes in IP production compared to that of the control (untreated COS-1 cells expressing the α1-AR subtype) , with the exception of 8, for which a distinct trend of increased IP production was observed at the α1A- and α1D-ARs.Across all α1, 2, 8 and 11) were selected for further biological testing with the aim of confirming and characterizing their activity quantitatively in terms of IC50 (antagonists) or EC50 (agonist) values for the α1A-AR. Criterion for selection of a compound was either an affinity (Ki) of ≤5 µM for the α1A-AR or agonist activity.Four compounds  norepinephrine stimulation at the respective α1-AR subtypes (1A-AR (pIC50 (M) 11, 4.88±0.27, n = 5, 1, 4.60±0.11, n = 5 and 2, 4.77±0.227, n = 4).Compounds subtypes . All thr8 of COS-1 cells expressing the α1A-AR ). Maximal IP production induced by compound 8 was approximately 30% of the (-) norepinephrine control  feature entirely  (11 onto the α1A-AR pharmacophore is consistent with the poor (micromolar) affinity of this compound at this receptor subtype, when compared to a typically nanomolar antagonist, such as the ones used in the development of the pharmacophore 1B  . This fephore 1B , with onacophore , all fivin silico, from which 12 compounds were selected based on structural diversity and novelty, predicted high affinity and selectivity for the α1D-AR. 75% of the tested compounds display affinity below 100 µM at the α1A and/or α1D -AR subtypes and 50% at the α1B-AR. Furthermore, 25% of compounds have affinity in the low micromolar range (Ki<5 µM) at the α1A-AR, and 17% at the α1B- and α1D-ARs. As these compounds only represent ‘hits’, it is not expected at this stage of the drug discovery process that compounds will have affinities comparable to established α1-AR ligands such as prazosin, which has a Ki value of approximately 0.1 nM at all α1-AR subtypes et al., We have used pharmacophores to screen 241859 compounds 1-AR pharmacophores is comparable to the ‘hit’ rates achieved using the structure based virtual screening technique of docking at the serotonin 5-HT1A and 5-HT4, dopamine D2, chemokine CCR3 and tachykinin NK1 receptors Ki values <5 µM). A similar docking study using an α1A-AR homology model identified 37 novel antagonists, with an impressive ‘hit’ rate  of 46% Ki value cut-off not defined) The ‘hit’ rate of 17–25% displayed by our α1D-AR selective 1, α1A-AR selective 2, and the α1A/D-AR selective compounds 8, 9, 11 and 12 indicates that the pharmacophores do contain structural motifs important for α1-AR subtype selectivity. Furthermore, as no selective α1B-AR compounds were isolated and 50% of the compounds were α1A and/or α1D –AR selective, this suggests screening the compound libraries using the α1B-AR pharmacophore did successfully identify and eliminate compounds with this characteristic from the pool of compounds.The isolation of the α1A- and α1D-AR subtypes reflects the lack of α1A/D- AR selectivity of the training sets used to generate the α1A- and α1D-AR pharmacophores 1A over α1D-ARs, and therefore it is not expected that compounds isolated by the pharmacophores would display large α1A/α1D selectivity.The inability to distinguish between the α1-AR pharmacophores in the literature have been primarily used to screen the affinity of derivatives of established α1-AR ligands 1-AR affinity, with the purpose of isolating which chemical moieties provide the most advantageous characteristics of affinity and selectivity. In contrast to this, in this study large compound libraries of structurally diverse compounds have been screened, which has the benefit of identifying compounds with novel structural scaffolds. This represents the first attempt to screen diverse compound databases using α1-AR pharmacophores, representing a novel approach to the identification of α1-AR ligands.α1-AR antagonists. All the compounds possess a central basic nitrogen, but it is the nature of the basic centre, the substitution of aromatic rings and the spatial orientation of chemical groups that determines subtype selectivity profile 1 contains a piperazine ring motif, which is a common structural motif in α1-AR antagonists. There has been extensive research into this class of α1-AR antagonists, and analysis of the chemical structures of selective α1-AR antagonists indicates that a large group of active compounds contain the N-aryl or N-heteroaryl piperazine motif 1-AR selectivity 2-AR 1A1 does not represent a suitable lead compounds in terms of structurally novelty, and potential for subtype selectivity.There are currently eight established structural classes of α11 however contains a novel fused isoquinoline three-ring system. Whilst fused four-ring motifs are found in berbine derivatives, such as the natural product (-) discretamine 1-AR antagonism, a fused three-ring system has not previously been described for α1-AR ligands , facilitating synthetic elaboration to enhance affinity and selectivity. While the free base has a relatively high calculated partition coefficient (clogP 4.9), salts can easily be prepared to enhance aqueous solubility.Compound  ligands . Further1-AR subtypes, optimisation will be guided by docking into our previously described homology models We are currently developing a convergent synthesis of compound 11, allowing synthetic access to the molecule itself, as well as analogues for optimisation. In the absence of crystal structures of the three α11 therefore represents a suitable lead compound for future drug development projects, due to its novel conformationally constrained structure, its “lead-like” properties and desirable affinity, efficacy and selectivity characteristics.In conclusion, the computer-aided drug discovery ligand-based pharmacophore technique has been established as a powerful alternative virtual screening tool. Compound


Field assessments were conducted to examine the interplay between host plant and predation in complex agricultural mosaic on pea aphid clover and alfalfa races. In one experiment, we examined the relative fitness on clover race (CR) and alfalfa race (AR) pea aphids on broad bean, red clover and alfalfa alone. But because clover is typically grown in a more complex agricultural mosaic with alfalfa and broad bean, a second experiment was conducted to assess the fitness consequences under predation in a more complex agricultural field setting that also included potential apparent competition with AR pea aphids. In a third experiment we tested for the effect of differential host race density on the fitness of the other host race mediated by a predator effect. CR pea aphids always had fitness losses when on broad bean (had lower fitness on broad bean relative to red clover) and fitness benefits when on red clover (higher fitness on red clover relative to broad bean), whether or not in apparent competition with alfalfa race aphids on bean and alfalfa. AR suffered fitness loss on both alfalfa and bean in apparent competition with CR on clover. Therefore we can conclude that the predation rate between host races was highly asymmetrical. The complexity of the agricultural mosaic thus can influence prey selection by predators on different host plants. These may have evolutionary consequences through context dependent fitness benefits on particular host plants. Speciation in phytophagous insects has earned significant attention in recent years Acyrthosiphon pisum) populations. This species is considered a useful model to identify how divergence in host use may have arisen Here, we explore the potential for predation to be a determinant factor for differences in the performance of host adapted pea aphid (Vicia faba) and red clover (Trifolium pratense) and then the performance of AR pea aphids on broad bean and alfalfa (Medicago sativa) in the presence and absence of predation  of CR pea aphids on broad bean  are often planted in close proximity in mosaics of different sizes. This adjacency may have direct influence on predation rate of a widespread herbivorous species such as pea aphid. Lady beetles are generalist predators typically present in these agricultural mosaics and feeding in pea aphid colonies. Their predation level might differ between aphid host plants and thus create the conditions needed to cause differential aphid fitness among different host plants. Pea aphids have complex life cycles that include all-female, parthenogenetic generations that alternate with sexual generations. Each female gives birth to 50–100 living young at the rate of 6 or 12 a day. There are up to 20 or more generations a year. Pea aphids provide some of the best studied instances of host-plant adaptation and has repeatedly generated host-specialized populations adapted to both crops and wild legumes Aphids for rearing were collected as a part of a pest-management program that local farmers used to control aphid damage on agricultural fields. We were not responsible for, nor executed the pest-management program. Before aphid collection, farmers were contacted and permission obtained to enter their fields. For insect collection, no permits were required since the area where pea aphids and lady beetles were collected did not contain any strictly protected areas. Permits were also not required to use insects for experiments due to the observational nature of the data collection. All animal work was conducted according to relevant national and international guidelines. All aphids and lady beetles were released after the experiments.CR and AR pea aphids used in experiments were collected during the spring and summer from four different clover and four different alfalfa fields. Fields were located between 5 and 270 km from each other. Adult aphids were sampled during May four times each to have genetically mixed individuals from the same host species, thereby reducing the possibility of similar susceptibility to biotic and abiotic factors due to possible local adaptation. Prior to experimentation, aphids were reared in low-density populations to avoid stress by overcrowding on host plants  and on broad bean (stock name The Sutton). Host plants were grown individually in 15-cm diameter and 20 cm deep plastic pots under controlled greenhouse conditions with 16 h light, 8 h dark, 25°C, and 75% relative humidity to simulate the normal summertime climate. Altogether, 20 host plants from clover, 20 from alfalfa, and 40 from broad bean were used to rear aphids. Host plants were potted individually and pots were placed in dishes and watered by filling the dishes. This allowed water to be drawn upward through holes in the bottom of the pots, thereby preventing disturbance to aphids on plants. Ten host plants were isolated from each other in two blocks to avoid mixing races, one containing CR on clover and bean (20 clover and 20 broad bean plants) and the other AR on alfalfa and bean . Aphids were controlled for age by removing the adults after three days of reproduction. The offspring were reared until they had just molted into adulthood and then they were transferred to new plants where they could reproduce for another three days and were then taken off the plant. This procedure was repeated again and aphids from the next generation were used for experiment. This method  were the most frequent predator during the whole assessment period, with numbers reaching a maximum of 50 individuals in one subplot. For experiments, lady beetles were obtained from the same fields  48 h prior to use in cages. To identify males and females, all individuals from the same field were kept together for 24 h. If mating between two individuals was observed, they were isolated together in a separate plastic dish and used together  in cages for the experiment. This avoided biased predator effects because predation level of males and females may differ; in particular, mated females are considered to have the higher appetites than males when forming eggs.During and after aphid collection, assessments were carried out daily for three-week periods in clover, alfalfa, and two bean fields to identify the dominant predator. Six plots/field of ∼6 mThis field experiment was performed using CR, AR and its lady beetle predators to test the relative performance of aphids in a simple agricultural mosaic. The experiment was conducted using red clover, alfalfa and broad bean host plants. Host plants were seeded at the end of April at normal crop density. The experiment started in the middle of June when host plants were approximately 40–45 cm high. Before the experiment, all other insects were removed from plants, after which plants were caged with low (0.2 cm) mesh-size net allocated at least 5 m from other blocks . There wRed clover with CR (10 control cages and 10 cages with predator).Broad bean with CR (10 control cages and 10 cages with predator).Alfalfa with AR (10 control cages and 10 cages with predator).Broad bean with AR (10 control cages and 10 cages with predator).Each plant was examined after one day (when each adult had given birth to 8–10 offspring). If no reproduction or dead females were observed, then individuals were replaced. Aphids were allowed to reproduce for three days, having approximately 160–180 offspring in each cage. In ten treatment cages, two adult  lady beetles were introduced and the cages were closed again. Ten cages from each combination were kept free of predators and used as the control. One day later, all cages were carefully checked. Any plants that were attacked by ants from the ground  were excluded from any further assessment. Cages were examined every second day until the end of the 12-day experiment because at that time, female beetles laid eggs and new emerging lady beetle larvae would bias the aphid predation rate. Therefore, once eggs were observed (first time after 10 days) the cage was removed and the entire host-plant plot cut and brushed into a white plastic dish. The experiment was run for 10 days during which time none of the original offspring reached adulthood and started reproducing. In none of the cages the adult density overreaches the initial stoking number of adults at the end of the experiment; however we found relatively high number of fourth instar pea aphid nymphs. All initial predators survived until the end of the experiment. Aphid population density was counted by assessing separately adults and offspring on the entire host plant.The second field experiment was conducted using the host plants alfalfa, red clover, and broad bean in a typical row-crop agriculture planting . The expRed clover with CR +Alfalfa with AR (9 control cages and 9 cages with predator).Red clover with CR +Broad bean with AR (9 control cages and 9 cages with predator).Alfalfa with AR +Broad bean with CR (9 control cages and 9 cages with predator).Broad bean with AR +Broad bean with CR (9 control cages and 9 cages with predator).These host plant combinations were selected because this mosaic pattern of cultivated leguminous plants is the most frequent in both US and Europe. Host plants within cages were separated by approximately 20 cm to prevent aphids from moving between host plants. Pea aphids feed by penetrating plant organs with their stylets in search of vascular tissues Nine cages from each combination were assigned as treatment and two adult  lady beetles were placed on host plants inside each cage and left to move and feed. Nine cages from each combination were kept free of predators, and used as the control. Any plants that were attacked by ants from the soil were excluded from any further assessment. Cages were examined every second day until the end of the experiment. During this time the initial ratio of color morphs (50–50% red and green for CR and 40–60% red and green for AR) was assessed to evaluate potential movement between host plants. We observed the same color combination ratio throughout the experiment including the final number of offspring. All predators survived the experiment and during routine checks we observed predation on aphids. Because of cage exclusion (one from each host plant combination except broad bean+broad bean where we excluded two from control and one from predator treatment), we balanced the number of replicates for the predation treatment and control before the final assessment was made by randomly selecting six blocks of each host-plant combination. Again, once beetle eggs were observed, the cage was removed and the entire host plant plot was cut and brushed into a white plastic dish. This experiment also ran for 10 days during which time none of the original offspring reached adulthood and started reproducing. Aphid population density was counted by assessing separately adults and offspring in the entire host plant.We conducted the third experiment using the same protocol as experiment II, but with different starting densities of pea aphids. Host plants were assigned in replicates as described above. Different starting densities of CR and AR pea aphids were placed on host plants in the following combinations:Red clover with 12 CR adult aphid+Alfalfa with 6 AR adult aphids (6 control cages and 6 with predator).Red clover with 6 CR adult aphid+Alfalfa with 12 AR adult aphids (6 control cages and 6 with predator).Red clover with 12 CR adult aphid+Broad bean with 6 AR adult aphids (6 control cages and 6 with predator).Red clover with 6 CR adult aphid+Broad bean with 12 AR adult aphids (6 control cages and 6 with predator).Alfalfa with 12 AR adult aphid+Broad bean with 6 CR adult aphids (6 control cages and 6 with predator).Alfalfa with 6 AR adult aphid+Broad bean with 12 CR adult aphids (6 control cages and 6 with predator).Broad bean with 12 AR adult aphid+Broad bean with 6 CR adult aphids (6 control cages and 6 with predator).Broad bean with6 AR adult aphid+Broad bean with 12 CR adult aphids (6 control cages and 6 with predator).A. bipunctata were placed in each cages. Six cages from each combination were kept as a predator free control. Cages were examined every second day until the end of the experiment. During this time the initial ratio of color morphs (50–50% red and green for CR and 40–60% red and green for AR) was assessed to account for movement between host plants. We observed the same color combination ratio throughout the experiment including the final number of offspring. All predators survived the experiment and during routine check aphid consumption was observed. No cages were excluded from the assessment. The same protocol was repeated throughout the experiment. The experiment lasted 9 days during which time none of the original offspring reached adulthood and started reproducing.All blocks were caged as described above. We let the aphids reproduce for three days having approximately 300–320 individuals/host plant in high and approximately 160 individuals/host plant in low density populations. Six cages from each combination were assigned as the predation treatment and two adult  For all experiments we used the final count of aphids for fitness analyses. The total counts of offspring at the end of the experiment were divided by the initially stocked adult density to estimate fitness (per capita reproduction). Data from experiment I did not meet the assumption of normality. Therefore the nonparametric Kruskal-Wallis test was used followed by a Mann-Whitney test to compare CR and AR fitness in the presence and absence of predators. Data from Experiment II met the assumption of normality therefore paired t-tests were used to evaluate whether fitness differences arose within host races. For the experiment II, we conducted four independent contrasts to evaluate CR fitness changes due to predation when CR on either clover or bean is juxtaposed with AR on either bean or alfalfa. The fitness loss for both experiments I and II was calculated as: Fd = P*100/C where Fd is the % fitness difference between predator (P) treatment and control (C). Relative fitness loss was calculated as 1-Fd.Data from experiment III did not meet the assumption of normality; therefore the nonparametric Kruskal-Wallis test was used, followed by a Mann-Whitney test to compare the CR and AR fitness with different starting adult densities in the presence and absence of predators. This was done by using comparisons of host races within same densities in host plants. The first comparison evaluated the performance of CR on clover and AR on alfalfa (separately low densities in the presence and absence of predator and high starting adult densities in the presence and absence of predators). The second evaluated the performance of CR on clover and AR on broad bean in the presence and absence of predator. The third evaluated the performance of CR on broad bean and AR on alfalfa, while the fourth evaluated the performance of CR and AR both on broad bean in the presence and absence of predators. Confidence limits of P≤0.05 were considered significant for all experiments.White bars on figures represent CR, grey bars represent AR. The per capita reproductions (fitness) in Experiment I revealed that within host plants CR fitness did not differ between predation treatment and control; however AR suffered significant fitness loss due to predation on both alfalfa and broad bean . ExperimFitness loss of CR and AR varied with CR and AR starting density. There was no significant predator effect on fitness of CR on clover in either high CR vs. low AR density (CR p = 0.37) or low CR vs. high AR density (CR p = 0.99). However AR suffered significant fitness loss in high CR vs. low AR density combinations (AR p = 0.03) but no fitness loss in low CR vs. high AR density combinations (AR p = 0.24) .CR did not suffer any fitness loss when on clover in high and low density combination with AR on broad bean , whereas AR suffered significant fitness loss in both cases  .CR and AR in both high and low densities encountered significant fitness loss when CR was on broad bean in combination with AR on alfalfa  .Fitness loss of CR and AR were significant when in high CR vs. low AR density on broad bean . Only AR suffered fitness loss when both races were on broad bean in low CR vs. high AR density  .Insect host races are expected to arise when individuals are under different pressure, potentially leading to divergent selection via reproductive isolation In combination, experiments 1 and 2 suggest that predation impacts fitness of CR aphids when CR aphids are on bean, but only when they are in the presence of AR aphids. Thus, for CR aphids, both host plant and the presence of competitors influence fitness . This isCollectively, the experiments cannot provide definitive evidence for context-dependent predator-mediated apparent competition between CR and AR. This is because the possibility still exists that predation impacts on CR fitness on clover could be an increase in reproduction by the aphids, or it could simply be an interaction between the plant and aphid in the presence of the predator, with not real negative indirect interaction as a consequence of sharing a common natural enemy. According to our results there is clearly some interaction between host plant and aphid biotype in response to predation, however if this is an increased in reproductive potential of CR aphids when the predator is present this is apparent mutualism. In the case of CR aphids on bean however there is clearly a shift in predation to attacking CR aphids, which is apparent competition. Thus, the impacts of predation on aphid fitness are highly asymmetric and complex and dependent on both aphid genotype and environmental context.Helicoverpa zea), that clearly benefits from the presence of pea aphid but not vice versa: an asymmetric apparent mutualism Theory suggests that interactions in which the effect of one prey species on another is negative and the reciprocal effect is positive should be common Moreover, broad bean excretes extrafloral nectar, which may attract predators. This may explain the high vulnerability of both races when on bean but not on their clover and alfalfa hosts . The red