Furthermore, resident fishes were 37% less abundant and 23% less species rich per reef, compared to control reefs. Such changes in site-attached fish may reflect lower fish growth rates and/or survivorship. Additionally, juveniles of visitors (fish likely to move between reefs) were 65% less abundant on removal reefs suggesting cleaners may also affect recruitment. This may, in part, explain the 23% lower abundance and 33% lower species richness of visitor fishes, and 66% lower abundance of visitor herbivores (Acanthuridae) on removal reefs that we also observed. This is the first study to demonstrate a benefit of cleaning behaviour to client individuals, in the form of increased size, and to elucidate potential mechanisms leading to community-wide effects on the fish population. Many of the fish groups affected may also indirectly affect other reef organisms, thus further impacting the reef community. The large-scale effect of the presence of the relatively small and uncommon fish, Labroides dimidiadus, on other fishes is unparalleled on coral reefs.Cleaning behaviour is deemed a mutualism, however the benefit of cleaning interactions to client individuals is unknown. Furthermore, mechanisms that may shift fish community structure in the presence of cleaning organisms are unclear. Here we show that on patch reefs (61–285 m Labroides dimidiatus−1 and consumes an average 1218 ectoparasites day−1−1On coral reefs, cleaning organisms - which include shrimps and fishes - perform the function of removing ectoparasites from ‘client’ organisms, usually reef fishes L. phthirophagus for one and seven months and L. dimidiatus for six months and two years There has been considerable debate about the mutualistic nature of cleaning symbioses. Benefits to cleaners are well documented; cleaners enjoy nutritional rewards from eating ectoparasites and protection from predation L. dimidiatus affected clients in three experiments. A short-term study (24 h and 12 d) at Lizard Island found that caged Hemigymnus melapterus had more and different sizes of parasitic isopods in the absence of cleaners, compared with controls In contrast, the removal of L. dimidiatus for 8.5 years, while similar control reefs had not had cleaner fish removed. First, to determine whether cleaning affects client size, we surveyed two common resident client fishes, Pomacentrus moluccensis and P. amboinensis, whose life spans are around eight  and six years , respectively. Therefore, many individuals had experienced these experimental conditions for their entire lives. For each of these two species on each reef, we measured the sizes of all individuals and their total abundance. Second, we recorded the abundance and species richness of residents, juvenile visitors, and adult visitors on experimental removal and on control reefs.We investigated the long-term effects of cleaners on fish communities at Lizard Island in the longest study of its kind. We used an ongoing study in which patch reefs at two sites had been kept free of P. moluccensis per reef differed with cleaner presence , with the mean abundance per size class on reefs without cleaners skewed toward smaller individuals, compared with control reefs  and control reefs (265.3±25.7) ; however, abundance per reef was higher at Casuarina Beach (292.79±34.0) compared with the Lagoon (180.5±22.6) , possibly due to the small number of individuals on two reefs . When these reefs were omitted, the size distributions of P. amboinensis were affected by cleaner presence   and control reefs (59.4±8.5)  or between sites  , as for P. moluccensis: χ2 = 54.6, df = 5, P<0.001; P. amboinensis: χ 2 = 11.2, df = 5, P = 0.048), with smaller individuals at Casuarina Beach; the interaction between cleaner presence and site was not significant .For both damselfishes, size distributions per reef differed between sites (P>0.05), except once where stated.In all analyses, no interactions between cleaner presence, site or time period of day  were significant  were included as a random effect in the model, resident abundance per reef was lower on reefs without cleaners, compared to those with cleaners . Resident abundance also differed between sites , and increased with reef area . Simpson's index of diversity per reef for residents did not differ between removal (0.78±0.03) and control reefs (0.77±0.02) , were identified with 11 only found on reefs with cleaners . After 11,11 = F6.9072, P = 0.0235, 1,11 = F2.0736, P = 0.1777, A total of nineteen species of juvenile visitor fishes were identified, with 7 and 1 found only on reefs with and without cleaners, respectively . JuvenilL. dimidiatus removal  compared with control reefs (102.3±4.5)  Acanthuridae abundance per reef was affected by cleaners ; when back-transformed, it was 66% lower on removal (7.5±0.2) compared with control reefs (22.1±0.2); it also increased with reef area  were included as a random effect, visitor abundance per reef was lower on reefs without cleaners, compared to those with cleaners . Abundance also differed between sites , did not differ among times of day (P>0.05), and increased with reef area . For the visitor Simpson's diversity index per reef, there was a significant interaction between cleaner presence and reef area  and no association with area on reefs with cleaners . Similarly, after 18 months, visitor abundance was lower on removal (7.6±3.3) compared to control reefs (25.9±2.9) , the species composition of clients was different, and species richness was lower, factors which all may contribute to how quickly an effect of cleaning is observed. Furthermore, abundance was not measured in the Red Sea, so it is possible that individuals of absent species were replaced by individuals from the remaining species. Finally, Simpson's diversity index did not differ with cleaner presence for residents in our study; this suggests that the relative abundances across resident species were relatively even, regardless of cleaner presence.While the species richness of resident fish (mostly damselfishes) per reef was not affected by cleaner presence after 18 months, it was lower after 8.5 years on reefs without cleaners. These results suggest that this effect of cleaners became apparent during this period. After 8.5 years, residents were also 37% less abundant, a parameter never previously measured. That the abundances of P. amboinensis larvae , by affecting their performance as measured by swimming and oxygen consumption Dascyllus damselfish larvae can recognise the cleaner fish L. phthirophagusThis is the first study to consider juveniles separately from adult clients. The abundance of visitor juveniles was 65% lower in the absence of cleaners, suggesting that cleaner absence may decrease recruitment success or increase post-settlement migration of visitor species. Indeed, attacks by single parasitic gnathiid isopods decrease the successful settlement of L. dimidiatus compared with control reefs both after 18 months and 8.5 years. This indicates the pattern likely persisted during this period. After 8.5 yrs, the Simpson's diversity index was also affected by cleaner presence but this was related to reef area, with a decrease with decreasing reef area on reefs without cleaners and no association with area on controls. Since visitor species richness increased with area, regardless of cleaner presence, while abundance did not, the lower species richness on smaller reefs may have made the diversity of such reefs more vulnerable to cleaner absence. This pattern may be related to habitat diversity, which often positively affects species richness For adults of visitor species, local abundance and species richness were lower on reefs without Hemigymnus melapterus) at this location were higher in the absence of cleaners after 24 h and 12 d Visitor clients, by definition, are more likely to modify their movements to search for cleaners, as these clients have the ability to select from several cleaning stations within their larger home ranges L. dimidiatus shortly before the observations were made as this occurred only on two reefs, and involved only two juvenile cleaner individuals. More importantly, collecting cleaners was done quickly and controls were similarly disturbed by counting L. dimidiatus on most surveys and leaving collecting equipment on the reef during counts.The effects of cleaner fish on clients are unlikely to have been a temporary effect due to disturbance from the removal of Acanthurus, Ctenochaetus, Zebrasoma), revealed abundance was 66% lower in the absence of cleaners. Herbivorous reef fishes limit the establishment and growth of algae that impede coral recruitment The localised ecological effects of cleaner fish on fishes may have other indirect cascading effects on the reef community. Resident fishes consisted of herbivores and planktivores and visitors included herbivores, detritivores, piscivores, corallivores, and invertebrate predators. Herbivores were diverse and prominent on the reef . The abundance of the most abundant and ubiquitous trophic group and family, the herbivorous Acanthuridae surgeonfishes  the behavioural interaction of cleaning of client fish by a relatively small number of small-sized fish has profound ecological consequences and (b) as ectoparasites are central to cleaning interactions, parasites can have a large effect on the population and community ecology of reef-fish. The presence of Positive interactions, including mutualisms, are considered important to communities because they make the environment, directly or indirectly, more favourable for associated species which in turn often facilitates the establishment of other species L. dimidiatus is one of the top ten most exported aquarium fish species to the United States of America and the United Kingdom L. dimidiatus, however, are unknown. Given the importance of the species L. dimidiatus, conservation and management strategies may need to also focus on the protection of this key species.This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of Australia. The protocol was approved by the Animal Experimentation Ethics Committee of the University of Queensland (Permit Number: SIB/821/08/URG). To ameliorate animal suffering, cleaner fish removed from experimental reefs were immediately placed in plastic bags with seawater and then released in a similar habitat.2; mean ± s.e.: 131±34 m2) and nine control reefs  in September 2000 L. dimidiatus  were removed from removal reefs in September 2000. On 35 subsequent occasions at several month intervals, reefs were inspected for L. dimidiatus and any new recruits were removed. Subsequent removals occurred in 28% of all reef inspections, mostly in the summer, with 78% of removals involving 1–2 individuals reef−1, usually juveniles . These reefs were the least isolated experimental reefs, being about 5 m from the nearest reef Periclimines or Urocaridella shrimp, were also observed on reef 11  and 15 (control), respectively, but not removed; their densities were low and so their presence unlikely to have a significant impact. All reefs were resurveyed 4–6, April 2009 for L. dimidiatus. A just-settled juvenile was observed on 4 April (reef 3), 4 d before the survey of visitors; it was so small it could not be captured with the available handnet and had disappeared the next day. Another juvenile was observed and collected 2 May (reef 8), after resident and visitor surveys and 2 d before damselfish size surveys.We used 18 small spatially isolated patch reefs (3 to 7 m depth) located off Lizard Island , GBR, Australia at two sites: in the southern lagoon  and off the research station  uveniles . All reeol reefs . On remoet al.Acanthurus spp.), or species that are likely to spend weeks or months at one reef, but might move between reefs over a longer period, such as wrasses (Labridae), butterflyfishes (Chaetodontidae) and groupers (Serranidae). Because of their cryptic behaviour, cardinalfishes (Apogonidae), pipefishes (Sygnathidae), blennies (Blennidae), dottybacks (Pseudochromidae), and gobies (Gobidae) were not counted.Fish surveys alternated between randomly selected control and removal reefs within a site. Fishes were classified as either ‘visitors’ or ‘residents’ using lists adapted from Grutter et al.Adult visitors were identified and counted per reef (7–9 April 2009) in the morning (0900–1030 hrs), midday (1115–1245 hrs) and afternoon (1330–1500 hrs) following Grutter Resident fishes , which aPomacentrus moluccensis and P. amboinensis were ideal resident client study species for the assessment of size class distributions because they occurred on all experimental reefs, their home ranges are small , and migration is extremely limited Damselfish et al.All individuals per reef were grouped into 10 mm size classes. Size estimates were made by two observers . Prior to conducting estimates, sizes of 12–74 mm fish painted on metal disks placed on reefs were estimated. Errors in size estimates were examined following Bell P. moluccensis and P. amboinensis, abundances and species richness of juvenile and adult visitors and residents, and the log10 (x+1) abundance of all  adult surgeonfishes (the most abundant and ubiquitous trophic group), per reef, were each analysed separately using analysis of covariance (ANCOVA) with two fixed factors , and reef area as a covariate; reef area was included as a covariate to test whether or not area significantly explained some of the variation in fish abundance or richness per reef. For adult visitors, time of day  was a fixed factor; Acanthuridae abundance was log10(x+1) transformed to linearise data with area. Simpson's indices of diversity P>0.25) following Quinn and Keough Abundances of P. moluccensis and P. amboinensis were pooled, where necessary, to reduce the number of zero counts within any one size class to less than four reefs. A Dirichlet-Multinomial Vector Generalised Linear Modelling (VGLM) approach Size classes of To evaluate if fish abundance was affected by cleaners, with species taken into account, species that were present on 15 or 16 reefs were used. Separate generalised linear mixed models (GLMM) with a Poisson distribution were used for residents and adult visitors, with treatment, site, and time (visitors only) as fixed factors, species identity and reef as random variables, and reef area as a covariate. These statistical analyses were done using R v2.9.0 Table S1Statistical results for fish abundance, species richness, and Simpson's diversity index analyses.(DOC)Click here for additional data file.Table S2Species list of site-attached resident fishes surveyed.(DOC)Click here for additional data file.Table S3Species list of juvenile visitor fishes surveyed.(DOC)Click here for additional data file.Table S4Species list of adult visitor fishes surveyed.(DOC)Click here for additional data file.Table S5Experimental reefs with number of cleaner fish present or removed.(DOC)Click here for additional data file.


Laboratory assays are needed for early stage non-small lung cancer (NSCLC) that can link molecular and clinical heterogeneity to predict relapse after surgical resection. We technically validated two miRNA assays for prediction of relapse in NSCLC. Total RNA from seventy-five formalin-fixed and paraffin-embedded (FFPE) specimens was extracted, labeled and hybridized to Affymetrix miRNA arrays using different RNA input amounts, ATP-mix dilutions, array lots and RNA extraction- and labeling methods in a total of 166 hybridizations. Two combinations of RNA extraction- and labeling methods (assays I and II) were applied to a cohort of 68 early stage NSCLC patients.RNA input amount and RNA extraction- and labeling methods affected signal intensity and the number of detected probes and probe sets, and caused large variation, whereas different ATP-mix dilutions and array lots did not. Leave-one-out accuracies for prediction of relapse were 63% and 73% for the two assays. Prognosticator calls ("no recurrence" or "recurrence") were consistent, independent on RNA amount, ATP-mix dilution, array lots and RNA extraction method. The calls were not robust to changes in labeling method.In this study, we demonstrate that some analytical conditions such as RNA extraction- and labeling methods are important for the variation in assay performance whereas others are not. Thus, careful optimization that address all analytical steps and variables can improve the accuracy of prediction and facilitate the introduction of microRNA arrays in the clinic for prediction of relapse in stage I non-small cell lung cancer (NSCLC). Early stage non-small cell lung (NSCLC) cancer is characterized by both clinical and molecular genetic heterogeneity with five-year recurrence and survival rates of 50% and 73% respectively . AlthougHowever, in spite of tumor heterogeneity, new techniques in molecular profiling -5 can suIn this study, we performed global microarray expression profiling targeting several small non-coding RNA species including microRNAs (miRNAs). MicroRNAs are small noncoding RNAs of approximately 18-25 nucleotides in length that regulate gene expression at the post transcriptional level by base pairing with mRNA, leading to either translational repression , or mRNAThe enhanced stability of microRNAs in contrast to mRNAs, allow expression profiling in routinely stored formalin-fixed and paraffin-embedded (FFPE) specimens, including samples that are more than ten years old . Large FIn order to reach this goal, carefully conducted studies are needed ,16, incoRNA input amounts using one RNA preparation of a single tumor specimen, ii) three different ATP-mix dilutions using two RNA preparations of two tumor specimens, iii) two different array lot numbers using one RNA preparation of a single tumor specimen, iv) two different RNA extraction kits using eight RNA preparations of four tumor specimens, and, v) two different RNA labeling kits using four RNA preparations of four tumor specimens in 8 labeling reactions. In addition, RNA was extracted twice from the same specimens in a cohort of more than 60 NSCLC patients in a direct comparison of the two assays. Thus, 139 RNA extractions and 166 hybridizations were performed from a total of 75 NSCLC specimens. To qualify the impact of any variation in the assay specific analytical conditions, principal component analysis was performed. In addition, prognosticator calls (i.e. "recurrence" or "no recurrence") was examined after varying the analytical conditions for selected samples.In this study, we compared two laboratory assays for prognostication in stage I NSCLC based on miRNA profiling in FFPE tissue specimens. To perform an objective evaluation , of the bsignal = 0.03 ± 0.01, t = 2.6, p < 0.05, R2 = 0.58; bprobes = 3.64 ± 0.60, t = 6.0, p < 0.01, R2 = 0.88; bprobe sets = 0.94 ± 0.12, t = 7.6, p < 0.001, R2 = 0.88; figure 100 ng = 3674 vs. mean600 ng = 4627, t = -2.04, df = 18, p = 0.05; figure 100 ng = 803 vs. mean600 ng = 1134, t = -2.41, df = 18, p < 0.05; figure bDevRNAinput = -0.0042 ± 0.0004, t = -10.0, p < 0.001, R2 = 0.95; figure A linear regression model showed that the amount of purified small RNA used for hybridization significantly affected mean signal intensity; the number of detected probes; and the number of detected probe sets (The effect of ATP-mix dilution was not significant in a linear regression model (results not shown), when analyzing six hybridizations with RNA from two NSCLC specimens, each labeled using three different ATP-mix dilutions. Thus, mean signal intensity, background intensity, the numbers of detected probes, and the numbers of detected probe sets were stable across the tested range table . Self-sewithin and between lots did not vary (table within one lot of arrays (cc = 0.973) was similar to the estimated average correlation between two different lots of arrays .Hybridizations (in triplicates) with labeled RNA from a single T2 NSCLC tumor revealed that signal intensity and the number of probes and probe sets were not significantly different across different lot numbers (results not shown). In addition, the observed self-self correlation coefficient across probe signal intensities ry table . In partRecoverAll = 247.7 ± 26.9 vs. xHighPure = 190.1 ± 8.2), the number of detected probes ± se (xRecoverAll = 9407.8 ± 98.0 vs. xHighPure = 7733.5 ± 671.1) and the number of detected probe sets ± se (xRecoverAll = 2328.8 ± 27.9 vs. xHighPure = 2088.5 ± 150.0) in hybridizations with total RNA extracted using the RA kit all exceeded that for the HP kit . Background intensity was not significantly different between the kits  as revealed by the first principal component , the numbers of detected probes  and the numbers of detected probe sets , all exceeded those in hybridizations with RNA labeled using the FlashTag Biotin labeling kit . A major proportion of the variance could be assigned to the different labeling methods (between-kit variance) as revealed by PC1 in the PCA . Figure By performing 1000 Monte Carlo simulations we obtained a prognostic accuracy of 60.0% (95% C.I.: 59.5% - 60.5%) for assay I and 62.6% (95% C.I.: 61.9% - 63.2%) for assay II (p = 9.82e-10 for the hypothesis that the accuracy is similar for the two assays). Nested LOOCV that optimized the number of selected non-coding RNAs in a separate loop resulted in an LOOCV accuracy of 63% for assay I and 73% for assay II. A multivariate analysis examined for the effects of the miRNA chip based prognosis (i.e. "recurrence" or "no recurrence"), age, smoking status, stage (Ia or Ib) and histology (squamous or adeno) on recurrence after surgery. Only the miRNA based prognosticator was significant  were consistent independent of the RNA amount, ATP-mix dilution, chip lot number and RNA extraction method being used. In contrast, the calls were not robust to changes in labeling method table .Validation of a microarray based laboratory assay poses two technical challenges; first, ensuring that data are aquired with the best laboratory proficiency; and second, that data are analyzed appropriately. In order for a chip based prognostic assay to be practically usefull and accurate for prognostication in NSCLC, concern must be adressed towards the concordance of expression measurements and the impact of variation across analytical conditions. Here we assessed the impact of variation in several analytical conditions including varying RNA input amount, ATP-mix dilution, chip lot numbers, RNA extraction- and RNA labeling kit.Increasing the input RNA amounts led to an increase in mean signal intensity and the number of detected probes and probe sets figure , 4 and 5RA kit) was used as input in labeling reactions, ATP-mix dilutions did not significantly affect mean signal intensity and the number of detected probes and probe sets. Self-self correlations in probe signal intensities between arrays were also not affected by changing ATP-mix dilutions . Doleshal et al. [RecoverAll (Ambion). PCA for all human non-coding RNAs revealed substantial variation between the two extraction kits. Thus, the results of the PCA indicate that a particular tumor sample is more distantly separated from itself when RNA is extracted with a different kit, as compared with tumor samples from different patients when RNA is extracted with the same kit. As a consequence, the two RNA extraction procedures are not interchangeable within either an experiment, or across different experiments that are performed for validation purposes.Mean intensity and the number of detected probes and probe sets, in RNA preparations from the findings , showingl et al. , compareFlashTag Biotin HSR labeling kit, all exceed those in RNA preparations labeled with the original FlashTag Biotin labeling kit. PCA for all human non-coding RNAs revealed substantial variation between the two labeling kits. The results of the PCA indicate that a particular tumor sample is more distantly separated from itself when RNA is labeled with a different kit, as compared to tumor RNA samples from different patients labeled with the same kit. Within-kit variance for the FlashTag Biotin labeling kit was very small compared to the FlashTag Biotin HSR labeling kit. The small variance for the FlashTag Biotin labeling kit may be a consequence of a compressed mean (and variance) in signal intensity  for each assay, and performing 1000 Monte Carlo simulations, a significantly better performance of assay II 62.6%) was observed as compared to assay I (60%). The accuracy of the final profiles (after performing nested LOOCV) for assay I and assay II were 63% and 73% respectively, again pointing to a better performance of assay II. A Kaplan-Meier time-to recurrence plot using data from assay II demonstrated a clear and significant separation of the predicted "recurrence" and "no recurrence" groups  for selected samples under varying analytical conditions table  were conIn this study, we demonstrate that some analytic variables are important for the variation in assay performance while others are not. Thus, careful optimization that address all analytical steps and variables can facilitate the introduction of microRNA arrays for prediction of relapse in stage I non-small cell lung cancer (NSCLC). In result, stratification of patients with stage I disease can be improved by prediction of relapse after surgery, potentially allowing to direct intensive surveillance and/or adjuvant therapy toward patients at high risk of relapse figure .Den Videnskabsetiske Komité. The study was conducted in accordance with the Helsinki declaration. In total 75 NSCLC specimens were included in the study. These comprised 68 stage I NSCLC from a US cohort collected and treated at RPCI [RNAlater  with approval by Den Videnskabsetiske Komité in Denmark and with informed consent obtained from the patient.Patient tumor samples were collected retrospectively from Roswell Park Cancer Institute (RPCI), Buffalo, NY and from Aarhus and Odense University Hospitals in Denmark. The use of all included samples in this study was approved by the institutional review board at Roswell Park Cancer Institute, and, in Denmark, by http://www.ncbi.nlm.nih.gov/pubmed search using the search terms "miRNA" AND "Cancer" AND "FFPE", 33 publications were retrieved covering the period from 2009 to 2011. Of these, 16 publications described the use of global miRNA profiling, and in over half of these (i.e. in 9 studies), RNA was extracted using the RecoverAll kit (Ambion). In the present study we compared two different RNA extraction methods. In addition to the widely used RecoverAll kit , we included the High Pure miRNA Isolation Kit . For the HP Kit, RNA was extracted from deparaffinized and proteinase K-treated FFPE core tissues (20-40 mg) or sections according to the manufacturer's instructions. In approximately one-third of the cases, RNA preparations were of poor quality. Consequently, RNA was extracted again from FFPE tissue. For the RA Kit, RNA was extracted from deparaffinized and protease-treated FFPE core tissues (20-40 mg) or sections with on column DNAse digestion according to the manufacturer's instructions. RNA concentration and quality was assessed by absorbance spectrometry and electrophoresis using the NanoDrop  and Bioanalyzer 2100 (Agilent Technologies) instruments.In a PubMed FlashTag™ Biotin RNA Labeling Kit , and the new HSR version of the same kit were used according to the manufacturer's instructions unless otherwise stated. Poly (A)-tailing: 100-800 ng RNA including the small RNA species was used as starting material for the polyA-tailing reaction with different ATP-mix dilutions (from 1:10-1:500). Poly (A)-tailing was performed at 37°C for 15 minutes . Ligation: Using the entire reaction product from the poly (A) tailing reaction, a biotin-labeled 3DNA® dendrimer was ligated to the poly (A) tails using a T4 DNA Ligase and incubated at 25°C for 30 minutes  following the manufacturer's instructions.Two different RNA labeling methods were compared in this study; the http://www.ncbi.nlm.nih.gov/pubmed search describing global miRNA profiling, 12 studies used six different commercially available platforms and the remaining four studies used different custom platforms. Between 365 and 847 human miRNAs were profiled using from 20 ng to 5 ug totalRNA as input. In the present study we used the platform with the broadest coverage, i.e. the Afymetrix GeneChip® miRNA Array that interrogates 847 human miRNAs and about an equal number of small non-coding RNAs. Hybridization washing and staining were performed using the Affymetrix GeneChip Hybridization, Wash and Stain Kit . Briefly, the hybridization cocktail containing the biotin labeled RNA was heated to 99°C for 5 minutes and then to 45°C for 5 minutes  before loading onto the Affymetrix probe array cartridge (GeneChip® miRNA Array). The volume of the hybridization cocktail loaded on the chip was changed from 100 ml to 80 ml in order to improve movement/flow of the cocktail in the hybridization chamber, ensuring a better and more even hybridization process. Thus, in effect only 80% of the labeled RNA was placed on the chip. The probe array was incubated for 17 hours at 48°C with constant rotation (60 r.p.m.). The probe array was incubated for 17 h at 48°C at constant rotation (60 r.p.m.). The biotin labeled RNA was stained with a streptavidin-phycoerythrin conjugate and the signals amplified using a biotinylated goat antibody against streptavidin. Finally, the samples were stained with a streptavidin-phycoerythrin conjugate.Of the 16 studies from the PubMed http://www.ebi.ac.uk/arrayexpress/ and has been assigned accession number E-MTAB-618 ).The probe arrays were scanned using a confocal laser-scanning microscope (Affymetrix GCS3000Dx2). The readings from the quantitative scanning were analyzed using the Affymetrix Molecular Diagnostics Software (AMDS). The microarray data was deposited in the Array Express public database RNAlater (Ambion) within 2 hours of after surgery. RNA was subsequently extracted using the HP Kit. The effect of varying RNA input amounts  for hybridization was examined. In addition, RNA was prepared from ten stage I NSCLC surgical FFPE specimens using the HP Kit (100 and 600 ng) and these samples were labeled and hybridized to miRNA arrays. Signal intensities were examined on the chip using laser scanning microscopy. Background intensity ranged from 31 to 36 and was unrelated to the amount of input RNA (results not shown). Subtraction of background intensities did not affect the results (data not shown).For comparisons, RNA was extracted from a sample collected under conditions where RNA degradation is expected to be minimal. Thus, a sample of a T2 NSCLC post-resection surgical specimen was collected and preserved in HP Kit and labeled using the FlashTag™ Biotin RNA Labeling Kit (Genisphere). In addition, different ATP-mix dilutions  were examined using two preparations of 600 ng RNA extracted from two different NSCLC FFPE specimens using the RA Kit and labeled using the FlashTag™ Biotin HSR RNA Labeling Kit (Genisphere).The effect of different ATP-mix dilutions  was examined using 100 ng RNA extracted from a single NSCLC specimen using the FlashTag™ Biotin RNA Labeling Kit, ATP-mix dilution 1:50) from of a single RNA preparation of a T2 NSCLC tumor using the HP Kit.Correlations in signal intensities were examined across two different lots of arrays that were hybridized (in triplicates) to 100 ng of labeled RNA  and RecoverAll  extraction methods were compared in an RNA extraction experiment with four FFPE NSCLC specimens. From each specimen, 20 sections (20 mm thick) were cut, every other slide being used for one extraction method and the remaining slides for the other. For each extraction method, 1000 ng RNA of each specimen was polyadenylated (ATP-mix dilution 1:50) and labeled with biotin using the FlashTag™ Biotin HSR RNA Labeling Kit .The FlashTag™ Biotin RNA Labeling Kit (Genisphere), and the new HSR version of this kit were compared in an RNA labeling experiment using RNA from four NSCLC specimens from the RPCI cohort extracted using the HP Kit. For each labeling kit, 600 ng RNA from each specimen was polyadenylated (ATP-mix dilution 1:50) and labeled with biotin.The High Pure miRNA Isolation Kit (Roche) and 600 ng was labeled using the FlashTag™ Biotin RNA Labeling Kit (Genisphere). For assay II, total RNA including small RNA was extracted from 63 of the 68 stage I NSCLC specimens using RecoverAll (Ambion) and 600 ng was labeled using the FlashTag™ Biotin HSR RNA Labeling Kit (Genisphere).For assay I, total RNA including small RNA was extracted from 68 stage I NSCLC specimens using the We tested the performance of a SVM classifier on both assays using a Monte Carlo approach. First, two-thirds of a data set was randomly chosen and used as a training set. Second, training was done by setting the number of features (i.e. non-coding RNAs) to 30, chosen according to a highest t statistic, MCRestimate package , in a LOTo qualify the impact of any variances in the analytical conditions of the assay, the calls (i.e. "recurrence" or "no recurrence") of the prognosticator were examined after varying RNA input amount, ATP-mix dilution, chip lot numbers, RNA extraction kit and RNA labeling kit for eleven selected NSCLC samples. The prognosticator was trained using either 68 (assay I) or 63 (assay II) stage I NSCLC samples using a SVM classifier and the identified prognostic profiles of each assay. Second, the trained SVM classifier was used to predict the outcome and thus examine the robustness of the prognosticator.workflow set to "default"). T-tests and ANOVA, assuming equal variances were performed using the R software package [For testing the effects of RNA amount; ATPmix dilution; extraction kit and labeling kit on signal intensity, background intensity, the numbers of detected probes and probe sets, arrays were pre-processed using Affymetrix miRNA QC Tool 1.0.33 (with  package . For cor package  generatiJ Dahlgaard, W. Mazin, T Jensen, A Hansen and S. Knudsen are employees at Medical Prognosis Institute, Denmark, a company that focuses on developing microarray-based technology for cancer treatment. The other authors disclosed no potential competing interest.JD: Design of study, acquisition of miRNA expression data, statistical data analysis and data interpretation, drafting of the manuscript and final approval. WM: Design of study, statistical data analysis including prognostic models and interpretation, revising the manuscript and final approval. TJ: Design of study; acquisition and interpretation of miRNA expression data; revising the manuscript and final approval. MP: Collection and acquisition of data from FFPE specimens, revising the manuscript and final approval. WB: Collection and acquisition of data from FFPE specimens, revising the manuscript and final approval. AH: Acquisition of miRNA expression data, revising the manuscript and final approval. EK: Acquisition of data, revising the manuscript and final approval. SJHD: Acquisition of data from FFPE specimens, revising the manuscript and final approval. OH: Acquisition of data, revising the manuscript and final approval. HH: Collection and acquisition of data from FFPE specimens, revising the manuscript and final approval. HJD: Acquisition of data; revising the manuscript and final approval. SY Design of study; acquisition and interpretation of clinical data revising the manuscript and final approval. SK Design of study, interpretation and analysis of data including prognostic models, revising the manuscript and final approval.


The choice of two novel alternative 5′ ss (nt 221 5′ ss and nt 191 5′ ss) produces two novel isoforms of E6E7 mRNAs (E6*V and E6*VI). The nt 226 5′ ss and nt 409 3′ ss is preferentially selected over the other splice sites crossing over the intron to excise a minimal length of the intron in RNA splicing. We identified AACAAAC as the preferred branch point sequence (BPS) and an adenosine at nt 385 (underlined) in the BPS as a branch site to dictate the selection of the nt 409 3′ ss for E6*I splicing and E7 expression. Introduction of point mutations into the mapped BPS led to reduced U2 binding to the BPS and thereby inhibition of the second step of E6E7 splicing at the nt 409 3′ ss. Importantly, the E6E7 bicistronic RNA with a mutant BPS and inefficient splicing makes little or no E7 and the resulted E6 with mutations of 91QYNK94 to 91PSFW94 displays attenuate activity on p53 degradation. Together, our data provide structural basis of the E6E7 intron 1 for better understanding of how viral E6 and E7 expression is regulated by alternative RNA splicing. This study elucidates for the first time a mapped branch point in HPV16 genome involved in viral oncogene expression.HPV16 E6 and E7, two viral oncogenes, are expressed from a single bicistronic pre-mRNA. In this report, we provide the evidence that the bicistronic pre-mRNA intron 1 contains three 5′ splice sites (5′ ss) and three 3′ splice sites (3′ ss) normally used in HPV16 Human Papillomaviruses (HPV) are a large group of small, non-enveloped, double stranded DNA tumor viruses, with a total of ∼120 genotypes The HPV16 E6 and E7 genes are positioned side by side at the beginning of the papillomavirus genome and are initially transcribed as a single bicistronic pre-mRNA from a major early promoter P97. This bicistronic E6E7 pre-mRNA contains three exons and two introns and its intron 1 extends from E6 open reading frame (ORF) to E7 ORF and contains three alternative 3′ splice sites (3′ ss) However, a small proportion of the E6E7 bicistronic RNA with intron 1 retention is detectable in cervical cancer tissues and cervical cancer-derived cell lines and this species of E6E7 mRNA is responsible for translation of a full-length E6. Mechanistically, there are only limited data currently available on how the intron 1 escapes recognition by cellular splicing machinery to produce a full-length E6 protein. The cap-binding complex at the RNA 5′ end was initially found to promote splicing of the intron 1 of HPV16 E6E7 transcripts, but the cap-enhanced splicing of intron 1 can be restrained by the distance of intron 1 from its RNA 5′ cap In this report, we have carefully characterized the intron 1 of HPV16 E6E7 pre-mRNA and identified two novel 5′ splice sites (5′ ss) and a functional BPS that controls selection of the intron 1 nt 409 3′ ss for production of E6*I. Our data indicate that splicing of the HPV16 intron 1 is coordinated with a simple principle of proximal selection over the intron for preferential excision of a minimal length of the intron.2 in Dulbecco′s modified Eagle′s medium , except U2OS and HCT116 cells in McCoy′s 5a medium (Invitrogen), supplemented with 10% fetal bovine serum , 2 mM L-glutamine, 100 U/ml penicillin, and 100 µg/ml streptomycin.CaSki and SiHa cells are cervical cancer cell lines with integrated HPV16 genome. W12 cell line was originated from a CIN I lesion Plasmid pSB22 was constructed to express HPV16 E6 ORF (nt 104–586) with a disrupted nt 226 5′ ss (GU to GG mutation or U228G mutation) driven by a cytomegalovirus immediate early (CMV IE) promoter. The pSB22 was derived from plasmid pTMF1 HCT116 cells were transfected with pMA16, pMA18, pMA26 or p3xFLAG CMV-14  and were collected 48 h after transfection. Cell lysates were then analyzed for protein expression with anti-p53 (DO1) mouse monoclonal antibody , anti-HPV16 E7 (ED17) mouse monoclonal antibody  and anti-β-actin (Ac-15) mouse monoclonal antibody (Santa Cruz Biotechnology).http://rulai.cshl.edu/ESE) http://rulai.cshl.edu/dbCASE) http://www.umd.be/HSF/) 5′ ss and 3′ ss matrix score were calculated by using ESE finder software (5) or CV-1 cells (1.0×106) in a 6-cm dish were transfected with 2 µg of pSB22 by Lipofectamine 2000 (Invitrogen) or HPV16 E6E7 expression vectors with LipoD293 transfection reagent . Total RNA at 24 h after transfection was extracted using TRIzol (Invitrogen) and treated by RNase-free DNase I to remove plasmid DNA. The same protocol was also used to prepare total RNA from CaSki, SiHa, and W12 subclone cells 20861 and 20863. Total RNA from cervical cancer (Ca) or normal (N) tissues pretreated with DNase I  was purchased from Ambion  or obtained as gifts (Ca 3 and Ca 4) from Yang Li and Xing Xie of Zhejiang University, China. Poly (A)-selected mRNA was prepared from total RNA by using QuickPrep mRNA Purification Kit . For RT-PCR detection, total RNA (0.25 µg) was reverse transcribed by MultiScribe Reverse Transcriptase  with random hexamer and then amplified by AmpliTaq (Applied Biosystems) in the presence of a specific primer set as described in each figure and detailed in HEK 293 cells  in 50 µl of 1 X transcription buffer  rCTP and 80 U T7 RNA polymerase]. The in vitro transcription was carried out at 37°C for 2 h and the DNA template was removed with TURBO DNA-free enzyme (Invitrogen). The transcription products were resolved in a 6% denaturing PAGE gel containing 7.5 M Urea , and the full length transcripts were cut and eluted from the PAGE gel and subsequently purified and quantified.Templates used to transcribe HPV16 E6E7 pre-mRNA (nt 107–889 or nt 107–881 attached with a U1 binding site) were prepared from plasmid pMA16 to have a 5′ T7 promoter by PCR amplification using a primer set of oZMZ208 and oZMZ275  for a tein vitro splicing assay, 4.0 ng of [α-32P] rCTP-labeled HPV16 E6E7 pre-mRNA transcribed in vitro were applied for in vitro RNA splicing as described 32P] ATP was used as a size marker.For DNA oligo-directed U2 snRNA depletion was performed as described previously with a few modifications 32P] ATP. The membrane was then washed once with a 2X SSPE  −0.5% SDS for 5 min at 42°C, twice with 0.2X SSPE−0.1% SDS for 30 min at 42°C, and exposed to a phosphoimager screen.U2 depletion efficiency of HeLa nuclear extract was examined by Northern blot. Briefly, total RNA from 8 µl of HeLa nuclear extract with or without U2 depletion was extracted by phenol/chloroform/isoamyl alcohol, dissolved in 10 µl of NorthernMax formaldehyde loading dye (Ambion), denatured at 75°C for 10 min, resolved in 6% denaturing PAGE gel containing 7.5 M Urea , and transferred onto a nylon membrane with a constant currency of 400 mA for 2 h. After prehybridization for 1 h at 42°C in Super-Hybridization buffer (Sigma), hybridization was carried out for 16 h at 42°C with an antisense DNA oligo oKY48 for U1 snRNA, oKY50 for U2 snRNA, or oST197  for U6 s32P] rCTP-labeled pre-mRNA transcribed in vitro was mixed with 8 µl (7.5 µg/µl) of HeLa nuclear extract in a reaction volume of 20 µl in the presence of the reaction buffer containing final concentration of 40% HeLa nuclear extract, 5.0 mM HEPES (pH 7.9), 0.6% polyvinyl alcohol, 0.4 mM ATP, 20 mM creatine phosphate, 3 mM MgCl2. After incubation at 30°C for 30 min, the mixture was incubated for additional 10 min at 30°C in the presence of 500 nM DNA oligo oMA64 for wild type BPS, oMA76 for mt-11 BPS, oMA60 for mt-7 BPS, or oMA61  and incubated for 20 min at 75°C. The digested products were extracted by phenol/chloroform/isoamyl alcohol and were resolved in a 6% denaturing PAGE gel containing 7.5 M Urea . The PAGE gel was then transferred onto a 3M filter paper and dried. The radioactivity of the digested products was captured by exposing the filter paper to a storage phosphor screen (Molecular Dynamics). The screen was then imaged by a PhosphoImager STORM 860 and analyzed with ImageQuant software (Molecular Dynamics).Four ng of [α-or oMA61  for PPT,32P-labeled pre-mRNA (4 ng) and a corresponding BPS-specific DNA oligo  were added to each depletion reaction described above, and the mixture was incubated for 10 min at 30°C before proteinase K digestion HeLa nuclear extract with U2 depletion was also used for RNase H protection assays. In this case, a http://rulai.cshl.edu/ESE), we obtained a matrix score for each 5′ ss, with a strength order for nt ine226 (5.682) > nt 221 (4.338) > nt 191 (3.853)  carrying a mutation at nt 226 5′ ss   in the E (3.853) . Moreove (3.853)  after th+ cervical cancer cell lines has not been carefully studied. Data in It has been well documented that HPV16 E6E7 pre-mRNA is predominantly spliced from nt 226 5′ ss to nt 409 3′ ss to make an E6*I transcript or to nt 526 3′ ss to make an E6*II transcript. We and others had also identified the third 3′ ss at nt 742 in the HPV16 genome to encode a E6∧E7 fusion protein Intron definition indicates that pairing of splice sites in eukaryotes most likely occurs across introns in a manner that favors excision of the smallest segment When a splice junction-specific primer set of Pr221/409 and Pr855 was used in our RT-PCR assays, however, we could easily detect and confirm by sequencing the nt 221 5′ ss usage for splicing of the E6E7 bicistronic RNA in HPV16-positive cervical cancer tissues and cervical cancer cell lines, SiHa and CaSki cells , but notin intro transcription and compared for in vitro RNA splicing  in the intron 1 was incubated with HeLa nuclear extract with or without U2 depletion at 30°C for 30 min in the presence of an antisense DNA oligo to wt or mt BPS. The mixtures were then subject to RNase H digestion  signals for viral early and late gene expression http://rulai.cshl.edu/ESE). U1 pairing efficiency was reported as an critical factor for selection of the proximal 5′ ss when a competing 5′ ss is separated by <80 nucleotides Proximal pairing of donor and acceptor sites is known as the proximal rule in RNA alternative splicing and was initially reported in 1986 Previous report suggested that the G at nt 328 in HPV16 E6E7 intron 1 might function as a putative branch site for splicing of the nt 409 3′ss The BPS is required for pairing with U2 and is important for the second step of RNA splicing and choice of the first AG 3′ ss downstream of the branch site By introduction of mutations into the mapped BPS region to prevent RNA splicing, we found that the unspliced E6E7 RNA from the mt-7 encodes a mutant E6 protein containing four aa substitutions . These aa substitutions in the mt-7 E6 was detrimental for E6 activity in degradation of p53 and presumably affect the structure and/or folding of HPV16 E6 protein Figure S1Sequencing results of RT-PCR products derived from HPV16 RNA spliced from nt 221 or 191 5′ ss to nt 409 3′ ss. RT-PCR products from total RNA of the Ca 1 tissues or CaSki cells were amplified with a splice junction-specific primer pair of Pr221/409+ Pr562 for 221∧409 splicing and Pr191/409+ Pr562 for 191∧409 splicing (splicing  and then(TIF)Click here for additional data file.Figure S2Exon definition promotes the splicing of HPV16 E6E7 pre-mRNA at nt 742 3′ ss in vitro. (A) Structures of two HPV16 E6E7 pre-mRNAs used in in vitro splicing assay. Exons are indicated with white or gray boxes with a native 5′ ss (pre-mRNA 1) or 11 nt-consensus U1 binding site  at the RNA 3′ end. (B) Illustration of base-pairing of each RNA 3′ end  with U1, U5 and U6 snRNAs, showing suboptimal base-pairing of the pre-mRNA 1 and optimal base-paring of the pre-mRNA 2. Ψ, pseudo-uridine; Gm3, 2,2,7-tri-methyl guanosine. (C) A splicing gel showing RNA splicing at nt 742 3′ss. In vitro splicing products were resolved in an 8% denaturing PAGE gel. The numbers above the splicing gel indicate the pre-mRNAs corresponding to panel A and splicing reaction time (h). Identities of the spliced products are shown on the right. (D) A band with the size corresponding to a splicing product from nt 226 5′ ss to nt 742 3′ ss in (C) was purified from the gel and sequenced, confirming the fully spliced product from nt 226 to 742. (E) Structures of other HPV16 E6E7 pre-mRNAs with a short exon 2 used in in vitro RNA splicing assay. See other descriptions in (A) for details. (F) A splicing gel showing RNA splicing at nt 409 3′ ss when the pre-mRNAs had a short exon attached by an U1 binding site.(TIF)Click here for additional data file.Figure S3Disruption of the mapped BPS in HPV16 nt 409 3′ ss does not affect protein factors to interact with PPT. (A) Strategy flow chart of RNase H protection assays to analyze U2 interaction with the mapped BPS and other cellular proteins interaction with PPT. A 32P-labeled HPV16 E6 RNA with a wt or mt-7 BPS was incubated with HeLa nuclear extract in the presence of an AS DNA oligo complimentary to wt or mt-7 BPS (AS-BPS), or downstream PPT (AS-PPT) for 10 min and followed by RNase H digestion. Association of U2 snRNP or other factors with BPS and U2AF65 with PPT prevent DNA oligo-mediated RNase H cleavage of the pre-mRNA. (B) RNase H digestion products were resolved in 6% denaturing PAGE gel containing 7.5 M Urea. Identities of cleavage products are indicated on the right side. An arrow on the left of the gel indicates a spliced 226∧409 product from 30 min incubation with HeLa nuclear reaction during RNase H digestion. Cleavage efficiency (%) was calculated as described in (TIF)Click here for additional data file.Table S1A list of expression vectors used in this study.(TIF)Click here for additional data file.Table S2A list of DNA oligomers used in this study.(TIF)Click here for additional data file.Table S3Prediction scores for 5′ ss and 3′ ss in HPV16 nt 97–880 by ESE finder.(TIF)Click here for additional data file.Table S4Branch point sequence consensus values in the nt 409 3′ ss of HPV16 intron 1.(TIF)Click here for additional data file.


A metabolon has been defined as a “temporary, structural-functional, supramolecular complex of sequential metabolic enzymes and cellular structural elements, in which metabolites are passed from one active site to another without complete equilibration with the bulk cellular fluids” Srere, , 1987. T−/HCO−3 exchanger AE1 , the Na+/H+ exchanger NHE1, the Na+/HCO−3 cotransporter NBCe1, and various monocarboxylate transporters (MCTs) have been demonstrated to physically and/or functionally interact with isoforms of carbonic anhydrase (CA) to form a “transport metabolon.” This functional interaction includes an increase in transport activity, and therefore may enhance both the rate and the capacity of ion/metabolite transport in tissues where these membrane transporters and enzymes are co-localized.Some of the major acid/base-coupled membrane transporters, such as the Cl1/2 of 20 nM . In line with the physiological findings, pull-down assays demonstrated physical binding between CAIV and a GST fusion protein of the NBCe1's 4th extracellular loop, but neither to a GST fusion protein of the 4th extracellular loop in which G767 was mutated to T, nor to a GST fusion protein of the transporter's 3rd extracellular loop. These data indicate that CAIV can bind to the 4th extracellular loop of NBCe1 [as it binds to the 4th extracellular loop of AE1 , of which 14 isoforms have been described. The first four of these 14 isoforms (MCT1-4) have been shown to transport monocarboxylates together with HXenopus oocytes, suggesting a steric suppression of the interaction by the antibody , which acts as a H+ donor/acceptor, indeed restored the ability of the CAII-H64A mutant to enhance transport activity of MCT1/4 , analogous to the proton shuttle in CAII, which had been shown to be crucial for the interaction of CAII with MCT1/4, led to a significantly smaller increase in MCT2 activity than did CAIV-WT, but did not fully abolish the interaction with MCT2 (Klier et al., While injection of CAII does not increase transport activity of MCT2, heterologously expressed in + and HCO−3 carrying transporters interact with one or several isoforms of carbonic anhydrase, the mode of interaction also shows some unexpected variability. Membrane transporters may interact with intracellular and extracellular carbonic anhydrases, and this interaction may be direct including physical binding, or may possibly be mediated by chaperones associated with the transport proteins. Most of the interactions require the catalytic activity of the carbonic anhydrases, and functional interaction may be attributable mainly to the faster conversion of CO2, HCO−3, and H+ by CAs, while co-localization and perhaps physical attachment between acid/base-coupled transporters and CAs may meet the structural and spatial requirements of this process. The isoform-specific interplay between all monocarboxylate transporters and carbonic anhydrase isoforms so far tested, is independent of the anhydrase enzymatic activity. Moreover, similar binding domains have been identified in various MCT and CA isoforms. Future studies on the interaction between transporters and carbonic anhydrases, should help to unravel the molecular mechanisms of this functional metabolon system in more detail, from which we may learn more about transport metabolons in general.Transport metabolons between carbonic anhydrases and acid/base-coupled membrane transporters display a great versatility. Not only that most of the H


Since the discovery of microRNAs, non-coding RNAs (NC-RNAs) have increasingly attracted the attention of cancer investigators. Two classes of NC-RNAs are emerging as putative metastasis-related genes: long non-coding RNAs (lncRNAs) and small nucleolar RNAs (snoRNAs). LncRNAs orchestrate metastatic progression through several mechanisms, including the interaction with epigenetic effectors, splicing control and generation of microRNA-like molecules. In contrast, snoRNAs have been long considered “housekeeping” genes with no relevant function in cancer. However, recent evidence challenges this assumption, indicating that some snoRNAs are deregulated in cancer cells and may play a specific role in metastasis. Interestingly, snoRNAs and lncRNAs share several mechanisms of action, and might synergize with protein-coding genes to generate a specific cellular phenotype. This evidence suggests that the current paradigm of metastatic progression is incomplete. We propose that NC-RNAs are organized in complex interactive networks which orchestrate cellular phenotypic plasticity. Since plasticity is critical for cancer cell metastasis, we suggest that a molecular interactome composed by both NC-RNAs and proteins orchestrates cancer metastasis. Interestingly, expression of lncRNAs and snoRNAs can be detected in biological fluids, making them potentially useful biomarkers. NC-RNA expression profiles in human neoplasms have been associated with patients’ prognosis. SnoRNA and lncRNA silencing in pre-clinical models leads to cancer cell death and/or metastasis prevention, suggesting they can be investigated as novel therapeutic targets. Based on the literature to date, we critically discuss how the NC-RNA interactome can be explored and manipulated to generate more effective diagnostic, prognostic, and therapeutic strategies for metastatic neoplasms. For many years, the so-called central dogma of molecular biology has been dominant in cancer research, as well as in all other bio-medical fields . This doloci in the human genome [LncRNAs are arbitrarily defined as RNA sequences longer than 200 bp with no protein-coding function . This win genome  and is in genome . Althougn genome .loci in the human genome. These sequences are 60–300 base pairs long and have been classically associated with “housekeeping” functions, like rRNA modification and splicing [SnoRNAs are another abundant class of non-coding RNAs, encoded by approximately 500 different splicing , 12. Duesplicing . Howeversplicing –16. It isplicing .Metastatic spreading is the main cause of cancer-related deaths . It is wRecent transcriptomic analyses of human neoplasms have challenged the common belief that random sequential genetic mutations occurring in protein-coding genes underlie the acquisition of metastatic phenotype , 22. CanThe emergence of lncRNAs in cancer biology is already revolutionizing our approach to translational oncology. The past decade has revealed several examples of differentially expressed lncRNAs carrying diagnostic and/or prognostic value, some of which are now routinely used in the clinic . Interesin vitro and in vivo, correlating with shorter MFS in colon and breast cancer [While previously discussed lncRNAs promote metastatic spreading, there are also many examples of oncosuppressive lncRNAs whose down-regulation strikingly associates with metastatic behavior in the clinical setting. Among them, BM742401 exhibits decreased expression in more aggressive cancers, correlating with metastatic properties and decreased survival in gastric cancer tissues . Moreovet cancer . Even ifloci either in cis or in trans [The heavily altered lncRNA transcriptome in human cancer metastases has opened the way for a number of functional studies to uncover the molecular mechanisms by which lncRNAs influence cancer progression  and trans (PRC2-dependent silencing) mechanisms, thereby playing an oncogenic role. This multi-layer regulatory network occurring in one locus suggests that ceRNAs may control multiple targets in cancer cells, thereby acting either as pro- or anti-metastatic genes in a context-specific manner [One of the most interesting discoveries in recent years has been that not only can lncRNAs be actively shuttled in the cytoplasm, they can also carry out multiple pro-metastatic functions in this subcellular compartment  can inhibit metastasis by physically associating with NF90 and promoting its proteasomal degradation  in the human genome, raising the number of snoRNA-like genes to over 1,000 [SnoRNAs are an evolutionary conserved class of RNAs expressed by all eukaryotic cells . They we snoRNAs . Indeed,er 1,000 . Since sAs research on snoRNAs progressed, it became apparent that these non-coding RNAs can have several non-classical functions. Recent evidence indicates that snoRNAs can be processed to obtain shorter sequences that are involved in the control of mRNA alternative splicing . For exaIn parallel with the emergence of non-classical molecular functions, it has become apparent that snoRNAs might play a role in human diseases, including cancer , 136. SiThe first mechanistic insight on how snoRNAs can inhibit tumorigenesis came from a study aimed at identifying the genetic roots of a chromosomal deletion (6q14–q22) common to many cancer types . To idenlocus is frequently amplified in lung cancer lesions. SnoRNA42 silencing leads to growth arrest and p53-dependent apoptosis in lung cancer cells [A few snoRNAs have been also characterized as putative oncogenes. Among them is snoRNA42, whose er cells . Again, er cells . In multer cells . As a coSplicing control. This is an important mechanism of action of ZEB2-AS1 and MALAT1 lncRNAs , 143, whProduction of snoRNA-derived miRNAs. Classical miRNAs are master regulators of human cancer metastasis, by targeting multiple molecular pathways involved in each step of this complex phenomenon . SnoRNA-Different sets of snoRNAs can enhance or inhibit cell death in response to oxidative stress , 142. ItThe evidence presented above shows that snoRNAs can play tumor-suppressive or oncogenic functions in human neoplasms and that they can exert their action through several mechanisms, some of which probably remain to be discovered. Even if the link between snoRNAs and metastatic progression needs to be confirmed, we think that current knowledge suggests that this relationship should be investigated. Figure vs. lymph-node-positive prostate cancer samples [vs. primary prostate cancer. Figure p < 0.01, ANOVA and Tukey’s post-test) incremental increase in expression through progression from normal prostate to localized and then metastatic PCa samples. Notably, SNORD30  was among the 71 differentially expressed snoRNAs described by Martens and co-workers [To date, we found only one study directly showing that snoRNAs are deregulated during metastatic progression. A deep sequencing analysis investigated the whole small RNA transcriptome in organ-confined  samples . The aut samples . The aut samples , 148. We-workers .Fig. 3ExAlbeit preliminary and mainly based on gene expression patterns, these results provide compelling preliminary data suggesting that snoRNAs may be involved in metastatic progression, not unlike the better characterized miRNAs and lncRNAs. Future studies should investigate their role in other neoplasms, and more importantly the molecular mechanisms underlying their pro- or anti-metastatic functions. We believe that such analyses of this ancient class of non-coding RNAs have the potential to reveal unexpected molecular insights into the process of human cancer metastasis.Despite being the major cause of cancer-related deaths, metastasis remains a poorly understood phenomenon . This isloci, thus silencing anti-metastatic genes and triggering metastatic transcriptional programs [The recent discovery that the non-coding transcriptome exceeds the protein-coding one by number and diversity, and that many NC-RNAs are involved in cancer progression, suggests that an uncharted molecular network might orchestrate cancer cell dissemination Fig. . It is bprograms , 76. In programs . Pioneerprograms . ImportaIn addition to epigenetic regulation, alternative splicing represents the second molecular process in which a structurally diverse set of NC-RNAs interact to generate spatial and temporal complexity in cellular signaling pathways, underpinning phenotypic plasticity. Both snoRNAs and lncRNAs have been shown to co-localize in subnuclear compartments associated with RNA editing . AdditioThe third critical juncture in our proposed RNA-based molecular network involves the regulation of transcript stability by antisense RNAs. By post-transcriptionally regulating gene expression, this phenomenon has the potential to reprogram cellular phenotype rapidly in response to dynamic changes in the extracellular milieu. A highly diverse set of regulatory RNAs contribute to this process, consistent with the existence of an interconnected regulatory network controlled by NC-RNAs. Multiple RNA–RNA interactions are involved in this complex phenomenon, all of which can influence the functional output of this fundamental process. First, it has been extensively demonstrated that miRNAs play a central role by directly base pairing with target transcripts and inducing their degradation. A number of studies have highlighted the master regulatory role of miRNA networks in promoting cancer metastasis . While ploci can all be processed through Dicer-dependent mechanisms, leading to complementary RNA (either mRNA or NC-RNA silencing and degradation). We propose to collectively name this class of NC-RNAs “antisense-RNA-inhibitors”. This subclass will also include ceRNAs and CATs. The classification system we propose has the advantage of allowing one NC-RNA to be classified in many groups, which reflects the extensive functional diversity exhibited by the non-coding transcriptome. In addition, this system also allows the easy addition of novel subgroups as new molecular functions are discovered over time, making it flexible to the numerous paradigm changes that often arise in the search for scientific knowledge. In summary, the novel classification system we are proposing is based on function and not size, subclassifying individual NC-RNAs into three groups: (1) epigenetic co-factors, (2) non-coding splicing regulators, and (3) antisense RNA inhibitors. We believe that as research on NC-RNA proceeds, this classification system can become wider and more accurate.The current classification of NC-RNAs is mainly based on transcript length and/or biogenesis, thereby ignoring the high degree of functional overlap shared by some of those molecules. As summarized in previous paragraphs, significant evidence indicates that NC-RNAs with different length may play very similar cellular functions, thereby suggesting the need for a classification system based not on transcript size but on molecular function. After reviewing the implications of a non-coding interactome underlying cancer metastasis, we now propose the first attempt to classify NC-RNA based on functionality. As mentioned before, epigenetic regulation involves a diverse spectrum of molecular interactions in which both short and long non-coding RNAs play master regulatory roles. To account for this functional overlap, we propose to group together all NC-RNAs known to be involved in controlling chromatin dynamics and name them “epigenetic co-factors”. At the same time, some lncRNAs and many snoRNAs share the property to interact with sRNP, thereby orchestrating mRNA splicing. This second class of splicing-related NC-RNAs could be named “non-coding splicing regulators”. Finally, it has been extensively demonstrated that small antisense transcripts generated by miRNA, snoRNA, and lncRNA It is worth noting that currently available NC-RNA databases mainly rely on bioinformatics algorithms for the identification of non-coding sequences . Functiovs. metastatic disease [Finally, we believe that the hypothesis of a NC-RNA interactome has clear implications for translational cancer research. It has been already proposed that NC-RNAs can be exploited as easy-to-detect biomarkers and therapeutic targets to block cancer progression , 144. Pr disease . A deepe


Tetrahymena large subunit ribosomal RNA (LSU rRNA) as a platform for new template RNAs. In this group I intron-based self-assembling platform, modules for the recognition of substrate peptides can be installed independently from modules holding the platform structure. The new self-assembling platform allows us to expand the repertoire of substrate peptides in template RNA design.Multicomponent RNA-peptide complexes are attractive from the viewpoint of artificial design of functional biomacromolecular systems. We have developed self-folding and self-assembling RNAs that serve as templates to assist chemical ligation between two reactive peptides with RNA-binding capabilities. The design principle of previous templates, however, can be applied only to limited classes of RNA-binding peptides. In this study, we employed a two-piece derivative of a group I intron RNA from the  Caulobacter and Euglena, in which the tmRNA  ;MALDI-TOF-MS: m/z = 2944.282  ;MALDI-TOF-MS: m/z = 2824.679  ;MALDI-TOF-MS: m/z = 2949.034  .MALDI-TOF-MS: m/z = 3096.007 . In. InTetraThe third step involves the introduction of two peptide-recognition motifs (PRMs) to the complex Figures . The oneStructure-based design of the template RNAs was carried out by installing two PRMs (PRM1 and PRM2) on the platform P5 : Ez complex . Each PRλN-peptide1, P22N-peptide1, and Rev-peptide1, λboxB, P22boxB, and RRE). As the substrate peptides2 recognized by the Ez RNA, we used two peptides  were around 10–20% , product yields of the four reactions were improved to around 40% , we designed and examined six combinations of peptide ligation reactions based on the model 3D structures of the substrate-template complexes . In the ound 40% . The realate RNA .λN-peptide1 and λN-peptide2  and PRM2 (RRE motif). The product yields in the presence of the mutant complexes possessing one PRM  intrinsic reactivity of the two peptides, (ii) assistance of RNA in a PRM-independent manner, or (iii) assistance of RNA in a PRM-dependent manner . To eval-RRE RNA . The pro-RRE RNA . The res-RRE RNA . These rRE alone . This diTetrahymena intron RNA (P5 : ΔP5 complex) as a self-assembling platform for a template RNA to assist peptide ligation. The structural organization of the P5 : ΔP5 platform ensures structural independence between the modules for RNA-RNA assembly and the modules for recognition of substrate peptides (PRM), suggesting the versatility and flexibility of the P5 : ΔP5 platform in molecular design. This study confirmed the versatility of the P5 : ΔP5 platform for template design because six types of template RNA complex were designed and their template capabilities were tested experimentally. On the other hand, this study also revealed the current limitation of the P5 : ΔP5 platform. In the case of the reaction between λN-peptide1 and Rev-peptide2, the PRM-dependent facilitation by the P5 : Ez complexes possessing two PRMs was similar to the facilitation by the self-folding P4–P6 RNA with two PRMs [In this study, we employed the two-piece derivative of the two PRMs . The PRMtwo PRMs . The negtwo PRMs , 34. Thitwo PRMs , 36. PosλN-peptide1 and λN-peptide2 (λN-peptide2 (λN-peptide (λN-peptide is less hydrophilic than P22N- and Rev-peptides (λN- and Rev-peptides [An unexpected finding of the present study was the exceptionally efficient RNA assistance of ligations between P22N-peptide1 and Rev-peptide2 and between Rev-peptide1 and Rev-peptide2 without PRMs . In contpeptide2 . No PRM-peptide2 . These r-peptide . Althougpeptides , and P22peptides . Thus, i


Ecological habitats with greater structural complexity contain more species due to increased niche diversity. This is especially apparent on coral reefs where individual coral colonies aggregate to give a reef its morphology, species zonation, and three dimensionality. Structural complexity is classically measured with a reef rugosity index, which is the ratio of a straight line transect to the distance a flexible chain of equal length travels when draped over the reef substrate; yet, other techniques from visual categories to remote sensing have been used to characterize structural complexity at scales from microhabitats to reefscapes. Reef-scale methods either lack quantitative precision or are too time consuming to be routinely practical, while remotely sensed indices are mismatched to the finer scale morphology of coral colonies and reef habitats. In this communication a new digital technique, Digital Reef Rugosity (DRR) is described which utilizes a self-contained water level gauge enabling a diver to quickly and accurately characterize rugosity with non-invasive millimeter scale measurements of coral reef surface height at decimeter intervals along meter scale transects. The precise measurements require very little post-processing and are easily imported into a spreadsheet for statistical analyses and modeling. To assess its applicability we investigated the relationship between DRR and fish community structure at four coral reef sites on Menjangan Island off the northwest corner of Bali, Indonesia and one on mainland Bali to the west of Menjangan Island; our findings show a positive relationship between DRR and fish diversity. Since structural complexity drives key ecological processes on coral reefs, we consider that DRR may become a useful quantitative community-level descriptor to characterize reef complexity. Goreau's 1959 seminal paper on the zonation of West Indian corals highlighted hermatypic corals as the structural architects of the reef Risk's original chain/tape ratio analog method was universally accepted because it was simple, inexpensive, and captured the essence of rugosity in a simple ratio. But chains tangle easily with reef organisms and their substrate and the ratio is an imprecise descriptor of structural complexity across a wide range of scales. Sampling techniques that increase small scale spatial resolution are time consuming In this communication we describe a new technique to digitally parameterize coral reef structural complexity with a diver operated recording digital submersible level gauge designed to monitor groundwater water levels.Preliminary data are presented suggesting a positive relationship between digital reef rugosity (DRR) and fish diversity across a number of different habitats on shallow water Balinese coral reefs, reinforcing the conclusion of others that structural complexity is a fundamental ecological property of reef communities Acropora foliose and branching corals fitting into the r-K-s ternary classification CC = 2 of Endinger and Risk for Indonesian coral reef conservation Four sites on Menjangan Island off the northwest corner of Bali, Indonesia  and one on mainland Bali to the west of Menjangan Island (Kelor Point), were surveyed . The reeOur field studies were conducted in calm seas on the terrace between the reef flat and wall communities. At each site a 20–50 meter transect tape was set parallel to the general reef zonation (approximately perpendicular to swell direction) working along bathymetric contours within rather than across habitat zones. Transects varied in length depending on the patch size of reef substrate  and depth .http://www.onsetcomp.com/products/data-loggers/u20-001-02). The ceramic pressure transducer of the instrument has a nominal operating depth range of 0–30 meters with a resolution of 0.41 cm and an accuracy of +/− 1.5 cm over its depth range. Temperature recording  enables a diver to profile water column temperature and/or assess the fine scale distribution of temperature on the reef. The instrument has the capacity to record 42,400 individual data points at intervals as fine as one second, equaling almost 4 hours of data collection for pressure, temperature, time, and battery voltage which can be extended to almost 6 hours by omitting the battery voltage recording. The instrument communicates with a computer via an optically coupled base station and proprietary software . The level gauge can be programmed to start recording at a predetermined time which alleviates the necessity of bringing a computer into the field. Recording stops when the instrument's memory capacity is reached or by software control. Thus the instrument logs data continuously for an entire dive or day in the field until its memory is full. The actual useful data are subsets from the raw file after it has been downloaded and exported to a spreadsheet. While this greatly simplifies operation underwater, the operator must keep careful track of time and develop a protocol (as described in the next paragraph) to embed metadata information such as transect measurement start and stop into the constantly streaming raw data recording.Structural complexity was parameterized with fine scale pressure measurements recorded by a digital level gauge, an instrument normally used to track groundwater or stream levels  as the standard deviation describes the variation of a set of measurements. This is different from the traditional rugosity chain/tape ratio but it has been widely used in many studies that do not employ the traditional methodology STD can be calculated from raw sensor data because all the calibration factors are constants which do not affect transect variability. Fast Fourier transform (DRRFFT) was employed to explore the spatial distribution of structural complexity at horizontal scales within transects. The pressure measurements were subject to Single Series Fourier Analysis with an even number of samples based on the assumption of equally spaced sampling points at 10 cm intervals along each transect .The raw level gauge data were downloaded, exported in ASCII format to a spreadsheet for atmospheric pressure correction and conversion into units of depth (meters), and parsed into individual transects. The distant marks were notated in the data file and used to examine the rate of travel (points-per-meter) for consistency. The contour of the reef along each transect was calculated by subtracting the deepest point from all other depths (relative depth). Consecutive depth differences were calculated from these data by subtracting each point from the next point −1 and biomass hectare−1 using published length-weight relationships at four organization levels: species, genera, families and morphological groups Benthic community percent cover  was estimated by pointcounting consecutive still digital photographs of each transect The study sites spanned a wide range of combined stony and soft coral cover . Coral rTen transects varying in length from 23 to 50 meters with 6 of the surveys coinciding with fish counts were completed . The samSTD varied between transects and reefs but was not significantly correlated with coral cover . Levels of DRRSTD may be characteristic of a particular reef zone and/or morphology but the sample size was too small to make any assertions.The richest of the reefs we sampled were virtually intact with bush-like branching colonies closely packed to form a dense, near-continuous canopy. Transects on the deeper forereef were more complex as the coral colonies of many different morphologies  grow seaward and upwards, rather than simply upwards as in shallow water . DRRSTD The periodograms resulting from Fast Fourier Transform varied between sites and depth. Highly degraded reef displayed very little variability across scale compared to an adjacent nearly intact rich shallow reef . Richly More than 120 species of fish were observed whose abundance, biomass, and diversity varied widely across sites . These dSTD as has been seen in other studies of rugosity STD and fish species diversity (Shannon index (H′ = −∑ pi Log pi) based on either fish species abundance or estimated biomass  and DRRIn this communication we have presented a novel digital method to parameterize the structural complexity (rugosity) of coral reefs using a robust, off-the-shelf recording submersible pressure gauge. Initially, we have chosen to use the standard deviation of these fine scale pressure measurements as an estimate of rugosity but, with development, there may be other statistics that perform better. DRR measurements are relatively easy to carry out by a skilled SCUBA diver. The diver must swim the transect at a relatively constant swimming speed and use good buoyancy control; both are achievable with practice and concentration. Since it is a pressure measurement, waves and swell of any significant size will add information to the data. Increased wave height will add noise to the signal. Deeper transects will experience less “noise” from waves and/or swells as their signal becomes proportionally smaller with depth. At our sites below 5 meters the “noise” added to the variation in pressure was insignificant compared to the vertical relief of the coral reef. In some instances the use of a second stationary reference instrument may be helpful to remove wave variability in post processing, but one also has to recognize when it is too rough to work as it is far less complicated to confine data collection to calm sea conditions. Since diving conditions and substrates vary widely, each investigator will have to adapt the methodology to their specific study site conditions.std and fish diversity corroborates earlier work on fish species richness and reef structural heterogeneity analogous to the classic work of MacArthur for terrestrial forests The Menjangan Island fringing reef community provided a range of reef habitats to explore the utility of DRR at scales commensurate with the scale of many coral reef monitoring programs (10 to 50 m transects). The positive correlation between DRRstd because stony corals and soft corals generate the topographical structure. High coral cover often generates a tightly knit canopy which reduces rugosity but may impart a DRR signature that will have diagnostic importance for long term monitoring as has been suggested for monitoring tropical forest systems with remote sensing It is also somewhat perplexing that there was no significant correlation between coral cover and DRRFast Fourier analysis partitioned the variation in structural complexity as a function of horizontal transect scale within the range of 0.2 m to approximately 5 m. The one-second sampling rate approximating 10 cm of horizontal distance enabled a spatial resolution of 20 cm following Nyquist sampling theory where the smallest scale detectable is twice the sampling interval FFT reveal the distribution of rugosity as a function of scale . DRRFFT spectral density plots from two rich shallow reefs (Kelor Point and Northwest Corner) displayed strong variation at similar scales ranging from 0.5–2 m (FFT may improve our understanding of the contribution made by individual colonies to community structural complexity and reef morphology. Additionally, since fish and other mobile organisms tend to scale with their habitat FFT may provide further insight into the influence of habitat complexity on substrate preference and niche partitioning.The periodograms of DRR 0.5–2 m . These r 0.5–2 m  and 3A.  0.5–2 m  illustra 0.5–2 m . ColonieFFT analysis could be employed to characterize the relationship of reef canopies with prevailing seas or calculate hydrodynamic forces through an analysis of wave height time series measurements along depth transects using stationary instruments Digital Reef Rugosity can be applied across a wide range of spatial and temporal scales without sacrificing accuracy or precision since the length of a transect is virtually unlimited. Thus the technique provides a precise link between marine ecology and remote sensing which has eluded satellite-based remote sensing efforts because the smallest scale detectable from space is usually greater than the scale used in most ecological studies Globally, coral reef decline is embodied by the loss of coral cover, which is itself a proxy for reduced structural complexity analogous to terrestrial deforestation. Rugosity that is generated by coral colonies integrates ecological integrity, complexity, and vitality because these functions are biologically inseparable from structure on reefs. At some point in the degradation process the structural complexity of the reef ceases to support its fish community. In this time of dwindling management resources and accelerating reef degradation, a simple field technique that could help detect, or even predict, such tipping points would be an invaluable tool to help triage reefs for the most appropriate course of conservation; no-take policies might be applicable for overfished reefs but others might require rebuilding the physical structure to augment rugosity. Digital Reef Rugosity provides a modern method to more fully parameterize the fundamental community property of coral reefs so elegantly conceived by Risk over 40 years ago