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Imperfect centered miRNA binding sites are common and can mediate repression of target mRNAs
DOI: 10.1186/gb-2014-15-3-r51
© Martin et al.; licensee BioMed Central Ltd. 2014
Received: 1 August 2013
Accepted: 19 February 2014
Published: 14 March 2014
MicroRNAs (miRNAs) bind to mRNAs and target them for translational inhibition or transcriptional degradation. It is thought that most miRNA-mRNA interactions involve the seed region at the 5′ end of the miRNA. The importance of seed sites is supported by experimental evidence, although there is growing interest in interactions mediated by the central region of the miRNA, termed centered sites. To investigate the prevalence of these interactions, we apply a biotin pull-down method to determine the direct targets of ten human miRNAs, including four isomiRs that share centered sites, but not seeds, with their canonical partner miRNAs.
We confirm that miRNAs and their isomiRs can interact with hundreds of mRNAs, and that imperfect centered sites are common mediators of miRNA-mRNA interactions. We experimentally demonstrate that these sites can repress mRNA activity, typically through translational repression, and are enriched in regions of the transcriptome bound by AGO. Finally, we show that the identification of imperfect centered sites is unlikely to be an artifact of our protocol caused by the biotinylation of the miRNA. However, the fact that there was a slight bias against seed sites in our protocol may have inflated the apparent prevalence of centered site-mediated interactions.
Our results suggest that centered site-mediated interactions are much more frequent than previously thought. This may explain the evolutionary conservation of the central region of miRNAs, and has significant implications for decoding miRNA-regulated genetic networks, and for predicting the functional effect of variants that do not alter protein sequence.
MicroRNAs (miRNAs) are small non-coding RNAs (approximately 22 nucleotides) that regulate the expression of protein-coding genes in association with the RNA-induced silencing complex (RISC). They are present in most eukaryotic cells, have been predicted to affect the expression of over 60% of mammalian genes [1], and have been implicated in multiple cellular processes and human diseases. They can repress their targets via several mechanisms: preventing translation initiation or elongation, directing mRNA cleavage, and prompting mRNA decay [2]. It was thought that miRNA-mRNA interactions almost always involved contiguous and perfect Watson-Crick base-pairing between the miRNA 'seed region' and the mRNA target [3], and that binding outside the seed served to augment imperfect seed binding [3].
The attractive simplicity of using nucleotide complementarity to identify mRNA targets has given rise to many bioinformatics tools. These are based (to differing extents) on complementarity to the seed, evolutionary conservation, and free energy of binding [4]. The presence of canonical seed sites (in the absence of other more extensive complementarity to the miRNA) is by far the most discriminatory feature for target prediction [5], and incorporation of other modes of binding dramatically reduces the accuracy of these programs [6, 7]. However, results from our lab [8] and others [6, 9, 10] suggest that even the best algorithms have false positive rates of 20 to 40%, and any non-seed interactions will be absent from these predictions. In order to comprehensively understand the cohort of direct miRNA targets, unbiased transcriptome-wide experimental methods are needed.
While most experimental effort has been directed at verifying seed-based interactions, non-seed based interactions have also been demonstrated, albeit far less frequently [3, 7, 19, 20]. The most common variations appear to be 'seed-like' with mismatches or wobble in positions 5, 6, and 7 [20], and 'G-bulge' sites, in which the mRNA nucleotide that would normally pair with position 6 of the miRNA is bulged out of the interaction [19]. The strong evolutionary conservation of the central region of miRNAs [7] prompted a successful search for 'centered site'-mediated miRNA activity, demonstrating that 11 nucleotides of perfect complementarity starting at position 3, 4 or 5 could inhibit mRNA translation [21]. However, these centered sites were found only occasionally within the human transcriptome, similar in frequency to the 3′ supplementary and 3′ complementary sites that together account for <10% of interactions [3]. It remains an open question as to why the central region of miRNAs is strongly conserved; it may be driven by miRNA-mRNA interactions and/or by miRNA biogenesis. We hypothesized that imperfect centered sites could mediate miRNA-mRNA interactions, and that they are more commonly used than results from degradome sequencing would suggest. To test this hypothesis, we employed the biotin pull-down approach [13] to identify the direct miRNA targets for 10 carefully selected miRNAs (Table S1 in Additional file 1). We included two closely related miRNAs, miR-10a and miR-10b, which share identical seed sites, but differ by a single nucleotide in the center region. We also included four shifted isomiRs, which are miRNAs produced from the same pre-miRNA as the 'canonical' mature miRNA, but differing in 5′ and/or 3′ end cleavage [13, 22]. These isomiRs provide an ideal naturally occurring biological control, as the centered sites are shared between a miRNA and its isomiR, whilst the seed sites differ (Figure 1C). We show that imperfect-centered sites are common mediators of mRNA interactions, a finding that may explain the evolutionary conservation of the central region of miRNAs, and that will be important for decoding miRNA-regulated genetic networks.
Biotin pull-downs identify hundreds of miRNA-mRNA interactions
Number of inferred targets for each miRNA tested
Predicted and validated targets are significantly enriched in the biotin pull-downs
Luciferase assays are usually considered to be the 'gold standard' for validating miRNA-mRNA interactions. We examined the concordance between our biotin pull-down results and miRNA targets that have been confirmed by luciferase assays in the literature (Table S2 in Additional file 1). We excluded genes that were not targeted by an Illumina microarray probe (and therefore could not be detected by our biotin pull-down) or that were not expressed in HEK293T cells, leaving 93 genes for this analysis. Forty-three previously validated targets were enriched by biotin pull-downs (Table S2 in Additional file 1) in HEK293T cells, which was significantly more than expected by chance (Table S3 in Additional file 1; Fisher's exact test (FET), P-value <1.01 × 10-12). Interestingly, a lower proportion of targets validated in non-HEK cell lines were confirmed by our biotin pull-down (43.2%) than targets validated in HEK cell lines (51.4%), suggesting that cell type-specific factors can lower the concordance between orthogonal validation methods.
As a third control, we compared the biotin pull-down results to those obtained using both PAR-CLIP [12] and miR-17-5p over-expression studies [23, 24]. The PAR-CLIP experiment was conducted in HEK293 cells, which differs from the HEK293T cells used in our experiments by the exogenous expression of the SV40 large T antigen. This protein binds to and inactivates the p53 transcription factor [25], so the gene expression patterns between these cell lines differ. The over-expression experiments were also performed in very different cell lines (human umbilical vein endothelial cells (HUVECs) [23] and HCT116 cells [24]), and therefore we do not expect a perfect overlap between the targets detected between these orthogonal methods. By comparing the distribution of the miR-17-5p fold-change observed in this study between the transcripts that were detected as targets in previous studies and those that were not, we observed a significantly greater fold-change in the corresponding biotin pull-down in the former class (Figure 2C-E; Additional file 4; Kolmogorov-Smirnov tests, P-values from 1 × 10-2 to 1 × 10-22). Additionally, the overlaps between our inferred miRNA target sets and those deduced from the other studies were significantly greater than expected by chance (Table S3 in Additional file 1; FET, P-values from 4.68 × 10-2 to 5.17 × 10-20), although the enrichment was modest (odds ratio (OR) = 1.85; 95% confidence interval (CI) 1.7 to 2.1). Finally, although biotin-labeled miRNAs have been previously shown to incorporate into RISC [17], we wanted to be sure that our results were dependent on RISC association, and not due to cytoplasmic binding of free biotin-labeled miRNAs. To test this, we performed a hybrid AGO immune-precipitation and biotin pull-down (Figure 2F). HEK293T cells were transfected with either a standard biotinylated, double-stranded miR-17-5p miRNA duplex, or with a biotinylated single-stranded miR-17-5p sequence. Cells were lysed and subject to AGO immune-precipitation, creating an AGO2 enriched and AGO2-depleted fraction. Each fraction was then subject to a biotin pull-down, and the relative enrichment compared to input RNA (Figure 2F) was measured by quantitative RT-PCR (qRT-PCR). We specifically assessed the levels of the three novel seed sites identified above (Figure 2B) and two previously validated miRNA binding sites [8]. As endogenous RISC loading preferentially requires double-stranded miRNA duplexes [26, 27], we would expect double-stranded but not single-stranded molecules to enrich for targets in an AGO2 precipitation. Four of five targets were found to be enriched in the AGO2 enriched fraction when a double-stranded molecule was used (Figure 2G), and but not when a single-stranded molecule was used (Figure 2H). This, when considered along with the data presented above, confirms that the biotin pull-down is consistently enriching for genuine targets of miRNAs, although we do not know if or how these interactions result in target repression.
Biotin pull-downs are less likely to enrich for destabilized mRNAs, but have low rates of false positive target identification
If we are to use the biotin pull-downs to characterize non-seed site interactions, then it is important to understand the limitations of this protocol. To start characterizing the potential false negatives of the biotin pull-down approach, we selected six genes that we had previously reported to be targets of miR-17-5p that were not enriched in our pull-down [8]. We used qRT-PCR to determine whether these mRNA targets were destabilized by miR-17-5p and therefore less likely to appear as significantly enriched in the biotin pull-down. After transient transfection with biotinylated miR-17-5p (replicating the conditions of the biotin pull-down) we observed significant degradation of five of the six genes (Additional file 5). This result suggests that mRNA degradation probably affects whether or not a target can be detected via the biotin pull-down approach, and suggests that the concordance between biotin pull-down and luciferase assay could be higher when only comparing targets that are translationally regulated.
Hundreds of miRNA-mRNA interactions are mediated by centered sites
Having confirmed to our satisfaction that the biotin pull-downs could provide a high level of sensitivity for examining non-seed mediated interactions, we then searched for putative seed and perfect or imperfect centered binding sites (Figure 1C; Additional file 6) of each of our 10 miRNAs in the transcripts detected by the microarray probes. We asked what proportion of putative miRNA targets could be explained by the presence of these sites (Additional file 7). Studies that measured the change in protein output after miRNA transfection found that 50 to 70% of down-regulated proteins (log2 fold-change < -0.5) had a seed site [6, 10] for the relevant miRNA. Hafner et al.[12] reported that 50% of their PAR-CLIP clusters contained a seed site for one of the top 100 most expressed miRNAs in HEK293 cells. We found that, on average, 41.3% (standard deviation 10.1%) of significantly enriched transcripts contained one or more seed sites for the biotinylated miRNA. When centered sites were considered, allowing for GU wobble and up to one mismatch, we could account for substantially more of the significantly enriched targets (mean 82.7%, standard deviation 7.5%), suggesting that centered sites could indeed bind mRNAs on a large scale.
Shin et al.[21] reported that centered site matches were significantly associated with repression only if they involved perfect Watson-Crick base-pairing. However, we postulated that these sites might still be able to mediate interactions if they included GU pairs or a mismatch. Thus, in our analysis, we considered centered sites with only Watson-Crick binding (centered-WC) or with GU wobble (centered-GU) and with either no mismatches (0MM) or with one mismatch (1MM) (that is, any base pair other than C-G, A-U or G-U). Centered sites with only Watson-Crick matches accounted for only a small proportion of the significantly enriched transcripts (0.5% and 6.6% for 0MM and 1MM sites, respectively), but a much greater proportion of these putative target transcripts contained centered-GU sites (12.5% and 72%); thus, these were far more prevalent than seeds in our data set.
Centered sites can mediate interactions in the coding sequence and 3′UTR of mRNAs
To investigate whether the location of the putative miRNA binding sites affected whether or not a transcript would be enriched in the pull-down, we fitted a logistic regression model for enrichment status, including the counts of each type of site within different transcript regions as covariates (see Materials and methods). This model was highly significant (P < 0.0001), although it only explains a small fraction of the variance (Nagelkerke r2 = 0.04). As expected, the more seed sites there were in a transcript's 3′ UTR, the more likely it was to be significantly enriched in the pull-down (Figure 4B, left-most yellow bar). Interestingly, all types of centered sites in the 3′ UTR were significantly associated with enrichment status (Figure 4B, yellow bars). Consistent with recent literature [6, 20, 29–32], most site types were significant in the coding sequence (CDS) too (Figure 4B, orange bars), although the effects were strongest in the 3′ UTR in most cases. Curiously, when we controlled for the length of the regions by fitting the logistic regression with site densities as covariates, the coefficient estimates were greater for the CDS than the 3′ UTR (Figure 4C) for all site types. It may be that while miRNAs are more likely to target UTRs with more sites, there is a trade-off between the number and accessibility of sites (reflected by site density), and site accessibility is more important in the UTR than the CDS, perhaps because of mRNA secondary structure. Interestingly, though, the r2 was much lower for this model (0.008) than when we fit site counts as covariates, although it was still significant (P < 0.0001). To ensure that the logistic regression was not being confounded by the inclusion of multiple transcripts bound by the same probe (which are not independent of one another), we ran the analysis again including only the canonical isoform of each gene. This did not substantially change the results (P < 0.0001, Nagelkerke r2 = 0.05 for site count; P < 0.0001, Nagelkerke r2 = 0.009 for site density; Figures S7B,C in Additional file 8). We conclude that centered sites can mediate interactions both within and outside the 3′ UTR, although 3′ UTR interactions are more important, as has previously been shown for seed sites [33–35].
Similarity between target sets of canonical miRNAs and their isomiRs
If centered sites are indeed mediating biologically relevant interactions, then we would expect this to be reflected in the pattern of transcripts that are enriched in the biotin pull-down of both a canonical miRNA and its isomiR.
Centered sites are enriched in AGO-bound regions
If centered sites are truly mediating miRNA-mRNA interactions, and are not an artifact of the experimental approach used here, then we would expect such sites to be enriched in regions of mRNAs bound by RISC and endogenous miRNAs. In 2012, Loeb et al.[20] used differential AGO2 HITS-CLIP to profile murine primary T cells that were either miR-155 wild-type or were miR-155 deficient due to genetic knock out. Due to the high number of biological replicates (12 of each condition), the authors were able to robustly define 14,634 AGO2 bound regions, with 398 of these differentially detected only in wild type compared to knock out (adjusted P < 0.05), and therefore likely to be directly mediated by miR-155. We exploited these data to look for the frequency and location of imperfect centered sites and seed sites relative to the peak. We first confirmed that seed sites were significantly enriched in differentially detected AGO peaks compared to AGO peaks that were unchanged between wild type and knock out (FET, P ≈ 8.07 × 10-32, n = 111), and were significantly skewed towards the center of the predicted peak (excess kurtosis = 7.34; Figure 5D). We also observed enrichment and kurtosis for imperfect centered sites (FET, P ≈ 5.19 × 10-3, n = 29; excess kurtosis = 3.50; Figure 5E), although these sites were less frequent than seed sites. The overlap between seed and centered sites (n = 6) was not significantly different to what would be expected by chance (FET, P = 0.7887). Together these results suggest that imperfect centered sites can mediate endogenous miRNA-mRNA interactions independently of seed sites.
Imperfect centered sites primarily suppress target mRNAs through translational inhibition
To ensure that the centered sites were mediating their function through RISC, we repeated the hybrid AGO immune-precipitation/biotin pull-down approach (Figure 2F) to look for enrichment of these centered sites in AGO2-RISC. For both miR-17-5p imperfect centered sites (Figure 6C), and miR-27a imperfect centered sites (Figure 6D), all targets were found to be significantly enriched (P ≤ 0.05) in the AGO2 enriched fraction compared to the input mRNA population, demonstrating that interactions between an imperfect centered site and its target mRNA were mediated through RISC.
Finally, to determine whether imperfect centered sites mediate mRNA destabilization or translational inhibition, we repeated the luciferase assays described above (Figure 6B), and measured the level of luciferase gene mRNA via qRT-PCR. Changes in the mRNA levels between the control mimic and the test miRNA would indicate mRNA destabilization, whereas no changes in the mRNA levels would indicate translational inhibition. Only one out of four sites for miR17-5p (Figure 6E) and one out of five sites for miR-27a (Figure 6F) showed significant (P < 0.05) reduction of mRNA levels, indicating that most interactions that result in reduced protein are due to translational inhibition rather than mRNA degradation, although both types of regulation are possible. These experiments together provide substantial experimental evidence that imperfect centered sites are common targets of miRNAs, and mediate functional interactions.
The biotin pull-down technique is slightly biased against seed sites
A consideration for interpreting the results derived from this protocol is that the biotin tag on the synthetic miRNA duplexes may prevent their 3′ ends from binding to the PAZ domain of Ago [2]. This may allow biotin-labeled miRNAs to interact more easily with target mRNAs and alleviate the requirement for 5′ end binding. The method may therefore be biased towards detecting interactions that are not mediated by the canonical seed.
As expected, the association rates for seed sites are the highest of all sites, and dramatically higher than for 3' sites. Although we find no statistically significant difference between native RISC and biotin RISC for any interaction, we did observe a trend for native RISC to associate with all binding sites faster than biotin RISC (Figure 7D) and for native RISC to disassociate slower (Figure 7E) than biotin RISC. The only exceptions were imperfect-GU sites, which showed the same dissociation rate for native and biotin RISC, and 3' sites, which were much higher for native risk (approaching statistical significance, P ≈ 0.06). Thus, all but 3' site-mediated interactions are stronger in the absence of the biotin tag. Overall affinities (as measured by the ratio of association/disassociation) are very similar between biotin and native RISC for all types of sites (Figure 7F), but it is worth noting that the protocol used here could be affected by the higher disassociation rates of the seed sites. This is because in the biotin pull-down, unlike CLIP-based methods, the interactions are not fixed in the cell before isolation, so they can disassociate, and we would expect biotin RISC to disassociate more quickly from seed sites than native RISC. Together, this could result in a reduced affinity, transcriptome-wide, for seed sites in our biotin pull-down compared to what would be expected for native RISC-based protocols. We see some evidence for this in the slightly lower proportion of targets that are accounted for only by seed sites in our study compared to other studies - approximately 41% of our biotin pull-down targets can be explained by a seed site, versus 50% for PAR-CLIP data [12] (although we note that this 50% refers to a seed match to any of the top 100 expressed miRNAs). We interpret these results to mean that the biotin pull-down has a slight bias away from seed sites rather than any particular bias towards centered sites. In our data, this probably manifests as a lower percentage of seed sites, but importantly, the affinity between native RISC or biotin RISC to centered sites is essentially equivalent and therefore our conclusions regarding the biological relevance of these sites are unlikely to be an artifact of the protocol used, although the prevalence of these interactions may be slightly inflated by the bias away from seed sites.
In order to understand the function of a particular miRNA, it is essential to know its targets. All methods for elucidating these have weaknesses, including the biotin pull-down approach described previously [17, 18] and used here. We chose this protocol because it is not confounded by secondary effects (unlike microarray-based miRNA modulation studies) and because it is more sensitive for detecting differences between two closely related miRNAs than other whole-transcriptome approaches such as HITS-CLIP. The inclusion of stringent bead-blocking and washing steps has allowed us to substantially increase the specificity and dynamic range of the assay; the protocol described by Orom et al. [18] achieved a maximum fold-change of 4, while the transcripts in our biotin pull-downs were enriched up to eight-fold (Figure S1B in Additional file 2). However, we should anticipate that a proportion of transcripts detected as significantly enriched in our biotin pull-down may still not interact with the miRNA of interest. This type of false positive could occur through non-specific interaction with the magnetic streptavidin beads, or by association with endogenous biotin rather than with a biotinylated miRNA. Several lines of evidence suggest that this type of false positive is reasonably uncommon: (i) up to 90% of significantly enriched transcripts contain a predicted binding site (average 82.7%); (ii) of the remaining annotated (HUGO) transcripts without predicted binding sites, almost 40% were shown to contain novel transcriptional events with predicted bindings sites within them; and (iii) the vast majority of miRNA binding sites tested in luciferase assays were validated (Figures 2B and 6B) and were enriched in AGO2 containing silencing complexes (Figures 2G,H and 6C,D), although this was a small number of sites.
A second class of false positives would be those interactions that genuinely involve the biotinylated miRNAs but that do not occur endogenously in cells. This set is more difficult to define in the absence of a large cohort of true positives - even the 'gold standard' luciferase assays involve exogenous plasmids tested with exogenous miRNA mimics or inhibitors. While these assays can show that it is possible for a specific miRNA to interact with a specific binding site, they cannot prove that a specific miRNA interacts with a specific binding site endogenously. Factors such as RNA secondary structure, differences in the cellular concentration of miRNA and other miRNA binding factors, and secondary effects of miRNA modulation can all confound the interpretation of what are 'true targets' of a given miRNA. Just as precise false positive rates are difficult to calculate, the false-negative rates are equally intractable. An accurate assessment of the false negative rate would require a very large number of luciferase assays (if these are considered the gold standard) to establish a true positive set, and then ask how many of these were missed by the biotin pull-down approach. Such an experiment is impractical and expensive. However, like any difficult biological problem, orthogonal validation and careful interpretation are critical, and we were encouraged that miRNA targets inferred from all high-throughput methods and luciferase assays were significantly more likely to be enriched in our pull-downs than other genes (Table S2 in Additional file 1), and that the overlap seen between our results and those from the miR-17-5p over-expression experiments is similar to that observed between the latter and AGO2 immuno-precipitation datasets [34, 37].
Although we did not find any statistically significant differences between native RISC and biotin RISC in their affinities to seed or centered sites, the trend did suggest that biotin-labeled miRNAs were slightly less able to detect seed sites than native miRNAs, which could result in a relative increase in the proportion of centered sites in our data. This could explain the drop from 50% seed sites in the PAR-CLIP data [12] to 41% in our study. However, the large variability amongst individual miRNAs is likely to be a substantial contributing factor - we observed a standard deviation of 10.1% in the proportion of transcripts containing seed sites. Similarly, although imperfect centered sites were significantly enriched in endogenous AGO2 clusters mediated by miR-155 [20], they were almost four times less frequent than seed sites (7.3% versus 27.9%, respectively). This difference is likely to be a combination of the bias of the biotin pull-down approach, unexplored biases in the HITS-CLIP detection (including cluster stringency and bioinformatic inference of sites), and genuine biological differences in the targeting profiles of different RISC species. Regardless, while any bias towards site types should be considered when interpreting their relative importance, it is clear that imperfect centered sites account for a substantial fraction of the total interactions between the miRNA and mRNA populations.
We have used the biotin pull-down technique to investigate associations between the number of predicted miRNA-binding sites and a transcript's enrichment in the pull-down (Figure 4). These associations were stronger for site counts in the 3′ UTR than in the CDS, consistent with previous reports that 3′ UTR seed matches are more important for mediating interactions [33–35]. It is striking that the number and density of centered sites, and not just of seed sites, was also significantly associated with enrichment in the pull-down. The hypothesis that centered sites mediate many interactions is also supported by the considerable differences between the target sets of miR-10a and miR-10b (Figure 5A), which share the same seed but have different centered sites, although it is possible that some differences are accounted for by 3′ complementary sites.
Shin et al. [21] reported that 'perfect 11-mer matches starting at miRNA positions 3, 4 and 5 were each significantly associated with repression' in over-expression studies, but that 11-mer matches with single mismatches or GU wobbles were not. However, microarray based-assays that rely on changes in the expression levels of target mRNAs will not identify translationally repressed mRNAs, which have been shown to be the primary direct effect of miRNAs [38]. Results from our luciferase assays, which detect miRNA effects at both the mRNA and protein levels, suggest that imperfect centered sites are bona fide miRNA-binding sites that can elicit repression. Given that only a small proportion of the imperfect centered sites result in mRNA destabilization (Figure 6E,F), this would explain why these sites failed to validate in microarray-based studies, but did validate here in luciferase assays (Figure 6B).
Further experimental work on a larger number of sites would be required to elucidate precisely the minimal length and maximum number of mismatches required for centered site-mediated interactions. Regardless, the finding that both perfect and imperfect centered sites can repress gene expression has significant implications for understanding miRNA-controlled genetic networks, as the prevalence of centered sites in the mammalian transcriptome dramatically increases the connectivity and complexity of the networks. It may also explain the evolutionary conservation of regions outside of the seed site [7, 21], although we cannot formally exclude the hypothesis that these regions are conserved due to processes related to miRNA biogenesis. Further experimental work would also be required to compare the efficacy of seed versus centered sites. Although the percentage reduction in luciferase activity shown here (Figure 6B) is comparable with that seen in other studies for seed sites [8], a thorough comparison would require thousands of luciferase assays with accompanying RNAseq and proteomics data.
While centered sites will clearly need to be factored into systems biology models of genetic regulation, it is currently unclear how much (if any) predictive power would be added to target prediction algorithms by the inclusion of imperfect centered sites. It was beyond the scope of this study to develop a prediction model incorporating centered site information, although it seems likely that the high frequency of these sites in the transcriptome would require that additional information such as evolutionary conservation and site accessibility/RNA secondary structure be incorporated to reduce the rate of false positive predictions, as is the case for seed sites. Despite the conceptual simplicity of looking for regions of complementarity, miRNA target prediction suffers from both a lack of specificity (due to the short binding sites), and a lack of sensitivity due to the exclusion of known binding modalities to increase prediction accuracy. This is analogous to the problems suffered by transcription factor binding prediction software, and was a significant driver in the quest for unbiased experimental methods such as ChIP-seq. We believe that the biotin pull-down methodology is complementary to other transcriptome-wide tools such as HITS-CLIP to examine targets of miRNAs without prior expectation of binding modes.
While we have demonstrated here that centered sites are direct targets of miRNAs that result in molecular repression of the target, the larger relationship between targeting and functional repression remains an open question. In biological networks, mRNAs can be insulated from the effects of miRNAs by simply expressing more copies of the mRNA [8], so whilst individual transcripts are still targeted and repressed, the overall protein levels may not change. How many of the targets identified here are functionally repressed versus molecularly repressed is currently unknown, but this is not a weakness of the biotin pull-down (or indeed, a weakness of any other transcriptome-wide method). Instead, this presents us with the interaction data necessary to model properly the outcomes of biological networks in different cell types or tissues with different mRNA expression levels. It will be the combination of these transcriptomic methods with proteomics data that will enable the next leap in understanding.
We used a biotin pull-down method to determine the direct targets of 10 human miRNAs, and found that imperfect centered sites are common mediators of miRNA-mRNA interactions. These sites can repress mRNA activity, typically through translational repression, but further work is needed to establish their functional importance relative to seed sites. Our findings may explain the evolutionary conservation of the central region of miRNAs, and they have important implications for studying miRNA-regulated genetic networks, and for interpreting putative disease-causing variants that do not alter protein sequence but that may fall inside miRNA binding sites.
Materials and methods
Biotin pull-downs, microarray hybridizations and sequencing
We optimized the biotin pull-down method of Orom et al. [18] to improve RNA yield and dynamic range. Briefly, 200 pmoles of synthetic biotin-labeled miRNA duplexes (Table S1 in Additional file 1) were transfected into 4 × 106 HEK293T cells using HiPerFect Transfection Reagent (QIAGEN, Melbourne, VIC, Australia). Cells were harvested after 24 hours, and lysed in hypotonic lysis buffer (10 mM KCl, 1.5 mM MgCl2,10 mM Tris-Cl pH 7.5, 5 mM DTT, 0.5% NP-40, 60U/ML SUPERase•In (Ambion, Austin, TX, USA) and 1X Complete Mini protease inhibitor (Roche, Brisbane, QLD, Australia)). Cell debris was cleared by centrifugation (≥10,000 g at 4°C for 2 minutes). The supernatant was transferred to a clean tube, and NaCl was added to a final concentration of 1 M. myOne C1 Dynabeads (25 μl; Invitrogen) were pre-blocked with 1 μg/μl bovine serum albumin and 1 μg/μl yeast tRNA (Invitrogen), and incubated with the supernatant for 30 minutes at room temperature. Beads were then washed with hypotonic lysis buffer and 1 M NaCl before RNA extraction using an RNeasy Kit (QIAGEN) according to the manufacturer's instructions. Pull-downs were conducted in duplicate or triplicate for each miRNA, and 50 ng of the captured mRNAs per sample were amplified and labeled using the Illumina TotalPrep RNA Amplification Kit (Invitrogen) as per the manufacturer's instructions. Samples were profiled on Illumina Human HT-12 chips along with control RNA from mock-transfected cells to which no miRNA had been introduced. In parallel, RNA extracted from the miR-17-5p pull-down was used in RNAseq library construction as previously described [39] and 50 bp tags were generated on the Applied Biosystems SOLiD (Melbourne, VIC, Australia). These were mapped to the human genome (GRCh37) using the default parameters of the X-MATE pipeline [40]; 70,714,217 of the 101,137,997 tags aligned to GRCh37 (70%).
Hybrid AGO immuno-precipitations and biotin pull-downs
We transfected cells with either synthetic biotinylated miRNA duplexes or synthetic single-stranded biotinylated miRNAs and lysed the cells as described above. After clearing the cell lysate, we harvested 10 μl to use as the input RNA sample. We then used a Dynabeads Protein G Immunoprecipitation Kit (Invitrogen) combined with a ChIP grade mouse monoclonal antibody to AGO2 (ab57113, Abcam, Cambridge, MA, USA) to perform the AGO enrichments according to the manufacturers' instructions. Briefly, 50 μl of beads per precipitation were washed prior to incubation with 10 μg of antibody at room temperature for 10 minutes. Cell lysate was added to the bead-antibody complexes, and incubated for 10 minutes at room temperature. The supernatant from this step was saved as the AGO2-depleted fraction, and the beads were kept as the AGO2-enriched fraction. The beads were washed three times in 200 μl of wash buffer, prior to elution in 30 μl of elution buffer. We then completed the biotin pull-down protocol on both the AGO2-enriched fractions and the AGO2-depleted fractions, as described above.
Primary analysis of microarray data
Statistical tests were conducted in R. Microarray data were normalized using the lumi package [41], by applying background adjustment, variance-stabilizing transformation [42] and robust spline normalization [43] successively. Hierarchical clustering of normalized data (Additional file 9) showed that replicates tended to cluster together and that the samples from the pull-down of a canonical miRNA clustered close to those from the corresponding isomiR pull-down, as expected given the similarity in their sequences. One miR-10b pull-down sample was excluded because it did not cluster with the other replicates. Microarray probes that detected expression above background (detection P-value <0.01) in all control samples were retained (n = 12,008). The lmFit and eBayes functions in the limma package [44] were used to test for differences in RNA abundance ('differential expression') between the pull-down samples and the controls. The FDR was calculated to account for multiple testing [45]. Probes that met the 5% FDR threshold (for one-sided tests) were considered significantly enriched in the pull-down. The transcripts (EnsEMBL V62) to which they matched exactly were considered putative targets of that miRNA.
Analysis of published data on miRNA-mRNA interactions
These lists of targets were compared to results from published datasets, considering miRNA-target interactions that had been demonstrated by luciferase assays (Table S3 in Additional file 1) and by various high-throughput methods. Table S5 in Additional file 1 summarizes our analysis of the latter. To test whether the biotin pull-down targets were enriched in the target list from another study, a FET was applied to ask whether the biotin pull-down targets were more likely than non-targets to be in the target list from another study. Unless otherwise stated, reported one-sided P-values are from an upper-tailed test, and an OR >1 indicates that genes/transcripts/probes that are targets in our biotin pull-down are more enriched amongst the targets identified in the experiment being examined than those that are not targets in the pull-down.
Unless otherwise stated, reported one-sided P-values are from an upper-tailed test, which evaluates the hypothesis that the odds ratio, , is greater than 1. Ambiguous genes/transcripts (those that were detected both by a probe that was significantly enriched and by a probe that was not) were excluded unless otherwise specified. Kolmogorov-Smirnov tests were conducted to compare the distribution of fold-change (expression in biotin pull-down/control) between canonical transcript targets inferred from published experiments and all other canonical transcripts (the canonical EnsEMBL transcript is the longest produced from a gene).
In silicoprediction of miRNA-binding sites
TargetScanS [1] was run on all EnsEMBL transcripts to find seed matches to the miRNAs of interest. A Perl script was also written to count matches to the centered site (11 bp sequence starting at position 3, 4 or 5 of the miRNA). For centered sites, we allowed GU wobble and up to one mismatch (MM) in the middle of the site. We divided the centered sites into four classes (WC 0MM, WC 1MM, GU 0MM, GU 1MM) for all analyses except those of the combined target sets of isomiRs and their canonical partners, in which we pooled all classes together.
Statistical analysis of predicted binding sites and enrichment status
A FET was applied to ask whether transcripts containing at least one predicted binding site of a particular type were more likely than those with no site to be unambiguously classified as targets in the pull-down.
where p i,m is the probability that the probe detecting transcript i is significantly enriched in the pull-down of miRNA m; x a,b,m,i is the number of miR-m sites of type a in region b of transcript i (for example, miR-17-5p seed sites in the 3′ UTR); β a,b is the coefficient (or weight) corresponding to that count and β 0 is some constant. A value of β a,b significantly greater than zero would indicate that, as the number of sites of type a in region b of a transcript increases, so too does the probability that the transcript is detected as significantly enriched in the pull-down. All coding transcripts with unambiguous enrichment status were included.
Luciferase assays
Luciferase assays were carried out as previously described [8]. Briefly, complementary oligonucleotides corresponding to 54 nucleotides surrounding the miRNA binding site were annealed before being cloned into the SpeI and HindIII sites of pMIR-REPORT Luciferase (Ambion). A list of all oligonucleotides used is available in Table S6 in Additional file 1. All constructs were verified by capillary sequencing. HEK293T cells were co-transfected with 50 ng of a pMIR-REPORT Luciferase construct, 50 ng of pMIR-REPORT β-galactosidase (Ambion) and 10 nM of the appropriate mirVana miRNA mimic (Ambion/Life Technologies). After transfection, cells were incubated for 48 hours prior to harvesting. Luciferase activity was assayed using the Luciferase Assay System (Promega, Sydney, NSW, Australia), and detected on a Wallac 1420 luminometer (Perkin Elmer, Waltham, MA, USA). Transfection efficiency was assessed by β-galactosidase activity, using the β-Galactosidase Enzyme Assay System (Promega, Sydney, NSW, Australia), and detected on a PowerWave XS spectrophotometer (BioTek, Winooski, VT, USA).
Quantitative RT-PCR
Primers used to determine whether transcripts were degraded after miRNA transfection are listed in Table S7 in Additional file 1. Cells were either mock-transfected, or transfected with biotinylated miRNAs as described in the Materials and methods section. RNA was purified from cell pellets using an RNeasy Mini Kit (QIAGEN). RNA integrity was assessed using an Agilent Bioanalyzer 2100, cDNA synthesis was carried out using random hexamer primers and SuperScript III (Invitrogen). qRT-PCR was performed using SYBR green PCR master-mix (Applied Biosystems) on an Applied Biosystems ViiA™ 7 Real time PCR system. Expression levels were calculated relative to those in the mock-transfected cells.
Bio-layer interferometry
The generation and validation of the MDA-MB-231 miR-182-5p inducible cell line has been previously described [36]. miRNA expression was induced by the addition of 1 μg/ml doxycycline. Biotin-labeled miRNA duplexes were transfected into MDA-MB-231 cells using Dharmafect 4 (Thermo Fischer, Melbourne, VIC, Australia) according to the manufacturer's instructions for this cell line. All cells were incubated in 5% CO2 for 48 hours prior to harvesting. RISC affinity purification was performed as previously described [46] with the following modifications: (i) the lysis buffer used was 10 mM Tris pH7.5 (Ambion), 10 mM KCl (Ambion), 1.5 mM MgCl2 (Ambion), 0.5 mM DTT (Invitrogen), 0.5% NP40 (Sigma Aldrich, Sydney, NSW, Australia), and 1X EDTA-free Complete protease inhibitor (Roche); (ii) cell lysates were cleared by centrifugation at 16,000 g for 30 minutes at 4°C. The miR-182-5p capture oligo and all binding site oligo sequences are shown in Table S8 in Additional file 1. Association and disassociation profiles were generated using the Octet Red (Forte Bio, Menlo Park, CA, USA) and streptavidin biosensors (Forte Bio) using the following parameters: lysis buffer for 60 seconds; RNA oligo for 10 minutes; saturated biotin (Sigma Aldrich) solution for 10 minutes; lysis buffer for 60 seconds; RISC solution for 10 minutes (association); lysis buffer for 10 minutes (disassociation). Wells were kept at 30°C, and rotated at 1,000 rpm to ensure a homogenous mix.
Accession numbers
Data used in this manuscript are available from the Gene Expression Omnibus (GEO) under accession numbers GSE29101 (miR-10 family and mock transfection microarray data), GSE38593 (miR-182 microarray data), GSE40406 (miR-424 and miR-199a microarray data), and GSE55059 (all remaining microarray and sequencing data).
bio-layer interferometry
- bp:
base pair
coding sequence
- ChIP:
chromatin immunoprecipitation
confidence interval
crosslinking immunoprecipitation
false discovery rate
Fisher's exact test
high-throughput sequencing of RNAs isolated by crosslinking immunoprecipitation
- miRNA:
odds ratio
photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation
polymerase chain reaction
- qRT-PCR:
quantitative RT-PCR
RNA-induced silencing complex
untranslated region.
We are grateful for the helpful discussions with all members of QCMG, and we are particularly thankful to John Pearson, Darrin Taylor, and Scott Wood for HPC infrastructure and support, David Miller and Peter Wilson for sequencing infrastructure and support, as well as technical assistance from the QCMG sequencing and QCMG informatics teams. We also wish to thank Michael Yarski for excellent and timely assistance with the bio-layer interferometry, and the anonymous reviewers whose detailed reviews improved this manuscript.
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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.


text:
'This is snow,' Moomintroll whispered to himself.
Moomins always sleep through the winter - or they did until the year Moomintroll woke up and went exploring in the silent, snow-covered valley where the river used to scuttle along and all his friends were so busy in summer.
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- publisher: Penguin Books Ltd
- publisher imprint: Puffin
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subset: commoncrawl


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by Duncan Larkin, Published Jan. 12, 2012, Updated Jan. 12, 2012 at 10:54 PM UTC
One Air Force Academy graduate breaks the marathon mold.
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Skip to comments.Wildlife Officials Warn Hunters Of Deadly Rabbit Fever
Posted on 02/23/2013 4:20:32 PM PST by k4gypsyrose
RALEIGH, N.C. (CBS Charlotte) - Officials with both the North Carolina Division of Public Health and the Wildlife Commission are urging hunters to be wary about rabbit fever after two hunters contracted it this month.
(Excerpt) Read more at charlotte.cbslocal.com ...
Deadly Rabbbits can be Deadly. Just ask Jimmy Carter.
A saying in Wyoming is only hunt rabbit only in the months with r's
Well just let us let the terrorists know!
Never thought I would get to use this two nights in a row.
I'm a wabbit swayer
Here's the health warning:
Actually, I was thinking more along the lines of: "Da deadwey Sabah-Toot'd Wabbit"... *grin*
[clop clop whinny]
KNIGHT: Theyre nervous, sire.
ARTHUR: Then wed best leave them here and carry on on foot. Dis-mount!
TIM: Behold the cave of Kyre Banorg!
ARTHUR: Right! Keep me covered.
KNIGHT: What with?
ARTHUR: Just keep me covered.
TIM: Too late!
ARTHUR: What?
TIM: There he is!
ARTHUR: Where?
TIM: There!
ARTHUR: What, behind the rabbit?
TIM: It is the rabbit!
ARTHUR: You silly sod! You got us all worked up!
TIM: Well, thats no ordinary rabbit. Thats the most foul, cruel,
and bad-tempered rodent you ever set eyes on.
ROBIN: You tit! I soiled my armor I was so scared!
TIM: Look, that rabbits got a vicious streak a mile wide, its a
KNIGHT: Get stuffed!
TIM: Itll do you a trick, mate!
KNIGHT: Oh, yeah?
ROBIN: You mangy Scot git!
TIM: Im warning you!
ROBIN: Whats he do, nibble your bum?
TIM: Hes got huge, sharp he can leap about look at the bones!
ARTHUR: Go on, Boris. Chop his head off!
BORIS: Right! Silly little bleeder. One rabbit stew comin right up!
TIM: Look!
BORIS: Aaaugh!
ARTHUR: Jesus Christ!
TIM: I warned you!
ROBIN: I peed again!
TIM: I warned you! But did you listen to me? Oh, no, you knew it all, didnt you? Oh, its just a harmless little bunny, isnt it? Well,
its always the same, I always
ARTHUR: Oh, shut up!
TIM: But do they listen to me?
ARTHUR: Right!
TIM: -Oh, no
KNIGHTS: Charge!
[squeak squeak]
KNIGHTS: Aaaaugh! Aaaugh! etc.
KNIGHTS: Run away! Run away!
I'm surprised that hunters don't all know about Rabbit fever. I remember back in the 50s when we hunted Rabbits, we never touched them with our bare hands. We gutted and skinned them with gloves on and washed the meat. Then we cooked them and ate them. If it hadn't been for Rabbits I would have been hungry a lot more often. Think surviving through the great Depression and WWII.
Remember....this is exactly how the anthrax attack started....'cept the guy went fishing...not hunting..
The sequester will cause a deadly zombie rabbit apocolypse.
We never took any bunnies till after the first good hard freeze that would kill the sick ones off.
My Dad didn't back in the '40s when he hunted and skinned Idaho jackrabbits for making fur-lined gloves for the Army. He contracted Tularemia and nearly died from it. It's no joking matter.
I had Bunny Fever once. I found my Dad's Playboy mags.
dang, video didn't embed
LOL ... you're on to 'em.
It's been around for as long as I can remember...this sounds more like the press pointing out it's not safe to hunt so give up your guns.
This is getting out of hand, these apparently normal rabbits ...
See BS has no idea how this article has helped Americans locate terrorists. Once the terrorists begin harvesting wabbits American Hunters can unload on 'em and when the terrorists lay bleeding on the cold ground out in the woods, the police will say ... I can see you thought he was up to no good. Show me your terrorist's hunting license and I'll be on my way.
(i had to ;)
A few years ago in Arizona there was a veterinarian who died of it after hunting rabbits.
You'd think a vet would know about that sort of thing.
It's not a disease that gets much press. Even the doctors who treated my Dad had a difficult time diagnosing it.
I recall taking the same precautions in Arizona. We ate a fair number of cotton tails and no one got sick.
His encounter with peter cottentail is timeless. I think there's a video of it on youtube. Does anyone have the link?
"Dem Wabbits gone all Jihadi, now."
I thought the same thing, but I posted it to FR for 2 reasons. 1. Becuase many freepers are hunters and should know the warnings and 2. Let freepers decide if this is just more MSM "Keep up the agenda" writing.
Thanks for the laugh. I'm a noobie here...where's the sandbox?
No silly, you have rabbits confused with oysters. You are only supposed to eat oysters from the Gulf in months that have a "r" in it. :)
Welcome to the home of conservative keyboard activists. Do you mean the HTML sandbox? If so just do the inhouse search.
We pretty much lived on wild game during depression. During the big war we had been moved to the "city" of Huntsville, Ala. so my brother raised white rabbits in the backyard. We ate those bunnies.
You need "The Holy Hand Grenade of Antioch" for that rabbit.
You need "The Holy Hand Grenade of Antioch" for that rabbit.
Ok, will do. thanks
Sheesh, now I'll have people wondering if I am going to take over the world with rabbits.
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Hf240 300 Fully Automatic Biochemistry Analyzer - Chinaprice: contact company for price
1. Multi- channel post- spectro reaction system
2. Accurate reagent and sample collection system
3. High- efficient self- cleaning system
4. Intelligent accurate liquid level detection system
5. Easy and fast software operation system
6. Timely and thoughtful service network
1. Working Mode: Fully- auto, discrete, random access, measured in assay cup directly
2. Throughput: 300 tests/ h
3. Colorimetric cup: 120 ultraviolet colorimetric cups ( assay cup) , quartz cuvette is optional.
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5. Cleaning mechanism: 120 colorimetric cups on reaction plate can be cleaned automatically and recycling, low costs and convenient to use
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8. Analysis project: as many as 45 items online biochemical test ( standard configuration, extensible)
9. Sample position: 60 sample cups ( or primary tube)
10. Reagent position: 45 R1 or R2 kits can be contained at one time ( extensible and all of them will be refrigerated independently)
11. Sample injector: independent sample injector and reagent injector to reduce the cross contamination speed up the testing process
12. Response time: 0- 999 seconds
13. Injector : ceramic trace plunger pump
14. Measure Method: end- point method, dynamic method, immunoturbidimetry, fixed time method, etc
15. Measurable wavelength: 340- 800 nm ( single/ double wavelength)
16. Pre- dilution: samples whose concentration beyond the linear range can be diluted and remeasured automatically
17. System calibration: deduction of cell blank and reagent blank, automatic zero setting,
18. Quality control: quality control tests can be added. Data can be stored, displayed, counted and quality control chart can be printed
19. Calibration: linear/ nonlinear, single point/ multi- point calibration
20. Light source: 12 v long- life halogen lamp
21. Light path system: multi- channel optical fiber, post- spectro, display the response curve during the whole course
22. Receiver: original imported optical sensor
23. Resolution: 0.0001 ABS
24. Sample volume: 1 μ L - 100 μ L
25. Dose: R1: 1- 400 μ L, R2: 1- 400 μ L
26. Power: 600W( Max)
27. Dimension: 930* 730* 1000( mm)
28. Operation system: windows2000 or above, English interface, various reports printed
29. The minimum of reagents: 180μ L
Company Contact:
- Posted By: Han Fang Medical Instrument Co., Ltd
- Phone: 8613854853835
- Address: Room 2013, Block A, No. 7, Zhengfeng Road, Jinan H, Jinan,Shandong, China
- Email:
- Website: http://www.hanfangmed.com
Published date: January 7, 2015 -
- Business Description: We, Han Fang Medical Instrument, ISO 13485 certified, are a professional laboratory instrument supplier in China. Our products include biochemical analyzer, blood cell analyzer, blood coagulation analyzer, etc.
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HF6000- 4 semi- automatic coagulation analyzer has a bench- top design and is ideal for small and medium- sized hospitals, laboratories and clinical centers. Four channels for the same item of four persons or for four different items of one person. w...
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text:
This week's #WordlessWednesday inspiration comes from Blue Mountain…
Remember the Parent Club review of Blue Mountain Resorts?…with Family Day and March Break coming up it's timely to highlight as a pretty family friendly spot.
This week's #WordlessWednesday inspiration comes from Blue Mountain…
Remember the Parent Club review of Blue Mountain Resorts?…with Family Day and March Break coming up it's timely to highlight as a pretty family friendly spot.
Follow Caroline on Twitter (@ParentClub) and Instagram (parentclub). Author of two books: Boredom Busters (Cico Books, 2014) and More Boredom Busters (Cico Books, 2015). Boredom Busters was named a 2016 Silver Birch Non-Fiction Honour Book. Caroline is honoured to be listed as one of Toronto's Top Mom Bloggers.
Tammi @ My Organized Chaos says
Looks like a beautiful resort!!
parentcl says
It's a great combination of outdoor space and family ammenties (like restaurants 'cause Mamma's not cooking on vacation).
stevebethere says
Awesome I could do with going there now it's freezing here heheh!
Have a suntastic week 😉
parentcl says
I know – me too!
torontoteachermom says
I LOVE Blue Mountain! I'm going back in the summer just to tackle the Timber Challenge High Ropes one more time.
parentcl says
I could only manage the Low Rope course (and it freaked me out) but I was so proud to have finished it.
Meryl says
It looks wonderful!
parentcl says
It is a stunning location. Need. To. Go. Back.
Theresa says
That looks like a very pretty place to visit. And warm too. Wish I had that view instead of all the snow we do have here!
parentcl says
ah it was in the fall…oh to be there now.
Teresa Kindred says
How beautiful! Wish I was there!
parentcl says
I would certainly go back
Susie says
Beautiful! Makes me long for summer!
parentcl says
Makes me long for sunshine! Winter is too long.
Karly @ Three in Three says
What a gorgeous area!
parentcl says
North of Ontario – it is a little spot of heaven
alissa says
That's really pretty. It looks like an outside chess game was taking place.
parentcl says
My kids were playing the outside chess…I had to wait and wait til they took a thinking break to take the picture.
Judy Haughton-James says
What a wonderful place to spend a vacation! Beautiful shots. Thanks for hosting.
parentcl says
Thanks for visiting!
Christy J (@orangeheromama) says
I can't believe that I've never been there!! So gorgeous!
parentcl says
You gotta go once!
veronica lee says
Looks like a lovely place to visit. Love the pics.
parentcl says
Thanks – happy #WW!
Robin (Masshole Mommy) says
Looks like a great place for a family vacay!!
parentcl says
Total fun-ness
Wayne says
That is a great spot for families. Thanks for linking up with me this week. I appreciate it.
parentcl says
Looking forward to virtually visiting you again next week Wayne.
Amy @ The BOAT says
That looks like a great get away! Thanks for sharing and linking up to The BOAT!
thejennyevolution says
It does look beautiful there 🙂 Thanks for joining us at Wordless Wednesday Bloggers!
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Charlotte says
Looks like a beautiful place!
Victoria Ess says
Gorgeous — I love Blue in the summer and winter


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greatgma Review
This camera is very user friendly and I am enjoying it verymuch---thank you
- How did the image on site compare with the actual product? PERFECT
- Was the product free of any manufacturer defects? as far as I can tell so far
- Please tell us about the quality of the product. I am satisfied
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You're supposed to use it after you wipe elsewhere
Warning: This will probably change the way you look at dropped food forever
Find out if you're quenching your thirst with a nice, cold swig of germs
Your dumbbell has 362 times more germs than your toilet seat—and more dirty stats that'll have you dashing to the showers
The extra precautions you're taking to stay healthy might not be working at all
How to avoid breakouts, chafing, and more
Didn't think that was possible, did you?
A new study confirms that gyms are disgusting. Here's what to look out for—and how to stay healthy
It's sexy—until someone gets E. coli
You may want to think twice before touching them
You may be sabotaging your health—when you think you're saving it


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My Mom Thinks She's My Volleyball Coach... But She's Not!
By (author) Julia Cook
Format: Hardback
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My Mom Thinks She's My Volleyball Coach... But She's Not! by Julia Cook
Book DescriptionGrades 5-8) For all of us that love watching volleyball but have a tendency to get a little too involved in the game. For those of us that cross the line between supportive fan and obnoxious spectator. This book will serve as a gentle and hilarious reminder that... Coaches Coach, Officials Officiate, Players Play, and Parents Parent (cheer, hug, encourage, help transport, feed). Written by an experienced volleyball mom and USA Volleyball, this book is designed to make the volleyball court a much more enjoyable place for us all to be. Includes tips from USA Volleyball for parents, coaches, players, and officials. Proceeds from the sale of this book go to USA Volleyball
Buy My Mom Thinks She's My Volleyball Coach... But She's Not! book by Julia Cook from Australia's Online Bookstore, Boomerang Books.
Book DetailsISBN: 9781934073100
(235mm x 207mm x 8mm)
Pages: 30
Imprint: National Center for Youth Issues
Publisher: National Center for Youth Issues
Publish Date: 1-May-2007
Country of Publication: United States
Books By Author Julia Cook
View all books by Julia Cook
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