In prospective memory tasks different kinds of load can occur. Adding a prospective memory task can impose a load on ongoing task performance. Adding ongoing task load (OTL) can affect prospective memory performance. The existence of multiple target events increases prospective load (PL) and adding complexity to the to-be-remembered action increases retrospective load (RL). In two experiments, we systematically examined the effects of these different types of load on prospective memory performance. Results showed an effect of PL on costs in the ongoing task for categorical targets (Experiment 2), but not for specific targets (Experiment 1). RL and OTL both affected remembering the retrospective component of the prospective memory task. We suggest that PL can enhance costs in the ongoing task due to additional monitoring requirements. RL and OTL seem to impact the division of resources between the ongoing task and retrieval of the retrospective component, which may affect disengagement from the ongoing task. In general, the results demonstrate that the different types of load affect prospective memory differentially. This type of memory has been labeled prospective memory load(PML) refers to the additional demands that emerge for ongoing task processing when a prospective memory task is added  refers to the demands of the task in which the prospective memory task is embedded  refers to the number of potential prospective memory targets or target categories that are relevant for one or more pending prospective memory tasks  processes theory, PML costs occur for every prospective memory task, because participants rely on preparatory attentional processes to notice the prospective memory targets and respond accurately  to allow for a pure measurement of the prospective component. Nevertheless, it is still possible that participants detect a prospective memory target and correctly interrupt the ongoing task, but then fail to retrieve the retrospective component. If this happens, the prospective memory measure is contaminated by retrospective memory failure. In previous studies we have shown that this type of error is more likely to occur in older adults . In the high PL condition prospective memory targets were four specific words from four taxonomic categories . With high PL more resources may be required to detect prospective memory targets. Therefore, we expected that higher PL would increase PML costs. As target events were not presented repeatedly in the low PL condition, we did not expect an effect of PL for prospective memory performance . As the latter condition required that participants kept track of the number of encountered prospective memory targets, we expected RL to affect the retrospective component of prospective memory performance.M = 22.5, SD = 2.98) participated in this study. They were undergraduate volunteers from the University of Bern. The orthogonal combination of PL and RL resulted in a 2 × 2 between-subjects design. Participants were randomly assigned to one of the four experimental conditions. In each condition 15 participants were tested. The study was approved by the local ethical committee of the University of Bern, and all participants gave informed consent.Sixty young adults between 18 and 30 years (t(6) = 1.19, p > 0.28  and consisted of the German nouns “Pferd” (horse), “Vogel” (bird), “Fuchs” (fox), and “Frosch” (frog). In the high PL condition, prospective memory targets were selected from each of the four categories “animals”, “vehicles”, “musical instruments” and “sports equipment”. Prospective memory targets were “Pferd” (horse), “Auto” (car), “Geige” (violin), and “Ball” . Word frequencies did not differ for the two sets of prospective memory targets, SD = 62 ms). Specifically, for 48 participants presentation time was 250 ms, for 10 participants it was 375 ms, and for two it was 500 ms. An analysis of variance (ANOVA) with the four different groups as between-subject factor revealed no significant differences  = 1.04, p > 0.37). Next, the baseline phase followed, in which a total of 16 words and 16 nonwords were presented. Stimuli were presented for 120% of the individually adjusted presentation time.The procedure is depicted in Figure Then, participants were instructed on the prospective memory task. They were informed that an additional goal of the study was to investigate how well they could remember to carry out an intended activity in the future. For the low RL groups the activity was to press a particular key (“1”) on the keyboard for every target. The high RL groups were requested to press a different key for each prospective memory target . Specifically, they were instructed to press the appropriate key on the keyboard with the left index finger whenever they saw a prospective memory target. Moreover, for half of each RL group, the low PL condition, the prospective memory targets were four specific animal words , and for the other half, the high PL condition, prospective memory targets were four specific words from the categories “animals”, “vehicles”, “musical instruments” and “sports equipment” . The instructions were explained until participants understood and were able to repeat them.Next, an unrelated questionnaire was administered for 10 min to create a filled retention interval. Then, the ongoing task containing the prospective memory targets was started. The prospective memory task was not mentioned again. A total of 192 trials were presented. Prospective memory targets occurred on the 47th, 95th, 143rd, and 191st trial. The selection of one of four prospective memory targets was random without replacement. Whenever participants released the shift-key, the ongoing task was interrupted. When they appropriately released the shift-key and pressed any of the four keys for the prospective memory task, a screen with the request to “press the shift-key to continue” appeared.At the end of the experiment, participants who failed to correctly respond to any of the four prospective memory targets were asked whether they remembered the instructions for the prospective memory task. All participants managed to recall them accurately.η2 are partial η2. Prospective memory performance was measured as proportion of correct responses. First, overall prospective memory performance was analyzed. A response was scored as correct, when the shift-key was released and the appropriate key was pressed on the appropriate occasion. Proportions of correct prospective memory responses are displayed in Figure F = 6.49, p < 0.05, MSe = 0.14, η2 = 0.10 (M = 0.59 for low RL and M = 0.35 for high RL). No other effect was significant . Directed comparisons revealed that the main effect of RL was mainly driven by the difference in the low PL condition, t(28) = 2.37, p > 0.05, while the effect in the high PL condition was not statistically significant, t(28) = 1.23, p = 0.21.For all statistical analyses alpha was set at 0.05. All reported Fs < 1; all ps > 0.5; MSe = 0.12).Next, prospective memory performance was analyzed separately for the prospective component and the retrospective component. For the prospective component, a response was scored as correct when the shift-key was released on the appropriate occasion. Proportions of correct responses for the prospective component are displayed in Figure F = 24.64, p < 0.01, MSe = 0.10; η2 = 0.33 (M = 0.97 for low RL and M = 0.54 for high RL). No other effect was significant .t(26) = 3.99, p < 0.01 and t(24) = 3.04, p < 0.01, respectively.The retrospective component was scored as correct when the appropriate key was pressed after the shift-key had been released. For the high RL condition, a response was scored as correct, when the key-press corresponded to the correct position of individually detected prospective memory targets. Overall 54 of the 60 participants correctly interrupted the ongoing task at least once. For these participants performance on the retrospective component was calculated as conditional probabilities. Proportions of correct responses across the four groups are also shown in Figure t-test revealed that reaction times were significantly higher in the ongoing task (608 ms) than in the baseline phase (531 ms), t(59) = 7.19; p < 0.01. The difference between baseline performance and ongoing task performance was calculated as a measure of PML costs. Positive values indicate a slowing in reaction times for the ongoing task compared to the baseline. Mean differences are displayed in Figure Fs < 1; all ps > 0.25).Reaction times for correct responses to word trials of the lexical decision task were compared for the baseline and the ongoing task. In order to exclude potential after-effects of responding to prospective memory targets, we excluded 6 trials following a prospective memory response  than in the baseline phase (90.6%), t(59) = 2.37; p < 0.05, indicating a practice effect. A two-factorial ANOVA for the accuracy difference between baseline and ongoing task with PL and RL as between-subjects factors revealed no significant effects .We also compared accuracy in the lexical decision task for baseline and ongoing task trials. A paired sample The goal of Experiment 1 was to examine the effect of PL and RL on prospective memory performance. The results revealed an effect of RL, but not of PL for overall prospective memory performance. Separate analyses for both components revealed that RL affected the retrospective component, but not the prospective component. Moreover, neither PL nor RL affected PML costs.We did not find an effect of PL on prospective memory performance. This result is consistent with Einstein et al.  who did In the present study, there was also no effect of PL on PML costs. This may indicate that PL does not affect performance for specific targets. However, PL effects may materialize with categorical targets. To test this possibility, categorical prospective memory targets were used in the Experiment 2.In Experiment 1, RL affected prospective memory performance, particularly retrieval of the retrospective component. We assume that lower performance on the retrospective component in the high load condition is due to the additional requirements of updating the memory for future remembering. Because all participants were able to correctly recall the requirements for the retrospective component in the post-experimental interview, forgetting to press the correct key rather seems to be due to a transient failure of output monitoring than due to completely forgetting what one has to do. In prospective memory tasks, retrieval of the retrospective component is often resource demanding, because it also requires disengaging from the ongoing task and switching to the prospective memory task. As retrieval of the retrospective component and switching the tasks draw from the same pool of processing resources, almost simultaneously a competition between these processes occurs. As resource-demanding processes require time to complete, competition can result in a completion failure of already initiated processes  participated in this study. They were undergraduate volunteers from the University of Bern. PL was manipulated by using categorical prospective memory targets from either one taxonomic category (low PL) or four taxonomic categories (high PL). RL was manipulated by varying the complexity of to-be-remembered actions for the four prospective memory targets as in Experiment 1. OTL was manipulated by varying the pace of the ongoing lexical decision task. In the low OTL condition, stimuli were presented somewhat longer than the individually adjusted presentation time. In the high OTL condition, one half of the stimuli (including the four prospective memory targets) were also presented somewhat longer than the individually adjusted presentation time. The other half was presented somewhat shorter in order to increase the pace of the ongoing task. PL, RL, and OTL were crossed orthogonally, resulting in a 2 × 2 × 2 between-subjects design. Participants were randomly assigned to one of the eight experimental conditions. In each condition 18–20 participants were tested.Hundred and fifty-three young adults between 17 and 30 years  were also presented for 120%. The other half of the trials were presented for 80% of the individually adjusted presentation time.F = 9.87, p < 0.01, MSe = 0.13, η2 = 0.06, (M = 0.53 for low RL and M = 0.35 for high RL) and a significant effect of OTL, F = 7.32, p < 0.01, MSe = 0.13, η2 = 0.05 (M = 0.52 for low OTL and M = 0.36 for high OTL). No other effect was significant . As the pattern of results suggests a marginal interaction between PL and RL, we conducted further analyses. For the low PL conditions, these revealed consistent significant differences between high and low RL with t(36) = 2.50, p < 0.05 for the low OTL condition, and t(38) = 2.78, p < 0.05 for the high OTL condition. In contrast, no significant effect materialized in the high PL conditions .First, overall prospective memory performance was analyzed. A response was scored as correct when the shift-key was released and the appropriate key was pressed on the appropriate occasion. Proportions of correct responses are displayed in Figure Fs < 2.5 all ps > 0.1; MSe = 0.14). Although the scores for low PL were numerically higher (M = 0.59) than for high PL (M = 0.49) this difference was not significant, F = 2.44, p = 0.12; MSe = 0.14.Next, prospective memory performance was analyzed separately for the prospective and the retrospective components. For the prospective component, a response was scored as correct when the shift-key was released on the appropriate occasion. Proportions of correct responses are displayed in Figure F = 37.4, p < 0.01, MSe = 0.09, η2 = 0.25 (M = 0.95 for low RL and M = 0.61 for high RL), a significant main effect of OTL, F = 8.17, p < 0.01, MSe = 0.09, η2 = 0.07 (M = 0.86 for low OTL and M = 0.70 for high OTL) and a significant interaction between RL and OTL, F = 8.25, p < 0.01, MSe = 0.09, η2 = 0.07. Post hoct-tests revealed that OTL affected performance in the high RL condition  = 3.16, p < 0.01) but not in the low RL condition  = 0.13, p > 0.89). No other effect was significant .The retrospective component was scored as correct when the appropriate key was pressed after the participants had released the shift-key. For the high RL conditions, responses were scored as correct when the response corresponded to the position of the individually detected prospective memory targets. Overall, 119 of the 153 participants correctly interrupted the ongoing task at least once. For these participants performance on the retrospective component was analyzed as a conditional probability. Proportions of correct responses across the four groups are also shown in Figure t-test revealed that reaction times were significantly higher for the ongoing task (736 ms) than for the baseline (594 ms), t(151) = 9.68, p < 0.01. The difference in mean reaction times for the lexical decision task between the baseline phase and the ongoing task was calculated as a measure of PML costs. Positive values indicate a slowing in reaction times for the ongoing task compared to the baseline trials. Mean differences are displayed in Figure F = 15.78, p < 0.01, MSe = 30491, η2 = 0.10 (M = 89 ms for low PL and M = 201 ms for high PL), and a marginally significant effect of RL, F = 3.63, p = 0.06, MSe = 30491, η2 = 0.02 (M = 118 ms for low RL and M = 172 ms for high RL). No other main effect and interaction reached significance .Using the same procedure in Experiment 1, we compared reaction times for correct responses to word trials of the lexical decision task for the baseline and the ongoing task. A paired sample seline 59 ms, t than in the baseline phase (92.9%), t(151) = 3.50; p < 0.01, indicating a practice effect. A three-factorial ANOVA for the accuracy difference between baseline and ongoing task with PL, RL and OTL as between-subjects factors revealed no significant effects  should also interact with RL. To test this assumption we manipulated OTL by varying presentation times for stimuli in the ongoing task.Our results showed that OTL affected the retrospective component. This is consistent with our assumption. It is also in line with a proposition by Graf  that shiThis study addressed the question of whether different types of load affect prospective memory performance differentially. We manipulated PL, RL, and OTL to investigate their impact on the prospective and retrospective components of prospective memory separately. Our results revealed that PL affected PML costs, RL influenced retrieving the content of the intention and performing the required action, and OTL affected the ease with which participants managed to disengage from the ongoing task. In general, load affected the retrospective component rather than the prospective component. As automatic processes are assumed to require minimal processing resources and to occur without conscious control, remembering the prospective component may be less susceptible to resource demanding load manipulation. By contrast, controlled processes are slower and resource demanding and therefore, the retrospective component is more likely to be affected by resource demanding load manipulations.PL showed no effect for specific targets (Experiment 1) but affected PML costs for categorical targets (Experiment 2). Although this result may be based at least partly on the specific manipulation, it is also in line with the multiprocess theory  were found for both specific and categorical targets. This indicates that, in both experiments, processing resources were required for the prospective memory task. Therefore, this result is consistent with the PAM theory Smith, . HoweverIn the present study, we varied the pace of the ongoing task to manipulate OTL. This manipulation affected the retrospective component, most likely it resulted in an unsolved competition for processing resources between processes required for disengaging from the ongoing task and processes required for retrieving the retrospective component. This result suggests that depending on the strength of the manipulation of OTL and depending on RL, OTL can either lead to a deficit in noticing the prospective targets (e.g., Marsh and Hicks, To summarize, in the present study we systematically distinguished between different types of load that can occur in prospective memory situations. The distinction between OTL and PL is derived from the dual task requirements that are present in prospective memory tests. The distinction between PL and RL results from the two-component nature of a prospective memory task. We presented evidence that these types of load affect prospective memory performance differently. However, we believe that depending on the specific task requirements these effects can be moderated by other variables, for example by the degree of processing overlap between study and test phase processing, processing overlap between ongoing task and prospective memory task requirements and the association between prospective memory targets and the content of an intention.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Since it is the site of initial immune activation and priming of antigen-specific T cells, as well as the first location to which tumor cells metastasize, our research focuses on understanding the immune status and tumor-induced suppression within breast cancer (BrCa)-draining sentinel lymph nodes (SLN).Suppressive immune subsets were profiled by multi-color flow cytometry in two different BrCa SLN cohorts. In the first cohort, collected at the Providence Cancer Center (08/11-07/13), we looked at frequencies of HLA-DR- CD14+ myeloid cells and their expression of co-stimulatory and inhibitory receptors. Four metastasis+ SLN and 11 metastasis- SLN were assessed in this cohort. SLN in the second cohort were collected at the VUmc in Amsterdam and Kennemer Gasthuis in Haarlem (10/13-06/14) and contained 2 metastasis+ and 7 metastasis- SLN. In this cohort the frequencies of HLA-DR- CD14+ cells as well as CD25_hi FoxP3+ T regulatory cells (Treg) were analyzed. Since all tumors corresponding to the metastasis+ SLN turned out to be HER2 negative, only metastasis- SLN from HER2- tumors were included. Apart from 2 tumors in the Providence cohort, all tumors did express progesterone and/or estrogen receptors.Elevated frequencies of HLA-DR- CD14+ immature myeloid cells could be detected in the metastasis+ SLN in both cohorts. This difference was statistically significant for the Providence cohort (p < 0.0001) (3.8 fold increase). No differences were observed for expression levels of the co-stimulatory molecules CD80 and CD86 or the inhibitory molecules PD-L1 and B7H4 on HLA-DR- CD14+ cells between positive or negative SLN and expression was low for all these markers. Due to the small number of metastasis+ SLN in the Dutch cohort statistics could not yet be performed, but a 2.3 fold increase in HLA-DR- CD14+ cells was seen. In this cohort, frequencies of Treg were found to be 4-fold higher in the metastasis+ SLN compared to metastasis- SLN (0.31 ± 0.22 vs. 1.22 ± 0.24 Treg of CD4 T cells). Moreover, a significant correlation was observed between the frequencies of HLA-DR- CD14+ immature myeloid cells and the frequencies of Treg in these BrCa SLN .Our data suggest that tumor-derived factors negatively influence both the myeloid and the lymphoid compartments within SLN draining HER2 negative breast cancers.Written informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.


Stored biological samples with pathology information and medical records are invaluable resources for translational medical research. However, RNAs extracted from the archived clinical tissues are often substantially degraded. RNA degradation distorts the RNA-seq read coverage in a gene-specific manner, and has profound influences on whole-genome gene expression profiling.We developed the transcript integrity number (TIN) to measure RNA degradation. When applied to 3 independent RNA-seq datasets, we demonstrated TIN is a reliable and sensitive measure of the RNA degradation at both transcript and sample level. Through comparing 10 prostate cancer clinical samples with lower RNA integrity to 10 samples with higher RNA quality, we demonstrated that calibrating gene expression counts with TIN scores could effectively neutralize RNA degradation effects by reducing false positives and recovering biologically meaningful pathways. When further evaluating the performance of TIN correction using spike-in transcripts in RNA-seq data generated from the Sequencing Quality Control consortium, we found TIN adjustment had better control of false positives and false negatives , as compared to gene expression analysis results without TIN correction .TIN is a reliable measurement of RNA integrity and a valuable approach used to neutralize in vitro RNA degradation effect and improve differential gene expression analysis.The online version of this article (doi:10.1186/s12859-016-0922-z) contains supplementary material, which is available to authorized users. In vitro RNA degradation occurs in most of the isolated RNA samples and the degree of degradation depends on the specimen collection and storage conditions such as formalin-fixed, paraffin-embedded (FFPE) and fresh frozen –3. This https://www.illumina.com/content/dam/illumina-marketing/documents/products/technotes/evaluating-rnaquality-from-ffpe-samples-technical-note-470-2014-001.pdf). Illumina® proposed DV200 metric (the percentage of RNA fragments > 200 nucleotides) to assess RNA quality. However, similar to RIN, DV200 is also an overall measurement and fails to determine RNA degradation at transcript level.RNA Integrity Number (RIN) is the most widely used approach to assess in vitro RNA degradation –3, 7. HoThe reduction of sequencing cost has opened doors for large-scale, RNA-seq-based, gene expression profiling studies (like TCGA) that use clinical specimens with rich outcomes data. At the same time, the RNA quality of these clinical samples could vary significantly and poses a great challenge to gene expression analysis. Here we developed a novel algorithm–transcript integrity number (TIN)–to evaluate RNA integrity from RNA-seq data. We applied our TIN algorithm to RNA-seq data generated from 12 human glioblastoma (GBM) cell line samples, 20 human peripheral blood mononuclear cell samples (PBMC), and 120 metastatic castration resistant prostate cancer (mCRPC) samples. Our results showed that TIN metric accurately measured the mRNA integrity at transcript level, as demonstrated by high concordance with RNA fragment size that estimated from RNA-seq read pairs. We also demonstrated that the median TIN score (medTIN) across all transcripts can be an accurate and reliable measurement of RNA integrity at transcriptome (or “sample”) level. More importantly, the TIN that is computed for each transcript can be used to adjust gene expression and improve differential expression analysis by reducing the false positives ascribed to in vitro RNA degradation.P = 9.1 × 10−6; Fig. P < 2.2 × 10−16; Additional file P = 7.3 × 10−6; Fig. We used the median TIN score (medTIN) of all the transcripts to measure the overall RNA integrity of a sample. We evaluated the concordance between medTIN and the widely used RIN metric using three independent human datasets: GBM cell lines, PBMCs, and mCRPC. Each of these datasets has samples covering a broad range of RIN values. GBM samples have RIN values ranging from 2 to 10  also performed significantly better than RIN   Fig. , d. We f Fig. , dr = 0.88, P < 2.2 × 10−16; Spearman’s ρ = 0.71, P < 2.2 × 10−16) suggesting that TIN was a good metric to measure transcript integrity. Interestingly, we found the average RNA fragment size became asymptotically stable as TIN score went beyond certain threshold (i.e. saturation point). For instance, in Fig. r = 0.94, P < 2.2 × 10−16) than that of transcripts with TIN > 70 . We observed the similar trend in all GBM samples with different RIN values  size, 5′UTR (5-prime Untranslated Region) size, 3′UTR size and GC content of the transcripts to their corresponding TIN scores. We found no or very weak correlation between transcript size and TIN score in samples with high RNA integrity. However, we observed a strong negative correlation between the transcript size and TIN score for samples with lower RNA quality  values and another 10 samples with higher RIN  values  and 0.64 (P < 2.2 × 10−16) for mCRPC and GBM data, respectively  rates during gene expression analysis. We corrected this bias by normalizing a gene’s raw read count with its corresponding TIN score using a nonparametric locally weighted polynomial regression model see . As expeple Fig. , c but eple Fig. , d.Fig. P = 3.1 × 10−16) (Table P = 1.7 × 10−41)  using the unadjusted gene read count  between group A and group B. Additional 14 transcripts had identical molar concentration between the two groups. We considered the 45 transcripts as “true positives (TP)” and the 14 transcripts as “true negatives (TN)”. When TIN correction was not applied prior to gene differential expression analysis, 44 out of 45 TPs and 7 out of 14 TNs were called DEGs, resulting in a sensitivity of 0.98 and specificity of 0.5. When TIN correction was applied before gene differential expression, 40 out 45 TPs and 1 out of 14 TNs called as differentially expressed, resulting in a sensitivity of 0.89 and specificity of 0.93 Table . In esseThe qualities of commercially available reference RNA samples used in SEQC project were presumably high. Therefore, the improvement of TIN correction was unlikely to be explained by the mitigation of RNA quality differences. However, in addition to RNA degradation, RNA-seq has many other inherent biases  that could also produce non-uniform coverage, which could partially explain the improvement after TIN correction.N (0 ≤ N ≤ transcript length) nucleotides from the 3′ end, and all bases and exons beyond N length were left out. While 3TC could reduce false positives to some extent, it also reduced statistical power and increased false negatives since only a small fraction of all mapped reads were considered. For example, for 10 mCRPC samples with high RIN values, 61.8 ± 7.5 % of total reads was uniquely mapped to exon regions and can be used for gene expression analysis. However, if 3TC method only considered the 3′ 1 Kb region of transcript, only 26.9 ± 4.2 % of total reads were left to use. And when considered the 3′ 250 nucleotides (see below), only 6.6 ± 1.7 % of reads were left to use, which was equivalent to leave out 90 % usable reads  method to reduce false positives in differential expression analysis . To mitiads Fig. . Becauseads Fig. .Fig. 7CoN is not straightforward: to retain statistical power, N should be as large as possible; however, coverage bias cannot be effectively removed if N is too large. To determine the proper N size, we generated read coverage profiles for 20 mCRPC samples with all expressed transcripts aligned to the 3′ end (i.e. transcription end site)  Fig. . Based odure see . As we edure see . No prosdure see .r = 0.98, P = 1.7 × 10−8)  was slightly better than that of medTIN   performed slightly better than mRIN   Fig. , suggest−6) Fig. -c. Howev−5) Fig. -e. mRIN Although TIN and Agilent’s RIN are highly concordant, there are three major differences between them. First, RIN is a valuable approach for pre-sequencing sample screening, while TIN scores can only be calculated after RNA-seq data is produced. Second, when using RNA fragment size as a surrogate for RNA integrity to compare RIN and medTIN, we found that Agilent’s RIN only worked well for samples with relative higher RNA integrity, as evidenced by spread of the distribution of blue circles in Fig. Since RNA fragment size can be directly estimated from paired-end RNA-seq data, one might question the need for TIN. There are several drawbacks for measuring the RNA integrity using RNA fragment size alone. First, it can only be estimated from paired-end RNA-seq data. Second, RNA fragment size is influenced by other confounding factors such as the fragmentation and size selection steps during library preparation.P = 0.28, two-sided Wilcoxon rank sum test). This pathological differences between low and high RIN group also explained the detection of prostate cancer related DEGs. 2) Unlike SEQC which had spike-in transcripts with predetermined known expression values, there was no “true DEGs” available to accurately test the performance of TIN correction. However, we demonstrated through pathways analysis that TIN correction could remove ribosome genes and identify DEGs that related to prostate cancer.We chose 10 mCRPC samples with lower RIN/medTIN scores (low RIN group) and another 10 samples with higher RIN/medTIN scores (high RIN group) with the primary purpose of comparing “RNA degradation effect” on gene expression analysis. Unlike GBM and PBMC datasets that generated from cell lines, the mCRPC dataset was generated from real clinical tissues, and represented the genuine RNA degradation complexity and inter-tumor heterogeneity. However, this was a less than ideal dataset because: 1) these 20 clinical samples were not exact biological replicates and the pathology characteristics of these samples were slightly different  used oligo(dT) to deplete rRNA during RNA-seq library preparation for RNA samples collected from post-mortem tissues. Being designed to correct non-uniform coverage derived from RNA degradation as well as other biases, our TIN algorithm would be a useful approach to reanalyze or meta-analyze these RNA-seq data available from public repositories. On the other hand, even for samples with reasonable RNA integrity (eg. RIN = 8), 3′ bias still persist  is not a ideal choice for isolating mRNA from degraded samples. Other protocols such as exome capture has been demonstrated with greatly improved performance . Howeverist Fig. . And we In this study, we developed TIN as a novel metric to measure RNA integrity, and demonstrated with multiple datasets that the TIN metric is not only a reliable measurement of RNA integrity in both transcriptome and transcript level, but also a valuable metric to neutralize in vitro RNA degradation effect and improve differential gene expression analysis.http://www.ncbi.nlm.nih.gov/Traces/sra/) or Gene Expression Omnibus . Sequencing reads from all samples were independently aligned to the human reference genome (hg19/GRCh37) using Tophat (v2.0.6) software configured with default options.Human U-251 MG brain glioblastoma cell lines (GBM) [Human peripheral blood mononuclear cells (PBMC) . This daSequencing quality control consortium data set (SEQC) . The SeqHuman prostate cancer tissue samples (mCRPC). This study was approved by the Mayo Clinic Institutional Review Board and conducted in accordance with the Declaration of Helsinki. We obtained a total of 120 samples from 46 castration-resistant prostate cancer patients. Out of the collected 120 samples, 62 were blood samples, 18 were metastatic rib lesion biopsies and 40 were metastatic bone tissue biopsies. Tissues were snap frozen with liquid nitrogen and RNA was harvested using Rneasy Plus Mini Kit (Qiagen). RNA libraries were prepared according to the manufacturer’s instructions for the TruSeq RNA Sample Prep Kit v2 . Briefly, poly-A mRNA was purified from total RNA using oligo dT magnetic beads. The purified mRNA was fragmented at 95 °C for 8 min and eluted from the beads. Double stranded cDNA was made using SuperScript III reverse transcriptase, random primers  and DNA polymerase I and RNase H. The cDNA ends were repaired and an “A” base added to the 3′ ends. TruSeq paired end index DNA adaptors  with a single “T” base overhang at the 3′ end were ligated and the resulting constructs were purified using AMPure SPRI beads from Agencourt. The adapter-modified DNA fragments were enriched by 12 cycles of PCR using Illumina TruSeq PCR primers. The concentration and size distribution of the libraries was determined on an Agilent Bioanalyzer DNA 1000 chip and Qubit fluorometry . Pair-end RNA sequencing was performed using Illumina HiSeq 2500. Additional file This study used a total of four datasets including three published RNA-seq datasets. All three published datasets were obtained from the NCBI Sequence Read Archive . the relative coverage (Pi) of each nucleotide is calculated as:P1 + P2 + P3 + … + Pn = 1. The coverage evenness of a transcript can be measured by Shannon’s entropy:We assumed that a systematic in vitro degradation of a transcript would result in areas with shallow read depths. Hence we designed the TIN metric to capture the uniformity of coverage for a given transcript. Given a transcript of Pi = 0), the entropy H = Pi × log Pi = 0. H is maximized if the coverage is perfectly uniform (i.e. P1 = P2 = P3 = … = Pn = 1/n) across the entire length of the transcript. For computational efficiency, we did not use the entire transcripts to calculate the H. Instead, we selected k equally spaced positions across the transcript from 5′ end (transcription start site) to 3′ end (transcription end site). k is an adjustable parameter in our TIN program. To distinguish different transcripts transcribed from the same gene locus, all the exon-exon joint positions (j) were also taken into calculation:If a particular nucleotide position has no read coverage  as suggested by Jost et al. [U (0 ≤ U ≤ (k + j)) is technically and biologically meaningful since it is equivalent to the number of nucleotides with uniform read coverage. Accordingly, the TIN score is the percentage of transcript that has uniform read coverage:Although Shannon’s  compare . We addrt et al. :\documenRNA fragment size is the natural measure of the in vitro RNA degradation. Since read pairs were sequenced from both ends of RNA  fragments, the size of each RNA fragment in the sequencing library can be directly estimated from the distance between read pairs after mapping them to the reference genome. We used uniquely mapped high quality (mapq ≥ 30) read pairs to estimate the RNA fragment size. When a read pair was mapped to the same exon, the fragment size is defined as the genomic distance covered by the two reads (i.e. distance between the “start” of the first read and “end” of the second read). When a read pair was mapped to different exons of the same gene, introns lying between the two reads were subtracted from the genomic distance covered by the read pair. We considered the longest RNA isoform when multiple splicing isoforms  exist. We removed transcripts with <30 mapped read-pairs to improve the reliability of library fragment size estimation. The “sample level” RNA fragment size was estimated by taking the average of fragment sizes calculated from all read pairs that uniquely mapped to the reference genome. Similarly, the “transcript level” RNA fragment size was estimated from all read pairs that specifically mapped to a transcript.yi  were regressed to TIN score ti using a locally weighted polynomial regression method. For this, we utilized the logarithmic scale of the gene-level counts because it is more robust to outliers that can bias the fit. The R function loess was used for the following function.For samples with poor RNA quality, both raw read counts and normalized read counts (FPKMs) were positively correlated with TIN scores (see Results). This type of in vitro degradation bias would tamper with gene expression analysis and produce significant numbers of false positives. To correct this bias, we recalibrated the gene level read count using the corresponding TIN score within each sample. In brief, gene level raw read counts yi′ denote the normalized read count of gene i and ŷi denote the fitted value.Where We applied the same procedure for mCRPC dataset , GBM dataset (compared three samples with RIN = 10 to three samples with RIN = 4) and SEQC dataset (compared group A to group B). This method utilized edgeR (version 3.6.8) to perform differential expression analysis . The sofhttp://www.ncbi.nlm.nih.gov/geo/) with accession number: GSE70285 (reviewers’ link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=knchmaksrfqfnov&acc=GSE70285). Python Code to calculate TIN score (tin.py) is freely available from RSeQC package (www.http://rseqc.sourceforge.net) [Twenty RNA-seq data generated from metastatic prostate cancer tissues were submitted to Gene Expression Omnibus (rge.net) .


Although a key determinant of hepatic recovery after injury is active liver regeneration, the ability to detect ongoing regeneration is lacking. The restoration of liver mass after hepatectomy involves systemic changes with coordinated changes in gene expression guiding regenerative responses, activation of progenitor cells, and proliferation of quiescent hepatocytes. We postulated that these responses involve intercellular communication involving extracellular RNA and that these could represent biomarkers of active regenerative responses.RNA sequencing was performed to identify temporal changes in serum extracellular non-coding RNA after partial hepatectomy in C57BL/6 male mice. Tissue expression of selected RNA was performed by microarray analysis and validated using qRT-PCR. Digital PCR was used to detect and quantify serum expression of selected RNA.A peak increase in extracellular RNA content occurred six hours after hepatectomy. RNA sequencing identified alterations in several small non-coding RNA including known and novel microRNAs, snoRNAs, tRNA, antisense and repeat elements after partial hepatectomy. Combinatorial effects and network analyses identified signal regulation, protein complex assembly, and signal transduction as the most common biological processes targeted by miRNA that altered. miR-1A and miR-181 were most significantly altered microRNA in both serum and in hepatic tissues, and their presence in serum was quantitated using digital PCR.Extracellular RNA selectively enriched during acute regeneration can be detected within serum and represent biomarkers of ongoing liver regeneration in mice. The ability to detect ongoing active regeneration would improve the assessment of hepatic recovery from liver injury. Although the liver has the capability to regenerate following injury, the mechanisms of liver regeneration remain incompletely understood. Liver regeneration involves activation of progenitor cell populations recapitulating signaling mechanisms involved in liver development. These reMany cells, including progenitor and differentiated human liver cells, can release extracellular RNA (exRNA) enclosed within extracellular vesicles (EVs) into their local environment. The release of exRNA occurs in a selective manner because there are significant differences between the RNA content of the vesicles and that of their cells of origin. We and others have identified that the majority of the RNA content found in liver cell-derived EVs comprises small RNA (< 200 bp) and ncRNA. The tranThe exRNA that are released into the circulation during hepatic regeneration also have the potential to serve as specific biomarkers of the hepatic regenerative response. Their presence within circulating EV or their association with proteins or lipoproteins may protect these RNA from degradation. Recent studies have shown that EV can be detected in the circulation following liver injury. MoreoverTwelve-week-old C57BL/6 mice (Charles River Laboratory) were subjected to a partial hepatectomy during which the left and medial hepatic lobes were ligated and excised, resulting in the removal of 65–70%  of the liver. For detection of circulating exRNA, serum samples were obtained by cardiac puncture from four mice each at 1, 6 and 24 hours after partial hepatectomy. The entire surgical process was approved by the Charles River Institutional Animal Care and Use Committee. Details of methods to minimize potential suffering, including surgical anesthesia and postsurgical pain relief and supportive care, can be requested from Charles River Laboratories . RNA was isolated using ExoQuick . The exRNA content was purified using SeraMir kits  and quantified using a Nanodrop ND-1000 . For tissue RNA studies, mice were euthanized, and the residual liver tissue was harvested at 15, 45, 90 and 240 minutes posthepatectomy; tissue samples were obtained from five animals at each time point. A half of each liver was stored in RNA-later solution , and the rest was either lysed for RNA isolation or was immediately frozen on dry ice and subsequently stored at -80°C. Total RNA was isolated with Trizol  according to the manufacturer's instructions. We considered changes occurring within the first 6 hours as indicating early stages of hepatic regeneration after partial hepatectomy.Purified exRNA was made into Illumina Tru-Seq RNA-Sequencing libraries, and samples were indexed using the NEBNext Small RNA Library prep kit . Libraries were amplified for 12–18 cycles according to the manufacturer’s instructions. Amplified libraries were sized-fractionated using Sage Bioscience Pippin prep station on 2% agarose gels (Sage Bio cat # SDF2010) with a collection range of 135 bp—200 bp. The size and concentration of the purified libraries were analyzed using an Agilent 2100 Bioanalyzer high sensitivity DNA chip. Libraries were pooled in equal molar amounts for multiplex sequencing on an Illumina MiSeq sequencer.Sequencing analysis was conducted using the Exosome/Small RNA-seq Analysis Kit 1.0 . Raw sequencing reads with a length of 75 bp were quality checked for potential sequencing issues and contaminants using FastQC . Adapter sequences, primers, poly-Ns, and bases with quality scores below 28 were trimmed using fastq-mcf of ea-utils and PRINSEQ., 13 ReadFive micrograms of total RNA obtained from livers at different time-points up to 240 minutes after partial hepatectomy were hybridized onto custom miRNA microarray chips (OSU_CCC version 3.0), containing approximately 1100 miRNA probes, including 345 human and 249 mouse miRNA genes as well as predicted and ultraconserved RNA genes, with each gene spotted in duplicates. The miRNA microarray is based on a one-channel system. RNA labeling and hybridization on miRNA microarray chips were completed as described.[Total RNA was isolated from frozen liver specimens using Trizol . Expression levels of specific mature miRNAs were confirmed by real-time PCR analysis using a TaqMan Human MicroRNA Assay kit .Digital PCR was performed using the QX100 system . cDNA was transcribed from RNA treated with RNase-free DNase I  and an RNase inhibitor (10U/μl)  using iScript cDNA synthesis kit . Reaction mixtures were prepared using 10 μl ddPCR 2x Master Mix , 1 μl 20x Primer & TaqMan Probe Mix , 5 μl nuclease free water, and 4 μl reverse-transcribed product. 1 nL reaction droplets were generated using a QX100 Droplet generator  and a droplet generator DG8 cartridge  containing 20 μl of reaction mixture and 70 μl of droplet generation oil  per well. Thirty-five microliters of the generated droplets were transferred to 96-well PCR plates and amplified using a thermal cycler as follows: initial denaturation at 95°C for 10 minutes, followed by 40 cycles of 94°C for 30 seconds and 60°C for 1 minute, and finally 98°C for 10 minutes. The fluorescence intensity of each droplet was then measured using the QX100 droplet reader . Data was analyzed using the QuantaSoft software  with thresholds based on fluorescence of negative controls.Data were expressed as the mean and standard error from four biological replicates for RNA sequencing and digital PCR assays and from three replicates for microarray analysis at each time point. Comparisons between groups were performed using the two-tailed Student’s t test. Results were considered to be statistically significant when P < 0.05.All authors had access to the study data and had reviewed and approved the final manuscriptThere was a transient increase in circulating exRNA following partial hepatectomy , with a miRNAs have been the most extensively studied non-coding RNAs, and alterations in miRNA expression have been reported following partial hepatectomy., 7 FirstWe postulated that changes in circulating exRNAs would reflect alterations in hepatic RNA during hepatic regeneration. In this model, portions of the liver that undergo injury are completely removed, and thus subsequent changes are unlikely to reflect hepatic injury. However, circulating exRNA could also reflect non-regeneration related changes, such as non-specific release from other injured cells or local or systemic changes related to anaesthesia or the surgical procedure. To further determine the relevance of changes in circulating exRNA, we examined tissue expression of miRNA at very early stages of regeneration after partial hepatectomy. Changes in miRNA expression have been reported to occur during regeneration after partial hepatectomy, but most studies have described changes that occur several hours after hepatectomy. Although the expression of most miRNAs did not change, we observed early alterations in hepatic expression of ~10% of miRNA by >5 fold (P < 0.05) after partial hepatectomy. The expression levels of seven selected miRNAs from five different time points were validated by RT-PCR, and in all cases, the expression levels observed paralleled the data obtained from the microarray analysis (data not shown). To detect the earliest changes in tissue expression, we focused our efforts on those miRNA that had deregulated expression within an hour after partial hepatectomy. Sixteen of the 496 miRNA identified had expression that was a log2-fold increase of 1.2 or more at 90 minutes after partial hepatectomy. Of these 16, three were also increased in livers collected after 240 minutes, indicating a sustained alteration in tissue expression. A comparison of miRNA that were increased within hepatic tissues as well as elevated in the circulation following partial hepatectomy revealed that the most prominent and sustained changes occurred for miRNA-1A and miRNA-181a-5p-A . Both ofFor validation, the expression of miR-1A and miR-181 was examined in exRNA obtained from serum samples obtained from an independent group of mice undergoing partial hepatectomy. The expression of these two miRNA was barely detectable by qRT-PCR, with cycle threshold (Ct) values > 40 for baseline and greater than 35 at the assayed time points after partial hepatectomy. To detect and quantitatively assay these circulating RNA transcripts with adequate sensitivity, we used a digital PCR assay. In our dNon-coding RNA other than known miRNA could have potential value as markers. We have shown that lncRNA can be detected within EV released from both malignant and non-malignant hepatocytes.–28 ThereThe discovery approach for circulating extracellular miRNA is based on the analysis of RNA sequencing data and could be dependent on the choice of bioinformatics analytical pipelines. Thus, we directly compared different analytical strategies using data from exRNA samples obtained at baseline, one hour, and 24 hours after hepatectomy. All three samples had sufficient coverage of the miRNAs for comparison of the analytic pipelines. We compared the analyses performed by Maverix Biomics , a Mayo-developed miRNA analytic pipeline (CAP-miRSeq), and the Genboree workbench NIH Extracellular RNA Communications Consortium small RNA pipeline (exceRpt) . The MavBiochemical markers of hepatic function or injury currently used in clinical practice do not provide information on the presence of active regeneration. The availability of such markers would be helpful to guide management when the amount of functional liver is reduced after acute liver injury and necrosis or after partial liver resection. By using an unbiased and comprehensive RNA sequencing-based profiling and data-analysis strategy that included isolation of extracellular RNA, library preparation, RNA sequencing, and RNA annotation, we identified temporal alterations in diverse RNA species within the circulation after partial hepatectomies in C57BL/6 mice. These circulating exRNA may provide a powerful tool for the non-invasive assessment of ongoing liver regeneration. We further (i) identified ncRNA that were both increased in tissue and could be detected in the circulation within extracellular vesicles, (ii) detected novel circulating ncRNA that were increased in the circulation following partial hepatectomy, and (iii) report the utility of a quantitative digital PCR assay with adequate sensitivity for the detection of extracellular RNA that can be used to examine temporal changes in circulating exRNA biomarkers of the regenerative response in the liver.In this study, selected circulating exRNA that were specifically increased following partial hepatectomy were correlated with temporal data on changes in expression of these RNA within hepatic tissues. An increase in exRNA, such as miRNA, following partial hepatectomy supports their involvement in biological responses. MiRNA expression is altered during the priming phase of liver regeneration, and several genes and proteins are known to have altered expression during this phase. We identified alterations in the hepatic expression of 30 miRNA genes (P < 0.05) within the first 90 minutes after hepatectomy. The alterations in expression of virtually all of these miRNA were transient, consistent with a high degree of regulation and temporal trends in the expression of several factors, such as priming factors at the onset of the regenerative process. The very rapid alterations in circulating extracellular miRNA observed after partial hepatectomy supports their involvement in systemic responses during this early priming phase of the regenerative process. In addition to their potential role as circulating biomarkers of the regenerative response, future studies could examine the mechanistic role of these RNA in modulating gene expression and hepatocyte proliferation during hepatic regeneration, as well as the regulation of their production by progenitor cell populations within the liver.This analysis presumes that the source of circulating exRNA is remnant hepatic tissue and that enhanced release occurs as a consequence of increased hepatic expression of RNA. Interestingly, changes in the expression of mature miRNA were noted as early as 15 minutes posthepatectomy, with a significant decrease in expression of 23 miRNA by more than 3-fold (P < 0.05). Of note, no appreciable changes were noted in expression levels of the corresponding precursor miRNA, suggesting that the regulation of mature miRNA expression does not involve changes in miRNA transcription or processing from precursor forms. Thus, an increase in exRNA release could involve the selective release of pre-formed RNA or be the result of release by non-hepatic tissues in the absence of increased hepatic expression. Although not evaluated in the present study, disconcordant exRNA candidates for which elevated hepatic expression was not identified may have biological significance or clinical utility.In addition to known miRNAs, we have identified several other types of ncRNA as candidate markers of ongoing regeneration, such as the novel miRNA and several lncRNA. The biological significance of several of these is unknown. Although the role and involvement of lncRNA in hepatic neoplasia has been extensively explored, the contribution of these RNA to hepatic regeneration or to other physiological or pathophysiological responses in the liver is not well understood. Recent studies have implicated specific lncRNA in hepatic regeneration, and further studies are warranted to systematically examine the biological and functional roles of these candidates. Such studies may offer insights into their contribution to regenerative processes following hepatic resection or small-for-size partial liver transplants.S1 FigAn overview of two different bioinformatics small RNA sequencing analytic pipelines, CAP-miRSeq (19) and exceRpt (PPTX)Click here for additional data file.S2 FigAnalyses were performed on normalized read counts for miRNA using the exceRpt pipeline (GENBOREE) and the CAP-miRSeq pipeline (Mayo).(PPTX)Click here for additional data file.S3 FigA. Analyses were performed on normalized read counts for all miRNA using the exceRpt pipeline (GENBOREE) and the CAP-miRSeq pipeline (Mayo). B. Analyses was performed for miRNAs with 5 or more raw read counts in at least 1 sample.(PPTX)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.


The human microbiome plays a significant role in maintaining normal physiology. Changes in its composition have been associated with bowel disease, metabolic disorders and atherosclerosis. Sequences of microbial origin have been observed within small RNA sequencing data obtained from blood samples. The aim of this study was to characterise the microbiome from which these sequences are derived.Proteobacteria, whilst for 5 of 6 individuals over 90% of the more abundant fungal reads were from the phylum Ascomycota; of these over 90% were from the order Hypocreales. Many contigs were from plants, presumably of dietary origin. In addition, extremely abundant small RNAs derived from human Y RNAs were detected.Abundant non-human small RNA sequences were identified in plasma and plasma exosomal samples. Assembly of these short sequences into longer contigs was the pivotal novel step in ascertaining their origin by BLAST searches. Most reads mapped to rRNA sequences. The taxonomic profiles of the microbes detected were very consistent between individuals but distinct from microbiomes reported at other sites. The majority of bacterial reads were from the phylum A characteristic profile of a subset of the human microbiome can be obtained by sequencing small RNAs present in the blood. The source and functions of these molecules remain to be determined, but the specific profiles are likely to reflect health status. The potential to provide biomarkers of diet and for the diagnosis and prognosis of human disease is immense.The online version of this article (doi:10.1186/1471-2164-15-933) contains supplementary material, which is available to authorized users. It has been estimated that there are at least ten times more microbial cells associated with our bodies than there are human cells, 2. ReceThe microbiome has a significant influence upon health. The majority of microbes are found in the gut and have essential roles in normal human physiology and immune responses, 8. The et al. have documented the existence of RNA from bacteria and fungi in plasma and suggested that they may serve as signaling molecules or indicators of human health[Most metagenomic studies to date have involved isolation of DNA from external body sites or from the respiratory or digestive tracts, with fecal samples being the most commonly used source for investigation of the gut microbiome. Certain small RNAs are stable in the blood and in particular microRNAs have been widely studied as potential predictors of disease, 24. Hown health. The oriHypocreales. This work has further demonstrated the feasibility of generating a microbiome profile from small RNAs in plasma[The aim of this study was to construct a profile of the microbiome from which the exogenous small RNAs present in human plasma are derived. The merging of overlapping sequences to generate contigs facilitated identification of the origin of the short RNA sequences. The microbiome profiles generated were consistent across 6 individuals (3 from this study and 3 from publicly available data). In addn plasma. The easRNA was extracted from three plasma samples and small RNA libraries prepared using an Illumina kit. Each library was sequenced on a MiSeq (Illumina). The unique reads and raw sequencing data have been deposited in Gene Expression Omnibus (GEO), accession number GSE52981. Sequencing data for three plasma exosomal small RNA libraries prepared with a kit from Bioo Scientific were downloaded from GEO. For oneThe proportions of reads annotated to human genes are illustrated in Figure −3) in a megablast search of the NCBI non-redundant database were assigned the identity of the top hit . However, in most instances the sequences were sufficiently divergent from human rRNA to support the notion that they are derived from dietary plant material  were analysed with the MEGAN taxonomic classification tool, 33. The Figure . The relenenatum. AlthougHypocreales are extremely similar to the published sequences. For example, contig 44 has a similarity of 98.6% identity over 1162 nucleotides to Hypocreales Cordycipitaceae Cordyceps gunnii 28S ribosomal RNA . Whilst members of this order have occasionally been reported as opportune pathogens in immunocompromised patients[Hypocrea jecorina is a widely used source of cellulases[The taxonomic breakdown of the originating organisms achieved with our contig-based strategy is in broad agreement with that reported by Wang patients, they arpatients, while Hllulases. It is rActinobacteria (and to a lesser degree Firmicutes and Proteobacteria)[Malassezia of the Basidiomycota phylum[Actinobacteria comprised an average of 1.5% percent of bacterial reads in 5 of 6 samples and only 17.6% in the remaining sample. Firmicutes averaged 1% percent across all samples, although Proteobacteria were the most abundant (50%). With regard to fungi, only 3 contigs (91 reads) were assigned to Malassezia. It seems unlikely that contamination during sample processing could result in such similar microbiome profiles in three independent plasma small RNA datasets and across multiple library preparation methods.The composition of both the fungal and bacterial plasma microbiome detected suggests that the sequences do not result from contamination from the skin microbiome during collection of blood samples. Whilst the human skin microbiome varies widely, it is dominated by the bacterial phylum acteria), 5 and ta phylum. Reads fBacteroidetes and Firmicutes[Ascomycota[Hypocreales. Perhaps the niche occupied by these species within the gut predisposes them to uptake into the circulation. The respiratory tract is another potential source and indeed Fusarium is one of the four most common pathogenic fungi detected, along with Candida, Aspergillus and Cryptococcus[Small RNA sequences have been reported to enter the circulation from the gastrointestinal tract and pharrmicutes, 5, and comycota. It is ttococcus. Althougtococcus, 50, mantococcus, 52 and tococcus. Indeed tococcus. DiffereIn addition to RNAs of microbial origin, some sequences potentially derived from foodstuffs were detected. Notably the greatest proportion of reads matching plant sequences were found in sample 3, which was obtained from the one individual who reported following a vegetarian diet. Although it has been reported that plant microRNAs (xenomiRs) are not reliably detected in plasma after ingestion, 55 the Great care must be taken when comparing between studies because differences in sample collection and library preparation can have profound effects upon the small RNA profiles observed and the proportion of reads mapping to Y RNAs or exogenous small RNAs. Nonetheless, the detection of these same small RNAs in diverse studies confirms that they are a common feature of the circulation.Hypocreales. This raises questions about how these exogenous RNAs reach the circulation, whether they are functional and why specific fungi are so highly represented. This work has demonstrated the feasibility of determining the microbiome that contributes small RNAs to the blood. The profile of microbial sequences detected is almost certainly influenced by the composition of the wider microbiome, particularly in the gut. Given the integral role of the human microbiome in normal health and pathology, it seems likely that knowledge of the plasma microbiome will be soon prove to be of clinical importance.Abundant fragments derived from the non-coding hY4 RNA, but of unknown function, have been detected in human plasma. RNAs from a diverse range of microbes are also present, but the majority of fungal sequences are from species in the Order g and subsequently at 10,000 g for 10 minutes prior to RNA extraction using a miRNeasy kit . RNA purity and quantity were determined using a Nanodrop spectrophotometer (Thermo Scientific) and Qubit fluorimeter (Life Technologies). RNA integrity was assessed using RNA 2000 and small RNA chips on a Bioanalyzer (Agilent).Three healthy individuals aged 20–40 years were recruited from Belfast, N. Ireland, UK: male, Caucasian (sample 1); female, Caucasian (sample 2); and male, Indian (sample 3). All participants completed a food-frequency questionnaire which included questions on any special dietary requirements. A blood sample was taken in EDTA-treated tubes and plasma was separated immediately by centrifugation for 10 minutes at 1,000 This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human participants/patients were approved by the Research Ethics Committee of the School of Medicine and Dentistry, Queen’s University Belfast (Ref:11/05v3). Written informed consent was obtained from all participants.Small RNA libraries were prepared using a Truseq small RNA sample prep kit (Illumina) following the manufacturer’s protocol. This included size selection using a 6% PAGE Gel; the region between the custom Illumina markers was excised, corresponding to insert sizes of approximately 20–35 nucleotides. Cluster generation and sequencing with 40 nucleotide reads on a MiSeq was performed at the Trinity Genome Sequencing Laboratory, Dublin.Sequencing data were analyzed using Genomics workbench software v5.5.1 . After removal of adapter sequences, reads >15 bp and with at least 2 copies were aligned, allowing 2 mismatches, to miRBase (Release 19), a database of human non-coding RNA downloaded from Ensembl using Biomart and the Y-RNA custom small RNA Taqman assays (Life Technologies) were designed to target the following sequences: HY4_5p; GGCUGGUCCGAUGGUAGUGGGUUAUCAGAACU and HY4_3p; CCCCCCACUGCUAAAUUUGACUGGCUU . Taqman reverse transcription and PCR were performed according to the manufacturer’s instructions on a LightCycler480 platform (Roche).E. coli Poly(A) Polymerase I (Ambion) and reverse transcribed using Super Script III reverse transcriptase (Life Technologies) and an oligo-dt adaptor: GCGAGCACAGAATTAATACGACTCACTATAGGTTTTTTTTTTTTVN. PCR was performed using the common reverse primer GCGAGCACAGAATTAATACGAC and either an HY4_5p primer: GGCTGGTCCGATGGTAGT or HY4_3p primer: CCCCCCACTGCTAAAATTTGA. 35 cycles of PCR were performed with the following conditions 94°C 30 sec; 56°C 30 sec; 72°C 1 minute using Hotstar Taq DNA polymerase (Qiagen).For detection of Y-RNA fragments, RNA was polyadenylated using https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE52981) and the publicly available plasma small RNA sequencing data[The data sets supporting the results of this article are available in the Gene Expression Omnibus (GEO) repository. The seqing data analysedExcel spreadsheet. Number of reads from each sample annotated by gene type or phylogenetic category (XLSX 19 KB)Additional file 1:et al.[et al.[et al.[Additional file 2: Figure S1: Distribution of read lengths in a range of sequencing libraries prepared from blood. The percentages of reads of each length are shown for libraries prepared from plasma, exosomes isolated from plasma or whole blood, including cells. Both the source material and library preparation protocol (eg size selection) influence the insert sizes observed. References: Huang et al.; Wang et[et al.; Leiding[et al.. Additional file 3:Fusarium venenatum. (PDF 283 KB)Additional file 4: Figure S2: Multiple alignment of Contig_1808 with fungal rRNAs. Contig 1808 is aligned with the five most similar sequences in the NCBI nr database and the rRNA sequence of et al.[Additional file 5: Figure S3: Analysis of plasma sequence data from Wang et al.. (a) Taxet al. with conAdditional file 6: Figure S4: Phylogenetic profiles predicted from individual reads or contigs. A random subset of the reads that were unannotated to human databases was generated from Sample 3A. These were input either directly or after assembly into contigs to BLAST searches of the nt database. Similarities with fungal sequences are a key feature detected by both approaches. Using this subset of sequences no contigs with potential bacterial origin were detected, probably reflecting the relatively low abundance of putative bacterial reads in this sample in comparison to fungal reads (see Figure


Neolamarckia cadamba contains large quantities of other components, particularly RNA-binding alkaloids, which makes the isolation even more challenging. Here, we describe a concise and efficient RNA isolation method that combines the cetyltrimethyl ammonium bromide (CTAB) and Plant RNA Kit (Omega) protocols. Gel electrophoresis showed that RNA extracted from all tissues, using this protocol, was of good integrity and without DNA contamination. Furthermore, the isolated RNA was of high purity, with an A260/A280 ratio of 2.1 and an A260/A230 ratio of >2.0. The isolated RNA was also suitable for downstream applications, such as reverse transcription-polymerase chain reaction (RT-PCR) and quantitative RT-PCR (RT-qPCR). The RNA isolation method was also efficient for recalcitrant plant tissues.Plant tissues contain abundant polysaccharides, phenolic compounds and other metabolites, which makes it difficult to isolate high-quality RNA from them. In addition,  This is a fast-growing evergreen broadleaf tree species distributed in tropical and southern Asia.[N. cadamba, particularly alkaloids,[ern Asia. It was ulkaloids, but few N. cadamba contains abundant alkaloids that bind RNA, increasing the difficulty of isolation.[N. cadamba tissues (data not shown), may be because the efficiency of the spin columns used in these kits decreases significantly in the presence of alkaloid compounds.[N. cadamba.The isolation of high-quality RNA lacking polysaccharides, proteins, phenolic compounds, genomic DNA or secondary metabolites is crucial for the multiple techniques used to investigate gene expression patterns and functions during plant growth and development. Such techniques are reverse transcription-polymerase chain reaction (RT-PCR), quantitative RT-PCR (RT-qPCR), complementary DNA (cDNA) library construction, Northern blotting and RNA sequencing. Phenolic compounds are oxidized to form quinones, which bind irreversibly to nucleic acids and proteins. Polysaccsolation. Currentlompounds. Ouyang eompounds. isolatedN. cadamba tissues, according to these protocols, smeared severely (data not shown). Here, we combined a modified CTAB lysis buffer and purification on RNA mini columns (Omega), which not only reduced the required time but also yielded large quantities of high-quality total RNA.RNA has been successfully extracted from various plant species, rich in phenolic compounds and polysaccharides, using the cetyltrimethyl ammonium bromide (CTAB) protocol, but thisFour young tissues, buds, leaves, cambium scrapings and roots, were collected as described previously. Flowers 2O.Frozen tissue was ground to a fine powder in liquid nitrogen, using a mortar and pestle. Then, 100 mg samples of the powder were transferred into individual 1.5 mL RNase-free tubes containing 600 μL of prewarmed extraction buffer at 60 °C. The extraction buffer contained the following: 2% CTAB, 2% polyvinylpyrrolidone (PVP) K-40, 100 mmol/L Tris–HCl (pH 8.0), 25 mmol/L ethylenediaminetetraacetic acid , 2.0 mol/L NaCl, 2 g/L spermidine and 2% β-mercaptoethanol (added immediately before use). Lysis buffer without spermidine or β-mercaptoethanol was treated with 0.1% diethyl pyrocarbonate (DEPC) and autoclaved. 2 g/L spermidine was added and the mixture was stored at room temperature. The extracts were mixed by vortexing and incubated at 60 °C in a water bath for 10 min with vigorous shaking for several times. An equal volume of chloroform/isoamyl alcohol (24:1) was added to the homogenate and was mixed completely by vortexing. The mixture was centrifuged at 12,000 r/min for 10 min at 4 °C, except for bud samples, which were centrifuged for 20 min. The supernatant was transferred to a new tube and the above step was repeated. The supernatant was then transferred to a new tube containing an equal volume of RB buffer from the Plant RNA Kit (Omega); an equal volume of ethanol was then added to each tube. The mixture was blended by inverting the tube and was filtered through an RNA mini column (Omega), according to the manufacturer's protocol. The final steps were according to this protocol and RNA was eluted with 40 μL of DEPC HA260/A280 and A260/A230 ratios to evaluate the levels of protein and polysaccharide/phenolic compound contamination, respectively. The integrity of total RNA was verified by resolving a ∼1 μg RNA sample on a 1.2% (w/v) formaldehyde denaturing agarose gel with DNA marker DL2000 as control and 6× loading buffer  as staining buffer. Further analysis was done in an Agilent 2100 Bioanalyzer to calculate RIN (RNA integrity number) values.The RNA concentration was determined by measuring the absorbance at 230, 260 and 280 nm, using a spectrophotometer . The purity of the RNA was estimated by calculating the Total RNA (0.5 μg) was reverse-transcribed to first-strand cDNA, according to the manufacturer's instructions in the PrimeScript™ RT Master Mix kit . According to Xiao et al., for furtN. cadamba. Other methods were also ineffective.[The RNA isolation protocols of currently commercially available kits and reagents are simple, rapid, non-toxic and give good yields of high-quality RNA from suitable plant tissues. However, good yields cannot be obtained, or RNA cannot be extracted from recalcitrant plant tissues, using these kits or reagents. Several commercially available kits and reagents, such as Promega, Omega and TRIzol, failed to yield good-quality RNA isolated from leaves, buds, flowers and fruits of ffective.N. cadamba tissues in 2 h.The CTAB protocol is used widely for extraction of RNA from plant tissues but is tedious and time consuming. In the present study, we introduced several changes to the original CTAB protocol with inclusion of OMEGA kit-based steps; this method facilitated the isolation of large quantities of high-quality RNA from various N. cadamba. Pure RNA has an A260/A280 ratio of 1.8–2.2 and an A260/A230 ratio of >2.0.[A260/A230 ratio ranged from 2.06 to 2.25, indicating that the RNA was of high purity and free of polyphenol and polysaccharide contamination. Similarly, the A260/A280 ratio ranged from 2.13 to 2.19, which also indicated lack of protein contamination  to denature RNases and other contaminating proteins released during tissue disruption and homogenization.,23–25 ByA260/A280 ≥ 1.8 , as shown in The RNA extracted from N. cadamba tissues. This type of RNA cannot be isolated by other methods due to the presence of abundant alkaloids, high RNase activity and polysaccharides, polyphenols and secondary metabolites. The method is also cost effective, time saving and universal. This simple protocol can be used as an alternative method for RNA isolation from recalcitrant plant tissues.Our results demonstrated that, using a modified CTAB protocol, a large quantity of high-quality total RNA can be isolated from various http://dx.doi.org/10.1080/13102818.2014.981086.Supplemental data for this article can be accessed at


The acquisition of an appropriate set of chemical modifications is required in order to establish correct structure of RNA molecules, and essential for their function. Modification of RNA bases affects RNA maturation, RNA processing, RNA quality control, and protein translation. Some RNA modifications are directly involved in the regulation of these processes. RNA epigenetics is emerging as a mechanism to achieve dynamic regulation of RNA function. Other modifications may prevent or be a signal for degradation. All types of RNA species are subject to processing or degradation, and numerous cellular mechanisms are involved. Unexpectedly, several studies during the last decade have established a connection between DNA and RNA surveillance mechanisms in eukaryotes. Several proteins that respond to DNA damage, either to process or to signal the presence of damaged DNA, have been shown to participate in RNA quality control, turnover or processing. Some enzymes that repair DNA damage may also process modified RNA substrates. In this review, we give an overview of the DNA repair proteins that function in RNA metabolism. We also discuss the roles of two base excision repair enzymes, SMUG1 and APE1, in RNA quality control. Some of these modified bases have well known regulatory functions; pseudouridine is, for example, the most common post-transcriptionally introduced RNA modification, and is particularly important for structure and function of ribosomal RNA (rRNA) and small nuclear RNA (snRNA) [1A) and 3-methylcytidine (m3C) raised the exciting hypothesis that RNA modifications may be enzymatically repaired or reversed in mammalian cells [Cellular RNA is susceptible to chemical modification and so far, 66 different modifications have been identified in eukaryotes [The RNA Modification Database  . Pseudou (snRNA) . Moreove (snRNA) , which g (snRNA) . Interes (snRNA) , but inoan cells . Regulatan cells . Apart fEukaryotes possess numerous mechanisms that process or eliminate specific RNA molecules including rRNAs, tRNAs and mRNAs Fig. . SuperfiThe exosome degrades RNA to single-nucleotide monophosphates and a residual four-nucleotide fragment, but it can only degrade RNA substrates that enter the core with their 3′ ends . This meCytoplasmic mRNAs subject to degradation are either deadenylated prior to 3′ to 5′ degradation by the cytoplasmic exosome , or decaNuclear mRNAs may also be degraded when processing or export is altered. In these cases, mRNAs are degraded by the nuclear exosome , or, at The functional noncoding rRNAs and tRNAs may also be degraded both in the cytoplasm and the nucleus. Upon translation failure, cytoplasmic rRNAs are degraded by a process referred to as nonfunctional ribosomal decay (NRD) . IntroduSaccharomyces cerevisiae; in the absence of pre-rRNA dimethylation, for example, Dim1p blocks pre-rRNA processing steps required for maturation of 18S rRNA [In the nucleus, tRNAs and rRNAs having maturation defects can be polyadenylated by the Trf4-Air2-Mtr4 polyadenylation (TRAMP) complex before degradation by the nuclear exosome. The TRAMP complex adds short poly(A) tails to aberrant transcripts, forming a favourable substrate for the exosome and thus facilitating RNA digestion by the exosome . In addi18S rRNA .Degradation of mRNAs plays an important role in regulating the level of mRNA transcripts. This is the case of the c-myc mRNA, which is degraded via two distinct pathways. One pathway comprises deadenylation followed by 3′–5′ exonucleolytic degradation . AnotherEndoribonucleolytic RNA degradation may be used as a strategy for cells to respond quickly to external stimuli. For example, tRNAs and rRNAs have been shown to be cleaved by the yeast endonuclease Rny1 upon oxidative stress . This doAs part of the RNA maturation process, specific cleavages and modifications of RNA molecules are essential for producing stable mRNAs and functional non-coding RNAs. Splicing of tRNAs involves the precise removal of intronic sequences, which requires two incisions of the pre-tRNA at the exon–intron borders. The cleavage reactions are catalysed by a tRNA splicing endonuclease that recognises the structure of the pre-tRNA and yields 2′–3′-cyclic phosphate and 5′-OH termini in the cleaved tRNA and the excised linear intron . In eukaSaccharomyces cerevisiae with impact on pre-mRNA splicing [5U) and 5-methoxycarbonylmethyl-2-thiouridine (mcm5s2U), classified as key determinants of translational fidelity [5U), or derivatives thereof, in the wobble position, which are believed to restrict wobbling and improve translational efficiency. Recently, the ALKBH8 member of the AlkB protein family was reported to methylate 5-carboxymethyluridine (cm5U) and 5-carboxymethyl-2-thiouridine (cm5s2U) and, thus, participate in the maturation of the tRNASec, tRNAGlu and tRNAArg [Gly, further expanding the function of the ALKBH oxygenases beyond nucleic acid repair [Pre-RNAs are not only cleaved to generate mature RNA molecules, but are also modified at specific bases. Pseudouridylation has thus far been considered to provide constitutive modifications. Recently, it was demonstrated that pseudouridylation in U2 snRNA can be conditionally induced in splicing . This infidelity . In mamm tRNAArg , 48. It  tRNAArg . An addid repair .N6-methyladenosine (m6A), which is one of the most common modifications in RNA. It is introduced enzymatically by an unidentified methyltransferase complex containing the subunit methyltransferase-like 3 (METTL3) [6A in mRNA [Alkbh5-deficient male mice have increased m6A in mRNA and are characterised by impaired fertility [6A modification has fundamental and broad functions in mammalian cells. RNA epigenetics may thus represent an example of how DNA repair enzymes, or DNA repair-like enzymes, may contribute important functions beyond the regulation of RNA metabolism.The concept of RNA epigenetics emerged with the discovery that post-transcriptional RNA modifications can be dynamic and might have regulatory roles analogous to those of epigenetic DNA modifications . One exa(METTL3) , and era(METTL3) . FTO per(METTL3) . Similar in mRNA . This de in mRNA . Moreoveertility , demonstArg [RNA editing changes the coding properties of an RNA molecule relative to that of the encoding DNA. Substitutions and insertions/deletions are the two types of editing occurring in all types of cellular RNA. Adenosine-to-inosine (A-to-I) RNA editing is a central generator of transcriptome diversity and regulation in eukaryotes. The reaction is catalysed by a family of adenosine deaminases acting on RNA (ADARs). A-to-I editing of the tRNA anti-codon plays a crucial role in the function of tRNAs during protein synthesis and is performed by enzymes homologous to the ADAR; adenosine deaminase acting on tRNA (ADATs) . RecentlArg . These fEscherichia coli EndoV is, in contrast, a DNA repair enzyme that recognises a wide range of modified bases and cleaves the DNA in addition to I-containing RNA [E. coli has no ADAR enzyme but has an ADAT enzyme, and therefore likely utilises inosine as a modified base only in the tRNA wobble position. In higher eukaryotes that express ADAR enzymes, inosine may have become a more widely used regulatory modification in RNA.ning RNA , 58. IntRecent data indicate that some proteins responding to DNA damage may function in RNA metabolism. The DNA repair enzyme 5′-tyrosyl-DNA phopshodiesterase-2 (TDP2) cleaves the protein-RNA linkage generated by picornaviruses, and thus has a VPg unlinkase activity, a unique RNA repair-like function . TDP2 reDrosophila ribosomal proteins S3 and PO exhibit apurinic/apyrimidinic (AP) endonuclease activities in vitro [Conversely, RNA processing proteins or complexes may be involved in the DNA damage response or exhibit DNA repair activities. For instance, the Ccr4-Not complex promotes transcription coupled nucleotide excision repair . The verin vitro , 71. Thein vitro   is a multifunctional protein. It was first shown to stimulate the DNA-binding activity of the proto-oncogenes c-fos and c-jun by a reduction–oxidation (redox) mechanism . Later, Ape1 leads to early lethality [Ape1 is essential for early embryonic development in mice, since deletion of both alleles of ethality . Howeverethality .Moreover, APE1 interferes with the granzyme A-induced cell death response . Recent In an attempt to identify APE1 interaction partners, the nucleophosmin 1 (NPM1) protein was found to directly interact with the N-terminal region of APE1 . InteresSMUG1 was identified in a genome-wide screen for DNA glycosylases on the basis of its ability to bind synthetic inhibitors . SMUG1 bXenopus laevis bound to double-stranded DNA substrates confirmed the conservation of the core structural fold common to the UDG superfamily, and that the enzyme utilises the characteristic mechanism of extrahelical pyrimidine recognition [N-glycosidic bond, Phe98 and Asn163 for the discrimination of pyrimidine rings, and Gly87 and Met91 for the recognition of the C5 substituent [The crystal structure of SMUG1 from ognition . Furtherstituent .Smug1 inactivation resulted in loss of all detectable hmU-excision activity, indicating that Smug1 is the major, if not the only, enzyme responsible for hmU excision in the mouse [In addition to the activity on uracil substrates, SMUG1 has a special function to repair oxidised pyrimidines; it excises uracil derivatives bearing an oxidised group at the C5 position, such as 5-hydroxyuracil (hoU), 5-hydroxymethyluracil (hmU), and 5-formyluracil (fU), but not the analogous cytosine derivatives 5-hydroxycytosine (hoC) and 5-formylcytosine (fC) . Recentlhe mouse .Smug1 nor Ung/Smug1 double-deficient mice show any obvious phenotype [SMUG1 is a recent evolutionary acquisition; it is conserved among coelomata but absent in nematodes, plants, yeast, and bacteria. SMUG1 was originally suggested to have evolved in higher eukaryotes as an anti-mutator distinct from the UNG enzyme , 106. Cohenotype .http://mods.rna.albany.edu/), yet our data show that it is present in human rRNA in the absence of exogenous stress. It might originate from incorporation of hmU recycled from damaged DNA, as previously suggested [Recently, we showed that SMUG1 directly interacts with the pseudouridine synthase DKC1 . DKC1 cauggested . Howeveruggested .RRP6 and the BER pathway was reported in Saccharomyces cerevisiae [Rrp6 and apn1 (AP endonuclease) single mutants showed similar growth rates, as compared with the double mutant strain, upon 5-fluorouracil (5FU) treatment, which induces both DNA and RNA damage [UNG1 gene did not rescue the growth of both single mutants [Caenorhabditis elegans [APN1 and RRP6 may be interesting, and in fact be the first indication of a connection between DNA repair and RNA surveillance pathways.A genetic interaction between the exosome subunit revisiae . Rrp6 anA damage . This ep mutants , as woul elegans . TherefoIn contrast to the deep understanding of the RNA degradation processes of RNA quality control, the mechanisms that control the specificity of RNA degradation are still poorly defined. Many different types of aberrations may trigger RNA degradation, and it is unlikely that a single quality control system is capable of precisely recognising such diverse aberrations. A biochemical rationale for the involvement of BER proteins in RNA quality control could be that the ability of these enzymes to recognise subtle chemical modifications could contribute to identify substrates destined for degradation. Our recent findings demonstrating that the BER enzyme SMUG1 excises RNA-containing hmU and controls hmU levels in 28S and 18S rRNA species, as well as their expression levels , are conBecause little is known about how aberrant RNA species are recognised and specifically targeted for destruction, one important future challenge is to understand how the quality control machinery distinguishes its RNA substrates from other RNA molecules. As discussed above, BER enzymes may represent one pathway for targeting of specific RNA molecules for degradation. However, other enzymes probably have similar roles, and their identification is crucial to unravel the complexity of RNA quality control mechanisms.6A, which is reversed by FTO by direct demethylation [There is increasing evidence that RNA modifications may be reversible. One example is mhylation , 53 (Fighylation , and hmUhylation . hmU mayIn summary, the currently available data point to an emerging role of specific BER repair enzymes in RNA metabolism and RNA surveillance pathways. The unique ability of BER DNA glycosylases to recognise even subtle chemical modifications of nucleic acid bases may serve to distinguish normal and aberrant RNA molecules. The concerted action between DNA glycosylases and APE1 would, in turn, cleave modified RNA molecules. Further research is, however, required to determine whether this may be a general strategy to identify and prepare aberrant RNA molecules for degradation as part of a bona fide RNA quality control pathway. The recently described RNA processing activities of DNA repair enzymes warrant studies into whether their RNA processing functions contribute to pathologies associated with RNA processing defects.


Translation and replication of positive stranded RNA viruses are directly initiated in the cellular cytoplasm after uncoating of the viral genome. Accordingly, infectious virus can be generated by transfection of RNA genomes into susceptible cells. In the present study, efficiency of conventional virus isolation after inoculation of cells with infectious sample material was compared to virus recovery after transfection of total RNA derived from organ samples of pigs infected with Classical swine fever virus (CSFV). Compared to the conventional method of virus isolation applied in three different porcine cell lines used in routine diagnosis of CSF, RNA transfection showed a similar efficiency for virus rescue. For two samples, recovery of infectious virus was only possible by RNA transfection, but not by the classical approach of virus isolation. Therefore, RNA transfection represents a valuable alternative to conventional virus isolation in particular when virus isolation is not possible, sample material is not suitable for virus isolation or when infectious material is not available. To estimate the potential risk of RNA prepared from sample material for infection of pigs, five domestic pigs were oronasally inoculated with RNA that was tested positive for virus rescue after RNA transfection. This exposure did not result in viral infection or clinical disease of the animals. In consequence, shipment of CSFV RNA can be regarded as a safe alternative to transportation of infectious virus and thereby facilitates the exchange of virus isolates among authorized laboratories with appropriate containment facilities. Flaviviridae  were tested, which were taken from pigs that were culled during a CSF outbreak in Serbia in November 2010 (sample no.: 154–1 to 154–8). Since these samples were collected in the context of CSF control measures no ethical approval was required. The samples were sent by the Scientific Institute of Veterinary Medicine of Serbia, Virology Department, Belgrade, Serbia to the EURL for CSF  to confirm the CSF outbreak. After CSF diagnosis remaining sample material was used in the present study.Three different cell lines . For the first set of samples different amounts of total RNA were used for transfection, ranging from approximately 1 μg to 33 μg of total RNA  including recommendations of the ethics committee which was appointed by the LAVES according to the German animal welfare act . Herewith we confirm that this ethic committee is the competent ethics authority and that no other specific Institutional Animal Care and Use Committee for the performance of the animal experiment were required. On the basis of a CSF clinical signs scoring system  the genead libitum. Animals of the RNA inoculation group were oronasally inoculated with 2 ml EMEM containing 3.3 μg RNA which was prepared from whole blood of an animal infected with highly virulent CSFV strain Koslov. RNA transfection of SK6 cells and subsequent serial dilution of the transfected cells was used to calculate the infection equivalents and to confirm that the RNA was infectious after transfection of susceptible cells. The infection equivalents were determined on the basis of the highest dilution of transfected cells with a positive result for virus recovery and the RNA amount used for inoculation of one animal. Accordingly, each animal was inoculated with ~1.3 x 103 infection equivalents. Additionally, to show that material used for RNA preparation is per se infectious, three weaner pigs were oronasally inoculated with the original material (control group). The inoculation volume was equal to the volume used for RNA preparation and corresponds to the infection dose of 1.13 x 105 TCID50/ animal.The animal experiment was carried out at the high containment unit of the EURL . Eight pigs  of both genders were purchased from a breeding farm of the University of Veterinary Medicine Hannover, Germany. They were tested negative for pestivirus genomes and for neutralizing antibodies against pestiviruses and were randomly allocated into two groups comprising five  and three animals , respectively. The animals were housed in two separate fenced pens under high containment conditions with no direct and indirect contact. They were kept litter-less, were fed with commercial pig feed and had access to water In Vivo Experiments) Guidelines Checklist of this animal experiment is available as supporting information  of all ormation .Virus neutralization assay was performed with serum samples that were taken at seven days post inoculation and later on. The assay was performed according to the standard protocols , 5.2 and 5.8 x 105 genome equivalents/ μg RNA [quantification cycle (Cq) values from 20 to 30] (3 (284-kidney) and 1.9 x 102 (285-kidney) genome equivalents/ μg RNA, respectively   cells] and five (STE cells) samples, respectively. The CSFV genome copy numbers of these samples ranged between 1.5 x 101 to 28) . Since i1 to 28) . In compTo answer the question whether RNA isolated from infectious sample material, can be regarded as non-dangerous goods in case of shipment an animal experiment was performed. All five animals which were inoculated with RNA prepared from blood of an animal infected with the highly virulent strain Koslov showed no clinical signs referred to CSFV infection. A slight increase of leucocyte counts was detected after RNA inoculation which reached a plateau (~25 x 10E9/ l) on five days post inoculation . No leucThe RNA used for animal inoculation was only infectious after transfection of SK6 cells. Direct inoculation of SK6 cells with RNA mixed in culture medium lead to no virus production whereas virus was detected for an included positive control (inoculation of the cells with infectious cell culture supernatant containing CSFV Alfort/187).q values 34.98 to 37.41), followed by an increase until last sampling day . Swabs were tested positive on day three post infection  until last sampling day . Furthermore, high copy numbers of CSFV RNA were detected analyzing the organ samples of the control group .In contrast to the RNA inoculation group, animals of the infection group developed high fever on day three post infection, showed severe clinical signs of CSF, and were finally euthanized on day seven post infection in a moribund stage . A decre5 CSFV genome equivalents was very efficient. For these samples, infectious virus was recovered even in high dilutions of transfected cells. Genome equivalents in this range can be expected in 10 to 15 μl volumes of RNA preparations with Cq values between 20 and 24 in qRT-PCR. However, it was also shown that samples with higher Cq values (25 to 30) allow virus rescue by RNA transfection. The minimal amount of extracted RNA resulting in successful virus rescue was tested using field samples from an outbreak in Serbia. One microgram of total RNA, which contained between 1.5 x 103 and 1.5 x 106 CSFV genome equivalents, was sufficient for successful virus rescue of all field samples. From the methodological point of view, RNA transfection is less labor and time intensive and not prone to microbial contamination of cell culture. It is well known that microbial contamination can significantly limit the efficiency of virus isolation after inoculation of cells with infectious sample suspension. In this context, it seems to be likely that bacterial contamination observed for sample 284-kidney was at least partly responsible for the failure of conventional virus isolation although virus rescue by RNA transfection was successful. Furthermore, it is known that autolyzed sample material has cytotoxic effects on cell culture as well [Virological methods for the diagnosis of CSF are based on virus isolation after incubation of sample material on susceptible cells and detection of virus antigen and virus genome . RNA tra as well . Thus itper se infectious and hazardous for pigs after oronasal exposure. Since neither CSFV genomes nor CSFV-specific antibodies were present in any of the samples, it can be concluded that the mild unspecific clinical signs observed for animal 357 and the transient decrease of thrombocyte counts after RNA inoculation detected for animal 356 were not due to CSFV infection. In the present study pigs were inoculated with 3.3 μg of RNA corresponding to a dose of ~103 TCID50 produced after electroporation of susceptible cells. Similar amounts of RNA material are likely to be handled and transported between laboratories. To our knowledge, the minimal infectious dose of highly virulent CSFV strain Koslov has not been determined so far. However, previous studies have shown that an inoculation dose between ~102.5 and 103 TCID50/ animal of virulent CSFV strains (Brescia and Alfort/187) resulted in animal infection and disease [50/ animal was used for challenge infection with CSFV Koslov [3 TCID50/ animal of the highly virulent strain Koslov can be expected to be above the minimal infectious dose. Taken into account the amount and quality of RNA used for the inoculation of pigs described in the present study together with the assumption that exposure of pigs with RNA samples represents a very rare event, it seems to be very unlikely that an accidental oral up-take of RNA sample will lead to infection of pigs.For a clear classification of RNA as non-hazardous material the innocuity of RNA isolated from samples of CSFV infected pigs, has to be assessed in the natural host. To our knowledge inoculation studies of pigs or wild boar via oronasal route with prepared RNA have not been reported before. The results of the present study show that experimental oronasal inoculation of RNA from the highly virulent CSFV strain Koslov did not result in infection or disease of pigs. Since CSFV Koslov causes a severe acute disease with 100% lethality, this strain has been frequently used as challenge virus and therefore is an appropriate read-out system to proof the non-hazardous character of the RNA preparations used for inoculation of pigs –33. As e disease , 35 and V Koslov . Based oBiosecurity classification during transportation of samples containing full length genomes of other positive stranded RNA has to be estimated for each RNA virus separately and depends also on legislation of the country. For example in the United Kingdom samples containing full length genome of FMDV require the same biosecurity level as described for infectious sample material. This includes that only shipment to laboratories with appropriate containment facilities is allowed .per se not infectious for the host species and can therefore be classified as non-hazardous material. Nevertheless, the presented data highlighted that RNA can be converted relatively easy into hazardous material after transfection. Appropriate security arrangements to prevent intentional misuse or unintentional contamination (e.g. transfection reagents) are still required, although these security arrangements may not be the same as for infectious virus. The RNA transfection method described here can contribute to facilitate the exchange of virus isolates among national and international reference laboratories for CSFV as well as other authorized laboratories.Taken together, RNA transfection is a highly efficient approach for obtaining infectious CSFV isolates. It represents a valuable alternative to conventional virus isolation in particular for samples from which infectious virus cannot be isolated or when infectious material is not available. Accordingly, it is recommended to include the method of virus rescue by RNA transfection as an alternative approach for virus isolation in the Diagnostic Manual for CSF (Commission Decision 2002/106/EC). Furthermore, this study revealed that RNA prepared from samples of CSFV infected pigs, at least for the RNA amount used in the animal experiment described here, is S1 File(PDF)Click here for additional data file.