Mycobacterium tuberculosis to enter a state of slow growth for survival. However, the underlying regulatory mechanism remains unclear. DnaA is essential for DNA replication initiation and represents an efficient target for growth regulation in bacteria. Here, we show that the nucleoid-associated protein NapM is a DnaA antagonist, protecting M. tuberculosis from stress-mediated killing. NapM can be induced by diverse stressful signals. It binds to DnaA to inhibit both its DNA replication origin-binding and ATP hydrolysis activity. As a DnaA antagonist, NapM inhibits the mycobacterial DNA synthesis in vitro and in vivo in M. tuberculosis. Furthermore, we show that NapM contributes to the survival of M. tuberculosis under stress and within macrophages during infection. Our findings provide a previously unidentified mechanism of mycobacterial survival under stress and also suggest NapM as a potential drug target for tuberculosis control.Hostile environmental cues cause  M. tuberculosis in macrophages under stress by inhibiting DNA synthesis as a DnaA antagonist. This study suggests NapM as a potential drug target for tuberculosis control.Yu Liu, Zhiwei Xie et al. show that nucleoid-associated protein NapM enhances the survival of  This is an important strategy for a pathogen to escape from the killing mechanisms of a host and achieve successful infection4. Mycobacterium tuberculosis, the causative agent of tuberculosis, is a notorious intracellular pathogen that causes millions of global deaths annually5. M. tuberculosis has unique abilities to survive in the host and to cope with the pressure of the host environment, which leads to difficulty in controlling the infection of tuberculosis7. However, the molecular mechanism underlying such stress-inducible survival remains largely unclear.Most bacteria can survive under stressful conditions8. The growth and replication of nearly all bacteria essentially depend on the conserved ATPase protein DnaA, which binds to the replication origin (ori) and unwinds DNA9. By contrast, excess DnaA in bacterial cells results in replication over-initiation and subsequent growth inhibition10. Therefore, DnaA is an efficient target for growth regulation during the cell cycle, and the amount and activity of DnaA must be strictly controlled11. Notably, M. tuberculosis enters a state of very slow replication when encountering a hostile environment, and this strategy contributes to its survival within the host12. The regulation of DnaA expression has recently been found to be associated with the drug-inducible survival of M. tuberculosis13. Nevertheless, very little is known regarding the strategy of DnaA activity regulation and its relationship with the stress-inducible survival of M. tuberculosis.Recent studies show that bacteria have evolved mechanisms to transduce environmental cues into the cell-cycle engine and can thus reprogram their growth to rapidly adapt to stress conditions14. In the present study, we have shown that NapM acts as a broad stress-inducible factor. It acts as a DnaA antagonist in M. tuberculosis and is required for the pathogen’s survival under stress. Our findings provided new clues for understanding the regulatory mechanism of pathogenesis in this important human pathogen.Our group has characterized a conserved protein in mycobacteria, NapM (Rv0047c), as a nucleoid-associated proteinnapM expression is correlated with stress. As shown in Fig. M. tuberculosis H37Ra exposure to several major anti-TB drugs increased napM expression three- to sixfold compared with drug–stress absence. By contrast, a similar expression change of the negative control sigA was not observed under the same conditions. Interestingly, a search of previously published data and the TB database (http://www.tbdb.org/) produced by other groups revealed that napM expression in several mycobacterial species was induced almost more than twofold by different drugs and several stressful growth conditions , were constructed  for the specific interaction between NapM and DnaA was measured to be 0.38 μM, indicating a strong binding affinity between NapM and DnaA. No response was obtained when the negative control protein GroEL 2 was passed over the chip  assay confirmed the physical interaction between NapM and DnaA. DnaA protein was initially immobilized on the surface of CM5 chip. Response increased with increased NapM protein  amounts passed over the chip Fig. , indicat μM Fig. .A co-immunoprecipitation (Co-IP) experiment further confirmed the interaction of these two proteins in mycobacteria in vivo. Protein A beads that were conjugated with an antibody raised against NapM were used for our Co-IP assays. As shown in Supplementary Fig. oriC and that the complex band of NapM-oriC was a little lower than that of DnaA-oriC on the gel (lanes 2 and 8). A larger protein–DNA complex (NapM–DnaA–oriC DNA complex) appeared on the gel with an increased amount of NapM protein added into the reaction mixture containing fixed concentrations of DnaA and DNA. However, with progressively increased ratio of NapM/DnaA from 1:1 to 3:1 (lanes 3–5), the amount of protein/DNA complex decreased. Meanwhile, a NapM–DNA complex began to appear on the gel when the NapM/DnaA mixture was of 3:1 ratio, and the DnaA–oriC complex band almost disappeared at 5.5:1 ratio, indicating that DnaA–oriC complex formation competed with NapM protein. Interestingly, if NapM CTD was used to replace NapM to conduct a similar experiment as above, DnaA/oriC complex formation was also inhibited although a relatively higher concentration of NapM CTD was required in the reactions (NapM CTD/DnaA ratio of 3:1–18:1); however, no larger protein–DNA complex was clearly observed. This finding was most likely due to the fact that NapM CTD-DNA retained only partial interaction ability, which was insufficient to form a stable complex with DnaA/oriC on the gel under our experimental conditions. Moreover, NapM CTD lost its DNA-binding ability, and no additional NapM CTD -DNA band was observed  than NapM   assays to determine the ATPase activity of DnaA, both in the presence and in the absence of NapM protein. As shown in Fig. ATPase activity promoted rapid oligomerization of DnaA on oriC DNA, both of which are essential for DNA replication initiation17, suggesting that NapM suppressed DNA replication. For confirmation, we conducted an in vitro DNA replication assay. The fraction with DNA replication activity was produced from M. tuberculosis H37Ra. With increased concentrations of NapM  obtained a much lower DNA content based on the determination of mean fluorescence intensity of 4,6-diamidino-2-phenylindole staining, the result of which is very similar to the observation for dnaA-overexpressed strain (Mtb/pMV261-dnaA). In addition, the napM-deleted mutant (Mtb napM::/pMV261) also obtained a lower DNA content although to a lesser extent when compared with the wild-type strain  could neutralize either of their respective inhibitions on DNA synthesis, and the DNA content of the coexpression strain was similar to that of the wild-type strain  of wild-type M. tuberculosis H37Ra was about 4.6-fold higher than that of the napM-deleted mutant strain. We also observed a similar effect of NapM, although a little less, on mycobacterial survival when bacterial cells were exposed to cell-membrane damage stress (by sodium dodecyl sulfate (SDS)) ) Fig. . These rM. tuberculosis is exposed to acute intracellular stresses. To further assess the effect of NapM on the intracellular survival of M. tuberculosis, macrophage RAW264.7 was used as a model and was infected with wild-type or mutant mycobacterial strains. As shown in Fig. M. tuberculosis was demonstrated to survive well within the macrophages for 48 h. By contrast, the napM-deleted mutant strain retained a much lower survival percentage (10% at 24 h and 3% at 48 h after infection) than the wild-type M. tuberculosis strain, indicating that NapM played an essential role in M. tuberculosis survival within macrophages.During infection, 14. In the present study, we have shown that NapM was a broad stress-inducible protein in M. tuberculosis and can regulate mycobacterial growth. NapM physically interacted with DnaA and inhibited DNA replication initiation both in vitro and in vivo. Strikingly, the protein was shown to contribute to the survival of M. tuberculosis under stressful conditions and within macrophages during infection. In this work, we reported a novel regulatory mechanism on the survival of M. tuberculosis under stress.NapM has recently been characterized as a nucleoid-associated protein and is conserved in all sequenced mycobacterial genomes18. Many studies suggest that M. tuberculosis can retain slow growth and replication under environmental stresses2. However, the underlying regulatory mechanisms remain unclear. The regulation of DNA replication initiation can efficiently prevent over-replication or decrease bacterial growth under stressful environments19. One of our most interesting findings was that NapM can deliver environmental cues into the DNA-replication engine and can thus potentially influence the growth of M. tuberculosis under stress. NapM directly targeted DnaA to prevent its binding to oriC, which decreased the amount of DnaA in oriC. Meanwhile, NapM inhibited the ATPase activity of DnaA, which suppressed its rapid oligomerization in oriC. Several proteins from different bacteria have been identified as a direct DnaA-binding factor, such as DiaA in Escherichia coli, HobA in Helicobacter pylori, and YabA in Bacillus subtilis22. However, NapM did not share sequence identity with these regulators. NapM was also a broad stress-inducible protein and was essential to the survival of M. tuberculosis under stress. Therefore, NapM was a novel DnaA-interacting protein.To ensure that chromosomal DNA is accurately replicated and that this process is correlated with cell growth, bacteria must tightly regulate the initiation step of DNA synthesis, especially under stressful conditionsM. tuberculosis  . All antibiotics and enzymes, including T4 ligase, DNA polymerase, and restriction enzymes, were obtained from TaKaRa Biotech . Ni–NTA (Ni2+–nitrilotriacetate) agarose columns were purchased from Qiagen . Invitrogen  synthesized all PCR primers for our assay. The radioactive-labeled [α-32P]ATP was purchased from Perkin Elmer (USA). Middlebrook 7H9 medium and Oleic acid-Albumin-Dextrose-Catalase (OADC) enrichment were purchased from Becton-Dickinson Company (USA) and were used for growing M. tuberculosis.pET28a (Novagen) was used for the overexpression of napM gene from M. tuberculosis H37Ra genome by PCR. The amplification was performed as follows: 95 °C for 5 min, followed by 30 cycles of 95 °C for 30 s, 50 °C for 30 s, 72 °C for 1 min and a final extension of 72 °C for 10 min, respectively. The napM N-terminal DNA-binding domain region was amplified by a pair of primers (5′-AGACGAATTCAAATGCTGG AGCTCGCCAT-3′ and 5′-AGACTCTAGATTAGAAACCGTCGTCGGTGTAG-3′), and the napM CTD region was amplified by a pair of primers (5′-ATAT GAATTC AA ATGCCAGCGGGCACCCCGGT-3′ and 5′-ACAGTCTAGATTACGTCTGTTCG GCGGG-3′) from M. tuberculosis H37Ra genome. The dnaA gene was amplified by using forward primer 5′-ATATGCGGCCGCATTGACCGATGACCCCGG-3′ and reverse primer 5′- GTGGTCTAGACTAGCGCTTGGAGCGCTGAC-3′. The napM gene was digested by restriction endonucleases and cloned into modified pET28a for protein overexpression in the host strain E. coli BL21 (λDE3). The recombinant proteins were purified according to our previously published procedures25. The purity of these proteins was estimated by 15% SDS-polyacrylamide gel electrophoresis  was used to amplify the napM gene of M. tuberculosis was knocked out according to previously described procedures with some modifications26. A pMind-derived suicide plasmid carrying a hygromycin resistance gene was constructed and a sacB gene was inserted to confer sensitivity to sucrose as a negative selection marker. pMind-napM KO was constructed by inserting the upstream fragment and downstream fragment (amplified with corresponding primers from M. tuberculosis H37Ra genome) into the pMind vector. Then, pMind-napM KO (1 µg) was electroporated into M. tuberculosis H37Ra and selected on 7H10 medium containing 100 µg ml−1 hygromycin, 2% sucrose, and 50 µg ml−1 X-gal. Both PCR products and the subsequent sequencing analysis  medium and was ensured at the same initial OD. Then, the cells were grown under various stressful conditions, including antibiotics , acid shock (pH 4.0), nutrient starvation, heat shock (55 °C), oxidative stress (2.5 μM H2O2), and cell-membrane damage (0.05% SDS). Nutrient-starvation cultures were set up as previously described27 in phosphate buffer saline containing 0.05% Tween 80. Cultures were harvested at an OD600 1.0. Total RNA from M. tuberculosis H37Ra was prepared according to previously described procedures28. For qRT-PCR, the following primers were used: napM, 5′-TCGCCATCCTGGGTCTGT T-3′ (forward) and 5′-CAGCGCCGGGTATAACGAA-3′ (reverse); dnaA, 5′-CATC TGACCGCCCACCCAA-3′ (forward) and 5′-AGCCGTTCCATCTGTGCTTTCT-3′ (reverse). For normalizing data, the following sigA-specific primers were used: 5′ -CGACGAAGACCACGAAGACC-3′ (forward) and 5′-TTCATCCCAGACGAA ATCACC-3′ (reverse). The real-time PCR was performed in a Bio-Rad CFX RT-PCR machine. The levels of sigA or dnaA transcripts were used as the internal control to normalize expression levels of different genes, and melting curves were used to analyze amplification specificity. The rates of expression change were calculated by Log-phase cultures of the wild-type 29. Positive-growth co-transformants were characterized on a screening plate containing 5 mM 3-amino-1,2,4-triazole (3-AT) (Stratagene), 8 mg ml−1 streptomycin, 15 mg ml−1 tetracycline, 34 mg ml−1 chloramphenicol, and 50 mg ml−1 kanamycin. Co-transformants containing pBT-LGF2 and pTRG-Gal11P (Stratagene) were used as positive controls, and the recombinant strains containing empty vector pBT and pTRG were used as negative controls.The BacterioMatch II Two-Hybrid System Library Construction Kit (Stratagene) was used to detect the interactions between DnaA and NapM proteins30. Briefly, to detect the physical interaction between NapM  and DnaA, DnaA protein was immobilized onto the CM5 chips, and then NapM and its mutant proteins were passed over the chips. All proteins were diluted in the reaction buffer (10 mM hydroxyethyl piperazineethanesulfonic acid (HEPES), 150 mM NaCl, 3 mM ethylenediaminetetraacetic acid (EDTA), and 0.01% (vol/vol) surfactant p20) (pH 7.4) to concentrations of 10–128 nM and were injected at 10 ml min−1 for 5 min at 25 °C. Each analysis was performed in triplicate. An overlay plot was produced using the BIA evaluation 3.1 software to depict the interaction between NapM and DnaA. In order to identify the interaction between NapM and domains of DnaA, NapM was immobilized onto the NTA chips, and DnaA and its mutant proteins were passed over the chips.SPR analysis for the binding of NapM with DnaA was conducted on a Biacore 3000 instrument with CM5 sensor chips according to previously published proceduresM. tuberculosis between NapM and DnaA were analyzed by Co-IP according to previously published procedures with some modifications29. Briefly, exponentially growing cells of M. tuberculosis H37Ra with recombinant plasmid pMV261-dnaA were harvested, resuspended, and lysed in 4 ml of buffer (50 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1 mM EDTA, and 0.5% Nonidet P-40). Co-IPs were performed by incubating and shaking 0.5 mg of the mycobacterial cell extract with 5 μl of NapM antiserum. Finally, the samples were analyzed by western blotting using anti-DnaA antibody. The antibodies were ordered from the Animal Immunology Center of Wuhan Institute of Virology, Chinese Academy of Sciences. Briefly, the purified NapM protein (300–500 µg) was dissolved in 600 µl of Freund’s complete adjuvant and injected into rabbits or mouse. Subsequently, the protein was dissolved in Freund’s incomplete adjuvant for the same immunization after an interval of 14 days. Seven days after the injection, animals were bled for antibody preparation.The in vivo interactions in oriC fragments were generated by PCR amplification using a pair of primers (5′-GTGTCGTGAGCTCACCGATC-3′ and 5′-AAAATCTGCCAGCCAGGCC-3′) from H37Ra genome and purified with a DNA purification kit (BioFlux). The 5′-end of DNA substrate was labeled and EMSAs were performed according to previously described procedures14. The total volume of the reaction mixtures was 20 μl, including reaction buffer, 1 μM labeled DNA fragments, 0.5 μM DnaA, and various amounts of NapM/ NapM CTD.The 15. Specifically, the reaction mixtures (10 μl) contained 20 mM Tris-HCl (pH 8.0), 1 mM MgCl2, 100 mM KCl, 8 mM dithiothreitol, 4% sucrose, 80 μg ml−1 bovine serum albumin, 1 mM ATP, 3.4 fmol of [α-32P] ATP, 1.93 μM DnaA, and NapM at concentrations indicated in the figure legends. The reactions were performed at 37 °C for 30 min and stopped by placing on ice. Products were separated by TLC on a polyethylenemine cellulose strip (Merck) in 0.5 M LiCl and 1 M formic acid at room temperature for 45 min. The TLC plate was dried and autoradiographed.ATPase activity was assayed according to previously described procedures with minor modifications31, the fractionation of DNA-replication activity in vitro was collected through ammonium sulfate. M. tuberculosis H37Ra was grown in 7H9 media for 7 days in roller bottles at 37 °C. The cells were harvested, washed, and resuspended with buffer A (25 mM HEPES/KOH (pH 7.6), 0.1 mM EDTA, 2 mM dithiothreitol, and 100 mM potassium glutamate). The supernatant was acquired by rupturing the cells with sonication and then precipitated slowly by the addition of ammonium sulfate at 4 °C. The obtained precipitate (fraction II) was resuspended and dialyzed for 60–90 min at 4 °C with buffer A. The protein concentration was estimated by Bio-Rad protein assay. In vitro DNA replication was carried out with a buffer including 40 mM HEPES-KOH (pH 7.6), 21.6 mM creatine phosphate (Fluka), 6 mM ATP, 500 µM each of GTP, CTP, and UTP, 100 µM each of dGTP, dCTP, and dTTP, 50 µM dATP, 50 µg ml−1 bovine serum albumin, 200 cpm M−1 of total deoxynucleotide α-32P dATP, 7% polyethylene glycol 10,000, 11 mM magnesium acetate, 35 µg creatine kinase (Sigma), and 2.5 µg supercoiled plasmid DNA (pUC-oriC). The reaction mixture was incubated at 30 °C for 90 min after adding 200 µg of fraction II. Total nucleotide incorporated within the supernatant was purified using a DNA purification kit , dotted on nylon membrane and measured by determining radioactivity. All the reactions were quantitated by Typhoon Variable Mode Imager and Image Quant software.Following a previously published procedure32. Cells were centrifugated at 1000 rpm for 3 min to remove clumps. Supernatant cells were centrifuged at a high speed and washed three times in phosphate-buffered saline (PBS). Then, the cells were fixed in 4% paraformaldehyde and 50 mM ammonium chloride. The fixed samples were permeabilized with 0.1% Triton X-100 and 2 mg ml−1 lysozyme33, and then stained with 100 μM 4,6-diamidino-2-phenylindole diluted in PBS for 20 min at room temperature. Stained cells were rinsed with PBS, then sonicated and passed through a 70 μm filter. Samples were gated based on forward and side scatter of unstained cells, and were analyzed using Beckman cytoFlex (USA)  monocyte/macrophages (RAW264.7) were maintained at 37 °C in a humidified incubator with 5% CO2 and infected with M. tuberculosis H37Ra at a multiplicity of infection of 3 as previously described34. Macrophages (RAW264.7) were incubated with a mutant or wild-type strain of M. tuberculosis H37Ra for 4 h, and the extracellular bacteria were washed away by replacing the culture supernatant with fresh medium. At the indicated times, RAW264.7 were lysed with 0.2% Triton X-100, and serial dilutions were plated on Middlebrook 7H10 solid medium. The P values of the relative growth data were calculated by unpaired two-tailed Student’s t test.The Further information on experimental design is available in the Supplementary InformationReporting Summary


One of the major challenges of RNA-based therapeutics is the method for delivery of RNA molecules. In a recent article (Nat Commun 9(1):2359), we described a novel delivery platform for RNA-based drugs using red blood cell extracellular vesicles which can efficiently deliver both small and large RNAs to solid and liquid tumours. Our RBCEVs platform features exceptional merits over conventional RNA delivery methods in biosafety, biocompatibility, efficiency, accessibility, and cost effectiveness. The emerging RNA-based therapeutics are renowned for a wide array of druggable targets, which are difficult to achieve by conventional therapies, with high specificity and great versatility. RNA-based drugs function depends on different mechanisms, such as RNA interference using small-interfering RNAs (siRNAs), inhibition of RNA functions using antisense oligonucleotides (ASOs), and genome editing using the CRISPR-Cas9 system with guide RNAs (gRNAs). The advantages of RNA-based therapeutics boost the translation into various clinical applications, from repairing genetic disorders to fighting against cancers to silencing virus replication. However, there currently exist two major challenges in RNA-based therapeutics: (i) instability of RNA drugs in physiological environment and (ii) difficulty in delivery of RNA drugs. The former can be resolved by chemical modifications to enhance the stability, which has already been tested in clinical trials, whereas the delivery issue remains largely unresolved. Delivery via viruses and/or lipid-based nanoparticles/reagents is suboptimal due to cytotoxicity, immunogenicity, and uncertainty in biosafety.Extracellular vesicles (EVs), which are secreted by most cell types and represent a natural mode of intercellular communication, are thriving as novel carriers of RNA-based drugs with appreciable biocompatibility. EVs can be isolated from human cells including cancer cells, fibroblasts, epithelial cells, etc., or non-human sources such as plants and bovine milk. RNA-based therapeutic agents such as ASOs, mRNAs, and miRNAs, have been successfully loaded into EVs by passive loading using physical incubation, by active loading using electroporation and sonication, or by transfection of EVs donor cells. The diversity of administration methods of RNAs-loaded EVs ranging from oral administration, intratumoural injection to systematic administration allows the therapeutics to be tailored to maximise the targeting and delivery efficiency to treat various diseases. The beauty of using EVs as RNA-based therapeutics carriers lies in low immunogenicity, high biocompatibility, and natural interaction with target cells in comparison with traditional RNAs delivery strategies. Despite such perks, RNA delivery technology using EVs is hampered by both the difficulty in producing a large amount of homogenous, ultrapure EVs and the risk of horizontal gene transfer due to DNA encapsulated in EVs.13 to 1014 RBCEVs particles per blood unit with high purity.In our recent article, we described a robust RNA drugs delivery platform based on red blood cell extracellular vesicles (RBCEVs), which harbours plenty of advantages over conventional delivery methods. RBCEVs are derived from human red blood cells (RBCs), which lack both mitochondrial and nuclear DNA, thus avoiding the risk of horizontal gene transfer. RBCs have been widely used for blood transfusion over decades, which highlights the extraordinary biosafety and biocompatibility of the filial vesicles, i.e. RBCEVs. Furthermore, RBCEVs can be stored at -80°C for a long period and remain stable and intact, even after multiple freeze-thaw cycles, without affecting the moiety, uptake and RNA loading capacity. Qualities of such can facilitate the storage and transportation of RBCEVs. Last but not least, it is easy to produce ultrapure RBCEVs in a large scale at low cost. RBCs are readily available from human subjects in blood banks and we can treat RBCs with calcium ionophore to induce EV release, then purify intact and ultrapure RBCEVs through series of ultracentrifugation and sucrose cushions. Since no expensive culture medium is needed, the method is rather cost-effective. It is possible to produce about 10In our study, we loaded a variety of RNA-based therapeutics into RBCEVs, used the powerful RBCEVs delivery platform to treat both solid and liquid tumours and observed impressive efficacies. Breast cancer and acute myeloid leukaemia (AML) were used as representatives of solid and liquid tumours in the investigation.TM 3000 and INTERFERin. RBCEVs-mediated delivery of miR-125b ASOs resulted in the down-regulation of miR-125b in vitro, which led to an increase in the expression level of its target gene BAK1 and inhibited the proliferation of MOLM13 cells. We observed the same effect in the human metastatic breast cancer MCF10CA1a cells. In vivo imaging showed that RBCEVs were taken up by breast cancer cells engrafted in immunodeficient mice with high efficiency. miR-125b ASOs loaded RBCEVs inhibited cancer cell proliferation, suppressed miR-125b expression level and reduced infiltrated cancer cells in AML MOLM13 engrafted mice. In addition, Cas9 mRNA and gRNA were successfully introduced into AML cell line MOLM13 using RBCEVs with agreeable functionality, which demonstrated the capacity of RBCEVs delivery platform in genome editing.The human AML cell line MOLM13 is known as a difficult-to-transfect cell line with common RNA delivery vehicles. When using our RBCEVs delivery platform, MOLM13 cells could take up RNA-loaded RBCEVs easily at high efficiency and low toxicity as compared to commercial transfection reagents such as LipofectamineThe capacity to load RNA-based drugs including ASOs, Cas9 mRNA and gRNAs or even plasmids has broadened the scope of RBCEVs application to treat diseases with current undruggable targets. Future development of RBCEVs research includes the specific targeting of RBCEVs, which can be achieved by conjugating antibodies or peptides to RBCEVs with the capacity to bind to their target cancer cells specifically. The targeted delivery of RBCEVs will not only enhance the efficacy of RNA drugs, but also significantly reduce side effects on normal tissues, thus weaponizing RBCEVs to treat various diseases.


By inducing nuclear eIF2α phosphorylation, these PKR activator elements enable highly efficient early spliceosome assembly yet do not impair translation of the mature spliced mRNA. The TNF-α RNA activator of PKR folds into a compact pseudoknot that is highly conserved within the phylogeny. Upon excision of β-globin first intron, the RNA activator of PKR, located in exon 1, is silenced through strand displacement by a short sequence within exon 2, restricting thereby the ability to activate PKR to the splicing process without impeding subsequent synthesis of β-globin essential for survival. This activator/silencer mechanism likewise controls splicing of α-globin pre-mRNA, but the exonic locations of PKR activator and silencer sequences are reversed, demonstrating evolutionary flexibility. Impaired splicing efficiency may underlie numerous human β-thalassemia mutations that map to the β-globin RNA activator of PKR or its silencer. Even where such mutations change the encoded amino acid sequence during subsequent translation, they carry the potential of first impairing PKR-dependent mRNA splicing or shutoff of PKR activation needed for optimal translation.A critical step in the cellular stress response is transient activation of the RNA-dependent protein kinase PKR by double-helical RNA, resulting in down-regulation of protein synthesis through phosphorylation of the α chain of translation initiation factor eIF2, a major PKR substrate. However, intragenic elements of 100–200 nucleotides in length within primary transcripts of cellular genes, exemplified by the  PKR gene transcription in the cell  is critical for mounting the integrated cellular stress response . Transiethe cell . To becolication . Highly lication . Once aclication .cis to potently activate PKR, rendering splicing highly efficient  gene does not harbor an intragenic activator of PKR and its mRNA is spliced sluggishly; yet, upon transposition of the TNF-α element into the TNF-β 3′-UTR, splicing of TNF-β pre-mRNA became as efficient as that of TNF-α, showing that the 2-APRE functions as an autonomous splicing control element  by truncation, mutational analysis, and in-line probing of the RNA  shows that numerous human β-thalassemia mutations map to the β-globin RNA activator of PKR or to its silencer  map to the PKR activator and silencer domains as delineated at present.Minimal sequences encoding the silencer  were defsilencer ; their Rβ-globin, the RNA activator of PKR of γ-globin, the fetal form of β-globin, is located within the first exon and γ-globin mRNA splicing is strictly dependent on PKR activation and eIF2α phosphorylation .Mutational analysis of the  2-APRE,  demonstr 2-APRE, . Length analysis . It is tIFN-γ mRNA and TNF-α pre-mRNA, even single-nucleotide substitutions or the inversion of a single base pair can lead to loss of the ability of the RNA element to activate PKR (β-globin pre-mRNA, on the other hand, silencing of the ability of its RNA activator of PKR to activate the kinase, through effective base pairing with RNA encoded by a separate silencer element that induces conformational changes within the RNA activator structure, in this case through strand displacement, is likewise sensitive to mutation (The discovery of intragenic elements that once transcribed, control splicing by activating PKR in the nucleus or by silencing the ability to activate PKR, adds a new dimension to the analysis and interpretation of human gene mutations. As shown for the RNA activators of PKR within vate PKR . This demutation .Thus, short intragenic RNA elements that activate PKR or that silence PKR activators are not only essential for controlling efficient mRNA splicing but also create potential etiology for human disease. In a broader sense, this novel perspective may account for and/or contribute to the phenotype of gene mutations analyzed hitherto primarily for their effect on protein sequence. Even where such mutations change the encoded amino acid sequence during subsequent translation in the cytoplasm, they also carry the potential of first impairing PKR-dependent mRNA splicing in the nucleus or the shutoff of PKR activation needed for optimal translation. That concept extends to silent mutations and to mutations that alter amino acid sequence without having a major effect on protein function.OT searched the human gene mutation database. OT and RK analyzed the human mutation data. LI, SC-C, LN, FO, and RK designed and performed the experiments and analyzed the results. RK wrote the manuscript. All authors read and approved the final version of the manuscript for submission.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.


However, the autolytic process is slow, resulting in high production costs. This work evaluated the effect of adding sonicated lees and combining it with oak chips, as a new technique to accelerate the AOL process and improve the aromatic quality of aged red wine. Cell disruption due to sonication was verified by optical microscopy. Volatile acidity, total polyphenol index, color intensity, tonality, dissolved oxygen, anthocyanins, and fermentative volatiles were monitored throughout the ageing of the wines. Sensory analysis was performed at the end of the ageing process. Polysaccharides released from the cell walls and the oxygen consumption, was quantified using a hydroalcoholic solution. The results indicated a 20% increase of the polysaccharide content and suggested an increase in the antioxidant capacity of the lees. No significant changes were observed in the fermentative volatile compounds and the total polyphenol index (TPI), except for those wines in contact with wood. The sonication of lees had some protective effect on the total anthocyanins content, however, color intensity was significantly lower in the sonicated treatments. The sonication of the lees did not cause any defect at the sensory level. Therefore, sonication could allow a reduction in the SO Ageing on lees (AOL) is a technique traditionally used in the production of sparkling wines . It is aAOL has a number of economic impacts because of the large infrastructure investments producers make to store the wines in cellars, and winemakers face additional potential risks, such as microbiological and organoleptic alterations . It is aUltrasound is sound waves with frequencies higher than the upper audible limit of human hearing, typically ~20 kHz . UltrasoIn previous studies by the authors, the polysaccharide content of red wines increased after the use of US, during AOL . HoweverThe effect on the wet lees was observable through an optical microscope, after 20 min of US treatment a,b. CellThe lysis effect seems to be responsible for an increase in the content of polysaccharides released from the cell wall, during ageing in the hydroalcoholic solution. The polysaccharides are released by the yeast, during the AOL process, in particular, mannoproteins, which play an important role, since they may interact with volatile compounds, contribute to protein and tartrate stability, stabilize the color, and decrease both the astringency and the bitterness of the wine . No signThe US treatment also had an effect on the cell decanting time in the hydroalcoholic solutions d. After The control wines (control wine (W) and wine with oak chips (WC)) showed the greatest concentration of dissolved oxygen, during all ageing periods a. With rIn general, lower concentrations of dissolved oxygen were found in wines, compared to the hydroalcoholic solutions b. This cRegarding volatile acidity, no significant differences were found between the samples during the first 30 days of ageing (0.38 ± 0.01 g/L); after 60 days, differences were found between the wine with sonicated lees and oak chips (WCLS) and the wine with sonicated lees (WLS), with a slight increase in the WCL samples (0.44 ± 0.01 g/L). There was no noticeable increase in the volatile acidity associated with the use of lees, sonicated lees, or oak chips.An increase in color intensity was evident for all samples, in the last 30 days of the ageing period a. The coRegarding the total polyphenol index (TPI) b, signifStable pigments were formed because of the condensation between grape anthocyanins and the metabolites, acetaldehyde and pyruvic acid . At the As a result of the condensation between the anthocyanins and the vinylphenols, another stable pigment was formed, i.e., vinylphenolic pyranoanthocyanin . In geneDuring the first 30 days of ageing, the control wines (W and WC) showed significantly higher total volatile content than the wines aged on lees (WL and WCL) a. In addAfter 60 days of ageing, an increase in the higher alcohols content (>400 mg/L) was found in all of the wines. These values are seen as a negative quality factor . SignifiA PCA was carried out for the 16 volatile compounds c. The diThe wines aged with oak chips and lees obtained the highest scores in terms of global quality, possibly because of the aromatic complexity, due to the combination of both ageing systems  Figure . In the Saccharomyces cerevisiae) used in this study was isolated in “Comenge Bodegas y Viñedos SA” by the Chemistry and Food Technology Department of ETSI Agronómica, Alimentaria y de Biosistemas (UPM). This winery is situated in the Ribera Del Duero area of Spain.The yeast strain CTPL22 . The wine was aged for 3 months in French oak barrels. The following parameters were measured: pH = 3.6; volatile acidity = 0.38 g/L of acetic acid; ethanol content = 13.5% v/v; lactic acid = 2 g/L; total SO2 = 80 mg/L; total polyphenol index (TPI) = 56; total anthocyanin content = 175 mg/L; color intensity = 1.2 absorbance units; tonality = 60.8 ; and total fermentative volatile compounds = 1755.8 mg/L .The red wine used in this experiment was elaborated by Bodegas Comenge , conventionally produced with grapes from the 2016 harvest (v/v) was used to simulate the AOL in the red wine and measure the content of polysaccharides released by the lees. In addition, this hydroalcoholic solution was sulphited to 80 mg/L of the total SO2 with K2S2O5. The pH was adjusted to 3.6, with phosphoric acid.A hydroalcoholic solution composed of water and ethanol (13.5% 2), was used to apply the US treatment. The sonotrode was introduced into the yeast biomass until the headspace was completely filled. The US treatment was sufficient when the cellular lysis effects were evident using an optical microscope.50 mL of pure yeast biomass was treated with ultrasound, for twenty minutes, in a 100 mL volume ISO flask. A UP400ST digital ultrasonic processor  of 400 W and 24 kHz, equipped with a H22DL2 sonotrode , wine with lees (WL), wine with sonicated lees (WLS), wine with oak chips (WC), wine with lees and oak chips (WCL), and wine with sonicated lees and oak chips (WCLS). The dosage of oak chips was 2.5 g/L. The medium-toasted oak chips were provided by Boisé . The dosage of wet lees was 6 g/L. The wine samples were aged in a dark room, at a temperature of 14 °C, for 60 days. The samples were shaken manually, once a week, without opening the flasks, with the aim of resuspending the lees in the wine and, thus, increasing the contact surface. Samples were drawn every two weeks to measure the dissolved oxygen, volatile acidity, TPI, chromatic characteristics , fermentative volatile compounds, and the anthocyanin content. A sensory analysis was performed at the end of the ageing period.The hydroalcoholic solutions were also prepared in triplicates, using ISO flasks of 1 L. The different treatments were: hydroalcoholic solution with lees (ML) and hydroalcoholic solution with sonicated lees (MLS). The dosage of wet lees was 6 g/L. The ageing conditions were the same as those of the wine samples. Every two weeks, the analyses undertaken were dissolved oxygen and polysaccharides content. Absorbance at 480 nm was monitored after a stirring cycle, in order to establish the differences in the decanting time of the lees (25 °C).The analysis of polysaccharides was only done in the hydroalcoholic solutions, using an HPLC-RI technique. A Waters e2695  chromatograph with a Ultrahydrogel 250 molecular exclusion column (Waters) was used, according to the method described by Loira and co-workers .The volatile acidity (expressed as acetic acid) was measured by Fourier transform infrared spectroscopy (FTIR), using an OenoFoss™ instrument . The decanting time was obtained by consecutive measurements of absorbance at 480 nm, for a total time of 28.33 h in the hydroalcoholic solutions, at the end of the ageing period. The TPI of the wine samples was calculated by spectrophotometric measurements, after diluting the samples 100 times with deionized water (absorbance at 280 nm with 1 cm path length quartz cuvette) . The colA HI9146V oximeter  was used to determine the dissolved oxygen content, both in the wine samples and the hydroalcoholic solutions. A magnetic stirrer was used for homogenization around the membrane. The reading was made after 1 min, while keeping the probe inside the sample, under agitation, for the time necessary for the stabilization of the oximeter.The anthocyanin and pyranoanthocyanin contents were obtained using an 1100 HPLC chromatograph  equipped with a diode array detector and a Kinetex RP-C18 100 Å Phenomenex column  , as described by Fresno and co-workers [The fermentative volatile compounds were determined using an Agilent Technologies 6850 gas chromatograph, equipped with an integrated flame ionization detector (GC-FID). Analyses were performed according to the method described by Ábalos et al. .The sensory analysis was carried out by a panel of expert wine tasters, consisting of nine trained judges . The blind tasting took place under fluorescent lighting and the samples were presented in a random order. Approximately 20 mL of wine was served into odor-free tasting glasses. Serving temperature was set at 20 ± 2 °C. A glass of water was used for palate cleansing between samples. The panelists used a scale from 1 (low perception) to 5 (high perception), to rate the intensity of each attribute, with the exception of the tonality parameter, which was evaluated from 1 (purple tones) to 5 (yellow tones). The visual parameters evaluated were color intensity and tonality; the aromatic parameters evaluated were aromatic intensity, aromatic quality, wood, spicy aromas, roasted, cooked flavor, yeasty aroma, oxidation, and reduction; the flavor parameters evaluated were acidity, astringency, balance, bitterness, and body. Finally, the overall impression was assessed, which included all the parameters of the wines tasted.p < 0.05.Means and standard deviations were calculated and analysis of variance (ANOVA) and least significant difference (LSD) tests were performed using PC Statgraphics v.5 software . The LSD test was used to detect significant differences between means. Significance was set at 2 addition, as well as the ageing times. Furthermore, reductions in the lees decanting time could facilitate clarification, prior to bottling.The use of US on wet lees could accelerate the cellular lysis, since the addition of sonicated lees to wines increased the rate of transfer of polysaccharides, during the ageing process. There seems to have been an increase in the antioxidant capacity of the lees, based on the low content of dissolved oxygen found in the wines aged with the sonicated lees. A faster decantation rate was also observed. The AOL process affected the different oenological parameters, including reductions in color intensity and TPI. In addition, when the AOL process was combined with oak chips, both aromatic intensity and aromatic quality were improved. The use of this technique in wineries could be beneficial because it might reduce the SO


The diversity and evolution of RNA viruses has been well studied in arthropods and especially in insects. However, the diversity of RNA viruses in the basal hexapods has not been analysed yet. To better understand their diversity, evolutionary histories and genome organizations, we searched for RNA viruses in transcriptome and genome databases of basal hexapods. We discovered  40 novel RNA viruses, some of which are also present as endogenous viral elements derived from RNA viruses. Here, we demonstrated that basal hexapods host 14 RNA viral clades that have been recently identified in invertebrates. The following RNA viral clades are associated with basal hexapods: Reo, Partiti-Picobirna, Toti-Chryso, Mono-Chu, Bunya-Arena, Orthomyxo, Qinvirus, Picorna-Calici, Hepe-Virga, Narna-Levi, Tombus-Noda, Luteo-Sobemo, Permutotetra and Flavi. We have found representatives of the nine RNA viral clades that are present as endogenous genomic copies in the genomes of Machilis (Monocondylia) and Catajapyx (Diplura). Our study provided a first insight into the diversity of RNA viruses in basal hexapods and demonstrated that the basal hexapods possess quite high diversity of RNA viral clades. The analysis of the invertebrate RNA virosphere uncovered a vast diversity of RNA viruses in insects, their evolutionary histories, highly diverse and dynamic genome organizations, as well as the presence of distinct RNA viromes in diverse insect lineages . MetazoaLepisma saccharina (Zygentoma) or the lucerna flea Sminthurus viridis (Collembola). Springtails have the widest distribution of any hexapod group, occurring throughout the world, including Antarctica. They are found in soil, leaf litter, logs, dung, cave, shorelines, etc. and are probably the most abundant hexapods on Earth, with up to one quarter of billion individuals per square acre . They are an assemblage of five groups: Protura (coneheads), Collembola (springtails), Diplura (two-pronged bristletails), Monocondylia: Archaeognatha (jumping bristletails) and Zygentoma  and represent the earliest splits of hexapod lineages . Basal hare acre .RNA viruses in the basal hexapods have largely been ignored and were not included in the study of invertebrate RNA virosphere . Until nhttp://www.ncbi.nlm.nih.gov). To detect all available representatives of the particular RNA viral family, database searches were performed iteratively. Comparisons were made using the TBLASTN program . The nucleotide sequences of all basal hexapod RNA viruses are available in the Sequence database searches were finished in May 2019. The protein queries were RNA dependent RNA polymerase (RdRp) sequences representing every RNA virus family recognized by ICTV , as well program , with thE-value cutoff set to 10−5 and default settings for other parameters. For each potential endogenous virus, the query process was reversed to determine their corresponding phylogenetic group. The nucleotide and amino acid sequences of EVEs are available in the Endogenous copies of the RNA viruses were detected using the TBLASTN algorithm against basal hexapod genomes available in the Whole Genome Shotgun Database (WGS) at the NCBI, using viral protein sequences as queries. The queries involved protein sequences translated from both the virus genomes that were identified for the first time here as well as the reference virus genomes. Comparisons were made using the TBLASTN program , with thhttp://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi), by applying a cut-off E-value of 0.01. Some proteins were compared against SMART (smart.embl-heidelberg.de), InterPro (http://www.ebi.ac.uk/interpro/) and Pfam (pfam.xfam.org) protein domain databases at default parameters.In order to recognize potential protein domains in the protein sequences analysed, we used NCBI CDD database (http://itol.embl.de/) was used for phylogenetic tree annotation  and Whole Genome Sequence (WGS) databases for basal hexapods offers an attractive possibility to obtain the first insight into the diversity of their RNA viromes. We performed the analysis of RNA viruses in 16 transcriptomes and 6 genomes of the springtails (Collembola), silverfish (Zygentoma), diplurans (Diplura) and bristletails (Monocondylia: Archeaognatha) . 12 tranThe most complete set of the RNA viruses was obtained from the springtails, due to the largest number of the transcriptomes. All novel RNA viruses were compared with the known viruses in the NCBI databases. In such a way, we obtained information about the RNA virus family/clade they belong to and their similarity to the already known viruses. To infer their phylogenetic position in the particular RNA viral clade, we used ML phylogenetic analysis. Phylogenies of basal hexapod RNA viruses –3 demonsWe found that basal hexapods possess representatives of 14 out of 24 RNA viral clades . Such RNAnurida maritima. Although this genome is partial, it is segmented. Six segments of reovirus were found and encode RdRp (VP1), VP2, VP3, VP4, VP5 and VP10 proteins  was discovered in insect genomes , which iThe comparison of basal hexapod RNA virome composition with that of insects  demonstrThe basal position of apterygote hexapods in the hexapod tree  is impordsRNA virome of the basal hexapods is represented by three RNA viral clades, while winged insects possess representatives of five viral clades. Some insect orders are without (Orthoptera), with a single  or with just two dsRNA viral clades (Coleoptera). Insect orders with three or four RNA viral clades are Odonata, Hemiptera and Diptera. As evident from the Many insects are known vectors for the dissemination of RNA viruses, such as mosquitoes and many plant pests  . Since sThe research on insect viruses has been very intensive in the last decade . This haHere, we demonstrated that basal hexapods possess 14 out of 24 RNA viral clades, which are the following: Reo, Partiti-Picobirna, Toti-Chryso, Mono-Chu, Bunya-Arena, Orthomyxo, Qinvirus, Picorna-Calici, Hepe-Virga, Narna-Levi, Tombus-Noda, Luteo-Sobemo, Permutotetra and Flavi. Such RNA virome diversity is similar to that of insects and is even higher than in some large insect orders . In thisShi et al. (2016), on both extremes and in the middle of the tree. Instead of the default parameters in homology searching with TBlastN, we also used some modified parameters to find remote homologs or very divergent RNA viruses. However, in both cases we obtained the same set of RNA viruses and no extremely divergent viruses. Despite this, the novel basal hexapod RNA viruses are among the most divergent arthropod RNA viruses; very often they share just 22–40% identity with the already described RNA viruses. It should be noted that the closest relatives of the novel basal hexapod RNA viruses are always from the arthropod hosts.We believe that our approach was sensitive enough to find some of the most divergent arthropod RNA viruses. Due to the high divergence of basal hexapod RNA viruses, we used several representatives of the particular RNA viral family or clade as queries. As a rule, we used three representatives of the RNA viral clade, as defined by EVEs in basal hexapods came from nine RNA viral clades: Mono-Chu, Orthomyxo, Qin, Partiti-Picobirna, Reo, Tombus-Noda, Hepe-Virga, Bunya-Arena and Toti-Chryso ; Data S1Basal hexapods were the earliest splits of hexapod lineages . The sisMany of the RNA viruses might not infect hexapods, but their parasites . The proWhat are these viruses doing to their hosts? Although viruses are parasites, some of them might be mutualists or commensals and their impact on host fitness may be negligible . We werehttp://www.1kite.org) and i5K (arthropodgenomes.org/wiki/i5K/) projects will generate numerous additional genomes and transcriptomes for understudied basal hexapods. These new data may provide additional insights into the RNA virome of the basal hexapod lineages.Our study demonstrated that basal hexapods possess quite a diverse RNA virome and some highly divergent RNA viruses. Going forward, the 1KITE  are red, Diplura are violet, Monocondylia are green, and Zygentoma are blue. The star symbol denotes host taxa that contain endogenous virus copies (EVEs). The best fit model of amino acid substitution for this data set was determined as Blosum62+I+G4 according to the Bayesian information criterion. Most sequences were obtained from the GenBank; species names and accession numbers are included. Sequences from the Click here for additional data file.10.7717/peerj.8336/supp-2Figure S2Each phylogeny provided in this and the other supplementary figures is based on the analysis of the viral RdRP domain. The names of the viruses are marked with different colours based on their host taxonomy; springtails (Collembola) are red, Diplura are violet, Monocondylia are green, and Zygentoma are blue. The star symbol denotes host taxa that contain endogenous virus copies (EVEs). The best fit model of amino acid substitution for this data set was determined as Blosum62+I+G4 according to the Bayesian information criterion. Most sequences were obtained from the GenBank; species names and accession numbers are included. Sequences from the Click here for additional data file.10.7717/peerj.8336/supp-3Figure S3Each phylogeny provided in this and the other supplementary figures is based on the analysis of the viral RdRP domain. The names of the viruses are marked with different colours based on their host taxonomy; springtails (Collembola) are red, Diplura are violet, Monocondylia are green, and Zygentoma are blue. The star symbol denotes host taxa that contain endogenous virus copies (EVEs). The best fit model of amino acid substitution for this data set was determined as Blosum62+I+G4 according to the Bayesian information criterion. Most sequences were obtained from the GenBank; species names and accession numbers are included. Sequences from the Click here for additional data file.10.7717/peerj.8336/supp-4Figure S4Each phylogeny provided in this and the other supplementary figures is based on the analysis of the viral RdRP domain. The names of the viruses are marked with different colours based on their host taxonomy; springtails (Collembola) are red, Diplura are violet, Monocondylia are green, and Zygentoma are blue. The star symbol denotes host taxa that contain endogenous virus copies (EVEs). The best fit model of amino acid substitution for this data set was determined as Blosum62+I+G4 according to the Bayesian information criterion. Most sequences were obtained from the GenBank; species names and accession numbers are included. Sequences from the Click here for additional data file.10.7717/peerj.8336/supp-5Figure S5Each phylogeny provided in this and the other supplementary figures is based on the analysis of the viral RdRP domain. The names of the viruses are marked with different colours based on their host taxonomy; springtails (Collembola) are red, Diplura are violet, Monocondylia are green, and Zygentoma are blue. The star symbol denotes host taxa that contain endogenous virus copies (EVEs). The best fit model of amino acid substitution for this data set was determined as Blosum62+I+G4 according to the Bayesian information criterion. Most sequences were obtained from the GenBank; species names and accession numbers are included. Sequences from the Click here for additional data file.10.7717/peerj.8336/supp-6Figure S6Each phylogeny provided in this and the other supplementary figures is based on the analysis of the viral RdRP domain. The names of the viruses are marked with different colours based on their host taxonomy; springtails (Collembola) are red, Diplura are violet, Monocondylia are green, and Zygentoma are blue. The star symbol denotes host taxa that contain endogenous virus copies (EVEs). The best fit model of amino acid substitution for this data set was determined as Blosum62+I+G4 according to the Bayesian information criterion. Most sequences were obtained from the GenBank; species names and accession numbers are included. Sequences from the Click here for additional data file.10.7717/peerj.8336/supp-7Figure S7Each phylogeny provided in this and the other supplementary figures is based on the analysis of the viral RdRP domain. The names of the viruses are marked with different colours based on their host taxonomy; springtails (Collembola) are red, Diplura are violet, Monocondylia are green, and Zygentoma are blue. The star symbol denotes host taxa that contain endogenous virus copies (EVEs). The best fit model of amino acid substitution for this data set was determined as Blosum62+I+G4 according to the Bayesian information criterion. Most sequences were obtained from the GenBank; species names and accession numbers are included. Sequences from the Click here for additional data file.10.7717/peerj.8336/supp-8Figure S8Each phylogeny provided in this and the other supplementary figures is based on the analysis of the viral RdRP domain. The names of the viruses are marked with different colours based on their host taxonomy; springtails (Collembola) are red, Diplura are violet, Monocondylia are green, and Zygentoma are blue. The star symbol denotes host taxa that contain endogenous virus copies (EVEs). The best fit model of amino acid substitution for this data set was determined as Blosum62+I+G4 according to the Bayesian information criterion. Most sequences were obtained from the GenBank; species names and accession numbers are included. Sequences from the Click here for additional data file.10.7717/peerj.8336/supp-9Figure S9Each phylogeny provided in this and the other supplementary figures is based on the analysis of the viral RdRP domain. The names of the viruses are marked with different colours based on their host taxonomy; springtails (Collembola) are red, Diplura are violet, Monocondylia are green, and Zygentoma are blue. The star symbol denotes host taxa that contain endogenous virus copies (EVEs). The best fit model of amino acid substitution for this data set was determined as Blosum62+I+G4 according to the Bayesian information criterion. Most sequences were obtained from the GenBank; species names and accession numbers are included. Sequences from the Click here for additional data file.10.7717/peerj.8336/supp-10Figure S10Each phylogeny provided in this and the other supplementary figures is based on the analysis of the viral RdRP domain. The names of the viruses are marked with different colours based on their host taxonomy; springtails (Collembola) are red, Diplura are violet, Monocondylia are green, and Zygentoma are blue. The star symbol denotes host taxa that contain endogenous virus copies (EVEs). The best fit model of amino acid substitution for this data set was determined as Blosum62+I+G4 according to the Bayesian information criterion. Most sequences were obtained from the GenBank; species names and accession numbers are included. Sequences from the Click here for additional data file.10.7717/peerj.8336/supp-11Figure S11Within each genome, the outer boxes define the ORF boundaries, while the inner boxes define regions with blast matches to a viral protein or a protein domain whose detailed information is provided in the upper right corner of the figure. Each major homologous protein/domain among different genomes is marked with a different colour.Click here for additional data file.10.7717/peerj.8336/supp-12Figure S12Within each genome, the outer boxes define the ORF boundaries, while the inner boxes define regions with blast matches to a viral protein or a protein domain whose detailed information is provided in the upper right corner of the figure. Each major homologous protein/domain among different genomes is marked with a different colour.Click here for additional data file.10.7717/peerj.8336/supp-13Figure S13Within each genome, the outer boxes define the ORF boundaries, while the inner boxes define regions with blast matches to a viral protein or a protein domain whose detailed information is provided in the upper right corner of the figure. Each major homologous protein/domain among different genomes is marked with a different colour.Click here for additional data file.10.7717/peerj.8336/supp-14Figure S14Within each genome, the outer boxes define the ORF boundaries, while the inner boxes define regions with blast matches to a viral protein or a protein domain whose detailed information is provided in the upper right corner of the figure. Each major homologous protein/domain among different genomes is marked with a different colour.Click here for additional data file.10.7717/peerj.8336/supp-15Figure S15Within each genome, the outer boxes define the ORF boundaries, while the inner boxes define regions with blast matches to a viral protein or a protein domain whose detailed information is provided in the upper right corner of the figure. Each major homologous protein/domain among different genomes is marked with a different colour.Click here for additional data file.10.7717/peerj.8336/supp-16Figure S16Within each genome, the outer boxes define the ORF boundaries, while the inner boxes define regions with blast matches to a viral protein or a protein domain whose detailed information is provided in the upper right corner of the figure. Each major homologous protein/domain among different genomes is marked with a different colour.Click here for additional data file.10.7717/peerj.8336/supp-17Data S1Click here for additional data file.


Arabidopsis thaliana RNA 5′ end annotations and quantify microRNA-mediated cleavage events across five different flower tissues.Diverse RNA 5′ ends are generated through both transcriptional and post-transcriptional processes. These important modes of gene regulation often vary across cell types and can contribute to the diversification of transcriptomes and thus cellular differentiation. Therefore, the identification of primary and processed 5′ ends of RNAs is important for their functional characterization. Methods have been developed to profile either RNA 5′ ends from primary transcripts or the products of RNA degradation genome-wide. However, these approaches either require high amounts of starting RNA or are performed in the absence of paired gene-body mRNA-seq data. This limits current efforts in RNA 5′ end annotation to whole tissues and can prevent accurate RNA 5′ end classification due to biases in the data sets. To enable the accurate identification and precise classification of RNA 5′ ends from standard and low-input RNA, we developed a next-generation sequencing-based method called nanoPARE and associated software. By integrating RNA 5′ end information from nanoPARE with gene-body mRNA-seq data from the same RNA sample, our method enables the identification of transcription start sites at single-nucleotide resolution from single-cell levels of total RNA, as well as small RNA-mediated cleavage events from at least 10,000-fold less total RNA compared to conventional approaches. NanoPARE can therefore be used to accurately profile transcription start sites, noncapped RNA 5′ ends, and small RNA targeting events from individual tissue types. As a proof-of-principle, we utilized nanoPARE to improve  Diverse RNA 5′ ends are generated during and after transcription as the result of a variety of gene regulatory functions. Alternative transcription start sites (TSSs) can generate RNA isoforms that differentially impact cellular activities. Alternative TSSs have also been demonstrated to affect downstream translation and protein function through inclusion or exclusion of regulatory N-terminal peptides such as upstream open reading frames or protein localization sequences . Post-trArabidopsis thaliana (Arabidopsis) where the phytochrome photoreceptor regulates alternative promoter usage in a light-dependent manner that ultimately leads to gene products with distinct functions and subcellular localization (Next-generation sequencing (NGS)-based methods have recently been used to identify RNA 5′ ends genome-wide. For example, TSS profiling using cap analysis of gene expression (CAGE) led to the annotation of TSSs from polyadenylated mRNA and long noncoding RNA . TSS prolization . Methodslization .Cell-type–specific TSSs and sRNA-mediated cleavage events contribute to the diversification of cellular transcriptomes and thus can impact cellular differentiation . HoweverTo profile RNA 5′ ends genome-wide from low amounts of total RNA, we developed an NGS-based method called nanoPARE  . Tn5 traTemplate switching readily occurs at the 5′ ends of RNA templates with or without 7-methylguanosine (m7G) cap structures . We reasArabidopsis floral buds in biological triplicate and reproducibly identified a total of 22,852 5′ end features from polyadenylated RNA in at least two of the three biological replicates . Reverse transcription produces untemplated cytosines at the template 5′ terminus that can base-pair with a m7G cap to yield an untemplated upstream guanosine (uuG) in the cDNA between the TSO and genome-matching sequence . We analyzed the total proportion of reads in all 5′ end features that contained uuG, and we could observe a striking bimodal distribution, with most 5′ end features  containing >10% uuG reads . The 5′ ends of chloroplast and mitochondrial RNA do not possess m7G caps . Several noncapped features mapping to pre-tRNA and rRNA loci, which are not transcribed by Pol II, could also be identified . While these products normally do not possess a poly(A) tail, a subset will be transiently polyadenylated by the TRAMP complex prior to their degradation  and/or xrn4-5 floral buds were combined to produce a unified set of 5′ end features . Because XRN4 is restricted to the cytoplasm , were not increased in xrn4-5 floral buds relative to wild type. In contrast, these features were sensitive to Xrn1 digestion in vitro .Protein-coding mRNA also displays a distinct distribution of capped and noncapped 5′ end features. Among capped features overlapping nuclear protein-coding genes, 95% mapped to the annotated 5′ UTRs E. Noncapytoplasm , noncytoxrn4-5 mutants, concomitant with a relative increase in reads contained by capped features . Together, these trends predict an increase in full-length transcripts with 5′-monophosphates in xrn4 mutants. Indeed, the accumulation of full-length decapped mRNA has been reported for some transcripts in xrn4 mutants . Overall, the capped and noncapped 5′ features identified with nanoPARE support the existing model of XRN4 as a general RNA decay factor that acts downstream from decapping.Consistent with wild-type XRN4 digesting full-length decapped mRNA, noncapped features upstream and adjacent to stop codons were globally decreased in relative abundance in  mutants . We reanescences  and founArabidopsis roots . Therefore, nanoPARE capped features represent genuine transcription start sites and can be used for transcription start site annotation with as little as 10 pg of input RNA.To test the reproducibility of nanoPARE to detect 5′ end features from low-input RNA, we generated nanoPARE libraries from a dilution series of the original floral bud total RNA in triplicate: 1 ng, 100 pg, and 10 pg of total RNA input, which is typically less than or equal to the amount of total RNA found in a single cell . We perfis roots . As a bafinition A. The mofinition A. Furthefinition A,B. Finafinition C. Remarkfinition A,B. Multtrans-acting siRNAs (tasiRNAs) in libraries prepared from 5 ng of total RNA isolated from floral buds. The 5′ ends of nanoPARE reads were enriched at cleavage sites pairing to highly complementary miRNAs, including those from previously characterized miRNA cleavage sites in wild-type (Col-0) flowers . As expected for sRNA-directed cleavage products that are 5′ monophosphorylated, the number of nanoPARE reads at cleavage sites were reduced when RNA was incubated with the Xrn1 exoribonuclease prior to library generation. Conversely, nanoPARE read enrichment at cleavage sites was increased in xrn4-5 exoribonuclease mutants which stabilize sRNA cleavage products . EndCut uses two metrics to calculate this likelihood: the level of sRNA-target complementarity (Allen score) and the number of read 5′ ends at predicted cleavage sites divided by the maximum number detected at a single site within 20 or 50 nt of flanking transcribed regions (fold change).In addition to biological variation between tissues or genotypes, variability between nanoPARE/PARE libraries can also be largely due to technical differences in RNA quality and quantity, as well as library complexity and sequencing depth. Therefore, we developed software called EndCut that employs empirically determined null models from randomized versions of each sRNA to compute the likelihood that nanoPARE read 5′ ends are enriched at predicted target sites greater than expected by chance in each library  . The mean number of miRNA target sites identified upon Xrn1 treatment was significantly reduced sevenfold and significantly increased 1.6-fold in xrn4-5  . As expected for miRNA cleavage sites, the number of nanoPARE reads at these sites was significantly decreased 9.7-fold upon Xrn1 treatment (Col-0 [+Xrn1]) or significantly increased 1.8-fold in S tests) B. Moreovral buds . We ident-tests) E. We alsectively G.Supplemental Data S5). In contrast, both the number of significantly detected tasiRNA target sites and reads mapping to cleavage sites were increased in xrn4-5 mutants  had been previously validated by a modified 5′ RACE technique , while five of the remaining nine have genetic or expression data indicating that they are sRNA targets  floral buds, including two of which were detected in at least two biological replicates. Similar to what was observed for miRNA cleavage sites, tasiRNA cleavage sites significantly detected in Col-0 (−Xrn1) samples had reduced numbers of reads mapping to cleavage sites upon Xrn1 treatment .PARE methods capture sRNA cleavage products through a series of adapter-RNA ligations, Type IIS restriction enzyme digestions, and PCR amplifications . BecauseArabidopsis possesses two A genes, two B genes, and a single C gene whose transcript spatial distributions are maintained through late flower development except for APETALA2 (AP2) mRNA, which has been observed in all four whorls of mature flowers . While the target cleavage sites directed by three miRNAs  are robustly detected across all tissues examined, over half of the high-confidence interactions were enriched in specific tissues. To better estimate differences in miRNA-guided cleavage activity, we calculated the proportion of nanoPARE signal at the cleavage site relative to the total cleaved and capped (full-length) signal for each gene . For most miRNA target interactions, the proportion of cleaved transcripts varied strongly between tissues. For example, we found that AUXIN RESPONSE FACTOR 6 and 8 (ARF6/8) transcripts were preferentially cleaved in sepals, anthers, and ovules, which is consistent with both MIR167 transcript levels as well as previous reports (GRF1/2/3/4/7/8/9) to the developing carpel (GRF1) was identified in wild-type flowers, six were identified in xrn4-5 mutant flowers, indicating that the cleavage products from this gene family are efficiently cleared from wild-type cells . Despite their transient nature, miR396-directed GRF1 cleavage products accumulated to a higher proportion in noncarpel tissues than in stigmas or ovules . Lastly, genetic data supports a model whereby miR172 represses AP2 in whorl 3 to maintain stamen identity  seeds were in Col-0 accession backgrounds and were grown in climate-controlled growth chambers with 20°C–22°C temperature and 16 h light/8 h dark cycle. The dcl234 mutants were composed of dcl2-1, dcl3-1, and dcl4-2 alleles . Stage 13 flowers were collected in 1 mL of 500 µM DTSSP   with 1× PBS, pH 7.4, vacuum-infiltrated for 5 min, and incubated for 10 min. Individual floral tissues were dissected under a binocular microscope on a silanized slide and snap-frozen in liquid nitrogen. Tissues were then homogenized using Mixer Mill MM 400 (Retsch), and the resulting pellets were resuspended in 300 µL TRIzol (Life Technologies). Total RNA was extracted using a Direct-zol kit (ZymoResearch) according to the manufacturer's instructions. RNA integrity was assessed by a Fragment Analyzer (AATI) using the standard RNA sensitivity kit (DNF-471).Supplemental Methods. In brief, cDNA library preparation from 5 ng or less total RNA was carried out according to the original Smart-seq2 method . PCR reaction products with Tn5.1/TSO enrichment oligonucleotide and Tn5.2/TSO enrichment oligonucleotide primer sets were pooled and purified using AMPureXP DNA beads.A detailed protocol can be found in 2 method . cDNA waFor in vitro biochemical degradation of 5′ monophosphate-containing RNA, 100 ng of total RNA were treated with XRN1 exoribonuclease (NEB) for 60 min at 37°C in a 20-µL reaction volume containing 1× NEB Buffer 3 and 1 U of XRN1. The equivalent of 5 ng total RNA (1 µL of XRN1-treated reaction) was used for Smart-seq2 cDNA synthesis without additional purification.Supplemental Table S1; Supplemental Data S1).To control for library quality, final nanoPARE libraries were checked on an Agilent DNA HS Bioanalyzer Chip. Libraries with size ranges between 150 and 800 bp were diluted and sequenced to 10–15 million single-end 50-bp reads per sample using a custom sequencing primer (TSO_Seq) and a custom P5/P7 index primer mix on an Illumina HiSeq 2500 instrument (Mapping of 5P and BODY reads to the genome (EndMap)5P end feature identification (EndGraph)Classification of capped and noncapped 5P features (EndClass)Transcript-level output of read noncapped reads (EndMask)The nanoPARE analysis pipeline was written to identify capped and noncapped 5′ end features in the genome using paired nanoPARE (5P) reads Smart-seq2 (BODY) reads. Analysis is divided into four major steps:Arabidopsis thaliana TAIR10 genome  the read depth for all positions with >1 read was set to 1, because RNA seq reads are not expected to have even coverage at all genomic locations. After bias correction, reads that mapped to more than one genomic location were assigned via a “rich-get-richer” algorithm similar to that employed by the software MuMRescue and MuMRescueLite .After alignment to the genome, a bias correction algorithm was applied to the aligned BAM file to adjust for sequence-specific biases in the BODY and 5P libraries. The bias correction method defined by Wang et al.  was usedscueLite . First, S) was estimated to normalize the read depth of the 5P library against the BODY library using the formulan is the total number of transcripts, TPMi is the abundance of a transcript in transcripts per million, Li is the length of a transcript in nucleotides, F is the mean fragment length of the BODY library, RB is the total number of mapped BODY reads, and RE is the total number of mapped 5P reads. Then, a Laplace kernel with a bandwidth of 15 nt was fit over the set of values (ER * S) – BR, where ER is the set of 5P end read counts and BR is the set of body read counts. Regions of continuous positive density were extracted and written as discrete features to a bed file.Discrete 5P features were identified genome-wide via subtractive kernel density estimations. bedGraph files output from EndMap corresponding to a sample's 5P and BODY libraries were evaluated together. First, strand invasion artifacts  were masIf a 5P experiment was designed with multiple replicates, EndClass merged all 5P features that could be reproducibly identified in ≥2 replicates. Then, the presence of a m7G cap was predicted for each replicable feature by calculating the proportion of reads containing upstream untemplated guanosine (uuG). A feature was considered capped if ≥10% of all reads from a sample type that map within the feature contained uuG; otherwise, the feature was considered noncapped.EndMask prepared a bedGraph file of 5P read positions relative to the start site of the dominant isoform of each gene in the reference annotation. Dominant isoforms were defined as the transcript isoform containing the most mapped reads. For nanoPARE libraries, this transcript-level bedGraph was generated with a cap-masked input in which 5P reads contained within replicable capped 5P features were discarded.i.fa files, where i is an integer between 0 and 999. For annotated miRNA, tasiRNA and the corresponding 1000 randomized variants for each miRNA/tasiRNA, GSTAr.pl (https://github.com/MikeAxtell/GSTAr) was used to predict target sites in transcript models annotated as protein-coding genes, transposable element genes, or other RNAs . Target sites were determined based on the level of complementarity between sRNAs and transcripts computed using previously developed criteria based on the frequency and position of the miRNA-target duplex mismatches  (Supplementary Data S1), but alignments overlapping capped features were not excluded from downstream analyses.Sequences of miRNAs and tasiRNAs annotated in TAIR10 or miRBase21  were sel scores) . As descECDFFC) and Allen scores (ECDFAS). These were then used as null models to test whether the observed cleavage site fold changes were not equal to or lesser than ECDFFC, as well as if the observed site Allen scores were not equal to or greater than ECDFAS. Final P-values were computed for each site by combining these two P-values using Fisher's combined probability test and then adjusted for multiple testing using the Benjamini-Hochberg method. For our analyses, we defined significant cleavage sites that had adjusted P-values < 0.05, fold changes > 1.0, and that were also represented by at least one read per 10 million transcriptome-mapping reads.Predicted target sites and EndGraph output were used by EndCut_step1.sh to quantify the number of reads at predicted target sites and in adjacent 20-nt or 50-nt regions on the sense strand of the same transcript. Adjacent sites within 1 nt of predicted cleavage sites were not considered in order to not penalize sites for sRNA isoforms with slightly offset target recognition sites. The local enrichment of nanoPARE read 5′ ends at predicted cleavage sites relative to surrounding transcribed regions, or fold changes, were calculated by dividing the numbers of nanoPARE read 5′ ends at predicted cleavage sites +1 by the maximum numbers of reads in adjacent transcript regions +1. Allen scores were also assigned to each predicted cleavage site detected. For each randomized sRNA control set, EndCut_step2.R computed empirical cumulative distribution functions of fold changes (https://www.ncbi.nlm.nih.gov/geo/) under accession number GSE112869. All software code is publicly available at GitHub (https://github.com/Gregor-Mendel-Institute/NanoPARE) and is available as Supplemental Code S1.All sequencing data generated in this study have been submitted to the NCBI Gene Expression Omnibus (GEO; M.A.S., M.J.K., and M.D.N. were employed by the Gregor Mendel Institute, a nonprofit research organization that has filed a patent application on the nanoPARE technology described in this work.


Development of a robust automated platform for enrichment of extracellular vesicles from low sample volume that matches the needs for next-generation sequencing could remove major hurdles for genomic biomarker discovery. Here, we document a protocol for urinary EVs enrichment by utilizing an automated microfluidic system, termed acoustic trap, followed by next-generation sequencing of microRNAs (miRNAs) for biomarker discovery. Specifically, we compared the sequencing output from two small RNA library preparations, NEXTFlex and CATS, using only 130 pg of input total RNA. The samples prepared using NEXTflex was found to contain larger number of unique miRNAs that was the predominant RNA species whereas rRNA was the dominant RNA species in CATS prepared samples. A strong correlation was found between the miRNA expressions of the acoustic trap technical replicate in the NEXTFlex prepared samples, as well as between the acoustic trap and ultracentrifugation enrichment methods. Together, these results demonstrate a robust and automated strategy for biomarker discovery from small volumes of urine. Extracellular vesicles (EVs) are secreted cellular products that harbor proteins, lipids, DNA and RNA, especially small RNA such as microRNA (miRNA) within the phospholipid bilayer that protects them from the degradative effect of circulating proteases and nucleases . Recent At present, the established EV enrichment method is differential centrifugation . UnfortuCurrently, next-generation sequencing is the most widely used method for miRNA discovery due to the high sensitivity and ability to detect different isoforms. There are challenges associated with miRNA sequencing, mainly during library construction owing to the short length, secondary structure, and high GC content of miRNA –12. In aHere we investigated a comprehensive biomarker discovery pipeline for miRNA derived from both small and large urinary EVs. We utilized the acoustic trap instrument to enrich urinary EVs and then compared the libraries obtained from two commercially available, low-input compatible, small RNA library kits, followed by next generation sequencing. In order to assess if the acoustic trap could replace ultracentrifugation as the preferred EV-enrichment method, we investigated the reproducibility of acoustic trapping and compared the miRNAs content of the EVs obtained using the different enrichment methods.pp and 4.2 MHz. Next, 12 μm seeding particles were trapped and washed with PBS follow by aspiration of 0.75 mL of urine sample at 15 μLmin-1 into the capillary for EV enrichment then washed with 200 μL PBS prior to elution with 30 μL PBS. A total of 9.75 mL of urine samples were trapped in eleven fractions, totaling 330 μL of purified sample volume. Nanoparticle-tracking analysis (NTA) was performed using NanoSight LM10  on urine samples diluted eight-times (0.125x of stock) with PBS using continuous flush mode and measured five times. Camera level was set to ten and gain set to one.A single spot urine sample collected from a heathy male donor with written consent and approval by Regional Ethical Review Board in Lund # 2013–400 was immediately centrifuged at 2,000xg for ten minutes at room temperature to remove cell debris while preserving the small and large EVs in the sample. A total of 72 mL of supernatant was aliquoted for EVs enrichment by ultracentrifugation; spun twice at 100,000xg for 1.5 h at 4°C with a PBS wash in-between centrifugation using a SW41-Ti swing bucket rotor in an Optima XE-90 . The pellets were resuspended in 330 μL PBS and stored at -80°C. Acoustic trapping was performed as described previously [8 copies of cel-miR-39 synthetic spike-in  was added before RNA extraction. The quantity and size profile of the extracted RNA were determined by Qubit RNA HS assay  and the Pico RNA chip of the Bioanalyzer  respectively. Quantitation of miRNA levels was performed by qRT-PCR using TaqMan assay  with cel-miR-39, -16, -21, and -24 specific primers (TaqMan microRNA Assay) on QuantStudio 7K system . The RNA concentration of the acoustic trap was estimated by the following formula:AcT is the estimated RNA concentration of acoustic trap sample, CUC is the RNA concentration of ultracentrifugation sample determined by Qubit RNA HS kit, n is the number of miRNA excluding the spike-in and Enriched EVs were treated with 10 μg/mL of RNase A for 10 min at 37° prior to RNA extraction with Single Cell RNA Extraction kit  per manufacturer’s plasma sample protocol RNA were eluted in a total of 30 μL of elution buffer per sample. Purified RNA was used as a positive control for RNase A activity . To estiThree libraries were constructed using NEXTflex small RNA library kit  and the CATS small RNA library . The three libraries consist of two technical replicates from the acoustic trap and an ultracentrifugation sample per manufacturer’s protocol using an estimated 130 pg of input RNA for both acoustic trap replicates and ultracentrifugation. Briefly, NEXTFlex libraries were constructed by 3’- and 5’-adapters ligations followed by reverse transcription and 22 cycles of PCR with barcodes. Cleanup was performed with manufacturer provided kit. CATs libraries were constructed by dephosphorylation and polyadenylated at the 3’-end followed by cDNA strand synthesis with poly(dT) primer containing the P7 adapter sequence. P5 adapter sequence is incorporated onto the 5’-end of the RNA after template switching follow by PCR of 15 cycles. Cleanup was performed using Agencourt AMPure XP . The size, concentration and adapter-dimer fraction of the cDNA products were calculated from the electropherogram of the Bioanalzyer and Qubit RNA HS assay . Paired-end sequencing of 75 bp was performed on the NextSeq 500/550 platform (Illumina) using a mid-output flow cell with 10% PhiX spike-in.Fold change from qRT-PCR were calculated using the ΔΔCt follow by log2 transformation in quadruplicates. Adapters were trimmed per manufacturer protocol. Sequences were annotated using the Unitas pipeline v1.5.2 allowing one mismatch and greater than 15 nt in length to miRbase v22, human tRNA piRBase v2.0, coding gene in ensembl Database release 92 . Set anaEVs enriched using acoustic trapping or ultracentrifugation were investigated by nanoparticle tracking analysis. Size distribution analysis showed that the mean diameter (Dv50±SD) of EVs enriched using acoustic trapping (149±14) is similar to that of the input (143±4), whereas EVs enriched by ultracentrifugation are larger (198±8). . Owing tThe cDNA libraries were produced from an estimated 130 pg of total RNA. Both kits produced libraries with fluorescent peaks corresponding to the miRNA fraction of ~150 nt, which is the expected size for adapters with insert . Quantif6, 1.5x106 and 11x106 reads were obtained for acoustic trap replicate 1, 2 and ultracentrifugation respectively for NEXTFlex libraries and 0.74x106, 0.60x106, 0.94x106 reads for CATS libraries after adapter trimming. From the NEXTFlex libraries, 23%, 15% and 83% of the reads were mappable . However, a similar comparison for miRNAs in EVs extracted using acoustic trap could not be performed due to the limited number of miRNAs found in CATS libraries.A comparison of the miRNAs identified in the ultracentrifugation sample of the NEXTFlex and CATS libraries showed that 114 miRNAs overlap while 393 miRNAs are exclusive to the NEXTFlex prepared samples and 28 miRNAs exclusive to CATS prepared samples . The miR-16  Pure RNA after RNase A treatment at 37° for 10min shows complete degradation. b) RNA extraction efficiency of acoustic trap and ultracentrifugation determined by spike-in of cel-miR-39 prior to RNA isolation. c) miRNA are detectable from aoucstic trap and ultracentrifugation samples after RNase A treatment.(PDF)Click here for additional data file.S2 Figa) NEXTflex prepared libraries with acoustic trap replicates on the left and ultracentrifugation samples on the right. The libraries showed maximal peak (highlighted) at the expected miRNA size of ~150bp (insert + adapters) with calculated adapter-dimer (AD) fractions displayed. b) CATS prepared libraries showed maximal peak (highlighted) at the expected miRNA size of ~154bp (insert + adapters) and AD fractions displayed.(PDF)Click here for additional data file.S3 Figa) Venn diagram of the miRNAs identified in the ultracentrifugation samples showed 114 common and 421 exclusive miRNAs between the NEXTFlex and CATS preparations. b) Spearman correlation analysis of the ultracentrifugation miRNA expression derived from NEXTFlex and CATS preparations showed significant correlation, rho = 0.46.(PDF)Click here for additional data file.S4 Fig(PDF)Click here for additional data file.S5 Figa) Analysis of common and exclusive miRNAs found in the acoustic trap, ultracentrifugation and Rodriguez et al. dataset b) Spearman correlation resulted in Rho of 0.64 and 0.72 respectively for acoustic trap, left and ultracentrifugation, right.(PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S5 TableYellow hightlighted cells represents miRNA found in AcT samples but not UC that were validated and blue highlights are differentially enriched miRNA in AcT samples used for validation.(PDF)Click here for additional data file.S6 Table(PDF)Click here for additional data file.S7 Table(PDF)Click here for additional data file.