When expressed in E. coli, the DNB aptamer could be labelled and visualized with different-coloured fluorophores and therefore it can be used as a genetically encoded tag to image target RNAs. Furthermore, combining contact-quenched fluorogenic probes with orthogonal DNB (the quencher-binding RNA aptamer) and SRB-2 aptamers (a fluorophore-binding RNA aptamer) allowed dual-colour imaging of two different fluorescence-enhancing RNA tags in living cells, opening new avenues for studying RNA co-localization and trafficking.In order to gain deeper insight into the functions and dynamics of RNA in cells, the development of methods for imaging multiple RNAs simultaneously is of paramount importance. Here, we describe a modular approach to image RNA in living cells using an RNA aptamer that binds to dinitroaniline, an efficient general contact quencher. Dinitroaniline quenches the fluorescence of different fluorophores when directly conjugated to them via ethylene glycol linkers by forming a non-fluorescent intramolecular complex. Since the binding of the RNA aptamer to the quencher destroys the fluorophore-quencher complex, fluorescence increases dramatically upon binding. Using this principle, a series of fluorophores were turned into fluorescent turn-on probes by conjugating them to dinitroaniline. These probes ranged from fluorescein-dinitroaniline (green) to TexasRed-dinitroaniline (red) spanning across the visible spectrum. The dinitroaniline-binding aptamer (DNB) was generated by  However, the absence of an effective parallel method to image RNA in vivo . The RN vivo  that binds to 3,5-difluoro-4-hydroxybenzylidine imidazolinone (DFHBI), a derivative of the GFP chromophore, has been developed and used for in vivo RNA imaging, which was the first successful attempt to image RNA with small molecules in live cells   have beeve cells –20. Anotve cells . Lately,ve cells . Contactve cells . The advve cells  or PeT-. These probes were fluorescein-dinitroaniline (FL-DN), rhodamine green-dinitroaniline (RG-DN), tetramethylrhodamine-dinitroaniline (TMR-DN), sulforhodamine-dinitroaniline (SR-DN) and TexasRed-dinitroaniline (TR-DN) Figure . We hypo®310-25 LiChroprep® RP-18 (40–63 μm) column (Merck) and compounds were eluted with a mixture of acetonitrile and water containing 0.1% trifluoroacetic acid. MALDI-TOF mass spectrometry  was used to monitor the progress and success of the reactions. High resolution mass spectra were recorded on a Bruker microTOFQ-II ESI mass spectrometer. RNA concentrations were determined by a Qubit® 2.0 fluorometer (Life Technologies). Fluorescence measurements were performed with a JASCO FP-6500 spectrofluorometer. Absorbance spectra were recorded on a Cary 50 UV-Vis spectrophotometer (Varian). Agarose gels were stained with ethidium bromide and visualized by UV illumination using an AlphaImager™ 2200.Unless otherwise stated, chemicals were purchased from Sigma–Aldrich, Thermo Scientific or Invitrogen and used without further purification. Reactions were typically performed in anhydrous solvents and under normal atmosphere. The reaction progress was monitored by TLC, visualized under UV-light or by staining with blue-shift reagent. Reverse phase HPLC purifications were performed on a LobarIn vitro transcriptions were performed as follows: 0.5 μM of dsDNA template was added in transcription buffer  along with 10 mM DTT, 0.01 mg/ml BSA, 4 mM of ATP, CTP, UTP and GTP. The transcription reaction was doped with 50–100 μCi of radioactive CTP . 1 μM of T7 RNA polymerase (lab prepared stock) was added and the transcription reaction was incubated at 37°C for 4 h. The transcription reaction was purified on a 10% denaturing polyacrylamide gel, eluted in 0.3 M Na-acetate (pH 5.5) overnight and iso-propanol precipitated. The pellets were washed with 75% ethanol and dissolved in Millipore water. The RNA was folded prior to the binding step by incubating the RNA at 75°C for 2 min, followed by controlled cooling to 25°C over 15 min. Then, one-fifth volume of 6X selection buffer  was added and the aptamer was incubated at 25°C for additional 15 min. To remove RNAs that bound to the affinity resin, the RNA library was first incubated with mock resin for 30 min at 25°C. The unbound RNA obtained after mock treatment was incubated with dinitroaniline-(PEG)3-amine-functionalized resin for 30 min at 25°C. The resin was washed with 12 volumes of 1X selection buffer and bound RNA was eluted with 5 mM EDTA by heat denaturation. The bound RNA was ethanol precipitated and dissolved in MilliQ water. For the reverse transcription (RT) reaction, 5 μM primer B and 0.5 mM dNTPs were added to the dissolved RNA and heated at 65°C for 5 min. After cooling down on ice, 5 mM DTT, 1X first-strand buffer  and 10 U/μl of RT enzyme  were added and the reaction was incubated at 53°C for 1 h. For PCR amplification of the selected species, the following reagents were added directly to the reverse transcription reaction: 1X PCR buffer 2SO4, 0.01% Tween 20), 5.25 mM MgCl2, 5 μM forward primer and 3.75 μM reverse primer, 0.375 mM of each dNTP and 0.1 U/μl Taq polymerase (Rapidozyme). DNA was amplified under the following conditions: 94°C/1 min, 52°C/1 min, 72°C/1 min with nine additional cycles from step 2 and a final amplification at 72°C/20 min. Prior to the start of the next round, the RT-PCR product was purified via a Qiagen PCR purification kit.In order to increase the stringency of the selection for evolving high-affinity binders, biotinylated dinitroaniline was synthesized  to allow for a sequential decrease in the amount of ligand in each round. The concentration of the biotinylated ligand used in round 9 was 100 μM and was decreased subsequently in next rounds. Streptavidin, immobilized on Agarose CL-4B (Fluka) was used as the solid support for affinity binding. The SELEX protocol was the same as described above except that the elution was performed specifically with 20 mM DTT which cleaves the dithiol group present in the biotinylated ligand (DN-SS-Biotin), releasing the resin-bound RNA while biotin remains bound to the streptavidin resin.2 (22 mM), Triton-X-100 (0.01%), BSA (40 μg/ml), pyrophosphatase (1 U/ml) and T7 RNA polymerase . Transcription was carried out for 4 h at 37°C, and then the reaction mixture was treated with DNaseI (50 U/ml) for 30 min at 37°C. RNA was purified by electrophoresis on a 10% denaturing polyacrylamide gel and excised from the gel. The excised gel was incubated in sodium acetate buffer  overnight. Eluted RNA was ethanol-precipitated and dissolved in MilliQ water. RNA samples were stored at −20°C.Template DNA for wt-DNB or DNB aptamer (0.5 μM) was added into a transcription mixture containing NTPs (4 mM each), DTT (10 mM), spermidine (1 mM), Tris–HCl , MgClKD) for the RNA–probe complexes were determined by measuring the increase in fluorescence as a function of increasing RNA concentration in the presence of a fixed amount of the probe (100 nM) at 25°C. Just before the measurements, RNA was folded in the selection buffer as mentioned before. The excitation (Ex) and emission (Em) wavelength used for various probes were as follows: FL-DN , RG-DN , TMR-DN , SR-DN  and TR-DN . A bandwidth of ±5 nm for both excitation and emission filters was used in all measurements.Dissociation constants  was first saturated with SR-DN (1 μM) and the decrease in fluorescence was measured as a function of increasing concentration of dinitroaniline-amine. The ICterature .m is the slope of the line obtained from the plot of the area under the fluorescence emission spectrum versus absorbance, n is the refractive index of the solvent and the subscript R refers to the reference fluorophore of known quantum yield.Sulforhodamine 101  and fluoE. coli cells (Invitrogen) were transformed with 50 ng of plasmid DNA expressing the tRNA scaffold  was added and cells were shaken for 3–4 h at 37°C. Then, 0.2 ml of the culture was removed, pelleted, washed and resuspended in 1 ml of live-cell imaging solution (Invitrogen) supplied additionally with 5 mM MgSO4 and 20 mM glucose. 400 μl of this suspension was transferred in to a poly-d-lysine-coated 4-well glass chamber and incubated at 37°C for 30 min. The cell suspension was removed and the wells were washed twice gently with the live-cell imaging solution. The cells were incubated with 1 μM of various probes in live-cell imaging solution at 37°C for 5 min. An inverted Nikon eclipse Ti microscope equipped with 100X oil objective was used for imaging and the image was background corrected using ImageJ software.BL21-DE3 star scaffold  or the dIn vitro selection (SELEX) was performed to evolve RNA aptamers that bind to dinitroaniline with a library containing ∼2 × 1015 DNA molecules . We prepared a partially structured DNA library containing two fixed primer binding sites flanking a 64-nucleotide region that consists of two 26-base random stretches separated by a 12-base constant region which forms a stable stem–loop  (ure S1B) . The DNAure S1B)  and the KD of 1.4 μM and was named as wt-DNB . Again, transcribed sequences were screened against SR-DN to identify the best sequence giving the highest fluorescence enhancement. The best clone identified showed 56-fold fluorescence enhancement when bound to SR-DN with a Truncation experiments revealed a 75-nucleotide minimal domain (named DNB), obtained by deleting the primer binding regions from both ends Figure . FurtherE. coli total RNA. The fluorogenic probes FL-DN, RG-DN, TMR-DN, SR-DN and TR-DN showed 5-, 6-, 73-, 56- and 15-fold fluorescence enhancement upon binding to the aptamer, respectively  was evaluated in a binding assay. The fluorescence value of the respective fluorophore-dinitroaniline probe (1 μM) in the presence of excess DNB (10 μM) was measured and divided by the fluorescence of the probe in KD) between the probes and DNB by titrating a solution of the probes (100 nM) with increasing amounts of DNB  in a competition experiment as 100 ± 14 nM  and very high fluorescence turn-on ratios . In addition, we investigated the fluorescence quantum yields of the free probes as well as the DNB-bound probes Table . As expe2+ concentrations, and the fluorescence intensity decreased to 80% and 60% in the presence of 0.5 and 0.25 mM magnesium, respectively .Moreover, DNB aptamer was folded in the presence of different concentrations of magnesium ions and the fluorescence emission measured upon addition of TMR-DN. Only the correctly folded fraction of the DNB aptamer would bind to the probe, resulting in a fluorescence increase. The highest fluorescence signal (100%) was observed at 1 mM and higher MgTo determine the melting temperature of the DNB aptamer, DNB aptamer and TMR-DN probe were mixed and the fluorescence intensity measured at different temperatures. The melting temperature was determined to be 43°C, indicating that ∼80% of the aptamer is correctly folded when imaged at 37°C .Escherichia coli bacteria were transformed with a plasmid expressing the DNB aptamer embedded within the tRNA scaffold (pET28-DNB)  . As a neT28-DNB) . Dependip-nitrobenzylamine (MN), to yield the probe SR-MN for exclusive labelling of the SRB-2 aptamer  were significantly quenched via contact quenching and showed very low fluorescence quantum yields in aqueous solution. However, in the presence of the quencher binding aptamer (DNB), fluorescence increased dramatically due to the disruption of the non-fluorescent complex formed between the fluorophore and dinitroaniline. The use of a high-affinity, specific quencher-binding aptamer (DNB) to restore the fluorescence of a palette of fluorogenic probes provides the important opportunity to select an appropriate fluorophore for the specific requirements of an experiment.in vitro, however the mechanisms of quenching were significantly different from the one used here. Murata et al. developed a method for real-time detection of mRNA transcripts in vitro  (Quencher binding aptamers were previously used for detection of RNA in vitro  by usingin vitro . The speer (PeT) . Both FRWe furthermore demonstrated that this strategy in combination with a fluorophore-binding aptamer (SRB-2) could also be used for dual-colour imaging of RNA inside live bacteria, thereby facilitating research on RNA–RNA interactions and co-localization of RNAs in a cellular environment. Importantly, the DNB/DN probe combination is not only fully orthogonal to the SRB-2 system, but also to many other commonly used RNA imaging methods such as MS2-GFP or the Spinach system. Therefore, it would allow for efficient multiplexing as spectral bleed-through can be minimized by choosing an appropriate fluorophore with orthogonal emission properties. Previously, it was shown that, despite lacking organelles, bacterial cells can spatially organize not only proteins but also RNAs such that the cell interior is functionally compartmentalized ,35. Thusin vivo imaging of target RNAs. In addition, TMR-DN and SR-DN probes when bound to DNB are about ∼2-fold brighter than GFP (Table in vivo.Furthermore, it is noteworthy to state that DNB aptamer is able to fold properly in the presence of biologically relevant magnesium concentrations and its melting temperature is significantly higher than the physiological temperature. Therefore, it is a very promising tag for FP Table , and theIn conclusion, our strategy enables imaging of highly abundant target RNAs in live bacterial cells. However, imaging RNAs that are scarcely present in the cells requires further improvement of the methodology to increase sensitivity. Tandem repeats of RNA tags have been previously used to image low-abundance RNAs in cells successfully –38. Comb


Arabidopsis thaliana, abundant 24 nucleotide small interfering RNAs (24 nt siRNA) guide the cytosine methylation and silencing of transposons and a subset of genes. 24 nt siRNA biogenesis requires nuclear RNA polymerase IV (Pol IV), RNA-dependent RNA polymerase 2 (RDR2) and DICER-like 3 (DCL3). However, siRNA precursors are mostly undefined. We identified Pol IV and RDR2-dependent RNAs (P4R2 RNAs) that accumulate in dcl3 mutants and are diced into 24 nt RNAs by DCL3 in vitro. P4R2 RNAs are mostly 26-45 nt and initiate with a purine adjacent to a pyrimidine, characteristics shared by Pol IV transcripts generated in vitro. RDR2 terminal transferase activity, also demonstrated in vitro, may account for occasional non-templated nucleotides at P4R2 RNA 3’ termini. The 24 nt siRNAs primarily correspond to the 5’ or 3’ ends of P4R2 RNAs, suggesting a model whereby siRNAs are generated from either end of P4R2 duplexes by single dicing events.In DOI:http://dx.doi.org/10.7554/eLife.09591.001 Genes contain instructions for processes in cells and therefore their activities must be carefully controlled. The addition of small chemical tags called methyl groups to DNA is one of the many ways by which cells can influence gene activity. These methyl groups can silence genes by altering the DNA so that is more tightly packed within the nucleus of the cell. Virus genes and mobile sections of DNA called transposable elements (sometimes known as jumping genes) are also silenced by DNA methylation to keep them from doing harm.In plants, methyl groups can be attached to DNA by proteins that are guided to the DNA by molecules called short interfering ribonucleic acids (or siRNAs for short). Each siRNA is made of a chain of 24 building blocks called nucleotides and is able to bind to matching RNA molecules that are attached to the target DNA. The siRNAs are made from longer RNA molecules in a process that involves trimming by an enzyme called DCL3. However, it is not clear how long these “precursor” molecules are before DCL3 cuts them down to size.Arabidopsis thaliana. The experiments show that RNAs containing around 26-45 nucleotides accumulate in cells that lack DCL3 and these cells are unable to make 24 nucleotide long siRNAs. Furthermore, the purified DCL3 enzyme can cut these precursor RNAs to make the siRNAs. Because the precursors are relatively short, the experiments suggest that DCL3 only cuts each precursor RNA once when making siRNAs.Here, Blevins, Podicheti et al. studied how siRNAs are made in a plant called Blevins, Podicheti et al. also show that the siRNA precursors are made by a partnership of two RNA synthesizing enzymes. Therefore, a challenge for the future will be to understand exactly how they work together.DOI:http://dx.doi.org/10.7554/eLife.09591.002 Arabidopsis thaliana give rise to clusters of 24 nt siRNAs, collectively accounting for more than 90% of the total small RNA pool  that are then cleaved by DICER-like 3 (DCL3) to produce 24 nt siRNA duplexes, one strand of which is incorporated into AGO4  or a clo mutants , Pol IV  mutants . Currentdcl2 dcl3 dcl4 (dcl2/3/4) mutants were identified  or RDR2 . This indicates that Pol IV and RDR2 are each required for the biogenesis of the longer RNAs, paralleling their requirement for 24 and 23 nt siRNA biogenesis . The longer RNAs (>25 nt) are also reduced in abundance if Pol V or AGO4 are mutated in the dcl2/3/4 triple mutant background , analogous to the degree to which siRNA levels are reduced, but not eliminated, in ago4 or pol V single mutants . These observations are consistent with Pol V and AGO4 being important, but not essential, for biogenesis of the majority of 23/24 nt siRNAs  hybridize to 5S gene intergenic region probes corresponding to either DNA strand, as do homologous siRNAs . Interesdcl2/3/4 triple mutants are substrates for DCL3. In this experiment, RNA isolated from dcl2/3/4 triple mutant plants was incubated with FLAG-tagged DCL3 that had been affinity purified from transgenic plants using anti-FLAG resin. In parallel control reactions, dcl2/3/4 RNA was incubated with anti-FLAG resin that had been incubated with a cell-free lysate of non-transgenic plants (ecotype Col-0), or with anti-FLAG resin in reaction buffer with no added proteins  or rdr2 mutants and conducted RNA sequencing (RNA-seq) analyses using Illumina deep sequencing technology, performing two biological replicates for each sample , mple see . In dcl2see also . These gof 30 nt . These >dcl2/3/4 triple mutants, as visualized in the RNA blots of Although P4R2 RNAs accumulate to their highest levels in dcl2/3/4 triple mutants show a high degree of correspondence to 24 and 23 nt siRNA sequences, genome-wide. To simplify the discussion we focus solely on 24 nt siRNAs. Ninety-six percent of P4R2 RNAs identified in dcl2/3/4 mutants fully encompass or overlap 24 nt siRNA sequences . Among the P4R2 loci we identified are 20 of the 22 loci that Li et al.  at the 5’ end , which hen masse, regardless of length, hold true for P4R2 RNAs of each length considered separately , with the order of nucleotide preference at this 3’ terminal position being U > C > A. P4R2 RNAs also tend to end with U, but the order of nucleotide preference at their 3’ termini is slightly different: U > A > C. Interestingly, a larger (but weak) consensus, ACU can be discerned at the 3’ end of P4R2 RNAs  by expressing the protein in insect cells using a baculovirus vector system . As show the RNA , lane 2.dcl2/3/4 triple mutants .Our data indicate that the short double-stranded P4R2 RNAs that accumulate in ger RNAs . Our anardr2 mutant and be detectable on RNA blots using sense or antisense probes that detect abundant siRNAs (such as the 5S gene intergenic spacer siRNAs). Alternatively, if RDR2 were to act upstream of Pol IV, which is contrary to current models, but a formal possibility, one might similarly expect to detect RDR2 transcripts in a pol IV mutant. However, our RNA blot results  loci, as can be seen in the browser displays of A. thaliana mutants rdr2-1, nrpd1-3 (pol IV) and nrpe1-11 (pol V) were described in ago4-7 was selected from seed obtained from the Arabidopsis Biological Resource Center (stock ID: SALK_095100). The single mutants dcl2-5, dcl3-1, and dcl4-2; double mutants dcl2-5 dcl3-1 (dcl2/3), dcl2-5 dcl4-2 (dcl2/4) and dcl3-1 dcl4-2 (dcl3/4); and the triple mutant dcl2-5 dcl3-1 dcl4-2 (dcl2/3/4) were described in  was previously described .Total RNA (∼100 μg) was extracted from leaves of 2-week-old plants using TRIzol  and then size-fractionated on RNeasy Mini Columns  as in http://www.fasteris.com/). In brief, 5 µg total RNA was subjected to 15% denaturing polyacrylamide gel electrophoresis. The desired RNA size-range was excised and eluted, and 3’ and 5’ adapters were added according to the ligation-based Illumina small RNA-seq protocol. Sequencing by synthesis (1 × 100) was performed on an Illumina HiSeq 2500  instrument following manufacturer’s recommendations . Basecalling was performed using the HiSeq Control Software (v2.0.10.0), RTA (v1.17.21.3) and CASAVA (v1.8.2). Insert lengths ranged from 15-94 nt following adapter sequence removal. RNA-seq statistics are provided in Custom libraries for ∼15–90 nt RNAs were constructed and sequenced by Fasteris SA (Two independent replicates (Rep 1 and Rep 2) for RNA samples of four different genotypes were barcoded and sequenced on a single HiSeq 2500 instrument. Yield (Mb) is the total number of sequenced bases. %PF (% passed filter) indicates the percentage of clusters (sequenced polynucleotides) that fulfill default Illumina quality criteria; Cluster (PF) indicates the number of such clusters. Q30 is the percentage of bases detected with a quality score greater or equal to 30. Mean quality is the average of quality scores for all called bases.A. thaliana Col-0 reference genome (TAIR10) using Bowtie v0.12.8  using Bowtie v0.12.8. The total number of reads used for analyses in the paper, which includes reads with 100% match to the genome or reads with a maximum of one mismatch, are provided.RNA-seq reads of ∼15–94 nt (after adapter trimming) were mapped to the http://trace.ncbi.nlm.nih.gov/Traces/sra/?study=SRP059814)RNA-seq data for the eight libraries generated in this study  are avai2, 5 mM dithiothreitol [DTT], 1 mM phenylmethylsulfonyl fluoride [PMSF] and 1:200 plant protease inhibitor cocktail [Sigma]), filtered through two layers of Miracloth , and centrifuged to pellet cellular debris. Supernatants were incubated with 25 μL anti-FLAG-M2 resin  for 3 hr at 4°C on a rotating mixer. Resin was recovered and washed three times with extraction buffer supplemented with 0.5% NP-40.Protein extraction and affinity immunoprecipitation were performed as in . Frozen dcl2/3/4 triple mutant inflorescence tissue and size-fractionated (see 'RNA blot hybridization') to obtain substrates for DCL3 activity assays. Low-molecular-weight RNA was divided into 12-μg aliquots, which were then mixed with: protein extraction buffer (buffer control), FLAG-resin previously incubated with Col-0 protein extract (wild-type/resin control), or FLAG-resin previously incubated with cell-free extract from transgenic plants expressing the DCL3–FLAG protein (the DCL3 assay). These mixtures were then incubated at 30°C for 3 hr in dsRNA cleavage buffer . RNA products were isolated from the reactions by phenol–chloroform extraction, and then precipitated by addition of 2 μl GlycoBlue (Life Technologies) and two volumes ethanol, followed by centrifugation. The precipitated RNA was washed twice in 75% ethanol, resuspended in loading buffer and analyzed by RNA blot hybridization.Total RNA (∼360 μg) was extracted from wild-type (Col-0) or Pols II and IV were immunoprecipitated from transgenic lines expressing NRPB2-FLAG or NRPD1-FLAG, respectively, as described previously . Brieflyfree kit reagent . The samples were then treated with Terminator exonuclease  to remove potentially degraded RNAs with 5’ monophosphates, cleaned with RNA Clean and Concentrator kit , and then treated with RNA 5’ Polyphosphatase (Epicentre Biotechnologies) to convert 5’ triphosphate groups to monophosphates. All enzyme treatments were performed according to the manufacturer’s protocols. Adapter ligation and library construction was performed using a TruSeq small RNA kit (Illumina). Paired-end sequencing was conducted using an Illumina MiSeq instrument. Paired reads were mapped to the M13 sequence using default settings of BWA  and incubated at room temperature for 1 hr on a rotating mixer. Reactions were subjected to centrifugation through Performa spin columns , the filtrate was adjusted to 0.3M sodium acetate, and nucleic acids were precipitated with isopropanol. The pellets were resuspended in 8 μl water and DNase-treated using Turbo DNA-s of BWA  for IlluRDR2 cDNA, amplified by PCR using primers 5’-CACCATGGTGTCAGAGACGACGACGAAC-3’ and 5’-TCAAATGGATACAAGTCCACTTGTTTT-3’, was cloned into pENTR and recombined into the baculovirus vector using LR clonase. The resulting baculovirus vector was transfected into Sf9 insect cells and recombinant virus was harvested according to the instructions of the manufacturer. RecRDR2 was purified from High Five cells infected with the recombinant virus and lysed in a buffer containing 50 mM HEPES-KOH (pH 7.5), 400 mM KCl, 5 mM DTT, 1 mM PMSF, 5 mM benzamidine-HCl and 10% glycerol. The lysate was subjected to centrifugation at 39,000 ×g for 30 min at 4°C. Anti-V5 agarose beads were used to selectively bind rec_RDR2 in the cleared lysate. The beads were collected by centrifugation at 170 × g for 5 min, washed 3 times with the same buffer, and eluted using V5 peptide in a buffer containing 50 mM HEPES-KOH (pH 7.5), 100 mM NaCl, 0.01% of NP-40 and 10% glycerol. The protein was concentrated and washed by buffer exchange using a Centricon column.RecRDR2 was overexpressed in insect cells using the BaculoDirect baculovirus protein expression system . 32P-CTP, 5 mM MgCl2, 5 mM DTT, 0.8 U/µl RNaseOUT and 1 µM of RNA template in a 50 µl reaction and incubated at room temperature (∼24°C) for 60 min. Reactions were terminated by adding 10 mM ethylenediaminetetraacetic acid and then a clean-up step was performed using EdgeBio Performa  spin columns. RNA products were ethanol precipitated and separated on a denaturing 15% polyacrylamide gel. The gel was transferred on Whatman 3MM filter paper and dried under vacuum at 80°C prior to phosphorimaging. The RNase treatment assay was conducted using a 20 µl RDR2 reaction with 0.05 U/µl of RNase ONE in 1 × reaction buffer. The reaction was incubated at 37°C for 30 min and terminated by 0.2% SDS .RDR2 terminal transferase assays were performed according to  with som review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.eLife posts the editorial decision letter and author response on a selection of the published articles . An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent  and three reviewers, one of whom is a member of our Board of Reviewing Editors. The reviewers feel the discovery that RNA Pol IV creates short transcripts is of major interest, as it substantially alters the existing model of RNA-directed DNA methylation. However, the reviewers expressed substantial concerns regarding the strength of the proof that the short RNA molecules described in the manuscript represent primary Pol IV transcripts.Thank you for submitting your work entitled "Identification of Pol IV and RDR2-dependent precursors of 24 nt siRNAs guiding de novo DNA methylation in Arabidopsis" for peer review at The reviewers have discussed the reviews with one another and the Reviewing editor has drafted this decision to help you prepare a revised submission.Essential revisions:1) The evidence that short RNA molecules depend on Pol IV and RDR2 is provided for only one locus. This is insufficient evidence to claim that all such RNAs are made by Pol IV instead of Pol II or Pol V. Please provide additional evidence for Pol IV dependence, such as additional Northern blots or sequencing RNAs from POL IV dcl234 mutants. Depending on the strength of the additional evidence, the "P4R2" nomenclature may have to be reconsidered.2) The data presented do not exclude the possibility that short RNAs are processed from longer primary Pol IV transcripts. Given the central conclusion of the paper, please strengthen the evidence that primary Pol IV transcripts are indeed short. This might be done through analysis of nascent transcripts, expanding the analysis that links short RNAs to Pol II consensus start sites that is briefly presented in the discussion, or through other approaches. Depending on the strength of the additional evidence, the authors may need to discuss the possibility that longer Pol IV transcripts are processed into the detected short molecules.3) The data regarding Pol V dependence may be confusing by suggesting that all short RNAs depend on Pol V, whereas this is probably not the case. This could be resolved by probing the Northern for loci that do not depend on Pol V for 24-nt sRNA production (in conjunction with addressing point 1) or by a clear explanation in the text.4) For the DCL3 in vitro assay, please include a time zero control to ensure that there were indeed larger RNAs present in the extracts from the dcl234 mutant plants that are processed by the Flag tagged DCL3 protein.5) Please include information describing RDR2 expression and purification and remove the "data not shown" parts of the Results and Discussion.6) The treatment of sRNA phasing is confusing. A new analysis is referenced in the Introduction, and lack of phasing could easily result from random Pol IV initiation or DCL3 cleavage. Please present the phasing analysis in the Results and consider discussing its significance in the Discussion section.7) Please provide significance information  of the motifs or the parameters used to identify the motifs presented in the manuscript.8) Please define the "R" lane in  1) The evidence that short RNA molecules depend on Pol IV and RDR2 is provided for only one locus. This is insufficient evidence to claim that all such RNAs are made by Pol IV instead of Pol II or Pol V. Please provide additional evidence for Pol IV dependence, such as additional Northern blots or sequencing RNAs from POL IV dcl234 mutants. Depending on the strength of the additional evidence, the "P4R2" nomenclature may have to be reconsidered.dcl2 dcl3 dcl4 (abbreviated as dcl2/3/4) mutants, in which P4R2 RNAs accumulate to their highest levels. However, in parallel with these Col-0 and dcl2/3/4 datasets, we had also performed RNA-seq analyses for nrpd1 and rdr2 mutants . In the revised manuscript, we now make use of all of these datasets to show that the P4R2 RNAs that accumulate in dcl2/3/4 mutants are also detected  in wild-type Col-0 but are absent or depleted in nrpd1 or rdr2 mutants. A genome browser view making this point graphically for three representative loci is shown in new dcl2/3/4 and wild-type, but are depleted in nrpd1 or rdr2 mutants. In this table, data are provided for both independent biological replicates for each genotype, with high confidence P4R2 RNA – generating intervals being those in which the RNAs are depleted in both nrpd1 and rdr2 replicates. In We thank the reviewers for this comment, as it has prompted us to expand our analyses and strengthen our story. To address this comment we have added four new figures or supplemental figures to the revised manuscript, namely 2) The data presented do not exclude the possibility that short RNAs are processed from longer primary Pol IV transcripts. Given the central conclusion of the paper, please strengthen the evidence that primary Pol IV transcripts are indeed short. This might be done through analysis of nascent transcripts, expanding the analysis that links short RNAs to Pol II consensus start sites that is briefly presented in the discussion, or through other approaches. Depending on the strength of the additional evidence, the authors may need to discuss the possibility that longer Pol IV transcripts are processed into the detected short molecules.This request by the reviewers was not trivial. To address this concern as best we can, we have included data from a separate, ongoing study by student, and new author, Michelle Marasco. We show, as new 3) The data regarding Pol V dependence may be confusing by suggesting that all short RNAs depend on Pol V, whereas this is probably not the case. This could be resolved by probing the Northern for loci that do not depend on Pol V for 24-nt sRNA production (in conjunction with addressing point 1) or by a clear explanation in the text.pol V and ago4 mutants most likely affect P4R2 and siRNA levels indirectly via their involvement in DNA methylation and histone modifications that have been shown to recruit Pol IV to target sites. We cite several relevant, recent papers.We have clarified this point by adding a sentence to the Results section stating that 4) For the DCL3 in vitro assay, please include a time zero control to ensure that there were indeed larger RNAs present in the extracts from the dcl234 mutant plants that are processed by the Flag tagged DCL3 protein.Apparently, we did a poor job of explaining the controls for this figure, as these controls satisfy the reviewer (s)’s concern. We have re-written this section to make it clearer. The two controls  were conducted side-by-side with the affinity-purified DCL3 sample, and they show that undigested precursor RNAs remain even after the incubation period allowed for DCL3 digestion. Thus the precursor RNAs must also have been present at time zero.5) Please include information describing RDR2 expression and purification and remove the "data not shown" parts of the Results and Discussion.We have added two new panels to what is now 6) The treatment of sRNA phasing is confusing. A new analysis is referenced in the Introduction, and lack of phasing could easily result from random Pol IV initiation or DCL3 cleavage. Please present the phasing analysis in the Results and consider discussing its significance in the Discussion section.Frankly, the phasing data are unnecessary, as it is obvious from our study that the dicing of precursors so short that they can only produce single siRNAs precludes the possibility of phasing. Thus we have deleted the figure panel in question and any discussion of phasing. This has helped keep the manuscript a manageable length while discussing the numerous new figures.7) Please provide significance information  of the motifs or the parameters used to identify the motifs presented in the manuscript.We now provide bit scores for the sequence logos. We neglected to include them in the original version of the manuscript, which was an oversight.8) Please define the "R" lane in This is a lane showing end-labeled template RNA, as a size marker. This is now made explicit in the figure.


Fetal bovine serum (FBS) has been used in eukaryotic cell cultures for decades. However, little attention has been paid to the biological effects associated with RNA content of FBS on cell cultures. Here, using RNA sequencing, we demonstrate that FBS contains a diverse repertoire of protein-coding and regulatory RNA species, including mRNA, miRNA, rRNA, and snoRNA. The majority of them (>70%) are retained even after extended ultracentrifugation in the preparations of vesicle-depleted FBS (vdFBS) commonly utilized in the studies of extracellular vesicles (EV) and intercellular communication. FBS-associated RNA is co-isolated with cell-culture derived extracellular RNA (exRNA) and interferes with the downstream RNA analysis. Many evolutionally conserved FBS-derived RNA species can be falsely annotated as human or mouse transcripts. Notably, specific miRNAs abundant in FBS, such as miR-122, miR-451a and miR-1246, have been previously reported as enriched in cell-culture derived EVs, possibly due to the confounding effect of the FBS. Analysis of publically available exRNA datasets supports the notion of FBS contamination. Furthermore, FBS transcripts can be taken up by cultured cells and affect the results of highly sensitive gene expression profiling technologies. Therefore, precautions for experimental design are warranted to minimize the interference and misinterpretations caused by FBS-derived RNA. Deep sequence analysis of extracellular RNA (exRNA) released by cultured cells in forms of extracellular vesicles (EVs) and lipoprotein complexes (RNPs) is an expanding area of research. An important question raised years ago and still highly debated in the field, is whether specific RNA species or motifs are enriched in EVs and RNPs. Such enrichment would support an active and regulated mechanism of RNA secretion. Alternatively, exRNA may reflect the entire cellular transcriptome, a specific RNA class (e.g. miRNA), or one of the steps of RNA metabolism, and thus, provide a peripheral measure for monitoring the cellular transcriptome. Addressing this question is critical for the study of intercellular communication and development of RNA biomarkers. Cell culture systems employed in the studies of exRNA biogenesis and release, rely heavily on the fetal bovine serum (FBS), a commonly used reagent vital for the growth of numerous cell types. Although many reports characterized exRNA isolated from human and mouse serum and suggested serum RNA as the major source of disease biomarkersSeveral observations suggested that FBS-associated RNA might interfere with the analysis of exRNA. First, we detected high levels of miR-122, a specific miRNA abundantly expressed in liver but undetected in other tissues25678910We next set to characterize the composition of FBS RNA and investigate whether RNA can be removed from serum. Serum RNA is associated with exosomes and other EVs, as well as non-membrane lipid and protein RNPs. Most researchers use 70,000 g to 110,000 g UC for 2 h–18 h to produce vdFBS. It has been demonstrated that prolonged UC removes the majority, although not all EVs, as monitored by NanoSightTo further evaluate the potential of FBS RNA to interfere with cell culture derived exRNA, we performed RNA deep sequencing of the FBS fractions. Three different batches of FBS were spun at 100,000 g for 24 h, and the RNA samples isolated from the pelleted EV-enriched fractions and EV-depleted supernatants were used for the construction of the NEBNext small RNA libraries, followed by the HiSeq 2000 RNA-seq. Read mapping to the hg19 version of Human Genome was performed using the exceRpt small RNA-seq pipeline V2.2.8 of Genboree Workbench with default parametersFrom 5.2% to 12.9% reads mapped to human genome corresponded to miRNA. MiR-122 was the most abundant miRNA in the FBS, followed by miR-1246, miR-423-5p, miR-148a-3p, and let-7 family . High le81015The additional question of broader importance is whether FBS-associated RNA may interfere with cellular RNA analysis. MiR-1246 gene that encodes one of the most abundantly expressed miRNAs in FBS, is present in only 4 out of 223 species, including bovine, human, orangutan and chimpanzee, but not in mouse or ratU test for all the samples together as a global comparison. Bovine-contamination was significantly more severe in exRNA than in cellular RNA (exact p = 0.016). Therefore, the analysis of public datasets is indicative of common contamination of FBS-derived RNA in the various exRNA samples preparations.To further confirm that FBS-derived RNA contamination is common in cell culture exRNA, we interrogated several public exRNA-seq datasets and examined whether they contain bovine-specific reads. Totally, 13 exosomal RNA samples and 8 corresponding human cellular RNA samples from 4 different cell types were analyzed. To adjust variable mapping rates between the samples, the ratio of bovine-specific reads to the human-specific reads was used as the normalized level for bovine contamination. In the exosomes, roughly 2.6–17.2% of reads (the inter-quartile range) corresponded to bovine-specific transcripts. As shown in This data lead us to consider several factors that influence cell culture-based exRNA research. First, media composition, including serum, growth factors, and other natural derivatives, would affect the results of exRNA analysis. As demonstrated in Several controls should be considered to help minimize these factors. First, analysis of cell culture-derived exRNA should include RNA samples isolated using the same procedure from the corresponding fresh media. Of note, various cell types and lines secrete vastly different amounts of exRNA ranging from a few nanograms to a hundred nanograms per ml of conditioned media812U251 and 20/3 human glioma cells, GL261 mouse glioma cells, mouse embryonic fibroblast cells , CMT-93 mouse rectum cells, RAW264.7 mouse macrophage  and EL4 mouse T lymphocytes  were cultured in DMEM  with 10% FBS , either EV-depleted or not, and passaged by trypsinization (Gibco). Glioma cells cultured as neurospheres were grown in Neurobasal medium (Gibco) supplemented with 3 mM GlutaMAX (Gibco), 1x B-27 supplement (Gibco), 0.5x N-2 supplement (Gibco), 20 ng/mL EGF , and 20 ng/mL FGF . None of these cell lines is in the database for misidentified cell lines (ICLAC). All of them are mycoplasma-free.For cellular RNA isolation, cells were washed thoroughly with cold DPBS (Corning) three times. RNA was then isolated using miRCURY RNA Isolation Kit , with on-column DNase  treatment step added to the manufacturer’s protocol. For tissue RNA isolation, fresh tissues were excised from one C57BL/6J mouse and transferred to Lysis Solution immediately, followed by homogenization. The lysate was spun at 14,000 g for 2 min to remove cell debris, and RNA isolated as above. For exRNA isolation from FBS, either 11.5 mL or 40 mL of freshly thawed FBS were injected into Quick-Seal Centrifuge Tubes and spun at 100,000 g, 4 °C using an Optima L-90K ultracentrifuge  in SW 41 Ti Rotor  or SW 28 rotor , respectively. RNA from the pellet was isolated as above. Either 2 mL or 20 mL of the supernatant was concentrated using 3 kDa Amicon Ultra Centrifugal Filters  at 4,000 g 4 °C for 80 min. The concentrate was then lysed using six volumes of Lysis Solution of miRCURY RNA Isolation Kit (Exiqon), followed by the RNA isolation as above. For exRNA isolation from conditioned or fresh media, 40 mL media was first spun at 300 g 4 °C for 10 min, and further at 2,000 g 4 °C for 15 min, and the supernatants filtered through a 0.8 μm filter  to remove cells and cell debris. After adding 10 U/mL SUPERase-In RNase Inhibitor (Thermo Fisher Scientific), EVs were pelleted by ultracentrifugation at 100,000 g 4 °C for 80 min in an SW 28 rotor, and RNA isolated from EV pellets as described above. The concentration of cellular/tissue RNA was determined using NanoDrop 2000 Spectrophotometer (Thermo Fisher Scientific), and concentration of exRNA was determined using Quant-iT RiboGreen RNA Assay Kit (Thermo Fisher Scientific).Ten ng total RNA in 10 μl of reverse transcription reaction mix was used for Universal cDNA Synthesis kit II (Exiqon). The cDNA was diluted 80 times, and 4 μl was used in 10 μl qPCR reactions with ExiLENT SYBR Green and LNA primers (Exiqon). The qPCR reactions were performed on a ViiA 7 instrument (Thermo Fisher Scientific) in triplicates. Alternatively, for amplification of cell/tissue RNA, 100 ng of total RNA was used as input and cDNA was diluted 30 times. The U6 snRNA was monitored as the endogenous control for cellular RNA. A panel of 4 endogenous controls  was used for geNorm normalization between cells and tissues. The specificity of all qPCR primers was verified by the melt curve analysis. For qRT-PCR using TaqMan assays, manufacturer’s protocol was carried out with the following modifications: the input of 3.33 ng RNA was used for 5 μl reverse transcription reaction and PCR reactions were performed in 10 μl volume.60 ng of total RNA was treated with T4-PNK and used as an input for NEBNext small RNA library construction , with size selection for 15-65nt inserts. The libraries were examined using Agilent Bioanalyzer 2100 , quantified with KAPA Library Quantification Kits for Illumina , and sequenced on HiSeq 2000  with single-end 50 bp reads, at the Center for Cancer Computational Biology at Dana-Farber Cancer Institute. On average, 19 million reads per sample were produced. Reads annotation to hg19 was performed using exceRpt small RNA-seq pipeline V2.2.8 of the Genboree WorkbenchRaw sequence data were downloaded from the NCBI GEO database or SRA database. For the SRA files, they were converted to the FASTQ format using the SRA toolkit v2.6. The quality of the reads was estimated with the FastQC software v0.11. Based on the FastQC report, the optimal read spans were identified as the longest uninterrupted read sequence spans, where for all the base positions the quality scores exceeded 30, on the PHRED scale. The datasets, whose optimal read spans were shorter than 20 bases, were discarded from the analysis. The reads were mapped, using the Bowtie2 software v2.2.8 with the following set of parameters: -p 8, -local, -L 25, -X 1300, -N 0. For each individual FASTQ file containing the sequencing reads of a given experiment, the reads were aligned independently onto two unmasked reference genomes: H.sapiens (GRCh38) and B.taurus (UMD3.1.1). The species-specific reads were defined as such reads that align to only one of the reference genomes. Considering variable aligned reads count between samples/datasets, human-specific reads count was used to normalize bovine-specific reads count. Therefore, the ratio of bovine-specific reads count to human-specific reads count was calculated as the index to quantify FBS-derived RNA contamination. To accelerate the sample analysis, a random subsampling of 1 million reads from each analyzed FASTQ file, using the seqtk software tool, was used as input for the analysis.When two groups were compared, significance was determined using an unpaired two-tailed t-test. Before performing t-test, normal distribution was verified by 1-sample K-S test and equality of variances was verified by Levene’s test using SPSS . To assess the statistical significance of difference of bovine-specific reads ratio between the exRNA and the cellular RNA, the two-tailed Mann–Whitney U test was applied using SPSS. A p value < 0.05 is considered as statistical significance. All bars on the graphs represent mean ± SEM.How to cite this article: Wei, Z. et al. Fetal Bovine Serum RNA Interferes with the Cell Culture derived Extracellular RNA. Sci. Rep.6, 31175; doi: 10.1038/srep31175 (2016).


Using ensemble and single molecule fluorescence spectroscopy, we show that σNS also binds to a partially double-stranded RNA, resulting in gradual helix unwinding. The hexamer can bind multiple RNA molecules and exhibits strand-annealing activity, thus mediating conversion of metastable, intramolecular stem-loops into more stable heteroduplexes. We demonstrate that the ARV σNS acts as an RNA chaperone facilitating specific RNA–RNA interactions between genomic precursors during segment assortment and packaging.Reoviruses are important human, animal and plant pathogens having 10–12 segments of double-stranded genomic RNA. The mechanisms controlling the assortment and packaging of genomic segments in these viruses, remain poorly understood. RNA–protein and RNA–RNA interactions between viral genomic segment precursors have been implicated in the process. While non-structural viral RNA-binding proteins, such as avian reovirus σNS, are essential for virus replication, the mechanism by which they assist packaging is unclear. Here we demonstrate that σNS assembles into stable elongated hexamers  Orthoreovirus of the Reoviridae family, which encompasses numerous human and animal pathogens, including rotaviruses, bluetongue virus and coltiviruses. Reoviruses possess double-stranded (ds) RNA genomes, partitioned into 10–12 genomic segments (Avian reoviruses (ARVs) are commercially significant pathogens that cause considerable losses in the poultry industry worldwide . ARVs besegments , where tReoviridae family suggest that multiple RNA–RNA interactions are involved in segment assortment . The RNA was reverse-transcribed using Superscript III Reverse Transcriptase and random hexamer oligonucleotide primers (Invitrogen). Oligonucleotide primers F_sns and R_sns (Supplementary Table S1) were used to PCR-amplify the resulting cDNA, with NdeI and XhoI restriction sites used for ligating the resulting double-digested σNS-coding DNA fragment into a linearized pET-15b vector (Novagen). The resulting pET-15b-σNS DNA construct was verified by sequencing.Escherichia coli cell cultures grown at 37°C were induced with 1 mM isopropyl-β-d-thiogalactopyranoside (IPTG) upon reaching optical density (600 nm) of 0.6–0.7, after which the protein expression was continued at 21°C overnight. Following a low-speed centrifugation harvesting, cells were resuspended and incubated for 30 min in lysis buffer , complemented with a complete protease inhibitor cocktail tablet (Roche), and then treated with DNAseI (0.1 mg/ml) for 15 min at room temperature (RT) before cellular debris were removed by centrifugation at 20 000r pm for 30 min. The clarified cell lysate was loaded onto a pre-equilibrated Ni2+-charged HisTrap FF column , washed with buffer A , and eluted using a linear gradient of buffer B . Collected protein-containing fractions were dialysed against buffer C  at 4°C, treated with human plasma thrombin (1 U/100 μg of recombinant protein) for 12 h at 22°C in order to remove His-tags. Protein samples were then loaded onto a pre-equilibrated HiTrap Q column, washed with buffer D , and the protein was eluted with buffer E . Concentrated σNS samples were injected onto a Superdex 200 10 × 300 GL column  in 25 mM HEPES–Na, pH 7.5, 150 mM NaCl. After the final purification step, the A260/A280 absorbance ratio of ∼0.57 suggested negligible contamination with nucleic acids.pET-15b-σNS-transformed BL21(DE3)pLysS For strand-annealing assays, rotaviral protein NSP2 was expressed and purified, as previously described in .All oligonucleotides were obtained from Integrated DNA Technologies (IDT). A 120-nt long RNA sequence was designed with a fixed nucleotide composition distribution  in order to minimise any potential base-pairing. The resulting nucleotide sequence was examined using the mfold web server , and the3/g  with an estimated hydration level of 0.3733 g/g . SV analyses were conducted at 21°C with protein concentrations ranging between 5 and 25 μM and RNA concentrations of 50–60 nM. Changes in solute concentration were detected using absorbance scans at 260 nm for nucleic acids and 280 nm for proteins, as well as by interference. Each cell was scanned 200 times during the 12 h run, preceded with 1 h pre-run period in the rotor at a given speed . Buffer density and viscosity were calculated using Sednterp . Partial3733 g/g .h) were calculated using Einstein–Stokes relationship, implemented in Sedfit  Lamm equation model using the Sedfit version 12.1b software . During n Sedfit .Protein samples (6–25 μM) were examined by SE, which was attained at 8000 rpm for 24 h and 12 000 rpm for 12 h at 20°C in an eight-hole An50 Ti rotor. Global analysis of several datasets of radial absorbance obtained at different loading concentrations and rotor speeds was performed in Sedphat , and SE Five microliters of the σNS–RNA complex, used in SV experiments (see above), was applied onto carbon-coated grids (Agar Scientific) to absorb for 1 min, after which the excess of sample was removed by blotting with filter paper. Grids were stained with 2% (w/v) uranyl acetate, and examined using JEOL 1200EX transmission microscope operating at 80 kV at 30 000× and 40 000× magnifications.2/dmol). CD spectra were deconvolved by applying CDSSTR algorithm  were analysed in a 0.5-mm path length cuvette using a Chirascan CD spectrometer (Applied Photophysics). CD spectra were acquired between 260 and 170 nm at 21°C. Two spectra were recorded and averaged for each concentration, followed by subtraction of the buffer spectrum. ProData Viewer software (Applied Photophysics) was used to view the recorded spectra and to assess the quality of the spectral data by examining HT voltage (absorbance). Measured ellipticities (mdeg) were expressed in terms of mean residue ellipticity .Apparent hydrodynamic radii of σNS species (10–60 μM) were measured by DLS using a PrecisionDeconvolve PDDLS/Batch platform, equipped with a PD2000 DLS detector. All measurements were performed in a buffer with an estimated viscosity, m/z spectra were plotted against the drift time using Driftscope software . Calibration of the drift time cross-section was done by the combined analyses of denatured proteins . For each protein, the individual charge state ions were identified by m/z ratios and their measured drift times were plotted against collision cross-sections (Ω), taken from Prof. D. Clemmer's database (Indiana University Bloomington), as described previously  were acquired in the positive-ion mode using a Synapt HDMS , with quadrupole-orthogonal acceleration time-of-flight geometry and a built-in traveling wave ion mobility device. Protein mass spectra were also acquired using the LCT Premier  specially modified for the analysis of non-covalently bound macromolecular complexes. The ESI conditions were optimized for the highest sensitivity detection of multimeric complexes in the gas phase . The drieviously ,32.I0 values. Data were processed using ATSAS v. 2.5.1 (Rg) were estimated using AUTORG . SAXS data were acquired at 21°C using a 2D Photon counting Pilatus 1M-W pixel X-ray detector with a sample to detector distance set to 2.7 m. Protein samples  were examined, while serial dilutions (1–10 mg/ml) of bovine serum albumin (BSA) in the same buffer were used for calibrating v. 2.5.1 . Backgrov. 2.5.1 . Radii od DAMMIF . Multipld DAMMIF . Models d DAMMIF . The reshR values were estimated based on measured diffusion time values for AF488 dye molecule as described before . σNS was titrated  into 1 nM of each of the RNA in 10 mM HEPES–NaOH, pH 7.5, 150 mM NaCl, allowing equilibration for 30 min prior FA data collection. Normalized anisotropy was plotted as a function of protein concentration and fitted to a single-site binding model using OriginPro 9.0 software.Fluorescently labeled 46-nt long probe with a FRET donor (AF488) and acceptor (Texas Red) pair at the 5′ and 3′ ends, respectively, was designed (Supplementary Table S1). Since σNS was shown to bind ssDNA, as well as ssRNA , due to 2, 50 mM Tris–HCl, pH 7.9, slowly cooled and diluted in assay buffer  to 5 ng/μl. Reactions were set up with equimolar amounts of 33A and 33B  and variable amounts (1–20 μM) of the ARV σNS or acetylated BSA (negative control). Reactions were allowed to proceed at 37°C for 5–30 min before they were stopped by adding gel-loading buffer, after which they were kept on ice before resolving products on a 1× TBE 15% PAGE. Gels were stained with SYBR Gold (Invitrogen) and visualized by a fluorescence scanner with a 488 nm laser excitation.Two 33-nt long oligonucleotides, 33A and 33B, with self-complementary stem-forming regions (Supplementary Table S1) were designed with the aid of mfold  and usedin vitro transcription using T7 polymerase. The resulting RNA products were purified, and each RNA strand was heat-annealed (as described above) prior strand-annealing reactions. For strand-annealing reactions, s1 and s4 RNAs (1.5 μM each) were incubated with 50–70 μM σNS for 5–15 min at 37°C. Similarly, strand-annealing reactions were set up with the rotaviral nonstructural protein NSP2. All reactions were stopped by adding 40 μg of proteinase K (NEB), and incubating for another 15 min. RNA samples were resolved on a native 12% 1× TBE PAGE and visualised by staining with SYBR Gold (Invitrogen).Additional strand-annealing assays were performed with viral RNA fragments, encompassing the last 91 nucleotides of the 3′ end 1552–1643 nt) of segment s1 precursor and a similarly sized RNA fragment (422–513 nt) of segment s4 precursor (S1133 strain of ARV). These regions were identified using RactIP tool  nt of se. DNA UlthR) of 5.0 ± 0.4 nm , reveals 11.3S oligomers with a corresponding mass of 237.6 ± 23.0 kDa. Taken together, these analyses demonstrate that at low micromolar concentrations the ARV σNS assembles into stable 11.3S hexamers.A full-length recombinant ARV σNS was expressed and purified as described in ‘Materials and Methods’ section, and a homogeneous, intact protein sample was obtained by size-exclusion chromatography Figure  B, combiPreviously, smaller oligomeric species of the ARV σNS were reported . We thergR) of 5.3 ± 0.3 nm, while the gR/hR ratio > 1  Figure . The estatio > 1  suggestsAXS data , withoutin vitro (Kd) of 26.5 ± 4.2 nM for the 20-nt RNA , consistent with binding to a single hexamer.Due to the oligomeric nature of the ARV σNS, it is possible that a single hexamer could bind several RNA strands simultaneously. At molar excess of the 20-mer RNA (Supplementary Table S3), native ESI-MS reveals 1:1 and 2:1 RNA:hexamer complexes, thus directly demonstrating binding of up to two RNAs per single hexamer. Other smaller protein oligomers were also detected, but only the hexamer bound RNA, suggesting that it is the functional RNA-binding oligomer. Since the stability of higher order species may be compromised in the gas phase, we also examined whether the 20-mer is capable of binding more than a single hexamer using fluorescence correlation spectroscopy (FCS). At saturating protein concentrations, the hR) of these complexes. The hR of the 120-mer (∼3.6 nm), incubated with 0.5–1 μM σNS, increases to 4.8 ± 0.8 nm , corresponding to the size of a single hexamer, independently measured by DLS (see above). At higher protein concentrations (5–10 μM), the hR further increases to 5.9 ± 1.0 nm, consistent with binding of a second hexamer to the RNA. Thus combining hR and S values of ribonucleoproteins, the estimated masses of 13S and 18S species correspond only to complexes of 1:1 and 2:1 hexamer:RNA stoichiometry, respectively. A 2:2 stoichiometry is not compatible with the sedimentation data  reveals a single 5.2 S species for the 41-kDa RNA Figure , red. InKd = 333 ± 10 nM, Figure We then examined how nucleic acid secondary structure affects its affinity for σNS. Since σNS exhibits similar affinities for both ssRNA and ssDNA, we designed a 46-nt long dual end-labeled ssDNA probe , comprising a 30-nt stem-loop and a 16-nt long single-stranded region Figure . The choKd of 1.1 ± 0.22 μM, i.e. significantly higher than that measured by fluorescence anisotropy. This result agrees with a model in which binding of a hexamer captures transiently opened single-stranded regions, leading to gradual helix unwinding at higher protein concentrations. In this model binding effectively competes with the duplex stability, leading to the higher apparent, FRET-derived Kd for unwound species.We then examined whether σNS binding to the stem–loop results in destabilization of its base-paired region by monitoring changes in FRET upon protein binding. The probe alone exhibits high FRET efficiency, consistent with its predicted secondary structure Figure . When tiE = 0.89) is observed for the probe alone  population  method  in ordere Figure , blue, wn Figure , red. Inn Figure . FurtherhR of RNA , than for unstructured shorter ssRNA, consistent with the high content of secondary structure in the 3.6 kb RNA (hR reflects expansion of the RNA and formation of large ribonucleoproteins (hR ∼ 18 nm), rather than aggregation of multiple ssRNA molecules. In order to characterize the shape and dimensions of these ribonucleoproteins, we performed SV analysis of long ssRNAs (60 nM), incubated with 6 μM σNS. Multiple spherical 50–90 S complexes, presumably of variable RNA:σNS stoichiometry, are formed  spectroscopy. A positive peak at 263 nm was observed for RNA alone Figure , black, Since helix-unwinding activity is often associated with a strand exchange between preformed helices ,50,51, wHaving established that σNS promotes strand-annealing between short complementary RNA stem-loops, we then examined whether it exerts similar effects on longer viral RNAs, e.g. ARV segment precursors. In ARVs, segment assortment and packaging signals are believed to involve terminal untranslated regions (UTRs), extending into the protein-coding regions of each segment ,53. We tin vivo.Non-structural ssRNA-binding protein σNS is one of the major components of viroplasms in avian reovirus-infected cells. It has been suggested that the protein is involved in the viral genome packaging ,3. AlthoReoviridae have many common features, these proteins share very little, if any sequence homology. Non-structural ssRNA-binding proteins of most non-turreted Reoviridae, including bluetongue virus (BTV), rotaviruses, and some phytoreoviruses assemble into large oligomers, having a ring-like appearance (σNS forms 7–9S species without obvious ring-like architecture (Reoviridae. It is unclear whether the viroplasm-building blocks of most turreted Reoviridae, e.g., ARV and MRV, are different in their quaternary organization from the non-structural viroplasm-forming proteins of non-turreted viruses. However, given a small fraction of octameric σNS species, observed in native ESI-MS spectrum at high protein concentration, it is possible that different functional oligomeric states of these proteins may be important for protein-RNA and protein-protein interactions during formation of viroplasms and subsequent virus assembly.While both avian and mammalian reovirus σNS, as well as other viroplasm-forming non-structural proteins from pearance ,56–58. Ipearance . Likewispearance , while iitecture , suggestBoth mammalian and avian reovirus σNS readily bind ssRNA, forming large ribonucleoproteins of variable stoichiometries ,14,62. IReoviridae family, including rotavirus NSP2 and MRV σNS (Previously, helix-unwinding activity has been reported for a number of non-structural proteins from  MRV σNS ,63. Howe MRV σNS . DetaileOur results suggest that σNS hexamer appears to be the functional RNA-binding species. Previously, σNS has been proposed to act as a condensing agent for long viral ssRNAs in viroplasms . Here, wSince hexameric σNS does not exhibit ATPase activity and ring-like shape of typical hexameric helicases , the obsin silico secondary structure and disorder sequence analysis using Phyre2 (Given its non-specific ssRNA-binding and ATP-independent helix-unwinding activity, ARV σNS exhibits typical characteristics of an RNA chaperone . While ig Phyre2  predictsg Phyre2 . Interesg Phyre2 , contrasin vitro. The reaction appears to be more efficient with shorter, less stable RNA stem–loops, likely as the result of higher thermodynamic stabilities of longer viral RNA fragments with multiple and more stable RNA helices. This agrees well with previous observations that mammalian reovirus σNS fails to unwind a 17-bp long helix (in vitro. However, in infected cells this process requires expression of NS2 and formation of viroplasms prerequisite for RNA replication and packaging (The strand-annealing activity of σNS appears to result from helix unwinding, followed by strand hybridization, presumably mediated by the proximity of two complementary strands bound to a single hexamer Figure . This mong helix , while tng helix . Interesackaging .In ARVs, strand-annealing reaction leads to a stable helix formation between the two strands, resulting in displacement of the σNS hexamer from the duplex Figure  A, or itKd for ssRNA. It should be noted that early morphogenesis of ARVs occurs exclusively within the viroplasm (Figure While the ARV σNS has high affinity for unstructured ssRNA, the amount of protein required for its helix-unwinding and strand-annealing activities is significantly above its m Figure , into whm Figure . Thus, tm Figure  B, consiReoviridae, RNA–RNA interactions are likely to be involved in genome assortment and packaging (In ackaging . For aviackaging ,53,68. H


Echinococcus spp. differentiation.High-resolution melting (HRM) provides a low-cost, fast and sensitive scanning method that allows the detection of DNA sequence variations in a single step, which makes it appropriate for application in parasite identification and genotyping. The aim of this work was to implement an HRM-PCR assay targeting part of the mitochondrial cox1 gene to achieve an accurate and fast method for Echinococcus granulosus (n = 41) and Echinococcus ortleppi (n = 50) from bovine, Echinococcus vogeli (n = 2) from paca, Echinococcus oligarthra (n = 3) from agouti, Echinococcus multilocularis (n = 6) from monkey and Echinococcus canadensis (n = 2) and Taenia hydatigena (n = 3) from pig. DNA extraction was performed, and a 444-bp fragment of the cox1 gene was amplified. Two approaches were used, one based on HRM analysis, and a second using SYBR Green Tm-based. In the HRM analysis, a specific profile for each species was observed. Although some species exhibited almost the same melting temperature (Tm) value, the HRM profiles could be clearly discriminated. The SYBR Green Tm-based analysis showed differences between E. granulosus and E. ortleppi and between E. vogeli and E. oligarthra.For melting analysis, a total of 107 samples from seven species were used in this study. The species analyzed included Echinococcus using part of the mitochondrial gene cox1. This method may be also potentially applied to identify other species belonging to the Taeniidae family.In this work, we report the implementation of HRM analysis to differentiate species of the genus  Taenia Linnaeus, 1758 and Echinococcus Rudolphi, 1801. Currently, there are nine recognized species within the genus Echinococcus, and four of them have medical significance: Echinococcus multilocularis, Echinococcus granulosus, Echinococcus oligarthra and Echinococcus vogeli[E. granulosus has been recently revised, and species status was attributed to some of its 10 genotypes (G1-G10): E. granulosus sensu stricto (G1-G3), E. equinus (G4), E. ortleppi (G5), and E. canadensis (G6-G10) [Echinococcus genus, E. shiquicus and E. felidis[E. granulosus and E. ortleppi and for E. oligarthra and E. vogeli[Taenia consists of approximately 50 species that are difficult to identify. Most of these are of medical and veterinary importance and lead to systemic (cysticercosis and coenurosis) and intestinal infections (taeniasis) [The cyclophyllidean family Taeniidae is generally accepted to be composed of two valid genera, G6-G10) . Anothericto G1-G, E. equiequinus G, E. ortl-G10 . AnCryptococcus neoformans-Cryptococcus gatti complex, and for parasites of the phylum Platyhelminthes and Protozoa [Trypanosoma cruzi, the HRM method has been implemented based on the amplification of a 383-bp DNA fragment of the cytochrome b gene (cyt b), allowing the effective differentiation of 14 genotypes and showing that the use of amplicons derived from mitochondrial genes is reliable and sufficiently robust for use in HRM [As a genotyping tool, the high-resolution melting (HRM) method has been used for the rapid differentiation of influenza A subtypes, for identification of the Protozoa -13. For Echinococcus genus. In this work, we report the successful implementation of HRM analysis to differentiate species of the genus Echinococcus using part of the mitochondrial cox1 gene.The aim of this work was to develop an HRM-PCR assay targeting part of the mitochondrial cox1 gene to achieve a rapid, accurate, and low cost diagnostic method for detecting species belonging to the E. granulosus and E. ortleppi was performed from protoscoleces, using proteinase K, and from germinal layer [A total of seven species belonging to the Taeniidae family were used in this study Table . The DNAal layer ,15. DNA 2, 1 U Taq polymerase , 20 mM Tris–HCl (pH 8.4), 50 mM KCl, in a total volume of 20 μL. The PCR reactions were performed in a 7500 thermal cycler (Applied Biosystems) under primer annealing touchdown strategy [A 444-bp fragment of the cytochrome c oxidase subunit I (cox1) gene , was ampstrategy . All PCR, in which the dissociation step was obtained from the 7500 Applied Biosystems machine (with SDS software) using 1X SYBR green dye  and increasing the temperature from 60°C to 95°C at ramping increments of 0.2°C/s  as described above, in attempt to show that this method is reproducible with alternative systems. As reference curves of HRM, a known sample for E. granulosus and E. ortleppi was used.To validate HRM-cox 1 profiles, 58 isolates of http://www.ncbi.nlm.nih.gov).One positive amplicon of each sample derived from PCR-HRM that displayed distinct curve shapes were sequenced. Sequence quality assessment and assembly was performed using DNAStar software (version 8.1.3). After PCR amplification, confirmation of the species was performed by a homology search against reference sequences using the Basic Local Alignment Search Tool (BLAST) program hosted by the National Centre for Biotechnology Information . With SYBR Green Tm-based and HRM analyses, very low Tm variability was observed (Table E. multilocularis and E. ortleppi or between E. canadensis (G7) and E. oligarthra (Table E. ortleppi and twenty-six of the samples obtained were identified as E. granulosus sensu stricto (G1)  Table C. The reE. granulosus from E. ortleppi as well as E. vogeli from E. oligarthra using the Tm obtained from the melting analysis of cox1. Furthermore, we compared this species with E. multilocularis, E. canadensis and T. hydatigena, and discriminated them by HRM, that is a useful and advantageous method that can be routinely employed in endemic regions of echinococcosis. This observation will be useful for additional HRM analyses of the Taeniidae family and, thus, will serve as a basis for subsequent interpretations.We show, for the first time, that it is possible to distinguish Echinococcus species identification has been the subject of numerous studies. For instance, morphological differences and the cut-off value for adult and larval hook were determined to distinguish E. granulosus sensu lato isolates [The development of fast and effective tools for isolates ,21. HoweEchinococcus genotyping tool, a multiplex PCR (mPCR) test was used, using eleven pairs of primers, and it successfully differentiated the species of the Echinococcus granulosus complex [Echinococcus genus (Figure Echinococcus took approximately 6 hours. Recently, the application of HRM analysis was reported for genotyping E. granulosus sensu lato in Iran to distinguish G6 from the G1 and G3 genotypes, but it did not show good results in distinguishing G1 from G3 [In an attempt to implement an  complex . Here, ws Figure A and B.  from G3 .Echinococcus species in epidemiological surveys or in basic research (Figure In conclusion, we propose the use of HRM of the cox1 gene as a routine method to distinguish h Figure . This meHRM: High-resolution melting; NTCs: Non-template controls; BLAST: Basic local alignment search tool; Tm: Melting temperature; SD: Standard deviation.There are no conflicts of interest.GBS participated in the design of the study, and in the HRM experiments. Wrote the manuscript. SME participated in the SYBR Green Tm-based experiments, helped to draft the manuscript. HBF participated in the design of the study and helped to draft the manuscript. RM participated in HRM experiments and helped to draft the manuscript. AZ participated in the design of the study and helped to draft the manuscript. All authors read and approved the final version of the manuscript.


Using a modified microcirculation imager (integrated sidestream dark field - laser speckle contrast imaging [SDF-LSCI]), we experimentally investigate on the influence of the optical properties of scatterers on α in vitro and in vivo. We found a good agreement to theoretical predictions within certain limits for scatterer size and multiple scattering. We present a practical model-based scaling factor to correct for multiple scattering in microcirculatory vessels. Our results show that SDF-LSCI offers a quantitative measure of flow velocity in addition to vessel morphology, enabling the quantification of the clinically relevant blood flow, velocity and tissue perfusion.Laser speckle flowmetry suffers from a debated quantification of the inverse relation between decorrelation time ( V through the morphology of the vasculature (e.g. vessel diameters and vessel density).Quantitative imaging of microcirculatory blood supply to tissues is of paramount importance for diagnosis, therapy planning and monitoring, e.g. of metabolic, vascular and critical diseases1467K, defined as the ratio of the standard deviation (σi) to the mean (<I>) of the pixel intensity, decreases with increasing ratio of the camera exposure time T and the characteristic timescale of the speckle dynamics τc20Laser speckle flowmetry10111213141516179τc as a measure of blood flow, velocity or tissue perfusion is confounded2223τc = αV in flow phantom experiments, the exact value of the proportionality constant α is debated and has not been verified in vivo24α ranged from a dependence on system parameters242624α beyond speculation is a necessity.The interpretation of τc and V in microcirculatory vessels or phantom flow channels. Our recent study showed that correction for additional decorrelation sources  improves the relation between τc and V. Since α was suggested to depend on scatterer size through the scatterer phase function24in vitro flow phantom to investigate on the influence of scatterer size and volume fraction. We place our results in theoretical context taking into account the optical properties and experimental geometry, resulting in a practical relation 1/τc = α1A(N) × V where α1 is the proportionality constant for single scattering and A(N) scales for the average number of dynamic scattering events N. Applying this theoretical framework to chick embryo and human microcirculation beds demonstrates the feasibility of LSCI for quantitative mapping of blood flow velocities in vivo. Importantly, LSCI additionally provides means to derive the clinically relevant parameters blood flow and perfusion from the vessel geometry in microcirculation images.Thereto, we integrated sidestream dark field (SDF) microscopy29in vivo was realized using the integrated SDF-LSCI system as schematically shown in τc22τc,total and τc,offset refer to τcfrom vessel and tissue regions, respectively, and are required for our offset correctionAcquiring blood flow velocities and decorrelation times τc of the fluctuation can be used to quantify the motion of scattering particles. The parameter τc parameterizes the temporal electric field autocorrelation function (ACF) g1(τ) describing the sample dynamics. However, g1(τ) and thus τc depend on optical and physical properties of the tissue, e.g. the scattering phase function. Moreover, scattering from more than one moving particle causes faster decorrelation of the speckle pattern (shorter τc). We review the optical properties relevant to our application and their relationship with g1(τ) and τc in 28333635pN(n) is generally taken to be PoissonianpN (n), where the relation between mean (N) and variance (σn2) is determined by the pair correlation function39N is estimated from Monte Carlo simulations of our measurement geometry (g1(τ) and associated τc in terms of optical properties, organization and scattering order.When coherent light backscattered from different positions in biological tissue is imaged on a camera, the ensemble of phase differences gives rise to a randomly varying spatial intensity distribution (speckle). Movement of scatterers results in a temporally fluctuating speckle pattern. The characteristic timescale geometry . The resτc = αV in multiple scattering scenarios, we introduce the rescale parameter A(N), defined as A(N) = τc,1/τc or A(N) = α/α1, where the subscript ‘1’ denotes single scattering. Using the theoretical model outlined above we calculated A(N) for RBCs and a range of values for N, as plotted in Α(N) for Gaussian and Lorentzian shape of g1,(τ) (Α(N) practically relates V to τcin vivo via 1/τc = α1Α(N) × V.To fulfil our aim to quantify the relationship 1/τc of temporal speckle dynamics can be derived from spatial intensity statistics of an imaged speckle pattern (42g1(τ) is appropriateK(T/τc) can be derived for curve fitting, where T is the camera exposure time varied in the measurement. Next to the sought τc the model incorporates the parameters βM2144ρ , with If the detected intensity of the fluctuating scattered light and Is the detected intensity of the light scattered by static components) that can both be measured. The resulting expression is τc can be reliably estimated by applying a multi-exposure acquisition scheme and subsequent nonlinear curve fit1622The characteristic timescale  pattern . After tτc was estimated by fitting c vs. V is plotted for the different sphere sizes, where the slope defines α. For large scatterers  α increases with decreasing size. For small scatterers  however, α is approximately constant. The theoretical predictions for α follow from α plotted (data points) for all scatterer sizes, together with predictions (solid line). The shaded area represents the uncertainty in the calculation due to variations in size and refractive index of the scatterers.Experimental LSCI data was acquired using an integrated SDF-LSCI device . Multi-eα shown in α from 2.5 vol% solutions of 0.6, 7 and 10 μm. In μs and N, which results in a more uniform increase of α with increasing μs resp. N, until α remains constant. α (low μs and N), however for higher α theory overestimates the experimental measurement. We note that for in vivo blood flow velocity measurements small values for α are predicted.In order to determine the effect of concentration, we prepared different volume fractions of solutions of 1, 2 and 5 μm spheres  and detein vivo decorrelation times by imaging the readily available microcirculation of the chorioallantoic membrane of a chick embryo grown ex ovo. Multi-exposure SDF-LSCI and conventional SDF frames were recorded for 35 unique vessels for which RBC tracking was possible, to independently estimate τc (by LSCI) and V (by SDF) of the same vessels. Compared to controlled phantom experiments, first it is essential to account for ‘offset’ decorrelation due to dynamic scattering of photons outside the focal plane or caused by muscle movementsα) can be found. We assume that for the microcirculation, scattering coefficient μs and phase function p(q) are invariant and we can write α(N). This allows rescaling of each τc to N = 1 by a model-based in vivo scaling factor Α(N) = α/α1, denoting the parameters rescaled for single scattering α1 and τc,1. The scaling factor A(N) calculated for chick embryo blood vessels is shown in τc, (top panel) and the rescaled 1/τc,1 (bottom panel) are plotted versus blood flow velocity for the chick embryo blood vessels. The correlation coefficient of the linear fit of 1/τc and 1/τc,1 vs. V improved after rescaling from r = 0.11 to r = 0.74, respectively. The slope of the rescaled linear fit gave α1 = 0.20 ± 0.07 (95% CI), close to theoretical α1 = 0.27 with an uncertainty range of [0.24–0.30] calculated by varying the size ±5% and refractive index nRBC ±1% (τc using A(N) from τc  was 0.41 ± 0.50 (95% CI) for the original data and α1 was 0.39 ± 0.15 (95% CI) for the rescaled data, near identical to the theoretical prediction for α1 of 0.38 with an uncertainty range of [0.34–0.41] calculated by varying the size ±5% and nRBC ±1%. In both (a) and (b) in We assessed nRBC ±1% . Next, wτc map (representing the basic LSCI outcome) and a blood flow velocity map as shown in To illustrate the quantitative imaging ability of laser speckle flowmetry we constructed a 1/in vivo, using a relatively simple and available technique based on LSCI. LSCI suffers from a debated quantitative relationship with blood flow, velocity or tissue perfusion22τcand flow velocity quantified by the proportionality constant αα have been suggested in literature, but disagree in their absolute value and physical dependence262728τc and Vα is particularly influenced by the scattering phase function and multiple scattering effects. Our assumption that the scattering properties of RBCs in the microcirculation are invariant allows for rescaling by the number of scattering events, enabling quantitative in vivo blood flow velocity measurements. This has previously been implemented empirically by rescaling τc by a weighting term that is proportional to the vessel diameterτc is essentially related to flow velocity and vessel diameter/blood content, therefore a strong linear correlation with V alone is not expected, however, by correcting for volume fraction of RBCs the linear correlation is much improved as also evidenced by the reduction in 95% CI range for α1. We estimated the average number of scattering events with Monte Carlo simulations and related their distribution to the Mie-Percus-Yevick (MPY) scattering model of whole blood. This approach resulted in an excellent agreement between theory and experiment, validating α and its correction factor for multiple dynamic scattering, A(N), in vivo for microcirculatory blood flow velocities and confirming that quantitative measurement of flow velocity by LSCI is feasible. Conveniently, vessel diameters and vessel density can be estimated from the images, allowing quantitative mapping of both blood flow and velocity and estimating tissue perfusion using laser speckle flowmetry.In this Article we demonstrate non-invasive quantitative blood flow velocity measurements α is overestimated by theory. For the small scatterers, which are below the resolution limit of the system, the measured α seems to saturate to a value of 2–2.5 μm−1 in our system. A similar value for α was found in our previous report, using 2.5 vol% Intralipid® as flowing fat emulsion with sub-resolution effective scatterer sizeα is expected for small scatterers, albeit at much higher values. Moreover, α does not show dependence on volume fraction for these small spheres  multiple scattering is present for most vessels (our data set: vessel diameter = [10–55 μm]) the average number of scattering events N = α unlikely. Numerically simulating N in vivo and applying the theoretical model to the optical properties of blood allowed to rescale the obtained τc for multiple scattering resulting in a high linear correlation between 1/τc,1 and flow velocity. In addition, the measured α1 is in perfect agreement with the theoretical prediction. Though in vivo α could only be validated against low flow velocities (<2 mm/s) measured by conventional SDF flowmetry, the in vitro experiments verified α up to 15 mm/s indicating that LSCI is capable of measuring high microcirculatory flow velocities as well. Extending the multi-exposure regime to shorter exposure times will increase the maximum flow velocity limit further.In our in vivo scaling factor Α(N) in N can be estimated. To recapitulate, dynamic scattering by multiple moving particles yields a different time-constant τc compared to single scattering. Α(N) is simply the ratio of these time constants (A(N) = τc,1/τc or A(N) = α/α1) at a certain value for N, relating V to τcin vivo via 1/τc = α1Α(N) ×V. Thus, the practical realization of quantitative laser speckle flowmetry necessitates the estimation of N from the geometry of blood vessels. Then, τc,1 is calculated according to 1/τc,1 = (1/τc)/Α(N) and the flow velocity estimated from 1/τc,1≈ [0.38 ± 0.04]V. For comparison to conventional LSCI approaches we also plotted Α(N) for Gaussian and Lorentzian shape of g1,(τ) (pN(n). Rescaling for multiple scattering is thus highly model dependent, where the Lorentzian (A(N) ~ N) and the Gaussian (A(N) ~ √N) model result in an underestimation or overestimation of V, respectively.Our multiple scattering model in whole blood based on the MPY approach matches the experimental results well, therefore the K(T) vs. T curves, based on the assumption that this model accurately retrieves the actual decorrelation time τc, even though our derived g1(τ) is not necessarily purely Gaussian. We verified the validity of this approach by calculation  curve. We therefore conclude that assuming a Gaussian ACF, thereby making the fit model for K(T) analytical and practical, results in an acceptably small error in τc estimation. This result does not imply that scaling factors A(N) should be based on Gaussian approximations to g1(τ) as evidenced by in vivo measured τc to the value τc,1 (for single scattering) using the MPY model-based factor A(N). This highlights an important finding of our study: although the in vivo estimation of τc is valid using a Gaussian form for g1 and its often-used expression for K(T)2124τc to τc,1 is recommended using our MPY-based A(N) in V when using the Gaussian or Lorentzian model respectively. A recent study by Kazmi et al.N-scattering correction using the more straightforward Gaussian approach and found an improved correlation coefficient between 1/τc and V, as compared to uncorrected values. However, the absolute at certain still differed by a factor of 2 for different animals. This good relative relationship between both quantities can also be explained by our modelling in A(N) results in similar relative correction factors between V and τc. Thus, in order to absolutely quantify flow velocity , we believe that our MPY-based rescaling factor, and its related pN(n), are crucial. We emphasize that τcin vivo is subject to additive decorrelation sources along the photon path through tissueWe use the analytical model of culation . It is s1 yields a quantitative blood velocity map . However, in highly scattering tissues such as skin the offset correction warrants further study. To illustrate the importance of the offset-correction in the sublingual microcirculation, we plotted the data from τc,total and 1/τc1,total vs. V. As chick embryo vessels are embedded in a weakly scattering medium (egg-white) and have low vessel density, the offset decorrelation times are long compared to flow decorrelation times and therefore have less influence. For human vessels on the other hand, not applying the offset correction reduces the linear correlation coefficient between 1/τc,1,total and V substantially and the resulting values for α1 deviate from theoretical values  thus ρ needs appropriate estimation/calibration. In vivo, ρ is influenced by imaging geometry, vessel diameter, vessel depth and Hct values and can be estimated from measurements at long exposure times. When neglecting to appropriately estimate ρ the resulting value for τc can deviate majorly16N in vivo using Monte Carlo simulations depends on the geometrical and optical properties such as vessel depth, diameter and μs,blood. Varying the vessel depth between 0.1 and 0.4 mm and the Hct between 30% and 45% resulted in comparable values for N  and the theoretically and experimentally derived value for α1 the relationship between 1/τc and V simplifies to 1/τc = 0.6V, 1/τc = 1.2V and 1/τc = 2.0V for 20, 50 and 100 μm microcirculatory vessels, respectively.To make our results more widely applicable we performed Monte Carlo simulations for a conventional speckle imaging set-up where wide field laser light illuminates tissue at an angle and the backscattered light is captured by a camera directly above the tissue1013141516operties , which gg1 for multiple scattering has been recognized in literature5052g1 between LDF, DWS and our approach are discussed in g1 and a valid expression for pN(n) in the specific geometry. Here we have shown that our experimental α1 = 0.39 (and estimation of pN(n)) matches very well with theory (α = 0.38) and falls in between predictions from the LDF framework  and DWS framework .The approach to calculate in vivo speckle flowmetry reliable estimation of τc, correction for ‘offset’ decorrelationα, for example when choosing flowing scattering solutions in phantom experiments. The highly vascularised chorioallantoic membrane of the chick embryo can be a practical calibration model as an intermediate between in vitro and in vivo validation.The experimental and theoretical findings in this study improve the quantitative flowmetry capabilities of LSCI and show that the clinically relevant parameters blood flow, velocity and tissue perfusion, can be quantitatively represented in SDF-LSCI microcirculation images, escaping the doctrine of qualitative and relative flow measures . This enin vitro)/100 ms (in vivo) using neutral density filters to prevent overexposure  was modified to provide illumination with laser light . Four multimode fibres surround a central imaging pathway  21. Back-exposure . For con2, anatase form, Sigma Aldrich, US) in the concentration [TiO2] = 1 mg/ml to mimic tissue scatteringμs was 7–150 mm−1 as specified in We designed a flow phantom consisting of a polymer tube  embedded in silicone elastomer  mixed with titanium dioxide . Next, nonlinear curve-fitting of τc. Here, βM and ρ were a-priori estimated at T << τc (static phantom) and at T >> τc (flow >15 mm/s and T > 10 ms) respectively, leaving τc the only fit parameter in βM is expected to be constant throughout and was found to be 0.40 ± 0.02. Specifically, ρ was estimated for each scatterer size and volume fraction and kept constant for different flow velocities. The goodness of nonlinear fit <Radj2> averaged over all fits of K(T) vs. T was 0.98 ± 0.02.In vivo: To calculate K a spatiotemporal local region of 7 × 7 × 20 pixels was applied to optimize the in vivo spatiotemporal resolution and minimize the standard deviation in in K (<7%)K values were obtained per vessel (or adjacent tissue region) and T. The exposure time range was extended to longer T [0.5–100 ms] and ρ and βM were a-priori estimated at long and short T respectively. In the subsequent curve fit both were constraint within 5% of their estimated value, and τc was unconstraint. The goodness of nonlinear fit <Radj2> averaged over all fits was 0.99 ± 0.01. The in vivo decorrelation times  were corrected for statistically independent sources of decorrelation via τc,offset measured from adjacent tissue  as described in Supplementary equation (13)In vivo flow measurements were repeated minimally 3 times per vessel and vessels with a large variation in flow were excluded. To correct the decorrelation times for multiple scattering the number of scattering events N in the vessel were estimated using Monte Carlo simulations as described in in vivo scaling factor Α(N) = α(N)/α1, where α(N) was theoretically derived using the optical properties of blood /Α(N).of blood  for N scThe chick embryo experiments are exempt from animal ethics committee approval, in accordance with the EU directive/Dutch law on animal experiments (WOD). For this Article we have not done additional human experiments as we have re-analyzed previously obtained data from human microcirculation ref. .How to cite this article: Nadort, A. et al. Quantitative blood flow velocity imaging using laser speckle flowmetry. Sci. Rep.6, 25258; doi: 10.1038/srep25258 (2016).