Using cross-linking coupled to matrix-assisted laser desorption/ionization mass spectrometry and CLIP-Seq sequencing, we determined the peptide and oligonucleotide sequences at the interfaces between the capsid proteins and the genomic RNA of bacteriophage MS2. The results suggest that the same coat protein (CP)–RNA and maturation protein (MP)–RNA interfaces are used in every viral particle. The portions of the viral RNA in contact with CP subunits span the genome, consistent with a large number of discrete and similar contacts within each particle. Many of these sites match previous predictions of the locations of multiple, dispersed and degenerate RNA sites with cognate CP affinity termed packaging signals (PSs). Chemical RNA footprinting was used to compare the secondary structures of protein-free genomic fragments and the RNA in the virion. Some PSs are partially present in protein-free RNA but others would need to refold from their dominant solution conformations to form the contacts identified in the virion. The RNA-binding peptides within the MP map to two sections of the N-terminal half of the protein. Comparison of MP sequences from related phages suggests a similar arrangement of RNA-binding sites, although these N-terminal regions have only limited sequence conservation. In contrast, the sequences of the C-termini are highly conserved, consistent with them encompassing pilin-binding domains required for initial contact with host cells. These results provide independent and unambiguous support for the assembly of MS2 virions via a PS-mediated mechanism involving a series of induced-fit viral protein interactions with RNA.  •CLIP-Seq reveals a defined set of RNA–coat interactions in a single-stranded RNA virion.•RNA sites match previous predictions of multiple PSs.•Data provide unambiguous confirmation of PS-mediated assembly. High-resolution X-ray structures of ssRNA viruses mostly reveal only a limited ordering of the encapsidated genome, again implying that RNA has no, or very little, overt roles in virion assembly Spherical viral capsids assemble by two distinct mechanisms in vitro and in vivoT = 3 capsid. Electron microscopy (EM) reconstruction of the virion is also consistent with this concept revealing extensively ordered genome segments in contact with the inner surface of the CPs , using X-ray crystallography, and we have investigated the PS-mediated assembly mechanism using mass spectrometry single-molecule fluorescence correlation spectroscopy) T = 3 shell  to separate domains , the N-tmatrix-assisted laser desorption/ionization)-ToF (time of flight) mass spectrometry (The genomic RNA footprint on the capsid proteins within the virion was determined by an RNA cross-linking and peptide mapping assay (RCAP), used previously to map the interaction between the capsid and the nucleic acid of brome mosaic virus trometry a. Controtrometry b. ArginiMS2 virion peptides identified using RCAP are shown mapped onto the amino acid sequences of both the CP c and theThe RNA–MP complex is the only part of the virion to enter the host cell during infection where the MP undergoes proteolytic cleavage into two fragments of 15 and 24 kDa that are presumed to be separate globular domains RNA sequences in contact with the MS2 CP subunits were identified using CLIP-Seq The individual MS2 sequence reads were converted into sense-strand RNA and mapped onto the genomic sequence of the phage creating a histogram of hits at each nucleotide for both irradiated (green) and control (blue) samples, yielding The pattern of peaks, some of which are clearly symmetrical implying discrete sites of contact, is consistent with the presence of the same series of discrete RNA oligonucleotides in contact with the capsid in every virus particle, that is, that the highest matching nucleotide in each peak should be within or adjacent to a PS. A random arrangement of the genomic RNA within each capsid would not be expected to yield this distribution. Importantly, the level of sequencing multiplicity in the MiSeq data (Supplementary Table 2) suggests that they provide an accurate sampling of the virion population; thus, the peaks represent the most frequently cross-linked fragments. Unfortunately, most peaks are not well resolved from their neighbors, making such direct identification more difficult, but the TR site is clearly within one of these higher peaks .There have been two previous attempts to predict the locations of the PSs in the MS2 genome. We used information on the preferred RNA-binding sites for CP from X-ray crystal structures and SELEX together with the reported solution structure of CP-free RNA to create a minimal RNA motif. This yielded 54 of the expected 60 PSs required in this The CLIP-Seq data also contain a sequence previously reported as one of two RNA-binding sites of the MP, Peak 8  correspoin vitro with the full genome and large sub-fragments, all containing the TR site, show that assembly is divided into two separate kinetic phases. There is an initially rapid phase that occurs above a minimum threshold CP concentration during which the RNA conformational ensemble collapses to facilitate encapsidation T = 3 particles. Controlling the partitioning of these two stages is presumably an essential feature of assembly efficiency. One way that this could be achieved is via PSs with a distinct hierarchy of affinities, with higher-affinity interactions forming in the first phase and lower-affinity ones forming in the later phase. Alternatively, the RNA could undergo conformational change revealing functional PSs after the binding of the initial CP subunits.The experiments described above provide direct evidence that MS2 assembles via a PS-mediated mechanism, but they do not address how the CPs locate their respective PS sites during virion assembly. The latter cannot always be present in the active form of a stem–loop due to the many roles the genome plays in the phage lifecycle. Previous smFCS assays of assembly 2 + ions that hydrolyse RNA via the deprotonation of the 2′ OH followed by cleavage of the phosphodiester bond at the 3′ position In order to discriminate between these mechanisms, we carried out secondary structure probing of transcripts encompassing large sections of the MS2 RNA, as well as the intact virion a. This wThe lead-ion-induced hydrolysis sites on three MS2 RNA transcripts  were compared to that of the genome within virions b. We assConserved lead ion hydrolysis sites were observed across all the RNA fragments that together span the MS2 genome . For exaThe conserved solution secondary structure elements in the virion imply that the tertiary RNA conformation is a compacted version of the RNA solution structure TR is the highest-affinity PS within the MS2 genome and is thus the site Starting from the 3′ end of the probed region, there is a CLIP-Seq peak at 2116 that is adjacent to nucleotides with altered accessibility to lead hydrolysis in the virion, implying that this is a PS although it was not previously predicted to be one. The next peak at 2056 lies between two stem–loops predicted to be PSs, XII/SL + 5 and XI/SL + 4, the former having one nucleotide with a detectable change in accessibility. The results with TR and SL − 1 suggest that these sites are indeed PSs. Peak 1960 lies between X/SL + 3 and SL + 2, with both sequences showing some altered lead accessibility, implying two PSs, one present in solution and one that must refold during assembly. Peak 1938 overlaps with the region of SL + 2 and with IX. The latter is not predicted as a PS and shows no changes in lead accessibility; thus, its status cannot be confirmed. Peak 1807 overlaps with VII/SL + 1, which shows some altered accessibility and therefore is likely a PS. Peak 1696 overlaps with V/SL − 1 and IV, the pattern showing increased cleavage at a single nucleotide but seemingly not at a PS. Peak 1634 overlaps an area that undergoes slight changes in accessibility but does not form stem–loops and hence cannot be a PS. Peak 1485 is centered on SL − 2 but is not in the form of a stem–loop and therefore must refold extensively into its PS conformation. It also overlaps with I/SL − 3 where the decreased lead accessibility to the loop region confirms its role as a PS. These correlations with solution secondary structures, CLIP-Seq and PS predictions confirm the ideas of a PS-mediated assembly reaction without the need for extensive mutagenesis that could have pleiotropic effects on MS2 infection.in vitro and, it is assumed, in vivo. This reaction has been proposed to be largely driven by electrostatic interactions. The data presented above show clearly that the end product of such assembly has a highly organized relationship between its virion proteins and genomic RNA, which is most unlikely to arise by a simple charge compaction process. Instead, we have shown that the process is highly regulated and involves multiple RNA–protein contacts at sites distributed throughout the genome, PSs. Such interactions occur in viruses from bacteria  are similar to those seen in high-resolution X-ray structures of the TR bound to every position. In principle, each PS contact within a genome would be to an A/B dimer . The VLPWe have also investigated the architecture of the MP. Its contacts to the genome are localized to the N-terminal half of the molecule, consistent with predictions of two RNA-binding sites in this region. Although these RNA-binding motifs seem to occur across a large range of the known MPs, the sequences of these N-termini are quite variable. In contrast, there is extensive conservation at the C-termini, perhaps consistent with it encompassing the pilus-binding domain.in vitro. This scenario is somewhat analogous to that seen for assembly of the ribosome Combining CLIP-Seq information with RNA chemical structure probing allows us to interrogate the presence/appearance of PSs before and after virion assembly. It is clear that there are two classes of PS sites, those that are detectable in the protein-free RNA and those that are only detected after CP-induced refolding and capsid assembly. Presumably, the PS folds are flickering in and out of existence and the lead ions are sensitive to equilibrium. This is consistent with the two phases of assembly previously detected using smFCS Escherichia coli. The virions were purified 4 and 50 mM Hepes (pH 7.5)] to identify regions in the MS2 CP and MP that contact the RNA. The RCAP protocol was as described in Ni et al.MS2 virions were from the American Type Culture Collection and propagated in male strains of 4 and 50 mM Tris–HCl (pH 7.5)] were irradiated at 400 mJ/cm2 by 254-nm light, on ice in a CL-1000 ultraviolet cross-linker (UVP). The samples were mixed with gentle pipetting and incubated on ice for 3 min. Irradiation was repeated twice more. The virions were then pelleted by ultracentrifugation at 60,000 RPM for 4 min at 4 °C and resuspended in RNA fragmentation buffer [100 mM Tris–HCl (pH 7.0) and 10 mM ZnCl2] at 70 °C for 20 min. The reaction was quenched by adding EDTA, pH 8, to a final concentration of 42 mM. Immunoprecipitation used an anti-MS2 CP serum (EMD Millipore) bound to protein A/G magnetic beads (Pierce) according to the manufacturer's protocol. The eluted CP–RNA complex was electrophoresed on a NuPAGE 4–12% (w/v) Bis-Tris SDS-PAGE gel in 1 × 4-morpholineethanesulfonic acid buffer on ice and then transferred to a nitrocellulose membrane using a wet transfer apparatus (BioRad) at 100 V for 1 h. The membrane was stained with 0.1% (w/v) Ponceau-S in 5% (v/v) acetic acid for ~ 5 min, and the region 6–100 kDa above the CP band was excised from the membrane. Material on the membrane was digested with 0.8 mg/mL proteinase K at 37 °C for 1 h to release the cross-linked RNA fragments. The RNA was extracted using Trizol and precipitated with 3 volumes of ethanol containing 0.3 M ammonium acetate.MS2 virions in SM buffer ATP for 30 min at 37 °C according to the manufacturer's instructions (NEB). The material was then electrophoresed in NuPAGE 4–12% (w/v) Bis-Tris SDS-PAGE gel in 1 × 4-morpholineethanesulfonic acid buffer. The gel was wrapped in plastic film and the signal was detected using a Phosphorimager. Western blots of the CP were performed as described in Hema et al.To visualize and quantify the RNAs covalently attached to MS2 CP, we incubated CP–RNA complexes treated with ZnClFASTQ Quality Trimmer, removing the 3´ adaptor and discarding any reads shorter than 15 nt using Clip. The cleaned reads were aligned to the MS2 reference genome using Bowtie2 Analysis of the MiSeq reads used the Galaxy user interface Leviviridae MP sequences were identified using BLASTP and TBLASTN searches at National Center for Biotechnology Information MS2 MP secondary structure composition was predicted using the Jpred3 algorithm RNA-binding sites in MPs were predicted using the RNABindRPlus server 4OAc and 1 mM Mg(OAc)2 (pH 7.2). We then added 2 μL of freshly prepared 2 mM lead acetate to each reaction to a final concentration of 0.4 mM lead ions. Reactions were incubated at room temperature for 5, 10, 30 and 60 min followed by addition of 5 μL of 0.1 M EDTA, 1.5 μL of 3 M NaOAc and 35 μL of EtOH and were stored at − 20 °C for ≥ 2 h. RNA was recovered as a pellet by centrifugation at 13,000 RPM and washed once with 70% EtOH prior to resuspension in 5 μL DEPC-treated H2O. Wild-type MS2 capsids were treated similarly but were phenol/chloroform extracted prior to precipitation with 3 M NaOAc. Prior to reverse transcription, the appropriate 32P-labeled primer was annealed to the cleaved RNA by addition of 1 μL of 1 μM labeled primer stock solution and incubated at 65 °C for 10 min followed by snap cooling on ice. The primers used for reverse transcription were as follows:1568_R:AAGCTCTACACCACCAACAGTCT1666_R:CCTTGCATTGCCTTAACA1812_R:CGCGAGGAAGATCAATACATA1951_R:TCATTACCAGAACCTAAGGTCGGA2061_R:GATCCCATGACAAGGATTTG2223_R:TAACGGTTGCTTGTTCAGCThe production and purification of the MS2 RNA fragments was as previously described Reverse transcription was performed with Transcriptor® reverse transcriptase (Roche Diagnostics) at 52 °C for 30 min according to the manufacturer's description. Single-stranded DNA products were then precipitated by addition of 3 μL of 3 M NaOAc and 60 μL of EtOH, recovered by centrifugation and washed once with 70% EtOH and allowed to dry at room temperature for 15 min. Single-stranded DNA was dissolved in 95% formamide RNA loading buffer and run on 6–8% (w/v) denaturing polyacrylamide slab gels versus control after 60 min was higher in sample containing lead ions, this was defined as a hydrolysis position. The nucleotide position of induced hydrolysis within the MS2 genome was deduced from dideoxy sequencing ladders (G and C) and a size standard. Identified positions were not quantified, and thus, a comparison of cleavage intensities between RNAs was not performed. All lead-ion-induced hydrolysis was therefore identified in a Boolean manner with regard to the abovementioned criteria. Lead ion hydrolysis positions were mapped onto the MS2 genome and their nucleotide positions were compared with respect to whether cleavage occurred only in the RNA sub-genomic fragments in vitro, only within the virion or in both the virion and the sub-genomic fragments in vitro. The numbers of cleavages occurring in these three groups were taken as an indicator of structural similarity of these RNAs in the different environments.Lead ion cleavage positions were identified from exposed film first and foremost as signals whose intensity increased with increasing lead ion incubation time. An absence of a signal in the control lane was taken as an indicator but not a requirement of lead-ion-induced cleavage. Because control reactions were incubated in assembly buffer for 60 min at room temperature, non-specific hydrolysis sites were always detected. If intensity at these positions was observed to increase in the presence of lead acetate over time and the intensity with lead ions Supplementary Tables− 1). Protein–RNA contacts seen in the X-ray crystal structure are shown as dotted lines. Peptides cross-linking to the genomic RNA are in red (see Peptides in contact with genomic RNA in the virion. Peptides from (a) the CP or (b) MP identified by MALDI-ToF of formaldehyde cross-linked virions are highlighted by colored bars above the sequences for trypsin digestion alone (red) or trypsin plus Glu-C (blue). These results are also summarized in  red see b.Comparison of lead ion cleavage maps. The map highlights all lead ion cleavage positions identified within the 1450-2190 region of all sub-genomic RNAs and the genomic RNA within the virion. Cleavage sites are indicated with vertical bars that are color coded according to the RNA. No discrimination is made between strong and weak cleavage positions when the cleavage sites were identified from autoradiographs. The annealing positions of the primers used in primer extension reactions are shown as black arrows.The following are the supplementary data related to this article.


SNF7 inhibits BMV RNA replication > 25-fold and abolishes detectable BMV spherule formation, even though the BMV RNA replication proteins accumulate and localize normally on perinuclear ER membranes. Moreover, BMV ESCRT recruitment and spherule assembly depend on different sets of protein-protein interactions from those used by multivesicular body vesicles, HIV-1 virion budding, or tomato bushy stunt virus (TBSV) spherule formation. These and other data demonstrate that BMV requires cellular ESCRT components for proper formation and function of its vesicular RNA replication compartments. The results highlight growing but diverse interactions of ESCRT factors with many viruses and viral processes, and potential value of the ESCRT pathway as a target for broad-spectrum antiviral resistance.Positive-strand RNA viruses genome replication invariably is associated with vesicles or other rearranged cellular membranes. Brome mosaic virus (BMV) RNA replication occurs on perinuclear endoplasmic reticulum (ER) membranes in ~70 nm vesicular invaginations (spherules). BMV RNA replication vesicles show multiple parallels with membrane-enveloped, budding retrovirus virions, whose envelopment and release depend on the host ESCRT  membrane-remodeling machinery. We now find that deleting components of the ESCRT pathway results in at least two distinct BMV phenotypes. One group of genes regulate RNA replication and the frequency of viral replication complex formation, but had no effect on spherule size, while a second group of genes regulate RNA replication in a way or ways independent of spherule formation. In particular, deleting  Positive-strand RNA {(+)RNA} viruses cause numerous human, animal, and plant diseases. (+)RNA viruses reorganize host intracellular membranes to assemble their RNA replication compartments, which are mini-organelles featuring the close association of both viral and host components. To further understand the role of host components in forming such RNA replication compartments, we used brome mosaic virus (BMV), a well characterized model virus, to study some common features of (+)RNA virus RNA replication. We show that knocking out several components of the cellular Endosomal Complex Required for Transport (ESCRT) machinery resulted in parallel defects in BMV RNA replication and replication compartment formation, whereas other ESCRT components affected RNA replication independently of replication compartment formation. Deleting a subset of ESCRT proteins altered the frequency of replication compartment formation but had no effect on the size of these compartments, whereas a second subset affected RNA replication independently of replication compartment formation. Moreover, BMV’s interaction with the ESCRT machinery appears to be distinct from that reported for other viruses and from the ESCRT requirements for forming vesicles in cellular multivesicular bodies. These findings further illuminate the remarkable abilities of positive-strand RNA viruses to integrate viral and host protein functions to remodel membranes, and suggest potentially potent new ways to control such viruses. A universal feature of positive-strand RNA ((+)RNA) viruses is that they multiply their RNA on intracellular membranes, usually in association with vesiculation or other membrane rearrangements –3. CelluSaccharomyces cerevisiae . To. To~100 hse1 Δ), ESCRT-II (vps36 Δ), or the Vps4 accessory proteins Vta1 and Vps60 did not significantly affect either negative-strand RNA3 or positive-strand RNA4 synthesis  and nonionic (1% NP-40) detergents to disrupt membranes, and anti-1a or anti-HA antibodies and protein A sepharose beads were used to precipitate protein complexes. Total cell lysates and the immunoprecipitates eluted from protein A sepharose beads were subjected to SDS-PAGE and immunoblotted using anti-1a or anti-HA antibodies. As expected, on Western blots of lysates that were immunoprecipitated with anti-1a antibodies, a 1a signal was detected for all samples expressing 1a  that are known to disrupt its interaction with Bro1p [E233Q, a Vps4p mutant that is incapable of mediating ESCRT-III disassembly [snf7 Δ yeast expressing BMV 1a, Snf7L231A/L234A-HA and Vps4E233Q-FLAG, Snf7L231A/L234A-HA co-localized with 1a in the perinuclear ER, showing that Bro1p is not required for Snf7p to interact with 1a  , 43. Preth Bro1p . Additioassembly . In snf7 with 1a . This reAs noted earlier, in wt yeast, expressing 1a alone induces the invagination of the outer, perinuclear ER membrane to form spherular compartments associated with BMV RNA protection and replication . IntriguBromoviridae in yeast [To determine whether the formation or structure of such spherules was affected by deleting the tested ESCRT proteins, we examined wt and single-knockout yeast by electron microscopy (EM) and measured the abundance and diameter of spherules in the subset of cells that were sectioned through the nucleus among a total of 250 cells for each strain. In wt yeast, the average diameter of spherules was 67 ± 9 nm , similarin yeast  and planin yeast –25.vps2 Δ, 20 Δ, 23 Δ and did2 Δ), which inhibited RNA4 production to 10–33% of wt, produced spherules at 77–90% of normal frequency RNA viruses, we tested tobacco mosaic virus (TMV), which replicates in the perinuclear ER , and tobSince the assembly of BMV RNA replication complexes shares multiple similarities with budding retroviral virions , we inveBelow we discuss the roles of Snf7p, Vps4p and associated factors in BMV spherule formation, how the ESCRT dependence of BMV spherule formation differs from that of MVB formation, retrovirus budding and tombusvirus spherule formation, and how some ESCRT factors contribute to BMV replication independently of spherule formation, and compare ESCRT dependence of BMV spherule formation to its dependence on host reticulons, another class of membrane-shaping proteins [Our results show that ESCRT requirements for MVB vesicle formation and BMV spherule formation differ in important ways. MVB formation requires sequential recruitment of ESCRT-0 to cluster ubiquitinated cargo, the ESCRT-I and-II supercomplex to generate membrane invaginations into the MVB lumen, and ESCRT-III to direct membrane scission and vesicle release , 37. In snf7 Δ yeast. Both spherule formation and BMV RNA replication in snf7 Δ yeast were restored upon ectopic expression of HA-tagged Snf7p ,  ~6-fold . Similaron Figs. . While tpherules , 65. Botpherules , 67, andpherules .Based on insights from electron microscope tomography, a new model for HIV budding was proposed in which HIV-1 Gag accumulates at the membrane, forming a partial shell that leads to plasma membrane invagination. Subsequently, Gag recruits ESCRT-I and—III factors, which constrict the initially wide membrane rim induced by Gag assembly, contributing further membrane bending to complete formation and budding of a full, vesicular membrane envelope lined by a partial Gag shell .Similarly, our recent results show that 1a parallels HIV-1 Gag in achieving high-level multimerization on the ER membrane, and implicate this 1a multimerization as one critical driver of membrane invagination , perhapsWhile ESCRT-III constriction continues to cleave the vesicle neck to release MVB intralumenal vesicles and HIV-1 virions, BMV avoids this step, leaving the spherule neck stably attached to the ER membrane as neck scission might be blocked by 1a, host factors or both. One possibility shown in VPS4 , vps23Δ (YPH500 vps23::kanMX4), vps36Δ (YPH500 vps36::kanMX4), vps20Δ (YPH500 vps20::kanMX4), snf7Δ (YPH500 snf7::kanMX4), vps24Δ (YPH500 vps24::kanMX4), vps2Δ (YPH500 vps2::kanMX4), vps4Δ (YPH500 vps4::kanMX4), vps60Δ (YPH500 vps60::kanMX4), did2Δ (YPH500 did2::kanMX4), vta1Δ (YPH500 vta1::kanMX4). Genomic replacements were made using amplified KanMX4 cassettes flanked by 5’ and 3’ homologous recombination regions. The strain expressing the chromosomal alleles of RTN1 as a GFP fusion was obtained from Invitrogen . For endogenous expression of ESCRT proteins, the coding region of the full-length protein plus the ~500 base-pair upstream sequences were PCR amplified from wt yeast DNA with appropriate primers and inserted into a CEN plasmid. An HA- or a FLAG-tag was added at the C-terminus of the ESCRT ORFs. Snf7L231A/L234A-HA and Vps4E233Q-FLAG were created by site directed mutagenesis.Yeast strain YPH500 and culture conditions were as described previously . The folArabidopsis thaliana SNF7–2 in the yeast snf7Δ mutant strain, AtSNF7–2 cDNA was amplified by PCR and inserted into ycpLAC33, a CEN plasmid. An HA tag sequence is attached to the 3’ end of AtSNF7–2 coding sequence and expression is under the control of the GAL1 promoter. Plasmids expressing the dominant negative mutant of AtSNF7–2, SNF7-HZZ, was made by adding the sequence of the HZZ multitag from pBG1805 at the 3’ end of AtSNF7–2 using PCR. The multitag from pBG1805 contains 6×His, HA, and the ZZ domain of protein A [GAL1 promoter using pB1YT3L, a pB3YT3 [LEU marker, 2apol was expressed from pB2CT15 (ADH1 promoter) [CUP1 promoter from pB3VG128H, or under control of a GAL1 promoter from pB3MS82, both RNA3 derivatives have a four-nucleotide insertion in the coat protein gene that abolishes expression of the coat protein [EcoRI and PstI digestions. Plasmids launching tobacco mosaic virus (TMV) and tobacco rattle virus (TRV) by agroinfiltration were pTRBO [To express rotein A . AtSNF7-rotein A , which ea pB3YT3  derivati protein . To makere pTRBO  and pTRVre pTRBO .N. benthamiana plants were grown in a growth chamber under long day conditions (16 h light and 8 h dark) at 26°C. Agrobacterium infiltrations were performed following a protocol described by Bendahmane et al. 2000 [600 reached 0.8–1.0. Agrobacterial cells were brought to OD600 = 1.0 in the infiltration solution  and incubated at room temperature for at least 3 hours. These cultures were then mixed for co-infiltration suspensions with final concentrations listed as followings: BMV RNA1, 2, or 3 at OD600 = 0.05; pTRBO, pTRV-1 and pTRV-2 at OD600 = 0.25; pMD32-RFU1, or pAG2P-HZZ at OD600 = 0.5. The aforementioned culture combinations were co-infiltrated into 8-week-old plants. After 48 hours, the infiltrated leaves were harvested for RNA extraction. Plants infiltrated with BMV only or co-infiltrated with pMDC32-RFU1-HZZ were used as controls. For the Northern blot in al. 2000 . Agrobac600 units of yeast cells grown to mid-logarithmic phase were spheroplasted and resuspended in 350 μl buffer TNE (50 mM Tris-HCl (pH 7.4), 150 mM NaCl, 5 mM EDTA, 5 mM benzamidine, 1 mM PMSF, and 10 μg/ml each aprotinin, leupeptin, and pepstatin A). Spheroplasts were lysed via 25 passes through a 22 gauge, 4 cm long needle. Total lysates were centrifuged for 5 minutes at 4°C at 500×g to remove cell debris, and 250 μl of supernatants were mixed with 500 μl of 60% Optiprep . Density gradient centrifugation was performed for 2 hours at 55,000 rpm in a Beckman TLS55 rotor using 600 μl of each sample overlaid by 1.4 ml of 30% Optiprep and 100 μl of lysis buffer [Ten ODs buffer . After cpol, anti-Dpm1, anti-FLAG and anti-Pgk1 antibodies were as described [Total yeast RNA isolation by the hot phenol method, Northern blot analysis, total protein extractions and Western blot analysis, and anti-1a, anti-2aescribed , 81, 82.Yeast cells were lysed in RIPA buffer  using glass beads and a bead beater and the supernatant was collected after centrifugation. For immunoprecipitation, yeast lysates were mixed with Protein A Sepharose beads  and anti-1a, anti-HA, or anti-GFP antibodies overnight at 4°C. Beads were pelleted and washed with RIPA buffer before boiling in 1x SDS gel loading buffer and running samples in 4–15% SDS-PAGE gels.pol proteins. To detect the localization of the ESCRT proteins, HA-tagged ESCRTs were transformed with empty plasmids or plasmids encoding BMV 1a. Cells were fixed with 4% formaldehyde, spheroplasted with lyticase, and permeabilized with 0.1% Triton X-100. Spheroplasts were then stained either by using rabbit anti-1a serum, mouse anti-PDI, mouse anti-HA antibodies or combinations thereof followed by anti-rabbit or anti-mouse secondary antibodies conjugated to Alexa-488, or Alexa-568. For nuclear staining, a 10-minute incubation with 300 nM DAPI (Invitrogen) was added after secondary antibody incubation. Fluorescent images were acquired with a Nikon A1R Bio-Rad inverted confocal microscope system. To avoid spectral bleed-through in the multi-color imaging, images were acquired by sequentially scanning with the individual lasers and detecting fluorescence in each channel to coincide with laser illumination.Confocal microscopy was as described . BrieflySamples were prepared for electron microscopy as described . In brieS1 Fighse1Δ, or vps36Δ deletion strains expressing 1a, 2apol, and RNA3 and accumulation of negative-strand RNA3 and positive-strand subgenomic RNA4 was measured by Northern blotting. Equal loading was verified by probing for 18S ribosomal RNA. Values represent the mean of four independent experiments, with each condition tested in triplicate in each experiment. A representative blot is shown. All samples were compared to the wt control using a two tailed student t-test. ns: not significant.Total RNA extracts were obtained from wt, (EPS)Click here for additional data file.


However, the actual temporal and sequential dynamics of successive choices made among multiple alternatives remain unclear. In the current study, we tested the hypothesis that there is a general bursting property in both the timing and sequential patterns of foraging decisions. We conducted a foraging experiment in which rats chose among four different foods over a continuous two-week time period. Regarding when choices were made, we found bursts of rapidly occurring actions, separated by time-varying inactive periods, partially based on a circadian rhythm. Regarding what was chosen, we found sequential dynamics in affective choices characterized by two key features: (a) a highly biased choice distribution; and (b) preferential attachment, in which the animals were more likely to choose what they had previously chosen. To capture the temporal dynamics, we propose a dual-state model consisting of active and inactive states. We also introduce a satiation-attainment process for bursty activity, and a non-homogeneous Poisson process for longer inactivity between bursts. For the sequential dynamics, we propose a dual-control model consisting of goal-directed and habit systems, based on outcome valuation and choice history, respectively. This study provides insights into how the bursty nature of behavior emerges from the interaction of different underlying systems, leading to heavy tails in the distribution of behavior over time and choices.A fundamental understanding of behavior requires predicting  when an action is made and what is chosen. Here, we conducted a foraging experiment in which rats chose among four different foods over a continuous two-week time period. With respect to when, we found bursts of rapidly occurring responses separated by long inactive periods. With respect to what, we found biased choice behavior toward the favorite items as well as repetitive behavior, reflecting goal-directed and habitual responding, respectively. We account for the when and what components with two distinct computational mechanisms, each composed of two processes: (a) active and inactive states for the temporal dynamics, and (b) goal-directed and habitual control for the sequential dynamics. This study provides behavioral and computational insights into the dynamical properties of decision-making that determine both when an animal will act and what the animal will choose. Our findings provide an integrated framework for describing the temporal and sequential structure of everyday choices among, for example, food, music, books, brands, web-browsing and social interaction.To understand spontaneous animal behavior, two key elements must be explained:  Although the processes governing when and what to choose have been studied in their own right, how both sets of underlying mechanisms together produce the dynamical properties of behavior over time remains poorly understood. To help characterize these fundamental mechanisms and their interaction, we examined and modeled the foraging decisions of rats in a paradigm designed to mirror the daily life of mammals composed of continuous free choices among multiple alternatives.Humans and non-human animals engage in a number of distinct activities on a daily basis, from working to attain resources to resting. Once engaged in a particular activity, such as foraging, they typically must select among multiple alternatives a number of times before they are satisfied. A systematic understanding of behavior, then, requires a characterization of the mechanisms that determine bursts of high activity separated by long inactive periods heavy tail in the distribution of the inter-event intervals  Rather than regular, like a metronome, or homogenous , timing of behavior and/or events in humans, non-human animals, and natural phenomena is often non-homogeneous, with periods or Although a non-homogeneous process has been suggested as a universal feature of natural dynamical systems Here, we focus on foraging, a fundamental and frequent behavior for survival. Foraging mechanisms underlie the daily energy budget allocation across activities i.e., it is bursty Feeding behavior has been studied in large data sets of farm animals, pets, and captive wild animals, including cattle, pigs, chickens, ducks, turkeys, rats, and dolphins Once activity timing is characterized, the decision dynamics of which option to select and whether to continue selecting it over repeated choices must be specified Therefore, the second objective of the current study was to help specify the mechanisms underlying seemingly unpredictable preference-based choices with (a) multiple qualitatively different options; and (b) repeated choices over an extended period in a stable environment that reflects real-world choice behavior. Here we extracted two distinctive features from an individual's dynamic choice sequence: (1) preference bias , and (2) choice persistence , which capture distinct underlying control processes that determine what to choose and whether to continue choosing it, respectively.We found individual differences in preferences that nonetheless could be characterized by choice option rank, reflecting a value-based process, as well as some persistent choice behavior, in which choices tended to be repeated, with an increasing likelihood of repeating a choice as a run of identical choices increased, reflecting a preferential-attachment process. We then developed a dual-control model incorporating a combination of goal-directed and habitual control to describe the dynamical patterns of the choice sequences.We investigated the continuous choice behavior of 12 rats over the course of two weeks using a four-armed bandit task with four differently flavored pellets: chocolate, banana, coffee, and cinnamon. Each rat lived in an operant chamber for the entire two-week duration as a “closed economy” when and what the animals chose, timing and choice sequences of lever-pressing activity for all rats were recorded for the entire experiment. With respect to when they chose, the animals actively foraged during the dark cycle and sporadically so during the light cycle as shown in what they chose, we found dynamic changes in the animals' food choices, indicating that the rats did not commit themselves to a specific option but rather intermittently explored alternatives.To examine p<0.001). Thus, this result shows that previous choices influenced the current choice, consistent with other reports To assess the degree of the animals' exploration or exploitation, we first computed entropy of choice sequences every hundred trials F  = 0.781, p = 0.511)   = 0.009, p = 0.998), suggesting that the animals' response vigor for each location was similar We next examined the amount of consumed pellets with respect to flavor, location, and rank. Rank was defined as the order of overall consumption of each food type for an individual, which would reflect the order of an individual's subjective values for the qualitatively different rewards. The percentages of mean choice for the four different locations – left (LL), middle left (ML), middle right (MR) and right (RR) – were not significantly different  , reflectF  = 5.043, p<0.01): the chocolate flavor was statistically more consumed than the coffee flavor at the group level   , althoug= 0.021) ; nonetheF  = 74.897, p<0.001; Dunnett-T3 post hoc test).Since the rats exhibited individual differences in preference, and since quality has no obvious natural corresponding number to represent its value , we analyzed choice behavior based on rank, which should be driven by an individual's subjective values of the options, and which provides a common scale to compare individuals. Comparing the percentages of mean choice for rank, there was a clear difference between food pellets of different ranks as shown in p as a function of rank r was well described by the log-linear distribution (p versus log(r) was −70.7±4.95 , indicating that preference was highly skewed toward the higher rank.Interestingly, choice rate appeared to decrease by nearly half as rank increased. To confirm this tendency, we transformed the percentage of food choice by rank to a log-linear scale. We found that the mean distribution of the choice percentage ribution , where tspecific timing of foraging was determined at a short timescale.Examining the timing characteristics of the choice behavior in more detail, we found periodic changes in food consumption. First, the animals consumed more pellets during the dark than the light cycle . To inveB, defined as B ranges between −1 and 1: B = 1 is the most bursty signal, B = 0 is neutral, and B = −1 is a completely periodic signal. We found that B of the foraging behavior was 0.794±0.008 (mean ± s.e.m), indicating that the majority of activity was densely concentrated in short durations.We characterized the underlying action dynamics by analyzing the features of the inter-choice interval (ICI) distribution. We found that the majority of ICIs were short, but very long ICIs also sporadically occurred, indicating that there were bursts of activity separated by relatively long inactive periods . To meas1m (2m) and M ranges between −1 and 1: M is positive when the length of the current ICI is positively proportional to the length of the previous ICI; whereas, M is negative when the length of the current ICI is inversely proportional to the length of the previous ICI; M = 0 is neutral; and M = −1 is a completely periodic signal. We found that M of the foraging behavior was 0.046±0.006 (mean ± s.e.m), indicating that the foraging activity had a relatively low correlation between consecutive ICIs.Next, to characterize a memory effect, we calculated the correlation coefficient of consecutive inter-choice intervals, which is defined as The bursty nature of the foraging behavior was reflected in the heavy-tailed ICI distributions. The cumulative distribution of ICIs, which is the probability of ICIs longer than a given ICI , exhibited a heavy tail that was clearly seen in a log-log scale, representing a deviation from an exponential distribution resulting from a simple homogeneous Poisson process . This inp = 0.68±0.09 for the fit to the power-law distribution—i.e., the empirical and power-law distributions were not significantly different; see “Estimation of parameters in the inter-choice interval (ICI) distribution” in Material and Methods)   inset. TMethods) .λ is a scale parameter, and γ is the shape parameter of the distribution. We calculated the value of 0τ as the local minimum of the bimodal distribution of ICIs, which separated the short and longer ICIs in the distributions. The estimated parameters of the bimodal ICI distributions are shown in Thus, the cumulative bimodal ICI distributions for both the light and dark cycles could be described as the following:λ , whereas the power-law distributions for the short ICIs in both cycles appeared to have similar slopes   . This fiwhat is chosen over trials. First, we determined how long the rats continued to make the same choice. We defined a “run” as a series of consecutive identical choices. A trial-dependent change in a distribution of runs was then calculated, as shown in We next analyzed the choice patterns to examine the sequential dynamics governing p<0.001) To test for a sequential dependency of previous choices, we compared the run distributions of the empirical sequences with those of randomly shuffled sequences of the same data for each rat. The randomly shuffled sequence has no dependency on previous choices yet maintains the same choice frequency as the empirical data. The cumulative run distribution of the empirical data was significantly different from that of the randomly shuffled choice sequences for all subjects  In addition, we examined whether there was an effect of choice history regardless of rank by comparing the run distribution of empirical data for each rank with that of randomly shuffled data . AlthougF  = 0.666, p = 0.577). Thus, in general, the rats were more likely to choose what they had chosen previously, irrespective of outcome, reflecting a status quo bias or preferential-attachment process that tends to continue a run until switching one's choice finally becomes more compelling.Conducting a simple calculation with the cumulative distribution of runs, we obtained the hazard rate for ending a run as a function of the number of preceding choices in a run for each rank, i.e., the conditional probability of ending a run at a given length of a run . We founWe next propose two models that capture the temporal and sequential dynamics of free choice behavior. First, we account for the temporal features of the decision patterns by proposing a dual-state model that captures both the bursty property and the circadian rhythm influence on the rats' choice behavior, leading to a heavy-tailed distribution of the ICIs with bimodality. Second, we account for the sequential features of the decision patterns by proposing a dual-control model that incorporates the combination of two distinct control processes: goal-directed and habit control, which characterize the bias in choice frequency with respect to rank order and the heavy-tailed nature in the run distribution, respectively.A bimodal distribution has been suggested as a mixture of distinct distributions formed by different underlying processes satiation-attainment process, i.e., an active waiting process based on feedback for upcoming satiation within each active state. In this process for the active state, we assume that whenever animals eat, they wait for the feedback signal by which they determine whether to eat more or stop. In other words, animals initiate eating and wait until they receive the satiety signal, which informs them that satiation is attained. If the satiety signal is lower than the satiation threshold, they would continue to eat and wait for the next feedback signal. Thus, the waiting time between eating and the feedback signal is important to determine time intervals between actions in an active state. Instead of a constant time delay of feedback, we assume that there is a non-linear relationship in the waiting time between eating and the feedback signal. A number of studies on human dynamics have suggested that the waiting time based on feedback in human communication patterns follows a power-law distribution We consider an animal to be in an active state when the animal exhibits a high frequency of activity, with short ICIs that are less than a certain time period T is the period of the process. Since the animals' periodic activity is modulated by a circadian rhythm, we set the period T as 1 day. Second, the inactivity rate b is the shape parameter. To quantify the transition between active and inactive states, we assume that a state transits from the active state to the inactive state with a probability ξ after each choice and remains in the active state with probability 1 – ξ.In addition, an animal is considered to be in an inactive state when there is a period of inactivity longer than when choices are made specified, we next delineate those that determine what choices are made. Here, we propose a simple heuristic model that accounts for two key sequential features of decision-making: (1) the heavy-tailed nature of the run distribution, reflecting choice persistence as habitual behavior, and (2) the biased rank distribution, reflecting goal-directed outcome valuation.With the computational processes that determine habitual control.First, to account for persistence in choice behavior, we assume an underlying preferential-attachment process, which has been proposed as the mechanism underlying heavy-tailed distributions i at trial t, i on trial t. The choice vector i was chosen on trial t and 0 if the option was not chosen on that trial.In the habit system, in addition to the preferential-attachment process, we apply a leaky integrator to the dynamic trial-by-trial model of habitual behavior, in which the integrated choice frequency over previous trials is discounted as a function of the distance passed from a given trial t, the action value for the chosen option c and for the unchosen option u are updated according to:t for the chosen and unchosen options, respectively. The reward prediction errors, i.e., the difference between the expected and received reward values, for the chosen and unchosen options are as follows:Second, for goal-directed control, we use a temporal difference (TD) reinforcement learning algorithm that updates the action-value on each trial according to its prediction error R: i at trial t, Finally, for action selection, to capture the effects of both the habit and goal-directed systems on choice behavior, the goal-directed value We conducted simulations based on the dual-state model to examine how well the model captured the temporal dynamics of foraging behavior . We set details) . Using teach rat .First, we compared the cumulative ICI distributions of the empirical data with those of simulated data. The cumulative ICI distributions of empirical and simulated data were similar to each other, with the simulated data exhibiting a heavy tail with bimodality in agreement with that of the empirical data . Next, wTo determine whether the dual-control choice model could capture the two key sequential features in the choice patterns – a biased rank distribution and a heavy-tailed run distribution – we simulated choice sequences for individual rats with the best-estimated free parameters and then compared the fits of the models to the empirical data. We estimated the free parameters of the model for each rat by minimizing the negative log-likelihood of the individual choice sequences  [72].r2 results in the far right column of We found that the predictions of the dual-control model significantly deviated from that of a random choice model for all subjects, indicating that the model fit to the empirical data was significantly better than chance (the pseudo- c+u); (2) the goal-directed control model alone with update for the chosen option only, i.e., standard TD learning for the chosen option ; (3) the habitual control model alone (Habit); (4) the submodel of dual-control  composed of the mixture of Goalc (with update for the chosen option only) and Habit; and (5) The dual-control model  composed of the mixture of Goalc+u (with update for the chosen option and decay for the unchosen options)and Habit  The goal-directed control model alone with update for the chosen option and decay for the unchosen options  distribution comprised of a power-law for the short timescale  and the Weibull distribution for the longer timescale . Although the specific mechanisms of the bimodal inter-event times could vary across different systems Regarding For the short timescale, we found an inverse square power-law distribution for short ICIs with exponent For the longer timescale, we found that longer ICIs follow the Weibull distribution in both the light and dark cycles. At the same time, the cumulative distributions of the longer ICIs in the light and dark cycles exhibited different decay rates. One possible account for this difference between the light and dark cycles is the effects of the circadian rhythm on the motivation for general activity The longer ICIs are likely influenced by the homeostatic hunger drive. The Weibull distribution is commonly used to describe the time to a first event what was chosen, we examined sequential dynamics underlying free choice patterns in a stable environment in which an animal could obtain the food items with certainty. Despite the certainty of reward delivery as well as a stable reward value, the rats exhibited rich choice dynamics rather than a monotonous pattern. In contrast to the popular notion that goal-directed behavior gives way to automatic habitual behavior in a stable environment Regarding rank as a means to measure their relative subjective value based on individual preference. Indeed, we found a highly biased rank distribution toward an individual's favorite option. This rank distribution reflects one of goal-directed behavior's key properties, that action selection is guided by the value of outcomes to the individual To extend beyond quantity-based decision-making, in this study we focused on the dynamics underlying choices based on individual preference with respect to qualitatively different rewards with different flavors. Because qualitatively different rewards have no obvious corresponding numerical value, we used In our dual-control model, the subjective value of qualitatively different rewards was deductively estimated from each individual's choice behavior on the basis of the generalized matching law in which the choice rate matches the relative value of the options modulated by a sensitivity parameter To capture both the value-based and internal amplifying control processes, we modified the standard TD algorithm For habitual control, the dynamic choice patterns revealed two key characteristics of habitual behavior: repeated responses and insensitivity to outcome Our empirical study shows that even in stable environments animals can exhibit rich temporal and sequential behavioral dynamics. In addition, our modeling work demonstrates how the interaction of different underlying processes can give rise to dynamic activity patterns. A dual-state model suggests that dynamic transitions between active and inactive states produce bursty and circadian rhythmic properties of temporal dynamics. A dual-control model suggests that goal-directed and habitual control processes cooperate, rather than compete, to generate sequential dynamics of choices that lead to a better option and increase the reliability of a performed action. Considering the ubiquity of decision-making in the lives of animals and in our everyday lives, temporal and sequential dynamics of spontaneous choice behavior raise the intriguing possibility that such dynamics derive from a harmonious collaboration of multiple underlying neural control systems – a collaboration that, when discordant, may lead to aberrant decisions such as binge eating or other forms of addictive behavior.All procedures of animal care and experiment were performed according the KAIST guidelines for the care and use of laboratory animals and approved by the KAIST Institutional Animal Care and Use Committee.Twelve eight-week-old naïve male Sprague Dawley rats weighing 250–350 g were used in the study. The rats had all experienced a standard laboratory diet, and none had experience with the flavors used in the experiment.ad libitum access to water. Food was available according to the experimental task described below. The four types of flavored 45 mg pellets—chocolate, banana, coffee, and cinnamon—were made from the same meal substrate  and were consequently matched with regards to all macro- and micro-nutrients. The locations of the flavored pellets were counterbalanced across subjects.Each rat was individually housed in an operant chamber see  and mainTrials were signaled by the illumination of the nose-poke light  inside the box. When the light was on, a nose-poke into the lighted opening resulted in the nose-poke light turning off and four retractable levers  extending on the opposite wall. A press of one of the four levers initiated (a) the delivery of a food pellet according to the flavor assigned to that lever as well as (b) the retraction of all levers. After a pellet was delivered, the nose-poke light was turned on again for the next trial. During the experiment, the spontaneous choices and corresponding response times were recorded  BIC = −2•LL + k•ln Nr2 statistic defined as (R-L)/R, where R is the log-likelihood of the random choice model and L is that of our models where LL is the log-likehood of the model, k is the number of parameters of the model, and N is the number of trials. To examine how much better the models fit to empirical data compared to a random choice model, we calculated a pseudo-Figure S1Illustration of the experimental apparatus. The rat was required to nose-poke and then press one of four levers to receive the particular flavored food pellet in the corresponding receptacle. Water was freely accessible and located above the nose-poke hall.(TIF)Click here for additional data file.Figure S2c+u model; the Goalc model; the Habit model; and the Goalc+Habit model for all four ranks. (B–G) Red, orange, green, and blue represent the rank order from rank 1 to rank 4, respectively.Comparison of choice models for an example rat (subject 7). (A) The cumulative run distributions of the empirical data and the model predictions. (B) The cumulative choice frequency of the empirical data for all four ranks (C–G) The prediction of the dual-control model ; the Goal(TIF)Click here for additional data file.Figure S3Comparisons of the simulation of the dual-state model with the empirical data. Cumulative ICI distributions of the empirical data (black squares) and the simulated data (red circles) are presented in a log-log scale for all 12 rats.(TIF)Click here for additional data file.Figure S4Comparisons of a choice sequence generated from the dual-control model with the empirical data. Cumulative run distributions of the empirical data and the simulated data are displayed in a log-log scale for all 12 rats. The black squares denote the empirical data and the blue circles the simulated data. In addition, cumulative choice frequency graphs for each rank for both the empirical data (solid lines) and simulation (dashed lines) are displayed. Red, orange, green, and blue represent the rank order from rank 1 to rank 4, respectively.(TIF)Click here for additional data file.Table S1The estimated parameters from 12 subjects for choice models. Values are given as mean (s.e.m).(DOCX)Click here for additional data file.Text S1Supporting text. Experiment apparatus, data pre-processing, choice model comparison, and appendix for modeling results of all subjects are described.(DOCX)Click here for additional data file.


In addition, whether the aptamer-fluorogen system may perturb the native RNA characteristics has not been systematically characterized at the levels of RNA transcription, translation and degradation. To increase the brightness of these aptamer-fluorogen systems, we constructed and tested tandem arrays containing multiple Spinach aptamers (8–64 aptamer repeats). Such arrays enhanced the brightness of the tagged mRNA molecules by up to ~17 fold in living cells. Strong laser excitation with pulsed illumination further increased the imaging sensitivity of Spinach array-tagged RNAs. Moreover, transcriptional fusion to the Spinach array did not affect mRNA transcription, translation or degradation, indicating that aptamer arrays might be a generalizable labeling method for high-performance and low-perturbation live cell RNA imaging.Live cell RNA imaging using genetically encoded fluorescent labels is an important tool for monitoring RNA activities. A recently reported RNA aptamer-fluorogen system, the Spinach, in which an RNA aptamer binds and induces the fluorescence of a GFP-like 3,5-difluoro-4-hydroxybenzylidene imidazolinone (DFHBI) ligand, can be readily tagged to the RNA of interest. Although the aptamer–fluorogen system is sufficient for imaging highly abundant non-coding RNAs (tRNAs, rRNAs,  We also characterized the effects of such tandem arrays on mRNA transcription, translation, localization and degradation, and found that the Spinach array does not alter these RNA characteristics, indicating that making tandem repeats of these aptamers might be a generally applicable strategy for mRNA live cell imaging.Here we use Spinach as our model system and fused multiple repeats of the Spinach aptamer in tandem on a single RNA molecule. We applied the tandem Spinach arrays to cellular mRNA imaging. In both nR, n = 8, 16, 32, 64). Between two adjacent aptamer repeats we inserted 17-nt randomized spacer sequence, which was used for constructing tandem repeats of MS2 RNA sequence26in vitro and cellular RNA expression under the control of T7 promoter and lac operator system, respectivelyin vitro transcribed Spinach arrays (100 nM RNA) were measured using a fluorometer after RNA folding and incubation with DFHBI (20 μM). Compared to single Spinach aptamer (Spi), Spi-nR shows greatly enhanced fluorescence signal with the same maximum excitation/emission wavelengths at 460/505 nm  as binding to single Spinach aptamer (Spi)  .nR may misfold more extensively through inter-aptamer misfolding, similar to the example where repeat proteins are known to misfold due to interdomain interactions5152There are two possible explanations for the less than 2-fold increase in the brightness when the repeat number was doubled: fluorescence quenching between adjacent aptamers, and misfolding/incomplete folding of multiple aptamers2735nR )  of the monomeric red fluorescent protein (mRFP1) coding sequence ) . For comE. coli transcribing RFP-Spi showed no fluorescence enhancement in the Spinach channel over the background autofluorescence level of cells expressing untagged RFP  generally reflects the in vitro trend (~16 fold enhancement from Spi to Spi-64R). Moreover, distinct from the homogenously distributed fluorescence observed for RFP-Spi-tRNA, the fluorescence signal of RFP-Spi-nR preferentially accumulated at cell poles. In order to determine whether the apparent difference in cellular localization between the two constructs is caused by Spinach arrays, we conducted an RNA FISH experiment on cells expressing RFP, RFP-Spi-tRNA or RFP-Spi-nR , using Cy5-labeled oligonucleotide probes targeting the mRFP1 sequence  as a function of time after IPTG removal  with a native lacZYA promoter (Plac) for RFP-Spi-32R transcription (Plac-RFP-Spi-32R). RNA synthesis by endogenous E. coli RNA polymerase instead of T7 polymerase reduced the mRNA expression level by approximately two orders of magnitude according to qPCR quantification , where we hardly observed any fluorescence signal (lac-RFP-Spi-32R (~50–180 mRNA copies per E. coli cell), where we found bright spots in many cells residing at cell poles , we further applied pulsed illumination strategy to effectively boost the fluorescence of the Spinach array such that we could observe mRNA localizations. Despite the 17-fold fluorescence enhancement achieved by constructing the aptamer array, we also noted that the average efficiency for an aptamer to correctly fold seems to decrease with the increase of the aptamer repeat number. One possible reason for this is the crosstalk and mispairing between adjacent or spatially close aptamers in a tandem array, which were reported and discussed for tandem arrays in previous RNA and protein folding studies515253The Spinach system is a recently developed RNA labeling and imaging method based on aptamer binding and fluorescence induction of the fluorogenic small molecule DFHBIcoli  using thE. coli, Spinach array-tagged mRNA had no significant alterations on transcription, translation or degradation. This may be attributed to the small size and high dissociation constant (KD) of the fluorogen. In contrast, the MS2/PP7 coat protein labeling method has been reported to impede RNA degradation in bacteria in previous studiess2611With a series of characterizations on the aptamer tandem array, we demonstrated that in etc, showed the potential to further enhance the performance. All of those newly discovered fluorogen/aptamer systems have similar fluorescing mechanisms as that of the Spinach aptamer while showing higher brightness, shorter length or more robust folding behavior. We envision that incorporating the newly reported aptamers into a tandem array could also enhance their fluorescence signals per RNA molecule. Furthermore, we expect the tandem arrays derived from those aptamers would be very likely to bring minimal perturbation to their target RNAs, due to their similarities to the Spinach aptamer.In conclusion, we constructed a tandem Spinach aptamer array that could enhance fluorescence imaging quality of the Spinach/DFHBI system for live cell RNA imaging while introducing minimal perturbation to the target RNA. Nevertheless, Spinach arrays still show several limitations, including relatively low brightness and large size, making them ill-suited for studying mammalian cells, where autofluorescence is stronger and RNAs are more dispersedly distributed and undergo intensive motor-driven transport. Several recently developed fluorogen/aptamer systems, including RNA Mango, Spinach 2, Broccoli, The methods can be found in the How to cite this article: Zhang, J. et al. Tandem Spinach Array for mRNA Imaging in Living Bacterial Cells. Sci. Rep.5, 17295; doi: 10.1038/srep17295 (2015).


The centrality of RNA within the biological world is an irrefutable fact that currently attracts increasing attention from the scientific community. The panoply of functional RNAs requires the existence of specific biological caretakers, RNA helicases, devoted to maintain the proper folding of those molecules, resolving unstable structures. However, evolution has taken advantage of the specific position and characteristics of RNA helicases to develop new functions for these proteins, which are at the interface of the basic processes for transference of information from DNA to proteins. RNA helicases are involved in many biologically relevant processes, not only as RNA chaperones, but also as signal transducers, scaffolds of molecular complexes, and regulatory elements. Structural biology studies during the last decade, founded in X-ray crystallography, have characterized in detail several RNA-helicases. This comprehensive review summarizes the structural knowledge accumulated in the last two decades within this family of proteins, with special emphasis on the structure-function relationships of the most widely-studied families of RNA helicases: the DEAD-box, RIG-I-like and viral NS3 classes. RNA molecules often need to fold into specific three-dimensional structures in order to exert their biological functions. RNA folding is an intrinsically difficult problem which is commonly prevented by two major RNA features: the chemical characteristics of RNA make it “prone to misfold”, thereby becoming trapped into inactive energy minima; and the functional conformations are sometimes not energetically favored over the overall universe of folding intermediates . For theX-ray crystallography studies of selected small and medium-size RNA molecules determined that the rules governing RNA folding are complex and comparable to those observed in proteins ,5. With −1 for human RNA PolII, 50–100 nt·s−1 for bacterial polymerases and 200 nt·s−1 for viral polymerases), it is evident that the majority of nascent RNAs will undergo folding during transcription. First evidence of co-transcriptional folding was obtained by the study of ribozymes, showing that transcriptional pausing events also affect RNA folding [ in vitro models, and this fact has prevented a wider knowledge of the nucleic acid folding processes within cells [RNA folding is a relatively rapid process when compared with other biological time scales; small RNA molecules will fold in the range of pico to the milliseconds, whereas large RNAs may need minutes to hours to reach their functional three-dimensional structures . Tertiar folding ,15,16. Iin cells ,18.Intramolecular interactions are the main driving forces that control the propensity of RNA to form secondary and tertiary structures. Some of these interactions are required for RNA maturation, localization or biological activity; however some of them could be also deleterious for its properties. The centrality of RNA molecules within cells has designed an ubiquitous and largely heterogeneous group of proteins, globally known as RNA chaperones or RNA helicases, that help RNA to reach and maintain its functional conformational state ,19. SomeRNA helicases are RNA-binding proteins able to resolve secondary and tertiary RNA structures in an active manner, in some cases coupling this enzymatic activity to the hydrolysis of ATP ,22,23. THuman RNA helicases are included in five different sub-families: Upf1-like, DEAD-box, DEAH-RHA, RIG-I like and Ski2-like proteins  . This class of RNAs are >200 bp in length, lacking significant protein coding capacity. The biological roles of lncRNAs are diverse, ranging from the transcriptional control of gene expression at the chromatin level to the interactions with other regulatory RNAs as miRNAs ,69. In sThe RIG-I family of helicases is composed of multidomain proteins that belong to the innate immune system, a well conserved first line of defense against pathogens. The mission of the innate immune system is to generically detect pathogen-associated molecular patterns (PAMPs), which include RNA molecules harboring stable secondary structures as double-stranded regions, but also other molecules from the external surface of the invading agents. Defense lines integrated within the innate immunity comprise the presence of extracellular and intracellular receptors. The RIG-I-like family of proteins (RLRs: RIG-I-like receptors) are part of the cytoplasmic receptors for PAMPs, interacting with nucleic acid molecules from infecting viruses . RLRs acThe RIG-I family of cytoplasmic receptors is composed of the retinoic-acid inducible gene , the melanoma-differentiation associated (MDA5) and the LGP2 genes. Besides these genes, the RIG-I family of helicases also includes DICER, a hybrid helicase-nuclease involved in the biosynthesis of miRNAs and the RNA interference process ,82. The N-terminal region is composed of two caspase-recruitment domains (CARDs), followed by the typical helicase core region formed by two RecA-like domains. The C-terminal region of the protein contains a regulatory domain, characteristic of this family, which harbors a structural Zn atom [The RIG-I protein, the main representative of this protein family, was initially identified as a coding transcript associated with retinoic acid-induced differentiation of acute promyelocytic leukemia cells, being included in a wider family of interferon-stimulated genes . RIG-I i Zn atom ,79. RIG- Zn atom ,88. The  Zn atom ,90. Stru Zn atom . Recentl Zn atom  showed tN-terminal CARD domains are interacting with the Hel2i domain, blocking the RNA-binding pocket formed between the Hel1 and Hel2 domains , which interacts with the RNA bases  comes in several flavors, namely methods such as SHAPE-seq [ in vivo RNA structure determination is based on the chemical or enzymatic probing of secondary RNA structures followed by a sequencing step. This powerful family of methods is however limited by the intrinsic characteristics of the RNA-seq protocols, and also by the structural diversity of RNA molecules. Methods such as Structure-seq [However, many questions related to this cohort of proteins remain to be answered, including the determinants of specificity (if they exist) for each particular RNA helicase and the additional functions of these proteins rather than those related to RNA folding. Also a matter of further studies will be the presence of putative groups of functionally specialized RNA helicases, devoted to the control of the homeostasis of selected groups of RNAs such as non-coding RNAs. High-throughput techniques will also be essential for the characterization of RNA helicase function in several contexts, especially for the determination of their roles in the pervasive transcription and the homeostasis of non-coding RNAs. Recently a new family of methods that combine high-throughput sequencing with RNA structure probing has been developed ,125. TheHAPE-seq , StructuHAPE-seq , Mod-seqHAPE-seq , Dash-seHAPE-seq , or SPOTHAPE-seq . The subture-seq  and Mod-ture-seq  are baseture-seq . Combiniture-seq ,125. Othture-seq ,130. TheThus, this family of widespread proteins is composed of essential players within the core of the cellular transfer of information and constitutes a very exciting scientific area, which has been empowered by the rising importance of the non-coding genomic output. The already described roles of RNA helicases in some human diseases will certainly open new research areas with the aim of characterizing the functional factors that regulate RNA homeostasis within the cell and their relationships with the onset and progression of RNA-dependent diseases.


Double-stranded (ds) RNA is a key player in numerous biological activities in cells, including RNA interference, anti-viral immunity and mRNA transport. The class of proteins responsible for recognizing dsRNA is termed double-stranded RNA binding proteins (dsRBP). However, little is known about the molecular mechanisms underlying the interaction between dsRBPs and dsRNA. Here we examined four human dsRBPs, ADAD2, TRBP, Staufen 1 and ADAR1 on six dsRNA substrates that vary in length and secondary structure. We combined single molecule pull-down (SiMPull), single molecule protein-induced fluorescence enhancement (smPIFE) and molecular dynamics (MD) simulations to investigate the dsRNA-dsRBP interactions. Our results demonstrate that despite the highly conserved dsRNA binding domains, the dsRBPs exhibit diverse substrate specificities and dynamic properties when in contact with different RNA substrates. While TRBP and ADAR1 have a preference for binding simple duplex RNA, ADAD2 and Staufen1 display higher affinity to highly structured RNA substrates. Upon interaction with RNA substrates, TRBP and Staufen1 exhibit dynamic sliding whereas two deaminases ADAR1 and ADAD2 mostly remain immobile when bound. MD simulations provide a detailed atomic interaction map that is largely consistent with the affinity differences observed experimentally. Collectively, our study highlights the diverse nature of substrate specificity and mobility exhibited by dsRBPs that may be critical for their cellular function. While all cellular RNA molecules are synthesized in single-stranded (ss) form, many can form into secondary structures that encompass segments of double stranded (ds) RNA. Hence, dsRNA molecules are common in cells and are recognized as critical regulatory factors in many biological processes –3. For eThe family of proteins responsible for processing dsRNA is called double stranded RNA binding proteins (dsRBP). Various dsRNAs serve as cargoes, activators and substrates of dsRBPs in many biological pathways ,5. For eThe dsRBP family is defined by the presence of one or more double-stranded RNA binding domains (dsRBD) . The dsRTwo types of dsRBDs are found in dsRBPs; type-1 dsRBD (dsRBD-I) usually binds dsRNA while type-2 (dsRBD-II) is mainly involved in protein–protein interaction ,14. The To address some of these outstanding questions, we examined dsRNA interaction with four dsRBPs: ADAD2, TRBP, Staufen1 and ADAR1. We chose dsRBPs that contain different number of dsRBD-I units and participate in various cellular functions. ADAD2 has only a single dsRBD-I, followed by Staufen1 and TRBP containing two, and ADAR1 possessing three units of dsRBD-Is. In terms of biological function, both ADAD2 and ADAR1 are RNA deaminases that edit adenosine to inosine (A to I) in mRNA and microRNA precursors . StaufenWe investigated the binding affinity of the four dsRBPs toward six different dsRNA substrates with varying length and secondary structure. The length variants include 25, 40 and 55 bp dsRNA whereas the imperfectly base-paired/structured RNA includes pre-let7 (pre-microRNA), TAR RNA and tRNA-like RNA. All proteins were overexpressed in mammalian cells (HEK 293) and pulled down to a single molecule imaging surface coated with the appropriate antibody . In addi3 at pH 8.5 and then incubated overnight. Unreacted dye was removed by two rounds of ethanol precipitation. The resulting labeling efficiency was ∼90%. For tRNA preparation, we incubated 1 μM of tRNA in a buffer containing 10 mM Tris, 50 mM NaCl, 3 mM MgCl2, pH 7.5 at 90°C for 2 min and quickly cooled it down on ice. Due to the protocol, we expect the tRNA sample to include some misfolded, yet secondary structured RNAs  and heated at ∼90°C for 2 min and gradually cooled to room temperature. U40 with 3′ amine modification was purchased from IDT and labeled with Cy3 NHS ester dye from GE Healthcare . Brieflyred RNAs . TherefoADAD2, TRBP and Staufen1 were cloned from Human Open Reading Frame Library and a C-terminal EYFP was added to each protein sequence. Then, C-terminal EYFP-TRBP, C-terminal EYGP-Staufen1 and N-terminal EGFP-ADAR1 were overexpressed in human A549 cells, and C-terminal EYFP-ADAD2 was overexpressed in HEK293 cells. Cells were lysed using RIPA  24 h after transfection and cell lysates were collected and centrifuged; finally supernatants were collected for each protein. The dsRBP levels were quantified by fluorometry measurement based on EYFP or EGFP intensity using cy5 dye as standard . Cell lysates were stored in −80°C for later use.Polyethylene glycol (PEG)-coated quartz slides with flow chambers were obtained according to previously published protocol . A PEG s® 488 Conjugate . We note that anti-GFP antibody is sufficient to pull down EYFP as well as GFP.To measure the level of dsRBPs on the PEG surface, we used the level of TRBP-EYFP as standard for all dsRBPs, since the concentration of four dsRBPs were calibrated and dilution factors were normalized to make sure they were applied at the same level on the PEG surface. To measure the level of TRBP after SM Pull-down using biotinylated GFP antibody, we used anti-TRBP antibody (Abcam [1D9](ab129325)) and Anti-mouse Alexa FluorSingle-molecule detection of protein–RNA interaction dynamics assay was achieved employing custom-built prism-type total internal reflection fluorescence (TIRF) microscopy ,31. AfteIn order to complement the experimental studies, we examined structural models of RNA constructs used in experiments and several of the dsRNA binding domains (dsRBDs). Structures of U40 and 25, 40 and 55 bp dsRNA were prepared with the software 3DNA . 3D struTo compare dsRNA-binding interfaces of studied dsRBDs, we either examined existing crystal structures or prepared homology models as described below. dsRBDs with known structures include TRBP dsRBD 1 (pdbID 3LLH), TRBP dsRBD 2 (pdbID 3ADL), and ADAR1 dsRBD 3 (pdbID 2MDR). The homology models of three additional dsRBDs were prepared employing the Protein Model Portal : StaufenThe stability of prepared homology models of dsRBDs was examined through PACE hybrid resolution model simulations, where dsRBDs were described with a united-atom model, placed in a coarse-grained solvent model ,37. PACE2). Then, unconstrained complexes were simulated for 100 ns (TRBP dsRBDs) or 55 ns . The simulations were performed in NpT ensemble, at a constant temperature T = 310 K, a Langevin constant γLang = 1.0 ps−1, and at a constant pressure p = 1 bar.To examine the binding strength between dsRNA and individual dsRBDs, we simulated complexes of dsRNA with: (a) TRBP-dsRBD2, based on pdbID 3ADL, (b) TRBP-dsRBD1, based on pdbID 3LLH, (c) ADAR1-dsRBD3, based on pdbID 2MDR, (d) ADAD2 dsRBD, based on the above described homology model. Initial structures of complexes were based on the crystal structure of TRBP-dsRBD2 bound to coaxially stacked RNA duplexes (pdbID 3ADL), where the resolved RNA was replaced by a 35-bp RNA duplex, prepared with the software 3DNA . The sysFour dsRBPs, ADAD2, TRBP, Staufen1 and ADAR1 were chosen because they all have at least one dsRBD-I (type I dsRBD) with highly conserved amino acid residues Figure  and B. HUpon determining the concentration of each protein based on the fluorescence intensity of EYFP/EGFP , the same concentration of each dsRBP was applied on a single molecule surface coated with anti-GFP/anti-YFP antibody  Figure . We confTo investigate the RNA binding specificity of the four dsRBPs, 1 nM of Cy3-labeled RNA molecules was applied to the dsRBP-immobilized imaging surface Figure . The fluAfter checking the density of dsRBP molecules on the imaging surface, we applied Cy3 labeled RNA, washed out the unbound RNA and visualized the fluorescence signal by home-built total internal reflection fluorescence (TIRF) microscope Figure . The sinWe quantified the fraction of RNA-bound dsRBP to total dsRBP molecules (sum of bound- and unbound molecules) for each dsRBP with six dsRNAs and one ssRNA. Amongst the four dsRBPs, TRBP showed the highest relative binding affinity to all substrates, mostly ranging between 80 and 90%, except for the reduced binding to tRNA (∼50%). Staufen1, ADAR1 and ADAD2 exhibit substantially lower affinities to all RNAs in general; on average, 20–40% of protein was occupied by RNA Figure . NotablyThe four dsRBPs also displayed different binding affinities to various structural features of RNAs. To compare the binding propensity toward structured RNA, we obtained the average of all bound fractions corresponding to structured  and non-structured RNA  substrates for each dsRBP Figure  and calcIn conclusion, the four tested dsRBPs exhibit different substrate specificities in our single molecule platform, which may arise from different binding affinities toward RNA substrates with varying secondary structures. Furthermore, RNA binding affinity of dsRBP does not seem to depend on the number of its dsRBD-I.Previously, we had reported that TRBP exhibits ATP-independent sliding/diffusion activity along dsRNA . The motThe sliding activity of dsRBPs was detected using single molecule protein induced fluorescent enhancement (smPIFE) , in whict) reflects the average time it takes for the proteins to complete one round of sliding along dsRNA axis . For both TRBP and Staufen1, the dwell time distribution exhibited a clear length dependence, i.e longer time taken for sliding a longer distance, indicating that the PIFE signal fluctuation likely represents sliding activity  binds to siRNA with higher affinity than does dsRBD1 (Kd = 220 nM)  . In cont 220 nM) . Our MD The functions of dsRBPs are implicated in diverse cellular pathways including micro RNA, RNA editing, antiviral signaling and mRNA transport. We sought to profile a set of dsRBPs in three respects. First, we probed the binding specificity of dsRBPs to different lengths and structures of dsRNA that are relevant to cellular RNAs. Second, we examined dynamic properties of dsRBP–dsRNA interactions, based on our previous study of TRBP sliding . Third, There are ∼30 known dsRBD-containing proteins in human cells. Most of the dsRBDs, including dsRBD1 and dsRBD2 of TRBP, dsRBD2 of Staufen1 and dsRBD3 of ADAR1, possess the canonical dsRNA binding motifs that contact the minor–major–minor pattern on A-form dsRNA helix Figure . One excKd = 0.21 nM), or with lower affinity when dimerization is prevented due to a single mutation (Kd = 2.2 nM) (Our binding affinity results indicate a plausible distinction between the strong (TRBP) and weak binders  to dsRNA, although most of the dsRBDs contain all the dsRNA binding consensus residues (besides ADAD2 and Staufen1-dsRBD3). A possible reason for this discrepancy in RNA binding strength might be the presence of a basic residue adjacent to the KKxxK motif (either K or R) observed in several dsRBDs; MD simulations show that such R residue of TRBP dsRBD2, which is not present in dsRBD1, enhances the binding strength of only dsRBD2 to dsRNA . Alterna 2.2 nM) .It is interesting and puzzling that the number of type-1 dsRBD per protein is highly variable in the dsRBP family, ranging from one to five. It is not known if the number of dsRBDs determines its binding strength to dsRNA or if they contribute to substrate specificity of the dsRBP. We characterized four dsRBPs with a different number of dsRBDs. Our data shows that the binding affinity of dsRBPs toward RNA substrates is not necessarily correlated with the number of dsRBD-Is Figure . ADAR1 wKd values for dsRNA binding to several TRBP and ADAR1 constructs . However, the experimental Kd value of TRBP–RBD1+2 (250 pM) is an order of magnitude higher than the theoretically estimated lower-bound Kd (24.9 pM), which indicates that dsRBDs are not completely independent of each other in TRBP. Therefore, the presence of multiple dsRBDs in a protein is likely to strengthen protein–dsRNA binding and lower the Kd value, but not to the strongest possible binding associated with the predicted lower-boundKd value.Based on the experimentally determined nstructs ,51, we cd 220 nM , respectThe interaction between dsRBP and RNA probed by the smPIFE assay revealed two distinct binding modes, sliding and static Figure . Based oAlong the same line, we expect that rigid or protein-embedded dsRBDs may not slide well on RNA substrates. In the case of ADAD2, its dsRBD has a large content of hydrophobic residues on its surface, making it likely to be protected by other proteins or domains from water exposure. Consequently, the only dsRBD in ADAD2 could be less flexible and occluded from optimal dsRNA contact by other domains or partner proteins. ADAR1 is significantly larger than the other proteins studied here, including several additional domains, like Z-DNA binding and deaminase domains. It is plausible that such bigger and complex domain arrangement leads to a more rigid structure and, hence, restricts the dynamic behavior of the dsRBDs on RNA. Since both ADAD2 and ADAR1 are RNA deaminases , they neOur study offers a new approach to investigate RNA–protein interaction that may lead to more quantitative and deeper understanding of molecular mechanism.


Staphylococcus aureus is considered an importantvirulence trait in the pathogenesis of infections associated with implantable medicaldevices. Gene expression analyses are important strategies for determining themechanisms involved in production and regulation of biofilm. Obtaining intact RNApreparations is the first and most critical step for these studies. In this article,we describe an optimized protocol for obtaining total RNA from sessile cells ofS. aureus using the RNeasy Mini Kit. This method essentiallyconsists of a few steps, as follows: 1) addition of acetone-ethanol to sessile cells,2) lysis with lysostaphin at 37°C/10 min, 3) vigorous mixing, 4) three cycles offreezing and thawing, and 5) purification of the lysate in the RNeasy column. Thissimple pre-kit procedure yields high-quality total RNA from planktonic and sessilecells of S. aureus.Biofilm formed by  Staphylococcusaureus. The ability to develop biofilms is critical for establishing medicaldevice-related infections, which contribute to increased morbidity, mortality, andhealthcare costs ,polysaccharide intercellular adhesin-independent biofilm appears to be the most commontype of biofilm produced by these isolates , NucleoSpin RNAII , InnuREPRNA Mini , Trizol , and the MasterPure RNA PurificationKit . None of the commercial kits that were tested bythese authors provided high RNA yields and they proposed a new method based on phenolextraction , following the protocol suggested by themanufacturer, were mostly unacceptable. However, this kit produced good-quality totalRNA from planktonic cells of the same isolates. The Mini Kit is the most commoncommercial system used to prepare total RNA from S. aureus,29.ThermecIII), which exhibits strongaccumulation of biofilm (S. aureus(MSSA) isolate HC474 (mecIII), an agr-dysfunctional isolatefrom our laboratory collection  and at 18 h of incubation(OD600=4.5). The colony forming units (CFU) were determined by platingdilutions of the bacterial growth in trypticase soy agar , after vigorous mixing.Bacterial cells were grown in trypticase soy broth  at 37°C, in a shaker at 250 rpm. Aliquots were collected at theabsorbance value of 0.25 . The culture wasincubated at 37°C for 18 h, under shaking at 250 rpm, and diluted 1:100 in the samebroth. A volume of 200 µL was placed into each well of the 96-well polystyrenemicrotiter plate . The plate was incubated at 37°C for 20h. After this time, the liquid culture was removed and the biofilm was washed oncewith RNase-free water. Subsequently, TSE buffer  was added to the wells, thesessile cells were dispersed with the aid of sterile toothpicks, and the CFU weredetermined by plating dilutions of the cell suspension in TSA, after vigorousmixing.8-109 bacterial cells were treated with 100µg/mL lysostaphin  at 37°C for 10 min. After thisincubation, the protoplasts were used for RNA isolation with the RNeasy Mini Kit,following recommendation of the manufacturer for RNA preparation from bacterial cells(Qiagen). In another lysis protocol, bacterial cells (108-109CFU/700 µL) were transferred to 2 mL lysing matrix B tubes  anddisrupted at the reciprocating device FastPrep FP120 , using thefollowing settings: 5.0 m/s for 20 s (first pass), 5-min rest period on ice, and 4.5m/s for 20 s (second pass). After centrifugation at 9,000 g at 4°Cfor 5 min, the supernatant was used for RNA isolation with the RNeasy Mini Kit,according to the manufacturer’s recommendations. More than three independentexperiments were performed for each procedure.Approximately 10S. aureus, we modified the protocol for RNA preparation byusing sheared whole-cell lysate coupled to RNA isolation using the RNeasy Mini Kit.The sheared whole-cell lysate method was based on that described by Kornblum et al. containing 14.4 M 2-mercaptoethanol was added to each 200 µL of the cell lysate. Thelysate was then placed in a microtube mixer for 30 min at 4000 rpm at room temperature. Subsequently, the material was quickly frozen (ethanol-dry ice)and thawed (water bath at 60°C) three times. Finally, the RNA was purified using theRNeasy Mini Kit, following the manufacturer's specifications for bacterial cells.To improve the quality and quantity of the total RNA that was obtained from sessilecells of m et al. with somTo ensure that the total RNA from the sessile cells was free of DNA, the firsttreatment with DNase I was performed during the RNA clean-up with the RNeasy MiniKit, following the manufacturer’s instructions (Qiagen). A second treatment withDNase I was performed after eluting the purified RNA from the column, as recommendedby the manufacturer (Invitrogen). The RNA preparation was stored at −80°C.Total RNA was quantified using the NanoDrop 1000TM .The integrity of total RNA was initially assessed by visualization of the 23S/16Sbanding pattern using 1.2% agarose gel electrophoresis in 1×TAE  run at 110 V for 50 min. The gel was treated with ethidiumbromide and visualized in a gel capture system .S. aureus, theagrRNAIII-downregulated spa (encoding protein A),and the agrRNAIII-upregulated psmα3 (encodingphenol soluble modulin α3). In addition, levels of RNAIII, the effector molecule ofthe Agr virulence regulator system, were also determined. The gene encoding for 16SrRNA was used as a reference. The reactions were standardized to a total reactionvolume of 20 μL and cycling conditions for all primers were as follows: an initialcycle at 48°C for 30 min (for obtaining cDNA); and a denaturation step at 95°C for 10min and 35 cycles at 95°C for 30 s, 55°C for 45 s, and 72°C for 45 s (for cDNAamplification). The experiment was performed using the StepOne Real-Time PCR System(Applied Biosystems). To ensure the absence of genomic DNA, a negative control wasincluded, without reverse transcriptase. The cycle threshold (Ct) of each geneamplification was determined using the standard parameters of the software. Meltingcurves were evaluated to ensure the absence of primer-dimer formation and unspecificproducts. Relative quantification of the transcripts was determined by using the ΔΔCtmethod as described in the StepOne and StepOnePlus Real Time PCR Systems GettingStarted Guide (Applied Biosystems). Data analysis was based on two independentexperiments with triplicates, using StepOne Software 2.2 (Applied Biosystems). To further analyze the quality and stability of the RNA preparations, 0.1 ng of totalRNA was reverse transcribed, and cDNA was amplified using the Power SYBR¯ GreenRNA-to-CTTM 1-Step Kit , according to the manufacturer'sinstructions. Real-time qRT-PCR was performed to relatively quantify mRNA ofwell-known virulence genes of hld gene, encoding for δ-hemolysin (Hld), is codified within thernaIII region. Consequently, detection of δ-hemolysin is anindication of agr expression. To correlate Hld activity with theresults obtained in the gene expression experiments, the biofilm producers BMB9393 and GV69 were also tested for hemolytic activity on plates containing a blood agar base with5% defibrinated sheep blood , as previously described , following the specifications of the manufacturer. To determinethe concentration, integrity of the mRNA, and percentage of rRNA contamination, thematerial was analyzed using the Agilent BioAnalyzer with the 2100 Expert mRNA PicoChip, following the manufacturer’s recommendations .To further insure the quality of bacterial mRNA obtained by the optimized protocol,total RNA preparation from sessile cells was enriched using theMICROBUsing the lysis protocols that are described above in the Material and Methodssection, we determined if the RNeasy Mini Kit was working properly when total RNA wasobtained from planktonic staphylococcal cells. We carried out RNA preparations fromlogarithmic- and stationary-phase MRSA cells. We obtained high-quality RNA whenlogarithmic- or stationary-phase free-living cells were used, independently of theprotocol that was chosen for lysis .When enzymatic  or mecha2O.Treatment of free-living or sessile bacterial cells with acetone-ethanol 1:1 andvigorous mixing, combined with three cycles of freeze/thawing after lysostaphintreatment, resulted in increased quantity and high-quality RNA. These results werevisualized by ribosomal RNA band patterns after total RNA separation using gelelectrophoresis . The amoS. aureus for which the expressionpatterns are well known, and its regulation is under control of the main S.aureusquorum-sensing system, Agr , using shearedwhole-cell lysis coupled to the RNeasy Mini Kit . This finding was due to expression of the hldgene codified in the region of agr-rnaIII  . We chostem, Agr . For theMini Kit . The hemr-rnaIII . We did for GV69 . Additioith GV69 . In acco isolate .The quality and integrity of the RNA preparations using the modified protocol, werefuther accessed using the Agilent 2100 Bioanalyzer. The gel images showed no mRNAsmearing, indicating that there was no degradation of this molecule . In addiS. aureus cells can be performed with accuracy. Theadvantage of the proposed protocol is that it avoids the use of phenol, as proposedby Atshan et al. . This enus cells-31.S. aureus biofilms that are developed in vitroand in vivo (in vivo by binding to the host fibronectin (S. aureusbiofilms that develop during thecourse of an infection, problems related to a low number of bacterial cells andcontamination with eukaryotic RNA can be critical. However, these difficulties couldpossibly be overcome by growing sessile cells collected from an invivo model, in an enriched culture media for approximately 10generations, to maintain the in vivo adapted stage (Previous studies have demonstrated that there is a good correlation between in vivo . Indeed,ronectin . Althouged stage .