Salmonella and Escherichia coli, binding to dozens of small RNAs (sRNAs) and messenger RNAs (mRNAs) to regulate mRNA-expression levels through interactions with both 5′ and 3′ untranslated regions (UTRs). Despite excitement around ProQ as a novel global RNA-binding protein, and its potential to serve as a matchmaking RNA chaperone, significant gaps remain in our understanding of the molecular mechanisms ProQ uses to interact with RNA. In order to apply the tools of molecular genetics to this question, we have adapted a bacterial three-hybrid (B3H) assay to detect ProQ’s interactions with target RNAs. Using domain truncations, site-directed mutagenesis and an unbiased forward genetic screen, we have identified a group of highly conserved residues on ProQ’s NTD as the primary face for in vivo recognition of two RNAs, and propose that the NTD structure serves as an electrostatic scaffold to recognize the shape of an RNA duplex.The FinO-domain-protein ProQ is an RNA-binding protein that has been known to play a role in osmoregulation in proteobacteria. Recently, ProQ has been shown to act as a global RNA-binding protein in  Regulatory, small RNAs (sRNAs) are found in nearly all bacterial species and implicated in important processes such as virulence, biofilm formation, host interactions and antibiotic resistance . These sEscherichia coli protein FinO is the founding member of the FinO structural class of RNA-binding proteins. In E. coli, FinO binds the FinP sRNA and regulates the 5′ untranslated region (UTR) of traJ , to support RaiZ’s repression of hupA  ProQ have been solved, demonstrating that the NTD adopts a FinO-like fold  with a poorly conserved and likely unstructured linker connecting them . NMR strike fold . RNA-binin vitro , as has in vitro . On the in vitro . Within in vitro , while bin vitro . Thus, tE. coli reporter cells  assay that facilitates the detection of RNA-protein interactions inside of living er cells . While tA complete list of plasmids, strains, and oligonucleotides (oligos) used in this study is provided in L2-62-lacZ reporter on an F’ episome bearing tetracycline resistance was generated as previously described  immediately downstream of OL2 site. Thus, KB511 carries a single copy L2-83-lacZO reporter on F’ episome bearing tetracycline resistance, in which the lambda operator L2O is centered at a position of −83 relative to the transcription start site (TSS). The recombinant F’ episome was then moved via conjugation into Δhfq strain KB496 to give strain SP5, which was used as the reporter strain for the unbiased screen (described below). Except for this screen and data presented in Figure L2-62-lacZ; ΔhfqO) was used as the reporter strain for all B3H experiments in this study.A single-copy Oescribed ,32 by cosistance ,33. The llection  were intproQ was conducted with the Q5 Site-Directed Mutagenesis Kit (New England Biolabs) using end-to-end primers designed with NEBaseChanger. The construction of key parent vectors is described below. Residues 2–119, 2–131, 2–176, 181–232 and 2–232 of Ec ProQ were fused to the α-NTD (residues 1–248) in pBRα between NotI and BamHI to generate pSP90 (pBRα-ProQNTD), pKB951 (pBRα-ProQNTD+12aa), pKB955 (pBRα-ProQΔCTD), pSP92 (pBRα-ProQCTD) and pKB949  respectively.Plasmids were constructed as specified in constit-λCI-MS2CP) was derived from pKB989 (pAC-placUV5-λCI-MS2CP)  with the following sequence lacking a lacO element : CTCGAGACGATAGCTAGCTCAGTCCTAGGTATAGTGCTAGCGCATGC. Stepwise, this substitution was made using Gibson Assembly of a backbone (PCR product of oCW6 and oCW7 on pKB989) and insert (hybridization of oCW18 and oCW19), followed by mutagenesis PCR on the resulting plasmid (with primers oCW28 and oCW29).pCW17 (pAC-pI-MS2CP)  by substhp-XmaI-HindIII) was derived from pKB845 (pCDF-pBAD-2x MS2hp-XmaI-HindIII) (hp moieties via vector digestion (EcoRI + XmaI) followed by ligation of an insert formed by kinase-treated oCH1 + oCH2, which encodes an EcoRI site, one copy of a 21-nt RNA hairpin from bacteriophage MS2 (MS2hp), and an XmaI site. All hybrid RNAs used in this study are 1xMS2hp-RNA hybrids and constructed by inserting the RNA of interest into the XmaI/HindIII sites of pCH1. The full sequence of each hybrid RNA is provided in pCH1 (pCDF-pBAD-1xMS2HindIII) , by remod-thiogalactoside (IPTG) when noted. Cells were grown to mid-log (OD600 ≈ 0.6) in optically clear 200 μl flat bottom 96-well plates (Olympus) covered with plastic lids, as above. Cells were lysed and β-galactosidase  activity was measured as previously described (CP and MS2hp-Bait-RNA), divided by the highest activity from negative controls—cells containing plasmids where one of the hybrid constructs is replaced by an α empty, CI empty or MS2hp empty construct. Assays were conducted in biological triplicate on at least three separate days. Absolute β-gal values from a representative dataset of a biological triplicate experiment, including values for all negative controls, are shown in For B3H assays, reporter cells  were freshly co-transformed with compatible pAC-, pBR- and pCDF-derived plasmids, as indicated. From each transformation three colonies (unless otherwise noted) were picked into 1 ml LB broth supplemented with carbenicillin (100 μg/ml), chloramphenicol (25 μg/ml), tetracycline (10 μg/ml), spectinomycin (100 μg/ml) and 0.2% arabinose in a 2 ml 96-well deep well block (VWR), sealed with breathable film (VWR) and shaken at 900 rpm at 37°C. Overnight cultures were diluted 1:50 into 200 μl LB supplemented as above, with an additional 50 μM isopropyl-β-escribed . B3H int600. Lysates were mixed with 6× Laemmli loading dye with PopCulture Reagent (EMD Millipore Corp), boiled for 10 min at 95°C and electrophoresed on 10–20% Tris–glycine gels (Thermo Fisher) in 1× NuPAGE MES Running Buffer (Thermo Fisher). Proteins were transferred to PVDF membranes (BioRad) using a semi-dry transfer system (BioRad Trans-blot Semi-Dry and Turbo Transfer System) according to manufacturer's instructions, and probed with 1:10 000 primary antibody  overnight at 4°C and then a horseradish peroxidase (HRP)-conjugated secondary antibody . Note that, throughout the paper, ‘anti-ProQ’ is written out rather than using the standard abbreviation of ‘α-ProQ.’ This is to avoid confusion with the fusion protein we call ‘α-ProQ’ consisting of the NTD of RpoA (α) fused in frame to ProQ. Chemiluminescent signal from bound peroxidase complexes was detected using ECL Plus western blot detection reagents (BioRad) and a c600 imaging system (Azure) according to manufacturer's instructions.Cell lysates from β-gal assays were normalized based on pre-lysis ODproQ library was generated first by 30 rounds of PCR amplification of the proQ portion of the pBRα-ProQFL plasmid (pKB949) using Phusion DNA Polymerase (New England Biolabs) in 70 mM MgCl2, 500 mM KCl, 100 mM Tris (pH 8.0), 0.1% bovine serum albumin, 2 mM dGTP, 2 mM dATP, 10 mM dCTP, 10 mM dTTP and primers oKB1077 and oKB1078. A second mutant proQ library was generated under the same condition but with the addition of 0.1 mM MnCl2. The PCR products of both libraries were digested with DpnI (New England Biolabs) to remove template plasmid, then with NotI-HF and BamHI-HF (New England Biolabs), gel purified, and ligated  into a pBRα vector cut with NotI-HF and BamHI-HF. Following ligation and transformation into NEB 5-alpha F’Iq cells (New England Biolabs), cells were grown as near-lawns on LB-carbenicillin plates and a miniprep was performed from resuspension of ∼23 000 colonies to yield the plasmid library.A mutant proQ mutants were sequenced, all of which resulted in reduced β-gal activity on plates and in liquid, five of which showed reduced levels by dot blot and five of which showed approximate wild-type-levels by dot blot. There was a 100% correspondence between the levels of ProQ indicated by dot blot and the presence or absence of a premature stop codon in the NTD  from β-gal assays were transferred to nitrocellulose Protran membranes (Amersham) by multichannel pipette. Membranes were allowed to dry, then probed and imaged as above. To verify that the dot-blot assay could identify destabilized α-ProQ proteins, 10  the NTD .CP) and pSP10 (pCDF-MS2hp-cspE) or pSP14 (pCDF-MS2hp-SibB) and plated on LB agar supplemented with inducers (0.2% arabinose and 1.5 μM IPTG), antibiotics (carbenicillin (100 μg/ml), chloramphenicol (25 μg/ml), tetracycline (10 μg/ml) and spectinomycin (100 μg/ml)) and indicators  and phenylethyl-β-d-thiogalactopyranoside ). These conditions were chosen to enable a clear distinction between blue positive-control colonies (containing the WT fusion proteins and the cspE hybrid RNA) and white negative-control colonies (instead containing a plasmid encoding α-empty). Reporter strain SP5,  was used only for the high-throughput screen and results of RNA-binding defects were subsequently verified in KB483 (L2-62-lacZO). Plates were incubated overnight at 37°C, then at 4°C for an additional ∼48 h. 536 white or pale colonies were isolated (372 against cspE + 164 against SibB), and liquid β-gal assays were conducted to confirm the effects of these white colonies, followed by a dot-blot counter-screen with anti-ProQ antibody to eliminate mutants with low expression levels. To analyze dot-blot results of colonies that were identified in the primary screen, densitometry was conducted using ImageJ software to quantify the intensity of individual dots. The intensity of each dot was normalized to the OD600 of the culture before lysis and β-gal activity of each colony was plotted against normalized ProQ intensity. Normalized intensities were compared to positive and negative controls and colonies with ProQ-expression levels in the wild-type range were selected for sequencing.For the primary screen, the pBRα-proQ plasmid library was transformed into SP5 cells along with pCW17  and pSP10 (pCDF-1xMS2hp-cspE) or pSP14 (pCDF-1xMS2hp-SibB). Liquid β-gal assays were conducted as above, with induction of α-ProQ from both 0 and 50 μM IPTG, and ProQ-expression levels were evaluated in triplicate at IPTG concentrations. The basal level β-gal activity was set by activity in reporter cells containing an α-empty plasmid rather than an pBRα-proQ plasmid isolated in the screen. Average fold-stimulation of β-gal activity and dot-blot intensities of each mutant were then normalized to the values of WT α-ProQ (set to 1.0) and α-empty (set to 0.0) using the expression /. Note that relative expression and fold-stimulation of each mutant at 0 μM and 50 μM IPTG can be directly compared to one another, as both sets of values were normalized to WT α-ProQ at 0 μM IPTG.Plasmids were isolated from 86 colonies that produced low β-gal activity but wild-type levels of α-ProQ fusion protein, and the DNA encoding cspE 3′UTR was chosen as an initial RNA candidate due to its strong interaction with ProQ that has been observed both in vivo and in vitro (ΔCTD). For the envisioned assay, ProQΔCTD, the ‘prey’ protein, is fused to the N-terminal domain of the alpha subunit of RNAP  of a lacZ reporter gene. The 3′-terminal 85 nts of the cspE transcript (hereafter cspE) serves as the ‘bait’ and is expressed as a hybrid RNA following either one or two copies of a 21-nt RNA hairpin from bacteriophage MS2 (MS2hp). This hybrid RNA is tethered to the upstream OL2 DNA sequence via a constitutively expressed RNA–DNA ‘adapter’ protein consisting of a fusion between the CI protein from bacteriophage λ (CI) and the coat protein from bacteriophage MS2 (MS2CP). In this system, interaction between DNA-tethered cspE RNA and the RNAP-assembled α-NTD-ProQ fusion protein stabilizes the binding of RNAP to the test promoter, thereby activating reporter gene expression.Our previous studies with the bacterial three-hybrid (B3H) assay have focused on Hfq–RNA interactions . We sougin vitro ,28. To shp RNA as has been used extensively in yeast three-hybrid systems  is left out from ‘empty’ constructs that express only α, MS2hp or CI, respectively   did not interact with the ProQ fusion protein, though it is possible the lack of interaction is due to the shorter length of this TtrpA RNA. To compare the RNA-binding activity of ProQ to Hfq in this assay, we tested the same panel of nine hybrid RNAs for interaction with α-Hfq  and one sRNA (SibB).Given that ProQ has been found to interact with dozens of sRNAs and hundreds of mRNAs inside of li cells ,22, we sr, fbaA) ,22,38; ar, fbaA)  30). Wh. WhSalmos Figure . As withn Figure . In addith α-Hfq . We concth α-Hfq ,39. As hin vivo, we compared the binding of five domain-truncation mutants of ProQ  protein, as assessed by an antibody recognizing the region of α shared by each protein  and the CTD on its own did not afford any detectable interaction with either hybrid RNA . Interestingly, a construct with only the first 12aa of the 61-aa linker partially restored the interaction of ProQ with SibB . Together, our results indicate that the ProQ CTD is not required for interaction with either the cspE 3′UTR or SibB RNAs in vivo and that the NTD/FinO-domain is the primary RNA-binding site for both of these RNAs.Conflicting evidence has been collected about the contributions of the linker and CTD of ProQ to RNA binding ,21,28,40Q Figure  with cspn Figure . RemovalA Figure , D, despA Figure . RemovalcspE and SibB RNAs in vivo, we wanted to identify amino acids in the NTD beyond Arg80 that are required for RNA interaction. Hereafter, we call the two faces of the ProQ NTD the ‘concave face’  and ‘convex face’ , le, leEc Prresidues , blue anresidues , cyan. Aresidues  and remoB Figure . SubstitB Figure . TogetheΔCTD with both cspE and SibB hybrid RNAs without strong effects on expression levels of the ProQ fusion protein .Two of the most highly conserved residues along the NTD’s concave face are aromatic and hydrophobic residues in which the side chains are partially surface exposed: Tyr70 and Leu71 Figure . As suchn Figure . Even ven Figure , consistn Figure . That Ph2– group. While α-ProQΔCTD with a D41E substitution was able to interact well with both cspE and SibB hybrid RNAs, a D82E substitution strongly impaired interaction with both RNAs  to leave open the possibility of finding substitutions anywhere in the protein that would disrupt interaction with either cspE or SibB hybrid RNAs. We first confirmed that the ProQ-B3H interactions we had observed in liquid were also apparent when cells were grown on X-gal-containing indicator medium and found a robust difference in colony color between positive and negative controls . In this primary screen, ∼15% of colonies were white or pale, the phenotype expected for transformants that contained α-proQ mutants that no longer interacted with a hybrid RNA , the dot-blot assay identified the subset (∼30%) that maintained wild-type levels of expression . To. ToproQ,rid RNAs . Many murid RNAs . To deteimpaired . Substitimpaired . Given timpaired . This hiimpaired –C. In adimpaired , while GWhile there are multiple ways that the ProQ residues we have identified could contribute to RNA binding, we wished to develop a preliminary structural model that would combine results from our forward and reverse genetic approaches Figure  with litcspE and SibB RNAs in vivo and have dissected the roles of residues on multiple surfaces of this domain in RNA binding. Results from both forward- and reverse-genetic analyses are in strong agreement with one another, converging to implicate the more highly conserved surface of the NTD, which we call the concave face, as the primary site for recognition of both RNAs. We have proposed a working structural model that interprets the positions of residues identified in this study as critical for RNA binding in light of ProQ’s established preference for binding to structured RNAs. In this model, the global structure of the NTD/FinO-domain pre-positions highly conserved residues across the concave face to recognize the conserved shape and charge of double-stranded RNA. By allowing conservation to guide our initial studies and taking an unbiased genetic approach, we have demonstrated that, along with basic residues, conserved acidic, aromatic and hydrophobic residues also play an important role in ProQ’s ability to bind RNA.In this work, we have conducted the first comprehensive mutagenesis study of ProQ to identify the functional surface used by ProQ to bind to RNA substrates. In order to apply both forward and reverse genetic approaches to this question, we adapted a bacterial three-hybrid (B3H) assay for genetic detection of RNA-protein interactions to report on binding of ProQ to RNA. Using this system, we have established that the NTD/FinO-domain of ProQ is the primary site that mediates interaction with in vivo binding site for interaction with the two RNAs closely investigated here. First, truncation analysis demonstrates that the ProQ NTD, along with the first 12 aa of the linker, is sufficient for full interaction with both the 3′ UTR of cspE and the sRNA SibB. Further, an unbiased forward genetic screen starting with mutagenized full-length proQ did not identify any mutations in the region encoding the linker or CTD that were sufficient to disrupt interaction of ProQ with either hybrid RNA. In contrast, 37 amino-acid substitutions at 25 residues within the NTD/FinO-domain were identified by our screen to disrupt interactions with one or both hybrid RNAs.The relative roles in RNA binding played by disordered regions and structured domains of ProQ/FinO-like proteins have been a subject of inquiry over several years ,21,28,29in vivo, we cannot rule out the possibility that other regions in the linker or CTD contribute important interactions with certain RNA substrates. In particular, our data suggest that the most N-terminal 12 aa of the unstructured linker may be necessary for full interaction with certain RNA substrates (e.g. SibB), while not for others  NMB1681 .,41.in vi protein . It is nEc numbering; cspE and SibB interactions. Interestingly, a Y-to-F mutation at the analogous position was found in an unbiased screen to disrupt RocR activity in L. pneumophila  and could mediate an intramolecular hydrogen bond within the polypeptide, or could be directly involved in contacting RNA.A universally conserved residue across all of these FinO-domain proteins is the aromatic residue Tyr70 , an, anEc nuEc ProQ, Nm NMB1681 and FinO is the β3–4 hairpin implicated by our data as a critical structural element for RNA interaction by ProQ  were found in our unbiased screen to be necessary for RNA interaction; even an alanine at these positions prevents interaction with ibB RNAs . One intibB RNAs  and locaibB RNAs . ConsideE. coli. In this study, ProQ was found to bind to a wider range of RNAs than Hfq, producing B3H interactions with RNAs found to interact both with ProQ as well as with Hfq in vivo   . It willymerase) ,38.in vivo  what the detailed role of Arg80 and the convex face are in RNA binding, (ii) to what extent unique modes of interaction exist for distinct RNAs or classes of RNAs, (iii) whether ProQ mediates RNA annealing and which part(s) of ProQ would contribute to this activity, (iv) which part(s) of ProQ may recruit additional cellular factors, such as the ribosome , RNA polgkaa144_Supplemental_FilesClick here for additional data file.


Our data are consistent with a model in which 3B copy number expansion within the FMDV genome has allowed evolution of separate cis and trans acting functions, providing selective pressure to maintain multiple copies of 3B.For gene duplication to be maintained, particularly in the small genomes of RNA viruses, this should offer some advantages. We have investigated the functions of a small protein termed VPg or 3B, which acts as a primer in the replication of foot‐and‐mouth disease virus (FMDV). Many related picornaviruses encode a single copy but uniquely the FMDV genome includes three  copies of the 3B coding region. Using sub‐genomic replicons incorporating nonfunctional 3Bs and 3B fusion products in competition and complementation assays, we investigated the contributions of individual 3Bs to replication and the structural requirements for functionality. We showed that a free N‐terminus is required for 3B to function as a primer and although a single 3B can support genome replication, additional copies provide a competitive advantage. However, a fourth copy confers no further advantage. Furthermore, we find that a minimum of two 3Bs is necessary for  ATCCAmerican type culture collectionBHK‐21baby hamster kidney cell‐lot 21cDNAcomplementary deoxyribonucleic acidDMEMDulbecco’s minimum essential mediaEV71enterovirus‐71FBSfetal bovine serumFMDVfoot‐and‐mouth disease virush.p.t.hours post‐transfectionkbkilobaseMUSCLEMultiple Sequence Comparison by Log‐ExpectationNCBINational Center for Biotechnology InformationNEBNew England BiolabsORFopen reading framePBSphosphate‐buffered salinepolpolymerasepRepplasmid repliconproproteasePVpoliovirusRdRpRNA‐dependent RNA polymeraseRNAribonucleic acidS.D.standard deviationS.E.M.standard error of the meanSDS‐PAGEsodium dodecyl sulfate poly‐acrylamide gel electrophoresisNTTtranscription and translationVPggenome‐linked viral proteinWTwild‐typeY3Ftyrosine to phenylalanine substitution of the third residue in the protein1The evolution of small RNA viruses is largely driven by the error‐prone RNA‐dependent RNA polymerase (RdRp), which is responsible for replicating the viral genome. Hence, RNA viruses exist as populations of related quasispecies.Aphthovirus genus of the Picornaviridae family. The FMDV genome comprises an open reading frame (ORF) flanked at the 5ʹ and 3ʹ ends by untranslated regions. The single ORF encodes both the structural and nonstructural proteins starting with the leader protease followed by a capsid coding P1‐2A region. P1 is processed into the four structural proteins VP4, VP2, VP3, and VP1. Downstream of the P1‐2A region lies the nonstructural protein‐coding region, required for RNA replication and organized as two sub‐regions, P2 and P3. The P2 region encodes the 2B and 2C proteins, 2A being a C‐terminal extension of P1. The P3 region encodes 3A, triplicate copies of the replication primer, 3B , the viral protease 3Cpro and the RdRp termed 3Dpol.Foot‐and‐mouth disease (FMD) is a highly contagious disease affecting cloven‐hoofed animals, which imposes a global economic burden of between US$ 6.5 and 21 billion in endemic regions, and over US$ 1.5 billion annually in FMD‐free countries and regions.pol, the 3CD precursor protein and a viral RNA structure termed the cis‐active replicative element or cre.Most picornaviruses, such as the well‐studied poliovirus (PV), encode a single copy of 3B and although there is evidence for duplication of 3B in some, FMDV is the only picornavirus that has been demonstrated to have three  copies of the 3B coding region. This feature is almost 100% conserved among naturally occurring FMDV isolates to date.Earlier studies, using sub‐genomic replicons and infectious virions, have shown that although multiple copies of 3B may influence host specificity and virulence,22.1Baby hamster kidney cells‐lot 21 (BHK‐21) and HeLa cells were obtained from ATCC  and propagated according to standard methods.2.2pro proteolysis, and hence, produce a series of defined fusion proteins. An FMDV construct was also designed to incorporate four copies of 3B by duplicating the 3B1 sequence using alternative codons . The duplication was inserted between 3A and 3B1, while retaining the 3A‐3B1 and 3B1‐3B2 junctions. The replicon constructs used in this study are listed in Table Two previously described picornaviral sub‐genomic replicons in which the capsid protein coding regions were replaced with fluorescent reporter genes mCherry2.3AscI . RNA transcripts were generated from sub‐genomic replicon cDNAs using T7 RNA polymerase  in the presence of nucleoside triphosphates  and MnCl2 according to the manufacturer’s protocol and our established methods.Replicon plasmid DNA was linearized with 2.4BHK‐21 cells were propagated in duplicate wells of a 12‐well plate according to standard methods. Cells were transfected with 1 µg of purified mCherry or GFP replicon RNA transcripts using Lipofectin reagents  according to the manufacturer’s protocol. Replication was monitored hourly for red and/or green fluorescence within an IncuCyte Zoom  as previously described.2.53H]‐U (uridine) per well at 1‐hour post‐transfection (h.p.t.). At 8 h.p.t., total RNA was harvested using guanidinium thiocyanate‐phenol‐chloroform methodsg using an SW 55 Ti rotor for 50 minutes at room temperature. Gradient fractions were counted by scintillation for [3H] in a scintillation cocktail according to standard protocols.BHK‐21 cells seeded in duplicate wells of a 6‐well plate were pretreated for 1 hour with 10 µg/mL of actinomycin D at 37°C. Pretreated cells were transfected with 4 µg of replicon RNAs, before radiolabeling with 18 µCi of  labeled methionine according to the manufacturer’s protocol. Following a 40‐minute incubation, reactions were chased with excess unlabeled methionine/cysteine with sample collection at 30‐minute intervals. Reactions were stopped by addition of 2x Laemmli buffer and boiling. Proteins were separated by 12% SDS‐PAGE and detected by autoradiography.Coupled transcription/translation reactions  were carried out using expression plasmid constructs of FMDV WT or mutated P3 polyproteins in the presence of ‐U. To maximize the labeling of replicon RNA, BHK‐21 cells were pretreated with actinomycin‐D to reduce incorporation of [3H]‐U into cellular RNA. After the addition of [3H]‐U at 1 h.p.t, total cellular RNA was harvested at 8 h.p.t., separated by sucrose gradient centrifugation and analyzed by scintillation counting  and the replicon with a single functional 3B3  had slightly reduced levels of [3H]‐U incorporation, although the differences were not statistically different from WT. The replicons containing only a functional 3B1 or 3B2  had nine‐ and eightfold reduction in [3H]‐U incorporation compared to WT, respectively. Incorporation of [3H]‐U from a replicon with a replication‐defective 3D‐GNN substitution was used to measure levels of input translation and the levels recorded here were similar to cells alone or to the construct lacking all three 3Bs (3B123Y3F).To address the question of why FMDV maintains three copies of 3B, we first determined the efficacy of each 3B protein in priming genome replication using a sub‐genomic replicon Figures  and S3. Y3F, 3B2Y3F, or 3B3Y3F) and these all replicated similarly to WT . However, constructs lacking a functional 3B3  appeared to replicate less well, although this was only statistically significant for the former. Reporter expression from a construct with a replication‐defective 3D‐GNN substitution was used to measure levels of input translation. Although levels of reporter expression recorded were low as expected, it is interesting to note that for the construct lacking any active 3Bs , expression was slightly higher than for the 3D‐GNN control for unknown reasons.We also monitored replication over time by measuring mCherry fluorescence using our established protocols.T Figure . FurtherThese data are broadly consistent with those shown in Figure 3.2pro enzyme which recognizes defined boundary sequences, the natural 3A‐3B1 and 3B3‐3C junction sequences were maintained in all cases to minimize effects due to differential processing  when mCherry replicons were co‐transfected with ptGFP replicons containing a single functional 3B, suggesting that they competed equally with each other, thus, reducing the level of expression of each. These data Figure , togethe3.3pro. Replicons were generated incorporating alanine substitution to disrupt cleavage boundaries between individual 3B proteins, between 3A and 3B1, and between 3B3 and 3C in different combinations  or C‐terminal 3B (Δ3B1 3B2/3B3Y3F) or to both as a control (Δ3B1 3B2Y3F/3B3Y3F). Replicon RNA was then generated and transfected into BHK‐21 cells and monitored for replication as described above. In agreement with the data in Figure Further constructs were generated to investigate whether the position of the 3B molecule within a fusion product was important. Replicons were made where 3B1 was deleted (Δ3B1). The 3B2 and 3B3 proteins were then fused together by substitution of the cleavage boundary. Y3F substitutions were introduced to either the N‐terminal 3B .Having demonstrated the importance of multiple 3Bs in replication and the requirement for a free N‐terminus, we asked the question whether additional copies of 3B might be tolerated and if so, whether these would offer a further replicative advantage. A mutant construct (termed 3Bx) was designed that encoded an additional copy of 3B1 at the C‐terminus of 3A, while retaining the natural 3A‐3B1 and 3B1‐3B2 cleavage motifs at the new 3A‐3Bx and 3Bx‐3B1 junctions Figure . Fluores Figures  and S7. 3.5trans to support replication, as for the enteroviruses PV and enterovirus 71 (EV71).pol active site could be rescued in trans by co‐transfection with a second replicon containing a functional 3Dpol. However, not all substitutions within the 3Dpol could be rescued, demonstrating unique cis and trans activities.Y3F substitutions were introduced into WT or mutant ptGFP replicons. RNAs from these constructs were co‐transfected with RNA from WT, 3D‐GNN, or 3BY3F mCherry replicon constructs (or with yeast tRNA as a transfection control). Replication was monitored by both ptGFP and mCherry expression and data shown at 8 h.p.t.  but had WT 3B3, replicated to higher levels to those relying solely on WT 3B1 or 3B2, consistent with some of the studies above. However, the effects were subtle and there were slight differences between replication measured via fluorescent reporter expression or via radiolabel incorporation into RNA, possibly due to the different sensitivities of the assays. We also showed that the addition of a fourth 3B coding region  offered no replicative advantage. However, importantly, our studies using combinations of 3Bs, rendered inactive by substitution or by deletion (while maintaining boundary sequences) in competition experiments indicated that a competitive advantage was conferred by possession of more than one 3B.NT assays demonstrated the expected overall changes in polyprotein boundary cleavage in that substitution of the boundary increased the abundance of the expected precursor. However, in some cases it appears that reducing processing at one site may interfere with the normal cleavage cascade, resulting in enhanced proteolysis at others. It should also be noted that it was not possible to ascertain some small size changes, for example, the fusion of two 3Bs, and some proteolysis of the mutated boundaries was still observed as may be expected from the modest alterations introduced. More dramatic boundary substitutions would have resulted in greater inhibition of proteolysis but this may have resulted in structural changes, which we chose to avoid. However, when taken overall, the data showed that 3Bs with C‐terminal fusions were replication‐competent, whereas N‐terminal fusions were not tolerated, suggesting that the location of the uridylylated tyrosine at position three in 3B is essential for it to function as a primer for RNA synthesis.Constructs were also generated with N‐ or C‐terminal fusions, that is, between 3B molecules and 3A or 3C. By leaving only one 3B functional, it was possible to ascertain whether the fusion could be tolerated for replication. The Tpol uncovered a tight network of interactions securing the N‐terminus (and Y3 residue) of 3B within the active site cavity of 3Dpol.pol to reach the active site. This potentially explains why the N‐terminal fusions were not tolerated; the 3A‐3B1 fusion would require “threading” the full‐length of 3A through the 3Dpol cavity before Y3 could reach its site of action, which is implausible given the narrow dimensions of the cavity ; we would argue that this is plausible and may itself explain why Y3 is located so close to the N‐terminus of 3B. This result is also compatible with the suggestion that during the optimal functioning of the replication complex, the active 3B is derived from the N‐terminus of a 3B‐3C(‐3D) precursor and not from the C‐terminus of a 3A‐3B precursor.Interestingly, previous structural studies of 3B in complex with 3Dy Figure . While 3Sub‐genomic replicons offer the advantage of being able to separate replication from other parts of the virus lifecycle. In this way, we have been able to tease apart the relatively subtle advantages that multiple copies of 3B provide. However, although we have clearly demonstrated that two copies are better than one, the role for a third copy is less clear. It is possible that further competitive passages would be needed for the advantage conferred by three copies to become apparent. It is also possible that the possession of three copies of 3B is important for other aspects of the viral lifecycle, such as immune evasion or virion assembly.trans complementation required a helper with a minimum of two functional 3Bs. Our previous studiesin trans to support replication. Together, this suggests FMDV may have evolved two distinct mechanisms of replication, where the extra copies of 3B are nonessential but preferable for optimal cis active replication through active 3B‐3C(‐3D) precursors, but the extra copies are necessary to facilitate trans complementation via 3A‐3B delivery. This may offer a replicative advantage, thus, providing the selective pressure to maintain multiple copies of the 3B coding region in the genome.In conclusion, although the single 3B present in the enterovirus replicons used here could rescue a replicon with a defective 3B, rescue of a defective FMDV replicon lacking any functional 3Bs by The authors declare no conflict of interests.O.O. Adeyemi, J.C. Ward, M.R. Herod, D.J. Rowlands, and N.J. Stonehouse designed the research; O.O. Adeyemi, J.C. Ward, and M.R. Herod designed and conducted the experiments; O.O. Adeyemi, J.C. Ward, J.S. Snowden, and M.R. Herod analyzed data; O.O. Adeyemi, J.C. Ward, and N.J. Stonehouse wrote the manuscript; M.R. Herod, D.J. Rowlands, and N.J. Stonehouse edited the manuscript; D.J. Rowlands, M.R. Herod, and N.J. Stonehouse supervised the project; D.J. Rowlands, M.R. Herod, and N.J. Stonehouse are the guarantors of this work and, as such, had full access to all the data and take responsibility for the integrity of the data and the accuracy of the data analysis.Fig S1‐S8Click here for additional data file.Supplementary MaterialClick here for additional data file.


Background: Healthcare workers and large parts of the population are currently using personal protective equipment, such as face masks, to avoid infections with the novel coronavirus SARS-CoV-2. This equipment must be sterilized as gently as possible before reuse. One possibility is thermal inactivation, but professional autoclaves with their high temperatures are often not available or suitable. If the inactivation period is long enough, coronavirus inactivation can also be carried out at relatively low temperatures. The required duration was determined in this study. Material and methods: Data from published thermal inactivation studies on coronaviruses were applied to determine the temperature dependence of the rate constant k(T) for each coronavirus by employing Arrhenius models. Results: The data obtained exhibit large variations, which appear to be at least partially caused by different sample properties. Samples with high protein content or samples in dry air sometimes seem to be more difficult to inactivate. Apart from this, the Arrhenius models describe the thermal inactivation properties well and SARS-CoV and SARS-CoV-2 can even be represented by a combined model. Furthermore, the available data suggest that all samples, including critical ones, can be mathematically included by a worst-case Arrhenius model. Conclusion: Coronaviruses can already be inactivated at relatively low temperatures. For most samples, application times of approximately 32.5, 3.7, and 0.5 minutes will be sufficient at 60°C, 80°C, and 100°C, respectively, for a 5 log-reduction. For difficult conditions, the worst-case model provides significantly longer application times of 490, 55, and 8 minutes for the temperatures mentioned. The emergence of the novel coronavirus SARS-CoV 2 in Wuhan (China) in 2019 has led to a pandemic that is still spreading. In order to contain its further expansion, personal protective equipment, such as face masks, is increasingly being used both in the healthcare system and among the population. This sudden rise in demand has led to a worldwide shortage, so that even disposable items are sometimes used several times . This leThermal inactivation, which in the professional sector is often carried out with steam sterilizers at temperatures of up to 121°C or even 135°C, has long been known as a very effective disinfection technique for a wide range of pathogens , [5], 66. HoweveA recent overview on coronavirus inactivation temperatures by Kampf et al. , as wellIn a simple first-order reaction model, the relationship between virus concentration c(t) and time t can be described by an exponential function with the rate constant k , 16]. . 16]. Equation 1For coronaviruses, this can be observed particularly well in the experimental data of Hofmann and Wyler ,The rate constant k=k(T) is a function of the inactivation temperature T, which can be mathematically described by an Arrhenius approach , 16]. T. T16]. TEquation 2In this expression, log k(T) is represented by a straight line with the slope –a, the variable 1/T and the intercept b. The aim of this paper was to apply this mathematical model for calculating rate constants based on published coronavirus inactivation data, and use them to recommend temperature-dependent inactivation durations.PubMed and Google Scholar were used to search for different combinations of the terms coronavirus, heat, temperature, inactivation, disinfection and sterilization. The references of the publications found in this process were checked for further relevant studies. Since the focus of this investigation was on heat inactivation, only data with temperatures above about 40°C and pH values between 6 and 8 were included in the further analysis, since higher and lower pH values already lead to coronavirus inactivation without additional heating , 18], , , 22]..22].If the authors did not provide rate constants themselves, the log-reduction and the required exposure time were determined from text, tables or figures to calculate the rate constant k. If data were available for several exposure durations, as a rule, the longest exposure at which a coronavirus concentration above the detection limit was still found was chosen. The reason for this is that the heating and cooling of the investigated samples – before and after reaching the intended temperature – also contribute to inactivation, but this is not recorded separately and their relative proportions are higher for short exposures than for longer ones.The rate constants thus obtained for different temperatures were then applied to generate equations for k(T) for the different coronaviruses according to the Arrhenius model.About 35 publications on thermal inactivation of the human viruses human coronavirus (HCoV), Middle East respiratory syndrome coronavirus (MERS-CoV), severe acute respiratory syndrome coronavirus (SARS-CoV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were found. Additionally, inactivation data for the following animal viruses was available: bovine coronavirus (BCoV), canine coronavirus (CCoV), feline infectious peritonitis coronavirus (FIPV), infectious bronchitis coronavirus (IBV), murine coronavirus (MHV), porcine epidemic diarrhea virus (PEDV), and transmissible gastroenteritis virus (TGEV). The studies contain approx. 120 data sets that met the above-mentioned selection criteria with regard to temperature and pH. However, not all of them could be evaluated quantitatively, as in some cases, only lower limits for the achieved log-reduction are given. The data exhibit large variability. The rate constants can differ by an order of magnitude even for one temperature and one coronavirus species. Some of these variations are probably caused by experimental inaccuracies. This can be assumed, for example, from the fact that in some experiments the determined virus concentration not only decreased but also increased again at certain phases during incubation. A further experimental factor is the effect of the heating and cooling phases already mentioned above, which can be particularly noticeable for short inactivation periods. Strain differences also contribute to this variability , 23], , .Another aspect tat has been observed in earlier publications is the influence of medium or environment. In liquid media, higher protein concentrations often seem to reduce virus inactivation , 26], ,  but exceThese large variations can also be observed in the logarithmic representation of the determined rate constants log(k), which are plotted separately for human and animal coronaviruses in Figure 1 Apart from the variabilities mentioned above, and the differences for the individual coronavirus species represented in Table 1 Figure 1 With the data for k(T) from Table 1 Equation 3As an example of the application of these models, Table 2 All investigations prove that coronaviruses can be inactivated quite quickly at relatively low temperatures, e.g., 60°C or 80°C. These are temperatures for which no professional autoclaves are necessary, but which can even be achieved with domestic cooking equipment such as an oven or rice cooker.The observed temperature dependence of coronavirus inactivation behavior – represented by the rate constant k(T) – is well described by Arrhenius models, so that necessary inactivation times can be calculated for each coronavirus and each inactivation temperature. The two particularly important and related human coronaviruses SARS-CoV and SARS-CoV-2 behave very similarly and can be described by a combined Arrhenius model. This model delivers inactivation durations of approx. 32.5, 3.7 and 0.5 minutes for temperatures of 60°C, 80°C and 100°C, respectively, for a 5 log-reduction. For potentially critical samples the proposed worst-case model should be applied for safety reasons. The authors declare that they have no competing interests.


Using immunohistochemistry, enterovirus capsid proteins were demonstrated in pancreatic islets of patients with type 1 diabetes. Virus proteins are mainly located in beta cells, supporting the hypothesis that enterovirus infections may contribute to the pathogenesis of type 1 diabetes. In samples of pancreatic tissue, enterovirus RNA was also detected, but in extremely small quantities and in a smaller proportion of cases compared to the enteroviral protein. Difficulties in detecting viral RNA could be due to the very small number of infected cells, the possible activity of PCR inhibitors, and the presence—during persistent infection—of the viral genome in unencapsidated forms. The aim of this study was twofold: (a) to examine if enzymes or other compounds in pancreatic tissue could affect the molecular detection of encapsidated vs. unencapsidated enterovirus forms, and (b) to compare the sensitivity of RT-PCR methods used in different laboratories. Dilutions of encapsidated and unencapsidated virus were spiked into human pancreas homogenate and analyzed by RT-PCR. Incubation of pancreatic homogenate on wet ice for 20 h did not influence the detection of encapsidated virus. In contrast, a 15-min incubation on wet ice dramatically reduced detection of unencapsidated forms of virus. PCR inhibitors could not be found in pancreatic extract. The results show that components in the pancreas homogenate may selectively affect the detection of unencapsidated forms of enterovirus. This may lead to difficulties in diagnosing persisting enterovirus infection in the pancreas of patients with type 1 diabetes. Enteroviruses (EVs) are linked to the pathogenesis of type 1 diabetes (T1D). Epidemiological studies showed a risk association between EV infections and the development of islet autoimmunity and T1D, and recent reports indicated that a low-level EV infection may occur in the pancreata of patients with recent onset T1D ,3,4, wheIn fact, detection of EV RNA in the pancreas of T1D patients turned out to be challenging, and the amount of genome equivalents is extremely low and close to the detection limits of sensitive RT-PCR assays . One reaThus, there is an intense interest in whether persistent infections as reported above can also be found in pancreata of T1D patients. In addition to the supposedly low virus amount, the pancreas may also contain compounds that inhibit PCR reactions. The above observations may explain why detection of EV RNA in the pancreas of T1D patients is so difficult. The nPOD (Network for Pancreatic Organ Donors with Diabetes) pancreas tissue biobank  greatly We set out to evaluate the sensitivity of EV detection using different RT-PCR methods in pancreas homogenates. Particularly, we addressed the question whether pancreatic components may affect the ability of RT-PCR methods to detect encapsidated vs. unencapsidated virus RNA including the terminally deleted form of viral RNA. We also addressed if the organ procurement procedure (including transport to the laboratory on wet ice) could affect virus detection. This study was performed at three collaborating laboratories of the nPOD-V working group. Thus, we could compare the sensitivity of EV detection using five different RT-PCR approaches targeting the conserved 5′ UTR region of viral genome.Three virology laboratories of the nPOD-V consortium contributed to the study: (a) University of Tampere, Finland; (b) Baylor College of Medicine, Houston, Texas; (c) University of Insubria, Varese, Italy.−3, 10−6, 10−7, 10−8, 10−9) and immediately frozen at −80 °C. One set of CVB1 dilutions was kept on wet ice for 20 h after spiking and frozen as above. An identical CVB1 dilution series was made in sterile water. Pancreas extract and water samples with no addition of virus were used as negative controls.An EV-negative pancreas sample of a non-diabetic organ donor from the PanFin study  was homoFrozen samples were coded and distributed to the three laboratories. Blinded samples were tested at the three nPOD-V laboratories that used five different RT-PCR methods for EV detection. Tampere laboratory: RNA was extracted from pancreas homogenate samples using the Viral RNA Kit . Samples were analyzed using two RT-PCR methods: a semi-quantitative RT-PCR coupled with hybridization with an EV-specific probe (PCR 1) [ (PCR 1) , and a q (PCR 1) .Houston laboratory: RNA was extracted with MagMax Viral RNA Isolation Kit . RNA was converted to complementary DNA (cDNA) with Superscript III RT (Invitrogen) according to the manufacturer’s directions with random primers. PCR was carried out with SYBR-Green PCR master mix (Invitrogen) using the same primers as above [as above . PCR wasVarese laboratory: Pancreas homogenates were analyzed using two different procedures: (a) direct RNA extraction (PCR 1), and (b) RNA extraction following blinded passage in four different cell lines  in order to enrich the possibly present virus (PCR 2). The procedure was performed essentially as reported [reported . Total RAll used enterovirus primer pairs and probes are listed in 5 cells per well. Cells were transfected with a combination of the CVB3 RNA and plasmid DNA expressing GFP (green fluorescent protein) which served as carrier nucleic acid and as a marker of transfection efficiency. For each well, a combination of GFP plasmid DNA (250 ng) and 1.2 × 106 genome copies of either CVB3 RNA or TD-CVB3 RNA was transfected using Lipofectamine 3000 (Invitrogen) and standard transfection protocols. This generated an estimated maximal transfection rate of 10 viral genomes per cell. GFP expression in control wells at 12 h post transfection was monitored by fluorescence microscopy, and the efficiency of plasmid/RNA uptake into cells was routinely judged to be approximately 80%.Infectious cDNA clones of full-length CVB3 strain 28 (CBV3), as well as of CVB3 containing a 5′ terminal deletion of 49 nt (TD-CVB3) , were us5 transfected cells to 105 untreated cells, down to one transfected/infected cell in a background of 105 untreated cells. Each cell dilution was centrifuged, the supernatant was removed, and pancreatic lysate was added to the cell pellets. Cells were incubated with pancreatic lysate on wet ice for 15 min, then flash frozen at −80 °C overnight before RNA extraction. RNA was isolated from cells in 50 µL of elution buffer using the MagMAX Viral RNA Isolation Kit (Invitrogen). cDNA was generated with the SuperScript III Reverse Transcriptase (Invitrogen) before analysis by qRT-PCR as described above.Alternatively, cells were infected with CVB3 virus at MOI (multiplicity of infection) = 10. Transfected cells and infected cells were incubated for 6 h at 37 °C in the presence or absence of 2 mM guanidine HCl before cells were harvested. To remove unabsorbed transfection RNA or virus, cells were washed five times with growth medium, then treated with RNase A (1 mg/mL) in medium for 30 min at 37 °C. Cells were again washed three times with PBS  and trypsinized. The transfected/infected cells were removed from the plate and mixed in serial one log dilution increments with untreated HeLa cells beginning at 10The ability of different RT-PCR methods to detect enterovirus RNA in pancreas was analyzed using pancreas homogenates spiked with different amounts of infectious CVB1 and CVA6 . The senTo evaluate the ability of detecting unencapsidated viral RNA, an experiment was carried out where transfected cells containing viral RNA were diluted into a background of non-transfected cells before recovery from pancreatic extracts A. Using In condition B, cells were infected 60 min to allow uptake, penetration, and release into the cytoplasm. Unadsorbed virus was washed away, and infected cells were diluted into a background of uninfected cells A. Then, RNA from the wild-type CVB3, as well as free RNA purified from terminally deleted CVB3, was tested for stability in pancreatic extract after incubation on ice for 15 min. Results indicate that almost no such terminally deleted RNA survived the interaction with pancreatic extract for a short period of time B.Since it is difficult to determine precisely how much transfected RNA is delivered into cells, we performed another experiment to compare viral recovery during replication versus non-replication conditions. Infections and transfections were carried out in HeLa cells as described above. Both wild-type CVB3 RNA and terminally deleted CVB3 RNA were transfected into the cells. To verify that viral RNA was introduced into the cells, we allowed six hours of incubation time for a measurable replication to occur B. Parall5 genome equivalents were introduced into the experiment. Notably, comparison of intact CVB3 RNA to terminally deleted CVB3 RNA indicated nearly a log lower detection level, likely due to the additional instability of terminally deleted CVB3 to cytoplasmic nucleases resulting from a loss of the stabilizing 5′ hairpin structure [Comparison of the detection of transfected wild-type CVB3 RNA versus terminally deleted CVB3 RNA from cultured cells indicates a further nine-fold loss of recovery under conditions where the replication was blocked A. There tructure .The present study demonstrates that detection of encapsidated enterovirus RNA by RT-PCR was not much affected by a 20-h-long incubation on ice in pancreatic homogenates prior to RNA extraction, while even a short incubation on ice led to dramatic decrease in the detection of unencapsidated viral RNA. In addition, the results showed that the sensitivity of different EV RT-PCR assays differed slightly depending on the assay itself and the sample type analyzed.All assays were capable of detecting very small levels of virus but did not always lead to amplicons when fewer than 1000 genomes per reaction were present, which is typical for this type of analysis. Importantly, the results indicate that pancreas tissue does not contain factors that significantly inhibit polymerase activity in molecular assays of this kind.An additional test in the experimental design was to see if the transport of pancreas on wet ice, which is an unavoidable part of the nPOD organ procurement procedure, adversely impacts the recovery of RNA from encapsidated virions. The data indicate that it does not, as the 20-h incubation with pancreatic extract on wet ice did not cause a significant decrease in the number of viral genomes detected. Thus, the transport of pancreas tissues on wet ice seems to be adequate for EV detection by RT-PCR, preventing the loss of viral RNA which easily happens at high temperatures . TogetheFurther experiments indicated that viral RNA with terminal deletions is rapidly destroyed by brief incubation on ice with pancreatic extract, and that detection of unencapsidated RNA was much lower than that of RNA encapsidated in complete virus particles. Under the conditions used, less viral RNA was recovered from transfected cells than from naturally infected cells. This could be partly due to the lack of nuclease-protective VPg  on transfected RNA and delivery via liposomes to cytoplasmic compartments that undergo lysosomal decay. These limitations make it difficult to quantitatively model the exact conditions of a low-level replicating terminally deleted CVB3 in cells. Nonetheless, the comparison of transfected RNA under non-replicating versus replicating conditions indicates that a proportion of transfected RNA is delivered to the correct cytoplasmic compartment to initiate genome replication. Under these conditions, we cannot precisely determine the limit of detection of unencapsidated CVB3 RNA in cells. However, taken together, the data indicate that detection would be approximately 100–1000-fold lower than that of encapsidated virion RNA. Detection of terminally deleted CVB3 RNA would add an additional eight-fold reduction of efficiency as compared to intact CVB3 RNA.Taken together, the results indicate that virus RNA that is protected inside capsids is stable to the RNase activities in pancreas extract, such that no substantial effect on virus RNA detection was noted. However, an increasing amount of data suggest that virus in the pancreas of T1D patients may be terminally deleted and replication-deficient. Such virus may have a much lower rate of encapsidation since enterovirus encapsidation efficiency is coupled to replication rates . FurtherIn conclusion, the study indicates that detection of unencapsidated viral RNA within rare cells in a population of uninfected cells, in an environment that contains pancreatic enzymes, is quite difficult. This does not derive from inhibitory effects of pancreatic factors on RT-PCR polymerases, but mostly from the exposure of viral RNA to RNase activities. The recovery of unencapsidated enterovirus RNA from such samples is not impossible but may require 100–1000 genome equivalents in each sample. The problem becomes more pronounced with terminally deleted EV that lacks a protective 5′ stem loop structure and undergoes encapsidation with greatly reduced efficiency . The res


The concentrations of distinct types of RNA in cells result from a dynamic equilibrium between RNA synthesis and decay. Despite the critical importance of RNA decay rates, current approaches for measuring them are generally labor-intensive, limited in sensitivity, and/or disruptive to normal cellular processes. Here, we introduce a simple method for estimating relative RNA half-lives that is based on two standard and widely available high-throughput assays: Precision Run-On sequencing (PRO-seq) and RNA sequencing (RNA-seq).Our method treats PRO-seq as a measure of transcription rate and RNA-seq as a measure of RNA concentration, and estimates the rate of RNA decay required for a steady-state equilibrium. We show that this approach can be used to assay relative RNA half-lives genome-wide, with good accuracy and sensitivity for both coding and noncoding transcription units. Using a structural equation model (SEM), we test several features of transcription units, nearby DNA sequences, and nearby epigenomic marks for associations with RNA stability after controlling for their effects on transcription. We find that RNA splicing-related features are positively correlated with RNA stability, whereas features related to miRNA binding and DNA methylation are negatively correlated with RNA stability. Furthermore, we find that a measure based on U1 binding and polyadenylation sites distinguishes between unstable noncoding and stable coding transcripts but is not predictive of relative stability within the mRNA or lincRNA classes. We also identify several histone modifications that are associated with RNA stability.We introduce an approach for estimating the relative half-lives of individual RNAs. Together, our estimation method and systematic analysis shed light on the pervasive impacts of RNA stability on cellular RNA concentrations.The online version contains supplementary material available at 10.1186/s12915-021-00949-x. Gene regulation is an exquisitely complex process that operates at all stages of gene expression, ranging from pre-transcriptional chromatin remodeling to post-translational modification of proteins. However, the concentration of RNA molecules in the cell appears to serve as the primary target of many regulatory mechanisms. Many studies of gene regulation focus on the production of RNA, often at the stages of transcriptional pre-initiation, initiation, or release from pausing into productive elongation. RNA concentrations, however, result from a dynamic equilibrium between the production of new RNA molecules and their decay –7. IndeeOver several decades, investigators have developed numerous methods for measuring RNA decay rates or half-lives –15. A clRecently, it has been shown that changes to RNA half-lives can be identified in a simpler manner, by working directly from high-throughput RNA-seq data , 22, 25.In this article, we show that this same general approach—but using a measure of nascent transcription based on PRO-seq rather than intronic RNA-seq reads—results in improved estimates of relative RNA half-life. Our approach requires only two standard and widely applicable experimental protocols—PRO-seq and RNA-seq. It applies to intron-less as well as intron-containing transcription units, it requires no correction for RNA-processing rates, it makes efficient use of the available sample material and can be extended to tissue samples using ChRO-seq , it is rn = 11,011), lincRNA (n = 1143), antisense (n = 1066), and pseudogene (n = 590) classes. We quantified expression by the total number of mapped reads in transcripts per million (TPM), a measure that normalizes by both library size and TU length, and discarded TUs with insufficient read counts from either assay. Notably, we excluded the first 500 bp downstream of the TSS and 500 bp upstream of TES for PRO-seq to avoid a bias from promoter-proximal pausing and polymerase deceleration [We first compared PRO-seq and RNA-seq measurements for various TUs from across the human genome, to assess the degree to which transcriptional activity, as assayed by PRO-seq, is predictive of steady-state RNA concentrations, as assayed by RNA-seq. We obtained previously published PRO-seq  and rRNAleration   at 4351 genes measured by both methods. We found that the two sets of estimates were reasonably well correlated  [To reveal potential determinants of RNA stability, we sought to identify features of TUs that were predictive of our estimated RNA half-lives. We focused on the mRNA and lincRNA classes, for which we could identify the most informative features. Anticipating an effect from splicing , 38, we el (SEM)  that expOur analysis revealed positive correlations with half-life of both splice junction density and total intron length, for intron-containing mRNAs and lincRNAs Fig. ” sectionn = 1429) also analyzed by Veloso et al. [To evaluate the degree to which these findings were influenced by elongation rate, we repeated the SEM analysis for a subset of genes  of various lengths near the TSS  , 45, 46.see the “” sectionpts Fig. ” sectionThe atypical patterns around CpG dinucleotides raise the possibility of an association with DNA methylation near the TSS. We therefore compared the methylation patterns of TUs exhibiting low, medium, or high levels of RNA stability, summarizing these patterns with meta-plots of average signal of the methylated DNA immunoprecipitation (MeDIP-seq) assay in K562 cells , 49 as aWe also directly tested for the possibility that differences in RNA half-life could reflect the presence or absence of either U1 binding sites (5′ splice sites) or polyadenylation sites (PAS) downstream of the TSS. Comparisons of (stable) protein-coding TUs and (unstable) upstream antisense RNA (uaRNA) TUs have revealed significant enrichments for proximal PAS in uaRNAs, suggesting that they may lead to early termination that triggers RNA decay. These studies have also found significant enrichments for U1 binding sites in protein-coding TUs, suggesting that splicing may play a role in enhancing RNA stability , 46. In T1/2PR values. We also computed the SSI for the eRNAs identified from PRO-seq data and classified as stable or unstable based on CAGE data. We found that the mRNAs had the highest SSI, followed by lincRNAs, and then eRNAs . More work will be required to clarify the relative strengths and weaknesses of the available methods.In a comparison of half-life estimates from several methods that have all been applied to K562 cells, including TimeLapse-seq , TT-seq Notably, our method has limited sensitivity for highly unstable transcripts. When half-lives are low, the RNA-seq signal tends toward zero, leading to limited ability to identify gradations of stability. For this reason, we have focused our half-life analysis on genes with fairly strong signals from both assays , or a back-up in traffic . Consequently, variation in ell type   that explicitly describes the separate effects of each feature on transcription and half-life, as well as the resulting impact on RNA concentrations, PRO-seq, and RNA-seq data. While multivariate regression has been used to identify features associated with RNA stability , our anaIt has recently been reported that U1 binding sites are enriched, and polyadenylation sites are depleted, downstream of the TSS in stable mRNAs relative to unstable upstream antisense RNAs (uaRNAs) and enhancer RNAs (eRNAs), suggesting that RNA stability is determined, in part, by the DNA sequence near the TSS. In this study, we tested not only whether this “U1-PAS axis” could distinguish TUs in stable classes (mRNAs) from those in unstable classes (uaRNAs and eRNAs) but also how predictive it is of half-life within these classes. We confirmed that a U1-PAS-based “sequence stability index” (SSI) is generally elevated for mRNAs, intermediate for lincRNAs, and reduced for eRNAs. Furthermore, this SSI can distinguish between more and less stable eRNAs, as quantified using CAGE Fig. e. SomewhSome of the associations that we observed with half-life concerned G+C content, but these observations are generally difficult to interpret. Indeed, even the comparatively straightforward question of the relationship between G+C content and transcriptional activity has a long and contradictory literature, with several studies finding correlations between them –62, but There is now substantial evidence for connections between events that occur before or during transcription and a variety of post-transcriptional processes, some of which impact RNA stability. In addition to the apparent enhancement of RNA stability by splicing, there is now evidence that some RNA-binding proteins having roles in RNA export and stability are recruited to the RNA in a promoter-dependent manner –69. SimiOne general pattern that emerges from the SEM analysis of histone modifications is that the coefficients for transcription and half-life are often different from zero in opposite directions  and RNA-seq (n = 4) libraries, generated from cells grown in the same flask under the same conditions. Human K562 cells were cultured using standard cell culture procedures and sterile techniques. The cells were cultured in RPMI-1640 media supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin. For PRO-seq, 3′ and 5′ adapters were ligated as described [https://assets.thermofisher.com/TFS-Assets/LSG/manuals/trizol_reagent.pdf), followed by rRNA depletion using the Ribozero HMR Gold kit. Libraries were prepared using the NEB kit with TruSeq RNAseq adaptors. Single-end sequencing (length = 75) was performed on a NextSeq500 instrument by the RNA Sequencing Core at the College of Veterinary Medicine, Cornell University. Sequencing data is deposited on GEO under accession GSE153200.Our main analysis is based on PRO-seq data for K562  and HeLaescribed  followedescribed . SequencRaw data files in fastq format were trimmed using Cutadapt  with parβi; a constant per-RNA-molecular rate of decay, αi; and a number of RNA molecules, Mi. At steady state, βi = αiMi; therefore, the decay rate can be estimated as αi = βi/Mi, and the half-life as T1/2 = ln(2)/αi = ln(2) × Mi/βi. We further assume that the normalized PRO-seq read counts (omitting regions near the TSS and TES) are proportional to the rate of production of new RNAs, Pi ∝ βi, and that the normalized RNA-seq read counts are proportional to the number of RNA molecules, Ri ∝ Mi. Therefore, T1/2 ∝ Ri/Pi. We define our unit-less estimator of half-life as T1/2PR = Ri/Pi, where PR denotes a PRO-seq/RNA-seq-based estimator. Notice that these unit-less T1/2PR values can be compared across experiments only up to a proportionality constant, unless the raw read counts have been appropriately normalized. To compare our PRO-seq-based approach with an approach based on intronic reads, we repeated the estimation using normalized intron reads instead of PRO-seq read counts to represent the transcription rate.We assume a constant rate of production of new RNAs, A potential confounding factor in the comparison of normalized read counts for PRO-seq and RNA-seq is elongation rate. Because PRO-seq read depth reflects a combination of transcription initiation rates and elongation rates , 77, somXn be the nth feature associated with a TU. We assume that the logarithms of this TU’s transcription rate and half-life, i.e., b = log β and t1/2 = log T1/2PR, are linear combinations of the Xn’s and a TU-level random effect: b λnXn + εb and t1/2 μnXn + εt where ϵb ∼ N and ϵt ∼ N are independent Gaussian random variables explaining all variation not attributable to known features. Assuming a fixed value X0 = 1 for all genes, the parameters λ0 and μ0 can be interpreted as intercepts whereas λn≠0 and μn≠0 are regression coefficients indicating the contributions of feature n to transcription rate and half-life, respectively.To separate the effects of TU features on decay from the effects on transcription, we developed a SEM using the “lavaan” R package . Let Xn T1/2PR∝ M/β, where M is the number of RNA molecules; therefore, m = log M is given by m = b + t1/2 + C, where C is an arbitrary constant that can be ignored here because it does not affect the estimation of regression coefficients. Denoting pj = log Pj and rj = log Rj as the logarithms of the PRO-seq and RNA-seq measurements in replicate j, respectively, we assume pj ~ b + εp and rj ~ m + εr where ϵp ∼ N and ϵr ∼ N are independent Gaussian random variables describing the noise in PRO-seq and RNA-seq experiments, respectively. Finally, we assume that all observations are independent across TUs. With these assumptions, and pooling information across TUs of the same class, we can estimate separate regression coefficients for transcription rates (λn) and half-life (μn) for all features by maximum likelihood.According to the model derived above, at steady state, Transcription unit (TU) sequences were downloaded from BioMart using the R package biomaRt , 79. We n = 21,816). To measure steady-state RNA levels, we used CAGE in place of RNA-seq owing to its greater sensitivity. We used the Nucleus PolyA and Non-polyA CAGE libraries from ENCODE (GEO accession number GSE34448). To measure transcription rates, we used PRO-seq data from same study [n = 510).We used eRNAs identified from our previous GRO-cap analysis in K562 cells  restrictme study . For thek ∈ {2, 3, 4}. For each word w, we counted the total number of appearances in our set of stable TUs (top 20% by T1/2PR), denoted cs,w, and the total number of appearances in unstable TUs (bottom 20% by T1/2PR), denoted cu,w. These counts were collected in 1 kb windows beginning at various distances downstream of the TSS . The enrichment score for each word w and each window position was then computed as log2. A positive value of this score indicates an enrichment, and a negative score indicates a depletion in stable TUs relative to unstable TUs. For eRNAs, we used a similar procedure but with 400 bp windows at distances of 0, 200, 400, and 600 bp from the TSS.We considered all DNA words  of sizes T1/2PR as the primary sequences and the bottom 20% as the control sequences. For the unstable motifs, we reversed the primary and control sequences.For motif discovery, we used the discriminative motif finder “DREME”  with defhttps://github.com/Danko-Lab/stabilityHMM.We define the SSI to be the probability that a TU is “stable” based on our previously published U1-PAS hidden Markov model (HMM) . BrieflyWe used the R package “MatchIt” , 83 to mhttp://www.targetscan.org/vert_72/vert_72_data_download/Predicted_Targets_Info.default_predictions.txt.zip). We used all default predictions of conserved targets for each conserved miRNA family in the database.We obtained microRNA targets from TargetScanHuman , Releasehttps://www.genenames.org/).We obtained lists of genes encoding ribosomal proteins and zinc fingers from the HUGO Gene Nomenclature Committee (http://hgdownload.soe.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeSydhHistone/) and DNA methylation IP  data were downloaded from the ENCODE consortium [T1/2PR values, and then subsampled from classes 1 (low stability), 3 (medium stability), and 5 (high stability) to obtain distributions matched by PRO-seq signal. We then produced meta-plots for each of these three classes showing the average signal of the histone modifications (ChIP-seq) and methylated DNA immunoprecipitation (MeDIP-seq) assays in K562 cells [Histone modifications  or intron-less  transcription units in K562 cells. Figure S5. Scatter plots of PRO-seq vs. RNA-seq for lincRNAs and protein-coding mRNAs in K562 cells after matching by PRO-seq signal. Figures S6-S7. Scatter plots of PRO-seq vs. RNA-seq for transcription units in K562 cells  or HeLa cells . Figure S8. Scatter plots of PRO-seq vs. RNA-seq for mRNAs and lincRNAs in K562 cells before and after correcting for elongation rate. Figure S9. Intronic half-life vs. TimeLapse-seq half-life. Figure S10. Empirical cumulative distribution functions (eCDFs) for estimated half-lives of predicted targets of miR-125-5p and miR-19-3p vs. non-targets. Figure S11. Correlation of estimated RNA half-lives under various methods. Figure S12. Correlation of PRO-seq-based half-lives  vs. estimates from TimeLapse-seq  after correcting for elongation rate. Figures S13-S14. SEM results for features of intron-containing  or intron-less  transcription units in K562. Figure S15. Estimated half-lives for intron-containing and intron-less transcription units. Figure S16. SEM results for features of intron-containing transcripts in K562 cells, with and without a correction for elongation rate. Figure S17. Multiple linear regression (MLR) for features of transcription units versus RNA stability in K562 cells. Figures S18-S19. DNA word enrichments in stable transcripts for protein-coding mRNAs  or lincRNAs . Figure S20. G+C content in intervals downstream of the TSS for various classes of transcription units. Figure S21. DNA word enrichments in stable transcripts for eRNAs. Figure S22. DNA methylation in lincRNAs of various stability levels. Figure S23. Sequence Stability Index of intron-containing versus intron-less genes. Figures S24-S25. Sequence Stability Index (SSI) for mRNAs  or lincRNAs  of various stability classes. Figures S26-S27. Histone modification signals for protein-coding mRNAs of various stability classes. Half-live estimations are based on published data  or newly collected data for this study . Figures S28-S29. Estimated SEM coefficients for transcription  and half-life  for 11 histone modifications. It’s assayed by ChIP-seq in the 500 bases  or 1000-1500 bases  downstream of the TSS. Figures S30-S31. Estimated SEM coefficients for transcription  and half-life  for 11 histone modifications. It’s based either on published data  or on the newly collected PRO-seq and RNA-seq data .Additional file 3. Variation in Elongation Rate is Insufficient to Explain Variation in Half-Life.


PPR proteinsare classified into P and PLS subfamilies. In this work, we have designed RNAbiotinylated probes based in soybean plastid RNA editing sites to performtrans-factor specific protein isolation. Soybeancis-elements from these three different RNA probes showdifferences in respect to other species. Pulldown samples were submitted to massspectrometry for protein identification. Among detected proteins, fivecorresponded to PPR proteins. More than one PPR protein, with distinctfunctional domains, was pulled down with each one of the RNA probes. Comparisonof the soybean PPR proteins to Arabidopsis allowed identification of the closesthomologous. Differential gene expression analysis demonstrated that the PPRlocus Glyma.02G174500 doubled its expression under salt stress, which correlateswith the increase of its potential rps14 editing. The present study representsthe first identification of RNA editing trans-factors insoybean. Data also indicated that potential multipletrans-factors should interact with RNAcis-elements to perform the RNA editing.RNA editing is a posttranscriptional process that changes nucleotide sequences,among which cytosine-to-uracil by a deamination reaction can revert non-neutralcodon mutations. Pentatricopeptide repeat (PPR) proteins comprise a family ofRNA-binding proteins, with members acting as editing A strong selective pressure acted to maintain theremaining endosymbiotic genetic information. Posttranscriptional processes wereselected by promoting the maintenance of essential sequences for gene expression andfunctional proteins. In plastids, RNA editing is a nucleotide change from cytosineto uracil (C-to-U) and less frequently, from uracil to cytosine (U-to-C) bydeamination and amination reactions, respectively . These changes are necessary for RNA maturation, togenerate start or stop codons, or even to result in changes in amino acid identity. In general, 20 nucleotides upstream and, in somecases, 10 nucleotides downstream from the sequence of the RNA editing sitecorrespond to the cis-elements for RNA editing (trans-factor identified was a Pentatricopeptide Repeat protein(PPR). PPR proteins are characterized by tandem arrays of degenerated 31 to 36-aminoacid repeating units, called PPR motifs, repeated in tandem up to 30 times, thatfolds into a pair of antiparallel α-helices, forming a solenoid structure . This protein family has thousands of members in land plants, withabout 450 members in Arabidopsis, corresponding to the most studied RNA editingfactor so far recognized . PPR proteins form sequence-specific associationswith RNA, and these associations affect folding, processing, and translation of theRNA, thus manipulating the expression of the transcript .Extensive studies have been performed to elucidate molecular features, mechanism, andthe machinery of plastid RNA editing. Arabidopsis thaliana (43) . These findings can be used to evaluate the impact ofdifferent stresses on editing mechanisms. Soybean is a model crop with some priorstudies about plastid RNA editing. Our group has described 43 phylogeneticallyconserved and five non-conserved editing sites in Glycine max usingRNA sequencing data . Besides that, we also have described a salt stresseffect in soybean plastid RNA editing .Plastid RNA editing was reported in most of the plant lineages, and the number ofediting sites varies among species. In seed plants, plastid editing sites havealready been reported in rice (21), maize (26), tobacco (34), cucumber (51), andcis-elements were selected, all of them presenting high editinglevels, where intense plastid RNA editing trans-factors activity isexpected. Biotinylated probes were designed based on thesecis-element sequences to perform an RNA-pulldown proteinpurification. Plastid RNA editing trans-factors acting in selectedsoybean plastid cis-element were identified, and its specificityamong sites was evaluated. Also, other proteins were identified that havenon-specific cis-element binding activity.Based on these sequencing data, three plastid RNA editingatpF (GlmaCp025), ndhB(GlmaCp064), and rps14 (GlmaCp013) genes were used to designRNA probes. Three probes were produced corresponding toatpF-92, ndhB-1481, andrps14-80 editing sites as the reference to select 28 upstreamand 7 downstream nucleotides, totalizing a 36-nucleotide probe from each editingsite: atpF-92,UUUAAUACCGAUAUUUUAGCAACAAAUCCAAUAAAU;ndhB-1481,AUUGUAUGUGUGAUAGCAUCUACUAUACCAGGAAUA; andrps14-80,CAGAAAUAUCAUUUGAUUCGCCGAUCCUCAAAAAAA. The RNA probeswere synthesized and biotinylated at the 5’ end. To analyze the conservation ofRNA cis-element sequences among species, chloroplast codingsequences for each transcript were identified in the eight species listed inet al., 2013). Sequence logos were generated using WebLogo3 Merrill)cultivars Conquista were cultivated until the fifth trifoliate (V5) stage. Themodified high salt chloroplast isolation protocol was followed to obtainchloroplasts .For chloroplast isolation, soybean  andtransferred to a microcentrifuge tube. The resuspended solution was pulledthrough a syringe (0.3 mm 8 mm) 60 times. The homogenate was centrifuged twiceat 16,000 x g for 20 min at 4 °C. A supernatant aliquot wastransferred to a new tube, and the same volume of incubation buffer  wasadded. The homogenate was transferred to a new tube and biotinylated probes corresponding to each editing site were added. Thesolution was incubated at 160 rpm for 30 min at 25 °C. Control blank analysescorresponded to resin incubated with total protein extracts without any RNAprobe. In addition to the blank control, each probe can be considered and usedas the control of each other in the protein identification assays, forming agroup in the analyses. The homogenate was transferred to a centrifuge tubecontaining streptavidin-agarose resin previously washed with lysis andincubation buffer 1:1 (v/v) thrice. The washing step consisted of adding thesolution, gentle manual shaking and resin decantation, followed by discardingthe volume above the resin. The solution was maintained on a gentle manualshaking for 15 min. Two washing steps were performed with lysis and incubationbuffer 1:1 (v/v), followed by three washing steps with lysis and incubationbuffer (without Triton X-100) 1:1 (v/v). The final solution containingstreptavidin-agarose resin, biotinylated probes/blank control, and plastidproteins was maintained at -20 °C before sample preparation.All the following steps were carried out at 0 °C if not otherwise stated. Thefinal chloroplast pellet was resuspended in lysis buffer  overnight at 35 °C. Trifluoroacetic acid (TFA) was added  in order to stop digestion, and peptides were passed throughC18 spin columns (Harvard Apparatus), dried under vacuum and stored at -20 °Cfor further use. Two biological replicates were subjected to digestion for eachRNA probe.The resins were incubated for 5 min at room temperature, with 7 M urea/2 Mthiourea. Proteins extracted from resins were further reduced using 10 mM DTTfor 60 min at 35 °C and alkylated using 40 mM iodoacetamide for 60 min at 35 °Cin the dark. Urea concentration was diluted to less than 1 M using 50 mMNH® Self-Pack column . The sampleswere analyzed in an EASY-nLC II system (Proxeon Biosystems) coupled in sequenceto a high-resolution ESI-LTQ-Orbitrap Velos mass spectrometer (ThermoScientific). The peptides were eluted using the gradient starting from 100%phase A  to 35% phase B  for 107 minutes, 35-100% of phase B for 5 min, and 100% ofphase B for 8 min, totaling 120 min in a flow of 250 mL/min. After each run, thecolumn was washed with 100% of phase B and re-equilibrated with phase A. Peptides obtained from the tryptic digestion (2 μg) were loaded onto a C18reversed-phase pre-column  and fractionated on a NewObjective PicoFritTM algorithm and a G.max database downloaded from Phytozome (June 2017). The parametersused were: full-tryptic search space, up to two missed cleavages allowed fortrypsin, precursor mass tolerance of 10 ppm, and fragment mass tolerance of 0.1Da. Carbamidomethylation of cysteine was included as fixed modification, andmethionine oxidation and protein N-terminal acetylation as dynamicmodifications.The m/z spectra were obtained in positive mode with data-dependent automaticacquisition - Data-Dependent Acquisition (DDA) - of the MS and MS/MS spectra.The MS spectra were obtained in high resolution in the Orbitrap analyzer with aresolution from 30,000 at m/z 400, mass range of m/z 350-2000, Automatic GainControl (AGC) of 1 x 106 and maximum injection time of 500 MS. The MS/MS spectrawere obtained by higher energy collisional dissociation (HCD) in the Orbitrapfor the 10 most intense ions, with a charge ≥ 2, resolution of 7500 at m/z 400,signal threshold of 10,000, the normalized energy of collision (NCE) of 30, anddynamic exclusion of 45 s. Proteome Discoverer 2.1 software was used for dataanalysis applying the Sequestet al., 2016) was used to evaluate how and where the PPRprotein binds to the RNA designed probes, and if this binding event has astatistical significance. The sequences from the PPR proteins and the RNA probeswere used as input. The chloroplast genome sequence of soybean was used asinformation for random alignment. Binding events that had high statisticalsignificance (p < 0.05) were selected.To determine the specificity of the interaction between selected PPR and therespective probe sequence, the aPPRove method  for the predictionof functional domains . The sequence domain found in each proteinsequence was retrieved to create a fasta file. The protein domain sequences werealigned using MUSCLE .The model of protein evolution for each protein matrix substitution wascalculated from multiple alignments by ProtTest3 . The phylogenetic tree was constructed using theBayesian method, performed in BEAST 1.8.4 software  with default parameters and zero mismatches. Acount table containing data from all libraries was created and used as an inputfile for differential expression analysis performed using the BioconductorDESeq2 package  with an adjusted p-value cutoffof 0.05. Public mRNAs libraries of soybean leaves, deposited by our group in NCBI GEO(http://www.ncbi.nlm.nih.gov/geo/), accession number GSE69571, were used toevaluate the differential gene expression of the identified PPR proteins. SAMfiles were created using Bowtie software . Monocots already have thymine in theediting site location . Other differences occur after 26 upstreamand 10 downstream nucleotides. The ndhB-1481 recognitionsequence is the most conserved among all analyzed recognition sequences.Differences could be observed only in position 27 upstream and 19 downstreamfrom an editing site . The rps14-80recognition sequence is the most variable sequence among all analyzed ones.Differences could be observed even within monocots . In total, 14positions with nucleotide differences were observed in therps14-80 recognition sequence .Recognition sequences from  species . The atpatpF-92, ndhB-1481, andrps14-80 probes comprises 83, 106, and 78 proteinsrespectively, while the blank profile, corresponding to a sample not incubatedwith RNA-probes, comprises 160 proteins  thatpresents a DYW motif.In total, five PPR proteins were identified in different RNA probe pulldownprofiles (Table 1). Glyma.11G217500 and Glyma.19G025700 proteins were identifiedin the rps14-80 probe.Glyma.02G174500 with two PPR domains (three copies of PF01535 and two PF13041)plus the cytosine-deaminase domain with the DYW motif (PF14432). The second PPRprotein, Glyma.11G111200 has only two PPR domains (four copies of PF01535 and asingle PF13041). This protein was also identified in thendhB-1481 pulldown, as was also observed with Glyma.01G016100that contains three PPR domains  (Two others PPR proteins were associated with the PF13041) . et al., 2016). This analysis provides an evaluationof the binding event between the PPR and the probe as not occurring at random.All PPR proteins had more than one alignment per probe. The best alignment foreach PPR protein in its respective probe is shown in Figure 2b. All PPR-probealignments to each PPR protein are listed in The specificity of the PPR-probe alignment was evaluated using the aPPRove method, ndhB-1481 (OTP84),and rps14-80 (OTP86) do not cluster to soybean PPR proteinsfound in the pulldown assays. The soybean PPRs isolated from the pulldowncontinued to cluster to distinct Arabidopsis PPRs , OTP84 (AT3G57430),and OTP86 (AT3G63370)  and compared to thePPR-probe alignment of Glyma.02G174500, Glyma.01G016100, and Glyma.19G025700. Inall PPR-probe alignments evaluated, the soybean PPRs of the probe pulldownassays had the best alignment, with a p-value more significantthan the Arabidopsis or its most similar soybean PPR (Table 2). All Arabidopsisand their most similar soybean PPRs aligning to RNAcis-elements are listed in A different approach using BLASTP analysis, against soybean PPRs, was performedto identify the three most similar proteins to Arabidopsis3G63370) . The RNAet al., 2012). Only two genes, Glyma.02G174500 andGlyma.11G111200, both identified in rps14-80 probe pulldown,demonstrated differential expression between control and salt treatmentlibraries p-value 0.0117), whileGlyma.11G111200 had a decrease of -0.65-fold change   and two F-box genes(Glyma.11G126500.1 and Glyma.12G051100). These genes were already described asreference genes for normalization in soybean under salt stress (0.0004) .cis-elements and trans-factors fromthree soybean plastid RNA editing sites were analyzed. Each evaluatedcis-element of an editing site has a conservation pattern thatmay lead to an alteration in site-recognition of homologous proteins among species.In tobacco plastids, RNA editing sites with similar cis-elementsare recognized by an identical site-recognition protein . Along this same line, in vitro RNAediting demonstrated that deletions, insertions, and mutations incis-elements could lead to changes in a protein that recognizean editing site between plant species without loss of RNA editing .In this work, trans- factors andtheir interactions are based on co-immunoprecipitation and mutant genetic screening,and the model species have been restricted to Arabidopsis, maize, rice, andPhyscomitrella patens . In this study we used an alternative method in theprotein isolation step for mass spectrometry assays that allowed us to identify PPRproteins in each probe pulldown. Recently, a study redefined the structural motifsof PPR domains . According to this definitionand based on our phylogenetic analysis, Glyma.01G016100, Glyma.11G217500, andGlyma.11G111200 belong to the P subfamily, while Glyma.02G174500 and Glyma.19G025700to DYW subgroup of PLS subfamily. P-type PPR proteins are involved in two mainfunctions: stabilization and processing of specific RNA termini and control of thetranslation of specific mRNAs . The distribution of PPR among probe pulldown profilesuggests that multiple trans-factors are necessary for editing.To date, studies that identified RNA editing trans-factorto RNA editing: AEF1/MRF25 to atpF-92 , OTP84 to ndhB-1481, and OTP86 torps14-80 . In soybean atpF-92 andrps14-80, a P-type and a DYW-type can interact to promoteediting. Some studies have demonstrated the requirement of two PPR proteins for RNAediting in plastids and mitochondria . The Glyma.11G111200 protein was identified in twopulldown profiles, ndhB-1481 and rps14-80. OTP82and CRR22 have been reported to act as site-specificity factors at multiple RNAediting sites with unrelated cis-acting elements in plastids , and multiple PPR proteins could interact with aunique cis-element of an RNA editing site . Sharing of trans-factors can conferan advantage by being able to recognize more editing sites with a lower number ofrequired proteins. Besides that, a unique PPR can be a dual target to plastids andmitochondria, acting in different cis-elements of differentorganelles .In Arabidopsis, the three editing sites have only one trans-factors using phylogeneticanalysis can be difficult due to massive gene duplication and evolution of the PPRfamily in land plants . This massive duplication enables theevolution of plant RNA editing trans-factors despite changes in thecis-element sequence or the loss of editing sites . One of them wasthe rps14-80 editing site. Here, we evaluated the expressionpattern of PPR transcripts under salt stress. Interestingly, Glyma.02G174500, aDYW-type protein identified in the rps14-80 pulldown, has anincrease of about one-fold, corresponding to a double increase in its geneexpression. Thus, it is plausible to propose that the increase in the editing rateof rps14-80 editing site and the increase in Glyma.02G174500 geneexpression are related, as it corresponds to its cognatetrans-factor. The nucleotide alignment with the aPPRove methodsupports the proposition of the trans-factor function of thisDYW-type protein in the rps14-80 editing site.In a previous study, we demonstrated some plastid RNA editing enhancement in soybeanleaves under salt stress . Under salt stress, the increase in Glyma.02G174500 expressionand the decrease in Glyma.11G111200 can lead to a change in protein concentrationsand the binding equilibrium at the rps14-80 editing site, with aslight increment of the C-to-U editing rate (A model in which two distinct soybean PPRs can bind to the sameing rate .cis-elements that will berecognized by them.The study of the different classes of PPR proteins harboring a diversity of PPR andcatalytic domains and their interaction with RNA cis-elements, remains a topic thatrequires much more investigation, particularly in non-model organisms others thanArabidopsis and rice. As demonstrated by our analysis, it is not easy to identifythe homologous sequences of Arabidopsis PPRs in other plant species, and much lessso to obtain a good prediction of the