Ribonucleic acid (RNA) and proteins play critical roles in gene expression and regulation. The relevant study increases the understanding of various life processes and contributes to the diagnosis and treatment of different diseases. RNA imaging and mapping RNA-protein interactions expand the understanding of RNA biology. However, the existing methods have some limitations. Recently, precise RNA targeting of CRISPR-Cas13 in cells has been reported, which is considered a new promising platform for RNA imaging in living cells and recognition of RNA-protein interactions. In this review, we first described the current findings on Cas13. Furthermore, we introduced current tools of RNA real-time imaging and mapping RNA-protein interactions and highlighted the latest advances in Cas13-mediated tools. Finally, we discussed the advantages and disadvantages of Cas13-based methods, providing a set of new ideas for the optimization of Cas13-mediated methods. CRISPR-Cas  systems have received increasing attention in the scientific community due to their accurate targeting and excellent editing ability. The CRISPR-Cas loci encode an adaptive immune system in most archaea and many bacteria, which specifically recognize and cut foreign DNA or RNA sequences for improved protection against viral invaders .CRISPR-Cas systems have two principal modules, the adaptive module and the effector module . The adaβ-actin mRNA movement  have been recognized as one of the real components that regulate cellular functions, such as precise translation of spatiotemporal localization and promotion of correct cell expression . RBPs pl ability , Cas13 c ability .In this review, we first described the current findings on Cas13. Then, we discussed various Cas13-mediated imaging tools in the field of RNA imaging and detection of RNA-protein interactions and compared them with conventional tools. Finally, we comprehensively analyzed the advantages and disadvantages of Cas13-based imaging technology, provided relevant suggestions based on existing research, and put forward prospects for future research.Cas13 (type VI system) is the only member of the CRISPR-Cas systems that can specifically target RNA, in addition to the Class I Type III systems . Cas13 hCas13a is a large protein that belongs to the type VI-A CRISPR-Cas system . Cas13a Cas13b is more powerful than Cas13a. Zhang’s group tested 21 orthologs of Cas13a, 15 orthologs of Cas13b and seven orthologs of Cas13c for knockdown activity of Cas13 family members and indicated that the knockdown level of PspCas13b increased continuously relative to LwaCas13a  . Comparein vivo delivery because of its relatively small size , Nano-MBs, and Quencher-free probes. MBs are oligonucleotide probes formed by antisense stem-loop with a fluorophore and quenching agent at the end. The stem-loop structures contain recognition sequences binding to target RNA . With a As the quencher and the carrier, nanoparticles can combine with MBs to form Nano-MBs that consist of gold nanoparticles (GNPs) . GNP-NanQuencher-free probes can quench fluorophores by themselves, resulting in low background fluorescence without quenchers. Forced Intercalation Probes (FIT Probes) and Exciton-Controlled Hybridization-sensitive fluorescent Oligonucleotide probes (ECHO Probes) are two classical probes among them. Within the FIT probe, thiazole orange (TO) dyes serve as fluorescent base surrogates and signal hybridization in a single-nucleotide specific manner. The FIT probe can be used to develop brighter probes by incorporating fluorophore intercalators with higher fluorescence . ECHO prASH1 mRNA particles (Probes imaging exogenous RNAs in living cells mainly include the RNA binding protein-fluorescent protein system (RBP-FP system), bimolecular fluorescence complementation (BiFC) system, RNA aptamer/fluorophore system, and reporter gene system. The RBP-FP system can be applied in mRNA imaging. RBP refers to MS2 coat protein (MCP) binding to MBs (MS2-binding sequence), and FP refers to GFP. In this imaging system, the targeted mRNA is first pretreated by inserting six units of MBs into the 3′-UTR (untranslated region). Subsequently, the MCP-GFP fusion protein is added to the pretreated system, which helps illuminate the specific mRNAs. The RBP-FP system was first used in living yeast to track the transport and localization of articles . Howeverarticles . In addiarticles . The anaBiFC uses two different RBPs conjugated to two halves of split FPs (RBP1-N-FP and RBP2-C-FP) . MCP-PCPUnlike RBP-FP systems and BiFC systems, RNA aptamer/fluorophore systems enable real-time imaging due to the fast-binding interactions of the aptamer and small molecule fluorophores . There aReporter gene systems are specifically suitable for miRNA imaging . It can β-actin mRNA under stress  labeled with GFP can effectively re-localize and achieve imaging of r stress  , and the co-location of multiple NEAT1 molecules on the fluorescence background shows sufficient S/N  differentiation, which is suitable for screening RNA imaging. The results showed that dPspCas13b and dPguCas13b were the most effective Cas proteins. However, the mentioned dLwaCas13a protein is not available for NEAT1. Previous studies have discovered that the length and mismatch location of gRNA affected the efficiency of RNA cleavage and labeling  protein is excellent at DNA or RNA imaging . FurtherMUC4 and SatIII DNAs, and dPspCas13b-mScarlet successfully labeled MUC4 and SatIII RNAs, realizing simultaneous labeling of genomic DNA and transcriptional RNAs  to bind dCas9, visualizing both the MS2-repeat-tagged mRNA and DNA in real time  could realize dual-color imaging of DNA and RNA . dCas9 snal RNAs . In addieal time .Revealing the interactions of RNA and RBPs offers essential clues for understanding RNA biology. The interactions are complex, and a particular RNA tends to have fixed protein-binding domains with multiple RBPs. Similarly, a particular protein can also work with different RNAs . When thCurrently, there are a variety of methods for identifying RNA and its binding proteins, which can be broadly divided into two categories, protein-centered and RNA-centered . Proteinin vitro and in vivo methods  RNA with specific markers and then add cell extracts and elution proteins and analysis thereafter  binds biotin ligase to BoxB, which helps deliver the system around the targeted RNA through the  labeled . Other a labeled . However labeled . TherefoXist lncRNAs have been identified in mammals and play an important role in gene silencing  as an oxidant to catalyze the one-electron oxidation of biotin-phenol (BP), which helps to pull down the proteins (A new system to study human telomerase RNA (hTR) was developed by Han et al. for the detection of RNA-protein interactions. hTR plays a critical role in regulating cellular senescence as a template for reverse transcription and affects the development of diseases . In theiproteins . Howeverproteins . TherefoTo improve the stability and targeting potential of the imaging system, Han et al. introduced a double-stranded RNA binding domain (dsRBD) , which wBased on the development of the PUP-IT system for detecting membrane protein interactions , Zhang ep21 mRNA and detected hnRNA-bound proteins such as HNRNPK and HNRNPA1, which also indirectly reflected the maturation mechanism of mRNA. The results indicate that the CRUIS system has a wide range of applications and broad potential. However, the efficiency of single sgRNA protein detection is limited and thus greatly affects the detection efficiency. Moreover, the presence of RNA secondary structures also continues to influence the system  tail proximal proteins and can rapidly identify RBPs and uncover novel RBPs such as KPNB1 (U1 with high abundance (as KPNB1 . To redubundance  and desibundance .U6 promoter (U1 snRNA, and RPL7 was verified as a novel U1 binding protein. Meanwhile, the potential of this system for lncRNA was also demonstrated by validating RBM15 as an XIST-binding protein (Recently, promoter . A total protein . However protein .SatIII RNA visualization was achieved only after treatment with heat shock or SA (The precise targeting and editable properties of Cas13 make it an excellent tool for RNA imaging and detection of RNA-protein interactions. However, Cas13-mediated RNA imaging and mapping RNA-protein interactions are still in the exploration stage. Compared with other imaging methods, Cas13-mediated tools provide real-time imaging in living cells with lower background noise, better stability, and better imaging efficiency. Although these Cas13-mediated imaging methods have been optimized, there is still room for further improvements in their performance. Screening of Cas13 proteins is still tedious work, and not all proteins can be used for imaging. One reason could be that some Cas13 proteins cannot produce labeling signals. Furthermore, the design process of gRNAs is very difficult, and not all gRNAs can work well. Even small changes in gRNA position will lead to significant differences in imaging effects. In addition, the existing Cas13 imaging methods are only suitable for high abundance RNA whereas they cannot achieve good imaging effect for RNA with low abundance. Moreover, some cells also need to be processed in advance before imaging. For example, ck or SA . The mecTo date, multiple Cas13-mediated RNA-protein detection tools have been reported and initially evaluated. Cas-mediated methods have many advantages. It is noteworthy that Cas13 does not require pre-labeling of target RNA , design There are several directions for future optimization of the current approaches for Cas13-mediated RNA imaging and detection of RNA-protein interactions. First, a structural design database should be set up, and the design methods of gRNA should be optimized to simplify the design process of gRNA. With the development of deep learning technology, new gRNA efficiency prediction and design tools are expected to be developed. Second, more Cas13 proteins, especially newfound ones, can be screened out to further improve the targeting ability. Third, current linker proteins can be chemically modified so that they have a stronger signal when they bind to their target. Finally, optimizing the observation imaging equipment can also achieve better visualization results.However, there are more difficult problems to address. The space structure of RNA changes may affect the targeted efficiency, such as the existence of the secondary structure, which may affect the gRNA combined with the target RNA . In addi


Among the currently available virus detection assays, those based on the programmable CRISPR-Cas enzymes have the advantage of rapid reporting and high sensitivity without the requirement of thermocyclers. Type III-A CRISPR-Cas system is a multi-component and multipronged immune effector, activated by viral RNA that previously has not been repurposed for disease detection owing in part to the complex enzyme reconstitution process and functionality. Here, we describe the construction and application of a virus detection method, based on an in vivo-reconstituted Type III-A CRISPR-Cas system. This system harnesses both RNA- and transcription-activated dual nucleic acid cleavage activities as well as internal signal amplification that allow virus detection with high sensitivity and at multiple settings. We demonstrate the use of the Type III-A system-based method in detection of SARS-CoV-2 that reached 2000 copies/μl sensitivity in amplification-free and 60 copies/μl sensitivity via isothermal amplification within 30 min and diagnosed SARS-CoV-2-infected patients in both settings. The high sensitivity, flexible reaction conditions, and the small molecular-driven amplification make the Type III-A system a potentially unique nucleic acid detection method with broad applications. CRISPR-Cas based virus detection assays can be both rapid and sensitive. Here the authors use a Type III-A CRISPR-Cas system to detect SARS-CoV-2. Some of these diseases are highly contagious and broadly affect human health. Historically, several outbreaks namely Spanish flu and Swine flu caused by H1N1 influenza virus4, Acquired Immunodeficiency Syndrome (AIDS) caused by Human Immunodeficiency virus (HIV)5, Zika disease caused by the Zika virus6, Ebola Virus Disease (EVD) caused by the Ebola virus7, Severe Acute Respiratory Syndrome (SARS) caused by SARS coronavirus (SARS-CoV) and Middle East Respiratory Syndrome (MERS) caused by MERS coronavirus (MERS-CoV) have wreaked havoc on general population and had widespread economic implications in the world9. The global outbreak of Coronavirus disease 2019 (COVID-19) caused by a novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the most recent and ongoing public health emergency, transmitting from human to human at very high pace across countries12. The recent emergence of genetic variants of COVID-19 across the world has further increased the risk of mortality17. One of the confounding challenges posed by this pandemic and previous infectious diseases has been the availability of rapid testing of the virus, which could limit the spread of the disease.Human infectious diseases constitute a broad class of diseases caused by microorganisms such as bacteria and viruses transmitted via food, air, body fluids, and physical contact19. Antigen-based tests, although effective and rapid, requires prior manufacture of antibodies to be incorporated into the test and usually lack high sensitivity. Serology and other adaptive immune response tests are mature technology but do not distinguish past from active infections. The traditional nucleic acid-based detection, based on Polymerase Chain Reaction (PCR) makes use of nucleic acid amplification methods that has many advantages over antigen-based and serological tests. It is quantitative, highly sensitive and can be made available prior to the onset of a potential pandemic. The recently developed Clustered, Regularly Interspaced, Short Palindromic Repeat (CRISPR) and CRISPR-Associated (Cas) detection methods20 further revolutionized nucleic acid test. The CRISPR-Cas-based detection has shown high sensitivity and accuracy without requiring the thermocycler used in PCR. In addition, the CRISPR-Cas-based detection is inexpensive, mobile, and rapid, making it deployable as point-of-care testing to locations without sophisticated biochemistry equipment. Current CRISPR-Cas based diagnostic technologies employ mainly Cas12 and Cas13 enzymes that possess either viral DNA or RNA-stimulated collateral DNase or RNase activities, respectively20. The Cas13-based methods23 detect the viral RNA by RNA-stimulated cleavage of RNA probes. The Cas12-based methods25, on the other hand, detect the viral DNA by DNA-stimulated cleavage of DNA probes. Since the binding constants of Cas13 and Cas12 for their respective targets are typically higher than the potential viral titers in patient samples26, direct detection by the CRISPR enzymes would not be possible without additional assistance. The use of isothermal amplification27, rapid PCR amplification28, multiplex targeting29, tandem nucleases cleavage30, and autocatalytic looping31 are some of the example strategies employed in CRISPR-based detection.Respiratory virus infections are generally diagnosed by the presence of either virus-derived antigens, patient immune responses, or nucleic acid materials34  complex from an all-in-one expression plasmid in two simple chromatography steps with high yield35. Here, we demonstrate the concept of a Csm-derived virus detection system that we termed MORIARTY for Multipronged, One-pot, target RNA-Induced, Augmentable, Rapid, Test sYstem. We further showed the effectiveness of MORIARTY in rapid detection of SARS-CoV-2 virus with high sensitivity, thereby offering a Class I CRISPR-Cas based viral diagnostic.The Type III-A CRISPR-Cas system, or Csm, is a viral RNA or transcription-activated ribonucleoprotein enzyme system that comprises four enzymatic activities: (1) specific cleavage of the viral transcript by the Csm3 subunit, (2) collateral DNase by the HD domain of the Csm1 subunit, (3) cyclic oligoadenylate (cOA) synthesis by the Csm1 GGDD motif, and (4) cOA-activated collateral RNase by the ancillary enzyme Csm634 Fig. . The dua6, upon binding to its cognate target RNA (CTR) but not noncognate target RNA (NTR) or self RNA  and the RNA reporter flanked by the Fluorescein (FAM) fluorophore-quencher (hereafter referred to as RNA-FAM) with absorption/emission wavelength of 570/630 nm and 480/530 nm respectively . The choice of the targeting region within the S gene was made such as to ensure that the 3′-protospacer flanking sequence (3′-PFS) of the viral target RNA would remain non-complementary to the 5′-tag of the LlCsm crRNA39 to mimic that for CTR  or an in vitro transcribed S mRNA (hereafter S_IVT_RNA)   and nucleotides 25061–25089 (LlCsm_S8), respectively  followed by double stranded DNA synthesis from a T7 promoter-containing primer and a downstream primer via three recombinase-polymerase amplification (RPA) enzymes: a recombinase, single-stranded DNA-binding protein and strand-displacing polymerase44 e44 Fig. . We took0_D30A/LlCsm6 with T7 promoter-containing DNA that encodes S0_CTR   and in presence of both RNA-FAM and DNA-FAM had a noticeable benefit when the target DNA concentration was low  with known viral titers . Initial experiments suggested that dilutions constituting to ~100 copies/μL could be reliably detected by MORIARTY when RNA-FAM was at 1.5 μM . However, Cas12 is able to distinguish single-base variants49. Finally, unlike Cas13 or Cas12 where activator cleavage is required for their respective collateral activities26, Csm uses separate active sites for the activator cleavage and, therefore, the collateral activities do not depend on cleavage of the target RNA.We have constructed and demonstrated the effectiveness of a Type III-A CRISPR-Cas system for virus detection employing both amplification-free and RT-RPA based strategies. Similar to other CRISPR-Cas-based virus detection methods, MORIARTY-based detection is a highly sensitive system and has advantage over those based on qPCR without the requirement for thermocyclers2+-only condition that primarily reports the RNA-induced cOA6 synthesis activity without the need for the DNA-FAM fluorescence reporter. The Mg2+ ion facilitates cOA6 synthesis that then drives the Csm6 RNase activity. This detection strategy differs from the previously developed tandem nuclease strategy where cleavage of linear oligonucleotides by Cas13 activate the Csm6 RNase activity30. The Mg2+ ion was also helpful in multiplex detection likely due to its additional roles in stabilizing viral RNA structures. A combination of Mg2+ and Mn2+, on the other hand, was found to be optimal for the RT-RPA MORIARTY where both cOA6 synthesis and DNase activities were used in reporting the presence of a cognate target. The choice of Mg2+ and Mn2+ or other possible metal ions, however, may depend on the range of target RNA to be detected and other enzymatic processes present in the detection reaction.We found that amplification-free detection of target RNA at low concentrations benefited from a Mg6. However, the amount of ATP used depends on which metal ion is present in the reaction. For the Mg2+ conditions, a range of 1–2 mM could be used while for the Mn2+ conditions, 0.03–0.06 mM was used. Interesting, signal contrast falls off when ATP increases beyond these ranges. Multiple explanations for this phenomenon are possible that include a negative impact of ATP on the DNase activity or inhibition of fluorescence probe binding by ATP.ATP in general increases sensitivity because it increases the availability of cOA2+ and high ATP concentration and were able to directly detect in vitro transcribed SARS-CoV-2 S mRNA at ~5 fM with LlCsm targeting a single site. This sensitivity is comparable with or better than the previously reported sensitivities of 10 fM (~6000 copies/μL) by LbuCas13a50 and 50 fM (~30000 copies/μL) by LwCas13a21 in amplification-free settings but is insufficient to detect viruses present in nasal swab, serum or urine samples that are in the sub-attomolar range. We thus applied a multiplexing detection strategy against S gene mRNA that reached ~2000 copies/μL detection sensitivity with the SARS-CoV-2 RNA and can identify infected patients with high viral titers within 30 min . A similar but more extensive multiplexing detection strategy with Cas13 reached the remarkable sensitivity of sub-attomolar with amplification-free detection51, indicating the possibility for MORIARTY to achieve the same sensitivity when targeting sites are further expanded.We explored amplification-free detection with MORIARTY under a condition containing Mg52.We took advantage of the enzymatic property of Csm in its activation by RNA transcription by constructing a one-pot RT-RPA-coupled detection of viral RNA. This convenient procedure reached high sensitivity with either model SARS-CoV-2 virus or human patient samples. Strikingly, MORIARTY-based assay results show a consistent detection sensitivity to those by q-RT-PCR and seems to have a larger dynamic range than q-RT-PCR in detecting viral RNA. Noteworthy, the temperature range requirement of 37 °C to 42 °C for all the steps in T7-MORIARTY-based detection eliminates the requirement of expensive equipment and makes it potentially compatible with the low-cost hand warmer-mediated heating solution as demonstrated previouslyThe Csm-derived MORIARTY is thus a versatile virus detection method with high sensitivity.Given that the genomes of infectious pathogens are made up of either DNA or RNA, multipronged diagnostic tools such as MORIARTY can be employed towards the detection of multiple nucleic acid targets. With the availability of many known Type III-A CRISPR-Cas systems and their individual biochemical differences, MORIARTY offers a broad range of nucleic acid detections under a wide range of conditions.Lactococcus lactis Csm (LlCsm) effector module plasmid encoding Cas6, Csm1-6, and CRISPR locus was as described previously53. The desired mutations including Csm1 H13A/D14N, Csm3 D30A, and Csm6 R355A were introduced by Q5 mutagenesis (New England Biolabs). To make it convenient for incorporating guide RNA, the guide region was incorporated with two BbsI sites54. The plasmids encoding LlCsm-S0 effector complex targeting the S gene of SARS-CoV-2 with 29mer gene-complementarity to nucleotides 22280–22308, LlCsm_S7 targeting nucleotides 24702–24730, and LlCsm_S8 targeting nucleotides 25061–25089 of NCBI MT801051.1 were constructed but either Q5 mutagenesis or through BbsI cloning. All three effectors also harbor the Csm1 H13A and Csm3 D30A mutations. All clones were verified using sequencing primers (Eurofins Genomics).The pACYC 35. Briefly, The all-in-one pACYC plasmid  stain (New England BioLab) and the cells were grown to log phase before induction by addition of 0.3 mM isopropyl β-D-1 thiogalactopyranoside (IPTG). The N-terminal His6-tag on LlCsm2 enabled isolation of LlCsm RNP using Ni-NTA affinity chromatography. The Ni-NTA elution pools were loaded on to a size-exclusion column equilibrated with the storage buffer that contains 20 mM HEPES pH 7.5, 200 mM NaCl, 5 mM MgCl2, 14 mM 2-mercaptoethanol. Each LlCsm complex was concentrated to ~55 μM and stored at −80 °C. As LlCsm6 is not a component of the effector complex, it was produced separately from the pLlCsm6 plasmid , 5 mM NTPs, and 480 μg/mL T7 RNA polymerase. The transcription reaction was incubated at 37 °C for 3 h and treated with 2 units of Turbo DNase (Invitrogen). The RNA transcript was purified using Monarch RNA Cleanup kit (New England Biolabs), eluted in water, aliquoted, flash frozen using liquid nitrogen and stored at −80 °C.The plasmid encoding for the SARS-CoV-2 surface glycoprotein (Spike protein), pGBW-m4046887 (Addgene), was amplified in DH5α cell and subjected to plasmid DNA extraction. The extracted plasmid DNA digested by BamH1 (New England Biolabs) overnight and verified by gel analysis. To produce S mRNA, 1 μg of the linearized DNA was used as the template for in vitro transcription in a reaction containing 1x transcription buffer  at 37 °C. For multiplexing experiments, 250 nM of each LlCsm RNP was included and the final buffer contained 0.1x TAPA, 10 mM MgCl2, and 2 µM RNA-FAM. When the target RNA was either SARS-CoV-2 control or nasal swab extracted patient samples, 12.5 μL RNA at the specified concentrations was added to the 12.5 µL master mix.For two-channel fluorescence experiments, a short 8-nt DNA-oligo and a short 5-nt RNA-oligo were designed such that the DNA-oligo was covalently linked to 5′ Alexa Fluor 594 (NHS Ester) fluorescent dye and 3′ Iowa Black RQ quencher (DNA-Alexa) while the RNA-oligo was covalently linked to 5′ 6-FAM (Fluorescein) fluorescent dye and 3′ Iowa Black FQ quencher (RNA-FAM) (Supplementary Table 2) containing 2 μM DNA-FAM, 2 μM RNA-FAM, 250 nM LlCsm effector complex, 250 nM LlCsm6, 10 mM MgCl2, 0.5 mM MnCl2, 0.5 mM rNTPs, 10 mM TCEP, 60 μg/mL T7 RNA polymerase, and 0–5 nM target DNA (or 12.5 μL of RT-RPAed product) at 37 °C. The fluorescence was measured on Spectramax iD5 multi-mode microplate reader (Molecular Devices) using 480 nm/530 nm excitation/emission wavelength at 5 min intervals. The reactions were performed in triplicates and averaged for the final plots (GraphPad Prism). The reaction products were transferred to 0.2 mL PCR tubes and imaged against Fluorescein wavelength using Chemidoc imaging system (BioRad).The T7-MORIARTY methodology was designed to track LlCsm co-transcriptional activation of template viral DNA obtained either from synthetic DNA (Supplementary Table The RT-RPA was performed using TwistAmp Basic kit following manufacturer’s instructions (TwistDx). For each lyophilized pellet provided by the kit, a 50 μL reaction mix containing 29.5 μL of rehydration buffer (TwistAmp Basic kit), 0.5 μM each of forward and reverse primers (Eurofins Genomics) and 100 U Protoscript reverse transcriptase (NEB) was prepared. The master-mix was added to the RPA tube on ice to resuspend the pellet. After the pellet is dissolved completely, 5 μL RNA samples extracted from patient nasopharyngeal swab (Zymo Research) using QIAamp viral mini kit (Qiagen) was added. To initiate the RT-RPA reaction, 14 mM Magnesium Acetate (provided with the kit) was added and the reactions were incubated for 30 min at 42 °C with intermittent mixing every 10 min. After the reaction was complete, the RT-RPA product was transferred to ice until T7-MORIARTY detection assay was ready.To quantify copy numbers of in vitro transcribed S gene mRNA (S_IVT_RNA), we performed a 2-step laboratory-based assay in ABI 7500 Fast Real-Time PCR System. Briefly, cDNA was synthesized using SuperScript III First-Strand cDNA kit (Invitrogen) followed by DNA amplification using PerfeCTa SYBR Green FastMix (Quantabio) and S gene specific RPA primers (Supplementary Table t) values of less than 35 are reported as “positive” for that measurand, while a Ct of <35.00, or “No Ct” is reported as “negative.”To detect patient samples via RT-PCR, we performed the assay consistent with the FDA EUA “OSCEOLA SARS-CoV-2 Real-time Reverse Transcriptase (RT)-PCR Diagnostic Assay.” Briefly, 5 μL RNA samples extracted from patient nasopharyngeal swab (Zymo Research) using QIAamp viral mini kit (Qiagen) was used in each of four independent qPCR reactions using the CDC primer-probe sets for human RNase P, chr10:90872001-90872065 (hg38), SARS-CoV-2 Nucleocapsid target 1, 2787-28332 (NC_045512), SARS-CoV-2 Nucleocapsid target 2 29164-29210 (NC_045512), and the WHO primer-probe sets for human SARS-CoV-2 Envelope, 26294-26357 (NC_045512), (Supplementary Table Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


In addition, the RNA assemblies herein were further characterizedby means of the “atoms in molecules” (AIM) and noncovalentinteractions plot (NCIplot) methodologies. We believe the resultsderived from this study might be important in the fields of chemicalbiology (RNA folding and engineering) and supramolecular chemistry(anion−π interactions) as well as to further expand thecurrent knowledge regarding RNA structural motifs.In this study, wedemonstrate that anion−π interactions are involved in the stabilization of GAAA and GGAG RNAtetraloops. Using the single recognition particle (SRP)–RNAcomplexes as a case of study, we combined molecular dynamics (MD)and quantum mechanics (QM) calculations to shed light on the structuralinfluence of phosphate–G anion−π interactionsand hydrogen bonds (HBs) involving K In this regard, one ofthe key structural descriptors of the U-turn proposed by d’Ascenzoet al. was the formation of an oxygen−π or phosphate−πstacking contact between the first nucleobase of the loop and an OPatom from the third nucleotide.21 Thisintramolecular contact between the phosphate group and G has beenwell described and characterized in the field of supramolecular chemistryas an anion−π interaction .22 While anion−π interactions havebeen contextualized in many chemistry-related fields of research25 , as wellas in biology28 (protein–ligand interactions and enzyme chemistry),few studies have analyzed their implications in RNA folding motifsto date.31Unveiling and understandingthe driving forces lying beneath RNAfolding and recognition is of crucial importance to biology. The RNAfunctionality is intimately related to its ability to assemble intocomplex three-dimensional architectures, thus forming specific sitesimplicated in molecular recognition and catalysis phenomena.32 thus playing a crucialrole in cell communication processes in both eukaryote and prokaryoteorganisms. Among the three systems studied, two of them (structures 1HQ1 and 1DUL) are part of theribonucleoprotein core of E. coli and exhibit a GAAAtetraloop. The third one (structure 1JID) is present in Homo sapiens and shows a less common GGAG folding motif –RNAcomplexes as a case study . SRP–RNA complexes are presentin all three kingdoms of life and are involved in the recognitionand transport of specific proteins to cellular membranes for insertionor secretion,E. coli) or SRP54 protein (H. sapiens) bound to the minor groove of domain IV of 4.5SRNA protein (E. coli) or 7S RNA (H. sapiens). This core region is the most conserved part of SRP across thethree kingdoms of life. In fact, human SRP is functional even if itsRNA is replaced by that of E. coli. SRP will identifya signal peptide sequence emerging from ribosomes early in the translationprocess. If identified, SRP will bind to that ribosome and stop thetranslation process while transporting the whole ribosome to specificreceptors on the endoplasmic reticulum (eukaryotes) or cytoplasmicmembrane (prokaryotes) where translation will resume. The M domaincontains the recognition site for both the RNA and the peptide. Asnoticed in Theribonucleoprotein core, which we model, consists of the M domainof Ffh protein  the structural effects upon mutation of G. On the otherhand, QM calculations shed light on the strength and directionalityof anion−π and K+/Mg2+ water clusterhydrogen bonds (HBs). Finally, Bader’s theory of “atomsin molecules” (AIM) and NCIplot analyses further characterized the interactions studied herein froma charge-density perspective. As far as our knowledge extends, thisreport represents the first computational study of anion−πinteractions in RNA tetraloop folding motifs. Hence, the results derivedfrom this study might be useful for both chemical biologists (RNAfolding and engineering) and supramolecular chemists, as well as toincrease the visibility of the anion−π interaction amongthe RNA community.Our approach combinesclassical molecular dynamics (MD) simulationswith quantum mechanics (QM) calculations at the RI-MP2/def2-TZVPDlevel of theory. More precisely, explicit solvent MD simulations ofboth the isolated and protein bound RNA structure were carried outto understand (i) the influence of the phosphate···Ganion−π interaction on the tetraloop structure, (ii)the stabilizing role of K36 Recognition by proteins and RNA is believed to follow a shape complementaritymechanism in which the tetraloop plays an important role. The recognitionis facilitated by the accessibility of the Watson and Crick hydrogen-bondingpatterns in three of the bases in the tetraloop as well as by a determinedbackbone conformation.34 In recent years,the AMBER family of RNA force fields has seen significant changesto overcome known limitations for the modeling of RNA systems.39 While current force fields are not always able to fold all tetraloopscorrectly,37 they can correctly stabilizethe native conformation. Triplicate sets of simulations starting fromthe experimental structure , as well as thelocal details of the backbone  and side chain  tetraloop region. For 1HQ1 and 1DUL, the protein is bound far from the tetraloop region, whereas for 1J1D, the protein bindingregion encompasses the tetraloop . Correlations between angle and distances showed that shorter distancescorrelate with a 90° angle between the π-system of G andthe phosphate group, as expected from a canonical anion−πinteraction .The combination of forcefields and molecular dynamics has often been used to describe noncanonicalDNA and RNA structures for which the force fields were not initiallyparametrized. The success in representing those systems is a testamentto the transferability of such potentials. Tetraloop motifs are ubiquitousin RNA structure as a building block during RNA folding and hairpinformation. They are also highly functional, involved in translationprocesses and have been proposed to mediate long-range RNA–RNAinteractions.ture see 2 retaineture see S1, top, loop see  distanceture see S1, top, SI Figures S1 and S2) for thelength of the trajectory with an overall similar RMSD to the initialsimulations. However, RNA nucleotide fluctuations increased , especially in regions where the proteinwas previously bound. This is to be expected, reflecting the higherentropic freedom and flexibility of the free RNA . The RMSF of the tetraloop in 1J1D remained stabledespite the absence of the protein and the RMSF increased to similarranges as in the other two systems . The angle and distance distributions in the absenceof the protein also behaved the same as when the protein was present.The presence of the protein in the tetraloop regiondid not influencethe RNA loop conformational preferences in 1JID with respect to the other two systems.We further tested the effect of simulating all three RNA systems inthe absence of their binding partners. All three systems remainedstable , the structure of the tetraloopis significantly affected by this mutation . While fluctuations in the backbone RMSDare small in magnitude, they represent distinct states, correlatedwith the larger changes in the side chain RMSD. Transitions happenbeyond the 100 ns time scale, with some replicates being stable forthe duration of the simulation (500 ns). However, once a transitionhappens, they are irreversible in the simulated time scales, compatiblewith more energetically favorable metastable states. To further quantifythis effect, we have calculated the backbone torsional preferences and entropy  of different dihedral parameters dictating backbone andside chain conformations. The analysis shows the greater conformationalspace available to the mutants (1DUL and 1HQ1) consistent with losing the tetraloopstructure . For the 1JID case, the presenceof the protein in the active site narrows down the conformationalspace, resulting in similar entropies before and after the mutation.Interestingly, for 1HQ1 we observe a large entropy increase for all bases in the tetraloop,while for 1DUL, only the two central bases have a significant behavior change.In all cases, the anion−π interaction is no longer presentand the distance and angle distribution mapping the oxygen to thecytosine ring presents a very different distribution than the canonicalcase for 1DUL and 1HQ1 . For these two systems,finding the anion near the ring is a low probability event, with thephosphate having a greater propensity to interact with the solventenvironment than with the base. The case of 1J1D tells a differentstory: the presence of the protein forces the anion and π-ringto remain in close proximity. The interaction is stabilized by hydrogenbonds from Cys43, Arg60, and Arg127, which directly interact withboth anion−π partners. In addition, the longer tail inthe distance and angle distributions is reminiscent of 1HQ1 and 1DUL systems, and onlythe presence of the protein stops the tetraloop from following thesame behavior. As a final analysis, we looked at the effect of themutation in the conservation of protein–RNA contacts . We notice that in 1HQ1 and 1DUL, where the proteinbinds far from the tetraloop region, the number of contacts fluctuatesaround the same values in the wild-type and mutant. For the case of 1JID, the mutation leadsto a steady reduction of native contacts over the first 100 ns ofsimulation, most of which are not re-established in the simulationtime. Taken together, the G to C mutation provokes a large backboneand side chain rearrangement in the current systems, which will likelyaffect shape recognition by proteins and long-range RNA interactions.Further tests on other tetraloops will reveal if this is a more generalizableproperty.We furthertested the ability of a guanine to cytosine mutationin the tetraloop region to disrupt the anion−π interactionin all three systems. We simulated all three systems with their proteinbinding partners in place. Although the overall RNA structure is maintained. Each value gatheredin Supporting Information) werealso performed for comparison purposes. From the inspection of theresults several interesting conclusions can be extracted.With the purpose tounderstand the energetics and directionality of the anion−πinteraction, a series of MD snapshots were selected for QM calculations, ranging between −0.3 and −4.3kcal/mol. Second, geometries tagged as “close” exhibitlarger anion−π interaction energy values than their “far”analogous, as expected. Third, both the energetics and equilibriumdistance of the anion−π interaction exhibit good agreementbetween the selected snapshots and the X-ray structures, thus indicatingthat the force field effectively samples conformations fluctuatingaround the initial X-ray crystal structure. This is observed in (i) 1JID structure, whichachieved interaction energy values above  and below  those obtainedfor the X-ray structure, and (ii) 1HQ1, where the “close” conformation obtained a similar value comparedto the experimental structure . Finally, in 1DUL a more discrepantpicture between the force field and the X-ray structure was obtained.While comparing both “close” and“far”dispositions an interesting picture is revealed. That is, in the “close”conformation of 1HQ1 and 1DUL structures,the anion−π interaction is slightly reinforced withoutthe presence of the protein . This is contrary to whatis observed in case of 1JID, where the presence of the protein bound to RNA resultsin a strengthening of the anion−π interaction, in agreementwith the results obtained from the MD simulations . On the otherhand, in all “far” geometries, the anion−πinteraction is further stabilized when the protein is bound to theRNA molecule .E = −3.4 and −2.4 kcal/mol, respectively)compared to their protein-complexed analogous .The opposite behavior was obtained for 1JID complex . Finally, the anion−πinteraction angles range between 77.7° and 95°, thus exhibitinga certain directionally, being close to an ideal anion−πinteraction (90°), as was also indicated in the MD study.Moreover, in the case of 1HQ1-NP and1DUL-NP systems, we observeda more pronounced strengthening of the anion−π upon goingfrom “far” to “close” conformations (ΔΔSupporting Information for more details), and the results are gathered in We finally optimized (BP86-D3/def2-SVP) and evaluated energetically(single points at RI-MP2/def2-TZVPD level of theory) a set of anion−πcomplexes corresponding to 1JID structure in order to analyze the quality of the structuresgathered directly from the MD trajectory. To preserve the existenceof the anion−π interaction, a set of distance and dihedralrestraints was used . The results are gathered in We have also expandedour study to additional loop interactions between the A and G basesfor 1HQ1 and 1JID structures 4. ConcreIn the casewhen the protein is bound to RNA, the 1HQ1-stacking-1interaction achieved a larger interaction energy value than 1HQ1-stacking-2complex, while in 1JID structure both stacking interactions achieved a similar strength.Additionally, for both systems the base stacking interactions showedmore favorable interaction energy values than the N–H···Nhydrogen bonds . On the other hand, adifferent picture is observed upon removal of the protein, that is,complexes named as stacking-2 achieved a stronger interaction energythan their stacking-1 analogues, in agreement with a shorter base–basedistances. Finally, the N–H···N hydrogen bondinteraction is reinforced upon removal of the protein for both systems, owing to a decrease in theintermolecular N–H···N distance.ESI for more details) from the whole trajectory, thus being useful tofurther characterize both the anion−π interaction andthe interactions between the RNA tetraloop and the K+ andMg2+ water clusters. In both analyses, the two tetraloopmiddle bases (A155–A156 in case of 1HQ1 and G155–A156 in case of 1JID) have been omittedfor clarity purposes .To further complement theresults derived from the energetic study, in 2+ water cluster is denotedby (i) the presence of two BCPs connecting an O atom from the phosphatemoiety and an O from the carbonyl group of G to the Mg2+ ion, (ii) the presence of two BCPs connecting a Mg2+ coordinatedwater molecule and two phosphate O atoms (strong HBs) and (iii) aBCP connecting a −CH group from the RNA backbone with an Oatom from a Mg2+ coordinated water (moderate HB).As noted, in the case of 1HQ1-NP 5A, two b2+ water cluster, whichparticularly involve (i) two O atoms from the phosphate moiety, (ii)the N1 atom from G, and (iii) a phosphate backbone group from RNA.QM calculations of these HBs resulted in an average interaction energyvalue of −52.8 kcal/mol per HB. This value is noticeably strongowing to the charged nature of both HB donor and acceptor partners.Other intramolecular interactions within the RNA assembly common toboth systems mainly encompass HBs involving (i) two sugar moieties,(ii) G154-NH2 and A157-N7, and (iii) phosphate and N1 fromG154.On the other hand, once the protein is bound to the RNA 1HQ1 in 5B, only 2+ ion, in a similar fashion to 1HQ1-NP. Finally, a BCP characterizesa strong HB established between a Mg2+ coordinated watermolecule and an O atom from the phosphate group.In 2 group from its guanidinium moiety with the carbonyl groupof G and a −CH group from the RNA backbone, respectively, thereforecharacterizing the presence of two ancillary HBs. The computed strengthof the HBs established between Arg127 and the RNA loop resulted in−56.5 kcal/mol per HB. Other intramolecular interactions withinthe RNA assembly common to 1JID-NP and 1JID systems mainly involveHBs involving (i) two sugar moieties, (ii) G154-NH2 andG157-N7, and (iii) phosphate and N1 from G154.In the caseof the protein–RNA complex 6B, an Ar2+ water clusters  and Arg127 residue (1JID)are denoted by blue isosurfaces between both HB counterparts (involving−OH and −NH groups as donors and O and N atoms as acceptors).Lastly, in case of 1JID structure, the ancillary HBs are characterizedby a greenish surface, indicating a weaker nature than those involvingcharged counterparts.Finally, theNCIplot analyses of all four tetraloop structureswere computed, owing to their usefulness to analyze noncovalent interactionsaccurately and unveil their location in real space. As noticed in + and Mg2+ ionsdid not show remarkable residence times in either isolated or complexedRNA systems near the tetraloop region. Furthermore, mutation of theG base resulted in total disruption of both the HB base pair structureand the phosphate···G anion−π interaction.On the other hand, QM analyses (RI-MP2/def2-TZVPD level of theory)of selected MD snapshots revealed that anion−π interactionstrength ranges between −0.3 and −4.3 kcal/mol and theinteraction is directional in these systems. The energetic study wasalso extended to the additional noncovalent interactions present inthe RNA tetraloop structure (π–π stacking and HB).Finally, the RNA tetraloops were further characterized by means ofAIM and NCIplot analyses, being useful for characterizing the noncovalentpartners involved in formation of the RNA assemblies as well as theintermolecular interactions with K+/Mg2+ waterclusters and vicinal protein residues. We hope the findings gatheredin this work will be useful for scientists working in the fields ofRNA folding and engineering, as well as to increase the visibilityof anion−π interactions among the protein–RNAcommunity.In conclusion, we haveevaluated the structural and energetic implicationsof phosphate···G anion−π interactionsin GAAA and GGAG RNA tetraloops through a combined MD and QM study.Using as a case study three SRP–RNA complexes, MD simulationsindicate that these tetraloops are highly stable, even in the absenceof the protein bound to RNA. KA preliminaryPDB surveywas carried out for SRP-RNA complexes. As a result, 23 structureswere found: 2PXQ, 2PXP, 2PXL, 2PXK, 2PXV, 2PXU, 2PXT, 2PXF, 2PXE, 2PXD, 2PXB, 1HQ1, 1MFQ, 1QZW, 1L9A, 1LNG, 1JID, 1DUL, 3UCZ, 3UD3, 3UD4, 3UCU, and 3NDB. From these, threesystems  were selected forMD simulations owing to the high quality of the X-ray crystal structures(below 2 Å resolution).40 We modeled unresolved residues in the protein for 1DUL and 1HQ1 using SwissModel,using 1HQ1 asa template for both.41 From each modeledPDB file, three systems were created : (1) proteinand RNA with its wild-type sequence; (2) protein and RNA with a guanineto cytosine mutation at position 25 for 1DUL and 1HQ1 and at position 13 for 1JID; (3) RNA-only withthe wild-type sequence.Initialstructures wereretrieved from the Protein Data Bank using PDB codes 1DUL, 1HQ1, and 1JID.42 while RNA was defined usingthe OL3 force field.44 The system was solvated in acubic box using the TIP3P water model with a minimum 12 Å clearancebetween the edge of the macromolecules and any side of the box.45 Crystallographic waters and ions were retained.K+ and Cl– ions46 were added to neutralize the system and reach a 150 mM concentrationsimilar to physiological conditions. K+ and Mg2+ ions present in the experimental structure were included in thesimulations.47 All systems were minimizedin five stages with decreasing restraint weights of 25, 20, 15, 10,and 5 kcal/mol on heavy atoms. Each minimization stage comprised 1000steps using the steepest descent algorithm48 followed by 1000 steps using the conjugate gradient algorithm.49 The systems were then gradually heated to 298.15K using the Langevin thermostat over 50 ps and then equilibrated underNVT conditions for 950 ps with a time step of 2 fs and a collisionfrequency of 2.0 ps. We use SHAKE to constrain bonds involving hydrogenatoms.50 The systems were then subjectedto 2 ns of equilibration under NPT conditions to stabilize the pressureusing the Berendsen barostat with a relaxation time of 1.0 ps.51 The final production run was carried out usingthe GPU-enabled version of pmemd52 for500 ns using the leapfrog integrator. Each simulation protocol wascarried out in triplicate for each system. A 10 Å cutoff wasused to approximate long-range electrostatic interactions using theparticle mesh Ewald method.53 The first50 ns of each simulation were disregarded as equilibration for analysispurposes unless otherwise specified. CPPTRAJ, MDTRAJ, VMD, and UCSFChimeraX were employed for analysis and visualization.57Proteins were treated with the ff19SBforce field,We monitored the anion−π interaction by lookingatthe distance between the oxygen in the phosphate facing the firstguanine in the tetraloop and the center of mass of the heavy atomsin the 6 membered ring of guanine. We further looked at the orientationby using the angle defined by adding the C4 heavy atom on the ringto the atoms used in the distance calculation. Based on these distributions,we selected five structures close to the average value as well asrepresentative cases of the extremes in the distribution. Finally,we analyzed high residency waters and ions by using VMD’s volumetricmap tool, which analyzes the whole trajectory for the presence ofions or waters at each grid point. The program then calculates thedensity at each grid point and saves the results as a grid file tobe used in data visualization.p log p). We use 10° angle intervals for binning and adda plus one count on all bin to avoid log(0) issues in regions of dihedralspace with no population.We characterizebackbone torsiondifferences in the tetraloop region by using a simplified dimensionlessmeasure of entropy  surfacesand wave function analysis have been carried out using Gaussian 16software.63 The Bader’s “atomsin molecules” theory has been used to study the interactionsdiscussed herein by means of the AIMall calculation package.64 The wave function analysis has been performedat the B3LYP/def2-TZVP level of theory. The NCIplot65 isosurfaces correspond to both favorable and unfavorableinteractions, as differentiated by the sign of the second densityHessian eigenvalue and defined by the isosurface color. The colorscheme is a red–yellow–green–blue scale withred for repulsive (ρcut+) and blue for attractive (ρcut–) NCIinteraction density. Yellow and green surfaces correspond to weakrepulsive and weak attractive interactions, respectively.The energies of allcomplexes included in this study were computed at the RI-MP2


In recent years, much progress has been made in elucidating the functional roles of plant glycine-rich RNA-binding proteins (GR-RBPs) during development and stress responses. Canonical GR-RBPs contain an RNA recognition motif (RRM) or a cold-shock domain (CSD) at the N-terminus and a glycine-rich domain at the C-terminus, which have been associated with several different RNA processes, such as alternative splicing, mRNA export and RNA editing. However, many aspects of GR-RBP function, the targeting of their RNAs, interacting proteins and the consequences of the RNA target process are not well understood. Here, we discuss recent findings in the field, newly defined roles for GR-RBPs and the actions of GR-RBPs on target RNA metabolism. An increasing occurrence of extreme weather events , together with dire projections regarding climate change, makes the improvement of crop resilience to environmental and pathogen stress of paramount importance for feeding a growing global population . To thisArabidopsis thaliana, tobacco (Nicotiana tabacum), rice (Oryza sativa), maize (Zea mays), sweet potato (Ipomoea batatas), Camelina sativa and others . I. IA. thaRBPs are chaperones that bind RNA via one or multiple RRM domains, thereby changing the function or fate of the RNA targets. Here, we provide examples of the involvement of GR-RBPs in plant RNA metabolism, which collectively underscore the complexity of in vivo RNA-mediated processes .A. thaliana by binding to the target pre-mRNA and generating an intron-terminating alternatively spliced transcript, which is unstable and degraded through the nonsense-mediated decay pathway ..A. thali2a cells [pancreas-associated transcription factor 1a (Ptf1a) mRNA, regulating the accumulation of the encoded Ptf1a protein to maintain pancreas development [GR-RBPs are involved in a range of abiotic and biotic stress responses, including cold adaptation and responses to pathogens. Czolpinska et al. (2018) demonstrated that GRPs play important roles in responses to diverse stress conditions . In this2a cells . RNA-binelopment . Among telopment . These celopment . Liquid–elopment . The stuelopment . Xie et elopment . Furtherelopment . Therefo


Ribonuclease P (RNase P) is an important ribonucleoprotein (RNP), responsible for the maturation of the 5′ end of precursor tRNAs (pre-tRNAs). In all organisms, the cleavage activity of a single phosphodiester bond adjacent to the first nucleotide of the acceptor stem is indispensable for cell viability and lies within an essential catalytic RNA subunit. Although RNase P is a ribozyme, its kinetic efficiency in vivo, as well as its structural variability and complexity throughout evolution, requires the presence of one protein subunit in bacteria to several protein partners in archaea and eukaryotes. Moreover, the existence of protein-only RNase P (PRORP) enzymes in several organisms and organelles suggests a more complex evolutionary timeline than previously thought. Recent detailed structures of bacterial, archaeal, human and mitochondrial RNase P complexes suggest that, although apparently dissimilar enzymes, they all recognize pre-tRNAs through conserved interactions. Interestingly, individual protein subunits of the human nuclear and mitochondrial holoenzymes have additional functions and contribute to a dynamic network of elaborate interactions and cellular processes. Herein, we summarize the role of each RNase P subunit with a focus on the human nuclear RNP and its putative role in flawless gene expression in light of recent structural studies. E. coli, as a complex of one protein subunit  and an RNA subunit . Surprisingly, the RNA subunit was found to perform standalone catalysis in vitro, paving the way for the discovery of ribozymes and the contemporary RNA biology . Th. Th20]. RPP14 gene is mapped to chromosome 3p14.3, and the protein is produced by a bi-cistronic transcript, which also produces the HTD2 protein (hydroxyacyl-thioester dehydratase type 2) from a downstream open reading frame. hRpp14 is localized in nucleoplasm and also in the dense fibrillar component of nucleoli .RPP38 gene is mapped to chromosome 10p13. Similar to Rpp29, Rpp38 is localized in the nucleolus but also in Cajal bodies [RPPH1 RNA through recognition of the K-turn (kink-turn) of the S domain [The human l bodies . The strS domain . InteresS domain . RecentlS domain . In addiS domain ,78,79. TRPP40, which maps to locus chr6p25.1. It is considered a newly acquired protein, based on the absence of a Rpp40 homologue from archaeal and yeast holoenzymes 2 tetramer, making contacts with Pop5 and one Rpp30 protein subunit. On the other hand, Rpp40 is connected to the “wrist” module through the interactions between Rpp29 and the other Rpp30 molecule [hRpp40 is encoded by oenzymes . The locRPPH1 RNA via extensive interactions with the C domain, essentially embracing the C domain from one side as well as with the heterodimer Rpp20–Rpp25 [POP1 gene is essential for viability. Mutations can cause defects in pre-rRNA and pre-tRNA processing [POP1 gene exhibited anauxetic dysplasia 2 (ANXD2), characterized by extremely short stature [Pop1 is the largest protein subunit of the human RNase P holoenzyme, and its gene is mapped to chromosome 8q22.2. Immunofluorescence experiments showed that hPop1 is localized in the nucleolus and nucleoplasm . The Pop20–Rpp25 . In yeasocessing . Moreoveocessing ,83. hPopocessing . Interesocessing . Finally stature .RMRP (RNA component of RNase MRP) confirmed their heterodimerization and binding to the P3 domain [RPPH1 or RMRP [RMRP abolishes Pop6 binding and leads to reduced survival. In contrast, deletion or mutations at the end of the P3 domain that is recognized by Pop7 does not cause any noticeable defect [As mentioned before, Rpp20 and Rpp25 proteins belong to the Alba-like superfamily, a group of multifunctional proteins participating in various processes, such as RNA stability and metabolism, genome organization, and transcriptional and translational regulation . Rpp20 a3 domain . A simil or RMRP . Althoug or RMRP ,89. The e defect ,91,92.Drosophila, do not encode a distinct and recognizable gene that is dedicated to the production of the RNase P RNA subunit (RPR). Surprisingly, the RNA component of RNase P in these species is produced as part of intron 2 during the transcription of the ATPsynC gene. As the intron is transcribed, the RNase P subunits Pop1, Pop4 (homologue of hRpp29), Rpp25 and Rpp20 bind to the RPR and protect it from exonucleolytic activity of the Rat1/Xrn2 exonuclease and the nuclear RNA exosome. The knockdown of each of these protein subunits causes decreased abundance of RPR. On the other hand, knocking down Pop5, Rpp14, Rpp21 or Rpp30 does not significantly affect the expression levels of RPR. The role of the Rpp20–Rpp25–Pop1–Pop4 subcomplex in the production of RPR is essential and highlights the importance of protein subunit interactions for the assembly of the RNase P holoenzyme, which is coupled to RPR transcription [Arthropods, such as cription .RPPH1 RNA under specific conditions  [RPPH1 and that Rpp29 represents the bridge between the C and the S domains [in vitro, suggesting that Rpp29 can provide the necessary environment for pre-tRNA binding, recognition and catalysis [RPPH1 RNA subunit, implying that possible interactions with the PARP family cannot be excluded.The addition of hRpp21 and hRpp29 during in vitro reconstitution assays can support RNase P activity in the presence of tral pH) . The samtral pH) . Based o domains . In addiatalysis ,95. Furtatalysis . In addiatalysis . More spatalysis . Interes1A9 and m1G9 methyl group modifications, and MRPP2 is a mitochondrial dehydrogenase involved in fatty acid, branched-chain amino acid and neuroactive steroid metabolism [The nature of RNase P from organelles, such as mitochondria and chloroplasts, puzzled the field for many years, with many reports suggesting that the holoenzymes were either very proteinaceous with an inaccessible RNA subunit or that the RNA subunit was dispensable for activity as suggested from experiments showing RNase P activity resistant to treatment with ribonucleases ,97. Surptabolism ,99. Moretabolism .1G/A methylation at position 9 of mitochondrial tRNAs, the efficient 3′ end maturation, and finally, the 3′ CCA addition [The structures of MRPP1, MRPP2 and MRPP3, determined individually and combined with low resolution SAXS analysis of the holoenzyme, gave a first description on the stoichiometry and the architecture of the human mt-RNase P ,101,102.addition ,103.Drosophila  leads to accumulation of precursor transcripts and is lethal during early development. The same effect is also observed after knocking down or completely inactivating the MRPP1 and MRPP2 homologues in Drosophila . Knocking out MRPP1 and MRPP2 in a mammalian animal model has not yet been tested; however, knocking down MRPP1 and MRPP2 in HeLa and U2OS cell cultures disrupts the proper maturation of mitochondrial RNA and leads to an increased abundance of higher molecular weight transcripts [MRPP3 knockout mouse model in heart and skeletal muscle tissues was developed, but the mutants exhibited short lifespans and succumbed at approximately 11 weeks due to cardiomyopathy [Drosophila larval neuroblasts results in mitochondrial swelling. The complete absence of each subunit differentially affects the 5′ and 3′processing of tRNAs, but also of non-canonical junctions, depending possibly on their upstream RNA content. Additionally, the effect on the steady-state levels of transcripts produced from the same polycistronic transcript differ upon knocking out each mt-RNase P subunit. These discrepancies possibly stem from the fact that other ribonucleases may have moonlighting mitochondrial RNA processing activity [Given that the mitochondrial RNA maturation process obeys the tRNA-punctuation model, it is possible that ablation of either subunit of the mt-RNase P complex could have excessive effects, leading to lethality . As expenscripts ,105. Mutnscripts . Moreovenscripts . A viablmyopathy . Isolateactivity .Rprl1-3), which are differentially expressed in various tissues, suggests that possible heterogeneous pools of RNase P RNPs may exist [Almost 40 years after its original discovery and characterization, RNase P remains an appealing model to study structural and functional attributes during the transition from an RNA to an RNP, or even protein, world. The multi-subunit protein composition of both the nuclear and mt-RNase P holoenzymes suggests that proteins with possibly pre-existing function were acquired during evolution and some of them still serve important alternative cellular roles, either as individual components or in combination with other proteins. The fact that many protein subunits act as molecular “patches” to cover for the structural peculiarities or deficiencies of RNA is an important feature that possibly could reflect the putative structural heterogeneity of the holoenzyme under specific conditions . The existence of three RNase P RNA-like transcripts in mice . Although RNase MRP was initially characterized as a nuclease that cleaves the primers for DNA replication in mitochondria, later, it was shown that it is involved in pre-rRNA processing by cleaving the A3 site in the internal transcribed spacer 1 (ITS1). Interestingly, individual reports have linked RNase P and/or MRP activity with the cleavage of specific mRNAs, either in their 5′UTR (as in the case of Cyclin B2 mRNA) or through interactions with YTHDF2 (YTH N6-Methyladenosine RNA Binding Protein 2) and HRSP12 (2-iminobutanoate/2-iminopropanoate deaminase), which are recruited on m6A modification sites to regulate mRNA cleavage ,115. In


RNA-seq derived sites could be calculated. We identify 72% of these sites correctly, with 98% of them located ≤ 80 bases downstream of the stop codon. The predicted hairpins form a cluster (when present < 15 bases) in two-thirds of the cases, the remaining being single hairpins. The largest number of clusters is formed by two hairpins, and the occurrence decreases exponentially with an increasing number of hairpins in the cluster. Our study reveals that hairpins form an effective ITT unit when they act in concert in a cluster. Their pervasiveness along with single hairpin terminators corroborates a wider utilization of ITT mechanisms for transcription control across bacteria.Intrinsic transcription termination (ITT) sites are currently identified by locating single and double-adjacent RNA hairpins downstream of the stop codon. ITTs for a limited number of genes/operons in only a few bacterial genomes are currently known. This lack of coverage is a lacuna in the existing ITT inference methods. We have studied the inter-operon regions of 13 genomes covering all major phyla in bacteria, for which good quality public RNA-seq data exist. We identify ITT sites in 87% of cases by predicting hairpin(s) and validate against 81% of cases for which the  It is continued through the elongation and termination steps that are tightly regulated. Any obstruction of transcription could be a pause, but a pause followed by the dismantling of the transcription complex causes transcription termination3. The cause of termination could be intrinsic4 or extrinsic5. Although many facets of the intrinsic transcription termination (ITT) driven by product mRNA are understood6, the common determinants required for such mechanisms to operate across bacterial organisms remain unclear.Transcription is the first step of decoding genomic information and is initiated post recruitment of the RNA polymerase (RNAP) at the DNA start site8. Poly U tract, located immediately after the end of a hairpin, drive detachment of the RNA-polymerase from mRNA-genome complex11. Strong mRNA hairpins can also allosterically alter the RNAP structure to cause ITT12. Several algorithms, such as by Carafa et al.13, Brendel et al.14, or software like TransTerm15, RNAMotif16, and RNIE17 try to capture these genomic features to detect termination-capable hairpins. However, bacterial genome sequence analysis has shown the intergenic continuous poly U tract (in nascent RNA) to be infrequently present downstream of the stop codon. The 26,000 best candidate hairpins observed immediately downstream of the stop codon across 1060 bacterial species did not have any U stretch in ~ 50% cases18.During ITT, RNAP translocation on DNA is stalled by the product mRNA synthesized due to hairpin(s) formed from GC rich inverted repeat sequence stabilized by more number of hydrogen bonds21, it was observed by computational as well as in vivo methods that poly U trail is not necessary for ITT. In M. tuberculosis, nearly 90% of such terminator structures are found either without a U trail or with a mixed U/A trail, unlike the trends in E. coli where many studies claim the importance of downstream U trail. Other organisms with such findings include Streptomyces, H. pylori24. Even some genes in E. coli show that termination efficiency only reduces slightly when the poly U trail is reduced26.By our analysis and others28. A summary of the pertinent literature is given in Supplementary Table Other features in sequences downstream of the stop codon also affect termination efficiency along with stem-loop and poly U segment downstream of the hairpin stem. This includes two G/C base pairs in the U-rich tract, an elemental pause sequence, or conserved sequences like TCTG downstream of hairpin18. Classification labels such as I- and L-shape have been given to single hairpins where L shape hairpins are I hairpins extended by a poly-U trail. When consecutive I hairpins are separated by a short RNA sequence, they are classified as U-, or V-shaped when there is no separation, and X-shaped when coded by the opposite DNA strands. U-, V-shaped hairpins are less frequent with only 10% and 15% cases found in M. tuberculosis and E. coli, respectively21, although they are deemed equally effective as the I or L-shaped hairpins29. A survey on 1060 genomes found only about one-third of the genes to have a hairpin downstream of the stop codon, and of these, 86% I/L-shaped and the remaining U/X/V-shaped  made up the whole composition18. How the remaining two-third of genes are accomplishing transcription termination is the key question to be answered. If these happen through extrinsic termination mechanisms, proteins like the Rho and NusA need to be commonly overexpressed or conditionally overexpressed relative to RNAP. The published literature does not document such facts, especially when the hexameric form of the Rho protein is known to be required for fruitful transcription termination . On imposing the high confidence criterion of > 90% read coverage in an IR, we obtain 16,027 IRs . On further removing the IRs with outlier (5% tail of coverage-data) read depth, we obtained 14,738 IRs. Nostoc punctiforme PCC 73102 and Fusobacterium nucleatum ATCC 25586 have the lowest and the highest number of genes per operon, respectively  units giving an average of about 5 hairpins per cluster. The remaining 25,696 hairpins do not form any cluster and are deemed as single-hairpin (single) units. The number of hairpins is not proportional to the number of IRs, and the highest is predicted for Mycobacterium gilvum (at 161 hairpins / IR) followed by Pseudomonas aeruginosa (129 hairpins / IR). In comparison, the lowest is found in Fusobacteruim nucleatum with 15 hairpins / IR. The number of hairpins per IR (hairpin density) is a consequence of the GC percent of the IRs; the correlation coefficient is 0.8, which is expected due to the dominant contribution of GC hydrogen bonds to stem-stability in hairpins.As already outlined before, we term a group of hairpins such that the distance between the end of one hairpin and the start of the next hairpin is always < 15 nucleotides as a cluster or single unit nearest to the stop codon is termed the identified termination unit since it is expected to provide the most efficient termination. It would also kinetically be the first hairpin to form and disrupt RNAP movement. A total of 12,787 termination sites (in 87% IRs) are identified closest to the stop codon, of which 7394 and 5393 could be linked to cluster- and single-hairpin units, respectively. The total number of hairpins in identified clusters is 22,519, with an average of 3 hairpins per cluster. We also calculated the identified termination units for rRNA % and 58(± 11)% of the IRs Fig. ; for a wts Table . Table 2cluster or single units that are closest to posst are termed as RNA-seq derived hairpins. The distribution of cluster or single termination units in the forward and reverse strand and their zonal location is shown in Table RNA-seq derived termination units were found, 75% lay in Zone 1 and the remaining 25% in the buffer Zone 2.The st with ’n’ ranging from 0 to 75 bases. n is calculated as the shortest distance from the hairpin base, and therefore it is the last hairpin in the cluster unit for Zone 1 and the first hairpin for Zone 2. Figure st. Of these, in 50(± 11)% cases, the posst is with n = 0; i.e., it coincides with the hairpin start. There is a gradual decrease of cases by distance with 29(± 6)%, 3(± 1)%, and 0.4% of the termination sites lying within 25, 25–50, and 50–75 bases of posst. 13(± 1)%, 1(± 1)%, 0.3% of cluster units lie within 25, 25–50, and 50–75 bases, respectively. The corresponding values for single are 16(± 6)%, 1%, and 0.2%. Of the RNA-seq derived termination units, 67%, and 33% are from the cluster and single, respectively; therefore, higher occurrence of the former points to their utility in bacterial ITT.Figure st lies close to the stop codon, which indicates an early termination and correct estimate of the pos and the predicted hairpin. The Zone 2 lengths are largely restricted within 100 bases for all IRs % hairpin units with energy scores between 0 and − 5 kcal/mole, 36(± 6)% between 5 and 0 kcal/mol and 7(± 2)% between − 5 and − 10 kcal/mol. A minuscule 1% fraction of hairpins has an energy score lower than − 10 kcal/mol . Not all organisms have a similar fraction of identified and RNA-seq derived hairpins found at the same location, with the best predictions for P. marinus at 83% and worst for C. phytofermentans at 46%. If we look at the distance of the matched termination units from the stop codon, 67(± 10)% of the cluster- and 57(± 11)% of single are within 20 bases  of the matched cases occur in Zone 1 compared to 22%  in Zone 2. For remaining IRs, where identified and RNA-seq derived hairpin units did not match, 70% are within 60 bases of each other  content must add up to 100%.Of the 13 genomes in our data set, we found six genomes to be GC rich with > 50% GC pairs. The number of hairpins and the identified termination units using the transcribed DNA information. Of the 13 diverse bacterial genomes scanned for A/U patterns, the existing patterns are rarely co-located at the base of the RNA-seq derived and identified hairpins  was used to search the sequences for their corresponding mapping regions in E. coli K-12 MG1655 (NCBI ID: NC_000913/U_00096) for which we also calculated the identified hairpins by our algorithm. It may be noted that Carafa et al. used a list of literature-identified hairpins that have poly U stretch with a strong bias of U to be present in the first two positions from the 3′ end of the hairpin. Also, these hairpins must have either 4 GC base pairs in the stem if no bulge or internal loop exists, or a minimum of 6GC base pairs if otherwise. Also a liberal criterion is used whereby termination zones are used to identify ITT location instead for of the exact location of the terminator hairpin. Yet we found only 83 of the 143 sequences to have a match in the IR region. Of these only 8 termination zones matched the identified hairpin or alternate termination site (other putative hairpins if the first site does not terminate transcription). In 3 other cases, we found a partial match between hairpins and the termination zones. On dividing the matches strandwise, 131 cases were found on the forward strand and remaining on the complementary strand. Of these, in 96 cases the hairpin was present either inside the operon region in the forward strand  read profiles bridges the conjecture that bacteria commonly prefer the ITT mechanism as their favored transcription regulation process. This inference is an improvement over our previous observation18, where we identified approximately one-third of the IRs to have stable hairpins based on GC-rich stem composition criteria.The lack of solid evidence on the wide prevalence of ITT units across diverse organisms has, therefore, been intriguing. The extrinsic transcription termination mechanism involves concertedly acting protein factors and thus requires more sophisticated control than ITT. Therefore, our identification of 72% of the bacterial IRs with an ITT unit validated by RNA-seq  is as effective as a single strong hairpin to cause ITT. As such, most isolated hairpins can fold in solution within microseconds33 and the rate is determined by the number of nucleation points in the sequence34. For example, in hairpin helix, A6 C6 U6, at 24 °C the rates of formation and dissociation are 2.4 × 104 s−1 and 2.6 × 104 s−1, respectively35. Similarly, for 21 nucleotides hairpin UAUAUCGC7CGAUAUA at 37 °C, they are 1.3 × 106 s−1 for the formation and 3.2 × 106 s−1 for dissociation36. In contrast, the average mRNA elongation rate in E. coli is found to be 58 nucleotides/sec at 37 °C. Thus, the RNA folding rates are much faster compared to elongation rates as corroborated by experimental data37. The time difference is large enough to accommodate the actual folding time variations of a hairpin arising out of multiple factors including stem and loop sequence, neighboring bases, which alter the rate-limiting step of folding38. Folding experiments also show a preference for alternating structures (11 out of 14 to 40-length sequences) where there is interconversion between single and two hairpin states, the latter being the major one34. When long mRNA sequences fold it was observed that short-range interactions have higher stability over long-range reactions, and they are thus retained39. In physiological conditions, the number of accessible nucleation points and short-range forces are also expected to dominate the RNA folding process. However, folded hairpins herein may face a steep transition barrier to interconversion due to concomitant RNA–protein interaction; thus early formation of short hairpins forming a cluster would be preferred as suggested by our genome analysis.For a basic ITT process to occur, the 42, once the loop-closing base pair is available. In in vivo situation, the RNA secondary structures may fold sequentially as the RNA gets elongated, but they rapidly change to alternating more stable structures43. This reduces the chance of misfolded structure formation, as observed in ribozyme folding studies44. However, small hairpins (like in cluster) may have similar folding rates both in vivo and in vitro as shown by hairpin folding studies of ribozymes44. Accessory factors like the NusA may further enhance the hairpin folding rates in vivo.Nascent hairpin formation during transcription may be impeded by spatial constraints in the RNA exit channel; however, during ITT, hairpins are known to form outside the channel45 by stabilizing the RNAP structure by virtue of its interaction with the protein complex. Therefore, a cluster unit, which presents a larger count of shorter hairpins may further stabilize the RNAP complex by additional RNA–protein interaction, and this is expected to be more efficient in stalling and dislodging the transcription complex than a single hairpin. This is statistically consistent due to the higher occurrence of loop regions from shorter hairpins that can engage the protein in both hydrogen bonding and hydrophobic interactions. In such circumstances, many short contiguous hairpins can be more effective in RNAP pause and dismantling. It is also possible that the initial hairpins in the cluster slow down the polymerase while the later hairpins finally cause the release21.From structural studies, it is known that an RNA hairpin can pause transcription46; therefore, our observation of the first hairpin (or cluster of hairpins) downstream of the stop codon as the effective terminator unit is consistent with the optimal arrangement necessary for efficient ITT. Forward translocation, another suggested mechanism of RNAP dissociation in ITT is also consistent with our proposition. Here the hairpin formation forces the RNAP to move downstream (relative to DNA template) while the mRNA does not move, thus breaking the DNA: RNA hybrid bonds. Cluster hairpins are dominantly placed to promote dissociation, reducing the over-reliance on poly U/A occurrence, which are thought to weaken the links in the DNA-RNA hybrid for easier dissociation.It is interesting to note that the presence of secondary structures that hinder the formation of terminator hairpins reduces termination efficiency. This was shown by the application of force that suppressed the formation of such secondary structures, which led to an increase in termination efficiency48. These factors work by two modes during ITT, one by interacting with the RNAP and stabilizing it or interact with the emergent RNA transcript50. The NusA and NusG are known to form complexes to enhance their interaction with RNAP to increase termination efficiency; whereas, NusG alone is known to suppress transcription pause, but not termination47. Factors like RfaH, a homolog of NusG suppresses stabilizing effects of nascent RNA hairpin51 and decreases termination52. The interplay of accessory factors thus complicates the building of a true ITT thermodynamic model. Attempts for such a model two decades back have focussed primarily on understanding the stability of the termination complex, especially the contribution of RNA–DNA base-pairing54.The ITT, although perceived, is not entirely intrinsic to RNA, DNA, and RNAP activity alone, and is influenced by accessory factors like the NusA and NusG during transcription and terminationCluster hairpins can, however, explain simple entropy-driven processes that may achieve efficient ITT. Such processes have been investigated in less complex systems for understanding the potential mechanisms at play56. If we assume RNAP:DNA:RNA hybrid and the immediate solvent environment as a quasi thermodynamic system inside the cell, the hybrid typically contributes to entropy change by its thermal fluctuations and translocation during transcription. The nucleotide addition cycle during transcription gradually alters the entropic state of the system till the time the nascent RNA at the exit channel is long enough to fold into a hairpin. We already know that RNA folding and thermal equilibration of the structure occur much faster than nucleotide addition by RNAP37. As RNA folding is driven by entropy57 there is a rapid entropy change locally in the system. This entropy change can act as a perturbation and a trigger for conformational transitions along soft modes55 of the RNAP complex. The perturbation may drive thermalization in the system leading to overcoming the transition barrier56 for ITT to take place. The probability of such perturbations increases with the formation of more hairpins and thus increases the probability of stochastic ITT. This predisposes cluster hairpins for more efficient ITT compared to the single. In vivo studies in M. smegmatis indeed show that two tandem hairpins downstream of the gyrA gene have a higher termination efficiency than individual single hairpins21. Please note that accessory factors that interact with the RNAP or the nascent RNA can alter the probabilities of the ITT process, but the proposition that cluster hairpins can achieve more efficient ITT than single hairpin remains consistent on both kinetic and thermodynamic considerations.11. This is consistent with our study as well. Another study found that termination  was seen 7 nucleotides downstream from the stem end of hairpin32 in both in vitro and in vivo. There is also a relationship between the stop codon and the terminator position. Hairpins should be present at least 30 nucleotides away from the stop codon31. It has also been observed that terminators within 100 bases from the coding region have high termination efficiency. As mentioned above, all the analyses are performed only on the E. coli genome, and further experimental/mechanistic studies would be required to see if these trends are statistically significant and followed across other bacteria. We also tried to find regions of conservation near the stop codon and around the hairpins but could not find any such sequence conservation within 25 bases from the stop codon  as a fail-safe mechanism for termination32, but they work independently. The insights from our work appear to be consistent with these previous observations.Existing literature suggests that Rho-dependent terminators mostly occur in enteric (rod-shaped gram-negative) bacteria49, as DNA uptake elements62, translational surveillance63, or riboswitches64. However, the location of these elements is distinct from the region downstream of the stop codon.Other functional roles of hairpins might involve the presence of specific sequence motifs, or in inhibition of RNA degradationcluster and single units in filtered IRs co-located against RNA-seq derived terminators. We show that if hairpins work in tandem , they can bring about ITT, as evidenced by the absence of RNA-seq reads contiguous to our identified hairpin sites. 91% of the matched bacterial termination units are present close to the stop codon in each transcription unit within 50 bases. They typically have a stem length between 4 and 14 base pairs and a 5 and 10 loop length. The requirement of a poly A/U pattern at the hairpin base is not essential. The detection of hairpins is independent of its GC content; i.e., we are able to find ITT units across GC as well as AT rich genomes. Our work contributes to the understanding of the genomic requirements necessary to execute an ITT process.To summarize, we identified 72% of cases of the 65. A representative from each group is chosen if it had public RNA-seq data . Entries from Planctomyces, Thermodesulfobacteria, Chlamydia, Chloroflexi, and Acidobacteria from bacterial phyla are excluded due to the absence of high-quality RNA-seq data. To increase the confidence and coverage of RNA-seq data being used, sample replicates under the same experimental conditions are taken wherever available. This data is indexed and aligned to the respective reference genomes using Bowtie266. Reads present in a proper pair , with Transcript Length (TLEN) or insert size ≥ read length, and map quality ≥ 30, are filtered out from the initially obtained alignment. TLEN is the distance between the 5′ end of the leftmost read to the 3′ end of the rightmost read that is mapped to the same cDNA fragment  represent the stability of the hairpins. The scores in terms of ∆G output by MFold represent the stability accrued primarily from the secondary structure interactions. Additional stability may accrue from tertiary structure interaction, which may not be faithfully accounted for by the MFold scoring function. To check for this fact, we took all the predicted hairpins with > 0 ∆G  score from MFold and subjected them to three-dimensional structure modeling using SimRNA72. SimRNA is a computational RNA three-dimensional structure prediction method that uses Monte Carlo simulations to check possible folding structures and outputs an energy score for it. The secondary structure output from MFold was used to put constraints on the conformational search space of the three-dimensional structures during sampling. For each hairpin, we find 11 all-atom structure frames after 1600 iterations and add protons using the REDUCE program73. We screen if the predicted three-dimensional RNA structure is valid with help of the MolProbity program74. It checks for the presence of wrong sugar puckers in each predicted structure. Trial three-dimensional hairpin models are first generated in batches to check for stable structures. All the hairpins returned at least one tertiary model with < 0 ∆G  score among the first 100 trial structures generated respecting the expected sugar puckering geometries, bond length and bond angle values. To additionally confirm the veracity of our methodology, we searched through the literature and culled 110 hairpin structures for which we had information on experimentally determined free energy of hairpin formation. These hairpins have been predominantly reported in E. coli, in addition to P. aeruginosa, M. formicicum, and T. acidophilum75. The sequences are subjected to MFold secondary structure prediction, and those with > 0 ∆G score are taken for tertiary structure modelling using SimRNA as outlined above. All the energy scores output for the three-dimensional models are found to be < 0 ∆G   Fig. . The pre77; therefore, the non-coding region downstream of a stop codon of an operon or individual gene is found for each transcription unit up to the defined scan window (+ 270). The FGENESB module of the Molquest software (http://www.molquest.com)78 is used to obtain the start and stop codon positions of genes and operons. It predicts operon locations using distances between locations of predicted genes in combination with data from homolog databases like COG79, KEGG80 after performing a BLAST81 search. It uses a Markov model for coding region annotation, and distances between predicted genes to predict operons. It supposedly predicts 70% single transcription units and about 50% operons exactly. Accuracy determination is done on a set of difficult short genes that have been used for evaluation accuracy of bacterial gene finders as well. It was seen that the accuracy of Molquest is better than previously used Glimmer and GeneMarkS softwares82, which previously provided the best accuracy. Accuracy was tested on highly annotated sets from B. subtilis and E. coli. Predicted promoters and terminators are used to increase the accuracy of operon identification, as they now have defined boundaries thus training of initial parameters is better. Genes annotated in the NCBI genome database but not identified by Molquest are included in our list as additional entries. We calculate the inter operon/gene region (IR), defined by the region between the 3′ end of an operon or individually transcribed gene and the 5′ end of the next transcription unit. The intergenic regions within an operon are not included in IR.RNA-seq reads do not reduce in number in the intergenic regions of an operon83. If read coverage in either the CDS or IR region of a transcription unit is several orders higher than the rest of the genome, it is removed as an outlier; for this, we check the 5% tail region of the average read depth histogram of CDS or IR regions.For each genome, read depth is calculated at each location. In case the organism had replicate experimental data, reads from all of them are combined and averaged to find an average read depth. Only cases where the read coverage of the CDS region is > 90% are taken for further analysis because of PCR amplification errors, degree of annotation in operons, PCR duplicates, alignment efficiency of paired-end mapping, etc.cluster if the distance between the end of one hairpin and the start of the next is < 15 nucleotides. All such clusters are labeled cluster. In the case of larger hairpin subsuming the smaller, first occurring  hairpin is chosen for cluster calculation. The choice of < 15 nucleotides as hairpin separating distance for identifying hairpin cluster is based on the typical length of the nascent RNA nucleotide strand that can be enclosed in the RNA exit channel (5 nucleotides) and DNA-RNA hybrid (9–10 bp)6 and unavailable for folding into a hairpin at any given time. It is ensured that a subset of hairpins from a higher size cluster is not present as a separate entry in a lower size cluster. Aside from the cluster, those hairpins without any neighbor at < 15 nucleotides are labeled as single. For those cases where two hairpins have partial overlaps, each is checked if they can form a cluster as per the defined criteria or left as a single hairpin. We take each single or cluster as a potential termination unit, irrespective of the size of the hairpin or the number of hairpins in a cluster. For each IR, such a termination unit lying closest to the stop codon is labeled as an identified cluster or identified single.Out of all predicted hairpin structures, those falling within screened IRs are filtered out for the two strands. These structures belong to a RNA-seq transcript/read data is mapped to locations on the genome by alignment where the transcription took place. For finding slopes, we first calculate the cumulative frequency of reads for an operon. We then find slopes-sl1 (that would represent the average read increase per window) for the whole region. RNA-seq data show that even when the read coverage falls drastically in the IR implying a termination has occurred, the reads are not completely absent in the region beyond the putative termination site. Therefore, to identify the termination site, all the regions where the count of reads increase after the stop codon is found. So, if we take the adjacent differences of sl1 slope values, we are taking the second derivative of the cumulative frequency curves, defined by sl2.a and b be two points on cumulative frequency plot at positions (i) and (i + w), where w is the varying window size. Let read frequency at a be af and at b be bf.Let w’ ranging from 5, 10, 15 and so on up to 30. An example case is shown in Figure We calculated slope values for different windows ‘A = {a1, a2, a3, a4, … n} be a set of sl1 slopes for IR region of an operon.Let a2-a1, a3-a2, a4-a3, … an-a(n-1)).Then sl2 = {sl2 would have positive and negative values as well as saddle points (points of inflection). In the IR we find the first negative sl2 slope after the stop codon which is followed by the positive sl2 slope. We take such saddle point and extend it till another drop in slope is seen.The changes in slope are prominently visible early in the IR using window sizes 5, 10, and sometimes 15, but many such inflection points are lost when higher lengths of the window, i.e. 20–30 are taken. So, we take 10 as the window size for our analysis Fig. .4 to 106. By taking the ratio of IR slope values : coding region slope values; i.e. 0–400: 104–106, would be in the range of ~ 0 to 0.004. showing that even though the slope values are positive in IR, the marginal increase of reads is negligible.Now, we rationalize that termination must have taken place at the start of such a region. This is because, the drastic decrease in read frequency points to termination, and in order for an efficient termination, the cell is likely to pick an early termination site, and hence we too choose the first such region for the presence of hairpin termination units. Taking w = 10, if the average of all slope values are calculated in the coding region then it is the coding (operon) region slope and if it is calculated in IR then it is IR slope. IR slope values range from 0 to 400 in our data, while coding region slope values range from 10st, posst, posend, and IRend, which represent IR start, positive slope region start, positive slope region end, and IR end, respectively  divides the IR into three zones; Zone 1, Zone 2, and Zone 3, marked with the help of IRcluster that straddles across Zone 1 and Zone 2 has n = 0, and the one restricted to Zone 1, the n value is calculated from the last base of the last hairpin, while for Zone 2 it is the first base of the first hairpin  and anti-sense (−) strands. The poly U or poly A pattern associated with the intrinsic terminators is supposed to be a continuous stretch that is not often interspersed with other bases. Therefore, for pattern search, we use a minimum criterion that at least three consecutive A or U bases must be present to label it as a true site in the IR. The pattern may not be perfect and can have mismatches with the presence of other bases in between. To account for this, we check for patterns with ≤ 1 and ≤ 2 mismatches as well. If there is more than one pattern in the IR, the one nearest to the upstream hairpin is taken. These are further divided into identified termination units located ahead of Molquest predicted terminators. Our exclusive predictions are primarily comprised of cluster cases. In 10 out of 13 genomes, > 50% of termination units corresponded to cluster with as high as 77% in P. aeruginosa.Along with operon prediction, Molquest also gives predictions for ITT sites in bacterial genomes. This feature was used to predict hairpins for the 13 bacterial genomes used in our analysis and the results obtained were compared with hairpins identified by our algorithm. In 44% of IRs both Molquest and our method predicted hairpin sites (common); in 7%, neither could make any prediction, while in 6% and 43% cases Molquest and our method, respectively, made exclusive predictions. For common case predictions, very few sites had a match comparing the distance between midpoints of the predicted terminators Fig. . Here 69This work is entirely computational and does not require any approval.All authors have read and approved the manuscript for publication.Supplementary Information 1.