Substrate Cleavage Site Research Articles

Cryo-EM structures of human DICER dicing a pre-miRNA substrate.

Dicer, a multi-domain ribonuclease III (RNase III) protein, is crucial for gene regulation via RNA interference. It processes hairpin-like precursors into microRNAs (miRNAs) and long double-stranded RNAs (dsRNAs) into small interfering RNAs (siRNAs). During the "dicing" process, the miRNA or siRNA substrate is stably anchored and cleaved by Dicer's RNase III domain. Although numerous studies have investigated long dsRNA cleavage by Dicer, the specific mechanism by which human Dicer (hDICER) processes pre-miRNA remains unelucidated. This review introduces the recently revealed hDICER structure bound to pre-miRNA uncovered through cryo-electron microscopy and compares it with previous reports describing Dicer. The domain-wise movements of the helicase and dsRNA-binding domain (dsRBD) and specific residues involved in substrate sequence recognition have been identified. During RNA substrate binding, the hDICER apical domains and dsRBD recognize the pre-miRNA termini and cleavage site, respectively. Residue rearrangements in positively charged pockets within the apical domain influence substrate recognition and cleavage site determination. The specific interactions between dsRBD positively charged residues and nucleotide bases near the cleavage site emphasize the significance of cis-acting elements in the hDICER processing mechanism. These findings provide valuable insights for understanding hDICER-related diseases.

ProsperousPlus: a one-stop and comprehensive platform for accurate protease-specific substrate cleavage prediction and machine-learning model construction.

Proteases contribute to a broad spectrum of cellular functions. Given a relatively limited amount of experimental data, developing accurate sequence-based predictors of substrate cleavage sites facilitates a better understanding of protease functions and substrate specificity. While many protease-specific predictors of substrate cleavage sites were developed, these efforts are outpaced by the growth of the protease substrate cleavage data. In particular, since data for 100+ protease types are available and this number continues to grow, it becomes impractical to publish predictors for new protease types, and instead it might be better to provide a computational platform that helps users to quickly and efficiently build predictors that address their specific needs. To this end, we conceptualized, developed, tested and released a versatile bioinformatics platform, ProsperousPlus, that empowers users, even those with no programming or little bioinformatics background, to build fast and accurate predictors of substrate cleavage sites. ProsperousPlus facilitates the use of the rapidly accumulating substrate cleavage data to train, empirically assess and deploy predictive models for user-selected substrate types. Benchmarking tests on test datasets show that our platform produces predictors that on average exceed the predictive performance of current state-of-the-art approaches. ProsperousPlus is available as a webserver and a stand-alone software package at http://prosperousplus.unimelb-biotools.cloud.edu.au/.

Integrative modeling of diverse protein-peptide systems using CABS-dock.

The CABS model can be applied to a wide range of protein-protein and protein-peptide molecular modeling tasks, such as simulating folding pathways, predicting structures, docking, and analyzing the structural dynamics of molecular complexes. In this work, we use the CABS-dock tool in two diverse modeling tasks: 1) predicting the structures of amyloid protofilaments and 2) identifying cleavage sites in the peptide substrates of proteolytic enzymes. In the first case, simulations of the simultaneous docking of amyloidogenic peptides indicated that the CABS model can accurately predict the structures of amyloid protofilaments which have an in-register parallel architecture. Scoring based on a combination of symmetry criteria and estimated interaction energy values for bound monomers enables the identification of protofilament models that closely match their experimental structures for 5 out of 6 analyzed systems. For the second task, it has been shown that CABS-dock coarse-grained docking simulations can be used to identify the positions of cleavage sites in the peptide substrates of proteolytic enzymes. The cleavage site position was correctly identified for 12 out of 15 analyzed peptides. When combined with sequence-based methods, these docking simulations may lead to an efficient way of predicting cleavage sites in degraded proteins. The method also provides the atomic structures of enzyme-substrate complexes, which can give insights into enzyme-substrate interactions that are crucial for the design of new potent inhibitors.

Cooperation of N- and C-terminal substrate transmembrane domain segments in intramembrane proteolysis by γ-secretase

Intramembrane proteases play a pivotal role in biology and medicine, but how these proteases decode cleavability of a substrate transmembrane (TM) domain remains unclear. Here, we study the role of conformational flexibility of a TM domain, as determined by deuterium/hydrogen exchange, on substrate cleavability by γ-secretase in vitro and in cellulo. By comparing hybrid TMDs based on the natural amyloid precursor protein TM domain and an artificial poly-Leu non-substrate, we find that substrate cleavage requires conformational flexibility within the N-terminal half of the TMD helix (TM-N). Robust cleavability also requires the C-terminal TM sequence (TM-C) containing substrate cleavage sites. Since flexibility of TM-C does not correlate with cleavage efficiency, the role of the TM-C may be defined mainly by its ability to form a cleavage-competent state near the active site, together with parts of presenilin, the enzymatic component of γ-secretase. In sum, cleavability of a γ-secretase substrate appears to depend on cooperating TM domain segments, which deepens our mechanistic understanding of intramembrane proteolysis.

Identification of SARS-CoV-2 Main Protease (Mpro) Cleavage Sites Using Two-Dimensional Electrophoresis and In Silico Cleavage Site Prediction

The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays a crucial role in its life cycle. The Mpro-mediated limited proteolysis of the viral polyproteins is necessary for the replication of the virus, and cleavage of the host proteins of the infected cells may also contribute to viral pathogenesis, such as evading the immune responses or triggering cell toxicity. Therefore, the identification of host substrates of the viral protease is of special interest. To identify cleavage sites in cellular substrates of SARS-CoV-2 Mpro, we determined changes in the HEK293T cellular proteome upon expression of the Mpro using two-dimensional gel electrophoresis. The candidate cellular substrates of Mpro were identified by mass spectrometry, and then potential cleavage sites were predicted in silico using NetCorona 1.0 and 3CLP web servers. The existence of the predicted cleavage sites was investigated by in vitro cleavage reactions using recombinant protein substrates containing the candidate target sequences, followed by the determination of cleavage positions using mass spectrometry. Unknown and previously described SARS-CoV-2 Mpro cleavage sites and cellular substrates were also identified. Identification of target sequences is important to understand the specificity of the enzyme, as well as aiding the improvement and development of computational methods for cleavage site prediction.

APLP2 is predominantly cleaved by β‐secretase and γ‐secretase in the human brain

Amyloid-β peptide is well-known as a pathogen of Alzheimer's disease, but its precursor, amyloid-beta precursor protein (APP), remains unexplained 30 years after its discovery. APP has two homologues called amyloid precursor-like protein 1 (APLP1) and amyloid precursor-like protein 2 (APLP2), and shares a similar structural organisation with them and has partially overlapping functions. APP family proteins are essential for survival, shown by the crossbreeding analysis of knockout mice of APP family molecules, including APLP1 and APLP2. APLP2 is known to play the most important role among them, but the molecular metabolism of APLP2 is only partially understood. Here, we analysed ectodomain shedding and γ-secretase cleavage of APLP2 by molecular biological and biochemical techniques. We analysed the culture supernatant of HEK293 cells overexpressing APLP2 and human cerebrospinal fluid. For the analysis of secreted APLP2 fragments, we raised the OA603 antibody that reacts with the juxtamembrane domain of APLP2. Substrate cleavage sites were identified by matrix assisted laser desorption/ionisation mass spectrometry. By overexpressing in HEK293 cells, APLP2 undergoes ectodomain shedding at three sites in the extracellular region by α- and β-secretase-like activity and then is intramembranously cleaved at three sites by γ-secretase. In particular, in shedding, α-secretase-like activity was dominant in HEK cells. Surprisingly, in human cerebrospinal fluid, APLP2-derived metabolic fragments were mainly cleaved by β-secretase-like activity, not by α-secretase-like activity. Because APP is also mainly cleaved by beta-site amyloid precursor protein cleaving enzyme 1 in neurons and APLP1 is expressed exclusively in neurons, these findings suggest that APP family proteins may play a common role via β-secretase-like cleavage in the central nerve system. Thus, these findings may contribute to a better understanding of the role of APP family proteins in Alzheimer's disease.

Identification of Molecular Determinants in iRhoms1 and 2 That Contribute to the Substrate Selectivity of Stimulated ADAM17.

The metalloprotease ADAM17 is a key regulator of the TNFα, IL-6R and EGFR signaling pathways. The maturation and function of ADAM17 is controlled by the seven-membrane-spanning proteins iRhoms1 and 2. The functional properties of the ADAM17/iRhom1 and ADAM17/iRhom2 complexes differ, in that stimulated shedding of most ADAM17 substrates tested to date can be supported by iRhom2, whereas iRhom1 can only support stimulated shedding of very few ADAM17 substrates, such as TGFα. The first transmembrane domain (TMD1) of iRhom2 and the sole TMD of ADAM17 are important for the stimulated shedding of ADAM17 substrates by iRhom2. However, little is currently known about how the iRhoms interact with different substrates to control their stimulated shedding by ADAM17. To provide new insights into this topic, we tested how various chimeras between iRhom1 and iRhom2 affect the stimulated processing of the EGFR-ligands TGFα (iRhom1- or 2-dependent) and EREG (iRhom2-selective) by ADAM17. This uncovered an important role for the TMD7 of the iRhoms in determining their substrate selectivity. Computational methods utilized to characterize the iRhom1/2/substrate interactions suggest that the substrate selectivity is determined, at least in part, by a distinct accessibility of the substrate cleavage site to stimulated ADAM17. These studies not only provide new insights into why the substrate selectivity of stimulated iRhom2/ADAM17 differs from that of iRhom1/ADAM17, but also suggest new approaches for targeting the release of specific ADAM17 substrates.

Peptidomic analysis characterising proteolysis in thaw-aging of beef short plate

Recent studies have suggested that thaw-aging can improve sensory attributes of freeze-thawed meat. Acceleration of proteolysis is expected to promote tenderisation and improve taste; however, the details of protein degradation, including substrate proteins and cleavage sites, remain unclear. Here, we report a time course overview of the peptidome of beef short plates during thaw-aging. The accelerated degradation of key proteins for meat tenderisation, such as troponin T and desmin, was confirmed. Additionally, 11 cleavage sites in troponin T related to taste-active peptide generation were identified. Terminome analysis showed that the contribution of each protease varies depending on the substrate proteins and the thaw-aging period. Based on our results; proteases, not only calpains, but also others contributed to the degradation of myofibrillar proteins. The techniques employed indicate that meat proteolysis during thaw-aging is not constant but dynamic.

HIV-1 Gag Non-Cleavage Site PI Resistance Mutations Stabilize Protease/Gag Substrate Complexes In Silico via a Substrate-Clamp

HIV-1 protease active site inhibitors are a key part of antiretroviral therapy, though resistance can evolve rendering therapy ineffective. Protease inhibitor resistance typically starts with primary mutations around the active site, which reduces inhibitor binding, protease affinity for substrate cleavage site residues P4-P4′, and viral replication. This is often followed by secondary mutations in the protease substrate-grooves which restore viral replication by increasing protease affinity for cleavage site residues P12-P5/P5′-P12′, while maintaining resistance. However, mutations in Gag alone can also result in resistance. The Gag resistance mutations can occur in cleavage sites (P12-P12′) to increase PR binding, as well as at non-cleavage sites. Here we show in silico that Gag non-cleavage site protease inhibitor resistance mutations can stabilize protease binding to Gag cleavage sites which contain structured subdomains on both sides: SP1/NC, SP2/p6, and MA/CA. The Gag non-cleavage site resistance mutations coordinated a network of H-bond interactions between the adjacent structured subdomains of the Gag substrates to form a substrate-clamp around the protease bound to cleavage site residues P12-P12′. The substrate-clamp likely slows protease disassociation from the substrate, restoring the cleavage rate in the presence of the inhibitor. Native Gag substrates can also form somewhat weaker substrate-clamps. This explains the 350-fold slower cleavage rate for the Gag CA/SP1 cleavage site in that the CA-SP1 substrate lacks structured subdomains on both sides of the cleavage site, and so cannot form a substrate-clamp around the PR.

Caspase-9 Activation of Procaspase-3 but Not Procaspase-6 Is Based on the Local Context of Cleavage Site Motifs and on Sequence.

Studying the interactions between a protease and its protein substrates at a molecular level is crucial for identifying the factors facilitating selection of particular proteolytic substrates and not others. These selection criteria include both the sequence and the local context of the substrate cleavage site where the active site of the protease initially binds and then performs proteolytic cleavage. Caspase-9, an initiator of the intrinsic apoptotic pathway, mediates activation of executioner procaspase-3 by cleavage of the intersubunit linker (ISL) at site 172IETD↓S. Although procaspase-6, another executioner, possesses two ISL cleavage sites (site 1, 176DVVD↓N; site 2, 190TEVD↓A), neither is directly cut by caspase-9. Thus, caspase-9 directly activates procaspase-3 but not procaspase-6. To elucidate this selectivity of caspase-9, we engineered constructs of procaspase-3 (e.g., swapping the ISL site, 172IETD↓S, with DVVDN and TEVDA) and procaspase-6 (e.g., swapping site 1, 176DVVD↓N, and site 2, 190TEVD↓A, with IETDS). Using the substrate digestion data of these constructs, we show here that the P4-P1' sequence of procaspase-6 ISL site 1 (DVVDN) can be accessed but not cleaved by caspase-9. We also found that caspase-9 can recognize the P4-P1' sequence of procaspase-6 ISL site 2 (TEVDA); however, the local context of this cleavage site is the critical factor that prevents proteolytic cleavage. Overall, our data have demonstrated that both the sequence and the local context of the ISL cleavage sites play a vital role in preventing the activation of procaspase-6 directly by caspase-9.

Structure of the multiple functional domains from coronavirus nonstructural protein 3

ABSTRACT Coronaviruses (CoVs) are potential pandemic pathogens that can infect a variety of hosts and cause respiratory, enteric, hepatic and neurological diseases. Nonstructural protein 3 (nsp3), an essential component of the replication/transcription complex, is one of the most important antiviral targets. Here, we report the first crystal structure of multiple functional domains from porcine delta-coronavirus (PDCoV) nsp3, including the macro domain (Macro), ubiquitin-like domain 2 (Ubl2) and papain-like protease (PLpro) catalytic domain. In the asymmetric unit, two of the subunits form the head-to-tail homodimer with an interaction interface between Macro and PLpro. However, PDCoV Macro-Ubl2-PLpro mainly exists as a monomer in solution. Then, we conducted fluorescent resonance energy transfer-based protease assays and found that PDCoV PLpro can cleave a peptide by mimicking the cognate nsp2/nsp3 cleavage site in peptide substrates and exhibits deubiquitinating and de-interferon stimulated gene(deISGylating) activities by hydrolysing ubiquitin-7-amino-4-methylcoumarin (Ub-AMC) and ISG15-AMC substrates. Moreover, the deletion of Macro or Macro-Ubl2 decreased the enzyme activity of PLpro, indicating that Macro and Ubl2 play important roles in maintaining the stability of the PLpro domain. Two active sites of PLpro, Cys260 and His398, were determined; unexpectedly, the conserved site Asp412 was not the third active site. Furthermore, the motif “NGYDT” (amino acids 409–413) was important for stabilizing the enzyme activity of PLpro, and the N409A mutant significantly decreased the enzyme activity of PLpro. These results provide novel insights into the replication mechanism of CoV and new clues for future drug design.

A computer-simulated mechanism of familial Alzheimer’s disease: Mutations enhance thermal dynamics and favor looser substrate-binding to γ-secretase

The 4-subunit intramembrane protease complex γ-secretase cleaves many substrates including fragments of the β-amyloid precursor protein (APP), leading to formation of Aβ peptides, and Notch. Mutations in APP and the catalytic subunit of γ-secretase, presenilin, cause familial Alzheimer’s disease (fAD). Mutations are assumed to change the substrate-binding and cleavage and thereby the Aβ formed. Whereas a wild-type structure of substrate-bound γ-secretase became recently available from cryogenic electron microscopy (6IYC), the structure and dynamics of mutant proteins remain obscure. Here, we studied five prominent mutants of substrate-bound γ-secretase by explicit all-atom molecular dynamics in a phospholipid membrane model at physiological temperature using the experimental structure as template: The presenilin 1 mutants E280A, G384A, A434C, and L435F and the V717I mutant of APP. Our structures and dynamics provide the first atomic detail into how fAD-causing mutations affect substrate binding to γ-secretase. The pathogenic mutations tend to increase the space and variability in the substrate binding site, as seen e.g. from the distance from catalytic aspartate to substrate cleavage sites. We suggest that we have identified the molecular cause of the “imprecise cleavage” that leads to two trimming pathways in γ-secretase, consistent with the FIST model, which may rationalize the experimental Aβ42/Aβ40 ratios as a molecular basis for fAD.

How to use the MEROPS database and website to help understand peptidase specificity

The MEROPS website (https://www.ebi.ac.uk/merops) and database was established in 1996 to present the classification and nomenclature of proteolytic enzymes. This was expanded to include a classification of protein inhibitors of proteolytic enzymes in 2004. Each peptidase or inhibitor is assigned to a distinct identifier, based on its biochemical and biological properties, and homologous sequences are assembled into a family. Families in which the proteins share similar tertiary structures are assembled into a clan. The MEROPS classification is thus a hierarchy with at least three levels (protein‐species, family, and clan) showing the evolutionary relationship. Several other data collections have been assembled, which are accessed from all levels in the hierarchy. These include, sequence homologs, selective bibliographies, substrate cleavage sites, peptidase–inhibitor interactions, alignments, and phylogenetic trees. The substrate cleavage collection has been assembled from the literature and includes physiological, pathological, and nonphysiological cleavages in proteins, peptides, and synthetic substrates. In this article, we make recommendations about how best to analyze these data and show analyses to indicate peptidase binding site preferences and exclusions. We also identify peptidases where co‐operative binding occurs between adjacent binding sites.

Distance dependent shedding of IL-6R

Proteolytic processing of membrane proteins by A disintegrin and metalloprotease-17 (ADAM17) is a key regulatory step in many physiological and pathophysiological processes. This so-called shedding is essential for development, regeneration and immune defense. An uncontrolled ADAM17 activity promotes cancer development, chronic inflammation and autoimmune diseases. Consequently, the ADAM17 activity is tightly regulated. As a final trigger for the shedding event a phosphatidylserine (PS) flip to the outer leaflet of the cell membrane was recently described. PS interacts with the extracellular part of ADAM17, which results in the shedding event by shifting the catalytic domain towards the membrane close to the cleavage sites within ADAM17 substrates. Our data indicate that the intrinsic proteolytic activity of the catalytic domain is prerequisite for the shedding activity and constantly present. However, the accessibility for substrate cleavage sites is controlled on several levels. In this report, we demonstrate that the positioning of the catalytic domain towards the cleavage sites is a crucial part of the shedding process. This finding contributes to the understanding of the complex and multilayered regulation of ADAM17 at the cell surface.

Procleave: Predicting Protease-specific Substrate Cleavage Sites by Combining Sequence and Structural Information

Proteases are enzymes that cleave and hydrolyse the peptide bonds between two specific amino acid residues of target substrate proteins. Protease-controlled proteolysis plays a key role in the degradation and recycling of proteins, which is essential for various physiological processes. Thus, solving the substrate identification problem will have important implications for the precise understanding of functions and physiological roles of proteases, as well as for therapeutic target identification and pharmaceutical applicability. Consequently, there is a great demand for bioinformatics methods that can predict novel substrate cleavage events with high accuracy by utilizing both sequence and structural information. In this study, we present Procleave, a novel bioinformatics approach for predicting protease-specific substrates and specific cleavage sites by taking into account both their sequence and 3D structural information. Structural features of known cleavage sites were represented by discrete values using a LOWESS data-smoothing optimization method, which turned out to be critical for the performance of Procleave. The optimal approximations of all structural parameter values were encoded in a conditional random field (CRF) computational framework, alongside sequence and chemical group-based features. Here, we demonstrate the outstanding performance of Procleave through extensive benchmarking and independent tests. Procleave is capable of correctly identifying most cleavage sites in the case study. Importantly, when applied to the human structural proteome encompassing 17,628 protein structures, Procleave suggests a number of potential novel target substrates and their corresponding cleavage sites of different proteases. Procleave is implemented as a webserver and is freely accessible at http://procleave.erc.monash.edu/.

Elucidation of degradation pattern and immobilization of a novel alginate lyase for preparation of alginate oligosaccharides

Alginate lyases are important enzymes to prepare alginate oligosaccharides for industrial applications and elucidating the degradation pattern of alginate lyases is essential for expanding their applications. Herein, we cloned and expressed AlyPL6, a novel member of polysaccharide lyase family-6 (PL6) with high activity from Pedobacter hainanensis NJ-02. It was found that AlyPL6 could recognize tetrasaccharide as the minimal substrate to release oligosaccharides with low degrees of polymerization (DPs). As a result, it could be speculated that the cleavage site of substrate is located between −1 and +1 subsites. For further application, AlyPL6 was then immobilized onto mesoporous titanium oxide particles (MTOPs) with >55.4% of maximal activity retained at 45 °C after it was reused for 10 times. The research provided extended insights into the substrate recognition and degradation pattern of PL 6 alginate lyases, which may benefit the further application of alginate lyases a lot.

DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites.

Proteases are enzymes that cleave target substrate proteins by catalyzing the hydrolysis of peptide bonds between specific amino acids. While the functional proteolysis regulated by proteases plays a central role in the 'life and death' cellular processes, many of the corresponding substrates and their cleavage sites were not found yet. Availability of accurate predictors of the substrates and cleavage sites would facilitate understanding of proteases' functions and physiological roles. Deep learning is a promising approach for the development of accurate predictors of substrate cleavage events. We propose DeepCleave, the first deep learning-based predictor of protease-specific substrates and cleavage sites. DeepCleave uses protein substrate sequence data as input and employs convolutional neural networks with transfer learning to train accurate predictive models. High predictive performance of our models stems from the use of high-quality cleavage site features extracted from the substrate sequences through the deep learning process, and the application of transfer learning, multiple kernels and attention layer in the design of the deep network. Empirical tests against several related state-of-the-art methods demonstrate that DeepCleave outperforms these methods in predicting caspase and matrix metalloprotease substrate-cleavage sites. The DeepCleave webserver and source code are freely available at http://deepcleave.erc.monash.edu/. Supplementary data are available at Bioinformatics online.

Revealing favorable and unfavorable residues in cooperative positions in protease cleavage sites

Proteases play critical roles in a wide variety of fundamental biological functions, and numerous protease inhibitors have been developed to treat various diseases including cancer. A wide range of experimental and computational methods have been developed to investigate the specificity and catalytic mechanisms of proteases. However, these methods only focused on the preferences of a single position around a cleavage site in a substrate, rarely on the compositionality of the subsites. We present new methods to quantify the specificity of proteases by considering the combinatorial patterns of amino acid residuals of cleavage sites in substrates. By incorporating the preference at positions, we modeled three types of favorable combinations of residues in cleavage sites. Moreover, by constructing a relationship weight matrix of residues between two positions, we can easily identify unfavorable combinations of residues at the positions. Applying these methods to a set of known cleavage sites of proteases, we revealed numerous favorable and unfavorable residues in cooperative positions in the protease cleavage sites. The results can help understand the specificity and catalytic mechanisms of proteases. To our knowledge, this is the first study that quantifies unfavorable combinations of amino acids between two sites. Furthermore, this method is not limited to the study of proteases and cleavage sites, and can be generalized to uncover the relationships of residues at meaningful sites in other proteins.

LabCaS for Ranking Potential Calpain Substrate Cleavage Sites from Amino Acid Sequence.

Calpains are a family of Ca2+-dependent cysteine proteases involved in many important biological processes, where they selectively cleave relevant substrates at specific cleavage sites to regulate the function of the substrate proteins. Presently, our knowledge about the function of calpains and the mechanism of substrate cleavage is still limited due to the fact that the experimental determination and validation on calpain bindings are usually laborious and expensive. This chapter describes LabCaS, an algorithm that is designed for predicting the calpain substrate cleavage sites from amino acid sequences. LabCaS is built on a conditional random field (CRF) statistic model, which trains the cleavage site prediction on multiple features of amino acid residue preference, solvent accessibility information, pair-wise alignment similarity score, secondary structure propensity, and physical-chemistry properties. Large-scale benchmark tests have shown that LabCaS can achieve a reliable recognition of the cleavage sites for most calpain proteins with an average AUC score of 0.862. Due to the fast speed and convenience of use, the protocol should find its usefulness in large-scale calpain-based function annotations of the newly sequenced proteins. The online web server of LabCaS is freely available at http://www.csbio.sjtu.edu.cn/bioinf/LabCaS .

In vivo cleavage rules and target repertoire of RNase III in Escherichia coli.

Bacterial RNase III plays important roles in the processing and degradation of RNA transcripts. A major goal is to identify the cleavage targets of this endoribonuclease at a transcriptome-wide scale and delineate its in vivo cleavage rules. Here we applied to Escherichia coli grown to either exponential or stationary phase a tailored RNA-seq-based technology, which allows transcriptome-wide mapping of RNase III cleavage sites at a nucleotide resolution. Our analysis of the large-scale in vivo cleavage data substantiated the established cleavage pattern of a double cleavage in an intra-molecular stem structure, leaving 2-nt-long 3′ overhangs, and refined the base-pairing preferences in the cleavage site vicinity. Intriguingly, we observed that the two stem positions between the cleavage sites are highly base-paired, usually involving at least one G-C or C-G base pair. We present a clear distinction between intra-molecular stem structures that are RNase III substrates and intra-molecular stem structures randomly selected across the transcriptome, emphasizing the in vivo specificity of RNase III. Our study provides a comprehensive map of the cleavage sites in both intra-molecular and inter-molecular duplex substrates, providing novel insights into the involvement of RNase III in post-transcriptional regulation in the bacterial cell.