Genome-wide bioinformatics analysis of human protease capacity for proteolytic cleavage of the SARS-CoV-2 spike glycoprotein.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) primarily enters the cell by binding the virus's spike (S) glycoprotein to the angiotensin-converting enzyme 2 receptor on the cell surface, followed by proteolytic cleavage by host proteases. Studies have identified furin and transmembrane protease serine 2 proteases in priming and triggering cleavages of the S glycoprotein, converting it into a fusion-competent form and initiating membrane fusion, respectively. Alternatively, SARS-CoV-2 can enter the cell through the endocytic pathway, where activation is triggered by lysosomal cathepsin L. However, other proteases are also suspected to be involved in both entry routes. In this study, we conducted a genome-wide bioinformatics analysis to explore the capacity of human proteases in hydrolyzing peptide bonds of the S glycoprotein. Predictive models of sequence specificity for 169 human proteases were constructed and applied to the S glycoprotein together with the method for predicting structural susceptibility to proteolysis of protein regions. After validating our approach on extensively studied S2' and S1/S2 cleavage sites, we applied our method to each peptide bond of the S glycoprotein across all 169 proteases. Our results indicate that various members of the proprotein convertase subtilisin/kexin type, type II transmembrane family serine protease, and kallikrein families, as well as specific coagulation factors, are capable of cleaving S2' or S1/S2 sites. We have also identified a potential cleavage site of cathepsin L at the K790 position within the S2' loop. Structural analysis suggests that cleavage of this site induces conformational changes similar to the cleavage at the R815 (S2') position, leading to the exposure of the fusion peptide and subsequent fusion with the membrane. Other potential cleavage sites and the influence of mutations in common SARS-CoV-2 variants on proteolytic efficiency are discussed.IMPORTANCEThe entry of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) into the cell, activated by host proteases, is considerably more complex in coronaviruses than in most other viruses and is not fully understood. There is evidence that other proteases beyond the known furin and transmembrane protease serine 2 can activate the spike protein. Another example of uncertainty is the cleavage site for the alternative endocytic route of SARS-CoV-2 entrance, which is still unknown. Bioinformatics methods, modeling protease specificity and estimating the structural susceptibility of protein regions to proteolysis, can aid in studying this topic by predicting the involved proteases and their cleavage sites, thereby substantially reducing the amount of experimental work. Elucidating the mechanisms of spike protein activation is crucial for preventing possible future coronavirus pandemics and developing antiviral drugs.

Bioactive glycans in a microbiome-directed food for children with malnutrition.

Evidence is accumulating that perturbed postnatal development of the gut microbiome contributes to childhood malnutrition1-4. Here we analyse biospecimens from a randomized, controlled trial of a microbiome-directed complementary food (MDCF-2) that produced superior rates of weight gain compared with a calorically more dense conventional ready-to-use supplementary food in 12-18-month-old Bangladeshi children with moderate acute malnutrition4. We reconstructed 1,000 bacterial genomes (metagenome-assembled genomes (MAGs)) from the faecal microbiomes of trial participants, identified 75 MAGs of which the abundances were positively associated with ponderal growth (change in weight-for-length Z score (WLZ)), characterized changes in MAG gene expression as a function of treatment type and WLZ response, and quantified carbohydrate structures in MDCF-2 and faeces. The results reveal that two Prevotella copri MAGs that are positively associated with WLZ are the principal contributors to MDCF-2-induced expression of metabolic pathways involved in utilizing the component glycans of MDCF-2. The predicted specificities of carbohydrate-active enzymes expressed by their polysaccharide-utilization loci are correlated with (1) the in vitro growth of Bangladeshi P. copri strains, possessing varying degrees of polysaccharide-utilization loci and genomic conservation with these MAGs, in defined medium containing different purified glycans representative of those in MDCF-2, and (2) the levels of faecal carbohydrate structures in the trial participants. These associations suggest that identifying bioactive glycan structures in MDCFs metabolized by growth-associated bacterial taxa will help to guide recommendations about their use in children with acute malnutrition and enable the development of additional formulations.

Bioactive glycans in a microbiome-directed food for malnourished children.

Evidence is accumulating that perturbed postnatal development of the gut microbiome contributes to childhood malnutrition1-4. Designing effective microbiome-directed therapeutic foods to repair these perturbations requires knowledge about how food components interact with the microbiome to alter its expressed functions. Here we use biospecimens from a randomized, controlled trial of a microbiome-directed complementary food prototype (MDCF-2) that produced superior rates of weight gain compared to a conventional ready-to-use supplementary food (RUSF) in 12-18-month-old Bangladeshi children with moderate acute malnutrition (MAM)4. We reconstructed 1000 bacterial genomes (metagenome-assembled genomes, MAGs) present in their fecal microbiomes, identified 75 whose abundances were positively associated with weight gain (change in weight-for-length Z score, WLZ), characterized gene expression changes in these MAGs as a function of treatment type and WLZ response, and used mass spectrometry to quantify carbohydrate structures in MDCF-2 and feces. The results reveal treatment-induced changes in expression of carbohydrate metabolic pathways in WLZ-associated MAGs. Comparing participants consuming MDCF-2 versus RUSF, and MDCF-2-treated children in the upper versus lower quartiles of WLZ responses revealed that two Prevotella copri MAGs positively associated with WLZ were principal contributors to MDCF-2-induced expression of metabolic pathways involved in utilization of its component glycans. Moreover, the predicted specificities of carbohydrate active enzymes expressed by polysaccharide utilization loci (PULs) in these two MAGs correlate with the (i) in vitro growth of Bangladeshi P. copri strains, possessing differing degrees of PUL and overall genomic content similarity to these MAGs, cultured in defined medium containing different purified glycans representative of those in MDCF-2, and (ii) levels of carbohydrate structures identified in feces from clinical trial participants. In the accompanying paper5, we use a gnotobiotic mouse model colonized with age- and WLZ-associated bacterial taxa cultured from this study population, and fed diets resembling those consumed by study participants, to directly test the relationship between P. copri, MDCF-2 glycan metabolism, host ponderal growth responses, and intestinal gene expression and metabolism. The ability to identify bioactive glycan structures in MDCFs that are metabolized by growth-associated bacterial taxa will help guide recommendations about use of this MDCF for children with acute malnutrition representing different geographic locales and ages, as well as enable development of bioequivalent, or more efficacious, formulations composed of culturally acceptable and affordable ingredients.

Predicting Structural Susceptibility of Proteins to Proteolytic Processing.

The importance of 3D protein structure in proteolytic processing is well known. However, despite the plethora of existing methods for predicting proteolytic sites, only a few of them utilize the structural features of potential substrates as predictors. Moreover, to our knowledge, there is currently no method available for predicting the structural susceptibility of protein regions to proteolysis. We developed such a method using data from CutDB, a database that contains experimentally verified proteolytic events. For prediction, we utilized structural features that have been shown to influence proteolysis in earlier studies, such as solvent accessibility, secondary structure, and temperature factor. Additionally, we introduced new structural features, including length of protruded loops and flexibility of protein termini. To maximize the prediction quality of the method, we carefully curated the training set, selected an appropriate machine learning method, and sampled negative examples to determine the optimal positive-to-negative class size ratio. We demonstrated that combining our method with models of protease primary specificity can outperform existing bioinformatics methods for the prediction of proteolytic sites. We also discussed the possibility of utilizing this method for bioinformatics prediction of other post-translational modifications.

Glycidamide-induced hypermutation in yeast single-stranded DNA reveals a ubiquitous clock-like mutational motif in humans.

Mutagens often prefer specific nucleotides or oligonucleotide motifs that can be revealed by studying the hypermutation spectra in single-stranded (ss) DNA. We utilized a yeast model to explore mutagenesis by glycidamide, a simple epoxide formed endogenously in humans from the environmental toxicant acrylamide. Glycidamide caused ssDNA hypermutation in yeast predominantly in cytosines and adenines. The most frequent mutations in adenines occurred in the nAt→nGt trinucleotide motif. Base substitutions A→G in this motif relied on Rev1 translesion polymerase activity. Inactivating Rev1 did not alter the nAt trinucleotide preference, suggesting it may be an intrinsic specificity of the chemical reaction between glycidamide and adenine in the ssDNA. We found this mutational motif enriched in published sequencing data from glycidamide-treated mouse cells and ubiquitous in human cancers. In cancers, this motif was positively correlated with the single base substitution (SBS) smoking-associated SBS4 signature, with the clock-like signatures SBS1, SBS5, and was strongly correlated with smoking history and with age of tumor donors. Clock-like feature of the motif was also revealed in cells of human skin and brain. Given its pervasiveness, we propose that this mutational motif reflects mutagenic lesions to adenines in ssDNA from a potentially broad range of endogenous and exogenous agents.

APOBEC mutagenesis is low in most types of non-B DNA structures.

While somatic mutations are known to be enriched in genome regions with non-canonical DNA secondary structure, the impact of particular mutagens still needs to be elucidated. Here, we demonstrate that in human cancers, the APOBEC mutagenesis is not enriched in direct repeats, mirror repeats, short tandem repeats, and G-quadruplexes, and even decreased below its level in B-DNA for cancer samples with very high APOBEC activity. In contrast, we observe that the APOBEC-induced mutational density is positively associated with APOBEC activity in inverted repeats (cruciform structures), where the impact of cytosine at the 3'-end of the hairpin loop is substantial. Surprisingly, the APOBEC-signature mutation density per TC motif in the single-stranded DNA of a G-quadruplex (G4) is lower than in the four-stranded part of G4 and in B-DNA. The APOBEC mutagenesis, as well as the UV-mutagenesis in melanoma samples, are absent in Z-DNA regions, owing to the depletion of their mutational signature motifs.

Analysis of gene expression and mutation data points on contribution of transcription to the mutagenesis by APOBEC enzymes.

Since the discovery of the role of the APOBEC enzymes in human cancers, the mechanisms of this type of mutagenesis remain little understood. Theoretically, targeting of single-stranded DNA by the APOBEC enzymes could occur during cellular processes leading to the unwinding of DNA double-stranded structure. Some evidence points to the importance of replication in the APOBEC mutagenesis, while the role of transcription is still underexplored. Here, we analyzed gene expression and whole genome sequencing data from five types of human cancers with substantial APOBEC activity to estimate the involvement of transcription in the APOBEC mutagenesis and compare its impact with that of replication. Using the TCN motif as the mutation signature of the APOBEC enzymes, we observed a correlation of active APOBEC mutagenesis with gene expression, confirmed the increase of APOBEC-induced mutations in early-replicating regions and estimated the relative impact of transcription and replication on the APOBEC mutagenesis. We also found that the known effect of higher density of APOBEC-induced mutations on the lagging strand was highest in middle-replicating regions and observed higher APOBEC mutation density on the sense strand, the latter bias positively correlated with the gene expression level.

Predictive models of protease specificity based on quantitative protease-activity profiling data.

Bioinformatics-based prediction of protease substrates can help to elucidate regulatory proteolytic pathways that control a broad range of biological processes such as apoptosis and blood coagulation. The majority of published predictive models are position weight matrices (PWM) reflecting specificity of proteases toward target sequence. These models are typically derived from experimental data on positions of hydrolyzed peptide bonds and show a reasonable predictive power. New emerging techniques that not only register the cleavage position but also measure catalytic efficiency of proteolysis are expected to improve the quality of predictions or at least substantially reduce the number of tested substrates required for confident predictions. The main goal of this study was to develop new prediction models based on such data and to estimate the performance of the constructed models. We used data on catalytic efficiency of proteolysis measured for eight major human matrix metalloproteinases to construct predictive models of protease specificity using a variety of regression analysis techniques. The obtained results suggest that efficiency-based (quantitative) models show a comparable performance with conventional PWM-based algorithms, while less training data are required. The derived list of candidate cleavage sites in human secreted proteins may serve as a starting point for experimental analysis.

Comparative immunogenicity and structural analysis of epitopes of different bacterial L-asparaginases.

BACKGROUND: E.coli type II L-asparaginase is widely used for treatment of acute lymphoblastic leukemia. However, serious side effects such as allergic or hypersensitivity reactions are common for L-asparaginase treatment. Methods for minimizing immune response on L-asparaginase treatment in human include bioengeneering of less immunogenic version of the enzyme or utilizing the homologous enzymes of different origin. To rationalize these approaches we compared immunogenicity of L-asparaginases from five bacterial organisms and performed sequence-structure analysis of the presumable epitope regions. METHODS: IgG and IgM immune response in C57B16 mice after immunization with Wollinella succinogenes type II (WsA), Yersinia pseudotuberculosis type II (YpA), Erwinia carotovora type II (EwA), and Rhodospirillum rubrum type I (RrA) and Escherichia coli type II (EcA) L-asparaginases was evaluated using standard ELISA method. The comparative bioinformatics analysis of structure and sequence of the bacterial L-asparaginases presumable epitope regions was performed. RESULTS: We showed different immunogenic properties of five studied L-asparaginases and confirmed the possibility of replacement of EcA with L-asparaginase from different origin as a second-line treatment. Studied L-asparaginases might be placed in the following order based on the immunogenicity level: YpA > RrA, WsA ≥ EwA > EcA. Most significant cross-immunogenicity was shown between EcA and YpA. We propose that a long N-terminus of YpA enzyme enriched with charged aminoacids and tryptophan could be a reason of higher immunogenicity of YpA in comparison with other considered enzymes. Although the recognized structural and sequence differences in putative epitope regions among five considered L-asparaginases does not fully explain experimental observation of the immunogenicity of the enzymes, the performed analysis set the foundation for further research in this direction. CONCLUSIONS: The performed studies showed different immunogenic properties of L-asparaginases and confirmed the possibility of replacement of EcA with L-asparaginase from different origin. The preferable enzymes for the second line treatment are WsA, RrA, or EwA.

APOBEC-Induced Cancer Mutations Are Uniquely Enriched in Early-Replicating, Gene-Dense, and Active Chromatin Regions.

An antiviral component of the human innate immune system-the APOBEC cytidine deaminases-was recently identified as a prominent source of mutations in cancers. Here, we investigated the distribution of APOBEC-induced mutations across the genomes of 119 breast and 24 lung cancer samples. While the rate of most mutations is known to be elevated in late-replicating regions that are characterized by reduced chromatin accessibility and low gene density, we observed a marked enrichment of APOBEC mutations in early-replicating regions. This unusual mutagenesis profile may be associated with a higher propensity to form single-strand DNA substrates for APOBEC enzymes in early-replicating regions and should be accounted for in statistical analyses of cancer genome mutation catalogs aimed at understanding the mechanisms of carcinogenesis as well as highlighting genes that are significantly mutated in cancer.

Horizontal gene transfer and genome evolution in Methanosarcina.

BACKGROUND: Genomes of Methanosarcina spp. are among the largest archaeal genomes. One suggested reason for that is massive horizontal gene transfer (HGT) from bacteria. Genes of bacterial origin may be involved in the central metabolism and solute transport, in particular sugar synthesis, sulfur metabolism, phosphate metabolism, DNA repair, transport of small molecules etc. Horizontally transferred (HT) genes are considered to play the key role in the ability of Methanosarcina spp. to inhabit diverse environments. At the moment, genomes of three Methanosarcina spp. have been sequenced, and while these genomes vary in length and number of protein-coding genes, they all have been shown to accumulate HT genes. However, previous estimates had been made when fewer archaeal genomes were known. Moreover, several Methanosarcinaceae genomes from other genera have been sequenced recently. Here, we revise the census of genes of bacterial origin in Methanosarcinaceae. RESULTS: About 5% of Methanosarcina genes have been shown to be horizontally transferred from various bacterial groups to the last common ancestor either of Methanosarcinaceae, or Methanosarcina, or later in the evolution. Simulation of the composition of the NCBI protein non-redundant database for different years demonstrates that the estimates of the HGT rate have decreased drastically since 2002, the year of publication of the first Methanosarcina genome. The phylogenetic distribution of HT gene donors is non-uniform. Most HT genes were transferred from Firmicutes and Proteobacteria, while no HGT events from Actinobacteria to the common ancestor of Methanosarcinaceae were found. About 50% of HT genes are involved in metabolism. Horizontal transfer of transcription factors is not common, while 46% of horizontally transferred genes have demonstrated differential expression in a variety of conditions. HGT of complete operons is relatively infrequent and half of HT genes do not belong to operons. CONCLUSIONS: While genes of bacterial origin are still more frequent in Methanosarcinaceae than in other Archaea, most HGT events described earlier as Methanosarcina-specific seem to have occurred before the divergence of Methanosarcinaceae. Genes horizontally transferred from bacteria to archaea neither tend to be transferred with their regulators, nor in long operons.

CleavPredict: A Platform for Reasoning about Matrix Metalloproteinases Proteolytic Events.

CleavPredict (http://cleavpredict.sanfordburnham.org) is a Web server for substrate cleavage prediction for matrix metalloproteinases (MMPs). It is intended as a computational platform aiding the scientific community in reasoning about proteolytic events. CleavPredict offers in silico prediction of cleavage sites specific for 11 human MMPs. The prediction method employs the MMP specific position weight matrices (PWMs) derived from statistical analysis of high-throughput phage display experimental results. To augment the substrate cleavage prediction process, CleavPredict provides information about the structural features of potential cleavage sites that influence proteolysis. These include: secondary structure, disordered regions, transmembrane domains, and solvent accessibility. The server also provides information about subcellular location, co-localization, and co-expression of proteinase and potential substrates, along with experimentally determined positions of single nucleotide polymorphism (SNP), and posttranslational modification (PTM) sites in substrates. All this information will provide the user with perspectives in reasoning about proteolytic events. CleavPredict is freely accessible, and there is no login required.

Mycobacterial nicotinate mononucleotide adenylyltransferase: structure, mechanism, and implications for drug discovery.

Nicotinate mononucleotide adenylyltransferase NadD is an essential enzyme in the biosynthesis of the NAD cofactor, which has been implicated as a target for developing new antimycobacterial therapies. Here we report the crystal structure of Mycobacterium tuberculosis NadD (MtNadD) at a resolution of 2.4 Å. A remarkable new feature of the MtNadD structure, compared with other members of this enzyme family, is a 310 helix that locks the active site in an over-closed conformation. As a result, MtNadD is rendered inactive as it is topologically incompatible with substrate binding and catalysis. Directed mutagenesis was also used to further dissect the structural elements that contribute to the interactions of the two MtNadD substrates, i.e. ATP and nicotinic acid mononucleotide (NaMN). For inhibitory profiling of partially active mutants and wild type MtNadD, we used a small molecule inhibitor of MtNadD with moderate affinity (Ki ∼ 25 µM) and antimycobacterial activity (MIC80) ∼ 40-80 µM). This analysis revealed interferences with some of the residues in the NaMN binding subsite consistent with the competitive inhibition observed for the NaMN substrate (but not ATP). A detailed steady-state kinetic analysis of MtNadD suggests that ATP must first bind to allow efficient NaMN binding and catalysis. This sequential mechanism is consistent with the requirement of transition to catalytically competent (open) conformation hypothesized from structural modeling. A possible physiological significance of this mechanism is to enable the down-regulation of NAD synthesis under ATP-limiting dormancy conditions. These findings point to a possible new strategy for designing inhibitors that lock the enzyme in the inactive over-closed conformation.

Sequence and conformational specificity in substrate recognition: several human Kunitz protease inhibitor domains are specific substrates of mesotrypsin.

Mesotrypsin is an isoform of trypsin that is uniquely resistant to polypeptide trypsin inhibitors and can cleave some inhibitors rapidly. Previous studies have shown that the amyloid precursor protein Kunitz protease inhibitor domain (APPI) is a specific substrate of mesotrypsin and that stabilization of the APPI cleavage site in a canonical conformation contributes to recognition by mesotrypsin. We hypothesized that other proteins possessing potential cleavage sites stabilized in a similar conformation might also be mesotrypsin substrates. Here we evaluated a series of candidate substrates, including human Kunitz protease inhibitor domains from amyloid precursor-like protein 2 (APLP2), bikunin, hepatocyte growth factor activator inhibitor type 2 (HAI2), tissue factor pathway inhibitor-1 (TFPI1), and tissue factor pathway inhibitor-2 (TFPI2), as well as E-selectin, an unrelated protein possessing a potential cleavage site displaying canonical conformation. We find that Kunitz domains within APLP2, bikunin, and HAI2 are cleaved by mesotrypsin with kinetic profiles of specific substrates. TFPI1 and TFPI2 Kunitz domains are cleaved less efficiently by mesotrypsin, and E-selectin is not cleaved at the anticipated site. Cocrystal structures of mesotrypsin with HAI2 and bikunin Kunitz domains reveal the mode of mesotrypsin interaction with its canonical substrates. Our data suggest that major determinants of mesotrypsin substrate specificity include sequence preferences at the P1 and P'2 positions along with conformational stabilization of the cleavage site in the canonical conformation. Mesotrypsin up-regulation has been implicated previously in cancer progression, and proteolytic clearance of Kunitz protease inhibitors offers potential mechanisms by which mesotrypsin may mediate pathological effects in cancer.

Characterization of bacterial NMN deamidase as a Ser/Lys hydrolase expands diversity of serine amidohydrolases.

NMN deamidase (PncC) is a bacterial enzyme involved in NAD biosynthesis. We have previously demonstrated that PncC is structurally distinct from other known amidohydrolases. Here, we extended PncC characterization by mutating all potential catalytic residues and assessing their individual roles in catalysis through kinetic analyses. Inspection of these residues' spatial arrangement in the active site, allowed us to conclude that PncC is a serine-amidohydrolase, employing a Ser/Lys dyad for catalysis. Analysis of the PncC structure in complex with a modeled NMN substrate supported our conclusion, and enabled us to propose the catalytic mechanism.

Evaluation and comparison of current fetal ultrasound image segmentation methods for biometric measurements: a grand challenge.

This paper presents the evaluation results of the methods submitted to Challenge US: Biometric Measurements from Fetal Ultrasound Images, a segmentation challenge held at the IEEE International Symposium on Biomedical Imaging 2012. The challenge was set to compare and evaluate current fetal ultrasound image segmentation methods. It consisted of automatically segmenting fetal anatomical structures to measure standard obstetric biometric parameters, from 2D fetal ultrasound images taken on fetuses at different gestational ages (21 weeks, 28 weeks, and 33 weeks) and with varying image quality to reflect data encountered in real clinical environments. Four independent sub-challenges were proposed, according to the objects of interest measured in clinical practice: abdomen, head, femur, and whole fetus. Five teams participated in the head sub-challenge and two teams in the femur sub-challenge, including one team who tackled both. Nobody attempted the abdomen and whole fetus sub-challenges. The challenge goals were two-fold and the participants were asked to submit the segmentation results as well as the measurements derived from the segmented objects. Extensive quantitative (region-based, distance-based, and Bland-Altman measurements) and qualitative evaluation was performed to compare the results from a representative selection of current methods submitted to the challenge. Several experts (three for the head sub-challenge and two for the femur sub-challenge), with different degrees of expertise, manually delineated the objects of interest to define the ground truth used within the evaluation framework. For the head sub-challenge, several groups produced results that could be potentially used in clinical settings, with comparable performance to manual delineations. The femur sub-challenge had inferior performance to the head sub-challenge due to the fact that it is a harder segmentation problem and that the techniques presented relied more on the femur's appearance.

Sequence-derived structural features driving proteolytic processing.

Proteolytic signaling, or regulated proteolysis, is an essential part of many important pathways such as Notch, Wnt, and Hedgehog. How the structure of the cleaved substrate regions influences the efficacy of proteolytic processing remains underexplored. Here, we analyzed the relative importance in proteolysis of various structural features derived from substrate sequences using a dataset of more than 5000 experimentally verified proteolytic events captured in CutDB. Accessibility to the solvent was recognized as an essential property of a proteolytically processed polypeptide chain. Proteolytic events were found nearly uniformly distributed among three types of secondary structure, although with some enrichment in loops. Cleavages in α-helices were found to be relatively abundant in regions apparently prone to unfolding, while cleavages in ß-structures tended to be located at the periphery of ß-sheets. Application of the same statistical procedures to proteolytic events divided into separate sets according to the catalytic classes of proteases proved consistency of the results and confirmed that the structural mechanisms of proteolysis are universal. The estimated prediction power of sequence-derived structural features, which turned out to be sufficiently high, presents a rationale for their use in bioinformatic prediction of proteolytic events.

RegPrecise 3.0--a resource for genome-scale exploration of transcriptional regulation in bacteria.

BACKGROUND: Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in prokaryotes is one of the critical tasks of modern genomics. Bacteria from different taxonomic groups, whose lifestyles and natural environments are substantially different, possess highly diverged transcriptional regulatory networks. The comparative genomics approaches are useful for in silico reconstruction of bacterial regulons and networks operated by both transcription factors (TFs) and RNA regulatory elements (riboswitches). DESCRIPTION: RegPrecise (http://regprecise.lbl.gov) is a web resource for collection, visualization and analysis of transcriptional regulons reconstructed by comparative genomics. We significantly expanded a reference collection of manually curated regulons we introduced earlier. RegPrecise 3.0 provides access to inferred regulatory interactions organized by phylogenetic, structural and functional properties. Taxonomy-specific collections include 781 TF regulogs inferred in more than 160 genomes representing 14 taxonomic groups of Bacteria. TF-specific collections include regulogs for a selected subset of 40 TFs reconstructed across more than 30 taxonomic lineages. Novel collections of regulons operated by RNA regulatory elements (riboswitches) include near 400 regulogs inferred in 24 bacterial lineages. RegPrecise 3.0 provides four classifications of the reference regulons implemented as controlled vocabularies: 55 TF protein families; 43 RNA motif families; ~150 biological processes or metabolic pathways; and ~200 effectors or environmental signals. Genome-wide visualization of regulatory networks and metabolic pathways covered by the reference regulons are available for all studied genomes. A separate section of RegPrecise 3.0 contains draft regulatory networks in 640 genomes obtained by an conservative propagation of the reference regulons to closely related genomes. CONCLUSIONS: RegPrecise 3.0 gives access to the transcriptional regulons reconstructed in bacterial genomes. Analytical capabilities include exploration of: regulon content, structure and function; TF binding site motifs; conservation and variations in genome-wide regulatory networks across all taxonomic groups of Bacteria. RegPrecise 3.0 was selected as a core resource on transcriptional regulation of the Department of Energy Systems Biology Knowledgebase, an emerging software and data environment designed to enable researchers to collaboratively generate, test and share new hypotheses about gene and protein functions, perform large-scale analyses, and model interactions in microbes, plants, and their communities.

Comparative genomics of metabolic capacities of regulons controlled by cis-regulatory RNA motifs in bacteria.

BACKGROUND: In silico comparative genomics approaches have been efficiently used for functional prediction and reconstruction of metabolic and regulatory networks. Riboswitches are metabolite-sensing structures often found in bacterial mRNA leaders controlling gene expression on transcriptional or translational levels.An increasing number of riboswitches and other cis-regulatory RNAs have been recently classified into numerous RNA families in the Rfam database. High conservation of these RNA motifs provides a unique advantage for their genomic identification and comparative analysis. RESULTS: A comparative genomics approach implemented in the RegPredict tool was used for reconstruction and functional annotation of regulons controlled by RNAs from 43 Rfam families in diverse taxonomic groups of Bacteria. The inferred regulons include ~5200 cis-regulatory RNAs and more than 12000 target genes in 255 microbial genomes. All predicted RNA-regulated genes were classified into specific and overall functional categories. Analysis of taxonomic distribution of these categories allowed us to establish major functional preferences for each analyzed cis-regulatory RNA motif family. Overall, most RNA motif regulons showed predictable functional content in accordance with their experimentally established effector ligands. Our results suggest that some RNA motifs (including thiamin pyrophosphate and cobalamin riboswitches that control the cofactor metabolism) are widespread and likely originated from the last common ancestor of all bacteria. However, many more analyzed RNA motifs are restricted to a narrow taxonomic group of bacteria and likely represent more recent evolutionary innovations. CONCLUSIONS: The reconstructed regulatory networks for major known RNA motifs substantially expand the existing knowledge of transcriptional regulation in bacteria. The inferred regulons can be used for genetic experiments, functional annotations of genes, metabolic reconstruction and evolutionary analysis. The obtained genome-wide collection of reference RNA motif regulons is available in the RegPrecise database (http://regprecise.lbl.gov/).