Marat D. Kazanov

RegPrecise 3.0 – A resource for genome-scale exploration of transcriptional regulation in bacteria

BackgroundGenome-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).DescriptionRegPrecise (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.ConclusionsRegPrecise 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 genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus

BackgroundGenome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in bacteria is one of the critical tasks of modern genomics. The Shewanella genus is comprised of metabolically versatile gamma-proteobacteria, whose lifestyles and natural environments are substantially different from Escherichia coli and other model bacterial species. The comparative genomics approaches and computational identification of regulatory sites are useful for the in silico reconstruction of transcriptional regulatory networks in bacteria.ResultsTo explore conservation and variations in the Shewanella transcriptional networks we analyzed the repertoire of transcription factors and performed genomics-based reconstruction and comparative analysis of regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors and their DNA binding sites, 8 riboswitches and 6 translational attenuators. Forty five regulons were newly inferred from the genome context analysis, whereas others were propagated from previously characterized regulons in the Enterobacteria and Pseudomonas spp.. Multiple variations in regulatory strategies between the Shewanella spp. and E. coli include regulon contraction and expansion (as in the case of PdhR, HexR, FadR), numerous cases of recruiting non-orthologous regulators to control equivalent pathways (e.g. PsrA for fatty acid degradation) and, conversely, orthologous regulators to control distinct pathways (e.g. TyrR, ArgR, Crp).ConclusionsWe tentatively defined the first reference collection of ~100 transcriptional regulons in 16 Shewanella genomes. The resulting regulatory network contains ~600 regulated genes per genome that are mostly involved in metabolism of carbohydrates, amino acids, fatty acids, vitamins, metals, and stress responses. Several reconstructed regulons including NagR for N-acetylglucosamine catabolism were experimentally validated in S. oneidensis MR-1. Analysis of correlations in gene expression patterns helps to interpret the reconstructed regulatory network. The inferred regulatory interactions will provide an additional regulatory constrains for an integrated model of metabolism and regulation in S. oneidensis MR-1.

Evolution of Pan-Genomes of Escherichia coli, Shigella spp., and Salmonella enterica

Multiple sequencing of genomes belonging to a bacterial species allows one to analyze and compare statistics and dynamics of the gene complements of species, their pan-genomes. Here, we analyzed multiple genomes of Escherichia coli, Shigella spp., and Salmonella enterica. We demonstrate that the distribution of the number of genomes harboring a gene is well approximated by a sum of two power functions, describing frequent genes (present in many strains) and rare genes (present in few strains). The virtual absence of Shigella-specific genes not present in E. coli genomes confirms previous observations that Shigella is not an independent genus. While the pan-genome size is increasing with each new strain, the number of genes present in a fixed fraction of strains stabilizes quickly. For instance, slightly fewer than 4,000 genes are present in at least half of any group of E. coli genomes. Comparison of S. enterica and E. coli pan-genomes revealed the existence of a common periphery, that is, genes present in some but not all strains of both species. Analysis of phylogenetic trees demonstrates that rare genes from the periphery likely evolve under horizontal transfer, whereas frequent periphery genes may have been inherited from the periphery genome of the common ancestor.

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 femurs appearance.

Functional Specialization in Proline Biosynthesis of Melanoma

Proline metabolism is linked to hyperprolinemia, schizophrenia, cutis laxa, and cancer. In the latter case, tumor cells tend to rely on proline biosynthesis rather than salvage. Proline is synthesized from either glutamate or ornithine; both are converted to pyrroline-5-carboxylate (P5C), and then to proline via pyrroline-5-carboxylate reductases (PYCRs). Here, the role of three isozymic versions of PYCR was addressed in human melanoma cells by tracking the fate of 13C-labeled precursors. Based on these studies we conclude that PYCR1 and PYCR2, which are localized in the mitochondria, are primarily involved in conversion of glutamate to proline. PYCRL, localized in the cytosol, is exclusively linked to the conversion of ornithine to proline. This analysis provides the first clarification of the role of PYCRs to proline biosynthesis.

Complete Genome and Proteome of Acholeplasma laidlawii

We present the complete genome sequence and proteogenomic map for Acholeplasma laidlawii PG-8A (class Mollicutes, order Acholeplasmatales, family Acholeplasmataceae). The genome of A. laidlawii is represented by a single 1,496,992-bp circular chromosome with an average G+C content of 31 mol%. This is the longest genome among the Mollicutes with a known nucleotide sequence. It contains genes of polymerase type I, SOS response, and signal transduction systems, as well as RNA regulatory elements, riboswitches, and T boxes. This demonstrates a significant capability for the regulation of gene expression and mutagenic response to stress. Acholeplasma laidlawii and phytoplasmas are the only Mollicutes known to use the universal genetic code, in which UGA is a stop codon. Within the Mollicutes group, only the sterol-nonrequiring Acholeplasma has the capacity to synthesize saturated fatty acids de novo. Proteomic data were used in the primary annotation of the genome, validating expression of many predicted proteins. We also detected posttranslational modifications of A. laidlawii proteins: phosphorylation and acylation. Seventy-four candidate phosphorylated proteins were found: 16 candidates are proteins unique to A. laidlawii, and 11 of them are surface-anchored or integral membrane proteins, which implies the presence of active signaling pathways. Among 20 acylated proteins, 14 contained palmitic chains, and six contained stearic chains. No residue of linoleic or oleic acid was observed. Acylated proteins were components of mainly sugar and inorganic ion transport systems and were surface-anchored proteins with unknown functions.

Structural determinants of limited proteolysis.

Limited or regulatory proteolysis plays a critical role in many important biological pathways like blood coagulation, cell proliferation, and apoptosis. A better understanding of mechanisms that control this process is required for discovering new proteolytic events and for developing inhibitors with potential therapeutic value. Two features that determine the susceptibility of peptide bonds to proteolysis are the sequence in the vicinity of the scissile bond and the structural context in which the bond is displayed. In this study, we assessed statistical significance and predictive power of individual structural descriptors and combination thereof for the identification of cleavage sites. The analysis was performed on a data set of >200 proteolytic events documented in CutDB for a variety of mammalian regulatory proteases and their physiological substrates with known 3D structures. The results confirmed the significance and provided a ranking within three main categories of structural features: exposure > flexibility > local interactions. Among secondary structure elements, the largest frequency of proteolytic cleavage was confirmed for loops and lower but significant frequency for helices. Limited proteolysis has lower albeit appreciable frequency of occurrence in certain types of β-strands, which is in contrast with some previous reports. Descriptors deduced directly from the amino acid sequence displayed only marginal predictive capabilities. Homology-based structural models showed a predictive performance comparable to protein substrates with experimentally established structures. Overall, this study provided a foundation for accurate automated prediction of segments of protein structure susceptible to proteolytic processing and, potentially, other post-translational modifications.

Basis for substrate recognition and distinction by matrix metalloproteinases

Significance Specificity-determining positions (SDPs) account for distinctions in function across a protein family. Many theories on the evolution of functional specificity have led to approaches for predicting SDPs in silico, but large experimental datasets allowing a statistical assignment are lacking. Here, the SDPs of matrix metalloproteinases are elucidated by querying the proteolytic efficiency of eight matrix metalloproteinases, representing three phylogenetic branches, in an extended and diverse substrate space. More than 10,000 measures of cleavage efficiency reveal a near-perfect correlation between similarity in proteolytic function and sequence identity at 50–57 positions on the front face of the catalytic domain. These positions are assigned as SDPs. Transmutation of proteolytic function is possible by swapping SDPs nearest to bound substrate. Genomic sequencing and structural genomics produced a vast amount of sequence and structural data, creating an opportunity for structure–function analysis in silico [Radivojac P, et al. (2013) Nat Methods 10(3):221–227]. Unfortunately, only a few large experimental datasets exist to serve as benchmarks for function-related predictions. Furthermore, currently there are no reliable means to predict the extent of functional similarity among proteins. Here, we quantify structure–function relationships among three phylogenetic branches of the matrix metalloproteinase (MMP) family by comparing their cleavage efficiencies toward an extended set of phage peptide substrates that were selected from ∼64 million peptide sequences (i.e., a large unbiased representation of substrate space). The observed second-order rate constants [k(obs)] across the substrate space provide a distance measure of functional similarity among the MMPs. These functional distances directly correlate with MMP phylogenetic distance. There is also a remarkable and near-perfect correlation between the MMP substrate preference and sequence identity of 50–57 discontinuous residues surrounding the catalytic groove. We conclude that these residues represent the specificity-determining positions (SDPs) that allowed for the expansion of MMP proteolytic function during evolution. A transmutation of only a few selected SDPs proximal to the bound substrate peptide, and contributing the most to selectivity among the MMPs, is sufficient to enact a global change in the substrate preference of one MMP to that of another, indicating the potential for the rational and focused redesign of cleavage specificity in MMPs.

Genomic Reconstruction of the Transcriptional Regulatory Network in Bacillus subtilis

The adaptation of microorganisms to their environment is controlled by complex transcriptional regulatory networks (TRNs), which are still only partially understood even for model species. Genome scale annotation of regulatory features of genes and TRN reconstruction are challenging tasks of microbial genomics. We used the knowledge-driven comparative-genomics approach implemented in the RegPredict Web server to infer TRN in the model Gram-positive bacterium Bacillus subtilis and 10 related Bacillales species. For transcription factor (TF) regulons, we combined the available information from the DBTBS database and the literature with bioinformatics tools, allowing inference of TF binding sites (TFBSs), comparative analysis of the genomic context of predicted TFBSs, functional assignment of target genes, and effector prediction. For RNA regulons, we used known RNA regulatory motifs collected in the Rfam database to scan genomes and analyze the genomic context of new RNA sites. The inferred TRN in B. subtilis comprises regulons for 129 TFs and 24 regulatory RNA families. First, we analyzed 66 TF regulons with previously known TFBSs in B. subtilis and projected them to other Bacillales genomes, resulting in refinement of TFBS motifs and identification of novel regulon members. Second, we inferred motifs and described regulons for 28 experimentally studied TFs with previously unknown TFBSs. Third, we discovered novel motifs and reconstructed regulons for 36 previously uncharacterized TFs. The inferred collection of regulons is available in the RegPrecise database (http://regprecise.lbl.gov/) and can be used in genetic experiments, metabolic modeling, and evolutionary analysis.

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

BackgroundIn 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.ResultsA 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.ConclusionsThe 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/).