sRNAscanner: A Computational Tool for Intergenic Small RNA Detection in Bacterial Genomes

Background:Bacterial non-coding small RNAs (sRNAs) have attracted considerable attention due to their ubiquitous nature and contribution to numerous cellular processes including survival, adaptation and pathogenesis. Existing computational approaches for identifying bacterial sRNAs demonstrate varying levels of success and there remains considerable room for improvement. Methodology/Principal Findings: Here we have proposed a transcriptional signal-based computational method to identify intergenic sRNA transcriptional units (TUs) in completely sequenced bacterial genomes. Our sRNAscanner tool uses position weight matrices derived from experimentally defined E. coli K-12 MG1655 sRNA promoter and rho-independent terminator signals to identify intergenic sRNA TUs through sliding window based genome scans. Analysis of genomes representative of twelve species suggested that sRNAscanner demonstrated equivalent sensitivity to sRNAPredict2, the best performing bioinformatics tool available presently. However, each algorithm yielded substantial numbers of known and uncharacterized hits that were unique to one or the other tool only. sRNAscanner identified 118 novel putative intergenic sRNA genes in Salmonella enterica Typhimurium LT2, none of which were flagged by sRNAPredict2. Candidate sRNA locations were compared with available deep sequencing libraries derived from Hfq-co-immunoprecipitated RNA purified from a second Typhimurium strain (Sittka et al. (2008) PLoS Genetics 4: e1000163). Sixteen potential novel sRNAs computationally predicted and detected in deep sequencing libraries were selected for experimental validation by Northern analysis using total RNA isolated from bacteria grown under eleven different growth conditions. RNA bands of expected sizes were detected in Northern blots for six of the examined candidates. Furthermore, the 5'-ends of these six Northern-supported sRNA candidates were successfully mapped using 5'-RACE analysis. Conclusions/Significance: We have developed, computationally examined and experimentally validated the sRNAscanner algorithm. Data derived from this study has successfully identified six novel S. Typhimurium sRNA genes. In addition, the computational specificity analysis we have undertaken suggests that similar to 40% of sRNAscanner hits with high cumulative sum of scores represent genuine, undiscovered sRNA genes. Collectively, these data strongly support the utility of sRNAscanner and offer a glimpse of its potential to reveal large numbers of sRNA genes that have to date defied identification. sRNAscanner is available from: http://bicmku.in:8081/sRNAscanner or http://cluster.physics.iisc.ernet.in/sRNAscanner/.

High-quality annotation of promoter regions for 913 bacterial genomes

Motivation: The number of bacterial genomes being sequenced is increasing very rapidly and hence, it is crucial to have procedures for rapid and reliable annotation of their functional elements such as promoter regions, which control the expression of each gene or each transcription unit of the genome. The present work addresses this requirement and presents a generic method applicable across organisms. Results: Relative stability of the DNA double helical sequences has been used to discriminate promoter regions from non-promoter regions. Based on the difference in stability between neighboring regions, an algorithm has been implemented to predict promoter regions on a large scale over 913 microbial genome sequences. The average free energy values for the promoter regions as well as their downstream regions are found to differ, depending on their GC content. Threshold values to identify promoter regions have been derived using sequences flanking a subset of translation start sites from all microbial genomes and then used to predict promoters over the complete genome sequences. An average recall value of 72% (which indicates the percentage of protein and RNA coding genes with predicted promoter regions assigned to them) and precision of 56% is achieved over the 913 microbial genome dataset.

Promiscuous restriction is a cellular defense strategy that confers fitness advantage to bacteria

Most bacterial genomes harbor restriction-modification systems, encoding a REase and its cognate MTase. On attack by a foreign DNA, the REase recognizes it as nonself and subjects it to restriction. Should REases be highly specific for targeting the invading foreign DNA? It is often considered to be the case. However, when bacteria harboring a promiscuous or high-fidelity variant of the REase were challenged with bacteriophages, fitness was maximal under conditions of catalytic promiscuity. We also delineate possible mechanisms by which the REase recognizes the chromosome as self at the noncanonical sites, thereby preventing lethal dsDNA breaks. This study provides a fundamental understanding of how bacteria exploit an existing defense system to gain fitness advantage during a host-parasite coevolutionary ``arms race.''

Polyketide Quinones Are Alternate Intermediate Electron Carriers during Mycobacterial Respiration in Oxygen-Deficient Niches

Mycobacterium tuberculosis (Mtb) adaptation to hypoxia is considered crucial to its prolonged latent persistence in humans. Mtb lesions are known to contain physiologically heterogeneous microenvironments that bring about differential responses from bacteria. Here we exploit metabolic variability within biofilm cells to identify alternate respiratory polyketide quinones (PkQs) from both Mycobacterium smegmatis (Msmeg) and Mtb. PkQs are specifically expressed in biofilms and other oxygen-deficient niches to maintain cellular bioenergetics. Under such conditions, these metabolites function as mobile electron carriers in the respiratory electron transport chain. In the absence of PkQs, mycobacteria escape from the hypoxic core of biofilms and prefer oxygenrich conditions. Unlike the ubiquitous isoprenoid pathway for the biosynthesis of respiratory quinones, PkQs are produced by type III polyketide synthases using fatty acyl-CoA precursors. The biosynthetic pathway is conserved in several other bacterial genomes, and our study reveals a redox-balancing chemicocellular process in microbial physiology.

CsrA interacting small RNAs in Haemophilus spp genomes: a theoretical analysis

The csrA is a carbon storage regulator gene that encodes a protein with multiple RNA interaction sites. Bacterial non-coding small RNAs like csrB, csrC and their counterparts in diverse bacterial genus are identified to control the regulatory activities of CsrA and its orthologs. An attempt has been made in this study to identify 'novel' non-coding small RNAs that are involved in the regulatory activities of csrA gene. All CsrA-interacting small RNAs are computationally fingerprinted to have multiple occurrence of 7-nucleotide CsrA interacting repeats [CAGGA(U/A/C)G] along with a 18-nucleotide upstream binding site. However, in several of the genomes like Haemophilus spp, the upstream binding site is not identified. The current methodology overcomes this difficulty by identifying small RNA-specific orphan transcriptional units within the intergenic regions of the genome. The results could identify all known CsrA-interacting small RNAs in E. coli, Vibrio cholerae and Pseudomonas aeruginosa genomes and additionally has picked six new possible CsrA-interacting small RNA regions in E. coli. Our computational analysis indicates that known rygD and rprA sRNAs in E. coli could possibly interact with CsrA proteins. The study is extended to three of the Haemophilus genomes that could identify seven new possible CsrA interacting small RNAs.

Functional correlation of bacterial LuxS with their quaternary associations: interface analysis of the structure networks

Background The genome of a wide variety of prokaryotes contains the luxS gene homologue, which encodes for the protein S-ribosylhomocysteinelyase (LuxS). This protein is responsible for the production of the quorum sensing molecule, AI-2 and has been implicated in a variety of functions such as flagellar motility, metabolic regulation, toxin production and even in pathogenicity. A high structural similarity is present in the LuxS structures determined from a few species. In this study, we have modelled the structures from several other species and have investigated their dimer interfaces. We have attempted to correlate the interface features of LuxS with the phenotypic nature of the organisms. Results The protein structure networks (PSN) are constructed and graph theoretical analysis is performed on the structures obtained from X-ray crystallography and on the modelled ones. The interfaces, which are known to contain the active site, are characterized from the PSNs of these homodimeric proteins. The key features presented by the protein interfaces are investigated for the classification of the proteins in relation to their function. From our analysis, structural interface motifs are identified for each class in our dataset, which showed distinctly different pattern at the interface of LuxS for the probiotics and some extremophiles. Our analysis also reveals potential sites of mutation and geometric patterns at the interface that was not evident from conventional sequence alignment studies. Conclusion The structure network approach employed in this study for the analysis of dimeric interfaces in LuxS has brought out certain structural details at the side-chain interaction level, which were elusive from the conventional structure comparison methods. The results from this study provide a better understanding of the relation between the luxS gene and its functional role in the prokaryotes. This study also makes it possible to explore the potential direction towards the design of inhibitors of LuxS and thus towards a wide range of antimicrobials.

Genome analysis: A new approach for visualization of sequence organization in genomes

In this article we describe and demonstrate the versatility of a computer program, GENOME MAPPING, that uses interactive graphics and runs on an IRIS workstation. The program helps to visualize as well as analyse global and local patterns of genomic DNA sequences. It was developed keeping in mind the requirements of the human genome sequencing programme, which requires rapid analysis of the data. Using GENOME MAPPING one can discern signature patterns of different kinds of sequences and analyse such patterns for repetitive as well as rare sequence strings. Further, one can visualize the extent of global homology between different genomic sequences. An application of our method to the published yeast mitochondrial genome data shows similar sequence organizations in the entire sequence and in smaller subsequences.

DNA Free Energy-Based Promoter Prediction and Comparative Analysis of Arabidopsis and Rice Genomes

The cis-regulatory regions on DNA serve as binding sites for proteins such as transcription factors and RNA polymerase. The combinatorial interaction of these proteins plays a crucial role in transcription initiation, which is an important point of control in the regulation of gene expression. We present here an analysis of the performance of an in silico method for predicting cis-regulatory regions in the plant genomes of Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) on the basis of free energy of DNA melting. For protein-coding genes, we achieve recall and precision of 96% and 42% for Arabidopsis and 97% and 31% for rice, respectively. For noncoding RNA genes, the program gives recall and precision of 94% and 75% for Arabidopsis and 95% and 90% for rice, respectively. Moreover, 96% of the false-positive predictions were located in noncoding regions of primary transcripts, out of which 20% were found in the first intron alone, indicating possible regulatory roles. The predictions for orthologous genes from the two genomes showed a good correlation with respect to prediction scores and promoter organization. Comparison of our results with an existing program for promoter prediction in plant genomes indicates that our method shows improved prediction capability.

Systematic Analysis of Mycobacterial Acylation Reveals First Example of Acylation-mediated Regulation of Enzyme Activity of a Bacterial Phosphatase

Protein lysine acetylation is known to regulate multiple aspects of bacterial metabolism. However, its presence in mycobacterial signal transduction and virulence-associated proteins has not been studied. In this study, analysis of mycobacterial proteins from different cellular fractions indicated dynamic and widespread occurrence of lysine acetylation. Mycobacterium tuberculosis proteins regulating diverse physiological processes were then selected and expressed in the surrogate host Mycobacterium smegmatis. The purified proteins were analyzed for the presence of lysine acetylation, leading to the identification of 24 acetylated proteins. In addition, novel lysine succinylation and propionylation events were found to co-occur with acetylation on several proteins. Protein-tyrosine phosphatase B (PtpB), a secretory phosphatase that regulates phosphorylation of host proteins and plays a critical role in Mycobacterium infection, is modified by acetylation and succinylation at Lys-224. This residue is situated in a lid region that covers the enzyme's active site. Consequently, acetylation and succinylation negatively regulate the activity of PtpB.

targetTB: A target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis

Background: Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results: We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion: The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes.

Additional binding sites in lysozyme. X-ray analysis of lysozyme complexes with bromophenol red and bromophenol blue

The binding sites in hen egg-white lysozyme for neutral bromophenol red (BPR) and ionized bromophenol blue (BPB) have been characterized at 2 Å resolution. In either case, the dye-bound enzyme is active against the polysaccharide, but not against the cell wall. Both binding sites are outside, but close to, the hexasaccharide binding cleft in the enzyme. The binding site of BPR made up of Arg5, Lys33, Phe34, Asn37, Phe38, Ala122, Trp123 and possibly Arg125, is dose to subsite F while that of BPB made up of Tyr20, Arg21, Asn93, Lys96, Lys97 and Ser100, is close to subsites A and B. The binding sites of the neutral dye and the ionized dye are thus spatially far apart. The peptide component of the bacterial cell wall probably interacts with these cells during enzyme action. Such interactions are perhaps necessary for appropriately positioning the enzyme molecule on the bacterial cell wall.

Analysis of the amino acid sequences of plant Bowman-Birk inhibitors

Plant seeds contain a large number of protease inhibitors of animal, fungal, and bacterial origin. One of the well-studied families of these inhibitors is the Bowman-Birk family(BBI). The BBIs from dicotyledonous seeds are 8K, double-headed proteins. In contrast, the 8K inhibitors from monocotyledonous seeds are single headed. Monocots also have a 16K, double-headed inhibitor. We have determined the primary structure of a Bowman-Birk inhibitor from a dicot, horsegram, by sequential edman analysis of the intact protein and peptides derived from enzymatic and chemical cleavage. The 76-residue-long inhibitor is very similar to that ofMacrotyloma axillare. An analysis of this inhibitor along with 26 other Bowman-Birk inhibitor domains (MW 8K) available in the SWISSPROT databank revealed that the proteins from monocots and dicots belong to related but distinct families. Inhibitors from monocots show larger variation in sequence. Sequence comparison shows that a crucial disulphide which connects the amino and carboxy termini of the active site loop is lost in monocots. The loss of a reactive site in monocots seems to be correlated to this. However, it appears that this disulphide is not absolutely essential for retention of inhibitory function. Our analysis suggests that gene duplication leading to a 16K inhibitor in monocots has occurred, probably after the divergence of monocots and dicots, and also after the loss of second reactive site in monocots.

Relative stability of DNA as a generic criterion for promoter prediction: whole genome annotation of microbial genomes with varying nucleotide base composition

The rapid increase in genome sequence information has necessitated the annotation of their functional elements, particularly those occurring in the non-coding regions, in the genomic context. Promoter region is the key regulatory region, which enables the gene to be transcribed or repressed, but it is difficult to determine experimentally. Hence an in silico identification of promoters is crucial in order to guide experimental work and to pin point the key region that controls the transcription initiation of a gene. In this analysis, we demonstrate that while the promoter regions are in general less stable than the flanking regions, their average free energy varies depending on the GC composition of the flanking genomic sequence. We have therefore obtained a set of free energy threshold values, for genomic DNA with varying GC content and used them as generic criteria for predicting promoter regions in several microbial genomes, using an in-house developed tool `PromPredict'. On applying it to predict promoter regions corresponding to the 1144 and 612 experimentally validated TSSs in E. coli (50.8% GC) and B. subtilis (43.5% GC) sensitivity of 99% and 95% and precision values of 58% and 60%, respectively, were achieved. For the limited data set of 81 TSSs available for M. tuberculosis (65.6% GC) a sensitivity of 100% and precision of 49% was obtained.

Location of Pathogenic Bacteria during Persistent Infections: Insights from an Analysis Using Game Theory

Bacterial persistent infections are responsible for a significant amount of the human morbidity and mortality. Unlike acute bacterial infections, it is very difficult to treat persistent bacterial infections (e.g. tuberculosis). Knowledge about the location of pathogenic bacteria during persistent infection will help to treat such conditions by designing novel drugs which can reach such locations. In this study, events of bacterial persistent infections were analyzed using game theory. A game was defined where the pathogen and the host are the two players with a conflict of interest. Criteria for the establishment of Nash equilibrium were calculated for this game. This theoretical model, which is very simple and heuristic, predicts that during persistent infections pathogenic bacteria stay in both intracellular and extracellular compartments of the host. The result of this study implies that a bacterium should be able to survive in both intracellular and extracellular compartments of the host in order to cause persistent infections. This explains why persistent infections are more often caused by intracellular pathogens like Mycobacterium and Salmonella. Moreover, this prediction is in consistence with the results of previous experimental studies.

Analysis of the binding of polymyxin B to endotoxic lipid A and core glycolipid using a fluorescent displacement probe

Dansylcadaverine, a cationic fluorescent probe binds to bacterial lipopolysaccharide and lipid A, and is displaced competitively by other compounds which possess affinity toward endotoxins. The binding parameters of dansylcadaverine for lipid A were determined by Scatchard analysis to be two apparently equivalent sites with apparent dissociation constants (Kd) ranging between 16 μM to 26 μM, while that obtained for core glycolipid from Salmonella minnesota Re595 yielded a Kd of 22 μM to 28 μM with three binding sites. The Kd of polymyxin B for lipid A was computed from dansylcadaverine displacement by the method of Horovitz and Levitzki (Horovitz, A., and Levitzki, A. (1987) Proc. Natl. Acad. Sci. USA 84, 6654–6658). The applicability of this method for analyzing fluorescence data was validated by comparing the Kds of melittin for lipid A obtained by direct Scatchard analysis, and by the Horovitz-Levitzki method. The displacement of dansylcadaverine from lipid A by polymyxin B was distinctly biphasic with Kds for polymyxin B-lipid A interactions corresponding to 0.4 μM and 1.5 μM, probably resulting as a consequence of lipid A being a mixture of mono- and di-phosphoryl species. This was not observed with core glycolipid, for which the Kd for polymyxin was estimated to range from 1.1 μM to 5.8 μM. The use of dansylcadaverine as a displacement probe offers a novel and convenient method of quantitating the interactions of a wide variety of substances with lipid A.