The comparative utility of fluorescence in situ hybridization and reverse transcription-polymerase chain reaction in the diagnosis of alveolar rhabdomyosarcoma.

Fluorescence in situ hybridization (FISH) for FOXO1 gene rearrangement and reverse transcription-polymerase chain reaction (PCR) for PAX3/7-FOXO1 fusion transcripts have become routine ancillary tools for the diagnosis of alveolar rhabdomyosarcomas (ARMS). Here we summarize our experience of these adjunct diagnostic modalities at a tertiary center, presenting the largest comparative series of FISH and PCR for suspected or possible ARMS to date. All suspected or possible ARMS tested by FISH or PCR for FOXO1 rearrangement or PAX3/7-FOXO1 fusion transcripts over a 7-year period were included. FISH and PCR results were correlated with clinical and histologic findings. One hundred samples from 95 patients had FISH and/or PCR performed. FISH had higher rates of technical success (96.8 %) compared with PCR (88 %). Where both tests were utilized successfully, there was high concordance rate between them (94.9 %). In 24 histologic ARMS tested for FISH or PCR, 83.3 % were translocation-positive (all for PAX3-FOXO1 by PCR) and included 3 histologic solid variants. In 76 cases where ARMS was excluded, there were 3 potential false-positive cases with FISH but none with PCR. PCR had similar sensitivity (85.7 %) and better specificity (100 %) in aiding the diagnosis of ARMS, compared with FISH (85 and 95.8 %, respectively). All solid variant ARMS harbored FOXO1 gene rearrangements and PAX3-FOXO1 ARMS were detected to the exclusion of PAX7-FOXO1. In comparative analysis, both FISH and PCR are useful in aiding the diagnosis of ARMS and excluding its sarcomatous mimics. FISH is more reliable technically but has less specificity than PCR. In cases where ARMS is in the differential diagnosis, it is optimal to perform both PCR and FISH: both have similar sensitivities for detecting ARMS, but FISH may confirm or exclude cases that are technically unsuccessful with PCR, while PCR can detect specific fusion transcripts that may be useful prognostically.

Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

Reconstruction of the ancestral marsupial karyotype from comparative gene maps

BACKGROUND: The increasing number of assembled mammalian genomes makes it possible to compare genome organisation across mammalian lineages and reconstruct chromosomes of the ancestral marsupial and therian (marsupial and eutherian) mammals. However, the reconstruction of ancestral genomes requires genome assemblies to be anchored to chromosomes. The recently sequenced tammar wallaby (Macropus eugenii) genome was assembled into over 300,000 contigs. We previously devised an efficient strategy for mapping large evolutionarily conserved blocks in non-model mammals, and applied this to determine the arrangement of conserved blocks on all wallaby chromosomes, thereby permitting comparative maps to be constructed and resolve the long debated issue between a 2n=14 and 2n=22 ancestral marsupial karyotype. RESULTS: We identified large blocks of genes conserved between human and opossum, and mapped genes corresponding to the ends of these blocks by fluorescence in situ hybridization (FISH). A total of 242 genes was assigned to wallaby chromosomes in the present study, bringing the total number of genes mapped to 554 and making it the most densely cytogenetically mapped marsupial genome. We used these gene assignments to construct comparative maps between wallaby and opossum, which uncovered many intrachromosomal rearrangements, particularly for genes found on wallaby chromosomes X and 3. Expanding comparisons to include chicken and human permitted the putative ancestral marsupial (2n=14) and therian mammal (2n=19) karyotypes to be reconstructed. CONCLUSIONS: Our physical mapping data for the tammar wallaby has uncovered the events shaping marsupial genomes and enabled us to predict the ancestral marsupial karyotype, supporting a 2n=14 ancestor. Futhermore, our predicted therian ancestral karyotype has helped to understand the evolution of the ancestral eutherian genome.

Comparative susceptibility of mosquito populations in North Queensland, Australia to oral infection with dengue virus

Dengue is the most prevalent arthropod-borne virus, with at least 40% of the world’s population at risk of infection each year. In Australia, dengue is not endemic, but viremic travelers trigger outbreaks involving hundreds of cases. We compared the susceptibility of Aedes aegypti mosquitoes from two geographically isolated populations with two strains of dengue virus serotype 2. We found, interestingly, that mosquitoes from a city with no history of dengue were more susceptible to virus than mosquitoes from an outbreak-prone region, particularly with respect to one dengue strain. These findings suggest recent evolution of population-based differences in vector competence or different historical origins. Future genomic comparisons of these populations could reveal the genetic basis of vector competence and the relative role of selection and stochastic processes in shaping their differences. Lastly, we show the novel finding of a correlation between midgut dengue titer and titer in tissues colonized after dissemination.

How to sequence and annotate insect mitochondrial genomes for systematic and comparative genomics research

Over the past decade the mitochondrial (mt) genome has become the most widely used genomic resource available for systematic entomology. While the availability of other types of ‘–omics’ data – in particular transcriptomes – is increasing rapidly, mt genomes are still vastly cheaper to sequence and are far less demanding of high quality templates. Furthermore, almost all other ‘–omics’ approaches also sequence the mt genome, and so it can form a bridge between legacy and contemporary datasets. Mitochondrial genomes have now been sequenced for all insect orders, and in many instances representatives of each major lineage within orders (suborders, series or superfamilies depending on the group). They have also been applied to systematic questions at all taxonomic scales from resolving interordinal relationships (e.g. Cameron et al., 2009; Wan et al., 2012; Wang et al., 2012), through many intraordinal (e.g. Dowton et al., 2009; Timmermans et al., 2010; Zhao et al. 2013a) and family-level studies (e.g. Nelson et al., 2012; Zhao et al., 2013b) to population/biogeographic studies (e.g. Ma et al., 2012). Methodological issues around the use of mt genomes in insect phylogenetic analyses and the empirical results found to date have recently been reviewed by Cameron (2014), yet the technical aspects of sequencing and annotating mt genomes were not covered. Most papers which generate new mt genome report their methods in a simplified form which can be difficult to replicate without specific knowledge of the field. Published studies utilize a sufficiently wide range of approaches, usually without justification for the one chosen, that confusion about commonly used jargon such as ‘long PCR’ and ‘primer walking’ could be a serious barrier to entry. Furthermore, sequenced mt genomes have been annotated (gene locations defined) to wildly varying standards and improving data quality through consistent annotation procedures will benefit all downstream users of these datasets. The aims of this review are therefore to: 1. Describe in detail the various sequencing methods used on insect mt genomes; 2. Explore the strengths/weakness of different approaches; 3. Outline the procedures and software used for insect mt genome annotation, and; 4. Highlight quality control steps used for new annotations, and to improve the re-annotation of previously sequenced mt genomes used in systematic or comparative research.

Integrated analysis of epigenomic and genomic changes by DNA methylation dependent mechanisms provides potential novel biomarkers for prostate cancer

Epigenetic silencing mediated by CpG methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with tumor progression may identify potential prognostic markers for prostate cancer (PCa). We treated two PCa cell lines, 22Rv1 and DU-145 with the demethylating agent 5-Aza 2’–deoxycitidine (DAC) and global methylation status was analyzed by performing methylation-sensitive restriction enzyme based differential methylation hybridization strategy followed by genome-wide CpG methylation array profiling. In addition, we examined gene expression changes using a custom microarray. Gene Set Enrichment Analysis (GSEA) identified the most significantly dysregulated pathways. In addition, we assessed methylation status of candidate genes that showed reduced CpG methylation and increased gene expression after DAC treatment, in Gleason score (GS) 8 vs. GS6 patients using three independent cohorts of patients; the publically available The Cancer Genome Atlas (TCGA) dataset, and two separate patient cohorts. Our analysis, by integrating methylation and gene expression in PCa cell lines, combined with patient tumor data, identified novel potential biomarkers for PCa patients. These markers may help elucidate the pathogenesis of PCa and represent potential prognostic markers for PCa patients.

Comparative genomics of koala, cattle and sheep strains of Chlamydia pecorum

Background Chlamydia pecorum is an important pathogen of domesticated livestock including sheep, cattle and pigs. This pathogen is also a key factor in the decline of the koala in Australia. We sequenced the genomes of three koala C. pecorum strains, isolated from the urogenital tracts and conjunctiva of diseased koalas. The genome of the C. pecorum VR629 (IPA) strain, isolated from a sheep with polyarthritis, was also sequenced. Results Comparisons of the draft C. pecorum genomes against the complete genomes of livestock C. pecorum isolates revealed that these strains have a conserved gene content and order, sharing a nucleotide sequence similarity > 98%. Single nucleotide polymorphisms (SNPs) appear to be key factors in understanding the adaptive process. Two regions of the chromosome were found to be accumulating a large number of SNPs within the koala strains. These regions include the Chlamydia plasticity zone, which contains two cytotoxin genes (toxA and toxB), and a 77 kbp region that codes for putative type III effector proteins. In one koala strain (MC/MarsBar), the toxB gene was truncated by a premature stop codon but is full-length in IPTaLE and DBDeUG. Another five pseudogenes were also identified, two unique to the urogenital strains C. pecorum MC/MarsBar and C. pecorum DBDeUG, respectively, while three were unique to the koala C. pecorum conjunctival isolate IPTaLE. An examination of the distribution of these pseudogenes in C. pecorum strains from a variety of koala populations, alongside a number of sheep and cattle C. pecorum positive samples from Australian livestock, confirmed the presence of four predicted pseudogenes in koala C. pecorum clinical samples. Consistent with our genomics analyses, none of these pseudogenes were observed in the livestock C. pecorum samples examined. Interestingly, three SNPs resulting in pseudogenes identified in the IPTaLE isolate were not found in any other C. pecorum strain analysed, raising questions over the origin of these point mutations. Conclusions The genomic data revealed that variation between C. pecorum strains were mainly due to the accumulation of SNPs, some of which cause gene inactivation. The identification of these genetic differences will provide the basis for further studies to understand the biology and evolution of this important animal pathogen. Keywords: Chlamydia pecorum; Single nucleotide polymorphism; Pseudogene; Cytotoxin

Optimizing de novo transcriptome assembly and extending genomic resources for striped catfish (Pangasianodon hypophthalmus)

Striped catfish (Pangasianodon hypophthalmus) is a commercially important freshwater fish used in inland aquaculture in the Mekong Delta, Vietnam. The culture industry is facing a significant challenge however from saltwater intrusion into many low topographical coastal provinces across the Mekong Delta as a result of predicted climate change impacts. Developing genomic resources for this species can facilitate the production of improved culture lines that can withstand raised salinity conditions, and so we have applied high-throughput Ion Torrent sequencing of transcriptome libraries from six target osmoregulatory organs from striped catfish as a genomic resource for use in future selection strategies. We obtained 12,177,770 reads after trimming and processing with an average length of 97 bp. De novo assemblies were generated using CLC Genomic Workbench, Trinity and Velvet/Oases with the best overall contig performance resulting from the CLC assembly. De novo assembly using CLC yielded 66,451 contigs with an average length of 478 bp and N50 length of 506 bp. A total of 37,969 contigs (57%) possessed significant similarity with proteins in the non-redundant database. Comparative analyses revealed that a significant number of contigs matched sequences reported in other teleost fishes, ranging in similarity from 45.2% with Atlantic cod to 52% with zebrafish. In addition, 28,879 simple sequence repeats (SSRs) and 55,721 single nucleotide polymorphisms (SNPs) were detected in the striped catfish transcriptome. The sequence collection generated in the current study represents the most comprehensive genomic resource for P. hypophthalmus available to date. Our results illustrate the utility of next-generation sequencing as an efficient tool for constructing a large genomic database for marker development in non-model species.

Analysis of a Genomic DNA Expression Library of Mycobacterium tuberculosis Using Tuberculosis Patient Sera: Evidence for Modulation of Host Immune Response

DNA obtained from a human sputum isolate of Mycobacterium tuberculosis, NTI-64719, which showed extensive dissemination in the guinea pig model resulting in a high score for virulence was used to construct an expression library in the lambda ZAP vector. The size of DNA inserts in the library ranged from 1 to 3 kb, and recombinants represented 60% of the total plaques obtained. When probed with pooled serum from chronically infected tuberculosis patients, the library yielded 176 recombinants with a range of signal intensities. Among these, 93 recombinants were classified into 12 groups on the basis of DNA hybridization experiments, The polypeptides synthesized by the recombinants were predominantly LacZ fusion proteins, Serum obtained from patients who were clinically diagnosed to be in the early phase of M. tuberculosis infection was used to probe the 176 recombinants obtained. interestingly, some recombinants that gave very strong signals in the original screen did not react with early-phase serum; conversely, others whose signals were extremely weak in the original screen gave very intense signals with serum from recently infected patients, This indicates the differential nature of either the expression of these antigens or the immune response elicited by them as a function of disease progression.

A comparative study of tbe regulation of cytochrome P-450 and glutathione transferase gene expression in rat liver

A cDNA clone for the Ya subunit of glutathione transferase from rat liver was constructed in E.coli. The clone hybridized to Ya and Yc subunit messenger RNAs. On the basis of experiments involving cell-free translation and hybridization to the cloned probe, it was shown that prototype inducers of cytochrome P-450 such as phenobarbitone and 3-methylcholanthrene as well as inhibitors such as CoCl2 and 3-amino-l,2,4-triazole enhanced the glutathione transferase (Ya+Yc) messenger RNA contents in rat liver. A comparative study with the induction of cytochrome P-450 (b+e) by phenobarbitone revealed that the drug manifested a striking increase in the nuclear pre-messenger RNAs for the cytochrome at 12 hr, but did not significantly affect the same in the case of glutathione transferase (Ya+Yc). 3-Amino-l, 2,4-tnazole and CoCl- blocked the phenobarbitone mediated increase in cytochrome P-450 (b+e) nuclear pre-messenger RNAs. These compounds did not significantly affect the glutathione transferase (Ya+Yc) nuclear pre-messenger RNA levels. The polysomal, poly (A)- containing messenger RNAs for cytochrome P-450 (b+e) increased by 12–15 fold after phenobarbitone administration, reached a maximum around 16hr and then decreased sharply. In comparison, the increase in the case of glutathione transferase (Ya+Yc) mesenger RNAs was sluggish and steady and a value of 3–4 fold was reached around 24 hr. Run-off transcription rates for cytochrome P-450 (b+e) increased by nearly 15 fold in 4 hr after phenobarbitone administration, whereas the increase for glutathione transferase (Ya+Yc) was only 2.0 fold. At 12 hr after the drug administration, the glutathione transferase (Ya+Yc) transcription rates were near normal. Administration of 3-amino-l,2,4-triazole and CoCl2 blocked the phenobarbitone-mediated increase in the transcription of cytochrome P-450 (b+e) messenger RNAs. These compounds at best had only marginal effects on the transcription of glutathione transferase (Ya+Yc) messenger RNAs. The half-life of cytochrome P-450 (b+e) messenger RNA was estimated to be 3–4 hr, whereas that for glutathione transferase (Ya+Yc) was found to be 8-9 hr. Administration of phenobarbitone enhanced the half-life of glutathione transferase (Ya+Yc) messenger RNA by nearly two fold. It is suggested that while transcription activation may play a primary role in the induction of cytochrome P-450 (b+e), the induction of glutathione transferase (Ya+Yc) may essentially involve stabilization of the messenger RNAs.

Microarrays in Lung Cancer Research: From Comparative Analyses to Verified Findings

Keuhkosyöpä on yleisimpiä syöpätauteja. Se jaetaan kahteen päätyyppiin: pienisoluiseen ja ei-pienisoluiseen keuhkosyöpään. Ei-pienisoluinen keuhkosyöpä jaetaan lisäksi alatyyppeihin, joista suurimmat ovat levyepiteeli-, adeno- ja suurisoluinen karsinooma. Keuhkosyövän tärkein riskitekijä on tupakointi, mutta muutkin työ- ja elinympäristön altisteet, kuten asbesti, voivat johtaa syöpään. Väitöstyössä tutkittiin kahdenlaisten keuhkosyöpäryhmien erityispiirteitä. Työssä kartoitettiin, onko löydettävissä muutoksia, jotka erottavat asbestikeuhkosyövät muista syövistä sekä luuytimeen varhaisessa vaiheessa leviävät keuhkosyövät leviämättömistä syövistä. Tutkimusten ensimmäisessä vaiheessa käytettiin mikrosirupohjaisia menetelmiä, jotka mahdollistavat jopa kaikkien geenien tarkastelun yhden kokeen avulla. Vertailevien mikrosirututkimusten avulla on mahdollista paikantaa geenejä tai kromosomialueita, joiden muutokset erottelevat ryhmät toisistaan. Asbestiin liittyvissä tutkimuksissa paikannettiin kuusi kromosomialuetta, joissa geenien kopiolukumäärän sekä ilmenemistason muutokset erottelivat potilaat altistushistorian mukaan. Riippumattomilla laboratoriomenetelmillä tehtyjen jatkoanalyysien avulla pystyttiin varmistamaan, että 19p-alueen häviämä oli yhteydessä asbestialtistukseen. Työssä osoitettiin myös, että 19p-alueen muutoksia voidaan indusoida altistamalla soluja asbestille in vitro. Tutkimuksessa saatiin lisäksi viitteitä asbestispesifisistä muutoksista signaalinvälitysreiteissä, sillä yhdessä toimivien geenien ilmentymisessä havaittiin eroja asbestille altistuneiden ja altistumattomien välillä. Vertailemalla luuytimeen syövän aikaisessa vaiheessa levinneiden ja leviämättömien keuhkoadenokarsinoomien muutosprofiileita toisiinsa, paikannettiin viisi aluetta, joilla geenien kopiolukumäärä- sekä ilmenemistason muutokset erottelivat ryhmät toisistaan. Jatkoanalyyseissä havaittiin, että 4q-alueen häviämää esiintyi adenokarsinoomien lisäksi levyepiteelikarsinoomiin, jotka olivat levinneet luuytimeen. Myös keuhkosyöpien aivometastaaseissa alue oli toistuvasti hävinnyt. Väitöstyön tutkimukset osoittavat, että vertailevien mikrosiruanalyysien avulla saadaan tietoa syöpäryhmien erityispiirteistä. Työssä saadut tulokset osoittavat, että 19p-alueen muutokset ovat tyypillisiä asbestikeuhkosyöville ja 4q-alueen muutokset luuytimeen aikaisessa vaiheessa leviäville keuhkosyöville.

Comparative analysis of thermophilic and mesophilic proteins using Protein Energy Networks

Background: Thermophilic proteins sustain themselves and function at higher temperatures. Despite their structural and functional similarities with their mesophilic homologues, they show enhanced stability. Various comparative studies at genomic, protein sequence and structure levels, and experimental works highlight the different factors and dominant interacting forces contributing to this increased stability. Methods: In this comparative structure based study, we have used interaction energies between amino acids, to generate structure networks called as Protein Energy Networks (PENs). These PENs are used to compute network, sub-graph, and node specific parameters. These parameters are then compared between the thermophile-mesophile homologues. Results: The results show an increased number of clusters and low energy cliques in thermophiles as the main contributing factors for their enhanced stability. Further more, we see an increase in the number of hubs in thermophiles. We also observe no community of electrostatic cliques forming in PENs. Conclusion: In this study we were able to take an energy based network approach, to identify the factors responsible for enhanced stability of thermophiles, by comparative analysis. We were able to point out that the sub-graph parameters are the prominent contributing factors. The thermophiles have a better-packed hydrophobic core. We have also discussed how thermophiles, although increasing stability through higher connectivity retains conformational flexibility, from a cliques and communities perspective.

Comparative analysis of thermophilic and mesophilic proteins using Protein Energy Networks

Background: Thermophilic proteins sustain themselves and function at higher temperatures. Despite their structural and functional similarities with their mesophilic homologues, they show enhanced stability. Various comparative studies at genomic, protein sequence and structure levels, and experimental works highlight the different factors and dominant interacting forces contributing to this increased stability. Methods: In this comparative structure based study, we have used interaction energies between amino acids, to generate structure networks called as Protein Energy Networks (PENs). These PENs are used to compute network, sub-graph, and node specific parameters. These parameters are then compared between the thermophile-mesophile homologues. Results: The results show an increased number of clusters and low energy cliques in thermophiles as the main contributing factors for their enhanced stability. Further more, we see an increase in the number of hubs in thermophiles. We also observe no community of electrostatic cliques forming in PENs. Conclusion: In this study we were able to take an energy based network approach, to identify the factors responsible for enhanced stability of thermophiles, by comparative analysis. We were able to point out that the sub-graph parameters are the prominent contributing factors. The thermophiles have a better-packed hydrophobic core. We have also discussed how thermophiles, although increasing stability through higher connectivity retains conformational flexibility, from a cliques and communities perspective.

Comparative genomics reveals `novel' Fur regulated sRNAs and coding genes in diverse proteobacteria

Ferric uptake regulator (Fur) is a transcriptional regulator controlling the expression of genes involved in iron homeostasis and plays an important role in pathogenesis. Fur-regulated sRNAs/CDSs were found to have upstream Fur Binding Sites (FBS). We have constructed a Positional Weight Matrix from 100 known FBS (19 nt) and tracked the `Orphan' FBSs. Possible Fur regulated sRNAs and CDSs were identified by comparing their genomic locations with the `Orphan' FBSs identified. Thirty-eight `novel' and all known Fur regulated sRNAs in nine proteobacteria were identified. In addition, we identified high scoring FBSs in the promoter regions of the 304 CDSs and 68 of them were involved in siderophore biosynthesis, iron-transporters, two-component system, starch/sugar metabolism, sulphur/methane metabolism, etc. The present study shows that the Fur regulator controls the expression of genes involved in diverse metabolic activities and it is not limited to iron metabolism alone. (C) 2012 Elsevier B.V. All rights reserved.