Identification of signature and primers specific to genus <Emphasis Type="Italic">Pseudomonas</Emphasis> using mismatched patterns of 16S rDNA sequences

Background

Pseudomonas, a soil bacterium, has been observed as a dominant genus that survives in different habitats with wide hostile conditions. We had a basic assumption that the species level variation in 16S rDNA sequences of a bacterial genus is mainly due to substitutions rather than insertion or deletion of bases. Keeping this in view, the aim was to identify a region of 16S rDNA sequence and within that focus on substitution prone stretches indicating species level variation and to derive patterns from these stretches that are specific to the genus.

Results

Repeating elements that are highly conserved across different species of Pseudomonas were considered as guiding markers to locate a region within the 16S gene. Four repeating patterns showing more than 80% consistency across fifty different species of Pseudomonas were identified. The sub-sequences between the repeating patterns yielded a continuous region of 495 bases. The sub-sequences after alignment and using Shanon's entropy measure yielded a consensus pattern. A stretch of 24 base positions in this region, showing maximum variations across the sampled sequences was focused for possible genus specific patterns. Nine patterns in this stretch showed nearly 70% specificity to the target genus. These patterns were further used to obtain a signature that is highly specific to Pseudomonas. The signature region was used to design PCR primers, which yielded a PCR product of 150 bp whose specificity was validated through a sample experiment.

Conclusions

The developed approach was successfully applied to genus Pseudomonas. It could be tried in other bacterial genera to obtain respective signature patterns and thereby PCR primers, for their rapid tracking in the environmental samples.

     

Improved alignment quality by combining evolutionary information, predicted secondary structure and self-organizing maps

Background  

Protein sequence alignment is one of the basic tools in bioinformatics. Correct alignments are required for a range of tasks including the derivation of phylogenetic trees and protein structure prediction. Numerous studies have shown that the incorporation of predicted secondary structure information into alignment algorithms improves their performance. Secondary structure predictors have to be trained on a set of somewhat arbitrarily defined states (e.g. helix, strand, coil), and it has been shown that the choice of these states has some effect on alignment quality. However, it is not unlikely that prediction of other structural features also could provide an improvement. In this study we use an unsupervised clustering method, the self-organizing map, to assign sequence profile windows to "structural states" and assess their use in sequence alignment.     

The structure of selective dinucleotide interactions and periodicities in D melanogaster mtDNA

Background

We found a strong selective 3-sites periodicity of deviations from randomness of the dinucleotide (DN) distribution, where both bases of DN were separated by 1, 2, K sites in prokaryotes and mtDNA. Three main aspects are studied. I) the specific 3 K-sites periodic structure of the 16 DN. II) to discard the possibility that the periodicity was produced by the highly nonrandom interactive association of contiguous bases, by studying the interaction of non-contiguous bases, the first one chosen each I sites and the second chosen J sites downstream. III) the difference between this selective periodicity of association (distance to randomness) of the four bases with the described fixed periodicities of base sequences.

Results

I) The 16 pairs presented a consistent periodicity in the strength of association of both bases of the pairs; the most deviated pairs are those where G and C are involved and the least deviated ones are those where A and T are involved. II) we found significant non-random interactions when the first nucleotide is chosen every I sites and the second J sites downstream until I = J = 76. III) we showed conclusive differences between these internucleotide association periodicities and sequence periodicities.

Conclusions

This relational selective periodicity is different from sequence periodicities and indicates that any base strongly interacts with the bases of the residual genome; this interaction and periodicity is highly structured and systematic for every pair of bases. This interaction should be destroyed in few generations by recurrent mutation; it is only compatible with the Synthetic Theory of Evolution and agrees with the Wright’s adaptive landscape conception and evolution by shifting balanced adaptive peaks.

Electronic supplementary material

The online version of this article (doi:10.1186/0717-6287-47-18) contains supplementary material, which is available to authorized users.     

Gene expression signatures of radiation response are specific, durable and accurate in mice and humans

Background

Previous work has demonstrated the potential for peripheral blood (PB) gene expression profiling for the detection of disease or environmental exposures.

Methods and Findings

We have sought to determine the impact of several variables on the PB gene expression profile of an environmental exposure, ionizing radiation, and to determine the specificity of the PB signature of radiation versus other genotoxic stresses. Neither genotype differences nor the time of PB sampling caused any lessening of the accuracy of PB signatures to predict radiation exposure, but sex difference did influence the accuracy of the prediction of radiation exposure at the lowest level (50 cGy). A PB signature of sepsis was also generated and both the PB signature of radiation and the PB signature of sepsis were found to be 100% specific at distinguishing irradiated from septic animals. We also identified human PB signatures of radiation exposure and chemotherapy treatment which distinguished irradiated patients and chemotherapy-treated individuals within a heterogeneous population with accuracies of 90% and 81%, respectively.

Conclusions

We conclude that PB gene expression profiles can be identified in mice and humans that are accurate in predicting medical conditions, are specific to each condition and remain highly accurate over time.     

Pinyon pine (Pinus edulis) mortality and response to water addition across a three million year substrate age gradient in northern Arizona, USA

Background and aims

Pinyon pine (Pinus edulis Engelm.) is an important tree species in the western United States that has experienced large-scale mortality during recent severe drought. The influence of soil conditions on pinyon pine response to water availability is poorly understood. We investigated patterns of tree mortality and response of tree water relations and growth to experimental water addition at four sites across a three million year soil-substrate age gradient.

Methods

We measured recent pinyon mortality at four sites, and tree predawn water potential, leaf carbon isotope signature, and branch, leaf, and stem radial growth on 12 watered and unwatered trees at each site. Watered trees recieved fifty percent more than growing season precipitation for 6 years.

Results

Substrate age generally had a greater effect on tree water stress and growth than water additions. Pinyon mortality was higher on intermediate-aged substrates (50–55%) than on young (15%) and old (17%) substrates, and mortality was positively correlated with pinyon abundance prior to drought.

Conclusions

These results suggest high soil resource availability and consequent high stand densities at intermediate-age substrates predisposes trees to drought-induced mortality in semi-arid regions. The response of tree water relations to water addition was consistent with the inverse texture hypothesis; watering reduced tree water stress most in young, coarsely textured soil, likely because water rapidly penetrated deep in the soil profile where it was protected from evapotranspiration.     

Effect of the assignment of ancestral CpG state on the estimation of nucleotide substitution rates in mammals

Background  

Molecular evolutionary studies in mammals often estimate nucleotide substitution rates within and outside CpG dinucleotides separately. Frequently, in alignments of two sequences, the division of sites into CpG and non-CpG classes is based simply on the presence or absence of a CpG dinucleotide in either sequence, a procedure that we refer to as CpG/non-CpG assignment. Although it likely that this procedure is biased, it is generally assumed that the bias is negligible if species are very closely related.     

The use of Multiple Displacement Amplified DNA as a control for Methylation Specific PCR,Pyrosequencing, Bisulfite Sequencing and Methylation-Sensitive Restriction Enzyme PCR

Background  

Genomic DNA methylation affects approximately 1% of DNA bases in humans, with the most common event being the addition of a methyl group to the cytosine residue present in the CpG (cytosine-guanine) dinucleotide. Methylation is of particular interest because of its role in gene silencing in many pathological conditions. CpG methylation can be measured using a wide range of techniques, including methylation-specific (MS) PCR, pyrosequencing (PSQ), bisulfite sequencing (BS) and methylation-sensitive restriction enzyme (MSRE) PCR. However, although it is possible to utilise these methods to measure CpG methylation, optimisation of the assays can be complicated due to the absence of suitable control DNA samples.     

Quantum-chemical study of interactions of <Emphasis Type="Italic">trans-</Emphasis>resveratrol with guanine-thymine dinucleotide and DNA-nucleobases

Trans-resveratrol, a natural phytoalexin present in red wine and grapes, has gained considerable attention because of its antiproliferative, chemopreventive and proapoptotic activity against human cancer cells. The accurate quantum-chemical computations based on the density functional theory (DFT) and ab initio second-order Møller-Plesset perturbation method (MP2) have been performed for the first time to study interactions of trans-resveratrol with guanine-thymine dinucleotide and DNA-derived nitrogenous bases: adenine, guanine, cytosine and thymine in vacuum and water medium. This compound is found to show high affinity to nitrogenous bases and guanine-thymine dinucleotide. The electrostatic interactions from intermolecular hydrogen bonding increase the stability of complexes studied. In particular, significantly strong hydrogen bonds between 4′-H atom of trans-resveratrol and imidazole nitrogen as well as carbonyl oxygen atoms of nucleobases studied stabilize these systems. The stabilization energies computed reveal that the negatively charged trans-resveratrol-dinucleotide complex is more energetically stable in water medium than in vacuum. MP2 method gives more reliable and significantly high values of stabilization energy of trans-resveratrol-dinucleotide, trans-resveratrol-guanine and trans-resveratrol-thymine complexes than B3LYP exchange-correlation functional because it takes into account London dispersion energy. According to the results, in the presence of trans-resveratrol the 3′-5′ phosphodiester bond in dinucleotide can be cleaved and the proton from 4′-OH group of trans-resveratrol migrates to the 3′-O atom of dinucleotide. It is concluded that trans-resveratrol is able to break the DNA strand. Hence, the findings obtained help understand antiproliferative and anticancer properties of this polyphenol.     

Dissection of a metastatic gene expression signature into distinct components

Background

Metastasis, the process whereby cancer cells spread, is in part caused by an incompletely understood interplay between cancer cells and the surrounding stroma. Gene expression studies typically analyze samples containing tumor cells and stroma. Samples with less than 50% tumor cells are generally excluded, thereby reducing the number of patients that can benefit from clinically relevant signatures.

Results

For a head-neck squamous cell carcinoma (HNSCC) primary tumor expression signature that predicts the presence of lymph node metastasis, we first show that reduced proportions of tumor cells results in decreased predictive accuracy. To determine the influence of stroma on the predictive signature and to investigate the interaction between tumor cells and the surrounding microenvironment, we used laser capture microdissection to divide the metastatic signature into six distinct components based on tumor versus stroma expression and on association with the metastatic phenotype. A strikingly skewed distribution of metastasis associated genes is revealed.

Conclusion

Dissection of predictive signatures into different components has implications for design of expression signatures and for our understanding of the metastatic process. Compared to primary tumors that have not formed metastases, primary HNSCC tumors that have metastasized are characterized by predominant down-regulation of tumor cell specific genes and exclusive up-regulation of stromal cell specific genes. The skewed distribution agrees with poor signature performance on samples that contain less than 50% tumor cells. Methods for reducing tumor composition bias that lead to greater predictive accuracy and an increase in the types of samples that can be included are presented.     

Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods

Background

Alternative splicing is the critical process in a single gene coding, which removes introns and joins exons, and splicing branchpoints are indicators for the alternative splicing. Wet experiments have identified a great number of human splicing branchpoints, but many branchpoints are still unknown. In order to guide wet experiments, we develop computational methods to predict human splicing branchpoints.

Results

Considering the fact that an intron may have multiple branchpoints, we transform the branchpoint prediction as the multi-label learning problem, and attempt to predict branchpoint sites from intron sequences. First, we investigate a variety of intron sequence-derived features, such as sparse profile, dinucleotide profile, position weight matrix profile, Markov motif profile and polypyrimidine tract profile. Second, we consider several multi-label learning methods: partial least squares regression, canonical correlation analysis and regularized canonical correlation analysis, and use them as the basic classification engines. Third, we propose two ensemble learning schemes which integrate different features and different classifiers to build ensemble learning systems for the branchpoint prediction. One is the genetic algorithm-based weighted average ensemble method; the other is the logistic regression-based ensemble method.

Conclusions

In the computational experiments, two ensemble learning methods outperform benchmark branchpoint prediction methods, and can produce high-accuracy results on the benchmark dataset.

     

A simple and robust method for connecting small-molecule drugs using gene-expression signatures

Background  

Interaction of a drug or chemical with a biological system can result in a gene-expression profile or signature characteristic of the event. Using a suitably robust algorithm these signatures can potentially be used to connect molecules with similar pharmacological or toxicological properties by gene expression profile. Lamb et al first proposed the Connectivity Map [Lamb et al (2006), Science 313, 1929–1935] to make successful connections among small molecules, genes, and diseases using genomic signatures.     

An Analysis of Peer-Reviewed Scores and Impact Factors with Different Citation Time Windows: A Case Study of 28 Ophthalmologic Journals

Background

An important attribute of the traditional impact factor was the controversial 2-year citation window. So far, several scholars have proposed using different citation time windows for evaluating journals. However, there is no confirmation whether a longer citation time window would be better. How did the journal evaluation effects of 3IF, 4IF, and 6IF comparing with 2IF and 5IF? In order to understand these questions, we made a comparative study of impact factors with different citation time windows with the peer-reviewed scores of ophthalmologic journals indexed by Science Citation Index Expanded (SCIE) database.

Methods

The peer-reviewed scores of 28 ophthalmologic journals were obtained through a self-designed survey questionnaire. Impact factors with different citation time windows (including 2IF, 3IF, 4IF, 5IF, and 6IF) of 28 ophthalmologic journals were computed and compared in accordance with each impact factor’s definition and formula, using the citation analysis function of the Web of Science (WoS) database. An analysis of the correlation between impact factors with different citation time windows and peer-reviewed scores was carried out.

Results

Although impact factor values with different citation time windows were different, there was a high level of correlation between them when it came to evaluating journals. In the current study, for ophthalmologic journals’ impact factors with different time windows in 2013, 3IF and 4IF seemed the ideal ranges for comparison, when assessed in relation to peer-reviewed scores. In addition, the 3-year and 4-year windows were quite consistent with the cited peak age of documents published by ophthalmologic journals.

Research Limitations

Our study is based on ophthalmology journals and we only analyze the impact factors with different citation time window in 2013, so it has yet to be ascertained whether other disciplines (especially those with a later cited peak) or other years would follow the same or similar patterns.

Originality/ Value

We designed the survey questionnaire ourselves, specifically to assess the real influence of journals. We used peer-reviewed scores to judge the journal evaluation effect of impact factors with different citation time windows. The main purpose of this study was to help researchers better understand the role of impact factors with different citation time windows in journal evaluation.     

Divergent selection in trailing- versus leading-edge populations of Biscutella laevigata

Background and Aims

Knowledge on how climate-induced range shifts might affect natural selection is crucial to understand the evolution of species ranges.

Methods

Using historical demographic perspectives gathered from regional-scale phylogeography on the alpine herb Biscutella laevigata, indirect inferences on gene flow and signature of selection based on AFLP genotyping were compared between local populations persisting at the trailing edge and expanding at the leading edge.

Key Results

Spatial autocorrelation revealed that gene flow was two times more restricted at the trailing edge and genome scans indicated divergent selection in this persisting population. In contrast, no pattern of selection emerged in the expanding population at the leading edge.

Conclusions

Historical effects may determine different architecture of genetic variation and selective patterns within local populations, what is arguably important to understand evolutionary processes acting across the species ranges.     

A network perspective on the topological importance of enzymes and their phylogenetic conservation

Background  

A metabolic network is the sum of all chemical transformations or reactions in the cell, with the metabolites being interconnected by enzyme-catalyzed reactions. Many enzymes exist in numerous species while others occur only in a few. We ask if there are relationships between the phylogenetic profile of an enzyme, or the number of different bacterial species that contain it, and its topological importance in the metabolic network. Our null hypothesis is that phylogenetic profile is independent of topological importance. To test our null hypothesis we constructed an enzyme network from the KEGG (Kyoto Encyclopedia of Genes and Genomes) database. We calculated three network indices of topological importance: the degree or the number of connections of a network node; closeness centrality, which measures how close a node is to others; and betweenness centrality measuring how frequently a node appears on all shortest paths between two other nodes.     

Bayesian probit regression model for the diagnosis of pulmonary fibrosis: proof-of-principle

Background

The accurate diagnosis of idiopathic pulmonary fibrosis (IPF) is a major clinical challenge. We developed a model to diagnose IPF by applying Bayesian probit regression (BPR) modelling to gene expression profiles of whole lung tissue.

Methods

Whole lung tissue was obtained from patients with idiopathic pulmonary fibrosis (IPF) undergoing surgical lung biopsy or lung transplantation. Controls were obtained from normal organ donors. We performed cluster analyses to explore differences in our dataset. No significant difference was found between samples obtained from different lobes of the same patient. A significant difference was found between samples obtained at biopsy versus explant. Following preliminary analysis of the complete dataset, we selected three subsets for the development of diagnostic gene signatures: the first signature was developed from all IPF samples (as compared to controls); the second signature was developed from the subset of IPF samples obtained at biopsy; the third signature was developed from IPF explants. To assess the validity of each signature, we used an independent cohort of IPF and normal samples. Each signature was used to predict phenotype (IPF versus normal) in samples from the validation cohort. We compared the models' predictions to the true phenotype of each validation sample, and then calculated sensitivity, specificity and accuracy.

Results

Surprisingly, we found that all three signatures were reasonably valid predictors of diagnosis, with small differences in test sensitivity, specificity and overall accuracy.

Conclusions

This study represents the first use of BPR on whole lung tissue; previously, BPR was primarily used to develop predictive models for cancer. This also represents the first report of an independently validated IPF gene expression signature. In summary, BPR is a promising tool for the development of gene expression signatures from non-neoplastic lung tissue. In the future, BPR might be used to develop definitive diagnostic gene signatures for IPF, prognostic gene signatures for IPF or gene signatures for other non-neoplastic lung disorders such as bronchiolitis obliterans.

     

Whole genome comparative analysis of transposable elements provides new insight into mechanisms of their inactivation in fungal genomes

Background

Transposable Elements (TEs) are key components that shape the organization and evolution of genomes. Fungi have developed defense mechanisms against TE invasion such as RIP (Repeat-Induced Point mutation), MIP (Methylation Induced Premeiotically) and Quelling (RNA interference). RIP inactivates repeated sequences by promoting Cytosine to Thymine mutations, whereas MIP only methylates TEs at C residues. Both mechanisms require specific cytosine DNA Methyltransferases (RID1/Masc1) of the Dnmt1 superfamily.

Results

We annotated TE sequences from 10 fungal genomes with different TE content (1-70%). We then used these TE sequences to carry out a genome-wide analysis of C to T mutations biases. Genomes from either Ascomycota or Basidiomycota that were massively invaded by TEs (Blumeria, Melampsora, Puccinia) were characterized by a low frequency of C to T mutation bias (10-20%), whereas other genomes displayed intermediate to high frequencies (25-75%). We identified several dinucleotide signatures at these C to T mutation sites (CpA, CpT, and CpG). Phylogenomic analysis of fungal Dnmt1 MTases revealed a previously unreported association between these dinucleotide signatures and the presence/absence of sub-classes of Dnmt1.

Conclusions

We identified fungal genomes containing large numbers of TEs with many C to T mutations associated with species-specific dinucleotide signatures. This bias suggests that a basic defense mechanism against TE invasion similar to RIP is widespread in fungi, although the efficiency and specificity of this mechanism differs between species. Our analysis revealed that dinucleotide signatures are associated with the presence/absence of specific Dnmt1 subfamilies. In particular, an RID1-dependent RIP mechanism was found only in Ascomycota.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1347-1) contains supplementary material, which is available to authorized users.