Evaluating Matrix Circuits

The circuit evaluation problem (also known as the compressed word problem) for finitely generated linear groups is studied. The best upper bound for this problem is $\mathsf{coRP}$, which is shown by a reduction to polynomial identity testing. Conversely, the compressed word problem for the linear group $\mathsf{SL}_3(\mathbb{Z})$ is equivalent to polynomial identity testing. In the paper, it is shown that the compressed word problem for every finitely generated nilpotent group is in $\mathsf{DET} \subseteq \mathsf{NC}^2$. Within the larger class of polycyclic groups we find examples where the compressed word problem is at least as hard as polynomial identity testing for skew arithmetic circuits

Application of Focal Conflict Theory to Psychoeducational Groups: Implications for Process, Content, and Leadership

Group psychoeducation is a common group type used for a range of purposes. The literature presents balancing content and process as a challenge for psychoeducational group leaders. While the significance of group psychoeducation is supported, practitioners are given little direction for addressing process in these groups. Focal Conflict Theory (FCT) is a model for conceptualizing and intervening in group process that has been applied to therapy and work groups. This article presents the challenges of psychoeducational groups, describes FCT, and discusses its application to psychoeducational groups using case examples. Implications for leaders of psychoeducation groups are discussed

P-value based visualization of codon usage data

Two important and not yet solved problems in bacterial genome research are the identification of horizontally transferred genes and the prediction of gene expression levels. Both problems can be addressed by multivariate analysis of codon usage data. In particular dimensionality reduction methods for visualization of multivariate data have shown to be effective tools for codon usage analysis. We here propose a multidimensional scaling approach using a novel similarity measure for codon usage tables. Our probabilistic similarity measure is based on P-values derived from the well-known chi-square test for comparison of two distributions. Experimental results on four microbial genomes indicate that the new method is well-suited for the analysis of horizontal gene transfer and translational selection. As compared with the widely-used correspondence analysis, our method did not suffer from outlier sensitivity and showed a better clustering of putative alien genes in most cases

What Are the Public Health Effects of Direct-to-Consumer Drug Advertising?

Background to the debate: Only two industrialized countries, the United States and New Zealand, allow direct-to-consumer advertising (DTCA) of prescription medicines, although New Zealand is planning a ban [ 1]. The challenge for these governments is ensuring that DTCA is more beneficial than harmful. Proponents of DTCA argue that it helps to inform the public about available treatments and stimulates appropriate use of drugs for high-priority illnesses (such as statin use in people with ischemic heart disease). Critics argue that the information in the adverts is often biased and misleading, and that DTCA raises prescribing costs without net evidence of health benefits

Pseudomonas Genome Database: improved comparative analysis and population genomics capability for Pseudomonas genomes

Pseudomonas is a metabolically-diverse genus of bacteria known for its flexibility and leading free living to pathogenic lifestyles in a wide range of hosts. The Pseudomonas Genome Database (http://www.pseudomonas.com) integrates completely-sequenced Pseudomonas genome sequences and their annotations with genome-scale, high-precision computational predictions and manually curated annotation updates. The latest release implements an ability to view sequence polymorphisms in P. aeruginosa PAO1 versus other reference strains, incomplete genomes and single gene sequences. This aids analysis of phenotypic variation between closely related isolates and strains, as well as wider population genomics and evolutionary studies. The wide range of tools for comparing Pseudomonas annotations and sequences now includes a strain-specific access point for viewing high precision computational predictions including updated, more accurate, protein subcellular localization and genomic island predictions. Views link to genome-scale experimental data as well as comparative genomics analyses that incorporate robust genera-geared methods for predicting and clustering orthologs. These analyses can be exploited for identifying putative essential and core Pseudomonas genes or identifying large-scale evolutionary events. The Pseudomonas Genome Database aims to provide a continually updated, high quality source of genome annotations, specifically tailored for Pseudomonas researchers, but using an approach that may be implemented for other genera-level research communities

A quantitative account of genomic island acquisitions in prokaryotes

<p>Abstract</p> <p>Background</p> <p>Microbial genomes do not merely evolve through the slow accumulation of mutations, but also, and often more dramatically, by taking up new DNA in a process called horizontal gene transfer. These innovation leaps in the acquisition of new traits can take place via the introgression of single genes, but also through the acquisition of large gene clusters, which are termed Genomic Islands. Since only a small proportion of all the DNA diversity has been sequenced, it can be hard to find the appropriate donors for acquired genes via sequence alignments from databases. In contrast, relative oligonucleotide frequencies represent a remarkably stable genomic signature in prokaryotes, which facilitates compositional comparisons as an alignment-free alternative for phylogenetic relatedness.</p> <p>In this project, we test whether Genomic Islands identified in individual bacterial genomes have a similar genomic signature, in terms of relative dinucleotide frequencies, and can therefore be expected to originate from a common donor species.</p> <p>Results</p> <p>When multiple Genomic Islands are present within a single genome, we find that up to 28% of these are compositionally very similar to each other, indicative of frequent recurring acquisitions from the same donor to the same acceptor.</p> <p>Conclusions</p> <p>This represents the first quantitative assessment of common directional transfer events in prokaryotic evolutionary history. We suggest that many of the resident Genomic Islands per prokaryotic genome originated from the same source, which may have implications with respect to their regulatory interactions, and for the elucidation of the common origins of these acquired gene clusters.</p

Genes optimized by evolution for accurate and fast translation encode in Archaea and Bacteria a broad and characteristic spectrum of protein functions

BACKGROUND: In many microbial genomes, a strong preference for a small number of codons can be observed in genes whose products are needed by the cell in large quantities. This codon usage bias (CUB) improves translational accuracy and speed and is one of several factors optimizing cell growth. Whereas CUB and the overrepresentation of individual proteins have been studied in detail, it is still unclear which high-level metabolic categories are subject to translational optimization in different habitats. RESULTS: In a systematic study of 388 microbial species, we have identified for each genome a specific subset of genes characterized by a marked CUB, which we named the effectome. As expected, gene products related to protein synthesis are abundant in both archaeal and bacterial effectomes. In addition, enzymes contributing to energy production and gene products involved in protein folding and stabilization are overrepresented. The comparison of genomes from eleven habitats shows that the environment has only a minor effect on the composition of the effectomes. As a paradigmatic example, we detailed the effectome content of 37 bacterial genomes that are most likely exposed to strongest selective pressure towards translational optimization. These effectomes accommodate a broad range of protein functions like enzymes related to glycolysis/gluconeogenesis and the TCA cycle, ATP synthases, aminoacyl-tRNA synthetases, chaperones, proteases that degrade misfolded proteins, protectants against oxidative damage, as well as cold shock and outer membrane proteins. CONCLUSIONS: We made clear that effectomes consist of specific subsets of the proteome being involved in several cellular functions. As expected, some functions are related to cell growth and affect speed and quality of protein synthesis. Additionally, the effectomes contain enzymes of central metabolic pathways and cellular functions sustaining microbial life under stress situations. These findings indicate that cell growth is an important but not the only factor modulating translational accuracy and speed by means of CUB

PIPS: Pathogenicity Island Prediction Software

The adaptability of pathogenic bacteria to hosts is influenced by the genomic plasticity of the bacteria, which can be increased by such mechanisms as horizontal gene transfer. Pathogenicity islands play a major role in this type of gene transfer because they are large, horizontally acquired regions that harbor clusters of virulence genes that mediate the adhesion, colonization, invasion, immune system evasion, and toxigenic properties of the acceptor organism. Currently, pathogenicity islands are mainly identified in silico based on various characteristic features: (1) deviations in codon usage, G+C content or dinucleotide frequency and (2) insertion sequences and/or tRNA genetic flanking regions together with transposase coding genes. Several computational techniques for identifying pathogenicity islands exist. However, most of these techniques are only directed at the detection of horizontally transferred genes and/or the absence of certain genomic regions of the pathogenic bacterium in closely related non-pathogenic species. Here, we present a novel software suite designed for the prediction of pathogenicity islands (pathogenicity island prediction software, or PIPS). In contrast to other existing tools, our approach is capable of utilizing multiple features for pathogenicity island detection in an integrative manner. We show that PIPS provides better accuracy than other available software packages. As an example, we used PIPS to study the veterinary pathogen Corynebacterium pseudotuberculosis, in which we identified seven putative pathogenicity islands

Blueprint for a minimal photoautotrophic cell: conserved and variable genes in Synechococcus elongatus PCC 7942

Background: Simpler biological systems should be easier to understand and to engineer towards pre-defined goals. One way to achieve biological simplicity is through genome minimization. Here we looked for genomic islands in the fresh water cyanobacteria Synechococcus elongatus PCC 7942 (genome size 2.7 Mb) that could be used as targets for deletion. We also looked for conserved genes that might be essential for cell survival.Results: By using a combination of methods we identified 170 xenologs, 136 ORFans and 1401 core genes in the genome of S. elongatus PCC 7942. These represent 6.5%, 5.2% and 53.6% of the annotated genes respectively. We considered that genes in genomic islands could be found if they showed a combination of: a) unusual G+C content; b) unusual phylogenetic similarity; and/or c) a small number of the highly iterated palindrome 1 (HIP1) motif plus an unusual codon usage. The origin of the largest genomic island by horizontal gene transfer (HGT) could be corroborated by lack of coverage among metagenomic sequences from a fresh water microbialite. Evidence is also presented that xenologous genes tend to cluster in operons. Interestingly, most genes coding for proteins with a diguanylate cyclase domain are predicted to be xenologs, suggesting a role for horizontal gene transfer in the evolution of Synechococcus sensory systems.Conclusions: Our estimates of genomic islands in PCC 7942 are larger than those predicted by other published methods like SIGI-HMM. Our results set a guide to non-essential genes in S. elongatus PCC 7942 indicating a path towards the engineering of a model photoautotrophic bacterial cell.Financial support was provided by grants BFU2009-12895-C02-01/BMC (Ministerio de Ciencia e Innovación, Spain), the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement number 212894 and Prometeo/2009/092 (Conselleria d’Educació, Generalitat Valenciana, Spain) to A. Moya. Work in the FdlC laboratory was supported by grants BFU2008-00995/BMC (Spanish Ministry of Education), RD06/0008/1012 (RETICS research network, Instituto de Salud Carlos III, Spanish Ministry of Health) and LSHM-CT- 2005_019023 (European VI Framework Program). Dr. González-Domenech was supported by grant from the University of Granada. LD, thanks to financial support from Facultad de Ciencias, Universidad Nacional Autónoma de México

A Benchmark of Parametric Methods for Horizontal Transfers Detection

Horizontal gene transfer (HGT) has appeared to be of importance for prokaryotic species evolution. As a consequence numerous parametric methods, using only the information embedded in the genomes, have been designed to detect HGTs. Numerous reports of incongruencies in results of the different methods applied to the same genomes were published. The use of artificial genomes in which all HGT parameters are controlled allows testing different methods in the same conditions. The results of this benchmark concerning 16 representative parametric methods showed a great variety of efficiencies. Some methods work very poorly whatever the type of HGTs and some depend on the conditions or on the metrics used. The best methods in terms of total errors were those using tetranucleotides as criterion for the window methods or those using codon usage for gene based methods and the Kullback-Leibler divergence metric. Window methods are very sensitive but less specific and detect badly lone isolated gene. On the other hand gene based methods are often very specific but lack of sensitivity. We propose using two methods in combination to get the best of each category, a gene based one for specificity and a window based one for sensitivity