Genomic characterization of ribitol teichoic acid synthesis in Staphylococcus aureus: genes, genomic organization and gene duplication

BACKGROUND: Staphylococcus aureus or MRSA (Methicillin Resistant S. aureus), is an acquired pathogen and the primary cause of nosocomial infections worldwide. In S. aureus, teichoic acid is an essential component of the cell wall, and its biosynthesis is not yet well characterized. Studies in Bacillus subtilis have discovered two different pathways of teichoic acid biosynthesis, in two strains W23 and 168 respectively, namely teichoic acid ribitol (tar) and teichoic acid glycerol (tag). The genes involved in these two pathways are also characterized, tarA, tarB, tarD, tarI, tarJ, tarK, tarL for the tar pathway, and tagA, tagB, tagD, tagE, tagF for the tag pathway. With the genome sequences of several MRSA strains: Mu50, MW2, N315, MRSA252, COL as well as methicillin susceptible strain MSSA476 available, a comparative genomic analysis was performed to characterize teichoic acid biosynthesis in these S. aureus strains. RESULTS: We identified all S. aureus tar and tag gene orthologs in the selected S. aureus strains which would contribute to teichoic acids sythesis.Based on our identification of genes orthologous to tarI, tarJ, tarL, which are specific to tar pathway in B. subtilis W23, we also concluded that tar is the major teichoic acid biogenesis pathway in S. aureus. Further analyses indicated that the S. aureus tar genes, different from the divergon organization in B. subtilis, are organized into several clusters in cis. Most interesting, compared with genes in B. subtilis tar pathway, the S. aureus tar specific genes (tarI,J,L) are duplicated in all six S. aureus genomes. CONCLUSION: In the S. aureus strains we analyzed, tar (teichoic acid ribitol) is the main teichoic acid biogenesis pathway. The tar genes are organized into several genomic groups in cis and the genes specific to tar (relative to tag): tarI, tarJ, tarL are duplicated. The genomic organization of the S. aureus tar pathway suggests their regulations are different when compared to B. subtilis tar or tag pathway, which are grouped in two operons in a divergon structure

On-Farm-Produced Organic Amendments on Maintaining and Enhancing Soil Fertility and Nitrogen Availability in Organic or Low Input Agriculture

Maintaining and enhancing soil fertility are key issues for sustainability in an agricultural system with organic or low input methods. On-farm–produced green manure as a source of soil organic matter (SOM) plays a critical role in long-term productivity. But producing green manure requires land and water; thus, increasing biodiversity, such as by intercropping with green manure crops, could be an approach to enhance the efficiency of renewable resources especially in developing countries. This article discusses soil fertility and its maintenance and enhancement with leguminous intercropping from four points of view: soil fertility and organic matter function, leguminous green manure, intercropping principles, and soil conservation. Important contributions of leguminous intercropping include SOM enhancement and fertility building, biological nitrogen (N) and other plant nutrition availability. Under a well-designed and managed system, competition between the target and intercropping crops can be reduced. The plant uptake efficiency of biologically fixed N is estimated to be double that of industrial N fertilizers. After N-rich plant residues are incorporated into soil, the carbon (C):nitrogen ratio of added straw decreases. Another high mitigation potential of legume intercropping lies in soil conservation by preventing soil and water erosion. Many opportunities exist to introduce legumes in short-term rotation, intercropping, living mulch, and cover crops in an organically managed farm system. Worldwide, long-term soil fertility enhancement remains a challenge due to the current world population and agricultural practices. Cropping system including legumes is a step in the right direction to meeting the needs of food security and sustainability

The combination approach of SVM and ECOC for powerful identification and classification of transcription factor

<p>Abstract</p> <p>Background</p> <p>Transcription factors (TFs) are core functional proteins which play important roles in gene expression control, and they are key factors for gene regulation network construction. Traditionally, they were identified and classified through experimental approaches. In order to save time and reduce costs, many computational methods have been developed to identify TFs from new proteins and to classify the resulted TFs. Though these methods have facilitated screening of TFs to some extent, low accuracy is still a common problem. With the fast growing number of new proteins, more precise algorithms for identifying TFs from new proteins and classifying the consequent TFs are in a high demand.</p> <p>Results</p> <p>The support vector machine (SVM) algorithm was utilized to construct an automatic detector for TF identification, where protein domains and functional sites were employed as feature vectors. Error-correcting output coding (ECOC) algorithm, which was originated from information and communication engineering fields, was introduced to combine with support vector machine (SVM) methodology for TF classification. The overall success rates of identification and classification achieved 88.22% and 97.83% respectively. Finally, a web site was constructed to let users access our tools (see Availability and requirements section for URL).</p> <p>Conclusion</p> <p>The SVM method was a valid and stable means for TFs identification with protein domains and functional sites as feature vectors. Error-correcting output coding (ECOC) algorithm is a powerful method for multi-class classification problem. When combined with SVM method, it can remarkably increase the accuracy of TF classification using protein domains and functional sites as feature vectors. In addition, our work implied that ECOC algorithm may succeed in a broad range of applications in biological data mining.</p

The use of global transcriptional analysis to reveal the biological and cellular events involved in distinct development phases of Trichophyton rubrum conidial germination

<p>Abstract</p> <p>Background</p> <p>Conidia are considered to be the primary cause of infections by <it>Trichophyton rubrum</it>.</p> <p>Results</p> <p>We have developed a cDNA microarray containing 10250 ESTs to monitor the transcriptional strategy of conidial germination. A total of 1561 genes that had their expression levels specially altered in the process were obtained and hierarchically clustered with respect to their expression profiles. By functional analysis, we provided a global view of an important biological system related to conidial germination, including characterization of the pattern of gene expression at sequential developmental phases, and changes of gene expression profiles corresponding to morphological transitions. We matched the EST sequences to GO terms in the <it>Saccharomyces </it>Genome Database (SGD). A number of homologues of <it>Saccharomyces cerevisiae </it>genes related to signalling pathways and some important cellular processes were found to be involved in <it>T. rubrum </it>germination. These genes and signalling pathways may play roles in distinct steps, such as activating conidial germination, maintenance of isotropic growth, establishment of cell polarity and morphological transitions.</p> <p>Conclusion</p> <p>Our results may provide insights into molecular mechanisms of conidial germination at the cell level, and may enhance our understanding of regulation of gene expression related to the morphological construction of <it>T. rubrum</it>.</p

Using GeneReg to construct time delay gene regulatory networks

<p>Abstract</p> <p>Background</p> <p>Understanding gene expression and regulation is essential for understanding biological mechanisms. Because gene expression profiling has been widely used in basic biological research, especially in transcription regulation studies, we have developed GeneReg, an easy-to-use R package, to construct gene regulatory networks from time course gene expression profiling data; More importantly, this package can provide information about time delays between expression change in a regulator and that of its target genes.</p> <p>Findings</p> <p>The R package GeneReg is based on time delay linear regression, which can generate a model of the expression levels of regulators at a given time point against the expression levels of their target genes at a later time point. There are two parameters in the model, time delay and regulation coefficient. Time delay is the time lag during which expression change of the regulator is transmitted to change in target gene expression. Regulation coefficient expresses the regulation effect: a positive regulation coefficient indicates activation and negative indicates repression. GeneReg was implemented on a real Saccharomyces cerevisiae cell cycle dataset; more than thirty percent of the modeled regulations, based entirely on gene expression files, were found to be consistent with previous discoveries from known databases.</p> <p>Conclusions</p> <p>GeneReg is an easy-to-use, simple, fast R package for gene regulatory network construction from short time course gene expression data. It may be applied to study time-related biological processes such as cell cycle, cell differentiation, or causal inference.</p

Gene-Centric Characteristics of Genome-Wide Association Studies

BACKGROUND: The high-throughput genotyping chips have contributed greatly to genome-wide association (GWA) studies to identify novel disease susceptibility single nucleotide polymorphisms (SNPs). The high-density chips are designed using two different SNP selection approaches, the direct gene-centric approach, and the indirect quasi-random SNPs or linkage disequilibrium (LD)-based tagSNPs approaches. Although all these approaches can provide high genome coverage and ascertain variants in genes, it is not clear to which extent these approaches could capture the common genic variants. It is also important to characterize and compare the differences between these approaches. METHODOLOGY/PRINCIPAL FINDINGS: In our study, by using both the Phase II HapMap data and the disease variants extracted from OMIM, a gene-centric evaluation was first performed to evaluate the ability of the approaches in capturing the disease variants in Caucasian population. Then the distribution patterns of SNPs were also characterized in genic regions, evolutionarily conserved introns and nongenic regions, ontologies and pathways. The results show that, no mater which SNP selection approach is used, the current high-density SNP chips provide very high coverage in genic regions and can capture most of known common disease variants under HapMap frame. The results also show that the differences between the direct and the indirect approaches are relatively small. Both have similar SNP distribution patterns in these gene-centric characteristics. CONCLUSIONS/SIGNIFICANCE: This study suggests that the indirect approaches not only have the advantage of high coverage but also are useful for studies focusing on various functional SNPs either in genes or in the conserved regions that the direct approach supports. The study and the annotation of characteristics will be helpful for designing and analyzing GWA studies that aim to identify genetic risk factors involved in common diseases, especially variants in genes and conserved regions

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure