Comprehensive prediction of chromosome dimer resolution sites in bacterial genomes

<p>Abstract</p> <p>Background</p> <p>During the replication process of bacteria with circular chromosomes, an odd number of homologous recombination events results in concatenated dimer chromosomes that cannot be partitioned into daughter cells. However, many bacteria harbor a conserved dimer resolution machinery consisting of one or two tyrosine recombinases, XerC and XerD, and their 28-bp target site, <it>dif</it>.</p> <p>Results</p> <p>To study the evolution of the <it>dif/</it>XerCD system and its relationship with replication termination, we report the comprehensive prediction of <it>dif </it>sequences <it>in silico </it>using a phylogenetic prediction approach based on iterated hidden Markov modeling. Using this method, <it>dif </it>sites were identified in 641 organisms among 16 phyla, with a 97.64% identification rate for single-chromosome strains. The <it>dif </it>sequence positions were shown to be strongly correlated with the GC skew shift-point that is induced by replicational mutation/selection pressures, but the difference in the positions of the predicted <it>dif </it>sites and the GC skew shift-points did not correlate with the degree of replicational mutation/selection pressures.</p> <p>Conclusions</p> <p>The sequence of <it>dif </it>sites is widely conserved among many bacterial phyla, and they can be computationally identified using our method. The lack of correlation between <it>dif </it>position and the degree of GC skew suggests that replication termination does not occur strictly at <it>dif </it>sites.</p

Comparative Analysis of Gene Content Evolution in Phytoplasmas and Mycoplasmas

Phytoplasmas and mycoplasmas are two groups of important pathogens in the bacterial class Mollicutes. Because of their economical and clinical importance, these obligate pathogens have attracted much research attention. However, difficulties involved in the empirical study of these bacteria, particularly the fact that phytoplasmas have not yet been successfully cultivated outside of their hosts despite decades of attempts, have greatly hampered research progress. With the rapid advancements in genome sequencing, comparative genome analysis provides a new approach to facilitate our understanding of these bacteria. In this study, our main focus is to investigate the evolution of gene content in phytoplasmas, mycoplasmas, and their common ancestor. By using a phylogenetic framework for comparative analysis of 12 complete genome sequences, we characterized the putative gains and losses of genes in these obligate parasites. Our results demonstrated that the degradation of metabolic capacities in these bacteria has occurred predominantly in the common ancestor of Mollicutes, prior to the evolutionary split of phytoplasmas and mycoplasmas. Furthermore, we identified a list of genes that are acquired by the common ancestor of phytoplasmas and are conserved across all strains with complete genome sequences available. These genes include several putative effectors for the interactions with hosts and may be good candidates for future functional characterization

Analyses of genome architecture and gene expression reveal novel candidate virulence factors in the secretome of Phytophthora infestans

<p>Abstract</p> <p>Background</p> <p><it>Phytophthora infestans </it>is the most devastating pathogen of potato and a model organism for the oomycetes. It exhibits high evolutionary potential and rapidly adapts to host plants. The <it>P. infestans </it>genome experienced a repeat-driven expansion relative to the genomes of <it>Phytophthora sojae </it>and <it>Phytophthora ramorum </it>and shows a discontinuous distribution of gene density. Effector genes, such as members of the RXLR and Crinkler (CRN) families, localize to expanded, repeat-rich and gene-sparse regions of the genome. This distinct genomic environment is thought to contribute to genome plasticity and host adaptation.</p> <p>Results</p> <p>We used <it>in silico </it>approaches to predict and describe the repertoire of <it>P. infestans </it>secreted proteins (the secretome). We defined the "plastic secretome" as a subset of the genome that (i) encodes predicted secreted proteins, (ii) is excluded from genome segments orthologous to the <it>P. sojae </it>and <it>P. ramorum </it>genomes and (iii) is encoded by genes residing in gene sparse regions of <it>P. infestans </it>genome. Although including only ~3% <it>of P. infestans </it>genes, the plastic secretome contains ~62% of known effector genes and shows >2 fold enrichment in genes induced <it>in planta</it>. We highlight 19 plastic secretome genes induced <it>in planta </it>but distinct from previously described effectors. This list includes a trypsin-like serine protease, secreted oxidoreductases, small cysteine-rich proteins and repeat containing proteins that we propose to be novel candidate virulence factors.</p> <p>Conclusions</p> <p>This work revealed a remarkably diverse plastic secretome. It illustrates the value of combining genome architecture with comparative genomics to identify novel candidate virulence factors from pathogen genomes.</p

Biomedical Images Processing Using Maxeler DataFlow Engines

Image segmentation is one of the most common procedures in medical imaging applications. It is also very important task in breast cancer detection. Breast cancer detection procedure based on mammography can be divided into several stages. The first stage is the extraction of region of interest from a breast image, after which the identification of suspicious mass regions, their classification, and comparison with the existing image database follows. It is often the case that already existing image databases have large sets of data for which processing requires a lot of time, thus the acceleration of each of the processing stages in breast cancer detection is a very important issue. Image filtering is also one of the most common and important tasks in image processing applications. It is, in most cases, preprocessing procedure for 3D visualization of an image stack. In order to achieve high-quality 3D visualization of a 2D image stack, it is of particular importance that all the images of the input stack are clear and sharp, thus their filtering should be executed carefully. There are also many algorithms for 3D visualization, so it is important to choose the right one which will execute fast enough and produce satisfied quality. In this chapter, the implementation of the already existing algorithm for region-of-interest-based image segmentation for mammogram images on High-Performance Reconfigurable DataFlow Computers (HPRDC) is proposed. As a DataFlow Engine (DFE) of such HPRDC, Maxeler’s acceleration card is used. The experiments for examining the acceleration of that algorithm on the Reconfigurable DataFlow Computers (RDC) are performed with two types of mammogram images with different resolutions. There were, also, several DFE configurations and each of them gave different acceleration of algorithm execution. Those accelerations are presented and experimental results have been shown good acceleration. Also, image processing using a mean filtering algorithm combined with thresholding and binarization algorithms and 3D visualization of murine lungs using marching cubes method are explained. These algorithms are mapped on the Maxeler’s DFE to significantly increase calculation speed. Optimal algorithm calculation speed was up to 20-fold baseline calculation speed