Secondary metabolism of the forest pathogen Dothistroma septosporum : a thesis presented in the partial fulfilment of the requirements for the degree of Doctor of Philosophy (PhD) in Genetics at Massey University, Manawatu, New Zealand

Dothistroma septosporum is a fungus causing the disease Dothistroma needle blight (DNB) on more than 80 pine species in 76 countries, and causes serious economic losses. A secondary metabolite (SM) dothistromin, produced by D. septosporum, is a virulence factor required for full disease expression but is not needed for the initial formation of disease lesions. Unlike the majority of fungal SMs whose biosynthetic enzyme genes are arranged in a gene cluster, dothistromin genes are dispersed in a fragmented arrangement. Therefore, it was of interest whether D. septosporum has other SMs that are required in the disease process, as well as having SM genes that are clustered as in other fungi. Genome sequencing of D. septosporum revealed that D. septosporum has 11 SM core genes, which is fewer than in closely related species. In this project, gene cluster analyses around the SM core genes were done to assess if there are intact or other fragmented gene clusters. In addition, one of the core SM genes, DsNps3, that was highly expressed at an early stage of plant infection, was knocked out and the phenotype of this mutant was analysed. Then, evolutionary selection pressures on the SM core genes were analysed using the SM core gene sequences across 19 D. septosporum strains from around the world. Finally, phylogenetic analyses on some of the SM core genes were done to find out if these genes have functionally characterised orthologs. Analysis of the ten D. septosporum SM core genes studied in this project showed that two of them were pseudogenes, and five others had very low expression levels in planta. Three of the SM core genes showed high expression levels in planta. These three genes, DsPks1, DsPks2 and DsNps3, were key genes of interest in this project. But despite the different expression levels, evolutionary selection pressure analyses showed that all of the SM core genes apart from the pseudogenes are under negative selection, suggesting that D. septosporum might actively use most of its SMs under certain conditions. In silico predictions based on the amino acid sequences of the proteins encoded by SM core genes and gene cluster analyses showed that four of the SM core genes are predicted to produce known metabolites. These are melanin (DsPks1), cyclosporin (DsNps1), ferricrocin (DsNps2) and cyclopiazonic acid (DsHps1). Gene cluster analyses revealed that at least three of the D. septosporum SMs might be produced by fragmented gene clusters (DsPks1, DsNps1, DsNps2). This suggested that dothistromin might not be the only fragmented SM gene cluster in D. septosporum. According to phylogenetic analyses, some of the D. septosporum SM core genes have no orthologs among its class (Dothideomycetes), suggesting some of the D. septosporum SMs may be unique. One such example is the metabolite produced by DsNps3. Comparison of wild type and ΔDsNps3 D. septosporum strains showed that the ΔDsNps3 strain produces fewer spores, less hyphal surface network at an early stage of plant infection, and lower levels of fungal biomass in disease lesions compared to wild type, suggesting that the DsNps3 SM may be a virulence factor. Attempts to identify a metabolite associated with DsNps3, and to knockout another gene of key interest, DsPks2, for functional characterization were unsuccessful. Further work is required to confirm the gene clusters, characterise the SMs and their roles. However, the findings so far suggest that dothistromin is unlikely to be the only D. septosporum SM that is a virulence factor in since the DsNps3 SM also appears to be involved in virulence. Likewise the fragmented dothistromin cluster may not be the only one in the genome and there may be at least three more fragmented SM gene clusters

Finding the Core-Genes of Chloroplasts

Due to the recent evolution of sequencing techniques, the number of available genomes is rising steadily, leading to the possibility to make large scale genomic comparison between sets of close species. An interesting question to answer is: what is the common functionality genes of a collection of species, or conversely, to determine what is specific to a given species when compared to other ones belonging in the same genus, family, etc. Investigating such problem means to find both core and pan genomes of a collection of species, \textit{i.e.}, genes in common to all the species vs. the set of all genes in all species under consideration. However, obtaining trustworthy core and pan genomes is not an easy task, leading to a large amount of computation, and requiring a rigorous methodology. Surprisingly, as far as we know, this methodology in finding core and pan genomes has not really been deeply investigated. This research work tries to fill this gap by focusing only on chloroplastic genomes, whose reasonable sizes allow a deep study. To achieve this goal, a collection of 99 chloroplasts are considered in this article. Two methodologies have been investigated, respectively based on sequence similarities and genes names taken from annotation tools. The obtained results will finally be evaluated in terms of biological relevance

The RNA Polymerase II Core Promoter in Drosophila.

Transcription by RNA polymerase II initiates at the core promoter, which is sometimes referred to as the "gateway to transcription." Here, we describe the properties of the RNA polymerase II core promoter in Drosophila The core promoter is at a strategic position in the expression of genes, as it is the site of convergence of the signals that lead to transcriptional activation. Importantly, core promoters are diverse in terms of their structure and function. They are composed of various combinations of sequence motifs such as the TATA box, initiator (Inr), and downstream core promoter element (DPE). Different types of core promoters are transcribed via distinct mechanisms. Moreover, some transcriptional enhancers exhibit specificity for particular types of core promoters. These findings indicate that the core promoter is a central component of the transcriptional apparatus that regulates gene expression

The cell cycle regulatory DREAM complex is disrupted by high expression of oncogenic B-Myb.

Overexpression of the oncogene MYBL2 (B-Myb) is associated with increased cell proliferation and serves as a marker of poor prognosis in cancer. However, the mechanism by which B-Myb alters the cell cycle is not fully understood. In proliferating cells, B-Myb interacts with the MuvB core complex including LIN9, LIN37, LIN52, RBBP4, and LIN54, forming the MMB (Myb-MuvB) complex, and promotes transcription of genes required for mitosis. Alternatively, the MuvB core interacts with Rb-like protein p130 and E2F4-DP1 to form the DREAM complex that mediates global repression of cell cycle genes in G0/G1, including a subset of MMB target genes. Here, we show that overexpression of B-Myb disrupts the DREAM complex in human cells, and this activity depends on the intact MuvB-binding domain in B-Myb. Furthermore, we found that B-Myb regulates the protein expression levels of the MuvB core subunit LIN52, a key adapter for assembly of both the DREAM and MMB complexes, by a mechanism that requires S28 phosphorylation site in LIN52. Given that high expression of B-Myb correlates with global loss of repression of DREAM target genes in breast and ovarian cancer, our findings offer mechanistic insights for aggressiveness of cancers with MYBL2 amplification, and establish the rationale for targeting B-Myb to restore cell cycle control

Data-mining the FlyAtlas online resource to identify core functional motifs across transporting epithelia

<p>Background Comparative analysis of tissue-specific transcriptomes is a powerful technique to uncover tissue functions. Our FlyAtlas.org provides authoritative gene expression levels for multiple tissues of Drosophila melanogaster (1). Although the main use of such resources is single gene lookup, there is the potential for powerful meta-analysis to address questions that could not easily be framed otherwise. Here, we illustrate the power of data-mining of FlyAtlas data by comparing epithelial transcriptomes to identify a core set of highly-expressed genes, across the four major epithelial tissues (salivary glands, Malpighian tubules, midgut and hindgut) of both adults and larvae.</p> <p>Method Parallel hypothesis-led and hypothesis-free approaches were adopted to identify core genes that underpin insect epithelial function. In the former, gene lists were created from transport processes identified in the literature, and their expression profiles mapped from the flyatlas.org online dataset. In the latter, gene enrichment lists were prepared for each epithelium, and genes (both transport related and unrelated) consistently enriched in transporting epithelia identified.</p> <p>Results: A key set of transport genes, comprising V-ATPases, cation exchangers, aquaporins, potassium and chloride channels, and carbonic anhydrase, was found to be highly enriched across the epithelial tissues, compared with the whole fly. Additionally, a further set of genes that had not been predicted to have epithelial roles, were co-expressed with the core transporters, extending our view of what makes a transporting epithelium work. Further insights were obtained by studying the genes uniquely overexpressed in each epithelium; for example, the salivary gland expresses lipases, the midgut organic solute transporters, the tubules specialize for purine metabolism and the hindgut overexpresses still unknown genes.</p> <p>Conclusion Taken together, these data provide a unique insight into epithelial function in this key model insect, and a framework for comparison with other species. They also provide a methodology for function-led datamining of FlyAtlas.org and other multi-tissue expression datasets.</p&gt

Improved Core Genes Prediction for Constructing well-supported Phylogenetic Trees in large sets of Plant Species

The way to infer well-supported phylogenetic trees that precisely reflect the evolutionary process is a challenging task that completely depends on the way the related core genes have been found. In previous computational biology studies, many similarity based algorithms, mainly dependent on calculating sequence alignment matrices, have been proposed to find them. In these kinds of approaches, a significantly high similarity score between two coding sequences extracted from a given annotation tool means that one has the same genes. In a previous work article, we presented a quality test approach (QTA) that improves the core genes quality by combining two annotation tools (namely NCBI, a partially human-curated database, and DOGMA, an efficient annotation algorithm for chloroplasts). This method takes the advantages from both sequence similarity and gene features to guarantee that the core genome contains correct and well-clustered coding sequences (\emph{i.e.}, genes). We then show in this article how useful are such well-defined core genes for biomolecular phylogenetic reconstructions, by investigating various subsets of core genes at various family or genus levels, leading to subtrees with strong bootstraps that are finally merged in a well-supported supertree.Comment: 12 pages, 7 figures, IWBBIO 2015 (3rd International Work-Conference on Bioinformatics and Biomedical Engineering

Genomic comparison of diverse Salmonella serovars isolated from swine.

Food animals act as a reservoir for many foodborne pathogens. Salmonella enterica is one of the leading pathogens that cause food borne illness in a broad host range including animals and humans. They can also be associated with a single host species or a subset of hosts, due to genetic factors associated with colonization and infection. Adult swine are often asymptomatic carriers of a broad range of Salmonella servoars and can act as an important reservoir of infections for humans. In order to understand the genetic variations among different Salmonella serovars, Whole Genome Sequences (WGS) of fourteen Salmonella serovars from swine products were analyzed. More than 75% of the genes were part of the core genome in each isolate and the higher fraction of gene assign to different functional categories in dispensable genes indicated that these genes acquired for better adaptability and diversity. High concordance (97%) was detected between phenotypically confirmed antibiotic resistances and identified antibiotic resistance genes from WGS. The resistance determinants were mainly located on mobile genetic elements (MGE) on plasmids or integrated into the chromosome. Most of known and putative virulence genes were part of the core genome, but a small fraction were detected on MGE. Predicted integrated phage were highly diverse and many harbored virulence, metal resistance, or antibiotic resistance genes. CRISPR (Clustered regularly interspaced short palindromic repeats) patterns revealed the common ancestry or infection history among Salmonella serovars. Overall genomic analysis revealed a great deal of diversity among Salmonella serovars due to acquired genes that enable them to thrive and survive during infection