Geraint Barton

Genome Expansion and Gene Loss in Powdery Mildew Fungi Reveal Tradeoffs in Extreme Parasitism

From Blight to Powdery Mildew Pathogenic effects of microbes on plants have widespread consequences. Witness, for example, the cultural upheavals driven by potato blight in the 1800s. A variety of microbial pathogens continue to afflict crop plants today, driving both loss of yield and incurring the increased costs of control mechanisms. Now, four reports analyze microbial genomes in order to understand better how plant pathogens function (see the Perspective by Dodds). Raffaele et al. (p. 1540) describe how the genome of the potato blight pathogen accommodates transfer to different hosts. Spanu et al. (p. 1543) analyze what it takes to be an obligate biotroph in barley powdery mildew, and Baxter et al. (p. 1549) ask a similar question for a natural pathogen of Arabidopsis. Schirawski et al. (p. 1546) compared genomes of maize pathogens to identify virulence determinants. Better knowledge of what in a genome makes a pathogen efficient and deadly is likely to be useful for improving agricultural crop management and breeding. A group of papers analyzes pathogen genomes to find the roots of virulence, opportunism, and life-style determinants. Powdery mildews are phytopathogens whose growth and reproduction are entirely dependent on living plant cells. The molecular basis of this life-style, obligate biotrophy, remains unknown. We present the genome analysis of barley powdery mildew, Blumeria graminis f.sp. hordei (Blumeria), as well as a comparison with the analysis of two powdery mildews pathogenic on dicotyledonous plants. These genomes display massive retrotransposon proliferation, genome-size expansion, and gene losses. The missing genes encode enzymes of primary and secondary metabolism, carbohydrate-active enzymes, and transporters, probably reflecting their redundancy in an exclusively biotrophic life-style. Among the 248 candidate effectors of pathogenesis identified in the Blumeria genome, very few (less than 10) define a core set conserved in all three mildews, suggesting that most effectors represent species-specific adaptations.

Structure and evolution of barley powdery mildew effector candidates

BackgroundProtein effectors of pathogenicity are instrumental in modulating host immunity and disease resistance. The powdery mildew pathogen of grasses Blumeria graminis causes one of the most important diseases of cereal crops. B. graminis is an obligate biotrophic pathogen and as such has an absolute requirement to suppress or avoid host immunity if it is to survive and cause disease.ResultsHere we characterise a superfamily predicted to be the full complement of Candidates for Secreted Effector Proteins (CSEPs) in the fungal barley powdery mildew parasite B. graminis f.sp. hordei. The 491 genes encoding these proteins constitute over 7% of this pathogen’s annotated genes and most were grouped into 72 families of up to 59 members. They were predominantly expressed in the intracellular feeding structures called haustoria, and proteins specifically associated with the haustoria were identified by large-scale mass spectrometry-based proteomics. There are two major types of effector families: one comprises shorter proteins (100–150 amino acids), with a high relative expression level in the haustoria and evidence of extensive diversifying selection between paralogs; the second type consists of longer proteins (300–400 amino acids), with lower levels of differential expression and evidence of purifying selection between paralogs. An analysis of the predicted protein structures underscores their overall similarity to known fungal effectors, but also highlights unexpected structural affinities to ribonucleases throughout the entire effector super-family. Candidate effector genes belonging to the same family are loosely clustered in the genome and are associated with repetitive DNA derived from retro-transposons.ConclusionsWe employed the full complement of genomic, transcriptomic and proteomic analyses as well as structural prediction methods to identify and characterize the members of the CSEPs superfamily in B. graminis f.sp. hordei. Based on relative intron position and the distribution of CSEPs with a ribonuclease-like domain in the phylogenetic tree we hypothesize that the associated genes originated from an ancestral gene, encoding a secreted ribonuclease, duplicated successively by repetitive DNA-driven processes and diversified during the evolution of the grass and cereal powdery mildew lineage.

Identification of genes selectively disallowed in the pancreatic islet

We have previously identified two genes, encoding lactate dehydrogenase (Ldha) and the monocarboxylate carrier, MCT1 (Slc16a1) whose expression is remarkably low in pancreatic β-cells and islets. We sought here to determine whether these may be part of a larger family of genes selectively repressed (“disallowed”) in the pancreatic islet. Using new and publicly available microarray data, we undertook a bioinformatic analysis of gene expression in islets and a range of other murine tissues. We compared data sets from three sources of mouse pancreatic islets with a total of 30 datasets from nine tissues, to identify genes with at least five-fold down-regulation in islets. 39 genes were revealed as being specifically repressed in islets. These included Ldha and Slc16a1 as expected but also genes involved in several other metabolic pathways which could affect glucose stimulated insulin secretion. Of these, adenylate kinase 3 (AK3) is a mitochondrial enzyme which acts on GTP, and ornithine aminotransferase (OAT) lies on the pathway converting glutamate to ornithine. The removal of an enzyme which could dissipate mitochondrial GTP levels in beta cells provides support for the theory that mitochondrial GTP may be an important for regulating insulin secretion, whilst blocking an alternative metabolic fate for glutamate is consistent with a signalling role for glutamate. The identification of these genes should inform efforts to generate fully functional β-cells from stem cell sources, and may provide new targets in type 2 diabetes.

Nitrogen stress response and stringent response are coupled in Escherichia coli

Assimilation of nitrogen is an essential process in bacteria. The nitrogen regulation stress response is an adaptive mechanism used by nitrogen-starved Escherichia coli to scavenge for alternative nitrogen sources and requires the global transcriptional regulator NtrC. In addition, nitrogen-starved E. coli cells synthesize a signal molecule, guanosine tetraphosphate (ppGpp), which serves as an effector molecule of many processes including transcription to initiate global physiological changes, collectively termed the stringent response. The regulatory mechanisms leading to elevated ppGpp levels during nutritional stresses remain elusive. Here, we show that transcription of relA, a key gene responsible for the synthesis of ppGpp, is activated by NtrC during nitrogen starvation. The results reveal that NtrC couples these two major bacterial stress responses to manage conditions of nitrogen limitation, and provide novel mechanistic insights into how a specific nutritional stress leads to elevating ppGpp levels in bacteria.

Genome wide analysis of the complete GlnR nitrogen-response regulon in Mycobacterium smegmatis

BackgroundNitrogen is an essential element for bacterial growth and an important component of biological macromolecules. Consequently, responding to nitrogen limitation is critical for bacterial survival and involves the interplay of signalling pathways and transcriptional regulation of nitrogen assimilation and scavenging genes. In the soil dwelling saprophyte Mycobacterium smegmatis the OmpR-type response regulator GlnR is thought to mediate the transcriptomic response to nitrogen limitation. However, to date only ten genes have been shown to be in the GlnR regulon, a vastly reduced number compared to other organisms.ResultsWe investigated the role of GlnR in the nitrogen limitation response and determined the entire GlnR regulon, by combining expression profiling of M. smegmatis wild type and glnR deletion mutant, with GlnR-specific chromatin immunoprecipitation and high throughput sequencing. We identify 53 GlnR binding sites during nitrogen limitation that control the expression of over 100 genes, demonstrating that GlnR is the regulator controlling the assimilation and utilisation of nitrogen. We also determine a consensus GlnR binding motif and identify key residues within the motif that are required for specific GlnR binding.ConclusionsWe have demonstrated that GlnR is the global nitrogen response regulator in M. smegmatis, directly regulating the expression of more than 100 genes. GlnR controls key nitrogen stress survival processes including primary nitrogen metabolism pathways, the ability to utilise nitrate and urea as alternative nitrogen sources, and the potential to use cellular components to provide a source of ammonium. These studies further our understanding of how mycobacteria survive nutrient limiting conditions.

CombFunc: predicting protein function using heterogeneous data sources

Only a small fraction of known proteins have been functionally characterized, making protein function prediction essential to propose annotations for uncharacterized proteins. In recent years many function prediction methods have been developed using various sources of biological data from protein sequence and structure to gene expression data. Here we present the CombFunc web server, which makes Gene Ontology (GO)-based protein function predictions. CombFunc incorporates ConFunc, our existing function prediction method, with other approaches for function prediction that use protein sequence, gene expression and protein–protein interaction data. In benchmarking on a set of 1686 proteins CombFunc obtains precision and recall of 0.71 and 0.64 respectively for gene ontology molecular function terms. For biological process GO terms precision of 0.74 and recall of 0.41 is obtained. CombFunc is available at http://www.sbg.bio.ic.ac.uk/combfunc.

Gene expression profiling in male genital lichen sclerosus

Male genital lichen sclerosus (MGLSc) has a bimodal distribution in boys and men. It is associated with squamous cell carcinoma (SCC). The pathogenesis of MGLSc is unknown. HPV and autoimmune mechanisms have been mooted. Anti extracellular matrix protein (ECM)1 antibodies have been identified in women with GLSc. The gene expression pattern of LSc is unknown. Using DNA microarrays we studied differences in gene expression in healthy and diseased prepuces obtained at circumcision in adult males with MGLSc (n = 4), paediatric LSc (n = 2) and normal healthy paediatric foreskin (n = 4). In adult samples 51 genes with significantly increased expression and 87 genes with significantly reduced expression were identified; paediatric samples revealed 190 genes with significantly increased expression and 148 genes with significantly reduced expression. Concordance of expression profiles between adult and paediatric samples indicates the same disease process. Functional analysis revealed increased expression in the adult and child MGSLc samples in the immune response/cellular defence gene ontology (GO) category and reduced expression in other categories including genes related to squamous cancer. No specific HPV, autoimmune or squamous carcinogenesis‐associated gene expression patterns were found. ECM1 and CABLES1 expression were significantly reduced in paediatric and adult samples respectively.

Interactions between inflammatory signals and the progesterone receptor in regulating gene expression in pregnant human uterine myocytes.

The absence of a fall in circulating progesterone levels has led to the concept that human labour is associated with ‘functional progesterone withdrawal’ caused through changes in the expression or function of progesterone receptor (PR). At the time of labour, the human uterus is heavily infiltrated with inflammatory cells, which release cytokines to create a ‘myometrial inflammation’ via NF‐κB activation. The negative interaction between NF‐κB and PR, may represent a mechanism to account for ‘functional progesterone withdrawal’ at term. Conversely, PR may act to inhibit NF‐κB function and so play a role in inhibition of myometrial inflammation during pregnancy. To model this inter‐relationship, we have used small interfering (si) RNA‐mediated knock‐down of PR in human pregnant myocytes and whole genome microarray analysis to identify genes regulated through PR. We then activated myometrial inflammation using IL‐1β stimulation to determine the role of PR in myometrial inflammation regulation. Through PR‐knock‐down, we found that PR regulates gene networks involved in myometrial quiescence and extracellular matrix integrity. Activation of myometrial inflammation was found to antagonize PR‐induced gene expression, of genes normally upregulated via PR. We found that PR does not play a role in repression of pro‐inflammatory gene networks induced by IL‐1β and that only MMP10 was significantly regulated in opposite directions by IL‐1β and PR. We conclude that progesterone acting through PR does not generally inhibit myometrial inflammation. Activation of myometrial inflammation does cause ‘functional progesterone withdrawal’ but only in the context of genes normally upregulated via PR.

MiMiR – an integrated platform for microarray data sharing, mining and analysis

BackgroundDespite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Mi croarray data Mi ning R esource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data.ResultsA user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package.ConclusionThe new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centres large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies.

Deciphering the metabolic response of Mycobacterium tuberculosis to nitrogen stress

A key component to the success of Mycobacterium tuberculosis as a pathogen is the ability to sense and adapt metabolically to the diverse range of conditions encountered in vivo, such as oxygen tension, environmental pH and nutrient availability. Although nitrogen is an essential nutrient for every organism, little is known about the genes and pathways responsible for nitrogen assimilation in M. tuberculosis. In this study we have used transcriptomics and chromatin immunoprecipitation and high‐throughput sequencing to address this. In response to nitrogen starvation, a total of 185 genes were significantly differentially expressed (96 up‐regulated and 89 down regulated; 5% genome) highlighting several significant areas of metabolic change during nitrogen limitation such as nitrate/nitrite metabolism, aspartate metabolism and changes in cell wall biosynthesis. We identify GlnR as a regulator involved in the nitrogen response, controlling the expression of at least 33 genes in response to nitrogen limitation. We identify a consensus GlnR binding site and relate its location to known transcriptional start sites. We also show that the GlnR response regulator plays a very different role in M. tuberculosis to that in non‐pathogenic mycobacteria, controlling genes involved in nitric oxide detoxification and intracellular survival instead of genes involved in nitrogen scavenging.