Transcriptional Down-Regulation and rRNA Cleavage in Dictyostelium discoideum Mitochondria during Legionella pneumophila Infection

Bacterial pathogens employ a variety of survival strategies when they invade eukaryotic cells. The amoeba Dictyostelium discoideum is used as a model host to study the pathogenic mechanisms that Legionella pneumophila, the causative agent of Legionnaire's disease, uses to kill eukaryotic cells. Here we show that the infection of D. discoideum by L. pneumophila results in a decrease in mitochondrial messenger RNAs, beginning more than 8 hours prior to detectable host cell death. These changes can be mimicked by hydrogen peroxide treatment, but not by other cytotoxic agents. The mitochondrial large subunit ribosomal RNA (LSU rRNA) is also cleaved at three specific sites during the course of infection. Two LSU rRNA fragments appear first, followed by smaller fragments produced by additional cleavage events. The initial LSU rRNA cleavage site is predicted to be on the surface of the large subunit of the mitochondrial ribosome, while two secondary sites map to the predicted interface with the small subunit. No LSU rRNA cleavage was observed after exposure of D. discoideum to hydrogen peroxide, or other cytotoxic chemicals that kill cells in a variety of ways. Functional L. pneumophila type II and type IV secretion systems are required for the cleavage, establishing a correlation between the pathogenesis of L. pneumophila and D. discoideum LSU rRNA destruction. LSU rRNA cleavage was not observed in L. pneumophila infections of Acanthamoeba castellanii or human U937 cells, suggesting that L. pneumophila uses distinct mechanisms to interrupt metabolism in different hosts. Thus, L. pneumophila infection of D. discoideum results in dramatic decrease of mitochondrial RNAs, and in the specific cleavage of mitochondrial rRNA. The predicted location of the cleavage sites on the mitochondrial ribosome suggests that rRNA destruction is initiated by a specific sequence of events. These findings suggest that L. pneumophila specifically disrupts mitochondrial protein synthesis in D. discoideum during the course of infection

GenePath: a System for Automated Construction of Genetic Networks from Mutant Data

Motivation: Genetic pathways are often used in the analysis of biological phenomena. In classical genetics, they are constructed manually from experimental data on mutants. The field lacks formalism to guide such analysis, and accounting for all the data becomes complicated when large amounts of data are considered. Results: We have developed GenePath, an intelligent assistant that mimics expert geneticists in the analysis of genetic data. GenePath employs expert-defined patterns to uncover gene relations from the data, and uses these relations as constraints that guide the search for a plausible genetic network. GenePath provides formalism to genetic data analysis, facilitates the consideration of all the available data in a consistent and systematic manner, and aids in the examination of the large number of possible consequences of a planned experiment. It also provides an explanation mechanism that traces back every finding to the pertinent data. GenePath was successfully tested on several genetic problems. Availability: GenePath can be accessed at http://genepath.org. Supplementary information: Supplementary material is available at http://genepath.org/bi-supp

Web-enabled knowledge-based analysis of genetic data

We present a web-based implementation of GenePath, an intelligent assistant tool for data analysis in functional genomics. GenePath considers mutant data and uses expert-defined patterns to find gene-to-gene or gene-to-outcome relations. It presents the results of analysis as genetic networks, wherein a set of genes has various influence on one another and on a biological outcome. In the paper, we particularly focus on its web-based interface and explanation mechanisms

High-throughput analysis of spatio-temporal dynamics in Dictyostelium

A time-lapse based approach is presented that allows a rapid examination of the spatio-temporal dynamics of Dictyostelium cell populations, enabling users to search and retrieve movies on a gene-by-gene and phenotype-by-phenotype basis

Gene prioritization by compressive data fusion and chaining

Data integration procedures combine heterogeneous data sets into predictive models, but they are limited to data explicitly related to the target object type, such as genes. Collage is a new data fusion approach to gene prioritization. It considers data sets of various association levels with the prediction task, utilizes collective matrix factorization to compress the data, and chaining to relate different object types contained in a data compendium. Collage prioritizes genes based on their similarity to several seed genes. We tested Collage by prioritizing bacterial response genes in Dictyostelium as a novel model system for prokaryote-eukaryote interactions. Using 4 seed genes and 14 data sets, only one of which was directly related to the bacterial response, Collage proposed 8 candidate genes that were readily validated as necessary for the response of Dictyostelium to Gram-negative bacteria. These findings establish Collage as a method for inferring biological knowledge from the integration of heterogeneous and coarsely related data sets

A new social gene in Dictyostelium discoideum, chtB

Background: Competitive social interactions are ubiquitous in nature, but their genetic basis is difficult to determine. Much can be learned from single gene knockouts in a eukaryote microbe. The mutants can be competed with the parent to discern the social impact of that specific gene. Dictyostelium discoideum is a social amoeba that exhibits cooperative behavior in the construction of a multicellular fruiting body. It is a good model organism to study the genetic basis of cooperation since it has a sequenced genome and it is amenable to genetic manipulation. When two strains of D. discoideum are mixed, a cheater strain can exploit its social partner by differentiating more spore than its fair share relative to stalk cells. Cheater strains can be generated in the lab or found in the wild and genetic analyses have shown that cheating behavior can be achieved through many pathways. Results: We have characterized the knockout mutant chtB, which was isolated from a screen for cheater mutants that were also able to form normal fruiting bodies on their own. When mixed in equal proportions with parental strain cells, chtB mutants contributed almost 60% of the total number of spores. To do so, chtB cells inhibit wild type cells from becoming spores, as indicated by counts and by the wild type cells’ reduced expression of the prespore gene, cotB. We found no obvious fitness costs (morphology, doubling time in liquid medium, spore production, and germination efficiency) associated with the cheating ability of the chtB knockout. Conclusions: In this study we describe a new gene in D. discoideum, chtB, which when knocked out inhibits the parental strain from producing spores. Moreover, under lab conditions, we did not detect any fitness costs associated with this behavior

Cell–Cell Adhesion Prevents Mutant Cells Lacking Myosin II from Penetrating Aggregation Streams ofDictyostelium

AbstractWhen a small number of fluorescently labeled myosin II mutant cells (mhcA−) are mixed with wild-type cells and development of the chimeras is observed by confocal microscopy, the mutant cells are localized to the edges of aggregation streams and mounds. Moreover, the mutant cells stick to wild-type cells and become distorted (Shelden and Knecht, 1995). Two independent adhesion mechanisms, Contact Sites A and Contact Sites B, function during the aggregation stage and either one or both might be responsible for excluding the myosin II null cells. We have mixedmhcA−cells with cells in which the appearance of Contact Sites B is delayed (strain TL72) as well as cells which lack Contact Sites A (strain GT10) and double mutants in which both adhesion mechanisms are affected (strain TL73). In all chimeras, themhcA−cells were distorted by interactions with the adhesion mutant cells, indicating that it does not require significant adhesive interaction to distort the flaccid cortex ofmhcA−cells.mhcA−cells were excluded from streams composed of cells lacking either Contact Sites A or Contact Sites B but mixed randomly with cells lacking both adhesion systems. By 10 hr of development, cells of strain TL73 acquire Contact Sites B adhesion. If cells of this strain were mixed with labeledmhcA−cells, allowed to develop for 9 hr, and then dissociated before replating, the myosin II null cells were seen to be distorted and excluded from the reaggregates. Thus the exclusion ofmhcA−cells from streams can be accomplished by either Contact Sites A or B. When chimeras of labeled TL73 and wild-type cells were made, the TL73 cells were found to be randomly mixed into aggregation streams. This result indicates that adhesive sorting does not function during aggregation and so cannot account for the exclusion ofmhcA−cells from streams. We hypothesize that the flaccid cortex ofmhcA−cells cannot generate sufficient protrusive force to break the contacts between adhered cells in aggregation streams but can enter streams where the cells are weakly adherent

Polymorphic members of the lag gene family mediate kin discrimination in Dictyostelium

Self and kin discrimination are observed in most kingdoms of life and are mediated by highly polymorphic plasma membrane proteins. Sequence polymorphism, which is essential for effective recognition, is maintained by balancing selection. Dictyostelium discoideum are social amoebas that propagate as unicellular organisms but aggregate upon starvation and form fruiting bodies with viable spores and dead stalk cells. Aggregative development exposes Dictyostelium to the perils of chimerism, including cheating, which raises questions about how the victims survive in nature and how social cooperation persists. Dictyostelids can minimize the cost of chimerism by preferential cooperation with kin, but the mechanisms of kin discrimination are largely unknown. Dictyostelium lag genes encode transmembrane proteins with multiple immunoglobulin (Ig) repeats that participate in cell adhesion and signaling. Here, we describe their role in kin discrimination. We show that lagB1 and lagC1 are highly polymorphic in natural populations and that their sequence dissimilarity correlates well with wild-strain segregation. Deleting lagB1 and lagC1 results in strain segregation in chimeras with wild-type cells, whereas elimination of the nearly invariant homolog lagD1 has no such consequences. These findings reveal an early evolutionary origin of kin discrimination and provide insight into the mechanism of social recognition and immunity

New components of the Dictyostelium PKA pathway revealed by Bayesian analysis of expression data

<p>Abstract</p> <p>Background</p> <p>Identifying candidate genes in genetic networks is important for understanding regulation and biological function. Large gene expression datasets contain relevant information about genetic networks, but mining the data is not a trivial task. Algorithms that infer Bayesian networks from expression data are powerful tools for learning complex genetic networks, since they can incorporate prior knowledge and uncover higher-order dependencies among genes. However, these algorithms are computationally demanding, so novel techniques that allow targeted exploration for discovering new members of known pathways are essential.</p> <p>Results</p> <p>Here we describe a Bayesian network approach that addresses a specific network within a large dataset to discover new components. Our algorithm draws individual genes from a large gene-expression repository, and ranks them as potential members of a known pathway. We apply this method to discover new components of the cAMP-dependent protein kinase (PKA) pathway, a central regulator of <it>Dictyostelium discoideum </it>development. The PKA network is well studied in <it>D. discoideum </it>but the transcriptional networks that regulate PKA activity and the transcriptional outcomes of PKA function are largely unknown. Most of the genes highly ranked by our method encode either known components of the PKA pathway or are good candidates. We tested 5 uncharacterized highly ranked genes by creating mutant strains and identified a candidate cAMP-response element-binding protein, yet undiscovered in <it>D. discoideum</it>, and a histidine kinase, a candidate upstream regulator of PKA activity.</p> <p>Conclusions</p> <p>The single-gene expansion method is useful in identifying new components of known pathways. The method takes advantage of the Bayesian framework to incorporate prior biological knowledge and discovers higher-order dependencies among genes while greatly reducing the computational resources required to process high-throughput datasets.</p