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Background Organisms typically face infection by diverse pathogens, and hosts are thought to have developed specific responses to each type of pathogen they encounter. The advent of transcriptomics now makes it possible to test this hypothesis and compare host gene expression responses to multiple pathogens at a genome-wide scale. Here, we performed a meta-analysis of multiple published and new transcriptomes using a newly developed bioinformatics approach that filters genes based on their expression profile across datasets. Thereby, we identified common and unique molecular responses of a model host species, the honey bee (Apis mellifera), to its major pathogens and parasites: the Microsporidia Nosema apis and Nosema ceranae, RNA viruses, and the ectoparasitic mite Varroa destructor, which transmits viruses. Results We identified a common suite of genes and conserved molecular pathways that respond to all investigated pathogens, a result that suggests a commonality in response mechanisms to diverse pathogens. We found that genes differentially expressed after infection exhibit a higher evolutionary rate than non-differentially expressed genes. Using our new bioinformatics approach, we unveiled additional pathogen-specific responses of honey bees; we found that apoptosis appeared to be an important response following microsporidian infection, while genes from the immune signalling pathways, Toll and Imd, were differentially expressed after Varroa/virus infection. Finally, we applied our bioinformatics approach and generated a gene co-expression network to identify highly connected (hub) genes that may represent important mediators and regulators of anti-pathogen responses. Conclusions Our meta-analysis generated a comprehensive overview of the host metabolic and other biological processes that mediate interactions between insects and their pathogens. We identified key host genes and pathways that respond to phylogenetically diverse pathogens, representing an important source for future functional studies as well as offering new routes to identify or generate pathogen resilient honey bee stocks. The statistical and bioinformatics approaches that were developed for this study are broadly applicable to synthesize information across transcriptomic datasets. These approaches will likely have utility in addressing a variety of biological questions. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3597-6) contains supplementary material, which is available to authorized users.

BackgroundHistone acetyltransferase enzymes (HATs) are implicated in regulation of transcription. HATs from different families may overlap in target and substrate specificity.ResultsWe isolated theelp3+gene encoding the histone acetyltransferase subunit of the Elongator complex in fission yeast and characterized the phenotype of an Δelp3mutant. We examined genetic interactions between Δelp3and two other HAT mutants, Δmst2and Δgcn5and used whole genome microarray analysis to analyze their effects on gene expression.ConclusionsComparison of phenotypes and expression profiles in single, double and triple mutants indicate that these HAT enzymes have overlapping functions. Consistent with this, overlapping specificity in histone H3 acetylation is observed. However, there is no evidence for overlap with another HAT enzyme, encoded by the essentialmst1+gene.

Background Bordetella pertussis, the causative agent of whooping cough, is a highly clonal pathogen of the respiratory tract. Its lack of genetic diversity, relative to many bacterial pathogens, could limit its ability to adapt to a hostile and changing host environment. This limitation might be overcome by phase variation, as observed for other mucosal pathogens. One of the most common mechanisms of phase variation is reversible expansion or contraction of homopolymeric tracts (HPTs). Results The genomes of B. pertussis and the two closely related species, B. bronchiseptica and B. parapertussis, were screened for homopolymeric tracts longer than expected on the basis of chance, given their nucleotide compositions. Sixty-nine such HPTs were found in total among the three genomes, 74% of which were polymorphic among the three species. Nine HPTs were genotyped in a collection of 90 geographically and temporally diverse B. pertussis strains using the polymerase chain reaction/ligase detection reaction (PCR/LDR) assay. Six HPTs were polymorphic in this collection of B. pertussis strains. Of note, one of these polymorphic HPTs was found in the fimX promoter, where a single base insertion variant was present in seven strains, all of which were isolated prior to introduction of the pertussis vaccine. Transcript abundance of fimX was found to be 3.8-fold lower in strains carrying the longer allele. HPTs in three other genes, tcfA, bapC, and BP3651, varied widely in composition across the strain collection and displayed allelic polymorphism within single cultures. Conclusion Allelic polymorphism at homopolymeric tracts is common within the B. pertussis genome. Phase variability may be an important mechanism in B. pertussis for evasion of the immune system and adaptation to different niches in the human host. High sensitivity and specificity make the PCR/LDR assay a powerful tool for investigating allelic variation at HPTs. Using this method, allelic diversity and phase variation were demonstrated at several B. pertussis loci.

Contains fulltext : 170302.pdf (Publisher’s version ) (Open Access) BACKGROUND: Organisms typically face infection by diverse pathogens, and hosts are thought to have developed specific responses to each type of pathogen they encounter. The advent of transcriptomics now makes it possible to test this hypothesis and compare host gene expression responses to multiple pathogens at a genome-wide scale. Here, we performed a meta-analysis of multiple published and new transcriptomes using a newly developed bioinformatics approach that filters genes based on their expression profile across datasets. Thereby, we identified common and unique molecular responses of a model host species, the honey bee (Apis mellifera), to its major pathogens and parasites: the Microsporidia Nosema apis and Nosema ceranae, RNA viruses, and the ectoparasitic mite Varroa destructor, which transmits viruses. RESULTS: We identified a common suite of genes and conserved molecular pathways that respond to all investigated pathogens, a result that suggests a commonality in response mechanisms to diverse pathogens. We found that genes differentially expressed after infection exhibit a higher evolutionary rate than non-differentially expressed genes. Using our new bioinformatics approach, we unveiled additional pathogen-specific responses of honey bees; we found that apoptosis appeared to be an important response following microsporidian infection, while genes from the immune signalling pathways, Toll and Imd, were differentially expressed after Varroa/virus infection. Finally, we applied our bioinformatics approach and generated a gene co-expression network to identify highly connected (hub) genes that may represent important mediators and regulators of anti-pathogen responses. CONCLUSIONS: Our meta-analysis generated a comprehensive overview of the host metabolic and other biological processes that mediate interactions between insects and their pathogens. We identified key host genes and pathways that respond to phylogenetically diverse pathogens, representing an important source for future functional studies as well as offering new routes to identify or generate pathogen resilient honey bee stocks. The statistical and bioinformatics approaches that were developed for this study are broadly applicable to synthesize information across transcriptomic datasets. These approaches will likely have utility in addressing a variety of biological questions.

Background Roberts syndrome (RBS) is a human developmental disorder caused by mutations in the cohesin acetyltransferase ESCO2. We previously reported that mTORC1 signaling was depressed and overall translation was reduced in RBS cells and zebrafish models for RBS. Treatment of RBS cells and zebrafish RBS models with L-leucine partially rescued mTOR function and protein synthesis, correlating with increased cell division and improved development. Results In this study, we use RBS cells to model mTORC1 repression and analyze transcription and translation with ribosome profiling to determine gene-level effects of L-leucine. L-leucine treatment partially rescued translational efficiency of ribosomal subunits, translation initiation factors, snoRNA production, and mitochondrial function in RBS cells, consistent with these processes being mTORC1 controlled. In contrast, other genes are differentially expressed independent of L-leucine treatment, including imprinted genes such as H19 and GTL2, miRNAs regulated by GTL2, HOX genes, and genes in nucleolar associated domains. Conclusions Our study distinguishes between gene expression changes in RBS cells that are TOR dependent and those that are independent. Some of the TOR independent gene expression changes likely reflect the architectural role of cohesin in chromatin looping and gene expression. This study reveals the dramatic rescue effects of L-leucine stimulation of mTORC1 in RBS cells and supports that normal gene expression and translation requires ESCO2 function. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-2354-y) contains supplementary material, which is available to authorized users.