Project description:This SuperSeries is composed of the following subset Series: GSE28549: Anaerobic Oxidation of Benzene by the Hyperthermophilic Archaeon Ferroglobus placidus (Phenol vs. Benzoate) GSE30798: Anaerobic Oxidation of Benzene by the Hyperthermophilic Archaeon Ferroglobus placidus (Benzene vs. Acetate) GSE30799: Anaerobic Oxidation of Benzene by the Hyperthermophilic Archaeon Ferroglobus placidus (Benzene vs. Phenol) GSE30801: Anaerobic Oxidation of Benzene by the Hyperthermophilic Archaeon Ferroglobus placidus (Benzene vs. Benzoate) Refer to individual Series
Project description:This SuperSeries is composed of the following subset Series: GSE26421: Expression analysis of benzoate degradation in the hyperthermophilic archaeon Ferroglobus placidus GSE26423: Expression analysis of phenol degradation in the hyperthermophilic archaeon Ferroglobus placidus Refer to individual Series
Project description:BackgroundThe relationship between the hyperthermophiles Ignicoccus hospitalis and Nanoarchaeum equitans is the only known example of a specific association between two species of Archaea. Little is known about the mechanisms that enable this relationship.ResultsWe sequenced the complete genome of I. hospitalis and found it to be the smallest among independent, free-living organisms. A comparative genomic reconstruction suggests that the I. hospitalis lineage has lost most of the genes associated with a heterotrophic metabolism that is characteristic of most of the Crenarchaeota. A streamlined genome is also suggested by a low frequency of paralogs and fragmentation of many operons. However, this process appears to be partially balanced by lateral gene transfer from archaeal and bacterial sources.ConclusionsA combination of genomic and cellular features suggests highly efficient adaptation to the low energy yield of sulfur-hydrogen respiration and efficient inorganic carbon and nitrogen assimilation. Evidence of lateral gene exchange between N. equitans and I. hospitalis indicates that the relationship has impacted both genomes. This association is the simplest symbiotic system known to date and a unique model for studying mechanisms of interspecific relationships at the genomic and metabolic levels.
Project description:In this study, we generated allelic knockouts of ATP-dependent RNA ligase (Rnl) in hyperthermophilic archaeon T. kodakarensis and analyze the small RNAs.
Project description:BackgroundStudies of interspecies interactions are inherently difficult due to the complex mechanisms which enable these relationships. A model system for studying interspecies interactions is the marine hyperthermophiles Ignicoccus hospitalis and Nanoarchaeum equitans. Recent independently-conducted 'omics' analyses have generated insights into the molecular factors modulating this association. However, significant questions remain about the nature of the interactions between these archaea.MethodsWe jointly analyzed multiple levels of omics datasets obtained from published, independent transcriptomics, proteomics, and metabolomics analyses. DAVID identified functionally-related groups enriched when I. hospitalis is grown alone or in co-culture with N. equitans. Enriched molecular pathways were subsequently visualized using interaction maps generated using STRING.ResultsKey findings of our multi-level omics analysis indicated that I. hospitalis provides precursors to N. equitans for energy metabolism. Analysis indicated an overall reduction in diversity of metabolic precursors in the I. hospitalis-N. equitans co-culture, which has been connected to the differential use of ribosomal subunits and was previously unnoticed. We also identified differences in precursors linked to amino acid metabolism, NADH metabolism, and carbon fixation, providing new insights into the metabolic adaptions of I. hospitalis enabling the growth of N. equitans.ConclusionsThis multi-omics analysis builds upon previously identified cellular patterns while offering new insights into mechanisms that enable the I. hospitalis-N. equitans association.General significanceOur study applies statistical and visualization techniques to a mixed-source omics dataset to yield a more global insight into a complex system, that was not readily discernable from separate omics studies.