Project description:During a 1,000 generations evolution experiment, two types of bacteria (S and L) repeatedly diverged from a common ancestor (A) in a fully sympatric seasonal environment containing glucose and acetate. We compare the transcription profile of the two derived types and the common ancestor in order to investigate the metabolic modifications associated with this adaptive diversification event. Keywords: time point, experimental evolution
Project description:The páramo ecosystem has the highest rate of diversification across plant lineages on earth, of which the genus Espeletia (Asteraceae) is a prime example. The current distribution and molecular phylogeny of Espeletia suggest the influence of Andean geography and past climatic fluctuations on the diversification of this genus. However, molecular markers have failed to reveal subtle biogeographical trends in Espeletia diversification, and metabolomic evidence for allopatric segregation in plants has never been reported. Here, we present for the first time a metabolomics approach based on liquid chromatography-mass spectrometry for revealing subtle biogeographical trends in Espeletia diversification. We demonstrate that Espeletia lineages can be distinguished by means of different metabolic fingerprints correlated to the country of origin on a global scale and to the páramo massif on a regional scale. Distinctive patterns in the accumulation of secondary metabolites according to the main diversification centers of Espeletia are also identified and a comprehensive phytochemical characterization is reported. These findings demonstrate that a variation in the metabolic fingerprints of Espeletia lineages followed the biogeography of this genus, suggesting that our untargeted metabolomics approach can be potentially used as a model to understand the biogeographic history of additional plant groups in the páramo ecosystem.
Project description:This study used an emerging analytical technology (cDNA microarrays) to assess the potential effects of PFC exposure on largemouth bass in TCMA lakes. Microarrays simultaneously measure the expression of thousands of genes in various tissues from organisms exposed to different environmental conditions. From this large data set, biomarkers (i.e., genes that are expressed in response to an exposure to known stressors) and bioindicators (e.g., suites of genes that correspond to changes in organism health) can be simultaneously measured to clarify the relationship between contaminant exposure and organism health. Based on current scientific literature, we hypothesized that gene expression patterns would be altered in fish exposed to PFCs (as compared with fish from reference lakes), and that the magnitude of these changes would correspond to the concentrations of PFCs present throughout TCMA lakes. Patterns of gene expression in largemouth bass observed across the TCMA lakes corresponded closely with PFC concentration. Concentrations of PFCs in largemouth bass varied significantly across the sampled lakes, where the lowest concentrations were found in Steiger and Upper Prior Lakes and the highest concentrations were found in Calhoun and Twin Lakes. Patterns of gene expression were most different (relative to controls) in fish with the highest PFC tissue concentrations, where fish from Twin and Calhoun Lakes were observed to have between 5437 and 5936 differentially expressed genes in liver and gonad tissues. Although gene expression patterns demonstrated a high degree of correlation with PFC concentrations, microarray data also suggest there are likely additional factors influencing gene expression patterns in largemouth bass in TCMA lakes.