Fall 2013 Seminar Schedule

4PM on Wednesdays in NW 169

11 December- Cat Adams (Pringle Lab). Spicy chili peppers, fungal seed pathogens, and a co-evolutionary arms race: Linking ecological patterns to molecular mechanisms- Cat will be talking about her research with the fungal seed pathogens of wild chili peppers, Capsicum chacoense. Chili peppers produce spice, or capsaicin, to deter these pathogens, inhibiting complex I of the electron transport chain. However, many fungi from wild chili populations have evolved considerable resistance to capsaicin. Cat will tell us about what is known so far about this spicy system, and then share some recent preliminary results that examine differences among the mitochondria of chili fungi that span a range of plant host populations and fungal genera. Your feedback and ideas for future directions would be very much appreciated!

20 November- Josh Michener (Marx Lab). Recapitulating Adaptation after Horizontal Gene Transfer- Horizontal gene transfer (HGT) is a ubiquitous process that has shaped microbial evolution and ecology. While biologists have elucidated the mechanisms by which physical DNA can transfer between organisms, much less is known about the process of adaptation following HGT. Newly-acquired abilities may be costly for the host until they are carefully integrated into existing metabolic and regulatory networks. Using dichloromethane (DCM) metabolism in Methylobacteria as a model system, we have explored the physiological and evolutionary consequences of acquiring a challenging new catabolic pathway. We first transferred the pathway into a range of naïve recipients, who varied in their ability to exploit their new catabolic potential. Phylogeny does not explain this variation in success, nor does any single physiological factor. Through serial propagation on DCM, we selected mutants with improved fitness on DCM. Sequencing the evolved isolates allowed us to identify the stresses that were previously limiting growth as well as the biochemical mechanisms to alleviate those stresses. We find partial parallelism between strains, indicating that some strains faced similar stresses and found similar solutions, but that these stresses and evolutionary solutions are not universal even among closely related species.

6 November- Chris Ford (Regev Lab). The evolution of drug resistance in clinical isolates of Candida albicans- Candida albicans is both a member of the healthy human microbiome and a major pathogen in immunocompromised individuals. Infections are most commonly treated with azole inhibitors of ergosterol biosynthesis. Prophylactic treatment in immunocompromised patients often leads to the development of drug resistance. Since C. albicans is diploid and lacks a complete sexual cycle, conventional genetic analysis is challenging. An alternative approach is to study the mutations that arise naturally during the evolution of drug resistance in vivo, using isolates sampled consecutively from the same patient. Studies in evolved isolates have implicated multiple mechanisms in drug resistance, but have focused on large-scale aberrations or candidate genes, and do not comprehensively chart the genetic basis of adaptation. We leveraged next-generation sequencing to systematically analyze 43 isolates from 11 oral candidiasis patients, collected sequentially at two to 16 time points per patient. Because most isolates from an individual patient were clonal, we could detect newly acquired mutations, including single-nucleotide polymorphisms (SNPs), copy-number variations and loss of heterozygosity (LOH) events. Focusing on new mutations that were both persistent within a patient and recurrent across patients, we found that LOH events were commonly associated with acquired resistance, and that persistent and recurrent point mutations in over 150 genes may be related to the complex process of adaptation to the host. Conversely, most aneuploidies were transient and did not directly correlate with changes in drug resistance. This work sheds new light on the molecular mechanisms underlying the evolution of drug resistance and host adaptation.

23 October- Will Harcombe (Marx Lab), Quantitatively predicting and testing the evolutionary ecology of microbial systems - Metabolic interactions such as cross-feeding and competition are abundant in natural microbial communities, and can be engineered in artificial ones. We show that in spatially structured environments, these interactions give rise to dynamic ecosystem-level effects that defy simple intuition. By implementing dynamic flux balance analysis on a lattice, we simulated the complete metabolic activity of multiple microbial species in time and space, and studied the dynamics of engineered consortia. We predicted, and experimentally confirmed, the convergence of a 2-species mutualistic consortium towards a fixed species ratio, and stable coexistence in a newly engineered 3-member community. Most surprisingly we predicted that colonies that obstruct the flow of nutrients between mutualistic partners can have a paradoxical benefit to the distal pair.  This result, confirmed experimentally, illustrates the complex nature of metabolism-mediated interactions in microbial communities. The predictability of these effects highlights the value of multi-level quantitative metabolic modeling in microbial ecology.

9 October- Elizabeth Jerison (Desai Lab), Adaptive Pleiotropy in Yeast - Although organisms evolve in complex and time-varying environments, little is known about the relationship between these environments from the perspective of adaptation. Here, we investigated the structure of these differences in yeast. We evolved 253 populations in 13 conditions that varied in the degree and type of stress, and measured the fitnesses of the evolved mutants in many of the conditions. We find that groups of evolved mutants, both within and between environments, cluster in phenotype space, giving a measure of the degree of overlap of targets of beneficial mutations in the different conditions. We are unraveling the genetic basis for these patterns using whole-genome sequencing of 253 clones.