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  1. Pinned Tweet
    13 Nov 2019

    What do you expect evolution to look like in a microbial population? Check out our new study offering a view of that over 1000 generations in yeast in the lab. co-led by , , in 's lab

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  2. Retweeted
    23 Dec 2019

    Excited to announce a new preprint w/ on the ecological and evolutionary responses of the human gut microbiome during antibiotic treatment. . A lot of surprises in here for me -- will post a longer summary after the holidays.

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  3. Retweeted
    29 Nov 2019

    Our approach generates high-resolution maps of capsid sequence space, illuminating how capsids work and how to make them better. Here’s a visualization showing tolerance to substitutions (red:beneficial, white:neutral, blue:deleterious, this view isn't even in the paper!)

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  4. Retweeted
    20 Nov 2019

    This week on the Nature cover: Waves of mutation. Barcode system images evolutionary dynamics of laboratory yeast. Browse the issue here:

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  5. Retweeted
    15 Nov 2019

    A renewable barcoding system reveals the evolutionary dynamics of laboratory budding yeast, showing that fitness changes over time in a travelling wave of adaptation that can fluctuate owing to leapfrogging events, according to a Nature paper.

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  6. Retweeted

    Here's a thread telling the story of our new technique for genetic recording of lineage history during long term evolution experiments. The work was co-led with and in 's lab. Read the paper here:

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  7. Retweeted
    13 Nov 2019
    Replying to

    Wonderful stuff! For those wondering about leapfrog, here's where Phil Gerrish & I introduced the idea: See Fig 7 for simple illustration, in which successively dominant genotypes may -- or not, in case of leapfrog -- represent sequential substitutions.

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  8. 13 Nov 2019

    But it also exists in a limit that we don't currently have a good quantitative description for. Instead of proceeding smoothly, the wave exhibits large fluctuations as mutations cause clones to continuously leapfrog over each other!

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  9. 13 Nov 2019

    We see that the population carries dozens of competing beneficial mutations, and that it forms a sort of 'traveling wave' if you look at its distribution of fitness. This agrees with theoretical predictions.

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  10. 13 Nov 2019

    I then developed an approach to use this lineage frequency data to reconstruct the clonal structure of the population and to detect individual beneficial mutations.

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  11. 13 Nov 2019

    By sequencing this genetic locus over time, we can measure the fractions of the population in different barcoded lineages.

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  12. 13 Nov 2019

    and developed a remarkable new approach to continuously re-introduce enormous numbers of DNA barcodes into an evolving yeast population, one right next to the other in the genome.

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  13. 13 Nov 2019

    But it has been difficult to observe the majority of those mutations: theory had predicted that most would be lost before reaching fractions of the population detectable by available methods.

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  14. 13 Nov 2019

    We've known for the past couple of decades that many microbial populations adapt in an incredibly dynamic way, with large numbers of beneficial mutations continuously arising and competing.

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  15. Retweeted
    25 Oct 2019

    We have an open post-doc position in the lab! Core current interests are recombination/reassortment/HGT in microbial evolution, but we can get excited about other questions as well. Please share!

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  16. Retweeted
    24 Oct 2019

    Our Tn-Seq paper with , Alena Martsul and is out in . Accompanied by a nice perspective by Craig Miller with a cool fitness landscape: Here is my original summary:

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  17. Retweeted
    8 Oct 2019

    Our work is out on ! Check out how we altered substrate selectivity of an ABC transporter. Collaboration of and .

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  18. Retweeted
    30 Sep 2019

    How do T cells access many spatial scales in vivo? Excited to share our results in my first preprint, with Stephen Quake: Comments from all communities welcome and with many thanks to 2017.

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  19. Retweeted
    20 Jun 2019

    How does the local neighborhood of mutations change across the combinatorially sprawling expanse of the fitness landscape? To find out, we did lots of yeast xformations and thunderdome all-v-all competitions (w/ , , Alena Martsul):

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  20. Retweeted
    3 Nov 2018

    Distinguishing multiple-merger from Kingman coalescence using two-site frequency spectra

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