Blog posts

  • Marine Fungi Workshop

    This post was originally uploaded to the seagrass microbiome website .

  • Now out in PeerJ: Microbiome succession during ammonification in eelgrass bed sediments

    This post was originally uploaded to the seagrass microbiome website .

  • Preprint available: Microbiome succession during ammonification in eelgrass bed sediments

    This post was originally uploaded to the seagrass microbiome website .

  • Now out in PeerJ: Microbial communities in sediment from Zostera marina patches, but not the Z. marina leaf or root microbiomes, vary in relation to distance from patch edge

    This post was originally uploaded to the seagrass microbiome website .

  • EYH 2016

    Updated (from 2014) instructions for the "Genome Detectives" workshop at UC Berkeley's Expanding Your Horizons 2016 event to introduce 6th-9th grade girls to STEM careers.

  • MBL Microbial Diversity Summer Course

    This post was originally uploaded to the seagrass microbiome website .

  • ASM Highlights

    This post was originally uploaded to the seagrass microbiome website .

  • Thoughts on Fluidity and Inter-connectivity of Microbial Community Dynamics

    This post is adapted from a blog post I wrote for my advanced soil microbiology graduate class.

    This post is in response to: Shade, Ashley, Hannes Peter, Steven D. Allison, Didier L. Baho, Mercè Berga, Helmut Bürgmann, David H. Huber et al. "Fundamentals of microbial community resistance and resilience."  Frontiers in microbiology  3 (2012).

    Three ideas stood out to me: that their can be multiple stable states, the treatment of microbial communities as networks and the description of communities as systems of genes and their functions.

    Multiple Stable States 
    I think that the idea that microbial communities might have multiple stable states that they can shift between is really interesting. This essentially lends weight to the notion that there is no one healthy microbiome. Instead there are dozens upon dozens of microbial communities that are "healthy". Also, microbial communities are composed of lots of different microorganisms living in concert. If the cellist suddenly dies (or leaves town), an orchestra will usually find another cellist, have someone already in the orchestra stand in or shift the music they play to not include cellos. The orchestra is no less stable, just slightly different.

    Microbial communities as networks
    People have been using network analysis to investigate complex traits and molecular pathways for a while now. I think that the using microbial co-occurrence to do network analysis on microbial communities is brilliant. Network analysis could potentially allow you to find/see functional groups of organisms (N fixers, etc) and might even allow you to discover common microbial "teams" (different microbes often found together). It'd be interesting to overlay functional information and metadata into the network analysis and see what falls out.

    Communities as Systems of Genes and their Functions
    We've talked a lot in this class about the dilemma of "who's there" vs. "what are they doing". A lot of the reason that I think we are interested in "who's there" is to try to either a) narrow in on the "who" to investigate that "what" or b) to use the "who" to estimate the "what". Genomics and high throughput sequencing techniques (amplicon gene sequencing, metagenomics, metatranscriptomics, metametabolomics, etc) allow us to more easily answer both the "who" and the "what". Although such techniques are data heavy (and thus, could cause us to drown in unanalyzed data), I think that these techniques will definitely be influential if not transformative for the whole of microbial ecology.


  • How Meta!

    This post is adapted from a blog post I wrote for my advanced soil microbiology graduate class.

    In class we recently talked about metagenomics. I know that a lot of the class missed out because of the soils conference, so I thought I'd use this post to introduce a really good metagenomics review paper by Tom Sharpton from Oregon State. It goes through the basic theory and approach to metagenomic analysis and Table 1 is a really good resource for online metagenomic resources.

    I also suggest looking through these resources (or applying to go to this workshop). I attended this past year and it was very informative for both amplicon based sequencing (16S, ITS, etc) and metagenomics. All of the resources from the workshop are online.

    Also the notes and slides from this ESA workshop may prove useful to some.

    For those just getting into microbiology, our lab released a "Swabs to Genomes" workflow which takes you from, well, swab to genome. The workflow includes culturing microbes from the swab, isolating microbes, doing 16S Sanger sequencing to determine microbial identity and then full genome sequencing and assembly. Although this approach is not metagenomics, instead "simple" genomics, it might still be helpful for those unfamiliar with assembly, phylogenetics, etc.


  • What is more important for classification - taxonomy or function?

    This post is adapted from a blog post I wrote for my advanced soil microbiology graduate class.

    Something I've been thinking a lot about recently is how we characterize microbial communities. Now that sequencing is relatively cheap, we can generate large amounts of data about the microbes of our respective research projects. However, should we be performing amplicon sequencing (16S, 18S, ITS) or metagenomics? Should we be classifying communities by function or taxonomy? 

    A recent short article by Xu et al, discusses this very question. Xu et al used PICRUST to examine if either function or taxonomy was a better indicator of microbial community composition. Using several publicly available datasets, they compared 16S classification to functional classification from PICRUST and in one instance to annotated metagenomic data. They determined that adding functional information DOES NOT improve classification accuracy of microbial communities. However, the authors don't downplay the importance of functional information, emphasizing that functional information may be very important depending on the research question. The authors state that improving our ability to classify samples into biologically relevant categories is not a reason to obtain functional data over taxonomic data. So if the goal of your research question is survey a microbial community, then metagenomics might actually provide you with less useful data than plain old 16S rRNA gene sequencing for answering your question. 



  • The Microbe Alliance: Resisting Long-Term Change

    This post is adapted from a blog post I wrote for my advanced soil microbiology graduate class.

    For the class we discussed the resilience of soil microbes to change based on the rainfall study done by Banfield et al (2009). Our discussion reminded me of a talk I'd recently seen by Lawrence David from Duke University on the human gut microbiome. His talk was on his recent Genome Biology paper: Host lifestyle affects human microbiota on daily timescales. The paper follows two subjects (rumor has it these subjects were Lawrence and his PhD professor, Eric Alm) for a little less than a year. The subjects collected a ton of metadata along with their samples including diet. The study found that overall the subjects gut microbiota were stable and relatively unchanging. Despite the plethora of metadata they were only able to correlate a few different factors to the presence or absence of certain OTU's.

    However, the authors were able to observe two large changes in the microbial gut communities of the subjects. Subject A traveled to Southeast Asia and as his diet drastically changed so did his gut microbiota. However, upon return from Southeast Asia, his gut community returned to the original community after two weeks. Subject B had food poisoning resulting in a drastic change to his gut microbiota. Subject B's gut microbiota never fully went back to the original community - however only 1.3% of reads post-infection were from new taxa and most of the community was closely related to the original community which the authors concluded was the result of a conservation of function over the conservation of specific species.

    Sampling every day especially when dealing with the human gut, is a huge enterprise (hence the n of 2). However, Lawrence David et al were able to observe changes to the microbial gut communities of the subjects and the return of these communities to a stable state only because of the frequency of sampling that they did. In the Banfield et al study on grassland soil, they sampled only four times a year for two years. They did see the microbial communities change at two time points, but these changes had disappeared by the next time point indicating microbial resilience.


    Although these two studies involve different environments (human gut vs. soil), they both bring up a good question: How often should we sample microbial communities to observe changes to community composition (temporary or permanent)? Across days? Across years? Across decades?

    For those interested in learning more about the human microbiome, at the time of the class there was a coursera course offered by Rob Knight's lab on it. Also if you are unfamiliar with alpha and beta diversity; I like these lecture slides on alpha diversity and beta diversity.
  • Lake Arrowhead: Posters, Comics and Doodles Galore!

    This post was originally uploaded to the seagrass microbiome website .

  • EDAMAME 2014's Greatest Hits

    This post was originally uploaded to the seagrass microbiome website .

  • Congratulations Henna!

    This post was originally uploaded to the seagrass microbiome website .

  • Expanding Your Horizon 2014 - Genome Detectives

    Instructions for the "Genome Detectives" workshop at UC Berkeley's Expanding Your Horizons 2014 event to introduce 6th-9th grade girls to STEM careers.