PIRE/PASI 2011 Field Course

I had the good fortune to attend a PIRE/PASI field course this past summer in the Peruvian Amazon. It was incredible! My first taste of tropical forest research. The course was split between cloud forest at ~3,500m in the Andes and lowland forest at ~sea level. In the cloud forest we stayed at Wayquecha, a fantastic field station with delicious traditional Peruvian food. Highlights include quinoa porridge with chunks of sugarcane and pasta casseroles.

High-tech microbe flux sampling device.

I was part of the “A-team”, sampling microbes. In addition to taking “real” samples (i.e. preserving leaf samples and air samples in Lifeguard for chemical analysis in the U.S.), we took culturable samples  using a high-tech microbe flux sampling device. We hung it from the meteorological boom another group installed on cabin 2B (right). They had wind sensors, temperature and humidity probes, light intensity sensors, and would have been taking water isotope measurements if their very expensive laser had arrived in Peru intact. We built our microbe sampler out of popsicle sticks, gorrila tape, and duct tape. The petri dishes were of the miniature variety, with malt agar to embed and foster the growth of bacteria and fungi. The up/down design was largely due to Kerton Victory, with confirmation from the atmospheric scientists on the course, to separate microbes falling down from those being wafted up.

High-tech sampling device

We regularly replenished the Gorilla tape.

We sampled with 30 minute exposures multiple times per day. In addition to sampling at the station, where there was a lot of air flow up and down the valley over the course of a day, we hiked out to the canopy walkway to sample a vertical gradient through the cloud forest. This involved dangling our high-tech sampling device off the walkway at different heights. Some misty times of day, the dishes would be wet after sampling from all the fog deposition. Not a problem, Parafilm! Rachel Gallery, whom we have to thank for bring the petri dishes to Peru in the first place, has a trick for Parafilming: rub your hands together first. (The heat softens the plastic.)

Rachel’s expertise was also key in storing our precious dishes. Her work with culturable fungi in other tropical places alerted her to a key source of microbiological failure: mites and other insects that eat through the Parafilm and mess up the sample. This actually happened to me in my current lab—most of the lab works on Drosophila and the last time they had a mite outbreak some nice plates I had just poured and was letting dry on my bench acquired suspicious trails of assorted bacteria.

You may be suspicious, as we were, that everything would be horribly contaminated. But it wasn’t! A large number of plates didn’t grow anything. Nothing. Zip. Zero. Zilch. Nada. Rinsing our hands in ethanol apparently worked. I had a very difficult time doing microbiology without a sterile hood and built a little area in my room enclosed in plastic that I could wipe down with ethanol… Ziploc bags are apparently pretty darn clean. Go A-team!

Gallery, Friesen, Victory, Womack

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Medicago phenotype app is live!

We’re still in demo/development mode, but the basic application is up at mt.usc.edu.

Model legume growing on Roman ruins in Tunis.

Welcome to Medicago Diversity Experiments

This application aims to enable interaction with phenotype and genotype data in Medicago.
Click on the links in the navigation bar to view data by Project or by Phenotype.

At the foundation of this application is a custom phenotype Ontology specific to Medicago.

There is a GBrowse for M. truncatula and Sinorhizobium

Redmine is an issue-tracker that we use for development. Submit a bug or feature request!

Next Goals:

  • expand plotting capabilities
  • upload additional phenotype data-sets
  • add connections between phenotypes and GWAS results

I’m really excited about the future of this application. Its guts are a well-reasoned schema modified slightly from the current Natural Diversity Module of Chado (GMOD’s collection of schemas). Each experiment that we conduct has meta-data as well as manipulations of genotypes and environments. All of that is transparent in the schema, so we can easily compare across experiments. Additionally, in developing our custom Medicago Ontology we documented measurement protocols to ensure that traits mean the same thing across experiments [working on uploading this].  I hope it becomes useful to the model legume community!


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It’s raining in Los Angeles!

Hooray! Los Angeles, while having a lot to offer in terms of culture (especially FOOD!), does not get nearly enough rain. Witness the drying of the Colorado River into the faucets of the city, or look at a map of California and note all of the dried up lakes North of the metropolis. In addition to basic water needs, rain has two major aesthetic benefits: (i) it cleans the air and (ii) it cleans the sidewalks. Those of you that live in ritzier parts of the city may not appreciate (ii), but in my neighbourhood the sidewalks are, to put it mildly, disgusting. But they are currently being washed clean!

I guess today I won’t need to listen to http://www.rainymood.com, since it’s coming in live.




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Microbially Mediated Plant Functional Traits

My Annual Review is available online, representing a ton of work by my fabulous coauthors (thanks Stef, Eric, Joel, Scott and Esperanza!).

Plants are rife with bacteria and fungi that colonize roots and shoots both externally and internally. By providing novel nutritional and defense pathways and influencing plant biochemical pathways, microbes can fundamentally alter plant phenotypes. Here we review the widespread nature of microbially mediated plant functional traits. We highlight that there is likely fitness conflict between hosts and symbionts and that fitness outcomes can depend on partner genotypes and ecological factors. Microbes may influence ecosystems through their effects on the functional trait values and population dynamics of their plant hosts. These effects may feed back on symbiont evolution by altering transmission rates of symbionts and scale up to ecosystem processes and services. We end by proposing new avenues of research in this emerging field.

DOI: 10.1146/annurev-ecolsys-102710-145039

This arose after a workshop at UC Davis, where Joel Sachs was an invited speaker. Since Joel, Stef and myself all work with rhizobia and legumes, we hang out to talk shop whenever possible (I love talking about science). Joel gave a great talk about his potential cheater strain of Brady that makes lots of tiny nodules that are chock full of bacteria—reminding me of a similar account by Parniske of a strain that has a similar phenotype but only on particular host genotypes. Parniske shows this crazy picture of “naked” rhizobia inside nodules, which does not happen in normal symbioses. Typically, the bacteria remain enveloped in a plant membrane to comprise the symbiosome.

Anyways, Stef and I were taking Joel to the airport and we were talking about how we’d love to actually work on something together. I proposed my rhizobia-legume fitness correlation meta-analysis project—version 1 is now complete and in prep. (Anyone interested in version 2, i.e. compiling hundreds of studies on ABM & NBM? Email me!) Joel said he was getting interested in ‘the rest’ of symbiotic (and non-symbiotic) microbes, so we came up with a simple idea: see what is known about who alters plant traits and explore the evolutionary and ecological implications.

Eric (key member of the Medicago project team) had been reading about mycorrhizae and Scott actually works on plant functional traits and how to scale them up to ecosystem & global processes. Then we contacted Esperanza, who Stef and I met when she was visited Doug Cook’s lab. Esperanza is a leader in the field of bacterial endophytes and she leant her vast and foundational knowledge to the cause.

So we put together our proposal, went through a couple rounds at the AREES editors’ meeting, and got the thumbs up! From there we tried a google doc, a wiki, and finally ended up mainly just sending our sections around in doc files. We spent a lot of time on the structure, then divvied up each section to a person. I collated, then we’d meet and discuss. The sections were supposed to change owners multiple times, but never quite did… at one point someone said their section was like a baby and they weren’t ready to pass it to a stranger (though we’re all friends…).

Then we got close to the deadline and I started orchestrating Skype meetings where people were assigned/volunteered for specific, small tasks like re-working a concept or looking for additional literature on X. Around this point we had a major hang-up on the definition of a “functional trait”. Our starting point had been Cornellison’s table of functional traits, which we used to try to estimate the potential impact of microbes on plant functional traits. I still default to this in my head, since most definitions seem to center largely around measurability on individuals. This is more complicated for things like drought tolerance, since you need multiple copies of the same individual to measure it. Working with selfed genotypes of Medicago, I’m totally down with that.

Then there was the word count reality check. I think the final manuscript is a little under 50% of the original length, due to several weeks and several sleepless nights. I tried to Strunk and White it: “Make definite assertions. Avoid tame, colorless, hesitating, non-committal language.” —Rule 12 William Strunk, Jr.

As our test audience, we were fortunate to have R. Ford Denison (evolution of cooperation in rhizobia master) and Scott Saleska (scaling from biosphere to atmosphere ecosystem processes); they gave us fantastic suggestions. We hope that it stimulates research and discussion!

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New site!


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