Tag Archives: microbial diversity

Guest post by Lizzy Wilbanks: Story behind the paper "Microscale sulfur cycling in the phototrophic pink berry consortia of the Sippewissett Salt Marsh"

Here’s another entry in the “Story behind the paper series”.  This one is from Lizzy Wilbanks, a co-advised PhD student in my lab (Twitter: @LizzyWilbanks)

A sulfurous symbiosis: Microscale sulfur cycling in the phototrophic pink berry consortia of the Sippewissett salt marsh 

Here’s the story behind my recent publication (with many talented coauthors) on the pink berries, the marvelous, macroscopic microbial aggregates of the Sippewissett.

A bit of background:

The wild microbe rarely eats alone. The microbial world is a jungle far more exotic than those we can see (metabolically and phylogenetically, at least), one rife with fierce competition, intimate cooperation, and intricately inter-dependent food webs. Eavesdropping on the metabolic conversations of uncultured microbes, though, remains a major technical challenge.  It requires tools to navigate the world from the microbe’s-eye view.

 Your binoculars just aren’t gonna cut it…  (image source )
In our recent paper, my co-authors and I describe how we were able to tune in to one such metabolic conversation, and look at a nutrient (‘biogeochemical’) cycle on the microbial scale. Here’s the back-story on how this project got started, and why I’m so excited to share our work with you!

Let’s get one thing straightened out:

‘Pink berries’ are a nickname for these pink colored microbial aggregates.  We’re not talking about fruit or frozen yogurt here.
(image source: my own, here, and here)

My first encounter….

I first encountered these eye-popping pink wonders in 2010 when I was as a second year grad student attending the Microbial Diversity summer course at the Marine Biological Laboratory in Woods Hole, MA.  Exploring the nearby Little Sippewissett Salt marsh for our first field trip, I stomped through the marsh grass into a muddy, sulfidic pool.
And people wonder why I think sulfide smells like beautiful summers and nostalgia?
(image source: my own)
Below the surface of the pool’s water, scattered across the sediment, was a truly magnificent carpet of pink blobs. 
(image source: my own)
After a bioinformatics-heavy start to grad school at UC Davis, I was dying to get my hands dirty with some fieldwork.  I was transfixed by the stinky, sulfidic marsh mud and these slimy pink aggregates. 
Me, awfully excited and really “diving-in” to the project.
Can’t remember how many times TA Annie Rowe and others had to fish me out of the mud that summer!

(image source: Melissa Cregger 🙂 
Course directors at the time, Dan Buckley and Steve Zinder, told me that these were the pink berries, balls of uncultured bacteria found in the Sippewissett marsh (and, so far as they knew, nowhere else). Summer students had been looking at the berries ever since the course was founded 40 years ago, they said, and they pointed me towards a pile of old course reports back at the lab.  

Berries: an MBL Microbial Diversity legacy.

These reports (now digitized and freely available) tell the tale of many happy, hard-working summers where students took a crack at these exotic looking blobs during their independent research mini-projects.  One of the most fun parts of this project has been meeting all of these “berry alumni”, both via email and in person, who are now scattered throughout the world. From helpful discussions, to sharing data and suggestions, and even digging up never-published 16S rRNA gene sequences from over a decade ago (thanks Bruce Paster and Jarrod Scott!), the berry-alums have helped lay the groundwork for our project and have been an amazing network of friends and collaborators.  
Our paper is a sequel, 20 years in the making, to the first and only other paper describing the pink berries.  Published in 1993 by MBL summer students Angelica Seitz and Tommy Nielsen with course faculty Dr. Jörg Overmann, this work described the berries as aggregates dominated by uncultured purple sulfur bacteria, anoxygenic phototrophs that oxidize hydrogen sulfide to sulfate (unlike cyanobacteria and green plants that oxidize water to oxygen). By spearing berries with oxygen microsensors, they found that the berries were such hot-spots of microbial activity that all oxygen was consumed just a few micrometers below the surface, creating a haven for anaerobic microorganisms.  
My obviously-not-to-scale cartoon of berry spearing with oxygen microsensors.
The purple sulfur bacteria give the berries their rosy hue with their photosynthetic pigments that have evolved to capture lower-energy, longer wavelength light (compared that used by green phototrophs). 
Peering into the pink berries with a dissection microscope (real color!).
Pink blobs are islands of purple sulfur bacterial cells.

(image source: Verena Salman) 
With the introduction of 16S rRNA gene sequencing to the course in 1997, students discovered that, in addition the conspicuous purple sulfur bacteria, the berries also harbored an abundance of an uncultured species related to sulfate reducing bacteria (sulfate -> sulfide).  The co-occurrence of putative sulfide-oxidizing purple sulfur bacteria and sulfate reducing bacteria spawned the hypothesis that these species might be metabolically interdependent, creating a “cryptic” sulfur cycle within the berries.  
The hypothesis! Purple sulfur bacteria in pink, sulfate reducing bacteria in green.
(image source: my own, modified version of Figure 9 from our paper) 
These sulfate reducing bacteria, though, had remained elusive, uncultured, and their activity, undetected. This intriguing hypothesis about an “intraberry” sulfur cycle and metabolic cooperation (‘syntrophy’) remained untested like so many other questions about the secret lives of uncultured microbes.

Project launch: Team berry 2010

Resolved to work on the pink berries for my mini-project, I banded together with fellow students and co-authors Ulli Jaekel and Parris Humphrey, and with the help of TAs Cristina Moraru and Rebekah Young – formed Team Berry 2010.  We began investigating the pink berries using DNA sequencing (16S, metagenomics), microscopy (FISH, TEM) and other incubation studies. 

The first few weeks at the MBL course were bonanza of microbial excitement for me as a huge metabolism geek.  My mornings were spent trying to drink from the fire hose of information in lecture, followed by afternoons of lab, then dinner, more lab, and finally trying to piece together the day’s ideas over beers.

“Drinking from a fire hose” – another gem from PhDComics

Coming back from Dan Buckley and Victoria Orphan‘s lectures about the uses of stable isotopes in microbial ecology (reviewed here), I wondered if there was a way to use sulfur stable isotopes to track the cryptic sulfur cycle in the pink berries.  Brainstorming with Victoria, we devised a plan to conduct incubations with the pink berries using isotopically heavy sulfate (34SO42-) as a stable isotope label.  The purple sulfur bacteria in the berries had abundant intracellular sulfur reserves, which typically come exclusively from reduced forms of sulfur (e.g. sulfide).  Our hope was that the sulfate reducing bacteria would reduce the heavy sulfate we added to heavy sulfide, which would then be oxidized by the purple sulfur bacterial and incorporated into their cells.

To track the flow of our isotopically labelled sulfur, we planned to image thin sections of the incubated berries using nanometer scale secondary ion mass spectrometry (nanoSIMS), an instrument commonly used by the Orphan lab for studying anaerobic methane oxidizing consortia.

Using the nanoSIMS to blast sections of pink berries with  focused cesium beam (~50nm spot size)
and generate spatial maps of isotopic and elemental abundance.  
(image source: my own)

At that time, there was no precedent in the literature for using 34S-isotope labeling in this way (most stable isotope probing experiments focused on carbon or nitrogen compounds), but Victoria’s group was interested in exploring this area for studying other tightly coupled sulfur-cycling.  The berries were an accessible testing ground. After a madcap two weeks of rush-orders, late nights, midnight berry slicing, and help from so many wonderful, patient TAs, our samples made a cross-country journey to the Orphan lab at Caltech where they, and thankfully the nanoSIMS, survived a minor earthquake.  

The nanoSIMS beast in its subterranean lair @ the Caltech Microanalysis Center.
(image source: my own)

It was a wild ride during those final weeks, but just before the end, we got exciting results from Victoria’s nanoSIMS run that suggested our experiment had worked.  The preliminary nanoSIMS data showed accumulation of our sulfur isotope label (enrichment in 34S compared to controls), and also found evidence for carbon fixation (13C enrichment from labeled bicarbonate additions).

Can’t stop, won’t stop… the side-project that ate my thesis.

After returning to Davis, passing my qualify exam and wrapping up prior projects, I was determined to get back to berries but wasn’t sure exactly how.  Victoria suggested that she could include berries in a collaborative NSF proposal on the biogeochemistry of tightly coupled sulfur cycling consortia (along with David Fike, Greg Druschel and Jesse Dillon).  When their funding came through, it held out the safety net I needed to work on berries full time.  With approval from Victoria and my co-advisers at Davis, I jumped!

Returning as a TA to the MBL Microbial Diversity course in 2011, I had a chance to conduct follow up isotope experiments, and collaborate with course student and co-author Verena Salman on developing species-specific FISH probes to identify the spatial arrangements of the two berry symbiotic.  Since then, I’ve followed up on our initial metagenomic sequencing to reconstruct near-complete genomes for the two berry symbionts, demonstrating the genetic potential for a complete sulfur cycle.

Figure 4 from our paper showing:
the sulfate reducing species (green rods, 16S rRNA gene FISH probe)
snuggled up with their metabolic partners,
the purple sulfur bacteria (pink/purple cocci, autofluorescence),
but not in the exopoylmer matrix with  
other cell types  (blue, DNA stain: DAPI).

In 2012, the final pieces of this project came together during a week of Sippewissett fieldwork with biogeochemistry collaborators  David FikeGreg Druschel, and their groups.  With high resolution geochemistry equipment aboard our homemade raft, we were able to link our existing microbiological measurements with microscale geochemical signatures in the berries.

(image sources: my own)


Using the pink berries, we demonstrate how an integrative microbiological and microgeochemical approach can be used to decrypt the microbial metabolic partnerships that drive sulfur cycling at the microscale. This methodology, which may ultimately be used to examine more complex ecosystems, offers direct evidence of syntrophic interspecies sulfur transfer. 
For more details on how all these different pieces came together, you’ll just have to check out our paper yourself!   


What do they taste like?
Mostly just salty, and a bit sandy 🙂

Are the pink berries found anywhere else?
Not really!  I’ve looked through the literature and chatted up loads of people, but no one’s ever reported seeing pink berry-type macroscopic consortia of purple sulfur bacteria and sulfate reducers.  There’s a description of a microscopic type pink berry-like aggregates in the chemocline of Lake Cadagno, and interestingly those aggregates’ sulfate reducing isolate (Cad626) is closely related to our PB-SRB1 sulfate reducing species.   Should you find berries somewhere else during your marshly peregrinations, email me!
Have you tried culturing them?
Yes!  My undergraduate students recently confirmed that we have an enrichment culture of the purple sulfur bacterial strain, and are working to purify it, and submit it to a culture collection.  If you’re interested in working on it, I’m happy to send you a sample of the culture.  The sulfate reducer has, so far, resisted my efforts to coaxing it into culture but hasn’t really been a major focus of my project (I’d wager it’s possible).
So wait, why are you studying them again?
  • My naturalist’s answer is: because they’re the pink, charasmatic macrofauana of the microbial world. They’re nifty, and we don’t know what they do. But seriously… 
  • Microbial metabolism is the engine that drives the nutrient (biogeochemical) cycling that shapes the health of both our planet and our bodies.
  • However, many key transformations in these cycles are carried out by microbial consortia over short spatiotemporal scales that elude detection by traditional analytical approaches. 
  • The berries provide a tractable, reproducible model microbial consortia for developing methods to eavesdrop on these otherwise cryptic metabolic conversations between the wild microbes.
  • Understanding the biosignatures (e.g. sulfur isotopic fractionation) produced by microbial communities like the pink berries improves our ability to interpret the rock record and construct models of ecosystem function in both ancient and modern environments.

    Thank you:

    Through this project, I’ve had the privilege of working with truly amazing people and making life-long friends.  The author list and acknowledgement are just the tip of the iceberg in terms of people who have contributed to this project in one way or another.  You all know who you are; I feel so lucky to have gotten to know and work with you. THANK YOU!

    This project was started as grass-roots style, curiosity-driven student research, and as such, the funding for it has been fairly eclectic.  I want to take a moment to acknowledge those organizations that have supported this kind of research and made my work possible.

    Funding to the MBL Microbial Diversity course from:

    • Howard Hughes Medical Institute
    • Gordon and Betty Moore Foundation (#2493)
    • National Science Foundation (DEB-0917499)
    • US Department of Energy (DE-FG02-10ER13361)
    • NASA Astrobiology Institute (NAI)

    Grants to collaborators Victoria Orphan and David Fike from:

    • NSF (EAR-1124389 & EAR-1123391)
    • Gordon and Betty Moore Foundation (#3306)

    Grad-student grants and fellowships supporting my work at UC Davis from:

    • National Science Foundation Graduate Research Fellowship
    • UC Davis Dissertation Year Fellowship
    • P.E.O. Scholar Award
    • NAI/APS Lewis and Clark Fund in Astrobiology
    • NSF Doctoral Dissertation Improvement Grant (DEB-1310168)

    Full citation:

    Wilbanks EG, Jaekel U, Salman V, Humphrey PT, Eisen JA, Faccioti MT, Buckley DH, Zinder SH, Druschel GK, Fike DA, Orphan VJ. (2014) “Microscale sulfur cycling in the phototrophic pink berry consortia of the Sippewissett Salt Marsh.” Environmental Microbiology,  doi:10.1111/1462-2920.12388http://dx.doi.org/10.1111/1462-2920.12388.

    The Quest for a Field Guide to the Microbes: talk at "Science in the River City"

    I got invited a while back to give a talk at a “Science in the River City” workshop for 3rd – 12th grade science teachers.  I proposed (and they said yes) to the idea of talking about my “Quest for A Field Guide to the Microbes.”  I recorded the screen (slides) and audio from my talk using Camtasia and have now posted the slideshow and slides.  Here they are:

    Talk slideshow with Audio on Youtube:


     Slides on Slideshare

    Is the New York Times microbial diversity centric?

    The answer to the question in the title – I think – is yes.  Here are some recent stories in the Times on topics of relevance to microbial diversity.

    Plus – of course – there is a continuous stream of information on microbes from Carl Zimmer who writes frequently for the NY Times.  Perhaps the best example of this is his coverage of the Human Microbiome Project papers: Studies of Human Microbiome Yield New Insights June 18, 2012.  But there have been and I am sure will be others. 
    Sure – the NY Times is not the only place with a bunch of stories about microbial diversity and microbiomes. But they do seem tto have a good ratio of “diversity” themed coverage vs. germoophobia themed topics which are common in many other places.

    Who are the microbes on your fruits and veggies?

    Nice paper from Jonathan Leff and Noah Fierer in PLOS One: Bacterial Communities Associated with the Surfaces of Fresh Fruits and Vegetables

    Abstract: Fresh fruits and vegetables can harbor large and diverse populations of bacteria. However, most of the work on produce-associated bacteria has focused on a relatively small number of pathogenic bacteria and, as a result, we know far less about the overall diversity and composition of those bacterial communities found on produce and how the structure of these communities varies across produce types. Moreover, we lack a comprehensive view of the potential effects of differing farming practices on the bacterial communities to which consumers are exposed. We addressed these knowledge gaps by assessing bacterial community structure on conventional and organic analogs of eleven store-bought produce types using a culture-independent approach, 16 S rRNA gene pyrosequencing. Our results demonstrated that the fruits and vegetables harbored diverse bacterial communities, and the communities on each produce type were significantly distinct from one another. However, certain produce types (i.e., sprouts, spinach, lettuce, tomatoes, peppers, and strawberries) tended to share more similar communities as they all had high relative abundances of taxa belonging to the family Enterobacteriaceae when compared to the other produce types (i.e., apples, peaches, grapes, and mushrooms) which were dominated by taxa belonging to the Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria phyla. Although potentially driven by factors other than farming practice, we also observed significant differences in community composition between conventional and organic analogs within produce types. These differences were often attributable to distinctions in the relative abundances of Enterobacteriaceae taxa, which were generally less abundant in organically-grown produce. Taken together, our results suggest that humans are exposed to substantially different bacteria depending on the types of fresh produce they consume with differences between conventionally and organically farmed varieties contributing to this variation.

    Getting press attention.  Examples include:

    Definitely worth a look.

    Guest post from Ashley Bateman on "Full contact microbes" – Roller Derby

    A special guest post from Ashley Bateman.


    Roller derby players share their skin microbes during play
    Single-celled organisms are intimately associated with multicellular organisms across the tree of life, and human beings are no exception. Making up 90% of our cellular composition, these invisible passengers (our microbiome) contribute to our health and well-being in crucial ways, including aiding our digestion, the education of our immune system, and resistance to pathogens. Despite this importance, we still lack a fundamental understanding of where our host-associated microbes actually come from. We know that infants are born practically sterile; early-life events such as birth mode can contribute to the types of microbial species found on an individual, but these events cannot adequately explain the majority of spatiotemporal variation observed over a host’s lifetime. To be able to accurately describe the processes that drive host-associated microbial community dynamics, we must have an informed understanding of the role of dispersal in structuring host-associated microbial communities.
    Where do they come from? How do they get there? Do these changes (if any) last?
    The Green Lab at the University of Oregon-Eugene attempted to answer some of these questions in our latest publication “Significant changes in the skin microbiome mediated by the sport of Roller Derby”, released today by PeerJWe decided to use Roller Derby as a model system to investigate the role of contact in dispersing skin microbial communities between hosts. We have known for a long time that pathogens can be transmitted via direct contact; could not our commensal microbial communities be shared in this way?

    We swabbed the upper arms (a frequent contact point between players during a bout) of players belonging to 3 geographically distinct derby teams and characterized the skin microbiome of each player using 16s rRNA gene Illumina sequencing. We found that each team’s upper arm microbiome was significantly different from one another before play, and that this difference decreased after bouts were played. Not only did teams’ skin microbiomes become less different from one another after play, but the differences were driven in part “by the presence of unique indicator taxa that are commonly associated with human skin, gut, mouth, and respiratory tract.” There were also environmental bacteria associated with soil and plants found in the skin samples.

    Although we weren’t able to show a direct link between contact and transfer of specific microbial taxa, the best explanation of the data seems to be that contact between these players during a one-hour bout effectively resulted in homogenization of their upper arm skin microbiomes.
    So much yet to explore! As a 2nd year graduate student in the Green Lab I hope to address some of the questions that the Roller Derby paper has brought to our attention. My dissertation research is gearing up to understand the role of dispersal on our skin microbiome. Are some skin sites more amenable to changes than others? Can we pick up host-associated microbes not just from other individuals, but from objects that other individuals have touched? Can we pick up non-host-associated microbes? If we can pick them up, how long do they stick around? How do they participate in the functions attributed to the skin microbiome?
    Hope to keep up the fantastic momentum that has been launched by this latest publication – if you have any thoughts or comments, feel free to contact me at abateman@uoregon.edu, or via Twitter: @microbesrock
    And you can check out a stop-motion video I made on the skin microbiome here:

    Interesting paper on strategy to use PCR to simultaneously characterize eukaryotic, bacterial and archaeal microbes

    Interesting new paper in PLOS One: PLOS ONE: Simultaneous Amplicon Sequencing to Explore Co-Occurrence Patterns of Bacterial, Archaeal and Eukaryotic Microorganisms in Rumen Microbial Communities

    Full citation:  Kittelmann S, Seedorf H, Walters WA, Clemente JC, Knight R, et al. (2013) Simultaneous Amplicon Sequencing to Explore Co-Occurrence Patterns of Bacterial, Archaeal and Eukaryotic Microorganisms in Rumen Microbial Communities. PLoS ONE 8(2): e47879. doi:10.1371/journal.pone.0047879

    Basically, the paper describes the development and use of a PCR strategy to simultaneously characterize eukaryotic, bacterial and archaeal microbes from samples.

    Primers used are summarized in Table 2

    The strategy they employ attempt to correct for differences in amplification differences between the different amplicons which should therefore allow better normalization of relative abundance estimates.  See results in Figure 2.

    Definitely worth a look.

    Metadata to collect while collecting plant associated microbial samples in the field

    Another question for Twitter with some answers by Storify. Not I am putting in below the fold here so that the Storify emded only launches for those who want it to …
    //storify.com/phylogenomics/metadata-to-collect-while-collecting-plant-associa.js[View the story “Metadata to collect while collecting plant associated microbial samples in the field” on Storify] In addition Russell Neches in my lab would like to add the following comments, which were too long for the comment option here.

    The most important thing for interpreting -omic data is context. For
    genomic data, this mostly means compare and contrast analysis against
    other genomes, although there are other tools (GWAS-type studies,
    ChIP-seq/chip, footprinting…). For metagenomes, comparisons against
    other similar metagenomes can be of limited utility if the taxa
    represented do not overlap very much.

    The easiest thing would be to bring a smart phone and log GPS

    coordinates and take wide and closeup photos, and make absolutely sure

    that each one is explained in the field notes. This doesn’t necessarily
    provide quantitative information, but it’s *REALLY* helpful to anyone

    trying to analyze the data who wasn’t on the field mission. And it’s
    cheap and easy.

    For quantitative metadata, there are usually a number of abiotic
    parameters that drive community structure, and many of these are
    relatively easy to instrument. For example, pH, temperature and moisture
    are very strongly correlated with community structure in terrestrial
    soils. These parameters are very easy to measure. There are of course
    other parameters that might be interesting; CO2, CO, CH4, C2H5OH, O2,
    N2, nitrate, nitrite, phosphorous… but these are somewhat more
    difficult to instrument at the moment, and (as far as I know) are
    usually not as correlated with the very broad impact of pH, temperature
    and moisture unless the system is near an extreme (e.g., the whole
    system goes anaerobic, or metal-starvation in the open ocean).

    However, while these parameters are easy to measure, they can also
    fluctuate on time-scales that are relevant to microbial growth. As a
    result, the temporal (and perhaps spacial) variation of these parameters
    may be more important to the community structure than their “typical”
    values. In way that is tends to frustrate field mission planning, it is
    the temporal fluctuations *PRIOR* to sampling that are relevant.

    There are two approaches : telemetry and local assistance. Telemetry
    (“measurement from afar”) means placing instrumentation at the site that
    has the ability to log or transmit data. Local assistance would vary
    depending on the context of the site, but basically amounts to
    partnering with someone who actually lives near the study site and
    somehow convincing them to take measurements for you. Of course, the two
    approaches are not mutually exclusive.

    The simplest and probably best approach would be to partner with someone
    near the study site who teaches fourth grade. Send them enough simple
    gardener’s soil chemistry meters for their class (plus some extra for
    the ones that inevitably get lost, disassembled or turned into
    implements of mayhem and destruction).

    For example, a quick search on Amazon turns up dozens of fairly
    inexpensive gardening tools for measuring pH, moisture, temperature and
    light intensity. Here’s one that looks like it might be useful :


    Here’s an even cheaper one that does pH, moisture and light, doesn’t
    need a battery, and costs less than seven bucks :


    If you were asking a class of fourth graders to help gather metadata for
    you, using instruments like these would cost perhaps $300, including
    instruments, stationary, surveying flags, etc. Make that $500, and send
    lots of extra stationary. Fourth grade classrooms never have enough

    Of course, if you’re going to ask people to do work for you, you must
    treat them accordingly. Taking careful, regular measurements and writing
    them down in a notebook is the bread-and-butter of science, and people
    who do this work are called “scientists,” not “helpers.” There are
    myriad implications to this, but one that I hope more people will
    consider is sharing authorship. It is fair, it is honest, and it is

    The other option is telemetry. Thanks in no small part to the Arudino
    project, this has gotten vastly easier and cheaper. At the cost of
    learning a little bit about soldering and digital logic, you can wire up
    virtually any sensor you like to a microcontroller, and then push that
    data over a variety of communications platforms. There are Arduino
    shields that interface with Ethernet, Wifi, Bluetooth, GSM, and even
    satellite networks. Even a satellite uplink interface can be hacked
    together for less than $200.

    Of course, there are a lot of people interested in telemetry of various
    sorts, and so you can find Arduino derivatives that have a lot of the
    work done for you. For example, if you happen to want to want pH
    telemetry, and your site happens to be within a few dozen meters of
    someplace you can safely leave an old laptop, this product might
    interest you :


    Here’s another Arduino variant with an onboard FLASH logging interface,
    solar/LiPo power management, a real time clock, a temperature sensor,
    and interfaces for standard Arduino shields (e.g., a GSM shield), and an
    interface for Xbee-style boards (e.g., bluetooth, Xbee, GPS, FM radio,


    Attach sensors. Write software. Add battery and solar panel. Put into
    watertight box. Deposit at field site.

    The kitten microbiome – new related paper and Mendeley collection

    Saw this new paper today: Dietary format alters fecal bacterial populations in the domestic cat (Felis catus) – Bermingham – 2013 – MicrobiologyOpen – Wiley Online Library

    And was reminded on the Kitten Microbiome project. It was conceived as a (sort of) joke but studying the microbes in our domestic companion animals is a good thing and could be very interesting in many ways.

    So I created a Mendeley group on cat / kitten microbiome studies:

    Oh, and while I was at it I created a group for the Dog Microbiome.


    Not sure these should really be completely separate (i.e., there could be a collection on the domestic animal microbiome) but am keeping them separate for now.

    Interesting new #PLOS One paper on study design in rRNA surveys

    Interesting new paper in PLoS One:  PLOS ONE: Taxonomic Classification of Bacterial 16S rRNA Genes Using Short Sequencing Reads: Evaluation of Effective Study Designs

    Abstract: Massively parallel high throughput sequencing technologies allow us to interrogate the microbial composition of biological samples at unprecedented resolution. The typical approach is to perform high-throughout sequencing of 16S rRNA genes, which are then taxonomically classified based on similarity to known sequences in existing databases. Current technologies cause a predicament though, because although they enable deep coverage of samples, they are limited in the length of sequence they can produce. As a result, high-throughout studies of microbial communities often do not sequence the entire 16S rRNA gene. The challenge is to obtain reliable representation of bacterial communities through taxonomic classification of short 16S rRNA gene sequences. In this study we explored properties of different study designs and developed specific recommendations for effective use of short-read sequencing technologies for the purpose of interrogating bacterial communities, with a focus on classification using naïve Bayesian classifiers. To assess precision and coverage of each design, we used a collection of ~8,500 manually curated 16S rRNA gene sequences from cultured bacteria and a set of over one million bacterial 16S rRNA gene sequences retrieved from environmental samples, respectively. We also tested different configurations of taxonomic classification approaches using short read sequencing data, and provide recommendations for optimal choice of the relevant parameters. We conclude that with a judicious selection of the sequenced region and the corresponding choice of a suitable training set for taxonomic classification, it is possible to explore bacterial communities at great depth using current technologies, with only a minimal loss of taxonomic resolution.

    Not sure I like everything in the paper.  For example, they focus on naive Bayesian classification methods … when (of course) I prefer phylogenetic methods.  But that is a small issue.  Overall there is a lot of useful detail in here about rRNA based taxonomic studies.  I note – some of this probably applies to metagenomic studies as well … perhaps this group will do a comparable analysis of metagenomics next?

    Mizrahi-Man O, Davenport ER, Gilad Y (2013) Taxonomic Classification of Bacterial 16S rRNA Genes Using Short Sequencing Reads: Evaluation of Effective Study Designs. PLoS ONE 8(1): e53608. doi:10.1371/journal.pone.0053608

    I note – if you want to catch up / learn / research metagenomics and phylogeny or classification check out the Mendeley group I started on the topic:


    RIP Carl Woese: Collecting posts / notes / other information about my main science hero here

    My tribute to Carl Woese 12/30/12

    Sadly, Carl Woese has passed away.  I am collecting some links and posts about him here in his memory.  He was without a doubt the person who most influenced my career as a scientist.

    News stories about Woese’s passing

    Some of my posts about Woese

    Woese Tree of Life pumpkin (by J. Eisen)

    Storification of Tweets and other posts about his passing //storify.com/phylogenomics/rip-carl-woese.js?template=slideshow[View the story “RIP Carl Woese” on Storify]

    Other posts worth reading about Woese’s passing

    Some videos with Woese 


    My graduate student Russell Neches used a laser to etch a picture of Carl Woese on a piece of toast.