Overselling the mcirobiome award: Dr Roizen's Preventative and Integrative Medicine Conference

Just got an email announcement for "Dr. Roizen's Preventative and Integrative Medicine Conference" in Las Vegas in December 2015.

The announcement did not start of well for me with the gender balance of the key speakers

But since I spoke at this meeting in 2013 and since there was a good gender balance at that meeting, I decided to give the benefit of the doubt and keep reading (though I note - not trying to say this 5:0 gender ratio is a good thing).

And this is when it got worse - here are the bullet points for what one should learn from attending this meeting

• The key concept about optimal aging that Dr. Roizen learned from 56 million people who took the RealAge® test
• Smart tips about changing you and your patient's microbiomes and what to do for your microbiome to promote weight loss and how it inhibits aging
• How you can affect the role of the GI tract in chronic disease
• How to understand the clinical utility of TMAO testing for monitoring cardiometabolic risk
• The tricks about measuring your microbiome's effects
• Why some choose a plant based diet and why you might not
• What supplements do you and your patient's need with a plant based diet to decrease inflammation and improve your microbiome
• Clarify how a systems-based approach can effectively treat illness and promote wellness

Now - I don't know much about Dr. Roizen or his optimal aging claims in his books (I am skeptical). But the microbiome stuff in here is silly.

Let's start with: "Smart tips about changing you and your patient's microbiomes and what to do for your microbiome to promote weight loss and how it inhibits aging".  I wonder how he will give these smart tips when as far as I know there is nothing actually known about this.  How the microbiome inhibits aging?  Really? Is this going to be a summary of future research not yet done or even imagined?

What about "The tricks about measuring your microbiome's effects."  So - there are 1000s of scientists studying this, they mostly say it is very very very hard to study the effects of the microbiome and Roizen and crew are going to solve this with a few "tricks"?  So is he saying everyone in the field is incompetent since they can't measure these effects but he knows how to with a few tricks?

Dr. Roizen seems like a smart person and some of what I have heard from him sounds reasonable.  These microbiome claims from him here are a clear example of "Overselling the microbiome" and buying into the hype and not staying with the science. Maybe he was not paying attention for my talk for this meeting in 2013 when I discussed overselling the microbiome

I hope he tones down his claims in the future ... but for now he is a winner of a coveted "Overselling the Microbiome Award".  For other "winners" see here.

Blind trust in unblinded observation in Ecology, Evolution and Behavior (Guest Post by Melissa Kardish)

This is a guest post from Melissa Kardish - a PhD student at UC Davis - writing about a recent paper from work she did at her prior position.  The citation for the paper she is writing about is below:

Kardish MR, Mueller UG, Amador-Vargas S, Dietrich EI, Ma R, Barrett B and Fang C-C (2015) Blind trust in unblinded observation in Ecology, Evolution, and Behavior. Front. Ecol. Evol. 3:51. doi: 10.3389/fevo.2015.00051

Here is her post.

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Blind trust in unblinded observation in Ecology, Evolution and Behavior

We recently published our study in Frontiers in Ecology and Evolution where we found that a remarkable number of studies that could be affected by observer bias didn’t indicate whether or not they blinded their research. In fact only 13.3% of studies reported this:

We tried to make this a very transparent study. In addition to journal level data in the main article, we include in our supplemental material a table with the score for every article we read for this study (a summary of these scores per journal can be found in Figure S2 included here). If anything, our results under-represent the amount of studies that could have been scored blind (the real underreporting/underuse of blind observation is probably less than the 13.3% we report). For instance, we did not assess that there was potential for bias in the scoring of microsatellite markers (scored as unlikely to have observer bias). However, we did identify one study which was based on data from microsatellites which did blindly score their markers and report this scoring in their methods (and was therefore scored as “blind” in our study).  We also considered a study blind in its entirety for the purposes of our scoring if only one aspect is reported even if other experiments could also have been influenced by observer bias (Check out our supplemental methods for more ways we conservatively scored in our study).

We recognize that not all EEB studies can be blinded due to a variety of logistical or hypothesis driven reasons; however, we encourage such studies to accurately report this rationale and consider and attempt to minimize observer bias when designing experiments.

Thus far we have had a great response from the surveyed journals. Many of them have notified their editors about the lack of blind observation that we found reported in their journal. One journal has even notified us of plans already in place to address this issue at their next editorial board meeting.

We’re excited to have this work out there and hope this will inspire people to blind their studies and accurately report the science they are doing. We’re also excited to have the study published in an open-access format where we hope the encouragement for blind observation can reach all levels of science. Finally, as reporting of science in our fields improves in the coming years, we hope this study can serve as a template to address other potential concerns in experimental design and reporting.

For our article check out:  http://journal.frontiersin.org/article/10.3389/fevo.2015.00051/full

For our supplemental text and methods:  http://journal.frontiersin.org/file/downloadfile/10238/octet-stream/Data%20Sheet%201.PDF/711/2/142945

For our data table with each of the articles we surveyed: http://journal.frontiersin.org/file/downloadfile/10235/octet-stream/Table%201.XLSX/711/1/142945

Nice story from Dan Potter on KQED about Women Science PhDs

Nice story on KQED from Dan Potter: Women Getting Science Ph.D.s Still Face Gender Barriers    

Time to boycott Oxford Global meetings due to blatant sexism

I don't even know what to say or do about this it is so stunningly pathetic.  I saw this Tweet earlier in the day:

Oxford Global’s Pharmaceutical IT Congress: All 38 speakers male! (it seems)
http://t.co/ctu18mKLAw
@phylogenomics @GenderAvenger #YAMMM

— Elisabeth Bik (@MicrobiomDigest) May 13, 2015

I figured even in an era of blatant sexism in science, this must be a mistake right?  How could there be a conference with 38 male speakers and 0 female speakers.  So I went to the site: Who is Speaking – Oxford Global's 13th Pharmaceutical IT Congress, September 2015.  And, well, as far as I can tell Elisabeth Bik has the numbers right.  (See a list at the end of this post).  They even have a running slideshow of the speakers faces.

This is even worse than the 25:1 ratio of the qBio meeting I lost it over a few years ago.  I have never seen anything like this. I note - a 38:0 ratio is nearly impossible by chance in any field and I think pretty clearly an indication of massive bias of some kind.

I note - this is not the first case of a mostly male meeting from Oxford Global.  See for example:
Oxford Global Sequencing Meetings: Where MEN Tell You About Sequencing #YAMMM

I think it is time to just boycott meetings meetings from Oxford Global.  The only way they will change is if people stop speaking at or going to their meetings.  So please - stop going to their meetings.  Stop speaking at their meetings.

Koalas, Chlamydia, Antibiotics and Microbiomes - what else do you need?

Katie Dahlhausen, a PhD student in my lab, has become really really interested (perhaps a bit obsessed) with a really interesting case study regarding koalas, Chlamydia, antibiotics, and microbiomes.  Since we do not have funds to work on this in the lab, she has started an Indiegogo campaign to raise funds to work on this.  For more information on this project and how Koalas, Chlamydia, antibiotics and microbiomes are connected see "The Koala Project" page.

9 things PBS Newshour famously gets horrible wrong in story on fast food and microbiomes

Well, this is one of the worst microbiome news stories in a long time: Fast food kills gut bacteria that can keep you slim, book claims.  So many things wrong with it I don't even know where to go.  Here are nine:

1. The original headline: "Fast food kills gut bacteria that can keep you slim, study finds"

Here is the Tweet

Fast food kills gut bacteria that can keep you slim, study finds http://t.co/3fPIhJTuAB | @newshour

— PBS (@PBS) May 11, 2015

2. The correction:

is just completely lame and they should, as the New York Times does when it makes a correction, say what it used to say before they changed it

3. The sentence with the reference to Rob Knight is just bad reporting #1

Here is the quote:

Previous studies made similar findings: Professor Rob Knight of the University of Colorado Boulder, who collaborates with Spector, famously showed that transferring gut bacteria from obese humans to mice could make the rodents gain weight.

First of all - the paper they link to does include Rob Knight as a co-author, but the corresponding and senior author is Jeffrey Gordon and Rob is fourth to last (mind you I love Rob and his work, but in this case, saying this is something Rob showed without mentioning Gordon is just not right).

4 . The sentence with the reference to Rob Knight is just bad reporting #2

What the *$*$# does "famously showed" mean? Really.  What does it mean?

5 . The sentence with the reference to Rob Knight is just bad reporting #3

The statement "Previous studies made similar findings" is just so incredibly misleading.   It seems to be referring back to the previous sentences:

“What is emerging is that changes in our gut microbe community , or microbiome, are likely to be responsible for much of our obesity epidemic, and consequences like diabetes, cancer and heart disease,” he said. “It is clear that the more diverse your diet, the more diverse your microbes and the better your health at any age.”

This is just completely overblown.  The more diverse your diet the better your health at any age?  Oh #FFS that is just not based on any science.  And the "likely responsible for" is silly too.

6 . The sentence with the reference to Rob Knight is just bad reporting #4

Why exactly tell us he is collaborating with Rob Knight?  So some of Rob's good work rubs off?  I mean, Spector may do some fine work (and he has done some really good stuff).  But casually mentioning he collaborates with Knight who famously showed something (when actually it was more Jeff Gordon's work) which did not actually show what the article implies it showed.  Aaaaaaaaaaarg.

7. Good news.

Spector’s book claims that the diversity of microbes in the human body has decreased almost a third over the last century. But there’s also good news: Foods like dark chocolate, garlic, coffee and Belgian beer may help increase gut microbes.

Really?  Thinking about microbes MAY also increase gut microbes.  And so might listening to NPR.  Not something worth reporting here.

8. This sentence

This discovery suggested to his father that many cases of obesity may not simply be due to overeating.

That is right.  Looking at his son's poop and the microbes in it is the key to knowing that obesity might actually be fuc$*@#@ complex and not only caused by overeating.  Oh, that and 100 years of epidemiology and research.

9. This sentence

“Once on the diet I rapidly lost 1,300 species of bacteria and my gut was dominated by a different group called bacteroidetes. The implication is that the McDonald’s diet killed 1,300 of my gut species,” he said.

Sorry but that is NOT the implication.


UPDATE 1: May 11, 2015. 8:00 PM

Thanks to a Tweet from Jennifer Gunter I changed the title of my post from " 9 things horribly wrong with Newshour story on fast food and microbiomes" to "9 things PBS Newshour famously gets horrible wrong in story on fast food and microbiomes"

@PBS famously showed bad science reporting https://t.co/8VuGq5njWU

— Jennifer Gunter (@DrJenGunter) May 12, 2015

Cell Symposia have a problem with gender balance of speakers

With apologies I don't have time right now to tease apart all the details on these meetings. But, yuck. Cell Symposia have a big and persistent problem with gender balance of speakers. See the Storify below:

Coming today to a cat near you - microbes

Only three years after first imagined ...

Guest post from Rachid Ounit on CLARK: Fast and Accurate Classification of Metagenomic and Genomic Sequences

Recently I received and email from Rachid Ounit pointing me to a new open access paper he had on a metagenomics analysis tool called CLARK.  I asked him if he would be willing to write a guest post about it and, well, he did.  Here is it:

CLARK: Accurate metagenomic analysis of a million reads in 20 seconds or less…

At the University of California, Riverside, we have developed a new lightweight algorithm to classify accurately metagenomic samples while minimizing computational resources better than any other classifiers (e.g., Kraken).  While CLARK and Kraken have comparable accuracy, CLARK is significantly faster (cf. Fig. a) and uses less RAM and disk space (cf. Fig. b-c). In default mode and single-threaded, CLARK’s classification speed is higher than 3 million short reads per minute (cf. Fig. a), and it also scales better in multithreading (cf. Fig. d). Like Kraken, CLARK uses k-mers (short DNA words of length k) to solve the classification problem. However, while Kraken and other k-mers based classifiers consider the whole taxonomy tree and must resolve k-mers that match genomes from different taxa (by using the concept of “lowest common ancestor” from MEGAN), CLARK rather considers taxa defined for a unique taxonomy rank (e.g. species/genus), and, during the preprocessing, discards any k-mers that can be found in any pair of taxon. In other words, CLARK exploits specificities of each taxon (against all others) to populate its light and efficient data structure. It uses a customized dictionary of k-mers, in which each k-mer is associated to at most one taxon and results in fast k-mer queries. Then, the read is assigned to the taxon that has the highest amount of k-mers matches with it. Since these matches are discriminative, CLARK assignments are highly accurate. We also show that the choice of the value of k is critical for the optimal performance, and long k-mers (e.g., 31-mers) are not necessarily the best choice to perform accurate identification.  For example, high confidence assignments using 20-mers from real metagenomes show strong consistency with several published and independent results. 

Finally, CLARK can be used for detecting contamination in draft reference genome or, in genomics, chimera in sequenced BACs. We are currently investigating new techniques for improving the sensitivity and the speed of the tool, and we plan to release a new version later this year. We are also extending the tool for comparative genomics/metagenomics purposes. A “RAM-light” version of CLARK for your 4 GB RAM laptop is also available. CLARK is user-friendly (i.e., easy to use, it does not require strong background in programming/bioinformatics) and self-contained (i.e., does not need depend on any external software tool). The latest version of CLARK (v1.1.2) contains several features to analyze your results and is freely available under the GNU GPL license (for more details, please visit CLARK’s webpage). Experimental results and algorithm details can be found in the BMC genomics manuscript.

Performance of Kraken (v0.10.4-beta) and CLARK (v1.0) for the classification of a metagenome sample of 10,000 reads (average reads length 92bp).  a) The classification speed (in 103 reads per minute) in default mode. b) RAM usage (in GB) for the classification. c) Disk space (in GB) required for the database (bacterial genomes from NCBI/RefSeq). d) Classification speed (in 10^3 reads per minute) using 1, 2, 4 and 8 threads.

Rob Dunn seeking community participation in suveying & analyzing Duke Forest warming chambers

Just got this email from Rob Dunn from NC State.  He said it was OK to post it ... so I am .. (I note - I just completely love this idea).

Hi folks,

As you might (or might not) know, we have for five years now been running a large-scale warming experiment in which we have warmed twelve 5 meter diameter open-top chambers in forest understory at Duke Forest. We have warmed these chambers in a regression design with the warmest chambers as warm as temperatures are predicted to be in the region in 2100 and the coolest chambers at ambient temperatures (We also have no-chamber controls). These are small worlds each of which mimics aspects of futures we might face. This entire set-up is replicated at Harvard Forest. In these chambers we have been studying the response of insects (with a focus on ants) and plants  over the last five years. When we built them these chambers were the biggest warming experiment in a forest understory in the world. I don't know if it is still true, but it probably is, if only because chambers of this size are so hard to keep going (especially in the early we felt like Fitzcarraldo dragging a ship through the rainforest) that most people have decided against repeating them elsewhere. 

Some basics on the chambers... http://robdunnlab.com/projects/warming-chambers/

I'm writing because on May 25th we are taking the chambers down and doing a final inventory of the response of everything--all the life we can possibly evaluate--to this warming. To varying extents we have considered the phenology of plants in the chambers, many things about ants in the chambers, shifts in composition of invertebrates in the chambers and simple responses of bacterial and fungal assemblages in the chambers. But, we have done all of this delicately, always mindful to not overly disturb the future world we are simulating. Now though that the chambers are coming down we can and will consider roots, plant biomass, the abundance of insect pests, fungal pathogens and much, much, more. 

As we do this intensive survey, we are hoping to train as many different eyes, lenses and perspectives on the chambers as possible. If you are potentially interested in studying some aspect of the response of understory forest life to warming, let us know. If you are interested in studying something that can be extracted from soil or litter samples, we may be able to send you material you can work on. If you have something grander in mind (and we love grand things), then we may need more help from you. If interested, send an email to me, copied to MJ Epps (Mj Epps <mycota@gmail.com>).  This collaboration might be in the form of bringing a new method to the chambers (looking at microbial processes, for instance) or considering a group of organisms we've somewhat ignored (e.g., fly larvae) or it might be something totally off the wall. Feel free to share this email with likable folks that might be interested. 

I'm also delighted to hear creative ideas about visualizing the differences that have emerged over the years of this experiment (hence the inclusion of several artists of various sorts on this email list, if you were wondering why you were copied). 

I hope this email finds you well. 

Best,

Rob