Global Engage Plant Genomics Meeting - Bring Your Y Chromosome Because they Don't Take XX - Calling for a Boycott of this Group

Saw this tweet earlier today

And something seemed hauntingly familiar about the organization referenced.  Turns out this is not the first time they have had issues with Gender Balance.  So I responded

Incredibly distasteful and painful to see this. This group "Global Engage" ran a Plant Genomics meeting last year that I posted about becuase the gender ratio was quite bad for the speakers: YAMMGM - yet another mostly male genomics meeting (series): Plant Genomic Congresses by Global Engage

And after seeing this new Tweet I dug around their web site some more and it is really unpleasant.  Look at their Advisory Panel (which is what Female Scientist was pointing to):

24 scientists.  All of them men.  If you know any of them, as I do, I would recommend you contact them and suggest they resign from this apparently gender-biased organization or force them to add some women to their advisory panel.

The speaker list for their next plant genomics meeting is quite skewed too.  I could find 49 men and 5 women.  What a joke.

I call upon everyone in the community to boycott this meeting and any organized by Global Engage in the future.  They have been informed previously of their gender ratio issues and are clearly not doing anything about it.  And in plant genomics there are so many excellent female scientists that this simply has to be a case of some type of bias.

In addition, I would recommend calling on the sponsors to withhold funding from this meeting and others organized by this group.

Sponsors include


Life Technologies








And let the microbiology word play begin (re Entamoeba feeding)

New paper out about feeding by the parasitic amoeba Entamoeba histolytica.  Apparently, the work shows that this organism feeds by in essence taking bites out of cells.  (I say apparently because the paper is not open access and I don't have access to it from where I am writing).

Anyway - there are a lot of news stories about this.  And for some reason (I am not quite sure why) this has inspired headline writers to get out their pun pens and creative thinking caps.  Here are some of the headlines:

And more coming I assume.

Though as far as I can tell none of the stories picked up on a key word play that could have been made.  The lead scientist behind the study is named Petri.   Someone really should have had "dish" in the title ...

And in non shocking news of the day - more overselling of the microbiome

Well, just read this story: Possible link between bacteria and breast cancer: study | CTV London News.  Serious overselling of the microbiome going on here.  As far as I can tell, all that was shown in the work discussed here (for which there is no publication or presentation of any kind reported) is that the bacteria found in canecrous breast tissue differs from that in non cancerous tissue.  Interesting perhaps.  But not really that informative as just about every time anyone has ever looked at two samples from patients with different health conditions, the microbiome is different.  Much worse that suggestions about the meaning of the differences they observe, the article then goes on to state:

And since we know that priobiotics can positively affect gut health, might the same beneficial substances influence breast health? Related bacterial research offers tantalizing possibilities. 
"It shows you how closely associated microbes are with our body and our health," Reid says. "And therefore when you try and modulate them through probiotics chances are you could have an effect that's beneficial."
What?  Not only does Dr. Reid say, incorrectly, that "chances are you could have an effect that's beneficial" simply by trying to use probtiotics to modeulate health.  But the whole ending to the article implies that somehow, magically, probiotics are a good idea for preventing breast cancer.  Uggh.

Guest post by Kevin Penn: In Search of Bacteria on Drugs: Secondary Metabolites and Microbial Ecology

Below is a guest post from Kevin Penn, who used to work in my lab ...

I am a former Research Associate of Jonathan’s interested in understanding evolution and ecology of microbes in natural environments.  Recently I’ve become interested in learning about the expression of secondary metabolite related genes in natural settings to put the gene’s products into an ecological context, because almost certainly microbes are not making natural products just to benefit humans.   I am currently studying these topics as a post-doc in Janelle Thompson’s lab at MIT. 

When I got to MIT there was a set of paired end Illumina HiSeq data from six time points collected over one day night cycle from the Kranji Reservoir in Singapore, which was experiencing a cyanobacterial Harmful Algal Bloom (cyanoHAB).  Note algal in this case means bacterial, I used to argue that this is taxonomically incorrect but used colloquially I think it works.  These samples are what the paper “Secondary metabolite gene expression and interplay of bacterial functions in a tropical freshwater cyanobacteria bloom” is based on.  MIT has a program in Singapore called Center for Environmental Sensing and modeling/Singapore MIT Alliance (CENSAM/SMART) and one of the projects is to learn about microbial populations associated with the drainage and reservoirs over the city/state/country.  The motivation for the study (Penn, et al 2014) is based on two observations.  1) The idea to sample a day night cycle of a harmful algal bloom derived from experiments done for marine Prochlorococcus showing major changes in gene expression in the evenings and morning and more similar profiles at noon and midnight (Zinser, et al 2009). 2) An initial sample collection and analysis for this study did not readily detect genes for the toxin microcystin from drainages around the reservoir catchment (Nshimyimana, et al 2014) indicating the Cyanobacterium was growing in the reservoir (i.e. not being flushed in).  We knew the bloom in the Reservoir was dominated by Microcystis aeruginosa but now we wanted to learn if microcystin toxin genes were expressed in the reservoir and if so were they expressed around the clock.


Harmful algal blooms are of concern because they appear to be increasing in frequency on a global scale.  HABs are not only eyesores they also produce toxins that make lakes unusable for drinking water and recreation.  For a good introduction to HABs I suggest reading an excellent book “The algal bowl: overfertilization of the world's freshwaters and estuaries” by David W. Schindler & John R. Vallentyne.  But I should note there are probably thousands of books written on the subject.  Below you can see what our study site looked like during a bloom with a surface scum visible and during conditions where the water is a bit more clear (post bloom).

Polyketide synthases (PKS) and Non-ribsomal peptide synthetases (NRPS)

The search for expression of microcystin toxin genes is also a part of my larger interest to learn about the expression of PKS and NRPS genes in natural settings.  PKS and NRPS derived molecules represent a large class of natural products famous for being toxins and used as medicine to treat human disease.  Two phyla of bacteria are historically known for their production of these compounds (Actinobacteria and Cyanobacteria).  For example the PKS and NRPS derived microcystin toxin is produced by M. aeruginosa and members of the Phylum Actinobacteria produce the potent antibiotic rifamycin.  The expression and presence of most PKS and NRPS pathways in natural settings is currently not very well understood. 

Prior to this work it was not clear that bacterial PKS and NRPS pathways are expressed in natural settings.  The products of the microcystin pathways are present in harmful algal blooms (thus the term Harmful). This made Kranji Reservoir a good system to study because we should observe the transcripts for microcystin.  PKS and NRPS genes can be highly repetitive and similar between different pathways so we were not sure we find them with Illumina type sequencing.  Based on my initial tests using a tool called NaPDoS, which I helped developed at Scripps to quickly identify sequence tags from PKS and NRPS gene pathways, it was clear we could see the expression of many different pathways in our data.  This spurred me on to look at the differences in expression over time.  The examination of the time series revealed that there appears to be a rhythm to expression of PKS and NRPS genes and that strikingly, one of the most highly expressed PKS/NRPS gene cluster in M. aeruginosa has not been linked to a molecule.  This is especially interestingly from an ecological perspective, as one of the most highly expressed PKS/NRPS pathways have yet to be associated with a product.


One of the cool things about science is that it can be predictive. Within an experiment of photosynthetic bacteria then you would hope that your expression data reflects the idea that photosynthetic life uses light to photosynthesize and that the genes that code for the machines that harness light would be most highly expressed during the day.  We call that,  the the “sanity check,”  and it came out very nicely in our metatranscript data; showing that photosynthesis related genes cycle in the environment and are highly correlated with the day night cycle.  Our observation that the things we expected to be highly expressed were highly expressed gave us confidence that our data may have other patterns that we would not necessarily think to look for.  We started to look at broader categories of function genes for the top four phyla.  From this analysis we noticed that some phyla were enriched for particular genes relative to other phyla, which in turn allowed us to make some ecological predictions in relation to how each group, might be functioning in the bloom community.  For example look at figure 4 and 5 in the paper and you can see that Actinobacteria are mostly transporting photosynthetically derived carbohydrates but Bacteroidetes groups are mostly transporting peptides furthermore groups within the proteobacteria are expressing most of the motility and chemotaxis related genes. 

Quantifying natural microbial communities remains a significant challenge and more importantly identifying ecological functions for phenotypes promises to provide microbial evolutionary biologist with crucial data to learn about the evolution of bacteria.  Imagine trying to study the evolution of a hand if you had no idea of the ecological function for the hand.

Problem Solving- paired end reads

One of the important decisions we had to make for us to start the analysis of Illumina data center on the state of paired end sequencing in metatranscriptomics.  Paired end sequencing is a great boon for Illumina sequencing and Illumina sequencing created a huge opportunity for the field of metagenomics.  But paired Illumina reads that do not collapse into one can represent a large portion of an Illumina sequence run despite efforts to create short enough sequences to have overlap and yet make the fragments large enough to make paired end sequences more informative.  Paired ends can complicate issues because they may represent two genes but one operon, or two genes from different operons which is a problem for analysis trying to assign function to reads. The other issue is that in assigning taxonomy to reads by chance alone similar sequences although part of a pair may match different organisms.  MEGAN tries to deal with this by increasing bit scores for sequences that match the same thing.   We made the decision to use paired information to improve the confidence in function assignment in MEGAN if both reads hit the same gene, and treated 1 and 2 reads as separate for counting total reads matching a gene if the read counts were not to be normalized to gene length.  Another aspect of the study focused on calculating expression for genes from the bloom former M. aeruginosa using RPKM which does take into account gene length thus we decided to treat the 1 and 2 reads as technical replicates for calculating RPKMs and averaged the values.


This experiment has given us the first glimpse at expression of toxin genes in a natural setting and provided us with some clues of microbial phylum level interplay. The next experiment to further test our observations includes a greater sampling effort over two day night cycles at a greater frequency and with replicates and sampling at the surface and subsurface.  This work is being done in collaboration with another research group interested in Microcystis and harmful algal blooms at the National University of Singapore led by Prof. Karina Gin. It is known that M. aeruginosa strains migrate up and down in the water column and we want to check to see if some of our cyclic observations relate to the presence of different strains present on the surface throughout the day. A follow up study in progress is to look at the reservoir community during non-bloom conditions and run perturbations to identify the effects of the addition of nitrate, phosphate, and microcystin on the microbial community in hopes to learn if there are expression patterns that show how Microcystis is able to bloom.

My Background

The exact story behind the paper will be better understood if it is supplemented with a brief background about my introduction to Genomics and microbial ecology which mainly occurred after starting work as a Research Associate for Jonathan.  Looking back “many years ago” I had just finished up an undergrad degree at UCSB in Aquatic biology and I was looking for a job as a scientist when I met Jonathan.  It was really my first meetings with Jonathan that have set my way forward in research.  I wanted to learn about how things evolve and the ecological functions of traits and Jonathan wanted to understand how all life evolved which meant he was studying the genomes of microbes.  In our first meeting we discussed how genomics and methods associated with genomics namely 16S rRNA gene community studies were going to allow us to learn all about microbial ecosystems and even allow us to do insitu ecological studies of microbes (the term metagenomics was not widely known or used at this time).   As TIGR slowly evolved into JCVI, I began my move to grad school to work in Paul Jensen’s lab at Scripps Institute of Oceanography who had recently sequenced the genome of a couple species of marine actinomycetes.  In grad school I spent a lot of time learning about natural products and the genomes of famous group of organism called Actinomycetes, which make about 80% of the antibiotics we take today.  By the time I finished grad school I had become acutely interested in learning about the expression of natural products related genes in a natural setting.


Our latest paper published in ISME reflects a combination of my exposure to some very different fields of scientific research, from studying genomics and community diversity at The Institute for Genomic Research (TIGR) to my PhD work in natural products research at Scripps and now my studies on community gene expression dynamics in Harmful Algal blooms at MIT.  I have been researching the ideas about insitu microbial ecology that Jonathan discussed with me those many years ago and continue to expand our knowledge about what microbes are doing in natural setting in this paper.  

Of course I did not do this paper in a vacuum at MIT. Prof. Janelle Thompson organized the data collection, co-wrote the paper and taught me a lot about the appropriate statistics we needed to use to analyze our data and interpret the results.  Graduate students Tim Helbig and Sonia Timberlake helped me get going on the computer clusters here at MIT. One of my favorite parts of moving institutions is learning the in and outs of new computer clusters.  I have been funded as a postdoctoral associate at MIT and subsequently by the NSF post-doctoral fellowship intersection of math and biology during this research. Singapore CENSAM/SMART has supported our travels to Singapore along with sequencing costs.

Good reading on the history of the terms/concepts of prokaryote & eukaryote

Preparing for some lectures at UC Davis for Biodiversity and The Tree of Life course and came across this: The Prokaryote-Eukaryote Dichotomy: Meanings and Mythology by Jan Sapp which I had not really scrutinized before.  It is quite good and has lots of information on the history of microbiology and the twisted history of the prokaryote - eukaryote distinction.  Veryvery interesting stuff.  And freely available in Pubmed Central. Thank you thank you thank you Pubmed Central and the American Society for Microbiology.

It takes a village - and if you are interested in plants - here is one

Continuing to be impressed with PlantVillage. Their mantra is

PlantVillage is built on the premise that the all knowledge that helps people grow food should be openly accessible to anyone on the planet. PlantVillage is a user moderated Q & A forum dedicated to the goal of helping people grow their own food. It is an open freely available resource that helps you solve all your plant related questions.
I first found out about this when David Hughes was visiting UC Davis a few weeks ago to give a talk.  I met with him (to discuss zombie ants - what else) and he told me about PlantVillage which he helps run.

So I registered and I am going to start uploading various information about our plants in my yard and elsewhere.   I tested the system by posting a pic of my peach / nectarine.

Lots of people there posting pics and asking questions about identifying issues with their plants.  Seems like an interesting site.

Closed access irony award: Christine Greenhow & Benjamin Gleason on social media and scholars

Well, isn't this ironic.  There are a few news stories I was pointed to about a recent paper from Christine Greenhow & Benjamin Gleason at Michigan State.  Here is one of the stories: Why scholars don't trust social media? | Business Standard.  And here is a link to the paper: Social scholarship: Reconsidering scholarly practices in the age of social media.

In the news story linked above one of the authors of the study is reported to have said:
"Only a minority of university researchers are using free and widely available social media to get their results and published insights out and into the hands of the public, even though the mission of public universities is to create knowledge that makes a difference in people's lives," Greenhow explained.
And here are some quotes from another story: The "Ivory Tower" Appears Reluctant to Use Social Media:
I'm arguing that we need more “social scholars.” Social scholars use social media to publish and interact with scholarly output and to join an online community around their topic. Social scholarship is characterized by openness, conversation, collaboration, access, sharing and transparent revision... engaging an informal, social review process may help surface inaccuracies and engage a wider, nonspecialist audience.
And also
“Academia is not serving as a model of social media use or preparing future faculty to do this,” Greenhow said. Adding, “The issue is at the heart of larger discussions regarding accessibility, equal rights to higher education, transparency and accountability.”
Obviously people who know me would know that I certainly feel that it would be good to have more scholars being active users of social media. Though I don't think I would push the discussion too far into "equal rights" at least in this context.

But though I support the general idea of some of the quotes from Greenhow, I can't say I agree with what is in the paper.  I can't say I disagree with it either.  You know why.  Because I do not have %&(#(&$ access to the paper.  This is what I get when I try to get the paper:

So let me get this straight.  There is a scholarly paper discussing the limited use of social / free / open media by scholars.  And one of the authors of the paper is lamenting this limited sharing of knowledge.  And the paper is not openly available.  Brilliant.

Why I don't like to pre-submit slides for talks - lessons from #AAASMoBE meeting

So - I gave a talk at a meeting on Thursday.  The meeting was called "Microbiomes of the Built Environment" and it was sponsored by the Alfred P. Sloan Foundation and run by AAAS.

The meeting organizers, as is often the case, wanted me to submit my slides a few days in advance, in theory to make sure they were loaded into their system and that all worked OK.  Well, as usual, I did not do this.  I like to make my talks fresh - just before the meeting so that I can incorporate new ideas into them and so that they do not have that canned feeling that a lot of talks do.

My talk was to be 15 minutes long and was to focus on my Sloan Foundation funded project "microBEnet: the microbiology of the built environment network" (see for information about the project). I figured, I would work on the talk on the plane - five plus hours to edit a talk I had given relatively recently on the topic of this project.  And all would be good.  Plus, United had told me there would be WiFi on the plane so if I needed any new material I should be able to get it from the web right?  Well, the flight took off on time - 8 AM on Wednesday morning.  And I opened my laptop once allowed and paid the $15+ dollars for the WiFi and got to work.  Then, about 10 minutes later, the WiFi died and despite heroic efforts by the flight attendants, it never came back. And I plugged away at my slides doing some edits of the following presentation.

Guest post by Jay Kaufman: A Bad Taste That Keeps Not Getting Any Better....

Guest post by Jay Kaufman.  Jay and I have been having some email discussions about a paper in PLOS One.  I offered to let him write a guest post to my blog about his concerns.


Jonathan Eisen already posted on this blog about a PLoS ONE paper by Mason et.. published on 23 October 2013.  And he posted related comments on the PLoS ONE website.  I also commented at this site, in reference to his comments and the authors' response. The purpose of my comments here are just to review those concerns and comment additionally on the PLos ONE response and what this means for the journal's publication model and the progress of science.

The paper by Mason and colleagues analyzes data on 48 people in each of 4 self-identified ethnic groups (African American, Caucasian, Chinese, and Latino). These study subjects are apparently volunteers, and the paper only states that they are non-smokers over 18 years old who are free of a list of diagnosed diseases and who have not recently had their teeth cleaned. Based on the text of the published paper, there is no consideration of their age, diet, social class, or even gender. The authors culture bacterial species from the study subjects and process the data through an algorithm that maximizes the prediction of racial group membership based on these measured data.

The prediction is moderately successful, but this could result from any number of unsurprising reasons. For example, if alcohol consumption affects some particular bacterial species, and whites drink more than Asians in central Ohio, then whatever species is diminished by alcohol exposure would help predict that a sample was from a white rather than from an Asian volunteer. And likewise for any of a million possible lifestyle, social class and demographic differences.  In fact, this is a general problem with data mining exercises that Lazer et al describe in the current issue of Science.

The authors provide no information about how balanced this sample is with respect to any of these variables. Maybe the 48 Hispanics are younger than the 48 whites on average, or have more tooth decay or eat more refined sugar or any of a million other possibilities. The fact that these countless potentially imbalanced factors get represented in the oral bio-environment hardly seems surprising, and the fact that these behaviors and exposures might be differential by race is an observation that is completely trivial from a sociological perspective.

My concern here, however, the authors assert in the published text that these differences do not arise from any of these myriad environmental factors, but from some innate genetic characteristics of the groups. In the Discussion section on page 3 they state that "ethnicity exerts a selection pressure on the oral microbiome, and...this selection pressure is genetic rather than environmental, since the two ethnicities that shared a common food, nutritional and lifestyle heritage (Caucasians and African Americans) demonstrated significant microbial divergence." Here is a remarkable statement, that Caucasians and African Americans experience no differential dietary or lifestyle factors. It is directly contradicted by thousands of published papers in sociology, epidemiology and anthropology that document these differences for reasons of culture, geographic origin, social class and discrimination.

Jonathan Eisen's post directly confronted the authors on this point, and they responded with the following explanation:

"Subjects were selected based on extensive questionnaire surveys and clinical examinations to ensure homogeneity. These questionnaires evaluated educational level, socio-economic status, diet and nutritional history, systemic health status, oral hygiene habits and dental visits, among other things."

This is surely an important statement about the research design, but the problem is that it appears nowhere in the peer-reviewed text of the published paper. What exactly do the authors mean when they insist that the study subjects were perfectly balanced on factors such as socio-economic status and nutritional history? These complex social and lifestyle variables are notoriously difficult to define and measure. While the authors describe the laboratory techniques in baroque detail, they do not even mention in the published paper that they measured these factors, let alone how these variables were defined and considered in the analysis. This represents a profound limitation for the reader in assessing the validity of these measures and adjustments, and therefore the adequacy of the claimed "homogeneity". The complete omission of these crucial aspects of the analysis in the paper prevents the reader from investing much confidence in the boldly stated claim that observed differences are "genetic rather than environmental" in origin.

I expressed these concerns in my own post at the journal website on 14 November 2013, but the authors did not respond.  Therefore, at Jonathan's suggestion, I addressed this concern to the PLoS ONE editors in an e-mail on 22 November 2013. I got passed along from one editor to another, and finally I got a very nice response from Elizabeth Silva on 4 December 2013. She wrote:

I wanted to let you know that I am discussing this article and your concerns with both the Academic Editor and the authors, as well as with my colleagues. We take such concerns very seriously and will ensure that appropriate measures are taken to correct any errors or discrepancies. 

Then I waited.  After 2 months I had heard nothing, so I wrote to Dr. Silva again asking for any word on progress, but received no reply.  So I waited another month.

On 4 March it had been 3 months since the note from PLoS ONE promising appropriate measures to correct any errors or discrepancies, so I wrote again, this time a bit more insistently.  This did message did finally generate a quick and reassuring response from Dr. Silva:

I really am very sorry for the extended delay in replying to you, and for my neglect in providing you with an update. Following your correspondence I contacted the authors to ask them for additional information relating to their statement that they corrected for confounding factors, and details of these methods. They promptly replied with a table of details of the baseline variables that they corrected for, and that they described in the comment on their article (see attached), as well as an additional correction to one of their figure legends. I then contacted the Academic Editor, Dr. Indranil Biswas with the full details of your concerns, as well as the table sent by the authors and the correction they requested for their figure legend. We asked Dr. Biswas to revisit the manuscript, in light of this new information, and he has informed us that he feels the conclusions of the manuscript are sound. We will now work with the authors to draft and issue a formal correction to the published article to update the methods to include the table, and to amend the figure legend in question.

The table that Dr. Silva forwarded displayed a list of variables and a p-value for some kind of test between the values in the 4 race groups. The test is not specified (t-test? chi-square test?) but presumably it is for any difference in means or proportions between the 4 groups.  Most of the p-values are large, indicating little evidence for any difference between the groups in income, age, education, or frequency of tooth-brushing, etc.  Based on this table, the populations differed only in their diets, which were characterized as "Asian Diet", "Hispanic Diet" and "American Diet".  Not unsurprisingly, the Asians were significantly more likely to report an "Asian Diet" and the Hispanics were significantly more likely to report a "Hispanic Diet".  The Blacks and Whites had similar reported consumption of the "American Diet", which presumably was the basis for the authors' assertion that these groups have identical social environments.

To date, there has been no correction made to the Mason et al paper at the PLoS ONE website.  Therefore it is perhaps somewhat premature to speculate on how the authors will address the concern voiced by Jonathan Eisen's posted comment and blog post that balance across a handful of measured covariates does not in any way imply balance across all relevant factors except for genetics. Indeed, it has long been argued in the epidemiology literature that one cannot make indirect inferences about genes by measuring and adjusting for a few environmental exposures and attributing all remaining differences to genes.  The argument that Blacks and Whites in Ohio experience identical environments is clearly false, even if a handful of measured covariates are not significantly different in their small convenience sample, the exact origin of which is still obscure.

There are many observations that can be made from this episode. I offer just a few:

  1. These authors are assiduous in describing their lab techniques, but regarding the study design and analysis they are quite cavalier.  Presumably the reviewers were not population scientists, and so they failed to point out these embarrassing flaws. This raises the question of whether a multidisciplinary journal such as PLoS ONE has the relevant expertise to screen out scientifically invalid papers. The fact that Dr. Silva suggested that the authors' table of covariates and p-values solves the issue demonstrates a wide gap of understanding.  Specialty journals that handle a narrow disciplinary range are not faced with this kind of crisis of competence.
  2. PLoS ONE is such a large operation with so many papers, that quality control seems to suffer. These beleaguered editors are responsible for an enormous publishing volume. Has quantity overwhelmed quality to the extent that gross errors of logic slip through? Months later, the Mason paper has been accessed thousands of times and generated a great deal of media attention, and yet no correction or erratum has appeared, despite the fact that the authors freely admit that the methods in their published paper are not accurate. 
  3. The publishing model gives PLoS ONE a big incentive (almost $2000) to accept a paper, but once it is published, little incentive to correct or withdraw it. 

Sadly, this is not an isolated example.  This week, PLoS ONE published a paper by Wikoff et al which makes a similar logical gaffe about observed racial difference proving a genetic difference.  We could post a comment online, but it seems that nobody (neither the authors nor the editors) has much time to spend monitoring such comments, nor much incentive to care about them.  The authors have their publication, the journal has its $2000, and another tiny piece of horrific misinformation has been released into the world.  The basic philosophy of PLoS ONE is to reduce the gate-keeper role of scientific publication. I am starting to become convinced that a little gate-keeping is not such a bad idea.

Wrap up of Twitter chat on the human microbiome with a high school bio teacher

It started with this
And eventually we worked out a date, which was yesterday. Now I note I had no idea who these people are/were. But it seemed like a good chance to do some some outreach. So I said yes. And yesterday it happened. OK it was chaotic. But it was fun. Here is a Storify of the Tweets.