Session Report: Citizen Microbiology at Citizen Science 2015

A couple of weeks ago in San Jose was the inaugural meeting of the Citizen Science Association, “Citizen Science 2015“.   I previously posted my thoughts on day one here at microBEnet.

On day 2, Holly Menninger, Jenna Lang, and I organized a session entitled “Citizen Microbiology: Engaging the public in the study of invisible life”.   The format of the session was to have lightning talks by several speakers and then a moderated discussion.   We tried to get speakers with a variety of perspectives on the broad topic of “citizen microbiology”.   Here was the final panel:

Holly Menninger (Wildlife of Our Homes, Belly Button Biodiversity Project)

Jenna Lang (Project MERCCURI)

Bethany Dixon (High school science teacher)

Adam Robbins-Pianka (American Gut)

Sally James (Science reporter and citizen science participant)

Patrik D’Haeseleer (DIY Bio: Counter Culture Labs and Biocurious)

Everyone gave a five-minute lightning talk (more or less) and then we fielded questions… and there were plenty!   Even though it was the last session of the day the audience seemed really engaged and there was a lot of productive discussion.   I’d say the biggest take-home message was that there’s a lot of excitement about citizen microbiology.   Many of the challenges are shared by any kind of citizen science but it seems like the two biggest ones that are at the forefront in citizen microbiology are the problems related to data communication/visualization and biosafety (e.g. culturing unknown microbes in a classroom).

Here’s our abstract from the session:

Increased public interest in both microbiology and citizen science, combined with technological advances in DNA sequencing, has recently led to the rise of many “citizen microbiology” projects including Wild Life of Our Homes, the American Gut Project, and Project MERCURRI. Citizen microbiology faces a number of special challenges for public engagement that set these projects apart from many other successful, ecologically focused projects: microbes cannot be seen with the naked eye, are often feared as the cause of disease, and are typically identified by genetic sequences, not physical characters. On the flipside, citizen microbiology projects are uniquely positioned to help participants engage in meaningful and intensely personal ways with topics that have significant consequences on human health and well-being (i.e., microbiome, overuse of antibacterial agents, sick building syndrome).

The objective of our citizen microbiology symposium is to shine a spotlight on this emerging field and discuss opportunities and challenges both unique to citizen microbiology and shared in common across more traditional citizen science projects. Our session will start with five-minute speed talks presented by stakeholders from all aspects of citizen microbiology (scientists, participants, project managers, teachers) to provide brief project overviews and set the context for discussion: (1) Wild Life of Our Homes and Belly Button Biodiversity (Menninger); (2) American Gut Project (Robbins-Pianka); (3) Project MERCURRI (Lang); (4) Microbes in the Classroom (Dixon); (5) DIYbio and the citizen microbiology connection (D’haeseleer); (6) Participant perspective on citizen microbiology (James).  Speakers will then transition to a moderated panel discussion (led by Coil) to discuss cross-cutting topics like data visualization, data return and sharing, managing participant expectations, biosafety, and participant privacy.

A big thanks to all the participants and especially to the great speakers!

 

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Issues classifying ITS data? The answer could be simply using “blast” during taxonomy assignment in QIIME

I wrote a post on the Seagrass Microbiome website yesterday about my struggles with fungal ITS sequencing data which I thought I’d share here as well in case anyone is looking to jump into the fungal fray. To summarize: changing the default method of the QIIME assign_taxonomy.py script from “UCLUST” to “blast” dramatically increased the number of ITS sequences reads that were classified in my dataset. Blast is not the best (or even a good) method for classifying sequences, but for our purposes we just need kingdom level classification (i.e. we just want to know that we are actually analyzing fungi and not, for example, seagrass) so its likely alright. However, if anyone knows of a way to perform phylogenetic analysis on sequence reads that cannot be aligned (like ITS), please speak up!

After posting about my struggles (and their subsequent solution) on twitter, a real mycologist pointed me towards the methods section of Smith and Peay 2014. In Smith and Peay 2014 the authors use UPARSE (vs. UCLUST) to pick OTUs; something I’ve been thinking about trying for 16S analysis already. Additionally, the article references Peay et al 2013 when discussing taxonomic assignment and Peay et al 2013 uses the QIIME assign_taxonomy.py script, with you guessed it, the “blast” method.  Thus, it appears that there is at least some precedence in the literature for using “blast” for ITS sequence classification in QIIME which is reassuring; I just wish I had figured this out earlier!

The full post can be found here: http://seagrassmicrobiome.org/2015/02/23/fungal-its-taxonomy-problem-solved-for-now/

Cassie Ettinger (@casettron) is a PhD student in Jonathan Eisen’s lab and is interested in plant-microbe interactions and host-microbe coevolution.

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Does microbiology of the built environment have any Big Data issues? If so …. $$$$

Just was sent this by our grants office: nsf.gov – Funding – Critical Techniques and Technologies for Advancing Foundations and Applications of Big Data Science & Engineering – US National Science Foundation (NSF).

Seems like this may be of interest to folks working on microbiology of the built environment as there are some serious Big Data challenges here.

Summary text is below:

The BIGDATA program seeks novel approaches in computer science, statistics, computational science, and mathematics, along with innovative applications in domain science, including social and behavioral sciences, geosciences, education, biology, the physical sciences, and engineering that lead towards the further development of the interdisciplinary field of data science.  The solicitation invites two types of proposals: “Foundations” (F): those developing or studying fundamental theories, techniques, methodologies, technologies of broad applicability to Big Data problems; and “Innovative Applications” (IA): those developing techniques, methodologies and technologies of key importance to a Big Data problem directly impacting at least one specific application.  Therefore, projects in this category must be collaborative, involving researchers from domain disciplines and one or more methodological disciplines, e.g., computer science, statistics, mathematics, simulation and modeling, etc. While Innovative Applications (IA) proposals may address critical big data challenges within a specific domain, a high level of innovation is expected in all proposals and proposals should, in general, strive to provide solutions with potential for a broader impact on data science and its applications. IA proposals may focus on novel theoretical analysis and/or on experimental evaluation of techniques and methodologies within a specific domain. Proposals in all areas of sciences and engineering covered by participating directorates at NSF are welcome.

While notions of volume, velocity, and variety are commonly ascribed to big data problems, other key issues include data quality and provenance. Data-driven solutions must carefully ascribe quality and provenance to results in a manner that is helpful to the users of the results. For example, in some cases, such as in education research, data quality may aggregate to test or measurement instrument quality, where a composite of variables may be used to describe one or more constructs.

In addition to approaches such as search, query processing, and analysis, visualization techniques will also become critical across many stages of big data use–to obtain an initial assessment of data as well as through subsequent stages of scientific discovery. Research on visualization techniques and models will be necessary for serving not only the experts, who are collecting the data, but also those who are users of the data, including “cross-over” scientists who may be working with big data and analytics for the first time, and those using the data for teaching at the undergraduate and graduate levels. The BIGDATA program seeks novel approaches related to all of these areas of study.

Before preparing a proposal in response to this BIGDATA solicitation, applicants are strongly urged to consult the list of related solicitations available at: http://www.nsf.gov/cise/news/bigdata.jsp and consult the respective NSF program officers listed in them should those solicitations be more appropriate.  In particular, applicants interested in deployable cyberinfrastructure pilots that would support a broader research community should see the Campus Cyberinfrastructure – Data, Networking, and Innovation Program (CC*DNI) solicitation (http://www.nsf.gov/pubs/2015/nsf15534/nsf15534.htm?WT.mc_id=USNSF_25&WT.mc_ev=click). Applicants should also consider the Computational and Data Enabled Science and Engineering (CDS&E, PD 12-8084) (http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504813) and Exploiting Parallelism and Scalability (XPS, NSF 15-511) (http://www.nsf.gov/pubs/2015/nsf15511/nsf15511.htm) solicitations for potential fit.

 

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Quick post: interesting read from December on “The Urban Microbiome”

Quick post here.  I discovered this a few weeks ago but just have not had time to write about it in detail or even scrutinize it exceptionally carefully but it seems of interest to the theme here at microBEnet:  Invisible City Life: The Urban Microbiome | The Nature of Cities.  By Marina Alberti from the University of Washington “College of Built Environments”.  Sorry I cannot write more about it right now but wanted to share it with others.  If you have thoughts on it please post comments …

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Open courses and course materials on microbiology of the built environment

One activity we have been hoping to do more of here at microBEnet is to catalyze the development and sharing and evaluation of course materials (preferably free and open) for teaching about microbiology of the built environment.  I confess this is just not my area of expertise so I am going to be writing a series of posts about this to solicit input from the community.

Today I am focusing on exisiting available course materials that cover topics related to  microbiology of the built environment.  If people out there know of any such materials specifically about microbiology of the built environment it would be greatly appreciated if you could share such information.

What I have found so far is limited and virtually none of it is specifically focused on microbiology of the built environment.  The closest I have found:

There is certainly a decent amount of related material out there on either microbiomes, or microbial ecology, or building science including:

I am sure there is more out there on these related topics.

Any pointers, especially to online courses or course materials directly about microbiology of the built environment would be greatly appreciated.

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IPython notebook for basic microbial ecology analysis using QIIME

I’ve gone public with my default QIIME workflow. I hope this will be helpful to some, and I encourage anyone with QIIME skills to read through it to see if I’m missing anything.

Brief blog post about it is here:

http://jennomics.com/2015/02/20/ipython-notebook-for-basic-microbial-ecology-analysis-using-qiime/

and the notebook is hosted here:

jennomics.github.io/QIIMEbyJennomics/

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Answering questions about microbes in the built environment

Laura Williams recently posted a great writeup of some of the materials she covered with her microbiology class – specifically focused on microbes in the built environment. It turns out they were reading one of the papers we recently published (!) about how humans can influence the microbes indoors by the way we interact with surfaces.  I’m glad this stuff is making it into a microbiology course! Here is a response to some of the questions that came up during the class, and I hope this can add to the BE microbiome discussion.


Why should we care about all of this?

This is a great question, and one we constantly debate. Of course we should care about how we disperse pathogens, bioterrorism threats, and the sorts of microbes that degrade our building materials or otherwise influence our health. But being able to detect those types of microbes (sometimes at a very low abundance threshold), requires an in-depth understanding of what ‘normal’ should look like.

The new NYC subway paper (which blew up in the media) is an excellent example. They found lots of things that seem troubling at first glance, but almost certainly are not dangerous to people riding the subway, and might not even exist. And anytime we sequence from surfaces in buildings, like classrooms, we pretty much always find microbes that are closely related to pathogens. But that, again, is teaching us what normal should look like. That way we will be better able to distinguish real threats when they do show up. It is probably shocking to most people the first time they learn that chairs are covered in gut and vaginal microbes, but it turns out that is pretty normal, so now we know what to look for.

Another reason I think all of this is really important it to constantly keep an eye on the future of sequencing technology. When we do studies, like the classroom microbiome or the subway study, it takes months to process, analyze and interpret the data. That is an unacceptable turnaround if we really care about detecting threats in real time. However, I tend to approach all of these studies as a way to calibrate our understanding of the built environment, as well as the tools we use, because we are likely only a few years from essentially real time sequencing and detection. When we get there, we will have a better handle on the sequencing technology and on the ecology of the built environment because of these early studies. In other words, these early studies are laying the foundation for what is coming soon – the ability to make sense of the built environment microbiome in real time.


How can we influence the types of microbes that grow in the BE?

There are two parts of this question: how to influence what grows in the BE, and how to influence what shows up in the BE.

Almost all of these high-throughput bacterial studies are mostly detecting microbes (or their leftover DNA) that are just hanging out in relatively dry conditions. So they dispersed in from other environments and now they have a chance to interact with us and our indoor environments. From that perspective, we now know of lots of ways to influence the microbes indoors.

Ventilation is one major way to influence the BE microbiome. Ventilated air carries around lots of microbes, either from outdoors (e.g., soils, plant leaves, ag fields, marine environments, …) or from other rooms (e.g., human-associated microbes floating in from the hallway). The simple choice of opening a window vs mechanically filtering air through an HVAC system can have a major influence on the sorts of microbes in the air, on surfaces, and accumulated in dust.

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Building Drainage Systems

When drainage systems fail, a lot of undesirable effects may follow, from leaks that cause mold to fecal-laden water contaminating groundwater and houses. A study from the Heriot Watt University in Edinburgh, Scotland found yet another concern we should have about broken or inadequate building drainage. Airflows in pipes can contain aerosolized pathogens and then escape into indoor spaces through faulty junctions or breaks in the pipes. This is the method by which they believe Norovirus transmission occurs. They suggest that the virus uses building drainage systems as a reservoir, and that this mechanism of dispersal may feasibly occur with other aerosolizable pathogens that are common in drainage water (like Clostridium difficile). The researchers also created a drainage model that they were able to propose might have aided in the Amoy Gardens SARS outbreak. Specifically, the seal on a toilet’s U-bend showed the potential of causing bioaerosols by the mechanism they propose. In short, you now have another reason to check your house’s pipes on a regular basis for damage.

 

 

Alex Alexiev is an undergraduate in Jonathan Eisen’s lab, working on aquariums as part of the microbiology of the built environment

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