2018 Year in Review

No one is sorry to say goodbye to 2018, yet it still seems like the 2018 Year in Review has arrived too soon. As usual, I’ve been keeping busy; you can find my reviews for 2017 and 2016 in the archives. For the first year in the
three years since I started this blog, I’m not starting a new job! I’ve been at BioBE for a year and a half, and it’s a relief to be in an academic position long enough to finish the projects you started (I’m only just starting to submit some manuscripts for work I did back in Montana).

BioBE and ESBL staff (not all pictured), Sept 2018

Research

Two papers of mine were published this year, including one on the bacteria along the GI tract of calves, one on the effect of dietary zinc on bacteria in sheep.  A comprehensive culturing initiative of rumen microorganisms, called the Hungate 1000 Project, an international initiative to which I contributed data, was also published.  That puts me up to 17 scientific articles, of which 9 are first-authored, as well as 5 scientific reviews.  I have three manuscripts in review right now, and another five being prepared – 2019 will be a busy year.

I joined two journal editorial boards this year, PloS One and Applied and Environmental Microbiology. Both positions are as an Academic (or handling) Editor; I will oversee manuscript review by soliciting reviewers, assessing their recommendations, and interfacing with authors. In recent years, the gender discrepancy in science has received more attention, and some journals are making efforts towards increasing the number of female editors, reviewers, and contributors to reduce implicit bias in science publishing. I am pleased to be in a position where I can help change that!

I’ve been spending a lot of time writing grants and developing potential projects on microbiology and health in the built environment, many of which should be moving forward in 2019. I’ve also been spending time training the 9 undergraduate students I hired over the summer and fall to work at BioBE. In addition to microbiology and molecular biology laboratory skills, I have been training them on DNA sequence analysis and coding, scientific literature review, and science writing and communications.

Teaching

This fall term, I taught Introduction to Mammalian Microbiomes for the University of Oregon Clark Honor’s College.  I proposed this new course last year, and developed the curricula largely from scratch.  I’d previously taught some of the subject material at Montana State University in Carl Yeoman and Seth Walk’s Host-Associated Microbiomes course; however in IMM I was teaching to non-science majors.  The course went well, and I’ll be diving into it in detail with a full blog post in a few weeks. I proposed the course again for next year, as well as another new course; Microbiology of the Built Environment.

Presentations and travel

Early in the year, I gave two public talks on the gut microbiome for Oregon Museum of Science and Industry; one in Eugene and one in Portland. Both were a lot of fun, and I really enjoyed getting to share my work with the public.

In May, the research group I am part of (the Institute for Health in the Built Environment, comprising the Biology and the Built Environment Center, the Energy Studies in Buildings Laboratory, and Baker Lighting Lab) hosted a mini-conference in Portland in May; the Health and Energy Consortium 2018.  I presented some results on how some home factors affect the bacteria community found indoors, as well as brainstormed research ideas with industry professionals and researchers.

At the end of the spring term, I also presented at the University of Oregon IDEAL Framework Showcase.  Over the 2017/2018 academic year I served on the Implicit Bias working group, tasked with assessing the need for campus-wide training and making recommendations to the college.

In June, I attended the HOMEChem Open House at the UT Austin Test House, University of Texas at Austin’s J.J. Pickle Research Campus.  I got to tour the amazing indoor chemistry labs there, and met with BioBE collaborators to discuss pilot projects exploring the link between indoor chemistry and indoor microbiology.

In July, I had a double header of back-to-back conferences, both of which I was attending for the first time.  The first was Microbiology of Built Environment 2018 Gordon Research Conference in Biddeford, ME, followed by Indoor Air 2018 in Philadelphia, PA.

MoBE 2018 was an intensive meeting that brought together the top names and the rising stars of MoBE research.  Gordon conferences are closed-session to encourage the presentation of unpublished data and ideas, and to facilitate discussion and theoretical contemplation.  While in Biddeford, I had the opportunity to eat seafood, visit friends, and check out Mug Buddy Cookies!! 

Immediately after MoBE, I flew to Philadelphia for the Indoor Air 2018 conference.  I again presented some of the work I’ve been part of, exploring the effect of weatherization and lifestyle on bacteria indoors. I also found some incredible shoes.

Then, in August I went to Leipzig, Germany for the 17th International Society for Microbial Ecology (ISME17).  Here as well, I presented some of the work I’ve been part of, and had the chance to revisit a city I haven’t been to in 5 years – since the last microbial ecology conference held here.

Outreach

I spent a great deal of 2018 participating in activities for 500 Women Scientists. I am a Pod Coordinator for the Eugene Pod, and as such I meet regularly with other Coordinators to plan events. The majority of our 2018 events were Science Salons: science talks by local female researchers around a particular theme, with a hands-on activity to match, and a Q&A session about life as a (female) scientist. We heard about some awesome research, raised $1300 for local science non-profits, and learned how to be better community members by sharing personal stories about the triumphs and troughs of being a woman in science.

We also hosted a film screening of My Love Affair with the Brain, generously lent to 500WS by Luna Productions, followed by a panel discussion of women neuroscientists here in Eugene.

Along with two other Eugene Pod Coordinators, I wrote a small proposal which was funded, to coordinate workshops at UO: “Amplifying diverse voices: training and support for managing identity-based harassment in science communication”. Those workshops will take place in 2019.


This year, I acted as a judge for several robotics competitions and STEM design projects for local schools, I even dressed up as a giant spider to throw corn starch at campers. You know, for the kids.

I again participated in citizen science through Adventure Scientists, as part of their wood crews for the Timber Tracking 2018 campaign. Lee and I drove around a 20,000 sq mi section of southwestern Oregon to collect samples from big leaf maple trees at 10 locations which adhered to certain sampling parameters. Despite the large number of big leafs in Oregon, the sampling criteria made it difficult to find the perfect tree in an entire forest, and we logged a lot of mileage. Lee and I also volunteered for their Gallatin County Microplastics Initiative while we lived in Bozeman, MT.

Blog

I published 30 posts this year! The most popular post this year continues to be Work-Life Balance: What Do Professors Do?, self explanatory, and the least popular this year is Show Me the (Grant) Money, detailing the grant proposal writing process. Although, I was significantly less wordy this year as compared to other years.

As of today, my site received 4,447 view from 97 countries and 3,101 visitors in 2018. So far, I’ve published 109 posts, and received 6,147 visitors who viewed the site 9,481 times.

Life

It’s easy to forget how many life events go by in a year, unless your social media is making you a video about them. But they were all important parts of my life and had some impact, however negligible, on my work. The one I’m most proud of was officiating the wedding of two dear friends, in Vermont.


I marched (seriously and facetiously) for science.

Lee and I picked up trash at the beach, using a sieve he built to pick up trash.

I tried to spend more time on creative projects, including getting back into art after more-or-less tabling it for several years.

Looking Ahead

As usual, 2019 promises an abundance of opportunities. Already, I am planning out my conference schedule, seeking speakers for upcoming 500WS Science Salons, and writing, writing, writing. But through all of it, I will be trying to cultivate a more open, inclusive, and supportive work environment. In 2018, after more than a decade of trying to convince doctors that I should have agency over my own organs, I was finally approved for the hysterectomy that I’d wanted for so long, and the medical diagnostics to show that I’d actually needed it for probably just as long.

The surgery has dramatically improved my quality of life, and the scars are a constant reminder that you never know who is dealing with something in their life that isn’t visible to you, who is trying to pretend they aren’t in pain because they can’t afford to take time off to resolve their situation. At first, I kept the details to myself and I kept it off my professional social media. I did share, in exquisite detail, on my personal social media, and was flooded with similar stories from other women. It encouraged me to share a little more, after all, if I’d had surgery on a knee or a kidney I would talk about it openly, why not a uterus?

In a typical semester, one to two-thirds of the students that I teach or mentor will disclose that they experienced a serious life event, most often while at school. They may casually joke about how they couldn’t get time off or almost failed out that semester, or recall how receiving help saved them. I take my role as an educator, mentor, or supervisor seriously – the competition in academia forces students to work long or odd hours, to prioritize other things over study, to accept positions of low or no pay “for the experience”, or to accept professional relationships where they are not respected or may be taken advantage of. I have always tried to be a supportive mentor to students, but the higher up the ladder I climb the more important it is for me to set a good example for these students who will one day mentor people of their own.

In addition to listening to them, and having frank conversations, my response this year has been to get rid of student employee deadlines whenever possible. We are asked to do so much with our time in school, or in academia, but there are so many hours in the day. Sure, I routinely wish things were accomplished more promptly, but I have never once regretted not causing someone to have a breakdown. And constantly telling my students to take care of themselves first and work second reminds me to do the same, it benefits my work , and it’s made a certain furball very happy. Happy New Year!

Introduction to Mammalian Microbiomes

Since the end of September, I’ve been teaching a course for the UO Clark Honors College; Introduction to Mammalian Microbiomes.   And in a novel challenge for me – I’m teaching the idea of complex, dynamic microbial ecosystems and their interaction with animal hosts … to non-majors.  My undergraduate students almost entirely hail from the humanities and liberal arts, and I couldn’t be more pleased. So far, it’s been a wonderful opportunity for me to pilot a newly developed course, improve my teaching skills, and flex my creativity, both in how I explain concepts and how I design course objectives.

I enthusiastically support efforts towards science communication, especially in making science more accessible to a wider audience.  My students likely won’t be scientific researchers themselves, but some will be reporting on science publications, or considering funding bills, and all of them are exposed to information about human-associated microbial communities from a variety of sources. To navigate the complicated and occasionally conflicting deluge of information online about the human microbiome, my students will need to build skills in scientific article reading comprehension, critical thinking, and discussion.  To that end, many of my assignments are designed to engage students in these skills.

I feel that it’s important to teach not only what we know about the microbial community living in the mouth or the skin, but to teach the technologies that provide that knowledge, and how that technology has informed our working theories and understanding of microbiology over centuries.  Importantly, I hope to teach them that science, and health sciences, are not static fields, we are learning new things every day.  I don’t just teach about what science has done right, but I try to put our accomplishments in the context of the number of years and personnel to achieve publications, or the counter-theories that were posited and disproved along the way.

And most of, I want the course to be engaging, interesting, and thought provoking.  I encouraged class discussions and student questions as they puzzle through complex theories, and I’ve included a few surprise additions to the syllabus along the way.  Yesterday, University of Oregon physics Ph.D. student Deepika Sundarraman taught us about her research in Dr. Parthasarathy’s lab on using light sheet fluorescence microscopy to visualize bacterial communities in the digestive tract of larval zebra fish! Stay tuned for more fun in #IntroMammalianMicrobiomes!

 

(Reblog) A perspective on tackling contamination in microbial ecology

Original posting from BioBE.

To study DNA or RNA, there are a number of “wet-lab” (laboratory) and “dry-lab” (analysis) steps which are required to access the genetic code from inside cells, polish it to a high-sheen such that the delicate technology we rely on can use it, and then make sense of it all.  Destructive enzymes must be removed, one strand of DNA must be turned into millions of strands so that collectively they create a measurable signal for sequencing, and contamination must be removed.  Yet, what constitutes contamination, and when or how to deal with it, remains an actively debated topic in science. Major contamination sources include human handlers, non-sterile laboratory materials, other samples during processing, and artificial generation due to technological quirks.

Contamination from human handlers

This one is easiest to understand; we constantly shed microorganisms and our own cells and these aerosolized cells may fall into samples during collection or processing.  This might be of minimal concern working with feces, where the sheer number of microbial cells in a single teaspoon swamp the number that you might have shed into it, or it may be of vital concern when investigating house dust which not only has comparatively few cells and little diversity, but is also expected to have a large amount of human-associated microorganisms present.  To combat this, researchers wear personal protective equipment (PPE) which protects you from your samples and your samples from you, and work in biosafety cabinets which use laminar air flow to prevent your microbial cloud from floating onto your workstation and samples.

Fun fact, many photos in laboratories are staged, including this one, of me as a grad student.  I’m just pretending to work.  Reflective surfaces, lighting, cramped spaces, busy scenes, and difficulty in positioning oneself makes “action shots” difficult.  That’s why many lab photos are staged, and often lack PPE.

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Photo Credit: Kristina Drobny

Contamination from laboratory materials

Microbiology or molecular biology laboratory materials are sterilized before and between uses, perhaps using chemicals (ex. 70% ethanol), an ultraviolet lamp, or autoclaving which combines heat and pressure to destroy, and which can be used to sterilize liquids, biological material, clothing, metal, some plastics, etc.  However, microorganisms can be tough – really tough, and can sometimes survive the harsh cleaning protocols we use.  Or, their DNA can survive, and get picked up by sequencing techniques that don’t discriminate between live and dead cellular DNA.

In addition to careful adherence to protocols, some of this biologically-sourced contamination can be handled in analysis.  A survey of human cell RNA sequence libraries found widespread contamination by bacterial RNA, which was attributed to environmental contamination.  The paper includes an interesting discussion on how to correct this bioinformatically, as well as a perspective on contamination.  Likewise, you can simply remove sequences belonging to certain taxa during quality control steps in sequence processing. There are a number of hardy bacteria that have been commonly found in laboratory reagents and are considered contaminants, the trouble is that many of these are also found in the environment, and in certain cases may be real community members.  Should one throw the Bradyrhizobium out with the laboratory water bath?

Chimeras

Like the mythical creatures these are named for, sequence chimeras are DNA (or cDNA) strands which are accidentally created when two other DNA strands merged.  Chimeric sequences can be made up of more than two DNA strand parents, but the probability of that is much lower.  Chimeras occur during PCR, which takes one strand of genetic code and makes thousands to millions of copies, and a process used in nearly all sequencing workflows at some point.  If there is an uneven voltage supplied to the machine, the amplification process can hiccup, producing partial DNA strands which can concatenate and produce a new strand, which might be confused for a new species.  These can be removed during analysis by comparing the first and second half of each of your sequences to a reference database of sequences.  If each half matches to a different “parent”, it is deemed chimeric and removed.

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Chimeric DNA

Cross – sample contamination

During DNA or RNA extraction, genetic code can be flicked from one sample to another during any number of wash or shaking steps, or if droplets are flicked from fast moving pipettes.  This can be mitigated by properly sealing all sample containers or plates, moving slowly and carefully controlling your technique, or using precision robots which have been programmed with exacting detail — down to the curvature of the tube used, the amount and viscosity of the liquid, and how fast you want to pipette to move, so that the computer can calculate the pressure needed to perform each task.  Sequencing machines are extremely expensive, and many labs are moving towards shared facilities or third-party service providers, both of which may use proprietary protocols.  This makes it more difficult to track possible contamination, as was the case in a recent study using RNA; the researchers found that much of the sample-sample contamination occurred at the facility or in shipping, and that this negatively affected their ability to properly analyze trends in the data.

Sample-sample contamination during sequencing

Controlling sample-sample contamination during sequencing, however, is much more difficult to control. Each sequencing technology was designed with a different research goal in mind, for example, some generate an immense amount of short reads to get high resolution on specific areas, while others aim to get the longest continuous piece of DNA sequenced as possible before the reaction fails or become unreliable.  they each come with their own quirks and potential for quality control failures.

Due to the high cost of sequencing, and the practicality that most microbiome studies don’t require more than 10,000 reads per sample, it is very common to pool samples during a run.  During wet-lab processing to prepare your biological samples into a “sequencing library”, a unique piece of artificial “DNA” called a barcode, tag, or index, is added to all the pieces of genetic code in a single sample (in reality, this is not DNA but a single strand of nucleotides without any of DNA’s bells and whistles).  Each of your samples gets a different barcode, and then all your samples can be mixed together in a “pool”.  After sequencing the pool, your computer program can sort the sequences back into their respective samples using those barcodes.

While this technique has made sequencing significantly cheaper, it adds other complications.  For example, Illumina MiSeq machines generate a certain number of sequence reads (about 200 million right now) which are divided up among the samples in that run (like a pie).   The samples are added to a sequencing plate or flow cell (for things like Illumina MiSeq).  The flow cells have multiple lanes where samples can be added; if you add a smaller number of samples to each lane, the machine will generate more sequences per sample, and if you add a larger number of samples, each one has fewer sequences at the end of the run. you have contamination.  One drawback to this is that positive controls always sequence really well, much better than your low-biomass biological samples, which can mean that your samples do not generate many sequences during a run or means that tag switching is encouraged from your high-biomass samples to your low-biomass samples.

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Illumina GAIIx for high-throughput sequencing.

Cross-contamination can happen on a flow cell when the sample pool wasn’t thoroughly cleaned of adapters or primers, and there are great explanations of this here and here.  To generate many copies of genetic code from a single strand, you mimic DNA replication in the lab by providing all the basic ingredients (process described here).   To do that, you need to add a primer (just like with painting) which can attach to your sample DNA at a specific site and act as scaffolding for your enzyme to attach to the sample DNA and start adding bases to form a complimentary strand.  Adapters are just primers with barcodes and the sequencing primer already attached.   Primers and adapters are small strands, roughly 10 to 50 nucleotides long, and are much shorter than your DNA of interest, which is generally 100 to 1000 nucleotides long.  There are a number of methods to remove them, but if they hang around and make it to the sequencing run, they can be incorporated incorrectly and make it seem like a sequence belongs to a different sample.

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DNA Purification

 

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Barcode swapping

This may sound easy to fix, but sequencing library preparation already goes through a lot of stringent cleaning procedures to remove everything but the DNA (or RNA) strands you want to work with.  It’s so stringent, that the problem of barcode swapping, also known as tag switching or index hopping, was not immediately apparent.  Even when it is noted, it typically affects a small number of the total sequences.  This may not be an issue, if you are working with rumen samples and are only interested in sequences which represent >1% of your total abundance.  But it can really be an issue in low biomass samples, such as air or dust, particularly in hospitals or clean rooms.  If you were trying to determine whether healthy adults were carrying but not infected by the pathogen C. difficile in their GI tract, you would be very interested in the presence of even one C. difficile sequence and would want to be extremely sure of which sample it came from.  Tag switching can be made worse by combining samples from very different sample types or genetic code targets on the same run.

There are a number of articles proposing methods of dealing with tag switching using double tags to reduce confusion or other primer design techniques, computational correction or variance stabilization of the sequence data, identification and removal of contaminant sequences, or utilizing synthetic mock controls.  Mock controls are microbial communities which have been created in the lab by mixed a few dozen microbial cultures together, and are used as a positive control to ensure your procedures are working.  because you are adding the cells to the sample yourself, you can control the relative concentrations of each species which can act as a standard to estimate the number of cells that might be in your biological samples.  Synthetic mock controls don’t use real organisms, they instead use synthetically created DNA to act as artificial “organisms”. If you find these in a biological sample, you know you have contamination.  One drawback to this is that positive controls always sequence really well, much better than your low-biomass biological samples, which can mean that your samples do not generate many sequences during a run or means that tag switching is encouraged from your high-biomass samples to your low-biomass samples.

Incorrect base calls

Cross-contamination during sequencing can also be a solely bioinformatic problem – since many of the barcodes are only a few nucleotides (10 or 12 being the most commonly used), if the computer misinterprets the bases it thinks was just added, it can interpret the barcode as being a different one and attribute that sequence to being from a different sample than it was.  This may not be a problem if there aren’t many incorrect sequences generated and it falls below the threshold of what is “important because it is abundant”, but again, it can be a problem if you are looking for the presence of perhaps just a few hundred cells.

Implications

When researching environments that have very low biomass, such as air, dust, and hospital or cleanroom surfaces, there are very few microbial cells to begin with.  Adding even a few dozen or several hundred cells can make a dramatic impactinto what that microbial community looks like, and can confound findings.

Collectively, contamination issues can lead to batch effects, where all the samples that were processed together have similar contamination.  This can be confused with an actual treatment effect if you aren’t careful in how you process your samples.  For example, if all your samples from timepoint 1 were extracted, amplified, and sequenced together, and all your samples from timepoint 2 were extracted, amplified, and sequenced together later, you might find that timepoint 1 and 2 have significantly different bacterial communities.  If this was because a large number of low-abundance species were responsible for that change, you wouldn’t really know if that was because the community had changed subtly or if it was because of the collective effect of low-level contamination.

Stay tuned for a piece on batch effects in sequencing!