Catalyzing Advocacy for Science and Engineering: Learning about science policy and how to be an effective advocate

By Amanda Koch, Ph.D. Candidate

Department of Biochemistry and Molecular Biology, Colorado State University

 

First, I would like to introduce myself. My name is Amanda Koch. I am a graduate student pursuing my Ph.D. in Biochemistry and Molecular Biology at Colorado State University. I work in Dr. Tim Stasevich’s lab where I study a particular mechanism that viruses use to steal away host machinery to make viral particles, ultimately causing cell death and systemic infection. Our lab has this awesome, home-made microscope that allows us to see this process happening in real time, within living cells, and at a single molecule level (see video below), all of which are revolutionary to the field. I am super excited about science and my research, but, I am also curious as to what else a scientist can do besides bench work and analysis.

I quickly realized that I enjoyed communicating my science to other people. At times, I felt my enthusiasm for my research transferring to others which were extremely rewarding. Because I enjoyed science communication, I wanted to be a better communicator and I wanted to use my skill to advocate for research and for scientists! Around the same time, I became interested in science policy and politics leading to my drive to begin a science policy organization at CSU, Science in Action.

A few months ago, I caught word about a science policy and communication workshop called Catalyzing Advocacy for Science and Engineering hosted by the AAAS in Washington, D.C. The whole idea of the workshop is to teach students how to communicate science in a simple but effective way and to use that skill to advocate for science research funding to policy-makers.

image.png

To effectively ask for funding for science, we needed to first understand how the federal budget is formulated, how funds are appropriated, and what agencies receive the funds. The first day we learned from experts about the federal budget process, the structure and law-making processes of Congress, and how science policy is made. With all this information and understanding, it was easier to formulate a conversation with policymakers about research and science funding.

The second day focused on job opportunities in the science policy realm, how congressional offices and committees operate, and importantly how to effectively communicate to policymakers. The panels of experts that spoke to us about jobs in science policy were extremely insightful and opened my eyes to the wide range of opportunities that exist within science policy realm.  Many of the speakers that worked for congresspeople or on committees received fellowships through the AAAS after completion of a Ph.D. They all said that the fellowship was a wonderful way to get experience working for a congressperson and begin building a network.

Finally, we put all of what we learned to the test in meetings with our state’s congresspeople and their staff at the Capitol. We familiarized ourselves with different legislations that affect science or education and used that knowledge as talking points to begin a conversation with our congresspeople. The main idea of these meetings is to make your point as quick and concise as possible because congresspeople and their employees do not have much time allocated for each individual meeting. WHY your science is important is the most critical talking point in these meetings. Having anecdotes pertaining to the influence of your research to the state you live in or the US, in general, is also invaluable.

Polis.jpg

Colorado graduate students meet with Congressman Jared Polis

A few fellow graduate students from CU Boulder and I met with staffers with science and education portfolios from Senator Bennet, Senator Gardner, and Congressman Polis’s offices at the Capitol. We were also lucky enough to catch Congressman Polis as he was going to lunch and have a brief conversation with him. In these meetings, we talked in simple terms about our research first. We thanked Senator Bennet, Gardner, and Congressman Polis for their consistent support of science funding and urged them to continue to do so in the upcoming voting events. We then focused on how federal funding is absolutely necessary for our work and livelihood. It was also important to emphasize how science and innovation increase the quality of life by strengthening the economy and by improving healthcare technology in the state of Colorado.

In these discussions and throughout the workshop, I learned the essential tools of communicating in a concise manner about my work and science policy to politicians. I hope to now take all that I have learned at the CASE workshop to Colorado State University and teach my fellow scientists how to effectively advocate for science.

image copy

It is challenging to talk about complicated scientific topics to non-scientists, but it is important that we work hard to make what we do accessible to the public and to policy-makers. Ultimately, they are the ones paying our bills!

Using mosquitoes for good- How blood sucking insects can assist in disease surveillance

By Joseph Fauver, Postdoctoral researcher, Washington University in St. Louis, Missouri

Follow Dr. Fauver on twitter @josephfauver

The study of vector-borne disease (VBD) is broad, and necessarily so.  Zika virus, malaria, Lyme disease, elephantiasis, all of these recognizable ailments have one thing in common, they are transmitted to humans by the bite of an infectious arthropod. The outcomes of these diseases are wide ranging, from hemorrhagic fever and potential death, to a benign infection, to a debilitating and stigmatizing disease. The pathogens that cause these conditions cover all major taxa of microbes; bacteria, protozoan and eukaryotic parasites, and viruses. Fortunately for humankind, prions, or potentially infectious proteins, have not been demonstrated to be transmissible by hematophagous (“blood eating”) arthropods. The vectors themselves, all animals in the massively diverse phylum Arthropoda, include individuals as large as quarters and as small as a pinhead. Expectedly, the professionals in VBDs are just as diverse as the biological systems they are working on. This includes a long list of “-ologists” and often individuals working on these complex disease systems wear multiple hats. However, they are all brought together at the intersection of “bugs” and the “bugs” they transmit unified by a common goal; controlling, treating, and potentially eliminating some of the world’s deadliest foes. This variety of expertise often results in unique and innovative ways to accomplish these goals.

I was initially attracted to this field because it offered a route that appeared to be relatively distinctive in the larger discipline of biomedical science. Vector biology allowed me to combine a child-like curiosity about insects and biodiversity with the opportunity to work on some of the world’s most neglected diseases. Fortunately, this variety was reflected in my Ph.D. work at Colorado State University (CSU). I worked on multiple disease systems in the countries where they occur all under a unifying theme, the idea that hematophagous insects, specifically mosquitoes, can be tools that we could take advantage of.

Surveillance of VBDs is routine and a vital aspect of most control programs. Many mosquito abatement districts throughout the country will regularly collect large numbers of these insects and test them for the presence of arboviruses (Arthropod-Borne Virus). This information can give us an idea about the size of mosquito populations, how many of them may be infected with the virus, and what those measures mean for human risk. This information is crucial to making decisions about control efforts. In a sense, we are using mosquitoes here as a tool to tell us about the intensity of transmission and potential risk to humans. Their biology lends itself to this practice. Mosquito populations can exist in immense numbers, trapping them is relatively simple and inexpensive, and because they are responsible for maintaining transmission cycles, we will be able to detect the virus if it is there.

Anopheles

Anopheles mosquito taking a blood-meal. Photo from Wikipedia.

A few years ago, a group at CSU took the idea of using mosquitoes in disease surveillance a step further. Drs. Doug Brackney, Greg Ebel, and Brian Foy asked the question: Could we use blood from mosquitoes to perform surveillance on a larger scale and survey for more than just VBDs? This is an interesting question, and one that has been posed before. The rationale behind it is simple; mosquitoes are nature’s best blood collectors. In most species, the female must take a blood-meal to develop a clutch of eggs and perpetuate their life cycle. While host preferences of these mosquitoes vary, many species are anthropophilic (“human loving”). The question became can we capture mosquitoes that have likely taken their blood-meal from a human and using a variety of molecular techniques, can we detect genetic signatures of pathogens in that blood-meal? Our culprit became Anopheles gambiae, the main vector of malaria in sub-Saharan Africa. This mosquito, more specifically the parasite it transmits, is responsible for an almost incomprehensible amount of morbidity and mortality. As you could imagine, this species takes most of its blood-meals from humans and is relatively easy to capture because they prefer to rest indoors on walls after they have fed.   

After some initial laboratory testing regarding the stability of pathogen nucleic acid in a mosquito midgut, former CSU graduate students (now doctors) Nathan Grubaugh and Ben Krajacich travelled to Lofa County, Liberia and brought the project to the field. With the help of collaborators at the Liberian Institute of Biomedical Research (LIBR) they mastered the technique of using Insectazookas, essentially PVC pipes with cups on the ends of them acting like a vacuum, to collect large numbers of blood-fed mosquitoes from the inside of people’s homes. They had also developed a technique to carefully dissect off the mosquito abdomen and coax the fresh blood out of the abdomen and on to filter paper cards for preservation. This low-tech way of collecting human blood samples proved successful, as they were able to identify Epstein-Barr virus using Next Generation Sequencing (NGS) from these mosquito blood spots. Thus Xenosurveillance, the coined term for this technique, was born and resulted in the inaugural publication.

Insectazookas

Ben Krajacich and Lawrence Fakoli using Insectazookas to collect blood-fed mosquitoes resting inside a home in Liberia.

The question remained whether blood collected by mosquitoes would reveal similar genetic signatures of pathogens to blood collected from humans that did not go through a mosquito midgut (i.e. finger stick blood blotted directly onto filter paper). To this end, former Ebel Laboratory post-doc James Weger and myself found ourselves back in northern Liberia conducting Xenosurveillance with the help of Kpehe, Lawrence, and Andrew from LIBR. We faced a few unique challenges, largely due to our timing. We arrived in the summer of 2015, just on the tail-end of the Ebola virus outbreak in West Africa. The signs of this epidemic were all around, sticking out against the African landscape.

EbolaIsReal

Container of chlorine solution used for hand washing that reads “EBOLA IS REAL”. These vats were found at checkpoints along roadsides and outside of many buildings and homes.

Participation in the study was better than we had expected, almost every household in both villages enrolled. After obtaining consent, we collected finger stick blood from all members staying in the household and visited each house every other day for two weeks with our Insectazookas to collect mosquitoes.

BlueResearchTruck

Nathan Grubaugh, Ben Krajacich and Lawrence Fakoli by the infamous Blue Research Truck in Liberia.

Most mornings following mosquito collections, we spent time at the Foya-Burma Hospital collecting more bloodspots while assisting with malaria diagnostics. This area was hit particularly hard a year prior during the outbreak, and the hospital staff was laboring to return to their normal affairs. Witnessing the resilience and doggedness of the citizens and healthcare workers to recover following the epidemic was nothing short of inspiring.

Hospital

The Foya-Burma hospital in Lofa County, Liberia. The hospital treated the first Ebola virus cases in Liberia during the 2014-2016 outbreak in West Africa.

With samples collected, we returned stateside, which was an ordeal in its own right (think quarantine at the airport and daily check ins with the CDC). We decided to use NGS to determine if pathogen nucleic acids were present in our samples. Thanks to the brainchild of Dr. Weger, we developed an in-house method that removed excessive and uninformative nucleic acid from all our samples, which increased the pathogen signal in the host noise. We were able to identify RNA and DNA genetic signatures of human viruses, specifically GB virus C and Hepatitis B virus, in our NGS datasets from both Xenosurveillance samples and human finger stick samples. We were able to confirm the presence of viral nucleic acid from both Xenosurveillance and human samples using basic PCR and sanger sequencing. Phylogenetic analysis of the longest contiguous sequences produced from the NGS data placed both viruses in clades made up of other virus genomes from West Africa, indicating that these sequences were very likely derived from individuals in Liberia.

PhylogeneticTree

Phylogenetic trees showing the placement (red lines) of GB virus C (Left) and Hepatitis B virus (Right) contigs derived from Xenosurveillance and human samples, indicating their placement in clades made up of strains from West Africa.

Due to the sample collection method, we were able to estimate a prevalence for these viruses that is in line with previously reported data. Following our analysis, we felt confident in our conclusion that Xenosurveillance is a viable option to complement existing disease surveillance strategies (paper here).

ResearchTeam

The mosquito collection team made up of James Weger, Andrew, Edwin, Kpehe Bolay, Bendu and Joseph Fauver in a village in Liberia during the summer of 2015.

Our idea was to develop a simple, less-intrusive way of collecting samples in areas of the world that have little to no infrastructure for this type of passive surveillance. There are still kinks that need to be worked out, for example, the fact we had to send samples back to our laboratory at CSU in order to process them. As well, NGS is resource intensive and requires expertise in both molecular and computational biology. These are not insurmountable hurdles, however, as the ability to acquire large amounts of sequencing data in field conditions is no longer a dream due to platforms like the Oxford Nanopore Minion. As our technological abilities continue to expand and become more democratic, it will be exciting to see how they will be used to combat disease and poverty throughout the developing world.

Xenosurveillance is the result of folks from a variety of backgrounds and countries trying to fill in a blatant gap in infectious disease surveillance using the tool that we know best: the mosquito. In a world more perfect than ours, mosquitoes could not or would not bite humans and transmit these pathogens, but until that day comes, we can find a bit of a silver lining and use these blood-feeding insects as a tool to complement disease surveillance systems and ultimately increase our understanding of the pathogens we carry.

 

Tipping the scales: diverse women in science advance our understanding of disease from molecules to individuals

By Adrienne Williams, Ruchi Malik, Sumi Sato & Stephanie Moon

        We met at a scientist development & science communication workshop hosted by The Jackson Laboratory.  During a discussion session at the workshop, we formed a group and learned about the similarities and differences of our backgrounds. We realized that we are all women researchers in biomedical science and engineering of culturally diverse backgrounds, with the common goal of discovering how diseases work and new ways to diagnose or treat them. However, we were surprised to find that we all approach the study of disease in very different ways, by focusing on different scales of biomedical research.

What are biomedical science and engineering fields, and what are the scales of biomedical research?

        In biomedical sciences and engineering, we study biological systems, therapies and disease processes.  Research in the biomedical sciences and biomedical engineering spans many scales, both in time and space.  Spatially, biology can be studied at the subcellular (molecular biology, >10-6 m), cellular (cell biology, 10-6 m < cell < 10-3 m), tissue (~ 10-2 m), organ or system/whole body (10-2 m < organ < 101 m) scales.  The scale of the research must match the the biological system or disease being studied.  

        We all study diseases of the human body, but at different scales.  Stephanie studies aspects of the brain in Down’s syndrome, at the molecular/cellular scale.  Ruchi studies aspects of pancreatic cancer, at the cellular/tissue scale.  Adrienne’s research on Duchenne muscular dystrophy is focused on the organ/whole body scale.  At the whole body scale, Sumi studies how the brain adapts to different walking environments.  She hopes to apply her findings to help stroke patients. We hope that our research will eventually lead to new ways of diagnosing and treating diseases.

What educational background do women in biomedical research need?  

        We have been educated at both small colleges and large universities, within and outside of the United States.  In our discussions, we found that our individual differences made us stronger as a group, because we each had unique contributions to make to our discussions at the workshop.  Our various educational, research and cultural backgrounds and experiences made our group discussions more interesting and inspired us to share our stories with you!  We hope that we show you how many interesting areas of research there are in the field of biomedical science and engineering and that there is no single path to becoming a biomedical researcher.  Check out our stories below!

What kinds of research do women biomedical scientists/engineers do?

 

Molecular Biology: Stephanie MoonStephanie

 

  • Research scale: Molecular/cellular
  • Area of research: RNA regulation in neurodevelopmental disorders
  • Where I am at in my career in becoming a scientist: Postdoctoral Fellow at University of Colorado, Boulder

Stephanie’s path to becoming a scientist:

        I grew up in a small mountain town in rural Colorado. A big reason for why I ended up going into science as a career was that I spent a lot of time at the Keystone Science School, where my dad worked as a cook for many years. I went to a small liberal arts college, Fort Lewis College, in Durango, Colorado and ended up majoring in both Biology and Chemistry. I was able to work in research labs there in the Chemistry and Biology departments, and decided I wanted to go to graduate school to study how diseases work. I was accepted to go to Colorado State University, where I worked in Jeffrey Wilusz’s lab and studied how viruses like Dengue virus and West Nile virus affect the cell to cause disease. My Ph.D. dissertation work uncovered a new way that these viruses interfere with normal cell processes to potentially cause disease. You can read about this research and related research in an open-access review article here. After graduating, I decided to work as a post-doc (a temporary research position where you join another lab to learn new skills and gain experience) and am now working in Dr. Roy Parker’s lab at University of Colorado, Boulder.

About Stephanie’s research:

        I study how certain changes in our DNA can lead to brain diseases. In the lab I do experiments using cells (the smallest living building blocks of our bodies) isolated from patients with Down Syndrome or other genetic disorders. Scientists have devised different methods to immortalize cells taken from blood or skin, and we can freeze and recover these cells, so we are able to work with cells isolated from one patient for a long time. Using a pure culture of these immortalized human cells in the lab, I am able to test many different conditions in controlled environments to see how the cells from a patient with a genetic disorder differ from cells from an unaffected person. I am working on figuring out how a common genetic disorder called Down Syndrome leads to problems with certain areas of the brain. The experiments I am doing may eventually help us learn why Down Syndrome and other genetic disorders impact specific areas of the brain, and could lead to new treatment options.

Bioengineering: Ruchi Malik

Ruchi

 

 

  • Research scale: Tissue
  • Area of research: Cell-ECM interactions in pancreatic cancer
  • Where I am at in my career in becoming a scientist: Postdoctoral
    Associate in Bioengineering/Cancer Biology at the Fox Chase Cancer Center/Temple University

Ruchi’s path to becoming a scientist:

        I hold a B.S. degree in Pharmacy from India and Ph.D. degrees in Pharmaceutical Sciences from North Dakota State University, Fargo. After receiving my PhD, I took on an interdisciplinary postdoctoral position in in Bioengineering/Cancer Biology in August 2013 where I am studying cell-ECM interactions in pancreatic cancer under the mentorship of Edna Cukierman, PhD at Fox Chase Cancer Center and my co-mentor Peter I Lelkes, PhD at Temple University in Philadelphia, Pennsylvania. My research interests include 3D cell culture, cell-ECM interactions, biomaterials for diagnostic/therapeutics, tumor microenvironment and microscopy.

        I have always been interested in finding solutions by leveraging integrated healthcare technologies and combining interdisciplinary approaches. Cancer is a very complex disease and difficult to treat; therefore it is crucial to design to new ways and for designing effective treatment. In my PhD, I was working with peptide based nanofibers, and using them as a diagnostic/drug delivery tool in cancer. This got me interested in how biomaterials have the potential to be used as technology for creating bioengineered materials for diverse purposes. In my current role, I am using bioengineered 3D stromal systems for studying pancreatic cancer.

About Ruchi’s research:

        Pancreatic cancer is extremely deadly where 95% of patients with pancreatic cancer die within 5 years of diagnosis. The incidence of pancreatic is rapidly growing and is on the rise to become the second leading cause for cancer deaths in the U.S by 2020. The extracellular matrix (ECM) of pancreatic cancer iis characterized by an extremely stiff and aligned architecture, which is caused by excessive deposition of variety of ECM proteins. These altered mechanical features of ECM are known to have major influences on tumor progression, yet not fully understood. I became interested in identifying how global ECM changes impact pancreatic cancer progression. By combining cell-derived ECMs with tunable hydrogels, I developed 3D stromal ECM model that closely mimics the actual microenvironment in which cancer cells reside. My ultimate aim is to as a natural in vitro 3D system to study cell-ECM crosstalk and cell-cell cross-talk in a more accurate way which will help in the identification of novel stromal and cancer related future clinical targets.

Biomechanics: Adrienne Williams

Adrienne

 

  • Research scale: Organ
  • Area of research: Computational modelling of lower limb muscles and tendons –  Duchenne Muscular dystrophy
  • Where I am at in my career in becoming a scientist: PhD student in Biomedical Engineering, University of Virginia

Adrienne’s path to becoming a scientist:

        Adrienne is from Kingston, Jamaica. She did her undergraduate studies at the University of the West Indies, Jamaica in Medical Physics with a double minor in Alternative Energy and Spanish. She then completed her M.S. in Bioengineering and performed research in the NSF ERC for Revolutionizing Metallic Biomaterials at North Carolina A&T State University. Her current research in the M3 lab at UVA has been to develop a model that determines which regions in the lower limb muscles of DMD patients are most susceptible to damage caused by lengthening contractions. Adrienne enjoys watching funny videos on social media, TV shows and movies with her husband and playing soccer.

About Adrienne’s research:

        Duchenne Muscular Dystrophy (DMD) is a fatal genetic disease.  Patients with DMD experience progressive muscle damage as a result of a lack of dystrophin – a protein that connects the inside of muscle fiber cells to their cell membranes.  Because this important protein is missing, dystrophic muscles are more susceptible to damage from muscle contractions than healthy muscles.  There is a limited understanding of how muscle contractions from daily activities like walking influence the progression of muscle damage in DMD, especially in the lower limbs.  It is important to understand why lower limb muscles are damaged more quickly than other muscles of the body, as they are essential for walking.  Understanding patterns of muscle damage is crucial to the improvement of DMD patient care and wellbeing.  Our goal is to develop  computer models of patients’ muscles from magnetic resonance images (MRIs).  The MRIs allow us to get the specific shapes of the muscles and to determine the amount of damage present in the muscles.  We will use the models to match the damage we quantify from the MRI with the contractions experienced during walking.  The walking movements that cause these contractions are recorded as patients walk on a treadmill.  Once we determine the relationship between movement and muscle degeneration, we may be able to predict the impact of movement on the progression of muscle damage in DMD.

Motor control: Sumi Sato

Sumi

  • Research scale: System/whole body
  • Area of research: Motor control and motor learning
  • Where I am at in my career in becoming a scientist: Completed a clinical doctorate degree in physical therapy, currently a PhD student, Neuroscience and Behavior Graduate Program, University of Massachusetts, Amherst

Sumi’s path to becoming a scientist:

        I was born in Vancouver, Canada, but grew up in Tokyo, Japan. I decided to venture out to the US for my undergraduate degree and went to Boston University, where I majored in Human Physiology. I got interested in wellness and clinical science, and went to get a doctorate in physical therapy at Emory University School of Medicine. When I was completing my clinical rotations as a physical therapy student, I was most interested in working with the neuro-rehab population and especially the stroke patient population; it was the most rewarding thing to be next to patients as I assisted them to walk for the first time after their neurological injury. I wanted to know more about the research that grounded some of the therapeutic options for the patients and was blessed by the opportunity to work in a research lab at Emory. From then I just fell in love working in research and decided to pursue a PhD after the completion of my clinical doctorate. I am currently starting my second year at the University of Massachusetts studying neural mechanisms underlying walking adaptation under Dr. Julia Choi. I never thought my little venture out into the US will lead me to stay so long, but I love what I do!

About Sumi’s research:

        I am currently studying the neural changes that occur when our body is adapting to new walking environments. I am studying this because in rehabilitation, we introduce a lot of movements that are “new” (e.g. challenging walking tasks to help you to eventually walk better and safer) and to make therapeutic exercises more efficient, I think we must first understand the changes that occurs during movement adaptation.

        Right now, my study is looking at the neural changes in healthy young adults, but as you probably know, we walk pretty well in a lot of different environments! So to introduce this “new” environment for our healthy subjects, I am using a special treadmill called the split-belt treadmill. Basically, this special treadmill is made up of two belts for each leg instead of one for both. This allows each leg to be manipulated differently. I use a 2:1 ratio where the “fast” leg walks at a speed of 1.0 m/s, where the “slow” leg walks at a speed of 0.5 m/s. People find it challenging at first and but they quickly learn to adjust the way they walk so they look like they are walking normally (even though the speed for each leg is different!). This special treadmill has been studied in the stroke population. When people have a stroke, most times only one side of the brain is affected. This leads to one side of the body being able to move less. When you put the stroke patients on the split-belt treadmill, we would put the affected leg on the “fast” belt, and the non-affected leg on the “slow” belt. After just 15 minutes of training on the split-belt treadmill, when we but the treadmill at normal settings (i.re. both treadmill belts going at the same speed), patients walk more symmetrically by adjusting the way they walk (like the length of each of their step and the time at which both legs are on the ground during walking). Unfortunately, this effect is short-lasting, and more studies need to be done for this special treadmill to be an efficient treatment option for patients. That’s where my study comes in- My long-term goal is to develop effective gait interventions that are grounded on neuroplasticity changes that occur during walking adaptation. After my study on healthy subjects, I hope to study the stroke population to see if we see the same or different neural changes during the split-belt treadmill training.

Every molecule has a story to tell

The story of how single molecule microscopy shed new light on RNA transcription initiation

By Abigail Horn, PhD candidate, Department of Chemistry & Biochemistry, University of Colorado-Boulder

Since its inception in the 16th century, the goal of microscopy has always been to visualize phenomena smaller than our eyes are capable of seeing. Between 1925 and present day, five different Nobel Prizes have been awarded for scientific advances related to microscopy and the theory behind it. To this day, scientists are still working to push the limits of our current systems. Just three years ago, three world renowned chemists were awarded the Nobel Prize in Chemistry for the invention of “super-resolution microscopy.” In short, we are now able to visualize molecules within the cell that are smaller than the diffraction limit of light. What this means, is that super-resolution microscopy can allow us to watch two objects that previously were too close together to distinguish as separate. To put that in perspective, the diffraction limit of light is 200 nm, or 2,500x smaller than a grain of salt !

In the era of super-resolution microscopy, we can begin to investigate important aspects of biology by looking at individual molecules! Countless new insights have been obtained using this type of technology because it allows us to watch important biological entities (such as proteins or DNA) moving in their native environment (within the cell). Being able to visualize the way a molecule behaves in its normal environment is incredibly powerful, and has not been possible until very recently.

Figure1_AH

Our custom-built single molecule microscopy setup

 

I like to think of the benefits of single molecule microscopy using a football stadium analogy. If we look at a stadium from a bird’s eye view, there is certain information we can learn about it; for example, we can look at the size of it, the location of it, and we can maybe even see that most fans are wearing a certain color. But when we zoom in on a row of fans, there is an entirely new set of details we can learn. We can now see which team each individual fan is supporting and whether or not those fans are happy or sad in response to the game. So from the bird’s eye view, we learn very broad information about the stadium, whereas once we zoom in, we can learn more specific details. A typical biochemistry experiment would be analogous to looking at the entire stadium, but single molecule microscopy allows us to look at each individual “fan” in our stadium and learn lots of new information about our system.

Today I will tell you about what we have learned in my lab using single molecule fluorescence microscopy.

To set the stage a little bit, my lab is interested in the study of RNA transcription. Because RNA transcription is a crucial step in every process a cell must undergo, we think that it is incredibly important to understand the details of how it works. From the Central Dogma of Biology we know that the flow of information in cells goes from DNA, to RNA, to protein. RNA transcription is the step at which the information encoded in the genome (DNA) of a cell is “transcribed” into a different molecule called RNA. This means that a machine called RNA polymerase is capable of reading the genome, and creating a corresponding molecule that is related to that sequence of DNA. RNA transcription is a regulation point for the cell, and proper maintenance of this step is required for a cell to maintain itself and interact with its environment.

Central Dogma

The Central Dogma of Biology describes the flow of information within cells.

 

The focus of my project is to understand the precise details of how RNA transcription begins. To do this, we use single molecule fluorescence microscopy to watch this process happen at a scale that was previously not possible.

Proper regulation of transcription requires the concerted effort of hundreds of different proteins. It would be nearly impossible to study every one of these proteins so, in my project, I study a small subset of them called general transcription factors (GTFs). The GTFs help to guide RNA polymerase to the spot on the DNA where transcription needs to begin. Once the polymerase is in position, it can begin building the RNA using building blocks called nucleotide triphosphates, or NTPs.

Figure3_AH

Transcription is complex! We use a subset of proteins to simplify this highly complicated system.

 

I spent the first few years of my PhD research working on getting RNA transcription to work properly under specific conditions. I needed transcription to work at room temperature (since our microscope is at room temperature) and I needed it to work efficiently on a microscope slide, since the goal was to be able to watch individual molecules being transcribed over time. While these might sound trivial, transcription using proteins that come out of human cells is highly finicky and requires precise conditions to work properly. Tweaking each condition to see efficient transcription took months of optimization.

Our approach for studying transcription at the single molecule level was somewhat unique, in that we relied upon a special type of DNA to perform our experiments. With this DNA, we have a strand labeled with two fluorescent molecules (green and red), and then a second strand that contains (1) a bubble over the transcription start site, (2) a nick in the phosphodiester backbone, and (3) a quencher molecule that due to its proximity to the red dye, will quench the red signal when this strand is in place.

Figure4_AH

DNA used to study transcription at the single molecule level.

 

Since that is a whole lot of information at once, I want to unravel each of those pieces one at a time, given that this DNA makes up the crux of my research project. The reason that we implement a “bubble” in the DNA is to simplify the system. Given that we are working with numerous different proteins, placing a bubble over the site where transcription will start allows us to leave two additional proteins out of the system without compromising our setup. The “nick” in the DNA allows the short piece of DNA to be pushed off of the template when RNA polymerase begins moving as it transcribes. Once this short piece of DNA is pushed off the template, this means that the quenching molecule no longer resides adjacent to the red dye. So, the “signature” for a DNA that has been transcribed is the appearance of the red dye after the addition of NTPs (the RNA building blocks). Therefore, what we look for after performing transcription is how many of the green dyes in the sample are colocalizing with red dyes. Colocalizing is just a fancy way of saying that the dyes are located in the same place in the sample being imaged, meaning they are located on the same piece of DNA.

Now that we have our system set up to study transcription at individual pieces of DNA, we are poised to start asking biological questions about how the initiation of transcription is regulated. Working at the single molecule level allows us a limit of detection that is much better than other experimental techniques, meaning that in our system, we may be able to see transcriptional signal that would be invisible in a different type of experiment. Additionally, since we are working on a microscope slide, we have the ability to completely control the order in which proteins are added into the system and we can wash out excess proteins, giving us complete power over how transcription complexes form. With that in mind, we set out to investigate the very first step in RNA transcription; the formation of an active transcriptional complex.

As you probably learned in biology class, there is a certain order in which the first transcription factors bind to DNA: first, the TATA-binding protein (TBP) binds DNA, followed by TFIIA, TFIIB, and then TFIIF, bound to RNA polymerase II. This would mean that proteins are interacting with DNA first, and then interacting with each other. This is a simplified model of how transcription is thought to begin.

With our single molecule setup, we were able to test other options for the formation of active complexes. Our most exciting finding was that the major players in transcription initiation (Pol II, TBP, TFIIB, and TFIIF) can actually interact with each other in the absence of any DNA at all. Thus, these four key proteins can interact and then subsequently, as a complex, can bind to DNA and lead to transcription. This a new model for how transcription may start at individual genes within a cell.

The cool thing about what we found is that other scientists see similar protein-protein interactions between RNA polymerase and the GTFs within live cells. Researchers have observed what are termed “transcription factories” where RNA polymerase hangs out with its protein friends and then associate proteins guide the DNA into the factories to be transcribed. In situations where certain genes need to be transcribed really quickly, they can be guided into a pre-assembled factory and then everything is ready to go once the gene enters. The data from our single molecule system agree nicely with this transcription factory model. In future studies, it would be exciting to work toward building these transcription factories entirely in our system and watching individual molecules of DNA be transcribed in the presence of all of the auxiliary proteins.

 

Further reading:

Rebecca H. Blair*, Abigail E. Horn*, Yogitha Pazhani, Lizbeth Grado, James A. Goodrich, Jennifer F. Kugel “The HMGB1 C-Terminal Tail Regulates DNA BendingJournal of Molecular Biology. *these authors contributed equally

 

 

Genomic epidemiology to combat virus outbreaks

By Nathan Grubaugh, PhD (@NathanGrubaugh)

Post-doctoral sequencing ninja in the Andersen Lab, The Scripps Research Institute, La Jolla, CA

We are constantly bombarded with news headlines about some deadly virus lurking in our back yard, ready to spring at moments notice. Certainly some of this is just fear-mongering serving as click bait, but many of these headlines are justified. And it is mostly our own fault. Sure, viruses can mutate, changing the way that they behave, but that is not what really makes them suddenly emerge. It is our modern societies, encroaching on new territories, developing large urban centers, and connecting distant parts of the world, that is creating the perfect recipe for pandemics. Since these activities will likely increase, severe disease outbreaks caused by viruses such as influenza, Ebola, and Zika will stay as fixtures in the news. It is up to scientists to develop new tactics to make them obscure.

Epidemiologist are at the front lines of our battles with infectious diseases and must often employ the latest technology to improve outbreak response. While going door-to-door is still essential for contact tracing, many scientists also use sophisticated models to estimate some of the unknown factors influencing virus transmission. Now epidemiologists are adding genomics to their array of tools.

The virus’ history is written in its genome. Sequencing many virus genomes from an outbreak and determining their relationships can reveal the pathways of transmission. Dudas et al. provides an excellent example. By analyzing >1600 Ebola virus genomes – the largest dataset ever analyzed from an outbreak – they reconstructed the pathways that virus followed during the 2013–2016 West African epidemic (see video). If that is not impressive enough, Worobey et al. sequenced virus genomes to uncover how HIV-1 entered North America in the 1970’s and proved that the so called “Patient 0” was not the cause. This field of study has been coined genomic epidemiology, and is critical for our future outbreak control efforts.

Time lapse of the Ebola epidemic in West Africa. Left panel shows local transmission intensity (circle sizes) and virus spread (vectors). Top right is the phylogenetic tree colored by country and bottom right are the case numbers. Guinea = green, Seirra Leone = blue, Liberia = red. Created by Gytis Dudas (@evogytis).

 

I consider myself as a virologist, not a genomic epidemiologist. And actually, I am not even sure if there is anyone that could be defined as a true “genomic epidemiologist”. The field itself consists of scientists who specialize in different areas, but come together for a common cause. You need clinicians and epidemiologists reporting on the ground, in some cases entomologists collecting mosquitoes, molecular biologists sequencing the viruses, computational biologists crunching the numbers, and geneticists connecting the dots. On top of that, there are often many people with grey-area skill sets bridging the gaps. The outstanding Dudas et al. paper had >90 authors. So to say the least, this field would not exist without incredible cooperation and collaboration.

Novel and important scientific findings are often not discovered in isolation, especially in modern times. Human activities, such as urbanization and globalization, are generating conditions for explosive outbreaks. In response, we must combine ideas, expertise, resources, and technology to have the greatest impact. Genomic epidemiology provides a unique example of how the field is swiftly changing competitors into collaborators. Not only is this the right thing to do for science and society, but it is a certain benefit to your career. Here is the secret: My current advisor, Kristian Andersen, is an open-data-sharing junky. He has shown me that making data and ideas publicly available before publication 1) gets the important information disseminated immediately and 2) gets the attention of other interested scientists. Sometimes this can lead to your data getting “scooped” (i.e. published before you do), but 9 out of 10 times it gets smart people that can do something awesome with your data wanting to collaborate. This makes your projects better, exposes you to new fields of science, and expands your professional network. I like those odds.

My first genomic epidemiology project was to investigate the Zika virus outbreak in Florida. The crux of the project is to be able to sequence the virus’ genome, and for Zika virus, this was not easy. The main factor was that there just is not much viral RNA present in human blood to sequence, so the workhorse of molecular biologists, RNAseq (sequencing all of the RNA present without bias), did not produce much usable data. Something targeted needed to be developed. This is where I first encountered the true collaborative spirit of the field. Nick Loman and Josh Quick, two sequencing gurus and field pioneers, generated a brilliantly easy and efficient protocol, and shared it with the world. Even though we only really knew Nick and Josh through Twitter, we teamed up to adapt the protocol to the two most popular sequencing machines, the Oxford Nanopore minION and Illumina MiSeq. Armed with a new tool, teams around the world were now rapidly generating Zika virus data, and for the most part, openly sharing their data for the larger community to use. All available Zika sequencing data is displayed on NextStrain, which recently won the Open Science Prize.  

Honestly, this project would not have happened without Sharon Isern and Scott Michael at Florida Gulf Coast University. They were our connections to the outbreak in Florida, retrieved samples from the Department of Health, tested mosquitoes for Zika virus, and shared all of this with us. Once we started generating and sharing our Zika virus genetic data another wave of collaboration began again. Groups were willing to share their case investigations (e.g. infection locations), transmission models (e.g. infection risk), and travel data (e.g. number of passengers) so that we could collectively make the greatest impact on public health.

We also discovered through (a forum for sharing virus genetic data during outbreaks) that other groups were independently sequencing Zika virus from the Florida outbreak. While competition in science can be beneficial in some respects, it is mostly harmful when accurate information is urgently needed, like during an outbreak. Therefore, we partnered with Jason Ladner and Gus Palacios from the US Army Medical Research Institute of Infectious Disease and Pardis Sabeti at The Broad to put together a more comprehensive data set. Our manuscript was recently published in Nature.

Central to our story was determining the relationships among the Zika virus genomes that we sequenced from Florida and those sequenced from other places in the Americas. Those relationships are displayed in the form of a phylogenetic tree (see Figure 1, Zika virus from Florida is shown in red). The points where the tree branches merge and the number of distinct red Florida groups (called clades) indicate when and the number of times the virus arrived, respectively. With this basic information, we determined that Zika virus transmission started in Florida 2-3 months before it was first detected and at least 4 separate introductions (but as many as 40 based on our models) may have contributed to the outbreak. The Zika virus genomes that sit closest to the Florida genomes in the tree are mostly from the Caribbean. Combining the sequence data with Miami being a major travel hub and intense Zika virus outbreak occurring on many popular vacation hot spots, we hypothesized that the Caribbean Islands are a significant source of Zika virus introductions into Florida. Once transmission started, we discovered that the outbreak within Miami was likely more widespread than what was previously thought. On a positive note, we found evidence that the intense mosquito control programs helped to end the Zika virus outbreak.

 

Figure1_NG

Figure 1. Time-resolved phylogenetic tree of Zika virus in the Americas. The tips are positioned on the sample collection date (x-axis) and the nodes (where branches converge back in time) represent the most recent common ancestor. The ancestors can indicate when a virus emerged into a new region. Image was created using Nextstrain.

We also joined up with two other teams investigating the spread of Zika virus in the Americas. Again, instead of competing for the spotlight, we co-submitted our work so that the collective story would have a greater impact. Metsky et al. generated >100 new Zika virus genomes to analyze the timing and patterns of introductions across the Americas. Faria et al. used a mobile genomics lab to sequence Zika virus from Brazil to discover that transmission occurred unnoticed for more than a year prior to detection. The importance of all of these papers being published together was to show how the Zika virus epidemic expanded in the Americas. It was not just a uniform wave, spreading to one bordering country to the next, but a series of large jumps followed by intense local transmission (Figure 2).

Figure2_NG2017

Figure 2. Zika virus spread in the Americas based on the phylogenetic tree presented in Figure 1. The color scheme is from Figure 1. The circle diameter represents the number of Zika virus genomes collected from a country. Arrowed lines indicate directionality of spread. Under-sampling of Zika virus genomes prevents us from deciphering more precise movements. Image was created using Nextstrain.

Our Zika virus studies demonstrated how vulnerable we are to epidemics of unexpected viruses. By the time Zika virus was first discovered in Brazil, we estimated that it had already spread to most of the Americas. At that point, no control efforts in Brazil would have stopped the epidemic. However, the patterns that we discovered using genomic epidemiology can help to inform policy and direct control efforts. For example, we now know that if we want to prevent future Zika virus outbreaks in Florida, we need to devote resources to combating the outbreaks in the Caribbean. Moreover, we provided evidence that local transmission can be reduced with intense mosquito control campaigns. This is tangible data that can be acted upon, only made possible by many friends, colleagues, and total strangers finding a common ground. While there are many other groups freely open to collaboration and data sharing (e.g. the Zika experimental science team), much of the Zika research has been a race to publish something first (see the story of antibody-dependent enhancement). The problem is that the first is not always the best and our literature is now muddied with incomplete findings. I am becoming increasingly worried that this sort of guarded, competitive research will undermine our response efforts. How well we are able to come together, in my opinion, will ultimately decide the fate of this epidemic and the next.