Biotechnology: getting on-base

By John Casey

President Obama’s strategy of hitting singles and doubles instead of home runs may be controversial when it comes to foreign policy, but is without a doubt an increasingly popular approach for biotech entrepreneurs.

As biotechnology mushroomed throughout the aughts, predictable disappointments came to pass. Lab-reared human limbs have remained beyond reach, and, no, we can’t program a tree to grow your house. Similarly, the green biofuel revolution has languished, retrenching with meager progress despite congressional mandates of Himalayan proportion. Instead, a fresh wave of metabolic engineers and microbiologists are adapting the armaments of synthetic biology to take on more manageable industrial problems. Entrepreneurs and investors have come to understand that industries with immense scale and slender margins – e.g., fuels – can be inappropriate first targets of underdeveloped biological systems. Rather than committing fickle biological entities to massive, capital-intensive projects, a new generation of guerrilla scientists are targeting the small and value-rich: fragrances, moisturizers, dietary products, plastics.

Have we abandoned the health of the planet for individual vanity? Hardly. The high-value molecules exemplified by cosmetics are intermediates to bigger goals; not alternate destinations, but stepping stones. By first getting “on-base,” successful enterprises are putting themselves in better position to score bigger goals

The marketable outcomes of biotechnology can be seen as a continuum from low-volume, high-value (cosmetics or “orphan” drugs) to high-volume, low-value products (grains, fuels). While the latter end of the continuum has the potential for the greatest worldwide impact, it also requires a magnitude of production and reliability uniquely challenging for biological processes. Without proof that a new biotechnology will work as well when measured in acres or thousands of gallons as it does at the bench, funding is hard to come by. Of course, without such funding, sufficient evidence is impossible.

While less likely to change the world, narrower markets for high-margin products like algal anti-aging cream can nurture and sustain emerging technologies. By generating more revenue for less product and capital expenditure, these niches allow biotechnologists to simultaneously build a stable business while iterating on the fundamental technology for longer-term projects. Thusly focused startups are proliferating around Boston and Cambridge: Gingko Bioworks and Manus Biosynthesis, each founded by recent MIT BE alumni, are developing independent approaches for biocatalysis of highly valuable chemicals and are already earning revenue. Importantly, they’re finding that lower funding requirements grants them a great deal of independence. When asking for seven figures instead of nine, one finds a wider variety of partners willing to talk.

So what does this have to do with those of us still working on bench-scale technologies in academic labs? Too often, our projects are targeted at holy grail, home run outcomes. Sure, there is usually a series of aims that lead (conveniently) linearly to our holy grail, but ultimately progress is measured by how close a student or investigator gets to this lofty goal. Resulting do-or-die situations only result in greater pressure on researchers to find any positive, potentially illusory, inclinations in their experiments. Reimagining engineering projects as a series of independently useful and sustainable steps could facilitate the field’s ability to serve society while improving the education of those young scientists conducting the research. Incrementality and flexibility could both contribute to a higher hit percentage. Projects could be funded in smaller chunks but still yield concrete outcomes to funding stakeholders, widening the scope of grant sources. Technologies that fail to cure cancer or replace fossil fuels could still spin out tangible value for investigators and potential consumers. For students, the more intermediate successes built into a project, the less risk and pressure involved in its undertaking. More broadly, when we frame our projects to taxpayers in terms of multifaceted, attainable goals, we decrease the chances of disappointment and eventual disillusionment with the scientific enterprise.

Image credit: Davidson

What’s the Point, Honestly, of Doing this?

By: Georgia Lagoudas

What do we really want out of a PhD? Do we come here to rub elbows with intellectuals and like-minded scientists? Do we come here to shadow and learn from the best and brightest in our field? Do we come to develop our personal skills? Do we want to learn how to communicate, how to conduct science, how to generate and test innovative new ideas? Do we come here to make an impact in the field of biology, medicine, ecology, or energy? Or do we come here to do cool science and perhaps increment our fundamental knowledge by one more inch?

I don’t know the answer to this. I haven’t decided what I want out of a PhD. Most of my peers don’t know what they want out of a PhD, although some proclaim they do. In the later years of the trajectory, most begin to clarify where they want to go next, and thus identify the skills that they can transfer to the next position. Many of us merely do what our advisors tell us, struggle along with a demanding project, or push to the next publication deadline. How often do we stop and think about WHY we are doing what we are doing? Not exactly in the scientific sense, but in the practical, real-life sense. Is this the research that will propel us to our next career and enable us to find a new faculty position? Is this the project that we can discuss at our next interview? Or are we doing this to learn a new set of bench-top techniques that we’d like to translate over to another lab or industry setting? Perhaps, it’s none of these. Perhaps what we most get out of our PhD is learning how to LEARN. We need to understand the process of defining a problem, identifying hurdles, and painstakingly strike down each successive obstacle until we can emerge with rock-solid data on the other end. Once we emerge triumphant, however, we must develop a skill set to communicate these ideas and pitch these new concepts with persuasive passion.

Maybe that’s what a PhD is about. It’s about learning how to learn, and importantly, it’s about teaching ourselves new things we do not know. Scientific thought process, new techniques, data analysis, communicating with others in our field, organizational skills – these are all capabilities we have to acquire to be successful in a PhD.

But when does someone tell us what we should aim to get out of a PhD? Do we need to consciously dedicate time to develop our skill sets? Should we invest time in “soft skills” training? Should we aim for the science, or aim for the path that allows us to hone the best set of skills? This answer is different for everyone, as we all came to graduate school for slightly different reasons. But in the end, it’s pointless to trudge along as a graduate student, only thinking of the “pot of gold” (a.k.a., science) at the end of the tunnel, without stopping to think about what we’d like to discover along the way. If we pause to think about this only at the end, when the journey is almost done, then we’ve squandered this golden opportunity and precious years.

However, it’s hard to stop and think, why? We feel the pressure to move forward, collect data, and publish results. That’s the academic cycle that dictates our life and our world. But we’ll only get caught in the cogs of this rusty, wheeled behemoth, without staying free to dictate our own path. The world of academia is changing, slowly, and we need to embrace our independence and free will. We need to pause, humbly, and decide, what next? Why?

Destroying the world, pipette tip by pipette tip

By: Sean Kearney

My face morphs into a painful grimace as I toss a stalk of excessively wilted, two-week-old celery into my compost bin. Wasting food is hard for me. I think about the billions of people who scrape by every day without the luxury to dispose of food. It’s unfair, I think, that I can choose to trash a moldy peach or unceremoniously pour out a soured gallon of soy milk. All I would need to do is to plan more strategically, to predict my culinary digressions and I could save 90% or more of the food I end up tossing.

But then, working in the lab, I think it’s nothing to dispose a liter of contaminated cell culture media after forgetting in a dark place for some weeks or months. Surely, the media is orders of magnitude more expensive than a stalk of celery–yet, emotionally it feels so much easier to part with. Somehow, I’ve become desensitized to the tremendous amount of waste that I produce every day as a lab-bound scientist, and I wonder what’s contributed to this negligence.

Each day I toss out hundreds (sometimes thousands) of used pipette tips, destined straight for the biohazard burn box. Add these disposables to the plastic wrappings covering each new package, the cardboard boxes carrying new supplies, the styrofoam containers carrying ice (or dry ice) for temperature sensitive reagents, and the tremendous amount of reagents leftover after any given protocol, and I start to feel overwhelmed. If an alien walked into my lab, it’d be more likely to think that my job is to fill trash receptacles than to actually do science.

Lost in this sea of waste, I start to have an existential crisis. Is my work worth the many landfills of material I’m producing? What’s the cost-benefit analysis here? Why are people funding me to destroy the planet pipette tip by pipette tip? It can be easy to forget that for every batch of happy enterocytes, I’ve probably inadvertently released enough carcinogenic hydrocarbons into the atmosphere to cause a worrisome spike in the number of gastric cancers thirty years in the future.

Of course, I can’t really afford to think this way. We as humans are really good at making messes; we may only be slightly better at cleaning them up. But as long as the pace at which we clean up our messes just exceeds the pace of our making them, it’s a promising future. So the next time I toss a bottle of media, I’ll try to think about the new niche I’ve created for a swarm of happy microbes; the next time I have to part with a moldy peach, I’ll think of the yeast returning the fruit to the soil and air from which it was born.

Image credit: Mettler-Toledo, Rainin Pipettes

Video games

By: Sarah Spencer

After college graduation, my brother and his two roommates split the cost of a flatscreen TV and a brand new PlayStation 3 (PS3). Since they were recent graduates from course 6 (Electrical Engineering and Computer Science), they filled the PS3 up with some seriously nerdy background programs. This is when I got introduced to Folding@home, a program that uses the idle computing power of personal electronics to run protein folding simulations in support of disease research. This effort, which started from an academic lab, joins a long list of video games and crowd-sourcing platforms that have jump-started efforts in science and science education.

I am a huge believer in scientific crowd-sourcing, and the idea seems to be gaining momentum based on recent articles in publications ranging from the Harvard engineering newsletter to USA Today. In addition to projects like Folding@home, which use excess computing power, there are protein-folding programs, e.g. Foldit, which actually involve players solving real-life protein-folding puzzles. The game Eyewire is from MIT and allows users around the world to map neuron branches within three-dimensional space. The project called Zooniverse allows users to study satellite images for new planets, asteroids, and solar disturbances. These examples join a myriad of other efforts to gather scientific data with the help of millions of citizen scientists.

My personal experience with crowd science involved a somewhat smaller crowd of eighty undergraduates finishing and annotating multiple Drosophila chromosomes. At Washington University in St. Louis, I worked with the Genomics Education Partnership led by Prof. Elgin in the biology department. For years, she taught a computational lab class that enabled undergraduates to transform whole genome shotgun data into finished contigs with annotated genes, supporting a much broader evolutionary study of the Drosophila fourth chromosome. This project has been on my mind lately since it is finally written and planned for submission with eighty co-authors. The combined effort of these undergraduates from universities across the US was channeled into a research structure that produced concrete, cutting-edge genomic discovery.

In addition to research, there are incredible opportunities for education through scientific games and crowd-sourced projects. The Genomics Education Partnership taught me gene structure, splicing rules, chromosome packaging, and regulation of expression in a memorable, hands-on environment. My undergraduate university also pioneered the story-telling game Alice to help teach middle school kids how to program (including looping, conditionals, and even recursion). Then there are tons of educational sites on the web, like the PBS RNA VirtuaLab which provides gorgeous visuals as users solve puzzles to learn the basic and advanced rules of RNA secondary structure.

As we barrel into a future tied to advanced computing and personal electronic devices, video games can be harnessed as a source of outreach and crowd-sourced research effort. Video games could be a great way to hook more people into science and engineering fields, especially if we can capitalize on the ‘angry birds’ mentality that maintains interest over time. I’ve seen both small-scale and large-scale projects contribute toward single-lab academic research efforts and also translate into consortia incorporating government and industry sponsors (e.g. Citizen Science Alliance). Remember that people outside of the fifteen you talk to on a daily basis can help you accomplish more than you can in isolation – you just have to get creative and provide the right framework.

Image credit: Foldit

Educating the next generation of biotechnologists

By: Tony Kulesa

In 48BC the Library of Alexandria burned to the ground, and with it, the extent of all human knowledge. Or so the legend goes. If all our knowledge burned today, where would we start rebuilding? What is the one fact worth tattooing on our forearms, such that even as our servers and notebooks are purged of all thought, all history, we will never lose?

Richard Feynman once said if he had one fact with which he would start science over again with, it would be the atomic theory of matter. I think I’d be hard pressed to disagree. At least for molecular biologists, the fact we might most hang onto is what’s going on far below where our eyes can see: this picture of molecules chaotically vibrating, but forming complex structures of the crystals in my watch, the grayness of the clouds, the grain of the wood.

Perhaps the more practical question is, not what knowledge we might save, but what we would hope to do with it. How would we imagine the generations after us rebuilding science? Contrast the vision of the last paragraph with the current progression of science education in K-12. In these formative childhood years, we are also attempting to start with a few facts accepted as truths, plus some limited years of experience in the world, and rebuild much of the extent of human knowledge.

Are we starting with the wrong facts? Why is high school physics about skateboards and rockets, magnets and batteries? Why is biology about nephrons and tundras?

Are we building knowledge in the wrong direction? Why do we save the most fundamental, physics, for post-calculus, when even without it Archimedes and Galileo gained superior understandings of our world.

To serve different interests, we may have different answers. But what our government has deemed our most worthwhile interest via the language of funding dollars, is poorly served by the current paradigm of K12 science education. Perhaps we can use this exercise to think about and discuss the skills, experience, and intuition that we deem most essential to biology (ical engineering). In my experience working the lab, this is the molecular, statistical thermodynamic intuition about biomolecules and larger biological systems.

Students are missing this molecular intuition for these systems until years after an undergraduate degree. To them, DNA is the white goop in strawberries, or abstract, lego models of double helices. Unlike electrical engineering, where one can lick a 9V battery and feel the force electrons that powers their lightbulb, how can we give students the same intuition for proteins vibrating, the squishiness of membranes, the fractal structure of the human genome, or the grip and pull that cells exert on substrates?

If we start with the fundamentals of the what the microscopic world “feels” like, we might find the answer.