our bioLab for our vibrant StreetBio community, EMW Bookstore - Cambridge, MA
Fall of 2015, I participated in the very first course of H.T.G.A.A.
H.T.G.A.A. is a Synthetic Biology Program directed by George Church, professor of Genetics at Harvard Medical School. The class is a part of the growing Academy of (almost) Anything, or the academany. It is modeled around the MIT Open CourseWare, How to Build (almost) Anything, that sprouted Fabrication Labs all over the globe - biology, your time is here!
We are based at StreetBio, a community bio lab in the basement of the East Meets West Bookstore founded by synthetic biology extraordinaire David Kong, Ph.D.. Every Wednesday fantastical lecturers teaches us about their journeys into synthetic biology, and classmates around the world tune in. In our lab, the Grotto, we discuss theory and design, build the lab, and do miscellaneous biohacking things. Come check us out :)
Extremophile sensors in the search for extremophile forms of life.
In 2008, NASA Mars lander, Phoenix, transmitted pictures of crystal white shards of subsurface ice from the Dodo-Goldilocks dig site. Equip with on-board wet lab capsules, Phoenix further fed our curiosity with data on the ionic composition of this soil. Life as we know it is mediated by water, and its universal ‘currency’ is salts; responsible for osmatic retention, metabolism and even the highest functions of mental thought. The pressing question remained, did this hostile rock planet once breathe life? And the ever more urgently, could this landscape comprise of compounds to support human life in our future?
On our team, I fabricated extremophile sensors to search for evidence of extremophile lifeforms. On Earth, Ion Selective Electrodes (ISEs) are used ubiquitously (most commonly pH meters), but we needed counterparts with the robustness for space travel and future Mars missions. I worked on iterative designs for miniaturized arrays of 80 unique sensors, fit on a circuit board the size of a Popsicle stick. These galvanic cells required fabrication of tiny electrodes and selective barriers, so I employed methods of electroplating thin layers of silver (aq. AgCl), followed by photo-curing ion selective resins. I cycled through materials, from sealants to Navy ship paints, to find things that could survive a full 235⁰F range, massive vibrations and the corrosive properties of water.
Dealing with leakage, a highlighted breakthrough came as the idea to invert our fabrication process (and the shape of our sensor). Instead of depositing layers of polymer into wells, we could attain the same effect via an additive ‘candle-dipping’ process, which consistently created sensors as tiny bulbs on the tips of wire!
Neil Gershenfeld (MIT), David Kong (MIT), George Church (Harvard), Megan Palmer (Stanford)
Unbeknownst to me in Istanbul, something amazing was taking root 4,821 miles away, in a bright little basement between Harvard and Central Square…
It would be weeks till my universe collided with the EMW Street Bio, but in my review, I find the lessons covered here to be a ardent foundation to the space established for the new-found ‘Grotto’.
Starting with municipal rules and regulations, mixed with the norms and cultural pillars. Within just a few weeks, a group of people in an empty room can populate the mental and physical space with their vision; and viola, IT LIVES!!
Setting up our lab in Cambridge, MA for hypothtical synbio projects (i.e. to Express GFP in a cell free system), we must find out:
We are so excited to bring this lab to life and engage with the city to gain necessary approvals this semester!
Joseph Jacobson (MIT)
For my first class, I met Professor Joe Jacobson – a physicist who’s sauntered elegantly into synbio. Current head of the Molecular Machines group a MIT Media Lab, he’s got a dogged vision that biology can be tamed into high functioning microelectronics. Vice versa, his work with microelectronics is pushing the outer limits of our capabilities to control and synthesize biological constructs.
Specifically, as co-founder of Gen9, Jacobson’s on the leading wave of the next generation DNA synthesis; writing base pairs by the billion, and enumerating the vastly expanding world of capabilities made possible when the cost of synthesis plummets.
The technological advances in our ability to sequence (read) DNA have preceded our ability to synthesize (write) it. Those who have sat in on lectures or TED talks about sequencing triumphs are probably familiar with the allusion to Moore’s Law.
Yet this next half of the story, for DNA synthesis to follow the same exponential curve, is what will make genetic engineering more than just a spectator sport. Time to build… on the scale of whole BLAST databases or even, maybe, genomes.
Homework contained some skills I have worked on for the better part of the last three years, primer design! Yet, there's still an art to craft a fine set. Luckily Prof. Jacobson brought along some nice tools for us to use.
Assignment #1: Primer design to linearize plasmid backbone
Theory: Use NuPack to help select 18 bp priming sites that amplify a ~2.25 kb region of pUC19 (NEB) immediately upstream of the plac promoter and downstream of the start of lacZalpha. The resulting amplicon excludes the plac promoter and n-terminus of lacZalpha, which enables you to swap in a gene of interest under the control of a promoter of interest using Gibson Assembly later on in your workflow. Design one pair of oligos that prime optimally and another that prime poorly. Describe the PCR thermocycling program that uses Phusion polymerase (NEB) for these pairs. Crucially, determine annealing temperatures and extension times. Nupack task check list:
First, the FORWARD (CW) primers!
P.S. This is what Nupack looks like. It can be found here.
Then, the REVERSE (CCW) primers.
From my results, I picked one FWD and one REV primer that represents optimal features individually, as well as their interactions with eachother. Likewise, I picked a FWD and REV pair that were the worst- i.e. they fold back on themselves in ugly peanut-shaped loops, as seen in the Nupack pictures above.
While we weren't able to execute the Experimental portion of the homework, this is conceptually how a PCR works and what amplified DNA fragments visualized on a gel would look like.
Assignment #2: Build a gene from shorter gene synthesis fragments
Theory: Recode a fluorescent reporter and use NuPack to help design 200-300 bp IDT gBlocksfor building the reporter with Gibson Assembly. Check that your 15-30 bp overlaps do not fold into undesirable secondary structure during the isothermal reaction.
Patrick Boyle (Gingko Bioworks)
Patrick Boyle, in his own words, “was a Synthetic Biologist before it was cool”. He was an early member of the celebrity biosynthesis startup, Gingko Bioworks, which was Y-combinated and has pulled in over $45M in its Series B round this past year. Of the early offerings of commercial bio-production, he has worked with perfumers to perfect the scent of a rose which has never before been smelled in this natural world.
Patrick came to show us how one can engineer a microbe, such as bacteria or yeast, to produce an interesting small molecule. (Like the highest-tech beer brewing!) Apparently, this IS rocket science, but at least it comes in rainbow colors.
Notably, he framed his field in the greater expanse of history with a fascinating Nature article, which compares biosynthesis to past scientific breakthroughs and their translation to industrial revolutions; take the 19th century’s radical developments into chemical synthesis!
The aproach is to Design, Test, and Build synthesis, strategies with an extreme amount of iteration. Thus..
Map a stratedgy for the biosynthesisof a compound of your choice.
The product we chose is estrogen (estradiol) beginning with an endogenous cholesterol precursor. While cholesterol-producing yeast-strains can be utilized to create our starting material, it is also possible to use the cholesterol from egg yolks after some purification. We would consider which source is most for efficient for optimal production.
The chasis we chose is our handy workhorse, yeast (Saccharomyces cerevisiae), for which we can model off the exisiting Steriod Hormone synthesis pathway.
From the pathway representation, we see there are multiple metabolic pathways for estrogen biosynthesis. We isolated the pathway we wanted (red), and characterized the associated enzymes using the KEGG database. Our desired pathway is highlighted below!
KEGG is a powerful tool that combines literature and bioinformatics to map all known metabolism. Listed out are the required enzymes, which must be present via yeast expression or suplementation in broth.
Optionally, one step further, with CYP1A1 can bring us to ESTRIOL (Target estrogen, predominant during reproductive years). The creation of a synthetic protein through 8 enzymes is no small task, so we must next decide how we will test the efficacy of this hypothetical pathway design.
To measure product formation, we can add a GFP reporter protein gene gated by an estrogen receptor “Tightly Regulated, betaestradiol DoseDependent Expression System for Yeast” (2000) (left). Alternatively, for the scrappy, there is the option of purchasing a comercially availible estrogen-meter, in the form of a Fertility Montior (right).
Wheeew! I feel quite smart now :)
George Church (Harvard/MIT)
Bio design! Diversity! Selection! Geneticist George Church has a wild side - which includes fantastical pontifications around woolly mammoth resurrection and reverse chirality for supreme virus resistance. He spoke about directed evolution as well as the possibilities of a Human Genome Project 2.0.
George gave us a peek into his intircate world to equip us to address his question; "How do we compete with Darwin?" He refers to the vast amount of time and space for which genetic code has been allowed to evolve through on its own. For his response, let's just say a picture's worth 1000 words:
In class we discussed the idea of a “Human Genome Project 2.0”, but instead of reading DNA, writing DNA. George Church poses the following questions:
1. If humanity were to undertake such a project, what would be the benefits? What types of new science and engineering would be enabled if we had such a synthetic human genome? Please provide specific examples.
3. Map out a technical strategy for synthesizing a human genome. What technologies would be required? What are existing tools we could leverage? For certain tools that do not exist, what should their capabilities be?
The lesson of the Human Genome Project 1.0, sequencing, was that you should shoot for the moon in the hopes of advance technology far enough to know how to make tools capable of moon shooting. In other words, we set an – at the time- ludicrous goal of sequencing 3 billion bp. After 13 years, $2.7 billion and international collaboration, we had ourselves a reading of the human genome. Yet, the truly invaluable outcome of this project was the acceleration the field of genetics put on the state of technology as a whole.
Andrew Hessle of Singularity University wrote, “The HGP was visionary, initiated even before the first bacterial genome (much smaller) had been sequenced. It transformed biology into a digital information science, yielding ongoing returns that include new insights into the molecular basis of life, cancer, and evolution, and also practical applications, like rapid genetic tests for important diseases."
In the same way, I see the main triumph of a HGP 2.0 is so far beyond the actual synthetic genome. It is the marathon of technological advancements required to print DNA that big, to organize that much and to pack DNA that small. Solving this wicked problem is going to require the ‘Biggest’-Data Scientists and even origami-ists to accompany biological engineers. And it is going to help solve many other real-world problems in the extent that it solves the one we started with. If HGP 1.0 came about with the digital age, HGP 2.0 is our spyglass in which to envision what’s next. We will exceed the speed limits to silicon, we will create the most integrative international collaboration and connectivity platforms, and we will have the data and computational capacity to predict the economy, the environment. From our desire to print 3 billion bp, autonomous and automated machines will be integrated into every aspect of our lives. At this point we will have singularity.
2. Conversely, why might we not want to proceed with such an endeavor? What are the risks?
We will eventually have to entertain the societal and ethical risks of designer babies. People seem to be comfortable with germ line modifications to human embryos for the prevention of disease, but this trails off into the murky water of subjectivity very fast. If genetic disposal to breast cancer is a medical condition worth preventing, then is ADHD or a physical disfiguration? The idea of controlling intelligence or appearance, among other things, immediately points to the idea of optimizing them. Luckily, there is no single variable or metric to rate the vast diversity of types of intelligence, beauty and strength, without homogeny. Thus I hope people will never try.
In the more near term focus, I believe the true risk of DNA synthesis will be data security. Besides coding for the complex protein functions which make up life, DNA can be a platform for digital data storage analogous to the binary our computers today. George Church is familiar with this, as he and Kosuri recently beat the world record in successfully storing 5.5 petabits of data — around 700 terabytes — in a single gram of hardy DNA. To store the same kind of data on the densest hard drives in use today, you’d need 233 3TB drives, weighing a total of 151 kilos. And those probably won’t survive the hundreds of thousands of year that DNA can. (George successfully used around 44 petabytes of data in DNA, immortalizing 70 billion copies of his latest book.)
To paraphrase Sebastian Anthony of ExtremeTech: To foresee a world where biological storage would allow us to record anything and everything, every square meter of Earth could be blanketed with cameras, recording every moment for all eternity/human posterity. If the entirety of human knowledge — every book, uttered word, and funny cat video — can be stored in a few hundred kilos of DNA, though… well, it might just be possible to record everything (hello, police state!)
Images and figures from the MIT Review, the Pew Research Center, Genisyss, ExtremeTech and the Huffington Post.
John Glass (JCVI)
Professor John Glass works at the J. Craig Venter Institute on a fascinating puzzle worthy only of the most meticulous organizers; the methods to create a minimal genome. As an artifact of coming about organically instead of by a neat and proper ‘programmer’, prokaryotic genomes are hopelessly jumbled, and contain redundancy as well as encoded ‘dark matter’ (currently unknown if it is useful at all). If we could throw out the junk, keep only the DNA required for the most critical functions, and reorder and label everything, you’ve got an ISTJ-type person’s dream cell.
More simple and predictable, minimal cells are important for research and for potential approvals as medical treatments. Currently, Mycoplasma genitalium is being targeted as a model organism, with the smallest genome of any organism that can be grown in pure culture. It has a minimal metabolism and little genomic redundancy. Consequently, its genome is expected to be a close approximation to the minimal set of genes needed to sustain bacterial life.
Using global transposon mutagenesis, John and his group isolated and characterized the genes of M.genitalium. To achieve rapid and large scale genome modification, they have developed a genome engineering strategy that uses a combination of bioinformatics aided design, large synthetic DNA and site-specific recombinases.
The highlight of the lecture was asking about FUGU(!!!), a.k.a. pufferfish. They have the smallest vertebrate genomes yet measured, at ∼400 million bp (eight times smaller than the ~3B bp human genome). For whatever evolutionary reason, it appears that their genome has contracted naturally in the last 50–70 million years, with extreme gene density and nothing extra! In 1993, Nature proposed them proposed as an ideal model organism to study homology to a not yet obtainable human genome. They're also quite exciting to eat!
Make a set of rules for redesigning a bacterial genome, based on biological knowledge and transposon bombardment data.
Provided is an Excel file that lists all the genes in Mycoplasma mycoides JCVI syn1.0, and tells you what transposon bombardment revealed about each gene, i.e. essential (e), not-essential (n), or whether a disruption of that gene causes impaired growth (i). If one were to design an algorithm for a minimized cell capable of rapid growth, what are the rules one would use to program the algorithm.
Minimum "Living" Cell Algorithm:
From patternts in past 'minimization' experiments we know that certain genes, such as the two below, are imndisposable to minimal cells. Our strategy employs these trends.
In our literature search, we came across Essence of life: essential genes of minimal genomes, a paper by John Glass's group which describes several answers to the question of the homework. Our answer matches their first proposed method (a.).
Evan Daugharthy (Harvard/MIT)
Evan Daugherty, from the very inspired Wyss Institute for Biologically Inspired Engineering at Harvard University, has helped develop a new technology called in situ sequencing (latin for “in place”). This allows researchers to detect single RNA molecules where they naturally reside—spatially positioned inside biological samples. Oy- In ‘er natural habitat!
Analytic “read” tools span many scales of biology including DNA sequencing (genomics), RNA sequence content (transcriptomics), protein expression (proteomics) and other biomolecules.. The ability to view them simultaneously, mapped along a 3D structural morphometry renders a powerful picture.
“This is really exciting because it’s the first time researchers have been able to look inside cells and see thousands of different types of molecules at the same time.”
Implied applications are that we can make new products that resemble real biological systems; i.e. fibroblast wound healing, understanding how the brain works, and to developing new organoids to further our understanding of biological development.
Create an in situ sequencing library inside a polyacrylamide hydrogel, and detect the sequencing amplicons using fluorescent sequencing by hybridization.
We will do the experimental assignment later in the semester as we have to gather up resources to buy the templates and buffers. Yet, we had some time this week to begin assembling our first DIY thermocycler (left) and fix our chemical hood (right)! (minor drawback: it might need new filters).
Analyze a FISSEQ dataset and find some in situ sequences. These instructions are adapted from Lee, Je Hyuk, et al. (2015) “Fluorescent in situ sequencing (FISSEQ) of RNA for gene expression profiling in intact cells and tissues.” Nature protocols 10.3: 442-458.
Question: What happens when you use different values for the parameters? How does it affect the image registration quality? Open the results in Fiji and take a look! Note, you may have to adjust the contrast in Fiji to get a good look at the images.
Question: Take a look at the reads in the resulting .csfasta file. How do they look? What happens to the number of reads if you change the value for maximum number of missing base calls ('6' in the command line).
As you can see in the following snippet of the reads file, each read is 32 bases long, and has from 1 to 6 gaps, as this was the maximum allowed. Changing the gap parameter to lower values decreases the number of reads and to higher it increases.
Question: Take a look at the output. What happens if you change the size of the kernel to something less than 3? To something much greater than 3?
If I change the value to something less than 3, there is no clustering! For something much greater than 3 (e.g. 7), the number of clusters is very small.
Uh-oh, must repeat with more RAM to complete these tasks.
Think back to your experience so far with HTGAA. Were there any experiments where in situ data of RNA, DNA, protein, or other cellular features would be helpful in understanding the engineering process? You should try to answer the following questions:
Nina Tandon (EpiBone, Cooper Union)
Among many outstanding things, Nina Tandon is CEO and co-founder of EpiBone, the world’s first company growing living human bones for skeletal reconstruction. She joined us this week to teach on the biomimetic paradigms for tissue engineering.
In practice, this is the design of environments (i.e. bioreactors) that can mimic the settings for developmental biology, so as to grow differentiated tissues in the laboratory. Changing the properties of the bioreactors can result in the grow of different tissue types, from electrical impulses giving rise to cardiac muscle cells to physical motion giving rise to skeletal muscle.
Meanwhile, a fun application of bioreactors for a different purpose: building biotic video games! BWAHA!
Build a Paramecium/Arduino interface. Measure how fast the paramecia (a) swim and (b) change direction in response to electrical stimulation.
Components (Based off making.do!):
Our special guests arrived in the mail from Carolina: Paramecia, a genus of unicellular ciliated protozoan, widespread in freshwater and brackish environments. Their magic power; galvanotaxis, the directional movement of motile cells in response to an electric field. (ok- it's not that magical..you've heard of moths having phototaxis)
Also, the microscope came. Along with the live paramecia, we had slides with paramecia samples fixed and dyed, so we go a sneek peak of who we were working with. You can see their cilla and oral groove- cute!
We began to build a paramecium playground by modifying the provided vector drawing using CoralDraw and then rastering it out of acrylic using a lasercutter. It took a couple tries..
The set up required us to create an electrode along each edge of the 'playground', which would control movement in that direction. As Nina described, it is very important to find a electrode material that does not create paramecium-toxic biproduct with electrochemical degridation, when a current is run through. We used pencil lead, connected with copper tape to our arduino-controled power source .
Finally, we placed our assembled device under a microscrope and pippetted the paramecia onto the center opening. We had unforseen trouble visualizing them because the laser-cutting created a rough surface to the bottom of the well. Thus, the acrylic was not optically clear enough for the microscope to see through. Back to the drawing board!
Here are some example of more developed playgrounds. With visual tracking, they are able to be iphone games.
Problem 1: Design considerations for electrical stimulation systems. Below appears an oscilloscope reading for a stimulus waveform from commercial stimulator. When a bioreactor is attached (pink), the stimulus waveform (blue) is no longer faithfully applied.
Problem 2: Morphological changes associated with electrical stimulation. Below appears Human adipose derived stem cells (hASCs) which were exposed to direct-current electrical stimulation for a period of 4 hours (from Tandon et al IEEE 2009).
Problem 3: Design considerations for perfusion bioreactors.
Fiorenzo Omenetto, Benedetto Marelli (SilkLab, Tufts University)
Biofabrication has taken the nation by storm. Only a week ago, the second-ever BIOFABRICATE summit in NYC showcased a menagerie of organisms, yeast and bacteria to mushrooms and mammalian cells, which have been coaxed into growing disruptive materials of the future.
Fiorenzo Omenetto and Benedetto Marelli, from SilkLab at Tufts University, have long been at this work; unlocking new properties from an age-old biomaterial, silk. They describe, the guiding principle is to reinvent structural biopolymers into high-technological materials through basic principles of materials science, advanced fabrication and ingenuity.
The duo shared their developed method for biopolymer ‘regeneration’, i.e. liquidizing spun cocoons, and reforming into new solids with new uses. The proteins characteristically self-assemble.
In this way, silk can be re-engineered to serve at the interface between the biotic and abiotic world. Optics. Biocompatability. Drug release. Furthermore, the natural origin of biopolymers also allows for the engineering of materials with remarkably low-energy processing and little environmental impact.
From this cocoon:
To this hologram:
Fiorenzo presents silk as a material platform technology! Enumerated forms and applications:
1. Regeneration of silk fibroin into an aqueous suspension (Refer to Step 1-23 in Rockwood et al. Nature Protocols, 6, 1612–1631 (2011)).
Pre-step! Making Baking Soda (Sodium Bicarbonate, NaHCO3)into Washing Soda (Sodium Carbonate, NaCO3). Heating at 400 degrees does the job to pop off that extra hydrogen.
We boilded the coccoons for 30 min in our 0.02 M Washing Soda solution. This denatures the outer seracin coating that adheres the two fibrion strands together. Thus, a few rinses and drying and we've got a big fluffy knot!
Preparation of the Lithuim Bromide (LiBr) required us to brush off some old stocheometry; also- exothermic, it should be prepared on ice. Next, the addition of LiBr to our tightly packed silk to solubilize the proteins.
During 4 hr incubation, the silk disolves into a golden syrup. We must inject this into a dialysis cassette, and filter via submersion in DI water for 48 hours.
Cleaned up, the biopolymer is ready to rock. It can be poured out into flat sheets (below). It can pick up the fine grooves of a hologram or even loaded into a addative printer.
2. Fabrication of an edible, implantable, biodegradable diffraction grating through soft lithography (please, refer to Step 25H in Rockwood et al. Nature Protocols, 6, 1612–1631 (2011) in background reading).
3. Superfab Assignment - Biomanufacturing in 3D Using the silk suspension obtained in Assignment #1 in combination with a XYZ dispensing system for the 3D printing of silk fibroin
Kevin Esvelt (Wyss Institute)
Kevin Esvelt, is a research scientist of the Wyss Institute *(recently inducted as faculty at MIT Media Lab), is a fascinating voice within the burgeoning CRISPR/Cas-9 community. He is outspoken on the technical potential of this newfound genome editing and an even more outspoken on the ethical, political and safeguard considerations surrounding Synthetic Gene Drive. He’ got an itch for ecological engineering.
Gene drive, derived in by Burt 2003in relation to “selfish” genes, occurs when a DNA sequence ensures that is inherited more often than normal. In this case the sequence of DNA can spread itself through subsequent population, regardless of its expense to the organism’s survival or reproductive fitness.
Kevin explains that the synthetic induction of gene drive was not possible until recently.Typically, if a genetically modified organism were released into the wild, little would happen because of the golden rule:
“Because wild organisms have been selected for efficient reproduction in their ancestral habitat, altering them almost always decreases reproduction. Hence, releasing engineered or selectively bred organisms into the wild has little if any lasting impact because natural selection weeds out the human-made changes.”
Survival of the fittest 101.
However he proposes CRISPR/Cas9 genome editing has a distinct ability to build gene drives. If inherited by one parent, it actually ‘reaches over’ to edit the inherited genes of the other parent, to convert heterozygotes into homozygotes which are guaranteed to pass the RNA-guided gene drive to all of their progeny. Wow!
Scary? Consider that the technology has potential to be a much more refined solution than some of the ‘blunt instruments’ we unheedingly use now, with severe ecological impact, like globally toxic chemical pesticides. CRISPR could alter characteristics in animal or insect populations’ that cause them to be agricultural pests or disease vectors, without exterminating them and creating voids in the ecosystem. Insects that think corn tastes icky? Fruit bats with Ebola resistance, anyone? Unintended consequences??
So, CRISPR Gene Drive: risky ecological medalling or a valuable tool in minimizing environmental and man-made problems? When is it applicable- and how.
What features would you want to see in an online discussion platform devoted to guiding the development of gene drives? Assume that the researchers involved in the project are interested in soliciting public feedback before and during experiments so that they can better identify problems and redesign the technology.
Please give specific examples of already-existing elements – if you want a discussion forum, should it be more like reddit, Quora, or something else? What should moderation be like?
What would it take to get you to regularly participate in such a community?
In the case of a new technology as controversial as CRISPR gene drives, public discussion is extremely important to maintain, but must be well structured and handled delicately. Online discussion boards are notoriously places where the societal norms of sensible dialogue unravel into derisive ‘online comment culture’, spurred by anonymity (They’re science on that.). The simmering international debate over GMO foods creates an intense backdrop for the Gene Drive discussion to enter.
Furthermore, Scientists and the public are going to be challenged to communicate information from their specific spheres to general audience. There are going to be technical as well as cultural challenges in understanding. Scientists are proposing engineered modifications to an infinitely complex environment, which the General Public is ‘immersed’ in. They are actively making assumptions about intended and unintended consequence to the ecological ‘system’, yet may have blind spots or lack resolution that people ‘on the ground’ (i.e. farmers) may be well acquainted with. The platform should level the assigned positions of ‘expert’ versus ‘lay person’, in order to equalize power distribution in dialogue.
I propose a platform that can provide never before seen levels of immersive, interpersonal contact to not only engage scientists and the general public, but also fully contextualize the ‘worlds’ and ’lives’ of the participants involved. If the CRISPR campaign is looking to provide disruptive solutions to farming ecology, there should be equal knowledge and skill transfer disseminating from the daily walks of farmers to the scientists, and not just the other way around.
Thus, I think we can support disruptive technology with disruptive technology. Eyeing the $2B acquisition of Oculus Rift by FB, and Go-Pros- I see an online platform that can support video streaming onto virtual reality piping in from around the world, like a human-network equivalent of the Google Maps vehicle.
Humanized communication engineering for prospective ecological engineering. Crazy- but maybe they have some tricks at the Media Lab to help us out.
Identify a problem that could be addressed using a CRISPR gene drive.
Which organism would you target and how would you alter it? Why is a gene drive a good solution relative to other options?
What could go wrong? Don't go into detail, but list several possibilities. Who should be involved in the discussion of whether to consider this application? Design a basic but evolutionarily stable gene drive that should function in your organism.
The Gypsy Moth (Lymantria dispar) is an important economic pest that causes large-scale damage to agricultural crops, forests, and humans worldwide. That's why it has drawn the attention of olfactory receptor research as a form of pest management. A potential application for gene drives is an olfactory receptor gene suppression that would alter the species odorant binding affinities at a population level to no longer be able to detect its target crop.
Optimally, the gypsy moth can exist in its natural ecosystem carrying out its ecological niche without acting as a pest to agricultural crops. Realistically, a modification like this may create an unfit moth, leading to species supression and major ecological disruption. For one, the Gypsy moth uses its olfactory receptors also for mating, which means that altering the target odorant repertoire could putatively render them unable to detect their mates. Possibly, the gene drive would not be effective, and thus not catastrophic, as by inhibiting mating we are essentially stripping the ability of the drive to be passed to the next generation.
Your goal is to design an experiment that will determine whether CRISPR gene drives can function efficiently in the target organism. Your drive system should not cause population suppression, carry any 'cargo' genes, or change the sequence of any protein produced by the organism. It should only spread itself.
Sean Kearney (MIT, Alm Lab) and Professor Neri Oxman (MIT Media Lab)
Emerging from a crazy week of ecological engineering, our fearless leader, David Kong, accompanied by Sean Kearney from Alm Lab at MIT and Professor Neri Oxman from MIT Media Lab, discuss an **intestinal** track on the human gut microbiota. This is in fact one of the most densely populated ecosystems of microorganisms on earth.
With an estimated 100 trillion microorganisms, the gut is an extraordinarily complex system in which we are beginning to elucidate both microbe-microbe and microbe-host interactions. With plummeting costs for sequencing, we are finally able to closely inspect and confirm correlations of nutrition, disease, and even cognition to the chemo-signals shared with our gut buddy composition.
The gradual adoption fecal matter transplants (FMTs) as a socially acceptable treatment for infectious disease has allowed microbes to emerge as a unique therapeutic in our modern medical world. As a growing fascination, it is also emerging in pop-culture.
Sean and David are involved with some of the newest research on model systems, to both prototype and study complex polymicrobial systems. Their work overlaps with that of Neri Oxman, the designer of a novel wearable microbiota ecosystem.
This technological statement piece suggests a synthetically engineered symbiotic relationship completely unique unto itself; beautifully displaying the mixing of cyanobacteria to harness the energy of light into sugar, with modified E.coli to consume the sugar in the generation of some product for the wearer.
3D print a 14 mL culture tube in at least one material. Culture a bacterial strain of your choice in this tube and compare the growth rate (optical density) over time versus a polystyrene control tube. Ideally use a strain featuring antibiotic resistance and culture in the presence of an antibiotic.
Tube and cap design files.
We 3D printed the design in 4 different materials:
First, we planned our procedure for creating a standard bacterial growth curve. E.coli cells were taken from frozen aliquot and incubated for 12 hrs to stabilize as a liquid culture stock. WAKE UP!
The next day, we prepared each candidate test tubes with 3mL LB-Ampicillin and inoculated them simultaneously with 3uL stock (1:1000 ratio). We put the tubes in the shaking incubator at 37 degrees.
At given time points, we loaded a fraction of each tube’s culture sample into a cuvette, and measured the absorbance in the spectrophotometer. This number, the O.D. (Optical Density), is measurement of light shown through the side of the square cuvette. It is a common indices of how densely populated the bacterial culture is.
Growth Curves typically have an S-shape, an exponential growth phase from around OD 4.0 – 8.0. The lag phase prior shows accelerating growth, while the stationary phase after occurs when growth slows (due to space and energy resource limitations). Below are the resulting growth curves for our different materials.
Extra Credit: Culture multiple combinations of tube materials and strains, comparing growth rates for each against polystyrene.
Design a milli- or micro-fluidic 'artificial gut' or other 'organ-on-a-chip' device to be utilized, at a minimum, for cell culture. Feel free to design your device in 2D-CAD software or vector drawing tool (e.g. Adobe Illustrator, AutoCAD) or 3D design tool (e.g. Rhino, SolidWorks).
Srivatsan Raman (University of Wisconsin-Madison)
Srivatsan Raman, from University of Wisconsin-Madison, works on synthetic and systems biology, protein design, and the developments of protein science with computational techniques. In fact, he emphasized that if we were to come away from this lesson with one thing, it would be a respect for the shear amount of computational *OOompHF* niomolecular simulations and modeling requires. We did have to leave our computers running all night...
Proteins are defined by their amino acid sequence, and the way they snap up into a folded shape in 3D space. The latter is the major determinant and predictor of protein function (i.e. binding sites, activation sites, etc.). It can be predicted as a lowest energy form, but the inticacies and non-static nature of proteins make this complex, fast.
Computational protein modeling has achieved unprecedented accuracy in predicting protein structures at atomic-level accuracy, making major advances in protein science. Not a minute too soon, because protein databases are filling up with known proteins sequences at a rate faster than we could ever catch up using experimental methods (i.e. x-ray crystallography) to predict structure and shape. These powerful tools can even design proteins as biocatalysts, with new binding partners and self-assembling materials.e. binding sites, activation sites, etc.).
In class, we learned computational methods for modeling protein structures and interactions, including the tools in Rosetta protein modeling suite. It works by creating hundreds of possible folded posibilities and assigning each an energy score. Plodding a slow walk toward the lowest energy form.
Rossetta has its place, but we are also fond of FoldIt, protein folding GAME! (Above.)Computers are good at large scale topology computation, but in all honesty, there is indispensable value to human intuition. This game you can manipulate and fold the proteins with your own hands, while you compete with high-scorers around the world to discover the protein structure!
We will run the Rosetta protein structure prediction simulations and analyze the results, in order to get an understanding of how computational protein modeling works. This includses looking at protein structures using a viewer (PyMol or Chimera or Rasmol).
First, we must pick one of the test cases to run structure prediction calculations. We picked 2HFQ.
Then, generate models using AbInitio folding in Rosetta. Once the code is set, we just say the magic words:
and the program will boot and run until it has made 100 models, aaaaaaall night.
Pick the lowest energy model and structurally compare it to the native. How close is it to the native? If its different, what parts did the computer program get wrong? You'll have to compare the structures using a Viewer like pymol or chimera or rasmol.
Native conformation of 2HFQ protein (left) versus the minimum energy structure prediction (right), in PyMol viewer.
Pick the lowest rms model and structurally compare it to the native. How close is it to the native? If its different, how is it different? Remember that in a blind case, we will not have the benefit of an rms column.
Native conformation of 2HFQ protein (left) versus the lowest rms model prediction (right), in PyMol viewer.
David Sun Kong (MIT), Will Canine (Opentrons), and Julie Legault (Amino).
This week, David Kong spoke about some of the current efforts towards the development of hardware platforms. Synthetic biology requires great hardware. Every synthetic biology experiment utilizes a variety of hardware, from liquid handling systems to centrifuges to culture machines and microscopes.
David presents an interesting incentive to create tools that are open source and accessible. From an industry that is traditionally exclusive to individuals in large institutions that can support high capital equipment, these are big moves. Why? For a more diverse community of 'next gen' syn-engineers. A publication in a sociology journal which David showed us actually demonstrates increased 'innovative breakthrough' from people in the 'outer edge' of a field who bring in more diverse skill sets; especially women.
Some of our favorite syn-biologists hail from from far out places, like Drew Endy from Civil Engineering and comic book land! (...who may or may not have been associated with this shirt, the one time I met him )
David's been working on a Ring mixer Chip : a microfluidic system geared towards making high throughput cloning as tiny, cheap and automated as possible. It is an Arduino system with 32 tiny manifolds of solenoid valves, which are choreographed in different ways to perform four basic functions; (1) fill, (2) mix, (3) incubate and (4) flow – a good start for any biological protocol. The ring where all the action happens is only 15nL in volume! Prototype1 cost +$1000, but hopefully it gets cheaper or I get paid more money soon.
We also enjoyed tales from guest lecturers Julie Legault of Amino, and Will Canine of Opentrons speak about their hardware projects turned start up companies (blasting off or Indiegogo and Kickstarter).
[Amino.ONE], for you to take care of and love in your home.
[OT.One], accelerating and empowering research.
Amino One , a laptop-sized platform with some inspiration from Tamagachi keychains us 90's kids know so well.It is meant to easily enables anyone to grow living cells to create new and interesting things - like fragrances, flavours, materials, medicine, and more.
The OT.One liquid handling robot, the core of OpenTrons' rapid-prototyping platform. Affordable and easy-to-use, it is a huge reprieve from the time we spend manually moving around tiny amounts of liquid. Lower error rate, more epic bio accomplished!
During this week, we have to create our own open hardware!