Computational systems as diverse as vending machines, computers, and cells have something in common: They are all finite-state machines. That is, they may have an initial state, accept inputs, pass to different states according to the inputs received, and even enter states that lead to specific outputs. This kind of activity has been exploited in cells, but not with the degree of control we take for granted with the humble vending machine, which can dispense the right snacks depending on whether we press, say, B4 or C2. The vending machine can even refuse to dispense anything until a certain threshold has been surpassed (the right combination of coins).
In hopes of installing this kind of control into cells, MIT scientists have developed a way to program cells to respond to up to three different inputs. Crucially, the programming is capable of recognizing the order of inputs and responding accordingly. Although three inputs permit just 16 states, the MIT researchers point out that their method is scalable. It could accommodate additional inputs and thereby enable many additional states, enough to permit complex processes such as disease progression and cell differentiation to be tracked. The new synthetic biology approach could even make it possible to intervene in these processes, leading to cancer therapies or guiding the outcome of stem cell development.
Details of the new approach appeared July 22 in the journal Science, in an article entitled, “Synthetic Recombinase-Based State Machines in Living Cells.” The article describes how MIT scientists led by Timothy Lu, Ph.D., followed up on earlier work in which cell circuits were designed that could perform a logic function and then store a memory of the event by encoding it in DNA.
In the new paper, the MIT scientists designed state machine circuits that rely on enzymes called recombinases. When activated by a specific input in the cell, such as a chemical signal, recombinases either delete or invert a particular stretch of DNA, depending on the orientation of two DNA target sequences known as recognition sites. The stretch of DNA between those sites may contain recognition sites for other recombinases that respond to different inputs. Flipping or deleting those sites alters what will happen to the DNA if a second or third recombinase is later activated. Therefore, a cell's history can be determined by sequencing its DNA.
The MIT scientists programmed Escherichia coli cells to respond to substances commonly used in lab experiments, including ATc (an analogue of the antibiotic tetracycline), a sugar called arabinose, and a chemical called DAPG. Such programming could be used with other inputs, such as acidity or the presence of specific transcription factors. In addition, cells could be programmed to not only provide a convenient readout of successive states, but also to enable the complex regulation of gene expression.
“We validated our framework by engineering state machines in Escherichia coli that used one, two, or three chemical inputs to control up to 16 DNA states,” wrote the authors of the Science paper. "These state machines were capable of recording the temporal order of all inputs and performing multi-input, multi-output control of gene expression. We also developed a computational tool for the automated design of gene regulation programs using recombinase-based state machines.”
The researchers tested their approach with three genes that code for different fluorescent proteins—green, red, and blue—constructing a circuit that expressed a different combination of the fluorescent proteins for each identity and order of two inputs. For example, when cells carrying this circuit received input A followed by input B they fluoresced red and green, whereas cells that received B before A fluoresced red and blue.
Dr. Lu's lab now hopes to use this approach to study cellular processes that are controlled by a series of events, such as the appearance of cytokines or other signaling molecules, or the activation of certain genes. "You can build very complex computing systems if you integrate the element of memory together with computation," noted Dr. Lu, who is senior author of the current study.
"This idea that we can record and respond to not just combinations of biological events but also their orders opens up a lot of potential applications,” added Nathaniel Roquet, an MIT graduate student who is also the paper’s lead author. "A lot is known about what factors regulate differentiation of specific cell types or lead to the progression of certain diseases, but not much is known about the temporal organization of those factors. That's one of the areas we hope to dive into with our device," Roquet says.
For example, scientists could use this technique to follow the trajectory of stem cells or other immature cells into differentiated, mature cell types. They could also follow the progression of diseases such as cancer. A recent study has shown that the order in which cancer-causing mutations are acquired can determine the behavior of the disease, including how cancer cells respond to drugs and develop into tumors. Furthermore, engineers could use the state machine platform developed here to program cell functions and differentiation pathways.
MIT engineers have developed biological computational circuits capable of both remembering and responding to sequential input data.
The group's work, which is described in this week's issue of Science, represents a critical step in the progression of synthetic biology with the integration of DNA-based memory, in particular, pointing the way toward building large computational systems from biological components—computing devices that are living cells—and, ultimately, programming complex biological functions.
More specifically, Nathaniel Roquet and colleagues at MIT's Synthetic Biology Group were able to implement within a living cell what's known as a state machine: an abstract mathematical model describing computation as a list of of distinct internal states paired with an associated list of operations (or machine inputs) required to transition from state to state. So: a new state is always the result of an old state taken in combination with new inputs (history matters). State machines happen to describe a very large number of different things, from natural language processing algorithms to neurological systems to something as simple as a vending machine.
In a living cell, DNA is the natural candidate for storing state information. After all, that's what DNA does: store information. What Roquet and co. have created is a framework for chemically manipulating DNA such that states are encoded in DNA sequences. As a storage mechanism, this allows for both conveniently reading out a given state via genetic sequencing and also regulating gene expression via state transitions. In other words, the states can be linked to cellular behavior. The DNA serves as the memory for the state machine. The rest is in how, specifically, the DNA is manipulated and what effect that has on cellular behavior.
This could mean integrating biological state machines into tumor models, where they may be used to genetically surveil the activation of genes that may cause cancer In their experiments, Roquet and co. programmed E. coli cells to react to several substances commonly used in biological laboratory experiments, including an analogue of the antibiotic tetracycline, a sugar called arabinose, and a chemical called DAPG that helps plants protect their roots from pathogens. The cells could be reprogrammed to other inputs as needed, however.
The actual cell behavior being programmed by the researchers was the expression of genes coding for the production of different fluorescent proteins representing different colors. With three different inputs they were able to produce 16 different combinations of colors.
"Synthetic state machines that record and respond to sequences of signaling and gene regulatory events within a cell could be transformative tools in the study and engineering of complex living systems," Roquet writes. In other words, by implementing a state machine (a computer) in a living cell, it's possible to use that state machine to surveil otherwise impossible-to-observe cellular happenings.
For example, progenitor cells (similar to stem cells) develop into differentiated cell types with specific functions thanks to transcription factors, proteins that help regulate gene expression in cells. Transcription factors have allowed researchers to program both progenitor cells to become certain specific types of functional cells—and also to do the opposite, programming functional cells to behave as undifferentiated cells. However, much about the process remains mysterious. A state machine that could record the DNA transitions resulting from TF activation could go a long way toward not only understanding these processes, but manipulating them as well. The circuits in the biological state machine are dependent on enzymes called recombinases. These enzymes are activated by various inputs into a cell, such as chemical signals, and act to tweak that cell's DNA. But the tweak that actually occurs depends on the orientation of two DNA sequences known as recognition sites. The important thing is that the effect of changing any two recognition sites (the resulting cellular behavior) depends on how other recognition sites have been altered previously. Hence, memory.
There's really no shortage of potential applications here. The example Roquet gives is in integrating biological state machines into tumor models, where they may be used to genetically surveil the activation of oncogenes (genes that may cause cancer) and deactivation of tumor suppression mechanisms in individual cells.
"This idea that we can record and respond to not just combinations of biological events but also their orders opens up a lot of potential applications," Roquet offers in a statement. "A lot is known about what factors regulate differentiation of specific cell types or lead to the progression of certain diseases, but not much is known about the temporal organization of those factors. That's one of the areas we hope to dive into with our device."
Computers have become "alive," but perhaps not in the way that many of us anticipated. A unicellular organism itself won't ever be packing much computational horsepower, but considered as a building block, the potential is pretty wild.
"Silicon-based invention is tiny, soft, wirelessly functional
In the campy 1966 science fiction movie “Fantastic Voyage,” scientists miniaturize a submarine with themselves inside and travel through the body of a colleague to break up a potentially fatal blood clot. Micro-humans aside, imagine the inflammation that metal sub would cause.
Ideally, injectable or implantable medical devices should not only be small and electrically functional, they should be soft, like the body tissues with which they interact. Scientists from two UChicago labs set out to see if they could design a material with all three of those properties.
The material they came up with, the subject of a study published June 27 in Nature Materials, forms the basis of an ingenious light-activated injectable device that could eventually be used to stimulate nerve cells and manipulate the behavior of muscles and organs.
“Most traditional materials for implants are very rigid and bulky, especially if you want to do electrical stimulation,” said Bozhi Tian, an assistant professor in chemistry whose lab collaborated with that of neuroscientist Francisco Bezanilla, the Lillian Eichelberger Cannon Professor of Biochemistry and Molecular Biology.
The new material, in contrast, is soft and tiny, composed of particles just a few micrometers in diameter—far less than the width of a human hair—that disperse easily in a saline solution so they can be injected. The particles also degrade naturally inside the body after a few months, so no surgery would be needed to remove them."
David Baker appreciates nature’s masterpieces. “This is my favorite spot,” says the Seattle native, admiring the views from a terrace at the University of Washington (UW) here. To the south rises Mount Rainier, a 4400-meter glacier-draped volcano; to the west, the white-capped Olympic Mountain range.
But head inside to his lab and it’s quickly apparent that the computational biochemist is far from satisfied with what nature offers, at least when it comes to molecules. On a low-slung coffee table lie eight toy-sized, 3D-printed replicas of proteins. Some resemble rings and balls, others tubes and cages—and none existed before Baker and his colleagues designed and built them. Over the last several years, with a big assist from the genomics and computer revolutions, Baker’s team has all but solved one of the biggest challenges in modern science: figuring out how long strings of amino acids fold up into the 3D proteins that form the working machinery of life. Now, he and colleagues have taken this ability and turned it around to design and then synthesize unnatural proteins intended to act as everything from medicines to materials.
Synthetic biology is increasingly used to develop sophisticated living devices for basic and applied research. Many of these genetic devices are engineered using multi-copy plasmids, but as the field progresses from proof-of-principle demonstrations to practical applications, it is important to develop single-copy synthetic modules that minimize consumption of cellular resources and can be stably maintained as genomic integrants. Here we use empirical design, mathematical modeling, and iterative construction and testing to build single-copy, bistable toggle switches with improved performance and reduced metabolic load that can be stably integrated into the host genome. Deterministic and stochastic models led us to focus on basal transcription to optimize circuit performance and helped to explain the resulting circuit robustness across a large range of component expression levels. The design parameters developed here provide important guidance for future efforts to convert functional multi-copy gene circuits into optimized single-copy circuits for practical, real-world use.
gro is a language for programming, modeling, specifying and simulating the behavior of cells in growing microcolonies of microorganisms. The simulator models cell growth, cell division, intrinsic and extrinsic noise, diffusing molecular signals, microchemostats, chemotaxis, and more. The gro framework is intended to be used in synthetic biology to prototype distributed, multicell behaviors and check that, logically, the local interaction rules you specify produce the desired global result. The language allows behaviors to be specified at whatever level of abstraction makes sense: from high level code, to low level biomolecular interations. The gro framework has been also been used in the classroom, at UW and elsewhere, to teach synthetic biology to engineers. If you would like to learn more about gro, start by reading the documentation (see the link at the left). The tutorial, in particular, describes many of the main features of gro. For examples, click on the Gallery link on the left, or visit our youtube channel! Publications S.S. Jang, K.T. Oishi, R.G. Egbert, and E. Klavins, "Specification and simulation of multicelled behaviors", ACS Synthetic Biology, July, 2012. Tutorial Slides Writing programs, modeling protein expression, working with data. (pptx), (pdf) Controlling the simulation, chemostats, program composition. (pptx), (pdf) Signals and reaction/diffusion equations. (pptx), (pdf) Saving frames and making movies. (pptx), (pdf)
Nature provides a wide range of inspiration for building mobile micromachines that can navigate through confined heterogenous environments and perform minimally invasive environmental and biomedical operations. For example, microstructures fabricated in the form of bacterial or eukaryotic flagella can act as artificial microswimmers. Due to limitations in their design and material properties, these simple micromachines lack multifunctionality, effective addressability and manoeuvrability in complex environments. Here we develop an origami-inspired rapid prototyping process for building self-folding, magnetically powered micromachines with complex body plans, reconfigurable shape and controllable motility. Selective reprogramming of the mechanical design and magnetic anisotropy of body parts dynamically modulates the swimming characteristics of the micromachines. We find that tail and body morphologies together determine swimming efficiency and, unlike for rigid swimmers, the choice of magnetic field can subtly change the motility of soft microswimmers.
Chinese scientists are embarking on what appear to be the first human trials with the Crispr gene editing tool, the latest effort by the country’s researchers to master a technology that might someday be a potent tool in developing therapies worldwide.
Finite state machines are logic circuits with a predetermined sequence of actions that are triggered depending on the starting conditions. They are used for a variety of devices and biological systems, from vending machines to neural circuits. Roquet et al. have taken a finite state machine approach to control the expression of integrases, or enzymes that insert or excise phage DNA into or out of bacterial chromosomes. The integrases altered the DNA sequence of a plasmid to record all five possible combinations of two inputs. Such circuits can be used to record the states that the cell experienced over time and can be deployed in state-dependent gene expression programs.
We investigate the dynamics of the heterodimer autorepression loop (HAL), a small genetic module in which a protein A acts as an autorepressor and binds to a second protein B to form an AB dimer. For suitable values of the rate constants, the HAL produces pulses of A alternating with pulses of B. By means of analytical and numerical calculations, we show that the duration of A pulses is extremely robust against variation of the rate constants while the duration of the B pulses can be flexibly adjusted. The HAL is thus a minimal genetic module generating robust pulses with a tunable duration, an interesting property for cellular signaling.
In Redesigning Life, molecular pharmacologist John Parrington has produced a veritable compendium of games that scientists like him can play with life itself. He invites us to imagine the potential of life forms “whose very genetic recipe was manufactured in a chemistry lab using new components never seen before on Earth”. What larks!
What follows is a thorough and comprehensive account of the methodologies for altering life that have been or are being developed, and the directions that they may take in future. Those methodologies include the insertion or deletion of genes, the engineering of synthetic genes and the design of creatures unprecedented in nature. As Parrington shows, many of the technologies are familiar: for example, designing immunity to disease through vaccination, or animal and plant breeding. He ends with the concept of a “redesigned planet”, replete with new types of people, as well as designer babies, pets, plants and drugs. Invoking the catchphrase of comic-book superhero Spiderman, “with great power comes great responsibility”, he touches on the challenges that such a possibility would entail.
However, Parrington's way of dealing with the ethical issues raised by the technologies that he so gleefully explores is rather limited. Three examples give a sense of the nature of this problem.
Early on, he notes that in agriculture, it is important to ensure that genome editing benefits the majority of humanity rather than stuffing the coffers of vast corporations. But he fails to say how this might be achieved. Given that we cannot ensure this for any product or service in any field, I wonder what this criticism amounts to? Attempting global distributive justice is a major political problem of moral significance, but really, only governments can approach such utopian ideals. Demanding the impossible can never be rational ethics.
Later, Parrington worries about designer babies engineered for looks, intelligence or extraordinary talent (opining, “Such fears run deep among scientists”). But he offers not a word about the cogency of the fears, or about the moral basis — or lack of it — for how people see things. Parrington also questions the use of stem-cell technology in helping older women to have children: “Would this be seen as liberating or an irresponsible extension of a woman's reproductive age?” However, how it would be seen is a sociological question. The ethical responsibility involves showing how it should be seen, and why.
“Why might it be better to increase intelligence by education, diet or exercise than through gene editing?”
Science is a collective effort, but human nature — including that of people who sit on grant committees and decide prizes — tends to select and reward individuals. Hence the popular parlour game among scientists: speculating on who will get the Nobel prize for impressive discoveries.
They don’t come much more impressive than a molecular-biology technique that has swept through laboratories in the past few years, accelerating genetic research and tantalizing the public with its potential to change how genetic diseases are treated. As a result, the scientists who helped establish the technique — which rewrites DNA using a bacterial immune system called CRISPR–Cas9 — have received accolades and awards, and ample coverage in the media.
But the researchers who did much of the work — the graduate students and postdocs who carried out the experiments — are rarely mentioned. In this week’s Nature, we take a look at a small sample of those researchers and how their experience with CRISPR has affected their careers.
Our article is an attempt to grant these junior investigators a little of the limelight, but it also shows how difficult it is to do so: owing to space limitations, many young scientists who made important contributions to the field were left out of the article. (It is a decision that journalists face all the time, but it was made all the more painful in this case.)
A new programming language developed at the Massachusetts Institute of Technology (MIT) enables virtually anyone to take control of a bacteria cell's functions to generate plans for a genetically encoded circuit.
The new technique takes only moments to create the sequencing for a DNA-encoded circuit, which previously took years to create. It also is accessible to virtually anyone.
"You could be completely naive as to how any of it works; that’s what’s really different about this," says Chris Voigt, a professor of biological engineering at MIT. "You could be a student in high school and go onto the Web-based server and type out the program you want, and it spits back the DNA sequence."
The heart of Voigt's tool is Cello, a system that takes an electronic circuit created in a hardware description language called Verilog, and auto-converts it into plans for a DNA sequence. Once a researcher has the sequence, creating a new function for E. Coli, for example, is as simple as having a gene synthesis firm to cook up the new DNA sequence and inserting it into an E. coli cell.
Voigt and his team developed the tool in part to free up researchers from the generally laborious, multi-year task of developing DNA circuits. With Cello, researchers can instead focus on what they are really after: changing the way a cell functions. Programming bacteria to produce an anti-cancer drug when they detect a tumor; creating cells that can halt their own fermentation process if too many toxic by-products build up; altering bacteria to degrade oil when there is an oil spill—these are scenarios researchers now can pursue much more easily.
"It is literally a programming language for bacteria," Voigt says. "You use a text-based language, just like you’re programming a computer; then you take that text and you compile it and it turns it into a DNA sequence that you put into the cell, and the circuit runs inside the cell."
The prospect of giving everyone the ability to re-engineer life at the DNA level may seem frightening so some, but do not expect to see a modern-day Frankenstein monster emerge from a lab any time soon.
For starters, Voigt's tool currently only works on one, very simple life form: E. coli bacteria. Also, while the goal is to expand the tool's use to more complex life forms, getting there will take some doing.
"Some people have shown basic circuit functions in mammalian cells," Voigt says, "but we are a long ways from having the underlying principles that would be required to automate design."
Even if one can find a firm capable of generating a strand of DNA, "For a gene sequence of just 5,000 base pairs, that's $1,150 or more outsourced to, say, Genscript (a gene synthesis firm)," says Brian Hanley, founder of gene therapy firm Butterfly Sciences. "Genscript might get it to you in three to six months? You can get faster, but it'll cost you."
Voigt's work may one day be seen as a turning point in synthetic biology: the day when people who really have no idea what they are doing were given the ability to alter life at the DNA level.
That is fine if you are a scientist like Voigt, and your only ambitions are to improve things for everyone else. However, one wonders what would happen if a terrorist organization were to get wind of Cello and start playing around with the functions of E. coli to weaponize it in some fashion.
"I am sure that the first thought most people who understand the new technology might have is something along the lines of, 'if anyone can do it, what's to stop malicious people, or those too ignorant of molecular biology, from creating a DNA program with drastic consequences?'" says Steven Umbrello, managing director of the Willington, CT-based Institute for Ethics and Emerging Technologies.
As with most scientific developments, Umbrello says, it is all about maintaining the delicate balance of allowing researchers to do their work, while ensuring that work is not put to malicious use.
"Programming DNA circuits may now have become easier," Umbrello says. "But the manufacturing of the circuits, the devices themselves, could be themselves created with constraints to limit the production to produce predetermined outputs.
"Our laws must work hard to ensure that research and development can take place in science and engineering without putting an undue burden on them, while simultaneously making sure that there are enough 'teeth' in the statutes to ensure deterrence of malicious use."
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