A team of researchers at MIT has developed a technique to integrate both analogue and digital computation in living cells, allowing them to form gene circuits capable of carrying out complex processing operations.
Living cells are capable of performing complex computations on the environmental signals they encounter.
These computations can be continuous, or analogue, in nature — the way eyes adjust to gradual changes in the light levels. They can also be digital, involving simple on or off processes, such as a cell’s initiation of its own death.
Synthetic biological systems, in contrast, have tended to focus on either analogue or digital processing, limiting the range of applications for which they can be used.
The synthetic circuits are capable of measuring the level of an analogue input, such as a particular chemical relevant to a disease, and deciding whether the level is in the right range to turn on an output, such as a drug that treats the disease.
In this way they act like electronic devices known as comparators, which take analogue input signals and convert them into a digital output, according to Timothy Lu, an associate professor of electrical engineering and computer science and of biological engineering, and head of the Synthetic Biology Group at MIT’s Research Laboratory of Electronics, who led the research alongside former microbiology PhD student Jacob Rubens.
A startup company, Synlogic, is aiming to create a new class of medicines, by re-programming bacteria found in the gut as “living therapeutics.” In March, 2016, Synlogic raised an additional $40 million in venture capital and secured its first industry partnership with pharmaceutical giant AbbVie.
Synlogic is working with Abbvie to create innovative synthetic biotics for the treatment of certain forms of inflammatory bowel disease (IBD) such as Crohn’s disease and ulcerative colitis.
Synlogic engineers synthetic biotics, a new class of medicines designed from natural probiotic bacteria that are programmed with exquisite precision to correct disease-causing metabolic dysregulation while operating within the microbiome
Two of Synlogic’s main candidate drugs, expected to enter clinical trials during the next 12 months, treat rare genetic metabolic disorders. One drug candidate is for treating urea cycle disorder (UCD), which is caused by an enzyme deficiency that leads to a buildup of toxic ammonia in the blood. The other is for treating phenylketonuria (PKU), which involves a dangerous excess of the amino acid phenylalanine due to a mutation in another metabolic enzyme. In both cases, Synlogic’s drugs process and flush out the toxic metabolites from the body.
Local programming of the microbiome using synthetic biology enables therapeutic impact throughout the body. Synlogic achieves the therapeutic programming of synthetic biotics by engineering the bacteria to carry specialized assemblies of DNA, called genetic circuits. Genetic circuits are built using synthetic biology methods and components from our proprietary platform. The genetic circuits allow the synthetic biotic to sense a patient’s internal environment and respond by turning an engineered metabolic pathway on or off. When turned on, the synthetic biotic completes all of the necessary, programmed biochemical steps in a metabolic pathway to achieve therapeutic effect.
They engineer synthetic biotics from probiotic bacteria.
The human microbiota consists of hundreds of trillions of symbiotic microbial cells that live within and on each of us. The human microbiome are the quadrillion genes of those cells. To put these numbers into perspective, there are 10 times more microbial cells than human cells and 100 times more microbial genes than human genes in each of us. The role of human microboime as an agent of health and a potential avenue for therapeutic intervention is rapidly evolving.
Many scientists are beginning to regard the microbiota that resides in the gut as an additional human organ, albeit an organ who’s function is still emerging. It weighs as much as many organs somewhere between two and six pounds, is highly organized, and carries out functions essential to our health.
“Most of the work in synthetic biology has focused on the digital approach, because [digital systems] are much easier to program,” Lu says.
However, since digital systems are based on a simple binary output such as 0 or 1, performing complex computational operations requires the use of a large number of parts, which is difficult to achieve in synthetic biological systems.
“Digital is basically a way of computing in which you get intelligence out of very simple parts, because each part only does a very simple thing, but when you put them all together you get something that is very smart,” Lu says. “But that requires you to be able to put many of these parts together, and the challenge in biology, at least currently, is that you can’t assemble billions of transistors like you can on a piece of silicon,” he says.
The mixed signal device the researchers have developed is based on multiple elements. A threshold module consists of a sensor that detects analogue levels of a particular chemical.
This threshold module controls the expression of the second component, a recombinase gene, which can in turn switch on or off a segment of DNA by inverting it, thereby converting it into a digital output.
If the concentration of the chemical reaches a certain level, the threshold module expresses the recombinase gene, causing it to flip the DNA segment. This DNA segment itself contains a gene or gene-regulatory element that then alters the expression of a desired output.
“So this is how we take an analogue input, such as a concentration of a chemical, and convert it into a 0 or 1 signal,” Lu says. “And once that is done, and you have a piece of DNA that can be flipped upside down, then you can put together any of those pieces of DNA to perform digital computing,” he says.
The team has already built an analogue-to-digital converter circuit that implements ternary logic, a device that will only switch on in response to either a high or low concentration range of an input, and which is capable of producing two different outputs.
In the future, the circuit could be used to detect glucose levels in the blood and respond in one of three ways depending on the concentration, he says.
“If the glucose level was too high you might want your cells to produce insulin, if the glucose was too low you might want them to make glucagon, and if it was in the middle you wouldn’t want them to do anything,” he says.
Similar analogue-to-digital converter circuits could also be used to detect a variety of chemicals, simply by changing the sensor, Lu says.
The researchers are investigating the idea of using analogue-to-digital converters to detect levels of inflammation in the gut caused by inflammatory bowel disease, for example, and releasing different amounts of a drug in response.
Immune cells used in cancer treatment could also be engineered to detect different environmental inputs, such as oxygen or tumor lysis levels, and vary their therapeutic activity in response.
Other research groups are also interested in using the devices for environmental applications, such as engineering cells that detect concentrations of water pollutants, Lu says.
Ahmad Khalil, an assistant professor of biomedical engineering at Boston University, who was not involved in the work, says the researchers have expanded the repertoire of computation in cells.
“Developing these foundational tools and computational primitives is important as researchers try to build additional layers of sophistication for precisely controlling how cells interact with their environment,” Khalil says.
Living cells implement complex computations on the continuous environmental signals that they encounter. These computations involve both analogue- and digital-like processing of signals to give rise to complex developmental programs, context-dependent behaviours and homeostatic activities. In contrast to natural biological systems, synthetic biological systems have largely focused on either digital or analogue computation separately. Here we integrate analogue and digital computation to implement complex hybrid synthetic genetic programs in living cells. We present a framework for building comparator gene circuits to digitize analogue inputs based on different thresholds. We then demonstrate that comparators can be predictably composed together to build band-pass filters, ternary logic systems and multi-level analogue-to-digital converters. In addition, we interface these analogue-to-digital circuits with other digital gene circuits to enable concentration-dependent logic. We expect that this hybrid computational paradigm will enable new industrial, diagnostic and therapeutic applications with engineered cells.
SOURCES- Synlogic, MIT News, Nature Communications