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How would you use readthrough as part of a genetic circuit design?

How would you use readthrough as part of a genetic circuit design?



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Traditionally, in synthetic biology, researchers tried to avoid some transcription phenomena (like roadblocking of tandem promoters or readthrough of weak terminators) since they are not in line with the discipline's strive to design modular, digital genetic circuits. However, some researchers have started using these "problems" as part of the intended design (see Bordoy et al., for example).

How do you think transcriptional readthrough could be used as part of a genetic circuit design? When would you want to have a readthrough? What kind of logic or function would this emulate?


Readthrough has already been used to implement transcriptional NOR gates, wherein tandem input promoters express a repressor that represses an output promoter. (First time I recall here: 21150903, used widely here: 27034378, roadblocking modeled here: 32141239.) An advantage of this design is that the repressor need only be encoded in DNA once, which can significantly reduce the DNA footprint of the design and the likelihood of recombination if the repressor's DNA sequence is long (e.g., protein-based repressors). OR gates have similarly been implemented as two tandem promoters expressing a common output gene. (An alternative NOR design-which is common with repressors with short DNA sequences (e.g., sgRNAs)-is to duplicate the repressor and express it separately from both input promoters. This approach circumvents the roadblocking and input asymmetry that can occur with tandem promoters.)

Readthrough has also been used with antisense promoters to tune gene expression (see 26769567). In these designs, an input promoter must read through a downstream antisense promoter, and the strength of the antisense promoter can be used to tune the response of the input promoter.

Another application that comes to mind is encoding the relative ratio of expression of multiple genes by separating them with weak terminators (e.g., to achieve X-fold expression of the first gene relative to the second). This begins to evoke an operon, as jakebeal notes. The closest example I can think of comes from this paper: 23727987, although they actually used readthrough to address the inverse problem of characterizing terminator strength.


I think this is an interesting proposal to try to turn a problem into a benefit.

What you are considering is conceptually similar to the organization of an operon, in which multiple genes are controlled by a single promoter, with multiple ribosome binding site (RBS) entry points for translation, and read-through can certainly occur in these cases too. Structurally, this would be the same behavior, except that the entry points are promoters instead of RBSs.

At a logical level, in effect the second promoter ends up implementing one of two functions:

  • If it is positively regulated, then it would be an OR, activated either by its own transcription factor or read-through from the 5' sequence.
  • If it is negatively regulated, then it would a NOT IMPLY, activated by the 5' sequence, but dominated by its own repression, since steric repression mechanisms will tend to block the read-through as well.

There are lots of potential concerns regarding signal strength of the read-through, but if one wanted to make use of this mechanism there is no reason to think they would not be susceptible to engineering.


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Highlights

CRISPR is an incredibly useful tool for geneticists and microbiologists. Short for clustered regularly interspaced short palindromic repeats, it sounds intimidating on the basis of name alone. Yet it’s a tool that Annie Taylor—a senior applied and engineering physics major at Cornell University—uses extensively in her research. What she does with CRISPR showcases some of its powers.

“I can write out a nucleotide sequence on my computer, buy a custom-made DNA fragment for that sequence, and use it to program the CRISPR system to target practically any DNA sequence I want with high specificity.” She explains. Hearing how she uses it, it’s easy to imagine that CRISPR has had a tremendous impact in biological research, with applications in countless subdisciplines.

Creating Genetic Circuits to Operate Like Computer Circuits

Taylor conducts her research in Guillaume Lambert’s lab, Applied and Engineering Physics, which focuses on creating genetic circuits in cells—an application of CRISPR in synthetic biology. Genetic circuits are analogous to logic circuits in electrical engineering. Logic circuits are comprised of many logic gates they alter the voltage and current of a system as it passes through them. Similarly to how computers function, genetic circuits may eventually be used to perform complex logic functions in a cell.

Many types of logic gates perform a variety of functions. Taylor is working on a particular type of logic gate known as a NOT gate, or an inverter. The input of the gate is at a high voltage, while the output of the gate is at a low voltage (or vice versa). In electrical engineering, high voltage is represented by one, while low voltage is zero. A one at the input of a NOT gate would produce a zero at the output. The same is true the other way around.

In biological systems, there is no high voltage or low voltage. Instead, one and zero would correspond to high and low protein expression. A one would mean that a certain protein is expressed, while a zero would mean the protein is inactive.

“While the systems and the techniques are biological, a lot of the underlying theories of our work revolve around physics.”

In a cell, protein expression can be easily examined. One can insert marker genes such as the green fluorescent protein (GFP) gene. A cell that is expressing GFP will glow green in ultraviolet light or blue light, so one can tell whether or not GFP is being expressed by simply shining a blue light over the colonies. Taylor inserts these marker genes into a cell by inserting them into a plasmid, a structure that carries genetic information, which is then absorbed and incorporated into bacterial cells. The end result is a colony of cells that glows green in blue light. Taylor then uses the CRISPR system to target this inserted GFP gene.

How CRISPR Works

“The CRISPR system, in nature, is a bacterial immune system. Bacteria are trying to protect themselves from viruses, which are basically sequences of foreign DNA. They have to be able to recognize what genetic information is foreign and what genetic information is their own.”

To do this, bacterial cells produce Cas proteins, which bind to a guide RNA sequence. Then the Cas protein inspects any DNA it encounters. If any sequences on the DNA match with the guide RNA sequence, the Cas protein recognizes it as being foreign DNA and destroys it.

The most commonly used Cas protein for gene editing, Cas9, natively acts to cut DNA at the place where it is identical to the guide RNA sequence, but Cas9 can be modified in many ways. For instance, the Lambert lab often uses dead Cas9—known as dCas9)—which has been modified so that it is catalytically inactive. When it recognizes a DNA sequence, instead of cutting the DNA, dCas9 binds to that sequence and inhibits transcription. The target DNA sequence is not cleaved but becomes unable to express the protein for which it codes.

The power of the CRISPR system lies in the fact that one can modify the 20-base pair guide RNA sequence that the Cas9 protein binds to. If one knows a critical sequence of DNA on a gene of interest, they can create a corresponding guide RNA sequence that will cause the Cas9 protein to target that area of DNA. If it is dCas9 protein, then it will bind to that sequence of DNA and inhibit transcription, the expression of a protein at that site.

Taylor can design a guide RNA sequence that she knows will correspond to a sequence on one of the marker genes she inserts. For example, she can create a sequence of RNA that corresponds to a critical part of the GFP gene. Before she inserts the guide RNA sequence, the bacterial cells will express the GFP gene. Afterward when the dCas9 has bound to the RNA sequence, recognized the corresponding sequence on the DNA, and deactivated it, the colonies will no longer produce GFP and will no longer glow under ultraviolet light.

“There are a variety of Cas proteins,” Taylor explains. “Each Cas protein may have a different guide RNA structures or may deactivate genes in different ways. And while dead Cas9 inhibits transcriptions, there are other ways to modify Cas proteins to activate genes. It gives us control over which genes are expressed in a cell and which are inhibited.”

Creating Genetics Circuits

One of the aims of the Lambert lab is to use this control over gene expression in order to generate a genetic circuit. They want to develop a system in which they can submit certain inputs, and knowing how the logic gates in the cell will interact with the inputs, be able to obtain a predictable result.

Living systems are incredibly complex, however. Having multiple logic gates might cause them to interfere with each other’s function. The Lambert lab is working to understand the limitations of the system. How many logic gates can be inserted until their behavior is no longer predictable and stable? What are the off-target effects of the CRISPR system?

“If you have a genome that is millions or billions of base pairs long, there might be several locations that the Cas protein will unintendedly target, because they match the 20-base pair guide RNA sequence simply by chance,” Taylor says. “This might be disastrous for the cell, or the cell might appear to be unaffected. It just depends on where those off-target sequences are and what they code for.”

The Fusion of Physics and Biology

Taylor appreciates the intersection between sciences, which is the focus of the Lambert lab. She entered Cornell interested in aerospace engineering, yet in her senior year she has found a passion for combining physics and biology. Minoring in biological sciences, Taylor has been able to apply her coursework to her lab work.

“While the systems and the techniques are biological, a lot of the underlying theories of our work revolve around physics,” she says. She hopes to use the gene editing and manipulation tools that she has learned through her work with the Lambert lab in her future research.

CRISPR is both a scary name and a powerful tool, and as Taylor has learned through her work with the Lambert lab, its applications to scientific research are widespread. It has the potential to turn genetic loci into logic gates and cells into circuits, to turn proteins on or off at will, and to inform our growing knowledge of how cells—and life—function.


Introduction

Synthetic biologists use bottom-up approaches to assemble genetic parts into more complex gene circuits to enable the programming of new functions into cells. This approach combines individual gene expression parts, or modules, that can be characterized independently and used to build novel genetic circuits by combining multiple modules that interact with each other to perform a defined function in cells. The inception of synthetic biology started with engineering prokaryotes with novel functions [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18], and efforts to engineer mammalian cells soon followed. Mammalian synthetic biology has traditionally focused on transcriptional and post-transcriptional regulation to program cells with new functions. These efforts include programming feedback [19,20,21], controlling gene expression levels [22,23,24,25,26,27,28,29,30,31,32], implementing Boolean logic functions [33,34,35,36,37,38,39], and targeting specific disease states [40,41,42,43,44,45,46]. More recent approaches that target specific locations in the genome using zinc finger (ZF) proteins, transcription activator-like effectors (TALEs), and clustered regulatory interspaced short palindromic repeats (CRISPR) coupled with a modified Cas9 protein with its nuclease activity removed (dCas9), have been used to interrogate endogenous transcription factors [47,48,49,50,51,52,53,54,55,56]. These studies have enabled the interrogation of endogenous DNA sequences to better understand the role of natural transcriptional networks within cells to better understand how cells control these networks [57, 58]. The details of these genetic tools have been extensively reviewed elsewhere [59,60,61,62,63], therefore, here we aim to provide a framework for using genetic circuits to design new therapies by engineering tissues with alternative functions.

Pluripotent stem cells are cells that have the potential to produce any cell or tissue in the body.

In the early development of complex organisms, pluripotent stem cells undergo specialized decision-making in a remarkably ordered process to yield tissue patterns, morphogenesis, and organogenesis [64,65,66,67,68]. The underlying mechanisms of this lineage specification process is not fully understood. However, coordinated clusters of transcription factors, or gene networks, have emerged as key regulators of stem cell pluripotency and differentiation. Additionally, studies have shown that dysregulation of these natural gene networks contributes to the onset of cancer and tissue degeneration, thereby underlying multiple types of human disease.

Stem cells can naturally direct their lineage commitment by controlling the timing and level of expression of key transcription factors resulting in desired differentiation pathways [69]. Previous work to recapitulate transcription factor expression in stem cells to drive differentiation into desired lineages included the overexpression of key transcription factors [70,71,72,73]. These studies demonstrated improved desired differentiation outcomes, however, this method often produces inefficient cell yields, relies on subpopulation selection, and generates heterogeneous cell types [74]. These challenges have recently led to efforts from synthetic biologists to implement genetic circuits capable of tight gene control that provide precise spatial and temporal expression of key transcription factors in stem cells.

In this review, we provide a framework for implementing synthetic biology in stem cells to direct stem cell differentiation into desired lineages. We detail studies that have implemented genetic circuits in stem cells and discuss the outcomes of these studies on the robustness of driving stem cell fate decisions. We next consider using synthetic biology to design artificial tissues that are endowed with alternative functions to provide new therapies for diseased states.

Stem cells and synthetic biology

Stem cells play an important role in the development and regeneration of human tissues. A universal network of endogenous transcription factors control cell fate and continuously send and respond to physiological signals that adjust their cell-type specific gene expression. For example, the overexpression of the master transcription factors Oct4, Sox2, Klf4, and c-Myc is capable of overriding previously made cell fate choices to convert somatic cell types into a pluripotent state [75,76,77,78,79,80,81]. However, the differentiation of pluripotent precursor cells into adult cell types requires tightly controlled spatial and temporal gene expression dynamics of lineage-specific master transcription factors. Stem cell differentiation and the development of organs involves a complex coordination of both intrinsic and extrinsic cues that control cell behavior. This coordination of cues is critical for stem cells to make fate decisions and for robust tissue to develop.

Significant efforts are currently underway to program stem cells with genetic circuits to push their differentiation into desired lineages. Implementing genetic circuits to dynamically control gene expression (e.g. transcription factor expression) in stem cells is thought to improve differentiation outcomes because these circuits are able to replicate the dynamic gene expression patterns that are observed during development. Recently, a new genetic circuit was constructed coupling genetic parts from a mold, Neorospora crassa, and the bacterial Lac repressor system to create an orthogonal genetic switch to be used in mammalian cells [27]. After confirming tunability in immortalized cell lines for proof of concept performance, the tight gene control and tunability of gene expression of this genetic switch were demonstrated in pluripotent stem cells. These results suggest that synthetic biologists can program stem cells with artificial decision-making abilities that can be used to direct stem cell fate into desired lineages. For example, using genetic circuits that control the level and timing of expression of multiple transcription factors, it is possible to tune key cell fate regulators at various differentiation checkpoints to drive the differentiation of stem cells into one or many desired cell fates (Fig. 1).

Tools in synthetic biology to drive stem cell differentiation. Genetic tools built by synthetic biologists enable tight control of gene expression that allow the dynamic control of transcription factor expression in stem cells. This includes various levels of expression (e.g. low, medium, and high), in addition to controlling levels of expression in dynamic patterns including tuning, pulsing, oscillations, etc. Controlling the levels, timing, and patterns of gene expression at various checkpoints of stem cell fate improves differentiation outcomes

To demonstrate the utility of using genetic circuits to drive decision-making in cells, a two-way communication genetic circuit was engineered to mimic the natural gene expression patterns during angiogenesis, the formation of blood vessels [82]. Cell-to-cell communication was the framework for this synthetic network. Specifically, sender cells were programmed with a genetic circuit to constitutively express tryptophan synthase (TrpB 26 ), an enzyme from E. coli, which converts indole (a compound in the media) into L-tryptophan. The authors also engineered receiver cells with a genetic circuit designed to allow the cells to sense the secreted L-tryptophan and, in response, turn on the expression of a reporter gene, secreted alkaline phosphatase (SEAP). Next, the authors used this engineered cell-cell communication system to implement enhanced angiogenesis. During natural angiogenesis, two transcription factors, vascular endothelial growth factor (VEGF) and angiopoietin-1 (Ang1), function in a sequential and coordinated fashion to produce mature blood vessels [83]. In the engineered cell-cell communication system, the sender and receiver cells each possessed genetic circuits that generated output genes expressed at different times, to guide cellular differentiation and produce blood vessels. Due to the relatively small diffusion length of nutrients into tissues, vascularization strategies, such as angiogenesis in newly formed tissue, will be critical to the success of engineered tissues.

Genetic circuits have also been used to program stem cells with decision-making capabilities that enable them to produce efficient numbers of beta (β) cells. β cells are the cells found in the pancreas that synthesize and secrete insulin in response to glucose in the blood in a dose-dependent manner. Type 1 diabetes is a chronic condition in which the pancreas produces little to no insulin, and the primary cause of Type 1 diabetes is believed to be an auto-immune destruction of the β cells. The resulting destruction of these cells reduces the body’s ability to respond to glucose levels, making it nearly impossible to regulate glucose levels in the bloodstream properly. To develop alternative therapies for Type 1 diabetes, scientists have focused on producing β cells in vitro from pancreatic progenitor stem cells by overexpressing the three master-regulator transcription factors, Pdx1, Ngn3, and Mafa. This approach results in the differentiation of pancreatic progenitor stem cells into mature insulin producing β cells [76, 84]. Recently, a genetic circuit that functions as a band-pass filter was built to dynamically control the expression of the three master-regulator transcription factors [85]. This genetic circuit enabled the timely coordination of the three transcription factors, which produced a homogeneous population of cells that demonstrated robust insulin production over cells produced using traditional growth factor and chemical based techniques. This study emphasizes the need for the temporal regulation of gene expression during cell fate decisions.

In addition to controlling when key transcription factors turn on during differentiation, a recent study has shown that some cell fate pathways require pulsing the expression of key transcription factors [72]. In this study, the pulsing expression of Gata6 in human induced pluripotent stem (iPS) cells initiated the formation of all three germ layers giving rise to a complex three-dimensional (3D) multicellular tissue construct, or organoid, that exhibited a liver bud-like phenotype. Without pulsing only one germ layer formed. Genetic circuits enable fine-tuned control over the expression of transcription factors, suggesting that the possible gene expression patterns that can be implemented using genetic circuits are effectively limitless. Patterns including pulsing, tuning, oscillations are all within the realm of possibilities. Therefore, genetic circuits offer extraordinarily precise control over gene expression and cell fate that will likely transform their applicability in basic science and clinical research.

Replicating physiological functions in alternative cell types

Precise control over the intensity, duration, and timing of gene expression have advanced our abilities to direct stem cell fate into desired lineages, in addition to developing organoids. Using the same genetic tools, synthetic biologists have also created therapeutic cells that are capable of sensing and responding to various signals in a therapeutic fashion [43,44,45, 86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104]. For example, in two separate studies, genetic circuits were used to regulate glucose levels in the bloodstream of diabetic mice. In the first study, the expression and secretion of the glucagon-like peptide 1 (GLP-1), a peptide that has the ability to decrease blood sugar levels in the blood by enhancing to secretion of insulin [105], was controlled in human embryonic kidney (HEK) 293 cells using an optogenetic-controlled genetic circuit [106]. This genetic circuit allowed the implanted cells to detect blue light and, in response, initiate the transcription of GLP-1, causing blood glucose levels to fall in diabetic mice. In the second study, Chinese hamster ovarian (CHO) cells were engineered with a genetic circuit that produced insulin in response to decreasing pH levels. This study demonstrated controlled production of insulin when environmental pH dropped below the physiological range [41]. When these engineered cells were implanted into diabetic mice, they were able to restore insulin and glucose levels to the same level as that of healthy mice.

In addition to engineering therapeutic cells for metabolic disorders, a recent study demonstrated the use of a genetic circuit to endow HEK293 cells with the ability to control an inflammatory response [107]. This circuit was comprised of three basic modules to detect and respond to inflammatory signals: a sensor to sense inflammation signals an amplifier with positive feedback to ensure sustainability of the response and an effector that neutralized the inflammatory response. Therapeutic cells that are endowed with the ability to keep the body’s inflammatory response in check are an exciting advance in the field because these types of cells can be implanted after surgery to prevent a prolonged inflammatory response from hindering may proper healing and to allow for the restoration of healthy levels of inflammatory cytokines.

Future directions

Mammalian synthetic biologists have made great strides in engineering novel genetic tools to tightly regulate gene expression in various cell types. These genetic tools have been used for directing stem cell differentiation to produce desired cell lineages, to make organoids, and to engineer therapeutic cells to sense and respond to disease. With these accomplishments under our belts, it stands to reason that synthetic biologists can engineer implantable mini tissues, or organoids, that have been engineered to sense and respond to disease.

Rather than trying to recreate a failing pancreas for diabetic patients, can we engineer implantable adipose tissue (fat) with the ability to regulate blood glucose levels? Studies have shown that a patients’ own fat can be harvested and injected back into the individual’s joints to help alleviate joint pain [108]. In fact, Lipogems are an FDA approved system that are small bits of fat removed individuals, washed, and reinjected into various joints for those suffering from spinal conditions, joint pain, arthritis, or rotor cut tears [109,110,111,112]. One can start to image engineering personalized synthetic adipose tissue by first making iPS cells from a patient’s skin cells, and programming them with various genetic circuits: one to drive the differentiation into adipose cells, and the other with a program to regulate blood glucose levels (Fig. 2). These small synthetic tissues can then be injected under the armpit, or other unnoticeable locations, to regulate blood glucose levels over long periods of time. Of course, once one accepts the idea of injectable synthetic fat tissue, it’s easy to imagine engineering other synthetic organs (e.g. skin) that can function in various ways to improve the health of an individual.

Engineering synthetic tissues for employing personalized medicine. Engineering synthetic fat tissue for regulating blood glucose levels in diabetic patients will likely be a reality in the near future. In this hypothetical therapy, adipose cells are programmed with a genetic circuits capable of sensing glucose levels and, if pre-programmed physiologically high levels of glucose are sensed, they will respond by secreting a tightly regulated amount of insulin. These small synthetic tissues can be implanted under the skin in unnoticeable locations (e.g. in the armpit), to regulate blood glucose levels over long periods of time

Organoids are another area where synthetic biologists can have a significant impact. Unlike a purified tissue, like adipose tissue, organoids are miniaturized versions of an organ that can be isolated from organ progenitor cells, or pluripotent stem cells, and differentiated to form an organ-like structure. These organoids have multiple cell types that self-organize to create a structure similar to an organ found in vivo [113]. Because multiple cell types are in organoids, this offers opportunities to engineer more complex interactions (e.g. synthetic pattern formation, spatial and temporal communication between cell types, etc.) that may be required to recapitulate failing organs whose function cannot be replaced with a single tissue. For example, a synthetic organoid can be engineered with genetic circuits that can mimic healthy pathways to alter underlying disease states and rewire them to restore the healthy state [114].


Speaker Bio

Chris Voigt

Chris Voigt obtained his Bachelor’s degree in chemical engineering from the University of Michigan and his PhD in biochemistry and biophysics from the California Institute of Technology. We was a postdoctoral researcher at the University of California, Berkeley and later joined the faculty at the University of California, San Francisco. In 2011, he joined the Department… Continue Reading


Abstract

Multiple input changes can cause unwanted switching variations, or glitches, in the output of genetic combinational circuits. These glitches can have drastic effects if the output of the circuit causes irreversible changes within or with other cells such as a cascade of responses, apoptosis, or the release of a pharmaceutical in an off-target tissue. Therefore, avoiding unwanted variation of a circuit’s output can be crucial for the safe operation of a genetic circuit. This paper investigates what causes unwanted switching variations in combinational genetic circuits using hazard analysis and a new dynamic model generator. The analysis is done in previously built and modeled genetic circuits with known glitching behavior. The dynamic models generated not only predict the same steady states as previous models but can also predict the unwanted switching variations that have been observed experimentally. Multiple input changes may cause glitches due to propagation delays within the circuit. Modifying the circuit’s layout to alter these delays may change the likelihood of certain glitches, but it cannot eliminate the possibility that the glitch may occur. In other words, function hazards cannot be eliminated. Instead, they must be avoided by restricting the allowed input changes to the system. Logic hazards, on the other hand, can be avoided using hazard-free logic synthesis. This paper demonstrates this by showing how a circuit designed using a popular genetic design automation tool can be redesigned to eliminate logic hazards.


Researchers reveal new understandings of synthetic gene circuits

Tian and Wang’s research reveals new insights about the complex relationships between synthetic gene circuits and the cells that host them. Credit: Xiaojun Tian/ASU

Recent discoveries by two research teams in the Ira A. Fulton Schools of Engineering at Arizona State University are advancing the field of synthetic biology.

Assistant Professor Xiaojun Tian and Associate Professor Xiao Wang conducted a year-long collaboration with their laboratory groups in the School of Biological and Health Systems Engineering, one of the six Fulton Schools. Results from their novel research into ways that engineered gene circuits interact with biological host cells have been published this week in the scientific journal Nature Chemical Biology.

Synthetic biology applies engineering methods to design new biological networks or redesign aspects of existing biological systems. It is a rapidly emerging field of study, and many significant advances have been made during the past 20 years.

Early work included creating synthetic gene circuits and placing them within natural host cells.

"But the concept of a circuit here is an abstract one," Wang says. "Imagine a sequence of genetic segments in which the first one encodes or produces a particular protein. That protein, in turn, can either activate or inhibit the expression or protein production from another segment in the genetic sequence. If you keep expanding this idea, you can imagine it's like a network."

It is this chain of influence or inducement that is functioning as a circuit, rather than the physical connections within the genetic sequence. However, previous research has focused on just the behaviors of engineered genetic circuits themselves, with little attention to the background or context represented by host cells.

"It is hard to predict how these interactions affect the functions of the engineered genetic circuits," Tian says, "not to mention how to control them and make the circuits operate as desired within complicated, real-life environments."

Indeed, these synthetic gene circuits generally work only in a laboratory environment, not in more lifelike conditions. And this limitation greatly inhibits the application of engineered gene circuits in clinical settings.

Seeking to advance the field in that practical direction, the new research by Tian and Wang explored the relationship between the synthetic gene circuits and their host cells. Specifically, they examined the impact of "memory" circuits implanted within host cells, and the influence of gene circuit "topologies," or the architecture of interconnections among circuit components, in relation to host cell growth.

In the context of this work, the idea of memory relates to the continuation of influence or inducement within an engineered gene circuit even with the absence of a stimulus.

"Think about a light switch in your house," Wang says. "The light stays on even when you remove your finger from the switch. We refer to that persistent state as memory."

Tian and Wang's new research revealed that memory circuit topologies are significantly influenced by host cell behavior.

"We verified that influences are exchanged between the gene circuit and the host cell," Tian says. "That is, the circuit impacts the host cell, which in return has an impact on the circuit. It's like a loop.

"But we also demonstrated that the impact on a circuit's functionality is dependent on its topology," he says. "So, one circuit topology shows better performance than others within a dynamic host environment."

Their discovery relating circuit topology to a host cell's impact on circuit function is a first in the field of synthetic biology, and it expands meaningful scientific understanding of these complex interactions.

"It paves the way for building robust, engineered gene circuits," Tian says. "These could one day enhance interventions against the metastasis of cancer, for example, by slowing the ability of cancer cells to translate their development."

Progressing from the research that Tian and Wang have published includes examining the impact of adding additional synthetic gene circuits or modules into host cells, which substantially elevates the level of complexity as modules compete for resources within the cellular system.

Wang says that the School of Biological and Health Systems Engineering within the Fulton Schools is particularly well-placed for discoveries in synthetic biology.

"We have a critical mass of dedicated people who are strategically invested in advancing this area of research for the long term," he says. "So, we are seeking to be a leader in this field."


Synthetic biology, genetic engineering and you: Two-component signaling pathways as elements in synthetic circuit design

Schematics of native and transplanted two-component signaling pathways. (A) The native pathway consists of a receptor histidine kinase protein, which senses and propagates the signal to a cognate response regulator that regulates gene expression. (B) The envisioned adaptation to the mammalian host. Subscript “hum” indicates human-optimized codon sequence. DNAB, DNA binding. Pconst, constitutive mammalian promoter. P, phosphate Pmin, minimal mammalian promoter VP16, VP16 transactivator domain. Credit: Hansen J et al. (2014) Transplantation of prokaryotic two-component signaling pathways into mammalian cells. Proc Natl Acad Sci USA 111 (44):15705-15710.

(Phys.org) —Two of the most exciting areas of science and technology, synthetic biology and genetic engineering, have just taken a step towards a brave new future in which large-scale synthetic biological circuits composed of bioengineered logic gates, orthogonal to (that is, independent of) the host in which they operate, will enable a range of applications that include biosensors, gene expression control, cell motility, programmable gene circuits for cell physiology control, and other sophisticated gene circuits. This capability is based on the use of two-component regulatory system – basic stimulus-response coupling mechanisms that allow organisms to sense and respond to changes in many different environmental conditions. These systems consist of a membrane-bound histidine kinase that senses a specific environmental stimulus and a corresponding response regulator that mediates the cellular response, primarily through differential expression of target genes. ((A histidine kinase, or HK, is a multifunctional, typically transmembrane, protein involved in signal transduction across the cellular membrane a response regulator, or RR, protein is the second component in two-component signal transduction systems.)

A particularly promising type of two-component regulatory system – two-component signaling pathways – are the prevalent signal processing modality in prokaryotes and are also found in low eukaryotes and plants, but absent from vertebrate cells. Recently, scientists in the Department of Biosystems Science and Engineering at Eidgenössische Technische Hochschule Zürich (ETH Zurich, or Swiss Federal Institute of Technology Zurich), Basel, Switzerland transplanted two-component pathways into a mammalian host, demonstrating that these pathways could be partially reconstituted in mammalian cell culture and used for programmable control of gene expression. They found that the core biochemical processes are maintained, and while the capacity to sense chemical ligands is diminished or obscured and the preservation of basic biochemical processes during mammalian pathway transplantation is not guaranteed, they were able to use the pathways for multi-input gene regulation and show that they can be used as building blocks for gene expression control in mammalian cells, thereby creating new investigative possibilities in synthetic circuit design.

Prof. Dr. Yaakov (Kobi) Benenson discussed the paper that he, graduate student Jonathan Hansen and their co-authors published in Proceedings of the National Academy of Sciences. "The key step was to think about this possibility," Benenson tells Phys.org. "The idea occurred to me in the year 2007, when I was a Bauer Fellow at the Harvard FAS Center for Systems Biology. Michael Laub 1,2 , at the time also a Bauer fellow, worked on two-component signaling pathways in prokaryotes. I was exposed to this area through his research, and discussed with him the possibility of implementing these pathways in human cells." It was several years before Benenson and his group members started the project in their new lab at ETH Zurich. "The practical challenge to investigating whether the elements of prokaryotic two-component pathways are operational in mammalian cells was to first read a large volume of papers to identify the candidate pathways for trans-kingdom transplantation, and then to redesign them such that operation in mammalian cells was possible." The scientists built on their experience with mammalian gene circuit design to make a few informed decisions that turned out to be correct.

Benenson lists several other challenges the researchers faced, the first being using the pathways for multi-input gene regulation and showing that they can serve as a rich source of orthogonal building blocks for gene expression control in mammalian cells. The two challenges here, he notes, was to ensure that there was no crosstalk between the transplanted components, and that the observed prokaryote behavior is recapitulated in mammalian cells. Secondly, he continues, was implementing two-input logical AND-like gene regulation in mammalian cells. "Here in particular," Benenson says, "the challenge was the pathway's high sensitivity to low expression levels of the histidine kinase receptor. This made it difficult to achieve a low off state."

The third issue Benenson describes was based on implementing the three conditions – preserving pathway internal operations, pathway components being orthogonal to the host, and host to pathway components – needed to preserve basic biochemical processes during mammalian transplantation. "Given the vast differences in just about any aspect of biological processes between the two hosts, there was no guarantee that the processes occurring in bacteria would take place in mammalian cells," Benenson explains.

Logic with TCS. (A) NOR-gate circuit schematics comprising antibiotic-regulated HK and RR genes. (B) Quantitative data for antibiotic-regulated NarXL pathway. (C) Quantitative data for antibiotic-regulated DcuSR pathway. PI and ET are at 10 μg/mL and 4 μg/mL, respectively. Plasmid composition and output values are in SI Appendix, Tables S13 and S14. (D) (Top) Schematic representation of an OR gate between NarX and NarQ. (Bottom) Quantitative data and representative images. Plasmid composition and output values are in SI Appendix, Tables S15 and S16. In all panels the images are shown with red pseudocolor indicating DsRed Transfection marker, and cyan pseudocolor indicating AmCyan output. The resultant data are presented as mean ± SD of biological triplicates. Credit: Hansen J et al. (2014) Transplantation of prokaryotic two-component signaling pathways into mammalian cells. Proc Natl Acad Sci USA 111 (44):15705-15710.

The scientists addressed these challenges though a number of insights and innovations. "One approach was to perform accurate trans-kingdom transplantation by codon optimization and placing the expression of the pathway genes under mammalian promoters," Benenson recounts. (A codon is a sequence of three nucleotides that together form a unit of genetic code in a DNA or RNA molecule.) "Another key innovation was the development of the regulated promoter controlled by the phosphorylated response regulators, where we used a novel minimal core promoter sequence developed in our lab as well as experimenting with the number of binding site repeats upstream of this core promoter – and it turned out that having two or more binding sites is essential for strong induction." Benenson adds that research 3,4,5 about synthetic two-component signaling in plants published by the June Medford Lab was valuable resource – especially in clarifying the role of nuclear localization signals. (A nuclear localization signal, or NLS, is an amino acid sequence that tags a protein for import into the cell nucleus by nuclear transport.)

Benenson discussed several key aspects of the study detailed in their paper, the first being the finding that in mammalian cells, core prokaryotic two-component biochemical processes are maintained but the capacity to sense chemical ligands is diminished or obscured. "We observed constitutive strong signaling via the pathway once both the histidine kinase and the response regulator components were constitutively expressed," he explains. "In prokaryotes, signaling is typically induced upon external stimulation." This led the scientists to speculate that there are multiple cytoplasmic and environmental components in mammalian cells and their growth medium that might stimulate the HK receptors. "More research is needed to understand this phenomenon in full," Benenson adds.

A fascinating aspect of two-component signaling is the support for complex logic signal integration in mammalian cells. "The two-component system naturally lends itself to performing two-input logic, because the expression of both histidine kinase and response regulator genes is required for downstream gene activation. While the natural way to control the pathway is via appropriate ligand or stimulus, another way to utilize this feature is by controlling the expression of these genes via gene regulatory tools, for example transcriptional regulation. In addition, having multiple pathways operating in parallel allows scaling of this approach to larger logic cascades.

In their paper, the scientists tie the two preceding points together by discussing the ability of two-component signaling to implement AND, NOR, and OR gates using constitutive and inducible histidine kinases and response regulators. "The core requirement of two-components naturally lends itself to an AND-like logic behavior," Benenson notes. "By appropriate wiring of upstream gene regulation, the gate can be converted into the NOR gate OR gates are possible with pathways of known cross-reactivity – for example, when two different histidine kinase receptors activate the same response regulator."

Activity of mutant TCS components. Full-length, truncated, and mutant TCS genes are shown with each protein domain color-coded and labeled. Experimental data are given below. Each bar represents mean ± SD of a biological triplicate. The output values for NarX + NarL and NarL are from Fig. 3B they are displayed again for side-by-side comparison. Plasmid composition and output values are in SI Appendix, Tables S17 and S18. TM, transmembrane domain. Credit: Hansen J et al. (2014) Transplantation of prokaryotic two-component signaling pathways into mammalian cells. Proc Natl Acad Sci USA 111 (44):15705-15710.

The researchers also state in their paper that their findings open new avenues in synthetic circuit design, citing the example of using histidine kinases as biosensors for cytoplasmic metabolites if cytoplasmic metabolites or media components can be responsible for histidine kinase activation. Benenson expands on this and gives additional examples of novel synthetic biology and genetic engineering technologies and applications that may be possible due to their results. "Apart from potential use as biosensors, new avenues arise due to the fact that these pathways enable AND, OR and NOR logic," he tells Phys.org. "Due to the multiple existing pathways that exhibit minimal cross-talk, large logic circuits can be envisaged via cascading of multiple pathways." Specifically, he points out that while building AND gates in mammalian cells is difficult, they are very useful because they produce an output when multiple conditions hold simultaneously – so having the building blocks of two-component pathways will facilitate the construction of such gates for precise actuation in mammalian cells. "In addition, we showed that certain response regulator mutants can act as efficient constitutive activators, meaning that the plethora of response regulators can therefore generate large sets of orthogonal transcriptional activators for gene circuits of increasing sophistication."

When asked if a longer-term implication of their study might be that an ability to implement robust logic circuits in mammalian cells could lead to a novel translational approach to medical protocols, Benenson replied, "I think that this novel methodology will mesh with existing synthetic biology tools to enable better, more robust, and more programmable gene circuits for rational control of cell physiology, including the control of cell fate or the detection of pathological cell states. Being a signaling cascade, transplanted two-component pathways might improve the speed of information processing in these circuits and enable new ways to sense metabolites." That said, he points that metabolite sensing will have to be experimentally demonstrated.

As to the planned next steps in their research, the scientists plan to investigate the sensory function of HKs, which Benenson says was obscured in their experiments to date. "We also plan to test how building blocks derived from the two-component pathways can lead to the construction of large synthetic circuits," he adds. "In the long run, it would be intriguing to see if more complex pathways based on two-component systems, such as chemotaxis, can be similarly transplanted and perhaps coupled with cell motility machinery." (Chemotaxis is movement of somatic cells, bacteria, and other single-cell or multicellular organisms in response to a chemical stimulus.)

Regarding other areas of research that might benefit from their study, Benenson tells Phys.org that their discovery that key steps of two-component signaling are functional in human cells "can enable a clean cell-based model system for researchers who investigate these pathways. Usually," he adds, "such studies involved labor-intensive purification of protein components, because it is difficult to study these pathways in isolation in bacteria where tens of pathways coexist. We showed that the components can be expressed in human cells, and cross-talk as well as mutant behavior mirrors those found in prokaryotes. We also found one instance of previously-unreported crosstalk, and we suspect that it might also manifest itself in prokaryotes. This," he concludes, "would be an interesting area to pursue."

1 Two-component signal transduction pathways regulating growth and cell cycle progression in a bacterium: a system-level analysis, PLoS Biology (2005) 3(10):e334, doi:10.1371/journal.pbio.0030334

2 Specificity in Two-Component Signal Transduction Pathways, Annual Review of Genetics (2007) Vol. 41, pp 121–145, doi:10.1146/annurev.genet.41.042007.170548

3 Developing a Synthetic Signal Transduction System in Plants, Methods in Enzymology, Academic Press, 2011, Volume 497, Synthetic Biology, Part A, Chapter 25, Pages 581-602

4 Programmable Ligand Detection System in Plants through a Synthetic Signal Transduction Pathway, PLoSOne 6 (2011) e16292, doi:10.1371/journal.pone.0016292

5 Engineering Key Components in a Synthetic Eukaryotic Signal Transduction Pathway, Molecular Systems Biology (2009) 5:270, doi:10.1038/msb.2009.28


Synthetic Biology Comes into Its Own

Richard A. Muscat
Jun 1, 2016

© ISTOCK.COM/FATIDO/FEORIS

E very two hours in Matthew Bennett&rsquos Rice University lab, cyan and yellow lights flashed in synchronization. Bennett and his team had engineered 12 components to generate the coordinated oscillations. This circuit wasn&rsquot electronic, however it was biological. Two populations of E. coli, each carrying a synthetic gene circuit, cycled in synchronous pulses every 14 hours.
Bennett&rsquos work, published last year in Science, 1 is a key application of modern synthetic biology: taking biological components and linking them together to form novel functional circuits. Instead of a program coded in Java and executed by a computer&rsquos working memory, commands were written in DNA and carried out by the microbes&rsquo cellular machinery. LEDs were replaced with fluorescent proteins, and molecular signaling cascades served as the system&rsquos wires.

Stripped back to its most basic components, a synthetic or natural biological network consists of a gene that either.

The first synthetic networks were created in 2000, when researchers built an oscillator and others constructed a bistable switch in E. coli. In an oscillator circuit, three genes form a cascade, in which each gene triggers the inactivation of the next gene. In the case of the landmark oscillator constructed by Rockefeller University’s Stanislas Leibler, then at Princeton, and his graduate student Michael Elowitz, one of the three repressor genes was also linked to green fluorescent protein (GFP), resulting in visible pulses of light. 2 A bistable switch, on the other hand, consists of just two genes that inactivate each other. When one gene is on, the other is off. Due to variation in the expression of the active gene, the inactive gene occasionally gets the chance to switch on and suppress the expression of the first gene. Like Leibler and Elowitz, MIT bioengineer James Collins and his grad student Tim Gardner, then at Boston University, linked one of the genes with a sequence encoding GFP, and they were able to see the cells switch between states. 3 (See “Tinkering With Life,” The Scientist, October 2011.)

Since these early studies, engineers, computer scientists, mathematicians, and physicists have been applying their expertise to engineer synthetic gene networks. In addition to supporting the creation of novel functions, synthetic networks can also give insight into how naturally occurring ones work. As physicist Richard Feynman once wrote on his office blackboard, “What I cannot create, I do not understand.” Studying gene circuits in their natural context is complicated by the complex cellular environment in which they function reconstructing and tuning gene interactions in vitro can provide a simplified model for how equivalent networks behave in nature. (See illustration below.)

“Naturally occurring gene oscillators, especially the circadian oscillator that regulates our daily rhythms, are hard to study,” says Bennett. “We can easily make changes and fine-tune synthetic gene circuits in ways that are difficult in natural systems. Though our synthetic circuits are inherently different from their natural counterparts, we can use them to study some of the basic principles of how genes dynamically regulate each other.”

Stripped back to its most basic com­ponents, a synthetic or natural biologi­cal network consists of a gene that either switches another gene on or turns it off.

Researchers at the J. Craig Venter Institute (JCVI) in San Diego have even gone so far as to create the smallest functional genome to date, a mycoplasma bacterium consisting of just 473 genes. 4 This stripped-down cell can now provide insights into what each of the genes and their respective proteins are doing to keep the organism alive.

Building man-made circuits can also lead to something entirely new, Bennett adds. “I try to find ways to engineer a new synthetic circuit that can mimic the unexplained phenomenon, even if my solution is not the same as nature’s. Sometimes this leads to new insights into the natural circuit and sometimes not. Either way it’s exciting.”

Genetic networking

In the early 2000s, Uri Alon of the Weizmann Institute of Science in Israel and colleagues studied the connections between genes in E. coli, discovering common motifs, or patterns of gene connectivity. Importantly, the researchers found that these motifs occurred more often than could be expected if you took the same number of genes and randomly connected them, suggesting that biological networks have evolved these patterns. 5 After early studies demonstrated researchers’ ability to create novel gene circuits, many synthetic biologists began making synthetic replicas of these natural motifs.

DECIPHERING THE NETWORK: A naturally occurring gene network consists of many interacting genes that can activate or repress each other (top). But embedded within a larger network, their function can be hard to study. Synthetic biology can simplify the study of such gene interactions by engineering analogous circuits separate from the larger network (bottom).
See full infographic: WEB COURTESY OF RICHARD MUSCAT

By isolating a subset of genes and inserting them into a new cell, synthetic biologists can assemble a motif that has little interaction with the molecular machinery of that cell the genes are considered orthogonal. For example, viral promoters—sequences of DNA that drive gene expression—can be used to express GFP, a gene taken from jellyfish, inside mammalian cells. Modifications to promoters can allow them to be controlled by signaling molecules, not only allowing novel genes to be expressed, but giving synthetic biologists the ability to switch them on and off.

One of the simplest signaling motifs involves a gene that either activates or represses itself. Positive autoregulation is when a protein triggers its own expression. At first, due to the absence or very low concentration of protein, its expression is very low. After a while, however, an intermediate level of the protein builds up, speeding up the rise in expression levels. The overall effect of positive autoregulation is thus a delay before the gene reaches normal expression rates. 6 Conversely, negative regulation, when a gene inhibits its own expression, allows the fast activation of a gene upon exposure to a signaling molecule, but then slows its own production once it reaches a critical level, allowing it to rapidly reach a steady state. 7 (See illustration below.)

Another common motif includes the interaction of several genes forming feed-forward loops, in which one gene activates or represses the expression of another only under certain conditions. Synthetic implementation of one particular feed-forward loop has been shown to produce a pulse of gene activation—a large peak of gene expression followed by steady state expression. 8

Autoregulation and feed-forward loops highlight how synthetic biology can create direct replicas of naturally occurring circuits to understand their function. However, synthetic biologists also have engineered a number of novel behaviors in cells: for example, different types of computation. One of the choices a synthetic biologist might make when constructing a synthetic circuit is whether to make it digital (i.e., on/off) or analog (varying levels of output). Researchers have constructed digital circuits implementing Boolean computations such as AND/OR and NOT/NOR logic with up to 10 regulators and 55 component parts in E. coli. 9 Of course, many genes are not expressed in a digital manner neither completely on nor completely off, they are, rather, expressed dynamically over a range of levels. As a result, synthetic biologists are increasingly taking inspiration from nature and designing computational circuits in analog, implementing functions such as addition, subtraction, and division. 10

More than 15 years of constructing such biological gene networks has made waves in a wide variety of scientific fields. For example, Mary Dunlop of the University of Vermont is taking advantage of feedback circuits in the design of biofuel-producing bacteria. Her group has modified E. coli to express biofuels such as alcohols, diesels, or jet fuels that are exported from the cell by efflux pumps. Too much biofuel accumulating in a cell is toxic, and expression of too many efflux pumps places a strain on the cell. Either of these problems can prevent cell growth and the production of more biofuel. Through mathematical simulation, Dunlop has demonstrated that a negative-feedback sensor could control the balance by delaying pump expression until it is needed, when there is enough biofuel inside the cell to necessitate pumping it out. 11

DYNAMIC GENE EXPRESSION: A number of motifs that appear in naturally occurring networks have been reconstructed in synthetic circuits. Positive autoregulation (left) occurs when a gene is activated by its own product this results in delayed activation. (The black dotted line provides a comparison to gene activation with no autoregulation.) Conversely, negative autoregulation occurs when a gene represses its own expression (middle), allowing its rapid activation until it reaches a steady state, and then preventing overexpression. Finally, a combination of several genes can form a motif known as a feed-forward loop (right). Depending on the way the genes are connected, activating a single gene triggers the simultaneous activation and repression of another gene, causing a pulse in expression followed by a lower steady state.
See full infographic: WEB COURTESY OF RICHARD MUSCAT

Synthetic circuits are also showing potential as valuable tools for diagnosing and treating disease. In one study, researchers created synthetic circuits designed to detect combinations of microRNAs associated with a particular case of cervical cancer, and inserted the circuits into cancer and noncancer cell lines. Using a combination of AND and OR logic allowed the detection of specific combinations of different microRNA species only present in HeLa cells. If the right microRNA combination was detected, the synthetic circuit expressed a gene that caused the cells to die. 12

While many technical challenges stand in the way of applying synthetic biology techniques in treating patients, a more near-term application may come in the form of paper-based diagnostics. In 2014, Collins and his colleagues at Harvard and Boston Universities developed synthetic gene circuits that function outside of cells and can be embedded in paper, which changes color through the expression of fluorescent proteins if certain markers are present in the sample. In this proof-of-concept study, the researchers showed that such paper-based diagnostics could be designed for a diverse range of applications, from glucose detection to the identification of different strains of Ebola virus, with outputs that can be seen by eye or a cheap microscope. 13 This year, the team updated the test to detect 24 RNA sequences found in the Zika genome when a target RNA is present, a series of interactions turns the paper purple. 14 Paper-based diagnostics are easy to store through freeze-drying and to move to low-resource settings out of the lab, and researchers are now working to design such diagnostics for use in the field.

Working in tandem

BACTERIAL MOSAIC: Two populations of E. coli fluoresce yellow and cyan in unison as they activate or repress the other’s expression as well as their own. (See illustration below.) SCIENCE, 349:986-89, 2015, COURTESY OF MATTHEW BENNETT The examples described so far have been of genetic circuits operating in isolation inside many identical cells or outside cells altogether. In nature, however, cells don’t exist in a vacuum rather, small signaling molecules that can be easily transmitted across cell membranes allow cells to communicate with their neighbors.

In the case of the oscillator created in 2000, each individual cell in a population of bacteria would act in isolation, with one cell oscillating out of phase from its neighbors. Ten years later, University of California, San Diego’s Jeff Hasty and his colleagues used small signaling molecules that could pass out of one cell and into another to regulate the gene network within that cell. As a result, the oscillations of entire populations of bacteria were linked together and cycled in unison. 15

Bennett’s group at Rice University took this idea one step further when they made use of two interacting populations of E. coli carrying different genetic circuits to coordinate the long-term, stable oscillations of fluorescent protein expression. One population of bacteria acted as an activator strain while the other population acted as a repressor strain. The activator strain produced a signaling molecule that activated even more of its own signal production, triggering activation of the repressor strain. When activated, the repressor strain produced another signaling molecule that repressed both itself and the activator strain. Each strain also produced an enzyme that degraded the signaling molecules in the system, preventing the buildup of leftover signal.

“We took the circuitry of a single strain oscillator and reconfigured it so that two strains must work together to achieve the oscillations,” Bennett explains. “It’s similar to taking a book and giving the even pages to one person and the odd pages to another. To either individual, their portion of the book is useless. But if the two can communicate and work together, the book will make sense.”

COORDINATED OSCILLATIONS: Two populations of bacteria interact via signaling molecules to coordinate expression of fluorescent proteins. When using positive and negative autoregulation (top), the oscillations are robust as the two populations grow. The negative feedback loop of the repressor strain and the positive feedback loop of the activator strain thus reinforce oscillations when feedback is removed from the circuit (bottom), oscillations are less coordinated and prone to failure. “You can think of feedback loops as self-correction mechanisms,” says Bennett. “They are constantly assessing the current performance of the circuit and make changes if necessary.”
See full infographic: WEB COURTESY OF RICHARD MUSCAT

As each strain is activated, a fluorescent molecule is produced: cyan in the activator strain and yellow in the repressor strain. When mixed together, both populations are activated and repressed in unison, causing fluorescent oscillations over the entire cell population. When one strain is grown in isolation, no oscillations are observed.

Applying principles of basic gene motifs such as feedback loops with cell population biology can thus expand the repertoire of synthetic biologists looking to create novel genetic circuits. Likewise, implementing synthetic biological circuits in mixed cell populations that have coordinated behavior might illustrate ways in which complex synthetic tissues and organs could be engineered.

The decreasing cost of DNA synthesis and sequencing, the ability to share plasmids, the creation of databases describing genetic components, and the development of novel techniques to easily assemble and edit genomes have greatly accelerated progress in this area. As researchers engineer new genetic components, the relatively new field of synthetic biology could soon begin to bear actionable fruit, with applications that include compound synthesis, diagnostics, and even medical treatments. In addition, the design and study of synthetic systems will continue to give us a deeper understanding of the biology that exists around us.

“I take a great deal of inspiration from nature,” says Bennett. “Sometimes I see a circuit that is well-characterized and wonder if we can build it just as well as nature. Other times, I look at a phenomenon in nature that is unexplained. Then I get really excited.”

Richard A. Muscat works at the London-based Cancer Research UK, bringing together multidisciplinary teams of researchers using engineering and physical sciences to find new ways to tackle cancer.


Cell circuits remember their history: Engineers design new synthetic biology circuits that combine memory and logic

Engineers at MIT have developed genetic circuits in bacterial cells that not only perform logic functions, but also remember the results. Credit: LIANG ZONG AND YAN LIANG

MIT engineers have created genetic circuits in bacterial cells that not only perform logic functions, but also remember the results, which are encoded in the cell's DNA and passed on for dozens of generations.

The circuits, described in the Feb. 10 online edition of Nature Biotechnology, could be used as long-term environmental sensors, efficient controls for biomanufacturing, or to program stem cells to differentiate into other cell types.

"Almost all of the previous work in synthetic biology that we're aware of has either focused on logic components or on memory modules that just encode memory. We think complex computation will involve combining both logic and memory, and that's why we built this particular framework to do so," says Timothy Lu, an MIT assistant professor of electrical engineering and computer science and biological engineering and senior author of the Nature Biotechnology paper.

Lead author of the paper is MIT postdoc Piro Siuti. Undergraduate John Yazbek is also an author.

Synthetic biologists use interchangeable genetic parts to design circuits that perform a specific function, such as detecting a chemical in the environment. In that type of circuit, the target chemical would generate a specific response, such as production of green fluorescent protein (GFP).

Circuits can also be designed for any type of Boolean logic function, such as AND gates and OR gates. Using those kinds of gates, circuits can detect multiple inputs. In most of the previously engineered cellular logic circuits, the end product is generated only as long as the original stimuli are present: Once they disappear, the circuit shuts off until another stimulus comes along.

Lu and his colleagues set out to design a circuit that would be irreversibly altered by the original stimulus, creating a permanent memory of the event. To do this, they drew on memory circuits that Lu and colleagues designed in 2009. Those circuits depend on enzymes known as recombinases, which can cut out stretches of DNA, flip them, or insert them. Sequential activation of those enzymes allows the circuits to count events happening inside a cell.

Lu designed the new circuits so that the memory function is built into the logic gate itself. With a typical cellular AND gate, the two necessary inputs activate proteins that together turn on expression of an output gene. However, in the new circuits, the inputs stably alter regions of DNA that control GFP production. These regions, known as promoters, recruit the cellular proteins responsible for transcribing the GFP gene into messenger RNA, which then directs protein assembly.

For example, in one circuit described in the paper, two DNA sequences called terminators are interposed between the promoter and the output gene (GFP, in this case). Each of these terminators inhibits the transcription of the output gene and can be flipped by a different recombinase enzyme, making the terminator inactive.

Each of the circuit's two inputs turns on production of one of the recombinase enzymes needed to flip a terminator. In the absence of either input, GFP production is blocked. If both are present, both terminators are flipped, resulting in their inactivation and subsequent production of GFP.

Once the DNA terminator sequences are flipped, they can't return to their original state—the memory of the logic gate activation is permanently stored in the DNA sequence. The sequence also gets passed on for at least 90 generations. Scientists wanting to read the cell's history can either measure its GFP output, which will stay on continuously, or if the cell has died, they can retrieve the memory by sequencing its DNA.

Using this design strategy, the researchers can create all two-input logic gates and implement sequential logic systems. "It's really easy to swap things in and out," says Lu, who is also a member of MIT's Synthetic Biology Center. "If you start off with a standard parts library, you can use a one-step reaction to assemble any kind of function that you want."

Such circuits could also be used to create a type of circuit known as a digital-to-analog converter. This kind of circuit takes digital inputs—for example, the presence or absence of single chemicals—and converts them to an analog output, which can be a range of values, such as continuous levels of gene expression.

For example, if the cell has two circuits, each of which expresses GFP at different levels when they are activated by their specific input, those inputs can produce four different analog output levels. Moreover, by measuring how much GFP is produced, the researchers can figure out which of the inputs were present.

That type of circuit could offer better control over the production of cells that generate biofuels, drugs or other useful compounds. Instead of creating circuits that are always on, or using promoters that need continuous inputs to control their output levels, scientists could transiently program the circuit to produce at a certain level. The cells and their progeny would always remember that level, without needing any more information.

Used as environmental sensors, such circuits could also provide very precise long-term memory. "You could have different digital signals you wanted to sense, and just have one analog output that summarizes everything that was happening inside," Lu says.

This platform could also allow scientists to more accurately control the fate of stem cells as they develop into other cell types. Lu is now working on engineering cells to follow sequential development steps, depending on what kinds of inputs they receive from the environment.

Michael Jewett, an assistant professor of chemical and biological engineering at Northwestern University, says the new design represents a "huge advancement in DNA-encoded memory storage."

"I anticipate that the innovations reported here will help to inspire larger synthetic biology efforts that push the limits of engineered biological systems," says Jewett, who was not involved in the research.


This work was supported by US Defense Advanced Research Projects Agency (DARPA) 1KM and SD2 awards HR0011-15-C-0084 and FA8750-17-C-0229 (C.A.V., A.E.B., and Y.P.), National Science Foundation Award CCF-1807575 (C.A.V.), U Colorado-Boulder/Dept of Energy subaward DE-SC0018368 (C.A.V., J.S.), and a Samsung Scholarship (Y.P.).

YP and CAV conceived the study and designed the experiments YP performed all the experiments JS designed and constructed plasmid-based genetic circuits used in the study YP and TEG developed new terminator prediction pipeline YP and AEB performed the RNA sequencing data analysis and YP, AEB, and CAV wrote the manuscript with input from all the authors.