Scientists Mimic a Living Cell on a Silicon Chip, to Decipher Genetic Expression

The artificial cell system developed at the Weizmann Institute can advance our understanding of gene expression.

Alexandra Tayar, Karzbrun, Weizmann Institute of Science

Scientists have managed to artificially mimic basic mechanisms of a biological cell on a silicon chip, an achievement they expect will shed light on the complex process of gene expression.

The cell isn't alive, explain the scientists at the Weizmann Institute. It includes biological components extracted from living cells and placed in the chip's controllable environment.

This enabled the researchers to imitate the inflow and outflow of molecular material in living cells, as well as model communication between cells.

By imitating these basic mechanisms in the controlled environment of a silicon chip, the researchers are able to study the complicated mechanisms of genetic regulatory networks.

The significance of deciphering these networks is immense. Regulatory gene networks are key biochemical mechanisms that control genetic expression: which genes are expressed to produce proteins and which genes are shut off – and when they do so.

Ohad Herches, Weizmann Institute of Science

The regulatory networks are intricate interactions between whole clusters of genes and the proteins they produce. It is the regulatory networks which are responsible for stem cell differentiation into the different cell types such as muscle cells or retina cells.

All cells in a given organism have an identical genome. Gene networks create cellular differentiation by activating different sets of genes in each cell type, in order to produce the appropriate enzymes and proteins needed for a given cell's specific task in the body.

Cracking the code

The artificial cell system developed at the Weizmann Institute has its roots in early efforts to decipher the genetic code, over half a century ago, shortly after Francis Crick formulated the central dogma of molecular biology: that DNA codes for RNA, and RNA codes for proteins.

Researchers then set out to study how the basic genetic code gets translated into a specific protein. Studying living cells in action in order to "crack the code" wasn't an option.

As multitudes of proteins are being produced at the same time, it was difficult to figure out which genetic sequence codes for which amino acid – the building blocks of proteins.

In 1961, Marshall Nirenberg and Heinrich Matthaei conducted a landmark experiment: they extracted the enzymatic machinery responsible for protein synthesis from bacteria and put the cellular “juice” in a test tube. They deliberately left the DNA outside.

Instead of the original DNA, they inserted synthetic RNA sequences, one at a time, into the test tube. They could thus correlate these sequences with the resulting amino acid sequences.

Gumming up the work

Cell-free systems of the sort built by Nirenberg and Matthaei provide to this day a useful environment in which aspects of gene expression can be studied in a controlled manner. They are also used for artificially producing proteins, for research or medical purposes.

But when it comes to studying regulatory gene networks, cell-free systems are problematic. For one, these systems continuously produce proteins which accumulate in the test tube and clog the system. At the same time, nutrients that are essential for synthesizing proteins run out after a few hours and the reaction dies out as a result.

Existing cell-free systems can't mimic the natural process of protein replenishment in living cells, which constantly multiply and in the process dilute and replace their proteins with newly synthesized material. This is an obstacle to studying regulatory gene networks, whose dynamic nature requires new proteins to be synthesized when necessary and removed when no longer needed.

Building the "cell" chip

In a paper recently published in Science, the Weizmann Institute researchers describe an innovative solution to this problem.

Doctorate students Eyal Karzbrun and Alexandra Tayar, with Prof. Roy Bar-Ziv from the Institute's Materials and Interfaces Department, in collaboration with Prof. Vincent Noireaux from the University of Minnesota, developed a system that more closely mimics the living cell's capacity to dynamically turn on and off genes.

The researchers carved a miniaturize chamber into a silicon chip, attached genes to the bottom of this chamber, and filled it with the protein-synthesizing machinery extracted from a living cell. They also connected this chamber to a small channel, allowing the accumulating proteins to drift out of the compartment.

Through this same channel, the artificial cell was fed with “fresh” enzymes – ribosomes and polymerases required for protein synthesis – as well as fresh nutrients. This innovative chamber structure solved the problem of dilution and replenishment that persisted in previous cell-free systems.

And it worked

With this new system, they achieved the hoped-for breakthrough. “For the first time, we were able to observe a regulatory gene network in action in the controlled environment mimicking a living cell," says Tayar.

The synthetic genetic network which the researchers inserted into the silicon chip was composed of two genes. The first encoded a protein that activated the second gene. The second gene encoded a protein that suppressed the expression of the first gene.

The result was cyclical gene activation and suppression: a simplified dynamic model of real genetic networks. The chip-based system allowed this dynamic to take place.

“They have engineered a system in which genetic circuits can operate in a way that closely mimics the situation in growing cells,” says Michael Elowitz, a professor of biology and biological engineering at Caltech who wasn't involved in the research project. “These elegant devices will enable us to answer fundamental questions about how different genetic circuit designs operate, and to design and build new synthetic genetic circuits that create all kinds of dynamic cellular behaviors.”

According to Roy Bar-Ziv, “The next challenge is to scale up and program our artificial cells to express 100 genes, which will allow us to study complex processes, such as regulation of cellular metabolism, and response to environmental changes, just as in a living cell. Ultimately, one can envision encoding all the genes required for replication of the cell’s basic machinery itself, and in doing so get closer to a living cell, which is bound to teach us how cells work,” he says.

In the future, he adds, “Artificial cells on a chip may be useful in a variety of biomedical applications, including programmable biological sensors, screening of drugs, and interfacing with living systems."