Single GFP-expressing cell is basis of living laser device

ScienceDaily (June 13, 2011) — It sounds like something out of a comic book or a science fiction movie -- a living laser -- but that is exactly what two investigators at the Wellman Center for Photomedicine at Massachusetts General Hospital have developed. In a report that will appear in the journal Nature Photonics and is receiving advance online release, Wellman researchers Malte Gather, PhD, and Seok Hyun Yun, PhD, describe how a single cell genetically engineered to express green fluorescent protein (GFP) can be used to amplify the light particles called photons into nanosecond-long pulses of laser light.

"Since they were first developed some 50 years ago, lasers have used synthetic materials such as crystals, dyes and purified gases as optical gain media, within which photon pulses are amplified as they bounces back and forth between two mirrors," says Yun, corresponding author of the report. "Ours is the first report of a successful biological laser based on a single, living cell."

Adds Gather, a research fellow and the paper's lead author, "Part of the motivation of this project was basic scientific curiosity. In addition to realizing that biological substances had not played a major role in lasers, we wondered whether there was a fundamental reason why laser light, as far as we know, does not occur in nature or if we could find a way to achieve lasing in biological substances or living organisms."

The investigators chose GFP for their exploration of those questions because the protein -- originally found in a species of jellyfish -- can be induced to emit light without the application of additional enzymes. Its properties are well understood, and there are established techniques to genetically program many organisms to express GFP. To determine the protein's potential for generating laser light, the researcher first assembled a device consisting of an inch-long cylinder, with mirrors at each end, filled with a solution of GFP in water. After first confirming that the GFP solution could amplify input energy into brief pulses of laser light, the researchers estimated the concentration of GFP required to produce the laser effect.

Using that information, their next step was to develop a line of mammalian cells expressing GFP at the required levels. The cellular laser was assembled by placing a single GFP-expressing cell -- with a diameter of from 15 to 20 millionths of a meter -- in a microcavity consisting of two highly reflective mirrors spaced 20 millionths of a meter apart. Not only did the cell-based device produce pulses of laser light as in the GFP solution experiment, the researchers also found that the spherical shape of the cell itself acted as a lens, refocusing the light and inducing emission of laser light at lower energy levels than required for the solution-based device. The cells used in the device survived the lasing process and were able to continue producing hundreds of pulses of laser light.

"While the individual laser pulses last for only a few nanoseconds, they are bright enough to be readily detected and appear to carry very useful information that may give us new ways to analyze the properties of large numbers of cells almost instantaneously," says Yun, who is an associate professor of Dermatology at Harvard Medical School. "And the ability to generate laser light from a biocompatible source placed inside a patient could be useful for photodynamic therapies, in which drugs are activated by the application of light, or novel forms of imaging."

Gather adds, "One of our long-term goals will be finding ways to bring optical communications and computing, currently done with inanimate electronic devices, into the realm of biotechnology. That could be particularly useful in projects requiring the interfacing of electronics with biological organisms. We also hope to be able to implant a structure equivalent to the mirrored chamber right into a cell, which would the next milestone in this research." The study was supported by grants from the National Science Foundation and the Korea National Research Foundation.

Story Source:

The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by Massachusetts General Hospital, via EurekAlert!, a service of AAAS.

Journal Reference:

Malte C. Gather, Seok Hyun Yun. Single-cell biological lasers. Nature Photonics, 2011; DOI: 10.1038/nphoton.2011.99

Note: If no author is given, the source is cited instead.

Disclaimer: This article is not intended to provide medical advice, diagnosis or treatment. Views expressed here do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

Single GFP-expressing cell is basis of living laser device

ScienceDaily (June 13, 2011) — It sounds like something out of a comic book or a science fiction movie -- a living laser -- but that is exactly what two investigators at the Wellman Center for Photomedicine at Massachusetts General Hospital have developed. In a report that will appear in the journal Nature Photonics and is receiving advance online release, Wellman researchers Malte Gather, PhD, and Seok Hyun Yun, PhD, describe how a single cell genetically engineered to express green fluorescent protein (GFP) can be used to amplify the light particles called photons into nanosecond-long pulses of laser light.

"Since they were first developed some 50 years ago, lasers have used synthetic materials such as crystals, dyes and purified gases as optical gain media, within which photon pulses are amplified as they bounces back and forth between two mirrors," says Yun, corresponding author of the report. "Ours is the first report of a successful biological laser based on a single, living cell."

Adds Gather, a research fellow and the paper's lead author, "Part of the motivation of this project was basic scientific curiosity. In addition to realizing that biological substances had not played a major role in lasers, we wondered whether there was a fundamental reason why laser light, as far as we know, does not occur in nature or if we could find a way to achieve lasing in biological substances or living organisms."

The investigators chose GFP for their exploration of those questions because the protein -- originally found in a species of jellyfish -- can be induced to emit light without the application of additional enzymes. Its properties are well understood, and there are established techniques to genetically program many organisms to express GFP. To determine the protein's potential for generating laser light, the researcher first assembled a device consisting of an inch-long cylinder, with mirrors at each end, filled with a solution of GFP in water. After first confirming that the GFP solution could amplify input energy into brief pulses of laser light, the researchers estimated the concentration of GFP required to produce the laser effect.

Using that information, their next step was to develop a line of mammalian cells expressing GFP at the required levels. The cellular laser was assembled by placing a single GFP-expressing cell -- with a diameter of from 15 to 20 millionths of a meter -- in a microcavity consisting of two highly reflective mirrors spaced 20 millionths of a meter apart. Not only did the cell-based device produce pulses of laser light as in the GFP solution experiment, the researchers also found that the spherical shape of the cell itself acted as a lens, refocusing the light and inducing emission of laser light at lower energy levels than required for the solution-based device. The cells used in the device survived the lasing process and were able to continue producing hundreds of pulses of laser light.

"While the individual laser pulses last for only a few nanoseconds, they are bright enough to be readily detected and appear to carry very useful information that may give us new ways to analyze the properties of large numbers of cells almost instantaneously," says Yun, who is an associate professor of Dermatology at Harvard Medical School. "And the ability to generate laser light from a biocompatible source placed inside a patient could be useful for photodynamic therapies, in which drugs are activated by the application of light, or novel forms of imaging."

Gather adds, "One of our long-term goals will be finding ways to bring optical communications and computing, currently done with inanimate electronic devices, into the realm of biotechnology. That could be particularly useful in projects requiring the interfacing of electronics with biological organisms. We also hope to be able to implant a structure equivalent to the mirrored chamber right into a cell, which would the next milestone in this research." The study was supported by grants from the National Science Foundation and the Korea National Research Foundation.

Story Source:

The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by Massachusetts General Hospital, via EurekAlert!, a service of AAAS.

Journal Reference:

Malte C. Gather, Seok Hyun Yun. Single-cell biological lasers. Nature Photonics, 2011; DOI: 10.1038/nphoton.2011.99

Note: If no author is given, the source is cited instead.

Disclaimer: This article is not intended to provide medical advice, diagnosis or treatment. Views expressed here do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

New algorithm offers ability to influence systems such as living cells or social networks

ScienceDaily (May 14, 2011) — At first glance, a diagram of the complex network of genes that regulate cellular metabolism might seem hopelessly complex, and efforts to control such a system futile.

However, an MIT researcher has come up with a new computational model that can analyze any type of complex network -- biological, social or electronic -- and reveal the critical points that can be used to control the entire system.

Potential applications of this work, which appears as the cover story in the May 12 issue of Nature, include reprogramming adult cells and identifying new drug targets, says study author Jean-Jacques Slotine, an MIT professor of mechanical engineering and brain and cognitive sciences.

Slotine and his co-authors applied their model to dozens of real-life networks, including cell-phone networks, social networks, the networks that control gene expression in cells and the neuronal network of the C. elegans worm. For each, they calculated the percentage of points that need to be controlled in order to gain control of the entire system.

For sparse networks such as gene regulatory networks, they found the number is high, around 80 percent. For dense networks -- such as neuronal networks -- it's more like 10 percent.

The paper, a collaboration with Albert-Laszlo Barabasi and Yang-Yu Liu of Northeastern University, builds on more than half a century of research in the field of control theory.

Control theory -- the study of how to govern the behavior of dynamic systems -- has guided the development of airplanes, robots, cars and electronics. The principles of control theory allow engineers to design feedback loops that monitor input and output of a system and adjust accordingly. One example is the cruise control system in a car.

However, while commonly used in engineering, control theory has been applied only intermittently to complex, self-assembling networks such as living cells or the Internet, Slotine says. Control research on large networks has been concerned mostly with questions of synchronization, he says.

In the past 10 years, researchers have learned a great deal about the organization of such networks, in particular their topology -- the patterns of connections between different points, or nodes, in the network. Slotine and his colleagues applied traditional control theory to these recent advances, devising a new model for controlling complex, self-assembling networks.

"The area of control of networks is a very important one, and although much work has been done in this area, there are a number of open problems of outstanding practical significance," says Adilson Motter, associate professor of physics at Northwestern University. The biggest contribution of the paper by Slotine and his colleagues is to identify the type of nodes that need to be targeted in order to control complex networks, says Motter, who was not involved with this research.

The researchers started by devising a new computer algorithm to determine how many nodes in a particular network need to be controlled in order to gain control of the entire network. (Examples of nodes include members of a social network, or single neurons in the brain.)

"The obvious answer is to put input to all of the nodes of the network, and you can, but that's a silly answer," Slotine says. "The question is how to find a much smaller set of nodes that allows you to do that."

There are other algorithms that can answer this question, but most of them take far too long -- years, even. The new algorithm quickly tells you both how many points need to be controlled, and where those points -- known as "driver nodes" -- are located.

Next, the researchers figured out what determines the number of driver nodes, which is unique to each network. They found that the number depends on a property called "degree distribution," which describes the number of connections per node.

A higher average degree (meaning the points are densely connected) means fewer nodes are needed to control the entire network. Sparse networks, which have fewer connections, are more difficult to control, as are networks where the node degrees are highly variable.

In future work, Slotine and his collaborators plan to delve further into biological networks, such as those governing metabolism. Figuring out how bacterial metabolic networks are controlled could help biologists identify new targets for antibiotics by determining which points in the network are the most vulnerable.

Story Source:

The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by Massachusetts Institute of Technology. The original article was written by Anne Trafton, MIT News Office.

Journal Reference:

Yang-Yu Liu, Jean-Jacques Slotine, Albert-László Barabási. Controllability of complex networks. Nature, 2011; 473 (7346): 167 DOI: 10.1038/nature10011

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

New algorithm offers ability to influence systems such as living cells or social networks

ScienceDaily (May 14, 2011) — At first glance, a diagram of the complex network of genes that regulate cellular metabolism might seem hopelessly complex, and efforts to control such a system futile.

However, an MIT researcher has come up with a new computational model that can analyze any type of complex network -- biological, social or electronic -- and reveal the critical points that can be used to control the entire system.

Potential applications of this work, which appears as the cover story in the May 12 issue of Nature, include reprogramming adult cells and identifying new drug targets, says study author Jean-Jacques Slotine, an MIT professor of mechanical engineering and brain and cognitive sciences.

Slotine and his co-authors applied their model to dozens of real-life networks, including cell-phone networks, social networks, the networks that control gene expression in cells and the neuronal network of the C. elegans worm. For each, they calculated the percentage of points that need to be controlled in order to gain control of the entire system.

For sparse networks such as gene regulatory networks, they found the number is high, around 80 percent. For dense networks -- such as neuronal networks -- it's more like 10 percent.

The paper, a collaboration with Albert-Laszlo Barabasi and Yang-Yu Liu of Northeastern University, builds on more than half a century of research in the field of control theory.

Control theory -- the study of how to govern the behavior of dynamic systems -- has guided the development of airplanes, robots, cars and electronics. The principles of control theory allow engineers to design feedback loops that monitor input and output of a system and adjust accordingly. One example is the cruise control system in a car.

However, while commonly used in engineering, control theory has been applied only intermittently to complex, self-assembling networks such as living cells or the Internet, Slotine says. Control research on large networks has been concerned mostly with questions of synchronization, he says.

In the past 10 years, researchers have learned a great deal about the organization of such networks, in particular their topology -- the patterns of connections between different points, or nodes, in the network. Slotine and his colleagues applied traditional control theory to these recent advances, devising a new model for controlling complex, self-assembling networks.

"The area of control of networks is a very important one, and although much work has been done in this area, there are a number of open problems of outstanding practical significance," says Adilson Motter, associate professor of physics at Northwestern University. The biggest contribution of the paper by Slotine and his colleagues is to identify the type of nodes that need to be targeted in order to control complex networks, says Motter, who was not involved with this research.

The researchers started by devising a new computer algorithm to determine how many nodes in a particular network need to be controlled in order to gain control of the entire network. (Examples of nodes include members of a social network, or single neurons in the brain.)

"The obvious answer is to put input to all of the nodes of the network, and you can, but that's a silly answer," Slotine says. "The question is how to find a much smaller set of nodes that allows you to do that."

There are other algorithms that can answer this question, but most of them take far too long -- years, even. The new algorithm quickly tells you both how many points need to be controlled, and where those points -- known as "driver nodes" -- are located.

Next, the researchers figured out what determines the number of driver nodes, which is unique to each network. They found that the number depends on a property called "degree distribution," which describes the number of connections per node.

A higher average degree (meaning the points are densely connected) means fewer nodes are needed to control the entire network. Sparse networks, which have fewer connections, are more difficult to control, as are networks where the node degrees are highly variable.

In future work, Slotine and his collaborators plan to delve further into biological networks, such as those governing metabolism. Figuring out how bacterial metabolic networks are controlled could help biologists identify new targets for antibiotics by determining which points in the network are the most vulnerable.

Story Source:

The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by Massachusetts Institute of Technology. The original article was written by Anne Trafton, MIT News Office.

Journal Reference:

Yang-Yu Liu, Jean-Jacques Slotine, Albert-László Barabási. Controllability of complex networks. Nature, 2011; 473 (7346): 167 DOI: 10.1038/nature10011

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here