MIT的系统生物学研究

生物谷

Summary of “Rendering Images in 3-D: New software tools provide functional beauty from 2-D slices”.
Posted on 5/20/2004
By Aileen Constans, The Scientist, April 26, 2004

“To the uninitiated, three-dimensional microscopy makes the pretty pictures of fluorescently labeled cells that grace the covers of scientific journals. But to today’s microscopists, the capacity to render images from 3-D and 4-D datasets is critical for studying the distances between objects in a sample and for tracking how complex samples change over time.”

With in the advancement of computing capabilities and “3-D gaming technology” imaging has progressed rapidly in the past decade.   “ Yet challenges remain.   Now a diverse group of software and hardware vendors and academicians are working to overcome these hurdles, improving both tools and their applications.”

Sharpening Tools
The most common technique for acquiring 3-D images is through confocal microscopy but this technique often creates blurred images due to the scattering of light.   Deconvolution or image restoration helps manipulate these datasets to sharpen the images. “’Deconvolution collects all of that light and puts it back essentially where it came from…[this allows you to] get more information and a lot more accurate information about your sample,’ explains David Biggs, senior research scientist, AutoQuant Imaging, Watervilet, NY.”   A critical part of these new advanced imaging technologies is the ability to interpret the datasets to answer biological questions.   Software produced by Scientific Volume Imaging (SVI), Hilversum, Netherlands   “…computes an estimated image based on an optical model of the microscope, and compares this with the actual recorded image.”   Another technique employed by Germany’s ApoTome from Carl Zeiss is to take multiple images. “Combining the three images creates an optical section from which unfocused light is removed.”

On Being Trendy
“Despite the rapid pace of software development, companies can find it difficult to keep up with emerging trends.”   Visualization of data collected at academic institutions is pushing the microscopy envelope.   “Some companies respond to new imaging techniques by filling a niche, and many imaging software vendors currently are developing methods for resolving 3-D datasets over time.”

Managing Data
“Because software companies generally respond to researchers' needs, most current imaging limitations occur downstream of acquisition, explains James G. Evans, research scientist at the Computational and Systems Biology Initiative (CSBi)…

Evans and colleagues are developing an imaging pipeline to collect data directly from microscopes and shuttle this data at high speeds into a database for storage and management, where the data can then be sent for image restoration by deconvolution. To this end, Evans says he has had a lot of success with SVI's Huygens software. ‘It's very well parallelized, working across many processors, and is almost platform-independent,’ Evans says.

Another problem is the lack of a standardized data format among microscope vendors. ‘Often they have two, three, or four internal proprietary formats, which makes it extremely hard to exchange data among researchers using different equipment,’ says Marius Messerli, CEO of Zurich-based Bitplane. Researchers doing specialized work often have to cobble together hardware from different vendors, which compounds the problem. ‘When you're trying to do 3-D reconstructions, you could spend half your time having to plug in parameters and work them out, because the softwares aren't really talking to each other properly,’ explains North.”

Another solution for the platform incompatibility issues is the Open Microscopy Environment (OME).   “Developed by Peter Sorger of MIT and Jason Swedlow of the University of Dundee, Scotland, the OME's goal is to develop a standardized language for storing and sharing image data. The consortium has created an XML schema listing approximately 150 different image parameters, Evans notes. ‘Without ever talking to the guy who collected the data, you can find out a lot of information as to how that data was acquired,’ he says.”

Advances in Multiphoton Microscopy
Academic laboratories have advanced microscopy hardware as well as software.   “Scientists at Cornell University and the University of Rennes, France, used a variation of two-photon microscopy to capture nerve cell signaling events in sea slug neurons at submilli-second resolution.”   By including a second harmonic signal arising from dye molecules, they have developed high-resolution imaging of signaling events that cannot be captured with existing technology.

“Faster imaging can also aid in multidimensional whole-organ imaging, explains MIT’s Peter So, whose laboratory develops instrumentation for high-speed automated imaging of deep tissues.”   The So lab has developed a very high-speed automated platform that allows imaging of one-micron resolution slices of whole tissues. “So plans to use this technology to map every cell in an organ and link it to genomics and proteomics data.”

Enhancing the resolution
The issue of resolution historically was thought to be limited by the diffraction of light or in the case of modern microscopes 200 nm in the x-y focal plane and 600 nm in the z-direction.   “Several new techniques challenge this conventional wisdom.   A number of microscopy laboratories now use a more advanced form of structured illumination (the technology behind the Zeiss ApoTome). This technique applies a fine pattern in several directions and employs more complex frequency-space processing to provide optical sectioning and double the resolution in both the x-y and z directions.”

Other methods have been developed to increase resolution of light microscopy including 4Pi method that changes the focal characteristics of the microscope and stimulated emission depletion (STED) that manipulates fluorescence, both developed by Stefan Hell, and Mats Gustafsson’s I3M that uses two objectives over a whole image.

“Though 3-D imaging has become routine, one thing is clear: It is far from stagnant. Advancements in live-cell and 4-D imaging, as well as improvements in image acquisition speed and resolution, are pushing the limits of what biologists can see under the microscope. Says Bitplane’s Messerli, ‘Ten years ago biologists would dream about these methods and now they are available.’”
Summary of: Synthetic Life
Posted on 5/12/2004
W. Wayt Gibbs, Scientific American
May 2004

“Biologists are crafting libraries of interchangeable DNA parts and assembling them inside microbes to create programmable, living machines.”

While evolution has produced a wide range of things with useful skills, there is still room for improvement. Explosive-sensing microbes and bacteria that produce a natural malaria drug are some examples of the problems researchers are tackling by engineering cells. “And although many cancer researchers would trade their eyeteeth for a cell with a built-in, easy-to-read counter that ticks over reliably each time it divides, nature apparently has not deemed such a thing fit enough to survive in the wild.” It may seem simple to “...rewire cells to glow in the presence of a particular toxin…” and other things but the reality is that after 30 years, “…genetic engineering is still more of a craft than a mature engineering discipline.”

“[Drew] Endy is one of a small but rapidly growing number of scientists who have set out in recent years to buttress the foundation of genetic engineering with what they call synthetic biology. They are designing and building living systems that behave in predictable ways, that use interchangeable parts, and in some cases that operate with an expanded genetic code, which allows them to do things that no natural organism can.”

“This nascent field has three major goals: One, learn about life by building it, rather than by tearing it apart. Two, make genetic engineering worthy of its name – a discipline that continuously improves by standardizing its previous creations and recombining them to make new and more sophisticated systems. And three, stretch the boundaries of life and of machine until the two overlap to yield truly programmable organisms.”

A Light Blinks On
The history of Synthetic Biology begins 15 years ago with the “…pioneering work by Steven A. Benner and Peter G. Schultz.”  Their team “…created DNA containing two artificial genetic ‘letters’ in addition to the four that appear in life as we know it.” Since then, they and others have advanced the science to new levels. “Just within the past year, however, Schultz’s group at the Scripps Research Institute developed cells (containing normal DNA) that generate unnatural amino acids and string them together to make novel proteins.”

The buzz surrounding this research is its application to technology development with two recent devices constructed using the principles of synthetic biology. “Michael Elowitz and Stanislaus Leibler … assembled three interacting genes in a way that made the E. coli blink predictably, like microscopic Christmas tree lights…” James Collins and colleagues “…made a genetic toggle switch…” that flips between two states. Ideally, these two systems could be combined to make a blinking bacteria that can be switched on and off but in practice that is a long way off.

“We would like to be able to routinely assemble systems from pieces that are well described and well behaved,’ Endy remarks. ‘That way, if in the future someone asks me to make an organism that, say, counts to 3,000 and then turns left, I can grab the parts I need off the shelf…and predict how they will perform.”

Building with BioBricks
At MIT, the Endy lab and others have created a collection of “parts” stored in vials where each of the “…vials contains copies of a distinct section of DNA that either performs some function on its own or can be used by a cell to make a protein that does something useful.” These parts have been carefully designed to work together predictably and the scientist can manipulate the outcome by interchanging the parts. Analogous to electronic circuits, synthetic biology strives to create defined elements that make life work. “[S]tandardized parts offer another powerful advantage: the ability to design a functional genetic system without knowing exactly how to make it.” Students can design systems without having to design or manufacture the DNA themselves.

Hijacking Cells
While the analogy to electronic circuits works for the creation of “parts”, it is in getting the parts to work where the analogy breaks down. “[S]ynthetic Biologists are mainly interested in building genetic devices within living cells, so that the systems can move, reproduce and interact with the real world. From a cell’s point of view, the synthetic device inside it is a parasite. The cell provides it with energy, raw materials and the biochemical infrastructure that decodes DNA to messenger RNA and then to protein.”

The necessity of a host cell adds tremendous complexity to the problem. Different people have taken alternative approaches to “dodge” the host genetic machinery. Ron Weiss of Princeton uses multiple steps (consisting of inverters) to create a cell that lights up when a chemical concentration is “just right” (the “Goldilocks” genetic circuit). Endy has changed the input to be a rate rather than concentration where “…[t]he inverter responds to how many messenger RNAs are produced per second.” This solution will be tested in a new set of genetic systems designed by students in a winter course at MIT. “The aim…was to reprogram cells to work cooperatively to form patterns, such as polka dots, in a Petri dish.” “Endy expects to have the …designs ready for testing…in time to show off at the first synthetic biology conference, scheduled for this June.”

Link to Synthetic Biology 1.0 ConferenceRewriting the Book of Life
The conference will no doubt encompass many of the challenges that arise from engineering “…DNA to work reliably within a living cell that is constantly changing.” Changes in the engineered DNA through mutation present a substantial obstacle to synthetic biology. One solution for this is redundancy but another is to “…understand better how simple forms of life, such as viruses, have solved the problem of persistence.” Many researchers are using viruses to learn about just that. Craig Venter has created the phiX174 bacteriophage from scratch in two weeks, a bacterium with a minimal set of genes whereas Endy is rebuilding the T7 bacteriophage and reengineering the genome in the process.

Beta-Testing Life 2.0
Applications of synthetic biology range from mammalian cells that respond genetically to antibiotics, natural sensor proteins that detect toxins, and bacteria that manufacture an anti-malaria drug precursor, detect and destroy nuclear waste and remove heavy metals from water. While all of this seems admirable, “...if you become a touch uneasy at the thought of undergraduates creating new kinds of germs…, you are not alone.” Because of the ease of access to the DNA sequence of many potentially harmful organisms, the opportunities for misapplication are real. Endy indicates that “[u]ltimately we deal with the risks of biological technology by creating a society that can use the technology constructively.” But he agrees that people in the synthetic biology field should address the concerns. “This June, as leaders in the field meet to share their latest ideas about what can now be created, perhaps they will also devote some thought to what shouldn’t.”

The CSBi Technology Platform
CSBi has identified six technologies that will be required to advance systems biology at MIT. Each technology is treated as a core competency distributed across multiple core facilities. When integrated, these core competencies will serve as an enabling research infrastructure - the CSBi Technology Platform.

The Platform will be actively managed by a group of faculty and supported by a network of CSBi Research Scientists. These scientists will act as a link among the disparate computational and experimental facilities and will engage in systems biology research and training.

The CSBi Technology Platform has four mandates:

Service - providing training, equipment, methods and materials for researchers requiring access to sophisticated computational and experimental technologies;
Research - engaging in novel research and technology development inspired by technology-driven experimentation (including the development and application of disruptive technologies), and new modeling and computational capabilities;
Education - providing support for wet-bench work in lab courses and computing work in computational courses;
Outreach - hosting summer students and visiting scientists from academia and industry, and developing a mechanism for easy public access to research tools and data.

The Six Core Technologies

Imaging - Hardware, software and methods development for the acquisition and computational analysis of optical, EM and CT images.
Proteomics and Structure - Mass spectroscopy, 2D gel technologies, biophysical chemistry, X-ray crystallography and NMR for the high-throughput analysis of proteins and their structures.
Microsystems - Fabrication and testing of microelectromechanical systems (MEMS) that incorporate microfluidic, optical, microelectronic and biological components.
High-Performance Computing (HPC) - Cluster systems and large-scale parallel computing for biology-directed high-performance computing and modeling.
Modeling, Information Technology and Bioinformatics (MIB) - Hardware, software and programming expertise for processing biological data and building numerical models at different levels of abstraction.
Microarraying, Molecular Genetics and Genomics (MGG) - Robotic instrumentation, clone sets and facilities for DNA and protein microarraying, RNAi-based gene inhibition and high-throughput DNA manipulation.

Links to the Harvard Medical School
In addition to the core competencies, CSBi is in the process of establishing synergistic links with neighboring academic institutions, such as the Harvard Medical School. For example, a link to Harvard's Institute of Chemistry and Cell Biology (ICCB), directed by Harvard professor Stuart Schreiber, will add a seventh core competency in the area of small-molecule chemical libraries and high-throughput screening capabilities. A link to the Macromolecular Crystallography Facility (directed by Harvard Professor Stephen Harrison) will strengthen existing capabilities of the CSBi Technology Platform by providing access to the beamline at Argonne National Laboratory.

Initially, the effort of establishing a more formalized connection between the Harvard Medical School and CSBi is aimed at enhancing the technical capabilities at MIT. In the long-term, sharing and integration at the level of technology will serve as a catalyst for joint research projects between the two institutions and accelerate the application of systems biology to medical research.

Click the image above to see CSBi's Technology Platform.

The CSBi Research Scientists
Under the direction of CSBi faculty, the CSBi Research Scientists are charged with the task of building the CSBi Technology Platform by improving upon existing and inventing new technologies. These individuals are based in existing laboratories and facilities, but unlike conventional facility staff, they coordinate the activities needed to create unified technology competencies. In addition to their research responsibilities, the CSBi Research Scientists provide a service function by ensuring that a single point of contact is available for researchers who seek assistance in methods outside their primary expertise, an essential aspect of interdisciplinary research.

The CSBi Research Scientists are also involved in platform-related outreach activities. A special feature of MIT undergraduate education and teaching is that they feature hands-on experience with the latest laboratory techniques, labs and lecture-based courses. These scientists will also teach short technology-oriented courses and provide materials to course instructors and they will assist CSBi faculty in hosting visiting scientists from industry and in sponsoring summer students and faculty visitors from economically disadvantaged institutions.

Matrix Management
The key to building the CSBi Technology Platform lies in defining an effective mechanism by which the six CSBi core technologies can be supported by new and existing core facilities. This challenge represents a classic problem in matrix management. Each CSBi core technology or core competency must be mapped onto operational units by determining customer-provider relationships. For example, the BioMicro Center is a provider of server-based bioinformatics applications, whereas the Proteomics and Structure facilities are customers. In addition, the BioMicro Center is both a provider and consumer of high-performance computing.

A complete mapping of the organizational matrix illustrates that effective links between facilities are as important as the facilities themselves . Providing these links is the responsibility of the CSBi Research Scientists and is a prerequisite to a functional CSBi Technology Platform.

Industry Links
Another important aspect of developing and maintaining up-to-date core facilities is close contact with companies that provide instruments, computer hardware and software, and reagents. CSBi technology partnerships are being established with companies across a range of industries, but differ from CSBi�s strategic partnerships in being limited to particular technologies and instruments. For example, Entelos and Gene Network Sciences both are working with CSBi on schematic languages and software for describing gene and protein networks. Applied Precision, Beckman-Coulter and MolecularWare are assisting with automation and scanning equipment for microarray analysis, and Network Appliance and IBM are providing hardware for the CSBi high-performance computing core.

Summary of “Rendering Images in 3-D: New software tools provide functional beauty from 2-D slices”.
Posted on 5/20/2004
The Scientist summarizes new technology in 3-D microscopy, including MIT's research with Peter So and James Evans.

Summary of: Synthetic Life
Posted on 5/12/2004
Scientific American takes an in depth look at the emerging Synthetic Biology field and the work of Drew Endy.

Summary of: Electronics, Biology: Twins under the skin
Posted on 4/22/2004
Electronic Engineering News examines the connections between electronics and biotechnology.

Summary of: Is pharma smart enough to do systems biology?
Posted on 3/26/2004
Genome Technology outlines the efforts of "Big Pharma" to move into systems biology.

Spectrum: Van Oudenaarden - Disarming Pathogens
Posted on 2/18/2004
Read more here.

Spectrum: Research Briefs - Really Big Chill
Posted on 2/18/2004
Prof. Alexander van Oudenaarden suggests new tactics for disarming pathogens. Read more here.

MIT News: MIT approves new Ph.D.Program
Posted on 2/27/2004
The CSB Ph.D. program was approved for launch in the fall 2004 by unanimous vote at the February 2004 MIT faculty meeting.

Summary of "The big picture..."
Posted on 2/18/2004
The Boston Globe takes an eagle-eye view of the systems biology field, focusing on CSBi.

Biology needs a model of living systems
Posted on 2/17/2004
CSBi's director, Prof Peter Sorger, has described the kinds of models we need to understand biology. See his comments in this Tech Talk story.

Summary of "Is the Genbank Era Over?"
Posted on 2/13/2004
BioInform explores the blurring boundaries between bioinformatics and computational biology.

Tech Talk: Grant aids MIT systems biology
Posted on 2/12/2004
A five-year, $16 million grant has been awarded to CSBi by the National Institutes of Health.
See Tech Talk's story about the grant here.