There is an increasing appreciation that the regulation of growth (size) plays critical roles in many biological phenomena. In mammals, changes in cell size rather than cell number underlie important physiological changes in organ size, such as heart enlargement induced by exercise or liver shrinking caused by starvation. During development changes in cell size are frequent, perhaps best exemplified by the massive increase in cell size that accompanies the differentiation and arborization of neurons. We now know that derangements of cell size underlie certain human diseases. These include tuberous sclerosis complex, a mental retardation and tumor-prone syndrome, as well as pathological cardiac hypertrophy.
We are studying at the biochemical, cellular and organismal level a signaling network called the mTOR pathway. This pathway is emerging as a critical integrator of growth signals in mammals and is under the control of nutrients, stress, and growth factors like insulin. We are interested in understanding how the mTOR pathway senses and integrates upstream signals and coordinates cell growth with the cell cycle. We are also studying the function of novel components of the pathway in mice.
The mammalian Target Of Rapamycin (mTOR) protein was discovered in studies into the mechanism of action of rapamycin, a macrolide antibiotic produced by a streptomyces species of bacteria. When rapamycin enters mammalian cells it binds to a small protein called FKBP12 to create a drug-receptor complex that interacts with mTOR, a large protein kinase related to PI3-kinase. Exactly how FKBP12-rapamycin perturbs mTOR function is not known. mTOR is evolutionarily conserved and integrates nutrient-and growth factor-derived signals to control the cell growth machinery. Within cells mTOR is part of two large protein complexes, called mTOR Complex 1 (mTORC1) and Complex 2 (mTORC2) (see Figure). Over the last few years we have identified many of the components (e.g., raptor, rictor, PRAS40, DEPTOR, mLST8/GbL) of these complexes and their upstream regulators, most recently many of the proteins that signal amino acid availability to mTORC1 (e.g. Rag GTPases, Ragulator). We are just starting to understand mTORC2 function but significant evidence indicates that it is an upstream kinase for Akt/PKB and is thus part of the PI3K/PTEN pathway.
Links relating to rapamycin (generic name: sirolimus; trade name: rapamune)
Expression profiles induced by rapamycin in human and mouse cells
Immunosuppressive uses of rapamycin: Wyeth home page for rapamune
Use of rapamycin-coated stents to prevent restenosis after angioplasty
Where rapamycin was discovered: Easter Island (Rapa Nui) Homepage
There are a number of reasons to think that energy and nutrient metabolism in cancer cells in a solid tumor is likely to be different than in normal cells and thus a potential point of attack for cancer therapy. First, during the initiation and growth of a solid tumor regions of the tumor may be poorly vascularized and thus lack the oxygen and nutrients necessary for normal cells to live. To survive, tumor cells must adapt their energy demands and intermediary metabolism to their environment. Second, the deranged signaling common to cancer cells can alter the expression and activity of metabolic enzymes, affecting metabolic processes in ways that may not occur in normal cells. Third, many cancer cells grow and proliferate at rates far higher than most others cells in an adult, creating a demand for the building blocks of macromolecules that is not shared by most normal cells. For these reasons, it is surprising that the literature contains relatively little information on the metabolic processes, besides glycolysis, that are necessary for tumor cell life. We would like to identify the metabolic processes that are necessary for cancer cells to proliferate and survive in tumors. The lab is using in vivo shRNA screening as well as bioinformatic analyses to systematically identify all metabolic genes that are necessary for in vivo tumorigenesis. Several interesting pathways have been identified and are being studied at the mechanistic level.
Click here for a review of cancer cell metabolism which we recently wrote.
Because of the difficulty of identifying the components of signaling networks in mammalian cells, we are creating and using technologies that allow us to probe gene function in a highly parallel fashion. Our work has lead to the development of ‘cell-based microarrays’. The features (or spots) of these microarrays consist of clusters of mammalian cells that either over- or under-express a particular gene product or are under the influence of a small drug-like molecule. The features are only 100-250 microns in diameter and, thus, on a standard microscope slide we can create arrays containing thousands of individual cell clusters, each with a perturbation in a different gene.
With this technology we can rapidly identify candidate genes that may underlie phenotypes of interest in mammalian cells (e.g. cell size) as well perform synthetic effect type screens. To create cell-based microarrays we use a robot to print onto a surface compatible with cell attachment and proliferation nanoliters of biodegradable polymers mixed with reagents that perturb gene function. We then culture adherent cells on the biopolymer-containing spots. As the polymers degrade the reagents are released, affecting, without the need of wells to sequester the individual reagents, gene function in defined local areas of a cell monolayer. Using this approach we have locally introduced into mammalian cells cDNAs in expression vectors (through a process named ‘reverse transfection’), lentiviruses, siRNAs, and small molecules. We can examine the cells for alterations in particular phenotypes using techniques compatible with cells growing on a surface, such as immunofluorescence or in situ hybridization. We have also adapting the cell microarray concept for screening double-stranded RNAs that mediated RNAi in Drosophila tissue culture cells.
Lentiviral shRNA Collection
Small interfering RNAs (siRNAs) expressed from short hairpin RNAs are proving to be a powerful way to mediate gene specific RNA interfering (RNAi) in mammalian cells. We are part of a consortium of labs at the Whitehead Institute, Broad Institute, Harvard Medical School, Dana-Farber Cancer Institute, Massachusetts General Hospital, and MIT Department of Biology that is collaborating to produce a pan-genomic collection of lentivirally-expressed shRNAs that target human and mouse genes as well as the techniques to screen this library. We are using the library in both traditional high-throughput well-based assays as well as to construct high-density loss of function cell microarrays.
Link to WIBR siRNA selection homepage
The CRISPR/Cas9 system has been adapted in recent years to allow the rapid generation of loss-of-function alleles in mammalian cells. The Functional Genomics Platform utilizes the CRISPR/Cas9 system to perform unbiased large-scale genetic screens in mammalian cells in culture. We use these screens to systematically identify genes involved in a given phenotype of interest using a sequencing-based readout. This screening approach is best suited to phenotypes that affect cell number (e.g., resistance or sensitivity to a drug), although more complex experimental designs may be possible.
Established in 2016, the purpose of the Functional Genomics Platform is to work with researchers to design, implement, and analyze the data from CRISPR/Cas9-based genetic screens. We serve the Whitehead community, as well as the larger MIT community and external collaborators. The platform is operated by Heather Keys, Ph.D., with assistance from a full-time technician, Maria Virgilio. The faculty advisor for the platform is David M. Sabatini, M.D., Ph.D.
The Functional Genomics Platform anticipates being able to accept new projects by September 2016, but please do not hesitate to contact us prior to then to discuss your project!
Recent research in cancer biology, aging, microbial pathogenesis, and many other areas has revealed a key role for small molecule and lipid metabolites in a wide range of biological processes. The Metabolite Profiling Core Facility was established in 2013 to support studies in this rapidly developing field. Due to the extreme chemical diversity of small molecules and lipids – which greatly exceeds that of proteins and nucleic acids – the facility operates on a collaborative model in which experimental design, sample preparation, data collection, and data analysis are tailored to each study. We serve the Whitehead as well as the larger MIT community and external collaborators.
The facility is operated by Elizaveta (Lisa) Freinkman, Ph.D., who assists researchers with experimental design and sample preparation strategies, performs LC/MS experiments, and analyzes data, in addition to developing new analytical techniques for metabolites that are not adequately measured by our existing methods. Also, a full-time technician, Tenzin Kunchok, performs routine instrument maintenance and sample preparation, and also assists with facility operations.
More information on the Metabolite Profiling Facility