Scott Manalis has been a faculty member at MIT since 1999. He received the B.S. degree in physics from the University of California, Santa Barbara in 1994, and the PhD degree in applied physics from Stanford University, Palo Alto, CA in 1998.
The Manalis laboratory develops quantitative and real-time techniques for biomolecular detection and single cell analysis. We use conventional silicon processing techniques to fabricate fluidic devices, and exploit the unique physical properties associated with micro- and nanoscale dimensions for developing precision measurement methods.
The laboratory has developed a technology that enables mass to be measured in the aqueous environment with a resolution that is more than a million-fold better than existing methods. This approach, known as the suspended microchannel resonator (SMR), places the fluid inside of the resonator instead of immersing the resonator in the fluid and thereby solves the long-standing problem of signal degradation from viscous drag. This has enabled single cells, nanoparticles and biomolecules to be weighed in solution with sub-femtogram resolution.
The lab is currently exploring a wide range of biological applications with the SMR. For example, they are using the SMR's ability to resolve mammalian cell mass with a precision near ~0.01% to investigate how cell growth relates to progression through the division cycle, and if the response of cancer cells to pathway-directed therapeutics can be classified according to subtle changes in growth.
The Manalis laboratory is also developing approaches for measuring physical properties of single cells with high precision and high throughput. Examples include: i) using intracellular water exchange for measuring changes in dry mass, water content and chemical composition of the cell, and ii) characterizing the deformability and surface friction of cancer cells. Ultimately, the ability to combine multi-parameter physical with molecular measurements at the single-cell level could not only be used to further understanding of important cellular processes such as malignant transformation but may also be used to increase the predictive power of clinical diagnostics.