Collaborators

• T. Daniel, Univ. Washington
• H. Ploegh, MIT
• P. Sorger, Harvard Med. School
• J. White, MIT

Postdoctoral Associates

• M. Castellarnau
• T. Honegger
• C. T. Lo
• J. Prieto
• T. Sun

Graduate Students

• A. Dighe, Research Asst., ME
• B. Dura, Research Asst., EECS
• L. Pryzbyla, Res. Asst., Biology
• H.-W. Su, Research Asst., EECS
• S. Varma, Research Asst., EECS

Support Staff

• C. Collins, Administrative Assistant

Publications

M. D. Vahey and J. Voldman, “Isodielectric separation and analysis of cells,” in Single-cell analysis: Methods and protocols, S. Lindström and H. Andersson-Svahn, Eds.: Springer Science+Business Media, 2012, pp. 53-63.

W. M. Tsang, A. L. Stone, D. Otten, Z. N. Aldworth, T. L. Daniel, J. G. Hildebrand, R. D. Levine, and J. Voldman, “Insect-machine interface: A carbon nanotube-enhanced flexible neural probe,” Journal of Neuroscience Methods, vol. 204, pp. 355-65, 2012.

L. M. Przybyla and J. Voldman, “Attenuation of extrinsic signaling reveals the importance of matrix remodeling on maintenance of embryonic stem cell self-renewal,” Proceedings of the National Academy of Sciences, vol. 109, pp. 835-840, January 17, 2012 2012.

L. Przybyla and J. Voldman, “Probing embryonic stem cell autocrine and paracrine signaling using microfluidics,” Annual Review of Analytical Chemistry, 2012.

M. D. Vahey and J. Voldman, “Emergent behavior in particle-laden microfluidic systems informs strategies for improving cell and particle separations,” Lab on a Chip, vol. 11, pp. 2071-2080, 2011.

Y.-C. Toh and J. Voldman, “Fluid shear stress primes mouse embryonic stem cells for differentiation in a self-renewing environment via heparan sulfate proteoglycans transduction,” Faseb Journal, vol. 25, pp. 1208-17, 2011.

Y.-C. Toh, K. Blagovic, H. Yu, and J. Voldman, “Differential environmental spatial patterning (δesp) recreates proximal-distal axial patterns in embryonic stem cell colonies,” in Micro Total Analysis Systems Seattle, WA USA, 2011, pp. 30-32.

Y.-C. Toh, K. Blagovic, H. Yu, and J. Voldman, “Spatially organized in vitro models instruct asymmetric stem cell differentiation,” Integrative Biology, vol. 3, pp. 1179-1187, 2011.

T. Sun and J. Voldman, “Image-based screening of high-performing clones using photoactivated cell sorting via dual photopoylmerized microwell arrays,” in Micro Total Analysis Systems Seattle, WA USA, 2011, pp. 693-5.

N. Mittal and J. Voldman, “Non-mitogenic survival-enhancing autocrine factors including cyclophilin a contribute to density-dependent mesc growth,” Stem Cell Research, vol. 6, pp. 168-76, 2011.

M. M. Hoehl, S. K. Dougan, H. L. Ploegh, and J. Voldman, “Massively parallel microfluidic cell-pairing platform for the statistical study of immunolgical cell-cell interactions,” in Micro Total Analysis Systems Seattle, WA USA, 2011, pp. 1508-10.

S. P. Desai and J. Voldman, “Cell-based sensors for quantifying the physiological impact of microsystems,” Integrative Biology, vol. 3, pp. 48-56, 2011.

K. Blagovic, L. Y. Kim, and J. Voldman, “Microfluidic perfusion for regulating diffusible signaling in stem cells,” PLoS ONE, vol. 6, p. e22892, 2011.

The vision of the Medical Electronic Device Research Center (MEDRC) is to transform the medical electronic device industry: to revolutionize medical diagnostics and treatments, bringing health care directly to the individual; and to create enabling technology for the future information-driven healthcare system. Specific areas that show promise are wearable or minimally invasive monitoring devices, medical imaging, laboratory instrumentation, and the data communication from these devices and instruments to healthcare providers and caregivers.

The MEDRC establishes a partnership between the microelectronics industry, the medical devices industry, medical professionals, and MIT to collaboratively achieve improvements in the cost and performance of medical electronic devices similar to those that have occurred in personal computers, communication devices and consumer electronics. The Medical Electronic Device Realization Center (MEDRC) was established to better connect industry, academia, and physicians.  In the MEDRC, research activities are jointly defined by faculty, physicians and clinicians, and industrial partners.  A visiting scientist from a project’s sponsoring company is present at MIT.  Ultimately this individual is the champion that helps translate the technology back to the company for commercialization and provide the industrial viewpoint in the realization of the technology.    We foster the creation of prototype devices and intellectual property in the field of medical electronic systems and serve as a catalyst for the successful deployment of innovative healthcare technology at an affordable price.

MEDRC projects have the advantage of insight from the technology arena, the medical arena, and the business arena, thus significantly increasing the chances that their devices will fulfill a real healthcare need as well as be profitable for companies to ensure a stable supply of the new devices.  With a new trend toward increased healthcare quality, disease prevention, and cost-effectiveness, such a comprehensive perspective is crucial.

The collective aim of the MEDRC is to revolutionize medical diagnostics and treatments, bringing health care directly to the individual, and creating technology for the future of information-driven healthcare.   We focus on areas of medical devices that are enabled and enhanced by electronics and computation – imaging, point-of-care devices, diagnostics and therapeutic instrumentation, ambulatory physiological monitors, etc.

The MEDRC serves as a focal point for large business, for venture-funded startups, and for the medical community. The Center fosters the creation of prototype devices and intellectual property and aims to serve as the catalyst for the deployment of innovative healthcare technology that will reduce the cost of healthcare in both the developed and developing world. Current members are Analog Devices, GE Global Research/Healthcare, and Maxim Integrated Products.

A major challenge in immunobiology is to better understand how the immune cells dynamically interact with each other and with their environment. Any insights in that direction can help provide a clearer picture of the immune response’s evolution and reaction to infectious diseases; to this end, the use of clinical samples is extremely valuable ^[1] . However, most of the current analytical techniques used to characterize cells in a sample (e.g., ELISA, flow cytometry, PCR, DNA/RNA sequencing) do not preserve the cells after the analysis, and they typically fail to give multiple parameters of interest from the same sample. In addition, those analyses return only a snapshot of the sample state at a given time, which in most cases cannot be realistically compared with the in vivo conditions. Therefore, there is a need to develop new approaches for high-throughput and multiparameter analyses on clinical samples in a time-dependent manner and with single-cell resolution, to obtain the maximum information from a clinical sample.

Recently developed single-cell, multiparameter analytical platforms ^{[2] [3]} are oriented to this purpose and can be complemented with DNA/RNA analysis and sequencing to provide a complete picture of the immune cells from a sample, as illustrated in Figure 1. Nevertheless, linking the results of those different approaches requires keeping the identity of the cells all along the multiple analyses. The proposed solution consists of four steps (i) a stochastic bead-based labeling of the cells of interest in the multiparameter analytical platform, (ii)  imaging of the labeled cells, (iii) an optical cell release to allow sorting of the selected cells ^[4] and finally, (iv) a read-out of the labels on the cells in the final platform to re-assign the cell identity.

Figure 1: Schematic of the envisioned multiparameter analytical platform. (A) Cells settle down in a microwell array for multiparameter dynamic analysis. (B) Cells randomly labeled with beads. (C) Imaging of the labels on selected cells. (D) Optical-based sorting of the selected cells for genetic analysis.

1. T. D. Querec, R. S. Akondy, E. K. Lee, W. Cao, H. I. Nakaya, D. Teuwen, A. Pirani, K. Gernert, J. Deng, B. Marzolf, K. Kennedy, H. Wu, S. Bennouna, H. Oluoch, J. Miller, R. Z. Vencio, M. Mulligan, A. Aderem, R. Ahmed, and B. Pulendran, “Systems biology approach predicts immunogenicity of the yellow fever vaccine in humans,” Nature Immunology, vol. 10, pp. 116-125, 2008.
2. J. C. Love, J. L. Ronan, G. M. Grotenbreg, A. G. van der Veen, and H. L. Ploegh, “A microengraving method for rapid selection of single cells producing antigen-specific antibodies,” Nature Biotechnology, vol. 24, pp. 703-707, 2006.
3. J. C. Love, “Integrated process design for single-cell analytical technologies,” AIChE Journal, vol. 56, pp. 2496-2502, 2010.
4. J. R. Kovac and J. Voldman, “Intuitive, Image-Based Cell Sorting Using Optofluidic Cell Sorting,” Analytical Chemistry, vol. 79, pp. 9321-9330, 2007.

Interfaces with the nervous system are important for understanding basic neurobiology and for neuromedicine.  We are part of a multi-university NSF Engineering Research Center (ERC) focused on sensorimotor neural engineering.  One of the challenges that our team is addressing is making multi-functional interfaces with the nervous system.  This work builds upon a previous collaboration developing flexible multi-site electrodes (FME) for insect flight control that directly interfaced with the animal’s central nervous system (Figure 1).  The FMEs are made of two layers of polyimide with gold sandwiched in between in a split-ring geometry using standard MEMS processing (Figure 2) ^[1] . The FMEs have a novel split-ring design that incorporates the anatomical bi-cylinder structure of the nerve cord of the moth Manduca Sexta. Additionally, we integrated carbon nanotube (CNT)-Au nanocomposites into the FMEs to enhance the charge injection capability of the electrode.

As part of the NSF ERC, we are working with collaborators to extend this work by integrating the latest knowledge on electrode design into the probes.  We are also investigating addition of multi-functionality to the probes, for example integrating both sensing and actuation modalities onto the same device.  This integration would allow closed-loop operation of the probes, which we believe will have applicability both to uncover the basic mechanisms behind neurological disorders as well as to serve as eventual “smart” therapeutic devices.

1. W. M. Tsang, A. Stone, Z. Aldworth, D. Otten, T. Akinwande, T. Daniel, J. G. Hildebrand, R. Levine, and J. Voldman, “Remote control of a cyborg moth using carbon nanotube-enhanced flexible neuroprosthetic probe,” in Proc. IEEE MEMS, 2010, pp. 39-42.

The use of microsystems to manipulate and study cells in microenvironments is continually increasing.  However, along with such increase in usage comes a growing concern regarding the impact of these microsystems on cell physiology.  In this project, we are developing a set of cell-based fluorescent sensors to measure the impact of common stresses experienced in microsystems on cell physiology.  We are including stress agents commonly found in microsystems (e.g., UV exposure, heat shock, fluid flow, etc.).  Each sensor is designed to respond to one particular stress agent but can also be combined for multiplexed analysis of multiple stresses at once, as might be experienced in a typical microsystem.  Each sensor will use different colors to both indicate the type of sensor and the strength of the signal, to ease multiplexed analysis.

We are currently developing a sensor that responds to activation of the p53 protein pathway, for generalized DNA damage analysis.  Similar to the heat shock sensor we previously reported ^{[1] [2]} , which coupled fluorescent protein expression to activation of heat shock factor 1, the DNA damage sensor will couple fluorescent protein expression to activation of p53.  The new sensor will have cyan (cerulean) as the constitutive color and red (RFP) as the activation color.  Figure 1 shows the DNA damage sensor response after 30 min of UV exposure.  One of the more relevant sources for physiological stress on cells cultured in microfluidic devices is shear stress. Construction of a shear stress sensor cell line requires an understanding and characterization of the gene expression mechanisms and mechanotransduction pathways, especially since the pathways are known to have a varying correlation towards cell types, magnitudes, and dynamics of applied stresses. Therefore, we are using a multi-flow microfluidic device (see Figure 2) that can simultaneously apply different flows to cells across a 1000× range to first understand the behavior of NIH3T3 mouse fibroblast cells under flow ^[3] .  Specifically, these cells are seeded in 6 chambers concurrently, exposed to flow for 1-6 hours, and assayed for gene expression changes. Once they are characterized, we will construct a transfected NIH3T3 cell line with RFP expression correlating to shear stress.

1. S. P. Desai and J. Voldman, “Cell-based sensors for quantifying the physiological impact of microsystems,” Integrative Biology, vol. 3, pp. 48-56, 2011.
2. S. P. Desai and J. Voldman, “Measuring the impact of dielectrophoresis on cell physiology using a high-content screening platform,” in Micro Total Analysis Systems, 2008, pp. 1308-10.
3. Y.-C. Toh and J. Voldman, “Fluid shear stress primes mouse embryonic stem cells for differentiation in a self-renewing environment via heparan sulfate proteoglycans transduction,” Faseb Journal, vol. 25, pp. 1208-17, 2011.

The development of new techniques to separate and characterize cells with high throughput has been essential to many advances in biology and biotechnology.  We are developing a novel method for the simultaneous separation and characterization of cells based upon their electrical properties.  This method, iso-dielectric separation (IDS), uses dielectrophoresis (the force on a polarizable object ^[1] ) and a medium with spatially varying conductivity to sort electrically distinct cells while measuring their effective conductivity (Figure 1).  It is similar to iso-electric focusing except that it uses DEP instead of electrophoresis to concentrate cells and particles to the region in a conductivity gradient where their polarization charge vanishes ^{[2] [3] [4]} .

Sepsis is a clinical condition caused by infection; despite state-of-the-art facilities and treatments, sepsis has a mortality rate of ~30%. Sepsis induces inflammation and organ failure and a possible treatment would require removing inflammatory agents from whole blood such as activated neutrophils. Using an automated IDS system (see Figure 2a) we could see electrical differences between white and red blood cells (Figure 2b). Furthermore, we measured the electrical properties of activated vs. non-activated neutrophils (see Figure 2c). The populations show differences that indicate that the populations are amenable to efficient separation. Using the position as a classifier to determine if a neutrophil is activated or non-activated yields receiver operating characteristic (ROC) curves with high area-under-curve (AUC), which would result in good specificity (see Figure 2d).

1. H. A. Pohl and J. S. Crane, “Dielectrophoresis of cells,” Biophysical Journal, vol. 11, pp. 711-727, 1971.
2. M. D. Vahey and J. Voldman, “An equilibrium method for continuous-flow cell sorting using cielectrophoresis,” Analytical Chemistry, vol. 80, no. 9, pp. 3135-3143, 2008.
3. M. D. Vahey and J. Voldman,  “Iso-dielectric separation: A new method for the continuous-flow screening of cells,” Micro Total Analysis Systems ’06, vol. 2, pp. 1058-1060, 2006.
4. M. D. Vahey and J. Voldman, “High-throughput cell and particle characterization using isodielectric separation,” Analytical Chemistry, vol. 81, no. 7, pp. 2446-2455, 2009.

Stem cell phenotype and function are influenced by microenvironmental cues that include cell-cell, cell-extracellular matrix (ECM), and cell-media interactions (i.e., diffusible signaling), which we can control using microscale systems. Our research focuses on cell-ECM and cell-media control of mouse embryonic stem cells (mESCs). Cells are constantly secreting and responding to soluble signals, the removal of which can be mediated by modulating flow properties at the microscale ^[1] . To assess the contribution of cell-secreted factors to mESC differentiation and self-renewal, we utilized a two-layer microfluidic perfusion device allowing for parallel comparison of different cell culture conditions (see Figure 1A).

Our results demonstrate that mESCs do not grow in differentiation conditions with minimal autocrine signaling, even with supplementation by Fgf4, a signal that has been shown to be a crucial factor in differentiation toward a neuronal stem cell fate, while they do grow when supplemented with media saturated with soluble signals (conditioned media, CM) (see Figure 1B). Consistent with this effect, inhibiting the Fgf4 receptor does not affect growth of mESCs in differentiation conditions (as Figure 1C shows), but it does affect differentiation toward a neuronal stem cell fate (as in Figure 1D) ^[2] .

ESCs grown under self-renewal conditions are able to proliferate without conditioned media, but they lose expression of the self-renewal marker Nanog (see Figure 2A), results that, together with signaling and downstream differentiation assays, indicate differentiation towards an epiblast-like state under conditions that had previously been shown to be sufficient for self-renewal. This differentiation can be reversed by disrupting the ECM using sodium chlorate, which affects the ability of growth factors to bind to the ECM (as Figure 2B shows). This effect is evident based on colony morphology and can be duplicated by disrupting the matrix using collagenase (see Figure 2C) ^[3] . Together, these results indicate the importance of diffusible cell-secreted signals for mESC growth and ECM-based signals for mESC self-renewal.

1. L. Przybyla and J. Voldman, “Probing embryonic stem cell autocrine and paracrine signaling using microfluidics,” Annual Review of Analytical Chemistry, vol. 5, pp. 293-315, Mar. 2012.
2. K. Blagovic, L. Y. Kim, and J. Voldman, “Microfluidic perfusion for regulating diffusible signaling in stem cells,” PLoS ONE, vol. 6, p. e22892, Nov. 2011.
3. L. M. Przybyla and J. Voldman, “Attenuation of extrinsic signaling reveals the importance of matrix remodeling on maintenance of embryonic stem cell self-renewal,” in Proc. Natl. Acad. Sci. U.S.A., 2012, vol. 109, pp. 835-840.

Microfluidic approaches to cell sorting include purely dielectrophoretic (DEP) trap arrays ^[1] , passive hydrodynamic trap arrays with active DEP-based cell release ^[2] , and passive microwell arrays with optical cell release to permit sorting of non-adhered cells ^[3] .  As in the preceding technologies, we developed an image-based single-cell sorting method that enables parallel cell sorting using a dual-photopolymerization scheme. Our approach enables simultaneously sorting multiple cells of interest following high-resolution imaging with high purity using a method that requires only common equipment at modest cost. Our overall approach was to spatially segregate cells using a microwell array, image them, and then remove desired cells from the array by encapsulating all the undesired cells in a photopolymer (see Figure 1).  To demonstrate the sorting of minority populations (e.g., rare cell isolation), we mixed the GFP- and mCherry-expressing cells at a ratio of 1:100 and targeted to sort the GFP-expressing cells, while RFP-expressing cells were undesired.  First, the desired GFP-expressing cells were targeted via microscopy (as Figure 2a shows). The desired GFP-expressing cell in the center was isolated from its surrounding mCherry-expressing cells by the photopolymerized PEGDA sorting well, while the undesired mCherry-expressing cells were encapsulated in the cross-linked gel (in Figure 2b, the gel is autofluorescent in the green channel). Finally, the desired GFP-expressing cells were removed by simply washing the array, leaving the undesired mCherry-expressing cell (see Figure 2c).  Figure 2d shows a 1 mm × 1.4 mm region of the array after the desired cells were sorted. The two layers of microwells are evident: the trapping wells made from the photopolymerized optical adhesive and the sorting wells made from the photopolymerized PEGDA hydrogel. The overall technique requires standard equipment found in biological labs and inexpensive reagents (<$10 per experiment), encouraging widespread adoption.

1. J. R. Kovac, B. M. Taff, and J. Voldman, “Enabling technologies for image-based cell sorting,” in Methods in Bioengineering, M. Yarmush, R. Langer, Eds. 2009.
2. B. M. Taff, S. P. Desai, and J. Voldman, “Electroactive hydrodynamic weirs for micro-particle manipulation and patterning,” Applied Physics Letters, vol. 94, no. 8, p. 084102, 2009.
3. J. R. Kovac and J. Voldman, “ Intuitive, image-based cell sorting using opto-fluidic cell sorting,” Analytical Chemistry, vol. 79, pp. 9321-9330, 2007.