Key Points
-
New biological understanding is emerging from the physical and chemical regimes that are found in microfluidic systems. The small volumes (sub-microlitre), predictable flows (low Reynolds number) and in vivo length scale and timescale matching of microfluidic devices underpin notable recent advances in molecular cell biology research.
-
Microfluidic tools combined with advanced molecular, imaging and bioinformatics techniques form a flexible 'toolbox' that life scientists are actively adopting and adapting to facilitate new lines of biological enquiry.
-
Microfluidic single-cell immunoassays can profile the secretomes and proteomes of thousands of cells in parallel. This has been used, for example, to study the population dynamics of glioma cells in terms of the effects of drug treatment on the PI3K pathway.
-
Emerging platforms for biophysical cytometry — which measure the mechanical properties of cells — offer a label-free cell screening platform for induced pluripotency and cancer diagnostics at a throughput rate that compares with that of fluorescence-based flow cytometry.
-
Water-in-oil droplet emulsions are being used to create discrete reaction vessels for high-throughput screening and directed evolution. Recent examples of the use of this strategy include antibody selection from hundreds of thousands of single hybridoma cells and high-resolution optimization of drug efficacy over a near-continuum of drug concentrations.
-
Precise temporal and spatial flow control in microfluidics make it a powerful platform for studying dynamic biological processes that occur over short timescales. Studies elucidating the dynamics of protein folding, signal transduction and the kinetics of transcription factor binding demonstrate the transient biological phenomena that have been made accessible for research using microfluidic tools.
-
Microfluidics allows researchers to deconstruct complex biological relationships by representing biology in tailored microenvironmental contexts, which can be perturbed in a controlled manner and closely monitored using, for example, real-time high-resolution imaging. In a prominent example, organ-on-a-chip platforms seek to recapitulate the functions of organs to create an in vitro model system for drug screening.
Abstract
The underlying physical properties of microfluidic tools have led to new biological insights through the development of microsystems that can manipulate, mimic and measure biology at a resolution that has not been possible with macroscale tools. Microsystems readily handle sub-microlitre volumes, precisely route predictable laminar fluid flows and match both perturbations and measurements to the length scales and timescales of biological systems. The advent of fabrication techniques that do not require highly specialized engineering facilities is fuelling the broad dissemination of microfluidic systems and their adaptation to specific biological questions. We describe how our understanding of molecular and cell biology is being and will continue to be advanced by precision microfluidic approaches and posit that microfluidic tools — in conjunction with advanced imaging, bioinformatics and molecular biology approaches — will transform biology into a precision science.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 12 print issues and online access
$189.00 per year
only $15.75 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Lanier, L. L. Just the FACS. J. Immunol. 193, 2043–2044 (2014).
Dovichi, N. J. & Zhang, J. Z. How capillary electrophoresis sequenced the human genome. Angew. Chem. Int. Ed. Engl. 39, 4463–4468 (2000).
Duffy, D. C., McDonald, J. C., Schueller, O. J. & Whitesides, G. M. Rapid prototyping of microfluidic systems in poly(dimethylsiloxane). Anal. Chem. 70, 4974–4984 (1998).
Agresti, J. J. et al. Ultrahigh-throughput screening in drop-based microfluidics for directed evolution. Proc. Natl Acad. Sci. USA 107, 4004–4009 (2010).
Shi, Q. et al. Single-cell proteomic chip for profiling intracellular signaling pathways in single tumor cells. Proc. Natl Acad. Sci. USA 109, 419–424 (2012). Multiplexed single-cell resolution immunoassays were used to directly correlate protein phosphorylation in a signalling pathway within a single cell, for thousands of cells in parallel.
El Debs, B., Utharala, R., Balyasnikova, I. V., Griffiths, A. D. & Merten, C. A. Functional single-cell hybridoma screening using droplet-based microfluidics. Proc. Natl Acad. Sci. USA 109, 11570–11575 (2012). The functional screening of secreted monoclonal antibodies from hundreds of thousands of single hybridoma cells expedites the process and reduces the cost of production of high quality monoclonal antibodies.
Beebe, D. J., Mensing, G. A. & Walker, G. M. Physics and applications of microfluidics in biology. Annu. Rev. Biomed. Eng. 4, 261–286 (2002).
Shapiro, H. M. Practical Flow Cytometry (John Wiley & Sons, 2005).
Takayama, S. et al. Patterning cells and their environments using multiple laminar fluid flows in capillary networks. Proc. Natl Acad. Sci. USA 96, 5545–5548 (1999).
Dudani, J. S., Gossett, D. R., Tse, H. T. & Di Carlo, D. Pinched-flow hydrodynamic stretching of single-cells. Lab Chip 13, 3728–3734 (2013).
Tse, H. T. et al. Quantitative diagnosis of malignant pleural effusions by single-cell mechanophenotyping. Sci. Transl Med. 5, 212ra163 (2013). The high-throughput cell deformability assay was developed for rapid and label-free diagnostic screening to accurately identify the malignant pleural effusions phenotype.
Gossett, D. R. et al. Hydrodynamic stretching of single cells for large population mechanical phenotyping. Proc. Natl Acad. Sci. USA 109, 7630–7635 (2012).
Unger, M. A., Chou, H. P., Thorsen, T., Scherer, A. & Quake, S. R. Monolithic microfabricated valves and pumps by multilayer soft lithography. Science 288, 113–116 (2000).
Stone, H. A., Stroock, A. D. & Ajdari, A. Engineering flows in small devices: microfluidics toward a lab-on-a-chip. Annu. Rev. Fluid Mech. 36, 381–411 (2004).
Huh, D. et al. Reconstituting organ-level lung functions on a chip. Science 328, 1662–1668 (2010). The biomimetic lung-on-a-chip system showed that cyclic mechanical strain accentuates toxic and inflammatory responses of the lung to silica nanoparticles — establishing the platform as a potential low-cost alternative to animal and clinical studies for drug screening and toxicology applications.
Bhatia, S. N. & Ingber, D. E. Microfluidic organs-on-chips. Nat. Biotechnol. 32, 760–772 (2014).
Geertz, M., Shore, D. & Maerkl, S. J. Massively parallel measurements of molecular interaction kinetics on a microfluidic platform. Proc. Natl Acad. Sci. USA 109, 16540–16545 (2012).
Fordyce, P. M. et al. De novo identification and biophysical characterization of transcription-factor binding sites with microfluidic affinity analysis. Nat. Biotechnol. 28, 970–975 (2010). In a single experiment, the binding affinities of 28 yeast transcription factors were measured against all possible 8-bp DNA sequences (a total of 65,536 sequences).
Jovic, A., Wade, S. M., Neubig, R. R., Linderman, J. J. & Takayama, S. Microfluidic interrogation and mathematical modeling of multi-regime calcium signaling dynamics. Integr. Biol. 5, 932–939 (2013).
Wang, P. et al. Robust growth of Escherichia coli. Curr. Biol. 20, 1099–1103 (2010).
Rafelski, S. M. et al. Mitochondrial network size scaling in budding yeast. Science 338, 822–824 (2012).
Xie, Z. et al. Molecular phenotyping of aging in single yeast cells using a novel microfluidic device. Aging Cell 11, 599–606 (2012).
Sun, J. et al. A microfluidic platform for systems pathology: multiparameter single-cell signaling measurements of clinical brain tumor specimens. Cancer Res. 70, 6128–6138 (2010).
Kim, M. S., Kwon, S., Kim, T., Lee, E. S. & Park, J. K. Quantitative proteomic profiling of breast cancers using a multiplexed microfluidic platform for immunohistochemistry and immunocytochemistry. Biomaterials 32, 1396–1403 (2011).
Ciftlik, A. T., Lehr, H. A. & Gijs, M. A. Microfluidic processor allows rapid HER2 immunohistochemistry of breast carcinomas and significantly reduces ambiguous (2+) read-outs. Proc. Natl Acad. Sci. USA 110, 5363–5368 (2013).
Yu, J. et al. Microfluidics-based single-cell functional proteomics for fundamental and applied biomedical applications. Annu. Rev. Anal. Chem. 7, 275–295 (2014).
Li, J. J., Bickel, P. J. & Biggin, M. D. System wide analyses have underestimated protein abundances and the importance of transcription in mammals. PeerJ 2, e270 (2014).
Tzur, A., Kafri, R., LeBleu, V. S., Lahav, G. & Kirschner, M. W. Cell growth and size homeostasis in proliferating animal cells. Science 325, 167–171 (2009).
Lin, L. et al. Human NK cells licensed by killer Ig receptor genes have an altered cytokine program that modifies CD4+ T cell function. J. Immunol. 193, 940–949 (2014).
Gerver, R. E. et al. Programmable microfluidic synthesis of spectrally encoded microspheres. Lab Chip 12, 4716–4723 (2012).
Lee, J. et al. Universal process-inert encoding architecture for polymer microparticles. Nat. Mater. 13, 524–529 (2014).
Ma, C. et al. A clinical microchip for evaluation of single immune cells reveals high functional heterogeneity in phenotypically similar T cells. Nat. Med. 17, 738–743 (2011).
Shin, Y. S. et al. Protein signaling networks from single cell fluctuations and information theory profiling. Biophys. J. 100, 2378–2386 (2011).
Konry, T., Dominguez-Villar, M., Baecher-Allan, C., Hafler, D. A. & Yarmush, M. L. Droplet-based microfluidic platforms for single T cell secretion analysis of IL-10 cytokine. Biosens. Bioelectron. 26, 2707–2710 (2011).
Hathout, Y. Approaches to the study of the cell secretome. Expert Rev. Proteomics 4, 239–248 (2007).
Sachs, K., Perez, O., Pe'er, D., Lauffenburger, D. A. & Nolan, G. P. Causal protein-signaling networks derived from multiparameter single-cell data. Science 308, 523–529 (2005).
Saper, C. B. An open letter to our readers on the use of antibodies. J. Comp. Neurol. 493, 477–478 (2005).
Hughes, A. J. et al. Single-cell western blotting. Nat. Methods 11, 749–755 (2014).
Kang, C. C., Lin, J. M., Xu, Z., Kumar, S. & Herr, A. E. Single-cell Western blotting after whole-cell imaging to assess cancer chemotherapeutic response. Anal. Chem. 86, 10429–10436 (2014).
[No authors listed.] Method of the Year 2013. Nat. Methods 11, 1 (2014).
Eberwine, J., Sul, J.-Y., Bartfai, T. & Kim, J. The promise of single-cell sequencing. Nat. Methods 11, 25–27 (2014).
Wu, A. R. et al. Quantitative assessment of single-cell RNA-sequencing methods. Nat. Methods 11, 41–46 (2014).
Streets, A. M. et al. Microfluidic single-cell whole-transcriptome sequencing. Proc. Natl Acad. Sci. USA 111, 7048–7053 (2014).
Wang, J., Fan, H. C., Behr, B. & Quake, S. R. Genome-wide single-cell analysis of recombination activity and de novo mutation rates in human sperm. Cell 150, 402–412 (2012).
Zong, C., Lu, S., Chapman, A. R. & Xie, X. S. Genome-wide detection of single-nucleotide and copy-number variations of a single human cell. Science 338, 1622–1626 (2012).
Shuga, J. et al. Single molecule quantitation and sequencing of rare translocations using microfluidic nested digital PCR. Nucleic Acids Res. 41, 1–11 (2013).
Marcy, Y. et al. Nanoliter reactors improve multiple displacement amplification of genomes from single cells. PLoS Genet. 3, 1702–1708 (2007).
Di Carlo, D., Wu, L. Y. & Lee, L. P. Dynamic single cell culture array. Lab Chip 6, 1445–1449 (2006).
Schoenberg, D. R. & Maquat, L. E. Regulation of cytoplasmic mRNA decay. Nat. Rev. Genet. 13, 246–259 (2012).
White, A. K. et al. High-throughput microfluidic single-cell RT-qPCR. Proc. Natl Acad. Sci. USA 108, 13999–14004 (2011).
White, A. K., Heyries, K. A., Doolin, C., Vaninsberghe, M. & Hansen, C. L. High-throughput microfluidic single-cell digital polymerase chain reaction. Anal. Chem. 85, 7182–7190 (2013).
Hashimshony, T., Wagner, F., Sher, N. & Yanai, I. CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification. Cell Rep. 2, 666–673 (2012).
Islam, S. et al. Highly multiplexed and strand-specific single-cell RNA 5′ end sequencing. Nat. Protoc. 7, 813–828 (2012).
Fletcher, D. A. & Mullins, R. D. Cell mechanics and the cytoskeleton. Nature 463, 485–492 (2010).
Pajerowski, J. D., Dahl, K. N., Zhong, F. L., Sammak, P. J. & Discher, D. E. Physical plasticity of the nucleus in stem cell differentiation. Proc. Natl Acad. Sci. USA 104, 15619–15624 (2007).
Mathur, A. B., Collinsworth, A. M., Reichert, W. M., Kraus, W. E. & Truskey, G. A. Endothelial, cardiac muscle and skeletal muscle exhibit different viscous and elastic properties as determined by atomic force microscopy. J. Biomech. 34, 1545–1553 (2001).
Rosenbluth, M. J., Lam, W. A. & Fletcher, D. A. Analyzing cell mechanics in hematologic diseases with microfluidic biophysical flow cytometry. Lab Chip 8, 1062–1070 (2008).
Adamo, A. et al. Microfluidics-based assessment of cell deformability. Anal. Chem. 84, 6438–6443 (2012).
Guo, Q. et al. Microfluidic analysis of red blood cell deformability. J. Biomech. 47, 1767–1776 (2014).
Zhang, W. et al. Microfluidics separation reveals the stem-cell-like deformability of tumor-initiating cells. Proc. Natl Acad. Sci. USA 109, 18707–18712 (2012).
Adewumi, O. et al. Characterization of human embryonic stem cell lines by the International Stem Cell Initiative. Nat. Biotechnol. 25, 803–816 (2007).
Chowdhury, F. et al. Material properties of the cell dictate stress-induced spreading and differentiation in embryonic stem cells. Nat. Mater. 9, 82–88 (2010).
Huberts, D. H. et al. Construction and use of a microfluidic dissection platform for long-term imaging of cellular processes in budding yeast. Nat. Protoc. 8, 1019–1027 (2013).
Rowat, A. C., Bird, J. C., Agresti, J. J., Rando, O. J. & Weitz, D. A. Tracking lineages of single cells in lines using a microfluidic device. Proc. Natl Acad. Sci. USA 106, 18149–18154 (2009).
Lee, S. S., Vizcarra, I. A., Huberts, D. H., Lee, L. P. & Heinemann, M. Whole lifespan microscopic observation of budding yeast aging through a microfluidic dissection platform. Proc. Natl Acad. Sci. USA 109, 4916–4920 (2012).
Sivagnanam, V. & Gijs, M. A. M. Exploring living multicellular organisms, organs, and tissues using microfluidic systems. Chem. Rev. 113, 3214–3247 (2013).
Busch, W. et al. A microfluidic device and computational platform for high-throughput live imaging of gene expression. Nat. Methods 9, 1101–1106 (2012).
Choudhury, D. et al. Fish and Chips: a microfluidic perfusion platform for monitoring zebrafish development. Lab Chip 12, 892–900 (2012).
Akagi, J. et al. Integrated chip-based physiometer for automated fish embryo toxicity biotests in pharmaceutical screening and ecotoxicology. Cytometry A 85, 537–547 (2014).
Akagi, J. et al. Opensource lab-on-a-chip physiometer for accelerated zebrafish embryo biotests. Curr. Protoc. Cytom. 67, 9.44.1–9.44.16 (2014).
Zheng, C. et al. Fish in chips: an automated microfluidic device to study drug dynamics in vivo using zebrafish embryos. Chem. Commun. 50, 981–984 (2014).
Kirby, B. J. Micro- and Nanoscale Fluid Mechanics: Transport in Microfluidic Devices (Cambridge University Press, 2010).
Hansen, A. S. & O'Shea, E. K. Promoter decoding of transcription factor dynamics involves a trade-off between noise and control of gene expression. Mol. Syst. Biol. 9, 1–14 (2013).
Morel, M. et al. Amplification and temporal filtering during gradient sensing by nerve growth cones probed with a microfluidic assay. Biophys. J. 103, 1648–1656 (2012).
McClean, M. N., Hersen, P. & Ramanathan, S. In vivo measurement of signaling cascade dynamics. Cell Cycle 8, 373–376 (2009).
Amir, A., Meshner, S., Beatus, T. & Stavans, J. Damped oscillations in the adaptive response of the iron homeostasis network of E. coli. Mol. Microbiol. 76, 428–436 (2010).
Maerkl, S. J. & Quake, S. R. A systems approach to measuring the binding energy landscapes of transcription factors. Science 315, 233–237 (2007).
Hens, K. et al. Automated protein-DNA interaction screening of Drosophila regulatory elements. Nat. Methods 8, 1065–1070 (2011).
Hernday, A. D. et al. Structure of the transcriptional network controlling white-opaque switching in Candida albicans. Mol. Microbiol. 90, 22–35 (2013).
Gubelmann, C. et al. A yeast one-hybrid and microfluidics-based pipeline to map mammalian gene regulatory networks. Mol. Syst. Biol. 9, 1–18 (2013).
Fordyce, P. M. et al. Basic leucine zipper transcription factor Hac1 binds DNA in two distinct modes as revealed by microfluidic analyses. Proc. Natl Acad. Sci. USA 109, E3084–E3093 (2012).
Martin, L. et al. Systematic reconstruction of RNA functional motifs with high-throughput microfluidics. Nat. Methods 9, 1192–1194 (2012).
Neveu, G. et al. Identification and targeting of an interaction between a tyrosine motif within hepatitis C virus core protein and AP2M1 essential for viral assembly. PLos Pathog. 8, e1002845 (2012).
Chiang, Y.-Y. & West, J. Ultrafast cell switching for recording cell surface transitions: new insights into epidermal growth factor receptor signalling. Lab Chip 13, 1031–1034 (2013).
Hughes, A. J., Tentori, A. M. & Herr, A. E. Bistable isoelectric point photoswitching in green fluorescent proteins observed by dynamic immunoprobed isoelectric focusing. J. Am. Chem. Soc. 134, 17582–17591 (2012).
Fazelinia, H., Xu, M., Cheng, H. & Roder, H. Ultrafast hydrogen exchange reveals specific structural events during the initial stages of folding of cytochrome c. J. Am. Chem. Soc. 136, 733–740 (2014). Ultra-fast microfluidic mixing for hydrogen–deuterium exchange enabled researchers to determine that decreased chain dimensions during the early stages of cytochrome c folding are due to specific α-helix interactions and not a general hydrophobic collapse of the protein.
Simpson, P. C. et al. High-throughput genetic analysis using microfabricated 96-sample capillary array electrophoresis microplates. Proc. Natl Acad. Sci. USA 95, 2256–2261 (1998).
Edwards, B. S., Oprea, T., Prossnitz, E. R. & Sklar, L. A. Flow cytometry for high-throughput, high-content screening. Curr. Opin. Chem. Biol. 8, 392–398 (2004).
Song, H., Chen, D. L. & Ismagilov, R. F. Reactions in droplets in microfluidic channels. Angew. Chem. Int. Ed. Engl. 45, 7336–7356 (2006).
Thorsen, T., Roberts, R. W., Arnold, F. H. & Quake, S. R. Dynamic pattern formation in a vesicle-generating microfluidic device. Phys. Rev. Lett. 86, 4163–4166 (2001).
Anna, S. L., Bontoux, N. & Stone, H. A. Formation of dispersions using “flow focusing” in microchannels. Appl. Phys. Lett. 82, 364 (2003).
Su, X. et al. Microfluidic cell culture and its application in high-throughput drug screening: cardiotoxicity assay for hERG channels. J. Biomol. Screen. 16, 101–111 (2011).
Rauch, J. N., Nie, J., Buchholz, T. J., Gestwicki, J. E. & Kennedy, R. T. Development of a capillary electrophoresis platform for identifying inhibitors of protein–protein interactions. Anal. Chem. 85, 9824–9831 (2013).
Desai, B. et al. Rapid discovery of a novel series of Abl kinase inhibitors by application of an integrated microfluidic synthesis and screening platform. J. Med. Chem. 56, 3033–3047 (2013).
Hansen, C. L., Skordalakes, E., Berger, J. M. & Quake, S. R. A robust and scalable microfluidic metering method that allows protein crystal growth by free interface diffusion. Proc. Natl Acad. Sci. USA 99, 16531–16536 (2002).
Guo, M. T., Rotem, A., Heyman, J. A. & Weitz, D. A. Droplet microfluidics for high-throughput biological assays. Lab Chip 12, 2146–2155 (2012).
Schneider, T., Kreutz, J. & Chiu, D. T. The potential impact of droplet microfluidics in biology. Anal. Chem. 85, 3476–3482 (2013).
Granieri, L., Baret, J. C., Griffiths, A. D. & Merten, C. A. High-throughput screening of enzymes by retroviral display using droplet-based microfluidics. Chem. Biol. 17, 229–235 (2010).
Wang, B. L. et al. Microfluidic high-throughput culturing of single cells for selection based on extracellular metabolite production or consumption. Nat. Biotechnol. 32, 473–478 (2014).
Miller, O. J. et al. High-resolution dose-response screening using droplet-based microfluidics. Proc. Natl Acad. Sci. USA 109, 378–383 (2012).
Klopfenstein, S. R. et al. 1,2,3,4-Tetrahydroisoquinolinyl sulfamic acids as phosphatase PTP1B inhibitors. Bioorg. Med. Chem. Lett. 16, 1574–1578 (2006).
Knowles, T. P. et al. Observation of spatial propagation of amyloid assembly from single nuclei. Proc. Natl Acad. Sci. USA 108, 14746–14751 (2011). This study of amyloid nucleation showed that cellular compartmentalization probably offers protection from uncontrolled fibril aggregation.
Hsiao, A. Y. et al. Microfluidic system for formation of PC-3 prostate cancer co-culture spheroids. Biomaterials 30, 3020–3027 (2009).
Kuo, C. T. et al. Modeling of cancer metastasis and drug resistance via biomimetic nano-cilia and microfluidics. Biomaterials 35, 1562–1571 (2014).
Zervantonakis, I. K. et al. Three-dimensional microfluidic model for tumor cell intravasation and endothelial barrier function. Proc. Natl Acad. Sci. USA 109, 13515–13520 (2012). An in vitro microfluidic model of a tumour–vascular interface yielded dynamic and high-resolution images of the progression of cancer intravasation.
Bersini, S. et al. A microfluidic 3D in vitro model for specificity of breast cancer metastasis to bone. Biomaterials 35, 2454–2461 (2014).
Zheng, Y. et al. In vitro microvessels for the study of angiogenesis and thrombosis. Proc. Natl Acad. Sci. USA 109, 9342–9347 (2012).
Nguyen, D. H. et al. Biomimetic model to reconstitute angiogenic sprouting morphogenesis in vitro. Proc. Natl Acad. Sci. USA 110, 6712–6717 (2013).
Nishida, N., Yano, H., Nishida, T., Kamura, T. & Kojiro, M. Angiogenesis in cancer. Vasc. Health Risk Manag. 2, 213–219 (2006).
Sung, J. H. et al. Microfabricated mammalian organ systems and their integration into models of whole animals and humans. Lab Chip 13, 1201–1212 (2013).
Martin, J. G. et al. Toward an artificial Golgi: redesigning the biological activities of heparan sulfate on a digital microfluidic chip. J. Am. Chem. Soc. 131, 11041–11048 (2009).
Wang, G. et al. Modeling the mitochondrial cardiomyopathy of Barth syndrome with induced pluripotent stem cell and heart-on-chip technologies. Nat. Med. 20, 616–623 (2014).
Ho, C. T. et al. Liver-cell patterning lab chip: mimicking the morphology of liver lobule tissue. Lab Chip 13, 3578–3587 (2013).
Ahmad, A. A. et al. Optimization of 3D organotypic primary colonic cultures for organ-on-chip applications. J. Biol. Eng. 8, 9 (2014).
Booth, R. & Kim, H. Characterization of a microfluidic in vitro model of the blood-brain barrier (muBBB). Lab Chip 12, 1784–1792 (2012).
Wilson, K., Das, M., Wahl, K. J., Colton, R. J. & Hickman, J. Measurement of contractile stress generated by cultured rat muscle on silicon cantilevers for toxin detection and muscle performance enhancement. PLoS ONE 5, e11042 (2010).
Karzbrun, E., Tayar, A. M., Noireaux, V. & Bar-Ziv, R. H. Synthetic biology. Programmable on-chip DNA compartments as artificial cells. Science 345, 829–832 (2014).
Esch, M. B., King, T. L. & Shuler, M. L. The role of body-on-a-chip devices in drug and toxicity studies. Annu. Rev. Biomed. Eng. 13, 55–72 (2011).
Sung, J. H. et al. Using physiologically-based pharmacokinetic-guided “body-on-a-chip” systems to predict mammalian response to drug and chemical exposure. Exp. Biol. Med. 239, 1225–1239 (2014).
Shamloo, A. et al. Complex chemoattractive and chemorepellent Kit signals revealed by direct imaging of murine mast cells in microfluidic gradient chambers. Integr. Biol. 5, 1076–1085 (2013).
Fuller, D. et al. External and internal constraints on eukaryotic chemotaxis. Proc. Natl Acad. Sci. USA 107, 9656–9659 (2010).
Justin, R. T. & Engler, A. J. Stiffness gradients mimicking in vivo tissue variation regulate mesenchymal stem cell fate. PLoS ONE 6, e15978 (2011).
Prentice-Mott, H. V. et al. Biased migration of confined neutrophil-like cells in asymmetric hydraulic environments. Proc. Natl Acad. Sci. USA 110, 21006–21011 (2013).
Xu, H. & Heilshorn, S. C. Microfluidic investigation of BDNF-enhanced neural stem cell chemotaxis in CXCL12 gradients. Small 9, 585–595 (2013).
Haessler, U., Pisano, M., Wu, M. & Swartz, M. A. Dendritic cell chemotaxis in 3D under defined chemokine gradients reveals differential response to ligands CCL21 and CCL19. Proc. Natl Acad. Sci. USA 108, 5614–5619 (2011).
Giridharan, G. A. et al. Microfluidic cardiac cell culture model (muCCCM). Anal. Chem. 82, 7581–7587 (2010).
Neeves, K. B., Illing, D. A. & Diamond, S. L. Thrombin flux and wall shear rate regulate fibrin fiber deposition state during polymerization under flow. Biophys. J. 98, 1344–1352 (2010).
Tsai, M. et al. In vitro modeling of the microvascular occlusion and thrombosis that occur in hematologic diseases using microfluidic technology. J. Clin. Invest. 122, 408–418 (2012).
Kuwano, Y., Spelten, O., Zhang, H., Ley, K. & Zarbock, A. Rolling on E- or P-selectin induces the extended but not high-affinity conformation of LFA-1 in neutrophils. Blood 116, 617–624 (2010).
Christophis, C. et al. Shear stress regulates adhesion and rolling of CD44+ leukemic and hematopoietic progenitor cells on hyaluronan. Biophys. J. 101, 585–593 (2011).
Vedel, S., Tay, S., Johnston, D. M., Bruus, H. & Quake, S. R. Migration of cells in a social context. Proc. Natl Acad. Sci. USA 110, 129–134 (2013).
Kravchenko-Balasha, N., Wang, J., Remacle, F., Levine, R. D. & Heath, J. R. Glioblastoma cellular architectures are predicted through the characterization of two-cell interactions. Proc. Natl Acad. Sci. USA 111, 6521–6526 (2014).
Sen, A. et al. Innate immune response to homologous rotavirus infection in the small intestinal villous epithelium at single-cell resolution. Proc. Natl Acad. Sci. USA 109, 20667–20672 (2012).
Uckun, F. M. et al. Serine phosphorylation by SYK is critical for nuclear localization and transcription factor function of Ikaros. Proc. Natl Acad. Sci. USA 109, 18072–18077 (2012).
Berthier, E., Young, E. W. K. & Beebe, D. Engineers are from PDMS-land, biologists are from Polystyrenia. Lab Chip 12, 1224–1237 (2012).
Hjerten, S. Free zone electrophoresis. Chromatogr. Rev. 9, 122–219 (1967).
Fulwyler, M. J. Electronic separation of biological cells by volume. Science 150, 910–911 (1965).
Coulter, W. Means for counting particles suspended in a fluid. US patent US2656508A (1953).
Manz, A., Graber, N. & Widmer, H. M. Miniaturized total chemical-analysis systems: a novel concept for chemical sensing. Sens. Actuators B Chem. 1, 244–248 (1990).
Kane, R. S., Takayama, S., Ostuni, E., Ingber, D. E. & Whitesides, G. M. Patterning proteins and cells using soft lithography. Biomaterials 20, 2363–2376 (1999).
Harrison, D. J., Manz, A., Fan, Z. H., Ludi, H. & Widmer, H. M. Capillary electrophoresis and sample injection systems integrated on a planar glass chip. Anal. Chem. 64, 1926–1932 (1992).
Emrich, C. A., Tian, H., Medintz, I. L. & Mathies, R. A. Microfabricated 384-lane capillary array electrophoresis bioanalyzer for ultrahigh-throughput genetic analysis. Anal. Chem. 74, 5076–5083 (2002).
Delamarche, E., Bernard, A., Schmid, H., Michel, B. & Biebuyck, H. Patterned delivery of immunoglobulins to surfaces using microfluidic networks. Science 276, 779–781 (1997).
Kazuo, H. & Ryutaro, M. A pneumatically-actuated three-way microvalve fabricated with polydimethylsiloxane using the membrane transfer technique. J. Micromech. Microeng. 10, 415 (2000).
Di Carlo, D. Inertial microfluidics. Lab Chip 9, 3038–3046 (2009).
Avila, K. et al. The onset of turbulence in pipe flow. Science 333, 192–196 (2011).
Acknowledgements
T.A.D. was supported by a US National Science Foundation Graduate Research Fellowship. A.M.T. was supported by a US Department of Homeland Security ORISE Fellowship, a Siebel Scholarship and a California Cancer Coordinating Committee Fellowship. This work was also supported by a US National Institutes of Health (NIH) New Innovator Award (DP2OD007294 to A.E.H.) and a UC Berkeley Bakar Fellowship (to A.E.H.).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The authors declare competing financial interests. T.A.D., A.M.T. and A.E.H. are co-inventors on patents related to microfluidic analysis, and A.E.H. has equity interest in a company commercializing a microfluidic analysis tool.
Glossary
- Laminar flow
-
A flow regime that is observed when the Reynolds number is less than 2,000 in pipe flow; in such cases, fluid moves in parallel stream lines or 'lamina'.
- Reynolds number
-
(Re). A dimensionless number that is defined as the ratio of inertial forces to viscous forces in a system. The value of Re increases with flow velocity and the characteristic length scale (of, for example, the channel diameter) and decreases with viscosity. Microfluidic flows typically have a low Re (<10), which results in laminar flow.
- Laminar flow patterning
-
Laminar patterning uses the slow mixing between multiple microfluidic flows with low Reynolds numbers for spatial patterning or to deliver soluble agents within the channel. The shape and location of patterning are controlled by modulating the relative flow rates of each fluid in the channel.
- Multiplexing
-
The measurement of multiple signals in parallel; that is, carrying out several assays simultaneously.
- Barcoding
-
The use of recognizable labels (tags) to track individual samples throughout an assay or to track the output of distinct assays from a single sample for multiplexing. Examples of such tags include DNA sequences, spectrally-encoded fluorescent beads and spatial patterning of capture reagents.
- Strouhal number
-
A dimensionless number that is defined as the ratio of inertial forces resulting from changes in velocity in the flow field to the inertial forces resulting from unsteady flow oscillation. The Strouhal number increases with flow velocity and decreases with the characteristic length scale of the channel and with oscillation frequency.
- Dissociation constant
-
(Kd). An equilibrium constant that describes the susceptibility of a complex to dissociate into its components. It is often used to describe how strongly molecules interact.
- Directed evolution
-
A method for the engineering of new biomolecules using the principle of natural selection. Typically, several rounds of selection are used.
- Taylor–Aris dispersion
-
A phenomenon that can enhance effective diffusion when there is a non-uniform flow velocity across a channel, as is typically the case in pressure-driven microfluidic flows.
- Intravasation
-
The invasion of cancer cells through the basement membrane into a blood or lymphatic vessel, which is a crucial step in cancer metastasis.
Rights and permissions
About this article
Cite this article
Duncombe, T., Tentori, A. & Herr, A. Microfluidics: reframing biological enquiry. Nat Rev Mol Cell Biol 16, 554–567 (2015). https://doi.org/10.1038/nrm4041
Published:
Issue Date:
DOI: https://doi.org/10.1038/nrm4041
This article is cited by
-
Microfluidics for adaptation of microorganisms to stress: design and application
Applied Microbiology and Biotechnology (2024)
-
Functional precision oncology using patient-derived assays: bridging genotype and phenotype
Nature Reviews Clinical Oncology (2023)
-
A ‘print–pause–print’ protocol for 3D printing microfluidics using multimaterial stereolithography
Nature Protocols (2023)
-
Microfluidic dose–response platform to track the dynamics of drug response in single mycobacterial cells
Scientific Reports (2022)