High signal-to-noise ratio ultra-compact lab-on-a-chip microflow cytometer enabled by silicon optical antennas

[EN] We experimentally demonstrate an all-silicon nanoantenna-based micro-optofluidic cytometer showing a combination of high signal-to-noise ratio (SNR) > 14 dB and ultra-compact size. Thanks to the ultra-high directivity of the antennas (>150), which enables a state-of-the-art sub-micron resolution, we are able to avoid the use of the bulky devices typically employed to collimate light on chip (such as lenses or fibers). The nm-scale antenna cross section allows a dramatic reduction of the optical system footprint, from the mm-scale of previous approaches to a few mu m(2), yielding a notable reduction in the fabrication costs. This scheme paves the way to ultra-compact lab-on-a-chip devices that may enable new applications with potential impact on all branches of biological and health science.Funding from grant TEC2015-63838-C3-1-R OPTONANOSENS (MINECO/FEDER, UE) is acknowledged. C. G.-M. acknowledges support from project TEC2015-73581-JIN PHUTURE (AEI/FEDER, UE). This work was also supported by the EU-funded projects FP7-ICT PHOXTROT (No. 318240), the EU-funded H2020-FET-HPC EXANEST (No. 671553) and the Generalitat Valenciana's PROMETEO grant NANOMET PLUS (PROMETEO II/2014/34).Lechago-Buendia, S.; García Meca, C.; Sánchez Losilla, N.; Griol Barres, A.; Martí Sendra, J. (2018). High signal-to-noise ratio ultra-compact lab-on-a-chip microflow cytometer enabled by silicon optical antennas. Optics Express. 26(20):25645-25656. https://doi.org/10.1364/OE.26.02564525645256562620Redding, B., Liew, S. F., Sarma, R., & Cao, H. (2013). Compact spectrometer based on a disordered photonic chip. Nature Photonics, 7(9), 746-751. doi:10.1038/nphoton.2013.190Malinauskas, M., Žukauskas, A., Hasegawa, S., Hayasaki, Y., Mizeikis, V., Buividas, R., & Juodkazis, S. (2016). Ultrafast laser processing of materials: from science to industry. Light: Science & Applications, 5(8), e16133-e16133. doi:10.1038/lsa.2016.133Fan, X., & White, I. M. (2011). Optofluidic microsystems for chemical and biological analysis. Nature Photonics, 5(10), 591-597. doi:10.1038/nphoton.2011.206Zheludev, N. I., & Kivshar, Y. S. (2012). From metamaterials to metadevices. Nature Materials, 11(11), 917-924. doi:10.1038/nmat3431Zhang, Y., Watts, B., Guo, T., Zhang, Z., Xu, C., & Fang, Q. (2016). Optofluidic Device Based Microflow Cytometers for Particle/Cell Detection: A Review. Micromachines, 7(4), 70. doi:10.3390/mi7040070Chen, X., Li, C., & Tsang, H. K. (2011). Device engineering for silicon photonics. NPG Asia Materials, 3(1), 34-40. doi:10.1038/asiamat.2010.194Luka, G., Ahmadi, A., Najjaran, H., Alocilja, E., DeRosa, M., Wolthers, K., … Hoorfar, M. (2015). Microfluidics Integrated Biosensors: A Leading Technology towards Lab-on-a-Chip and Sensing Applications. Sensors, 15(12), 30011-30031. doi:10.3390/s151229783Padgett, M., & Bowman, R. (2011). Tweezers with a twist. Nature Photonics, 5(6), 343-348. doi:10.1038/nphoton.2011.81Yih Shiau. (1976). Dielectric Rod Antennas for Millimeter-Wave Integrated Circuits (Short Papers). IEEE Transactions on Microwave Theory and Techniques, 24(11), 869-872. doi:10.1109/tmtt.1976.1128980Brongersma, M. L. (2008). Engineering optical nanoantennas. Nature Photonics, 2(5), 270-272. doi:10.1038/nphoton.2008.60Alù, A., & Engheta, N. (2010). Wireless at the Nanoscale: Optical Interconnects using Matched Nanoantennas. Physical Review Letters, 104(21). doi:10.1103/physrevlett.104.213902Novotny, L., & van Hulst, N. (2011). Antennas for light. Nature Photonics, 5(2), 83-90. doi:10.1038/nphoton.2010.237Giannini, V., Fernández-Domínguez, A. I., Heck, S. C., & Maier, S. A. (2011). Plasmonic Nanoantennas: Fundamentals and Their Use in Controlling the Radiative Properties of Nanoemitters. Chemical Reviews, 111(6), 3888-3912. doi:10.1021/cr1002672Sun, J., Timurdogan, E., Yaacobi, A., Hosseini, E. S., & Watts, M. R. (2013). Large-scale nanophotonic phased array. Nature, 493(7431), 195-199. doi:10.1038/nature11727Van Acoleyen, K., Rogier, H., & Baets, R. (2010). Two-dimensional optical phased array antenna on silicon-on-Insulator. Optics Express, 18(13), 13655. doi:10.1364/oe.18.013655García-Meca, C., Lechago, S., Brimont, A., Griol, A., Mas, S., Sánchez, L., … Martí, J. (2017). On-chip wireless silicon photonics: from reconfigurable interconnects to lab-on-chip devices. Light: Science & Applications, 6(9), e17053-e17053. doi:10.1038/lsa.2017.53Robinson, J. P., & Roederer, M. (2015). Flow cytometry strikes gold. Science, 350(6262), 739-740. doi:10.1126/science.aad6770Mao, X., Nawaz, A. A., Lin, S.-C. S., Lapsley, M. I., Zhao, Y., McCoy, J. P., … Huang, T. J. (2012). An integrated, multiparametric flow cytometry chip using «microfluidic drifting» based three-dimensional hydrodynamic focusing. Biomicrofluidics, 6(2), 024113. doi:10.1063/1.3701566Huang, N.-T., Zhang, H., Chung, M.-T., Seo, J. H., & Kurabayashi, K. (2014). Recent advancements in optofluidics-based single-cell analysis: optical on-chip cellular manipulation, treatment, and property detection. Lab Chip, 14(7), 1230-1245. doi:10.1039/c3lc51211hPsaltis, D., Quake, S. R., & Yang, C. (2006). Developing optofluidic technology through the fusion of microfluidics and optics. Nature, 442(7101), 381-386. doi:10.1038/nature05060Cheung, K. C., Di Berardino, M., Schade-Kampmann, G., Hebeisen, M., Pierzchalski, A., Bocsi, J., … Tárnok, A. (2010). Microfluidic impedance-based flow cytometry. Cytometry Part A, 77A(7), 648-666. doi:10.1002/cyto.a.20910Cheung, K., Gawad, S., & Renaud, P. (2005). Impedance spectroscopy flow cytometry: On-chip label-free cell differentiation. Cytometry Part A, 65A(2), 124-132. doi:10.1002/cyto.a.20141Xie, X., Cheng, Z., Xu, Y., Liu, R., Li, Q., & Cheng, J. (2017). A sheath-less electric impedance micro-flow cytometry device for rapid label-free cell classification and viability testing. Analytical Methods, 9(7), 1201-1212. doi:10.1039/c6ay03326aBlasi, T., Hennig, H., Summers, H. D., Theis, F. J., Cerveira, J., Patterson, J. O., … Rees, P. (2016). Label-free cell cycle analysis for high-throughput imaging flow cytometry. Nature Communications, 7(1). doi:10.1038/ncomms10256Soref, R. (2006). The Past, Present, and Future of Silicon Photonics. IEEE Journal of Selected Topics in Quantum Electronics, 12(6), 1678-1687. doi:10.1109/jstqe.2006.883151Frankowski, M., Theisen, J., Kummrow, A., Simon, P., Ragusch, H., Bock, N., … Neukammer, J. (2013). Microflow Cytometers with Integrated Hydrodynamic Focusing. Sensors, 13(4), 4674-4693. doi:10.3390/s130404674Barat, D., Spencer, D., Benazzi, G., Mowlem, M. C., & Morgan, H. (2012). Simultaneous high speed optical and impedance analysis of single particles with a microfluidic cytometer. Lab Chip, 12(1), 118-126. doi:10.1039/c1lc20785gTesta, G., Persichetti, G., & Bernini, R. (2014). Micro flow cytometer with self-aligned 3D hydrodynamic focusing. Biomedical Optics Express, 6(1), 54. doi:10.1364/boe.6.000054Etcheverry, S., Faridi, A., Ramachandraiah, H., Kumar, T., Margulis, W., Laurell, F., & Russom, A. (2017). High performance micro-flow cytometer based on optical fibres. Scientific Reports, 7(1). doi:10.1038/s41598-017-05843-7Kosako, T., Kadoya, Y., & Hofmann, H. F. (2010). Directional control of light by a nano-optical Yagi–Uda antenna. Nature Photonics, 4(5), 312-315. doi:10.1038/nphoton.2010.34Taillaert, D., Van Laere, F., Ayre, M., Bogaerts, W., Van Thourhout, D., Bienstman, P., & Baets, R. (2006). Grating Couplers for Coupling between Optical Fibers and Nanophotonic Waveguides. Japanese Journal of Applied Physics, 45(8A), 6071-6077. doi:10.1143/jjap.45.6071Potcoava, M. C., Futia, G. L., Aughenbaugh, J., Schlaepfer, I. R., & Gibson, E. A. (2014). Raman and coherent anti-Stokes Raman scattering microscopy studies of changes in lipid content and composition in hormone-treated breast and prostate cancer cells. Journal of Biomedical Optics, 19(11), 111605. doi:10.1117/1.jbo.19.11.111605Traub, M. C., Longsine, W., & Truskett, V. N. (2016). Advances in Nanoimprint Lithography. Annual Review of Chemical and Biomolecular Engineering, 7(1), 583-604. doi:10.1146/annurev-chembioeng-080615-034635Xu, B.-B., Zhang, Y.-L., Xia, H., Dong, W.-F., Ding, H., & Sun, H.-B. (2013). Fabrication and multifunction integration of microfluidic chips by femtosecond laser direct writing. Lab on a Chip, 13(9), 1677. doi:10.1039/c3lc50160dZucker, R. M., Ortenzio, J. N. R., & Boyes, W. K. (2015). Characterization, detection, and counting of metal nanoparticles using flow cytometry. Cytometry Part A, 89(2), 169-183. doi:10.1002/cyto.a.22793Kowalczyk, B., Lagzi, I., & Grzybowski, B. A. (2011). Nanoseparations: Strategies for size and/or shape-selective purification of nanoparticles. Current Opinion in Colloid & Interface Science, 16(2), 135-148. doi:10.1016/j.cocis.2011.01.00

On-Chip Fabry-Pérot Microcavity for Refractive Index Cytometry and Deformability Characterization of Single Cells

Une identification correcte et précise du phénotype et des fonctions cellulaires est fondamentale pour le diagnostic de plusieurs pathologies ainsi qu’à la compréhension de phénomènes biologiques tels que la croissance, les réponses immunitaires et l’évolution de maladies. Conséquemment, le développement de technologies de pointe offrant une mesure multiparamétrique à haut débit est capital. À cet égard, la cytométrie en flux est l’étalon de référence due à sa grande spécificité, sa grande sensibilité et ses débits élevés. Ces performances sont atteintes grâce à l’évaluation précise du taux d’émission de fluorophores, conjugués à des anticorps, ciblant certains traits cellulaires spécifiques. Néanmoins, sans ce précieux étiquetage, les propriétés physiques caractérisées par la cytométrie sont limitées à la taille et la granularité des cellules. Bien que la cytométrie en flux soit fondamentalement un détecteur optique, elle ne tire pas avantage de l’indice de réfraction, un paramètre reflétant la composition interne de la cellule. Dans la littérature, l’indice de réfraction cellulaire a été utilisé comme paramètre phénotypique discriminant pour la détection de nombreux cancers, d’infections, de la malaria ou encore de l’anémie. Également, les structures fluidiques de la cytométrie sont conçues afin d’empêcher une déformation cellulaire de se produire. Cependant, les preuves que la déformabilité est un indicateur de plusieurs pathologies et d’état de santé cellulaire sont manifestes. Pour ces raisons, l’étude de l’indice de réfraction et de la déformabilité cellulaire en tant que paramètres discriminants est une avenue prometteuse pour l’identification de phénotypes cellulaires. En conséquence, de nombreux biodétecteurs qui exploitent l’une ou l’autre de ces propriétés cellulaires ont émergé au cours des dernières années. D’une part, les dispositifs microfluidiques sont des candidats idéaux pour la caractérisation mécanique de cellules individuelles. En effet, la taille des structures microfluidiques permet un contrôle rigoureux de l’écoulement ainsi que de ses attributs. D’autre part, les dispositifs microphotoniques excellent dans la détection de faibles variations d’indice de réfraction, ce qui est critique pour un phénotypage cellulaire correcte. Par conséquent, l’intégration de composants microfluidiques et microphotoniques à l’intérieur d’un dispositif unique permet d’exploiter ces propriétés cellulaires d’intérêt. Néanmoins, les dispositifs capables d’atteindre une faible limite de détection de l’indice de réfraction tels que les détecteurs à champ évanescent souffrent de faibles profondeurs de pénétration. Ces dispositifs sont donc plus adéquats pour la détection de fluides ou de molécules. De manière opposée, les détecteurs interférométriques tels que les Fabry- Pérots sont sensibles aux éléments présents à l’intérieur de leurs cavités, lesquelles peuvent mesurer jusqu’à plusieurs dizaines de micromètres.----------Abstract Accurate identification of cellular phenotype and function is fundamental to the diagnostic of many pathologies as well as to the comprehension of biological phenomena such as growth, immune responses and diseases development. Consequently, development of state-of-theart technologies offering high-throughput and multiparametric single cell measurement is crucial. Therein, flow cytometry has become the gold standard due to its high specificity and sensitivity while reaching a high-throughput. Its marked performance is a result of its ability to precisely evaluate expression levels of antibody-fluorophore complexes targeting specific cellular features. However, without this precious fluorescence labelling, characterized physical properties are limited to the size and granularity. Despite flow cytometry fundamentally being an optical sensor, it does not take full advantage of the refractive index (RI), a valuable labelfree measurand which reflects the internal composition of a cell. Notably, the cellular RI has proven to be a discriminant phenotypic parameter for various cancer, infections, malaria and anemia. Moreover, flow cytometry is designed to prevent cellular deformation but there is growing evidence that deformability is an indicator of many pathologies, cell health and state. Therefore, cellular RI and deformability are promising avenues to discriminate and identify cellular phenotypes. Novel biosensors exploiting these cellular properties have emerged in the last few years. On one hand, microfluidic devices are ideal candidates to characterize single cells mechanical properties at large rates due to their small structures and controllable flow characteristics. On the other hand, microphotonic devices can detect very small RI variations, critical for an accurate cellular phenotyping. Hence, the integration of microfluidic and microphotonic components on a single device can harness these promising cellular physical properties. However, devices achieving very small RI limit of detection (LOD) such as evanescent field sensors suffer from very short penetration depths and thus are better suited for fluid or single molecule detection. In opposition, interference sensors such as Fabry-Pérots are sensitive to the medium inside their cavity, which can be several tens of micrometers in length, and thus are ideally suited for whole-cell measurement. Still, most of these volume sensors suffer from large LOD or require out-of-plane setups not appropriate for an integrated solution. Such a complex integration of high-throughput, sensitivity and large penetration depth on-chip is an ongoing challenge. Besides, simultaneous characterization of whole-cell RI and deformability has never been reported in the literature