Imaging-based spectrometer-less optofluidic biosensors based on dielectric metasurfaces for detecting extracellular vesicles
Authors: Eduardo R Arvelo
Filiz Yesilkoy
Kirill Koshelev
Yuri Kivshar
Michele De Palma
Yasaman Jahani
Chiara Cianciaruso
Hatice Altug
Journal: Nature Communications (2021)
Discipline: Multidisciplinary
Keywords: Biosensors; Imaging; Spectral shift; Biomarkers; Data processing
Affiliations: Institute of Bioengineering, √âcole Polytechnique F√©d√©rale de Lausanne (EPFL), Lausanne, Switzerland., Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA., Nonlinear Physics Center, Research School of Physics, Australian National University, Canberra, Australia., School of Physics and Engineering, ITMO University, St Petersburg, Russia., Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, √âcole Polytechnique F√©d√©rale de Lausanne (EPFL), Lausanne, Switzerland., Institute of Bioengineering, √âcole Polytechnique F√©d√©rale de Lausanne (EPFL), Lausanne, Switzerland. .

Abstract:  Biosensors are indispensable tools for public, global, and personalized healthcare as they provide tests that can be used from early disease detection and treatment monitoring to preventing pandemics. We introduce single-wavelength imaging biosensors capable of reconstructing spectral shift information induced by biomarkers dynamically using an advanced data processing technique based on an optimal linear estimator. Our method achieves superior sensitivity without wavelength scanning or spectroscopy instruments. We engineered diatomic dielectric metasurfaces supporting bound states in the continuum that allows high-quality resonances with accessible near-fields by in-plane symmetry breaking. The large-area metasurface chips are configured as microarrays and integrated with microfluidics on an imaging platform for real-time detection of breast cancer extracellular vesicles encompassing exosomes. The optofluidic system has high sensing performance with nearly 70 1/RIU figure-of-merit enabling detection of on average 0.41 nanoparticle/¬µm2 and real-time measurements of extracellular vesicles binding from down to 204 femtomolar solutions. Our biosensors provide the robustness of spectrometric approaches while substituting complex instrumentation with a single-wavelength light source and a complementary-metal-oxide-semiconductor camera, paving the way toward miniaturized devices for point-of-care diagnostics. 

Retracted: No

PubPeer comments:
 It s a nice paper written concisely and neatly, and the concept is easy to understand. However, several doubts and questions arise in my mind. Will appreciate it if the author(s) could have a look and answer them. Two big questions: 1. Both the title and the introduction highlight the device as ** imaging-based ** and ** spectrometer-less. ** While Fig. 1 illustrates the concept, Fig. 2 shows the physics of metasurface, Fig. 3 validates the performance of OLE correction; there is only one figure, more precisely, half of Fig. 4 shows us the actual data of exosome detection. More importantly, this data is quantified by spectral shifts, not image intensities promised by the author. Moreover, no further quantitative detection result is found in the SI. Could the author explain why no intensity-based quantification is presented? 2. The main idea of implementing the OLE algorithm is to compensate for the imperfections of chip fabrication. Therefore, it would be understandable to exploit this algorithm if a significant heterogeneous optical response was revealed with optimized dielectric fabrication. However, we can see clearly from Fig. 2 the rough and irregular shape of the dielectric structures. Has the author optimized the fabrication part? If so, to what extent does the spectrum vary within a single sensor area and among different sensors? I asked this after noticing other dielectric metasurface work published by the same group, such as *Science, 2018, 360, 1105-1109*, and *Adv. Funct. Mater. 2020, 30, 1910259*. The fabrication quality looks much better, and they didn t implement an algorithm to correct the images. Could the author elaborate on this issue? Minor questions: 1. About equation (1), it seems that the two brackets on the right side of the fraction are identical and thus can be eliminated. Is there a typo here, or the author forgot to simply the equation? Also, the variant *T* is not explained in the text below. 2. Could the author elaborate on how they derive both equations? 3. How much can the sensor s sensitivity be improved for exosome detection? The lowest detectable concentration in the paper is 100 million mL. However, this value is so much higher than other sensor formats, such as electrochemical devices. To fulfill the purpose of early cancer diagnosis, the sensitivity needs to be elevated several orders of magnitude. I don t think using another surface chemistry would play a big role in this issue. What does the author have in mind? 4. It s impossible now to rewrite any part, so this is just a suggestion. The **Discussion** part reads more like **Conclusions**. The authors did not give many comprehensive comparisons and analyses to formulating a discussion. ,