(Invited) On-Chip Characterization of Microcapsules Using a Capacitive Sensor for Microencapsulation and Single-Cell Analysis Applications

Introduction Droplet microfluidics has emerged as a versatile tool for a wide range of biomedical applications. Recently, various types of microfluidic droplet-generation platforms such as T-junction, flow-focusing, and co-flow, have been used for high throughput generation of microcapsules containing cells, drugs and biomolecules. microfluidic microencapsulation is a fast and well-controlled method for the generation of uniform microcapsules with the capability of tuning the size and physicochemical properties of microcapsules during the encapsulation process [1,2]. In a microfluidic droplet generation system, droplet formation can be widely classified into three regimes (squeezing, dripping, and jetting). The quality of the generated droplets in terms of stability and uniformity can be highly affected by the type of flow regimes. Since the flow regime and size of the droplets can be influenced by a small change in the system variables (such as the flow rate ratio of the dispersed and continuous phase), real-time monitoring of the droplet generation is vital especially for biomedical applications [3,4]. To address the above challenges, in this work we developed microfluidic droplet generation devices (T-junction and flow-focusing) for a well-controlled encapsulation of probiotic bacteria. In order to characterize microcapsules, a capacitive sensor was designed and integrated into the chip. Finally, the performance of the fabricated microfluidic device for on-chip monitoring of the encapsulating process was evaluated. Materials and Methods The device is made out of gold microelectrodes integrated into a polydimethylsiloxane (PDMS) chip. The microfluidic chip was fabricated in a cleanroom facility using a glass substrate with electrodes patterned by photolithography and wet etching process. A microfluidic channel was then fabricated with inlets and outlets by pouring PDMS over a mold followed by bonding the PDMS channel to the glass slide via plasma treatment machine. The dispersion phase (DP) containing alginate and Escherichia coli DH5-alpha (E. coli DH5a), as a bacterial model, was injected through a central channel. The continuous phase (CP) was the mixture solution of mineral oil and span 80 that injected through the other channel. To characterize the generated microcapsules, the change in capacitance between the electrodes was recorded using a potentiostat as probiotic bacteria were encapsulated on the chip. Results and Conclusions E.coli cells were encapsulated inside of hydrogel microcapsules using the microfluidic device. The polymeric microcapsules, once ingested, will protect the probiotics in the acidic pH of the stomach and dissolve or swell in the intestine where the pH increases above 7 to release the entrapped probiotics. The proposed microfluidic microencapsulation method can be used for the high-throughput production of microencapsulates containing probiotic cells as new drug delivery systems. The size and shape of the generated microcapsules was precisely tuned by changing the flow rate ratio of the dispersed and continuous phases followed by measuring the capacitance between the microelectrodes. The results show that the size and shape of microcapsules, as well as the flow regime, can be determined by the sensors signal (Fig 1). Individual microcapsules can be identified based on differences in dielectric properties using impedance spectroscopy techniques which are non-invasive and label-free. The microcapsule characterization system permits will be a powerful tool for evaluating the microencapsulation process as well as calculating the number of produced microcapsules. Besides, there is a potential to calculate the number of single cells in each capsule if the method is optimized. Monodisperse droplet generation in microfluidic devices has wide biomedical applications such as drug encapsulation. Due to the fine control of individual droplets using the developed device, we hope this study attracts significant interest in food and pharmaceutical studies. Reference Zhu, Pingan, and Liqiu Wang. "Passive and active droplet generation with microfluidics: a review." Lab on a Chip1 (2017): 34-75. Chong, Zhuang Zhi, et al. "Active droplet generation in microfluidics." Lab on a Chip1 (2016): 35-58. Shang, Luoran, Yao Cheng, and Yuanjin Zhao. "Emerging droplet microfluidics." Chemical reviews12 (2017): 7964-8040 Shi, Zhi, et al. "Step emulsification in microfluidic droplet generation: mechanisms and structures." Chemical Communications64 (2020): 9056-9066. Figure 1

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.