A Multi-depth Spiral Milli Fluidic Device for Whole Mount Zebrafish Antibody Staining

A Multi-depth Spiral Milli Fluidic Device for Whole Mount Zebrafish Antibody Staining | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Multi-depth Spiral Milli Fluidic Device for Whole Mount Zebrafish Antibody Staining Songtao Ye, Wei-Chun Chin, Chih-Wen Ni This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2913815/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Aug, 2023 Read the published version in Biomedical Microdevices → Version 1 posted 7 You are reading this latest preprint version Abstract Whole mount zebrafish antibody staining (ABS) is a common staining technique for protein information localization on a zebrafish embryo or larva. Like most biological assays, the whole mount zebrafish ABS is still largely conducted manually through labor intensive and time-consuming steps which affect both consistency and throughput of the assay. In this work, we develop a milli fluidic device that can automatically trap and immobilize the fixed chorion-less zebrafish embryos for the whole mount ABS. With just a single loading step, the zebrafish embryos can be immobilized in the milli fluidic device through a chaotic hydrodynamic trapping process. Moreover, a consistent body orientation pattern (i.e., head point inward) for the trapped zebrafish embryos can be achieved without any additional orientation adjustment device. Furthermore, we employed a consumer-grade SLA 3D printer assisted method for device prototyping which is ideal for labs with limited budgets. Notably, the milli fluidic device has enabled the optimization and successful implementation of whole mount zebrafish Caspase-3 ABS. We demonstrated our device can accelerate the overall procedure by reducing at least 50% of washing time in the standard well-plate-based manual procedure. Also, the consistency is improved, and manual steps are reduced using the milli fluidic device. This work fills the gap in the milli fluidic application for whole mount zebrafish immunohistochemistry. We hope the device can be accepted by the zebrafish community and be used for other types of whole mount zebrafish ABS procedures or expanded to more complicated in situ hybridization (ISH) procedure. zebrafish embryo milli fluidic whole mount antibody staining 3D printing Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1 Introduction Since the 1960s, zebrafish have served as one of the powerful and convenient small animal models in biomedical research. With its high reproduction rate, small size, body transparency, and closer phylogenetic relationship to humans, zebrafish coupled with molecular tools is ideal for high throughput in situ studies such as drug screening, embryotoxicity tests, genetic or tissue functional studies. However, most of the zebrafish related studies are still conducted manually in microplates or microtubes. Very little changes have been made in the last decades in the way of conducting zebrafish studies. The whole mount zebrafish ABS and ISH using protein and antisense RNA probes are common molecular staining techniques for detecting the protein and gene localization information on zebrafish. The conventional manual procedure for the whole mount zebrafish molecular staining usually takes hours or days to complete and involves a series of tedious and time-consuming steps (Sorrells et al., 2013 ; Thisse & Thisse, 2014 ). Moreover, the performance and consistency of the procedure is usually skill dependent. To overcome these limitations, automated liquid handling platforms have developed to perform the assays. These platforms use robotic arms or hydraulic systems for automated liquid handling and are usually compatible with well-plate or tubes (Fuqua et al., 2021 ). Although they can greatly reduce the labor and improve the consistency of the assays, the platforms are not usually affordable by labs with limited budgets. In 2021, Fuqua et al. developed a semi-automated liquid handling platform, Flyspresso , for the whole mount fruit fly ABS. The Flyspresso utilizes a programmed gas-powered hydraulic system for the liquid handling which has a portable size and is compatible with various staining procedures (Fuqua et al., 2021 ). This open-source platform provides an economic way for developing customized automated platform for whole organism assays. However, it is not a “sample-in and answer-out” platform as the specimens still need to be retrieved and manually mounted for imaging. Moreover, the shaking or repeat pipetting-based mass transfer enhancements in tube and well-plate limit the room for process optimization and time reduction (Fuqua et al., 2021 ) To address these limitations, one way is to integrate the automated platform with fluidic devices. In the last decades, several fluidic devices have been developed for ABS and ISH. Most of them are used for biomarker detection at cell and tissue levels (Brajkovic et al., 2018 ; Ciftlik et al., 2013 ; Huber et al., 2018 ; Kao et al., 2015 ; Maïno et al., 2019 ; H. T. Nguyen et al., 2017 ; Vanderhoeven et al., 2005 ). These devices have demonstrated that both sensitivity and specificity of the assay can be improved by the controlled microenvironments and the procedure can be speeded up by enhancing the convective mass transfer (Brajkovic et al., 2018 ; Ciftlik et al., 2013 ; Kao et al., 2015 ; Vanderhoeven et al., 2005 ). Despite these, the fluidic platforms for the whole organism ABS or ISH were rarely reported. In 2012, Akagi et al. developed a milli fluidic device that can automatically trap, immobilize and micro perfuse on lived zebrafish embryos. Integrating with a USB microscope, the system can be used for long term real-time in situ monitoring during fish embryo toxicity tests (FET) (Akagi et al., 2012 ). Notably, the whole mount zebrafish Trypan blue staining was performed using the milli fluidic device and staining process was found sped up by micro perfusing at high flowrate (Akagi et al., 2012 ). Although Trypan blue is not a macromolecular probe, the proof-of-concept study suggested that the mass transfer process can be enhanced with high flowrate even for the whole mount zebrafish. This study provides evidence that the whole mount zebrafish molecular staining procedure has the potential to be accelerated by using fluidic devices. From engineering and economic perspectives, integrating the fluidic device, especially micro- or nano- fluidic with the automated platforms is indeed debatable. The main controversy lies in the complexity of the use, as well as the high cost associated with the device fabrication and development. Nevertheless, these concerns may not apply to milli fluidic devices. Compared with the conventional microfluidic device, the milli fluidic device that is used for whole organism studies usually has more resolution tolerance (Frey et al., 2022 ). Also, because the subject (i.e., whole organism) is at macroscopic level, applications such as trapping (Akagi et al., 2012 ), sorting (Panuška et al., 2021 ), drug dosage generation (Kao et al., 2015 ), etc. can be realized by applying relatively simple channel geometry and the results are unlikely to be prone to defects (Frey et al., 2022 ). For these, the design and fabrication of the milli fluidic device can be achieved without the cleanroom. With the assistance of micro-milling machines (Akagi et al., 2012 ) or 3D printers (Fuad et al., 2017 ; Vanderhoeven et al., 2005 ), new channel designs can be rapidly prototyped and tested. Also, manufacturing processes such as injection molding and hot embossing can be easily adapted for mass production at low cost. Collectively, in contrast to the micro- or nano- fluidic device, the milli fluidic device will have more potential to be incorporated with the automated liquid handling platform and more likely to achieve the procedure automation level of “sample-in and answer-out”. In this study, we developed a simple multi-depth milli fluidic device that can trap and immobilize the zebrafish embryo. The device is fabricated by a consumer-grade LCD SLA 3D printer assisted rapid prototyping method. For the first time, the complete procedure for the whole mount zebrafish ABS was performed and optimized on a milli fluidic device. 2 Materials and Methods 2.1 Design and 3D printer assisted fast prototyping The 2D layout of the milli fluidic device was generated by using AutoCAD (Autodesk Inc. San Rafael, California, USA) and then converted into 3D models in AutoCAD Fusion 360. The negative master model of the milli fluidic device was exported as an STL file and sliced in an Anycubic Photon Workshop slicer (Anycubic Inc. Shenzhen, China) for 3D printing. The master mold was printed by the Anycubic Photon Mono X LCD SLA 3D printer using the Anycubic gray UV resin. Briefly, the layer thickness was set to 50 µm with 16 seconds off time and 2 seconds UV exposure time to avoid the overcuring (Mohamed et al., 2019 ). After the 3D printing, the master mold was washed in 90% isopropanol for 30 mins and dried in the air. To prevent PDMS (Sylgard 184; DowCorning Corp, Midland, MI, USA) curing inhibition, the 3D printed master model was then UV exposed for 2 hours following a 16-hour heat treatment at 80 0 C (Venzac et al., 2021 ). For the PDMS soft lithography, the PDMS elastomer and curing agent were mixed at 10:1 (w/w) ratio and degassed before and after the PDMS casting to remove the air bubbles. The PDMS was then cured for 1 hour at 80 0 C and peeled off from the resin mold. For the tubing and accessory interconnection, 3 mm holes were punched in the PDMS layer with a biopsy punch (Robbins Instruments, Sunnyvale, California, USA). The PDMS layer was bonded with a manually cut microscope glass slide using an air plasma cleaner (Harrick Plasma Inc. New York, USA). 2.2 Computational simulations COMSOL 5.5 (COMSOL 5.5 Inc. Stockholm, Sweden) was used to perform the fluid dynamic and mass transfer simulations to evaluate the on-chip trapping and mass transfer processes. The “free and porous media flow” was used to simulate the steady state fluidic fields for the initial (i.e., no trap is occupied) and final (i.e., all traps are occupied) states of the trapping. The steady state fluidic field for the final state of trapping is then coupled with “the transport of diluted species in porous media '' to simulate the buffer replacement during the flushing process in a time-dependent study. The inlet flowrate was set to be 10 ml/min for both trapping and flushing simulations. Water was used as the carrying fluid in the simulations and the diffusion coefficient for the IgG antibody was defined as 1 \(\times\) 10 −7 cm 2 /s (Kao et al., 2015 ). To determine the maximum shear stress applied on embryos after trapping, the inlet flowrate was set to 20 ml/min as it is the maximum flowrate for the current system. The dechorionated zebrafish was molded as a cone-shape rigid body with 2 mm overall length and 0.5 mm maximum head diameter. 2.3 System setup and operation procedure A peristaltic pump (Kamoer Fluid Tech Co., Ltd, Shanghai, China) using a 2.3 mm ID and 4.6 mm OD polyurethane tube was used to drive the fluid in the system. To reduce the oscillation and smoothen the flow, a homemade pulse damper assembled by a 60 ml syringe and a two way-valve (Cole-Parmer Inc.) connected the chip outlet and the peristaltic pump inlet. A three way-valve was used to connect the peristaltic pump outlet, a 10 ml loading reservoir, and a waste container to allow both the close-loop perfusion and open-loop flushing. Silicone tubes with 2 mm ID and a 3 mm OD were used for the connection. This tubing size allows multiple embryos to be loaded and travel in the system simultaneously. Before operation, the fluidic device was first flushed with 70% (v/v) ethanol to wet the channel wall and prevent the bubble formation. The PBST buffer was used as the carrying buffer for the embryo trapping. To speed up the trapping process, the chip can be titled to let the gravitational force assist the trapping. For the consistency of the experiments, the flowrates for the trapping were set to be 10 ml/min. An acrylic M3 screw was used as the flow restrictor (FR) to partially block the main channel during the whole mount zebrafish ABS procedure (ON mode). Also, the FR was lifted during the trapping and flushing (i.e., OFF mode). When switching the buffers, the old buffer was first drained out into the waste container. The new buffer was then introduced into the system and flushing the channel in the open-loop for 30 seconds before switching back to close-loop perfusion. The flowrate used during buffer switching is 10 ml/min. 2.4 Zebrafish husbandry, embryo UV treatment and fixation Adult wild type zebrafish (EKW line) were raised in the UC Merced fish facility with a 14/10-hour light and dark switching cycle. The zebrafish were fed twice daily with dry feed (300 to 400 pellet size) to ensure healthy development. The zebrafish were randomly paired a night before the mating and spawning. The embryos were collected using a sieve and then rinsed with the E3 buffer to filter out the debris and wastes. The collected embryos were cultivated in the petri dish filled with E3 buffer at 28.5 0 C and dead embryos were sorted during the development. To activate the Caspase-3, 24 hpf embryos were manually dechorionated and then transferred into a petri dish (~ 100 embryos per dish) filled with 15 ml E3 buffer. The embryos were then exposed under the UV lights (~ 0.44 W/cm 2 ) in the biosafety cabinet (NuAire Inc. Plymouth, USA) for 2 hours following 8 hours recovery in an incubator at 28.5°C. The treated embryos were fixed in 4% formaldehydes/PBST for overnight at 4 o C and then stored in 100% methanol at – 20 o C for later staining, Fig. 1 A&B. 2.5 Whole mount zebrafish Caspase-3 antibody staining The procedures for the plate-based and device-based whole mount zebrafish Caspase-3 ABS are listed in Table 1 . The sample preprocessing for both plate-based and device-based procedures are performed in the 24-well plate. A belly-dancer (IBI Scientific Inc., Iowa, USA) was used to provide medium level shaking for the on-plate steps. For the plate-based whole mount zebrafish Caspase-3 ABS, 10 to 15 embryos were loaded per well in the 24-well plate. For the device-based whole mount zebrafish Caspase-3 ABS, the number of embryos tested on the device was dependent on the trapping result. The flowrate and time for each on-chip staining step was kept constant at 10 ml/min and 2 hours, respectively. The dilution ratios for the primary antibody and secondary antibody were kept at 1:1000 (Cell signaling technology #9661, -Caspase-3, Rabbit) and 1:200 (Invitrogen #31686, -Rabbit Rhodamine, 0.5 mg/ml in stock), respectively. 2.6 Imaging and signal quantification The fluorescence images were acquired under the confocal microscope (Leica Biosystem Inc.) with 100 \(\times\) magnification, 15% laser power, and 800 volts digital gain. The laser beam scanned the zebrafish embryo along the Z direction every 5 µm to get the sliced images. The sliced images were then stacked to form a Z projected image using the maximum intensity. ImageJ was used to analyze the signal levels on the Z-projected images by applying masks with threshold level of 100 on the 8-bit gray scaled images. 2.7 Data analysis and reproducibility The statistical analysis was conducted by GraphPad Prism (GraphPad Software) and MS Excel (Microsoft, USA). The Student T-tests were used to measure the significant level (P < 0.5) between the groups. To ensure unbiased experimental results, the controlled experiments were conducted for at least 3 replicates (i.e., N \(\ge\) 3) with at least 10 embryos per replicate (i.e., n \(\ge\) 10). The results were measured and quantified under the same standard. Embryos collected from the same batch were only to be used for the same type of experiments. To avoid the risk of contamination, the PDMS-glass devices were only for one time use and all the buffers were used within the recommended storage periods. 3 Experimental Results 3.1 Device design and fabrication A multi-depth spiral device was designed to trap, immobilize, and perform the whole mount ABS on the 24 to 48 hpf chorion-less zebrafish embryos. The device contains 3 major functional parts: a spiral main channel, an inner suction chamber, and 26 trapping channels that interconnect the main channel and inner reservoir, Fig. 2 A. Hydrodynamic suction was used as the main trapping and immobilization force in this design. When operating, the inner chamber, which connects the peristaltic pump at the outlet, provides a negative pressure to draw the fluids from the main channel via the traps. The height for the main and the trap channel is 1.2 mm and 0.8 mm, respectively. The funnel-like outlet has a peak height of 2 mm, a 2 mm ID and an 8 mm OD. The purposes for the different heights in the trap, main channel, and outlet are: 1) to shorten the mass transfer distance in the traps; 2) to prevent bubbles from entering the traps; 3) to drain out the bubbles accumulating in the inner reservoir. Also, the main channel has a width of 3.5 mm which allows multiple chorion-less embryos to travel simultaneously and let individual embryo to freely self-orientate. The trap entrance has a width of 2 mm, a length of 2.14 mm, and the width of the trap nozzle is 0.25 mm. The nozzle length is used to regulate the strength of the hydrodynamic suction force during trapping. The length of each individual trap is decreasing from 1 mm to 0.5 mm at a rate of 0.02 mm/trap along the main channel. This configuration is to ensure a close hydrodynamic trapping effect or embryo drawing ability at each trap for the purpose of maximizing the trap usage, smooth the trapping process, and minimize the procedure lagging, Fig. 2 S. A 3 mm diameter flow restrictor (i.e., an acrylic M3 screw) is used to partially block the end of the main channel during the whole mount zebrafish ABS. The total internal volume of the device is about 1 ml which is close to the volume commonly used at a single well in a 24-well plate. Besides, the internal volume of individual trap is about 1.37 \(\mu l\) which ensures “one embryo per trap” and a high surface-to-volume environment for the embryo. To reduce the flow pulsing caused by the peristaltic pump, a homemade pulse dampener, customized by a 60 ml lure head syringe, is connected in between the device outlet and the peristaltic pump, Fig. 4 S. The minimum system volume is about 6 ml when perfusing in the close loop. Unlike the previously reported zebrafish trapping systems (Akagi et al., 2012 ; Fuad et al., 2017 ; Zhu et al., 2019 ), that only allow one embryo to be loaded each time, in this work, embryos can be loaded all at once for close-loop trapping, Fig. 2 E. The PDMS-glass device in this work was fabricated by using the LCD SLA 3D printer assisted fast prototyping method, Fig. 2 B. The negative mold of the device was printed by the Anycubic Photon Mono X LCD SLA 3D printer, Fig. 2 C. After printing, the mold was washed with 70% IPA and dried in the air. To prevent the PDMS curing inhibition, the 3D printed mold was post-treated with UV light for 2 hours following 16 hours heat treatment at 80 0 C (Venzac et al., 2021 ). The PDMS was then casted onto the 3D printed mold and cured at 80 0 C for 1 hour. After curing, the PDMS layer was peeled off from the mold and plasma bonded with a microscopic glass slide, Fig. 2 D. The LCD SLA 3D printer used in this work uses a 3840 2400 (4K) LCD screen and an array of UV lamp beads to control the pattern printing at each layer. To avoid overcuring and resin flow disturbing, the UV exposure time at each layer was set to 2 seconds with a 0.25 mm/s lifting speed and a 3 mm/s retract speed. The 3D printer employs an LCD screen with 50 µm by 50 µm pixel size that cannot always fit the edge of design perfectly. Therefore, jagged channel walls are expected to be casted using the mold printed by LCD SLA 3D printer. To reduce the edge jaggedness of the mold, the anti-aliasing algorithm was also applied in the settings. To evaluate the fabrication quality, the nozzle width is inspected as it is the smallest feature in the device. The result has indicated that the average nozzle width is about 0.2850 ± 0.031 mm (N = 5) when the target width is 0.25 mm, Fig. 1 S. As expected, the channel wall was also found to be rough, even applied with the highest level of anti-aliasing. The variation of the channel width and the rough channel wall were considered acceptable as only a limited hydrodynamic difference could be caused by the small variations and the elastic property of the PDMS would extenuate the mechanical damage on the zebrafish embryo. 3.2 Embryo trapping and immobilization During trapping, the hydrodynamic suction force deviates the embryos towards the inner wall and then drags the embryos into the traps, Fig. 3 A. The hydrodynamic trapping process can be easily explained by a simplified circular analogy diagram, Fig. 3 B. Briefly, the embryo trapping occurs, when the overall flow that passes through the traps is greater than the flow that travels through the main channel (Q traps > Q main ). In this chip design, the traps are arranged in a parallel configuration (M.-A. Nguyen et al., 2016 ) and the inner reservoir can be treated as the ground that provides a relatively constant downstream pressure, Fig. 2 S. Based on the CFD simulation, the flow that passes through the traps drops from 76%, when all traps are empty, to about 59%, when all the traps are occupied. Thus, the trapping is expected to get harder when more traps are being occupied during the process. Despite this, the possibility for the trapping remains at the last moment as the flow passing through the traps is still higher than the flow going through the main channel. To maximize the usage of the traps, gravitational force was also used to assist the trapping at the late trapping phase (i.e., most traps are occupied) in which the device was titled towards the remaining empty traps (Movie S1). When using 10 ml/min for close-loop trapping, the trap occupation rate can easily reach over 84% without gravitational force (Movie S2, data not shown) and can achieve 93.6 ± 4.0% (N = 24, n = 624) with the assistance of the gravitational force, Fig. 3 E. The trapping results also indicate that the first trap was usually skipped by the embryos even with the help of the gravitational force. This is due to the high main channel velocity near the inlet which gives the embryo a less deviation time towards the inner wall. Therefore, the first trap in this design mostly plays the role of the divergent channel to help the embryos deviate towards the inner wall. The aim for the chip is to automatically immobilize the zebrafish embryo and then perform the antibody staining. Because a confocal microscope is used in the signal measurement, the orientation control of the zebrafish embryo was not in the design considerations initially. Interestingly, the validation experiments show that about 93.7 ± 4.3% (N = 24) trapped embryos had their heads pointing inward after the chaotic trapping. One of the explanations for this orientation consistency is that the head of the zebrafish embryo experiences a much stronger drag force compared with the narrowed body and tail in the channel, Fig. 3 S. Thus, it is more likely for the head of the embryos to point towards the inner wall and then be dragged into the traps. To stably transfer the device to various imaging platforms without disturbing the embryos’ positions, the buffer is drained out of the devices after the trapping. Due to the presence of Laplace pressure, the holdup volume of the remaining buffer will form droplets inside the traps, Fig. 3 D. These droplets can wrap around individual zebrafish embryos forming isolated chambers. The encapsulated zebrafish embryos are unlikely to be disturbed by actions such as device unplugging and relocation. Thereafter, the portable device can be transferred to microscope stations for imaging. To our best knowledge, this feature has not been reported by other similar devices. Potential usages for this feature in zebrafish embryonic studies such as metabolism analysis, hypoxia studies, and toxicity tests may be worth investigating in the future. 3.3 On-Chip flow settings The multi-depth spiral device uses a simple parallel trapping configuration. However, the limitation for this configuration is also obvious as the flowrate in the individual traps drops along the spiral main channel (M.-A. Nguyen et al., 2016 ). This is not ideal for the on-chip ABS because the convective mass transfer rate is now different at each trap and the last trap always takes the longest time to complete the mass transfer. To minimize this procedure lagging, a flow restrictor (FR) is added to partially block the main channel during the on-chip ABS. Based on the CFD simulation, the add-on of the FR can boost the flowrate in the traps as well as close the flowrate differences among the traps, Fig. 4 A. The validation experiments using the methylene blue/PBST also confirmed that the FR ON mode enhances the perfusion in the traps as it took less time for the dye to fill the traps, Fig. 4 B &C. Here, the flowrate for both the CFD simulations and validation experiments was set to 10 ml/min. During the buffer switching (Movie 3S), the old buffer will first be flushing out in the system. To ensure the overall system is replaced by the new buffer and all the holdup volume inside traps is cleaned up, the system is then flushed with the new buffer in the open loop before switching to the close loop circulation. In the simulation, the old buffer (i.e., the PBDT with antibody) was set to be replaced by the new buffer (i.e., PBDT) at 10 ml/min. The simulation showed that it takes about 7 seconds for new buffer to reach and flush out the old buffer in the last trap, Fig. 5 , middle panel. However, the device is not completely cleaned as the old buffer is still accumulated at the center chamber, Fig. 5 , top and bottom panels. To completely flush out the old buffer from the system, the flushing process needs to carry on for another 23 seconds to an overall 30 second flushing time. Both simulation and validation experiments using methylene blue/PBST have shown that the system can be completely replaced by the new buffer after flushing for 30 seconds at 10 ml/min (Movie 4S). Note, during the buffer switching, the FR is turned OFF (i.e., M3 is lifted) to prevent the potential bubble blocking. One of the concerns for on-chip flowthrough operations is the body shear stress exerted by the superficial flow may damage the fixed embryos. The CFD simulation showed that when perfusion flow is at 20 ml/min and the FR is turned ON, the maximum shear stress applied on the embryo is about 0.672 Pa and the shear stress hot spot is located at the upper surface of the embryo, Fig. 6 . We believe this shear stress level is unlikely to damage the fixed zebrafish embryos as tissue becomes more rigid and less fragile after formaldehyde fixation. Indeed, most observed embryo damages were during the off-chip pipetting and embryo transferring. 3.4 Multi-depth Channel for Bubble Prevention The air bubble introduction is the major cause of biases for the device-based zebrafish assays. Bubbles can obstruct the trap during the perfusion, interfere with the embryo imaging, and induce backflow, all of which can adversely affect the accuracy and reliability of the assay results. As most PDMS-glass milli fluidic devices are integrated with open pumping systems, the air may enter the device through both inlet and the gas permeable PDMS layer leading to the formation of liquid-gas flow in the device. Likewise, in our current system setup, the flow is driven by a peristaltic pump. To reduce the pulsing caused by the peristaltic pump, the buffer loading tube must open to the air. Therefore, air can potentially be introduced into the device during the operation. By far, the only attempt to prevent the air bubbles in the milli fluidic device is made by Zhu et al. The group reported a bubble free milli fluidic device by bonding a PDMS vacuum layer on top of the PDMS zebrafish embryo culture channel layer (Zhu et al., 2019 ). In their study, the negative pressure in the vacuum chamber can effectively remove the bubbles from the embryo culture channel. However, the multilayer PDMS device will complicate the fabrication steps and the additional PDMS layer may affect the signal detection during the imaging. Moreover, the application of external negative pressure may affect the zebrafish embryo culture environment such as oxygen level. Here, we demonstrated a simple channel geometry-based bubble prevention method for the single layer milli fluidic device. In our current system setting, buffer switching, and high flowrate perfusion are the two situations where most bubble introduction events occur. Nevertheless, the types of bubbles that are introduced in these two situations are different, as are the underlying bubble formation mechanisms. During the buffer switching step, the channel was first emptied and the new buffer together with air was then perfused into the channel. The bubbles introduced during the buffer switching step are usually large or medium sized bubbles, Fig. 7 A. These bubbles which usually have larger size than the trap is unlikely to enter the trap during the perfusion. However, the movement of the large bubbles may cause pressure fluctuations, induce backflow, and as a result disturb the trapped embryos. Our milli fluidic device offers a spacious main channel for the large bubbles which can minimize the pressure fluctuations caused by their movements and thus unlikely to disturb the trapped embryo. Also, because of their large radius, the large air bubbles experience less capillary retaining force in the main channel and therefore can be easily flushed out of the device (Movie 5S). Note the narrow section at the end of the main channel may prevent the large bubbles from being removed. Increase the flushing flowrate or slightly title the device can help to remove the large bubbles stuck at the end of the main channel. When operating at the high perfusion flowrate (i.e., 20 ml/min), micro bubbles were found in the channels, Fig. 7 B. This is because air was introduced with the buffer at high pumping speed generating dispersed-bubble flow in the channel. Besides, the use of detergents such as Triton X-100 and Tween 20 also aggravates the formation of the micro bubbles. In our device, because the main channel height is greater than the trapping channels, micro bubbles travel near the top surface of the main channel and are unlikely to enter the traps (Movie 6S). 3.5 Optimization of the on-chip whole mount zebrafish Caspase-3 antibody staining The whole mount zebrafish Caspase-3 ABS is a well-established assay to detect the level of cell apoptosis in the zebrafish (Sorrells et al., 2013 ). To induce the Caspase-3 cleavage, we applied UV light, a common environmental stress triggering apoptosis pathway, on the zebrafish embryo (Zeng et al., 2009 ). To investigate if the whole mount zebrafish ABS can be improved in the flowthrough environment, we next tested the whole mount zebrafish Caspase-3 ABS on the fluidic device and compared the performance with conventional plate-based manual procedure. The procedures for the plate-based and device-based whole mount zebrafish Caspase-3 ABS are shown in Table 1 . Note the washing time and flowrate shown in device-based procedure is the final optimized results. The standard on-plate washing time is 120 mins. Table 1 Whole mount zebrafish Caspase-3 ABS procedures. The general whole mount zebrafish ABS procedure involves both staining and washing steps (Sorrells et al., 2013 ). To ensure the antibody can sufficiently bind to the antigen, the staining time is usually kept at an extended level (e.g., overnight). Despite no systematic study has been conducted to investigate how the fluidic flow can affect the antibody-antigen interaction in the whole mount zebrafish, the studies performed in tubes or well-plates suggested that the antibody staining took longer in older embryos as the tissue became denser (Sorrells et al., 2013 ). The intact tissue of the zebrafish embryo certainly affects the antibody penetration. Therefore, optimizing the whole organism staining procedure by reducing the staining time may result in loss of sensitivity. The washing step, on the other hand, is for the removal of the nonspecific binding after the staining step and is crucial for the specificity of the procedure. Targeting the washing steps will be a safer option for the optimization of the whole organism staining as the true signal is ensured with sufficient staining time. Also, the manual buffer refreshing steps can be avoided during on-chip washing as the wash buffer is circulated in a close-loop. For these, the washing steps were targeted for the on-chip whole mount zebrafish Caspase-3 ABS optimization. Briefly, in the milli fluidic device, two flowrates viz., 10 ml/min and 20 ml/min were used to perform 30 mins, 60 mins, 90 mins, and 120 mins washings after each staining step, Fig. 6 A, top panel. To ensure the consistency and sufficient Casapse-3 binding, the flowrate and time for the two staining steps were kept constant at 10 ml/min and 120 mins, respectively. For comparison, the same washing times were tested in the plate-based procedure using a 24-well plate. After the procedure, the Caspase-3 signals were measured from the zebrafish embryos encapsulated by the PDST droplets in the milli fluidic device and 0.5% agarose in well-plate. Based on the experiment results, the washing process was found to be accelerated using the device as significant intensity differences were found at 30 mins, 60 mins, and 90 mins between the on-plate and the on-chip washings, Fig. 8 A, bottom panel. Also, the samples were found already sufficiently washed at 60 mins when the on-chip washing flowrate is 20 ml/min. In addition, a significant intensity difference was found between the two tested on-chip washing flowrates at the 60 mins which implied a higher on-chip washing flowrate can speed up the washing process. The two tested on-chip washing flowrates showed insufficient washing at 30 mins as the intensities for both flowrates were significantly higher than the control and no significant intensity difference can be distinct between them. Regarding the image taking environments, the intensity measured from the PBDT droplets inside the chip has a slightly decreased signal when compared to the intensity measured in the 0.5% agarose gel. This is likely due to the power attenuation of the fluorescent laser by the thick PDMS layer on top of the device. Despite this, the signal difference between the on-chip and in agarose measurements is not significant, Fig. 8 B. We next normalized the intensity of all the experimental results measured by respective means and the consistency of the device-based procedure is found higher than that of the plate-based procedure, Fig. 8 C. Also, the consistency of the assay seemed to be improved when applying higher on-chip washing flowrate. All in all, the milli fluidic-based whole mount zebrafish ABS outperforms the conventional plate-based manual approach by reducing both manual steps and time while increasing the consistency of the results. This highlights the benefits of miniaturization and mechanization of zebrafish assays. 4 Discussion and Conclusions Zebrafish-on-a-chip may have experienced significant growth lately, but it is still in the early development phase (Li et al., 2014 ; Yang et al., 2016 ). The needs for optimizing and automating the time consuming and labor-intensive procedures such as whole mount zebrafish ABS and ISH is still largely unfulfilled. To fill the gap, we developed a multi-depth spiral device that can trap, immobilize, and perform the whole mount Caspase-3 ABS on the chorion-less zebrafish embryo. The device was fabricated by using a 3D printer assisted rapid prototyping method. Remarkably, the commercial leveled 3D printer and photo resin were used in making the master mold in this study. Compared with the fabrication methods reported previously (Fuad et al., 2017 ; Yang et al., 2016 ), our method is more economical in prototyping zebrafish-on-a-chip devices and can be easily adapted by small budget labs. The multi-depth spiral device developed in the study uses the classic hydrodynamic trapping mechanism yet a chaotic trapping process to trap chorion-less zebrafish embryos in the close-loop pumping system. The device showed a trap usage rate that is comparable to the previously reported zebrafish embryo trapping platforms (Akagi et al., 2012 ; Fuad et al., 2017 ), but with a more convenient operating procedure as multiple embryos can be loaded into the chip at the same time. Also, the orientation preference (i.e., head point inward) found when trapping the cone-shaped fixed zebrafish embryo can be used for the future optimization of devices that need orientation control. This phenomenon may also provide some insights for the trapping and sorting of non-spherical particles in other fluidic devices. In addition, the trapped embryos were found to be encapsulated in the droplets after draining out the buffer. The encapsulation of embryos in droplets makes the device become portable and allows the device to access various imaging platforms after trapping. This feature, which has not been reported by similar devices, may have potential to be used for the applications such as embryonic toxicity tests, drug screening, metabolite analysis, hypoxia study etc. In this study, for the first time, the complete procedure of the whole mount zebrafish ABS was performed and optimized on a zebrafish-on-chip system. We proved that the washing process in the whole mount zebrafish Caspsae-3 ABS procedure can be accelerated by a higher perfusion flowrate. We believe this finding can also be applied to other types of whole mount zebrafish ABS procedures or even more complicated ISH procedures. The current device and system setting still have limitations that need to be optimized in the future. First, the on-chip close loop system requires more reagent volume (i.e., ~ 2 times for washing and ~ 6 times for staining) compared to the on-plate procedure due to off-chip volumes contributed by the tubing and pump. The large reagents requirement could be reduced by shortening or reducing the size of the tubing. Also, the effect of large reagent consumption may be minimized by conducting large scale tests (i.e., connect multiple devices in series) or by reusing the reagents (Fuqua et al., 2021 ). Second, although the multi-depth device can prevent large- or micro- sized bubbles from entering the trap, the medium sized bubbles may still occasionally enter the traps during the perfusion. This is the major cause of bias in the study as the trapped bubbles will not only affect the flow through the traps but also block the embryo during the imaging. Therefore, a special bubble trapping or breaking device (Fu et al., 2011 ) could be added at the device inlet to trap the medium size bubbles or break the medium size bubble into micro bubbles. Finally, the current procedure still requires the operator to manually load the embryos and switch the buffers during each step. The manual buffer switching process can be eliminated by integrating the device with automated imaging and liquid handling platforms (Fuqua et al., 2021 ) in the future to reach the degree of “sample-in and answer-out”. Declarations Conflicts of interest There are no conflicts to declare. References Akagi, J., Khoshmanesh, K., Evans, B., Hall, C. J., Crosier, K. E., Cooper, J. M., Crosier, P. S., & Wlodkowic, D. (2012). Miniaturized Embryo Array for Automated Trapping, Immobilization and Microperfusion of Zebrafish Embryos. PLoS ONE , 7 (5), e36630. https://doi.org/10.1371/journal.pone.0036630 Brajkovic, S., Pelz, B., Procopio, M.-G., Leblond, A.-L., Repond, G., Schaub-Clerigué, A., Dupouy, D. G., & Soltermann, A. (2018). Microfluidics-based immunofluorescence for fast staining of ALK in lung adenocarcinoma. Diagnostic Pathology , 13 (1), 79. https://doi.org/10.1186/s13000-018-0757-1 Ciftlik, A. T., Lehr, H.-A., & Gijs, M. A. M. (2013). Microfluidic processor allows rapid HER2 immunohistochemistry of breast carcinomas and significantly reduces ambiguous (2+) read-outs. Proceedings of the National Academy of Sciences , 110 (14), 5363–5368. https://doi.org/10.1073/pnas.1211273110 Frey, N., Sönmez, U. M., Minden, J., & LeDuc, P. (2022). Microfluidics for understanding model organisms. Nature Communications , 13 (1), 3195. https://doi.org/10.1038/s41467-022-30814-6 Fu, T., Ma, Y., Funfschilling, D., & Li, H. Z. (2011). Dynamics of bubble breakup in a microfluidic T-junction divergence. Chemical Engineering Science , 66 (18), 4184–4195. https://doi.org/10.1016/j.ces.2011.06.003 Fuad, N. M., Kaslin, J., & Wlodkowic, D. (2017). Development of chorion-less zebrafish embryos in millifluidic living embryo arrays. Biomicrofluidics , 11 (5), 051101. https://doi.org/10.1063/1.5001848 Fuqua, T., Jordan, J., Halavatyi, A., Tischer, C., Richter, K., & Crocker, J. (2021). An open-source semi-automated robotics pipeline for embryo immunohistochemistry. Scientific Reports , 11 (1), 10314. https://doi.org/10.1038/s41598-021-89676-5 Huber, D., Voith von Voithenberg, L., & Kaigala, G. V. (2018). Fluorescence in situ hybridization (FISH): History, limitations and what to expect from micro-scale FISH? Micro and Nano Engineering , 1 , 15–24. https://doi.org/10.1016/j.mne.2018.10.006 Kao, K.-J., Tai, C.-H., Chang, W.-H., Yeh, T.-S., Chen, T.-C., & Lee, G.-B. (2015). A fluorescence in situ hybridization (FISH) microfluidic platform for detection of HER2 amplification in cancer cells. Biosensors and Bioelectronics , 69 , 272–279. https://doi.org/10.1016/j.bios.2015.03.003 Li, Y., Yang, F., Chen, Z., Shi, L., Zhang, B., Pan, J., Li, X., Sun, D., & Yang, H. (2014). Zebrafish on a Chip: A Novel Platform for Real-Time Monitoring of Drug-Induced Developmental Toxicity. PLoS ONE , 9 (4), e94792. https://doi.org/10.1371/journal.pone.0094792 Maïno, N., Hauling, T., Cappi, G., Madaboosi, N., Dupouy, D. G., & Nilsson, M. (2019). A microfluidic platform towards automated multiplexed in situ sequencing. Scientific Reports , 9 (1), 3542. https://doi.org/10.1038/s41598-019-40026-6 Mohamed, M., Kumar, H., Wang, Z., Martin, N., Mills, B., & Kim, K. (2019). Rapid and Inexpensive Fabrication of Multi-Depth Microfluidic Device using High-Resolution LCD Stereolithographic 3D Printing. Journal of Manufacturing and Materials Processing , 3 (1), 26. https://doi.org/10.3390/jmmp3010026 Nguyen, H. T., Trouillon, R., Matsuoka, S., Fiche, M., de Leval, L., Bisig, B., & Gijs, M. A. (2017). Microfluidics-assisted fluorescence in situ hybridization for advantageous human epidermal growth factor receptor 2 assessment in breast cancer. Laboratory Investigation , 97 (1), 93–103. https://doi.org/10.1038/labinvest.2016.121 Nguyen, M.-A., Srijanto, B., Collier, C. P., Retterer, S. T., & Sarles, S. A. (2016). Hydrodynamic trapping for rapid assembly and in situ electrical characterization of droplet interface bilayer arrays. Lab on a Chip , 16 (18), 3576–3588. https://doi.org/10.1039/C6LC00810K Panuška, P., Nejedlá, Z., Smejkal, J., Aubrecht, P., Liegertová, M., Štofik, M., Havlica, J., & Malý, J. (2021). A millifluidic chip for cultivation of fish embryos and toxicity testing fabricated by 3D printing technology. RSC Advances , 11 (33), 20507–20518. https://doi.org/10.1039/D1RA00846C Sorrells, S., Toruno, C., Stewart, R. A., & Jette, C. (2013). Analysis of Apoptosis in Zebrafish Embryos by Whole-mount Immunofluorescence to Detect Activated Caspase 3. Journal of Visualized Experiments , 82 . https://doi.org/10.3791/51060 Thisse, B., & Thisse, C. (2014). In Situ Hybridization on Whole-Mount Zebrafish Embryos and Young Larvae (pp. 53–67). https://doi.org/10.1007/978-1-4939-1459-3_5 Vanderhoeven, J., Pappaert, K., Dutta, B., Van Hummelen, P., & Desmet, G. (2005). DNA Microarray Enhancement Using a Continuously and Discontinuously Rotating Microchamber. Analytical Chemistry , 77 (14), 4474–4480. https://doi.org/10.1021/ac0502091 Venzac, B., Deng, S., Mahmoud, Z., Lenferink, A., Costa, A., Bray, F., Otto, C., Rolando, C., & Le Gac, S. (2021). PDMS Curing Inhibition on 3D-Printed Molds: Why? Also, How to Avoid It? Analytical Chemistry , 93 (19), 7180–7187. https://doi.org/10.1021/acs.analchem.0c04944 Yang, F., Gao, C., Wang, P., Zhang, G.-J., & Chen, Z. (2016). Fish-on-a-chip: microfluidics for zebrafish research. Lab on a Chip , 16 (7), 1106–1125. https://doi.org/10.1039/C6LC00044D Zeng, Z., Richardson, J., Verduzco, D., Mitchell, D. L., & Patton, E. E. (2009). Zebrafish Have a Competent p53-Dependent Nucleotide Excision Repair Pathway to Resolve Ultraviolet B–Induced DNA Damage in the Skin. Zebrafish , 6 (4), 405–415. https://doi.org/10.1089/zeb.2009.0611 Zhu, Z., Geng, Y., Yuan, Z., Ren, S., Liu, M., Meng, Z., & Pan, D. (2019). A Bubble-Free Microfluidic Device for Easy-to-Operate Immobilization, Culturing and Monitoring of Zebrafish Embryos. Micromachines , 10 (3), 168. https://doi.org/10.3390/mi10030168 Additional Declarations No competing interests reported. Supplementary Files Movie1SEmbryotrappingassistedbyGforce.mp4 Movie2SEmbryoTrappingwithoutGforce.mp4 Movie3SBufferswitchingandFROFFtoON.mp4 Movie4SFlushing.mp4 Movie5SLargebubbleprevention.mp4 Movie6SMicrobubbuleprevention.mp4 GraphicalAbstract.png Supplymentaryfile.docx Cite Share Download PDF Status: Published Journal Publication published 15 Aug, 2023 Read the published version in Biomedical Microdevices → Version 1 posted Editorial decision: Major revision 06 Jul, 2023 Reviews received at journal 31 May, 2023 Reviewers agreed at journal 13 May, 2023 Reviewers invited by journal 13 May, 2023 Editor assigned by journal 13 May, 2023 Submission checks completed at journal 12 May, 2023 First submitted to journal 09 May, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2913815","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":199815980,"identity":"b785381c-7e29-4fc2-b44c-10050164b66a","order_by":0,"name":"Songtao Ye","email":"","orcid":"","institution":"University of California, Merced","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Songtao","middleName":"","lastName":"Ye","suffix":""},{"id":199815981,"identity":"b48b394f-249b-4651-8f5e-49cb4f9d3f01","order_by":1,"name":"Wei-Chun Chin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYFACHoYDDBU2MB4zECcQo+VMGolaGBjbDpOgxeD42YOHC9jOJ/ZPO3zsw48KawZ+9hwD/FrO5CUcnsFzO3HG7bTkmT1n0hkke97g12J2g8fgMI/E7cQN0jnGzCAXGtwgYAtEi8E5oJb8z8yM/w4z2BOnJeEAyBZmZsYGoC0SBLTYn8kBajmQbAz0izFjz7F0HokzzwrwapFsP2P8mfefnWz/7OTHDD9qrOX425M34NWCAXhIUz4KRsEoGAWjACsAAEkCR0+aPcBdAAAAAElFTkSuQmCC","orcid":"","institution":"University of California, Merced","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Wei-Chun","middleName":"","lastName":"Chin","suffix":""},{"id":199815982,"identity":"13cca0d6-a52b-460c-8ef5-c4b354528e98","order_by":2,"name":"Chih-Wen Ni","email":"","orcid":"","institution":"University of California, Merced","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chih-Wen","middleName":"","lastName":"Ni","suffix":""}],"badges":[],"createdAt":"2023-05-10 00:59:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2913815/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2913815/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10544-023-00670-2","type":"published","date":"2023-08-15T21:59:50+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":37103873,"identity":"cbfb793d-cf92-42d0-8312-2e1b1c2eecc6","added_by":"auto","created_at":"2023-05-16 17:48:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":830846,"visible":true,"origin":"","legend":"\u003cp\u003eZebrafish embryo Caspase-3 cleavage activation and sample preparation.\u003cstrong\u003e A)\u003c/strong\u003e The schedule for the zebrafish embryo Caspase-3 cleavage activation treatments and sample preparation. \u003cstrong\u003eB)\u003c/strong\u003e The image showing the dechorionated zebrafish embryos were under UV treatment.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/128a6781c1e0eb5557176ba9.png"},{"id":37104662,"identity":"f0247540-080f-4f67-a349-f78b684e23bc","added_by":"auto","created_at":"2023-05-16 17:56:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":893160,"visible":true,"origin":"","legend":"\u003cp\u003eMulti-depth spiral milli fluidic device for zebrafish immobilization and antibody staining. \u003cstrong\u003eA)\u003c/strong\u003eThe engineering drawing showing the dimension of the multi-depth spiral device. \u003cstrong\u003eB)\u003c/strong\u003e The 3D printing assisted prototyping process. \u003cstrong\u003eC)\u003c/strong\u003e Photography showing the 3D printed negative master mold for the multi-depth spiral device. \u003cstrong\u003eD)\u003c/strong\u003e Photography showing the assembled PDMS-glass device after soft lithography. \u003cstrong\u003eE) \u003c/strong\u003eSchematic showing the system setups. The arrows indicate the flow directions.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/b09bd50df6600cf33b4ac90e.png"},{"id":37103874,"identity":"f8f22145-d35c-40c2-bbe9-cecbc8d9501a","added_by":"auto","created_at":"2023-05-16 17:48:53","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":692785,"visible":true,"origin":"","legend":"\u003cp\u003eThe zebrafish embryo trapping principles and validations.\u003cstrong\u003e A)\u003c/strong\u003e The schematic showing the torpedo-shaped embryos are dragged into the traps due to the hydrodynamic suction force. \u003cstrong\u003eB) \u003c/strong\u003eThe simplified circular analogy for the multi-depth spiral device showing the parallel trapping and source and sink configurations for the design. \u003cstrong\u003eC)\u003c/strong\u003e The CFD simulations for initial and final fluidic conditions for the trapping process. The possibility for the trapping retained during the trapping process as the overall flowrate pass through the traps is always higher than the flowrate passes through the main channel. Inlet flowrate is set to 10 ml/min. \u003cstrong\u003eD)\u003c/strong\u003e Microscopy images showing the zebrafish embryos are immobilized inside the traps and encapsulated in the PBST droplets due to the presence of the Laplace pressure. \u003cstrong\u003eE)\u003c/strong\u003e The trap occupation rate for each individual traps (N= 24, n=624).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/03359899bf375dba7f85dc20.png"},{"id":37105131,"identity":"276dcdaf-8f64-40cb-a1e5-96c623bfbe2e","added_by":"auto","created_at":"2023-05-16 18:04:53","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1487905,"visible":true,"origin":"","legend":"\u003cp\u003eOn-chip flow settings for the multi-depth spiral device.\u003cstrong\u003e A)\u003c/strong\u003e Top: The flow restrictor (FR) ON and OFF modes for the device. Bottom: The flowrates at each individual traps at FR ON (blue) and FR OFF (orange) modes. \u003cstrong\u003eB) \u003c/strong\u003eThe perfusion simulation (top) and validation (bottom) for FR OFF mode at 10 ml/min inlet flowrate. \u003cstrong\u003eC)\u003c/strong\u003e The perfusion simulation (top) and validation (bottom) for the FR ON mode at 10 ml/min inlet flowrate.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/9f2124f46b847f9e78b16b19.png"},{"id":37103877,"identity":"b1714d66-dc60-4571-a61c-3d785c920e87","added_by":"auto","created_at":"2023-05-16 17:48:53","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":957873,"visible":true,"origin":"","legend":"\u003cp\u003eThe flushing time estimation. \u003cstrong\u003eTop panel\u003c/strong\u003e: the overall mass transfer simulation for the flushing process. \u003cstrong\u003eMiddle panel\u003c/strong\u003e: mass transfer simulation for the last trap (i.e., 26\u003csup\u003eth\u003c/sup\u003e trap) during open loop flushing. \u003cstrong\u003eBottom panel\u003c/strong\u003e: the flushing validation experiment using methylene blue/PBST. The flushing flowrate for both simulation and experiment are 10 ml/min.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/a1b6cf887308d6aa909a688c.png"},{"id":37103875,"identity":"4d635745-8125-4ecd-a5b4-f21a49cf4632","added_by":"auto","created_at":"2023-05-16 17:48:53","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":294067,"visible":true,"origin":"","legend":"\u003cp\u003eThe simulated body shear stress on the fixed zebrafish embryos during on-chip perfusion. The embryo in the first trap is selected to show the maximum shear stress level and the shear stress distribution. The flowrate is set at 20 ml/min and the FR is turned on.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/a267fd37f6cc95fb3c5e17cd.png"},{"id":37103880,"identity":"9977c59c-2b70-45cb-9d18-e3f6a79d771e","added_by":"auto","created_at":"2023-05-16 17:48:53","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1524859,"visible":true,"origin":"","legend":"\u003cp\u003eBubble prevention in the milli fluidic device. \u003cstrong\u003eA) \u003c/strong\u003eThe large bubble formed during buffer switching can be easily flushed out by increasing the flowrate or slightly tilting the device. \u003cstrong\u003eB) \u003c/strong\u003eThe micro bubbles formed at high perfusion flowrates are traveling near the top surface of the main channel and not entering the traps due to the channel height difference.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/8be182c8099ec3aa492abc44.png"},{"id":37103878,"identity":"894837fe-9edd-4c30-a9eb-b8da8e25ef02","added_by":"auto","created_at":"2023-05-16 17:48:53","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":389169,"visible":true,"origin":"","legend":"\u003cp\u003eOn-chip versus. on-plate whole mount zebrafish Caspase-3 ABS.\u003cstrong\u003e A)\u003c/strong\u003e Top: gray scale images of the tail and trunk for 34 hpf UV treated zebrafish embryo after Caspase-3 ABS. (Vertical axis: on-plate ABS and on-chip ABS at different washing flowrates; Horizontal axis: different PBDT washing times). Bottom: The quantified signal levels for on-plate ABS (measured in 0.5% agarose) and on-chip ABS (measure on-chip in PBDT droplets) at different PBDT washing times and flowrates. (N≥3, n≥10, error bar: +SEM. \u003cstrong\u003eB)\u003c/strong\u003e The signal levels for the same set of embryos measured on-chip and in 0.5% agarose, error bar: +SEM. \u003cstrong\u003eC)\u003c/strong\u003e The experiment variances for on-chip and on-plate whole mount zebrafish Caspase-3 ABS (N≥12).\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/3b71c76bb8a6b5c2cfdce67a.png"},{"id":44735632,"identity":"b94bbaaf-b101-4bab-bcd4-288dad68b3a5","added_by":"auto","created_at":"2023-10-16 22:26:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5825625,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/30dd4908-cf9f-44ed-b84b-789c1c24903f.pdf"},{"id":37103969,"identity":"daa8e9ec-e7e3-45a3-8994-acb830d23633","added_by":"auto","created_at":"2023-05-16 17:49:14","extension":"mp4","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":392031159,"visible":true,"origin":"","legend":"","description":"","filename":"Movie1SEmbryotrappingassistedbyGforce.mp4","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/fc402e66a6aeae0ceea7c450.mp4"},{"id":37103906,"identity":"514b653a-b5fd-4687-b954-3a5b7db8d5b6","added_by":"auto","created_at":"2023-05-16 17:49:04","extension":"mp4","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":237486023,"visible":true,"origin":"","legend":"","description":"","filename":"Movie2SEmbryoTrappingwithoutGforce.mp4","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/6c6227c0556e1cb6349bd564.mp4"},{"id":37103884,"identity":"788ae050-5de2-47e2-8cfa-0e48ab2cdfb0","added_by":"auto","created_at":"2023-05-16 17:48:56","extension":"mp4","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":52813396,"visible":true,"origin":"","legend":"","description":"","filename":"Movie3SBufferswitchingandFROFFtoON.mp4","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/7098d6e5b9de42a1629792ce.mp4"},{"id":37103886,"identity":"47ef18d9-8cf9-44d1-9115-c7d73ade664c","added_by":"auto","created_at":"2023-05-16 17:48:57","extension":"mp4","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":92268844,"visible":true,"origin":"","legend":"","description":"","filename":"Movie4SFlushing.mp4","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/2afa58511f4e229e5b1f6890.mp4"},{"id":37103885,"identity":"97b6f888-a412-48e3-9cdf-892f28d8d66a","added_by":"auto","created_at":"2023-05-16 17:48:56","extension":"mp4","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":56384671,"visible":true,"origin":"","legend":"","description":"","filename":"Movie5SLargebubbleprevention.mp4","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/dbaa7da43ea08910facd2a15.mp4"},{"id":37103883,"identity":"b105f8d9-3421-4ad6-94a3-738cbf64fd49","added_by":"auto","created_at":"2023-05-16 17:48:55","extension":"mp4","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":39610611,"visible":true,"origin":"","legend":"","description":"","filename":"Movie6SMicrobubbuleprevention.mp4","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/376eb429ea6758dfed014079.mp4"},{"id":37103881,"identity":"a77f3722-7a3f-40fb-8c63-584f808c1043","added_by":"auto","created_at":"2023-05-16 17:48:53","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":733373,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.png","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/5e8aae28008fbc6ce6d27387.png"},{"id":37103882,"identity":"93ee7d7f-a26a-4980-89a1-4469409b6d0d","added_by":"auto","created_at":"2023-05-16 17:48:53","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":3698140,"visible":true,"origin":"","legend":"","description":"","filename":"Supplymentaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-2913815/v1/d5b4e8f896a956476e5f8884.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Multi-depth Spiral Milli Fluidic Device for Whole Mount Zebrafish Antibody Staining","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eSince the 1960s, zebrafish have served as one of the powerful and convenient small animal models in biomedical research. With its high reproduction rate, small size, body transparency, and closer phylogenetic relationship to humans, zebrafish coupled with molecular tools is ideal for high throughput \u003cem\u003ein situ\u003c/em\u003e studies such as drug screening, embryotoxicity tests, genetic or tissue functional studies. However, most of the zebrafish related studies are still conducted manually in microplates or microtubes. Very little changes have been made in the last decades in the way of conducting zebrafish studies.\u003c/p\u003e \u003cp\u003eThe whole mount zebrafish ABS and ISH using protein and antisense RNA probes are common molecular staining techniques for detecting the protein and gene localization information on zebrafish. The conventional manual procedure for the whole mount zebrafish molecular staining usually takes hours or days to complete and involves a series of tedious and time-consuming steps (Sorrells et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Thisse \u0026amp; Thisse, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Moreover, the performance and consistency of the procedure is usually skill dependent. To overcome these limitations, automated liquid handling platforms have developed to perform the assays. These platforms use robotic arms or hydraulic systems for automated liquid handling and are usually compatible with well-plate or tubes (Fuqua et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Although they can greatly reduce the labor and improve the consistency of the assays, the platforms are not usually affordable by labs with limited budgets. In 2021, Fuqua et al. developed a semi-automated liquid handling platform, \u003cem\u003eFlyspresso\u003c/em\u003e, for the whole mount fruit fly ABS. The \u003cem\u003eFlyspresso\u003c/em\u003e utilizes a programmed gas-powered hydraulic system for the liquid handling which has a portable size and is compatible with various staining procedures (Fuqua et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This open-source platform provides an economic way for developing customized automated platform for whole organism assays. However, it is not a \u0026ldquo;sample-in and answer-out\u0026rdquo; platform as the specimens still need to be retrieved and manually mounted for imaging. Moreover, the shaking or repeat pipetting-based mass transfer enhancements in tube and well-plate limit the room for process optimization and time reduction (Fuqua et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) To address these limitations, one way is to integrate the automated platform with fluidic devices.\u003c/p\u003e \u003cp\u003eIn the last decades, several fluidic devices have been developed for ABS and ISH. Most of them are used for biomarker detection at cell and tissue levels (Brajkovic et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ciftlik et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Huber et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kao et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ma\u0026iuml;no et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; H. T. Nguyen et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Vanderhoeven et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). These devices have demonstrated that both sensitivity and specificity of the assay can be improved by the controlled microenvironments and the procedure can be speeded up by enhancing the convective mass transfer (Brajkovic et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ciftlik et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Kao et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Vanderhoeven et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Despite these, the fluidic platforms for the whole organism ABS or ISH were rarely reported. In 2012, Akagi et al. developed a milli fluidic device that can automatically trap, immobilize and micro perfuse on lived zebrafish embryos. Integrating with a USB microscope, the system can be used for long term real-time \u003cem\u003ein situ\u003c/em\u003e monitoring during fish embryo toxicity tests (FET) (Akagi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Notably, the whole mount zebrafish Trypan blue staining was performed using the milli fluidic device and staining process was found sped up by micro perfusing at high flowrate (Akagi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Although Trypan blue is not a macromolecular probe, the proof-of-concept study suggested that the mass transfer process can be enhanced with high flowrate even for the whole mount zebrafish. This study provides evidence that the whole mount zebrafish molecular staining procedure has the potential to be accelerated by using fluidic devices.\u003c/p\u003e \u003cp\u003eFrom engineering and economic perspectives, integrating the fluidic device, especially micro- or nano- fluidic with the automated platforms is indeed debatable. The main controversy lies in the complexity of the use, as well as the high cost associated with the device fabrication and development. Nevertheless, these concerns may not apply to milli fluidic devices. Compared with the conventional microfluidic device, the milli fluidic device that is used for whole organism studies usually has more resolution tolerance (Frey et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Also, because the subject (i.e., whole organism) is at macroscopic level, applications such as trapping (Akagi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), sorting (Panuška et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), drug dosage generation (Kao et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), etc. can be realized by applying relatively simple channel geometry and the results are unlikely to be prone to defects (Frey et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For these, the design and fabrication of the milli fluidic device can be achieved without the cleanroom. With the assistance of micro-milling machines (Akagi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) or 3D printers (Fuad et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Vanderhoeven et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), new channel designs can be rapidly prototyped and tested. Also, manufacturing processes such as injection molding and hot embossing can be easily adapted for mass production at low cost. Collectively, in contrast to the micro- or nano- fluidic device, the milli fluidic device will have more potential to be incorporated with the automated liquid handling platform and more likely to achieve the procedure automation level of \u0026ldquo;sample-in and answer-out\u0026rdquo;.\u003c/p\u003e \u003cp\u003eIn this study, we developed a simple multi-depth milli fluidic device that can trap and immobilize the zebrafish embryo. The device is fabricated by a consumer-grade LCD SLA 3D printer assisted rapid prototyping method. For the first time, the complete procedure for the whole mount zebrafish ABS was performed and optimized on a milli fluidic device.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Design and 3D printer assisted fast prototyping\u003c/h2\u003e \u003cp\u003eThe 2D layout of the milli fluidic device was generated by using AutoCAD (Autodesk Inc. San Rafael, California, USA) and then converted into 3D models in AutoCAD Fusion 360. The negative master model of the milli fluidic device was exported as an STL file and sliced in an Anycubic Photon Workshop slicer (Anycubic Inc. Shenzhen, China) for 3D printing. The master mold was printed by the Anycubic Photon Mono X LCD SLA 3D printer using the Anycubic gray UV resin. Briefly, the layer thickness was set to 50 \u0026micro;m with 16 seconds off time and 2 seconds UV exposure time to avoid the overcuring (Mohamed et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). After the 3D printing, the master mold was washed in 90% isopropanol for 30 mins and dried in the air. To prevent PDMS (Sylgard 184; DowCorning Corp, Midland, MI, USA) curing inhibition, the 3D printed master model was then UV exposed for 2 hours following a 16-hour heat treatment at 80 \u003csup\u003e0\u003c/sup\u003eC (Venzac et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). For the PDMS soft lithography, the PDMS elastomer and curing agent were mixed at 10:1 (w/w) ratio and degassed before and after the PDMS casting to remove the air bubbles. The PDMS was then cured for 1 hour at 80 \u003csup\u003e0\u003c/sup\u003eC and peeled off from the resin mold. For the tubing and accessory interconnection, 3 mm holes were punched in the PDMS layer with a biopsy punch (Robbins Instruments, Sunnyvale, California, USA). The PDMS layer was bonded with a manually cut microscope glass slide using an air plasma cleaner (Harrick Plasma Inc. New York, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Computational simulations\u003c/h2\u003e \u003cp\u003eCOMSOL 5.5 (COMSOL 5.5 Inc. Stockholm, Sweden) was used to perform the fluid dynamic and mass transfer simulations to evaluate the on-chip trapping and mass transfer processes. The \u0026ldquo;free and porous media flow\u0026rdquo; was used to simulate the steady state fluidic fields for the initial (i.e., no trap is occupied) and final (i.e., all traps are occupied) states of the trapping. The steady state fluidic field for the final state of trapping is then coupled with \u0026ldquo;the transport of diluted species in porous media '' to simulate the buffer replacement during the flushing process in a time-dependent study. The inlet flowrate was set to be 10 ml/min for both trapping and flushing simulations. Water was used as the carrying fluid in the simulations and the diffusion coefficient for the IgG antibody was defined as 1\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e10\u003csup\u003e\u0026minus;7\u003c/sup\u003e cm\u003csup\u003e2\u003c/sup\u003e/s (Kao et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). To determine the maximum shear stress applied on embryos after trapping, the inlet flowrate was set to 20 ml/min as it is the maximum flowrate for the current system. The dechorionated zebrafish was molded as a cone-shape rigid body with 2 mm overall length and 0.5 mm maximum head diameter.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 System setup and operation procedure\u003c/h2\u003e \u003cp\u003eA peristaltic pump (Kamoer Fluid Tech Co., Ltd, Shanghai, China) using a 2.3 mm ID and 4.6 mm OD polyurethane tube was used to drive the fluid in the system. To reduce the oscillation and smoothen the flow, a homemade pulse damper assembled by a 60 ml syringe and a two way-valve (Cole-Parmer Inc.) connected the chip outlet and the peristaltic pump inlet. A three way-valve was used to connect the peristaltic pump outlet, a 10 ml loading reservoir, and a waste container to allow both the close-loop perfusion and open-loop flushing. Silicone tubes with 2 mm ID and a 3 mm OD were used for the connection. This tubing size allows multiple embryos to be loaded and travel in the system simultaneously. Before operation, the fluidic device was first flushed with 70% (v/v) ethanol to wet the channel wall and prevent the bubble formation. The PBST buffer was used as the carrying buffer for the embryo trapping. To speed up the trapping process, the chip can be titled to let the gravitational force assist the trapping. For the consistency of the experiments, the flowrates for the trapping were set to be 10 ml/min. An acrylic M3 screw was used as the flow restrictor (FR) to partially block the main channel during the whole mount zebrafish ABS procedure (ON mode). Also, the FR was lifted during the trapping and flushing (i.e., OFF mode). When switching the buffers, the old buffer was first drained out into the waste container. The new buffer was then introduced into the system and flushing the channel in the open-loop for 30 seconds before switching back to close-loop perfusion. The flowrate used during buffer switching is 10 ml/min.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Zebrafish husbandry, embryo UV treatment and fixation\u003c/h2\u003e \u003cp\u003eAdult wild type zebrafish (EKW line) were raised in the UC Merced fish facility with a 14/10-hour light and dark switching cycle. The zebrafish were fed twice daily with dry feed (300 to 400 pellet size) to ensure healthy development. The zebrafish were randomly paired a night before the mating and spawning. The embryos were collected using a sieve and then rinsed with the E3 buffer to filter out the debris and wastes. The collected embryos were cultivated in the petri dish filled with E3 buffer at 28.5 \u003csup\u003e0\u003c/sup\u003eC and dead embryos were sorted during the development. To activate the Caspase-3, 24 hpf embryos were manually dechorionated and then transferred into a petri dish (~\u0026thinsp;100 embryos per dish) filled with 15 ml E3 buffer. The embryos were then exposed under the UV lights (~\u0026thinsp;0.44 W/cm\u003csup\u003e2\u003c/sup\u003e) in the biosafety cabinet (NuAire Inc. Plymouth, USA) for 2 hours following 8 hours recovery in an incubator at 28.5\u0026deg;C. The treated embryos were fixed in 4% formaldehydes/PBST for overnight at 4 \u003csup\u003eo\u003c/sup\u003eC and then stored in 100% methanol at \u0026ndash; 20 \u003csup\u003eo\u003c/sup\u003eC for later staining, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA\u0026amp;B.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Whole mount zebrafish Caspase-3 antibody staining\u003c/h2\u003e \u003cp\u003eThe procedures for the plate-based and device-based whole mount zebrafish Caspase-3 ABS are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The sample preprocessing for both plate-based and device-based procedures are performed in the 24-well plate. A belly-dancer (IBI Scientific Inc., Iowa, USA) was used to provide medium level shaking for the on-plate steps. For the plate-based whole mount zebrafish Caspase-3 ABS, 10 to 15 embryos were loaded per well in the 24-well plate. For the device-based whole mount zebrafish Caspase-3 ABS, the number of embryos tested on the device was dependent on the trapping result. The flowrate and time for each on-chip staining step was kept constant at 10 ml/min and 2 hours, respectively. The dilution ratios for the primary antibody and secondary antibody were kept at 1:1000 (Cell signaling technology #9661, -Caspase-3, Rabbit) and 1:200 (Invitrogen #31686, -Rabbit Rhodamine, 0.5 mg/ml in stock), respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Imaging and signal quantification\u003c/h2\u003e \u003cp\u003eThe fluorescence images were acquired under the confocal microscope (Leica Biosystem Inc.) with 100 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e magnification, 15% laser power, and 800 volts digital gain. The laser beam scanned the zebrafish embryo along the Z direction every 5 \u0026micro;m to get the sliced images. The sliced images were then stacked to form a Z projected image using the maximum intensity. ImageJ was used to analyze the signal levels on the Z-projected images by applying masks with threshold level of 100 on the 8-bit gray scaled images.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Data analysis and reproducibility\u003c/h2\u003e \u003cp\u003eThe statistical analysis was conducted by GraphPad Prism (GraphPad Software) and MS Excel (Microsoft, USA). The Student T-tests were used to measure the significant level (P\u0026thinsp;\u0026lt;\u0026thinsp;0.5) between the groups. To ensure unbiased experimental results, the controlled experiments were conducted for at least 3 replicates (i.e., N \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\ge\\)\u003c/span\u003e\u003c/span\u003e 3) with at least 10 embryos per replicate (i.e., n \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\ge\\)\u003c/span\u003e\u003c/span\u003e10). The results were measured and quantified under the same standard. Embryos collected from the same batch were only to be used for the same type of experiments. To avoid the risk of contamination, the PDMS-glass devices were only for one time use and all the buffers were used within the recommended storage periods.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Experimental Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Device design and fabrication\u003c/h2\u003e\n \u003cp\u003eA multi-depth spiral device was designed to trap, immobilize, and perform the whole mount ABS on the 24 to 48 hpf chorion-less zebrafish embryos. The device contains 3 major functional parts: a spiral main channel, an inner suction chamber, and 26 trapping channels that interconnect the main channel and inner reservoir, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA. Hydrodynamic suction was used as the main trapping and immobilization force in this design. When operating, the inner chamber, which connects the peristaltic pump at the outlet, provides a negative pressure to draw the fluids from the main channel via the traps. The height for the main and the trap channel is 1.2 mm and 0.8 mm, respectively. The funnel-like outlet has a peak height of 2 mm, a 2 mm ID and an 8 mm OD. The purposes for the different heights in the trap, main channel, and outlet are: 1) to shorten the mass transfer distance in the traps; 2) to prevent bubbles from entering the traps; 3) to drain out the bubbles accumulating in the inner reservoir. Also, the main channel has a width of 3.5 mm which allows multiple chorion-less embryos to travel simultaneously and let individual embryo to freely self-orientate. The trap entrance has a width of 2 mm, a length of 2.14 mm, and the width of the trap nozzle is 0.25 mm. The nozzle length is used to regulate the strength of the hydrodynamic suction force during trapping. The length of each individual trap is decreasing from 1 mm to 0.5 mm at a rate of 0.02 mm/trap along the main channel. This configuration is to ensure a close hydrodynamic trapping effect or embryo drawing ability at each trap for the purpose of maximizing the trap usage, smooth the trapping process, and minimize the procedure lagging, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eS. A 3 mm diameter flow restrictor (i.e., an acrylic M3 screw) is used to partially block the end of the main channel during the whole mount zebrafish ABS. The total internal volume of the device is about 1 ml which is close to the volume commonly used at a single well in a 24-well plate. Besides, the internal volume of individual trap is about 1.37 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\mu l\\)\u003c/span\u003e\u003c/span\u003e which ensures \u0026ldquo;one embryo per trap\u0026rdquo; and a high surface-to-volume environment for the embryo. To reduce the flow pulsing caused by the peristaltic pump, a homemade pulse dampener, customized by a 60 ml lure head syringe, is connected in between the device outlet and the peristaltic pump, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eS. The minimum system volume is about 6 ml when perfusing in the close loop. Unlike the previously reported zebrafish trapping systems (Akagi et al., \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e; Fuad et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zhu et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e), that only allow one embryo to be loaded each time, in this work, embryos can be loaded all at once for close-loop trapping, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eE.\u003c/p\u003e\n \u003cp\u003eThe PDMS-glass device in this work was fabricated by using the LCD SLA 3D printer assisted fast prototyping method, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB. The negative mold of the device was printed by the Anycubic Photon Mono X LCD SLA 3D printer, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC. After printing, the mold was washed with 70% IPA and dried in the air. To prevent the PDMS curing inhibition, the 3D printed mold was post-treated with UV light for 2 hours following 16 hours heat treatment at 80 \u003csup\u003e0\u003c/sup\u003eC (Venzac et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). The PDMS was then casted onto the 3D printed mold and cured at 80 \u003csup\u003e0\u003c/sup\u003eC for 1 hour. After curing, the PDMS layer was peeled off from the mold and plasma bonded with a microscopic glass slide, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD. The LCD SLA 3D printer used in this work uses a 3840 2400 (4K) LCD screen and an array of UV lamp beads to control the pattern printing at each layer. To avoid overcuring and resin flow disturbing, the UV exposure time at each layer was set to 2 seconds with a 0.25 mm/s lifting speed and a 3 mm/s retract speed. The 3D printer employs an LCD screen with 50 \u0026micro;m by 50 \u0026micro;m pixel size that cannot always fit the edge of design perfectly. Therefore, jagged channel walls are expected to be casted using the mold printed by LCD SLA 3D printer. To reduce the edge jaggedness of the mold, the anti-aliasing algorithm was also applied in the settings. To evaluate the fabrication quality, the nozzle width is inspected as it is the smallest feature in the device. The result has indicated that the average nozzle width is about 0.2850\u0026thinsp;\u0026plusmn;\u0026thinsp;0.031 mm (N\u0026thinsp;=\u0026thinsp;5) when the target width is 0.25 mm, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eS. As expected, the channel wall was also found to be rough, even applied with the highest level of anti-aliasing. The variation of the channel width and the rough channel wall were considered acceptable as only a limited hydrodynamic difference could be caused by the small variations and the elastic property of the PDMS would extenuate the mechanical damage on the zebrafish embryo.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Embryo trapping and immobilization\u003c/h2\u003e\n \u003cp\u003eDuring trapping, the hydrodynamic suction force deviates the embryos towards the inner wall and then drags the embryos into the traps, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA. The hydrodynamic trapping process can be easily explained by a simplified circular analogy diagram, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB. Briefly, the embryo trapping occurs, when the overall flow that passes through the traps is greater than the flow that travels through the main channel (Q\u003csub\u003etraps\u003c/sub\u003e \u0026gt; Q\u003csub\u003emain\u003c/sub\u003e). In this chip design, the traps are arranged in a parallel configuration (M.-A. Nguyen et al., \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e) and the inner reservoir can be treated as the ground that provides a relatively constant downstream pressure, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eS. Based on the CFD simulation, the flow that passes through the traps drops from 76%, when all traps are empty, to about 59%, when all the traps are occupied. Thus, the trapping is expected to get harder when more traps are being occupied during the process. Despite this, the possibility for the trapping remains at the last moment as the flow passing through the traps is still higher than the flow going through the main channel. To maximize the usage of the traps, gravitational force was also used to assist the trapping at the late trapping phase (i.e., most traps are occupied) in which the device was titled towards the remaining empty traps (Movie S1). When using 10 ml/min for close-loop trapping, the trap occupation rate can easily reach over 84% without gravitational force (Movie S2, data not shown) and can achieve 93.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0% (N\u0026thinsp;=\u0026thinsp;24, n\u0026thinsp;=\u0026thinsp;624) with the assistance of the gravitational force, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eE. The trapping results also indicate that the first trap was usually skipped by the embryos even with the help of the gravitational force. This is due to the high main channel velocity near the inlet which gives the embryo a less deviation time towards the inner wall. Therefore, the first trap in this design mostly plays the role of the divergent channel to help the embryos deviate towards the inner wall. The aim for the chip is to automatically immobilize the zebrafish embryo and then perform the antibody staining. Because a confocal microscope is used in the signal measurement, the orientation control of the zebrafish embryo was not in the design considerations initially. Interestingly, the validation experiments show that about 93.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3% (N\u0026thinsp;=\u0026thinsp;24) trapped embryos had their heads pointing inward after the chaotic trapping. One of the explanations for this orientation consistency is that the head of the zebrafish embryo experiences a much stronger drag force compared with the narrowed body and tail in the channel, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eS. Thus, it is more likely for the head of the embryos to point towards the inner wall and then be dragged into the traps.\u003c/p\u003e\n \u003cp\u003eTo stably transfer the device to various imaging platforms without disturbing the embryos\u0026rsquo; positions, the buffer is drained out of the devices after the trapping. Due to the presence of Laplace pressure, the holdup volume of the remaining buffer will form droplets inside the traps, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eD. These droplets can wrap around individual zebrafish embryos forming isolated chambers. The encapsulated zebrafish embryos are unlikely to be disturbed by actions such as device unplugging and relocation. Thereafter, the portable device can be transferred to microscope stations for imaging. To our best knowledge, this feature has not been reported by other similar devices. Potential usages for this feature in zebrafish embryonic studies such as metabolism analysis, hypoxia studies, and toxicity tests may be worth investigating in the future.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 On-Chip flow settings\u003c/h2\u003e\n \u003cp\u003eThe multi-depth spiral device uses a simple parallel trapping configuration. However, the limitation for this configuration is also obvious as the flowrate in the individual traps drops along the spiral main channel (M.-A. Nguyen et al., \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). This is not ideal for the on-chip ABS because the convective mass transfer rate is now different at each trap and the last trap always takes the longest time to complete the mass transfer. To minimize this procedure lagging, a flow restrictor (FR) is added to partially block the main channel during the on-chip ABS. Based on the CFD simulation, the add-on of the FR can boost the flowrate in the traps as well as close the flowrate differences among the traps, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA. The validation experiments using the methylene blue/PBST also confirmed that the FR ON mode enhances the perfusion in the traps as it took less time for the dye to fill the traps, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB \u0026amp;C. Here, the flowrate for both the CFD simulations and validation experiments was set to 10 ml/min.\u003c/p\u003e\n \u003cp\u003eDuring the buffer switching (Movie 3S), the old buffer will first be flushing out in the system. To ensure the overall system is replaced by the new buffer and all the holdup volume inside traps is cleaned up, the system is then flushed with the new buffer in the open loop before switching to the close loop circulation. In the simulation, the old buffer (i.e., the PBDT with antibody) was set to be replaced by the new buffer (i.e., PBDT) at 10 ml/min. The simulation showed that it takes about 7 seconds for new buffer to reach and flush out the old buffer in the last trap, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, middle panel. However, the device is not completely cleaned as the old buffer is still accumulated at the center chamber, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, top and bottom panels. To completely flush out the old buffer from the system, the flushing process needs to carry on for another 23 seconds to an overall 30 second flushing time. Both simulation and validation experiments using methylene blue/PBST have shown that the system can be completely replaced by the new buffer after flushing for 30 seconds at 10 ml/min (Movie 4S). Note, during the buffer switching, the FR is turned OFF (i.e., M3 is lifted) to prevent the potential bubble blocking.\u003c/p\u003e\n \u003cp\u003eOne of the concerns for on-chip flowthrough operations is the body shear stress exerted by the superficial flow may damage the fixed embryos. The CFD simulation showed that when perfusion flow is at 20 ml/min and the FR is turned ON, the maximum shear stress applied on the embryo is about 0.672 Pa and the shear stress hot spot is located at the upper surface of the embryo, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e. We believe this shear stress level is unlikely to damage the fixed zebrafish embryos as tissue becomes more rigid and less fragile after formaldehyde fixation. Indeed, most observed embryo damages were during the off-chip pipetting and embryo transferring.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 Multi-depth Channel for Bubble Prevention\u003c/h2\u003e\n \u003cp\u003eThe air bubble introduction is the major cause of biases for the device-based zebrafish assays. Bubbles can obstruct the trap during the perfusion, interfere with the embryo imaging, and induce backflow, all of which can adversely affect the accuracy and reliability of the assay results. As most PDMS-glass milli fluidic devices are integrated with open pumping systems, the air may enter the device through both inlet and the gas permeable PDMS layer leading to the formation of liquid-gas flow in the device. Likewise, in our current system setup, the flow is driven by a peristaltic pump. To reduce the pulsing caused by the peristaltic pump, the buffer loading tube must open to the air. Therefore, air can potentially be introduced into the device during the operation. By far, the only attempt to prevent the air bubbles in the milli fluidic device is made by Zhu et al. The group reported a bubble free milli fluidic device by bonding a PDMS vacuum layer on top of the PDMS zebrafish embryo culture channel layer (Zhu et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). In their study, the negative pressure in the vacuum chamber can effectively remove the bubbles from the embryo culture channel. However, the multilayer PDMS device will complicate the fabrication steps and the additional PDMS layer may affect the signal detection during the imaging. Moreover, the application of external negative pressure may affect the zebrafish embryo culture environment such as oxygen level. Here, we demonstrated a simple channel geometry-based bubble prevention method for the single layer milli fluidic device.\u003c/p\u003e\n \u003cp\u003eIn our current system setting, buffer switching, and high flowrate perfusion are the two situations where most bubble introduction events occur. Nevertheless, the types of bubbles that are introduced in these two situations are different, as are the underlying bubble formation mechanisms. During the buffer switching step, the channel was first emptied and the new buffer together with air was then perfused into the channel. The bubbles introduced during the buffer switching step are usually large or medium sized bubbles, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eA. These bubbles which usually have larger size than the trap is unlikely to enter the trap during the perfusion. However, the movement of the large bubbles may cause pressure fluctuations, induce backflow, and as a result disturb the trapped embryos. Our milli fluidic device offers a spacious main channel for the large bubbles which can minimize the pressure fluctuations caused by their movements and thus unlikely to disturb the trapped embryo. Also, because of their large radius, the large air bubbles experience less capillary retaining force in the main channel and therefore can be easily flushed out of the device (Movie 5S). Note the narrow section at the end of the main channel may prevent the large bubbles from being removed. Increase the flushing flowrate or slightly title the device can help to remove the large bubbles stuck at the end of the main channel.\u003c/p\u003e\n \u003cp\u003eWhen operating at the high perfusion flowrate (i.e., 20 ml/min), micro bubbles were found in the channels, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eB. This is because air was introduced with the buffer at high pumping speed generating dispersed-bubble flow in the channel. Besides, the use of detergents such as Triton X-100 and Tween 20 also aggravates the formation of the micro bubbles. In our device, because the main channel height is greater than the trapping channels, micro bubbles travel near the top surface of the main channel and are unlikely to enter the traps (Movie 6S).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5 Optimization of the on-chip whole mount zebrafish Caspase-3 antibody staining\u003c/h2\u003e\n \u003cp\u003eThe whole mount zebrafish Caspase-3 ABS is a well-established assay to detect the level of cell apoptosis in the zebrafish (Sorrells et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). To induce the Caspase-3 cleavage, we applied UV light, a common environmental stress triggering apoptosis pathway, on the zebrafish embryo (Zeng et al., \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e). To investigate if the whole mount zebrafish ABS can be improved in the flowthrough environment, we next tested the whole mount zebrafish Caspase-3 ABS on the fluidic device and compared the performance with conventional plate-based manual procedure. The procedures for the plate-based and device-based whole mount zebrafish Caspase-3 ABS are shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. Note the washing time and flowrate shown in device-based procedure is the final optimized results. The standard on-plate washing time is 120 mins.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e Whole mount zebrafish Caspase-3 ABS procedures.\u003c/p\u003e\n \u003cp\u003e\u003cimg 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\" width=\"944\" height=\"603\"\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eThe general whole mount zebrafish ABS procedure involves both staining and washing steps (Sorrells et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). To ensure the antibody can sufficiently bind to the antigen, the staining time is usually kept at an extended level (e.g., overnight). Despite no systematic study has been conducted to investigate how the fluidic flow can affect the antibody-antigen interaction in the whole mount zebrafish, the studies performed in tubes or well-plates suggested that the antibody staining took longer in older embryos as the tissue became denser (Sorrells et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). The intact tissue of the zebrafish embryo certainly affects the antibody penetration. Therefore, optimizing the whole organism staining procedure by reducing the staining time may result in loss of sensitivity. The washing step, on the other hand, is for the removal of the nonspecific binding after the staining step and is crucial for the specificity of the procedure. Targeting the washing steps will be a safer option for the optimization of the whole organism staining as the true signal is ensured with sufficient staining time. Also, the manual buffer refreshing steps can be avoided during on-chip washing as the wash buffer is circulated in a close-loop. For these, the washing steps were targeted for the on-chip whole mount zebrafish Caspase-3 ABS optimization. Briefly, in the milli fluidic device, two flowrates viz., 10 ml/min and 20 ml/min were used to perform 30 mins, 60 mins, 90 mins, and 120 mins washings after each staining step, Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eA, top panel. To ensure the consistency and sufficient Casapse-3 binding, the flowrate and time for the two staining steps were kept constant at 10 ml/min and 120 mins, respectively. For comparison, the same washing times were tested in the plate-based procedure using a 24-well plate. After the procedure, the Caspase-3 signals were measured from the zebrafish embryos encapsulated by the PDST droplets in the milli fluidic device and 0.5% agarose in well-plate.\u003c/p\u003e\n \u003cp\u003eBased on the experiment results, the washing process was found to be accelerated using the device as significant intensity differences were found at 30 mins, 60 mins, and 90 mins between the on-plate and the on-chip washings, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003eA, bottom panel. Also, the samples were found already sufficiently washed at 60 mins when the on-chip washing flowrate is 20 ml/min. In addition, a significant intensity difference was found between the two tested on-chip washing flowrates at the 60 mins which implied a higher on-chip washing flowrate can speed up the washing process. The two tested on-chip washing flowrates showed insufficient washing at 30 mins as the intensities for both flowrates were significantly higher than the control and no significant intensity difference can be distinct between them. Regarding the image taking environments, the intensity measured from the PBDT droplets inside the chip has a slightly decreased signal when compared to the intensity measured in the 0.5% agarose gel. This is likely due to the power attenuation of the fluorescent laser by the thick PDMS layer on top of the device. Despite this, the signal difference between the on-chip and in agarose measurements is not significant, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003eB. We next normalized the intensity of all the experimental results measured by respective means and the consistency of the device-based procedure is found higher than that of the plate-based procedure, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003eC. Also, the consistency of the assay seemed to be improved when applying higher on-chip washing flowrate.\u003c/p\u003e\n \u003cp\u003eAll in all, the milli fluidic-based whole mount zebrafish ABS outperforms the conventional plate-based manual approach by reducing both manual steps and time while increasing the consistency of the results. This highlights the benefits of miniaturization and mechanization of zebrafish assays.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4 Discussion and Conclusions","content":"\u003cp\u003eZebrafish-on-a-chip may have experienced significant growth lately, but it is still in the early development phase (Li et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The needs for optimizing and automating the time consuming and labor-intensive procedures such as whole mount zebrafish ABS and ISH is still largely unfulfilled. To fill the gap, we developed a multi-depth spiral device that can trap, immobilize, and perform the whole mount Caspase-3 ABS on the chorion-less zebrafish embryo. The device was fabricated by using a 3D printer assisted rapid prototyping method. Remarkably, the commercial leveled 3D printer and photo resin were used in making the master mold in this study. Compared with the fabrication methods reported previously (Fuad et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), our method is more economical in prototyping zebrafish-on-a-chip devices and can be easily adapted by small budget labs.\u003c/p\u003e \u003cp\u003eThe multi-depth spiral device developed in the study uses the classic hydrodynamic trapping mechanism yet a chaotic trapping process to trap chorion-less zebrafish embryos in the close-loop pumping system. The device showed a trap usage rate that is comparable to the previously reported zebrafish embryo trapping platforms (Akagi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Fuad et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), but with a more convenient operating procedure as multiple embryos can be loaded into the chip at the same time. Also, the orientation preference (i.e., head point inward) found when trapping the cone-shaped fixed zebrafish embryo can be used for the future optimization of devices that need orientation control. This phenomenon may also provide some insights for the trapping and sorting of non-spherical particles in other fluidic devices. In addition, the trapped embryos were found to be encapsulated in the droplets after draining out the buffer. The encapsulation of embryos in droplets makes the device become portable and allows the device to access various imaging platforms after trapping. This feature, which has not been reported by similar devices, may have potential to be used for the applications such as embryonic toxicity tests, drug screening, metabolite analysis, hypoxia study etc.\u003c/p\u003e \u003cp\u003eIn this study, for the first time, the complete procedure of the whole mount zebrafish ABS was performed and optimized on a zebrafish-on-chip system. We proved that the washing process in the whole mount zebrafish Caspsae-3 ABS procedure can be accelerated by a higher perfusion flowrate. We believe this finding can also be applied to other types of whole mount zebrafish ABS procedures or even more complicated ISH procedures.\u003c/p\u003e \u003cp\u003eThe current device and system setting still have limitations that need to be optimized in the future. First, the on-chip close loop system requires more reagent volume (i.e., ~\u0026thinsp;2 times for washing and ~\u0026thinsp;6 times for staining) compared to the on-plate procedure due to off-chip volumes contributed by the tubing and pump. The large reagents requirement could be reduced by shortening or reducing the size of the tubing. Also, the effect of large reagent consumption may be minimized by conducting large scale tests (i.e., connect multiple devices in series) or by reusing the reagents (Fuqua et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Second, although the multi-depth device can prevent large- or micro- sized bubbles from entering the trap, the medium sized bubbles may still occasionally enter the traps during the perfusion. This is the major cause of bias in the study as the trapped bubbles will not only affect the flow through the traps but also block the embryo during the imaging. Therefore, a special bubble trapping or breaking device (Fu et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) could be added at the device inlet to trap the medium size bubbles or break the medium size bubble into micro bubbles. Finally, the current procedure still requires the operator to manually load the embryos and switch the buffers during each step. The manual buffer switching process can be eliminated by integrating the device with automated imaging and liquid handling platforms (Fuqua et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) in the future to reach the degree of \u0026ldquo;sample-in and answer-out\u0026rdquo;.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflicts of interest\u0026nbsp;\u003c/strong\u003eThere are no conflicts to declare.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAkagi, J., Khoshmanesh, K., Evans, B., Hall, C. J., Crosier, K. E., Cooper, J. M., Crosier, P. S., \u0026amp; Wlodkowic, D. (2012). 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A Bubble-Free Microfluidic Device for Easy-to-Operate Immobilization, Culturing and Monitoring of Zebrafish Embryos. \u003cem\u003eMicromachines\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(3), 168. https://doi.org/10.3390/mi10030168\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"biomedical-microdevices","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmmd","sideBox":"Learn more about [Biomedical Microdevices]()","snPcode":"10544","submissionUrl":"https://submission.nature.com/new-submission/10544/3","title":"Biomedical Microdevices","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"zebrafish embryo, milli fluidic, whole mount antibody staining, 3D printing","lastPublishedDoi":"10.21203/rs.3.rs-2913815/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2913815/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWhole mount zebrafish antibody staining (ABS) is a common staining technique for protein information localization on a zebrafish embryo or larva. Like most biological assays, the whole mount zebrafish ABS is still largely conducted manually through labor intensive and time-consuming steps which affect both consistency and throughput of the assay. In this work, we develop a milli fluidic device that can automatically trap and immobilize the fixed chorion-less zebrafish embryos for the whole mount ABS. With just a single loading step, the zebrafish embryos can be immobilized in the milli fluidic device through a chaotic hydrodynamic trapping process. Moreover, a consistent body orientation pattern (i.e., head point inward) for the trapped zebrafish embryos can be achieved without any additional orientation adjustment device. Furthermore, we employed a consumer-grade SLA 3D printer assisted method for device prototyping which is ideal for labs with limited budgets. Notably, the milli fluidic device has enabled the optimization and successful implementation of whole mount zebrafish Caspase-3 ABS. We demonstrated our device can accelerate the overall procedure by reducing at least 50% of washing time in the standard well-plate-based manual procedure. Also, the consistency is improved, and manual steps are reduced using the milli fluidic device. This work fills the gap in the milli fluidic application for whole mount zebrafish immunohistochemistry. We hope the device can be accepted by the zebrafish community and be used for other types of whole mount zebrafish ABS procedures or expanded to more complicated \u003cem\u003ein situ\u003c/em\u003e hybridization (ISH) procedure.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e","manuscriptTitle":"A Multi-depth Spiral Milli Fluidic Device for Whole Mount Zebrafish Antibody Staining","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-05-16 17:48:48","doi":"10.21203/rs.3.rs-2913815/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-07-06T19:16:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-05-31T21:44:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"0af0ab29-2ff6-4b9a-8a23-5e343707ddc6","date":"2023-05-13T22:29:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-05-13T22:27:09+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-05-13T22:25:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-05-12T08:03:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"Biomedical Microdevices","date":"2023-05-10T00:43:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"biomedical-microdevices","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmmd","sideBox":"Learn more about [Biomedical Microdevices]()","snPcode":"10544","submissionUrl":"https://submission.nature.com/new-submission/10544/3","title":"Biomedical Microdevices","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"892ec725-93b4-424a-bab3-83349a3cd99f","owner":[],"postedDate":"May 16th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T22:12:54+00:00","versionOfRecord":{"articleIdentity":"rs-2913815","link":"https://doi.org/10.1007/s10544-023-00670-2","journal":{"identity":"biomedical-microdevices","isVorOnly":false,"title":"Biomedical Microdevices"},"publishedOn":"2023-08-15 21:59:50","publishedOnDateReadable":"August 15th, 2023"},"versionCreatedAt":"2023-05-16 17:48:48","video":"","vorDoi":"10.1007/s10544-023-00670-2","vorDoiUrl":"https://doi.org/10.1007/s10544-023-00670-2","workflowStages":[]},"version":"v1","identity":"rs-2913815","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2913815","identity":"rs-2913815","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}