Method Article
This protocol outlines the implementation of image-guided, laser-based hydrogel degradation to fabricate vascular-derived, biomimetic microfluidic networks embedded in poly(ethylene glycol) diacrylate (PEGDA) hydrogels. These biomimetic microfluidic systems may be useful for tissue engineering applications, generation of in vitro disease models, and fabrication of advanced "on-a-chip" devices.
此详细的协议概述图像制导,激光为基础的水凝胶降解嵌入在PEGDA水凝胶血管源性微流体网络的制造执行。在这里,我们描述的虚拟面具,使图像引导的激光控制的建立;一个微成形PEGDA水凝胶,适用于微流体网络制造和压头驱动流的光聚合;设置和使用飞秒脉冲钛配对市售的激光扫描共聚焦显微镜:秒激光诱导水凝胶退化;并使用制造的微流体网络的成像荧光物质和共焦显微镜。多协议的集中在显微镜软件和显微镜宏的适当的设置和实施方式中,因为这些是在使用市售的显微镜对包含许多复杂的微流体制造目的的关键步骤。此techniqu的图像引导部件e可以为3D图像堆栈或用户生成3D模型的实现,从而使创意微设计和几乎所有的配置复杂的微流体系统的制造。在组织工程中的预期效果,在该协议中概述的方法可以在先进的仿生microtissue构建用于器官和人体上的单芯片器件的制造提供帮助。通过模仿复杂结构,扭曲,尺寸和体内脉管系统的密度,基本生物运输过程可以在这些构造中复制,导致药代动力学和疾病的更准确的体外模型。
血管系统,包括两个淋巴和cardiovasculature的,形式高度致密的网络,是用于营养和氧气的传输和用于去除代谢废物是必不可少的。因此,居住在血管化组织细胞从来没有超过50-100微米远离容器1。重现体内血管结构体外的能力,关键是要精确地模拟使用工程结构在体内的运输过程。随着最近的驱动开发用于高通量药物器官上的单芯片器件2筛选3,4和疾病建模5,6,方法创建一个概括的合成或天然水凝胶在体内般的交通正在绘制微流控网络显著的兴趣。以提高在这些设备中使用microtissues的仿生学,我们开发了利用三dimensiona一个图像引导,基于激光的水凝胶降解法作为模板天然脉管l的(3D)图像栈以生成嵌入PEGDA水凝胶7血管源性的微流体网络中。这个协议概括了使用配备有飞秒脉冲激光经由图像引导,基于激光的降解来制造在PEGDA凝胶血管源性,仿生微流体网络的市售激光扫描共焦显微镜的。
来流化水凝胶当前的方法包括的血管8-10或血管生成10-12内皮细胞自组装和微制造技术中的诱导对内皮13-16创建预定义的信道。而自组装网络概括密度和微血管的复杂结构,它们往往比体内网络11,17,18,这可能是在造型运输用于药物筛选应用问题更加可渗透的。自组装网络由physiolog的ically相关,毛细管尺寸的容器,但它们可能难以与散装流体流动整合由于在产生较大的动脉大小船只限制。因为是在这些网络的装配没有直接控制,最终的结构可以从样本变化来样,使得难以重复地制备具有相同的流体流动和输运性质网络。
为了产生3D,水凝胶的嵌有重复的几何形状和良好定义的体系结构的微流体网络中,若干微细加工技术得到了发展,其中包括模块式组件13,牺牲材料16,直接写入组件14,和全向印刷15的三维印刷。应用这些方法,微流体结构,因此,流体流动和输运性质,可以在许多结构被重复制造。这些方法的主要限制,然而,这是无法创造微法luidic网络与毛细管大小的功能,4〜10微米19。多数的微细加工技术往往局限于特征在直径13,16从150至650微米。一些现有技术能够在很宽的直径范围内具有通道产生分层网络,10至300微米为直接写入组件14,和18至600微米为全向印刷15,但它们在他们的产生密集网络或能力有限到单个构建体7内产生极为接近的多个微流体网络。
为了克服这些限制,我们开发的图像制导,激光为基础的水凝胶降解技术,使仿生的重复制造,即概括体内微血管的结构层次微流体网络。要做到这一点,一个790纳米,140飞秒脉冲激光在80 MHz工作是光栅扫描我Ñ所需的水凝胶内的三维位置, 通过体内脉管系统的图像作为限定。我们推测,降解过程通过水的激光诱导光学击穿,所得等离子体形成时,水的随后的快速热弹扩张,和水凝胶的局部降解操作作为水膨胀20。这种机制从基于蛋白的水凝胶21-24的基于激光的降解略有不同。不像PEGDA,其具有低多光子截面,蛋白质常常具有大的多光子截面,因此通过多光子吸收引起的化学断裂23降解。以生成图像引导的微流体网络中,激光快门被图像衍生虚拟口罩,其由限定微流体结构的兴趣9区域的镶嵌的控制。使用这种方法,我们已经证明,制作三维血管源性仿生微流体的能力集成电路网络,概括在体内脉管系统的密集和曲折结构,以便通过改变能量的降解期间输送的量局部地控制水凝胶的孔隙率。我们也已经能够产生交织在接近(15微米),但从未直接连接7两个独立的微流控网络。我们还证明,通过交降解官能与整结扎肽序列endothelialize激光恶化微通道的能力,精氨酸-甘氨酸-天冬氨酸-丝氨酸(RGDS),以促进内皮细胞的粘附和管腔形成7。
有了这个协议,复杂的微流控网络在PEGDA水凝胶的生成是使用在许多大学校园访问市售显微镜通过影像引导下,基于激光的下降成为可能。作为降解过程是由数字,虚拟掩模导向,这法布里卡化技术是适合于微流体网络的创意设计,允许其在各种应用中使用。我们预计,在这里所描述的方法将是在设计能够复制生物运输过程建模药物转运2重要的仿生器官和人体上的单芯片器件最有利的。这种制造技术也可用于在体外疾病模型,包括癌症转移5,6-和血脑屏障模型25的产生兴趣。如基于激光的水凝胶降解以前已用于创建神经元向外生长21-23的引导轨道,该技术的图像引导的延伸可在高级组织工程策略证明是有用的定位在用户定义三维空间排列的细胞。
1. Generating Virtual Masks
NOTE: A 3D image stack of mouse brain microvasculature was chosen as the microfluidic model for this protocol, having been culled from a much larger dataset containing images of an entire mouse brain microvasculature. Microvascular images were acquired via knife-edged scanning microscopy (KESM)26,2; similar microvascular data are openly available through the KESM Mouse Brain Atlas28.
2. Configuring the Laser-scanning Confocal Microscope
NOTE: While other laser scanning microscopes equipped with pulsed lasers can be used, the settings and protocol here describe the use of a laser scanning microscope (LSM) in conjunction with its software.
3. Creating a Recipe and Uploading Virtual Masks to the Microscope Software and Macro
4. Photopolymerizing a PEGDA Hydrogel
5. Fabricating Vascular-derived Microfluidic Networks via Laser-based Degradation
6. Visualizing the Microfluidic Network
To demonstrate the implementation of image-guided, laser-based hydrogel degradation to generate a 3D, vascular-derived microfluidic network, we utilized a 3D image stack of mouse brain vasculature that was acquired via knife-edged scanning microscopy (KESM)26,27. A selected 3D region of the larger microvascular dataset was converted into a series of virtual masks for image-guided microfluidic network formation, as described above. After fabrication, the resulting microfluidic network was perfused with a solution of FITC-labeled, 2,000 kDa dextran and imaged via confocal microscopy. The image stack of the in vivo vasculature that defined the network architecture (Figure 1A and C) and the fabricated microfluidic network (Figure 1B and D) were used to generate Z-projections (Figure 1A and B) and 3D renderings (Figure 1C and D). The comparison of the images demonstrates that image-guided, laser-based hydrogel degradation enables the fabrication of 3D biomimetic microfluidic networks that recapitulate the size, tortuosity, and complex architecture of in vivo vasculature. The technique is amenable to fabrication of networks containing a wide range of diameters; within Figure 1, channels ranging from 3.3 to 28.8 µm in diameter were generated. Note that the larger rectangular structure in the top left of Figure 1B and in the left corner of Figure 1D is the inlet channel to introduce flow into the network.
Figure 1: Vascular-Derived Microfluidic Network. A series of virtual masks, derived from an image stack of mouse brain vasculature (A and C), were used to fabricate a 3D biomimetic microfluidic network embedded in a PEGDA hydrogel (B and D) via image-guided, laser-based degradation. The microfluidic network was perfused with 2,000 kDa FITC-labeled dextran and imaged via confocal microscopy. Z-projections (A and B) and 3D renderings (C and D) of the two networks demonstrate the ability to generate microfluidic networks that recapitulate the density, organization, and overall architecture of in vivo vasculature. The arrow (D) marks the rectangular inlet created to introduce the dextran. The scale bar represents 50 µm. Please click here to view a larger version of this figure.
We have implemented two methods, pressure heads and syringe pumps, to initiate fluid flow in these embedded microfluidic networks. For example, a 30 by 30 µm rectangular channel was fabricated to connect two wells in a micromolded PEGDA hydrogel (Figure 2A), with fluid flow driven via a pressure head7. Generated in the left well, the pressure head induced flow through the microchannel and into the well on the right. In Figure 2A, an initial front of tetramethylrhodamine (TRITC)-labeled, 70 kDa dextran was observed moving through the channel using time-lapse microscopy. Later, in Figure 2B, a 10-µm diameter fluorescent polystyrene sphere flowed from the left well, through the channel, to the well on the right. With the duration of flow controlled by the volume of fluid present in the micromolded well at the inlet, and the flow-rate controlled by the hydrostatic gradient generated between the inlet and outlet well, pressure head-driven flow in micromolded hydrogels provides a simple method for flow induction, without the need for an external housing or a syringe pump.
Figure 2: Pressure Head-Driven Flow in a Micromolded PEGDA Hydrogel. PEGDA was micromolded to form a hydrogel containing two wells connected by an embedded microchannel. A pressure head was generated in the left well to initiate flow of TRITC-labeled, 70 kDa dextran (A1-A3) and a 10-µm polystyrene sphere (B1-B3) through a 30 by 30 µm rectangular channel from one well to the other. The scale bar represents 50 µm. Please click here to view a larger version of this figure.
Alternatively, to generate constant fluid flow within microfluidic networks, syringe pump-driven flow can be initiated by photopolymerizing the hydrogel inside of a secondary microfluidic device with inlet and outlet ports for syringe pump interfacing. In Figure 3A, a commercially available, pre-fabricated microfluidic device is shown with a 1-mm band of hydrogel photopolymerized across the width of the device7. Laser-based degradation was implemented to fabricate microfluidic channels and networks in housed hydrogels using the same protocol described here for freestanding hydrogels. Syringe pump-generated flow can be seen in Figure 3B, where a 20-µm diameter cylindrical channel was fabricated in a hydrogel housed in a microfluidic device. In this 20-µm diameter channel, individual 2-µm fluorescent polystyrene spheres are easily resolved without fluid flow (Figure 3B1), whereas when a 5 µL/s flowrate is applied, the spheres move through the field of view, as evidenced by streaking (Figure 3B2). This same approach was used to induce flow through a 2D, vascular-derived network to monitor flow of TRITC-labeled, 65 kDa dextran through the network and diffusion into the surrounding hydrogel (Figure 3C).
Figure 3: Syringe Pump-Driven Flow in PEGDA Hydrogels Polymerized in Microfluidic Housings. A commercially available, pre-fabricated microfluidic device (A) with a 17 x 3.8 x 0.53 mm (x,y,z) microchannel houses a photopolymerized 1 x 3.8 x 0.53 mm (x,y,z) PEGDA hydrogel, indicated by the black arrow. A 20-µm diameter cylindrical channel was degraded through the hydrogel, and 2-µm polystyrene spheres were pumped through the device (B). The spheres are clearly resolved without fluid flow (B1), but they appear as streaks at a flowrate of 5 µL/s (B2). In another housed hydrogel, a 2D vascular-derived network was fabricated and TRITC-labeled, 65 kDa dextran was pumped through the network (C). Time-lapse microscopy was used to monitor the fluorescent dextran as it filled the channels and diffused into the surrounding hydrogel. White arrows in (B) and (C) indicate the direction of fluid flow. The calibration bar in (C) indicates the intensity of the fluorescent dextran. The scale bars represent 20 µm in (B1) and (B2) and 50 µm in (C). Please click here to view a larger version of this figure.
Critical in overriding the standard functions of the microscope software to enable the use of virtual masks for image-guided, laser-based degradation, the microscope macro must be setup and manipulated carefully. How the microscope software interfaces with the microscope macro can sometimes be counterintuitive, and much effort was invested in determining the optimal settings in both programs to develop this method. A general understanding of basic laser-scanning confocal microscope use is recommended, especially with the "Stage" and "Focus" windows for finding and correctly positioning the hydrogel in the x, y, and z dimensions, before attempting laser-based degradation. Additionally, the fabrication of an inlet channel is critical to the protocol; suspended fluorescent species must be able to enter the microfluidic systems for successful imaging and network characterization. It is important to note that this protocol applies to a specific laser-scanning confocal microscope configured with a specific femtosecond pulsed laser, running specific versions of the microscope software and the microscope macro (see details in the List of Specific Materials/Equipment). We have discovered that newer versions of the microscope macro lack the necessary control and functionality needed for image-guided laser control. While other microscope platforms and pulsed laser sources can be used, this protocol applies specifically to this system and will need modification according to the platform, laser source, and software implemented. The underlying principles throughout this protocol still apply, however.
A potential modification to this protocol involves changing the hydrogel composition. Here, we utilized 5 wt%, 3.4 kDa PEGDA hydrogels, but laser-based degradation (for purposes aside from microfluidic network generation) has been implemented to degrade both synthetic and natural hydrogels, including PEGylated fibrinogen21,22, silk protein hydrogels23, and collagen24. Adjustment of the laser power, scan speed, spacing between Z-slices, and number of repetitions will aid in determining the optimal parameters to fabricate microfluidic networks in other hydrogel formulations.
One current limitation of the technique is the overall volume of hydrogel that can be degraded in a feasible amount of time. To create open voids or microfluidic features within the hydrogel, the laser dwell time must be at or above 8.96 µs/pixel (or a laser scan speed of 0.021 µm/µs) when using a laser fluence of 37.7 nJ/µm2. With these settings, it takes 1.4 h to degrade vessels within a 0.014 mm3 volume (as seen in Figure 1). Using a laser dwell time of 4.48 µs/pixel or below, the energy delivered is not enough for full degradation of the hydrogel formulation used here. Implementing a different hydrogel composition could overcome this limitation. The use of photolabile gels that contain light-sensitive components34-36 or hydrogels that have large multiphoton cross-sections21-24 are good options that would enable the use of less energy and would result in faster degradation. With respect to dimensional limitations, features have been fabricated up to 1.5 mm deep in the hydrogel7. The depth achievable is a function of the working distance of the objective and can be increased using ultra-long working distance objectives optimized for in vivo imaging. The smallest measured channel7 created using a 20X (NA1.0) water immersion objective had a width of 3.3 µm and depth of 8.9 µm, which is on par with the size of the smallest channels generated in Figure 1. While other labs have used lower NA objectives21,23,24, we anticipate that microfluidic networks with smaller features can be generated using higher NA objectives at the expense of a reduced working distance. Ultimately, however, the resolution of the technique is a function of the point spread function of the focused laser beam, the laser scanning properties, the amount of energy delivered by the laser, and the laser absorption properties of the material being degraded.
Furthermore, laser properties (speed, fluence, spacing between virtual masks, and number of repetitions) must be optimized based on hydrogel properties (crosslink density, macromer/monomer molecular weight, weight percent, and type of hydrogel: protein-based vs. synthetic), as these will inherently alter interactions with the laser and thus the ultimate resolution of the process. As the energy delivered is also influenced by the objective used, additional optimization is required when switching between objectives. With respect to the costs involved, access to a microscope with a pulsed laser is required, and while many different objectives can be used, those with a high NA and long working distance (for in vivo imaging) can be expensive.
Above and beyond the protocol detailed here, microfluidic networks generated using this technique can also be functionalized with cell-adhesive peptides post-channel fabrication to induce endothelial cell adhesion and lumen formation7. Additionally, the incorporation of cell-degradable peptide sequences in the bulk material9 prior to channel degradation could allow for the study of cell migration into and through the hydrogel. For continuous fluidization of the microfluidic network within the hydrogel, hydrogels can be photopolymerized in larger fluidic devices or housings, as demonstrated in Figures 2 and 37.
The generation of vascular networks via vasculogenic or angiogenic self-assembly8-12 provides a straightforward approach to induce vascularization throughout a relatively large hydrogel volume. While this approach results in perfusable fluidic networks, it is difficult to directly control the size, tortuosity, density, and overall network architecture. Due to this limitation, the flow profile and shear rates in the vasculature may differ between experiments. Alternatively, microfabrication techniques13-16 allow for direct control over network architecture but are often limited by their inability to generate small, capillary-sized channels or the fabrication of dense networks that mimic in vivo vascular architecture. While the laser-based hydrogel degradation technique outlined here has been newly repurposed for microfluidic generation, it simultaneously overcomes both the architectural control and size-based limitations of existing microfabrication methods by enabling the creation of 3D biomimetic microfluidic networks that recapitulate the density, tortuosity, size range, and overall architecture of in vivo vasculature. Furthermore, multiple fluidic networks can be generated in a single hydrogel, allowing the study of inter-network transport7. For tissue engineering applications that strive to more closely replicate in vivo transport processes in vitro, the highly resolved hydrogel-embedded microfluidic networks outlined here are well suited. We anticipate that this protocol will be useful in developing tissue constructs that more accurately mimic in vivo transport for use as drug screening devices and in vitro disease models.
The authors have nothing to disclose.
The authors thank Dr. Jeff Caplan and Mr. Michael Moore at the Delaware Biotechnology Institute Bio-Imaging Center for their support with confocal microscopy. Access to microscopy equipment was supported by the National Institutes of Health (NIH) shared instrumentation grants (S10 RR0272773 and S10 OD016361) and the State of Delaware Federal Research and Development Grant Program (16A00471). This research was supported by grants from the Institutional Development Award (IDeA) from the NIH National Institute of General Medical Sciences (P20GM103446), the American Cancer Society (14-251-07-IRG), the University of Delaware Research Foundation (14A00778), the Cancer Prevention and Research Institute of Texas (CPRIT) (RR140013), and the NIH National Library of Medicine (4 R00 LM011390-02).
Name | Company | Catalog Number | Comments |
MATLAB | Mathworks | R2015a | named "programming software" in protocol; refer to source 9 for details on algorithm |
FIJI (Fiji is Just Image J) | NIH | version 1.51a | named "image processing software" in protocol |
LSM 780 Confocal Microscope | Zeiss | named "laser-scanning confocal microscope" in protocol; for laser-based hydrogel degradation | |
Zen 2010B SP1 | Zeiss | release version 6.0 | named "microscope software" in protocol; for use on Zeiss LSM-780 |
Multitime, 2010 | Zeiss | v16.0 | named "microscope macro" in protocol; for use on Zeiss LSM-780 (in conjunction with Zen) |
Objective W Plan-Apochromat 20X/1.0 DIC D=0.17 M27 75 mm | Zeiss | 421452-9880-000 | for use on Zeiss LSM-780 |
Chameleon Vision II Modelocked Ti:S Laser | Coherent | named "high-powered pulsed laser" in protocol | |
Sodium chloride | Sigma-Aldrich | S5886-1KG | |
HEPES | Sigma-Aldrich | H3375-250G | |
Triethanolamine (TEOA) | Sigma-Aldrich | 90279-100ML | flammable; skin and eye irritant; work with in a fume hood |
Sodium hydroxide | Sigma-Aldrich | S5881-500G | |
150 mL Vacuum Filtration Cups with 0.2 µm PES Membrane | VWR | 10040-460 | |
PEGDA | synthesized in house | refer to source 33 for synthesis methods; store under argon | |
Eosin Y disodium salt | Sigma-Aldrich | E6003-25G | |
1-vinyl-2-pyrrolidinone (NVP) | Sigma-Aldrich | V3409-5G | store under argon; carcinogenic; work with in a fume hood |
3M Double Coated Tape, 9500PC, 6.0 mil | Thomas Goldkamp | 37728 | |
Flexmark 90 PFW Liner | FLEXcon | FLX000620 | backing for handling of double coated tape |
Model SC Plotter (adhesive cutter) | USCutter | SC631E | used to cut adhesive in ring shapes to connect coverslips to petri dishes |
60 mm Petri Dish with 20 mm Hole | MatTek Corporation | P60-20-F-NON | |
High Intensity Illuminator (white light source) | Fiber-Lite | 4715MS-12WB10 | |
Power Meter | Newport | 1916-R | detect power at 524 nm when using white light source |
Slim Profile Wand Detector | Newport | 918D-ST | for use with power meter |
Sylgard 184 Silicone Elastomer Kit | Dow Corning | 3097358-1004 | used to make PDMS molds; refer to source 7 for methods |
TMPSA-Functionalized #1.5 Coverslips, 40 mm Round | synthesized in house | refer to source 7 for methods | |
Dextran, Fluorescein, 2,000,000 MW, Anionic, Lysine Fixable | Life Technologies | D7137 | can use alternative tagged dextrans; 2,000 kDa does not diffuse readily into a 5% 3.4 kDa PEGDA hydrogel |
1 mL Syringe, Luer-Lok | BD | 309628 | |
Acrodisc Syring Filter, 0.2 µm Supor Membrane, Low Protein Binding | Pall | PN 4602 | |
sticky-Slide VI0.4 | Ibidi | 80601 | microfluidic devices that can be used to house hydrogels |
请求许可使用此 JoVE 文章的文本或图形
请求许可This article has been published
Video Coming Soon
版权所属 © 2025 MyJoVE 公司版权所有,本公司不涉及任何医疗业务和医疗服务。