Microfluidics, a science of precise fluid handling within the network of channels, has shown great promise in manipulating cells and particles. Microfluidics has attracted significant attention in biology and medical research due to their unique features including low price, high throughput, high customisability, and energy-efficiently compared to other technologies (Wang and Dandy 2017; Figeys and Pinto 2000). For example, micromixers have been used in chemicals synthesis and microparticle coating (Vasilescu et al. 2020). Multiple microfluidic devices, especially spiral microfluidic channels, have been demonstrated to separate or concentrate cells based on particle sizes (Xiang et al. 2019; Nivedita et al. 2017). To date, microfluidic devices are widely used in laboratories but one of the major limitations for applying microfluidics in the industry is its customisability (Yi-Qiang et al. 2018). For instance, in the stem cell bioprocessing industry, each company has its own manufacturing protocol. The lack of standard procedure is one of the reasons for the low yield of cell products and the inconsistent clinical outcome of stem cell therapy (Jossen et al. 2018; Schnitzler et al. 2016). Although microfluidic devices have been applied in the stem cell bioprocessing industry as cell separator and concentrator in a labour-free, low-cost, and high-throughput manner (Moloudi et al. 2018, 2019), the lack of modularity and integrity makes them hard to be applied in the bioprocessing industry. Microfluidic devices are normally made from polydimethylsiloxane (PDMS) by soft lithography. Compiling these single microfluidic devices together to increase the throughput requires multiple external tubing and diverters to meet the industrial need, and testing and modifying them to meet the demand requires a huge amount of time and effort. 3D printing technology can be a good solution for this inadequacy. In recent years, the advances in 3D printing technologies have made it increasingly appealing for producing microfluidic devices (Bhattacharjee et al. 2016). The resolution of 3D printing allows direct construction of microfluidic channels with micrometre-level features, and the study and treatment of 3D printed resin enable the production of soft-lithography mould in a few hours (Vasilescu et al. 2020; Razavi Bazaz et al. 2019). Although 3D printing technologies are not the solution for large-scale manufacturing of microfluidic devices, their potential to modify changes and fabricate microfluidic devices in a few hours is unique and valuable for the industry. This feature hugely decreases the cost and time needed for rapid prototyping and building integrated microfluidic systems.
In the stem cell industry, microcarriers (MC)-based culture systems are a promising candidate for maximising cell manufacturing on a large scale. MCs facilitate massive cell expansion at a lower cost and allow control of cell culture parameters in a homogenous condition to produce consistent quality cell products at a large scale (Fardjahromi et al. 2020; Chen et al. 2020). Despite the enormous advantages of microcarrier-based technologies in maximising cell production, harvesting cells from MCs still faces challenges with high product quality and yield (Chen et al. 2013). The common method for harvesting is detaching cells with digestive enzymes and separating them from MCs using membrane-based filtration or centrifugation (Chilima et al. 2018; Tavassoli et al. 2018). Membrane-based filtration separates the cells with a physical porous filter. Clogging filters is the major limitation of this method (Schnitzler et al. 2016; Zydney 2016). In addition, membrane fouling has been shown to cause cell death, cell fate changes, and reduce the therapeutic potential of harvested cells (Chilima et al. 2018; Zydney 2016; Rodrigues et al. 2018). Centrifugation-based methods, particularly continuous flow centrifugation, are another alternative method for separating cells from MCs (Schnitzler et al. 2016). The advantage of this method is that it washes cells during separation, but the centrifugation process is time-consuming, potentially causing cell damage (Joseph et al. 2016). In addition, the continuous washing and centrifuging process cost more reagents and disposables (Serra et al. 2018). Hence, a continuous, clogging-free, highly efficient, and low-cost harvesting method is severely lacking in this area.
Herein, in this paper we report an integrated 3D printed modular microfluidic system containing two micromixers, one spiral separator, and one zig-zag concentrator. We used this system to detach and separate mesenchymal stem cells (MSCs) from MCs and eventually concentrate them in a smaller volume for downstream processing. At first, each module was characterised using cells and microbeads in different volume fractions and flow rates to obtain the optimum condition for the MSC harvesting. Then, the viability, proliferation, and therapeutic properties of MSCs harvested with our proposed integrated system were compared with the manual method, i.e., Millipore filtration. The results indicate that the developed microfluidic device is a promising candidate for automated MSCs harvesting and concentrating from MCs. In the end, we demonstrated that the system could be multiplexed to process samples with higher throughput.
Figure 1A depicts the general concept of unidirectional imaging. To create a unidirectional imager using reciprocal structured materials that are linear and isotropic, we optimized the structure of phase-only diffractive layers (i.e., L1, L2, …, L5), as illustrated in Fig. 1 (B and C). In our design, all the diffractive layers share the same number of diffractive phase features (200 by 200), where each dielectric feature has a lateral size of ~λ/2 and a trainable/learnable thickness providing a phase modulation range of 0 to 2π. The diffractive layers are connected to each other and the input/output FOVs through free space (air), resulting in a compact system with a total length of 80λ (see Fig. 2A). The thickness profiles of these diffractive layers were iteratively updated in a data-driven fashion using 55,000 distinct images of the MNIST handwritten digits (see Materials and Methods). A custom loss function is used to simultaneously achieve the following three objectives: (i) minimize the structural differences between the forward output images (A → B) and the ground truth images based on the normalized mean square error (MSE), (ii) maximize the output diffraction efficiency (overall transmission) in the forward path, A → B, and (iii) minimize the output diffraction efficiency in the backward path, B → A. More information about the architecture of the diffractive unidirectional imager, loss functions, and other training-related implementation details can be found in Materials and Methods. After the completion of the training, the phase modulation coefficients of the resulting diffractive layers are shown in Fig. 2C. Upon closer inspection, it can be found that the phase patterns of these diffractive layers have stronger modulation in their central regions, while the edge regions appear relatively smooth, with weaker phase modulation. This behavior can be attributed to the size difference between the smaller input/output FOVs and the relatively larger diffractive layers, which causes the edge regions of the diffractive layers to receive weaker waves from the input, as a result of which their optimization remains suboptimal.For the fabrication of microfluidic devices using additive manufacturing, different techniques exist. Fused Deposition Modelling (FDM), Stereolithography (SLA), Digital Light Processing (DLP), two-photon polymerisation (2PP), Multijet, and wax printing are all capable of fabricating microfluidic devices. For the creation of complex microfluidic devices, however, DLP and wax printing methods show more promise in this regard. The fabrication process of these two methods is illustrated in Additional file 1: Fig. S1. The wax 3D printing method is a multi-step process, and the printed microfluidics are inherently fragile and prone to fault and error. As an alternative, DLP method has been selected for the current study because of its accuracy, precision, fast turn-around time, and the ability to fabricate robust complex microfluidic channels (Chai et al. 2021; Ding et al. 2022). Design selection consideration is introduced in detail in Additional file 1: Section S1.
The micromixers were designed in Solidworks 2018 × 64 edition (SolidWorks Corporation, USA) and fabricated with a high-resolution DLP resin printer (MiiCraft II, Hsinchu, Taiwan), with the layer thickness of 50 µm. BV-007 resin was used, which is an acrylate-based resin containing 80–95% acrylate components and 10–15% photoinitiator and additives (Razavi Bazaz et al. 2020a). After printing, the micromixers were carefully removed from the build plate, washed with isopropyl alcohol, and dried by air nozzle. This process was repeated three times to prevent uncured resin from clogging the channels. Then, the micromixers were cured by 450 nm UV light in a UV-curing chamber. The design and dimension of the micromixer are shown in Additional file 1: Fig. S2.
The spiral chip and zig-zag channel were produced as previously described (Razavi Bazaz et al. 2020a; Ding et al. 2022). Briefly, the devices were designed by SolidWorks and printed by the MiiCraft II 3D printer with a 10-µm layer thickness. Then the devices were rinsed with IPA and dried with an air nozzle three times. These devices were further post-processed by UV light in a UV-curing chamber and then bound to a PMMA sheet with a double-sided tape (ARclear®, Adhesive Research). Next, Tygon tubes (Tygon tubing, inner diameter: 0.50″, outer diameter: 0.90″) were used as connections of inlets and outlets to connect each part. Finally, the printed parts were then connected in series, as shown in Fig. 1.
FL is affected by the density of fluid ρ , the hydraulic diameter Dh (which can be calculated by 4A/P , A= channel cross-section and P= perimeter of the channel), the maximum fluid velocity Umax which is approximated as 2×Uf (Uf is the average velocity), CL which is a constant named dimensionless lift coefficient number and is dependent on the channel Reynolds number (Re=ρUfDh/μ,μ is the viscosity of the liquid) and the diameter of particles a . FL consists of two forces: shear-gradient and wall-induced lift force. Shear gradient lift force pushes the particles towards the wall due to the velocity difference between the middle area and the side area of the channel. When the particles move close to the wall, the wall lift force pushes the particles away. The balancing point of inertial equilibrium position contributed to the lift force is where these two forces balance each other (Razavi Bazaz et al. 2020c).
In a curved channel, the channel’s curvature causes the inner wall (IW) fluid to flow faster than the outer wall (OW) due to the shorter distance travelled. This transverse fluid flow creates another force that affects the focusing position of the particles, which is the Dean drag force (FD ). FD is defined in Eq. (2), where De=ReDh/2R−−−−−−√ is the Dean number, and R is the radius of curvature; it describes the strength of FD . According to Eqs. (1) and (2), the forces applied to the particles are proportional to the particle size (FL∝a4,FD∝a ). Therefore, different particle sizes have different focusing positions across the channel cross-section, and they can be collected through separate outlets (Mihandoust et al. 2020; Ozbey et al. 2019).
In a normal spiral channel, the particles inside the channel need to follow the rules of Cr>0.07 , where Cr=a/Dh to be affected by the inertial forces inside the channel. In a scaled-up microfluidic channel, the increase in Dh results in a reduction of absolute flow velocity compared with a normal microfluidic channel. Therefore, the secondary forces applied to the microparticles were weaker, and the Cr value in the scaled-up microfluidic channel was much higher than the microfluidic channels (Cr>0.17) (Moloudi et al. 2019; Carlo 2009). Another factor that affects particle focusing is channel rigidness. There is no swelling or channel inflation in rigid channels compared to traditional PDMS chips; thus, the scaled-up device should have theoretically a lower Cr . Also, larger particles are more likely to be affected by mass and gravity since they are not neutrally buoyant (Moloudi et al. 2019), adding another variable despite flow velocity; the variable sizes of particles would also increase the difficulty in the channel design. When MCs and cells pass through the channels, focusing MCs near the IW causes the MSCs to be dispersed in the channel due to the large size difference between MCs and cells (MCs size are 150–220 µm, and MSCs are 15–20 µm). However, since large particles occupy the inner channel, the particle–particle interaction can stop some of the MSCs from going out through the inner outlet (Moloudi et al. 2018). Considering all these factors, in this study, we have designed the channel with a trapezoidal cross-section and heights of 550 µm and 620 µm, and a width of 1100 µm. This spiral chip has 6 loops and a slightly slanted enlarged inlet size to prevent clogging of MCs at the beginning of the channel (Fig. 1).
Working principle of the microconcentrator module
The zig-zag channel relies on inertial, and Dean drag forces to focus the MSCs at the centre of the channel. When Reynolds number of the channel falls in the intermediate range 1 < Re < 100, the fluid flow is laminar, between Stokes and turbulent flow regimes. Therefore, inertial forces focus the randomly dispersed particles toward certain equilibrium positions after a sufficiently long channel length. As explained above, shear-gradient and wall-induced lift force are the main forces affecting the particle focusing in straight channels, and they both contribute to the overall inertial lift force FL . Straight channel relies on the difference in particle sizes to focus the particles at different positions (FL∝a4 ). In zig-zag channels, Dean force FD is introduced differently compared to the spiral microfluidic channel. The interchanging channel direction creates a mismatch of fluid flow velocity in an alternating pattern and introduces Dean force, accelerating the focusing of particles inside the channel. A zig-zag channel has three focusing modes across different flow rates. When FL<FD , the particles focus at the side of the channels. When FL>FD , the particles were focused in the middle of the channel due to due to the strong FL . When FL∼FD , particles are in the transition mode. For the aim of this study, MSCs need to satisfy the condition of FL>FD. One primary advantage of the zig-zag channel is its operating ranges of flow rates, i.e., it can focus particles at the centre over a wide range of flow rates. After careful evaluations, the zig-zag channel with a cross-section of 360 µm × 60 µm, 60° angle has been proposed to concentrate cells after the spiral microfluidic device. To avoid clogging of zig-zag channels caused by the remaining MCs in the target outlet, some obstacles were planted at the target outlet of the spiral to ensure no MCs could enter the zig-zag channel.
Pressure balance of microfluidic system
ombining multiple microfluidic devices in one system requires careful arrangement to balance the fluid flow and pressure change. An electronic circuit was used as an analogy for our system to understand better the fluid behaviour in the system (Additional file 1: Fig. S5). These microfluidic devices resemble the resistors that reduce the pressure input from the pumps, similar to the voltage drop in an electronic circuit (Oh et al. 2012). Keeping the flow rate and pressure stable according to the following equation is the key point of the successful operation of this system:
The setup and components of each layer. The multiplexing system consists of five layers: a top guide layer to distribute the liquid evenly into the micromixers; a micromixers layer that detaches MSCs from MCs; a spiral layer separating MSCs and MCs; a middle guide layer that provided a base for spiral and zig-zag channels and a zig-zag channel and pressure-damping channel layer that concentrate the MSCs. The cells and MCs are left from the outlets, respectively
The merits of microfluidic devices, such as low-cost, high throughput, labour-free, customisability, and energy efficiency, meet the need of the bioprocessing industry. Recently, multiple attempts have been made to bring microfluidic devices to solve the challenges associated with bioprocessing. However, microfluidic devices are still facing difficulty in accommodating and integrating themselves in the bioprocessing industry. In this manner, 3D printing technology can be used as a bridge to connect microfluidic devices and the bioprocessing industry. The one-step fabrication method of 3D printing technology (printing and washing) allowed us to test 16 zig-zag channels with different dimensions, six different inertial concentrator designs and three micromixers.
In our proposed microfluidic system, cells detachment, separation, and concentration–time are short, 5 min for incubation and 20 s for passing through the system with a total length of < 5 cm. This short processing time could effectively minimise the negative impact of enzymatic treatment on the cell membrane and enhance attachment and growth of harvested cells (Fig. 4), indicating well-preserved cell membrane integrity and functionality. Although the damages caused by enzymatic treatment can be reversible (Tsuji et al. 2017), it takes a few passages for the cells to recover and is not feasible for clinical applications.
The results of cell viability and MTS assays indicate that the viability and proliferation rate of the microfluidic-harvested cells are the same as the control. This is in agreement with the results reported by Nienow et al. (2016), who suggested that agitating cell–MCs suspension facilitates cell detachment while not compromising cells’ properties and viability. As expected, the cells maintain their differentiation potential trilineage (Fig. 5D), their size, spindle morphology (Fig. 4D), and surface markers expression (Fig. 5A). The size and morphology of the cells are important indicators of the cell potencies and secretion profile since different sizes MSCs were shown to have a different expression levels of differentiation promotor/inhibitor genes and different secretion levels of therapeutic factors (Yin et al. 2018, 2020; Lee et al. 2014).
Our experiment showed that the anti-inflammatory surface proteins expression level of the harvested cells during the subsequent subculture had no difference compared to the control group (Fig. 5C). This indicates that the cells preserved their therapeutic properties after the process, and the microfluidic system is safe for the industrial production of stem cells for clinical purposes. The high secretion level of SDF-1α and TIMP-1 proteins suggest strong potential in therapeutic applications. However, these results are not enough to draw the conclusion of whether this harvesting method alters cytokine secretion levels of the MSCs. Previous works show that the topography of the culture system (Leuning et al. 2018) and shifting from 2 to 3D culture (Russell et al. 2018) influenced the cytokine expression level of cells. Ng and Wang (2021) showed that even growing cells on different types of microcarriers influence the secretion profile. Therefore, the secretion profile changes caused by our 3D printed modular harvesting system require further characterisation. These results showed that the cells harvested with our 3D printed modular microfluidic system preserved all the cell properties with no cytotoxic effect, and damage caused by the material, or the hydrodynamic forces was observed.
With the aid of 3D printed technologies (Additional file 1: Section S6), our microfluidics system has multiple advantages over the current laboratory and industrial adherent cell harvesting methods. This microfluidic system requires only two pumps to trigger, and no complicated tubing and valve is needed. This system is cGMP compatible and the design of the system ensures negligible risk of contamination (Tamura et al. 2012; Caruso et al. 2014); The device can be operated in a continuous manner, which is particularly suitable for industrial-scale application (Castilho and Medronho 2002); The system can be used as a single unit system for lab-scale production or easily scaled-up by paralleling the devices together for large volume processing; Other microfluidic devices can also be integrated to perform other functions such as quality control of cellular products (Ding et al. 2021). With the small device footprint, reaching 2 L/min flow rate requires 100 chips, and the total volume would be only 1 m3. It will take 25 min to harvest 50 L MCs. The small footprint allows easy integration into any current-available system, 3D printing technologies allow easy and rapid prototyping of customised fluidic interconnects at a low cost to aid the industrial integration (Ho et al. 2015). On the other hand, our system shows clear advantages over TFF (Schnitzler et al. 2016) with its clogging-free operation manner. This important feature reduces the production cost since the device does not need frequent membrane replacement and maintenance and can be single used due to the low-cost. Also, the low flow rate in each individual unit of our device ensures the cells are not suffering from shear stress like TFF, resulting in cell damage (Cunha et al. 2015). Moreover, this system can be integrated into other enzymatic detachment methods or even enzyme-free cell detachment procedures as well. In recent years, frontier research about smart MCs shows that thermosensitive MCs and soluble MCs have great potential in future cell culture (Tamura et al. 2012; Kalra et al. 2019; Hanga et al. 2021). Proceeding these MCs through our microfluidic gadget may increase exposure to light and heat while benefiting from the agitation of fluid flow. In our multiplexing design, we showcased the first multiplexed modular microfluidic system. The system is built in a nonlinear and modular manner which has not been showcased before. This rapid, low-cost prototyping is not possible without 3D printing technology.