The authors acknowledge the members of the Centre in Regenerative Medicine at QUT, in particular, Antonia Horst and Pawel Mieszczanek for their helpful suggestions and feedback. This work was supported by the QUT&#8217;s Postgraduate Research Award for SE, and by the Australian Research Council (ARC) under grant agreement IC160100026 (ARC Industrial Transformation Training Centre in Additive Biomanufacturing). NB was supported by a National Health and Medical Research Council (NHMRC) Peter Doherty Early Career Research Fellowship (APP1091734).

CM and DWH are founders and shareholders of Gelomics Pty Ltd. CM is also the Director of Gelomics Pty Ltd. The authors declare no conflict of interests relevant to the subject of this article. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the article apart from those disclosed.

Pipetting of viscous materials, especially hydrogels for biomedical applications19,20,21,33,47, are routine tasks in many research labs to prepare a user-defined concentration or a dilution series with varying concentrations. Although it is repetitive and the execution is rather simple, it is mostly performed manually with low sample throughput18. This tutorial is introducing the operation of an open source workstation, which has been specifically designed for viscous materials, to enable automated mixing of viscous materials for reproducible generation of desired concentrations. This workstation is optimized for pipetting of hydrogels to enable automated and highly reliable handling by the integration of temperature docks for thermoresponsive materials, positive displacement pipettes for viscous materials, and an optional tip touch dock to remove excess material from the tip. The pipetting module has been specifically optimized to enable the processing of viscous material in a standardized and automated manner. In comparison to air cushion pipettes (Figure 5a), positive displacement pipettes (Figure 5b) dispense viscous materials without leaving residual material left in the tip, resulting in accurate aspirating and dispensing volumes. The optional tip touch dock removes excess sample material from the tip (Figure 5c,d), which is useful for gluey materials (e.g., 4% (w/v)&#160;alginate).
The protocol designer application has been specifically programmed for hydrogels and allows the dilution of up to four reagents with different concentrations and up to two diluents. The risk of errors in the calculation of final dilutions is prevented in this application, as users only choose the desired concentration or the serial dilution steps. Required aspirating and dispensing volumes are calculated automatically, saved in a separate documentation text file, and then filled into the protocol script. This protocol design application gives the user full control of all experimental parameters (e.g., pipetting speed) and ensures internal documentation of the important parameters. The protocol design app takes the filling level of the reservoir (e.g., well) into account and varies the aspirating/dispensing height to prevent unnecessary dipping into the viscous materials. This integrated feature avoids material accumulation on the outer wall of the tip, and, thereby, ensures reliable aspirating and dispensing tasks throughout the protocol. Although the protocol designer application has been developed for hydrogel dilution steps, it can be also used for dilution of nonviscous liquids, such as Orange G dyes. The protocol designer application, which is accessible via the repository under &#8216;/examples/publication-JoVE&#8217;, is the version which is explained in the protocol section and highlighted in the video. This version will not be updated. However, an updated version of the protocol designer application is available via the main repository page. The calibration terminal was initially developed by Sanderson48&#160;and has been optimized for the calibration of positive displacement pipettes.
As described in the protocol section 4, pipettes as well as containers must be calibrated initially. This calibration process is crucial to define and save the positions which are then used to calculate the movement increments. Therefore, successful protocol execution relies on well-defined calibration positions, as wrong calibration points could result in crashing of the tip into a container. Since the plunger positions of the pipettes must be calibrated manually, pipetting accuracy and precision depend greatly on the performed calibration. These calibration procedures depend highly on the user experience with the pipetting module, and, therefore, training with experienced staff is recommended at the beginning to ensure proper calibration procedures. In addition to the manual calibration on the pipetting module, the pipette itself must be calibrated to ensure accurate pipetting. It is recommended to calibrate the pipettes at least every 12 months to meet to acceptance criteria as specified in ISO 8655. To evaluate the pipette calibration internally, validation and verification are available as described by Stangegaard et al.16.
For the generation of a reliable data set, it is crucial to start with reagents of high quality. This is especially important for hydrogel processing tasks, as batch-to-batch variations might impact the generated results within this protocol. In addition to batch-to-batch variations, subtle changes in the preparation of small volumes may also contribute to property differences. To prevent this, preparation of larger volumes is recommended, which can be used for the entire experiments.
The validation and verification procedures rely on the usage of a dye to identify reliable mixtures. The presented protocol describes the application of Orange G, but the general protocol and analysis workflow can be also adapted to fluorescent dyes49,50. The usage of Orange G reduces the technical requirements of the spectrophotometer and eliminates precautions taken to prevent bleaching of the fluorescent dyes after exposure to light. Issues in the dissolving behavior or cluster formation of the dye have not been observed with the presented materials during experiments but might appear with other materials. Potential cluster formation and, therefore, the interaction between dye and material could be easily detected with a microscope.
The procedures and techniques presented in this tutorial add automation capability to current workflows for viscous materials to achieve highly reliable tasks with minimal human labor. The provided troubleshooting table (Table 2) includes identified issues and presents possible reasons as well as solutions to solve the problems. The presented workstation has been successfully applied to natural (gelatin, gellan gum, matrigel) and synthetic (e.g., poly(ethylene glycol) [PEG], Pluronic F127, Lutrol F127) polymeric materials for automated pipetting tasks. In particular, the combination of an open source workstation and an open source protocol design application designed for viscous materials will be very useful for researchers working in the fields of biomedical engineering, material science, and microbiology.

Reproducibility and replicability are of paramount importance in scientific work1,2,3,4. However, recent evidence has highlighted significant challenges in repeating high-impact biomedical studies in fundamental science as well as translational research4,5,6,7. Factors contributing to irreproducible results are complex and manifold, such as poor or biased study design6,8, insufficient statistical power3,9, missing compliance with reporting standards7,10,11, pressure to publish6, or unavailable methods or software code6,9. Amongst them, subtle changes in the protocol and &#65279;human errors in the execution of experiments have been identified as further elements accounting for irreproducibility4. For instance, manual pipetting tasks introduce intra- and inter-individual imprecision12,13 and increase the probability of human errors14. While commercial liquid handling robots are able to overcome these drawbacks and have demonstrated increased reliability for liquids15,16,17, automated handling of materials with significant viscous properties is still challenging.
Commercial liquid handling robots commonly use air cushion pipettes, also known as air piston or air displacement pipettes. The reagent and the piston are separated by an air cushion which shrinks during dispensing steps and expands during aspirating steps. Using air cushion pipettes, viscous materials &#8216;flow&#8217; only slowly into and out of the tip, and early withdrawal of the pipette from the reservoir may result in the aspiration of air bubbles. During dispensing tasks, the viscous material leaves a film on the inner tip wall which &#8216;flows&#8217; only slowly or not at all when being forced by air. To overcome these issues, positive displacement pipettes were introduced commercially to actively extrude the viscous material out of the tip using a solid piston. Although these positive displacement pipettes enable accurate and reliable handling of viscous materials, automated solutions with positive displacement pipettes are still too expensive for academic laboratory settings, and, therefore, most workflows with viscous materials rely solely on manual pipetting tasks18.
In general, viscosity is defined as the resistance of a fluid to flow, and viscous materials are further being defined as materials with a greater viscosity of water (0.89 mPa&#183;s s at 25 &#176;C). In the field of biomedical applications, experimental setups often contain multiple materials with a greater viscosity than water, such as dimethyl sulfoxide (DMSO; 1.99 mPa&#183;s at 25 &#176;C), glycerol (208.1 mPa&#183;s at 25 &#176;C for 90% glycerol [v/v]), Triton X-100 (240 mPa&#183;s at 25 &#176;C), and water-swollen polymers, referred to as hydrogels19,20. Hydrogels are hydrophilic polymer networks arranged in a physical or/and chemical mode used for various applications, including cell encapsulation, drug delivery, and soft actuators19,20,21,22. The viscosity of hydrogels depends on the polymer concentration and molecular weight19. Routinely used hydrogels for biomedical applications exhibit viscosity values between 1 and 1000 mPa&#183;s, while specific hydrogel systems have been reported with values of up to 6 x 107 mPa&#183;s19,23,24. However, viscosity measurements of hydrogels are not standardized in terms of measurement protocol and sample preparation, and, therefore, viscosity values between different studies are difficult to compare.
Since commercially available automated solutions specifically designed for hydrogels are either missing or too expensive, current workflows for hydrogel depend on manual handling18. To understand the limitations of the current manual-based workflow for pipetting of hydrogels, it is important to comprehend essential handling tasks18. For example, once a novel hydrogel material has been synthetized, a desired concentration or a dilution series with varying concentrations is generated to identify reliable synthesis protocols and crosslinking characteristics with subsequent analysis of the mechanical properties25,26,27,28. In general, a stock solution is prepared or purchased, and subsequently mixed with a diluent and/or other reagents to obtain a mixture. The mixing tasks are mostly not performed directly in a well plate (or any output format), and are rather performed in a separate reaction tube, which is commonly referred to as master mix. During these preparation tasks, various aspirating and dispensing steps are required to transfer the viscous material(s), mix the reagents, and transfer the mixture to an output format (e.g., a 96 well plate). These tasks require a high amount of human labor18, long experimental hours, and increase the probability of human errors which could potentially manifest as inaccurate results. Moreover, manual handling prevents efficient preparation of high sample numbers to screen various parameter combinations for detailed characterization. The manual processing also impedes the usage of hydrogels for high-throughput screening applications, such as the identification of promising compounds during drug development. The current manual-based preparation steps are not feasible to screen drug libraries consisting of thousands of drugs. For these reasons, automated solutions are required to provide an efficient development process and enable the successful translation of hydrogels for drug screening applications.
To move from manual-based workflows to automated processes, we have optimized a commercial open source pipetting robot for the handling of viscous materials by the integration of temperature docks for thermoresponsive materials, the usage of off-the-shelf positive displacement pipettes using capillary piston tips, and an optional tip touch dock for pipette tip cleaning. This pipetting robot has been further integrated as a pipetting module into a newly developed open source workstation, which consists of ready-to-install and customizable modules18,29. Detailed assembly instructions for the developed workstation including hardware and software files are freely accessible from the GitHub (https://github.com/SebastianEggert/OpenWorkstation) and the Zenodo repository (https://doi.org/10.5281/zenodo.3612757). In addition to the hardware development, an open source protocol design application has been programmed and released to guide the user through the parameter selection process and generate a ready-to-use protocol code (https://github.com/SebastianEggert/ProtocolDesignApp). This code runs on the commercial open source pipetting robot as well as on the developed open source workstation.
Herein, a comprehensive tutorial is provided on the operation of the open source workstation to automate mixing tasks for viscous materials (Figure 1). The tutorial-specific protocol steps can be carried out with the developed open source workstation as well as the commercial open source pipetting robot. Supported by an in-house developed open source protocol design application, automated mixing and preparation of required concentrations for glycerol, gelatin methacryloyl (GelMA) and alginate is demonstrated. Glycerol has been selected in this tutorial, since it is well characterized30,31, it is inexpensive and readily available, and, therefore, it is commonly used as viscous reference material for automated pipetting tasks. As examples for hydrogels used in biomedical applications, GelMA and alginate hydrogel precursor solutions have been applied for automated mixing experiments. GelMA presents one of the most commonly used hydrogels for cell encapsulation studies32,33, and alginate was selected in this study to demonstrate the ability to manufacture double network hydrogels34,35. Using Orange G as a dye, a fast and inexpensive procedure was implemented to validate and verify the mixing results with a spectrophotometer16.
A commercial open source pipetting robot has been integrated as a pipetting module into the developed open source workstation (Figure 2a), and therefore, the name &#8216;pipetting module&#8217; is further used to describe the pipetting robot. A detailed description of the installed hardware is beyond the scope of this protocol and is available via the provided repositories which also include step-by-step instructions for the general assembly of the open source platform. The pipetting module can be equipped with two pipettes (single- or 8-channel pipette) which are installed on axis A (right) and axis B (left) (Figure 2b). The pipetting module offers a 10-deck capacity according to American National Standards Institute/Society for Laboratory Automation and Screening (ANSI/SLAS) standards, and the following location positions are defined on the deck: A1, A2, B1, B2, C1, C2, D1, D2, E1, E2 (Figure 2c). To initiate photo-induced polymerization of hydrogel solutions, a separate crosslinker module is required and has been added to the workstation. The crosslinker module is equipped with LEDs with a wavelength of 400 nm and, therefore, substances that excite at a visible light wavelength can be used with the current systems, such as lithium phenyl-2,4,6 trimethylbenzoylphosphinate (LAP)36,37. The intensity (in mW/cm2) of the LEDs can be addressed by the user in the protocol design application to study the crosslinking behavior38. The workstation includes also a storage module to enable increased throughput studies; however, this module is not used within this study and, therefore, not further described. In general, it is recommended to operate the pipetting module in a biological safety cabinet to avoid sample contamination. The main power circuit to operate the pipetting module is a 12 V circuit, which is considered as a low-voltage application in most countries. All electrical components are based in a dedicated control box preventing users from coming into contact with the source of an electrical hazard.
By following these standardized mixing protocols, researchers are able to achieve reliable mixtures for viscous as well as non-viscous materials in an automated fashion. The open source approach allows users to optimize mixing sequences and share newly developed protocols with the community. Ultimately, this approach will facilitate the screening of multiple parameter combinations to investigate the interdependencies between different factors and, thereby, accelerate the reliable application and development of viscous materials for biomedical applications.

<table><tbody><tr><td>15 reaction tubes</td><td>Fisher Scientific, Inc. (USA)</td><td>14-959-53A</td><td></td></tr><tr><td>5 mL tubes</td><td>Pacific Laboratory Products Australia Pty. Ltd. (Australia)</td><td>SCT-5ML</td><td>size depends on experimentl protocol; also Eppies (0.5, 1, 1.5 mL) or Falcon tubes (15, 50mL) can be used; product is manufactured by Axygen, Inc. https://www.pacificlab.com.au/shop/tubes-plastic/sct-5ml-tubewith-screwcap-blue-unassembled-5ml-self-standing/1/name</td></tr><tr><td>50 mL reaction tubes</td><td>Fisher Scientific, Inc. (USA)</td><td>14-432-22</td><td></td></tr><tr><td>70% w/w Ethanol</td><td>LabChem, Inc. (USA)</td><td>aja726-5Lpl</td><td></td></tr><tr><td>96-well plate</td><td>Thermo Fisher Scientific, Inc. (USA)</td><td></td><td>https://www.thermofisher.com/order/catalog/product/168055</td></tr><tr><td>Alginate</td><td>NovaMatrix</td><td>4200001</td><td>https://www.novamatrix.biz/store/pronova-up-lvg/</td></tr><tr><td>Demineralized or ultrapure (MilliQ) water</td><td></td><td></td><td></td></tr><tr><td>Gelatin methacryloyl (GelMA)</td><td>Synthetized in-house</td><td></td><td>detailed protocol (incl materials and references) is available in Loessner et al. (2016), Nature Protocols. https://www.nature.com/articles/nprot.2016.037</td></tr><tr><td>Lithium phenyl-2,4,6-trimethylbenzoylphosphinate (LAP)</td><td>Sigma-Aldrich, Inc. (USA)</td><td>900889</td><td></td></tr><tr><td>M4 and M5 Allen key</td><td>OpenBuilds, inc. (USA)</td><td>179, 190</td><td>also available in every hardware store. https://openbuildspartstore.com/allen-wrench/</td></tr><tr><td>OrangeG</td><td>Fisher Scientific (USA)</td><td>O267-25</td><td>https://www.fishersci.com/shop/products/orange-g-certified-biological-stain-fisher-chemical/O26725</td></tr><tr><td>Phosphate-buffered saline (PBS)</td><td>Thermo Fisher Scientific, Inc. (USA)</td><td>14190-144</td><td>alternativly: PBS tablets: 18912014 (Thermo Fisher Scientific)</td></tr><tr><td>&lt;strong&gt;Equipment&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Aluminium blocks for temperature dock</td><td>Ratek Instruments Pty. Ltd. (Australia)</td><td>SB16</td><td>blocks for different tube sizes are available. http://www.ratek.com.au/products/SB16-Block-with-12x16mm-holes.html</td></tr><tr><td>Analytical balance</td><td>Sartorius AG (Germany)</td><td>ED224S</td><td></td></tr><tr><td>Open source liquid handling robot: commercial product</td><td>Opentrons Laboratories, Inc. (USA)</td><td>OT-One S Pro</td><td>https://shop.opentrons.com/products/ot-one-pro</td></tr><tr><td>Open source liquid handling robot: open source hardware</td><td>Assembled in-house following an open source approach</td><td></td><td>hardware and software files are freely accessible on GitHub and Zenodo (links provided); building instructions are provided. https://github.com/SebastianEggert/OpenWorkstation. https://zenodo.org/record/3612757#.XipEjBV7F24</td></tr><tr><td>Positive displacement pipette: MicromanE</td><td>Gilson, Inc. (USA)</td><td>FD10006</td><td>depends on required size. https://www.gilson.com/default/shop-products/pipettes/positive-displacement.html</td></tr><tr><td>Spectrophotometer</td><td>BMG LABTECH GmbH (Germany)</td><td>CLARIOstar</td><td></td></tr><tr><td>Tips: capillary pistons</td><td>Gilson, Inc. (USA)</td><td>F148180</td><td>depends on required size. https://www.gilson.com/default/shop-products/pipette-tips.html?technique_en_ww_lk=191</td></tr></tbody></table>

an open source technology platform to manufacture hydrogel-based 3d culture models in an automated and standardized fashion

Current mixing steps of viscous materials rely on repetitive and time-consuming tasks which are performed mainly manually in a low throughput mode. These issues represent drawbacks in workflows that can ultimately result in irreproducibility of research findings. Manual-based workflows are further limiting the advancement and widespread adoption of viscous materials, such as hydrogels used for biomedical applications. These challenges can be overcome by using automated workflows with standardized mixing processes to increase reproducibility. In this study, we present step-by-step instructions to use an open source protocol designer, to operate an open source workstation, and to identify reproducible mixtures. Specifically, the open source protocol designer guides the user through the experimental parameter selection and generates a ready-to-use protocol code to operate the workstation. This workstation is optimized for pipetting of viscous materials to enable automated and highly reliable handling by the integration of temperature docks for thermoresponsive materials, positive displacement pipettes for viscous materials, and an optional tip touch dock to remove excess material from the pipette tip. The validation and verification of mixtures are performed by a fast and inexpensive absorbance measurement of Orange G. This protocol presents results to obtain 80% (v/v) glycerol mixtures, a dilution series for gelatin methacryloyl (GelMA), and double network hydrogels of 5% (w/v) GelMA and 2% (w/v) alginate. A troubleshooting guide is included to support users with protocol adoption. The described workflow can be broadly applied to a number of viscous materials to generate user-defined concentrations in an automated fashion.

This tutorial presents results for experiments with glycerol (Figure 3) and GelMA with LAP and alginate (Figure 4).
The generation of an 80% (v/v) glycerol solution was investigated either without temperature control (room temperature, 22 &#176;C) and without tip touch (defined as setup 1), with temperature control (40 &#176;C) and without tip touch (setup 2), or with temperature control (40 &#176;C) and with tip touch (setup 3) (Figure 3a-i). These two temperature settings were chosen to evaluate the handling difference, since glycerol&#8217;s viscosity is decreasing almost by a factor of 3 when heated from 22 &#176;C (139.5 mPa&#183;s) to 40 &#176;C (46.6 mPa&#183;s)30. An 85% (v/v) stock solution of glycerol was diluted to a final concentration of 80% and uniformly distributed into a 96 well plate (n = 96 per setup). The experimental time, which includes the dispensing of each material into the mixture tube, the respective mixing tasks, and sample distribution into a 96 well plate, was 30 min 42 s. To identify differences between dilution mixtures, ultrapure water&#8211;as the diluent for glycerol&#8211;was prepared with 1 mg/mL Orange G. The absorbance readings highlight that the integration of the temperature control and the tip touch significantly impacts the mixtures (p &#60; 0.0001). In addition to the performed two-way analysis of variance (ANOVA), the CV values were calculated to evaluate the relative standard deviation. The coefficient of variation describes a standardized indicator to identify the degree of deviation in relation to the mean and is expressed as a percentage. If the sample means are not particularly the point of interest, but the variability within the measurements, the coefficient of variation provides additional insights to identify reproducible mixtures46. Within this experiment with three different setups, the absorbance values showed decreasing CV values from 5.6%, 4.2%, to 2.0% for setup 1, setup 2, and setup 3, respectively, demonstrating the significant influence of the temperature dock and the tip touch function on producing reliable results (Figure 3a-ii). Plotting of sample absorbance values for setup 3 (sample number #1 to #96 in a 96 well plate) yields no increasing or decreasing values throughout the experiment and, therefore, indicates no influence of the sample position on the absorbance values (Figure 3a-iii). Visualizing the data for each measured well plate with heat maps provides additional insights to identify heterogeneities for a specific row or column, or varying absorbance values throughout the dispensing tasks. The visualized heatmaps for the three setups display decreased heterogeneities across the entire well plates from setup 1 to setup 3 (Figure 3b). Finally, the replicability of the conducted mixing was evaluated within eight independent runs (Figure 3c-i,ii), where each run took 6 min 57 s. Single mixing runs showed low CV values between 1.1% to 2.6%, which indicate very reliable mixing and dispensing tasks for the individual runs. Absorbance values of all eight runs yielded a CV value of 3.3% and demonstrated the reproducibility of the established mixing protocol.
GelMA dilution series were prepared by diluting a 20% (w/v) stock solution with PBS to 14, 12, 10, 8, 6, 4, 2, and 0% (w/v) and adding LAP to a constant concentration of 0.15% (w/v) (Figure 4a-i), which took in total 55 min 12 s. As specified in the experimental protocol script, the hydrogel was crosslinking for 30 s with an intensity of 2.0 mW/cm2 at 400 nm. To evaluate the differences between the mixtures, PBS&#8213;as the diluent for GelMA and alginate&#8213;was prepared with 1 mg/mL Orange G. Hence, absorbance difference between samples within one mixture as well as between the serial dilutions are identified with a spectrophotometer. Measured absorbance values of each concentration step are significantly different (p &#60; 0.0001) and have very low CV values between 1.2% and 3.4% throughout the concentration steps (n = 12 per concentration step). Linear regression demonstrated high fit with an R&#178; value of 0.9869 (Figure 4a-ii) and a heatmap confirmed the homogenous distribution for each concentration and the difference between the concentrations (Figure 4a-iii). Automated mixing of four reagents was conducted for the generation of 5% (w/v) GelMA, 2%&#160;(w/v) alginate, 0.15% (w/v) LAP, and PBS as diluent without (setup 2) and with (setup 3) touch tip (n = 96 for each setup) with the same crosslinking parameters (30 s, 2.0 mW/cm2, 400 nm). Dispensing of the four materials, mixing, and distributing into a 96 well plate took 32 min 22 s. All experiments with GelMA and alginate were conducted at 37 &#176;C to prevent thermal gelling which prevents pipetting of GelMA. With the tip touch option, the CV value was reduced from 5.2% to 3.4% and, especially, outliers in the lower region were prevented by removing excess material from the tip (Figure 4b-i). Although the mean value of 1.927 and 1.944 for setup 2 and setup 3 are very close, the coefficient of variation highlights the decreasing deviation in relation to the mean. Single rows of the 96 well plate can be compared with each other using a heatmap visualization to detect row and/or column differences (Figure 4b-ii).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61261/61261fig1.jpg" /> 
Figure 1: Protocol workflow with individual tasks. The described workflow is divided into seven&#160;tasks, which are separated into setup, preparation, execution, and analysis. In the beginning, the software (task 1) as well as the hardware (task 2) must be set up. After the preparation of the materials (task 3) and the generation of the protocol script (task 4), the pipetting module is calibrated by defining the pipette and container positions (task 5). Next, the protocol script is executed on the workstation (task 6) and validation and verification (task 7) of mixtures are carried out to evaluate mixtures. <a href="https://www.jove.com/files/ftp_upload/61261/61261fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/61261/61261fig2.jpg" /> 
Figure 2: Open source workstation and deck setup of the pipetting module. (a) The developed workstation is inspired by an assembly line approach, where samples are being transported through different modules, and consists of the following modules: pipetting, crosslinker, storage, transport, and computational module. (b) The deck of the pipetting module is set up depending on the experimental layout (e.g., well plate type, tube volume, etc.). The displayed deck setup was used for the presented experiments and consists of positive displacement pipettes with a range from 10&#8722;100 &#181;L (M100E) and 100&#8722;1,000 &#181;L (M1000E), the tip racks with capillary pistons (CP) for 100 &#181;L (CP1000) and 1,000 &#181;L (CP1000), a trash container, a mixing tray, and an input tray for the input reagents. (c) The available deck positions are defined with the displayed numbers. <a href="https://www.jove.com/files/ftp_upload/61261/61261fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/61261/61261fig3.jpg" /> 
Figure 3: Results for automated pipetting of glycerol mixtures. (a) The flexible workstation design enables the evaluation of three different setups (i) to identify optimal parameters for reproducible results. (ii) The addition of a tip touch and heating of the material resulted in a decreased coefficient of variance (CV) values and highly reproducible mixtures for setup 3. Each experiment was conducted with 96 samples. (iii) Plotting of single sample values showed no influence on the pipetting sequence. (b) Experimental results of each setup were visualized with heat maps to identify the influence on raw/column differences, edges, or master mixture. (c) The reproducibility of setup 3 was analyzed within eight independent runs using (i) median, standard deviation, CV value, and (ii) heatmaps. Data in panels a-ii (n = 96) and b-i (n = 12) are presented with the means and the single data points. Statistical significance was defined as ****p &#60; 0.0001 using two-way analysis of variance (ANOVA). <a href="https://www.jove.com/files/ftp_upload/61261/61261fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/61261/61261fig4.jpg" /> 
Figure 4: Results for mixing tasks with hydrogels. (a) From a gelatin metacryloyl (GelMA) 20% (w/v) stock solution, a serial dilution of 14, 12, 10, 8, 6, 4, 2, and 0% (w/v) was generated within one experimental run using a 96 well plate (n = 12 per concentration). (i) The coefficient of variance (CV) values varied between 1.2% and 3.4% throughout the prepared concentrations, and (ii) linear regression showed a high fit with an R&#178; value of 0.9869. (iii) Homogenous dilutions were confirmed visually with the generated heatmap. (b) Double network hydrogels were generated with 5% (w/v) GelMA, 2% (w/v) alginate, and 0.15% (w/v) LAP (i) with and without tip touch (n = 96 for each setup) and crosslinked for 30 s with an intensity of 2.0 mW/cm2 at 400 nm. The integration of the tip touch resulted in decreasing CV values from 5.2% to 3.4%. (ii,iii) Heatmaps confirm fewer deviations when using tip touch to remove excess material from tip. Data in panels a-i and b-i are presented with the means and the single data points. Statistical significance was defined as *p &#60; 0.05, ***p &#60; 0.001, and ****p &#60; 0.0001 using one-way analysis of variance (ANOVA). <a href="https://www.jove.com/files/ftp_upload/61261/61261fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/61261/61261fig5.jpg" /> 
Figure 5: Summary of the pipette type difference and issues with viscous biomaterials. (a) The reagent and the piston are separated by an air cushion that shrinks during dispensing steps and expands during aspirating steps. When aspirating and dispensing viscous materials, the slow &#8216;flow&#8217; introduces problems such as air bubbles and irregular pipetting behavior. (b) Positive displacement pipettes enable reliable aspirating and dispensing of viscous material by the usage of a piston inside the tip. (c) Pipetting of highly viscous materials (e.g., 4% (w/v)&#160;alginate) can result in the accumulation of excess material on the tip, which leads to inaccuracy throughout the experiments. (d) The implementation of a simple tip touch tray enables the removing of the excess material on the tip and results in accurate aspirating and dispensing volumes. This is realized by using the inner side of the well plate lid placed onto a tip rack container. <a href="https://www.jove.com/files/ftp_upload/61261/61261fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:font-size="9px" fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Material #1 (stock concentration)</td>
			<td>Final concentration of material #1</td>
			<td>Material #2 (stock concentration)</td>
			<td>Final concentration of material #2</td>
			<td>Materials #3 (stock concentration)</td>
			<td>Final concentration of material #3</td>
			<td>Diluent (Orange G working solution)</td>
			<td>Final Orange G concentration in mixture</td>
			<td>Displayed in figure</td>
		</tr>
		<tr>
			<td>Glycerol (85% (w/v))</td>
			<td>80% (w/v)</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td>water (1 mg/mL Orange G)</td>
			<td>0.059 mg/mL</td>
			<td>Figure 3a&#8722;c</td>
		</tr>
		<tr>
			<td>GelMA (20% (w/v))</td>
			<td>0% (w/v)</td>
			<td>LAP (3% (w/v))</td>
			<td>0.15% (w/v)</td>
			<td></td>
			<td></td>
			<td>PBS (1 mg/mL Orange G)</td>
			<td>1 mg/mL</td>
			<td>Figure 4a</td>
		</tr>
		<tr>
			<td>GelMA (20% (w/v))</td>
			<td>2% (w/v)</td>
			<td>LAP (3% (w/v))</td>
			<td>0.15% (w/v)</td>
			<td></td>
			<td></td>
			<td>PBS (1 mg/mL Orange G)</td>
			<td>0.85 mg/mL</td>
			<td>Figure 4a</td>
		</tr>
		<tr>
			<td>GelMA (20% (w/v))</td>
			<td>4% (w/v)</td>
			<td>LAP (3% (w/v))</td>
			<td>0.15% (w/v)</td>
			<td></td>
			<td></td>
			<td>PBS (1 mg/mL Orange G)</td>
			<td>0.75 mg/mL</td>
			<td>Figure 4a</td>
		</tr>
		<tr>
			<td>GelMA (20% (w/v))</td>
			<td>6% (w/v)</td>
			<td>LAP (3% (w/v))</td>
			<td>0.15% (w/v)</td>
			<td></td>
			<td></td>
			<td>PBS (1 mg/mL Orange G)</td>
			<td>0.65 mg/mL</td>
			<td>Figure 4a</td>
		</tr>
		<tr>
			<td>GelMA (20% (w/v))</td>
			<td>8% (w/v)</td>
			<td>LAP (3% (w/v))</td>
			<td>0.15% (w/v)</td>
			<td></td>
			<td></td>
			<td>PBS (1 mg/mL Orange G)</td>
			<td>0.55 mg/mL</td>
			<td>Figure 4a</td>
		</tr>
		<tr>
			<td>GelMA (20% (w/v))</td>
			<td>10% (w/v)</td>
			<td>LAP (3% (w/v))</td>
			<td>0.15% (w/v)</td>
			<td></td>
			<td></td>
			<td>PBS (1 mg/mL Orange G)</td>
			<td>0.45 mg/mL</td>
			<td>Figure 4a</td>
		</tr>
		<tr>
			<td>GelMA (20% (w/v))</td>
			<td>12% (w/v)</td>
			<td>LAP (3% (w/v))</td>
			<td>0.15% (w/v)</td>
			<td></td>
			<td></td>
			<td>PBS (1 mg/mL Orange G)</td>
			<td>0.35 mg/mL</td>
			<td>Figure 4a</td>
		</tr>
		<tr>
			<td>GelMA (20% (w/v))</td>
			<td>14% (w/v)</td>
			<td>LAP (3% (w/v))</td>
			<td>0.15% (w/v)</td>
			<td></td>
			<td></td>
			<td>PBS (1 mg/mL Orange G)</td>
			<td>0.25 mg/mL</td>
			<td>Figure 4a</td>
		</tr>
		<tr>
			<td>GelMA (20% (w/v))</td>
			<td>5% (w/v)</td>
			<td>Alginate (4% (w/v))</td>
			<td>2% (w/v)</td>
			<td>LAP (3% (w/v))</td>
			<td>0.15% (w/v)</td>
			<td>PBS (1 mg/mL Orange G)</td>
			<td>0.2 mg/mL</td>
			<td>Figure 4b</td>
		</tr>
	</tbody>
</table>
Table 1: Parameter overview for the conducted experiments.
<table border="1" fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Protocol step</td>
			<td>Problem</td>
			<td>Possible reason</td>
			<td>Solution</td>
		</tr>
		<tr>
			<td>1.1</td>
			<td>Software cannot be installed or updated</td>
			<td>Running out of disk space on SD card</td>
			<td>Check disk space on SD card. If required, remove unnecessary items, empty bin, or use an appropriately sized SD card</td>
		</tr>
		<tr>
			<td>1.2</td>
			<td>API cannot be installed</td>
			<td>Users ability for installation is restricted (no root user permission)</td>
			<td>Use &#8216;sudo&#8217; command in front of specified commands to gain admin rights. In Linux, this kind of access is known as the superuser.</td>
		</tr>
		<tr>
			<td>3.1</td>
			<td>Troubles with GelMA</td>
			<td>Functionalization, dialysis or lyophilization</td>
			<td>Detailed step-by-step protocol including troubleshooting list available in Loessner et al.33.</td>
		</tr>
		<tr>
			<td>5.1 and 6.2</td>
			<td>Workstation is not reacting to commands</td>
			<td>Connection issues</td>
			<td>Turn of everything and shut down the computer. Switch off the power supply for 10 s. Power computer and workstation back on.</td>
		</tr>
		<tr>
			<td>5.1 and 6.2</td>
			<td>Workstation is not reacting to commands</td>
			<td>Connection issues</td>
			<td>Check if the computer is recognizing the USB connection and the USB port is defined correctly. Make sure that firewall is not preventing the connection process (see the link below Table 2).</td>
		</tr>
		<tr>
			<td>5.1 and 6.2</td>
			<td>Cannot open file</td>
			<td>Wrong directory</td>
			<td>Check director (folder path) to ensure that the right path is being used. If a file (e.g., interface.py) cannot be found, it is likely that the wrong path is being used.</td>
		</tr>
		<tr>
			<td>6.6.2</td>
			<td>Tip is not properly attached or falls during movement</td>
			<td>Calibration issue</td>
			<td>Repeat calibration steps for the pipette and make sure that the capillary piston is connected properly with the pipette.</td>
		</tr>
		<tr>
			<td>6.6.2</td>
			<td>Tip is not properly attached or falls during movement</td>
			<td>Attachment issue</td>
			<td>Pipette is not properly connected to the pipette axis and moves during the movement steps. Tighten screws firmly to prevent this.</td>
		</tr>
		<tr>
			<td>6.6.2</td>
			<td>Tip is aspirating above material</td>
			<td>Calibration issue</td>
			<td>Repeat calibration of this tray type to define height properly.</td>
		</tr>
		<tr>
			<td>6.6.2</td>
			<td>Tip is aspirating above material</td>
			<td>Calibration issue</td>
			<td>Check volume in tube and make sure that the volume equals the volume defined in the protocol designer application.</td>
		</tr>
		<tr>
			<td>6.6.2</td>
			<td>Material is dipping during movement</td>
			<td>Too much excess material on tip</td>
			<td>Add tip touch dock option; optionally, also the time for tip touch can be increased.</td>
		</tr>
		<tr>
			<td>6.6.2</td>
			<td>Material is solid or too viscous for pipetting</td>
			<td>Thermoresponsive behaviour of material</td>
			<td>Check thermoresponsive material characterization and adjust heating/cooling temperature of temperature dock accordingly.</td>
		</tr>
		<tr>
			<td colspan="4">https://support.opentrons.com/en/articles/2687601-c-having-trouble-connecting-try-this-basic-troubleshooting</td>
		</tr>
	</tbody>
</table>
Table 2: Troubleshooting table with identified issues, possible reasons as well as solutions to solve the problems.
Supplemental File.&#160;<a href="https://www.jove.com/files/ftp_upload/61261/supplementary_template-analysis.xlsx" target="_blank">Please click here to download this file.</a>

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An Open Source Technology Platform to Manufacture Hydrogel-Based 3D Culture Models in an Automated and Standardized Fashion

This protocol serves as a comprehensive tutorial for standardized and reproducible mixing of viscous materials with a novel open source automation technology. Detailed instructions are provided on the operation of a newly developed open source workstation, the usage of an open source protocol designer, and the validation and verification to identify reproducible mixtures.

Current mixing steps of viscous materials rely on repetitive and time-consuming tasks which are performed mainly manually in a low throughput mode. These ...

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Research

JoVE Journal

Bioengineering

4.4K Views.  Queensland University of Technology. Biomedisch onderzoek wordt geconfronteerd met een reproduceerbaarheidscrisis omdat nieuwe onderzoeksresultaten zelden worden vertaald in therapeutische toepassingen. Dit protocol vermindert de menselijke factor en introduceert automatisering en standaardisatie in de productie. Deze methode richt zich specifiek op foto-cross-linkable hydrogels voor 3D-celkweektoepassingen, aangezien hydrogels het afgelopen decennium het meest gebruikte platform zijn geworden in kanker- en andere ziekteweefselm...

Video: An Open Source Technology Platform to Manufacture Hydrogel-Based 3D Culture Models in an Automated and Standardized Fashion

Microfabricated Platforms for Mechanically Dynamic Cell Culture

The ability to systematically probe in vitro cellular response to combinations of mechanobiological stimuli for tissue engineering, drug discovery or fundamental cell biology studies is limited by current bioreactor technologies, which cannot simultaneously apply a variety of mechanical stimuli to cultured cells. In order to address this issue, we have developed a series of microfabricated platforms designed to screen for the effects of mechanical stimuli in a high-throughput format. In this protocol, we demonstrate the fabrication of a microactuator array of vertically displaced posts on which the technology is based, and further demonstrate how this base technology can be modified to conduct high-throughput mechanically dynamic cell culture in both two-dimensional and three-dimensional culture paradigms.

In this protocol, we demonstrate the fabrication of a microactuator array of vertically displaced posts on which the technology is based, and how this base technology can be modified to conduct high-throughput mechanically dynamic cell culture in both two-dimensional and three-dimensional culture paradigms.

The ability to systematically probe in vitro cellular response to combinations of mechanobiological stimuli for tissue engineering, drug discovery or ...

Fabrication of Micropatterned Hydrogels for Neural Culture Systems using Dynamic Mask Projection Photolithography

Increasingly, patterned cell culture environments are becoming a relevant technique to study cellular characteristics, and many researchers believe in the need for 3D environments to represent in vitro experiments which better mimic in vivo qualities 1-3. Studies in fields such as cancer research 4, neural engineering 5, cardiac physiology 6, and cell-matrix interaction7,8have shown cell behavior differs substantially between traditional monolayer cultures and 3D constructs.
Hydrogels are used as 3D environments because of their variety, versatility and ability to tailor molecular composition through functionalization 9-12. Numerous techniques exist for creation of constructs as cell-supportive matrices, including electrospinning13, elastomer stamps14, inkjet printing15, additive photopatterning16, static photomask projection-lithography17, and dynamic mask microstereolithography18. Unfortunately, these methods involve multiple production steps and/or equipment not readily adaptable to conventional cell and tissue culture methods. The technique employed in this protocol adapts the latter two methods, using a digital micromirror device (DMD) to create dynamic photomasks for crosslinking geometrically specific poly-(ethylene glycol) (PEG) hydrogels, induced through UV initiated free radical polymerization. The resulting "2.5D" structures provide a constrained 3D environment for neural growth. We employ a dual-hydrogel approach, where PEG serves as a cell-restrictive region supplying structure to an otherwise shapeless but cell-permissive self-assembling gel made from either Puramatrix or agarose. The process is a quick simple one step fabrication which is highly reproducible and easily adapted for use with conventional cell culture methods and substrates.
Whole tissue explants, such as embryonic dorsal root ganglia (DRG), can be incorporated into the dual hydrogel constructs for experimental assays such as neurite outgrowth. Additionally, dissociated cells can be encapsulated in the photocrosslinkable or self polymerizing hydrogel, or selectively adhered to the permeable support membrane using cell-restrictive photopatterning. Using the DMD, we created hydrogel constructs up to ~1mm thick, but thin film (&lt;200 &mu;m) PEG structures were limited by oxygen quenching of the free radical polymerization reaction. We subsequently developed a technique utilizing a layer of oil above the polymerization liquid which allowed thin PEG structure polymerization.
In this protocol, we describe the expeditious creation of 3D hydrogel systems for production of microfabricated neural cell and tissue cultures. The dual hydrogel constructs demonstrated herein represent versatile in vitro models that may prove useful for studies in neuroscience involving cell survival, migration, and/or neurite growth and guidance. Moreover, as the protocol can work for many types of hydrogels and cells, the potential applications are both varied and vast.

Simple techniques are described for the rapid production of microfabricated neural culture systems using a digital micromirror device for dynamic mask projection lithography on regular cell culture substrates. These culture systems may be more representative of natural biological architecture, and the techniques described could be adapted for numerous applications.

Increasingly, patterned cell culture environments are becoming a relevant technique to study cellular characteristics, and many researchers believe in the ...

Enhanced Viability for Ex vivo 3D Hydrogel Cultures of Patient-Derived Xenografts in a Perfused Microfluidic Platform

Patient-derived xenografts (PDX), generated when resected patient tumor tissue is engrafted directly into immunocompromised mice, remain biologically stable, thereby preserving molecular, genetic, and histological features, as well as heterogeneity of the original tumor. However, using these models to perform a multitude of experiments, including drug screening, is prohibitive both in terms of cost and time. Three-dimensional (3D) culture systems are widely viewed as platforms in which cancer cells retain their biological integrity through biochemical interactions, morphology, and architecture. Our team has extensive experience culturing PDX cells in vitro using 3D matrices composed of hyaluronic acid (HA). In order to separate mouse fibroblast stromal cells associated with PDXs, we use rotation culture, where stromal cells adhere to the surface of tissue culture-treated plates while dissociated PDX tumor cells float and self-associate into multicellular clusters. Also floating in the supernatant are single, often dead cells, which present a challenge in collecting viable PDX clusters for downstream encapsulation into hydrogels for 3D cell culture. In order to separate these single cells from live cell clusters, we have employed density step gradient centrifugation. The protocol described here allows for the depletion of non-viable single cells from the healthy population of cell clusters that will be used for further in vitro experimentation. In our studies, we incorporate the 3D cultures in microfluidic plates which allow for media perfusion during culture. After assessing the resultant cultures using a fluorescent image-based viability assay of purified versus non-purified cells, our results show that this additional separation step substantially reduced the number of non-viable cells from our cultures.

This protocol demonstrates methods to enable extended in vitro culture of patient-derived xenografts (PDX). One step enhances overall viability of multicellular cluster cultures in 3D hydrogels, through straightforward removal of non-viable single cells. A secondary step demonstrates best practices for PDX culture in a perfused microfluidic platform.

Patient-derived xenografts (PDX), generated when resected patient tumor tissue is engrafted directly into immunocompromised mice, remain biologically ...

Cancer Research

Printing Thermoresponsive Reverse Molds for the Creation of Patterned Two-component Hydrogels for 3D Cell Culture

Bioprinting is an emerging technology that has its origins in the rapid prototyping industry. The different printing processes can be divided into contact bioprinting1-4 (extrusion, dip pen and soft lithography), contactless bioprinting5-7 (laser forward transfer, ink-jet deposition) and laser based techniques such as two photon photopolymerization8. It can be used for many applications such as tissue engineering9-13, biosensor microfabrication14-16 and as a tool to answer basic biological questions such as influences of co-culturing of different cell types17. Unlike common photolithographic or soft-lithographic methods, extrusion bioprinting has the advantage that it does not require a separate mask or stamp. Using CAD software, the design of the structure can quickly be changed and adjusted according to the requirements of the operator. This makes bioprinting more flexible than lithography-based approaches.
Here we demonstrate the printing of a sacrificial mold to create a multi-material 3D structure using an array of pillars within a hydrogel as an example. These pillars could represent hollow structures for a vascular network or the tubes within a nerve guide conduit. The material chosen for the sacrificial mold was poloxamer 407, a thermoresponsive polymer with excellent printing properties which is liquid at 4 &deg;C and a solid above its gelation temperature ~20 &deg;C for 24.5% w/v solutions18. This property allows the poloxamer-based sacrificial mold to be eluted on demand and has advantages over the slow dissolution of a solid material especially for narrow geometries. Poloxamer was printed on microscope glass slides to create the sacrificial mold. Agarose was pipetted into the mold and cooled until gelation. After elution of the poloxamer in ice cold water, the voids in the agarose mold were filled with alginate methacrylate spiked with FITC labeled fibrinogen. The filled voids were then cross-linked with UV and the construct was imaged with an epi-fluorescence microscope.

A bioprinter was used to create patterned hydrogels based on a sacrificial mold. The poloxamer mold was backfilled with a second hydrogel and then eluted, leaving voids which were filled with a third hydrogel. This method uses fast elution and good printability of poloxamer to generate complex architectures from biopolymers.

Bioprinting is an emerging technology that has its origins in the rapid prototyping industry. The different printing processes can be divided into contact ...

Immunology and Infection

Bioprinting Cellularized Constructs Using a Tissue-specific Hydrogel Bioink

Bioprinting has emerged as a versatile biofabrication approach for creating tissue engineered organ constructs. These constructs have potential use as organ replacements for implantation in patients, and also, when created on a smaller size scale as model "organoids" that can be used in in vitro systems for drug and toxicology screening.
Despite development of a wide variety of bioprinting devices, application of bioprinting technology can be limited by the availability of materials that both expedite bioprinting procedures and support cell viability and function by providing tissue-specific cues. Here we describe a versatile hyaluronic acid (HA) and gelatin-based hydrogel system comprised of a multi-crosslinker, 2-stage crosslinking protocol, which can provide tissue specific biochemical signals and mimic the mechanical properties of in vivo tissues. 
Biochemical factors are provided by incorporating tissue-derived extracellular matrix materials, which include potent growth factors. Tissue mechanical properties are controlled combinations of PEG-based crosslinkers with varying molecular weights, geometries (linear or multi-arm), and functional groups to yield extrudable bioinks and final construct shear stiffness values over a wide range (100 Pa to 20 kPa). Using these parameters, hydrogel bioinks were used to bioprint primary liver spheroids in a liver-specific bioink to create in vitro liver constructs with high cell viability and measurable functional albumin and urea output. This methodology provides a general framework that can be adapted for future customization of hydrogels for biofabrication of a wide range of tissue construct types.

We describe a set of protocols that together provide a tissue-mimicking hydrogel bioink with which functional and viable 3-D tissue constructs can be bioprinted for use in in vitro screening applications.

Bioprinting has emerged as a versatile biofabrication approach for creating tissue engineered organ constructs. These constructs have potential use as ...

3D Microtissues for Injectable Regenerative Therapy and High-throughput Drug Screening

To upgrade traditional 2D cell culture to 3D cell culture, we have integrated microfabrication with cryogelation technology to produce macroporous microscale cryogels (microcryogels), which can be loaded with a variety of cell types to form 3D microtissues. Herein, we present the protocol to fabricate versatile 3D microtissues and their applications in regenerative therapy and drug screening. Size and shape-controllable microcryogels can be fabricated on an array chip, which can be harvested off-chip as individual cell-loaded carriers for injectable regenerative therapy or be further assembled on-chip into 3D microtissue arrays for high-throughput drug screening. Due to the high elastic nature of these microscale cryogels, the 3D microtissues exhibit great injectability for minimally invasive cell therapy by protecting cells from mechanical shear force during injection. This ensures enhanced cell survival and therapeutic effect in the mouse limb ischemia model. Meanwhile, assembly of 3D microtissue arrays in a standard 384-multi-well format facilitates the use of common laboratory facilities and equipment, enabling high-throughput drug screening on this versatile 3D cell culture platform.

This protocol describes the fabrication of elastic 3D macroporous microcryogels by integrating microfabrication with cryogelation technology. Upon loading with cells, 3D microtissues are generated, which can be readily injected in vivo to facilitate regenerative therapy or assembled into arrays for in vitro high-throughput drug screening.

To upgrade traditional 2D cell culture to 3D cell culture, we have integrated microfabrication with cryogelation technology to produce macroporous ...

An Additive Manufacturing Technique for the Facile and Rapid Fabrication of Hydrogel-based Micromachines with Magnetically Responsive Components

Polyethylene glycol (PEG)-based hydrogels are biocompatible hydrogels that have been approved for use in humans by the FDA. Typical PEG-based hydrogels have simple monolithic architectures and often function as scaffolding materials for tissue engineering applications. More sophisticated structures typically take a long time to fabricate and do not contain moving components. This protocol describes a photolithography method that allows for facile and rapid microfabrication of PEG structures and devices. This strategy involves an in-house developed fabrication stage that allows for the rapid fabrication of 3D structures by building upwards in a layer-by-layer fashion. Independent moving components can also be aligned and assembled onto support structures to form integrated devices. These independent components are doped with superparamagnetic iron oxide nanoparticles that are sensitive to magnetic actuation. In this manner, the fabricated devices can be actuated using external magnets to yield movement of the components within. Hence, this technique allows for the fabrication of sophisticated MEMS-like devices (micromachines) that are composed entirely out of a biocompatible hydrogel, able to function without an onboard power source, and respond to a contact-less method of actuation. This manuscript describes the fabrication of both the fabrication set-up as well as the step-by-step method for the microfabrication of these hydrogels-based MEMS-like devices.

An additive manufacturing strategy for processing UV-crosslinkable hydrogels has been developed. This strategy allows for the layer-by-layer assembly of microfabricated hydrogel structures as well as the assembly of independent components, yielding integrated devices containing moving components that are responsive to magnetic actuation.

Polyethylene glycol (PEG)-based hydrogels are biocompatible hydrogels that have been approved for use in humans by the FDA. Typical PEG-based hydrogels ...

Bioprintable Alginate/Gelatin Hydrogel 3D In Vitro Model Systems Induce Cell Spheroid Formation

The cellular, biochemical, and biophysical heterogeneity of the native tumor microenvironment is not recapitulated by growing immortalized cancer cell lines using conventional two-dimensional (2D) cell culture. These challenges can be overcome by using bioprinting techniques to build heterogeneous three-dimensional (3D) tumor models whereby different types of cells are embedded. Alginate and gelatin are two of the most common biomaterials employed in bioprinting due to their biocompatibility, biomimicry, and mechanical properties. By combining the two polymers, we achieved a bioprintable composite hydrogel with similarities to the microscopic architecture of a native tumor stroma. We studied the printability of the composite hydrogel via rheology and obtained the optimal printing window. Breast cancer cells and fibroblasts were embedded in the hydrogels and printed to form a 3D model mimicking the in vivo microenvironment. The bioprinted heterogeneous model achieves a high viability for long-term cell culture (&#62; 30 days) and promotes the self-assembly of breast cancer cells into multicellular tumor spheroids (MCTS). We observed the migration and interaction of the cancer-associated fibroblast cells (CAFs) with the MCTS in this model. By using bioprinted cell culture platforms as co-culture systems, it offers a unique tool to study the dependence of tumorigenesis on the stroma composition. This technique features a high-throughput, low cost, and high reproducibility, and it can also provide an alternative model to conventional cell monolayer cultures and animal tumor models to study cancer biology.

Bioprintable Alginate/Gelatin Hydrogel 3D In Vitro Model Systems Induce Cell Spheroid Formation

We developed a heterogeneous breast cancer model consisting of immortalized tumor and fibroblast cells embedded in a bioprintable alginate/gelatin bioink. The model recapitulates the in vivo tumor microenvironment and facilitates the formation of multicellular tumor spheroids, yielding insight into the mechanisms driving tumorigenesis.

The cellular, biochemical, and biophysical heterogeneity of the native tumor microenvironment is not recapitulated by growing immortalized cancer cell ...

Hydrogel Arrays Enable Increased Throughput for Screening Effects of Matrix Components and Therapeutics in 3D Tumor Models

Cell-matrix interactions mediate complex physiological processes through biochemical, mechanical, and geometrical cues, influencing pathological changes and therapeutic responses. Accounting for matrix effects earlier in the drug development pipeline is expected to increase the likelihood of clinical success of novel therapeutics. Biomaterial-based strategies recapitulating specific tissue microenvironments in 3D cell culture exist but integrating these with the 2D culture methods primarily used for drug screening has been challenging. Thus, the protocol presented here details the development of methods for 3D culture within miniaturized biomaterial matrices in a multi-well plate format to facilitate integration with existing drug screening pipelines and conventional assays for cell viability. Since the matrix features critical for preserving clinically relevant phenotypes in cultured cells are expected to be highly tissue- and disease-specific, combinatorial screening of matrix parameters will be necessary to identify appropriate conditions for specific applications. The methods described here use a miniaturized culture format to assess cancer cell responses to orthogonal variation of matrix mechanics and ligand presentation. Specifically, this study demonstrates the use of this platform to investigate the effects of matrix parameters on the responses of patient-derived glioblastoma (GBM) cells to chemotherapy.

The present protocol describes an experimental platform to assess the effects of mechanical and biochemical cues on chemotherapeutic responses of patient-derived glioblastoma cells in 3D matrix-mimetic cultures using a custom-made UV illumination device facilitating high-throughput photocrosslinking of hydrogels with tunable mechanical features.

Cell-matrix interactions mediate complex physiological processes through biochemical, mechanical, and geometrical cues, influencing pathological changes ...

Preparation of a User-Defined Peptide Gel for Controlled 3D Culture Models of Cancer and Disease

There is a growing awareness that cells grown in 3D better model in vivo behavior than those grown in 2D. In this protocol, we describe a simple and tunable 3D hydrogel, suitable for culturing cells and tissue in a setting that matches their native environment. This is particularly important for researchers investigating the initiation, growth, and treatment of cancer where the interaction between cells and their local extracellular matrix is a fundamental part of the model. Moving to 3D culture can be challenging and is often associated with a lack of reproducibility due to high batch-to-batch variation in animal-derived 3D culture matrices. Similarly, handling issues can limit the usefulness of synthetic hydrogels. In response to this need, we have optimized a simple self-assembling peptide gel, to enable the culture of relevant cell line models of cancer and disease, as well as patient-derived tissue/cells. The gel itself is free from matrix components, apart from those added during encapsulation or deposited into the gel by the encapsulated cells. The mechanical properties of the hydrogels can also be altered independent of matrix addition. It, therefore, acts as a &#8216;blank slate&#8217; allowing researchers to build a 3D culture environment that reflects the target tissue of interest and to dissect the influences of mechanical forces and/or biochemical control of cell behavior independently.

We present a method for creating a 3D cell culture environment, which can be used to investigate the importance of cell/matrix interactions in cancer progression. Using a simple self-assembling octapeptide, the matrix surrounding encapsulated cells can be controlled, with independent regulation of mechanical and biochemical cues.

There is a growing awareness that cells grown in 3D better model in vivo behavior than those grown in 2D. In this protocol, we describe a simple and ...

An Open Source Technology Platform to Manufacture Hydrogel-Based 3D Culture Models in an Automated and Standardized Fashion

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