Overview:

  From April to October, we spent every single time in the laboratory, Lab 311. Every member concentrated on the project and put our heads together to create the possibility of each process. We set our goals to accomplish the automation of synthetic biology experiments in order to bring synthetic biology closer to people and solve problems with numerous errors due by humans.

  To achieve what we wanted that are mentioned above, we used a single 6-axis robot arm to replace human movements perfectly and conduct as an innovative system for foundation advance. Also, we required the device to avoid human errors, save materials and time, increase the precision and accuracy of the data, and be easily applied to any cell through the modularization of software functions. We are proud to say that we achieved the goal and keep trying better over and over again.



Goal:

Wet Lab Goal


  Provide sufficient information of synthetic biology, protocol of goal experiments, and additional details.
  Figure out errors occur from the robot’s postures and speed that are executed in each movement.
  Gather and analyze data from the automated experiment.
  Communicate with external groups for information exchange and promotion of synthetic biology.

Robot Goal


  Study detailed protocols of experiments including cell culturing and transduction with the lentiviral system (since all robot members are majoring in mechanical engineering). Convert human gestures to robot movements.
  Design the 'SynBioBot' to guarantee flexible interaction between the hardware and the software.
  Make sure the 'SynBioBot' can be used practically in the field of education and the automation of researchs.

Hardware Goal


  Create optimized hardware items(3D models) as supporting parts to handle laboratory equipment with the robot.
  Design pleasant and safety environment to operate the ‘SynBioBot’.
  Arrange hardware items in a pliable way for the use of the whole device in a variety of experiments.

Software Goal


  Design algorithm to guarantee robot’s decision process.
  Construct the most fitted coordinate recognition and correction method.
  Subdivide the experimental process and modularize the repetitive motions into specific functions.
  Create a user-friendly interface that can make non-professional users can utilize the program by themselves.


Wiki Goal:


  Conduct contents arrangement
  Manage art work of wiki
  Carry out HTML coding to develop a classy wiki page

Human Practices Goal:


  Participate in many external events such as competitions for technology and communication activity (to promote what we are developing for future synthetic biology and receive feedback for improvement)
  Arrange as many interim inspections to accommodate professional feedback on technological aspects as well as business plans for the future of SynBioBot.


Result:

  The goals of each part have been set with thorough discussion. We used the goals as a roadmap of the project ‘SynBioBot’. Following the roadmap, we fulfilled the success in the automation of experiments. We would like to begin introducing the achievement of the project with the working result of the Robot part.


Robot Result


  First and foremost, we focused on studying the basic information of biology and synthetic biology. The experiments were relatively easy for students who are majoring in biology, but robot members are not quite experienced on the subject. After learning what we should do, we started the mechanical process with the robot arm.


Fig 1. Diagram of experiment processes organized by the robot team to help understanding

  The below Fig 2. shows what we have done before modeling items and planning algorithms for automation. The content specifies the robot arm's and the gripper's motions in detail according to Experiments. Human emotions are very flexible and connected so smoothly that we don’t usually recognize what we have conducted. Despite the difficulty of mimicking human motions, we clearly organized experiment processes.


Fig 2. human motions and robot motions to conduct subculturing

Hardware Result


  As we all know, the hardware items are the spine of the project. Through the ‘DDCC’ process mentioned on in Engineering Success, we created ingenious items just for the synthetic biology experiments using ‘SynBioBot’.


Fig 3. The photo of SynBioBot taken from the top

  You may check the above Fig 3. Production processes and functions of Hardware items are explained in detail on Hardware. It is quite a fact to say we made impressive advancements with all of our devices.


  Selected the most suitable gripper for motions and the wiring work.
  Create optimized hardware items as supporting parts to handle laboratory equipment with the robot.
  Made a flexible and practical arrangement of hardware items to apply a variety of experiments that we have not challenged yet.
  Maximized efficiency of space to cut back waste time.
  Applied visually modern and pleasant colors.
  Got design patents of the plate stand, the pipette stand and the pipette case.

Software Result


  Next to the hardware, we focused on the software, including robotics coding and user interface development. Based on the well-made hardware items such as the plate stand, pipette case, tip remover, etc, we were able to conduct experiments only through the control of the robot arm and the gripper.


Fig 4. Scheme for software development

Fig 5. Operation GIF of GUI software

  Here, Software page demonstrates the particular meanings of each progress. As we tried our best to operate the robot and be accessible for non-professional people, We want to sum up the software achievement through the words below.


  Planned algorithms and designed schemes to guarantee our progress of development to be successful.
  Organized the experimental processes into robot motions and modularized the repetitive gestures into specific functions
  Constructed the vision control using ArUCO Marker and increased precision and accuracy of the experiment.
  Created a user-friendly, intuitive GUI program especially for students and whom it may regarded as rookies on synthetic biology.

  Next, the wet lab evaluated the motions’ precision & accuracy and provided feedback to the robot team during the development process. For example, when modeling the plate stand, the robot team only focused on the safe separation distance between the gripper and the table. However, it is widely known that enough plate slope is necessary to conduct the suction of the medium. The wet lab team noticed the problem and provided feedback in real-time as we cooperated all through the progress. Finally, the robot has achieved not only the robot operation but also avoided several pitfalls.



Video 1. Cell Seeding by SynBioBot

Video 2. Sub-culturing by SynBioBot

Video 3. Transduction of lentiviral system by SynBioBot

  The above videos display how SynBioBot operates as a whole.
  Yet, we still need improvement in our robot movements regarding the utilization of a centrifuge in the process of subculturing. The problem is that the specifications of the centrifuge do not fit the gripper specification. Since the 15mL conical tube cab is thinner than the 30mm space between the toes of the gripper(tough PLA), it is required to be grabbed by the 10mm inner part space of the gripper(aluminum). To conduct such a gesture, the gripper should enter the internal centrifuge in a deeper manner so that there was a limitation upon the gripper entrance.
  But don’t worry! We completed the ‘get_pos’ function in Python, which contains the code that can define the conical tube’s location obtained by the vision data processing after the centrifuge. This means that we will definitely solve the problem just after the new centrifuge, which fits the current situation, arrives.
  In this regard, we are proud to say that we have achieved a Sustainable technology by ourselves with creativeness, innovativeness, and clear objectives and strategies for foundational advances to reduce human errors.


Wet Lab Result


[1] Preliminary Experiment of Lentivirus Transduction in HEK293T Cells


  We received the 𝝰5 lentivirus in February 2022 from a bio company and we conducted the transduction experiment using HEK293T cells in a level 2 biosafety cabinet. The first step was testing a range of volume or MOI (multiplicity of infection). MOI is the number of transducing lentiviral particles per cell and MOIs of 1, 5, 10 were used to determine the transduction efficiency.


Fig 6. Confocal images of HEK293T cells infected by 𝝰5 lentivirus in different MOI number.

  The successful infection of 𝝰5 lentivirus or 𝝰5 integrin overexpressed (OE) cell is shown by the emission of EGFP fluorescent from the infected cell (Fig 6.). Based on the result above, we decided to use MOI 10 for the further experiment.

  To select the infected cells, we used antibiotic selection method by using G418 (Geneticin). G418 is an aminoglycoside antibiotic that works by blocking polypeptide synthesis by inhibiting the elongation step in eukaryotic cells. Two days after transduction, HEK cells were incubated with 5 ug/ml G418 in DMEM medium supplemented with 1% FBS. G418 selection was conducted for 8 days with DMEM medium change interval every 2-3 days.


Fig 7. Confocal images of HEK293T cells 24h after transduction (upper) and after antibiotic selection (lower).

  After antibiotic selection for 8 days, EGFP fluorescent images showed wider distribution among the HEK cells population (Fig 7.). Some uninfected cells remained found after the antibiotic selection. To solve this issue, the selection procedure were repeated until only the 𝝰5 integrin OE HEK cells were detected. Once the stable 𝝰5 integrin OE HEK cell line generation was obtained, the expression of 𝝰5 integrin was monitored by western blot.


Fig 8. Characterization of 𝝰5 integrin OE cells. (a) Western blot profiles of 𝝰5 integrin expression in wildtype (WT) and 𝝰5 integrin OE cell. (b) Relative band intensity of western blot profiles (a).

  The western blot profiles showed a significantly higher band intensity of 𝝰5 integrin protein observed at approximately 135 kDa compared to the control (WT) (Fig 8.)[1]. This data indicates a successful transduction of HEK293T cells with 𝝰5 integrin lentivirus.


[2] Cell Culturing in An Open Space


  Due to the size and working space of SynBioBot, it could not be operated inside a biosafety cabinet. To improvise, we set up a simple open bench as an additional working area to prepare some of the culture work that was located in the same room with SynBioBot.


Fig 9. A clean bench (left) and an open bench set up (right).

  The set up of the open bench consisted of a water bath, pipette, pipette tips, cell culture dishes, conical tubes, a tube rack and tissue (Fig 9.). The area was kept as clean as possible, and efforts were made to maintain a clean environment using clean wipers, ethanol, and gloves.


Fig 10. The microscope images of human keratinocytes cultured in a clean bench (left) and an open space (right). The scale bar is 100 µm.

  To check whether there would be no contamination or unsuccessful cell experiment, we cultured human keratinocytes (HaCaT) cells in a clean bench and open space, simultaneously. In both conditions, cells were attached after 24 hours of incubation in 5% CO2 and 37oC incubator. HaCaT cells cultured in the open space were concentrated at certain areas in the petri dish and had no sign of contamination, showing the possibility to be cultured in open space.


[3] Cells Seeding and Passaging


  Cell seeding is the initial protocol step and standard procedure in cell-based experiments. For consistent experiment outcomes, a proper and standardized cell seeding process is essential. The main challenge in this step is to achieve and maintain comparable cell numbers in all replicate experiments[2]. Here, we programmed SynBioBot to perform HaCaT cell seeding steps from taking the culture dish to storing the dish containing seeded cells in the incubator.


Fig 11. Graph of cell seeding operation time conducted by SynBioBot (automated) and human hands (manual).

  We compared the time consumed by SynBioBot to conduct cell seeding to manual operation performed by a trained member of Sogang_Korea (Fig 11.). SynBioBot showed a constant operating time in cell seeding with an average time of 8:56 and SD of 0.016. Human hands were three times faster than SynBioBot with an average time of 2:52 and SD of 0.092. This result was anticipated because it took time for SynBioBot to do initial recognition and it is a single arm robot. Even though manual procedure was faster, SynBioBot showed well and constant operating steps of cell seeding.


Fig 12. Bar graph of counted cell number (a) and microscope images (b) of HaCaT cells conducted by SynBioBot (automated) and human hands (manual). The scale bar is 300µm.

  The cultured cells were observed for two consecutive days under light microscope 24 hours after the cell seeding. Microscope images were taken from petri dishes containing cultured HaCaT in three different areas and counted using ImageJ software. On the first day, cells counted from automated cell seeding have a slightly lower average and higher SD compared to the manual (Fig 12a.). This was possibly caused by the pipetting process of SynBioBot leaving some of the liquid containing cells. On the second day, both automated and manual had the same average number of cells and showed a growing HaCaT number. Morphologically, HaCaT cells looked healthy and there was no sign of contamination (Fig 12b.).

  After successfully programming the cell seeding using SynBioBot, we also managed a trial in cell subculturing. Passaging or subculturing is the removal of the medium and transfer of cells from a previous culture into fresh growth medium, a procedure that enables the further propagation of the cell line or cell strain[3]. Cell passaging performed by SynBioBot incorporated phosphate buffer saline (PBS) washing, suction, trypsinization, and cell medium dividing steps.


Fig 13. Graph of cell passaging operation time conducted by SynBioBot (automated) and human hands (manual).

  Cell passaging consumed a longer time compared to cell seeding as more steps were required to subculture confluent state cells. SynBioBot needed forty one minutes and fifty six seconds to perform cell passaging and the manual process needed twenty five minutes and thirty one seconds (Fig 13.). Note that centrifugation step was the issue of the automated cell subculturing as the position of the conical tube inside the centrifuge could change from the initial position after the centrifugation and SynBioBot was not able to recognize it.


[4] α5 Integrin Lentivirus Transduction in Human Keratinocytes


  Integrins are widely distributed cell surface receptors that are essential for regulating the interaction between a cell and its microenvironment to control cell fate and development[4]. 𝝰5𝛃1 integrin binds to fibronectin and has a well-defined role in cell adhesion, migration, and matrix formation. In wound healing, human keratinocyte motility on a fibronectin substratum is critical in the re-epithelization of injured skin and in the spread of cutaneous malignancy[5]. Knowing the pivotal role of 𝝰5𝛃1 integrin as a fibronectin receptor, we initiated to program lentivirus transduction process through SynBioBot to make 𝝰5 integrin overexpressed (OE) HaCaT cells. The 𝝰5 OE HaCaT could be potentially used to study the interaction of HaCaT and its microenvironment in healing wounds or skin tumors.


Fig 14. Graph of lentivirus transduction operation time conducted by SynBioBot (automated) and human hands (manual).

  Lentivirus transduction protocol conducted by SynBioBot was started with HaCaT cell seeding in the concentration of 3x105 cells/mL. After being incubated for 18-20 hours, cells were incubated with polybrene for an hour to enhance the transduction efficiency. 𝝰5 lentivirus with MOI 10 was prepared in the antibiotic-free medium and added into the petri dish containing HaCaT cells. After overnight incubation, the virus-containing medium was replaced and continued with another overnight incubation. The lentivirus transduction process was well performed by SynBioBot in a constant time with the average of 18:40 and SD of 0.014 (Fig. 14). The manual process took the average of 5:55 and SD of 0.516.


Fig 15. Graph of EGFP positive cells after transduction (a) and the confocal images of infected HaCat (b) and its magnification (c). The scale bar is 100µm.

  After transduction, HaCaT cells were observed using a confocal microscope and the number of EGFP positive cells was counted using ImageJ software. The results showed that the number of infected cells in the automated process was slightly higher compared to the manual (Fig 15a). The successfully infected HaCaT cells observed under the confocal microscope with differential interference contrast (DIC) imaging as the background, showing the EGFP expression that followed the cell shape (Fig 15b,c). These results revealed the capability of SynBioBot to perform lentivirus transduction as part of synthetic biology research.


Human Practices Result

  We have always tried to learn and improve SynBioBot through various human practice activities that inspire us. We have participated in and led two types of events:

  • Inreach events(S.M.A.R.T, ICEAS, technical advice from Onrobot.Inc, professor advice)
  • Outreach events(community service, EBPH, Synthetic Biology Debate Competition).

  During events, we received technologic advise to develop a better system of high precision and high accuracy. Communication with both professional and non-professional people resulted in significant improvement on SynBioBot. For example, Evidence-Based Practice with High school(EBPH) supported several creative approaches on the pipette case to increase the applicability of the gripper on pipettes.

  Among those positive impacts of activities, the most significant gain was the conviction of SynBioBot’s educational effectiveness. Since the concept construction of project ‘SynBioBot’, we’ve always kept remote education in view. However, during the community service at SD KANISIUS DUWET in Indonesia, we conducted remote education from Seoul, Korea to Indonesia utilizing SynBioBot. According to the research of Sogang Korea, students’ interest and comprehension level of the experiments after the robotic education were exceptionally positive. You may check the result on Proof of Concept.


Fig 16. community service at SD KANISIUS DUWET in Indonesia, we conducted remote education with 35 students.

  We arranged overall human practice activities in a detailed manner here. Also, we demonstrated different aspects of activities via Education and Communication. We wish you to check the details of our practices.



Lastly,


  The wiki team perfectly developed the wiki page that is full of explanations of the project. Every member fully participated in the writing work and the wiki managers always achieved more than expected. We wish you may browse around every category for various information about us in Sogang_Korea.



Future Plan:


  We already have 3-year plans for the future ‘SynBioBot’. We will deploy the beta-version software that we developed to high schools first. And we can do many other experiments and the experiments we've tried and get feedback from users. After then, we will launch a service; receiving the experimental protocol from users, proceeding customized coding, and if we update the GUI, customers will be able to proceed with new and personal experiments using the ‘SynBioBot’. Subsequently, we will expand our technology, including vision control, to provide an environment where we can perform the desired experiment using the robot arm freely. Above plans would lead us to a significant advancement after all.


References:


 [1] Xiong S, Xu Y, Wang Y, Kumar A, Peters DM, Du Y. α5β1 Integrin Promotes Anchoring and Integration of Transplanted Stem Cells to the Trabecular Meshwork in the Eye for Regeneration. Stem Cells Dev. 2020 Mar 1;29(5):290-300. doi: 10.1089/scd.2019.0254. Epub 2020 Jan 20. PMID: 31854234; PMCID: PMC7047116.


 [2] Liu Z, Tamaddon M, Gu Y, Yu J, Xu N, Gang F, Sun X, Liu C. Cell Seeding Process Experiment and Simulation on Three-Dimensional Polyhedron and Cross-Link Design Scaffolds. Front Bioeng Biotechnol. 2020 Mar 4;8:104. doi: 10.3389/fbioe.2020.00104. PMID: 32195229; PMCID: PMC7064471.


 [3] Segeritz CP, Vallier L. Cell Culture: Growing Cells as Model Systems In Vitro. Basic Science Methods for Clinical Researchers. 2017:151–72. doi: 10.1016/B978-0-12-803077-6.00009-6. Epub 2017 Apr 7. PMCID: PMC7149418.


 [4] Mezu-Ndubuisi, O.J., Maheshwari, A. The role of integrins in inflammation and angiogenesis. Pediatr Res 89, 1619–1626 (2021).


 [5] Werner S, Krieg T, Smola H. Keratinocyte-fibroblast interactions in wound healing. J Invest Dermatol. 2007 May;127(5):998-1008. doi: 10.1038/sj.jid.5700786. PMID: 17435785.