Presented by Team Purdue 2020
Madhumitha Prakash¹, Hailey Szadowski¹, Miles Thompson¹, Andres Dextre¹, Matthew Chan¹, Jieun Lee¹, Dalton Saylor¹, Karthik Ravichandran¹, Ben Howard¹, Swagat Bhattacharyya¹, Xander Weintraut¹, Victor Pacheco¹, Alex Boyd¹, Casey Ernest¹, Pim Jitnavasathien¹, Ana Stenstrom¹,²Ethan Hillman, ³Kevin Solomon, §Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN, USA, §College of Agriculture, Purdue University, West Lafayette, IN, USA, §College of Engineering, Purdue University, West Lafayette, IN, USA
Abstract
The COVID-19 pandemic has strained global diagnostic capacities and highlighted the limitations of conventional lab-based assays, which can take between 1-14 days to receive conclusive results. Current on-site kits have false-negative rates as high as 33%. In an effort to provide accurate, non-invasive, affordable, and rapid Point of Care(POC) testing for COVID-19 and other emerging pandemics, Purdue iGEM is working on a research project called cArgo: A COVID-19 Argonaute mediated saliva-based diagnostic device. The purpose of this project is to study the use of Argonaute proteins found in Thermus thermophilus bacteria (TtAgo) to develop a saliva-based rapid and accurate microfluidic COVID-19 diagnostic device. The diagnostic device works as such: Saliva is inputted into the chip and viral RNA is extracted from it. The RNA is then amplified, converted into double-stranded DNA (dsDNA), and cleaved by TtAgo producing single-stranded DNA fragments(ssDNA). These ssDNA fragments bind to molecular beacons emitting a quantifiable fluorescent signal for conclusive result determination. With limited to no access to wet lab, the team used programming to optimize the biologics of the device, developed CAD models of the microfluidic chip, modeled the adsorption kinetics of chitosan, and developed a heating circuit for the chip. Through the research project, the team consulted experts regarding the device’s design and safety and spearheaded an intercollegiate synthetic biology educational initiative. Coupling the biologics of cArgo with chip barcoding and app integration, the team hopes to revolutionize POC diagnostics while making data more accessible for simultaneous viral detection and contact tracing.
Team:Purdue/Poster
Poster: Purdue
Microfluidic Argonaute Mediated COVID-19 Point of Care Diagnostic Device.
cArgo:"Delivering Global Safety"
To address the issues of current viral diagnostic devices, Purdue iGEM decided to dedicate its 2020 project to the development of a non-invasive rapid COVID-19 diagnostic device called cArgo. The three main objectives that influenced the design of our diagnostic device cArgo are Reliability, Rapid Testing, and Affordability. Using these goals to guide our design process, we set out to design cArgo: An inexpensive Point of Care(POC) diagnostic device capable of producing accurate, easy-to-understand results in less than a day at an affordable cost.
Why Purdue iGEM Masked Up and Joined the Fight Against COVID-19
The COVID-19 pandemic has changed the world. From government-mandated social distancing regulations and lockdown orders to hospitals and healthcare systems overwhelmed with ill patients, the pandemic has transformed our global landscape. With a death count of over one million, COVID-19 has brought grief and distress to the lives of many. Hearing the stories of others, and those of our own members, Purdue iGEM knew it was time to mask up and join the global fight against COVID-19.
Limitations of Current COVID-19 Diagnostic Devices
As of November 9th over 1.26 Million people all over the world have died from the SARS-CoV-2 or COVID-19. Since the genesis of the COVID-19 pandemic, companies, and scientists globally have concentrated their efforts towards developing rapid COVID-19 detection kits as well as a vaccine. Given the urgency of the situation along with governmental pressures, the majority of available testing kits were rushed to the market for production. As a result, the market is inundated with tests that are rapid yet compromised inaccuracy. According to studies conducted by UC Davis, conventional tests not only take between 1-14 days to get results, but they also produce false-negative rates up to 29%. The current tests on the market include nasal swab, saliva-based, and antibody tests, and their efficiency and purposes are outlined in the graphic below:
As indicated by the aforementioned reasons and the diagram above, there is a clear need for a rapid, accurate, and affordable COVID-19 diagnostic test.
As indicated by the aforementioned reasons and the diagram above, there is a clear need for a rapid, accurate, and affordable COVID-19 diagnostic test.
How cArgo Works
Purdue iGEM masked up to address the imminent need for a non-invasive, rapid POC diagnostic device for COVID-19 and other emerging pandemics. Our solution to the problem is our 2-year research project called cArgo. cArgo is a COVID-19 microfluidic POC Argonaute mediated viral diagnostic device. The device utilizes microfluidics to increase runtime via the miniaturization of biologics and improves detection accuracy via the use of an Argonaute mediated nucleic acid detection system. The science behind the device is outlined in the steps below.
- Patient saliva is inputted into the microfluidic chip
- RNA from the saliva is extracted by an embedded chitosan capillary
- RNA is converted to DNA and amplifies producing double-stranded DNA (dsDNA)
- Argonaute cuts the dsDNA to generate single-stranded DNA (ssDNA)
- The ssDNA fragments bind to molecular beacon
- Fluorescence is emitted and quantified via spectrophotometer
- The result is outputted on a smartphone-compatible app.
See the graphic below for a visual demonstration of how the test works:
Safety
The dominant safety concern related to our device is potential exposure to hazardous material. The spit/ swab samples that are collected are potential biohazards so samples should be collected and handled by trained medical professionals. There are also some buffer solutions inside the chip so it is important that nothing leaks since it could potentially be harmful. We initially planned on using the PDMS (Polydimethylsiloxane) but are exploring more environmentally friendly alternatives.
Regulations
To distribute our final product, it must first be approved for sale by regulatory agencies such as the FDA. We talked to Frederick Gates who worked on regulatory affairs at Pfizer for 15 years and he gave us advice on our device. The FDA is one of the key players in regulating medical devices and diagnostics. Under standard FDA review, it would take about 12 months for a diagnostics device to enter the market. The FDA CFR Title 21, Section 820 outlines the requirements for medical devices. From this interview, we made sure to be more aware of FDA regulations and make sure our device follows them as well as introducing a control into the design of our chip and conducting validation assays.
Engineering
Biologics
For efficient and specific detection of RNA we used an integrated Python script to design our biologics. The final code is capable of:
Microfluidics
Complimentary to our biologics part we also designed a microfluidic chip with sample-to-result capabilities. Our initial design was a 75 mm x 25 mm chip consisting of long channels for induced microfluidic mixing through patterned channels and microvalves to actuate fluid control.
After consulting with experts, we developed a second improved version. This consisted of a 25 mm x 25 mm chip with short channels to reduce deadweight and a syringe pump for fluid actuation. Mixing was then determined to be achieved through acoustofluidic methods rather than patterned channels and all reactions were to occur in a single reaction chamber. The new design also allocated space for a control reaction.
Heater Design
Finally, we designed and tested a circular heater capable of maintaining temperatures between 30-90 °C within a 1°C accuracy. Such a device would be capable of maintaining temperatures required for RPA (37-42 °C) and Argonaute cleavage (70-80 °C) of our microfluidic device.
For efficient and specific detection of RNA we used an integrated Python script to design our biologics. The final code is capable of:
- Identifying a suitable target sequence based on %GC content
- Design of guide DNA sequences for TtAgo mediated cleavage
- Design primers suitable for Recombinase Polymerase Amplification
- Design and identify compatible molecular beacon probes based on increasing ΔG
Microfluidics
Complimentary to our biologics part we also designed a microfluidic chip with sample-to-result capabilities. Our initial design was a 75 mm x 25 mm chip consisting of long channels for induced microfluidic mixing through patterned channels and microvalves to actuate fluid control.
After consulting with experts, we developed a second improved version. This consisted of a 25 mm x 25 mm chip with short channels to reduce deadweight and a syringe pump for fluid actuation. Mixing was then determined to be achieved through acoustofluidic methods rather than patterned channels and all reactions were to occur in a single reaction chamber. The new design also allocated space for a control reaction.
Heater Design
Finally, we designed and tested a circular heater capable of maintaining temperatures between 30-90 °C within a 1°C accuracy. Such a device would be capable of maintaining temperatures required for RPA (37-42 °C) and Argonaute cleavage (70-80 °C) of our microfluidic device.
Contribution and Proposed Implementation
Contribution
As our contribution to other iGEM teams, Purdue iGEM designed and developed 3D CAD models of our microfluidic device and made them available to all the teams for their use on our wiki. All of our CAD Models were designed to be assembled either via standard Lithography or 3D printing and laser cutting bonded with industrial adhesives. The following CAD Models developed would be assembled as indicated in the graphics below.
First Iteration Device
Second Iteration Device
Proposed Implementation
Our microfluidic device is currently set up for rapid Covid-19 detection outside of lab conditions. Due to the unique ability of our diagnostic device to operate outside of lab conditions, our device is primarily intended to be used to rapidly screen individuals for Covid-19. The complex nature and the potential risks associated with working with the materials contained in the device means that the device will need to be operated by a trained professional. Using our device will likely require dedicated operators and is thus more suited for commercial or public health applications. This would include use in airports to prevent the spread of infectious diseases or in hospitals to protect vulnerable populations.
As our contribution to other iGEM teams, Purdue iGEM designed and developed 3D CAD models of our microfluidic device and made them available to all the teams for their use on our wiki. All of our CAD Models were designed to be assembled either via standard Lithography or 3D printing and laser cutting bonded with industrial adhesives. The following CAD Models developed would be assembled as indicated in the graphics below.
First Iteration Device
Second Iteration DeviceProposed Implementation
Our microfluidic device is currently set up for rapid Covid-19 detection outside of lab conditions. Due to the unique ability of our diagnostic device to operate outside of lab conditions, our device is primarily intended to be used to rapidly screen individuals for Covid-19. The complex nature and the potential risks associated with working with the materials contained in the device means that the device will need to be operated by a trained professional. Using our device will likely require dedicated operators and is thus more suited for commercial or public health applications. This would include use in airports to prevent the spread of infectious diseases or in hospitals to protect vulnerable populations.
Human Practices
Integrated Human Practices
Over the course of our projects we had the opportunity to interview experts and people affected by COVID, collaborate with other iGEM Teams, and develop an educational YouTube Syn-Bio crash course series.
Collaborations
We also had the opportunity to collaborate with Harvard University, The University of Rochester, Michigan State, Ohio State, William and Mary, University of Maryland, and Cornell.
Educational Outreach
On top of working on our device, we took advantage of the new virtual learning transition to improve access to Synthetic biology education in highschools and in general. Through a collaborative effort with MSU, OSU, Cornell, William and Mary, and the University of Maryland iGEM we develop “Breaking Down synthetic biology”, A Youtube syn-bio crash course series. Specifically for the education of high school students, we developed a google survey check for understandings for each video and developed a sample test curriculum to send out to highschool biology teachers. Two teachers from Tipton High School in Tipton Indiana, who we reached out to were willing to implement our test curriculum. The table below shows the summarized results from our test curriculum. Overall the students' knowledge of the material improved and the difficulty of the videos were just right for high school students.
Modelling
Chitosan Overview
Chitosan—a polysaccharide found in the exoskeletons of insects and crustaceans—is a bioadhesive polymer that attaches to negatively-charged molecules at specific pH values. The cArgo diagnostic test utilizes the bioadhesive properties of chitosan to capture the RNA present within the saliva sample being tested for COVID-19.
Visualization of Chitosan Capillary’s Ability to Change Charge at Different pH to Extract RNA from a Saliva Sample
RNA Absorption Model
We developed a model to determine the RNA capture efficiency from the chitosan capillary. The Langmuir Isotherm Adsorption model was derived from assumed adsorption and desorption kinetics of chitosan and RNA. Several assumptions were made and a constant was derived from previous literature. Since we were unable to experimentally determine the equilibrium constant, we graphed several adsorption models with different equilibrium constants as shown below.
Assumptions:
Capillary Length Model:
Another model was created that related RNA elution to varying equilibrium concentration and length of the chitosan capillary. Since we assumed that Qm was proportional to the surface area of the chitosan capillary, we were able to vary the length of the chitosan capillary. The elution efficiency of chitosan was also found from previous literature so that RNA elution could be determined. Below we have two graphs, one where equilibrium concentration is kept constant to see the relationship between length of the chitosan capillary and RNA elution, and another graph that shows the full relationship between RNA elution, chitosan capillary length, and equilibrium concentration. This model will allow us to find the minimum capillary length required to extract sufficient RNA for detection and a length that will also be suitable for the dimensions of our microfluidic chip.
Chitosan—a polysaccharide found in the exoskeletons of insects and crustaceans—is a bioadhesive polymer that attaches to negatively-charged molecules at specific pH values. The cArgo diagnostic test utilizes the bioadhesive properties of chitosan to capture the RNA present within the saliva sample being tested for COVID-19.
Visualization of Chitosan Capillary’s Ability to Change Charge at Different pH to Extract RNA from a Saliva Sample
RNA Absorption Model
We developed a model to determine the RNA capture efficiency from the chitosan capillary. The Langmuir Isotherm Adsorption model was derived from assumed adsorption and desorption kinetics of chitosan and RNA. Several assumptions were made and a constant was derived from previous literature. Since we were unable to experimentally determine the equilibrium constant, we graphed several adsorption models with different equilibrium constants as shown below.
Assumptions:
- One layer of RNA can bind to chitosan capillary
- There are no interactions between adjacent RNA molecules
- Proportional relationship between surface area and Qm (max number of binding sites)
Capillary Length Model:
Another model was created that related RNA elution to varying equilibrium concentration and length of the chitosan capillary. Since we assumed that Qm was proportional to the surface area of the chitosan capillary, we were able to vary the length of the chitosan capillary. The elution efficiency of chitosan was also found from previous literature so that RNA elution could be determined. Below we have two graphs, one where equilibrium concentration is kept constant to see the relationship between length of the chitosan capillary and RNA elution, and another graph that shows the full relationship between RNA elution, chitosan capillary length, and equilibrium concentration. This model will allow us to find the minimum capillary length required to extract sufficient RNA for detection and a length that will also be suitable for the dimensions of our microfluidic chip.
Results
Medaling Criteria
In the first phase of our project cArgo, we were able to accomplish the following detailed in the chart below
Phase 2 Plan
Biologics of cArgo:In phase 2 we hope to test each of our biologic systems independently and test the whole detection system from the RT-RPA to fluorescent quantification of our sample. We also plan on conducting wet lab experimentation to validate our model for our chitosan capillary and will be developing a model for RT-RPA
Hardware: For our hardware design we are exploring the idea of combining microfluidics along with paper-based assays for autonomous fluid actuation. This integrated design will hopefully be fabricated and tested to confirm the integrity of the device. The portable electric heater will also be used to simultaneously test the biologics as well as the heating circuit design
Education and Outreach: Purdue iGEM plans to continue working on the collaborative educational YouTube series “Breaking Down Synthetic Biology.” We hope to consider the feedback received from our test curriculum implementation at Tipton Highschool and improve our old videos, create new videos, and reach out to more high schools across the US for implementation
Acknowledgements and Sponsors
Acknowledgements
We would like to thank the following people for supporting our project:
Kevin Solomon, Ethan Hillman, Meng Zhou, Charlotte Hoo, Janie Brennan, Rithwik Pallivella, Steven Werely, Jacqueline Linnes, Elijse Pienaar, Saheed Mohammadi, Dr. Fredrick Gates, Nidhi Menon, Mark Aaronson, Radha Venkat, Lorenzo McGhie, and Omar Gillani
Sponsors
References
COVID-19: Global total tops 42 million, death toll surges past 1.14 million.(2020, October 24). Retrieved November 10, 2020, from http://www.orissapost.com/covid-19-global-total-tops-42-million-death-toll-surges-past-1-14-million
He, R., Wang, L., Wang, F., Li, W., Liu, Y., Li, A., . . . Ma, L. (2019, October 02). Pyrococcus furiosus Argonaute-mediated nucleic acid detection. Retrieved November 10, 2020, from https://pubs.rsc.org/en/content/articlelanding/2019/cc/c9cc07339f
Liu, Y., & A. R. (2020, August 17). Challenges and Implications of False Negative COVID-19 Testing. Retrieved November 10, 2020, from https://blog.ucdmc.ucdavis.edu/labbestpractice/index.php/2020/08/17/challenges-and-implications-of-false-negative-covid-19-testing/
What Is COVID-19? (n.d.). Retrieved November 10, 2020, from https://coronavirus.dc.gov/page/what-covid-19
Zhu, X., Zhao, J., Hu, A., Pan, J., Deng, G., Hua, C., . . . Zhu, L. (2020, February 11). A Novel Microfluidic Device Integrated with Chitosan-Modified Capillaries for Rapid ZIKV Detection. Retrieved November 10, 2020, from https://www.mdpi.com/2072-666X/11/2/186/htm
We would like to thank the following people for supporting our project:
Kevin Solomon, Ethan Hillman, Meng Zhou, Charlotte Hoo, Janie Brennan, Rithwik Pallivella, Steven Werely, Jacqueline Linnes, Elijse Pienaar, Saheed Mohammadi, Dr. Fredrick Gates, Nidhi Menon, Mark Aaronson, Radha Venkat, Lorenzo McGhie, and Omar Gillani
Sponsors
References
COVID-19: Global total tops 42 million, death toll surges past 1.14 million.(2020, October 24). Retrieved November 10, 2020, from http://www.orissapost.com/covid-19-global-total-tops-42-million-death-toll-surges-past-1-14-million
He, R., Wang, L., Wang, F., Li, W., Liu, Y., Li, A., . . . Ma, L. (2019, October 02). Pyrococcus furiosus Argonaute-mediated nucleic acid detection. Retrieved November 10, 2020, from https://pubs.rsc.org/en/content/articlelanding/2019/cc/c9cc07339f
Liu, Y., & A. R. (2020, August 17). Challenges and Implications of False Negative COVID-19 Testing. Retrieved November 10, 2020, from https://blog.ucdmc.ucdavis.edu/labbestpractice/index.php/2020/08/17/challenges-and-implications-of-false-negative-covid-19-testing/
What Is COVID-19? (n.d.). Retrieved November 10, 2020, from https://coronavirus.dc.gov/page/what-covid-19
Zhu, X., Zhao, J., Hu, A., Pan, J., Deng, G., Hua, C., . . . Zhu, L. (2020, February 11). A Novel Microfluidic Device Integrated with Chitosan-Modified Capillaries for Rapid ZIKV Detection. Retrieved November 10, 2020, from https://www.mdpi.com/2072-666X/11/2/186/htm