Opentrons user interviews with University of London

In this issue, we interviewed three of our senior users from the University of London. They used the Opentrons OT-2 liquid handling robot and the open source platform of Python protocol API in the Adaptable and Responsive Nanomaterials Group (AdReNa Group) project. Laboratory automation to accelerate materials innovation.

Stefan Guldin, Associate Professor, Department of Chemical Engineering, University College London ,Leading the Adaptive and Responsive Nanomaterials GroupAdaptive & Responsive Nanomaterials Group (AdReNa Group). Alaric Taylor , Physicist at Imperial College London, Master of Engineering from Cambridge University, PhD in Electrical and Electronic Engineering from University of London; Honorary Researcher and Chief Technology Officer of UCL startup Vesynta. Yann Mamie, Master of Materials Science and Engineering from EPFL, Switzerland .

Opentrons: Please introduce your professional background

Alaric Taylor: I started out as a physicist at Imperial College London. I then entered engineering and gained a master's degree at Cambridge University, followed by a PhD in electronics and electrical engineering at University College London. After that, I joined the AdReNa group and worked with Stefan on nanomaterial self-assembly at the air-water interface as an EPSRC researcher. I was inspired by a former group member (Stuart Ibsen, now a professor at Oregon Health & Science University) and shifted my focus to bioanalytical device development in hopes of supporting children with cancer. AdReNa was an early adopter of OT-1 (and later OT-2) and we strongly trust the Opentrons platform and use it to automate our labs.

Yann Mamie: I have an MSc in Materials Science and Engineering from EPFL (Switzerland) and completed my final research project in collaboration with the AdReNa group at UCL. After graduating, I returned to London and rejoined a research and development project supported by UCL start-up Vesynta, where we are developing laboratory automation of biological sample processing for therapeutic drug monitoring (TDM). Innovative uses.

Stefan Guldin: I studied applied physics at the Technical University of Karlsruhe and the Technical University of Munich, with a focus on soft matter. During my PhD studies, I went to the University of Cambridge to conduct research on organic self-assembled nanostructured inorganic materials. Subsequently, I joined EPFL in Switzerland for postdoctoral research, studying the interaction of liquid crystals and nanoparticles in biosensing applications. At UCL, I am an Associate Professor in the Department of Chemical Engineering, leading the AdReNa research group and teaching molecular engineering and soft nanotechnology. I am also co-director of the Soft Materials Network at UCL, I am actively involved in the Center for PhD Training in Transformative Pharmaceutical Technologies, and I am developing a new MSc in Digital Fabrication of Advanced Materials.

Opentrons: Please introduce your research project

Stefan Guldin: We are using molecular self-assembly to create materials that can interact with their environment – ​​most prominently for sensing chemicals or biomarkers. We also apply our research results to functional coatings, such as self-cleaning applications, as well as coatings with optical properties. Our work is driven by improvements in high-throughput sample preparation, materials characterization and analytical capabilities.

Opentrons: How do you use OT-2 to fit into your workflow?

Yann Mamie: We are extending the pipetting capabilities of Opentrons OT-2 by tracking the liquid volume and liquid height in the container. By using our custom function, we can track the meniscus of a liquid and determine the depth of aspiration. With this kind of consistent and reproducible data results, we can drive the implementation of advanced protocols. We are also using laboratory equipment specifically designed and manufactured for the OT-2.

Stefan Guldin: Custom pipetting can help disperse compounds more quickly or make them more soluble. Aqueous two-phase systems are a hot topic, and custom pipetting is very useful for these biphasic mixtures, where you can pipet in one phase and disperse in the other. We also checked the accuracy of the pipetting as a position measurement: we found that the Opentrons OT-2 are accurate, and if you are dealing with solutions of regular viscosity, the position of the pipette in the well is not that important for accuracy.

Alaric Taylor: It is very important to be grateful to our predecessors and peers for their willingness to develop open source. I hope our development outlasts our current applications and potentially brings more research momentum to people on the other side of the world.

Opentrons: Have you considered using other automations?

Yann Mamie: We are performing automatic error propagation calculations for each pipette stroke of the protocol in order to minimize errors when creating optimized pipetting protocols. If we know that there is some uncertainty in pipetting, we can track the volume of liquid contained in each well and the uncertainty in the volume of liquid transferred from one well to another. With simple settings within the protocol, we can visually view liquid volumes and concentrations across all wells.

Opentrons: Please describe your research project

Stefan Guldin: We use OT-2 in conjunction with qTLC – our web application that quantifies compounds by thin layer chromatography. Already used in 37 countries on six continents, it supports analytical chemistry in a very simple way. Users follow a protocol for isolating molecules, taking images from their smartphones and uploading them to a server, where we then help them analyze and quantify their compounds.

Alaric Taylor: The ability to automatically handle liquids on a user-friendly, code-flexible platform such as the OT-2 supports many proof-of-principle studies in our laboratory. Applications range from controlled and reproducible bioanalytical sample preparation to screening the chemical composition of reactions. Based on these competencies, departments within the Faculty, the University as a whole, and other research institutions frequently ask us to collaborate with them.

Opentrons: What else would you use the OT-2 for?

Stefan Guldin: We are leading an NIHR-funded project called ChromaDose, which aims to establish a new method for assessing the concentration of chemotherapy drugs in liquids. Current oncology dosing is based on body surface area, but this has nothing to do with individual metabolism. This means that the extra concentration in patients is highly variable, especially in children. This is a huge problem because it can lead to serious side effects and lower efficacy. We are trying to use Opentrons to automatically analyze blood samples in a relatively short time and then quantify them. This helps doctors assess the concentration of chemotherapy drugs in patients, allowing for more accurate dosing. The Opentrons platform is very important for us to realize program automation, and it provides us with good prototyping services.

Yann Mamie: We also created a debugger to simulate the Opentrons protocol and create easy-to-read logs. In addition, it provides guidance on laboratory equipment requirements and their respective positioning and content. Users simply enter the file of the corresponding pipetting protocol and any custom labware definition folders. Here are two examples of printout obtained using this debugger:

Opentrons: What was it like to get your OT-2 up and running?

Yann Mamie: When I came here in September 2020, OT-2 was already here. I started playing around with it and used the Opentrons Python API to figure out the encoding of the protocol. I've been developing custom features such as meniscus tracking, video, mixing or transfer feature types, as well as designing some custom labware for our own vessels.

Opentrons: What challenges have you encountered while using the OT-2?

Alaric Taylor: The OT-1 is our first pipetting robot and we love it! But when OT-2 came out, we realized that all the engineering was to improve the user experience, from mechanical parts to software upgrades. Updating the Opentrons Python API has been a challenge for us as we identify and debug bugs that existed in the previous protocol. We know this because we are using an actively developed tool, and we appreciate the enhancements these API updates bring to OT-2's general functionality.

Opentrons: Will students at your university use OT-2?

Stefan Guldin: In our new Master's program in Digital Fabrication of Advanced Materials, we want to teach a new generation of engineers a holistic approach that combines materials fabrication with high-throughput characterization and data analysis. We will have eight Opentrons robots in our lab, and students will solve problems in a fully integrated way. They will work to design and plan experimental content; generate large samples using Opentrons robots; collect data through high-throughput characterization; apply statistical methods, including machine learning, to analyze the data; and map the experimental domain in an iterative fashion.

Opentrons: Can you share your thoughts on open source sharing

Stefan Guldin: We think we can have the greatest positive impact on this field by sharing our tools. We're trying to create something that works for us and then communicate and check it out with the community. We are firmly committed to open source our group's hardware and software development. That's why we share all our work on the GitHub platform. Ultimately, using, adopting and sharing experiences helps us all improve - and since Opentrons believes in this and provides tools to help make it happen, we really love it.