SARS-Cov-2 sensor for rapid sensitive virus detection
| Reference number | |
| Coordinator | SureCapture Technologies AB |
| Funding from Vinnova | SEK 300 000 |
| Project duration | July 2020 - June 2021 |
| Status | Completed |
| Venture | Innovative Startups |
| Call | Innovative Startups step 1 spring 2020 |
Important results from the project
** Denna text är maskinöversatt ** Our objective has been to develop a new cost-effective and sensitive test method for the detection of intact active SARS-CoV variants, including the most contagious variants. This is based on Reversible Self-Assembled Monolayers (rSAM) as a reversible surface modification method for strong virus binding. Coupling with SPR (surface plasmon resonance) and LSPR detection allows ultra-sensitive real-time virus detection. The following subgoals have been partly achieved with promising results, 1) the rSAM receptor and 2) transfer to SPR / LSPR.
Expected long term effects
** Denna text är maskinöversatt ** With short peptide epitopes, we have succeeded in constructing a semisynthetic receptor that binds SARS-CoV-2s spike protein with an affinity exceeding that measured with host cell receptor ACE2 as measured with surface plasmon resonance (SPR) and localized surface plasmon resonance technology (LSPR). The results have been presented at three international conferences (Affinity 2021, Biosensors 2021, Labroots 2021). The system is now optimized for testing on RBDs and VLPs from newer mutants (eg the delta variant) and later on patient samples.
Approach and implementation
** Denna text är maskinöversatt ** The implementation of the project has entailed some changes with regard to staffing and timing of the various project steps. A break in the work occurred due to a change of staff after about 6 months. This led to a certain delay and modified focus of the project. Despite this, important progress has been made and the collaboration with Linköping Universitet has been able to start as planned. This is now progressing according to plan and we therefore hope to be able to achieve validation of the sensor prototype on patient samples in the near future.