Autobiotip aims at awakening the bio-Atomic Force Microscope (Bio-AFM) to cells populations. We propose a method for automating force measurements that will generate massive data on at least 1000 cells. Traditional biophysical analyses and machine learning methods will then be adapted to extract mechanobiological information from the large amount of data generated and to access the heterogeneity of cell populations.

Task 1.1: Development of cell chips compatible with automated AFM analysis

Task 1.2: Development of the software for automatic movement of the AFM tip from one cell to another

Tasks 1.3: Study of the biophysical parameters that induce the heterogeneity of AFM mechanical measurements.

Task 2.1: Development of a process to automate the analysis of the large quantities of data produced, by the classical AFM data analysis softwares.

Task 2.2: Analysis by supervised learning (a priori)

Task 2.3: Extraction of signatures by unsupervised learning (without a priori)

Task 3.1: Measure and analyze the biophysical properties of cells synchronized in the different phases of the cell cycle

Task 3.3 Deconvolution of data obtained from unsynchronized cells

- Severac C.,, Proa-Coronado S., Formosa-Dague C., Martinez-Rivas A., Dague E. 2020
Automation of Bio-Atomic Force Microscope Measurements on Hundreds of  C. albicans Cells
Journal of Visualized Experiments e61315 URL: https://www.jove.com/video/61315 doi:10.3791/61315

- Proa-Coronado S., Severac C., Martinez-Rivas A., Dague E. 2019
Beyond the paradigm of nanomechanical measurements on cells using AFM: an automated methodology to      rapidly analyze thousands of cells.
Nanoscale Horizons, DOI : 10.1039/c9nh00438f

Researchers implied in the project

The consortium brings together researchers from 2 LAAS-CNRS teams (ELIA and DISCO), a research engineer from ITAV-CNRS, a researcher and a Post-Doc fromIPN-CIC (Mexico), and the BIOSOFT joint laboratory.

Etienne Dague Coordinator develops biophysical thematics using AFM for the study of living organisms. Member ofthe ELIA team of LAAS-CNRS, he is the author of 76 publications (H index 33, >3000 citations). He has been coordinator of an ANR JCJC project (2011-2014); Head of an interdisciplinary project team at ITAV-CNRS(2011-2016); Coordinator of an IDEX transversality project (2015-2017); Coordinator of an ECOS-Nord collaboration (2015-2019); Scientific head of ANRGraphics (avril 2018-mars 2021).

Emmanuelle TREVISIOL is a full-time researcher at LAAS-CNRS in the ELiA Team. She received a master of science degree in Biochemistry at the J. Fourier University (Grenoble, France) and a PhD in Bioorganic Chemistry (Grenoble,France).Emmanuelle has a strong background in Biochemistry and Bioanalysis. Her main experiencecovers the field of nucleic acid chemistry, bioconjugation and biofunctionalization for molecular diagnosis purpose. Emmanuelle devoted alarge part of her research activities to biomolecular interaction detection and biosensors. In Autobiotip project, Emmanuelle will provide expertise inbiochemistry, surface biofunctionalization and particularly in the design, production and characterization of cell microarrays.

Christophe Vieu will be involved in the supervision of the fabrication of individual cell arrays and their optimizationfor the interest of the project and will contribute to the analysis of the parameters of categorization extracted byAutomatic Learning procedures of AFM Data and their confrontation to biophysical models.

Marie-Véronique LE LANN est professeur au département de Génie Electrique et Informatique de l'INSA de Toulouse, et chercheuse au LAAS/CNRS dans l'équipe DISCO - DIagnostic Supervision et COnduite. Elle est en charge des relations partenariales et industrielles et de la formation continue au GEI. Elle est aussi Membre de la Commission des Titres d’Ingénieur (CTI).

Childérick Severac
Adrian Martinez-Rivas
Sergio Proa-Coronado
Ophélie Thomas-Duchemin

The Biosoft joint laboratory (ANR LabCom; LabComConsolidation) has developed an automated technology for the deterministic immobilization of livingcells on microarrays. Its expertise will be essential to prepare the cells according to defined patterns (deliverable 1). Biosoft is a joint laboratoryfunded by the ANR between the LAAS-CNRS and the company Innopsys which shows the effective nature of the collaboration.

Secondly, the participation (without funding) of the Computer Science Research Center (CIC) of the IPN (Mexico City) provides us with the expertiseand programming skills required to automate AFM tip moves (deliverables 2 and 5). A. Martinez (CIC) and E. Dague (LAAS-CNRS) supervised S. Proa's thesis ininternational co-supervision (2017-20) and were recipients of ECOS-NORD funding for the mobility of researchers and PhD students (2016-20). Once the protocolshave been established (deliverable 4), data will be acquired, in large numbers, thanks to a collaboration with ITAV-CNRS which has 2 AFMs (deliverable 1.3.1 to1.3.5).

 Finally, the DISCO team of the LAAS-CNRS will bring its expertise in automatic learning to analyse the data from automated AFM measurements, withoutany a priori (deliverables 2.2.1, 2.2.2; and 2.3.1 and 2.3.2). The DISCO team has an history of collaboration with C. Séverac and ITAV since 2009 (2009-13,Fondation Innabiosanté and 2012-15, Toulouse métropole).