Capture, dissemination and analysis of multiscale cell migration data for biological and clinical applications (MULTIMOT)

Project Information

MULTIMOT

Grant agreement ID: 634107

DOI

10.3030/634107

Project closed

EC signature date 27 March 2015

Start date 1 August 2015

End date 31 July 2018

Funded under

• SOCIETAL CHALLENGES - Health, demographic change and well-being

Total cost

€ 2 999 354,00

EU contribution

€ 2 999 354,00

Coordinated by

VIB VZW
Belgium

Periodic Reporting for period 2 - MULTIMOT (Capture, dissemination and analysis of multiscale cell migration data for biological and clinical applications (MULTIMOT))

Reporting period: 2017-02-01 to 2018-07-31

Summary of the context and overall objectives of the project

Cell migration is a fundamental process in topics highly relevant to medicine, including morphogenesis, immune function, wound healing, and cancer metastasis. The study of cell migration therefore has a direct impact on major clinical applications, especially regarding personalized treatment and diagnosis. Over the last few years, cell migration research has benefited enormously from advances in methodology and instrumentation, enabling the wide use of multiplexing and multi-parameter post-processing of cell migration analyses. Yet this progress also caused a largely unmet bioinformatics need, which consists of data management systems, standardization and dissemination infrastructure, and novel algorithms for large-scale data analysis. In order to create these challenges, the MULTIMOT project has assembled a multidisciplinary team of highly accomplished researchers and a successful SME to construct a comprehensive, open and free data exchange ecosystem for cell migration data, based on the development of extensible community standards and a robust, future-proof repository that collects, annotates and disseminates these data in the standardized formats. The standards and repository will be supported by freely available and open source tools for data management, submission, extraction and analysis. Importantly, we will also demonstrate the application of large-scale integrative data analysis from cell migration studies in two specific contexts: guiding personalized cancer treatment based on patient-derived tumour cells, and providing patient-specific diagnosis based on peripheral blood leukocyte motility.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

Within the MULTIMOT project, we have developed the project website, at http://www.multimot.org where an interested person can find all relevant information about the project, its participants, and its goals and objectives. We also list all relevant events and results from the project on this website.
The MULTIMOT project has also created the Cell Migration Standardization Organization (CMSO; http://www.cmso.science) which hosts a community that is developing community-based standards for cell migration researchers. The CMSO has produced the three key standards required for the field (minimal reporting requirements, controlled vocabularies, and a data format), and we have also built the associated software libraries to read from, and write to these formats. At the same time, the central data repository for cell migration data has progressed to beta stage, with a clear view to a first release in a few months (according to schedule). In order to make the most of cell migration data, we have developed a powerful, open source, cross-platform tool called CellMojo (complete with user-friendly graphical user interface) to process the raw images in a migration movie into a large set of individual cell tracks, and we have supplemented this with a considerable update to the CellMissy software (https://github.com/compomics/cellmissy) that allows it to perform downstream analysis of these single cell tracks. On the experimental side, we have firmly established the two model systems for personalized medicine on which the second part of the project will build, and we have started the analysis and processing of data from these model systems. Throughout, we have communicated clearly and openly with the community, predominantly through active interactions via the CMSO.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The overall impact of this project is to timely boost the cell migration research field, including both basic biomedical research as well as clinical research, and to pave the way toward similar efforts in other fields that will benefit from standardizing the recording, quantification and data sharing of dynamic biological processes. We will enable the data acquired during high-content, high-throughput cell migration experiments to reach their full clinical potential, by providing the necessary infrastructure for comprehensive, multiscale analyses. This will be demonstrated by two proof-of-concept studies: guiding personalized cancer treatment through organoid studies, and performing patient diagnosis based on peripheral blood leukocyte motility. Moreover, we will disseminate the bioinformatics outcomes of the project through the creation of an open data exchange ecosystem, consisting of community standards, open software tools and a public data repository, thus maximizing accessibility for the high-content, biologically and medically relevant data obtained in cell migration experiments. Notably, this can also lead to increased commercial products in bioinformatics. This is one of the reasons why our project specifically includes SMEs in the field, as this ensures active participation from the commercial sector in the data exchange ecosystem. The provision of permissively licensed open source software to interact with this ecosystem will also benefit commercial developers, greatly facilitating the development of new types of commercial software services that are aimed at leveraging private experimental results in the context of public data, to answer biological or medical questions for clients. It should also be noted that the data exchange ecosystem we create in this project, together with our innovative applications in personalized health, will provide a new platform for research and innovation in this field. European SMEs will be ideally placed to quickly adopt and adapt these novel approaches into new translational commercial services. Overall, the MULTIMOT project will build on European excellence to further strengthen the EU as the prime location for advanced bioinformatics research in this field. Indeed, the recent transfer of the Cell Migration Gateway from the US to the Geiger lab, combined with the existing leadership in life sciences standards development in Europe, coalesces in a timely fashion with this project proposal, providing a unique opportunity for Europe to take the global lead on cell migration data standardization, dissemination and meta-analysis. This leadership will provide a key incentive for bioinformaticians to come to Europe to work in this promising field. Importantly, this project will have a similar attractive effect on cell biology researchers, who will drive the further adoption of these approaches in clinical settings.

MULTIMOT project schematic overview