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European collaboration project set to track all human cells

Written by ALB on in the category Insights with the tags , , .


Over sixty leading European scientists are uniting in an ambitious project to track every cell in the human body. The FET-Flag LifeTime project will use and develop new technologies to monitor how cells change over time, through ageing and disease. Two Belgian scientists, Prof. Stein Aerts and Prof Chris Marine, both from VIB-KU Leuven, are set to participate in the project. 

The FET-Flag LifeTime project is an unprecedented European scientific endeavor, created to track, understand and predict how the molecular make-up of cells changes over a person’s lifetime. The project aims to create new single-cell technologies to extract and analyze different omics (DNA, RNA, proteins etc.) on a high-throughput scale. The ultimate aim is not just to understand how cells change through ageing, but to gain enough knowledge to enable intervention of human diseases.

Human experts for a human project

The project has already been launched, enabled by a consortium of sixty expert scientists from over 50 European institutions in 18 countries. As the LifeTime project involves many different disciplines, experts have been included from various fields, including single-cell biology, computer science, pathology, mathematics and physics.

If combined with the right models and tools this technology will simply revolutionize medicine. - Marine


Marine: “Single-cell biology is a new field that combines multiple disciplines. This is why being part of this consortium, together with experts in technology development, bioinformatics and systems biology, is so critical and exciting for us.”

The LifeTime consortium will build on the achievements of the Human Cell Atlas (HCA), another new project aiming to create a map of healthy tissues with single-cell technologies. Unlike HCA, LifeTime will attempt to go beyond static tissue maps to track cells over time. It is a vision that can steer both life and health sciences into the future and promote a single-cell innovation ecosystem in Europe.

Aerts: “All of these efforts combined will generate new fundamental insights into the biology of our body, which will in turn provide a better understanding of diseases and ultimately new therapeutic avenues.”

Omics technologies changing lives

Recently, the use of omics technologies has emerged as a vital tool in the life sciences. The technology is evolving rapidly: where omics experiments used to require tens of thousands of cells, single-cell methods now enable scientists to generate an enormous amount of multidimensional data.

Marine: “We have so far only performed a hand-full of single-cell experiments in our lab. Yet it has become immediately obvious to us that the single-cell resolution is a revolution. It is creating a real shift in our understanding of biology and disease. If combined with the right models and tools this technology will simply revolutionize medicine.”

All of these efforts combined will generate new fundamental insights into the biology of our body, which will in turn provide a better understanding of diseases and ultimately new therapeutic avenues. - Aerts


The success of the LifeTime project is heavily dependent on the development of new technologies. Therefore, single-cell technologies will be applied to model systems like organoids and combined with CRISPR-Cas9 and microscopy. Participating scientists also hope to develop new computational strategies, like powerful machine-learning and artificial intelligence methods.

Aerts: “We are keen on inventing new bioinformatics and machine learning algorithms to analyze and model which genes are active in individual cells. A variety of genome-wide information layers or omics data will be generated for millions, perhaps even billions of single cells. We’ll need smart ways of making sense of this data if we want to use it to make valuable predictions for patients, including disease outcome, therapy choice, or prognosis.”

Taken together, the aim is to use these techniques to improve early diagnosis and intervention for human diseases and enable identification of new drug targets and individual patient treatment strategies.

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