What is Live Cell Atlas?

The Live Cell Atlas (LCA) will be made up of comprehensive four-dimensional reference map of cells, with a focus on dynamics of interactive networks between biomolecules and cells, including cell-cell communications. It will contribute as a basis for wide range of life science research, from basics to applied, such as understanding the fundamentals of biological events and acceleration of drug discovery. This proposal covers the strategies to build the scientific and technological foundations that are required to establish the LCA. The LCA project focuses on the dynamics of the interaction networks of wide range of biomolecules that can be found in a cell, however, the dynamics shall be analysed not only in a single cell manner, but also in multicellular systems. The dynamics will be captured in a spatial, temporal, and quantitative manner, contemplating to build up mathematical models that simulate the behaviour of each molecule in the biological system. Deciphering the regulatory system of life and the effort to build up mathematical models that could simulate the biological event with following the uncovered regulatory system would strongly contribute for applied biology area, such as streamlining drug discovery process, as well as to deepen our understanding of rules of life as basic research. For example, it is thought that in the recent drug discovery scene, the major bottlenecks of the clinical test are the insufficient efficacy and safety issues (severe side effects and toxicity). Quantitative visualisation of biological process from the aspect of human science could provide better understanding of clinical condition, which enables to simulate the effects of the candidate drug on the biological target. Such work flow in the drug discovery process would facilitate more streamlined and effective prediction of efficacy and the side effects of the candidate drugs.

Background and present state

Any biological events consist of the dynamic changes of intra-cellular interactome, where the networks of the various types of biomolecules that interact each other within a minute space of a cell, and cell-cell interaction networks. The biomolecules can be categorised into several levels following the canonical central dogma in molecular biology: like nucleic acids (DNA & RNA), proteins, and metabolites. The interaction between these biomolecules occur in both intra- and inter-cellular manner. Qualitative and static information, such as the list of biomolecules involved in certain interaction networks and the nature of interactions, has been relatively well collected; however, the dynamics of interactome and cell-cell interaction have not been well described. This is partially because of that all the conventional analytical methods have been invasive and brought critical damage to the living system; the molecular consequences in living cells have been left almost untouched. In other words, knowledge regarding truly "living" cell has been surprisingly limited, as majority of data have been actually collected from dead cells.

Challenges to be conquered

Here comes the "Live" Cell Atlas. In order to capture the dynamics of interactome and cell-cell communication to decipher the living status of cells and multicellular system, the changes in location and its quantity of the biomolecules and cells should be acquired in a time course manner in living cell(s). The acquired data for LCA have at least four-dimensional information: location (three dimensional), time, and quantity. As each element of LCA would contain such four-dimensional information, whole LCA would have a structure of super multidimensional data. It used to be very challenging to obtain such multidimensional data at single cell level, however, recent dramatic advances in next generation sequencing technology allowed us to quantify mRNA at single cell level. Moreover, the invention of super-resolution microscopy has opened a new door for the quantification of protein dynamics at the spatiotemporal resolution of 100 nm and millisecond order. Now that such state of art analytical instruments are progressively advancing, to obtain above described super-multidimensional data in (a) living cell(s) is becoming more and more feasible research strategy. Development of new technologies to obtain multidimensional quantitative data of cellular dynamics, however, is still a big issue. In addition, in order to integrate such multidimensional big data in a sensible way, mathematical models have to be build up to simulate the state of living cells.

List of proposed research targets

• 1) To develop new technologies for the comprehensive and quantitative analysis of biomolcules in multi-cellular system at single cell level.

  • Technologies involved in the separation of cells following certain categorisation.
  • Technologies that allow to analyse the location and expression status of biomolecules (such as RNAs) in intact living cells.
  • Proteome and metabolomes at single cell level

• 2) To develop technologies that enable to capture spatiotemporal distribution of biomolecules/cells with high resolution. 2) To develop technologies that enable to capture spatiotemporal distribution of biomolecules/cells with high resolution.

  • To develop high-throughput in situ sequencing
  • Multi-channel probe technologies that facilitate the spatiotemporal analysis of various proteins metabolites in a simultaneous manner.
  • Imaging technologies that allow to observe whole multi-cellular system at cellular level resolution (wide view field and high resolution).
  • Development and improvement of imaging technologies required for long time live imaging, such as observation of developmental process, for example, auto focusing and cell tracking.

• 3) Building up mathematical models that facilitate the understanding of dynamics of biomolecules and cells, in a quantitative manner

  • To build up integrative database to store and utilise the various omics and imaging big data.
  • To develop integrative analytical technologies which facilitate to overarching omics and imaging data.
  • To build up mathematical models to visualise the interaction networks of biomolecules and cells in a quantitative manner.

The LCA would bring together wide variety of experts, such as imaging, omics, mathematical modelling, medical science, and biological science in an integrative research environment, where ideally, all the experts could work together under one roof. Such an integrative research centre would promote speedy and effective technology development, as new technological requirements arisen from medical/biological scientists could smoothly be passed to imaging/omics experts. Participation and cooperation of analytical instruments industry to such an integrative research centre would accelerate the development of cutting edge new analytical instruments to worldwide market.

Above described integrative, comprehensive and quantitative analysis of living cells with high resolution is now a kind of worldwide trend. For example, a US led cell biology project, Human Cell Atlas (HCA) aims to catalogue all the human cells via gene expression data; the type, status, and lineage of all the human cells in all the tissues and organs will be stated on a reference map. status and of to build up a reference map of human cells. "Life time initiative" led by EU Horizon 2020 (started March 2019), is another example of this direction. The European initiative focuses on human cells during disease and will pursue to understand how genomes function within cells, and how cells form tissues and dynamically remodel their activities when tissues progress towards disease. This initiative also has an emphasis on the integration of genomics and imaging aiming to deliver single cell level pathology.

Comparing to these oversea big projects, our proposal has a unique aspect which highlights on imaging related technologies where researchers in Japan retain world class reputations. By driving this project forward, Japan would strengthen its presence in bioscience research at worldwide level.