The Molecular Nose
Mammalian cells use more genes to regulate biological processes than to carry them out. These include all fundamental processes such as cell growth, differentiation, survival, metabolism and the ability to sense and produce the correct complement of biomolecules to communicate with the environment. Complexity is further enhanced by the organization of biological processes as networks. Understanding the behaviour and responses of such complex networks will be crucial to solve eminent questions in biology.
To address this need we will build a multiplexed sensor platform that can assess and quantify dynamic changes in the functional state of biochemical networks in mammalian cells, and use these data to reconstruct cell network interactions and their dynamic behaviour on a systems wide level. The concept underpinning this platform is fundamentally different from existing methods used in the biological sciences to assess cell function, and similar to the “Electronic Nose”, where an array of sensors is first trained with individual stimuli to establish a library of response patterns which subsequently are used to deconvolute complex inputs.
The “Molecular Nose” will monitor the outputs of several hundred network components simultaneously in cell populations or single cells using artificial transcriptional reporters, and design a software framework and algorithms for their functional analysis. The Molecular Nose will be built in three versions. One will be constructed using molecular biology tools, and will permit to use a large array (up to 1000) of sensors. However, it requires the cell being lysed for the measurement as the detector is outside of the cell. This version will be particularly useful for training the system and establishing a large library of response patterns. The second version will be built by integrating both individual sensors and their corresponding detectors onto bar-coded nanoparticles which will be introduced into cells and read using surface enhanced resonance Raman scattering spectroscopy. This setup will use a smaller number of sensors (up to 30), but can be used to monitor responses in living cells in real time. In parallel we will develop methods for the controlled introduction of these particle libraries into cells. The third version is the stable integration of a plasmid based sensor library into the embryonic mouse stem cells with the aim to generate a transgenic sensor mouse. The stem cells also can be used for organotypic cultures and in vitro differentiation systems.
The Molecular Nose will enable the systematic testing and rational interpretation of the behaviour of cellular networks. The technique is generic with a wide range of applications in both single cells and cell populations, including eminent biological problems such as the analysis of drug effects and prediction of side effects; stem cell differentiation with a view to eventually control differentiation; cell fate specification in order to support tissue engineering; genetic and biochemical networks for the production of desired proteins and metabolites by synthetically engineered pathways; and the investigation of adaptive network responses and evolution. Currently, we are lacking efficient experimental tools to analyse these complex interactions.
The overall objectives of this proposal are:
<![if !supportLists]>· <![endif]>to construct and establish a Sensor-Detector platform in single cells, cell population, tissues and eventually mice
<![if !supportLists]>· <![endif]>to design an Analyser and associated algorithms that will decode the cellular responses measured by the Sensor-Detector
<![if !supportLists]>· <![endif]>to prove application of this technology for the measurements of drug responses and signalling network adaptation
The Molecular Nose is a generic tool. It permits to gain mechanistic understanding on how cells process signals, and by tractably linking a specific signal input with biological responses allows the deconvolution of complex inputs in single cells, tissues and even whole organisms. Each of the underpinning workpackages (WP 1-6), advances the state of the art in its own specialised field, and when combined (in WP7) provides a generic platform technology that is applicable to all biological and biomedical questions where dynamic changes in cellular signalling networks play a central role. The applications are broad and reach all the way from basic to applied research including e.g. the analysis of (i) stem cell differentiation with a view to later control differentiation; (ii) inductive processes in cell fate specification in order to support tissue engineering; (iii) genetic and biochemical networks for the production of desired proteins and metabolites by synthetically engineered pathways; (iv) testing and prediction of responses to drugs and environmental influences, such as nutrients, toxins, radiation, etc. Thus, the beneficiaries include basic researchers in the fields of biology, biomedicine and pharmacology as well as industrial researchers. The ability to test and eventually predict drug responses, effects and side effects will be of particular interest to the pharmaceutical and biotech industry.