Cytomics, the human cytome project and systems biology: top-down resolution of the molecular biocomplexity of organisms by single cell analysis.
A large amount of structural and functional information is obtained by molecular cell phenotype analysis of tissues, organs and organisms at the single cell level by image or flow cytometry in combination with bioinformatic knowledge extraction (cytomics) concerning nuclei acids, proteins and metabolites (cellular genomics, proteomics and metabolomics) as well as cell function parameters like intracellular pH, transmembrane potentials or ion gradients. In addition, differential molecular cell phenotypes between diseased and healthy cells provide molecular data patterns for (i) predictive medicine by cytomics or for (ii) drug discovery purposes using reverse engineering of the data patterns by biomedical cell systems biology. Molecular pathways can be explored in this way including the detection of suitable target molecules, without detailed a priori knowledge of specific disease mechanisms. This is useful during the analysis of complex diseases such as infections, allergies, rheumatoid diseases, diabetes or malignancies. The top-down approach reaching from single cell heterogeneity in cell systems and tissues down to the molecular level seems suitable for a human cytome project to systematically explore the molecular biocomplexity of human organisms. The analysis of already existing data from scientific studies or routine diagnostic procedures will be of immediate value in clinical medicine, for example as personalized therapy by cytomics.
Valet
G
G
Max-Planck-Institut für Biochemie, Martinsried, Germany. valet@biochem.mpg.de
D003585:Cell Biology / Q000639:trends; D019295:Computational Biology / Q000379:methods*; D003584:Cytological Techniques / Q000379:methods / Q000639:trends; D003592:Cytophotometry / Q000379:methods*; D015195:Drug Design; D005057:Eukaryotic Cells / Q000166:cytology / Q000378:metabolism; D005434:Flow Cytometry; D006801:Humans; D019044:Image Cytometry; D049490:Systems Biology