A three‐symbol code for organized proteomes based on cyclical imaging of protein locations

Abstract

Background: A major challenge in the post genomic era is to map and decipher the functional molecular networks of proteins directly in a cell or a tissue. This task requires technologies for the colocalization of random numbers of different molecular components (e.g. proteins) in one sample in one experiment. Methods: Multi‐epitope‐ligand‐“kartographie” (MELK) was developed as a microscopic imaging technology running cycles of iterative fluorescence tagging, imaging, and bleaching, to colocalize a large number of proteins in one sample (morphologically intact routinely fixed cells or tissue). Results: In the present study, 18 different cell surface proteins were colocalized by MELK in cells and tissue sections in different compartments of the human immune system. From the resulting sets of multidimensional binary vectors the most prominent groups of protein–epitope arrangements were extracted and imaged as protein “toponome” maps providing direct insight in the higher order topological organization of immune compartments uncovering new tissue domains. The data sets suggest that protein networks, topologically organized in proteomes in situ, obey a unique protein‐colocation and ‐anticolocation code describable by three symbols. Conclusion: The technology has the potential to colocalize hundreds of proteins and other molecular components in one sample and may offer many applications in biology and medicine. © 2007 International Society for Analytical Cytology.

On the origin of cell functions encoded in the toponome

“…Illustration of the topological hierarchies of proteins within the toponome. L, lead protein (common to all CMPs of a CMP motif); A, absent protein signal (absent in all CMPs of a CMP motif); W, wild card protein signals (proteins that are variably associated with the (L) and the (A) proteins of a CMP motif) (from Schubert, 2007a). or, after introducing a threshold for each signal, as a combinatorial binary code. In either of these cases all existing signal combinations (indicating protein clusters) can be assembled in what we call a toponome map, visualizing the location of given protein clusters present in groups of pixels or voxels, referred to as combinatorial molecular phenotypes (CMPs) (Fig.…”

“…By using the three symbols code (LAW, Fig. 2) (Schubert, 2007a), differences of cell states and cell types can be readily identified in studies comparing large experiments, or, diseases with normal conditions. The TIS technology is unparalleled when it comes to the colocalization of a very large number of proteins using photonic microscopy.…”

“…It is evident that these protein clusters have in common the proteolytic enzyme CD13 as lead protein, while the other shown proteins are variably associated with the lead protein in the different clusters (present or absent). The common feature of all clusters can be expressed as a three symbol code (Schubert, 2007a) (a) Spherical cell displaying the cluster (colocation of CD13, CD44, CD138, CD71CD56) (a, arrow, dark blue colour). Note that this node (cluster) corresponds to the protein cluster "dark blue" displayed by cells in Fig.…”

Multimolecular Analysis of Stable Immunological Synapses Reveals Sustained Recruitment and Sequential Assembly of Signaling Clusters

“…We tested the frequencies of co-localization of pZAP70 and pSLP76 in synaptic areas that were also positive for pLAT and CD3 (pCD3[Y5]). The use of binarized imaging data resulting from the thresholding of fluorescent signals was not only useful in evaluating low-intensity signals of individual markers, but could also be used to generate and quantify CMP motifs (25,42,43), patterns of localizations of several markers within one spot (pixel). Although it is conceptually easier to think of a CMP motif as a protein complex, MELC analysis does not provide data on actual binding between proteins-only on shared locations.…”

An information theoretic thresholding method for detecting protein colocalizations in stacks of fluorescence images

“…Details regarding this technology and the tasks associated with the data obtained by using it are discussed in Cottingham (2008) and Sage (2009); for biological applications of MELK Technology, see Schubert et al (2009), Schubert et al (2008a,b), Bode et al (2008) and Schubert (2007b). This technique produces a whole stack of intensity images of one and the same biological object (for example, a slice of nervous tissue), each image in the stack corresponding to one particular protein (or any other biologically relevant molecule of interest).…”