Publications

BACKGROUND: Optimization of gene therapy protocols requires accurate and non-invasive quantification of vector delivery and gene expression. To facilitate non-invasive imaging of gene expression, we have genetically engineered 'artificial receptors', i.e. membrane proteins that bind (99m)Tc-oxotechnetate ((99m)TcOT) via transchelation from a complex with glucoheptonate. The latter is a component of a widely used clinical imaging kit.

METHODS: The engineered marker proteins were designed as type I and II membrane proteins and consisted of (1) an (99m)TcOT-binding domain, metallothionein (MT), and (2) a membrane-anchoring domain. Engineered constructs were used for transfection of COS-1 and 293 cells; the expression of mRNA was verified by RT-PCR.

RESULTS: Immunofluorescent analysis, cell fractionation and immunoblotting revealed expression of marker proteins on plasma membrane. Transfection of cells resulted in strong positive staining of plasma membrane with anti-His-tag antibodies. Scintigraphic imaging in vitro confirmed the ability of transfected cells to bind (99m)TcOT. The fraction of bound radioactivity reached a peak (3.53%) when 0.93 MBq (99m)TcOT was added to transfected COS-1 cells. The experiment-to-control signal ratio was equal to 32 at the same added dose.

CONCLUSIONS: (1) Both types of engineered 'artificial receptors' were expressed on the surface of eukaryotic cells; (2) marker proteins were functional in binding (99m)TcOT; and (3) type II membrane proteins were more efficient in binding (99m)TcOT than type I proteins. We anticipate that the developed approach could be useful for 'tagging' transfected cells with (99m)TcOT enabling imaging of tracking in vivo transduced cells or cell therapies.

By integrating functional genomic and proteomic mapping approaches, biological hypotheses should be formulated with increasing levels of confidence. For example, yeast interactome and transcriptome data can be correlated in biologically meaningful ways. Here, we combine interactome mapping data generated for a multicellular organism with data from both large-scale phenotypic analysis ("phenome mapping") and transcriptome profiling. First, we generated a two-hybrid interactome map of the Caenorhabditis elegans germline by using 600 transcripts enriched in this tissue. We compared this map to a phenome map of the germline obtained by RNA interference (RNAi) and to a transcriptome map obtained by clustering worm genes across 553 expression profiling experiments. In this dataset, we find that essential proteins have a tendency to interact with each other, that pairs of genes encoding interacting proteins tend to exhibit similar expression profiles, and that, for approximately 24% of germline interactions, both partners show overlapping embryonic lethal or high incidence of males RNAi phenotypes and similar expression profiles. We propose that these interactions are most likely to be relevant to germline biology. Similar integration of interactome, phenome, and transcriptome data should be possible for other biological processes in the nematode and for other organisms, including humans.