Giving Quantitative Meaning to Microscope Images

The new program can be used by multiple researchers to answer questions and test hypotheses about protein expression, cell morphology, and cellular organization in tissues and cell cultures.

BioSig, which was developed by a multidisciplinary group at the Lawrence Berkeley National Laboratory (Berkeley, CA, USA), gives quantitative meaning to microscope images in a way that promises far-reaching consequences for the field called ‘phenomics'. Phenomics deals with the proteins a genome codes for--how they are regulated and expressed in the cell and how they interact with each other to condition the cell's responses to outside stimuli and a changing microenvironment.

Researchers in the biological sciences have always faced problems due to the complexity of the systems under investigation. Any biological system exhibits significant variations to begin with. Coupled with technical variability in sample preparations, image representation becomes quite heterogeneous: staining is non-uniform, images are noisy, and subcellular compartments can overlap each other.

Each compartment within the cell must be clearly separated from its neighbors in a process called segmentation. BioSig incorporates segmentation program that removes noise and clearly outlines each cell or nucleus in 2-D images as readily as in 3-D ones. The method is completely automatic and does not require human interaction, as other segmentation programs do. The process recognizes curved sections of the envelopes or membranes of nuclei. By calculating individual ‘centroids' from this information, adjacent objects can be distinguished even when they overlap. With further calculation, the location and magnitude of expressed proteins--identified by specific antibodies--can be resolved with great precision.

Two applications that illustrate BioSig's ability to track different variables in complex situations were presented in the July 2002 issue of Computer. One was an in vitro study of how colonies of human breast cells are influenced by the extracellular matrix, while the other was an in vivo study that looked at two important regulatory proteins interacting to control DNA damage response in mouse mammary cells. In the in vitro study, BioSig allowed the researchers to establish the pathways by which radiation and a protein modifier, acting separately and together, affect the formation of crucial structures in human breast cells. In the in vivo study, BioSig was used to quantify a link between an extracellular factor and intracellular response in mouse mammary glands.

BioSig's developers feel that by enabling researchers to save and access large amounts of quantitative information in images, BioSig makes them useful in ways never before practical.





Related Links:
Lawrence Berkeley National Laboratory