Abstracts of Current Research:
A Proteomic Approach - Identification of Cell Surface Proteins:
We developed a new unbiased approach that provides a global view of cell surface proteins.
We have applied state of the art proteomic tools to collect, separate and then identify in
parallel a large numbers of membranous proteins.
The method, called PROCEED (PROteome of CEllular Exposed Domains) is based on an
enzymatic-controlled proteolysis combined with liquid chromatography and mass spectrometry (LC-MS/MS).
The method is the first step in a more extensive Proteomics package for surface proteome
identification in live cells.
Synaptic proteins and their modulations:
Specific focus on modulating protein-protein interactions between key proteins in the synapse. We study the role of receptor occupancy (muscarinic receptors) and depolarization on protein-protein interactions. Investigating the role of syntaxin. G-protein and presynaptoc receptors in exocytosis and endocytosis.
A molecular basis of exocrine secretion:
- The secretory apparatus in this exocrine system is analysed in molecular terms. The SNAREs that participates in secretion were also detected in the parotid gland proteins and their role in modulating secretion is studied. We manipulate the exocrine gland in vitro and accordingly, we study the response of the gland in changing its gene expression by differential screening.
Neuronal development, synapse formation and maturation in neuronal cell culture system:
The model system is P19 embryonic carcinoma cell line.
The cells undergo differentiation upon induction toward neuronal lineage.
The neuronal phenotype of these cells and their ability to release neurotransmitter
The cells are genetically manipulated using transfection experiments
and the function of key components in synaptic maturation and differentiation
DNA chip technology, 2D-gels and Mess Spectroscopy analyses are
applied for identifying key factors in the process of neuronal differentiation.
A global view on proteins using computational tools:
Novel methods for self-organization of proteins are developed.
We clustered the entire protein database and provided new tools to analyse unidentified proteins.
We expect the hierarchical organization to serve as a basis for for functional predictions.
A statistical-comutational approach for Structural genomics:
Learning the protein space by the structural space serves to create a
statistical model according to which we can predeict proteins to have new folds.
The list of proteins serves the structural community to accelerate the pace
of finding missing folds in the structural.
Functional classifications of proteins:
Clustering and developing distances between proteins that are
based on multi-dimensional information such as annotations of enzymes,
cellular location, sequence homologies and mainly evolutionary relationships.
This approach will lead to functional predictions on unknown proteins and
other biological sequences. We present the result in several interactive web sites.
Biotechnology in HUJI:
- - Biotechnology in HUJI, Scopus Magazine, 2003