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Molecular genotype-based characterization of isolates (differing in
sequence even with a single-base) within a species is a vital
essence for classification of Life in present information-rich age
of transparent Biology. The most common technology must be the
ribosomal-DNA sequencing but is not sufficient nor suitable for
identification of species. For such purposes, our laboratory have
invented a realistic solution for genome identification and termed
as Genome Profiling (GP) which uses TGGE (Temperature Gradient Gel
Electrophoresis) analysis of random-PCR products
(J.
Biochemistry, 2000).
We have refined GP to quantitatively measure the closeness between
two unidentified genomes and further improved by introducing its
miniaturized-version, giving a 100-fold high-throughput productivity
by drastically reducing the time, operation effort and cost of the
system (Electrophoresis,
2000). A development and successful operation
of web-based databases for GP (Genome
Biol., 2002)
makes this technique further distinct from known molecular
techniques. GP is currently considered to have the most optimal
nature for identification of species since it can reproducibly
reduce a huge amount of genome information to a manageable size and
can extract a sufficient amount of required information. In terms of
the reduction of labor time (<4h), relatively low running cost (<$3
per sample), parallel and easy application, and reliable results, GP
can be considered a powerful, potential tool for the routine
identification of species. Here we believe, GP will lead to a
revolutionary improvement in species authentications studies and
must be beneficial in many fields of biology, including agricultural
or microbe-related disciplines and particularly, in clinical
microbiology in developing countries, land of rich-of-clinical
isolates but limited in resources.
We are interested to use the GP in following research proposals:
Rapid detection, identification, genetic characterization and
forensic attribution of high-priority clinical strains including
viruses (e.g, Influenza-A), bacteria (e.g.
Salmonella) or yeast (e.g. Candida) pathogens.
Identification and evaluation of genetic diversity in inter-
and intra-species of medicinal plants
(e.g, Withania somnifera, Plumbago zeylanica).
Introduction of multi-micro TGGE for high-throughput genome
analysis. |
