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Note:
Structural Biology 2018 & STD AIDS 2018
Journal of Genetics and Molecular Biology
|
Volume 2
S e p t e m b e r 0 3 - 0 4 , 2 0 1 8 | B a n g k o k , T h a i l a n d
allied
academies
STD-AIDS AND INFECTIOUS DISEASES
STRUCTURAL BIOLOGY AND PROTEOMICS
&
International Conference on
International Conference on
Joint Event on
A S Kolaskar et al., J Genet Mol Biol 2018, Volume 2
CATEGORIZATION OF METABOLIC
PATHWAYS IN BACTERIA
A S Kolaskar
and
Shweta Kolhi
The Neotia University, India
F
ully sequenced bacterial genomes having more than ≥250 well annotated
metabolic pathways were analysed to find out identical pathways in all
these bacteria in more than 100 well annotated bacteria ≥250 well annotated
pathways and fully sequenced genomes, 42 identical pathways were found
in each of these bacteria. These pathways were called as stage I pathways
or Fundamental pathways. The categorization of pathways was carried out
by comparing compounds for each of the stage I pathways with compounds
from remaining pathways. Pathways having common compounds with stage
I pathways are categorized as stage II pathways. Following the logic of
identifying common compounds between newly categorized pathways and
the remaining pathways, this tool categorizes the metabolome iteratively.
Categorization process is stopped when no common compounds exist
between newly categorized pathways and remaining pathways. This was
termed as metabolic categorization. In each metabolome, non-interacting
pathways can be used to engineer bacteria without affecting other networks/
interacting pathways. The case study of
Escherichia coli
O157, having 433
annotated pathways, shows that 376 pathways interact directly or indirectly
with 42 stage I pathways while 17 pathways are non-interacting. These 376
pathways are distributed in the stage II (285), stage III (76), stage IV (13)
and stage V (two) category. This approach allows a better understanding of
the complexity of metabolic networks. This approach suggests that stage I
pathways could be the most ancient pathways and compounds that interact
with maximum pathways maybe compounds with high biosynthetic potential,
which can be easily identified. Further, it has been shown that interactions of
pathways at various stages could be one to one, one to many, many to one,
many to many mappings through interacting compounds. The granularity
of the method being high, the impact of pathway perturbation on the
metabolome and particularly sub-networks can be studied precisely. This can
help in engineering a bacterium with desired characteristics.
A S Kolaskar has played a key role in shaping India’s
educational direction. Currently, he splits his time
between being the Honorary Vice Chancellor at the
University of Pune in India, the Director of the Bioinfor-
matics Program for the American Type Culture Collec-
tion and an affiliate professor in the School of Com-
putational Sciences at George Mason University. For
the past 13 years, he has served as a professor and as
Director of the Bioinformatics Center at the University
of Pune. His main areas of research include theoreti-
cal molecular biophysics work and bioinformatics. He
also has spent time in various management positions,
from advising PhD students as a chairman of the
post-graduate department at the University of Pune
and as the chief investigator of large research and
infra-structural grants and contracts from the Indian
government. He has also been actively involved with
international scientific organizations from the Tech-
nology Transfer Society to the American Association
for the Advancement of Science and the Maharashtra
Association for the Cultivation of Science. He has im-
plementedmajor reforms in the university governance
during his tenure as Vice Chancellor of the University
of Pune, one of the largest universities in India.
kolaskar72@gmail.comBIOGRAPHY