Transcript DISCOVERY OF NEW ENZYMES IN EXTREME ENVIRONMENTS …

DISCOVERY OF EXTREMOZYMES IN
METAGENOMIC SEQUENCES
RITA DESAI
School of Informatics, IUB
Capstone Presentation,
May 22, 2009
Advisors : Yuzhen Ye and Sun Kim
Overview
 Extremozymes & Metagenomics
 Challenges and bottlenecks…
 Flow chart of the computational tool
 Results so far..
 Future prospects
Why Extremozymes?
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What are extremozymes?
– Enzymes isolated from organisms inhabiting unconventional ecosystems
(Biotechnology (N Y). 1995 Jul;13(7):662-8)
Extremozymes expand the limits of biocatalysis
– The information acquired from the study of extremozymes makes it possible
to modify enzymes to improve their ranges of stability and activity (for
industrial and medical applications)
However, the organisms living in extreme environments are hard to be cultured, so
they are less well studied as compared to other organisms.
– Vast majority of microbes uncultured –>99% of soil organisms; >50% in human
gut; >99.9% in seawater and thus cannot understand the community as a
whole.
Metagenomics enables sequencing of an entire microbial community without the
need to culture them
Why Metagenomics?
Metagenomics as concept and tool??
the genomic analysis of an
assemblage of organisms
“meta”= Greek for transcending; more comprehensive.
Metagenomics constitute a challenging domain to discover new enzymes from
diverse niches.
Two early metagenomic projects: Acid Mine drainage project and Sargasso sea metagenomic
survey.
Bottlenecks and Challenges
• Bottlenecks
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No robust metagenomic screening methods (experimental methods) to directly retrieve
enzymes of interest . Low biomass yields and low cell number that hinder cloning. Also,
Experimental methods are exhaustive and expensive.
• Challenges
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Over 3.3 million non redundant protein sequences (up to 40% being hypothetical) have
so far been predicted and deposited in electronic databases and only 8% correspond to
extremophiles. Many more enzymes still need to be discovered.
Goals
• The objective is to discover novel extremozymes
in
metagenomic sequences that may exhibit unique sequential
and structural features.
Research Design
• Collecting known extremozymes from the literature
– Ref: Ferrer M., Golyshina O., Beloqui A., Goylshin P. Mining enzymes
from extreme environments (2007). Current opinion in Microbiology
10:207-214.
• Homolog search of extremozymes
– Search against IMG and IMG/M databases by BLAST
– Multiple sequence alignment using CLustalW tool –hits with cutoff of
E values smaller than 10-20.
• Molecular modeling
– Homology modeling using Modeller to predict 3D structures
Examples Of Extremozymes Identified In
Metagenomic Sequences
Enzyme
Sample and ID
Identity
Esterase
Acid mine drainage(2001201141)
92
Soil(2001288613)
33
Human gut (2004033831)
34
Sludge (2000613520)
83
Whalefall (2001431860)
78
Whalefall (2001496341)
73
Sludge(2000495850)
67
Sludge (2000145560)
44
Uranium (2007096904)
43
Catalase
Isocitrate dehydrogenase
Threonine dehydrogenase
Esterase
• Esterase belong to various classes: family II with motif GDSL, serine
hydrolases with motif GXSXG, and family VIII with motif SXXK.
• Serine hydrolase family II: characteristic motif Gly-X-Ser-X-Gly, catalytic
triad Ser-119, Asp-248 and His-276.
• Ref : Olga V., Golyshin P., Timmis K., Ferrer M.,The pH anomaly of
intracellular enzymes of Ferroplasma acidiphilum.(2006) Environmental
Microbiology, 8(3) : 416-425
Structural Modeling
Predicted esterase from extremophile
ferroplasma acidiphilum
Predicted esterase from AMD
(ID: 20012011141) with 92%
identity
The structures were modeled using known structure (PDB ID 1EVQ)
(39%identity) by modeller, in which the active sites (ser156, asp251, his281) are
conserved.
Motif Analysis
Motif gly-X-Ser-X-Gly, characteristic of
serine hydrolase family found conserved in
homologs of esterase.
gly-X-Ser-X-Gly
Catalase
• Examples of catalase homologs discovered in metagenomic sequences
– Sludge /US phrap community with ID 2000613520 , with 83% sequence identify
– Whalefall (ID 2001431860) with 78% sequence identity to enzyme
• Using structure (PDB ID: 2ISA) as the template, 3D models were built for
the catalase homologs discovered in various metagenomic communities.
• Ref: Lorentzen E., Moe, H., Willansen N.Cold adapted features of Vibrio
salmonicida catalase: characterisation and comparison to the mesophilic
counterpart from Proteus mirabilis.(2006) . 10:427-440
Structural Models of Predicted Catalases
a) The
experimental
structure of
catalase (PDB ID:
2ISA) used as the
template
b) Predicted structure of a
homolog identified in sludge
phrap assembly (ID: 2000613520)
with 83% sequence identity.
c) Predicted structure
of a homolog from
whale fall sample (ID:
2001431860) with
78% sequence
identity.
Isocitrate Dehydrogenase
Isocitrate dehydrogenase structure
(PDF ID: 1J1W).
Predicted Isocitrate dehydrogenase
structure from sludge phrap assembly( ID
2000231240) with 65% identity
Ref: Maki M., Takada Y. Two Isocitrate dehydrogenase from a psychrophilic
bacterium Colwellia Psychrerythrea. (2006). Extremophiles 10:237-249.
Alpha Glucosidase
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A membrane bound alpha glucosidase (531 amino acids) isolated from
extremophile Ferroplasma acidiphilum was used as the query in homolog search
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In case of glucosidase, the carboxylic side chains of glutamic and aspartic acids are
involved in catalysis, but this novel glucosidase from extremophile has a catalytic
center involving threonine-212 and histidine-390.
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Identified homologs include a protein (ID: 638394706) from ferroplasma
acidarmanus , which has 99% sequence identity.
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Ref: Ferrer M., Golyshina O., Plou F., Timmis K., Golyshin P. A novel alphaglucosidase from the acidophilic archeon Ferroplasma acidiphilum strain Y with
high transglycosylation activity and an unusual catalytic nucleophile. (2005) 391:
269-276.
Multiple Sequence Alignment of Alpha Glucosidase and
Homologs
Histidine-390 found to be conserved in two homologs
Threonine-212 found to be conserved in almost
five homologs.
A Web Resource for Extremozymes and
their Homologs
• We created a MySQL database to deposit the homologs of the extreme
enzymes and the analysis results and implement an online search tool.
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Two tables were created, one for extremozymes, and one for homologs .
A Web Resource for Extremozymes and
their Homologs
Conclusion
• We predicted 3D structures , active sites for extremozymes
predicted from metagenomic sequences.
• Web resource is set up to deposit the data for extremozymes
and their homologs .
Future prospects
• Intensive study and discovery of various enzymes (not
limited to extremozymes ) in metagenomic sequences
• Explore other sequence based approaches for active site
prediction and implement online tool
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Study structure – function relations, domain studies using
predicted 3D models.
Acknowledgements
Thanks to
• Primary Advisor- Dr. Yuzhen Ye
• Co- advisor – Dr Sun Kim
• Prof Adrian German , CS department
• Kwangmin Choi
• Linda Hostetter for her support throughout.
• Rachel Lawmaster
• Bioinformatics Faculty and Staff,
School of Informatics.
Thank You.