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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?

• 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

– 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

– 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

Catalase Sludge (2000613520) 83

Whalefall (2001431860) 78

Isocitrate dehydrogenase Whalefall (2001496341) 73

Sludge(2000495850) 67

Threonine dehydrogenase Sludge (2000145560) 44

Uranium (2007096904) 43

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 Predicted esterase from AMD

ferroplasma acidiphilum (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 c) Predicted structure

b) Predicted structure of a

experimental of a homolog from

homolog identified in sludge

structure of whale fall sample (ID:

phrap assembly (ID: 2000613520)

catalase (PDB ID: 2001431860) with

with 83% sequence identity.

2ISA) used as the 78% sequence

template identity.

Isocitrate Dehydrogenase









Isocitrate dehydrogenase structure

Predicted Isocitrate dehydrogenase

(PDF ID: 1J1W).

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

• A membrane bound alpha glucosidase (531 amino acids) isolated from

extremophile Ferroplasma acidiphilum was used as the query in homolog search



• 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.



• Identified homologs include a protein (ID: 638394706) from ferroplasma

acidarmanus , which has 99% sequence identity.



• Ref: Ferrer M., Golyshina O., Plou F., Timmis K., Golyshin P. A novel alpha-

glucosidase 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.



• 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



• 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.


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