ComPath Comparative Metabolic Pathway Analyzer

Kwangmin Choi and Sun KimSchool of Informatics

Indiana University

Contents

Introduction System Components Current Implementation Experiment Result Future Plan

INTRODUCTION&

SYSTEM COMPONENTS

Introduction

ComPath is a web-based sequence analysis system built upon:

KEGG (Kyoto Encyclopedia of Genes and Genomes)

PLATCOM (A Platform for Computational Comparative Genomics)

KEGGKyoto Encyclopedia of Genes and Genomes

Four Databases PATHWAY 32,657 pathways gen

erated from 262 reference pathways

GENES 1,213,035 genes in 32 eukaryotes + 260 bacteria + 24 archaea

LIGAND 13,387 compounds, 2,543 drugs, 11,161 glycans, 6,446 reactions

BRITE 7,817 KO (KEGG Orthology) groups

KEGG adopts EC enzyme classification system

EC system 0/2

An Old, but still universally accepted system by biochemists

EC system was developed long before protein sequence or structure information were available, so the system focuses on reaction, not sequence homology and structure

Many biochemists and structural biologists try to harmonize newly available chemical, sequential, and structural data with traditional understanding of enzyme function.

Problems in EC system 1/2

Inconsistency in the EC hierarchy For each of the six top-level EC classes, subclasses and sub-subclasses ma

y have different meanings. e.g. EC1.* are divided by substrate type, but EC5.* by general isomerase typ

e Problem with Multi-functional enzymes and multiple subunits involved in

a function EC presumes only a 1:1:1 relationship between gene, protein, and reaction.

Different sequence/structure, but similar EC Two enzymes with lower sequence identities sometimes belong to the same

or very similar EC. e.g. o-succinylbenzoate synthase across several bacteria have below the

40% sequence identity

Problems in EC system 2/2

Similar sequence/structure, but different EC Even variation in the fourth digit of the EC number is rare above a sequence identity thre

shold of 40%. However, exceptions to this rule are prevalent. e.g. melamine deaminase and atrazine chlorohydrolase have 98% identical, b

ut belong to different EC.

No information on sequence/structure-mechanism relationship EC system considers only overall transformation Similarity among sequences is strongly correlated with similarities in the level of a com

mon (structural domain-related) partial reaction, rather than overall transformation How to combine enzyme structure data with partial reaction data?

Research Goal We provide a computational environment for enzyme analysis via genome comparison And it will be built on PLATCOM system

Our Research Goal

We provide a computational environment for enzyme analysis via multiple genome comparison

And it will be built on PLATCOM system

PLATCOM http://platcom.org/platcom

A Platform for Comparative Genomics

Providing a platform for comparative genomics ON THE WEB

Comparative analysis system for users to freely select any sets of genomes

Scalable system interactively combining high-performance sequence analysis tools

CURRENT IMPLEMENTATION

ComPath http://platcom.org/compath

Compatative Metabolic Pathway Analyzer

ComPath = KEGG + PLATCOM

Not just for retrieving information from Database,

but focuses on analyzing enzymes using the enzyme-genome table

Easy to use {Optional} Upload a user sequence and/or a saved enzyme-

genome table data Select a metabolic pathway Select any combination of genomes in KEGG Create an enzyme-genome table Then use the table for various enzyme sequence analysis tasks

Screenshot: Pathway Selection

11 categories

123 pathways

Users can upload the previous Enzyme-Genome table datatype to continue analysis

Screenshot: Genome Selection

250 genomes from KEGG database

Users can select genomes by taxonomical and alphabetical order

Screenshot: Operations 1/2

Screenshot: Operations 2/2

Enzyme-Genome Table

An enzyme-genome table allows for tests on whether a certain enzyme in a given pathway is present or missing using sequence analysis techniques.

Information in this table can be easily saved, uploaded, transferred.

Users also can upload their sequence set, e.g.,  an entire set of predicted proteins in a newly sequenced genome, and perform annotation of the sequences in terms of KEGG pathways.

Screenshot: ComPath’ Enzyme-Genome Table – INTERACTIVE!

Screenshot: KEGG’s Ortholog Table – STATIC!

How ComPath works:Overall Design

How ComPath works:

Sequence Analyses

Missing enzyme search Pairwise (FASTA) and multiple sequence alignment (CLUSTALW), Domain search using SCOPEC/SUPERFAMILY and PDB domains Domain-based analysis using hidden markov models (HMM), Contextual sequence analysis

Sequence analysis for further investigation Phylogenetic analysis of enzymes in selected genomes, Gibbs motif sampler. BAG clustering Contextual sequence analysis

Global network analysis Physical network analysis

TEST

Experiments:Genomes, Queries, Pathways

Selected Genomes B.subtilus, B.Halodurans, E.coli H.Influenza, H.pylori, M.genitalium, Y.pestis KIM

Query genomes M.tuberculosis A.aeolicus B.anthracis

Metabolic Pathways 00010 (glycolysis+glycogenesis), 00020 (TCA cycle)

Experiments:Comparison of Sequence Analysis Methods Four methods (abbr.)

HMMer HMM search using the whole sequence

CSR HMM search using common shared regions generated by BAG progra

m SCOPEC

Domain search using SCOP/SUPERFMAILY and PDB database FASTA

Simple FASTA search

Cutoff

1e-10, 1e-20, 1e-30

Experiments:Overall Design

Screenshot: ComPath’ Enzyme-Genome Table – INTERACTIVE!

Experiment Results (e.g.)Query Genome Pathway Mehthod Sensitivity Specificity E-value

M. tuberculosis Path 00010 HMMer 0.596491228 0.454545455 1.00E-30

CSR 0.666666667 0.454545455 1.00E-30

SCOPEC 0.614035088 0.348484848 1.00E-30

FASTA 0.649122807 0.378787879 1.00E-30

HMMer 0.623188406 0.524590164 1.00E-10

CSR 0.739130435 0.360655738 1.00E-10

SCOPEC 0.652173913 0.418032787 1.00E-10

FASTA 0.811594203 0.204918033 1.00E-10

Query Genome Pathway Method Sensitivity Specificity E-value

M. tuberculosis Path 00020 HMMer 0.535714286 0.769230769 1.00E-30

CSR 0.642857143 0.846153846 1.00E-30

SCOPEC 0.535714286 0.769230769 1.00E-30

FASTA 0.678571429 0.615384615 1.00E-30

HMMer 0.516129032 0.777777778 1.00E-10

CSR 0.709677419 0.666666667 1.00E-10

SCOPEC 0.548387097 0.777777778 1.00E-10

FASTA 0.741935484 0.333333333 1.00E-10

A. aeolicus

B. anthracis

M. tuberculosis

FUTURE PLAN

Future Plan:More Resources

ComPath is being extended to incorporate more resources, including KEGG LIGAND : A composite database consisting of compound, glycan, reaction et

c. ProRule : A new database containing functional and structural information on PRO

SITE profiles SFLD : Structure-Function Linkage Database

Also we are developing databases and algorithms for enzyme analysis, e.g.

Classifiers using a database of enzyme-specific HMMs.

ComPath is in an early stage of system development and we solicit feedback and suggestions from biology and bioinformatics communities.

Future Plan:More Algorithms and Tools

More integrative understanding on biochemical network evolution Algorithms to handle isozyme problem Algorithms to computationally reconstruct alternative pathways Algorithms to combine sequence, structure, chemical reaction, and co

ntextual information for better enzyme annotation Etc.

ComPath is in an early stage of system development and we solicit feedback and suggestions from biology and bioinformatics communities.