Toral Joshi

M.Phil (Bioinformatics)

Disha Life Sciences

IN SILICO ANALYSIS TO METABOLOMICS

INTRODUCTION

Metabolism:- It is the set of chemical reactions that happen in living organisms to maintain life.

Catabolism :- Breaks down organic matter.

Anabolism :- Uses energy to construct components of cells such as proteins and mucliec acid

Metabolite :- Metabolites are the intermediates and products of metabolism.Usually metabolites refers to small molecules.

Metabolic Pathway :- Series of Chemical reaction occuring within the cell.

Metabolic Network :- Collection of Metabolic pathways is called a metabolic Network.

INTRODUCTION

• Metabolome :- Metabolome refers to the complete set of small-molecule metabolites

• Metabolomics:-Investigation of metabolic regulation and fluxes in individual cells or cell types.Metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind" - specifically, the study of their small-molecule metabolite profiles.

• Metabonomics:- the determination of systemic biochemical profiles and regulation of function in whole organisms by analysing biofluidsand tissues

The History of Metabolomics

Linus Pauling hypothesised on the predictive capacity of chromatographic profiling of bodily fluids for detection and diagnosis of human disease.

Chromatographic separation techniques were developed in the late 1960's.

Robinson and Pauling published “Quantitative Analysis of Urine Vapor and Breath by Gas-Liquid Partition Chromatography” in 1971.

The Metabolome and Metabolomics were coined in the 1990s.

In January 2007 the Human Metabolome Project, completed the first draft of thehuman metabolome, consisting of 2,500 metabolites, 1,200 drugs and 3,500 foodcomponents.

WHAT IS A METABOLITE?

• Any organic molecule detectable in the body with a MW < 1000 Da

• Includes peptides, oligonucleotides, sugars, nucelosides, organic acids, ketones, aldehydes, amines, amino acids, lipids, steroids, alkaloids and drugs (xenobiotics)

• Includes human & microbial products

• Concentration > 1mM

SIZE OF METABOLOMES VARIES GREATLY

• Saccharomyces cereviciae ~ 600 metabolites (compared to over ~6,000 genes)

• Plants: ~ 200,000 primary & secondary metabolites• Human metabolome: Much larger

• Degree of diversity encompasses:• Molecular weights (wide range of mwt)• Polar (carbohydrates)• Non-polar (terpenoids & lipids)• Volatile vs. non-volatile organic compounds

METABOLITES

Some common metabolites include:• cholesterol• glucose, sucrose, fructose• amino acids• lactic acid, uric acid• ATP, ADP• drug metabolites, legal and illegal

These are produced in metabolic pathways, such as the Krebs (citrate) cycle for oxidation of glucose.

METABOLITES & FUNCTION

• Serum Creatinine

• Late stage organ stress and tissue breakdown

• TMAO

• Early stage buffering response

• Creatine, methyl-histidine, taurine, glycine

• Tissue damage, muscle breakdown, remodelling

• Citrate, lactate, acetate, acetone

• Oxidative stress, apoptosis, anoxia, ischemia

• Histamine, chlorotyrosine, thromoxane, NO3

• Immune response, inflammation

THE PYRAMID OF LIFE

25,000 Genes

2500 Enzymes

1400Chemicals

Metabolomics

Proteomics

Genomics

Primary Molecules

Secondary Molecules

Metabolomics

Chemical Fingerprint

METABONOMICS

• Evaluation of tissues & biological fluids for changes in endogeneous metabolite levels resulting from disease, genetic changes or (particularly important for pharmaceuticals) from therapeutic treatments.

METABOLITE PROFILING

Both Metabolomics and Metabonomics involve nonselective or non bias analysis.

In contrast ‘Metabolite profiling’ involves the identification and quantitation by a particular analytical procedure of a predefined set of metabolites of known or unknown identity and belonging to a selected metabolic pathway.

Metabolome analysis

Metabolite target analysis

Specific metabolites

e.g. particularenzyme system that

would be directlyaffected by abiotic

or bioticperturbation.

Metaboliteprofiling

Group of metabolites,

e.g. a class ofcompounds such

ascarbohydrates,

aminoacids or those

associated with aspecific pathway.

Metabolomics

All metabolites, present

in a cell or sample.Comprehensiveanalysis of the

wholemetabolome under

agiven set ofconditions.

Metabolitefingerprinting

The intention is notto identify each

observedcompound but tocompare patterns

orfingerprints of

metabolites thatchange in responseto disease or toxin

exposure.

IMPORTANT TERMINOLGIES

• Some important terminology that may be confusing:• Target metabolite analysis: Focussed approach, few metabolites• Metabolite profiling: Metabolic networks and compound classes• Metabolomics: Analysis of “all” metabolites in a specific living

organism• Metabonomics = Metabolomics in clinical disease• Metabolic fingerprinting: Rapid classification of metabolite groups• Metabolic pathway – metabolic network• Pleiotropic effects – rather a rule than an exception

METABOLOMICS

Integration of genomics, transcriptomics, proteomics and metabolomics is a goal of systems biology.

THE ”OMICS”

• Term Investigates RoleGenomics DNA sequences Information

Transcriptomics mRNA sequences Messenger

Proteomics Protein sequences Factory

Metabolomics Metabolites Function

Phenomics Phenotype Form

HUMAN METABOLOME PROJECT

• $7.5 million Genome Canada Project launched in Jan. 2005

• Mandate to quantify (normal and abnormal ranges) and identify all metabolites in urine, CSF, plasma and WBC’s

• Make all data freely and electronically accessible (HMDB)

• Make all cmpds publicly available (HML)

HUMAN METABOLOME PROJECT

• Purpose is to facilitate Metabolomics

• Objective is to improve

• Disease identification

• Disease prognosis & prediction

• Disease monitoring

• Drug metabolism and toxicology

• Linkage between metabolome & genome

• Development of software for metabolomics

20

BIOCHEMICAL PROFILE MAP TO METABOLIC PATHWAYS

Biochemical Profile

Metabolomics

Separation Methods

GC

HPLC

Capillary Electrophoresis

Detection Methods

MS

NMR

ANALYTICAL TECHNOLOGIES

ANALYTICAL TECHNOLOGIES: SEPARATION

Gas chromatographyIt offers high resolution, but requires chemical derivatization for many biomolecules and only volatile chemicals can be analysed without derivatization.Gas-liquid chromatography - involves a sample being vapourised and injected onto the head of the chromatographic column. The sample is transported through the column by the flow of inert, gaseous mobile phase. The column itself contains a liquid stationary phase which is adsorbed onto the surface of an inert solid.

High performance liquid chromatography

ANALYTICAL TECHNOLOGIES: SEPARATION

HPLC has lower resolution than GC, but it does have the advantage that a much wider range of analytes can potentially be measured.

Capillary electrophoresis

ANALYTICAL TECHNOLOGIES: SEPARATION

It has a higher theoretical separation efficiency than HPLC and is suitable for usewith a wider range of metabolite classes than is GC. As for all electrophoretictechniques, it is most appropriate for charged analytes.

ANALYTICAL TECHNOLOGIES: DETECTION

Mass spectrometryUsed to identify and to quantify metabolites after separation by GC, HPLC, or CE. In addition, mass spectral fingerprint libraries exist that allow identification of a metabolite according to its fragmentation pattern.

There are many types of mass spectrometers that not only analyze the ions differently but produce different types of ions; however they all use electric and magnetic fields to change the path of ions in some way.

Sector instrument

Nuclear magnetic resonance (NMR) spectroscopy

ANALYTICAL TECHNOLOGIES: DETECTION

NMR is almost the only detection technique whichdoes not rely on extraction and separation of theanalytes, and the sample can thus be analysed in vivoand recovered for further analyses.

Any molecule containing one or more atoms with anon-zero magnetic moment can potentially bedetected. In practice metabolites are labelled byfeeding substrates containing 1H, 13C, 14N, 15N or 31Pisotopes.

NMR is close to being a universal detector. However,it possesses one major disadvantage, which is that it isrelatively insensitive compared to mass spectrometry-based techniques.

POST-GENOMIC ERA OF BIOLOGY

Genome

Gene expression (mRNA)

Proteins

Metabolism

Genome

Gene expression (mRNA)

Proteins

Metabolism

Metabolomics

Proteomics

Genomics

Transcriptomics (Microarrays)

POST-GENOMIC ERA OF BIOLOGY

FunctionalMolecular

Phenotype

Genome

Gene expression (mRNA)

Proteins

Metabolism

Proteomics

Genomics

Transcriptomics (Microarrays)

Metabolomics

Genotype

POST-GENOMIC ERA OF BIOLOGY

FunctionalMolecular

Phenotype

Genome

Gene expression (mRNA)

Proteins

Metabolism

Metabolomics

Proteomics

Genomics

Environmental stressors

Transcriptomics (Microarrays)

Genotype

POST-GENOMIC ERA OF BIOLOGY

"METABOLOMICS: HOW AND WHAT FOR ? "

6 steps:

1- sampling (storage)

2- metabolite extraction (standardisation, reproducibility)

3- biochemical analysis (GC-MS, LC-MS, NMR)

4- data pre-processing (base line correction….)

5- data visualisation and mining (PCA, data bases)

6- integration of data (metabolic pathways, genome..)

Identify metabolites and pathways that influence drug response

Nature Reviews Genetics 5; 669-676 (2004);

To monitor in parallel hundreds or even thousands of metabolites, high-

throughput techniques are required that enable screening for relative changes

rather than absolute concentrations of compounds

• Samples (complex tissues, cells, etc.)

• Extract metabolites from sample.

• Separate metabolites (chromatography).

• Detect and characterize individual metabolites

• Quantify and perform data analysis.

METABOLOME ANALYSIS

Data is collected from instruments (GCMS,LCMS,NMR,CEMS,FTMS,etc.) in high a throughput manner.

Data is deconvoluted and stored automatically in appropriate format and database

Computer based applications automatically transform analysedata .

Statistically significant differences and/or similarities are reported to researcher in an easy to understand format.

METABOLOME DATA ANALYSIS

Protein

MetaboliteTranscript

Gene

APPLICATIONS

• Genetic Disease Tests

• Nutritional Analysis

• Clinical Blood Analysis

• Clinical Urinalysis

• Cholesterol Testing

• Drug Compliance

• Dialysis Monitoring

• MRS and fMRI

• Toxicology Testing

• Clinical Trial Testing

• Fermentation Monitoring

• Food & Beverage Tests

• Nutraceutical Analysis

• Drug Phenotyping

• Water Quality Testing

• Organ Transplantation

METABOLIC PROFILING: THE POSSIBILITIES

MEDICAL METABOLOMICS• Generate metabolic “signatures” for disease states or host

responses

• Obtain a more “holistic” view of metabolism (and treatment)

• Accelerate assessment & diagnosis

• More rapidly and accurately (and cheaply) assess/identify disease phenotypes

• Monitor gene/environment interactions

• Rapidly track effects from drugs/surgery

APPLICATIONS IN METABOLITE IMAGING

N-acetyl-aspartateLactate

Glutamate

CitrateAlanine

METABOLIC MICROARRAYS

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Patient 1Patient 2Patient 3Patient 4Patient 5Patient 6Patient 7Patient 8Patient 9Patient 10Patient 11Patient 12Patient 13Patient 14Patient 15

NormalBelow NormalAbove NorrmalAbsent

DNANutrigenetics

Nutritional Epigenetics

Nutritional Transcriptomics

Proteomics

Metabolomics

Bioactive Food Component

RNA

Protein

Metabolite

The “Omics” of Nutrition

Phenotype

Nutrigenomics

DNANutrigenetics

Nutritional Epigenetics

Nutritional Transcriptomics

Proteomics

Metabolomics

Bioactive Food Component

RNA

Protein

Metabolite

Nutritional Metabolomics

Phenotype

Nutrigenomics

Intake of Dietary

Constituent

AbsorbedDose Biologically

Effective Dose

Inactive Metabolite

Altered Altered Structure Structure/ FunctionFunction

Health Effects+ and -

Susceptibility (Genetic/

Environment)

Early BiologicEffect

Can Metabolomics Shed Light on these 3 Nutrition Related Biomarkers

CAN METABOLOMICS PROVIDE CLUES ABOUT THE PROGRESSION OF DISEASE

TreatmentOptions

QualityOf Life

GeneticRisk

EarlyDetection

Patient Stratification

DiseaseStaging

Outcomes

Natural History of Disease Treatment History

Biomarkers

Environment+ Lifestyle

METABOLOMICS: APPLICATIONS

• Identification of metabolic biomarkers that change as an indicator of the presence of disease or in response to drug-based intervention.

• Determination of the effect of biochemical or environmental stresses on plants or microbes

APPLICATIONS (CONT’D)

• Bacterial characterizations

• Human health assessments (potential for “translational research”?)

• Metabolic engineering

Metabolomics Applications

Diagnosis

Disease (e.g. coronary heart disease).Toxicology

Functional genomics

Ascribing functions to genes

Systems biology

Integration with data sets from other omics.

• Genetic Disease Tests

• Nutritional Analysis

• Clinical Blood Analysis

• Clinical Urinalysis

• Cholesterol Testing

• Drug Compliance

• Transplant Monitoring

• MRS and fMRI

• Food & Beverage Tests

• Nutraceutical Analysis

• Drug Phenotyping

• Water Quality Testing

• Petrochemical Analysis • Fermentation Monitorin• Toxicology Testing

• Clinical Trial Testing

OTHER APPLICATIONS

Metabolomics approaches have been widely used to provide a phenotypic description of a cell as a function

of time and/or condition by a set of metabolites.

Changes in levels of metabolic intermediates of a sequential series of reactions are often more

pronounced than the changes in enzymatic kinetics or individual fluxes. For this reason, metabolomics is

considered a sensitive tool for the study of genotype-phenotype correlations as well as the pharmacological

and toxicological effects of drugs.

DATABASES FOR METABOLOMICS

KEGG• KEGG is a suite of databases.

• PATHWAY

• holds the current knowledge on molecular interaction networks,

• including metabolic pathways, regulatory pathways,and molecular complexes.

• GENES

• is a collection of gene catalogs for all the complete genomes and some

• partial genomes. Each gene catalog is computationally derived from public

• resources, and is manually reannotated for reconstruction of KEGG pathways.

• KEGG GENES is associated with KEGG GENOME containing chromosome maps,

• KO for manually curated ortholog groups, and KEGG SSDB for computationally

• generated ortholog/paralog clusters and gene clusters.

• COMPOUND/

• GLYCAN/REACTION contains information about chemical

• compounds and reactions.

KEGG:- LIGAND DATABASE• LIGAND Database of Chemical Compounds and Reactions in

Biological Pathways

• provide the linkage between chemical and biological aspects of life in the

• light of enzymatic reactions.

• The database consists of four sections:

• COMPOUND, GLYCAN, REACTION, and ENZYME.

FOOD COMPONENT DATABASE

SOFTWARES FOR METABOLOMICS

LIST OF OTHER SOFTWARES

• mzmine and mzmine2 (http://mzmine.sourceforge.net/) - mzxml, mzdata, netCDF and XCalibur data (LC-MS, GC-MS, MS data)

• metAlign (RIKILT-WUR Institute of Food Safety) - LC-MS and GC-MS data

• BinBase (fiehnlab.ucdavis.edu) • xcms and xcms2 (Scripps) - netCDF data (LC-MS, GC-MS, MS and

MS2 data)• MarkerLynx (Waters) (LC-MS data)• BluFuse (BlueGnome) - for MS and NMR data • SpecAlign University of Oxford (Jason Wong) - Alignment of SELDI,

MALDI, NMR, RAMAN, IR (via TXT import)• HiRes (Columbia University Medical Center) - for NMR data• msInspect (Proteomics Fred Hutchinson Cancer Center)• Progenesis PG600 (Nonlinear) - for MALDI and SELDI mass spectra• caMassClass (NCBI) - for SELDI protein mass spectra

SOFTWARESXalign - for LC-MS data [DOI] - request here

msalign from Matlab Bioinformatics Toolbox - for MS data (example using msalign)

pairseqsim - (Bioconductor - Witold Wolski) - for mass spectra [DOI]

Randolph Yasui code - [DOI] download Matlab code and WMTSA wavelet toolbox

RTAlign algorithm of MSFACTs (noble.org) - GC-MS and LC-MS data

Genedata Expressionist (genedata.com) - for LC-MS and infusion MS data.

MS Align (David Grant - Uconn.edu) - for high resolution mass spectral data [DOI]

LCMSWARP (PNNL) - for proteomics and metabolomics LC-MS data (http://ncrr.pnl.gov/software)

ChromAlign (Thermo) - included in Sieve and Biosieve package for LC-MS and LC-MS-MS data

PETAL - Peptide Element Alignment for LC-MS data (http://peiwang.fhcrc.org/research-project.html)

MarkerView (ABI/Sciex) - for LC-MS and MALDI data peak picking and alignment and statistics

SOFTWARES• MathDAMP (Keio University) - for GC-MS, LC-MS, CE-MS data with Mathematica source code [DOI]

• NameLess - for MALDI MS and FT-MS data with JAVA source code [DOI]

• CPM MatLab toolbox (J Listgarten) - for LC-MS, proteomics, metabolomics and time series data + source code.

• GASP (genedrift.org) - for GC-MS alignment

• AnalyzerPro (SpectralWorks) - for alignment of GC-MS data

• meta-b (Vladimir Likic) - for alignment of LC-MS data with python source code (go SVN)

• spectconnect (MIT) - for alignment of GC-MS data using AMDIS for deconvolution

• ChenomX Profiler (Chenomx) - for binning and alignment of NMR signals (+ DB search)

• KnowItAll Metabolomics Editions (BioRad) - with IntelliBucket bucketing and binning of NMR data (+ DB search)

• MS-Xelerator (MSMETRIX) - Advanced Algorithms for LC/MS Data Processing (Marco Ruijken)

• OBI-Warp (U Texas) - Ordered Bijective Interpolated Warping for LC-MS data [PDF]

THANK YOU FOR YOUR PATIENCE