Functional Genomics: using genome- wide approaches to … · 1st bacteria 1st arqueobacteria Haemophilus influenza The post-genomic era ... resistance to multiple drugs and chemical

Functional Genomics: using genome-wide approaches to unveil gene

function

1st bacteria

1st arqueobacteriaHaemophilus influenza

The post-genomic era

Mammals

Insects

Mus musculus

Anopheles gambiae

Homo sapiens Canis familiaris

1st eukaryote

1st eukaryoteMethanococcus janaschii

Saccharomyces cerevisiae

Plants

Drosophila melanogaster

Arabidopsis thaliana

Gallus gallus

Oryza sativa

Pan troglodytes

Birds

Fugu rubripes

Fish

Saccharomyces cerevisiae

Functional analysis in the post-genomic world

YBR180w

YIL120w

YIL121w

YBR043c

YNL065w

Cluster I

A WHOLE NEW WORLD…OF REVERSE GENETICS

YNR055c

YPR156c

YGR138c

YOR273c

YOR273c

YHR048w

YBR008c

Cluster II

A WHOLE NEW WORLD…OF REVERSE GENETICS

Characterization of the participation of the new MDR transporters in resistance to multiple drugs and chemical stresses

Systematic functional analysis of yeast multidrug resistance transporters

b)a) c) b)a) c)

wt

∆∆∆∆geneA

∆∆∆∆genA∆∆∆∆genB

∆∆∆∆geneB

b)a) c) b)a) c)

Protein sub-celular localization


Proteina de fusão ORF-GFP

Transport assays to determine the role of each MDR transporters in drug extrusion


Studies on the stress induced changes at the transcript and protein levels, by Northern blotting, RT-PCR and Western blotting

Acti

vati

on

fo

ld

Gene1

5

10

15

Gene2

5 2.5 5 7 140

Strain:

Time (h):

wt∆∆∆∆geneA

ProteinA

Pma1p

B


Strain

Acti

vati

on

fo

ld

Gene3 Gene4

5

0

5

10

0

0.2

0.4

0.6

0.8

Pro

tein

A/P

ma1

p (�

)

(arb

itra

ry u

nits

)Time (h)

0 10 20 300.1

1

10

(�)

Characterization of the physiological role of new MDR transporters

DTR1 (YBR180w)QuinineQuinidinePropionic acidBarban

QDR1 (YIL120w)QuinidineFluconazoleKetoconazoleBarban

QDR2 (YIL121w)QuinidineKetoconazoleBarbanCisplatinBleomycin

QDR3 (YBR043c)QuinidineKetoconazoleFluconazoleBarbanCisplatin

AQR1 (YNL065w)QuinineQuinidineKetoconazoleBarban

Crystal violetAcetic acidPropionic acidButyric acid

Cluster I


NystatinMCPA2,4-DArtesunateMycophenolic acidCaspofunginIndomethacin

CisplatinBleomycinMn2+

HOL1 (YNR055c)Histidinol uptake

TPO3 (YPR156c)Polyamine

- SpermineQuinidineAcetic acidPropionic acidButyric acid

TPO2 (YGR138c)Polyamine

- SpermineQuinidineAcetic acidPropionic acidButyric acid

TPO4 (YoR273c)Polyamine

- SpermineQuinidineCycloheximide

TPO1 (YoR273c)Polyamine

- Spermine- Putrescine- Spermidine

QuinidineCycloheximide

YHK8 (YHR048w)ItraconazoleFluconazole

FLR1 (YBR008c)FluconazoleCycloheximide4-NQOMancozebBenomylMethotrexate

DiazoborineCeruleninDiamideDiethylmaleateMenadioneParacetamol

Cluster II

Functional Genomics

- a field of molecular biology that attempts to make use of the

vast wealth of data produced by genomic projects to describe

gene functions and interactions, foccusing on the dynamic

aspects of gene transcription, translation, interactions...

EUROPEAN SCIENCE FOUNDATION PROGRAMME ON

FRONTIERS OF FUNCTIONAL GENOMICS

Functional Genomics

“New” experimental methods to obtain genome-wide data

Phenotypic analysis:• disruptome• genetic interactions

Gene expression analysis:• at the RNA level• at the protein level• at the protein level

Physical and chemical interactions within the cell• protein-protein• protein-DNA• protein-lipids/substracts• protein modifications

Metabolome and fluxome analysis

Integrative approaches – Systems Biology

Methods for genome-wide phenotypic analysis

Disruptome analysis

Control Stress

Chemical genomic portrait of Yeast




Disruptome analysis: competition assays

Each deletion mutant contains specific Tags

kanMX4

kanMX4

PCR

Tag 1Tag 2


Disruptome analysis: competition assays

Relative quantification of the

abundance of each unique tag

KAN RTAG

TAG

TAGTAG

TAG

TAG

Array de Tags


Synthetic lethality – SGA method



132 SGAs permitem

estabelecer cerca de

4000 interacções entre

cerca de 1000 genes de

levedura





Genome-wide expression analysis: transcriptomics

DNA MicroarraysMeasures the concentration of each transcript in the cell, including mRNA, rRNA, tRNA, sRNA.

Control Stress

Genome-wide expression analysis: proteomics

Electroforése bidimensional

• mede-se a concentração de cada proteína/forma proteíca na célula.

6.05.04.5

MW/kDa

pI

97.0

66.0

45.0

control + stress

His4p

Met6p

30.0

20.1

14.4

Hsp12p

Ahp1p(oxidized form)

Ahp1p(reduced form)

LOCALIZOMICSSub-celullar protein localization at the proteome-wide scale

Huh et al., Nature,

2003, 425: 686-91

75% of the proteome in natural conditions

Flow cytometry analysis of candidate deletion strains.

Plot of the log10 fluorescence of candidate deletion

strains tested at 6 h and 24 h of oleate incubation.

Deletion strains are indicated with open circles, while

wild type is indicated by the line. The tables at the right

show the flow cytometry analysis of the candidate genes

with percentage of Pot1p-GFP fluorescence relative to

wild type, the mean of the fluorescence values and the z

value or standard score of the fluorescence at 6 h or 24 h

respectively. Genes are shown that show decreases of

Pot1p-GFP fluorescence that are at least 1SD from the

wild type POT1-GFP strain. Genes boxed by blue or red

indicate the naturally occurring separation of values

shown in the plot at 6 h (blue) and 24 h (red).

Identification of

peroxisomal mutants.

Bright field images are

shown on the left panel and

fluorescence images are

shown on the right. Known

peroxins show

mislocalization of themislocalization of the

Pot1p-GFP reporter when

deleted. Partial

mislocalization phenotypes

are seen in pex1D, pex18D,

and pex21D.

Vps52p, Pir3p and YKL015C are novel peroxisome

inheritance factors. A. Strains lacking Inp1p, Vps52p, Pir3p

or YKL015Cp accumulate peroxisomes near the bud neck or

in daughter cells as indicated by the arrowheads. B.

Summary of the effect of (i) deletions, (ii) complementation,

and (iii) double deletions of vps52D, pir3D and ykl015cD.

Mnn11p and Hsl7p are regulators of

peroxisome morphology. Strains deleted for

mnn11 or the 59 end of hsl7 (hsl7DN generated

by the ybr134w deletion) were backcrossed

against an allelic deletion or a wild type strain

(BY4742). An increased number of small

peroxisomes are seen in cells deleted for

mnn11, while hsl7DN lead to an increase in

size or tendency for the peroxisomes to cluster.

Both phenotypes are complemented by mating

to the wild type strain.

Single-cell quantification of GFP-tagged protein levels reveals diverse proteomic changes during nitrogen starvation.

Breker M et al. J Cell Biol 2013;200:839-850

© 2013 Breker et al.

A bet-hedging strategy in yeast underlies prolonged survival under starvation.



Integration of proteome abundance and subcellular organization enables characterization of the dynamics of organelle morphology and composition under stress.



Protein localization is dynamic under stress.



Integration of all proteomic changes gives a “thumbprint” of cellular stress responses.



“New” experimental methods to obtain genome-wide data

Phenotypic analysis:• disruptome• genetic interactions

Gene expression analysis:• at the RNA level• at the protein level

Physical and chemical interactions within the cellPhysical and chemical interactions within the cell• protein-protein• protein-DNA• protein-lipids/substracts• protein modifications

Metabolome and fluxome analysis

Integrative approaches – Systems Biology

BaitProtein

BindingDomain

Prey Protein

ActivationDomain

Protein-protein interaction analysis : two-hybrid system

For cytosolic proteins: classical Gal4 method

Reporter GeneDomain

Reporter Gene

BaitProtein

BindingDomain

Prey Protein

ActivationDomain

Protein-protein interaction analysis : two-hybrid system

For membrane protein: split-ubiquitin method

Protein-protein interaction analysis : fluorescence complementation

In vivo detection of protein-protein interaction in their sub-cellular localization

Protein-protein interaction analysis : fluorescence complementation

INTERACTÓMICAAnálise de interacções proteicas: método de dois híbridos

à escala do genoma

Análise de interacções proteicas: método de dois híbridosà escala do genoma - resultados

Neste único trabalho:

4549 interacções (de entre 4 milhões testadas).

Science, 2001, 293: 2101-2105

Análise de interacções proteicas: chips de proteínas

Detecção de interacções proteicas in vitro na sua localização subcelular

Análise de interacções proteicas: chips de proteínas

Protein-ligand interaction analysis:

protein chips

Análise de interacções proteína-DNA: ChIP e ChIP-on-chip

Crosslink DNA in vivo

Fragmentação do DNA

ChIP

Isolamento do complexo proteína-DNA por imunoprecipitação

Amplificação por PCR de fragmentos específicos

Análise de interacções proteína-DNA: ChIP e ChIP-on-chip

Isolamento de todos os complexos proteína-DNA por imunoprecipitação

ChIP-on-chip

Hibridação em microarrays de promotores de todos os fragmentos de DNA

Análise de interacções proteína-DNA: ChIP-on-chip

Expression proteomics using antibody chips

Chemical chips

Chemical chip is a platform were chemical

interactions may performed, registered and

analyzed.

DNA, protein and antibodies chips are specific

(bio)chemical chips.(bio)chemical chips.

With nanotechnologies high-throughput analysis,

reduced sample volumes, integration of different

components – Lab-on-a-chip and µTAS (Micro

total analysis system).

Types of chemical chips

Haishing Ma

et al, 2006

Types of chemical chipsDry chemical microarray enzyme assay

The figure report a study of kinase inhibitors:

� 8640 different compounds were spotted in and dried in a polystyrene sheet;

� Agarose gel containing kinase was laid on top of the compounds;

� A second agarose gel containing peptide substrates was laid on top of previous

agarose gel.

Structural proteomics

• Major objective: to obtain experimentally the

3D structures of all the proteins

� Reasonable objective: To determine the structure and obtainrepresentative models of all possible protein folding structures


� Goal: Infer the function of new proteins

The most common method is to compare the amino acid

sequence of the new protein with those available for

functional inference functional inference

The 3D structure of a protein is much more conserved than

the primary aminoacid structure!


Structural proteomics• Worldwide consortia:

– Protein Structure Initiative (PSI)

– Structural Proteomics in Europe (SPINE)

– National Project on Protein Structural andFunctional Analyses (RIKEN)

� Protein Data Bank (PDB)

•Choosing the protein(s)

•High-throughput expression and purification

Experimental approach

•High-throughput expression and purification

•3D structure determination•X-ray crystallography

•Nuclear magnetic resonance (NMR)

•PDB annotation

TM0449 Protein from Thermotoga maritima: "Thymidylate synthase”

� X-ray crystalography

Examples

New Folding

� New folding identification

� A new pathway for the synthesis

of Thymine in human pathogens

� New target for antibiotics

• MTH1880 from Methanobacterium thermoautotrophicum

– Protein with no sequence homology.

– Structure determination identified an acidic cation bound motif,

leading to the association of Ca-transport to MTH1880 function

Examples

Function prediction from a 3D structure

leading to the association of Ca-transport to MTH1880 function

– Functional prediction to a whole family of uncharacterized proteins

Applications of Functional Genomics

Biomedical:

- Epigenomics

- Neurogenomics and disease

- Pharmacogenomics

- Predictive, preventive and personalized medicine- Predictive, preventive and personalized medicine

Environmental:

- Metagenomics

- Toxicogenomics

Agricultural, Biotechnological, Economical, Social...

Research

SmallMolecules

Animal Models

FunctionalGenomics

Proteomics

CellAssays

DrugTargets

GenesDrugTests

GenomicsCombinatorial Combinatorial

ChemistryChemistryScreening

DrugLeads

Pharmacogenomics

HumanTrials Drug

DevelopmentStage

ApprovalDrug Discovery Preclinical

I II III IV

Clinical

PostPost--genomic approaches in genomic approaches in

Drug Discovery/Development ProcessDrug Discovery/Development Process

Technology

ResearchArea

Bioinformatics

Positional Cloning

Parallel Sequencing

2-D Gel,Mass Spec.

Cellular AssaysModel Organism,Gene Knock-outs

ModelsGenomicsProteomicsGenomics

ChemistryChemistryScreening Pharmacogenomics

Genotyping,Phenotyping,SNPs Markers

StructuralDrug Design

Molecular Informatics

Differential Display, Expression Patterns, Reporter Gene Technologies

Chip Technologies, DNA Chips, Protein Chips, Microarrays

Source: IBM Life Science, 2002

Análise quantitativa de metabolitos

Métodos tradicionais: HPLC, GC, CE, MS

Métodos globais: NMR, MS• conseguem medir de uma só vez dezenas de metabolitos• NMR é quantitativo mas mais limitado no nº de metabolitos que analisa

Análise do metaboloma: 2 caminhos

1234567ppm

Métodos Métodos

1234567ppm

hippurate urea

allantoin creatininehippurate

2-oxoglutarate

citrate

TMAO

succinatefumarate

water

creatinine

taurine

-25

-20

-15

-10

-5

0

5

10

15

20

25

-30 -20 -10 0 10

PC1

PC2

PAP

ANIT

Control

Métodos quantitativos quimiométricos

Ace

tic

Aci

d

Bet

ain

e

Car

nit

ine

Cit

ric

Aci

d

Cre

atin

ine

Dim

eth

ylg

lyci

ne

Dim

eth

yla

min

e

Hip

pu

lric

Aci

d

Lac

tic

Aci

d

Su

ccin

ic A

cid

Tri

met

hyla

min

e

Tri

mn

-N-O

xid

e

Ure

a

Lac

tose

Su

ber

ic A

cid

Seb

acic

Aci

d

Ho

mo

van

illi

c A

cid

Th

reo

nin

e

Ala

nin

e

Gly

cin

e

Glu

cose

Patient 1

Patient 2

Patient 3

Patient 4

Normal

Below Normal

Above Norrmal

Absent

Aplicações clínicas…

Patient 4

Patient 5

Patient 6

Patient 7

Patient 8

Patient 9

Patient 10

Patient 11

Patient 12

Patient 13

Patient 14

Patient 15

Documents

Functional Genomics: using genome- wide approaches to … · 1st bacteria 1st arqueobacteria Haemophilus influenza The post-genomic era ... resistance to multiple drugs and chemical