Yeast in drug development

Properties: unicellular eukaryoteMethodology: forward and reverse genetics, two-hybrid

system, surrogate hostApplications: Model system for cellular eukaryotic functions

(animal or plant):Intracellular signal transductionDNA repair, replication, cell cycletranscriptionchromosome biologyprotein transportwater transportetc.

Protein-protein interactionsGlobal transcriptional regulationDrug target identificationDrug screening/selectionDisease diagnosticsModel for fungal pathogens (plant/animal)

Advantages of yeast in molecular biology

• Short life cycle, easy to cultivate• Compact genome, fully sequenced• Many fundamental processes on cellular level conserved• Lots of information available per gene product• Genetically tractable:

• haploid• DNA transformation• multiple genetic markers available, both selection and counterselectionpossible• genetic crosses possible• gene knockout by homologous recombination very efficient –complete set of 4 x 6000 knockout mutants available

Yeast for production of proteins – hepatitis B vaccine

+ =

Advantages:

• higher yield, faster growth than animal cells• eukaryotic post-translational modifications

Hepatitis B surface antigen (HbSAg)

Yeast as a genetically tractable organism to identify drug targets,establish cellular disease models, diagnosis, and for screening ofreceptor ligands and lead compounds

The yeast genomeis densely packedwith genes

Saccharomycescerevisiae is themost information-dense of allexperimentalorganisms

Functional Catalogue version from 06.12.2001 •METABOLISM (1066 ORFs)

•amino acid metabolism (204 ORFs) •amino acid biosynthesis (118 ORFs)

•biosynthesis of the aspartate family (1 ORF) •biosynthesis of lysine (1 ORF)

•biosynthesis of the cysteine-aromatic group (2 ORFs) •biosynthesis of serine (1 ORF)

•biosynthesis of the pyruvate family (alanine, isoleucine, leucine, valine) and D-alanine (1 ORF) •regulation of amino acid metabolism (33 ORFs) •amino acid transport (23 ORFs) •amino acid degradation (catabolism) (35 ORFs)

•degradation of amino acids of the glutamate group (1 ORF) •degradation of glutamate (1 ORF)

•degradation of amino acids of the cysteine-aromatic group (1 ORF) •degradation of glycine (1 ORF)

•other amino acid metabolism activities (5 ORFs) •nitrogen and sulfur metabolism (67 ORFs)

•nitrogen and sulfur utilization (38 ORFs) •regulation of nitrogen and sulphur utilization (29 ORFs)

•nucleotide metabolism (148 ORFs) •purine ribonucleotide metabolism (45 ORFs) •pyrimidine ribonucleotide metabolism (29 ORFs) •deoxyribonucleotide metabolism (11 ORFs) •metabolism of cyclic and unusual nucleotides (8 ORFs) •regulation of nucleotide metabolism (13 ORFs) •polynucleotide degradation (27 ORFs)

•RNA degradation (4 ORFs) •nucleotide transport (14 ORFs) •other nucleotide-metabolism activities (7 ORFs)

•phosphate metabolism (33 ORFs) •phosphate utilization (14 ORFs) •regulation of phosphate utilization (8 ORFs) •phosphate transport (10 ORFs) •other phosphate metabolism activities (1 ORF)

•C-compound and carbohydrate metabolism (415 ORFs) •C-compound and carbohydrate utilization (261 ORFs)

•C-compound, carbohydrate anabolism (1 ORF) •polysaccharide biosynthesis (1 ORF)

•regulation of C-compound and carbohydrate utilization (120 ORFs) •C-compound, carbohydrate transport (42 ORFs) •other C-compound, carbohydrate metabolism activities (2 ORFs)

•lipid, fatty-acid and isoprenoid metabolism (213 ORFs) •lipid, fatty-acid and isoprenoid biosynthesis (119 ORFs)

•phospholipid biosynthesis (2 ORFs) •glycolipid biosynthesis (1 ORF) •isoprenoid biosynthesis (1 ORF)

•tetracyclic and pentacyclic triterpenes (cholesterin, steroids and hopanoids) biosynthesis (1 ORF) •breakdown of lipids, fatty acids and isoprenoids (25 ORFs) •lipid, fatty-acid and isoprenoid utilization (26 ORFs) •regulation of lipid, fatty-acid and isoprenoid metabolism (20 ORFs) •lipid and fatty-acid transport (21 ORFs) •other lipid, fatty-acid and isoprenoid metabolism activities (13 ORFs)

•metabolism of vitamins, cofactors, and prosthetic groups (86 ORFs) •biosynthesis of vitamins, cofactors, and prosthetic groups (63 ORFs) •utilization of vitamins, cofactors, and prosthetic groups (7 ORFs) •regulation of vitamins, cofactors, and prosthetic groups metabolism (3 ORFs) •transport of vitamins, cofactors, and prosthetic groups (3 ORFs) •other vitamin, cofactor, and prosthetic group metabolism activities (8 ORFs)

•secondary metabolism (5 ORFs) •metabolism of primary metabolic sugars derivatives (1 ORF)

•biosynthesis of glycosides (1 ORF) •biosynthesis of secondary products derived from primary amino acids (4 ORFs)

•biosynthesis of amines (4 ORFs)

Pathway and graphical function informationin databases

Genetic engineering of yeast for drug sensitivity assays

Problem:

• Many hydrophobic low Mw compoundsdo not enter the yeast cell

• Yeast has multiple transport proteins involvedIn drug transport: 35 in major facilitator super-family, plus 14 ABC transporters

• Each transporter is highly promiscuous

Solutions:

• make mutants defective in membrane lipidbiosynthesis, e.g. erg6

• make multiple deletions of genes fortransporter proteins.

• Nine-tuple deletant strain 100x moresensitive to wide range of compounds

The ”compendium” approach:

Goal: to identify proteintargets of drugs with unknownmechanism

Principle: disturbance of a pathway bya drug or a mutation should yield similar phenotypes, including on transcript profiles

Method: clustering of transcript profilesof yeast deletion mutants withexperimental conditions

Hughes et al., Cell 102:109 (2000)

Transcript profile clusteringidentifies similarity betweendyclonine treatment anddisruption of ergosterol metabolism

Y’

Gal4AD

X

Gal4DB

HIS3Gal4 bindingsite

The two-hybrid systemGal4AD

X

Gal4DB

HIS3Gal4 bindingsite

Y

No growth on -His medium

Growth on -His medium

Physical interactionbetween hybridproteins activatesreporter gene undercontrol of Gal4 transcription factor

Bait

Prey

Gavin et al. Nature 415:141 (2002)

Network of physical protein complexes in yeast

Internet databases combine physical andgenetic interaction information

Genetic and physical interactions visualised by dedicated software

Y

AD

X

GBDHIS3

Gal4 bindingsite

Y

AD

X

GBDHIS3

Gal4 bindingsite

YAD

Z

LBDURA3

LexA bindingsite

YAD

Z

LBDURA3

LexA bindingsite

Reverse two-hybrid: selection ofinteraction-disrupting agents andmapping of interaction domains

1. a) Mutagenize Y

or

b) Transform withlibrary encoding randompeptides, or add library oforganic compounds

2. Select for 5-FOAR and His+

Extensions of two-hybrid for drug target identification:aptamers and DB-anchored drugs

Selection for aptamers thatbind to the bait

Selection for aptamers thatdisrupt an interaction

Selection for proteins that bindto a drug which is anchored to aDB through a covalent link to anotherdrug

Systematic analysis of synthetic lethalityby SGA – ”synthetic gene arrays”

Network of genetically connectedgene functions

Tong et al., Science 303:808 – 813 (2004)

Two-dimensional hierarchical clustering of the synthetic genetic interactions determined by SGA analysis

SGA analysis clustersrelated genes andfunctional groups

Fig. 3. Toxicity profiles of cytotoxic anticancer agents: topoisomerase poisons, X-rays, bleomycin, and actinomycin D. The graphs show the IC50 (log M for compounds, log k rad for X-rays) for each agent against the strain panel. The vertical line is set at the IC50

of the wild-type strain. The strains are grouped and color-coded according to the DNA damage response pathway they represent.

The ”Seattle Project”

Antitumor treatments (drugs, irradiation) are tested on sets of yeast mutantswhere different DNA repair and DNA damage response pwahtways are inactivated.Hypothesis: synthetic effects if the drug an the mutation in the tumour affect parallell pathways. Goal: individualised tumour therapy

Genetics

Scope

• The causal relationship between the genome (genotype) and properties of

the organism (phenotype)

Scope

• The causal relationship between the genome (genotype) and properties of

the organism (phenotype)

Scope

• The causal relationship between the genome (genotype) and properties of

the organism (phenotype)

Method

•Observe properties of whole system (cell, organism) altered in one (several) genes (Cf. physiology: observe whole system, infer relationship between parts; biochemistry: study gene products in isolation)

Forward genetics

Aim

- To go from function to gene

Means

-Screen populations of mutants for

gain or loss of a particular function

Reverse genetics

Aim

- To define the function(s) of a gene

Means

- Analyze a particular mutant for gain or loss of

a variety of functions

The geneticist's dilemma

• Most mutations are recessive, loss-of-function

• Most mutations confer sensitivity, not resistance to a specific condition

• Screening for resistance is easy, simply selecting will do

• Screening for sensitivity is extremely labor-intensive, involves replica-plating and visual inspection

Control screen: tunicamycin

Step1: Heterozygous mutations in three loci conferred sensitivity:

• ALG7 (Asn-linked glycosyl transferase;

previously known target)

• YMR007w (unknown function)

• YMR266w (membrane transport)

Step 2: test cognate homozygous mutations:

• alg7/alg7 wild-type sensitivity

• ymr007w/ymr007w supersensitive

• ymr266w/ymr266w supersensitive

Ymr007w and Ymr266w ruled out as direct drug

targets because of supersensitivity in the absence of

the gene product

Direct drug effect on target (1)

Output

Normal situation Drug

Smaller output

Direct drug effect on target (2)

Drug

Insufficient output(cell dies)

Haploinsufficiency(less gene product)

Homozygous mutation(no gene product)

Drug

Insufficient output(cell dies)

Insufficient output(cell dies)

Indirect effects (drug binds to gene productrelated to the mutated one)

Output Output

Drug

Indirect effects (2)

Drug

Insufficient output

Haploinsufficiency(heterozygous mutation)

Drug

Insufficient output

Homozygous mutation

Principle of ”molecular bar-codes”:

Synthetic DNA sequence (”tag” or ”bar-code”) is inserted adjacent to site of genomic disruption

Due to flanking common sequences,the bar-code is PCR-amplifiable andcan be hybridized to DNA array

Competition experiments using the ”bar-code” concept

Tunicamycin controlexperiment:

• array hybridization

• quantification

A sensor in yeast for ligand binding

• deletion of the yeast’s own DHFR gene (dhr1) from the genome• insertion in mouse DHFR of heterologous amino acids with binding domains from different proteins• ts variant of DHFR makes the protein extra sensitive to conformationalchanges• binding of ligand gives increased stability of DHFR

Tucker & Fields, Nature Biotechnology 19:1042 (2001)

Growth is selectivefor ligand interaction

Growth correlates withbinding affinity

Yeast-based p53 diagnosis

• p53 is the most commonly mutated gene in human tumors• wide mutation spectrum, many mutated alleles• p53 is transcription factor; functional assay time-saving• variation: ADE2 gene as a reporter. Colony-color based readout(ratio red/white colonies), diagnosis of heterozygous mutations possible

• 7-TM receptor in yeast eliminated• mammalian homolog expressed,interacts with yeast G-protein• large numbers of yeast clones canbe screened efficiently • variety of marker genes makespossible selection both for andagainst interactions

Further improvements:

• express human G-protein insteadof yeast homolog

• delete FAR1 gene to preventcell cycle arrest as a result ofpathway activation

Identification of surrogate agonists for the human FPRL-1 receptor by autocrine selection in yeastChristine Klein et al.

Nature Biotechnology 16, 1334 - 1337 (1998)

• Human formyl peptide receptor like-1 (FPRL-1) receptor expressed in yeast

• Expression of random peptides (13-mers) linked to secretion signal

• Activation of receptor-coupled pathway linked to expression of HIS3 reporter

• Three rounds of selection yielded 5 positive peptides out of 106 initial clones