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Yeast
in drug development
Properties:
Methodology:
Applications:
unicellular eukaryote
forward and reverse genetics, two-hybrid
system, surrogate host
Model system for cellular eukaryotic functions
(animal or plant):
Intracellular signal transduction
DNA repair, replication, cell cycle
transcription
chromosome biology
protein transport
water transport
etc.
Protein-protein interactions
Global transcriptional regulation
Drug target identification
Drug screening/selection
Disease diagnostics
Model 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 counterselection
possible
• 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
Hepatitis B surface antigen (HbSAg)
Advantages:
• higher yield, faster growth than animal cells
• eukaryotic post-translational modifications
+
=
Yeast as a genetically tractable organism to identify drug targets,
establish cellular disease models, diagnosis, and for screening of
receptor ligands and lead compounds
The yeast genome
is densely packed
with genes
Saccharomyces
cerevisiae is the
most informationdense of all
experimental
organisms
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 information
in databases
Genetic engineering of yeast for drug sensitivity assays
Problem:
Solutions:
• Many hydrophobic low Mw compounds
do not enter the yeast cell
• make mutants defective in membrane lipid
biosynthesis, e.g. erg6
• Yeast has multiple transport proteins involved
In drug transport: 35 in major facilitator superfamily, plus 14 ABC transporters
• make multiple deletions of genes for
transporter proteins.
• Each transporter is highly promiscuous
• Nine-tuple deletant strain 100x more
sensitive to wide range of compounds
The ”compendium” approach:
Goal: to identify protein
targets of drugs with unknown
mechanism
Principle: disturbance of a pathway by
a drug or a mutation should yield
similar phenotypes, including on
transcript profiles
Method: clustering of transcript profiles
of yeast deletion mutants with
experimental conditions
Hughes et al., Cell 102:109 (2000)
Transcript profile clustering
identifies similarity between
dyclonine treatment and
disruption of ergosterol metabolism
The two-hybrid system
Gal4
AD
Y
Prey
X
Bait
Gal4
DB
HIS3
Gal4 binding
site
No growth on
-His medium
Gal4
AD
Y’
X
Gal4
DB
HIS3
Gal4 binding
site
Growth on
-His medium
Physical interaction
between hybrid
proteins activates
reporter gene under
control of Gal4
transcription factor
Network of physical protein complexes in yeast
Gavin et al. Nature 415:141 (2002)
Internet databases combine physical and
genetic interaction information
Genetic and physical interactions visualised by
dedicated software
AD
Reverse two-hybrid: selection of
interaction-disrupting agents and
mapping of interaction domains
Y
X
Z
GBD
LBD
HIS3
Gal4 binding
site
URA3
1.
a) Mutagenize Y
LexA binding
site
or
AD
b) Transform with
library encoding random
peptides, or add library of
organic compounds
Y
X
2. Select for 5-FOAR and His+
GBD
Z
LBD
HIS3
Gal4 binding
site
URA3
LexA binding
site
Extensions of two-hybrid for drug target identification:
aptamers and DB-anchored drugs
Selection for aptamers that
bind to the bait
Selection for aptamers that
disrupt an interaction
Selection for proteins that bind
to a drug which is anchored to a
DB through a covalent link to another
drug
Systematic analysis of
synthetic lethality
by SGA – ”synthetic
gene arrays”
SGA analysis clusters
related genes and
functional groups
Network of genetically connected
gene functions
Tong et al., Science 303:808 – 813 (2004)
Two-dimensional hierarchical clustering
of the synthetic genetic interactions determined
by SGA analysis
The ”Seattle Project”
Antitumor treatments (drugs, irradiation) are tested on sets of yeast mutants
where 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
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.
Genetics
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
Reverse genetics
Aim
Aim
- To go from function to gene
Means
-Screen populations of mutants for
gain or loss of a particular function
- 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:
Step 2: test cognate homozygous mutations:
• alg7/alg7 wild-type sensitivity
• ALG7 (Asn-linked glycosyl transferase;
previously known target)
• ymr007w/ymr007w supersensitive
• ymr266w/ymr266w supersensitive
• YMR007w (unknown function)
• YMR266w (membrane transport)
 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)
Normal situation
Drug
Output
Smaller output
Haploinsufficiency
(less gene product)
Drug
Direct drug effect on target (2)
Insufficient output
(cell dies)
Homozygous mutation
(no gene product)
Drug
Insufficient output
(cell dies)
Insufficient output
(cell dies)
Indirect effects (drug binds to gene product
related to the mutated one)
Drug
Output
Output
Indirect effects (2)
Haploinsufficiency
(heterozygous mutation)
Drug
Homozygous mutation
Drug
Insufficient output
Insufficient output
Principle of ”molecular bar-codes”:
Synthetic DNA sequence (”tag” or ”barcode”) is inserted adjacent to site of
genomic disruption
Due to flanking common sequences,
the bar-code is PCR-amplifiable and
can be hybridized to DNA array
Competition experiments using the ”bar-code” concept
Tunicamycin control
experiment:
• 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 conformational
changes
• binding of ligand gives increased stability of DHFR
Tucker & Fields, Nature Biotechnology 19:1042 (2001)
Growth is selective
for ligand interaction
Growth correlates with
binding 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 can
be screened efficiently
• variety of marker genes makes
possible selection both for and
against interactions
Further improvements:
• express human G-protein instead
of yeast homolog
• delete FAR1 gene to prevent
cell cycle arrest as a result of
pathway activation
Identification of surrogate agonists for the
human FPRL-1 receptor by autocrine selection
in yeast
Christine 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