Gene Essentialities of Bacterial Systems
Introduction of following two talks:
Takehide Soh “Predicting Gene Knockout Effects by Minimal Pathway Enumeration”
Takeyuki Tamura “Predicting essential genes via impact degree on metabolic networks”
TOMOYA BABA
Research Organization of Information and Systems
Transdisciplinary Research Integration Center
National Institute of Genetics, Misima, Japan
Joint work with: Barry L. Wanner (Purdue Univ., US)
Masaru Tomita (Keio Univ., Japan)
Hirotada Mori (NAIST, Japan)
ISSSB’11, Nov. 16th 2011, Shonan Village Centre, Japan
1
Systems Engineering
Blueprint
Parts
Genes (Genome)
Proteins
Robot
Organism
Human
E. coli
Systems Biology
2
Escherichia coli K-12
Genome sequenced at 1997
Revised at 2006
Re-annotation at 2006
Well-characterized Bacteria
Science (1997)
32%
14%
54%
Riley M., Nuc. Acid. Res., 34, 1-9 (2006)
3
Ultimate Goal : Comprehensive Understanding of Life
E. coli cell
310
Translation
mRNA
Protein
Transcription
Promoter
ORF
Enzyme
Regulation
Chromosome
Genome DNA
Unknown
691
405
1,484
Transport
756
Secretion
Signal-Transduction
etc
Metabolites
Replication
Cell-Division
446
Yes it is, however, life is so complicated systems.
Simple Question
Which genes are essential for the life systems?
4
Gene-Knockout Experimental Method
kan
Step 1. PCR of Maker gene
Step 2. Transformation
l Red
recombinase
E. coli
Wild type cell
(BW25113)
(30℃)
pKD46
(ts-ori)
Target Gene
Chromosome
bla
37℃, LB(Km+)
Gene-knockout cell
1, Precise design
2, Complete deletion
Chromosome
Datsenko K.A., Wanner B.L., (2000) Proc. Natl. Acad. Sci. 97, 6640.
5
Designing for In-frame Deletion
Step 1. PCR of Kanamycin resistance (kan) gene
H1
P1 FRT
FRT
Kanamycin resistance gene
H2
P2
H1
H2
geneB (target)
geneA
geneC
SD of downstream gene
Met
21 bp
Step 2. Transformation
FRT
l Red recombinase
FRT
Kanamycin resistance gene
FRT
( Step 3. Elimination of kan gene)
geneA
21 bp
geneC
FLP recombinase
FRT
34 a.a. (102 bp)
MIPGIRRPAVRSSTSLGSIGTSKQLQPT+6aa
6
Single Gene-Knockout Results
Essential
303
Result
•
73
Small ORFs
(no longer
303 genes (7% of total genes) are essential
in E.annotated)
coli K-12.
3912
with annotation
3985
Keio collection
Total targeted ORFs
4288
Named genes
2157
y genes
1755
E: 1819
C: 1655
ORF evidence
E; experimental
C; computational
C: 331
E: 100
Baba T., (2006) Mol. Syst. Biol. 2006, 2, 8.
7
Classification of E. coli K-12 Gene Functions
Essential Total
303 4288
77
170
15
288
237
15
34
19
9
133
39
219
11
151
1
253
6
187
6
281
8
355
7
390
11
83
29
144
24
96
5 95
15
448
18
447
COGs (Clusters of Orthologous Groups of proteins) category
Information storage and processing ( 107 / 695 )
J Translation, ribosomal structure and biogenesis
K Transcription
L DNA replication, recombination and repair
Cellular processes ( 85 / 977 )
D Cell division and chromosome partitioning
O Posttranslational modification, protein turnover, chaperones
Result
M Cell envelope biogenesis, outer membrane
motility and secretion
2. N90Cellgenes
(6% of metabolic genes) are essential.
P Inorganic ion transport and metabolism
T Signal transduction mechanisms
Metabolism ( 90 / 1,444)
C Energy production and conversion
G Carbohydrate transport and metabolism
E Amino acid transport and metabolism
F Nucleotide transport and metabolism
H Coenzyme metabolism
I Lipid metabolism
Q Secondary metabolites biosynthesis, transport and catabolism
Poorly characterized ( 59 / 2,109)
R General function prediction only
S, U or V
Function unknown
26
20
10
No COG assignment
1214
0
10
20
% of Essential or Total ORFs
Baba T., (2006) Mol. Syst. Biol. 2006, 2, 8.
8
Growth of Gene-Knockout Mutants
OD600
1.2
MOPS-0.4% Glucose (48 hrs)
1.0
AVE-2SD
AVE+2SD
COGs category
Result
◆; Information essential
storage and processing
3. 104 genes (7% of metabolic genes) are conditionally
in glucose minimum medium.
■; Cellular processes
▲; Metabolism
●; Poorly characterized
0.8
●; No COG assignment
0.6
Nucleotide
23 Genes
AVE+2SD
Auxotroph
Conditionally Essential
0.4
(Metabolism Genes)
0.2
AVE-2SD
0.0
0.0
0.2
0.4
0.6
LB (22 hrs)
0.8
1.0
1.2
OD600
Amino Acid
81 Genes
Baba T., (2006) Mol. Syst. Biol. 2006, 2, 8.
9
Metabolic Pathway of E. coli (1,163 genes / 1,119 metabolites)
Result
Glucose
4. A lot of detour pathways are existing in E. coli metabolic pathway.
Pentose phosphate
pathway
(Detour pathway)
Glycolysis
TCA
Pyruvate
10
Cell Growth of Glycolysis Gene Knockouts in E. coli
aGLC
galM
ADP
ATP
G1P
pgm
bGLC
G6P
F6P
glk
Glucose
DHAP tpiA
pfkA ADP
ATP pfkB
FBP
6PG
GAP
fbaA
fbaB
E4P
S7P
3.5
ATP
BPG
gapA
gapC
X5P
E4P
Pentose phosphate
pathway
(Detour pathway)
ADP pykA
pykF ATP
ADP
NADH
fbp
pgi
NAD
3PG
pgk
2PG
gpmA
gpmB
PEP
eno
PYR
ppsA
OAA
4 Essential Genes
TCA
R5P, S7P
(Far from Detour pathway?)
ACoA
LAC
FORM
wild
galM
3.0
glk
pgm
Growth (O.D.=600nm)
2.5
pgi
pfkA
2.0
pfkB
fbp
fbaB
1.5
tpiA
gapC
1.0
gpmB
Glucose
pykA
0.5
Minimal Medium
pykF
ppsA
0.0
0
6
12
18
24
30
Time (h)
36
42
48
Time (h)
11
Intracellular Expression of E. coli Cells
Glycolysis
遺伝子欠失株
rpe
Metabolites
mRNA
Proteins
Metabolites
134
Pentose phosphate
pathway
(Detour pathway)
Proteins
68
mRNA
85
Gene-Knockouts
Ishii N., Science, 316, 593 (2007)
12
Robustness of Metabolic Network
Metabolites
Proteins
Metabolic Flux (path-flow)
Forward
(Wild type)
Reverse
Regulation of
Gene Expression
Pentose phosphate
pathway
(Detour pathway)
Keeping Metabolic
Balance
Result
5. E. coli cells regulate the gene expression level for keeping metabolic balance .
Ishii N., Science, 316, 593 (2007)
13
Conclusions
1. 303 genes (7% of total genes) are essential in E. coli K-12.
2. 90 genes (6% of metabolic genes) are essential.
3. 104 genes (7% of metabolic genes) are conditionally essential in glucose minimum
medium.
4. A lot of detour pathways are existing in E. coli metabolic pathway.
5. E. coli cells regulate the gene expression level for keeping metabolic balance .
Further Question
What is meaning of metabolic essential and conditional essential genes in E. coli?
Are the detour pathway lengths (steps) related for them?
→ Takehide Soh “Predicting Gene Knockout Effects by Minimal Pathway Enumeration”
Are there another type or meaning of metabolic essential genes in E. coli?
→ Takeyuki Tamura “Predicting essential genes via impact degree on metabolic networks”
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