[TMP] (µM) DHF › meetings › abscicon2017 › e... · DHF D27 NADPH 0 25 50 75 100 Time (sec) 0...
1
Towards understanding the evolution of trimethoprim resistance in E. coli Yusuf Talha TAMER 1,2 , Erdal Toprak 1 1, Green Center for Systems Biology, University of Texas Southwestern Medical Center Abstract & Introduction Methods Biochemical Parameters bifurcates in 3 rd or higher order mutants Figure 1. 3D structure of DHFR (PDB ID: 1rx2). Experimentally observed resistance conferring mutations are shown with colored sticks Both high order mutation cycles and ensemble average epistasis calculations used to understand the epistatic structure A highly connected epistatic network is driving DHFR to increased catalysis and higher trimethoprim resistance k cat & K m Measurements K i Measurements D27 DHF NADPH 0 25 50 75 100 Time (sec) 0 3 6 9 12 [DHF] (μM) ∆t ∆DHF m 1 m 3 m 7 m 9 m 11 m 13 m 15 m 5 = ∆DHF ∆t 0 2 4 6 8 10 0.007 0.014 0.026 0.057 V max /2 V max m 2 m 3 K m m 1 V 0 (μM/sec) [DHF] (μM) Figure2. A340 decreases over the course of reaction showing that DHF and NADPH is converted to THF and NADP + . Decreasing conversion rate can be used to fit in Michelis-Menten Curve and to calculate the K m and k cat values. 0 10 15 20 25 30 35 Time (sec) 0 2 4 6 8 10 12 [DHF] (μM) [TMP] =10μM [TMP] =3.3μM [TMP] =333nM [TMP] =10nM [TMP] = 0nM 5 0 10 10 3 10 5 [TMP] (nM) 0 50 100 150 200 250 V 0 (nM/sec) K i V 0 = V max [S] K m + [S] . V max [S] . V 0 = K app + [S] Figure3. Since the inhibition is competitive, increasing concentrations of trimethoprim decreases the rate and using relative K m (or K app ) and actual K m values we can calculate K i (relative binding affinity to trimethoprim) K app = K m [I] K i . WT k cat /K m (mM -1 s -1 ) K i (μM) 10 -3 10 -2 10 -1 10 0 10 1 10 -1 10 2 10 1 10 0 10 -2 10 4 10 3 WT Figure4. Acquisition of each mutation decreases the binding affinity to trimethoprim. Accumulation of P21L (red mutation) causes a bifurcation in higher order mutations. Each color is represents a mutation shown in the legend pentagon. Circles denote the mutants observed in the forward evolution experiment that is repeated for 33 independent experimental cultures • We chose THF production as a fitness function to calculate the epistatic interactions of DHFR mutants. • Antibiotic resistance is a growing health problem. Understanding the evolution of resistance will help battle against the drug-resistant infections. • Trimethoprim is an antibiotic that competitively inhibits Dihydrofolate Reductase (DHFR) enzyme that is essential for DNA and amino acid metabolism. • Both clinically and experimentally evolved E. coli populations acquire mutations only in the folA gene and its regulatory region encoding the DHFR enzyme. • In this study, we made all combinations of 5 resistance-conferring mutations and biochemically characterized their substrate binding, catalytic activity and trimethoprim affinity. • Results revealed an epistatically coupled highly cooperative network. THF Production = k cat K m [E] [S] . . 1+ + [S] K m [I] K i Biochemical Epistasis or Mutation Cycles Ensemble Average Epistasis V enzyme [TMP] (μM) MIC enzyme V max Wild Type Mutant-1 Mutant-2 Conclusions References 1 2 3 4 5 Degree of Epistasis -2000 0 2000 Ensemble Averaged Epistasis Epistasis for MIC enzyme 1 2 3 4 5 Degree of Epistasis -2 0 2 Ensemble Averaged Epistasis Epistasis for V max 1 2 3 4 5 Degree of Epistasis 0 1000 2000 3000 |Ensemble Averaged Epistasis| mean 1 2 3 4 5 Degree of Epistasis 0 1 2 |Ensemble Averaged Epistasis| mean 1 2 3 4 5 Degree of Epistasis -2000 0 2000 Mutant Cycle Epistasis for MIC enzyme 1 2 3 4 5 Degree of Epistasis -2 0 2 Mutant Cycle Epistasis for V max 1 2 3 4 5 Degree of Epistasis 0 1000 2000 3000 |Mutant Cycle| mean 1 2 3 4 5 Degree of Epistasis 0 1 2 |Mutant Cycle| mean Biochemical Epistasis or Mutation Cycles Ensemble Average Epistasis • Increased epistasis correlates with the degree of epistasis showing that both V max and MIC enzyme are controlled with a cooperative network. • P21L mutation decreases the catalytic power drastically when there are two or more background mutations in folA / DHFR. • Exponentially increasing trend in ensemble averaged epistasis is showing that there is a highly connected network of residues working for both THF production and trimethoprim resistance. • Palmer, A. C., Toprak, E., Baym, M., Kim, S., Veres, A., Bershtein, S., & Kishony, R. (2015). Delayed commit- ment to evolutionary fate in antibiotic resistance fitness landscapes. Nat Commun, 6, 7385. doi:10.1038/ncom- ms8385 • Poelwijk, F. J., Krishna, V., & Ranganathan, R. (2016). The Context-Dependence of Mutations: A Linkage of Formalisms. PLoS Comput Biol, 12(6), e1004771. doi:10.1371/journal.pcbi.1004771 • Toprak, E., Veres, A., Michel, J. B., Chait, R., Hartl, D. L., & Kishony, R. (2011). Evolutionary paths to antibiotic resistance under dynamically sustained drug selection. Nat Genet, 44(1), 101-105. doi:10.1038/ng.1034
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Towards understanding the evolution of trimethoprim resistance in E. coli
Yusuf Talha TAMER1,2, Erdal Toprak1
1, Green Center for Systems Biology, University of Texas Southwestern Medical Center Abstract & Introduction
Methods
Biochemical Parameters bifurcates in 3rd or higher order mutants
Figure 1. 3D structure of DHFR (PDB ID: 1rx2). Experimentally observed resistance conferring mutations are shown with colored sticks
Both high order mutation cycles and ensemble average epistasis calculations used to understand the epistatic structure
A highly connected epistatic network is driving DHFR to increased catalysis and higher trimethoprim resistance
kcat & Km Measurements
Ki Measurements
D27DHF
NADPH
0 25 50 75 100Time (sec)
0
3
6
9
12
[DH
F] (µ
M)
∆t∆DHF
m1
m3
m7
m9m11 m13 m15
m5=∆DHF
∆t
0 2 4 6 8 100.007
0.014
0.026
0.057
Vmax/2
Vmax
m2m3
Km
m1
V0 (µ
M/s
ec)
[DHF] (µM)
Figure2. A340 decreases over the course of reaction showing that DHF and NADPH is converted to THF and NADP+. Decreasing conversion rate can be used to fit in Michelis-Menten Curve and to calculate the Km and kcat values.
0 10 15 20 25 30 35Time (sec)
0
2
4
6
8
10
12
[DH
F] (µ
M)
[TMP] =10µM
[TMP] =3.3µM
[TMP] =333nM[TMP] =10nM
[TMP] = 0nM
5 0 10 103 105
[TMP] (nM) 0
50
100
150
200
250
V0 (
nM/s
ec)
Ki
V0 =
Vmax [S]Km + [S]
.
Vmax [S].V0 = Kapp+ [S] Figure3. Since the inhibition is
competitive, increasing concentrations of trimethoprim decreases the rate and using relative Km (or Kapp) and actual Km values we can calculate Ki (relative binding affinity to trimethoprim)
Kapp = Km [I]Ki
.
WT
k cat/K
m (m
M-1s-1
)
Ki (µM)10-3
10-2
10-1
100
101
10-1 10210110010-2 104103
WT
Figure4. Acquisition of each mutation decreases the binding affinity to trimethoprim. Accumulation of P21L (red mutation) causes a bifurcation in higher order mutations. Each color is represents a mutation shown in the legend pentagon. Circles denote the mutants observed in the forward evolution experiment that is repeated for 33 independent experimental cultures
• We chose THF production as a fitness function to calculate the epistatic interactions of DHFR mutants.
• Antibiotic resistance is a growing health problem. Understanding the evolution of resistance will help battle against the drug-resistant infections.• Trimethoprim is an antibiotic that competitively inhibits Dihydrofolate Reductase (DHFR) enzyme that is essential for DNA and amino acid metabolism. • Both clinically and experimentally evolved E. coli populations acquire mutations only in the folA gene and its regulatory region encoding the DHFR enzyme.• In this study, we made all combinations of 5 resistance-conferring mutations and biochemically characterized their substrate binding, catalytic activity and trimethoprim affinity.• Results revealed an epistatically coupled highly cooperative network.
THF Production = kcat
Km
[E] [S]..
1+ +[S]Km
[I]Ki
Biochemical Epistasis or Mutation Cycles
Ensemble AverageEpistasis
V enzy
me
[TMP] (µM)
MICenzyme
VmaxWild TypeMutant-1Mutant-2
Conclusions
References
1 2 3 4 5Degree of Epistasis
-2000
0
2000
Ense
mbl
e Av
erag
edEp
ista
sis
Epistasis for MICenzyme
1 2 3 4 5Degree of Epistasis
-2
0
2
Ense
mbl
e Av
erag
edEp
ista
sis
Epistasis for Vmax
1 2 3 4 5Degree of Epistasis
0
1000
2000
3000
|Ens
embl
e Av
erag
edEp
ista
sis|
mea
n
1 2 3 4 5Degree of Epistasis
0
1
2
|Ens
embl
e Av
erag
edEp
ista
sis|
mea
n
1 2 3 4 5Degree of Epistasis
-2000
0
2000
Mut
ant C
ycle
Epistasis for MICenzyme
1 2 3 4 5Degree of Epistasis
-2
0
2
Mut
ant C
ycle
Epistasis for Vmax
1 2 3 4 5Degree of Epistasis
0
1000
2000
3000
|Mut
ant C
ycle
| mea
n
1 2 3 4 5Degree of Epistasis
0
1
2
|Mut
ant C
ycle
| mea
n
Biochemical Epistasis or Mutation Cycles
Ensemble AverageEpistasis
• Increased epistasis correlates with the degree of epistasis showing that both Vmax and MICenzyme are controlled with a cooperative network.
• P21L mutation decreases the catalytic power drastically when there are two or more background mutations in folA / DHFR.
• Exponentially increasing trend in ensemble averaged epistasis is showing that there is a highly connected network of residues working for both THF production and trimethoprim resistance.
• Palmer, A. C., Toprak, E., Baym, M., Kim, S., Veres, A., Bershtein, S., & Kishony, R. (2015). Delayed commit-ment to evolutionary fate in antibiotic resistance fitness landscapes. Nat Commun, 6, 7385. doi:10.1038/ncom-ms8385• Poelwijk, F. J., Krishna, V., & Ranganathan, R. (2016). The Context-Dependence of Mutations: A Linkage of Formalisms. PLoS Comput Biol, 12(6), e1004771. doi:10.1371/journal.pcbi.1004771• Toprak, E., Veres, A., Michel, J. B., Chait, R., Hartl, D. L., & Kishony, R. (2011). Evolutionary paths to antibiotic resistance under dynamically sustained drug selection. Nat Genet, 44(1), 101-105. doi:10.1038/ng.1034
