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Model-driven discovery of synergistic inhibitors against E. coli and S. enterica serovar Typhimurium targeting a novel synthetic lethal pair, aldA and prpC.

Aziz RK, Khaw VL, Monk JM, Brunk E, Lewis R, Loh SI, Mishra A, Nagle AA, Satyanarayana C, Dhakshinamoorthy S, Luche M, Kitchen DB, Andrews KA, Palsson BØ, Charusanti P - Front Microbiol (2015)

Bottom Line: Here, we reconcile this disparity by providing evidence that aldA and prpC form a synthetic lethal pair, as the double knockout could only be created through complementation with a plasmid-borne copy of aldA.Moreover, virtual and biological screening against the two proteins led to a set of compounds that inhibited the growth of E. coli and Salmonella enterica serovar Typhimurium synergistically at 100-200 μM individual concentrations.These results highlight the power of metabolic models to drive basic biological discovery and their potential use to discover new combination antibiotics.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology and Immunology, Faculty of Pharmacy, Cairo University Cairo, Egypt ; Department of Bioengineering, University of California, San Diego La Jolla, CA, USA.

ABSTRACT
Mathematical models of biochemical networks form a cornerstone of bacterial systems biology. Inconsistencies between simulation output and experimental data point to gaps in knowledge about the fundamental biology of the organism. One such inconsistency centers on the gene aldA in Escherichia coli: it is essential in a computational model of E. coli metabolism, but experimentally it is not. Here, we reconcile this disparity by providing evidence that aldA and prpC form a synthetic lethal pair, as the double knockout could only be created through complementation with a plasmid-borne copy of aldA. Moreover, virtual and biological screening against the two proteins led to a set of compounds that inhibited the growth of E. coli and Salmonella enterica serovar Typhimurium synergistically at 100-200 μM individual concentrations. These results highlight the power of metabolic models to drive basic biological discovery and their potential use to discover new combination antibiotics.

No MeSH data available.


Related in: MedlinePlus

Dose response matrix for ALDA-112/ALDA-170, and ALDA-112/PRPC-034 against E. coli and S. Typhimurium. The single agent effects are depicted in the far left column and along the bottom row of each matrix. Each square represents a unique combination of the indicated compounds, and the number represents the level of growth inhibition that was measured plus standard deviation. (A) The ALDA-112/ALDA-170 pair exhibits mostly additivite inhibition against both E. coli and S. Typhimurium, with synergy at 100–200 μM concentration (red boxes). (B) Likewise, ALDA-112/PRPC-034 primarily exhibits additive inhibition at most concentrations against E. coli but there is one region of synergy (red box) and another region of antagonism (yellow box). No discernible pattern against S. Typhimurium is observed.
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Figure 4: Dose response matrix for ALDA-112/ALDA-170, and ALDA-112/PRPC-034 against E. coli and S. Typhimurium. The single agent effects are depicted in the far left column and along the bottom row of each matrix. Each square represents a unique combination of the indicated compounds, and the number represents the level of growth inhibition that was measured plus standard deviation. (A) The ALDA-112/ALDA-170 pair exhibits mostly additivite inhibition against both E. coli and S. Typhimurium, with synergy at 100–200 μM concentration (red boxes). (B) Likewise, ALDA-112/PRPC-034 primarily exhibits additive inhibition at most concentrations against E. coli but there is one region of synergy (red box) and another region of antagonism (yellow box). No discernible pattern against S. Typhimurium is observed.

Mentions: Two hundred seventy-three compounds were identified from virtual screening against AldA and PrpC. The selected compounds were tested in an eight-point dose response format (top test concentration of 200 μM and twofold dilution) against E. coli and S. Typhimurium to determine their IC50 and percent inhibition (where IC50 could not be established) against the two bacteria. Although the virtual screening was carried out against protein targets, biological screening was performed as a growth inhibition assay in which the readout was bacterial growth. For all bacterial growth assay plates, the Z’ scores were greater than 0.5, and the percent CV for positive and negative controls on each assay plate were less than 10%. Furthermore, the MIC data generated with the reference antibiotics for each strain were consistent between multiple experimental days, confirming uniformity across the screening campaign. Two compounds targeting AldA, ALDA-112 and ALDA-170 exhibited growth inhibition against E. coli with an IC50 of 108 and 200 μM, respectively (Table 1). Two additional compounds, one targeting AldA (ALDA-087) and one targeting PrpC (PRPC-034), showed weaker activity against both E. coli and S. Typhimurium (>20% inhibition at 200 μM). IC50 values could not be determined for these two compounds due to their weak activity. The structures are shown in Figure 4 and Supplementary Figure S3.


Model-driven discovery of synergistic inhibitors against E. coli and S. enterica serovar Typhimurium targeting a novel synthetic lethal pair, aldA and prpC.

Aziz RK, Khaw VL, Monk JM, Brunk E, Lewis R, Loh SI, Mishra A, Nagle AA, Satyanarayana C, Dhakshinamoorthy S, Luche M, Kitchen DB, Andrews KA, Palsson BØ, Charusanti P - Front Microbiol (2015)

Dose response matrix for ALDA-112/ALDA-170, and ALDA-112/PRPC-034 against E. coli and S. Typhimurium. The single agent effects are depicted in the far left column and along the bottom row of each matrix. Each square represents a unique combination of the indicated compounds, and the number represents the level of growth inhibition that was measured plus standard deviation. (A) The ALDA-112/ALDA-170 pair exhibits mostly additivite inhibition against both E. coli and S. Typhimurium, with synergy at 100–200 μM concentration (red boxes). (B) Likewise, ALDA-112/PRPC-034 primarily exhibits additive inhibition at most concentrations against E. coli but there is one region of synergy (red box) and another region of antagonism (yellow box). No discernible pattern against S. Typhimurium is observed.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4585216&req=5

Figure 4: Dose response matrix for ALDA-112/ALDA-170, and ALDA-112/PRPC-034 against E. coli and S. Typhimurium. The single agent effects are depicted in the far left column and along the bottom row of each matrix. Each square represents a unique combination of the indicated compounds, and the number represents the level of growth inhibition that was measured plus standard deviation. (A) The ALDA-112/ALDA-170 pair exhibits mostly additivite inhibition against both E. coli and S. Typhimurium, with synergy at 100–200 μM concentration (red boxes). (B) Likewise, ALDA-112/PRPC-034 primarily exhibits additive inhibition at most concentrations against E. coli but there is one region of synergy (red box) and another region of antagonism (yellow box). No discernible pattern against S. Typhimurium is observed.
Mentions: Two hundred seventy-three compounds were identified from virtual screening against AldA and PrpC. The selected compounds were tested in an eight-point dose response format (top test concentration of 200 μM and twofold dilution) against E. coli and S. Typhimurium to determine their IC50 and percent inhibition (where IC50 could not be established) against the two bacteria. Although the virtual screening was carried out against protein targets, biological screening was performed as a growth inhibition assay in which the readout was bacterial growth. For all bacterial growth assay plates, the Z’ scores were greater than 0.5, and the percent CV for positive and negative controls on each assay plate were less than 10%. Furthermore, the MIC data generated with the reference antibiotics for each strain were consistent between multiple experimental days, confirming uniformity across the screening campaign. Two compounds targeting AldA, ALDA-112 and ALDA-170 exhibited growth inhibition against E. coli with an IC50 of 108 and 200 μM, respectively (Table 1). Two additional compounds, one targeting AldA (ALDA-087) and one targeting PrpC (PRPC-034), showed weaker activity against both E. coli and S. Typhimurium (>20% inhibition at 200 μM). IC50 values could not be determined for these two compounds due to their weak activity. The structures are shown in Figure 4 and Supplementary Figure S3.

Bottom Line: Here, we reconcile this disparity by providing evidence that aldA and prpC form a synthetic lethal pair, as the double knockout could only be created through complementation with a plasmid-borne copy of aldA.Moreover, virtual and biological screening against the two proteins led to a set of compounds that inhibited the growth of E. coli and Salmonella enterica serovar Typhimurium synergistically at 100-200 μM individual concentrations.These results highlight the power of metabolic models to drive basic biological discovery and their potential use to discover new combination antibiotics.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology and Immunology, Faculty of Pharmacy, Cairo University Cairo, Egypt ; Department of Bioengineering, University of California, San Diego La Jolla, CA, USA.

ABSTRACT
Mathematical models of biochemical networks form a cornerstone of bacterial systems biology. Inconsistencies between simulation output and experimental data point to gaps in knowledge about the fundamental biology of the organism. One such inconsistency centers on the gene aldA in Escherichia coli: it is essential in a computational model of E. coli metabolism, but experimentally it is not. Here, we reconcile this disparity by providing evidence that aldA and prpC form a synthetic lethal pair, as the double knockout could only be created through complementation with a plasmid-borne copy of aldA. Moreover, virtual and biological screening against the two proteins led to a set of compounds that inhibited the growth of E. coli and Salmonella enterica serovar Typhimurium synergistically at 100-200 μM individual concentrations. These results highlight the power of metabolic models to drive basic biological discovery and their potential use to discover new combination antibiotics.

No MeSH data available.


Related in: MedlinePlus