High Density Transposon Mutant Profiling to Enable Discovery …€¦ · transposons....
1
Clive Mason 1 , Paul Meo, Tim Avis, Elena Breidenstein, Christopher Coward, Sara Malara, David Jones, Joana Martins, Nawaz Khan Platform Discovery, Summit Therapeutics, Cambridge, UK . High Density Transposon Mutant Profiling to Enable Discovery and Development of Novel Antimicrobials Background: There is an urgent need for new antibiotics with novel mechanisms of action to treat life-threatening infections caused by multi-drug resistant bacteria. Summit Therapeutics’s proprietary transposon-based platform technology (Discuva Platform) allows the identification of totally novel anti-bacterial chemical classes from phenotypic screening revealing the molecular targets and mechanisms of resistance of hit compounds. This platform is also used to refine target/resistance profiles throughout chemical optimisation allowing selection of the best clinical candidates. Methods: Transposon Library Generation • High density transposon mutant libraries were generated in identified bacterial strains (Figure 1). Tn5 or mariner transposition methodologies were adapted to ensure maximum efficiency in the targeted strain. Mutant pools were generated to ensure a frequency of insertion across the genome every 5-10bp (Figure 2). Depending on the insertion context the transposon can give rise to activation, downregulation or inactivation at a particular loci. The targeted pathogens capture the priority and urgent threat organisms recognised by CDC 1 and WHO 2 . Summit Therapeutics [email protected] +44 (0)1223 394200 Abstract 662 Sunday 10 th June 2018 ASM Microbe Atlanta Figure 1: Range of bacterial strains represented with high density transposon libraries to enable antibiotic drug discovery and development Figure 2: Section of S. aureus (left) and E. coli (right) genome showing high density transposon insertion. Boxed section in lower panels reveals essential genes lacking insertion. Gene-modulating transposons transcriptional promoters Tn libraries in multiple genus/species/strains of antibiotic-sensitive and resistant bacteria Transposon libraries + Compounds • Multiple strains • Multiple concentrations Next Generation Sequencing • >Billion sequence reads/day • Sort, process reads • Map to genome Data Assignment • Quality control • Statistical analysis • Essential gene id • Database storage Comparative Analysis and Biochemical Pathway Mapping • Identification of critical genes • Pathways analysis • Deconvolution - Antibiotic target(s) - Resistance genes Target Mapping Confirmation Figure 3: The Discuva Technology consisting of high density transposon mutants libraries in bacterial pathogens, Next Generation Sequencing and bespoke bioinformatic data processing and analysis tools Figure 4: Activation signals revealed following exposure of the E. coli transposon library to fosfomycin Figure 5: Disruption (inactivation) signals revealed following exposure of the E. coli transposon library to fosfomycin Figure 7: Iterative cycle of profiling through the Discuva Technology to track SAR and inform on compound prioritisation and optimisation HTS hits, follow-up compounds and analogs Map all compound- specific mutations to bacterial genomes Identify all essential target & resistance genes Map and track target, pathway & resistance impacts Chemical optimisation Discuva Technology Figure 6: (A) Unbiased vector analysis reveals differentiation between antibiotic classes, and gives a first indication if a novel compound exploits new biological space. (B) Gene interaction networks give a detailed view of shared and distinct impacts for antimicrobial compounds A Conclusions: There is a desperate need for differentiated antibiotics represented by new chemotypes associated with novel mechanisms of action that are devoid of pre-existing resistance liabilities. Our Discuva Platform brings together a proprietary transposon-based platform technology and bespoke bioinformatics software to revolutionise the antimicrobial discovery and development process. It empowers phenotypic screening by rapidly moving from a antimicrobial activity to a genome-wide interaction profile to inform on compound mechanism of action and resistance liabilities. The Discuva Platform not only provides a mechanism to prioritise compounds from HTS but also enables informed decisions to be taken during lead optimisation. Ultimately, the Discuva Platform can select from within a chemical series or across different series the most optimal compound for clinical development. References: 1. CDC Antimicrobial Resistance Threats Report 2013 2. WHO priority pathogens list for R&D of new antibiotics 2017 3. Nilsson et al (2003) AAC : 47 (9) pp: 2850-8 • This is coupled with Next Generation Sequencing Technology that simultaneously assays all of the transposon mutants in a single pool • Insertion site data is mapped, analysed and interpreted to reveal a genome-wide profile of a compound on a target pathogen. Target and Resistance Identification • The mechanism of action and resistance profile are identified using the Discuva Technology (Figure 3), which combines high density transposon mutant libraries in the target pathogens with a bespoke bioinformatics platform. Technology Exemplification: Fosfomycin Exposure of E. coli (BW25113) transposon library to fosfomycin (fractions and multiples of MIC) reveals key target and resistance impacts (Figure 4 and 5) of this antibiotic. Upregulation of murA (target) is a strong driver of resistance (to 4xMIC), the analysis also identifies upregulation of a carbon-phosphorus lyase complex (phnG-P) as a potential driver for resistance through metabolism and inactivation of Fosfomycin (Figure 4). . Key disruption (inactivation) signals (Figure 5) reflect the mode of uptake and transport of Fosfomycin; Disruption of the hexose phosphate transporter (uhpT,C,A) instils a survival benefit by reducing uptake of fosfomycin. Additionally expression of uhpTCA is regulated by cAMP levels and disruption signals for cyoA and ptsI reflect a mechanism to reduce cAMP and hence downregulate the transporter. Disruption at the pst loci (pstB,A,C,S) also confers a mild survival benefit (below MIC) attributed to the function in phosphate sensing and transport. The genomic profile revealed by the Discuva Technology aligns very well with reported in vitro and clinical resistance identified for fosfomycin 1 . Insertion site data is also used for comparative analysis across antibiotic classes and for benchmarking novel compounds (Fig. 6) B Technology Exploitation This powerful genome profiling technology is routinely being deployed on internal and collaborative antibiotic discovery and development projects. The process has been adapted to deliver a throughput and turnaround time compatible with cycles of chemistry (SAR evolution and compound optimisation) and to inform on the next iteration. Application of this technology has been exemplified within our own antibiotic discovery programmes targeting Neisseria gonorrhoeae (Poster #647/648) . Gene Essentiality Mechanism of Action Resistance Profiling Compound Optimisation Optimising Combinations Maximise Clinical Utility
Transcript of High Density Transposon Mutant Profiling to Enable Discovery …€¦ · transposons....
Clive Mason1, Paul Meo, Tim Avis, Elena Breidenstein, Christopher Coward, Sara Malara, David Jones, Joana Martins, Nawaz KhanPlatform Discovery, Summit Therapeutics, Cambridge, UK
.
High Density Transposon Mutant Profiling to Enable Discovery and Development of Novel Antimicrobials
Background:There is an urgent need for new antibiotics with novel mechanisms of
action to treat life-threatening infections caused by multi-drug resistant
bacteria. Summit Therapeutics’s proprietary transposon-based platform
technology (Discuva Platform) allows the identification of totally novel
anti-bacterial chemical classes from phenotypic screening revealing the
molecular targets and mechanisms of resistance of hit compounds. This
platform is also used to refine target/resistance profiles throughout
chemical optimisation allowing selection of the best clinical candidates.
Methods: Transposon Library Generation• High density transposon mutant libraries were generated in identified
bacterial strains (Figure 1). Tn5 or mariner transposition
methodologies were adapted to ensure maximum efficiency in the
targeted strain. Mutant pools were generated to ensure a frequency of
insertion across the genome every 5-10bp (Figure 2). Depending on
the insertion context the transposon can give rise to activation,
downregulation or inactivation at a particular loci. The targeted
pathogens capture the priority and urgent threat organisms
recognised by CDC1 and WHO2.
Summit [email protected]
+44 (0)1223 394200
Abstract 662Sunday 10th June 2018ASM Microbe Atlanta
Figure 1: Range of bacterial strains represented with high density transposon libraries to enable antibiotic drug discovery and development
Figure 2: Section of S. aureus (left) and E. coli (right) genome showing high density transposon insertion. Boxed section in lower panels reveals essential genes lacking insertion.
Gene-modulating transposons
transcriptional promoters
Tn libraries in multiple genus/species/strains of antibiotic-sensitive and resistant bacteria
Transposon libraries + Compounds
• Multiple strains• Multiple
concentrations
Next Generation Sequencing
• >Billion sequence reads/day• Sort, process reads• Map to genome
Data Assignment
• Quality control• Statistical analysis• Essential gene id• Database storage
Comparative Analysis and Biochemical Pathway Mapping
• Identification of critical genes• Pathways analysis• Deconvolution-Antibiotic target(s)-Resistance genes
Target Mapping Confirmation
Figure 3: The Discuva Technology consisting of highdensity transposon mutants libraries in bacterialpathogens, Next Generation Sequencing and bespokebioinformatic data processing and analysis tools
Figure 4: Activation signals revealed following exposure of the E. coli transposon library to fosfomycin
Figure 5: Disruption (inactivation) signals revealed following exposure of the E. coli transposon library to fosfomycin
Figure 7: Iterative cycle of profiling through the Discuva Technology to track SAR and inform on compound prioritisation and optimisation
HTS hits, follow-up
compounds and analogs
Map all compound-
specific mutations to
bacterial genomes
Identify all essential target &
resistance genes
Map and track target,
pathway & resistance
impacts
Chemical optimisation
DiscuvaTechnology
Figure 6: (A) Unbiased vector analysis reveals differentiation between antibiotic classes, and gives a first indication if a novel compound exploits new biological space. (B) Gene interaction networks give a detailed view of shared and distinct impacts for antimicrobial compounds
A
Conclusions:There is a desperate need for differentiated antibiotics represented by new chemotypes associated
with novel mechanisms of action that are devoid of pre-existing resistance liabilities. Our Discuva
Platform brings together a proprietary transposon-based platform technology and bespoke
bioinformatics software to revolutionise the antimicrobial discovery and development process. It
empowers phenotypic screening by rapidly moving from a antimicrobial activity to a genome-wide
interaction profile to inform on compound mechanism of action and resistance liabilities. The Discuva
Platform not only provides a mechanism to prioritise compounds from HTS but also enables
informed decisions to be taken during lead optimisation. Ultimately, the Discuva Platform can select
from within a chemical series or across different series the most optimal compound for clinical
development.
References:1. CDC Antimicrobial Resistance Threats Report 2013
2. WHO priority pathogens list for R&D of new antibiotics 2017
3. Nilsson et al (2003) AAC : 47 (9) pp: 2850-8
• This is coupled with Next Generation Sequencing Technology that
simultaneously assays all of the transposon mutants in a single pool
• Insertion site data is mapped, analysed and interpreted to reveal a
genome-wide profile of a compound on a target pathogen.
Target and Resistance Identification• The mechanism of action and resistance profile are identified using
the Discuva Technology (Figure 3), which combines high density
transposon mutant libraries in the target pathogens with a bespoke
bioinformatics platform.
Technology Exemplification: FosfomycinExposure of E. coli (BW25113) transposon library to fosfomycin (fractions and multiples of MIC) reveals key target and resistance
impacts (Figure 4 and 5) of this antibiotic. Upregulation of murA (target) is a strong driver of resistance (to 4xMIC), the analysis
also identifies upregulation of a carbon-phosphorus lyase complex (phnG-P) as a potential driver for resistance through
metabolism and inactivation of Fosfomycin (Figure 4)..
Key disruption (inactivation) signals (Figure 5) reflect the mode of uptake and transport of Fosfomycin; Disruption of the hexose
phosphate transporter (uhpT,C,A) instils a survival benefit by reducing uptake of fosfomycin. Additionally expression of uhpTCA is
regulated by cAMP levels and disruption signals for cyoA and ptsI reflect a mechanism to reduce cAMP and hence downregulate
the transporter. Disruption at the pst loci (pstB,A,C,S) also confers a mild survival benefit (below MIC) attributed to the function in
phosphate sensing and transport.
The genomic profile revealed by the Discuva Technology aligns very well with reported in vitro and clinical resistance identified for
fosfomycin1.
Insertion site data is also used for comparative analysis across antibiotic classes and for benchmarking novel compounds (Fig. 6)
B
Technology ExploitationThis powerful genome profiling technology is routinely being deployed on internal and collaborative
antibiotic discovery and development projects. The process has been adapted to deliver a throughput
and turnaround time compatible with cycles of chemistry (SAR evolution and compound optimisation)
and to inform on the next iteration.
Application of this technology has been exemplified within our own antibiotic discovery programmes
targeting Neisseria gonorrhoeae (Poster #647/648).
Gene Essentiality Mechanism of Action Resistance Profiling Compound Optimisation Optimising Combinations Maximise Clinical Utility
