Periodic Reporting for period 4 - uCARE (Understanding Circumventing Antibiotic REsistance)
Período documentado: 2023-09-01 hasta 2024-08-31
Infections by bacteria resistant to most, if not all, available antibiotics are found in alarmingly increasing numbers world-wide. As a result, bacterial infections, once considered easily treatable, are becoming life-threatening again, and pose a serious threat to public health. Deaths associated with antimicrobial resistance (AMR) rose to 5 million/year in 2019, with linked costs being estimated to reach tens of trillion dollars over the next decades. Awareness for the seriousness of the situation has risen over the past years, and actions to mitigate aspects of this complex problem, e.g. controlling better antibiotic use, are underway. At the same time, fundamental research is needed to find new strategies and sustainable solutions to tackle AMR, and avoid that it becomes the source for a continuous pandemic over the next decades.
New effective antibiotics are urgently needed, and effort is put towards this direction. Yet, antibiotic discovery takes time and has high attrition rates. Importantly, developing new compounds without understanding the paths and mechanisms that lead to resistance selection and spreading, and finding ways to overcome them, is a Sisyphean effort. The overarching goals of this proposal are to improve our understanding of antibiotic resistance, assessing the role of a previously unappreciated source of selective pressure for resistance development, that of non-antibiotic drugs, and exploring ways of combating AMR with combinatorial therapies.
Since their discovery, antibiotics have been used for prophylaxis. Their popularity is linked to their high efficacy and the high-gain/low-risk for the individual. Community risks, such as antibiotic resistance, were put in second line for decades, since the high pace of new compound development ensured we were several steps ahead in this race. However, as the antibiotic development tap started to run dry, the community risks of uncontrolled antibiotic usage became apparent, and nowadays large efforts to controlling antibiotic use are under way– e.g. antibiotic stewardship programs. Yet, is antibiotic consumption the only driving force for resistance?
We recently established that commonly used drugs against diseases unrelated to infection also impact the human gut microbiota. Microbes that are more resistant to non-antibiotic drugs are also more resistant to antibiotics, due to partially common resistance mechanisms. This implies that by affecting the gut microbiota, many non-antibiotic drugs may be also selecting for AMR. As we use non-antibiotic pharmaceuticals frequently and often chronically, this raises the question of whether polypharmacy is a driver of AMR. In this project, we wanted to explore this hypothesis by mapping the cross-resistance/sensitivity patterns between antibiotics and non-antibiotics, and by elucidating the underlying antibacterial mode-of-action and resistance mechanisms of non-antibiotic drugs. This knowledge would be then used to mitigate or exploit the microbial side-effects of these drugs in a targeted manner, using designed drug combinations.
Although extensively used for other diseases, drug combinations have had limited use for treating bacterial infections, mostly to increase spectrum coverage. The lack of new antibiotics has revived interest in them, especially since they can immediately offer solutions when individual compounds are approved for clinical use. We have shown that drug interactions are species-specific in bacteria, and one can identify potent synergies to the targeted pathogen. As part of this project we wanted to come up with drug combinations that delay AMR development or revert existing one. To delay resistance one needs to minimize the selective pressure placed by the antibiotic (narrow-spectrum therapies), or to make it harder for the microbe to find survival strategies. To revert resistance, the resistance trait needs to be turned into fitness cost for the microbe.
The overall objectives of this project were to:
i. Understand the extent non-antibiotics drive AMR and the underlying mechanisms
ii. Elucidate the antimicrobial action of non-antibiotic drugs and try to mitigate it.
iii. Use the antimicrobial side-effects of non-antibiotic drugs to revert AMR
iv. Identify genetic elements that slow down AMR development and use knowledge to design new less-prone-to-AMR combination therapies
New effective antibiotics are urgently needed, and effort is put towards this direction. Yet, antibiotic discovery takes time and has high attrition rates. Importantly, developing new compounds without understanding the paths and mechanisms that lead to resistance selection and spreading, and finding ways to overcome them, is a Sisyphean effort. The overarching goals of this proposal are to improve our understanding of antibiotic resistance, assessing the role of a previously unappreciated source of selective pressure for resistance development, that of non-antibiotic drugs, and exploring ways of combating AMR with combinatorial therapies.
Since their discovery, antibiotics have been used for prophylaxis. Their popularity is linked to their high efficacy and the high-gain/low-risk for the individual. Community risks, such as antibiotic resistance, were put in second line for decades, since the high pace of new compound development ensured we were several steps ahead in this race. However, as the antibiotic development tap started to run dry, the community risks of uncontrolled antibiotic usage became apparent, and nowadays large efforts to controlling antibiotic use are under way– e.g. antibiotic stewardship programs. Yet, is antibiotic consumption the only driving force for resistance?
We recently established that commonly used drugs against diseases unrelated to infection also impact the human gut microbiota. Microbes that are more resistant to non-antibiotic drugs are also more resistant to antibiotics, due to partially common resistance mechanisms. This implies that by affecting the gut microbiota, many non-antibiotic drugs may be also selecting for AMR. As we use non-antibiotic pharmaceuticals frequently and often chronically, this raises the question of whether polypharmacy is a driver of AMR. In this project, we wanted to explore this hypothesis by mapping the cross-resistance/sensitivity patterns between antibiotics and non-antibiotics, and by elucidating the underlying antibacterial mode-of-action and resistance mechanisms of non-antibiotic drugs. This knowledge would be then used to mitigate or exploit the microbial side-effects of these drugs in a targeted manner, using designed drug combinations.
Although extensively used for other diseases, drug combinations have had limited use for treating bacterial infections, mostly to increase spectrum coverage. The lack of new antibiotics has revived interest in them, especially since they can immediately offer solutions when individual compounds are approved for clinical use. We have shown that drug interactions are species-specific in bacteria, and one can identify potent synergies to the targeted pathogen. As part of this project we wanted to come up with drug combinations that delay AMR development or revert existing one. To delay resistance one needs to minimize the selective pressure placed by the antibiotic (narrow-spectrum therapies), or to make it harder for the microbe to find survival strategies. To revert resistance, the resistance trait needs to be turned into fitness cost for the microbe.
The overall objectives of this project were to:
i. Understand the extent non-antibiotics drive AMR and the underlying mechanisms
ii. Elucidate the antimicrobial action of non-antibiotic drugs and try to mitigate it.
iii. Use the antimicrobial side-effects of non-antibiotic drugs to revert AMR
iv. Identify genetic elements that slow down AMR development and use knowledge to design new less-prone-to-AMR combination therapies
Key findings of this project include the following:
• Human-targeted drugs have mostly distinct targets from antibiotics in gut bacteria, while resistance mechanisms can be overlapping. At the same time the degree of collateral sensitivity (resistance to non-antibiotic drug leading to sensitivity to an antibiotic) is also common, which may increase the collateral damage of specific antibiotics on the gut microbiota of individuals taking chronically other medication.
• We devised a new adjuvant strategy (antidotes) to mitigate the collateral damage of broad-spectrum antibiotics to the gut microbiome (PMID 34646011). We showed that the strategy works in animal models and filed a successful patent (WO/2021/122809).
• We discovered that microbiome communities have emergent behaviors in their responses to drugs (PMID 39321801). Sensitive species are often protected when in community, but up to a certain drug level. Above this, cross-protection mechanisms dissipate and negative interactions emerge.
• Mapping how resistance to one antibiotic affects resistance to a second drug has been a laborious process. We established a method to do this rapidly with available chemical genetics data and with high sensitivity, while providing insights into the underlying mechanism. The identified new collateral sensitive drug pairs (several fold more than previously known in E. coli) can be used to prevent the evolution of antibiotic resistance (PMID 39623067). By generating the necessary tools and resources for doing chemical genetics in non-model gut microbes and other pathogens, we opened the door for mapping drug cross-resistance and collateral-sensitivity in many bacteria.
• We found that epistatic genetic interactions between resistance elements and other genes in the genome strongly affect resistance evolution, and developed a suite of new methods to look into genetic interactions between resistance mutations and the genome across different genetic backgrounds.
• Human-targeted drugs have mostly distinct targets from antibiotics in gut bacteria, while resistance mechanisms can be overlapping. At the same time the degree of collateral sensitivity (resistance to non-antibiotic drug leading to sensitivity to an antibiotic) is also common, which may increase the collateral damage of specific antibiotics on the gut microbiota of individuals taking chronically other medication.
• We devised a new adjuvant strategy (antidotes) to mitigate the collateral damage of broad-spectrum antibiotics to the gut microbiome (PMID 34646011). We showed that the strategy works in animal models and filed a successful patent (WO/2021/122809).
• We discovered that microbiome communities have emergent behaviors in their responses to drugs (PMID 39321801). Sensitive species are often protected when in community, but up to a certain drug level. Above this, cross-protection mechanisms dissipate and negative interactions emerge.
• Mapping how resistance to one antibiotic affects resistance to a second drug has been a laborious process. We established a method to do this rapidly with available chemical genetics data and with high sensitivity, while providing insights into the underlying mechanism. The identified new collateral sensitive drug pairs (several fold more than previously known in E. coli) can be used to prevent the evolution of antibiotic resistance (PMID 39623067). By generating the necessary tools and resources for doing chemical genetics in non-model gut microbes and other pathogens, we opened the door for mapping drug cross-resistance and collateral-sensitivity in many bacteria.
• We found that epistatic genetic interactions between resistance elements and other genes in the genome strongly affect resistance evolution, and developed a suite of new methods to look into genetic interactions between resistance mutations and the genome across different genetic backgrounds.
We developed methods to create pooled genome-wide mutant libraries in non-model gut bacteria and to rapidly deconvolute them to comprehensive arrayed libraries. These efforts led to invaluable new resources for the field – arrayed genome-wide libraries in Bacteroidota and in several E. coli strains (commensal as Nissle, and uropathogenic as UTI89). The knowhow and resources generated are a part of a newly built core facility at EMBL on Microbial Automation and Culturomics.
We developed a method to map and understand how resistance to one drug affects resistance to a second one (PMID 39623067), surpassing in throughput and sensitivity previous methods, while providing direct insights into the underlying mechanisms. We also established new methods to systematically measure genetic interactions between resistance elements and all genes in the genetic background. Finally, we filed a patent (WO/2021/122809) on how to use a second drug to selectively mask the collateral damage of antibiotics to prominent gut bacteria, while allowing it to still act on the bacterial pathogens it was intended for (PMID 34646011).
We developed a method to map and understand how resistance to one drug affects resistance to a second one (PMID 39623067), surpassing in throughput and sensitivity previous methods, while providing direct insights into the underlying mechanisms. We also established new methods to systematically measure genetic interactions between resistance elements and all genes in the genetic background. Finally, we filed a patent (WO/2021/122809) on how to use a second drug to selectively mask the collateral damage of antibiotics to prominent gut bacteria, while allowing it to still act on the bacterial pathogens it was intended for (PMID 34646011).