The escalating incidence and prevalence of antibiotic resistance (ABR) makes treating bacterial infection increasingly difficult. ABR has severe implications for recovery from routine surgery and from such immunosuppressive treatments as cancer chemotherapy and prevention of transplant rejection. Drug developers address this problem by exploring novel antibacterial targets whose inhibitors are not cross-resistant to existing antibiotics. However, increasingly resistance appears before the new antibiotics can be marketed. The high cost of developing new chemical entities (NCEs), typically 0.5 billion dollars to take a NCE to market, makes new antibiotic development challenging for non-commercial organizations and unattractive even to multinational pharmaceutical companies.
Many thousand point mutations have been identified in genes encoding antibiotic target proteins that confer antibiotic resistance. Copy number changes, non-specific efflux mechanisms and deletions of membrane transport protein are also frequently observed. In addition to “vertical” modes of resistance transmission (i.e., transmitted by bacterial replication) and, horizontal gene transfer (HGT), which can transfer antibiotic resistance across species barriers, is now widespread. The use of antibiotics in combination reduces the probability of treatment failure compared with single-agent therapy but has the potential of resulting in the selection of multidrug-resistant strains.
The dynamics of mutation and HGT are such that antibiotic resistance is inevitable. Still, knowledge of bacterial genetics and evolutionary dynamics can reduce the incidence of ABR by orders of magnitude. Such strategies include use of non-cross-resistant combinations, using simultaneous rather than sequential combinations, or switching treatment before new mutations can accumulate. Applying these principles can reduce treatment failure rates at a fraction of the cost of NCE development.
There is a growing literature on approaches to the ABR problem other than NCE development. There are ABR-sensitive approaches looking at the prevention of infections by the use of vaccines, infection prevention and control (IPC) programmes and efficient water, sanitation and hygiene (WASH) infrastructure.
utilizing knowledge of bacterial genetics, evolutionary dynamics-based protocols, adaptive therapy, resistance blockers, and using multiple molecular diagnostics can minimize ABR. If multiple diagnostic tests are applied before treatment, a database of the resulting outcomes can guide future treatment. Pattern-recognition algorithms can then be used to optimize response rates to combinations of existing antibiotics.
Submissions appropriate to this topic will include research articles and reviews on strategies to mitigate antibiotic resistance. ABR-specific examples might include the use of resistance blockers, including efflux pump inhibitors, approaches that modify the dynamics of horizontal gene transmission, e.g. by selective plasmid inhibition or plasmid curing, and the use of database-driven therapy based upon patterns of response to molecular diagnostics. Novel non-cross-resistant combinations of existing agents sequenced, such as to reduce the evolution of multi-drug resistance, would also be of interest. ABR-sensitive examples using vaccination, IPC and WASH to prevent infections, reduce the need for antibiotics and the subsequent selection pressure for ABR will also be considered.
Please note: If patient data are analyzed, a comprehensive description of the patients including sex, age, diagnostic criteria, inclusion and exclusion criteria, disease stage, therapy received, comorbidities as well as additional clinical information and assessment of clinical response/effects should be included. If genetic, proteomics, metabolomics, or other omics data are analyzed, a comprehensive description of the methods and the rationale for the selection of the specific data studied should be provided. Studies relating to natural compounds (other than antibiotics), herbal extracts, or traditional medicine products, are outside the scope of this Research Topic and should instead be submitted to the specialty section Ethnopharmacology. Studies solely based on the analysis of public databases or published evidence, with no further experimental insights or experimental validation, will not be included in this Research Topic.
Keywords:
Adaptive therapy, antibiotics, drug resistance, horizontal gene transmission, resistance genetics
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
The escalating incidence and prevalence of antibiotic resistance (ABR) makes treating bacterial infection increasingly difficult. ABR has severe implications for recovery from routine surgery and from such immunosuppressive treatments as cancer chemotherapy and prevention of transplant rejection. Drug developers address this problem by exploring novel antibacterial targets whose inhibitors are not cross-resistant to existing antibiotics. However, increasingly resistance appears before the new antibiotics can be marketed. The high cost of developing new chemical entities (NCEs), typically 0.5 billion dollars to take a NCE to market, makes new antibiotic development challenging for non-commercial organizations and unattractive even to multinational pharmaceutical companies.
Many thousand point mutations have been identified in genes encoding antibiotic target proteins that confer antibiotic resistance. Copy number changes, non-specific efflux mechanisms and deletions of membrane transport protein are also frequently observed. In addition to “vertical” modes of resistance transmission (i.e., transmitted by bacterial replication) and, horizontal gene transfer (HGT), which can transfer antibiotic resistance across species barriers, is now widespread. The use of antibiotics in combination reduces the probability of treatment failure compared with single-agent therapy but has the potential of resulting in the selection of multidrug-resistant strains.
The dynamics of mutation and HGT are such that antibiotic resistance is inevitable. Still, knowledge of bacterial genetics and evolutionary dynamics can reduce the incidence of ABR by orders of magnitude. Such strategies include use of non-cross-resistant combinations, using simultaneous rather than sequential combinations, or switching treatment before new mutations can accumulate. Applying these principles can reduce treatment failure rates at a fraction of the cost of NCE development.
There is a growing literature on approaches to the ABR problem other than NCE development. There are ABR-sensitive approaches looking at the prevention of infections by the use of vaccines, infection prevention and control (IPC) programmes and efficient water, sanitation and hygiene (WASH) infrastructure.
utilizing knowledge of bacterial genetics, evolutionary dynamics-based protocols, adaptive therapy, resistance blockers, and using multiple molecular diagnostics can minimize ABR. If multiple diagnostic tests are applied before treatment, a database of the resulting outcomes can guide future treatment. Pattern-recognition algorithms can then be used to optimize response rates to combinations of existing antibiotics.
Submissions appropriate to this topic will include research articles and reviews on strategies to mitigate antibiotic resistance. ABR-specific examples might include the use of resistance blockers, including efflux pump inhibitors, approaches that modify the dynamics of horizontal gene transmission, e.g. by selective plasmid inhibition or plasmid curing, and the use of database-driven therapy based upon patterns of response to molecular diagnostics. Novel non-cross-resistant combinations of existing agents sequenced, such as to reduce the evolution of multi-drug resistance, would also be of interest. ABR-sensitive examples using vaccination, IPC and WASH to prevent infections, reduce the need for antibiotics and the subsequent selection pressure for ABR will also be considered.
Please note: If patient data are analyzed, a comprehensive description of the patients including sex, age, diagnostic criteria, inclusion and exclusion criteria, disease stage, therapy received, comorbidities as well as additional clinical information and assessment of clinical response/effects should be included. If genetic, proteomics, metabolomics, or other omics data are analyzed, a comprehensive description of the methods and the rationale for the selection of the specific data studied should be provided. Studies relating to natural compounds (other than antibiotics), herbal extracts, or traditional medicine products, are outside the scope of this Research Topic and should instead be submitted to the specialty section Ethnopharmacology. Studies solely based on the analysis of public databases or published evidence, with no further experimental insights or experimental validation, will not be included in this Research Topic.
Keywords:
Adaptive therapy, antibiotics, drug resistance, horizontal gene transmission, resistance genetics
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.