Resetting the agenda for antibiotic resistance through a health systems perspective.

Although the individual and societal consequences of antibiotic resistance spiral upwards, coordinated action has not kept pace on a global scale. The COVID-19 pandemic has highlighted the need for resilient health systems and has resulted in an unprecedented rate of collaboration in scientific, medical, social, and political dimensions. The pandemic has also created a renewed awareness of the importance of infectious diseases and is a substantial entry point for reigniting the momentum towards containing the silent pandemic of antibiotic resistance. In this Viewpoint, we discuss the limitations in the current narrative on antibiotic resistance and how it could be improved, including concerted efforts to close essential data gaps. We discuss the need for capacity building and coordination at the national and global levels to strengthen the understanding of the importance of sustainable access to effective antibiotics for all health systems that could generate tangible links to current processes for global health and development.

Coevolutionary Governance of Antibiotic and Pesticide Resistance.

Development of new biocides has dominated human responses to evolution of antibiotic and pesticide resistance. Increasing and uniform biocide use, the spread of resistance genes, and the lack of new classes of compounds indicate the importance of navigating toward more sustainable coevolutionary dynamics between human culture and species that evolve resistance. To inform this challenge, we introduce the concept of coevolutionary governance and propose three priorities for its implementation: (i) new norms and mental models for lowering use, (ii) diversifying practices to reduce directional selection, and (iii) investment in collective action institutions to govern connectivity. We highlight the availability of solutions that facilitate broader sustainable development, which for antibiotic resistance include improved sanitation and hygiene, strong health systems, and decreased meat consumption.

Ciprofloxacin selects for RNA polymerase mutations with pleiotropic antibiotic resistance effects.

OBJECTIVES: Resistance to the fluoroquinolone drug ciprofloxacin is commonly linked to mutations that alter the drug target or increase drug efflux via the major AcrAB-TolC transporter. Very little is known about other mutations that might also reduce susceptibility to ciprofloxacin. We discovered that an Escherichia coli strain experimentally evolved for resistance to ciprofloxacin had acquired a mutation in rpoB, the gene coding for the ß-subunit of RNA polymerase. The aim of this work was to determine whether this mutation, and other mutations in rpoB, contribute to ciprofloxacin resistance and, if so, by which mechanism. METHODS: Independent lineages of E. coli were evolved in the presence of ciprofloxacin and clones from endpoint cultures were screened for mutations in rpoB. Ciprofloxacin-selected rpoB mutations were identified and characterized in terms of effects on susceptibility and mode of action. RESULTS: Mutations in rpoB were selected at a high frequency in 3 out of 10 evolved lineages, in each case arising after the occurrence of mutations affecting topoisomerases and drug efflux. All ciprofloxacin-selected rpoB mutations had a high fitness cost in the absence of drug, but conferred a competitive advantage in the presence of ciprofloxacin. RNA sequencing and quantitative RT-PCR analysis showed that expression of mdtK, encoding a multidrug efflux transporter, was significantly increased by the ciprofloxacin-selected rpoB mutations. The susceptibility phenotype was shown to depend on the presence of an active mdtK and a mutant rpoB allele. CONCLUSIONS: These data identify mutations in RNA polymerase as novel contributors to the evolution of resistance to ciprofloxacin and show that the phenotype is mediated by increased MdtK-dependent drug efflux.

Target Product Profile for a Diagnostic Assay to Differentiate between Bacterial and Non-Bacterial Infections and Reduce Antimicrobial Overuse in Resource-Limited Settings: An Expert Consensus.

Acute fever is one of the most common presenting symptoms globally. In order to reduce the empiric use of antimicrobial drugs and improve outcomes, it is essential to improve diagnostic capabilities. In the absence of microbiology facilities in low-income settings, an assay to distinguish bacterial from non-bacterial causes would be a critical first step. To ensure that patient and market needs are met, the requirements of such a test should be specified in a target product profile (TPP). To identify minimal/optimal characteristics for a bacterial vs. non-bacterial fever test, experts from academia and international organizations with expertise in infectious diseases, diagnostic test development, laboratory medicine, global health, and health economics were convened. Proposed TPPs were reviewed by this working group, and consensus characteristics were defined. The working group defined non-severely ill, non-malaria infected children as the target population for the desired assay. To provide access to the most patients, the test should be deployable to community health centers and informal health settings, and staff should require <2 days of training to perform the assay. Further, given that the aim is to reduce inappropriate antimicrobial use as well as to deliver appropriate treatment for patients with bacterial infections, the group agreed on minimal diagnostic performance requirements of >90% and >80% for sensitivity and specificity, respectively. Other key characteristics, to account for the challenging environment at which the test is targeted, included: i) time-to-result <10 min (but maximally <2 hrs); ii) storage conditions at 0-40°C, ≤90% non-condensing humidity with a minimal shelf life of 12 months; iii) operational conditions of 5-40°C, ≤90% non-condensing humidity; and iv) minimal sample collection needs (50-100µL, capillary blood). This expert approach to define assay requirements for a bacterial vs. non-bacterial assay should guide product development, and enable targeted and timely efforts by industry partners and academic institutions.

Antimicrobial resistance-a threat to the world's sustainable development.

This commentary examines how specific sustainable development goals (SDGs) are affected by antimicrobial resistance and suggests how the issue can be better integrated into international policy processes. Moving beyond the importance of effective antibiotics for the treatment of acute infections and health care generally, we discuss how antimicrobial resistance also impacts on environmental, social, and economic targets in the SDG framework. The paper stresses the need for greater international collaboration and accountability distribution, and suggests steps towards a broader engagement of countries and United Nations agencies to foster global intersectoral action on antimicrobial resistance.

International cooperation to improve access to and sustain effectiveness of antimicrobials.

Securing access to effective antimicrobials is one of the greatest challenges today. Until now, efforts to address this issue have been isolated and uncoordinated, with little focus on sustainable and international solutions. Global collective action is necessary to improve access to life-saving antimicrobials, conserving them, and ensuring continued innovation. Access, conservation, and innovation are beneficial when achieved independently, but much more effective and sustainable if implemented in concert within and across countries. WHO alone will not be able to drive these actions. It will require a multisector response (including the health, agriculture, and veterinary sectors), global coordination, and financing mechanisms with sufficient mandates, authority, resources, and power. Fortunately, securing access to effective antimicrobials has finally gained a place on the global political agenda, and we call on policy makers to develop, endorse, and finance new global institutional arrangements that can ensure robust implementation and bold collective action.

A general method for rapid determination of antibiotic susceptibility and species in bacterial infections.

To ensure correct antibiotic treatment and reduce the unnecessary use of antibiotics, there is an urgent need for new rapid methods for species identification and determination of antibiotic susceptibility in infectious pathogenic bacteria. We have developed a general method for the rapid identification of the bacterial species causing an infection and the determination of their antibiotic susceptibility profiles. An initial short cultivation step in the absence and presence of different antibiotics was combined with sensitive species-specific padlock probe detection of the bacterial target DNA to allow a determination of growth (i.e., resistance) and no growth (i.e., susceptibility). A proof-of-concept was established for urinary tract infections in which we applied the method to determine the antibiotic susceptibility profiles of Escherichia coli for two drugs with 100% accuracy in 3.5 h. The short assay time from sample to readout enables fast appropriate treatment with effective drugs and minimizes the need to prescribe broad-spectrum antibiotics due to unknown resistance profiles of the treated infection.

Overcoming scientific and structural bottlenecks in antibacterial discovery and development.

Antibiotic resistance is becoming an increasing threat, with too few novel antibiotics coming to market to replace those lost due to resistance development. Efforts by the pharmaceutical industry to screen for and design novel antibacterials have not been successful, with several companies minimizing or closing down their antibacterial research units, leading to a loss of skills and know-how. At the same time, antibiotic innovation in academia is not filling the void due to misaligned incentive structures and lack of vital knowledge of drug discovery. The scientific and structural difficulties in discovering new antibiotics have only begun to be appreciated in the latest years. Part of the problem has been a paradigm shift within both industry and academia to focus on 'rational' drug development with an emphasis on single targets and high-throughput screening of large chemical libraries, which may not be suited to target bacteria. The very particular aspects of 'targeting an organism inside another organism' have not been given enough attention. In this paper, researcher interviews have complemented literature studies to delve deeper into the specifics of the different scientific and structural barriers, and some potential solutions are offered.

Compensatory mutations in agrC partly restore fitness in vitro to peptide deformylase inhibitor-resistant Staphylococcus aureus.

OBJECTIVES: To determine how the fitness cost of deformylase inhibitor resistance conferred by fmt mutations can be genetically compensated. METHODS: Resistant mutants were isolated and characterized with regard to their growth rates in vitro and in neutropenic mice, MIC and DNA sequence. Faster-growing compensated mutants were isolated by serial passage in culture medium, and for a subset of the resistant and compensated mutants whole-genome sequencing was performed. RESULTS: Staphylococcus aureus mutants resistant to the peptide deformylase inhibitor actinonin had mutations in the fmt gene that conferred high-level actinonin resistance and reduced bacterial growth rate. Compensated mutants that remained fully resistant to actinonin and showed increased growth rates appeared within 30-60 generations of growth. Whole-genome sequencing and localized DNA sequencing of mutated candidate genes showed that alterations in the gene agrC were present in the majority of compensated strains. Resistant and compensated mutants grew at similar rates as the wild-type in a mouse thigh infection model. CONCLUSIONS: Resistance to deformylase inhibitors due to fmt mutations reduces bacterial growth rates, but these costs can be reduced by mutations in the agrC gene. Mutants defective in fmt (with or without compensatory agrC mutations) grew well in an animal model, implying that they can also cause infection in a host.

Colorimetric nucleic acid testing assay for RNA virus detection based on circle-to-circle amplification of padlock probes.

We developed a molecular diagnostic method for detection of RNA virus based on padlock probes and colorimetric readout. The feasibility of our approach was demonstrated by using detection of Crimean-Congo hemorrhagic fever (CCHF) virus as a model. Compared with conventional PCR-based methods, our approach does not require advanced equipment, involves easier assay design, and has a sensitivity of 10(3) viral copies/ml. By using a cocktail of padlock probes, synthetic templates representing different viral strain variants could be detected. We analyzed 34 CCHF patient samples, and all patients were correctly diagnosed when the results were compared to those of the current real-time PCR method. This is the first time that highly specific padlock probes have been applied to detection of a highly variable target sequence typical of RNA viruses.

Activation of initiation factor 2 by ligands and mutations for rapid docking of ribosomal subunits.

We previously identified mutations in the GTPase initiation factor 2 (IF2), located outside its tRNA-binding domain, compensating strongly (A-type) or weakly (B-type) for initiator tRNA formylation deficiency. We show here that rapid docking of 30S with 50S subunits in initiation of translation depends on switching 30S subunit-bound IF2 from its inactive to active form. Activation of wild-type IF2 requires GTP and formylated initiator tRNA (fMet-tRNA(i)). In contrast, extensive activation of A-type IF2 occurs with only GTP or with GDP and fMet-tRNA(i), implying a passive role for initiator tRNA as activator of IF2 in subunit docking. The theory of conditional switching of GTPases quantitatively accounts for all our experimental data. We find that GTP, GDP, fMet-tRNA(i) and A-type mutations multiplicatively increase the equilibrium ratio, K, between active and inactive forms of IF2 from a value of 4 × 10(-4) for wild-type apo-IF2 by factors of 300, 8, 80 and 20, respectively. Functional characterization of the A-type mutations provides keys to structural interpretation of conditional switching of IF2 and other multidomain GTPases.

Error-prone initiation factor 2 mutations reduce the fitness cost of antibiotic resistance.

Mutations in the fmt gene (encoding formyl methionine transferase) that eliminate formylation of initiator tRNA (Met-tRNA(i)) confer resistance to the novel antibiotic class of peptide deformylase inhibitors (PDFIs) while concomitantly reducing bacterial fitness. Here we show in Salmonella typhimurium that novel mutations in initiation factor 2 (IF2) located outside the initiator tRNA binding domain can partly restore fitness of fmt mutants without loss of antibiotic resistance. Analysis of initiation of protein synthesis in vitro showed that with non-formylated Met-tRNA(i) IF2 mutants initiated much faster than wild-type IF2, whereas with formylated fMet-tRNA(i) the initiation rates were similar. Moreover, the increase in initiation rates with Met-tRNA(i) conferred by IF2 mutations in vitro correlated well with the increase in growth rate conferred by the same mutations in vivo, suggesting that the mutations in IF2 compensate formylation deficiency by increasing the rate of in vivo initiation with Met-tRNA(i). IF2 mutants had also a high propensity for erroneous initiation with elongator tRNAs in vitro, which could account for their reduced fitness in vivo in a formylation-proficient strain. More generally, our results suggest that bacterial protein synthesis is mRNA-limited and that compensatory mutations in IF2 could increase the persistence of PDFI-resistant bacteria in clinical settings.

Reducing the fitness cost of antibiotic resistance by amplification of initiator tRNA genes.

Deformylase inhibitors belong to a novel antibiotic class that targets peptide deformylase, a bacterial enzyme that removes the formyl group from N-terminal methionine in nascent polypeptides. Using the bacterium Salmonella enterica, we isolated mutants with resistance toward the peptide deformylase inhibitor actinonin. Resistance mutations were identified in two genes that are required for the formylation of methionyl (Met) initiator tRNA (tRNAi)(fMet): the fmt gene encoding the enzyme methionyl-tRNA formyltransferase and the folD gene encoding the bifunctional enzyme methylenetetrahydrofolate-dehydrogenase and -cyclohydrolase. In the absence of antibiotic, these resistance mutations conferred a fitness cost that was manifested as a reduced growth rate in laboratory medium and in mice. By serially passaging the low-fitness mutants in growth medium without antibiotic, the fitness costs could be partly ameliorated either by intragenic mutations in the fmt/folD genes or by extragenic compensatory mutations. Of the extragenically compensated fmt mutants, approximately one-third carried amplifications of the identical, tandemly repeated metZ and metW genes, encoding tRNAi. The increase in metZW gene copy number varied from 5- to 40-fold and was accompanied by a similar increase in tRNAi levels. The rise in tRNAi level compensated for the lack of methionyl-tRNA formyltransferase activity and allowed translation initiation to proceed with nonformylated methionyl tRNAi. Amplified units varied in size from 1.9 to 94 kbp. Suppression of deleterious mutations by gene amplification may be involved in the evolution of new gene functions.

Supervised identification of allergen-representative peptides for in silico detection of potentially allergenic proteins.

MOTIVATION: Identification of potentially allergenic proteins is needed for the safety assessment of genetically modified foods, certain pharmaceuticals and various other products on the consumer market. Current methods in bioinformatic allergology exploit common features among allergens for the detection of amino acid sequences of potentially allergenic proteins. Features for identification still unexplored include the motifs occurring commonly in allergens, but rarely in ordinary proteins. In this paper, we present an algorithm for the identification of such motifs with the purpose of biocomputational detection of amino acid sequences of potential allergens. RESULTS: Identification of allergen-representative peptides (ARPs) with low or no occurrence in proteins lacking allergenic properties is the essential component of our new method, designated DASARP (Detection based on Automated Selection of Allergen-Representative Peptide). This approach consistently outperforms the criterion based on identical peptide match for predicting allergenicity recommended by ILSI/IFBC and FAO/WHO and shows results comparable to the alignment-based criterion as outlined by FAO/WHO. AVAILABILITY: The detection software and the ARP set needed for the analysis of a query protein reported here are properties of the Swedish National Food Agency and are available upon request. The protein sequence sets used in this work are publicly available on http://www.slv.se/templatesSLV/SLV_Page____9343.asp. Allergenicity assessment for specific protein sequences of interest is also possible via ulfh@slv.se

Prediction of food protein allergenicity: a bioinformatic learning systems approach.

Food hypersensitivity is constantly increasing in Western societies with a prevalence of about 1-2% in Europe and in the USA. Among children, the incidence is even higher. Because of the introduction of foods derived from genetically modified crops on the marketplace, the scientific community, regulatory bodies and international associations have intensified discussions on risk assessment procedures to identify potential food allergenicity of the newly introduced proteins. In this work, we present a novel biocomputational methodology for the classification of amino acid sequences with regard to food allergenicity and non-allergenicity. This method relies on a computerised learning system trained using selected excerpts of amino acid sequences. One example of such a successful learning system is presented which consists of feature extraction from sequence alignments performed with the FASTA3 algorithm (employing the BLOSUM50 substitution matrix) combined with the k-Nearest-Neighbour (kNN) classification algorithm. Briefly, the two features extracted are the alignment score and the alignment length and the kNN algorithm assigns the pair of extracted features from an unknown sequence to the prevalent class among its k nearest neighbours in the training (prototype) set available. 91 food allergens from several specialised public repositories of food allergy and the SWALL database were identified, pre-processed, and stored, yielding one of the most extensively characterised repositories of allergenic sequences known today. All allergenic sequences were classified using a standard one-leave-out cross validation procedure yielding about 81% correctly classified allergens and the classification of 367 non-allergens in an independent test set resulted in about 98% correct classifications. The biocomputational approach presented should be regarded as a significant extension and refinement of earlier attempts suggested for in silico food safety assessment. Our results show that the framework described here is powerful enough to become useful as part of a multiple-procedure test scheme that also depicts other evaluation approaches such as solid phase immunoassay and tests for stability to digestions.