Comparing treatment strategies to reduce antibiotic resistance in an in vitro epidemiological setting

Unraveling resistance mechanisms in combination therapy: A comprehensive review of recent advances and future directions

Antimicrobial resistance is a global health threat. Misuse and overuse of antimicrobials are the main drivers in developing drug-resistant bacteria. The emergence of the rapid global spread of multi-resistant bacteria requires urgent multisectoral action to generate novel treatment alternatives. Combination therapy offers the potential to exploit synergistic effects for enhanced antibacterial efficacy of drugs. Understanding the complex dynamics and kinetics of drug interactions in combination therapy is crucial. Therefore, this review outlines the current advances in antibiotic resistance's evolutionary and genetic dynamics in combination therapies-exposed bacteria. Moreover, we also discussed four pivotal future research areas to comprehend better the development of antibiotic resistance in bacteria treated with combination strategies.

Building pyramids against the evolutionary emergence of pathogens

Mutations allowing pathogens to escape host immunity promote the spread of infectious diseases in heterogeneous host populations and can lead to major epidemics. Understanding the conditions that slow down this evolution is key for the development of durable control strategies against pathogens. Here, we use theory and experiments to compare the efficacy of three strategies for the deployment of resistance: (i) a mixing strategy where the host population contains two single-resistant genotypes, (ii) a pyramiding strategy where the host carries a double-resistant genotype, (iii) a combining strategy where the host population is a mix of a single-resistant genotype and a double-resistant genotype. First, we use evolutionary epidemiology theory to clarify the interplay between demographic stochasticity and evolutionary dynamics to show that the pyramiding strategy always yields lower probability of evolutionary emergence. Second, we test experimentally these predictions with the introduction of bacteriophages into bacterial populations where we manipulated the diversity and the depth of immunity using a Clustered Regularly Interspaced Short Palindromic Repeats-CRISPR associated (CRISPR-Cas) system. These biological assays confirm that pyramiding multiple defences into the same host genotype and avoiding combination with single-defence genotypes is a robust way to reduce pathogen evolutionary emergence. The experimental validation of these theoretical recommendations has practical implications in various areas, including for the optimal deployment of resistance varieties in agriculture and for the design of durable vaccination strategies.

Ecological spectroscopic methodologies for quantifying co-administered drugs in human plasma by photochemical quantum mechanical simulation

Urinary tract infections (UTIs) constitute the second most prevalent bacterial infections in the elderly demographic. The treatment landscape involves various antibiotics targeting the causative organisms; nevertheless, the emergence of resistance significantly impacts therapeutic effectiveness. Presently, a fixed-dose pharmaceutical combination is advocated to optimize patient outcomes by mitigating the risks of bacterial resistance and associated side effects. Ofloxacin (OFL) and cefpodoxime proxetil (CPD) combinations, co-administered with flavoxate hydrochloride (FLV), have demonstrated efficacy in UTI cases, offering relief from concomitant symptoms. In the pharmaceutical market, fixed-dose combinations have gained prominence, driven by advantages such as enhanced patient medication adherence and compliance. In the realm of analytical chemistry, the integration of green practices in the initial phases of method development is exemplified by the Greenness by Design (GbD) strategy. While univariate spectroscopic methods are conventionally considered suboptimal compared to chemometric techniques for resolving intricate mixtures, GbD approach, when applied to UV spectroscopy, enable univariate methods to attain comparable or superior outcomes. GbD adopts a systematic approach to optimize experimental conditions, minimizing environmental impact and maximizing analytical performance. Critical to GbD applications in UV spectroscopy is solvent selection, influencing spectral resolution and measurement sensitivity. GbD employs a combination of in-vitro and in-silico experiments to evaluate solute-solvent interactions with underlying photochemical quantum phenomena affecting the resulting spectral morphology, identifying an optimal compromise solvent with high resolution and minimal ecological impact. Consequently, it facilitates the efficient resolution of spectral overlapping and determination of complex mixtures in UV spectroscopy using univariate methods. Comparative analysis with chemometric techniques, acknowledged as potent spectral resolving methods, demonstrated that GbD-based univariate methods performed equivalently. The methodology was validated according to ICH recommendations, establishing a linear quantitation range (2-30 μg/mL) and a limit of detection (0.355-0.414 μg/mL) for the three drugs in human plasma. The greenness of the developed methodology was affirmed through the AGREE assessment protocol, confirming its environmentally conscious attributes.

The effect of combining antibiotics on resistance: A systematic review and meta-analysis

When and under which conditions antibiotic combination therapy decelerates rather than accelerates resistance evolution is not well understood. We examined the effect of combining antibiotics on within-patient resistance development across various bacterial pathogens and antibiotics. We searched CENTRAL, EMBASE and PubMed for (quasi)-randomised controlled trials (RCTs) published from database inception to November 24th, 2022. Trials comparing antibiotic treatments with different numbers of antibiotics were included. A patient was considered to have acquired resistance if, at the follow-up culture, a resistant bacterium was detected that had not been present in the baseline culture. We combined results using a random effects model and performed meta-regression and stratified analyses. The trials' risk of bias was assessed with the Cochrane tool. 42 trials were eligible and 29, including 5054 patients, were qualified for statistical analysis. In most trials, resistance development was not the primary outcome and studies lacked power. The combined odds ratio (OR) for the acquisition of resistance comparing the group with the higher number of antibiotics with the comparison group was 1.23 (95% CI 0.68-2.25), with substantial between-study heterogeneity (I2 =77%). We identified tentative evidence for potential beneficial or detrimental effects of antibiotic combination therapy for specific pathogens or medical conditions. The evidence for combining a higher number of antibiotics compared to fewer from RCTs is scarce and overall, is compatible with both benefit or harm. Trials powered to detect differences in resistance development or well-designed observational studies are required to clarify the impact of combination therapy on resistance.

Mathematical Model for Growth and Rifampicin-Dependent Killing Kinetics of Escherichia coli Cells

Antibiotic resistance is a global health threat. We urgently need better strategies to improve antibiotic use to combat antibiotic resistance. Currently, there are a limited number of antibiotics in the treatment repertoire of existing bacterial infections. Among them, rifampicin is a broad-spectrum antibiotic against various bacterial pathogens. However, during rifampicin exposure, the appearance of persisters or resisters decreases its efficacy. Hence, to benefit more from rifampicin, its current standard dosage might be reconsidered and explored using both computational tools and experimental or clinical studies. In this study, we present the mathematical relationship between the concentration of rifampicin and the growth and killing kinetics of Escherichia coli cells. We generated time-killing curves of E. coli cells in the presence of 4, 16, and 32 μg/mL rifampicin exposures. We specifically focused on the oscillations with decreasing amplitude over time in the growth and killing kinetics of rifampicin-exposed E. coli cells. We propose the solution form of a second-order linear differential equation for a damped oscillator to represent the mathematical relationship. We applied a nonlinear curve fitting solver to time-killing curve data to obtain the model parameters. The results show a high fitting accuracy.

Development of a Polymicrobial Checkerboard Assay as a Tool for Determining Combinatorial Antibiotic Effectiveness in Polymicrobial Communities

The checkerboard assay is a well-established tool used to determine the antimicrobial effects of two compounds in combination. Usually, data collected from the checkerboard assay use visible turbidity and optical density as a readout. While helpful in traditional checkerboard assays, these measurements become less useful in a polymicrobial context as they do not enable assessment of the drug effects on the individual members of the community. The methodology described herein allows for the determination of cell viability through selective and differential plating of each individual species in a community while retaining much of the high-throughput nature of a turbidity-based analysis and requiring no specialized equipment. This methodology further improves turbidity-based measurements by providing a distinction between bacteriostatic versus bactericidal concentrations of antibiotics. Herein, we use this method to demonstrate that the clinically used antibiotic combination of ceftazidime and gentamicin works synergistically against Pseudomonas aeruginosa in monoculture but antagonistically in a polymicrobial culture also containing Acinetobacter baumannii, Staphylococcus aureus, and Enterococcus faecalis, highlighting the fundamental importance of this methodology in improving clinical practices. We propose that this method could be implemented in clinical microbiology laboratories with minimal impact on the overall time for diagnosis.

Structure-function-guided design of synthetic peptides with anti-infective activity derived from wasp venom

Antimicrobial peptides (AMPs) derived from natural toxins and venoms offer a promising alternative source of antibiotics. Here, through structure-function-guided design, we convert two natural AMPs derived from the venom of the solitary eumenine wasp Eumenes micado into α-helical AMPs with reduced toxicity that kill Gram-negative bacteria in vitro and in a preclinical mouse model. To identify the sequence determinants conferring antimicrobial activity, an alanine scan screen and strategic single lysine substitutions are made to the amino acid sequence of these natural peptides. These efforts yield a total of 34 synthetic derivatives, including alanine substituted and lysine-substituted sequences with stabilized α-helical structures and increased net positive charge. The resulting lead synthetic peptides kill the Gram-negative pathogens Escherichia coli and Pseudomonas aeruginosa (PAO1 and PA14) by rapidly permeabilizing both their outer and cytoplasmic membranes, exhibit anti-infective efficacy in a mouse model by reducing bacterial loads by up to three orders of magnitude, and do not readily select for bacterial resistance.

Epsilon-poly-l-lysine conjugated erythromycin for enhanced antibiotic therapy

Antibiotic resistance is a big threat to public health. How to improve the therapeutic efficacy of conventional antibiotics is an effective way to address this issue. In order to enhance the antibacterial activity of conventional antibiotic erythromycin (EM), EM is conjugated to positively charged ε-poly-l-lysine (EPL) to obtain EPL modified EM (EPL-EM). The grafting ratio of EM can be calculated from the ¹H NMR spectrum. EPL-EM is stable in physiological environment, while EM can be readily released from EPL-EM upon incubating with esterase which can be secreted by most bacteria. Because of the presence of cationic EPL, EPL-EM showed much stronger antibacterial activity than free EM, with much lower minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). Moreover, compared to free EM, the development of drug resistance can be slowed down if EPL-EM is used, which can be ascribed to the reduction of EM dosage. Meanwhile, EPL-EM cannot induce hemolysis and cytotoxicity, which indicates that EPL-EM exhibits excellent biocompatibility. The design of EPL-EM with enhanced antibacterial activity and excellent biocompatibility provides an innovative way to combat antibiotic resistance.

Efficacy of Omadacycline-Containing Regimen in a Mouse Model of Pulmonary Mycobacteroides abscessus Disease

Mycobacteroides abscessus is an opportunistic pathogen in people with structural lung conditions such as bronchiectasis, chronic obstructive pulmonary disease, and cystic fibrosis. Pulmonary M. abscessus infection causes progressive symptomatic and functional decline as well as diminished lung function and is often incurable with existing antibiotics. We investigated the efficacy of a new tetracycline, omadacycline, in combination with existing antibiotics recommended to treat this indication, in a mouse model of M. abscessus lung disease. Amikacin, azithromycin, bedaquiline, biapenem, cefoxitin, clofazimine, imipenem, linezolid, and rifabutin were selected as companions to omadacycline. M. abscessus burden in the lungs of mice over a 4-week treatment duration was considered the endpoint. Omadacycline in combination with linezolid, imipenem, cefoxitin, biapenem, or rifabutin exhibited early bactericidal activity compared to any single drug. Using three M. abscessus isolates, we also determined the in vitro frequency of spontaneous resistance against omadacycline to be between 1.9 × 10-10 and 6.2 × 10-10 and the frequency of persistence against omadacycline to be between 5.3 × 10-6 and 1.3 × 10-5. Based on these findings, the combination of omadacycline and select drugs that are included in the recent treatment guidelines may exhibit improved potency to treat M. abscessus lung disease. IMPORTANCE M. abscessus disease incidence is increasing in the United States. This disease is difficult to cure with existing antibiotics. In this study, we describe the efficacy of a new tetracycline antibiotic, omadacycline, in combination with an existing antibiotic to treat this disease. A mouse model of M. abscessus lung disease was used to assess the efficacies of these experimental treatment regimens. Omadacycline in combination with select existing antibiotics exhibited bactericidal activity during the early phase of treatment.

A Novel Zinc (II) Porphyrin Is Synergistic with PEV2 Bacteriophage against Pseudomonas aeruginosa Infections

Pseudomonas aeruginosa (PsA) is an opportunistic bacterial pathogen that causes life-threatening infections in individuals with compromised immune systems and exacerbates health concerns for those with cystic fibrosis (CF). PsA rapidly develops antibiotic resistance; thus, novel therapeutics are urgently needed to effectively combat this pathogen. Previously, we have shown that a novel cationic Zinc (II) porphyrin (ZnPor) has potent bactericidal activity against planktonic and biofilm-associated PsA cells, and disassembles the biofilm matrix via interactions with eDNA In the present study, we report that ZnPor caused a significant decrease in PsA populations in mouse lungs within an in vivo model of PsA pulmonary infection. Additionally, when combined with an obligately lytic phage PEV2, ZnPor at its minimum inhibitory concentration (MIC) displayed synergy against PsA in an established in vitro lung model resulting in greater protection of H441 lung cells versus either treatment alone. Concentrations above the minimum bactericidal concentration (MBC) of ZnPor were not toxic to H441 cells; however, no synergy was observed. This dose-dependent response is likely due to ZnPor's antiviral activity, reported herein. Together, these findings show the utility of ZnPor alone, and its synergy with PEV2, which could be a tunable combination used in the treatment of antibiotic-resistant infections.

Perceptions of community pharmacists regarding their role in antimicrobial stewardship in Pakistan: A way forward

Background

Antimicrobial resistance is one of the biggest challenges to healthcare resulting in increased morbidity and mortality, and associated with drug resistant infections. Community pharmacists (CPs) can play a key role in antimicrobial stewardship (AMS) programs to aid the prudent use of antibiotics, and in infection prevention and control.

Objective

The aim of this study was to assess perceptions of CPs regarding their role, awareness, collaboration, facilitators and barriers towards effective AMS practices in Pakistan.

Method

ology: A descriptive, cross-sectional study design was adopted, where convenience and snowball sampling methods were applied to enroll respondents (pharmacists working at these community pharmacies in different cities of Pakistan) of the study. After sample size determination, n = 386 CPs were enrolled. A pre-validated questionnaire was used regarding CPs roles and perceptions in association with AMS. Statistical analysis was performed using SPSS v. 21.

Results

The results of the study reported that 57.3% (n = 221) of CPs had strong familiarity with term AMS. 52.1% (n = 201) of CPs agreed that they require adequate training to undertake activities in AMS programmes in their setting. The results of the study showed that 92.7% (n = 358) of the pharmacists thought real time feedback would be helpful. Significant association was observed in AMS awareness, approach, collaboration and barriers with regards to the respondents' gender, age groups and levels of experience in a community pharmacy.

Conclusions

The study concluded that CPs were aware of AMS programmes, their relevance and necessity of AMS in their everyday practice, but had inadequate training and resources to implement it in Pakistan.

Occurrence and Multidrug Resistance in Strains of Listeria monocytogenes Recovered from the Anaerobic Co-Digestion Sludge Contained in a Single Stage Steel Biodigester: Implications for Antimicrobial Stewardship

L. monocytogenes is a zoonotic foodborne pathogen with inherent adaptability to tolerate environmental and physiological stresses, thereby causing severe disease outbreaks. Antibiotic resistant foodborne pathogens are a challenge to the food industry. A total of 18 samples were pooled from a bio-digester co-digesting swine manure/pinewood sawdust, and evaluated for the occurrence of bacterium plus total viable counts using the spread plate method. The recovered bacterial isolates were presumptively identified by growth on selective medium and confirmed by biochemical characterisation, leading to the isolation of 43 L. monocytogenes. The isolates were characterized based on their susceptibility to antibiotics via the Kirby-Bauer disc diffusion technique against a panel of 14 antibiotics. Equally, the multiple antibiotic resistance (MAR) index was calculated, and MAR phenotypes generated. The bacterial counts were between 102 and104 cfu/mL. Complete susceptibility (100%) was demonstrated to ampicillin, gentamicin and sulfamethoxazole, which are the drugs of choice in the treatment of listeriosis. In addition, intermediate sensitivity occurred at 25.58% to cefotaxime, and the highest resistance (51.16%) was exhibited against nalidixic acid. The MAR index ranged from 0 to 0.71. Overall, 41.86% of the Listeria isolates displayed multidrug resistance, with 18 different MAR phenotypes, demonstrating CIP, E, C, TET, AUG, S, CTX, NA, AML, NI as the greatest MAR phenotype. It can be concluded that the isolates yielding MAR > 0.2 originated from the farm, where antibiotics had been in routine use. Therefore, strict monitoring of antibiotics use in the farm is crucial to mitigate further increase in antibiotic resistance amongst these bacterial isolates.

Fast drug rotation reduces bacterial resistance evolution in a microcosm experiment

Drug rotation (cycling), in which multiple drugs are administrated alternatively, has the potential for limiting resistance evolution in pathogens. The frequency of drug alternation could be a major factor to determine the effectiveness of drug rotation. Drug rotation practices often have low frequency of drug alternation, with an expectation of resistance reversion. Here we, based on evolutionary rescue and compensatory evolution theories, suggest that fast drug rotation can limit resistance evolution in the first place. This is because fast drug rotation would give little time for the evolutionarily rescued populations to recover in population size and genetic diversity, and thus decrease the chance of future evolutionary rescue under alternate environmental stresses. We experimentally tested this hypothesis using the bacterium Pseudomonas fluorescens and two antibiotics (chloramphenicol and rifampin). Increasing drug rotation frequency reduced the chance of evolutionary rescue, and most of the finally surviving bacterial populations were resistant to both drugs. Drug resistance incurred significant fitness costs, which did not differ among the drug treatment histories. A link between population sizes during the early stages of drug treatment and the end-point fates of populations (extinction vs survival) suggested that population size recovery and compensatory evolution before drug shift increase the chance of population survival. Our results therefore advocate fast drug rotation as a promising approach to reduce bacterial resistance evolution, which in particular could be a substitute for drug combination when the latter has safety risks.

Resistance-resistant antibacterial treatment strategies

Antibiotic resistance is a major danger to public health that threatens to claim the lives of millions of people per year within the next few decades. Years of necessary administration and excessive application of antibiotics have selected for strains that are resistant to many of our currently available treatments. Due to the high costs and difficulty of developing new antibiotics, the emergence of resistant bacteria is outpacing the introduction of new drugs to fight them. To overcome this problem, many researchers are focusing on developing antibacterial therapeutic strategies that are "resistance-resistant"-regimens that slow or stall resistance development in the targeted pathogens. In this mini review, we outline major examples of novel resistance-resistant therapeutic strategies. We discuss the use of compounds that reduce mutagenesis and thereby decrease the likelihood of resistance emergence. Then, we examine the effectiveness of antibiotic cycling and evolutionary steering, in which a bacterial population is forced by one antibiotic toward susceptibility to another antibiotic. We also consider combination therapies that aim to sabotage defensive mechanisms and eliminate potentially resistant pathogens by combining two antibiotics or combining an antibiotic with other therapeutics, such as antibodies or phages. Finally, we highlight promising future directions in this field, including the potential of applying machine learning and personalized medicine to fight antibiotic resistance emergence and out-maneuver adaptive pathogens.

Combinatorial screening SlipChip for rapid phenotypic antimicrobial susceptibility testing

Antimicrobial resistance (AMR) by bacteria is a serious global threat, and a rapid, high-throughput, and easy-to-use phenotypic antimicrobial susceptibility testing (AST) method is essential for making timely treatment decisions and controlling the spread of antibiotic resistant micro-organisms. Traditional culture-based methods are time-consuming, and their capability to screen against a large number of different conditions is limited; meanwhile genotypic based methods, including sequencing and PCR based methods, are constrained by rarely identified resistance genes and complicated resistance mechanisms. Here, a combinatorial-screening SlipChip (cs-SlipChip) containing 192 nanoliter-sized compartments is developed which can perform high-throughput phenotypic AST within three hours by monitoring the bacterial growth within nanoliter-sized droplets with bright-field imaging and analyzing the changes in bacterial number and morphology. The minimum inhibitory concentration (MIC) of Escherichia coli ATCC 25922 against four antibiotics (ampicillin, ciprofloxacin, ceftazidime, and nitrofurantoin) can be measured in one chip within 3 hours. Furthermore, five antibiotic-resistant E. coli strains were isolated from patients diagnosed with urinary tract infections (UTIs), and an individual isolate was tested using four antibiotics and eleven antibiotic combinations simultaneously with three different concentrations of each. The results from the cs-SlipChip agree with those of a VITEK 2 automated system. This cs-SlipChip provides a practical high-throughput and rapid phenotypic method for AST and can also be used to screen different chemicals and antibiotic combinations for the treatment of multiple antibiotic-resistant bacteria.

3-indoleacetonitrile attenuates biofilm formation and enhances sensitivity to imipenem in Acinetobacter baumannii

Acinetobacter baumannii poses a global danger due to its ability to resist most of the currently available antimicrobial agents. Furthermore, the rise of carbapenem-resistant A. baumannii isolates has limited the treatment options available. In the present study, plant auxin 3-indoleacetonitrile was found to inhibit biofilm formation and motility of A. baumannii at sub-lethal concentration. Mechanistically, 3-indoleacetonitrile inhibited the synthesis of the quorum sensing signal 3-OH-C12-HSL by downregulating the expression of the abaI autoinducer synthase gene. 3-indoleacetonitrile was found to reduce MIC of A. baumannii ATCC 17 978 against imipenem, ofloxacin, ciprofloxacin, tobramycin, and levofloxacin, and significantly decreased persistence against imipenem. Inhibition of efflux pumps by down-regulating genes expression may be responsible for enhanced sensitivity and low persistence. 3-indoleacetonitrile reduced the resistance to imipenem in carbapenem-resistant A. baumannii isolates by down-regulating the expression of OXA β-lactamases (blaoxa-51 and blaoxa-23), outer membrane protein carO and transporter protein adeB. These findings demonstrate the therapeutic potential of 3-indoleacetonitrile which could be explored as an adjuvant with antibiotics for controlling A. baumannii infections.

Antibiotic-loaded lipid-based nanocarrier: a promising strategy to overcome bacterial infection

According to the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC), bacterial infections are one of the greatest threats to global health, food production, and life expectancy. In this sense, the development of innovative formulations aiming at greater therapeutic efficacy, safety, and shorter treatment duration compared to conventional products is urgently needed. Lipid-based nanocarriers (LBNs) have demonstrated the potential to enhance the effectiveness of available antibiotics. Among them, liposome, nanoemulsion, solid lipid nanoparticle (SLN), and nanostructured lipid carrier (NLC) are the most promising due to their solid technical background for laboratory and industrial production. This review describes recent advances in developing antibiotic-loaded LBNs against susceptible and resistant bacterial strains and biofilm. LBNs revealed to be a promising alternative to deliver antibiotics due to their superior characteristics compared to conventional preparations, including their modified drug release, improved bioavailability, drug protection against chemical or enzymatic degradation, greater drug loading capacity, and biocompatibility. Antibiotic-loaded LBNs can improve current clinical drug therapy, bring innovative products and rescue discarded antibiotics. Thus, antibiotic-loaded LBNs have potential to open a window of opportunities to continue saving millions of lives and prevent the devastating impact of bacterial infection.

Applying Machine Learning Techniques to the Audit of Antimicrobial Prophylaxis

High rates of inappropriate use of surgical antimicrobial prophylaxis were reported in many countries. Auditing the prophylactic antimicrobial use in enormous medical records by manual review is labor-intensive and time-consuming. The purpose of this study is to develop accurate and efficient machine learning models for auditing appropriate surgical antimicrobial prophylaxis. The supervised machine learning classifiers (Auto-WEKA, multilayer perceptron, decision tree, SimpleLogistic, Bagging, and AdaBoost) were applied to an antimicrobial prophylaxis dataset, which contained 601 instances with 26 attributes. Multilayer perceptron, SimpleLogistic selected by Auto-WEKA, and decision tree algorithms had outstanding discrimination with weighted average AUC > 0.97. The Bagging and SMOTE algorithms could improve the predictive performance of decision tree against imbalanced datasets. Although with better performance measures, multilayer perceptron and Auto-WEKA took more execution time as compared with that of other algorithms. Multilayer perceptron, SimpleLogistic, and decision tree algorithms have outstanding performance measures for identifying the appropriateness of surgical prophylaxis. The efficient models developed by machine learning can be used to assist the antimicrobial stewardship team in the audit of surgical antimicrobial prophylaxis. In future research, we still have the challenges and opportunities of enriching our datasets with more useful clinical information to improve the performance of the algorithms.

Impact of a Novel Anticoccidial Analogue on Systemic Staphylococcus aureus Infection in a Bioluminescent Mouse Model

In this study, we investigated the potential of an analogue of robenidine (NCL179) to expand its chemical diversity for the treatment of multidrug-resistant (MDR) bacterial infections. We show that NCL179 exhibits potent bactericidal activity, returning minimum inhibitory concentration/minimum bactericidal concentrations (MICs/MBCs) of 1–2 µg/mL against methicillin-resistant Staphylococcus aureus, MICs/MBCs of 1–2 µg/mL against methicillin-resistant S. pseudintermedius and MICs/MBCs of 2–4 µg/mL against vancomycin-resistant enterococci. NCL179 showed synergistic activity against clinical isolates and reference strains of Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa in the presence of sub-inhibitory concentrations of colistin, whereas NCL179 alone had no activity. Mice given oral NCL179 at 10 mg/kg and 50 mg/kg (4 × doses, 4 h apart) showed no adverse clinical effects and no observable histological effects in any of the organs examined. In a bioluminescent S. aureus sepsis challenge model, mice that received four oral doses of NCL179 at 50 mg/kg at 4 h intervals exhibited significantly reduced bacterial loads, longer survival times and higher overall survival rates than the vehicle-only treated mice. These results support NCL179 as a valid candidate for further development to treat MDR bacterial infections as a stand-alone antibiotic or in combination with existing antibiotic classes.

The rising dominance of microbiology: what to expect in the next 15 years?

What microbiology beholds after a decade and a half in the future requires a vision based on the facts and ongoing trends in research and technological advancements. While the latter, assisted by microbial dark matter, presents a greater potential of creating an upsurge in in-situ and ex-situ rapid microbial detection techniques, this anticipated change will also set forth a revolution in microbial cultivation and diversity analyses. The availability of a microbial genetic toolbox at the expanse will help complement the current understanding of the microbiome and assist in real-time monitoring of the dynamics for detecting the health status of the host with utmost precision. Alongside, in light of the emerging infectious diseases, antimicrobial resistance (AMR) and social demands for safer and better health care alternatives, microbiology laboratories are prospected to drift in terms of the volume and nature of research and outcomes. With today's microbiological lens, one can predict with certainty that in the years to come, microbes will play a significant role in therapeutic treatment and the designing of novel diagnostic techniques. Another area where the scope of microbial application seems to be promising is the use of novel probiotics as a method to offer health benefits whilst promoting metabolic outputs specific for microbiome replenishment. Nonetheless, the evolution of extraterrestrial microbes or the adaptation of earth microbes as extraterrestrial residents are also yet another prominent microbial event one may witness in the upcoming years. But like the two sides of the coin, there is also an urgent need to dampen the bloom of urbanization, overpopulation and global trade and adopting sustainable approaches to control the recurrence of epidemics and pandemics.

Targeted (PCR-based) screening of antibiotic resistance genes' prevalence in the gut microbiota of tribal people of Nabarangpur, Odisha, India

Antibiotic resistance is a major public health concerns worldwide. The gut microbiota harbours multiple antibiotic-resistant genes (ARGs) that contribute to the existing and future microbial population in a community or ecosystem. This study aimed to investigate the prevalence of 35 antibiotic-resistance genes (ARGs) in the gut microbiota of the tribal people of Nabarangpur, Odisha, India. A total of 83 faecal samples were collected from three different tribes (Bhatra, Gond, and Paraja). Total faecal DNA was extracted and the simplex polymerase chain reaction (PCR) was performed to detect selected ARGs. Further analysis was done to estimate the incidence of these ARGs across these tribes based on alcohol consumption habits. We identified a higher prevalence of tetracycline resistance genes (tetW, tetQ, and tetM) in the gut microbiota among three populations. Further, a significant (p=0.024) difference in ARG prevalence against vancomycin in individuals with and without alcohol consumption habits was noticed. The overall distribution of ARGs among the three major tribes of this location was found to be very similar. Together, irrespective of the tribes, the people of this location have gut microbiota harbouring different kinds of ARGs and tetracycline-resistant genes are the most commonly found ARGs.

Leveraging laboratory and clinical studies to design effective antibiotic combination therapy

Interest in antibiotic combination therapy is increasing due to antimicrobial resistance and a slowing antibiotic pipeline. However, aside from specific indications, combination therapy in the clinic is often not administered systematically; instead, it is used at the physician's discretion as a bet-hedging mechanism to increase the chances of appropriately targeting a pathogen(s) with an unknown antibiotic resistance profile. Some recent clinical trials have been unable to demonstrate superior efficacy of combination therapy over monotherapy. Other trials have shown a benefit of combination therapy in defined circumstances consistent with recent studies indicating that factors including species, strain, resistance profile, and microenvironment affect drug combination efficacy and drug interactions. In this review, we discuss how a careful study design that takes these factors into account, along with the different drug interaction and potency metrics for assessing combination performance, may provide the necessary insight to understand the best clinical use-cases for combination therapy.

Design principles of collateral sensitivity-based dosing strategies

Collateral sensitivity (CS)-based antibiotic treatments, where increased resistance to one antibiotic leads to increased sensitivity to a second antibiotic, may have the potential to limit the emergence of antimicrobial resistance. However, it remains unclear how to best design CS-based treatment schedules. To address this problem, we use mathematical modelling to study the effects of pathogen- and drug-specific characteristics for different treatment designs on bacterial population dynamics and resistance evolution. We confirm that simultaneous and one-day cycling treatments could supress resistance in the presence of CS. We show that the efficacy of CS-based cycling therapies depends critically on the order of drug administration. Finally, we find that reciprocal CS is not essential to suppress resistance, a result that significantly broadens treatment options given the ubiquity of one-way CS in pathogens. Overall, our analyses identify key design principles of CS-based treatment strategies and provide guidance to develop treatment schedules to suppress resistance.

Antibiotic treatment protocols revisited: the challenges of a conclusive assessment by mathematical modelling

Hospital-acquired bacterial infections lead to prolonged hospital stays and increased mortality. The problem is exacerbated by antibiotic-resistant strains that delay or impede effective treatment. To ensure successful therapy and to manage antibiotic resistance, treatment protocols that draw on several different antibiotics might be used. This includes the administration of drug cocktails to individual patients (combination therapy) but also the random assignment of drugs to different patients (mixing) and a regular switch in the default drug used in the hospital from drug A to drug B and back (cycling). For more than 20 years, mathematical models have been used to assess the prospects of antibiotic combination therapy, mixing and cycling. But while tendencies in their ranking across studies have emerged, the picture remains surprisingly inconclusive and incomplete. In this article, we review existing modelling studies and demonstrate by means of examples how methodological factors complicate the emergence of a consistent picture. These factors include the choice of the criterion by which the effects of the protocols are compared, the model implementation and its analysis. We thereafter discuss how progress can be made and suggest future modelling directions.