Variation of MIC measurements: the contribution of strain and laboratory variability to measurement precision

Acetic and citric acids effect the type II secretion system and decrease the metabolic activities of salmon spoilage-related Rahnella aquatilis KM05

Rahnella aquatilis causes seafoods to spoil by metabolizing sulfur-containing amino acids and/or proteins, producing H2S in products. The type II secretion system (T2SS) regulates the transport of proteases from the cytoplasm to the surrounding environment and promotes bacterial growth at low temperatures. To prevent premature fish spoilage, new solutions for inhibiting the T2SS of bacteria should be researched. In this study, global transcriptome sequencing was used to analyze the spoilage properties of R. aquatilis KM05. Two of the mapped genes/coding sequences (CDSs) were matched to the T2SS, namely, qspF and gspE, and four of the genes/CDSs, namely, ftsH, rseP, ptrA and pepN, were matched to metalloproteases or peptidases in R. aquatilis KM05. Subinhibitory concentrations of citric (18 µM) and acetic (41 µM) acids caused downregulation of T2SS-related genes (range from - 1.0 to -4.5) and genes involved in the proteolytic activities of bacteria (range from - 0.5 to -4.0). The proteolytic activities of R. aquatilis KM05 in vitro were reduced by an average of 40%. The in situ experiments showed the antimicrobial properties of citric and acetic acids against R. aquatilis KM05; the addition of an acidulant to salmon fillets limited microbial growth. Citric and acetic acids extend the shelf life of fish-based products and prevent food waste.

Association of Vancomycin AUC/MIC and Trough Concentration With Early Clinical Response in Enterococcus or Coagulase-Negative Staphylococcus Infection: A Prospective Study

This study was condcuted to examine the association of area under the curve (AUC)/minimum inhibitory concentration (MIC) and trough concentration (Ctrough) of vancomycin with treatment outcome and nephrotoxicity in infections caused by Enterococcus spp. and coagulase-negative Staphylococci (CoNS). Peak and trough concentrations were used to calculate AUC in 89 patients receiving vancomycin for infections with Enterococcus spp. (n = 65) or CoNS (n = 24). Correlations between Ctrough, AUC/MIC, early clinical response (ECR), and nephrotoxicity were assessed and cutoff values were determined. Sixty-three (70.8%) patients showed improvement in ECR and 10 (11.2%) experienced nephrotoxicity. Enterococcus spp. infections displayed correlations between AUC/MIC and ECR for AUC0-24 h/MIC (r2 = 0.27, P ≤ .05) and AUC24-48 h/MIC (r2 = 0.28, P ≤ .05), but not for Ctrough (r2 = 0.21, P > .05). There were no correlations between Ctrough (r2 = 0.26, P > .05), AUC0-24 h/MIC (r2 = -0.12, P > .05), AUC24-48 h/MIC (r2 = 0.01, P > .05) and ECR for CoNS. In the CoNS group, a moderate correlation was found between ECR and Ctrough at a cutoff value of 6.9 μg/mL. In addition, nephrotoxicity is also moderately associated with AUC0-24 h and AUC24-48 h at 505.7 and 667.1 μg•h/mL, respectively. A strong correlation between nephrotoxicity and Ctrough was observed when the cutoff value was 18.9 μg/mL. AUC/MIC during the first 48 h was a determinant of vancomycin efficacy in Enterococcus infections but not for CoNS. Ctrough was not correlated with clinical outcome. Nephrotoxicity could be predicted using Ctrough and AUC for infections with both pathogens.

Determination of minimum inhibitory concentrations using machine-learning-assisted agar dilution

Effective policy to address the global threat of antimicrobial resistance requires robust antimicrobial susceptibility data. Traditional methods for measuring minimum inhibitory concentration (MIC) are resource intensive, subject to human error, and require considerable infrastructure. AIgarMIC streamlines and standardizes MIC measurement and is especially valuable for large-scale surveillance activities. MICs were measured using agar dilution for n = 10 antibiotics against clinical Enterobacterales isolates (n = 1,086) obtained from a large tertiary hospital microbiology laboratory. Escherichia coli (n = 827, 76%) was the most common organism. Photographs of agar plates were divided into smaller images covering one inoculation site. A labeled data set of colony images was created and used to train a convolutional neural network to classify images based on whether a bacterial colony was present (first-step model). If growth was present, a second-step model determined whether colony morphology suggested antimicrobial growth inhibition. The ability of the AI to determine MIC was then compared with standard visual determination. The first-step model classified bacterial growth as present/absent with 94.3% accuracy. The second-step model classified colonies as "inhibited" or "good growth" with 88.6% accuracy. For the determination of MIC, the rate of essential agreement was 98.9% (644/651), with a bias of -7.8%, compared with manual annotation. AIgarMIC uses artificial intelligence to automate endpoint assessments for agar dilution and potentially increases throughput without bespoke equipment. AIgarMIC reduces laboratory barriers to generating high-quality MIC data that can be used for large-scale surveillance programs.

IMPORTANCE

This research uses modern artificial intelligence and machine-learning approaches to standardize and automate the interpretation of agar dilution minimum inhibitory concentration testing. Artificial intelligence is currently of significant topical interest to researchers and clinicians. In our manuscript, we demonstrate a use-case in the microbiology laboratory and present validation data for the model's performance against manual interpretation.

Identifying and mathematically modeling the time-course of extracellular metabolic markers associated with resistance to ceftolozane/tazobactam in Pseudomonas aeruginosa

Extracellular bacterial metabolites have potential as markers of bacterial growth and resistance emergence but have not been evaluated in dynamic in vitro studies. We investigated the dynamic metabolomic footprint of a multidrug-resistant hypermutable Pseudomonas aeruginosa isolate exposed to ceftolozane/tazobactam as continuous infusion (4.5 g/day, 9 g/day) in a hollow-fiber infection model over 7-9 days in biological replicates (n = 5). Bacterial samples were collected at 0, 7, 23, 47, 71, 95, 143, 167, 191, and 215 h, the supernatant quenched, and extracellular metabolites extracted. Metabolites were analyzed via untargeted metabolomics, including hierarchical clustering and correlation with quantified total and resistant bacterial populations. The time-courses of five (of 1,921 detected) metabolites from enriched pathways were mathematically modeled. Absorbed L-arginine and secreted L-ornithine were highly correlated with the total bacterial population (r -0.79 and 0.82, respectively, P<0.0001). Ribose-5-phosphate, sedoheptulose-7-phosphate, and trehalose-6-phosphate correlated with the resistant subpopulation (0.64, 0.64, and 0.67, respectively, P<0.0001) and were likely secreted due to resistant growth overcoming oxidative and osmotic stress induced by ceftolozane/tazobactam. Using pharmacokinetic/pharmacodynamic-based transduction models, these metabolites were successfully modeled based on the total or resistant bacterial populations. The models well described the abundance of each metabolite across the differing time-course profiles of biological replicates, based on bacterial killing and, importantly, resistant regrowth. These proof-of-concept studies suggest that further exploration is warranted to determine the generalizability of these findings. The metabolites modeled here are not exclusive to bacteria. Future studies may use this approach to identify bacteria-specific metabolites correlating with resistance, which would ultimately be extremely useful for clinical translation.

Comparison of Aerobic Bacterial Culture Among Four Veterinary Microbiology Laboratories from Dogs with Superficial Pyoderma

Bacterial culture and susceptibility are widely used in veterinary medicine to determine the specific bacteria causing infection as well as aid in appropriate antimicrobial selection. Previous studies have shown variable results with culture and susceptibility depending on the laboratory and methodology used. Samples from dogs with superficial pyoderma were obtained to make a homogeneous solution of bacteria. Sample acquisition from this solution was randomized and submitted to four veterinary laboratories for microbial identification and sensitivity. There was fair agreement among the laboratories in identification of a Staphylococcus spp. as well as fair agreement among the laboratories on the same Staphylococcus sp. Very good agreement was noted on identification of methicillin-resistant Staphylococcus spp. Additionally, good to very good agreement was noted on all antimicrobials that were tested across all four laboratories. A difference in turnaround time for sample processing was observed between the laboratories in the present study. Overall, there was mild variability among the laboratory results in this study.

Wild-type distributions of minimum inhibitory concentrations and epidemiological cut-off values-laboratory and clinical utility

The characterization of wild-type minimum inhibitory concentration (MIC) and zone diameter distributions with the setting of epidemiological cut-off values (ECOFFs or ECVs) provides a reference for the otherwise relative MIC values in the international system for antimicrobial susceptibility testing. Distributions of MIC values for a species and an agent follow a log-normal distribution, which in the absence of resistance mechanisms is monomodal and designated wild type (WT). The upper end of the WT distribution, the ECOFF, can be identified with statistical methods. In the presence of phenotypically detectable resistance, the distribution has at least one more mode (the non-WT), but despite this, the WT is most often identifiable using the same methods. The ECOFF provides the most sensitive measure of resistance development in a species against an agent. The WT and non-WT modes are independent of the organism´s response to treatment, but when the European Committee on Antimicrobial Susceptibility Testing (EUCAST) determines the clinical breakpoints, the committee avoids breakpoints that split WT distributions of target species. This is to avoid the poorer reproducibility of susceptibility categorization when breakpoints split major populations but also because the EUCAST has failed to identify different clinical outcomes for isolates with different MIC values inside the wild-type distribution. In laboratory practice, the ECOFF is used to screen for and exclude resistance and allows the comparison of resistance between systems with different breakpoints from different breakpoint organizations, breakpoints evolving over time, and different breakpoints between human and animal medicine. The EUCAST actively encourages colleagues to question MIC distributions as presented on the website (https://www.eucast.org/mic_and_zone_distributions_and_ecoffs) and to contribute MIC and inhibition zone diameter data.

Efficiency of dosing software using Bayesian forecasting in achieving target antibiotic exposures in critically ill patients, a prospective cohort study

INTRODUCTION

Broad-spectrum antibiotics such as beta-lactams and vancomycin are frequently used to treat critically ill patients, however, a significant number do not achieve target exposures. Therapeutic drug monitoring (TDM) combined with Bayesian forecasting dosing software may improve target attainment in these patients. This study aims to describe the efficiency of dosing software for achieving target exposures of selected beta-lactam antibiotics and vancomycin in critically ill patients.

METHODS

A prospective cohort study was undertaken in an adult intensive care unit (ICU). Patients prescribed vancomycin, piperacillin-tazobactam and meropenem were included if they exhibited a subtherapeutic or supratherapeutic exposure informed by TDM. The dosing software, ID-ODS™, was used to generate dosing recommendations which could be either accepted or rejected by the treating team. Repeat antibiotic TDM were requested to determine if target exposures were achieved.

RESULTS

Between March 2020 and December 2021, 70 were included in the analysis. Software recommendations were accepted for 56 patients (80%) with 50 having repeated antibiotic measurements. Forty-three of the 50 patients (86%) achieved target exposures after one software recommendation, with 3 of the remaining 7 patients achieving target exposures after 2. Forty-seven patients out of the 50 patients (94%) achieved the secondary outcome of clinical cure. There were no antibiotic exposure-related adverse events reported.

CONCLUSION

The use of TDM combined with Bayesian forecasting dosing software increases the efficiency for achieving target antibiotic exposures in the ICU. Clinical trials comparing this approach with other dosing strategies are required to further validate these findings.

The in vitro effect of new combinations of carbapenem-β-lactamase inhibitors for Mycobacterium abscessus

As new treatment alternatives for Mycobacterium abscessus complex (MABC) are urgently needed, we determined the minimum inhibitory concentrations (MICs) for novel carbapenem combinations, including imipenem-relebactam and tebipenem-avibactam against 98 MABC isolates by broth microdilution. The MIC50 was reduced from 16 to 8 mg/L by adding relebactam to imipenem, while the addition of avibactam to tebipenem showed a more pronounced reduction from 256 to 16 mg/L, representing a promising non-toxic, oral treatment option for further exploration.

In vitro activity of new combinations of β-lactam and β-lactamase inhibitors against the Mycobacterium tuberculosis complex

As meropenem-clavulanic acid is recommended for the treatment of drug-resistant tuberculosis, the repurposing of new carbapenem combinations may provide new treatment options, including oral alternatives. Therefore, we studied the in vitro activities of meropenem-vaborbactam, meropenem-clavulanic acid, and tebipenem-clavulanic acid. One hundred nine Mycobacterium tuberculosis complex (MTBC) clinical isolates were tested, of which 69 were pan-susceptible and the remaining pyrazinamide- or multidrug-resistant. Broth microdilution MICs were determined using the EUCAST reference method. Meropenem and tebipenem were tested individually and in combination with vaborbactam 8 mg/L and clavulanic-acid 2 and 4 mg/L, respectively. Whole-genome sequencing was performed to explore resistance mechanisms. Clavulanic acid lowered the modal tebipenem MIC approximately 16-fold (from 16 to 1 mg/L). The modal meropenem MIC was reduced twofold by vaborbactam compared with an approximately eightfold decrease by clavulanic acid. The only previously described high-confidence carbapenem resistance mutation, crfA T62A, was shared by a subgroup of lineage 4.3.4.1 isolates and did not correlate with elevated MICs. The presence of a β-lactamase inhibitor reduced the MTBC MICs of tebipenem and meropenem. The resulting MIC distribution was lowest for the orally available drugs tebipenem-clavulanic acid. Whether this in vitro activity translates to similar or greater clinical efficacy of tebipenem-clavulanic acid compared with the currently WHO-endorsed meropenem-clavulanic acid requires clinical studies. IMPORTANCE Repurposing of already approved antibiotics, such as β-lactams in combination with β-lactamase inhibitors, may provide new treatment alternatives for drug-resistant tuberculosis. Meropenem-clavulanic acid was more active in vitro compared to meropenem-vaborbactam. Notably, tebipenem-clavulanic acid showed even better activity, raising the potential of an all-oral treatment option. Clinical data are needed to investigate whether the better in vitro activity of tebipenem-clavulanic acid correlates with greater clinical efficacy compared with the currently WHO-endorsed meropenem-clavulanic acid.

Potential Failure of Vancomycin Dosing Using AUC/MIC in a Patient With Purulent Methicillin-Resistant Staphylococcus aureus Pericarditis

Objective: The objective of this case report is to describe utilization of area under the curve (AUC)/minimum inhibitory concentration (MIC) vancomycin dosing with variable MIC results in a patient with methicillin-resistant Staphylococcus aureus (MRSA) purulent pericarditis. Case: A 57-year-old Caucasian male presented with cardiac tamponade and pulmonary emboli. Echocardiogram showed moderate-large pericardial effusion with signs of early tamponade physiology. Pericardiocentesis removed serosanguinous, straw yellow fluid. Blood and pericardial cultures revealed MRSA. Patient was then initiated on vancomycin with an initial AUC of 415. MIC of repeat blood cultures were inconsistent. After 8 days of persistent bacteremia, patient was transitioned to daptomycin and ceftaroline with blood culture clearance within 48 hours. Discussion/Conclusion: Guidelines recommend AUC/MIC vancomycin dosing in patients with MRSA bacteremia. Literature regarding treatment of MRSA purulent pericarditis is limited to case reports. Evidence shows variation in MIC results dependent on analysis methods. Further studies on obtaining accurate MIC values and use of AUC/MIC dosing for MRSA purulent pericarditis are prudent to provide appropriate therapy in these patients as mortality is high.

The Current Status and Future Perspectives of Beta-Lactam Therapeutic Drug Monitoring in Critically Ill Patients

Beta-lactams (BL) are the first line agents for the antibiotic management of critically ill patients with sepsis or septic shock. BL are hydrophilic antibiotics particularly subject to unpredictable concentrations in the context of critical illness because of pharmacokinetic (PK) and pharmacodynamics (PD) alterations. Thus, during the last decade, the literature focusing on the interest of BL therapeutic drug monitoring (TDM) in the intensive care unit (ICU) setting has been exponential. Moreover, recent guidelines strongly encourage to optimize BL therapy using a PK/PD approach with TDM. Unfortunately, several barriers exist regarding TDM access and interpretation. Consequently, adherence to routine TDM in ICU remains quite low. Lastly, recent clinical studies failed to demonstrate any improvement in mortality with the use of TDM in ICU patients. This review will first aim at explaining the value and complexity of the TDM process when translating it to critically ill patient bedside management, interpretating the results of clinical studies and discussion of the points which need to be addressed before conducting further TDM studies on clinical outcomes. In a second time, this review will focus on the future aspects of TDM integrating toxicodynamics, model informed precision dosing (MIPD) and “at risk” ICU populations that deserve further investigations to demonstrate positive clinical outcomes.

Update on Therapeutic Drug Monitoring of Beta-Lactam Antibiotics in Critically Ill Patients—A Narrative Review

Beta-lactam antibiotics remain one of the most preferred groups of antibiotics in critical care due to their excellent safety profiles and their activity against a wide spectrum of pathogens. The cornerstone of appropriate therapy with beta-lactams is to achieve an adequate plasmatic concentration of a given antibiotic, which is derived primarily from the minimum inhibitory concentration (MIC) of the specific pathogen. In a critically ill patient, the plasmatic levels of drugs could be affected by many significant changes in the patient’s physiology, such as hypoalbuminemia, endothelial dysfunction with the leakage of intravascular fluid into interstitial space and acute kidney injury. Predicting antibiotic concentration from models based on non-critically ill populations may be misleading. Therapeutic drug monitoring (TDM) has been shown to be effective in achieving adequate concentrations of many drugs, including beta-lactam antibiotics. Reliable methods, such as high-performance liquid chromatography, provide the accurate testing of a wide range of beta-lactam antibiotics. Long turnaround times remain the main drawback limiting their widespread use, although progress has been made recently in the implementation of different novel methods of antibiotic testing. However, whether the TDM approach can effectively improve clinically relevant patient outcomes must be proved in future clinical trials.

Artificial Intelligence for Antimicrobial Resistance Prediction: Challenges and Opportunities towards Practical Implementation

Antimicrobial resistance (AMR) is emerging as a potential threat to many lives worldwide. It is very important to understand and apply effective strategies to counter the impact of AMR and its mutation from a medical treatment point of view. The intersection of artificial intelligence (AI), especially deep learning/machine learning, has led to a new direction in antimicrobial identification. Furthermore, presently, the availability of huge amounts of data from multiple sources has made it more effective to use these artificial intelligence techniques to identify interesting insights into AMR genes such as new genes, mutations, drug identification, conditions favorable to spread, and so on. Therefore, this paper presents a review of state-of-the-art challenges and opportunities. These include interesting input features posing challenges in use, state-of-the-art deep-learning/machine-learning models for robustness and high accuracy, challenges, and prospects to apply these techniques for practical purposes. The paper concludes with the encouragement to apply AI to the AMR sector with the intention of practical diagnosis and treatment, since presently most studies are at early stages with minimal application in the practice of diagnosis and treatment of disease.

Phenotypes, genotypes and breakpoints: an assessment of β-lactam/β-lactamase inhibitor combinations against OXA-48

BACKGROUND

Two of the three recently approved β-lactam agent (BL)/β-lactamase inhibitor (BLI) combinations have higher CLSI susceptibility breakpoints (ceftazidime/avibactam 8 mg/L; meropenem/vaborbactam 4 mg/L) compared with the BL alone (ceftazidime 4 mg/L; meropenem 1 mg/L). This can lead to a therapeutic grey area on susceptibility reports depending on resistance mechanism. For instance, a meropenem-resistant OXA-48 isolate (MIC 4 mg/L) may appear as meropenem/vaborbactam-susceptible (MIC 4 mg/L) despite vaborbactam's lack of OXA-48 inhibitory activity.

METHODS

OXA-48-positive (n = 51) and OXA-48-negative (KPC, n = 5; Klebsiella pneumoniae wild-type, n = 1) Enterobacterales were utilized. Susceptibility tests (broth microdilution) were conducted with ceftazidime/avibactam, imipenem/relebactam and meropenem/vaborbactam, as well as their respective BL partner. Antimicrobial activity of all six agents was evaluated in the murine neutropenic thigh model using clinically relevant exposures. Efficacy was assessed as the change in bacterial growth at 24 h, compared with 0 h controls.

RESULTS

On average, the three BL/BLI agents resulted in robust bacteria killing among OXA-48-negative isolates. Among OXA-48-positive isolates, poor in vivo activity with imipenem/relebactam was concordant with its resistant phenotypic profile. Variable meropenem/vaborbactam activity was observed among isolates with a 'susceptible' MIC of 4 mg/L. Only 30% (7/23) of isolates at meropenem/vaborbactam MICs of 2 and 4 mg/L met the ≥1-log bacterial reduction threshold predictive of clinical efficacy in serious infections. In contrast, ceftazidime/avibactam resulted in marked bacterial density reduction across the range of MICs, and 96% (49/51) of isolates exceeded the ≥1-log bacterial reduction threshold.

CONCLUSIONS

Data demonstrate that current imipenem/relebactam and ceftazidime/avibactam CLSI breakpoints are appropriate. Data also suggest that higher meropenem/vaborbactam breakpoints relative to meropenem can translate to potentially poor clinical outcomes in patients infected with OXA-48-harbouring isolates.

Antimicrobial susceptibility testing: An updated primer for clinicians in the era of antimicrobial resistance: Insights from the Society of Infectious Diseases Pharmacists

Antimicrobial susceptibility testing (AST) is a critical function of the clinical microbiology laboratory and is essential for optimizing care of patients with infectious diseases, monitoring antimicrobial resistance (AMR) trends, and informing public health initiatives. Several methods are available for performing AST including broth microdilution, agar dilution, and disk diffusion. Technological advances such as the development of commercial automated susceptibility testing platforms and the advent of rapid diagnostic tests have improved the rapidity, robustness, and clinical application of AST. Numerous accrediting and regulatory agencies are involved in the process of AST and setting and revising breakpoints, including the U.S. Food and Drug Administration and the Clinical and Laboratory Standards Institute. Challenges to optimizing AST include the emergence of new resistance mechanisms, the development of new antimicrobial agents, and generation of new data requiring updates and revisions to established methods and breakpoints. Together, the challenges in AST methods and their interpretation create important opportunities for well-informed clinicians to improve patient outcomes and provide value to antimicrobial stewardship programs, especially in the setting of rapidly changing and increasing AMR. Addressing AST challenges will involve continued development of new technologies along with collaboration between clinicians and the laboratory to facilitate optimal antimicrobial use, combat the increasing burden of AMR, and inform the development of novel antimicrobials. This updated primer serves to reinforce important principles of AST, and to provide guidance on their implementation and optimization.

Evaluation of Piperacillin-Tazobactam Testing against Enterobacterales by the Phoenix, MicroScan, and Vitek2 Tests Using Updated Clinical and Laboratory Standards Institute Breakpoints

In 2022, the Clinical and Laboratory Standards Institute (CLSI) updated piperacillin-tazobactam (TZP) breakpoints for Enterobacterales, based on substantial data suggesting that historical breakpoints did not predict treatment outcomes for TZP. The U.S. Food and Drug Administration (FDA) has not yet adopted these breakpoints, meaning commercial manufacturers of antimicrobial susceptibility testing devices cannot obtain FDA clearance for the revised breakpoints. We evaluated the Phoenix (BD, Sparks, MD), MicroScan (Beckman Coulter, Sacramento, CA), and Vitek2 (bioMérieux, Durham, NC) TZP MICs compared to reference broth microdilution for a collection of 284 Enterobacterales isolates. Phoenix (n = 167 isolates) demonstrated 84.4% categorical agreement (CA), with 4.2% very major errors (VMEs) and 1.8% major errors (MEs) by CLSI breakpoints. In contrast, CA was 85.0% with 4.3% VMEs and 0.8% MEs for the Phoenix with FDA breakpoints. MicroScan (n = 55 isolates) demonstrated 80.0% CA, 36.4% VMEs, and 4.8% MEs by CLSI breakpoints and 81.8% CA, 44.4% VMEs, and 0.0% MEs by FDA breakpoints. Vitek2 (n = 62 isolates) demonstrated 95.2% CA, 6.3% VMEs, and 0.0% MEs by CLSI and 96.8% CA, 0.0% VMEs, and 2.2% MEs by FDA breakpoints. Overall, the performance of the test systems was not substantially different using CLSI breakpoints off-label than using on-label FDA breakpoints. However, limitations were noted with higher-than-desired VME rates (all three systems) and lower-than-desired CA (MicroScan and Phoenix). Laboratories should consider adoption of the revised CLSI breakpoints with automated test systems but be aware that some performance challenges exist for testing TZP on automated systems, regardless of breakpoints applied.

Using random forest to predict antimicrobial minimum inhibitory concentrations of nontyphoidal Salmonella in Taiwan

Antimicrobial resistance (AMR) is a global health issue and surveillance of AMR can be useful for understanding AMR trends and planning intervention strategies. Salmonella, widely distributed in food-producing animals, has been considered the first priority for inclusion in the AMR surveillance program by the World Health Organization (WHO). Recent advances in rapid and affordable whole-genome sequencing (WGS) techniques lead to the emergence of WGS as a one-stop test to predict the antimicrobial susceptibility. Since the variation of sequencing and minimum inhibitory concentration (MIC) measurement methods could result in different results, this study aimed to develop WGS-based random forest models for predicting MIC values of 24 drugs using data generated from the same laboratories in Taiwan. The WGS data have been transformed as a feature vector of 10-mers for machine learning. Based on rigorous validation and independent tests, a good performance was obtained with an average mean absolute error (MAE) less than 1 for both validation and independent test. Feature selection was then applied to identify top-ranked 10-mers that can further improve the prediction performance. For surveillance purposes, the genome sequence-based machine learning methods could be utilized to monitor the difference between predicted and experimental MIC, where a large difference might be worthy of investigation on the emerging genomic determinants.

Evaluation of Piperacillin-Tazobactam ETEST for the Detection of OXA-1 Resistance Mechanism among Escherichia coli and Klebsiella pneumoniae

Globally, piperacillin-tazobactam resistance among Escherichia coli and Klebsiella pneumoniae is driven by OXA-1 beta-lactamases. Expression of bla_OXA-1 yields piperacillin-tazobactam MICs of 8 to 16 μg/mL, which straddle the susceptible/susceptible-dose dependent breakpoint set by the Clinical and Laboratory Standards Institute in 2022. Variability of the reference broth microdilution method (BMD) was evaluated by manufacturing BMD panels using 2 brands of piperacillin, 2 brands of tazobactam and 2 brands of cation-adjusted Mueller-Hinton broth. In addition, ETEST, which harbors an intermediate dilution of 12 μg/mL was evaluated for the ability to differentiate isolates with and without bla_OXA-1. A collection of 200 E. coli and K. pneumoniae, of which 82 harbored a bla_OXA-1 gene, were tested. BMD variability was on average 1.3-fold, within the accepted 2-fold variability of MICs. However, categorical agreement (CA) between BMD reads was 74.0% for all isolates and 63.4% for those with a bla_OXA-1 gene and 81.3% for those without bla_OXA-1 detected (P = 0.004, Pearson's Chi Square). ETEST overall CA with the BMD mode was 68.0% and essential agreement (EA) was 80.5%. For isolates with bla_OXA-1, CA was 50.0% and EA was 69.5%, versus 80.5% and 88.1%, respectively, for isolates without bla_OXA-1 (P < 0.0001 for both comparisons). All ETEST errors were major errors (false resistance) compared to BMD mode. However, the negative predictive value of the ETEST for the presence of bla_OXA-1 was 94.1%, compared to only 74.2% negative predictive value for BMD. Clinicians and microbiologists should be aware of the challenges associated with testing piperacillin-tazobactam in regions where bla_OXA-1 is prevalent.

Population Pharmacokinetic Model and Optimal Sampling Strategies for Micafungin in Critically Ill Patients Diagnosed with Invasive Candidiasis

Candida bloodstream infections are associated with high attributable mortality, where early initiation of adequate antifungal therapy is important to increase survival in critically ill patients. The exposure variability of micafungin, a first-line agent used for the treatment of invasive candidiasis, in critically ill patients is significant, potentially resulting in underexposure in a substantial portion of these patients. The objective of this study was to develop a population pharmacokinetic model including appropriate sampling strategies for assessing micafungin drug exposure in critically ill patients to support adequate area under the concentration-time curve (AUC) determination. A two-compartment pharmacokinetic model was developed using data from intensive care unit (ICU) patients (n = 19), with the following parameters: total body clearance (CL), volume of distribution of the central compartment (V1), inter-compartmental clearance (CL12), and volume of distribution of the peripheral compartment (V2). The final model was evaluated with bootstrap analysis and the goodness-of-fit plots for the population and individual predicted micafungin plasma concentrations. Optimal sampling strategies (with sampling every hour, 24 h per day) were developed with 1- and 2-point sampling schemes. Final model parameters (±SD) were: CL = 1.03 (0.37) (L/h/1.85 m²), V1 = 0.17 (0.07) (L/kg LBMc), CL12 = 1.80 (4.07) (L/h/1.85 m²), and V2 = 0.12 (0.06) (L/kg LBMc). Sampling strategies with acceptable accuracy and precision were developed to determine the micafungin AUC. The developed model with optimal sampling procedures provides the opportunity to achieve quick optimization of the micafungin exposure from a single blood sample using Bayesian software and may be helpful in guiding early dose decision-making.

Phenotypes, genotypes and breakpoints: an assessment of β-lactam/ β-lactamase inhibitor combinations against OXA-48

BACKGROUND

Two out of the three recently approved β-lactam (BL)/β-lactamase inhibitors (BLIs) have higher CLSI susceptibility breakpoints (ceftazidime/avibactam 8 mg/L; meropenem/vaborbactam 4 mg/L) compared with the BL alone (ceftazidime 4 mg/L; meropenem 1 mg/L). This can lead to a therapeutic grey area on susceptibility reports depending on resistance mechanism. For instance, a meropenem-resistant OXA-48 isolate (MIC 4 mg/L) may appear as meropenem/vaborbactam-susceptible (MIC 4 mg/L) despite vaborbactam's lack of OXA-48 inhibitory activity.

METHODS

OXA-48-positive (n = 51) and OXA-48-negative (KPC, n = 5; Klebsiella pneumoniae WT, n = 1) Enterobacterales were utilized. Susceptibility tests (broth microdilution) were conducted with ceftazidime/avibactam, imipenem/relebactam and meropenem/vaborbactam, as well as their respective BL partner. Antimicrobial activity of all six agents was evaluated in the murine neutropenic thigh model using clinically relevant exposures. Efficacy was assessed as the change in bacterial growth at 24 h, compared with 0 h controls.

RESULTS

On average, the three BL/BLI agents resulted in robust bacteria killing among OXA-48-negative isolates. Among OXA-48-positive isolates, poor in vivo activity with imipenem/relebactam was concordant with its resistant phenotypic profile. Variable meropenem/vaborbactam activity was observed among isolates with a 'susceptible' MIC of 4 mg/L. Only 30% (7/23) of isolates at meropenem/vaborbactam MICs of 2 and 4 mg/L met the ≥1 log bacterial reduction threshold predictive of clinical efficacy in serious infections. In contrast, ceftazidime/avibactam resulted in marked bacterial density reduction across the range of MICs and 73% (37/51) of isolates exceeded the ≥1 log bacterial reduction threshold.

CONCLUSIONS

Data demonstrate that current imipenem/relebactam and ceftazidime/avibactam CLSI breakpoints are appropriate. Data also suggest that higher meropenem/vaborbactam breakpoints relative to meropenem can translate to potentially poor clinical outcomes in patients infected with OXA-48-harbouring isolates.

The mysteries of target site concentrations of antibiotics in bone and joint infections: what is known? A narrative review

INTRODUCTION

Currently, antibiotic treatment is often a standard dosing regimen in bone and joint infections (BJI). However, it remains unknown if exposure at the target-site is adequate. The aim of this review is to gain more insight in the relationship between the target site concentration of antibiotic and the minimal inhibitory concentration to target the bacteria in bone and joint infections (BJI).

AREAS COVERED

A literature search was performed by Erasmus MC Medical library. Bone, bone tissue and synovial concentration of antibiotics were covered in humans. In addition, we reported number of patients, dose, sampling method, analytical method and tissue and plasma concentrations. We used the epidemiological cut-off value (ECOFF) values of the targeted micro-organisms. If more than 3 publications were available on the antibiotic, we graphically presented ECOFFS values against reported antibiotic concentrations.

EXPERT OPINION

For most antibiotics the literature is sparse. In addition, a lot of variable and total antibiotic concentrations are published. Ciprofloxacin, cefazolin, cefuroxime, vancomycin and linezolid seem to have adequate average exposure if correlating total concentration to ECOFF, when standard dosing is used. With regards to other antibiotics, results are inconclusive. More extensive pharmacokinetic/pharmacodynamic modeling in BJI is needed.

β-Lactam Therapeutic Drug Monitoring in Critically Ill Patients: Weighing the Challenges and Opportunities to Assess Clinical Value

OBJECTIVE:

DATA SOURCES:

STUDY SELECTION:

DATA EXTRACTION:

DATA SYNTHESIS:

CONCLUSIONS:

Insights into the Antimicrobial Activities and Metabolomes of Aquimarina (Flavobacteriaceae, Bacteroidetes) Species from the Rare Marine Biosphere

Two novel natural products, the polyketide cuniculene and the peptide antibiotic aquimarin, were recently discovered from the marine bacterial genus Aquimarina. However, the diversity of the secondary metabolite biosynthetic gene clusters (SM-BGCs) in Aquimarina genomes indicates a far greater biosynthetic potential. In this study, nine representative Aquimarina strains were tested for antimicrobial activity against diverse human-pathogenic and marine microorganisms and subjected to metabolomic and genomic profiling. We found an inhibitory activity of most Aquimarina strains against Candida glabrata and marine Vibrio and Alphaproteobacteria species. Aquimarina sp. Aq135 and Aquimarina muelleri crude extracts showed particularly promising antimicrobial activities, amongst others against methicillin-resistant Staphylococcus aureus. The metabolomic and functional genomic profiles of Aquimarina spp. followed similar patterns and were shaped by phylogeny. SM-BGC and metabolomics networks suggest the presence of novel polyketides and peptides, including cyclic depsipeptide-related compounds. Moreover, exploration of the ‘Sponge Microbiome Project’ dataset revealed that Aquimarina spp. possess low-abundance distributions worldwide across multiple marine biotopes. Our study emphasizes the relevance of this member of the microbial rare biosphere as a promising source of novel natural products. We predict that future metabologenomics studies of Aquimarina species will expand the spectrum of known secondary metabolites and bioactivities from marine ecosystems.

Essential Oils in Respiratory Mycosis: A Review

Respiratory mycosis is a major health concern, due to the expanding population of immunosuppressed and immunocompromised patients and the increasing resistance to conventional antifungals and their undesired side-effects, thus justifying the development of new therapeutic strategies. Plant metabolites, namely essential oils, represent promising preventive/therapeutic strategies due to their widely reported antifungal potential. However, regarding fungal infections of the respiratory tract, information is disperse and no updated compilation on current knowledge is available. Therefore, the present review aims to gather and systematize relevant information on the antifungal effects of several essential oils and volatile compounds against the main type of respiratory mycosis that impact health care systems. Particular attention is paid to Aspergillus fumigatus, the main pathogen involved in aspergillosis, Candida auris, currently emerging as a major pathogen in certain parts of the world, and Cryptococcus neoformans, one of the main pathogens involved in pulmonary cryptococcosis. Furthermore, the main mechanisms of action underlying essential oils’ antifungal effects and current limitations in clinical translation are presented. Overall, essential oils rich in phenolic compounds seem to be very effective but clinical translation requires more comprehensive in vivo studies and human trials to assess the efficacy and tolerability of these compounds in respiratory mycosis.

Updating the approaches to define susceptibility and resistance to anti-tuberculosis agents: implications for diagnosis and treatment

Approximately 85 000 deaths globally in 2019 were due to drug-resistant tuberculosis (TB), which corresponds to 7% of global deaths attributable to bacterial antimicrobial resistance [1]. Yet concerns have been mounting that drug-resistant TB was being underestimated because the approaches to define susceptibility and resistance to anti-TB agents had not kept up with those used for other major bacterial pathogens [2–9]. Here, we outline the recent, evidence-based initiatives spearheaded by the World Health Organization (WHO) and others to update breakpoints (traditionally referred to as critical concentrations (CCs)) that are used for phenotypic antimicrobial susceptibility testing (AST), also called drug susceptibility testing in the TB literature.

Inappropriately high breakpoints have resulted in systematic false-susceptible AST results to anti-TB drugs. MIC, PK/PD and clinical outcome data should be combined when setting breakpoints to minimise the emergence and spread of antimicrobial resistance. https://bit.ly/3i43wb6

Model-Informed Precision Dosing of Linezolid in Patients with Drug-Resistant Tuberculosis

Linezolid is an efficacious medication for the treatment of drug-resistant tuberculosis but has been associated with serious safety issues that can result in treatment interruption. The objectives of this study were thus to build a population pharmacokinetic model and to use the developed model to establish a model-informed precision dosing (MIPD) algorithm enabling safe and efficacious dosing in patients with multidrug- and extensively drug-resistant tuberculosis. Routine hospital therapeutic drug monitoring data, collected from 70 tuberculosis patients receiving linezolid, was used for model development. Efficacy and safety targets for MIPD were the ratio of unbound area under the concentration versus time curve between 0 and 24 h over minimal inhibitory concentration (fAUC_0–24h/MIC) above 119 and unbound plasma trough concentration (fC_min) below 1.38 mg/L, respectively. Model building was performed in NONMEM 7.4.3. The final population pharmacokinetic model consisted of a one-compartment model with transit absorption and concentration- and time-dependent auto-inhibition of elimination. A flat dose of 600 mg once daily was appropriate in 67.2% of the simulated patients from an efficacy and safety perspective. Using the here developed MIPD algorithm, the proportion of patients reaching the efficacy and safety target increased to 81.5% and 88.2% using information from two and three pharmacokinetic sampling occasions, respectively. This work proposes an MIPD approach for linezolid and suggests using three sampling occasions to derive an individualized dose that results in adequate efficacy and fewer safety concerns compared to flat dosing.

Therapeutic Drug Monitoring of Antibiotic Drugs: The Role of the Clinical Laboratory

BACKGROUND

Therapeutic drug monitoring (TDM) of anti-infective drugs is an increasingly complex field, given that in addition to the patient and drug as 2 usual determinants, its success is driven by the pathogen. Pharmacodynamics is related both to the patient (toxicity) and bacterium (efficacy or antibiotic susceptibility). The specifics of TDM of antimicrobial drugs stress the need for multidisciplinary knowledge and expertise, as in any other field. The role and the responsibility of the laboratory in this interplay are both central and multifaceted. This narrative review highlights the role of the clinical laboratory in the TDM process.

METHODS

A literature search was conducted in PubMed and Google Scholar, focusing on the past 5 years (studies published since 2016) to limit redundancy with previously published review articles. Furthermore, the references cited in identified publications of interest were screened for additional relevant studies and articles.

RESULTS

The authors addressed microbiological methods to determine antibiotic susceptibility, immunochemical and chromatographic methods to measure drug concentrations (primarily in blood samples), and endogenous clinical laboratory biomarkers to monitor treatment efficacy and toxicity. The advantages and disadvantages of these methods are critically discussed, along with existing gaps and future perspectives on strategies to provide clinicians with as reliable and useful results as possible.

CONCLUSIONS

Although interest in the field has been the driver for certain progress in analytical technology and quality in recent years, laboratory professionals and commercial providers persistently encounter numerous unresolved challenges. The main tasks that need tackling include broadly and continuously available, easily operated, and cost-effective tests that offer short turnaround times, combined with reliable and easy-to-interpret results. Various fields of research are currently addressing these features.

OUP accepted manuscript

Objectives

To develop a robust phenotypic antimicrobial susceptibility testing (AST) method with a correctly set breakpoint for pretomanid (Pa), the most recently approved anti-tuberculosis drug.

Methods

The Becton Dickinson Mycobacterial Growth Indicator Tube™ (MGIT) system was used at six laboratories to determine the MICs of a phylogenetically diverse collection of 356 Mycobacterium tuberculosis complex (MTBC) strains to establish the epidemiological cut-off value for pretomanid. MICs were correlated with WGS data to study the genetic basis of differences in the susceptibility to pretomanid.

Results

We observed ancient differences in the susceptibility to pretomanid among various members of MTBC. Most notably, lineage 1 of M. tuberculosis, which is estimated to account for 28% of tuberculosis cases globally, was less susceptible than lineages 2, 3, 4 and 7 of M. tuberculosis, resulting in a 99th percentile of 2 mg/L for lineage 1 compared with 0.5 mg/L for the remaining M. tuberculosis lineages. Moreover, we observed that higher MICs (≥8 mg/L), which probably confer resistance, had recently evolved independently in six different M. tuberculosis strains. Unlike the aforementioned ancient differences in susceptibility, these recent differences were likely caused by mutations in the known pretomanid resistance genes.

Conclusions

In light of these findings, the provisional critical concentration of 1 mg/L for MGIT set by EMA must be re-evaluated. More broadly, these findings underline the importance of considering the global diversity of MTBC during clinical development of drugs and when defining breakpoints for AST.

Predicting Antimicrobial Activity at the Target Site: Pharmacokinetic/Pharmacodynamic Indices versus Time-Kill Approaches

Antibiotic dosing strategies are generally based on systemic drug concentrations. However, drug concentrations at the infection site drive antimicrobial effect, and efficacy predictions and dosing strategies should be based on these concentrations. We set out to review different translational pharmacokinetic-pharmacodynamic (PK/PD) approaches from a target site perspective. The most common approach involves calculating the probability of attaining animal-derived PK/PD index targets, which link PK parameters to antimicrobial susceptibility measures. This approach is time efficient but ignores some aspects of the shape of the PK profile and inter-species differences in drug clearance and distribution, and provides no information on the PD time-course. Time–kill curves, in contrast, depict bacterial response over time. In vitro dynamic time–kill setups allow for the evaluation of bacterial response to clinical PK profiles, but are not representative of the infection site environment. The translational value of in vivo time–kill experiments, conversely, is limited from a PK perspective. Computational PK/PD models, especially when developed using both in vitro and in vivo data and coupled to target site PK models, can bridge translational gaps in both PK and PD. Ultimately, clinical PK and experimental and computational tools should be combined to tailor antibiotic treatment strategies to the site of infection.

Limitations of Antibiotic MIC-Based PK-PD Metrics: Looking Back to Move Forward

Within a few years after the first successful clinical use of penicillin, investigations were conducted in animal infection models to explore a range of factors that were considered likely to influence the antibacterial response to the drug. Those studies identified that the response was influenced by not only the total daily dose but also the interval between individual doses across the day, and whether penicillin was administered in an intermittent or continuous manner. Later, as more antibiotics were discovered and developed, antimicrobial pharmacologists began to measure antibiotic concentrations in biological fluids. This enabled the linking of antibacterial response at a single time point in an animal or in vitro infection model with one of three summary pharmacokinetic (PK) measures of in vivo exposure to the antibiotic. The summary PK exposure measures were normalised to the minimum inhibitory concentration (MIC), an in vitro measure of the pharmacodynamic (PD) potency of the drug. The three PK-PD indices (ratio of maximum concentration to MIC, ratio of area under the concentration-time curve to MIC, time concentration is above MIC) have been used extensively since the 1980s. While these MIC-based summary PK-PD metrics have undoubtedly facilitated the development of new antibiotics and the clinical application of both new and old antibiotics, it is increasingly recognised that they have a number of substantial limitations. In this article we use a historical perspective to review the origins of the three traditional PK-PD indices before exploring in detail their limitations and the implications arising from those limitations. Finally, in the interests of improving antibiotic development and dosing in patients, we consider a model-based approach of linking the full time-course of antibiotic concentrations with that of the antibacterial response. Such an approach enables incorporation of other factors that can influence treatment outcome in patients and has the potential to drive model-informed precision dosing of antibiotics into the future.

Drug exposure and susceptibility of second-line drugs correlate with treatment response in patients with multidrug-resistant tuberculosis: a multi-centre prospective cohort study in China

Background

Understanding the impact of drug exposure and susceptibility on treatment response of multidrug-resistant tuberculosis (MDR-TB) will help to optimise treatment. This study aimed to investigate the association between drug exposure, susceptibility and response to MDR-TB treatment.

Methods

Drug exposure and susceptibility for second-line drugs were measured for patients with MDR-TB. Multivariate analysis was applied to investigate the impact of drug exposure and susceptibility on sputum culture conversion and treatment outcome. Probability of target attainment was evaluated. Random Forest and CART (Classification and Regression Tree) analysis was used to identify key predictors and their clinical targets among patients on World Health Organization-recommended regimens.

Results

Drug exposure and corresponding susceptibility were available for 197 patients with MDR-TB. The probability of target attainment was highly variable, ranging from 0% for ethambutol to 97% for linezolid, while patients with fluoroquinolones above targets had a higher probability of 2-month culture conversion (56.3% versus 28.6%; adjusted OR 2.91, 95% CI 1.42–5.94) and favourable outcome (88.8% versus 68.8%; adjusted OR 2.89, 95% CI 1.16–7.17). Higher exposure values of fluoroquinolones, linezolid and pyrazinamide were associated with earlier sputum culture conversion. CART analysis selected moxifloxacin area under the drug concentration–time curve/minimum inhibitory concentration (AUC_0–24h/MIC) of 231 and linezolid AUC_0–24h/MIC of 287 as best predictors for 6-month culture conversion in patients receiving identical Group A-based regimens. These associations were confirmed in multivariate analysis.

Conclusions

Our findings indicate that target attainment of TB drugs is associated with response to treatment. The CART-derived thresholds may serve as targets for early dose adjustment in a future randomised controlled study to improve MDR-TB treatment outcome.

Drug exposure and susceptibility were proved to be associated with treatment responses during multidrug-resistant tuberculosis treatment, and identified thresholds may serve as targets for dose adjustment in future clinical studies to improve treatment efficacyhttps://bit.ly/3pZQbFU

Quantification of persister formation of Escherichia coli leveraging electronic cell counting and semi-mechanistic pharmacokinetic/pharmacodynamic modelling

BACKGROUND

Persister formation of Escherichia coli under fluoroquinolone exposure causes treatment failure and promotes emergence of resistant strains. Semi-mechanistic pharmacokinetic/pharmacodynamic modelling of data obtained from in vitro infection model experiments comprehensively characterizes exposure-effect relationships, providing mechanistic insights.

OBJECTIVES

To quantify persister formation of E. coli under levofloxacin exposure and to explain the observed growth-kill behaviour, leveraging electronic cell counting and pharmacokinetic/pharmacodynamic modelling.

METHODS

Three fluoroquinolone-resistant clinical E. coli isolates were exposed to levofloxacin in static and dynamic in vitro infection model experiments. Complementary to plate counting, bacterial concentrations over time were quantified by electronic cell counting and amalgamated in a semi-mechanistic pharmacokinetic/pharmacodynamic model (1281 bacterial and 394 levofloxacin observations).

RESULTS

Bacterial regrowth was observed under exposure to clinically relevant dosing regimens in the dynamic in vitro infection model. Electronic cell counting facilitated identification of three bacterial subpopulations: persisters, viable cells and dead cells. Two strain-specific manifestations of the levofloxacin effect were identified: a killing effect, characterized as a sigmoidal Emax model, and an additive increase in persister formation under levofloxacin exposure. Significantly different EC50 values quantitatively discerned levofloxacin potency for two isolates displaying the same MIC value: 8 mg/L [EC50 = 17.2 (95% CI = 12.6-23.8) mg/L and 8.46 (95% CI = 6.86-10.3) mg/L, respectively]. Persister formation was most pronounced for the isolate with the lowest MIC value (2 mg/L).

CONCLUSIONS

The developed pharmacokinetic/pharmacodynamic model adequately characterized growth-kill behaviour of three E. coli isolates and unveiled strain-specific levofloxacin potencies and persister formation. The mimicked dosing regimens did not eradicate the resistant isolates and enhanced persister formation to a strain-specific extent.

Stochastic response of bacterial cells to antibiotics: its mechanisms and implications for population and evolutionary dynamics

The effectiveness of antibiotics against bacterial infections has been declining due to the emergence of resistance. Precisely understanding the response of bacteria to antibiotics is critical to maximizing antibiotic-induced bacterial eradication while minimizing the emergence of antibiotic resistance. Cell-to-cell heterogeneity in antibiotic susceptibility is observed across various bacterial species for a wide range of antibiotics. Heterogeneity in antibiotic susceptibility is not always due to the genetic differences. Rather, it can be caused by non-genetic mechanisms such as stochastic gene expression and biased partitioning upon cell division. Heterogeneous susceptibility leads to the stochastic growth and death of individual cells and stochastic fluctuations in population size. These fluctuations have important implications for the eradication of bacterial populations and the emergence of genotypic resistance.

Variability of Beta-Lactam Broth Microdilution for Pseudomonas aeruginosa

Antimicrobial susceptibility testing for Pseudomonas aeruginosa is critical to determine suitable treatment options. Commercial susceptibility tests are typically calibrated against the reference method, broth microdilution (BMD). Imprecision of minimum inhibitory concentrations (MICs) obtained by BMD for the same isolate on repeat testing is known to exist. Factors that impact the extent of variability include concentration of the inoculum, operator effects, contents of the media, inherent strain properties, and the testing process or materials. We evaluated the variability of BMD for anti-pseudomonal beta-lactams (aztreonam, cefepime, ceftazidime, meropenem, piperacillin-tazobactam, ceftazidime-avibactam, ceftolozane-tazobactam) tested against a collection of P. aeruginosa isolates. Multiple replicate BMD tests were performed and MICs were compared to assess reproducibility, including the impact of the inoculum and operator. Overall, essential agreement (EA) was ≥ 90% for all beta-lactams tested. Absolute agreement (AA) was as low as 70% for some beta-lactams. Variability from the inoculum and operators impacted the reproducibility of MICs. Piperacillin-tazobactam exhibited the highest degree of variability with 74% AA and 94%% EA. The implications of MIC variability are extensive as the MIC is essential for multiple facets of microbiology, such as the development of new compounds and susceptibility tests, dose optimization and pharmacokinetic/pharmacodynamic (PK/PD) targets for individual patients.

Optimizing Antimicrobial Drug Dosing in Critically Ill Patients

A fundamental step in the successful management of sepsis and septic shock is early empiric antimicrobial therapy. However, for this to be effective, several decisions must be addressed simultaneously: (1) antimicrobial choices should be adequate, covering the most probable pathogens; (2) they should be administered in the appropriate dose, (3) by the correct route, and (4) using the correct mode of administration to achieve successful concentration at the infection site. In critically ill patients, antimicrobial dosing is a common challenge and a frequent source of errors, since these patients present deranged pharmacokinetics, namely increased volume of distribution and altered drug clearance, which either increased or decreased. Moreover, the clinical condition of these patients changes markedly over time, either improving or deteriorating. The consequent impact on drug pharmacokinetics further complicates the selection of correct drug schedules and dosing during the course of therapy. In recent years, the knowledge of pharmacokinetics and pharmacodynamics, drug dosing, therapeutic drug monitoring, and antimicrobial resistance in the critically ill patients has greatly improved, fostering strategies to optimize therapeutic efficacy and to reduce toxicity and adverse events. Nonetheless, delivering adequate and appropriate antimicrobial therapy is still a challenge, since pathogen resistance continues to rise, and new therapeutic agents remain scarce. We aim to review the available literature to assess the challenges, impact, and tools to optimize individualization of antimicrobial dosing to maximize exposure and effectiveness in critically ill patients.

Applications of Machine Learning to the Problem of Antimicrobial Resistance: an Emerging Model for Translational Research

Antimicrobial resistance (AMR) remains one of the most challenging phenomena of modern medicine. Machine learning (ML) is a subfield of artificial intelligence that focuses on the development of algorithms that learn how to accurately predict outcome variables using large sets of predictor variables that are typically not hand selected and are minimally curated. Models are parameterized using a training data set and then applied to a test data set on which predictive performance is evaluated. The application of ML algorithms to the problem of AMR has garnered increasing interest in the past 5 years due to the exponential growth of experimental and clinical data, heavy investment in computational capacity, improvements in algorithm performance, and increasing urgency for innovative approaches to reducing the burden of disease. Here, we review the current state of research at the intersection of ML and AMR with an emphasis on three domains of work. The first is the prediction of AMR using genomic data. The second is the use of ML to gain insight into the cellular functions disrupted by antibiotics, which forms the basis for understanding mechanisms of action and developing novel anti-infectives. The third focuses on the application of ML for antimicrobial stewardship using data extracted from the electronic health record. Although the use of ML for understanding, diagnosing, treating, and preventing AMR is still in its infancy, the continued growth of data and interest ensures it will become an important tool for future translational research programs.

Atypical Genetic Basis of Pyrazinamide Resistance in Monoresistant Mycobacterium tuberculosis

Pyrazinamide (PZA) is a widely used antitubercular chemotherapeutic. Typically, PZA resistance (PZA-R) emerges in Mycobacterium tuberculosis strains with existing resistance to isoniazid and rifampin (i.e., multidrug resistance [MDR]) and is conferred by loss-of-function pncA mutations that inhibit conversion to its active form, pyrazinoic acid (POA). PZA-R departing from this canonical scenario is poorly understood. Here, we genotyped pncA and purported alternative PZA-R genes (panD, rpsA, and clpC1) with long-read sequencing of 19 phenotypically PZA-monoresistant isolates collected in Sweden and compared their phylogenetic and genomic characteristics to a large set of MDR PZA-R (MDR_PZA-R) isolates. We report the first association of ClpC1 mutations with PZA-R in clinical isolates, in the ClpC1 promoter (clpC1p₋₁₃₈) and the N terminus of ClpC1 (ClpC1_Val63Ala). Mutations have emerged in both these regions under POA selection in vitro, and the N-terminal region of ClpC1 has been implicated further, through its POA-dependent efficacy in PanD proteolysis. ClpC1_Val63Ala mutants spanned 4 Indo-Oceanic sublineages. Indo-Oceanic isolates invariably harbored ClpC1_Val63Ala and were starkly overrepresented (odds ratio [OR] = 22.2, P < 0.00001) among PZA-monoresistant isolates (11/19) compared to MDR_PZA-R isolates (5/80). The genetic basis of Indo-Oceanic isolates’ overrepresentation in PZA-monoresistant tuberculosis (TB) remains undetermined, but substantial circumstantial evidence suggests that ClpC1_Val63Ala confers low-level PZA resistance. Our findings highlight ClpC1 as potentially clinically relevant for PZA-R and reinforce the importance of genetic background in the trajectory of resistance development.

Endophytic Bacteria Enterobacter hormaechei Fabricated Silver Nanoparticles and Their Antimicrobial Activity

Antimicrobial resistance (AMR), one of the greatest issues for humankind, draws special attention to the scientists formulating new drugs to prevent it. Great emphasis on the biological synthesis of silver nanoparticles (AgNPs) for utilization in single or combinatorial therapy will open up new avenues to the discovery of new antimicrobial drugs. The purpose of this study was to synthesize AgNPs following a green approach by using an endophytic bacterial strain, Enterobacter hormaechei, and to assess their antimicrobial potential against five pathogenic and four multidrug-resistant (MDR) microbes. UV-Vis spectroscopy, fourier-transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDX), and zeta potential (ζ) were used to characterize the synthesized AgNPs. Endophytic E. hormaechei-mediated AgNPs (Eh-AgNPs) were represented by a strong UV-Vis absorbance peak at 418 nm within 5 min, forming spherical and polydispersed nanoparticles in the size range of 9.91 nm to 92.54 nm. The Eh-AgNPs were moderately stable with a mean ζ value of -19.73 ± 3.94 mV. The presence of amine, amide, and hydroxyl functional groups was observed from FTIR analysis. In comparison to conventional antibiotics, the Eh-AgNPs were more effective against Bacillus cereus (ATCC 10876) and Candida albicans (ATCC 10231), exhibiting 9.14 ± 0.05 mm and 8.24 ± 0.05 mm zones of inhibition (ZOIs), respectively, while displaying effective inhibitory activity with ZOIs ranging from 10.98 ± 0.08 to 13.20 ± 0.07 mm against the MDR bacteria. Eh-AgNP synthesis was rapid and eco-friendly. The results showed that Eh-AgNPs are promising antimicrobial agents that can be used in the development and formulation of new drugs to curb the menace of antimicrobial resistance in pathogenic and MDR microbes.

Microfluidic Single-Cell Phenotyping of the Activity of Peptide-Based Antimicrobials

Antibiotic resistance is a major challenge for modern medicine, and there is a dire need to refresh the antibiotic development pipeline to treat infections that are resistant to currently available drugs. Peptide-based antimicrobials represent a promising source of novel anti-infectives, but their development is severely impeded due to the lack of suitable techniques to accurately quantify their antimicrobial efficacy. A major problem involves the heterogeneity of cellular phenotypes in response to these peptides, even within a clonal population of bacteria. There is thus a need to develop single-cell resolution assays to quantify drug efficacy for these novel therapeutics. We present here a detailed microfluidics-microscopy protocol for testing the efficacy of peptide-based antimicrobials on hundreds to thousands of individual bacteria in well-defined microenvironments. This enables the study of cell-to-cell differences in drug response within a clonal population. It is a highly versatile tool, which can be used to quantify drug efficacy, including the number of individual survivors at defined drug doses; it even enables the potential exploration of the molecular mechanisms of action of the drug, which are often unknown in the early stages of drug development. We present here protocols for working with Escherichia coli, but organisms of different geometric shapes and sizes may also be tested with suitable modifications of the microfluidic device.

A murine model to study the gut bacteria parameters during complex antibiotics like cefotaxime and ceftriaxone treatment

Background

The globally increasing resistance due to extended-spectrum beta-lactamase producing Enterobacteriaceae is a major concern. The objective of this work was to develop a murine model to study the gut bacteria parameters during complex antibiotics like cefotaxime and ceftriaxone treatment and to compare the fecal carriage of ESBL-producing Enterobacteriaceae.

Methods

SWISS mice were treated either with ceftriaxone or with cefotaxime or with NaCl 0.9% as a control group from day 1 to day 5. We performed a gavage at day 4 with a Klebsiella pneumonia CTX-M9. We collected stools and performed pharmacological measurements, cultures and 16S rRNA gene amplification and sequencing during the 12 days of the stool collection.

Results

Mice treated with ceftriaxone were more colonized than mice treated with cefotaxime after gavage (p-value = 0.008; Kruskal-Wallis test). Ceftriaxone and cefotaxime were both excreted in large quantity in gut lumen but they drove architecture of the gut microbiota in different trajectories. Highest levels of colonization were associated with particular microbiota composition using principal coordinate analysis (PCoA) which were more often achieved in ceftriaxone-treated mice and which were preceded by highest fecal antibiotics concentrations in both cefotaxime or ceftriaxone groups. Using LEfSe, we found that twelve taxa were significantly different between cefotaxime and ceftriaxone-treated mice. Using SplinectomeR, we found that relative abundances of Klebsiella were significantly higher in CRO than in CTX-treated mice (p-value = 0.01).

Conclusion

Ceftriaxone selects a particular microbial community and its substitution for cefotaxime could prevent the selection of extended-spectrum beta-lactamase producing Enterobacteriaceae.

Key Challenges in Providing Effective Antibiotic Therapy for Critically Ill Patients with Bacterial Sepsis and Septic Shock

Early initiation of effective antibiotic therapy is vitally important for saving the lives of critically ill patients with sepsis or septic shock. The susceptibility of the infecting pathogen and the ability of the selected dosage regimen to safely achieve the required antibiotic exposure need to be carefully considered to achieve a high probability of a successful outcome. Critically ill patients commonly experience substantial pathophysiological changes that impact the functions of various organs, including the kidneys. Many antibiotics are predominantly renally eliminated and thus renal function is a major determinant of the regimen needed to achieve the required antibiotic exposure. However, currently, there is a paucity of guidelines to inform antibiotic dosing in critically ill patients, including those with sepsis or septic shock. This paper briefly reviews methods that are commonly used in critically ill patients to provide a measure of renal function, and approaches that describe the relationship between the exposure to an antibiotic and its antibacterial effects. Two common conditions that very substantially complicate the use of antibiotics in critically ill patients with sepsis, unstable renal function, and augmented renal clearance, are considered in detail and their potential therapeutic implications are explored. Suggestions are provided on how treatment of bacterial infections in critically ill patients with sepsis might be improved. Of high potential are model-informed approaches that aim to individualize initial treatment regimens based on patient and bacterial characteristics, with refinement of regimens during treatment in response to monitoring antibiotic concentrations, responsive measures of renal function, and other important clinical data.

Evaluation and validation of Biolog OmniLog® system for antibacterial activity assays

Minimal inhibitory concentration of antimicrobials, determined by the broth microdilution method, requires visual assessment or absorbance measurement using a spectrophotometer. Both procedures are usually performed manually, requiring the presence of an operator to assess the plates at specific time point. To increase the throughput of antimicrobial susceptibility testing, and concurrently convert into an automatic assay, the Biolog OmniLog^® system was validated for a new, label-free application using standard 96-well microplates. OmniLog was evaluated for its signal strength to ensure that the signal intensity, detected and measured by the system's camera, was satisfactory. Variability due to the plate location inside the OmniLog incubator, as well as variation between wells, was investigated. Then the system was validated by determining the minimal inhibitory concentration of ciprofloxacin, piperacillin and linezolid against a selected Gram-negative and Gram-positive strains. No significant difference was observed in relation to position of the plates within the system. Plate edge effects were noticeable, thus the edge wells were not included in further experiments. Minimal inhibitory concentration results were comparable to those obtained by conventional protocol as well as to values defined by the Clinical Laboratory Standards Institute or published in the literature.

Model-Informed Drug Development for Antimicrobials: Translational PK and PK/PD Modeling to Predict an Efficacious Human Dose for Apramycin

Apramycin represents a subclass of aminoglycoside antibiotics that has been shown to evade almost all mechanisms of clinically relevant aminoglycoside resistance. Model-informed drug development may facilitate its transition from preclinical to clinical phase. This study explored the potential of pharmacokinetic/pharmacodynamic (PK/PD) modeling to maximize the use of in vitro time-kill and in vivo preclinical data for prediction of a human efficacious dose (HED) for apramycin. PK model parameters of apramycin from four different species (mouse, rat, guinea pig, and dog) were allometrically scaled to humans. A semimechanistic PK/PD model was developed from the rich in vitro data on four Escherichia coli strains and subsequently the sparse in vivo efficacy data on the same strains were integrated. An efficacious human dose was predicted from the PK/PD model and compared with the classical PK/PD index methodology and the aminoglycoside dose similarity. One-compartment models described the PK data and human values for clearance and volume of distribution were predicted to 7.07 L/hour and 26.8 L, respectively. The required fAUC/MIC (area under the unbound drug concentration-time curve over MIC ratio) targets for stasis and 1-log kill in the thigh model were 34.5 and 76.2, respectively. The developed PK/PD model predicted the efficacy data well with strain-specific differences in susceptibility, maximum bacterial load, and resistance development. All three dose prediction approaches supported an apramycin daily dose of 30 mg/kg for a typical adult patient. The results indicate that the mechanistic PK/PD modeling approach can be suitable for HED prediction and serves to efficiently integrate all available efficacy data with potential to improve predictive capacity.

Antimicrobial pharmacokinetics and preclinical in vitro models to support optimized treatment approaches for uncomplicated lower urinary tract infections

INTRODUCTION

Urinary tract infections (UTIs) are extremely common. Millions of people, particularly healthy women, are affected worldwide every year. One-in-two women will have a recurrence within 12-months of an initial UTI. Inadequate treatment risks worsening infection leading to acute pyelonephritis, bacteremia and sepsis. In an era of increasing antimicrobial resistance, it is critical to provide optimized antimicrobial treatment.

AREAS COVERED

Literature was searched using PubMed and Google Scholar (up to 06/2020), examining the etiology, diagnosis and oral antimicrobial therapy for uncomplicated UTIs, with emphasis on urinary antimicrobial pharmacokinetics (PK) and the application of dynamic in vitro models for the pharmacodynamic (PD) profiling of pathogen response.

EXPERT OPINION

The majority of antimicrobial agents included in international guidelines were developed decades ago without well-described dose-response relationships. Microbiology laboratories still apply standard diagnostic methodology that has essentially remained unchanged for decades. Furthermore, it is uncertain how relevant standard in vitro susceptibility is for predicting antimicrobial efficacy in urine. In order to optimize UTI treatments, clinicians must exploit the urine-specific PK of antimicrobial agents. Dynamic in vitro models are valuable tools to examine the PK/PD and urodynamic variables associated with UTIs, while informing uropathogen susceptibility reporting, optimized dosing schedules, clinical trials and treatment guidelines.

Cantilever Sensors for Rapid Optical Antimicrobial Sensitivity Testing

Growing antimicrobial resistance (AMR) is a serious global threat to human health. Current methods to detect resistance include phenotypic antibiotic sensitivity testing (AST), which measures bacterial growth and is therefore hampered by a slow time to obtain results (∼12–24 h). Therefore, new rapid phenotypic methods for AST are urgently needed. Nanomechanical cantilever sensors have recently shown promise for rapid AST but challenges of bacterial immobilization can lead to variable results. Herein, a novel cantilever-based method is described for detecting phenotypic antibiotic resistance within ∼45 min, capable of detecting single bacteria. This method does not require complex, variable bacterial immobilization and instead uses a laser and detector system to detect single bacterial cells in media as they pass through the laser focus. This provides a simple readout of bacterial antibiotic resistance by detecting growth (resistant) or death (sensitive), much faster than the current methods. The potential of this technique is demonstrated by determining the resistance in both laboratory and clinical strains of Escherichia coli (E. coli), a key species responsible for clinically burdensome urinary tract infections. This work provides the basis for a simple and fast diagnostic tool to detect antibiotic resistance in bacteria, reducing the health and economic burdens of AMR.

Antifungal Susceptibility Testing of Aspergillus niger on Silicon Microwells by Intensity-Based Reflectometric Interference Spectroscopy

There is a demonstrated and paramount need for rapid, reliable infectious disease diagnostics, particularly those for invasive fungal infections. Current clinical determinations for an appropriate antifungal therapy can take up to 3 days using current antifungal susceptibility testing methods, a time-to-readout that can prove detrimental for immunocompromised patients and promote the spread of antifungal resistant pathogens. Herein, we demonstrate the application of intensity-based reflectometric interference spectroscopic measurements (termed iPRISM) on microstructured silicon sensors for use as a rapid, phenotypic antifungal susceptibility test. This diagnostic platform optically tracks morphological changes of fungi corresponding to conidia growth and hyphal colonization at a solid-liquid interface in real time. Using Aspergillus niger as a model fungal pathogen, we can determine the minimal inhibitory concentration of clinically relevant antifungals within 12 h. This assay allows for expedited detection of fungal growth and provides a label-free alternative to broth microdilution and agar diffusion methods, with the potential to be used for point-of-care diagnostics.