Minimum Inhibitory Concentration Data Research Articles

Prevalence and genetic basis of Mycobacterium tuberculosis resistance to pretomanid in China

BackgroundPretomanid is a key component of new regimens for the treatment of drug-resistant tuberculosis (TB) which are being rolled out globally. However, there is limited information on the prevalence of pre-existing resistance to the drug.MethodsTo investigate pretomanid resistance rates in China and its underlying genetic basis, as well as to generate additional minimum inhibitory concentration (MIC) data for epidemiological cutoff (ECOFF)/breakpoint setting, we performed MIC determinations in the Mycobacterial Growth Indicator Tube™ (MGIT) system, followed by WGS analysis, on 475 Mycobacterium tuberculosis (MTB) isolated from Chinese TB patients between 2013 and 2020.ResultsWe observed a pretomanid MIC distribution with a 99% ECOFF equal to 0.5 mg/L. Of the 15 isolates with MIC values > 0.5 mg/L, one (MIC = 1 mg/L) was identified as MTB lineage 1 (L1), a genotype previously reported to be intrinsically less susceptible to pretomanid, two were borderline resistant (MIC = 2–4 mg/L) and the remaining 12 isolates were highly resistant (MIC ≥ 16 mg/L) to the drug. Five resistant isolates did not harbor mutations in the known pretomanid resistant genes.ConclusionsOur results further support a breakpoint of 0.5 mg/L for a non-L1 MTB population, which is characteristic of China. Further, our data point to an unexpected high (14/475, 3%) pre-existing pretomanid resistance rate in the country, as well as to the existence of yet-to-be-discovered pretomanid resistance genes.

Evaluation of omadacycline regimens for community-acquired bacterial pneumonia patients infected with Staphylococcus Aureus by pharmacokinetic/pharmacodynamic analysis

Omadacycline is an FDA-approved agent for community-acquired bacterial pneumonia (CABP). The purpose of this study is to evaluate the effectiveness of omadacycline for treating CABP patients infected with Staphylococcus aureus, including Methicillin-Resistant Staphylococcus aureus (MRSA) and Methicillin-Susceptible Staphylococcus aureus (MSSA), using pharmacokinetic/pharmacodynamic (PK/PD) analysis. Monte Carlo simulations (MCSs) were performed by utilizing omadacycline pharmacokinetic (PK) parameters, minimum inhibitory concentration (MIC) data, and in vivo PK/PD targets to calculate the probability of target attainment (PTA) and cumulative fraction of response (CFR) values for different dose regimens against MRSA and MSSA in CABP patients. A dosage regimen with a PTA or CFR expectation value greater than 90% was considered optimal. For all recommended dose regimens, PTA values for MRSA MIC ≤1 and MSSA MIC ≤4 on days 1, 4, and 7 were greater than 90%. Based on the MIC distribution of Staphylococcus aureus, all dose regimens had CFR values greater than 90% for both MRSA and MSSA. CFR values for different bacterial strains were still greater than 90% within the range of PK/PD target values less than 40, although they gradually decreased with increasing PK/PD target values. PK/PD modeling demonstrated that all recommended dose regimens of omadacycline are highly effective against CABP patients infected with MRSA and MSSA. The study provides theoretical support for the efficacy of omadacycline in different dose regimens.

Optimising machine learning prediction of minimum inhibitory concentrations in Klebsiella pneumoniae.

Minimum Inhibitory Concentrations (MICs) are the gold standard for quantitatively measuring antibiotic resistance. However, lab-based MIC determination can be time-consuming and suffers from low reproducibility, and interpretation as sensitive or resistant relies on guidelines which change over time. Genome sequencing and machine learning promise to allow in silico MIC prediction as an alternative approach which overcomes some of these difficulties, albeit the interpretation of MIC is still needed. Nevertheless, precisely how we should handle MIC data when dealing with predictive models remains unclear, since they are measured semi-quantitatively, with varying resolution, and are typically also left- and right-censored within varying ranges. We therefore investigated genome-based prediction of MICs in the pathogen Klebsiella pneumoniae using 4367 genomes with both simulated semi-quantitative traits and real MICs. As we were focused on clinical interpretation, we used interpretable rather than black-box machine learning models, namely, Elastic Net, Random Forests, and linear mixed models. Simulated traits were generated accounting for oligogenic, polygenic, and homoplastic genetic effects with different levels of heritability. Then we assessed how model prediction accuracy was affected when MICs were framed as regression and classification. Our results showed that treating the MICs differently depending on the number of concentration levels of antibiotic available was the most promising learning strategy. Specifically, to optimise both prediction accuracy and inference of the correct causal variants, we recommend considering the MICs as continuous and framing the learning problem as a regression when the number of observed antibiotic concentration levels is large, whereas with a smaller number of concentration levels they should be treated as a categorical variable and the learning problem should be framed as a classification. Our findings also underline how predictive models can be improved when prior biological knowledge is taken into account, due to the varying genetic architecture of each antibiotic resistance trait. Finally, we emphasise that incrementing the population database is pivotal for the future clinical implementation of these models to support routine machine-learning based diagnostics.

Bigger problems from smaller colonies: emergence of antibiotic-tolerant small colony variants of Mycobacterium avium complex in MAC-pulmonary disease patients.

Mycobacterium avium complex (MAC) is a group of slow-growing mycobacteria that includes Mycobacterium avium and Mycobacterium intracellulare. MAC pulmonary disease (MAC-PD) poses a threat to immunocompromised individuals and those with structural pulmonary diseases worldwide. The standard treatment regimen for MAC-PD includes a macrolide in combination with rifampicin and ethambutol. However, the treatment failure and disease recurrence rates after successful treatment remain high. In the present study, we investigated the unique characteristics of small colony variants (SCVs) isolated from patients with MAC-PD. Furthermore, revertant (RVT) phenotype, emerged from the SCVs after prolonged incubation on 7H10 agar. We observed that SCVs exhibited slower growth rates than wild-type (WT) strains but had higher minimum inhibitory concentrations (MICs) against multiple antibiotics. However, some antibiotics showed low MICs for the WT, SCVs, and RVT phenotypes. Additionally, the genotypes were identical among SCVs, WT, and RVT. Based on the MIC data, we conducted time-kill kinetic experiments using various antibiotic combinations. The response to antibiotics varied among the phenotypes, with RVT being the most susceptible, WT showing intermediate susceptibility, and SCVs displaying the lowest susceptibility. In conclusion, the emergence of the SCVs phenotype represents a survival strategy adopted by MAC to adapt to hostile environments and persist during infection within the host. Additionally, combining the current drugs in the treatment regimen with additional drugs that promote the conversion of SCVs to RVT may offer a promising strategy to improve the clinical outcomes of patients with refractory MAC-PD.

Molecular determinant deciphering of MIC-guided RND efflux substrates in E. coli

Antimicrobial resistance poses an urgent and formidable global public health threat. The escalation of bacterial multidrug resistance to antibiotics has the potential to become a leading cause of global mortality if there is no substantial improvement in antimicrobial development and therapy protocols. In light of this, it is imperative to identify the molecular determinants responsible for the reduced antibiotic activity associated with RND efflux pumps. This comprehensive study meticulously examines Minimum Inhibitory Concentration (MIC) data obtained from in vitro tests for various antibiotic families and non-active dye compounds, sourced from diverse literature references. The primary focus of this study is to assess the susceptibility of these agents to efflux-resistant Escherichia coli strains, integrating both MIC data and relevant physicochemical properties. The central objective is to unveil the specific substituents that significantly influence the uptake process mediated by the AcrAB-TolC efflux system. This exploration seeks to reveal the consequences of these substituents on pharmacodynamic responses, providing valuable insights into Structure-Activity Relationships. It is noteworthy that this analysis represents a pioneering effort, with prospective implications for RND efflux pump-producing strains. Ultimately, deciphering efflux markers is crucial to effectively mitigate the emergence of specific resistance and to better monitor the role of this primary resistance mechanism in Gram-negative bacteria, particularly as observed in clinical antibiotic therapy practice.

Challenges for global antibiotic regimen planning and establishing antimicrobial resistance targets: implications for the WHO Essential Medicines List and AWaRe antibiotic book dosing.

SUMMARYThe World Health Organisation's 2022 AWaRe Book provides guidance for the use of 39 antibiotics to treat 35 infections in primary healthcare and hospital facilities. We review the evidence underpinning suggested dosing regimens. Few (n = 18) population pharmacokinetic studies exist for key oral AWaRe antibiotics, largely conducted in homogenous and unrepresentative populations hindering robust estimates of drug exposures. Databases of minimum inhibitory concentration distributions are limited, especially for community pathogen-antibiotic combinations. Minimum inhibitory concentration data sources are not routinely reported and lack regional diversity and community representation. Of studies defining a pharmacodynamic target for ß-lactams (n = 80), 42 (52.5%) differed from traditionally accepted 30%-50% time above minimum inhibitory concentration targets. Heterogeneity in model systems and pharmacodynamic endpoints is common, and models generally use intravenous ß-lactams. One-size-fits-all pharmacodynamic targets are used for regimen planning despite complexity in drug-pathogen-disease combinations. We present solutions to enable the development of global evidence-based antibiotic dosing guidance that provides adequate treatment in the context of the increasing prevalence of antimicrobial resistance and, moreover, minimizes the emergence of resistance.

Minimum inhibitory concentrations of antifungals against invasive isolates of Cryptococcus species worldwide: Global antifungal antimicrobial testing leadership and surveillance program, 2010–2020

This study examined the geographic distribution of minimum inhibitory concentrations (MICs) of antifungals against Cryptococcus isolates. Data were collected on the MICs of specific antifungals (amphotericin B, 5-flucytosine, fluconazole, voriconazole, posaconazole, and isavuconazole) against various Cryptococcus species for the period 2010 to 2020 from the Antimicrobial Testing Leadership and Surveillance database. Cryptococcus isolates were collected from samples of blood and cerebrospinal fluid (CSF) from patients hospitalized in different regions worldwide. We applied the epidemiological cutoff values (ECVs) of antifungals against various Cryptococcus species to distinguish wild-type (WT) from non-WT Cryptococcus isolates. A total of 395 isolates of Cryptococcus species cultured from blood (n = 201) or CSF (n = 194) were analyzed. C. grubii (n = 270), C. neoformans (n = 111), and C. gattii (n = 11) were the three predominant species causing bloodstream infections (BSI) or meningitis/meningoencephalitis (MME). The proportion of MICs above the ECV (1 mg/L) for amphotericin B among C. neoformans isolates was significantly lower than that among C. gattii isolates (MICs >0.5 mg/L; P < 0.001), as evaluated using the chi-square test. For most isolates of the three predominant Cryptococcus species, the MICs of new triazoles were ≤0.25 mg/L. The MICs of fluconazole and amphotericin B in the BSI/MME-causing Cryptococcus isolates collected from patients hospitalized in the Asia-Western Pacific region and Europe were significantly lower (i.e., the distributions were more leftward) than those in North America and Latin America. Ongoing monitoring of MIC data for important antifungals against cryptococcosis is crucial.

In vitro susceptibility of Brachyspira hyodysenteriae strains isolated in pigs in northern Italy between 2005 and 2022

Pleuromutilins (tiamulin and valnemulin) are often used to treat swine dysentery due to recurrent resistance to macrolides and lincosamides. Recently, reduced susceptibility of B. hyodysenteriae to pleuromutilin has been reported. 536 strains of B. hyodysenteriae were isolated from symptomatic pigs weighing 30–150 kg in northern Italy between 2005 and 2022. B. hyodysenteriae was isolated by standard methods and confirmed by PCR. The minimum inhibitory concentration (MIC) to doxycycline, lincomycin, tiamulin, tylosin, tylvalosine and valnemulin was evaluated according to CLSI procedures and MIC data were reported as MIC 50 and MIC 90. The temporal trend of the MIC values was evaluated by dividing the data into two groups (2005–2013 and 2014–2022). Comparison of the distribution in frequency classes in the two periods was performed using Pearson's chi-squared test (p < 0.01).MIC 50 was close to the highest values tested for lincomycin and tylosin, while MIC 90 was close to the highest values tested for all antibiotics. 71.7% of the strains were susceptible to tylvalosin, while 75%–80.4% had reduced susceptibility to valnemulin and tiamulin, respectively. The difference in the distribution of MIC classes was statistically significant in the two periods for doxycycline, tiamulin, tylvalosin and valnemulin, and more MIC classes above the epidemiological cut-off were observed in 2014–2022 compared with 2005–2013. The evaluation of the trends during the period considered shows a decreasing rate of wild-type strains with MIC values below the epidemiological cut-off over time and confirms the presence of resistant strains in northern Italy.

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.

Assessment of the gradient diffusion method for fosfomycin susceptibility testing in Staphylococcus spp. and Enterococcus spp. isolated from the urine of companion dogs in Thailand.

The agar dilution method is the approved method for determining the minimum inhibitory concentration (MIC) in fosfomycin susceptibility testing, whereas the broth dilution method is not recommended. This study aimed to investigate the potential of the gradient diffusion method as a more convenient alternative to agar dilution method for MIC evaluation, particularly for the susceptibility testing of Staphylococcus spp. and Enterococcus spp. to fosfomycin. A total of 194 isolates of Staphylococcus spp. and Enterococcus spp. were collected from urine samples of dogs diagnosed with bacterial cystitis. Bacterial identification and susceptibility to multiple antibiotics were tested using the Vitek 2 automated system. The susceptibility to fosfomycin was compared between agar dilution (reference method) and the gradient diffusion method. We assessed the agreement rates and errors between the two approaches by analyzing the MIC data. Staphylococcus pseudintermedius (98.7%) and Enterococcus faecalis (80.0%) exhibited high fosfomycin susceptibility rates, whereas Enterococcus faecium exhibited a lower susceptibility rate (38.5%). The gradient diffusion method demonstrated unacceptably low essential agreement (EA) rates (>90%) but acceptable categorical agreement (CA) rates (≥ 90%) for S. pseudintermedius (83.54% EA and 97.47% CA) and coagulase-negative staphylococci (CoNS) such as Staphylococcus chromogenes, Staphylococcus hominis, and Staphylococcus simulans (85.00% EA and 95.00% CA). Enterococcus spp. had an acceptable EA of 93.75%, but an unacceptably low CA rate of 82.81%, with a minor error rate of 17.19%. No significant errors were observed for Staphylococcus and Enterococcus spp. The gradient diffusion method reliably determines MICs and interpretative breakpoints (S, I, R) for S. pseudintermedius. However, its applicability to CoNS and enterococci may be limited due to unacceptable errors.

Machine learning to predict ceftriaxone resistance using single nucleotide polymorphisms within a global database of Neisseria gonorrhoeae genomes.

Antimicrobial resistance (AMR) in Neisseria gonorrhoeae is an urgent global health issue. Machine learning (ML) is a powerful tool that can aid in identifying mutations and predicting their impact on AMR. The study aimed to use ML models to predict ceftriaxone susceptibility and decreased susceptibility (S/DS). A public database of N. gonorrhoeae genomes with minimum inhibitory concentration (MIC) data was used to evaluate seven ML models using 97 single nucleotide polymorphisms (SNPs) known to be associated with ceftriaxone resistance. Ceftriaxone MICs ≤ 0.064 mg/L were classified as susceptible, and ceftriaxoneMICs > 0.064 mg/L were classified as DS. The contributions of individual SNPs to predict S/DS were calculated using SHapley Additive exPlanation (SHAP) values. An ML model was retrained using different combinations of SNPs with the highest SHAP values. The performance of ML models was assessed using different metrics including area under the curve (AUC) and balanced accuracy (bAcc). The ML analyses included 9,540 N. gonorrhoeae genomes; 368 (0.04%) were classified as DS. Of the models evaluated, the model trained with a random forest classifier had the highest performance (AUC 0.965; bAcc 0.926). A model retrained the top five SNPs, according to SHAP values, demonstrated a similar performance (AUC 0.916; bAcc 0.879) as the model with 97 SNPs. An ML approach using mutations in N. gonorrhoeae can be used to predict S/DS to ceftriaxone. The results highlight a practical application of ML to identify mutations most associated with S/DS to ceftriaxone, which can aid in the development of assays to predict AMR. IMPORTANCE Antimicrobial resistance in Neisseria gonorrhoeae is an urgent global health issue. The objectives of the study were to use a global collection of 12,936 N. gonorrhoeae genomes from the PathogenWatch database to evaluate different machine learning models to predict ceftriaxone susceptibility/decreased susceptibility using 97 mutations known to be associated with ceftriaxone resistance. We found the random forest classifier model had the highest performance. The analysis also reported the relative contributions of different mutations within the ML model predictions, allowing for the identification of the mutations with the highest importance for ceftriaxone resistance. A machine learning model retrained with the top five mutations performed similarly to the model using all 97 mutations. These results could aid in the development of molecular tests to detect resistance to ceftriaxone in N. gonorrhoeae. Moreover, this approach could be applied to building and evaluating machine learning models for predicting antimicrobial resistance in other pathogens.

The Susceptibility Trends of Respiratory and Enteric Porcine Pathogens to Last-Resource Antimicrobials.

Monitoring the antimicrobial susceptibility of last-resource antimicrobials for veterinary pathogens is urgently needed from a one-health perspective. The objective of this study was to analyze the antimicrobial susceptibility trends of Spanish porcine bacteria to quinolones, cephalosporins, and polymyxins. Isolates of Actinobacillus pleuropneumoniae, Pasteurella multocida, and Escherichia coli were isolated from sick pigs from 2019 to 2022. An antimicrobial susceptibility test was determined based on the minimal inhibitory concentration (MIC) following an internationally accepted methodology. The MIC categorization was based on distributing the range of MIC values in four categories, with category one being the most susceptible (lowest MIC value) and category four the least susceptible (highest MIC value). Moreover, clinical susceptibility (susceptible/non-susceptible) was also determined according to the CLSI and EUCAST clinical breakpoints. A logistic and multinomial logistic regression model was used to analyze the susceptibility data for dichotomized and categorized MIC data, respectively, for any pair of antimicrobial/microorganism. In general terms, the antimicrobial susceptibility of pig bacteria to these antimicrobials remained stable or increased in the last four years in Spain. In the case of A. pleuropneumoniae and quinolones, a significant temporal trend was observed where isolates from 2020 had significantly increased odds of being more susceptible than isolates from 2019. In the case of E. coli and polymyxins, a significant temporal trend was observed where isolates from 2020 and 2021 had significantly increased odds of being more susceptible than isolates from 2019 and 2020, respectively. Finally, significant odds of being less susceptible were only observed for cephalosporins and E. coli for 2020 versus 2019, stagnating for the rest of study period. These results provide sound data on critically important antimicrobials in swine medicine.

Qualitative and quantitative contributions of intermolecular interactions, quantum chemical calculation, biological activity and visible-light driven photo catalysts studies of nickel complex of 4-amino-N-(5-methyl-1,3,4-thiadiazol-2-yl)benzenesulfonamide

This study reports the successful synthesis and characterization of a nickel complex of the sulfamethizole (smtz) ligand. The complex was characterized using 1H NMR and FT-IR spectroscopic analyses. The synthesized complex exhibited promising properties as a biological and visible light-driven photocatalyst. Under visible light radiation, it displayed remarkable photo-degradation capabilities, achieving a degradation efficiency of 91.2% within 80 min against a solution of methylene blue (MB) with a concentration of 10 PPM in 100 mL. To understand the complex's biological response, viscosity measurements were conducted to investigate its mode of binding with CT-DNA. The results demonstrated that the nickel complex exhibited stronger inhibitory activity and lower cytotoxicity compared to the smtz ligand, as evidenced by cytotoxic analysis and minimum inhibitory concentration (MIC) data against a range of gram-positive and gram-negative pathogens. Furthermore, the crystal structure of the complex was determined through single-crystal X-ray diffraction analysis, revealing its crystallization in the triclinic space group P-1. The asymmetric part of the unit cell consisted of a Ni0.5 metal atom, one -Picoline solvent molecule, one smtz ligand, and one coordinated water molecule. To gain further insights into the complex's properties, Hirshfeld surfaces (HS) and a 3D energy framework approach were utilized to visualize its active and inactive surfaces. The analysis indicated that the dispersion energy contribution in molecular packing was significantly greater than that of electrostatic energy. Additionally, calculations of the HOMO-LUMO energy and other quantum chemical parameters were performed to understand the molecule's stability. Overall, the synthesized nickel complex of the sulfamethizole ligand exhibited remarkable photocatalytic properties, strong inhibitory activity against pathogens, and a stable crystal structure. These findings contribute to the understanding of the complex's potential applications in photocatalysis and biomedical research.

A-233 Novel Microfluidic System for Antimicrobial Susceptibility Testing

Abstract Background Aiming to enhance antibiotic susceptibility testing (AST), BacterOMIC combines microdilution AST with cutting-edge microfluidics to quantitatively evaluate all clinically relevant antibiotics on a single disposable panel. In this study, we evaluated the performance of BacterOMIC in determining minimum inhibitory concentrations (MICs) of selected agents against Gram-positive and Gram-negative bacteria and in detecting the presence of extended spectrum beta-lactamase (ESBL) produced by Enterobacterales. Methods Using the BacterOMIC UNI Panel, we characterized bacterial strains collected from Polish hospitals in 2020–2022. We inoculated the BacterOMIC panels with bacterial suspensions in cation-adjusted Mueller-Hinton broth at a density of 5*10^5 CFU/mL. The panels then incubated in an analyzer for 16 h, and results were automatically calculated via built-in analytical software. For comparison, we obtained reference MIC data from laboratories contracted for determining strain MIC values via microdilution. We calculated the essential agreement (EA%) and bias according to ISO20776.We also qualitatively assessed several antibiotics via our panel. Categorical agreement (CA%) and discrepancies were determined for these antibiotics according to ISO20776.To assess ESBL detection, we compared BacterOMIC results with data obtained in our internal laboratory using the MIC Test Strip ESBL (Liofilchem). Results With the BacterOMIC system, CA% values exceeded 90% for amoxicillin, benzylpenicillin, ceftazidime/avibactam, ciprofloxacin, erythromycin, gentamicin, meropenem, moxifloxacin, tedizolid, and vancomycin. EA% values exceeded 90% for the following antimicrobials, with a bias of less than 30%. By comparing with our reference method, we found that BacterOMIC detected ESBL with a specificity of 92% (confidence interval [CI] 95%; 81%–98%) and sensitivity of 97% (CI 95%; 84%–99%). Conclusions Our data demonstrate that BacterOMIC provides reliable MIC and ESBL results for assessing the drug susceptibility of Gram-positive and Gram-negative bacteria against 25 agents in a single panel. Thus, the BacterOMIC system provides a valuable tool for automated AST systems.

Applications of Lab on a Chip in Antimicrobial Susceptibility of Staphylococcus aureus: A Systematic Review.

Background and Objectives: Staphylococcus aureus is a prevalent bacterium capable of inducing various infections, including skin and soft tissue infections, bloodstream infections, pneumonia, and surgical site infections. The emergence of antimicrobial resistance in S. aureus, particularly methicillin-resistant S. aureus, has raised substantial concerns within global healthcare settings. Prior to antibiotic prescription, the ideal approach is antimicrobial susceptibility testing (AST); however, this is frequently perceived as excessively complex and time-intensive. Lab-on-a-chip (LOC) technology holds promise in addressing these challenges and advancing fundamental microbiological research while also aiding in the development of therapeutic strategies. This systematic review aims to evaluate the potential utility of LOC for AST of S. aureus. Materials and Methods: This study adhered to the PRISMA guidelines. Various databases, including SCOPUS, PubMed/MEDLINE, SCIELO, and LILACS, in addition to gray literature sources, were employed in the review process. Results: Sixteen studies were included in this systematic review. All these studies detailed the effectiveness, rapidity, and predictability of LOC systems for assessing S. aureus susceptibility to various antibiotics. When comparing the LOC approach to traditional manual methods, it was evident that LOC requires a minimal quantity of reagents. Furthermore, most studies reported that the entire LOC procedure took 10 min to 7 h, with results being equally accurate as those obtained through traditional AST protocols. Conclusions: The potential application of LOC for AST of S. aureus is emphasized by its ability to provide rapid access to minimum inhibitory concentration data, which can substantially aid in selecting the most suitable antibiotics and dosages for treating challenging infections caused by this microorganism. Moreover, the rapid AST facilitated by LOC holds promise for enhancing the appropriateness and efficacy of therapy in clinical settings.

Optimizing tylosin dosage for co-infection of Actinobacillus pleuropneumoniae and Pasteurella multocida in pigs using pharmacokinetic/pharmacodynamic modeling.

Formulating a therapeutic strategy that can effectively combat concurrent infections of Actinobacillus pleuropneumoniae (A. pleuropneumoniae) and Pasteurella multocida (P. multocida) can be challenging. This study aimed to 1) establish minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), time kill curve, and post-antibiotic effect (PAE) of tylosin against A. pleuropneumoniae and P. multocida pig isolates and employ the MIC data for the development of epidemiological cutoff (ECOFF) values; 2) estimate the pharmacokinetics (PKs) of tylosin following its intramuscular (IM) administration (20mg/kg) in healthy and infected pigs; and 3) establish a PK-pharmacodynamic (PD) integrated model and predict optimal dosing regimens and PK/PD cutoff values for tylosin in healthy and infected pigs. The MIC of tylosin against both 89 and 363 isolates of A. pleuropneumoniae and P. multocida strains spread widely, ranging from 1 to 256μg/mL and from 0.5 to 128μg/mL, respectively. According to the European Committee on Antimicrobial Susceptibility Testing (EUCAST) ECOFFinder analysis ECOFF value (≤64µg/mL), 97.75% (87 strains) of the A. pleuropnumoniae isolates were wild-type, whereas with the same ECOFF value (≤64µg/mL), 99.72% (363 strains) of the P. multicoda isolates were considered wild-type to tylosin. Area under the concentration time curve (AUC), T1/2, and Cmax values were significantly greater in healthy pigs than those in infected pigs (13.33h × μg/mL, 1.99h, and 5.79μg/mL vs. 10.46h × μg/mL, 1.83h, and 3.59μg/mL, respectively) (p < 0.05). In healthy pigs, AUC24h/MIC values for the bacteriostatic activity were 0.98 and 1.10h; for the bactericidal activity, AUC24h/MIC values were 1.97 and 1.99h for A. pleuropneumoniae and P. multocida, respectively. In infected pigs, AUC24h/MIC values for the bacteriostatic activity were 1.03 and 1.12h; for bactericidal activity, AUC24h/MIC values were 2.54 and 2.36h for A. pleuropneumoniae and P. multocida, respectively. Monte Carlo simulation lead to a 2μg/mL calculated PK/PD cutoff. Managing co-infections can present challenges, as it often demands the administration of multiple antibiotics to address diverse pathogens. However, using tylosin, which effectively targets both A. pleuropneumoniae and P. multocida in pigs, may enhance the control of bacterial burden. By employing an optimized dosage of 11.94-15.37mg/kg and 25.17-27.79mg/kg of tylosin can result in achieving bacteriostatic and bactericidal effects in 90% of co-infected pigs.

Epidemiological cut-off values for Vibrio anguillarum MIC and disc diffusion data generated by standardised methods.

This work aims to generate the data needed to set epidemiological cut-off values for minimum inhibitory concentration (MIC) and disc-diffusion zone measurements of Vibrio anguillarum. A total of 261 unique isolates were tested, applying standard methods specifying incubation at 28°C for 24-28 h. Aggregated MIC distributions for a total of 247 isolates were determined in 9 laboratories for 11 agents. Data aggregations of the disc zone for the 10 agents analysed contained between 157 and 218 observations made by 4 to 7 laboratories. Acceptable ranges for quality control (QC) reference strains were available for 7 agents and the related multi-laboratory aggregated data were censored, excluding the data of a laboratory that failed to meet QC requirements. Statistical methods were applied to calculate epidemiological cut-off values. Cut-off values for MIC data were calculated for florfenicol (≤1 µg ml-1), gentamicin (≤4 µg ml-1), oxytetracycline (≤0.25 µg ml-1) and trimethoprim/sulfamethoxazole (≤0.125/2.38 µg ml-1). The cut-off values for disc zone data were calculated for enrofloxacin (≥29 mm), florfenicol (≥27 mm), gentamicin (≥19 mm), oxolinic acid (≥24 mm), oxytetracycline (≥24 mm) and trimethoprim/sulfamethoxazole (≥26 mm). MIC and disc-diffusion zone data for the other agents where not supported by QC, thus yielding only provisional cut-off values (meropenem, ceftazidime). Regardless of whether QC is available, some of the aggregated MIC distributions (enrofloxacin, oxolinic acid), disc zone (sulfamethoxazole), and MIC and disc-diffusion distributions (ampicillin, chloramphenicol) did not meet the statistical requirements. The data produced will be submitted to the Clinical Laboratory Standards Institute for their consideration in setting international consensus epidemiological cut-off values.

Air stable N-heterocyclic carbene silver complexes: synthesis, characterization, and antibacterial activity

A new benzimidazolium salt containing a 2,5-dimethylbenzyl substituent and six N-heterocyclic carbene (NHC) silver complexes were prepared. The complexes were characterized by NMR, FTIR, and LC-MS spectroscopic methods and elemental analyses. They are stable in solution for a week. The antibacterial properties of the Ag(I) complexes against two Gram-positive and two Gram-negative bacteria were investigated. Inhibition zone and minimum inhibitory concentration (MIC) data establish that these NHC-Ag(I) complexes possess antibacterial activities; 2b showed the highest antibacterial activity overall against Gram-positive and Gram-negative bacteria.

Clinical application of Vitek-derived minimum inhibitory concentration values: Proof of concept study.

Minimum inhibitory concentration (MIC) values are useful in guiding appropriate antimicrobial therapy however, routine provision and interpretation of MIC values to guide clinical decision-making is challenging. This proof of concept study aims to demonstrate the clinical utility and application of Vitek®-derived MIC values through categorisation of clinical isolates as wild type. A random selection of clinically relevant Gram negative isolates routinely tested on the Vitek® instrument were included. The Vitek® MIC values, for selected antimicrobials at the lowest calling range of that card, were compared to the broth microdilution reference method. The specified end-point was concordance between the two results if the reference MIC was less than or equal to the EUCAST-defined epidemiological cut-off value (ECOFF) for that drug-bug combination. A total of 525 isolates were included (468 Enterobacterales and 57 Pseudomonas aeruginosa), with an overall concordance rate of 96.4% (508/525). Correct ECOFF categorisation by the Vitek® was highest for ceftazidime and piperacillin (100%, n = 48 and n = 55, respectively) and lowest for cefepime (81.8%, n = 66). Vitek®-derived MIC values can be used to categorise organisms as wild-type if the MIC is reported at the card's lowest calling range (≤) as there is high likelihood that the MIC is at or below the ECOFF. This has important implications for antimicrobial management, assisting in choice of agent and in improving probability of target attainment for desired pharmacodynamic targets which can translate into improved clinical outcomes. Minimum inhibitory concentration data from an automated antimicrobial susceptibility testing instrument can be used to guide clinical decisions.

The In vitro activity of carbapenems alone and in combination with β-lactamase inhibitors against difficult-to-treat mycobacteria; Mycobacterium tuberculosis, Mycobacterium abscessus, and Mycobacterium avium complex: A systematic review.

Difficult-to-treat mycobacterial infections are increasing globally. There is an urgent need of new treatment alternatives for multidrug-resistant Mycobacterium tuberculosis (MTB), as well as nontuberculous mycobacteria such as the Mycobacterium abscessus complex (MABC) and Mycobacterium avium complex (MAC). Recently, new carbapenems and combinations of carbapenems with β-lactamase inhibitors have become available, but activity data in vitro against mycobacteria are so far scarce. Therefore, we performed a systematic review collating the minimum inhibitory concentrations (MICs) of carbapenems, with or without a β-lactamase inhibitors for MTB, MABC, and MAC. The databases PubMed and Web of Science were searched for the relevant articles in English up until September 21, 2022. Screening of studies was performed by two independent reviewers. MIC data by recommended methods with at least five individual MICs were included. Data were reported as MIC range, MIC50, modal MIC, and/or histograms when individual MICs were available. The study protocol was registered at PROSPERO (CRD42021258537). After screening, a total of 75 studies with MIC data for carbapenems with or without β-lactamase inhibitors were included in the review. For MTB, the oral carbapenem tebipenem combined with the β-lactamase inhibitor clavulanic acid resulted in the most significant reduction of MICs. For MABC, the addition of avibactam to tebipenem resulted in a 64-fold reduction of modal MIC. Data were insufficient for the analysis of MAC. Carbapenems, and in particular the novel oral compound tebipenem, in combination with clavulanic acid for MTB and avibactam for MABC may be an untapped potential for difficult-to-treat mycobacterial infections.